0s autopkgtest [05:48:03]: starting date and time: 2026-02-10 05:48:03+0000 0s autopkgtest [05:48:03]: git checkout: 4b346b80 nova: make wait_reboot return success even when a no-op 0s autopkgtest [05:48:03]: host juju-7f2275-prod-proposed-migration-environment-20; command line: /home/ubuntu/autopkgtest/runner/autopkgtest --output-dir /tmp/autopkgtest-work._9f3wgto/out --timeout-copy=6000 --needs-internet=try --setup-commands /home/ubuntu/autopkgtest-cloud/worker-config-production/setup-canonical.sh --apt-pocket=proposed=src:r-cran-ggplot2 --apt-upgrade r-cran-pscbs --timeout-short=300 --timeout-copy=20000 --timeout-build=20000 --env=ADT_TEST_TRIGGERS=r-cran-ggplot2/4.0.2+dfsg-1 -- ssh -s /home/ubuntu/autopkgtest/ssh-setup/nova -- --flavor autopkgtest-cpu2-ram4-disk20-amd64 --security-groups autopkgtest-juju-7f2275-prod-proposed-migration-environment-20@sto01-7.secgroup --name adt-resolute-amd64-r-cran-pscbs-20260210-053651-juju-7f2275-prod-proposed-migration-environment-20-b366f358-b7fe-4071-8296-d3ed64a90a2d --image adt/ubuntu-resolute-amd64-server --keyname testbed-juju-7f2275-prod-proposed-migration-environment-20 --net-id=net_prod-autopkgtest-workers-amd64 -e TERM=linux --mirror=http://ftpmaster.internal/ubuntu/ 3s Creating nova instance adt-resolute-amd64-r-cran-pscbs-20260210-053651-juju-7f2275-prod-proposed-migration-environment-20-b366f358-b7fe-4071-8296-d3ed64a90a2d from image adt/ubuntu-resolute-amd64-server-20260204.img (UUID fedf54b4-458b-493e-8072-6425c19717b4)... 76s autopkgtest [05:49:19]: testbed dpkg architecture: amd64 76s autopkgtest [05:49:19]: testbed apt version: 3.1.14 77s autopkgtest [05:49:20]: @@@@@@@@@@@@@@@@@@@@ test bed setup 77s autopkgtest [05:49:20]: testbed release detected to be: None 77s autopkgtest [05:49:20]: updating testbed package index (apt update) 77s Get:1 http://ftpmaster.internal/ubuntu resolute-proposed InRelease [124 kB] 77s Hit:2 http://ftpmaster.internal/ubuntu resolute InRelease 78s Hit:3 http://ftpmaster.internal/ubuntu resolute-updates InRelease 78s Hit:4 http://ftpmaster.internal/ubuntu resolute-security InRelease 78s Get:5 http://ftpmaster.internal/ubuntu resolute-proposed/universe Sources [1727 kB] 78s Get:6 http://ftpmaster.internal/ubuntu resolute-proposed/multiverse Sources [31.1 kB] 78s Get:7 http://ftpmaster.internal/ubuntu resolute-proposed/main Sources [178 kB] 78s Get:8 http://ftpmaster.internal/ubuntu resolute-proposed/main i386 Packages [219 kB] 78s Get:9 http://ftpmaster.internal/ubuntu resolute-proposed/main amd64 Packages [266 kB] 78s Get:10 http://ftpmaster.internal/ubuntu resolute-proposed/main amd64 c-n-f Metadata [6184 B] 78s Get:11 http://ftpmaster.internal/ubuntu resolute-proposed/restricted amd64 c-n-f Metadata [120 B] 78s Get:12 http://ftpmaster.internal/ubuntu resolute-proposed/universe amd64 Packages [1787 kB] 78s Get:13 http://ftpmaster.internal/ubuntu resolute-proposed/universe i386 Packages [792 kB] 78s Get:14 http://ftpmaster.internal/ubuntu resolute-proposed/universe amd64 c-n-f Metadata [32.5 kB] 78s Get:15 http://ftpmaster.internal/ubuntu resolute-proposed/multiverse i386 Packages [5020 B] 78s Get:16 http://ftpmaster.internal/ubuntu resolute-proposed/multiverse amd64 Packages [26.4 kB] 78s Get:17 http://ftpmaster.internal/ubuntu resolute-proposed/multiverse amd64 c-n-f Metadata [996 B] 79s Fetched 5197 kB in 1s (5152 kB/s) 80s Reading package lists... 80s Hit:1 http://ftpmaster.internal/ubuntu resolute-proposed InRelease 80s Hit:2 http://ftpmaster.internal/ubuntu resolute InRelease 80s Hit:3 http://ftpmaster.internal/ubuntu resolute-updates InRelease 80s Hit:4 http://ftpmaster.internal/ubuntu resolute-security InRelease 81s Reading package lists... 81s Reading package lists... 81s Building dependency tree... 81s Reading state information... 81s Calculating upgrade... 81s The following package was automatically installed and is no longer required: 81s libpython3.13 81s Use 'sudo apt autoremove' to remove it. 81s The following NEW packages will be installed: 81s gcc-16-base libpython3.14 libpython3.14-minimal libpython3.14-stdlib 81s linux-headers-6.19.0-3 linux-headers-6.19.0-3-generic 81s linux-image-6.19.0-3-generic linux-modules-6.19.0-3-generic 81s linux-tools-6.19.0-3 linux-tools-6.19.0-3-generic 81s The following packages will be upgraded: 81s 3cpio amd64-microcode apt bpftool busybox-initramfs busybox-static 81s cryptsetup-bin dash dbus dbus-bin dbus-daemon dbus-session-bus-common 81s dbus-system-bus-common dbus-user-session debianutils dmsetup dracut-install 81s ethtool findutils gir1.2-girepository-3.0 gir1.2-glib-2.0 hwdata iproute2 81s iptables less libapt-pkg7.0 libatomic1 libattr1 libbpf1 libbrotli1 libbsd0 81s libcryptsetup12 libdbus-1-3 libdevmapper1.02.1 libdrm-amdgpu1 libdrm-common 81s libdrm2 libevent-core-2.1-7t64 libgcc-s1 libgdbm-compat4t64 libgdbm6t64 81s libgirepository-2.0-0 libglib2.0-0t64 libglib2.0-data libgpm2 libgudev-1.0-0 81s libidn2-0 libip4tc2 libip6tc2 libjansson4 libkeyutils1 liblsof0 81s libmaxminddb0 libnetfilter-conntrack3 libnpth0t64 libonig5 libpcap0.8t64 81s libpci3 libsensors-config libsensors5 libstdc++6 libusb-1.0-0 libwrap0 81s libxau6 libxkbcommon0 libxtables12 linux-generic linux-headers-generic 81s linux-headers-virtual linux-image-generic linux-image-virtual linux-perf 81s linux-tools-common linux-virtual lsof man-db mawk patch pciutils pnp.ids 81s pollinate python3-linkify-it python3-markdown-it python3-referencing sed 81s shared-mime-info tar tcpdump ubuntu-kernel-accessories ubuntu-standard wget 81s 91 upgraded, 10 newly installed, 0 to remove and 0 not upgraded. 81s Need to get 237 MB of archives. 81s After this operation, 339 MB of additional disk space will be used. 81s Get:1 http://ftpmaster.internal/ubuntu resolute/main amd64 debianutils amd64 5.23.2build1 [93.3 kB] 81s Get:2 http://ftpmaster.internal/ubuntu resolute/main amd64 dash amd64 0.5.12-12ubuntu3 [96.0 kB] 81s Get:3 http://ftpmaster.internal/ubuntu resolute/main amd64 findutils amd64 4.10.0-3build2 [307 kB] 81s Get:4 http://ftpmaster.internal/ubuntu resolute/main amd64 sed amd64 4.9-2build3 [195 kB] 81s Get:5 http://ftpmaster.internal/ubuntu resolute/main amd64 tar amd64 1.35+dfsg-3.1build2 [257 kB] 81s Get:6 http://ftpmaster.internal/ubuntu resolute/main amd64 libattr1 amd64 1:2.5.2-3build2 [11.4 kB] 81s Get:7 http://ftpmaster.internal/ubuntu resolute/main amd64 gcc-16-base amd64 16-20260208-1ubuntu1 [59.7 kB] 81s Get:8 http://ftpmaster.internal/ubuntu resolute/main amd64 libgcc-s1 amd64 16-20260208-1ubuntu1 [80.3 kB] 81s Get:9 http://ftpmaster.internal/ubuntu resolute/main amd64 libbsd0 amd64 0.12.2-2build2 [42.3 kB] 81s Get:10 http://ftpmaster.internal/ubuntu resolute/main amd64 mawk amd64 1.3.4.20260129-1 [133 kB] 81s Get:11 http://ftpmaster.internal/ubuntu resolute/main amd64 libstdc++6 amd64 16-20260208-1ubuntu1 [844 kB] 81s Get:12 http://ftpmaster.internal/ubuntu resolute/main amd64 libapt-pkg7.0 amd64 3.1.15 [1151 kB] 81s Get:13 http://ftpmaster.internal/ubuntu resolute/main amd64 apt amd64 3.1.15 [1479 kB] 81s Get:14 http://ftpmaster.internal/ubuntu resolute/main amd64 dbus-system-bus-common all 1.16.2-2ubuntu3 [55.8 kB] 81s Get:15 http://ftpmaster.internal/ubuntu resolute/main amd64 dbus-session-bus-common all 1.16.2-2ubuntu3 [54.4 kB] 81s Get:16 http://ftpmaster.internal/ubuntu resolute/main amd64 dbus-user-session amd64 1.16.2-2ubuntu3 [9696 B] 81s Get:17 http://ftpmaster.internal/ubuntu resolute/main amd64 dbus-daemon amd64 1.16.2-2ubuntu3 [119 kB] 81s Get:18 http://ftpmaster.internal/ubuntu resolute/main amd64 dbus-bin amd64 1.16.2-2ubuntu3 [40.1 kB] 81s Get:19 http://ftpmaster.internal/ubuntu resolute/main amd64 dbus amd64 1.16.2-2ubuntu3 [24.2 kB] 81s Get:20 http://ftpmaster.internal/ubuntu resolute/main amd64 libdbus-1-3 amd64 1.16.2-2ubuntu3 [185 kB] 81s Get:21 http://ftpmaster.internal/ubuntu resolute/main amd64 libdevmapper1.02.1 amd64 2:1.02.205-2ubuntu3 [142 kB] 81s Get:22 http://ftpmaster.internal/ubuntu resolute/main amd64 dmsetup amd64 2:1.02.205-2ubuntu3 [79.4 kB] 81s Get:23 http://ftpmaster.internal/ubuntu resolute/main amd64 ethtool amd64 1:6.15-3build1 [318 kB] 81s Get:24 http://ftpmaster.internal/ubuntu resolute/main amd64 gir1.2-girepository-3.0 amd64 2.87.2-2 [25.2 kB] 81s Get:25 http://ftpmaster.internal/ubuntu resolute/main amd64 libgirepository-2.0-0 amd64 2.87.2-2 [76.1 kB] 81s Get:26 http://ftpmaster.internal/ubuntu resolute/main amd64 libatomic1 amd64 16-20260208-1ubuntu1 [11.4 kB] 81s Get:27 http://ftpmaster.internal/ubuntu resolute/main amd64 gir1.2-glib-2.0 amd64 2.87.2-2 [182 kB] 81s Get:28 http://ftpmaster.internal/ubuntu resolute/main amd64 libglib2.0-0t64 amd64 2.87.2-2 [1613 kB] 81s Get:29 http://ftpmaster.internal/ubuntu resolute/main amd64 libbpf1 amd64 1:1.6.2-1build1 [184 kB] 81s Get:30 http://ftpmaster.internal/ubuntu resolute/main amd64 iptables amd64 1.8.11-2ubuntu3 [381 kB] 81s Get:31 http://ftpmaster.internal/ubuntu resolute/main amd64 libip4tc2 amd64 1.8.11-2ubuntu3 [24.2 kB] 81s Get:32 http://ftpmaster.internal/ubuntu resolute/main amd64 libip6tc2 amd64 1.8.11-2ubuntu3 [24.4 kB] 81s Get:33 http://ftpmaster.internal/ubuntu resolute/main amd64 libnetfilter-conntrack3 amd64 1.1.1-1 [47.5 kB] 81s Get:34 http://ftpmaster.internal/ubuntu resolute/main amd64 libxtables12 amd64 1.8.11-2ubuntu3 [36.6 kB] 82s Get:35 http://ftpmaster.internal/ubuntu resolute/main amd64 iproute2 amd64 6.18.0-1ubuntu1 [1178 kB] 82s Get:36 http://ftpmaster.internal/ubuntu resolute/main amd64 less amd64 668-1build1 [172 kB] 82s Get:37 http://ftpmaster.internal/ubuntu resolute/main amd64 libcryptsetup12 amd64 2:2.8.0-1ubuntu3 [283 kB] 82s Get:38 http://ftpmaster.internal/ubuntu resolute/main amd64 libglib2.0-data all 2.87.2-2 [58.2 kB] 82s Get:39 http://ftpmaster.internal/ubuntu resolute/main amd64 libidn2-0 amd64 2.3.8-4build1 [67.6 kB] 82s Get:40 http://ftpmaster.internal/ubuntu resolute/main amd64 libkeyutils1 amd64 1.6.3-6ubuntu3 [10.6 kB] 82s Get:41 http://ftpmaster.internal/ubuntu resolute/main amd64 python3-linkify-it all 2.0.3-1ubuntu3 [19.4 kB] 82s Get:42 http://ftpmaster.internal/ubuntu resolute/main amd64 python3-markdown-it all 3.0.0-3build1 [54.4 kB] 82s Get:43 http://ftpmaster.internal/ubuntu resolute/main amd64 shared-mime-info amd64 2.4-5build3 [476 kB] 82s Get:44 http://ftpmaster.internal/ubuntu resolute/main amd64 busybox-static amd64 1:1.37.0-7ubuntu1 [1034 kB] 82s Get:45 http://ftpmaster.internal/ubuntu resolute/main amd64 libdrm-common all 2.4.131-1 [9774 B] 82s Get:46 http://ftpmaster.internal/ubuntu resolute/main amd64 libdrm2 amd64 2.4.131-1 [42.3 kB] 82s Get:47 http://ftpmaster.internal/ubuntu resolute/main amd64 libgdbm6t64 amd64 1.26-1build1 [36.5 kB] 82s Get:48 http://ftpmaster.internal/ubuntu resolute/main amd64 libgpm2 amd64 1.20.7-12build1 [14.4 kB] 82s Get:49 http://ftpmaster.internal/ubuntu resolute/main amd64 libjansson4 amd64 2.14-2build4 [33.2 kB] 82s Get:50 http://ftpmaster.internal/ubuntu resolute/main amd64 lsof amd64 4.99.4+dfsg-2build2 [239 kB] 82s Get:51 http://ftpmaster.internal/ubuntu resolute/main amd64 liblsof0 amd64 4.99.4+dfsg-2build2 [56.5 kB] 82s Get:52 http://ftpmaster.internal/ubuntu resolute/main amd64 libmaxminddb0 amd64 1.12.2-1build2 [18.9 kB] 82s Get:53 http://ftpmaster.internal/ubuntu resolute/main amd64 libpcap0.8t64 amd64 1.10.5-2ubuntu3 [154 kB] 82s Get:54 http://ftpmaster.internal/ubuntu resolute/main amd64 pciutils amd64 1:3.14.0-1build2 [95.5 kB] 82s Get:55 http://ftpmaster.internal/ubuntu resolute/main amd64 libpci3 amd64 1:3.14.0-1build2 [38.1 kB] 82s Get:56 http://ftpmaster.internal/ubuntu resolute/main amd64 libsensors-config all 1:3.6.2-2build1 [6862 B] 82s Get:57 http://ftpmaster.internal/ubuntu resolute/main amd64 libsensors5 amd64 1:3.6.2-2build1 [28.9 kB] 82s Get:58 http://ftpmaster.internal/ubuntu resolute/main amd64 libusb-1.0-0 amd64 2:1.0.29-2build1 [56.9 kB] 82s Get:59 http://ftpmaster.internal/ubuntu resolute/main amd64 libxau6 amd64 1:1.0.11-1build2 [7502 B] 82s Get:60 http://ftpmaster.internal/ubuntu resolute/main amd64 libxkbcommon0 amd64 1.13.1-1 [159 kB] 82s Get:61 http://ftpmaster.internal/ubuntu resolute/main amd64 man-db amd64 2.13.1-1build1 [1392 kB] 82s Get:62 http://ftpmaster.internal/ubuntu resolute/main amd64 tcpdump amd64 4.99.5-2ubuntu3 [477 kB] 82s Get:63 http://ftpmaster.internal/ubuntu resolute/main amd64 wget amd64 1.25.0-2ubuntu4 [353 kB] 82s Get:64 http://ftpmaster.internal/ubuntu resolute/main amd64 ubuntu-standard amd64 1.564 [13.3 kB] 82s Get:65 http://ftpmaster.internal/ubuntu resolute/main amd64 3cpio amd64 0.14.0-1ubuntu1 [285 kB] 82s Get:66 http://ftpmaster.internal/ubuntu resolute/main amd64 bpftool amd64 7.7.0+6.19.0-3.3 [1229 kB] 82s Get:67 http://ftpmaster.internal/ubuntu resolute/main amd64 busybox-initramfs amd64 1:1.37.0-7ubuntu1 [191 kB] 82s Get:68 http://ftpmaster.internal/ubuntu resolute/main amd64 cryptsetup-bin amd64 2:2.8.0-1ubuntu3 [228 kB] 82s Get:69 http://ftpmaster.internal/ubuntu resolute/main amd64 dracut-install amd64 109-11ubuntu1 [45.8 kB] 82s Get:70 http://ftpmaster.internal/ubuntu resolute/main amd64 hwdata all 0.394-1build1 [1566 B] 82s Get:71 http://ftpmaster.internal/ubuntu resolute/main amd64 pnp.ids all 0.394-1build1 [29.6 kB] 82s Get:72 http://ftpmaster.internal/ubuntu resolute/main amd64 libbrotli1 amd64 1.2.0-3 [343 kB] 82s Get:73 http://ftpmaster.internal/ubuntu resolute/main amd64 libdrm-amdgpu1 amd64 2.4.131-1 [23.2 kB] 82s Get:74 http://ftpmaster.internal/ubuntu resolute/main amd64 libevent-core-2.1-7t64 amd64 2.1.12-stable-10build2 [93.1 kB] 82s Get:75 http://ftpmaster.internal/ubuntu resolute/main amd64 libgdbm-compat4t64 amd64 1.26-1build1 [6796 B] 82s Get:76 http://ftpmaster.internal/ubuntu resolute/main amd64 libgudev-1.0-0 amd64 1:238-7build1 [15.9 kB] 82s Get:77 http://ftpmaster.internal/ubuntu resolute/main amd64 libnpth0t64 amd64 1.8-3build1 [9302 B] 82s Get:78 http://ftpmaster.internal/ubuntu resolute/main amd64 libonig5 amd64 6.9.10-1build1 [174 kB] 82s Get:79 http://ftpmaster.internal/ubuntu resolute/main amd64 libpython3.14-minimal amd64 3.14.2-1 [920 kB] 82s Get:80 http://ftpmaster.internal/ubuntu resolute/main amd64 libpython3.14-stdlib amd64 3.14.2-1 [2398 kB] 82s Get:81 http://ftpmaster.internal/ubuntu resolute/main amd64 libpython3.14 amd64 3.14.2-1 [2568 kB] 82s Get:82 http://ftpmaster.internal/ubuntu resolute/main amd64 libwrap0 amd64 7.6.q-36build2 [48.5 kB] 82s Get:83 http://ftpmaster.internal/ubuntu resolute/main amd64 linux-modules-6.19.0-3-generic amd64 6.19.0-3.3 [171 MB] 85s Get:84 http://ftpmaster.internal/ubuntu resolute/main amd64 linux-image-6.19.0-3-generic amd64 6.19.0-3.3+1 [16.8 MB] 86s Get:85 http://ftpmaster.internal/ubuntu resolute/main amd64 amd64-microcode amd64 3.20251202.1ubuntu1 [459 kB] 86s Get:86 http://ftpmaster.internal/ubuntu resolute/main amd64 linux-generic amd64 6.19.0-3.3 [1698 B] 86s Get:87 http://ftpmaster.internal/ubuntu resolute/main amd64 linux-image-generic amd64 6.19.0-3.3 [12.2 kB] 86s Get:88 http://ftpmaster.internal/ubuntu resolute/main amd64 linux-virtual amd64 6.19.0-3.3 [1700 B] 86s Get:89 http://ftpmaster.internal/ubuntu resolute/main amd64 linux-image-virtual amd64 6.19.0-3.3 [12.1 kB] 86s Get:90 http://ftpmaster.internal/ubuntu resolute/main amd64 linux-headers-virtual amd64 6.19.0-3.3 [1646 B] 86s Get:91 http://ftpmaster.internal/ubuntu resolute/main amd64 linux-headers-6.19.0-3 all 6.19.0-3.3 [14.9 MB] 86s Get:92 http://ftpmaster.internal/ubuntu resolute/main amd64 linux-headers-6.19.0-3-generic amd64 6.19.0-3.3 [4330 kB] 86s Get:93 http://ftpmaster.internal/ubuntu resolute/main amd64 linux-headers-generic amd64 6.19.0-3.3 [12.0 kB] 86s Get:94 http://ftpmaster.internal/ubuntu resolute/main amd64 linux-perf amd64 6.19.0-3.3 [4480 kB] 86s Get:95 http://ftpmaster.internal/ubuntu resolute/main amd64 linux-tools-common all 6.19.0-3.3 [345 kB] 86s Get:96 http://ftpmaster.internal/ubuntu resolute/main amd64 linux-tools-6.19.0-3 amd64 6.19.0-3.3 [1455 kB] 86s Get:97 http://ftpmaster.internal/ubuntu resolute/main amd64 linux-tools-6.19.0-3-generic amd64 6.19.0-3.3 [1612 B] 86s Get:98 http://ftpmaster.internal/ubuntu resolute/main amd64 patch amd64 2.8-2build1 [95.7 kB] 86s Get:99 http://ftpmaster.internal/ubuntu resolute/main amd64 pollinate all 4.33-4ubuntu5 [14.0 kB] 86s Get:100 http://ftpmaster.internal/ubuntu resolute/main amd64 python3-referencing all 0.36.2-1ubuntu2 [22.2 kB] 86s Get:101 http://ftpmaster.internal/ubuntu resolute/main amd64 ubuntu-kernel-accessories amd64 1.564 [13.1 kB] 86s dpkg-preconfigure: unable to re-open stdin: No such file or directory 86s Fetched 237 MB in 5s (48.6 MB/s) 86s (Reading database ... (Reading database ... 5% (Reading database ... 10% (Reading database ... 15% (Reading database ... 20% (Reading database ... 25% (Reading database ... 30% (Reading database ... 35% (Reading database ... 40% (Reading database ... 45% (Reading database ... 50% (Reading database ... 55% (Reading database ... 60% (Reading database ... 65% (Reading database ... 70% (Reading database ... 75% (Reading database ... 80% (Reading database ... 85% (Reading database ... 90% (Reading database ... 95% (Reading database ... 100% (Reading database ... 83957 files and directories currently installed.) 86s Preparing to unpack .../debianutils_5.23.2build1_amd64.deb ... 86s Unpacking debianutils (5.23.2build1) over (5.23.2) ... 86s Setting up debianutils (5.23.2build1) ... 87s (Reading database ... (Reading database ... 5% (Reading database ... 10% (Reading database ... 15% (Reading database ... 20% (Reading database ... 25% (Reading database ... 30% (Reading database ... 35% (Reading database ... 40% (Reading database ... 45% (Reading database ... 50% (Reading database ... 55% (Reading database ... 60% (Reading database ... 65% (Reading database ... 70% (Reading database ... 75% (Reading database ... 80% (Reading database ... 85% (Reading database ... 90% (Reading database ... 95% (Reading database ... 100% (Reading database ... 83957 files and directories currently installed.) 87s Preparing to unpack .../dash_0.5.12-12ubuntu3_amd64.deb ... 87s Unpacking dash (0.5.12-12ubuntu3) over (0.5.12-12ubuntu2) ... 87s Setting up dash (0.5.12-12ubuntu3) ... 87s (Reading database ... (Reading database ... 5% (Reading database ... 10% (Reading database ... 15% (Reading database ... 20% (Reading database ... 25% (Reading database ... 30% (Reading database ... 35% (Reading database ... 40% (Reading database ... 45% (Reading database ... 50% (Reading database ... 55% (Reading database ... 60% (Reading database ... 65% (Reading database ... 70% (Reading database ... 75% (Reading database ... 80% (Reading database ... 85% (Reading database ... 90% (Reading database ... 95% (Reading database ... 100% (Reading database ... 83957 files and directories currently installed.) 87s Preparing to unpack .../findutils_4.10.0-3build2_amd64.deb ... 87s Unpacking findutils (4.10.0-3build2) over (4.10.0-3build1) ... 87s Setting up findutils (4.10.0-3build2) ... 87s (Reading database ... (Reading database ... 5% (Reading database ... 10% (Reading database ... 15% (Reading database ... 20% (Reading database ... 25% (Reading database ... 30% (Reading database ... 35% (Reading database ... 40% (Reading database ... 45% (Reading database ... 50% (Reading database ... 55% (Reading database ... 60% (Reading database ... 65% (Reading database ... 70% (Reading database ... 75% (Reading database ... 80% (Reading database ... 85% (Reading database ... 90% (Reading database ... 95% (Reading database ... 100% (Reading database ... 83957 files and directories currently installed.) 87s Preparing to unpack .../sed_4.9-2build3_amd64.deb ... 87s Unpacking sed (4.9-2build3) over (4.9-2build2) ... 87s Setting up sed (4.9-2build3) ... 87s (Reading database ... (Reading database ... 5% (Reading database ... 10% (Reading database ... 15% (Reading database ... 20% (Reading database ... 25% (Reading database ... 30% (Reading database ... 35% (Reading database ... 40% (Reading database ... 45% (Reading database ... 50% (Reading database ... 55% (Reading database ... 60% (Reading database ... 65% (Reading database ... 70% (Reading database ... 75% (Reading database ... 80% (Reading database ... 85% (Reading database ... 90% (Reading database ... 95% (Reading database ... 100% (Reading database ... 83957 files and directories currently installed.) 87s Preparing to unpack .../tar_1.35+dfsg-3.1build2_amd64.deb ... 87s Unpacking tar (1.35+dfsg-3.1build2) over (1.35+dfsg-3.1build1) ... 87s Setting up tar (1.35+dfsg-3.1build2) ... 87s (Reading database ... (Reading database ... 5% (Reading database ... 10% (Reading database ... 15% (Reading database ... 20% (Reading database ... 25% (Reading database ... 30% (Reading database ... 35% (Reading database ... 40% (Reading database ... 45% (Reading database ... 50% (Reading database ... 55% (Reading database ... 60% (Reading database ... 65% (Reading database ... 70% (Reading database ... 75% (Reading database ... 80% (Reading database ... 85% (Reading database ... 90% (Reading database ... 95% (Reading database ... 100% (Reading database ... 83957 files and directories currently installed.) 87s Preparing to unpack .../libattr1_1%3a2.5.2-3build2_amd64.deb ... 87s Unpacking libattr1:amd64 (1:2.5.2-3build2) over (1:2.5.2-3build1) ... 87s Setting up libattr1:amd64 (1:2.5.2-3build2) ... 87s Selecting previously unselected package gcc-16-base:amd64. 87s (Reading database ... (Reading database ... 5% (Reading database ... 10% (Reading database ... 15% (Reading database ... 20% (Reading database ... 25% (Reading database ... 30% (Reading database ... 35% (Reading database ... 40% (Reading database ... 45% (Reading database ... 50% (Reading database ... 55% (Reading database ... 60% (Reading database ... 65% (Reading database ... 70% (Reading database ... 75% (Reading database ... 80% (Reading database ... 85% (Reading database ... 90% (Reading database ... 95% (Reading database ... 100% (Reading database ... 83957 files and directories currently installed.) 87s Preparing to unpack .../gcc-16-base_16-20260208-1ubuntu1_amd64.deb ... 87s Unpacking gcc-16-base:amd64 (16-20260208-1ubuntu1) ... 87s Setting up gcc-16-base:amd64 (16-20260208-1ubuntu1) ... 87s (Reading database ... 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Setting up libgdbm-compat4t64:amd64 (1.26-1build1) ... 94s Setting up bpftool (7.7.0+6.19.0-3.3) ... 94s Setting up libip6tc2:amd64 (1.8.11-2ubuntu3) ... 94s Setting up liblsof0 (4.99.4+dfsg-2build2) ... 94s Setting up libmaxminddb0:amd64 (1.12.2-1build2) ... 94s Setting up libbrotli1:amd64 (1.2.0-3) ... 94s Setting up libpython3.14-minimal:amd64 (3.14.2-1) ... 94s Setting up libsensors-config (1:3.6.2-2build1) ... 94s Setting up less (668-1build1) ... 94s Setting up linux-headers-6.19.0-3 (6.19.0-3.3) ... 94s Setting up libidn2-0:amd64 (2.3.8-4build1) ... 94s Setting up amd64-microcode (3.20251202.1ubuntu1) ... 94s amd64-microcode: microcode will be updated at next boot 94s Setting up man-db (2.13.1-1build1) ... 95s Updating database of manual pages ... 96s man-db.service is a disabled or a static unit not running, not starting it. 96s Setting up libjansson4:amd64 (2.14-2build4) ... 96s Setting up libglib2.0-data (2.87.2-2) ... 96s Setting up pollinate (4.33-4ubuntu5) ... 106s Setting up busybox-static (1:1.37.0-7ubuntu1) ... 106s Setting up libwrap0:amd64 (7.6.q-36build2) ... 106s Setting up linux-image-6.19.0-3-generic (6.19.0-3.3+1) ... 107s I: /boot/vmlinuz is now a symlink to vmlinuz-6.19.0-3-generic 107s I: /boot/initrd.img is now a symlink to initrd.img-6.19.0-3-generic 108s Setting up libdbus-1-3:amd64 (1.16.2-2ubuntu3) ... 108s Setting up libatomic1:amd64 (16-20260208-1ubuntu1) ... 108s Setting up patch (2.8-2build1) ... 108s Setting up libsensors5:amd64 (1:3.6.2-2build1) ... 108s Setting up busybox-initramfs (1:1.37.0-7ubuntu1) ... 108s Setting up libxtables12:amd64 (1.8.11-2ubuntu3) ... 108s Setting up lsof (4.99.4+dfsg-2build2) ... 108s Setting up libpci3:amd64 (1:3.14.0-1build2) ... 108s Setting up libdevmapper1.02.1:amd64 (2:1.02.205-2ubuntu3) ... 108s Setting up dracut-install (109-11ubuntu1) ... 108s Setting up dmsetup (2:1.02.205-2ubuntu3) ... 108s Setting up libnetfilter-conntrack3:amd64 (1.1.1-1) ... 108s Setting up pnp.ids (0.394-1build1) ... 108s Setting up dbus-session-bus-common (1.16.2-2ubuntu3) ... 108s Setting up python3-linkify-it (2.0.3-1ubuntu3) ... 108s Setting up libpcap0.8t64:amd64 (1.10.5-2ubuntu3) ... 108s Setting up libcryptsetup12:amd64 (2:2.8.0-1ubuntu3) ... 108s Setting up mawk (1.3.4.20260129-1) ... 108s Setting up libevent-core-2.1-7t64:amd64 (2.1.12-stable-10build2) ... 108s Setting up libusb-1.0-0:amd64 (2:1.0.29-2build1) ... 108s Setting up linux-image-virtual (6.19.0-3.3) ... 108s Setting up dbus-system-bus-common (1.16.2-2ubuntu3) ... 108s Setting up libbsd0:amd64 (0.12.2-2build2) ... 108s Setting up libdrm-common (2.4.131-1) ... 108s Setting up libstdc++6:amd64 (16-20260208-1ubuntu1) ... 108s Setting up dbus-bin (1.16.2-2ubuntu3) ... 108s Setting up libonig5:amd64 (6.9.10-1build1) ... 108s Setting up libbpf1:amd64 (1:1.6.2-1build1) ... 108s Setting up ethtool (1:6.15-3build1) ... 108s Setting up python3-referencing (0.36.2-1ubuntu2) ... 108s Setting up libxkbcommon0:amd64 (1.13.1-1) ... 108s Setting up cryptsetup-bin (2:2.8.0-1ubuntu3) ... 108s Setting up linux-headers-6.19.0-3-generic (6.19.0-3.3) ... 108s Setting up tcpdump (4.99.5-2ubuntu3) ... 108s Setting up linux-image-generic (6.19.0-3.3) ... 108s Setting up wget (1.25.0-2ubuntu4) ... 108s Setting up libpython3.14-stdlib:amd64 (3.14.2-1) ... 108s Setting up iptables (1.8.11-2ubuntu3) ... 108s Setting up iproute2 (6.18.0-1ubuntu1) ... 108s Setting up linux-headers-generic (6.19.0-3.3) ... 108s Setting up dbus-daemon (1.16.2-2ubuntu3) ... 108s Setting up hwdata (0.394-1build1) ... 108s Setting up dbus-user-session (1.16.2-2ubuntu3) ... 108s Setting up libglib2.0-0t64:amd64 (2.87.2-2) ... 108s No schema files found: doing nothing. 108s Setting up dbus (1.16.2-2ubuntu3) ... 108s A reboot is required to replace the running dbus-daemon. 108s Please reboot the system when convenient. 108s Setting up shared-mime-info (2.4-5build3) ... 109s Setting up gir1.2-glib-2.0:amd64 (2.87.2-2) ... 109s Setting up pciutils (1:3.14.0-1build2) ... 109s Setting up python3-markdown-it (3.0.0-3build1) ... 109s Setting up libdrm2:amd64 (2.4.131-1) ... 109s Setting up libpython3.14:amd64 (3.14.2-1) ... 109s Setting up libapt-pkg7.0:amd64 (3.1.15) ... 109s Setting up linux-tools-common (6.19.0-3.3) ... 109s Setting up libgudev-1.0-0:amd64 (1:238-7build1) ... 109s Setting up libdrm-amdgpu1:amd64 (2.4.131-1) ... 109s Setting up apt (3.1.15) ... 109s Setting up linux-headers-virtual (6.19.0-3.3) ... 109s Setting up linux-generic (6.19.0-3.3) ... 109s Setting up libgirepository-2.0-0:amd64 (2.87.2-2) ... 109s Setting up linux-tools-6.19.0-3 (6.19.0-3.3) ... 109s Setting up ubuntu-standard (1.564) ... 109s Setting up gir1.2-girepository-3.0:amd64 (2.87.2-2) ... 109s Setting up linux-virtual (6.19.0-3.3) ... 109s Setting up linux-perf (6.19.0-3.3) ... 109s Setting up linux-tools-6.19.0-3-generic (6.19.0-3.3) ... 109s Processing triggers for debianutils (5.23.2build1) ... 109s Processing triggers for install-info (7.2-5) ... 109s Processing triggers for initramfs-tools (0.150ubuntu7) ... 110s update-initramfs: Generating /boot/initrd.img-6.18.0-9-generic 114s Processing triggers for libc-bin (2.42-2ubuntu4) ... 114s Processing triggers for linux-image-6.19.0-3-generic (6.19.0-3.3+1) ... 114s /etc/kernel/postinst.d/initramfs-tools: 114s update-initramfs: Generating /boot/initrd.img-6.19.0-3-generic 117s /etc/kernel/postinst.d/zz-update-grub: 117s Sourcing file `/etc/default/grub' 117s Sourcing file `/etc/default/grub.d/50-cloudimg-settings.cfg' 117s Sourcing file `/etc/default/grub.d/90-autopkgtest.cfg' 117s Generating grub configuration file ... 118s Found linux image: /boot/vmlinuz-6.19.0-3-generic 118s Found initrd image: /boot/initrd.img-6.19.0-3-generic 118s Found linux image: /boot/vmlinuz-6.18.0-9-generic 118s Found initrd image: /boot/initrd.img-6.18.0-9-generic 118s Warning: os-prober will not be executed to detect other bootable partitions. 118s Systems on them will not be added to the GRUB boot configuration. 118s Check GRUB_DISABLE_OS_PROBER documentation entry. 118s Adding boot menu entry for UEFI Firmware Settings ... 118s done 118s autopkgtest [05:50:01]: upgrading testbed (apt dist-upgrade and autopurge) 119s Reading package lists... 119s Building dependency tree... 119s Reading state information... 119s Calculating upgrade... 119s The following package was automatically installed and is no longer required: 119s libpython3.13 119s Use 'sudo apt autoremove' to remove it. 119s 0 upgraded, 0 newly installed, 0 to remove and 0 not upgraded. 119s Reading package lists... 119s Building dependency tree... 119s Reading state information... 119s Solving dependencies... 119s The following packages will be REMOVED: 119s libpython3.13* 120s 0 upgraded, 0 newly installed, 1 to remove and 0 not upgraded. 120s After this operation, 7599 kB disk space will be freed. 120s (Reading database ... (Reading database ... 5% (Reading database ... 10% (Reading database ... 15% (Reading database ... 20% (Reading database ... 25% (Reading database ... 30% (Reading database ... 35% (Reading database ... 40% (Reading database ... 45% (Reading database ... 50% (Reading database ... 55% (Reading database ... 60% (Reading database ... 65% (Reading database ... 70% (Reading database ... 75% (Reading database ... 80% (Reading database ... 85% (Reading database ... 90% (Reading database ... 95% (Reading database ... 100% (Reading database ... 125273 files and directories currently installed.) 120s Removing libpython3.13:amd64 (3.13.11-1) ... 120s Processing triggers for libc-bin (2.42-2ubuntu4) ... 120s autopkgtest [05:50:03]: rebooting testbed after setup commands that affected boot 148s autopkgtest [05:50:31]: testbed running kernel: Linux 6.19.0-3-generic #3-Ubuntu SMP PREEMPT_DYNAMIC Fri Jan 23 20:01:24 UTC 2026 150s autopkgtest [05:50:33]: @@@@@@@@@@@@@@@@@@@@ apt-source r-cran-pscbs 151s Get:1 http://ftpmaster.internal/ubuntu resolute/universe r-cran-pscbs 0.68.0-1 (dsc) [2315 B] 151s Get:2 http://ftpmaster.internal/ubuntu resolute/universe r-cran-pscbs 0.68.0-1 (tar) [3591 kB] 151s Get:3 http://ftpmaster.internal/ubuntu resolute/universe r-cran-pscbs 0.68.0-1 (diff) [4040 B] 151s gpgv: Signature made Thu Jan 29 01:13:59 2026 UTC 151s gpgv: using RSA key 73471499CC60ED9EEE805946C5BD6C8F2295D502 151s gpgv: issuer "plessy@debian.org" 151s gpgv: Can't check signature: No public key 151s dpkg-source: warning: cannot verify inline signature for ./r-cran-pscbs_0.68.0-1.dsc: no acceptable signature found 151s autopkgtest [05:50:34]: testing package r-cran-pscbs version 0.68.0-1 151s autopkgtest [05:50:34]: build not needed 153s autopkgtest [05:50:36]: test run-unit-test: preparing testbed 153s Reading package lists... 153s Building dependency tree... 153s Reading state information... 153s Solving dependencies... 154s The following NEW packages will be installed: 154s fontconfig fontconfig-config fonts-dejavu-core fonts-dejavu-mono libblas3 154s libcairo2 libdatrie1 libdeflate0 libfontconfig1 libgfortran5 libgomp1 154s libgraphite2-3 libharfbuzz0b libice6 libjbig0 libjpeg-turbo8 libjpeg8 154s liblapack3 liblerc4 libpango-1.0-0 libpangocairo-1.0-0 libpangoft2-1.0-0 154s libpaper-utils libpaper2 libpixman-1-0 libsharpyuv0 libsm6 libtcl8.6 154s libthai-data libthai0 libtiff6 libtk8.6 libwebp7 libxcb-render0 libxcb-shm0 154s libxft2 libxrender1 libxss1 libxt6t64 r-base-core r-bioc-aroma.light 154s r-bioc-biocgenerics r-bioc-dnacopy r-cran-base64enc r-cran-cli 154s r-cran-codetools r-cran-digest r-cran-farver r-cran-future r-cran-ggplot2 154s r-cran-globals r-cran-glue r-cran-gtable r-cran-isoband r-cran-labeling 154s r-cran-lifecycle r-cran-listenv r-cran-matrixstats r-cran-parallelly 154s r-cran-pscbs r-cran-r.cache r-cran-r.devices r-cran-r.methodss3 r-cran-r.oo 154s r-cran-r.rsp r-cran-r.utils r-cran-r6 r-cran-rcolorbrewer r-cran-rlang 154s r-cran-s7 r-cran-scales r-cran-vctrs r-cran-viridislite r-cran-withr tcl 154s tcl8.6 unzip x11-common xdg-utils zip 154s 0 upgraded, 80 newly installed, 0 to remove and 0 not upgraded. 154s Need to get 68.2 MB of archives. 154s After this operation, 126 MB of additional disk space will be used. 154s Get:1 http://ftpmaster.internal/ubuntu resolute/main amd64 fonts-dejavu-mono all 2.37-8build1 [502 kB] 154s Get:2 http://ftpmaster.internal/ubuntu resolute/main amd64 fonts-dejavu-core all 2.37-8build1 [834 kB] 154s Get:3 http://ftpmaster.internal/ubuntu resolute/main amd64 fontconfig-config amd64 2.17.1-3ubuntu1 [38.5 kB] 154s Get:4 http://ftpmaster.internal/ubuntu resolute/main amd64 libfontconfig1 amd64 2.17.1-3ubuntu1 [144 kB] 154s Get:5 http://ftpmaster.internal/ubuntu resolute/main amd64 fontconfig amd64 2.17.1-3ubuntu1 [180 kB] 154s Get:6 http://ftpmaster.internal/ubuntu resolute/main amd64 libblas3 amd64 3.12.1-7ubuntu1 [260 kB] 154s Get:7 http://ftpmaster.internal/ubuntu resolute/main amd64 libpixman-1-0 amd64 0.46.4-1 [287 kB] 154s Get:8 http://ftpmaster.internal/ubuntu resolute/main amd64 libxcb-render0 amd64 1.17.0-2ubuntu1 [16.2 kB] 154s Get:9 http://ftpmaster.internal/ubuntu resolute/main amd64 libxcb-shm0 amd64 1.17.0-2ubuntu1 [5808 B] 154s Get:10 http://ftpmaster.internal/ubuntu resolute/main amd64 libxrender1 amd64 1:0.9.12-1 [19.8 kB] 154s Get:11 http://ftpmaster.internal/ubuntu resolute/main amd64 libcairo2 amd64 1.18.4-3 [579 kB] 154s Get:12 http://ftpmaster.internal/ubuntu resolute/main amd64 libdatrie1 amd64 0.2.14-1 [19.8 kB] 154s Get:13 http://ftpmaster.internal/ubuntu resolute/main amd64 libdeflate0 amd64 1.23-2build1 [51.6 kB] 154s Get:14 http://ftpmaster.internal/ubuntu resolute/main amd64 libgfortran5 amd64 16-20260208-1ubuntu1 [957 kB] 154s Get:15 http://ftpmaster.internal/ubuntu resolute/main amd64 libgomp1 amd64 16-20260208-1ubuntu1 [162 kB] 154s Get:16 http://ftpmaster.internal/ubuntu resolute/main amd64 libgraphite2-3 amd64 1.3.14-11ubuntu1 [73.7 kB] 154s Get:17 http://ftpmaster.internal/ubuntu resolute/main amd64 libharfbuzz0b amd64 12.3.2-1 [519 kB] 154s Get:18 http://ftpmaster.internal/ubuntu resolute/main amd64 x11-common all 1:7.7+24ubuntu1 [22.4 kB] 154s Get:19 http://ftpmaster.internal/ubuntu resolute/main amd64 libice6 amd64 2:1.1.1-1build1 [44.0 kB] 154s Get:20 http://ftpmaster.internal/ubuntu resolute/main amd64 libjpeg-turbo8 amd64 2.1.5-4ubuntu3 [156 kB] 154s Get:21 http://ftpmaster.internal/ubuntu resolute/main amd64 libjpeg8 amd64 8c-2ubuntu12 [2142 B] 154s Get:22 http://ftpmaster.internal/ubuntu resolute/main amd64 liblapack3 amd64 3.12.1-7ubuntu1 [2739 kB] 154s Get:23 http://ftpmaster.internal/ubuntu resolute/main amd64 liblerc4 amd64 4.0.0+ds-5ubuntu2 [207 kB] 154s Get:24 http://ftpmaster.internal/ubuntu resolute/main amd64 libthai-data all 0.1.30-1 [155 kB] 154s Get:25 http://ftpmaster.internal/ubuntu resolute/main amd64 libthai0 amd64 0.1.30-1 [19.2 kB] 154s Get:26 http://ftpmaster.internal/ubuntu resolute/main amd64 libpango-1.0-0 amd64 1.57.0-1 [241 kB] 154s Get:27 http://ftpmaster.internal/ubuntu resolute/main amd64 libpangoft2-1.0-0 amd64 1.57.0-1 [53.3 kB] 154s Get:28 http://ftpmaster.internal/ubuntu resolute/main amd64 libpangocairo-1.0-0 amd64 1.57.0-1 [29.0 kB] 154s Get:29 http://ftpmaster.internal/ubuntu resolute/main amd64 libpaper2 amd64 2.2.5-0.3build1 [17.3 kB] 154s Get:30 http://ftpmaster.internal/ubuntu resolute/main amd64 libpaper-utils amd64 2.2.5-0.3build1 [15.6 kB] 154s Get:31 http://ftpmaster.internal/ubuntu resolute/main amd64 libsharpyuv0 amd64 1.5.0-0.1build1 [17.6 kB] 154s Get:32 http://ftpmaster.internal/ubuntu resolute/main amd64 libsm6 amd64 2:1.2.6-1build1 [16.9 kB] 154s Get:33 http://ftpmaster.internal/ubuntu resolute/main amd64 libtcl8.6 amd64 8.6.17+dfsg-1build1 [1003 kB] 154s Get:34 http://ftpmaster.internal/ubuntu resolute/main amd64 libjbig0 amd64 2.1-6.1ubuntu3 [30.0 kB] 154s Get:35 http://ftpmaster.internal/ubuntu resolute/main amd64 libwebp7 amd64 1.5.0-0.1build1 [264 kB] 154s Get:36 http://ftpmaster.internal/ubuntu resolute/main amd64 libtiff6 amd64 4.7.0-3ubuntu3 [209 kB] 154s Get:37 http://ftpmaster.internal/ubuntu resolute/main amd64 libxft2 amd64 2.3.6-1build2 [45.1 kB] 154s Get:38 http://ftpmaster.internal/ubuntu resolute/main amd64 libxss1 amd64 1:1.2.3-1build4 [7084 B] 154s Get:39 http://ftpmaster.internal/ubuntu resolute/main amd64 libtk8.6 amd64 8.6.17-1 [823 kB] 154s Get:40 http://ftpmaster.internal/ubuntu resolute/main amd64 libxt6t64 amd64 1:1.2.1-1.3 [173 kB] 154s Get:41 http://ftpmaster.internal/ubuntu resolute/main amd64 zip amd64 3.0-15ubuntu3 [175 kB] 154s Get:42 http://ftpmaster.internal/ubuntu resolute/main amd64 unzip amd64 6.0-29ubuntu1 [180 kB] 154s Get:43 http://ftpmaster.internal/ubuntu resolute/main amd64 xdg-utils all 1.2.1-2ubuntu2 [66.1 kB] 154s Get:44 http://ftpmaster.internal/ubuntu resolute/universe amd64 r-base-core amd64 4.5.2-1ubuntu2 [28.8 MB] 155s Get:45 http://ftpmaster.internal/ubuntu resolute/universe amd64 r-bioc-biocgenerics all 0.52.0-2 [624 kB] 155s Get:46 http://ftpmaster.internal/ubuntu resolute/universe amd64 r-cran-r.methodss3 all 1.8.2-1 [84.0 kB] 155s Get:47 http://ftpmaster.internal/ubuntu resolute/universe amd64 r-cran-r.oo all 1.27.1-1 [978 kB] 155s Get:48 http://ftpmaster.internal/ubuntu resolute/universe amd64 r-cran-r.utils all 2.13.0-1 [1423 kB] 155s Get:49 http://ftpmaster.internal/ubuntu resolute/universe amd64 r-cran-matrixstats amd64 1.5.0-1 [542 kB] 155s Get:50 http://ftpmaster.internal/ubuntu resolute/universe amd64 r-bioc-aroma.light all 3.36.0-2 [583 kB] 155s Get:51 http://ftpmaster.internal/ubuntu resolute/universe amd64 r-bioc-dnacopy amd64 1.80.0-2 [500 kB] 155s Get:52 http://ftpmaster.internal/ubuntu resolute/universe amd64 r-cran-base64enc amd64 0.1-3-3build1 [28.5 kB] 155s Get:53 http://ftpmaster.internal/ubuntu resolute/universe amd64 r-cran-cli amd64 3.6.4-1 [1394 kB] 155s Get:54 http://ftpmaster.internal/ubuntu resolute/universe amd64 r-cran-codetools all 0.2-20-1build1 [91.1 kB] 155s Get:55 http://ftpmaster.internal/ubuntu resolute/universe amd64 r-cran-digest amd64 0.6.39-1 [203 kB] 155s Get:56 http://ftpmaster.internal/ubuntu resolute/universe amd64 r-cran-farver amd64 2.1.2-1 [1355 kB] 155s Get:57 http://ftpmaster.internal/ubuntu resolute/universe amd64 r-cran-globals all 0.19.0-1 [160 kB] 155s Get:58 http://ftpmaster.internal/ubuntu resolute/universe amd64 r-cran-listenv all 0.10.0+dfsg-1 [113 kB] 155s Get:59 http://ftpmaster.internal/ubuntu resolute/universe amd64 r-cran-parallelly amd64 1.42.0-1 [540 kB] 155s Get:60 http://ftpmaster.internal/ubuntu resolute/universe amd64 r-cran-future all 1.34.0+dfsg-1 [646 kB] 155s Get:61 http://ftpmaster.internal/ubuntu resolute/universe amd64 r-cran-glue amd64 1.8.0-1 [164 kB] 155s Get:62 http://ftpmaster.internal/ubuntu resolute/universe amd64 r-cran-rlang amd64 1.1.5-3 [1721 kB] 155s Get:63 http://ftpmaster.internal/ubuntu resolute/universe amd64 r-cran-lifecycle all 1.0.5+dfsg-1 [120 kB] 155s Get:64 http://ftpmaster.internal/ubuntu resolute/universe amd64 r-cran-gtable all 0.3.6+dfsg-1 [199 kB] 155s Get:65 http://ftpmaster.internal/ubuntu resolute/universe amd64 r-cran-isoband amd64 0.2.7-1 [1481 kB] 155s Get:66 http://ftpmaster.internal/ubuntu resolute/universe amd64 r-cran-s7 amd64 0.2.0-1 [328 kB] 155s Get:67 http://ftpmaster.internal/ubuntu resolute/universe amd64 r-cran-labeling all 0.4.3-1 [62.1 kB] 155s Get:68 http://ftpmaster.internal/ubuntu resolute/universe amd64 r-cran-r6 all 2.6.1-1 [101 kB] 155s Get:69 http://ftpmaster.internal/ubuntu resolute/universe amd64 r-cran-rcolorbrewer all 1.1-3-1build2 [54.0 kB] 155s Get:70 http://ftpmaster.internal/ubuntu resolute/universe amd64 r-cran-viridislite all 0.4.3-1 [1088 kB] 155s Get:71 http://ftpmaster.internal/ubuntu resolute/universe amd64 r-cran-scales all 1.4.0-1 [725 kB] 155s Get:72 http://ftpmaster.internal/ubuntu resolute/universe amd64 r-cran-vctrs amd64 0.6.5-1 [1335 kB] 155s Get:73 http://ftpmaster.internal/ubuntu resolute/universe amd64 r-cran-withr all 3.0.2+dfsg-1 [214 kB] 156s Get:74 http://ftpmaster.internal/ubuntu resolute-proposed/universe amd64 r-cran-ggplot2 all 4.0.2+dfsg-1 [4941 kB] 156s Get:75 http://ftpmaster.internal/ubuntu resolute/universe amd64 r-cran-r.cache all 0.17.0-1 [117 kB] 156s Get:76 http://ftpmaster.internal/ubuntu resolute/universe amd64 r-cran-pscbs all 0.68.0-1 [4234 kB] 156s Get:77 http://ftpmaster.internal/ubuntu resolute/universe amd64 r-cran-r.devices all 2.17.3+ds-1 [400 kB] 156s Get:78 http://ftpmaster.internal/ubuntu resolute/main amd64 tcl8.6 amd64 8.6.17+dfsg-1build1 [14.9 kB] 156s Get:79 http://ftpmaster.internal/ubuntu resolute/main amd64 tcl amd64 8.6.16build1 [4200 B] 156s Get:80 http://ftpmaster.internal/ubuntu resolute/universe amd64 r-cran-r.rsp all 0.46.0+ds-1 [1412 kB] 156s Preconfiguring packages ... 156s Fetched 68.2 MB in 2s (31.7 MB/s) 156s Selecting previously unselected package fonts-dejavu-mono. 156s (Reading database ... (Reading database ... 5% (Reading database ... 10% (Reading database ... 15% (Reading database ... 20% (Reading database ... 25% (Reading database ... 30% (Reading database ... 35% (Reading database ... 40% (Reading database ... 45% (Reading database ... 50% (Reading database ... 55% (Reading database ... 60% (Reading database ... 65% (Reading database ... 70% (Reading database ... 75% (Reading database ... 80% (Reading database ... 85% (Reading database ... 90% (Reading database ... 95% (Reading database ... 100% (Reading database ... 125269 files and directories currently installed.) 156s Preparing to unpack .../00-fonts-dejavu-mono_2.37-8build1_all.deb ... 156s Unpacking fonts-dejavu-mono (2.37-8build1) ... 156s Selecting previously unselected package fonts-dejavu-core. 156s Preparing to unpack .../01-fonts-dejavu-core_2.37-8build1_all.deb ... 156s Unpacking fonts-dejavu-core (2.37-8build1) ... 156s Selecting previously unselected package fontconfig-config. 156s Preparing to unpack .../02-fontconfig-config_2.17.1-3ubuntu1_amd64.deb ... 156s Unpacking fontconfig-config (2.17.1-3ubuntu1) ... 156s Selecting previously unselected package libfontconfig1:amd64. 156s Preparing to unpack .../03-libfontconfig1_2.17.1-3ubuntu1_amd64.deb ... 156s Unpacking libfontconfig1:amd64 (2.17.1-3ubuntu1) ... 156s Selecting previously unselected package fontconfig. 156s Preparing to unpack .../04-fontconfig_2.17.1-3ubuntu1_amd64.deb ... 156s Unpacking fontconfig (2.17.1-3ubuntu1) ... 156s Selecting previously unselected package libblas3:amd64. 156s Preparing to unpack .../05-libblas3_3.12.1-7ubuntu1_amd64.deb ... 156s Unpacking libblas3:amd64 (3.12.1-7ubuntu1) ... 156s Selecting previously unselected package libpixman-1-0:amd64. 156s Preparing to unpack .../06-libpixman-1-0_0.46.4-1_amd64.deb ... 156s Unpacking libpixman-1-0:amd64 (0.46.4-1) ... 156s Selecting previously unselected package libxcb-render0:amd64. 156s Preparing to unpack .../07-libxcb-render0_1.17.0-2ubuntu1_amd64.deb 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previously unselected package libgfortran5:amd64. 157s Preparing to unpack .../13-libgfortran5_16-20260208-1ubuntu1_amd64.deb ... 157s Unpacking libgfortran5:amd64 (16-20260208-1ubuntu1) ... 157s Selecting previously unselected package libgomp1:amd64. 157s Preparing to unpack .../14-libgomp1_16-20260208-1ubuntu1_amd64.deb ... 157s Unpacking libgomp1:amd64 (16-20260208-1ubuntu1) ... 157s Selecting previously unselected package libgraphite2-3:amd64. 157s Preparing to unpack .../15-libgraphite2-3_1.3.14-11ubuntu1_amd64.deb ... 157s Unpacking libgraphite2-3:amd64 (1.3.14-11ubuntu1) ... 157s Selecting previously unselected package libharfbuzz0b:amd64. 157s Preparing to unpack .../16-libharfbuzz0b_12.3.2-1_amd64.deb ... 157s Unpacking libharfbuzz0b:amd64 (12.3.2-1) ... 157s Selecting previously unselected package x11-common. 157s Preparing to unpack .../17-x11-common_1%3a7.7+24ubuntu1_all.deb ... 157s Unpacking x11-common (1:7.7+24ubuntu1) ... 157s Selecting previously unselected package libice6:amd64. 157s Preparing to unpack .../18-libice6_2%3a1.1.1-1build1_amd64.deb ... 157s Unpacking libice6:amd64 (2:1.1.1-1build1) ... 157s Selecting previously unselected package libjpeg-turbo8:amd64. 157s Preparing to unpack .../19-libjpeg-turbo8_2.1.5-4ubuntu3_amd64.deb ... 157s Unpacking libjpeg-turbo8:amd64 (2.1.5-4ubuntu3) ... 157s Selecting previously unselected package libjpeg8:amd64. 157s Preparing to unpack .../20-libjpeg8_8c-2ubuntu12_amd64.deb ... 157s Unpacking libjpeg8:amd64 (8c-2ubuntu12) ... 157s Selecting previously unselected package liblapack3:amd64. 157s Preparing to unpack .../21-liblapack3_3.12.1-7ubuntu1_amd64.deb ... 157s Unpacking liblapack3:amd64 (3.12.1-7ubuntu1) ... 157s Selecting previously unselected package liblerc4:amd64. 157s Preparing to unpack .../22-liblerc4_4.0.0+ds-5ubuntu2_amd64.deb ... 157s Unpacking liblerc4:amd64 (4.0.0+ds-5ubuntu2) ... 157s Selecting previously unselected package libthai-data. 157s Preparing to unpack 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libpaper2:amd64 (2.2.5-0.3build1) ... 157s Selecting previously unselected package libpaper-utils. 157s Preparing to unpack .../29-libpaper-utils_2.2.5-0.3build1_amd64.deb ... 157s Unpacking libpaper-utils (2.2.5-0.3build1) ... 157s Selecting previously unselected package libsharpyuv0:amd64. 157s Preparing to unpack .../30-libsharpyuv0_1.5.0-0.1build1_amd64.deb ... 157s Unpacking libsharpyuv0:amd64 (1.5.0-0.1build1) ... 157s Selecting previously unselected package libsm6:amd64. 157s Preparing to unpack .../31-libsm6_2%3a1.2.6-1build1_amd64.deb ... 157s Unpacking libsm6:amd64 (2:1.2.6-1build1) ... 157s Selecting previously unselected package libtcl8.6:amd64. 157s Preparing to unpack .../32-libtcl8.6_8.6.17+dfsg-1build1_amd64.deb ... 157s Unpacking libtcl8.6:amd64 (8.6.17+dfsg-1build1) ... 157s Selecting previously unselected package libjbig0:amd64. 157s Preparing to unpack .../33-libjbig0_2.1-6.1ubuntu3_amd64.deb ... 157s Unpacking libjbig0:amd64 (2.1-6.1ubuntu3) ... 157s Selecting previously unselected package libwebp7:amd64. 157s Preparing to unpack .../34-libwebp7_1.5.0-0.1build1_amd64.deb ... 157s Unpacking libwebp7:amd64 (1.5.0-0.1build1) ... 157s Selecting previously unselected package libtiff6:amd64. 157s Preparing to unpack .../35-libtiff6_4.7.0-3ubuntu3_amd64.deb ... 157s Unpacking libtiff6:amd64 (4.7.0-3ubuntu3) ... 157s Selecting previously unselected package libxft2:amd64. 157s Preparing to unpack .../36-libxft2_2.3.6-1build2_amd64.deb ... 157s Unpacking libxft2:amd64 (2.3.6-1build2) ... 157s Selecting previously unselected package libxss1:amd64. 157s Preparing to unpack .../37-libxss1_1%3a1.2.3-1build4_amd64.deb ... 157s Unpacking libxss1:amd64 (1:1.2.3-1build4) ... 157s Selecting previously unselected package libtk8.6:amd64. 157s Preparing to unpack .../38-libtk8.6_8.6.17-1_amd64.deb ... 157s Unpacking libtk8.6:amd64 (8.6.17-1) ... 157s Selecting previously unselected package libxt6t64:amd64. 157s Preparing to unpack .../39-libxt6t64_1%3a1.2.1-1.3_amd64.deb ... 157s Unpacking libxt6t64:amd64 (1:1.2.1-1.3) ... 157s Selecting previously unselected package zip. 157s Preparing to unpack .../40-zip_3.0-15ubuntu3_amd64.deb ... 157s Unpacking zip (3.0-15ubuntu3) ... 157s Selecting previously unselected package unzip. 157s Preparing to unpack .../41-unzip_6.0-29ubuntu1_amd64.deb ... 157s Unpacking unzip (6.0-29ubuntu1) ... 157s Selecting previously unselected package xdg-utils. 157s Preparing to unpack .../42-xdg-utils_1.2.1-2ubuntu2_all.deb ... 157s Unpacking xdg-utils (1.2.1-2ubuntu2) ... 157s Selecting previously unselected package r-base-core. 157s Preparing to unpack .../43-r-base-core_4.5.2-1ubuntu2_amd64.deb ... 157s Unpacking r-base-core (4.5.2-1ubuntu2) ... 157s Selecting previously unselected package r-bioc-biocgenerics. 157s Preparing to unpack .../44-r-bioc-biocgenerics_0.52.0-2_all.deb ... 157s Unpacking r-bioc-biocgenerics (0.52.0-2) ... 157s Selecting previously unselected package r-cran-r.methodss3. 157s Preparing to unpack .../45-r-cran-r.methodss3_1.8.2-1_all.deb ... 157s Unpacking r-cran-r.methodss3 (1.8.2-1) ... 157s Selecting previously unselected package r-cran-r.oo. 157s Preparing to unpack .../46-r-cran-r.oo_1.27.1-1_all.deb ... 157s Unpacking r-cran-r.oo (1.27.1-1) ... 157s Selecting previously unselected package r-cran-r.utils. 157s Preparing to unpack .../47-r-cran-r.utils_2.13.0-1_all.deb ... 157s Unpacking r-cran-r.utils (2.13.0-1) ... 157s Selecting previously unselected package r-cran-matrixstats. 157s Preparing to unpack .../48-r-cran-matrixstats_1.5.0-1_amd64.deb ... 157s Unpacking r-cran-matrixstats (1.5.0-1) ... 157s Selecting previously unselected package r-bioc-aroma.light. 157s Preparing to unpack .../49-r-bioc-aroma.light_3.36.0-2_all.deb ... 157s Unpacking r-bioc-aroma.light (3.36.0-2) ... 157s Selecting previously unselected package r-bioc-dnacopy. 157s Preparing to unpack .../50-r-bioc-dnacopy_1.80.0-2_amd64.deb ... 157s Unpacking r-bioc-dnacopy (1.80.0-2) ... 157s Selecting previously unselected package r-cran-base64enc. 157s Preparing to unpack .../51-r-cran-base64enc_0.1-3-3build1_amd64.deb ... 157s Unpacking r-cran-base64enc (0.1-3-3build1) ... 157s Selecting previously unselected package r-cran-cli. 157s Preparing to unpack .../52-r-cran-cli_3.6.4-1_amd64.deb ... 157s Unpacking r-cran-cli (3.6.4-1) ... 157s Selecting previously unselected package r-cran-codetools. 157s Preparing to unpack .../53-r-cran-codetools_0.2-20-1build1_all.deb ... 157s Unpacking r-cran-codetools (0.2-20-1build1) ... 157s Selecting previously unselected package r-cran-digest. 157s Preparing to unpack .../54-r-cran-digest_0.6.39-1_amd64.deb ... 157s Unpacking r-cran-digest (0.6.39-1) ... 157s Selecting previously unselected package r-cran-farver. 157s Preparing to unpack .../55-r-cran-farver_2.1.2-1_amd64.deb ... 157s Unpacking r-cran-farver (2.1.2-1) ... 157s Selecting previously unselected package r-cran-globals. 157s Preparing to 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r-cran-r.rsp. 158s Preparing to unpack .../79-r-cran-r.rsp_0.46.0+ds-1_all.deb ... 158s Unpacking r-cran-r.rsp (0.46.0+ds-1) ... 158s Setting up libgraphite2-3:amd64 (1.3.14-11ubuntu1) ... 158s Setting up libpixman-1-0:amd64 (0.46.4-1) ... 158s Setting up libsharpyuv0:amd64 (1.5.0-0.1build1) ... 158s Setting up liblerc4:amd64 (4.0.0+ds-5ubuntu2) ... 158s Setting up libxrender1:amd64 (1:0.9.12-1) ... 158s Setting up libdatrie1:amd64 (0.2.14-1) ... 158s Setting up libxcb-render0:amd64 (1.17.0-2ubuntu1) ... 158s Setting up unzip (6.0-29ubuntu1) ... 158s Setting up x11-common (1:7.7+24ubuntu1) ... 158s Setting up libdeflate0:amd64 (1.23-2build1) ... 158s Setting up libxcb-shm0:amd64 (1.17.0-2ubuntu1) ... 158s Setting up libgomp1:amd64 (16-20260208-1ubuntu1) ... 158s Setting up libjbig0:amd64 (2.1-6.1ubuntu3) ... 158s Setting up zip (3.0-15ubuntu3) ... 158s Setting up libblas3:amd64 (3.12.1-7ubuntu1) ... 158s update-alternatives: using /usr/lib/x86_64-linux-gnu/blas/libblas.so.3 to provide 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using /usr/lib/x86_64-linux-gnu/lapack/liblapack.so.3 to provide /usr/lib/x86_64-linux-gnu/liblapack.so.3 (liblapack.so.3-x86_64-linux-gnu) in auto mode 158s Setting up fontconfig-config (2.17.1-3ubuntu1) ... 158s Setting up libpaper-utils (2.2.5-0.3build1) ... 158s Setting up libthai0:amd64 (0.1.30-1) ... 158s Setting up libtiff6:amd64 (4.7.0-3ubuntu3) ... 158s Setting up tcl (8.6.16build1) ... 158s Setting up libfontconfig1:amd64 (2.17.1-3ubuntu1) ... 158s Setting up libsm6:amd64 (2:1.2.6-1build1) ... 158s Setting up fontconfig (2.17.1-3ubuntu1) ... 160s Regenerating fonts cache... done. 160s Setting up libxft2:amd64 (2.3.6-1build2) ... 160s Setting up libtk8.6:amd64 (8.6.17-1) ... 160s Setting up libpango-1.0-0:amd64 (1.57.0-1) ... 160s Setting up libcairo2:amd64 (1.18.4-3) ... 160s Setting up libxt6t64:amd64 (1:1.2.1-1.3) ... 160s Setting up libpangoft2-1.0-0:amd64 (1.57.0-1) ... 160s Setting up libpangocairo-1.0-0:amd64 (1.57.0-1) ... 160s Setting up r-base-core (4.5.2-1ubuntu2) ... 161s Creating config file /etc/R/Renviron with new version 161s Setting up r-cran-labeling (0.4.3-1) ... 161s Setting up r-cran-farver (2.1.2-1) ... 161s Setting up r-cran-viridislite (0.4.3-1) ... 161s Setting up r-cran-r6 (2.6.1-1) ... 161s Setting up r-cran-codetools (0.2-20-1build1) ... 161s Setting up r-bioc-biocgenerics (0.52.0-2) ... 161s Setting up r-cran-rlang (1.1.5-3) ... 161s Setting up r-cran-matrixstats (1.5.0-1) ... 161s Setting up r-cran-listenv (0.10.0+dfsg-1) ... 161s Setting up r-cran-withr (3.0.2+dfsg-1) ... 161s Setting up r-cran-base64enc (0.1-3-3build1) ... 161s Setting up r-cran-digest (0.6.39-1) ... 161s Setting up r-cran-glue (1.8.0-1) ... 161s Setting up r-cran-cli (3.6.4-1) ... 161s Setting up r-cran-lifecycle (1.0.5+dfsg-1) ... 161s Setting up r-cran-r.methodss3 (1.8.2-1) ... 161s Setting up r-cran-parallelly (1.42.0-1) ... 161s Setting up r-cran-s7 (0.2.0-1) ... 161s Setting up r-cran-rcolorbrewer (1.1-3-1build2) ... 161s Setting up r-cran-isoband (0.2.7-1) ... 161s Setting up r-cran-scales (1.4.0-1) ... 161s Setting up r-cran-gtable (0.3.6+dfsg-1) ... 161s Setting up r-bioc-dnacopy (1.80.0-2) ... 161s Setting up r-cran-globals (0.19.0-1) ... 161s Setting up r-cran-vctrs (0.6.5-1) ... 161s Setting up r-cran-ggplot2 (4.0.2+dfsg-1) ... 161s Setting up r-cran-r.oo (1.27.1-1) ... 161s Setting up r-cran-future (1.34.0+dfsg-1) ... 161s Setting up r-cran-r.utils (2.13.0-1) ... 161s Setting up r-cran-r.devices (2.17.3+ds-1) ... 161s Setting up r-bioc-aroma.light (3.36.0-2) ... 161s Setting up r-cran-r.cache (0.17.0-1) ... 161s Setting up r-cran-pscbs (0.68.0-1) ... 161s Setting up r-cran-r.rsp (0.46.0+ds-1) ... 161s Processing triggers for libc-bin (2.42-2ubuntu4) ... 161s Processing triggers for man-db (2.13.1-1build1) ... 161s Processing triggers for install-info (7.2-5) ... 162s autopkgtest [05:50:45]: test run-unit-test: [----------------------- 162s + pkg=r-cran-pscbs 162s + [ /tmp/autopkgtest.P73rVA/autopkgtest_tmp = ] 162s + cd /tmp/autopkgtest.P73rVA/autopkgtest_tmp 162s + cp -a /usr/share/doc/r-cran-pscbs/tests/PairedPSCBS,boot.R /usr/share/doc/r-cran-pscbs/tests/findLargeGaps.R /usr/share/doc/r-cran-pscbs/tests/randomSeed.R.gz /usr/share/doc/r-cran-pscbs/tests/segmentByCBS,bug67.R /usr/share/doc/r-cran-pscbs/tests/segmentByCBS,calls.R /usr/share/doc/r-cran-pscbs/tests/segmentByCBS,futures.R /usr/share/doc/r-cran-pscbs/tests/segmentByCBS,median.R /usr/share/doc/r-cran-pscbs/tests/segmentByCBS,prune.R /usr/share/doc/r-cran-pscbs/tests/segmentByCBS,report.R /usr/share/doc/r-cran-pscbs/tests/segmentByCBS,shiftTCN.R /usr/share/doc/r-cran-pscbs/tests/segmentByCBS,weights.R.gz /usr/share/doc/r-cran-pscbs/tests/segmentByCBS.R.gz /usr/share/doc/r-cran-pscbs/tests/segmentByNonPairedPSCBS,medianDH.R /usr/share/doc/r-cran-pscbs/tests/segmentByPairedPSCBS,DH.R /usr/share/doc/r-cran-pscbs/tests/segmentByPairedPSCBS,calls.R /usr/share/doc/r-cran-pscbs/tests/segmentByPairedPSCBS,futures.R /usr/share/doc/r-cran-pscbs/tests/segmentByPairedPSCBS,noNormalBAFs.R /usr/share/doc/r-cran-pscbs/tests/segmentByPairedPSCBS,report.R /usr/share/doc/r-cran-pscbs/tests/segmentByPairedPSCBS,seqOfSegmentsByDP.R /usr/share/doc/r-cran-pscbs/tests/segmentByPairedPSCBS.R.gz /tmp/autopkgtest.P73rVA/autopkgtest_tmp 162s + find . -name *.gz -exec gunzip {} ; 162s + export LC_ALL=C 162s + dpkg-architecture -qDEB_HOST_ARCH 162s dpkg-architecture: warning: cannot determine CC system type, falling back to default (native compilation) 162s + hostarch=amd64 162s + [ amd64 = armhf ] 162s + + sed s/\.R$// 162s ls PairedPSCBS,boot.R findLargeGaps.R randomSeed.R segmentByCBS,bug67.R segmentByCBS,calls.R segmentByCBS,futures.R segmentByCBS,median.R segmentByCBS,prune.R segmentByCBS,report.R segmentByCBS,shiftTCN.R segmentByCBS,weights.R segmentByCBS.R segmentByNonPairedPSCBS,medianDH.R segmentByPairedPSCBS,DH.R segmentByPairedPSCBS,calls.R segmentByPairedPSCBS,futures.R segmentByPairedPSCBS,noNormalBAFs.R segmentByPairedPSCBS,report.R segmentByPairedPSCBS,seqOfSegmentsByDP.R segmentByPairedPSCBS.R 162s + echo Begin test PairedPSCBS,boot 162s + exitcode=0Begin test PairedPSCBS,boot 162s 162s + R CMD BATCH PairedPSCBS,boot.R 164s + cat PairedPSCBS,boot.Rout 164s + [ 0 != 164s R version 4.5.2 (2025-10-31) -- "[Not] Part in a Rumble" 164s Copyright (C) 2025 The R Foundation for Statistical Computing 164s Platform: x86_64-pc-linux-gnu 164s 164s R is free software and comes with ABSOLUTELY NO WARRANTY. 164s You are welcome to redistribute it under certain conditions. 164s Type 'license()' or 'licence()' for distribution details. 164s 164s R is a collaborative project with many contributors. 164s Type 'contributors()' for more information and 164s 'citation()' on how to cite R or R packages in publications. 164s 164s Type 'demo()' for some demos, 'help()' for on-line help, or 164s 'help.start()' for an HTML browser interface to help. 164s Type 'q()' to quit R. 164s 164s > ########################################################### 164s > # This tests: 164s > # - Bootstrapping for PairedPSCBS objects 164s > ########################################################### 164s > library("PSCBS") 164s PSCBS v0.68.0 (2025-04-18 19:40:02 UTC) successfully loaded. See ?PSCBS for help. 164s > 164s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 164s > # Load SNP microarray data 164s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 164s > data <- PSCBS::exampleData("paired.chr01") 164s > 164s > 164s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 164s > # Paired PSCBS segmentation 164s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 164s > # Drop single-locus outliers 164s > dataS <- dropSegmentationOutliers(data) 164s > dataS <- dataS[seq(from=1, to=nrow(data), by=5),] 164s > nSegs <- 4L 164s > str(dataS) 164s 'data.frame': 14670 obs. of 6 variables: 164s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 164s $ x : int 1145994 2941694 3710825 4240737 4276892 4464544 4714611 5095111 5034491 5158416 ... 164s $ CT : num 1.63 1.4 1.41 1.17 1.16 ... 164s $ betaT : num 0.7574 0.169 0.2357 0.2604 0.0576 ... 164s $ CN : num 2.36 2.13 2.26 2.01 2.32 ... 164s $ betaN : num 0.8274 0.5072 0.1671 0.1609 0.0421 ... 164s > # Segment known regions 164s > knownSegments <- data.frame( 164s + chromosome = c( 1, 1, 1), 164s + start = c( -Inf, NA, 141510003), 164s + end = c(120992603, NA, +Inf) 164s + ) 164s > fit <- segmentByPairedPSCBS(dataS, knownSegments=knownSegments, avgDH="median", seed=0xBEEF) 164s > print(fit) 164s chromosome tcnId dhId start end tcnNbrOfLoci tcnMean tcnNbrOfSNPs 164s 1 1 1 1 554484 120992603 7586 1.385258 2108 164s 2 NA 2 1 NA NA NA NA 0 164s 3 1 3 1 141510003 185449813 2681 2.068861 777 164s 4 1 4 1 185449813 247137334 4391 2.634110 1311 164s tcnNbrOfHets dhNbrOfLoci dhMean c1Mean c2Mean 164s 1 2108 2108 0.54551245 0.3147912 1.070467 164s 2 0 0 NA NA NA 164s 3 777 777 0.07132277 0.9606521 1.108209 164s 4 1311 1311 0.21663871 1.0317300 1.602380 164s > 164s > 164s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 164s > # Bootstrap 164s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 164s > B <- 1L 164s > seed <- 0xBEEF 164s > probs <- c(0.025, 0.05, 0.95, 0.975) 164s > 164s > sets <- getBootstrapLocusSets(fit, B=B, seed=seed) 164s > 164s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 164s > # Subset by first segment 164s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 164s > ss <- 1L 164s > 164s > fitT <- extractSegment(fit, ss) 164s > dataT <- getLocusData(fitT) 164s > segsT <- getSegments(fitT) 164s > 164s > # Truth 164s > bootT <- bootstrapSegmentsAndChangepoints(fitT, B=B, seed=seed) 164s > bootT1 <- bootT$segments[1L,,,drop=FALSE] 164s > types <- dimnames(bootT1)[[3L]] 164s > dim(bootT1) <- dim(bootT1)[-1L] 164s > colnames(bootT1) <- types 164s > sumsT <- apply(bootT1, MARGIN=2L, FUN=quantile, probs=probs) 164s > print(sumsT) 164s tcn dh c1 c2 164s 2.5% 1.383213 0.5466788 0.3135198 1.069693 164s 5% 1.383213 0.5466788 0.3135198 1.069693 164s 95% 1.383213 0.5466788 0.3135198 1.069693 164s 97.5% 1.383213 0.5466788 0.3135198 1.069693 164s > 164s > fitTB <- bootstrapTCNandDHByRegion(fitT, B=B, seed=seed) 164s > segsTB <- getSegments(fitTB) 164s > segsTB <- unlist(segsTB[,grep("_", colnames(segsTB))]) 164s > dim(segsTB) <- dim(sumsT) 164s > dimnames(segsTB) <- dimnames(sumsT) 164s > print(segsTB) 164s tcn dh c1 c2 164s 2.5% 1.383213 0.5466788 0.3135198 1.069693 164s 5% 1.383213 0.5466788 0.3135198 1.069693 164s 95% 1.383213 0.5466788 0.3135198 1.069693 164s 97.5% 1.383213 0.5466788 0.3135198 1.069693 164s > 164s > # Sanity check 164s > stopifnot(all.equal(segsTB, sumsT)) 164s > 164s > # Calculate summaries using the existing bootstrap samples 164s > fitTBp <- bootstrapTCNandDHByRegion(fitT, .boot=bootT) 164s > # Sanity check 164s > all.equal(fitTBp, fitTB) 164s [1] "Component \"tcn_2.5%\": Mean relative difference: 0.003070405" 164s [2] "Component \"tcn_5%\": Mean relative difference: 0.002241362" 164s [3] "Component \"tcn_95%\": Mean relative difference: 0.005458479" 164s [4] "Component \"tcn_97.5%\": Mean relative difference: 0.006030363" 164s [5] "Component \"dh_2.5%\": Mean relative difference: 0.02683423" 164s [6] "Component \"dh_5%\": Mean relative difference: 0.02409533" 164s [7] "Component \"dh_95%\": Mean relative difference: 0.0150081" 164s [8] "Component \"dh_97.5%\": Mean relative difference: 0.01826461" 164s [9] "Component \"c1_2.5%\": Mean relative difference: 0.02397349" 164s [10] "Component \"c1_5%\": Mean relative difference: 0.01800948" 164s [11] "Component \"c1_95%\": Mean relative difference: 0.0303456" 164s [12] "Component \"c1_97.5%\": Mean relative difference: 0.03420614" 164s [13] "Component \"c2_2.5%\": Mean relative difference: 0.008723378" 164s [14] "Component \"c2_5%\": Mean relative difference: 0.006834962" 164s [15] "Component \"c2_95%\": Mean relative difference: 0.00741949" 164s [16] "Component \"c2_97.5%\": Mean relative difference: 0.008743911" 164s attr(,"what") 164s [1] "getSegments()" 164s > 164s > 164s > # Bootstrap from scratch 164s > setsT <- getBootstrapLocusSets(fitT, B=B, seed=seed) 164s > lociT <- setsT$locusSet[[1L]]$bootstrap$loci 164s > idxs <- lociT$tcn 164s > tcnT <- array(dataT$CT[idxs], dim=dim(idxs)) 164s > tcnT <- apply(tcnT, MARGIN=2L, FUN=mean, na.rm=TRUE) 164s > idxs <- lociT$dh 164s > dhT <- array(dataT$rho[idxs], dim=dim(idxs)) 164s > dhT <- apply(dhT, MARGIN=2L, FUN=median, na.rm=TRUE) 164s > c1T <- (1-dhT) * tcnT / 2 164s > c2T <- tcnT - c1T 164s > bootT2 <- array(c(tcnT, dhT, c1T, c2T), dim=c(1L, 4L)) 164s > colnames(bootT2) <- colnames(bootT1) 164s > print(bootT2) 164s tcn dh c1 c2 164s [1,] 1.383213 0.5466788 0.3135198 1.069693 164s > 164s > # This comparison is only valid if B == 1L 164s > if (B == 1L) { 164s + # Sanity check 164s + stopifnot(all.equal(bootT2, bootT1)) 164s + } 164s > 164s > proc.time() 164s user system elapsed 164s 1.359 0.051 1.406 164s 0 ] 164s + echo Test PairedPSCBS,boot passed 164s + echo 0 164s + echo Begin test findLargeGaps 164s + exitcode=0 164s + R CMD BATCH findLargeGaps.R 164s Test PairedPSCBS,boot passed 164s 0 164s Begin test findLargeGaps 165s + cat findLargeGaps.Rout 165s + [ 0 != 0 ] 165s + echo Test findLargeGaps passed 165s + echo 0 165s + echo Begin test randomSeed 165s + exitcode=0 165s + R CMD BATCH randomSeed.R 165s 165s R version 4.5.2 (2025-10-31) -- "[Not] Part in a Rumble" 165s Copyright (C) 2025 The R Foundation for Statistical Computing 165s Platform: x86_64-pc-linux-gnu 165s 165s R is free software and comes with ABSOLUTELY NO WARRANTY. 165s You are welcome to redistribute it under certain conditions. 165s Type 'license()' or 'licence()' for distribution details. 165s 165s R is a collaborative project with many contributors. 165s Type 'contributors()' for more information and 165s 'citation()' on how to cite R or R packages in publications. 165s 165s Type 'demo()' for some demos, 'help()' for on-line help, or 165s 'help.start()' for an HTML browser interface to help. 165s Type 'q()' to quit R. 165s 165s [Previously saved workspace restored] 165s 165s > library("PSCBS") 165s PSCBS v0.68.0 (2025-04-18 19:40:02 UTC) successfully loaded. See ?PSCBS for help. 165s > 165s > # Simulating copy-number data 165s > set.seed(0xBEEF) 165s > 165s > # Simulate CN data 165s > J <- 1000 165s > mu <- double(J) 165s > mu[200:300] <- mu[200:300] + 1 165s > mu[350:400] <- NA # centromere 165s > mu[650:800] <- mu[650:800] - 1 165s > eps <- rnorm(J, sd=1/2) 165s > y <- mu + eps 165s > x <- seq(from=1, to=100e6, length.out=J) 165s > 165s > data <- data.frame(chromosome=0L, x=x) 165s > 165s > gaps <- findLargeGaps(x=x, minLength=1e6) 165s > print(gaps) 165s [1] start end length 165s <0 rows> (or 0-length row.names) 165s > stopifnot(is.data.frame(gaps)) 165s > stopifnot(nrow(gaps) == 0L) 165s > segs <- gapsToSegments(gaps) 165s > print(segs) 165s chromosome start end 165s 1 0 -Inf Inf 165s > stopifnot(is.data.frame(segs)) 165s > stopifnot(nrow(segs) == 1L) 165s > 165s > 165s > gaps <- findLargeGaps(data, minLength=1e6) 165s > print(gaps) 165s [1] chromosome start end 165s <0 rows> (or 0-length row.names) 165s > stopifnot(is.data.frame(gaps)) 165s > stopifnot(nrow(gaps) == 0L) 165s > segs <- gapsToSegments(gaps) 165s > print(segs) 165s chromosome start end 165s 1 0 -Inf Inf 165s > stopifnot(is.data.frame(segs)) 165s > stopifnot(nrow(segs) == 1L) 165s > 165s > 165s > ## Add missing values 165s > data2 <- data 165s > data$x[30e6 < x & x < 50e6] <- NA 165s > gaps <- findLargeGaps(data, minLength=1e6) 165s > print(gaps) 165s chromosome start end length 165s 1 0 29929932 50050050 20120118 165s > stopifnot(is.data.frame(gaps)) 165s > stopifnot(nrow(gaps) == 1L) 165s > segs <- gapsToSegments(gaps) 165s > print(segs) 165s chromosome start end length 165s 1 0 -Inf 29929931 Inf 165s 2 0 29929932 50050050 20120118 165s 3 0 50050051 Inf Inf 165s > stopifnot(is.data.frame(segs)) 165s > stopifnot(nrow(segs) == 3L) 165s > 165s > 165s > 165s > # BUG FIX: Issue #6 165s > gaps <- findLargeGaps(chromosome=rep(1,10), x=1:10, minLength=2) 165s > print(gaps) 165s [1] chromosome start end 165s <0 rows> (or 0-length row.names) 165s > stopifnot(is.data.frame(gaps)) 165s > stopifnot(nrow(gaps) == 0L) 165s > # BUG FIX: Issue #9 165s > segs <- gapsToSegments(gaps) 165s > print(segs) 165s chromosome start end 165s 1 0 -Inf Inf 165s > stopifnot(is.data.frame(segs)) 165s > stopifnot(nrow(segs) == 1L) 165s > 165s > 165s > # BUG FIX: PSCBS GitHub Issue #8 165s > gaps <- try({ 165s + findLargeGaps(chromosome=rep(1,3), x=as.numeric(1:3), minLength=1) 165s + }) 165s Error in findLargeGaps.default(chromosome = rep(1, 3), x = as.numeric(1:3), : 165s Cannot identify large gaps. Argument 'resolution' (=1) is not strictly smaller than 'minLength' (=1). 165s > stopifnot(inherits(gaps, "try-error")) 165s > 165s > proc.time() 165s user system elapsed 165s 0.251 0.022 0.267 165s Test findLargeGaps passed 165s 0 165s Begin test randomSeed 165s + cat randomSeed.Rout 165s + [ 0 != 0 ] 165s + echo Test randomSeed passed 165s + echo 0 165s + echo Begin test segmentByCBS,bug67 165s + exitcode=0 165s + R CMD BATCH segmentByCBS,bug67.R 165s 165s R version 4.5.2 (2025-10-31) -- "[Not] Part in a Rumble" 165s Copyright (C) 2025 The R Foundation for Statistical Computing 165s Platform: x86_64-pc-linux-gnu 165s 165s R is free software and comes with ABSOLUTELY NO WARRANTY. 165s You are welcome to redistribute it under certain conditions. 165s Type 'license()' or 'licence()' for distribution details. 165s 165s R is a collaborative project with many contributors. 165s Type 'contributors()' for more information and 165s 'citation()' on how to cite R or R packages in publications. 165s 165s Type 'demo()' for some demos, 'help()' for on-line help, or 165s 'help.start()' for an HTML browser interface to help. 165s Type 'q()' to quit R. 165s 165s [Previously saved workspace restored] 165s 165s > library("PSCBS") 165s PSCBS v0.68.0 (2025-04-18 19:40:02 UTC) successfully loaded. See ?PSCBS for help. 165s > 165s > message("*** randomSeed() - setup ...") 165s *** randomSeed() - setup ... 165s > ovars <- ls(envir=globalenv()) 165s > genv <- globalenv() 165s > RNGkind("Mersenne-Twister") 165s > if (exists(".Random.seed", envir=genv, inherits=FALSE)) 165s + rm(list=".Random.seed", envir=genv, inherits=FALSE) 165s > seed0 <- genv$.Random.seed 165s > stopifnot(is.null(seed0)) 165s > okind0 <- RNGkind()[1L] 165s > 165s > sample1 <- function() { sample(0:9, size=1L) } 165s > message("*** randomSeed() - setup ... done") 165s *** randomSeed() - setup ... done 165s > 165s > 165s > message("*** randomSeed('get') ...") 165s *** randomSeed('get') ... 165s > ## Get random seed 165s > seed <- randomSeed("get") 165s > stopifnot(identical(seed, seed0)) 165s > 165s > ## Repeat after new sample 165s > y1 <- sample1() 165s > message(sprintf("Random number: %d", y1)) 165s Random number: 3 165s > seed1 <- randomSeed("get") 165s > stopifnot(!identical(seed1, seed0)) 165s > message("*** randomSeed('get') ... done") 165s *** randomSeed('get') ... done 165s > 165s > 165s > message("*** randomSeed('set', 42L) ...") 165s *** randomSeed('set', 42L) ... 165s > randomSeed("set", seed=42L) 165s > seed2 <- randomSeed("get") 165s > stopifnot(!identical(seed2, seed1)) 165s > 165s > y2 <- sample1() 165s > message(sprintf("Random number: %d (with random seed = 42L)", y2)) 165s Random number: 0 (with random seed = 42L) 165s > 165s > ## Reset to previous state 165s > randomSeed("reset") 165s > seed3 <- randomSeed("get") 165s > stopifnot(identical(seed3, seed1)) 165s > stopifnot(identical(RNGkind()[1L], okind0), 165s + identical(randomSeed("get"), seed1)) 165s > message("*** randomSeed('set', 42L) ... done") 165s *** randomSeed('set', 42L) ... done 165s > 165s > 165s > message("*** randomSeed('set', NULL) ...") 165s *** randomSeed('set', NULL) ... 165s > randomSeed("set", seed=NULL) 165s > seed4 <- randomSeed("get") 165s > stopifnot(is.null(seed4)) 165s > 165s > y3 <- sample1() 165s > message(sprintf("Random number: %d", y3)) 165s Random number: 2 165s > 165s > message("*** randomSeed('set', NULL) ... done") 165s *** randomSeed('set', NULL) ... done 165s > 165s > 165s > message("*** randomSeed('set', 42L) again ...") 165s *** randomSeed('set', 42L) again ... 165s > seed5 <- randomSeed("get") 165s > randomSeed("set", seed=42L) 165s > y4 <- sample1() 165s > message(sprintf("Random number: %d (with random seed = 42L)", y4)) 165s Random number: 0 (with random seed = 42L) 165s > stopifnot(identical(y4, y2)) 165s > 165s > randomSeed("reset") 165s > stopifnot(identical(RNGkind()[1L], okind0), 165s + identical(randomSeed("get"), seed5)) 165s > message("*** randomSeed('set', 42L) again ... done") 165s *** randomSeed('set', 42L) again ... done 165s > 165s > 165s > 165s > ## L'Ecuyer-CMRG: Random number generation for parallel processing 165s > message("*** randomSeed(): L'Ecuyer-CMRG stream ...") 165s *** randomSeed(): L'Ecuyer-CMRG stream ... 165s > 165s > okind <- RNGkind()[1L] 165s > stopifnot(identical(okind, okind0)) 165s > 165s > randomSeed("set", seed=NULL) 165s > oseed <- randomSeed("get") 165s > stopifnot(is.null(oseed)) 165s > 165s > randomSeed("set", seed=42L, kind="L'Ecuyer-CMRG") 165s > oseed2 <- randomSeed("reset") 165s > str(oseed2) 165s NULL 165s > stopifnot(identical(oseed2, oseed)) 165s > stopifnot(identical(RNGkind()[1L], okind), 165s + identical(randomSeed("get"), oseed)) 165s > 165s > randomSeed("set", seed=42L, kind="L'Ecuyer-CMRG") 165s > seed0 <- randomSeed("get") 165s > seeds0 <- lapply(1:10, FUN=function(i) randomSeed("advance")) 165s > oseed2 <- randomSeed("reset") 165s > stopifnot(identical(oseed2, oseed)) 165s > stopifnot(identical(RNGkind()[1L], okind), 165s + identical(randomSeed("get"), oseed)) 165s > 165s > 165s > ## Assert reproducible .Random.seed stream 165s > randomSeed("set", seed=42L, kind="L'Ecuyer-CMRG") 165s > seed1 <- randomSeed("get") 165s > seeds1 <- lapply(1:10, FUN=function(i) randomSeed("advance")) 165s > stopifnot(identical(seed1, seed0)) 165s > stopifnot(identical(seeds1, seeds0)) 165s > 165s > randomSeed("reset") 165s > stopifnot(identical(RNGkind()[1L], okind), 165s + identical(randomSeed("get"), oseed)) 165s > 165s > randomSeed("set", seed=42L, kind="L'Ecuyer-CMRG") 165s > seeds2 <- randomSeed("advance", n=10L) 165s > stopifnot(identical(seeds2, seeds0)) 165s > 165s > randomSeed("reset") 165s > stopifnot(identical(RNGkind()[1L], okind), 165s + identical(randomSeed("get"), oseed)) 165s > 165s > randomSeed("set", seed=seeds2[[1]], kind="L'Ecuyer-CMRG") 165s > randomSeed("reset") 165s > stopifnot(identical(RNGkind()[1L], okind), 165s + identical(randomSeed("get"), oseed)) 165s > 165s > randomSeed("set", seed=42L, kind="L'Ecuyer-CMRG") 165s > y0 <- sapply(1:10, FUN=function(ii) { 165s + randomSeed("advance") 165s + sample1() 165s + }) 165s > print(y0) 165s [1] 6 9 6 9 9 9 0 7 6 5 165s > randomSeed("reset") 165s > 165s > randomSeed("set", seed=42L, kind="L'Ecuyer-CMRG") 165s > y1 <- sapply(1:10, FUN=function(ii) { 165s + randomSeed("advance") 165s + sample1() 165s + }) 165s > print(y1) 165s [1] 6 9 6 9 9 9 0 7 6 5 165s > stopifnot(identical(y1, y0)) 165s > randomSeed("reset") 165s > 165s > stopifnot(identical(RNGkind()[1L], okind)) 165s > 165s > message("*** randomSeed(): L'Ecuyer-CMRG stream ... done") 165s *** randomSeed(): L'Ecuyer-CMRG stream ... done 165s > 165s > 165s > ## Cleanup 165s > message("*** randomSeed() - cleanup ...") 165s *** randomSeed() - cleanup ... 165s > genv <- globalenv() 165s > RNGkind("Mersenne-Twister") 165s > if (exists(".Random.seed", envir=genv, inherits=FALSE)) 165s + rm(list=".Random.seed", envir=genv, inherits=FALSE) 165s > rm(list=ovars, envir=globalenv()) 165s > message("*** randomSeed() - cleanup ... done") 165s *** randomSeed() - cleanup ... done 165s > 165s > proc.time() 165s user system elapsed 165s 0.232 0.021 0.246 165s Test randomSeed passed 165s 0 165s Begin test segmentByCBS,bug67 165s + cat segmentByCBS,bug67.Rout 165s 165s R version 4.5.2 (2025-10-31) -- "[Not] Part in a Rumble" 165s Copyright (C) 2025 The R Foundation for Statistical Computing 165s Platform: x86_64-pc-linux-gnu 165s 165s R is free software and comes with ABSOLUTELY NO WARRANTY. 165s You are welcome to redistribute it under certain conditions. 165s Type 'license()' or 'licence()' for distribution details. 165s 165s R is a collaborative project with many contributors. 165s Type 'contributors()' for more information and 165s 'citation()' on how to cite R or R packages in publications. 165s 165s Type 'demo()' for some demos, 'help()' for on-line help, or 165s 'help.start()' for an HTML browser interface to help. 165s Type 'q()' to quit R. 165s 165s [Previously saved workspace restored] 165s 165s > set.seed(0xBEEF) 165s > 165s > # Number of loci 165s > J <- 1000 165s > 165s > mu <- double(J) 165s > mu[200:300] <- mu[200:300] + 1 165s > mu[350:400] <- NA_real_ # centromere 165s > mu[650:800] <- mu[650:800] - 1 165s > eps <- rnorm(J, sd=1/2) 165s > y <- mu + eps 165s > x <- sort(runif(length(y), max=length(y))) * 1e5 165s > 165s > knownSegments <- data.frame( 165s + chromosome=c( 0, 0), 165s + start =x[c( 1, 401)], 165s + end =x[c(349, J)] 165s + ) 165s > 165s > fit2 <- PSCBS::segmentByCBS(y, x=x, knownSegments=knownSegments) 165s > 165s > proc.time() 165s user system elapsed 165s 0.349 0.029 0.372 165s + [ 0 != 0 ] 165s + echo Test segmentByCBS,bug67 passed 165s + echo 0 165s + echo Begin test segmentByCBS,calls 165s + exitcode=0 165s + R CMD BATCH segmentByCBS,calls.R 165s Test segmentByCBS,bug67 passed 165s 0 165s Begin test segmentByCBS,calls 165s + cat segmentByCBS,calls.Rout 165s 165s R version 4.5.2 (2025-10-31) -- "[Not] Part in a Rumble" 165s Copyright (C) 2025 The R Foundation for Statistical Computing 165s Platform: x86_64-pc-linux-gnu 165s 165s R is free software and comes with ABSOLUTELY NO WARRANTY. 165s You are welcome to redistribute it under certain conditions. 165s Type 'license()' or 'licence()' for distribution details. 165s 165s R is a collaborative project with many contributors. 165s Type 'contributors()' for more information and 165s 'citation()' on how to cite R or R packages in publications. 165s 165s Type 'demo()' for some demos, 'help()' for on-line help, or 165s 'help.start()' for an HTML browser interface to help. 165s Type 'q()' to quit R. 165s 165s [Previously saved workspace restored] 165s 165s > # This test script calls a report generator which requires 165s > # the 'ggplot2' package, which in turn will require packages 165s > # 'colorspace', 'dichromat', 'munsell', 'reshape2' and 'scales'. 165s > 165s > # Only run this test in full testing mode 165s > if (Sys.getenv("_R_CHECK_FULL_") != "") { 165s + library("PSCBS") 165s + stext <- R.utils::stext 165s + 165s + # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 165s + # Load SNP microarray data 165s + # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 165s + data <- PSCBS::exampleData("paired.chr01") 165s + str(data) 165s + 165s + data <- data.frame(chromosome=data$chromosome, x=data$x, y=data$CT) 165s + 165s + 165s + # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 165s + # CBS segmentation 165s + # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 165s + # Drop single-locus outliers 165s + dataS <- dropSegmentationOutliers(data) 165s + 165s + # Speed up example by segmenting fewer loci 165s + dataS <- dataS[seq(from=1, to=nrow(data), by=5),] 165s + 165s + str(dataS) 165s + 165s + gaps <- findLargeGaps(dataS, minLength=2e6) 165s + knownSegments <- gapsToSegments(gaps) 165s + 165s + # CBS segmentation 165s + fit <- segmentByCBS(dataS, knownSegments=knownSegments, 165s + seed=0xBEEF, verbose=-10) 165s + signalType(fit) <- "ratio" 165s + plotTracks(fit) 165s + 165s + 165s + # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 165s + # Call using the UCSF MAD caller (not recommended) 165s + # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 165s + fitC <- callGainsAndLosses(fit) 165s + plotTracks(fitC) 165s + pars <- fitC$params$callGainsAndLosses 165s + stext(side=3, pos=1/2, line=-1, substitute(sigma==x, list(x=sprintf("%.2f", pars$sigmaMAD)))) 165s + mu <- pars$muR 165s + tau <- unlist(pars[c("tauLoss", "tauGain")], use.names=FALSE) 165s + abline(h=mu, lty=2, lwd=2) 165s + abline(h=tau, lwd=2) 165s + mtext(side=4, at=tau[1], expression(Delta[LOSS]), adj=-0.2, cex=0.7, las=2, xpd=TRUE) 165s + mtext(side=4, at=tau[2], expression(Delta[GAIN]), adj=-0.2, cex=0.7, las=2, xpd=TRUE) 165s + title(main="CN caller: \"ucsf-mad\"") 165s + 165s + 165s + # Caller to be implemented 165s + deltaCN <- estimateDeltaCN(fit) 165s + tau <- mu + 1/2*c(-1,+1)*deltaCN 165s + abline(h=tau, lty=2, lwd=1, col="red") 165s + 165s + 165s + 165s + } # if (Sys.getenv("_R_CHECK_FULL_")) 165s > 165s > proc.time() 165s user system elapsed 165s 0.079 0.017 0.088 165s Test segmentByCBS,calls passed 165s 0 165s Begin test segmentByCBS,futures 165s + [ 0 != 0 ] 165s + echo Test segmentByCBS,calls passed 165s + echo 0 165s + echo Begin test segmentByCBS,futures 165s + exitcode=0 165s + R CMD BATCH segmentByCBS,futures.R 169s + cat segmentByCBS,futures.Rout 169s + [ 0 != 0 ] 169s + echo Test segmentByCBS,futures passed 169s + echo 0 169s + echo Begin test segmentByCBS,median 169s + exitcode=0 169s + R CMD BATCH segmentByCBS,median.R 169s 169s R version 4.5.2 (2025-10-31) -- "[Not] Part in a Rumble" 169s Copyright (C) 2025 The R Foundation for Statistical Computing 169s Platform: x86_64-pc-linux-gnu 169s 169s R is free software and comes with ABSOLUTELY NO WARRANTY. 169s You are welcome to redistribute it under certain conditions. 169s Type 'license()' or 'licence()' for distribution details. 169s 169s R is a collaborative project with many contributors. 169s Type 'contributors()' for more information and 169s 'citation()' on how to cite R or R packages in publications. 169s 169s Type 'demo()' for some demos, 'help()' for on-line help, or 169s 'help.start()' for an HTML browser interface to help. 169s Type 'q()' to quit R. 169s 169s [Previously saved workspace restored] 169s 169s > library("PSCBS") 169s PSCBS v0.68.0 (2025-04-18 19:40:02 UTC) successfully loaded. See ?PSCBS for help. 169s > 169s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 169s > # Simulating copy-number data 169s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 169s > set.seed(0xBEEF) 169s > 169s > # Number of loci 169s > J <- 1000 169s > 169s > mu <- double(J) 169s > mu[200:300] <- mu[200:300] + 1 169s > mu[350:400] <- NA # centromere 169s > mu[650:800] <- mu[650:800] - 1 169s > eps <- rnorm(J, sd=1/2) 169s > y <- mu + eps 169s > x <- sort(runif(length(y), max=length(y))) * 1e5 169s > w <- runif(J) 169s > w[650:800] <- 0.001 169s > 169s > ## Create multiple chromosomes 169s > data <- knownSegments <- list() 169s > for (cc in 1:3) { 169s + data[[cc]] <- data.frame(chromosome=cc, y=y, x=x) 169s + knownSegments[[cc]] <- data.frame( 169s + chromosome=c( cc, cc, cc), 169s + start =x[c( 1, 350, 401)], 169s + end =x[c(349, 400, J)] 169s + ) 169s + } 169s > data <- Reduce(rbind, data) 169s > str(data) 169s 'data.frame': 3000 obs. of 3 variables: 169s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 169s $ y : num 0.295 0.115 -0.194 -0.392 -0.518 ... 169s $ x : num 55168 593204 605649 630624 746896 ... 169s > knownSegments <- Reduce(rbind, knownSegments) 169s > str(knownSegments) 169s 'data.frame': 9 obs. of 3 variables: 169s $ chromosome: int 1 1 1 2 2 2 3 3 3 169s $ start : num 55168 34194740 41080533 55168 34194740 ... 169s $ end : num 34142178 41044125 99910827 34142178 41044125 ... 169s > 169s > message("*** segmentByCBS() via futures ...") 169s *** segmentByCBS() via futures ... 169s > 169s > 169s > message("*** segmentByCBS() via futures with 'future' attached ...") 169s *** segmentByCBS() via futures with 'future' attached ... 169s > library("future") 169s > oplan <- plan() 169s > 169s > strategies <- c("sequential", "multisession") 169s > 169s > ## Test 'future.batchtools' futures? 169s > pkg <- "future.batchtools" 169s > if (require(pkg, character.only=TRUE)) { 169s + strategies <- c(strategies, "batchtools_local") 169s + } 169s Loading required package: future.batchtools 169s Warning message: 169s In library(package, lib.loc = lib.loc, character.only = TRUE, logical.return = TRUE, : 169s there is no package called 'future.batchtools' 169s > 169s > message("Future strategies to test: ", paste(sQuote(strategies), collapse=", ")) 169s Future strategies to test: 'sequential', 'multisession' 169s > 169s > fits <- list() 169s > for (strategy in strategies) { 169s + message(sprintf("- segmentByCBS() using '%s' futures ...", strategy)) 169s + plan(strategy) 169s + fit <- segmentByCBS(data, seed=0xBEEF, verbose=TRUE) 169s + fits[[strategy]] <- fit 169s + stopifnot(all.equal(fit, fits[[1]])) 169s + } 169s - segmentByCBS() using 'sequential' futures ... 169s Segmenting by CBS... 169s Segmenting multiple chromosomes... 169s Number of chromosomes: 3 169s Random seed temporarily set (seed=c(48879), kind="L'Ecuyer-CMRG") 169s Produced 3 seeds from this stream for future usage 169s Chromosome #1 ('Chr01') of 3... 169s Segmenting by CBS... 169s Chromosome: 1 169s Random seed temporarily set (seed=c(10407, 1066287653, -51199871, 161854402, -1995183193, 1503453565, -747102133), kind="L'Ecuyer-CMRG") 169s Segmenting by CBS...done 169s Chromosome #1 ('Chr01') of 3...done 169s Chromosome #2 ('Chr02') of 3... 169s Segmenting by CBS... 169s Chromosome: 2 169s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 169s Segmenting by CBS...done 169s Chromosome #2 ('Chr02') of 3...done 169s Chromosome #3 ('Chr03') of 3... 169s Segmenting by CBS... 169s Chromosome: 3 169s Random seed temporarily set (seed=c(10407, -821273412, -52578226, 1415511586, 721384351, -665928286, 1316562960), kind="L'Ecuyer-CMRG") 169s Segmenting by CBS...done 169s Chromosome #3 ('Chr03') of 3...done 169s Segmenting multiple chromosomes...done 169s Segmenting by CBS...done 169s list() 169s - segmentByCBS() using 'multisession' futures ... 169s Segmenting by CBS... 169s Segmenting multiple chromosomes... 169s Number of chromosomes: 3 169s Random seed temporarily set (seed=c(48879), kind="L'Ecuyer-CMRG") 169s Produced 3 seeds from this stream for future usage 169s Chromosome #1 ('Chr01') of 3... 169s Chromosome #1 ('Chr01') of 3...done 169s Chromosome #2 ('Chr02') of 3... 169s Random seed temporarily set (seed=c(10407, 1066287653, -51199871, 161854402, -1995183193, 1503453565, -747102133), kind="L'Ecuyer-CMRG") 169s Segmenting by CBS...done 169s Chromosome #2 ('Chr02') of 3...done 169s Chromosome #3 ('Chr03') of 3... 169s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 169s Segmenting by CBS...done 169s Chromosome #3 ('Chr03') of 3...done 169s Segmenting by CBS... 169s Chromosome: 3 169s Random seed temporarily set (seed=c(10407, -821273412, -52578226, 1415511586, 721384351, -665928286, 1316562960), kind="L'Ecuyer-CMRG") 169s Segmenting by CBS...done 169s Segmenting multiple chromosomes...done 169s Segmenting by CBS...done 169s list() 169s > 169s > 169s > message("*** segmentByCBS() via futures with known segments ...") 169s *** segmentByCBS() via futures with known segments ... 169s > fits <- list() 169s > dataT <- subset(data, chromosome == 1) 169s > for (strategy in strategies) { 169s + message(sprintf("- segmentByCBS() w/ known segments using '%s' futures ...", strategy)) 169s + plan(strategy) 169s + fit <- segmentByCBS(dataT, knownSegments=knownSegments, seed=0xBEEF, verbose=TRUE) 169s + fits[[strategy]] <- fit 169s + stopifnot(all.equal(fit, fits[[1]])) 169s + } 169s - segmentByCBS() w/ known segments using 'sequential' futures ... 169s Segmenting by CBS... 169s Chromosome: 1 169s Random seed temporarily set (seed=c(48879), kind="L'Ecuyer-CMRG") 169s Produced 3 seeds from this stream for future usage 169s Segmenting by CBS...done 169s list() 169s - segmentByCBS() w/ known segments using 'multisession' futures ... 169s Segmenting by CBS... 169s Chromosome: 1 169s Random seed temporarily set (seed=c(48879), kind="L'Ecuyer-CMRG") 169s Produced 3 seeds from this stream for future usage 169s Segmenting by CBS...done 169s list() 169s > 169s > message("*** segmentByCBS() via futures ... DONE") 169s *** segmentByCBS() via futures ... DONE 169s > 169s > 169s > ## Cleanup 169s > plan(oplan) 169s > rm(list=c("fits", "dataT", "data", "fit")) 169s > 169s > 169s > proc.time() 169s user system elapsed 169s 1.085 0.092 3.233 169s Test segmentByCBS,futures passed 169s 0 169s Begin test segmentByCBS,median 170s + cat segmentByCBS,median.Rout 170s 170s R version 4.5.2 (2025-10-31) -- "[Not] Part in a Rumble" 170s Copyright (C) 2025 The R Foundation for Statistical Computing 170s Platform: x86_64-pc-linux-gnu 170s 170s R is free software and comes with ABSOLUTELY NO WARRANTY. 170s You are welcome to redistribute it under certain conditions. 170s Type 'license()' or 'licence()' for distribution details. 170s 170s R is a collaborative project with many contributors. 170s Type 'contributors()' for more information and 170s 'citation()' on how to cite R or R packages in publications. 170s 170s Type 'demo()' for some demos, 'help()' for on-line help, or 170s 'help.start()' for an HTML browser interface to help. 170s Type 'q()' to quit R. 170s 170s [Previously saved workspace restored] 170s 170s > library("PSCBS") 170s PSCBS v0.68.0 (2025-04-18 19:40:02 UTC) successfully loaded. See ?PSCBS for help. 170s > 170s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 170s > # Simulating copy-number data 170s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 170s > set.seed(0xBEEF) 170s > 170s > # Number of loci 170s > J <- 1000 170s > 170s > x <- sort(runif(J, max=J)) * 1e5 170s > 170s > mu <- double(J) 170s > mu[200:300] <- mu[200:300] + 1 170s > mu[350:400] <- NA # centromere 170s > mu[650:800] <- mu[650:800] - 1 170s > eps <- rnorm(J, sd=1/2) 170s > y <- mu + eps 170s > 170s > outliers <- seq(from=1L, to=J, length.out=0.2*J) 170s > y[outliers] <- y[outliers] + 1.5 170s > 170s > w <- rep(1.0, times=J) 170s > w[outliers] <- 0.01 170s > 170s > data <- data.frame(chromosome=1L, x=x, y=y) 170s > dataW <- cbind(data, w=w) 170s > 170s > 170s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 170s > # Single-chromosome segmentation 170s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 170s > par(mar=c(2,3,0.2,1)+0.1) 170s > # Segment without weights 170s > fit <- segmentByCBS(data) 170s > sampleName(fit) <- "CBS_Example" 170s > print(fit) 170s sampleName chromosome start end nbrOfLoci mean 170s 1 CBS_Example 1 6.066868e+02 19076007 199 0.2622 170s 2 CBS_Example 1 1.907601e+07 29630949 99 1.4289 170s 3 CBS_Example 1 2.963095e+07 63224332 299 0.2854 170s 4 CBS_Example 1 6.322433e+07 78801707 153 -0.7408 170s 5 CBS_Example 1 7.880171e+07 99917418 199 0.3541 170s > plotTracks(fit) 170s Warning message: 170s In plotTracks.CBS(fit) : 170s Setting default 'Clim' assuming the signal type is 'ratio' because signalType(fit) is unknown ('NA'). Use signalType(fit) <- 'ratio' to avoid this warning. 170s > ## Highlight outliers (they pull up the mean levels) 170s > points(x[outliers]/1e6, y[outliers], col="purple") 170s > 170s > # Segment without weights but with median 170s > fitM <- segmentByCBS(data, avg="median") 170s > sampleName(fitM) <- "CBS_Example (median)" 170s > print(fitM) 170s sampleName chromosome start end nbrOfLoci mean 170s 1 CBS_Example (median) 1 6.066868e+02 19076007 199 0.1005418 170s 2 CBS_Example (median) 1 1.907601e+07 29630949 99 1.2720955 170s 3 CBS_Example (median) 1 2.963095e+07 63224332 299 0.1337148 170s 4 CBS_Example (median) 1 6.322433e+07 78801707 153 -0.8655254 170s 5 CBS_Example (median) 1 7.880171e+07 99917418 199 0.1718179 170s > drawLevels(fitM, col="magenta", lty=3) 170s NULL 170s > 170s > # Segment with weights 170s > fitW <- segmentByCBS(dataW, avg="median") 170s > sampleName(fitW) <- "CBS_Example (weighted)" 170s > print(fitW) 170s sampleName chromosome start end nbrOfLoci mean 170s 1 CBS_Example (weighted) 1 6.066868e+02 19076007 199 -0.08745973 170s 2 CBS_Example (weighted) 1 1.907601e+07 30126128 101 1.12968951 170s 3 CBS_Example (weighted) 1 3.012613e+07 63224332 297 -0.06074638 170s 4 CBS_Example (weighted) 1 6.322433e+07 78801707 153 -1.06373835 170s 5 CBS_Example (weighted) 1 7.880171e+07 99917418 199 0.04204744 170s > drawLevels(fitW, col="red") 170s NULL 170s > 170s > # Segment with weights and median 170s > fitWM <- segmentByCBS(dataW, avg="median") 170s > sampleName(fitWM) <- "CBS_Example (weighted median)" 170s > print(fitWM) 170s sampleName chromosome start end nbrOfLoci 170s 1 CBS_Example (weighted median) 1 6.066868e+02 19076007 199 170s 2 CBS_Example (weighted median) 1 1.907601e+07 30126128 101 170s 3 CBS_Example (weighted median) 1 3.012613e+07 63224332 297 170s 4 CBS_Example (weighted median) 1 6.322433e+07 78801707 153 170s 5 CBS_Example (weighted median) 1 7.880171e+07 99917418 199 170s mean 170s 1 -0.08745973 170s 2 1.12968951 170s 3 -0.06074638 170s 4 -1.06373835 170s 5 0.04204744 170s > drawLevels(fitWM, col="orange", lty=3) 170s NULL 170s > 170s > legend("topright", bg="white", legend=c("outliers", "non-weighted CBS (mean)", "non-weighted CBS (median)", "weighted CBS (mean)", "weighted CBS (median)"), col=c("purple", "purple", "magenta", "red", "orange"), lwd=c(NA,3,3,3,3), lty=c(NA,1,3,1,3), pch=c(1,NA,NA,NA,NA)) 170s > 170s > ## Assert that weighted segment means are less biased 170s > dmean <- getSegments(fit)$mean - getSegments(fitW)$mean 170s > cat("Segment mean differences:\n") 170s Segment mean differences: 170s > print(dmean) 170s [1] 0.3496597 0.2992105 0.3461464 0.3229384 0.3120526 170s > stopifnot(all(dmean > 0, na.rm=TRUE)) 170s > 170s > dmean <- getSegments(fitM)$mean - getSegments(fitWM)$mean 170s > cat("Segment median differences:\n") 170s Segment median differences: 170s > print(dmean) 170s [1] 0.1880015 0.1424060 0.1944611 0.1982130 0.1297704 170s > stopifnot(all(dmean > 0, na.rm=TRUE)) 170s > 170s > 170s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 170s > # Multi-chromosome segmentation 170s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 170s > data2 <- data 170s > data2$chromosome <- 2L 170s > data <- rbind(data, data2) 170s > dataW <- cbind(data, w=w) 170s > 170s > par(mar=c(2,3,0.2,1)+0.1) 170s > # Segment without weights 170s > fit <- segmentByCBS(data) 170s > sampleName(fit) <- "CBS_Example" 170s > print(fit) 170s sampleName chromosome start end nbrOfLoci mean 170s 1 CBS_Example 1 6.066868e+02 19076007 199 0.2622 170s 2 CBS_Example 1 1.907601e+07 29630949 99 1.4289 170s 3 CBS_Example 1 2.963095e+07 63224332 299 0.2854 170s 4 CBS_Example 1 6.322433e+07 78801707 153 -0.7408 170s 5 CBS_Example 1 7.880171e+07 99917418 199 0.3541 170s 6 NA NA NA NA NA 170s 7 CBS_Example 2 6.066868e+02 19076007 199 0.2622 170s 8 CBS_Example 2 1.907601e+07 29630949 99 1.4289 170s 9 CBS_Example 2 2.963095e+07 63224332 299 0.2854 170s 10 CBS_Example 2 6.322433e+07 78801707 153 -0.7408 170s 11 CBS_Example 2 7.880171e+07 99917418 199 0.3541 170s > plotTracks(fit, Clim=c(-3,3)) 170s > 170s > # Segment without weights but with median 170s > fitM <- segmentByCBS(data, avg="median") 170s > sampleName(fitM) <- "CBS_Example (median)" 170s > print(fitM) 170s sampleName chromosome start end nbrOfLoci mean 170s 1 CBS_Example (median) 1 6.066868e+02 19076007 199 0.1005418 170s 2 CBS_Example (median) 1 1.907601e+07 29630949 99 1.2720955 170s 3 CBS_Example (median) 1 2.963095e+07 63224332 299 0.1337148 170s 4 CBS_Example (median) 1 6.322433e+07 78801707 153 -0.8655254 170s 5 CBS_Example (median) 1 7.880171e+07 99917418 199 0.1718179 170s 6 NA NA NA NA NA 170s 7 CBS_Example (median) 2 6.066868e+02 19076007 199 0.1005418 170s 8 CBS_Example (median) 2 1.907601e+07 29630949 99 1.2720955 170s 9 CBS_Example (median) 2 2.963095e+07 63224332 299 0.1337148 170s 10 CBS_Example (median) 2 6.322433e+07 78801707 153 -0.8655254 170s 11 CBS_Example (median) 2 7.880171e+07 99917418 199 0.1718179 170s > drawLevels(fitM, col="magenta", lty=3) 170s NULL 170s > 170s > # Segment with weights 170s > fitW <- segmentByCBS(dataW, avg="median") 170s > sampleName(fitW) <- "CBS_Example (weighted)" 170s > print(fitW) 170s sampleName chromosome start end nbrOfLoci 170s 1 CBS_Example (weighted) 1 6.066868e+02 19076007 199 170s 2 CBS_Example (weighted) 1 1.907601e+07 30126128 101 170s 3 CBS_Example (weighted) 1 3.012613e+07 63224332 297 170s 4 CBS_Example (weighted) 1 6.322433e+07 78801707 153 170s 5 CBS_Example (weighted) 1 7.880171e+07 99917418 199 170s 6 NA NA NA NA 170s 7 CBS_Example (weighted) 2 6.066868e+02 19076007 199 170s 8 CBS_Example (weighted) 2 1.907601e+07 30126128 101 170s 9 CBS_Example (weighted) 2 3.012613e+07 63224332 297 170s 10 CBS_Example (weighted) 2 6.322433e+07 78801707 153 170s 11 CBS_Example (weighted) 2 7.880171e+07 99917418 199 170s mean 170s 1 -0.08745973 170s 2 1.12968951 170s 3 -0.06074638 170s 4 -1.06373835 170s 5 0.04204744 170s 6 NA 170s 7 -0.08745973 170s 8 1.12968951 170s 9 -0.06074638 170s 10 -1.06373835 170s 11 0.04204744 170s > drawLevels(fitW, col="red") 170s NULL 170s > 170s > # Segment with weights and median 170s > fitWM <- segmentByCBS(dataW, avg="median") 170s > sampleName(fitWM) <- "CBS_Example (weighted median)" 170s > print(fitWM) 170s sampleName chromosome start end nbrOfLoci 170s 1 CBS_Example (weighted median) 1 6.066868e+02 19076007 199 170s 2 CBS_Example (weighted median) 1 1.907601e+07 30126128 101 170s 3 CBS_Example (weighted median) 1 3.012613e+07 63224332 297 170s 4 CBS_Example (weighted median) 1 6.322433e+07 78801707 153 170s 5 CBS_Example (weighted median) 1 7.880171e+07 99917418 199 170s 6 NA NA NA NA 170s 7 CBS_Example (weighted median) 2 6.066868e+02 19076007 199 170s 8 CBS_Example (weighted median) 2 1.907601e+07 30126128 101 170s 9 CBS_Example (weighted median) 2 3.012613e+07 63224332 297 170s 10 CBS_Example (weighted median) 2 6.322433e+07 78801707 153 170s 11 CBS_Example (weighted median) 2 7.880171e+07 99917418 199 170s mean 170s 1 -0.08745973 170s 2 1.12968951 170s 3 -0.06074638 170s 4 -1.06373835 170s 5 0.04204744 170s 6 NA 170s 7 -0.08745973 170s 8 1.12968951 170s 9 -0.06074638 170s 10 -1.06373835 170s 11 0.04204744 170s > drawLevels(fitWM, col="orange", lty=3) 170s NULL 170s > 170s > legend("topright", bg="white", legend=c("outliers", "non-weighted CBS (mean)", "non-weighted CBS (median)", "weighted CBS (mean)", "weighted CBS (median)"), col=c("purple", "purple", "magenta", "red", "orange"), lwd=c(NA,3,3,3,3), lty=c(NA,1,3,1,3), pch=c(1,NA,NA,NA,NA)) 170s > 170s > ## Assert that weighted segment means are less biased 170s > dmean <- getSegments(fit)$mean - getSegments(fitW)$mean 170s > cat("Segment mean differences:\n") 170s Segment mean differences: 170s > print(dmean) 170s [1] 0.3496597 0.2992105 0.3461464 0.3229384 0.3120526 NA 0.3496597 170s [8] 0.2992105 0.3461464 0.3229384 0.3120526 170s > stopifnot(all(dmean > 0, na.rm=TRUE)) 170s > 170s > dmean <- getSegments(fitM)$mean - getSegments(fitWM)$mean 170s > cat("Segment median differences:\n") 170s Segment median differences: 170s > print(dmean) 170s [1] 0.1880015 0.1424060 0.1944611 0.1982130 0.1297704 NA 0.1880015 170s [8] 0.1424060 0.1944611 0.1982130 0.1297704 170s > stopifnot(all(dmean > 0, na.rm=TRUE)) 170s > 170s > proc.time() 170s user system elapsed 170s 0.752 0.034 0.781 170s Test segmentByCBS,median passed 170s 0 170s Begin test segmentByCBS,prune 170s + [ 0 != 0 ] 170s + echo Test segmentByCBS,median passed 170s + echo 0 170s + echo Begin test segmentByCBS,prune 170s + exitcode=0 170s + R CMD BATCH segmentByCBS,prune.R 170s + cat segmentByCBS,prune.Rout 170s 170s R version 4.5.2 (2025-10-31) -- "[Not] Part in a Rumble" 170s Copyright (C) 2025 The R Foundation for Statistical Computing 170s Platform: x86_64-pc-linux-gnu 170s 170s R is free software and comes with ABSOLUTELY NO WARRANTY. 170s You are welcome to redistribute it under certain conditions. 170s Type 'license()' or 'licence()' for distribution details. 170s 170s R is a collaborative project with many contributors. 170s Type 'contributors()' for more information and 170s 'citation()' on how to cite R or R packages in publications. 170s 170s Type 'demo()' for some demos, 'help()' for on-line help, or 170s 'help.start()' for an HTML browser interface to help. 170s Type 'q()' to quit R. 170s 170s [Previously saved workspace restored] 170s 170s > library("PSCBS") 170s PSCBS v0.68.0 (2025-04-18 19:40:02 UTC) successfully loaded. See ?PSCBS for help. 170s > 170s > ## Compare segments 170s > assertMatchingSegments <- function(fitM, fit) { 170s + chrs <- getChromosomes(fitM) 170s + segsM <- lapply(chrs, FUN=function(chr) { 170s + getSegments(extractChromosome(fitM, chr)) 170s + }) 170s + segs <- lapply(fit[chrs], FUN=getSegments) 170s + stopifnot(all.equal(segsM, segs, check.attributes=FALSE)) 170s + } 170s > 170s > ## Simulate data 170s > set.seed(0xBEEF) 170s > J <- 1000 170s > mu <- double(J) 170s > mu[200:300] <- mu[200:300] + 1 170s > mu[350:400] <- NA 170s > mu[650:800] <- mu[650:800] - 1 170s > eps <- rnorm(J, sd=1/2) 170s > y <- mu + eps 170s > x <- sort(runif(length(y), max=length(y))) * 1e5 170s > 170s > data <- list() 170s > for (chr in 1:2) { 170s + data[[chr]] <- data.frame(chromosome=chr, x=x, y=y) 170s + } 170s > data$M <- Reduce(rbind, data) 170s > 170s > ## Segment 170s > message("*** segmentByCBS()") 170s *** segmentByCBS() 170s > fit <- lapply(data, FUN=segmentByCBS) 170s > print(fit) 170s [[1]] 170s sampleName chromosome start end nbrOfLoci mean 170s 1 1 65285.65 19648927 200 0.0109 170s 2 1 19648927.46 28239656 95 0.9529 170s 3 1 28239655.99 65697742 302 -0.0126 170s 4 1 65697742.20 79729368 153 -0.9534 170s 5 1 79729368.34 99819310 199 -0.0497 170s 170s [[2]] 170s sampleName chromosome start end nbrOfLoci mean 170s 1 2 65285.65 19648927 200 0.0109 170s 2 2 19648927.46 28239656 95 0.9529 170s 3 2 28239655.99 65697742 302 -0.0126 170s 4 2 65697742.20 79729368 153 -0.9534 170s 5 2 79729368.34 99819310 199 -0.0497 170s 170s $M 170s sampleName chromosome start end nbrOfLoci mean 170s 1 1 65285.65 19648927 200 0.0109 170s 2 1 19648927.46 28239656 95 0.9529 170s 3 1 28239655.99 65697742 302 -0.0126 170s 4 1 65697742.20 79729368 153 -0.9534 170s 5 1 79729368.34 99819310 199 -0.0497 170s 6 NA NA NA NA NA 170s 7 2 65285.65 19648927 200 0.0109 170s 8 2 19648927.46 28239656 95 0.9529 170s 9 2 28239655.99 65697742 302 -0.0126 170s 10 2 65697742.20 79729368 153 -0.9534 170s 11 2 79729368.34 99819310 199 -0.0497 170s 170s > assertMatchingSegments(fit$M, fit) 170s > 170s > ## Join segments 170s > message("*** joinSegments()") 170s *** joinSegments() 170s > fitj <- lapply(fit, FUN=joinSegments) 170s > print(fitj) 170s [[1]] 170s sampleName chromosome start end nbrOfLoci mean 170s 1 1 65285.65 19648927 200 0.0109 170s 2 1 19648927.46 28239656 95 0.9529 170s 3 1 28239655.99 65697742 302 -0.0126 170s 4 1 65697742.20 79729368 153 -0.9534 170s 5 1 79729368.34 99819310 199 -0.0497 170s 170s [[2]] 170s sampleName chromosome start end nbrOfLoci mean 170s 1 2 65285.65 19648927 200 0.0109 170s 2 2 19648927.46 28239656 95 0.9529 170s 3 2 28239655.99 65697742 302 -0.0126 170s 4 2 65697742.20 79729368 153 -0.9534 170s 5 2 79729368.34 99819310 199 -0.0497 170s 170s $M 170s sampleName chromosome start end nbrOfLoci mean 170s 1 1 65285.65 19648927 200 0.0109 170s 2 1 19648927.46 28239656 95 0.9529 170s 3 1 28239655.99 65697742 302 -0.0126 170s 4 1 65697742.20 79729368 153 -0.9534 170s 5 1 79729368.34 99819310 199 -0.0497 170s 6 NA NA NA NA NA 170s 7 2 65285.65 19648927 200 0.0109 170s 8 2 19648927.46 28239656 95 0.9529 170s 9 2 28239655.99 65697742 302 -0.0126 170s 10 2 65697742.20 79729368 153 -0.9534 170s 11 2 79729368.34 99819310 199 -0.0497 170s 170s > assertMatchingSegments(fitj$M, fitj) 170s > 170s > ## Reset segments 170s > message("*** resetSegments()") 170s *** resetSegments() 170s > fitj <- lapply(fit, FUN=resetSegments) 170s > print(fitj) 170s [[1]] 170s sampleName chromosome start end nbrOfLoci mean 170s 1 1 65285.65 19648927 200 0.0109 170s 2 1 19648927.46 28239656 95 0.9529 170s 3 1 28239655.99 65697742 302 -0.0126 170s 4 1 65697742.20 79729368 153 -0.9534 170s 5 1 79729368.34 99819310 199 -0.0497 170s 170s [[2]] 170s sampleName chromosome start end nbrOfLoci mean 170s 1 2 65285.65 19648927 200 0.0109 170s 2 2 19648927.46 28239656 95 0.9529 170s 3 2 28239655.99 65697742 302 -0.0126 170s 4 2 65697742.20 79729368 153 -0.9534 170s 5 2 79729368.34 99819310 199 -0.0497 170s 170s $M 170s sampleName chromosome start end nbrOfLoci mean 170s 1 1 65285.65 19648927 200 0.0109 170s 2 1 19648927.46 28239656 95 0.9529 170s 3 1 28239655.99 65697742 302 -0.0126 170s 4 1 65697742.20 79729368 153 -0.9534 170s 5 1 79729368.34 99819310 199 -0.0497 170s 6 NA NA NA NA NA 170s 7 2 65285.65 19648927 200 0.0109 170s 8 2 19648927.46 28239656 95 0.9529 170s 9 2 28239655.99 65697742 302 -0.0126 170s 10 2 65697742.20 79729368 153 -0.9534 170s 11 2 79729368.34 99819310 199 -0.0497 170s 170s > assertMatchingSegments(fitj$M, fitj) 170s > 170s > ## Prune by SD undo 170s > message("*** pruneBySdUndo()") 170s *** pruneBySdUndo() 170s > fitp <- lapply(fit, FUN=pruneBySdUndo) 170s > print(fitp) 170s [[1]] 170s sampleName chromosome start end nbrOfLoci mean 170s 1 1 65285.65 99819310 949 -0.07045097 170s 170s [[2]] 170s sampleName chromosome start end nbrOfLoci mean 170s 1 2 65285.65 99819310 949 -0.07045097 170s 170s $M 170s sampleName chromosome start end nbrOfLoci mean 170s 1 1 65285.65 99819310 949 -0.07045097 170s 2 NA NA NA NA NA 170s 3 2 65285.65 99819310 949 -0.07045097 170s 170s > assertMatchingSegments(fitp$M, fitp) 170s > 170s > ## Prune by hierarchical clustering 170s > message("*** pruneByHClust()") 170s *** pruneByHClust() 170s > fitp <- lapply(fit, FUN=pruneByHClust, k=1L) 170s > print(fitp) 170s [[1]] 170s sampleName chromosome start end nbrOfLoci mean 170s 1 1 65285.65 99819310 949 -0.07045097 170s 170s [[2]] 170s sampleName chromosome start end nbrOfLoci mean 170s 1 2 65285.65 99819310 949 -0.07045097 170s 170s $M 170s sampleName chromosome start end nbrOfLoci mean 170s 1 1 65285.65 99819310 949 -0.07045097 170s 6 NA NA NA NA NA 170s 7 2 65285.65 99819310 949 -0.07045097 170s 170s > assertMatchingSegments(fitp$M, fitp) 170s > 170s > proc.time() 170s user system elapsed 170s 0.546 0.019 0.560 170s Test segmentByCBS,prune passed 170s 0 170s Begin test segmentByCBS,report 170s + [ 0 != 0 ] 170s + echo Test segmentByCBS,prune passed 170s + echo 0 170s + echo Begin test segmentByCBS,report 170s + exitcode=0 170s + R CMD BATCH segmentByCBS,report.R 170s + cat segmentByCBS,report.Rout 170s 170s R version 4.5.2 (2025-10-31) -- "[Not] Part in a Rumble" 170s Copyright (C) 2025 The R Foundation for Statistical Computing 170s Platform: x86_64-pc-linux-gnu 170s 170s R is free software and comes with ABSOLUTELY NO WARRANTY. 170s You are welcome to redistribute it under certain conditions. 170s Type 'license()' or 'licence()' for distribution details. 170s 170s R is a collaborative project with many contributors. 170s Type 'contributors()' for more information and 170s 'citation()' on how to cite R or R packages in publications. 170s 170s Type 'demo()' for some demos, 'help()' for on-line help, or 170s 'help.start()' for an HTML browser interface to help. 170s Type 'q()' to quit R. 170s 170s [Previously saved workspace restored] 170s 170s > # This test script calls a report generator which requires 170s > # the 'ggplot2' package, which in turn will require packages 170s > # 'colorspace', 'dichromat', 'munsell', 'reshape2' and 'scales'. 170s > 170s > # Only run this test in full testing mode 170s > if (Sys.getenv("_R_CHECK_FULL_") != "") { 170s + library("PSCBS") 170s + 170s + # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 170s + # Load SNP microarray data 170s + # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 170s + data <- PSCBS::exampleData("paired.chr01") 170s + str(data) 170s + 170s + data <- data.frame(chromosome=data$chromosome, x=data$x, y=data$CT) 170s + 170s + 170s + # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 170s + # CBS segmentation 170s + # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 170s + # Drop single-locus outliers 170s + dataS <- dropSegmentationOutliers(data) 170s + 170s + # Speed up example by segmenting fewer loci 170s + dataS <- dataS[seq(from=1, to=nrow(data), by=5),] 170s + 170s + str(dataS) 170s + 170s + gaps <- findLargeGaps(dataS, minLength=2e6) 170s + knownSegments <- gapsToSegments(gaps) 170s + 170s + # CBS segmentation 170s + fit <- segmentByCBS(dataS, knownSegments=knownSegments, 170s + seed=0xBEEF, verbose=-10) 170s + signalType(fit) <- "ratio" 170s + 170s + # Fake a multi-chromosome segmentation 170s + fit1 <- fit 170s + fit2 <- renameChromosomes(fit, from=1, to=2) 170s + fit <- c(fit1, fit2) 170s + 170s + report(fit, sampleName="CBS", studyName="CBS-Ex", verbose=-10) 170s + 170s + } # if (Sys.getenv("_R_CHECK_FULL_")) 170s > 170s > proc.time() 170s user system elapsed 170s 0.114 0.018 0.125 170s Test segmentByCBS,report passed 170s 0 170s Begin test segmentByCBS,shiftTCN 170s + [ 0 != 0 ] 170s + echo Test segmentByCBS,report passed 170s + echo 0 170s + echo Begin test segmentByCBS,shiftTCN 170s + exitcode=0 170s + R CMD BATCH segmentByCBS,shiftTCN.R 175s 175s R version 4.5.2 (2025-10-31) -- "[Not] Part in a Rumble" 175s Copyright (C) 2025 The R Foundation for Statistical Computing 175s Platform: x86_64-pc-linux-gnu 175s 175s R is free software and comes with ABSOLUTELY NO WARRANTY. 175s You are welcome to redistribute it under certain conditions. 175s Type 'license()' or 'licence()' for distribution details. 175s 175s R is a collaborative project with many contributors. 175s Type 'contributors()' for more information and 175s 'citation()' on how to cite R or R packages in publications. 175s 175s Type 'demo()' for some demos, 'help()' for on-line help, or 175s 'help.start()' for an HTML browser interface to help. 175s Type 'q()' to quit R. 175s 175s [Previously saved workspace restored] 175s 175s > library("PSCBS") 175s PSCBS v0.68.0 (2025-04-18 19:40:02 UTC) successfully loaded. See ?PSCBS for help. 175s > subplots <- R.utils::subplots 175s > 175s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 175s > # Simulating copy-number data 175s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 175s > set.seed(0xBEEF) 175s > 175s > # Number of loci 175s > J <- 1000 175s > 175s > mu <- double(J) 175s > eps <- rnorm(J, sd=1/2) 175s > y <- mu + eps 175s > x <- sort(runif(length(y), max=length(y))) 175s > 175s > idxs <- which(200 <= x & x < 300) 175s > y[idxs] <- y[idxs] + 1 175s > idxs <- which(350 <= x & x < 400) 175s > y[idxs] <- NA # centromere 175s > x[idxs] <- NA # centromere 175s > idxs <- which(650 <= x & x < 800) 175s > y[idxs] <- y[idxs] - 1 175s > x <- x*1e5 175s > 175s > keep <- is.finite(x) 175s > x <- x[keep] 175s > y <- y[keep] 175s > 175s > data <- list() 175s > for (chr in 1:2) { 175s + data[[chr]] <- data.frame(chromosome=chr, y=y, x=x) 175s + } 175s > data <- Reduce(rbind, data) 175s > 175s > 175s > subplots(7, ncol=1) 175s > par(mar=c(1.7,1,0.2,1)+0.1) 175s > 175s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 175s > # Segmentation 175s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 175s > fit <- segmentByCBS(data) 175s > print(fit) 175s sampleName chromosome start end nbrOfLoci mean 175s 1 1 65285.65 20169684 205 0.0124 175s 2 1 20169684.05 29980147 103 0.9477 175s 3 1 29980147.36 64779929 287 -0.0299 175s 4 1 64779929.38 80010171 163 -0.9676 175s 5 1 80010171.14 99819310 196 -0.0484 175s 6 NA NA NA NA NA 175s 7 2 65285.65 20169684 205 0.0124 175s 8 2 20169684.05 29980147 103 0.9477 175s 9 2 29980147.36 64779929 287 -0.0299 175s 10 2 64779929.38 80010171 163 -0.9676 175s 11 2 80010171.14 99819310 196 -0.0484 175s > 175s > Clim <- c(-3,3) + c(0,10) 175s > plotTracks(fit, Clim=Clim) 175s > 175s > 175s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 175s > # Shifting every other chromosome 175s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 175s > fitList <- list() 175s > chrs <- getChromosomes(fit) 175s > for (kk in seq_along(chrs)) { 175s + chr <- chrs[kk] 175s + fitKK <- extractChromosome(fit, chr) 175s + if (kk %% 2 == 0) { 175s + fitKK <- shiftTCN(fitKK, shift=+10) 175s + } 175s + fitList[[kk]] <- fitKK 175s + } # for (kk ...) 175s > fitT <- do.call(c, fitList) 175s > # Sanity check 175s > stopifnot(nbrOfSegments(fitT) == nbrOfSegments(fit)) 175s > 175s > plotTracks(fitT, Clim=Clim) 175s > 175s > 175s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 175s > # Shifting every other known segment 175s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 175s > gaps <- findLargeGaps(data, minLength=40e5) 175s > knownSegments <- gapsToSegments(gaps, dropGaps=TRUE) 175s > fit <- segmentByCBS(data, knownSegments=knownSegments) 175s > 175s > subplots(2, ncol=1) 175s > plotTracks(fit, Clim=Clim) 175s > abline(v=c(knownSegments$start, knownSegments$end)/1e6, lty=3) 175s > 175s > fitList <- list() 175s > for (kk in seq_len(nrow(knownSegments))) { 175s + seg <- knownSegments[kk,] 175s + start <- seg$start 175s + end <- seg$end 175s + fitKK <- extractChromosome(fit, seg$chromosome) 175s + segsKK <- getSegments(fitKK) 175s + idxStart <- min(which(segsKK$start >= start)) 175s + idxEnd <- max(which(segsKK$end <= end)) 175s + idxs <- idxStart:idxEnd 175s + fitKK <- extractSegments(fitKK, idxs) 175s + if (kk %% 2 == 0) { 175s + fitKK <- shiftTCN(fitKK, shift=+10) 175s + } 175s + fitList[[kk]] <- fitKK 175s + } # for (kk ...) 175s > fitT <- do.call(c, fitList) 175s > # Sanity check 175s > stopifnot(nbrOfSegments(fitT) == nbrOfSegments(fit)) 175s > 175s > plotTracks(fitT, Clim=Clim) 175s > abline(v=c(knownSegments$start, knownSegments$end)/1e6, lty=3) 175s > 175s > 175s > segList <- seqOfSegmentsByDP(fit) 175s > K <- length(segList) 175s > subplots(K, ncol=2, byrow=FALSE) 175s > par(mar=c(2,1,1,1)) 175s > for (kk in 1:K) { 175s + knownSegments <- segList[[kk]] 175s + fitKK <- resegment(fit, knownSegments=knownSegments, undo=+Inf) 175s + plotTracks(fitKK, Clim=c(-3,3)) 175s + } # for (kk ...) 175s > 175s > proc.time() 175s user system elapsed 175s 4.246 0.039 4.282 175s Test segmentByCBS,shiftTCN passed 175s 0 175s Begin test segmentByCBS,weights 175s + cat segmentByCBS,shiftTCN.Rout 175s + [ 0 != 0 ] 175s + echo Test segmentByCBS,shiftTCN passed 175s + echo 0 175s + echo Begin test segmentByCBS,weights 175s + exitcode=0 175s + R CMD BATCH segmentByCBS,weights.R 177s + cat segmentByCBS,weights.Rout 177s 177s R version 4.5.2 (2025-10-31) -- "[Not] Part in a Rumble" 177s Copyright (C) 2025 The R Foundation for Statistical Computing 177s Platform: x86_64-pc-linux-gnu 177s 177s R is free software and comes with ABSOLUTELY NO WARRANTY. 177s You are welcome to redistribute it under certain conditions. 177s Type 'license()' or 'licence()' for distribution details. 177s 177s R is a collaborative project with many contributors. 177s Type 'contributors()' for more information and 177s 'citation()' on how to cite R or R packages in publications. 177s 177s Type 'demo()' for some demos, 'help()' for on-line help, or 177s 'help.start()' for an HTML browser interface to help. 177s Type 'q()' to quit R. 177s 177s [Previously saved workspace restored] 177s 177s > library("PSCBS") 177s PSCBS v0.68.0 (2025-04-18 19:40:02 UTC) successfully loaded. See ?PSCBS for help. 177s > 177s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 177s > # Simulating copy-number data 177s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 177s > set.seed(0xBEEF) 177s > 177s > # Number of loci 177s > J <- 1000 177s > 177s > x <- sort(runif(J, max=J)) * 1e5 177s > 177s > mu <- double(J) 177s > mu[200:300] <- mu[200:300] + 1 177s > mu[350:400] <- NA # centromere 177s > mu[650:800] <- mu[650:800] - 1 177s > eps <- rnorm(J, sd=1/2) 177s > y <- mu + eps 177s > 177s > outliers <- seq(from=1L, to=J, length.out=0.2*J) 177s > y[outliers] <- y[outliers] + 1.5 177s > 177s > w <- rep(1.0, times=J) 177s > w[outliers] <- 0.01 177s > 177s > data <- data.frame(chromosome=1L, x=x, y=y) 177s > dataW <- cbind(data, w=w) 177s > 177s > 177s > par(mar=c(2,3,0.2,1)+0.1) 177s > 177s > 177s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 177s > # Single-chromosome segmentation 177s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 177s > # Segment without weights 177s > fit <- segmentByCBS(data) 177s > sampleName(fit) <- "CBS_Example" 177s > print(fit) 177s sampleName chromosome start end nbrOfLoci mean 177s 1 CBS_Example 1 6.066868e+02 19076007 199 0.2622 177s 2 CBS_Example 1 1.907601e+07 29630949 99 1.4289 177s 3 CBS_Example 1 2.963095e+07 63224332 299 0.2854 177s 4 CBS_Example 1 6.322433e+07 78801707 153 -0.7408 177s 5 CBS_Example 1 7.880171e+07 99917418 199 0.3541 177s > plotTracks(fit) 177s Warning message: 177s In plotTracks.CBS(fit) : 177s Setting default 'Clim' assuming the signal type is 'ratio' because signalType(fit) is unknown ('NA'). Use signalType(fit) <- 'ratio' to avoid this warning. 177s > ## Highlight outliers (they pull up the mean levels) 177s > points(x[outliers]/1e6, y[outliers], col="purple") 177s > 177s > # Segment with weights 177s > fitW <- segmentByCBS(dataW) 177s > sampleName(fitW) <- "CBS_Example (weighted)" 177s > print(fitW) 177s sampleName chromosome start end nbrOfLoci mean 177s 1 CBS_Example (weighted) 1 6.066868e+02 19076007 199 -0.0610 177s 2 CBS_Example (weighted) 1 1.907601e+07 30126128 101 1.1283 177s 3 CBS_Example (weighted) 1 3.012613e+07 63224332 297 -0.0298 177s 4 CBS_Example (weighted) 1 6.322433e+07 78801707 153 -1.0436 177s 5 CBS_Example (weighted) 1 7.880171e+07 99917418 199 0.0461 177s > drawLevels(fitW, col="red") 177s NULL 177s > 177s > legend("topright", bg="white", legend=c("outliers", "non-weighted CBS", "weighted CBS"), col=c("purple", "purple", "red"), lwd=c(NA,3,3), pch=c(1,NA,NA)) 177s > 177s > ## Assert that weighted segment means are less biased 177s > dmean <- getSegments(fit)$mean - getSegments(fitW)$mean 177s > cat("Segment mean differences:\n") 177s Segment mean differences: 177s > print(dmean) 177s [1] 0.3232 0.3006 0.3152 0.3028 0.3080 177s > stopifnot(all(dmean > 0, na.rm=TRUE)) 177s > 177s > 177s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 177s > # Segmentation with some known change points 177s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 177s > knownSegments <- data.frame( 177s + chromosome=c( 1, 1), 177s + start =x[c( 1, 401)], 177s + end =x[c(349, J)] 177s + ) 177s > fit2 <- segmentByCBS(dataW, knownSegments=knownSegments, verbose=TRUE) 177s Segmenting by CBS... 177s Chromosome: 1 177s Segmenting by CBS...done 177s > sampleName(fit2) <- "CBS_Example_2 (weighted)" 177s > print(fit2) 177s sampleName chromosome start end nbrOfLoci mean 177s 1 CBS_Example_2 (weighted) 1 6.066868e+02 19076007 199 -0.0610 177s 2 CBS_Example_2 (weighted) 1 1.907601e+07 30126128 101 1.1283 177s 3 CBS_Example_2 (weighted) 1 3.012613e+07 35490554 49 -0.0832 177s 4 CBS_Example_2 (weighted) 1 3.987525e+07 63224332 248 -0.0192 177s 5 CBS_Example_2 (weighted) 1 6.322433e+07 78471531 152 -1.0480 177s 6 CBS_Example_2 (weighted) 1 7.847153e+07 99917418 200 0.0427 177s > plotTracks(fit2) 177s Warning message: 177s In plotTracks.CBS(fit2) : 177s Setting default 'Clim' assuming the signal type is 'ratio' because signalType(fit2) is unknown ('NA'). Use signalType(fit2) <- 'ratio' to avoid this warning. 177s > abline(v=c(knownSegments$start, knownSegments$end)/1e6, lty=3) 177s > 177s > 177s > # Chromosome boundaries can be specified as -Inf and +Inf 177s > knownSegments <- data.frame( 177s + chromosome=c( 1, 1), 177s + start =c( -Inf, x[401]), 177s + end =c(x[349], +Inf) 177s + ) 177s > fit2b <- segmentByCBS(dataW, knownSegments=knownSegments, verbose=TRUE) 177s Segmenting by CBS... 177s Chromosome: 1 177s Segmenting by CBS...done 177s > sampleName(fit2b) <- "CBS_Example_2b (weighted)" 177s > print(fit2b) 177s sampleName chromosome start end nbrOfLoci mean 177s 1 CBS_Example_2b (weighted) 1 6.066868e+02 19076007 199 -0.0610 177s 2 CBS_Example_2b (weighted) 1 1.907601e+07 30126128 101 1.1283 177s 3 CBS_Example_2b (weighted) 1 3.012613e+07 35490554 49 -0.0832 177s 4 CBS_Example_2b (weighted) 1 3.987525e+07 63224332 248 -0.0192 177s 5 CBS_Example_2b (weighted) 1 6.322433e+07 78471531 152 -1.0480 177s 6 CBS_Example_2b (weighted) 1 7.847153e+07 99917418 200 0.0427 177s > plotTracks(fit2b) 177s Warning message: 177s In plotTracks.CBS(fit2b) : 177s Setting default 'Clim' assuming the signal type is 'ratio' because signalType(fit2b) is unknown ('NA'). Use signalType(fit2b) <- 'ratio' to avoid this warning. 177s > abline(v=c(knownSegments$start, knownSegments$end)/1e6, lty=3) 177s > 177s > 177s > # As a proof of concept, it is possible to segment just the centromere, 177s > # which contains no data. All statistics will be NAs. 177s > knownSegments <- data.frame( 177s + chromosome=c( 1), 177s + start =x[c(350)], 177s + end =x[c(400)] 177s + ) 177s > fit3 <- segmentByCBS(dataW, knownSegments=knownSegments, verbose=TRUE) 177s Segmenting by CBS... 177s Chromosome: 1 177s Segmenting by CBS...done 177s > sampleName(fit3) <- "CBS_Example_3" 177s > print(fit3) 177s sampleName chromosome start end nbrOfLoci mean 177s 1 CBS_Example_3 1 35661013 39852333 0 NA 177s > plotTracks(fit3, Clim=c(0,5), xlim=c(0,100)) 177s > abline(v=c(knownSegments$start, knownSegments$end)/1e6, lty=3) 177s > 177s > 177s > # If one specify the (empty) centromere as a segment, then its 177s > # estimated statistics will be NAs, which becomes a natural 177s > # separator between the two "independent" arms. 177s > knownSegments <- data.frame( 177s + chromosome=c( 1, 1, 1), 177s + start =x[c( 1, 350, 401)], 177s + end =x[c(349, 400, J)] 177s + ) 177s > fit4 <- segmentByCBS(dataW, knownSegments=knownSegments, verbose=TRUE) 177s Segmenting by CBS... 177s Chromosome: 1 177s Segmenting by CBS...done 177s > sampleName(fit4) <- "CBS_Example_4" 177s > print(fit4) 177s sampleName chromosome start end nbrOfLoci mean 177s 1 CBS_Example_4 1 6.066868e+02 19076007 199 -0.0610 177s 2 CBS_Example_4 1 1.907601e+07 30126128 101 1.1283 177s 3 CBS_Example_4 1 3.012613e+07 35490554 49 -0.0832 177s 4 CBS_Example_4 1 3.566101e+07 39852333 0 NA 177s 5 CBS_Example_4 1 3.987525e+07 63224332 248 -0.0192 177s 6 CBS_Example_4 1 6.322433e+07 78471531 152 -1.0480 177s 7 CBS_Example_4 1 7.847153e+07 99917418 200 0.0427 177s > plotTracks(fit4) 177s Warning message: 177s In plotTracks.CBS(fit4) : 177s Setting default 'Clim' assuming the signal type is 'ratio' because signalType(fit4) is unknown ('NA'). Use signalType(fit4) <- 'ratio' to avoid this warning. 177s > abline(v=c(knownSegments$start, knownSegments$end)/1e6, lty=3) 177s > 177s > 177s > fit5 <- segmentByCBS(dataW, knownSegments=knownSegments, undo=Inf, verbose=TRUE) 177s Segmenting by CBS... 177s Chromosome: 1 177s Segmenting by CBS...done 177s > sampleName(fit5) <- "CBS_Example_5" 177s > print(fit5) 177s sampleName chromosome start end nbrOfLoci mean 177s 1 CBS_Example_5 1 6.066868e+02 35490554 349 0.59252133 177s 2 CBS_Example_5 1 3.566101e+07 39852333 0 NA 177s 3 CBS_Example_5 1 3.987525e+07 99917418 600 0.04882396 177s > plotTracks(fit5) 177s Warning message: 177s In plotTracks.CBS(fit5) : 177s Setting default 'Clim' assuming the signal type is 'ratio' because signalType(fit5) is unknown ('NA'). Use signalType(fit5) <- 'ratio' to avoid this warning. 177s > abline(v=c(knownSegments$start, knownSegments$end)/1e6, lty=3) 177s > stopifnot(nbrOfSegments(fit5) == nrow(knownSegments)) 177s > 177s > 177s > # One can also force a separator between two segments by setting 177s > # 'start' and 'end' to NAs ('chromosome' has to be given) 177s > knownSegments <- data.frame( 177s + chromosome=c( 1, 1, 1), 177s + start =x[c( 1, NA, 401)], 177s + end =x[c(349, NA, J)] 177s + ) 177s > fit6 <- segmentByCBS(dataW, knownSegments=knownSegments, verbose=TRUE) 177s Segmenting by CBS... 177s Chromosome: 1 177s Segmenting by CBS...done 177s > sampleName(fit6) <- "CBS_Example_6" 177s > print(fit6) 177s sampleName chromosome start end nbrOfLoci mean 177s 1 CBS_Example_6 1 6.066868e+02 19076007 199 -0.0610 177s 2 CBS_Example_6 1 1.907601e+07 30126128 101 1.1283 177s 3 CBS_Example_6 1 3.012613e+07 35490554 49 -0.0832 177s 4 NA NA NA NA NA 177s 5 CBS_Example_6 1 3.987525e+07 63224332 248 -0.0192 177s 6 CBS_Example_6 1 6.322433e+07 78471531 152 -1.0480 177s 7 CBS_Example_6 1 7.847153e+07 99917418 200 0.0427 177s > plotTracks(fit6) 177s Warning message: 177s In plotTracks.CBS(fit6) : 177s Setting default 'Clim' assuming the signal type is 'ratio' because signalType(fit6) is unknown ('NA'). Use signalType(fit6) <- 'ratio' to avoid this warning. 177s > abline(v=c(knownSegments$start, knownSegments$end)/1e6, lty=3) 177s > 177s > 177s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 177s > # Multi-chromosome segmentation 177s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 177s > data2 <- data 177s > data2$chromosome <- 2L 177s > data <- rbind(data, data2) 177s > dataW <- cbind(data, w=w) 177s > 177s > par(mar=c(2,3,0.2,1)+0.1) 177s > # Segment without weights 177s > fit <- segmentByCBS(data) 177s > sampleName(fit) <- "CBS_Example" 177s > print(fit) 177s sampleName chromosome start end nbrOfLoci mean 177s 1 CBS_Example 1 6.066868e+02 19076007 199 0.2622 177s 2 CBS_Example 1 1.907601e+07 29630949 99 1.4289 177s 3 CBS_Example 1 2.963095e+07 63224332 299 0.2854 177s 4 CBS_Example 1 6.322433e+07 78801707 153 -0.7408 177s 5 CBS_Example 1 7.880171e+07 99917418 199 0.3541 177s 6 NA NA NA NA NA 177s 7 CBS_Example 2 6.066868e+02 19076007 199 0.2622 177s 8 CBS_Example 2 1.907601e+07 29630949 99 1.4289 177s 9 CBS_Example 2 2.963095e+07 63224332 299 0.2854 177s 10 CBS_Example 2 6.322433e+07 78801707 153 -0.7408 177s 11 CBS_Example 2 7.880171e+07 99917418 199 0.3541 177s > plotTracks(fit, Clim=c(-3,3)) 177s > 177s > # Segment with weights 177s > fitW <- segmentByCBS(dataW) 177s > sampleName(fitW) <- "CBS_Example (weighted)" 177s > print(fitW) 177s sampleName chromosome start end nbrOfLoci mean 177s 1 CBS_Example (weighted) 1 6.066868e+02 19076007 199 -0.0610 177s 2 CBS_Example (weighted) 1 1.907601e+07 30126128 101 1.1283 177s 3 CBS_Example (weighted) 1 3.012613e+07 63224332 297 -0.0298 177s 4 CBS_Example (weighted) 1 6.322433e+07 78801707 153 -1.0436 177s 5 CBS_Example (weighted) 1 7.880171e+07 99917418 199 0.0461 177s 6 NA NA NA NA NA 177s 7 CBS_Example (weighted) 2 6.066868e+02 19076007 199 -0.0610 177s 8 CBS_Example (weighted) 2 1.907601e+07 30126128 101 1.1283 177s 9 CBS_Example (weighted) 2 3.012613e+07 63224332 297 -0.0298 177s 10 CBS_Example (weighted) 2 6.322433e+07 78801707 153 -1.0436 177s 11 CBS_Example (weighted) 2 7.880171e+07 99917418 199 0.0461 177s > drawLevels(fitW, col="red") 177s NULL 177s > 177s > legend("topright", bg="white", legend=c("outliers", "non-weighted CBS", "weighted CBS"), col=c("purple", "purple", "red"), lwd=c(NA,3,3), pch=c(1,NA,NA)) 177s > 177s > ## Assert that weighted segment means are less biased 177s > dmean <- getSegments(fit)$mean - getSegments(fitW)$mean 177s > cat("Segment mean differences:\n") 177s Segment mean differences: 177s > print(dmean) 177s [1] 0.3232 0.3006 0.3152 0.3028 0.3080 NA 0.3232 0.3006 0.3152 0.3028 177s [11] 0.3080 177s > stopifnot(all(dmean > 0, na.rm=TRUE)) 177s > 177s > proc.time() 177s user system elapsed 177s 1.428 0.050 1.474 177s Test segmentByCBS,weights passed 177s 0 177s Begin test segmentByCBS 177s + [ 0 != 0 ] 177s + echo Test segmentByCBS,weights passed 177s + echo 0 177s + echo Begin test segmentByCBS 177s + exitcode=0 177s + R CMD BATCH segmentByCBS.R 178s + cat segmentByCBS.Rout 178s + 178s R version 4.5.2 (2025-10-31) -- "[Not] Part in a Rumble" 178s Copyright (C) 2025 The R Foundation for Statistical Computing 178s Platform: x86_64-pc-linux-gnu 178s 178s R is free software and comes with ABSOLUTELY NO WARRANTY. 178s You are welcome to redistribute it under certain conditions. 178s Type 'license()' or 'licence()' for distribution details. 178s 178s R is a collaborative project with many contributors. 178s Type 'contributors()' for more information and 178s 'citation()' on how to cite R or R packages in publications. 178s 178s Type 'demo()' for some demos, 'help()' for on-line help, or 178s 'help.start()' for an HTML browser interface to help. 178s Type 'q()' to quit R. 178s 178s [Previously saved workspace restored] 178s 178s > ########################################################### 178s > # This tests: 178s > # - segmentByCBS(...) 178s > # - segmentByCBS(..., knownSegments) 178s > # - tileChromosomes() 178s > # - plotTracks() 178s > ########################################################### 178s > library("PSCBS") 178s PSCBS v0.68.0 (2025-04-18 19:40:02 UTC) successfully loaded. See ?PSCBS for help. 178s > subplots <- R.utils::subplots 178s > 178s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 178s > # Simulating copy-number data 178s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 178s > set.seed(0xBEEF) 178s > 178s > # Number of loci 178s > J <- 1000 178s > 178s > mu <- double(J) 178s > mu[200:300] <- mu[200:300] + 1 178s > mu[350:400] <- NA # centromere 178s > mu[650:800] <- mu[650:800] - 1 178s > eps <- rnorm(J, sd=1/2) 178s > y <- mu + eps 178s > x <- sort(runif(length(y), max=length(y))) * 1e5 178s > w <- runif(J) 178s > w[650:800] <- 0.001 178s > 178s > 178s > subplots(8, ncol=1L) 178s > par(mar=c(1.7,1,0.2,1)+0.1) 178s > 178s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 178s > # Segmentation 178s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 178s > fit <- segmentByCBS(y, x=x) 178s > sampleName(fit) <- "CBS_Example" 178s > print(fit) 178s sampleName chromosome start end nbrOfLoci mean 178s 1 CBS_Example 0 65285.65 19648927 200 0.0109 178s 2 CBS_Example 0 19648927.46 28239656 95 0.9529 178s 3 CBS_Example 0 28239655.99 65697742 302 -0.0126 178s 4 CBS_Example 0 65697742.20 79729368 153 -0.9534 178s 5 CBS_Example 0 79729368.34 99819310 199 -0.0497 178s > plotTracks(fit) 178s Warning message: 178s In plotTracks.CBS(fit) : 178s Setting default 'Clim' assuming the signal type is 'ratio' because signalType(fit) is unknown ('NA'). Use signalType(fit) <- 'ratio' to avoid this warning. 178s > 178s > 178s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 178s > # Segmentation with some known change points 178s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 178s > knownSegments <- data.frame( 178s + chromosome=c( 0, 0), 178s + start =x[c( 1, 401)], 178s + end =x[c(349, J)] 178s + ) 178s > fit2 <- segmentByCBS(y, x=x, knownSegments=knownSegments, verbose=TRUE) 178s Segmenting by CBS... 178s Chromosome: 0 178s Segmenting by CBS...done 178s > sampleName(fit2) <- "CBS_Example_2" 178s > print(fit2) 178s sampleName chromosome start end nbrOfLoci mean 178s 1 CBS_Example_2 0 65285.65 19648927 200 0.0109 178s 2 CBS_Example_2 0 19648927.46 28239656 95 0.9529 178s 3 CBS_Example_2 0 28239655.99 33106633 54 0.1169 178s 4 CBS_Example_2 0 38076667.59 65697742 248 -0.0408 178s 5 CBS_Example_2 0 65697742.20 79729368 153 -0.9534 178s 6 CBS_Example_2 0 79729368.34 99819310 199 -0.0497 178s > plotTracks(fit2) 178s Warning message: 178s In plotTracks.CBS(fit2) : 178s Setting default 'Clim' assuming the signal type is 'ratio' because signalType(fit2) is unknown ('NA'). Use signalType(fit2) <- 'ratio' to avoid this warning. 178s > abline(v=c(knownSegments$start, knownSegments$end)/1e6, lty=3) 178s > 178s > 178s > # Chromosome boundaries can be specified as -Inf and +Inf 178s > knownSegments <- data.frame( 178s + chromosome=c( 0, 0), 178s + start =c( -Inf, x[401]), 178s + end =c(x[349], +Inf) 178s + ) 178s > fit2b <- segmentByCBS(y, x=x, knownSegments=knownSegments, verbose=TRUE) 178s Segmenting by CBS... 178s Chromosome: 0 178s Segmenting by CBS...done 178s > sampleName(fit2b) <- "CBS_Example_2b" 178s > print(fit2b) 178s sampleName chromosome start end nbrOfLoci mean 178s 1 CBS_Example_2b 0 65285.65 19648927 200 0.0109 178s 2 CBS_Example_2b 0 19648927.46 28239656 95 0.9529 178s 3 CBS_Example_2b 0 28239655.99 33106633 54 0.1169 178s 4 CBS_Example_2b 0 38076667.59 65697742 248 -0.0408 178s 5 CBS_Example_2b 0 65697742.20 79729368 153 -0.9534 178s 6 CBS_Example_2b 0 79729368.34 99819310 199 -0.0497 178s > plotTracks(fit2b) 178s Warning message: 178s In plotTracks.CBS(fit2b) : 178s Setting default 'Clim' assuming the signal type is 'ratio' because signalType(fit2b) is unknown ('NA'). Use signalType(fit2b) <- 'ratio' to avoid this warning. 178s > abline(v=c(knownSegments$start, knownSegments$end)/1e6, lty=3) 178s > 178s > 178s > # As a proof of concept, it is possible to segment just the centromere, 178s > # which contains no data. All statistics will be NAs. 178s > knownSegments <- data.frame( 178s + chromosome=c( 0), 178s + start =x[c(350)], 178s + end =x[c(400)] 178s + ) 178s > fit3 <- segmentByCBS(y, x=x, knownSegments=knownSegments, verbose=TRUE) 178s Segmenting by CBS... 178s Chromosome: 0 178s Segmenting by CBS...done 178s > sampleName(fit3) <- "CBS_Example_3" 178s > print(fit3) 178s sampleName chromosome start end nbrOfLoci mean 178s 1 CBS_Example_3 0 33248518 37640521 0 NA 178s > plotTracks(fit3, Clim=c(0,5), xlim=c(0,100)) 178s > abline(v=c(knownSegments$start, knownSegments$end)/1e6, lty=3) 178s > 178s > 178s > 178s > # If one specify the (empty) centromere as a segment, then its 178s > # estimated statistics will be NAs, which becomes a natural 178s > # separator between the two "independent" arms. 178s > knownSegments <- data.frame( 178s + chromosome=c( 0, 0, 0), 178s + start =x[c( 1, 350, 401)], 178s + end =x[c(349, 400, J)] 178s + ) 178s > fit4 <- segmentByCBS(y, x=x, knownSegments=knownSegments, verbose=TRUE) 178s Segmenting by CBS... 178s Chromosome: 0 178s Segmenting by CBS...done 178s > sampleName(fit4) <- "CBS_Example_4" 178s > print(fit4) 178s sampleName chromosome start end nbrOfLoci mean 178s 1 CBS_Example_4 0 65285.65 19648927 200 0.0109 178s 2 CBS_Example_4 0 19648927.46 28239656 95 0.9529 178s 3 CBS_Example_4 0 28239655.99 33106633 54 0.1169 178s 4 CBS_Example_4 0 33248517.78 37640521 0 NA 178s 5 CBS_Example_4 0 38076667.59 65697742 248 -0.0408 178s 6 CBS_Example_4 0 65697742.20 79729368 153 -0.9534 178s 7 CBS_Example_4 0 79729368.34 99819310 199 -0.0497 178s > plotTracks(fit4) 178s Warning message: 178s In plotTracks.CBS(fit4) : 178s Setting default 'Clim' assuming the signal type is 'ratio' because signalType(fit4) is unknown ('NA'). Use signalType(fit4) <- 'ratio' to avoid this warning. 178s > abline(v=c(knownSegments$start, knownSegments$end)/1e6, lty=3) 178s > 178s > 178s > 178s > fit5 <- segmentByCBS(y, x=x, knownSegments=knownSegments, undo=Inf, verbose=TRUE) 178s Segmenting by CBS... 178s Chromosome: 0 178s Segmenting by CBS...done 178s > sampleName(fit5) <- "CBS_Example_5" 178s > print(fit5) 178s sampleName chromosome start end nbrOfLoci mean 178s 1 CBS_Example_5 0 65285.65 33106633 349 0.2836973 178s 2 CBS_Example_5 0 33248517.78 37640521 0 NA 178s 3 CBS_Example_5 0 38076667.59 99819310 600 -0.2764472 178s > plotTracks(fit5) 178s Warning message: 178s In plotTracks.CBS(fit5) : 178s Setting default 'Clim' assuming the signal type is 'ratio' because signalType(fit5) is unknown ('NA'). Use signalType(fit5) <- 'ratio' to avoid this warning. 178s > abline(v=c(knownSegments$start, knownSegments$end)/1e6, lty=3) 178s > stopifnot(nbrOfSegments(fit5) == nrow(knownSegments)) 178s > 178s > 178s > # One can also force a separator between two segments by setting 178s > # 'start' and 'end' to NAs ('chromosome' has to be given) 178s > knownSegments <- data.frame( 178s + chromosome=c( 0, 0, 0), 178s + start =x[c( 1, NA, 401)], 178s + end =x[c(349, NA, J)] 178s + ) 178s > fit6 <- segmentByCBS(y, x=x, knownSegments=knownSegments, verbose=TRUE) 178s Segmenting by CBS... 178s Chromosome: 0 178s Segmenting by CBS...done 178s > sampleName(fit6) <- "CBS_Example_6" 178s > print(fit6) 178s sampleName chromosome start end nbrOfLoci mean 178s 1 CBS_Example_6 0 65285.65 19648927 200 0.0109 178s 2 CBS_Example_6 0 19648927.46 28239656 95 0.9529 178s 3 CBS_Example_6 0 28239655.99 33106633 54 0.1169 178s 4 NA NA NA NA NA 178s 5 CBS_Example_6 0 38076667.59 65697742 248 -0.0408 178s 6 CBS_Example_6 0 65697742.20 79729368 153 -0.9534 178s 7 CBS_Example_6 0 79729368.34 99819310 199 -0.0497 178s > plotTracks(fit6) 178s Warning message: 178s In plotTracks.CBS(fit6) : 178s Setting default 'Clim' assuming the signal type is 'ratio' because signalType(fit6) is unknown ('NA'). Use signalType(fit6) <- 'ratio' to avoid this warning. 178s > abline(v=c(knownSegments$start, knownSegments$end)/1e6, lty=3) 178s > 178s > 178s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 178s > # Segment multiple chromosomes 178s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 178s > # Simulate multiple chromosomes 178s > fit1 <- renameChromosomes(fit, from=0, to=1) 178s > fit2 <- renameChromosomes(fit, from=0, to=2) 178s > fitM <- c(fit1, fit2) 178s > fitM <- segmentByCBS(fitM) 178s > sampleName(fitM) <- "CBS_Example_M" 178s > print(fitM) 178s sampleName chromosome start end nbrOfLoci mean 178s 1 CBS_Example_M 1 65285.65 19648927 200 0.0109 178s 2 CBS_Example_M 1 19648927.46 28239656 95 0.9529 178s 3 CBS_Example_M 1 28239655.99 65697742 302 -0.0126 178s 4 CBS_Example_M 1 65697742.20 79729368 153 -0.9534 178s 5 CBS_Example_M 1 79729368.34 99819310 199 -0.0497 178s 6 NA NA NA NA NA 178s 7 CBS_Example_M 2 65285.65 19648927 200 0.0109 178s 8 CBS_Example_M 2 19648927.46 28239656 95 0.9529 178s 9 CBS_Example_M 2 28239655.99 65697742 302 -0.0126 178s 10 CBS_Example_M 2 65697742.20 79729368 153 -0.9534 178s 11 CBS_Example_M 2 79729368.34 99819310 199 -0.0497 178s > plotTracks(fitM, Clim=c(-3,3)) 178s > 178s > 178s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 178s > # Tiling multiple chromosomes 178s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 178s > # Tile chromosomes 178s > fitT <- tileChromosomes(fitM) 178s > fitTb <- tileChromosomes(fitT) 178s > stopifnot(identical(fitTb, fitT)) 178s > 178s > 178s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 178s > # Write segmentation to file 178s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 178s > pathT <- tempdir() 178s > 178s > ## Tab-delimited file 178s > pathname <- writeSegments(fitM, path=pathT) 178s Warning message: 178s In write.table(file = pathnameT, data, append = TRUE, quote = FALSE, : 178s appending column names to file 178s > print(pathname) 178s [1] "/tmp/RtmpXRKyYS/CBS_Example_M.tsv" 178s > 178s > ## WIG file 178s > pathname <- writeWIG(fitM, path=pathT) 178s > print(pathname) 178s [1] "/tmp/RtmpXRKyYS/CBS_Example_M.wig" 178s > 178s > unlink(pathT, recursive=TRUE) 178s > 178s > proc.time() 178s user system elapsed 178s 1.293 0.053 1.341 178s Test segmentByCBS passed 178s 0 178s Begin test segmentByNonPairedPSCBS,medianDH 178s [ 0 != 0 ] 178s + echo Test segmentByCBS passed 178s + echo 0 178s + echo Begin test segmentByNonPairedPSCBS,medianDH 178s + exitcode=0 178s + R CMD BATCH segmentByNonPairedPSCBS,medianDH.R 179s + cat segmentByNonPairedPSCBS,medianDH.Rout 180s 180s R version 4.5.2 (2025-10-31) -- "[Not] Part in a Rumble" 180s Copyright (C) 2025 The R Foundation for Statistical Computing 180s Platform: x86_64-pc-linux-gnu 180s 180s R is free software and comes with ABSOLUTELY NO WARRANTY. 180s You are welcome to redistribute it under certain conditions. 180s Type 'license()' or 'licence()' for distribution details. 180s 180s R is a collaborative project with many contributors. 180s Type 'contributors()' for more information and 180s 'citation()' on how to cite R or R packages in publications. 180s 180s Type 'demo()' for some demos, 'help()' for on-line help, or 180s 'help.start()' for an HTML browser interface to help. 180s Type 'q()' to quit R. 180s 180s [Previously saved workspace restored] 180s 180s > library("PSCBS") 180s PSCBS v0.68.0 (2025-04-18 19:40:02 UTC) successfully loaded. See ?PSCBS for help. 180s > 180s > 180s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 180s > # Load SNP microarray data 180s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 180s > data <- PSCBS::exampleData("paired.chr01") 180s > str(data) 180s 'data.frame': 73346 obs. of 6 variables: 180s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 180s $ x : int 1145994 2224111 2319424 2543484 2926730 2941694 3084986 3155127 3292731 3695086 ... 180s $ CT : num 1.625 1.071 1.406 1.18 0.856 ... 180s $ betaT : num 0.757 0.771 0.834 0.778 0.229 ... 180s $ CN : num 2.36 2.13 2.59 1.93 1.71 ... 180s $ betaN : num 0.827 0.875 0.887 0.884 0.103 ... 180s > 180s > # Non-paired / tumor-only data 180s > data <- data[,c("chromosome", "x", "CT", "betaT")] 180s > str(data) 180s 'data.frame': 73346 obs. of 4 variables: 180s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 180s $ x : int 1145994 2224111 2319424 2543484 2926730 2941694 3084986 3155127 3292731 3695086 ... 180s $ CT : num 1.625 1.071 1.406 1.18 0.856 ... 180s $ betaT : num 0.757 0.771 0.834 0.778 0.229 ... 180s > 180s > 180s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 180s > # Paired PSCBS segmentation 180s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 180s > # Drop single-locus outliers 180s > dataS <- dropSegmentationOutliers(data) 180s > 180s > # Speed up example by segmenting fewer loci 180s > dataS <- dataS[seq(from=1, to=nrow(data), by=20),] 180s > 180s > # Fake a second chromosome 180s > dataT <- dataS 180s > dataT$chromosome <- 2L 180s > dataS <- rbind(dataS, dataT) 180s > rm(dataT) 180s > str(dataS) 180s 'data.frame': 7336 obs. of 4 variables: 180s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 180s $ x : int 1145994 4276892 5034491 6266412 8418532 11211748 13928296 14370144 15014887 16589707 ... 180s $ CT : num 1.63 1.16 1.35 1.39 1.55 ... 180s $ betaT : num 0.7574 0.0576 0.8391 0.7917 0.8141 ... 180s > 180s > # Non-Paired PSCBS segmentation 180s > fit <- segmentByNonPairedPSCBS(dataS, avgDH="median", seed=0xBEEF, verbose=-10) 180s Segmenting non-paired tumor signals using Non-paired PSCBS... 180s Number of loci: 7336 180s Number of SNPs: 7336 180s Calling "genotypes" from tumor allele B fractions... 180s num [1:7336] 0.7574 0.0576 0.8391 0.7917 0.8141 ... 180s Upper quantile: 0.475631667925522 180s Symmetric lower quantile: 0.290517384533512 180s (tauA, tauB) estimates: (%g,%g)0.2094826154664880.790517384533512 180s Homozygous treshholds: 180s [1] 0.2094826 0.7905174 180s Inferred germline genotypes (via tumor): 180s num [1:7336] 0.5 0 1 1 1 0 0 0 0.5 1 ... 180s muNx 180s 0 0.5 1 180s 2230 2910 2196 180s Calling "genotypes" from tumor allele B fractions...done 180s Segmenting non-paired tumor signals using Non-paired PSCBS...done 180s Segment using Paired PSCBS... 180s Segmenting paired tumor-normal signals using Paired PSCBS... 180s Setup up data... 180s 'data.frame': 7336 obs. of 6 variables: 180s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 180s $ x : num 1145994 4276892 5034491 6266412 8418532 ... 180s $ CT : num 1.63 1.16 1.35 1.39 1.55 ... 180s $ betaT : num 0.7574 0.0576 0.8391 0.7917 0.8141 ... 180s $ betaTN : num 0.7574 0.0576 0.8391 0.7917 0.8141 ... 180s $ muN : num 0.5 0 1 1 1 0 0 0 0.5 1 ... 180s Setup up data...done 180s Dropping loci for which TCNs are missing... 180s Number of loci dropped: 12 180s Dropping loci for which TCNs are missing...done 180s Ordering data along genome... 180s 'data.frame': 7324 obs. of 6 variables: 180s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 180s $ x : num 554484 1031563 1087198 1145994 1176365 ... 180s $ CT : num 1.88 1.64 1.77 1.63 1.59 ... 180s $ betaT : num 0.0646 0.6078 0.401 0.7574 0.645 ... 180s $ betaTN : num 0.0646 0.6078 0.401 0.7574 0.645 ... 180s $ muN : num 0 0.5 0.5 0.5 0.5 0.5 1 0.5 0.5 0.5 ... 180s Ordering data along genome...done 180s Segmenting multiple chromosomes... 180s Number of chromosomes: 2 180s Random seed temporarily set (seed=c(48879), kind="L'Ecuyer-CMRG") 180s Produced 2 seeds from this stream for future usage 180s Chromosome #1 ('Chr01') of 2... 180s 'data.frame': 3662 obs. of 7 variables: 180s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 180s $ x : num 554484 1031563 1087198 1145994 1176365 ... 180s $ CT : num 1.88 1.64 1.77 1.63 1.59 ... 180s $ betaT : num 0.0646 0.6078 0.401 0.7574 0.645 ... 180s $ betaTN : num 0.0646 0.6078 0.401 0.7574 0.645 ... 180s $ muN : num 0 0.5 0.5 0.5 0.5 0.5 1 0.5 0.5 0.5 ... 180s $ index : int 1 2 3 4 5 6 7 8 9 10 ... 180s Known segments: 180s [1] chromosome start end 180s <0 rows> (or 0-length row.names) 180s Segmenting paired tumor-normal signals using Paired PSCBS... 180s Setup up data... 180s 'data.frame': 3662 obs. of 6 variables: 180s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 180s $ x : num 554484 1031563 1087198 1145994 1176365 ... 180s $ CT : num 1.88 1.64 1.77 1.63 1.59 ... 180s $ betaT : num 0.0646 0.6078 0.401 0.7574 0.645 ... 180s $ betaTN : num 0.0646 0.6078 0.401 0.7574 0.645 ... 180s $ muN : num 0 0.5 0.5 0.5 0.5 0.5 1 0.5 0.5 0.5 ... 180s Setup up data...done 180s Ordering data along genome... 180s 'data.frame': 3662 obs. of 6 variables: 180s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 180s $ x : num 554484 1031563 1087198 1145994 1176365 ... 180s $ CT : num 1.88 1.64 1.77 1.63 1.59 ... 180s $ betaT : num 0.0646 0.6078 0.401 0.7574 0.645 ... 180s $ betaTN : num 0.0646 0.6078 0.401 0.7574 0.645 ... 180s $ muN : num 0 0.5 0.5 0.5 0.5 0.5 1 0.5 0.5 0.5 ... 180s Ordering data along genome...done 180s Keeping only current chromosome for 'knownSegments'... 180s Chromosome: 1 180s Known segments for this chromosome: 180s [1] chromosome start end 180s <0 rows> (or 0-length row.names) 180s Keeping only current chromosome for 'knownSegments'...done 180s alphaTCN: 0.009 180s alphaDH: 0.001 180s Number of loci: 3662 180s Calculating DHs... 180s Number of SNPs: 3662 180s Number of heterozygous SNPs: 1451 (39.62%) 180s Normalized DHs: 180s num [1:3662] NA 0.216 0.198 0.515 0.29 ... 180s Calculating DHs...done 180s Random seed temporarily set (seed=c(10407, 1066287653, -51199871, 161854402, -1995183193, 1503453565, -747102133), kind="L'Ecuyer-CMRG") 180s Produced 2 seeds from this stream for future usage 180s Identification of change points by total copy numbers... 180s Segmenting by CBS... 180s Chromosome: 1 180s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 180s Segmenting by CBS...done 180s List of 4 180s $ data :'data.frame': 3662 obs. of 4 variables: 180s ..$ chromosome: int [1:3662] 1 1 1 1 1 1 1 1 1 1 ... 180s ..$ x : num [1:3662] 554484 1031563 1087198 1145994 1176365 ... 180s ..$ y : num [1:3662] 1.88 1.64 1.77 1.63 1.59 ... 180s ..$ index : int [1:3662] 1 2 3 4 5 6 7 8 9 10 ... 180s $ output :'data.frame': 3 obs. of 6 variables: 180s ..$ sampleName: chr [1:3] NA NA NA 180s ..$ chromosome: int [1:3] 1 1 1 180s ..$ start : num [1:3] 5.54e+05 1.44e+08 1.85e+08 180s ..$ end : num [1:3] 1.44e+08 1.85e+08 2.47e+08 180s ..$ nbrOfLoci : int [1:3] 1880 671 1111 180s ..$ mean : num [1:3] 1.39 2.09 2.65 180s $ segRows:'data.frame': 3 obs. of 2 variables: 180s ..$ startRow: int [1:3] 1 1881 2552 180s ..$ endRow : int [1:3] 1880 2551 3662 180s $ params :List of 5 180s ..$ alpha : num 0.009 180s ..$ undo : num 0 180s ..$ joinSegments : logi TRUE 180s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 180s .. ..$ chromosome: int 1 180s .. ..$ start : num -Inf 180s .. ..$ end : num Inf 180s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 180s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 180s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.042 0 0.042 0 0 180s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 180s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 180s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 180s Identification of change points by total copy numbers...done 180s Restructure TCN segmentation results... 180s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean 180s 1 1 554484 143663981 1880 1.3916 180s 2 1 143663981 185240536 671 2.0925 180s 3 1 185240536 246679946 1111 2.6545 180s Number of TCN segments: 3 180s Restructure TCN segmentation results...done 180s TCN-only segmentation... 180s Total CN segment #1 ([ 554484,1.43664e+08]) of 3... 180s Number of TCN loci in segment: 1880 180s Locus data for TCN segment: 180s 'data.frame': 1880 obs. of 8 variables: 180s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 180s $ x : num 554484 1031563 1087198 1145994 1176365 ... 180s $ CT : num 1.88 1.64 1.77 1.63 1.59 ... 180s $ betaT : num 0.0646 0.6078 0.401 0.7574 0.645 ... 180s $ betaTN : num 0.0646 0.6078 0.401 0.7574 0.645 ... 180s $ muN : num 0 0.5 0.5 0.5 0.5 0.5 1 0.5 0.5 0.5 ... 180s $ index : int 1 2 3 4 5 6 7 8 9 10 ... 180s $ rho : num NA 0.216 0.198 0.515 0.29 ... 180s Number of loci: 1880 180s Number of SNPs: 765 (40.69%) 180s Number of heterozygous SNPs: 765 (100.00%) 180s Total CN segment #1 ([ 554484,1.43664e+08]) of 3...done 180s Total CN segment #2 ([1.43664e+08,1.85241e+08]) of 3... 180s Number of TCN loci in segment: 671 180s Locus data for TCN segment: 180s 'data.frame': 671 obs. of 8 variables: 180s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 180s $ x : num 1.44e+08 1.44e+08 1.44e+08 1.44e+08 1.44e+08 ... 180s $ CT : num 2.26 2.1 2.1 1.89 1.97 ... 180s $ betaT : num 0.958 0.19 0.909 0.13 0.141 ... 180s $ betaTN : num 0.958 0.19 0.909 0.13 0.141 ... 180s $ muN : num 1 0 1 0 0 0 0 0.5 0 1 ... 180s $ index : int 1881 1882 1883 1884 1885 1886 1887 1888 1889 1890 ... 180s $ rho : num NA NA NA NA NA ... 180s Number of loci: 671 180s Number of SNPs: 272 (40.54%) 180s Number of heterozygous SNPs: 272 (100.00%) 180s Total CN segment #2 ([1.43664e+08,1.85241e+08]) of 3...done 180s Total CN segment #3 ([1.85241e+08,2.4668e+08]) of 3... 180s Number of TCN loci in segment: 1111 180s Locus data for TCN segment: 180s 'data.frame': 1111 obs. of 8 variables: 180s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 180s $ x : num 1.85e+08 1.86e+08 1.86e+08 1.86e+08 1.86e+08 ... 180s $ CT : num 2.44 3 2.32 2.76 2.48 ... 180s $ betaT : num 0.0727 0.6845 0.2327 0.8118 0.0746 ... 180s $ betaTN : num 0.0727 0.6845 0.2327 0.8118 0.0746 ... 180s $ muN : num 0 0.5 0.5 1 0 1 0 1 1 0.5 ... 180s $ index : int 2552 2553 2554 2555 2556 2557 2558 2559 2560 2561 ... 180s $ rho : num NA 0.369 0.535 NA NA ... 180s Number of loci: 1111 180s Number of SNPs: 414 (37.26%) 180s Number of heterozygous SNPs: 414 (100.00%) 180s Total CN segment #3 ([1.85241e+08,2.4668e+08]) of 3...done 180s TCN-only segmentation...done 180s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 180s 1 1 1 1 554484 143663981 1880 1.3916 765 180s 2 1 2 1 143663981 185240536 671 2.0925 272 180s 3 1 3 1 185240536 246679946 1111 2.6545 414 180s tcnNbrOfHets dhNbrOfLoci dhStart dhEnd dhMean 180s 1 765 765 554484 143663981 0.3979122 180s 2 272 272 143663981 185240536 0.2306116 180s 3 414 414 185240536 246679946 0.2798120 180s Calculating (C1,C2) per segment... 180s Calculating (C1,C2) per segment...done 180s Number of segments: 3 180s Segmenting paired tumor-normal signals using Paired PSCBS...done 180s Updating mean level using different estimator... 180s TCN estimator: mean 180s DH estimator: median 180s Updating mean level using different estimator...done 180s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 180s 1 1 1 1 554484 143663981 1880 1.391608 765 180s 2 1 2 1 143663981 185240536 671 2.092452 272 180s 3 1 3 1 185240536 246679946 1111 2.654512 414 180s tcnNbrOfHets dhNbrOfLoci dhStart dhEnd dhMean c1Mean c2Mean 180s 1 765 765 554484 143663981 0.4206323 0.4031263 0.9884817 180s 2 272 272 143663981 185240536 0.1762428 0.8618360 1.2306156 180s 3 414 414 185240536 246679946 0.2697420 0.9692395 1.6852728 180s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 180s 1 1 1 1 554484 143663981 1880 1.391608 765 180s 2 1 2 1 143663981 185240536 671 2.092452 272 180s 3 1 3 1 185240536 246679946 1111 2.654512 414 180s tcnNbrOfHets dhNbrOfLoci dhStart dhEnd dhMean c1Mean c2Mean 180s 1 765 765 554484 143663981 0.4206323 0.4031263 0.9884817 180s 2 272 272 143663981 185240536 0.1762428 0.8618360 1.2306156 180s 3 414 414 185240536 246679946 0.2697420 0.9692395 1.6852728 180s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 180s 1 1 1 1 554484 143663981 1880 1.391608 765 180s 2 1 2 1 143663981 185240536 671 2.092452 272 180s 3 1 3 1 185240536 246679946 1111 2.654512 414 180s tcnNbrOfHets dhNbrOfLoci dhStart dhEnd dhMean c1Mean c2Mean 180s 1 765 765 554484 143663981 0.4206323 0.4031263 0.9884817 180s 2 272 272 143663981 185240536 0.1762428 0.8618360 1.2306156 180s 3 414 414 185240536 246679946 0.2697420 0.9692395 1.6852728 180s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 180s 1 1 1 1 554484 143663981 1880 1.391608 765 180s 2 1 2 1 143663981 185240536 671 2.092452 272 180s 3 1 3 1 185240536 246679946 1111 2.654512 414 180s tcnNbrOfHets dhNbrOfLoci dhStart dhEnd dhMean c1Mean c2Mean 180s 1 765 765 554484 143663981 0.4206323 0.4031263 0.9884817 180s 2 272 272 143663981 185240536 0.1762428 0.8618360 1.2306156 180s 3 414 414 185240536 246679946 0.2697420 0.9692395 1.6852728 180s Chromosome #1 ('Chr01') of 2...done 180s Chromosome #2 ('Chr02') of 2... 180s 'data.frame': 3662 obs. of 7 variables: 180s $ chromosome: int 2 2 2 2 2 2 2 2 2 2 ... 180s $ x : num 554484 1031563 1087198 1145994 1176365 ... 180s $ CT : num 1.88 1.64 1.77 1.63 1.59 ... 180s $ betaT : num 0.0646 0.6078 0.401 0.7574 0.645 ... 180s $ betaTN : num 0.0646 0.6078 0.401 0.7574 0.645 ... 180s $ muN : num 0 0.5 0.5 0.5 0.5 0.5 1 0.5 0.5 0.5 ... 180s $ index : int 3663 3664 3665 3666 3667 3668 3669 3670 3671 3672 ... 180s Known segments: 180s [1] chromosome start end 180s <0 rows> (or 0-length row.names) 180s Segmenting paired tumor-normal signals using Paired PSCBS... 180s Setup up data... 180s 'data.frame': 3662 obs. of 6 variables: 180s $ chromosome: int 2 2 2 2 2 2 2 2 2 2 ... 180s $ x : num 554484 1031563 1087198 1145994 1176365 ... 180s $ CT : num 1.88 1.64 1.77 1.63 1.59 ... 180s $ betaT : num 0.0646 0.6078 0.401 0.7574 0.645 ... 180s $ betaTN : num 0.0646 0.6078 0.401 0.7574 0.645 ... 180s $ muN : num 0 0.5 0.5 0.5 0.5 0.5 1 0.5 0.5 0.5 ... 180s Setup up data...done 180s Ordering data along genome... 180s 'data.frame': 3662 obs. of 6 variables: 180s $ chromosome: int 2 2 2 2 2 2 2 2 2 2 ... 180s $ x : num 554484 1031563 1087198 1145994 1176365 ... 180s $ CT : num 1.88 1.64 1.77 1.63 1.59 ... 180s $ betaT : num 0.0646 0.6078 0.401 0.7574 0.645 ... 180s $ betaTN : num 0.0646 0.6078 0.401 0.7574 0.645 ... 180s $ muN : num 0 0.5 0.5 0.5 0.5 0.5 1 0.5 0.5 0.5 ... 180s Ordering data along genome...done 180s Keeping only current chromosome for 'knownSegments'... 180s Chromosome: 2 180s Known segments for this chromosome: 180s [1] chromosome start end 180s <0 rows> (or 0-length row.names) 180s Keeping only current chromosome for 'knownSegments'...done 180s alphaTCN: 0.009 180s alphaDH: 0.001 180s Number of loci: 3662 180s Calculating DHs... 180s Number of SNPs: 3662 180s Number of heterozygous SNPs: 1451 (39.62%) 180s Normalized DHs: 180s num [1:3662] NA 0.216 0.198 0.515 0.29 ... 180s Calculating DHs...done 180s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 180s Produced 2 seeds from this stream for future usage 180s Identification of change points by total copy numbers... 180s Segmenting by CBS... 180s Chromosome: 2 180s Random seed temporarily set (seed=c(10407, -821273412, -52578226, 1415511586, 721384351, -665928286, 1316562960), kind="L'Ecuyer-CMRG") 180s Segmenting by CBS...done 180s List of 4 180s $ data :'data.frame': 3662 obs. of 4 variables: 180s ..$ chromosome: int [1:3662] 2 2 2 2 2 2 2 2 2 2 ... 180s ..$ x : num [1:3662] 554484 1031563 1087198 1145994 1176365 ... 180s ..$ y : num [1:3662] 1.88 1.64 1.77 1.63 1.59 ... 180s ..$ index : int [1:3662] 1 2 3 4 5 6 7 8 9 10 ... 180s $ output :'data.frame': 3 obs. of 6 variables: 180s ..$ sampleName: chr [1:3] NA NA NA 180s ..$ chromosome: int [1:3] 2 2 2 180s ..$ start : num [1:3] 5.54e+05 1.44e+08 1.85e+08 180s ..$ end : num [1:3] 1.44e+08 1.85e+08 2.47e+08 180s ..$ nbrOfLoci : int [1:3] 1880 671 1111 180s ..$ mean : num [1:3] 1.39 2.09 2.65 180s $ segRows:'data.frame': 3 obs. of 2 variables: 180s ..$ startRow: int [1:3] 1 1881 2552 180s ..$ endRow : int [1:3] 1880 2551 3662 180s $ params :List of 5 180s ..$ alpha : num 0.009 180s ..$ undo : num 0 180s ..$ joinSegments : logi TRUE 180s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 180s .. ..$ chromosome: int 2 180s .. ..$ start : num -Inf 180s .. ..$ end : num Inf 180s ..$ seed : int [1:7] 10407 -821273412 -52578226 1415511586 721384351 -665928286 1316562960 180s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 180s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.041 0 0.041 0 0 180s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 180s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 180s - attr(*, "randomSeed")= int [1:7] 10407 -821273412 -52578226 1415511586 721384351 -665928286 1316562960 180s Identification of change points by total copy numbers...done 180s Restructure TCN segmentation results... 180s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean 180s 1 2 554484 143663981 1880 1.3916 180s 2 2 143663981 185240536 671 2.0925 180s 3 2 185240536 246679946 1111 2.6545 180s Number of TCN segments: 3 180s Restructure TCN segmentation results...done 180s TCN-only segmentation... 180s Total CN segment #1 ([ 554484,1.43664e+08]) of 3... 180s Number of TCN loci in segment: 1880 180s Locus data for TCN segment: 180s 'data.frame': 1880 obs. of 8 variables: 180s $ chromosome: int 2 2 2 2 2 2 2 2 2 2 ... 180s $ x : num 554484 1031563 1087198 1145994 1176365 ... 180s $ CT : num 1.88 1.64 1.77 1.63 1.59 ... 180s $ betaT : num 0.0646 0.6078 0.401 0.7574 0.645 ... 180s $ betaTN : num 0.0646 0.6078 0.401 0.7574 0.645 ... 180s $ muN : num 0 0.5 0.5 0.5 0.5 0.5 1 0.5 0.5 0.5 ... 180s $ index : int 1 2 3 4 5 6 7 8 9 10 ... 180s $ rho : num NA 0.216 0.198 0.515 0.29 ... 180s Number of loci: 1880 180s Number of SNPs: 765 (40.69%) 180s Number of heterozygous SNPs: 765 (100.00%) 180s Total CN segment #1 ([ 554484,1.43664e+08]) of 3...done 180s Total CN segment #2 ([1.43664e+08,1.85241e+08]) of 3... 180s Number of TCN loci in segment: 671 180s Locus data for TCN segment: 180s 'data.frame': 671 obs. of 8 variables: 180s $ chromosome: int 2 2 2 2 2 2 2 2 2 2 ... 180s $ x : num 1.44e+08 1.44e+08 1.44e+08 1.44e+08 1.44e+08 ... 180s $ CT : num 2.26 2.1 2.1 1.89 1.97 ... 180s $ betaT : num 0.958 0.19 0.909 0.13 0.141 ... 180s $ betaTN : num 0.958 0.19 0.909 0.13 0.141 ... 180s $ muN : num 1 0 1 0 0 0 0 0.5 0 1 ... 180s $ index : int 1881 1882 1883 1884 1885 1886 1887 1888 1889 1890 ... 180s $ rho : num NA NA NA NA NA ... 180s Number of loci: 671 180s Number of SNPs: 272 (40.54%) 180s Number of heterozygous SNPs: 272 (100.00%) 180s Total CN segment #2 ([1.43664e+08,1.85241e+08]) of 3...done 180s Total CN segment #3 ([1.85241e+08,2.4668e+08]) of 3... 180s Number of TCN loci in segment: 1111 180s Locus data for TCN segment: 180s 'data.frame': 1111 obs. of 8 variables: 180s $ chromosome: int 2 2 2 2 2 2 2 2 2 2 ... 180s $ x : num 1.85e+08 1.86e+08 1.86e+08 1.86e+08 1.86e+08 ... 180s $ CT : num 2.44 3 2.32 2.76 2.48 ... 180s $ betaT : num 0.0727 0.6845 0.2327 0.8118 0.0746 ... 180s $ betaTN : num 0.0727 0.6845 0.2327 0.8118 0.0746 ... 180s $ muN : num 0 0.5 0.5 1 0 1 0 1 1 0.5 ... 180s $ index : int 2552 2553 2554 2555 2556 2557 2558 2559 2560 2561 ... 180s $ rho : num NA 0.369 0.535 NA NA ... 180s Number of loci: 1111 180s Number of SNPs: 414 (37.26%) 180s Number of heterozygous SNPs: 414 (100.00%) 180s Total CN segment #3 ([1.85241e+08,2.4668e+08]) of 3...done 180s TCN-only segmentation...done 180s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 180s 1 2 1 1 554484 143663981 1880 1.3916 765 180s 2 2 2 1 143663981 185240536 671 2.0925 272 180s 3 2 3 1 185240536 246679946 1111 2.6545 414 180s tcnNbrOfHets dhNbrOfLoci dhStart dhEnd dhMean 180s 1 765 765 554484 143663981 0.3979122 180s 2 272 272 143663981 185240536 0.2306116 180s 3 414 414 185240536 246679946 0.2798120 180s Calculating (C1,C2) per segment... 180s Calculating (C1,C2) per segment...done 180s Number of segments: 3 180s Segmenting paired tumor-normal signals using Paired PSCBS...done 180s Updating mean level using different estimator... 180s TCN estimator: mean 180s DH estimator: median 180s Updating mean level using different estimator...done 180s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 180s 1 2 1 1 554484 143663981 1880 1.391608 765 180s 2 2 2 1 143663981 185240536 671 2.092452 272 180s 3 2 3 1 185240536 246679946 1111 2.654512 414 180s tcnNbrOfHets dhNbrOfLoci dhStart dhEnd dhMean c1Mean c2Mean 180s 1 765 765 554484 143663981 0.4206323 0.4031263 0.9884817 180s 2 272 272 143663981 185240536 0.1762428 0.8618360 1.2306156 180s 3 414 414 185240536 246679946 0.2697420 0.9692395 1.6852728 180s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 180s 1 2 1 1 554484 143663981 1880 1.391608 765 180s 2 2 2 1 143663981 185240536 671 2.092452 272 180s 3 2 3 1 185240536 246679946 1111 2.654512 414 180s tcnNbrOfHets dhNbrOfLoci dhStart dhEnd dhMean c1Mean c2Mean 180s 1 765 765 554484 143663981 0.4206323 0.4031263 0.9884817 180s 2 272 272 143663981 185240536 0.1762428 0.8618360 1.2306156 180s 3 414 414 185240536 246679946 0.2697420 0.9692395 1.6852728 180s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 180s 1 2 1 1 554484 143663981 1880 1.391608 765 180s 2 2 2 1 143663981 185240536 671 2.092452 272 180s 3 2 3 1 185240536 246679946 1111 2.654512 414 180s tcnNbrOfHets dhNbrOfLoci dhStart dhEnd dhMean c1Mean c2Mean 180s 1 765 765 554484 143663981 0.4206323 0.4031263 0.9884817 180s 2 272 272 143663981 185240536 0.1762428 0.8618360 1.2306156 180s 3 414 414 185240536 246679946 0.2697420 0.9692395 1.6852728 180s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 180s 1 2 1 1 554484 143663981 1880 1.391608 765 180s 2 2 2 1 143663981 185240536 671 2.092452 272 180s 3 2 3 1 185240536 246679946 1111 2.654512 414 180s tcnNbrOfHets dhNbrOfLoci dhStart dhEnd dhMean c1Mean c2Mean 180s 1 765 765 554484 143663981 0.4206323 0.4031263 0.9884817 180s 2 272 272 143663981 185240536 0.1762428 0.8618360 1.2306156 180s 3 414 414 185240536 246679946 0.2697420 0.9692395 1.6852728 180s Chromosome #2 ('Chr02') of 2...done 180s Merging (independently) segmented chromosome... 180s List of 5 180s $ data :Classes 'PairedPSCNData' and 'data.frame': 7324 obs. of 7 variables: 180s ..$ chromosome: int [1:7324] 1 1 1 1 1 1 1 1 1 1 ... 180s ..$ x : num [1:7324] 554484 1031563 1087198 1145994 1176365 ... 180s ..$ CT : num [1:7324] 1.88 1.64 1.77 1.63 1.59 ... 180s ..$ betaT : num [1:7324] 0.0646 0.6078 0.401 0.7574 0.645 ... 180s ..$ betaTN : num [1:7324] 0.0646 0.6078 0.401 0.7574 0.645 ... 180s ..$ muN : num [1:7324] 0 0.5 0.5 0.5 0.5 0.5 1 0.5 0.5 0.5 ... 180s ..$ rho : num [1:7324] NA 0.216 0.198 0.515 0.29 ... 180s $ output :Classes 'PairedPSCNSegments' and 'data.frame': 7 obs. of 15 variables: 180s ..$ chromosome : int [1:7] 1 1 1 NA 2 2 2 180s ..$ tcnId : int [1:7] 1 2 3 NA 1 2 3 180s ..$ dhId : int [1:7] 1 1 1 NA 1 1 1 180s ..$ tcnStart : num [1:7] 5.54e+05 1.44e+08 1.85e+08 NA 5.54e+05 ... 180s ..$ tcnEnd : num [1:7] 1.44e+08 1.85e+08 2.47e+08 NA 1.44e+08 ... 180s ..$ tcnNbrOfLoci: int [1:7] 1880 671 1111 NA 1880 671 1111 180s ..$ tcnMean : num [1:7] 1.39 2.09 2.65 NA 1.39 ... 180s ..$ tcnNbrOfSNPs: int [1:7] 765 272 414 NA 765 272 414 180s ..$ tcnNbrOfHets: int [1:7] 765 272 414 NA 765 272 414 180s ..$ dhNbrOfLoci : int [1:7] 765 272 414 NA 765 272 414 180s ..$ dhStart : num [1:7] 5.54e+05 1.44e+08 1.85e+08 NA 5.54e+05 ... 180s ..$ dhEnd : num [1:7] 1.44e+08 1.85e+08 2.47e+08 NA 1.44e+08 ... 180s ..$ dhMean : num [1:7] 0.421 0.176 0.27 NA 0.421 ... 180s ..$ c1Mean : num [1:7] 0.403 0.862 0.969 NA 0.403 ... 180s ..$ c2Mean : num [1:7] 0.988 1.231 1.685 NA 0.988 ... 180s $ tcnSegRows:'data.frame': 7 obs. of 2 variables: 180s ..$ startRow: int [1:7] 1 1881 2552 NA 3663 5543 6214 180s ..$ endRow : int [1:7] 1880 2551 3662 NA 5542 6213 7324 180s $ dhSegRows :'data.frame': 7 obs. of 2 variables: 180s ..$ startRow: int [1:7] 2 1888 2553 NA 3664 5550 6215 180s ..$ endRow : int [1:7] 1876 2548 3659 NA 5538 6210 7321 180s $ params :List of 8 180s ..$ alphaTCN : num 0.009 180s ..$ alphaDH : num 0.001 180s ..$ flavor : chr "tcn" 180s ..$ tbn : logi FALSE 180s ..$ joinSegments : logi TRUE 180s ..$ knownSegments :'data.frame': 0 obs. of 3 variables: 180s .. ..$ chromosome: int(0) 180s .. ..$ start : int(0) 180s .. ..$ end : int(0) 180s ..$ seed : int [1:7] 10407 1066287653 -51199871 161854402 -1995183193 1503453565 -747102133 180s ..$ meanEstimators:List of 2 180s .. ..$ tcn: chr "mean" 180s .. ..$ dh : chr "median" 180s - attr(*, "class")= chr [1:3] "PairedPSCBS" "PSCBS" "AbstractCBS" 180s Merging (independently) segmented chromosome...done 180s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 180s 1 1 1 1 554484 143663981 1880 1.391608 765 180s 2 1 2 1 143663981 185240536 671 2.092452 272 180s 3 1 3 1 185240536 246679946 1111 2.654512 414 180s 4 NA NA NA NA NA NA NA NA 180s 5 2 1 1 554484 143663981 1880 1.391608 765 180s 6 2 2 1 143663981 185240536 671 2.092452 272 180s tcnNbrOfHets dhNbrOfLoci dhStart dhEnd dhMean c1Mean c2Mean 180s 1 765 765 554484 143663981 0.4206323 0.4031263 0.9884817 180s 2 272 272 143663981 185240536 0.1762428 0.8618360 1.2306156 180s 3 414 414 185240536 246679946 0.2697420 0.9692395 1.6852728 180s 4 NA NA NA NA NA NA NA 180s 5 765 765 554484 143663981 0.4206323 0.4031263 0.9884817 180s 6 272 272 143663981 185240536 0.1762428 0.8618360 1.2306156 180s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 180s 2 1 2 1 143663981 185240536 671 2.092452 272 180s 3 1 3 1 185240536 246679946 1111 2.654512 414 180s 4 NA NA NA NA NA NA NA NA 180s 5 2 1 1 554484 143663981 1880 1.391608 765 180s 6 2 2 1 143663981 185240536 671 2.092452 272 180s 7 2 3 1 185240536 246679946 1111 2.654512 414 180s tcnNbrOfHets dhNbrOfLoci dhStart dhEnd dhMean c1Mean c2Mean 180s 2 272 272 143663981 185240536 0.1762428 0.8618360 1.2306156 180s 3 414 414 185240536 246679946 0.2697420 0.9692395 1.6852728 180s 4 NA NA NA NA NA NA NA 180s 5 765 765 554484 143663981 0.4206323 0.4031263 0.9884817 180s 6 272 272 143663981 185240536 0.1762428 0.8618360 1.2306156 180s 7 414 414 185240536 246679946 0.2697420 0.9692395 1.6852728 180s Segmenting multiple chromosomes...done 180s Segmenting paired tumor-normal signals using Paired PSCBS...done 180s Segment using Paired PSCBS...done 180s Coercing to Non-Paired PSCBS results... 180s Coercing to Non-Paired PSCBS results...done 180s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 180s 1 1 1 1 554484 143663981 1880 1.391608 765 180s 2 1 2 1 143663981 185240536 671 2.092452 272 180s 3 1 3 1 185240536 246679946 1111 2.654512 414 180s 4 NA NA NA NA NA NA NA NA 180s 5 2 1 1 554484 143663981 1880 1.391608 765 180s 6 2 2 1 143663981 185240536 671 2.092452 272 180s tcnNbrOfHets dhNbrOfLoci dhStart dhEnd dhMean c1Mean c2Mean 180s 1 765 765 554484 143663981 0.4206323 0.4031263 0.9884817 180s 2 272 272 143663981 185240536 0.1762428 0.8618360 1.2306156 180s 3 414 414 185240536 246679946 0.2697420 0.9692395 1.6852728 180s 4 NA NA NA NA NA NA NA 180s 5 765 765 554484 143663981 0.4206323 0.4031263 0.9884817 180s 6 272 272 143663981 185240536 0.1762428 0.8618360 1.2306156 180s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 180s 2 1 2 1 143663981 185240536 671 2.092452 272 180s 3 1 3 1 185240536 246679946 1111 2.654512 414 180s 4 NA NA NA NA NA NA NA NA 180s 5 2 1 1 554484 143663981 1880 1.391608 765 180s 6 2 2 1 143663981 185240536 671 2.092452 272 180s 7 2 3 1 185240536 246679946 1111 2.654512 414 180s tcnNbrOfHets dhNbrOfLoci dhStart dhEnd dhMean c1Mean c2Mean 180s 2 272 272 143663981 185240536 0.1762428 0.8618360 1.2306156 180s 3 414 414 185240536 246679946 0.2697420 0.9692395 1.6852728 180s 4 NA NA NA NA NA NA NA 180s 5 765 765 554484 143663981 0.4206323 0.4031263 0.9884817 180s 6 272 272 143663981 185240536 0.1762428 0.8618360 1.2306156 180s 7 414 414 185240536 246679946 0.2697420 0.9692395 1.6852728 180s > print(fit) 180s chromosome tcnId dhId start end tcnNbrOfLoci tcnMean tcnNbrOfSNPs 180s 1 1 1 1 554484 143663981 1880 1.391608 765 180s 2 1 2 1 143663981 185240536 671 2.092452 272 180s 3 1 3 1 185240536 246679946 1111 2.654512 414 180s 4 NA NA NA NA NA NA NA NA 180s 5 2 1 1 554484 143663981 1880 1.391608 765 180s 6 2 2 1 143663981 185240536 671 2.092452 272 180s 7 2 3 1 185240536 246679946 1111 2.654512 414 180s tcnNbrOfHets dhNbrOfLoci dhMean c1Mean c2Mean 180s 1 765 765 0.4206323 0.4031263 0.9884817 180s 2 272 272 0.1762428 0.8618360 1.2306156 180s 3 414 414 0.2697420 0.9692395 1.6852728 180s 4 NA NA NA NA NA 180s 5 765 765 0.4206323 0.4031263 0.9884817 180s 6 272 272 0.1762428 0.8618360 1.2306156 180s 7 414 414 0.2697420 0.9692395 1.6852728 180s > 180s > 180s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 180s > # Bootstrap segment level estimates 180s > # (used by the AB caller, which, if skipped here, 180s > # will do it automatically) 180s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 180s > fit <- bootstrapTCNandDHByRegion(fit, B=100, verbose=-10) 180s Resample (TCN,DH) signals and re-estimate summaries for segment & changepoint... 180s Already done? 180s tcn_2.5% tcn_5% tcn_95% tcn_97.5% dh_2.5% dh_5% dh_95% dh_97.5% 180s FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE 180s c1_2.5% c1_5% c1_95% c1_97.5% c2_2.5% c2_5% c2_95% c2_97.5% 180s FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE 180s Bootstrapping (TCN,DH,C1,C2) segment mean levels... 180s Identifying heterozygous & homozygous SNPs and non-polymorphic loci... 180s Number of loci: 7324 180s Number of SNPs: 2902 180s Number of non-SNPs: 4422 180s Identifying heterozygous & homozygous SNPs and non-polymorphic loci...done 180s num [1:7, 1:100, 1:4] NA NA NA NA NA NA NA NA NA NA ... 180s - attr(*, "dimnames")=List of 3 180s ..$ : NULL 180s ..$ : NULL 180s ..$ : chr [1:4] "tcn" "dh" "c1" "c2" 180s Segment #1 (chr 1, tcnId=1, dhId=1) of 7... 180s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 180s 1 1 1 1 554484 143663981 1880 1.391608 765 180s tcnNbrOfHets dhNbrOfLoci dhStart dhEnd dhMean c1Mean c2Mean 180s 1 765 765 554484 143663981 0.4206323 0.4031263 0.9884817 180s Number of TCNs: 1880 180s Number of DHs: 765 180s int [1:1880] 1 2 3 4 5 6 7 8 9 10 ... 180s int [1:7324] 1 2 3 4 5 6 7 8 9 10 ... 180s int [1:1880] 1 2 3 4 5 6 7 8 9 10 ... 180s Identify loci used to bootstrap DH means... 180s Heterozygous SNPs to resample for DH: 180s int [1:765] 2 3 4 5 6 8 9 10 11 12 ... 180s Identify loci used to bootstrap DH means...done 180s Identify loci used to bootstrap TCN means... 180s SNPs: 180s int [1:765] 2 3 4 5 6 8 9 10 11 12 ... 180s Non-polymorphic loci: 180s int [1:1115] 1 7 15 28 30 32 34 35 36 37 ... 180s Heterozygous SNPs to resample for TCN: 180s int [1:765] 2 3 4 5 6 8 9 10 11 12 ... 180s Homozygous SNPs to resample for TCN: 180s int(0) 180s Non-polymorphic loci to resample for TCN: 180s int [1:1115] 1 7 15 28 30 32 34 35 36 37 ... 180s Heterozygous SNPs with non-DH to resample for TCN: 180s int(0) 180s Loci to resample for TCN: 180s int [1:1880] 1 2 3 4 5 6 7 8 9 10 ... 180s Identify loci used to bootstrap TCN means...done 180s Number of (#hets, #homs, #nonSNPs): (765,0,1115) 180s Bootstrapping while preserving (#hets, #homs, #nonSNPs)... 180s Number of bootstrap samples: 100 180s Bootstrapping while preserving (#hets, #homs, #nonSNPs)...done 180s Segment #1 (chr 1, tcnId=1, dhId=1) of 7...done 180s Segment #2 (chr 1, tcnId=2, dhId=1) of 7... 180s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 180s 2 1 2 1 143663981 185240536 671 2.092452 272 180s tcnNbrOfHets dhNbrOfLoci dhStart dhEnd dhMean c1Mean c2Mean 180s 2 272 272 143663981 185240536 0.1762428 0.861836 1.230616 180s Number of TCNs: 671 180s Number of DHs: 272 180s int [1:671] 1881 1882 1883 1884 1885 1886 1887 1888 1889 1890 ... 180s int [1:7324] 1 2 3 4 5 6 7 8 9 10 ... 180s int [1:671] 1881 1882 1883 1884 1885 1886 1887 1888 1889 1890 ... 180s Identify loci used to bootstrap DH means... 180s Heterozygous SNPs to resample for DH: 180s int [1:272] 1888 1893 1894 1895 1896 1897 1901 1903 1907 1908 ... 180s Identify loci used to bootstrap DH means...done 180s Identify loci used to bootstrap TCN means... 180s SNPs: 180s int [1:272] 1888 1893 1894 1895 1896 1897 1901 1903 1907 1908 ... 180s Non-polymorphic loci: 180s int [1:399] 1881 1882 1883 1884 1885 1886 1887 1889 1890 1891 ... 180s Heterozygous SNPs to resample for TCN: 180s int [1:272] 1888 1893 1894 1895 1896 1897 1901 1903 1907 1908 ... 180s Homozygous SNPs to resample for TCN: 180s int(0) 180s Non-polymorphic loci to resample for TCN: 180s int [1:399] 1881 1882 1883 1884 1885 1886 1887 1889 1890 1891 ... 180s Heterozygous SNPs with non-DH to resample for TCN: 180s int(0) 180s Loci to resample for TCN: 180s int [1:671] 1881 1882 1883 1884 1885 1886 1887 1888 1889 1890 ... 180s Identify loci used to bootstrap TCN means...done 180s Number of (#hets, #homs, #nonSNPs): (272,0,399) 180s Bootstrapping while preserving (#hets, #homs, #nonSNPs)... 180s Number of bootstrap samples: 100 180s Bootstrapping while preserving (#hets, #homs, #nonSNPs)...done 180s Segment #2 (chr 1, tcnId=2, dhId=1) of 7...done 180s Segment #3 (chr 1, tcnId=3, dhId=1) of 7... 180s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 180s 3 1 3 1 185240536 246679946 1111 2.654512 414 180s tcnNbrOfHets dhNbrOfLoci dhStart dhEnd dhMean c1Mean c2Mean 180s 3 414 414 185240536 246679946 0.269742 0.9692395 1.685273 180s Number of TCNs: 1111 180s Number of DHs: 414 180s int [1:1111] 2552 2553 2554 2555 2556 2557 2558 2559 2560 2561 ... 180s int [1:7324] 1 2 3 4 5 6 7 8 9 10 ... 180s int [1:1111] 2552 2553 2554 2555 2556 2557 2558 2559 2560 2561 ... 180s Identify loci used to bootstrap DH means... 180s Heterozygous SNPs to resample for DH: 180s int [1:414] 2553 2554 2561 2562 2563 2568 2569 2572 2573 2574 ... 180s Identify loci used to bootstrap DH means...done 180s Identify loci used to bootstrap TCN means... 180s SNPs: 180s int [1:414] 2553 2554 2561 2562 2563 2568 2569 2572 2573 2574 ... 180s Non-polymorphic loci: 180s int [1:697] 2552 2555 2556 2557 2558 2559 2560 2564 2565 2566 ... 180s Heterozygous SNPs to resample for TCN: 180s int [1:414] 2553 2554 2561 2562 2563 2568 2569 2572 2573 2574 ... 180s Homozygous SNPs to resample for TCN: 180s int(0) 180s Non-polymorphic loci to resample for TCN: 180s int [1:697] 2552 2555 2556 2557 2558 2559 2560 2564 2565 2566 ... 180s Heterozygous SNPs with non-DH to resample for TCN: 180s int(0) 180s Loci to resample for TCN: 180s int [1:1111] 2552 2553 2554 2555 2556 2557 2558 2559 2560 2561 ... 180s Identify loci used to bootstrap TCN means...done 180s Number of (#hets, #homs, #nonSNPs): (414,0,697) 180s Bootstrapping while preserving (#hets, #homs, #nonSNPs)... 180s Number of bootstrap samples: 100 180s Bootstrapping while preserving (#hets, #homs, #nonSNPs)...done 180s Segment #3 (chr 1, tcnId=3, dhId=1) of 7...done 180s Segment #5 (chr 2, tcnId=1, dhId=1) of 7... 180s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 180s 5 2 1 1 554484 143663981 1880 1.391608 765 180s tcnNbrOfHets dhNbrOfLoci dhStart dhEnd dhMean c1Mean c2Mean 180s 5 765 765 554484 143663981 0.4206323 0.4031263 0.9884817 180s Number of TCNs: 1880 180s Number of DHs: 765 180s int [1:1880] 3663 3664 3665 3666 3667 3668 3669 3670 3671 3672 ... 180s int [1:7324] 1 2 3 4 5 6 7 8 9 10 ... 180s int [1:1880] 3663 3664 3665 3666 3667 3668 3669 3670 3671 3672 ... 180s Identify loci used to bootstrap DH means... 180s Heterozygous SNPs to resample for DH: 180s int [1:765] 3664 3665 3666 3667 3668 3670 3671 3672 3673 3674 ... 180s Identify loci used to bootstrap DH means...done 180s Identify loci used to bootstrap TCN means... 180s SNPs: 180s int [1:765] 3664 3665 3666 3667 3668 3670 3671 3672 3673 3674 ... 180s Non-polymorphic loci: 180s int [1:1115] 3663 3669 3677 3690 3692 3694 3696 3697 3698 3699 ... 180s Heterozygous SNPs to resample for TCN: 180s int [1:765] 3664 3665 3666 3667 3668 3670 3671 3672 3673 3674 ... 180s Homozygous SNPs to resample for TCN: 180s int(0) 180s Non-polymorphic loci to resample for TCN: 180s int [1:1115] 3663 3669 3677 3690 3692 3694 3696 3697 3698 3699 ... 180s Heterozygous SNPs with non-DH to resample for TCN: 180s int(0) 180s Loci to resample for TCN: 180s int [1:1880] 3663 3664 3665 3666 3667 3668 3669 3670 3671 3672 ... 180s Identify loci used to bootstrap TCN means...done 180s Number of (#hets, #homs, #nonSNPs): (765,0,1115) 180s Bootstrapping while preserving (#hets, #homs, #nonSNPs)... 180s Number of bootstrap samples: 100 180s Bootstrapping while preserving (#hets, #homs, #nonSNPs)...done 180s Segment #5 (chr 2, tcnId=1, dhId=1) of 7...done 180s Segment #6 (chr 2, tcnId=2, dhId=1) of 7... 180s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 180s 6 2 2 1 143663981 185240536 671 2.092452 272 180s tcnNbrOfHets dhNbrOfLoci dhStart dhEnd dhMean c1Mean c2Mean 180s 6 272 272 143663981 185240536 0.1762428 0.861836 1.230616 180s Number of TCNs: 671 180s Number of DHs: 272 180s int [1:671] 5543 5544 5545 5546 5547 5548 5549 5550 5551 5552 ... 180s int [1:7324] 1 2 3 4 5 6 7 8 9 10 ... 180s int [1:671] 5543 5544 5545 5546 5547 5548 5549 5550 5551 5552 ... 180s Identify loci used to bootstrap DH means... 180s Heterozygous SNPs to resample for DH: 180s int [1:272] 5550 5555 5556 5557 5558 5559 5563 5565 5569 5570 ... 180s Identify loci used to bootstrap DH means...done 180s Identify loci used to bootstrap TCN means... 180s SNPs: 180s int [1:272] 5550 5555 5556 5557 5558 5559 5563 5565 5569 5570 ... 180s Non-polymorphic loci: 180s int [1:399] 5543 5544 5545 5546 5547 5548 5549 5551 5552 5553 ... 180s Heterozygous SNPs to resample for TCN: 180s int [1:272] 5550 5555 5556 5557 5558 5559 5563 5565 5569 5570 ... 180s Homozygous SNPs to resample for TCN: 180s int(0) 180s Non-polymorphic loci to resample for TCN: 180s int [1:399] 5543 5544 5545 5546 5547 5548 5549 5551 5552 5553 ... 180s Heterozygous SNPs with non-DH to resample for TCN: 180s int(0) 180s Loci to resample for TCN: 180s int [1:671] 5543 5544 5545 5546 5547 5548 5549 5550 5551 5552 ... 180s Identify loci used to bootstrap TCN means...done 180s Number of (#hets, #homs, #nonSNPs): (272,0,399) 180s Bootstrapping while preserving (#hets, #homs, #nonSNPs)... 180s Number of bootstrap samples: 100 180s Bootstrapping while preserving (#hets, #homs, #nonSNPs)...done 180s Segment #6 (chr 2, tcnId=2, dhId=1) of 7...done 180s Segment #7 (chr 2, tcnId=3, dhId=1) of 7... 180s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 180s 7 2 3 1 185240536 246679946 1111 2.654512 414 180s tcnNbrOfHets dhNbrOfLoci dhStart dhEnd dhMean c1Mean c2Mean 180s 7 414 414 185240536 246679946 0.269742 0.9692395 1.685273 180s Number of TCNs: 1111 180s Number of DHs: 414 180s int [1:1111] 6214 6215 6216 6217 6218 6219 6220 6221 6222 6223 ... 180s int [1:7324] 1 2 3 4 5 6 7 8 9 10 ... 180s int [1:1111] 6214 6215 6216 6217 6218 6219 6220 6221 6222 6223 ... 180s Identify loci used to bootstrap DH means... 180s Heterozygous SNPs to resample for DH: 180s int [1:414] 6215 6216 6223 6224 6225 6230 6231 6234 6235 6236 ... 180s Identify loci used to bootstrap DH means...done 180s Identify loci used to bootstrap TCN means... 180s SNPs: 180s int [1:414] 6215 6216 6223 6224 6225 6230 6231 6234 6235 6236 ... 180s Non-polymorphic loci: 180s int [1:697] 6214 6217 6218 6219 6220 6221 6222 6226 6227 6228 ... 180s Heterozygous SNPs to resample for TCN: 180s int [1:414] 6215 6216 6223 6224 6225 6230 6231 6234 6235 6236 ... 180s Homozygous SNPs to resample for TCN: 180s int(0) 180s Non-polymorphic loci to resample for TCN: 180s int [1:697] 6214 6217 6218 6219 6220 6221 6222 6226 6227 6228 ... 180s Heterozygous SNPs with non-DH to resample for TCN: 180s int(0) 180s Loci to resample for TCN: 180s int [1:1111] 6214 6215 6216 6217 6218 6219 6220 6221 6222 6223 ... 180s Identify loci used to bootstrap TCN means...done 180s Number of (#hets, #homs, #nonSNPs): (414,0,697) 180s Bootstrapping while preserving (#hets, #homs, #nonSNPs)... 180s Number of bootstrap samples: 100 180s Bootstrapping while preserving (#hets, #homs, #nonSNPs)...done 180s Segment #7 (chr 2, tcnId=3, dhId=1) of 7...done 180s Bootstrapped segment mean levels 180s num [1:7, 1:100, 1:4] 1.4 2.09 2.64 NA 1.39 ... 180s - attr(*, "dimnames")=List of 3 180s ..$ : NULL 180s ..$ : NULL 180s ..$ : chr [1:4] "tcn" "dh" "c1" "c2" 180s Calculating (C1,C2) mean levels from (TCN,DH) mean levels... 180s num [1:7, 1:100, 1:4] 1.4 2.09 2.64 NA 1.39 ... 180s - attr(*, "dimnames")=List of 3 180s ..$ : NULL 180s ..$ : NULL 180s ..$ : chr [1:4] "tcn" "dh" "c1" "c2" 180s Calculating (C1,C2) mean levels from (TCN,DH) mean levels...done 180s Calculating polar (alpha,radius,manhattan) for change points... 180s num [1:6, 1:100, 1:2] -0.448 -0.131 NA NA -0.477 ... 180s - attr(*, "dimnames")=List of 3 180s ..$ : NULL 180s ..$ : NULL 180s ..$ : chr [1:2] "c1" "c2" 180s Bootstrapped change points 180s num [1:6, 1:100, 1:5] -2.65 -1.87 NA NA -2.72 ... 180s - attr(*, "dimnames")=List of 3 180s ..$ : NULL 180s ..$ : NULL 180s ..$ : chr [1:5] "alpha" "radius" "manhattan" "d1" ... 180s Calculating polar (alpha,radius,manhattan) for change points...done 180s Bootstrapping (TCN,DH,C1,C2) segment mean levels...done 180s Summarizing bootstrapped segment ('tcn', 'dh', 'c1', 'c2') data... 180s num [1:7, 1:4, 1:4] NA NA NA NA NA NA NA NA NA NA ... 180s - attr(*, "dimnames")=List of 3 180s ..$ : NULL 180s ..$ : chr [1:4] "2.5%" "5%" "95%" "97.5%" 180s ..$ : chr [1:4] "tcn" "dh" "c1" "c2" 180s Field #1 ('tcn') of 4... 180s Segment #1 of 7... 180s Segment #1 of 7...done 180s Segment #2 of 7... 180s Segment #2 of 7...done 180s Segment #3 of 7... 180s Segment #3 of 7...done 180s Segment #4 of 7... 180s Segment #4 of 7...done 180s Segment #5 of 7... 180s Segment #5 of 7...done 180s Segment #6 of 7... 180s Segment #6 of 7...done 180s Segment #7 of 7... 180s Segment #7 of 7...done 180s Field #1 ('tcn') of 4...done 180s Field #2 ('dh') of 4... 180s Segment #1 of 7... 180s Segment #1 of 7...done 180s Segment #2 of 7... 180s Segment #2 of 7...done 180s Segment #3 of 7... 180s Segment #3 of 7...done 180s Segment #4 of 7... 180s Segment #4 of 7...done 180s Segment #5 of 7... 180s Segment #5 of 7...done 180s Segment #6 of 7... 180s Segment #6 of 7...done 180s Segment #7 of 7... 180s Segment #7 of 7...done 180s Field #2 ('dh') of 4...done 180s Field #3 ('c1') of 4... 180s Segment #1 of 7... 180s Segment #1 of 7...done 180s Segment #2 of 7... 180s Segment #2 of 7...done 180s Segment #3 of 7... 180s Segment #3 of 7...done 180s Segment #4 of 7... 180s Segment #4 of 7...done 180s Segment #5 of 7... 180s Segment #5 of 7...done 180s Segment #6 of 7... 180s Segment #6 of 7...done 180s Segment #7 of 7... 180s Segment #7 of 7...done 180s Field #3 ('c1') of 4...done 180s Field #4 ('c2') of 4... 180s Segment #1 of 7... 180s Segment #1 of 7...done 180s Segment #2 of 7... 180s Segment #2 of 7...done 180s Segment #3 of 7... 180s Segment #3 of 7...done 180s Segment #4 of 7... 180s Segment #4 of 7...done 180s Segment #5 of 7... 180s Segment #5 of 7...done 180s Segment #6 of 7... 180s Segment #6 of 7...done 180s Segment #7 of 7... 180s Segment #7 of 7...done 180s Field #4 ('c2') of 4...done 180s Bootstrap statistics 180s num [1:7, 1:4, 1:4] 1.38 2.07 2.63 NA 1.38 ... 180s - attr(*, "dimnames")=List of 3 180s ..$ : NULL 180s ..$ : chr [1:4] "2.5%" "5%" "95%" "97.5%" 180s ..$ : chr [1:4] "tcn" "dh" "c1" "c2" 180s Statistical sanity checks (iff B >= 100)... 180s Available summaries: 2.5%, 5%, 95%, 97.5% 180s Available quantiles: 0.025, 0.05, 0.95, 0.975 180s num [1:7, 1:4, 1:4] 1.38 2.07 2.63 NA 1.38 ... 180s - attr(*, "dimnames")=List of 3 180s ..$ : NULL 180s ..$ : chr [1:4] "2.5%" "5%" "95%" "97.5%" 180s ..$ : chr [1:4] "tcn" "dh" "c1" "c2" 180s Field #1 ('tcn') of 4... 180s Seg 1. mean=1.39161, range=[1.38025,1.40693], n=1880 180s Seg 2. mean=2.09245, range=[2.06856,2.1165], n=671 180s Seg 3. mean=2.65451, range=[2.62678,2.6834], n=1111 180s Seg 4. mean=NA, range=[NA,NA], n=NA 180s Seg 5. mean=1.39161, range=[1.37999,1.40474], n=1880 180s Seg 6. mean=2.09245, range=[2.06923,2.11747], n=671 180s Seg 7. mean=2.65451, range=[2.62867,2.68639], n=1111 180s Field #1 ('tcn') of 4...done 180s Field #2 ('dh') of 4... 180s Seg 1. mean=0.420632, range=[0.406983,0.437756], n=765 180s Seg 2. mean=0.176243, range=[0.141232,0.202975], n=272 180s Seg 3. mean=0.269742, range=[0.245337,0.292784], n=414 180s Seg 4. mean=NA, range=[NA,NA], n=NA 180s Seg 5. mean=0.420632, range=[0.406204,0.436189], n=765 180s Seg 6. mean=0.176243, range=[0.13696,0.212132], n=272 180s Seg 7. mean=0.269742, range=[0.230034,0.296763], n=414 180s Field #2 ('dh') of 4...done 180s Field #3 ('c1') of 4... 180s Seg 1. mean=0.403126, range=[0.391189,0.413437], n=765 180s Seg 2. mean=0.861836, range=[0.833296,0.900874], n=272 180s Seg 3. mean=0.969239, range=[0.937437,1.00659], n=414 180s Seg 4. mean=NA, range=[NA,NA], n=NA 180s Seg 5. mean=0.403126, range=[0.392112,0.414529], n=765 180s Seg 6. mean=0.861836, range=[0.823193,0.907577], n=272 180s Seg 7. mean=0.969239, range=[0.931951,1.01968], n=414 180s Field #3 ('c1') of 4...done 180s Field #4 ('c2') of 4... 180s Seg 1. mean=0.988482, range=[0.974501,1.00244], n=765 180s Seg 2. mean=1.23062, range=[1.18964,1.26157], n=272 180s Seg 3. mean=1.68527, range=[1.6481,1.72497], n=414 180s Seg 4. mean=NA, range=[NA,NA], n=NA 180s Seg 5. mean=0.988482, range=[0.9761,1.00076], n=765 180s Seg 6. mean=1.23062, range=[1.18936,1.26647], n=272 180s Seg 7. mean=1.68527, range=[1.63171,1.72526], n=414 180s Field #4 ('c2') of 4...done 180s Statistical sanity checks (iff B >= 100)...done 180s Summarizing bootstrapped segment ('tcn', 'dh', 'c1', 'c2') data...done 180s Summarizing bootstrapped changepoint ('alpha', 'radius', 'manhattan', 'd1', 'd2') data... 180s num [1:6, 1:4, 1:5] NA NA NA NA NA NA NA NA NA NA ... 180s - attr(*, "dimnames")=List of 3 180s ..$ : NULL 180s ..$ : chr [1:4] "2.5%" "5%" "95%" "97.5%" 180s ..$ : chr [1:5] "alpha" "radius" "manhattan" "d1" ... 180s Field #1 ('alpha') of 5... 180s Changepoint #1 of 6... 180s Changepoint #1 of 6...done 180s Changepoint #2 of 6... 180s Changepoint #2 of 6...done 180s Changepoint #3 of 6... 180s Changepoint #3 of 6...done 180s Changepoint #4 of 6... 180s Changepoint #4 of 6...done 180s Changepoint #5 of 6... 180s Changepoint #5 of 6...done 180s Changepoint #6 of 6... 180s Changepoint #6 of 6...done 180s Field #1 ('alpha') of 5...done 180s Field #2 ('radius') of 5... 180s Changepoint #1 of 6... 180s Changepoint #1 of 6...done 180s Changepoint #2 of 6... 180s Changepoint #2 of 6...done 180s Changepoint #3 of 6... 180s Changepoint #3 of 6...done 180s Changepoint #4 of 6... 180s Changepoint #4 of 6...done 180s Changepoint #5 of 6... 180s Changepoint #5 of 6...done 180s Changepoint #6 of 6... 180s Changepoint #6 of 6...done 180s Field #2 ('radius') of 5...done 180s Field #3 ('manhattan') of 5... 180s Changepoint #1 of 6... 180s Changepoint #1 of 6...done 180s Changepoint #2 of 6... 180s Changepoint #2 of 6...done 180s Changepoint #3 of 6... 180s Changepoint #3 of 6...done 180s Changepoint #4 of 6... 180s Changepoint #4 of 6...done 180s Changepoint #5 of 6... 180s Changepoint #5 of 6...done 180s Changepoint #6 of 6... 180s Changepoint #6 of 6...done 180s Field #3 ('manhattan') of 5...done 180s Field #4 ('d1') of 5... 180s Changepoint #1 of 6... 180s Changepoint #1 of 6...done 180s Changepoint #2 of 6... 180s Changepoint #2 of 6...done 180s Changepoint #3 of 6... 180s Changepoint #3 of 6...done 180s Changepoint #4 of 6... 180s Changepoint #4 of 6...done 180s Changepoint #5 of 6... 180s Changepoint #5 of 6...done 180s Changepoint #6 of 6... 180s Changepoint #6 of 6...done 180s Field #4 ('d1') of 5...done 180s Field #5 ('d2') of 5... 180s Changepoint #1 of 6... 180s Changepoint #1 of 6...done 180s Changepoint #2 of 6... 180s Changepoint #2 of 6...done 180s Changepoint #3 of 6... 180s Changepoint #3 of 6...done 180s Changepoint #4 of 6... 180s Changepoint #4 of 6...done 180s Changepoint #5 of 6... 180s Changepoint #5 of 6...done 180s Changepoint #6 of 6... 180s Changepoint #6 of 6...done 180s Field #5 ('d2') of 5...done 180s Bootstrap statistics 180s num [1:6, 1:4, 1:5] -2.76 -1.91 NA NA -2.76 ... 180s - attr(*, "dimnames")=List of 3 180s ..$ : NULL 180s ..$ : chr [1:4] "2.5%" "5%" "95%" "97.5%" 180s ..$ : chr [1:5] "alpha" "radius" "manhattan" "d1" ... 180s Summarizing bootstrapped changepoint ('alpha', 'radius', 'manhattan', 'd1', 'd2') data...done 180s Resample (TCN,DH) signals and re-estimate summaries for segment & changepoint...done 180s > print(fit) 180s chromosome tcnId dhId start end tcnNbrOfLoci tcnMean tcnNbrOfSNPs 180s 1 1 1 1 554484 143663981 1880 1.391608 765 180s 2 1 2 1 143663981 185240536 671 2.092452 272 180s 3 1 3 1 185240536 246679946 1111 2.654512 414 180s 4 NA NA NA NA NA NA NA NA 180s 5 2 1 1 554484 143663981 1880 1.391608 765 180s 6 2 2 1 143663981 185240536 671 2.092452 272 180s 7 2 3 1 185240536 246679946 1111 2.654512 414 180s tcnNbrOfHets dhNbrOfLoci dhMean c1Mean c2Mean 180s 1 765 765 0.4206323 0.4031263 0.9884817 180s 2 272 272 0.1762428 0.8618360 1.2306156 180s 3 414 414 0.2697420 0.9692395 1.6852728 180s 4 NA NA NA NA NA 180s 5 765 765 0.4206323 0.4031263 0.9884817 180s 6 272 272 0.1762428 0.8618360 1.2306156 180s 7 414 414 0.2697420 0.9692395 1.6852728 180s > 180s > 180s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 180s > # Calling segments in allelic balance (AB) 180s > # NOTE: Ideally, this should be done on whole-genome data 180s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 180s > # Explicitly estimate the threshold in DH for calling AB 180s > # (which be done by default by the caller, if skipped here) 180s > deltaAB <- estimateDeltaAB(fit, flavor="qq(DH)", verbose=-10) 180s Estimating DH threshold for calling allelic imbalances... 180s flavor: qq(DH) 180s scale: 1 180s Estimating DH threshold for AB caller... 180s quantile #1: 0.05 180s Symmetric quantile #2: 0.9 180s Number of segments: 6 180s Weighted 5% quantile of DH: 0.199618 180s Number of segments with small DH: 2 180s Number of data points: 1342 180s Number of finite data points: 544 180s Estimate of (1-0.9):th and 50% quantiles: (0.0289919,0.176243) 180s Estimate of 0.9:th "symmetric" quantile: 0.323494 180s Estimating DH threshold for AB caller...done 180s Estimated delta: 0.323 180s Estimating DH threshold for calling allelic imbalances...done 180s > print(deltaAB) 180s [1] 0.3234938 180s > 180s > fit <- callAB(fit, delta=deltaAB, verbose=-10) 180s Calling segments of allelic balance from one-sided DH bootstrap confidence intervals... 180s delta (offset adjusting for bias in DH): 0.323493772175137 180s alpha (CI quantile; significance level): 0.05 180s Calling segments... 180s Number of segments called allelic balance (AB): 4 (57.14%) of 7 180s Calling segments...done 180s Calling segments of allelic balance from one-sided DH bootstrap confidence intervals...done 180s > print(fit) 180s chromosome tcnId dhId start end tcnNbrOfLoci tcnMean tcnNbrOfSNPs 180s 1 1 1 1 554484 143663981 1880 1.391608 765 180s 2 1 2 1 143663981 185240536 671 2.092452 272 180s 3 1 3 1 185240536 246679946 1111 2.654512 414 180s 4 NA NA NA NA NA NA NA NA 180s 5 2 1 1 554484 143663981 1880 1.391608 765 180s 6 2 2 1 143663981 185240536 671 2.092452 272 180s 7 2 3 1 185240536 246679946 1111 2.654512 414 180s tcnNbrOfHets dhNbrOfLoci dhMean c1Mean c2Mean abCall 180s 1 765 765 0.4206323 0.4031263 0.9884817 FALSE 180s 2 272 272 0.1762428 0.8618360 1.2306156 TRUE 180s 3 414 414 0.2697420 0.9692395 1.6852728 TRUE 180s 4 NA NA NA NA NA NA 180s 5 765 765 0.4206323 0.4031263 0.9884817 FALSE 180s 6 272 272 0.1762428 0.8618360 1.2306156 TRUE 180s 7 414 414 0.2697420 0.9692395 1.6852728 TRUE 180s > 180s > 180s > # Even if not explicitly specified, the estimated 180s > # threshold parameter is returned by the caller 180s > stopifnot(fit$params$deltaAB == deltaAB) 180s > 180s > 180s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 180s > # Calling segments in loss-of-heterozygosity (LOH) 180s > # NOTE: Ideally, this should be done on whole-genome data 180s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 180s > # Explicitly estimate the threshold in C1 for calling LOH 180s > # (which be done by default by the caller, if skipped here) 180s > deltaLOH <- estimateDeltaLOH(fit, flavor="minC1|nonAB", verbose=-10) 180s Estimating DH threshold for calling LOH... 180s flavor: minC1|nonAB 180s Estimating DH threshold for calling LOH as the midpoint between guessed C1=0 and C1=1... 180s Argument 'midpoint': 0.5 180s Number of segments: 6 180s Number of segments in allelic balance: 4 (66.7%) of 6 180s Number of segments not in allelic balance: 2 (33.3%) of 6 180s Number of segments in allelic balance and TCN <= 3.00: 4 (66.7%) of 6 180s C: 2.09, 2.65, 2.09, 2.65 180s Corrected C1 (=C/2): 1.05, 1.33, 1.05, 1.33 180s Number of DHs: 272, 414, 272, 414 180s Weights: 0.198, 0.302, 0.198, 0.302 180s Weighted median of (corrected) C1 in allelic balance: 1.274 180s Smallest C1 among segments not in allelic balance: 0.403 180s There are 2 segments with in total 765 heterozygous SNPs with this level. 180s There are 2 segments with in total 765 heterozygous SNPs with this level. 180s Midpoint between the two: 0.839 180s Estimating DH threshold for calling LOH as the midpoint between guessed C1=0 and C1=1...done 180s delta: 0.839 180s Estimating DH threshold for calling LOH...done 180s > print(deltaLOH) 180s [1] 0.838563 180s > 180s > fit <- callLOH(fit, delta=deltaLOH, verbose=-10) 180s Calling segments of allelic balance from one-sided DH bootstrap confidence intervals... 180s delta (offset adjusting for bias in C1): 0.838562992888546 180s alpha (CI quantile; significance level): 0.05 180s Calling segments... 180s Number of segments called low C1 (LowC1, "LOH_C1"): 3 (42.86%) of 7 180s Calling segments...done 180s Calling segments of allelic balance from one-sided DH bootstrap confidence intervals...done 180s > print(fit) 180s chromosome tcnId dhId start end tcnNbrOfLoci tcnMean tcnNbrOfSNPs 180s 1 1 1 1 554484 143663981 1880 1.391608 765 180s 2 1 2 1 143663981 185240536 671 2.092452 272 180s 3 1 3 1 185240536 246679946 1111 2.654512 414 180s 4 NA NA NA NA NA NA NA NA 180s 5 2 1 1 554484 143663981 1880 1.391608 765 180s 6 2 2 1 143663981 185240536 671 2.092452 272 180s 7 2 3 1 185240536 246679946 1111 2.654512 414 180s tcnNbrOfHets dhNbrOfLoci dhMean c1Mean c2Mean abCall lohCall 180s 1 765 765 0.4206323 0.4031263 0.9884817 FALSE TRUE 180s 2 272 272 0.1762428 0.8618360 1.2306156 TRUE NA 180s 3 414 414 0.2697420 0.9692395 1.6852728 TRUE FALSE 180s 4 NA NA NA NA NA NA NA 180s 5 765 765 0.4206323 0.4031263 0.9884817 FALSE TRUE 180s 6 272 272 0.1762428 0.8618360 1.2306156 TRUE FALSE 180s 7 414 414 0.2697420 0.9692395 1.6852728 TRUE FALSE 180s > plotTracks(fit) 180s > 180s > # Even if not explicitly specified, the estimated 180s > # threshold parameter is returned by the caller 180s > stopifnot(fit$params$deltaLOH == deltaLOH) 180s > 180s > proc.time() 180s user system elapsed 180s 1.074 0.034 1.104 180s Test segmentByNonPairedPSCBS,medianDH passed 180s 0 180s Begin test segmentByPairedPSCBS,DH 180s + [ 0 != 0 ] 180s + echo Test segmentByNonPairedPSCBS,medianDH passed 180s + echo 0 180s + echo Begin test segmentByPairedPSCBS,DH 180s + exitcode=0 180s + R CMD BATCH segmentByPairedPSCBS,DH.R 181s + cat segmentByPairedPSCBS,DH.Rout 181s 181s R version 4.5.2 (2025-10-31) -- "[Not] Part in a Rumble" 181s Copyright (C) 2025 The R Foundation for Statistical Computing 181s Platform: x86_64-pc-linux-gnu 181s 181s R is free software and comes with ABSOLUTELY NO WARRANTY. 181s You are welcome to redistribute it under certain conditions. 181s Type 'license()' or 'licence()' for distribution details. 181s 181s R is a collaborative project with many contributors. 181s Type 'contributors()' for more information and 181s 'citation()' on how to cite R or R packages in publications. 181s 181s Type 'demo()' for some demos, 'help()' for on-line help, or 181s 'help.start()' for an HTML browser interface to help. 181s Type 'q()' to quit R. 181s 181s [Previously saved workspace restored] 181s 181s > library("PSCBS") 181s PSCBS v0.68.0 (2025-04-18 19:40:02 UTC) successfully loaded. See ?PSCBS for help. 181s > 181s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 181s > # Load SNP microarray data 181s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 181s > data <- PSCBS::exampleData("paired.chr01") 181s > str(data) 181s 'data.frame': 73346 obs. of 6 variables: 181s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 181s $ x : int 1145994 2224111 2319424 2543484 2926730 2941694 3084986 3155127 3292731 3695086 ... 181s $ CT : num 1.625 1.071 1.406 1.18 0.856 ... 181s $ betaT : num 0.757 0.771 0.834 0.778 0.229 ... 181s $ CN : num 2.36 2.13 2.59 1.93 1.71 ... 181s $ betaN : num 0.827 0.875 0.887 0.884 0.103 ... 181s > 181s > # Drop single-locus outliers 181s > dataS <- dropSegmentationOutliers(data) 181s > 181s > # Run light-weight tests 181s > # Use only every 5th data point 181s > dataS <- dataS[seq(from=1, to=nrow(data), by=5),] 181s > # Number of segments (for assertion) 181s > nSegs <- 3L 181s > # Number of bootstrap samples (see below) 181s > B <- 100L 181s > 181s > str(dataS) 181s 'data.frame': 14670 obs. of 6 variables: 181s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 181s $ x : int 1145994 2941694 3710825 4240737 4276892 4464544 4714611 5095111 5034491 5158416 ... 181s $ CT : num 1.63 1.4 1.41 1.17 1.16 ... 181s $ betaT : num 0.7574 0.169 0.2357 0.2604 0.0576 ... 181s $ CN : num 2.36 2.13 2.26 2.01 2.32 ... 181s $ betaN : num 0.8274 0.5072 0.1671 0.1609 0.0421 ... 181s > R.oo::attachLocally(dataS) 181s > 181s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 181s > # Calculate DH 181s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 181s > muN <- aroma.light::callNaiveGenotypes(betaN, censorAt=c(0,1)) 181s > # SNPs are identifies as those loci that have non-missing 'betaT' & 'muN' 181s > isSnp <- (!is.na(betaT) & !is.na(muN)) 181s > isHet <- isSnp & (muN == 1/2) 181s > rho <- rep(NA_real_, length=length(muN)) 181s > rho[isHet] <- 2*abs(betaT[isHet]-1/2) 181s > 181s > 181s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 181s > # Paired PSCBS segmentation using TCN and DH only 181s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 181s > fit <- segmentByPairedPSCBS(CT, rho=rho, 181s + chromosome=chromosome, x=x, 181s + seed=0xBEEF, verbose=-10) 181s Segmenting paired tumor-normal signals using Paired PSCBS... 181s Setup up data... 181s 'data.frame': 14670 obs. of 4 variables: 181s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 181s $ x : num 1145994 2941694 3710825 4240737 4276892 ... 181s $ CT : num 1.63 1.4 1.41 1.17 1.16 ... 181s $ rho : num NA 0.662 NA NA NA ... 181s Setup up data...done 181s Dropping loci for which TCNs are missing... 181s Number of loci dropped: 12 181s Dropping loci for which TCNs are missing...done 181s Ordering data along genome... 181s 'data.frame': 14658 obs. of 4 variables: 181s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 181s $ x : num 554484 730720 782343 878522 916294 ... 181s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 181s $ rho : num NA NA NA NA NA ... 181s Ordering data along genome...done 181s Keeping only current chromosome for 'knownSegments'... 181s Chromosome: 1 181s Known segments for this chromosome: 181s [1] chromosome start end 181s <0 rows> (or 0-length row.names) 181s Keeping only current chromosome for 'knownSegments'...done 181s alphaTCN: 0.009 181s alphaDH: 0.001 181s Number of loci: 14658 181s Random seed temporarily set (seed=c(48879), kind="L'Ecuyer-CMRG") 181s Produced 2 seeds from this stream for future usage 181s Identification of change points by total copy numbers... 181s Segmenting by CBS... 181s Chromosome: 1 181s Random seed temporarily set (seed=c(10407, 1066287653, -51199871, 161854402, -1995183193, 1503453565, -747102133), kind="L'Ecuyer-CMRG") 181s Segmenting by CBS...done 181s List of 4 181s $ data :'data.frame': 14658 obs. of 4 variables: 181s ..$ chromosome: int [1:14658] 1 1 1 1 1 1 1 1 1 1 ... 181s ..$ x : num [1:14658] 554484 730720 782343 878522 916294 ... 181s ..$ y : num [1:14658] 1.88 1.8 1.59 1.64 1.53 ... 181s ..$ index : int [1:14658] 1 2 3 4 5 6 7 8 9 10 ... 181s $ output :'data.frame': 3 obs. of 6 variables: 181s ..$ sampleName: chr [1:3] NA NA NA 181s ..$ chromosome: int [1:3] 1 1 1 181s ..$ start : num [1:3] 5.54e+05 1.44e+08 1.85e+08 181s ..$ end : num [1:3] 1.44e+08 1.85e+08 2.47e+08 181s ..$ nbrOfLoci : int [1:3] 7599 2668 4391 181s ..$ mean : num [1:3] 1.39 2.07 2.63 181s $ segRows:'data.frame': 3 obs. of 2 variables: 181s ..$ startRow: int [1:3] 1 7600 10268 181s ..$ endRow : int [1:3] 7599 10267 14658 181s $ params :List of 5 181s ..$ alpha : num 0.009 181s ..$ undo : num 0 181s ..$ joinSegments : logi TRUE 181s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 181s .. ..$ chromosome: int 1 181s .. ..$ start : num -Inf 181s .. ..$ end : num Inf 181s ..$ seed : int [1:7] 10407 1066287653 -51199871 161854402 -1995183193 1503453565 -747102133 181s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 181s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.265 0 0.265 0 0 181s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 181s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 181s - attr(*, "randomSeed")= int [1:7] 10407 1066287653 -51199871 161854402 -1995183193 1503453565 -747102133 181s Identification of change points by total copy numbers...done 181s Restructure TCN segmentation results... 181s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean 181s 1 1 554484 143926517 7599 1.3859 181s 2 1 143926517 185449813 2668 2.0704 181s 3 1 185449813 247137334 4391 2.6341 181s Number of TCN segments: 3 181s Restructure TCN segmentation results...done 181s Total CN segment #1 ([ 554484,1.43927e+08]) of 3... 181s Number of TCN loci in segment: 7599 181s Locus data for TCN segment: 181s 'data.frame': 7599 obs. of 5 variables: 181s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 181s $ x : num 554484 730720 782343 878522 916294 ... 181s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 181s $ rho : num NA NA NA NA NA ... 181s $ index : int 1 2 3 4 5 6 7 8 9 10 ... 181s Number of loci: 7599 181s Number of SNPs: 2111 (27.78%) 181s Number of heterozygous SNPs: 2111 (100.00%) 181s Chromosome: 1 181s Segmenting DH signals... 181s Segmenting by CBS... 181s Chromosome: 1 181s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 181s Segmenting by CBS...done 181s List of 4 181s $ data :'data.frame': 7599 obs. of 4 variables: 181s ..$ chromosome: int [1:7599] 1 1 1 1 1 1 1 1 1 1 ... 181s ..$ x : num [1:7599] 554484 730720 782343 878522 916294 ... 181s ..$ y : num [1:7599] NA NA NA NA NA ... 181s ..$ index : int [1:7599] 1 2 3 4 5 6 7 8 9 10 ... 181s $ output :'data.frame': 1 obs. of 6 variables: 181s ..$ sampleName: chr NA 181s ..$ chromosome: int 1 181s ..$ start : num 554484 181s ..$ end : num 1.44e+08 181s ..$ nbrOfLoci : int 2111 181s ..$ mean : num 0.524 181s $ segRows:'data.frame': 1 obs. of 2 variables: 181s ..$ startRow: int 10 181s ..$ endRow : int 7594 181s $ params :List of 5 181s ..$ alpha : num 0.001 181s ..$ undo : num 0 181s ..$ joinSegments : logi TRUE 181s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 181s .. ..$ chromosome: int 1 181s .. ..$ start : num 554484 181s .. ..$ end : num 1.44e+08 181s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 181s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 181s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.017 0 0.017 0 0 181s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 181s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 181s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 181s DH segmentation (locally-indexed) rows: 181s startRow endRow 181s 1 10 7594 181s int [1:7599] 1 2 3 4 5 6 7 8 9 10 ... 181s DH segmentation rows: 181s startRow endRow 181s 1 10 7594 181s Segmenting DH signals...done 181s DH segmentation table: 181s dhStart dhEnd dhNbrOfLoci dhMean 181s 1 554484 143926517 2111 0.5237 181s startRow endRow 181s 1 10 7594 181s Rows: 181s [1] 1 181s TCN segmentation rows: 181s startRow endRow 181s 1 1 7599 181s TCN and DH segmentation rows: 181s startRow endRow 181s 1 1 7599 181s startRow endRow 181s 1 10 7594 181s NULL 181s TCN segmentation (expanded) rows: 181s startRow endRow 181s 1 1 7599 181s TCN and DH segmentation rows: 181s startRow endRow 181s 1 1 7599 181s 2 7600 10267 181s 3 10268 14658 181s startRow endRow 181s 1 10 7594 181s startRow endRow 181s 1 1 7599 181s Total CN segmentation table (expanded): 181s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 181s 1 1 554484 143926517 7599 1.3859 2111 2111 181s (TCN,DH) segmentation for one total CN segment: 181s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 181s 1 1 1 1 554484 143926517 7599 1.3859 2111 181s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 181s 1 2111 554484 143926517 2111 0.5237 181s Total CN segment #1 ([ 554484,1.43927e+08]) of 3...done 181s Total CN segment #2 ([1.43927e+08,1.8545e+08]) of 3... 181s Number of TCN loci in segment: 2668 181s Locus data for TCN segment: 181s 'data.frame': 2668 obs. of 5 variables: 181s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 181s $ x : num 1.44e+08 1.44e+08 1.44e+08 1.44e+08 1.44e+08 ... 181s $ CT : num 2.1 2.1 2.09 1.8 2.34 ... 181s $ rho : num NA NA NA NA NA NA NA NA NA NA ... 181s $ index : int 7600 7601 7602 7603 7604 7605 7606 7607 7608 7609 ... 181s Number of loci: 2668 181s Number of SNPs: 774 (29.01%) 181s Number of heterozygous SNPs: 774 (100.00%) 181s Chromosome: 1 181s Segmenting DH signals... 181s Segmenting by CBS... 181s Chromosome: 1 181s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 181s Segmenting by CBS...done 181s List of 4 181s $ data :'data.frame': 2668 obs. of 4 variables: 181s ..$ chromosome: int [1:2668] 1 1 1 1 1 1 1 1 1 1 ... 181s ..$ x : num [1:2668] 1.44e+08 1.44e+08 1.44e+08 1.44e+08 1.44e+08 ... 181s ..$ y : num [1:2668] NA NA NA NA NA NA NA NA NA NA ... 181s ..$ index : int [1:2668] 1 2 3 4 5 6 7 8 9 10 ... 181s $ output :'data.frame': 1 obs. of 6 variables: 181s ..$ sampleName: chr NA 181s ..$ chromosome: int 1 181s ..$ start : num 1.44e+08 181s ..$ end : num 1.85e+08 181s ..$ nbrOfLoci : int 774 181s ..$ mean : num 0.154 181s $ segRows:'data.frame': 1 obs. of 2 variables: 181s ..$ startRow: int 15 181s ..$ endRow : int 2664 181s $ params :List of 5 181s ..$ alpha : num 0.001 181s ..$ undo : num 0 181s ..$ joinSegments : logi TRUE 181s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 181s .. ..$ chromosome: int 1 181s .. ..$ start : num 1.44e+08 181s .. ..$ end : num 1.85e+08 181s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 181s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 181s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.005 0 0.006 0 0 181s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 181s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 181s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 181s DH segmentation (locally-indexed) rows: 181s startRow endRow 181s 1 15 2664 181s int [1:2668] 7600 7601 7602 7603 7604 7605 7606 7607 7608 7609 ... 181s DH segmentation rows: 181s startRow endRow 181s 1 7614 10263 181s Segmenting DH signals...done 181s DH segmentation table: 181s dhStart dhEnd dhNbrOfLoci dhMean 181s 1 143926517 185449813 774 0.1542 181s startRow endRow 181s 1 7614 10263 181s Rows: 181s [1] 2 181s TCN segmentation rows: 181s startRow endRow 181s 2 7600 10267 181s TCN and DH segmentation rows: 181s startRow endRow 181s 2 7600 10267 181s startRow endRow 181s 1 7614 10263 181s startRow endRow 181s 1 1 7599 181s TCN segmentation (expanded) rows: 181s startRow endRow 181s 1 1 7599 181s 2 7600 10267 181s TCN and DH segmentation rows: 181s startRow endRow 181s 1 1 7599 181s 2 7600 10267 181s 3 10268 14658 181s startRow endRow 181s 1 10 7594 181s 2 7614 10263 181s startRow endRow 181s 1 1 7599 181s 2 7600 10267 181s Total CN segmentation table (expanded): 181s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 181s 2 1 143926517 185449813 2668 2.0704 774 774 181s (TCN,DH) segmentation for one total CN segment: 181s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 181s 2 2 1 1 143926517 185449813 2668 2.0704 774 181s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 181s 2 774 143926517 185449813 774 0.1542 181s Total CN segment #2 ([1.43927e+08,1.8545e+08]) of 3...done 181s Total CN segment #3 ([1.8545e+08,2.47137e+08]) of 3... 181s Number of TCN loci in segment: 4391 181s Locus data for TCN segment: 181s 'data.frame': 4391 obs. of 5 variables: 181s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 181s $ x : num 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 181s $ CT : num 2.93 2.15 2.82 2.93 2.46 ... 181s $ rho : num NA 0.0308 NA 0.2533 NA ... 181s $ index : int 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 181s Number of loci: 4391 181s Number of SNPs: 1311 (29.86%) 181s Number of heterozygous SNPs: 1311 (100.00%) 181s Chromosome: 1 181s Segmenting DH signals... 181s Segmenting by CBS... 181s Chromosome: 1 181s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 181s Segmenting by CBS...done 181s List of 4 181s $ data :'data.frame': 4391 obs. of 4 variables: 181s ..$ chromosome: int [1:4391] 1 1 1 1 1 1 1 1 1 1 ... 181s ..$ x : num [1:4391] 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 181s ..$ y : num [1:4391] NA 0.0308 NA 0.2533 NA ... 181s ..$ index : int [1:4391] 1 2 3 4 5 6 7 8 9 10 ... 181s $ output :'data.frame': 1 obs. of 6 variables: 181s ..$ sampleName: chr NA 181s ..$ chromosome: int 1 181s ..$ start : num 1.85e+08 181s ..$ end : num 2.47e+08 181s ..$ nbrOfLoci : int 1311 181s ..$ mean : num 0.251 181s $ segRows:'data.frame': 1 obs. of 2 variables: 181s ..$ startRow: int 2 181s ..$ endRow : int 4388 181s $ params :List of 5 181s ..$ alpha : num 0.001 181s ..$ undo : num 0 181s ..$ joinSegments : logi TRUE 181s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 181s .. ..$ chromosome: int 1 181s .. ..$ start : num 1.85e+08 181s .. ..$ end : num 2.47e+08 181s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 181s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 181s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.013 0 0.014 0 0 181s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 181s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 181s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 181s DH segmentation (locally-indexed) rows: 181s startRow endRow 181s 1 2 4388 181s int [1:4391] 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 181s DH segmentation rows: 181s startRow endRow 181s 1 10269 14655 181s Segmenting DH signals...done 181s DH segmentation table: 181s dhStart dhEnd dhNbrOfLoci dhMean 181s 1 185449813 247137334 1311 0.2512 181s startRow endRow 181s 1 10269 14655 181s Rows: 181s [1] 3 181s TCN segmentation rows: 181s startRow endRow 181s 3 10268 14658 181s TCN and DH segmentation rows: 181s startRow endRow 181s 3 10268 14658 181s startRow endRow 181s 1 10269 14655 181s startRow endRow 181s 1 1 7599 181s 2 7600 10267 181s TCN segmentation (expanded) rows: 181s startRow endRow 181s 1 1 7599 181s 2 7600 10267 181s 3 10268 14658 181s TCN and DH segmentation rows: 181s startRow endRow 181s 1 1 7599 181s 2 7600 10267 181s 3 10268 14658 181s startRow endRow 181s 1 10 7594 181s 2 7614 10263 181s 3 10269 14655 181s startRow endRow 181s 1 1 7599 181s 2 7600 10267 181s 3 10268 14658 181s Total CN segmentation table (expanded): 181s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 181s 3 1 185449813 247137334 4391 2.6341 1311 1311 181s (TCN,DH) segmentation for one total CN segment: 181s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 181s 3 3 1 1 185449813 247137334 4391 2.6341 1311 181s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 181s 3 1311 185449813 247137334 1311 0.2512 181s Total CN segment #3 ([1.8545e+08,2.47137e+08]) of 3...done 181s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 181s 1 1 1 1 554484 143926517 7599 1.3859 2111 181s 2 1 2 1 143926517 185449813 2668 2.0704 774 181s 3 1 3 1 185449813 247137334 4391 2.6341 1311 181s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 181s 1 2111 554484 143926517 2111 0.5237 181s 2 774 143926517 185449813 774 0.1542 181s 3 1311 185449813 247137334 1311 0.2512 181s Calculating (C1,C2) per segment... 181s Calculating (C1,C2) per segment...done 181s Number of segments: 3 181s Segmenting paired tumor-normal signals using Paired PSCBS...done 181s Post-segmenting TCNs... 181s Number of segments: 3 181s Number of chromosomes: 1 181s [1] 1 181s Chromosome 1 ('chr01') of 1... 181s Rows: 181s [1] 1 2 3 181s Number of segments: 3 181s TCN segment #1 ('1') of 3... 181s Nothing todo. Only one DH segmentation. Skipping. 181s TCN segment #1 ('1') of 3...done 181s TCN segment #2 ('2') of 3... 181s Nothing todo. Only one DH segmentation. Skipping. 181s TCN segment #2 ('2') of 3...done 181s TCN segment #3 ('3') of 3... 181s Nothing todo. Only one DH segmentation. Skipping. 181s TCN segment #3 ('3') of 3...done 181s Chromosome 1 ('chr01') of 1...done 181s Update (C1,C2) per segment... 181s Update (C1,C2) per segment...done 181s Post-segmenting TCNs...done 181s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 181s 1 1 1 1 554484 143926517 7599 1.3859 2111 181s 2 1 2 1 143926517 185449813 2668 2.0704 774 181s 3 1 3 1 185449813 247137334 4391 2.6341 1311 181s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 181s 1 2111 554484 143926517 2111 0.5237 0.3300521 1.055848 181s 2 774 143926517 185449813 774 0.1542 0.8755722 1.194828 181s 3 1311 185449813 247137334 1311 0.2512 0.9862070 1.647893 181s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 181s 1 1 1 1 554484 143926517 7599 1.3859 2111 181s 2 1 2 1 143926517 185449813 2668 2.0704 774 181s 3 1 3 1 185449813 247137334 4391 2.6341 1311 181s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 181s 1 2111 554484 143926517 2111 0.5237 0.3300521 1.055848 181s 2 774 143926517 185449813 774 0.1542 0.8755722 1.194828 181s 3 1311 185449813 247137334 1311 0.2512 0.9862070 1.647893 181s > print(fit) 181s chromosome tcnId dhId start end tcnNbrOfLoci tcnMean tcnNbrOfSNPs 181s 1 1 1 1 554484 143926517 7599 1.3859 2111 181s 2 1 2 1 143926517 185449813 2668 2.0704 774 181s 3 1 3 1 185449813 247137334 4391 2.6341 1311 181s tcnNbrOfHets dhNbrOfLoci dhMean c1Mean c2Mean 181s 1 2111 2111 0.5237 0.3300521 1.055848 181s 2 774 774 0.1542 0.8755722 1.194828 181s 3 1311 1311 0.2512 0.9862070 1.647893 181s > 181s > # Plot results 181s > plotTracks(fit) 181s > 181s > 181s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 181s > # Bootstrap segment level estimates 181s > # (used by the AB caller, which, if skipped here, 181s > # will do it automatically) 181s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 181s > fit <- bootstrapTCNandDHByRegion(fit, B=B, verbose=-10) 181s Resample (TCN,DH) signals and re-estimate summaries for segment & changepoint... 181s Already done? 181s tcn_2.5% tcn_5% tcn_95% tcn_97.5% dh_2.5% dh_5% dh_95% dh_97.5% 181s FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE 181s c1_2.5% c1_5% c1_95% c1_97.5% c2_2.5% c2_5% c2_95% c2_97.5% 181s FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE 181s Bootstrapping (TCN,DH,C1,C2) segment mean levels... 181s Identifying heterozygous & homozygous SNPs and non-polymorphic loci... 181s Number of loci: 14658 181s Number of SNPs: 4196 181s Number of non-SNPs: 10462 181s Identifying heterozygous & homozygous SNPs and non-polymorphic loci...done 181s num [1:3, 1:100, 1:4] NA NA NA NA NA NA NA NA NA NA ... 181s - attr(*, "dimnames")=List of 3 181s ..$ : NULL 181s ..$ : NULL 181s ..$ : chr [1:4] "tcn" "dh" "c1" "c2" 181s Segment #1 (chr 1, tcnId=1, dhId=1) of 3... 181s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 181s 1 1 1 1 554484 143926517 7599 1.3859 2111 181s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 181s 1 2111 554484 143926517 2111 0.5237 0.3300521 1.055848 181s Number of TCNs: 7599 181s Number of DHs: 2111 181s int [1:7599] 1 2 3 4 5 6 7 8 9 10 ... 181s int [1:14658] 1 2 3 4 5 6 7 8 9 10 ... 181s int [1:7599] 1 2 3 4 5 6 7 8 9 10 ... 181s Identify loci used to bootstrap DH means... 181s Heterozygous SNPs to resample for DH: 181s int [1:2111] 10 12 24 28 31 33 34 39 46 48 ... 181s Identify loci used to bootstrap DH means...done 181s Identify loci used to bootstrap TCN means... 181s SNPs: 181s int [1:2111] 10 12 24 28 31 33 34 39 46 48 ... 181s Non-polymorphic loci: 181s int [1:5488] 1 2 3 4 5 6 7 8 9 11 ... 181s Heterozygous SNPs to resample for TCN: 181s int [1:2111] 10 12 24 28 31 33 34 39 46 48 ... 181s Homozygous SNPs to resample for TCN: 181s int(0) 181s Non-polymorphic loci to resample for TCN: 181s int [1:5488] 1 2 3 4 5 6 7 8 9 11 ... 181s Heterozygous SNPs with non-DH to resample for TCN: 181s int(0) 181s Loci to resample for TCN: 181s int [1:7599] 1 2 3 4 5 6 7 8 9 10 ... 181s Identify loci used to bootstrap TCN means...done 181s Number of (#hets, #homs, #nonSNPs): (2111,0,5488) 181s Bootstrapping while preserving (#hets, #homs, #nonSNPs)... 181s Number of bootstrap samples: 100 181s Bootstrapping while preserving (#hets, #homs, #nonSNPs)...done 181s Segment #1 (chr 1, tcnId=1, dhId=1) of 3...done 181s Segment #2 (chr 1, tcnId=2, dhId=1) of 3... 181s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 181s 2 1 2 1 143926517 185449813 2668 2.0704 774 181s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 181s 2 774 143926517 185449813 774 0.1542 0.8755722 1.194828 181s Number of TCNs: 2668 181s Number of DHs: 774 181s int [1:2668] 7600 7601 7602 7603 7604 7605 7606 7607 7608 7609 ... 181s int [1:14658] 1 2 3 4 5 6 7 8 9 10 ... 181s int [1:2668] 7600 7601 7602 7603 7604 7605 7606 7607 7608 7609 ... 181s Identify loci used to bootstrap DH means... 181s Heterozygous SNPs to resample for DH: 181s int [1:774] 7614 7616 7626 7627 7628 7635 7638 7639 7640 7642 ... 181s Identify loci used to bootstrap DH means...done 181s Identify loci used to bootstrap TCN means... 181s SNPs: 181s int [1:774] 7614 7616 7626 7627 7628 7635 7638 7639 7640 7642 ... 181s Non-polymorphic loci: 181s int [1:1894] 7600 7601 7602 7603 7604 7605 7606 7607 7608 7609 ... 181s Heterozygous SNPs to resample for TCN: 181s int [1:774] 7614 7616 7626 7627 7628 7635 7638 7639 7640 7642 ... 181s Homozygous SNPs to resample for TCN: 181s int(0) 181s Non-polymorphic loci to resample for TCN: 181s int [1:1894] 7600 7601 7602 7603 7604 7605 7606 7607 7608 7609 ... 181s Heterozygous SNPs with non-DH to resample for TCN: 181s int(0) 181s Loci to resample for TCN: 181s int [1:2668] 7600 7601 7602 7603 7604 7605 7606 7607 7608 7609 ... 181s Identify loci used to bootstrap TCN means...done 181s Number of (#hets, #homs, #nonSNPs): (774,0,1894) 181s Bootstrapping while preserving (#hets, #homs, #nonSNPs)... 181s Number of bootstrap samples: 100 181s Bootstrapping while preserving (#hets, #homs, #nonSNPs)...done 181s Segment #2 (chr 1, tcnId=2, dhId=1) of 3...done 181s Segment #3 (chr 1, tcnId=3, dhId=1) of 3... 181s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 181s 3 1 3 1 185449813 247137334 4391 2.6341 1311 181s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 181s 3 1311 185449813 247137334 1311 0.2512 0.986207 1.647893 181s Number of TCNs: 4391 181s Number of DHs: 1311 181s int [1:4391] 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 181s int [1:14658] 1 2 3 4 5 6 7 8 9 10 ... 181s int [1:4391] 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 181s Identify loci used to bootstrap DH means... 181s Heterozygous SNPs to resample for DH: 181s int [1:1311] 10269 10271 10281 10282 10283 10293 10295 10297 10300 10302 ... 181s Identify loci used to bootstrap DH means...done 181s Identify loci used to bootstrap TCN means... 181s SNPs: 181s int [1:1311] 10269 10271 10281 10282 10283 10293 10295 10297 10300 10302 ... 181s Non-polymorphic loci: 181s int [1:3080] 10268 10270 10272 10273 10274 10275 10276 10277 10278 10279 ... 181s Heterozygous SNPs to resample for TCN: 181s int [1:1311] 10269 10271 10281 10282 10283 10293 10295 10297 10300 10302 ... 181s Homozygous SNPs to resample for TCN: 181s int(0) 181s Non-polymorphic loci to resample for TCN: 181s int [1:3080] 10268 10270 10272 10273 10274 10275 10276 10277 10278 10279 ... 181s Heterozygous SNPs with non-DH to resample for TCN: 181s int(0) 181s Loci to resample for TCN: 181s int [1:4391] 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 181s Identify loci used to bootstrap TCN means...done 181s Number of (#hets, #homs, #nonSNPs): (1311,0,3080) 181s Bootstrapping while preserving (#hets, #homs, #nonSNPs)... 181s Number of bootstrap samples: 100 181s Bootstrapping while preserving (#hets, #homs, #nonSNPs)...done 181s Segment #3 (chr 1, tcnId=3, dhId=1) of 3...done 181s Bootstrapped segment mean levels 181s num [1:3, 1:100, 1:4] 1.38 2.08 2.63 1.38 2.07 ... 181s - attr(*, "dimnames")=List of 3 181s ..$ : NULL 181s ..$ : NULL 181s ..$ : chr [1:4] "tcn" "dh" "c1" "c2" 181s Calculating (C1,C2) mean levels from (TCN,DH) mean levels... 181s num [1:3, 1:100, 1:4] 1.38 2.08 2.63 1.38 2.07 ... 181s - attr(*, "dimnames")=List of 3 181s ..$ : NULL 181s ..$ : NULL 181s ..$ : chr [1:4] "tcn" "dh" "c1" "c2" 181s Calculating (C1,C2) mean levels from (TCN,DH) mean levels...done 181s Calculating polar (alpha,radius,manhattan) for change points... 181s num [1:2, 1:100, 1:2] -0.5588 -0.0962 -0.5365 -0.1285 -0.5378 ... 181s - attr(*, "dimnames")=List of 3 181s ..$ : NULL 181s ..$ : NULL 181s ..$ : chr [1:2] "c1" "c2" 181s Bootstrapped change points 181s num [1:2, 1:100, 1:5] -2.89 -1.78 -2.87 -1.86 -2.88 ... 181s - attr(*, "dimnames")=List of 3 181s ..$ : NULL 181s ..$ : NULL 181s ..$ : chr [1:5] "alpha" "radius" "manhattan" "d1" ... 181s Calculating polar (alpha,radius,manhattan) for change points...done 181s Bootstrapping (TCN,DH,C1,C2) segment mean levels...done 181s Summarizing bootstrapped segment ('tcn', 'dh', 'c1', 'c2') data... 181s num [1:3, 1:4, 1:4] NA NA NA NA NA NA NA NA NA NA ... 181s - attr(*, "dimnames")=List of 3 181s ..$ : NULL 181s ..$ : chr [1:4] "2.5%" "5%" "95%" "97.5%" 181s ..$ : chr [1:4] "tcn" "dh" "c1" "c2" 181s Field #1 ('tcn') of 4... 181s Segment #1 of 3... 181s Segment #1 of 3...done 181s Segment #2 of 3... 181s Segment #2 of 3...done 181s Segment #3 of 3... 181s Segment #3 of 3...done 181s Field #1 ('tcn') of 4...done 181s Field #2 ('dh') of 4... 181s Segment #1 of 3... 181s Segment #1 of 3...done 181s Segment #2 of 3... 181s Segment #2 of 3...done 181s Segment #3 of 3... 181s Segment #3 of 3...done 181s Field #2 ('dh') of 4...done 181s Field #3 ('c1') of 4... 181s Segment #1 of 3... 181s Segment #1 of 3...done 181s Segment #2 of 3... 181s Segment #2 of 3...done 181s Segment #3 of 3... 181s Segment #3 of 3...done 181s Field #3 ('c1') of 4...done 181s Field #4 ('c2') of 4... 181s Segment #1 of 3... 181s Segment #1 of 3...done 181s Segment #2 of 3... 181s Segment #2 of 3...done 181s Segment #3 of 3... 181s Segment #3 of 3...done 181s Field #4 ('c2') of 4...done 181s Bootstrap statistics 181s num [1:3, 1:4, 1:4] 1.38 2.06 2.62 1.38 2.06 ... 181s - attr(*, "dimnames")=List of 3 181s ..$ : NULL 181s ..$ : chr [1:4] "2.5%" "5%" "95%" "97.5%" 181s ..$ : chr [1:4] "tcn" "dh" "c1" "c2" 181s Statistical sanity checks (iff B >= 100)... 181s Available summaries: 2.5%, 5%, 95%, 97.5% 181s Available quantiles: 0.025, 0.05, 0.95, 0.975 181s num [1:3, 1:4, 1:4] 1.38 2.06 2.62 1.38 2.06 ... 181s - attr(*, "dimnames")=List of 3 181s ..$ : NULL 181s ..$ : chr [1:4] "2.5%" "5%" "95%" "97.5%" 181s ..$ : chr [1:4] "tcn" "dh" "c1" "c2" 181s Field #1 ('tcn') of 4... 181s Seg 1. mean=1.3859, range=[1.38092,1.3949], n=7599 181s Seg 2. mean=2.0704, range=[2.05747,2.08326], n=2668 181s Seg 3. mean=2.6341, range=[2.62068,2.64694], n=4391 181s Field #1 ('tcn') of 4...done 181s Field #2 ('dh') of 4... 181s Seg 1. mean=0.5237, range=[0.51753,0.532002], n=2111 181s Seg 2. mean=0.1542, range=[0.144468,0.16453], n=774 181s Seg 3. mean=0.2512, range=[0.242575,0.258832], n=1311 181s Field #2 ('dh') of 4...done 181s Field #3 ('c1') of 4... 181s Seg 1. mean=0.330052, range=[0.323996,0.336038], n=2111 181s Seg 2. mean=0.875572, range=[0.86318,0.887699], n=774 181s Seg 3. mean=0.986207, range=[0.975123,0.998982], n=1311 181s Field #3 ('c1') of 4...done 181s Field #4 ('c2') of 4... 181s Seg 1. mean=1.05585, range=[1.05006,1.06231], n=2111 181s Seg 2. mean=1.19483, range=[1.18417,1.2081], n=774 181s Seg 3. mean=1.64789, range=[1.63403,1.66098], n=1311 181s Field #4 ('c2') of 4...done 181s Statistical sanity checks (iff B >= 100)...done 181s Summarizing bootstrapped segment ('tcn', 'dh', 'c1', 'c2') data...done 181s Summarizing bootstrapped changepoint ('alpha', 'radius', 'manhattan', 'd1', 'd2') data... 181s num [1:2, 1:4, 1:5] NA NA NA NA NA NA NA NA NA NA ... 181s - attr(*, "dimnames")=List of 3 181s ..$ : NULL 181s ..$ : chr [1:4] "2.5%" "5%" "95%" "97.5%" 181s ..$ : chr [1:5] "alpha" "radius" "manhattan" "d1" ... 181s Field #1 ('alpha') of 5... 181s Changepoint #1 of 2... 181s Changepoint #1 of 2...done 181s Changepoint #2 of 2... 181s Changepoint #2 of 2...done 181s Field #1 ('alpha') of 5...done 181s Field #2 ('radius') of 5... 181s Changepoint #1 of 2... 181s Changepoint #1 of 2...done 181s Changepoint #2 of 2... 181s Changepoint #2 of 2...done 181s Field #2 ('radius') of 5...done 181s Field #3 ('manhattan') of 5... 181s Changepoint #1 of 2... 181s Changepoint #1 of 2...done 181s Changepoint #2 of 2... 181s Changepoint #2 of 2...done 181s Field #3 ('manhattan') of 5...done 181s Field #4 ('d1') of 5... 181s Changepoint #1 of 2... 181s Changepoint #1 of 2...done 181s Changepoint #2 of 2... 181s Changepoint #2 of 2...done 181s Field #4 ('d1') of 5...done 181s Field #5 ('d2') of 5... 181s Changepoint #1 of 2... 181s Changepoint #1 of 2...done 181s Changepoint #2 of 2... 181s Changepoint #2 of 2...done 181s Field #5 ('d2') of 5...done 181s Bootstrap statistics 181s num [1:2, 1:4, 1:5] -2.92 -1.86 -2.91 -1.85 -2.87 ... 181s - attr(*, "dimnames")=List of 3 181s ..$ : NULL 181s ..$ : chr [1:4] "2.5%" "5%" "95%" "97.5%" 181s ..$ : chr [1:5] "alpha" "radius" "manhattan" "d1" ... 181s Summarizing bootstrapped changepoint ('alpha', 'radius', 'manhattan', 'd1', 'd2') data...done 181s Resample (TCN,DH) signals and re-estimate summaries for segment & changepoint...done 181s > print(fit) 181s chromosome tcnId dhId start end tcnNbrOfLoci tcnMean tcnNbrOfSNPs 181s 1 1 1 1 554484 143926517 7599 1.3859 2111 181s 2 1 2 1 143926517 185449813 2668 2.0704 774 181s 3 1 3 1 185449813 247137334 4391 2.6341 1311 181s tcnNbrOfHets dhNbrOfLoci dhMean c1Mean c2Mean 181s 1 2111 2111 0.5237 0.3300521 1.055848 181s 2 774 774 0.1542 0.8755722 1.194828 181s 3 1311 1311 0.2512 0.9862070 1.647893 181s > plotTracks(fit) 181s > 181s > 181s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 181s > # Calling segments in allelic balance (AB) and 181s > # in loss-of-heterozygosity (LOH) 181s > # NOTE: Ideally, this should be done on whole-genome data 181s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 181s > fit <- callAB(fit, verbose=-10) 181s Calling segments of allelic balance from one-sided DH bootstrap confidence intervals... 181s delta (offset adjusting for bias in DH): 0.3466649145302 181s alpha (CI quantile; significance level): 0.05 181s Calling segments... 181s Number of segments called allelic balance (AB): 2 (66.67%) of 3 181s Calling segments...done 181s Calling segments of allelic balance from one-sided DH bootstrap confidence intervals...done 181s > fit <- callLOH(fit, verbose=-10) 181s Calling segments of allelic balance from one-sided DH bootstrap confidence intervals... 181s delta (offset adjusting for bias in C1): 0.771236438183453 181s alpha (CI quantile; significance level): 0.05 181s Calling segments... 181s Number of segments called low C1 (LowC1, "LOH_C1"): 1 (33.33%) of 3 181s Calling segments...done 181s Calling segments of allelic balance from one-sided DH bootstrap confidence intervals...done 181s > print(fit) 181s chromosome tcnId dhId start end tcnNbrOfLoci tcnMean tcnNbrOfSNPs 181s 1 1 1 1 554484 143926517 7599 1.3859 2111 181s 2 1 2 1 143926517 185449813 2668 2.0704 774 181s 3 1 3 1 185449813 247137334 4391 2.6341 1311 181s tcnNbrOfHets dhNbrOfLoci dhMean c1Mean c2Mean abCall lohCall 181s 1 2111 2111 0.5237 0.3300521 1.055848 FALSE TRUE 181s 2 774 774 0.1542 0.8755722 1.194828 TRUE FALSE 181s 3 1311 1311 0.2512 0.9862070 1.647893 TRUE FALSE 181s > plotTracks(fit) 181s > 181s > proc.time() 181s user system elapsed 181s 1.353 0.051 1.400 181s Test segmentByPairedPSCBS,DH passed 181s 0 181s Begin test segmentByPairedPSCBS,calls 181s + [ 0 != 0 ] 181s + echo Test segmentByPairedPSCBS,DH passed 181s + echo 0 181s + echo Begin test segmentByPairedPSCBS,calls 181s + exitcode=0 181s + R CMD BATCH segmentByPairedPSCBS,calls.R 184s + cat segmentByPairedPSCBS,calls.Rout 184s 184s R version 4.5.2 (2025-10-31) -- "[Not] Part in a Rumble" 184s Copyright (C) 2025 The R Foundation for Statistical Computing 184s Platform: x86_64-pc-linux-gnu 184s 184s R is free software and comes with ABSOLUTELY NO WARRANTY. 184s You are welcome to redistribute it under certain conditions. 184s Type 'license()' or 'licence()' for distribution details. 184s 184s R is a collaborative project with many contributors. 184s Type 'contributors()' for more information and 184s 'citation()' on how to cite R or R packages in publications. 184s 184s Type 'demo()' for some demos, 'help()' for on-line help, or 184s 'help.start()' for an HTML browser interface to help. 184s Type 'q()' to quit R. 184s 184s [Previously saved workspace restored] 184s 184s > library("PSCBS") 184s PSCBS v0.68.0 (2025-04-18 19:40:02 UTC) successfully loaded. See ?PSCBS for help. 184s > 184s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 184s > # Load SNP microarray data 184s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 184s > data <- PSCBS::exampleData("paired.chr01") 184s > str(data) 184s 'data.frame': 73346 obs. of 6 variables: 184s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 184s $ x : int 1145994 2224111 2319424 2543484 2926730 2941694 3084986 3155127 3292731 3695086 ... 184s $ CT : num 1.625 1.071 1.406 1.18 0.856 ... 184s $ betaT : num 0.757 0.771 0.834 0.778 0.229 ... 184s $ CN : num 2.36 2.13 2.59 1.93 1.71 ... 184s $ betaN : num 0.827 0.875 0.887 0.884 0.103 ... 184s > 184s > 184s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 184s > # Paired PSCBS segmentation 184s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 184s > # Drop single-locus outliers 184s > dataS <- dropSegmentationOutliers(data) 184s > 184s > # Find centromere 184s > gaps <- findLargeGaps(dataS, minLength=2e6) 184s > knownSegments <- gapsToSegments(gaps) 184s > 184s > 184s > # Run light-weight tests by default 184s > if (Sys.getenv("_R_CHECK_FULL_") == "") { 184s + # Use only every 5th data point 184s + dataS <- dataS[seq(from=1, to=nrow(data), by=5),] 184s + # Number of segments (for assertion) 184s + nSegs <- 4L 184s + # Number of bootstrap samples (see below) 184s + B <- 100L 184s + } else { 184s + # Full tests 184s + nSegs <- 11L 184s + B <- 1000L 184s + } 184s > 184s > str(dataS) 184s 'data.frame': 14670 obs. of 6 variables: 184s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 184s $ x : int 1145994 2941694 3710825 4240737 4276892 4464544 4714611 5095111 5034491 5158416 ... 184s $ CT : num 1.63 1.4 1.41 1.17 1.16 ... 184s $ betaT : num 0.7574 0.169 0.2357 0.2604 0.0576 ... 184s $ CN : num 2.36 2.13 2.26 2.01 2.32 ... 184s $ betaN : num 0.8274 0.5072 0.1671 0.1609 0.0421 ... 184s > 184s > # Paired PSCBS segmentation 184s > fit <- segmentByPairedPSCBS(dataS, knownSegments=knownSegments, 184s + seed=0xBEEF, verbose=-10) 184s Segmenting paired tumor-normal signals using Paired PSCBS... 184s Calling genotypes from normal allele B fractions... 184s num [1:14670] 0.8274 0.5072 0.1671 0.1609 0.0421 ... 184s Called genotypes: 184s num [1:14670] 1 0.5 0 0 0 0 1 0 1 0.5 ... 184s - attr(*, "modelFit")=List of 1 184s ..$ :List of 7 184s .. ..$ flavor : chr "density" 184s .. ..$ cn : int 2 184s .. ..$ nbrOfGenotypeGroups: int 3 184s .. ..$ tau : num [1:2] 0.315 0.677 184s .. ..$ n : int 14640 184s .. ..$ fit :Classes 'PeaksAndValleys' and 'data.frame': 5 obs. of 3 variables: 184s .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 184s .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 184s .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 184s .. ..$ fitValleys :Classes 'PeaksAndValleys' and 'data.frame': 2 obs. of 3 variables: 184s .. .. ..$ type : chr [1:2] "valley" "valley" 184s .. .. ..$ x : num [1:2] 0.315 0.677 184s .. .. ..$ density: num [1:2] 0.522 0.551 184s ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 184s muN 184s 0 0.5 1 184s 5221 4198 5251 184s Calling genotypes from normal allele B fractions...done 184s Normalizing betaT using betaN (TumorBoost)... 184s Normalized BAFs: 184s num [1:14670] 0.9301 0.1667 0.0685 0.0995 0.0155 ... 184s - attr(*, "modelFit")=List of 5 184s ..$ method : chr "normalizeTumorBoost" 184s ..$ flavor : chr "v4" 184s ..$ delta : num [1:14670] -0.17264 0.00239 0.1671 0.16085 0.04213 ... 184s .. ..- attr(*, "modelFit")=List of 1 184s .. .. ..$ :List of 7 184s .. .. .. ..$ flavor : chr "density" 184s .. .. .. ..$ cn : int 2 184s .. .. .. ..$ nbrOfGenotypeGroups: int 3 184s .. .. .. ..$ tau : num [1:2] 0.315 0.677 184s .. .. .. ..$ n : int 14640 184s .. .. .. ..$ fit :Classes 'PeaksAndValleys' and 'data.frame': 5 obs. of 3 variables: 184s .. .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 184s .. .. .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 184s .. .. .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 184s .. .. .. ..$ fitValleys :Classes 'PeaksAndValleys' and 'data.frame': 2 obs. of 3 variables: 184s .. .. .. .. ..$ type : chr [1:2] "valley" "valley" 184s .. .. .. .. ..$ x : num [1:2] 0.315 0.677 184s .. .. .. .. ..$ density: num [1:2] 0.522 0.551 184s .. .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 184s ..$ preserveScale: logi FALSE 184s ..$ scaleFactor : num NA 184s Normalizing betaT using betaN (TumorBoost)...done 184s Setup up data... 184s 'data.frame': 14670 obs. of 7 variables: 184s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 184s $ x : num 1145994 2941694 3710825 4240737 4276892 ... 184s $ CT : num 1.63 1.4 1.41 1.17 1.16 ... 184s $ betaT : num 0.7574 0.169 0.2357 0.2604 0.0576 ... 184s $ betaTN : num 0.9301 0.1667 0.0685 0.0995 0.0155 ... 184s ..- attr(*, "modelFit")=List of 5 184s .. ..$ method : chr "normalizeTumorBoost" 184s .. ..$ flavor : chr "v4" 184s .. ..$ delta : num [1:14670] -0.17264 0.00239 0.1671 0.16085 0.04213 ... 184s .. .. ..- attr(*, "modelFit")=List of 1 184s .. .. .. ..$ :List of 7 184s .. .. .. .. ..$ flavor : chr "density" 184s .. .. .. .. ..$ cn : int 2 184s .. .. .. .. ..$ nbrOfGenotypeGroups: int 3 184s .. .. .. .. ..$ tau : num [1:2] 0.315 0.677 184s .. .. .. .. ..$ n : int 14640 184s .. .. .. .. ..$ fit :Classes 'PeaksAndValleys' and 'data.frame': 5 obs. of 3 variables: 184s .. .. .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 184s .. .. .. .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 184s .. .. .. .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 184s .. .. .. .. ..$ fitValleys :Classes 'PeaksAndValleys' and 'data.frame': 2 obs. of 3 variables: 184s .. .. .. .. .. ..$ type : chr [1:2] "valley" "valley" 184s .. .. .. .. .. ..$ x : num [1:2] 0.315 0.677 184s .. .. .. .. .. ..$ density: num [1:2] 0.522 0.551 184s .. .. .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 184s .. ..$ preserveScale: logi FALSE 184s .. ..$ scaleFactor : num NA 184s $ betaN : num 0.8274 0.5072 0.1671 0.1609 0.0421 ... 184s $ muN : num 1 0.5 0 0 0 0 1 0 1 0.5 ... 184s ..- attr(*, "modelFit")=List of 1 184s .. ..$ :List of 7 184s .. .. ..$ flavor : chr "density" 184s .. .. ..$ cn : int 2 184s .. .. ..$ nbrOfGenotypeGroups: int 3 184s .. .. ..$ tau : num [1:2] 0.315 0.677 184s .. .. ..$ n : int 14640 184s .. .. ..$ fit :Classes 'PeaksAndValleys' and 'data.frame': 5 obs. of 3 variables: 184s .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 184s .. .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 184s .. .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 184s .. .. ..$ fitValleys :Classes 'PeaksAndValleys' and 'data.frame': 2 obs. of 3 variables: 184s .. .. .. ..$ type : chr [1:2] "valley" "valley" 184s .. .. .. ..$ x : num [1:2] 0.315 0.677 184s .. .. .. ..$ density: num [1:2] 0.522 0.551 184s .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 184s Setup up data...done 184s Dropping loci for which TCNs are missing... 184s Number of loci dropped: 12 184s Dropping loci for which TCNs are missing...done 184s Ordering data along genome... 184s 'data.frame': 14658 obs. of 7 variables: 184s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 184s $ x : num 554484 730720 782343 878522 916294 ... 184s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 184s $ betaT : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 184s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 184s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 184s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 184s Ordering data along genome...done 184s Keeping only current chromosome for 'knownSegments'... 184s Chromosome: 1 184s Known segments for this chromosome: 184s chromosome start end length 184s 1 1 -Inf 120992603 Inf 184s 2 1 120992604 141510002 20517398 184s 3 1 141510003 Inf Inf 184s Keeping only current chromosome for 'knownSegments'...done 184s alphaTCN: 0.009 184s alphaDH: 0.001 184s Number of loci: 14658 184s Calculating DHs... 184s Number of SNPs: 14658 184s Number of heterozygous SNPs: 4196 (28.63%) 184s Normalized DHs: 184s num [1:14658] NA NA NA NA NA ... 184s Calculating DHs...done 184s Random seed temporarily set (seed=c(48879), kind="L'Ecuyer-CMRG") 184s Produced 2 seeds from this stream for future usage 184s Identification of change points by total copy numbers... 184s Segmenting by CBS... 184s Chromosome: 1 184s Segmenting multiple segments on current chromosome... 184s Number of segments: 3 184s Random seed temporarily set (seed=c(10407, 1066287653, -51199871, 161854402, -1995183193, 1503453565, -747102133), kind="L'Ecuyer-CMRG") 184s Produced 3 seeds from this stream for future usage 184s Segmenting by CBS... 184s Chromosome: 1 184s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 184s Segmenting by CBS...done 184s Segmenting by CBS... 184s Chromosome: 1 184s Random seed temporarily set (seed=c(10407, -1924040949, -1632234809, -437763632, -1464377300, 676654412, 2080370711), kind="L'Ecuyer-CMRG") 184s Segmenting by CBS...done 184s Segmenting multiple segments on current chromosome...done 184s Segmenting by CBS...done 184s List of 4 184s $ data :'data.frame': 14658 obs. of 4 variables: 184s ..$ chromosome: int [1:14658] 1 1 1 1 1 1 1 1 1 1 ... 184s ..$ x : num [1:14658] 554484 730720 782343 878522 916294 ... 184s ..$ y : num [1:14658] 1.88 1.8 1.59 1.64 1.53 ... 184s ..$ index : int [1:14658] 1 2 3 4 5 6 7 8 9 10 ... 184s $ output :'data.frame': 4 obs. of 6 variables: 184s ..$ sampleName: chr [1:4] NA NA NA NA 184s ..$ chromosome: int [1:4] 1 1 1 1 184s ..$ start : num [1:4] 5.54e+05 1.21e+08 1.42e+08 1.85e+08 184s ..$ end : num [1:4] 1.21e+08 1.42e+08 1.85e+08 2.47e+08 184s ..$ nbrOfLoci : int [1:4] 7586 0 2681 4391 184s ..$ mean : num [1:4] 1.39 NA 2.07 2.63 184s $ segRows:'data.frame': 4 obs. of 2 variables: 184s ..$ startRow: int [1:4] 1 NA 7587 10268 184s ..$ endRow : int [1:4] 7586 NA 10267 14658 184s $ params :List of 5 184s ..$ alpha : num 0.009 184s ..$ undo : num 0 184s ..$ joinSegments : logi TRUE 184s ..$ knownSegments:'data.frame': 4 obs. of 3 variables: 184s .. ..$ chromosome: int [1:4] 1 1 2 1 184s .. ..$ start : num [1:4] -Inf -Inf -Inf 1.42e+08 184s .. ..$ end : num [1:4] 1.21e+08 Inf Inf Inf 184s ..$ seed : int [1:7] 10407 1066287653 -51199871 161854402 -1995183193 1503453565 -747102133 184s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 184s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.084 0.001 0.085 0 0 184s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 184s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 184s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 184s Identification of change points by total copy numbers...done 184s Restructure TCN segmentation results... 184s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean 184s 1 1 554484 120992603 7586 1.3853 184s 2 1 120992604 141510002 0 NA 184s 3 1 141510003 185449813 2681 2.0689 184s 4 1 185449813 247137334 4391 2.6341 184s Number of TCN segments: 4 184s Restructure TCN segmentation results...done 184s Total CN segment #1 ([ 554484,1.20993e+08]) of 4... 184s Number of TCN loci in segment: 7586 184s Locus data for TCN segment: 184s 'data.frame': 7586 obs. of 9 variables: 184s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 184s $ x : num 554484 730720 782343 878522 916294 ... 184s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 184s $ betaT : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 184s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 184s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 184s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 184s $ index : int 1 2 3 4 5 6 7 8 9 10 ... 184s $ rho : num NA NA NA NA NA ... 184s Number of loci: 7586 184s Number of SNPs: 2108 (27.79%) 184s Number of heterozygous SNPs: 2108 (100.00%) 184s Chromosome: 1 184s Segmenting DH signals... 184s Segmenting by CBS... 184s Chromosome: 1 184s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 184s Segmenting by CBS...done 184s List of 4 184s $ data :'data.frame': 7586 obs. of 4 variables: 184s ..$ chromosome: int [1:7586] 1 1 1 1 1 1 1 1 1 1 ... 184s ..$ x : num [1:7586] 554484 730720 782343 878522 916294 ... 184s ..$ y : num [1:7586] NA NA NA NA NA ... 184s ..$ index : int [1:7586] 1 2 3 4 5 6 7 8 9 10 ... 184s $ output :'data.frame': 1 obs. of 6 variables: 184s ..$ sampleName: chr NA 184s ..$ chromosome: int 1 184s ..$ start : num 554484 184s ..$ end : num 1.21e+08 184s ..$ nbrOfLoci : int 2108 184s ..$ mean : num 0.512 184s $ segRows:'data.frame': 1 obs. of 2 variables: 184s ..$ startRow: int 10 184s ..$ endRow : int 7574 184s $ params :List of 5 184s ..$ alpha : num 0.001 184s ..$ undo : num 0 184s ..$ joinSegments : logi TRUE 184s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 184s .. ..$ chromosome: int 1 184s .. ..$ start : num 554484 184s .. ..$ end : num 1.21e+08 184s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 184s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 184s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.026 0 0.026 0 0 184s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 184s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 184s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 184s DH segmentation (locally-indexed) rows: 184s startRow endRow 184s 1 10 7574 184s int [1:7586] 1 2 3 4 5 6 7 8 9 10 ... 184s DH segmentation rows: 184s startRow endRow 184s 1 10 7574 184s Segmenting DH signals...done 184s DH segmentation table: 184s dhStart dhEnd dhNbrOfLoci dhMean 184s 1 554484 120992603 2108 0.5116 184s startRow endRow 184s 1 10 7574 184s Rows: 184s [1] 1 184s TCN segmentation rows: 184s startRow endRow 184s 1 1 7586 184s TCN and DH segmentation rows: 184s startRow endRow 184s 1 1 7586 184s startRow endRow 184s 1 10 7574 184s NULL 184s TCN segmentation (expanded) rows: 184s startRow endRow 184s 1 1 7586 184s TCN and DH segmentation rows: 184s startRow endRow 184s 1 1 7586 184s 2 NA NA 184s 3 7587 10267 184s 4 10268 14658 184s startRow endRow 184s 1 10 7574 184s startRow endRow 184s 1 1 7586 184s Total CN segmentation table (expanded): 184s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 184s 1 1 554484 120992603 7586 1.3853 2108 2108 184s (TCN,DH) segmentation for one total CN segment: 184s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 184s 1 1 1 1 554484 120992603 7586 1.3853 2108 184s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 184s 1 2108 554484 120992603 2108 0.5116 184s Total CN segment #1 ([ 554484,1.20993e+08]) of 4...done 184s Total CN segment #2 ([1.20993e+08,1.4151e+08]) of 4... 184s Number of TCN loci in segment: 0 184s Locus data for TCN segment: 184s 'data.frame': 0 obs. of 9 variables: 184s $ chromosome: int 184s $ x : num 184s $ CT : num 184s $ betaT : num 184s $ betaTN : num 184s $ betaN : num 184s $ muN : num 184s $ index : int 184s $ rho : num 184s Number of loci: 0 184s Number of SNPs: 0 (NaN%) 184s Number of heterozygous SNPs: 0 (NaN%) 184s Chromosome: 1 184s Segmenting DH signals... 184s Segmenting by CBS... 184s Chromosome: NA 184s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 184s Segmenting by CBS...done 184s List of 4 184s $ data :'data.frame': 0 obs. of 4 variables: 184s ..$ chromosome: int(0) 184s ..$ x : num(0) 184s ..$ y : num(0) 184s ..$ index : int(0) 184s $ output :'data.frame': 0 obs. of 6 variables: 184s ..$ sampleName: chr(0) 184s ..$ chromosome: num(0) 184s ..$ start : num(0) 184s ..$ end : num(0) 184s ..$ nbrOfLoci : int(0) 184s ..$ mean : num(0) 184s $ segRows:'data.frame': 0 obs. of 2 variables: 184s ..$ startRow: int(0) 184s ..$ endRow : int(0) 184s $ params :List of 5 184s ..$ alpha : num 0.001 184s ..$ undo : num 0 184s ..$ joinSegments : logi TRUE 184s ..$ knownSegments:'data.frame': 0 obs. of 3 variables: 184s .. ..$ chromosome: int(0) 184s .. ..$ start : num(0) 184s .. ..$ end : num(0) 184s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 184s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 184s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.001 0 0.001 0 0 184s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 184s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 184s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 184s DH segmentation (locally-indexed) rows: 184s [1] startRow endRow 184s <0 rows> (or 0-length row.names) 184s int(0) 184s DH segmentation rows: 184s [1] startRow endRow 184s <0 rows> (or 0-length row.names) 184s Segmenting DH signals...done 184s DH segmentation table: 184s dhStart dhEnd dhNbrOfLoci dhMean 184s NA NA NA NA NA 184s startRow endRow 184s NA NA NA 184s Rows: 184s [1] 2 184s TCN segmentation rows: 184s startRow endRow 184s 2 NA NA 184s TCN and DH segmentation rows: 184s startRow endRow 184s 2 NA NA 184s startRow endRow 184s NA NA NA 184s startRow endRow 184s 1 1 7586 184s TCN segmentation (expanded) rows: 184s startRow endRow 184s 1 1 7586 184s 2 NA NA 184s TCN and DH segmentation rows: 184s startRow endRow 184s 1 1 7586 184s 2 NA NA 184s 3 7587 10267 184s 4 10268 14658 184s startRow endRow 184s 1 10 7574 184s 2 NA NA 184s startRow endRow 184s 1 1 7586 184s 2 NA NA 184s Total CN segmentation table (expanded): 184s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 184s 2 1 120992604 141510002 0 NA 0 0 184s (TCN,DH) segmentation for one total CN segment: 184s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 184s 2 2 1 1 120992604 141510002 0 NA 0 184s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 184s 2 0 NA NA NA NA 184s Total CN segment #2 ([1.20993e+08,1.4151e+08]) of 4...done 184s Total CN segment #3 ([1.4151e+08,1.8545e+08]) of 4... 184s Number of TCN loci in segment: 2681 184s Locus data for TCN segment: 184s 'data.frame': 2681 obs. of 9 variables: 184s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 184s $ x : num 1.43e+08 1.43e+08 1.43e+08 1.43e+08 1.44e+08 ... 184s $ CT : num 2.27 1.55 1.47 1.5 1.81 ... 184s $ betaT : num 0.34 0.55 0.048 0.813 0.575 ... 184s $ betaTN : num 0.441 0.629 -0.05 0.958 0.872 ... 184s $ betaN : num 0.3851 0.3933 0.0981 0.8552 0.7028 ... 184s $ muN : num 0.5 0.5 0 1 1 1 1 0.5 1 1 ... 184s $ index : int 7587 7588 7589 7590 7591 7592 7593 7594 7595 7596 ... 184s $ rho : num 0.117 0.258 NA NA NA ... 184s Number of loci: 2681 184s Number of SNPs: 777 (28.98%) 184s Number of heterozygous SNPs: 777 (100.00%) 184s Chromosome: 1 184s Segmenting DH signals... 184s Segmenting by CBS... 184s Chromosome: 1 184s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 184s Segmenting by CBS...done 184s List of 4 184s $ data :'data.frame': 2681 obs. of 4 variables: 184s ..$ chromosome: int [1:2681] 1 1 1 1 1 1 1 1 1 1 ... 184s ..$ x : num [1:2681] 1.43e+08 1.43e+08 1.43e+08 1.43e+08 1.44e+08 ... 184s ..$ y : num [1:2681] 0.117 0.258 NA NA NA ... 184s ..$ index : int [1:2681] 1 2 3 4 5 6 7 8 9 10 ... 184s $ output :'data.frame': 1 obs. of 6 variables: 184s ..$ sampleName: chr NA 184s ..$ chromosome: int 1 184s ..$ start : num 1.42e+08 184s ..$ end : num 1.85e+08 184s ..$ nbrOfLoci : int 777 184s ..$ mean : num 0.0973 184s $ segRows:'data.frame': 1 obs. of 2 variables: 184s ..$ startRow: int 1 184s ..$ endRow : int 2677 184s $ params :List of 5 184s ..$ alpha : num 0.001 184s ..$ undo : num 0 184s ..$ joinSegments : logi TRUE 184s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 184s .. ..$ chromosome: int 1 184s .. ..$ start : num 1.42e+08 184s .. ..$ end : num 1.85e+08 184s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 184s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 184s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.006 0 0.005 0 0 184s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 184s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 184s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 184s DH segmentation (locally-indexed) rows: 184s startRow endRow 184s 1 1 2677 184s int [1:2681] 7587 7588 7589 7590 7591 7592 7593 7594 7595 7596 ... 184s DH segmentation rows: 184s startRow endRow 184s 1 7587 10263 184s Segmenting DH signals...done 184s DH segmentation table: 184s dhStart dhEnd dhNbrOfLoci dhMean 184s 1 141510003 185449813 777 0.0973 184s startRow endRow 184s 1 7587 10263 184s Rows: 184s [1] 3 184s TCN segmentation rows: 184s startRow endRow 184s 3 7587 10267 184s TCN and DH segmentation rows: 184s startRow endRow 184s 3 7587 10267 184s startRow endRow 184s 1 7587 10263 184s startRow endRow 184s 1 1 7586 184s 2 NA NA 184s TCN segmentation (expanded) rows: 184s startRow endRow 184s 1 1 7586 184s 2 NA NA 184s 3 7587 10267 184s TCN and DH segmentation rows: 184s startRow endRow 184s 1 1 7586 184s 2 NA NA 184s 3 7587 10267 184s 4 10268 14658 184s startRow endRow 184s 1 10 7574 184s 2 NA NA 184s 3 7587 10263 184s startRow endRow 184s 1 1 7586 184s 2 NA NA 184s 3 7587 10267 184s Total CN segmentation table (expanded): 184s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 184s 3 1 141510003 185449813 2681 2.0689 777 777 184s (TCN,DH) segmentation for one total CN segment: 184s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 184s 3 3 1 1 141510003 185449813 2681 2.0689 777 184s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 184s 3 777 141510003 185449813 777 0.0973 184s Total CN segment #3 ([1.4151e+08,1.8545e+08]) of 4...done 184s Total CN segment #4 ([1.8545e+08,2.47137e+08]) of 4... 184s Number of TCN loci in segment: 4391 184s Locus data for TCN segment: 184s 'data.frame': 4391 obs. of 9 variables: 184s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 184s $ x : num 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 184s $ CT : num 2.93 2.15 2.82 2.93 2.46 ... 184s $ betaT : num 0.0811 0.5154 0.9473 0.3734 0.7506 ... 184s $ betaTN : num -0.169 0.609 1.028 0.525 0.968 ... 184s $ betaN : num 0.25 0.38 0.919 0.34 0.783 ... 184s $ muN : num 0 0.5 1 0.5 1 1 0 1 0 1 ... 184s $ index : int 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 184s $ rho : num NA 0.2186 NA 0.0503 NA ... 184s Number of loci: 4391 184s Number of SNPs: 1311 (29.86%) 184s Number of heterozygous SNPs: 1311 (100.00%) 184s Chromosome: 1 184s Segmenting DH signals... 184s Segmenting by CBS... 184s Chromosome: 1 184s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 184s Segmenting by CBS...done 184s List of 4 184s $ data :'data.frame': 4391 obs. of 4 variables: 184s ..$ chromosome: int [1:4391] 1 1 1 1 1 1 1 1 1 1 ... 184s ..$ x : num [1:4391] 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 184s ..$ y : num [1:4391] NA 0.2186 NA 0.0503 NA ... 184s ..$ index : int [1:4391] 1 2 3 4 5 6 7 8 9 10 ... 184s $ output :'data.frame': 1 obs. of 6 variables: 184s ..$ sampleName: chr NA 184s ..$ chromosome: int 1 184s ..$ start : num 1.85e+08 184s ..$ end : num 2.47e+08 184s ..$ nbrOfLoci : int 1311 184s ..$ mean : num 0.23 184s $ segRows:'data.frame': 1 obs. of 2 variables: 184s ..$ startRow: int 2 184s ..$ endRow : int 4388 184s $ params :List of 5 184s ..$ alpha : num 0.001 184s ..$ undo : num 0 184s ..$ joinSegments : logi TRUE 184s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 184s .. ..$ chromosome: int 1 184s .. ..$ start : num 1.85e+08 184s .. ..$ end : num 2.47e+08 184s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 184s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 184s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.01 0 0.01 0 0 184s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 184s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 184s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 184s DH segmentation (locally-indexed) rows: 184s startRow endRow 184s 1 2 4388 184s int [1:4391] 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 184s DH segmentation rows: 184s startRow endRow 184s 1 10269 14655 184s Segmenting DH signals...done 184s DH segmentation table: 184s dhStart dhEnd dhNbrOfLoci dhMean 184s 1 185449813 247137334 1311 0.2295 184s startRow endRow 184s 1 10269 14655 184s Rows: 184s [1] 4 184s TCN segmentation rows: 184s startRow endRow 184s 4 10268 14658 184s TCN and DH segmentation rows: 184s startRow endRow 184s 4 10268 14658 184s startRow endRow 184s 1 10269 14655 184s startRow endRow 184s 1 1 7586 184s 2 NA NA 184s 3 7587 10267 184s TCN segmentation (expanded) rows: 184s startRow endRow 184s 1 1 7586 184s 2 NA NA 184s 3 7587 10267 184s 4 10268 14658 184s TCN and DH segmentation rows: 184s startRow endRow 184s 1 1 7586 184s 2 NA NA 184s 3 7587 10267 184s 4 10268 14658 184s startRow endRow 184s 1 10 7574 184s 2 NA NA 184s 3 7587 10263 184s 4 10269 14655 184s startRow endRow 184s 1 1 7586 184s 2 NA NA 184s 3 7587 10267 184s 4 10268 14658 184s Total CN segmentation table (expanded): 184s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 184s 4 1 185449813 247137334 4391 2.6341 1311 1311 184s (TCN,DH) segmentation for one total CN segment: 184s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 184s 4 4 1 1 185449813 247137334 4391 2.6341 1311 184s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 184s 4 1311 185449813 247137334 1311 0.2295 184s Total CN segment #4 ([1.8545e+08,2.47137e+08]) of 4...done 184s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 184s 1 1 1 1 554484 120992603 7586 1.3853 2108 184s 2 1 2 1 120992604 141510002 0 NA 0 184s 3 1 3 1 141510003 185449813 2681 2.0689 777 184s 4 1 4 1 185449813 247137334 4391 2.6341 1311 184s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 184s 1 2108 554484 120992603 2108 0.5116 184s 2 0 NA NA NA NA 184s 3 777 141510003 185449813 777 0.0973 184s 4 1311 185449813 247137334 1311 0.2295 184s Calculating (C1,C2) per segment... 184s Calculating (C1,C2) per segment...done 184s Number of segments: 4 184s Segmenting paired tumor-normal signals using Paired PSCBS...done 184s Post-segmenting TCNs... 184s Number of segments: 4 184s Number of chromosomes: 1 184s [1] 1 184s Chromosome 1 ('chr01') of 1... 184s Rows: 184s [1] 1 2 3 4 184s Number of segments: 4 184s TCN segment #1 ('1') of 4... 184s Nothing todo. Only one DH segmentation. Skipping. 184s TCN segment #1 ('1') of 4...done 184s TCN segment #2 ('2') of 4... 184s Nothing todo. Only one DH segmentation. Skipping. 184s TCN segment #2 ('2') of 4...done 184s TCN segment #3 ('3') of 4... 184s Nothing todo. Only one DH segmentation. Skipping. 184s TCN segment #3 ('3') of 4...done 184s TCN segment #4 ('4') of 4... 184s Nothing todo. Only one DH segmentation. Skipping. 184s TCN segment #4 ('4') of 4...done 184s Chromosome 1 ('chr01') of 1...done 184s Update (C1,C2) per segment... 184s Update (C1,C2) per segment...done 184s Post-segmenting TCNs...done 184s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 184s 1 1 1 1 554484 120992603 7586 1.3853 2108 184s 2 1 2 1 120992604 141510002 0 NA 0 184s 3 1 3 1 141510003 185449813 2681 2.0689 777 184s 4 1 4 1 185449813 247137334 4391 2.6341 1311 184s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 184s 1 2108 554484 120992603 2108 0.5116 0.3382903 1.047010 184s 2 0 NA NA NA NA NA NA 184s 3 777 141510003 185449813 777 0.0973 0.9337980 1.135102 184s 4 1311 185449813 247137334 1311 0.2295 1.0147870 1.619313 184s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 184s 1 1 1 1 554484 120992603 7586 1.3853 2108 184s 2 1 2 1 120992604 141510002 0 NA 0 184s 3 1 3 1 141510003 185449813 2681 2.0689 777 184s 4 1 4 1 185449813 247137334 4391 2.6341 1311 184s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 184s 1 2108 554484 120992603 2108 0.5116 0.3382903 1.047010 184s 2 0 NA NA NA NA NA NA 184s 3 777 141510003 185449813 777 0.0973 0.9337980 1.135102 184s 4 1311 185449813 247137334 1311 0.2295 1.0147870 1.619313 184s > print(fit) 184s chromosome tcnId dhId start end tcnNbrOfLoci tcnMean tcnNbrOfSNPs 184s 1 1 1 1 554484 120992603 7586 1.3853 2108 184s 2 1 2 1 120992604 141510002 0 NA 0 184s 3 1 3 1 141510003 185449813 2681 2.0689 777 184s 4 1 4 1 185449813 247137334 4391 2.6341 1311 184s tcnNbrOfHets dhNbrOfLoci dhMean c1Mean c2Mean 184s 1 2108 2108 0.5116 0.3382903 1.047010 184s 2 0 NA NA NA NA 184s 3 777 777 0.0973 0.9337980 1.135102 184s 4 1311 1311 0.2295 1.0147870 1.619313 184s > 184s > # Plot results 184s > plotTracks(fit) 184s > 184s > # Sanity check 184s > stopifnot(nbrOfSegments(fit) == nSegs) 184s > 184s > 184s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 184s > # Bootstrap segment level estimates 184s > # (used by the AB caller, which, if skipped here, 184s > # will do it automatically) 184s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 184s > fit <- bootstrapTCNandDHByRegion(fit, B=B, verbose=-10) 184s Resample (TCN,DH) signals and re-estimate summaries for segment & changepoint... 184s Already done? 184s tcn_2.5% tcn_5% tcn_95% tcn_97.5% dh_2.5% dh_5% dh_95% dh_97.5% 184s FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE 184s c1_2.5% c1_5% c1_95% c1_97.5% c2_2.5% c2_5% c2_95% c2_97.5% 184s FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE 184s Bootstrapping (TCN,DH,C1,C2) segment mean levels... 184s Identifying heterozygous & homozygous SNPs and non-polymorphic loci... 184s Number of loci: 14658 184s Number of SNPs: 4196 184s Number of non-SNPs: 10462 184s Identifying heterozygous & homozygous SNPs and non-polymorphic loci...done 184s num [1:4, 1:100, 1:4] NA NA NA NA NA NA NA NA NA NA ... 184s - attr(*, "dimnames")=List of 3 184s ..$ : NULL 184s ..$ : NULL 184s ..$ : chr [1:4] "tcn" "dh" "c1" "c2" 184s Segment #1 (chr 1, tcnId=1, dhId=1) of 4... 184s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 184s 1 1 1 1 554484 120992603 7586 1.3853 2108 184s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 184s 1 2108 554484 120992603 2108 0.5116 0.3382903 1.04701 184s Number of TCNs: 7586 184s Number of DHs: 2108 184s int [1:7586] 1 2 3 4 5 6 7 8 9 10 ... 184s int [1:14658] 1 2 3 4 5 6 7 8 9 10 ... 184s int [1:7586] 1 2 3 4 5 6 7 8 9 10 ... 184s Identify loci used to bootstrap DH means... 184s Heterozygous SNPs to resample for DH: 184s int [1:2108] 10 12 24 28 31 33 34 39 46 48 ... 184s Identify loci used to bootstrap DH means...done 184s Identify loci used to bootstrap TCN means... 184s SNPs: 184s int [1:2108] 10 12 24 28 31 33 34 39 46 48 ... 184s Non-polymorphic loci: 184s int [1:5478] 1 2 3 4 5 6 7 8 9 11 ... 184s Heterozygous SNPs to resample for TCN: 184s int [1:2108] 10 12 24 28 31 33 34 39 46 48 ... 184s Homozygous SNPs to resample for TCN: 184s int(0) 184s Non-polymorphic loci to resample for TCN: 184s int [1:5478] 1 2 3 4 5 6 7 8 9 11 ... 184s Heterozygous SNPs with non-DH to resample for TCN: 184s int(0) 184s Loci to resample for TCN: 184s int [1:7586] 1 2 3 4 5 6 7 8 9 10 ... 184s Identify loci used to bootstrap TCN means...done 184s Number of (#hets, #homs, #nonSNPs): (2108,0,5478) 184s Bootstrapping while preserving (#hets, #homs, #nonSNPs)... 184s Number of bootstrap samples: 100 184s Bootstrapping while preserving (#hets, #homs, #nonSNPs)...done 184s Segment #1 (chr 1, tcnId=1, dhId=1) of 4...done 184s Segment #2 (chr 1, tcnId=2, dhId=1) of 4... 184s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 184s 2 1 2 1 120992604 141510002 0 NA 0 184s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 184s 2 0 NA NA 0 NA NA NA 184s Number of TCNs: 0 184s Number of DHs: 0 184s int 0 184s int [1:14658] 1 2 3 4 5 6 7 8 9 10 ... 184s int(0) 184s Identify loci used to bootstrap DH means... 184s Heterozygous SNPs to resample for DH: 184s int 0 184s Identify loci used to bootstrap DH means...done 184s Identify loci used to bootstrap TCN means... 184s SNPs: 184s int(0) 184s Non-polymorphic loci: 184s int(0) 184s Heterozygous SNPs to resample for TCN: 184s int(0) 184s Homozygous SNPs to resample for TCN: 184s int(0) 184s Non-polymorphic loci to resample for TCN: 184s int(0) 184s Heterozygous SNPs with non-DH to resample for TCN: 184s int(0) 184s Loci to resample for TCN: 184s int(0) 184s Identify loci used to bootstrap TCN means...done 184s Number of (#hets, #homs, #nonSNPs): (0,0,0) 184s Bootstrapping while preserving (#hets, #homs, #nonSNPs)... 184s Number of bootstrap samples: 100 184s Bootstrapping while preserving (#hets, #homs, #nonSNPs)...done 184s Segment #2 (chr 1, tcnId=2, dhId=1) of 4...done 184s Segment #3 (chr 1, tcnId=3, dhId=1) of 4... 184s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 184s 3 1 3 1 141510003 185449813 2681 2.0689 777 184s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 184s 3 777 141510003 185449813 777 0.0973 0.933798 1.135102 184s Number of TCNs: 2681 184s Number of DHs: 777 184s int [1:2681] 7587 7588 7589 7590 7591 7592 7593 7594 7595 7596 ... 184s int [1:14658] 1 2 3 4 5 6 7 8 9 10 ... 184s int [1:2681] 7587 7588 7589 7590 7591 7592 7593 7594 7595 7596 ... 184s Identify loci used to bootstrap DH means... 184s Heterozygous SNPs to resample for DH: 184s int [1:777] 7587 7588 7594 7614 7616 7626 7627 7628 7635 7638 ... 184s Identify loci used to bootstrap DH means...done 184s Identify loci used to bootstrap TCN means... 184s SNPs: 184s int [1:777] 7587 7588 7594 7614 7616 7626 7627 7628 7635 7638 ... 184s Non-polymorphic loci: 184s int [1:1904] 7589 7590 7591 7592 7593 7595 7596 7597 7598 7599 ... 184s Heterozygous SNPs to resample for TCN: 184s int [1:777] 7587 7588 7594 7614 7616 7626 7627 7628 7635 7638 ... 184s Homozygous SNPs to resample for TCN: 184s int(0) 184s Non-polymorphic loci to resample for TCN: 184s int [1:1904] 7589 7590 7591 7592 7593 7595 7596 7597 7598 7599 ... 184s Heterozygous SNPs with non-DH to resample for TCN: 184s int(0) 184s Loci to resample for TCN: 184s int [1:2681] 7587 7588 7589 7590 7591 7592 7593 7594 7595 7596 ... 184s Identify loci used to bootstrap TCN means...done 184s Number of (#hets, #homs, #nonSNPs): (777,0,1904) 184s Bootstrapping while preserving (#hets, #homs, #nonSNPs)... 184s Number of bootstrap samples: 100 184s Bootstrapping while preserving (#hets, #homs, #nonSNPs)...done 184s Segment #3 (chr 1, tcnId=3, dhId=1) of 4...done 184s Segment #4 (chr 1, tcnId=4, dhId=1) of 4... 184s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 184s 4 1 4 1 185449813 247137334 4391 2.6341 1311 184s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 184s 4 1311 185449813 247137334 1311 0.2295 1.014787 1.619313 184s Number of TCNs: 4391 184s Number of DHs: 1311 184s int [1:4391] 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 184s int [1:14658] 1 2 3 4 5 6 7 8 9 10 ... 184s int [1:4391] 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 184s Identify loci used to bootstrap DH means... 184s Heterozygous SNPs to resample for DH: 184s int [1:1311] 10269 10271 10281 10282 10283 10293 10295 10297 10300 10302 ... 184s Identify loci used to bootstrap DH means...done 184s Identify loci used to bootstrap TCN means... 184s SNPs: 184s int [1:1311] 10269 10271 10281 10282 10283 10293 10295 10297 10300 10302 ... 184s Non-polymorphic loci: 184s int [1:3080] 10268 10270 10272 10273 10274 10275 10276 10277 10278 10279 ... 184s Heterozygous SNPs to resample for TCN: 184s int [1:1311] 10269 10271 10281 10282 10283 10293 10295 10297 10300 10302 ... 184s Homozygous SNPs to resample for TCN: 184s int(0) 184s Non-polymorphic loci to resample for TCN: 184s int [1:3080] 10268 10270 10272 10273 10274 10275 10276 10277 10278 10279 ... 184s Heterozygous SNPs with non-DH to resample for TCN: 184s int(0) 184s Loci to resample for TCN: 184s int [1:4391] 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 184s Identify loci used to bootstrap TCN means...done 184s Number of (#hets, #homs, #nonSNPs): (1311,0,3080) 184s Bootstrapping while preserving (#hets, #homs, #nonSNPs)... 184s Number of bootstrap samples: 100 184s Bootstrapping while preserving (#hets, #homs, #nonSNPs)...done 184s Segment #4 (chr 1, tcnId=4, dhId=1) of 4...done 184s Bootstrapped segment mean levels 184s num [1:4, 1:100, 1:4] 1.39 NA 2.08 2.63 1.38 ... 184s - attr(*, "dimnames")=List of 3 184s ..$ : NULL 184s ..$ : NULL 184s ..$ : chr [1:4] "tcn" "dh" "c1" "c2" 184s Calculating (C1,C2) mean levels from (TCN,DH) mean levels... 184s num [1:4, 1:100, 1:4] 1.39 NA 2.08 2.63 1.38 ... 184s - attr(*, "dimnames")=List of 3 184s ..$ : NULL 184s ..$ : NULL 184s ..$ : chr [1:4] "tcn" "dh" "c1" "c2" 184s Calculating (C1,C2) mean levels from (TCN,DH) mean levels...done 184s Calculating polar (alpha,radius,manhattan) for change points... 184s num [1:3, 1:100, 1:2] NA NA -0.0752 NA NA ... 184s - attr(*, "dimnames")=List of 3 184s ..$ : NULL 184s ..$ : NULL 184s ..$ : chr [1:2] "c1" "c2" 184s Bootstrapped change points 184s num [1:3, 1:100, 1:5] NA NA -1.73 NA NA ... 184s - attr(*, "dimnames")=List of 3 184s ..$ : NULL 184s ..$ : NULL 184s ..$ : chr [1:5] "alpha" "radius" "manhattan" "d1" ... 184s Calculating polar (alpha,radius,manhattan) for change points...done 184s Bootstrapping (TCN,DH,C1,C2) segment mean levels...done 184s Summarizing bootstrapped segment ('tcn', 'dh', 'c1', 'c2') data... 184s num [1:4, 1:4, 1:4] NA NA NA NA NA NA NA NA NA NA ... 184s - attr(*, "dimnames")=List of 3 184s ..$ : NULL 184s ..$ : chr [1:4] "2.5%" "5%" "95%" "97.5%" 184s ..$ : chr [1:4] "tcn" "dh" "c1" "c2" 184s Field #1 ('tcn') of 4... 184s Segment #1 of 4... 184s Segment #1 of 4...done 184s Segment #2 of 4... 184s Segment #2 of 4...done 184s Segment #3 of 4... 184s Segment #3 of 4...done 184s Segment #4 of 4... 184s Segment #4 of 4...done 184s Field #1 ('tcn') of 4...done 184s Field #2 ('dh') of 4... 184s Segment #1 of 4... 184s Segment #1 of 4...done 184s Segment #2 of 4... 184s Segment #2 of 4...done 184s Segment #3 of 4... 184s Segment #3 of 4...done 184s Segment #4 of 4... 184s Segment #4 of 4...done 184s Field #2 ('dh') of 4...done 184s Field #3 ('c1') of 4... 184s Segment #1 of 4... 184s Segment #1 of 4...done 184s Segment #2 of 4... 184s Segment #2 of 4...done 184s Segment #3 of 4... 184s Segment #3 of 4...done 184s Segment #4 of 4... 184s Segment #4 of 4...done 184s Field #3 ('c1') of 4...done 184s Field #4 ('c2') of 4... 184s Segment #1 of 4... 184s Segment #1 of 4...done 184s Segment #2 of 4... 184s Segment #2 of 4...done 184s Segment #3 of 4... 184s Segment #3 of 4...done 184s Segment #4 of 4... 184s Segment #4 of 4...done 184s Field #4 ('c2') of 4...done 184s Bootstrap statistics 184s num [1:4, 1:4, 1:4] 1.38 NA 2.06 2.63 1.38 ... 184s - attr(*, "dimnames")=List of 3 184s ..$ : NULL 184s ..$ : chr [1:4] "2.5%" "5%" "95%" "97.5%" 184s ..$ : chr [1:4] "tcn" "dh" "c1" "c2" 184s Statistical sanity checks (iff B >= 100)... 184s Available summaries: 2.5%, 5%, 95%, 97.5% 184s Available quantiles: 0.025, 0.05, 0.95, 0.975 184s num [1:4, 1:4, 1:4] 1.38 NA 2.06 2.63 1.38 ... 184s - attr(*, "dimnames")=List of 3 184s ..$ : NULL 184s ..$ : chr [1:4] "2.5%" "5%" "95%" "97.5%" 184s ..$ : chr [1:4] "tcn" "dh" "c1" "c2" 184s Field #1 ('tcn') of 4... 184s Seg 1. mean=1.3853, range=[1.37909,1.39287], n=7586 184s Seg 2. mean=NA, range=[NA,NA], n=0 184s Seg 3. mean=2.0689, range=[2.05903,2.079], n=2681 184s Seg 4. mean=2.6341, range=[2.62504,2.64649], n=4391 184s Field #1 ('tcn') of 4...done 184s Field #2 ('dh') of 4... 184s Seg 1. mean=0.5116, range=[0.502148,0.519941], n=2108 184s Seg 2. mean=NA, range=[NA,NA], n=NA 184s Seg 3. mean=0.0973, range=[0.0906366,0.105818], n=777 184s Seg 4. mean=0.2295, range=[0.222919,0.237005], n=1311 184s Field #2 ('dh') of 4...done 184s Field #3 ('c1') of 4... 184s Seg 1. mean=0.33829, range=[0.332209,0.345936], n=2108 184s Seg 2. mean=NA, range=[NA,NA], n=NA 184s Seg 3. mean=0.933798, range=[0.924112,0.941776], n=777 184s Seg 4. mean=1.01479, range=[1.00381,1.02461], n=1311 184s Field #3 ('c1') of 4...done 184s Field #4 ('c2') of 4... 184s Seg 1. mean=1.04701, range=[1.03882,1.05318], n=2108 184s Seg 2. mean=NA, range=[NA,NA], n=NA 184s Seg 3. mean=1.1351, range=[1.12454,1.1465], n=777 184s Seg 4. mean=1.61931, range=[1.60862,1.63328], n=1311 184s Field #4 ('c2') of 4...done 184s Statistical sanity checks (iff B >= 100)...done 184s Summarizing bootstrapped segment ('tcn', 'dh', 'c1', 'c2') data...done 184s Summarizing bootstrapped changepoint ('alpha', 'radius', 'manhattan', 'd1', 'd2') data... 184s num [1:3, 1:4, 1:5] NA NA NA NA NA NA NA NA NA NA ... 184s - attr(*, "dimnames")=List of 3 184s ..$ : NULL 184s ..$ : chr [1:4] "2.5%" "5%" "95%" "97.5%" 184s ..$ : chr [1:5] "alpha" "radius" "manhattan" "d1" ... 184s Field #1 ('alpha') of 5... 184s Changepoint #1 of 3... 184s Changepoint #1 of 3...done 184s Changepoint #2 of 3... 184s Changepoint #2 of 3...done 184s Changepoint #3 of 3... 184s Changepoint #3 of 3...done 184s Field #1 ('alpha') of 5...done 184s Field #2 ('radius') of 5... 184s Changepoint #1 of 3... 184s Changepoint #1 of 3...done 184s Changepoint #2 of 3... 184s Changepoint #2 of 3...done 184s Changepoint #3 of 3... 184s Changepoint #3 of 3...done 184s Field #2 ('radius') of 5...done 184s Field #3 ('manhattan') of 5... 184s Changepoint #1 of 3... 184s Changepoint #1 of 3...done 184s Changepoint #2 of 3... 184s Changepoint #2 of 3...done 184s Changepoint #3 of 3... 184s Changepoint #3 of 3...done 184s Field #3 ('manhattan') of 5...done 184s Field #4 ('d1') of 5... 184s Changepoint #1 of 3... 184s Changepoint #1 of 3...done 184s Changepoint #2 of 3... 184s Changepoint #2 of 3...done 184s Changepoint #3 of 3... 184s Changepoint #3 of 3...done 184s Field #4 ('d1') of 5...done 184s Field #5 ('d2') of 5... 184s Changepoint #1 of 3... 184s Changepoint #1 of 3...done 184s Changepoint #2 of 3... 184s Changepoint #2 of 3...done 184s Changepoint #3 of 3... 184s Changepoint #3 of 3...done 184s Field #5 ('d2') of 5...done 184s Bootstrap statistics 184s num [1:3, 1:4, 1:5] NA NA -1.77 NA NA ... 184s - attr(*, "dimnames")=List of 3 184s ..$ : NULL 184s ..$ : chr [1:4] "2.5%" "5%" "95%" "97.5%" 184s ..$ : chr [1:5] "alpha" "radius" "manhattan" "d1" ... 184s Summarizing bootstrapped changepoint ('alpha', 'radius', 'manhattan', 'd1', 'd2') data...done 184s Resample (TCN,DH) signals and re-estimate summaries for segment & changepoint...done 184s > print(fit) 184s chromosome tcnId dhId start end tcnNbrOfLoci tcnMean tcnNbrOfSNPs 184s 1 1 1 1 554484 120992603 7586 1.3853 2108 184s 2 1 2 1 120992604 141510002 0 NA 0 184s 3 1 3 1 141510003 185449813 2681 2.0689 777 184s 4 1 4 1 185449813 247137334 4391 2.6341 1311 184s tcnNbrOfHets dhNbrOfLoci dhMean c1Mean c2Mean 184s 1 2108 2108 0.5116 0.3382903 1.047010 184s 2 0 NA NA NA NA 184s 3 777 777 0.0973 0.9337980 1.135102 184s 4 1311 1311 0.2295 1.0147870 1.619313 184s > plotTracks(fit) 184s > 184s > 184s > 184s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 184s > # Calling segments with run of homozygosity (ROH) 184s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 184s > fit <- callROH(fit, verbose=-10) 184s Calling ROH... 184s Segment #1 of 4... 184s Calling ROH for a single segment... 184s Number of SNPs: 7586 184s Calling ROH for a single segment...done 184s Segment #1 of 4...done 184s Segment #2 of 4... 184s Calling ROH for a single segment... 184s Number of SNPs: 0 184s Calling ROH for a single segment...done 184s Segment #2 of 4...done 184s Segment #3 of 4... 184s Calling ROH for a single segment... 184s Number of SNPs: 2681 184s Calling ROH for a single segment...done 184s Segment #3 of 4...done 184s Segment #4 of 4... 184s Calling ROH for a single segment... 184s Number of SNPs: 4391 184s Calling ROH for a single segment...done 184s Segment #4 of 4...done 184s ROH calls: 184s logi [1:4] FALSE NA FALSE FALSE 184s Mode FALSE NA's 184s logical 3 1 184s Calling ROH...done 184s > print(fit) 184s chromosome tcnId dhId start end tcnNbrOfLoci tcnMean tcnNbrOfSNPs 184s 1 1 1 1 554484 120992603 7586 1.3853 2108 184s 2 1 2 1 120992604 141510002 0 NA 0 184s 3 1 3 1 141510003 185449813 2681 2.0689 777 184s 4 1 4 1 185449813 247137334 4391 2.6341 1311 184s tcnNbrOfHets dhNbrOfLoci dhMean c1Mean c2Mean rohCall 184s 1 2108 2108 0.5116 0.3382903 1.047010 FALSE 184s 2 0 NA NA NA NA NA 184s 3 777 777 0.0973 0.9337980 1.135102 FALSE 184s 4 1311 1311 0.2295 1.0147870 1.619313 FALSE 184s > plotTracks(fit) 184s > 184s > 184s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 184s > # Estimate background 184s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 184s > kappa <- estimateKappa(fit, verbose=-10) 184s Estimate global background (including normal contamination and more)... 184s Number of segments: 3 184s Estimating threshold Delta0.5 from the empirical density of C1:s... 184s adjust: 1 184s minDensity: 0.2 184s ploidy: 2 184s All peaks: 184s type x density 184s 1 peak 0.3362194 1.101242 184s 3 peak 0.9811492 1.065635 184s C1=0 and C1=1 peaks: 184s type x density 184s 1 peak 0.3362194 1.101242 184s 3 peak 0.9811492 1.065635 184s Estimate of Delta0.5: 0.65868427808456 184s Estimating threshold Delta0.5 from the empirical density of C1:s...done 184s Number of segments with C1 < Delta0.5: 1 184s Estimate of kappa: 0.33829026 184s Estimate global background (including normal contamination and more)...done 184s Warning message: 184s In density.default(c1, weights = weights, adjust = adjust, from = from, : 184s Selecting bandwidth *not* using 'weights' 184s > print(kappa) 184s [1] 0.3382903 184s > ## [1] 0.226011 184s > 184s > 184s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 184s > # Calling segments in allelic balance (AB) 184s > # NOTE: Ideally, this should be done on whole-genome data 184s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 184s > # Explicitly estimate the threshold in DH for calling AB 184s > # (which be done by default by the caller, if skipped here) 184s > deltaAB <- estimateDeltaAB(fit, flavor="qq(DH)", verbose=-10) 184s Estimating DH threshold for calling allelic imbalances... 184s flavor: qq(DH) 184s scale: 1 184s Estimating DH threshold for AB caller... 184s quantile #1: 0.05 184s Symmetric quantile #2: 0.9 184s Number of segments: 3 184s Weighted 5% quantile of DH: 0.257710 184s Number of segments with small DH: 2 184s Number of data points: 7072 184s Number of finite data points: 2088 184s Estimate of (1-0.9):th and 50% quantiles: (0.0310411,0.163658) 184s Estimate of 0.9:th "symmetric" quantile: 0.296275 184s Estimating DH threshold for AB caller...done 184s Estimated delta: 0.296 184s Estimating DH threshold for calling allelic imbalances...done 184s > if (Sys.getenv("_R_CHECK_FULL_") == "") { 184s + # Ad hoc workaround for not utilizing all of the data 184s + # in the test, which results in a poor estimate 184s + deltaAB <- 0.165 184s + } 184s > print(deltaAB) 184s [1] 0.165 184s > ## [1] 0.1657131 184s > 184s > fit <- callAB(fit, delta=deltaAB, verbose=-10) 184s Calling segments of allelic balance from one-sided DH bootstrap confidence intervals... 184s delta (offset adjusting for bias in DH): 0.165 184s alpha (CI quantile; significance level): 0.05 184s Calling segments... 184s Number of segments called allelic balance (AB): 1 (25.00%) of 4 184s Calling segments...done 184s Calling segments of allelic balance from one-sided DH bootstrap confidence intervals...done 184s > print(fit) 184s chromosome tcnId dhId start end tcnNbrOfLoci tcnMean tcnNbrOfSNPs 184s 1 1 1 1 554484 120992603 7586 1.3853 2108 184s 2 1 2 1 120992604 141510002 0 NA 0 184s 3 1 3 1 141510003 185449813 2681 2.0689 777 184s 4 1 4 1 185449813 247137334 4391 2.6341 1311 184s tcnNbrOfHets dhNbrOfLoci dhMean c1Mean c2Mean rohCall abCall 184s 1 2108 2108 0.5116 0.3382903 1.047010 FALSE FALSE 184s 2 0 NA NA NA NA NA NA 184s 3 777 777 0.0973 0.9337980 1.135102 FALSE TRUE 184s 4 1311 1311 0.2295 1.0147870 1.619313 FALSE FALSE 184s > plotTracks(fit) 184s > 184s > # Even if not explicitly specified, the estimated 184s > # threshold parameter is returned by the caller 184s > stopifnot(fit$params$deltaAB == deltaAB) 184s > 184s > 184s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 184s > # Calling segments in loss-of-heterozygosity (LOH) 184s > # NOTE: Ideally, this should be done on whole-genome data 184s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 184s > # Explicitly estimate the threshold in C1 for calling LOH 184s > # (which be done by default by the caller, if skipped here) 184s > deltaLOH <- estimateDeltaLOH(fit, flavor="minC1|nonAB", verbose=-10) 184s Estimating DH threshold for calling LOH... 184s flavor: minC1|nonAB 184s Estimating DH threshold for calling LOH as the midpoint between guessed C1=0 and C1=1... 184s Argument 'midpoint': 0.5 184s Number of segments: 4 184s Number of segments in allelic balance: 1 (25.0%) of 4 184s Number of segments not in allelic balance: 2 (50.0%) of 4 184s Number of segments in allelic balance and TCN <= 3.00: 1 (25.0%) of 4 184s C: 2.07 184s Corrected C1 (=C/2): 1.03 184s Number of DHs: 777 184s Weights: 1 184s Weighted median of (corrected) C1 in allelic balance: 1.034 184s Smallest C1 among segments not in allelic balance: 0.338 184s There are 1 segments with in total 2108 heterozygous SNPs with this level. 184s Midpoint between the two: 0.686 184s Estimating DH threshold for calling LOH as the midpoint between guessed C1=0 and C1=1...done 184s delta: 0.686 184s Estimating DH threshold for calling LOH...done 184s > print(deltaLOH) 184s [1] 0.6863701 184s > ## [1] 0.625175 184s > 184s > fit <- callLOH(fit, delta=deltaLOH, verbose=-10) 184s Calling segments of allelic balance from one-sided DH bootstrap confidence intervals... 184s delta (offset adjusting for bias in C1): 0.68637013 184s alpha (CI quantile; significance level): 0.05 184s Calling segments... 184s Number of segments called low C1 (LowC1, "LOH_C1"): 1 (25.00%) of 4 184s Calling segments...done 184s Calling segments of allelic balance from one-sided DH bootstrap confidence intervals...done 184s > print(fit) 184s chromosome tcnId dhId start end tcnNbrOfLoci tcnMean tcnNbrOfSNPs 184s 1 1 1 1 554484 120992603 7586 1.3853 2108 184s 2 1 2 1 120992604 141510002 0 NA 0 184s 3 1 3 1 141510003 185449813 2681 2.0689 777 184s 4 1 4 1 185449813 247137334 4391 2.6341 1311 184s tcnNbrOfHets dhNbrOfLoci dhMean c1Mean c2Mean rohCall abCall lohCall 184s 1 2108 2108 0.5116 0.3382903 1.047010 FALSE FALSE TRUE 184s 2 0 NA NA NA NA NA NA NA 184s 3 777 777 0.0973 0.9337980 1.135102 FALSE TRUE FALSE 184s 4 1311 1311 0.2295 1.0147870 1.619313 FALSE FALSE FALSE 184s > plotTracks(fit) 184s > 184s > # Even if not explicitly specified, the estimated 184s > # threshold parameter is returned by the caller 184s > stopifnot(fit$params$deltaLOH == deltaLOH) 184s > 184s > 184s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 184s > # Calling segments that are gained, copy neutral, and lost 184s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 184s > fit <- callGNL(fit, verbose=-10) 184s Calling gain, neutral, and loss based TCNs of AB segments... 184s Calling neutral TCNs... 184s callCopyNeutralByTCNofAB... 184s Alpha: 0.05 184s Delta CN: 0.33085487 184s Calling copy-neutral segments... 184s Retrieve TCN confidence intervals for all segments... 184s Interval: [0.025,0.975] 184s Retrieve TCN confidence intervals for all segments...done 184s Estimating TCN confidence interval of copy-neutral AB segments... 184s calcStatsForCopyNeutralABs... 184s Identifying copy neutral AB segments... 184s Number of AB segments: 1 184s Identifying segments that are copy neutral states... 184s Number of segments in allelic balance: 1 184s Identifying segments that are copy neutral states...done 184s Number of copy-neutral AB segments: 1 184s Extracting all copy neutral AB segments across all chromosomes into one big segment... 184s chromosome tcnId dhId start end tcnNbrOfLoci tcnMean tcnNbrOfSNPs 184s 3 1 3 1 141510003 185449813 2681 2.0689 777 184s tcnNbrOfHets dhNbrOfLoci dhMean c1Mean c2Mean rohCall abCall lohCall 184s 3 777 777 0.0973 0.933798 1.135102 FALSE TRUE FALSE 184s Extracting all copy neutral AB segments across all chromosomes into one big segment...done 184s Identifying copy neutral AB segments...done 184s Bootstrap the identified copy-neutral states... 184s Bootstrap the identified copy-neutral states...done 184s tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets dhNbrOfLoci dhMean c1Mean 184s 3 2681 2.0689 777 777 777 0.0973 0.933798 184s c2Mean tcn_2.5% tcn_5% tcn_95% tcn_97.5% dh_2.5% dh_5% dh_95% 184s 3 1.135102 2.055164 2.057694 2.078831 2.081454 0.08974138 0.09080508 0.1035891 184s dh_97.5% c1_2.5% c1_5% c1_95% c1_97.5% c2_2.5% c2_5% c2_95% 184s 3 0.1050478 0.923788 0.925412 0.9417056 0.9433752 1.124908 1.126631 1.143571 184s c2_97.5% 184s 3 1.145214 184s calcStatsForCopyNeutralABs...done 184s Bootstrap statistics for copy-neutral AB segments: 184s tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets dhNbrOfLoci dhMean c1Mean 184s 3 2681 2.0689 777 777 777 0.0973 0.933798 184s c2Mean tcn_2.5% tcn_5% tcn_95% tcn_97.5% dh_2.5% dh_5% dh_95% 184s 3 1.135102 2.055164 2.057694 2.078831 2.081454 0.08974138 0.09080508 0.1035891 184s dh_97.5% c1_2.5% c1_5% c1_95% c1_97.5% c2_2.5% c2_5% c2_95% 184s 3 0.1050478 0.923788 0.925412 0.9417056 0.9433752 1.124908 1.126631 1.143571 184s c2_97.5% 184s 3 1.145214 184s [1] "TCN statistics:" 184s tcnMean tcn_2.5% tcn_5% tcn_95% tcn_97.5% 184s 2.068900 2.055164 2.057694 2.078831 2.081454 184s 95%-confidence interval of TCN mean for the copy-neutral state: [2.05516,2.08145] (mean=2.0689) 184s Estimating TCN confidence interval of copy-neutral AB segments...done 184s Identify all copy-neutral segments... 184s DeltaCN: +/-0.330855 184s Call ("acceptance") region: [1.72431,2.41231] 184s Total number of segments: 4 184s Number of segments called allelic balance: 1 184s Number of segments called copy neutral: 1 184s Number of AB segments called copy neutral: 1 184s Number of non-AB segments called copy neutral: 0 184s Identify all copy-neutral segments...done 184s Calling copy-neutral segments...done 184s callCopyNeutralByTCNofAB...done 184s Calling neutral TCNs...done 184s Number of NTCN calls: 1 (25.00%) of 4 184s Mean TCN of AB segments: 2.06831 184s Calling loss... 184s Number of loss calls: 1 (25.00%) of 4 184s Calling loss...done 184s Calling gain... 184s Number of loss calls: 1 (25.00%) of 4 184s Calling gain...done 184s Calling gain, neutral, and loss based TCNs of AB segments...done 184s Warning message: 184s In density.default(c1, weights = weights, adjust = adjust, from = from, : 184s Selecting bandwidth *not* using 'weights' 184s > print(fit) 184s chromosome tcnId dhId start end tcnNbrOfLoci tcnMean tcnNbrOfSNPs 184s 1 1 1 1 554484 120992603 7586 1.3853 2108 184s 2 1 2 1 120992604 141510002 0 NA 0 184s 3 1 3 1 141510003 185449813 2681 2.0689 777 184s 4 1 4 1 185449813 247137334 4391 2.6341 1311 184s tcnNbrOfHets dhNbrOfLoci dhMean c1Mean c2Mean rohCall abCall lohCall 184s 1 2108 2108 0.5116 0.3382903 1.047010 FALSE FALSE TRUE 184s 2 0 NA NA NA NA NA NA NA 184s 3 777 777 0.0973 0.9337980 1.135102 FALSE TRUE FALSE 184s 4 1311 1311 0.2295 1.0147870 1.619313 FALSE FALSE FALSE 184s ntcnCall lossCall gainCall 184s 1 FALSE TRUE FALSE 184s 2 NA NA NA 184s 3 TRUE FALSE FALSE 184s 4 FALSE FALSE TRUE 184s > plotTracks(fit) 184s > 184s > proc.time() 184s user system elapsed 184s 2.159 0.049 2.207 184s Test segmentByPairedPSCBS,calls passed 184s 0 184s Begin test segmentByPairedPSCBS,futures 184s + [ 0 != 0 ] 184s + echo Test segmentByPairedPSCBS,calls passed 184s + echo 0 184s + echo Begin test segmentByPairedPSCBS,futures 184s + exitcode=0 184s + R CMD BATCH segmentByPairedPSCBS,futures.R 190s + cat segmentByPairedPSCBS,futures.Rout 190s 190s R version 4.5.2 (2025-10-31) -- "[Not] Part in a Rumble" 190s Copyright (C) 2025 The R Foundation for Statistical Computing 190s Platform: x86_64-pc-linux-gnu 190s 190s R is free software and comes with ABSOLUTELY NO WARRANTY. 190s You are welcome to redistribute it under certain conditions. 190s Type 'license()' or 'licence()' for distribution details. 190s 190s R is a collaborative project with many contributors. 190s Type 'contributors()' for more information and 190s 'citation()' on how to cite R or R packages in publications. 190s 190s Type 'demo()' for some demos, 'help()' for on-line help, or 190s 'help.start()' for an HTML browser interface to help. 190s Type 'q()' to quit R. 190s 190s [Previously saved workspace restored] 190s 190s > library(PSCBS) 190s PSCBS v0.68.0 (2025-04-18 19:40:02 UTC) successfully loaded. See ?PSCBS for help. 190s > library(utils) 190s > 190s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 190s > # Load SNP microarray data 190s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 190s > data <- PSCBS::exampleData("paired.chr01") 190s > 190s > 190s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 190s > # Paired PSCBS segmentation 190s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 190s > # Drop single-locus outliers 190s > dataS <- dropSegmentationOutliers(data) 190s > 190s > # Run light-weight tests by default 190s > if (Sys.getenv("_R_CHECK_FULL_") == "") { 190s + # Use only every 5th data point 190s + dataS <- dataS[seq(from=1, to=nrow(data), by=5),] 190s + # Number of segments (for assertion) 190s + nSegs <- 4L 190s + } else { 190s + # Full tests 190s + nSegs <- 11L 190s + } 190s > 190s > str(dataS) 190s 'data.frame': 14670 obs. of 6 variables: 190s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 190s $ x : int 1145994 2941694 3710825 4240737 4276892 4464544 4714611 5095111 5034491 5158416 ... 190s $ CT : num 1.63 1.4 1.41 1.17 1.16 ... 190s $ betaT : num 0.7574 0.169 0.2357 0.2604 0.0576 ... 190s $ CN : num 2.36 2.13 2.26 2.01 2.32 ... 190s $ betaN : num 0.8274 0.5072 0.1671 0.1609 0.0421 ... 190s > 190s > 190s > ## Create multiple chromosomes 190s > data <- list() 190s > for (cc in 1:3) { 190s + dataS$chromosome <- cc 190s + data[[cc]] <- dataS 190s + } 190s > data <- Reduce(rbind, data) 190s > str(data) 190s 'data.frame': 44010 obs. of 6 variables: 190s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 190s $ x : int 1145994 2941694 3710825 4240737 4276892 4464544 4714611 5095111 5034491 5158416 ... 190s $ CT : num 1.63 1.4 1.41 1.17 1.16 ... 190s $ betaT : num 0.7574 0.169 0.2357 0.2604 0.0576 ... 190s $ CN : num 2.36 2.13 2.26 2.01 2.32 ... 190s $ betaN : num 0.8274 0.5072 0.1671 0.1609 0.0421 ... 190s > 190s > 190s > message("*** segmentByPairedPSCBS() via futures ...") 190s *** segmentByPairedPSCBS() via futures ... 190s > 190s > library("future") 190s > oplan <- plan() 190s > 190s > strategies <- c("sequential", "multisession") 190s > 190s > ## Test 'future.batchtools' futures? 190s > pkg <- "future.batchtools" 190s > if (require(pkg, character.only=TRUE)) { 190s + strategies <- c(strategies, "batchtools_local") 190s + } 190s Loading required package: future.batchtools 190s Warning message: 190s In library(package, lib.loc = lib.loc, character.only = TRUE, logical.return = TRUE, : 190s there is no package called 'future.batchtools' 190s > 190s > message("Future strategies to test: ", paste(sQuote(strategies), collapse=", ")) 190s Future strategies to test: 'sequential', 'multisession' 190s > 190s > fits <- list() 190s > for (strategy in strategies) { 190s + message(sprintf("- segmentByPairedPSCBS() using '%s' futures ...", strategy)) 190s + plan(strategy) 190s + fit <- segmentByPairedPSCBS(data, seed=0xBEEF, verbose=TRUE) 190s + fits[[strategy]] <- fit 190s + equal <- all.equal(fit, fits[[1]]) 190s + if (!equal) { 190s + str(fit) 190s + str(fits[[1]]) 190s + print(equal) 190s + stop(sprintf("segmentByPairedPSCBS() using '%s' futures does not produce the same results as when using '%s' futures", strategy, names(fits)[1])) 190s + } 190s + } 190s - segmentByPairedPSCBS() using 'sequential' futures ... 190s Segmenting paired tumor-normal signals using Paired PSCBS... 190s Calling genotypes from normal allele B fractions... 190s num [1:44010] 0.8274 0.5072 0.1671 0.1609 0.0421 ... 190s Called genotypes: 190s num [1:44010] 1 0.5 0 0 0 0 1 0 1 0.5 ... 190s - attr(*, "modelFit")=List of 1 190s ..$ :List of 7 190s .. ..$ flavor : chr "density" 190s .. ..$ cn : int 2 190s .. ..$ nbrOfGenotypeGroups: int 3 190s .. ..$ tau : num [1:2] 0.312 0.678 190s .. ..$ n : int 43920 190s .. ..$ fit :Classes 'PeaksAndValleys' and 'data.frame': 5 obs. of 3 variables: 190s .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 190s .. .. ..$ x : num [1:5] 0.0999 0.312 0.4986 0.6775 0.8922 190s .. .. ..$ density: num [1:5] 1.622 0.465 1.125 0.496 1.587 190s .. ..$ fitValleys :Classes 'PeaksAndValleys' and 'data.frame': 2 obs. of 3 variables: 190s .. .. ..$ type : chr [1:2] "valley" "valley" 190s .. .. ..$ x : num [1:2] 0.312 0.678 190s .. .. ..$ density: num [1:2] 0.465 0.496 190s ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 190s muN 190s 0 0.5 1 190s 15627 12633 15750 190s Calling genotypes from normal allele B fractions...done 190s Normalizing betaT using betaN (TumorBoost)... 190s Normalized BAFs: 190s num [1:44010] 0.9301 0.1667 0.0685 0.0995 0.0155 ... 190s - attr(*, "modelFit")=List of 5 190s ..$ method : chr "normalizeTumorBoost" 190s ..$ flavor : chr "v4" 190s ..$ delta : num [1:44010] -0.17264 0.00239 0.1671 0.16085 0.04213 ... 190s .. ..- attr(*, "modelFit")=List of 1 190s .. .. ..$ :List of 7 190s .. .. .. ..$ flavor : chr "density" 190s .. .. .. ..$ cn : int 2 190s .. .. .. ..$ nbrOfGenotypeGroups: int 3 190s .. .. .. ..$ tau : num [1:2] 0.312 0.678 190s .. .. .. ..$ n : int 43920 190s .. .. .. ..$ fit :Classes 'PeaksAndValleys' and 'data.frame': 5 obs. of 3 variables: 190s .. .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 190s .. .. .. .. ..$ x : num [1:5] 0.0999 0.312 0.4986 0.6775 0.8922 190s .. .. .. .. ..$ density: num [1:5] 1.622 0.465 1.125 0.496 1.587 190s .. .. .. ..$ fitValleys :Classes 'PeaksAndValleys' and 'data.frame': 2 obs. of 3 variables: 190s .. .. .. .. ..$ type : chr [1:2] "valley" "valley" 190s .. .. .. .. ..$ x : num [1:2] 0.312 0.678 190s .. .. .. .. ..$ density: num [1:2] 0.465 0.496 190s .. .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 190s ..$ preserveScale: logi FALSE 190s ..$ scaleFactor : num NA 190s Normalizing betaT using betaN (TumorBoost)...done 190s Setup up data... 190s 'data.frame': 44010 obs. of 7 variables: 190s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 190s $ x : num 1145994 2941694 3710825 4240737 4276892 ... 190s $ CT : num 1.63 1.4 1.41 1.17 1.16 ... 190s $ betaT : num 0.7574 0.169 0.2357 0.2604 0.0576 ... 190s $ betaTN : num 0.9301 0.1667 0.0685 0.0995 0.0155 ... 190s ..- attr(*, "modelFit")=List of 5 190s .. ..$ method : chr "normalizeTumorBoost" 190s .. ..$ flavor : chr "v4" 190s .. ..$ delta : num [1:44010] -0.17264 0.00239 0.1671 0.16085 0.04213 ... 190s .. .. ..- attr(*, "modelFit")=List of 1 190s .. .. .. ..$ :List of 7 190s .. .. .. .. ..$ flavor : chr "density" 190s .. .. .. .. ..$ cn : int 2 190s .. .. .. .. ..$ nbrOfGenotypeGroups: int 3 190s .. .. .. .. ..$ tau : num [1:2] 0.312 0.678 190s .. .. .. .. ..$ n : int 43920 190s .. .. .. .. ..$ fit :Classes 'PeaksAndValleys' and 'data.frame': 5 obs. of 3 variables: 190s .. .. .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 190s .. .. .. .. .. ..$ x : num [1:5] 0.0999 0.312 0.4986 0.6775 0.8922 190s .. .. .. .. .. ..$ density: num [1:5] 1.622 0.465 1.125 0.496 1.587 190s .. .. .. .. ..$ fitValleys :Classes 'PeaksAndValleys' and 'data.frame': 2 obs. of 3 variables: 190s .. .. .. .. .. ..$ type : chr [1:2] "valley" "valley" 190s .. .. .. .. .. ..$ x : num [1:2] 0.312 0.678 190s .. .. .. .. .. ..$ density: num [1:2] 0.465 0.496 190s .. .. .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 190s .. ..$ preserveScale: logi FALSE 190s .. ..$ scaleFactor : num NA 190s $ betaN : num 0.8274 0.5072 0.1671 0.1609 0.0421 ... 190s $ muN : num 1 0.5 0 0 0 0 1 0 1 0.5 ... 190s ..- attr(*, "modelFit")=List of 1 190s .. ..$ :List of 7 190s .. .. ..$ flavor : chr "density" 190s .. .. ..$ cn : int 2 190s .. .. ..$ nbrOfGenotypeGroups: int 3 190s .. .. ..$ tau : num [1:2] 0.312 0.678 190s .. .. ..$ n : int 43920 190s .. .. ..$ fit :Classes 'PeaksAndValleys' and 'data.frame': 5 obs. of 3 variables: 190s .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 190s .. .. .. ..$ x : num [1:5] 0.0999 0.312 0.4986 0.6775 0.8922 190s .. .. .. ..$ density: num [1:5] 1.622 0.465 1.125 0.496 1.587 190s .. .. ..$ fitValleys :Classes 'PeaksAndValleys' and 'data.frame': 2 obs. of 3 variables: 190s .. .. .. ..$ type : chr [1:2] "valley" "valley" 190s .. .. .. ..$ x : num [1:2] 0.312 0.678 190s .. .. .. ..$ density: num [1:2] 0.465 0.496 190s .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 190s Setup up data...done 190s Dropping loci for which TCNs are missing... 190s Number of loci dropped: 36 190s Dropping loci for which TCNs are missing...done 190s Ordering data along genome... 190s 'data.frame': 43974 obs. of 7 variables: 190s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 190s $ x : num 554484 730720 782343 878522 916294 ... 190s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 190s $ betaT : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 190s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 190s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 190s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 190s Ordering data along genome...done 190s Segmenting multiple chromosomes... 190s Number of chromosomes: 3 190s Random seed temporarily set (seed=c(48879), kind="L'Ecuyer-CMRG") 190s Produced 3 seeds from this stream for future usage 190s Chromosome #1 ('Chr01') of 3... 190s 'data.frame': 14658 obs. of 8 variables: 190s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 190s $ x : num 554484 730720 782343 878522 916294 ... 190s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 190s $ betaT : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 190s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 190s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 190s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 190s $ index : int 1 2 3 4 5 6 7 8 9 10 ... 190s Known segments: 190s [1] chromosome start end 190s <0 rows> (or 0-length row.names) 190s Segmenting paired tumor-normal signals using Paired PSCBS... 190s Setup up data... 190s 'data.frame': 14658 obs. of 7 variables: 190s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 190s $ x : num 554484 730720 782343 878522 916294 ... 190s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 190s $ betaT : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 190s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 190s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 190s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 190s Setup up data...done 190s Ordering data along genome... 190s 'data.frame': 14658 obs. of 7 variables: 190s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 190s $ x : num 554484 730720 782343 878522 916294 ... 190s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 190s $ betaT : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 190s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 190s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 190s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 190s Ordering data along genome...done 190s Keeping only current chromosome for 'knownSegments'... 190s Chromosome: 1 190s Known segments for this chromosome: 190s [1] chromosome start end 190s <0 rows> (or 0-length row.names) 190s Keeping only current chromosome for 'knownSegments'...done 190s alphaTCN: 0.009 190s alphaDH: 0.001 190s Number of loci: 14658 190s Calculating DHs... 190s Number of SNPs: 14658 190s Number of heterozygous SNPs: 4209 (28.71%) 190s Normalized DHs: 190s num [1:14658] NA NA NA NA NA ... 190s Calculating DHs...done 190s Random seed temporarily set (seed=c(10407, 1066287653, -51199871, 161854402, -1995183193, 1503453565, -747102133), kind="L'Ecuyer-CMRG") 190s Produced 2 seeds from this stream for future usage 190s Identification of change points by total copy numbers... 190s Segmenting by CBS... 190s Chromosome: 1 190s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 190s Segmenting by CBS...done 190s List of 4 190s $ data :'data.frame': 14658 obs. of 4 variables: 190s ..$ chromosome: int [1:14658] 1 1 1 1 1 1 1 1 1 1 ... 190s ..$ x : num [1:14658] 554484 730720 782343 878522 916294 ... 190s ..$ y : num [1:14658] 1.88 1.8 1.59 1.64 1.53 ... 190s ..$ index : int [1:14658] 1 2 3 4 5 6 7 8 9 10 ... 190s $ output :'data.frame': 3 obs. of 6 variables: 190s ..$ sampleName: chr [1:3] NA NA NA 190s ..$ chromosome: int [1:3] 1 1 1 190s ..$ start : num [1:3] 5.54e+05 1.44e+08 1.85e+08 190s ..$ end : num [1:3] 1.44e+08 1.85e+08 2.47e+08 190s ..$ nbrOfLoci : int [1:3] 7599 2668 4391 190s ..$ mean : num [1:3] 1.39 2.07 2.63 190s $ segRows:'data.frame': 3 obs. of 2 variables: 190s ..$ startRow: int [1:3] 1 7600 10268 190s ..$ endRow : int [1:3] 7599 10267 14658 190s $ params :List of 5 190s ..$ alpha : num 0.009 190s ..$ undo : num 0 190s ..$ joinSegments : logi TRUE 190s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 190s .. ..$ chromosome: int 1 190s .. ..$ start : num -Inf 190s .. ..$ end : num Inf 190s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 190s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 190s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.221 0 0.22 0 0 190s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 190s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 190s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 190s Identification of change points by total copy numbers...done 190s Restructure TCN segmentation results... 190s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean 190s 1 1 554484 143926517 7599 1.3859 190s 2 1 143926517 185449813 2668 2.0704 190s 3 1 185449813 247137334 4391 2.6341 190s Number of TCN segments: 3 190s Restructure TCN segmentation results...done 190s Total CN segment #1 ([ 554484,1.43927e+08]) of 3... 190s Number of TCN loci in segment: 7599 190s Locus data for TCN segment: 190s 'data.frame': 7599 obs. of 9 variables: 190s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 190s $ x : num 554484 730720 782343 878522 916294 ... 190s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 190s $ betaT : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 190s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 190s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 190s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 190s $ index : int 1 2 3 4 5 6 7 8 9 10 ... 190s $ rho : num NA NA NA NA NA ... 190s Number of loci: 7599 190s Number of SNPs: 2120 (27.90%) 190s Number of heterozygous SNPs: 2120 (100.00%) 190s Chromosome: 1 190s Segmenting DH signals... 190s Segmenting by CBS... 190s Chromosome: 1 190s Random seed temporarily set (seed=c(10407, -821273412, -52578226, 1415511586, 721384351, -665928286, 1316562960), kind="L'Ecuyer-CMRG") 190s Segmenting by CBS...done 190s List of 4 190s $ data :'data.frame': 7599 obs. of 4 variables: 190s ..$ chromosome: int [1:7599] 1 1 1 1 1 1 1 1 1 1 ... 190s ..$ x : num [1:7599] 554484 730720 782343 878522 916294 ... 190s ..$ y : num [1:7599] NA NA NA NA NA ... 190s ..$ index : int [1:7599] 1 2 3 4 5 6 7 8 9 10 ... 190s $ output :'data.frame': 1 obs. of 6 variables: 190s ..$ sampleName: chr NA 190s ..$ chromosome: int 1 190s ..$ start : num 554484 190s ..$ end : num 1.44e+08 190s ..$ nbrOfLoci : int 2120 190s ..$ mean : num 0.51 190s $ segRows:'data.frame': 1 obs. of 2 variables: 190s ..$ startRow: int 10 190s ..$ endRow : int 7594 190s $ params :List of 5 190s ..$ alpha : num 0.001 190s ..$ undo : num 0 190s ..$ joinSegments : logi TRUE 190s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 190s .. ..$ chromosome: int 1 190s .. ..$ start : num 554484 190s .. ..$ end : num 1.44e+08 190s ..$ seed : int [1:7] 10407 -821273412 -52578226 1415511586 721384351 -665928286 1316562960 190s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 190s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.017 0 0.017 0 0 190s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 190s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 190s - attr(*, "randomSeed")= int [1:7] 10407 -821273412 -52578226 1415511586 721384351 -665928286 1316562960 190s DH segmentation (locally-indexed) rows: 190s startRow endRow 190s 1 10 7594 190s int [1:7599] 1 2 3 4 5 6 7 8 9 10 ... 190s DH segmentation rows: 190s startRow endRow 190s 1 10 7594 190s Segmenting DH signals...done 190s DH segmentation table: 190s dhStart dhEnd dhNbrOfLoci dhMean 190s 1 554484 143926517 2120 0.5101 190s startRow endRow 190s 1 10 7594 190s Rows: 190s [1] 1 190s TCN segmentation rows: 190s startRow endRow 190s 1 1 7599 190s TCN and DH segmentation rows: 190s startRow endRow 190s 1 1 7599 190s startRow endRow 190s 1 10 7594 190s NULL 190s TCN segmentation (expanded) rows: 190s startRow endRow 190s 1 1 7599 190s TCN and DH segmentation rows: 190s startRow endRow 190s 1 1 7599 190s 2 7600 10267 190s 3 10268 14658 190s startRow endRow 190s 1 10 7594 190s startRow endRow 190s 1 1 7599 190s Total CN segmentation table (expanded): 190s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 190s 1 1 554484 143926517 7599 1.3859 2120 2120 190s (TCN,DH) segmentation for one total CN segment: 190s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 190s 1 1 1 1 554484 143926517 7599 1.3859 2120 190s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 190s 1 2120 554484 143926517 2120 0.5101 190s Total CN segment #1 ([ 554484,1.43927e+08]) of 3...done 190s Total CN segment #2 ([1.43927e+08,1.8545e+08]) of 3... 190s Number of TCN loci in segment: 2668 190s Locus data for TCN segment: 190s 'data.frame': 2668 obs. of 9 variables: 190s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 190s $ x : num 1.44e+08 1.44e+08 1.44e+08 1.44e+08 1.44e+08 ... 190s $ CT : num 2.1 2.1 2.09 1.8 2.34 ... 190s $ betaT : num 0.027542 1.030222 1.094093 0.046763 -0.000948 ... 190s $ betaTN : num 0.027542 1.030222 1.094093 0.046763 -0.000948 ... 190s $ betaN : num 0.1624 0.8788 0.8225 0.1201 0.0317 ... 190s $ muN : num 0 1 1 0 0 1 0 0 0 0 ... 190s $ index : int 7600 7601 7602 7603 7604 7605 7606 7607 7608 7609 ... 190s $ rho : num NA NA NA NA NA NA NA NA NA NA ... 190s Number of loci: 2668 190s Number of SNPs: 775 (29.05%) 190s Number of heterozygous SNPs: 775 (100.00%) 190s Chromosome: 1 190s Segmenting DH signals... 190s Segmenting by CBS... 190s Chromosome: 1 190s Random seed temporarily set (seed=c(10407, -821273412, -52578226, 1415511586, 721384351, -665928286, 1316562960), kind="L'Ecuyer-CMRG") 190s Segmenting by CBS...done 190s List of 4 190s $ data :'data.frame': 2668 obs. of 4 variables: 190s ..$ chromosome: int [1:2668] 1 1 1 1 1 1 1 1 1 1 ... 190s ..$ x : num [1:2668] 1.44e+08 1.44e+08 1.44e+08 1.44e+08 1.44e+08 ... 190s ..$ y : num [1:2668] NA NA NA NA NA NA NA NA NA NA ... 190s ..$ index : int [1:2668] 1 2 3 4 5 6 7 8 9 10 ... 190s $ output :'data.frame': 1 obs. of 6 variables: 190s ..$ sampleName: chr NA 190s ..$ chromosome: int 1 190s ..$ start : num 1.44e+08 190s ..$ end : num 1.85e+08 190s ..$ nbrOfLoci : int 775 190s ..$ mean : num 0.097 190s $ segRows:'data.frame': 1 obs. of 2 variables: 190s ..$ startRow: int 15 190s ..$ endRow : int 2664 190s $ params :List of 5 190s ..$ alpha : num 0.001 190s ..$ undo : num 0 190s ..$ joinSegments : logi TRUE 190s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 190s .. ..$ chromosome: int 1 190s .. ..$ start : num 1.44e+08 190s .. ..$ end : num 1.85e+08 190s ..$ seed : int [1:7] 10407 -821273412 -52578226 1415511586 721384351 -665928286 1316562960 190s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 190s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.005 0 0.005 0 0 190s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 190s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 190s - attr(*, "randomSeed")= int [1:7] 10407 -821273412 -52578226 1415511586 721384351 -665928286 1316562960 190s DH segmentation (locally-indexed) rows: 190s startRow endRow 190s 1 15 2664 190s int [1:2668] 7600 7601 7602 7603 7604 7605 7606 7607 7608 7609 ... 190s DH segmentation rows: 190s startRow endRow 190s 1 7614 10263 190s Segmenting DH signals...done 190s DH segmentation table: 190s dhStart dhEnd dhNbrOfLoci dhMean 190s 1 143926517 185449813 775 0.097 190s startRow endRow 190s 1 7614 10263 190s Rows: 190s [1] 2 190s TCN segmentation rows: 190s startRow endRow 190s 2 7600 10267 190s TCN and DH segmentation rows: 190s startRow endRow 190s 2 7600 10267 190s startRow endRow 190s 1 7614 10263 190s startRow endRow 190s 1 1 7599 190s TCN segmentation (expanded) rows: 190s startRow endRow 190s 1 1 7599 190s 2 7600 10267 190s TCN and DH segmentation rows: 190s startRow endRow 190s 1 1 7599 190s 2 7600 10267 190s 3 10268 14658 190s startRow endRow 190s 1 10 7594 190s 2 7614 10263 190s startRow endRow 190s 1 1 7599 190s 2 7600 10267 190s Total CN segmentation table (expanded): 190s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 190s 2 1 143926517 185449813 2668 2.0704 775 775 190s (TCN,DH) segmentation for one total CN segment: 190s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 190s 2 2 1 1 143926517 185449813 2668 2.0704 775 190s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 190s 2 775 143926517 185449813 775 0.097 190s Total CN segment #2 ([1.43927e+08,1.8545e+08]) of 3...done 190s Total CN segment #3 ([1.8545e+08,2.47137e+08]) of 3... 190s Number of TCN loci in segment: 4391 190s Locus data for TCN segment: 190s 'data.frame': 4391 obs. of 9 variables: 190s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 190s $ x : num 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 190s $ CT : num 2.93 2.15 2.82 2.93 2.46 ... 190s $ betaT : num -0.169 0.609 1.028 0.525 0.968 ... 190s $ betaTN : num -0.169 0.609 1.028 0.525 0.968 ... 190s $ betaN : num 0.25 0.38 0.919 0.34 0.783 ... 190s $ muN : num 0 0.5 1 0.5 1 1 0 1 0 1 ... 190s $ index : int 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 190s $ rho : num NA 0.2186 NA 0.0503 NA ... 190s Number of loci: 4391 190s Number of SNPs: 1314 (29.92%) 190s Number of heterozygous SNPs: 1314 (100.00%) 190s Chromosome: 1 190s Segmenting DH signals... 190s Segmenting by CBS... 190s Chromosome: 1 190s Random seed temporarily set (seed=c(10407, -821273412, -52578226, 1415511586, 721384351, -665928286, 1316562960), kind="L'Ecuyer-CMRG") 190s Segmenting by CBS...done 190s List of 4 190s $ data :'data.frame': 4391 obs. of 4 variables: 190s ..$ chromosome: int [1:4391] 1 1 1 1 1 1 1 1 1 1 ... 190s ..$ x : num [1:4391] 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 190s ..$ y : num [1:4391] NA 0.2186 NA 0.0503 NA ... 190s ..$ index : int [1:4391] 1 2 3 4 5 6 7 8 9 10 ... 190s $ output :'data.frame': 1 obs. of 6 variables: 190s ..$ sampleName: chr NA 190s ..$ chromosome: int 1 190s ..$ start : num 1.85e+08 190s ..$ end : num 2.47e+08 190s ..$ nbrOfLoci : int 1314 190s ..$ mean : num 0.23 190s $ segRows:'data.frame': 1 obs. of 2 variables: 190s ..$ startRow: int 2 190s ..$ endRow : int 4388 190s $ params :List of 5 190s ..$ alpha : num 0.001 190s ..$ undo : num 0 190s ..$ joinSegments : logi TRUE 190s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 190s .. ..$ chromosome: int 1 190s .. ..$ start : num 1.85e+08 190s .. ..$ end : num 2.47e+08 190s ..$ seed : int [1:7] 10407 -821273412 -52578226 1415511586 721384351 -665928286 1316562960 190s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 190s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.009 0 0.009 0 0 190s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 190s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 190s - attr(*, "randomSeed")= int [1:7] 10407 -821273412 -52578226 1415511586 721384351 -665928286 1316562960 190s DH segmentation (locally-indexed) rows: 190s startRow endRow 190s 1 2 4388 190s int [1:4391] 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 190s DH segmentation rows: 190s startRow endRow 190s 1 10269 14655 190s Segmenting DH signals...done 190s DH segmentation table: 190s dhStart dhEnd dhNbrOfLoci dhMean 190s 1 185449813 247137334 1314 0.2295 190s startRow endRow 190s 1 10269 14655 190s Rows: 190s [1] 3 190s TCN segmentation rows: 190s startRow endRow 190s 3 10268 14658 190s TCN and DH segmentation rows: 190s startRow endRow 190s 3 10268 14658 190s startRow endRow 190s 1 10269 14655 190s startRow endRow 190s 1 1 7599 190s 2 7600 10267 190s TCN segmentation (expanded) rows: 190s startRow endRow 190s 1 1 7599 190s 2 7600 10267 190s 3 10268 14658 190s TCN and DH segmentation rows: 190s startRow endRow 190s 1 1 7599 190s 2 7600 10267 190s 3 10268 14658 190s startRow endRow 190s 1 10 7594 190s 2 7614 10263 190s 3 10269 14655 190s startRow endRow 190s 1 1 7599 190s 2 7600 10267 190s 3 10268 14658 190s Total CN segmentation table (expanded): 190s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 190s 3 1 185449813 247137334 4391 2.6341 1314 1314 190s (TCN,DH) segmentation for one total CN segment: 190s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 190s 3 3 1 1 185449813 247137334 4391 2.6341 1314 190s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 190s 3 1314 185449813 247137334 1314 0.2295 190s Total CN segment #3 ([1.8545e+08,2.47137e+08]) of 3...done 190s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 190s 1 1 1 1 554484 143926517 7599 1.3859 2120 190s 2 1 2 1 143926517 185449813 2668 2.0704 775 190s 3 1 3 1 185449813 247137334 4391 2.6341 1314 190s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 190s 1 2120 554484 143926517 2120 0.5101 190s 2 775 143926517 185449813 775 0.0970 190s 3 1314 185449813 247137334 1314 0.2295 190s Calculating (C1,C2) per segment... 190s Calculating (C1,C2) per segment...done 190s Number of segments: 3 190s Segmenting paired tumor-normal signals using Paired PSCBS...done 190s Post-segmenting TCNs... 190s Number of segments: 3 190s Number of chromosomes: 1 190s [1] 1 190s Chromosome 1 ('chr01') of 1... 190s Rows: 190s [1] 1 2 3 190s Number of segments: 3 190s TCN segment #1 ('1') of 3... 190s Nothing todo. Only one DH segmentation. Skipping. 190s TCN segment #1 ('1') of 3...done 190s TCN segment #2 ('2') of 3... 190s Nothing todo. Only one DH segmentation. Skipping. 190s TCN segment #2 ('2') of 3...done 190s TCN segment #3 ('3') of 3... 190s Nothing todo. Only one DH segmentation. Skipping. 190s TCN segment #3 ('3') of 3...done 190s Chromosome 1 ('chr01') of 1...done 190s Update (C1,C2) per segment... 190s Update (C1,C2) per segment...done 190s Post-segmenting TCNs...done 190s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 190s 1 1 1 1 554484 143926517 7599 1.3859 2120 190s 2 1 2 1 143926517 185449813 2668 2.0704 775 190s 3 1 3 1 185449813 247137334 4391 2.6341 1314 190s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 190s 1 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 190s 2 775 143926517 185449813 775 0.0970 0.9347856 1.135614 190s 3 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 190s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 190s 1 1 1 1 554484 143926517 7599 1.3859 2120 190s 2 1 2 1 143926517 185449813 2668 2.0704 775 190s 3 1 3 1 185449813 247137334 4391 2.6341 1314 190s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 190s 1 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 190s 2 775 143926517 185449813 775 0.0970 0.9347856 1.135614 190s 3 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 190s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 190s 1 1 1 1 554484 143926517 7599 1.3859 2120 190s 2 1 2 1 143926517 185449813 2668 2.0704 775 190s 3 1 3 1 185449813 247137334 4391 2.6341 1314 190s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 190s 1 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 190s 2 775 143926517 185449813 775 0.0970 0.9347856 1.135614 190s 3 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 190s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 190s 1 1 1 1 554484 143926517 7599 1.3859 2120 190s 2 1 2 1 143926517 185449813 2668 2.0704 775 190s 3 1 3 1 185449813 247137334 4391 2.6341 1314 190s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 190s 1 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 190s 2 775 143926517 185449813 775 0.0970 0.9347856 1.135614 190s 3 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 190s Chromosome #1 ('Chr01') of 3...done 190s Chromosome #2 ('Chr02') of 3... 190s 'data.frame': 14658 obs. of 8 variables: 190s $ chromosome: int 2 2 2 2 2 2 2 2 2 2 ... 190s $ x : num 554484 730720 782343 878522 916294 ... 190s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 190s $ betaT : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 190s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 190s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 190s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 190s $ index : int 14659 14660 14661 14662 14663 14664 14665 14666 14667 14668 ... 190s Known segments: 190s [1] chromosome start end 190s <0 rows> (or 0-length row.names) 190s Segmenting paired tumor-normal signals using Paired PSCBS... 190s Setup up data... 190s 'data.frame': 14658 obs. of 7 variables: 190s $ chromosome: int 2 2 2 2 2 2 2 2 2 2 ... 190s $ x : num 554484 730720 782343 878522 916294 ... 190s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 190s $ betaT : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 190s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 190s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 190s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 190s Setup up data...done 190s Ordering data along genome... 190s 'data.frame': 14658 obs. of 7 variables: 190s $ chromosome: int 2 2 2 2 2 2 2 2 2 2 ... 190s $ x : num 554484 730720 782343 878522 916294 ... 190s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 190s $ betaT : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 190s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 190s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 190s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 190s Ordering data along genome...done 190s Keeping only current chromosome for 'knownSegments'... 190s Chromosome: 2 190s Known segments for this chromosome: 190s [1] chromosome start end 190s <0 rows> (or 0-length row.names) 190s Keeping only current chromosome for 'knownSegments'...done 190s alphaTCN: 0.009 190s alphaDH: 0.001 190s Number of loci: 14658 190s Calculating DHs... 190s Number of SNPs: 14658 190s Number of heterozygous SNPs: 4209 (28.71%) 190s Normalized DHs: 190s num [1:14658] NA NA NA NA NA ... 190s Calculating DHs...done 190s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 190s Produced 2 seeds from this stream for future usage 190s Identification of change points by total copy numbers... 190s Segmenting by CBS... 190s Chromosome: 2 190s Random seed temporarily set (seed=c(10407, -821273412, -52578226, 1415511586, 721384351, -665928286, 1316562960), kind="L'Ecuyer-CMRG") 190s Segmenting by CBS...done 190s List of 4 190s $ data :'data.frame': 14658 obs. of 4 variables: 190s ..$ chromosome: int [1:14658] 2 2 2 2 2 2 2 2 2 2 ... 190s ..$ x : num [1:14658] 554484 730720 782343 878522 916294 ... 190s ..$ y : num [1:14658] 1.88 1.8 1.59 1.64 1.53 ... 190s ..$ index : int [1:14658] 1 2 3 4 5 6 7 8 9 10 ... 190s $ output :'data.frame': 3 obs. of 6 variables: 190s ..$ sampleName: chr [1:3] NA NA NA 190s ..$ chromosome: int [1:3] 2 2 2 190s ..$ start : num [1:3] 5.54e+05 1.44e+08 1.85e+08 190s ..$ end : num [1:3] 1.44e+08 1.85e+08 2.47e+08 190s ..$ nbrOfLoci : int [1:3] 7599 2668 4391 190s ..$ mean : num [1:3] 1.39 2.07 2.63 190s $ segRows:'data.frame': 3 obs. of 2 variables: 190s ..$ startRow: int [1:3] 1 7600 10268 190s ..$ endRow : int [1:3] 7599 10267 14658 190s $ params :List of 5 190s ..$ alpha : num 0.009 190s ..$ undo : num 0 190s ..$ joinSegments : logi TRUE 190s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 190s .. ..$ chromosome: int 2 190s .. ..$ start : num -Inf 190s .. ..$ end : num Inf 190s ..$ seed : int [1:7] 10407 -821273412 -52578226 1415511586 721384351 -665928286 1316562960 190s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 190s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.237 0 0.236 0 0 190s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 190s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 190s - attr(*, "randomSeed")= int [1:7] 10407 -821273412 -52578226 1415511586 721384351 -665928286 1316562960 190s Identification of change points by total copy numbers...done 190s Restructure TCN segmentation results... 190s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean 190s 1 2 554484 143926517 7599 1.3859 190s 2 2 143926517 185449813 2668 2.0704 190s 3 2 185449813 247137334 4391 2.6341 190s Number of TCN segments: 3 190s Restructure TCN segmentation results...done 190s Total CN segment #1 ([ 554484,1.43927e+08]) of 3... 190s Number of TCN loci in segment: 7599 190s Locus data for TCN segment: 190s 'data.frame': 7599 obs. of 9 variables: 190s $ chromosome: int 2 2 2 2 2 2 2 2 2 2 ... 190s $ x : num 554484 730720 782343 878522 916294 ... 190s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 190s $ betaT : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 190s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 190s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 190s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 190s $ index : int 1 2 3 4 5 6 7 8 9 10 ... 190s $ rho : num NA NA NA NA NA ... 190s Number of loci: 7599 190s Number of SNPs: 2120 (27.90%) 190s Number of heterozygous SNPs: 2120 (100.00%) 190s Chromosome: 2 190s Segmenting DH signals... 190s Segmenting by CBS... 190s Chromosome: 2 190s Random seed temporarily set (seed=c(10407, -1924040949, -1632234809, -437763632, -1464377300, 676654412, 2080370711), kind="L'Ecuyer-CMRG") 190s Segmenting by CBS...done 190s List of 4 190s $ data :'data.frame': 7599 obs. of 4 variables: 190s ..$ chromosome: int [1:7599] 2 2 2 2 2 2 2 2 2 2 ... 190s ..$ x : num [1:7599] 554484 730720 782343 878522 916294 ... 190s ..$ y : num [1:7599] NA NA NA NA NA ... 190s ..$ index : int [1:7599] 1 2 3 4 5 6 7 8 9 10 ... 190s $ output :'data.frame': 1 obs. of 6 variables: 190s ..$ sampleName: chr NA 190s ..$ chromosome: int 2 190s ..$ start : num 554484 190s ..$ end : num 1.44e+08 190s ..$ nbrOfLoci : int 2120 190s ..$ mean : num 0.51 190s $ segRows:'data.frame': 1 obs. of 2 variables: 190s ..$ startRow: int 10 190s ..$ endRow : int 7594 190s $ params :List of 5 190s ..$ alpha : num 0.001 190s ..$ undo : num 0 190s ..$ joinSegments : logi TRUE 190s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 190s .. ..$ chromosome: int 2 190s .. ..$ start : num 554484 190s .. ..$ end : num 1.44e+08 190s ..$ seed : int [1:7] 10407 -1924040949 -1632234809 -437763632 -1464377300 676654412 2080370711 190s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 190s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.017 0 0.017 0 0 190s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 190s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 190s - attr(*, "randomSeed")= int [1:7] 10407 -1924040949 -1632234809 -437763632 -1464377300 676654412 2080370711 190s DH segmentation (locally-indexed) rows: 190s startRow endRow 190s 1 10 7594 190s int [1:7599] 1 2 3 4 5 6 7 8 9 10 ... 190s DH segmentation rows: 190s startRow endRow 190s 1 10 7594 190s Segmenting DH signals...done 190s DH segmentation table: 190s dhStart dhEnd dhNbrOfLoci dhMean 190s 1 554484 143926517 2120 0.5101 190s startRow endRow 190s 1 10 7594 190s Rows: 190s [1] 1 190s TCN segmentation rows: 190s startRow endRow 190s 1 1 7599 190s TCN and DH segmentation rows: 190s startRow endRow 190s 1 1 7599 190s startRow endRow 190s 1 10 7594 190s NULL 190s TCN segmentation (expanded) rows: 190s startRow endRow 190s 1 1 7599 190s TCN and DH segmentation rows: 190s startRow endRow 190s 1 1 7599 190s 2 7600 10267 190s 3 10268 14658 190s startRow endRow 190s 1 10 7594 190s startRow endRow 190s 1 1 7599 190s Total CN segmentation table (expanded): 190s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 190s 1 2 554484 143926517 7599 1.3859 2120 2120 190s (TCN,DH) segmentation for one total CN segment: 190s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 190s 1 1 1 2 554484 143926517 7599 1.3859 2120 190s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 190s 1 2120 554484 143926517 2120 0.5101 190s Total CN segment #1 ([ 554484,1.43927e+08]) of 3...done 190s Total CN segment #2 ([1.43927e+08,1.8545e+08]) of 3... 190s Number of TCN loci in segment: 2668 190s Locus data for TCN segment: 190s 'data.frame': 2668 obs. of 9 variables: 190s $ chromosome: int 2 2 2 2 2 2 2 2 2 2 ... 190s $ x : num 1.44e+08 1.44e+08 1.44e+08 1.44e+08 1.44e+08 ... 190s $ CT : num 2.1 2.1 2.09 1.8 2.34 ... 190s $ betaT : num 0.027542 1.030222 1.094093 0.046763 -0.000948 ... 190s $ betaTN : num 0.027542 1.030222 1.094093 0.046763 -0.000948 ... 190s $ betaN : num 0.1624 0.8788 0.8225 0.1201 0.0317 ... 190s $ muN : num 0 1 1 0 0 1 0 0 0 0 ... 190s $ index : int 7600 7601 7602 7603 7604 7605 7606 7607 7608 7609 ... 190s $ rho : num NA NA NA NA NA NA NA NA NA NA ... 190s Number of loci: 2668 190s Number of SNPs: 775 (29.05%) 190s Number of heterozygous SNPs: 775 (100.00%) 190s Chromosome: 2 190s Segmenting DH signals... 190s Segmenting by CBS... 190s Chromosome: 2 190s Random seed temporarily set (seed=c(10407, -1924040949, -1632234809, -437763632, -1464377300, 676654412, 2080370711), kind="L'Ecuyer-CMRG") 190s Segmenting by CBS...done 190s List of 4 190s $ data :'data.frame': 2668 obs. of 4 variables: 190s ..$ chromosome: int [1:2668] 2 2 2 2 2 2 2 2 2 2 ... 190s ..$ x : num [1:2668] 1.44e+08 1.44e+08 1.44e+08 1.44e+08 1.44e+08 ... 190s ..$ y : num [1:2668] NA NA NA NA NA NA NA NA NA NA ... 190s ..$ index : int [1:2668] 1 2 3 4 5 6 7 8 9 10 ... 190s $ output :'data.frame': 1 obs. of 6 variables: 190s ..$ sampleName: chr NA 190s ..$ chromosome: int 2 190s ..$ start : num 1.44e+08 190s ..$ end : num 1.85e+08 190s ..$ nbrOfLoci : int 775 190s ..$ mean : num 0.097 190s $ segRows:'data.frame': 1 obs. of 2 variables: 190s ..$ startRow: int 15 190s ..$ endRow : int 2664 190s $ params :List of 5 190s ..$ alpha : num 0.001 190s ..$ undo : num 0 190s ..$ joinSegments : logi TRUE 190s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 190s .. ..$ chromosome: int 2 190s .. ..$ start : num 1.44e+08 190s .. ..$ end : num 1.85e+08 190s ..$ seed : int [1:7] 10407 -1924040949 -1632234809 -437763632 -1464377300 676654412 2080370711 190s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 190s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.006 0 0.005 0 0 190s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 190s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 190s - attr(*, "randomSeed")= int [1:7] 10407 -1924040949 -1632234809 -437763632 -1464377300 676654412 2080370711 190s DH segmentation (locally-indexed) rows: 190s startRow endRow 190s 1 15 2664 190s int [1:2668] 7600 7601 7602 7603 7604 7605 7606 7607 7608 7609 ... 190s DH segmentation rows: 190s startRow endRow 190s 1 7614 10263 190s Segmenting DH signals...done 190s DH segmentation table: 190s dhStart dhEnd dhNbrOfLoci dhMean 190s 1 143926517 185449813 775 0.097 190s startRow endRow 190s 1 7614 10263 190s Rows: 190s [1] 2 190s TCN segmentation rows: 190s startRow endRow 190s 2 7600 10267 190s TCN and DH segmentation rows: 190s startRow endRow 190s 2 7600 10267 190s startRow endRow 190s 1 7614 10263 190s startRow endRow 190s 1 1 7599 190s TCN segmentation (expanded) rows: 190s startRow endRow 190s 1 1 7599 190s 2 7600 10267 190s TCN and DH segmentation rows: 190s startRow endRow 190s 1 1 7599 190s 2 7600 10267 190s 3 10268 14658 190s startRow endRow 190s 1 10 7594 190s 2 7614 10263 190s startRow endRow 190s 1 1 7599 190s 2 7600 10267 190s Total CN segmentation table (expanded): 190s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 190s 2 2 143926517 185449813 2668 2.0704 775 775 190s (TCN,DH) segmentation for one total CN segment: 190s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 190s 2 2 1 2 143926517 185449813 2668 2.0704 775 190s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 190s 2 775 143926517 185449813 775 0.097 190s Total CN segment #2 ([1.43927e+08,1.8545e+08]) of 3...done 190s Total CN segment #3 ([1.8545e+08,2.47137e+08]) of 3... 190s Number of TCN loci in segment: 4391 190s Locus data for TCN segment: 190s 'data.frame': 4391 obs. of 9 variables: 190s $ chromosome: int 2 2 2 2 2 2 2 2 2 2 ... 190s $ x : num 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 190s $ CT : num 2.93 2.15 2.82 2.93 2.46 ... 190s $ betaT : num -0.169 0.609 1.028 0.525 0.968 ... 190s $ betaTN : num -0.169 0.609 1.028 0.525 0.968 ... 190s $ betaN : num 0.25 0.38 0.919 0.34 0.783 ... 190s $ muN : num 0 0.5 1 0.5 1 1 0 1 0 1 ... 190s $ index : int 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 190s $ rho : num NA 0.2186 NA 0.0503 NA ... 190s Number of loci: 4391 190s Number of SNPs: 1314 (29.92%) 190s Number of heterozygous SNPs: 1314 (100.00%) 190s Chromosome: 2 190s Segmenting DH signals... 190s Segmenting by CBS... 190s Chromosome: 2 190s Random seed temporarily set (seed=c(10407, -1924040949, -1632234809, -437763632, -1464377300, 676654412, 2080370711), kind="L'Ecuyer-CMRG") 190s Segmenting by CBS...done 190s List of 4 190s $ data :'data.frame': 4391 obs. of 4 variables: 190s ..$ chromosome: int [1:4391] 2 2 2 2 2 2 2 2 2 2 ... 190s ..$ x : num [1:4391] 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 190s ..$ y : num [1:4391] NA 0.2186 NA 0.0503 NA ... 190s ..$ index : int [1:4391] 1 2 3 4 5 6 7 8 9 10 ... 190s $ output :'data.frame': 1 obs. of 6 variables: 190s ..$ sampleName: chr NA 190s ..$ chromosome: int 2 190s ..$ start : num 1.85e+08 190s ..$ end : num 2.47e+08 190s ..$ nbrOfLoci : int 1314 190s ..$ mean : num 0.23 190s $ segRows:'data.frame': 1 obs. of 2 variables: 190s ..$ startRow: int 2 190s ..$ endRow : int 4388 190s $ params :List of 5 190s ..$ alpha : num 0.001 190s ..$ undo : num 0 190s ..$ joinSegments : logi TRUE 190s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 190s .. ..$ chromosome: int 2 190s .. ..$ start : num 1.85e+08 190s .. ..$ end : num 2.47e+08 190s ..$ seed : int [1:7] 10407 -1924040949 -1632234809 -437763632 -1464377300 676654412 2080370711 190s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 190s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.01 0 0.01 0 0 190s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 190s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 190s - attr(*, "randomSeed")= int [1:7] 10407 -1924040949 -1632234809 -437763632 -1464377300 676654412 2080370711 190s DH segmentation (locally-indexed) rows: 190s startRow endRow 190s 1 2 4388 190s int [1:4391] 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 190s DH segmentation rows: 190s startRow endRow 190s 1 10269 14655 190s Segmenting DH signals...done 190s DH segmentation table: 190s dhStart dhEnd dhNbrOfLoci dhMean 190s 1 185449813 247137334 1314 0.2295 190s startRow endRow 190s 1 10269 14655 190s Rows: 190s [1] 3 190s TCN segmentation rows: 190s startRow endRow 190s 3 10268 14658 190s TCN and DH segmentation rows: 190s startRow endRow 190s 3 10268 14658 190s startRow endRow 190s 1 10269 14655 190s startRow endRow 190s 1 1 7599 190s 2 7600 10267 190s TCN segmentation (expanded) rows: 190s startRow endRow 190s 1 1 7599 190s 2 7600 10267 190s 3 10268 14658 190s TCN and DH segmentation rows: 190s startRow endRow 190s 1 1 7599 190s 2 7600 10267 190s 3 10268 14658 190s startRow endRow 190s 1 10 7594 190s 2 7614 10263 190s 3 10269 14655 190s startRow endRow 190s 1 1 7599 190s 2 7600 10267 190s 3 10268 14658 190s Total CN segmentation table (expanded): 190s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 190s 3 2 185449813 247137334 4391 2.6341 1314 1314 190s (TCN,DH) segmentation for one total CN segment: 190s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 190s 3 3 1 2 185449813 247137334 4391 2.6341 1314 190s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 190s 3 1314 185449813 247137334 1314 0.2295 190s Total CN segment #3 ([1.8545e+08,2.47137e+08]) of 3...done 190s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 190s 1 2 1 1 554484 143926517 7599 1.3859 2120 190s 2 2 2 1 143926517 185449813 2668 2.0704 775 190s 3 2 3 1 185449813 247137334 4391 2.6341 1314 190s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 190s 1 2120 554484 143926517 2120 0.5101 190s 2 775 143926517 185449813 775 0.0970 190s 3 1314 185449813 247137334 1314 0.2295 190s Calculating (C1,C2) per segment... 190s Calculating (C1,C2) per segment...done 190s Number of segments: 3 190s Segmenting paired tumor-normal signals using Paired PSCBS...done 190s Post-segmenting TCNs... 190s Number of segments: 3 190s Number of chromosomes: 1 190s [1] 2 190s Chromosome 1 ('chr02') of 1... 190s Rows: 190s [1] 1 2 3 190s Number of segments: 3 190s TCN segment #1 ('1') of 3... 190s Nothing todo. Only one DH segmentation. Skipping. 190s TCN segment #1 ('1') of 3...done 190s TCN segment #2 ('2') of 3... 190s Nothing todo. Only one DH segmentation. Skipping. 190s TCN segment #2 ('2') of 3...done 190s TCN segment #3 ('3') of 3... 190s Nothing todo. Only one DH segmentation. Skipping. 190s TCN segment #3 ('3') of 3...done 190s Chromosome 1 ('chr02') of 1...done 190s Update (C1,C2) per segment... 190s Update (C1,C2) per segment...done 190s Post-segmenting TCNs...done 190s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 190s 1 2 1 1 554484 143926517 7599 1.3859 2120 190s 2 2 2 1 143926517 185449813 2668 2.0704 775 190s 3 2 3 1 185449813 247137334 4391 2.6341 1314 190s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 190s 1 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 190s 2 775 143926517 185449813 775 0.0970 0.9347856 1.135614 190s 3 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 190s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 190s 1 2 1 1 554484 143926517 7599 1.3859 2120 190s 2 2 2 1 143926517 185449813 2668 2.0704 775 190s 3 2 3 1 185449813 247137334 4391 2.6341 1314 190s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 190s 1 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 190s 2 775 143926517 185449813 775 0.0970 0.9347856 1.135614 190s 3 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 190s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 190s 1 2 1 1 554484 143926517 7599 1.3859 2120 190s 2 2 2 1 143926517 185449813 2668 2.0704 775 190s 3 2 3 1 185449813 247137334 4391 2.6341 1314 190s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 190s 1 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 190s 2 775 143926517 185449813 775 0.0970 0.9347856 1.135614 190s 3 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 190s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 190s 1 2 1 1 554484 143926517 7599 1.3859 2120 190s 2 2 2 1 143926517 185449813 2668 2.0704 775 190s 3 2 3 1 185449813 247137334 4391 2.6341 1314 190s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 190s 1 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 190s 2 775 143926517 185449813 775 0.0970 0.9347856 1.135614 190s 3 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 190s Chromosome #2 ('Chr02') of 3...done 190s Chromosome #3 ('Chr03') of 3... 190s 'data.frame': 14658 obs. of 8 variables: 190s $ chromosome: int 3 3 3 3 3 3 3 3 3 3 ... 190s $ x : num 554484 730720 782343 878522 916294 ... 190s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 190s $ betaT : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 190s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 190s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 190s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 190s $ index : int 29317 29318 29319 29320 29321 29322 29323 29324 29325 29326 ... 190s Known segments: 190s [1] chromosome start end 190s <0 rows> (or 0-length row.names) 190s Segmenting paired tumor-normal signals using Paired PSCBS... 190s Setup up data... 190s 'data.frame': 14658 obs. of 7 variables: 190s $ chromosome: int 3 3 3 3 3 3 3 3 3 3 ... 190s $ x : num 554484 730720 782343 878522 916294 ... 190s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 190s $ betaT : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 190s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 190s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 190s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 190s Setup up data...done 190s Ordering data along genome... 190s 'data.frame': 14658 obs. of 7 variables: 190s $ chromosome: int 3 3 3 3 3 3 3 3 3 3 ... 190s $ x : num 554484 730720 782343 878522 916294 ... 190s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 190s $ betaT : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 190s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 190s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 190s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 190s Ordering data along genome...done 190s Keeping only current chromosome for 'knownSegments'... 190s Chromosome: 3 190s Known segments for this chromosome: 190s [1] chromosome start end 190s <0 rows> (or 0-length row.names) 190s Keeping only current chromosome for 'knownSegments'...done 190s alphaTCN: 0.009 190s alphaDH: 0.001 190s Number of loci: 14658 190s Calculating DHs... 190s Number of SNPs: 14658 190s Number of heterozygous SNPs: 4209 (28.71%) 190s Normalized DHs: 190s num [1:14658] NA NA NA NA NA ... 190s Calculating DHs...done 190s Random seed temporarily set (seed=c(10407, -821273412, -52578226, 1415511586, 721384351, -665928286, 1316562960), kind="L'Ecuyer-CMRG") 190s Produced 2 seeds from this stream for future usage 190s Identification of change points by total copy numbers... 190s Segmenting by CBS... 190s Chromosome: 3 190s Random seed temporarily set (seed=c(10407, -1924040949, -1632234809, -437763632, -1464377300, 676654412, 2080370711), kind="L'Ecuyer-CMRG") 190s Segmenting by CBS...done 190s List of 4 190s $ data :'data.frame': 14658 obs. of 4 variables: 190s ..$ chromosome: int [1:14658] 3 3 3 3 3 3 3 3 3 3 ... 190s ..$ x : num [1:14658] 554484 730720 782343 878522 916294 ... 190s ..$ y : num [1:14658] 1.88 1.8 1.59 1.64 1.53 ... 190s ..$ index : int [1:14658] 1 2 3 4 5 6 7 8 9 10 ... 190s $ output :'data.frame': 3 obs. of 6 variables: 190s ..$ sampleName: chr [1:3] NA NA NA 190s ..$ chromosome: int [1:3] 3 3 3 190s ..$ start : num [1:3] 5.54e+05 1.44e+08 1.85e+08 190s ..$ end : num [1:3] 1.44e+08 1.85e+08 2.47e+08 190s ..$ nbrOfLoci : int [1:3] 7599 2668 4391 190s ..$ mean : num [1:3] 1.39 2.07 2.63 190s $ segRows:'data.frame': 3 obs. of 2 variables: 190s ..$ startRow: int [1:3] 1 7600 10268 190s ..$ endRow : int [1:3] 7599 10267 14658 190s $ params :List of 5 190s ..$ alpha : num 0.009 190s ..$ undo : num 0 190s ..$ joinSegments : logi TRUE 190s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 190s .. ..$ chromosome: int 3 190s .. ..$ start : num -Inf 190s .. ..$ end : num Inf 190s ..$ seed : int [1:7] 10407 -1924040949 -1632234809 -437763632 -1464377300 676654412 2080370711 190s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 190s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.219 0 0.22 0 0 190s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 190s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 190s - attr(*, "randomSeed")= int [1:7] 10407 -1924040949 -1632234809 -437763632 -1464377300 676654412 2080370711 190s Identification of change points by total copy numbers...done 190s Restructure TCN segmentation results... 190s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean 190s 1 3 554484 143926517 7599 1.3859 190s 2 3 143926517 185449813 2668 2.0704 190s 3 3 185449813 247137334 4391 2.6341 190s Number of TCN segments: 3 190s Restructure TCN segmentation results...done 190s Total CN segment #1 ([ 554484,1.43927e+08]) of 3... 190s Number of TCN loci in segment: 7599 190s Locus data for TCN segment: 190s 'data.frame': 7599 obs. of 9 variables: 190s $ chromosome: int 3 3 3 3 3 3 3 3 3 3 ... 190s $ x : num 554484 730720 782343 878522 916294 ... 190s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 190s $ betaT : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 190s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 190s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 190s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 190s $ index : int 1 2 3 4 5 6 7 8 9 10 ... 190s $ rho : num NA NA NA NA NA ... 190s Number of loci: 7599 190s Number of SNPs: 2120 (27.90%) 190s Number of heterozygous SNPs: 2120 (100.00%) 190s Chromosome: 3 190s Segmenting DH signals... 190s Segmenting by CBS... 190s Chromosome: 3 190s Random seed temporarily set (seed=c(10407, -1371615447, -889757879, 1692656974, -1723952224, 1378814990, 1816467252), kind="L'Ecuyer-CMRG") 190s Segmenting by CBS...done 190s List of 4 190s $ data :'data.frame': 7599 obs. of 4 variables: 190s ..$ chromosome: int [1:7599] 3 3 3 3 3 3 3 3 3 3 ... 190s ..$ x : num [1:7599] 554484 730720 782343 878522 916294 ... 190s ..$ y : num [1:7599] NA NA NA NA NA ... 190s ..$ index : int [1:7599] 1 2 3 4 5 6 7 8 9 10 ... 190s $ output :'data.frame': 1 obs. of 6 variables: 190s ..$ sampleName: chr NA 190s ..$ chromosome: int 3 190s ..$ start : num 554484 190s ..$ end : num 1.44e+08 190s ..$ nbrOfLoci : int 2120 190s ..$ mean : num 0.51 190s $ segRows:'data.frame': 1 obs. of 2 variables: 190s ..$ startRow: int 10 190s ..$ endRow : int 7594 190s $ params :List of 5 190s ..$ alpha : num 0.001 190s ..$ undo : num 0 190s ..$ joinSegments : logi TRUE 190s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 190s .. ..$ chromosome: int 3 190s .. ..$ start : num 554484 190s .. ..$ end : num 1.44e+08 190s ..$ seed : int [1:7] 10407 -1371615447 -889757879 1692656974 -1723952224 1378814990 1816467252 190s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 190s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.017 0 0.017 0 0 190s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 190s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 190s - attr(*, "randomSeed")= int [1:7] 10407 -1371615447 -889757879 1692656974 -1723952224 1378814990 1816467252 190s DH segmentation (locally-indexed) rows: 190s startRow endRow 190s 1 10 7594 190s int [1:7599] 1 2 3 4 5 6 7 8 9 10 ... 190s DH segmentation rows: 190s startRow endRow 190s 1 10 7594 190s Segmenting DH signals...done 190s DH segmentation table: 190s dhStart dhEnd dhNbrOfLoci dhMean 190s 1 554484 143926517 2120 0.5101 190s startRow endRow 190s 1 10 7594 190s Rows: 190s [1] 1 190s TCN segmentation rows: 190s startRow endRow 190s 1 1 7599 190s TCN and DH segmentation rows: 190s startRow endRow 190s 1 1 7599 190s startRow endRow 190s 1 10 7594 190s NULL 190s TCN segmentation (expanded) rows: 190s startRow endRow 190s 1 1 7599 190s TCN and DH segmentation rows: 190s startRow endRow 190s 1 1 7599 190s 2 7600 10267 190s 3 10268 14658 190s startRow endRow 190s 1 10 7594 190s startRow endRow 190s 1 1 7599 190s Total CN segmentation table (expanded): 190s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 190s 1 3 554484 143926517 7599 1.3859 2120 2120 190s (TCN,DH) segmentation for one total CN segment: 190s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 190s 1 1 1 3 554484 143926517 7599 1.3859 2120 190s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 190s 1 2120 554484 143926517 2120 0.5101 190s Total CN segment #1 ([ 554484,1.43927e+08]) of 3...done 190s Total CN segment #2 ([1.43927e+08,1.8545e+08]) of 3... 190s Number of TCN loci in segment: 2668 190s Locus data for TCN segment: 190s 'data.frame': 2668 obs. of 9 variables: 190s $ chromosome: int 3 3 3 3 3 3 3 3 3 3 ... 190s $ x : num 1.44e+08 1.44e+08 1.44e+08 1.44e+08 1.44e+08 ... 190s $ CT : num 2.1 2.1 2.09 1.8 2.34 ... 190s $ betaT : num 0.027542 1.030222 1.094093 0.046763 -0.000948 ... 190s $ betaTN : num 0.027542 1.030222 1.094093 0.046763 -0.000948 ... 190s $ betaN : num 0.1624 0.8788 0.8225 0.1201 0.0317 ... 190s $ muN : num 0 1 1 0 0 1 0 0 0 0 ... 190s $ index : int 7600 7601 7602 7603 7604 7605 7606 7607 7608 7609 ... 190s $ rho : num NA NA NA NA NA NA NA NA NA NA ... 190s Number of loci: 2668 190s Number of SNPs: 775 (29.05%) 190s Number of heterozygous SNPs: 775 (100.00%) 190s Chromosome: 3 190s Segmenting DH signals... 190s Segmenting by CBS... 190s Chromosome: 3 190s Random seed temporarily set (seed=c(10407, -1371615447, -889757879, 1692656974, -1723952224, 1378814990, 1816467252), kind="L'Ecuyer-CMRG") 190s Segmenting by CBS...done 190s List of 4 190s $ data :'data.frame': 2668 obs. of 4 variables: 190s ..$ chromosome: int [1:2668] 3 3 3 3 3 3 3 3 3 3 ... 190s ..$ x : num [1:2668] 1.44e+08 1.44e+08 1.44e+08 1.44e+08 1.44e+08 ... 190s ..$ y : num [1:2668] NA NA NA NA NA NA NA NA NA NA ... 190s ..$ index : int [1:2668] 1 2 3 4 5 6 7 8 9 10 ... 190s $ output :'data.frame': 1 obs. of 6 variables: 190s ..$ sampleName: chr NA 190s ..$ chromosome: int 3 190s ..$ start : num 1.44e+08 190s ..$ end : num 1.85e+08 190s ..$ nbrOfLoci : int 775 190s ..$ mean : num 0.097 190s $ segRows:'data.frame': 1 obs. of 2 variables: 190s ..$ startRow: int 15 190s ..$ endRow : int 2664 190s $ params :List of 5 190s ..$ alpha : num 0.001 190s ..$ undo : num 0 190s ..$ joinSegments : logi TRUE 190s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 190s .. ..$ chromosome: int 3 190s .. ..$ start : num 1.44e+08 190s .. ..$ end : num 1.85e+08 190s ..$ seed : int [1:7] 10407 -1371615447 -889757879 1692656974 -1723952224 1378814990 1816467252 190s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 190s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.005 0 0.005 0 0 190s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 190s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 190s - attr(*, "randomSeed")= int [1:7] 10407 -1371615447 -889757879 1692656974 -1723952224 1378814990 1816467252 190s DH segmentation (locally-indexed) rows: 190s startRow endRow 190s 1 15 2664 190s int [1:2668] 7600 7601 7602 7603 7604 7605 7606 7607 7608 7609 ... 190s DH segmentation rows: 190s startRow endRow 190s 1 7614 10263 190s Segmenting DH signals...done 190s DH segmentation table: 190s dhStart dhEnd dhNbrOfLoci dhMean 190s 1 143926517 185449813 775 0.097 190s startRow endRow 190s 1 7614 10263 190s Rows: 190s [1] 2 190s TCN segmentation rows: 190s startRow endRow 190s 2 7600 10267 190s TCN and DH segmentation rows: 190s startRow endRow 190s 2 7600 10267 190s startRow endRow 190s 1 7614 10263 190s startRow endRow 190s 1 1 7599 190s TCN segmentation (expanded) rows: 190s startRow endRow 190s 1 1 7599 190s 2 7600 10267 190s TCN and DH segmentation rows: 190s startRow endRow 190s 1 1 7599 190s 2 7600 10267 190s 3 10268 14658 190s startRow endRow 190s 1 10 7594 190s 2 7614 10263 190s startRow endRow 190s 1 1 7599 190s 2 7600 10267 190s Total CN segmentation table (expanded): 190s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 190s 2 3 143926517 185449813 2668 2.0704 775 775 190s (TCN,DH) segmentation for one total CN segment: 190s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 190s 2 2 1 3 143926517 185449813 2668 2.0704 775 190s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 190s 2 775 143926517 185449813 775 0.097 190s Total CN segment #2 ([1.43927e+08,1.8545e+08]) of 3...done 190s Total CN segment #3 ([1.8545e+08,2.47137e+08]) of 3... 190s Number of TCN loci in segment: 4391 190s Locus data for TCN segment: 190s 'data.frame': 4391 obs. of 9 variables: 190s $ chromosome: int 3 3 3 3 3 3 3 3 3 3 ... 190s $ x : num 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 190s $ CT : num 2.93 2.15 2.82 2.93 2.46 ... 190s $ betaT : num -0.169 0.609 1.028 0.525 0.968 ... 190s $ betaTN : num -0.169 0.609 1.028 0.525 0.968 ... 190s $ betaN : num 0.25 0.38 0.919 0.34 0.783 ... 190s $ muN : num 0 0.5 1 0.5 1 1 0 1 0 1 ... 190s $ index : int 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 190s $ rho : num NA 0.2186 NA 0.0503 NA ... 190s Number of loci: 4391 190s Number of SNPs: 1314 (29.92%) 190s Number of heterozygous SNPs: 1314 (100.00%) 190s Chromosome: 3 190s Segmenting DH signals... 190s Segmenting by CBS... 190s Chromosome: 3 190s Random seed temporarily set (seed=c(10407, -1371615447, -889757879, 1692656974, -1723952224, 1378814990, 1816467252), kind="L'Ecuyer-CMRG") 190s Segmenting by CBS...done 190s List of 4 190s $ data :'data.frame': 4391 obs. of 4 variables: 190s ..$ chromosome: int [1:4391] 3 3 3 3 3 3 3 3 3 3 ... 190s ..$ x : num [1:4391] 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 190s ..$ y : num [1:4391] NA 0.2186 NA 0.0503 NA ... 190s ..$ index : int [1:4391] 1 2 3 4 5 6 7 8 9 10 ... 190s $ output :'data.frame': 1 obs. of 6 variables: 190s ..$ sampleName: chr NA 190s ..$ chromosome: int 3 190s ..$ start : num 1.85e+08 190s ..$ end : num 2.47e+08 190s ..$ nbrOfLoci : int 1314 190s ..$ mean : num 0.23 190s $ segRows:'data.frame': 1 obs. of 2 variables: 190s ..$ startRow: int 2 190s ..$ endRow : int 4388 190s $ params :List of 5 190s ..$ alpha : num 0.001 190s ..$ undo : num 0 190s ..$ joinSegments : logi TRUE 190s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 190s .. ..$ chromosome: int 3 190s .. ..$ start : num 1.85e+08 190s .. ..$ end : num 2.47e+08 190s ..$ seed : int [1:7] 10407 -1371615447 -889757879 1692656974 -1723952224 1378814990 1816467252 190s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 190s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.01 0 0.01 0 0 190s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 190s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 190s - attr(*, "randomSeed")= int [1:7] 10407 -1371615447 -889757879 1692656974 -1723952224 1378814990 1816467252 190s DH segmentation (locally-indexed) rows: 190s startRow endRow 190s 1 2 4388 190s int [1:4391] 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 190s DH segmentation rows: 190s startRow endRow 190s 1 10269 14655 190s Segmenting DH signals...done 190s DH segmentation table: 190s dhStart dhEnd dhNbrOfLoci dhMean 190s 1 185449813 247137334 1314 0.2295 190s startRow endRow 190s 1 10269 14655 190s Rows: 190s [1] 3 190s TCN segmentation rows: 190s startRow endRow 190s 3 10268 14658 190s TCN and DH segmentation rows: 190s startRow endRow 190s 3 10268 14658 190s startRow endRow 190s 1 10269 14655 190s startRow endRow 190s 1 1 7599 190s 2 7600 10267 190s TCN segmentation (expanded) rows: 190s startRow endRow 190s 1 1 7599 190s 2 7600 10267 190s 3 10268 14658 190s TCN and DH segmentation rows: 190s startRow endRow 190s 1 1 7599 190s 2 7600 10267 190s 3 10268 14658 190s startRow endRow 190s 1 10 7594 190s 2 7614 10263 190s 3 10269 14655 190s startRow endRow 190s 1 1 7599 190s 2 7600 10267 190s 3 10268 14658 190s Total CN segmentation table (expanded): 190s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 190s 3 3 185449813 247137334 4391 2.6341 1314 1314 190s (TCN,DH) segmentation for one total CN segment: 190s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 190s 3 3 1 3 185449813 247137334 4391 2.6341 1314 190s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 190s 3 1314 185449813 247137334 1314 0.2295 190s Total CN segment #3 ([1.8545e+08,2.47137e+08]) of 3...done 190s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 190s 1 3 1 1 554484 143926517 7599 1.3859 2120 190s 2 3 2 1 143926517 185449813 2668 2.0704 775 190s 3 3 3 1 185449813 247137334 4391 2.6341 1314 190s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 190s 1 2120 554484 143926517 2120 0.5101 190s 2 775 143926517 185449813 775 0.0970 190s 3 1314 185449813 247137334 1314 0.2295 190s Calculating (C1,C2) per segment... 190s Calculating (C1,C2) per segment...done 190s Number of segments: 3 190s Segmenting paired tumor-normal signals using Paired PSCBS...done 190s Post-segmenting TCNs... 190s Number of segments: 3 190s Number of chromosomes: 1 190s [1] 3 190s Chromosome 1 ('chr03') of 1... 190s Rows: 190s [1] 1 2 3 190s Number of segments: 3 190s TCN segment #1 ('1') of 3... 190s Nothing todo. Only one DH segmentation. Skipping. 190s TCN segment #1 ('1') of 3...done 190s TCN segment #2 ('2') of 3... 190s Nothing todo. Only one DH segmentation. Skipping. 190s TCN segment #2 ('2') of 3...done 190s TCN segment #3 ('3') of 3... 190s Nothing todo. Only one DH segmentation. Skipping. 190s TCN segment #3 ('3') of 3...done 190s Chromosome 1 ('chr03') of 1...done 190s Update (C1,C2) per segment... 190s Update (C1,C2) per segment...done 190s Post-segmenting TCNs...done 190s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 190s 1 3 1 1 554484 143926517 7599 1.3859 2120 190s 2 3 2 1 143926517 185449813 2668 2.0704 775 190s 3 3 3 1 185449813 247137334 4391 2.6341 1314 190s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 190s 1 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 190s 2 775 143926517 185449813 775 0.0970 0.9347856 1.135614 190s 3 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 190s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 190s 1 3 1 1 554484 143926517 7599 1.3859 2120 190s 2 3 2 1 143926517 185449813 2668 2.0704 775 190s 3 3 3 1 185449813 247137334 4391 2.6341 1314 190s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 190s 1 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 190s 2 775 143926517 185449813 775 0.0970 0.9347856 1.135614 190s 3 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 190s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 190s 1 3 1 1 554484 143926517 7599 1.3859 2120 190s 2 3 2 1 143926517 185449813 2668 2.0704 775 190s 3 3 3 1 185449813 247137334 4391 2.6341 1314 190s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 190s 1 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 190s 2 775 143926517 185449813 775 0.0970 0.9347856 1.135614 190s 3 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 190s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 190s 1 3 1 1 554484 143926517 7599 1.3859 2120 190s 2 3 2 1 143926517 185449813 2668 2.0704 775 190s 3 3 3 1 185449813 247137334 4391 2.6341 1314 190s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 190s 1 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 190s 2 775 143926517 185449813 775 0.0970 0.9347856 1.135614 190s 3 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 190s Chromosome #3 ('Chr03') of 3...done 190s Merging (independently) segmented chromosome... 190s List of 5 190s $ data :Classes 'PairedPSCNData' and 'data.frame': 43974 obs. of 8 variables: 190s ..$ chromosome: int [1:43974] 1 1 1 1 1 1 1 1 1 1 ... 190s ..$ x : num [1:43974] 554484 730720 782343 878522 916294 ... 190s ..$ CT : num [1:43974] 1.88 1.8 1.59 1.64 1.53 ... 190s ..$ betaT : num [1:43974] 0.0646 0.1672 0.9284 0.113 0.7209 ... 190s ..$ betaTN : num [1:43974] -0.0515 -0.1172 1.0194 0.031 0.8604 ... 190s ..$ betaN : num [1:43974] 0.116 0.284 0.909 0.082 0.86 ... 190s ..$ muN : num [1:43974] 0 0 1 0 1 1 1 0 1 0.5 ... 190s ..$ rho : num [1:43974] NA NA NA NA NA ... 190s $ output :Classes 'PairedPSCNSegments' and 'data.frame': 11 obs. of 15 variables: 190s ..$ chromosome : int [1:11] 1 1 1 NA 2 2 2 NA 3 3 ... 190s ..$ tcnId : int [1:11] 1 2 3 NA 1 2 3 NA 1 2 ... 190s ..$ dhId : int [1:11] 1 1 1 NA 1 1 1 NA 1 1 ... 190s ..$ tcnStart : num [1:11] 5.54e+05 1.44e+08 1.85e+08 NA 5.54e+05 ... 190s ..$ tcnEnd : num [1:11] 1.44e+08 1.85e+08 2.47e+08 NA 1.44e+08 ... 190s ..$ tcnNbrOfLoci: int [1:11] 7599 2668 4391 NA 7599 2668 4391 NA 7599 2668 ... 190s ..$ tcnMean : num [1:11] 1.39 2.07 2.63 NA 1.39 ... 190s ..$ tcnNbrOfSNPs: int [1:11] 2120 775 1314 NA 2120 775 1314 NA 2120 775 ... 190s ..$ tcnNbrOfHets: int [1:11] 2120 775 1314 NA 2120 775 1314 NA 2120 775 ... 190s ..$ dhStart : num [1:11] 5.54e+05 1.44e+08 1.85e+08 NA 5.54e+05 ... 190s ..$ dhEnd : num [1:11] 1.44e+08 1.85e+08 2.47e+08 NA 1.44e+08 ... 190s ..$ dhNbrOfLoci : int [1:11] 2120 775 1314 NA 2120 775 1314 NA 2120 775 ... 190s ..$ dhMean : num [1:11] 0.51 0.097 0.23 NA 0.51 ... 190s ..$ c1Mean : num [1:11] 0.339 0.935 1.015 NA 0.339 ... 190s ..$ c2Mean : num [1:11] 1.05 1.14 1.62 NA 1.05 ... 190s $ tcnSegRows:'data.frame': 11 obs. of 2 variables: 190s ..$ startRow: int [1:11] 1 7600 10268 NA 14659 22258 24926 NA 29317 36916 ... 190s ..$ endRow : int [1:11] 7599 10267 14658 NA 22257 24925 29316 NA 36915 39583 ... 190s $ dhSegRows :'data.frame': 11 obs. of 2 variables: 190s ..$ startRow: int [1:11] 10 7614 10269 NA 14668 22272 24927 NA 29326 36930 ... 190s ..$ endRow : int [1:11] 7594 10263 14655 NA 22252 24921 29313 NA 36910 39579 ... 190s $ params :List of 7 190s ..$ alphaTCN : num 0.009 190s ..$ alphaDH : num 0.001 190s ..$ flavor : chr "tcn&dh" 190s ..$ tbn : logi FALSE 190s ..$ joinSegments : logi TRUE 190s ..$ knownSegments:'data.frame': 0 obs. of 3 variables: 190s .. ..$ chromosome: int(0) 190s .. ..$ start : int(0) 190s .. ..$ end : int(0) 190s ..$ seed : int [1:7] 10407 1066287653 -51199871 161854402 -1995183193 1503453565 -747102133 190s - attr(*, "class")= chr [1:3] "PairedPSCBS" "PSCBS" "AbstractCBS" 190s Merging (independently) segmented chromosome...done 190s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 190s 1 1 1 1 554484 143926517 7599 1.3859 2120 190s 2 1 2 1 143926517 185449813 2668 2.0704 775 190s 3 1 3 1 185449813 247137334 4391 2.6341 1314 190s 4 NA NA NA NA NA NA NA NA 190s 5 2 1 1 554484 143926517 7599 1.3859 2120 190s 6 2 2 1 143926517 185449813 2668 2.0704 775 190s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 190s 1 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 190s 2 775 143926517 185449813 775 0.0970 0.9347856 1.135614 190s 3 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 190s 4 NA NA NA NA NA NA NA 190s 5 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 190s 6 775 143926517 185449813 775 0.0970 0.9347856 1.135614 190s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 190s 6 2 2 1 143926517 185449813 2668 2.0704 775 190s 7 2 3 1 185449813 247137334 4391 2.6341 1314 190s 8 NA NA NA NA NA NA NA NA 190s 9 3 1 1 554484 143926517 7599 1.3859 2120 190s 10 3 2 1 143926517 185449813 2668 2.0704 775 190s 11 3 3 1 185449813 247137334 4391 2.6341 1314 190s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 190s 6 775 143926517 185449813 775 0.0970 0.9347856 1.135614 190s 7 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 190s 8 NA NA NA NA NA NA NA 190s 9 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 190s 10 775 143926517 185449813 775 0.0970 0.9347856 1.135614 190s 11 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 190s Segmenting multiple chromosomes...done 190s Segmenting paired tumor-normal signals using Paired PSCBS...done 190s - segmentByPairedPSCBS() using 'multisession' futures ... 190s Segmenting paired tumor-normal signals using Paired PSCBS... 190s Calling genotypes from normal allele B fractions... 190s num [1:44010] 0.8274 0.5072 0.1671 0.1609 0.0421 ... 190s Called genotypes: 190s num [1:44010] 1 0.5 0 0 0 0 1 0 1 0.5 ... 190s - attr(*, "modelFit")=List of 1 190s ..$ :List of 7 190s .. ..$ flavor : chr "density" 190s .. ..$ cn : int 2 190s .. ..$ nbrOfGenotypeGroups: int 3 190s .. ..$ tau : num [1:2] 0.312 0.678 190s .. ..$ n : int 43920 190s .. ..$ fit :Classes 'PeaksAndValleys' and 'data.frame': 5 obs. of 3 variables: 190s .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 190s .. .. ..$ x : num [1:5] 0.0999 0.312 0.4986 0.6775 0.8922 190s .. .. ..$ density: num [1:5] 1.622 0.465 1.125 0.496 1.587 190s .. ..$ fitValleys :Classes 'PeaksAndValleys' and 'data.frame': 2 obs. of 3 variables: 190s .. .. ..$ type : chr [1:2] "valley" "valley" 190s .. .. ..$ x : num [1:2] 0.312 0.678 190s .. .. ..$ density: num [1:2] 0.465 0.496 190s ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 190s muN 190s 0 0.5 1 190s 15627 12633 15750 190s Calling genotypes from normal allele B fractions...done 190s Normalizing betaT using betaN (TumorBoost)... 190s Normalized BAFs: 190s num [1:44010] 0.9301 0.1667 0.0685 0.0995 0.0155 ... 190s - attr(*, "modelFit")=List of 5 190s ..$ method : chr "normalizeTumorBoost" 190s ..$ flavor : chr "v4" 190s ..$ delta : num [1:44010] -0.17264 0.00239 0.1671 0.16085 0.04213 ... 190s .. ..- attr(*, "modelFit")=List of 1 190s .. .. ..$ :List of 7 190s .. .. .. ..$ flavor : chr "density" 190s .. .. .. ..$ cn : int 2 190s .. .. .. ..$ nbrOfGenotypeGroups: int 3 190s .. .. .. ..$ tau : num [1:2] 0.312 0.678 190s .. .. .. ..$ n : int 43920 190s .. .. .. ..$ fit :Classes 'PeaksAndValleys' and 'data.frame': 5 obs. of 3 variables: 190s .. .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 190s .. .. .. .. ..$ x : num [1:5] 0.0999 0.312 0.4986 0.6775 0.8922 190s .. .. .. .. ..$ density: num [1:5] 1.622 0.465 1.125 0.496 1.587 190s .. .. .. ..$ fitValleys :Classes 'PeaksAndValleys' and 'data.frame': 2 obs. of 3 variables: 190s .. .. .. .. ..$ type : chr [1:2] "valley" "valley" 190s .. .. .. .. ..$ x : num [1:2] 0.312 0.678 190s .. .. .. .. ..$ density: num [1:2] 0.465 0.496 190s .. .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 190s ..$ preserveScale: logi FALSE 190s ..$ scaleFactor : num NA 190s Normalizing betaT using betaN (TumorBoost)...done 190s Setup up data... 190s 'data.frame': 44010 obs. of 7 variables: 190s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 190s $ x : num 1145994 2941694 3710825 4240737 4276892 ... 190s $ CT : num 1.63 1.4 1.41 1.17 1.16 ... 190s $ betaT : num 0.7574 0.169 0.2357 0.2604 0.0576 ... 190s $ betaTN : num 0.9301 0.1667 0.0685 0.0995 0.0155 ... 190s ..- attr(*, "modelFit")=List of 5 190s .. ..$ method : chr "normalizeTumorBoost" 190s .. ..$ flavor : chr "v4" 190s .. ..$ delta : num [1:44010] -0.17264 0.00239 0.1671 0.16085 0.04213 ... 190s .. .. ..- attr(*, "modelFit")=List of 1 190s .. .. .. ..$ :List of 7 190s .. .. .. .. ..$ flavor : chr "density" 190s .. .. .. .. ..$ cn : int 2 190s .. .. .. .. ..$ nbrOfGenotypeGroups: int 3 190s .. .. .. .. ..$ tau : num [1:2] 0.312 0.678 190s .. .. .. .. ..$ n : int 43920 190s .. .. .. .. ..$ fit :Classes 'PeaksAndValleys' and 'data.frame': 5 obs. of 3 variables: 190s .. .. .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 190s .. .. .. .. .. ..$ x : num [1:5] 0.0999 0.312 0.4986 0.6775 0.8922 190s .. .. .. .. .. ..$ density: num [1:5] 1.622 0.465 1.125 0.496 1.587 190s .. .. .. .. ..$ fitValleys :Classes 'PeaksAndValleys' and 'data.frame': 2 obs. of 3 variables: 190s .. .. .. .. .. ..$ type : chr [1:2] "valley" "valley" 190s .. .. .. .. .. ..$ x : num [1:2] 0.312 0.678 190s .. .. .. .. .. ..$ density: num [1:2] 0.465 0.496 190s .. .. .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 190s .. ..$ preserveScale: logi FALSE 190s .. ..$ scaleFactor : num NA 190s $ betaN : num 0.8274 0.5072 0.1671 0.1609 0.0421 ... 190s $ muN : num 1 0.5 0 0 0 0 1 0 1 0.5 ... 190s ..- attr(*, "modelFit")=List of 1 190s .. ..$ :List of 7 190s .. .. ..$ flavor : chr "density" 190s .. .. ..$ cn : int 2 190s .. .. ..$ nbrOfGenotypeGroups: int 3 190s .. .. ..$ tau : num [1:2] 0.312 0.678 190s .. .. ..$ n : int 43920 190s .. .. ..$ fit :Classes 'PeaksAndValleys' and 'data.frame': 5 obs. of 3 variables: 190s .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 190s .. .. .. ..$ x : num [1:5] 0.0999 0.312 0.4986 0.6775 0.8922 190s .. .. .. ..$ density: num [1:5] 1.622 0.465 1.125 0.496 1.587 190s .. .. ..$ fitValleys :Classes 'PeaksAndValleys' and 'data.frame': 2 obs. of 3 variables: 190s .. .. .. ..$ type : chr [1:2] "valley" "valley" 190s .. .. .. ..$ x : num [1:2] 0.312 0.678 190s .. .. .. ..$ density: num [1:2] 0.465 0.496 190s .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 190s Setup up data...done 190s Dropping loci for which TCNs are missing... 190s Number of loci dropped: 36 190s Dropping loci for which TCNs are missing...done 190s Ordering data along genome... 190s 'data.frame': 43974 obs. of 7 variables: 190s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 190s $ x : num 554484 730720 782343 878522 916294 ... 190s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 190s $ betaT : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 190s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 190s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 190s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 190s Ordering data along genome...done 190s Segmenting multiple chromosomes... 190s Number of chromosomes: 3 190s Random seed temporarily set (seed=c(48879), kind="L'Ecuyer-CMRG") 190s Produced 3 seeds from this stream for future usage 190s Chromosome #1 ('Chr01') of 3... 190s 'data.frame': 14658 obs. of 8 variables: 190s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 190s $ x : num 554484 730720 782343 878522 916294 ... 190s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 190s $ betaT : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 190s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 190s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 190s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 190s $ index : int 1 2 3 4 5 6 7 8 9 10 ... 190s Known segments: 190s [1] chromosome start end 190s <0 rows> (or 0-length row.names) 190s Chromosome #1 ('Chr01') of 3...done 190s Chromosome #2 ('Chr02') of 3... 190s 'data.frame': 14658 obs. of 8 variables: 190s $ chromosome: int 2 2 2 2 2 2 2 2 2 2 ... 190s $ x : num 554484 730720 782343 878522 916294 ... 190s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 190s $ betaT : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 190s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 190s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 190s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 190s $ index : int 14659 14660 14661 14662 14663 14664 14665 14666 14667 14668 ... 190s Known segments: 190s [1] chromosome start end 190s <0 rows> (or 0-length row.names) 190s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 190s Chromosome #2 ('Chr02') of 3...done 190s Chromosome #3 ('Chr03') of 3... 190s 'data.frame': 14658 obs. of 8 variables: 190s $ chromosome: int 3 3 3 3 3 3 3 3 3 3 ... 190s $ x : num 554484 730720 782343 878522 916294 ... 190s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 190s $ betaT : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 190s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 190s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 190s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 190s $ index : int 29317 29318 29319 29320 29321 29322 29323 29324 29325 29326 ... 190s Known segments: 190s [1] chromosome start end 190s <0 rows> (or 0-length row.names) 190s Random seed temporarily set (seed=c(10407, -821273412, -52578226, 1415511586, 721384351, -665928286, 1316562960), kind="L'Ecuyer-CMRG") 190s Segmenting by CBS...done 190s List of 4 190s $ data :'data.frame': 14658 obs. of 4 variables: 190s ..$ chromosome: int [1:14658] 1 1 1 1 1 1 1 1 1 1 ... 190s ..$ x : num [1:14658] 554484 730720 782343 878522 916294 ... 190s ..$ y : num [1:14658] 1.88 1.8 1.59 1.64 1.53 ... 190s ..$ index : int [1:14658] 1 2 3 4 5 6 7 8 9 10 ... 190s $ output :'data.frame': 3 obs. of 6 variables: 190s ..$ sampleName: chr [1:3] NA NA NA 190s ..$ chromosome: int [1:3] 1 1 1 190s ..$ start : num [1:3] 5.54e+05 1.44e+08 1.85e+08 190s ..$ end : num [1:3] 1.44e+08 1.85e+08 2.47e+08 190s ..$ nbrOfLoci : int [1:3] 7599 2668 4391 190s ..$ mean : num [1:3] 1.39 2.07 2.63 190s $ segRows:'data.frame': 3 obs. of 2 variables: 190s ..$ startRow: int [1:3] 1 7600 10268 190s ..$ endRow : int [1:3] 7599 10267 14658 190s $ params :List of 5 190s ..$ alpha : num 0.009 190s ..$ undo : num 0 190s ..$ joinSegments : logi TRUE 190s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 190s .. ..$ chromosome: int 1 190s .. ..$ start : num -Inf 190s .. ..$ end : num Inf 190s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 190s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 190s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.264 0 0.264 0 0 190s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 190s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 190s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 190s Identification of change points by total copy numbers...done 190s Restructure TCN segmentation results... 190s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean 190s 1 1 554484 143926517 7599 1.3859 190s 2 1 143926517 185449813 2668 2.0704 190s 3 1 185449813 247137334 4391 2.6341 190s Number of TCN segments: 3 190s Restructure TCN segmentation results...done 190s Total CN segment #1 ([ 554484,1.43927e+08]) of 3... 190s Number of TCN loci in segment: 7599 190s Locus data for TCN segment: 190s 'data.frame': 7599 obs. of 9 variables: 190s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 190s $ x : num 554484 730720 782343 878522 916294 ... 190s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 190s $ betaT : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 190s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 190s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 190s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 190s $ index : int 1 2 3 4 5 6 7 8 9 10 ... 190s $ rho : num NA NA NA NA NA ... 190s Number of loci: 7599 190s Number of SNPs: 2120 (27.90%) 190s Number of heterozygous SNPs: 2120 (100.00%) 190s Chromosome: 1 190s Segmenting DH signals... 190s Segmenting by CBS... 190s Chromosome: 1 190s Random seed temporarily set (seed=c(10407, -821273412, -52578226, 1415511586, 721384351, -665928286, 1316562960), kind="L'Ecuyer-CMRG") 190s Segmenting by CBS...done 190s List of 4 190s $ data :'data.frame': 7599 obs. of 4 variables: 190s ..$ chromosome: int [1:7599] 1 1 1 1 1 1 1 1 1 1 ... 190s ..$ x : num [1:7599] 554484 730720 782343 878522 916294 ... 190s ..$ y : num [1:7599] NA NA NA NA NA ... 190s ..$ index : int [1:7599] 1 2 3 4 5 6 7 8 9 10 ... 190s $ output :'data.frame': 1 obs. of 6 variables: 190s ..$ sampleName: chr NA 190s ..$ chromosome: int 1 190s ..$ start : num 554484 190s ..$ end : num 1.44e+08 190s ..$ nbrOfLoci : int 2120 190s ..$ mean : num 0.51 190s $ segRows:'data.frame': 1 obs. of 2 variables: 190s ..$ startRow: int 10 190s ..$ endRow : int 7594 190s $ params :List of 5 190s ..$ alpha : num 0.001 190s ..$ undo : num 0 190s ..$ joinSegments : logi TRUE 190s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 190s .. ..$ chromosome: int 1 190s .. ..$ start : num 554484 190s .. ..$ end : num 1.44e+08 190s ..$ seed : int [1:7] 10407 -821273412 -52578226 1415511586 721384351 -665928286 1316562960 190s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 190s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.017 0 0.018 0 0 190s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 190s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 190s - attr(*, "randomSeed")= int [1:7] 10407 -821273412 -52578226 1415511586 721384351 -665928286 1316562960 190s DH segmentation (locally-indexed) rows: 190s startRow endRow 190s 1 10 7594 190s int [1:7599] 1 2 3 4 5 6 7 8 9 10 ... 190s DH segmentation rows: 190s startRow endRow 190s 1 10 7594 190s Segmenting DH signals...done 190s DH segmentation table: 190s dhStart dhEnd dhNbrOfLoci dhMean 190s 1 554484 143926517 2120 0.5101 190s startRow endRow 190s 1 10 7594 190s Rows: 190s [1] 1 190s TCN segmentation rows: 190s startRow endRow 190s 1 1 7599 190s TCN and DH segmentation rows: 190s startRow endRow 190s 1 1 7599 190s startRow endRow 190s 1 10 7594 190s NULL 190s TCN segmentation (expanded) rows: 190s startRow endRow 190s 1 1 7599 190s TCN and DH segmentation rows: 190s startRow endRow 190s 1 1 7599 190s 2 7600 10267 190s 3 10268 14658 190s startRow endRow 190s 1 10 7594 190s startRow endRow 190s 1 1 7599 190s Total CN segmentation table (expanded): 190s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 190s 1 1 554484 143926517 7599 1.3859 2120 2120 190s (TCN,DH) segmentation for one total CN segment: 190s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 190s 1 1 1 1 554484 143926517 7599 1.3859 2120 190s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 190s 1 2120 554484 143926517 2120 0.5101 190s Total CN segment #1 ([ 554484,1.43927e+08]) of 3...done 190s Total CN segment #2 ([1.43927e+08,1.8545e+08]) of 3... 190s Number of TCN loci in segment: 2668 190s Locus data for TCN segment: 190s 'data.frame': 2668 obs. of 9 variables: 190s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 190s $ x : num 1.44e+08 1.44e+08 1.44e+08 1.44e+08 1.44e+08 ... 190s $ CT : num 2.1 2.1 2.09 1.8 2.34 ... 190s $ betaT : num 0.027542 1.030222 1.094093 0.046763 -0.000948 ... 190s $ betaTN : num 0.027542 1.030222 1.094093 0.046763 -0.000948 ... 190s $ betaN : num 0.1624 0.8788 0.8225 0.1201 0.0317 ... 190s $ muN : num 0 1 1 0 0 1 0 0 0 0 ... 190s $ index : int 7600 7601 7602 7603 7604 7605 7606 7607 7608 7609 ... 190s $ rho : num NA NA NA NA NA NA NA NA NA NA ... 190s Number of loci: 2668 190s Number of SNPs: 775 (29.05%) 190s Number of heterozygous SNPs: 775 (100.00%) 190s Chromosome: 1 190s Segmenting DH signals... 190s Segmenting by CBS... 190s Chromosome: 1 190s Random seed temporarily set (seed=c(10407, -821273412, -52578226, 1415511586, 721384351, -665928286, 1316562960), kind="L'Ecuyer-CMRG") 190s Segmenting by CBS...done 190s List of 4 190s $ data :'data.frame': 2668 obs. of 4 variables: 190s ..$ chromosome: int [1:2668] 1 1 1 1 1 1 1 1 1 1 ... 190s ..$ x : num [1:2668] 1.44e+08 1.44e+08 1.44e+08 1.44e+08 1.44e+08 ... 190s ..$ y : num [1:2668] NA NA NA NA NA NA NA NA NA NA ... 190s ..$ index : int [1:2668] 1 2 3 4 5 6 7 8 9 10 ... 190s $ output :'data.frame': 1 obs. of 6 variables: 190s ..$ sampleName: chr NA 190s ..$ chromosome: int 1 190s ..$ start : num 1.44e+08 190s ..$ end : num 1.85e+08 190s ..$ nbrOfLoci : int 775 190s ..$ mean : num 0.097 190s $ segRows:'data.frame': 1 obs. of 2 variables: 190s ..$ startRow: int 15 190s ..$ endRow : int 2664 190s $ params :List of 5 190s ..$ alpha : num 0.001 190s ..$ undo : num 0 190s ..$ joinSegments : logi TRUE 190s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 190s .. ..$ chromosome: int 1 190s .. ..$ start : num 1.44e+08 190s .. ..$ end : num 1.85e+08 190s ..$ seed : int [1:7] 10407 -821273412 -52578226 1415511586 721384351 -665928286 1316562960 190s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 190s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.005 0 0.005 0 0 190s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 190s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 190s - attr(*, "randomSeed")= int [1:7] 10407 -821273412 -52578226 1415511586 721384351 -665928286 1316562960 190s DH segmentation (locally-indexed) rows: 190s startRow endRow 190s 1 15 2664 190s int [1:2668] 7600 7601 7602 7603 7604 7605 7606 7607 7608 7609 ... 190s DH segmentation rows: 190s startRow endRow 190s 1 7614 10263 190s Segmenting DH signals...done 190s DH segmentation table: 190s dhStart dhEnd dhNbrOfLoci dhMean 190s 1 143926517 185449813 775 0.097 190s startRow endRow 190s 1 7614 10263 190s Rows: 190s [1] 2 190s TCN segmentation rows: 190s startRow endRow 190s 2 7600 10267 190s TCN and DH segmentation rows: 190s startRow endRow 190s 2 7600 10267 190s startRow endRow 190s 1 7614 10263 190s startRow endRow 190s 1 1 7599 190s TCN segmentation (expanded) rows: 190s startRow endRow 190s 1 1 7599 190s 2 7600 10267 190s TCN and DH segmentation rows: 190s startRow endRow 190s 1 1 7599 190s 2 7600 10267 190s 3 10268 14658 190s startRow endRow 190s 1 10 7594 190s 2 7614 10263 190s startRow endRow 190s 1 1 7599 190s 2 7600 10267 190s Total CN segmentation table (expanded): 190s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 190s 2 1 143926517 185449813 2668 2.0704 775 775 190s (TCN,DH) segmentation for one total CN segment: 190s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 190s 2 2 1 1 143926517 185449813 2668 2.0704 775 190s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 190s 2 775 143926517 185449813 775 0.097 190s Total CN segment #2 ([1.43927e+08,1.8545e+08]) of 3...done 190s Total CN segment #3 ([1.8545e+08,2.47137e+08]) of 3... 190s Number of TCN loci in segment: 4391 190s Locus data for TCN segment: 190s 'data.frame': 4391 obs. of 9 variables: 190s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 190s $ x : num 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 190s $ CT : num 2.93 2.15 2.82 2.93 2.46 ... 190s $ betaT : num -0.169 0.609 1.028 0.525 0.968 ... 190s $ betaTN : num -0.169 0.609 1.028 0.525 0.968 ... 190s $ betaN : num 0.25 0.38 0.919 0.34 0.783 ... 190s $ muN : num 0 0.5 1 0.5 1 1 0 1 0 1 ... 190s $ index : int 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 190s $ rho : num NA 0.2186 NA 0.0503 NA ... 190s Number of loci: 4391 190s Number of SNPs: 1314 (29.92%) 190s Number of heterozygous SNPs: 1314 (100.00%) 190s Chromosome: 1 190s Segmenting DH signals... 190s Segmenting by CBS... 190s Chromosome: 1 190s Random seed temporarily set (seed=c(10407, -821273412, -52578226, 1415511586, 721384351, -665928286, 1316562960), kind="L'Ecuyer-CMRG") 190s Segmenting by CBS...done 190s List of 4 190s $ data :'data.frame': 4391 obs. of 4 variables: 190s ..$ chromosome: int [1:4391] 1 1 1 1 1 1 1 1 1 1 ... 190s ..$ x : num [1:4391] 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 190s ..$ y : num [1:4391] NA 0.2186 NA 0.0503 NA ... 190s ..$ index : int [1:4391] 1 2 3 4 5 6 7 8 9 10 ... 190s $ output :'data.frame': 1 obs. of 6 variables: 190s ..$ sampleName: chr NA 190s ..$ chromosome: int 1 190s ..$ start : num 1.85e+08 190s ..$ end : num 2.47e+08 190s ..$ nbrOfLoci : int 1314 190s ..$ mean : num 0.23 190s $ segRows:'data.frame': 1 obs. of 2 variables: 190s ..$ startRow: int 2 190s ..$ endRow : int 4388 190s $ params :List of 5 190s ..$ alpha : num 0.001 190s ..$ undo : num 0 190s ..$ joinSegments : logi TRUE 190s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 190s .. ..$ chromosome: int 1 190s .. ..$ start : num 1.85e+08 190s .. ..$ end : num 2.47e+08 190s ..$ seed : int [1:7] 10407 -821273412 -52578226 1415511586 721384351 -665928286 1316562960 190s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 190s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.009 0 0.009 0 0 190s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 190s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 190s - attr(*, "randomSeed")= int [1:7] 10407 -821273412 -52578226 1415511586 721384351 -665928286 1316562960 190s DH segmentation (locally-indexed) rows: 190s startRow endRow 190s 1 2 4388 190s int [1:4391] 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 190s DH segmentation rows: 190s startRow endRow 190s 1 10269 14655 190s Segmenting DH signals...done 190s DH segmentation table: 190s dhStart dhEnd dhNbrOfLoci dhMean 190s 1 185449813 247137334 1314 0.2295 190s startRow endRow 190s 1 10269 14655 190s Rows: 190s [1] 3 190s TCN segmentation rows: 190s startRow endRow 190s 3 10268 14658 190s TCN and DH segmentation rows: 190s startRow endRow 190s 3 10268 14658 190s startRow endRow 190s 1 10269 14655 190s startRow endRow 190s 1 1 7599 190s 2 7600 10267 190s TCN segmentation (expanded) rows: 190s startRow endRow 190s 1 1 7599 190s 2 7600 10267 190s 3 10268 14658 190s TCN and DH segmentation rows: 190s startRow endRow 190s 1 1 7599 190s 2 7600 10267 190s 3 10268 14658 190s startRow endRow 190s 1 10 7594 190s 2 7614 10263 190s 3 10269 14655 190s startRow endRow 190s 1 1 7599 190s 2 7600 10267 190s 3 10268 14658 190s Total CN segmentation table (expanded): 190s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 190s 3 1 185449813 247137334 4391 2.6341 1314 1314 190s (TCN,DH) segmentation for one total CN segment: 190s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 190s 3 3 1 1 185449813 247137334 4391 2.6341 1314 190s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 190s 3 1314 185449813 247137334 1314 0.2295 190s Total CN segment #3 ([1.8545e+08,2.47137e+08]) of 3...done 190s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 190s 1 1 1 1 554484 143926517 7599 1.3859 2120 190s 2 1 2 1 143926517 185449813 2668 2.0704 775 190s 3 1 3 1 185449813 247137334 4391 2.6341 1314 190s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 190s 1 2120 554484 143926517 2120 0.5101 190s 2 775 143926517 185449813 775 0.0970 190s 3 1314 185449813 247137334 1314 0.2295 190s Calculating (C1,C2) per segment... 190s Calculating (C1,C2) per segment...done 190s Number of segments: 3 190s Segmenting paired tumor-normal signals using Paired PSCBS...done 190s Post-segmenting TCNs... 190s Number of segments: 3 190s Number of chromosomes: 1 190s [1] 1 190s Chromosome 1 ('chr01') of 1... 190s Rows: 190s [1] 1 2 3 190s Number of segments: 3 190s TCN segment #1 ('1') of 3... 190s Nothing todo. Only one DH segmentation. Skipping. 190s TCN segment #1 ('1') of 3...done 190s TCN segment #2 ('2') of 3... 190s Nothing todo. Only one DH segmentation. Skipping. 190s TCN segment #2 ('2') of 3...done 190s TCN segment #3 ('3') of 3... 190s Nothing todo. Only one DH segmentation. Skipping. 190s TCN segment #3 ('3') of 3...done 190s Chromosome 1 ('chr01') of 1...done 190s Update (C1,C2) per segment... 190s Update (C1,C2) per segment...done 190s Segmenting by CBS...done 190s List of 4 190s $ data :'data.frame': 14658 obs. of 4 variables: 190s ..$ chromosome: int [1:14658] 2 2 2 2 2 2 2 2 2 2 ... 190s ..$ x : num [1:14658] 554484 730720 782343 878522 916294 ... 190s ..$ y : num [1:14658] 1.88 1.8 1.59 1.64 1.53 ... 190s ..$ index : int [1:14658] 1 2 3 4 5 6 7 8 9 10 ... 190s $ output :'data.frame': 3 obs. of 6 variables: 190s ..$ sampleName: chr [1:3] NA NA NA 190s ..$ chromosome: int [1:3] 2 2 2 190s ..$ start : num [1:3] 5.54e+05 1.44e+08 1.85e+08 190s ..$ end : num [1:3] 1.44e+08 1.85e+08 2.47e+08 190s ..$ nbrOfLoci : int [1:3] 7599 2668 4391 190s ..$ mean : num [1:3] 1.39 2.07 2.63 190s $ segRows:'data.frame': 3 obs. of 2 variables: 190s ..$ startRow: int [1:3] 1 7600 10268 190s ..$ endRow : int [1:3] 7599 10267 14658 190s $ params :List of 5 190s ..$ alpha : num 0.009 190s ..$ undo : num 0 190s ..$ joinSegments : logi TRUE 190s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 190s .. ..$ chromosome: int 2 190s .. ..$ start : num -Inf 190s .. ..$ end : num Inf 190s ..$ seed : int [1:7] 10407 -821273412 -52578226 1415511586 721384351 -665928286 1316562960 190s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 190s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.233 0.001 0.243 0 0 190s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 190s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 190s - attr(*, "randomSeed")= int [1:7] 10407 -821273412 -52578226 1415511586 721384351 -665928286 1316562960 190s Post-segmenting TCNs...done 190s Identification of change points by total copy numbers...done 190s Restructure TCN segmentation results... 190s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 190s 1 1 1 1 554484 143926517 7599 1.3859 2120 190s 2 1 2 1 143926517 185449813 2668 2.0704 775 190s 3 1 3 1 185449813 247137334 4391 2.6341 1314 190s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 190s 1 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 190s 2 775 143926517 185449813 775 0.0970 0.9347856 1.135614 190s 3 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 190s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean 190s 1 2 554484 143926517 7599 1.3859 190s 2 2 143926517 185449813 2668 2.0704 190s 3 2 185449813 247137334 4391 2.6341 190s Number of TCN segments: 3 190s Restructure TCN segmentation results...done 190s Total CN segment #1 ([ 554484,1.43927e+08]) of 3... 190s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 190s 1 1 1 1 554484 143926517 7599 1.3859 2120 190s 2 1 2 1 143926517 185449813 2668 2.0704 775 190s 3 1 3 1 185449813 247137334 4391 2.6341 1314 190s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 190s 1 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 190s 2 775 143926517 185449813 775 0.0970 0.9347856 1.135614 190s 3 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 190s Number of TCN loci in segment: 7599 190s Locus data for TCN segment: 190s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 190s 1 1 1 1 554484 143926517 7599 1.3859 2120 190s 2 1 2 1 143926517 185449813 2668 2.0704 775 190s 3 1 3 1 185449813 247137334 4391 2.6341 1314 190s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 190s 1 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 190s 2 775 143926517 185449813 775 0.0970 0.9347856 1.135614 190s 3 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 190s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 190s 1 1 1 1 554484 143926517 7599 1.3859 2120 190s 2 1 2 1 143926517 185449813 2668 2.0704 775 190s 3 1 3 1 185449813 247137334 4391 2.6341 1314 190s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 190s 1 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 190s 2 775 143926517 185449813 775 0.0970 0.9347856 1.135614 190s 3 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 190s 'data.frame': 7599 obs. of 9 variables: 190s $ chromosome: int 2 2 2 2 2 2 2 2 2 2 ... 190s $ x : num 554484 730720 782343 878522 916294 ... 190s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 190s $ betaT : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 190s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 190s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 190s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 190s $ index : int 1 2 3 4 5 6 7 8 9 10 ... 190s $ rho : num NA NA NA NA NA ... 190s Number of loci: 7599 190s Number of SNPs: 2120 (27.90%) 190s Number of heterozygous SNPs: 2120 (100.00%) 190s Chromosome: 2 190s Segmenting DH signals... 190s Segmenting by CBS... 190s Chromosome: 2 190s Random seed temporarily set (seed=c(10407, -1924040949, -1632234809, -437763632, -1464377300, 676654412, 2080370711), kind="L'Ecuyer-CMRG") 190s Segmenting by CBS...done 190s List of 4 190s $ data :'data.frame': 7599 obs. of 4 variables: 190s ..$ chromosome: int [1:7599] 2 2 2 2 2 2 2 2 2 2 ... 190s ..$ x : num [1:7599] 554484 730720 782343 878522 916294 ... 190s ..$ y : num [1:7599] NA NA NA NA NA ... 190s ..$ index : int [1:7599] 1 2 3 4 5 6 7 8 9 10 ... 190s $ output :'data.frame': 1 obs. of 6 variables: 190s ..$ sampleName: chr NA 190s ..$ chromosome: int 2 190s ..$ start : num 554484 190s ..$ end : num 1.44e+08 190s ..$ nbrOfLoci : int 2120 190s ..$ mean : num 0.51 190s $ segRows:'data.frame': 1 obs. of 2 variables: 190s ..$ startRow: int 10 190s ..$ endRow : int 7594 190s $ params :List of 5 190s ..$ alpha : num 0.001 190s ..$ undo : num 0 190s ..$ joinSegments : logi TRUE 190s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 190s .. ..$ chromosome: int 2 190s .. ..$ start : num 554484 190s .. ..$ end : num 1.44e+08 190s ..$ seed : int [1:7] 10407 -1924040949 -1632234809 -437763632 -1464377300 676654412 2080370711 190s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 190s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.017 0 0.017 0 0 190s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 190s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 190s - attr(*, "randomSeed")= int [1:7] 10407 -1924040949 -1632234809 -437763632 -1464377300 676654412 2080370711 190s DH segmentation (locally-indexed) rows: 190s startRow endRow 190s 1 10 7594 190s int [1:7599] 1 2 3 4 5 6 7 8 9 10 ... 190s DH segmentation rows: 190s startRow endRow 190s 1 10 7594 190s Segmenting DH signals...done 190s DH segmentation table: 190s dhStart dhEnd dhNbrOfLoci dhMean 190s 1 554484 143926517 2120 0.5101 190s startRow endRow 190s 1 10 7594 190s Rows: 190s [1] 1 190s TCN segmentation rows: 190s startRow endRow 190s 1 1 7599 190s TCN and DH segmentation rows: 190s startRow endRow 190s 1 1 7599 190s startRow endRow 190s 1 10 7594 190s NULL 190s TCN segmentation (expanded) rows: 190s startRow endRow 190s 1 1 7599 190s TCN and DH segmentation rows: 190s startRow endRow 190s 1 1 7599 190s 2 7600 10267 190s 3 10268 14658 190s startRow endRow 190s 1 10 7594 190s startRow endRow 190s 1 1 7599 190s Total CN segmentation table (expanded): 190s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 190s 1 2 554484 143926517 7599 1.3859 2120 2120 190s (TCN,DH) segmentation for one total CN segment: 190s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 190s 1 1 1 2 554484 143926517 7599 1.3859 2120 190s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 190s 1 2120 554484 143926517 2120 0.5101 190s Total CN segment #1 ([ 554484,1.43927e+08]) of 3...done 190s Total CN segment #2 ([1.43927e+08,1.8545e+08]) of 3... 190s Number of TCN loci in segment: 2668 190s Locus data for TCN segment: 190s 'data.frame': 2668 obs. of 9 variables: 190s $ chromosome: int 2 2 2 2 2 2 2 2 2 2 ... 190s $ x : num 1.44e+08 1.44e+08 1.44e+08 1.44e+08 1.44e+08 ... 190s $ CT : num 2.1 2.1 2.09 1.8 2.34 ... 190s $ betaT : num 0.027542 1.030222 1.094093 0.046763 -0.000948 ... 190s $ betaTN : num 0.027542 1.030222 1.094093 0.046763 -0.000948 ... 190s $ betaN : num 0.1624 0.8788 0.8225 0.1201 0.0317 ... 190s $ muN : num 0 1 1 0 0 1 0 0 0 0 ... 190s $ index : int 7600 7601 7602 7603 7604 7605 7606 7607 7608 7609 ... 190s $ rho : num NA NA NA NA NA NA NA NA NA NA ... 190s Number of loci: 2668 190s Number of SNPs: 775 (29.05%) 190s Number of heterozygous SNPs: 775 (100.00%) 190s Chromosome: 2 190s Segmenting DH signals... 190s Segmenting by CBS... 190s Chromosome: 2 190s Random seed temporarily set (seed=c(10407, -1924040949, -1632234809, -437763632, -1464377300, 676654412, 2080370711), kind="L'Ecuyer-CMRG") 190s Segmenting by CBS...done 190s List of 4 190s $ data :'data.frame': 2668 obs. of 4 variables: 190s ..$ chromosome: int [1:2668] 2 2 2 2 2 2 2 2 2 2 ... 190s ..$ x : num [1:2668] 1.44e+08 1.44e+08 1.44e+08 1.44e+08 1.44e+08 ... 190s ..$ y : num [1:2668] NA NA NA NA NA NA NA NA NA NA ... 190s ..$ index : int [1:2668] 1 2 3 4 5 6 7 8 9 10 ... 190s $ output :'data.frame': 1 obs. of 6 variables: 190s ..$ sampleName: chr NA 190s ..$ chromosome: int 2 190s ..$ start : num 1.44e+08 190s ..$ end : num 1.85e+08 190s ..$ nbrOfLoci : int 775 190s ..$ mean : num 0.097 190s $ segRows:'data.frame': 1 obs. of 2 variables: 190s ..$ startRow: int 15 190s ..$ endRow : int 2664 190s $ params :List of 5 190s ..$ alpha : num 0.001 190s ..$ undo : num 0 190s ..$ joinSegments : logi TRUE 190s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 190s .. ..$ chromosome: int 2 190s .. ..$ start : num 1.44e+08 190s .. ..$ end : num 1.85e+08 190s ..$ seed : int [1:7] 10407 -1924040949 -1632234809 -437763632 -1464377300 676654412 2080370711 190s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 190s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.005 0 0.005 0 0 190s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 190s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 190s - attr(*, "randomSeed")= int [1:7] 10407 -1924040949 -1632234809 -437763632 -1464377300 676654412 2080370711 190s DH segmentation (locally-indexed) rows: 190s startRow endRow 190s 1 15 2664 190s int [1:2668] 7600 7601 7602 7603 7604 7605 7606 7607 7608 7609 ... 190s DH segmentation rows: 190s startRow endRow 190s 1 7614 10263 190s Segmenting DH signals...done 190s DH segmentation table: 190s dhStart dhEnd dhNbrOfLoci dhMean 190s 1 143926517 185449813 775 0.097 190s startRow endRow 190s 1 7614 10263 190s Rows: 190s [1] 2 190s TCN segmentation rows: 190s startRow endRow 190s 2 7600 10267 190s TCN and DH segmentation rows: 190s startRow endRow 190s 2 7600 10267 190s startRow endRow 190s 1 7614 10263 190s startRow endRow 190s 1 1 7599 190s TCN segmentation (expanded) rows: 190s startRow endRow 190s 1 1 7599 190s 2 7600 10267 190s TCN and DH segmentation rows: 190s startRow endRow 190s 1 1 7599 190s 2 7600 10267 190s 3 10268 14658 190s startRow endRow 190s 1 10 7594 190s 2 7614 10263 190s startRow endRow 190s 1 1 7599 190s 2 7600 10267 190s Total CN segmentation table (expanded): 190s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 190s 2 2 143926517 185449813 2668 2.0704 775 775 190s (TCN,DH) segmentation for one total CN segment: 190s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 190s 2 2 1 2 143926517 185449813 2668 2.0704 775 190s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 190s 2 775 143926517 185449813 775 0.097 190s Total CN segment #2 ([1.43927e+08,1.8545e+08]) of 3...done 190s Total CN segment #3 ([1.8545e+08,2.47137e+08]) of 3... 190s Number of TCN loci in segment: 4391 190s Locus data for TCN segment: 190s 'data.frame': 4391 obs. of 9 variables: 190s $ chromosome: int 2 2 2 2 2 2 2 2 2 2 ... 190s $ x : num 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 190s $ CT : num 2.93 2.15 2.82 2.93 2.46 ... 190s $ betaT : num -0.169 0.609 1.028 0.525 0.968 ... 190s $ betaTN : num -0.169 0.609 1.028 0.525 0.968 ... 190s $ betaN : num 0.25 0.38 0.919 0.34 0.783 ... 190s $ muN : num 0 0.5 1 0.5 1 1 0 1 0 1 ... 190s $ index : int 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 190s $ rho : num NA 0.2186 NA 0.0503 NA ... 190s Number of loci: 4391 190s Number of SNPs: 1314 (29.92%) 190s Number of heterozygous SNPs: 1314 (100.00%) 190s Chromosome: 2 190s Segmenting DH signals... 190s Segmenting by CBS... 190s Chromosome: 2 190s Random seed temporarily set (seed=c(10407, -1924040949, -1632234809, -437763632, -1464377300, 676654412, 2080370711), kind="L'Ecuyer-CMRG") 190s Segmenting by CBS...done 190s List of 4 190s $ data :'data.frame': 4391 obs. of 4 variables: 190s ..$ chromosome: int [1:4391] 2 2 2 2 2 2 2 2 2 2 ... 190s ..$ x : num [1:4391] 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 190s ..$ y : num [1:4391] NA 0.2186 NA 0.0503 NA ... 190s ..$ index : int [1:4391] 1 2 3 4 5 6 7 8 9 10 ... 190s $ output :'data.frame': 1 obs. of 6 variables: 190s ..$ sampleName: chr NA 190s ..$ chromosome: int 2 190s ..$ start : num 1.85e+08 190s ..$ end : num 2.47e+08 190s ..$ nbrOfLoci : int 1314 190s ..$ mean : num 0.23 190s $ segRows:'data.frame': 1 obs. of 2 variables: 190s ..$ startRow: int 2 190s ..$ endRow : int 4388 190s $ params :List of 5 190s ..$ alpha : num 0.001 190s ..$ undo : num 0 190s ..$ joinSegments : logi TRUE 190s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 190s .. ..$ chromosome: int 2 190s .. ..$ start : num 1.85e+08 190s .. ..$ end : num 2.47e+08 190s ..$ seed : int [1:7] 10407 -1924040949 -1632234809 -437763632 -1464377300 676654412 2080370711 190s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 190s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.01 0 0.009 0 0 190s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 190s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 190s - attr(*, "randomSeed")= int [1:7] 10407 -1924040949 -1632234809 -437763632 -1464377300 676654412 2080370711 190s DH segmentation (locally-indexed) rows: 190s startRow endRow 190s 1 2 4388 190s int [1:4391] 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 190s DH segmentation rows: 190s startRow endRow 190s 1 10269 14655 190s Segmenting DH signals...done 190s DH segmentation table: 190s dhStart dhEnd dhNbrOfLoci dhMean 190s 1 185449813 247137334 1314 0.2295 190s startRow endRow 190s 1 10269 14655 190s Rows: 190s [1] 3 190s TCN segmentation rows: 190s startRow endRow 190s 3 10268 14658 190s TCN and DH segmentation rows: 190s startRow endRow 190s 3 10268 14658 190s startRow endRow 190s 1 10269 14655 190s startRow endRow 190s 1 1 7599 190s 2 7600 10267 190s TCN segmentation (expanded) rows: 190s startRow endRow 190s 1 1 7599 190s 2 7600 10267 190s 3 10268 14658 190s TCN and DH segmentation rows: 190s startRow endRow 190s 1 1 7599 190s 2 7600 10267 190s 3 10268 14658 190s startRow endRow 190s 1 10 7594 190s 2 7614 10263 190s 3 10269 14655 190s startRow endRow 190s 1 1 7599 190s 2 7600 10267 190s 3 10268 14658 190s Total CN segmentation table (expanded): 190s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 190s 3 2 185449813 247137334 4391 2.6341 1314 1314 190s (TCN,DH) segmentation for one total CN segment: 190s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 190s 3 3 1 2 185449813 247137334 4391 2.6341 1314 190s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 190s 3 1314 185449813 247137334 1314 0.2295 190s Total CN segment #3 ([1.8545e+08,2.47137e+08]) of 3...done 190s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 190s 1 2 1 1 554484 143926517 7599 1.3859 2120 190s 2 2 2 1 143926517 185449813 2668 2.0704 775 190s 3 2 3 1 185449813 247137334 4391 2.6341 1314 190s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 190s 1 2120 554484 143926517 2120 0.5101 190s 2 775 143926517 185449813 775 0.0970 190s 3 1314 185449813 247137334 1314 0.2295 190s Calculating (C1,C2) per segment... 190s Calculating (C1,C2) per segment...done 190s Number of segments: 3 190s Segmenting paired tumor-normal signals using Paired PSCBS...done 190s Post-segmenting TCNs... 190s Number of segments: 3 190s Number of chromosomes: 1 190s [1] 2 190s Chromosome 1 ('chr02') of 1... 190s Rows: 190s [1] 1 2 3 190s Number of segments: 3 190s TCN segment #1 ('1') of 3... 190s Nothing todo. Only one DH segmentation. Skipping. 190s TCN segment #1 ('1') of 3...done 190s TCN segment #2 ('2') of 3... 190s Nothing todo. Only one DH segmentation. Skipping. 190s TCN segment #2 ('2') of 3...done 190s TCN segment #3 ('3') of 3... 190s Nothing todo. Only one DH segmentation. Skipping. 190s TCN segment #3 ('3') of 3...done 190s Chromosome 1 ('chr02') of 1...done 190s Update (C1,C2) per segment... 190s Update (C1,C2) per segment...done 190s Post-segmenting TCNs...done 190s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 190s 1 2 1 1 554484 143926517 7599 1.3859 2120 190s 2 2 2 1 143926517 185449813 2668 2.0704 775 190s 3 2 3 1 185449813 247137334 4391 2.6341 1314 190s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 190s 1 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 190s 2 775 143926517 185449813 775 0.0970 0.9347856 1.135614 190s 3 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 190s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 190s 1 2 1 1 554484 143926517 7599 1.3859 2120 190s 2 2 2 1 143926517 185449813 2668 2.0704 775 190s 3 2 3 1 185449813 247137334 4391 2.6341 1314 190s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 190s 1 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 190s 2 775 143926517 185449813 775 0.0970 0.9347856 1.135614 190s 3 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 190s Chromosome #3 ('Chr03') of 3...done 190s Merging (independently) segmented chromosome... 190s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 190s 1 2 1 1 554484 143926517 7599 1.3859 2120 190s 2 2 2 1 143926517 185449813 2668 2.0704 775 190s 3 2 3 1 185449813 247137334 4391 2.6341 1314 190s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 190s 1 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 190s 2 775 143926517 185449813 775 0.0970 0.9347856 1.135614 190s 3 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 190s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 190s 1 2 1 1 554484 143926517 7599 1.3859 2120 190s 2 2 2 1 143926517 185449813 2668 2.0704 775 190s 3 2 3 1 185449813 247137334 4391 2.6341 1314 190s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 190s 1 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 190s 2 775 143926517 185449813 775 0.0970 0.9347856 1.135614 190s 3 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 190s Segmenting paired tumor-normal signals using Paired PSCBS... 190s Setup up data... 190s 'data.frame': 14658 obs. of 7 variables: 190s $ chromosome: int 3 3 3 3 3 3 3 3 3 3 ... 190s $ x : num 554484 730720 782343 878522 916294 ... 190s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 190s $ betaT : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 190s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 190s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 190s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 190s Setup up data...done 190s Ordering data along genome... 190s 'data.frame': 14658 obs. of 7 variables: 190s $ chromosome: int 3 3 3 3 3 3 3 3 3 3 ... 190s $ x : num 554484 730720 782343 878522 916294 ... 190s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 190s $ betaT : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 190s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 190s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 190s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 190s Ordering data along genome...done 190s Keeping only current chromosome for 'knownSegments'... 190s Chromosome: 3 190s Known segments for this chromosome: 190s [1] chromosome start end 190s <0 rows> (or 0-length row.names) 190s Keeping only current chromosome for 'knownSegments'...done 190s alphaTCN: 0.009 190s alphaDH: 0.001 190s Number of loci: 14658 190s Calculating DHs... 190s Number of SNPs: 14658 190s Number of heterozygous SNPs: 4209 (28.71%) 190s Normalized DHs: 190s num [1:14658] NA NA NA NA NA ... 190s Calculating DHs...done 190s Random seed temporarily set (seed=c(10407, -821273412, -52578226, 1415511586, 721384351, -665928286, 1316562960), kind="L'Ecuyer-CMRG") 190s Produced 2 seeds from this stream for future usage 190s Identification of change points by total copy numbers... 190s Segmenting by CBS... 190s Chromosome: 3 190s Random seed temporarily set (seed=c(10407, -1924040949, -1632234809, -437763632, -1464377300, 676654412, 2080370711), kind="L'Ecuyer-CMRG") 190s Segmenting by CBS...done 190s List of 4 190s $ data :'data.frame': 14658 obs. of 4 variables: 190s ..$ chromosome: int [1:14658] 3 3 3 3 3 3 3 3 3 3 ... 190s ..$ x : num [1:14658] 554484 730720 782343 878522 916294 ... 190s ..$ y : num [1:14658] 1.88 1.8 1.59 1.64 1.53 ... 190s ..$ index : int [1:14658] 1 2 3 4 5 6 7 8 9 10 ... 190s $ output :'data.frame': 3 obs. of 6 variables: 190s ..$ sampleName: chr [1:3] NA NA NA 190s ..$ chromosome: int [1:3] 3 3 3 190s ..$ start : num [1:3] 5.54e+05 1.44e+08 1.85e+08 190s ..$ end : num [1:3] 1.44e+08 1.85e+08 2.47e+08 190s ..$ nbrOfLoci : int [1:3] 7599 2668 4391 190s ..$ mean : num [1:3] 1.39 2.07 2.63 190s $ segRows:'data.frame': 3 obs. of 2 variables: 190s ..$ startRow: int [1:3] 1 7600 10268 190s ..$ endRow : int [1:3] 7599 10267 14658 190s $ params :List of 5 190s ..$ alpha : num 0.009 190s ..$ undo : num 0 190s ..$ joinSegments : logi TRUE 190s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 190s .. ..$ chromosome: int 3 190s .. ..$ start : num -Inf 190s .. ..$ end : num Inf 190s ..$ seed : int [1:7] 10407 -1924040949 -1632234809 -437763632 -1464377300 676654412 2080370711 190s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 190s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.241 0 0.247 0 0 190s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 190s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 190s - attr(*, "randomSeed")= int [1:7] 10407 -1924040949 -1632234809 -437763632 -1464377300 676654412 2080370711 190s Identification of change points by total copy numbers...done 190s Restructure TCN segmentation results... 190s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean 190s 1 3 554484 143926517 7599 1.3859 190s 2 3 143926517 185449813 2668 2.0704 190s 3 3 185449813 247137334 4391 2.6341 190s Number of TCN segments: 3 190s Restructure TCN segmentation results...done 190s Total CN segment #1 ([ 554484,1.43927e+08]) of 3... 190s Number of TCN loci in segment: 7599 190s Locus data for TCN segment: 190s 'data.frame': 7599 obs. of 9 variables: 190s $ chromosome: int 3 3 3 3 3 3 3 3 3 3 ... 190s $ x : num 554484 730720 782343 878522 916294 ... 190s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 190s $ betaT : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 190s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 190s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 190s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 190s $ index : int 1 2 3 4 5 6 7 8 9 10 ... 190s $ rho : num NA NA NA NA NA ... 190s Number of loci: 7599 190s Number of SNPs: 2120 (27.90%) 190s Number of heterozygous SNPs: 2120 (100.00%) 190s Chromosome: 3 190s Segmenting DH signals... 190s Segmenting by CBS... 190s Chromosome: 3 190s Random seed temporarily set (seed=c(10407, -1371615447, -889757879, 1692656974, -1723952224, 1378814990, 1816467252), kind="L'Ecuyer-CMRG") 190s Segmenting by CBS...done 190s List of 4 190s $ data :'data.frame': 7599 obs. of 4 variables: 190s ..$ chromosome: int [1:7599] 3 3 3 3 3 3 3 3 3 3 ... 190s ..$ x : num [1:7599] 554484 730720 782343 878522 916294 ... 190s ..$ y : num [1:7599] NA NA NA NA NA ... 190s ..$ index : int [1:7599] 1 2 3 4 5 6 7 8 9 10 ... 190s $ output :'data.frame': 1 obs. of 6 variables: 190s ..$ sampleName: chr NA 190s ..$ chromosome: int 3 190s ..$ start : num 554484 190s ..$ end : num 1.44e+08 190s ..$ nbrOfLoci : int 2120 190s ..$ mean : num 0.51 190s $ segRows:'data.frame': 1 obs. of 2 variables: 190s ..$ startRow: int 10 190s ..$ endRow : int 7594 190s $ params :List of 5 190s ..$ alpha : num 0.001 190s ..$ undo : num 0 190s ..$ joinSegments : logi TRUE 190s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 190s .. ..$ chromosome: int 3 190s .. ..$ start : num 554484 190s .. ..$ end : num 1.44e+08 190s ..$ seed : int [1:7] 10407 -1371615447 -889757879 1692656974 -1723952224 1378814990 1816467252 190s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 190s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.017 0 0.017 0 0 190s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 190s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 190s - attr(*, "randomSeed")= int [1:7] 10407 -1371615447 -889757879 1692656974 -1723952224 1378814990 1816467252 190s DH segmentation (locally-indexed) rows: 190s startRow endRow 190s 1 10 7594 190s int [1:7599] 1 2 3 4 5 6 7 8 9 10 ... 190s DH segmentation rows: 190s startRow endRow 190s 1 10 7594 190s Segmenting DH signals...done 190s DH segmentation table: 190s dhStart dhEnd dhNbrOfLoci dhMean 190s 1 554484 143926517 2120 0.5101 190s startRow endRow 190s 1 10 7594 190s Rows: 190s [1] 1 190s TCN segmentation rows: 190s startRow endRow 190s 1 1 7599 190s TCN and DH segmentation rows: 190s startRow endRow 190s 1 1 7599 190s startRow endRow 190s 1 10 7594 190s NULL 190s TCN segmentation (expanded) rows: 190s startRow endRow 190s 1 1 7599 190s TCN and DH segmentation rows: 190s startRow endRow 190s 1 1 7599 190s 2 7600 10267 190s 3 10268 14658 190s startRow endRow 190s 1 10 7594 190s startRow endRow 190s 1 1 7599 190s Total CN segmentation table (expanded): 190s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 190s 1 3 554484 143926517 7599 1.3859 2120 2120 190s (TCN,DH) segmentation for one total CN segment: 190s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 190s 1 1 1 3 554484 143926517 7599 1.3859 2120 190s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 190s 1 2120 554484 143926517 2120 0.5101 190s Total CN segment #1 ([ 554484,1.43927e+08]) of 3...done 190s Total CN segment #2 ([1.43927e+08,1.8545e+08]) of 3... 190s Number of TCN loci in segment: 2668 190s Locus data for TCN segment: 190s 'data.frame': 2668 obs. of 9 variables: 190s $ chromosome: int 3 3 3 3 3 3 3 3 3 3 ... 190s $ x : num 1.44e+08 1.44e+08 1.44e+08 1.44e+08 1.44e+08 ... 190s $ CT : num 2.1 2.1 2.09 1.8 2.34 ... 190s $ betaT : num 0.027542 1.030222 1.094093 0.046763 -0.000948 ... 190s $ betaTN : num 0.027542 1.030222 1.094093 0.046763 -0.000948 ... 190s $ betaN : num 0.1624 0.8788 0.8225 0.1201 0.0317 ... 190s $ muN : num 0 1 1 0 0 1 0 0 0 0 ... 190s $ index : int 7600 7601 7602 7603 7604 7605 7606 7607 7608 7609 ... 190s $ rho : num NA NA NA NA NA NA NA NA NA NA ... 190s Number of loci: 2668 190s Number of SNPs: 775 (29.05%) 190s Number of heterozygous SNPs: 775 (100.00%) 190s Chromosome: 3 190s Segmenting DH signals... 190s Segmenting by CBS... 190s Chromosome: 3 190s Random seed temporarily set (seed=c(10407, -1371615447, -889757879, 1692656974, -1723952224, 1378814990, 1816467252), kind="L'Ecuyer-CMRG") 190s Segmenting by CBS...done 190s List of 4 190s $ data :'data.frame': 2668 obs. of 4 variables: 190s ..$ chromosome: int [1:2668] 3 3 3 3 3 3 3 3 3 3 ... 190s ..$ x : num [1:2668] 1.44e+08 1.44e+08 1.44e+08 1.44e+08 1.44e+08 ... 190s ..$ y : num [1:2668] NA NA NA NA NA NA NA NA NA NA ... 190s ..$ index : int [1:2668] 1 2 3 4 5 6 7 8 9 10 ... 190s $ output :'data.frame': 1 obs. of 6 variables: 190s ..$ sampleName: chr NA 190s ..$ chromosome: int 3 190s ..$ start : num 1.44e+08 190s ..$ end : num 1.85e+08 190s ..$ nbrOfLoci : int 775 190s ..$ mean : num 0.097 190s $ segRows:'data.frame': 1 obs. of 2 variables: 190s ..$ startRow: int 15 190s ..$ endRow : int 2664 190s $ params :List of 5 190s ..$ alpha : num 0.001 190s ..$ undo : num 0 190s ..$ joinSegments : logi TRUE 190s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 190s .. ..$ chromosome: int 3 190s .. ..$ start : num 1.44e+08 190s .. ..$ end : num 1.85e+08 190s ..$ seed : int [1:7] 10407 -1371615447 -889757879 1692656974 -1723952224 1378814990 1816467252 190s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 190s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.005 0 0.005 0 0 190s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 190s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 190s - attr(*, "randomSeed")= int [1:7] 10407 -1371615447 -889757879 1692656974 -1723952224 1378814990 1816467252 190s DH segmentation (locally-indexed) rows: 190s startRow endRow 190s 1 15 2664 190s int [1:2668] 7600 7601 7602 7603 7604 7605 7606 7607 7608 7609 ... 190s DH segmentation rows: 190s startRow endRow 190s 1 7614 10263 190s Segmenting DH signals...done 190s DH segmentation table: 190s dhStart dhEnd dhNbrOfLoci dhMean 190s 1 143926517 185449813 775 0.097 190s startRow endRow 190s 1 7614 10263 190s Rows: 190s [1] 2 190s TCN segmentation rows: 190s startRow endRow 190s 2 7600 10267 190s TCN and DH segmentation rows: 190s startRow endRow 190s 2 7600 10267 190s startRow endRow 190s 1 7614 10263 190s startRow endRow 190s 1 1 7599 190s TCN segmentation (expanded) rows: 190s startRow endRow 190s 1 1 7599 190s 2 7600 10267 190s TCN and DH segmentation rows: 190s startRow endRow 190s 1 1 7599 190s 2 7600 10267 190s 3 10268 14658 190s startRow endRow 190s 1 10 7594 190s 2 7614 10263 190s startRow endRow 190s 1 1 7599 190s 2 7600 10267 190s Total CN segmentation table (expanded): 190s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 190s 2 3 143926517 185449813 2668 2.0704 775 775 190s (TCN,DH) segmentation for one total CN segment: 190s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 190s 2 2 1 3 143926517 185449813 2668 2.0704 775 190s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 190s 2 775 143926517 185449813 775 0.097 190s Total CN segment #2 ([1.43927e+08,1.8545e+08]) of 3...done 190s Total CN segment #3 ([1.8545e+08,2.47137e+08]) of 3... 190s Number of TCN loci in segment: 4391 190s Locus data for TCN segment: 190s 'data.frame': 4391 obs. of 9 variables: 190s $ chromosome: int 3 3 3 3 3 3 3 3 3 3 ... 190s $ x : num 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 190s $ CT : num 2.93 2.15 2.82 2.93 2.46 ... 190s $ betaT : num -0.169 0.609 1.028 0.525 0.968 ... 190s $ betaTN : num -0.169 0.609 1.028 0.525 0.968 ... 190s $ betaN : num 0.25 0.38 0.919 0.34 0.783 ... 190s $ muN : num 0 0.5 1 0.5 1 1 0 1 0 1 ... 190s $ index : int 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 190s $ rho : num NA 0.2186 NA 0.0503 NA ... 190s Number of loci: 4391 190s Number of SNPs: 1314 (29.92%) 190s Number of heterozygous SNPs: 1314 (100.00%) 190s Chromosome: 3 190s Segmenting DH signals... 190s Segmenting by CBS... 190s Chromosome: 3 190s Random seed temporarily set (seed=c(10407, -1371615447, -889757879, 1692656974, -1723952224, 1378814990, 1816467252), kind="L'Ecuyer-CMRG") 190s Segmenting by CBS...done 190s List of 4 190s $ data :'data.frame': 4391 obs. of 4 variables: 190s ..$ chromosome: int [1:4391] 3 3 3 3 3 3 3 3 3 3 ... 190s ..$ x : num [1:4391] 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 190s ..$ y : num [1:4391] NA 0.2186 NA 0.0503 NA ... 190s ..$ index : int [1:4391] 1 2 3 4 5 6 7 8 9 10 ... 190s $ output :'data.frame': 1 obs. of 6 variables: 190s ..$ sampleName: chr NA 190s ..$ chromosome: int 3 190s ..$ start : num 1.85e+08 190s ..$ end : num 2.47e+08 190s ..$ nbrOfLoci : int 1314 190s ..$ mean : num 0.23 190s $ segRows:'data.frame': 1 obs. of 2 variables: 190s ..$ startRow: int 2 190s ..$ endRow : int 4388 190s $ params :List of 5 190s ..$ alpha : num 0.001 190s ..$ undo : num 0 190s ..$ joinSegments : logi TRUE 190s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 190s .. ..$ chromosome: int 3 190s .. ..$ start : num 1.85e+08 190s .. ..$ end : num 2.47e+08 190s ..$ seed : int [1:7] 10407 -1371615447 -889757879 1692656974 -1723952224 1378814990 1816467252 190s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 190s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.01 0 0.01 0 0 190s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 190s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 190s - attr(*, "randomSeed")= int [1:7] 10407 -1371615447 -889757879 1692656974 -1723952224 1378814990 1816467252 190s DH segmentation (locally-indexed) rows: 190s startRow endRow 190s 1 2 4388 190s int [1:4391] 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 190s DH segmentation rows: 190s startRow endRow 190s 1 10269 14655 190s Segmenting DH signals...done 190s DH segmentation table: 190s dhStart dhEnd dhNbrOfLoci dhMean 190s 1 185449813 247137334 1314 0.2295 190s startRow endRow 190s 1 10269 14655 190s Rows: 190s [1] 3 190s TCN segmentation rows: 190s startRow endRow 190s 3 10268 14658 190s TCN and DH segmentation rows: 190s startRow endRow 190s 3 10268 14658 190s startRow endRow 190s 1 10269 14655 190s startRow endRow 190s 1 1 7599 190s 2 7600 10267 190s TCN segmentation (expanded) rows: 190s startRow endRow 190s 1 1 7599 190s 2 7600 10267 190s 3 10268 14658 190s TCN and DH segmentation rows: 190s startRow endRow 190s 1 1 7599 190s 2 7600 10267 190s 3 10268 14658 190s startRow endRow 190s 1 10 7594 190s 2 7614 10263 190s 3 10269 14655 190s startRow endRow 190s 1 1 7599 190s 2 7600 10267 190s 3 10268 14658 190s Total CN segmentation table (expanded): 190s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 190s 3 3 185449813 247137334 4391 2.6341 1314 1314 190s (TCN,DH) segmentation for one total CN segment: 190s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 190s 3 3 1 3 185449813 247137334 4391 2.6341 1314 190s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 190s 3 1314 185449813 247137334 1314 0.2295 190s Total CN segment #3 ([1.8545e+08,2.47137e+08]) of 3...done 190s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 190s 1 3 1 1 554484 143926517 7599 1.3859 2120 190s 2 3 2 1 143926517 185449813 2668 2.0704 775 190s 3 3 3 1 185449813 247137334 4391 2.6341 1314 190s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 190s 1 2120 554484 143926517 2120 0.5101 190s 2 775 143926517 185449813 775 0.0970 190s 3 1314 185449813 247137334 1314 0.2295 190s Calculating (C1,C2) per segment... 190s Calculating (C1,C2) per segment...done 190s Number of segments: 3 190s Segmenting paired tumor-normal signals using Paired PSCBS...done 190s Post-segmenting TCNs... 190s Number of segments: 3 190s Number of chromosomes: 1 190s [1] 3 190s Chromosome 1 ('chr03') of 1... 190s Rows: 190s [1] 1 2 3 190s Number of segments: 3 190s TCN segment #1 ('1') of 3... 190s Nothing todo. Only one DH segmentation. Skipping. 190s TCN segment #1 ('1') of 3...done 190s TCN segment #2 ('2') of 3... 190s Nothing todo. Only one DH segmentation. Skipping. 190s TCN segment #2 ('2') of 3...done 190s TCN segment #3 ('3') of 3... 190s Nothing todo. Only one DH segmentation. Skipping. 190s TCN segment #3 ('3') of 3...done 190s Chromosome 1 ('chr03') of 1...done 190s Update (C1,C2) per segment... 190s Update (C1,C2) per segment...done 190s Post-segmenting TCNs...done 190s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 190s 1 3 1 1 554484 143926517 7599 1.3859 2120 190s 2 3 2 1 143926517 185449813 2668 2.0704 775 190s 3 3 3 1 185449813 247137334 4391 2.6341 1314 190s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 190s 1 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 190s 2 775 143926517 185449813 775 0.0970 0.9347856 1.135614 190s 3 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 190s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 190s 1 3 1 1 554484 143926517 7599 1.3859 2120 190s 2 3 2 1 143926517 185449813 2668 2.0704 775 190s 3 3 3 1 185449813 247137334 4391 2.6341 1314 190s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 190s 1 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 190s 2 775 143926517 185449813 775 0.0970 0.9347856 1.135614 190s 3 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 190s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 190s 1 3 1 1 554484 143926517 7599 1.3859 2120 190s 2 3 2 1 143926517 185449813 2668 2.0704 775 190s 3 3 3 1 185449813 247137334 4391 2.6341 1314 190s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 190s 1 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 190s 2 775 143926517 185449813 775 0.0970 0.9347856 1.135614 190s 3 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 190s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 190s 1 3 1 1 554484 143926517 7599 1.3859 2120 190s 2 3 2 1 143926517 185449813 2668 2.0704 775 190s 3 3 3 1 185449813 247137334 4391 2.6341 1314 190s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 190s 1 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 190s 2 775 143926517 185449813 775 0.0970 0.9347856 1.135614 190s 3 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 190s List of 5 190s $ data :Classes 'PairedPSCNData' and 'data.frame': 43974 obs. of 8 variables: 190s ..$ chromosome: int [1:43974] 1 1 1 1 1 1 1 1 1 1 ... 190s ..$ x : num [1:43974] 554484 730720 782343 878522 916294 ... 190s ..$ CT : num [1:43974] 1.88 1.8 1.59 1.64 1.53 ... 190s ..$ betaT : num [1:43974] 0.0646 0.1672 0.9284 0.113 0.7209 ... 190s ..$ betaTN : num [1:43974] -0.0515 -0.1172 1.0194 0.031 0.8604 ... 190s ..$ betaN : num [1:43974] 0.116 0.284 0.909 0.082 0.86 ... 190s ..$ muN : num [1:43974] 0 0 1 0 1 1 1 0 1 0.5 ... 190s ..$ rho : num [1:43974] NA NA NA NA NA ... 190s $ output :Classes 'PairedPSCNSegments' and 'data.frame': 11 obs. of 15 variables: 190s ..$ chromosome : int [1:11] 1 1 1 NA 2 2 2 NA 3 3 ... 190s ..$ tcnId : int [1:11] 1 2 3 NA 1 2 3 NA 1 2 ... 190s ..$ dhId : int [1:11] 1 1 1 NA 1 1 1 NA 1 1 ... 190s ..$ tcnStart : num [1:11] 5.54e+05 1.44e+08 1.85e+08 NA 5.54e+05 ... 190s ..$ tcnEnd : num [1:11] 1.44e+08 1.85e+08 2.47e+08 NA 1.44e+08 ... 190s ..$ tcnNbrOfLoci: int [1:11] 7599 2668 4391 NA 7599 2668 4391 NA 7599 2668 ... 190s ..$ tcnMean : num [1:11] 1.39 2.07 2.63 NA 1.39 ... 190s ..$ tcnNbrOfSNPs: int [1:11] 2120 775 1314 NA 2120 775 1314 NA 2120 775 ... 190s ..$ tcnNbrOfHets: int [1:11] 2120 775 1314 NA 2120 775 1314 NA 2120 775 ... 190s ..$ dhStart : num [1:11] 5.54e+05 1.44e+08 1.85e+08 NA 5.54e+05 ... 190s ..$ dhEnd : num [1:11] 1.44e+08 1.85e+08 2.47e+08 NA 1.44e+08 ... 190s ..$ dhNbrOfLoci : int [1:11] 2120 775 1314 NA 2120 775 1314 NA 2120 775 ... 190s ..$ dhMean : num [1:11] 0.51 0.097 0.23 NA 0.51 ... 190s ..$ c1Mean : num [1:11] 0.339 0.935 1.015 NA 0.339 ... 190s ..$ c2Mean : num [1:11] 1.05 1.14 1.62 NA 1.05 ... 190s $ tcnSegRows:'data.frame': 11 obs. of 2 variables: 190s ..$ startRow: int [1:11] 1 7600 10268 NA 14659 22258 24926 NA 29317 36916 ... 190s ..$ endRow : int [1:11] 7599 10267 14658 NA 22257 24925 29316 NA 36915 39583 ... 190s $ dhSegRows :'data.frame': 11 obs. of 2 variables: 190s ..$ startRow: int [1:11] 10 7614 10269 NA 14668 22272 24927 NA 29326 36930 ... 190s ..$ endRow : int [1:11] 7594 10263 14655 NA 22252 24921 29313 NA 36910 39579 ... 190s $ params :List of 7 190s ..$ alphaTCN : num 0.009 190s ..$ alphaDH : num 0.001 190s ..$ flavor : chr "tcn&dh" 190s ..$ tbn : logi FALSE 190s ..$ joinSegments : logi TRUE 190s ..$ knownSegments:'data.frame': 0 obs. of 3 variables: 190s .. ..$ chromosome: int(0) 190s .. ..$ start : int(0) 190s .. ..$ end : int(0) 190s ..$ seed : int [1:7] 10407 1066287653 -51199871 161854402 -1995183193 1503453565 -747102133 190s - attr(*, "class")= chr [1:3] "PairedPSCBS" "PSCBS" "AbstractCBS" 190s Merging (independently) segmented chromosome...done 190s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 190s 1 1 1 1 554484 143926517 7599 1.3859 2120 190s 2 1 2 1 143926517 185449813 2668 2.0704 775 190s 3 1 3 1 185449813 247137334 4391 2.6341 1314 190s 4 NA NA NA NA NA NA NA NA 190s 5 2 1 1 554484 143926517 7599 1.3859 2120 190s 6 2 2 1 143926517 185449813 2668 2.0704 775 190s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 190s 1 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 190s 2 775 143926517 185449813 775 0.0970 0.9347856 1.135614 190s 3 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 190s 4 NA NA NA NA NA NA NA 190s 5 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 190s 6 775 143926517 185449813 775 0.0970 0.9347856 1.135614 190s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 190s 6 2 2 1 143926517 185449813 2668 2.0704 775 190s 7 2 3 1 185449813 247137334 4391 2.6341 1314 190s 8 NA NA NA NA NA NA NA NA 190s 9 3 1 1 554484 143926517 7599 1.3859 2120 190s 10 3 2 1 143926517 185449813 2668 2.0704 775 190s 11 3 3 1 185449813 247137334 4391 2.6341 1314 190s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 190s 6 775 143926517 185449813 775 0.0970 0.9347856 1.135614 190s 7 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 190s 8 NA NA NA NA NA NA NA 190s 9 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 190s 10 775 143926517 185449813 775 0.0970 0.9347856 1.135614 190s 11 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 190s Segmenting multiple chromosomes...done 190s Segmenting paired tumor-normal signals using Paired PSCBS...done 190s > 190s > message("*** segmentByPairedPSCBS() via futures ... DONE") 190s *** segmentByPairedPSCBS() via futures ... DONE 190s > 190s > 190s > message("*** segmentByPairedPSCBS() via futures with known segments ...") 190s *** segmentByPairedPSCBS() via futures with known segments ... 190s > fits <- list() 190s > dataT <- subset(data, chromosome == 1) 190s > gaps <- findLargeGaps(dataT, minLength=2e6) 190s > knownSegments <- gapsToSegments(gaps) 190s > 190s > for (strategy in strategies) { 190s + message(sprintf("- segmentByPairedPSCBS() w/ known segments using '%s' futures ...", strategy)) 190s + plan(strategy) 190s + fit <- segmentByPairedPSCBS(dataT, knownSegments=knownSegments, seed=0xBEEF, verbose=TRUE) 190s + fits[[strategy]] <- fit 190s + equal <- all.equal(fit, fits[[1]]) 190s + if (!equal) { 190s + str(fit) 190s + str(fits[[1]]) 190s + print(equal) 190s + stop(sprintf("segmentByPairedPSCBS() w/ known segments using '%s' futures does not produce the same results as when using '%s' futures", strategy, names(fits)[1])) 190s + } 190s + } 190s - segmentByPairedPSCBS() w/ known segments using 'sequential' futures ... 190s Segmenting paired tumor-normal signals using Paired PSCBS... 190s Calling genotypes from normal allele B fractions... 190s num [1:14670] 0.8274 0.5072 0.1671 0.1609 0.0421 ... 190s Called genotypes: 190s num [1:14670] 1 0.5 0 0 0 0 1 0 1 0.5 ... 190s - attr(*, "modelFit")=List of 1 190s ..$ :List of 7 190s .. ..$ flavor : chr "density" 190s .. ..$ cn : int 2 190s .. ..$ nbrOfGenotypeGroups: int 3 190s .. ..$ tau : num [1:2] 0.315 0.677 190s .. ..$ n : int 14640 190s .. ..$ fit :Classes 'PeaksAndValleys' and 'data.frame': 5 obs. of 3 variables: 190s .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 190s .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 190s .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 190s .. ..$ fitValleys :Classes 'PeaksAndValleys' and 'data.frame': 2 obs. of 3 variables: 190s .. .. ..$ type : chr [1:2] "valley" "valley" 190s .. .. ..$ x : num [1:2] 0.315 0.677 190s .. .. ..$ density: num [1:2] 0.522 0.551 190s ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 190s muN 190s 0 0.5 1 190s 5221 4198 5251 190s Calling genotypes from normal allele B fractions...done 190s Normalizing betaT using betaN (TumorBoost)... 190s Normalized BAFs: 190s num [1:14670] 0.9301 0.1667 0.0685 0.0995 0.0155 ... 190s - attr(*, "modelFit")=List of 5 190s ..$ method : chr "normalizeTumorBoost" 190s ..$ flavor : chr "v4" 190s ..$ delta : num [1:14670] -0.17264 0.00239 0.1671 0.16085 0.04213 ... 190s .. ..- attr(*, "modelFit")=List of 1 190s .. .. ..$ :List of 7 190s .. .. .. ..$ flavor : chr "density" 190s .. .. .. ..$ cn : int 2 190s .. .. .. ..$ nbrOfGenotypeGroups: int 3 190s .. .. .. ..$ tau : num [1:2] 0.315 0.677 190s .. .. .. ..$ n : int 14640 190s .. .. .. ..$ fit :Classes 'PeaksAndValleys' and 'data.frame': 5 obs. of 3 variables: 190s .. .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 190s .. .. .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 190s .. .. .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 190s .. .. .. ..$ fitValleys :Classes 'PeaksAndValleys' and 'data.frame': 2 obs. of 3 variables: 190s .. .. .. .. ..$ type : chr [1:2] "valley" "valley" 190s .. .. .. .. ..$ x : num [1:2] 0.315 0.677 190s .. .. .. .. ..$ density: num [1:2] 0.522 0.551 190s .. .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 190s ..$ preserveScale: logi FALSE 190s ..$ scaleFactor : num NA 190s Normalizing betaT using betaN (TumorBoost)...done 190s Setup up data... 190s 'data.frame': 14670 obs. of 7 variables: 190s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 190s $ x : num 1145994 2941694 3710825 4240737 4276892 ... 190s $ CT : num 1.63 1.4 1.41 1.17 1.16 ... 190s $ betaT : num 0.7574 0.169 0.2357 0.2604 0.0576 ... 190s $ betaTN : num 0.9301 0.1667 0.0685 0.0995 0.0155 ... 190s ..- attr(*, "modelFit")=List of 5 190s .. ..$ method : chr "normalizeTumorBoost" 190s .. ..$ flavor : chr "v4" 190s .. ..$ delta : num [1:14670] -0.17264 0.00239 0.1671 0.16085 0.04213 ... 190s .. .. ..- attr(*, "modelFit")=List of 1 190s .. .. .. ..$ :List of 7 190s .. .. .. .. ..$ flavor : chr "density" 190s .. .. .. .. ..$ cn : int 2 190s .. .. .. .. ..$ nbrOfGenotypeGroups: int 3 190s .. .. .. .. ..$ tau : num [1:2] 0.315 0.677 190s .. .. .. .. ..$ n : int 14640 190s .. .. .. .. ..$ fit :Classes 'PeaksAndValleys' and 'data.frame': 5 obs. of 3 variables: 190s .. .. .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 190s .. .. .. .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 190s .. .. .. .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 190s .. .. .. .. ..$ fitValleys :Classes 'PeaksAndValleys' and 'data.frame': 2 obs. of 3 variables: 190s .. .. .. .. .. ..$ type : chr [1:2] "valley" "valley" 190s .. .. .. .. .. ..$ x : num [1:2] 0.315 0.677 190s .. .. .. .. .. ..$ density: num [1:2] 0.522 0.551 190s .. .. .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 190s .. ..$ preserveScale: logi FALSE 190s .. ..$ scaleFactor : num NA 190s $ betaN : num 0.8274 0.5072 0.1671 0.1609 0.0421 ... 190s $ muN : num 1 0.5 0 0 0 0 1 0 1 0.5 ... 190s ..- attr(*, "modelFit")=List of 1 190s .. ..$ :List of 7 190s .. .. ..$ flavor : chr "density" 190s .. .. ..$ cn : int 2 190s .. .. ..$ nbrOfGenotypeGroups: int 3 190s .. .. ..$ tau : num [1:2] 0.315 0.677 190s .. .. ..$ n : int 14640 190s .. .. ..$ fit :Classes 'PeaksAndValleys' and 'data.frame': 5 obs. of 3 variables: 190s .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 190s .. .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 190s .. .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 190s .. .. ..$ fitValleys :Classes 'PeaksAndValleys' and 'data.frame': 2 obs. of 3 variables: 190s .. .. .. ..$ type : chr [1:2] "valley" "valley" 190s .. .. .. ..$ x : num [1:2] 0.315 0.677 190s .. .. .. ..$ density: num [1:2] 0.522 0.551 190s .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 190s Setup up data...done 190s Dropping loci for which TCNs are missing... 190s Number of loci dropped: 12 190s Dropping loci for which TCNs are missing...done 190s Ordering data along genome... 190s 'data.frame': 14658 obs. of 7 variables: 190s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 190s $ x : num 554484 730720 782343 878522 916294 ... 190s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 190s $ betaT : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 190s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 190s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 190s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 190s Ordering data along genome...done 190s Keeping only current chromosome for 'knownSegments'... 190s Chromosome: 1 190s Known segments for this chromosome: 190s chromosome start end length 190s 1 1 -Inf 120908858 Inf 190s 2 1 120908859 142693887 21785028 190s 3 1 142693888 Inf Inf 190s Keeping only current chromosome for 'knownSegments'...done 190s alphaTCN: 0.009 190s alphaDH: 0.001 190s Number of loci: 14658 190s Calculating DHs... 190s Number of SNPs: 14658 190s Number of heterozygous SNPs: 4196 (28.63%) 190s Normalized DHs: 190s num [1:14658] NA NA NA NA NA ... 190s Calculating DHs...done 190s Random seed temporarily set (seed=c(48879), kind="L'Ecuyer-CMRG") 190s Produced 2 seeds from this stream for future usage 190s Identification of change points by total copy numbers... 190s Segmenting by CBS... 190s Chromosome: 1 190s Random seed temporarily set (seed=c(10407, 1066287653, -51199871, 161854402, -1995183193, 1503453565, -747102133), kind="L'Ecuyer-CMRG") 190s Produced 3 seeds from this stream for future usage 190s Segmenting by CBS...done 190s List of 4 190s $ data :'data.frame': 14658 obs. of 4 variables: 190s ..$ chromosome: int [1:14658] 1 1 1 1 1 1 1 1 1 1 ... 190s ..$ x : num [1:14658] 554484 730720 782343 878522 916294 ... 190s ..$ y : num [1:14658] 1.88 1.8 1.59 1.64 1.53 ... 190s ..$ index : int [1:14658] 1 2 3 4 5 6 7 8 9 10 ... 190s $ output :'data.frame': 4 obs. of 6 variables: 190s ..$ sampleName: chr [1:4] NA NA NA NA 190s ..$ chromosome: int [1:4] 1 1 1 1 190s ..$ start : num [1:4] 5.54e+05 1.21e+08 1.43e+08 1.85e+08 190s ..$ end : num [1:4] 1.21e+08 1.43e+08 1.85e+08 2.47e+08 190s ..$ nbrOfLoci : int [1:4] 7586 0 2681 4391 190s ..$ mean : num [1:4] 1.39 NA 2.07 2.63 190s $ segRows:'data.frame': 4 obs. of 2 variables: 190s ..$ startRow: int [1:4] 1 NA 7587 10268 190s ..$ endRow : int [1:4] 7586 NA 10267 14658 190s $ params :List of 5 190s ..$ alpha : num 0.009 190s ..$ undo : num 0 190s ..$ joinSegments : logi TRUE 190s ..$ knownSegments:'data.frame': 4 obs. of 3 variables: 190s .. ..$ chromosome: int [1:4] 1 1 2 1 190s .. ..$ start : num [1:4] -Inf -Inf -Inf 1.43e+08 190s .. ..$ end : num [1:4] 1.21e+08 Inf Inf Inf 190s ..$ seed : int [1:7] 10407 1066287653 -51199871 161854402 -1995183193 1503453565 -747102133 190s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 190s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.079 0 0.079 0 0 190s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 190s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 190s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 190s Identification of change points by total copy numbers...done 190s Restructure TCN segmentation results... 190s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean 190s 1 1 554484 120908858 7586 1.3853 190s 2 1 120908859 142693887 0 NA 190s 3 1 142693888 185449813 2681 2.0689 190s 4 1 185449813 247137334 4391 2.6341 190s Number of TCN segments: 4 190s Restructure TCN segmentation results...done 190s Total CN segment #1 ([ 554484,1.20909e+08]) of 4... 190s Number of TCN loci in segment: 7586 190s Locus data for TCN segment: 190s 'data.frame': 7586 obs. of 9 variables: 190s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 190s $ x : num 554484 730720 782343 878522 916294 ... 190s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 190s $ betaT : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 190s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 190s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 190s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 190s $ index : int 1 2 3 4 5 6 7 8 9 10 ... 190s $ rho : num NA NA NA NA NA ... 190s Number of loci: 7586 190s Number of SNPs: 2108 (27.79%) 190s Number of heterozygous SNPs: 2108 (100.00%) 190s Chromosome: 1 190s Segmenting DH signals... 190s Segmenting by CBS... 190s Chromosome: 1 190s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 190s Segmenting by CBS...done 190s List of 4 190s $ data :'data.frame': 7586 obs. of 4 variables: 190s ..$ chromosome: int [1:7586] 1 1 1 1 1 1 1 1 1 1 ... 190s ..$ x : num [1:7586] 554484 730720 782343 878522 916294 ... 190s ..$ y : num [1:7586] NA NA NA NA NA ... 190s ..$ index : int [1:7586] 1 2 3 4 5 6 7 8 9 10 ... 190s $ output :'data.frame': 1 obs. of 6 variables: 190s ..$ sampleName: chr NA 190s ..$ chromosome: int 1 190s ..$ start : num 554484 190s ..$ end : num 1.21e+08 190s ..$ nbrOfLoci : int 2108 190s ..$ mean : num 0.512 190s $ segRows:'data.frame': 1 obs. of 2 variables: 190s ..$ startRow: int 10 190s ..$ endRow : int 7574 190s $ params :List of 5 190s ..$ alpha : num 0.001 190s ..$ undo : num 0 190s ..$ joinSegments : logi TRUE 190s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 190s .. ..$ chromosome: int 1 190s .. ..$ start : num 554484 190s .. ..$ end : num 1.21e+08 190s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 190s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 190s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.025 0 0.025 0 0 190s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 190s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 190s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 190s DH segmentation (locally-indexed) rows: 190s startRow endRow 190s 1 10 7574 190s int [1:7586] 1 2 3 4 5 6 7 8 9 10 ... 190s DH segmentation rows: 190s startRow endRow 190s 1 10 7574 190s Segmenting DH signals...done 190s DH segmentation table: 190s dhStart dhEnd dhNbrOfLoci dhMean 190s 1 554484 120908858 2108 0.5116 190s startRow endRow 190s 1 10 7574 190s Rows: 190s [1] 1 190s TCN segmentation rows: 190s startRow endRow 190s 1 1 7586 190s TCN and DH segmentation rows: 190s startRow endRow 190s 1 1 7586 190s startRow endRow 190s 1 10 7574 190s NULL 190s TCN segmentation (expanded) rows: 190s startRow endRow 190s 1 1 7586 190s TCN and DH segmentation rows: 190s startRow endRow 190s 1 1 7586 190s 2 NA NA 190s 3 7587 10267 190s 4 10268 14658 190s startRow endRow 190s 1 10 7574 190s startRow endRow 190s 1 1 7586 190s Total CN segmentation table (expanded): 190s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 190s 1 1 554484 120908858 7586 1.3853 2108 2108 190s (TCN,DH) segmentation for one total CN segment: 190s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 190s 1 1 1 1 554484 120908858 7586 1.3853 2108 190s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 190s 1 2108 554484 120908858 2108 0.5116 190s Total CN segment #1 ([ 554484,1.20909e+08]) of 4...done 190s Total CN segment #2 ([1.20909e+08,1.42694e+08]) of 4... 190s Number of TCN loci in segment: 0 190s Locus data for TCN segment: 190s 'data.frame': 0 obs. of 9 variables: 190s $ chromosome: int 190s $ x : num 190s $ CT : num 190s $ betaT : num 190s $ betaTN : num 190s $ betaN : num 190s $ muN : num 190s $ index : int 190s $ rho : num 190s Number of loci: 0 190s Number of SNPs: 0 (NaN%) 190s Number of heterozygous SNPs: 0 (NaN%) 190s Chromosome: 1 190s Segmenting DH signals... 190s Segmenting by CBS... 190s Chromosome: NA 190s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 190s Segmenting by CBS...done 190s List of 4 190s $ data :'data.frame': 0 obs. of 4 variables: 190s ..$ chromosome: int(0) 190s ..$ x : num(0) 190s ..$ y : num(0) 190s ..$ index : int(0) 190s $ output :'data.frame': 0 obs. of 6 variables: 190s ..$ sampleName: chr(0) 190s ..$ chromosome: num(0) 190s ..$ start : num(0) 190s ..$ end : num(0) 190s ..$ nbrOfLoci : int(0) 190s ..$ mean : num(0) 190s $ segRows:'data.frame': 0 obs. of 2 variables: 190s ..$ startRow: int(0) 190s ..$ endRow : int(0) 190s $ params :List of 5 190s ..$ alpha : num 0.001 190s ..$ undo : num 0 190s ..$ joinSegments : logi TRUE 190s ..$ knownSegments:'data.frame': 0 obs. of 3 variables: 190s .. ..$ chromosome: int(0) 190s .. ..$ start : num(0) 190s .. ..$ end : num(0) 190s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 190s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 190s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.001 0 0.001 0 0 190s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 190s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 190s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 190s DH segmentation (locally-indexed) rows: 190s [1] startRow endRow 190s <0 rows> (or 0-length row.names) 190s int(0) 190s DH segmentation rows: 190s [1] startRow endRow 190s <0 rows> (or 0-length row.names) 190s Segmenting DH signals...done 190s DH segmentation table: 190s dhStart dhEnd dhNbrOfLoci dhMean 190s NA NA NA NA NA 190s startRow endRow 190s NA NA NA 190s Rows: 190s [1] 2 190s TCN segmentation rows: 190s startRow endRow 190s 2 NA NA 190s TCN and DH segmentation rows: 190s startRow endRow 190s 2 NA NA 190s startRow endRow 190s NA NA NA 190s startRow endRow 190s 1 1 7586 190s TCN segmentation (expanded) rows: 190s startRow endRow 190s 1 1 7586 190s 2 NA NA 190s TCN and DH segmentation rows: 190s startRow endRow 190s 1 1 7586 190s 2 NA NA 190s 3 7587 10267 190s 4 10268 14658 190s startRow endRow 190s 1 10 7574 190s 2 NA NA 190s startRow endRow 190s 1 1 7586 190s 2 NA NA 190s Total CN segmentation table (expanded): 190s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 190s 2 1 120908859 142693887 0 NA 0 0 190s (TCN,DH) segmentation for one total CN segment: 190s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 190s 2 2 1 1 120908859 142693887 0 NA 0 190s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 190s 2 0 NA NA NA NA 190s Total CN segment #2 ([1.20909e+08,1.42694e+08]) of 4...done 190s Total CN segment #3 ([1.42694e+08,1.8545e+08]) of 4... 190s Number of TCN loci in segment: 2681 190s Locus data for TCN segment: 190s 'data.frame': 2681 obs. of 9 variables: 190s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 190s $ x : num 1.43e+08 1.43e+08 1.43e+08 1.43e+08 1.44e+08 ... 190s $ CT : num 2.27 1.55 1.47 1.5 1.81 ... 190s $ betaT : num 0.34 0.55 0.048 0.813 0.575 ... 190s $ betaTN : num 0.441 0.629 -0.05 0.958 0.872 ... 190s $ betaN : num 0.3851 0.3933 0.0981 0.8552 0.7028 ... 190s $ muN : num 0.5 0.5 0 1 1 1 1 0.5 1 1 ... 190s $ index : int 7587 7588 7589 7590 7591 7592 7593 7594 7595 7596 ... 190s $ rho : num 0.117 0.258 NA NA NA ... 190s Number of loci: 2681 190s Number of SNPs: 777 (28.98%) 190s Number of heterozygous SNPs: 777 (100.00%) 190s Chromosome: 1 190s Segmenting DH signals... 190s Segmenting by CBS... 190s Chromosome: 1 190s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 190s Segmenting by CBS...done 190s List of 4 190s $ data :'data.frame': 2681 obs. of 4 variables: 190s ..$ chromosome: int [1:2681] 1 1 1 1 1 1 1 1 1 1 ... 190s ..$ x : num [1:2681] 1.43e+08 1.43e+08 1.43e+08 1.43e+08 1.44e+08 ... 190s ..$ y : num [1:2681] 0.117 0.258 NA NA NA ... 190s ..$ index : int [1:2681] 1 2 3 4 5 6 7 8 9 10 ... 190s $ output :'data.frame': 1 obs. of 6 variables: 190s ..$ sampleName: chr NA 190s ..$ chromosome: int 1 190s ..$ start : num 1.43e+08 190s ..$ end : num 1.85e+08 190s ..$ nbrOfLoci : int 777 190s ..$ mean : num 0.0973 190s $ segRows:'data.frame': 1 obs. of 2 variables: 190s ..$ startRow: int 1 190s ..$ endRow : int 2677 190s $ params :List of 5 190s ..$ alpha : num 0.001 190s ..$ undo : num 0 190s ..$ joinSegments : logi TRUE 190s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 190s .. ..$ chromosome: int 1 190s .. ..$ start : num 1.43e+08 190s .. ..$ end : num 1.85e+08 190s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 190s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 190s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.005 0 0.005 0 0 190s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 190s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 190s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 190s DH segmentation (locally-indexed) rows: 190s startRow endRow 190s 1 1 2677 190s int [1:2681] 7587 7588 7589 7590 7591 7592 7593 7594 7595 7596 ... 190s DH segmentation rows: 190s startRow endRow 190s 1 7587 10263 190s Segmenting DH signals...done 190s DH segmentation table: 190s dhStart dhEnd dhNbrOfLoci dhMean 190s 1 142693888 185449813 777 0.0973 190s startRow endRow 190s 1 7587 10263 190s Rows: 190s [1] 3 190s TCN segmentation rows: 190s startRow endRow 190s 3 7587 10267 190s TCN and DH segmentation rows: 190s startRow endRow 190s 3 7587 10267 190s startRow endRow 190s 1 7587 10263 190s startRow endRow 190s 1 1 7586 190s 2 NA NA 190s TCN segmentation (expanded) rows: 190s startRow endRow 190s 1 1 7586 190s 2 NA NA 190s 3 7587 10267 190s TCN and DH segmentation rows: 190s startRow endRow 190s 1 1 7586 190s 2 NA NA 190s 3 7587 10267 190s 4 10268 14658 190s startRow endRow 190s 1 10 7574 190s 2 NA NA 190s 3 7587 10263 190s startRow endRow 190s 1 1 7586 190s 2 NA NA 190s 3 7587 10267 190s Total CN segmentation table (expanded): 190s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 190s 3 1 142693888 185449813 2681 2.0689 777 777 190s (TCN,DH) segmentation for one total CN segment: 190s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 190s 3 3 1 1 142693888 185449813 2681 2.0689 777 190s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 190s 3 777 142693888 185449813 777 0.0973 190s Total CN segment #3 ([1.42694e+08,1.8545e+08]) of 4...done 190s Total CN segment #4 ([1.8545e+08,2.47137e+08]) of 4... 190s Number of TCN loci in segment: 4391 190s Locus data for TCN segment: 190s 'data.frame': 4391 obs. of 9 variables: 190s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 190s $ x : num 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 190s $ CT : num 2.93 2.15 2.82 2.93 2.46 ... 190s $ betaT : num 0.0811 0.5154 0.9473 0.3734 0.7506 ... 190s $ betaTN : num -0.169 0.609 1.028 0.525 0.968 ... 190s $ betaN : num 0.25 0.38 0.919 0.34 0.783 ... 190s $ muN : num 0 0.5 1 0.5 1 1 0 1 0 1 ... 190s $ index : int 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 190s $ rho : num NA 0.2186 NA 0.0503 NA ... 190s Number of loci: 4391 190s Number of SNPs: 1311 (29.86%) 190s Number of heterozygous SNPs: 1311 (100.00%) 190s Chromosome: 1 190s Segmenting DH signals... 190s Segmenting by CBS... 190s Chromosome: 1 190s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 190s Segmenting by CBS...done 190s List of 4 190s $ data :'data.frame': 4391 obs. of 4 variables: 190s ..$ chromosome: int [1:4391] 1 1 1 1 1 1 1 1 1 1 ... 190s ..$ x : num [1:4391] 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 190s ..$ y : num [1:4391] NA 0.2186 NA 0.0503 NA ... 190s ..$ index : int [1:4391] 1 2 3 4 5 6 7 8 9 10 ... 190s $ output :'data.frame': 1 obs. of 6 variables: 190s ..$ sampleName: chr NA 190s ..$ chromosome: int 1 190s ..$ start : num 1.85e+08 190s ..$ end : num 2.47e+08 190s ..$ nbrOfLoci : int 1311 190s ..$ mean : num 0.23 190s $ segRows:'data.frame': 1 obs. of 2 variables: 190s ..$ startRow: int 2 190s ..$ endRow : int 4388 190s $ params :List of 5 190s ..$ alpha : num 0.001 190s ..$ undo : num 0 190s ..$ joinSegments : logi TRUE 190s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 190s .. ..$ chromosome: int 1 190s .. ..$ start : num 1.85e+08 190s .. ..$ end : num 2.47e+08 190s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 190s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 190s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.013 0 0.013 0 0 190s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 190s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 190s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 190s DH segmentation (locally-indexed) rows: 190s startRow endRow 190s 1 2 4388 190s int [1:4391] 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 190s DH segmentation rows: 190s startRow endRow 190s 1 10269 14655 190s Segmenting DH signals...done 190s DH segmentation table: 190s dhStart dhEnd dhNbrOfLoci dhMean 190s 1 185449813 247137334 1311 0.2295 190s startRow endRow 190s 1 10269 14655 190s Rows: 190s [1] 4 190s TCN segmentation rows: 190s startRow endRow 190s 4 10268 14658 190s TCN and DH segmentation rows: 190s startRow endRow 190s 4 10268 14658 190s startRow endRow 190s 1 10269 14655 190s startRow endRow 190s 1 1 7586 190s 2 NA NA 190s 3 7587 10267 190s TCN segmentation (expanded) rows: 190s startRow endRow 190s 1 1 7586 190s 2 NA NA 190s 3 7587 10267 190s 4 10268 14658 190s TCN and DH segmentation rows: 190s startRow endRow 190s 1 1 7586 190s 2 NA NA 190s 3 7587 10267 190s 4 10268 14658 190s startRow endRow 190s 1 10 7574 190s 2 NA NA 190s 3 7587 10263 190s 4 10269 14655 190s startRow endRow 190s 1 1 7586 190s 2 NA NA 190s 3 7587 10267 190s 4 10268 14658 190s Total CN segmentation table (expanded): 190s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 190s 4 1 185449813 247137334 4391 2.6341 1311 1311 190s (TCN,DH) segmentation for one total CN segment: 190s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 190s 4 4 1 1 185449813 247137334 4391 2.6341 1311 190s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 190s 4 1311 185449813 247137334 1311 0.2295 190s Total CN segment #4 ([1.8545e+08,2.47137e+08]) of 4...done 190s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 190s 1 1 1 1 554484 120908858 7586 1.3853 2108 190s 2 1 2 1 120908859 142693887 0 NA 0 190s 3 1 3 1 142693888 185449813 2681 2.0689 777 190s 4 1 4 1 185449813 247137334 4391 2.6341 1311 190s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 190s 1 2108 554484 120908858 2108 0.5116 190s 2 0 NA NA NA NA 190s 3 777 142693888 185449813 777 0.0973 190s 4 1311 185449813 247137334 1311 0.2295 190s Calculating (C1,C2) per segment... 190s Calculating (C1,C2) per segment...done 190s Number of segments: 4 190s Segmenting paired tumor-normal signals using Paired PSCBS...done 190s Post-segmenting TCNs... 190s Number of segments: 4 190s Number of chromosomes: 1 190s [1] 1 190s Chromosome 1 ('chr01') of 1... 190s Rows: 190s [1] 1 2 3 4 190s Number of segments: 4 190s TCN segment #1 ('1') of 4... 190s Nothing todo. Only one DH segmentation. Skipping. 190s TCN segment #1 ('1') of 4...done 190s TCN segment #2 ('2') of 4... 190s Nothing todo. Only one DH segmentation. Skipping. 190s TCN segment #2 ('2') of 4...done 190s TCN segment #3 ('3') of 4... 190s Nothing todo. Only one DH segmentation. Skipping. 190s TCN segment #3 ('3') of 4...done 190s TCN segment #4 ('4') of 4... 190s Nothing todo. Only one DH segmentation. Skipping. 190s TCN segment #4 ('4') of 4...done 190s Chromosome 1 ('chr01') of 1...done 190s Update (C1,C2) per segment... 190s Update (C1,C2) per segment...done 190s Post-segmenting TCNs...done 190s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 190s 1 1 1 1 554484 120908858 7586 1.3853 2108 190s 2 1 2 1 120908859 142693887 0 NA 0 190s 3 1 3 1 142693888 185449813 2681 2.0689 777 190s 4 1 4 1 185449813 247137334 4391 2.6341 1311 190s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 190s 1 2108 554484 120908858 2108 0.5116 0.3382903 1.047010 190s 2 0 NA NA NA NA NA NA 190s 3 777 142693888 185449813 777 0.0973 0.9337980 1.135102 190s 4 1311 185449813 247137334 1311 0.2295 1.0147870 1.619313 190s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 190s 1 1 1 1 554484 120908858 7586 1.3853 2108 190s 2 1 2 1 120908859 142693887 0 NA 0 190s 3 1 3 1 142693888 185449813 2681 2.0689 777 190s 4 1 4 1 185449813 247137334 4391 2.6341 1311 190s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 190s 1 2108 554484 120908858 2108 0.5116 0.3382903 1.047010 190s 2 0 NA NA NA NA NA NA 190s 3 777 142693888 185449813 777 0.0973 0.9337980 1.135102 190s 4 1311 185449813 247137334 1311 0.2295 1.0147870 1.619313 190s - segmentByPairedPSCBS() w/ known segments using 'multisession' futures ... 190s Segmenting paired tumor-normal signals using Paired PSCBS... 190s Calling genotypes from normal allele B fractions... 190s num [1:14670] 0.8274 0.5072 0.1671 0.1609 0.0421 ... 190s Called genotypes: 190s num [1:14670] 1 0.5 0 0 0 0 1 0 1 0.5 ... 190s - attr(*, "modelFit")=List of 1 190s ..$ :List of 7 190s .. ..$ flavor : chr "density" 190s .. ..$ cn : int 2 190s .. ..$ nbrOfGenotypeGroups: int 3 190s .. ..$ tau : num [1:2] 0.315 0.677 190s .. ..$ n : int 14640 190s .. ..$ fit :Classes 'PeaksAndValleys' and 'data.frame': 5 obs. of 3 variables: 190s .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 190s .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 190s .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 190s .. ..$ fitValleys :Classes 'PeaksAndValleys' and 'data.frame': 2 obs. of 3 variables: 190s .. .. ..$ type : chr [1:2] "valley" "valley" 190s .. .. ..$ x : num [1:2] 0.315 0.677 190s .. .. ..$ density: num [1:2] 0.522 0.551 190s ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 190s muN 190s 0 0.5 1 190s 5221 4198 5251 190s Calling genotypes from normal allele B fractions...done 190s Normalizing betaT using betaN (TumorBoost)... 190s Normalized BAFs: 190s num [1:14670] 0.9301 0.1667 0.0685 0.0995 0.0155 ... 190s - attr(*, "modelFit")=List of 5 190s ..$ method : chr "normalizeTumorBoost" 190s ..$ flavor : chr "v4" 190s ..$ delta : num [1:14670] -0.17264 0.00239 0.1671 0.16085 0.04213 ... 190s .. ..- attr(*, "modelFit")=List of 1 190s .. .. ..$ :List of 7 190s .. .. .. ..$ flavor : chr "density" 190s .. .. .. ..$ cn : int 2 190s .. .. .. ..$ nbrOfGenotypeGroups: int 3 190s .. .. .. ..$ tau : num [1:2] 0.315 0.677 190s .. .. .. ..$ n : int 14640 190s .. .. .. ..$ fit :Classes 'PeaksAndValleys' and 'data.frame': 5 obs. of 3 variables: 190s .. .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 190s .. .. .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 190s .. .. .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 190s .. .. .. ..$ fitValleys :Classes 'PeaksAndValleys' and 'data.frame': 2 obs. of 3 variables: 190s .. .. .. .. ..$ type : chr [1:2] "valley" "valley" 190s .. .. .. .. ..$ x : num [1:2] 0.315 0.677 190s .. .. .. .. ..$ density: num [1:2] 0.522 0.551 190s .. .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 190s ..$ preserveScale: logi FALSE 190s ..$ scaleFactor : num NA 190s Normalizing betaT using betaN (TumorBoost)...done 190s Setup up data... 190s 'data.frame': 14670 obs. of 7 variables: 190s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 190s $ x : num 1145994 2941694 3710825 4240737 4276892 ... 190s $ CT : num 1.63 1.4 1.41 1.17 1.16 ... 190s $ betaT : num 0.7574 0.169 0.2357 0.2604 0.0576 ... 190s $ betaTN : num 0.9301 0.1667 0.0685 0.0995 0.0155 ... 190s ..- attr(*, "modelFit")=List of 5 190s .. ..$ method : chr "normalizeTumorBoost" 190s .. ..$ flavor : chr "v4" 190s .. ..$ delta : num [1:14670] -0.17264 0.00239 0.1671 0.16085 0.04213 ... 190s .. .. ..- attr(*, "modelFit")=List of 1 190s .. .. .. ..$ :List of 7 190s .. .. .. .. ..$ flavor : chr "density" 190s .. .. .. .. ..$ cn : int 2 190s .. .. .. .. ..$ nbrOfGenotypeGroups: int 3 190s .. .. .. .. ..$ tau : num [1:2] 0.315 0.677 190s .. .. .. .. ..$ n : int 14640 190s .. .. .. .. ..$ fit :Classes 'PeaksAndValleys' and 'data.frame': 5 obs. of 3 variables: 190s .. .. .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 190s .. .. .. .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 190s .. .. .. .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 190s .. .. .. .. ..$ fitValleys :Classes 'PeaksAndValleys' and 'data.frame': 2 obs. of 3 variables: 190s .. .. .. .. .. ..$ type : chr [1:2] "valley" "valley" 190s .. .. .. .. .. ..$ x : num [1:2] 0.315 0.677 190s .. .. .. .. .. ..$ density: num [1:2] 0.522 0.551 190s .. .. .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 190s .. ..$ preserveScale: logi FALSE 190s .. ..$ scaleFactor : num NA 190s $ betaN : num 0.8274 0.5072 0.1671 0.1609 0.0421 ... 190s $ muN : num 1 0.5 0 0 0 0 1 0 1 0.5 ... 190s ..- attr(*, "modelFit")=List of 1 190s .. ..$ :List of 7 190s .. .. ..$ flavor : chr "density" 190s .. .. ..$ cn : int 2 190s .. .. ..$ nbrOfGenotypeGroups: int 3 190s .. .. ..$ tau : num [1:2] 0.315 0.677 190s .. .. ..$ n : int 14640 190s .. .. ..$ fit :Classes 'PeaksAndValleys' and 'data.frame': 5 obs. of 3 variables: 190s .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 190s .. .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 190s .. .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 190s .. .. ..$ fitValleys :Classes 'PeaksAndValleys' and 'data.frame': 2 obs. of 3 variables: 190s .. .. .. ..$ type : chr [1:2] "valley" "valley" 190s .. .. .. ..$ x : num [1:2] 0.315 0.677 190s .. .. .. ..$ density: num [1:2] 0.522 0.551 190s .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 190s Setup up data...done 190s Dropping loci for which TCNs are missing... 190s Number of loci dropped: 12 190s Dropping loci for which TCNs are missing...done 190s Ordering data along genome... 190s 'data.frame': 14658 obs. of 7 variables: 190s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 190s $ x : num 554484 730720 782343 878522 916294 ... 190s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 190s $ betaT : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 190s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 190s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 190s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 190s Ordering data along genome...done 190s Keeping only current chromosome for 'knownSegments'... 190s Chromosome: 1 190s Known segments for this chromosome: 190s chromosome start end length 190s 1 1 -Inf 120908858 Inf 190s 2 1 120908859 142693887 21785028 190s 3 1 142693888 Inf Inf 190s Keeping only current chromosome for 'knownSegments'...done 190s alphaTCN: 0.009 190s alphaDH: 0.001 190s Number of loci: 14658 190s Calculating DHs... 190s Number of SNPs: 14658 190s Number of heterozygous SNPs: 4196 (28.63%) 190s Normalized DHs: 190s num [1:14658] NA NA NA NA NA ... 190s Calculating DHs...done 190s Random seed temporarily set (seed=c(48879), kind="L'Ecuyer-CMRG") 190s Produced 2 seeds from this stream for future usage 190s Identification of change points by total copy numbers... 190s Segmenting by CBS... 190s Chromosome: 1 190s Random seed temporarily set (seed=c(10407, 1066287653, -51199871, 161854402, -1995183193, 1503453565, -747102133), kind="L'Ecuyer-CMRG") 190s Produced 3 seeds from this stream for future usage 190s Segmenting by CBS...done 190s List of 4 190s $ data :'data.frame': 14658 obs. of 4 variables: 190s ..$ chromosome: int [1:14658] 1 1 1 1 1 1 1 1 1 1 ... 190s ..$ x : num [1:14658] 554484 730720 782343 878522 916294 ... 190s ..$ y : num [1:14658] 1.88 1.8 1.59 1.64 1.53 ... 190s ..$ index : int [1:14658] 1 2 3 4 5 6 7 8 9 10 ... 190s $ output :'data.frame': 4 obs. of 6 variables: 190s ..$ sampleName: chr [1:4] NA NA NA NA 190s ..$ chromosome: int [1:4] 1 1 1 1 190s ..$ start : num [1:4] 5.54e+05 1.21e+08 1.43e+08 1.85e+08 190s ..$ end : num [1:4] 1.21e+08 1.43e+08 1.85e+08 2.47e+08 190s ..$ nbrOfLoci : int [1:4] 7586 0 2681 4391 190s ..$ mean : num [1:4] 1.39 NA 2.07 2.63 190s $ segRows:'data.frame': 4 obs. of 2 variables: 190s ..$ startRow: int [1:4] 1 NA 7587 10268 190s ..$ endRow : int [1:4] 7586 NA 10267 14658 190s $ params :List of 5 190s ..$ alpha : num 0.009 190s ..$ undo : num 0 190s ..$ joinSegments : logi TRUE 190s ..$ knownSegments:'data.frame': 4 obs. of 3 variables: 190s .. ..$ chromosome: int [1:4] 1 1 2 1 190s .. ..$ start : num [1:4] -Inf -Inf -Inf 1.43e+08 190s .. ..$ end : num [1:4] 1.21e+08 Inf Inf Inf 190s ..$ seed : int [1:7] 10407 1066287653 -51199871 161854402 -1995183193 1503453565 -747102133 190s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 190s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.089 0 0.089 0 0 190s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 190s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 190s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 190s Identification of change points by total copy numbers...done 190s Restructure TCN segmentation results... 190s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean 190s 1 1 554484 120908858 7586 1.3853 190s 2 1 120908859 142693887 0 NA 190s 3 1 142693888 185449813 2681 2.0689 190s 4 1 185449813 247137334 4391 2.6341 190s Number of TCN segments: 4 190s Restructure TCN segmentation results...done 190s Total CN segment #1 ([ 554484,1.20909e+08]) of 4... 190s Number of TCN loci in segment: 7586 190s Locus data for TCN segment: 190s 'data.frame': 7586 obs. of 9 variables: 190s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 190s $ x : num 554484 730720 782343 878522 916294 ... 190s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 190s $ betaT : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 190s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 190s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 190s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 190s $ index : int 1 2 3 4 5 6 7 8 9 10 ... 190s $ rho : num NA NA NA NA NA ... 190s Number of loci: 7586 190s Number of SNPs: 2108 (27.79%) 190s Number of heterozygous SNPs: 2108 (100.00%) 190s Chromosome: 1 190s Segmenting DH signals... 190s Segmenting by CBS... 190s Chromosome: 1 190s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 190s Segmenting by CBS...done 190s List of 4 190s $ data :'data.frame': 7586 obs. of 4 variables: 190s ..$ chromosome: int [1:7586] 1 1 1 1 1 1 1 1 1 1 ... 190s ..$ x : num [1:7586] 554484 730720 782343 878522 916294 ... 190s ..$ y : num [1:7586] NA NA NA NA NA ... 190s ..$ index : int [1:7586] 1 2 3 4 5 6 7 8 9 10 ... 190s $ output :'data.frame': 1 obs. of 6 variables: 190s ..$ sampleName: chr NA 190s ..$ chromosome: int 1 190s ..$ start : num 554484 190s ..$ end : num 1.21e+08 190s ..$ nbrOfLoci : int 2108 190s ..$ mean : num 0.512 190s $ segRows:'data.frame': 1 obs. of 2 variables: 190s ..$ startRow: int 10 190s ..$ endRow : int 7574 190s $ params :List of 5 190s ..$ alpha : num 0.001 190s ..$ undo : num 0 190s ..$ joinSegments : logi TRUE 190s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 190s .. ..$ chromosome: int 1 190s .. ..$ start : num 554484 190s .. ..$ end : num 1.21e+08 190s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 190s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 190s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.026 0 0.026 0 0 190s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 190s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 190s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 190s DH segmentation (locally-indexed) rows: 190s startRow endRow 190s 1 10 7574 190s int [1:7586] 1 2 3 4 5 6 7 8 9 10 ... 190s DH segmentation rows: 190s startRow endRow 190s 1 10 7574 190s Segmenting DH signals...done 190s DH segmentation table: 190s dhStart dhEnd dhNbrOfLoci dhMean 190s 1 554484 120908858 2108 0.5116 190s startRow endRow 190s 1 10 7574 190s Rows: 190s [1] 1 190s TCN segmentation rows: 190s startRow endRow 190s 1 1 7586 190s TCN and DH segmentation rows: 190s startRow endRow 190s 1 1 7586 190s startRow endRow 190s 1 10 7574 190s NULL 190s TCN segmentation (expanded) rows: 190s startRow endRow 190s 1 1 7586 190s TCN and DH segmentation rows: 190s startRow endRow 190s 1 1 7586 190s 2 NA NA 190s 3 7587 10267 190s 4 10268 14658 190s startRow endRow 190s 1 10 7574 190s startRow endRow 190s 1 1 7586 190s Total CN segmentation table (expanded): 190s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 190s 1 1 554484 120908858 7586 1.3853 2108 2108 190s (TCN,DH) segmentation for one total CN segment: 190s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 190s 1 1 1 1 554484 120908858 7586 1.3853 2108 190s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 190s 1 2108 554484 120908858 2108 0.5116 190s Total CN segment #1 ([ 554484,1.20909e+08]) of 4...done 190s Total CN segment #2 ([1.20909e+08,1.42694e+08]) of 4... 190s Number of TCN loci in segment: 0 190s Locus data for TCN segment: 190s 'data.frame': 0 obs. of 9 variables: 190s $ chromosome: int 190s $ x : num 190s $ CT : num 190s $ betaT : num 190s $ betaTN : num 190s $ betaN : num 190s $ muN : num 190s $ index : int 190s $ rho : num 190s Number of loci: 0 190s Number of SNPs: 0 (NaN%) 190s Number of heterozygous SNPs: 0 (NaN%) 190s Chromosome: 1 190s Segmenting DH signals... 190s Segmenting by CBS... 190s Chromosome: NA 190s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 190s Segmenting by CBS...done 190s List of 4 190s $ data :'data.frame': 0 obs. of 4 variables: 190s ..$ chromosome: int(0) 190s ..$ x : num(0) 190s ..$ y : num(0) 190s ..$ index : int(0) 190s $ output :'data.frame': 0 obs. of 6 variables: 190s ..$ sampleName: chr(0) 190s ..$ chromosome: num(0) 190s ..$ start : num(0) 190s ..$ end : num(0) 190s ..$ nbrOfLoci : int(0) 190s ..$ mean : num(0) 190s $ segRows:'data.frame': 0 obs. of 2 variables: 190s ..$ startRow: int(0) 190s ..$ endRow : int(0) 190s $ params :List of 5 190s ..$ alpha : num 0.001 190s ..$ undo : num 0 190s ..$ joinSegments : logi TRUE 190s ..$ knownSegments:'data.frame': 0 obs. of 3 variables: 190s .. ..$ chromosome: int(0) 190s .. ..$ start : num(0) 190s .. ..$ end : num(0) 190s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 190s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 190s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.001 0 0.001 0 0 190s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 190s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 190s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 190s DH segmentation (locally-indexed) rows: 190s [1] startRow endRow 190s <0 rows> (or 0-length row.names) 190s int(0) 190s DH segmentation rows: 190s [1] startRow endRow 190s <0 rows> (or 0-length row.names) 190s Segmenting DH signals...done 190s DH segmentation table: 190s dhStart dhEnd dhNbrOfLoci dhMean 190s NA NA NA NA NA 190s startRow endRow 190s NA NA NA 190s Rows: 190s [1] 2 190s TCN segmentation rows: 190s startRow endRow 190s 2 NA NA 190s TCN and DH segmentation rows: 190s startRow endRow 190s 2 NA NA 190s startRow endRow 190s NA NA NA 190s startRow endRow 190s 1 1 7586 190s TCN segmentation (expanded) rows: 190s startRow endRow 190s 1 1 7586 190s 2 NA NA 190s TCN and DH segmentation rows: 190s startRow endRow 190s 1 1 7586 190s 2 NA NA 190s 3 7587 10267 190s 4 10268 14658 190s startRow endRow 190s 1 10 7574 190s 2 NA NA 190s startRow endRow 190s 1 1 7586 190s 2 NA NA 190s Total CN segmentation table (expanded): 190s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 190s 2 1 120908859 142693887 0 NA 0 0 190s (TCN,DH) segmentation for one total CN segment: 190s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 190s 2 2 1 1 120908859 142693887 0 NA 0 190s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 190s 2 0 NA NA NA NA 190s Total CN segment #2 ([1.20909e+08,1.42694e+08]) of 4...done 190s Total CN segment #3 ([1.42694e+08,1.8545e+08]) of 4... 190s Number of TCN loci in segment: 2681 190s Locus data for TCN segment: 190s 'data.frame': 2681 obs. of 9 variables: 190s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 190s $ x : num 1.43e+08 1.43e+08 1.43e+08 1.43e+08 1.44e+08 ... 190s $ CT : num 2.27 1.55 1.47 1.5 1.81 ... 190s $ betaT : num 0.34 0.55 0.048 0.813 0.575 ... 190s $ betaTN : num 0.441 0.629 -0.05 0.958 0.872 ... 190s $ betaN : num 0.3851 0.3933 0.0981 0.8552 0.7028 ... 190s $ muN : num 0.5 0.5 0 1 1 1 1 0.5 1 1 ... 190s $ index : int 7587 7588 7589 7590 7591 7592 7593 7594 7595 7596 ... 190s $ rho : num 0.117 0.258 NA NA NA ... 190s Number of loci: 2681 190s Number of SNPs: 777 (28.98%) 190s Number of heterozygous SNPs: 777 (100.00%) 190s Chromosome: 1 190s Segmenting DH signals... 190s Segmenting by CBS... 190s Chromosome: 1 190s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 190s Segmenting by CBS...done 190s List of 4 190s $ data :'data.frame': 2681 obs. of 4 variables: 190s ..$ chromosome: int [1:2681] 1 1 1 1 1 1 1 1 1 1 ... 190s ..$ x : num [1:2681] 1.43e+08 1.43e+08 1.43e+08 1.43e+08 1.44e+08 ... 190s ..$ y : num [1:2681] 0.117 0.258 NA NA NA ... 190s ..$ index : int [1:2681] 1 2 3 4 5 6 7 8 9 10 ... 190s $ output :'data.frame': 1 obs. of 6 variables: 190s ..$ sampleName: chr NA 190s ..$ chromosome: int 1 190s ..$ start : num 1.43e+08 190s ..$ end : num 1.85e+08 190s ..$ nbrOfLoci : int 777 190s ..$ mean : num 0.0973 190s $ segRows:'data.frame': 1 obs. of 2 variables: 190s ..$ startRow: int 1 190s ..$ endRow : int 2677 190s $ params :List of 5 190s ..$ alpha : num 0.001 190s ..$ undo : num 0 190s ..$ joinSegments : logi TRUE 190s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 190s .. ..$ chromosome: int 1 190s .. ..$ start : num 1.43e+08 190s .. ..$ end : num 1.85e+08 190s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 190s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 190s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.005 0 0.006 0 0 190s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 190s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 190s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 190s DH segmentation (locally-indexed) rows: 190s startRow endRow 190s 1 1 2677 190s int [1:2681] 7587 7588 7589 7590 7591 7592 7593 7594 7595 7596 ... 190s DH segmentation rows: 190s startRow endRow 190s 1 7587 10263 190s Segmenting DH signals...done 190s DH segmentation table: 190s dhStart dhEnd dhNbrOfLoci dhMean 190s 1 142693888 185449813 777 0.0973 190s startRow endRow 190s 1 7587 10263 190s Rows: 190s [1] 3 190s TCN segmentation rows: 190s startRow endRow 190s 3 7587 10267 190s TCN and DH segmentation rows: 190s startRow endRow 190s 3 7587 10267 190s startRow endRow 190s 1 7587 10263 190s startRow endRow 190s 1 1 7586 190s 2 NA NA 190s TCN segmentation (expanded) rows: 190s startRow endRow 190s 1 1 7586 190s 2 NA NA 190s 3 7587 10267 190s TCN and DH segmentation rows: 190s startRow endRow 190s 1 1 7586 190s 2 NA NA 190s 3 7587 10267 190s 4 10268 14658 190s startRow endRow 190s 1 10 7574 190s 2 NA NA 190s 3 7587 10263 190s startRow endRow 190s 1 1 7586 190s 2 NA NA 190s 3 7587 10267 190s Total CN segmentation table (expanded): 190s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 190s 3 1 142693888 185449813 2681 2.0689 777 777 190s (TCN,DH) segmentation for one total CN segment: 190s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 190s 3 3 1 1 142693888 185449813 2681 2.0689 777 190s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 190s 3 777 142693888 185449813 777 0.0973 190s Total CN segment #3 ([1.42694e+08,1.8545e+08]) of 4...done 190s Total CN segment #4 ([1.8545e+08,2.47137e+08]) of 4... 190s Number of TCN loci in segment: 4391 190s Locus data for TCN segment: 190s 'data.frame': 4391 obs. of 9 variables: 190s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 190s $ x : num 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 190s $ CT : num 2.93 2.15 2.82 2.93 2.46 ... 190s $ betaT : num 0.0811 0.5154 0.9473 0.3734 0.7506 ... 190s $ betaTN : num -0.169 0.609 1.028 0.525 0.968 ... 190s $ betaN : num 0.25 0.38 0.919 0.34 0.783 ... 190s $ muN : num 0 0.5 1 0.5 1 1 0 1 0 1 ... 190s $ index : int 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 190s $ rho : num NA 0.2186 NA 0.0503 NA ... 190s Number of loci: 4391 190s Number of SNPs: 1311 (29.86%) 190s Number of heterozygous SNPs: 1311 (100.00%) 190s Chromosome: 1 190s Segmenting DH signals... 190s Segmenting by CBS... 190s Chromosome: 1 190s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 190s Segmenting by CBS...done 190s List of 4 190s $ data :'data.frame': 4391 obs. of 4 variables: 190s ..$ chromosome: int [1:4391] 1 1 1 1 1 1 1 1 1 1 ... 190s ..$ x : num [1:4391] 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 190s ..$ y : num [1:4391] NA 0.2186 NA 0.0503 NA ... 190s ..$ index : int [1:4391] 1 2 3 4 5 6 7 8 9 10 ... 190s $ output :'data.frame': 1 obs. of 6 variables: 190s ..$ sampleName: chr NA 190s ..$ chromosome: int 1 190s ..$ start : num 1.85e+08 190s ..$ end : num 2.47e+08 190s ..$ nbrOfLoci : int 1311 190s ..$ mean : num 0.23 190s $ segRows:'data.frame': 1 obs. of 2 variables: 190s ..$ startRow: int 2 190s ..$ endRow : int 4388 190s $ params :List of 5 190s ..$ alpha : num 0.001 190s ..$ undo : num 0 190s ..$ joinSegments : logi TRUE 190s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 190s .. ..$ chromosome: int 1 190s .. ..$ start : num 1.85e+08 190s .. ..$ end : num 2.47e+08 190s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 190s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 190s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.01 0 0.01 0 0 190s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 190s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 190s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 190s DH segmentation (locally-indexed) rows: 190s startRow endRow 190s 1 2 4388 190s int [1:4391] 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 190s DH segmentation rows: 190s startRow endRow 190s 1 10269 14655 190s Segmenting DH signals...done 190s DH segmentation table: 190s dhStart dhEnd dhNbrOfLoci dhMean 190s 1 185449813 247137334 1311 0.2295 190s startRow endRow 190s 1 10269 14655 190s Rows: 190s [1] 4 190s TCN segmentation rows: 190s startRow endRow 190s 4 10268 14658 190s TCN and DH segmentation rows: 190s startRow endRow 190s 4 10268 14658 190s startRow endRow 190s 1 10269 14655 190s startRow endRow 190s 1 1 7586 190s 2 NA NA 190s 3 7587 10267 190s TCN segmentation (expanded) rows: 190s startRow endRow 190s 1 1 7586 190s 2 NA NA 190s 3 7587 10267 190s 4 10268 14658 190s TCN and DH segmentation rows: 190s startRow endRow 190s 1 1 7586 190s 2 NA NA 190s 3 7587 10267 190s 4 10268 14658 190s startRow endRow 190s 1 10 7574 190s 2 NA NA 190s 3 7587 10263 190s 4 10269 14655 190s startRow endRow 190s 1 1 7586 190s 2 NA NA 190s 3 7587 10267 190s 4 10268 14658 190s Total CN segmentation table (expanded): 190s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 190s 4 1 185449813 247137334 4391 2.6341 1311 1311 190s (TCN,DH) segmentation for one total CN segment: 190s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 190s 4 4 1 1 185449813 247137334 4391 2.6341 1311 190s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 190s 4 1311 185449813 247137334 1311 0.2295 190s Total CN segment #4 ([1.8545e+08,2.47137e+08]) of 4...done 190s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 190s 1 1 1 1 554484 120908858 7586 1.3853 2108 190s 2 1 2 1 120908859 142693887 0 NA 0 190s 3 1 3 1 142693888 185449813 2681 2.0689 777 190s 4 1 4 1 185449813 247137334 4391 2.6341 1311 190s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 190s 1 2108 554484 120908858 2108 0.5116 190s 2 0 NA NA NA NA 190s 3 777 142693888 185449813 777 0.0973 190s 4 1311 185449813 247137334 1311 0.2295 190s Calculating (C1,C2) per segment... 190s Calculating (C1,C2) per segment...done 190s Number of segments: 4 190s Segmenting paired tumor-normal signals using Paired PSCBS...done 190s Post-segmenting TCNs... 190s Number of segments: 4 190s Number of chromosomes: 1 190s [1] 1 190s Chromosome 1 ('chr01') of 1... 190s Rows: 190s [1] 1 2 3 4 190s Number of segments: 4 190s TCN segment #1 ('1') of 4... 190s Nothing todo. Only one DH segmentation. Skipping. 190s TCN segment #1 ('1') of 4...done 190s TCN segment #2 ('2') of 4... 190s Nothing todo. Only one DH segmentation. Skipping. 190s TCN segment #2 ('2') of 4...done 190s TCN segment #3 ('3') of 4... 190s Nothing todo. Only one DH segmentation. Skipping. 190s TCN segment #3 ('3') of 4...done 190s TCN segment #4 ('4') of 4... 190s Nothing todo. Only one DH segmentation. Skipping. 190s TCN segment #4 ('4') of 4...done 190s Chromosome 1 ('chr01') of 1...done 190s Update (C1,C2) per segment... 190s Update (C1,C2) per segment...done 190s Post-segmenting TCNs...done 190s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 190s 1 1 1 1 554484 120908858 7586 1.3853 2108 190s 2 1 2 1 120908859 142693887 0 NA 0 190s 3 1 3 1 142693888 185449813 2681 2.0689 777 190s 4 1 4 1 185449813 247137334 4391 2.6341 1311 190s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 190s 1 2108 554484 120908858 2108 0.5116 0.3382903 1.047010 190s 2 0 NA NA NA NA NA NA 190s 3 777 142693888 185449813 777 0.0973 0.9337980 1.135102 190s 4 1311 185449813 247137334 1311 0.2295 1.0147870 1.619313 190s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 190s 1 1 1 1 554484 120908858 7586 1.3853 2108 190s 2 1 2 1 120908859 142693887 0 NA 0 190s 3 1 3 1 142693888 185449813 2681 2.0689 777 190s 4 1 4 1 185449813 247137334 4391 2.6341 1311 190s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 190s 1 2108 554484 120908858 2108 0.5116 0.3382903 1.047010 190s 2 0 NA NA NA NA NA NA 190s 3 777 142693888 185449813 777 0.0973 0.9337980 1.135102 190s 4 1311 185449813 247137334 1311 0.2295 1.0147870 1.619313 190s > 190s > message("*** segmentByPairedPSCBS() via futures ... DONE") 190s *** segmentByPairedPSCBS() via futures ... DONE 190s > 190s > 190s > ## Cleanup 190s > plan(oplan) 190s > rm(list=c("fits", "data", "fit")) 190s > 190s > proc.time() 190s user system elapsed 190s 3.528 0.102 6.401 190s Test segmentByPairedPSCBS,futures passed 190s 0 190s Begin test segmentByPairedPSCBS,noNormalBAFs 190s + [ 0 != 0 ] 190s + echo Test segmentByPairedPSCBS,futures passed 190s + echo 0 190s + echo Begin test segmentByPairedPSCBS,noNormalBAFs 190s + exitcode=0 190s + R CMD BATCH segmentByPairedPSCBS,noNormalBAFs.R 192s + cat segmentByPairedPSCBS,noNormalBAFs.Rout 192s 192s R version 4.5.2 (2025-10-31) -- "[Not] Part in a Rumble" 192s Copyright (C) 2025 The R Foundation for Statistical Computing 192s Platform: x86_64-pc-linux-gnu 192s 192s R is free software and comes with ABSOLUTELY NO WARRANTY. 192s You are welcome to redistribute it under certain conditions. 192s Type 'license()' or 'licence()' for distribution details. 192s 192s R is a collaborative project with many contributors. 192s Type 'contributors()' for more information and 192s 'citation()' on how to cite R or R packages in publications. 192s 192s Type 'demo()' for some demos, 'help()' for on-line help, or 192s 'help.start()' for an HTML browser interface to help. 192s Type 'q()' to quit R. 192s 192s [Previously saved workspace restored] 192s 192s > library("PSCBS") 192s PSCBS v0.68.0 (2025-04-18 19:40:02 UTC) successfully loaded. See ?PSCBS for help. 192s > 192s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 192s > # Load SNP microarray data 192s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 192s > data <- PSCBS::exampleData("paired.chr01") 192s > str(data) 192s 'data.frame': 73346 obs. of 6 variables: 192s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 192s $ x : int 1145994 2224111 2319424 2543484 2926730 2941694 3084986 3155127 3292731 3695086 ... 192s $ CT : num 1.625 1.071 1.406 1.18 0.856 ... 192s $ betaT : num 0.757 0.771 0.834 0.778 0.229 ... 192s $ CN : num 2.36 2.13 2.59 1.93 1.71 ... 192s $ betaN : num 0.827 0.875 0.887 0.884 0.103 ... 192s > 192s > # Drop single-locus outliers 192s > dataS <- dropSegmentationOutliers(data) 192s > 192s > # Run light-weight tests by default 192s > if (Sys.getenv("_R_CHECK_FULL_") == "") { 192s + # Use only every 5th data point 192s + dataS <- dataS[seq(from=1, to=nrow(data), by=5),] 192s + # Number of segments (for assertion) 192s + nSegs <- 3L 192s + # Number of bootstrap samples (see below) 192s + B <- 100L 192s + } else { 192s + # Full tests 192s + nSegs <- 8L 192s + B <- 1000L 192s + } 192s > 192s > str(dataS) 192s 'data.frame': 14670 obs. of 6 variables: 192s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 192s $ x : int 1145994 2941694 3710825 4240737 4276892 4464544 4714611 5095111 5034491 5158416 ... 192s $ CT : num 1.63 1.4 1.41 1.17 1.16 ... 192s $ betaT : num 0.7574 0.169 0.2357 0.2604 0.0576 ... 192s $ CN : num 2.36 2.13 2.26 2.01 2.32 ... 192s $ betaN : num 0.8274 0.5072 0.1671 0.1609 0.0421 ... 192s > 192s > R.oo::attachLocally(dataS) 192s > 192s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 192s > # Simulate that genotypes are known by other means 192s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 192s > library("aroma.light") 192s aroma.light v3.36.0 (2024-10-29) successfully loaded. See ?aroma.light for help. 192s > muN <- aroma.light::callNaiveGenotypes(betaN, censorAt=c(0,1)) 192s > 192s > 192s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 192s > # Paired PSCBS segmentation 192s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 192s > fit <- segmentByPairedPSCBS(CT, betaT=betaT, muN=muN, tbn=FALSE, 192s + chromosome=chromosome, x=x, 192s + seed=0xBEEF, verbose=-10) 192s Segmenting paired tumor-normal signals using Paired PSCBS... 192s Setup up data... 192s 'data.frame': 14670 obs. of 6 variables: 192s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 192s $ x : num 1145994 2941694 3710825 4240737 4276892 ... 192s $ CT : num 1.63 1.4 1.41 1.17 1.16 ... 192s $ betaT : num 0.7574 0.169 0.2357 0.2604 0.0576 ... 192s $ betaTN : num 0.7574 0.169 0.2357 0.2604 0.0576 ... 192s $ muN : num 1 0.5 0 0 0 0 1 0 1 0.5 ... 192s ..- attr(*, "modelFit")=List of 1 192s .. ..$ :List of 7 192s .. .. ..$ flavor : chr "density" 192s .. .. ..$ cn : int 2 192s .. .. ..$ nbrOfGenotypeGroups: int 3 192s .. .. ..$ tau : num [1:2] 0.315 0.677 192s .. .. ..$ n : int 14640 192s .. .. ..$ fit :Classes 'PeaksAndValleys' and 'data.frame': 5 obs. of 3 variables: 192s .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 192s .. .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 192s .. .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 192s .. .. ..$ fitValleys :Classes 'PeaksAndValleys' and 'data.frame': 2 obs. of 3 variables: 192s .. .. .. ..$ type : chr [1:2] "valley" "valley" 192s .. .. .. ..$ x : num [1:2] 0.315 0.677 192s .. .. .. ..$ density: num [1:2] 0.522 0.551 192s .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 192s Setup up data...done 192s Dropping loci for which TCNs are missing... 192s Number of loci dropped: 12 192s Dropping loci for which TCNs are missing...done 192s Ordering data along genome... 192s 'data.frame': 14658 obs. of 6 variables: 192s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 192s $ x : num 554484 730720 782343 878522 916294 ... 192s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 192s $ betaT : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 192s $ betaTN : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 192s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 192s Ordering data along genome...done 192s Keeping only current chromosome for 'knownSegments'... 192s Chromosome: 1 192s Known segments for this chromosome: 192s [1] chromosome start end 192s <0 rows> (or 0-length row.names) 192s Keeping only current chromosome for 'knownSegments'...done 192s alphaTCN: 0.009 192s alphaDH: 0.001 192s Number of loci: 14658 192s Calculating DHs... 192s Number of SNPs: 14658 192s Number of heterozygous SNPs: 4196 (28.63%) 192s Normalized DHs: 192s num [1:14658] NA NA NA NA NA ... 192s Calculating DHs...done 192s Random seed temporarily set (seed=c(48879), kind="L'Ecuyer-CMRG") 192s Produced 2 seeds from this stream for future usage 192s Identification of change points by total copy numbers... 192s Segmenting by CBS... 192s Chromosome: 1 192s Random seed temporarily set (seed=c(10407, 1066287653, -51199871, 161854402, -1995183193, 1503453565, -747102133), kind="L'Ecuyer-CMRG") 192s Segmenting by CBS...done 192s List of 4 192s $ data :'data.frame': 14658 obs. of 4 variables: 192s ..$ chromosome: int [1:14658] 1 1 1 1 1 1 1 1 1 1 ... 192s ..$ x : num [1:14658] 554484 730720 782343 878522 916294 ... 192s ..$ y : num [1:14658] 1.88 1.8 1.59 1.64 1.53 ... 192s ..$ index : int [1:14658] 1 2 3 4 5 6 7 8 9 10 ... 192s $ output :'data.frame': 3 obs. of 6 variables: 192s ..$ sampleName: chr [1:3] NA NA NA 192s ..$ chromosome: int [1:3] 1 1 1 192s ..$ start : num [1:3] 5.54e+05 1.44e+08 1.85e+08 192s ..$ end : num [1:3] 1.44e+08 1.85e+08 2.47e+08 192s ..$ nbrOfLoci : int [1:3] 7599 2668 4391 192s ..$ mean : num [1:3] 1.39 2.07 2.63 192s $ segRows:'data.frame': 3 obs. of 2 variables: 192s ..$ startRow: int [1:3] 1 7600 10268 192s ..$ endRow : int [1:3] 7599 10267 14658 192s $ params :List of 5 192s ..$ alpha : num 0.009 192s ..$ undo : num 0 192s ..$ joinSegments : logi TRUE 192s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 192s .. ..$ chromosome: int 1 192s .. ..$ start : num -Inf 192s .. ..$ end : num Inf 192s ..$ seed : int [1:7] 10407 1066287653 -51199871 161854402 -1995183193 1503453565 -747102133 192s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 192s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.256 0 0.257 0 0 192s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 192s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 192s - attr(*, "randomSeed")= int [1:7] 10407 1066287653 -51199871 161854402 -1995183193 1503453565 -747102133 192s Identification of change points by total copy numbers...done 192s Restructure TCN segmentation results... 192s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean 192s 1 1 554484 143926517 7599 1.3859 192s 2 1 143926517 185449813 2668 2.0704 192s 3 1 185449813 247137334 4391 2.6341 192s Number of TCN segments: 3 192s Restructure TCN segmentation results...done 192s Total CN segment #1 ([ 554484,1.43927e+08]) of 3... 192s Number of TCN loci in segment: 7599 192s Locus data for TCN segment: 192s 'data.frame': 7599 obs. of 8 variables: 192s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 192s $ x : num 554484 730720 782343 878522 916294 ... 192s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 192s $ betaT : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 192s $ betaTN : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 192s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 192s $ index : int 1 2 3 4 5 6 7 8 9 10 ... 192s $ rho : num NA NA NA NA NA ... 192s Number of loci: 7599 192s Number of SNPs: 2111 (27.78%) 192s Number of heterozygous SNPs: 2111 (100.00%) 192s Chromosome: 1 192s Segmenting DH signals... 192s Segmenting by CBS... 192s Chromosome: 1 192s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 192s Segmenting by CBS...done 192s List of 4 192s $ data :'data.frame': 7599 obs. of 4 variables: 192s ..$ chromosome: int [1:7599] 1 1 1 1 1 1 1 1 1 1 ... 192s ..$ x : num [1:7599] 554484 730720 782343 878522 916294 ... 192s ..$ y : num [1:7599] NA NA NA NA NA ... 192s ..$ index : int [1:7599] 1 2 3 4 5 6 7 8 9 10 ... 192s $ output :'data.frame': 1 obs. of 6 variables: 192s ..$ sampleName: chr NA 192s ..$ chromosome: int 1 192s ..$ start : num 554484 192s ..$ end : num 1.44e+08 192s ..$ nbrOfLoci : int 2111 192s ..$ mean : num 0.524 192s $ segRows:'data.frame': 1 obs. of 2 variables: 192s ..$ startRow: int 10 192s ..$ endRow : int 7594 192s $ params :List of 5 192s ..$ alpha : num 0.001 192s ..$ undo : num 0 192s ..$ joinSegments : logi TRUE 192s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 192s .. ..$ chromosome: int 1 192s .. ..$ start : num 554484 192s .. ..$ end : num 1.44e+08 192s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 192s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 192s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.017 0 0.017 0 0 192s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 192s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 192s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 192s DH segmentation (locally-indexed) rows: 192s startRow endRow 192s 1 10 7594 192s int [1:7599] 1 2 3 4 5 6 7 8 9 10 ... 192s DH segmentation rows: 192s startRow endRow 192s 1 10 7594 192s Segmenting DH signals...done 192s DH segmentation table: 192s dhStart dhEnd dhNbrOfLoci dhMean 192s 1 554484 143926517 2111 0.5237 192s startRow endRow 192s 1 10 7594 192s Rows: 192s [1] 1 192s TCN segmentation rows: 192s startRow endRow 192s 1 1 7599 192s TCN and DH segmentation rows: 192s startRow endRow 192s 1 1 7599 192s startRow endRow 192s 1 10 7594 192s NULL 192s TCN segmentation (expanded) rows: 192s startRow endRow 192s 1 1 7599 192s TCN and DH segmentation rows: 192s startRow endRow 192s 1 1 7599 192s 2 7600 10267 192s 3 10268 14658 192s startRow endRow 192s 1 10 7594 192s startRow endRow 192s 1 1 7599 192s Total CN segmentation table (expanded): 192s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 192s 1 1 554484 143926517 7599 1.3859 2111 2111 192s (TCN,DH) segmentation for one total CN segment: 192s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 192s 1 1 1 1 554484 143926517 7599 1.3859 2111 192s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 192s 1 2111 554484 143926517 2111 0.5237 192s Total CN segment #1 ([ 554484,1.43927e+08]) of 3...done 192s Total CN segment #2 ([1.43927e+08,1.8545e+08]) of 3... 192s Number of TCN loci in segment: 2668 192s Locus data for TCN segment: 192s 'data.frame': 2668 obs. of 8 variables: 192s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 192s $ x : num 1.44e+08 1.44e+08 1.44e+08 1.44e+08 1.44e+08 ... 192s $ CT : num 2.1 2.1 2.09 1.8 2.34 ... 192s $ betaT : num 0.1899 0.909 0.9166 0.1668 0.0308 ... 192s $ betaTN : num 0.1899 0.909 0.9166 0.1668 0.0308 ... 192s $ muN : num 0 1 1 0 0 1 0 0 0 0 ... 192s $ index : int 7600 7601 7602 7603 7604 7605 7606 7607 7608 7609 ... 192s $ rho : num NA NA NA NA NA NA NA NA NA NA ... 192s Number of loci: 2668 192s Number of SNPs: 774 (29.01%) 192s Number of heterozygous SNPs: 774 (100.00%) 192s Chromosome: 1 192s Segmenting DH signals... 192s Segmenting by CBS... 192s Chromosome: 1 192s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 192s Segmenting by CBS...done 192s List of 4 192s $ data :'data.frame': 2668 obs. of 4 variables: 192s ..$ chromosome: int [1:2668] 1 1 1 1 1 1 1 1 1 1 ... 192s ..$ x : num [1:2668] 1.44e+08 1.44e+08 1.44e+08 1.44e+08 1.44e+08 ... 192s ..$ y : num [1:2668] NA NA NA NA NA NA NA NA NA NA ... 192s ..$ index : int [1:2668] 1 2 3 4 5 6 7 8 9 10 ... 192s $ output :'data.frame': 1 obs. of 6 variables: 192s ..$ sampleName: chr NA 192s ..$ chromosome: int 1 192s ..$ start : num 1.44e+08 192s ..$ end : num 1.85e+08 192s ..$ nbrOfLoci : int 774 192s ..$ mean : num 0.154 192s $ segRows:'data.frame': 1 obs. of 2 variables: 192s ..$ startRow: int 15 192s ..$ endRow : int 2664 192s $ params :List of 5 192s ..$ alpha : num 0.001 192s ..$ undo : num 0 192s ..$ joinSegments : logi TRUE 192s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 192s .. ..$ chromosome: int 1 192s .. ..$ start : num 1.44e+08 192s .. ..$ end : num 1.85e+08 192s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 192s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 192s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.005 0 0.006 0 0 192s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 192s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 192s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 192s DH segmentation (locally-indexed) rows: 192s startRow endRow 192s 1 15 2664 192s int [1:2668] 7600 7601 7602 7603 7604 7605 7606 7607 7608 7609 ... 192s DH segmentation rows: 192s startRow endRow 192s 1 7614 10263 192s Segmenting DH signals...done 192s DH segmentation table: 192s dhStart dhEnd dhNbrOfLoci dhMean 192s 1 143926517 185449813 774 0.1542 192s startRow endRow 192s 1 7614 10263 192s Rows: 192s [1] 2 192s TCN segmentation rows: 192s startRow endRow 192s 2 7600 10267 192s TCN and DH segmentation rows: 192s startRow endRow 192s 2 7600 10267 192s startRow endRow 192s 1 7614 10263 192s startRow endRow 192s 1 1 7599 192s TCN segmentation (expanded) rows: 192s startRow endRow 192s 1 1 7599 192s 2 7600 10267 192s TCN and DH segmentation rows: 192s startRow endRow 192s 1 1 7599 192s 2 7600 10267 192s 3 10268 14658 192s startRow endRow 192s 1 10 7594 192s 2 7614 10263 192s startRow endRow 192s 1 1 7599 192s 2 7600 10267 192s Total CN segmentation table (expanded): 192s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 192s 2 1 143926517 185449813 2668 2.0704 774 774 192s (TCN,DH) segmentation for one total CN segment: 192s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 192s 2 2 1 1 143926517 185449813 2668 2.0704 774 192s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 192s 2 774 143926517 185449813 774 0.1542 192s Total CN segment #2 ([1.43927e+08,1.8545e+08]) of 3...done 192s Total CN segment #3 ([1.8545e+08,2.47137e+08]) of 3... 192s Number of TCN loci in segment: 4391 192s Locus data for TCN segment: 192s 'data.frame': 4391 obs. of 8 variables: 192s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 192s $ x : num 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 192s $ CT : num 2.93 2.15 2.82 2.93 2.46 ... 192s $ betaT : num 0.0811 0.5154 0.9473 0.3734 0.7506 ... 192s $ betaTN : num 0.0811 0.5154 0.9473 0.3734 0.7506 ... 192s $ muN : num 0 0.5 1 0.5 1 1 0 1 0 1 ... 192s $ index : int 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 192s $ rho : num NA 0.0308 NA 0.2533 NA ... 192s Number of loci: 4391 192s Number of SNPs: 1311 (29.86%) 192s Number of heterozygous SNPs: 1311 (100.00%) 192s Chromosome: 1 192s Segmenting DH signals... 192s Segmenting by CBS... 192s Chromosome: 1 192s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 192s Segmenting by CBS...done 192s List of 4 192s $ data :'data.frame': 4391 obs. of 4 variables: 192s ..$ chromosome: int [1:4391] 1 1 1 1 1 1 1 1 1 1 ... 192s ..$ x : num [1:4391] 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 192s ..$ y : num [1:4391] NA 0.0308 NA 0.2533 NA ... 192s ..$ index : int [1:4391] 1 2 3 4 5 6 7 8 9 10 ... 192s $ output :'data.frame': 1 obs. of 6 variables: 192s ..$ sampleName: chr NA 192s ..$ chromosome: int 1 192s ..$ start : num 1.85e+08 192s ..$ end : num 2.47e+08 192s ..$ nbrOfLoci : int 1311 192s ..$ mean : num 0.251 192s $ segRows:'data.frame': 1 obs. of 2 variables: 192s ..$ startRow: int 2 192s ..$ endRow : int 4388 192s $ params :List of 5 192s ..$ alpha : num 0.001 192s ..$ undo : num 0 192s ..$ joinSegments : logi TRUE 192s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 192s .. ..$ chromosome: int 1 192s .. ..$ start : num 1.85e+08 192s .. ..$ end : num 2.47e+08 192s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 192s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 192s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.012 0 0.013 0 0 192s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 192s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 192s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 192s DH segmentation (locally-indexed) rows: 192s startRow endRow 192s 1 2 4388 192s int [1:4391] 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 192s DH segmentation rows: 192s startRow endRow 192s 1 10269 14655 192s Segmenting DH signals...done 192s DH segmentation table: 192s dhStart dhEnd dhNbrOfLoci dhMean 192s 1 185449813 247137334 1311 0.2512 192s startRow endRow 192s 1 10269 14655 192s Rows: 192s [1] 3 192s TCN segmentation rows: 192s startRow endRow 192s 3 10268 14658 192s TCN and DH segmentation rows: 192s startRow endRow 192s 3 10268 14658 192s startRow endRow 192s 1 10269 14655 192s startRow endRow 192s 1 1 7599 192s 2 7600 10267 192s TCN segmentation (expanded) rows: 192s startRow endRow 192s 1 1 7599 192s 2 7600 10267 192s 3 10268 14658 192s TCN and DH segmentation rows: 192s startRow endRow 192s 1 1 7599 192s 2 7600 10267 192s 3 10268 14658 192s startRow endRow 192s 1 10 7594 192s 2 7614 10263 192s 3 10269 14655 192s startRow endRow 192s 1 1 7599 192s 2 7600 10267 192s 3 10268 14658 192s Total CN segmentation table (expanded): 192s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 192s 3 1 185449813 247137334 4391 2.6341 1311 1311 192s (TCN,DH) segmentation for one total CN segment: 192s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 192s 3 3 1 1 185449813 247137334 4391 2.6341 1311 192s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 192s 3 1311 185449813 247137334 1311 0.2512 192s Total CN segment #3 ([1.8545e+08,2.47137e+08]) of 3...done 192s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 192s 1 1 1 1 554484 143926517 7599 1.3859 2111 192s 2 1 2 1 143926517 185449813 2668 2.0704 774 192s 3 1 3 1 185449813 247137334 4391 2.6341 1311 192s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 192s 1 2111 554484 143926517 2111 0.5237 192s 2 774 143926517 185449813 774 0.1542 192s 3 1311 185449813 247137334 1311 0.2512 192s Calculating (C1,C2) per segment... 192s Calculating (C1,C2) per segment...done 192s Number of segments: 3 192s Segmenting paired tumor-normal signals using Paired PSCBS...done 192s Post-segmenting TCNs... 192s Number of segments: 3 192s Number of chromosomes: 1 192s [1] 1 192s Chromosome 1 ('chr01') of 1... 192s Rows: 192s [1] 1 2 3 192s Number of segments: 3 192s TCN segment #1 ('1') of 3... 192s Nothing todo. Only one DH segmentation. Skipping. 192s TCN segment #1 ('1') of 3...done 192s TCN segment #2 ('2') of 3... 192s Nothing todo. Only one DH segmentation. Skipping. 192s TCN segment #2 ('2') of 3...done 192s TCN segment #3 ('3') of 3... 192s Nothing todo. Only one DH segmentation. Skipping. 192s TCN segment #3 ('3') of 3...done 192s Chromosome 1 ('chr01') of 1...done 192s Update (C1,C2) per segment... 192s Update (C1,C2) per segment...done 192s Post-segmenting TCNs...done 192s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 192s 1 1 1 1 554484 143926517 7599 1.3859 2111 192s 2 1 2 1 143926517 185449813 2668 2.0704 774 192s 3 1 3 1 185449813 247137334 4391 2.6341 1311 192s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 192s 1 2111 554484 143926517 2111 0.5237 0.3300521 1.055848 192s 2 774 143926517 185449813 774 0.1542 0.8755722 1.194828 192s 3 1311 185449813 247137334 1311 0.2512 0.9862070 1.647893 192s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 192s 1 1 1 1 554484 143926517 7599 1.3859 2111 192s 2 1 2 1 143926517 185449813 2668 2.0704 774 192s 3 1 3 1 185449813 247137334 4391 2.6341 1311 192s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 192s 1 2111 554484 143926517 2111 0.5237 0.3300521 1.055848 192s 2 774 143926517 185449813 774 0.1542 0.8755722 1.194828 192s 3 1311 185449813 247137334 1311 0.2512 0.9862070 1.647893 192s > print(fit) 192s chromosome tcnId dhId start end tcnNbrOfLoci tcnMean tcnNbrOfSNPs 192s 1 1 1 1 554484 143926517 7599 1.3859 2111 192s 2 1 2 1 143926517 185449813 2668 2.0704 774 192s 3 1 3 1 185449813 247137334 4391 2.6341 1311 192s tcnNbrOfHets dhNbrOfLoci dhMean c1Mean c2Mean 192s 1 2111 2111 0.5237 0.3300521 1.055848 192s 2 774 774 0.1542 0.8755722 1.194828 192s 3 1311 1311 0.2512 0.9862070 1.647893 192s > 192s > # Plot results 192s > plotTracks(fit) 192s > 192s > # Sanity check 192s > stopifnot(nbrOfSegments(fit) == nSegs) 192s > 192s > 192s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 192s > # Bootstrap segment level estimates 192s > # (used by the AB caller, which, if skipped here, 192s > # will do it automatically) 192s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 192s > fit <- bootstrapTCNandDHByRegion(fit, B=B, verbose=-10) 192s Resample (TCN,DH) signals and re-estimate summaries for segment & changepoint... 192s Already done? 192s tcn_2.5% tcn_5% tcn_95% tcn_97.5% dh_2.5% dh_5% dh_95% dh_97.5% 192s FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE 192s c1_2.5% c1_5% c1_95% c1_97.5% c2_2.5% c2_5% c2_95% c2_97.5% 192s FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE 192s Bootstrapping (TCN,DH,C1,C2) segment mean levels... 192s Identifying heterozygous & homozygous SNPs and non-polymorphic loci... 192s Number of loci: 14658 192s Number of SNPs: 4196 192s Number of non-SNPs: 10462 192s Identifying heterozygous & homozygous SNPs and non-polymorphic loci...done 192s num [1:3, 1:100, 1:4] NA NA NA NA NA NA NA NA NA NA ... 192s - attr(*, "dimnames")=List of 3 192s ..$ : NULL 192s ..$ : NULL 192s ..$ : chr [1:4] "tcn" "dh" "c1" "c2" 192s Segment #1 (chr 1, tcnId=1, dhId=1) of 3... 192s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 192s 1 1 1 1 554484 143926517 7599 1.3859 2111 192s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 192s 1 2111 554484 143926517 2111 0.5237 0.3300521 1.055848 192s Number of TCNs: 7599 192s Number of DHs: 2111 192s int [1:7599] 1 2 3 4 5 6 7 8 9 10 ... 192s int [1:14658] 1 2 3 4 5 6 7 8 9 10 ... 192s int [1:7599] 1 2 3 4 5 6 7 8 9 10 ... 192s Identify loci used to bootstrap DH means... 192s Heterozygous SNPs to resample for DH: 192s int [1:2111] 10 12 24 28 31 33 34 39 46 48 ... 192s Identify loci used to bootstrap DH means...done 192s Identify loci used to bootstrap TCN means... 192s SNPs: 192s int [1:2111] 10 12 24 28 31 33 34 39 46 48 ... 192s Non-polymorphic loci: 192s int [1:5488] 1 2 3 4 5 6 7 8 9 11 ... 192s Heterozygous SNPs to resample for TCN: 192s int [1:2111] 10 12 24 28 31 33 34 39 46 48 ... 192s Homozygous SNPs to resample for TCN: 192s int(0) 192s Non-polymorphic loci to resample for TCN: 192s int [1:5488] 1 2 3 4 5 6 7 8 9 11 ... 192s Heterozygous SNPs with non-DH to resample for TCN: 192s int(0) 192s Loci to resample for TCN: 192s int [1:7599] 1 2 3 4 5 6 7 8 9 10 ... 192s Identify loci used to bootstrap TCN means...done 192s Number of (#hets, #homs, #nonSNPs): (2111,0,5488) 192s Bootstrapping while preserving (#hets, #homs, #nonSNPs)... 192s Number of bootstrap samples: 100 192s Bootstrapping while preserving (#hets, #homs, #nonSNPs)...done 192s Segment #1 (chr 1, tcnId=1, dhId=1) of 3...done 192s Segment #2 (chr 1, tcnId=2, dhId=1) of 3... 192s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 192s 2 1 2 1 143926517 185449813 2668 2.0704 774 192s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 192s 2 774 143926517 185449813 774 0.1542 0.8755722 1.194828 192s Number of TCNs: 2668 192s Number of DHs: 774 192s int [1:2668] 7600 7601 7602 7603 7604 7605 7606 7607 7608 7609 ... 192s int [1:14658] 1 2 3 4 5 6 7 8 9 10 ... 192s int [1:2668] 7600 7601 7602 7603 7604 7605 7606 7607 7608 7609 ... 192s Identify loci used to bootstrap DH means... 192s Heterozygous SNPs to resample for DH: 192s int [1:774] 7614 7616 7626 7627 7628 7635 7638 7639 7640 7642 ... 192s Identify loci used to bootstrap DH means...done 192s Identify loci used to bootstrap TCN means... 192s SNPs: 192s int [1:774] 7614 7616 7626 7627 7628 7635 7638 7639 7640 7642 ... 192s Non-polymorphic loci: 192s int [1:1894] 7600 7601 7602 7603 7604 7605 7606 7607 7608 7609 ... 192s Heterozygous SNPs to resample for TCN: 192s int [1:774] 7614 7616 7626 7627 7628 7635 7638 7639 7640 7642 ... 192s Homozygous SNPs to resample for TCN: 192s int(0) 192s Non-polymorphic loci to resample for TCN: 192s int [1:1894] 7600 7601 7602 7603 7604 7605 7606 7607 7608 7609 ... 192s Heterozygous SNPs with non-DH to resample for TCN: 192s int(0) 192s Loci to resample for TCN: 192s int [1:2668] 7600 7601 7602 7603 7604 7605 7606 7607 7608 7609 ... 192s Identify loci used to bootstrap TCN means...done 192s Number of (#hets, #homs, #nonSNPs): (774,0,1894) 192s Bootstrapping while preserving (#hets, #homs, #nonSNPs)... 192s Number of bootstrap samples: 100 192s Bootstrapping while preserving (#hets, #homs, #nonSNPs)...done 192s Segment #2 (chr 1, tcnId=2, dhId=1) of 3...done 192s Segment #3 (chr 1, tcnId=3, dhId=1) of 3... 192s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 192s 3 1 3 1 185449813 247137334 4391 2.6341 1311 192s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 192s 3 1311 185449813 247137334 1311 0.2512 0.986207 1.647893 192s Number of TCNs: 4391 192s Number of DHs: 1311 192s int [1:4391] 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 192s int [1:14658] 1 2 3 4 5 6 7 8 9 10 ... 192s int [1:4391] 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 192s Identify loci used to bootstrap DH means... 192s Heterozygous SNPs to resample for DH: 192s int [1:1311] 10269 10271 10281 10282 10283 10293 10295 10297 10300 10302 ... 192s Identify loci used to bootstrap DH means...done 192s Identify loci used to bootstrap TCN means... 192s SNPs: 192s int [1:1311] 10269 10271 10281 10282 10283 10293 10295 10297 10300 10302 ... 192s Non-polymorphic loci: 192s int [1:3080] 10268 10270 10272 10273 10274 10275 10276 10277 10278 10279 ... 192s Heterozygous SNPs to resample for TCN: 192s int [1:1311] 10269 10271 10281 10282 10283 10293 10295 10297 10300 10302 ... 192s Homozygous SNPs to resample for TCN: 192s int(0) 192s Non-polymorphic loci to resample for TCN: 192s int [1:3080] 10268 10270 10272 10273 10274 10275 10276 10277 10278 10279 ... 192s Heterozygous SNPs with non-DH to resample for TCN: 192s int(0) 192s Loci to resample for TCN: 192s int [1:4391] 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 192s Identify loci used to bootstrap TCN means...done 192s Number of (#hets, #homs, #nonSNPs): (1311,0,3080) 192s Bootstrapping while preserving (#hets, #homs, #nonSNPs)... 192s Number of bootstrap samples: 100 192s Bootstrapping while preserving (#hets, #homs, #nonSNPs)...done 192s Segment #3 (chr 1, tcnId=3, dhId=1) of 3...done 192s Bootstrapped segment mean levels 192s num [1:3, 1:100, 1:4] 1.38 2.08 2.63 1.38 2.07 ... 192s - attr(*, "dimnames")=List of 3 192s ..$ : NULL 192s ..$ : NULL 192s ..$ : chr [1:4] "tcn" "dh" "c1" "c2" 192s Calculating (C1,C2) mean levels from (TCN,DH) mean levels... 192s num [1:3, 1:100, 1:4] 1.38 2.08 2.63 1.38 2.07 ... 192s - attr(*, "dimnames")=List of 3 192s ..$ : NULL 192s ..$ : NULL 192s ..$ : chr [1:4] "tcn" "dh" "c1" "c2" 192s Calculating (C1,C2) mean levels from (TCN,DH) mean levels...done 192s Calculating polar (alpha,radius,manhattan) for change points... 192s num [1:2, 1:100, 1:2] -0.5588 -0.0962 -0.5365 -0.1285 -0.5378 ... 192s - attr(*, "dimnames")=List of 3 192s ..$ : NULL 192s ..$ : NULL 192s ..$ : chr [1:2] "c1" "c2" 192s Bootstrapped change points 192s num [1:2, 1:100, 1:5] -2.89 -1.78 -2.87 -1.86 -2.88 ... 192s - attr(*, "dimnames")=List of 3 192s ..$ : NULL 192s ..$ : NULL 192s ..$ : chr [1:5] "alpha" "radius" "manhattan" "d1" ... 192s Calculating polar (alpha,radius,manhattan) for change points...done 192s Bootstrapping (TCN,DH,C1,C2) segment mean levels...done 192s Summarizing bootstrapped segment ('tcn', 'dh', 'c1', 'c2') data... 192s num [1:3, 1:4, 1:4] NA NA NA NA NA NA NA NA NA NA ... 192s - attr(*, "dimnames")=List of 3 192s ..$ : NULL 192s ..$ : chr [1:4] "2.5%" "5%" "95%" "97.5%" 192s ..$ : chr [1:4] "tcn" "dh" "c1" "c2" 192s Field #1 ('tcn') of 4... 192s Segment #1 of 3... 192s Segment #1 of 3...done 192s Segment #2 of 3... 192s Segment #2 of 3...done 192s Segment #3 of 3... 192s Segment #3 of 3...done 192s Field #1 ('tcn') of 4...done 192s Field #2 ('dh') of 4... 192s Segment #1 of 3... 192s Segment #1 of 3...done 192s Segment #2 of 3... 192s Segment #2 of 3...done 192s Segment #3 of 3... 192s Segment #3 of 3...done 192s Field #2 ('dh') of 4...done 192s Field #3 ('c1') of 4... 192s Segment #1 of 3... 192s Segment #1 of 3...done 192s Segment #2 of 3... 192s Segment #2 of 3...done 192s Segment #3 of 3... 192s Segment #3 of 3...done 192s Field #3 ('c1') of 4...done 192s Field #4 ('c2') of 4... 192s Segment #1 of 3... 192s Segment #1 of 3...done 192s Segment #2 of 3... 192s Segment #2 of 3...done 192s Segment #3 of 3... 192s Segment #3 of 3...done 192s Field #4 ('c2') of 4...done 192s Bootstrap statistics 192s num [1:3, 1:4, 1:4] 1.38 2.06 2.62 1.38 2.06 ... 192s - attr(*, "dimnames")=List of 3 192s ..$ : NULL 192s ..$ : chr [1:4] "2.5%" "5%" "95%" "97.5%" 192s ..$ : chr [1:4] "tcn" "dh" "c1" "c2" 192s Statistical sanity checks (iff B >= 100)... 192s Available summaries: 2.5%, 5%, 95%, 97.5% 192s Available quantiles: 0.025, 0.05, 0.95, 0.975 192s num [1:3, 1:4, 1:4] 1.38 2.06 2.62 1.38 2.06 ... 192s - attr(*, "dimnames")=List of 3 192s ..$ : NULL 192s ..$ : chr [1:4] "2.5%" "5%" "95%" "97.5%" 192s ..$ : chr [1:4] "tcn" "dh" "c1" "c2" 192s Field #1 ('tcn') of 4... 192s Seg 1. mean=1.3859, range=[1.38092,1.3949], n=7599 192s Seg 2. mean=2.0704, range=[2.05747,2.08326], n=2668 192s Seg 3. mean=2.6341, range=[2.62068,2.64694], n=4391 192s Field #1 ('tcn') of 4...done 192s Field #2 ('dh') of 4... 192s Seg 1. mean=0.5237, range=[0.51753,0.532002], n=2111 192s Seg 2. mean=0.1542, range=[0.144468,0.16453], n=774 192s Seg 3. mean=0.2512, range=[0.242575,0.258832], n=1311 192s Field #2 ('dh') of 4...done 192s Field #3 ('c1') of 4... 192s Seg 1. mean=0.330052, range=[0.323996,0.336038], n=2111 192s Seg 2. mean=0.875572, range=[0.86318,0.887699], n=774 192s Seg 3. mean=0.986207, range=[0.975123,0.998982], n=1311 192s Field #3 ('c1') of 4...done 192s Field #4 ('c2') of 4... 192s Seg 1. mean=1.05585, range=[1.05006,1.06231], n=2111 192s Seg 2. mean=1.19483, range=[1.18417,1.2081], n=774 192s Seg 3. mean=1.64789, range=[1.63403,1.66098], n=1311 192s Field #4 ('c2') of 4...done 192s Statistical sanity checks (iff B >= 100)...done 192s Summarizing bootstrapped segment ('tcn', 'dh', 'c1', 'c2') data...done 192s Summarizing bootstrapped changepoint ('alpha', 'radius', 'manhattan', 'd1', 'd2') data... 192s num [1:2, 1:4, 1:5] NA NA NA NA NA NA NA NA NA NA ... 192s - attr(*, "dimnames")=List of 3 192s ..$ : NULL 192s ..$ : chr [1:4] "2.5%" "5%" "95%" "97.5%" 192s ..$ : chr [1:5] "alpha" "radius" "manhattan" "d1" ... 192s Field #1 ('alpha') of 5... 192s Changepoint #1 of 2... 192s Changepoint #1 of 2...done 192s Changepoint #2 of 2... 192s Changepoint #2 of 2...done 192s Field #1 ('alpha') of 5...done 192s Field #2 ('radius') of 5... 192s Changepoint #1 of 2... 192s Changepoint #1 of 2...done 192s Changepoint #2 of 2... 192s Changepoint #2 of 2...done 192s Field #2 ('radius') of 5...done 192s Field #3 ('manhattan') of 5... 192s Changepoint #1 of 2... 192s Changepoint #1 of 2...done 192s Changepoint #2 of 2... 192s Changepoint #2 of 2...done 192s Field #3 ('manhattan') of 5...done 192s Field #4 ('d1') of 5... 192s Changepoint #1 of 2... 192s Changepoint #1 of 2...done 192s Changepoint #2 of 2... 192s Changepoint #2 of 2...done 192s Field #4 ('d1') of 5...done 192s Field #5 ('d2') of 5... 192s Changepoint #1 of 2... 192s Changepoint #1 of 2...done 192s Changepoint #2 of 2... 192s Changepoint #2 of 2...done 192s Field #5 ('d2') of 5...done 192s Bootstrap statistics 192s num [1:2, 1:4, 1:5] -2.92 -1.86 -2.91 -1.85 -2.87 ... 192s - attr(*, "dimnames")=List of 3 192s ..$ : NULL 192s ..$ : chr [1:4] "2.5%" "5%" "95%" "97.5%" 192s ..$ : chr [1:5] "alpha" "radius" "manhattan" "d1" ... 192s Summarizing bootstrapped changepoint ('alpha', 'radius', 'manhattan', 'd1', 'd2') data...done 192s Resample (TCN,DH) signals and re-estimate summaries for segment & changepoint...done 192s > print(fit) 192s chromosome tcnId dhId start end tcnNbrOfLoci tcnMean tcnNbrOfSNPs 192s 1 1 1 1 554484 143926517 7599 1.3859 2111 192s 2 1 2 1 143926517 185449813 2668 2.0704 774 192s 3 1 3 1 185449813 247137334 4391 2.6341 1311 192s tcnNbrOfHets dhNbrOfLoci dhMean c1Mean c2Mean 192s 1 2111 2111 0.5237 0.3300521 1.055848 192s 2 774 774 0.1542 0.8755722 1.194828 192s 3 1311 1311 0.2512 0.9862070 1.647893 192s > plotTracks(fit) 192s > 192s > 192s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 192s > # Calling segments in allelic balance (AB) and 192s > # in loss-of-heterozygosity (LOH) 192s > # NOTE: Ideally, this should be done on whole-genome data 192s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 192s > fit <- callAB(fit, verbose=-10) 192s Calling segments of allelic balance from one-sided DH bootstrap confidence intervals... 192s delta (offset adjusting for bias in DH): 0.3466649145302 192s alpha (CI quantile; significance level): 0.05 192s Calling segments... 192s Number of segments called allelic balance (AB): 2 (66.67%) of 3 192s Calling segments...done 192s Calling segments of allelic balance from one-sided DH bootstrap confidence intervals...done 192s > fit <- callLOH(fit, verbose=-10) 192s Calling segments of allelic balance from one-sided DH bootstrap confidence intervals... 192s delta (offset adjusting for bias in C1): 0.771236438183453 192s alpha (CI quantile; significance level): 0.05 192s Calling segments... 192s Number of segments called low C1 (LowC1, "LOH_C1"): 1 (33.33%) of 3 192s Calling segments...done 192s Calling segments of allelic balance from one-sided DH bootstrap confidence intervals...done 192s > print(fit) 192s chromosome tcnId dhId start end tcnNbrOfLoci tcnMean tcnNbrOfSNPs 192s 1 1 1 1 554484 143926517 7599 1.3859 2111 192s 2 1 2 1 143926517 185449813 2668 2.0704 774 192s 3 1 3 1 185449813 247137334 4391 2.6341 1311 192s tcnNbrOfHets dhNbrOfLoci dhMean c1Mean c2Mean abCall lohCall 192s 1 2111 2111 0.5237 0.3300521 1.055848 FALSE TRUE 192s 2 774 774 0.1542 0.8755722 1.194828 TRUE FALSE 192s 3 1311 1311 0.2512 0.9862070 1.647893 TRUE FALSE 192s > plotTracks(fit) 192s > 192s > proc.time() 192s user system elapsed 192s 1.359 0.065 1.422 192s Test segmentByPairedPSCBS,noNormalBAFs passed 192s 0 192s Begin test segmentByPairedPSCBS,report 192s + [ 0 != 0 ] 192s + echo Test segmentByPairedPSCBS,noNormalBAFs passed 192s + echo 0 192s + echo Begin test segmentByPairedPSCBS,report 192s + exitcode=0 192s + R CMD BATCH segmentByPairedPSCBS,report.R 193s + cat segmentByPairedPSCBS,report.Rout 193s 193s R version 4.5.2 (2025-10-31) -- "[Not] Part in a Rumble" 193s Copyright (C) 2025 The R Foundation for Statistical Computing 193s Platform: x86_64-pc-linux-gnu 193s 193s R is free software and comes with ABSOLUTELY NO WARRANTY. 193s You are welcome to redistribute it under certain conditions. 193s Type 'license()' or 'licence()' for distribution details. 193s 193s R is a collaborative project with many contributors. 193s Type 'contributors()' for more information and 193s 'citation()' on how to cite R or R packages in publications. 193s 193s Type 'demo()' for some demos, 'help()' for on-line help, or 193s 'help.start()' for an HTML browser interface to help. 193s Type 'q()' to quit R. 193s 193s [Previously saved workspace restored] 193s 193s > # This test script calls a report generator which requires 193s > # the 'ggplot2' package, which in turn will require packages 193s > # 'colorspace', 'dichromat', 'munsell', 'reshape2' and 'scales'. 193s > 193s > # Only run this test in full testing mode 193s > if (Sys.getenv("_R_CHECK_FULL_") != "") { 193s + library("PSCBS") 193s + 193s + # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 193s + # Load SNP microarray data 193s + # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 193s + data <- PSCBS::exampleData("paired.chr01") 193s + str(data) 193s + 193s + 193s + # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 193s + # Paired PSCBS segmentation 193s + # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 193s + # Drop single-locus outliers 193s + dataS <- dropSegmentationOutliers(data) 193s + 193s + # Speed up example by segmenting fewer loci 193s + dataS <- dataS[seq(from=1, to=nrow(data), by=5),] 193s + 193s + str(dataS) 193s + 193s + gaps <- findLargeGaps(dataS, minLength=2e6) 193s + knownSegments <- gapsToSegments(gaps) 193s + 193s + # Paired PSCBS segmentation 193s + fit <- segmentByPairedPSCBS(dataS, knownSegments=knownSegments, 193s + seed=0xBEEF, verbose=-10) 193s + 193s + # Fake a multi-chromosome segmentation 193s + fit1 <- fit 193s + fit2 <- renameChromosomes(fit, from=1, to=2) 193s + fit <- c(fit1, fit2) 193s + 193s + report(fit, sampleName="PairedPSCBS", studyName="PSCBS-Ex", verbose=-10) 193s + 193s + } # if (Sys.getenv("_R_CHECK_FULL_")) 193s > 193s > proc.time() 193s user system elapsed 193s 0.196 0.021 0.210 193s + [ 0 != 0 ] 193s + echo Test segmentByPairedPSCBS,report passed 193s + echo 0 193s + echo Begin test segmentByPairedPSCBS,seqOfSegmentsByDP 193s + exitcode=0 193s + R CMD BATCH segmentByPairedPSCBS,seqOfSegmentsByDP.R 193s Test segmentByPairedPSCBS,report passed 193s 0 193s Begin test segmentByPairedPSCBS,seqOfSegmentsByDP 196s + cat segmentByPairedPSCBS,seqOfSegmentsByDP.Rout 196s 196s R version 4.5.2 (2025-10-31) -- "[Not] Part in a Rumble" 196s Copyright (C) 2025 The R Foundation for Statistical Computing 196s Platform: x86_64-pc-linux-gnu 196s 196s R is free software and comes with ABSOLUTELY NO WARRANTY. 196s You are welcome to redistribute it under certain conditions. 196s Type 'license()' or 'licence()' for distribution details. 196s 196s R is a collaborative project with many contributors. 196s Type 'contributors()' for more information and 196s 'citation()' on how to cite R or R packages in publications. 196s 196s Type 'demo()' for some demos, 'help()' for on-line help, or 196s 'help.start()' for an HTML browser interface to help. 196s Type 'q()' to quit R. 196s 196s [Previously saved workspace restored] 196s 196s > library("PSCBS") 196s PSCBS v0.68.0 (2025-04-18 19:40:02 UTC) successfully loaded. See ?PSCBS for help. 196s > subplots <- R.utils::subplots 196s > stext <- R.utils::stext 196s > 196s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 196s > # Load SNP microarray data 196s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 196s > data <- PSCBS::exampleData("paired.chr01") 196s > str(data) 196s 'data.frame': 73346 obs. of 6 variables: 196s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 196s $ x : int 1145994 2224111 2319424 2543484 2926730 2941694 3084986 3155127 3292731 3695086 ... 196s $ CT : num 1.625 1.071 1.406 1.18 0.856 ... 196s $ betaT : num 0.757 0.771 0.834 0.778 0.229 ... 196s $ CN : num 2.36 2.13 2.59 1.93 1.71 ... 196s $ betaN : num 0.827 0.875 0.887 0.884 0.103 ... 196s > 196s > 196s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 196s > # Paired PSCBS segmentation 196s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 196s > # Drop single-locus outliers 196s > dataS <- dropSegmentationOutliers(data) 196s > 196s > # Run light-weight tests by default 196s > if (Sys.getenv("_R_CHECK_FULL_") == "") { 196s + # Use only every 5th data point 196s + dataS <- dataS[seq(from=1, to=nrow(data), by=5),] 196s + # Number of segments (for assertion) 196s + nSegs <- 3L 196s + # Number of bootstrap samples (see below) 196s + B <- 100L 196s + } else { 196s + # Full tests 196s + nSegs <- 12L 196s + B <- 1000L 196s + } 196s > 196s > str(dataS) 196s 'data.frame': 14670 obs. of 6 variables: 196s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 196s $ x : int 1145994 2941694 3710825 4240737 4276892 4464544 4714611 5095111 5034491 5158416 ... 196s $ CT : num 1.63 1.4 1.41 1.17 1.16 ... 196s $ betaT : num 0.7574 0.169 0.2357 0.2604 0.0576 ... 196s $ CN : num 2.36 2.13 2.26 2.01 2.32 ... 196s $ betaN : num 0.8274 0.5072 0.1671 0.1609 0.0421 ... 196s > 196s > R.oo::attachLocally(dataS) 196s > 196s > 196s > gaps <- findLargeGaps(dataS, minLength=2e6) 196s > knownSegments <- gapsToSegments(gaps, dropGaps=TRUE) 196s > 196s > # Paired PSCBS segmentation 196s > fit <- segmentByPairedPSCBS(dataS, knownSegments=knownSegments, 196s + seed=0xBEEF, verbose=-10) 196s Segmenting paired tumor-normal signals using Paired PSCBS... 196s Calling genotypes from normal allele B fractions... 196s num [1:14670] 0.8274 0.5072 0.1671 0.1609 0.0421 ... 196s Called genotypes: 196s num [1:14670] 1 0.5 0 0 0 0 1 0 1 0.5 ... 196s - attr(*, "modelFit")=List of 1 196s ..$ :List of 7 196s .. ..$ flavor : chr "density" 196s .. ..$ cn : int 2 196s .. ..$ nbrOfGenotypeGroups: int 3 196s .. ..$ tau : num [1:2] 0.315 0.677 196s .. ..$ n : int 14640 196s .. ..$ fit :Classes 'PeaksAndValleys' and 'data.frame': 5 obs. of 3 variables: 196s .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 196s .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 196s .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 196s .. ..$ fitValleys :Classes 'PeaksAndValleys' and 'data.frame': 2 obs. of 3 variables: 196s .. .. ..$ type : chr [1:2] "valley" "valley" 196s .. .. ..$ x : num [1:2] 0.315 0.677 196s .. .. ..$ density: num [1:2] 0.522 0.551 196s ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 196s muN 196s 0 0.5 1 196s 5221 4198 5251 196s Calling genotypes from normal allele B fractions...done 196s Normalizing betaT using betaN (TumorBoost)... 196s Normalized BAFs: 196s num [1:14670] 0.9301 0.1667 0.0685 0.0995 0.0155 ... 196s - attr(*, "modelFit")=List of 5 196s ..$ method : chr "normalizeTumorBoost" 196s ..$ flavor : chr "v4" 196s ..$ delta : num [1:14670] -0.17264 0.00239 0.1671 0.16085 0.04213 ... 196s .. ..- attr(*, "modelFit")=List of 1 196s .. .. ..$ :List of 7 196s .. .. .. ..$ flavor : chr "density" 196s .. .. .. ..$ cn : int 2 196s .. .. .. ..$ nbrOfGenotypeGroups: int 3 196s .. .. .. ..$ tau : num [1:2] 0.315 0.677 196s .. .. .. ..$ n : int 14640 196s .. .. .. ..$ fit :Classes 'PeaksAndValleys' and 'data.frame': 5 obs. of 3 variables: 196s .. .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 196s .. .. .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 196s .. .. .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 196s .. .. .. ..$ fitValleys :Classes 'PeaksAndValleys' and 'data.frame': 2 obs. of 3 variables: 196s .. .. .. .. ..$ type : chr [1:2] "valley" "valley" 196s .. .. .. .. ..$ x : num [1:2] 0.315 0.677 196s .. .. .. .. ..$ density: num [1:2] 0.522 0.551 196s .. .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 196s ..$ preserveScale: logi FALSE 196s ..$ scaleFactor : num NA 196s Normalizing betaT using betaN (TumorBoost)...done 196s Setup up data... 196s 'data.frame': 14670 obs. of 7 variables: 196s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 196s $ x : num 1145994 2941694 3710825 4240737 4276892 ... 196s $ CT : num 1.63 1.4 1.41 1.17 1.16 ... 196s $ betaT : num 0.7574 0.169 0.2357 0.2604 0.0576 ... 196s $ betaTN : num 0.9301 0.1667 0.0685 0.0995 0.0155 ... 196s ..- attr(*, "modelFit")=List of 5 196s .. ..$ method : chr "normalizeTumorBoost" 196s .. ..$ flavor : chr "v4" 196s .. ..$ delta : num [1:14670] -0.17264 0.00239 0.1671 0.16085 0.04213 ... 196s .. .. ..- attr(*, "modelFit")=List of 1 196s .. .. .. ..$ :List of 7 196s .. .. .. .. ..$ flavor : chr "density" 196s .. .. .. .. ..$ cn : int 2 196s .. .. .. .. ..$ nbrOfGenotypeGroups: int 3 196s .. .. .. .. ..$ tau : num [1:2] 0.315 0.677 196s .. .. .. .. ..$ n : int 14640 196s .. .. .. .. ..$ fit :Classes 'PeaksAndValleys' and 'data.frame': 5 obs. of 3 variables: 196s .. .. .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 196s .. .. .. .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 196s .. .. .. .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 196s .. .. .. .. ..$ fitValleys :Classes 'PeaksAndValleys' and 'data.frame': 2 obs. of 3 variables: 196s .. .. .. .. .. ..$ type : chr [1:2] "valley" "valley" 196s .. .. .. .. .. ..$ x : num [1:2] 0.315 0.677 196s .. .. .. .. .. ..$ density: num [1:2] 0.522 0.551 196s .. .. .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 196s .. ..$ preserveScale: logi FALSE 196s .. ..$ scaleFactor : num NA 196s $ betaN : num 0.8274 0.5072 0.1671 0.1609 0.0421 ... 196s $ muN : num 1 0.5 0 0 0 0 1 0 1 0.5 ... 196s ..- attr(*, "modelFit")=List of 1 196s .. ..$ :List of 7 196s .. .. ..$ flavor : chr "density" 196s .. .. ..$ cn : int 2 196s .. .. ..$ nbrOfGenotypeGroups: int 3 196s .. .. ..$ tau : num [1:2] 0.315 0.677 196s .. .. ..$ n : int 14640 196s .. .. ..$ fit :Classes 'PeaksAndValleys' and 'data.frame': 5 obs. of 3 variables: 196s .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 196s .. .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 196s .. .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 196s .. .. ..$ fitValleys :Classes 'PeaksAndValleys' and 'data.frame': 2 obs. of 3 variables: 196s .. .. .. ..$ type : chr [1:2] "valley" "valley" 196s .. .. .. ..$ x : num [1:2] 0.315 0.677 196s .. .. .. ..$ density: num [1:2] 0.522 0.551 196s .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 196s Setup up data...done 196s Dropping loci for which TCNs are missing... 196s Number of loci dropped: 12 196s Dropping loci for which TCNs are missing...done 196s Ordering data along genome... 196s 'data.frame': 14658 obs. of 7 variables: 196s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 196s $ x : num 554484 730720 782343 878522 916294 ... 196s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 196s $ betaT : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 196s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 196s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 196s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 196s Ordering data along genome...done 196s Keeping only current chromosome for 'knownSegments'... 196s Chromosome: 1 196s Known segments for this chromosome: 196s chromosome start end length 196s 1 1 -Inf 120908858 Inf 196s 2 1 142693888 Inf Inf 196s Keeping only current chromosome for 'knownSegments'...done 196s alphaTCN: 0.009 196s alphaDH: 0.001 196s Number of loci: 14658 196s Calculating DHs... 196s Number of SNPs: 14658 196s Number of heterozygous SNPs: 4196 (28.63%) 196s Normalized DHs: 196s num [1:14658] NA NA NA NA NA ... 196s Calculating DHs...done 196s Random seed temporarily set (seed=c(48879), kind="L'Ecuyer-CMRG") 196s Produced 2 seeds from this stream for future usage 196s Identification of change points by total copy numbers... 196s Segmenting by CBS... 196s Chromosome: 1 196s Segmenting multiple segments on current chromosome... 196s Number of segments: 2 196s Random seed temporarily set (seed=c(10407, 1066287653, -51199871, 161854402, -1995183193, 1503453565, -747102133), kind="L'Ecuyer-CMRG") 196s Produced 2 seeds from this stream for future usage 196s Segmenting by CBS... 196s Chromosome: 1 196s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 196s Segmenting by CBS...done 196s Segmenting by CBS... 196s Chromosome: 1 196s Random seed temporarily set (seed=c(10407, -821273412, -52578226, 1415511586, 721384351, -665928286, 1316562960), kind="L'Ecuyer-CMRG") 196s Segmenting by CBS...done 196s Segmenting multiple segments on current chromosome...done 196s Segmenting by CBS...done 196s List of 4 196s $ data :'data.frame': 14658 obs. of 4 variables: 196s ..$ chromosome: int [1:14658] 1 1 1 1 1 1 1 1 1 1 ... 196s ..$ x : num [1:14658] 554484 730720 782343 878522 916294 ... 196s ..$ y : num [1:14658] 1.88 1.8 1.59 1.64 1.53 ... 196s ..$ index : int [1:14658] 1 2 3 4 5 6 7 8 9 10 ... 196s $ output :'data.frame': 3 obs. of 6 variables: 196s ..$ sampleName: chr [1:3] NA NA NA 196s ..$ chromosome: int [1:3] 1 1 1 196s ..$ start : num [1:3] 5.54e+05 1.43e+08 1.85e+08 196s ..$ end : num [1:3] 1.21e+08 1.85e+08 2.47e+08 196s ..$ nbrOfLoci : int [1:3] 7586 2681 4391 196s ..$ mean : num [1:3] 1.39 2.07 2.63 196s $ segRows:'data.frame': 3 obs. of 2 variables: 196s ..$ startRow: int [1:3] 1 7587 10268 196s ..$ endRow : int [1:3] 7586 10267 14658 196s $ params :List of 5 196s ..$ alpha : num 0.009 196s ..$ undo : num 0 196s ..$ joinSegments : logi TRUE 196s ..$ knownSegments:'data.frame': 2 obs. of 3 variables: 196s .. ..$ chromosome: int [1:2] 1 1 196s .. ..$ start : num [1:2] -Inf 1.43e+08 196s .. ..$ end : num [1:2] 1.21e+08 Inf 196s ..$ seed : int [1:7] 10407 1066287653 -51199871 161854402 -1995183193 1503453565 -747102133 196s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 196s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.086 0 0.086 0 0 196s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 196s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 196s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 196s Identification of change points by total copy numbers...done 196s Restructure TCN segmentation results... 196s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean 196s 1 1 554484 120908858 7586 1.3853 196s 2 1 142693888 185449813 2681 2.0689 196s 3 1 185449813 247137334 4391 2.6341 196s Number of TCN segments: 3 196s Restructure TCN segmentation results...done 196s Total CN segment #1 ([ 554484,1.20909e+08]) of 3... 196s Number of TCN loci in segment: 7586 196s Locus data for TCN segment: 196s 'data.frame': 7586 obs. of 9 variables: 196s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 196s $ x : num 554484 730720 782343 878522 916294 ... 196s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 196s $ betaT : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 196s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 196s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 196s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 196s $ index : int 1 2 3 4 5 6 7 8 9 10 ... 196s $ rho : num NA NA NA NA NA ... 196s Number of loci: 7586 196s Number of SNPs: 2108 (27.79%) 196s Number of heterozygous SNPs: 2108 (100.00%) 196s Chromosome: 1 196s Segmenting DH signals... 196s Segmenting by CBS... 196s Chromosome: 1 196s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 196s Segmenting by CBS...done 196s List of 4 196s $ data :'data.frame': 7586 obs. of 4 variables: 196s ..$ chromosome: int [1:7586] 1 1 1 1 1 1 1 1 1 1 ... 196s ..$ x : num [1:7586] 554484 730720 782343 878522 916294 ... 196s ..$ y : num [1:7586] NA NA NA NA NA ... 196s ..$ index : int [1:7586] 1 2 3 4 5 6 7 8 9 10 ... 196s $ output :'data.frame': 1 obs. of 6 variables: 196s ..$ sampleName: chr NA 196s ..$ chromosome: int 1 196s ..$ start : num 554484 196s ..$ end : num 1.21e+08 196s ..$ nbrOfLoci : int 2108 196s ..$ mean : num 0.512 196s $ segRows:'data.frame': 1 obs. of 2 variables: 196s ..$ startRow: int 10 196s ..$ endRow : int 7574 196s $ params :List of 5 196s ..$ alpha : num 0.001 196s ..$ undo : num 0 196s ..$ joinSegments : logi TRUE 196s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 196s .. ..$ chromosome: int 1 196s .. ..$ start : num 554484 196s .. ..$ end : num 1.21e+08 196s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 196s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 196s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.026 0 0.026 0 0 196s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 196s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 196s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 196s DH segmentation (locally-indexed) rows: 196s startRow endRow 196s 1 10 7574 196s int [1:7586] 1 2 3 4 5 6 7 8 9 10 ... 196s DH segmentation rows: 196s startRow endRow 196s 1 10 7574 196s Segmenting DH signals...done 196s DH segmentation table: 196s dhStart dhEnd dhNbrOfLoci dhMean 196s 1 554484 120908858 2108 0.5116 196s startRow endRow 196s 1 10 7574 196s Rows: 196s [1] 1 196s TCN segmentation rows: 196s startRow endRow 196s 1 1 7586 196s TCN and DH segmentation rows: 196s startRow endRow 196s 1 1 7586 196s startRow endRow 196s 1 10 7574 196s NULL 196s TCN segmentation (expanded) rows: 196s startRow endRow 196s 1 1 7586 196s TCN and DH segmentation rows: 196s startRow endRow 196s 1 1 7586 196s 2 7587 10267 196s 3 10268 14658 196s startRow endRow 196s 1 10 7574 196s startRow endRow 196s 1 1 7586 196s Total CN segmentation table (expanded): 196s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 196s 1 1 554484 120908858 7586 1.3853 2108 2108 196s (TCN,DH) segmentation for one total CN segment: 196s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 196s 1 1 1 1 554484 120908858 7586 1.3853 2108 196s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 196s 1 2108 554484 120908858 2108 0.5116 196s Total CN segment #1 ([ 554484,1.20909e+08]) of 3...done 196s Total CN segment #2 ([1.42694e+08,1.8545e+08]) of 3... 196s Number of TCN loci in segment: 2681 196s Locus data for TCN segment: 196s 'data.frame': 2681 obs. of 9 variables: 196s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 196s $ x : num 1.43e+08 1.43e+08 1.43e+08 1.43e+08 1.44e+08 ... 196s $ CT : num 2.27 1.55 1.47 1.5 1.81 ... 196s $ betaT : num 0.34 0.55 0.048 0.813 0.575 ... 196s $ betaTN : num 0.441 0.629 -0.05 0.958 0.872 ... 196s $ betaN : num 0.3851 0.3933 0.0981 0.8552 0.7028 ... 196s $ muN : num 0.5 0.5 0 1 1 1 1 0.5 1 1 ... 196s $ index : int 7587 7588 7589 7590 7591 7592 7593 7594 7595 7596 ... 196s $ rho : num 0.117 0.258 NA NA NA ... 196s Number of loci: 2681 196s Number of SNPs: 777 (28.98%) 196s Number of heterozygous SNPs: 777 (100.00%) 196s Chromosome: 1 196s Segmenting DH signals... 196s Segmenting by CBS... 196s Chromosome: 1 196s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 196s Segmenting by CBS...done 196s List of 4 196s $ data :'data.frame': 2681 obs. of 4 variables: 196s ..$ chromosome: int [1:2681] 1 1 1 1 1 1 1 1 1 1 ... 196s ..$ x : num [1:2681] 1.43e+08 1.43e+08 1.43e+08 1.43e+08 1.44e+08 ... 196s ..$ y : num [1:2681] 0.117 0.258 NA NA NA ... 196s ..$ index : int [1:2681] 1 2 3 4 5 6 7 8 9 10 ... 196s $ output :'data.frame': 1 obs. of 6 variables: 196s ..$ sampleName: chr NA 196s ..$ chromosome: int 1 196s ..$ start : num 1.43e+08 196s ..$ end : num 1.85e+08 196s ..$ nbrOfLoci : int 777 196s ..$ mean : num 0.0973 196s $ segRows:'data.frame': 1 obs. of 2 variables: 196s ..$ startRow: int 1 196s ..$ endRow : int 2677 196s $ params :List of 5 196s ..$ alpha : num 0.001 196s ..$ undo : num 0 196s ..$ joinSegments : logi TRUE 196s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 196s .. ..$ chromosome: int 1 196s .. ..$ start : num 1.43e+08 196s .. ..$ end : num 1.85e+08 196s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 196s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 196s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.005 0 0.005 0 0 196s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 196s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 196s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 196s DH segmentation (locally-indexed) rows: 196s startRow endRow 196s 1 1 2677 196s int [1:2681] 7587 7588 7589 7590 7591 7592 7593 7594 7595 7596 ... 196s DH segmentation rows: 196s startRow endRow 196s 1 7587 10263 196s Segmenting DH signals...done 196s DH segmentation table: 196s dhStart dhEnd dhNbrOfLoci dhMean 196s 1 142693888 185449813 777 0.0973 196s startRow endRow 196s 1 7587 10263 196s Rows: 196s [1] 2 196s TCN segmentation rows: 196s startRow endRow 196s 2 7587 10267 196s TCN and DH segmentation rows: 196s startRow endRow 196s 2 7587 10267 196s startRow endRow 196s 1 7587 10263 196s startRow endRow 196s 1 1 7586 196s TCN segmentation (expanded) rows: 196s startRow endRow 196s 1 1 7586 196s 2 7587 10267 196s TCN and DH segmentation rows: 196s startRow endRow 196s 1 1 7586 196s 2 7587 10267 196s 3 10268 14658 196s startRow endRow 196s 1 10 7574 196s 2 7587 10263 196s startRow endRow 196s 1 1 7586 196s 2 7587 10267 196s Total CN segmentation table (expanded): 196s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 196s 2 1 142693888 185449813 2681 2.0689 777 777 196s (TCN,DH) segmentation for one total CN segment: 196s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 196s 2 2 1 1 142693888 185449813 2681 2.0689 777 196s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 196s 2 777 142693888 185449813 777 0.0973 196s Total CN segment #2 ([1.42694e+08,1.8545e+08]) of 3...done 196s Total CN segment #3 ([1.8545e+08,2.47137e+08]) of 3... 196s Number of TCN loci in segment: 4391 196s Locus data for TCN segment: 196s 'data.frame': 4391 obs. of 9 variables: 196s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 196s $ x : num 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 196s $ CT : num 2.93 2.15 2.82 2.93 2.46 ... 196s $ betaT : num 0.0811 0.5154 0.9473 0.3734 0.7506 ... 196s $ betaTN : num -0.169 0.609 1.028 0.525 0.968 ... 196s $ betaN : num 0.25 0.38 0.919 0.34 0.783 ... 196s $ muN : num 0 0.5 1 0.5 1 1 0 1 0 1 ... 196s $ index : int 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 196s $ rho : num NA 0.2186 NA 0.0503 NA ... 196s Number of loci: 4391 196s Number of SNPs: 1311 (29.86%) 196s Number of heterozygous SNPs: 1311 (100.00%) 196s Chromosome: 1 196s Segmenting DH signals... 196s Segmenting by CBS... 196s Chromosome: 1 196s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 196s Segmenting by CBS...done 196s List of 4 196s $ data :'data.frame': 4391 obs. of 4 variables: 196s ..$ chromosome: int [1:4391] 1 1 1 1 1 1 1 1 1 1 ... 196s ..$ x : num [1:4391] 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 196s ..$ y : num [1:4391] NA 0.2186 NA 0.0503 NA ... 196s ..$ index : int [1:4391] 1 2 3 4 5 6 7 8 9 10 ... 196s $ output :'data.frame': 1 obs. of 6 variables: 196s ..$ sampleName: chr NA 196s ..$ chromosome: int 1 196s ..$ start : num 1.85e+08 196s ..$ end : num 2.47e+08 196s ..$ nbrOfLoci : int 1311 196s ..$ mean : num 0.23 196s $ segRows:'data.frame': 1 obs. of 2 variables: 196s ..$ startRow: int 2 196s ..$ endRow : int 4388 196s $ params :List of 5 196s ..$ alpha : num 0.001 196s ..$ undo : num 0 196s ..$ joinSegments : logi TRUE 196s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 196s .. ..$ chromosome: int 1 196s .. ..$ start : num 1.85e+08 196s .. ..$ end : num 2.47e+08 196s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 196s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 196s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.01 0 0.01 0 0 196s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 196s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 196s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 196s DH segmentation (locally-indexed) rows: 196s startRow endRow 196s 1 2 4388 196s int [1:4391] 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 196s DH segmentation rows: 196s startRow endRow 196s 1 10269 14655 196s Segmenting DH signals...done 196s DH segmentation table: 196s dhStart dhEnd dhNbrOfLoci dhMean 196s 1 185449813 247137334 1311 0.2295 196s startRow endRow 196s 1 10269 14655 196s Rows: 196s [1] 3 196s TCN segmentation rows: 196s startRow endRow 196s 3 10268 14658 196s TCN and DH segmentation rows: 196s startRow endRow 196s 3 10268 14658 196s startRow endRow 196s 1 10269 14655 196s startRow endRow 196s 1 1 7586 196s 2 7587 10267 196s TCN segmentation (expanded) rows: 196s startRow endRow 196s 1 1 7586 196s 2 7587 10267 196s 3 10268 14658 196s TCN and DH segmentation rows: 196s startRow endRow 196s 1 1 7586 196s 2 7587 10267 196s 3 10268 14658 196s startRow endRow 196s 1 10 7574 196s 2 7587 10263 196s 3 10269 14655 196s startRow endRow 196s 1 1 7586 196s 2 7587 10267 196s 3 10268 14658 196s Total CN segmentation table (expanded): 196s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 196s 3 1 185449813 247137334 4391 2.6341 1311 1311 196s (TCN,DH) segmentation for one total CN segment: 196s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 196s 3 3 1 1 185449813 247137334 4391 2.6341 1311 196s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 196s 3 1311 185449813 247137334 1311 0.2295 196s Total CN segment #3 ([1.8545e+08,2.47137e+08]) of 3...done 196s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 196s 1 1 1 1 554484 120908858 7586 1.3853 2108 196s 2 1 2 1 142693888 185449813 2681 2.0689 777 196s 3 1 3 1 185449813 247137334 4391 2.6341 1311 196s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 196s 1 2108 554484 120908858 2108 0.5116 196s 2 777 142693888 185449813 777 0.0973 196s 3 1311 185449813 247137334 1311 0.2295 196s Calculating (C1,C2) per segment... 196s Calculating (C1,C2) per segment...done 196s Number of segments: 3 196s Segmenting paired tumor-normal signals using Paired PSCBS...done 196s Post-segmenting TCNs... 196s Number of segments: 3 196s Number of chromosomes: 1 196s [1] 1 196s Chromosome 1 ('chr01') of 1... 196s Rows: 196s [1] 1 2 3 196s Number of segments: 3 196s TCN segment #1 ('1') of 3... 196s Nothing todo. Only one DH segmentation. Skipping. 196s TCN segment #1 ('1') of 3...done 196s TCN segment #2 ('2') of 3... 196s Nothing todo. Only one DH segmentation. Skipping. 196s TCN segment #2 ('2') of 3...done 196s TCN segment #3 ('3') of 3... 196s Nothing todo. Only one DH segmentation. Skipping. 196s TCN segment #3 ('3') of 3...done 196s Chromosome 1 ('chr01') of 1...done 196s Update (C1,C2) per segment... 196s Update (C1,C2) per segment...done 196s Post-segmenting TCNs...done 196s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 196s 1 1 1 1 554484 120908858 7586 1.3853 2108 196s 2 1 2 1 142693888 185449813 2681 2.0689 777 196s 3 1 3 1 185449813 247137334 4391 2.6341 1311 196s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 196s 1 2108 554484 120908858 2108 0.5116 0.3382903 1.047010 196s 2 777 142693888 185449813 777 0.0973 0.9337980 1.135102 196s 3 1311 185449813 247137334 1311 0.2295 1.0147870 1.619313 196s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 196s 1 1 1 1 554484 120908858 7586 1.3853 2108 196s 2 1 2 1 142693888 185449813 2681 2.0689 777 196s 3 1 3 1 185449813 247137334 4391 2.6341 1311 196s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 196s 1 2108 554484 120908858 2108 0.5116 0.3382903 1.047010 196s 2 777 142693888 185449813 777 0.0973 0.9337980 1.135102 196s 3 1311 185449813 247137334 1311 0.2295 1.0147870 1.619313 196s > print(fit) 196s chromosome tcnId dhId start end tcnNbrOfLoci tcnMean tcnNbrOfSNPs 196s 1 1 1 1 554484 120908858 7586 1.3853 2108 196s 2 1 2 1 142693888 185449813 2681 2.0689 777 196s 3 1 3 1 185449813 247137334 4391 2.6341 1311 196s tcnNbrOfHets dhNbrOfLoci dhMean c1Mean c2Mean 196s 1 2108 2108 0.5116 0.3382903 1.047010 196s 2 777 777 0.0973 0.9337980 1.135102 196s 3 1311 1311 0.2295 1.0147870 1.619313 196s > 196s > fit1 <- fit 196s > fit2 <- renameChromosomes(fit1, from=1, to=2) 196s > fit <- c(fit1, fit2) 196s > knownSegments <- tileChromosomes(fit)$params$knownSegments 196s > 196s > segList <- seqOfSegmentsByDP(fit, verbose=-10) 196s Identifying optimal sets of segments via dynamic programming... 196s Shifting TCN levels for every second segment... 196s Split up into non-empty independent regions... 196s Chromosome #1 ('1') of 2... 196s Number of loci on chromosome: 14658 196s Known segments on chromosome: 196s chromosome start end 196s 1 1 -Inf 120908858 196s 2 1 142693888 Inf 196s Known segment #1 of 2... 196s chromosome start end 196s 1 1 -Inf 120908858 196s Known segment #1 of 2...done 196s Known segment #2 of 2... 196s chromosome start end 196s 2 1 142693888 Inf 196s Known segment #2 of 2...done 196s Chromosome #1 ('1') of 2...done 196s Chromosome #2 ('2') of 2... 196s Number of loci on chromosome: 14658 196s Known segments on chromosome: 196s chromosome start end 196s 3 2 -Inf 120908858 196s 4 2 142693888 Inf 196s Known segment #1 of 2... 196s chromosome start end 196s 3 2 -Inf 120908858 196s Known segment #1 of 2...done 196s Known segment #2 of 2... 196s chromosome start end 196s 4 2 142693888 Inf 196s Known segment #2 of 2...done 196s Chromosome #2 ('2') of 2...done 196s Number of independent non-empty regions: 4 196s Split up into non-empty independent regions...done 196s Shift every other region... 196s Shift every other region...done 196s Merge... 196s Merge...done 196s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 196s 1 1 1 1 554484 120908858 7586 101.3853 2108 196s 2 1 2 1 142693888 185449813 2681 2.0689 777 196s 3 1 3 1 185449813 247137334 4391 2.6341 1311 196s 4 2 1 1 554484 120908858 7586 101.3853 2108 196s 5 2 2 1 142693888 185449813 2681 2.0689 777 196s 6 2 3 1 185449813 247137334 4391 2.6341 1311 196s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 196s 1 2108 554484 120908858 2108 0.511612 24.757671 76.627587 196s 2 777 142693888 185449813 777 0.097300 0.933798 1.135102 196s 3 1311 185449813 247137334 1311 0.229500 1.014787 1.619313 196s 4 2108 554484 120908858 2108 0.511612 24.757671 76.627587 196s 5 777 142693888 185449813 777 0.097300 0.933798 1.135102 196s 6 1311 185449813 247137334 1311 0.229500 1.014787 1.619313 196s Shifting TCN levels for every second segment...done 196s Extracting signals for dynamic programming... 196s CT rho 196s Min. : 0.805 Min. :0.0002 196s 1st Qu.: 2.407 1st Qu.:0.1393 196s Median :100.927 Median :0.2934 196s Mean : 53.638 Mean :0.3467 196s 3rd Qu.:101.370 3rd Qu.:0.5566 196s Max. :103.080 Max. :1.0217 196s NA's :20924 196s Extracting signals for dynamic programming...done 196s Dynamic programming... 196s Number of "DP" change points: 5 196s int [1:5] 7586 10267 14658 22244 24925 196s List of 4 196s $ jump :List of 5 196s ..$ : num 22244 196s ..$ : num [1:2] 7586 14658 196s ..$ : num [1:3] 7586 14658 22244 196s ..$ : num [1:4] 7586 10267 14658 22244 196s ..$ : num [1:5] 7586 10267 14658 22244 24925 196s $ rse : num [1:6] 71699116 47249179 35852530 5945 5410 ... 196s $ kbest: num 4 196s $ V : num [1:6, 1:6] 1114 0 0 0 0 ... 196s Dynamic programming...done 196s Excluding cases where known segments no longer correct... 196s Number of independent non-empty regions: 4 196s List of 3 196s $ : num [1:3] 7586 14658 22244 196s $ : num [1:4] 7586 10267 14658 22244 196s $ : num [1:5] 7586 10267 14658 22244 24925 196s Excluding cases where known segments no longer correct...done 196s List of 3 196s $ :'data.frame': 4 obs. of 3 variables: 196s ..$ chromosome: int [1:4] 1 1 2 2 196s ..$ start : num [1:4] 5.54e+05 1.43e+08 5.54e+05 1.43e+08 196s ..$ end : num [1:4] 1.21e+08 2.47e+08 1.21e+08 2.47e+08 196s $ :'data.frame': 5 obs. of 3 variables: 196s ..$ chromosome: int [1:5] 1 1 1 2 2 196s ..$ start : num [1:5] 5.54e+05 1.43e+08 1.85e+08 5.54e+05 1.43e+08 196s ..$ end : num [1:5] 1.21e+08 1.85e+08 2.47e+08 1.21e+08 2.47e+08 196s $ :'data.frame': 6 obs. of 3 variables: 196s ..$ chromosome: int [1:6] 1 1 1 2 2 2 196s ..$ start : num [1:6] 5.54e+05 1.43e+08 1.85e+08 5.54e+05 1.43e+08 ... 196s ..$ end : num [1:6] 1.21e+08 1.85e+08 2.47e+08 1.21e+08 1.85e+08 ... 196s Sequence of number of "DP" change points: 196s [1] 3 4 5 196s Sequence of number of segments: 196s [1] 4 5 6 196s Sequence of number of "discovered" change points: 196s [1] 0 1 2 196s Identifying optimal sets of segments via dynamic programming...done 196s > K <- length(segList) 196s > ks <- seq(from=1, to=K, length.out=min(5,K)) 196s > subplots(length(ks), ncol=1, byrow=TRUE) 196s > par(mar=c(2,1,1,1)) 196s > for (kk in ks) { 196s + knownSegmentsKK <- segList[[kk]] 196s + fitKK <- resegment(fit, knownSegments=knownSegmentsKK, undoTCN=+Inf, undoDH=+Inf) 196s + plotTracks(fitKK, tracks="tcn,c1,c2", Clim=c(0,5), add=TRUE) 196s + abline(v=c(knownSegments$start, knownSegments$end)/1e6, lty=3) 196s + stext(side=3, pos=0, sprintf("Number of segments: %d", nrow(knownSegmentsKK))) 196s + } # for (kk ...) 196s > 196s > proc.time() 196s user system elapsed 196s 2.471 0.060 2.531 196s Test segmentByPairedPSCBS,seqOfSegmentsByDP passed 196s 0 196s Begin test segmentByPairedPSCBS 196s + [ 0 != 0 ] 196s + echo Test segmentByPairedPSCBS,seqOfSegmentsByDP passed 196s + echo 0 196s + echo Begin test segmentByPairedPSCBS 196s + exitcode=0 196s + R CMD BATCH segmentByPairedPSCBS.R 200s + cat segmentByPairedPSCBS.Rout 200s 200s R version 4.5.2 (2025-10-31) -- "[Not] Part in a Rumble" 200s Copyright (C) 2025 The R Foundation for Statistical Computing 200s Platform: x86_64-pc-linux-gnu 200s 200s R is free software and comes with ABSOLUTELY NO WARRANTY. 200s You are welcome to redistribute it under certain conditions. 200s Type 'license()' or 'licence()' for distribution details. 200s 200s R is a collaborative project with many contributors. 200s Type 'contributors()' for more information and 200s 'citation()' on how to cite R or R packages in publications. 200s 200s Type 'demo()' for some demos, 'help()' for on-line help, or 200s 'help.start()' for an HTML browser interface to help. 200s Type 'q()' to quit R. 200s 200s [Previously saved workspace restored] 200s 200s > ########################################################### 200s > # This tests: 200s > # - segmentByPairedPSCBS(...) 200s > # - segmentByPairedPSCBS(..., knownSegments) 200s > # - tileChromosomes() 200s > # - plotTracks() 200s > ########################################################### 200s > library("PSCBS") 200s PSCBS v0.68.0 (2025-04-18 19:40:02 UTC) successfully loaded. See ?PSCBS for help. 200s > 200s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 200s > # Load SNP microarray data 200s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 200s > data <- PSCBS::exampleData("paired.chr01") 200s > 200s > 200s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 200s > # Paired PSCBS segmentation 200s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 200s > # Drop single-locus outliers 200s > dataS <- dropSegmentationOutliers(data) 200s > 200s > # Run light-weight tests by default 200s > if (Sys.getenv("_R_CHECK_FULL_") == "") { 200s + # Use only every 5th data point 200s + dataS <- dataS[seq(from=1, to=nrow(data), by=5),] 200s + # Number of segments (for assertion) 200s + nSegs <- 4L 200s + } else { 200s + # Full tests 200s + nSegs <- 11L 200s + } 200s > 200s > str(dataS) 200s 'data.frame': 14670 obs. of 6 variables: 200s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 200s $ x : int 1145994 2941694 3710825 4240737 4276892 4464544 4714611 5095111 5034491 5158416 ... 200s $ CT : num 1.63 1.4 1.41 1.17 1.16 ... 200s $ betaT : num 0.7574 0.169 0.2357 0.2604 0.0576 ... 200s $ CN : num 2.36 2.13 2.26 2.01 2.32 ... 200s $ betaN : num 0.8274 0.5072 0.1671 0.1609 0.0421 ... 200s > 200s > fig <- 1 200s > 200s > 200s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 200s > # (a) Don't segment the centromere (and force a separator) 200s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 200s > knownSegments <- data.frame( 200s + chromosome = c( 1, 1, 1), 200s + start = c( -Inf, NA, 141510003), 200s + end = c(120992603, NA, +Inf) 200s + ) 200s > 200s > 200s > # Paired PSCBS segmentation 200s > fit <- segmentByPairedPSCBS(dataS, knownSegments=knownSegments, 200s + seed=0xBEEF, verbose=-10) 200s Segmenting paired tumor-normal signals using Paired PSCBS... 200s Calling genotypes from normal allele B fractions... 200s num [1:14670] 0.8274 0.5072 0.1671 0.1609 0.0421 ... 200s Called genotypes: 200s num [1:14670] 1 0.5 0 0 0 0 1 0 1 0.5 ... 200s - attr(*, "modelFit")=List of 1 200s ..$ :List of 7 200s .. ..$ flavor : chr "density" 200s .. ..$ cn : int 2 200s .. ..$ nbrOfGenotypeGroups: int 3 200s .. ..$ tau : num [1:2] 0.315 0.677 200s .. ..$ n : int 14640 200s .. ..$ fit :Classes 'PeaksAndValleys' and 'data.frame': 5 obs. of 3 variables: 200s .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 200s .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 200s .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 200s .. ..$ fitValleys :Classes 'PeaksAndValleys' and 'data.frame': 2 obs. of 3 variables: 200s .. .. ..$ type : chr [1:2] "valley" "valley" 200s .. .. ..$ x : num [1:2] 0.315 0.677 200s .. .. ..$ density: num [1:2] 0.522 0.551 200s ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 200s muN 200s 0 0.5 1 200s 5221 4198 5251 200s Calling genotypes from normal allele B fractions...done 200s Normalizing betaT using betaN (TumorBoost)... 200s Normalized BAFs: 200s num [1:14670] 0.9301 0.1667 0.0685 0.0995 0.0155 ... 200s - attr(*, "modelFit")=List of 5 200s ..$ method : chr "normalizeTumorBoost" 200s ..$ flavor : chr "v4" 200s ..$ delta : num [1:14670] -0.17264 0.00239 0.1671 0.16085 0.04213 ... 200s .. ..- attr(*, "modelFit")=List of 1 200s .. .. ..$ :List of 7 200s .. .. .. ..$ flavor : chr "density" 200s .. .. .. ..$ cn : int 2 200s .. .. .. ..$ nbrOfGenotypeGroups: int 3 200s .. .. .. ..$ tau : num [1:2] 0.315 0.677 200s .. .. .. ..$ n : int 14640 200s .. .. .. ..$ fit :Classes 'PeaksAndValleys' and 'data.frame': 5 obs. of 3 variables: 200s .. .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 200s .. .. .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 200s .. .. .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 200s .. .. .. ..$ fitValleys :Classes 'PeaksAndValleys' and 'data.frame': 2 obs. of 3 variables: 200s .. .. .. .. ..$ type : chr [1:2] "valley" "valley" 200s .. .. .. .. ..$ x : num [1:2] 0.315 0.677 200s .. .. .. .. ..$ density: num [1:2] 0.522 0.551 200s .. .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 200s ..$ preserveScale: logi FALSE 200s ..$ scaleFactor : num NA 200s Normalizing betaT using betaN (TumorBoost)...done 200s Setup up data... 200s 'data.frame': 14670 obs. of 7 variables: 200s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 200s $ x : num 1145994 2941694 3710825 4240737 4276892 ... 200s $ CT : num 1.63 1.4 1.41 1.17 1.16 ... 200s $ betaT : num 0.7574 0.169 0.2357 0.2604 0.0576 ... 200s $ betaTN : num 0.9301 0.1667 0.0685 0.0995 0.0155 ... 200s ..- attr(*, "modelFit")=List of 5 200s .. ..$ method : chr "normalizeTumorBoost" 200s .. ..$ flavor : chr "v4" 200s .. ..$ delta : num [1:14670] -0.17264 0.00239 0.1671 0.16085 0.04213 ... 200s .. .. ..- attr(*, "modelFit")=List of 1 200s .. .. .. ..$ :List of 7 200s .. .. .. .. ..$ flavor : chr "density" 200s .. .. .. .. ..$ cn : int 2 200s .. .. .. .. ..$ nbrOfGenotypeGroups: int 3 200s .. .. .. .. ..$ tau : num [1:2] 0.315 0.677 200s .. .. .. .. ..$ n : int 14640 200s .. .. .. .. ..$ fit :Classes 'PeaksAndValleys' and 'data.frame': 5 obs. of 3 variables: 200s .. .. .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 200s .. .. .. .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 200s .. .. .. .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 200s .. .. .. .. ..$ fitValleys :Classes 'PeaksAndValleys' and 'data.frame': 2 obs. of 3 variables: 200s .. .. .. .. .. ..$ type : chr [1:2] "valley" "valley" 200s .. .. .. .. .. ..$ x : num [1:2] 0.315 0.677 200s .. .. .. .. .. ..$ density: num [1:2] 0.522 0.551 200s .. .. .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 200s .. ..$ preserveScale: logi FALSE 200s .. ..$ scaleFactor : num NA 200s $ betaN : num 0.8274 0.5072 0.1671 0.1609 0.0421 ... 200s $ muN : num 1 0.5 0 0 0 0 1 0 1 0.5 ... 200s ..- attr(*, "modelFit")=List of 1 200s .. ..$ :List of 7 200s .. .. ..$ flavor : chr "density" 200s .. .. ..$ cn : int 2 200s .. .. ..$ nbrOfGenotypeGroups: int 3 200s .. .. ..$ tau : num [1:2] 0.315 0.677 200s .. .. ..$ n : int 14640 200s .. .. ..$ fit :Classes 'PeaksAndValleys' and 'data.frame': 5 obs. of 3 variables: 200s .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 200s .. .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 200s .. .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 200s .. .. ..$ fitValleys :Classes 'PeaksAndValleys' and 'data.frame': 2 obs. of 3 variables: 200s .. .. .. ..$ type : chr [1:2] "valley" "valley" 200s .. .. .. ..$ x : num [1:2] 0.315 0.677 200s .. .. .. ..$ density: num [1:2] 0.522 0.551 200s .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 200s Setup up data...done 200s Dropping loci for which TCNs are missing... 200s Number of loci dropped: 12 200s Dropping loci for which TCNs are missing...done 200s Ordering data along genome... 200s 'data.frame': 14658 obs. of 7 variables: 200s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 200s $ x : num 554484 730720 782343 878522 916294 ... 200s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 200s $ betaT : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 200s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 200s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 200s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 200s Ordering data along genome...done 200s Keeping only current chromosome for 'knownSegments'... 200s Chromosome: 1 200s Known segments for this chromosome: 200s chromosome start end 200s 1 1 -Inf 120992603 200s 2 1 NA NA 200s 3 1 141510003 Inf 200s Keeping only current chromosome for 'knownSegments'...done 200s alphaTCN: 0.009 200s alphaDH: 0.001 200s Number of loci: 14658 200s Calculating DHs... 200s Number of SNPs: 14658 200s Number of heterozygous SNPs: 4196 (28.63%) 200s Normalized DHs: 200s num [1:14658] NA NA NA NA NA ... 200s Calculating DHs...done 200s Random seed temporarily set (seed=c(48879), kind="L'Ecuyer-CMRG") 200s Produced 2 seeds from this stream for future usage 200s Identification of change points by total copy numbers... 200s Segmenting by CBS... 200s Chromosome: 1 200s Segmenting multiple segments on current chromosome... 200s Number of segments: 3 200s Random seed temporarily set (seed=c(10407, 1066287653, -51199871, 161854402, -1995183193, 1503453565, -747102133), kind="L'Ecuyer-CMRG") 200s Produced 3 seeds from this stream for future usage 200s Segmenting by CBS... 200s Chromosome: 1 200s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 200s Segmenting by CBS...done 200s Segmenting by CBS... 200s Chromosome: 1 200s Random seed temporarily set (seed=c(10407, -1924040949, -1632234809, -437763632, -1464377300, 676654412, 2080370711), kind="L'Ecuyer-CMRG") 200s Segmenting by CBS...done 200s Segmenting multiple segments on current chromosome...done 200s Segmenting by CBS...done 200s List of 4 200s $ data :'data.frame': 14658 obs. of 4 variables: 200s ..$ chromosome: int [1:14658] 1 1 1 1 1 1 1 1 1 1 ... 200s ..$ x : num [1:14658] 554484 730720 782343 878522 916294 ... 200s ..$ y : num [1:14658] 1.88 1.8 1.59 1.64 1.53 ... 200s ..$ index : int [1:14658] 1 2 3 4 5 6 7 8 9 10 ... 200s $ output :'data.frame': 4 obs. of 6 variables: 200s ..$ sampleName: chr [1:4] NA NA NA NA 200s ..$ chromosome: int [1:4] 1 NA 1 1 200s ..$ start : num [1:4] 5.54e+05 NA 1.42e+08 1.85e+08 200s ..$ end : num [1:4] 1.21e+08 NA 1.85e+08 2.47e+08 200s ..$ nbrOfLoci : int [1:4] 7586 NA 2681 4391 200s ..$ mean : num [1:4] 1.39 NA 2.07 2.63 200s $ segRows:'data.frame': 4 obs. of 2 variables: 200s ..$ startRow: int [1:4] 1 NA 7587 10268 200s ..$ endRow : int [1:4] 7586 NA 10267 14658 200s $ params :List of 5 200s ..$ alpha : num 0.009 200s ..$ undo : num 0 200s ..$ joinSegments : logi TRUE 200s ..$ knownSegments:'data.frame': 4 obs. of 3 variables: 200s .. ..$ chromosome: num [1:4] 1 1 2 1 200s .. ..$ start : num [1:4] -Inf -Inf -Inf 1.42e+08 200s .. ..$ end : num [1:4] 1.21e+08 Inf Inf Inf 200s ..$ seed : int [1:7] 10407 1066287653 -51199871 161854402 -1995183193 1503453565 -747102133 200s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 200s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.087 0 0.088 0 0 200s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 200s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 200s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 200s Identification of change points by total copy numbers...done 200s Restructure TCN segmentation results... 200s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean 200s 1 1 554484 120992603 7586 1.3853 200s 2 NA NA NA NA NA 200s 3 1 141510003 185449813 2681 2.0689 200s 4 1 185449813 247137334 4391 2.6341 200s Number of TCN segments: 4 200s Restructure TCN segmentation results...done 200s Total CN segment #1 ([ 554484,1.20993e+08]) of 4... 200s Number of TCN loci in segment: 7586 200s Locus data for TCN segment: 200s 'data.frame': 7586 obs. of 9 variables: 200s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 200s $ x : num 554484 730720 782343 878522 916294 ... 200s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 200s $ betaT : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 200s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 200s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 200s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 200s $ index : int 1 2 3 4 5 6 7 8 9 10 ... 200s $ rho : num NA NA NA NA NA ... 200s Number of loci: 7586 200s Number of SNPs: 2108 (27.79%) 200s Number of heterozygous SNPs: 2108 (100.00%) 200s Chromosome: 1 200s Segmenting DH signals... 200s Segmenting by CBS... 200s Chromosome: 1 200s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 200s Segmenting by CBS...done 200s List of 4 200s $ data :'data.frame': 7586 obs. of 4 variables: 200s ..$ chromosome: int [1:7586] 1 1 1 1 1 1 1 1 1 1 ... 200s ..$ x : num [1:7586] 554484 730720 782343 878522 916294 ... 200s ..$ y : num [1:7586] NA NA NA NA NA ... 200s ..$ index : int [1:7586] 1 2 3 4 5 6 7 8 9 10 ... 200s $ output :'data.frame': 1 obs. of 6 variables: 200s ..$ sampleName: chr NA 200s ..$ chromosome: int 1 200s ..$ start : num 554484 200s ..$ end : num 1.21e+08 200s ..$ nbrOfLoci : int 2108 200s ..$ mean : num 0.512 200s $ segRows:'data.frame': 1 obs. of 2 variables: 200s ..$ startRow: int 10 200s ..$ endRow : int 7574 200s $ params :List of 5 200s ..$ alpha : num 0.001 200s ..$ undo : num 0 200s ..$ joinSegments : logi TRUE 200s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 200s .. ..$ chromosome: int 1 200s .. ..$ start : num 554484 200s .. ..$ end : num 1.21e+08 200s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 200s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 200s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.026 0 0.025 0 0 200s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 200s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 200s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 200s DH segmentation (locally-indexed) rows: 200s startRow endRow 200s 1 10 7574 200s int [1:7586] 1 2 3 4 5 6 7 8 9 10 ... 200s DH segmentation rows: 200s startRow endRow 200s 1 10 7574 200s Segmenting DH signals...done 200s DH segmentation table: 200s dhStart dhEnd dhNbrOfLoci dhMean 200s 1 554484 120992603 2108 0.5116 200s startRow endRow 200s 1 10 7574 200s Rows: 200s [1] 1 200s TCN segmentation rows: 200s startRow endRow 200s 1 1 7586 200s TCN and DH segmentation rows: 200s startRow endRow 200s 1 1 7586 200s startRow endRow 200s 1 10 7574 200s NULL 200s TCN segmentation (expanded) rows: 200s startRow endRow 200s 1 1 7586 200s TCN and DH segmentation rows: 200s startRow endRow 200s 1 1 7586 200s 2 NA NA 200s 3 7587 10267 200s 4 10268 14658 200s startRow endRow 200s 1 10 7574 200s startRow endRow 200s 1 1 7586 200s Total CN segmentation table (expanded): 200s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 200s 1 1 554484 120992603 7586 1.3853 2108 2108 200s (TCN,DH) segmentation for one total CN segment: 200s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 200s 1 1 1 1 554484 120992603 7586 1.3853 2108 200s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 200s 1 2108 554484 120992603 2108 0.5116 200s Total CN segment #1 ([ 554484,1.20993e+08]) of 4...done 200s Total CN segment #2 ([ NA, NA]) of 4... 200s No signals to segment. Just a "splitter" segment. Skipping. 200s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 200s NA 2 1 NA NA NA NA NA 0 200s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 200s NA 0 NA NA 0 NA 200s Total CN segment #2 ([ NA, NA]) of 4...done 200s Total CN segment #3 ([1.4151e+08,1.8545e+08]) of 4... 200s Number of TCN loci in segment: 2681 200s Locus data for TCN segment: 200s 'data.frame': 2681 obs. of 9 variables: 200s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 200s $ x : num 1.43e+08 1.43e+08 1.43e+08 1.43e+08 1.44e+08 ... 200s $ CT : num 2.27 1.55 1.47 1.5 1.81 ... 200s $ betaT : num 0.34 0.55 0.048 0.813 0.575 ... 200s $ betaTN : num 0.441 0.629 -0.05 0.958 0.872 ... 200s $ betaN : num 0.3851 0.3933 0.0981 0.8552 0.7028 ... 200s $ muN : num 0.5 0.5 0 1 1 1 1 0.5 1 1 ... 200s $ index : int 7587 7588 7589 7590 7591 7592 7593 7594 7595 7596 ... 200s $ rho : num 0.117 0.258 NA NA NA ... 200s Number of loci: 2681 200s Number of SNPs: 777 (28.98%) 200s Number of heterozygous SNPs: 777 (100.00%) 200s Chromosome: 1 200s Segmenting DH signals... 200s Segmenting by CBS... 200s Chromosome: 1 200s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 200s Segmenting by CBS...done 200s List of 4 200s $ data :'data.frame': 2681 obs. of 4 variables: 200s ..$ chromosome: int [1:2681] 1 1 1 1 1 1 1 1 1 1 ... 200s ..$ x : num [1:2681] 1.43e+08 1.43e+08 1.43e+08 1.43e+08 1.44e+08 ... 200s ..$ y : num [1:2681] 0.117 0.258 NA NA NA ... 200s ..$ index : int [1:2681] 1 2 3 4 5 6 7 8 9 10 ... 200s $ output :'data.frame': 1 obs. of 6 variables: 200s ..$ sampleName: chr NA 200s ..$ chromosome: int 1 200s ..$ start : num 1.42e+08 200s ..$ end : num 1.85e+08 200s ..$ nbrOfLoci : int 777 200s ..$ mean : num 0.0973 200s $ segRows:'data.frame': 1 obs. of 2 variables: 200s ..$ startRow: int 1 200s ..$ endRow : int 2677 200s $ params :List of 5 200s ..$ alpha : num 0.001 200s ..$ undo : num 0 200s ..$ joinSegments : logi TRUE 200s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 200s .. ..$ chromosome: int 1 200s .. ..$ start : num 1.42e+08 200s .. ..$ end : num 1.85e+08 200s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 200s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 200s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.006 0 0.005 0 0 200s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 200s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 200s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 200s DH segmentation (locally-indexed) rows: 200s startRow endRow 200s 1 1 2677 200s int [1:2681] 7587 7588 7589 7590 7591 7592 7593 7594 7595 7596 ... 200s DH segmentation rows: 200s startRow endRow 200s 1 7587 10263 200s Segmenting DH signals...done 200s DH segmentation table: 200s dhStart dhEnd dhNbrOfLoci dhMean 200s 1 141510003 185449813 777 0.0973 200s startRow endRow 200s 1 7587 10263 200s Rows: 200s [1] 3 200s TCN segmentation rows: 200s startRow endRow 200s 3 7587 10267 200s TCN and DH segmentation rows: 200s startRow endRow 200s 3 7587 10267 200s startRow endRow 200s 1 7587 10263 200s startRow endRow 200s 1 1 7586 200s NA NA NA 200s TCN segmentation (expanded) rows: 200s startRow endRow 200s 1 1 7586 200s NA NA NA 200s 3 7587 10267 200s TCN and DH segmentation rows: 200s startRow endRow 200s 1 1 7586 200s 2 NA NA 200s 3 7587 10267 200s 4 10268 14658 200s startRow endRow 200s 1 10 7574 200s 2 NA NA 200s 3 7587 10263 200s startRow endRow 200s 1 1 7586 200s 2 NA NA 200s 3 7587 10267 200s Total CN segmentation table (expanded): 200s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 200s 3 1 141510003 185449813 2681 2.0689 777 777 200s (TCN,DH) segmentation for one total CN segment: 200s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 200s 3 3 1 1 141510003 185449813 2681 2.0689 777 200s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 200s 3 777 141510003 185449813 777 0.0973 200s Total CN segment #3 ([1.4151e+08,1.8545e+08]) of 4...done 200s Total CN segment #4 ([1.8545e+08,2.47137e+08]) of 4... 200s Number of TCN loci in segment: 4391 200s Locus data for TCN segment: 200s 'data.frame': 4391 obs. of 9 variables: 200s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 200s $ x : num 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 200s $ CT : num 2.93 2.15 2.82 2.93 2.46 ... 200s $ betaT : num 0.0811 0.5154 0.9473 0.3734 0.7506 ... 200s $ betaTN : num -0.169 0.609 1.028 0.525 0.968 ... 200s $ betaN : num 0.25 0.38 0.919 0.34 0.783 ... 200s $ muN : num 0 0.5 1 0.5 1 1 0 1 0 1 ... 200s $ index : int 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 200s $ rho : num NA 0.2186 NA 0.0503 NA ... 200s Number of loci: 4391 200s Number of SNPs: 1311 (29.86%) 200s Number of heterozygous SNPs: 1311 (100.00%) 200s Chromosome: 1 200s Segmenting DH signals... 200s Segmenting by CBS... 200s Chromosome: 1 200s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 200s Segmenting by CBS...done 200s List of 4 200s $ data :'data.frame': 4391 obs. of 4 variables: 200s ..$ chromosome: int [1:4391] 1 1 1 1 1 1 1 1 1 1 ... 200s ..$ x : num [1:4391] 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 200s ..$ y : num [1:4391] NA 0.2186 NA 0.0503 NA ... 200s ..$ index : int [1:4391] 1 2 3 4 5 6 7 8 9 10 ... 200s $ output :'data.frame': 1 obs. of 6 variables: 200s ..$ sampleName: chr NA 200s ..$ chromosome: int 1 200s ..$ start : num 1.85e+08 200s ..$ end : num 2.47e+08 200s ..$ nbrOfLoci : int 1311 200s ..$ mean : num 0.23 200s $ segRows:'data.frame': 1 obs. of 2 variables: 200s ..$ startRow: int 2 200s ..$ endRow : int 4388 200s $ params :List of 5 200s ..$ alpha : num 0.001 200s ..$ undo : num 0 200s ..$ joinSegments : logi TRUE 200s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 200s .. ..$ chromosome: int 1 200s .. ..$ start : num 1.85e+08 200s .. ..$ end : num 2.47e+08 200s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 200s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 200s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.01 0 0.009 0 0 200s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 200s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 200s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 200s DH segmentation (locally-indexed) rows: 200s startRow endRow 200s 1 2 4388 200s int [1:4391] 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 200s DH segmentation rows: 200s startRow endRow 200s 1 10269 14655 200s Segmenting DH signals...done 200s DH segmentation table: 200s dhStart dhEnd dhNbrOfLoci dhMean 200s 1 185449813 247137334 1311 0.2295 200s startRow endRow 200s 1 10269 14655 200s Rows: 200s [1] 4 200s TCN segmentation rows: 200s startRow endRow 200s 4 10268 14658 200s TCN and DH segmentation rows: 200s startRow endRow 200s 4 10268 14658 200s startRow endRow 200s 1 10269 14655 200s startRow endRow 200s 1 1 7586 200s 2 NA NA 200s 3 7587 10267 200s TCN segmentation (expanded) rows: 200s startRow endRow 200s 1 1 7586 200s 2 NA NA 200s 3 7587 10267 200s 4 10268 14658 200s TCN and DH segmentation rows: 200s startRow endRow 200s 1 1 7586 200s 2 NA NA 200s 3 7587 10267 200s 4 10268 14658 200s startRow endRow 200s 1 10 7574 200s 2 NA NA 200s 3 7587 10263 200s 4 10269 14655 200s startRow endRow 200s 1 1 7586 200s 2 NA NA 200s 3 7587 10267 200s 4 10268 14658 200s Total CN segmentation table (expanded): 200s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 200s 4 1 185449813 247137334 4391 2.6341 1311 1311 200s (TCN,DH) segmentation for one total CN segment: 200s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 200s 4 4 1 1 185449813 247137334 4391 2.6341 1311 200s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 200s 4 1311 185449813 247137334 1311 0.2295 200s Total CN segment #4 ([1.8545e+08,2.47137e+08]) of 4...done 200s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 200s 1 1 1 1 554484 120992603 7586 1.3853 2108 200s 2 NA 2 1 NA NA NA NA 0 200s 3 1 3 1 141510003 185449813 2681 2.0689 777 200s 4 1 4 1 185449813 247137334 4391 2.6341 1311 200s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 200s 1 2108 554484 120992603 2108 0.5116 200s 2 0 NA NA 0 NA 200s 3 777 141510003 185449813 777 0.0973 200s 4 1311 185449813 247137334 1311 0.2295 200s Calculating (C1,C2) per segment... 200s Calculating (C1,C2) per segment...done 200s Number of segments: 4 200s Segmenting paired tumor-normal signals using Paired PSCBS...done 200s Post-segmenting TCNs... 200s Number of segments: 3 200s Number of chromosomes: 1 200s [1] 1 200s Chromosome 1 ('chr01') of 1... 200s Rows: 200s [1] 1 2 3 200s Number of segments: 3 200s TCN segment #1 ('1') of 3... 200s Nothing todo. Only one DH segmentation. Skipping. 200s TCN segment #1 ('1') of 3...done 200s TCN segment #2 ('3') of 3... 200s Nothing todo. Only one DH segmentation. Skipping. 200s TCN segment #2 ('3') of 3...done 200s TCN segment #3 ('4') of 3... 200s Nothing todo. Only one DH segmentation. Skipping. 200s TCN segment #3 ('4') of 3...done 200s Chromosome 1 ('chr01') of 1...done 200s Update (C1,C2) per segment... 200s Update (C1,C2) per segment...done 200s Post-segmenting TCNs...done 200s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 200s 1 1 1 1 554484 120992603 7586 1.3853 2108 200s 2 NA 2 1 NA NA NA NA 0 200s 3 1 3 1 141510003 185449813 2681 2.0689 777 200s 4 1 4 1 185449813 247137334 4391 2.6341 1311 200s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 200s 1 2108 554484 120992603 2108 0.5116 0.3382903 1.047010 200s 2 0 NA NA 0 NA NA NA 200s 3 777 141510003 185449813 777 0.0973 0.9337980 1.135102 200s 4 1311 185449813 247137334 1311 0.2295 1.0147870 1.619313 200s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 200s 1 1 1 1 554484 120992603 7586 1.3853 2108 200s 2 NA 2 1 NA NA NA NA 0 200s 3 1 3 1 141510003 185449813 2681 2.0689 777 200s 4 1 4 1 185449813 247137334 4391 2.6341 1311 200s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 200s 1 2108 554484 120992603 2108 0.5116 0.3382903 1.047010 200s 2 0 NA NA 0 NA NA NA 200s 3 777 141510003 185449813 777 0.0973 0.9337980 1.135102 200s 4 1311 185449813 247137334 1311 0.2295 1.0147870 1.619313 200s > print(fit) 200s chromosome tcnId dhId start end tcnNbrOfLoci tcnMean tcnNbrOfSNPs 200s 1 1 1 1 554484 120992603 7586 1.3853 2108 200s 2 NA 2 1 NA NA NA NA 0 200s 3 1 3 1 141510003 185449813 2681 2.0689 777 200s 4 1 4 1 185449813 247137334 4391 2.6341 1311 200s tcnNbrOfHets dhNbrOfLoci dhMean c1Mean c2Mean 200s 1 2108 2108 0.5116 0.3382903 1.047010 200s 2 0 0 NA NA NA 200s 3 777 777 0.0973 0.9337980 1.135102 200s 4 1311 1311 0.2295 1.0147870 1.619313 200s > 200s > # Plot results 200s > dev.set(2L) 200s null device 200s 1 200s > plotTracks(fit) 200s > abline(v=c(knownSegments$start, knownSegments$end)/1e6, lty=3) 200s > 200s > # Sanity check 200s > stopifnot(nbrOfSegments(fit) == nSegs) 200s > 200s > fit1 <- fit 200s > 200s > 200s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 200s > # (b) Segment also the centromere (which will become NAs) 200s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 200s > knownSegments <- data.frame( 200s + chromosome = c( 1, 1, 1), 200s + start = c( -Inf, 120992604, 141510003), 200s + end = c(120992603, 141510002, +Inf) 200s + ) 200s > 200s > 200s > # Paired PSCBS segmentation 200s > fit <- segmentByPairedPSCBS(dataS, knownSegments=knownSegments, 200s + seed=0xBEEF, verbose=-10) 200s Segmenting paired tumor-normal signals using Paired PSCBS... 200s Calling genotypes from normal allele B fractions... 200s num [1:14670] 0.8274 0.5072 0.1671 0.1609 0.0421 ... 200s Called genotypes: 200s num [1:14670] 1 0.5 0 0 0 0 1 0 1 0.5 ... 200s - attr(*, "modelFit")=List of 1 200s ..$ :List of 7 200s .. ..$ flavor : chr "density" 200s .. ..$ cn : int 2 200s .. ..$ nbrOfGenotypeGroups: int 3 200s .. ..$ tau : num [1:2] 0.315 0.677 200s .. ..$ n : int 14640 200s .. ..$ fit :Classes 'PeaksAndValleys' and 'data.frame': 5 obs. of 3 variables: 200s .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 200s .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 200s .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 200s .. ..$ fitValleys :Classes 'PeaksAndValleys' and 'data.frame': 2 obs. of 3 variables: 200s .. .. ..$ type : chr [1:2] "valley" "valley" 200s .. .. ..$ x : num [1:2] 0.315 0.677 200s .. .. ..$ density: num [1:2] 0.522 0.551 200s ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 200s muN 200s 0 0.5 1 200s 5221 4198 5251 200s Calling genotypes from normal allele B fractions...done 200s Normalizing betaT using betaN (TumorBoost)... 200s Normalized BAFs: 200s num [1:14670] 0.9301 0.1667 0.0685 0.0995 0.0155 ... 200s - attr(*, "modelFit")=List of 5 200s ..$ method : chr "normalizeTumorBoost" 200s ..$ flavor : chr "v4" 200s ..$ delta : num [1:14670] -0.17264 0.00239 0.1671 0.16085 0.04213 ... 200s .. ..- attr(*, "modelFit")=List of 1 200s .. .. ..$ :List of 7 200s .. .. .. ..$ flavor : chr "density" 200s .. .. .. ..$ cn : int 2 200s .. .. .. ..$ nbrOfGenotypeGroups: int 3 200s .. .. .. ..$ tau : num [1:2] 0.315 0.677 200s .. .. .. ..$ n : int 14640 200s .. .. .. ..$ fit :Classes 'PeaksAndValleys' and 'data.frame': 5 obs. of 3 variables: 200s .. .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 200s .. .. .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 200s .. .. .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 200s .. .. .. ..$ fitValleys :Classes 'PeaksAndValleys' and 'data.frame': 2 obs. of 3 variables: 200s .. .. .. .. ..$ type : chr [1:2] "valley" "valley" 200s .. .. .. .. ..$ x : num [1:2] 0.315 0.677 200s .. .. .. .. ..$ density: num [1:2] 0.522 0.551 200s .. .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 200s ..$ preserveScale: logi FALSE 200s ..$ scaleFactor : num NA 200s Normalizing betaT using betaN (TumorBoost)...done 200s Setup up data... 200s 'data.frame': 14670 obs. of 7 variables: 200s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 200s $ x : num 1145994 2941694 3710825 4240737 4276892 ... 200s $ CT : num 1.63 1.4 1.41 1.17 1.16 ... 200s $ betaT : num 0.7574 0.169 0.2357 0.2604 0.0576 ... 200s $ betaTN : num 0.9301 0.1667 0.0685 0.0995 0.0155 ... 200s ..- attr(*, "modelFit")=List of 5 200s .. ..$ method : chr "normalizeTumorBoost" 200s .. ..$ flavor : chr "v4" 200s .. ..$ delta : num [1:14670] -0.17264 0.00239 0.1671 0.16085 0.04213 ... 200s .. .. ..- attr(*, "modelFit")=List of 1 200s .. .. .. ..$ :List of 7 200s .. .. .. .. ..$ flavor : chr "density" 200s .. .. .. .. ..$ cn : int 2 200s .. .. .. .. ..$ nbrOfGenotypeGroups: int 3 200s .. .. .. .. ..$ tau : num [1:2] 0.315 0.677 200s .. .. .. .. ..$ n : int 14640 200s .. .. .. .. ..$ fit :Classes 'PeaksAndValleys' and 'data.frame': 5 obs. of 3 variables: 200s .. .. .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 200s .. .. .. .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 200s .. .. .. .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 200s .. .. .. .. ..$ fitValleys :Classes 'PeaksAndValleys' and 'data.frame': 2 obs. of 3 variables: 200s .. .. .. .. .. ..$ type : chr [1:2] "valley" "valley" 200s .. .. .. .. .. ..$ x : num [1:2] 0.315 0.677 200s .. .. .. .. .. ..$ density: num [1:2] 0.522 0.551 200s .. .. .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 200s .. ..$ preserveScale: logi FALSE 200s .. ..$ scaleFactor : num NA 200s $ betaN : num 0.8274 0.5072 0.1671 0.1609 0.0421 ... 200s $ muN : num 1 0.5 0 0 0 0 1 0 1 0.5 ... 200s ..- attr(*, "modelFit")=List of 1 200s .. ..$ :List of 7 200s .. .. ..$ flavor : chr "density" 200s .. .. ..$ cn : int 2 200s .. .. ..$ nbrOfGenotypeGroups: int 3 200s .. .. ..$ tau : num [1:2] 0.315 0.677 200s .. .. ..$ n : int 14640 200s .. .. ..$ fit :Classes 'PeaksAndValleys' and 'data.frame': 5 obs. of 3 variables: 200s .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 200s .. .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 200s .. .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 200s .. .. ..$ fitValleys :Classes 'PeaksAndValleys' and 'data.frame': 2 obs. of 3 variables: 200s .. .. .. ..$ type : chr [1:2] "valley" "valley" 200s .. .. .. ..$ x : num [1:2] 0.315 0.677 200s .. .. .. ..$ density: num [1:2] 0.522 0.551 200s .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 200s Setup up data...done 200s Dropping loci for which TCNs are missing... 200s Number of loci dropped: 12 200s Dropping loci for which TCNs are missing...done 200s Ordering data along genome... 200s 'data.frame': 14658 obs. of 7 variables: 200s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 200s $ x : num 554484 730720 782343 878522 916294 ... 200s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 200s $ betaT : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 200s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 200s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 200s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 200s Ordering data along genome...done 200s Keeping only current chromosome for 'knownSegments'... 200s Chromosome: 1 200s Known segments for this chromosome: 200s chromosome start end 200s 1 1 -Inf 120992603 200s 2 1 120992604 141510002 200s 3 1 141510003 Inf 200s Keeping only current chromosome for 'knownSegments'...done 200s alphaTCN: 0.009 200s alphaDH: 0.001 200s Number of loci: 14658 200s Calculating DHs... 200s Number of SNPs: 14658 200s Number of heterozygous SNPs: 4196 (28.63%) 200s Normalized DHs: 200s num [1:14658] NA NA NA NA NA ... 200s Calculating DHs...done 200s Random seed temporarily set (seed=c(48879), kind="L'Ecuyer-CMRG") 200s Produced 2 seeds from this stream for future usage 200s Identification of change points by total copy numbers... 200s Segmenting by CBS... 200s Chromosome: 1 200s Segmenting multiple segments on current chromosome... 200s Number of segments: 3 200s Random seed temporarily set (seed=c(10407, 1066287653, -51199871, 161854402, -1995183193, 1503453565, -747102133), kind="L'Ecuyer-CMRG") 200s Produced 3 seeds from this stream for future usage 200s Segmenting by CBS... 200s Chromosome: 1 200s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 200s Segmenting by CBS...done 200s Segmenting by CBS... 200s Chromosome: 1 200s Random seed temporarily set (seed=c(10407, -1924040949, -1632234809, -437763632, -1464377300, 676654412, 2080370711), kind="L'Ecuyer-CMRG") 200s Segmenting by CBS...done 200s Segmenting multiple segments on current chromosome...done 200s Segmenting by CBS...done 200s List of 4 200s $ data :'data.frame': 14658 obs. of 4 variables: 200s ..$ chromosome: int [1:14658] 1 1 1 1 1 1 1 1 1 1 ... 200s ..$ x : num [1:14658] 554484 730720 782343 878522 916294 ... 200s ..$ y : num [1:14658] 1.88 1.8 1.59 1.64 1.53 ... 200s ..$ index : int [1:14658] 1 2 3 4 5 6 7 8 9 10 ... 200s $ output :'data.frame': 4 obs. of 6 variables: 200s ..$ sampleName: chr [1:4] NA NA NA NA 200s ..$ chromosome: num [1:4] 1 1 1 1 200s ..$ start : num [1:4] 5.54e+05 1.21e+08 1.42e+08 1.85e+08 200s ..$ end : num [1:4] 1.21e+08 1.42e+08 1.85e+08 2.47e+08 200s ..$ nbrOfLoci : int [1:4] 7586 0 2681 4391 200s ..$ mean : num [1:4] 1.39 NA 2.07 2.63 200s $ segRows:'data.frame': 4 obs. of 2 variables: 200s ..$ startRow: int [1:4] 1 NA 7587 10268 200s ..$ endRow : int [1:4] 7586 NA 10267 14658 200s $ params :List of 5 200s ..$ alpha : num 0.009 200s ..$ undo : num 0 200s ..$ joinSegments : logi TRUE 200s ..$ knownSegments:'data.frame': 4 obs. of 3 variables: 200s .. ..$ chromosome: num [1:4] 1 1 2 1 200s .. ..$ start : num [1:4] -Inf -Inf -Inf 1.42e+08 200s .. ..$ end : num [1:4] 1.21e+08 Inf Inf Inf 200s ..$ seed : int [1:7] 10407 1066287653 -51199871 161854402 -1995183193 1503453565 -747102133 200s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 200s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.088 0 0.088 0 0 200s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 200s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 200s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 200s Identification of change points by total copy numbers...done 200s Restructure TCN segmentation results... 200s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean 200s 1 1 554484 120992603 7586 1.3853 200s 2 1 120992604 141510002 0 NA 200s 3 1 141510003 185449813 2681 2.0689 200s 4 1 185449813 247137334 4391 2.6341 200s Number of TCN segments: 4 200s Restructure TCN segmentation results...done 200s Total CN segment #1 ([ 554484,1.20993e+08]) of 4... 200s Number of TCN loci in segment: 7586 200s Locus data for TCN segment: 200s 'data.frame': 7586 obs. of 9 variables: 200s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 200s $ x : num 554484 730720 782343 878522 916294 ... 200s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 200s $ betaT : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 200s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 200s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 200s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 200s $ index : int 1 2 3 4 5 6 7 8 9 10 ... 200s $ rho : num NA NA NA NA NA ... 200s Number of loci: 7586 200s Number of SNPs: 2108 (27.79%) 200s Number of heterozygous SNPs: 2108 (100.00%) 200s Chromosome: 1 200s Segmenting DH signals... 200s Segmenting by CBS... 200s Chromosome: 1 200s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 200s Segmenting by CBS...done 200s List of 4 200s $ data :'data.frame': 7586 obs. of 4 variables: 200s ..$ chromosome: int [1:7586] 1 1 1 1 1 1 1 1 1 1 ... 200s ..$ x : num [1:7586] 554484 730720 782343 878522 916294 ... 200s ..$ y : num [1:7586] NA NA NA NA NA ... 200s ..$ index : int [1:7586] 1 2 3 4 5 6 7 8 9 10 ... 200s $ output :'data.frame': 1 obs. of 6 variables: 200s ..$ sampleName: chr NA 200s ..$ chromosome: int 1 200s ..$ start : num 554484 200s ..$ end : num 1.21e+08 200s ..$ nbrOfLoci : int 2108 200s ..$ mean : num 0.512 200s $ segRows:'data.frame': 1 obs. of 2 variables: 200s ..$ startRow: int 10 200s ..$ endRow : int 7574 200s $ params :List of 5 200s ..$ alpha : num 0.001 200s ..$ undo : num 0 200s ..$ joinSegments : logi TRUE 200s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 200s .. ..$ chromosome: int 1 200s .. ..$ start : num 554484 200s .. ..$ end : num 1.21e+08 200s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 200s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 200s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.028 0 0.028 0 0 200s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 200s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 200s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 200s DH segmentation (locally-indexed) rows: 200s startRow endRow 200s 1 10 7574 200s int [1:7586] 1 2 3 4 5 6 7 8 9 10 ... 200s DH segmentation rows: 200s startRow endRow 200s 1 10 7574 200s Segmenting DH signals...done 200s DH segmentation table: 200s dhStart dhEnd dhNbrOfLoci dhMean 200s 1 554484 120992603 2108 0.5116 200s startRow endRow 200s 1 10 7574 200s Rows: 200s [1] 1 200s TCN segmentation rows: 200s startRow endRow 200s 1 1 7586 200s TCN and DH segmentation rows: 200s startRow endRow 200s 1 1 7586 200s startRow endRow 200s 1 10 7574 200s NULL 200s TCN segmentation (expanded) rows: 200s startRow endRow 200s 1 1 7586 200s TCN and DH segmentation rows: 200s startRow endRow 200s 1 1 7586 200s 2 NA NA 200s 3 7587 10267 200s 4 10268 14658 200s startRow endRow 200s 1 10 7574 200s startRow endRow 200s 1 1 7586 200s Total CN segmentation table (expanded): 200s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 200s 1 1 554484 120992603 7586 1.3853 2108 2108 200s (TCN,DH) segmentation for one total CN segment: 200s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 200s 1 1 1 1 554484 120992603 7586 1.3853 2108 200s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 200s 1 2108 554484 120992603 2108 0.5116 200s Total CN segment #1 ([ 554484,1.20993e+08]) of 4...done 200s Total CN segment #2 ([1.20993e+08,1.4151e+08]) of 4... 200s Number of TCN loci in segment: 0 200s Locus data for TCN segment: 200s 'data.frame': 0 obs. of 9 variables: 200s $ chromosome: int 200s $ x : num 200s $ CT : num 200s $ betaT : num 200s $ betaTN : num 200s $ betaN : num 200s $ muN : num 200s $ index : int 200s $ rho : num 200s Number of loci: 0 200s Number of SNPs: 0 (NaN%) 200s Number of heterozygous SNPs: 0 (NaN%) 200s Chromosome: 1 200s Segmenting DH signals... 200s Segmenting by CBS... 200s Chromosome: NA 200s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 200s Segmenting by CBS...done 200s List of 4 200s $ data :'data.frame': 0 obs. of 4 variables: 200s ..$ chromosome: int(0) 200s ..$ x : num(0) 200s ..$ y : num(0) 200s ..$ index : int(0) 200s $ output :'data.frame': 0 obs. of 6 variables: 200s ..$ sampleName: chr(0) 200s ..$ chromosome: num(0) 200s ..$ start : num(0) 200s ..$ end : num(0) 200s ..$ nbrOfLoci : int(0) 200s ..$ mean : num(0) 200s $ segRows:'data.frame': 0 obs. of 2 variables: 200s ..$ startRow: int(0) 200s ..$ endRow : int(0) 200s $ params :List of 5 200s ..$ alpha : num 0.001 200s ..$ undo : num 0 200s ..$ joinSegments : logi TRUE 200s ..$ knownSegments:'data.frame': 0 obs. of 3 variables: 200s .. ..$ chromosome: int(0) 200s .. ..$ start : num(0) 200s .. ..$ end : num(0) 200s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 200s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 200s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.001 0 0.001 0 0 200s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 200s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 200s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 200s DH segmentation (locally-indexed) rows: 200s [1] startRow endRow 200s <0 rows> (or 0-length row.names) 200s int(0) 200s DH segmentation rows: 200s [1] startRow endRow 200s <0 rows> (or 0-length row.names) 200s Segmenting DH signals...done 200s DH segmentation table: 200s dhStart dhEnd dhNbrOfLoci dhMean 200s NA NA NA NA NA 200s startRow endRow 200s NA NA NA 200s Rows: 200s [1] 2 200s TCN segmentation rows: 200s startRow endRow 200s 2 NA NA 200s TCN and DH segmentation rows: 200s startRow endRow 200s 2 NA NA 200s startRow endRow 200s NA NA NA 200s startRow endRow 200s 1 1 7586 200s TCN segmentation (expanded) rows: 200s startRow endRow 200s 1 1 7586 200s 2 NA NA 200s TCN and DH segmentation rows: 200s startRow endRow 200s 1 1 7586 200s 2 NA NA 200s 3 7587 10267 200s 4 10268 14658 200s startRow endRow 200s 1 10 7574 200s 2 NA NA 200s startRow endRow 200s 1 1 7586 200s 2 NA NA 200s Total CN segmentation table (expanded): 200s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 200s 2 1 120992604 141510002 0 NA 0 0 200s (TCN,DH) segmentation for one total CN segment: 200s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 200s 2 2 1 1 120992604 141510002 0 NA 0 200s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 200s 2 0 NA NA NA NA 200s Total CN segment #2 ([1.20993e+08,1.4151e+08]) of 4...done 200s Total CN segment #3 ([1.4151e+08,1.8545e+08]) of 4... 200s Number of TCN loci in segment: 2681 200s Locus data for TCN segment: 200s 'data.frame': 2681 obs. of 9 variables: 200s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 200s $ x : num 1.43e+08 1.43e+08 1.43e+08 1.43e+08 1.44e+08 ... 200s $ CT : num 2.27 1.55 1.47 1.5 1.81 ... 200s $ betaT : num 0.34 0.55 0.048 0.813 0.575 ... 200s $ betaTN : num 0.441 0.629 -0.05 0.958 0.872 ... 200s $ betaN : num 0.3851 0.3933 0.0981 0.8552 0.7028 ... 200s $ muN : num 0.5 0.5 0 1 1 1 1 0.5 1 1 ... 200s $ index : int 7587 7588 7589 7590 7591 7592 7593 7594 7595 7596 ... 200s $ rho : num 0.117 0.258 NA NA NA ... 200s Number of loci: 2681 200s Number of SNPs: 777 (28.98%) 200s Number of heterozygous SNPs: 777 (100.00%) 200s Chromosome: 1 200s Segmenting DH signals... 200s Segmenting by CBS... 200s Chromosome: 1 200s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 200s Segmenting by CBS...done 200s List of 4 200s $ data :'data.frame': 2681 obs. of 4 variables: 200s ..$ chromosome: int [1:2681] 1 1 1 1 1 1 1 1 1 1 ... 200s ..$ x : num [1:2681] 1.43e+08 1.43e+08 1.43e+08 1.43e+08 1.44e+08 ... 200s ..$ y : num [1:2681] 0.117 0.258 NA NA NA ... 200s ..$ index : int [1:2681] 1 2 3 4 5 6 7 8 9 10 ... 200s $ output :'data.frame': 1 obs. of 6 variables: 200s ..$ sampleName: chr NA 200s ..$ chromosome: int 1 200s ..$ start : num 1.42e+08 200s ..$ end : num 1.85e+08 200s ..$ nbrOfLoci : int 777 200s ..$ mean : num 0.0973 200s $ segRows:'data.frame': 1 obs. of 2 variables: 200s ..$ startRow: int 1 200s ..$ endRow : int 2677 200s $ params :List of 5 200s ..$ alpha : num 0.001 200s ..$ undo : num 0 200s ..$ joinSegments : logi TRUE 200s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 200s .. ..$ chromosome: int 1 200s .. ..$ start : num 1.42e+08 200s .. ..$ end : num 1.85e+08 200s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 200s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 200s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.005 0 0.005 0 0 200s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 200s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 200s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 200s DH segmentation (locally-indexed) rows: 200s startRow endRow 200s 1 1 2677 200s int [1:2681] 7587 7588 7589 7590 7591 7592 7593 7594 7595 7596 ... 200s DH segmentation rows: 200s startRow endRow 200s 1 7587 10263 200s Segmenting DH signals...done 200s DH segmentation table: 200s dhStart dhEnd dhNbrOfLoci dhMean 200s 1 141510003 185449813 777 0.0973 200s startRow endRow 200s 1 7587 10263 200s Rows: 200s [1] 3 200s TCN segmentation rows: 200s startRow endRow 200s 3 7587 10267 200s TCN and DH segmentation rows: 200s startRow endRow 200s 3 7587 10267 200s startRow endRow 200s 1 7587 10263 200s startRow endRow 200s 1 1 7586 200s 2 NA NA 200s TCN segmentation (expanded) rows: 200s startRow endRow 200s 1 1 7586 200s 2 NA NA 200s 3 7587 10267 200s TCN and DH segmentation rows: 200s startRow endRow 200s 1 1 7586 200s 2 NA NA 200s 3 7587 10267 200s 4 10268 14658 200s startRow endRow 200s 1 10 7574 200s 2 NA NA 200s 3 7587 10263 200s startRow endRow 200s 1 1 7586 200s 2 NA NA 200s 3 7587 10267 200s Total CN segmentation table (expanded): 200s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 200s 3 1 141510003 185449813 2681 2.0689 777 777 200s (TCN,DH) segmentation for one total CN segment: 200s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 200s 3 3 1 1 141510003 185449813 2681 2.0689 777 200s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 200s 3 777 141510003 185449813 777 0.0973 200s Total CN segment #3 ([1.4151e+08,1.8545e+08]) of 4...done 200s Total CN segment #4 ([1.8545e+08,2.47137e+08]) of 4... 200s Number of TCN loci in segment: 4391 200s Locus data for TCN segment: 200s 'data.frame': 4391 obs. of 9 variables: 200s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 200s $ x : num 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 200s $ CT : num 2.93 2.15 2.82 2.93 2.46 ... 200s $ betaT : num 0.0811 0.5154 0.9473 0.3734 0.7506 ... 200s $ betaTN : num -0.169 0.609 1.028 0.525 0.968 ... 200s $ betaN : num 0.25 0.38 0.919 0.34 0.783 ... 200s $ muN : num 0 0.5 1 0.5 1 1 0 1 0 1 ... 200s $ index : int 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 200s $ rho : num NA 0.2186 NA 0.0503 NA ... 200s Number of loci: 4391 200s Number of SNPs: 1311 (29.86%) 200s Number of heterozygous SNPs: 1311 (100.00%) 200s Chromosome: 1 200s Segmenting DH signals... 200s Segmenting by CBS... 200s Chromosome: 1 200s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 200s Segmenting by CBS...done 200s List of 4 200s $ data :'data.frame': 4391 obs. of 4 variables: 200s ..$ chromosome: int [1:4391] 1 1 1 1 1 1 1 1 1 1 ... 200s ..$ x : num [1:4391] 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 200s ..$ y : num [1:4391] NA 0.2186 NA 0.0503 NA ... 200s ..$ index : int [1:4391] 1 2 3 4 5 6 7 8 9 10 ... 200s $ output :'data.frame': 1 obs. of 6 variables: 200s ..$ sampleName: chr NA 200s ..$ chromosome: int 1 200s ..$ start : num 1.85e+08 200s ..$ end : num 2.47e+08 200s ..$ nbrOfLoci : int 1311 200s ..$ mean : num 0.23 200s $ segRows:'data.frame': 1 obs. of 2 variables: 200s ..$ startRow: int 2 200s ..$ endRow : int 4388 200s $ params :List of 5 200s ..$ alpha : num 0.001 200s ..$ undo : num 0 200s ..$ joinSegments : logi TRUE 200s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 200s .. ..$ chromosome: int 1 200s .. ..$ start : num 1.85e+08 200s .. ..$ end : num 2.47e+08 200s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 200s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 200s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.01 0 0.01 0 0 200s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 200s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 200s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 200s DH segmentation (locally-indexed) rows: 200s startRow endRow 200s 1 2 4388 200s int [1:4391] 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 200s DH segmentation rows: 200s startRow endRow 200s 1 10269 14655 200s Segmenting DH signals...done 200s DH segmentation table: 200s dhStart dhEnd dhNbrOfLoci dhMean 200s 1 185449813 247137334 1311 0.2295 200s startRow endRow 200s 1 10269 14655 200s Rows: 200s [1] 4 200s TCN segmentation rows: 200s startRow endRow 200s 4 10268 14658 200s TCN and DH segmentation rows: 200s startRow endRow 200s 4 10268 14658 200s startRow endRow 200s 1 10269 14655 200s startRow endRow 200s 1 1 7586 200s 2 NA NA 200s 3 7587 10267 200s TCN segmentation (expanded) rows: 200s startRow endRow 200s 1 1 7586 200s 2 NA NA 200s 3 7587 10267 200s 4 10268 14658 200s TCN and DH segmentation rows: 200s startRow endRow 200s 1 1 7586 200s 2 NA NA 200s 3 7587 10267 200s 4 10268 14658 200s startRow endRow 200s 1 10 7574 200s 2 NA NA 200s 3 7587 10263 200s 4 10269 14655 200s startRow endRow 200s 1 1 7586 200s 2 NA NA 200s 3 7587 10267 200s 4 10268 14658 200s Total CN segmentation table (expanded): 200s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 200s 4 1 185449813 247137334 4391 2.6341 1311 1311 200s (TCN,DH) segmentation for one total CN segment: 200s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 200s 4 4 1 1 185449813 247137334 4391 2.6341 1311 200s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 200s 4 1311 185449813 247137334 1311 0.2295 200s Total CN segment #4 ([1.8545e+08,2.47137e+08]) of 4...done 200s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 200s 1 1 1 1 554484 120992603 7586 1.3853 2108 200s 2 1 2 1 120992604 141510002 0 NA 0 200s 3 1 3 1 141510003 185449813 2681 2.0689 777 200s 4 1 4 1 185449813 247137334 4391 2.6341 1311 200s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 200s 1 2108 554484 120992603 2108 0.5116 200s 2 0 NA NA NA NA 200s 3 777 141510003 185449813 777 0.0973 200s 4 1311 185449813 247137334 1311 0.2295 200s Calculating (C1,C2) per segment... 200s Calculating (C1,C2) per segment...done 200s Number of segments: 4 200s Segmenting paired tumor-normal signals using Paired PSCBS...done 200s Post-segmenting TCNs... 200s Number of segments: 4 200s Number of chromosomes: 1 200s [1] 1 200s Chromosome 1 ('chr01') of 1... 200s Rows: 200s [1] 1 2 3 4 200s Number of segments: 4 200s TCN segment #1 ('1') of 4... 200s Nothing todo. Only one DH segmentation. Skipping. 200s TCN segment #1 ('1') of 4...done 200s TCN segment #2 ('2') of 4... 200s Nothing todo. Only one DH segmentation. Skipping. 200s TCN segment #2 ('2') of 4...done 200s TCN segment #3 ('3') of 4... 200s Nothing todo. Only one DH segmentation. Skipping. 200s TCN segment #3 ('3') of 4...done 200s TCN segment #4 ('4') of 4... 200s Nothing todo. Only one DH segmentation. Skipping. 200s TCN segment #4 ('4') of 4...done 200s Chromosome 1 ('chr01') of 1...done 200s Update (C1,C2) per segment... 200s Update (C1,C2) per segment...done 200s Post-segmenting TCNs...done 200s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 200s 1 1 1 1 554484 120992603 7586 1.3853 2108 200s 2 1 2 1 120992604 141510002 0 NA 0 200s 3 1 3 1 141510003 185449813 2681 2.0689 777 200s 4 1 4 1 185449813 247137334 4391 2.6341 1311 200s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 200s 1 2108 554484 120992603 2108 0.5116 0.3382903 1.047010 200s 2 0 NA NA NA NA NA NA 200s 3 777 141510003 185449813 777 0.0973 0.9337980 1.135102 200s 4 1311 185449813 247137334 1311 0.2295 1.0147870 1.619313 200s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 200s 1 1 1 1 554484 120992603 7586 1.3853 2108 200s 2 1 2 1 120992604 141510002 0 NA 0 200s 3 1 3 1 141510003 185449813 2681 2.0689 777 200s 4 1 4 1 185449813 247137334 4391 2.6341 1311 200s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 200s 1 2108 554484 120992603 2108 0.5116 0.3382903 1.047010 200s 2 0 NA NA NA NA NA NA 200s 3 777 141510003 185449813 777 0.0973 0.9337980 1.135102 200s 4 1311 185449813 247137334 1311 0.2295 1.0147870 1.619313 200s > print(fit) 200s chromosome tcnId dhId start end tcnNbrOfLoci tcnMean tcnNbrOfSNPs 200s 1 1 1 1 554484 120992603 7586 1.3853 2108 200s 2 1 2 1 120992604 141510002 0 NA 0 200s 3 1 3 1 141510003 185449813 2681 2.0689 777 200s 4 1 4 1 185449813 247137334 4391 2.6341 1311 200s tcnNbrOfHets dhNbrOfLoci dhMean c1Mean c2Mean 200s 1 2108 2108 0.5116 0.3382903 1.047010 200s 2 0 NA NA NA NA 200s 3 777 777 0.0973 0.9337980 1.135102 200s 4 1311 1311 0.2295 1.0147870 1.619313 200s > 200s > # Plot results 200s > dev.set(3L) 200s pdf 200s 2 200s > plotTracks(fit) 200s > abline(v=c(knownSegments$start, knownSegments$end)/1e6, lty=3) 200s > 200s > # Sanity check [TO FIX: See above] 200s > stopifnot(nbrOfSegments(fit) == nSegs) 200s > 200s > fit2 <- fit 200s > 200s > 200s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 200s > # (c) Do not segment the centromere (without a separator) 200s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 200s > knownSegments <- data.frame( 200s + chromosome = c( 1, 1), 200s + start = c( -Inf, 141510003), 200s + end = c(120992603, +Inf) 200s + ) 200s > 200s > # Paired PSCBS segmentation 200s > fit <- segmentByPairedPSCBS(dataS, knownSegments=knownSegments, 200s + seed=0xBEEF, verbose=-10) 200s Segmenting paired tumor-normal signals using Paired PSCBS... 200s Calling genotypes from normal allele B fractions... 200s num [1:14670] 0.8274 0.5072 0.1671 0.1609 0.0421 ... 200s Called genotypes: 200s num [1:14670] 1 0.5 0 0 0 0 1 0 1 0.5 ... 200s - attr(*, "modelFit")=List of 1 200s ..$ :List of 7 200s .. ..$ flavor : chr "density" 200s .. ..$ cn : int 2 200s .. ..$ nbrOfGenotypeGroups: int 3 200s .. ..$ tau : num [1:2] 0.315 0.677 200s .. ..$ n : int 14640 200s .. ..$ fit :Classes 'PeaksAndValleys' and 'data.frame': 5 obs. of 3 variables: 200s .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 200s .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 200s .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 200s .. ..$ fitValleys :Classes 'PeaksAndValleys' and 'data.frame': 2 obs. of 3 variables: 200s .. .. ..$ type : chr [1:2] "valley" "valley" 200s .. .. ..$ x : num [1:2] 0.315 0.677 200s .. .. ..$ density: num [1:2] 0.522 0.551 200s ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 200s muN 200s 0 0.5 1 200s 5221 4198 5251 200s Calling genotypes from normal allele B fractions...done 200s Normalizing betaT using betaN (TumorBoost)... 200s Normalized BAFs: 200s num [1:14670] 0.9301 0.1667 0.0685 0.0995 0.0155 ... 200s - attr(*, "modelFit")=List of 5 200s ..$ method : chr "normalizeTumorBoost" 200s ..$ flavor : chr "v4" 200s ..$ delta : num [1:14670] -0.17264 0.00239 0.1671 0.16085 0.04213 ... 200s .. ..- attr(*, "modelFit")=List of 1 200s .. .. ..$ :List of 7 200s .. .. .. ..$ flavor : chr "density" 200s .. .. .. ..$ cn : int 2 200s .. .. .. ..$ nbrOfGenotypeGroups: int 3 200s .. .. .. ..$ tau : num [1:2] 0.315 0.677 200s .. .. .. ..$ n : int 14640 200s .. .. .. ..$ fit :Classes 'PeaksAndValleys' and 'data.frame': 5 obs. of 3 variables: 200s .. .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 200s .. .. .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 200s .. .. .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 200s .. .. .. ..$ fitValleys :Classes 'PeaksAndValleys' and 'data.frame': 2 obs. of 3 variables: 200s .. .. .. .. ..$ type : chr [1:2] "valley" "valley" 200s .. .. .. .. ..$ x : num [1:2] 0.315 0.677 200s .. .. .. .. ..$ density: num [1:2] 0.522 0.551 200s .. .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 200s ..$ preserveScale: logi FALSE 200s ..$ scaleFactor : num NA 200s Normalizing betaT using betaN (TumorBoost)...done 200s Setup up data... 200s 'data.frame': 14670 obs. of 7 variables: 200s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 200s $ x : num 1145994 2941694 3710825 4240737 4276892 ... 200s $ CT : num 1.63 1.4 1.41 1.17 1.16 ... 200s $ betaT : num 0.7574 0.169 0.2357 0.2604 0.0576 ... 200s $ betaTN : num 0.9301 0.1667 0.0685 0.0995 0.0155 ... 200s ..- attr(*, "modelFit")=List of 5 200s .. ..$ method : chr "normalizeTumorBoost" 200s .. ..$ flavor : chr "v4" 200s .. ..$ delta : num [1:14670] -0.17264 0.00239 0.1671 0.16085 0.04213 ... 200s .. .. ..- attr(*, "modelFit")=List of 1 200s .. .. .. ..$ :List of 7 200s .. .. .. .. ..$ flavor : chr "density" 200s .. .. .. .. ..$ cn : int 2 200s .. .. .. .. ..$ nbrOfGenotypeGroups: int 3 200s .. .. .. .. ..$ tau : num [1:2] 0.315 0.677 200s .. .. .. .. ..$ n : int 14640 200s .. .. .. .. ..$ fit :Classes 'PeaksAndValleys' and 'data.frame': 5 obs. of 3 variables: 200s .. .. .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 200s .. .. .. .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 200s .. .. .. .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 200s .. .. .. .. ..$ fitValleys :Classes 'PeaksAndValleys' and 'data.frame': 2 obs. of 3 variables: 200s .. .. .. .. .. ..$ type : chr [1:2] "valley" "valley" 200s .. .. .. .. .. ..$ x : num [1:2] 0.315 0.677 200s .. .. .. .. .. ..$ density: num [1:2] 0.522 0.551 200s .. .. .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 200s .. ..$ preserveScale: logi FALSE 200s .. ..$ scaleFactor : num NA 200s $ betaN : num 0.8274 0.5072 0.1671 0.1609 0.0421 ... 200s $ muN : num 1 0.5 0 0 0 0 1 0 1 0.5 ... 200s ..- attr(*, "modelFit")=List of 1 200s .. ..$ :List of 7 200s .. .. ..$ flavor : chr "density" 200s .. .. ..$ cn : int 2 200s .. .. ..$ nbrOfGenotypeGroups: int 3 200s .. .. ..$ tau : num [1:2] 0.315 0.677 200s .. .. ..$ n : int 14640 200s .. .. ..$ fit :Classes 'PeaksAndValleys' and 'data.frame': 5 obs. of 3 variables: 200s .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 200s .. .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 200s .. .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 200s .. .. ..$ fitValleys :Classes 'PeaksAndValleys' and 'data.frame': 2 obs. of 3 variables: 200s .. .. .. ..$ type : chr [1:2] "valley" "valley" 200s .. .. .. ..$ x : num [1:2] 0.315 0.677 200s .. .. .. ..$ density: num [1:2] 0.522 0.551 200s .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 200s Setup up data...done 200s Dropping loci for which TCNs are missing... 200s Number of loci dropped: 12 200s Dropping loci for which TCNs are missing...done 200s Ordering data along genome... 200s 'data.frame': 14658 obs. of 7 variables: 200s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 200s $ x : num 554484 730720 782343 878522 916294 ... 200s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 200s $ betaT : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 200s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 200s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 200s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 200s Ordering data along genome...done 200s Keeping only current chromosome for 'knownSegments'... 200s Chromosome: 1 200s Known segments for this chromosome: 200s chromosome start end 200s 1 1 -Inf 120992603 200s 2 1 141510003 Inf 200s Keeping only current chromosome for 'knownSegments'...done 200s alphaTCN: 0.009 200s alphaDH: 0.001 200s Number of loci: 14658 200s Calculating DHs... 200s Number of SNPs: 14658 200s Number of heterozygous SNPs: 4196 (28.63%) 200s Normalized DHs: 200s num [1:14658] NA NA NA NA NA ... 200s Calculating DHs...done 200s Random seed temporarily set (seed=c(48879), kind="L'Ecuyer-CMRG") 200s Produced 2 seeds from this stream for future usage 200s Identification of change points by total copy numbers... 200s Segmenting by CBS... 200s Chromosome: 1 200s Segmenting multiple segments on current chromosome... 200s Number of segments: 2 200s Random seed temporarily set (seed=c(10407, 1066287653, -51199871, 161854402, -1995183193, 1503453565, -747102133), kind="L'Ecuyer-CMRG") 200s Produced 2 seeds from this stream for future usage 200s Segmenting by CBS... 200s Chromosome: 1 200s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 200s Segmenting by CBS...done 200s Segmenting by CBS... 200s Chromosome: 1 200s Random seed temporarily set (seed=c(10407, -821273412, -52578226, 1415511586, 721384351, -665928286, 1316562960), kind="L'Ecuyer-CMRG") 200s Segmenting by CBS...done 200s Segmenting multiple segments on current chromosome...done 200s Segmenting by CBS...done 200s List of 4 200s $ data :'data.frame': 14658 obs. of 4 variables: 200s ..$ chromosome: int [1:14658] 1 1 1 1 1 1 1 1 1 1 ... 200s ..$ x : num [1:14658] 554484 730720 782343 878522 916294 ... 200s ..$ y : num [1:14658] 1.88 1.8 1.59 1.64 1.53 ... 200s ..$ index : int [1:14658] 1 2 3 4 5 6 7 8 9 10 ... 200s $ output :'data.frame': 3 obs. of 6 variables: 200s ..$ sampleName: chr [1:3] NA NA NA 200s ..$ chromosome: int [1:3] 1 1 1 200s ..$ start : num [1:3] 5.54e+05 1.42e+08 1.85e+08 200s ..$ end : num [1:3] 1.21e+08 1.85e+08 2.47e+08 200s ..$ nbrOfLoci : int [1:3] 7586 2681 4391 200s ..$ mean : num [1:3] 1.39 2.07 2.63 200s $ segRows:'data.frame': 3 obs. of 2 variables: 200s ..$ startRow: int [1:3] 1 7587 10268 200s ..$ endRow : int [1:3] 7586 10267 14658 200s $ params :List of 5 200s ..$ alpha : num 0.009 200s ..$ undo : num 0 200s ..$ joinSegments : logi TRUE 200s ..$ knownSegments:'data.frame': 2 obs. of 3 variables: 200s .. ..$ chromosome: num [1:2] 1 1 200s .. ..$ start : num [1:2] -Inf 1.42e+08 200s .. ..$ end : num [1:2] 1.21e+08 Inf 200s ..$ seed : int [1:7] 10407 1066287653 -51199871 161854402 -1995183193 1503453565 -747102133 200s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 200s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.088 0 0.089 0 0 200s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 200s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 200s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 200s Identification of change points by total copy numbers...done 200s Restructure TCN segmentation results... 200s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean 200s 1 1 554484 120992603 7586 1.3853 200s 2 1 141510003 185449813 2681 2.0689 200s 3 1 185449813 247137334 4391 2.6341 200s Number of TCN segments: 3 200s Restructure TCN segmentation results...done 200s Total CN segment #1 ([ 554484,1.20993e+08]) of 3... 200s Number of TCN loci in segment: 7586 200s Locus data for TCN segment: 200s 'data.frame': 7586 obs. of 9 variables: 200s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 200s $ x : num 554484 730720 782343 878522 916294 ... 200s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 200s $ betaT : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 200s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 200s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 200s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 200s $ index : int 1 2 3 4 5 6 7 8 9 10 ... 200s $ rho : num NA NA NA NA NA ... 200s Number of loci: 7586 200s Number of SNPs: 2108 (27.79%) 200s Number of heterozygous SNPs: 2108 (100.00%) 200s Chromosome: 1 200s Segmenting DH signals... 200s Segmenting by CBS... 200s Chromosome: 1 200s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 200s Segmenting by CBS...done 200s List of 4 200s $ data :'data.frame': 7586 obs. of 4 variables: 200s ..$ chromosome: int [1:7586] 1 1 1 1 1 1 1 1 1 1 ... 200s ..$ x : num [1:7586] 554484 730720 782343 878522 916294 ... 200s ..$ y : num [1:7586] NA NA NA NA NA ... 200s ..$ index : int [1:7586] 1 2 3 4 5 6 7 8 9 10 ... 200s $ output :'data.frame': 1 obs. of 6 variables: 200s ..$ sampleName: chr NA 200s ..$ chromosome: int 1 200s ..$ start : num 554484 200s ..$ end : num 1.21e+08 200s ..$ nbrOfLoci : int 2108 200s ..$ mean : num 0.512 200s $ segRows:'data.frame': 1 obs. of 2 variables: 200s ..$ startRow: int 10 200s ..$ endRow : int 7574 200s $ params :List of 5 200s ..$ alpha : num 0.001 200s ..$ undo : num 0 200s ..$ joinSegments : logi TRUE 200s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 200s .. ..$ chromosome: int 1 200s .. ..$ start : num 554484 200s .. ..$ end : num 1.21e+08 200s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 200s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 200s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.026 0 0.026 0 0 200s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 200s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 200s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 200s DH segmentation (locally-indexed) rows: 200s startRow endRow 200s 1 10 7574 200s int [1:7586] 1 2 3 4 5 6 7 8 9 10 ... 200s DH segmentation rows: 200s startRow endRow 200s 1 10 7574 200s Segmenting DH signals...done 200s DH segmentation table: 200s dhStart dhEnd dhNbrOfLoci dhMean 200s 1 554484 120992603 2108 0.5116 200s startRow endRow 200s 1 10 7574 200s Rows: 200s [1] 1 200s TCN segmentation rows: 200s startRow endRow 200s 1 1 7586 200s TCN and DH segmentation rows: 200s startRow endRow 200s 1 1 7586 200s startRow endRow 200s 1 10 7574 200s NULL 200s TCN segmentation (expanded) rows: 200s startRow endRow 200s 1 1 7586 200s TCN and DH segmentation rows: 200s startRow endRow 200s 1 1 7586 200s 2 7587 10267 200s 3 10268 14658 200s startRow endRow 200s 1 10 7574 200s startRow endRow 200s 1 1 7586 200s Total CN segmentation table (expanded): 200s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 200s 1 1 554484 120992603 7586 1.3853 2108 2108 200s (TCN,DH) segmentation for one total CN segment: 200s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 200s 1 1 1 1 554484 120992603 7586 1.3853 2108 200s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 200s 1 2108 554484 120992603 2108 0.5116 200s Total CN segment #1 ([ 554484,1.20993e+08]) of 3...done 200s Total CN segment #2 ([1.4151e+08,1.8545e+08]) of 3... 200s Number of TCN loci in segment: 2681 200s Locus data for TCN segment: 200s 'data.frame': 2681 obs. of 9 variables: 200s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 200s $ x : num 1.43e+08 1.43e+08 1.43e+08 1.43e+08 1.44e+08 ... 200s $ CT : num 2.27 1.55 1.47 1.5 1.81 ... 200s $ betaT : num 0.34 0.55 0.048 0.813 0.575 ... 200s $ betaTN : num 0.441 0.629 -0.05 0.958 0.872 ... 200s $ betaN : num 0.3851 0.3933 0.0981 0.8552 0.7028 ... 200s $ muN : num 0.5 0.5 0 1 1 1 1 0.5 1 1 ... 200s $ index : int 7587 7588 7589 7590 7591 7592 7593 7594 7595 7596 ... 200s $ rho : num 0.117 0.258 NA NA NA ... 200s Number of loci: 2681 200s Number of SNPs: 777 (28.98%) 200s Number of heterozygous SNPs: 777 (100.00%) 200s Chromosome: 1 200s Segmenting DH signals... 200s Segmenting by CBS... 200s Chromosome: 1 200s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 200s Segmenting by CBS...done 200s List of 4 200s $ data :'data.frame': 2681 obs. of 4 variables: 200s ..$ chromosome: int [1:2681] 1 1 1 1 1 1 1 1 1 1 ... 200s ..$ x : num [1:2681] 1.43e+08 1.43e+08 1.43e+08 1.43e+08 1.44e+08 ... 200s ..$ y : num [1:2681] 0.117 0.258 NA NA NA ... 200s ..$ index : int [1:2681] 1 2 3 4 5 6 7 8 9 10 ... 200s $ output :'data.frame': 1 obs. of 6 variables: 200s ..$ sampleName: chr NA 200s ..$ chromosome: int 1 200s ..$ start : num 1.42e+08 200s ..$ end : num 1.85e+08 200s ..$ nbrOfLoci : int 777 200s ..$ mean : num 0.0973 200s $ segRows:'data.frame': 1 obs. of 2 variables: 200s ..$ startRow: int 1 200s ..$ endRow : int 2677 200s $ params :List of 5 200s ..$ alpha : num 0.001 200s ..$ undo : num 0 200s ..$ joinSegments : logi TRUE 200s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 200s .. ..$ chromosome: int 1 200s .. ..$ start : num 1.42e+08 200s .. ..$ end : num 1.85e+08 200s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 200s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 200s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.005 0 0.005 0 0 200s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 200s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 200s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 200s DH segmentation (locally-indexed) rows: 200s startRow endRow 200s 1 1 2677 200s int [1:2681] 7587 7588 7589 7590 7591 7592 7593 7594 7595 7596 ... 200s DH segmentation rows: 200s startRow endRow 200s 1 7587 10263 200s Segmenting DH signals...done 200s DH segmentation table: 200s dhStart dhEnd dhNbrOfLoci dhMean 200s 1 141510003 185449813 777 0.0973 200s startRow endRow 200s 1 7587 10263 200s Rows: 200s [1] 2 200s TCN segmentation rows: 200s startRow endRow 200s 2 7587 10267 200s TCN and DH segmentation rows: 200s startRow endRow 200s 2 7587 10267 200s startRow endRow 200s 1 7587 10263 200s startRow endRow 200s 1 1 7586 200s TCN segmentation (expanded) rows: 200s startRow endRow 200s 1 1 7586 200s 2 7587 10267 200s TCN and DH segmentation rows: 200s startRow endRow 200s 1 1 7586 200s 2 7587 10267 200s 3 10268 14658 200s startRow endRow 200s 1 10 7574 200s 2 7587 10263 200s startRow endRow 200s 1 1 7586 200s 2 7587 10267 200s Total CN segmentation table (expanded): 200s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 200s 2 1 141510003 185449813 2681 2.0689 777 777 200s (TCN,DH) segmentation for one total CN segment: 200s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 200s 2 2 1 1 141510003 185449813 2681 2.0689 777 200s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 200s 2 777 141510003 185449813 777 0.0973 200s Total CN segment #2 ([1.4151e+08,1.8545e+08]) of 3...done 200s Total CN segment #3 ([1.8545e+08,2.47137e+08]) of 3... 200s Number of TCN loci in segment: 4391 200s Locus data for TCN segment: 200s 'data.frame': 4391 obs. of 9 variables: 200s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 200s $ x : num 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 200s $ CT : num 2.93 2.15 2.82 2.93 2.46 ... 200s $ betaT : num 0.0811 0.5154 0.9473 0.3734 0.7506 ... 200s $ betaTN : num -0.169 0.609 1.028 0.525 0.968 ... 200s $ betaN : num 0.25 0.38 0.919 0.34 0.783 ... 200s $ muN : num 0 0.5 1 0.5 1 1 0 1 0 1 ... 200s $ index : int 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 200s $ rho : num NA 0.2186 NA 0.0503 NA ... 200s Number of loci: 4391 200s Number of SNPs: 1311 (29.86%) 200s Number of heterozygous SNPs: 1311 (100.00%) 200s Chromosome: 1 200s Segmenting DH signals... 200s Segmenting by CBS... 200s Chromosome: 1 200s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 200s Segmenting by CBS...done 200s List of 4 200s $ data :'data.frame': 4391 obs. of 4 variables: 200s ..$ chromosome: int [1:4391] 1 1 1 1 1 1 1 1 1 1 ... 200s ..$ x : num [1:4391] 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 200s ..$ y : num [1:4391] NA 0.2186 NA 0.0503 NA ... 200s ..$ index : int [1:4391] 1 2 3 4 5 6 7 8 9 10 ... 200s $ output :'data.frame': 1 obs. of 6 variables: 200s ..$ sampleName: chr NA 200s ..$ chromosome: int 1 200s ..$ start : num 1.85e+08 200s ..$ end : num 2.47e+08 200s ..$ nbrOfLoci : int 1311 200s ..$ mean : num 0.23 200s $ segRows:'data.frame': 1 obs. of 2 variables: 200s ..$ startRow: int 2 200s ..$ endRow : int 4388 200s $ params :List of 5 200s ..$ alpha : num 0.001 200s ..$ undo : num 0 200s ..$ joinSegments : logi TRUE 200s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 200s .. ..$ chromosome: int 1 200s .. ..$ start : num 1.85e+08 200s .. ..$ end : num 2.47e+08 200s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 200s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 200s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.01 0 0.01 0 0 200s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 200s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 200s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 200s DH segmentation (locally-indexed) rows: 200s startRow endRow 200s 1 2 4388 200s int [1:4391] 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 200s DH segmentation rows: 200s startRow endRow 200s 1 10269 14655 200s Segmenting DH signals...done 200s DH segmentation table: 200s dhStart dhEnd dhNbrOfLoci dhMean 200s 1 185449813 247137334 1311 0.2295 200s startRow endRow 200s 1 10269 14655 200s Rows: 200s [1] 3 200s TCN segmentation rows: 200s startRow endRow 200s 3 10268 14658 200s TCN and DH segmentation rows: 200s startRow endRow 200s 3 10268 14658 200s startRow endRow 200s 1 10269 14655 200s startRow endRow 200s 1 1 7586 200s 2 7587 10267 200s TCN segmentation (expanded) rows: 200s startRow endRow 200s 1 1 7586 200s 2 7587 10267 200s 3 10268 14658 200s TCN and DH segmentation rows: 200s startRow endRow 200s 1 1 7586 200s 2 7587 10267 200s 3 10268 14658 200s startRow endRow 200s 1 10 7574 200s 2 7587 10263 200s 3 10269 14655 200s startRow endRow 200s 1 1 7586 200s 2 7587 10267 200s 3 10268 14658 200s Total CN segmentation table (expanded): 200s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 200s 3 1 185449813 247137334 4391 2.6341 1311 1311 200s (TCN,DH) segmentation for one total CN segment: 200s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 200s 3 3 1 1 185449813 247137334 4391 2.6341 1311 200s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 200s 3 1311 185449813 247137334 1311 0.2295 200s Total CN segment #3 ([1.8545e+08,2.47137e+08]) of 3...done 200s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 200s 1 1 1 1 554484 120992603 7586 1.3853 2108 200s 2 1 2 1 141510003 185449813 2681 2.0689 777 200s 3 1 3 1 185449813 247137334 4391 2.6341 1311 200s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 200s 1 2108 554484 120992603 2108 0.5116 200s 2 777 141510003 185449813 777 0.0973 200s 3 1311 185449813 247137334 1311 0.2295 200s Calculating (C1,C2) per segment... 200s Calculating (C1,C2) per segment...done 200s Number of segments: 3 200s Segmenting paired tumor-normal signals using Paired PSCBS...done 200s Post-segmenting TCNs... 200s Number of segments: 3 200s Number of chromosomes: 1 200s [1] 1 200s Chromosome 1 ('chr01') of 1... 200s Rows: 200s [1] 1 2 3 200s Number of segments: 3 200s TCN segment #1 ('1') of 3... 200s Nothing todo. Only one DH segmentation. Skipping. 200s TCN segment #1 ('1') of 3...done 200s TCN segment #2 ('2') of 3... 200s Nothing todo. Only one DH segmentation. Skipping. 200s TCN segment #2 ('2') of 3...done 200s TCN segment #3 ('3') of 3... 200s Nothing todo. Only one DH segmentation. Skipping. 200s TCN segment #3 ('3') of 3...done 200s Chromosome 1 ('chr01') of 1...done 200s Update (C1,C2) per segment... 200s Update (C1,C2) per segment...done 200s Post-segmenting TCNs...done 200s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 200s 1 1 1 1 554484 120992603 7586 1.3853 2108 200s 2 1 2 1 141510003 185449813 2681 2.0689 777 200s 3 1 3 1 185449813 247137334 4391 2.6341 1311 200s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 200s 1 2108 554484 120992603 2108 0.5116 0.3382903 1.047010 200s 2 777 141510003 185449813 777 0.0973 0.9337980 1.135102 200s 3 1311 185449813 247137334 1311 0.2295 1.0147870 1.619313 200s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 200s 1 1 1 1 554484 120992603 7586 1.3853 2108 200s 2 1 2 1 141510003 185449813 2681 2.0689 777 200s 3 1 3 1 185449813 247137334 4391 2.6341 1311 200s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 200s 1 2108 554484 120992603 2108 0.5116 0.3382903 1.047010 200s 2 777 141510003 185449813 777 0.0973 0.9337980 1.135102 200s 3 1311 185449813 247137334 1311 0.2295 1.0147870 1.619313 200s > print(fit) 200s chromosome tcnId dhId start end tcnNbrOfLoci tcnMean tcnNbrOfSNPs 200s 1 1 1 1 554484 120992603 7586 1.3853 2108 200s 2 1 2 1 141510003 185449813 2681 2.0689 777 200s 3 1 3 1 185449813 247137334 4391 2.6341 1311 200s tcnNbrOfHets dhNbrOfLoci dhMean c1Mean c2Mean 200s 1 2108 2108 0.5116 0.3382903 1.047010 200s 2 777 777 0.0973 0.9337980 1.135102 200s 3 1311 1311 0.2295 1.0147870 1.619313 200s > 200s > # Plot results 200s > dev.set(4L) 200s pdf 200s 2 200s > plotTracks(fit) 200s > abline(v=c(knownSegments$start, knownSegments$end)/1e6, lty=3) 200s > 200s > # Sanity check 200s > stopifnot(nbrOfSegments(fit) == nSegs-1L) 200s > 200s > fit3 <- fit 200s > 200s > 200s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 200s > # (d) Skip the identification of new change points 200s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 200s > knownSegments <- data.frame( 200s + chromosome = c( 1, 1), 200s + start = c( -Inf, 141510003), 200s + end = c(120992603, +Inf) 200s + ) 200s > 200s > # Paired PSCBS segmentation 200s > fit <- segmentByPairedPSCBS(dataS, knownSegments=knownSegments, 200s + undoTCN=Inf, undoDH=Inf, 200s + seed=0xBEEF, verbose=-10) 200s Segmenting paired tumor-normal signals using Paired PSCBS... 200s Calling genotypes from normal allele B fractions... 200s num [1:14670] 0.8274 0.5072 0.1671 0.1609 0.0421 ... 200s Called genotypes: 200s num [1:14670] 1 0.5 0 0 0 0 1 0 1 0.5 ... 200s - attr(*, "modelFit")=List of 1 200s ..$ :List of 7 200s .. ..$ flavor : chr "density" 200s .. ..$ cn : int 2 200s .. ..$ nbrOfGenotypeGroups: int 3 200s .. ..$ tau : num [1:2] 0.315 0.677 200s .. ..$ n : int 14640 200s .. ..$ fit :Classes 'PeaksAndValleys' and 'data.frame': 5 obs. of 3 variables: 200s .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 200s .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 200s .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 200s .. ..$ fitValleys :Classes 'PeaksAndValleys' and 'data.frame': 2 obs. of 3 variables: 200s .. .. ..$ type : chr [1:2] "valley" "valley" 200s .. .. ..$ x : num [1:2] 0.315 0.677 200s .. .. ..$ density: num [1:2] 0.522 0.551 200s ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 200s muN 200s 0 0.5 1 200s 5221 4198 5251 200s Calling genotypes from normal allele B fractions...done 200s Normalizing betaT using betaN (TumorBoost)... 200s Normalized BAFs: 200s num [1:14670] 0.9301 0.1667 0.0685 0.0995 0.0155 ... 200s - attr(*, "modelFit")=List of 5 200s ..$ method : chr "normalizeTumorBoost" 200s ..$ flavor : chr "v4" 200s ..$ delta : num [1:14670] -0.17264 0.00239 0.1671 0.16085 0.04213 ... 200s .. ..- attr(*, "modelFit")=List of 1 200s .. .. ..$ :List of 7 200s .. .. .. ..$ flavor : chr "density" 200s .. .. .. ..$ cn : int 2 200s .. .. .. ..$ nbrOfGenotypeGroups: int 3 200s .. .. .. ..$ tau : num [1:2] 0.315 0.677 200s .. .. .. ..$ n : int 14640 200s .. .. .. ..$ fit :Classes 'PeaksAndValleys' and 'data.frame': 5 obs. of 3 variables: 200s .. .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 200s .. .. .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 200s .. .. .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 200s .. .. .. ..$ fitValleys :Classes 'PeaksAndValleys' and 'data.frame': 2 obs. of 3 variables: 200s .. .. .. .. ..$ type : chr [1:2] "valley" "valley" 200s .. .. .. .. ..$ x : num [1:2] 0.315 0.677 200s .. .. .. .. ..$ density: num [1:2] 0.522 0.551 200s .. .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 200s ..$ preserveScale: logi FALSE 200s ..$ scaleFactor : num NA 200s Normalizing betaT using betaN (TumorBoost)...done 200s Setup up data... 200s 'data.frame': 14670 obs. of 7 variables: 200s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 200s $ x : num 1145994 2941694 3710825 4240737 4276892 ... 200s $ CT : num 1.63 1.4 1.41 1.17 1.16 ... 200s $ betaT : num 0.7574 0.169 0.2357 0.2604 0.0576 ... 200s $ betaTN : num 0.9301 0.1667 0.0685 0.0995 0.0155 ... 200s ..- attr(*, "modelFit")=List of 5 200s .. ..$ method : chr "normalizeTumorBoost" 200s .. ..$ flavor : chr "v4" 200s .. ..$ delta : num [1:14670] -0.17264 0.00239 0.1671 0.16085 0.04213 ... 200s .. .. ..- attr(*, "modelFit")=List of 1 200s .. .. .. ..$ :List of 7 200s .. .. .. .. ..$ flavor : chr "density" 200s .. .. .. .. ..$ cn : int 2 200s .. .. .. .. ..$ nbrOfGenotypeGroups: int 3 200s .. .. .. .. ..$ tau : num [1:2] 0.315 0.677 200s .. .. .. .. ..$ n : int 14640 200s .. .. .. .. ..$ fit :Classes 'PeaksAndValleys' and 'data.frame': 5 obs. of 3 variables: 200s .. .. .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 200s .. .. .. .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 200s .. .. .. .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 200s .. .. .. .. ..$ fitValleys :Classes 'PeaksAndValleys' and 'data.frame': 2 obs. of 3 variables: 200s .. .. .. .. .. ..$ type : chr [1:2] "valley" "valley" 200s .. .. .. .. .. ..$ x : num [1:2] 0.315 0.677 200s .. .. .. .. .. ..$ density: num [1:2] 0.522 0.551 200s .. .. .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 200s .. ..$ preserveScale: logi FALSE 200s .. ..$ scaleFactor : num NA 200s $ betaN : num 0.8274 0.5072 0.1671 0.1609 0.0421 ... 200s $ muN : num 1 0.5 0 0 0 0 1 0 1 0.5 ... 200s ..- attr(*, "modelFit")=List of 1 200s .. ..$ :List of 7 200s .. .. ..$ flavor : chr "density" 200s .. .. ..$ cn : int 2 200s .. .. ..$ nbrOfGenotypeGroups: int 3 200s .. .. ..$ tau : num [1:2] 0.315 0.677 200s .. .. ..$ n : int 14640 200s .. .. ..$ fit :Classes 'PeaksAndValleys' and 'data.frame': 5 obs. of 3 variables: 200s .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 200s .. .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 200s .. .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 200s .. .. ..$ fitValleys :Classes 'PeaksAndValleys' and 'data.frame': 2 obs. of 3 variables: 200s .. .. .. ..$ type : chr [1:2] "valley" "valley" 200s .. .. .. ..$ x : num [1:2] 0.315 0.677 200s .. .. .. ..$ density: num [1:2] 0.522 0.551 200s .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 200s Setup up data...done 200s Dropping loci for which TCNs are missing... 200s Number of loci dropped: 12 200s Dropping loci for which TCNs are missing...done 200s Ordering data along genome... 200s 'data.frame': 14658 obs. of 7 variables: 200s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 200s $ x : num 554484 730720 782343 878522 916294 ... 200s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 200s $ betaT : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 200s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 200s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 200s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 200s Ordering data along genome...done 200s Keeping only current chromosome for 'knownSegments'... 200s Chromosome: 1 200s Known segments for this chromosome: 200s chromosome start end 200s 1 1 -Inf 120992603 200s 2 1 141510003 Inf 200s Keeping only current chromosome for 'knownSegments'...done 200s alphaTCN: 0.009 200s alphaDH: 0.001 200s Number of loci: 14658 200s Calculating DHs... 200s Number of SNPs: 14658 200s Number of heterozygous SNPs: 4196 (28.63%) 200s Normalized DHs: 200s num [1:14658] NA NA NA NA NA ... 200s Calculating DHs...done 200s Random seed temporarily set (seed=c(48879), kind="L'Ecuyer-CMRG") 200s Produced 2 seeds from this stream for future usage 200s Identification of change points by total copy numbers... 200s Segmenting by CBS... 200s Chromosome: 1 200s Segmenting multiple segments on current chromosome... 200s Number of segments: 2 200s Random seed temporarily set (seed=c(10407, 1066287653, -51199871, 161854402, -1995183193, 1503453565, -747102133), kind="L'Ecuyer-CMRG") 200s Produced 2 seeds from this stream for future usage 200s Segmenting by CBS... 200s Chromosome: 1 200s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 200s Segmenting by CBS...done 200s Segmenting by CBS... 200s Chromosome: 1 200s Random seed temporarily set (seed=c(10407, -821273412, -52578226, 1415511586, 721384351, -665928286, 1316562960), kind="L'Ecuyer-CMRG") 200s Segmenting by CBS...done 200s Segmenting multiple segments on current chromosome...done 200s Segmenting by CBS...done 200s List of 4 200s $ data :'data.frame': 14658 obs. of 4 variables: 200s ..$ chromosome: int [1:14658] 1 1 1 1 1 1 1 1 1 1 ... 200s ..$ x : num [1:14658] 554484 730720 782343 878522 916294 ... 200s ..$ y : num [1:14658] 1.88 1.8 1.59 1.64 1.53 ... 200s ..$ index : int [1:14658] 1 2 3 4 5 6 7 8 9 10 ... 200s $ output :'data.frame': 2 obs. of 6 variables: 200s ..$ sampleName: chr [1:2] NA NA 200s ..$ chromosome: num [1:2] 1 1 200s ..$ start : num [1:2] 5.54e+05 1.42e+08 200s ..$ end : num [1:2] 1.21e+08 2.47e+08 200s ..$ nbrOfLoci : int [1:2] 7586 7072 200s ..$ mean : num [1:2] 1.39 2.42 200s $ segRows:'data.frame': 2 obs. of 2 variables: 200s ..$ startRow: int [1:2] 1 7587 200s ..$ endRow : int [1:2] 7586 14658 200s $ params :List of 7 200s ..$ undo.splits : chr "sdundo" 200s ..$ undo.SD : num Inf 200s ..$ alpha : num 0.009 200s ..$ undo : num Inf 200s ..$ joinSegments : logi TRUE 200s ..$ knownSegments:'data.frame': 2 obs. of 3 variables: 200s .. ..$ chromosome: num [1:2] 1 1 200s .. ..$ start : num [1:2] -Inf 1.42e+08 200s .. ..$ end : num [1:2] 1.21e+08 Inf 200s ..$ seed : int [1:7] 10407 1066287653 -51199871 161854402 -1995183193 1503453565 -747102133 200s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 200s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.001 0 0.001 0 0 200s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 200s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 200s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 200s Identification of change points by total copy numbers...done 200s Restructure TCN segmentation results... 200s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean 200s 1 1 554484 120992603 7586 1.385258 200s 2 1 141510003 247137334 7072 2.419824 200s Number of TCN segments: 2 200s Restructure TCN segmentation results...done 200s Total CN segment #1 ([ 554484,1.20993e+08]) of 2... 200s Number of TCN loci in segment: 7586 200s Locus data for TCN segment: 200s 'data.frame': 7586 obs. of 9 variables: 200s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 200s $ x : num 554484 730720 782343 878522 916294 ... 200s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 200s $ betaT : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 200s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 200s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 200s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 200s $ index : int 1 2 3 4 5 6 7 8 9 10 ... 200s $ rho : num NA NA NA NA NA ... 200s Number of loci: 7586 200s Number of SNPs: 2108 (27.79%) 200s Number of heterozygous SNPs: 2108 (100.00%) 200s Chromosome: 1 200s Segmenting DH signals... 200s Segmenting by CBS... 200s Chromosome: 1 200s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 200s Segmenting by CBS...done 200s List of 4 200s $ data :'data.frame': 7586 obs. of 4 variables: 200s ..$ chromosome: int [1:7586] 1 1 1 1 1 1 1 1 1 1 ... 200s ..$ x : num [1:7586] 554484 730720 782343 878522 916294 ... 200s ..$ y : num [1:7586] NA NA NA NA NA ... 200s ..$ index : int [1:7586] 1 2 3 4 5 6 7 8 9 10 ... 200s $ output :'data.frame': 1 obs. of 6 variables: 200s ..$ sampleName: chr NA 200s ..$ chromosome: int 1 200s ..$ start : num 554484 200s ..$ end : num 1.21e+08 200s ..$ nbrOfLoci : int 7586 200s ..$ mean : num 0.512 200s $ segRows:'data.frame': 1 obs. of 2 variables: 200s ..$ startRow: int 1 200s ..$ endRow : int 7586 200s $ params :List of 7 200s ..$ undo.splits : chr "sdundo" 200s ..$ undo.SD : num Inf 200s ..$ alpha : num 0.001 200s ..$ undo : num Inf 200s ..$ joinSegments : logi TRUE 200s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 200s .. ..$ chromosome: int 1 200s .. ..$ start : num 554484 200s .. ..$ end : num 1.21e+08 200s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 200s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 200s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.001 0 0.001 0 0 200s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 200s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 200s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 200s DH segmentation (locally-indexed) rows: 200s startRow endRow 200s 1 1 7586 200s int [1:7586] 1 2 3 4 5 6 7 8 9 10 ... 200s DH segmentation rows: 200s startRow endRow 200s 1 1 7586 200s Segmenting DH signals...done 200s DH segmentation table: 200s dhStart dhEnd dhNbrOfLoci dhMean 200s 1 554484 120992603 7586 0.511612 200s startRow endRow 200s 1 1 7586 200s Rows: 200s [1] 1 200s TCN segmentation rows: 200s startRow endRow 200s 1 1 7586 200s TCN and DH segmentation rows: 200s startRow endRow 200s 1 1 7586 200s startRow endRow 200s 1 1 7586 200s NULL 200s TCN segmentation (expanded) rows: 200s startRow endRow 200s 1 1 7586 200s TCN and DH segmentation rows: 200s startRow endRow 200s 1 1 7586 200s 2 7587 14658 200s startRow endRow 200s 1 1 7586 200s startRow endRow 200s 1 1 7586 200s Total CN segmentation table (expanded): 200s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 200s 1 1 554484 120992603 7586 1.385258 2108 2108 200s (TCN,DH) segmentation for one total CN segment: 200s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 200s 1 1 1 1 554484 120992603 7586 1.385258 2108 200s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 200s 1 2108 554484 120992603 7586 0.511612 200s Total CN segment #1 ([ 554484,1.20993e+08]) of 2...done 200s Total CN segment #2 ([1.4151e+08,2.47137e+08]) of 2... 200s Number of TCN loci in segment: 7072 200s Locus data for TCN segment: 200s 'data.frame': 7072 obs. of 9 variables: 200s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 200s $ x : num 1.43e+08 1.43e+08 1.43e+08 1.43e+08 1.44e+08 ... 200s $ CT : num 2.27 1.55 1.47 1.5 1.81 ... 200s $ betaT : num 0.34 0.55 0.048 0.813 0.575 ... 200s $ betaTN : num 0.441 0.629 -0.05 0.958 0.872 ... 200s $ betaN : num 0.3851 0.3933 0.0981 0.8552 0.7028 ... 200s $ muN : num 0.5 0.5 0 1 1 1 1 0.5 1 1 ... 200s $ index : int 7587 7588 7589 7590 7591 7592 7593 7594 7595 7596 ... 200s $ rho : num 0.117 0.258 NA NA NA ... 200s Number of loci: 7072 200s Number of SNPs: 2088 (29.52%) 200s Number of heterozygous SNPs: 2088 (100.00%) 200s Chromosome: 1 200s Segmenting DH signals... 200s Segmenting by CBS... 200s Chromosome: 1 200s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 200s Segmenting by CBS...done 200s List of 4 200s $ data :'data.frame': 7072 obs. of 4 variables: 200s ..$ chromosome: int [1:7072] 1 1 1 1 1 1 1 1 1 1 ... 200s ..$ x : num [1:7072] 1.43e+08 1.43e+08 1.43e+08 1.43e+08 1.44e+08 ... 200s ..$ y : num [1:7072] 0.117 0.258 NA NA NA ... 200s ..$ index : int [1:7072] 1 2 3 4 5 6 7 8 9 10 ... 200s $ output :'data.frame': 1 obs. of 6 variables: 200s ..$ sampleName: chr NA 200s ..$ chromosome: int 1 200s ..$ start : num 1.42e+08 200s ..$ end : num 2.47e+08 200s ..$ nbrOfLoci : int 7072 200s ..$ mean : num 0.18 200s $ segRows:'data.frame': 1 obs. of 2 variables: 200s ..$ startRow: int 1 200s ..$ endRow : int 7072 200s $ params :List of 7 200s ..$ undo.splits : chr "sdundo" 200s ..$ undo.SD : num Inf 200s ..$ alpha : num 0.001 200s ..$ undo : num Inf 200s ..$ joinSegments : logi TRUE 200s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 200s .. ..$ chromosome: int 1 200s .. ..$ start : num 1.42e+08 200s .. ..$ end : num 2.47e+08 200s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 200s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 200s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.001 0 0 0 0 200s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 200s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 200s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 200s DH segmentation (locally-indexed) rows: 200s startRow endRow 200s 1 1 7072 200s int [1:7072] 7587 7588 7589 7590 7591 7592 7593 7594 7595 7596 ... 200s DH segmentation rows: 200s startRow endRow 200s 1 7587 14658 200s Segmenting DH signals...done 200s DH segmentation table: 200s dhStart dhEnd dhNbrOfLoci dhMean 200s 1 141510003 247137334 7072 0.1803011 200s startRow endRow 200s 1 7587 14658 200s Rows: 200s [1] 2 200s TCN segmentation rows: 200s startRow endRow 200s 2 7587 14658 200s TCN and DH segmentation rows: 200s startRow endRow 200s 2 7587 14658 200s startRow endRow 200s 1 7587 14658 200s startRow endRow 200s 1 1 7586 200s TCN segmentation (expanded) rows: 200s startRow endRow 200s 1 1 7586 200s 2 7587 14658 200s TCN and DH segmentation rows: 200s startRow endRow 200s 1 1 7586 200s 2 7587 14658 200s startRow endRow 200s 1 1 7586 200s 2 7587 14658 200s startRow endRow 200s 1 1 7586 200s 2 7587 14658 200s Total CN segmentation table (expanded): 200s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 200s 2 1 141510003 247137334 7072 2.419824 2088 200s tcnNbrOfHets 200s 2 2088 200s (TCN,DH) segmentation for one total CN segment: 200s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 200s 2 2 1 1 141510003 247137334 7072 2.419824 2088 200s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 200s 2 2088 141510003 247137334 7072 0.1803011 200s Total CN segment #2 ([1.4151e+08,2.47137e+08]) of 2...done 200s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 200s 1 1 1 1 554484 120992603 7586 1.385258 2108 200s 2 1 2 1 141510003 247137334 7072 2.419824 2088 200s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 200s 1 2108 554484 120992603 7586 0.5116120 200s 2 2088 141510003 247137334 7072 0.1803011 200s Calculating (C1,C2) per segment... 200s Calculating (C1,C2) per segment...done 200s Number of segments: 2 200s Segmenting paired tumor-normal signals using Paired PSCBS...done 200s Post-segmenting TCNs... 200s Number of segments: 2 200s Number of chromosomes: 1 200s [1] 1 200s Chromosome 1 ('chr01') of 1... 200s Rows: 200s [1] 1 2 200s Number of segments: 2 200s TCN segment #1 ('1') of 2... 200s Nothing todo. Only one DH segmentation. Skipping. 200s TCN segment #1 ('1') of 2...done 200s TCN segment #2 ('2') of 2... 200s Nothing todo. Only one DH segmentation. Skipping. 200s TCN segment #2 ('2') of 2...done 200s Chromosome 1 ('chr01') of 1...done 200s Update (C1,C2) per segment... 200s Update (C1,C2) per segment...done 200s Post-segmenting TCNs...done 200s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 200s 1 1 1 1 554484 120992603 7586 1.385258 2108 200s 2 1 2 1 141510003 247137334 7072 2.419824 2088 200s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 200s 1 2108 554484 120992603 7586 0.5116120 0.3382717 1.046986 200s 2 2088 141510003 247137334 7072 0.1803011 0.9917635 1.428060 200s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 200s 1 1 1 1 554484 120992603 7586 1.385258 2108 200s 2 1 2 1 141510003 247137334 7072 2.419824 2088 200s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 200s 1 2108 554484 120992603 7586 0.5116120 0.3382717 1.046986 200s 2 2088 141510003 247137334 7072 0.1803011 0.9917635 1.428060 200s > print(fit) 200s chromosome tcnId dhId start end tcnNbrOfLoci tcnMean tcnNbrOfSNPs 200s 1 1 1 1 554484 120992603 7586 1.385258 2108 200s 2 1 2 1 141510003 247137334 7072 2.419824 2088 200s tcnNbrOfHets dhNbrOfLoci dhMean c1Mean c2Mean 200s 1 2108 7586 0.5116120 0.3382717 1.046986 200s 2 2088 7072 0.1803011 0.9917635 1.428060 200s > 200s > # Plot results 200s > dev.set(5L) 200s pdf 200s 2 200s > plotTracks(fit) 200s > abline(v=c(knownSegments$start, knownSegments$end)/1e6, lty=3) 200s > 200s > # Sanity check 200s > stopifnot(nbrOfSegments(fit) == nrow(knownSegments)) 200s > 200s > fit4 <- fit 200s > 200s > 200s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 200s > # Tiling multiple chromosomes 200s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 200s > # Simulate multiple chromosomes 200s > fit1 <- fit 200s > fit2 <- renameChromosomes(fit, from=1, to=2) 200s > fitM <- c(fit1, fit2) 200s > 200s > # Tile chromosomes 200s > fitT <- tileChromosomes(fitM) 200s > fitTb <- tileChromosomes(fitT) 200s > stopifnot(identical(fitTb, fitT)) 200s > 200s > # Plotting multiple chromosomes 200s > plotTracks(fitT) 200s > 200s > proc.time() 200s user system elapsed 200s 3.202 0.067 3.266 200s Test segmentByPairedPSCBS passed 200s 0 200s + [ 0 != 0 ] 200s + echo Test segmentByPairedPSCBS passed 200s + echo 0 200s + rm -f /tmp/autopkgtest.P73rVA/autopkgtest_tmp/PairedPSCBS,boot.R /tmp/autopkgtest.P73rVA/autopkgtest_tmp/PairedPSCBS,boot.Rout /tmp/autopkgtest.P73rVA/autopkgtest_tmp/Rplots.pdf /tmp/autopkgtest.P73rVA/autopkgtest_tmp/findLargeGaps.R /tmp/autopkgtest.P73rVA/autopkgtest_tmp/findLargeGaps.Rout /tmp/autopkgtest.P73rVA/autopkgtest_tmp/randomSeed.R /tmp/autopkgtest.P73rVA/autopkgtest_tmp/randomSeed.Rout /tmp/autopkgtest.P73rVA/autopkgtest_tmp/segmentByCBS,bug67.R /tmp/autopkgtest.P73rVA/autopkgtest_tmp/segmentByCBS,bug67.Rout /tmp/autopkgtest.P73rVA/autopkgtest_tmp/segmentByCBS,calls.R /tmp/autopkgtest.P73rVA/autopkgtest_tmp/segmentByCBS,calls.Rout /tmp/autopkgtest.P73rVA/autopkgtest_tmp/segmentByCBS,futures.R /tmp/autopkgtest.P73rVA/autopkgtest_tmp/segmentByCBS,futures.Rout /tmp/autopkgtest.P73rVA/autopkgtest_tmp/segmentByCBS,median.R /tmp/autopkgtest.P73rVA/autopkgtest_tmp/segmentByCBS,median.Rout /tmp/autopkgtest.P73rVA/autopkgtest_tmp/segmentByCBS,prune.R /tmp/autopkgtest.P73rVA/autopkgtest_tmp/segmentByCBS,prune.Rout /tmp/autopkgtest.P73rVA/autopkgtest_tmp/segmentByCBS,report.R /tmp/autopkgtest.P73rVA/autopkgtest_tmp/segmentByCBS,report.Rout /tmp/autopkgtest.P73rVA/autopkgtest_tmp/segmentByCBS,shiftTCN.R /tmp/autopkgtest.P73rVA/autopkgtest_tmp/segmentByCBS,shiftTCN.Rout /tmp/autopkgtest.P73rVA/autopkgtest_tmp/segmentByCBS,weights.R /tmp/autopkgtest.P73rVA/autopkgtest_tmp/segmentByCBS,weights.Rout /tmp/autopkgtest.P73rVA/autopkgtest_tmp/segmentByCBS.R /tmp/autopkgtest.P73rVA/autopkgtest_tmp/segmentByCBS.Rout /tmp/autopkgtest.P73rVA/autopkgtest_tmp/segmentByNonPairedPSCBS,medianDH.R /tmp/autopkgtest.P73rVA/autopkgtest_tmp/segmentByNonPairedPSCBS,medianDH.Rout /tmp/autopkgtest.P73rVA/autopkgtest_tmp/segmentByPairedPSCBS,DH.R /tmp/autopkgtest.P73rVA/autopkgtest_tmp/segmentByPairedPSCBS,DH.Rout /tmp/autopkgtest.P73rVA/autopkgtest_tmp/segmentByPairedPSCBS,calls.R /tmp/autopkgtest.P73rVA/autopkgtest_tmp/segmentByPairedPSCBS,calls.Rout /tmp/autopkgtest.P73rVA/autopkgtest_tmp/segmentByPairedPSCBS,futures.R /tmp/autopkgtest.P73rVA/autopkgtest_tmp/segmentByPairedPSCBS,futures.Rout /tmp/autopkgtest.P73rVA/autopkgtest_tmp/segmentByPairedPSCBS,noNormalBAFs.R /tmp/autopkgtest.P73rVA/autopkgtest_tmp/segmentByPairedPSCBS,noNormalBAFs.Rout /tmp/autopkgtest.P73rVA/autopkgtest_tmp/segmentByPairedPSCBS,report.R /tmp/autopkgtest.P73rVA/autopkgtest_tmp/segmentByPairedPSCBS,report.Rout /tmp/autopkgtest.P73rVA/autopkgtest_tmp/segmentByPairedPSCBS,seqOfSegmentsByDP.R /tmp/autopkgtest.P73rVA/autopkgtest_tmp/segmentByPairedPSCBS,seqOfSegmentsByDP.Rout /tmp/autopkgtest.P73rVA/autopkgtest_tmp/segmentByPairedPSCBS.R /tmp/autopkgtest.P73rVA/autopkgtest_tmp/segmentByPairedPSCBS.Rout 200s autopkgtest [05:51:23]: test run-unit-test: -----------------------] 200s autopkgtest [05:51:23]: test run-unit-test: - - - - - - - - - - results - - - - - - - - - - 200s run-unit-test PASS 201s autopkgtest [05:51:24]: test pkg-r-autopkgtest: preparing testbed 220s Creating nova instance adt-resolute-amd64-r-cran-pscbs-20260210-053651-juju-7f2275-prod-proposed-migration-environment-20-b366f358-b7fe-4071-8296-d3ed64a90a2d from image adt/ubuntu-resolute-amd64-server-20260204.img (UUID fedf54b4-458b-493e-8072-6425c19717b4)... 345s autopkgtest [05:53:48]: testbed dpkg architecture: amd64 345s autopkgtest [05:53:48]: testbed apt version: 3.1.14 345s autopkgtest [05:53:48]: @@@@@@@@@@@@@@@@@@@@ test bed setup 345s autopkgtest [05:53:48]: testbed release detected to be: resolute 346s autopkgtest [05:53:49]: updating testbed package index (apt update) 346s Get:1 http://ftpmaster.internal/ubuntu resolute-proposed InRelease [124 kB] 346s Hit:2 http://ftpmaster.internal/ubuntu resolute InRelease 346s Hit:3 http://ftpmaster.internal/ubuntu resolute-updates InRelease 346s Hit:4 http://ftpmaster.internal/ubuntu resolute-security InRelease 346s Get:5 http://ftpmaster.internal/ubuntu resolute-proposed/multiverse Sources [31.1 kB] 346s Get:6 http://ftpmaster.internal/ubuntu resolute-proposed/main Sources [178 kB] 346s Get:7 http://ftpmaster.internal/ubuntu resolute-proposed/universe Sources [1727 kB] 347s Get:8 http://ftpmaster.internal/ubuntu resolute-proposed/main i386 Packages [219 kB] 347s Get:9 http://ftpmaster.internal/ubuntu resolute-proposed/main amd64 Packages [266 kB] 347s Get:10 http://ftpmaster.internal/ubuntu resolute-proposed/main amd64 c-n-f Metadata [6184 B] 347s Get:11 http://ftpmaster.internal/ubuntu resolute-proposed/restricted amd64 c-n-f Metadata [120 B] 347s Get:12 http://ftpmaster.internal/ubuntu resolute-proposed/universe amd64 Packages [1787 kB] 347s Get:13 http://ftpmaster.internal/ubuntu resolute-proposed/universe i386 Packages [792 kB] 347s Get:14 http://ftpmaster.internal/ubuntu resolute-proposed/universe amd64 c-n-f Metadata [32.5 kB] 347s Get:15 http://ftpmaster.internal/ubuntu resolute-proposed/multiverse amd64 Packages [26.4 kB] 347s Get:16 http://ftpmaster.internal/ubuntu resolute-proposed/multiverse i386 Packages [5020 B] 347s Get:17 http://ftpmaster.internal/ubuntu resolute-proposed/multiverse amd64 c-n-f Metadata [996 B] 348s Fetched 5197 kB in 1s (3995 kB/s) 348s Reading package lists... 349s Hit:1 http://ftpmaster.internal/ubuntu resolute-proposed InRelease 349s Hit:2 http://ftpmaster.internal/ubuntu resolute InRelease 349s Hit:3 http://ftpmaster.internal/ubuntu resolute-updates InRelease 349s Hit:4 http://ftpmaster.internal/ubuntu resolute-security InRelease 350s Reading package lists... 350s Reading package lists... 350s Building dependency tree... 350s Reading state information... 350s Calculating upgrade... 350s The following package was automatically installed and is no longer required: 350s libpython3.13 350s Use 'sudo apt autoremove' to remove it. 350s The following NEW packages will be installed: 350s gcc-16-base libpython3.14 libpython3.14-minimal libpython3.14-stdlib 350s linux-headers-6.19.0-3 linux-headers-6.19.0-3-generic 350s linux-image-6.19.0-3-generic linux-modules-6.19.0-3-generic 350s linux-tools-6.19.0-3 linux-tools-6.19.0-3-generic 350s The following packages will be upgraded: 350s 3cpio amd64-microcode apt bpftool busybox-initramfs busybox-static 350s cryptsetup-bin dash dbus dbus-bin dbus-daemon dbus-session-bus-common 350s dbus-system-bus-common dbus-user-session debianutils dmsetup dracut-install 350s ethtool findutils gir1.2-girepository-3.0 gir1.2-glib-2.0 hwdata iproute2 350s iptables less libapt-pkg7.0 libatomic1 libattr1 libbpf1 libbrotli1 libbsd0 350s libcryptsetup12 libdbus-1-3 libdevmapper1.02.1 libdrm-amdgpu1 libdrm-common 350s libdrm2 libevent-core-2.1-7t64 libgcc-s1 libgdbm-compat4t64 libgdbm6t64 350s libgirepository-2.0-0 libglib2.0-0t64 libglib2.0-data libgpm2 libgudev-1.0-0 350s libidn2-0 libip4tc2 libip6tc2 libjansson4 libkeyutils1 liblsof0 350s libmaxminddb0 libnetfilter-conntrack3 libnpth0t64 libonig5 libpcap0.8t64 350s libpci3 libsensors-config libsensors5 libstdc++6 libusb-1.0-0 libwrap0 350s libxau6 libxkbcommon0 libxtables12 linux-generic linux-headers-generic 350s linux-headers-virtual linux-image-generic linux-image-virtual linux-perf 350s linux-tools-common linux-virtual lsof man-db mawk patch pciutils pnp.ids 350s pollinate python3-linkify-it python3-markdown-it python3-referencing sed 350s shared-mime-info tar tcpdump ubuntu-kernel-accessories ubuntu-standard wget 350s 91 upgraded, 10 newly installed, 0 to remove and 0 not upgraded. 350s Need to get 237 MB of archives. 350s After this operation, 339 MB of additional disk space will be used. 350s Get:1 http://ftpmaster.internal/ubuntu resolute/main amd64 debianutils amd64 5.23.2build1 [93.3 kB] 350s Get:2 http://ftpmaster.internal/ubuntu resolute/main amd64 dash amd64 0.5.12-12ubuntu3 [96.0 kB] 350s Get:3 http://ftpmaster.internal/ubuntu resolute/main amd64 findutils amd64 4.10.0-3build2 [307 kB] 350s Get:4 http://ftpmaster.internal/ubuntu resolute/main amd64 sed amd64 4.9-2build3 [195 kB] 350s Get:5 http://ftpmaster.internal/ubuntu resolute/main amd64 tar amd64 1.35+dfsg-3.1build2 [257 kB] 350s Get:6 http://ftpmaster.internal/ubuntu resolute/main amd64 libattr1 amd64 1:2.5.2-3build2 [11.4 kB] 350s Get:7 http://ftpmaster.internal/ubuntu resolute/main amd64 gcc-16-base amd64 16-20260208-1ubuntu1 [59.7 kB] 350s Get:8 http://ftpmaster.internal/ubuntu resolute/main amd64 libgcc-s1 amd64 16-20260208-1ubuntu1 [80.3 kB] 350s Get:9 http://ftpmaster.internal/ubuntu resolute/main amd64 libbsd0 amd64 0.12.2-2build2 [42.3 kB] 350s Get:10 http://ftpmaster.internal/ubuntu resolute/main amd64 mawk amd64 1.3.4.20260129-1 [133 kB] 350s Get:11 http://ftpmaster.internal/ubuntu resolute/main amd64 libstdc++6 amd64 16-20260208-1ubuntu1 [844 kB] 350s Get:12 http://ftpmaster.internal/ubuntu resolute/main amd64 libapt-pkg7.0 amd64 3.1.15 [1151 kB] 350s Get:13 http://ftpmaster.internal/ubuntu resolute/main amd64 apt amd64 3.1.15 [1479 kB] 350s Get:14 http://ftpmaster.internal/ubuntu resolute/main amd64 dbus-system-bus-common all 1.16.2-2ubuntu3 [55.8 kB] 350s Get:15 http://ftpmaster.internal/ubuntu resolute/main amd64 dbus-session-bus-common all 1.16.2-2ubuntu3 [54.4 kB] 350s Get:16 http://ftpmaster.internal/ubuntu resolute/main amd64 dbus-user-session amd64 1.16.2-2ubuntu3 [9696 B] 350s Get:17 http://ftpmaster.internal/ubuntu resolute/main amd64 dbus-daemon amd64 1.16.2-2ubuntu3 [119 kB] 350s Get:18 http://ftpmaster.internal/ubuntu resolute/main amd64 dbus-bin amd64 1.16.2-2ubuntu3 [40.1 kB] 350s Get:19 http://ftpmaster.internal/ubuntu resolute/main amd64 dbus amd64 1.16.2-2ubuntu3 [24.2 kB] 350s Get:20 http://ftpmaster.internal/ubuntu resolute/main amd64 libdbus-1-3 amd64 1.16.2-2ubuntu3 [185 kB] 350s Get:21 http://ftpmaster.internal/ubuntu resolute/main amd64 libdevmapper1.02.1 amd64 2:1.02.205-2ubuntu3 [142 kB] 350s Get:22 http://ftpmaster.internal/ubuntu resolute/main amd64 dmsetup amd64 2:1.02.205-2ubuntu3 [79.4 kB] 350s Get:23 http://ftpmaster.internal/ubuntu resolute/main amd64 ethtool amd64 1:6.15-3build1 [318 kB] 350s Get:24 http://ftpmaster.internal/ubuntu resolute/main amd64 gir1.2-girepository-3.0 amd64 2.87.2-2 [25.2 kB] 350s Get:25 http://ftpmaster.internal/ubuntu resolute/main amd64 libgirepository-2.0-0 amd64 2.87.2-2 [76.1 kB] 350s Get:26 http://ftpmaster.internal/ubuntu resolute/main amd64 libatomic1 amd64 16-20260208-1ubuntu1 [11.4 kB] 350s Get:27 http://ftpmaster.internal/ubuntu resolute/main amd64 gir1.2-glib-2.0 amd64 2.87.2-2 [182 kB] 350s Get:28 http://ftpmaster.internal/ubuntu resolute/main amd64 libglib2.0-0t64 amd64 2.87.2-2 [1613 kB] 350s Get:29 http://ftpmaster.internal/ubuntu resolute/main amd64 libbpf1 amd64 1:1.6.2-1build1 [184 kB] 350s Get:30 http://ftpmaster.internal/ubuntu resolute/main amd64 iptables amd64 1.8.11-2ubuntu3 [381 kB] 350s Get:31 http://ftpmaster.internal/ubuntu resolute/main amd64 libip4tc2 amd64 1.8.11-2ubuntu3 [24.2 kB] 350s Get:32 http://ftpmaster.internal/ubuntu resolute/main amd64 libip6tc2 amd64 1.8.11-2ubuntu3 [24.4 kB] 350s Get:33 http://ftpmaster.internal/ubuntu resolute/main amd64 libnetfilter-conntrack3 amd64 1.1.1-1 [47.5 kB] 350s Get:34 http://ftpmaster.internal/ubuntu resolute/main amd64 libxtables12 amd64 1.8.11-2ubuntu3 [36.6 kB] 350s Get:35 http://ftpmaster.internal/ubuntu resolute/main amd64 iproute2 amd64 6.18.0-1ubuntu1 [1178 kB] 350s Get:36 http://ftpmaster.internal/ubuntu resolute/main amd64 less amd64 668-1build1 [172 kB] 351s Get:37 http://ftpmaster.internal/ubuntu resolute/main amd64 libcryptsetup12 amd64 2:2.8.0-1ubuntu3 [283 kB] 351s Get:38 http://ftpmaster.internal/ubuntu resolute/main amd64 libglib2.0-data all 2.87.2-2 [58.2 kB] 351s Get:39 http://ftpmaster.internal/ubuntu resolute/main amd64 libidn2-0 amd64 2.3.8-4build1 [67.6 kB] 351s Get:40 http://ftpmaster.internal/ubuntu resolute/main amd64 libkeyutils1 amd64 1.6.3-6ubuntu3 [10.6 kB] 351s Get:41 http://ftpmaster.internal/ubuntu resolute/main amd64 python3-linkify-it all 2.0.3-1ubuntu3 [19.4 kB] 351s Get:42 http://ftpmaster.internal/ubuntu resolute/main amd64 python3-markdown-it all 3.0.0-3build1 [54.4 kB] 351s Get:43 http://ftpmaster.internal/ubuntu resolute/main amd64 shared-mime-info amd64 2.4-5build3 [476 kB] 351s Get:44 http://ftpmaster.internal/ubuntu resolute/main amd64 busybox-static amd64 1:1.37.0-7ubuntu1 [1034 kB] 351s Get:45 http://ftpmaster.internal/ubuntu resolute/main amd64 libdrm-common all 2.4.131-1 [9774 B] 351s Get:46 http://ftpmaster.internal/ubuntu resolute/main amd64 libdrm2 amd64 2.4.131-1 [42.3 kB] 351s Get:47 http://ftpmaster.internal/ubuntu resolute/main amd64 libgdbm6t64 amd64 1.26-1build1 [36.5 kB] 351s Get:48 http://ftpmaster.internal/ubuntu resolute/main amd64 libgpm2 amd64 1.20.7-12build1 [14.4 kB] 351s Get:49 http://ftpmaster.internal/ubuntu resolute/main amd64 libjansson4 amd64 2.14-2build4 [33.2 kB] 351s Get:50 http://ftpmaster.internal/ubuntu resolute/main amd64 lsof amd64 4.99.4+dfsg-2build2 [239 kB] 351s Get:51 http://ftpmaster.internal/ubuntu resolute/main amd64 liblsof0 amd64 4.99.4+dfsg-2build2 [56.5 kB] 351s Get:52 http://ftpmaster.internal/ubuntu resolute/main amd64 libmaxminddb0 amd64 1.12.2-1build2 [18.9 kB] 351s Get:53 http://ftpmaster.internal/ubuntu resolute/main amd64 libpcap0.8t64 amd64 1.10.5-2ubuntu3 [154 kB] 351s Get:54 http://ftpmaster.internal/ubuntu resolute/main amd64 pciutils amd64 1:3.14.0-1build2 [95.5 kB] 351s Get:55 http://ftpmaster.internal/ubuntu resolute/main amd64 libpci3 amd64 1:3.14.0-1build2 [38.1 kB] 351s Get:56 http://ftpmaster.internal/ubuntu resolute/main amd64 libsensors-config all 1:3.6.2-2build1 [6862 B] 351s Get:57 http://ftpmaster.internal/ubuntu resolute/main amd64 libsensors5 amd64 1:3.6.2-2build1 [28.9 kB] 351s Get:58 http://ftpmaster.internal/ubuntu resolute/main amd64 libusb-1.0-0 amd64 2:1.0.29-2build1 [56.9 kB] 351s Get:59 http://ftpmaster.internal/ubuntu resolute/main amd64 libxau6 amd64 1:1.0.11-1build2 [7502 B] 351s Get:60 http://ftpmaster.internal/ubuntu resolute/main amd64 libxkbcommon0 amd64 1.13.1-1 [159 kB] 351s Get:61 http://ftpmaster.internal/ubuntu resolute/main amd64 man-db amd64 2.13.1-1build1 [1392 kB] 351s Get:62 http://ftpmaster.internal/ubuntu resolute/main amd64 tcpdump amd64 4.99.5-2ubuntu3 [477 kB] 351s Get:63 http://ftpmaster.internal/ubuntu resolute/main amd64 wget amd64 1.25.0-2ubuntu4 [353 kB] 351s Get:64 http://ftpmaster.internal/ubuntu resolute/main amd64 ubuntu-standard amd64 1.564 [13.3 kB] 351s Get:65 http://ftpmaster.internal/ubuntu resolute/main amd64 3cpio amd64 0.14.0-1ubuntu1 [285 kB] 351s Get:66 http://ftpmaster.internal/ubuntu resolute/main amd64 bpftool amd64 7.7.0+6.19.0-3.3 [1229 kB] 351s Get:67 http://ftpmaster.internal/ubuntu resolute/main amd64 busybox-initramfs amd64 1:1.37.0-7ubuntu1 [191 kB] 351s Get:68 http://ftpmaster.internal/ubuntu resolute/main amd64 cryptsetup-bin amd64 2:2.8.0-1ubuntu3 [228 kB] 351s Get:69 http://ftpmaster.internal/ubuntu resolute/main amd64 dracut-install amd64 109-11ubuntu1 [45.8 kB] 351s Get:70 http://ftpmaster.internal/ubuntu resolute/main amd64 hwdata all 0.394-1build1 [1566 B] 351s Get:71 http://ftpmaster.internal/ubuntu resolute/main amd64 pnp.ids all 0.394-1build1 [29.6 kB] 351s Get:72 http://ftpmaster.internal/ubuntu resolute/main amd64 libbrotli1 amd64 1.2.0-3 [343 kB] 351s Get:73 http://ftpmaster.internal/ubuntu resolute/main amd64 libdrm-amdgpu1 amd64 2.4.131-1 [23.2 kB] 351s Get:74 http://ftpmaster.internal/ubuntu resolute/main amd64 libevent-core-2.1-7t64 amd64 2.1.12-stable-10build2 [93.1 kB] 351s Get:75 http://ftpmaster.internal/ubuntu resolute/main amd64 libgdbm-compat4t64 amd64 1.26-1build1 [6796 B] 351s Get:76 http://ftpmaster.internal/ubuntu resolute/main amd64 libgudev-1.0-0 amd64 1:238-7build1 [15.9 kB] 351s Get:77 http://ftpmaster.internal/ubuntu resolute/main amd64 libnpth0t64 amd64 1.8-3build1 [9302 B] 351s Get:78 http://ftpmaster.internal/ubuntu resolute/main amd64 libonig5 amd64 6.9.10-1build1 [174 kB] 351s Get:79 http://ftpmaster.internal/ubuntu resolute/main amd64 libpython3.14-minimal amd64 3.14.2-1 [920 kB] 351s Get:80 http://ftpmaster.internal/ubuntu resolute/main amd64 libpython3.14-stdlib amd64 3.14.2-1 [2398 kB] 351s Get:81 http://ftpmaster.internal/ubuntu resolute/main amd64 libpython3.14 amd64 3.14.2-1 [2568 kB] 351s Get:82 http://ftpmaster.internal/ubuntu resolute/main amd64 libwrap0 amd64 7.6.q-36build2 [48.5 kB] 351s Get:83 http://ftpmaster.internal/ubuntu resolute/main amd64 linux-modules-6.19.0-3-generic amd64 6.19.0-3.3 [171 MB] 353s Get:84 http://ftpmaster.internal/ubuntu resolute/main amd64 linux-image-6.19.0-3-generic amd64 6.19.0-3.3+1 [16.8 MB] 354s Get:85 http://ftpmaster.internal/ubuntu resolute/main amd64 amd64-microcode amd64 3.20251202.1ubuntu1 [459 kB] 354s Get:86 http://ftpmaster.internal/ubuntu resolute/main amd64 linux-generic amd64 6.19.0-3.3 [1698 B] 354s Get:87 http://ftpmaster.internal/ubuntu resolute/main amd64 linux-image-generic amd64 6.19.0-3.3 [12.2 kB] 354s Get:88 http://ftpmaster.internal/ubuntu resolute/main amd64 linux-virtual amd64 6.19.0-3.3 [1700 B] 354s Get:89 http://ftpmaster.internal/ubuntu resolute/main amd64 linux-image-virtual amd64 6.19.0-3.3 [12.1 kB] 354s Get:90 http://ftpmaster.internal/ubuntu resolute/main amd64 linux-headers-virtual amd64 6.19.0-3.3 [1646 B] 354s Get:91 http://ftpmaster.internal/ubuntu resolute/main amd64 linux-headers-6.19.0-3 all 6.19.0-3.3 [14.9 MB] 354s Get:92 http://ftpmaster.internal/ubuntu resolute/main amd64 linux-headers-6.19.0-3-generic amd64 6.19.0-3.3 [4330 kB] 354s Get:93 http://ftpmaster.internal/ubuntu resolute/main amd64 linux-headers-generic amd64 6.19.0-3.3 [12.0 kB] 354s Get:94 http://ftpmaster.internal/ubuntu resolute/main amd64 linux-perf amd64 6.19.0-3.3 [4480 kB] 354s Get:95 http://ftpmaster.internal/ubuntu resolute/main amd64 linux-tools-common all 6.19.0-3.3 [345 kB] 354s Get:96 http://ftpmaster.internal/ubuntu resolute/main amd64 linux-tools-6.19.0-3 amd64 6.19.0-3.3 [1455 kB] 354s Get:97 http://ftpmaster.internal/ubuntu resolute/main amd64 linux-tools-6.19.0-3-generic amd64 6.19.0-3.3 [1612 B] 354s Get:98 http://ftpmaster.internal/ubuntu resolute/main amd64 patch amd64 2.8-2build1 [95.7 kB] 354s Get:99 http://ftpmaster.internal/ubuntu resolute/main amd64 pollinate all 4.33-4ubuntu5 [14.0 kB] 354s Get:100 http://ftpmaster.internal/ubuntu resolute/main amd64 python3-referencing all 0.36.2-1ubuntu2 [22.2 kB] 354s Get:101 http://ftpmaster.internal/ubuntu resolute/main amd64 ubuntu-kernel-accessories amd64 1.564 [13.1 kB] 354s dpkg-preconfigure: unable to re-open stdin: No such file or directory 354s Fetched 237 MB in 4s (58.5 MB/s) 354s (Reading database ... (Reading database ... 5% (Reading database ... 10% (Reading database ... 15% (Reading database ... 20% (Reading database ... 25% (Reading database ... 30% (Reading database ... 35% (Reading database ... 40% (Reading database ... 45% (Reading database ... 50% (Reading database ... 55% (Reading database ... 60% (Reading database ... 65% (Reading database ... 70% (Reading database ... 75% (Reading database ... 80% (Reading database ... 85% (Reading database ... 90% (Reading database ... 95% (Reading database ... 100% (Reading database ... 83957 files and directories currently installed.) 354s Preparing to unpack .../debianutils_5.23.2build1_amd64.deb ... 354s Unpacking debianutils (5.23.2build1) over (5.23.2) ... 355s Setting up debianutils (5.23.2build1) ... 355s (Reading database ... (Reading database ... 5% (Reading database ... 10% (Reading database ... 15% (Reading database ... 20% (Reading database ... 25% (Reading database ... 30% (Reading database ... 35% (Reading database ... 40% (Reading database ... 45% (Reading database ... 50% (Reading database ... 55% (Reading database ... 60% (Reading database ... 65% (Reading database ... 70% (Reading database ... 75% (Reading database ... 80% (Reading database ... 85% (Reading database ... 90% (Reading database ... 95% (Reading database ... 100% (Reading database ... 83957 files and directories currently installed.) 355s Preparing to unpack .../dash_0.5.12-12ubuntu3_amd64.deb ... 355s Unpacking dash (0.5.12-12ubuntu3) over (0.5.12-12ubuntu2) ... 355s Setting up dash (0.5.12-12ubuntu3) ... 355s (Reading database ... (Reading database ... 5% (Reading database ... 10% (Reading database ... 15% (Reading database ... 20% (Reading database ... 25% (Reading database ... 30% (Reading database ... 35% (Reading database ... 40% (Reading database ... 45% (Reading database ... 50% (Reading database ... 55% (Reading database ... 60% (Reading database ... 65% (Reading database ... 70% (Reading database ... 75% (Reading database ... 80% (Reading database ... 85% (Reading database ... 90% (Reading database ... 95% (Reading database ... 100% (Reading database ... 83957 files and directories currently installed.) 355s Preparing to unpack .../findutils_4.10.0-3build2_amd64.deb ... 355s Unpacking findutils (4.10.0-3build2) over (4.10.0-3build1) ... 355s Setting up findutils (4.10.0-3build2) ... 355s (Reading database ... (Reading database ... 5% (Reading database ... 10% (Reading database ... 15% (Reading database ... 20% (Reading database ... 25% (Reading database ... 30% (Reading database ... 35% (Reading database ... 40% (Reading database ... 45% (Reading database ... 50% (Reading database ... 55% (Reading database ... 60% (Reading database ... 65% (Reading database ... 70% (Reading database ... 75% (Reading database ... 80% (Reading database ... 85% (Reading database ... 90% (Reading database ... 95% (Reading database ... 100% (Reading database ... 83957 files and directories currently installed.) 355s Preparing to unpack .../sed_4.9-2build3_amd64.deb ... 355s Unpacking sed (4.9-2build3) over (4.9-2build2) ... 355s Setting up sed (4.9-2build3) ... 355s (Reading database ... (Reading database ... 5% (Reading database ... 10% (Reading database ... 15% (Reading database ... 20% (Reading database ... 25% (Reading database ... 30% (Reading database ... 35% (Reading database ... 40% (Reading database ... 45% (Reading database ... 50% (Reading database ... 55% (Reading database ... 60% (Reading database ... 65% (Reading database ... 70% (Reading database ... 75% (Reading database ... 80% (Reading database ... 85% (Reading database ... 90% (Reading database ... 95% (Reading database ... 100% (Reading database ... 83957 files and directories currently installed.) 355s Preparing to unpack .../tar_1.35+dfsg-3.1build2_amd64.deb ... 355s Unpacking tar (1.35+dfsg-3.1build2) over (1.35+dfsg-3.1build1) ... 355s Setting up tar (1.35+dfsg-3.1build2) ... 355s (Reading database ... (Reading database ... 5% (Reading database ... 10% (Reading database ... 15% (Reading database ... 20% (Reading database ... 25% (Reading database ... 30% (Reading database ... 35% (Reading database ... 40% (Reading database ... 45% (Reading database ... 50% (Reading database ... 55% (Reading database ... 60% (Reading database ... 65% (Reading database ... 70% (Reading database ... 75% (Reading database ... 80% (Reading database ... 85% (Reading database ... 90% (Reading database ... 95% (Reading database ... 100% (Reading database ... 83957 files and directories currently installed.) 355s Preparing to unpack .../libattr1_1%3a2.5.2-3build2_amd64.deb ... 355s Unpacking libattr1:amd64 (1:2.5.2-3build2) over (1:2.5.2-3build1) ... 355s Setting up libattr1:amd64 (1:2.5.2-3build2) ... 355s Selecting previously unselected package gcc-16-base:amd64. 355s (Reading database ... (Reading database ... 5% (Reading database ... 10% (Reading database ... 15% (Reading database ... 20% (Reading database ... 25% (Reading database ... 30% (Reading database ... 35% (Reading database ... 40% (Reading database ... 45% (Reading database ... 50% (Reading database ... 55% (Reading database ... 60% (Reading database ... 65% (Reading database ... 70% (Reading database ... 75% (Reading database ... 80% (Reading database ... 85% (Reading database ... 90% (Reading database ... 95% (Reading database ... 100% (Reading database ... 83957 files and directories currently installed.) 355s Preparing to unpack .../gcc-16-base_16-20260208-1ubuntu1_amd64.deb ... 355s Unpacking gcc-16-base:amd64 (16-20260208-1ubuntu1) ... 355s Setting up gcc-16-base:amd64 (16-20260208-1ubuntu1) ... 355s (Reading database ... (Reading database ... 5% (Reading database ... 10% (Reading database ... 15% (Reading database ... 20% (Reading database ... 25% (Reading database ... 30% (Reading database ... 35% (Reading database ... 40% (Reading database ... 45% (Reading database ... 50% (Reading database ... 55% (Reading database ... 60% (Reading database ... 65% (Reading database ... 70% (Reading database ... 75% (Reading database ... 80% (Reading database ... 85% (Reading database ... 90% (Reading database ... 95% (Reading database ... 100% (Reading database ... 83962 files and directories currently installed.) 355s Preparing to unpack .../libgcc-s1_16-20260208-1ubuntu1_amd64.deb ... 355s Unpacking libgcc-s1:amd64 (16-20260208-1ubuntu1) over (15.2.0-12ubuntu1) ... 355s Setting up libgcc-s1:amd64 (16-20260208-1ubuntu1) ... 355s (Reading database ... (Reading database ... 5% (Reading database ... 10% (Reading database ... 15% (Reading database ... 20% (Reading database ... 25% (Reading database ... 30% (Reading database ... 35% (Reading database ... 40% (Reading database ... 45% (Reading database ... 50% (Reading database ... 55% (Reading database ... 60% (Reading database ... 65% (Reading database ... 70% (Reading database ... 75% (Reading database ... 80% (Reading database ... 85% (Reading database ... 90% (Reading database ... 95% (Reading database ... 100% (Reading database ... 83962 files and directories currently installed.) 355s Preparing to unpack .../00-libbsd0_0.12.2-2build2_amd64.deb ... 355s Unpacking libbsd0:amd64 (0.12.2-2build2) over (0.12.2-2build1) ... 355s Preparing to unpack .../01-mawk_1.3.4.20260129-1_amd64.deb ... 355s Unpacking mawk (1.3.4.20260129-1) over (1.3.4.20250131-2) ... 355s Preparing to unpack .../02-libstdc++6_16-20260208-1ubuntu1_amd64.deb ... 355s Unpacking libstdc++6:amd64 (16-20260208-1ubuntu1) over (15.2.0-12ubuntu1) ... 355s Preparing to unpack .../03-libapt-pkg7.0_3.1.15_amd64.deb ... 355s Unpacking libapt-pkg7.0:amd64 (3.1.15) over (3.1.14) ... 355s Preparing to unpack .../04-apt_3.1.15_amd64.deb ... 355s Unpacking apt (3.1.15) over (3.1.14) ... 355s Preparing to unpack .../05-dbus-system-bus-common_1.16.2-2ubuntu3_all.deb ... 355s Unpacking dbus-system-bus-common (1.16.2-2ubuntu3) over (1.16.2-2ubuntu2) ... 356s Preparing to unpack .../06-dbus-session-bus-common_1.16.2-2ubuntu3_all.deb ... 356s Unpacking dbus-session-bus-common (1.16.2-2ubuntu3) over (1.16.2-2ubuntu2) ... 356s Preparing to unpack .../07-dbus-user-session_1.16.2-2ubuntu3_amd64.deb ... 356s Unpacking dbus-user-session (1.16.2-2ubuntu3) over (1.16.2-2ubuntu2) ... 356s Preparing to unpack .../08-dbus-daemon_1.16.2-2ubuntu3_amd64.deb ... 356s Unpacking dbus-daemon (1.16.2-2ubuntu3) over (1.16.2-2ubuntu2) ... 356s Preparing to unpack .../09-dbus-bin_1.16.2-2ubuntu3_amd64.deb ... 356s Unpacking dbus-bin (1.16.2-2ubuntu3) over (1.16.2-2ubuntu2) ... 356s Preparing to unpack .../10-dbus_1.16.2-2ubuntu3_amd64.deb ... 356s Unpacking dbus (1.16.2-2ubuntu3) over (1.16.2-2ubuntu2) ... 356s Preparing to unpack .../11-libdbus-1-3_1.16.2-2ubuntu3_amd64.deb ... 356s Unpacking libdbus-1-3:amd64 (1.16.2-2ubuntu3) over (1.16.2-2ubuntu2) ... 356s Preparing to unpack .../12-libdevmapper1.02.1_2%3a1.02.205-2ubuntu3_amd64.deb ... 356s Unpacking libdevmapper1.02.1:amd64 (2:1.02.205-2ubuntu3) over (2:1.02.205-2ubuntu2) ... 356s Preparing to unpack .../13-dmsetup_2%3a1.02.205-2ubuntu3_amd64.deb ... 356s Unpacking dmsetup (2:1.02.205-2ubuntu3) over (2:1.02.205-2ubuntu2) ... 356s Preparing to unpack .../14-ethtool_1%3a6.15-3build1_amd64.deb ... 356s Unpacking ethtool (1:6.15-3build1) over (1:6.15-3) ... 356s Preparing to unpack .../15-gir1.2-girepository-3.0_2.87.2-2_amd64.deb ... 356s Unpacking gir1.2-girepository-3.0:amd64 (2.87.2-2) over (2.86.3-4) ... 356s Preparing to unpack .../16-libgirepository-2.0-0_2.87.2-2_amd64.deb ... 356s Unpacking libgirepository-2.0-0:amd64 (2.87.2-2) over (2.86.3-4) ... 356s Preparing to unpack .../17-libatomic1_16-20260208-1ubuntu1_amd64.deb ... 356s Unpacking libatomic1:amd64 (16-20260208-1ubuntu1) over (15.2.0-12ubuntu1) ... 356s Preparing to unpack .../18-gir1.2-glib-2.0_2.87.2-2_amd64.deb ... 356s Unpacking gir1.2-glib-2.0:amd64 (2.87.2-2) over (2.86.3-4) ... 356s Preparing to unpack .../19-libglib2.0-0t64_2.87.2-2_amd64.deb ... 356s Unpacking libglib2.0-0t64:amd64 (2.87.2-2) over (2.86.3-4) ... 356s Preparing to unpack .../20-libbpf1_1%3a1.6.2-1build1_amd64.deb ... 356s Unpacking libbpf1:amd64 (1:1.6.2-1build1) over (1:1.6.2-1) ... 356s Preparing to unpack .../21-iptables_1.8.11-2ubuntu3_amd64.deb ... 356s Unpacking iptables (1.8.11-2ubuntu3) over (1.8.11-2ubuntu2) ... 356s Preparing to unpack .../22-libip4tc2_1.8.11-2ubuntu3_amd64.deb ... 356s Unpacking libip4tc2:amd64 (1.8.11-2ubuntu3) over (1.8.11-2ubuntu2) ... 356s Preparing to unpack .../23-libip6tc2_1.8.11-2ubuntu3_amd64.deb ... 356s Unpacking libip6tc2:amd64 (1.8.11-2ubuntu3) over (1.8.11-2ubuntu2) ... 356s Preparing to unpack .../24-libnetfilter-conntrack3_1.1.1-1_amd64.deb ... 356s Unpacking libnetfilter-conntrack3:amd64 (1.1.1-1) over (1.1.0-1build1) ... 356s Preparing to unpack .../25-libxtables12_1.8.11-2ubuntu3_amd64.deb ... 356s Unpacking libxtables12:amd64 (1.8.11-2ubuntu3) over (1.8.11-2ubuntu2) ... 356s Preparing to unpack .../26-iproute2_6.18.0-1ubuntu1_amd64.deb ... 356s Unpacking iproute2 (6.18.0-1ubuntu1) over (6.16.0-1ubuntu3) ... 356s Preparing to unpack .../27-less_668-1build1_amd64.deb ... 356s Unpacking less (668-1build1) over (668-1) ... 356s Preparing to unpack .../28-libcryptsetup12_2%3a2.8.0-1ubuntu3_amd64.deb ... 356s Unpacking libcryptsetup12:amd64 (2:2.8.0-1ubuntu3) over (2:2.8.0-1ubuntu2) ... 356s Preparing to unpack .../29-libglib2.0-data_2.87.2-2_all.deb ... 356s Unpacking libglib2.0-data (2.87.2-2) over (2.86.3-4) ... 356s Preparing to unpack .../30-libidn2-0_2.3.8-4build1_amd64.deb ... 356s Unpacking libidn2-0:amd64 (2.3.8-4build1) over (2.3.8-4) ... 356s Preparing to unpack .../31-libkeyutils1_1.6.3-6ubuntu3_amd64.deb ... 356s Unpacking libkeyutils1:amd64 (1.6.3-6ubuntu3) over (1.6.3-6ubuntu2) ... 356s Preparing to unpack .../32-python3-linkify-it_2.0.3-1ubuntu3_all.deb ... 356s Unpacking python3-linkify-it (2.0.3-1ubuntu3) over (2.0.3-1ubuntu2) ... 356s Preparing to unpack .../33-python3-markdown-it_3.0.0-3build1_all.deb ... 357s Unpacking python3-markdown-it (3.0.0-3build1) over (3.0.0-3) ... 357s Preparing to unpack .../34-shared-mime-info_2.4-5build3_amd64.deb ... 357s Unpacking shared-mime-info (2.4-5build3) over (2.4-5build2) ... 357s Preparing to unpack .../35-busybox-static_1%3a1.37.0-7ubuntu1_amd64.deb ... 357s Unpacking busybox-static (1:1.37.0-7ubuntu1) over (1:1.37.0-4ubuntu1) ... 357s Preparing to unpack .../36-libdrm-common_2.4.131-1_all.deb ... 357s Unpacking libdrm-common (2.4.131-1) over (2.4.129-1) ... 357s Preparing to unpack .../37-libdrm2_2.4.131-1_amd64.deb ... 357s Unpacking libdrm2:amd64 (2.4.131-1) over (2.4.129-1) ... 357s Preparing to unpack .../38-libgdbm6t64_1.26-1build1_amd64.deb ... 357s Unpacking libgdbm6t64:amd64 (1.26-1build1) over (1.26-1) ... 357s Preparing to unpack .../39-libgpm2_1.20.7-12build1_amd64.deb ... 357s Unpacking libgpm2:amd64 (1.20.7-12build1) over (1.20.7-12) ... 357s Preparing to unpack .../40-libjansson4_2.14-2build4_amd64.deb ... 357s Unpacking libjansson4:amd64 (2.14-2build4) over (2.14-2build3) ... 357s Preparing to unpack .../41-lsof_4.99.4+dfsg-2build2_amd64.deb ... 357s Unpacking lsof (4.99.4+dfsg-2build2) over (4.99.4+dfsg-2build1) ... 357s Preparing to unpack .../42-liblsof0_4.99.4+dfsg-2build2_amd64.deb ... 357s Unpacking liblsof0 (4.99.4+dfsg-2build2) over (4.99.4+dfsg-2build1) ... 357s Preparing to unpack .../43-libmaxminddb0_1.12.2-1build2_amd64.deb ... 357s Unpacking libmaxminddb0:amd64 (1.12.2-1build2) 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361s Setting up ubuntu-kernel-accessories (1.564) ... 361s Setting up libgpm2:amd64 (1.20.7-12build1) ... 361s Setting up libgdbm6t64:amd64 (1.26-1build1) ... 361s Setting up linux-modules-6.19.0-3-generic (6.19.0-3.3) ... 362s Setting up libgdbm-compat4t64:amd64 (1.26-1build1) ... 362s Setting up bpftool (7.7.0+6.19.0-3.3) ... 362s Setting up libip6tc2:amd64 (1.8.11-2ubuntu3) ... 362s Setting up liblsof0 (4.99.4+dfsg-2build2) ... 362s Setting up libmaxminddb0:amd64 (1.12.2-1build2) ... 362s Setting up libbrotli1:amd64 (1.2.0-3) ... 362s Setting up libpython3.14-minimal:amd64 (3.14.2-1) ... 362s Setting up libsensors-config (1:3.6.2-2build1) ... 362s Setting up less (668-1build1) ... 362s Setting up linux-headers-6.19.0-3 (6.19.0-3.3) ... 362s Setting up libidn2-0:amd64 (2.3.8-4build1) ... 362s Setting up amd64-microcode (3.20251202.1ubuntu1) ... 362s amd64-microcode: microcode will be updated at next boot 362s Setting up man-db (2.13.1-1build1) ... 362s Updating database of manual pages ... 364s man-db.service is a disabled or a static unit not running, not starting it. 364s Setting up libjansson4:amd64 (2.14-2build4) ... 364s Setting up libglib2.0-data (2.87.2-2) ... 364s Setting up pollinate (4.33-4ubuntu5) ... 374s Setting up busybox-static (1:1.37.0-7ubuntu1) ... 374s Setting up libwrap0:amd64 (7.6.q-36build2) ... 374s Setting up linux-image-6.19.0-3-generic (6.19.0-3.3+1) ... 375s I: /boot/vmlinuz is now a symlink to vmlinuz-6.19.0-3-generic 375s I: /boot/initrd.img is now a symlink to initrd.img-6.19.0-3-generic 375s Setting up libdbus-1-3:amd64 (1.16.2-2ubuntu3) ... 375s Setting up libatomic1:amd64 (16-20260208-1ubuntu1) ... 375s Setting up patch (2.8-2build1) ... 375s Setting up libsensors5:amd64 (1:3.6.2-2build1) ... 375s Setting up busybox-initramfs (1:1.37.0-7ubuntu1) ... 375s Setting up libxtables12:amd64 (1.8.11-2ubuntu3) ... 375s Setting up lsof (4.99.4+dfsg-2build2) ... 375s Setting up libpci3:amd64 (1:3.14.0-1build2) ... 375s Setting up libdevmapper1.02.1:amd64 (2:1.02.205-2ubuntu3) ... 375s Setting up dracut-install (109-11ubuntu1) ... 375s Setting up dmsetup (2:1.02.205-2ubuntu3) ... 375s Setting up libnetfilter-conntrack3:amd64 (1.1.1-1) ... 375s Setting up pnp.ids (0.394-1build1) ... 375s Setting up dbus-session-bus-common (1.16.2-2ubuntu3) ... 375s Setting up python3-linkify-it (2.0.3-1ubuntu3) ... 375s Setting up libpcap0.8t64:amd64 (1.10.5-2ubuntu3) ... 375s Setting up libcryptsetup12:amd64 (2:2.8.0-1ubuntu3) ... 375s Setting up mawk (1.3.4.20260129-1) ... 375s Setting up libevent-core-2.1-7t64:amd64 (2.1.12-stable-10build2) ... 375s Setting up libusb-1.0-0:amd64 (2:1.0.29-2build1) ... 375s Setting up linux-image-virtual (6.19.0-3.3) ... 375s Setting up dbus-system-bus-common (1.16.2-2ubuntu3) ... 375s Setting up libbsd0:amd64 (0.12.2-2build2) ... 375s Setting up libdrm-common (2.4.131-1) ... 375s Setting up libstdc++6:amd64 (16-20260208-1ubuntu1) ... 376s Setting up dbus-bin (1.16.2-2ubuntu3) ... 376s Setting up libonig5:amd64 (6.9.10-1build1) ... 376s Setting up libbpf1:amd64 (1:1.6.2-1build1) ... 376s Setting up ethtool (1:6.15-3build1) ... 376s Setting up python3-referencing (0.36.2-1ubuntu2) ... 376s Setting up libxkbcommon0:amd64 (1.13.1-1) ... 376s Setting up cryptsetup-bin (2:2.8.0-1ubuntu3) ... 376s Setting up linux-headers-6.19.0-3-generic (6.19.0-3.3) ... 376s Setting up tcpdump (4.99.5-2ubuntu3) ... 376s Setting up linux-image-generic (6.19.0-3.3) ... 376s Setting up wget (1.25.0-2ubuntu4) ... 376s Setting up libpython3.14-stdlib:amd64 (3.14.2-1) ... 376s Setting up iptables (1.8.11-2ubuntu3) ... 376s Setting up iproute2 (6.18.0-1ubuntu1) ... 376s Setting up linux-headers-generic (6.19.0-3.3) ... 376s Setting up dbus-daemon (1.16.2-2ubuntu3) ... 376s Setting up hwdata (0.394-1build1) ... 376s Setting up dbus-user-session (1.16.2-2ubuntu3) ... 376s Setting up libglib2.0-0t64:amd64 (2.87.2-2) ... 376s No schema files found: doing nothing. 376s Setting up dbus (1.16.2-2ubuntu3) ... 376s A reboot is required to replace the running dbus-daemon. 376s Please reboot the system when convenient. 376s Setting up shared-mime-info (2.4-5build3) ... 377s Setting up gir1.2-glib-2.0:amd64 (2.87.2-2) ... 377s Setting up pciutils (1:3.14.0-1build2) ... 377s Setting up python3-markdown-it (3.0.0-3build1) ... 377s Setting up libdrm2:amd64 (2.4.131-1) ... 377s Setting up libpython3.14:amd64 (3.14.2-1) ... 377s Setting up libapt-pkg7.0:amd64 (3.1.15) ... 377s Setting up linux-tools-common (6.19.0-3.3) ... 377s Setting up libgudev-1.0-0:amd64 (1:238-7build1) ... 377s Setting up libdrm-amdgpu1:amd64 (2.4.131-1) ... 377s Setting up apt (3.1.15) ... 377s Setting up linux-headers-virtual (6.19.0-3.3) ... 377s Setting up linux-generic (6.19.0-3.3) ... 377s Setting up libgirepository-2.0-0:amd64 (2.87.2-2) ... 377s Setting up linux-tools-6.19.0-3 (6.19.0-3.3) ... 377s Setting up ubuntu-standard (1.564) ... 377s Setting up gir1.2-girepository-3.0:amd64 (2.87.2-2) ... 377s Setting up linux-virtual (6.19.0-3.3) ... 377s Setting up linux-perf (6.19.0-3.3) ... 377s Setting up linux-tools-6.19.0-3-generic (6.19.0-3.3) ... 377s Processing triggers for debianutils (5.23.2build1) ... 377s Processing triggers for install-info (7.2-5) ... 377s Processing triggers for initramfs-tools (0.150ubuntu7) ... 377s update-initramfs: Generating /boot/initrd.img-6.18.0-9-generic 382s Processing triggers for libc-bin (2.42-2ubuntu4) ... 382s Processing triggers for linux-image-6.19.0-3-generic (6.19.0-3.3+1) ... 382s /etc/kernel/postinst.d/initramfs-tools: 382s update-initramfs: Generating /boot/initrd.img-6.19.0-3-generic 386s /etc/kernel/postinst.d/zz-update-grub: 386s Sourcing file `/etc/default/grub' 386s Sourcing file `/etc/default/grub.d/50-cloudimg-settings.cfg' 386s Sourcing file `/etc/default/grub.d/90-autopkgtest.cfg' 386s Generating grub configuration file ... 386s Found linux image: /boot/vmlinuz-6.19.0-3-generic 386s Found initrd image: /boot/initrd.img-6.19.0-3-generic 386s Found linux image: /boot/vmlinuz-6.18.0-9-generic 386s Found initrd image: /boot/initrd.img-6.18.0-9-generic 386s Warning: os-prober will not be executed to detect other bootable partitions. 386s Systems on them will not be added to the GRUB boot configuration. 386s Check GRUB_DISABLE_OS_PROBER documentation entry. 386s Adding boot menu entry for UEFI Firmware Settings ... 386s done 386s autopkgtest [05:54:29]: upgrading testbed (apt dist-upgrade and autopurge) 387s Reading package lists... 387s Building dependency tree... 387s Reading state information... 387s Calculating upgrade... 387s The following package was automatically installed and is no longer required: 387s libpython3.13 387s Use 'sudo apt autoremove' to remove it. 387s 0 upgraded, 0 newly installed, 0 to remove and 0 not upgraded. 388s Reading package lists... 388s Building dependency tree... 388s Reading state information... 388s Solving dependencies... 388s The following packages will be REMOVED: 388s libpython3.13* 388s 0 upgraded, 0 newly installed, 1 to remove and 0 not upgraded. 388s After this operation, 7599 kB disk space will be freed. 388s (Reading database ... (Reading database ... 5% (Reading database ... 10% (Reading database ... 15% (Reading database ... 20% (Reading database ... 25% (Reading database ... 30% (Reading database ... 35% (Reading database ... 40% (Reading database ... 45% (Reading database ... 50% (Reading database ... 55% (Reading database ... 60% (Reading database ... 65% (Reading database ... 70% (Reading database ... 75% (Reading database ... 80% (Reading database ... 85% (Reading database ... 90% (Reading database ... 95% (Reading database ... 100% (Reading database ... 125273 files and directories currently installed.) 388s Removing libpython3.13:amd64 (3.13.11-1) ... 388s Processing triggers for libc-bin (2.42-2ubuntu4) ... 388s autopkgtest [05:54:31]: rebooting testbed after setup commands that affected boot 418s Reading package lists... 419s Building dependency tree... 419s Reading state information... 419s Solving dependencies... 419s The following NEW packages will be installed: 419s build-essential cpp cpp-15 cpp-15-x86-64-linux-gnu cpp-x86-64-linux-gnu 419s dctrl-tools fontconfig fontconfig-config fonts-dejavu-core fonts-dejavu-mono 419s g++ g++-15 g++-15-x86-64-linux-gnu g++-x86-64-linux-gnu gcc gcc-15 419s gcc-15-x86-64-linux-gnu gcc-x86-64-linux-gnu gfortran gfortran-15 419s gfortran-15-x86-64-linux-gnu gfortran-x86-64-linux-gnu icu-devtools libasan8 419s libblas-dev libblas3 libbz2-dev libc-dev-bin libc6-dev libcairo2 libcc1-0 419s libcrypt-dev libdatrie1 libdeflate-dev libdeflate0 libfontconfig1 419s libgcc-15-dev libgfortran-15-dev libgfortran5 libgomp1 libgraphite2-3 419s libharfbuzz0b libhwasan0 libice6 libicu-dev libisl23 libitm1 libjbig0 419s libjpeg-dev libjpeg-turbo8 libjpeg-turbo8-dev libjpeg8 libjpeg8-dev 419s liblapack-dev liblapack3 liblerc4 liblsan0 liblzma-dev libmpc3 419s libncurses-dev libpango-1.0-0 libpangocairo-1.0-0 libpangoft2-1.0-0 419s libpaper-utils libpaper2 libpcre2-16-0 libpcre2-32-0 libpcre2-dev 419s libpcre2-posix3 libpixman-1-0 libpkgconf3 libpng-dev libquadmath0 419s libreadline-dev libsharpyuv0 libsm6 libstdc++-15-dev libtcl8.6 libthai-data 419s libthai0 libtiff6 libtirpc-dev libtk8.6 libtsan2 libubsan1 libwebp7 419s libxcb-render0 libxcb-shm0 libxft2 libxrender1 libxss1 libxt6t64 libzstd-dev 419s linux-libc-dev pkg-r-autopkgtest pkgconf pkgconf-bin r-base-core r-base-dev 419s r-bioc-aroma.light r-bioc-biocgenerics r-bioc-dnacopy r-cran-cli 419s r-cran-codetools r-cran-digest r-cran-farver r-cran-future r-cran-ggplot2 419s r-cran-globals r-cran-glue r-cran-gtable r-cran-isoband r-cran-labeling 419s r-cran-lifecycle r-cran-listenv r-cran-matrixstats r-cran-parallelly 419s r-cran-pscbs r-cran-r.cache r-cran-r.methodss3 r-cran-r.oo r-cran-r.utils 419s r-cran-r6 r-cran-rcolorbrewer r-cran-rlang r-cran-s7 r-cran-scales 419s r-cran-vctrs r-cran-viridislite r-cran-withr rpcsvc-proto unzip x11-common 419s xdg-utils zip zlib1g-dev 419s 0 upgraded, 136 newly installed, 0 to remove and 0 not upgraded. 419s Need to get 178 MB of archives. 419s After this operation, 526 MB of additional disk space will be used. 419s Get:1 http://ftpmaster.internal/ubuntu resolute/main amd64 libc-dev-bin amd64 2.42-2ubuntu4 [23.3 kB] 419s Get:2 http://ftpmaster.internal/ubuntu resolute/main amd64 linux-libc-dev amd64 6.19.0-3.3 [1846 kB] 419s Get:3 http://ftpmaster.internal/ubuntu resolute/main amd64 libcrypt-dev amd64 1:4.5.1-1 [122 kB] 419s Get:4 http://ftpmaster.internal/ubuntu resolute/main amd64 rpcsvc-proto amd64 1.4.3-1build1 [68.3 kB] 419s Get:5 http://ftpmaster.internal/ubuntu resolute/main amd64 libc6-dev amd64 2.42-2ubuntu4 [2207 kB] 419s Get:6 http://ftpmaster.internal/ubuntu resolute/main amd64 libisl23 amd64 0.27-1build1 [691 kB] 419s Get:7 http://ftpmaster.internal/ubuntu resolute/main amd64 libmpc3 amd64 1.3.1-2 [54.8 kB] 419s Get:8 http://ftpmaster.internal/ubuntu resolute/main amd64 cpp-15-x86-64-linux-gnu amd64 15.2.0-12ubuntu1 [12.9 MB] 420s Get:9 http://ftpmaster.internal/ubuntu resolute/main amd64 cpp-15 amd64 15.2.0-12ubuntu1 [1034 B] 420s Get:10 http://ftpmaster.internal/ubuntu resolute/main amd64 cpp-x86-64-linux-gnu amd64 4:15.2.0-4ubuntu1 [5746 B] 420s Get:11 http://ftpmaster.internal/ubuntu resolute/main amd64 cpp amd64 4:15.2.0-4ubuntu1 [22.4 kB] 420s Get:12 http://ftpmaster.internal/ubuntu resolute/main amd64 libcc1-0 amd64 16-20260208-1ubuntu1 [51.2 kB] 420s Get:13 http://ftpmaster.internal/ubuntu resolute/main amd64 libgomp1 amd64 16-20260208-1ubuntu1 [162 kB] 420s Get:14 http://ftpmaster.internal/ubuntu resolute/main amd64 libitm1 amd64 16-20260208-1ubuntu1 [30.2 kB] 420s Get:15 http://ftpmaster.internal/ubuntu resolute/main amd64 libasan8 amd64 16-20260208-1ubuntu1 [3182 kB] 420s Get:16 http://ftpmaster.internal/ubuntu resolute/main amd64 liblsan0 amd64 16-20260208-1ubuntu1 [1392 kB] 420s Get:17 http://ftpmaster.internal/ubuntu resolute/main amd64 libtsan2 amd64 16-20260208-1ubuntu1 [2838 kB] 420s Get:18 http://ftpmaster.internal/ubuntu resolute/main amd64 libubsan1 amd64 16-20260208-1ubuntu1 [1238 kB] 420s Get:19 http://ftpmaster.internal/ubuntu resolute/main amd64 libhwasan0 amd64 16-20260208-1ubuntu1 [1729 kB] 420s Get:20 http://ftpmaster.internal/ubuntu resolute/main amd64 libquadmath0 amd64 16-20260208-1ubuntu1 [155 kB] 420s Get:21 http://ftpmaster.internal/ubuntu resolute/main amd64 libgcc-15-dev amd64 15.2.0-12ubuntu1 [2866 kB] 420s Get:22 http://ftpmaster.internal/ubuntu resolute/main amd64 gcc-15-x86-64-linux-gnu amd64 15.2.0-12ubuntu1 [25.4 MB] 420s Get:23 http://ftpmaster.internal/ubuntu resolute/main amd64 gcc-15 amd64 15.2.0-12ubuntu1 [530 kB] 420s Get:24 http://ftpmaster.internal/ubuntu resolute/main amd64 gcc-x86-64-linux-gnu amd64 4:15.2.0-4ubuntu1 [1208 B] 420s Get:25 http://ftpmaster.internal/ubuntu resolute/main amd64 gcc amd64 4:15.2.0-4ubuntu1 [5024 B] 420s Get:26 http://ftpmaster.internal/ubuntu resolute/main amd64 libstdc++-15-dev amd64 15.2.0-12ubuntu1 [2553 kB] 420s Get:27 http://ftpmaster.internal/ubuntu resolute/main amd64 g++-15-x86-64-linux-gnu amd64 15.2.0-12ubuntu1 [14.4 MB] 421s Get:28 http://ftpmaster.internal/ubuntu resolute/main amd64 g++-15 amd64 15.2.0-12ubuntu1 [25.3 kB] 421s Get:29 http://ftpmaster.internal/ubuntu resolute/main amd64 g++-x86-64-linux-gnu amd64 4:15.2.0-4ubuntu1 [966 B] 421s Get:30 http://ftpmaster.internal/ubuntu resolute/main amd64 g++ amd64 4:15.2.0-4ubuntu1 [1100 B] 421s Get:31 http://ftpmaster.internal/ubuntu resolute/main amd64 build-essential amd64 12.12ubuntu2 [5256 B] 421s Get:32 http://ftpmaster.internal/ubuntu resolute/main amd64 dctrl-tools amd64 2.24-3build4 [104 kB] 421s Get:33 http://ftpmaster.internal/ubuntu resolute/main amd64 fonts-dejavu-mono all 2.37-8build1 [502 kB] 421s Get:34 http://ftpmaster.internal/ubuntu resolute/main amd64 fonts-dejavu-core all 2.37-8build1 [834 kB] 421s Get:35 http://ftpmaster.internal/ubuntu resolute/main amd64 fontconfig-config amd64 2.17.1-3ubuntu1 [38.5 kB] 421s Get:36 http://ftpmaster.internal/ubuntu resolute/main amd64 libfontconfig1 amd64 2.17.1-3ubuntu1 [144 kB] 421s Get:37 http://ftpmaster.internal/ubuntu resolute/main amd64 fontconfig amd64 2.17.1-3ubuntu1 [180 kB] 421s Get:38 http://ftpmaster.internal/ubuntu resolute/main amd64 libgfortran5 amd64 16-20260208-1ubuntu1 [957 kB] 421s Get:39 http://ftpmaster.internal/ubuntu resolute/main amd64 libgfortran-15-dev amd64 15.2.0-12ubuntu1 [973 kB] 421s Get:40 http://ftpmaster.internal/ubuntu resolute/main amd64 gfortran-15-x86-64-linux-gnu amd64 15.2.0-12ubuntu1 [13.6 MB] 421s Get:41 http://ftpmaster.internal/ubuntu resolute/main amd64 gfortran-15 amd64 15.2.0-12ubuntu1 [18.1 kB] 421s Get:42 http://ftpmaster.internal/ubuntu resolute/main amd64 gfortran-x86-64-linux-gnu amd64 4:15.2.0-4ubuntu1 [1014 B] 421s Get:43 http://ftpmaster.internal/ubuntu resolute/main amd64 gfortran amd64 4:15.2.0-4ubuntu1 [1172 B] 421s Get:44 http://ftpmaster.internal/ubuntu resolute/main amd64 icu-devtools amd64 78.2-1ubuntu1 [214 kB] 421s Get:45 http://ftpmaster.internal/ubuntu resolute/main amd64 libblas3 amd64 3.12.1-7ubuntu1 [260 kB] 421s Get:46 http://ftpmaster.internal/ubuntu resolute/main amd64 libblas-dev amd64 3.12.1-7ubuntu1 [235 kB] 421s Get:47 http://ftpmaster.internal/ubuntu resolute/main amd64 libbz2-dev amd64 1.0.8-6build2 [36.2 kB] 421s Get:48 http://ftpmaster.internal/ubuntu resolute/main amd64 libpixman-1-0 amd64 0.46.4-1 [287 kB] 421s Get:49 http://ftpmaster.internal/ubuntu resolute/main amd64 libxcb-render0 amd64 1.17.0-2ubuntu1 [16.2 kB] 421s Get:50 http://ftpmaster.internal/ubuntu resolute/main amd64 libxcb-shm0 amd64 1.17.0-2ubuntu1 [5808 B] 421s Get:51 http://ftpmaster.internal/ubuntu resolute/main amd64 libxrender1 amd64 1:0.9.12-1 [19.8 kB] 421s Get:52 http://ftpmaster.internal/ubuntu resolute/main amd64 libcairo2 amd64 1.18.4-3 [579 kB] 421s Get:53 http://ftpmaster.internal/ubuntu resolute/main amd64 libdatrie1 amd64 0.2.14-1 [19.8 kB] 421s Get:54 http://ftpmaster.internal/ubuntu resolute/main amd64 libdeflate0 amd64 1.23-2build1 [51.6 kB] 421s Get:55 http://ftpmaster.internal/ubuntu resolute/main amd64 libdeflate-dev amd64 1.23-2build1 [58.8 kB] 421s Get:56 http://ftpmaster.internal/ubuntu resolute/main amd64 libgraphite2-3 amd64 1.3.14-11ubuntu1 [73.7 kB] 421s Get:57 http://ftpmaster.internal/ubuntu resolute/main amd64 libharfbuzz0b amd64 12.3.2-1 [519 kB] 421s Get:58 http://ftpmaster.internal/ubuntu resolute/main amd64 x11-common all 1:7.7+24ubuntu1 [22.4 kB] 421s Get:59 http://ftpmaster.internal/ubuntu resolute/main amd64 libice6 amd64 2:1.1.1-1build1 [44.0 kB] 421s Get:60 http://ftpmaster.internal/ubuntu resolute/main amd64 libicu-dev amd64 78.2-1ubuntu1 [12.5 MB] 421s Get:61 http://ftpmaster.internal/ubuntu resolute/main amd64 libjpeg-turbo8 amd64 2.1.5-4ubuntu3 [156 kB] 421s Get:62 http://ftpmaster.internal/ubuntu resolute/main amd64 libjpeg-turbo8-dev amd64 2.1.5-4ubuntu3 [300 kB] 421s Get:63 http://ftpmaster.internal/ubuntu resolute/main amd64 libjpeg8 amd64 8c-2ubuntu12 [2142 B] 421s Get:64 http://ftpmaster.internal/ubuntu resolute/main amd64 libjpeg8-dev amd64 8c-2ubuntu12 [1480 B] 421s Get:65 http://ftpmaster.internal/ubuntu resolute/main amd64 libjpeg-dev amd64 8c-2ubuntu12 [1480 B] 421s Get:66 http://ftpmaster.internal/ubuntu resolute/main amd64 liblapack3 amd64 3.12.1-7ubuntu1 [2739 kB] 421s Get:67 http://ftpmaster.internal/ubuntu resolute/main amd64 liblapack-dev amd64 3.12.1-7ubuntu1 [5433 kB] 421s Get:68 http://ftpmaster.internal/ubuntu resolute/main amd64 liblerc4 amd64 4.0.0+ds-5ubuntu2 [207 kB] 421s Get:69 http://ftpmaster.internal/ubuntu resolute/main amd64 libncurses-dev amd64 6.6+20251231-1 [389 kB] 421s Get:70 http://ftpmaster.internal/ubuntu resolute/main amd64 libthai-data all 0.1.30-1 [155 kB] 421s Get:71 http://ftpmaster.internal/ubuntu resolute/main amd64 libthai0 amd64 0.1.30-1 [19.2 kB] 421s Get:72 http://ftpmaster.internal/ubuntu resolute/main amd64 libpango-1.0-0 amd64 1.57.0-1 [241 kB] 421s Get:73 http://ftpmaster.internal/ubuntu resolute/main amd64 libpangoft2-1.0-0 amd64 1.57.0-1 [53.3 kB] 421s Get:74 http://ftpmaster.internal/ubuntu resolute/main amd64 libpangocairo-1.0-0 amd64 1.57.0-1 [29.0 kB] 421s Get:75 http://ftpmaster.internal/ubuntu resolute/main amd64 libpaper2 amd64 2.2.5-0.3build1 [17.3 kB] 421s Get:76 http://ftpmaster.internal/ubuntu resolute/main amd64 libpaper-utils amd64 2.2.5-0.3build1 [15.6 kB] 421s Get:77 http://ftpmaster.internal/ubuntu resolute/main amd64 libpcre2-16-0 amd64 10.46-1 [243 kB] 421s Get:78 http://ftpmaster.internal/ubuntu resolute/main amd64 libpcre2-32-0 amd64 10.46-1 [230 kB] 421s Get:79 http://ftpmaster.internal/ubuntu resolute/main amd64 libpcre2-posix3 amd64 10.46-1 [7354 B] 421s Get:80 http://ftpmaster.internal/ubuntu resolute/main amd64 libpcre2-dev amd64 10.46-1 [832 kB] 421s Get:81 http://ftpmaster.internal/ubuntu resolute/main amd64 libpkgconf3 amd64 1.8.1-4build1 [32.8 kB] 421s Get:82 http://ftpmaster.internal/ubuntu resolute/main amd64 zlib1g-dev amd64 1:1.3.dfsg+really1.3.1-1ubuntu2 [898 kB] 421s Get:83 http://ftpmaster.internal/ubuntu resolute/main amd64 libpng-dev amd64 1.6.54-1 [273 kB] 421s Get:84 http://ftpmaster.internal/ubuntu resolute/main amd64 libreadline-dev amd64 8.3-3 [189 kB] 421s Get:85 http://ftpmaster.internal/ubuntu resolute/main amd64 libsharpyuv0 amd64 1.5.0-0.1build1 [17.6 kB] 421s Get:86 http://ftpmaster.internal/ubuntu resolute/main amd64 libsm6 amd64 2:1.2.6-1build1 [16.9 kB] 421s Get:87 http://ftpmaster.internal/ubuntu resolute/main amd64 libtcl8.6 amd64 8.6.17+dfsg-1build1 [1003 kB] 421s Get:88 http://ftpmaster.internal/ubuntu resolute/main amd64 libjbig0 amd64 2.1-6.1ubuntu3 [30.0 kB] 421s Get:89 http://ftpmaster.internal/ubuntu resolute/main amd64 libwebp7 amd64 1.5.0-0.1build1 [264 kB] 421s Get:90 http://ftpmaster.internal/ubuntu resolute/main amd64 libtiff6 amd64 4.7.0-3ubuntu3 [209 kB] 421s Get:91 http://ftpmaster.internal/ubuntu resolute/main amd64 libxft2 amd64 2.3.6-1build2 [45.1 kB] 421s Get:92 http://ftpmaster.internal/ubuntu resolute/main amd64 libxss1 amd64 1:1.2.3-1build4 [7084 B] 421s Get:93 http://ftpmaster.internal/ubuntu resolute/main amd64 libtk8.6 amd64 8.6.17-1 [823 kB] 421s Get:94 http://ftpmaster.internal/ubuntu resolute/main amd64 libxt6t64 amd64 1:1.2.1-1.3 [173 kB] 421s Get:95 http://ftpmaster.internal/ubuntu resolute/main amd64 libzstd-dev amd64 1.5.7+dfsg-3 [376 kB] 421s Get:96 http://ftpmaster.internal/ubuntu resolute/main amd64 zip amd64 3.0-15ubuntu3 [175 kB] 422s Get:97 http://ftpmaster.internal/ubuntu resolute/main amd64 unzip amd64 6.0-29ubuntu1 [180 kB] 422s Get:98 http://ftpmaster.internal/ubuntu resolute/main amd64 xdg-utils all 1.2.1-2ubuntu2 [66.1 kB] 422s Get:99 http://ftpmaster.internal/ubuntu resolute/universe amd64 r-base-core amd64 4.5.2-1ubuntu2 [28.8 MB] 422s Get:100 http://ftpmaster.internal/ubuntu resolute/main amd64 liblzma-dev amd64 5.8.2-2 [179 kB] 422s Get:101 http://ftpmaster.internal/ubuntu resolute/main amd64 pkgconf-bin amd64 1.8.1-4build1 [21.7 kB] 422s Get:102 http://ftpmaster.internal/ubuntu resolute/main amd64 pkgconf amd64 1.8.1-4build1 [16.8 kB] 422s Get:103 http://ftpmaster.internal/ubuntu resolute/main amd64 libtirpc-dev amd64 1.3.6+ds-1 [195 kB] 422s Get:104 http://ftpmaster.internal/ubuntu resolute/universe amd64 r-base-dev all 4.5.2-1ubuntu2 [1880 B] 422s Get:105 http://ftpmaster.internal/ubuntu resolute/universe amd64 pkg-r-autopkgtest all 20250812 [6158 B] 422s Get:106 http://ftpmaster.internal/ubuntu resolute/universe amd64 r-bioc-biocgenerics all 0.52.0-2 [624 kB] 422s Get:107 http://ftpmaster.internal/ubuntu resolute/universe amd64 r-cran-r.methodss3 all 1.8.2-1 [84.0 kB] 422s Get:108 http://ftpmaster.internal/ubuntu resolute/universe amd64 r-cran-r.oo all 1.27.1-1 [978 kB] 422s Get:109 http://ftpmaster.internal/ubuntu resolute/universe amd64 r-cran-r.utils all 2.13.0-1 [1423 kB] 422s Get:110 http://ftpmaster.internal/ubuntu resolute/universe amd64 r-cran-matrixstats amd64 1.5.0-1 [542 kB] 422s Get:111 http://ftpmaster.internal/ubuntu resolute/universe amd64 r-bioc-aroma.light all 3.36.0-2 [583 kB] 422s Get:112 http://ftpmaster.internal/ubuntu resolute/universe amd64 r-bioc-dnacopy amd64 1.80.0-2 [500 kB] 422s Get:113 http://ftpmaster.internal/ubuntu resolute/universe amd64 r-cran-cli amd64 3.6.4-1 [1394 kB] 422s Get:114 http://ftpmaster.internal/ubuntu resolute/universe amd64 r-cran-codetools all 0.2-20-1build1 [91.1 kB] 422s Get:115 http://ftpmaster.internal/ubuntu resolute/universe amd64 r-cran-digest amd64 0.6.39-1 [203 kB] 422s Get:116 http://ftpmaster.internal/ubuntu resolute/universe amd64 r-cran-farver amd64 2.1.2-1 [1355 kB] 422s Get:117 http://ftpmaster.internal/ubuntu resolute/universe amd64 r-cran-globals all 0.19.0-1 [160 kB] 422s Get:118 http://ftpmaster.internal/ubuntu resolute/universe amd64 r-cran-listenv all 0.10.0+dfsg-1 [113 kB] 422s Get:119 http://ftpmaster.internal/ubuntu resolute/universe amd64 r-cran-parallelly amd64 1.42.0-1 [540 kB] 422s Get:120 http://ftpmaster.internal/ubuntu resolute/universe amd64 r-cran-future all 1.34.0+dfsg-1 [646 kB] 422s Get:121 http://ftpmaster.internal/ubuntu resolute/universe amd64 r-cran-glue amd64 1.8.0-1 [164 kB] 422s Get:122 http://ftpmaster.internal/ubuntu resolute/universe amd64 r-cran-rlang amd64 1.1.5-3 [1721 kB] 422s Get:123 http://ftpmaster.internal/ubuntu resolute/universe amd64 r-cran-lifecycle all 1.0.5+dfsg-1 [120 kB] 422s Get:124 http://ftpmaster.internal/ubuntu resolute/universe amd64 r-cran-gtable all 0.3.6+dfsg-1 [199 kB] 422s Get:125 http://ftpmaster.internal/ubuntu resolute/universe amd64 r-cran-isoband amd64 0.2.7-1 [1481 kB] 422s Get:126 http://ftpmaster.internal/ubuntu resolute/universe amd64 r-cran-s7 amd64 0.2.0-1 [328 kB] 422s Get:127 http://ftpmaster.internal/ubuntu resolute/universe amd64 r-cran-labeling all 0.4.3-1 [62.1 kB] 422s Get:128 http://ftpmaster.internal/ubuntu resolute/universe amd64 r-cran-r6 all 2.6.1-1 [101 kB] 422s Get:129 http://ftpmaster.internal/ubuntu resolute/universe amd64 r-cran-rcolorbrewer all 1.1-3-1build2 [54.0 kB] 422s Get:130 http://ftpmaster.internal/ubuntu resolute/universe amd64 r-cran-viridislite all 0.4.3-1 [1088 kB] 422s Get:131 http://ftpmaster.internal/ubuntu resolute/universe amd64 r-cran-scales all 1.4.0-1 [725 kB] 423s Get:132 http://ftpmaster.internal/ubuntu resolute/universe amd64 r-cran-vctrs amd64 0.6.5-1 [1335 kB] 423s Get:133 http://ftpmaster.internal/ubuntu resolute/universe amd64 r-cran-withr all 3.0.2+dfsg-1 [214 kB] 423s Get:134 http://ftpmaster.internal/ubuntu resolute-proposed/universe amd64 r-cran-ggplot2 all 4.0.2+dfsg-1 [4941 kB] 423s Get:135 http://ftpmaster.internal/ubuntu resolute/universe amd64 r-cran-r.cache all 0.17.0-1 [117 kB] 423s Get:136 http://ftpmaster.internal/ubuntu resolute/universe amd64 r-cran-pscbs all 0.68.0-1 [4234 kB] 423s Preconfiguring packages ... 423s Fetched 178 MB in 4s (46.3 MB/s) 423s Selecting previously unselected package libc-dev-bin. 423s (Reading database ... (Reading database ... 5% (Reading database ... 10% (Reading database ... 15% (Reading database ... 20% (Reading database ... 25% (Reading database ... 30% (Reading database ... 35% (Reading database ... 40% (Reading database ... 45% (Reading database ... 50% (Reading database ... 55% (Reading database ... 60% (Reading database ... 65% (Reading database ... 70% (Reading database ... 75% (Reading database ... 80% (Reading database ... 85% (Reading database ... 90% (Reading database ... 95% (Reading database ... 100% (Reading database ... 125269 files and directories currently installed.) 423s Preparing to unpack .../000-libc-dev-bin_2.42-2ubuntu4_amd64.deb ... 423s Unpacking libc-dev-bin (2.42-2ubuntu4) ... 423s Selecting previously unselected package linux-libc-dev:amd64. 423s Preparing to unpack .../001-linux-libc-dev_6.19.0-3.3_amd64.deb ... 423s Unpacking linux-libc-dev:amd64 (6.19.0-3.3) ... 423s Selecting previously unselected package libcrypt-dev:amd64. 423s Preparing to unpack .../002-libcrypt-dev_1%3a4.5.1-1_amd64.deb ... 423s Unpacking libcrypt-dev:amd64 (1:4.5.1-1) ... 423s Selecting previously unselected package rpcsvc-proto. 423s Preparing to unpack .../003-rpcsvc-proto_1.4.3-1build1_amd64.deb ... 423s Unpacking rpcsvc-proto (1.4.3-1build1) ... 423s Selecting previously unselected package libc6-dev:amd64. 423s Preparing to unpack .../004-libc6-dev_2.42-2ubuntu4_amd64.deb ... 423s Unpacking libc6-dev:amd64 (2.42-2ubuntu4) ... 423s Selecting previously unselected package libisl23:amd64. 423s Preparing to unpack .../005-libisl23_0.27-1build1_amd64.deb ... 423s Unpacking libisl23:amd64 (0.27-1build1) ... 423s Selecting previously unselected package libmpc3:amd64. 423s Preparing to unpack .../006-libmpc3_1.3.1-2_amd64.deb ... 423s Unpacking libmpc3:amd64 (1.3.1-2) ... 423s Selecting previously unselected package cpp-15-x86-64-linux-gnu. 423s Preparing to unpack .../007-cpp-15-x86-64-linux-gnu_15.2.0-12ubuntu1_amd64.deb ... 423s Unpacking cpp-15-x86-64-linux-gnu (15.2.0-12ubuntu1) ... 423s Selecting previously unselected package cpp-15. 423s Preparing to unpack .../008-cpp-15_15.2.0-12ubuntu1_amd64.deb ... 423s Unpacking cpp-15 (15.2.0-12ubuntu1) ... 423s Selecting previously unselected package cpp-x86-64-linux-gnu. 423s Preparing to unpack .../009-cpp-x86-64-linux-gnu_4%3a15.2.0-4ubuntu1_amd64.deb ... 423s Unpacking cpp-x86-64-linux-gnu (4:15.2.0-4ubuntu1) ... 424s Selecting previously unselected package cpp. 424s Preparing to unpack .../010-cpp_4%3a15.2.0-4ubuntu1_amd64.deb ... 424s Unpacking cpp (4:15.2.0-4ubuntu1) ... 424s Selecting previously unselected package libcc1-0:amd64. 424s Preparing to unpack .../011-libcc1-0_16-20260208-1ubuntu1_amd64.deb ... 424s Unpacking libcc1-0:amd64 (16-20260208-1ubuntu1) ... 424s Selecting previously unselected package libgomp1:amd64. 424s Preparing to unpack .../012-libgomp1_16-20260208-1ubuntu1_amd64.deb ... 424s Unpacking libgomp1:amd64 (16-20260208-1ubuntu1) ... 424s Selecting previously unselected package libitm1:amd64. 424s Preparing to unpack .../013-libitm1_16-20260208-1ubuntu1_amd64.deb ... 424s Unpacking libitm1:amd64 (16-20260208-1ubuntu1) ... 424s Selecting previously unselected package libasan8:amd64. 424s Preparing to unpack .../014-libasan8_16-20260208-1ubuntu1_amd64.deb ... 424s Unpacking libasan8:amd64 (16-20260208-1ubuntu1) ... 424s Selecting previously unselected package liblsan0:amd64. 424s Preparing to unpack .../015-liblsan0_16-20260208-1ubuntu1_amd64.deb ... 424s Unpacking liblsan0:amd64 (16-20260208-1ubuntu1) ... 424s Selecting previously unselected package libtsan2:amd64. 424s Preparing to unpack .../016-libtsan2_16-20260208-1ubuntu1_amd64.deb ... 424s Unpacking libtsan2:amd64 (16-20260208-1ubuntu1) ... 424s Selecting previously unselected package libubsan1:amd64. 424s Preparing to unpack .../017-libubsan1_16-20260208-1ubuntu1_amd64.deb ... 424s Unpacking libubsan1:amd64 (16-20260208-1ubuntu1) ... 424s Selecting previously unselected package libhwasan0:amd64. 424s Preparing to unpack .../018-libhwasan0_16-20260208-1ubuntu1_amd64.deb ... 424s Unpacking libhwasan0:amd64 (16-20260208-1ubuntu1) ... 424s Selecting previously unselected package libquadmath0:amd64. 424s Preparing to unpack .../019-libquadmath0_16-20260208-1ubuntu1_amd64.deb ... 424s Unpacking libquadmath0:amd64 (16-20260208-1ubuntu1) ... 424s Selecting previously unselected package libgcc-15-dev:amd64. 424s Preparing to unpack .../020-libgcc-15-dev_15.2.0-12ubuntu1_amd64.deb ... 424s Unpacking libgcc-15-dev:amd64 (15.2.0-12ubuntu1) ... 424s Selecting previously unselected package gcc-15-x86-64-linux-gnu. 424s Preparing to unpack .../021-gcc-15-x86-64-linux-gnu_15.2.0-12ubuntu1_amd64.deb ... 424s Unpacking gcc-15-x86-64-linux-gnu (15.2.0-12ubuntu1) ... 424s Selecting previously unselected package gcc-15. 424s Preparing to unpack .../022-gcc-15_15.2.0-12ubuntu1_amd64.deb ... 424s Unpacking gcc-15 (15.2.0-12ubuntu1) ... 424s Selecting previously unselected package gcc-x86-64-linux-gnu. 424s Preparing to unpack .../023-gcc-x86-64-linux-gnu_4%3a15.2.0-4ubuntu1_amd64.deb ... 424s Unpacking gcc-x86-64-linux-gnu (4:15.2.0-4ubuntu1) ... 424s Selecting previously unselected package gcc. 424s Preparing to unpack .../024-gcc_4%3a15.2.0-4ubuntu1_amd64.deb ... 424s Unpacking gcc (4:15.2.0-4ubuntu1) ... 424s Selecting previously unselected package libstdc++-15-dev:amd64. 424s Preparing to unpack .../025-libstdc++-15-dev_15.2.0-12ubuntu1_amd64.deb ... 424s Unpacking libstdc++-15-dev:amd64 (15.2.0-12ubuntu1) ... 424s Selecting previously unselected package g++-15-x86-64-linux-gnu. 424s Preparing to unpack .../026-g++-15-x86-64-linux-gnu_15.2.0-12ubuntu1_amd64.deb ... 424s Unpacking g++-15-x86-64-linux-gnu (15.2.0-12ubuntu1) ... 424s Selecting previously unselected package g++-15. 424s Preparing to unpack .../027-g++-15_15.2.0-12ubuntu1_amd64.deb ... 424s Unpacking g++-15 (15.2.0-12ubuntu1) ... 424s Selecting previously unselected package g++-x86-64-linux-gnu. 424s Preparing to unpack .../028-g++-x86-64-linux-gnu_4%3a15.2.0-4ubuntu1_amd64.deb ... 424s Unpacking g++-x86-64-linux-gnu (4:15.2.0-4ubuntu1) ... 424s Selecting previously unselected package g++. 424s Preparing to unpack .../029-g++_4%3a15.2.0-4ubuntu1_amd64.deb ... 424s Unpacking g++ (4:15.2.0-4ubuntu1) ... 424s Selecting previously unselected package build-essential. 424s Preparing to unpack .../030-build-essential_12.12ubuntu2_amd64.deb ... 424s Unpacking build-essential (12.12ubuntu2) ... 424s Selecting previously unselected package dctrl-tools. 424s Preparing to unpack .../031-dctrl-tools_2.24-3build4_amd64.deb ... 424s Unpacking dctrl-tools (2.24-3build4) ... 424s Selecting previously unselected package fonts-dejavu-mono. 424s Preparing to unpack .../032-fonts-dejavu-mono_2.37-8build1_all.deb ... 424s Unpacking fonts-dejavu-mono (2.37-8build1) ... 424s Selecting previously unselected package fonts-dejavu-core. 424s Preparing to unpack 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.../038-libgfortran-15-dev_15.2.0-12ubuntu1_amd64.deb ... 425s Unpacking libgfortran-15-dev:amd64 (15.2.0-12ubuntu1) ... 425s Selecting previously unselected package gfortran-15-x86-64-linux-gnu. 425s Preparing to unpack .../039-gfortran-15-x86-64-linux-gnu_15.2.0-12ubuntu1_amd64.deb ... 425s Unpacking gfortran-15-x86-64-linux-gnu (15.2.0-12ubuntu1) ... 425s Selecting previously unselected package gfortran-15. 425s Preparing to unpack .../040-gfortran-15_15.2.0-12ubuntu1_amd64.deb ... 425s Unpacking gfortran-15 (15.2.0-12ubuntu1) ... 425s Selecting previously unselected package gfortran-x86-64-linux-gnu. 425s Preparing to unpack .../041-gfortran-x86-64-linux-gnu_4%3a15.2.0-4ubuntu1_amd64.deb ... 425s Unpacking gfortran-x86-64-linux-gnu (4:15.2.0-4ubuntu1) ... 425s Selecting previously unselected package gfortran. 425s Preparing to unpack .../042-gfortran_4%3a15.2.0-4ubuntu1_amd64.deb ... 425s Unpacking gfortran (4:15.2.0-4ubuntu1) ... 425s Selecting previously unselected package icu-devtools. 425s Preparing to unpack .../043-icu-devtools_78.2-1ubuntu1_amd64.deb ... 425s Unpacking icu-devtools (78.2-1ubuntu1) ... 425s Selecting previously unselected package libblas3:amd64. 425s Preparing to unpack .../044-libblas3_3.12.1-7ubuntu1_amd64.deb ... 425s Unpacking libblas3:amd64 (3.12.1-7ubuntu1) ... 425s Selecting previously unselected package libblas-dev:amd64. 425s Preparing to unpack .../045-libblas-dev_3.12.1-7ubuntu1_amd64.deb ... 425s Unpacking libblas-dev:amd64 (3.12.1-7ubuntu1) ... 425s Selecting previously unselected package libbz2-dev:amd64. 425s Preparing to unpack .../046-libbz2-dev_1.0.8-6build2_amd64.deb ... 425s Unpacking libbz2-dev:amd64 (1.0.8-6build2) ... 425s Selecting previously unselected package libpixman-1-0:amd64. 425s Preparing to unpack .../047-libpixman-1-0_0.46.4-1_amd64.deb ... 425s Unpacking libpixman-1-0:amd64 (0.46.4-1) ... 425s Selecting previously unselected package libxcb-render0:amd64. 425s Preparing to unpack .../048-libxcb-render0_1.17.0-2ubuntu1_amd64.deb ... 425s Unpacking libxcb-render0:amd64 (1.17.0-2ubuntu1) ... 425s Selecting previously unselected package libxcb-shm0:amd64. 425s Preparing to unpack .../049-libxcb-shm0_1.17.0-2ubuntu1_amd64.deb ... 425s Unpacking libxcb-shm0:amd64 (1.17.0-2ubuntu1) ... 425s Selecting previously unselected package libxrender1:amd64. 425s Preparing to unpack .../050-libxrender1_1%3a0.9.12-1_amd64.deb ... 425s Unpacking libxrender1:amd64 (1:0.9.12-1) ... 425s Selecting previously unselected package libcairo2:amd64. 425s Preparing to unpack .../051-libcairo2_1.18.4-3_amd64.deb ... 425s Unpacking libcairo2:amd64 (1.18.4-3) ... 425s Selecting previously unselected package libdatrie1:amd64. 425s Preparing to unpack .../052-libdatrie1_0.2.14-1_amd64.deb ... 425s Unpacking libdatrie1:amd64 (0.2.14-1) ... 425s Selecting previously unselected package libdeflate0:amd64. 425s Preparing to unpack .../053-libdeflate0_1.23-2build1_amd64.deb ... 425s Unpacking libdeflate0:amd64 (1.23-2build1) ... 425s Selecting previously unselected package libdeflate-dev:amd64. 425s Preparing to unpack .../054-libdeflate-dev_1.23-2build1_amd64.deb ... 425s Unpacking libdeflate-dev:amd64 (1.23-2build1) ... 425s Selecting previously unselected package libgraphite2-3:amd64. 425s Preparing to unpack .../055-libgraphite2-3_1.3.14-11ubuntu1_amd64.deb ... 425s Unpacking libgraphite2-3:amd64 (1.3.14-11ubuntu1) ... 425s Selecting previously unselected package libharfbuzz0b:amd64. 425s Preparing to unpack .../056-libharfbuzz0b_12.3.2-1_amd64.deb ... 425s Unpacking libharfbuzz0b:amd64 (12.3.2-1) ... 425s Selecting previously unselected package x11-common. 425s Preparing to unpack .../057-x11-common_1%3a7.7+24ubuntu1_all.deb ... 425s Unpacking x11-common (1:7.7+24ubuntu1) ... 425s Selecting previously unselected package libice6:amd64. 425s Preparing to unpack .../058-libice6_2%3a1.1.1-1build1_amd64.deb ... 425s Unpacking libice6:amd64 (2:1.1.1-1build1) ... 425s Selecting previously unselected package libicu-dev:amd64. 425s Preparing to unpack .../059-libicu-dev_78.2-1ubuntu1_amd64.deb ... 425s Unpacking libicu-dev:amd64 (78.2-1ubuntu1) ... 425s Selecting previously unselected package libjpeg-turbo8:amd64. 425s Preparing to unpack .../060-libjpeg-turbo8_2.1.5-4ubuntu3_amd64.deb ... 425s Unpacking libjpeg-turbo8:amd64 (2.1.5-4ubuntu3) ... 425s Selecting previously unselected package libjpeg-turbo8-dev:amd64. 425s Preparing to unpack .../061-libjpeg-turbo8-dev_2.1.5-4ubuntu3_amd64.deb ... 425s Unpacking libjpeg-turbo8-dev:amd64 (2.1.5-4ubuntu3) ... 425s Selecting previously unselected package libjpeg8:amd64. 425s Preparing to unpack .../062-libjpeg8_8c-2ubuntu12_amd64.deb ... 425s Unpacking libjpeg8:amd64 (8c-2ubuntu12) ... 425s Selecting previously unselected package libjpeg8-dev:amd64. 425s Preparing to unpack .../063-libjpeg8-dev_8c-2ubuntu12_amd64.deb ... 425s Unpacking libjpeg8-dev:amd64 (8c-2ubuntu12) ... 425s Selecting previously unselected package libjpeg-dev:amd64. 425s Preparing to unpack .../064-libjpeg-dev_8c-2ubuntu12_amd64.deb ... 425s Unpacking libjpeg-dev:amd64 (8c-2ubuntu12) ... 425s Selecting previously unselected package liblapack3:amd64. 425s Preparing to unpack .../065-liblapack3_3.12.1-7ubuntu1_amd64.deb ... 425s Unpacking liblapack3:amd64 (3.12.1-7ubuntu1) ... 425s Selecting previously unselected package liblapack-dev:amd64. 425s Preparing to unpack .../066-liblapack-dev_3.12.1-7ubuntu1_amd64.deb ... 425s Unpacking liblapack-dev:amd64 (3.12.1-7ubuntu1) ... 425s Selecting previously unselected package liblerc4:amd64. 425s Preparing to unpack .../067-liblerc4_4.0.0+ds-5ubuntu2_amd64.deb ... 425s Unpacking liblerc4:amd64 (4.0.0+ds-5ubuntu2) ... 425s Selecting previously unselected package libncurses-dev:amd64. 425s Preparing to unpack .../068-libncurses-dev_6.6+20251231-1_amd64.deb ... 425s Unpacking libncurses-dev:amd64 (6.6+20251231-1) ... 425s Selecting previously unselected package libthai-data. 425s Preparing to unpack .../069-libthai-data_0.1.30-1_all.deb ... 425s Unpacking libthai-data (0.1.30-1) ... 425s Selecting previously unselected package libthai0:amd64. 426s Preparing to unpack .../070-libthai0_0.1.30-1_amd64.deb ... 426s Unpacking libthai0:amd64 (0.1.30-1) ... 426s Selecting previously unselected package libpango-1.0-0:amd64. 426s Preparing to unpack .../071-libpango-1.0-0_1.57.0-1_amd64.deb ... 426s Unpacking libpango-1.0-0:amd64 (1.57.0-1) ... 426s Selecting previously unselected package libpangoft2-1.0-0:amd64. 426s Preparing to unpack .../072-libpangoft2-1.0-0_1.57.0-1_amd64.deb ... 426s Unpacking libpangoft2-1.0-0:amd64 (1.57.0-1) ... 426s Selecting previously unselected package libpangocairo-1.0-0:amd64. 426s Preparing to unpack .../073-libpangocairo-1.0-0_1.57.0-1_amd64.deb ... 426s Unpacking libpangocairo-1.0-0:amd64 (1.57.0-1) ... 426s Selecting previously unselected package libpaper2:amd64. 426s Preparing to unpack .../074-libpaper2_2.2.5-0.3build1_amd64.deb ... 426s Unpacking libpaper2:amd64 (2.2.5-0.3build1) ... 426s Selecting previously unselected package libpaper-utils. 426s Preparing to unpack .../075-libpaper-utils_2.2.5-0.3build1_amd64.deb ... 426s Unpacking libpaper-utils (2.2.5-0.3build1) ... 426s Selecting previously unselected package libpcre2-16-0:amd64. 426s Preparing to unpack .../076-libpcre2-16-0_10.46-1_amd64.deb ... 426s Unpacking libpcre2-16-0:amd64 (10.46-1) ... 426s Selecting previously unselected package libpcre2-32-0:amd64. 426s Preparing to unpack .../077-libpcre2-32-0_10.46-1_amd64.deb ... 426s Unpacking libpcre2-32-0:amd64 (10.46-1) ... 426s Selecting previously unselected package libpcre2-posix3:amd64. 426s Preparing to unpack .../078-libpcre2-posix3_10.46-1_amd64.deb ... 426s Unpacking libpcre2-posix3:amd64 (10.46-1) ... 426s Selecting previously unselected package libpcre2-dev:amd64. 426s Preparing to unpack .../079-libpcre2-dev_10.46-1_amd64.deb ... 426s Unpacking libpcre2-dev:amd64 (10.46-1) ... 426s Selecting previously unselected package libpkgconf3:amd64. 426s Preparing to unpack .../080-libpkgconf3_1.8.1-4build1_amd64.deb ... 426s Unpacking libpkgconf3:amd64 (1.8.1-4build1) ... 426s Selecting previously unselected package zlib1g-dev:amd64. 426s Preparing to unpack .../081-zlib1g-dev_1%3a1.3.dfsg+really1.3.1-1ubuntu2_amd64.deb ... 426s Unpacking zlib1g-dev:amd64 (1:1.3.dfsg+really1.3.1-1ubuntu2) ... 426s Selecting previously unselected package libpng-dev:amd64. 426s Preparing to unpack .../082-libpng-dev_1.6.54-1_amd64.deb ... 426s Unpacking libpng-dev:amd64 (1.6.54-1) ... 426s Selecting previously unselected package libreadline-dev:amd64. 426s Preparing to unpack .../083-libreadline-dev_8.3-3_amd64.deb ... 426s Unpacking libreadline-dev:amd64 (8.3-3) ... 426s Selecting previously unselected package libsharpyuv0:amd64. 426s Preparing to unpack .../084-libsharpyuv0_1.5.0-0.1build1_amd64.deb ... 426s Unpacking libsharpyuv0:amd64 (1.5.0-0.1build1) ... 426s Selecting previously unselected package libsm6:amd64. 426s Preparing to unpack .../085-libsm6_2%3a1.2.6-1build1_amd64.deb ... 426s Unpacking libsm6:amd64 (2:1.2.6-1build1) ... 426s Selecting previously unselected package libtcl8.6:amd64. 426s Preparing to unpack .../086-libtcl8.6_8.6.17+dfsg-1build1_amd64.deb ... 426s Unpacking libtcl8.6:amd64 (8.6.17+dfsg-1build1) ... 426s Selecting previously unselected package libjbig0:amd64. 426s Preparing to unpack .../087-libjbig0_2.1-6.1ubuntu3_amd64.deb ... 426s Unpacking libjbig0:amd64 (2.1-6.1ubuntu3) ... 426s Selecting previously unselected package libwebp7:amd64. 426s Preparing to unpack .../088-libwebp7_1.5.0-0.1build1_amd64.deb ... 426s Unpacking libwebp7:amd64 (1.5.0-0.1build1) ... 426s Selecting previously unselected package libtiff6:amd64. 426s Preparing to unpack .../089-libtiff6_4.7.0-3ubuntu3_amd64.deb ... 426s Unpacking libtiff6:amd64 (4.7.0-3ubuntu3) ... 426s Selecting previously unselected package libxft2:amd64. 426s Preparing to unpack .../090-libxft2_2.3.6-1build2_amd64.deb ... 426s Unpacking libxft2:amd64 (2.3.6-1build2) ... 426s Selecting previously unselected package libxss1:amd64. 426s Preparing to unpack .../091-libxss1_1%3a1.2.3-1build4_amd64.deb ... 426s Unpacking libxss1:amd64 (1:1.2.3-1build4) ... 426s Selecting previously unselected package libtk8.6:amd64. 426s Preparing to unpack .../092-libtk8.6_8.6.17-1_amd64.deb ... 426s Unpacking libtk8.6:amd64 (8.6.17-1) ... 426s Selecting previously unselected package libxt6t64:amd64. 426s Preparing to unpack .../093-libxt6t64_1%3a1.2.1-1.3_amd64.deb ... 426s Unpacking libxt6t64:amd64 (1:1.2.1-1.3) ... 426s Selecting previously unselected package libzstd-dev:amd64. 426s Preparing to unpack .../094-libzstd-dev_1.5.7+dfsg-3_amd64.deb ... 426s Unpacking libzstd-dev:amd64 (1.5.7+dfsg-3) ... 426s Selecting previously unselected package zip. 426s Preparing to unpack .../095-zip_3.0-15ubuntu3_amd64.deb ... 426s Unpacking zip 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pkg-r-autopkgtest: /usr/share/dh-r/pkg-r-autopkgtest 432s autopkgtest [05:55:15]: test pkg-r-autopkgtest: [----------------------- 432s Test: Try to load the R library PSCBS 432s 432s R version 4.5.2 (2025-10-31) -- "[Not] Part in a Rumble" 432s Copyright (C) 2025 The R Foundation for Statistical Computing 432s Platform: x86_64-pc-linux-gnu 432s 432s R is free software and comes with ABSOLUTELY NO WARRANTY. 432s You are welcome to redistribute it under certain conditions. 432s Type 'license()' or 'licence()' for distribution details. 432s 432s R is a collaborative project with many contributors. 432s Type 'contributors()' for more information and 432s 'citation()' on how to cite R or R packages in publications. 432s 432s Type 'demo()' for some demos, 'help()' for on-line help, or 432s 'help.start()' for an HTML browser interface to help. 432s Type 'q()' to quit R. 432s 432s > library('PSCBS') 432s PSCBS v0.68.0 (2025-04-18 19:40:02 UTC) successfully loaded. See ?PSCBS for help. 432s > 432s Test: Run tests for PSCBS 432s Start: PairedPSCBS,boot.R 432s 432s R version 4.5.2 (2025-10-31) -- "[Not] Part in a Rumble" 432s Copyright (C) 2025 The R Foundation for Statistical Computing 432s Platform: x86_64-pc-linux-gnu 432s 432s R is free software and comes with ABSOLUTELY NO WARRANTY. 432s You are welcome to redistribute it under certain conditions. 432s Type 'license()' or 'licence()' for distribution details. 432s 432s R is a collaborative project with many contributors. 432s Type 'contributors()' for more information and 432s 'citation()' on how to cite R or R packages in publications. 432s 432s Type 'demo()' for some demos, 'help()' for on-line help, or 432s 'help.start()' for an HTML browser interface to help. 432s Type 'q()' to quit R. 432s 433s > ########################################################### 433s > # This tests: 433s > # - Bootstrapping for PairedPSCBS objects 433s > ########################################################### 433s > library("PSCBS") 433s PSCBS v0.68.0 (2025-04-18 19:40:02 UTC) successfully loaded. See ?PSCBS for help. 433s > 433s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 433s > # Load SNP microarray data 433s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 433s > data <- PSCBS::exampleData("paired.chr01") 433s > 433s > 433s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 433s > # Paired PSCBS segmentation 433s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 433s > # Drop single-locus outliers 433s > dataS <- dropSegmentationOutliers(data) 433s > dataS <- dataS[seq(from=1, to=nrow(data), by=5),] 433s > nSegs <- 4L 433s > str(dataS) 433s 'data.frame': 14670 obs. of 6 variables: 433s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 433s $ x : int 1145994 2941694 3710825 4240737 4276892 4464544 4714611 5095111 5034491 5158416 ... 433s $ CT : num 1.63 1.4 1.41 1.17 1.16 ... 433s $ betaT : num 0.7574 0.169 0.2357 0.2604 0.0576 ... 433s $ CN : num 2.36 2.13 2.26 2.01 2.32 ... 433s $ betaN : num 0.8274 0.5072 0.1671 0.1609 0.0421 ... 433s > # Segment known regions 433s > knownSegments <- data.frame( 433s + chromosome = c( 1, 1, 1), 433s + start = c( -Inf, NA, 141510003), 433s + end = c(120992603, NA, +Inf) 433s + ) 433s > fit <- segmentByPairedPSCBS(dataS, knownSegments=knownSegments, avgDH="median", seed=0xBEEF) 433s > print(fit) 433s chromosome tcnId dhId start end tcnNbrOfLoci tcnMean tcnNbrOfSNPs 433s 1 1 1 1 554484 120992603 7586 1.385258 2108 433s 2 NA 2 1 NA NA NA NA 0 433s 3 1 3 1 141510003 185449813 2681 2.068861 777 433s 4 1 4 1 185449813 247137334 4391 2.634110 1311 433s tcnNbrOfHets dhNbrOfLoci dhMean c1Mean c2Mean 433s 1 2108 2108 0.54551245 0.3147912 1.070467 433s 2 0 0 NA NA NA 433s 3 777 777 0.07132277 0.9606521 1.108209 433s 4 1311 1311 0.21663871 1.0317300 1.602380 433s > 433s > 433s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 433s > # Bootstrap 433s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 433s > B <- 1L 433s > seed <- 0xBEEF 433s > probs <- c(0.025, 0.05, 0.95, 0.975) 433s > 433s > sets <- getBootstrapLocusSets(fit, B=B, seed=seed) 433s > 433s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 433s > # Subset by first segment 433s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 433s > ss <- 1L 433s > 433s > fitT <- extractSegment(fit, ss) 433s > dataT <- getLocusData(fitT) 433s > segsT <- getSegments(fitT) 433s > 433s > # Truth 433s > bootT <- bootstrapSegmentsAndChangepoints(fitT, B=B, seed=seed) 433s > bootT1 <- bootT$segments[1L,,,drop=FALSE] 433s > types <- dimnames(bootT1)[[3L]] 433s > dim(bootT1) <- dim(bootT1)[-1L] 433s > colnames(bootT1) <- types 433s > sumsT <- apply(bootT1, MARGIN=2L, FUN=quantile, probs=probs) 433s > print(sumsT) 433s tcn dh c1 c2 433s 2.5% 1.383213 0.5466788 0.3135198 1.069693 433s 5% 1.383213 0.5466788 0.3135198 1.069693 433s 95% 1.383213 0.5466788 0.3135198 1.069693 433s 97.5% 1.383213 0.5466788 0.3135198 1.069693 433s > 433s > fitTB <- bootstrapTCNandDHByRegion(fitT, B=B, seed=seed) 433s > segsTB <- getSegments(fitTB) 433s > segsTB <- unlist(segsTB[,grep("_", colnames(segsTB))]) 433s > dim(segsTB) <- dim(sumsT) 433s > dimnames(segsTB) <- dimnames(sumsT) 433s > print(segsTB) 433s tcn dh c1 c2 433s 2.5% 1.383213 0.5466788 0.3135198 1.069693 433s 5% 1.383213 0.5466788 0.3135198 1.069693 433s 95% 1.383213 0.5466788 0.3135198 1.069693 433s 97.5% 1.383213 0.5466788 0.3135198 1.069693 433s > 433s > # Sanity check 433s > stopifnot(all.equal(segsTB, sumsT)) 433s > 433s > # Calculate summaries using the existing bootstrap samples 433s > fitTBp <- bootstrapTCNandDHByRegion(fitT, .boot=bootT) 434s > # Sanity check 434s > all.equal(fitTBp, fitTB) 434s [1] "Component “tcn_2.5%”: Mean relative difference: 0.003070405" 434s [2] "Component “tcn_5%”: Mean relative difference: 0.002241362" 434s [3] "Component “tcn_95%”: Mean relative difference: 0.005458479" 434s [4] "Component “tcn_97.5%”: Mean relative difference: 0.006030363" 434s [5] "Component “dh_2.5%”: Mean relative difference: 0.02683423" 434s [6] "Component “dh_5%”: Mean relative difference: 0.02409533" 434s [7] "Component “dh_95%”: Mean relative difference: 0.0150081" 434s [8] "Component “dh_97.5%”: Mean relative difference: 0.01826461" 434s [9] "Component “c1_2.5%”: Mean relative difference: 0.02397349" 434s [10] "Component “c1_5%”: Mean relative difference: 0.01800948" 434s [11] "Component “c1_95%”: Mean relative difference: 0.0303456" 434s [12] "Component “c1_97.5%”: Mean relative difference: 0.03420614" 434s [13] "Component “c2_2.5%”: Mean relative difference: 0.008723378" 434s [14] "Component “c2_5%”: Mean relative difference: 0.006834962" 434s [15] "Component “c2_95%”: Mean relative difference: 0.00741949" 434s [16] "Component “c2_97.5%”: Mean relative difference: 0.008743911" 434s attr(,"what") 434s [1] "getSegments()" 434s > 434s > 434s > # Bootstrap from scratch 434s > setsT <- getBootstrapLocusSets(fitT, B=B, seed=seed) 434s > lociT <- setsT$locusSet[[1L]]$bootstrap$loci 434s > idxs <- lociT$tcn 434s > tcnT <- array(dataT$CT[idxs], dim=dim(idxs)) 434s > tcnT <- apply(tcnT, MARGIN=2L, FUN=mean, na.rm=TRUE) 434s > idxs <- lociT$dh 434s > dhT <- array(dataT$rho[idxs], dim=dim(idxs)) 434s > dhT <- apply(dhT, MARGIN=2L, FUN=median, na.rm=TRUE) 434s > c1T <- (1-dhT) * tcnT / 2 434s > c2T <- tcnT - c1T 434s > bootT2 <- array(c(tcnT, dhT, c1T, c2T), dim=c(1L, 4L)) 434s > colnames(bootT2) <- colnames(bootT1) 434s > print(bootT2) 434s tcn dh c1 c2 434s [1,] 1.383213 0.5466788 0.3135198 1.069693 434s > 434s > # This comparison is only valid if B == 1L 434s > if (B == 1L) { 434s + # Sanity check 434s + stopifnot(all.equal(bootT2, bootT1)) 434s + } 434s > 434s Start: findLargeGaps.R 434s 434s R version 4.5.2 (2025-10-31) -- "[Not] Part in a Rumble" 434s Copyright (C) 2025 The R Foundation for Statistical Computing 434s Platform: x86_64-pc-linux-gnu 434s 434s R is free software and comes with ABSOLUTELY NO WARRANTY. 434s You are welcome to redistribute it under certain conditions. 434s Type 'license()' or 'licence()' for distribution details. 434s 434s R is a collaborative project with many contributors. 434s Type 'contributors()' for more information and 434s 'citation()' on how to cite R or R packages in publications. 434s 434s Type 'demo()' for some demos, 'help()' for on-line help, or 434s 'help.start()' for an HTML browser interface to help. 434s Type 'q()' to quit R. 434s 434s > library("PSCBS") 434s PSCBS v0.68.0 (2025-04-18 19:40:02 UTC) successfully loaded. See ?PSCBS for help. 434s > 434s > # Simulating copy-number data 434s > set.seed(0xBEEF) 434s > 434s > # Simulate CN data 434s > J <- 1000 434s > mu <- double(J) 434s > mu[200:300] <- mu[200:300] + 1 434s > mu[350:400] <- NA # centromere 434s > mu[650:800] <- mu[650:800] - 1 434s > eps <- rnorm(J, sd=1/2) 434s > y <- mu + eps 434s > x <- seq(from=1, to=100e6, length.out=J) 434s > 434s > data <- data.frame(chromosome=0L, x=x) 434s > 434s > gaps <- findLargeGaps(x=x, minLength=1e6) 434s > print(gaps) 434s [1] start end length 434s <0 rows> (or 0-length row.names) 434s > stopifnot(is.data.frame(gaps)) 434s > stopifnot(nrow(gaps) == 0L) 434s > segs <- gapsToSegments(gaps) 434s > print(segs) 434s chromosome start end 434s 1 0 -Inf Inf 434s > stopifnot(is.data.frame(segs)) 434s > stopifnot(nrow(segs) == 1L) 434s > 434s > 434s > gaps <- findLargeGaps(data, minLength=1e6) 434s > print(gaps) 434s [1] chromosome start end 434s <0 rows> (or 0-length row.names) 434s > stopifnot(is.data.frame(gaps)) 434s > stopifnot(nrow(gaps) == 0L) 434s > segs <- gapsToSegments(gaps) 434s > print(segs) 434s chromosome start end 434s 1 0 -Inf Inf 434s > stopifnot(is.data.frame(segs)) 434s > stopifnot(nrow(segs) == 1L) 434s > 434s > 434s > ## Add missing values 434s > data2 <- data 434s > data$x[30e6 < x & x < 50e6] <- NA 434s > gaps <- findLargeGaps(data, minLength=1e6) 434s > print(gaps) 434s chromosome start end length 434s 1 0 29929932 50050050 20120118 434s > stopifnot(is.data.frame(gaps)) 434s > stopifnot(nrow(gaps) == 1L) 434s > segs <- gapsToSegments(gaps) 434s > print(segs) 434s chromosome start end length 434s 1 0Error in findLargeGaps.default(chromosome = rep(1, 3), x = as.numeric(1:3), : 434s Cannot identify large gaps. Argument 'resolution' (=1) is not strictly smaller than 'minLength' (=1). 434s -Inf 29929931 Inf 434s 2 0 29929932 50050050 20120118 434s 3 0 50050051 Inf Inf 434s > stopifnot(is.data.frame(segs)) 434s > stopifnot(nrow(segs) == 3L) 434s > 434s > 434s > 434s > # BUG FIX: Issue #6 434s > gaps <- findLargeGaps(chromosome=rep(1,10), x=1:10, minLength=2) 434s > print(gaps) 434s [1] chromosome start end 434s <0 rows> (or 0-length row.names) 434s > stopifnot(is.data.frame(gaps)) 434s > stopifnot(nrow(gaps) == 0L) 434s > # BUG FIX: Issue #9 434s > segs <- gapsToSegments(gaps) 434s > print(segs) 434s chromosome start end 434s 1 0 -Inf Inf 434s > stopifnot(is.data.frame(segs)) 434s > stopifnot(nrow(segs) == 1L) 434s > 434s > 434s > # BUG FIX: PSCBS GitHub Issue #8 434s > gaps <- try({ 434s + findLargeGaps(chromosome=rep(1,3), x=as.numeric(1:3), minLength=1) 434s + }) 434s > stopifnot(inherits(gaps, "try-error")) 434s > 434s Start: randomSeed.R 434s 434s R version 4.5.2 (2025-10-31) -- "[Not] Part in a Rumble" 434s Copyright (C) 2025 The R Foundation for Statistical Computing 434s Platform: x86_64-pc-linux-gnu 434s 434s R is free software and comes with ABSOLUTELY NO WARRANTY. 434s You are welcome to redistribute it under certain conditions. 434s Type 'license()' or 'licence()' for distribution details. 434s 434s R is a collaborative project with many contributors. 434s Type 'contributors()' for more information and 434s 'citation()' on how to cite R or R packages in publications. 434s 434s Type 'demo()' for some demos, 'help()' for on-line help, or 434s 'help.start()' for an HTML browser interface to help. 434s Type 'q()' to quit R. 434s 434s > library("PSCBS") 434s PSCBS v0.68.0 (2025-04-18 19:40:02 UTC) successfully loaded. See ?PSCBS for help. 434s *** randomSeed() - setup ... 434s > 434s > message("*** randomSeed() - setup ...") 434s > ovars <- ls(envir=globalenv()) 434s > genv <- globalenv() 434s > RNGkind("Mersenne-Twister") 434s > if (exists(".Random.seed", envir=genv, inherits=FALSE)) 434s + rm(list=".Random.seed", envir=genv, inherits=FALSE) 434s > seed0 <- genv$.Random.seed 434s > stopifnot(is.null(seed0)) 434s > okind0 <- RNGkind()[1L] 434s > 434s > sample1 <- function() { sample(0:9, size=1L) } 434s *** randomSeed() - setup ... done 434s > message("*** randomSeed() - setup ... done") 434s > 434s > 434s > message("*** randomSeed('get') ...") 434s *** randomSeed('get') ... 434s Random number: 6 434s *** randomSeed('get') ... done 434s > ## Get random seed 434s > seed <- randomSeed("get") 434s > stopifnot(identical(seed, seed0)) 434s > 434s > ## Repeat after new sample 434s > y1 <- sample1() 434s > message(sprintf("Random number: %d", y1)) 434s > seed1 <- randomSeed("get") 434s > stopifnot(!identical(seed1, seed0)) 434s > message("*** randomSeed('get') ... done") 434s > 434s > 434s > message("*** randomSeed('set', 42L) ...") 434s *** randomSeed('set', 42L) ... 434s > randomSeed("set", seed=42L) 434s > seed2 <- randomSeed("get") 434s > stopifnot(!identical(seed2, seed1)) 434s > 434s > y2 <- sample1() 434s > message(sprintf("Random number: %d (with random seed = 42L)", y2)) 434s > 434s > ## Reset to previous state 434s > randomSeed("reset") 434s > seed3 <- randomSeed("get") 434s > stopifnot(identical(seed3, seed1)) 434s > stopifnot(identical(RNGkind()[1L], okind0), 434s + identical(randomSeed("get"), seed1)) 434s > message("*** randomSeed('set', 42L) ... done") 434s Random number: 0 (with random seed = 42L) 434s > 434s > 434s > message("*** randomSeed('set', NULL) ...") 434s > randomSeed("set", seed=NULL) 434s *** randomSeed('set', 42L) ... done 434s *** randomSeed('set', NULL) ... 434s > seed4 <- randomSeed("get") 434s > stopifnot(is.null(seed4)) 434s > 434s > y3 <- sample1() 434s > message(sprintf("Random number: %d", y3)) 434s > 434s > message("*** randomSeed('set', NULL) ... done") 434s > 434s > 434s > message("*** randomSeed('set', 42L) again ...") 434s > seed5 <- randomSeed("get") 434s > randomSeed("set", seed=42L) 434s > y4 <- sample1() 434s > message(sprintf("Random number: %d (with random seed = 42L)", y4)) 434s > stopifnot(identical(y4, y2)) 434s > 434s > randomSeed("reset") 434s Random number: 0 434s *** randomSeed('set', NULL) ... done 434s *** randomSeed('set', 42L) again ... 434s Random number: 0 (with random seed = 42L) 434s > stopifnot(identical(RNGkind()[1L], okind0), 434s + identical(randomSeed("get"), seed5)) 434s > message("*** randomSeed('set', 42L) again ... done") 434s > 434s > 434s > 434s > ## L'Ecuyer-CMRG: Random number generation for parallel processing 434s > message("*** randomSeed(): L'Ecuyer-CMRG stream ...") 434s > 434s > okind <- RNGkind()[1L] 434s > stopifnot(identical(okind, okind0)) 434s > 434s > randomSeed("set", seed=NULL) 434s > oseed <- randomSeed("get") 434s > stopifnot(is.null(oseed)) 434s > 434s > randomSeed("set", seed=42L, kind="L'Ecuyer-CMRG") 434s > oseed2 <- randomSeed("reset") 434s > str(oseed2) 434s NULL 434s > stopifnot(identical(oseed2, oseed)) 434s > stopifnot(identical(RNGkind()[1L], okind), 434s + identical(randomSeed("get"), oseed)) 434s > 434s > randomSeed("set", seed=42L, kind="L'Ecuyer-CMRG") 434s > seed0 <- randomSeed("get") 434s > seeds0 <- lapply(1:10, FUN=function(i) randomSeed("advance")) 434s *** randomSeed('set', 42L) again ... done 434s *** randomSeed(): L'Ecuyer-CMRG stream ... 434s > oseed2 <- randomSeed("reset") 434s > stopifnot(identical(oseed2, oseed)) 434s > stopifnot(identical(RNGkind()[1L], okind), 434s + identical(randomSeed("get"), oseed)) 434s > 434s > 434s > ## Assert reproducible .Random.seed stream 434s > randomSeed("set", seed=42L, kind="L'Ecuyer-CMRG") 434s > seed1 <- randomSeed("get") 434s > seeds1 <- lapply(1:10, FUN=function(i) randomSeed("advance")) 434s > stopifnot(identical(seed1, seed0)) 434s > stopifnot(identical(seeds1, seeds0)) 434s > 434s > randomSeed("reset") 434s > stopifnot(identical(RNGkind()[1L], okind), 434s + identical(randomSeed("get"), oseed)) 434s > 434s > randomSeed("set", seed=42L, kind="L'Ecuyer-CMRG") 434s > seeds2 <- randomSeed("advance", n=10L) 434s > stopifnot(identical(seeds2, seeds0)) 434s > 434s > randomSeed("reset") 434s > stopifnot(identical(RNGkind()[1L], okind), 434s + identical(randomSeed("get"), oseed)) 434s > 434s > randomSeed("set", seed=seeds2[[1]], kind="L'Ecuyer-CMRG") 434s > randomSeed("reset") 434s > stopifnot(identical(RNGkind()[1L], okind), 434s + identical(randomSeed("get"), oseed)) 434s > 434s > randomSeed("set", seed=42L, kind="L'Ecuyer-CMRG") 434s > y0 <- sapply(1:10, FUN=function(ii) { 434s + randomSeed("advance") 434s + sample1() 434s + }) 434s > print(y0) 434s [1] 6 9 6 9 9 9 0 7 6 5 434s > randomSeed("reset") 434s > 434s > randomSeed("set", seed=42L, kind="L'Ecuyer-CMRG") 434s > y1 <- sapply(1:10, FUN=function(ii) { 434s + randomSeed("advance") 434s + sample1() 434s + }) 434s > print(y1) 434s [1] 6 9 6 9 9 9 0 7 6 5 434s > stopifnot(identical(y1, y0)) 434s > randomSeed("reset") 434s > 434s > stopifnot(identical(RNGkind()[1L], okind)) 434s > 434s > message("*** randomSeed(): L'Ecuyer-CMRG stream ... done") 434s > 434s > 434s > ## Cleanup 434s > message("*** randomSeed() - cleanup ...") 434s > genv <- globalenv() 434s > RNGkind("Mersenne-Twister") 434s > if (exists(".Random.seed", envir=genv, inherits=FALSE)) 434s + rm(list=".Random.seed", envir=genv, inherits=FALSE) 434s > rm(list=ovars, envir=globalenv()) 434s > message("*** randomSeed() - cleanup ... done") 434s > 434s Start: segmentByCBS,bug67.R 434s *** randomSeed(): L'Ecuyer-CMRG stream ... done 434s *** randomSeed() - cleanup ... 434s *** randomSeed() - cleanup ... done 434s 434s R version 4.5.2 (2025-10-31) -- "[Not] Part in a Rumble" 434s Copyright (C) 2025 The R Foundation for Statistical Computing 434s Platform: x86_64-pc-linux-gnu 434s 434s R is free software and comes with ABSOLUTELY NO WARRANTY. 434s You are welcome to redistribute it under certain conditions. 434s Type 'license()' or 'licence()' for distribution details. 434s 434s R is a collaborative project with many contributors. 434s Type 'contributors()' for more information and 434s 'citation()' on how to cite R or R packages in publications. 434s 434s Type 'demo()' for some demos, 'help()' for on-line help, or 434s 'help.start()' for an HTML browser interface to help. 434s Type 'q()' to quit R. 434s 434s > set.seed(0xBEEF) 434s > 434s > # Number of loci 434s > J <- 1000 434s > 434s > mu <- double(J) 434s > mu[200:300] <- mu[200:300] + 1 434s > mu[350:400] <- NA_real_ # centromere 434s > mu[650:800] <- mu[650:800] - 1 434s > eps <- rnorm(J, sd=1/2) 434s > y <- mu + eps 434s > x <- sort(runif(length(y), max=length(y))) * 1e5 434s > 434s > knownSegments <- data.frame( 434s + chromosome=c( 0, 0), 434s + start =x[c( 1, 401)], 434s + end =x[c(349, J)] 434s + ) 434s > 434s > fit2 <- PSCBS::segmentByCBS(y, x=x, knownSegments=knownSegments) 435s > 435s Start: segmentByCBS,calls.R 435s 435s R version 4.5.2 (2025-10-31) -- "[Not] Part in a Rumble" 435s Copyright (C) 2025 The R Foundation for Statistical Computing 435s Platform: x86_64-pc-linux-gnu 435s 435s R is free software and comes with ABSOLUTELY NO WARRANTY. 435s You are welcome to redistribute it under certain conditions. 435s Type 'license()' or 'licence()' for distribution details. 435s 435s R is a collaborative project with many contributors. 435s Type 'contributors()' for more information and 435s 'citation()' on how to cite R or R packages in publications. 435s 435s Type 'demo()' for some demos, 'help()' for on-line help, or 435s 'help.start()' for an HTML browser interface to help. 435s Type 'q()' to quit R. 435s 435s > # This test script calls a report generator which requires 435s > # the 'ggplot2' package, which in turn will require packages 435s > # 'colorspace', 'dichromat', 'munsell', 'reshape2' and 'scales'. 435s > 435s > # Only run this test in full testing mode 435s > if (Sys.getenv("_R_CHECK_FULL_") != "") { 435s + library("PSCBS") 435s + stext <- R.utils::stext 435s + 435s + # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 435s + # Load SNP microarray data 435s + # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 435s + data <- PSCBS::exampleData("paired.chr01") 435s + str(data) 435s + 435s + data <- data.frame(chromosome=data$chromosome, x=data$x, y=data$CT) 435s + 435s + 435s + # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 435s + # CBS segmentation 435s + # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 435s + # Drop single-locus outliers 435s + dataS <- dropSegmentationOutliers(data) 435s + 435s + # Speed up example by segmenting fewer loci 435s + dataS <- dataS[seq(from=1, to=nrow(data), by=5),] 435s + 435s + str(dataS) 435s + 435s + gaps <- findLargeGaps(dataS, minLength=2e6) 435s + knownSegments <- gapsToSegments(gaps) 435s + 435s + # CBS segmentation 435s + fit <- segmentByCBS(dataS, knownSegments=knownSegments, 435s + seed=0xBEEF, verbose=-10) 435s + signalType(fit) <- "ratio" 435s + plotTracks(fit) 435s + 435s + 435s + # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 435s + # Call using the UCSF MAD caller (not recommended) 435s + # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 435s + fitC <- callGainsAndLosses(fit) 435s + plotTracks(fitC) 435s + pars <- fitC$params$callGainsAndLosses 435s + stext(side=3, pos=1/2, line=-1, substitute(sigma==x, list(x=sprintf("%.2f", pars$sigmaMAD)))) 435s + mu <- pars$muR 435s + tau <- unlist(pars[c("tauLoss", "tauGain")], use.names=FALSE) 435s + abline(h=mu, lty=2, lwd=2) 435s + abline(h=tau, lwd=2) 435s + mtext(side=4, at=tau[1], expression(Delta[LOSS]), adj=-0.2, cex=0.7, las=2, xpd=TRUE) 435s + mtext(side=4, at=tau[2], expression(Delta[GAIN]), adj=-0.2, cex=0.7, las=2, xpd=TRUE) 435s + title(main="CN caller: \"ucsf-mad\"") 435s + 435s + 435s + # Caller to be implemented 435s + deltaCN <- estimateDeltaCN(fit) 435s + tau <- mu + 1/2*c(-1,+1)*deltaCN 435s + abline(h=tau, lty=2, lwd=1, col="red") 435s + 435s + 435s + 435s + } # if (Sys.getenv("_R_CHECK_FULL_")) 435s > 435s Start: segmentByCBS,futures.R 435s 435s R version 4.5.2 (2025-10-31) -- "[Not] Part in a Rumble" 435s Copyright (C) 2025 The R Foundation for Statistical Computing 435s Platform: x86_64-pc-linux-gnu 435s 435s R is free software and comes with ABSOLUTELY NO WARRANTY. 435s You are welcome to redistribute it under certain conditions. 435s Type 'license()' or 'licence()' for distribution details. 435s 435s R is a collaborative project with many contributors. 435s Type 'contributors()' for more information and 435s 'citation()' on how to cite R or R packages in publications. 435s 435s Type 'demo()' for some demos, 'help()' for on-line help, or 435s 'help.start()' for an HTML browser interface to help. 435s Type 'q()' to quit R. 435s 435s > library("PSCBS") 435s PSCBS v0.68.0 (2025-04-18 19:40:02 UTC) successfully loaded. See ?PSCBS for help. 435s > 435s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 435s > # Simulating copy-number data 435s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 435s > set.seed(0xBEEF) 435s > 435s > # Number of loci 435s > J <- 1000 435s > 435s > mu <- double(J) 435s > mu[200:300] <- mu[200:300] + 1 435s > mu[350:400] <- NA # centromere 435s > mu[650:800] <- mu[650:800] - 1 435s > eps <- rnorm(J, sd=1/2) 435s > y <- mu + eps 435s > x <- sort(runif(length(y), max=length(y))) * 1e5 435s > w <- runif(J) 435s > w[650:800] <- 0.001 435s > 435s > ## Create multiple chromosomes 435s > data <- knownSegments <- list() 435s > for (cc in 1:3) { 435s + data[[cc]] <- data.frame(chromosome=cc, y=y, x=x) 435s + knownSegments[[cc]] <- data.frame( 435s + chromosome=c( cc, cc, cc), 435s + start =x[c( 1, 350, 401)], 435s + end =x[c(349, 400, J)] 435s + ) 435s + } 435s > data <- Reduce(rbind, data) 435s > str(data) 435s 'data.frame': 3000 obs. of 3 variables: 435s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 435s $ y : num 0.295 0.115 -0.194 -0.392 -0.518 ... 435s $ x : num 55168 593204 605649 630624 746896 ... 435s > knownSegments <- Reduce(rbind, knownSegments) 435s > str(knownSegments) 435s 'data.frame': 9 obs. of 3 variables: 435s $ chromosome: int 1 1 1 2 2 2 3 3 3 435s $ start : num 55168 34194740 41080533 55168 34194740 ... 435s $ end : num 34142178 41044125 99910827 34142178 41044125 ... 435s > 435s > message("*** segmentByCBS() via futures ...") 435s > 435s > 435s > *** segmentByCBS() via futures ... 435s *** segmentByCBS() via futures with 'future' attached ... 435s message("*** segmentByCBS() via futures with 'future' attached ...") 435s > library("future") 435s > oplan <- plan() 435s > 435s > strategies <- c("sequential", "multisession") 435s > 435s > ## Test 'future.batchtools' futures? 435s > pkg <- "future.batchtools" 435s > if (require(pkg, character.only=TRUE)) { 435s + strategies <- c(strategies, "batchtools_local") 435s + } 435s > 435s > message("Future strategies to test: ", paste(sQuote(strategies), collapse=", ")) 435s > 435s > fits <- list() 435s > for (strategy in strategies) { 435s + message(sprintf("- segmentByCBS() using '%s' futures ...", strategy)) 435s + plan(strategy) 435s + fit <- segmentByCBS(data, seed=0xBEEF, verbose=TRUE) 435s + fits[[strategy]] <- fit 435s + stopifnot(all.equal(fit, fits[[1]])) 435s + } 435s Loading required package: future.batchtools 435s Warning message: 435s In library(package, lib.loc = lib.loc, character.only = TRUE, logical.return = TRUE, : 435s there is no package called ‘future.batchtools’ 435s Future strategies to test: ‘sequential’, ‘multisession’ 435s - segmentByCBS() using 'sequential' futures ... 435s Segmenting by CBS... 435s Segmenting multiple chromosomes... 435s Number of chromosomes: 3 435s Random seed temporarily set (seed=c(48879), kind="L'Ecuyer-CMRG") 435s Produced 3 seeds from this stream for future usage 435s Chromosome #1 ('Chr01') of 3... 435s Segmenting by CBS... 435s Chromosome: 1 435s Random seed temporarily set (seed=c(10407, 1066287653, -51199871, 161854402, -1995183193, 1503453565, -747102133), kind="L'Ecuyer-CMRG") 435s Segmenting by CBS...done 435s Chromosome #1 ('Chr01') of 3...done 435s Chromosome #2 ('Chr02') of 3... 435s Segmenting by CBS... 435s Chromosome: 2 435s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 435s Segmenting by CBS...done 435s Chromosome #2 ('Chr02') of 3...done 435s Chromosome #3 ('Chr03') of 3... 435s Segmenting by CBS... 435s Chromosome: 3 435s Random seed temporarily set (seed=c(10407, -821273412, -52578226, 1415511586, 721384351, -665928286, 1316562960), kind="L'Ecuyer-CMRG") 435s Segmenting by CBS...done 435s Chromosome #3 ('Chr03') of 3...done 435s Segmenting multiple chromosomes...done 435s Segmenting by CBS...done 435s list() 435s - segmentByCBS() using 'multisession' futures ... 436s Segmenting by CBS... 436s Segmenting multiple chromosomes... 436s Number of chromosomes: 3 436s Random seed temporarily set (seed=c(48879), kind="L'Ecuyer-CMRG") 436s Produced 3 seeds from this stream for future usage 436s Chromosome #1 ('Chr01') of 3... 436s Chromosome #1 ('Chr01') of 3...done 436s Chromosome #2 ('Chr02') of 3... 436s Random seed temporarily set (seed=c(10407, 1066287653, -51199871, 161854402, -1995183193, 1503453565, -747102133), kind="L'Ecuyer-CMRG") 436s Segmenting by CBS...done 436s Chromosome #2 ('Chr02') of 3...done 436s Chromosome #3 ('Chr03') of 3... 436s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 436s Segmenting by CBS...done 436s Chromosome #3 ('Chr03') of 3...done 437s Segmenting by CBS... 437s Chromosome: 3 437s Random seed temporarily set (seed=c(10407, -821273412, -52578226, 1415511586, 721384351, -665928286, 1316562960), kind="L'Ecuyer-CMRG") 437s Segmenting by CBS...done 437s Segmenting multiple chromosomes...done 437s Segmenting by CBS...done 437s list() 437s *** segmentByCBS() via futures with known segments ... 437s > 437s > 437s > message("*** segmentByCBS() via futures with known segments ...") 437s > fits <- list() 437s > dataT <- subset(data, chromosome == 1) 437s > for (strategy in strategies) { 437s + message(sprintf("- segmentByCBS() w/ known segments using '%s' futures ...", strategy)) 437s + plan(strategy) 437s + fit <- segmentByCBS(dataT, knownSegments=knownSegments, seed=0xBEEF, verbose=TRUE) 437s + fits[[strategy]] <- fit 437s + stopifnot(all.equal(fit, fits[[1]])) 437s + } 437s - segmentByCBS() w/ known segments using 'sequential' futures ... 437s Segmenting by CBS... 437s Chromosome: 1 437s Random seed temporarily set (seed=c(48879), kind="L'Ecuyer-CMRG") 437s Produced 3 seeds from this stream for future usage 437s Segmenting by CBS...done 437s list() 437s - segmentByCBS() w/ known segments using 'multisession' futures ... 437s Segmenting by CBS... 437s Chromosome: 1 437s Random seed temporarily set (seed=c(48879), kind="L'Ecuyer-CMRG") 437s Produced 3 seeds from this stream for future usage 438s Segmenting by CBS...done 438s list() 438s > 438s > message("*** segmentByCBS() via futures ... DONE") 438s > 438s > 438s > ## Cleanup 438s > plan(oplan) 438s *** segmentByCBS() via futures ... DONE 438s > rm(list=c("fits", "dataT", "data", "fit")) 438s > 438s > 438s Start: segmentByCBS,median.R 438s 438s R version 4.5.2 (2025-10-31) -- "[Not] Part in a Rumble" 438s Copyright (C) 2025 The R Foundation for Statistical Computing 438s Platform: x86_64-pc-linux-gnu 438s 438s R is free software and comes with ABSOLUTELY NO WARRANTY. 438s You are welcome to redistribute it under certain conditions. 438s Type 'license()' or 'licence()' for distribution details. 438s 438s R is a collaborative project with many contributors. 438s Type 'contributors()' for more information and 438s 'citation()' on how to cite R or R packages in publications. 438s 438s Type 'demo()' for some demos, 'help()' for on-line help, or 438s 'help.start()' for an HTML browser interface to help. 438s Type 'q()' to quit R. 438s 438s > library("PSCBS") 438s PSCBS v0.68.0 (2025-04-18 19:40:02 UTC) successfully loaded. See ?PSCBS for help. 438s > 438s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 438s > # Simulating copy-number data 438s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 438s > set.seed(0xBEEF) 438s > 438s > # Number of loci 438s > J <- 1000 438s > 438s > x <- sort(runif(J, max=J)) * 1e5 438s > 438s > mu <- double(J) 438s > mu[200:300] <- mu[200:300] + 1 438s > mu[350:400] <- NA # centromere 438s > mu[650:800] <- mu[650:800] - 1 438s > eps <- rnorm(J, sd=1/2) 438s > y <- mu + eps 438s > 438s > outliers <- seq(from=1L, to=J, length.out=0.2*J) 438s > y[outliers] <- y[outliers] + 1.5 438s > 438s > w <- rep(1.0, times=J) 438s > w[outliers] <- 0.01 438s > 438s > data <- data.frame(chromosome=1L, x=x, y=y) 438s > dataW <- cbind(data, w=w) 438s > 438s > 438s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 438s > # Single-chromosome segmentation 438s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 438s > par(mar=c(2,3,0.2,1)+0.1) 438s > # Segment without weights 438s > fit <- segmentByCBS(data) 438s > sampleName(fit) <- "CBS_Example" 438s > print(fit) 438s sampleName chromosome start end nbrOfLoci mean 438s 1 CBS_Example 1 136857.7 19138391 199 0.2712 438s 2 CBS_Example 1 19138391.4 28682180 101 1.2168 438s 3 CBS_Example 1 28682180.1 64690253 298 0.3027 438s 4 CBS_Example 1 64690253.3 80738828 151 -0.7101 438s 5 CBS_Example 1 80738828.3 99932904 200 0.3655 438s > plotTracks(fit) 438s Warning message: 438s In plotTracks.CBS(fit) : 438s Setting default 'Clim' assuming the signal type is ‘ratio’ because signalType(fit) is unknown (‘NA’). Use signalType(fit) <- ‘ratio’ to avoid this warning. 438s > ## Highlight outliers (they pull up the mean levels) 438s > points(x[outliers]/1e6, y[outliers], col="purple") 438s > 438s > # Segment without weights but with median 438s > fitM <- segmentByCBS(data, avg="median") 438s > sampleName(fitM) <- "CBS_Example (median)" 438s > print(fitM) 438s sampleName chromosome start end nbrOfLoci mean 438s 1 CBS_Example (median) 1 136857.7 19138391 199 0.1203255 438s 2 CBS_Example (median) 1 19138391.4 28682180 101 0.9949202 438s 3 CBS_Example (median) 1 28682180.1 64690253 298 0.1471793 438s 4 CBS_Example (median) 1 64690253.3 80738828 151 -0.8770443 438s 5 CBS_Example (median) 1 80738828.3 99932904 200 0.2211061 438s > drawLevels(fitM, col="magenta", lty=3) 438s NULL 438s > 438s > # Segment with weights 438s > fitW <- segmentByCBS(dataW, avg="median") 438s > sampleName(fitW) <- "CBS_Example (weighted)" 438s > print(fitW) 438s sampleName chromosome start end nbrOfLoci mean 438s 1 CBS_Example (weighted) 1 136857.7 19138391 199 -0.02220950 438s 2 CBS_Example (weighted) 1 19138391.4 28682180 101 0.92421628 438s 3 CBS_Example (weighted) 1 28682180.1 64690253 298 -0.02364830 438s 4 CBS_Example (weighted) 1 64690253.3 80738828 151 -1.04750872 438s 5 CBS_Example (weighted) 1 80738828.3 99932904 200 0.08961195 438s > drawLevels(fitW, col="red") 438s NULL 438s > 438s > # Segment with weights and median 438s > fitWM <- segmentByCBS(dataW, avg="median") 438s > sampleName(fitWM) <- "CBS_Example (weighted median)" 438s > print(fitWM) 438s sampleName chromosome start end nbrOfLoci 438s 1 CBS_Example (weighted median) 1 136857.7 19138391 199 438s 2 CBS_Example (weighted median) 1 19138391.4 28682180 101 438s 3 CBS_Example (weighted median) 1 28682180.1 64690253 298 438s 4 CBS_Example (weighted median) 1 64690253.3 80738828 151 438s 5 CBS_Example (weighted median) 1 80738828.3 99932904 200 438s mean 438s 1 -0.02220950 438s 2 0.92421628 438s 3 -0.02364830 438s 4 -1.04750872 438s 5 0.08961195 438s > drawLevels(fitWM, col="orange", lty=3) 438s NULL 438s > 438s > legend("topright", bg="white", legend=c("outliers", "non-weighted CBS (mean)", "non-weighted CBS (median)", "weighted CBS (mean)", "weighted CBS (median)"), col=c("purple", "purple", "magenta", "red", "orange"), lwd=c(NA,3,3,3,3), lty=c(NA,1,3,1,3), pch=c(1,NA,NA,NA,NA)) 438s > 438s > ## Assert that weighted segment means are less biased 438s > dmean <- getSegments(fit)$mean - getSegments(fitW)$mean 438s > cat("Segment mean differences:\n") 438s Segment mean differences: 438s > print(dmean) 438s [1] 0.2934095 0.2925837 0.3263483 0.3374087 0.2758881 438s > stopifnot(all(dmean > 0, na.rm=TRUE)) 438s > 438s > dmean <- getSegments(fitM)$mean - getSegments(fitWM)$mean 438s > cat("Segment median differences:\n") 438s Segment median differences: 438s > print(dmean) 438s [1] 0.14253502 0.07070392 0.17082758 0.17046439 0.13149418 438s > stopifnot(all(dmean > 0, na.rm=TRUE)) 438s > 438s > 438s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 438s > # Multi-chromosome segmentation 438s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 438s > data2 <- data 438s > data2$chromosome <- 2L 438s > data <- rbind(data, data2) 438s > dataW <- cbind(data, w=w) 438s > 438s > par(mar=c(2,3,0.2,1)+0.1) 438s > # Segment without weights 438s > fit <- segmentByCBS(data) 438s > sampleName(fit) <- "CBS_Example" 438s > print(fit) 438s sampleName chromosome start end nbrOfLoci mean 438s 1 CBS_Example 1 136857.7 19138391 199 0.2712 438s 2 CBS_Example 1 19138391.4 28682180 101 1.2168 438s 3 CBS_Example 1 28682180.1 64690253 298 0.3027 438s 4 CBS_Example 1 64690253.3 80738828 151 -0.7101 438s 5 CBS_Example 1 80738828.3 99932904 200 0.3655 438s 6 NA NA NA NA NA 438s 7 CBS_Example 2 136857.7 19138391 199 0.2712 438s 8 CBS_Example 2 19138391.4 28682180 101 1.2168 438s 9 CBS_Example 2 28682180.1 64690253 298 0.3027 438s 10 CBS_Example 2 64690253.3 80738828 151 -0.7101 438s 11 CBS_Example 2 80738828.3 99932904 200 0.3655 438s > plotTracks(fit, Clim=c(-3,3)) 438s > 438s > # Segment without weights but with median 438s > fitM <- segmentByCBS(data, avg="median") 439s > sampleName(fitM) <- "CBS_Example (median)" 439s > print(fitM) 439s sampleName chromosome start end nbrOfLoci mean 439s 1 CBS_Example (median) 1 136857.7 19138391 199 0.1203255 439s 2 CBS_Example (median) 1 19138391.4 28682180 101 0.9949202 439s 3 CBS_Example (median) 1 28682180.1 64690253 298 0.1471793 439s 4 CBS_Example (median) 1 64690253.3 80738828 151 -0.8770443 439s 5 CBS_Example (median) 1 80738828.3 99932904 200 0.2211061 439s 6 NA NA NA NA NA 439s 7 CBS_Example (median) 2 136857.7 19138391 199 0.1203255 439s 8 CBS_Example (median) 2 19138391.4 28682180 101 0.9949202 439s 9 CBS_Example (median) 2 28682180.1 64690253 298 0.1471793 439s 10 CBS_Example (median) 2 64690253.3 80738828 151 -0.8770443 439s 11 CBS_Example (median) 2 80738828.3 99932904 200 0.2211061 439s > drawLevels(fitM, col="magenta", lty=3) 439s NULL 439s > 439s > # Segment with weights 439s > fitW <- segmentByCBS(dataW, avg="median") 439s > sampleName(fitW) <- "CBS_Example (weighted)" 439s > print(fitW) 439s sampleName chromosome start end nbrOfLoci mean 439s 1 CBS_Example (weighted) 1 136857.7 19138391 199 -0.02220950 439s 2 CBS_Example (weighted) 1 19138391.4 28682180 101 0.92421628 439s 3 CBS_Example (weighted) 1 28682180.1 64690253 298 -0.02364830 439s 4 CBS_Example (weighted) 1 64690253.3 80738828 151 -1.04750872 439s 5 CBS_Example (weighted) 1 80738828.3 99932904 200 0.08961195 439s 6 NA NA NA NA NA 439s 7 CBS_Example (weighted) 2 136857.7 19138391 199 -0.02220950 439s 8 CBS_Example (weighted) 2 19138391.4 28682180 101 0.92421628 439s 9 CBS_Example (weighted) 2 28682180.1 64690253 298 -0.02364830 439s 10 CBS_Example (weighted) 2 64690253.3 80738828 151 -1.04750872 439s 11 CBS_Example (weighted) 2 80738828.3 99932904 200 0.08961195 439s > drawLevels(fitW, col="red") 439s NULL 439s > 439s > # Segment with weights and median 439s > fitWM <- segmentByCBS(dataW, avg="median") 439s > sampleName(fitWM) <- "CBS_Example (weighted median)" 439s > print(fitWM) 439s sampleName chromosome start end nbrOfLoci 439s 1 CBS_Example (weighted median) 1 136857.7 19138391 199 439s 2 CBS_Example (weighted median) 1 19138391.4 28682180 101 439s 3 CBS_Example (weighted median) 1 28682180.1 64690253 298 439s 4 CBS_Example (weighted median) 1 64690253.3 80738828 151 439s 5 CBS_Example (weighted median) 1 80738828.3 99932904 200 439s 6 NA NA NA NA 439s 7 CBS_Example (weighted median) 2 136857.7 19138391 199 439s 8 CBS_Example (weighted median) 2 19138391.4 28682180 101 439s 9 CBS_Example (weighted median) 2 28682180.1 64690253 298 439s 10 CBS_Example (weighted median) 2 64690253.3 80738828 151 439s 11 CBS_Example (weighted median) 2 80738828.3 99932904 200 439s mean 439s 1 -0.02220950 439s 2 0.92421628 439s 3 -0.02364830 439s 4 -1.04750872 439s 5 0.08961195 439s 6 NA 439s 7 -0.02220950 439s 8 0.92421628 439s 9 -0.02364830 439s 10 -1.04750872 439s 11 0.08961195 439s > drawLevels(fitWM, col="orange", lty=3) 439s NULL 439s > 439s > legend("topright", bg="white", legend=c("outliers", "non-weighted CBS (mean)", "non-weighted CBS (median)", "weighted CBS (mean)", "weighted CBS (median)"), col=c("purple", "purple", "magenta", "red", "orange"), lwd=c(NA,3,3,3,3), lty=c(NA,1,3,1,3), pch=c(1,NA,NA,NA,NA)) 439s > 439s > ## Assert that weighted segment means are less biased 439s > dmean <- getSegments(fit)$mean - getSegments(fitW)$mean 439s > cat("Segment mean differences:\n") 439s Segment mean differences: 439s > print(dmean) 439s [1] 0.2934095 0.2925837 0.3263483 0.3374087 0.2758881 NA 0.2934095 439s [8] 0.2925837 0.3263483 0.3374087 0.2758881 439s > stopifnot(all(dmean > 0, na.rm=TRUE)) 439s > 439s > dmean <- getSegments(fitM)$mean - getSegments(fitWM)$mean 439s > cat("Segment median differences:\n") 439s Segment median differences: 439s > print(dmean) 439s [1] 0.14253502 0.07070392 0.17082758 0.17046439 0.13149418 NA 439s [7] 0.14253502 0.07070392 0.17082758 0.17046439 0.13149418 439s > stopifnot(all(dmean > 0, na.rm=TRUE)) 439s > 439s Start: segmentByCBS,prune.R 439s 439s R version 4.5.2 (2025-10-31) -- "[Not] Part in a Rumble" 439s Copyright (C) 2025 The R Foundation for Statistical Computing 439s Platform: x86_64-pc-linux-gnu 439s 439s R is free software and comes with ABSOLUTELY NO WARRANTY. 439s You are welcome to redistribute it under certain conditions. 439s Type 'license()' or 'licence()' for distribution details. 439s 439s R is a collaborative project with many contributors. 439s Type 'contributors()' for more information and 439s 'citation()' on how to cite R or R packages in publications. 439s 439s Type 'demo()' for some demos, 'help()' for on-line help, or 439s 'help.start()' for an HTML browser interface to help. 439s Type 'q()' to quit R. 439s 439s > library("PSCBS") 439s PSCBS v0.68.0 (2025-04-18 19:40:02 UTC) successfully loaded. See ?PSCBS for help. 439s > 439s > ## Compare segments 439s > assertMatchingSegments <- function(fitM, fit) { 439s + chrs <- getChromosomes(fitM) 439s + segsM <- lapply(chrs, FUN=function(chr) { 439s + getSegments(extractChromosome(fitM, chr)) 439s + }) 439s + segs <- lapply(fit[chrs], FUN=getSegments) 439s + stopifnot(all.equal(segsM, segs, check.attributes=FALSE)) 439s + } 439s > 439s > ## Simulate data 439s > set.seed(0xBEEF) 439s > J <- 1000 439s > mu <- double(J) 439s > mu[200:300] <- mu[200:300] + 1 439s > mu[350:400] <- NA 439s > mu[650:800] <- mu[650:800] - 1 439s > eps <- rnorm(J, sd=1/2) 439s > y <- mu + eps 439s > x <- sort(runif(length(y), max=length(y))) * 1e5 439s > 439s > data <- list() 439s > for (chr in 1:2) { 439s + data[[chr]] <- data.frame(chromosome=chr, x=x, y=y) 439s + } 439s > data$M <- Reduce(rbind, data) 439s > 439s > ## Segment 439s > message("*** segmentByCBS()") 439s *** segmentByCBS() 439s > fit <- lapply(data, FUN=segmentByCBS) 439s > print(fit) 439s [[1]] 439s sampleName chromosome start end nbrOfLoci mean 439s 1 1 55167.82 20774251 201 0.0164 439s 2 1 20774250.85 29320105 99 1.0474 439s 3 1 29320104.86 65874675 298 -0.0203 439s 4 1 65874675.06 81348129 151 -1.0813 439s 5 1 81348129.20 99910827 200 -0.0612 439s 439s [[2]] 439s sampleName chromosome start end nbrOfLoci mean 439s 1 2 55167.82 20774251 201 0.0164 439s 2 2 20774250.85 29320105 99 1.0474 439s 3 2 29320104.86 65874675 298 -0.0203 439s 4 2 65874675.06 81348129 151 -1.0813 439s 5 2 81348129.20 99910827 200 -0.0612 439s 439s $M 439s sampleName chromosome start end nbrOfLoci mean 439s 1 1 55167.82 20774251 201 0.0164 439s 2 1 20774250.85 29320105 99 1.0474 439s 3 1 29320104.86 65874675 298 -0.0203 439s 4 1 65874675.06 81348129 151 -1.0813 439s 5 1 81348129.20 99910827 200 -0.0612 439s 6 NA NA NA NA NA 439s 7 2 55167.82 20774251 201 0.0164 439s 8 2 20774250.85 29320105 99 1.0474 439s 9 2 29320104.86 65874675 298 -0.0203 439s 10 2 65874675.06 81348129 151 -1.0813 439s 11 2 81348129.20 99910827 200 -0.0612 439s 439s > assertMatchingSegments(fit$M, fit) 439s > 439s > ## Join segments 439s > message("*** joinSegments()") 439s *** joinSegments() 439s > fitj <- lapply(fit, FUN=joinSegments) 439s > print(fitj) 439s [[1]] 439s sampleName chromosome start end nbrOfLoci mean 439s 1 1 55167.82 20774251 201 0.0164 439s 2 1 20774250.85 29320105 99 1.0474 439s 3 1 29320104.86 65874675 298 -0.0203 439s 4 1 65874675.06 81348129 151 -1.0813 439s 5 1 81348129.20 99910827 200 -0.0612 439s 439s [[2]] 439s sampleName chromosome start end nbrOfLoci mean 439s 1 2 55167.82 20774251 201 0.0164 439s 2 2 20774250.85 29320105 99 1.0474 439s 3 2 29320104.86 65874675 298 -0.0203 439s 4 2 65874675.06 81348129 151 -1.0813 439s 5 2 81348129.20 99910827 200 -0.0612 439s 439s $M 439s sampleName chromosome start end nbrOfLoci mean 439s 1 1 55167.82 20774251 201 0.0164 439s 2 1 20774250.85 29320105 99 1.0474 439s 3 1 29320104.86 65874675 298 -0.0203 439s 4 1 65874675.06 81348129 151 -1.0813 439s 5 1 81348129.20 99910827 200 -0.0612 439s 6 NA NA NA NA NA 439s 7 2 55167.82 20774251 201 0.0164 439s 8 2 20774250.85 29320105 99 1.0474 439s 9 2 29320104.86 65874675 298 -0.0203 439s 10 2 65874675.06 81348129 151 -1.0813 439s 11 2 81348129.20 99910827 200 -0.0612 439s 439s > assertMatchingSegments(fitj$M, fitj) 439s > 439s > ## Reset segments 439s > message("*** resetSegments()") 439s > fitj <- lapply(fit, FUN=resetSegments) 439s *** resetSegments() 439s > print(fitj) 439s [[1]] 439s sampleName chromosome start end nbrOfLoci mean 439s 1 1 55167.82 20774251 201 0.0164 439s 2 1 20774250.85 29320105 99 1.0474 439s 3 1 29320104.86 65874675 298 -0.0203 439s 4 1 65874675.06 81348129 151 -1.0813 439s 5 1 81348129.20 99910827 200 -0.0612 439s 439s [[2]] 439s sampleName chromosome start end nbrOfLoci mean 439s 1 2 55167.82 20774251 201 0.0164 439s 2 2 20774250.85 29320105 99 1.0474 439s 3 2 29320104.86 65874675 298 -0.0203 439s 4 2 65874675.06 81348129 151 -1.0813 439s 5 2 81348129.20 99910827 200 -0.0612 439s 439s $M 439s sampleName chromosome start end nbrOfLoci mean 439s 1 1 55167.82 20774251 201 0.0164 439s 2 1 20774250.85 29320105 99 1.0474 439s 3 1 29320104.86 65874675 298 -0.0203 439s 4 1 65874675.06 81348129 151 -1.0813 439s 5 1 81348129.20 99910827 200 -0.0612 439s 6 NA NA NA NA NA 439s 7 2 55167.82 20774251 201 0.0164 439s 8 2 20774250.85 29320105 99 1.0474 439s 9 2 29320104.86 65874675 298 -0.0203 439s 10 2 65874675.06 81348129 151 -1.0813 439s 11 2 81348129.20 99910827 200 -0.0612 439s 439s > assertMatchingSegments(fitj$M, fitj) 439s *** pruneBySdUndo() 439s > 439s > ## Prune by SD undo 439s > message("*** pruneBySdUndo()") 439s > fitp <- lapply(fit, FUN=pruneBySdUndo) 439s > print(fitp) 439s [[1]] 439s sampleName chromosome start end nbrOfLoci mean 439s 1 1 55167.82 99910827 949 -0.07857059 439s 439s [[2]] 439s sampleName chromosome start end nbrOfLoci mean 439s 1 2 55167.82 99910827 949 -0.07857059 439s 439s $M 439s sampleName chromosome start end nbrOfLoci mean 439s 1 1 55167.82 99910827 949 -0.07857059 439s 2 NA NA NA NA NA 439s 3 2 55167.82 99910827 949 -0.07857059 439s 439s > assertMatchingSegments(fitp$M, fitp) 439s *** pruneByHClust() 439s > 439s > ## Prune by hierarchical clustering 439s > message("*** pruneByHClust()") 439s > fitp <- lapply(fit, FUN=pruneByHClust, k=1L) 439s > print(fitp) 439s [[1]] 439s sampleName chromosome start end nbrOfLoci mean 439s 1 1 55167.82 99910827 949 -0.07857059 439s 439s [[2]] 439s sampleName chromosome start end nbrOfLoci mean 439s 1 2 55167.82 99910827 949 -0.07857059 439s 439s $M 439s sampleName chromosome start end nbrOfLoci mean 439s 1 1 55167.82 99910827 949 -0.07857059 439s 6 NA NA NA NA NA 439s 7 2 55167.82 99910827 949 -0.07857059 439s 439s > assertMatchingSegments(fitp$M, fitp) 439s > 439s Start: segmentByCBS,report.R 439s 439s R version 4.5.2 (2025-10-31) -- "[Not] Part in a Rumble" 439s Copyright (C) 2025 The R Foundation for Statistical Computing 439s Platform: x86_64-pc-linux-gnu 439s 439s R is free software and comes with ABSOLUTELY NO WARRANTY. 439s You are welcome to redistribute it under certain conditions. 439s Type 'license()' or 'licence()' for distribution details. 439s 439s R is a collaborative project with many contributors. 439s Type 'contributors()' for more information and 439s 'citation()' on how to cite R or R packages in publications. 439s 439s Type 'demo()' for some demos, 'help()' for on-line help, or 439s 'help.start()' for an HTML browser interface to help. 439s Type 'q()' to quit R. 439s 439s > # This test script calls a report generator which requires 439s > # the 'ggplot2' package, which in turn will require packages 439s > # 'colorspace', 'dichromat', 'munsell', 'reshape2' and 'scales'. 439s > 439s > # Only run this test in full testing mode 439s > if (Sys.getenv("_R_CHECK_FULL_") != "") { 439s + library("PSCBS") 439s + 439s + # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 439s + # Load SNP microarray data 439s + # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 439s + data <- PSCBS::exampleData("paired.chr01") 439s + str(data) 439s + 439s + data <- data.frame(chromosome=data$chromosome, x=data$x, y=data$CT) 439s + 439s + 439s + # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 439s + # CBS segmentation 439s + # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 439s + # Drop single-locus outliers 439s + dataS <- dropSegmentationOutliers(data) 439s + 439s + # Speed up example by segmenting fewer loci 439s + dataS <- dataS[seq(from=1, to=nrow(data), by=5),] 439s + 439s + str(dataS) 439s + 439s + gaps <- findLargeGaps(dataS, minLength=2e6) 439s + knownSegments <- gapsToSegments(gaps) 439s + 439s + # CBS segmentation 439s + fit <- segmentByCBS(dataS, knownSegments=knownSegments, 439s + seed=0xBEEF, verbose=-10) 439s + signalType(fit) <- "ratio" 439s + 439s + # Fake a multi-chromosome segmentation 439s + fit1 <- fit 439s + fit2 <- renameChromosomes(fit, from=1, to=2) 439s + fit <- c(fit1, fit2) 439s + 439s + report(fit, sampleName="CBS", studyName="CBS-Ex", verbose=-10) 439s + 439s + } # if (Sys.getenv("_R_CHECK_FULL_")) 439s > 439s Start: segmentByCBS,shiftTCN.R 440s 440s R version 4.5.2 (2025-10-31) -- "[Not] Part in a Rumble" 440s Copyright (C) 2025 The R Foundation for Statistical Computing 440s Platform: x86_64-pc-linux-gnu 440s 440s R is free software and comes with ABSOLUTELY NO WARRANTY. 440s You are welcome to redistribute it under certain conditions. 440s Type 'license()' or 'licence()' for distribution details. 440s 440s R is a collaborative project with many contributors. 440s Type 'contributors()' for more information and 440s 'citation()' on how to cite R or R packages in publications. 440s 440s Type 'demo()' for some demos, 'help()' for on-line help, or 440s 'help.start()' for an HTML browser interface to help. 440s Type 'q()' to quit R. 440s 440s > library("PSCBS") 440s PSCBS v0.68.0 (2025-04-18 19:40:02 UTC) successfully loaded. See ?PSCBS for help. 440s > subplots <- R.utils::subplots 440s > 440s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 440s > # Simulating copy-number data 440s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 440s > set.seed(0xBEEF) 440s > 440s > # Number of loci 440s > J <- 1000 440s > 440s > mu <- double(J) 440s > eps <- rnorm(J, sd=1/2) 440s > y <- mu + eps 440s > x <- sort(runif(length(y), max=length(y))) 440s > 440s > idxs <- which(200 <= x & x < 300) 440s > y[idxs] <- y[idxs] + 1 440s > idxs <- which(350 <= x & x < 400) 440s > y[idxs] <- NA # centromere 440s > x[idxs] <- NA # centromere 440s > idxs <- which(650 <= x & x < 800) 440s > y[idxs] <- y[idxs] - 1 440s > x <- x*1e5 440s > 440s > keep <- is.finite(x) 440s > x <- x[keep] 440s > y <- y[keep] 440s > 440s > data <- list() 440s > for (chr in 1:2) { 440s + data[[chr]] <- data.frame(chromosome=chr, y=y, x=x) 440s + } 440s > data <- Reduce(rbind, data) 440s > 440s > 440s > subplots(7, ncol=1) 440s > par(mar=c(1.7,1,0.2,1)+0.1) 440s > 440s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 440s > # Segmentation 440s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 440s > fit <- segmentByCBS(data) 440s > print(fit) 440s sampleName chromosome start end nbrOfLoci mean 440s 1 1 55167.82 20341782 195 0.0145 440s 2 1 20341781.95 29617861 108 1.0437 440s 3 1 29617861.37 64995303 299 -0.0208 440s 4 1 64995302.97 80042680 151 -1.0700 440s 5 1 80042679.86 99910827 211 -0.0568 440s 6 NA NA NA NA NA 440s 7 2 55167.82 20341782 195 0.0145 440s 8 2 20341781.95 29617861 108 1.0437 440s 9 2 29617861.37 64995303 299 -0.0208 440s 10 2 64995302.97 80042680 151 -1.0700 440s 11 2 80042679.86 99910827 211 -0.0568 440s > 440s > Clim <- c(-3,3) + c(0,10) 440s > plotTracks(fit, Clim=Clim) 440s > 440s > 440s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 440s > # Shifting every other chromosome 440s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 440s > fitList <- list() 440s > chrs <- getChromosomes(fit) 440s > for (kk in seq_along(chrs)) { 440s + chr <- chrs[kk] 440s + fitKK <- extractChromosome(fit, chr) 440s + if (kk %% 2 == 0) { 440s + fitKK <- shiftTCN(fitKK, shift=+10) 440s + } 440s + fitList[[kk]] <- fitKK 440s + } # for (kk ...) 440s > fitT <- do.call(c, fitList) 440s > # Sanity check 440s > stopifnot(nbrOfSegments(fitT) == nbrOfSegments(fit)) 440s > 440s > plotTracks(fitT, Clim=Clim) 440s > 440s > 440s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 440s > # Shifting every other known segment 440s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 440s > gaps <- findLargeGaps(data, minLength=40e5) 440s > knownSegments <- gapsToSegments(gaps, dropGaps=TRUE) 440s > fit <- segmentByCBS(data, knownSegments=knownSegments) 440s > 440s > subplots(2, ncol=1) 440s > plotTracks(fit, Clim=Clim) 440s > abline(v=c(knownSegments$start, knownSegments$end)/1e6, lty=3) 440s > 440s > fitList <- list() 440s > for (kk in seq_len(nrow(knownSegments))) { 440s + seg <- knownSegments[kk,] 440s + start <- seg$start 440s + end <- seg$end 440s + fitKK <- extractChromosome(fit, seg$chromosome) 440s + segsKK <- getSegments(fitKK) 440s + idxStart <- min(which(segsKK$start >= start)) 440s + idxEnd <- max(which(segsKK$end <= end)) 440s + idxs <- idxStart:idxEnd 440s + fitKK <- extractSegments(fitKK, idxs) 440s + if (kk %% 2 == 0) { 440s + fitKK <- shiftTCN(fitKK, shift=+10) 440s + } 440s + fitList[[kk]] <- fitKK 440s + } # for (kk ...) 440s > fitT <- do.call(c, fitList) 440s > # Sanity check 440s > stopifnot(nbrOfSegments(fitT) == nbrOfSegments(fit)) 440s > 440s > plotTracks(fitT, Clim=Clim) 440s > abline(v=c(knownSegments$start, knownSegments$end)/1e6, lty=3) 440s > 440s > 440s > segList <- seqOfSegmentsByDP(fit) 440s > K <- length(segList) 440s > subplots(K, ncol=2, byrow=FALSE) 440s > par(mar=c(2,1,1,1)) 440s > for (kk in 1:K) { 440s + knownSegments <- segList[[kk]] 440s + fitKK <- resegment(fit, knownSegments=knownSegments, undo=+Inf) 440s + plotTracks(fitKK, Clim=c(-3,3)) 440s + } # for (kk ...) 444s > 444s Start: segmentByCBS,weights.R 444s 444s R version 4.5.2 (2025-10-31) -- "[Not] Part in a Rumble" 444s Copyright (C) 2025 The R Foundation for Statistical Computing 444s Platform: x86_64-pc-linux-gnu 444s 444s R is free software and comes with ABSOLUTELY NO WARRANTY. 444s You are welcome to redistribute it under certain conditions. 444s Type 'license()' or 'licence()' for distribution details. 444s 444s R is a collaborative project with many contributors. 444s Type 'contributors()' for more information and 444s 'citation()' on how to cite R or R packages in publications. 444s 444s Type 'demo()' for some demos, 'help()' for on-line help, or 444s 'help.start()' for an HTML browser interface to help. 444s Type 'q()' to quit R. 444s 444s > library("PSCBS") 444s PSCBS v0.68.0 (2025-04-18 19:40:02 UTC) successfully loaded. See ?PSCBS for help. 444s > 444s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 444s > # Simulating copy-number data 444s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 444s > set.seed(0xBEEF) 444s > 444s > # Number of loci 444s > J <- 1000 444s > 444s > x <- sort(runif(J, max=J)) * 1e5 444s > 444s > mu <- double(J) 444s > mu[200:300] <- mu[200:300] + 1 444s > mu[350:400] <- NA # centromere 444s > mu[650:800] <- mu[650:800] - 1 444s > eps <- rnorm(J, sd=1/2) 444s > y <- mu + eps 444s > 444s > outliers <- seq(from=1L, to=J, length.out=0.2*J) 444s > y[outliers] <- y[outliers] + 1.5 444s > 444s > w <- rep(1.0, times=J) 444s > w[outliers] <- 0.01 444s > 444s > data <- data.frame(chromosome=1L, x=x, y=y) 444s > dataW <- cbind(data, w=w) 444s > 444s > 444s > par(mar=c(2,3,0.2,1)+0.1) 444s > 444s > 444s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 444s > # Single-chromosome segmentation 444s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 444s > # Segment without weights 444s > fit <- segmentByCBS(data) 444s > sampleName(fit) <- "CBS_Example" 444s > print(fit) 444s sampleName chromosome start end nbrOfLoci mean 444s 1 CBS_Example 1 136857.7 19138391 199 0.2712 444s 2 CBS_Example 1 19138391.4 28682180 101 1.2168 444s 3 CBS_Example 1 28682180.1 64690253 298 0.3027 444s 4 CBS_Example 1 64690253.3 80738828 151 -0.7101 444s 5 CBS_Example 1 80738828.3 99932904 200 0.3655 444s > plotTracks(fit) 444s Warning message: 444s In plotTracks.CBS(fit) : 444s Setting default 'Clim' assuming the signal type is ‘ratio’ because signalType(fit) is unknown (‘NA’). Use signalType(fit) <- ‘ratio’ to avoid this warning. 444s > ## Highlight outliers (they pull up the mean levels) 444s > points(x[outliers]/1e6, y[outliers], col="purple") 444s > 444s > # Segment with weights 444s > fitW <- segmentByCBS(dataW) 444s > sampleName(fitW) <- "CBS_Example (weighted)" 444s > print(fitW) 444s sampleName chromosome start end nbrOfLoci mean 444s 1 CBS_Example (weighted) 1 136857.7 19138391 199 -0.0041 444s 2 CBS_Example (weighted) 1 19138391.4 28682180 101 0.8987 444s 3 CBS_Example (weighted) 1 28682180.1 64690253 298 0.0159 444s 4 CBS_Example (weighted) 1 64690253.3 80738828 151 -1.0215 444s 5 CBS_Example (weighted) 1 80738828.3 99932904 200 0.0653 444s > drawLevels(fitW, col="red") 444s NULL 444s > 444s > legend("topright", bg="white", legend=c("outliers", "non-weighted CBS", "weighted CBS"), col=c("purple", "purple", "red"), lwd=c(NA,3,3), pch=c(1,NA,NA)) 444s > 444s > ## Assert that weighted segment means are less biased 444s > dmean <- getSegments(fit)$mean - getSegments(fitW)$mean 444s > cat("Segment mean differences:\n") 444s Segment mean differences: 444s > print(dmean) 444s [1] 0.2753 0.3181 0.2868 0.3114 0.3002 444s > stopifnot(all(dmean > 0, na.rm=TRUE)) 444s > 444s > 444s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 444s > # Segmentation with some known change points 444s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 444s > knownSegments <- data.frame( 444s + chromosome=c( 1, 1), 444s + start =x[c( 1, 401)], 444s + end =x[c(349, J)] 444s + ) 444s > fit2 <- segmentByCBS(dataW, knownSegments=knownSegments, verbose=TRUE) 444s Segmenting by CBS... 444s Chromosome: 1 444s Segmenting by CBS...done 444s > sampleName(fit2) <- "CBS_Example_2 (weighted)" 444s > print(fit2) 444s sampleName chromosome start end nbrOfLoci mean 444s 1 CBS_Example_2 (weighted) 1 136857.7 19138391 199 -0.0041 444s 2 CBS_Example_2 (weighted) 1 19138391.4 28682180 101 0.8987 444s 3 CBS_Example_2 (weighted) 1 28682180.1 34062461 49 -0.0552 444s 4 CBS_Example_2 (weighted) 1 38343432.8 64690253 249 0.0298 444s 5 CBS_Example_2 (weighted) 1 64690253.3 80738828 151 -1.0215 444s 6 CBS_Example_2 (weighted) 1 80738828.3 99932904 200 0.0653 444s > plotTracks(fit2) 444s Warning message: 444s In plotTracks.CBS(fit2) : 444s Setting default 'Clim' assuming the signal type is ‘ratio’ because signalType(fit2) is unknown (‘NA’). Use signalType(fit2) <- ‘ratio’ to avoid this warning. 444s > abline(v=c(knownSegments$start, knownSegments$end)/1e6, lty=3) 444s > 444s > 444s > # Chromosome boundaries can be specified as -Inf and +Inf 444s > knownSegments <- data.frame( 444s + chromosome=c( 1, 1), 444s + start =c( -Inf, x[401]), 444s + end =c(x[349], +Inf) 444s + ) 444s > fit2b <- segmentByCBS(dataW, knownSegments=knownSegments, verbose=TRUE) 444s Segmenting by CBS... 444s Chromosome: 1 445s Segmenting by CBS...done 445s > sampleName(fit2b) <- "CBS_Example_2b (weighted)" 445s > print(fit2b) 445s sampleName chromosome start end nbrOfLoci mean 445s 1 CBS_Example_2b (weighted) 1 136857.7 19138391 199 -0.0041 445s 2 CBS_Example_2b (weighted) 1 19138391.4 28682180 101 0.8987 445s 3 CBS_Example_2b (weighted) 1 28682180.1 34062461 49 -0.0552 445s 4 CBS_Example_2b (weighted) 1 38343432.8 64690253 249 0.0298 445s 5 CBS_Example_2b (weighted) 1 64690253.3 80738828 151 -1.0215 445s 6 CBS_Example_2b (weighted) 1 80738828.3 99932904 200 0.0653 445s > plotTracks(fit2b) 445s > abline(v=c(knownSegments$start, knownSegments$end)/1e6, lty=3) 445s > 445s > 445s > # As a proof of concept, it is possible to segment just the centromere, 445s > # which contains no data. All statistics will be NAs. 445s > knownSegments <- data.frame( 445s + chromosome=c( 1), 445s + start =x[c(350)], 445s + end =x[c(400)] 445s + Warning message: 445s In plotTracks.CBS(fit2b) : 445s Setting default 'Clim' assuming the signal type is ‘ratio’ because signalType(fit2b) is unknown (‘NA’). Use signalType(fit2b) <- ‘ratio’ to avoid this warning. 445s ) 445s > fit3 <- segmentByCBS(dataW, knownSegments=knownSegments, verbose=TRUE) 445s Segmenting by CBS... 445s Chromosome: 1 445s > sampleName(fit3) <- "CBS_Example_3" 445s Segmenting by CBS...done 445s > print(fit3) 445s sampleName chromosome start end nbrOfLoci mean 445s 1 CBS_Example_3 1 34108010 38257409 0 NA 445s > plotTracks(fit3, Clim=c(0,5), xlim=c(0,100)) 445s > abline(v=c(knownSegments$start, knownSegments$end)/1e6, lty=3) 445s > 445s > 445s > # If one specify the (empty) centromere as a segment, then its 445s > # estimated statistics will be NAs, which becomes a natural 445s > # separator between the two "independent" arms. 445s > knownSegments <- data.frame( 445s + chromosome=c( 1, 1, 1), 445s + start =x[c( 1, 350, 401)], 445s + end =x[c(349, 400, J)] 445s + ) 445s > fit4 <- segmentByCBS(dataW, knownSegments=knownSegments, verbose=TRUE) 445s Segmenting by CBS... 445s Chromosome: 1 445s > sampleName(fit4) <- "CBS_Example_4" 445s > print(fit4) 445s sampleName chromosome start end nbrOfLoci mean 445s 1 CBS_Example_4 1 136857.7 19138391 199 -0.0041 445s 2 CBS_Example_4 1 19138391.4 28682180 101 0.8987 445s 3 CBS_Example_4 1 28682180.1 34062461 49 -0.0552Segmenting by CBS...done 445s 445s 4 CBS_Example_4 1 34108009.8 38257409 0 NA 445s 5 CBS_Example_4 1 38343432.8 64690253 249 0.0298 445s 6 CBS_Example_4 1 64690253.3 80738828 151 -1.0215 445s 7 CBS_Example_4 1 80738828.3 99932904 200 0.0653 445s > plotTracks(fit4) 445s Warning message: 445s In plotTracks.CBS(fit4) : 445s Setting default 'Clim' assuming the signal type is ‘ratio’ because signalType(fit4) is unknown (‘NA’). Use signalType(fit4) <- ‘ratio’ to avoid this warning. 445s > abline(v=c(knownSegments$start, knownSegments$end)/1e6, lty=3) 445s > 445s > 445s > fit5 <- segmentByCBS(dataW, knownSegments=knownSegments, undo=Inf, verbose=TRUE) 445s Segmenting by CBS... 445s Chromosome: 1 445s > sampleName(fit5) <- "CBS_Example_5" 445s > print(fit5) 445s Segmenting by CBS...done 445s sampleName chromosome start end nbrOfLoci mean 445s 1 CBS_Example_5 1 136857.7 34062461 349 0.54781248 445s 2 CBS_Example_5 1 34108009.8 38257409 0 NA 445s 3 CBS_Example_5 1 38343432.8 99932904 600 0.06959745 445s > plotTracks(fit5) 445s > abline(v=c(knownSegments$start, knownSegments$end)/1e6, lty=3) 445s > stopifnot(nbrOfSegments(fit5) == nrow(knownSegments)) 445s Warning message: 445s In plotTracks.CBS(fit5) : 445s Setting default 'Clim' assuming the signal type is ‘ratio’ because signalType(fit5) is unknown (‘NA’). Use signalType(fit5) <- ‘ratio’ to avoid this warning. 445s > 445s > 445s > # One can also force a separator between two segments by setting 445s > # 'start' and 'end' to NAs ('chromosome' has to be given) 445s > knownSegments <- data.frame( 445s + chromosome=c( 1, 1, 1), 445s + start =x[c( 1, NA, 401)], 445s + end =x[c(349, NA, J)] 445s + ) 445s > fit6 <- segmentByCBS(dataW, knownSegments=knownSegments, verbose=TRUE) 445s Segmenting by CBS... 445s Chromosome: 1 445s > sampleName(fit6) <- "CBS_Example_6" 445s Segmenting by CBS...done 445s > print(fit6) 445s sampleName chromosome start end nbrOfLoci mean 445s 1 CBS_Example_6 1 136857.7 19138391 199 -0.0041 445s 2 CBS_Example_6 1 19138391.4 28682180 101 0.8987 445s 3 CBS_Example_6 1 28682180.1 34062461 49 -0.0552 445s 4 NA NA NA NA NA 445s 5 CBS_Example_6 1 38343432.8 64690253 249 0.0298 445s 6 CBS_Example_6 1 64690253.3 80738828 151 -1.0215 445s 7 CBS_Example_6 1 80738828.3 99932904 200 0.0653 445s > plotTracks(fit6) 445s > abline(v=c(knownSegments$start, knownSegments$end)/1e6, lty=3) 445s > 445s > 445s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 445s > # Multi-chromosome segmentation 445s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 445s > data2 <- data 445s > data2$chromosome <- 2L 445s > data <- rbind(data, data2) 445s > dataW <- cbind(data, w=w) 445s > 445s > par(mar=c(2,3,0.2,1)+0.1) 445s > # Segment without weights 445s > fit <- segmentByCBS(data) 445s Warning message: 445s In plotTracks.CBS(fit6) : 445s Setting default 'Clim' assuming the signal type is ‘ratio’ because signalType(fit6) is unknown (‘NA’). Use signalType(fit6) <- ‘ratio’ to avoid this warning. 445s > sampleName(fit) <- "CBS_Example" 445s > print(fit) 445s sampleName chromosome start end nbrOfLoci mean 445s 1 CBS_Example 1 136857.7 19138391 199 0.2712 445s 2 CBS_Example 1 19138391.4 28682180 101 1.2168 445s 3 CBS_Example 1 28682180.1 64690253 298 0.3027 445s 4 CBS_Example 1 64690253.3 80738828 151 -0.7101 445s 5 CBS_Example 1 80738828.3 99932904 200 0.3655 445s 6 NA NA NA NA NA 445s 7 CBS_Example 2 136857.7 19138391 199 0.2712 445s 8 CBS_Example 2 19138391.4 28682180 101 1.2168 445s 9 CBS_Example 2 28682180.1 64690253 298 0.3027 445s 10 CBS_Example 2 64690253.3 80738828 151 -0.7101 445s 11 CBS_Example 2 80738828.3 99932904 200 0.3655 445s > plotTracks(fit, Clim=c(-3,3)) 445s > 445s > # Segment with weights 445s > fitW <- segmentByCBS(dataW) 445s > sampleName(fitW) <- "CBS_Example (weighted)" 445s > print(fitW) 445s sampleName chromosome start end nbrOfLoci mean 445s 1 CBS_Example (weighted) 1 136857.7 19138391 199 -0.0041 445s 2 CBS_Example (weighted) 1 19138391.4 28682180 101 0.8987 445s 3 CBS_Example (weighted) 1 28682180.1 64690253 298 0.0159 445s 4 CBS_Example (weighted) 1 64690253.3 80738828 151 -1.0215 445s 5 CBS_Example (weighted) 1 80738828.3 99932904 200 0.0653 445s 6 NA NA NA NA NA 445s 7 CBS_Example (weighted) 2 136857.7 19138391 199 -0.0041 445s 8 CBS_Example (weighted) 2 19138391.4 28682180 101 0.8987 445s 9 CBS_Example (weighted) 2 28682180.1 64690253 298 0.0159 445s 10 CBS_Example (weighted) 2 64690253.3 80738828 151 -1.0215 445s 11 CBS_Example (weighted) 2 80738828.3 99932904 200 0.0653 445s > drawLevels(fitW, col="red") 445s NULL 445s > 445s > legend("topright", bg="white", legend=c("outliers", "non-weighted CBS", "weighted CBS"), col=c("purple", "purple", "red"), lwd=c(NA,3,3), pch=c(1,NA,NA)) 445s > 445s > ## Assert that weighted segment means are less biased 445s > dmean <- getSegments(fit)$mean - getSegments(fitW)$mean 445s > cat("Segment mean differences:\n") 445s Segment mean differences: 445s > print(dmean) 445s [1] 0.2753 0.3181 0.2868 0.3114 0.3002 NA 0.2753 0.3181 0.2868 0.3114 445s [11] 0.3002 445s > stopifnot(all(dmean > 0, na.rm=TRUE)) 445s > 445s Start: segmentByCBS.R 445s 445s R version 4.5.2 (2025-10-31) -- "[Not] Part in a Rumble" 445s Copyright (C) 2025 The R Foundation for Statistical Computing 445s Platform: x86_64-pc-linux-gnu 445s 445s R is free software and comes with ABSOLUTELY NO WARRANTY. 445s You are welcome to redistribute it under certain conditions. 445s Type 'license()' or 'licence()' for distribution details. 445s 445s R is a collaborative project with many contributors. 445s Type 'contributors()' for more information and 445s 'citation()' on how to cite R or R packages in publications. 445s 445s Type 'demo()' for some demos, 'help()' for on-line help, or 445s 'help.start()' for an HTML browser interface to help. 445s Type 'q()' to quit R. 445s 445s > ########################################################### 445s > # This tests: 445s > # - segmentByCBS(...) 445s > # - segmentByCBS(..., knownSegments) 445s > # - tileChromosomes() 445s > # - plotTracks() 445s > ########################################################### 445s > library("PSCBS") 446s PSCBS v0.68.0 (2025-04-18 19:40:02 UTC) successfully loaded. See ?PSCBS for help. 446s > subplots <- R.utils::subplots 446s > 446s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 446s > # Simulating copy-number data 446s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 446s > set.seed(0xBEEF) 446s > 446s > # Number of loci 446s > J <- 1000 446s > 446s > mu <- double(J) 446s > mu[200:300] <- mu[200:300] + 1 446s > mu[350:400] <- NA # centromere 446s > mu[650:800] <- mu[650:800] - 1 446s > eps <- rnorm(J, sd=1/2) 446s > y <- mu + eps 446s > x <- sort(runif(length(y), max=length(y))) * 1e5 446s > w <- runif(J) 446s > w[650:800] <- 0.001 446s > 446s > 446s > subplots(8, ncol=1L) 446s > par(mar=c(1.7,1,0.2,1)+0.1) 446s > 446s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 446s > # Segmentation 446s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 446s > fit <- segmentByCBS(y, x=x) 446s > sampleName(fit) <- "CBS_Example" 446s > print(fit) 446s sampleName chromosome start end nbrOfLoci mean 446s 1 CBS_Example 0 55167.82 20774251 201 0.0164 446s 2 CBS_Example 0 20774250.85 29320105 99 1.0474 446s 3 CBS_Example 0 29320104.86 65874675 298 -0.0203 446s 4 CBS_Example 0 65874675.06 81348129 151 -1.0813 446s 5 CBS_Example 0 81348129.20 99910827 200 -0.0612 446s > plotTracks(fit) 446s Warning message: 446s In plotTracks.CBS(fit) : 446s Setting default 'Clim' assuming the signal type is ‘ratio’ because signalType(fit) is unknown (‘NA’). Use signalType(fit) <- ‘ratio’ to avoid this warning. 446s > 446s > 446s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 446s > # Segmentation with some known change points 446s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 446s > knownSegments <- data.frame( 446s + chromosome=c( 0, 0), 446s + start =x[c( 1, 401)], 446s + end =x[c(349, J)] 446s + ) 446s > fit2 <- segmentByCBS(y, x=x, knownSegments=knownSegments, verbose=TRUE) 446s Segmenting by CBS... 446s Chromosome: 0 446s Segmenting by CBS...done 446s > sampleName(fit2) <- "CBS_Example_2" 446s > print(fit2) 446s sampleName chromosome start end nbrOfLoci mean 446s 1 CBS_Example_2 0 55167.82 20774251 201 0.0164 446s 2 CBS_Example_2 0 20774250.85 29320105 99 1.0474 446s 3 CBS_Example_2 0 29320104.86 34142178 49 -0.0193 446s 4 CBS_Example_2 0 41080532.92 65874675 249 -0.0205 446s 5 CBS_Example_2 0 65874675.06 81348129 151 -1.0813 446s 6 CBS_Example_2 0 81348129.20 99910827 200 -0.0612 446s > plotTracks(fit2) 446s > abline(v=c(knownSegments$start, knownSegments$end)/1e6, lty=3) 446s > 446s > 446s > # Chromosome boundaries can be specified as -Inf and +Inf 446s > knownSegments <- data.frame( 446s + chromosome=c( 0, 0), 446s + start =c( -Inf, x[401]), 446s + end =c(x[349], +Inf) 446s + ) 446s Warning message: 446s In plotTracks.CBS(fit2) : 446s Setting default 'Clim' assuming the signal type is ‘ratio’ because signalType(fit2) is unknown (‘NA’). Use signalType(fit2) <- ‘ratio’ to avoid this warning. 446s > fit2b <- segmentByCBS(y, x=x, knownSegments=knownSegments, verbose=TRUE) 446s Segmenting by CBS... 446s Chromosome: 0 446s Segmenting by CBS...done 446s > sampleName(fit2b) <- "CBS_Example_2b" 446s > print(fit2b) 446s sampleName chromosome start end nbrOfLoci mean 446s 1 CBS_Example_2b 0 55167.82 20774251 201 0.0164 446s 2 CBS_Example_2b 0 20774250.85 29320105 99 1.0474 446s 3 CBS_Example_2b 0 29320104.86 34142178 49 -0.0193 446s 4 CBS_Example_2b 0 41080532.92 65874675 249 -0.0205 446s 5 CBS_Example_2b 0 65874675.06 81348129 151 -1.0813 446s 6 CBS_Example_2b 0 81348129.20 99910827 200 -0.0612 446s > plotTracks(fit2b) 446s > abline(v=c(knownSegments$start, knownSegments$end)/1e6, lty=3) 446s > 446s > 446s > # As a proof of concept, it is possible to segment just the centromere, 446s > # which contains no data. All statistics will be NAs. 446s > knownSegments <- data.frame( 446s + chromosome=c( 0), 446s + start =x[c(350)], 446s + end =x[c(400)] 446s + ) 446s Warning message: 446s In plotTracks.CBS(fit2b) : 446s Setting default 'Clim' assuming the signal type is ‘ratio’ because signalType(fit2b) is unknown (‘NA’). Use signalType(fit2b) <- ‘ratio’ to avoid this warning. 446s > fit3 <- segmentByCBS(y, x=x, knownSegments=knownSegments, verbose=TRUE) 446s Segmenting by CBS... 446s Chromosome: 0 446s > sampleName(fit3) <- "CBS_Example_3" 446s > print(fit3) 446s Segmenting by CBS...done 446s sampleName chromosome start end nbrOfLoci mean 446s 1 CBS_Example_3 0 34194740 41044125 0 NA 446s > plotTracks(fit3, Clim=c(0,5), xlim=c(0,100)) 446s > abline(v=c(knownSegments$start, knownSegments$end)/1e6, lty=3) 446s > 446s > 446s > 446s > # If one specify the (empty) centromere as a segment, then its 446s > # estimated statistics will be NAs, which becomes a natural 446s > # separator between the two "independent" arms. 446s > knownSegments <- data.frame( 446s + chromosome=c( 0, 0, 0), 446s + start =x[c( 1, 350, 401)], 446s + end =x[c(349, 400, J)] 446s + ) 446s > fit4 <- segmentByCBS(y, x=x, knownSegments=knownSegments, verbose=TRUE) 446s Segmenting by CBS... 446s Chromosome: 0 446s Segmenting by CBS...done 446s > sampleName(fit4) <- "CBS_Example_4" 446s > print(fit4) 446s sampleName chromosome start end nbrOfLoci mean 446s 1 CBS_Example_4 0 55167.82 20774251 201 0.0164 446s 2 CBS_Example_4 0 20774250.85 29320105 99 1.0474 446s 3 CBS_Example_4 0 29320104.86 34142178 49 -0.0193 446s 4 CBS_Example_4 0 34194739.81 41044125 0 NA 446s 5 CBS_Example_4 0 41080532.92 65874675 249 -0.0205 446s 6 CBS_Example_4 0 65874675.06 81348129 151 -1.0813 446s 7 CBS_Example_4 0 81348129.20 99910827 200 -0.0612 446s > plotTracks(fit4) 446s Warning message: 446s In plotTracks.CBS(fit4) : 446s Setting default 'Clim' assuming the signal type is ‘ratio’ because signalType(fit4) is unknown (‘NA’). Use signalType(fit4) <- ‘ratio’ to avoid this warning. 446s Segmenting by CBS... 446s Chromosome: 0 446s > abline(v=c(knownSegments$start, knownSegments$end)/1e6, lty=3) 446s > 446s > 446s > 446s > fit5 <- segmentByCBS(y, x=x, knownSegments=knownSegments, undo=Inf, verbose=TRUE) 446s Segmenting by CBS...done 446s > sampleName(fit5) <- "CBS_Example_5" 446s > print(fit5) 446s sampleName chromosome start end nbrOfLoci mean 446s 1 CBS_Example_5 0 55167.82 34142178 349 0.3038785 446s 2 CBS_Example_5 0 34194739.81 41044125 0 NA 446s 3 CBS_Example_5 0 41080532.92 99910827 600 -0.3010285 446s > plotTracks(fit5) 446s > abline(v=c(knownSegments$start, knownSegments$end)/1e6, lty=3) 446s > stopifnot(nbrOfSegments(fit5) == nrow(knownSegments)) 446s > 446s > 446s > # One can also force a separator between two segments by setting 446s > # 'start' and 'end' to NAs ('chromosome' has to be given) 446s > knownSegments <- data.frame( 446s + chromosome=c( 0, 0, 0), 446s + start =x[c( 1, NA, 401)], 446s + end =x[c(349, NA, J)] 446s + ) 446s > fit6 <- segmentByCBS(y, x=x, knownSegments=knownSegments, verbose=TRUE) 446s Warning message: 446s In plotTracks.CBS(fit5) : 446s Setting default 'Clim' assuming the signal type is ‘ratio’ because signalType(fit5) is unknown (‘NA’). Use signalType(fit5) <- ‘ratio’ to avoid this warning. 446s Segmenting by CBS... 446s Chromosome: 0 447s > sampleName(fit6) <- "CBS_Example_6" 447s Segmenting by CBS...done 447s > print(fit6) 447s sampleName chromosome start end nbrOfLoci mean 447s 1 CBS_Example_6 0 55167.82 20774251 201 0.0164 447s 2 CBS_Example_6 0 20774250.85 29320105 99 1.0474 447s 3 CBS_Example_6 0 29320104.86 34142178 49 -0.0193 447s 4 NA NA NA NA NA 447s 5 CBS_Example_6 0 41080532.92 65874675 249 -0.0205 447s 6 CBS_Example_6 0 65874675.06 81348129 151 -1.0813 447s 7 CBS_Example_6 0 81348129.20 99910827 200 -0.0612 447s > plotTracks(fit6) 447s Warning message: 447s In plotTracks.CBS(fit6) : 447s Setting default 'Clim' assuming the signal type is ‘ratio’ because signalType(fit6) is unknown (‘NA’). Use signalType(fit6) <- ‘ratio’ to avoid this warning. 447s > abline(v=c(knownSegments$start, knownSegments$end)/1e6, lty=3) 447s > 447s > 447s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 447s > # Segment multiple chromosomes 447s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 447s > # Simulate multiple chromosomes 447s > fit1 <- renameChromosomes(fit, from=0, to=1) 447s > fit2 <- renameChromosomes(fit, from=0, to=2) 447s > fitM <- c(fit1, fit2) 447s > fitM <- segmentByCBS(fitM) 447s > sampleName(fitM) <- "CBS_Example_M" 447s > print(fitM) 447s sampleName chromosome start end nbrOfLoci mean 447s 1 CBS_Example_M 1 55167.82 20774251 201 0.0164 447s 2 CBS_Example_M 1 20774250.85 29320105 99 1.0474 447s 3 CBS_Example_M 1 29320104.86 65874675 298 -0.0203 447s 4 CBS_Example_M 1 65874675.06 81348129 151 -1.0813 447s 5 CBS_Example_M 1 81348129.20 99910827 200 -0.0612 447s 6 NA NA NA NA NA 447s 7 CBS_Example_M 2 55167.82 20774251 201 0.0164 447s 8 CBS_Example_M 2 20774250.85 29320105 99 1.0474 447s 9 CBS_Example_M 2 29320104.86 65874675 298 -0.0203 447s 10 CBS_Example_M 2 65874675.06 81348129 151 -1.0813 447s 11 CBS_Example_M 2 81348129.20 99910827 200 -0.0612 447s > plotTracks(fitM, Clim=c(-3,3)) 447s > 447s > 447s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 447s > # Tiling multiple chromosomes 447s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 447s > # Tile chromosomes 447s > fitT <- tileChromosomes(fitM) 447s > fitTb <- tileChromosomes(fitT) 447s > stopifnot(identical(fitTb, fitT)) 447s > 447s > 447s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 447s > # Write segmentation to file 447s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 447s > pathT <- tempdir() 447s > 447s > ## Tab-delimited file 447s > pathname <- writeSegments(fitM, path=pathT) 447s Warning message: 447s In write.table(file = pathnameT, data, append = TRUE, quote = FALSE, : 447s appending column names to file 447s > print(pathname) 447s [1] "/tmp/RtmpriRcZK/CBS_Example_M.tsv" 447s > 447s > ## WIG file 447s > pathname <- writeWIG(fitM, path=pathT) 447s > print(pathname) 447s [1] "/tmp/RtmpriRcZK/CBS_Example_M.wig" 447s > 447s > unlink(pathT, recursive=TRUE) 447s > 447s Start: segmentByNonPairedPSCBS,medianDH.R 447s 447s R version 4.5.2 (2025-10-31) -- "[Not] Part in a Rumble" 447s Copyright (C) 2025 The R Foundation for Statistical Computing 447s Platform: x86_64-pc-linux-gnu 447s 447s R is free software and comes with ABSOLUTELY NO WARRANTY. 447s You are welcome to redistribute it under certain conditions. 447s Type 'license()' or 'licence()' for distribution details. 447s 447s R is a collaborative project with many contributors. 447s Type 'contributors()' for more information and 447s 'citation()' on how to cite R or R packages in publications. 447s 447s Type 'demo()' for some demos, 'help()' for on-line help, or 447s 'help.start()' for an HTML browser interface to help. 447s Type 'q()' to quit R. 447s 447s > library("PSCBS") 447s PSCBS v0.68.0 (2025-04-18 19:40:02 UTC) successfully loaded. See ?PSCBS for help. 447s > 447s > 447s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 447s > # Load SNP microarray data 447s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 447s > data <- PSCBS::exampleData("paired.chr01") 447s > str(data) 447s 'data.frame': 73346 obs. of 6 variables: 447s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 447s $ x : int 1145994 2224111 2319424 2543484 2926730 2941694 3084986 3155127 3292731 3695086 ... 447s $ CT : num 1.625 1.071 1.406 1.18 0.856 ... 447s $ betaT : num 0.757 0.771 0.834 0.778 0.229 ... 447s $ CN : num 2.36 2.13 2.59 1.93 1.71 ... 447s $ betaN : num 0.827 0.875 0.887 0.884 0.103 ... 447s > 447s > # Non-paired / tumor-only data 447s > data <- data[,c("chromosome", "x", "CT", "betaT")] 447s > str(data) 447s 'data.frame': 73346 obs. of 4 variables: 447s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 447s $ x : int 1145994 2224111 2319424 2543484 2926730 2941694 3084986 3155127 3292731 3695086 ... 447s $ CT : num 1.625 1.071 1.406 1.18 0.856 ... 447s $ betaT : num 0.757 0.771 0.834 0.778 0.229 ... 447s > 447s > 447s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 447s > # Paired PSCBS segmentation 447s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 447s > # Drop single-locus outliers 447s > dataS <- dropSegmentationOutliers(data) 447s > 447s > # Speed up example by segmenting fewer loci 447s > dataS <- dataS[seq(from=1, to=nrow(data), by=20),] 447s > 447s > # Fake a second chromosome 447s > dataT <- dataS 447s > dataT$chromosome <- 2L 447s > dataS <- rbind(dataS, dataT) 447s > rm(dataT) 447s > str(dataS) 447s 'data.frame': 7336 obs. of 4 variables: 447s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 447s $ x : int 1145994 4276892 5034491 6266412 8418532 11211748 13928296 14370144 15014887 16589707 ... 447s $ CT : num 1.63 1.16 1.35 1.39 1.55 ... 447s $ betaT : num 0.7574 0.0576 0.8391 0.7917 0.8141 ... 447s > 447s > # Non-Paired PSCBS segmentation 447s > fit <- segmentByNonPairedPSCBS(dataS, avgDH="median", seed=0xBEEF, verbose=-10) 447s Segmenting non-paired tumor signals using Non-paired PSCBS... 447s Number of loci: 7336 447s Number of SNPs: 7336 447s Calling "genotypes" from tumor allele B fractions... 447s num [1:7336] 0.7574 0.0576 0.8391 0.7917 0.8141 ... 447s Upper quantile: 0.475631667925522 447s Symmetric lower quantile: 0.290517384533512 447s (tauA, tauB) estimates: (%g,%g)0.2094826154664880.790517384533512 447s Homozygous treshholds: 447s [1] 0.2094826 0.7905174 447s Inferred germline genotypes (via tumor): 447s num [1:7336] 0.5 0 1 1 1 0 0 0 0.5 1 ... 447s muNx 447s 0 0.5 1 447s 2230 2910 2196 447s Calling "genotypes" from tumor allele B fractions...done 447s Segmenting non-paired tumor signals using Non-paired PSCBS...done 447s Segment using Paired PSCBS... 447s Segmenting paired tumor-normal signals using Paired PSCBS... 447s Setup up data... 447s 'data.frame': 7336 obs. of 6 variables: 447s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 447s $ x : num 1145994 4276892 5034491 6266412 8418532 ... 447s $ CT : num 1.63 1.16 1.35 1.39 1.55 ... 447s $ betaT : num 0.7574 0.0576 0.8391 0.7917 0.8141 ... 447s $ betaTN : num 0.7574 0.0576 0.8391 0.7917 0.8141 ... 447s $ muN : num 0.5 0 1 1 1 0 0 0 0.5 1 ... 447s Setup up data...done 447s Dropping loci for which TCNs are missing... 447s Number of loci dropped: 12 447s Dropping loci for which TCNs are missing...done 447s Ordering data along genome... 447s 'data.frame': 7324 obs. of 6 variables: 447s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 447s $ x : num 554484 1031563 1087198 1145994 1176365 ... 447s $ CT : num 1.88 1.64 1.77 1.63 1.59 ... 447s $ betaT : num 0.0646 0.6078 0.401 0.7574 0.645 ... 447s $ betaTN : num 0.0646 0.6078 0.401 0.7574 0.645 ... 447s $ muN : num 0 0.5 0.5 0.5 0.5 0.5 1 0.5 0.5 0.5 ... 447s Ordering data along genome...done 447s Segmenting multiple chromosomes... 447s Number of chromosomes: 2 447s Random seed temporarily set (seed=c(48879), kind="L'Ecuyer-CMRG") 447s Produced 2 seeds from this stream for future usage 447s Chromosome #1 ('Chr01') of 2... 447s 'data.frame': 3662 obs. of 7 variables: 447s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 447s $ x : num 554484 1031563 1087198 1145994 1176365 ... 447s $ CT : num 1.88 1.64 1.77 1.63 1.59 ... 447s $ betaT : num 0.0646 0.6078 0.401 0.7574 0.645 ... 447s $ betaTN : num 0.0646 0.6078 0.401 0.7574 0.645 ... 447s $ muN : num 0 0.5 0.5 0.5 0.5 0.5 1 0.5 0.5 0.5 ... 447s $ index : int 1 2 3 4 5 6 7 8 9 10 ... 447s Known segments: 447s [1] chromosome start end 447s <0 rows> (or 0-length row.names) 447s Segmenting paired tumor-normal signals using Paired PSCBS... 447s Setup up data... 447s 'data.frame': 3662 obs. of 6 variables: 447s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 447s $ x : num 554484 1031563 1087198 1145994 1176365 ... 447s $ CT : num 1.88 1.64 1.77 1.63 1.59 ... 447s $ betaT : num 0.0646 0.6078 0.401 0.7574 0.645 ... 447s $ betaTN : num 0.0646 0.6078 0.401 0.7574 0.645 ... 447s $ muN : num 0 0.5 0.5 0.5 0.5 0.5 1 0.5 0.5 0.5 ... 447s Setup up data...done 447s Ordering data along genome... 447s 'data.frame': 3662 obs. of 6 variables: 447s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 447s $ x : num 554484 1031563 1087198 1145994 1176365 ... 447s $ CT : num 1.88 1.64 1.77 1.63 1.59 ... 447s $ betaT : num 0.0646 0.6078 0.401 0.7574 0.645 ... 447s $ betaTN : num 0.0646 0.6078 0.401 0.7574 0.645 ... 447s $ muN : num 0 0.5 0.5 0.5 0.5 0.5 1 0.5 0.5 0.5 ... 447s Ordering data along genome...done 447s Keeping only current chromosome for 'knownSegments'... 447s Chromosome: 1 447s Known segments for this chromosome: 447s [1] chromosome start end 447s <0 rows> (or 0-length row.names) 447s Keeping only current chromosome for 'knownSegments'...done 447s alphaTCN: 0.009 447s alphaDH: 0.001 447s Number of loci: 3662 447s Calculating DHs... 447s Number of SNPs: 3662 447s Number of heterozygous SNPs: 1451 (39.62%) 447s Normalized DHs: 447s num [1:3662] NA 0.216 0.198 0.515 0.29 ... 447s Calculating DHs...done 447s Random seed temporarily set (seed=c(10407, 1066287653, -51199871, 161854402, -1995183193, 1503453565, -747102133), kind="L'Ecuyer-CMRG") 447s Produced 2 seeds from this stream for future usage 447s Identification of change points by total copy numbers... 447s Segmenting by CBS... 447s Chromosome: 1 447s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 447s Segmenting by CBS...done 447s List of 4 447s $ data :'data.frame': 3662 obs. of 4 variables: 447s ..$ chromosome: int [1:3662] 1 1 1 1 1 1 1 1 1 1 ... 447s ..$ x : num [1:3662] 554484 1031563 1087198 1145994 1176365 ... 447s ..$ y : num [1:3662] 1.88 1.64 1.77 1.63 1.59 ... 447s ..$ index : int [1:3662] 1 2 3 4 5 6 7 8 9 10 ... 447s $ output :'data.frame': 3 obs. of 6 variables: 447s ..$ sampleName: chr [1:3] NA NA NA 447s ..$ chromosome: int [1:3] 1 1 1 447s ..$ start : num [1:3] 5.54e+05 1.44e+08 1.85e+08 447s ..$ end : num [1:3] 1.44e+08 1.85e+08 2.47e+08 447s ..$ nbrOfLoci : int [1:3] 1880 671 1111 447s ..$ mean : num [1:3] 1.39 2.09 2.65 447s $ segRows:'data.frame': 3 obs. of 2 variables: 447s ..$ startRow: int [1:3] 1 1881 2552 447s ..$ endRow : int [1:3] 1880 2551 3662 447s $ params :List of 5 447s ..$ alpha : num 0.009 447s ..$ undo : num 0 447s ..$ joinSegments : logi TRUE 447s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 447s .. ..$ chromosome: int 1 447s .. ..$ start : num -Inf 447s .. ..$ end : num Inf 447s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 447s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 447s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.042 0.001 0.041 0 0 447s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 447s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 447s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 447s Identification of change points by total copy numbers...done 447s Restructure TCN segmentation results... 447s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean 447s 1 1 554484 143663981 1880 1.3916 447s 2 1 143663981 185240536 671 2.0925 447s 3 1 185240536 246679946 1111 2.6545 447s Number of TCN segments: 3 447s Restructure TCN segmentation results...done 447s TCN-only segmentation... 447s Total CN segment #1 ([ 554484,1.43664e+08]) of 3... 447s Number of TCN loci in segment: 1880 447s Locus data for TCN segment: 447s 'data.frame': 1880 obs. of 8 variables: 447s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 447s $ x : num 554484 1031563 1087198 1145994 1176365 ... 447s $ CT : num 1.88 1.64 1.77 1.63 1.59 ... 447s $ betaT : num 0.0646 0.6078 0.401 0.7574 0.645 ... 447s $ betaTN : num 0.0646 0.6078 0.401 0.7574 0.645 ... 447s $ muN : num 0 0.5 0.5 0.5 0.5 0.5 1 0.5 0.5 0.5 ... 447s $ index : int 1 2 3 4 5 6 7 8 9 10 ... 447s $ rho : num NA 0.216 0.198 0.515 0.29 ... 447s Number of loci: 1880 447s Number of SNPs: 765 (40.69%) 447s Number of heterozygous SNPs: 765 (100.00%) 447s Total CN segment #1 ([ 554484,1.43664e+08]) of 3...done 447s Total CN segment #2 ([1.43664e+08,1.85241e+08]) of 3... 447s Number of TCN loci in segment: 671 447s Locus data for TCN segment: 447s 'data.frame': 671 obs. of 8 variables: 447s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 447s $ x : num 1.44e+08 1.44e+08 1.44e+08 1.44e+08 1.44e+08 ... 447s $ CT : num 2.26 2.1 2.1 1.89 1.97 ... 447s $ betaT : num 0.958 0.19 0.909 0.13 0.141 ... 447s $ betaTN : num 0.958 0.19 0.909 0.13 0.141 ... 447s $ muN : num 1 0 1 0 0 0 0 0.5 0 1 ... 447s $ index : int 1881 1882 1883 1884 1885 1886 1887 1888 1889 1890 ... 447s $ rho : num NA NA NA NA NA ... 447s Number of loci: 671 447s Number of SNPs: 272 (40.54%) 447s Number of heterozygous SNPs: 272 (100.00%) 447s Total CN segment #2 ([1.43664e+08,1.85241e+08]) of 3...done 447s Total CN segment #3 ([1.85241e+08,2.4668e+08]) of 3... 447s Number of TCN loci in segment: 1111 447s Locus data for TCN segment: 447s 'data.frame': 1111 obs. of 8 variables: 447s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 447s $ x : num 1.85e+08 1.86e+08 1.86e+08 1.86e+08 1.86e+08 ... 447s $ CT : num 2.44 3 2.32 2.76 2.48 ... 447s $ betaT : num 0.0727 0.6845 0.2327 0.8118 0.0746 ... 447s $ betaTN : num 0.0727 0.6845 0.2327 0.8118 0.0746 ... 447s $ muN : num 0 0.5 0.5 1 0 1 0 1 1 0.5 ... 447s $ index : int 2552 2553 2554 2555 2556 2557 2558 2559 2560 2561 ... 447s $ rho : num NA 0.369 0.535 NA NA ... 447s Number of loci: 1111 447s Number of SNPs: 414 (37.26%) 447s Number of heterozygous SNPs: 414 (100.00%) 447s Total CN segment #3 ([1.85241e+08,2.4668e+08]) of 3...done 447s TCN-only segmentation...done 447s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 447s 1 1 1 1 554484 143663981 1880 1.3916 765 447s 2 1 2 1 143663981 185240536 671 2.0925 272 447s 3 1 3 1 185240536 246679946 1111 2.6545 414 447s tcnNbrOfHets dhNbrOfLoci dhStart dhEnd dhMean 447s 1 765 765 554484 143663981 0.3979122 447s 2 272 272 143663981 185240536 0.2306116 447s 3 414 414 185240536 246679946 0.2798120 447s Calculating (C1,C2) per segment... 447s Calculating (C1,C2) per segment...done 447s Number of segments: 3 447s Segmenting paired tumor-normal signals using Paired PSCBS...done 447s Updating mean level using different estimator... 447s TCN estimator: mean 447s DH estimator: median 447s Updating mean level using different estimator...done 447s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 447s 1 1 1 1 554484 143663981 1880 1.391608 765 447s 2 1 2 1 143663981 185240536 671 2.092452 272 447s 3 1 3 1 185240536 246679946 1111 2.654512 414 447s tcnNbrOfHets dhNbrOfLoci dhStart dhEnd dhMean c1Mean c2Mean 447s 1 765 765 554484 143663981 0.4206323 0.4031263 0.9884817 447s 2 272 272 143663981 185240536 0.1762428 0.8618360 1.2306156 447s 3 414 414 185240536 246679946 0.2697420 0.9692395 1.6852728 447s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 447s 1 1 1 1 554484 143663981 1880 1.391608 765 447s 2 1 2 1 143663981 185240536 671 2.092452 272 447s 3 1 3 1 185240536 246679946 1111 2.654512 414 447s tcnNbrOfHets dhNbrOfLoci dhStart dhEnd dhMean c1Mean c2Mean 447s 1 765 765 554484 143663981 0.4206323 0.4031263 0.9884817 447s 2 272 272 143663981 185240536 0.1762428 0.8618360 1.2306156 447s 3 414 414 185240536 246679946 0.2697420 0.9692395 1.6852728 447s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 447s 1 1 1 1 554484 143663981 1880 1.391608 765 447s 2 1 2 1 143663981 185240536 671 2.092452 272 447s 3 1 3 1 185240536 246679946 1111 2.654512 414 447s tcnNbrOfHets dhNbrOfLoci dhStart dhEnd dhMean c1Mean c2Mean 447s 1 765 765 554484 143663981 0.4206323 0.4031263 0.9884817 447s 2 272 272 143663981 185240536 0.1762428 0.8618360 1.2306156 447s 3 414 414 185240536 246679946 0.2697420 0.9692395 1.6852728 447s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 447s 1 1 1 1 554484 143663981 1880 1.391608 765 447s 2 1 2 1 143663981 185240536 671 2.092452 272 447s 3 1 3 1 185240536 246679946 1111 2.654512 414 447s tcnNbrOfHets dhNbrOfLoci dhStart dhEnd dhMean c1Mean c2Mean 447s 1 765 765 554484 143663981 0.4206323 0.4031263 0.9884817 447s 2 272 272 143663981 185240536 0.1762428 0.8618360 1.2306156 447s 3 414 414 185240536 246679946 0.2697420 0.9692395 1.6852728 447s Chromosome #1 ('Chr01') of 2...done 447s Chromosome #2 ('Chr02') of 2... 447s 'data.frame': 3662 obs. of 7 variables: 447s $ chromosome: int 2 2 2 2 2 2 2 2 2 2 ... 447s $ x : num 554484 1031563 1087198 1145994 1176365 ... 447s $ CT : num 1.88 1.64 1.77 1.63 1.59 ... 447s $ betaT : num 0.0646 0.6078 0.401 0.7574 0.645 ... 447s $ betaTN : num 0.0646 0.6078 0.401 0.7574 0.645 ... 447s $ muN : num 0 0.5 0.5 0.5 0.5 0.5 1 0.5 0.5 0.5 ... 447s $ index : int 3663 3664 3665 3666 3667 3668 3669 3670 3671 3672 ... 447s Known segments: 447s [1] chromosome start end 447s <0 rows> (or 0-length row.names) 447s Segmenting paired tumor-normal signals using Paired PSCBS... 447s Setup up data... 447s 'data.frame': 3662 obs. of 6 variables: 447s $ chromosome: int 2 2 2 2 2 2 2 2 2 2 ... 447s $ x : num 554484 1031563 1087198 1145994 1176365 ... 447s $ CT : num 1.88 1.64 1.77 1.63 1.59 ... 447s $ betaT : num 0.0646 0.6078 0.401 0.7574 0.645 ... 447s $ betaTN : num 0.0646 0.6078 0.401 0.7574 0.645 ... 447s $ muN : num 0 0.5 0.5 0.5 0.5 0.5 1 0.5 0.5 0.5 ... 447s Setup up data...done 447s Ordering data along genome... 447s 'data.frame': 3662 obs. of 6 variables: 447s $ chromosome: int 2 2 2 2 2 2 2 2 2 2 ... 447s $ x : num 554484 1031563 1087198 1145994 1176365 ... 447s $ CT : num 1.88 1.64 1.77 1.63 1.59 ... 447s $ betaT : num 0.0646 0.6078 0.401 0.7574 0.645 ... 447s $ betaTN : num 0.0646 0.6078 0.401 0.7574 0.645 ... 447s $ muN : num 0 0.5 0.5 0.5 0.5 0.5 1 0.5 0.5 0.5 ... 447s Ordering data along genome...done 447s Keeping only current chromosome for 'knownSegments'... 447s Chromosome: 2 447s Known segments for this chromosome: 447s [1] chromosome start end 447s <0 rows> (or 0-length row.names) 447s Keeping only current chromosome for 'knownSegments'...done 447s alphaTCN: 0.009 447s alphaDH: 0.001 447s Number of loci: 3662 447s Calculating DHs... 447s Number of SNPs: 3662 447s Number of heterozygous SNPs: 1451 (39.62%) 447s Normalized DHs: 447s num [1:3662] NA 0.216 0.198 0.515 0.29 ... 447s Calculating DHs...done 447s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 447s Produced 2 seeds from this stream for future usage 447s Identification of change points by total copy numbers... 447s Segmenting by CBS... 447s Chromosome: 2 447s Random seed temporarily set (seed=c(10407, -821273412, -52578226, 1415511586, 721384351, -665928286, 1316562960), kind="L'Ecuyer-CMRG") 447s Segmenting by CBS...done 447s List of 4 447s $ data :'data.frame': 3662 obs. of 4 variables: 447s ..$ chromosome: int [1:3662] 2 2 2 2 2 2 2 2 2 2 ... 447s ..$ x : num [1:3662] 554484 1031563 1087198 1145994 1176365 ... 447s ..$ y : num [1:3662] 1.88 1.64 1.77 1.63 1.59 ... 447s ..$ index : int [1:3662] 1 2 3 4 5 6 7 8 9 10 ... 447s $ output :'data.frame': 3 obs. of 6 variables: 447s ..$ sampleName: chr [1:3] NA NA NA 447s ..$ chromosome: int [1:3] 2 2 2 447s ..$ start : num [1:3] 5.54e+05 1.44e+08 1.85e+08 447s ..$ end : num [1:3] 1.44e+08 1.85e+08 2.47e+08 447s ..$ nbrOfLoci : int [1:3] 1880 671 1111 447s ..$ mean : num [1:3] 1.39 2.09 2.65 447s $ segRows:'data.frame': 3 obs. of 2 variables: 447s ..$ startRow: int [1:3] 1 1881 2552 447s ..$ endRow : int [1:3] 1880 2551 3662 447s $ params :List of 5 447s ..$ alpha : num 0.009 447s ..$ undo : num 0 447s ..$ joinSegments : logi TRUE 447s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 447s .. ..$ chromosome: int 2 447s .. ..$ start : num -Inf 447s .. ..$ end : num Inf 447s ..$ seed : int [1:7] 10407 -821273412 -52578226 1415511586 721384351 -665928286 1316562960 447s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 447s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.041 0 0.041 0 0 447s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 447s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 447s - attr(*, "randomSeed")= int [1:7] 10407 -821273412 -52578226 1415511586 721384351 -665928286 1316562960 447s Identification of change points by total copy numbers...done 447s Restructure TCN segmentation results... 447s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean 447s 1 2 554484 143663981 1880 1.3916 447s 2 2 143663981 185240536 671 2.0925 447s 3 2 185240536 246679946 1111 2.6545 447s Number of TCN segments: 3 447s Restructure TCN segmentation results...done 447s TCN-only segmentation... 447s Total CN segment #1 ([ 554484,1.43664e+08]) of 3... 447s Number of TCN loci in segment: 1880 447s Locus data for TCN segment: 447s 'data.frame': 1880 obs. of 8 variables: 447s $ chromosome: int 2 2 2 2 2 2 2 2 2 2 ... 447s $ x : num 554484 1031563 1087198 1145994 1176365 ... 447s $ CT : num 1.88 1.64 1.77 1.63 1.59 ... 447s $ betaT : num 0.0646 0.6078 0.401 0.7574 0.645 ... 447s $ betaTN : num 0.0646 0.6078 0.401 0.7574 0.645 ... 447s $ muN : num 0 0.5 0.5 0.5 0.5 0.5 1 0.5 0.5 0.5 ... 447s $ index : int 1 2 3 4 5 6 7 8 9 10 ... 447s $ rho : num NA 0.216 0.198 0.515 0.29 ... 447s Number of loci: 1880 447s Number of SNPs: 765 (40.69%) 447s Number of heterozygous SNPs: 765 (100.00%) 447s Total CN segment #1 ([ 554484,1.43664e+08]) of 3...done 447s Total CN segment #2 ([1.43664e+08,1.85241e+08]) of 3... 447s Number of TCN loci in segment: 671 447s Locus data for TCN segment: 447s 'data.frame': 671 obs. of 8 variables: 447s $ chromosome: int 2 2 2 2 2 2 2 2 2 2 ... 447s $ x : num 1.44e+08 1.44e+08 1.44e+08 1.44e+08 1.44e+08 ... 447s $ CT : num 2.26 2.1 2.1 1.89 1.97 ... 447s $ betaT : num 0.958 0.19 0.909 0.13 0.141 ... 447s $ betaTN : num 0.958 0.19 0.909 0.13 0.141 ... 447s $ muN : num 1 0 1 0 0 0 0 0.5 0 1 ... 447s $ index : int 1881 1882 1883 1884 1885 1886 1887 1888 1889 1890 ... 447s $ rho : num NA NA NA NA NA ... 447s Number of loci: 671 447s Number of SNPs: 272 (40.54%) 447s Number of heterozygous SNPs: 272 (100.00%) 447s Total CN segment #2 ([1.43664e+08,1.85241e+08]) of 3...done 447s Total CN segment #3 ([1.85241e+08,2.4668e+08]) of 3... 447s Number of TCN loci in segment: 1111 447s Locus data for TCN segment: 447s 'data.frame': 1111 obs. of 8 variables: 447s $ chromosome: int 2 2 2 2 2 2 2 2 2 2 ... 447s $ x : num 1.85e+08 1.86e+08 1.86e+08 1.86e+08 1.86e+08 ... 447s $ CT : num 2.44 3 2.32 2.76 2.48 ... 447s $ betaT : num 0.0727 0.6845 0.2327 0.8118 0.0746 ... 447s $ betaTN : num 0.0727 0.6845 0.2327 0.8118 0.0746 ... 447s $ muN : num 0 0.5 0.5 1 0 1 0 1 1 0.5 ... 447s $ index : int 2552 2553 2554 2555 2556 2557 2558 2559 2560 2561 ... 447s $ rho : num NA 0.369 0.535 NA NA ... 447s Number of loci: 1111 447s Number of SNPs: 414 (37.26%) 447s Number of heterozygous SNPs: 414 (100.00%) 447s Total CN segment #3 ([1.85241e+08,2.4668e+08]) of 3...done 447s TCN-only segmentation...done 447s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 447s 1 2 1 1 554484 143663981 1880 1.3916 765 447s 2 2 2 1 143663981 185240536 671 2.0925 272 447s 3 2 3 1 185240536 246679946 1111 2.6545 414 447s tcnNbrOfHets dhNbrOfLoci dhStart dhEnd dhMean 447s 1 765 765 554484 143663981 0.3979122 447s 2 272 272 143663981 185240536 0.2306116 447s 3 414 414 185240536 246679946 0.2798120 447s Calculating (C1,C2) per segment... 447s Calculating (C1,C2) per segment...done 447s Number of segments: 3 447s Segmenting paired tumor-normal signals using Paired PSCBS...done 447s Updating mean level using different estimator... 447s TCN estimator: mean 447s DH estimator: median 447s Updating mean level using different estimator...done 447s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 447s 1 2 1 1 554484 143663981 1880 1.391608 765 447s 2 2 2 1 143663981 185240536 671 2.092452 272 447s 3 2 3 1 185240536 246679946 1111 2.654512 414 447s tcnNbrOfHets dhNbrOfLoci dhStart dhEnd dhMean c1Mean c2Mean 447s 1 765 765 554484 143663981 0.4206323 0.4031263 0.9884817 447s 2 272 272 143663981 185240536 0.1762428 0.8618360 1.2306156 447s 3 414 414 185240536 246679946 0.2697420 0.9692395 1.6852728 447s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 447s 1 2 1 1 554484 143663981 1880 1.391608 765 447s 2 2 2 1 143663981 185240536 671 2.092452 272 447s 3 2 3 1 185240536 246679946 1111 2.654512 414 447s tcnNbrOfHets dhNbrOfLoci dhStart dhEnd dhMean c1Mean c2Mean 447s 1 765 765 554484 143663981 0.4206323 0.4031263 0.9884817 447s 2 272 272 143663981 185240536 0.1762428 0.8618360 1.2306156 447s 3 414 414 185240536 246679946 0.2697420 0.9692395 1.6852728 448s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 448s 1 2 1 1 554484 143663981 1880 1.391608 765 448s 2 2 2 1 143663981 185240536 671 2.092452 272 448s 3 2 3 1 185240536 246679946 1111 2.654512 414 448s tcnNbrOfHets dhNbrOfLoci dhStart dhEnd dhMean c1Mean c2Mean 448s 1 765 765 554484 143663981 0.4206323 0.4031263 0.9884817 448s 2 272 272 143663981 185240536 0.1762428 0.8618360 1.2306156 448s 3 414 414 185240536 246679946 0.2697420 0.9692395 1.6852728 448s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 448s 1 2 1 1 554484 143663981 1880 1.391608 765 448s 2 2 2 1 143663981 185240536 671 2.092452 272 448s 3 2 3 1 185240536 246679946 1111 2.654512 414 448s tcnNbrOfHets dhNbrOfLoci dhStart dhEnd dhMean c1Mean c2Mean 448s 1 765 765 554484 143663981 0.4206323 0.4031263 0.9884817 448s 2 272 272 143663981 185240536 0.1762428 0.8618360 1.2306156 448s 3 414 414 185240536 246679946 0.2697420 0.9692395 1.6852728 448s Chromosome #2 ('Chr02') of 2...done 448s Merging (independently) segmented chromosome... 448s List of 5 448s $ data :Classes ‘PairedPSCNData’ and 'data.frame': 7324 obs. of 7 variables: 448s ..$ chromosome: int [1:7324] 1 1 1 1 1 1 1 1 1 1 ... 448s ..$ x : num [1:7324] 554484 1031563 1087198 1145994 1176365 ... 448s ..$ CT : num [1:7324] 1.88 1.64 1.77 1.63 1.59 ... 448s ..$ betaT : num [1:7324] 0.0646 0.6078 0.401 0.7574 0.645 ... 448s ..$ betaTN : num [1:7324] 0.0646 0.6078 0.401 0.7574 0.645 ... 448s ..$ muN : num [1:7324] 0 0.5 0.5 0.5 0.5 0.5 1 0.5 0.5 0.5 ... 448s ..$ rho : num [1:7324] NA 0.216 0.198 0.515 0.29 ... 448s $ output :Classes ‘PairedPSCNSegments’ and 'data.frame': 7 obs. of 15 variables: 448s ..$ chromosome : int [1:7] 1 1 1 NA 2 2 2 448s ..$ tcnId : int [1:7] 1 2 3 NA 1 2 3 448s ..$ dhId : int [1:7] 1 1 1 NA 1 1 1 448s ..$ tcnStart : num [1:7] 5.54e+05 1.44e+08 1.85e+08 NA 5.54e+05 ... 448s ..$ tcnEnd : num [1:7] 1.44e+08 1.85e+08 2.47e+08 NA 1.44e+08 ... 448s ..$ tcnNbrOfLoci: int [1:7] 1880 671 1111 NA 1880 671 1111 448s ..$ tcnMean : num [1:7] 1.39 2.09 2.65 NA 1.39 ... 448s ..$ tcnNbrOfSNPs: int [1:7] 765 272 414 NA 765 272 414 448s ..$ tcnNbrOfHets: int [1:7] 765 272 414 NA 765 272 414 448s ..$ dhNbrOfLoci : int [1:7] 765 272 414 NA 765 272 414 448s ..$ dhStart : num [1:7] 5.54e+05 1.44e+08 1.85e+08 NA 5.54e+05 ... 448s ..$ dhEnd : num [1:7] 1.44e+08 1.85e+08 2.47e+08 NA 1.44e+08 ... 448s ..$ dhMean : num [1:7] 0.421 0.176 0.27 NA 0.421 ... 448s ..$ c1Mean : num [1:7] 0.403 0.862 0.969 NA 0.403 ... 448s ..$ c2Mean : num [1:7] 0.988 1.231 1.685 NA 0.988 ... 448s $ tcnSegRows:'data.frame': 7 obs. of 2 variables: 448s ..$ startRow: int [1:7] 1 1881 2552 NA 3663 5543 6214 448s ..$ endRow : int [1:7] 1880 2551 3662 NA 5542 6213 7324 448s $ dhSegRows :'data.frame': 7 obs. of 2 variables: 448s ..$ startRow: int [1:7] 2 1888 2553 NA 3664 5550 6215 448s ..$ endRow : int [1:7] 1876 2548 3659 NA 5538 6210 7321 448s $ params :List of 8 448s ..$ alphaTCN : num 0.009 448s ..$ alphaDH : num 0.001 448s ..$ flavor : chr "tcn" 448s ..$ tbn : logi FALSE 448s ..$ joinSegments : logi TRUE 448s ..$ knownSegments :'data.frame': 0 obs. of 3 variables: 448s .. ..$ chromosome: int(0) 448s .. ..$ start : int(0) 448s .. ..$ end : int(0) 448s ..$ seed : int [1:7] 10407 1066287653 -51199871 161854402 -1995183193 1503453565 -747102133 448s ..$ meanEstimators:List of 2 448s .. ..$ tcn: chr "mean" 448s .. ..$ dh : chr "median" 448s - attr(*, "class")= chr [1:3] "PairedPSCBS" "PSCBS" "AbstractCBS" 448s Merging (independently) segmented chromosome...done 448s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 448s 1 1 1 1 554484 143663981 1880 1.391608 765 448s 2 1 2 1 143663981 185240536 671 2.092452 272 448s 3 1 3 1 185240536 246679946 1111 2.654512 414 448s 4 NA NA NA NA NA NA NA NA 448s 5 2 1 1 554484 143663981 1880 1.391608 765 448s 6 2 2 1 143663981 185240536 671 2.092452 272 448s tcnNbrOfHets dhNbrOfLoci dhStart dhEnd dhMean c1Mean c2Mean 448s 1 765 765 554484 143663981 0.4206323 0.4031263 0.9884817 448s 2 272 272 143663981 185240536 0.1762428 0.8618360 1.2306156 448s 3 414 414 185240536 246679946 0.2697420 0.9692395 1.6852728 448s 4 NA NA NA NA NA NA NA 448s 5 765 765 554484 143663981 0.4206323 0.4031263 0.9884817 448s 6 272 272 143663981 185240536 0.1762428 0.8618360 1.2306156 448s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 448s 2 1 2 1 143663981 185240536 671 2.092452 272 448s 3 1 3 1 185240536 246679946 1111 2.654512 414 448s 4 NA NA NA NA NA NA NA NA 448s 5 2 1 1 554484 143663981 1880 1.391608 765 448s 6 2 2 1 143663981 185240536 671 2.092452 272 448s 7 2 3 1 185240536 246679946 1111 2.654512 414 448s tcnNbrOfHets dhNbrOfLoci dhStart dhEnd dhMean c1Mean c2Mean 448s 2 272 272 143663981 185240536 0.1762428 0.8618360 1.2306156 448s 3 414 414 185240536 246679946 0.2697420 0.9692395 1.6852728 448s 4 NA NA NA NA NA NA NA 448s 5 765 765 554484 143663981 0.4206323 0.4031263 0.9884817 448s 6 272 272 143663981 185240536 0.1762428 0.8618360 1.2306156 448s 7 414 414 185240536 246679946 0.2697420 0.9692395 1.6852728 448s Segmenting multiple chromosomes...done 448s Segmenting paired tumor-normal signals using Paired PSCBS...done 448s Segment using Paired PSCBS...done 448s Coercing to Non-Paired PSCBS results... 448s Coercing to Non-Paired PSCBS results...done 448s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 448s 1 1 1 1 554484 143663981 1880 1.391608 765 448s 2 1 2 1 143663981 185240536 671 2.092452 272 448s 3 1 3 1 185240536 246679946 1111 2.654512 414 448s 4 NA NA NA NA NA NA NA NA 448s 5 2 1 1 554484 143663981 1880 1.391608 765 448s 6 2 2 1 143663981 185240536 671 2.092452 272 448s tcnNbrOfHets dhNbrOfLoci dhStart dhEnd dhMean c1Mean c2Mean 448s 1 765 765 554484 143663981 0.4206323 0.4031263 0.9884817 448s 2 272 272 143663981 185240536 0.1762428 0.8618360 1.2306156 448s 3 414 414 185240536 246679946 0.2697420 0.9692395 1.6852728 448s 4 NA NA NA NA NA NA NA 448s 5 765 765 554484 143663981 0.4206323 0.4031263 0.9884817 448s 6 272 272 143663981 185240536 0.1762428 0.8618360 1.2306156 448s > print(fit) 448s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 448s 2 1 2 1 143663981 185240536 671 2.092452 272 448s 3 1 3 1 185240536 246679946 1111 2.654512 414 448s 4 NA NA NA NA NA NA NA NA 448s 5 2 1 1 554484 143663981 1880 1.391608 765 448s 6 2 2 1 143663981 185240536 671 2.092452 272 448s 7 2 3 1 185240536 246679946 1111 2.654512 414 448s tcnNbrOfHets dhNbrOfLoci dhStart dhEnd dhMean c1Mean c2Mean 448s 2 272 272 143663981 185240536 0.1762428 0.8618360 1.2306156 448s 3 414 414 185240536 246679946 0.2697420 0.9692395 1.6852728 448s 4 NA NA NA NA NA NA NA 448s 5 765 765 554484 143663981 0.4206323 0.4031263 0.9884817 448s 6 272 272 143663981 185240536 0.1762428 0.8618360 1.2306156 448s 7 414 414 185240536 246679946 0.2697420 0.9692395 1.6852728 448s chromosome tcnId dhId start end tcnNbrOfLoci tcnMean tcnNbrOfSNPs 448s 1 1 1 1 554484 143663981 1880 1.391608 765 448s 2 1 2 1 143663981 185240536 671 2.092452 272 448s 3 1 3 1 185240536 246679946 1111 2.654512 414 448s 4 NA NA NA NA NA NA NA NA 448s 5 2 1 1 554484 143663981 1880 1.391608 765 448s 6 2 2 1 143663981 185240536 671 2.092452 272 448s 7 2 3 1 185240536 246679946 1111 2.654512 414 448s tcnNbrOfHets dhNbrOfLoci dhMean c1Mean c2Mean 448s 1 765 765 0.4206323 0.4031263 0.9884817 448s 2 272 272 0.1762428 0.8618360 1.2306156 448s 3 414 414 0.2697420 0.9692395 1.6852728 448s 4 NA NA NA NA NA 448s 5 765 765 0.4206323 0.4031263 0.9884817 448s 6 272 272 0.1762428 0.8618360 1.2306156 448s 7 414 414 0.2697420 0.9692395 1.6852728 448s > 448s > 448s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 448s > # Bootstrap segment level estimates 448s > # (used by the AB caller, which, if skipped here, 448s > # will do it automatically) 448s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 448s > fit <- bootstrapTCNandDHByRegion(fit, B=100, verbose=-10) 448s Resample (TCN,DH) signals and re-estimate summaries for segment & changepoint... 448s Already done? 448s tcn_2.5% tcn_5% tcn_95% tcn_97.5% dh_2.5% dh_5% dh_95% dh_97.5% 448s FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE 448s c1_2.5% c1_5% c1_95% c1_97.5% c2_2.5% c2_5% c2_95% c2_97.5% 448s FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE 448s Bootstrapping (TCN,DH,C1,C2) segment mean levels... 448s Identifying heterozygous & homozygous SNPs and non-polymorphic loci... 448s Number of loci: 7324 448s Number of SNPs: 2902 448s Number of non-SNPs: 4422 448s Identifying heterozygous & homozygous SNPs and non-polymorphic loci...done 448s num [1:7, 1:100, 1:4] NA NA NA NA NA NA NA NA NA NA ... 448s - attr(*, "dimnames")=List of 3 448s ..$ : NULL 448s ..$ : NULL 448s ..$ : chr [1:4] "tcn" "dh" "c1" "c2" 448s Segment #1 (chr 1, tcnId=1, dhId=1) of 7... 448s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 448s 1 1 1 1 554484 143663981 1880 1.391608 765 448s tcnNbrOfHets dhNbrOfLoci dhStart dhEnd dhMean c1Mean c2Mean 448s 1 765 765 554484 143663981 0.4206323 0.4031263 0.9884817 448s Number of TCNs: 1880 448s Number of DHs: 765 448s int [1:1880] 1 2 3 4 5 6 7 8 9 10 ... 448s int [1:7324] 1 2 3 4 5 6 7 8 9 10 ... 448s int [1:1880] 1 2 3 4 5 6 7 8 9 10 ... 448s Identify loci used to bootstrap DH means... 448s Heterozygous SNPs to resample for DH: 448s int [1:765] 2 3 4 5 6 8 9 10 11 12 ... 448s Identify loci used to bootstrap DH means...done 448s Identify loci used to bootstrap TCN means... 448s SNPs: 448s int [1:765] 2 3 4 5 6 8 9 10 11 12 ... 448s Non-polymorphic loci: 448s int [1:1115] 1 7 15 28 30 32 34 35 36 37 ... 448s Heterozygous SNPs to resample for TCN: 448s int [1:765] 2 3 4 5 6 8 9 10 11 12 ... 448s Homozygous SNPs to resample for TCN: 448s int(0) 448s Non-polymorphic loci to resample for TCN: 448s int [1:1115] 1 7 15 28 30 32 34 35 36 37 ... 448s Heterozygous SNPs with non-DH to resample for TCN: 448s int(0) 448s Loci to resample for TCN: 448s int [1:1880] 1 2 3 4 5 6 7 8 9 10 ... 448s Identify loci used to bootstrap TCN means...done 448s Number of (#hets, #homs, #nonSNPs): (765,0,1115) 448s Bootstrapping while preserving (#hets, #homs, #nonSNPs)... 448s Number of bootstrap samples: 100 448s Bootstrapping while preserving (#hets, #homs, #nonSNPs)...done 448s Segment #1 (chr 1, tcnId=1, dhId=1) of 7...done 448s Segment #2 (chr 1, tcnId=2, dhId=1) of 7... 448s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 448s 2 1 2 1 143663981 185240536 671 2.092452 272 448s tcnNbrOfHets dhNbrOfLoci dhStart dhEnd dhMean c1Mean c2Mean 448s 2 272 272 143663981 185240536 0.1762428 0.861836 1.230616 448s Number of TCNs: 671 448s Number of DHs: 272 448s int [1:671] 1881 1882 1883 1884 1885 1886 1887 1888 1889 1890 ... 448s int [1:7324] 1 2 3 4 5 6 7 8 9 10 ... 448s int [1:671] 1881 1882 1883 1884 1885 1886 1887 1888 1889 1890 ... 448s Identify loci used to bootstrap DH means... 448s Heterozygous SNPs to resample for DH: 448s int [1:272] 1888 1893 1894 1895 1896 1897 1901 1903 1907 1908 ... 448s Identify loci used to bootstrap DH means...done 448s Identify loci used to bootstrap TCN means... 448s SNPs: 448s int [1:272] 1888 1893 1894 1895 1896 1897 1901 1903 1907 1908 ... 448s Non-polymorphic loci: 448s int [1:399] 1881 1882 1883 1884 1885 1886 1887 1889 1890 1891 ... 448s Heterozygous SNPs to resample for TCN: 448s int [1:272] 1888 1893 1894 1895 1896 1897 1901 1903 1907 1908 ... 448s Homozygous SNPs to resample for TCN: 448s int(0) 448s Non-polymorphic loci to resample for TCN: 448s int [1:399] 1881 1882 1883 1884 1885 1886 1887 1889 1890 1891 ... 448s Heterozygous SNPs with non-DH to resample for TCN: 448s int(0) 448s Loci to resample for TCN: 448s int [1:671] 1881 1882 1883 1884 1885 1886 1887 1888 1889 1890 ... 448s Identify loci used to bootstrap TCN means...done 448s Number of (#hets, #homs, #nonSNPs): (272,0,399) 448s Bootstrapping while preserving (#hets, #homs, #nonSNPs)... 448s Number of bootstrap samples: 100 448s Bootstrapping while preserving (#hets, #homs, #nonSNPs)...done 448s Segment #2 (chr 1, tcnId=2, dhId=1) of 7...done 448s Segment #3 (chr 1, tcnId=3, dhId=1) of 7... 448s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 448s 3 1 3 1 185240536 246679946 1111 2.654512 414 448s tcnNbrOfHets dhNbrOfLoci dhStart dhEnd dhMean c1Mean c2Mean 448s 3 414 414 185240536 246679946 0.269742 0.9692395 1.685273 448s Number of TCNs: 1111 448s Number of DHs: 414 448s int [1:1111] 2552 2553 2554 2555 2556 2557 2558 2559 2560 2561 ... 448s int [1:7324] 1 2 3 4 5 6 7 8 9 10 ... 448s int [1:1111] 2552 2553 2554 2555 2556 2557 2558 2559 2560 2561 ... 448s Identify loci used to bootstrap DH means... 448s Heterozygous SNPs to resample for DH: 448s int [1:414] 2553 2554 2561 2562 2563 2568 2569 2572 2573 2574 ... 448s Identify loci used to bootstrap DH means...done 448s Identify loci used to bootstrap TCN means... 448s SNPs: 448s int [1:414] 2553 2554 2561 2562 2563 2568 2569 2572 2573 2574 ... 448s Non-polymorphic loci: 448s int [1:697] 2552 2555 2556 2557 2558 2559 2560 2564 2565 2566 ... 448s Heterozygous SNPs to resample for TCN: 448s int [1:414] 2553 2554 2561 2562 2563 2568 2569 2572 2573 2574 ... 448s Homozygous SNPs to resample for TCN: 448s int(0) 448s Non-polymorphic loci to resample for TCN: 448s int [1:697] 2552 2555 2556 2557 2558 2559 2560 2564 2565 2566 ... 448s Heterozygous SNPs with non-DH to resample for TCN: 448s int(0) 448s Loci to resample for TCN: 448s int [1:1111] 2552 2553 2554 2555 2556 2557 2558 2559 2560 2561 ... 448s Identify loci used to bootstrap TCN means...done 448s Number of (#hets, #homs, #nonSNPs): (414,0,697) 448s Bootstrapping while preserving (#hets, #homs, #nonSNPs)... 448s Number of bootstrap samples: 100 448s Bootstrapping while preserving (#hets, #homs, #nonSNPs)...done 448s Segment #3 (chr 1, tcnId=3, dhId=1) of 7...done 448s Segment #5 (chr 2, tcnId=1, dhId=1) of 7... 448s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 448s 5 2 1 1 554484 143663981 1880 1.391608 765 448s tcnNbrOfHets dhNbrOfLoci dhStart dhEnd dhMean c1Mean c2Mean 448s 5 765 765 554484 143663981 0.4206323 0.4031263 0.9884817 448s Number of TCNs: 1880 448s Number of DHs: 765 448s int [1:1880] 3663 3664 3665 3666 3667 3668 3669 3670 3671 3672 ... 448s int [1:7324] 1 2 3 4 5 6 7 8 9 10 ... 448s int [1:1880] 3663 3664 3665 3666 3667 3668 3669 3670 3671 3672 ... 448s Identify loci used to bootstrap DH means... 448s Heterozygous SNPs to resample for DH: 448s int [1:765] 3664 3665 3666 3667 3668 3670 3671 3672 3673 3674 ... 448s Identify loci used to bootstrap DH means...done 448s Identify loci used to bootstrap TCN means... 448s SNPs: 448s int [1:765] 3664 3665 3666 3667 3668 3670 3671 3672 3673 3674 ... 448s Non-polymorphic loci: 448s int [1:1115] 3663 3669 3677 3690 3692 3694 3696 3697 3698 3699 ... 448s Heterozygous SNPs to resample for TCN: 448s int [1:765] 3664 3665 3666 3667 3668 3670 3671 3672 3673 3674 ... 448s Homozygous SNPs to resample for TCN: 448s int(0) 448s Non-polymorphic loci to resample for TCN: 448s int [1:1115] 3663 3669 3677 3690 3692 3694 3696 3697 3698 3699 ... 448s Heterozygous SNPs with non-DH to resample for TCN: 448s int(0) 448s Loci to resample for TCN: 448s int [1:1880] 3663 3664 3665 3666 3667 3668 3669 3670 3671 3672 ... 448s Identify loci used to bootstrap TCN means...done 448s Number of (#hets, #homs, #nonSNPs): (765,0,1115) 448s Bootstrapping while preserving (#hets, #homs, #nonSNPs)... 448s Number of bootstrap samples: 100 448s Bootstrapping while preserving (#hets, #homs, #nonSNPs)...done 448s Segment #5 (chr 2, tcnId=1, dhId=1) of 7...done 448s Segment #6 (chr 2, tcnId=2, dhId=1) of 7... 448s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 448s 6 2 2 1 143663981 185240536 671 2.092452 272 448s tcnNbrOfHets dhNbrOfLoci dhStart dhEnd dhMean c1Mean c2Mean 448s 6 272 272 143663981 185240536 0.1762428 0.861836 1.230616 448s Number of TCNs: 671 448s Number of DHs: 272 448s int [1:671] 5543 5544 5545 5546 5547 5548 5549 5550 5551 5552 ... 448s int [1:7324] 1 2 3 4 5 6 7 8 9 10 ... 448s int [1:671] 5543 5544 5545 5546 5547 5548 5549 5550 5551 5552 ... 448s Identify loci used to bootstrap DH means... 448s Heterozygous SNPs to resample for DH: 448s int [1:272] 5550 5555 5556 5557 5558 5559 5563 5565 5569 5570 ... 448s Identify loci used to bootstrap DH means...done 448s Identify loci used to bootstrap TCN means... 448s SNPs: 448s int [1:272] 5550 5555 5556 5557 5558 5559 5563 5565 5569 5570 ... 448s Non-polymorphic loci: 448s int [1:399] 5543 5544 5545 5546 5547 5548 5549 5551 5552 5553 ... 448s Heterozygous SNPs to resample for TCN: 448s int [1:272] 5550 5555 5556 5557 5558 5559 5563 5565 5569 5570 ... 448s Homozygous SNPs to resample for TCN: 448s int(0) 448s Non-polymorphic loci to resample for TCN: 448s int [1:399] 5543 5544 5545 5546 5547 5548 5549 5551 5552 5553 ... 448s Heterozygous SNPs with non-DH to resample for TCN: 448s int(0) 448s Loci to resample for TCN: 448s int [1:671] 5543 5544 5545 5546 5547 5548 5549 5550 5551 5552 ... 448s Identify loci used to bootstrap TCN means...done 448s Number of (#hets, #homs, #nonSNPs): (272,0,399) 448s Bootstrapping while preserving (#hets, #homs, #nonSNPs)... 448s Number of bootstrap samples: 100 448s Bootstrapping while preserving (#hets, #homs, #nonSNPs)...done 448s Segment #6 (chr 2, tcnId=2, dhId=1) of 7...done 448s Segment #7 (chr 2, tcnId=3, dhId=1) of 7... 448s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 448s 7 2 3 1 185240536 246679946 1111 2.654512 414 448s tcnNbrOfHets dhNbrOfLoci dhStart dhEnd dhMean c1Mean c2Mean 448s 7 414 414 185240536 246679946 0.269742 0.9692395 1.685273 448s Number of TCNs: 1111 448s Number of DHs: 414 448s int [1:1111] 6214 6215 6216 6217 6218 6219 6220 6221 6222 6223 ... 448s int [1:7324] 1 2 3 4 5 6 7 8 9 10 ... 448s int [1:1111] 6214 6215 6216 6217 6218 6219 6220 6221 6222 6223 ... 448s Identify loci used to bootstrap DH means... 448s Heterozygous SNPs to resample for DH: 448s int [1:414] 6215 6216 6223 6224 6225 6230 6231 6234 6235 6236 ... 448s Identify loci used to bootstrap DH means...done 448s Identify loci used to bootstrap TCN means... 448s SNPs: 448s int [1:414] 6215 6216 6223 6224 6225 6230 6231 6234 6235 6236 ... 448s Non-polymorphic loci: 448s int [1:697] 6214 6217 6218 6219 6220 6221 6222 6226 6227 6228 ... 448s Heterozygous SNPs to resample for TCN: 448s int [1:414] 6215 6216 6223 6224 6225 6230 6231 6234 6235 6236 ... 448s Homozygous SNPs to resample for TCN: 448s int(0) 448s Non-polymorphic loci to resample for TCN: 448s int [1:697] 6214 6217 6218 6219 6220 6221 6222 6226 6227 6228 ... 448s Heterozygous SNPs with non-DH to resample for TCN: 448s int(0) 448s Loci to resample for TCN: 448s int [1:1111] 6214 6215 6216 6217 6218 6219 6220 6221 6222 6223 ... 448s Identify loci used to bootstrap TCN means...done 448s Number of (#hets, #homs, #nonSNPs): (414,0,697) 448s Bootstrapping while preserving (#hets, #homs, #nonSNPs)... 448s Number of bootstrap samples: 100 448s Bootstrapping while preserving (#hets, #homs, #nonSNPs)...done 448s Segment #7 (chr 2, tcnId=3, dhId=1) of 7...done 448s Bootstrapped segment mean levels 448s num [1:7, 1:100, 1:4] 1.4 2.09 2.64 NA 1.39 ... 448s - attr(*, "dimnames")=List of 3 448s ..$ : NULL 448s ..$ : NULL 448s ..$ : chr [1:4] "tcn" "dh" "c1" "c2" 448s Calculating (C1,C2) mean levels from (TCN,DH) mean levels... 448s num [1:7, 1:100, 1:4] 1.4 2.09 2.64 NA 1.39 ... 448s - attr(*, "dimnames")=List of 3 448s ..$ : NULL 448s ..$ : NULL 448s ..$ : chr [1:4] "tcn" "dh" "c1" "c2" 448s Calculating (C1,C2) mean levels from (TCN,DH) mean levels...done 448s Calculating polar (alpha,radius,manhattan) for change points... 448s num [1:6, 1:100, 1:2] -0.448 -0.131 NA NA -0.477 ... 448s - attr(*, "dimnames")=List of 3 448s ..$ : NULL 448s ..$ : NULL 448s ..$ : chr [1:2] "c1" "c2" 448s Bootstrapped change points 448s num [1:6, 1:100, 1:5] -2.65 -1.87 NA NA -2.72 ... 448s - attr(*, "dimnames")=List of 3 448s ..$ : NULL 448s ..$ : NULL 448s ..$ : chr [1:5] "alpha" "radius" "manhattan" "d1" ... 448s Calculating polar (alpha,radius,manhattan) for change points...done 448s Bootstrapping (TCN,DH,C1,C2) segment mean levels...done 448s Summarizing bootstrapped segment (‘tcn’, ‘dh’, ‘c1’, ‘c2’) data... 448s num [1:7, 1:4, 1:4] NA NA NA NA NA NA NA NA NA NA ... 448s - attr(*, "dimnames")=List of 3 448s ..$ : NULL 448s ..$ : chr [1:4] "2.5%" "5%" "95%" "97.5%" 448s ..$ : chr [1:4] "tcn" "dh" "c1" "c2" 448s Field #1 ('tcn') of 4... 448s Segment #1 of 7... 448s Segment #1 of 7...done 448s Segment #2 of 7... 448s Segment #2 of 7...done 448s Segment #3 of 7... 448s Segment #3 of 7...done 448s Segment #4 of 7... 448s Segment #4 of 7...done 448s Segment #5 of 7... 448s Segment #5 of 7...done 448s Segment #6 of 7... 448s Segment #6 of 7...done 448s Segment #7 of 7... 448s Segment #7 of 7...done 448s Field #1 ('tcn') of 4...done 448s Field #2 ('dh') of 4... 448s Segment #1 of 7... 448s Segment #1 of 7...done 448s Segment #2 of 7... 448s Segment #2 of 7...done 448s Segment #3 of 7... 448s Segment #3 of 7...done 448s Segment #4 of 7... 448s Segment #4 of 7...done 448s Segment #5 of 7... 448s Segment #5 of 7...done 448s Segment #6 of 7... 448s Segment #6 of 7...done 448s Segment #7 of 7... 448s Segment #7 of 7...done 448s Field #2 ('dh') of 4...done 448s Field #3 ('c1') of 4... 448s Segment #1 of 7... 448s Segment #1 of 7...done 448s Segment #2 of 7... 448s Segment #2 of 7...done 448s Segment #3 of 7... 448s Segment #3 of 7...done 448s Segment #4 of 7... 448s Segment #4 of 7...done 448s Segment #5 of 7... 448s Segment #5 of 7...done 448s Segment #6 of 7... 448s Segment #6 of 7...done 448s Segment #7 of 7... 448s Segment #7 of 7...done 448s Field #3 ('c1') of 4...done 448s Field #4 ('c2') of 4... 448s Segment #1 of 7... 448s Segment #1 of 7...done 448s Segment #2 of 7... 448s Segment #2 of 7...done 448s Segment #3 of 7... 448s Segment #3 of 7...done 448s Segment #4 of 7... 448s Segment #4 of 7...done 448s Segment #5 of 7... 448s Segment #5 of 7...done 448s Segment #6 of 7... 448s Segment #6 of 7...done 448s Segment #7 of 7... 448s Segment #7 of 7...done 448s Field #4 ('c2') of 4...done 448s Bootstrap statistics 448s num [1:7, 1:4, 1:4] 1.38 2.07 2.63 NA 1.38 ... 448s - attr(*, "dimnames")=List of 3 448s ..$ : NULL 448s ..$ : chr [1:4] "2.5%" "5%" "95%" "97.5%" 448s ..$ : chr [1:4] "tcn" "dh" "c1" "c2" 448s Statistical sanity checks (iff B >= 100)... 448s Available summaries: 2.5%, 5%, 95%, 97.5% 448s Available quantiles: 0.025, 0.05, 0.95, 0.975 448s num [1:7, 1:4, 1:4] 1.38 2.07 2.63 NA 1.38 ... 448s - attr(*, "dimnames")=List of 3 448s ..$ : NULL 448s ..$ : chr [1:4] "2.5%" "5%" "95%" "97.5%" 448s ..$ : chr [1:4] "tcn" "dh" "c1" "c2" 448s Field #1 ('tcn') of 4... 448s Seg 1. mean=1.39161, range=[1.38025,1.40693], n=1880 448s Seg 2. mean=2.09245, range=[2.06856,2.1165], n=671 448s Seg 3. mean=2.65451, range=[2.62678,2.6834], n=1111 448s Seg 4. mean=NA, range=[NA,NA], n=NA 448s Seg 5. mean=1.39161, range=[1.37999,1.40474], n=1880 448s Seg 6. mean=2.09245, range=[2.06923,2.11747], n=671 448s Seg 7. mean=2.65451, range=[2.62867,2.68639], n=1111 448s Field #1 ('tcn') of 4...done 448s Field #2 ('dh') of 4... 448s Seg 1. mean=0.420632, range=[0.406983,0.437756], n=765 448s Seg 2. mean=0.176243, range=[0.141232,0.202975], n=272 448s Seg 3. mean=0.269742, range=[0.245337,0.292784], n=414 448s Seg 4. mean=NA, range=[NA,NA], n=NA 448s Seg 5. mean=0.420632, range=[0.406204,0.436189], n=765 448s Seg 6. mean=0.176243, range=[0.13696,0.212132], n=272 448s Seg 7. mean=0.269742, range=[0.230034,0.296763], n=414 448s Field #2 ('dh') of 4...done 448s Field #3 ('c1') of 4... 448s Seg 1. mean=0.403126, range=[0.391189,0.413437], n=765 448s Seg 2. mean=0.861836, range=[0.833296,0.900874], n=272 448s Seg 3. mean=0.969239, range=[0.937437,1.00659], n=414 448s Seg 4. mean=NA, range=[NA,NA], n=NA 448s Seg 5. mean=0.403126, range=[0.392112,0.414529], n=765 448s Seg 6. mean=0.861836, range=[0.823193,0.907577], n=272 448s Seg 7. mean=0.969239, range=[0.931951,1.01968], n=414 448s Field #3 ('c1') of 4...done 448s Field #4 ('c2') of 4... 448s Seg 1. mean=0.988482, range=[0.974501,1.00244], n=765 448s Seg 2. mean=1.23062, range=[1.18964,1.26157], n=272 448s Seg 3. mean=1.68527, range=[1.6481,1.72497], n=414 448s Seg 4. mean=NA, range=[NA,NA], n=NA 448s Seg 5. mean=0.988482, range=[0.9761,1.00076], n=765 448s Seg 6. mean=1.23062, range=[1.18936,1.26647], n=272 448s Seg 7. mean=1.68527, range=[1.63171,1.72526], n=414 448s Field #4 ('c2') of 4...done 448s Statistical sanity checks (iff B >= 100)...done 448s Summarizing bootstrapped segment (‘tcn’, ‘dh’, ‘c1’, ‘c2’) data...done 448s Summarizing bootstrapped changepoint (‘alpha’, ‘radius’, ‘manhattan’, ‘d1’, ‘d2’) data... 448s num [1:6, 1:4, 1:5] NA NA NA NA NA NA NA NA NA NA ... 448s - attr(*, "dimnames")=List of 3 448s ..$ : NULL 448s ..$ : chr [1:4] "2.5%" "5%" "95%" "97.5%" 448s ..$ : chr [1:5] "alpha" "radius" "manhattan" "d1" ... 448s Field #1 ('alpha') of 5... 448s Changepoint #1 of 6... 448s Changepoint #1 of 6...done 448s Changepoint #2 of 6... 448s Changepoint #2 of 6...done 448s Changepoint #3 of 6... 448s Changepoint #3 of 6...done 448s Changepoint #4 of 6... 448s Changepoint #4 of 6...done 448s Changepoint #5 of 6... 448s Changepoint #5 of 6...done 448s Changepoint #6 of 6... 448s Changepoint #6 of 6...done 448s Field #1 ('alpha') of 5...done 448s Field #2 ('radius') of 5... 448s Changepoint #1 of 6... 448s Changepoint #1 of 6...done 448s Changepoint #2 of 6... 448s Changepoint #2 of 6...done 448s Changepoint #3 of 6... 448s Changepoint #3 of 6...done 448s Changepoint #4 of 6... 448s Changepoint #4 of 6...done 448s Changepoint #5 of 6... 448s Changepoint #5 of 6...done 448s Changepoint #6 of 6... 448s Changepoint #6 of 6...done 448s Field #2 ('radius') of 5...done 448s Field #3 ('manhattan') of 5... 448s Changepoint #1 of 6... 448s Changepoint #1 of 6...done 448s Changepoint #2 of 6... 448s Changepoint #2 of 6...done 448s Changepoint #3 of 6... 448s Changepoint #3 of 6...done 448s Changepoint #4 of 6... 448s Changepoint #4 of 6...done 448s Changepoint #5 of 6... 448s Changepoint #5 of 6...done 448s Changepoint #6 of 6... 448s Changepoint #6 of 6...done 448s Field #3 ('manhattan') of 5...done 448s Field #4 ('d1') of 5... 448s Changepoint #1 of 6... 448s Changepoint #1 of 6...done 448s Changepoint #2 of 6... 448s Changepoint #2 of 6...done 448s Changepoint #3 of 6... 448s Changepoint #3 of 6...done 448s Changepoint #4 of 6... 448s Changepoint #4 of 6...done 448s Changepoint #5 of 6... 448s Changepoint #5 of 6...done 448s Changepoint #6 of 6... 448s Changepoint #6 of 6...done 448s Field #4 ('d1') of 5...done 448s Field #5 ('d2') of 5... 448s Changepoint #1 of 6... 448s Changepoint #1 of 6...done 448s Changepoint #2 of 6... 448s Changepoint #2 of 6...done 448s Changepoint #3 of 6... 448s Changepoint #3 of 6...done 448s Changepoint #4 of 6... 448s Changepoint #4 of 6...done 448s Changepoint #5 of 6... 448s Changepoint #5 of 6...done 448s Changepoint #6 of 6... 448s Changepoint #6 of 6...done 448s Field #5 ('d2') of 5...done 448s Bootstrap statistics 448s num [1:6, 1:4, 1:5] -2.76 -1.91 NA NA -2.76 ... 448s - attr(*, "dimnames")=List of 3 448s ..$ : NULL 448s ..$ : chr [1:4] "2.5%" "5%" "95%" "97.5%" 448s ..$ : chr [1:5] "alpha" "radius" "manhattan" "d1" ... 448s Summarizing bootstrapped changepoint (‘alpha’, ‘radius’, ‘manhattan’, ‘d1’, ‘d2’) data...done 448s Resample (TCN,DH) signals and re-estimate summaries for segment & changepoint...done 448s Estimating DH threshold for calling allelic imbalances... 448s flavor: qq(DH) 448s scale: 1 448s Estimating DH threshold for AB caller... 448s quantile #1: 0.05 448s Symmetric quantile #2: 0.9 448s Number of segments: 6 448s Weighted 5% quantile of DH: 0.199618 448s Number of segments with small DH: 2 448s Number of data points: 1342 448s Number of finite data points: 544 448s Estimate of (1-0.9):th and 50% quantiles: (0.0289919,0.176243) 448s Estimate of 0.9:th "symmetric" quantile: 0.323494 448s Estimating DH threshold for AB caller...done 448s Estimated delta: 0.323 448s Estimating DH threshold for calling allelic imbalances...done 448s Calling segments of allelic balance from one-sided DH bootstrap confidence intervals... 448s delta (offset adjusting for bias in DH): 0.323493772175137 448s alpha (CI quantile; significance level): 0.05 448s Calling segments... 448s Number of segments called allelic balance (AB): 4 (57.14%) of 7 448s Calling segments...done 448s Calling segments of allelic balance from one-sided DH bootstrap confidence intervals...done 448s Estimating DH threshold for calling LOH... 448s > print(fit) 448s chromosome tcnId dhId start end tcnNbrOfLoci tcnMean tcnNbrOfSNPs 448s 1 1 1 1 554484 143663981 1880 1.391608 765 448s 2 1 2 1 143663981 185240536 671 2.092452 272 448s 3 1 3 1 185240536 246679946 1111 2.654512 414 448s 4 NA NA NA NA NA NA NA NA 448s 5 2 1 1 554484 143663981 1880 1.391608 765 448s 6 2 2 1 143663981 185240536 671 2.092452 272 448s 7 2 3 1 185240536 246679946 1111 2.654512 414 448s tcnNbrOfHets dhNbrOfLoci dhMean c1Mean c2Mean 448s 1 765 765 0.4206323 0.4031263 0.9884817 448s 2 272 272 0.1762428 0.8618360 1.2306156 448s 3 414 414 0.2697420 0.9692395 1.6852728 448s 4 NA NA NA NA NA 448s 5 765 765 0.4206323 0.4031263 0.9884817 448s 6 272 272 0.1762428 0.8618360 1.2306156 448s 7 414 414 0.2697420 0.9692395 1.6852728 448s > 448s > 448s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 448s > # Calling segments in allelic balance (AB) 448s > # NOTE: Ideally, this should be done on whole-genome data 448s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 448s > # Explicitly estimate the threshold in DH for calling AB 448s > # (which be done by default by the caller, if skipped here) 448s > deltaAB <- estimateDeltaAB(fit, flavor="qq(DH)", verbose=-10) 448s > print(deltaAB) 448s [1] 0.3234938 448s > 448s > fit <- callAB(fit, delta=deltaAB, verbose=-10) 448s > print(fit) 448s chromosome tcnId dhId start end tcnNbrOfLoci tcnMean tcnNbrOfSNPs 448s 1 1 1 1 554484 143663981 1880 1.391608 765 448s 2 1 2 1 143663981 185240536 671 2.092452 272 448s 3 1 3 1 185240536 246679946 1111 2.654512 414 448s 4 NA NA NA NA NA NA NA NA 448s 5 2 1 1 554484 143663981 1880 1.391608 765 448s 6 2 2 1 143663981 185240536 671 2.092452 272 448s 7 2 3 1 185240536 246679946 1111 2.654512 414 448s tcnNbrOfHets dhNbrOfLoci dhMean c1Mean c2Mean abCall 448s 1 765 765 0.4206323 0.4031263 0.9884817 FALSE 448s 2 272 272 0.1762428 0.8618360 1.2306156 TRUE 448s 3 414 414 0.2697420 0.9692395 1.6852728 TRUE 448s 4 NA NA NA NA NA NA 448s 5 765 765 0.4206323 0.4031263 0.9884817 FALSE 448s 6 272 272 0.1762428 0.8618360 1.2306156 TRUE 448s 7 414 414 0.2697420 0.9692395 1.6852728 TRUE 448s > 448s > 448s > # Even if not explicitly specified, the estimated 448s > # threshold parameter is returned by the caller 448s > stopifnot(fit$params$deltaAB == deltaAB) 448s > 448s > 448s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 448s > # Calling segments in loss-of-heterozygosity (LOH) 448s > # NOTE: Ideally, this should be done on whole-genome data 448s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 448s > # Explicitly estimate the threshold in C1 for calling LOH 448s > # (which be done by default by the caller, if skipped here) 448s > deltaLOH <- estimateDeltaLOH(fit, flavor="minC1|nonAB", verbose=-10) 448s flavor: minC1|nonAB 448s Estimating DH threshold for calling LOH as the midpoint between guessed C1=0 and C1=1... 448s Argument 'midpoint': 0.5 448s Number of segments: 6 448s Number of segments in allelic balance: 4 (66.7%) of 6 448s Number of segments not in allelic balance: 2 (33.3%) of 6 448s Number of segments in allelic balance and TCN <= 3.00: 4 (66.7%) of 6 448s C: 2.09, 2.65, 2.09, 2.65 448s Corrected C1 (=C/2): 1.05, 1.33, 1.05, 1.33 448s Number of DHs: 272, 414, 272, 414 448s Weights: 0.198, 0.302, 0.198, 0.302 448s Weighted median of (corrected) C1 in allelic balance: 1.274 448s Smallest C1 among segments not in allelic balance: 0.403 448s There are 2 segments with in total 765 heterozygous SNPs with this level. 448s There are 2 segments with in total 765 heterozygous SNPs with this level. 448s Midpoint between the two: 0.839 448s Estimating DH threshold for calling LOH as the midpoint between guessed C1=0 and C1=1...done 448s delta: 0.839 448s Estimating DH threshold for calling LOH...done 448s > print(deltaLOH) 448s [1] 0.838563 448s > 448s > fit <- callLOH(fit, delta=deltaLOH, verbose=-10) 448s Calling segments of allelic balance from one-sided DH bootstrap confidence intervals... 448s delta (offset adjusting for bias in C1): 0.838562992888546 448s alpha (CI quantile; significance level): 0.05 448s Calling segments... 448s Number of segments called low C1 (LowC1, "LOH_C1"): 3 (42.86%) of 7 448s Calling segments...done 448s Calling segments of allelic balance from one-sided DH bootstrap confidence intervals...done 448s > print(fit) 448s chromosome tcnId dhId start end tcnNbrOfLoci tcnMean tcnNbrOfSNPs 448s 1 1 1 1 554484 143663981 1880 1.391608 765 448s 2 1 2 1 143663981 185240536 671 2.092452 272 448s 3 1 3 1 185240536 246679946 1111 2.654512 414 448s 4 NA NA NA NA NA NA NA NA 448s 5 2 1 1 554484 143663981 1880 1.391608 765 448s 6 2 2 1 143663981 185240536 671 2.092452 272 448s 7 2 3 1 185240536 246679946 1111 2.654512 414 448s tcnNbrOfHets dhNbrOfLoci dhMean c1Mean c2Mean abCall lohCall 448s 1 765 765 0.4206323 0.4031263 0.9884817 FALSE TRUE 448s 2 272 272 0.1762428 0.8618360 1.2306156 TRUE NA 448s 3 414 414 0.2697420 0.9692395 1.6852728 TRUE FALSE 448s 4 NA NA NA NA NA NA NA 448s 5 765 765 0.4206323 0.4031263 0.9884817 FALSE TRUE 448s 6 272 272 0.1762428 0.8618360 1.2306156 TRUE FALSE 448s 7 414 414 0.2697420 0.9692395 1.6852728 TRUE FALSE 448s > plotTracks(fit) 448s > 448s > # Even if not explicitly specified, the estimated 448s > # threshold parameter is returned by the caller 448s > stopifnot(fit$params$deltaLOH == deltaLOH) 448s > 448s Start: segmentByPairedPSCBS,DH.R 448s 448s R version 4.5.2 (2025-10-31) -- "[Not] Part in a Rumble" 448s Copyright (C) 2025 The R Foundation for Statistical Computing 448s Platform: x86_64-pc-linux-gnu 448s 448s R is free software and comes with ABSOLUTELY NO WARRANTY. 448s You are welcome to redistribute it under certain conditions. 448s Type 'license()' or 'licence()' for distribution details. 448s 448s R is a collaborative project with many contributors. 448s Type 'contributors()' for more information and 448s 'citation()' on how to cite R or R packages in publications. 448s 448s Type 'demo()' for some demos, 'help()' for on-line help, or 448s 'help.start()' for an HTML browser interface to help. 448s Type 'q()' to quit R. 448s 448s > library("PSCBS") 448s > 448s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 448s > # Load SNP microarray data 448s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 448s > data <- PSCBS::exampleData("paired.chr01") 448s PSCBS v0.68.0 (2025-04-18 19:40:02 UTC) successfully loaded. See ?PSCBS for help. 448s > str(data) 448s 'data.frame': 73346 obs. of 6 variables: 448s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 448s $ x : int 1145994 2224111 2319424 2543484 2926730 2941694 3084986 3155127 3292731 3695086 ... 448s $ CT : num 1.625 1.071 1.406 1.18 0.856 ... 448s $ betaT : num 0.757 0.771 0.834 0.778 0.229 ... 448s $ CN : num 2.36 2.13 2.59 1.93 1.71 ... 448s $ betaN : num 0.827 0.875 0.887 0.884 0.103 ... 448s > 448s > # Drop single-locus outliers 448s > dataS <- dropSegmentationOutliers(data) 448s > 448s > # Run light-weight tests 448s > # Use only every 5th data point 448s > dataS <- dataS[seq(from=1, to=nrow(data), by=5),] 448s > # Number of segments (for assertion) 448s > nSegs <- 3L 448s > # Number of bootstrap samples (see below) 448s > B <- 100L 448s > 448s > str(dataS) 448s 'data.frame': 14670 obs. of 6 variables: 448s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 448s $ x : int 1145994 2941694 3710825 4240737 4276892 4464544 4714611 5095111 5034491 5158416 ... 448s $ CT : num 1.63 1.4 1.41 1.17 1.16 ... 448s $ betaT : num 0.7574 0.169 0.2357 0.2604 0.0576 ... 448s $ CN : num 2.36 2.13 2.26 2.01 2.32 ... 448s $ betaN : num 0.8274 0.5072 0.1671 0.1609 0.0421 ... 448s > R.oo::attachLocally(dataS) 448s > 448s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 448s > # Calculate DH 448s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 448s > muN <- aroma.light::callNaiveGenotypes(betaN, censorAt=c(0,1)) 448s > # SNPs are identifies as those loci that have non-missing 'betaT' & 'muN' 448s > isSnp <- (!is.na(betaT) & !is.na(muN)) 448s > isHet <- isSnp & (muN == 1/2) 448s > rho <- rep(NA_real_, length=length(muN)) 448s > rho[isHet] <- 2*abs(betaT[isHet]-1/2) 448s > 448s > 448s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 448s > # Paired PSCBS segmentation using TCN and DH only 448s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 448s > fit <- segmentByPairedPSCBS(CT, rho=rho, 448s + chromosome=chromosome, x=x, 448s + seed=0xBEEF, verbose=-10) 448s Segmenting paired tumor-normal signals using Paired PSCBS... 448s Setup up data... 448s 'data.frame': 14670 obs. of 4 variables: 448s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 448s $ x : num 1145994 2941694 3710825 4240737 4276892 ... 448s $ CT : num 1.63 1.4 1.41 1.17 1.16 ... 448s $ rho : num NA 0.662 NA NA NA ... 448s Setup up data...done 448s Dropping loci for which TCNs are missing... 448s Number of loci dropped: 12 448s Dropping loci for which TCNs are missing...done 448s Ordering data along genome... 448s 'data.frame': 14658 obs. of 4 variables: 448s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 448s $ x : num 554484 730720 782343 878522 916294 ... 448s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 448s $ rho : num NA NA NA NA NA ... 448s Ordering data along genome...done 448s Keeping only current chromosome for 'knownSegments'... 448s Chromosome: 1 448s Known segments for this chromosome: 448s [1] chromosome start end 448s <0 rows> (or 0-length row.names) 448s Keeping only current chromosome for 'knownSegments'...done 448s alphaTCN: 0.009 448s alphaDH: 0.001 448s Number of loci: 14658 448s Random seed temporarily set (seed=c(48879), kind="L'Ecuyer-CMRG") 448s Produced 2 seeds from this stream for future usage 448s Identification of change points by total copy numbers... 448s Segmenting by CBS... 448s Chromosome: 1 448s Random seed temporarily set (seed=c(10407, 1066287653, -51199871, 161854402, -1995183193, 1503453565, -747102133), kind="L'Ecuyer-CMRG") 448s Segmenting by CBS...done 448s List of 4 448s $ data :'data.frame': 14658 obs. of 4 variables: 448s ..$ chromosome: int [1:14658] 1 1 1 1 1 1 1 1 1 1 ... 448s ..$ x : num [1:14658] 554484 730720 782343 878522 916294 ... 448s ..$ y : num [1:14658] 1.88 1.8 1.59 1.64 1.53 ... 448s ..$ index : int [1:14658] 1 2 3 4 5 6 7 8 9 10 ... 448s $ output :'data.frame': 3 obs. of 6 variables: 448s ..$ sampleName: chr [1:3] NA NA NA 448s ..$ chromosome: int [1:3] 1 1 1 448s ..$ start : num [1:3] 5.54e+05 1.44e+08 1.85e+08 448s ..$ end : num [1:3] 1.44e+08 1.85e+08 2.47e+08 448s ..$ nbrOfLoci : int [1:3] 7599 2668 4391 448s ..$ mean : num [1:3] 1.39 2.07 2.63 448s $ segRows:'data.frame': 3 obs. of 2 variables: 448s ..$ startRow: int [1:3] 1 7600 10268 448s ..$ endRow : int [1:3] 7599 10267 14658 448s $ params :List of 5 448s ..$ alpha : num 0.009 448s ..$ undo : num 0 448s ..$ joinSegments : logi TRUE 448s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 448s .. ..$ chromosome: int 1 448s .. ..$ start : num -Inf 448s .. ..$ end : num Inf 448s ..$ seed : int [1:7] 10407 1066287653 -51199871 161854402 -1995183193 1503453565 -747102133 448s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 448s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.217 0 0.217 0 0 448s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 448s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 448s - attr(*, "randomSeed")= int [1:7] 10407 1066287653 -51199871 161854402 -1995183193 1503453565 -747102133 448s Identification of change points by total copy numbers...done 448s Restructure TCN segmentation results... 448s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean 448s 1 1 554484 143926517 7599 1.3859 448s 2 1 143926517 185449813 2668 2.0704 448s 3 1 185449813 247137334 4391 2.6341 448s Number of TCN segments: 3 448s Restructure TCN segmentation results...done 448s Total CN segment #1 ([ 554484,1.43927e+08]) of 3... 448s Number of TCN loci in segment: 7599 448s Locus data for TCN segment: 448s 'data.frame': 7599 obs. of 5 variables: 448s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 448s $ x : num 554484 730720 782343 878522 916294 ... 448s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 448s $ rho : num NA NA NA NA NA ... 448s $ index : int 1 2 3 4 5 6 7 8 9 10 ... 448s Number of loci: 7599 448s Number of SNPs: 2111 (27.78%) 448s Number of heterozygous SNPs: 2111 (100.00%) 448s Chromosome: 1 448s Segmenting DH signals... 448s Segmenting by CBS... 448s Chromosome: 1 449s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 449s Segmenting by CBS...done 449s List of 4 449s $ data :'data.frame': 7599 obs. of 4 variables: 449s ..$ chromosome: int [1:7599] 1 1 1 1 1 1 1 1 1 1 ... 449s ..$ x : num [1:7599] 554484 730720 782343 878522 916294 ... 449s ..$ y : num [1:7599] NA NA NA NA NA ... 449s ..$ index : int [1:7599] 1 2 3 4 5 6 7 8 9 10 ... 449s $ output :'data.frame': 1 obs. of 6 variables: 449s ..$ sampleName: chr NA 449s ..$ chromosome: int 1 449s ..$ start : num 554484 449s ..$ end : num 1.44e+08 449s ..$ nbrOfLoci : int 2111 449s ..$ mean : num 0.524 449s $ segRows:'data.frame': 1 obs. of 2 variables: 449s ..$ startRow: int 10 449s ..$ endRow : int 7594 449s $ params :List of 5 449s ..$ alpha : num 0.001 449s ..$ undo : num 0 449s ..$ joinSegments : logi TRUE 449s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 449s .. ..$ chromosome: int 1 449s .. ..$ start : num 554484 449s .. ..$ end : num 1.44e+08 449s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 449s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 449s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.017 0 0.017 0 0 449s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 449s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 449s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 449s DH segmentation (locally-indexed) rows: 449s startRow endRow 449s 1 10 7594 449s int [1:7599] 1 2 3 4 5 6 7 8 9 10 ... 449s DH segmentation rows: 449s startRow endRow 449s 1 10 7594 449s Segmenting DH signals...done 449s DH segmentation table: 449s dhStart dhEnd dhNbrOfLoci dhMean 449s 1 554484 143926517 2111 0.5237 449s startRow endRow 449s 1 10 7594 449s Rows: 449s [1] 1 449s TCN segmentation rows: 449s startRow endRow 449s 1 1 7599 449s TCN and DH segmentation rows: 449s startRow endRow 449s 1 1 7599 449s startRow endRow 449s 1 10 7594 449s NULL 449s TCN segmentation (expanded) rows: 449s startRow endRow 449s 1 1 7599 449s TCN and DH segmentation rows: 449s startRow endRow 449s 1 1 7599 449s 2 7600 10267 449s 3 10268 14658 449s startRow endRow 449s 1 10 7594 449s startRow endRow 449s 1 1 7599 449s Total CN segmentation table (expanded): 449s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 449s 1 1 554484 143926517 7599 1.3859 2111 2111 449s (TCN,DH) segmentation for one total CN segment: 449s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 449s 1 1 1 1 554484 143926517 7599 1.3859 2111 449s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 449s 1 2111 554484 143926517 2111 0.5237 449s Total CN segment #1 ([ 554484,1.43927e+08]) of 3...done 449s Total CN segment #2 ([1.43927e+08,1.8545e+08]) of 3... 449s Number of TCN loci in segment: 2668 449s Locus data for TCN segment: 449s 'data.frame': 2668 obs. of 5 variables: 449s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 449s $ x : num 1.44e+08 1.44e+08 1.44e+08 1.44e+08 1.44e+08 ... 449s $ CT : num 2.1 2.1 2.09 1.8 2.34 ... 449s $ rho : num NA NA NA NA NA NA NA NA NA NA ... 449s $ index : int 7600 7601 7602 7603 7604 7605 7606 7607 7608 7609 ... 449s Number of loci: 2668 449s Number of SNPs: 774 (29.01%) 449s Number of heterozygous SNPs: 774 (100.00%) 449s Chromosome: 1 449s Segmenting DH signals... 449s Segmenting by CBS... 449s Chromosome: 1 449s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 449s Segmenting by CBS...done 449s List of 4 449s $ data :'data.frame': 2668 obs. of 4 variables: 449s ..$ chromosome: int [1:2668] 1 1 1 1 1 1 1 1 1 1 ... 449s ..$ x : num [1:2668] 1.44e+08 1.44e+08 1.44e+08 1.44e+08 1.44e+08 ... 449s ..$ y : num [1:2668] NA NA NA NA NA NA NA NA NA NA ... 449s ..$ index : int [1:2668] 1 2 3 4 5 6 7 8 9 10 ... 449s $ output :'data.frame': 1 obs. of 6 variables: 449s ..$ sampleName: chr NA 449s ..$ chromosome: int 1 449s ..$ start : num 1.44e+08 449s ..$ end : num 1.85e+08 449s ..$ nbrOfLoci : int 774 449s ..$ mean : num 0.154 449s $ segRows:'data.frame': 1 obs. of 2 variables: 449s ..$ startRow: int 15 449s ..$ endRow : int 2664 449s $ params :List of 5 449s ..$ alpha : num 0.001 449s ..$ undo : num 0 449s ..$ joinSegments : logi TRUE 449s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 449s .. ..$ chromosome: int 1 449s .. ..$ start : num 1.44e+08 449s .. ..$ end : num 1.85e+08 449s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 449s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 449s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.006 0 0.006 0 0 449s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 449s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 449s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 449s DH segmentation (locally-indexed) rows: 449s startRow endRow 449s 1 15 2664 449s int [1:2668] 7600 7601 7602 7603 7604 7605 7606 7607 7608 7609 ... 449s DH segmentation rows: 449s startRow endRow 449s 1 7614 10263 449s Segmenting DH signals...done 449s DH segmentation table: 449s dhStart dhEnd dhNbrOfLoci dhMean 449s 1 143926517 185449813 774 0.1542 449s startRow endRow 449s 1 7614 10263 449s Rows: 449s [1] 2 449s TCN segmentation rows: 449s startRow endRow 449s 2 7600 10267 449s TCN and DH segmentation rows: 449s startRow endRow 449s 2 7600 10267 449s startRow endRow 449s 1 7614 10263 449s startRow endRow 449s 1 1 7599 449s TCN segmentation (expanded) rows: 449s startRow endRow 449s 1 1 7599 449s 2 7600 10267 449s TCN and DH segmentation rows: 449s startRow endRow 449s 1 1 7599 449s 2 7600 10267 449s 3 10268 14658 449s startRow endRow 449s 1 10 7594 449s 2 7614 10263 449s startRow endRow 449s 1 1 7599 449s 2 7600 10267 449s Total CN segmentation table (expanded): 449s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 449s 2 1 143926517 185449813 2668 2.0704 774 774 449s (TCN,DH) segmentation for one total CN segment: 449s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 449s 2 2 1 1 143926517 185449813 2668 2.0704 774 449s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 449s 2 774 143926517 185449813 774 0.1542 449s Total CN segment #2 ([1.43927e+08,1.8545e+08]) of 3...done 449s Total CN segment #3 ([1.8545e+08,2.47137e+08]) of 3... 449s Number of TCN loci in segment: 4391 449s Locus data for TCN segment: 449s 'data.frame': 4391 obs. of 5 variables: 449s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 449s $ x : num 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 449s $ CT : num 2.93 2.15 2.82 2.93 2.46 ... 449s $ rho : num NA 0.0308 NA 0.2533 NA ... 449s $ index : int 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 449s Number of loci: 4391 449s Number of SNPs: 1311 (29.86%) 449s Number of heterozygous SNPs: 1311 (100.00%) 449s Chromosome: 1 449s Segmenting DH signals... 449s Segmenting by CBS... 449s Chromosome: 1 449s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 449s Segmenting by CBS...done 449s List of 4 449s $ data :'data.frame': 4391 obs. of 4 variables: 449s ..$ chromosome: int [1:4391] 1 1 1 1 1 1 1 1 1 1 ... 449s ..$ x : num [1:4391] 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 449s ..$ y : num [1:4391] NA 0.0308 NA 0.2533 NA ... 449s ..$ index : int [1:4391] 1 2 3 4 5 6 7 8 9 10 ... 449s $ output :'data.frame': 1 obs. of 6 variables: 449s ..$ sampleName: chr NA 449s ..$ chromosome: int 1 449s ..$ start : num 1.85e+08 449s ..$ end : num 2.47e+08 449s ..$ nbrOfLoci : int 1311 449s ..$ mean : num 0.251 449s $ segRows:'data.frame': 1 obs. of 2 variables: 449s ..$ startRow: int 2 449s ..$ endRow : int 4388 449s $ params :List of 5 449s ..$ alpha : num 0.001 449s ..$ undo : num 0 449s ..$ joinSegments : logi TRUE 449s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 449s .. ..$ chromosome: int 1 449s .. ..$ start : num 1.85e+08 449s .. ..$ end : num 2.47e+08 449s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 449s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 449s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.016 0 0.016 0 0 449s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 449s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 449s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 449s DH segmentation (locally-indexed) rows: 449s startRow endRow 449s 1 2 4388 449s int [1:4391] 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 449s DH segmentation rows: 449s startRow endRow 449s 1 10269 14655 449s Segmenting DH signals...done 449s DH segmentation table: 449s dhStart dhEnd dhNbrOfLoci dhMean 449s 1 185449813 247137334 1311 0.2512 449s startRow endRow 449s 1 10269 14655 449s Rows: 449s [1] 3 449s TCN segmentation rows: 449s startRow endRow 449s 3 10268 14658 449s TCN and DH segmentation rows: 449s startRow endRow 449s 3 10268 14658 449s startRow endRow 449s 1 10269 14655 449s startRow endRow 449s 1 1 7599 449s 2 7600 10267 449s TCN segmentation (expanded) rows: 449s startRow endRow 449s 1 1 7599 449s 2 7600 10267 449s 3 10268 14658 449s TCN and DH segmentation rows: 449s startRow endRow 449s 1 1 7599 449s 2 7600 10267 449s 3 10268 14658 449s startRow endRow 449s 1 10 7594 449s 2 7614 10263 449s 3 10269 14655 449s startRow endRow 449s 1 1 7599 449s 2 7600 10267 449s 3 10268 14658 449s Total CN segmentation table (expanded): 449s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 449s 3 1 185449813 247137334 4391 2.6341 1311 1311 449s (TCN,DH) segmentation for one total CN segment: 449s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 449s 3 3 1 1 185449813 247137334 4391 2.6341 1311 449s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 449s 3 1311 185449813 247137334 1311 0.2512 449s Total CN segment #3 ([1.8545e+08,2.47137e+08]) of 3...done 449s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 449s 1 1 1 1 554484 143926517 7599 1.3859 2111 449s 2 1 2 1 143926517 185449813 2668 2.0704 774 449s 3 1 3 1 185449813 247137334 4391 2.6341 1311 449s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 449s 1 2111 554484 143926517 2111 0.5237 449s 2 774 143926517 185449813 774 0.1542 449s 3 1311 185449813 247137334 1311 0.2512 449s Calculating (C1,C2) per segment... 449s Calculating (C1,C2) per segment...done 449s Number of segments: 3 449s Segmenting paired tumor-normal signals using Paired PSCBS...done 449s Post-segmenting TCNs... 449s Number of segments: 3 449s Number of chromosomes: 1 449s [1] 1 449s Chromosome 1 ('chr01') of 1... 449s Rows: 449s [1] 1 2 3 449s Number of segments: 3 449s TCN segment #1 ('1') of 3... 449s Nothing todo. Only one DH segmentation. Skipping. 449s TCN segment #1 ('1') of 3...done 449s TCN segment #2 ('2') of 3... 449s Nothing todo. Only one DH segmentation. Skipping. 449s TCN segment #2 ('2') of 3...done 449s TCN segment #3 ('3') of 3... 449s Nothing todo. Only one DH segmentation. Skipping. 449s TCN segment #3 ('3') of 3...done 449s Chromosome 1 ('chr01') of 1...done 449s Update (C1,C2) per segment... 449s Update (C1,C2) per segment...done 449s Post-segmenting TCNs...done 449s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 449s 1 1 1 1 554484 143926517 7599 1.3859 2111 449s 2 1 2 1 143926517 185449813 2668 2.0704 774 449s 3 1 3 1 185449813 247137334 4391 2.6341 1311 449s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 449s 1 2111 554484 143926517 2111 0.5237 0.3300521 1.055848 449s 2 774 143926517 185449813 774 0.1542 0.8755722 1.194828 449s 3 1311 185449813 247137334 1311 0.2512 0.9862070 1.647893 449s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 449s 1 1 1 1 554484 143926517 7599 1.3859 2111 449s 2 1 2 1 143926517 185449813 2668 2.0704 774 449s 3 1 3 1 185449813 247137334 4391 2.6341 1311 449s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 449s 1 2111 554484 143926517 2111 0.5237 0.3300521 1.055848 449s 2 774 143926517 185449813 774 0.1542 0.8755722 1.194828 449s 3 1311 185449813 247137334 1311 0.2512 0.9862070 1.647893 449s > print(fit) 449s chromosome tcnId dhId start end tcnNbrOfLoci tcnMean tcnNbrOfSNPs 449s 1 1 1 1 554484 143926517 7599 1.3859 2111 449s 2 1 2 1 143926517 185449813 2668 2.0704 774 449s 3 1 3 1 185449813 247137334 4391 2.6341 1311 449s tcnNbrOfHets dhNbrOfLoci dhMean c1Mean c2Mean 449s 1 2111 2111 0.5237 0.3300521 1.055848 449s 2 774 774 0.1542 0.8755722 1.194828 449s 3 1311 1311 0.2512 0.9862070 1.647893 449s > 449s > # Plot results 449s > plotTracks(fit) 449s > 449s > 449s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 449s > # Bootstrap segment level estimates 449s > # (used by the AB caller, which, if skipped here, 449s > # will do it automatically) 449s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 449s > fit <- bootstrapTCNandDHByRegion(fit, B=B, verbose=-10) 449s Resample (TCN,DH) signals and re-estimate summaries for segment & changepoint... 449s Already done? 449s tcn_2.5% tcn_5% tcn_95% tcn_97.5% dh_2.5% dh_5% dh_95% dh_97.5% 449s FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE 449s c1_2.5% c1_5% c1_95% c1_97.5% c2_2.5% c2_5% c2_95% c2_97.5% 449s FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE 449s Bootstrapping (TCN,DH,C1,C2) segment mean levels... 449s Identifying heterozygous & homozygous SNPs and non-polymorphic loci... 449s Number of loci: 14658 449s Number of SNPs: 4196 449s Number of non-SNPs: 10462 449s Identifying heterozygous & homozygous SNPs and non-polymorphic loci...done 449s num [1:3, 1:100, 1:4] NA NA NA NA NA NA NA NA NA NA ... 449s - attr(*, "dimnames")=List of 3 449s ..$ : NULL 449s ..$ : NULL 449s ..$ : chr [1:4] "tcn" "dh" "c1" "c2" 449s Segment #1 (chr 1, tcnId=1, dhId=1) of 3... 449s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 449s 1 1 1 1 554484 143926517 7599 1.3859 2111 449s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 449s 1 2111 554484 143926517 2111 0.5237 0.3300521 1.055848 449s Number of TCNs: 7599 449s Number of DHs: 2111 449s int [1:7599] 1 2 3 4 5 6 7 8 9 10 ... 449s int [1:14658] 1 2 3 4 5 6 7 8 9 10 ... 449s int [1:7599] 1 2 3 4 5 6 7 8 9 10 ... 449s Identify loci used to bootstrap DH means... 449s Heterozygous SNPs to resample for DH: 449s int [1:2111] 10 12 24 28 31 33 34 39 46 48 ... 449s Identify loci used to bootstrap DH means...done 449s Identify loci used to bootstrap TCN means... 449s SNPs: 449s int [1:2111] 10 12 24 28 31 33 34 39 46 48 ... 449s Non-polymorphic loci: 449s int [1:5488] 1 2 3 4 5 6 7 8 9 11 ... 449s Heterozygous SNPs to resample for TCN: 449s int [1:2111] 10 12 24 28 31 33 34 39 46 48 ... 449s Homozygous SNPs to resample for TCN: 449s int(0) 449s Non-polymorphic loci to resample for TCN: 449s int [1:5488] 1 2 3 4 5 6 7 8 9 11 ... 449s Heterozygous SNPs with non-DH to resample for TCN: 449s int(0) 449s Loci to resample for TCN: 449s int [1:7599] 1 2 3 4 5 6 7 8 9 10 ... 449s Identify loci used to bootstrap TCN means...done 449s Number of (#hets, #homs, #nonSNPs): (2111,0,5488) 449s Bootstrapping while preserving (#hets, #homs, #nonSNPs)... 449s Number of bootstrap samples: 100 449s Bootstrapping while preserving (#hets, #homs, #nonSNPs)...done 449s Segment #1 (chr 1, tcnId=1, dhId=1) of 3...done 449s Segment #2 (chr 1, tcnId=2, dhId=1) of 3... 449s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 449s 2 1 2 1 143926517 185449813 2668 2.0704 774 449s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 449s 2 774 143926517 185449813 774 0.1542 0.8755722 1.194828 449s Number of TCNs: 2668 449s Number of DHs: 774 449s int [1:2668] 7600 7601 7602 7603 7604 7605 7606 7607 7608 7609 ... 449s int [1:14658] 1 2 3 4 5 6 7 8 9 10 ... 449s int [1:2668] 7600 7601 7602 7603 7604 7605 7606 7607 7608 7609 ... 449s Identify loci used to bootstrap DH means... 449s Heterozygous SNPs to resample for DH: 449s int [1:774] 7614 7616 7626 7627 7628 7635 7638 7639 7640 7642 ... 449s Identify loci used to bootstrap DH means...done 449s Identify loci used to bootstrap TCN means... 449s SNPs: 449s int [1:774] 7614 7616 7626 7627 7628 7635 7638 7639 7640 7642 ... 449s Non-polymorphic loci: 449s int [1:1894] 7600 7601 7602 7603 7604 7605 7606 7607 7608 7609 ... 449s Heterozygous SNPs to resample for TCN: 449s int [1:774] 7614 7616 7626 7627 7628 7635 7638 7639 7640 7642 ... 449s Homozygous SNPs to resample for TCN: 449s int(0) 449s Non-polymorphic loci to resample for TCN: 449s int [1:1894] 7600 7601 7602 7603 7604 7605 7606 7607 7608 7609 ... 449s Heterozygous SNPs with non-DH to resample for TCN: 449s int(0) 449s Loci to resample for TCN: 449s int [1:2668] 7600 7601 7602 7603 7604 7605 7606 7607 7608 7609 ... 449s Identify loci used to bootstrap TCN means...done 449s Number of (#hets, #homs, #nonSNPs): (774,0,1894) 449s Bootstrapping while preserving (#hets, #homs, #nonSNPs)... 449s Number of bootstrap samples: 100 449s Bootstrapping while preserving (#hets, #homs, #nonSNPs)...done 449s Segment #2 (chr 1, tcnId=2, dhId=1) of 3...done 449s Segment #3 (chr 1, tcnId=3, dhId=1) of 3... 449s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 449s 3 1 3 1 185449813 247137334 4391 2.6341 1311 449s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 449s 3 1311 185449813 247137334 1311 0.2512 0.986207 1.647893 449s Number of TCNs: 4391 449s Number of DHs: 1311 449s int [1:4391] 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 449s int [1:14658] 1 2 3 4 5 6 7 8 9 10 ... 449s int [1:4391] 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 449s Identify loci used to bootstrap DH means... 449s Heterozygous SNPs to resample for DH: 449s int [1:1311] 10269 10271 10281 10282 10283 10293 10295 10297 10300 10302 ... 449s Identify loci used to bootstrap DH means...done 449s Identify loci used to bootstrap TCN means... 449s SNPs: 449s int [1:1311] 10269 10271 10281 10282 10283 10293 10295 10297 10300 10302 ... 449s Non-polymorphic loci: 449s int [1:3080] 10268 10270 10272 10273 10274 10275 10276 10277 10278 10279 ... 449s Heterozygous SNPs to resample for TCN: 449s int [1:1311] 10269 10271 10281 10282 10283 10293 10295 10297 10300 10302 ... 449s Homozygous SNPs to resample for TCN: 449s int(0) 449s Non-polymorphic loci to resample for TCN: 449s int [1:3080] 10268 10270 10272 10273 10274 10275 10276 10277 10278 10279 ... 449s Heterozygous SNPs with non-DH to resample for TCN: 449s int(0) 449s Loci to resample for TCN: 449s int [1:4391] 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 449s Identify loci used to bootstrap TCN means...done 449s Number of (#hets, #homs, #nonSNPs): (1311,0,3080) 449s Bootstrapping while preserving (#hets, #homs, #nonSNPs)... 449s Number of bootstrap samples: 100 449s Bootstrapping while preserving (#hets, #homs, #nonSNPs)...done 449s Segment #3 (chr 1, tcnId=3, dhId=1) of 3...done 449s Bootstrapped segment mean levels 449s num [1:3, 1:100, 1:4] 1.38 2.08 2.63 1.38 2.07 ... 449s - attr(*, "dimnames")=List of 3 449s ..$ : NULL 449s ..$ : NULL 449s ..$ : chr [1:4] "tcn" "dh" "c1" "c2" 449s Calculating (C1,C2) mean levels from (TCN,DH) mean levels... 449s num [1:3, 1:100, 1:4] 1.38 2.08 2.63 1.38 2.07 ... 449s - attr(*, "dimnames")=List of 3 449s ..$ : NULL 449s ..$ : NULL 449s ..$ : chr [1:4] "tcn" "dh" "c1" "c2" 449s Calculating (C1,C2) mean levels from (TCN,DH) mean levels...done 449s Calculating polar (alpha,radius,manhattan) for change points... 449s num [1:2, 1:100, 1:2] -0.5588 -0.0962 -0.5365 -0.1285 -0.5378 ... 449s - attr(*, "dimnames")=List of 3 449s ..$ : NULL 449s ..$ : NULL 449s ..$ : chr [1:2] "c1" "c2" 449s Bootstrapped change points 449s num [1:2, 1:100, 1:5] -2.89 -1.78 -2.87 -1.86 -2.88 ... 449s - attr(*, "dimnames")=List of 3 449s ..$ : NULL 449s ..$ : NULL 449s ..$ : chr [1:5] "alpha" "radius" "manhattan" "d1" ... 449s Calculating polar (alpha,radius,manhattan) for change points...done 449s Bootstrapping (TCN,DH,C1,C2) segment mean levels...done 449s Summarizing bootstrapped segment (‘tcn’, ‘dh’, ‘c1’, ‘c2’) data... 449s num [1:3, 1:4, 1:4] NA NA NA NA NA NA NA NA NA NA ... 449s - attr(*, "dimnames")=List of 3 449s ..$ : NULL 449s ..$ : chr [1:4] "2.5%" "5%" "95%" "97.5%" 449s ..$ : chr [1:4] "tcn" "dh" "c1" "c2" 449s Field #1 ('tcn') of 4... 449s Segment #1 of 3... 449s Segment #1 of 3...done 449s Segment #2 of 3... 449s Segment #2 of 3...done 449s Segment #3 of 3... 449s Segment #3 of 3...done 449s Field #1 ('tcn') of 4...done 449s Field #2 ('dh') of 4... 449s Segment #1 of 3... 449s Segment #1 of 3...done 449s Segment #2 of 3... 449s Segment #2 of 3...done 449s Segment #3 of 3... 449s Segment #3 of 3...done 449s Field #2 ('dh') of 4...done 449s Field #3 ('c1') of 4... 449s Segment #1 of 3... 449s Segment #1 of 3...done 449s Segment #2 of 3... 449s Segment #2 of 3...done 449s Segment #3 of 3... 449s Segment #3 of 3...done 449s Field #3 ('c1') of 4...done 449s Field #4 ('c2') of 4... 449s Segment #1 of 3... 449s Segment #1 of 3...done 449s Segment #2 of 3... 449s Segment #2 of 3...done 449s Segment #3 of 3... 449s Segment #3 of 3...done 449s Field #4 ('c2') of 4...done 449s Bootstrap statistics 449s num [1:3, 1:4, 1:4] 1.38 2.06 2.62 1.38 2.06 ... 449s - attr(*, "dimnames")=List of 3 449s ..$ : NULL 449s ..$ : chr [1:4] "2.5%" "5%" "95%" "97.5%" 449s ..$ : chr [1:4] "tcn" "dh" "c1" "c2" 449s Statistical sanity checks (iff B >= 100)... 449s Available summaries: 2.5%, 5%, 95%, 97.5% 449s Available quantiles: 0.025, 0.05, 0.95, 0.975 449s num [1:3, 1:4, 1:4] 1.38 2.06 2.62 1.38 2.06 ... 449s - attr(*, "dimnames")=List of 3 449s ..$ : NULL 449s ..$ : chr [1:4] "2.5%" "5%" "95%" "97.5%" 449s ..$ : chr [1:4] "tcn" "dh" "c1" "c2" 449s Field #1 ('tcn') of 4... 449s Seg 1. mean=1.3859, range=[1.38092,1.3949], n=7599 449s Seg 2. mean=2.0704, range=[2.05747,2.08326], n=2668 449s Seg 3. mean=2.6341, range=[2.62068,2.64694], n=4391 449s Field #1 ('tcn') of 4...done 449s Field #2 ('dh') of 4... 449s Seg 1. mean=0.5237, range=[0.51753,0.532002], n=2111 449s Seg 2. mean=0.1542, range=[0.144468,0.16453], n=774 449s Seg 3. mean=0.2512, range=[0.242575,0.258832], n=1311 449s Field #2 ('dh') of 4...done 449s Field #3 ('c1') of 4... 449s Seg 1. mean=0.330052, range=[0.323996,0.336038], n=2111 449s Seg 2. mean=0.875572, range=[0.86318,0.887699], n=774 449s Seg 3. mean=0.986207, range=[0.975123,0.998982], n=1311 449s Field #3 ('c1') of 4...done 449s Field #4 ('c2') of 4... 449s Seg 1. mean=1.05585, range=[1.05006,1.06231], n=2111 449s Seg 2. mean=1.19483, range=[1.18417,1.2081], n=774 449s Seg 3. mean=1.64789, range=[1.63403,1.66098], n=1311 449s Field #4 ('c2') of 4...done 449s Statistical sanity checks (iff B >= 100)...done 449s Summarizing bootstrapped segment (‘tcn’, ‘dh’, ‘c1’, ‘c2’) data...done 449s Summarizing bootstrapped changepoint (‘alpha’, ‘radius’, ‘manhattan’, ‘d1’, ‘d2’) data... 449s num [1:2, 1:4, 1:5] NA NA NA NA NA NA NA NA NA NA ... 449s - attr(*, "dimnames")=List of 3 449s ..$ : NULL 449s ..$ : chr [1:4] "2.5%" "5%" "95%" "97.5%" 449s ..$ : chr [1:5] "alpha" "radius" "manhattan" "d1" ... 449s Field #1 ('alpha') of 5... 449s Changepoint #1 of 2... 449s Changepoint #1 of 2...done 449s Changepoint #2 of 2... 449s Changepoint #2 of 2...done 449s Field #1 ('alpha') of 5...done 449s Field #2 ('radius') of 5... 449s Changepoint #1 of 2... 449s Changepoint #1 of 2...done 449s Changepoint #2 of 2... 449s Changepoint #2 of 2...done 449s Field #2 ('radius') of 5...done 449s Field #3 ('manhattan') of 5... 449s Changepoint #1 of 2... 449s Changepoint #1 of 2...done 449s Changepoint #2 of 2... 449s Changepoint #2 of 2...done 449s Field #3 ('manhattan') of 5...done 449s Field #4 ('d1') of 5... 449s Changepoint #1 of 2... 449s Changepoint #1 of 2...done 449s Changepoint #2 of 2... 449s Changepoint #2 of 2...done 449s Field #4 ('d1') of 5...done 449s Field #5 ('d2') of 5... 449s Changepoint #1 of 2... 449s Changepoint #1 of 2...done 449s Changepoint #2 of 2... 449s Changepoint #2 of 2...done 449s Field #5 ('d2') of 5...done 449s Bootstrap statistics 449s num [1:2, 1:4, 1:5] -2.92 -1.86 -2.91 -1.85 -2.87 ... 449s - attr(*, "dimnames")=List of 3 449s ..$ : NULL 449s ..$ : chr [1:4] "2.5%" "5%" "95%" "97.5%" 449s ..$ : chr [1:5] "alpha" "radius" "manhattan" "d1" ... 449s > print(fit) 449s chromosome tcnId dhId start end tcnNbrOfLoci tcnMean tcnNbrOfSNPs 449s 1 1 1 1 554484 143926517 7599 1.3859 Summarizing bootstrapped changepoint (‘alpha’, ‘radius’, ‘manhattan’, ‘d1’, ‘d2’) data...done 449s Resample (TCN,DH) signals and re-estimate summaries for segment & changepoint...done 449s 2111 449s 2 1 2 1 143926517 185449813 2668 2.0704 774 449s 3 1 3 1 185449813 247137334 4391 2.6341 1311 449s tcnNbrOfHets dhNbrOfLoci dhMean c1Mean c2Mean 449s 1 2111 2111 0.5237 0.3300521 1.055848 449s 2 774 774 0.1542 0.8755722 1.194828 449s 3 1311 1311 0.2512 0.9862070 1.647893 449s > plotTracks(fit) 449s > 449s > 449s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 449s > # Calling segments in allelic balance (AB) and 449s > # in loss-of-heterozygosity (LOH) 449s > # NOTE: Ideally, this should be done on whole-genome data 449s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 449s > fit <- callAB(fit, verbose=-10) 449s Calling segments of allelic balance from one-sided DH bootstrap confidence intervals... 449s delta (offset adjusting for bias in DH): 0.3466649145302 449s alpha (CI quantile; significance level): 0.05 449s Calling segments... 449s Number of segments called allelic balance (AB): 2 (66.67%) of 3 449s Calling segments...done 449s Calling segments of allelic balance from one-sided DH bootstrap confidence intervals...done 449s Calling segments of allelic balance from one-sided DH bootstrap confidence intervals... 449s delta (offset adjusting for bias in C1): 0.771236438183453 449s alpha (CI quantile; significance level): 0.05 449s > fit <- callLOH(fit, verbose=-10) 449s Calling segments... 449s Number of segments called low C1 (LowC1, "LOH_C1"): 1 (33.33%) of 3 449s Calling segments...done 449s Calling segments of allelic balance from one-sided DH bootstrap confidence intervals...done 449s > print(fit) 449s chromosome tcnId dhId start end tcnNbrOfLoci tcnMean tcnNbrOfSNPs 449s 1 1 1 1 554484 143926517 7599 1.3859 2111 449s 2 1 2 1 143926517 185449813 2668 2.0704 774 449s 3 1 3 1 185449813 247137334 4391 2.6341 1311 449s tcnNbrOfHets dhNbrOfLoci dhMean c1Mean c2Mean abCall lohCall 449s 1 2111 2111 0.5237 0.3300521 1.055848 FALSE TRUE 449s 2 774 774 0.1542 0.8755722 1.194828 TRUE FALSE 449s 3 1311 1311 0.2512 0.9862070 1.647893 TRUE FALSE 449s > plotTracks(fit) 449s > 449s Start: segmentByPairedPSCBS,calls.R 449s 449s R version 4.5.2 (2025-10-31) -- "[Not] Part in a Rumble" 449s Copyright (C) 2025 The R Foundation for Statistical Computing 449s Platform: x86_64-pc-linux-gnu 449s 449s R is free software and comes with ABSOLUTELY NO WARRANTY. 449s You are welcome to redistribute it under certain conditions. 449s Type 'license()' or 'licence()' for distribution details. 449s 449s R is a collaborative project with many contributors. 449s Type 'contributors()' for more information and 449s 'citation()' on how to cite R or R packages in publications. 449s 449s Type 'demo()' for some demos, 'help()' for on-line help, or 449s 'help.start()' for an HTML browser interface to help. 449s Type 'q()' to quit R. 449s 449s > library("PSCBS") 449s PSCBS v0.68.0 (2025-04-18 19:40:02 UTC) successfully loaded. See ?PSCBS for help. 449s > 449s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 449s > # Load SNP microarray data 449s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 449s > data <- PSCBS::exampleData("paired.chr01") 450s > str(data) 450s 'data.frame': 73346 obs. of 6 variables: 450s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 450s $ x : int 1145994 2224111 2319424 2543484 2926730 2941694 3084986 3155127 3292731 3695086 ... 450s $ CT : num 1.625 1.071 1.406 1.18 0.856 ... 450s $ betaT : num 0.757 0.771 0.834 0.778 0.229 ... 450s $ CN : num 2.36 2.13 2.59 1.93 1.71 ... 450s $ betaN : num 0.827 0.875 0.887 0.884 0.103 ... 450s > 450s > 450s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 450s > # Paired PSCBS segmentation 450s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 450s > # Drop single-locus outliers 450s > dataS <- dropSegmentationOutliers(data) 450s > 450s > # Find centromere 450s > gaps <- findLargeGaps(dataS, minLength=2e6) 450s > knownSegments <- gapsToSegments(gaps) 450s > 450s > 450s > # Run light-weight tests by default 450s > if (Sys.getenv("_R_CHECK_FULL_") == "") { 450s + # Use only every 5th data point 450s + dataS <- dataS[seq(from=1, to=nrow(data), by=5),] 450s + # Number of segments (for assertion) 450s + nSegs <- 4L 450s + # Number of bootstrap samples (see below) 450s + B <- 100L 450s + } else { 450s + # Full tests 450s + nSegs <- 11L 450s + B <- 1000L 450s + } 450s > 450s > str(dataS) 450s 'data.frame': 14670 obs. of 6 variables: 450s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 450s $ x : int 1145994 2941694 3710825 4240737 4276892 4464544 4714611 5095111 5034491 5158416 ... 450s $ CT : num 1.63 1.4 1.41 1.17 1.16 ... 450s $ betaT : num 0.7574 0.169 0.2357 0.2604 0.0576 ... 450s $ CN : num 2.36 2.13 2.26 2.01 2.32 ... 450s $ betaN : num 0.8274 0.5072 0.1671 0.1609 0.0421 ... 450s > 450s > # Paired PSCBS segmentation 450s > fit <- segmentByPairedPSCBS(dataS, knownSegments=knownSegments, 450s + seed=0xBEEF, verbose=-10) 450s Segmenting paired tumor-normal signals using Paired PSCBS... 450s Calling genotypes from normal allele B fractions... 450s num [1:14670] 0.8274 0.5072 0.1671 0.1609 0.0421 ... 450s Called genotypes: 450s num [1:14670] 1 0.5 0 0 0 0 1 0 1 0.5 ... 450s - attr(*, "modelFit")=List of 1 450s ..$ :List of 7 450s .. ..$ flavor : chr "density" 450s .. ..$ cn : int 2 450s .. ..$ nbrOfGenotypeGroups: int 3 450s .. ..$ tau : num [1:2] 0.315 0.677 450s .. ..$ n : int 14640 450s .. ..$ fit :Classes ‘PeaksAndValleys’ and 'data.frame': 5 obs. of 3 variables: 450s .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 450s .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 450s .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 450s .. ..$ fitValleys :Classes ‘PeaksAndValleys’ and 'data.frame': 2 obs. of 3 variables: 450s .. .. ..$ type : chr [1:2] "valley" "valley" 450s .. .. ..$ x : num [1:2] 0.315 0.677 450s .. .. ..$ density: num [1:2] 0.522 0.551 450s ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 450s muN 450s 0 0.5 1 450s 5221 4198 5251 450s Calling genotypes from normal allele B fractions...done 450s Normalizing betaT using betaN (TumorBoost)... 450s Normalized BAFs: 450s num [1:14670] 0.9301 0.1667 0.0685 0.0995 0.0155 ... 450s - attr(*, "modelFit")=List of 5 450s ..$ method : chr "normalizeTumorBoost" 450s ..$ flavor : chr "v4" 450s ..$ delta : num [1:14670] -0.17264 0.00239 0.1671 0.16085 0.04213 ... 450s .. ..- attr(*, "modelFit")=List of 1 450s .. .. ..$ :List of 7 450s .. .. .. ..$ flavor : chr "density" 450s .. .. .. ..$ cn : int 2 450s .. .. .. ..$ nbrOfGenotypeGroups: int 3 450s .. .. .. ..$ tau : num [1:2] 0.315 0.677 450s .. .. .. ..$ n : int 14640 450s .. .. .. ..$ fit :Classes ‘PeaksAndValleys’ and 'data.frame': 5 obs. of 3 variables: 450s .. .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 450s .. .. .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 450s .. .. .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 450s .. .. .. ..$ fitValleys :Classes ‘PeaksAndValleys’ and 'data.frame': 2 obs. of 3 variables: 450s .. .. .. .. ..$ type : chr [1:2] "valley" "valley" 450s .. .. .. .. ..$ x : num [1:2] 0.315 0.677 450s .. .. .. .. ..$ density: num [1:2] 0.522 0.551 450s .. .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 450s ..$ preserveScale: logi FALSE 450s ..$ scaleFactor : num NA 450s Normalizing betaT using betaN (TumorBoost)...done 450s Setup up data... 450s 'data.frame': 14670 obs. of 7 variables: 450s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 450s $ x : num 1145994 2941694 3710825 4240737 4276892 ... 450s $ CT : num 1.63 1.4 1.41 1.17 1.16 ... 450s $ betaT : num 0.7574 0.169 0.2357 0.2604 0.0576 ... 450s $ betaTN : num 0.9301 0.1667 0.0685 0.0995 0.0155 ... 450s ..- attr(*, "modelFit")=List of 5 450s .. ..$ method : chr "normalizeTumorBoost" 450s .. ..$ flavor : chr "v4" 450s .. ..$ delta : num [1:14670] -0.17264 0.00239 0.1671 0.16085 0.04213 ... 450s .. .. ..- attr(*, "modelFit")=List of 1 450s .. .. .. ..$ :List of 7 450s .. .. .. .. ..$ flavor : chr "density" 450s .. .. .. .. ..$ cn : int 2 450s .. .. .. .. ..$ nbrOfGenotypeGroups: int 3 450s .. .. .. .. ..$ tau : num [1:2] 0.315 0.677 450s .. .. .. .. ..$ n : int 14640 450s .. .. .. .. ..$ fit :Classes ‘PeaksAndValleys’ and 'data.frame': 5 obs. of 3 variables: 450s .. .. .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 450s .. .. .. .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 450s .. .. .. .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 450s .. .. .. .. ..$ fitValleys :Classes ‘PeaksAndValleys’ and 'data.frame': 2 obs. of 3 variables: 450s .. .. .. .. .. ..$ type : chr [1:2] "valley" "valley" 450s .. .. .. .. .. ..$ x : num [1:2] 0.315 0.677 450s .. .. .. .. .. ..$ density: num [1:2] 0.522 0.551 450s .. .. .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 450s .. ..$ preserveScale: logi FALSE 450s .. ..$ scaleFactor : num NA 450s $ betaN : num 0.8274 0.5072 0.1671 0.1609 0.0421 ... 450s $ muN : num 1 0.5 0 0 0 0 1 0 1 0.5 ... 450s ..- attr(*, "modelFit")=List of 1 450s .. ..$ :List of 7 450s .. .. ..$ flavor : chr "density" 450s .. .. ..$ cn : int 2 450s .. .. ..$ nbrOfGenotypeGroups: int 3 450s .. .. ..$ tau : num [1:2] 0.315 0.677 450s .. .. ..$ n : int 14640 450s .. .. ..$ fit :Classes ‘PeaksAndValleys’ and 'data.frame': 5 obs. of 3 variables: 450s .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 450s .. .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 450s .. .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 450s .. .. ..$ fitValleys :Classes ‘PeaksAndValleys’ and 'data.frame': 2 obs. of 3 variables: 450s .. .. .. ..$ type : chr [1:2] "valley" "valley" 450s .. .. .. ..$ x : num [1:2] 0.315 0.677 450s .. .. .. ..$ density: num [1:2] 0.522 0.551 450s .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 450s Setup up data...done 450s Dropping loci for which TCNs are missing... 450s Number of loci dropped: 12 450s Dropping loci for which TCNs are missing...done 450s Ordering data along genome... 450s 'data.frame': 14658 obs. of 7 variables: 450s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 450s $ x : num 554484 730720 782343 878522 916294 ... 450s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 450s $ betaT : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 450s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 450s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 450s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 450s Ordering data along genome...done 450s Keeping only current chromosome for 'knownSegments'... 450s Chromosome: 1 450s Known segments for this chromosome: 450s chromosome start end length 450s 1 1 -Inf 120992603 Inf 450s 2 1 120992604 141510002 20517398 450s 3 1 141510003 Inf Inf 450s Keeping only current chromosome for 'knownSegments'...done 450s alphaTCN: 0.009 450s alphaDH: 0.001 450s Number of loci: 14658 450s Calculating DHs... 450s Number of SNPs: 14658 450s Number of heterozygous SNPs: 4196 (28.63%) 450s Normalized DHs: 450s num [1:14658] NA NA NA NA NA ... 450s Calculating DHs...done 450s Random seed temporarily set (seed=c(48879), kind="L'Ecuyer-CMRG") 450s Produced 2 seeds from this stream for future usage 450s Identification of change points by total copy numbers... 450s Segmenting by CBS... 450s Chromosome: 1 450s Segmenting multiple segments on current chromosome... 450s Number of segments: 3 450s Random seed temporarily set (seed=c(10407, 1066287653, -51199871, 161854402, -1995183193, 1503453565, -747102133), kind="L'Ecuyer-CMRG") 450s Produced 3 seeds from this stream for future usage 450s Segmenting by CBS... 450s Chromosome: 1 450s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 450s Segmenting by CBS...done 450s Segmenting by CBS... 450s Chromosome: 1 450s Random seed temporarily set (seed=c(10407, -1924040949, -1632234809, -437763632, -1464377300, 676654412, 2080370711), kind="L'Ecuyer-CMRG") 450s Segmenting by CBS...done 450s Segmenting multiple segments on current chromosome...done 450s Segmenting by CBS...done 450s List of 4 450s $ data :'data.frame': 14658 obs. of 4 variables: 450s ..$ chromosome: int [1:14658] 1 1 1 1 1 1 1 1 1 1 ... 450s ..$ x : num [1:14658] 554484 730720 782343 878522 916294 ... 450s ..$ y : num [1:14658] 1.88 1.8 1.59 1.64 1.53 ... 450s ..$ index : int [1:14658] 1 2 3 4 5 6 7 8 9 10 ... 450s $ output :'data.frame': 4 obs. of 6 variables: 450s ..$ sampleName: chr [1:4] NA NA NA NA 450s ..$ chromosome: int [1:4] 1 1 1 1 450s ..$ start : num [1:4] 5.54e+05 1.21e+08 1.42e+08 1.85e+08 450s ..$ end : num [1:4] 1.21e+08 1.42e+08 1.85e+08 2.47e+08 450s ..$ nbrOfLoci : int [1:4] 7586 0 2681 4391 450s ..$ mean : num [1:4] 1.39 NA 2.07 2.63 450s $ segRows:'data.frame': 4 obs. of 2 variables: 450s ..$ startRow: int [1:4] 1 NA 7587 10268 450s ..$ endRow : int [1:4] 7586 NA 10267 14658 450s $ params :List of 5 450s ..$ alpha : num 0.009 450s ..$ undo : num 0 450s ..$ joinSegments : logi TRUE 450s ..$ knownSegments:'data.frame': 4 obs. of 3 variables: 450s .. ..$ chromosome: int [1:4] 1 1 2 1 450s .. ..$ start : num [1:4] -Inf -Inf -Inf 1.42e+08 450s .. ..$ end : num [1:4] 1.21e+08 Inf Inf Inf 450s ..$ seed : int [1:7] 10407 1066287653 -51199871 161854402 -1995183193 1503453565 -747102133 450s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 450s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.086 0 0.086 0 0 450s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 450s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 450s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 450s Identification of change points by total copy numbers...done 450s Restructure TCN segmentation results... 450s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean 450s 1 1 554484 120992603 7586 1.3853 450s 2 1 120992604 141510002 0 NA 450s 3 1 141510003 185449813 2681 2.0689 450s 4 1 185449813 247137334 4391 2.6341 450s Number of TCN segments: 4 450s Restructure TCN segmentation results...done 450s Total CN segment #1 ([ 554484,1.20993e+08]) of 4... 450s Number of TCN loci in segment: 7586 450s Locus data for TCN segment: 450s 'data.frame': 7586 obs. of 9 variables: 450s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 450s $ x : num 554484 730720 782343 878522 916294 ... 450s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 450s $ betaT : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 450s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 450s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 450s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 450s $ index : int 1 2 3 4 5 6 7 8 9 10 ... 450s $ rho : num NA NA NA NA NA ... 450s Number of loci: 7586 450s Number of SNPs: 2108 (27.79%) 450s Number of heterozygous SNPs: 2108 (100.00%) 450s Chromosome: 1 450s Segmenting DH signals... 450s Segmenting by CBS... 450s Chromosome: 1 450s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 450s Segmenting by CBS...done 450s List of 4 450s $ data :'data.frame': 7586 obs. of 4 variables: 450s ..$ chromosome: int [1:7586] 1 1 1 1 1 1 1 1 1 1 ... 450s ..$ x : num [1:7586] 554484 730720 782343 878522 916294 ... 450s ..$ y : num [1:7586] NA NA NA NA NA ... 450s ..$ index : int [1:7586] 1 2 3 4 5 6 7 8 9 10 ... 450s $ output :'data.frame': 1 obs. of 6 variables: 450s ..$ sampleName: chr NA 450s ..$ chromosome: int 1 450s ..$ start : num 554484 450s ..$ end : num 1.21e+08 450s ..$ nbrOfLoci : int 2108 450s ..$ mean : num 0.512 450s $ segRows:'data.frame': 1 obs. of 2 variables: 450s ..$ startRow: int 10 450s ..$ endRow : int 7574 450s $ params :List of 5 450s ..$ alpha : num 0.001 450s ..$ undo : num 0 450s ..$ joinSegments : logi TRUE 450s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 450s .. ..$ chromosome: int 1 450s .. ..$ start : num 554484 450s .. ..$ end : num 1.21e+08 450s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 450s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 450s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.025 0 0.026 0 0 450s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 450s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 450s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 450s DH segmentation (locally-indexed) rows: 450s startRow endRow 450s 1 10 7574 450s int [1:7586] 1 2 3 4 5 6 7 8 9 10 ... 450s DH segmentation rows: 450s startRow endRow 450s 1 10 7574 450s Segmenting DH signals...done 450s DH segmentation table: 450s dhStart dhEnd dhNbrOfLoci dhMean 450s 1 554484 120992603 2108 0.5116 450s startRow endRow 450s 1 10 7574 450s Rows: 450s [1] 1 450s TCN segmentation rows: 450s startRow endRow 450s 1 1 7586 450s TCN and DH segmentation rows: 450s startRow endRow 450s 1 1 7586 450s startRow endRow 450s 1 10 7574 450s NULL 450s TCN segmentation (expanded) rows: 450s startRow endRow 450s 1 1 7586 450s TCN and DH segmentation rows: 450s startRow endRow 450s 1 1 7586 450s 2 NA NA 450s 3 7587 10267 450s 4 10268 14658 450s startRow endRow 450s 1 10 7574 450s startRow endRow 450s 1 1 7586 450s Total CN segmentation table (expanded): 450s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 450s 1 1 554484 120992603 7586 1.3853 2108 2108 450s (TCN,DH) segmentation for one total CN segment: 450s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 450s 1 1 1 1 554484 120992603 7586 1.3853 2108 450s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 450s 1 2108 554484 120992603 2108 0.5116 450s Total CN segment #1 ([ 554484,1.20993e+08]) of 4...done 450s Total CN segment #2 ([1.20993e+08,1.4151e+08]) of 4... 450s Number of TCN loci in segment: 0 450s Locus data for TCN segment: 450s 'data.frame': 0 obs. of 9 variables: 450s $ chromosome: int 450s $ x : num 450s $ CT : num 450s $ betaT : num 450s $ betaTN : num 450s $ betaN : num 450s $ muN : num 450s $ index : int 450s $ rho : num 450s Number of loci: 0 450s Number of SNPs: 0 (NaN%) 450s Number of heterozygous SNPs: 0 (NaN%) 450s Chromosome: 1 450s Segmenting DH signals... 450s Segmenting by CBS... 450s Chromosome: NA 450s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 450s Segmenting by CBS...done 450s List of 4 450s $ data :'data.frame': 0 obs. of 4 variables: 450s ..$ chromosome: int(0) 450s ..$ x : num(0) 450s ..$ y : num(0) 450s ..$ index : int(0) 450s $ output :'data.frame': 0 obs. of 6 variables: 450s ..$ sampleName: chr(0) 450s ..$ chromosome: num(0) 450s ..$ start : num(0) 450s ..$ end : num(0) 450s ..$ nbrOfLoci : int(0) 450s ..$ mean : num(0) 450s $ segRows:'data.frame': 0 obs. of 2 variables: 450s ..$ startRow: int(0) 450s ..$ endRow : int(0) 450s $ params :List of 5 450s ..$ alpha : num 0.001 450s ..$ undo : num 0 450s ..$ joinSegments : logi TRUE 450s ..$ knownSegments:'data.frame': 0 obs. of 3 variables: 450s .. ..$ chromosome: int(0) 450s .. ..$ start : num(0) 450s .. ..$ end : num(0) 450s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 450s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 450s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.001 0 0.001 0 0 450s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 450s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 450s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 450s DH segmentation (locally-indexed) rows: 450s [1] startRow endRow 450s <0 rows> (or 0-length row.names) 450s int(0) 450s DH segmentation rows: 450s [1] startRow endRow 450s <0 rows> (or 0-length row.names) 450s Segmenting DH signals...done 450s DH segmentation table: 450s dhStart dhEnd dhNbrOfLoci dhMean 450s NA NA NA NA NA 450s startRow endRow 450s NA NA NA 450s Rows: 450s [1] 2 450s TCN segmentation rows: 450s startRow endRow 450s 2 NA NA 450s TCN and DH segmentation rows: 450s startRow endRow 450s 2 NA NA 450s startRow endRow 450s NA NA NA 450s startRow endRow 450s 1 1 7586 450s TCN segmentation (expanded) rows: 450s startRow endRow 450s 1 1 7586 450s 2 NA NA 450s TCN and DH segmentation rows: 450s startRow endRow 450s 1 1 7586 450s 2 NA NA 450s 3 7587 10267 450s 4 10268 14658 450s startRow endRow 450s 1 10 7574 450s 2 NA NA 450s startRow endRow 450s 1 1 7586 450s 2 NA NA 450s Total CN segmentation table (expanded): 450s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 450s 2 1 120992604 141510002 0 NA 0 0 450s (TCN,DH) segmentation for one total CN segment: 450s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 450s 2 2 1 1 120992604 141510002 0 NA 0 450s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 450s 2 0 NA NA NA NA 450s Total CN segment #2 ([1.20993e+08,1.4151e+08]) of 4...done 450s Total CN segment #3 ([1.4151e+08,1.8545e+08]) of 4... 450s Number of TCN loci in segment: 2681 450s Locus data for TCN segment: 450s 'data.frame': 2681 obs. of 9 variables: 450s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 450s $ x : num 1.43e+08 1.43e+08 1.43e+08 1.43e+08 1.44e+08 ... 450s $ CT : num 2.27 1.55 1.47 1.5 1.81 ... 450s $ betaT : num 0.34 0.55 0.048 0.813 0.575 ... 450s $ betaTN : num 0.441 0.629 -0.05 0.958 0.872 ... 450s $ betaN : num 0.3851 0.3933 0.0981 0.8552 0.7028 ... 450s $ muN : num 0.5 0.5 0 1 1 1 1 0.5 1 1 ... 450s $ index : int 7587 7588 7589 7590 7591 7592 7593 7594 7595 7596 ... 450s $ rho : num 0.117 0.258 NA NA NA ... 450s Number of loci: 2681 450s Number of SNPs: 777 (28.98%) 450s Number of heterozygous SNPs: 777 (100.00%) 450s Chromosome: 1 450s Segmenting DH signals... 450s Segmenting by CBS... 450s Chromosome: 1 450s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 450s Segmenting by CBS...done 450s List of 4 450s $ data :'data.frame': 2681 obs. of 4 variables: 450s ..$ chromosome: int [1:2681] 1 1 1 1 1 1 1 1 1 1 ... 450s ..$ x : num [1:2681] 1.43e+08 1.43e+08 1.43e+08 1.43e+08 1.44e+08 ... 450s ..$ y : num [1:2681] 0.117 0.258 NA NA NA ... 450s ..$ index : int [1:2681] 1 2 3 4 5 6 7 8 9 10 ... 450s $ output :'data.frame': 1 obs. of 6 variables: 450s ..$ sampleName: chr NA 450s ..$ chromosome: int 1 450s ..$ start : num 1.42e+08 450s ..$ end : num 1.85e+08 450s ..$ nbrOfLoci : int 777 450s ..$ mean : num 0.0973 450s $ segRows:'data.frame': 1 obs. of 2 variables: 450s ..$ startRow: int 1 450s ..$ endRow : int 2677 450s $ params :List of 5 450s ..$ alpha : num 0.001 450s ..$ undo : num 0 450s ..$ joinSegments : logi TRUE 450s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 450s .. ..$ chromosome: int 1 450s .. ..$ start : num 1.42e+08 450s .. ..$ end : num 1.85e+08 450s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 450s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 450s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.005 0 0.005 0 0 450s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 450s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 450s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 450s DH segmentation (locally-indexed) rows: 450s startRow endRow 450s 1 1 2677 450s int [1:2681] 7587 7588 7589 7590 7591 7592 7593 7594 7595 7596 ... 450s DH segmentation rows: 450s startRow endRow 450s 1 7587 10263 450s Segmenting DH signals...done 450s DH segmentation table: 450s dhStart dhEnd dhNbrOfLoci dhMean 450s 1 141510003 185449813 777 0.0973 450s startRow endRow 450s 1 7587 10263 450s Rows: 450s [1] 3 450s TCN segmentation rows: 450s startRow endRow 450s 3 7587 10267 450s TCN and DH segmentation rows: 450s startRow endRow 450s 3 7587 10267 450s startRow endRow 450s 1 7587 10263 450s startRow endRow 450s 1 1 7586 450s 2 NA NA 450s TCN segmentation (expanded) rows: 450s startRow endRow 450s 1 1 7586 450s 2 NA NA 450s 3 7587 10267 450s TCN and DH segmentation rows: 450s startRow endRow 450s 1 1 7586 450s 2 NA NA 450s 3 7587 10267 450s 4 10268 14658 450s startRow endRow 450s 1 10 7574 450s 2 NA NA 450s 3 7587 10263 450s startRow endRow 450s 1 1 7586 450s 2 NA NA 450s 3 7587 10267 450s Total CN segmentation table (expanded): 450s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 450s 3 1 141510003 185449813 2681 2.0689 777 777 450s (TCN,DH) segmentation for one total CN segment: 450s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 450s 3 3 1 1 141510003 185449813 2681 2.0689 777 450s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 450s 3 777 141510003 185449813 777 0.0973 450s Total CN segment #3 ([1.4151e+08,1.8545e+08]) of 4...done 450s Total CN segment #4 ([1.8545e+08,2.47137e+08]) of 4... 450s Number of TCN loci in segment: 4391 450s Locus data for TCN segment: 450s 'data.frame': 4391 obs. of 9 variables: 450s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 450s $ x : num 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 450s $ CT : num 2.93 2.15 2.82 2.93 2.46 ... 450s $ betaT : num 0.0811 0.5154 0.9473 0.3734 0.7506 ... 450s $ betaTN : num -0.169 0.609 1.028 0.525 0.968 ... 450s $ betaN : num 0.25 0.38 0.919 0.34 0.783 ... 450s $ muN : num 0 0.5 1 0.5 1 1 0 1 0 1 ... 450s $ index : int 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 450s $ rho : num NA 0.2186 NA 0.0503 NA ... 450s Number of loci: 4391 450s Number of SNPs: 1311 (29.86%) 450s Number of heterozygous SNPs: 1311 (100.00%) 450s Chromosome: 1 450s Segmenting DH signals... 450s Segmenting by CBS... 450s Chromosome: 1 450s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 450s Segmenting by CBS...done 450s List of 4 450s $ data :'data.frame': 4391 obs. of 4 variables: 450s ..$ chromosome: int [1:4391] 1 1 1 1 1 1 1 1 1 1 ... 450s ..$ x : num [1:4391] 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 450s ..$ y : num [1:4391] NA 0.2186 NA 0.0503 NA ... 450s ..$ index : int [1:4391] 1 2 3 4 5 6 7 8 9 10 ... 450s $ output :'data.frame': 1 obs. of 6 variables: 450s ..$ sampleName: chr NA 450s ..$ chromosome: int 1 450s ..$ start : num 1.85e+08 450s ..$ end : num 2.47e+08 450s ..$ nbrOfLoci : int 1311 450s ..$ mean : num 0.23 450s $ segRows:'data.frame': 1 obs. of 2 variables: 450s ..$ startRow: int 2 450s ..$ endRow : int 4388 450s $ params :List of 5 450s ..$ alpha : num 0.001 450s ..$ undo : num 0 450s ..$ joinSegments : logi TRUE 450s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 450s .. ..$ chromosome: int 1 450s .. ..$ start : num 1.85e+08 450s .. ..$ end : num 2.47e+08 450s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 450s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 450s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.009 0 0.01 0 0 450s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 450s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 450s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 450s DH segmentation (locally-indexed) rows: 450s startRow endRow 450s 1 2 4388 450s int [1:4391] 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 450s DH segmentation rows: 450s startRow endRow 450s 1 10269 14655 450s Segmenting DH signals...done 450s DH segmentation table: 450s dhStart dhEnd dhNbrOfLoci dhMean 450s 1 185449813 247137334 1311 0.2295 450s startRow endRow 450s 1 10269 14655 450s Rows: 450s [1] 4 450s TCN segmentation rows: 450s startRow endRow 450s 4 10268 14658 450s TCN and DH segmentation rows: 450s startRow endRow 450s 4 10268 14658 450s startRow endRow 450s 1 10269 14655 450s startRow endRow 450s 1 1 7586 450s 2 NA NA 450s 3 7587 10267 450s TCN segmentation (expanded) rows: 450s startRow endRow 450s 1 1 7586 450s 2 NA NA 450s 3 7587 10267 450s 4 10268 14658 450s TCN and DH segmentation rows: 450s startRow endRow 450s 1 1 7586 450s 2 NA NA 450s 3 7587 10267 450s 4 10268 14658 450s startRow endRow 450s 1 10 7574 450s 2 NA NA 450s 3 7587 10263 450s 4 10269 14655 450s startRow endRow 450s 1 1 7586 450s 2 NA NA 450s 3 7587 10267 450s 4 10268 14658 450s Total CN segmentation table (expanded): 450s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 450s 4 1 185449813 247137334 4391 2.6341 1311 1311 450s (TCN,DH) segmentation for one total CN segment: 450s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 450s 4 4 1 1 185449813 247137334 4391 2.6341 1311 450s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 450s 4 1311 185449813 247137334 1311 0.2295 450s Total CN segment #4 ([1.8545e+08,2.47137e+08]) of 4...done 450s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 450s 1 1 1 1 554484 120992603 7586 1.3853 2108 450s 2 1 2 1 120992604 141510002 0 NA 0 450s 3 1 3 1 141510003 185449813 2681 2.0689 777 450s 4 1 4 1 185449813 247137334 4391 2.6341 1311 450s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 450s 1 2108 554484 120992603 2108 0.5116 450s 2 0 NA NA NA NA 450s 3 777 141510003 185449813 777 0.0973 450s 4 1311 185449813 247137334 1311 0.2295 450s Calculating (C1,C2) per segment... 450s Calculating (C1,C2) per segment...done 450s Number of segments: 4 450s Segmenting paired tumor-normal signals using Paired PSCBS...done 450s Post-segmenting TCNs... 450s Number of segments: 4 450s Number of chromosomes: 1 450s [1] 1 450s Chromosome 1 ('chr01') of 1... 450s Rows: 450s [1] 1 2 3 4 450s Number of segments: 4 450s TCN segment #1 ('1') of 4... 450s Nothing todo. Only one DH segmentation. Skipping. 450s TCN segment #1 ('1') of 4...done 450s TCN segment #2 ('2') of 4... 450s Nothing todo. Only one DH segmentation. Skipping. 450s TCN segment #2 ('2') of 4...done 450s TCN segment #3 ('3') of 4... 450s Nothing todo. Only one DH segmentation. Skipping. 450s TCN segment #3 ('3') of 4...done 450s TCN segment #4 ('4') of 4... 450s Nothing todo. Only one DH segmentation. Skipping. 450s TCN segment #4 ('4') of 4...done 450s Chromosome 1 ('chr01') of 1...done 450s Update (C1,C2) per segment... 450s Update (C1,C2) per segment...done 450s Post-segmenting TCNs...done 450s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 450s 1 1 1 1 554484 120992603 7586 1.3853 2108 450s 2 1 2 1 120992604 141510002 0 NA 0 450s 3 1 3 1 141510003 185449813 2681 2.0689 777 450s 4 1 4 1 185449813 247137334 4391 2.6341 1311 450s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 450s 1 2108 554484 120992603 2108 0.5116 0.3382903 1.047010 450s 2 0 NA NA NA NA NA NA 450s 3 777 141510003 185449813 777 0.0973 0.9337980 1.135102 450s 4 1311 185449813 247137334 1311 0.2295 1.0147870 1.619313 450s > print(fit) 450s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 450s 1 1 1 1 554484 120992603 7586 1.3853 2108 450s 2 1 2 1 120992604 141510002 0 NA 0 450s 3 1 3 1 141510003 185449813 2681 2.0689 777 450s 4 1 4 1 185449813 247137334 4391 2.6341 1311 450s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 450s 1 2108 554484 120992603 2108 0.5116 0.3382903 1.047010 450s 2 0 NA NA NA NA NA NA 450s 3 777 141510003 185449813 777 0.0973 0.9337980 1.135102 450s 4 1311 185449813 247137334 1311 0.2295 1.0147870 1.619313 450s chromosome tcnId dhId start end tcnNbrOfLoci tcnMean tcnNbrOfSNPs 450s 1 1 1 1 554484 120992603 7586 1.3853 2108 450s 2 1 2 1 120992604 141510002 0 NA 0 450s 3 1 3 1 141510003 185449813 2681 2.0689 777 450s 4 1 4 1 185449813 247137334 4391 2.6341 1311 450s tcnNbrOfHets dhNbrOfLoci dhMean c1Mean c2Mean 450s 1 2108 2108 0.5116 0.3382903 1.047010 450s 2 0 NA NA NA NA 450s 3 777 777 0.0973 0.9337980 1.135102 450s 4 1311 1311 0.2295 1.0147870 1.619313 450s > 450s > # Plot results 450s > plotTracks(fit) 450s > 450s > # Sanity check 450s > stopifnot(nbrOfSegments(fit) == nSegs) 450s > 450s > 450s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 450s > # Bootstrap segment level estimates 450s > # (used by the AB caller, which, if skipped here, 450s > # will do it automatically) 450s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 450s > fit <- bootstrapTCNandDHByRegion(fit, B=B, verbose=-10) 450s Resample (TCN,DH) signals and re-estimate summaries for segment & changepoint... 450s Already done? 450s tcn_2.5% tcn_5% tcn_95% tcn_97.5% dh_2.5% dh_5% dh_95% dh_97.5% 450s FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE 450s c1_2.5% c1_5% c1_95% c1_97.5% c2_2.5% c2_5% c2_95% c2_97.5% 450s FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE 450s Bootstrapping (TCN,DH,C1,C2) segment mean levels... 450s Identifying heterozygous & homozygous SNPs and non-polymorphic loci... 450s Number of loci: 14658 450s Number of SNPs: 4196 450s Number of non-SNPs: 10462 450s Identifying heterozygous & homozygous SNPs and non-polymorphic loci...done 450s num [1:4, 1:100, 1:4] NA NA NA NA NA NA NA NA NA NA ... 450s - attr(*, "dimnames")=List of 3 450s ..$ : NULL 450s ..$ : NULL 450s ..$ : chr [1:4] "tcn" "dh" "c1" "c2" 450s Segment #1 (chr 1, tcnId=1, dhId=1) of 4... 450s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 450s 1 1 1 1 554484 120992603 7586 1.3853 2108 450s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 450s 1 2108 554484 120992603 2108 0.5116 0.3382903 1.04701 450s Number of TCNs: 7586 450s Number of DHs: 2108 450s int [1:7586] 1 2 3 4 5 6 7 8 9 10 ... 450s int [1:14658] 1 2 3 4 5 6 7 8 9 10 ... 450s int [1:7586] 1 2 3 4 5 6 7 8 9 10 ... 450s Identify loci used to bootstrap DH means... 450s Heterozygous SNPs to resample for DH: 450s int [1:2108] 10 12 24 28 31 33 34 39 46 48 ... 450s Identify loci used to bootstrap DH means...done 450s Identify loci used to bootstrap TCN means... 450s SNPs: 450s int [1:2108] 10 12 24 28 31 33 34 39 46 48 ... 450s Non-polymorphic loci: 450s int [1:5478] 1 2 3 4 5 6 7 8 9 11 ... 450s Heterozygous SNPs to resample for TCN: 450s int [1:2108] 10 12 24 28 31 33 34 39 46 48 ... 450s Homozygous SNPs to resample for TCN: 450s int(0) 450s Non-polymorphic loci to resample for TCN: 450s int [1:5478] 1 2 3 4 5 6 7 8 9 11 ... 450s Heterozygous SNPs with non-DH to resample for TCN: 450s int(0) 450s Loci to resample for TCN: 450s int [1:7586] 1 2 3 4 5 6 7 8 9 10 ... 450s Identify loci used to bootstrap TCN means...done 450s Number of (#hets, #homs, #nonSNPs): (2108,0,5478) 450s Bootstrapping while preserving (#hets, #homs, #nonSNPs)... 450s Number of bootstrap samples: 100 451s Bootstrapping while preserving (#hets, #homs, #nonSNPs)...done 451s Segment #1 (chr 1, tcnId=1, dhId=1) of 4...done 451s Segment #2 (chr 1, tcnId=2, dhId=1) of 4... 451s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 451s 2 1 2 1 120992604 141510002 0 NA 0 451s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 451s 2 0 NA NA 0 NA NA NA 451s Number of TCNs: 0 451s Number of DHs: 0 451s int 0 451s int [1:14658] 1 2 3 4 5 6 7 8 9 10 ... 451s int(0) 451s Identify loci used to bootstrap DH means... 451s Heterozygous SNPs to resample for DH: 451s int 0 451s Identify loci used to bootstrap DH means...done 451s Identify loci used to bootstrap TCN means... 451s SNPs: 451s int(0) 451s Non-polymorphic loci: 451s int(0) 451s Heterozygous SNPs to resample for TCN: 451s int(0) 451s Homozygous SNPs to resample for TCN: 451s int(0) 451s Non-polymorphic loci to resample for TCN: 451s int(0) 451s Heterozygous SNPs with non-DH to resample for TCN: 451s int(0) 451s Loci to resample for TCN: 451s int(0) 451s Identify loci used to bootstrap TCN means...done 451s Number of (#hets, #homs, #nonSNPs): (0,0,0) 451s Bootstrapping while preserving (#hets, #homs, #nonSNPs)... 451s Number of bootstrap samples: 100 451s Bootstrapping while preserving (#hets, #homs, #nonSNPs)...done 451s Segment #2 (chr 1, tcnId=2, dhId=1) of 4...done 451s Segment #3 (chr 1, tcnId=3, dhId=1) of 4... 451s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 451s 3 1 3 1 141510003 185449813 2681 2.0689 777 451s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 451s 3 777 141510003 185449813 777 0.0973 0.933798 1.135102 451s Number of TCNs: 2681 451s Number of DHs: 777 451s int [1:2681] 7587 7588 7589 7590 7591 7592 7593 7594 7595 7596 ... 451s int [1:14658] 1 2 3 4 5 6 7 8 9 10 ... 451s int [1:2681] 7587 7588 7589 7590 7591 7592 7593 7594 7595 7596 ... 451s Identify loci used to bootstrap DH means... 451s Heterozygous SNPs to resample for DH: 451s int [1:777] 7587 7588 7594 7614 7616 7626 7627 7628 7635 7638 ... 451s Identify loci used to bootstrap DH means...done 451s Identify loci used to bootstrap TCN means... 451s SNPs: 451s int [1:777] 7587 7588 7594 7614 7616 7626 7627 7628 7635 7638 ... 451s Non-polymorphic loci: 451s int [1:1904] 7589 7590 7591 7592 7593 7595 7596 7597 7598 7599 ... 451s Heterozygous SNPs to resample for TCN: 451s int [1:777] 7587 7588 7594 7614 7616 7626 7627 7628 7635 7638 ... 451s Homozygous SNPs to resample for TCN: 451s int(0) 451s Non-polymorphic loci to resample for TCN: 451s int [1:1904] 7589 7590 7591 7592 7593 7595 7596 7597 7598 7599 ... 451s Heterozygous SNPs with non-DH to resample for TCN: 451s int(0) 451s Loci to resample for TCN: 451s int [1:2681] 7587 7588 7589 7590 7591 7592 7593 7594 7595 7596 ... 451s Identify loci used to bootstrap TCN means...done 451s Number of (#hets, #homs, #nonSNPs): (777,0,1904) 451s Bootstrapping while preserving (#hets, #homs, #nonSNPs)... 451s Number of bootstrap samples: 100 451s Bootstrapping while preserving (#hets, #homs, #nonSNPs)...done 451s Segment #3 (chr 1, tcnId=3, dhId=1) of 4...done 451s Segment #4 (chr 1, tcnId=4, dhId=1) of 4... 451s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 451s 4 1 4 1 185449813 247137334 4391 2.6341 1311 451s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 451s 4 1311 185449813 247137334 1311 0.2295 1.014787 1.619313 451s Number of TCNs: 4391 451s Number of DHs: 1311 451s int [1:4391] 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 451s int [1:14658] 1 2 3 4 5 6 7 8 9 10 ... 451s int [1:4391] 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 451s Identify loci used to bootstrap DH means... 451s Heterozygous SNPs to resample for DH: 451s int [1:1311] 10269 10271 10281 10282 10283 10293 10295 10297 10300 10302 ... 451s Identify loci used to bootstrap DH means...done 451s Identify loci used to bootstrap TCN means... 451s SNPs: 451s int [1:1311] 10269 10271 10281 10282 10283 10293 10295 10297 10300 10302 ... 451s Non-polymorphic loci: 451s int [1:3080] 10268 10270 10272 10273 10274 10275 10276 10277 10278 10279 ... 451s Heterozygous SNPs to resample for TCN: 451s int [1:1311] 10269 10271 10281 10282 10283 10293 10295 10297 10300 10302 ... 451s Homozygous SNPs to resample for TCN: 451s int(0) 451s Non-polymorphic loci to resample for TCN: 451s int [1:3080] 10268 10270 10272 10273 10274 10275 10276 10277 10278 10279 ... 451s Heterozygous SNPs with non-DH to resample for TCN: 451s int(0) 451s Loci to resample for TCN: 451s int [1:4391] 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 451s Identify loci used to bootstrap TCN means...done 451s Number of (#hets, #homs, #nonSNPs): (1311,0,3080) 451s Bootstrapping while preserving (#hets, #homs, #nonSNPs)... 451s Number of bootstrap samples: 100 451s Bootstrapping while preserving (#hets, #homs, #nonSNPs)...done 451s Segment #4 (chr 1, tcnId=4, dhId=1) of 4...done 451s Bootstrapped segment mean levels 451s num [1:4, 1:100, 1:4] 1.39 NA 2.08 2.63 1.38 ... 451s - attr(*, "dimnames")=List of 3 451s ..$ : NULL 451s ..$ : NULL 451s ..$ : chr [1:4] "tcn" "dh" "c1" "c2" 451s Calculating (C1,C2) mean levels from (TCN,DH) mean levels... 451s num [1:4, 1:100, 1:4] 1.39 NA 2.08 2.63 1.38 ... 451s - attr(*, "dimnames")=List of 3 451s ..$ : NULL 451s ..$ : NULL 451s ..$ : chr [1:4] "tcn" "dh" "c1" "c2" 451s Calculating (C1,C2) mean levels from (TCN,DH) mean levels...done 451s Calculating polar (alpha,radius,manhattan) for change points... 451s num [1:3, 1:100, 1:2] NA NA -0.0752 NA NA ... 451s - attr(*, "dimnames")=List of 3 451s ..$ : NULL 451s ..$ : NULL 451s ..$ : chr [1:2] "c1" "c2" 451s Bootstrapped change points 451s num [1:3, 1:100, 1:5] NA NA -1.73 NA NA ... 451s - attr(*, "dimnames")=List of 3 451s ..$ : NULL 451s ..$ : NULL 451s ..$ : chr [1:5] "alpha" "radius" "manhattan" "d1" ... 451s Calculating polar (alpha,radius,manhattan) for change points...done 451s Bootstrapping (TCN,DH,C1,C2) segment mean levels...done 451s Summarizing bootstrapped segment (‘tcn’, ‘dh’, ‘c1’, ‘c2’) data... 451s num [1:4, 1:4, 1:4] NA NA NA NA NA NA NA NA NA NA ... 451s - attr(*, "dimnames")=List of 3 451s ..$ : NULL 451s ..$ : chr [1:4] "2.5%" "5%" "95%" "97.5%" 451s ..$ : chr [1:4] "tcn" "dh" "c1" "c2" 451s Field #1 ('tcn') of 4... 451s Segment #1 of 4... 451s Segment #1 of 4...done 451s Segment #2 of 4... 451s Segment #2 of 4...done 451s Segment #3 of 4... 451s Segment #3 of 4...done 451s Segment #4 of 4... 451s Segment #4 of 4...done 451s Field #1 ('tcn') of 4...done 451s Field #2 ('dh') of 4... 451s Segment #1 of 4... 451s Segment #1 of 4...done 451s Segment #2 of 4... 451s Segment #2 of 4...done 451s Segment #3 of 4... 451s Segment #3 of 4...done 451s Segment #4 of 4... 451s Segment #4 of 4...done 451s Field #2 ('dh') of 4...done 451s Field #3 ('c1') of 4... 451s Segment #1 of 4... 451s Segment #1 of 4...done 451s Segment #2 of 4... 451s Segment #2 of 4...done 451s Segment #3 of 4... 451s Segment #3 of 4...done 451s Segment #4 of 4... 451s Segment #4 of 4...done 451s Field #3 ('c1') of 4...done 451s Field #4 ('c2') of 4... 451s Segment #1 of 4... 451s Segment #1 of 4...done 451s Segment #2 of 4... 451s Segment #2 of 4...done 451s Segment #3 of 4... 451s Segment #3 of 4...done 451s Segment #4 of 4... 451s Segment #4 of 4...done 451s Field #4 ('c2') of 4...done 451s Bootstrap statistics 451s num [1:4, 1:4, 1:4] 1.38 NA 2.06 2.63 1.38 ... 451s - attr(*, "dimnames")=List of 3 451s ..$ : NULL 451s ..$ : chr [1:4] "2.5%" "5%" "95%" "97.5%" 451s ..$ : chr [1:4] "tcn" "dh" "c1" "c2" 451s Statistical sanity checks (iff B >= 100)... 451s Available summaries: 2.5%, 5%, 95%, 97.5% 451s Available quantiles: 0.025, 0.05, 0.95, 0.975 451s num [1:4, 1:4, 1:4] 1.38 NA 2.06 2.63 1.38 ... 451s - attr(*, "dimnames")=List of 3 451s ..$ : NULL 451s ..$ : chr [1:4] "2.5%" "5%" "95%" "97.5%" 451s ..$ : chr [1:4] "tcn" "dh" "c1" "c2" 451s Field #1 ('tcn') of 4... 451s Seg 1. mean=1.3853, range=[1.37909,1.39287], n=7586 451s Seg 2. mean=NA, range=[NA,NA], n=0 451s Seg 3. mean=2.0689, range=[2.05903,2.079], n=2681 451s Seg 4. mean=2.6341, range=[2.62504,2.64649], n=4391 451s Field #1 ('tcn') of 4...done 451s Field #2 ('dh') of 4... 451s Seg 1. mean=0.5116, range=[0.502148,0.519941], n=2108 451s Seg 2. mean=NA, range=[NA,NA], n=NA 451s Seg 3. mean=0.0973, range=[0.0906366,0.105818], n=777 451s Seg 4. mean=0.2295, range=[0.222919,0.237005], n=1311 451s Field #2 ('dh') of 4...done 451s Field #3 ('c1') of 4... 451s Seg 1. mean=0.33829, range=[0.332209,0.345936], n=2108 451s Seg 2. mean=NA, range=[NA,NA], n=NA 451s Seg 3. mean=0.933798, range=[0.924112,0.941776], n=777 451s Seg 4. mean=1.01479, range=[1.00381,1.02461], n=1311 451s Field #3 ('c1') of 4...done 451s Field #4 ('c2') of 4... 451s Seg 1. mean=1.04701, range=[1.03882,1.05318], n=2108 451s Seg 2. mean=NA, range=[NA,NA], n=NA 451s Seg 3. mean=1.1351, range=[1.12454,1.1465], n=777 451s Seg 4. mean=1.61931, range=[1.60862,1.63328], n=1311 451s Field #4 ('c2') of 4...done 451s Statistical sanity checks (iff B >= 100)...done 451s Summarizing bootstrapped segment (‘tcn’, ‘dh’, ‘c1’, ‘c2’) data...done 451s Summarizing bootstrapped changepoint (‘alpha’, ‘radius’, ‘manhattan’, ‘d1’, ‘d2’) data... 451s num [1:3, 1:4, 1:5] NA NA NA NA NA NA NA NA NA NA ... 451s - attr(*, "dimnames")=List of 3 451s ..$ : NULL 451s ..$ : chr [1:4] "2.5%" "5%" "95%" "97.5%" 451s ..$ : chr [1:5] "alpha" "radius" "manhattan" "d1" ... 451s Field #1 ('alpha') of 5... 451s Changepoint #1 of 3... 451s Changepoint #1 of 3...done 451s Changepoint #2 of 3... 451s Changepoint #2 of 3...done 451s Changepoint #3 of 3... 451s Changepoint #3 of 3...done 451s Field #1 ('alpha') of 5...done 451s Field #2 ('radius') of 5... 451s Changepoint #1 of 3... 451s Changepoint #1 of 3...done 451s Changepoint #2 of 3... 451s Changepoint #2 of 3...done 451s Changepoint #3 of 3... 451s Changepoint #3 of 3...done 451s Field #2 ('radius') of 5...done 451s Field #3 ('manhattan') of 5... 451s Changepoint #1 of 3... 451s Changepoint #1 of 3...done 451s Changepoint #2 of 3... 451s Changepoint #2 of 3...done 451s Changepoint #3 of 3... 451s Changepoint #3 of 3...done 451s Field #3 ('manhattan') of 5...done 451s Field #4 ('d1') of 5... 451s Changepoint #1 of 3... 451s Changepoint #1 of 3...done 451s Changepoint #2 of 3... 451s Changepoint #2 of 3...done 451s Changepoint #3 of 3... 451s Changepoint #3 of 3...done 451s Field #4 ('d1') of 5...done 451s Field #5 ('d2') of 5... 451s Changepoint #1 of 3... 451s Changepoint #1 of 3...done 451s Changepoint #2 of 3... 451s Changepoint #2 of 3...done 451s Changepoint #3 of 3... 451s Changepoint #3 of 3...done 451s Field #5 ('d2') of 5...done 451s Bootstrap statistics 451s num [1:3, 1:4, 1:5] NA NA -1.77 NA NA ... 451s - attr(*, "dimnames")=List of 3 451s ..$ : NULL 451s ..$ : chr [1:4] "2.5%" "5%" "95%" "97.5%" 451s ..$ : chr [1:5] "alpha" "radius" "manhattan" "d1" ... 451s Summarizing bootstrapped changepoint (‘alpha’, ‘radius’, ‘manhattan’, ‘d1’, ‘d2’) data...done 451s Resample (TCN,DH) signals and re-estimate summaries for segment & changepoint...done 451s > print(fit) 451s chromosome tcnId dhId start end tcnNbrOfLoci tcnMean tcnNbrOfSNPs 451s 1 1 1 1 554484 120992603 7586 1.3853 2108 451s 2 1 2 1 120992604 141510002 0 NA 0 451s 3 1 3 1 141510003 185449813 2681 2.0689 777 451s 4 1 4 1 185449813 247137334 4391 2.6341 1311 451s tcnNbrOfHets dhNbrOfLoci dhMean c1Mean c2Mean 451s 1 2108 2108 0.5116 0.3382903 1.047010 451s 2 0 NA NA NA NA 451s 3 777 777 0.0973 0.9337980 1.135102 451s 4 1311 1311 0.2295 1.0147870 1.619313 451s > plotTracks(fit) 451s > 451s > 451s > 451s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 451s > # Calling segments with run of homozygosity (ROH) 451s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 451s > fit <- callROH(fit, verbose=-10) 451s Calling ROH... 451s Segment #1 of 4... 451s Calling ROH for a single segment... 451s Number of SNPs: 7586 451s Calling ROH for a single segment...done 451s Segment #1 of 4...done 451s Segment #2 of 4... 451s Calling ROH for a single segment... 451s Number of SNPs: 0 451s Calling ROH for a single segment...done 451s Segment #2 of 4...done 451s Segment #3 of 4... 451s Calling ROH for a single segment... 451s Number of SNPs: 2681 451s Calling ROH for a single segment...done 451s Segment #3 of 4...done 451s Segment #4 of 4... 451s Calling ROH for a single segment... 451s Number of SNPs: 4391 451s Calling ROH for a single segment...done 451s Segment #4 of 4...done 451s ROH calls: 451s logi [1:4] FALSE NA FALSE FALSE 451s Mode FALSE NA's 451s logical 3 1 451s > print(fit) 451s chromosome tcnId dhId start end tcnNbrOfLoci tcnMean tcnNbrOfSNPs 451s 1 1 1 1 554484 120992603 7586 1.3853 2108 451s 2 1 2 1 120992604 141510002 0 NA 0 451s 3 1 3 1 141510003 185449813 2681 2.0689 777 451s 4 1 4 1 185449813 247137334 4391 2.6341 1311 451s tcnNbrOfHets dhNbrOfLoci dhMean c1Mean c2Mean rohCall 451s 1 2108 2108 0.5116 0.3382903 1.047010 FALSE 451s 2 0 NA NA NA NA NA 451s 3 777 777 0.0973 0.9337980 1.135102 FALSE 451s 4 1311 1311 0.2295 1.0147870 1.619313 FALSE 451s > plotTracks(fit) 451s Calling ROH...done 451s > 451s > 451s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 451s > # Estimate background 451s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 451s > kappa <- estimateKappa(fit, verbose=-10) 451s Estimate global background (including normal contamination and more)... 451s Number of segments: 3 451s Estimating threshold Delta0.5 from the empirical density of C1:s... 451s adjust: 1 451s minDensity: 0.2 451s ploidy: 2 451s All peaks: 451s type x density 451s 1 peak 0.3362194 1.101242 451s 3 peak 0.9811492 1.065635 451s C1=0 and C1=1 peaks: 451s type x density 451s 1 peak 0.3362194 1.101242 451s 3 peak 0.9811492 1.065635 451s Estimate of Delta0.5: 0.65868427808456 451s Estimating threshold Delta0.5 from the empirical density of C1:s...done 451s Number of segments with C1 < Delta0.5: 1 451s Estimate of kappa: 0.33829026 451s Estimate global background (including normal contamination and more)...done 451s Warning message: 451s In density.default(c1, weights = weights, adjust = adjust, from = from, : 451s Selecting bandwidth *not* using 'weights' 451s > print(kappa) 451s [1] 0.3382903 451s > ## [1] 0.226011 451s > 451s > 451s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 451s > # Calling segments in allelic balance (AB) 451s > # NOTE: Ideally, this should be done on whole-genome data 451s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 451s > # Explicitly estimate the threshold in DH for calling AB 451s > # (which be done by default by the caller, if skipped here) 451s > deltaAB <- estimateDeltaAB(fit, flavor="qq(DH)", verbose=-10) 451s Estimating DH threshold for calling allelic imbalances... 451s flavor: qq(DH) 451s scale: 1 451s Estimating DH threshold for AB caller... 451s quantile #1: 0.05 451s Symmetric quantile #2: 0.9 451s Number of segments: 3 451s Weighted 5% quantile of DH: 0.257710 451s Number of segments with small DH: 2 451s Number of data points: 7072 451s Number of finite data points: 2088 451s Estimate of (1-0.9):th and 50% quantiles: (0.0310411,0.163658) 451s Estimate of 0.9:th "symmetric" quantile: 0.296275 451s Estimating DH threshold for AB caller...done 451s Estimated delta: 0.296 451s > if (Sys.getenv("_R_CHECK_FULL_") == "") { 451s + # Ad hoc workaround for not utilizing all of the data 451s + # in the test, which results in a poor estimate 451s + deltaAB <- 0.165 451s + } 451s > print(deltaAB) 451s [1] 0.165 451s > ## [1] 0.1657131 451s > 451s > fit <- callAB(fit, delta=deltaAB, verbose=-10) 451s Estimating DH threshold for calling allelic imbalances...done 451s Calling segments of allelic balance from one-sided DH bootstrap confidence intervals... 451s delta (offset adjusting for bias in DH): 0.165 451s alpha (CI quantile; significance level): 0.05 451s Calling segments... 451s Number of segments called allelic balance (AB): 1 (25.00%) of 4 451s Calling segments...done 451s > print(fit) 451s Calling segments of allelic balance from one-sided DH bootstrap confidence intervals...done 451s chromosome tcnId dhId start end tcnNbrOfLoci tcnMean tcnNbrOfSNPs 451s 1 1 1 1 554484 120992603 7586 1.3853 2108 451s 2 1 2 1 120992604 141510002 0 NA 0 451s 3 1 3 1 141510003 185449813 2681 2.0689 777 451s 4 1 4 1 185449813 247137334 4391 2.6341 1311 451s tcnNbrOfHets dhNbrOfLoci dhMean c1Mean c2Mean rohCall abCall 451s 1 2108 2108 0.5116 0.3382903 1.047010 FALSE FALSE 451s 2 0 NA NA NA NA NA NA 451s 3 777 777 0.0973 0.9337980 1.135102 FALSE TRUE 451s 4 1311 1311 0.2295 1.0147870 1.619313 FALSE FALSE 451s > plotTracks(fit) 451s > 451s > # Even if not explicitly specified, the estimated 451s > # threshold parameter is returned by the caller 451s > stopifnot(fit$params$deltaAB == deltaAB) 451s > 451s > 451s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 451s > # Calling segments in loss-of-heterozygosity (LOH) 451s > # NOTE: Ideally, this should be done on whole-genome data 451s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 451s > # Explicitly estimate the threshold in C1 for calling LOH 451s > # (which be done by default by the caller, if skipped here) 451s > deltaLOH <- estimateDeltaLOH(fit, flavor="minC1|nonAB", verbose=-10) 451s Estimating DH threshold for calling LOH... 451s flavor: minC1|nonAB 451s Estimating DH threshold for calling LOH as the midpoint between guessed C1=0 and C1=1... 451s Argument 'midpoint': 0.5 451s Number of segments: 4 451s Number of segments in allelic balance: 1 (25.0%) of 4 451s Number of segments not in allelic balance: 2 (50.0%) of 4 451s Number of segments in allelic balance and TCN <= 3.00: 1 (25.0%) of 4 451s C: 2.07 451s Corrected C1 (=C/2): 1.03 451s Number of DHs: 777 451s Weights: 1 451s Weighted median of (corrected) C1 in allelic balance: 1.034 451s Smallest C1 among segments not in allelic balance: 0.338 451s There are 1 segments with in total 2108 heterozygous SNPs with this level. 451s Midpoint between the two: 0.686 451s Estimating DH threshold for calling LOH as the midpoint between guessed C1=0 and C1=1...done 451s delta: 0.686 451s > print(deltaLOH) 451s [1] 0.6863701 451s > ## [1] 0.625175 451s > 451s > fit <- callLOH(fit, delta=deltaLOH, verbose=-10) 451s Estimating DH threshold for calling LOH...done 451s Calling segments of allelic balance from one-sided DH bootstrap confidence intervals... 451s delta (offset adjusting for bias in C1): 0.68637013 451s alpha (CI quantile; significance level): 0.05 451s Calling segments... 451s Number of segments called low C1 (LowC1, "LOH_C1"): 1 (25.00%) of 4 451s Calling segments...done 451s Calling segments of allelic balance from one-sided DH bootstrap confidence intervals...done 451s > print(fit) 451s chromosome tcnId dhId start end tcnNbrOfLoci tcnMean tcnNbrOfSNPs 451s 1 1 1 1 554484 120992603 7586 1.3853 2108 451s 2 1 2 1 120992604 141510002 0 NA 0 451s 3 1 3 1 141510003 185449813 2681 2.0689 777 451s 4 1 4 1 185449813 247137334 4391 2.6341 1311 451s tcnNbrOfHets dhNbrOfLoci dhMean c1Mean c2Mean rohCall abCall lohCall 451s 1 2108 2108 0.5116 0.3382903 1.047010 FALSE FALSE TRUE 451s 2 0 NA NA NA NA NA NA NA 451s 3 777 777 0.0973 0.9337980 1.135102 FALSE TRUE FALSE 451s 4 1311 1311 0.2295 1.0147870 1.619313 FALSE FALSE FALSE 451s > plotTracks(fit) 451s > 451s > # Even if not explicitly specified, the estimated 451s > # threshold parameter is returned by the caller 451s > stopifnot(fit$params$deltaLOH == deltaLOH) 451s > 451s > 451s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 451s > # Calling segments that are gained, copy neutral, and lost 451s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 451s > fit <- callGNL(fit, verbose=-10) 451s Calling gain, neutral, and loss based TCNs of AB segments... 451s Calling neutral TCNs... 451s callCopyNeutralByTCNofAB... 451s Alpha: 0.05 451s Delta CN: 0.33085487 451s Calling copy-neutral segments... 451s Retrieve TCN confidence intervals for all segments... 451s Interval: [0.025,0.975] 451s Retrieve TCN confidence intervals for all segments...done 451s Estimating TCN confidence interval of copy-neutral AB segments... 451s calcStatsForCopyNeutralABs... 451s Identifying copy neutral AB segments... 451s Number of AB segments: 1 451s Identifying segments that are copy neutral states... 451s Number of segments in allelic balance: 1 451s Identifying segments that are copy neutral states...done 451s Number of copy-neutral AB segments: 1 451s Extracting all copy neutral AB segments across all chromosomes into one big segment... 451s chromosome tcnId dhId start end tcnNbrOfLoci tcnMean tcnNbrOfSNPs 451s 3 1 3 1 141510003 185449813 2681 2.0689 777 451s tcnNbrOfHets dhNbrOfLoci dhMean c1Mean c2Mean rohCall abCall lohCall 451s 3 777 777 0.0973 0.933798 1.135102 FALSE TRUE FALSE 451s Extracting all copy neutral AB segments across all chromosomes into one big segment...done 451s Identifying copy neutral AB segments...done 451s Bootstrap the identified copy-neutral states... 451s Bootstrap the identified copy-neutral states...done 451s tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets dhNbrOfLoci dhMean c1Mean 451s 3 2681 2.0689 777 777 777 0.0973 0.933798 451s c2Mean tcn_2.5% tcn_5% tcn_95% tcn_97.5% dh_2.5% dh_5% dh_95% 451s 3 1.135102 2.055164 2.057694 2.078831 2.081454 0.08974138 0.09080508 0.1035891 451s dh_97.5% c1_2.5% c1_5% c1_95% c1_97.5% c2_2.5% c2_5% c2_95% 451s 3 0.1050478 0.923788 0.925412 0.9417056 0.9433752 1.124908 1.126631 1.143571 451s c2_97.5% 451s 3 1.145214 451s calcStatsForCopyNeutralABs...done 451s Bootstrap statistics for copy-neutral AB segments: 451s tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets dhNbrOfLoci dhMean c1Mean 451s 3 2681 2.0689 777 777 777 0.0973 0.933798 451s c2Mean tcn_2.5% tcn_5% tcn_95% tcn_97.5% dh_2.5% dh_5% dh_95% 451s 3 1.135102 2.055164 2.057694 2.078831 2.081454 0.08974138 0.09080508 0.1035891 451s dh_97.5% c1_2.5% c1_5% c1_95% c1_97.5% c2_2.5% c2_5% c2_95% 451s 3 0.1050478 0.923788 0.925412 0.9417056 0.9433752 1.124908 1.126631 1.143571 451s c2_97.5% 451s 3 1.145214 451s [1] "TCN statistics:" 451s tcnMean tcn_2.5% tcn_5% tcn_95% tcn_97.5% 451s 2.068900 2.055164 2.057694 2.078831 2.081454 451s 95%-confidence interval of TCN mean for the copy-neutral state: [2.05516,2.08145] (mean=2.0689) 451s Estimating TCN confidence interval of copy-neutral AB segments...done 451s Identify all copy-neutral segments... 451s DeltaCN: +/-0.330855 451s Call ("acceptance") region: [1.72431,2.41231] 451s Total number of segments: 4 451s Number of segments called allelic balance: 1 451s Number of segments called copy neutral: 1 451s Number of AB segments called copy neutral: 1 451s Number of non-AB segments called copy neutral: 0 451s Identify all copy-neutral segments...done 451s Calling copy-neutral segments...done 451s callCopyNeutralByTCNofAB...done 451s Calling neutral TCNs...done 451s Number of NTCN calls: 1 (25.00%) of 4 451s Mean TCN of AB segments: 2.06831 451s Calling loss... 451s Number of loss calls: 1 (25.00%) of 4 451s Calling loss...done 451s Calling gain... 451s Number of loss calls: 1 (25.00%) of 4 451s Calling gain...done 451s Calling gain, neutral, and loss based TCNs of AB segments...done 451s Warning message: 451s In density.default(c1, weights = weights, adjust = adjust, from = from, : 451s Selecting bandwidth *not* using 'weights' 451s > print(fit) 451s chromosome tcnId dhId start end tcnNbrOfLoci tcnMean tcnNbrOfSNPs 451s 1 1 1 1 554484 120992603 7586 1.3853 2108 451s 2 1 2 1 120992604 141510002 0 NA 0 451s 3 1 3 1 141510003 185449813 2681 2.0689 777 451s 4 1 4 1 185449813 247137334 4391 2.6341 1311 451s tcnNbrOfHets dhNbrOfLoci dhMean c1Mean c2Mean rohCall abCall lohCall 451s 1 2108 2108 0.5116 0.3382903 1.047010 FALSE FALSE TRUE 451s 2 0 NA NA NA NA NA NA NA 451s 3 777 777 0.0973 0.9337980 1.135102 FALSE TRUE FALSE 451s 4 1311 1311 0.2295 1.0147870 1.619313 FALSE FALSE FALSE 451s ntcnCall lossCall gainCall 451s 1 FALSE TRUE FALSE 451s 2 NA NA NA 451s 3 TRUE FALSE FALSE 451s 4 FALSE FALSE TRUE 451s > plotTracks(fit) 451s > 451s Start: segmentByPairedPSCBS,futures.R 451s 451s R version 4.5.2 (2025-10-31) -- "[Not] Part in a Rumble" 451s Copyright (C) 2025 The R Foundation for Statistical Computing 451s Platform: x86_64-pc-linux-gnu 451s 451s R is free software and comes with ABSOLUTELY NO WARRANTY. 451s You are welcome to redistribute it under certain conditions. 451s Type 'license()' or 'licence()' for distribution details. 451s 451s R is a collaborative project with many contributors. 451s Type 'contributors()' for more information and 451s 'citation()' on how to cite R or R packages in publications. 451s 451s Type 'demo()' for some demos, 'help()' for on-line help, or 451s 'help.start()' for an HTML browser interface to help. 451s Type 'q()' to quit R. 451s 452s > library(PSCBS) 452s PSCBS v0.68.0 (2025-04-18 19:40:02 UTC) successfully loaded. See ?PSCBS for help. 452s > library(utils) 452s > 452s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 452s > # Load SNP microarray data 452s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 452s > data <- PSCBS::exampleData("paired.chr01") 452s > 452s > 452s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 452s > # Paired PSCBS segmentation 452s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 452s > # Drop single-locus outliers 452s > dataS <- dropSegmentationOutliers(data) 452s > 452s > # Run light-weight tests by default 452s > if (Sys.getenv("_R_CHECK_FULL_") == "") { 452s + # Use only every 5th data point 452s + dataS <- dataS[seq(from=1, to=nrow(data), by=5),] 452s + # Number of segments (for assertion) 452s + nSegs <- 4L 452s + } else { 452s + # Full tests 452s + nSegs <- 11L 452s + } 452s > 452s > str(dataS) 452s 'data.frame': 14670 obs. of 6 variables: 452s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 452s $ x : int 1145994 2941694 3710825 4240737 4276892 4464544 4714611 5095111 5034491 5158416 ... 452s $ CT : num 1.63 1.4 1.41 1.17 1.16 ... 452s $ betaT : num 0.7574 0.169 0.2357 0.2604 0.0576 ... 452s $ CN : num 2.36 2.13 2.26 2.01 2.32 ... 452s $ betaN : num 0.8274 0.5072 0.1671 0.1609 0.0421 ... 452s > 452s > 452s > ## Create multiple chromosomes 452s > data <- list() 452s > for (cc in 1:3) { 452s + dataS$chromosome <- cc 452s + data[[cc]] <- dataS 452s + } 452s > data <- Reduce(rbind, data) 452s > str(data) 452s 'data.frame': 44010 obs. of 6 variables: 452s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 452s $ x : int 1145994 2941694 3710825 4240737 4276892 4464544 4714611 5095111 5034491 5158416 ... 452s $ CT : num 1.63 1.4 1.41 1.17 1.16 ... 452s $ betaT : num 0.7574 0.169 0.2357 0.2604 0.0576 ... 452s $ CN : num 2.36 2.13 2.26 2.01 2.32 ... 452s $ betaN : num 0.8274 0.5072 0.1671 0.1609 0.0421 ... 452s > 452s > 452s > message("*** segmentByPairedPSCBS() via futures ...") 452s > 452s > library("future") 452s *** segmentByPairedPSCBS() via futures ... 452s Loading required package: future.batchtools 452s Warning message: 452s In library(package, lib.loc = lib.loc, character.only = TRUE, logical.return = TRUE, : 452s there is no package called ‘future.batchtools’ 452s Future strategies to test: ‘sequential’, ‘multisession’ 452s > oplan <- plan() 452s > 452s > strategies <- c("sequential", "multisession") 452s > 452s > ## Test 'future.batchtools' futures? 452s > pkg <- "future.batchtools" 452s > if (require(pkg, character.only=TRUE)) { 452s + strategies <- c(strategies, "batchtools_local") 452s + } 452s > 452s > message("Future strategies to test: ", paste(sQuote(strategies), collapse=", ")) 452s > 452s > fits <- list() 452s > for (strategy in strategies) { 452s + message(sprintf("- segmentByPairedPSCBS() using '%s' futures ...", strategy)) 452s + plan(strategy) 452s + fit <- segmentByPairedPSCBS(data, seed=0xBEEF, verbose=TRUE) 452s + fits[[strategy]] <- fit 452s + equal <- all.equal(fit, fits[[1]]) 452s + if (!equal) { 452s + str(fit) 452s + str(fits[[1]]) 452s + print(equal) 452s + stop(sprintf("segmentByPairedPSCBS() using '%s' futures does not produce the same results as when using '%s' futures", strategy, names(fits)[1])) 452s + } 452s + } 452s - segmentByPairedPSCBS() using 'sequential' futures ... 452s Segmenting paired tumor-normal signals using Paired PSCBS... 452s Calling genotypes from normal allele B fractions... 452s num [1:44010] 0.8274 0.5072 0.1671 0.1609 0.0421 ... 452s Called genotypes: 452s num [1:44010] 1 0.5 0 0 0 0 1 0 1 0.5 ... 452s - attr(*, "modelFit")=List of 1 452s ..$ :List of 7 452s .. ..$ flavor : chr "density" 452s .. ..$ cn : int 2 452s .. ..$ nbrOfGenotypeGroups: int 3 452s .. ..$ tau : num [1:2] 0.312 0.678 452s .. ..$ n : int 43920 452s .. ..$ fit :Classes ‘PeaksAndValleys’ and 'data.frame': 5 obs. of 3 variables: 452s .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 452s .. .. ..$ x : num [1:5] 0.0999 0.312 0.4986 0.6775 0.8922 452s .. .. ..$ density: num [1:5] 1.622 0.465 1.125 0.496 1.587 452s .. ..$ fitValleys :Classes ‘PeaksAndValleys’ and 'data.frame': 2 obs. of 3 variables: 452s .. .. ..$ type : chr [1:2] "valley" "valley" 452s .. .. ..$ x : num [1:2] 0.312 0.678 452s .. .. ..$ density: num [1:2] 0.465 0.496 452s ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 452s muN 452s 0 0.5 1 452s 15627 12633 15750 452s Calling genotypes from normal allele B fractions...done 452s Normalizing betaT using betaN (TumorBoost)... 452s Normalized BAFs: 452s num [1:44010] 0.9301 0.1667 0.0685 0.0995 0.0155 ... 452s - attr(*, "modelFit")=List of 5 452s ..$ method : chr "normalizeTumorBoost" 452s ..$ flavor : chr "v4" 452s ..$ delta : num [1:44010] -0.17264 0.00239 0.1671 0.16085 0.04213 ... 452s .. ..- attr(*, "modelFit")=List of 1 452s .. .. ..$ :List of 7 452s .. .. .. ..$ flavor : chr "density" 452s .. .. .. ..$ cn : int 2 452s .. .. .. ..$ nbrOfGenotypeGroups: int 3 452s .. .. .. ..$ tau : num [1:2] 0.312 0.678 452s .. .. .. ..$ n : int 43920 452s .. .. .. ..$ fit :Classes ‘PeaksAndValleys’ and 'data.frame': 5 obs. of 3 variables: 452s .. .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 452s .. .. .. .. ..$ x : num [1:5] 0.0999 0.312 0.4986 0.6775 0.8922 452s .. .. .. .. ..$ density: num [1:5] 1.622 0.465 1.125 0.496 1.587 452s .. .. .. ..$ fitValleys :Classes ‘PeaksAndValleys’ and 'data.frame': 2 obs. of 3 variables: 452s .. .. .. .. ..$ type : chr [1:2] "valley" "valley" 452s .. .. .. .. ..$ x : num [1:2] 0.312 0.678 452s .. .. .. .. ..$ density: num [1:2] 0.465 0.496 452s .. .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 452s ..$ preserveScale: logi FALSE 452s ..$ scaleFactor : num NA 452s Normalizing betaT using betaN (TumorBoost)...done 452s Setup up data... 452s 'data.frame': 44010 obs. of 7 variables: 452s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 452s $ x : num 1145994 2941694 3710825 4240737 4276892 ... 452s $ CT : num 1.63 1.4 1.41 1.17 1.16 ... 452s $ betaT : num 0.7574 0.169 0.2357 0.2604 0.0576 ... 452s $ betaTN : num 0.9301 0.1667 0.0685 0.0995 0.0155 ... 452s ..- attr(*, "modelFit")=List of 5 452s .. ..$ method : chr "normalizeTumorBoost" 452s .. ..$ flavor : chr "v4" 452s .. ..$ delta : num [1:44010] -0.17264 0.00239 0.1671 0.16085 0.04213 ... 452s .. .. ..- attr(*, "modelFit")=List of 1 452s .. .. .. ..$ :List of 7 452s .. .. .. .. ..$ flavor : chr "density" 452s .. .. .. .. ..$ cn : int 2 452s .. .. .. .. ..$ nbrOfGenotypeGroups: int 3 452s .. .. .. .. ..$ tau : num [1:2] 0.312 0.678 452s .. .. .. .. ..$ n : int 43920 452s .. .. .. .. ..$ fit :Classes ‘PeaksAndValleys’ and 'data.frame': 5 obs. of 3 variables: 452s .. .. .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 452s .. .. .. .. .. ..$ x : num [1:5] 0.0999 0.312 0.4986 0.6775 0.8922 452s .. .. .. .. .. ..$ density: num [1:5] 1.622 0.465 1.125 0.496 1.587 452s .. .. .. .. ..$ fitValleys :Classes ‘PeaksAndValleys’ and 'data.frame': 2 obs. of 3 variables: 452s .. .. .. .. .. ..$ type : chr [1:2] "valley" "valley" 452s .. .. .. .. .. ..$ x : num [1:2] 0.312 0.678 452s .. .. .. .. .. ..$ density: num [1:2] 0.465 0.496 452s .. .. .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 452s .. ..$ preserveScale: logi FALSE 452s .. ..$ scaleFactor : num NA 452s $ betaN : num 0.8274 0.5072 0.1671 0.1609 0.0421 ... 452s $ muN : num 1 0.5 0 0 0 0 1 0 1 0.5 ... 452s ..- attr(*, "modelFit")=List of 1 452s .. ..$ :List of 7 452s .. .. ..$ flavor : chr "density" 452s .. .. ..$ cn : int 2 452s .. .. ..$ nbrOfGenotypeGroups: int 3 452s .. .. ..$ tau : num [1:2] 0.312 0.678 452s .. .. ..$ n : int 43920 452s .. .. ..$ fit :Classes ‘PeaksAndValleys’ and 'data.frame': 5 obs. of 3 variables: 452s .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 452s .. .. .. ..$ x : num [1:5] 0.0999 0.312 0.4986 0.6775 0.8922 452s .. .. .. ..$ density: num [1:5] 1.622 0.465 1.125 0.496 1.587 452s .. .. ..$ fitValleys :Classes ‘PeaksAndValleys’ and 'data.frame': 2 obs. of 3 variables: 452s .. .. .. ..$ type : chr [1:2] "valley" "valley" 452s .. .. .. ..$ x : num [1:2] 0.312 0.678 452s .. .. .. ..$ density: num [1:2] 0.465 0.496 452s .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 452s Setup up data...done 452s Dropping loci for which TCNs are missing... 452s Number of loci dropped: 36 452s Dropping loci for which TCNs are missing...done 452s Ordering data along genome... 452s 'data.frame': 43974 obs. of 7 variables: 452s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 452s $ x : num 554484 730720 782343 878522 916294 ... 452s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 452s $ betaT : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 452s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 452s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 452s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 452s Ordering data along genome...done 452s Segmenting multiple chromosomes... 452s Number of chromosomes: 3 452s Random seed temporarily set (seed=c(48879), kind="L'Ecuyer-CMRG") 452s Produced 3 seeds from this stream for future usage 452s Chromosome #1 ('Chr01') of 3... 452s 'data.frame': 14658 obs. of 8 variables: 452s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 452s $ x : num 554484 730720 782343 878522 916294 ... 452s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 452s $ betaT : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 452s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 452s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 452s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 452s $ index : int 1 2 3 4 5 6 7 8 9 10 ... 452s Known segments: 452s [1] chromosome start end 452s <0 rows> (or 0-length row.names) 452s Segmenting paired tumor-normal signals using Paired PSCBS... 452s Setup up data... 452s 'data.frame': 14658 obs. of 7 variables: 452s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 452s $ x : num 554484 730720 782343 878522 916294 ... 452s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 452s $ betaT : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 452s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 452s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 452s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 452s Setup up data...done 452s Ordering data along genome... 452s 'data.frame': 14658 obs. of 7 variables: 452s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 452s $ x : num 554484 730720 782343 878522 916294 ... 452s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 452s $ betaT : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 452s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 452s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 452s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 452s Ordering data along genome...done 452s Keeping only current chromosome for 'knownSegments'... 452s Chromosome: 1 452s Known segments for this chromosome: 452s [1] chromosome start end 452s <0 rows> (or 0-length row.names) 452s Keeping only current chromosome for 'knownSegments'...done 452s alphaTCN: 0.009 452s alphaDH: 0.001 452s Number of loci: 14658 452s Calculating DHs... 452s Number of SNPs: 14658 452s Number of heterozygous SNPs: 4209 (28.71%) 452s Normalized DHs: 452s num [1:14658] NA NA NA NA NA ... 452s Calculating DHs...done 452s Random seed temporarily set (seed=c(10407, 1066287653, -51199871, 161854402, -1995183193, 1503453565, -747102133), kind="L'Ecuyer-CMRG") 452s Produced 2 seeds from this stream for future usage 452s Identification of change points by total copy numbers... 452s Segmenting by CBS... 452s Chromosome: 1 452s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 452s Segmenting by CBS...done 452s List of 4 452s $ data :'data.frame': 14658 obs. of 4 variables: 452s ..$ chromosome: int [1:14658] 1 1 1 1 1 1 1 1 1 1 ... 452s ..$ x : num [1:14658] 554484 730720 782343 878522 916294 ... 452s ..$ y : num [1:14658] 1.88 1.8 1.59 1.64 1.53 ... 452s ..$ index : int [1:14658] 1 2 3 4 5 6 7 8 9 10 ... 452s $ output :'data.frame': 3 obs. of 6 variables: 452s ..$ sampleName: chr [1:3] NA NA NA 452s ..$ chromosome: int [1:3] 1 1 1 452s ..$ start : num [1:3] 5.54e+05 1.44e+08 1.85e+08 452s ..$ end : num [1:3] 1.44e+08 1.85e+08 2.47e+08 452s ..$ nbrOfLoci : int [1:3] 7599 2668 4391 452s ..$ mean : num [1:3] 1.39 2.07 2.63 452s $ segRows:'data.frame': 3 obs. of 2 variables: 452s ..$ startRow: int [1:3] 1 7600 10268 452s ..$ endRow : int [1:3] 7599 10267 14658 452s $ params :List of 5 452s ..$ alpha : num 0.009 452s ..$ undo : num 0 452s ..$ joinSegments : logi TRUE 452s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 452s .. ..$ chromosome: int 1 452s .. ..$ start : num -Inf 452s .. ..$ end : num Inf 452s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 452s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 452s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.243 0 0.244 0 0 452s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 452s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 452s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 452s Identification of change points by total copy numbers...done 452s Restructure TCN segmentation results... 452s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean 452s 1 1 554484 143926517 7599 1.3859 452s 2 1 143926517 185449813 2668 2.0704 452s 3 1 185449813 247137334 4391 2.6341 452s Number of TCN segments: 3 452s Restructure TCN segmentation results...done 452s Total CN segment #1 ([ 554484,1.43927e+08]) of 3... 452s Number of TCN loci in segment: 7599 452s Locus data for TCN segment: 452s 'data.frame': 7599 obs. of 9 variables: 452s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 452s $ x : num 554484 730720 782343 878522 916294 ... 452s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 452s $ betaT : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 452s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 452s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 452s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 452s $ index : int 1 2 3 4 5 6 7 8 9 10 ... 452s $ rho : num NA NA NA NA NA ... 452s Number of loci: 7599 452s Number of SNPs: 2120 (27.90%) 452s Number of heterozygous SNPs: 2120 (100.00%) 452s Chromosome: 1 452s Segmenting DH signals... 452s Segmenting by CBS... 452s Chromosome: 1 452s Random seed temporarily set (seed=c(10407, -821273412, -52578226, 1415511586, 721384351, -665928286, 1316562960), kind="L'Ecuyer-CMRG") 452s Segmenting by CBS...done 452s List of 4 452s $ data :'data.frame': 7599 obs. of 4 variables: 452s ..$ chromosome: int [1:7599] 1 1 1 1 1 1 1 1 1 1 ... 452s ..$ x : num [1:7599] 554484 730720 782343 878522 916294 ... 452s ..$ y : num [1:7599] NA NA NA NA NA ... 452s ..$ index : int [1:7599] 1 2 3 4 5 6 7 8 9 10 ... 452s $ output :'data.frame': 1 obs. of 6 variables: 452s ..$ sampleName: chr NA 452s ..$ chromosome: int 1 452s ..$ start : num 554484 452s ..$ end : num 1.44e+08 452s ..$ nbrOfLoci : int 2120 452s ..$ mean : num 0.51 452s $ segRows:'data.frame': 1 obs. of 2 variables: 452s ..$ startRow: int 10 452s ..$ endRow : int 7594 452s $ params :List of 5 452s ..$ alpha : num 0.001 452s ..$ undo : num 0 452s ..$ joinSegments : logi TRUE 452s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 452s .. ..$ chromosome: int 1 452s .. ..$ start : num 554484 452s .. ..$ end : num 1.44e+08 452s ..$ seed : int [1:7] 10407 -821273412 -52578226 1415511586 721384351 -665928286 1316562960 452s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 452s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.017 0 0.017 0 0 452s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 452s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 452s - attr(*, "randomSeed")= int [1:7] 10407 -821273412 -52578226 1415511586 721384351 -665928286 1316562960 452s DH segmentation (locally-indexed) rows: 452s startRow endRow 452s 1 10 7594 452s int [1:7599] 1 2 3 4 5 6 7 8 9 10 ... 452s DH segmentation rows: 452s startRow endRow 452s 1 10 7594 452s Segmenting DH signals...done 452s DH segmentation table: 452s dhStart dhEnd dhNbrOfLoci dhMean 452s 1 554484 143926517 2120 0.5101 452s startRow endRow 452s 1 10 7594 452s Rows: 452s [1] 1 452s TCN segmentation rows: 452s startRow endRow 452s 1 1 7599 452s TCN and DH segmentation rows: 452s startRow endRow 452s 1 1 7599 452s startRow endRow 452s 1 10 7594 452s NULL 452s TCN segmentation (expanded) rows: 452s startRow endRow 452s 1 1 7599 452s TCN and DH segmentation rows: 452s startRow endRow 452s 1 1 7599 452s 2 7600 10267 452s 3 10268 14658 452s startRow endRow 452s 1 10 7594 452s startRow endRow 452s 1 1 7599 452s Total CN segmentation table (expanded): 452s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 452s 1 1 554484 143926517 7599 1.3859 2120 2120 452s (TCN,DH) segmentation for one total CN segment: 452s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 452s 1 1 1 1 554484 143926517 7599 1.3859 2120 452s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 452s 1 2120 554484 143926517 2120 0.5101 452s Total CN segment #1 ([ 554484,1.43927e+08]) of 3...done 452s Total CN segment #2 ([1.43927e+08,1.8545e+08]) of 3... 452s Number of TCN loci in segment: 2668 452s Locus data for TCN segment: 452s 'data.frame': 2668 obs. of 9 variables: 452s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 452s $ x : num 1.44e+08 1.44e+08 1.44e+08 1.44e+08 1.44e+08 ... 452s $ CT : num 2.1 2.1 2.09 1.8 2.34 ... 452s $ betaT : num 0.027542 1.030222 1.094093 0.046763 -0.000948 ... 452s $ betaTN : num 0.027542 1.030222 1.094093 0.046763 -0.000948 ... 452s $ betaN : num 0.1624 0.8788 0.8225 0.1201 0.0317 ... 452s $ muN : num 0 1 1 0 0 1 0 0 0 0 ... 452s $ index : int 7600 7601 7602 7603 7604 7605 7606 7607 7608 7609 ... 452s $ rho : num NA NA NA NA NA NA NA NA NA NA ... 452s Number of loci: 2668 452s Number of SNPs: 775 (29.05%) 452s Number of heterozygous SNPs: 775 (100.00%) 452s Chromosome: 1 452s Segmenting DH signals... 452s Segmenting by CBS... 452s Chromosome: 1 452s Random seed temporarily set (seed=c(10407, -821273412, -52578226, 1415511586, 721384351, -665928286, 1316562960), kind="L'Ecuyer-CMRG") 452s Segmenting by CBS...done 452s List of 4 452s $ data :'data.frame': 2668 obs. of 4 variables: 452s ..$ chromosome: int [1:2668] 1 1 1 1 1 1 1 1 1 1 ... 452s ..$ x : num [1:2668] 1.44e+08 1.44e+08 1.44e+08 1.44e+08 1.44e+08 ... 452s ..$ y : num [1:2668] NA NA NA NA NA NA NA NA NA NA ... 452s ..$ index : int [1:2668] 1 2 3 4 5 6 7 8 9 10 ... 452s $ output :'data.frame': 1 obs. of 6 variables: 452s ..$ sampleName: chr NA 452s ..$ chromosome: int 1 452s ..$ start : num 1.44e+08 452s ..$ end : num 1.85e+08 452s ..$ nbrOfLoci : int 775 452s ..$ mean : num 0.097 452s $ segRows:'data.frame': 1 obs. of 2 variables: 452s ..$ startRow: int 15 452s ..$ endRow : int 2664 452s $ params :List of 5 452s ..$ alpha : num 0.001 452s ..$ undo : num 0 452s ..$ joinSegments : logi TRUE 452s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 452s .. ..$ chromosome: int 1 452s .. ..$ start : num 1.44e+08 452s .. ..$ end : num 1.85e+08 452s ..$ seed : int [1:7] 10407 -821273412 -52578226 1415511586 721384351 -665928286 1316562960 452s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 452s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.005 0 0.005 0 0 452s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 452s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 452s - attr(*, "randomSeed")= int [1:7] 10407 -821273412 -52578226 1415511586 721384351 -665928286 1316562960 452s DH segmentation (locally-indexed) rows: 452s startRow endRow 452s 1 15 2664 452s int [1:2668] 7600 7601 7602 7603 7604 7605 7606 7607 7608 7609 ... 452s DH segmentation rows: 452s startRow endRow 452s 1 7614 10263 452s Segmenting DH signals...done 452s DH segmentation table: 452s dhStart dhEnd dhNbrOfLoci dhMean 452s 1 143926517 185449813 775 0.097 452s startRow endRow 452s 1 7614 10263 452s Rows: 452s [1] 2 452s TCN segmentation rows: 452s startRow endRow 452s 2 7600 10267 452s TCN and DH segmentation rows: 452s startRow endRow 452s 2 7600 10267 452s startRow endRow 452s 1 7614 10263 452s startRow endRow 452s 1 1 7599 452s TCN segmentation (expanded) rows: 452s startRow endRow 452s 1 1 7599 452s 2 7600 10267 452s TCN and DH segmentation rows: 452s startRow endRow 452s 1 1 7599 452s 2 7600 10267 452s 3 10268 14658 452s startRow endRow 452s 1 10 7594 452s 2 7614 10263 452s startRow endRow 452s 1 1 7599 452s 2 7600 10267 452s Total CN segmentation table (expanded): 452s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 452s 2 1 143926517 185449813 2668 2.0704 775 775 452s (TCN,DH) segmentation for one total CN segment: 452s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 452s 2 2 1 1 143926517 185449813 2668 2.0704 775 452s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 452s 2 775 143926517 185449813 775 0.097 452s Total CN segment #2 ([1.43927e+08,1.8545e+08]) of 3...done 452s Total CN segment #3 ([1.8545e+08,2.47137e+08]) of 3... 452s Number of TCN loci in segment: 4391 452s Locus data for TCN segment: 452s 'data.frame': 4391 obs. of 9 variables: 452s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 452s $ x : num 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 452s $ CT : num 2.93 2.15 2.82 2.93 2.46 ... 452s $ betaT : num -0.169 0.609 1.028 0.525 0.968 ... 452s $ betaTN : num -0.169 0.609 1.028 0.525 0.968 ... 452s $ betaN : num 0.25 0.38 0.919 0.34 0.783 ... 452s $ muN : num 0 0.5 1 0.5 1 1 0 1 0 1 ... 452s $ index : int 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 452s $ rho : num NA 0.2186 NA 0.0503 NA ... 452s Number of loci: 4391 452s Number of SNPs: 1314 (29.92%) 452s Number of heterozygous SNPs: 1314 (100.00%) 452s Chromosome: 1 452s Segmenting DH signals... 452s Segmenting by CBS... 452s Chromosome: 1 452s Random seed temporarily set (seed=c(10407, -821273412, -52578226, 1415511586, 721384351, -665928286, 1316562960), kind="L'Ecuyer-CMRG") 452s Segmenting by CBS...done 452s List of 4 452s $ data :'data.frame': 4391 obs. of 4 variables: 452s ..$ chromosome: int [1:4391] 1 1 1 1 1 1 1 1 1 1 ... 452s ..$ x : num [1:4391] 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 452s ..$ y : num [1:4391] NA 0.2186 NA 0.0503 NA ... 452s ..$ index : int [1:4391] 1 2 3 4 5 6 7 8 9 10 ... 452s $ output :'data.frame': 1 obs. of 6 variables: 452s ..$ sampleName: chr NA 452s ..$ chromosome: int 1 452s ..$ start : num 1.85e+08 452s ..$ end : num 2.47e+08 452s ..$ nbrOfLoci : int 1314 452s ..$ mean : num 0.23 452s $ segRows:'data.frame': 1 obs. of 2 variables: 452s ..$ startRow: int 2 452s ..$ endRow : int 4388 452s $ params :List of 5 452s ..$ alpha : num 0.001 452s ..$ undo : num 0 452s ..$ joinSegments : logi TRUE 452s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 452s .. ..$ chromosome: int 1 452s .. ..$ start : num 1.85e+08 452s .. ..$ end : num 2.47e+08 452s ..$ seed : int [1:7] 10407 -821273412 -52578226 1415511586 721384351 -665928286 1316562960 452s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 452s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.01 0 0.01 0 0 452s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 452s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 452s - attr(*, "randomSeed")= int [1:7] 10407 -821273412 -52578226 1415511586 721384351 -665928286 1316562960 452s DH segmentation (locally-indexed) rows: 452s startRow endRow 452s 1 2 4388 452s int [1:4391] 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 452s DH segmentation rows: 452s startRow endRow 452s 1 10269 14655 452s Segmenting DH signals...done 452s DH segmentation table: 452s dhStart dhEnd dhNbrOfLoci dhMean 452s 1 185449813 247137334 1314 0.2295 452s startRow endRow 452s 1 10269 14655 452s Rows: 452s [1] 3 452s TCN segmentation rows: 452s startRow endRow 452s 3 10268 14658 452s TCN and DH segmentation rows: 452s startRow endRow 452s 3 10268 14658 452s startRow endRow 452s 1 10269 14655 452s startRow endRow 452s 1 1 7599 452s 2 7600 10267 452s TCN segmentation (expanded) rows: 452s startRow endRow 452s 1 1 7599 452s 2 7600 10267 452s 3 10268 14658 452s TCN and DH segmentation rows: 452s startRow endRow 452s 1 1 7599 452s 2 7600 10267 452s 3 10268 14658 452s startRow endRow 452s 1 10 7594 452s 2 7614 10263 452s 3 10269 14655 452s startRow endRow 452s 1 1 7599 452s 2 7600 10267 452s 3 10268 14658 452s Total CN segmentation table (expanded): 452s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 452s 3 1 185449813 247137334 4391 2.6341 1314 1314 452s (TCN,DH) segmentation for one total CN segment: 452s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 452s 3 3 1 1 185449813 247137334 4391 2.6341 1314 452s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 452s 3 1314 185449813 247137334 1314 0.2295 452s Total CN segment #3 ([1.8545e+08,2.47137e+08]) of 3...done 452s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 452s 1 1 1 1 554484 143926517 7599 1.3859 2120 452s 2 1 2 1 143926517 185449813 2668 2.0704 775 452s 3 1 3 1 185449813 247137334 4391 2.6341 1314 452s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 452s 1 2120 554484 143926517 2120 0.5101 452s 2 775 143926517 185449813 775 0.0970 452s 3 1314 185449813 247137334 1314 0.2295 452s Calculating (C1,C2) per segment... 452s Calculating (C1,C2) per segment...done 452s Number of segments: 3 452s Segmenting paired tumor-normal signals using Paired PSCBS...done 452s Post-segmenting TCNs... 452s Number of segments: 3 452s Number of chromosomes: 1 452s [1] 1 452s Chromosome 1 ('chr01') of 1... 452s Rows: 452s [1] 1 2 3 452s Number of segments: 3 452s TCN segment #1 ('1') of 3... 452s Nothing todo. Only one DH segmentation. Skipping. 452s TCN segment #1 ('1') of 3...done 452s TCN segment #2 ('2') of 3... 452s Nothing todo. Only one DH segmentation. Skipping. 452s TCN segment #2 ('2') of 3...done 452s TCN segment #3 ('3') of 3... 452s Nothing todo. Only one DH segmentation. Skipping. 452s TCN segment #3 ('3') of 3...done 452s Chromosome 1 ('chr01') of 1...done 452s Update (C1,C2) per segment... 452s Update (C1,C2) per segment...done 452s Post-segmenting TCNs...done 452s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 452s 1 1 1 1 554484 143926517 7599 1.3859 2120 452s 2 1 2 1 143926517 185449813 2668 2.0704 775 452s 3 1 3 1 185449813 247137334 4391 2.6341 1314 452s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 452s 1 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 452s 2 775 143926517 185449813 775 0.0970 0.9347856 1.135614 452s 3 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 452s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 452s 1 1 1 1 554484 143926517 7599 1.3859 2120 452s 2 1 2 1 143926517 185449813 2668 2.0704 775 452s 3 1 3 1 185449813 247137334 4391 2.6341 1314 452s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 452s 1 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 452s 2 775 143926517 185449813 775 0.0970 0.9347856 1.135614 452s 3 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 452s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 452s 1 1 1 1 554484 143926517 7599 1.3859 2120 452s 2 1 2 1 143926517 185449813 2668 2.0704 775 452s 3 1 3 1 185449813 247137334 4391 2.6341 1314 452s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 452s 1 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 452s 2 775 143926517 185449813 775 0.0970 0.9347856 1.135614 452s 3 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 452s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 452s 1 1 1 1 554484 143926517 7599 1.3859 2120 452s 2 1 2 1 143926517 185449813 2668 2.0704 775 452s 3 1 3 1 185449813 247137334 4391 2.6341 1314 452s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 452s 1 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 452s 2 775 143926517 185449813 775 0.0970 0.9347856 1.135614 452s 3 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 452s Chromosome #1 ('Chr01') of 3...done 452s Chromosome #2 ('Chr02') of 3... 452s 'data.frame': 14658 obs. of 8 variables: 452s $ chromosome: int 2 2 2 2 2 2 2 2 2 2 ... 452s $ x : num 554484 730720 782343 878522 916294 ... 452s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 452s $ betaT : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 452s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 452s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 452s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 452s $ index : int 14659 14660 14661 14662 14663 14664 14665 14666 14667 14668 ... 452s Known segments: 452s [1] chromosome start end 452s <0 rows> (or 0-length row.names) 452s Segmenting paired tumor-normal signals using Paired PSCBS... 452s Setup up data... 452s 'data.frame': 14658 obs. of 7 variables: 452s $ chromosome: int 2 2 2 2 2 2 2 2 2 2 ... 452s $ x : num 554484 730720 782343 878522 916294 ... 452s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 452s $ betaT : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 452s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 452s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 452s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 452s Setup up data...done 452s Ordering data along genome... 452s 'data.frame': 14658 obs. of 7 variables: 452s $ chromosome: int 2 2 2 2 2 2 2 2 2 2 ... 452s $ x : num 554484 730720 782343 878522 916294 ... 452s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 452s $ betaT : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 452s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 452s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 452s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 452s Ordering data along genome...done 452s Keeping only current chromosome for 'knownSegments'... 452s Chromosome: 2 452s Known segments for this chromosome: 452s [1] chromosome start end 452s <0 rows> (or 0-length row.names) 452s Keeping only current chromosome for 'knownSegments'...done 452s alphaTCN: 0.009 452s alphaDH: 0.001 452s Number of loci: 14658 452s Calculating DHs... 452s Number of SNPs: 14658 452s Number of heterozygous SNPs: 4209 (28.71%) 452s Normalized DHs: 452s num [1:14658] NA NA NA NA NA ... 452s Calculating DHs...done 452s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 452s Produced 2 seeds from this stream for future usage 452s Identification of change points by total copy numbers... 452s Segmenting by CBS... 452s Chromosome: 2 452s Random seed temporarily set (seed=c(10407, -821273412, -52578226, 1415511586, 721384351, -665928286, 1316562960), kind="L'Ecuyer-CMRG") 453s Segmenting by CBS...done 453s List of 4 453s $ data :'data.frame': 14658 obs. of 4 variables: 453s ..$ chromosome: int [1:14658] 2 2 2 2 2 2 2 2 2 2 ... 453s ..$ x : num [1:14658] 554484 730720 782343 878522 916294 ... 453s ..$ y : num [1:14658] 1.88 1.8 1.59 1.64 1.53 ... 453s ..$ index : int [1:14658] 1 2 3 4 5 6 7 8 9 10 ... 453s $ output :'data.frame': 3 obs. of 6 variables: 453s ..$ sampleName: chr [1:3] NA NA NA 453s ..$ chromosome: int [1:3] 2 2 2 453s ..$ start : num [1:3] 5.54e+05 1.44e+08 1.85e+08 453s ..$ end : num [1:3] 1.44e+08 1.85e+08 2.47e+08 453s ..$ nbrOfLoci : int [1:3] 7599 2668 4391 453s ..$ mean : num [1:3] 1.39 2.07 2.63 453s $ segRows:'data.frame': 3 obs. of 2 variables: 453s ..$ startRow: int [1:3] 1 7600 10268 453s ..$ endRow : int [1:3] 7599 10267 14658 453s $ params :List of 5 453s ..$ alpha : num 0.009 453s ..$ undo : num 0 453s ..$ joinSegments : logi TRUE 453s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 453s .. ..$ chromosome: int 2 453s .. ..$ start : num -Inf 453s .. ..$ end : num Inf 453s ..$ seed : int [1:7] 10407 -821273412 -52578226 1415511586 721384351 -665928286 1316562960 453s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 453s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.283 0 0.284 0 0 453s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 453s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 453s - attr(*, "randomSeed")= int [1:7] 10407 -821273412 -52578226 1415511586 721384351 -665928286 1316562960 453s Identification of change points by total copy numbers...done 453s Restructure TCN segmentation results... 453s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean 453s 1 2 554484 143926517 7599 1.3859 453s 2 2 143926517 185449813 2668 2.0704 453s 3 2 185449813 247137334 4391 2.6341 453s Number of TCN segments: 3 453s Restructure TCN segmentation results...done 453s Total CN segment #1 ([ 554484,1.43927e+08]) of 3... 453s Number of TCN loci in segment: 7599 453s Locus data for TCN segment: 453s 'data.frame': 7599 obs. of 9 variables: 453s $ chromosome: int 2 2 2 2 2 2 2 2 2 2 ... 453s $ x : num 554484 730720 782343 878522 916294 ... 453s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 453s $ betaT : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 453s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 453s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 453s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 453s $ index : int 1 2 3 4 5 6 7 8 9 10 ... 453s $ rho : num NA NA NA NA NA ... 453s Number of loci: 7599 453s Number of SNPs: 2120 (27.90%) 453s Number of heterozygous SNPs: 2120 (100.00%) 453s Chromosome: 2 453s Segmenting DH signals... 453s Segmenting by CBS... 453s Chromosome: 2 453s Random seed temporarily set (seed=c(10407, -1924040949, -1632234809, -437763632, -1464377300, 676654412, 2080370711), kind="L'Ecuyer-CMRG") 453s Segmenting by CBS...done 453s List of 4 453s $ data :'data.frame': 7599 obs. of 4 variables: 453s ..$ chromosome: int [1:7599] 2 2 2 2 2 2 2 2 2 2 ... 453s ..$ x : num [1:7599] 554484 730720 782343 878522 916294 ... 453s ..$ y : num [1:7599] NA NA NA NA NA ... 453s ..$ index : int [1:7599] 1 2 3 4 5 6 7 8 9 10 ... 453s $ output :'data.frame': 1 obs. of 6 variables: 453s ..$ sampleName: chr NA 453s ..$ chromosome: int 2 453s ..$ start : num 554484 453s ..$ end : num 1.44e+08 453s ..$ nbrOfLoci : int 2120 453s ..$ mean : num 0.51 453s $ segRows:'data.frame': 1 obs. of 2 variables: 453s ..$ startRow: int 10 453s ..$ endRow : int 7594 453s $ params :List of 5 453s ..$ alpha : num 0.001 453s ..$ undo : num 0 453s ..$ joinSegments : logi TRUE 453s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 453s .. ..$ chromosome: int 2 453s .. ..$ start : num 554484 453s .. ..$ end : num 1.44e+08 453s ..$ seed : int [1:7] 10407 -1924040949 -1632234809 -437763632 -1464377300 676654412 2080370711 453s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 453s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.017 0 0.017 0 0 453s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 453s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 453s - attr(*, "randomSeed")= int [1:7] 10407 -1924040949 -1632234809 -437763632 -1464377300 676654412 2080370711 453s DH segmentation (locally-indexed) rows: 453s startRow endRow 453s 1 10 7594 453s int [1:7599] 1 2 3 4 5 6 7 8 9 10 ... 453s DH segmentation rows: 453s startRow endRow 453s 1 10 7594 453s Segmenting DH signals...done 453s DH segmentation table: 453s dhStart dhEnd dhNbrOfLoci dhMean 453s 1 554484 143926517 2120 0.5101 453s startRow endRow 453s 1 10 7594 453s Rows: 453s [1] 1 453s TCN segmentation rows: 453s startRow endRow 453s 1 1 7599 453s TCN and DH segmentation rows: 453s startRow endRow 453s 1 1 7599 453s startRow endRow 453s 1 10 7594 453s NULL 453s TCN segmentation (expanded) rows: 453s startRow endRow 453s 1 1 7599 453s TCN and DH segmentation rows: 453s startRow endRow 453s 1 1 7599 453s 2 7600 10267 453s 3 10268 14658 453s startRow endRow 453s 1 10 7594 453s startRow endRow 453s 1 1 7599 453s Total CN segmentation table (expanded): 453s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 453s 1 2 554484 143926517 7599 1.3859 2120 2120 453s (TCN,DH) segmentation for one total CN segment: 453s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 453s 1 1 1 2 554484 143926517 7599 1.3859 2120 453s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 453s 1 2120 554484 143926517 2120 0.5101 453s Total CN segment #1 ([ 554484,1.43927e+08]) of 3...done 453s Total CN segment #2 ([1.43927e+08,1.8545e+08]) of 3... 453s Number of TCN loci in segment: 2668 453s Locus data for TCN segment: 453s 'data.frame': 2668 obs. of 9 variables: 453s $ chromosome: int 2 2 2 2 2 2 2 2 2 2 ... 453s $ x : num 1.44e+08 1.44e+08 1.44e+08 1.44e+08 1.44e+08 ... 453s $ CT : num 2.1 2.1 2.09 1.8 2.34 ... 453s $ betaT : num 0.027542 1.030222 1.094093 0.046763 -0.000948 ... 453s $ betaTN : num 0.027542 1.030222 1.094093 0.046763 -0.000948 ... 453s $ betaN : num 0.1624 0.8788 0.8225 0.1201 0.0317 ... 453s $ muN : num 0 1 1 0 0 1 0 0 0 0 ... 453s $ index : int 7600 7601 7602 7603 7604 7605 7606 7607 7608 7609 ... 453s $ rho : num NA NA NA NA NA NA NA NA NA NA ... 453s Number of loci: 2668 453s Number of SNPs: 775 (29.05%) 453s Number of heterozygous SNPs: 775 (100.00%) 453s Chromosome: 2 453s Segmenting DH signals... 453s Segmenting by CBS... 453s Chromosome: 2 453s Random seed temporarily set (seed=c(10407, -1924040949, -1632234809, -437763632, -1464377300, 676654412, 2080370711), kind="L'Ecuyer-CMRG") 453s Segmenting by CBS...done 453s List of 4 453s $ data :'data.frame': 2668 obs. of 4 variables: 453s ..$ chromosome: int [1:2668] 2 2 2 2 2 2 2 2 2 2 ... 453s ..$ x : num [1:2668] 1.44e+08 1.44e+08 1.44e+08 1.44e+08 1.44e+08 ... 453s ..$ y : num [1:2668] NA NA NA NA NA NA NA NA NA NA ... 453s ..$ index : int [1:2668] 1 2 3 4 5 6 7 8 9 10 ... 453s $ output :'data.frame': 1 obs. of 6 variables: 453s ..$ sampleName: chr NA 453s ..$ chromosome: int 2 453s ..$ start : num 1.44e+08 453s ..$ end : num 1.85e+08 453s ..$ nbrOfLoci : int 775 453s ..$ mean : num 0.097 453s $ segRows:'data.frame': 1 obs. of 2 variables: 453s ..$ startRow: int 15 453s ..$ endRow : int 2664 453s $ params :List of 5 453s ..$ alpha : num 0.001 453s ..$ undo : num 0 453s ..$ joinSegments : logi TRUE 453s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 453s .. ..$ chromosome: int 2 453s .. ..$ start : num 1.44e+08 453s .. ..$ end : num 1.85e+08 453s ..$ seed : int [1:7] 10407 -1924040949 -1632234809 -437763632 -1464377300 676654412 2080370711 453s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 453s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.005 0 0.006 0 0 453s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 453s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 453s - attr(*, "randomSeed")= int [1:7] 10407 -1924040949 -1632234809 -437763632 -1464377300 676654412 2080370711 453s DH segmentation (locally-indexed) rows: 453s startRow endRow 453s 1 15 2664 453s int [1:2668] 7600 7601 7602 7603 7604 7605 7606 7607 7608 7609 ... 453s DH segmentation rows: 453s startRow endRow 453s 1 7614 10263 453s Segmenting DH signals...done 453s DH segmentation table: 453s dhStart dhEnd dhNbrOfLoci dhMean 453s 1 143926517 185449813 775 0.097 453s startRow endRow 453s 1 7614 10263 453s Rows: 453s [1] 2 453s TCN segmentation rows: 453s startRow endRow 453s 2 7600 10267 453s TCN and DH segmentation rows: 453s startRow endRow 453s 2 7600 10267 453s startRow endRow 453s 1 7614 10263 453s startRow endRow 453s 1 1 7599 453s TCN segmentation (expanded) rows: 453s startRow endRow 453s 1 1 7599 453s 2 7600 10267 453s TCN and DH segmentation rows: 453s startRow endRow 453s 1 1 7599 453s 2 7600 10267 453s 3 10268 14658 453s startRow endRow 453s 1 10 7594 453s 2 7614 10263 453s startRow endRow 453s 1 1 7599 453s 2 7600 10267 453s Total CN segmentation table (expanded): 453s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 453s 2 2 143926517 185449813 2668 2.0704 775 775 453s (TCN,DH) segmentation for one total CN segment: 453s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 453s 2 2 1 2 143926517 185449813 2668 2.0704 775 453s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 453s 2 775 143926517 185449813 775 0.097 453s Total CN segment #2 ([1.43927e+08,1.8545e+08]) of 3...done 453s Total CN segment #3 ([1.8545e+08,2.47137e+08]) of 3... 453s Number of TCN loci in segment: 4391 453s Locus data for TCN segment: 453s 'data.frame': 4391 obs. of 9 variables: 453s $ chromosome: int 2 2 2 2 2 2 2 2 2 2 ... 453s $ x : num 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 453s $ CT : num 2.93 2.15 2.82 2.93 2.46 ... 453s $ betaT : num -0.169 0.609 1.028 0.525 0.968 ... 453s $ betaTN : num -0.169 0.609 1.028 0.525 0.968 ... 453s $ betaN : num 0.25 0.38 0.919 0.34 0.783 ... 453s $ muN : num 0 0.5 1 0.5 1 1 0 1 0 1 ... 453s $ index : int 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 453s $ rho : num NA 0.2186 NA 0.0503 NA ... 453s Number of loci: 4391 453s Number of SNPs: 1314 (29.92%) 453s Number of heterozygous SNPs: 1314 (100.00%) 453s Chromosome: 2 453s Segmenting DH signals... 453s Segmenting by CBS... 453s Chromosome: 2 453s Random seed temporarily set (seed=c(10407, -1924040949, -1632234809, -437763632, -1464377300, 676654412, 2080370711), kind="L'Ecuyer-CMRG") 453s Segmenting by CBS...done 453s List of 4 453s $ data :'data.frame': 4391 obs. of 4 variables: 453s ..$ chromosome: int [1:4391] 2 2 2 2 2 2 2 2 2 2 ... 453s ..$ x : num [1:4391] 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 453s ..$ y : num [1:4391] NA 0.2186 NA 0.0503 NA ... 453s ..$ index : int [1:4391] 1 2 3 4 5 6 7 8 9 10 ... 453s $ output :'data.frame': 1 obs. of 6 variables: 453s ..$ sampleName: chr NA 453s ..$ chromosome: int 2 453s ..$ start : num 1.85e+08 453s ..$ end : num 2.47e+08 453s ..$ nbrOfLoci : int 1314 453s ..$ mean : num 0.23 453s $ segRows:'data.frame': 1 obs. of 2 variables: 453s ..$ startRow: int 2 453s ..$ endRow : int 4388 453s $ params :List of 5 453s ..$ alpha : num 0.001 453s ..$ undo : num 0 453s ..$ joinSegments : logi TRUE 453s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 453s .. ..$ chromosome: int 2 453s .. ..$ start : num 1.85e+08 453s .. ..$ end : num 2.47e+08 453s ..$ seed : int [1:7] 10407 -1924040949 -1632234809 -437763632 -1464377300 676654412 2080370711 453s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 453s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.009 0 0.01 0 0 453s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 453s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 453s - attr(*, "randomSeed")= int [1:7] 10407 -1924040949 -1632234809 -437763632 -1464377300 676654412 2080370711 453s DH segmentation (locally-indexed) rows: 453s startRow endRow 453s 1 2 4388 453s int [1:4391] 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 453s DH segmentation rows: 453s startRow endRow 453s 1 10269 14655 453s Segmenting DH signals...done 453s DH segmentation table: 453s dhStart dhEnd dhNbrOfLoci dhMean 453s 1 185449813 247137334 1314 0.2295 453s startRow endRow 453s 1 10269 14655 453s Rows: 453s [1] 3 453s TCN segmentation rows: 453s startRow endRow 453s 3 10268 14658 453s TCN and DH segmentation rows: 453s startRow endRow 453s 3 10268 14658 453s startRow endRow 453s 1 10269 14655 453s startRow endRow 453s 1 1 7599 453s 2 7600 10267 453s TCN segmentation (expanded) rows: 453s startRow endRow 453s 1 1 7599 453s 2 7600 10267 453s 3 10268 14658 453s TCN and DH segmentation rows: 453s startRow endRow 453s 1 1 7599 453s 2 7600 10267 453s 3 10268 14658 453s startRow endRow 453s 1 10 7594 453s 2 7614 10263 453s 3 10269 14655 453s startRow endRow 453s 1 1 7599 453s 2 7600 10267 453s 3 10268 14658 453s Total CN segmentation table (expanded): 453s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 453s 3 2 185449813 247137334 4391 2.6341 1314 1314 453s (TCN,DH) segmentation for one total CN segment: 453s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 453s 3 3 1 2 185449813 247137334 4391 2.6341 1314 453s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 453s 3 1314 185449813 247137334 1314 0.2295 453s Total CN segment #3 ([1.8545e+08,2.47137e+08]) of 3...done 453s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 453s 1 2 1 1 554484 143926517 7599 1.3859 2120 453s 2 2 2 1 143926517 185449813 2668 2.0704 775 453s 3 2 3 1 185449813 247137334 4391 2.6341 1314 453s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 453s 1 2120 554484 143926517 2120 0.5101 453s 2 775 143926517 185449813 775 0.0970 453s 3 1314 185449813 247137334 1314 0.2295 453s Calculating (C1,C2) per segment... 453s Calculating (C1,C2) per segment...done 453s Number of segments: 3 453s Segmenting paired tumor-normal signals using Paired PSCBS...done 453s Post-segmenting TCNs... 453s Number of segments: 3 453s Number of chromosomes: 1 453s [1] 2 453s Chromosome 1 ('chr02') of 1... 453s Rows: 453s [1] 1 2 3 453s Number of segments: 3 453s TCN segment #1 ('1') of 3... 453s Nothing todo. Only one DH segmentation. Skipping. 453s TCN segment #1 ('1') of 3...done 453s TCN segment #2 ('2') of 3... 453s Nothing todo. Only one DH segmentation. Skipping. 453s TCN segment #2 ('2') of 3...done 453s TCN segment #3 ('3') of 3... 453s Nothing todo. Only one DH segmentation. Skipping. 453s TCN segment #3 ('3') of 3...done 453s Chromosome 1 ('chr02') of 1...done 453s Update (C1,C2) per segment... 453s Update (C1,C2) per segment...done 453s Post-segmenting TCNs...done 453s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 453s 1 2 1 1 554484 143926517 7599 1.3859 2120 453s 2 2 2 1 143926517 185449813 2668 2.0704 775 453s 3 2 3 1 185449813 247137334 4391 2.6341 1314 453s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 453s 1 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 453s 2 775 143926517 185449813 775 0.0970 0.9347856 1.135614 453s 3 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 453s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 453s 1 2 1 1 554484 143926517 7599 1.3859 2120 453s 2 2 2 1 143926517 185449813 2668 2.0704 775 453s 3 2 3 1 185449813 247137334 4391 2.6341 1314 453s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 453s 1 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 453s 2 775 143926517 185449813 775 0.0970 0.9347856 1.135614 453s 3 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 453s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 453s 1 2 1 1 554484 143926517 7599 1.3859 2120 453s 2 2 2 1 143926517 185449813 2668 2.0704 775 453s 3 2 3 1 185449813 247137334 4391 2.6341 1314 453s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 453s 1 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 453s 2 775 143926517 185449813 775 0.0970 0.9347856 1.135614 453s 3 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 453s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 453s 1 2 1 1 554484 143926517 7599 1.3859 2120 453s 2 2 2 1 143926517 185449813 2668 2.0704 775 453s 3 2 3 1 185449813 247137334 4391 2.6341 1314 453s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 453s 1 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 453s 2 775 143926517 185449813 775 0.0970 0.9347856 1.135614 453s 3 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 453s Chromosome #2 ('Chr02') of 3...done 453s Chromosome #3 ('Chr03') of 3... 453s 'data.frame': 14658 obs. of 8 variables: 453s $ chromosome: int 3 3 3 3 3 3 3 3 3 3 ... 453s $ x : num 554484 730720 782343 878522 916294 ... 453s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 453s $ betaT : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 453s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 453s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 453s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 453s $ index : int 29317 29318 29319 29320 29321 29322 29323 29324 29325 29326 ... 453s Known segments: 453s [1] chromosome start end 453s <0 rows> (or 0-length row.names) 453s Segmenting paired tumor-normal signals using Paired PSCBS... 453s Setup up data... 453s 'data.frame': 14658 obs. of 7 variables: 453s $ chromosome: int 3 3 3 3 3 3 3 3 3 3 ... 453s $ x : num 554484 730720 782343 878522 916294 ... 453s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 453s $ betaT : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 453s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 453s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 453s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 453s Setup up data...done 453s Ordering data along genome... 453s 'data.frame': 14658 obs. of 7 variables: 453s $ chromosome: int 3 3 3 3 3 3 3 3 3 3 ... 453s $ x : num 554484 730720 782343 878522 916294 ... 453s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 453s $ betaT : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 453s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 453s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 453s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 453s Ordering data along genome...done 453s Keeping only current chromosome for 'knownSegments'... 453s Chromosome: 3 453s Known segments for this chromosome: 453s [1] chromosome start end 453s <0 rows> (or 0-length row.names) 453s Keeping only current chromosome for 'knownSegments'...done 453s alphaTCN: 0.009 453s alphaDH: 0.001 453s Number of loci: 14658 453s Calculating DHs... 453s Number of SNPs: 14658 453s Number of heterozygous SNPs: 4209 (28.71%) 453s Normalized DHs: 453s num [1:14658] NA NA NA NA NA ... 453s Calculating DHs...done 453s Random seed temporarily set (seed=c(10407, -821273412, -52578226, 1415511586, 721384351, -665928286, 1316562960), kind="L'Ecuyer-CMRG") 453s Produced 2 seeds from this stream for future usage 453s Identification of change points by total copy numbers... 453s Segmenting by CBS... 453s Chromosome: 3 453s Random seed temporarily set (seed=c(10407, -1924040949, -1632234809, -437763632, -1464377300, 676654412, 2080370711), kind="L'Ecuyer-CMRG") 453s Segmenting by CBS...done 453s List of 4 453s $ data :'data.frame': 14658 obs. of 4 variables: 453s ..$ chromosome: int [1:14658] 3 3 3 3 3 3 3 3 3 3 ... 453s ..$ x : num [1:14658] 554484 730720 782343 878522 916294 ... 453s ..$ y : num [1:14658] 1.88 1.8 1.59 1.64 1.53 ... 453s ..$ index : int [1:14658] 1 2 3 4 5 6 7 8 9 10 ... 453s $ output :'data.frame': 3 obs. of 6 variables: 453s ..$ sampleName: chr [1:3] NA NA NA 453s ..$ chromosome: int [1:3] 3 3 3 453s ..$ start : num [1:3] 5.54e+05 1.44e+08 1.85e+08 453s ..$ end : num [1:3] 1.44e+08 1.85e+08 2.47e+08 453s ..$ nbrOfLoci : int [1:3] 7599 2668 4391 453s ..$ mean : num [1:3] 1.39 2.07 2.63 453s $ segRows:'data.frame': 3 obs. of 2 variables: 453s ..$ startRow: int [1:3] 1 7600 10268 453s ..$ endRow : int [1:3] 7599 10267 14658 453s $ params :List of 5 453s ..$ alpha : num 0.009 453s ..$ undo : num 0 453s ..$ joinSegments : logi TRUE 453s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 453s .. ..$ chromosome: int 3 453s .. ..$ start : num -Inf 453s .. ..$ end : num Inf 453s ..$ seed : int [1:7] 10407 -1924040949 -1632234809 -437763632 -1464377300 676654412 2080370711 453s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 453s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.252 0 0.252 0 0 453s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 453s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 453s - attr(*, "randomSeed")= int [1:7] 10407 -1924040949 -1632234809 -437763632 -1464377300 676654412 2080370711 453s Identification of change points by total copy numbers...done 453s Restructure TCN segmentation results... 453s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean 453s 1 3 554484 143926517 7599 1.3859 453s 2 3 143926517 185449813 2668 2.0704 453s 3 3 185449813 247137334 4391 2.6341 453s Number of TCN segments: 3 453s Restructure TCN segmentation results...done 453s Total CN segment #1 ([ 554484,1.43927e+08]) of 3... 453s Number of TCN loci in segment: 7599 453s Locus data for TCN segment: 453s 'data.frame': 7599 obs. of 9 variables: 453s $ chromosome: int 3 3 3 3 3 3 3 3 3 3 ... 453s $ x : num 554484 730720 782343 878522 916294 ... 453s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 453s $ betaT : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 453s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 453s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 453s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 453s $ index : int 1 2 3 4 5 6 7 8 9 10 ... 453s $ rho : num NA NA NA NA NA ... 453s Number of loci: 7599 453s Number of SNPs: 2120 (27.90%) 453s Number of heterozygous SNPs: 2120 (100.00%) 453s Chromosome: 3 453s Segmenting DH signals... 453s Segmenting by CBS... 453s Chromosome: 3 453s Random seed temporarily set (seed=c(10407, -1371615447, -889757879, 1692656974, -1723952224, 1378814990, 1816467252), kind="L'Ecuyer-CMRG") 453s Segmenting by CBS...done 453s List of 4 453s $ data :'data.frame': 7599 obs. of 4 variables: 453s ..$ chromosome: int [1:7599] 3 3 3 3 3 3 3 3 3 3 ... 453s ..$ x : num [1:7599] 554484 730720 782343 878522 916294 ... 453s ..$ y : num [1:7599] NA NA NA NA NA ... 453s ..$ index : int [1:7599] 1 2 3 4 5 6 7 8 9 10 ... 453s $ output :'data.frame': 1 obs. of 6 variables: 453s ..$ sampleName: chr NA 453s ..$ chromosome: int 3 453s ..$ start : num 554484 453s ..$ end : num 1.44e+08 453s ..$ nbrOfLoci : int 2120 453s ..$ mean : num 0.51 453s $ segRows:'data.frame': 1 obs. of 2 variables: 453s ..$ startRow: int 10 453s ..$ endRow : int 7594 453s $ params :List of 5 453s ..$ alpha : num 0.001 453s ..$ undo : num 0 453s ..$ joinSegments : logi TRUE 453s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 453s .. ..$ chromosome: int 3 453s .. ..$ start : num 554484 453s .. ..$ end : num 1.44e+08 453s ..$ seed : int [1:7] 10407 -1371615447 -889757879 1692656974 -1723952224 1378814990 1816467252 453s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 453s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.018 0 0.017 0 0 453s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 453s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 453s - attr(*, "randomSeed")= int [1:7] 10407 -1371615447 -889757879 1692656974 -1723952224 1378814990 1816467252 453s DH segmentation (locally-indexed) rows: 453s startRow endRow 453s 1 10 7594 453s int [1:7599] 1 2 3 4 5 6 7 8 9 10 ... 453s DH segmentation rows: 453s startRow endRow 453s 1 10 7594 453s Segmenting DH signals...done 453s DH segmentation table: 453s dhStart dhEnd dhNbrOfLoci dhMean 453s 1 554484 143926517 2120 0.5101 453s startRow endRow 453s 1 10 7594 453s Rows: 453s [1] 1 453s TCN segmentation rows: 453s startRow endRow 453s 1 1 7599 453s TCN and DH segmentation rows: 453s startRow endRow 453s 1 1 7599 453s startRow endRow 453s 1 10 7594 453s NULL 453s TCN segmentation (expanded) rows: 453s startRow endRow 453s 1 1 7599 453s TCN and DH segmentation rows: 453s startRow endRow 453s 1 1 7599 453s 2 7600 10267 453s 3 10268 14658 453s startRow endRow 453s 1 10 7594 453s startRow endRow 453s 1 1 7599 453s Total CN segmentation table (expanded): 453s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 453s 1 3 554484 143926517 7599 1.3859 2120 2120 453s (TCN,DH) segmentation for one total CN segment: 453s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 453s 1 1 1 3 554484 143926517 7599 1.3859 2120 453s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 453s 1 2120 554484 143926517 2120 0.5101 453s Total CN segment #1 ([ 554484,1.43927e+08]) of 3...done 453s Total CN segment #2 ([1.43927e+08,1.8545e+08]) of 3... 453s Number of TCN loci in segment: 2668 453s Locus data for TCN segment: 453s 'data.frame': 2668 obs. of 9 variables: 453s $ chromosome: int 3 3 3 3 3 3 3 3 3 3 ... 453s $ x : num 1.44e+08 1.44e+08 1.44e+08 1.44e+08 1.44e+08 ... 453s $ CT : num 2.1 2.1 2.09 1.8 2.34 ... 453s $ betaT : num 0.027542 1.030222 1.094093 0.046763 -0.000948 ... 453s $ betaTN : num 0.027542 1.030222 1.094093 0.046763 -0.000948 ... 453s $ betaN : num 0.1624 0.8788 0.8225 0.1201 0.0317 ... 453s $ muN : num 0 1 1 0 0 1 0 0 0 0 ... 453s $ index : int 7600 7601 7602 7603 7604 7605 7606 7607 7608 7609 ... 453s $ rho : num NA NA NA NA NA NA NA NA NA NA ... 453s Number of loci: 2668 453s Number of SNPs: 775 (29.05%) 453s Number of heterozygous SNPs: 775 (100.00%) 453s Chromosome: 3 453s Segmenting DH signals... 453s Segmenting by CBS... 453s Chromosome: 3 453s Random seed temporarily set (seed=c(10407, -1371615447, -889757879, 1692656974, -1723952224, 1378814990, 1816467252), kind="L'Ecuyer-CMRG") 453s Segmenting by CBS...done 453s List of 4 453s $ data :'data.frame': 2668 obs. of 4 variables: 453s ..$ chromosome: int [1:2668] 3 3 3 3 3 3 3 3 3 3 ... 453s ..$ x : num [1:2668] 1.44e+08 1.44e+08 1.44e+08 1.44e+08 1.44e+08 ... 453s ..$ y : num [1:2668] NA NA NA NA NA NA NA NA NA NA ... 453s ..$ index : int [1:2668] 1 2 3 4 5 6 7 8 9 10 ... 453s $ output :'data.frame': 1 obs. of 6 variables: 453s ..$ sampleName: chr NA 453s ..$ chromosome: int 3 453s ..$ start : num 1.44e+08 453s ..$ end : num 1.85e+08 453s ..$ nbrOfLoci : int 775 453s ..$ mean : num 0.097 453s $ segRows:'data.frame': 1 obs. of 2 variables: 453s ..$ startRow: int 15 453s ..$ endRow : int 2664 453s $ params :List of 5 453s ..$ alpha : num 0.001 453s ..$ undo : num 0 453s ..$ joinSegments : logi TRUE 453s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 453s .. ..$ chromosome: int 3 453s .. ..$ start : num 1.44e+08 453s .. ..$ end : num 1.85e+08 453s ..$ seed : int [1:7] 10407 -1371615447 -889757879 1692656974 -1723952224 1378814990 1816467252 453s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 453s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.005 0 0.005 0 0 453s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 453s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 453s - attr(*, "randomSeed")= int [1:7] 10407 -1371615447 -889757879 1692656974 -1723952224 1378814990 1816467252 453s DH segmentation (locally-indexed) rows: 453s startRow endRow 453s 1 15 2664 453s int [1:2668] 7600 7601 7602 7603 7604 7605 7606 7607 7608 7609 ... 453s DH segmentation rows: 453s startRow endRow 453s 1 7614 10263 453s Segmenting DH signals...done 453s DH segmentation table: 453s dhStart dhEnd dhNbrOfLoci dhMean 453s 1 143926517 185449813 775 0.097 453s startRow endRow 453s 1 7614 10263 453s Rows: 453s [1] 2 453s TCN segmentation rows: 453s startRow endRow 453s 2 7600 10267 453s TCN and DH segmentation rows: 453s startRow endRow 453s 2 7600 10267 453s startRow endRow 453s 1 7614 10263 453s startRow endRow 453s 1 1 7599 453s TCN segmentation (expanded) rows: 453s startRow endRow 453s 1 1 7599 453s 2 7600 10267 453s TCN and DH segmentation rows: 453s startRow endRow 453s 1 1 7599 453s 2 7600 10267 453s 3 10268 14658 453s startRow endRow 453s 1 10 7594 453s 2 7614 10263 453s startRow endRow 453s 1 1 7599 453s 2 7600 10267 453s Total CN segmentation table (expanded): 453s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 453s 2 3 143926517 185449813 2668 2.0704 775 775 453s (TCN,DH) segmentation for one total CN segment: 453s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 453s 2 2 1 3 143926517 185449813 2668 2.0704 775 453s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 453s 2 775 143926517 185449813 775 0.097 453s Total CN segment #2 ([1.43927e+08,1.8545e+08]) of 3...done 453s Total CN segment #3 ([1.8545e+08,2.47137e+08]) of 3... 453s Number of TCN loci in segment: 4391 453s Locus data for TCN segment: 453s 'data.frame': 4391 obs. of 9 variables: 453s $ chromosome: int 3 3 3 3 3 3 3 3 3 3 ... 453s $ x : num 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 453s $ CT : num 2.93 2.15 2.82 2.93 2.46 ... 453s $ betaT : num -0.169 0.609 1.028 0.525 0.968 ... 453s $ betaTN : num -0.169 0.609 1.028 0.525 0.968 ... 453s $ betaN : num 0.25 0.38 0.919 0.34 0.783 ... 453s $ muN : num 0 0.5 1 0.5 1 1 0 1 0 1 ... 453s $ index : int 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 453s $ rho : num NA 0.2186 NA 0.0503 NA ... 453s Number of loci: 4391 453s Number of SNPs: 1314 (29.92%) 453s Number of heterozygous SNPs: 1314 (100.00%) 453s Chromosome: 3 453s Segmenting DH signals... 453s Segmenting by CBS... 453s Chromosome: 3 453s Random seed temporarily set (seed=c(10407, -1371615447, -889757879, 1692656974, -1723952224, 1378814990, 1816467252), kind="L'Ecuyer-CMRG") 453s Segmenting by CBS...done 453s List of 4 453s $ data :'data.frame': 4391 obs. of 4 variables: 453s ..$ chromosome: int [1:4391] 3 3 3 3 3 3 3 3 3 3 ... 453s ..$ x : num [1:4391] 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 453s ..$ y : num [1:4391] NA 0.2186 NA 0.0503 NA ... 453s ..$ index : int [1:4391] 1 2 3 4 5 6 7 8 9 10 ... 453s $ output :'data.frame': 1 obs. of 6 variables: 453s ..$ sampleName: chr NA 453s ..$ chromosome: int 3 453s ..$ start : num 1.85e+08 453s ..$ end : num 2.47e+08 453s ..$ nbrOfLoci : int 1314 453s ..$ mean : num 0.23 453s $ segRows:'data.frame': 1 obs. of 2 variables: 453s ..$ startRow: int 2 453s ..$ endRow : int 4388 453s $ params :List of 5 453s ..$ alpha : num 0.001 453s ..$ undo : num 0 453s ..$ joinSegments : logi TRUE 453s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 453s .. ..$ chromosome: int 3 453s .. ..$ start : num 1.85e+08 453s .. ..$ end : num 2.47e+08 453s ..$ seed : int [1:7] 10407 -1371615447 -889757879 1692656974 -1723952224 1378814990 1816467252 453s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 453s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.01 0 0.009 0 0 453s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 453s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 453s - attr(*, "randomSeed")= int [1:7] 10407 -1371615447 -889757879 1692656974 -1723952224 1378814990 1816467252 453s DH segmentation (locally-indexed) rows: 453s startRow endRow 453s 1 2 4388 453s int [1:4391] 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 453s DH segmentation rows: 453s startRow endRow 453s 1 10269 14655 453s Segmenting DH signals...done 453s DH segmentation table: 453s dhStart dhEnd dhNbrOfLoci dhMean 453s 1 185449813 247137334 1314 0.2295 453s startRow endRow 453s 1 10269 14655 453s Rows: 453s [1] 3 453s TCN segmentation rows: 453s startRow endRow 453s 3 10268 14658 453s TCN and DH segmentation rows: 453s startRow endRow 453s 3 10268 14658 453s startRow endRow 453s 1 10269 14655 453s startRow endRow 453s 1 1 7599 453s 2 7600 10267 453s TCN segmentation (expanded) rows: 453s startRow endRow 453s 1 1 7599 453s 2 7600 10267 453s 3 10268 14658 453s TCN and DH segmentation rows: 453s startRow endRow 453s 1 1 7599 453s 2 7600 10267 453s 3 10268 14658 453s startRow endRow 453s 1 10 7594 453s 2 7614 10263 453s 3 10269 14655 453s startRow endRow 453s 1 1 7599 453s 2 7600 10267 453s 3 10268 14658 453s Total CN segmentation table (expanded): 453s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 453s 3 3 185449813 247137334 4391 2.6341 1314 1314 453s (TCN,DH) segmentation for one total CN segment: 453s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 453s 3 3 1 3 185449813 247137334 4391 2.6341 1314 453s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 453s 3 1314 185449813 247137334 1314 0.2295 453s Total CN segment #3 ([1.8545e+08,2.47137e+08]) of 3...done 453s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 453s 1 3 1 1 554484 143926517 7599 1.3859 2120 453s 2 3 2 1 143926517 185449813 2668 2.0704 775 453s 3 3 3 1 185449813 247137334 4391 2.6341 1314 453s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 453s 1 2120 554484 143926517 2120 0.5101 453s 2 775 143926517 185449813 775 0.0970 453s 3 1314 185449813 247137334 1314 0.2295 453s Calculating (C1,C2) per segment... 453s Calculating (C1,C2) per segment...done 453s Number of segments: 3 453s Segmenting paired tumor-normal signals using Paired PSCBS...done 453s Post-segmenting TCNs... 453s Number of segments: 3 453s Number of chromosomes: 1 453s [1] 3 453s Chromosome 1 ('chr03') of 1... 453s Rows: 453s [1] 1 2 3 453s Number of segments: 3 453s TCN segment #1 ('1') of 3... 453s Nothing todo. Only one DH segmentation. Skipping. 453s TCN segment #1 ('1') of 3...done 453s TCN segment #2 ('2') of 3... 453s Nothing todo. Only one DH segmentation. Skipping. 453s TCN segment #2 ('2') of 3...done 453s TCN segment #3 ('3') of 3... 453s Nothing todo. Only one DH segmentation. Skipping. 453s TCN segment #3 ('3') of 3...done 453s Chromosome 1 ('chr03') of 1...done 453s Update (C1,C2) per segment... 453s Update (C1,C2) per segment...done 453s Post-segmenting TCNs...done 453s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 453s 1 3 1 1 554484 143926517 7599 1.3859 2120 453s 2 3 2 1 143926517 185449813 2668 2.0704 775 453s 3 3 3 1 185449813 247137334 4391 2.6341 1314 453s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 453s 1 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 453s 2 775 143926517 185449813 775 0.0970 0.9347856 1.135614 453s 3 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 453s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 453s 1 3 1 1 554484 143926517 7599 1.3859 2120 453s 2 3 2 1 143926517 185449813 2668 2.0704 775 453s 3 3 3 1 185449813 247137334 4391 2.6341 1314 453s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 453s 1 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 453s 2 775 143926517 185449813 775 0.0970 0.9347856 1.135614 453s 3 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 453s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 453s 1 3 1 1 554484 143926517 7599 1.3859 2120 453s 2 3 2 1 143926517 185449813 2668 2.0704 775 453s 3 3 3 1 185449813 247137334 4391 2.6341 1314 453s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 453s 1 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 453s 2 775 143926517 185449813 775 0.0970 0.9347856 1.135614 453s 3 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 453s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 453s 1 3 1 1 554484 143926517 7599 1.3859 2120 453s 2 3 2 1 143926517 185449813 2668 2.0704 775 453s 3 3 3 1 185449813 247137334 4391 2.6341 1314 453s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 453s 1 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 453s 2 775 143926517 185449813 775 0.0970 0.9347856 1.135614 453s 3 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 453s Chromosome #3 ('Chr03') of 3...done 453s Merging (independently) segmented chromosome... 453s List of 5 453s $ data :Classes ‘PairedPSCNData’ and 'data.frame': 43974 obs. of 8 variables: 453s ..$ chromosome: int [1:43974] 1 1 1 1 1 1 1 1 1 1 ... 453s ..$ x : num [1:43974] 554484 730720 782343 878522 916294 ... 453s ..$ CT : num [1:43974] 1.88 1.8 1.59 1.64 1.53 ... 453s ..$ betaT : num [1:43974] 0.0646 0.1672 0.9284 0.113 0.7209 ... 453s ..$ betaTN : num [1:43974] -0.0515 -0.1172 1.0194 0.031 0.8604 ... 453s ..$ betaN : num [1:43974] 0.116 0.284 0.909 0.082 0.86 ... 453s ..$ muN : num [1:43974] 0 0 1 0 1 1 1 0 1 0.5 ... 453s ..$ rho : num [1:43974] NA NA NA NA NA ... 453s $ output :Classes ‘PairedPSCNSegments’ and 'data.frame': 11 obs. of 15 variables: 453s ..$ chromosome : int [1:11] 1 1 1 NA 2 2 2 NA 3 3 ... 453s ..$ tcnId : int [1:11] 1 2 3 NA 1 2 3 NA 1 2 ... 453s ..$ dhId : int [1:11] 1 1 1 NA 1 1 1 NA 1 1 ... 453s ..$ tcnStart : num [1:11] 5.54e+05 1.44e+08 1.85e+08 NA 5.54e+05 ... 453s ..$ tcnEnd : num [1:11] 1.44e+08 1.85e+08 2.47e+08 NA 1.44e+08 ... 453s ..$ tcnNbrOfLoci: int [1:11] 7599 2668 4391 NA 7599 2668 4391 NA 7599 2668 ... 453s ..$ tcnMean : num [1:11] 1.39 2.07 2.63 NA 1.39 ... 453s ..$ tcnNbrOfSNPs: int [1:11] 2120 775 1314 NA 2120 775 1314 NA 2120 775 ... 453s ..$ tcnNbrOfHets: int [1:11] 2120 775 1314 NA 2120 775 1314 NA 2120 775 ... 453s ..$ dhStart : num [1:11] 5.54e+05 1.44e+08 1.85e+08 NA 5.54e+05 ... 453s ..$ dhEnd : num [1:11] 1.44e+08 1.85e+08 2.47e+08 NA 1.44e+08 ... 453s ..$ dhNbrOfLoci : int [1:11] 2120 775 1314 NA 2120 775 1314 NA 2120 775 ... 453s ..$ dhMean : num [1:11] 0.51 0.097 0.23 NA 0.51 ... 453s ..$ c1Mean : num [1:11] 0.339 0.935 1.015 NA 0.339 ... 453s ..$ c2Mean : num [1:11] 1.05 1.14 1.62 NA 1.05 ... 453s $ tcnSegRows:'data.frame': 11 obs. of 2 variables: 453s ..$ startRow: int [1:11] 1 7600 10268 NA 14659 22258 24926 NA 29317 36916 ... 453s ..$ endRow : int [1:11] 7599 10267 14658 NA 22257 24925 29316 NA 36915 39583 ... 453s $ dhSegRows :'data.frame': 11 obs. of 2 variables: 453s ..$ startRow: int [1:11] 10 7614 10269 NA 14668 22272 24927 NA 29326 36930 ... 453s ..$ endRow : int [1:11] 7594 10263 14655 NA 22252 24921 29313 NA 36910 39579 ... 453s $ params :List of 7 453s ..$ alphaTCN : num 0.009 453s ..$ alphaDH : num 0.001 453s ..$ flavor : chr "tcn&dh" 453s ..$ tbn : logi FALSE 453s ..$ joinSegments : logi TRUE 453s ..$ knownSegments:'data.frame': 0 obs. of 3 variables: 453s .. ..$ chromosome: int(0) 453s .. ..$ start : int(0) 453s .. ..$ end : int(0) 453s ..$ seed : int [1:7] 10407 1066287653 -51199871 161854402 -1995183193 1503453565 -747102133 453s - attr(*, "class")= chr [1:3] "PairedPSCBS" "PSCBS" "AbstractCBS" 453s Merging (independently) segmented chromosome...done 453s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 453s 1 1 1 1 554484 143926517 7599 1.3859 2120 453s 2 1 2 1 143926517 185449813 2668 2.0704 775 453s 3 1 3 1 185449813 247137334 4391 2.6341 1314 453s 4 NA NA NA NA NA NA NA NA 453s 5 2 1 1 554484 143926517 7599 1.3859 2120 453s 6 2 2 1 143926517 185449813 2668 2.0704 775 453s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 453s 1 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 453s 2 775 143926517 185449813 775 0.0970 0.9347856 1.135614 453s 3 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 453s 4 NA NA NA NA NA NA NA 453s 5 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 453s 6 775 143926517 185449813 775 0.0970 0.9347856 1.135614 453s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 453s 6 2 2 1 143926517 185449813 2668 2.0704 775 453s 7 2 3 1 185449813 247137334 4391 2.6341 1314 453s 8 NA NA NA NA NA NA NA NA 453s 9 3 1 1 554484 143926517 7599 1.3859 2120 453s 10 3 2 1 143926517 185449813 2668 2.0704 775 453s 11 3 3 1 185449813 247137334 4391 2.6341 1314 453s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 453s 6 775 143926517 185449813 775 0.0970 0.9347856 1.135614 453s 7 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 453s 8 NA NA NA NA NA NA NA 453s 9 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 453s 10 775 143926517 185449813 775 0.0970 0.9347856 1.135614 453s 11 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 453s Segmenting multiple chromosomes...done 453s Segmenting paired tumor-normal signals using Paired PSCBS...done 453s - segmentByPairedPSCBS() using 'multisession' futures ... 454s Segmenting paired tumor-normal signals using Paired PSCBS... 454s Calling genotypes from normal allele B fractions... 454s num [1:44010] 0.8274 0.5072 0.1671 0.1609 0.0421 ... 454s Called genotypes: 454s num [1:44010] 1 0.5 0 0 0 0 1 0 1 0.5 ... 454s - attr(*, "modelFit")=List of 1 454s ..$ :List of 7 454s .. ..$ flavor : chr "density" 454s .. ..$ cn : int 2 454s .. ..$ nbrOfGenotypeGroups: int 3 454s .. ..$ tau : num [1:2] 0.312 0.678 454s .. ..$ n : int 43920 454s .. ..$ fit :Classes ‘PeaksAndValleys’ and 'data.frame': 5 obs. of 3 variables: 454s .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 454s .. .. ..$ x : num [1:5] 0.0999 0.312 0.4986 0.6775 0.8922 454s .. .. ..$ density: num [1:5] 1.622 0.465 1.125 0.496 1.587 454s .. ..$ fitValleys :Classes ‘PeaksAndValleys’ and 'data.frame': 2 obs. of 3 variables: 454s .. .. ..$ type : chr [1:2] "valley" "valley" 454s .. .. ..$ x : num [1:2] 0.312 0.678 454s .. .. ..$ density: num [1:2] 0.465 0.496 454s ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 454s muN 454s 0 0.5 1 454s 15627 12633 15750 454s Calling genotypes from normal allele B fractions...done 454s Normalizing betaT using betaN (TumorBoost)... 454s Normalized BAFs: 454s num [1:44010] 0.9301 0.1667 0.0685 0.0995 0.0155 ... 454s - attr(*, "modelFit")=List of 5 454s ..$ method : chr "normalizeTumorBoost" 454s ..$ flavor : chr "v4" 454s ..$ delta : num [1:44010] -0.17264 0.00239 0.1671 0.16085 0.04213 ... 454s .. ..- attr(*, "modelFit")=List of 1 454s .. .. ..$ :List of 7 454s .. .. .. ..$ flavor : chr "density" 454s .. .. .. ..$ cn : int 2 454s .. .. .. ..$ nbrOfGenotypeGroups: int 3 454s .. .. .. ..$ tau : num [1:2] 0.312 0.678 454s .. .. .. ..$ n : int 43920 454s .. .. .. ..$ fit :Classes ‘PeaksAndValleys’ and 'data.frame': 5 obs. of 3 variables: 454s .. .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 454s .. .. .. .. ..$ x : num [1:5] 0.0999 0.312 0.4986 0.6775 0.8922 454s .. .. .. .. ..$ density: num [1:5] 1.622 0.465 1.125 0.496 1.587 454s .. .. .. ..$ fitValleys :Classes ‘PeaksAndValleys’ and 'data.frame': 2 obs. of 3 variables: 454s .. .. .. .. ..$ type : chr [1:2] "valley" "valley" 454s .. .. .. .. ..$ x : num [1:2] 0.312 0.678 454s .. .. .. .. ..$ density: num [1:2] 0.465 0.496 454s .. .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 454s ..$ preserveScale: logi FALSE 454s ..$ scaleFactor : num NA 454s Normalizing betaT using betaN (TumorBoost)...done 454s Setup up data... 454s 'data.frame': 44010 obs. of 7 variables: 454s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 454s $ x : num 1145994 2941694 3710825 4240737 4276892 ... 454s $ CT : num 1.63 1.4 1.41 1.17 1.16 ... 454s $ betaT : num 0.7574 0.169 0.2357 0.2604 0.0576 ... 454s $ betaTN : num 0.9301 0.1667 0.0685 0.0995 0.0155 ... 454s ..- attr(*, "modelFit")=List of 5 454s .. ..$ method : chr "normalizeTumorBoost" 454s .. ..$ flavor : chr "v4" 454s .. ..$ delta : num [1:44010] -0.17264 0.00239 0.1671 0.16085 0.04213 ... 454s .. .. ..- attr(*, "modelFit")=List of 1 454s .. .. .. ..$ :List of 7 454s .. .. .. .. ..$ flavor : chr "density" 454s .. .. .. .. ..$ cn : int 2 454s .. .. .. .. ..$ nbrOfGenotypeGroups: int 3 454s .. .. .. .. ..$ tau : num [1:2] 0.312 0.678 454s .. .. .. .. ..$ n : int 43920 454s .. .. .. .. ..$ fit :Classes ‘PeaksAndValleys’ and 'data.frame': 5 obs. of 3 variables: 454s .. .. .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 454s .. .. .. .. .. ..$ x : num [1:5] 0.0999 0.312 0.4986 0.6775 0.8922 454s .. .. .. .. .. ..$ density: num [1:5] 1.622 0.465 1.125 0.496 1.587 454s .. .. .. .. ..$ fitValleys :Classes ‘PeaksAndValleys’ and 'data.frame': 2 obs. of 3 variables: 454s .. .. .. .. .. ..$ type : chr [1:2] "valley" "valley" 454s .. .. .. .. .. ..$ x : num [1:2] 0.312 0.678 454s .. .. .. .. .. ..$ density: num [1:2] 0.465 0.496 454s .. .. .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 454s .. ..$ preserveScale: logi FALSE 454s .. ..$ scaleFactor : num NA 454s $ betaN : num 0.8274 0.5072 0.1671 0.1609 0.0421 ... 454s $ muN : num 1 0.5 0 0 0 0 1 0 1 0.5 ... 454s ..- attr(*, "modelFit")=List of 1 454s .. ..$ :List of 7 454s .. .. ..$ flavor : chr "density" 454s .. .. ..$ cn : int 2 454s .. .. ..$ nbrOfGenotypeGroups: int 3 454s .. .. ..$ tau : num [1:2] 0.312 0.678 454s .. .. ..$ n : int 43920 454s .. .. ..$ fit :Classes ‘PeaksAndValleys’ and 'data.frame': 5 obs. of 3 variables: 454s .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 454s .. .. .. ..$ x : num [1:5] 0.0999 0.312 0.4986 0.6775 0.8922 454s .. .. .. ..$ density: num [1:5] 1.622 0.465 1.125 0.496 1.587 454s .. .. ..$ fitValleys :Classes ‘PeaksAndValleys’ and 'data.frame': 2 obs. of 3 variables: 454s .. .. .. ..$ type : chr [1:2] "valley" "valley" 454s .. .. .. ..$ x : num [1:2] 0.312 0.678 454s .. .. .. ..$ density: num [1:2] 0.465 0.496 454s .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 454s Setup up data...done 454s Dropping loci for which TCNs are missing... 454s Number of loci dropped: 36 454s Dropping loci for which TCNs are missing...done 454s Ordering data along genome... 454s 'data.frame': 43974 obs. of 7 variables: 454s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 454s $ x : num 554484 730720 782343 878522 916294 ... 454s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 454s $ betaT : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 454s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 454s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 454s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 454s Ordering data along genome...done 454s Segmenting multiple chromosomes... 454s Number of chromosomes: 3 454s Random seed temporarily set (seed=c(48879), kind="L'Ecuyer-CMRG") 454s Produced 3 seeds from this stream for future usage 454s Chromosome #1 ('Chr01') of 3... 454s 'data.frame': 14658 obs. of 8 variables: 454s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 454s $ x : num 554484 730720 782343 878522 916294 ... 454s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 454s $ betaT : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 454s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 454s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 454s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 454s $ index : int 1 2 3 4 5 6 7 8 9 10 ... 454s Known segments: 454s [1] chromosome start end 454s <0 rows> (or 0-length row.names) 454s Chromosome #1 ('Chr01') of 3...done 454s Chromosome #2 ('Chr02') of 3... 454s 'data.frame': 14658 obs. of 8 variables: 454s $ chromosome: int 2 2 2 2 2 2 2 2 2 2 ... 454s $ x : num 554484 730720 782343 878522 916294 ... 454s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 454s $ betaT : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 454s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 454s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 454s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 454s $ index : int 14659 14660 14661 14662 14663 14664 14665 14666 14667 14668 ... 454s Known segments: 454s [1] chromosome start end 454s <0 rows> (or 0-length row.names) 454s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 455s Chromosome #2 ('Chr02') of 3...done 455s Chromosome #3 ('Chr03') of 3... 455s Segmenting by CBS...done 455s 'data.frame': 14658 obs. of 8 variables: 455s $ chromosome: int 3 3 3 3 3 3 3 3 3 3 ... 455s $ x : num 554484 730720 782343 878522 916294 ... 455s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 455s $ betaT : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 455s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 455s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 455s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 455s $ index : int 29317 29318 29319 29320 29321 29322 29323 29324 29325 29326 ... 455s Known segments: 455s [1] chromosome start end 455s <0 rows> (or 0-length row.names) 455s List of 4 455s $ data :'data.frame': 14658 obs. of 4 variables: 455s ..$ chromosome: int [1:14658] 1 1 1 1 1 1 1 1 1 1 ... 455s ..$ x : num [1:14658] 554484 730720 782343 878522 916294 ... 455s ..$ y : num [1:14658] 1.88 1.8 1.59 1.64 1.53 ... 455s ..$ index : int [1:14658] 1 2 3 4 5 6 7 8 9 10 ... 455s $ output :'data.frame': 3 obs. of 6 variables: 455s ..$ sampleName: chr [1:3] NA NA NA 455s ..$ chromosome: int [1:3] 1 1 1 455s ..$ start : num [1:3] 5.54e+05 1.44e+08 1.85e+08 455s ..$ end : num [1:3] 1.44e+08 1.85e+08 2.47e+08 455s ..$ nbrOfLoci : int [1:3] 7599 2668 4391 455s ..$ mean : num [1:3] 1.39 2.07 2.63 455s $ segRows:'data.frame': 3 obs. of 2 variables: 455s ..$ startRow: int [1:3] 1 7600 10268 455s ..$ endRow : int [1:3] 7599 10267 14658 455s $ params :List of 5 455s ..$ alpha : num 0.009 455s ..$ undo : num 0 455s ..$ joinSegments : logi TRUE 455s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 455s .. ..$ chromosome: int 1 455s .. ..$ start : num -Inf 455s .. ..$ end : num Inf 455s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 455s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 455s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.245 0 0.247 0 0 455s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 455s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 455s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 455s Identification of change points by total copy numbers...done 455s Restructure TCN segmentation results... 455s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean 455s 1 1 554484 143926517 7599 1.3859 455s 2 1 143926517 185449813 2668 2.0704 455s 3 1 185449813 247137334 4391 2.6341 455s Number of TCN segments: 3 455s Restructure TCN segmentation results...done 455s Total CN segment #1 ([ 554484,1.43927e+08]) of 3... 455s Number of TCN loci in segment: 7599 455s Locus data for TCN segment: 455s 'data.frame': 7599 obs. of 9 variables: 455s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 455s $ x : num 554484 730720 782343 878522 916294 ... 455s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 455s $ betaT : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 455s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 455s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 455s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 455s $ index : int 1 2 3 4 5 6 7 8 9 10 ... 455s $ rho : num NA NA NA NA NA ... 455s Number of loci: 7599 455s Number of SNPs: 2120 (27.90%) 455s Number of heterozygous SNPs: 2120 (100.00%) 455s Chromosome: 1 455s Segmenting DH signals... 455s Segmenting by CBS... 455s Chromosome: 1 455s Random seed temporarily set (seed=c(10407, -821273412, -52578226, 1415511586, 721384351, -665928286, 1316562960), kind="L'Ecuyer-CMRG") 455s Segmenting by CBS...done 455s List of 4 455s $ data :'data.frame': 7599 obs. of 4 variables: 455s ..$ chromosome: int [1:7599] 1 1 1 1 1 1 1 1 1 1 ... 455s ..$ x : num [1:7599] 554484 730720 782343 878522 916294 ... 455s ..$ y : num [1:7599] NA NA NA NA NA ... 455s ..$ index : int [1:7599] 1 2 3 4 5 6 7 8 9 10 ... 455s $ output :'data.frame': 1 obs. of 6 variables: 455s ..$ sampleName: chr NA 455s ..$ chromosome: int 1 455s ..$ start : num 554484 455s ..$ end : num 1.44e+08 455s ..$ nbrOfLoci : int 2120 455s ..$ mean : num 0.51 455s $ segRows:'data.frame': 1 obs. of 2 variables: 455s ..$ startRow: int 10 455s ..$ endRow : int 7594 455s $ params :List of 5 455s ..$ alpha : num 0.001 455s ..$ undo : num 0 455s ..$ joinSegments : logi TRUE 455s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 455s .. ..$ chromosome: int 1 455s .. ..$ start : num 554484 455s .. ..$ end : num 1.44e+08 455s ..$ seed : int [1:7] 10407 -821273412 -52578226 1415511586 721384351 -665928286 1316562960 455s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 455s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.017 0 0.017 0 0 455s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 455s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 455s - attr(*, "randomSeed")= int [1:7] 10407 -821273412 -52578226 1415511586 721384351 -665928286 1316562960 455s DH segmentation (locally-indexed) rows: 455s startRow endRow 455s 1 10 7594 455s int [1:7599] 1 2 3 4 5 6 7 8 9 10 ... 455s DH segmentation rows: 455s startRow endRow 455s 1 10 7594 455s Segmenting DH signals...done 455s DH segmentation table: 455s dhStart dhEnd dhNbrOfLoci dhMean 455s 1 554484 143926517 2120 0.5101 455s startRow endRow 455s 1 10 7594 455s Rows: 455s [1] 1 455s TCN segmentation rows: 455s startRow endRow 455s 1 1 7599 455s TCN and DH segmentation rows: 455s startRow endRow 455s 1 1 7599 455s startRow endRow 455s 1 10 7594 455s NULL 455s TCN segmentation (expanded) rows: 455s startRow endRow 455s 1 1 7599 455s TCN and DH segmentation rows: 455s startRow endRow 455s 1 1 7599 455s 2 7600 10267 455s 3 10268 14658 455s startRow endRow 455s 1 10 7594 455s startRow endRow 455s 1 1 7599 455s Total CN segmentation table (expanded): 455s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 455s 1 1 554484 143926517 7599 1.3859 2120 2120 455s (TCN,DH) segmentation for one total CN segment: 455s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 455s 1 1 1 1 554484 143926517 7599 1.3859 2120 455s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 455s 1 2120 554484 143926517 2120 0.5101 455s Total CN segment #1 ([ 554484,1.43927e+08]) of 3...done 455s Total CN segment #2 ([1.43927e+08,1.8545e+08]) of 3... 455s Number of TCN loci in segment: 2668 455s Locus data for TCN segment: 455s 'data.frame': 2668 obs. of 9 variables: 455s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 455s $ x : num 1.44e+08 1.44e+08 1.44e+08 1.44e+08 1.44e+08 ... 455s $ CT : num 2.1 2.1 2.09 1.8 2.34 ... 455s $ betaT : num 0.027542 1.030222 1.094093 0.046763 -0.000948 ... 455s $ betaTN : num 0.027542 1.030222 1.094093 0.046763 -0.000948 ... 455s $ betaN : num 0.1624 0.8788 0.8225 0.1201 0.0317 ... 455s $ muN : num 0 1 1 0 0 1 0 0 0 0 ... 455s $ index : int 7600 7601 7602 7603 7604 7605 7606 7607 7608 7609 ... 455s $ rho : num NA NA NA NA NA NA NA NA NA NA ... 455s Number of loci: 2668 455s Number of SNPs: 775 (29.05%) 455s Number of heterozygous SNPs: 775 (100.00%) 455s Chromosome: 1 455s Segmenting DH signals... 455s Segmenting by CBS... 455s Chromosome: 1 455s Random seed temporarily set (seed=c(10407, -821273412, -52578226, 1415511586, 721384351, -665928286, 1316562960), kind="L'Ecuyer-CMRG") 455s Segmenting by CBS...done 455s List of 4 455s $ data :'data.frame': 2668 obs. of 4 variables: 455s ..$ chromosome: int [1:2668] 1 1 1 1 1 1 1 1 1 1 ... 455s ..$ x : num [1:2668] 1.44e+08 1.44e+08 1.44e+08 1.44e+08 1.44e+08 ... 455s ..$ y : num [1:2668] NA NA NA NA NA NA NA NA NA NA ... 455s ..$ index : int [1:2668] 1 2 3 4 5 6 7 8 9 10 ... 455s $ output :'data.frame': 1 obs. of 6 variables: 455s ..$ sampleName: chr NA 455s ..$ chromosome: int 1 455s ..$ start : num 1.44e+08 455s ..$ end : num 1.85e+08 455s ..$ nbrOfLoci : int 775 455s ..$ mean : num 0.097 455s $ segRows:'data.frame': 1 obs. of 2 variables: 455s ..$ startRow: int 15 455s ..$ endRow : int 2664 455s $ params :List of 5 455s ..$ alpha : num 0.001 455s ..$ undo : num 0 455s ..$ joinSegments : logi TRUE 455s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 455s .. ..$ chromosome: int 1 455s .. ..$ start : num 1.44e+08 455s .. ..$ end : num 1.85e+08 455s ..$ seed : int [1:7] 10407 -821273412 -52578226 1415511586 721384351 -665928286 1316562960 455s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 455s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.005 0 0.005 0 0 455s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 455s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 455s - attr(*, "randomSeed")= int [1:7] 10407 -821273412 -52578226 1415511586 721384351 -665928286 1316562960 455s DH segmentation (locally-indexed) rows: 455s startRow endRow 455s 1 15 2664 455s int [1:2668] 7600 7601 7602 7603 7604 7605 7606 7607 7608 7609 ... 455s DH segmentation rows: 455s startRow endRow 455s 1 7614 10263 455s Segmenting DH signals...done 455s DH segmentation table: 455s dhStart dhEnd dhNbrOfLoci dhMean 455s 1 143926517 185449813 775 0.097 455s startRow endRow 455s 1 7614 10263 455s Rows: 455s [1] 2 455s TCN segmentation rows: 455s startRow endRow 455s 2 7600 10267 455s TCN and DH segmentation rows: 455s startRow endRow 455s 2 7600 10267 455s startRow endRow 455s 1 7614 10263 455s startRow endRow 455s 1 1 7599 455s TCN segmentation (expanded) rows: 455s startRow endRow 455s 1 1 7599 455s 2 7600 10267 455s TCN and DH segmentation rows: 455s startRow endRow 455s 1 1 7599 455s 2 7600 10267 455s 3 10268 14658 455s startRow endRow 455s 1 10 7594 455s 2 7614 10263 455s startRow endRow 455s 1 1 7599 455s 2 7600 10267 455s Total CN segmentation table (expanded): 455s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 455s 2 1 143926517 185449813 2668 2.0704 775 775 455s (TCN,DH) segmentation for one total CN segment: 455s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 455s 2 2 1 1 143926517 185449813 2668 2.0704 775 455s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 455s 2 775 143926517 185449813 775 0.097 455s Total CN segment #2 ([1.43927e+08,1.8545e+08]) of 3...done 455s Total CN segment #3 ([1.8545e+08,2.47137e+08]) of 3... 455s Number of TCN loci in segment: 4391 455s Locus data for TCN segment: 455s Random seed temporarily set (seed=c(10407, -821273412, -52578226, 1415511586, 721384351, -665928286, 1316562960), kind="L'Ecuyer-CMRG") 455s 'data.frame': 4391 obs. of 9 variables: 455s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 455s $ x : num 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 455s $ CT : num 2.93 2.15 2.82 2.93 2.46 ... 455s $ betaT : num -0.169 0.609 1.028 0.525 0.968 ... 455s $ betaTN : num -0.169 0.609 1.028 0.525 0.968 ... 455s $ betaN : num 0.25 0.38 0.919 0.34 0.783 ... 455s $ muN : num 0 0.5 1 0.5 1 1 0 1 0 1 ... 455s $ index : int 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 455s $ rho : num NA 0.2186 NA 0.0503 NA ... 455s Number of loci: 4391 455s Number of SNPs: 1314 (29.92%) 455s Number of heterozygous SNPs: 1314 (100.00%) 455s Chromosome: 1 455s Segmenting DH signals... 455s Segmenting by CBS... 455s Chromosome: 1 455s Random seed temporarily set (seed=c(10407, -821273412, -52578226, 1415511586, 721384351, -665928286, 1316562960), kind="L'Ecuyer-CMRG") 455s Segmenting by CBS...done 455s List of 4 455s $ data :'data.frame': 4391 obs. of 4 variables: 455s ..$ chromosome: int [1:4391] 1 1 1 1 1 1 1 1 1 1 ... 455s ..$ x : num [1:4391] 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 455s ..$ y : num [1:4391] NA 0.2186 NA 0.0503 NA ... 455s ..$ index : int [1:4391] 1 2 3 4 5 6 7 8 9 10 ... 455s $ output :'data.frame': 1 obs. of 6 variables: 455s ..$ sampleName: chr NA 455s ..$ chromosome: int 1 455s ..$ start : num 1.85e+08 455s ..$ end : num 2.47e+08 455s ..$ nbrOfLoci : int 1314 455s ..$ mean : num 0.23 455s $ segRows:'data.frame': 1 obs. of 2 variables: 455s ..$ startRow: int 2 455s ..$ endRow : int 4388 455s $ params :List of 5 455s ..$ alpha : num 0.001 455s ..$ undo : num 0 455s ..$ joinSegments : logi TRUE 455s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 455s .. ..$ chromosome: int 1 455s .. ..$ start : num 1.85e+08 455s .. ..$ end : num 2.47e+08 455s ..$ seed : int [1:7] 10407 -821273412 -52578226 1415511586 721384351 -665928286 1316562960 455s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 455s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.009 0 0.009 0 0 455s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 455s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 455s - attr(*, "randomSeed")= int [1:7] 10407 -821273412 -52578226 1415511586 721384351 -665928286 1316562960 455s DH segmentation (locally-indexed) rows: 455s startRow endRow 455s 1 2 4388 455s int [1:4391] 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 455s DH segmentation rows: 455s startRow endRow 455s 1 10269 14655 455s Segmenting DH signals...done 455s DH segmentation table: 455s dhStart dhEnd dhNbrOfLoci dhMean 455s 1 185449813 247137334 1314 0.2295 455s startRow endRow 455s 1 10269 14655 455s Rows: 455s [1] 3 455s TCN segmentation rows: 455s startRow endRow 455s 3 10268 14658 455s TCN and DH segmentation rows: 455s startRow endRow 455s 3 10268 14658 455s startRow endRow 455s 1 10269 14655 455s startRow endRow 455s 1 1 7599 455s 2 7600 10267 455s TCN segmentation (expanded) rows: 455s startRow endRow 455s 1 1 7599 455s 2 7600 10267 455s 3 10268 14658 455s TCN and DH segmentation rows: 455s startRow endRow 455s 1 1 7599 455s 2 7600 10267 455s 3 10268 14658 455s startRow endRow 455s 1 10 7594 455s 2 7614 10263 455s 3 10269 14655 455s startRow endRow 455s 1 1 7599 455s 2 7600 10267 455s 3 10268 14658 455s Total CN segmentation table (expanded): 455s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 455s 3 1 185449813 247137334 4391 2.6341 1314 1314 455s (TCN,DH) segmentation for one total CN segment: 455s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 455s 3 3 1 1 185449813 247137334 4391 2.6341 1314 455s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 455s 3 1314 185449813 247137334 1314 0.2295 455s Total CN segment #3 ([1.8545e+08,2.47137e+08]) of 3...done 455s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 455s 1 1 1 1 554484 143926517 7599 1.3859 2120 455s 2 1 2 1 143926517 185449813 2668 2.0704 775 455s 3 1 3 1 185449813 247137334 4391 2.6341 1314 455s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 455s 1 2120 554484 143926517 2120 0.5101 455s 2 775 143926517 185449813 775 0.0970 455s 3 1314 185449813 247137334 1314 0.2295 455s Calculating (C1,C2) per segment... 455s Calculating (C1,C2) per segment...done 455s Number of segments: 3 455s Segmenting paired tumor-normal signals using Paired PSCBS...done 455s Post-segmenting TCNs... 455s Number of segments: 3 455s Number of chromosomes: 1 455s [1] 1 455s Chromosome 1 ('chr01') of 1... 455s Rows: 455s [1] 1 2 3 455s Number of segments: 3 455s TCN segment #1 ('1') of 3... 455s Nothing todo. Only one DH segmentation. Skipping. 455s TCN segment #1 ('1') of 3...done 455s TCN segment #2 ('2') of 3... 455s Nothing todo. Only one DH segmentation. Skipping. 455s TCN segment #2 ('2') of 3...done 455s TCN segment #3 ('3') of 3... 455s Nothing todo. Only one DH segmentation. Skipping. 455s TCN segment #3 ('3') of 3...done 455s Chromosome 1 ('chr01') of 1...done 455s Update (C1,C2) per segment... 455s Update (C1,C2) per segment...done 455s Post-segmenting TCNs...done 455s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 455s 1 1 1 1 554484 143926517 7599 1.3859 2120 455s 2 1 2 1 143926517 185449813 2668 2.0704 775 455s 3 1 3 1 185449813 247137334 4391 2.6341 1314 455s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 455s 1 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 455s 2 775 143926517 185449813 775 0.0970 0.9347856 1.135614 455s 3 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 455s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 455s 1 1 1 1 554484 143926517 7599 1.3859 2120 455s 2 1 2 1 143926517 185449813 2668 2.0704 775 455s 3 1 3 1 185449813 247137334 4391 2.6341 1314 455s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 455s 1 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 455s 2 775 143926517 185449813 775 0.0970 0.9347856 1.135614 455s 3 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 455s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 455s 1 1 1 1 554484 143926517 7599 1.3859 2120 455s 2 1 2 1 143926517 185449813 2668 2.0704 775 455s 3 1 3 1 185449813 247137334 4391 2.6341 1314 455s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 455s 1 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 455s 2 775 143926517 185449813 775 0.0970 0.9347856 1.135614 455s 3 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 455s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 455s 1 1 1 1 554484 143926517 7599 1.3859 2120 455s 2 1 2 1 143926517 185449813 2668 2.0704 775 455s 3 1 3 1 185449813 247137334 4391 2.6341 1314 455s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 455s 1 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 455s 2 775 143926517 185449813 775 0.0970 0.9347856 1.135614 455s 3 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 455s Chromosome #3 ('Chr03') of 3...done 455s Merging (independently) segmented chromosome... 455s Segmenting by CBS...done 455s List of 4 455s $ data :'data.frame': 14658 obs. of 4 variables: 455s ..$ chromosome: int [1:14658] 2 2 2 2 2 2 2 2 2 2 ... 455s ..$ x : num [1:14658] 554484 730720 782343 878522 916294 ... 455s ..$ y : num [1:14658] 1.88 1.8 1.59 1.64 1.53 ... 455s ..$ index : int [1:14658] 1 2 3 4 5 6 7 8 9 10 ... 455s $ output :'data.frame': 3 obs. of 6 variables: 455s ..$ sampleName: chr [1:3] NA NA NA 455s ..$ chromosome: int [1:3] 2 2 2 455s ..$ start : num [1:3] 5.54e+05 1.44e+08 1.85e+08 455s ..$ end : num [1:3] 1.44e+08 1.85e+08 2.47e+08 455s ..$ nbrOfLoci : int [1:3] 7599 2668 4391 455s ..$ mean : num [1:3] 1.39 2.07 2.63 455s $ segRows:'data.frame': 3 obs. of 2 variables: 455s ..$ startRow: int [1:3] 1 7600 10268 455s ..$ endRow : int [1:3] 7599 10267 14658 455s $ params :List of 5 455s ..$ alpha : num 0.009 455s ..$ undo : num 0 455s ..$ joinSegments : logi TRUE 455s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 455s .. ..$ chromosome: int 2 455s .. ..$ start : num -Inf 455s .. ..$ end : num Inf 455s ..$ seed : int [1:7] 10407 -821273412 -52578226 1415511586 721384351 -665928286 1316562960 455s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 455s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.28 0.002 0.288 0 0 455s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 455s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 455s - attr(*, "randomSeed")= int [1:7] 10407 -821273412 -52578226 1415511586 721384351 -665928286 1316562960 455s Identification of change points by total copy numbers...done 455s Restructure TCN segmentation results... 455s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean 455s 1 2 554484 143926517 7599 1.3859 455s 2 2 143926517 185449813 2668 2.0704 455s 3 2 185449813 247137334 4391 2.6341 455s Number of TCN segments: 3 455s Restructure TCN segmentation results...done 455s Total CN segment #1 ([ 554484,1.43927e+08]) of 3... 455s Number of TCN loci in segment: 7599 455s Locus data for TCN segment: 455s 'data.frame': 7599 obs. of 9 variables: 455s $ chromosome: int 2 2 2 2 2 2 2 2 2 2 ... 455s $ x : num 554484 730720 782343 878522 916294 ... 455s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 455s $ betaT : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 455s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 455s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 455s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 455s $ index : int 1 2 3 4 5 6 7 8 9 10 ... 455s $ rho : num NA NA NA NA NA ... 455s Number of loci: 7599 455s Number of SNPs: 2120 (27.90%) 455s Number of heterozygous SNPs: 2120 (100.00%) 455s Chromosome: 2 455s Segmenting DH signals... 455s Segmenting by CBS... 455s Chromosome: 2 455s Random seed temporarily set (seed=c(10407, -1924040949, -1632234809, -437763632, -1464377300, 676654412, 2080370711), kind="L'Ecuyer-CMRG") 455s Segmenting paired tumor-normal signals using Paired PSCBS... 455s Setup up data... 455s 'data.frame': 14658 obs. of 7 variables: 455s $ chromosome: int 3 3 3 3 3 3 3 3 3 3 ... 455s $ x : num 554484 730720 782343 878522 916294 ... 455s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 455s $ betaT : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 455s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 455s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 455s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 455s Setup up data...done 455s Ordering data along genome... 455s 'data.frame': 14658 obs. of 7 variables: 455s $ chromosome: int 3 3 3 3 3 3 3 3 3 3 ... 455s $ x : num 554484 730720 782343 878522 916294 ... 455s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 455s $ betaT : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 455s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 455s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 455s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 455s Ordering data along genome...done 455s Keeping only current chromosome for 'knownSegments'... 455s Chromosome: 3 455s Known segments for this chromosome: 455s [1] chromosome start end 455s <0 rows> (or 0-length row.names) 455s Keeping only current chromosome for 'knownSegments'...done 455s alphaTCN: 0.009 455s alphaDH: 0.001 455s Number of loci: 14658 455s Calculating DHs... 455s Number of SNPs: 14658 455s Number of heterozygous SNPs: 4209 (28.71%) 455s Normalized DHs: 455s num [1:14658] NA NA NA NA NA ... 455s Calculating DHs...done 455s Random seed temporarily set (seed=c(10407, -821273412, -52578226, 1415511586, 721384351, -665928286, 1316562960), kind="L'Ecuyer-CMRG") 455s Produced 2 seeds from this stream for future usage 455s Identification of change points by total copy numbers... 455s Segmenting by CBS... 455s Segmenting by CBS...done 455s Chromosome: 3 455s List of 4 455s $ data :'data.frame': 7599 obs. of 4 variables: 455s ..$ chromosome: int [1:7599] 2 2 2 2 2 2 2 2 2 2 ... 455s ..$ x : num [1:7599] 554484 730720 782343 878522 916294 ... 455s ..$ y : num [1:7599] NA NA NA NA NA ... 455s ..$ index : int [1:7599] 1 2 3 4 5 6 7 8 9 10 ... 455s $ output :'data.frame': 1 obs. of 6 variables: 455s ..$ sampleName: chr NA 455s ..$ chromosome: int 2 455s ..$ start : num 554484 455s ..$ end : num 1.44e+08 455s ..$ nbrOfLoci : int 2120 455s ..$ mean : num 0.51 455s $ segRows:'data.frame': 1 obs. of 2 variables: 455s ..$ startRow: int 10 455s ..$ endRow : int 7594 455s $ params :List of 5 455s ..$ alpha : num 0.001 455s ..$ undo : num 0 455s ..$ joinSegments : logi TRUE 455s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 455s .. ..$ chromosome: int 2 455s .. ..$ start : num 554484 455s .. ..$ end : num 1.44e+08 455s ..$ seed : int [1:7] 10407 -1924040949 -1632234809 -437763632 -1464377300 676654412 2080370711 455s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 455s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.017 0 0.017 0 0 455s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 455s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 455s - attr(*, "randomSeed")= int [1:7] 10407 -1924040949 -1632234809 -437763632 -1464377300 676654412 2080370711 455s DH segmentation (locally-indexed) rows: 455s startRow endRow 455s 1 10 7594 455s int [1:7599] 1 2 3 4 5 6 7 8 9 10 ... 455s DH segmentation rows: 455s startRow endRow 455s 1 10 7594 455s Segmenting DH signals...done 455s DH segmentation table: 455s Random seed temporarily set (seed=c(10407, -1924040949, -1632234809, -437763632, -1464377300, 676654412, 2080370711), kind="L'Ecuyer-CMRG") 455s dhStart dhEnd dhNbrOfLoci dhMean 455s 1 554484 143926517 2120 0.5101 455s startRow endRow 455s 1 10 7594 455s Rows: 455s [1] 1 455s TCN segmentation rows: 455s startRow endRow 455s 1 1 7599 455s TCN and DH segmentation rows: 455s startRow endRow 455s 1 1 7599 455s startRow endRow 455s 1 10 7594 455s NULL 455s TCN segmentation (expanded) rows: 455s startRow endRow 455s 1 1 7599 455s TCN and DH segmentation rows: 455s startRow endRow 455s 1 1 7599 455s 2 7600 10267 455s 3 10268 14658 455s startRow endRow 455s 1 10 7594 455s startRow endRow 455s 1 1 7599 455s Total CN segmentation table (expanded): 455s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 455s 1 2 554484 143926517 7599 1.3859 2120 2120 455s (TCN,DH) segmentation for one total CN segment: 455s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 455s 1 1 1 2 554484 143926517 7599 1.3859 2120 455s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 455s 1 2120 554484 143926517 2120 0.5101 455s Total CN segment #1 ([ 554484,1.43927e+08]) of 3...done 455s Total CN segment #2 ([1.43927e+08,1.8545e+08]) of 3... 455s Number of TCN loci in segment: 2668 455s Locus data for TCN segment: 455s 'data.frame': 2668 obs. of 9 variables: 455s $ chromosome: int 2 2 2 2 2 2 2 2 2 2 ... 455s $ x : num 1.44e+08 1.44e+08 1.44e+08 1.44e+08 1.44e+08 ... 455s $ CT : num 2.1 2.1 2.09 1.8 2.34 ... 455s $ betaT : num 0.027542 1.030222 1.094093 0.046763 -0.000948 ... 455s $ betaTN : num 0.027542 1.030222 1.094093 0.046763 -0.000948 ... 455s $ betaN : num 0.1624 0.8788 0.8225 0.1201 0.0317 ... 455s $ muN : num 0 1 1 0 0 1 0 0 0 0 ... 455s $ index : int 7600 7601 7602 7603 7604 7605 7606 7607 7608 7609 ... 455s $ rho : num NA NA NA NA NA NA NA NA NA NA ... 455s Number of loci: 2668 455s Number of SNPs: 775 (29.05%) 455s Number of heterozygous SNPs: 775 (100.00%) 455s Chromosome: 2 455s Segmenting DH signals... 455s Segmenting by CBS... 455s Chromosome: 2 455s Random seed temporarily set (seed=c(10407, -1924040949, -1632234809, -437763632, -1464377300, 676654412, 2080370711), kind="L'Ecuyer-CMRG") 455s Segmenting by CBS...done 455s List of 4 455s $ data :'data.frame': 2668 obs. of 4 variables: 455s ..$ chromosome: int [1:2668] 2 2 2 2 2 2 2 2 2 2 ... 455s ..$ x : num [1:2668] 1.44e+08 1.44e+08 1.44e+08 1.44e+08 1.44e+08 ... 455s ..$ y : num [1:2668] NA NA NA NA NA NA NA NA NA NA ... 455s ..$ index : int [1:2668] 1 2 3 4 5 6 7 8 9 10 ... 455s $ output :'data.frame': 1 obs. of 6 variables: 455s ..$ sampleName: chr NA 455s ..$ chromosome: int 2 455s ..$ start : num 1.44e+08 455s ..$ end : num 1.85e+08 455s ..$ nbrOfLoci : int 775 455s ..$ mean : num 0.097 455s $ segRows:'data.frame': 1 obs. of 2 variables: 455s ..$ startRow: int 15 455s ..$ endRow : int 2664 455s $ params :List of 5 455s ..$ alpha : num 0.001 455s ..$ undo : num 0 455s ..$ joinSegments : logi TRUE 455s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 455s .. ..$ chromosome: int 2 455s .. ..$ start : num 1.44e+08 455s .. ..$ end : num 1.85e+08 455s ..$ seed : int [1:7] 10407 -1924040949 -1632234809 -437763632 -1464377300 676654412 2080370711 455s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 455s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.005 0 0.006 0 0 455s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 455s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 455s - attr(*, "randomSeed")= int [1:7] 10407 -1924040949 -1632234809 -437763632 -1464377300 676654412 2080370711 455s DH segmentation (locally-indexed) rows: 455s startRow endRow 455s 1 15 2664 455s int [1:2668] 7600 7601 7602 7603 7604 7605 7606 7607 7608 7609 ... 455s DH segmentation rows: 455s startRow endRow 455s 1 7614 10263 455s Segmenting DH signals...done 455s DH segmentation table: 455s dhStart dhEnd dhNbrOfLoci dhMean 455s 1 143926517 185449813 775 0.097 455s startRow endRow 455s 1 7614 10263 455s Rows: 455s [1] 2 455s TCN segmentation rows: 455s startRow endRow 455s 2 7600 10267 455s TCN and DH segmentation rows: 455s startRow endRow 455s 2 7600 10267 455s startRow endRow 455s 1 7614 10263 455s startRow endRow 455s 1 1 7599 455s TCN segmentation (expanded) rows: 455s startRow endRow 455s 1 1 7599 455s 2 7600 10267 455s TCN and DH segmentation rows: 455s startRow endRow 455s 1 1 7599 455s 2 7600 10267 455s 3 10268 14658 455s startRow endRow 455s 1 10 7594 455s 2 7614 10263 455s startRow endRow 455s 1 1 7599 455s 2 7600 10267 455s Total CN segmentation table (expanded): 455s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 455s 2 2 143926517 185449813 2668 2.0704 775 775 455s (TCN,DH) segmentation for one total CN segment: 455s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 455s 2 2 1 2 143926517 185449813 2668 2.0704 775 455s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 455s 2 775 143926517 185449813 775 0.097 455s Total CN segment #2 ([1.43927e+08,1.8545e+08]) of 3...done 455s Total CN segment #3 ([1.8545e+08,2.47137e+08]) of 3... 455s Number of TCN loci in segment: 4391 455s Locus data for TCN segment: 455s 'data.frame': 4391 obs. of 9 variables: 455s $ chromosome: int 2 2 2 2 2 2 2 2 2 2 ... 455s $ x : num 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 455s $ CT : num 2.93 2.15 2.82 2.93 2.46 ... 455s $ betaT : num -0.169 0.609 1.028 0.525 0.968 ... 455s $ betaTN : num -0.169 0.609 1.028 0.525 0.968 ... 455s $ betaN : num 0.25 0.38 0.919 0.34 0.783 ... 455s $ muN : num 0 0.5 1 0.5 1 1 0 1 0 1 ... 455s $ index : int 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 455s $ rho : num NA 0.2186 NA 0.0503 NA ... 455s Number of loci: 4391 455s Number of SNPs: 1314 (29.92%) 455s Number of heterozygous SNPs: 1314 (100.00%) 455s Chromosome: 2 455s Segmenting DH signals... 455s Segmenting by CBS... 455s Chromosome: 2 455s Random seed temporarily set (seed=c(10407, -1924040949, -1632234809, -437763632, -1464377300, 676654412, 2080370711), kind="L'Ecuyer-CMRG") 455s Segmenting by CBS...done 455s List of 4 455s $ data :'data.frame': 4391 obs. of 4 variables: 455s ..$ chromosome: int [1:4391] 2 2 2 2 2 2 2 2 2 2 ... 455s ..$ x : num [1:4391] 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 455s ..$ y : num [1:4391] NA 0.2186 NA 0.0503 NA ... 455s ..$ index : int [1:4391] 1 2 3 4 5 6 7 8 9 10 ... 455s $ output :'data.frame': 1 obs. of 6 variables: 455s ..$ sampleName: chr NA 455s ..$ chromosome: int 2 455s ..$ start : num 1.85e+08 455s ..$ end : num 2.47e+08 455s ..$ nbrOfLoci : int 1314 455s ..$ mean : num 0.23 455s $ segRows:'data.frame': 1 obs. of 2 variables: 455s ..$ startRow: int 2 455s ..$ endRow : int 4388 455s $ params :List of 5 455s ..$ alpha : num 0.001 455s ..$ undo : num 0 455s ..$ joinSegments : logi TRUE 455s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 455s .. ..$ chromosome: int 2 455s .. ..$ start : num 1.85e+08 455s .. ..$ end : num 2.47e+08 455s ..$ seed : int [1:7] 10407 -1924040949 -1632234809 -437763632 -1464377300 676654412 2080370711 455s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 455s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.011 0 0.01 0 0 455s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 455s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 455s - attr(*, "randomSeed")= int [1:7] 10407 -1924040949 -1632234809 -437763632 -1464377300 676654412 2080370711 455s DH segmentation (locally-indexed) rows: 455s startRow endRow 455s 1 2 4388 455s int [1:4391] 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 455s DH segmentation rows: 455s startRow endRow 455s 1 10269 14655 455s Segmenting DH signals...done 455s DH segmentation table: 455s dhStart dhEnd dhNbrOfLoci dhMean 455s 1 185449813 247137334 1314 0.2295 455s startRow endRow 455s 1 10269 14655 455s Rows: 455s [1] 3 455s TCN segmentation rows: 455s startRow endRow 455s 3 10268 14658 455s TCN and DH segmentation rows: 455s startRow endRow 455s 3 10268 14658 455s startRow endRow 455s 1 10269 14655 455s startRow endRow 455s 1 1 7599 455s 2 7600 10267 455s TCN segmentation (expanded) rows: 455s startRow endRow 455s 1 1 7599 455s 2 7600 10267 455s 3 10268 14658 455s TCN and DH segmentation rows: 455s startRow endRow 455s 1 1 7599 455s 2 7600 10267 455s 3 10268 14658 455s startRow endRow 455s 1 10 7594 455s 2 7614 10263 455s 3 10269 14655 455s startRow endRow 455s 1 1 7599 455s 2 7600 10267 455s 3 10268 14658 455s Total CN segmentation table (expanded): 455s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 455s 3 2 185449813 247137334 4391 2.6341 1314 1314 455s (TCN,DH) segmentation for one total CN segment: 455s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 455s 3 3 1 2 185449813 247137334 4391 2.6341 1314 455s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 455s 3 1314 185449813 247137334 1314 0.2295 455s Total CN segment #3 ([1.8545e+08,2.47137e+08]) of 3...done 455s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 455s 1 2 1 1 554484 143926517 7599 1.3859 2120 455s 2 2 2 1 143926517 185449813 2668 2.0704 775 455s 3 2 3 1 185449813 247137334 4391 2.6341 1314 455s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 455s 1 2120 554484 143926517 2120 0.5101 455s 2 775 143926517 185449813 775 0.0970 455s 3 1314 185449813 247137334 1314 0.2295 455s Calculating (C1,C2) per segment... 455s Calculating (C1,C2) per segment...done 455s Number of segments: 3 455s Segmenting paired tumor-normal signals using Paired PSCBS...done 455s Post-segmenting TCNs... 455s Number of segments: 3 455s Number of chromosomes: 1 455s [1] 2 455s Chromosome 1 ('chr02') of 1... 455s Rows: 455s [1] 1 2 3 455s Number of segments: 3 455s TCN segment #1 ('1') of 3... 455s Nothing todo. Only one DH segmentation. Skipping. 455s TCN segment #1 ('1') of 3...done 455s TCN segment #2 ('2') of 3... 455s Nothing todo. Only one DH segmentation. Skipping. 455s TCN segment #2 ('2') of 3...done 455s TCN segment #3 ('3') of 3... 455s Nothing todo. Only one DH segmentation. Skipping. 455s TCN segment #3 ('3') of 3...done 455s Chromosome 1 ('chr02') of 1...done 455s Update (C1,C2) per segment... 455s Update (C1,C2) per segment...done 455s Post-segmenting TCNs...done 455s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 455s 1 2 1 1 554484 143926517 7599 1.3859 2120 455s 2 2 2 1 143926517 185449813 2668 2.0704 775 455s 3 2 3 1 185449813 247137334 4391 2.6341 1314 455s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 455s 1 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 455s 2 775 143926517 185449813 775 0.0970 0.9347856 1.135614 455s 3 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 455s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 455s 1 2 1 1 554484 143926517 7599 1.3859 2120 455s 2 2 2 1 143926517 185449813 2668 2.0704 775 455s 3 2 3 1 185449813 247137334 4391 2.6341 1314 455s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 455s 1 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 455s 2 775 143926517 185449813 775 0.0970 0.9347856 1.135614 455s 3 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 455s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 455s 1 2 1 1 554484 143926517 7599 1.3859 2120 455s 2 2 2 1 143926517 185449813 2668 2.0704 775 455s 3 2 3 1 185449813 247137334 4391 2.6341 1314 455s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 455s 1 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 455s 2 775 143926517 185449813 775 0.0970 0.9347856 1.135614 455s 3 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 455s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 455s 1 2 1 1 554484 143926517 7599 1.3859 2120 455s 2 2 2 1 143926517 185449813 2668 2.0704 775 455s 3 2 3 1 185449813 247137334 4391 2.6341 1314 455s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 455s 1 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 455s 2 775 143926517 185449813 775 0.0970 0.9347856 1.135614 455s 3 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 455s Segmenting by CBS...done 455s List of 4 455s $ data :'data.frame': 14658 obs. of 4 variables: 455s ..$ chromosome: int [1:14658] 3 3 3 3 3 3 3 3 3 3 ... 455s ..$ x : num [1:14658] 554484 730720 782343 878522 916294 ... 455s ..$ y : num [1:14658] 1.88 1.8 1.59 1.64 1.53 ... 455s ..$ index : int [1:14658] 1 2 3 4 5 6 7 8 9 10 ... 455s $ output :'data.frame': 3 obs. of 6 variables: 455s ..$ sampleName: chr [1:3] NA NA NA 455s ..$ chromosome: int [1:3] 3 3 3 455s ..$ start : num [1:3] 5.54e+05 1.44e+08 1.85e+08 455s ..$ end : num [1:3] 1.44e+08 1.85e+08 2.47e+08 455s ..$ nbrOfLoci : int [1:3] 7599 2668 4391 455s ..$ mean : num [1:3] 1.39 2.07 2.63 455s $ segRows:'data.frame': 3 obs. of 2 variables: 455s ..$ startRow: int [1:3] 1 7600 10268 455s ..$ endRow : int [1:3] 7599 10267 14658 455s $ params :List of 5 455s ..$ alpha : num 0.009 455s ..$ undo : num 0 455s ..$ joinSegments : logi TRUE 455s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 455s .. ..$ chromosome: int 3 455s .. ..$ start : num -Inf 455s .. ..$ end : num Inf 455s ..$ seed : int [1:7] 10407 -1924040949 -1632234809 -437763632 -1464377300 676654412 2080370711 455s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 455s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.239 0.001 0.247 0 0 455s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 455s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 455s - attr(*, "randomSeed")= int [1:7] 10407 -1924040949 -1632234809 -437763632 -1464377300 676654412 2080370711 455s Identification of change points by total copy numbers...done 455s Restructure TCN segmentation results... 455s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean 455s 1 3 554484 143926517 7599 1.3859 455s 2 3 143926517 185449813 2668 2.0704 455s 3 3 185449813 247137334 4391 2.6341 455s Number of TCN segments: 3 455s Restructure TCN segmentation results...done 455s Total CN segment #1 ([ 554484,1.43927e+08]) of 3... 455s Number of TCN loci in segment: 7599 455s Locus data for TCN segment: 455s 'data.frame': 7599 obs. of 9 variables: 455s $ chromosome: int 3 3 3 3 3 3 3 3 3 3 ... 455s $ x : num 554484 730720 782343 878522 916294 ... 455s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 455s $ betaT : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 455s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 455s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 455s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 455s $ index : int 1 2 3 4 5 6 7 8 9 10 ... 455s $ rho : num NA NA NA NA NA ... 455s Number of loci: 7599 455s Number of SNPs: 2120 (27.90%) 455s Number of heterozygous SNPs: 2120 (100.00%) 455s Chromosome: 3 455s Segmenting DH signals... 455s Segmenting by CBS... 455s Chromosome: 3 455s Random seed temporarily set (seed=c(10407, -1371615447, -889757879, 1692656974, -1723952224, 1378814990, 1816467252), kind="L'Ecuyer-CMRG") 455s Segmenting by CBS...done 455s List of 4 455s $ data :'data.frame': 7599 obs. of 4 variables: 455s ..$ chromosome: int [1:7599] 3 3 3 3 3 3 3 3 3 3 ... 455s ..$ x : num [1:7599] 554484 730720 782343 878522 916294 ... 455s ..$ y : num [1:7599] NA NA NA NA NA ... 455s ..$ index : int [1:7599] 1 2 3 4 5 6 7 8 9 10 ... 455s $ output :'data.frame': 1 obs. of 6 variables: 455s ..$ sampleName: chr NA 455s ..$ chromosome: int 3 455s ..$ start : num 554484 455s ..$ end : num 1.44e+08 455s ..$ nbrOfLoci : int 2120 455s ..$ mean : num 0.51 455s $ segRows:'data.frame': 1 obs. of 2 variables: 455s ..$ startRow: int 10 455s ..$ endRow : int 7594 455s $ params :List of 5 455s ..$ alpha : num 0.001 455s ..$ undo : num 0 455s ..$ joinSegments : logi TRUE 455s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 455s .. ..$ chromosome: int 3 455s .. ..$ start : num 554484 455s .. ..$ end : num 1.44e+08 455s ..$ seed : int [1:7] 10407 -1371615447 -889757879 1692656974 -1723952224 1378814990 1816467252 455s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 455s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.017 0 0.017 0 0 455s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 455s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 455s - attr(*, "randomSeed")= int [1:7] 10407 -1371615447 -889757879 1692656974 -1723952224 1378814990 1816467252 455s DH segmentation (locally-indexed) rows: 455s startRow endRow 455s 1 10 7594 455s int [1:7599] 1 2 3 4 5 6 7 8 9 10 ... 455s DH segmentation rows: 455s startRow endRow 455s 1 10 7594 455s Segmenting DH signals...done 455s DH segmentation table: 455s dhStart dhEnd dhNbrOfLoci dhMean 455s 1 554484 143926517 2120 0.5101 455s startRow endRow 455s 1 10 7594 455s Rows: 455s [1] 1 455s TCN segmentation rows: 455s startRow endRow 455s 1 1 7599 455s TCN and DH segmentation rows: 455s startRow endRow 455s 1 1 7599 455s startRow endRow 455s 1 10 7594 455s NULL 455s TCN segmentation (expanded) rows: 455s startRow endRow 455s 1 1 7599 455s TCN and DH segmentation rows: 455s startRow endRow 455s 1 1 7599 455s 2 7600 10267 455s 3 10268 14658 455s startRow endRow 455s 1 10 7594 455s startRow endRow 455s 1 1 7599 455s Total CN segmentation table (expanded): 455s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 455s 1 3 554484 143926517 7599 1.3859 2120 2120 455s (TCN,DH) segmentation for one total CN segment: 455s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 455s 1 1 1 3 554484 143926517 7599 1.3859 2120 455s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 455s 1 2120 554484 143926517 2120 0.5101 455s Total CN segment #1 ([ 554484,1.43927e+08]) of 3...done 455s Total CN segment #2 ([1.43927e+08,1.8545e+08]) of 3... 455s Number of TCN loci in segment: 2668 455s Locus data for TCN segment: 455s 'data.frame': 2668 obs. of 9 variables: 455s $ chromosome: int 3 3 3 3 3 3 3 3 3 3 ... 455s $ x : num 1.44e+08 1.44e+08 1.44e+08 1.44e+08 1.44e+08 ... 455s $ CT : num 2.1 2.1 2.09 1.8 2.34 ... 455s $ betaT : num 0.027542 1.030222 1.094093 0.046763 -0.000948 ... 455s $ betaTN : num 0.027542 1.030222 1.094093 0.046763 -0.000948 ... 455s $ betaN : num 0.1624 0.8788 0.8225 0.1201 0.0317 ... 455s $ muN : num 0 1 1 0 0 1 0 0 0 0 ... 455s $ index : int 7600 7601 7602 7603 7604 7605 7606 7607 7608 7609 ... 455s $ rho : num NA NA NA NA NA NA NA NA NA NA ... 455s Number of loci: 2668 455s Number of SNPs: 775 (29.05%) 455s Number of heterozygous SNPs: 775 (100.00%) 455s Chromosome: 3 455s Segmenting DH signals... 455s Segmenting by CBS... 455s Chromosome: 3 455s Random seed temporarily set (seed=c(10407, -1371615447, -889757879, 1692656974, -1723952224, 1378814990, 1816467252), kind="L'Ecuyer-CMRG") 455s Segmenting by CBS...done 455s List of 4 455s $ data :'data.frame': 2668 obs. of 4 variables: 455s ..$ chromosome: int [1:2668] 3 3 3 3 3 3 3 3 3 3 ... 455s ..$ x : num [1:2668] 1.44e+08 1.44e+08 1.44e+08 1.44e+08 1.44e+08 ... 455s ..$ y : num [1:2668] NA NA NA NA NA NA NA NA NA NA ... 455s ..$ index : int [1:2668] 1 2 3 4 5 6 7 8 9 10 ... 455s $ output :'data.frame': 1 obs. of 6 variables: 455s ..$ sampleName: chr NA 455s ..$ chromosome: int 3 455s ..$ start : num 1.44e+08 455s ..$ end : num 1.85e+08 455s ..$ nbrOfLoci : int 775 455s ..$ mean : num 0.097 455s $ segRows:'data.frame': 1 obs. of 2 variables: 455s ..$ startRow: int 15 455s ..$ endRow : int 2664 455s $ params :List of 5 455s ..$ alpha : num 0.001 455s ..$ undo : num 0 455s ..$ joinSegments : logi TRUE 455s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 455s .. ..$ chromosome: int 3 455s .. ..$ start : num 1.44e+08 455s .. ..$ end : num 1.85e+08 455s ..$ seed : int [1:7] 10407 -1371615447 -889757879 1692656974 -1723952224 1378814990 1816467252 455s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 455s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.005 0 0.005 0 0 455s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 455s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 455s - attr(*, "randomSeed")= int [1:7] 10407 -1371615447 -889757879 1692656974 -1723952224 1378814990 1816467252 455s DH segmentation (locally-indexed) rows: 455s startRow endRow 455s 1 15 2664 455s int [1:2668] 7600 7601 7602 7603 7604 7605 7606 7607 7608 7609 ... 455s DH segmentation rows: 455s startRow endRow 455s 1 7614 10263 455s Segmenting DH signals...done 455s DH segmentation table: 455s dhStart dhEnd dhNbrOfLoci dhMean 455s 1 143926517 185449813 775 0.097 455s startRow endRow 455s 1 7614 10263 455s Rows: 455s [1] 2 455s TCN segmentation rows: 455s startRow endRow 455s 2 7600 10267 455s TCN and DH segmentation rows: 455s startRow endRow 455s 2 7600 10267 455s startRow endRow 455s 1 7614 10263 455s startRow endRow 455s 1 1 7599 455s TCN segmentation (expanded) rows: 455s startRow endRow 455s 1 1 7599 455s 2 7600 10267 455s TCN and DH segmentation rows: 455s startRow endRow 455s 1 1 7599 455s 2 7600 10267 455s 3 10268 14658 455s startRow endRow 455s 1 10 7594 455s 2 7614 10263 455s startRow endRow 455s 1 1 7599 455s 2 7600 10267 455s Total CN segmentation table (expanded): 455s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 455s 2 3 143926517 185449813 2668 2.0704 775 775 455s (TCN,DH) segmentation for one total CN segment: 455s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 455s 2 2 1 3 143926517 185449813 2668 2.0704 775 455s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 455s 2 775 143926517 185449813 775 0.097 455s Total CN segment #2 ([1.43927e+08,1.8545e+08]) of 3...done 455s Total CN segment #3 ([1.8545e+08,2.47137e+08]) of 3... 455s Number of TCN loci in segment: 4391 455s Locus data for TCN segment: 455s 'data.frame': 4391 obs. of 9 variables: 455s $ chromosome: int 3 3 3 3 3 3 3 3 3 3 ... 455s $ x : num 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 455s $ CT : num 2.93 2.15 2.82 2.93 2.46 ... 455s $ betaT : num -0.169 0.609 1.028 0.525 0.968 ... 455s $ betaTN : num -0.169 0.609 1.028 0.525 0.968 ... 455s $ betaN : num 0.25 0.38 0.919 0.34 0.783 ... 455s $ muN : num 0 0.5 1 0.5 1 1 0 1 0 1 ... 455s $ index : int 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 455s $ rho : num NA 0.2186 NA 0.0503 NA ... 455s Number of loci: 4391 455s Number of SNPs: 1314 (29.92%) 455s Number of heterozygous SNPs: 1314 (100.00%) 455s Chromosome: 3 455s Segmenting DH signals... 455s Segmenting by CBS... 455s Chromosome: 3 455s Random seed temporarily set (seed=c(10407, -1371615447, -889757879, 1692656974, -1723952224, 1378814990, 1816467252), kind="L'Ecuyer-CMRG") 455s Segmenting by CBS...done 455s List of 4 455s $ data :'data.frame': 4391 obs. of 4 variables: 455s ..$ chromosome: int [1:4391] 3 3 3 3 3 3 3 3 3 3 ... 455s ..$ x : num [1:4391] 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 455s ..$ y : num [1:4391] NA 0.2186 NA 0.0503 NA ... 455s ..$ index : int [1:4391] 1 2 3 4 5 6 7 8 9 10 ... 455s $ output :'data.frame': 1 obs. of 6 variables: 455s ..$ sampleName: chr NA 455s ..$ chromosome: int 3 455s ..$ start : num 1.85e+08 455s ..$ end : num 2.47e+08 455s ..$ nbrOfLoci : int 1314 455s ..$ mean : num 0.23 455s $ segRows:'data.frame': 1 obs. of 2 variables: 455s ..$ startRow: int 2 455s ..$ endRow : int 4388 455s $ params :List of 5 455s ..$ alpha : num 0.001 455s ..$ undo : num 0 455s ..$ joinSegments : logi TRUE 455s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 455s .. ..$ chromosome: int 3 455s .. ..$ start : num 1.85e+08 455s .. ..$ end : num 2.47e+08 455s ..$ seed : int [1:7] 10407 -1371615447 -889757879 1692656974 -1723952224 1378814990 1816467252 455s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 455s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.01 0 0.01 0 0 455s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 455s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 455s - attr(*, "randomSeed")= int [1:7] 10407 -1371615447 -889757879 1692656974 -1723952224 1378814990 1816467252 455s DH segmentation (locally-indexed) rows: 455s startRow endRow 455s 1 2 4388 455s int [1:4391] 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 455s DH segmentation rows: 455s startRow endRow 455s 1 10269 14655 455s Segmenting DH signals...done 455s DH segmentation table: 455s dhStart dhEnd dhNbrOfLoci dhMean 455s 1 185449813 247137334 1314 0.2295 455s startRow endRow 455s 1 10269 14655 455s Rows: 455s [1] 3 455s TCN segmentation rows: 455s startRow endRow 455s 3 10268 14658 455s TCN and DH segmentation rows: 455s startRow endRow 455s 3 10268 14658 455s startRow endRow 455s 1 10269 14655 455s startRow endRow 455s 1 1 7599 455s 2 7600 10267 455s TCN segmentation (expanded) rows: 455s startRow endRow 455s 1 1 7599 455s 2 7600 10267 455s 3 10268 14658 455s TCN and DH segmentation rows: 455s startRow endRow 455s 1 1 7599 455s 2 7600 10267 455s 3 10268 14658 455s startRow endRow 455s 1 10 7594 455s 2 7614 10263 455s 3 10269 14655 455s startRow endRow 455s 1 1 7599 455s 2 7600 10267 455s 3 10268 14658 455s Total CN segmentation table (expanded): 455s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 455s 3 3 185449813 247137334 4391 2.6341 1314 1314 455s (TCN,DH) segmentation for one total CN segment: 455s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 455s 3 3 1 3 185449813 247137334 4391 2.6341 1314 455s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 455s 3 1314 185449813 247137334 1314 0.2295 455s Total CN segment #3 ([1.8545e+08,2.47137e+08]) of 3...done 455s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 455s 1 3 1 1 554484 143926517 7599 1.3859 2120 455s 2 3 2 1 143926517 185449813 2668 2.0704 775 455s 3 3 3 1 185449813 247137334 4391 2.6341 1314 455s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 455s 1 2120 554484 143926517 2120 0.5101 455s 2 775 143926517 185449813 775 0.0970 455s 3 1314 185449813 247137334 1314 0.2295 455s Calculating (C1,C2) per segment... 455s Calculating (C1,C2) per segment...done 455s Number of segments: 3 455s Segmenting paired tumor-normal signals using Paired PSCBS...done 455s Post-segmenting TCNs... 455s Number of segments: 3 455s Number of chromosomes: 1 455s [1] 3 455s Chromosome 1 ('chr03') of 1... 455s Rows: 455s [1] 1 2 3 455s Number of segments: 3 455s TCN segment #1 ('1') of 3... 455s Nothing todo. Only one DH segmentation. Skipping. 455s TCN segment #1 ('1') of 3...done 455s TCN segment #2 ('2') of 3... 455s Nothing todo. Only one DH segmentation. Skipping. 455s TCN segment #2 ('2') of 3...done 455s TCN segment #3 ('3') of 3... 455s Nothing todo. Only one DH segmentation. Skipping. 455s TCN segment #3 ('3') of 3...done 455s Chromosome 1 ('chr03') of 1...done 455s Update (C1,C2) per segment... 455s Update (C1,C2) per segment...done 455s Post-segmenting TCNs...done 455s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 455s 1 3 1 1 554484 143926517 7599 1.3859 2120 455s 2 3 2 1 143926517 185449813 2668 2.0704 775 455s 3 3 3 1 185449813 247137334 4391 2.6341 1314 455s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 455s 1 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 455s 2 775 143926517 185449813 775 0.0970 0.9347856 1.135614 455s 3 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 455s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 455s 1 3 1 1 554484 143926517 7599 1.3859 2120 455s 2 3 2 1 143926517 185449813 2668 2.0704 775 455s 3 3 3 1 185449813 247137334 4391 2.6341 1314 455s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 455s 1 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 455s 2 775 143926517 185449813 775 0.0970 0.9347856 1.135614 455s 3 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 455s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 455s 1 3 1 1 554484 143926517 7599 1.3859 2120 455s 2 3 2 1 143926517 185449813 2668 2.0704 775 455s 3 3 3 1 185449813 247137334 4391 2.6341 1314 455s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 455s 1 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 455s 2 775 143926517 185449813 775 0.0970 0.9347856 1.135614 455s 3 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 455s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 455s 1 3 1 1 554484 143926517 7599 1.3859 2120 455s 2 3 2 1 143926517 185449813 2668 2.0704 775 455s 3 3 3 1 185449813 247137334 4391 2.6341 1314 455s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 455s 1 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 455s 2 775 143926517 185449813 775 0.0970 0.9347856 1.135614 455s 3 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 455s List of 5 455s $ data :Classes ‘PairedPSCNData’ and 'data.frame': 43974 obs. of 8 variables: 455s ..$ chromosome: int [1:43974] 1 1 1 1 1 1 1 1 1 1 ... 455s ..$ x : num [1:43974] 554484 730720 782343 878522 916294 ... 455s ..$ CT : num [1:43974] 1.88 1.8 1.59 1.64 1.53 ... 455s ..$ betaT : num [1:43974] 0.0646 0.1672 0.9284 0.113 0.7209 ... 455s ..$ betaTN : num [1:43974] -0.0515 -0.1172 1.0194 0.031 0.8604 ... 455s ..$ betaN : num [1:43974] 0.116 0.284 0.909 0.082 0.86 ... 455s ..$ muN : num [1:43974] 0 0 1 0 1 1 1 0 1 0.5 ... 455s ..$ rho : num [1:43974] NA NA NA NA NA ... 455s $ output :Classes ‘PairedPSCNSegments’ and 'data.frame': 11 obs. of 15 variables: 455s ..$ chromosome : int [1:11] 1 1 1 NA 2 2 2 NA 3 3 ... 455s ..$ tcnId : int [1:11] 1 2 3 NA 1 2 3 NA 1 2 ... 455s ..$ dhId : int [1:11] 1 1 1 NA 1 1 1 NA 1 1 ... 455s ..$ tcnStart : num [1:11] 5.54e+05 1.44e+08 1.85e+08 NA 5.54e+05 ... 455s ..$ tcnEnd : num [1:11] 1.44e+08 1.85e+08 2.47e+08 NA 1.44e+08 ... 455s ..$ tcnNbrOfLoci: int [1:11] 7599 2668 4391 NA 7599 2668 4391 NA 7599 2668 ... 455s ..$ tcnMean : num [1:11] 1.39 2.07 2.63 NA 1.39 ... 455s ..$ tcnNbrOfSNPs: int [1:11] 2120 775 1314 NA 2120 775 1314 NA 2120 775 ... 455s ..$ tcnNbrOfHets: int [1:11] 2120 775 1314 NA 2120 775 1314 NA 2120 775 ... 455s ..$ dhStart : num [1:11] 5.54e+05 1.44e+08 1.85e+08 NA 5.54e+05 ... 455s ..$ dhEnd : num [1:11] 1.44e+08 1.85e+08 2.47e+08 NA 1.44e+08 ... 455s ..$ dhNbrOfLoci : int [1:11] 2120 775 1314 NA 2120 775 1314 NA 2120 775 ... 455s ..$ dhMean : num [1:11] 0.51 0.097 0.23 NA 0.51 ... 455s ..$ c1Mean : num [1:11] 0.339 0.935 1.015 NA 0.339 ... 455s ..$ c2Mean : num [1:11] 1.05 1.14 1.62 NA 1.05 ... 455s $ tcnSegRows:'data.frame': 11 obs. of 2 variables: 455s ..$ startRow: int [1:11] 1 7600 10268 NA 14659 22258 24926 NA 29317 36916 ... 455s ..$ endRow : int [1:11] 7599 10267 14658 NA 22257 24925 29316 NA 36915 39583 ... 455s $ dhSegRows :'data.frame': 11 obs. of 2 variables: 455s ..$ startRow: int [1:11] 10 7614 10269 NA 14668 22272 24927 NA 29326 36930 ... 455s ..$ endRow : int [1:11] 7594 10263 14655 NA 22252 24921 29313 NA 36910 39579 ... 455s $ params :List of 7 455s ..$ alphaTCN : num 0.009 455s ..$ alphaDH : num 0.001 455s ..$ flavor : chr "tcn&dh" 455s ..$ tbn : logi FALSE 455s ..$ joinSegments : logi TRUE 455s ..$ knownSegments:'data.frame': 0 obs. of 3 variables: 455s .. ..$ chromosome: int(0) 455s .. ..$ start : int(0) 455s .. ..$ end : int(0) 455s ..$ seed : int [1:7] 10407 1066287653 -51199871 161854402 -1995183193 1503453565 -747102133 455s - attr(*, "class")= chr [1:3] "PairedPSCBS" "PSCBS" "AbstractCBS" 455s Merging (independently) segmented chromosome...done 455s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 455s 1 1 1 1 554484 143926517 7599 1.3859 2120 455s 2 1 2 1 143926517 185449813 2668 2.0704 775 455s 3 1 3 1 185449813 247137334 4391 2.6341 1314 455s 4 NA NA NA NA NA NA NA NA 455s 5 2 1 1 554484 143926517 7599 1.3859 2120 455s 6 2 2 1 143926517 185449813 2668 2.0704 775 455s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 455s 1 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 455s 2 775 143926517 185449813 775 0.0970 0.9347856 1.135614 455s 3 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 455s 4 NA NA NA NA NA NA NA 455s 5 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 455s 6 775 143926517 185449813 775 0.0970 0.9347856 1.135614 455s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 455s 6 2 2 1 143926517 185449813 2668 2.0704 775 455s 7 2 3 1 185449813 247137334 4391 2.6341 1314 455s 8 NA NA NA NA NA NA NA NA 455s 9 3 1 1 554484 143926517 7599 1.3859 2120 455s 10 3 2 1 143926517 185449813 2668 2.0704 775 455s 11 3 3 1 185449813 247137334 4391 2.6341 1314 455s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 455s 6 775 143926517 185449813 775 0.0970 0.9347856 1.135614 455s 7 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 455s 8 NA NA NA NA NA NA NA 455s 9 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 455s 10 775 143926517 185449813 775 0.0970 0.9347856 1.135614 455s 11 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 455s Segmenting multiple chromosomes...done 455s Segmenting paired tumor-normal signals using Paired PSCBS...done 455s *** segmentByPairedPSCBS() via futures ... DONE 455s > 455s > message("*** segmentByPairedPSCBS() via futures ... DONE") 455s > 455s > 455s > message("*** segmentByPairedPSCBS() via futures with known segments ...") 455s *** segmentByPairedPSCBS() via futures with known segments ... 456s > fits <- list() 456s > dataT <- subset(data, chromosome == 1) 456s > gaps <- findLargeGaps(dataT, minLength=2e6) 456s > knownSegments <- gapsToSegments(gaps) 456s > 456s > for (strategy in strategies) { 456s + message(sprintf("- segmentByPairedPSCBS() w/ known segments using '%s' futures ...", strategy)) 456s + plan(strategy) 456s + fit <- segmentByPairedPSCBS(dataT, knownSegments=knownSegments, seed=0xBEEF, verbose=TRUE) 456s + fits[[strategy]] <- fit 456s + equal <- all.equal(fit, fits[[1]]) 456s + if (!equal) { 456s + str(fit) 456s + str(fits[[1]]) 456s + print(equal) 456s + stop(sprintf("segmentByPairedPSCBS() w/ known segments using '%s' futures does not produce the same results as when using '%s' futures", strategy, names(fits)[1])) 456s + } 456s + } 456s - segmentByPairedPSCBS() w/ known segments using 'sequential' futures ... 456s Segmenting paired tumor-normal signals using Paired PSCBS... 456s Calling genotypes from normal allele B fractions... 456s num [1:14670] 0.8274 0.5072 0.1671 0.1609 0.0421 ... 456s Called genotypes: 456s num [1:14670] 1 0.5 0 0 0 0 1 0 1 0.5 ... 456s - attr(*, "modelFit")=List of 1 456s ..$ :List of 7 456s .. ..$ flavor : chr "density" 456s .. ..$ cn : int 2 456s .. ..$ nbrOfGenotypeGroups: int 3 456s .. ..$ tau : num [1:2] 0.315 0.677 456s .. ..$ n : int 14640 456s .. ..$ fit :Classes ‘PeaksAndValleys’ and 'data.frame': 5 obs. of 3 variables: 456s .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 456s .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 456s .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 456s .. ..$ fitValleys :Classes ‘PeaksAndValleys’ and 'data.frame': 2 obs. of 3 variables: 456s .. .. ..$ type : chr [1:2] "valley" "valley" 456s .. .. ..$ x : num [1:2] 0.315 0.677 456s .. .. ..$ density: num [1:2] 0.522 0.551 456s ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 456s muN 456s 0 0.5 1 456s 5221 4198 5251 456s Calling genotypes from normal allele B fractions...done 456s Normalizing betaT using betaN (TumorBoost)... 456s Normalized BAFs: 456s num [1:14670] 0.9301 0.1667 0.0685 0.0995 0.0155 ... 456s - attr(*, "modelFit")=List of 5 456s ..$ method : chr "normalizeTumorBoost" 456s ..$ flavor : chr "v4" 456s ..$ delta : num [1:14670] -0.17264 0.00239 0.1671 0.16085 0.04213 ... 456s .. ..- attr(*, "modelFit")=List of 1 456s .. .. ..$ :List of 7 456s .. .. .. ..$ flavor : chr "density" 456s .. .. .. ..$ cn : int 2 456s .. .. .. ..$ nbrOfGenotypeGroups: int 3 456s .. .. .. ..$ tau : num [1:2] 0.315 0.677 456s .. .. .. ..$ n : int 14640 456s .. .. .. ..$ fit :Classes ‘PeaksAndValleys’ and 'data.frame': 5 obs. of 3 variables: 456s .. .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 456s .. .. .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 456s .. .. .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 456s .. .. .. ..$ fitValleys :Classes ‘PeaksAndValleys’ and 'data.frame': 2 obs. of 3 variables: 456s .. .. .. .. ..$ type : chr [1:2] "valley" "valley" 456s .. .. .. .. ..$ x : num [1:2] 0.315 0.677 456s .. .. .. .. ..$ density: num [1:2] 0.522 0.551 456s .. .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 456s ..$ preserveScale: logi FALSE 456s ..$ scaleFactor : num NA 456s Normalizing betaT using betaN (TumorBoost)...done 456s Setup up data... 456s 'data.frame': 14670 obs. of 7 variables: 456s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 456s $ x : num 1145994 2941694 3710825 4240737 4276892 ... 456s $ CT : num 1.63 1.4 1.41 1.17 1.16 ... 456s $ betaT : num 0.7574 0.169 0.2357 0.2604 0.0576 ... 456s $ betaTN : num 0.9301 0.1667 0.0685 0.0995 0.0155 ... 456s ..- attr(*, "modelFit")=List of 5 456s .. ..$ method : chr "normalizeTumorBoost" 456s .. ..$ flavor : chr "v4" 456s .. ..$ delta : num [1:14670] -0.17264 0.00239 0.1671 0.16085 0.04213 ... 456s .. .. ..- attr(*, "modelFit")=List of 1 456s .. .. .. ..$ :List of 7 456s .. .. .. .. ..$ flavor : chr "density" 456s .. .. .. .. ..$ cn : int 2 456s .. .. .. .. ..$ nbrOfGenotypeGroups: int 3 456s .. .. .. .. ..$ tau : num [1:2] 0.315 0.677 456s .. .. .. .. ..$ n : int 14640 456s .. .. .. .. ..$ fit :Classes ‘PeaksAndValleys’ and 'data.frame': 5 obs. of 3 variables: 456s .. .. .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 456s .. .. .. .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 456s .. .. .. .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 456s .. .. .. .. ..$ fitValleys :Classes ‘PeaksAndValleys’ and 'data.frame': 2 obs. of 3 variables: 456s .. .. .. .. .. ..$ type : chr [1:2] "valley" "valley" 456s .. .. .. .. .. ..$ x : num [1:2] 0.315 0.677 456s .. .. .. .. .. ..$ density: num [1:2] 0.522 0.551 456s .. .. .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 456s .. ..$ preserveScale: logi FALSE 456s .. ..$ scaleFactor : num NA 456s $ betaN : num 0.8274 0.5072 0.1671 0.1609 0.0421 ... 456s $ muN : num 1 0.5 0 0 0 0 1 0 1 0.5 ... 456s ..- attr(*, "modelFit")=List of 1 456s .. ..$ :List of 7 456s .. .. ..$ flavor : chr "density" 456s .. .. ..$ cn : int 2 456s .. .. ..$ nbrOfGenotypeGroups: int 3 456s .. .. ..$ tau : num [1:2] 0.315 0.677 456s .. .. ..$ n : int 14640 456s .. .. ..$ fit :Classes ‘PeaksAndValleys’ and 'data.frame': 5 obs. of 3 variables: 456s .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 456s .. .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 456s .. .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 456s .. .. ..$ fitValleys :Classes ‘PeaksAndValleys’ and 'data.frame': 2 obs. of 3 variables: 456s .. .. .. ..$ type : chr [1:2] "valley" "valley" 456s .. .. .. ..$ x : num [1:2] 0.315 0.677 456s .. .. .. ..$ density: num [1:2] 0.522 0.551 456s .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 456s Setup up data...done 456s Dropping loci for which TCNs are missing... 456s Number of loci dropped: 12 456s Dropping loci for which TCNs are missing...done 456s Ordering data along genome... 456s 'data.frame': 14658 obs. of 7 variables: 456s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 456s $ x : num 554484 730720 782343 878522 916294 ... 456s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 456s $ betaT : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 456s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 456s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 456s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 456s Ordering data along genome...done 456s Keeping only current chromosome for 'knownSegments'... 456s Chromosome: 1 456s Known segments for this chromosome: 456s chromosome start end length 456s 1 1 -Inf 120908858 Inf 456s 2 1 120908859 142693887 21785028 456s 3 1 142693888 Inf Inf 456s Keeping only current chromosome for 'knownSegments'...done 456s alphaTCN: 0.009 456s alphaDH: 0.001 456s Number of loci: 14658 456s Calculating DHs... 456s Number of SNPs: 14658 456s Number of heterozygous SNPs: 4196 (28.63%) 456s Normalized DHs: 456s num [1:14658] NA NA NA NA NA ... 456s Calculating DHs...done 456s Random seed temporarily set (seed=c(48879), kind="L'Ecuyer-CMRG") 456s Produced 2 seeds from this stream for future usage 456s Identification of change points by total copy numbers... 456s Segmenting by CBS... 456s Chromosome: 1 456s Random seed temporarily set (seed=c(10407, 1066287653, -51199871, 161854402, -1995183193, 1503453565, -747102133), kind="L'Ecuyer-CMRG") 456s Produced 3 seeds from this stream for future usage 456s Segmenting by CBS...done 456s List of 4 456s $ data :'data.frame': 14658 obs. of 4 variables: 456s ..$ chromosome: int [1:14658] 1 1 1 1 1 1 1 1 1 1 ... 456s ..$ x : num [1:14658] 554484 730720 782343 878522 916294 ... 456s ..$ y : num [1:14658] 1.88 1.8 1.59 1.64 1.53 ... 456s ..$ index : int [1:14658] 1 2 3 4 5 6 7 8 9 10 ... 456s $ output :'data.frame': 4 obs. of 6 variables: 456s ..$ sampleName: chr [1:4] NA NA NA NA 456s ..$ chromosome: int [1:4] 1 1 1 1 456s ..$ start : num [1:4] 5.54e+05 1.21e+08 1.43e+08 1.85e+08 456s ..$ end : num [1:4] 1.21e+08 1.43e+08 1.85e+08 2.47e+08 456s ..$ nbrOfLoci : int [1:4] 7586 0 2681 4391 456s ..$ mean : num [1:4] 1.39 NA 2.07 2.63 456s $ segRows:'data.frame': 4 obs. of 2 variables: 456s ..$ startRow: int [1:4] 1 NA 7587 10268 456s ..$ endRow : int [1:4] 7586 NA 10267 14658 456s $ params :List of 5 456s ..$ alpha : num 0.009 456s ..$ undo : num 0 456s ..$ joinSegments : logi TRUE 456s ..$ knownSegments:'data.frame': 4 obs. of 3 variables: 456s .. ..$ chromosome: int [1:4] 1 1 2 1 456s .. ..$ start : num [1:4] -Inf -Inf -Inf 1.43e+08 456s .. ..$ end : num [1:4] 1.21e+08 Inf Inf Inf 456s ..$ seed : int [1:7] 10407 1066287653 -51199871 161854402 -1995183193 1503453565 -747102133 456s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 456s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.086 0 0.086 0 0 456s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 456s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 456s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 456s Identification of change points by total copy numbers...done 456s Restructure TCN segmentation results... 456s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean 456s 1 1 554484 120908858 7586 1.3853 456s 2 1 120908859 142693887 0 NA 456s 3 1 142693888 185449813 2681 2.0689 456s 4 1 185449813 247137334 4391 2.6341 456s Number of TCN segments: 4 456s Restructure TCN segmentation results...done 456s Total CN segment #1 ([ 554484,1.20909e+08]) of 4... 456s Number of TCN loci in segment: 7586 456s Locus data for TCN segment: 456s 'data.frame': 7586 obs. of 9 variables: 456s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 456s $ x : num 554484 730720 782343 878522 916294 ... 456s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 456s $ betaT : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 456s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 456s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 456s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 456s $ index : int 1 2 3 4 5 6 7 8 9 10 ... 456s $ rho : num NA NA NA NA NA ... 456s Number of loci: 7586 456s Number of SNPs: 2108 (27.79%) 456s Number of heterozygous SNPs: 2108 (100.00%) 456s Chromosome: 1 456s Segmenting DH signals... 456s Segmenting by CBS... 456s Chromosome: 1 456s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 456s Segmenting by CBS...done 456s List of 4 456s $ data :'data.frame': 7586 obs. of 4 variables: 456s ..$ chromosome: int [1:7586] 1 1 1 1 1 1 1 1 1 1 ... 456s ..$ x : num [1:7586] 554484 730720 782343 878522 916294 ... 456s ..$ y : num [1:7586] NA NA NA NA NA ... 456s ..$ index : int [1:7586] 1 2 3 4 5 6 7 8 9 10 ... 456s $ output :'data.frame': 1 obs. of 6 variables: 456s ..$ sampleName: chr NA 456s ..$ chromosome: int 1 456s ..$ start : num 554484 456s ..$ end : num 1.21e+08 456s ..$ nbrOfLoci : int 2108 456s ..$ mean : num 0.512 456s $ segRows:'data.frame': 1 obs. of 2 variables: 456s ..$ startRow: int 10 456s ..$ endRow : int 7574 456s $ params :List of 5 456s ..$ alpha : num 0.001 456s ..$ undo : num 0 456s ..$ joinSegments : logi TRUE 456s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 456s .. ..$ chromosome: int 1 456s .. ..$ start : num 554484 456s .. ..$ end : num 1.21e+08 456s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 456s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 456s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.025 0 0.025 0 0 456s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 456s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 456s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 456s DH segmentation (locally-indexed) rows: 456s startRow endRow 456s 1 10 7574 456s int [1:7586] 1 2 3 4 5 6 7 8 9 10 ... 456s DH segmentation rows: 456s startRow endRow 456s 1 10 7574 456s Segmenting DH signals...done 456s DH segmentation table: 456s dhStart dhEnd dhNbrOfLoci dhMean 456s 1 554484 120908858 2108 0.5116 456s startRow endRow 456s 1 10 7574 456s Rows: 456s [1] 1 456s TCN segmentation rows: 456s startRow endRow 456s 1 1 7586 456s TCN and DH segmentation rows: 456s startRow endRow 456s 1 1 7586 456s startRow endRow 456s 1 10 7574 456s NULL 456s TCN segmentation (expanded) rows: 456s startRow endRow 456s 1 1 7586 456s TCN and DH segmentation rows: 456s startRow endRow 456s 1 1 7586 456s 2 NA NA 456s 3 7587 10267 456s 4 10268 14658 456s startRow endRow 456s 1 10 7574 456s startRow endRow 456s 1 1 7586 456s Total CN segmentation table (expanded): 456s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 456s 1 1 554484 120908858 7586 1.3853 2108 2108 456s (TCN,DH) segmentation for one total CN segment: 456s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 456s 1 1 1 1 554484 120908858 7586 1.3853 2108 456s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 456s 1 2108 554484 120908858 2108 0.5116 456s Total CN segment #1 ([ 554484,1.20909e+08]) of 4...done 456s Total CN segment #2 ([1.20909e+08,1.42694e+08]) of 4... 456s Number of TCN loci in segment: 0 456s Locus data for TCN segment: 456s 'data.frame': 0 obs. of 9 variables: 456s $ chromosome: int 456s $ x : num 456s $ CT : num 456s $ betaT : num 456s $ betaTN : num 456s $ betaN : num 456s $ muN : num 456s $ index : int 456s $ rho : num 456s Number of loci: 0 456s Number of SNPs: 0 (NaN%) 456s Number of heterozygous SNPs: 0 (NaN%) 456s Chromosome: 1 456s Segmenting DH signals... 456s Segmenting by CBS... 456s Chromosome: NA 456s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 456s Segmenting by CBS...done 456s List of 4 456s $ data :'data.frame': 0 obs. of 4 variables: 456s ..$ chromosome: int(0) 456s ..$ x : num(0) 456s ..$ y : num(0) 456s ..$ index : int(0) 456s $ output :'data.frame': 0 obs. of 6 variables: 456s ..$ sampleName: chr(0) 456s ..$ chromosome: num(0) 456s ..$ start : num(0) 456s ..$ end : num(0) 456s ..$ nbrOfLoci : int(0) 456s ..$ mean : num(0) 456s $ segRows:'data.frame': 0 obs. of 2 variables: 456s ..$ startRow: int(0) 456s ..$ endRow : int(0) 456s $ params :List of 5 456s ..$ alpha : num 0.001 456s ..$ undo : num 0 456s ..$ joinSegments : logi TRUE 456s ..$ knownSegments:'data.frame': 0 obs. of 3 variables: 456s .. ..$ chromosome: int(0) 456s .. ..$ start : num(0) 456s .. ..$ end : num(0) 456s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 456s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 456s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.001 0 0.001 0 0 456s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 456s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 456s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 456s DH segmentation (locally-indexed) rows: 456s [1] startRow endRow 456s <0 rows> (or 0-length row.names) 456s int(0) 456s DH segmentation rows: 456s [1] startRow endRow 456s <0 rows> (or 0-length row.names) 456s Segmenting DH signals...done 456s DH segmentation table: 456s dhStart dhEnd dhNbrOfLoci dhMean 456s NA NA NA NA NA 456s startRow endRow 456s NA NA NA 456s Rows: 456s [1] 2 456s TCN segmentation rows: 456s startRow endRow 456s 2 NA NA 456s TCN and DH segmentation rows: 456s startRow endRow 456s 2 NA NA 456s startRow endRow 456s NA NA NA 456s startRow endRow 456s 1 1 7586 456s TCN segmentation (expanded) rows: 456s startRow endRow 456s 1 1 7586 456s 2 NA NA 456s TCN and DH segmentation rows: 456s startRow endRow 456s 1 1 7586 456s 2 NA NA 456s 3 7587 10267 456s 4 10268 14658 456s startRow endRow 456s 1 10 7574 456s 2 NA NA 456s startRow endRow 456s 1 1 7586 456s 2 NA NA 456s Total CN segmentation table (expanded): 456s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 456s 2 1 120908859 142693887 0 NA 0 0 456s (TCN,DH) segmentation for one total CN segment: 456s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 456s 2 2 1 1 120908859 142693887 0 NA 0 456s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 456s 2 0 NA NA NA NA 456s Total CN segment #2 ([1.20909e+08,1.42694e+08]) of 4...done 456s Total CN segment #3 ([1.42694e+08,1.8545e+08]) of 4... 456s Number of TCN loci in segment: 2681 456s Locus data for TCN segment: 456s 'data.frame': 2681 obs. of 9 variables: 456s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 456s $ x : num 1.43e+08 1.43e+08 1.43e+08 1.43e+08 1.44e+08 ... 456s $ CT : num 2.27 1.55 1.47 1.5 1.81 ... 456s $ betaT : num 0.34 0.55 0.048 0.813 0.575 ... 456s $ betaTN : num 0.441 0.629 -0.05 0.958 0.872 ... 456s $ betaN : num 0.3851 0.3933 0.0981 0.8552 0.7028 ... 456s $ muN : num 0.5 0.5 0 1 1 1 1 0.5 1 1 ... 456s $ index : int 7587 7588 7589 7590 7591 7592 7593 7594 7595 7596 ... 456s $ rho : num 0.117 0.258 NA NA NA ... 456s Number of loci: 2681 456s Number of SNPs: 777 (28.98%) 456s Number of heterozygous SNPs: 777 (100.00%) 456s Chromosome: 1 456s Segmenting DH signals... 456s Segmenting by CBS... 456s Chromosome: 1 456s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 456s Segmenting by CBS...done 456s List of 4 456s $ data :'data.frame': 2681 obs. of 4 variables: 456s ..$ chromosome: int [1:2681] 1 1 1 1 1 1 1 1 1 1 ... 456s ..$ x : num [1:2681] 1.43e+08 1.43e+08 1.43e+08 1.43e+08 1.44e+08 ... 456s ..$ y : num [1:2681] 0.117 0.258 NA NA NA ... 456s ..$ index : int [1:2681] 1 2 3 4 5 6 7 8 9 10 ... 456s $ output :'data.frame': 1 obs. of 6 variables: 456s ..$ sampleName: chr NA 456s ..$ chromosome: int 1 456s ..$ start : num 1.43e+08 456s ..$ end : num 1.85e+08 456s ..$ nbrOfLoci : int 777 456s ..$ mean : num 0.0973 456s $ segRows:'data.frame': 1 obs. of 2 variables: 456s ..$ startRow: int 1 456s ..$ endRow : int 2677 456s $ params :List of 5 456s ..$ alpha : num 0.001 456s ..$ undo : num 0 456s ..$ joinSegments : logi TRUE 456s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 456s .. ..$ chromosome: int 1 456s .. ..$ start : num 1.43e+08 456s .. ..$ end : num 1.85e+08 456s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 456s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 456s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.005 0 0.005 0 0 456s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 456s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 456s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 456s DH segmentation (locally-indexed) rows: 456s startRow endRow 456s 1 1 2677 456s int [1:2681] 7587 7588 7589 7590 7591 7592 7593 7594 7595 7596 ... 456s DH segmentation rows: 456s startRow endRow 456s 1 7587 10263 456s Segmenting DH signals...done 456s DH segmentation table: 456s dhStart dhEnd dhNbrOfLoci dhMean 456s 1 142693888 185449813 777 0.0973 456s startRow endRow 456s 1 7587 10263 456s Rows: 456s [1] 3 456s TCN segmentation rows: 456s startRow endRow 456s 3 7587 10267 456s TCN and DH segmentation rows: 456s startRow endRow 456s 3 7587 10267 456s startRow endRow 456s 1 7587 10263 456s startRow endRow 456s 1 1 7586 456s 2 NA NA 456s TCN segmentation (expanded) rows: 456s startRow endRow 456s 1 1 7586 456s 2 NA NA 456s 3 7587 10267 456s TCN and DH segmentation rows: 456s startRow endRow 456s 1 1 7586 456s 2 NA NA 456s 3 7587 10267 456s 4 10268 14658 456s startRow endRow 456s 1 10 7574 456s 2 NA NA 456s 3 7587 10263 456s startRow endRow 456s 1 1 7586 456s 2 NA NA 456s 3 7587 10267 456s Total CN segmentation table (expanded): 456s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 456s 3 1 142693888 185449813 2681 2.0689 777 777 456s (TCN,DH) segmentation for one total CN segment: 456s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 456s 3 3 1 1 142693888 185449813 2681 2.0689 777 456s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 456s 3 777 142693888 185449813 777 0.0973 456s Total CN segment #3 ([1.42694e+08,1.8545e+08]) of 4...done 456s Total CN segment #4 ([1.8545e+08,2.47137e+08]) of 4... 456s Number of TCN loci in segment: 4391 456s Locus data for TCN segment: 456s 'data.frame': 4391 obs. of 9 variables: 456s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 456s $ x : num 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 456s $ CT : num 2.93 2.15 2.82 2.93 2.46 ... 456s $ betaT : num 0.0811 0.5154 0.9473 0.3734 0.7506 ... 456s $ betaTN : num -0.169 0.609 1.028 0.525 0.968 ... 456s $ betaN : num 0.25 0.38 0.919 0.34 0.783 ... 456s $ muN : num 0 0.5 1 0.5 1 1 0 1 0 1 ... 456s $ index : int 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 456s $ rho : num NA 0.2186 NA 0.0503 NA ... 456s Number of loci: 4391 456s Number of SNPs: 1311 (29.86%) 456s Number of heterozygous SNPs: 1311 (100.00%) 456s Chromosome: 1 456s Segmenting DH signals... 456s Segmenting by CBS... 456s Chromosome: 1 456s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 456s Segmenting by CBS...done 456s List of 4 456s $ data :'data.frame': 4391 obs. of 4 variables: 456s ..$ chromosome: int [1:4391] 1 1 1 1 1 1 1 1 1 1 ... 456s ..$ x : num [1:4391] 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 456s ..$ y : num [1:4391] NA 0.2186 NA 0.0503 NA ... 456s ..$ index : int [1:4391] 1 2 3 4 5 6 7 8 9 10 ... 456s $ output :'data.frame': 1 obs. of 6 variables: 456s ..$ sampleName: chr NA 456s ..$ chromosome: int 1 456s ..$ start : num 1.85e+08 456s ..$ end : num 2.47e+08 456s ..$ nbrOfLoci : int 1311 456s ..$ mean : num 0.23 456s $ segRows:'data.frame': 1 obs. of 2 variables: 456s ..$ startRow: int 2 456s ..$ endRow : int 4388 456s $ params :List of 5 456s ..$ alpha : num 0.001 456s ..$ undo : num 0 456s ..$ joinSegments : logi TRUE 456s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 456s .. ..$ chromosome: int 1 456s .. ..$ start : num 1.85e+08 456s .. ..$ end : num 2.47e+08 456s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 456s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 456s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.01 0 0.009 0 0 456s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 456s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 456s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 456s DH segmentation (locally-indexed) rows: 456s startRow endRow 456s 1 2 4388 456s int [1:4391] 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 456s DH segmentation rows: 456s startRow endRow 456s 1 10269 14655 456s Segmenting DH signals...done 456s DH segmentation table: 456s dhStart dhEnd dhNbrOfLoci dhMean 456s 1 185449813 247137334 1311 0.2295 456s startRow endRow 456s 1 10269 14655 456s Rows: 456s [1] 4 456s TCN segmentation rows: 456s startRow endRow 456s 4 10268 14658 456s TCN and DH segmentation rows: 456s startRow endRow 456s 4 10268 14658 456s startRow endRow 456s 1 10269 14655 456s startRow endRow 456s 1 1 7586 456s 2 NA NA 456s 3 7587 10267 456s TCN segmentation (expanded) rows: 456s startRow endRow 456s 1 1 7586 456s 2 NA NA 456s 3 7587 10267 456s 4 10268 14658 456s TCN and DH segmentation rows: 456s startRow endRow 456s 1 1 7586 456s 2 NA NA 456s 3 7587 10267 456s 4 10268 14658 456s startRow endRow 456s 1 10 7574 456s 2 NA NA 456s 3 7587 10263 456s 4 10269 14655 456s startRow endRow 456s 1 1 7586 456s 2 NA NA 456s 3 7587 10267 456s 4 10268 14658 456s Total CN segmentation table (expanded): 456s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 456s 4 1 185449813 247137334 4391 2.6341 1311 1311 456s (TCN,DH) segmentation for one total CN segment: 456s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 456s 4 4 1 1 185449813 247137334 4391 2.6341 1311 456s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 456s 4 1311 185449813 247137334 1311 0.2295 456s Total CN segment #4 ([1.8545e+08,2.47137e+08]) of 4...done 456s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 456s 1 1 1 1 554484 120908858 7586 1.3853 2108 456s 2 1 2 1 120908859 142693887 0 NA 0 456s 3 1 3 1 142693888 185449813 2681 2.0689 777 456s 4 1 4 1 185449813 247137334 4391 2.6341 1311 456s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 456s 1 2108 554484 120908858 2108 0.5116 456s 2 0 NA NA NA NA 456s 3 777 142693888 185449813 777 0.0973 456s 4 1311 185449813 247137334 1311 0.2295 456s Calculating (C1,C2) per segment... 456s Calculating (C1,C2) per segment...done 456s Number of segments: 4 456s Segmenting paired tumor-normal signals using Paired PSCBS...done 456s Post-segmenting TCNs... 456s Number of segments: 4 456s Number of chromosomes: 1 456s [1] 1 456s Chromosome 1 ('chr01') of 1... 456s Rows: 456s [1] 1 2 3 4 456s Number of segments: 4 456s TCN segment #1 ('1') of 4... 456s Nothing todo. Only one DH segmentation. Skipping. 456s TCN segment #1 ('1') of 4...done 456s TCN segment #2 ('2') of 4... 456s Nothing todo. Only one DH segmentation. Skipping. 456s TCN segment #2 ('2') of 4...done 456s TCN segment #3 ('3') of 4... 456s Nothing todo. Only one DH segmentation. Skipping. 456s TCN segment #3 ('3') of 4...done 456s TCN segment #4 ('4') of 4... 456s Nothing todo. Only one DH segmentation. Skipping. 456s TCN segment #4 ('4') of 4...done 456s Chromosome 1 ('chr01') of 1...done 456s Update (C1,C2) per segment... 456s Update (C1,C2) per segment...done 456s Post-segmenting TCNs...done 456s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 456s 1 1 1 1 554484 120908858 7586 1.3853 2108 456s 2 1 2 1 120908859 142693887 0 NA 0 456s 3 1 3 1 142693888 185449813 2681 2.0689 777 456s 4 1 4 1 185449813 247137334 4391 2.6341 1311 456s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 456s 1 2108 554484 120908858 2108 0.5116 0.3382903 1.047010 456s 2 0 NA NA NA NA NA NA 456s 3 777 142693888 185449813 777 0.0973 0.9337980 1.135102 456s 4 1311 185449813 247137334 1311 0.2295 1.0147870 1.619313 456s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 456s 1 1 1 1 554484 120908858 7586 1.3853 2108 456s 2 1 2 1 120908859 142693887 0 NA 0 456s 3 1 3 1 142693888 185449813 2681 2.0689 777 456s 4 1 4 1 185449813 247137334 4391 2.6341 1311 456s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 456s 1 2108 554484 120908858 2108 0.5116 0.3382903 1.047010 456s 2 0 NA NA NA NA NA NA 456s 3 777 142693888 185449813 777 0.0973 0.9337980 1.135102 456s 4 1311 185449813 247137334 1311 0.2295 1.0147870 1.619313 456s - segmentByPairedPSCBS() w/ known segments using 'multisession' futures ... 456s Segmenting paired tumor-normal signals using Paired PSCBS... 456s Calling genotypes from normal allele B fractions... 456s num [1:14670] 0.8274 0.5072 0.1671 0.1609 0.0421 ... 456s Called genotypes: 456s num [1:14670] 1 0.5 0 0 0 0 1 0 1 0.5 ... 456s - attr(*, "modelFit")=List of 1 456s ..$ :List of 7 456s .. ..$ flavor : chr "density" 456s .. ..$ cn : int 2 456s .. ..$ nbrOfGenotypeGroups: int 3 456s .. ..$ tau : num [1:2] 0.315 0.677 456s .. ..$ n : int 14640 456s .. ..$ fit :Classes ‘PeaksAndValleys’ and 'data.frame': 5 obs. of 3 variables: 456s .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 456s .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 456s .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 456s .. ..$ fitValleys :Classes ‘PeaksAndValleys’ and 'data.frame': 2 obs. of 3 variables: 456s .. .. ..$ type : chr [1:2] "valley" "valley" 456s .. .. ..$ x : num [1:2] 0.315 0.677 456s .. .. ..$ density: num [1:2] 0.522 0.551 456s ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 456s muN 456s 0 0.5 1 456s 5221 4198 5251 456s Calling genotypes from normal allele B fractions...done 456s Normalizing betaT using betaN (TumorBoost)... 456s Normalized BAFs: 456s num [1:14670] 0.9301 0.1667 0.0685 0.0995 0.0155 ... 456s - attr(*, "modelFit")=List of 5 456s ..$ method : chr "normalizeTumorBoost" 456s ..$ flavor : chr "v4" 456s ..$ delta : num [1:14670] -0.17264 0.00239 0.1671 0.16085 0.04213 ... 456s .. ..- attr(*, "modelFit")=List of 1 456s .. .. ..$ :List of 7 456s .. .. .. ..$ flavor : chr "density" 456s .. .. .. ..$ cn : int 2 456s .. .. .. ..$ nbrOfGenotypeGroups: int 3 456s .. .. .. ..$ tau : num [1:2] 0.315 0.677 456s .. .. .. ..$ n : int 14640 456s .. .. .. ..$ fit :Classes ‘PeaksAndValleys’ and 'data.frame': 5 obs. of 3 variables: 456s .. .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 456s .. .. .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 456s .. .. .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 456s .. .. .. ..$ fitValleys :Classes ‘PeaksAndValleys’ and 'data.frame': 2 obs. of 3 variables: 456s .. .. .. .. ..$ type : chr [1:2] "valley" "valley" 456s .. .. .. .. ..$ x : num [1:2] 0.315 0.677 456s .. .. .. .. ..$ density: num [1:2] 0.522 0.551 456s .. .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 456s ..$ preserveScale: logi FALSE 456s ..$ scaleFactor : num NA 456s Normalizing betaT using betaN (TumorBoost)...done 456s Setup up data... 456s 'data.frame': 14670 obs. of 7 variables: 456s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 456s $ x : num 1145994 2941694 3710825 4240737 4276892 ... 456s $ CT : num 1.63 1.4 1.41 1.17 1.16 ... 456s $ betaT : num 0.7574 0.169 0.2357 0.2604 0.0576 ... 456s $ betaTN : num 0.9301 0.1667 0.0685 0.0995 0.0155 ... 456s ..- attr(*, "modelFit")=List of 5 456s .. ..$ method : chr "normalizeTumorBoost" 456s .. ..$ flavor : chr "v4" 456s .. ..$ delta : num [1:14670] -0.17264 0.00239 0.1671 0.16085 0.04213 ... 456s .. .. ..- attr(*, "modelFit")=List of 1 456s .. .. .. ..$ :List of 7 456s .. .. .. .. ..$ flavor : chr "density" 456s .. .. .. .. ..$ cn : int 2 456s .. .. .. .. ..$ nbrOfGenotypeGroups: int 3 456s .. .. .. .. ..$ tau : num [1:2] 0.315 0.677 456s .. .. .. .. ..$ n : int 14640 456s .. .. .. .. ..$ fit :Classes ‘PeaksAndValleys’ and 'data.frame': 5 obs. of 3 variables: 456s .. .. .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 456s .. .. .. .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 456s .. .. .. .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 456s .. .. .. .. ..$ fitValleys :Classes ‘PeaksAndValleys’ and 'data.frame': 2 obs. of 3 variables: 456s .. .. .. .. .. ..$ type : chr [1:2] "valley" "valley" 456s .. .. .. .. .. ..$ x : num [1:2] 0.315 0.677 456s .. .. .. .. .. ..$ density: num [1:2] 0.522 0.551 456s .. .. .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 456s .. ..$ preserveScale: logi FALSE 456s .. ..$ scaleFactor : num NA 456s $ betaN : num 0.8274 0.5072 0.1671 0.1609 0.0421 ... 456s $ muN : num 1 0.5 0 0 0 0 1 0 1 0.5 ... 456s ..- attr(*, "modelFit")=List of 1 456s .. ..$ :List of 7 456s .. .. ..$ flavor : chr "density" 456s .. .. ..$ cn : int 2 456s .. .. ..$ nbrOfGenotypeGroups: int 3 456s .. .. ..$ tau : num [1:2] 0.315 0.677 456s .. .. ..$ n : int 14640 456s .. .. ..$ fit :Classes ‘PeaksAndValleys’ and 'data.frame': 5 obs. of 3 variables: 456s .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 456s .. .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 456s .. .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 456s .. .. ..$ fitValleys :Classes ‘PeaksAndValleys’ and 'data.frame': 2 obs. of 3 variables: 456s .. .. .. ..$ type : chr [1:2] "valley" "valley" 456s .. .. .. ..$ x : num [1:2] 0.315 0.677 456s .. .. .. ..$ density: num [1:2] 0.522 0.551 456s .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 456s Setup up data...done 456s Dropping loci for which TCNs are missing... 456s Number of loci dropped: 12 456s Dropping loci for which TCNs are missing...done 456s Ordering data along genome... 456s 'data.frame': 14658 obs. of 7 variables: 456s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 456s $ x : num 554484 730720 782343 878522 916294 ... 456s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 456s $ betaT : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 456s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 456s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 456s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 456s Ordering data along genome...done 456s Keeping only current chromosome for 'knownSegments'... 457s Chromosome: 1 457s Known segments for this chromosome: 457s chromosome start end length 457s 1 1 -Inf 120908858 Inf 457s 2 1 120908859 142693887 21785028 457s 3 1 142693888 Inf Inf 457s Keeping only current chromosome for 'knownSegments'...done 457s alphaTCN: 0.009 457s alphaDH: 0.001 457s Number of loci: 14658 457s Calculating DHs... 457s Number of SNPs: 14658 457s Number of heterozygous SNPs: 4196 (28.63%) 457s Normalized DHs: 457s num [1:14658] NA NA NA NA NA ... 457s Calculating DHs...done 457s Random seed temporarily set (seed=c(48879), kind="L'Ecuyer-CMRG") 457s Produced 2 seeds from this stream for future usage 457s Identification of change points by total copy numbers... 457s Segmenting by CBS... 457s Chromosome: 1 457s Random seed temporarily set (seed=c(10407, 1066287653, -51199871, 161854402, -1995183193, 1503453565, -747102133), kind="L'Ecuyer-CMRG") 457s Produced 3 seeds from this stream for future usage 458s Segmenting by CBS...done 458s List of 4 458s $ data :'data.frame': 14658 obs. of 4 variables: 458s ..$ chromosome: int [1:14658] 1 1 1 1 1 1 1 1 1 1 ... 458s ..$ x : num [1:14658] 554484 730720 782343 878522 916294 ... 458s ..$ y : num [1:14658] 1.88 1.8 1.59 1.64 1.53 ... 458s ..$ index : int [1:14658] 1 2 3 4 5 6 7 8 9 10 ... 458s $ output :'data.frame': 4 obs. of 6 variables: 458s ..$ sampleName: chr [1:4] NA NA NA NA 458s ..$ chromosome: int [1:4] 1 1 1 1 458s ..$ start : num [1:4] 5.54e+05 1.21e+08 1.43e+08 1.85e+08 458s ..$ end : num [1:4] 1.21e+08 1.43e+08 1.85e+08 2.47e+08 458s ..$ nbrOfLoci : int [1:4] 7586 0 2681 4391 458s ..$ mean : num [1:4] 1.39 NA 2.07 2.63 458s $ segRows:'data.frame': 4 obs. of 2 variables: 458s ..$ startRow: int [1:4] 1 NA 7587 10268 458s ..$ endRow : int [1:4] 7586 NA 10267 14658 458s $ params :List of 5 458s ..$ alpha : num 0.009 458s ..$ undo : num 0 458s ..$ joinSegments : logi TRUE 458s ..$ knownSegments:'data.frame': 4 obs. of 3 variables: 458s .. ..$ chromosome: int [1:4] 1 1 2 1 458s .. ..$ start : num [1:4] -Inf -Inf -Inf 1.43e+08 458s .. ..$ end : num [1:4] 1.21e+08 Inf Inf Inf 458s ..$ seed : int [1:7] 10407 1066287653 -51199871 161854402 -1995183193 1503453565 -747102133 458s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 458s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.08 0.001 0.081 0 0 458s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 458s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 458s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 458s Identification of change points by total copy numbers...done 458s Restructure TCN segmentation results... 458s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean 458s 1 1 554484 120908858 7586 1.3853 458s 2 1 120908859 142693887 0 NA 458s 3 1 142693888 185449813 2681 2.0689 458s 4 1 185449813 247137334 4391 2.6341 458s Number of TCN segments: 4 458s Restructure TCN segmentation results...done 458s Total CN segment #1 ([ 554484,1.20909e+08]) of 4... 458s Number of TCN loci in segment: 7586 458s Locus data for TCN segment: 458s 'data.frame': 7586 obs. of 9 variables: 458s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 458s $ x : num 554484 730720 782343 878522 916294 ... 458s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 458s $ betaT : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 458s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 458s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 458s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 458s $ index : int 1 2 3 4 5 6 7 8 9 10 ... 458s $ rho : num NA NA NA NA NA ... 458s Number of loci: 7586 458s Number of SNPs: 2108 (27.79%) 458s Number of heterozygous SNPs: 2108 (100.00%) 458s Chromosome: 1 458s Segmenting DH signals... 458s Segmenting by CBS... 458s Chromosome: 1 458s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 458s Segmenting by CBS...done 458s List of 4 458s $ data :'data.frame': 7586 obs. of 4 variables: 458s ..$ chromosome: int [1:7586] 1 1 1 1 1 1 1 1 1 1 ... 458s ..$ x : num [1:7586] 554484 730720 782343 878522 916294 ... 458s ..$ y : num [1:7586] NA NA NA NA NA ... 458s ..$ index : int [1:7586] 1 2 3 4 5 6 7 8 9 10 ... 458s $ output :'data.frame': 1 obs. of 6 variables: 458s ..$ sampleName: chr NA 458s ..$ chromosome: int 1 458s ..$ start : num 554484 458s ..$ end : num 1.21e+08 458s ..$ nbrOfLoci : int 2108 458s ..$ mean : num 0.512 458s $ segRows:'data.frame': 1 obs. of 2 variables: 458s ..$ startRow: int 10 458s ..$ endRow : int 7574 458s $ params :List of 5 458s ..$ alpha : num 0.001 458s ..$ undo : num 0 458s ..$ joinSegments : logi TRUE 458s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 458s .. ..$ chromosome: int 1 458s .. ..$ start : num 554484 458s .. ..$ end : num 1.21e+08 458s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 458s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 458s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.026 0 0.025 0 0 458s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 458s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 458s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 458s DH segmentation (locally-indexed) rows: 458s startRow endRow 458s 1 10 7574 458s int [1:7586] 1 2 3 4 5 6 7 8 9 10 ... 458s DH segmentation rows: 458s startRow endRow 458s 1 10 7574 458s Segmenting DH signals...done 458s DH segmentation table: 458s dhStart dhEnd dhNbrOfLoci dhMean 458s 1 554484 120908858 2108 0.5116 458s startRow endRow 458s 1 10 7574 458s Rows: 458s [1] 1 458s TCN segmentation rows: 458s startRow endRow 458s 1 1 7586 458s TCN and DH segmentation rows: 458s startRow endRow 458s 1 1 7586 458s startRow endRow 458s 1 10 7574 458s NULL 458s TCN segmentation (expanded) rows: 458s startRow endRow 458s 1 1 7586 458s TCN and DH segmentation rows: 458s startRow endRow 458s 1 1 7586 458s 2 NA NA 458s 3 7587 10267 458s 4 10268 14658 458s startRow endRow 458s 1 10 7574 458s startRow endRow 458s 1 1 7586 458s Total CN segmentation table (expanded): 458s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 458s 1 1 554484 120908858 7586 1.3853 2108 2108 458s (TCN,DH) segmentation for one total CN segment: 458s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 458s 1 1 1 1 554484 120908858 7586 1.3853 2108 458s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 458s 1 2108 554484 120908858 2108 0.5116 458s Total CN segment #1 ([ 554484,1.20909e+08]) of 4...done 458s Total CN segment #2 ([1.20909e+08,1.42694e+08]) of 4... 458s Number of TCN loci in segment: 0 458s Locus data for TCN segment: 458s 'data.frame': 0 obs. of 9 variables: 458s $ chromosome: int 458s $ x : num 458s $ CT : num 458s $ betaT : num 458s $ betaTN : num 458s $ betaN : num 458s $ muN : num 458s $ index : int 458s $ rho : num 458s Number of loci: 0 458s Number of SNPs: 0 (NaN%) 458s Number of heterozygous SNPs: 0 (NaN%) 458s Chromosome: 1 458s Segmenting DH signals... 458s Segmenting by CBS... 458s Chromosome: NA 458s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 458s Segmenting by CBS...done 458s List of 4 458s $ data :'data.frame': 0 obs. of 4 variables: 458s ..$ chromosome: int(0) 458s ..$ x : num(0) 458s ..$ y : num(0) 458s ..$ index : int(0) 458s $ output :'data.frame': 0 obs. of 6 variables: 458s ..$ sampleName: chr(0) 458s ..$ chromosome: num(0) 458s ..$ start : num(0) 458s ..$ end : num(0) 458s ..$ nbrOfLoci : int(0) 458s ..$ mean : num(0) 458s $ segRows:'data.frame': 0 obs. of 2 variables: 458s ..$ startRow: int(0) 458s ..$ endRow : int(0) 458s $ params :List of 5 458s ..$ alpha : num 0.001 458s ..$ undo : num 0 458s ..$ joinSegments : logi TRUE 458s ..$ knownSegments:'data.frame': 0 obs. of 3 variables: 458s .. ..$ chromosome: int(0) 458s .. ..$ start : num(0) 458s .. ..$ end : num(0) 458s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 458s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 458s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.001 0 0.001 0 0 458s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 458s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 458s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 458s DH segmentation (locally-indexed) rows: 458s [1] startRow endRow 458s <0 rows> (or 0-length row.names) 458s int(0) 458s DH segmentation rows: 458s [1] startRow endRow 458s <0 rows> (or 0-length row.names) 458s Segmenting DH signals...done 458s DH segmentation table: 458s dhStart dhEnd dhNbrOfLoci dhMean 458s NA NA NA NA NA 458s startRow endRow 458s NA NA NA 458s Rows: 458s [1] 2 458s TCN segmentation rows: 458s startRow endRow 458s 2 NA NA 458s TCN and DH segmentation rows: 458s startRow endRow 458s 2 NA NA 458s startRow endRow 458s NA NA NA 458s startRow endRow 458s 1 1 7586 458s TCN segmentation (expanded) rows: 458s startRow endRow 458s 1 1 7586 458s 2 NA NA 458s TCN and DH segmentation rows: 458s startRow endRow 458s 1 1 7586 458s 2 NA NA 458s 3 7587 10267 458s 4 10268 14658 458s startRow endRow 458s 1 10 7574 458s 2 NA NA 458s startRow endRow 458s 1 1 7586 458s 2 NA NA 458s Total CN segmentation table (expanded): 458s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 458s 2 1 120908859 142693887 0 NA 0 0 458s (TCN,DH) segmentation for one total CN segment: 458s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 458s 2 2 1 1 120908859 142693887 0 NA 0 458s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 458s 2 0 NA NA NA NA 458s Total CN segment #2 ([1.20909e+08,1.42694e+08]) of 4...done 458s Total CN segment #3 ([1.42694e+08,1.8545e+08]) of 4... 458s Number of TCN loci in segment: 2681 458s Locus data for TCN segment: 458s 'data.frame': 2681 obs. of 9 variables: 458s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 458s $ x : num 1.43e+08 1.43e+08 1.43e+08 1.43e+08 1.44e+08 ... 458s $ CT : num 2.27 1.55 1.47 1.5 1.81 ... 458s $ betaT : num 0.34 0.55 0.048 0.813 0.575 ... 458s $ betaTN : num 0.441 0.629 -0.05 0.958 0.872 ... 458s $ betaN : num 0.3851 0.3933 0.0981 0.8552 0.7028 ... 458s $ muN : num 0.5 0.5 0 1 1 1 1 0.5 1 1 ... 458s $ index : int 7587 7588 7589 7590 7591 7592 7593 7594 7595 7596 ... 458s $ rho : num 0.117 0.258 NA NA NA ... 458s Number of loci: 2681 458s Number of SNPs: 777 (28.98%) 458s Number of heterozygous SNPs: 777 (100.00%) 458s Chromosome: 1 458s Segmenting DH signals... 458s Segmenting by CBS... 458s Chromosome: 1 458s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 458s Segmenting by CBS...done 458s List of 4 458s $ data :'data.frame': 2681 obs. of 4 variables: 458s ..$ chromosome: int [1:2681] 1 1 1 1 1 1 1 1 1 1 ... 458s ..$ x : num [1:2681] 1.43e+08 1.43e+08 1.43e+08 1.43e+08 1.44e+08 ... 458s ..$ y : num [1:2681] 0.117 0.258 NA NA NA ... 458s ..$ index : int [1:2681] 1 2 3 4 5 6 7 8 9 10 ... 458s $ output :'data.frame': 1 obs. of 6 variables: 458s ..$ sampleName: chr NA 458s ..$ chromosome: int 1 458s ..$ start : num 1.43e+08 458s ..$ end : num 1.85e+08 458s ..$ nbrOfLoci : int 777 458s ..$ mean : num 0.0973 458s $ segRows:'data.frame': 1 obs. of 2 variables: 458s ..$ startRow: int 1 458s ..$ endRow : int 2677 458s $ params :List of 5 458s ..$ alpha : num 0.001 458s ..$ undo : num 0 458s ..$ joinSegments : logi TRUE 458s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 458s .. ..$ chromosome: int 1 458s .. ..$ start : num 1.43e+08 458s .. ..$ end : num 1.85e+08 458s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 458s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 458s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.005 0 0.005 0 0 458s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 458s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 458s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 458s DH segmentation (locally-indexed) rows: 458s startRow endRow 458s 1 1 2677 458s int [1:2681] 7587 7588 7589 7590 7591 7592 7593 7594 7595 7596 ... 458s DH segmentation rows: 458s startRow endRow 458s 1 7587 10263 458s Segmenting DH signals...done 458s DH segmentation table: 458s dhStart dhEnd dhNbrOfLoci dhMean 458s 1 142693888 185449813 777 0.0973 458s startRow endRow 458s 1 7587 10263 458s Rows: 458s [1] 3 458s TCN segmentation rows: 458s startRow endRow 458s 3 7587 10267 458s TCN and DH segmentation rows: 458s startRow endRow 458s 3 7587 10267 458s startRow endRow 458s 1 7587 10263 458s startRow endRow 458s 1 1 7586 458s 2 NA NA 458s TCN segmentation (expanded) rows: 458s startRow endRow 458s 1 1 7586 458s 2 NA NA 458s 3 7587 10267 458s TCN and DH segmentation rows: 458s startRow endRow 458s 1 1 7586 458s 2 NA NA 458s 3 7587 10267 458s 4 10268 14658 458s startRow endRow 458s 1 10 7574 458s 2 NA NA 458s 3 7587 10263 458s startRow endRow 458s 1 1 7586 458s 2 NA NA 458s 3 7587 10267 458s Total CN segmentation table (expanded): 458s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 458s 3 1 142693888 185449813 2681 2.0689 777 777 458s (TCN,DH) segmentation for one total CN segment: 458s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 458s 3 3 1 1 142693888 185449813 2681 2.0689 777 458s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 458s 3 777 142693888 185449813 777 0.0973 458s Total CN segment #3 ([1.42694e+08,1.8545e+08]) of 4...done 458s Total CN segment #4 ([1.8545e+08,2.47137e+08]) of 4... 458s Number of TCN loci in segment: 4391 458s Locus data for TCN segment: 458s 'data.frame': 4391 obs. of 9 variables: 458s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 458s $ x : num 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 458s $ CT : num 2.93 2.15 2.82 2.93 2.46 ... 458s $ betaT : num 0.0811 0.5154 0.9473 0.3734 0.7506 ... 458s $ betaTN : num -0.169 0.609 1.028 0.525 0.968 ... 458s $ betaN : num 0.25 0.38 0.919 0.34 0.783 ... 458s $ muN : num 0 0.5 1 0.5 1 1 0 1 0 1 ... 458s $ index : int 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 458s $ rho : num NA 0.2186 NA 0.0503 NA ... 458s Number of loci: 4391 458s Number of SNPs: 1311 (29.86%) 458s Number of heterozygous SNPs: 1311 (100.00%) 458s Chromosome: 1 458s Segmenting DH signals... 458s Segmenting by CBS... 458s Chromosome: 1 458s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 458s Segmenting by CBS...done 458s List of 4 458s $ data :'data.frame': 4391 obs. of 4 variables: 458s ..$ chromosome: int [1:4391] 1 1 1 1 1 1 1 1 1 1 ... 458s ..$ x : num [1:4391] 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 458s ..$ y : num [1:4391] NA 0.2186 NA 0.0503 NA ... 458s ..$ index : int [1:4391] 1 2 3 4 5 6 7 8 9 10 ... 458s $ output :'data.frame': 1 obs. of 6 variables: 458s ..$ sampleName: chr NA 458s ..$ chromosome: int 1 458s ..$ start : num 1.85e+08 458s ..$ end : num 2.47e+08 458s ..$ nbrOfLoci : int 1311 458s ..$ mean : num 0.23 458s $ segRows:'data.frame': 1 obs. of 2 variables: 458s ..$ startRow: int 2 458s ..$ endRow : int 4388 458s $ params :List of 5 458s ..$ alpha : num 0.001 458s ..$ undo : num 0 458s ..$ joinSegments : logi TRUE 458s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 458s .. ..$ chromosome: int 1 458s .. ..$ start : num 1.85e+08 458s .. ..$ end : num 2.47e+08 458s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 458s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 458s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.01 0 0.01 0 0 458s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 458s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 458s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 458s DH segmentation (locally-indexed) rows: 458s startRow endRow 458s 1 2 4388 458s int [1:4391] 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 458s DH segmentation rows: 458s startRow endRow 458s 1 10269 14655 458s Segmenting DH signals...done 458s DH segmentation table: 458s dhStart dhEnd dhNbrOfLoci dhMean 458s 1 185449813 247137334 1311 0.2295 458s startRow endRow 458s 1 10269 14655 458s Rows: 458s [1] 4 458s TCN segmentation rows: 458s startRow endRow 458s 4 10268 14658 458s TCN and DH segmentation rows: 458s startRow endRow 458s 4 10268 14658 458s startRow endRow 458s 1 10269 14655 458s startRow endRow 458s 1 1 7586 458s 2 NA NA 458s 3 7587 10267 458s TCN segmentation (expanded) rows: 458s startRow endRow 458s 1 1 7586 458s 2 NA NA 458s 3 7587 10267 458s 4 10268 14658 458s TCN and DH segmentation rows: 458s startRow endRow 458s 1 1 7586 458s 2 NA NA 458s 3 7587 10267 458s 4 10268 14658 458s startRow endRow 458s 1 10 7574 458s 2 NA NA 458s 3 7587 10263 458s 4 10269 14655 458s startRow endRow 458s 1 1 7586 458s 2 NA NA 458s 3 7587 10267 458s 4 10268 14658 458s Total CN segmentation table (expanded): 458s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 458s 4 1 185449813 247137334 4391 2.6341 1311 1311 458s (TCN,DH) segmentation for one total CN segment: 458s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 458s 4 4 1 1 185449813 247137334 4391 2.6341 1311 458s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 458s 4 1311 185449813 247137334 1311 0.2295 458s Total CN segment #4 ([1.8545e+08,2.47137e+08]) of 4...done 458s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 458s 1 1 1 1 554484 120908858 7586 1.3853 2108 458s 2 1 2 1 120908859 142693887 0 NA 0 458s 3 1 3 1 142693888 185449813 2681 2.0689 777 458s 4 1 4 1 185449813 247137334 4391 2.6341 1311 458s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 458s 1 2108 554484 120908858 2108 0.5116 458s 2 0 NA NA NA NA 458s 3 777 142693888 185449813 777 0.0973 458s 4 1311 185449813 247137334 1311 0.2295 458s Calculating (C1,C2) per segment... 458s Calculating (C1,C2) per segment...done 458s Number of segments: 4 458s Segmenting paired tumor-normal signals using Paired PSCBS...done 458s Post-segmenting TCNs... 458s Number of segments: 4 458s Number of chromosomes: 1 458s [1] 1 458s Chromosome 1 ('chr01') of 1... 458s Rows: 458s [1] 1 2 3 4 458s Number of segments: 4 458s TCN segment #1 ('1') of 4... 458s Nothing todo. Only one DH segmentation. Skipping. 458s TCN segment #1 ('1') of 4...done 458s TCN segment #2 ('2') of 4... 458s Nothing todo. Only one DH segmentation. Skipping. 458s TCN segment #2 ('2') of 4...done 458s TCN segment #3 ('3') of 4... 458s Nothing todo. Only one DH segmentation. Skipping. 458s TCN segment #3 ('3') of 4...done 458s TCN segment #4 ('4') of 4... 458s Nothing todo. Only one DH segmentation. Skipping. 458s TCN segment #4 ('4') of 4...done 458s Chromosome 1 ('chr01') of 1...done 458s Update (C1,C2) per segment... 458s Update (C1,C2) per segment...done 458s Post-segmenting TCNs...done 458s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 458s 1 1 1 1 554484 120908858 7586 1.3853 2108 458s 2 1 2 1 120908859 142693887 0 NA 0 458s 3 1 3 1 142693888 185449813 2681 2.0689 777 458s 4 1 4 1 185449813 247137334 4391 2.6341 1311 458s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 458s 1 2108 554484 120908858 2108 0.5116 0.3382903 1.047010 458s 2 0 NA NA NA NA NA NA 458s 3 777 142693888 185449813 777 0.0973 0.9337980 1.135102 458s 4 1311 185449813 247137334 1311 0.2295 1.0147870 1.619313 458s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 458s 1 1 1 1 554484 120908858 7586 1.3853 2108 458s 2 1 2 1 120908859 142693887 0 NA 0 458s 3 1 3 1 142693888 185449813 2681 2.0689 777 458s 4 1 4 1 185449813 247137334 4391 2.6341 1311 458s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 458s 1 2108 554484 120908858 2108 0.5116 0.3382903 1.047010 458s 2 0 NA NA NA NA NA NA 458s 3 777 142693888 185449813 777 0.0973 0.9337980 1.135102 458s 4 1311 185449813 247137334 1311 0.2295 1.0147870 1.619313 458s > 458s > message("*** segmentByPairedPSCBS() via futures ... DONE") 458s *** segmentByPairedPSCBS() via futures ... DONE 458s > 458s > 458s > ## Cleanup 458s > plan(oplan) 458s > rm(list=c("fits", "data", "fit")) 458s > 458s Start: segmentByPairedPSCBS,noNormalBAFs.R 458s 458s R version 4.5.2 (2025-10-31) -- "[Not] Part in a Rumble" 458s Copyright (C) 2025 The R Foundation for Statistical Computing 458s Platform: x86_64-pc-linux-gnu 458s 458s R is free software and comes with ABSOLUTELY NO WARRANTY. 458s You are welcome to redistribute it under certain conditions. 458s Type 'license()' or 'licence()' for distribution details. 458s 458s R is a collaborative project with many contributors. 458s Type 'contributors()' for more information and 458s 'citation()' on how to cite R or R packages in publications. 458s 458s Type 'demo()' for some demos, 'help()' for on-line help, or 458s 'help.start()' for an HTML browser interface to help. 458s Type 'q()' to quit R. 458s 458s > library("PSCBS") 458s PSCBS v0.68.0 (2025-04-18 19:40:02 UTC) successfully loaded. See ?PSCBS for help. 458s > 458s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 458s > # Load SNP microarray data 458s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 458s > data <- PSCBS::exampleData("paired.chr01") 458s > str(data) 458s 'data.frame': 73346 obs. of 6 variables: 458s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 458s $ x : int 1145994 2224111 2319424 2543484 2926730 2941694 3084986 3155127 3292731 3695086 ... 458s $ CT : num 1.625 1.071 1.406 1.18 0.856 ... 458s $ betaT : num 0.757 0.771 0.834 0.778 0.229 ... 458s $ CN : num 2.36 2.13 2.59 1.93 1.71 ... 458s $ betaN : num 0.827 0.875 0.887 0.884 0.103 ... 458s > 458s > # Drop single-locus outliers 458s > dataS <- dropSegmentationOutliers(data) 458s > 458s > # Run light-weight tests by default 458s > if (Sys.getenv("_R_CHECK_FULL_") == "") { 458s + # Use only every 5th data point 458s + dataS <- dataS[seq(from=1, to=nrow(data), by=5),] 458s + # Number of segments (for assertion) 458s + nSegs <- 3L 458s + # Number of bootstrap samples (see below) 458s + B <- 100L 458s + } else { 458s + # Full tests 458s + nSegs <- 8L 458s + B <- 1000L 458s + } 458s > 458s > str(dataS) 458s 'data.frame': 14670 obs. of 6 variables: 458s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 458s $ x : int 1145994 2941694 3710825 4240737 4276892 4464544 4714611 5095111 5034491 5158416 ... 458s $ CT : num 1.63 1.4 1.41 1.17 1.16 ... 458s $ betaT : num 0.7574 0.169 0.2357 0.2604 0.0576 ... 458s $ CN : num 2.36 2.13 2.26 2.01 2.32 ... 458s $ betaN : num 0.8274 0.5072 0.1671 0.1609 0.0421 ... 458s > 458s > R.oo::attachLocally(dataS) 458s > 458s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 458s > # Simulate that genotypes are known by other means 458s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 458s > library("aroma.light") 458s aroma.light v3.36.0 (2024-10-29) successfully loaded. See ?aroma.light for help. 458s > muN <- aroma.light::callNaiveGenotypes(betaN, censorAt=c(0,1)) 458s > 458s > 458s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 458s > # Paired PSCBS segmentation 458s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 458s > fit <- segmentByPairedPSCBS(CT, betaT=betaT, muN=muN, tbn=FALSE, 458s + chromosome=chromosome, x=x, 458s + seed=0xBEEF, verbose=-10) 458s Segmenting paired tumor-normal signals using Paired PSCBS... 458s Setup up data... 458s 'data.frame': 14670 obs. of 6 variables: 458s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 458s $ x : num 1145994 2941694 3710825 4240737 4276892 ... 458s $ CT : num 1.63 1.4 1.41 1.17 1.16 ... 458s $ betaT : num 0.7574 0.169 0.2357 0.2604 0.0576 ... 458s $ betaTN : num 0.7574 0.169 0.2357 0.2604 0.0576 ... 458s $ muN : num 1 0.5 0 0 0 0 1 0 1 0.5 ... 458s ..- attr(*, "modelFit")=List of 1 458s .. ..$ :List of 7 458s .. .. ..$ flavor : chr "density" 458s .. .. ..$ cn : int 2 458s .. .. ..$ nbrOfGenotypeGroups: int 3 458s .. .. ..$ tau : num [1:2] 0.315 0.677 458s .. .. ..$ n : int 14640 458s .. .. ..$ fit :Classes ‘PeaksAndValleys’ and 'data.frame': 5 obs. of 3 variables: 458s .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 458s .. .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 458s .. .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 458s .. .. ..$ fitValleys :Classes ‘PeaksAndValleys’ and 'data.frame': 2 obs. of 3 variables: 458s .. .. .. ..$ type : chr [1:2] "valley" "valley" 458s .. .. .. ..$ x : num [1:2] 0.315 0.677 458s .. .. .. ..$ density: num [1:2] 0.522 0.551 458s .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 458s Setup up data...done 458s Dropping loci for which TCNs are missing... 458s Number of loci dropped: 12 458s Dropping loci for which TCNs are missing...done 458s Ordering data along genome... 458s 'data.frame': 14658 obs. of 6 variables: 458s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 458s $ x : num 554484 730720 782343 878522 916294 ... 458s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 458s $ betaT : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 458s $ betaTN : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 458s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 458s Ordering data along genome...done 458s Keeping only current chromosome for 'knownSegments'... 458s Chromosome: 1 458s Known segments for this chromosome: 458s [1] chromosome start end 458s <0 rows> (or 0-length row.names) 458s Keeping only current chromosome for 'knownSegments'...done 458s alphaTCN: 0.009 458s alphaDH: 0.001 458s Number of loci: 14658 458s Calculating DHs... 458s Number of SNPs: 14658 458s Number of heterozygous SNPs: 4196 (28.63%) 458s Normalized DHs: 458s num [1:14658] NA NA NA NA NA ... 458s Calculating DHs...done 458s Random seed temporarily set (seed=c(48879), kind="L'Ecuyer-CMRG") 458s Produced 2 seeds from this stream for future usage 458s Identification of change points by total copy numbers... 458s Segmenting by CBS... 458s Chromosome: 1 458s Random seed temporarily set (seed=c(10407, 1066287653, -51199871, 161854402, -1995183193, 1503453565, -747102133), kind="L'Ecuyer-CMRG") 458s Segmenting by CBS...done 458s List of 4 458s $ data :'data.frame': 14658 obs. of 4 variables: 458s ..$ chromosome: int [1:14658] 1 1 1 1 1 1 1 1 1 1 ... 458s ..$ x : num [1:14658] 554484 730720 782343 878522 916294 ... 458s ..$ y : num [1:14658] 1.88 1.8 1.59 1.64 1.53 ... 458s ..$ index : int [1:14658] 1 2 3 4 5 6 7 8 9 10 ... 458s $ output :'data.frame': 3 obs. of 6 variables: 458s ..$ sampleName: chr [1:3] NA NA NA 458s ..$ chromosome: int [1:3] 1 1 1 458s ..$ start : num [1:3] 5.54e+05 1.44e+08 1.85e+08 458s ..$ end : num [1:3] 1.44e+08 1.85e+08 2.47e+08 458s ..$ nbrOfLoci : int [1:3] 7599 2668 4391 458s ..$ mean : num [1:3] 1.39 2.07 2.63 458s $ segRows:'data.frame': 3 obs. of 2 variables: 458s ..$ startRow: int [1:3] 1 7600 10268 458s ..$ endRow : int [1:3] 7599 10267 14658 458s $ params :List of 5 458s ..$ alpha : num 0.009 458s ..$ undo : num 0 458s ..$ joinSegments : logi TRUE 458s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 458s .. ..$ chromosome: int 1 458s .. ..$ start : num -Inf 458s .. ..$ end : num Inf 458s ..$ seed : int [1:7] 10407 1066287653 -51199871 161854402 -1995183193 1503453565 -747102133 458s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 458s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.23 0 0.231 0 0 458s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 458s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 458s - attr(*, "randomSeed")= int [1:7] 10407 1066287653 -51199871 161854402 -1995183193 1503453565 -747102133 458s Identification of change points by total copy numbers...done 458s Restructure TCN segmentation results... 458s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean 458s 1 1 554484 143926517 7599 1.3859 458s 2 1 143926517 185449813 2668 2.0704 458s 3 1 185449813 247137334 4391 2.6341 458s Number of TCN segments: 3 458s Restructure TCN segmentation results...done 458s Total CN segment #1 ([ 554484,1.43927e+08]) of 3... 458s Number of TCN loci in segment: 7599 458s Locus data for TCN segment: 458s 'data.frame': 7599 obs. of 8 variables: 458s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 458s $ x : num 554484 730720 782343 878522 916294 ... 458s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 458s $ betaT : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 458s $ betaTN : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 458s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 458s $ index : int 1 2 3 4 5 6 7 8 9 10 ... 458s $ rho : num NA NA NA NA NA ... 458s Number of loci: 7599 458s Number of SNPs: 2111 (27.78%) 458s Number of heterozygous SNPs: 2111 (100.00%) 458s Chromosome: 1 458s Segmenting DH signals... 458s Segmenting by CBS... 458s Chromosome: 1 458s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 459s Segmenting by CBS...done 459s List of 4 459s $ data :'data.frame': 7599 obs. of 4 variables: 459s ..$ chromosome: int [1:7599] 1 1 1 1 1 1 1 1 1 1 ... 459s ..$ x : num [1:7599] 554484 730720 782343 878522 916294 ... 459s ..$ y : num [1:7599] NA NA NA NA NA ... 459s ..$ index : int [1:7599] 1 2 3 4 5 6 7 8 9 10 ... 459s $ output :'data.frame': 1 obs. of 6 variables: 459s ..$ sampleName: chr NA 459s ..$ chromosome: int 1 459s ..$ start : num 554484 459s ..$ end : num 1.44e+08 459s ..$ nbrOfLoci : int 2111 459s ..$ mean : num 0.524 459s $ segRows:'data.frame': 1 obs. of 2 variables: 459s ..$ startRow: int 10 459s ..$ endRow : int 7594 459s $ params :List of 5 459s ..$ alpha : num 0.001 459s ..$ undo : num 0 459s ..$ joinSegments : logi TRUE 459s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 459s .. ..$ chromosome: int 1 459s .. ..$ start : num 554484 459s .. ..$ end : num 1.44e+08 459s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 459s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 459s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.016 0 0.017 0 0 459s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 459s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 459s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 459s DH segmentation (locally-indexed) rows: 459s startRow endRow 459s 1 10 7594 459s int [1:7599] 1 2 3 4 5 6 7 8 9 10 ... 459s DH segmentation rows: 459s startRow endRow 459s 1 10 7594 459s Segmenting DH signals...done 459s DH segmentation table: 459s dhStart dhEnd dhNbrOfLoci dhMean 459s 1 554484 143926517 2111 0.5237 459s startRow endRow 459s 1 10 7594 459s Rows: 459s [1] 1 459s TCN segmentation rows: 459s startRow endRow 459s 1 1 7599 459s TCN and DH segmentation rows: 459s startRow endRow 459s 1 1 7599 459s startRow endRow 459s 1 10 7594 459s NULL 459s TCN segmentation (expanded) rows: 459s startRow endRow 459s 1 1 7599 459s TCN and DH segmentation rows: 459s startRow endRow 459s 1 1 7599 459s 2 7600 10267 459s 3 10268 14658 459s startRow endRow 459s 1 10 7594 459s startRow endRow 459s 1 1 7599 459s Total CN segmentation table (expanded): 459s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 459s 1 1 554484 143926517 7599 1.3859 2111 2111 459s (TCN,DH) segmentation for one total CN segment: 459s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 459s 1 1 1 1 554484 143926517 7599 1.3859 2111 459s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 459s 1 2111 554484 143926517 2111 0.5237 459s Total CN segment #1 ([ 554484,1.43927e+08]) of 3...done 459s Total CN segment #2 ([1.43927e+08,1.8545e+08]) of 3... 459s Number of TCN loci in segment: 2668 459s Locus data for TCN segment: 459s 'data.frame': 2668 obs. of 8 variables: 459s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 459s $ x : num 1.44e+08 1.44e+08 1.44e+08 1.44e+08 1.44e+08 ... 459s $ CT : num 2.1 2.1 2.09 1.8 2.34 ... 459s $ betaT : num 0.1899 0.909 0.9166 0.1668 0.0308 ... 459s $ betaTN : num 0.1899 0.909 0.9166 0.1668 0.0308 ... 459s $ muN : num 0 1 1 0 0 1 0 0 0 0 ... 459s $ index : int 7600 7601 7602 7603 7604 7605 7606 7607 7608 7609 ... 459s $ rho : num NA NA NA NA NA NA NA NA NA NA ... 459s Number of loci: 2668 459s Number of SNPs: 774 (29.01%) 459s Number of heterozygous SNPs: 774 (100.00%) 459s Chromosome: 1 459s Segmenting DH signals... 459s Segmenting by CBS... 459s Chromosome: 1 459s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 459s Segmenting by CBS...done 459s List of 4 459s $ data :'data.frame': 2668 obs. of 4 variables: 459s ..$ chromosome: int [1:2668] 1 1 1 1 1 1 1 1 1 1 ... 459s ..$ x : num [1:2668] 1.44e+08 1.44e+08 1.44e+08 1.44e+08 1.44e+08 ... 459s ..$ y : num [1:2668] NA NA NA NA NA NA NA NA NA NA ... 459s ..$ index : int [1:2668] 1 2 3 4 5 6 7 8 9 10 ... 459s $ output :'data.frame': 1 obs. of 6 variables: 459s ..$ sampleName: chr NA 459s ..$ chromosome: int 1 459s ..$ start : num 1.44e+08 459s ..$ end : num 1.85e+08 459s ..$ nbrOfLoci : int 774 459s ..$ mean : num 0.154 459s $ segRows:'data.frame': 1 obs. of 2 variables: 459s ..$ startRow: int 15 459s ..$ endRow : int 2664 459s $ params :List of 5 459s ..$ alpha : num 0.001 459s ..$ undo : num 0 459s ..$ joinSegments : logi TRUE 459s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 459s .. ..$ chromosome: int 1 459s .. ..$ start : num 1.44e+08 459s .. ..$ end : num 1.85e+08 459s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 459s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 459s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.006 0 0.005 0 0 459s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 459s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 459s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 459s DH segmentation (locally-indexed) rows: 459s startRow endRow 459s 1 15 2664 459s int [1:2668] 7600 7601 7602 7603 7604 7605 7606 7607 7608 7609 ... 459s DH segmentation rows: 459s startRow endRow 459s 1 7614 10263 459s Segmenting DH signals...done 459s DH segmentation table: 459s dhStart dhEnd dhNbrOfLoci dhMean 459s 1 143926517 185449813 774 0.1542 459s startRow endRow 459s 1 7614 10263 459s Rows: 459s [1] 2 459s TCN segmentation rows: 459s startRow endRow 459s 2 7600 10267 459s TCN and DH segmentation rows: 459s startRow endRow 459s 2 7600 10267 459s startRow endRow 459s 1 7614 10263 459s startRow endRow 459s 1 1 7599 459s TCN segmentation (expanded) rows: 459s startRow endRow 459s 1 1 7599 459s 2 7600 10267 459s TCN and DH segmentation rows: 459s startRow endRow 459s 1 1 7599 459s 2 7600 10267 459s 3 10268 14658 459s startRow endRow 459s 1 10 7594 459s 2 7614 10263 459s startRow endRow 459s 1 1 7599 459s 2 7600 10267 459s Total CN segmentation table (expanded): 459s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 459s 2 1 143926517 185449813 2668 2.0704 774 774 459s (TCN,DH) segmentation for one total CN segment: 459s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 459s 2 2 1 1 143926517 185449813 2668 2.0704 774 459s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 459s 2 774 143926517 185449813 774 0.1542 459s Total CN segment #2 ([1.43927e+08,1.8545e+08]) of 3...done 459s Total CN segment #3 ([1.8545e+08,2.47137e+08]) of 3... 459s Number of TCN loci in segment: 4391 459s Locus data for TCN segment: 459s 'data.frame': 4391 obs. of 8 variables: 459s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 459s $ x : num 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 459s $ CT : num 2.93 2.15 2.82 2.93 2.46 ... 459s $ betaT : num 0.0811 0.5154 0.9473 0.3734 0.7506 ... 459s $ betaTN : num 0.0811 0.5154 0.9473 0.3734 0.7506 ... 459s $ muN : num 0 0.5 1 0.5 1 1 0 1 0 1 ... 459s $ index : int 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 459s $ rho : num NA 0.0308 NA 0.2533 NA ... 459s Number of loci: 4391 459s Number of SNPs: 1311 (29.86%) 459s Number of heterozygous SNPs: 1311 (100.00%) 459s Chromosome: 1 459s Segmenting DH signals... 459s Segmenting by CBS... 459s Chromosome: 1 459s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 459s Segmenting by CBS...done 459s List of 4 459s $ data :'data.frame': 4391 obs. of 4 variables: 459s ..$ chromosome: int [1:4391] 1 1 1 1 1 1 1 1 1 1 ... 459s ..$ x : num [1:4391] 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 459s ..$ y : num [1:4391] NA 0.0308 NA 0.2533 NA ... 459s ..$ index : int [1:4391] 1 2 3 4 5 6 7 8 9 10 ... 459s $ output :'data.frame': 1 obs. of 6 variables: 459s ..$ sampleName: chr NA 459s ..$ chromosome: int 1 459s ..$ start : num 1.85e+08 459s ..$ end : num 2.47e+08 459s ..$ nbrOfLoci : int 1311 459s ..$ mean : num 0.251 459s $ segRows:'data.frame': 1 obs. of 2 variables: 459s ..$ startRow: int 2 459s ..$ endRow : int 4388 459s $ params :List of 5 459s ..$ alpha : num 0.001 459s ..$ undo : num 0 459s ..$ joinSegments : logi TRUE 459s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 459s .. ..$ chromosome: int 1 459s .. ..$ start : num 1.85e+08 459s .. ..$ end : num 2.47e+08 459s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 459s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 459s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.013 0 0.013 0 0 459s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 459s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 459s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 459s DH segmentation (locally-indexed) rows: 459s startRow endRow 459s 1 2 4388 459s int [1:4391] 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 459s DH segmentation rows: 459s startRow endRow 459s 1 10269 14655 459s Segmenting DH signals...done 459s DH segmentation table: 459s dhStart dhEnd dhNbrOfLoci dhMean 459s 1 185449813 247137334 1311 0.2512 459s startRow endRow 459s 1 10269 14655 459s Rows: 459s [1] 3 459s TCN segmentation rows: 459s startRow endRow 459s 3 10268 14658 459s TCN and DH segmentation rows: 459s startRow endRow 459s 3 10268 14658 459s startRow endRow 459s 1 10269 14655 459s startRow endRow 459s 1 1 7599 459s 2 7600 10267 459s TCN segmentation (expanded) rows: 459s startRow endRow 459s 1 1 7599 459s 2 7600 10267 459s 3 10268 14658 459s TCN and DH segmentation rows: 459s startRow endRow 459s 1 1 7599 459s 2 7600 10267 459s 3 10268 14658 459s startRow endRow 459s 1 10 7594 459s 2 7614 10263 459s 3 10269 14655 459s startRow endRow 459s 1 1 7599 459s 2 7600 10267 459s 3 10268 14658 459s Total CN segmentation table (expanded): 459s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 459s 3 1 185449813 247137334 4391 2.6341 1311 1311 459s (TCN,DH) segmentation for one total CN segment: 459s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 459s 3 3 1 1 185449813 247137334 4391 2.6341 1311 459s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 459s 3 1311 185449813 247137334 1311 0.2512 459s Total CN segment #3 ([1.8545e+08,2.47137e+08]) of 3...done 459s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 459s 1 1 1 1 554484 143926517 7599 1.3859 2111 459s 2 1 2 1 143926517 185449813 2668 2.0704 774 459s 3 1 3 1 185449813 247137334 4391 2.6341 1311 459s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 459s 1 2111 554484 143926517 2111 0.5237 459s 2 774 143926517 185449813 774 0.1542 459s 3 1311 185449813 247137334 1311 0.2512 459s Calculating (C1,C2) per segment... 459s Calculating (C1,C2) per segment...done 459s Number of segments: 3 459s Segmenting paired tumor-normal signals using Paired PSCBS...done 459s Post-segmenting TCNs... 459s Number of segments: 3 459s Number of chromosomes: 1 459s [1] 1 459s Chromosome 1 ('chr01') of 1... 459s Rows: 459s [1] 1 2 3 459s Number of segments: 3 459s TCN segment #1 ('1') of 3... 459s Nothing todo. Only one DH segmentation. Skipping. 459s TCN segment #1 ('1') of 3...done 459s TCN segment #2 ('2') of 3... 459s Nothing todo. Only one DH segmentation. Skipping. 459s TCN segment #2 ('2') of 3...done 459s TCN segment #3 ('3') of 3... 459s Nothing todo. Only one DH segmentation. Skipping. 459s TCN segment #3 ('3') of 3...done 459s Chromosome 1 ('chr01') of 1...done 459s Update (C1,C2) per segment... 459s Update (C1,C2) per segment...done 459s Post-segmenting TCNs...done 459s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 459s 1 1 1 1 554484 143926517 7599 1.3859 2111 459s 2 1 2 1 143926517 185449813 2668 2.0704 774 459s 3 1 3 1 185449813 247137334 4391 2.6341 1311 459s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 459s 1 2111 554484 143926517 2111 0.5237 0.3300521 1.055848 459s 2 774 143926517 185449813 774 0.1542 0.8755722 1.194828 459s 3 1311 185449813 247137334 1311 0.2512 0.9862070 1.647893 459s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 459s 1 1 1 1 554484 143926517 7599 1.3859 2111 459s 2 1 2 1 143926517 185449813 2668 2.0704 774 459s 3 1 3 1 185449813 247137334 4391 2.6341 1311 459s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 459s 1 2111 554484 143926517 2111 0.5237 0.3300521 1.055848 459s 2 774 143926517 185449813 774 0.1542 0.8755722 1.194828 459s 3 1311 185449813 247137334 1311 0.2512 0.9862070 1.647893 459s > print(fit) 459s chromosome tcnId dhId start end tcnNbrOfLoci tcnMean tcnNbrOfSNPs 459s 1 1 1 1 554484 143926517 7599 1.3859 2111 459s 2 1 2 1 143926517 185449813 2668 2.0704 774 459s 3 1 3 1 185449813 247137334 4391 2.6341 1311 459s tcnNbrOfHets dhNbrOfLoci dhMean c1Mean c2Mean 459s 1 2111 2111 0.5237 0.3300521 1.055848 459s 2 774 774 0.1542 0.8755722 1.194828 459s 3 1311 1311 0.2512 0.9862070 1.647893 459s > 459s > # Plot results 459s > plotTracks(fit) 459s Resample (TCN,DH) signals and re-estimate summaries for segment & changepoint... 459s > 459s > # Sanity check 459s > stopifnot(nbrOfSegments(fit) == nSegs) 459s > 459s > 459s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 459s > # Bootstrap segment level estimates 459s > # (used by the AB caller, which, if skipped here, 459s > # will do it automatically) 459s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 459s > fit <- bootstrapTCNandDHByRegion(fit, B=B, verbose=-10) 459s Already done? 459s tcn_2.5% tcn_5% tcn_95% tcn_97.5% dh_2.5% dh_5% dh_95% dh_97.5% 459s FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE 459s c1_2.5% c1_5% c1_95% c1_97.5% c2_2.5% c2_5% c2_95% c2_97.5% 459s FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE 459s Bootstrapping (TCN,DH,C1,C2) segment mean levels... 459s Identifying heterozygous & homozygous SNPs and non-polymorphic loci... 459s Number of loci: 14658 459s Number of SNPs: 4196 459s Number of non-SNPs: 10462 459s Identifying heterozygous & homozygous SNPs and non-polymorphic loci...done 459s num [1:3, 1:100, 1:4] NA NA NA NA NA NA NA NA NA NA ... 459s - attr(*, "dimnames")=List of 3 459s ..$ : NULL 459s ..$ : NULL 459s ..$ : chr [1:4] "tcn" "dh" "c1" "c2" 459s Segment #1 (chr 1, tcnId=1, dhId=1) of 3... 459s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 459s 1 1 1 1 554484 143926517 7599 1.3859 2111 459s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 459s 1 2111 554484 143926517 2111 0.5237 0.3300521 1.055848 459s Number of TCNs: 7599 459s Number of DHs: 2111 459s int [1:7599] 1 2 3 4 5 6 7 8 9 10 ... 459s int [1:14658] 1 2 3 4 5 6 7 8 9 10 ... 459s int [1:7599] 1 2 3 4 5 6 7 8 9 10 ... 459s Identify loci used to bootstrap DH means... 459s Heterozygous SNPs to resample for DH: 459s int [1:2111] 10 12 24 28 31 33 34 39 46 48 ... 459s Identify loci used to bootstrap DH means...done 459s Identify loci used to bootstrap TCN means... 459s SNPs: 459s int [1:2111] 10 12 24 28 31 33 34 39 46 48 ... 459s Non-polymorphic loci: 459s int [1:5488] 1 2 3 4 5 6 7 8 9 11 ... 459s Heterozygous SNPs to resample for TCN: 459s int [1:2111] 10 12 24 28 31 33 34 39 46 48 ... 459s Homozygous SNPs to resample for TCN: 459s int(0) 459s Non-polymorphic loci to resample for TCN: 459s int [1:5488] 1 2 3 4 5 6 7 8 9 11 ... 459s Heterozygous SNPs with non-DH to resample for TCN: 459s int(0) 459s Loci to resample for TCN: 459s int [1:7599] 1 2 3 4 5 6 7 8 9 10 ... 459s Identify loci used to bootstrap TCN means...done 459s Number of (#hets, #homs, #nonSNPs): (2111,0,5488) 459s Bootstrapping while preserving (#hets, #homs, #nonSNPs)... 459s Number of bootstrap samples: 100 459s Bootstrapping while preserving (#hets, #homs, #nonSNPs)...done 459s Segment #1 (chr 1, tcnId=1, dhId=1) of 3...done 459s Segment #2 (chr 1, tcnId=2, dhId=1) of 3... 459s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 459s 2 1 2 1 143926517 185449813 2668 2.0704 774 459s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 459s 2 774 143926517 185449813 774 0.1542 0.8755722 1.194828 459s Number of TCNs: 2668 459s Number of DHs: 774 459s int [1:2668] 7600 7601 7602 7603 7604 7605 7606 7607 7608 7609 ... 459s int [1:14658] 1 2 3 4 5 6 7 8 9 10 ... 459s int [1:2668] 7600 7601 7602 7603 7604 7605 7606 7607 7608 7609 ... 459s Identify loci used to bootstrap DH means... 459s Heterozygous SNPs to resample for DH: 459s int [1:774] 7614 7616 7626 7627 7628 7635 7638 7639 7640 7642 ... 459s Identify loci used to bootstrap DH means...done 459s Identify loci used to bootstrap TCN means... 459s SNPs: 459s int [1:774] 7614 7616 7626 7627 7628 7635 7638 7639 7640 7642 ... 459s Non-polymorphic loci: 459s int [1:1894] 7600 7601 7602 7603 7604 7605 7606 7607 7608 7609 ... 459s Heterozygous SNPs to resample for TCN: 459s int [1:774] 7614 7616 7626 7627 7628 7635 7638 7639 7640 7642 ... 459s Homozygous SNPs to resample for TCN: 459s int(0) 459s Non-polymorphic loci to resample for TCN: 459s int [1:1894] 7600 7601 7602 7603 7604 7605 7606 7607 7608 7609 ... 459s Heterozygous SNPs with non-DH to resample for TCN: 459s int(0) 459s Loci to resample for TCN: 459s int [1:2668] 7600 7601 7602 7603 7604 7605 7606 7607 7608 7609 ... 459s Identify loci used to bootstrap TCN means...done 459s Number of (#hets, #homs, #nonSNPs): (774,0,1894) 459s Bootstrapping while preserving (#hets, #homs, #nonSNPs)... 459s Number of bootstrap samples: 100 459s Bootstrapping while preserving (#hets, #homs, #nonSNPs)...done 459s Segment #2 (chr 1, tcnId=2, dhId=1) of 3...done 459s Segment #3 (chr 1, tcnId=3, dhId=1) of 3... 459s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 459s 3 1 3 1 185449813 247137334 4391 2.6341 1311 459s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 459s 3 1311 185449813 247137334 1311 0.2512 0.986207 1.647893 459s Number of TCNs: 4391 459s Number of DHs: 1311 459s int [1:4391] 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 459s int [1:14658] 1 2 3 4 5 6 7 8 9 10 ... 459s int [1:4391] 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 459s Identify loci used to bootstrap DH means... 459s Heterozygous SNPs to resample for DH: 459s int [1:1311] 10269 10271 10281 10282 10283 10293 10295 10297 10300 10302 ... 459s Identify loci used to bootstrap DH means...done 459s Identify loci used to bootstrap TCN means... 459s SNPs: 459s int [1:1311] 10269 10271 10281 10282 10283 10293 10295 10297 10300 10302 ... 459s Non-polymorphic loci: 459s int [1:3080] 10268 10270 10272 10273 10274 10275 10276 10277 10278 10279 ... 459s Heterozygous SNPs to resample for TCN: 459s int [1:1311] 10269 10271 10281 10282 10283 10293 10295 10297 10300 10302 ... 459s Homozygous SNPs to resample for TCN: 459s int(0) 459s Non-polymorphic loci to resample for TCN: 459s int [1:3080] 10268 10270 10272 10273 10274 10275 10276 10277 10278 10279 ... 459s Heterozygous SNPs with non-DH to resample for TCN: 459s int(0) 459s Loci to resample for TCN: 459s int [1:4391] 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 459s Identify loci used to bootstrap TCN means...done 459s Number of (#hets, #homs, #nonSNPs): (1311,0,3080) 459s Bootstrapping while preserving (#hets, #homs, #nonSNPs)... 459s Number of bootstrap samples: 100 459s Bootstrapping while preserving (#hets, #homs, #nonSNPs)...done 459s Segment #3 (chr 1, tcnId=3, dhId=1) of 3...done 459s Bootstrapped segment mean levels 459s num [1:3, 1:100, 1:4] 1.38 2.08 2.63 1.38 2.07 ... 459s - attr(*, "dimnames")=List of 3 459s ..$ : NULL 459s ..$ : NULL 459s ..$ : chr [1:4] "tcn" "dh" "c1" "c2" 459s Calculating (C1,C2) mean levels from (TCN,DH) mean levels... 459s num [1:3, 1:100, 1:4] 1.38 2.08 2.63 1.38 2.07 ... 459s - attr(*, "dimnames")=List of 3 459s ..$ : NULL 459s ..$ : NULL 459s ..$ : chr [1:4] "tcn" "dh" "c1" "c2" 459s Calculating (C1,C2) mean levels from (TCN,DH) mean levels...done 459s Calculating polar (alpha,radius,manhattan) for change points... 459s num [1:2, 1:100, 1:2] -0.5588 -0.0962 -0.5365 -0.1285 -0.5378 ... 459s - attr(*, "dimnames")=List of 3 459s ..$ : NULL 459s ..$ : NULL 459s ..$ : chr [1:2] "c1" "c2" 459s Bootstrapped change points 459s num [1:2, 1:100, 1:5] -2.89 -1.78 -2.87 -1.86 -2.88 ... 459s - attr(*, "dimnames")=List of 3 459s ..$ : NULL 459s ..$ : NULL 459s ..$ : chr [1:5] "alpha" "radius" "manhattan" "d1" ... 459s Calculating polar (alpha,radius,manhattan) for change points...done 459s Bootstrapping (TCN,DH,C1,C2) segment mean levels...done 459s Summarizing bootstrapped segment (‘tcn’, ‘dh’, ‘c1’, ‘c2’) data... 459s num [1:3, 1:4, 1:4] NA NA NA NA NA NA NA NA NA NA ... 459s - attr(*, "dimnames")=List of 3 459s ..$ : NULL 459s ..$ : chr [1:4] "2.5%" "5%" "95%" "97.5%" 459s ..$ : chr [1:4] "tcn" "dh" "c1" "c2" 459s Field #1 ('tcn') of 4... 459s Segment #1 of 3... 459s Segment #1 of 3...done 459s Segment #2 of 3... 459s Segment #2 of 3...done 459s Segment #3 of 3... 459s Segment #3 of 3...done 459s Field #1 ('tcn') of 4...done 459s Field #2 ('dh') of 4... 459s Segment #1 of 3... 459s Segment #1 of 3...done 459s Segment #2 of 3... 459s Segment #2 of 3...done 459s Segment #3 of 3... 459s Segment #3 of 3...done 459s Field #2 ('dh') of 4...done 459s Field #3 ('c1') of 4... 459s Segment #1 of 3... 459s Segment #1 of 3...done 459s Segment #2 of 3... 459s Segment #2 of 3...done 459s Segment #3 of 3... 459s Segment #3 of 3...done 459s Field #3 ('c1') of 4...done 459s Field #4 ('c2') of 4... 459s Segment #1 of 3... 459s Segment #1 of 3...done 459s Segment #2 of 3... 459s Segment #2 of 3...done 459s Segment #3 of 3... 459s Segment #3 of 3...done 459s Field #4 ('c2') of 4...done 459s Bootstrap statistics 459s num [1:3, 1:4, 1:4] 1.38 2.06 2.62 1.38 2.06 ... 459s - attr(*, "dimnames")=List of 3 459s ..$ : NULL 459s ..$ : chr [1:4] "2.5%" "5%" "95%" "97.5%" 459s ..$ : chr [1:4] "tcn" "dh" "c1" "c2" 459s Statistical sanity checks (iff B >= 100)... 459s Available summaries: 2.5%, 5%, 95%, 97.5% 459s Available quantiles: 0.025, 0.05, 0.95, 0.975 459s num [1:3, 1:4, 1:4] 1.38 2.06 2.62 1.38 2.06 ... 459s - attr(*, "dimnames")=List of 3 459s ..$ : NULL 459s ..$ : chr [1:4] "2.5%" "5%" "95%" "97.5%" 459s ..$ : chr [1:4] "tcn" "dh" "c1" "c2" 459s Field #1 ('tcn') of 4... 459s Seg 1. mean=1.3859, range=[1.38092,1.3949], n=7599 459s Seg 2. mean=2.0704, range=[2.05747,2.08326], n=2668 459s Seg 3. mean=2.6341, range=[2.62068,2.64694], n=4391 459s Field #1 ('tcn') of 4...done 459s Field #2 ('dh') of 4... 459s Seg 1. mean=0.5237, range=[0.51753,0.532002], n=2111 459s Seg 2. mean=0.1542, range=[0.144468,0.16453], n=774 459s Seg 3. mean=0.2512, range=[0.242575,0.258832], n=1311 459s Field #2 ('dh') of 4...done 459s Field #3 ('c1') of 4... 459s Seg 1. mean=0.330052, range=[0.323996,0.336038], n=2111 459s Seg 2. mean=0.875572, range=[0.86318,0.887699], n=774 459s Seg 3. mean=0.986207, range=[0.975123,0.998982], n=1311 459s Field #3 ('c1') of 4...done 459s Field #4 ('c2') of 4... 459s Seg 1. mean=1.05585, range=[1.05006,1.06231], n=2111 459s Seg 2. mean=1.19483, range=[1.18417,1.2081], n=774 459s Seg 3. mean=1.64789, range=[1.63403,1.66098], n=1311 459s Field #4 ('c2') of 4...done 459s Statistical sanity checks (iff B >= 100)...done 459s Summarizing bootstrapped segment (‘tcn’, ‘dh’, ‘c1’, ‘c2’) data...done 459s Summarizing bootstrapped changepoint (‘alpha’, ‘radius’, ‘manhattan’, ‘d1’, ‘d2’) data... 459s num [1:2, 1:4, 1:5] NA NA NA NA NA NA NA NA NA NA ... 459s - attr(*, "dimnames")=List of 3 459s ..$ : NULL 459s ..$ : chr [1:4] "2.5%" "5%" "95%" "97.5%" 459s ..$ : chr [1:5] "alpha" "radius" "manhattan" "d1" ... 459s Field #1 ('alpha') of 5... 459s Changepoint #1 of 2... 459s Changepoint #1 of 2...done 459s Changepoint #2 of 2... 459s Changepoint #2 of 2...done 459s Field #1 ('alpha') of 5...done 459s Field #2 ('radius') of 5... 459s Changepoint #1 of 2... 459s Changepoint #1 of 2...done 459s Changepoint #2 of 2... 459s Changepoint #2 of 2...done 459s Field #2 ('radius') of 5...done 459s Field #3 ('manhattan') of 5... 459s Changepoint #1 of 2... 459s Changepoint #1 of 2...done 459s Changepoint #2 of 2... 459s Changepoint #2 of 2...done 459s Field #3 ('manhattan') of 5...done 459s Field #4 ('d1') of 5... 459s Changepoint #1 of 2... 459s Changepoint #1 of 2...done 459s Changepoint #2 of 2... 459s Changepoint #2 of 2...done 459s Field #4 ('d1') of 5...done 459s Field #5 ('d2') of 5... 459s Changepoint #1 of 2... 459s Changepoint #1 of 2...done 459s Changepoint #2 of 2... 459s Changepoint #2 of 2...done 459s Field #5 ('d2') of 5...done 459s Bootstrap statistics 459s num [1:2, 1:4, 1:5] -2.92 -1.86 -2.91 -1.85 -2.87 ... 459s - attr(*, "dimnames")=List of 3 459s ..$ : NULL 459s ..$ : chr [1:4] "2.5%" "5%" "95%" "97.5%" 459s ..$ : chr [1:5] "alpha" "radius" "manhattan" "d1" ... 459s Summarizing bootstrapped changepoint (‘alpha’, ‘radius’, ‘manhattan’, ‘d1’, ‘d2’) data...done 459s Resample (TCN,DH) signals and re-estimate summaries for segment & changepoint...done 459s > print(fit) 459s chromosome tcnId dhId start end tcnNbrOfLoci tcnMean tcnNbrOfSNPs 459s 1 1 1 1 554484 143926517 7599 1.3859 2111 459s 2 1 2 1 143926517 185449813 2668 2.0704 774 459s 3 1 3 1 185449813 247137334 4391 2.6341 1311 459s tcnNbrOfHets dhNbrOfLoci dhMean c1Mean c2Mean 459s 1 2111 2111 0.5237 0.3300521 1.055848 459s 2 774 774 0.1542 0.8755722 1.194828 459s 3 1311 1311 0.2512 0.9862070 1.647893 459s > plotTracks(fit) 459s > 459s > 459s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 459s > # Calling segments in allelic balance (AB) and 459s > # in loss-of-heterozygosity (LOH) 459s > # NOTE: Ideally, this should be done on whole-genome data 459s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 459s > fit <- callAB(fit, verbose=-10) 459s Calling segments of allelic balance from one-sided DH bootstrap confidence intervals... 459s delta (offset adjusting for bias in DH): 0.3466649145302 459s alpha (CI quantile; significance level): 0.05 459s Calling segments... 459s Number of segments called allelic balance (AB): 2 (66.67%) of 3 459s Calling segments...done 459s Calling segments of allelic balance from one-sided DH bootstrap confidence intervals...done 459s > fit <- callLOH(fit, verbose=-10) 459s Calling segments of allelic balance from one-sided DH bootstrap confidence intervals... 459s delta (offset adjusting for bias in C1): 0.771236438183453 459s alpha (CI quantile; significance level): 0.05 459s Calling segments... 459s Number of segments called low C1 (LowC1, "LOH_C1"): 1 (33.33%) of 3 459s Calling segments...done 459s Calling segments of allelic balance from one-sided DH bootstrap confidence intervals...done 459s > print(fit) 459s chromosome tcnId dhId start end tcnNbrOfLoci tcnMean tcnNbrOfSNPs 459s 1 1 1 1 554484 143926517 7599 1.3859 2111 459s 2 1 2 1 143926517 185449813 2668 2.0704 774 459s 3 1 3 1 185449813 247137334 4391 2.6341 1311 459s tcnNbrOfHets dhNbrOfLoci dhMean c1Mean c2Mean abCall lohCall 459s 1 2111 2111 0.5237 0.3300521 1.055848 FALSE TRUE 459s 2 774 774 0.1542 0.8755722 1.194828 TRUE FALSE 459s 3 1311 1311 0.2512 0.9862070 1.647893 TRUE FALSE 459s > plotTracks(fit) 459s > 459s Start: segmentByPairedPSCBS,report.R 459s 459s R version 4.5.2 (2025-10-31) -- "[Not] Part in a Rumble" 459s Copyright (C) 2025 The R Foundation for Statistical Computing 459s Platform: x86_64-pc-linux-gnu 459s 459s R is free software and comes with ABSOLUTELY NO WARRANTY. 459s You are welcome to redistribute it under certain conditions. 459s Type 'license()' or 'licence()' for distribution details. 459s 459s R is a collaborative project with many contributors. 459s Type 'contributors()' for more information and 459s 'citation()' on how to cite R or R packages in publications. 459s 459s Type 'demo()' for some demos, 'help()' for on-line help, or 459s 'help.start()' for an HTML browser interface to help. 459s Type 'q()' to quit R. 459s 459s > # This test script calls a report generator which requires 459s > # the 'ggplot2' package, which in turn will require packages 459s > # 'colorspace', 'dichromat', 'munsell', 'reshape2' and 'scales'. 459s > 459s > # Only run this test in full testing mode 459s > if (Sys.getenv("_R_CHECK_FULL_") != "") { 459s + library("PSCBS") 459s + 459s + # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 459s + # Load SNP microarray data 459s + # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 459s + data <- PSCBS::exampleData("paired.chr01") 459s + str(data) 459s + 459s + 459s + # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 459s + # Paired PSCBS segmentation 459s + # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 459s + # Drop single-locus outliers 459s + dataS <- dropSegmentationOutliers(data) 459s + 459s + # Speed up example by segmenting fewer loci 459s + dataS <- dataS[seq(from=1, to=nrow(data), by=5),] 459s + 459s + str(dataS) 459s + 459s + gaps <- findLargeGaps(dataS, minLength=2e6) 459s + knownSegments <- gapsToSegments(gaps) 459s + 459s + # Paired PSCBS segmentation 459s + fit <- segmentByPairedPSCBS(dataS, knownSegments=knownSegments, 459s + seed=0xBEEF, verbose=-10) 459s + 459s + # Fake a multi-chromosome segmentation 459s + fit1 <- fit 459s + fit2 <- renameChromosomes(fit, from=1, to=2) 459s + fit <- c(fit1, fit2) 459s + 459s + report(fit, sampleName="PairedPSCBS", studyName="PSCBS-Ex", verbose=-10) 459s + 459s + } # if (Sys.getenv("_R_CHECK_FULL_")) 459s > 459s Start: segmentByPairedPSCBS,seqOfSegmentsByDP.R 459s 459s R version 4.5.2 (2025-10-31) -- "[Not] Part in a Rumble" 459s Copyright (C) 2025 The R Foundation for Statistical Computing 459s Platform: x86_64-pc-linux-gnu 459s 459s R is free software and comes with ABSOLUTELY NO WARRANTY. 459s You are welcome to redistribute it under certain conditions. 459s Type 'license()' or 'licence()' for distribution details. 459s 459s R is a collaborative project with many contributors. 459s Type 'contributors()' for more information and 459s 'citation()' on how to cite R or R packages in publications. 459s 459s Type 'demo()' for some demos, 'help()' for on-line help, or 459s 'help.start()' for an HTML browser interface to help. 459s Type 'q()' to quit R. 459s 459s > library("PSCBS") 460s PSCBS v0.68.0 (2025-04-18 19:40:02 UTC) successfully loaded. See ?PSCBS for help. 460s > subplots <- R.utils::subplots 460s > stext <- R.utils::stext 460s > 460s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 460s > # Load SNP microarray data 460s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 460s > data <- PSCBS::exampleData("paired.chr01") 460s > str(data) 460s 'data.frame': 73346 obs. of 6 variables: 460s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 460s $ x : int 1145994 2224111 2319424 2543484 2926730 2941694 3084986 3155127 3292731 3695086 ... 460s $ CT : num 1.625 1.071 1.406 1.18 0.856 ... 460s $ betaT : num 0.757 0.771 0.834 0.778 0.229 ... 460s $ CN : num 2.36 2.13 2.59 1.93 1.71 ... 460s $ betaN : num 0.827 0.875 0.887 0.884 0.103 ... 460s > 460s > 460s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 460s > # Paired PSCBS segmentation 460s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 460s > # Drop single-locus outliers 460s > dataS <- dropSegmentationOutliers(data) 460s > 460s > # Run light-weight tests by default 460s > if (Sys.getenv("_R_CHECK_FULL_") == "") { 460s + # Use only every 5th data point 460s + dataS <- dataS[seq(from=1, to=nrow(data), by=5),] 460s + # Number of segments (for assertion) 460s + nSegs <- 3L 460s + # Number of bootstrap samples (see below) 460s + B <- 100L 460s + } else { 460s + # Full tests 460s + nSegs <- 12L 460s + B <- 1000L 460s + } 460s > 460s > str(dataS) 460s 'data.frame': 14670 obs. of 6 variables: 460s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 460s $ x : int 1145994 2941694 3710825 4240737 4276892 4464544 4714611 5095111 5034491 5158416 ... 460s $ CT : num 1.63 1.4 1.41 1.17 1.16 ... 460s $ betaT : num 0.7574 0.169 0.2357 0.2604 0.0576 ... 460s $ CN : num 2.36 2.13 2.26 2.01 2.32 ... 460s $ betaN : num 0.8274 0.5072 0.1671 0.1609 0.0421 ... 460s > 460s > R.oo::attachLocally(dataS) 460s > 460s > 460s > gaps <- findLargeGaps(dataS, minLength=2e6) 460s > knownSegments <- gapsToSegments(gaps, dropGaps=TRUE) 460s > 460s > # Paired PSCBS segmentation 460s > fit <- segmentByPairedPSCBS(dataS, knownSegments=knownSegments, 460s + seed=0xBEEF, verbose=-10) 460s Segmenting paired tumor-normal signals using Paired PSCBS... 460s Calling genotypes from normal allele B fractions... 460s num [1:14670] 0.8274 0.5072 0.1671 0.1609 0.0421 ... 460s Called genotypes: 460s num [1:14670] 1 0.5 0 0 0 0 1 0 1 0.5 ... 460s - attr(*, "modelFit")=List of 1 460s ..$ :List of 7 460s .. ..$ flavor : chr "density" 460s .. ..$ cn : int 2 460s .. ..$ nbrOfGenotypeGroups: int 3 460s .. ..$ tau : num [1:2] 0.315 0.677 460s .. ..$ n : int 14640 460s .. ..$ fit :Classes ‘PeaksAndValleys’ and 'data.frame': 5 obs. of 3 variables: 460s .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 460s .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 460s .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 460s .. ..$ fitValleys :Classes ‘PeaksAndValleys’ and 'data.frame': 2 obs. of 3 variables: 460s .. .. ..$ type : chr [1:2] "valley" "valley" 460s .. .. ..$ x : num [1:2] 0.315 0.677 460s .. .. ..$ density: num [1:2] 0.522 0.551 460s ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 460s muN 460s 0 0.5 1 460s 5221 4198 5251 460s Calling genotypes from normal allele B fractions...done 460s Normalizing betaT using betaN (TumorBoost)... 460s Normalized BAFs: 460s num [1:14670] 0.9301 0.1667 0.0685 0.0995 0.0155 ... 460s - attr(*, "modelFit")=List of 5 460s ..$ method : chr "normalizeTumorBoost" 460s ..$ flavor : chr "v4" 460s ..$ delta : num [1:14670] -0.17264 0.00239 0.1671 0.16085 0.04213 ... 460s .. ..- attr(*, "modelFit")=List of 1 460s .. .. ..$ :List of 7 460s .. .. .. ..$ flavor : chr "density" 460s .. .. .. ..$ cn : int 2 460s .. .. .. ..$ nbrOfGenotypeGroups: int 3 460s .. .. .. ..$ tau : num [1:2] 0.315 0.677 460s .. .. .. ..$ n : int 14640 460s .. .. .. ..$ fit :Classes ‘PeaksAndValleys’ and 'data.frame': 5 obs. of 3 variables: 460s .. .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 460s .. .. .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 460s .. .. .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 460s .. .. .. ..$ fitValleys :Classes ‘PeaksAndValleys’ and 'data.frame': 2 obs. of 3 variables: 460s .. .. .. .. ..$ type : chr [1:2] "valley" "valley" 460s .. .. .. .. ..$ x : num [1:2] 0.315 0.677 460s .. .. .. .. ..$ density: num [1:2] 0.522 0.551 460s .. .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 460s ..$ preserveScale: logi FALSE 460s ..$ scaleFactor : num NA 460s Normalizing betaT using betaN (TumorBoost)...done 460s Setup up data... 460s 'data.frame': 14670 obs. of 7 variables: 460s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 460s $ x : num 1145994 2941694 3710825 4240737 4276892 ... 460s $ CT : num 1.63 1.4 1.41 1.17 1.16 ... 460s $ betaT : num 0.7574 0.169 0.2357 0.2604 0.0576 ... 460s $ betaTN : num 0.9301 0.1667 0.0685 0.0995 0.0155 ... 460s ..- attr(*, "modelFit")=List of 5 460s .. ..$ method : chr "normalizeTumorBoost" 460s .. ..$ flavor : chr "v4" 460s .. ..$ delta : num [1:14670] -0.17264 0.00239 0.1671 0.16085 0.04213 ... 460s .. .. ..- attr(*, "modelFit")=List of 1 460s .. .. .. ..$ :List of 7 460s .. .. .. .. ..$ flavor : chr "density" 460s .. .. .. .. ..$ cn : int 2 460s .. .. .. .. ..$ nbrOfGenotypeGroups: int 3 460s .. .. .. .. ..$ tau : num [1:2] 0.315 0.677 460s .. .. .. .. ..$ n : int 14640 460s .. .. .. .. ..$ fit :Classes ‘PeaksAndValleys’ and 'data.frame': 5 obs. of 3 variables: 460s .. .. .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 460s .. .. .. .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 460s .. .. .. .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 460s .. .. .. .. ..$ fitValleys :Classes ‘PeaksAndValleys’ and 'data.frame': 2 obs. of 3 variables: 460s .. .. .. .. .. ..$ type : chr [1:2] "valley" "valley" 460s .. .. .. .. .. ..$ x : num [1:2] 0.315 0.677 460s .. .. .. .. .. ..$ density: num [1:2] 0.522 0.551 460s .. .. .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 460s .. ..$ preserveScale: logi FALSE 460s .. ..$ scaleFactor : num NA 460s $ betaN : num 0.8274 0.5072 0.1671 0.1609 0.0421 ... 460s $ muN : num 1 0.5 0 0 0 0 1 0 1 0.5 ... 460s ..- attr(*, "modelFit")=List of 1 460s .. ..$ :List of 7 460s .. .. ..$ flavor : chr "density" 460s .. .. ..$ cn : int 2 460s .. .. ..$ nbrOfGenotypeGroups: int 3 460s .. .. ..$ tau : num [1:2] 0.315 0.677 460s .. .. ..$ n : int 14640 460s .. .. ..$ fit :Classes ‘PeaksAndValleys’ and 'data.frame': 5 obs. of 3 variables: 460s .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 460s .. .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 460s .. .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 460s .. .. ..$ fitValleys :Classes ‘PeaksAndValleys’ and 'data.frame': 2 obs. of 3 variables: 460s .. .. .. ..$ type : chr [1:2] "valley" "valley" 460s .. .. .. ..$ x : num [1:2] 0.315 0.677 460s .. .. .. ..$ density: num [1:2] 0.522 0.551 460s .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 460s Setup up data...done 460s Dropping loci for which TCNs are missing... 460s Number of loci dropped: 12 460s Dropping loci for which TCNs are missing...done 460s Ordering data along genome... 460s 'data.frame': 14658 obs. of 7 variables: 460s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 460s $ x : num 554484 730720 782343 878522 916294 ... 460s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 460s $ betaT : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 460s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 460s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 460s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 460s Ordering data along genome...done 460s Keeping only current chromosome for 'knownSegments'... 460s Chromosome: 1 460s Known segments for this chromosome: 460s chromosome start end length 460s 1 1 -Inf 120908858 Inf 460s 2 1 142693888 Inf Inf 460s Keeping only current chromosome for 'knownSegments'...done 460s alphaTCN: 0.009 460s alphaDH: 0.001 460s Number of loci: 14658 460s Calculating DHs... 460s Number of SNPs: 14658 460s Number of heterozygous SNPs: 4196 (28.63%) 460s Normalized DHs: 460s num [1:14658] NA NA NA NA NA ... 460s Calculating DHs...done 460s Random seed temporarily set (seed=c(48879), kind="L'Ecuyer-CMRG") 460s Produced 2 seeds from this stream for future usage 460s Identification of change points by total copy numbers... 460s Segmenting by CBS... 460s Chromosome: 1 460s Segmenting multiple segments on current chromosome... 460s Number of segments: 2 460s Random seed temporarily set (seed=c(10407, 1066287653, -51199871, 161854402, -1995183193, 1503453565, -747102133), kind="L'Ecuyer-CMRG") 460s Produced 2 seeds from this stream for future usage 460s Segmenting by CBS... 460s Chromosome: 1 460s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 460s Segmenting by CBS...done 460s Segmenting by CBS... 460s Chromosome: 1 460s Random seed temporarily set (seed=c(10407, -821273412, -52578226, 1415511586, 721384351, -665928286, 1316562960), kind="L'Ecuyer-CMRG") 460s Segmenting by CBS...done 460s Segmenting multiple segments on current chromosome...done 460s Segmenting by CBS...done 460s List of 4 460s $ data :'data.frame': 14658 obs. of 4 variables: 460s ..$ chromosome: int [1:14658] 1 1 1 1 1 1 1 1 1 1 ... 460s ..$ x : num [1:14658] 554484 730720 782343 878522 916294 ... 460s ..$ y : num [1:14658] 1.88 1.8 1.59 1.64 1.53 ... 460s ..$ index : int [1:14658] 1 2 3 4 5 6 7 8 9 10 ... 460s $ output :'data.frame': 3 obs. of 6 variables: 460s ..$ sampleName: chr [1:3] NA NA NA 460s ..$ chromosome: int [1:3] 1 1 1 460s ..$ start : num [1:3] 5.54e+05 1.43e+08 1.85e+08 460s ..$ end : num [1:3] 1.21e+08 1.85e+08 2.47e+08 460s ..$ nbrOfLoci : int [1:3] 7586 2681 4391 460s ..$ mean : num [1:3] 1.39 2.07 2.63 460s $ segRows:'data.frame': 3 obs. of 2 variables: 460s ..$ startRow: int [1:3] 1 7587 10268 460s ..$ endRow : int [1:3] 7586 10267 14658 460s $ params :List of 5 460s ..$ alpha : num 0.009 460s ..$ undo : num 0 460s ..$ joinSegments : logi TRUE 460s ..$ knownSegments:'data.frame': 2 obs. of 3 variables: 460s .. ..$ chromosome: int [1:2] 1 1 460s .. ..$ start : num [1:2] -Inf 1.43e+08 460s .. ..$ end : num [1:2] 1.21e+08 Inf 460s ..$ seed : int [1:7] 10407 1066287653 -51199871 161854402 -1995183193 1503453565 -747102133 460s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 460s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.089 0 0.089 0 0 460s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 460s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 460s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 460s Identification of change points by total copy numbers...done 460s Restructure TCN segmentation results... 460s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean 460s 1 1 554484 120908858 7586 1.3853 460s 2 1 142693888 185449813 2681 2.0689 460s 3 1 185449813 247137334 4391 2.6341 460s Number of TCN segments: 3 460s Restructure TCN segmentation results...done 460s Total CN segment #1 ([ 554484,1.20909e+08]) of 3... 460s Number of TCN loci in segment: 7586 460s Locus data for TCN segment: 460s 'data.frame': 7586 obs. of 9 variables: 460s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 460s $ x : num 554484 730720 782343 878522 916294 ... 460s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 460s $ betaT : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 460s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 460s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 460s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 460s $ index : int 1 2 3 4 5 6 7 8 9 10 ... 460s $ rho : num NA NA NA NA NA ... 460s Number of loci: 7586 460s Number of SNPs: 2108 (27.79%) 460s Number of heterozygous SNPs: 2108 (100.00%) 460s Chromosome: 1 460s Segmenting DH signals... 460s Segmenting by CBS... 460s Chromosome: 1 460s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 460s Segmenting by CBS...done 460s List of 4 460s $ data :'data.frame': 7586 obs. of 4 variables: 460s ..$ chromosome: int [1:7586] 1 1 1 1 1 1 1 1 1 1 ... 460s ..$ x : num [1:7586] 554484 730720 782343 878522 916294 ... 460s ..$ y : num [1:7586] NA NA NA NA NA ... 460s ..$ index : int [1:7586] 1 2 3 4 5 6 7 8 9 10 ... 460s $ output :'data.frame': 1 obs. of 6 variables: 460s ..$ sampleName: chr NA 460s ..$ chromosome: int 1 460s ..$ start : num 554484 460s ..$ end : num 1.21e+08 460s ..$ nbrOfLoci : int 2108 460s ..$ mean : num 0.512 460s $ segRows:'data.frame': 1 obs. of 2 variables: 460s ..$ startRow: int 10 460s ..$ endRow : int 7574 460s $ params :List of 5 460s ..$ alpha : num 0.001 460s ..$ undo : num 0 460s ..$ joinSegments : logi TRUE 460s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 460s .. ..$ chromosome: int 1 460s .. ..$ start : num 554484 460s .. ..$ end : num 1.21e+08 460s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 460s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 460s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.026 0 0.026 0 0 460s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 460s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 460s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 460s DH segmentation (locally-indexed) rows: 460s startRow endRow 460s 1 10 7574 460s int [1:7586] 1 2 3 4 5 6 7 8 9 10 ... 460s DH segmentation rows: 460s startRow endRow 460s 1 10 7574 460s Segmenting DH signals...done 460s DH segmentation table: 460s dhStart dhEnd dhNbrOfLoci dhMean 460s 1 554484 120908858 2108 0.5116 460s startRow endRow 460s 1 10 7574 460s Rows: 460s [1] 1 460s TCN segmentation rows: 460s startRow endRow 460s 1 1 7586 460s TCN and DH segmentation rows: 460s startRow endRow 460s 1 1 7586 460s startRow endRow 460s 1 10 7574 460s NULL 460s TCN segmentation (expanded) rows: 460s startRow endRow 460s 1 1 7586 460s TCN and DH segmentation rows: 460s startRow endRow 460s 1 1 7586 460s 2 7587 10267 460s 3 10268 14658 460s startRow endRow 460s 1 10 7574 460s startRow endRow 460s 1 1 7586 460s Total CN segmentation table (expanded): 460s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 460s 1 1 554484 120908858 7586 1.3853 2108 2108 460s (TCN,DH) segmentation for one total CN segment: 460s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 460s 1 1 1 1 554484 120908858 7586 1.3853 2108 460s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 460s 1 2108 554484 120908858 2108 0.5116 460s Total CN segment #1 ([ 554484,1.20909e+08]) of 3...done 460s Total CN segment #2 ([1.42694e+08,1.8545e+08]) of 3... 460s Number of TCN loci in segment: 2681 460s Locus data for TCN segment: 460s 'data.frame': 2681 obs. of 9 variables: 460s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 460s $ x : num 1.43e+08 1.43e+08 1.43e+08 1.43e+08 1.44e+08 ... 460s $ CT : num 2.27 1.55 1.47 1.5 1.81 ... 460s $ betaT : num 0.34 0.55 0.048 0.813 0.575 ... 460s $ betaTN : num 0.441 0.629 -0.05 0.958 0.872 ... 460s $ betaN : num 0.3851 0.3933 0.0981 0.8552 0.7028 ... 460s $ muN : num 0.5 0.5 0 1 1 1 1 0.5 1 1 ... 460s $ index : int 7587 7588 7589 7590 7591 7592 7593 7594 7595 7596 ... 460s $ rho : num 0.117 0.258 NA NA NA ... 460s Number of loci: 2681 460s Number of SNPs: 777 (28.98%) 460s Number of heterozygous SNPs: 777 (100.00%) 460s Chromosome: 1 460s Segmenting DH signals... 460s Segmenting by CBS... 460s Chromosome: 1 460s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 460s Segmenting by CBS...done 460s List of 4 460s $ data :'data.frame': 2681 obs. of 4 variables: 460s ..$ chromosome: int [1:2681] 1 1 1 1 1 1 1 1 1 1 ... 460s ..$ x : num [1:2681] 1.43e+08 1.43e+08 1.43e+08 1.43e+08 1.44e+08 ... 460s ..$ y : num [1:2681] 0.117 0.258 NA NA NA ... 460s ..$ index : int [1:2681] 1 2 3 4 5 6 7 8 9 10 ... 460s $ output :'data.frame': 1 obs. of 6 variables: 460s ..$ sampleName: chr NA 460s ..$ chromosome: int 1 460s ..$ start : num 1.43e+08 460s ..$ end : num 1.85e+08 460s ..$ nbrOfLoci : int 777 460s ..$ mean : num 0.0973 460s $ segRows:'data.frame': 1 obs. of 2 variables: 460s ..$ startRow: int 1 460s ..$ endRow : int 2677 460s $ params :List of 5 460s ..$ alpha : num 0.001 460s ..$ undo : num 0 460s ..$ joinSegments : logi TRUE 460s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 460s .. ..$ chromosome: int 1 460s .. ..$ start : num 1.43e+08 460s .. ..$ end : num 1.85e+08 460s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 460s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 460s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.005 0 0.005 0 0 460s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 460s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 460s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 460s DH segmentation (locally-indexed) rows: 460s startRow endRow 460s 1 1 2677 460s int [1:2681] 7587 7588 7589 7590 7591 7592 7593 7594 7595 7596 ... 460s DH segmentation rows: 460s startRow endRow 460s 1 7587 10263 460s Segmenting DH signals...done 460s DH segmentation table: 460s dhStart dhEnd dhNbrOfLoci dhMean 460s 1 142693888 185449813 777 0.0973 460s startRow endRow 460s 1 7587 10263 460s Rows: 460s [1] 2 460s TCN segmentation rows: 460s startRow endRow 460s 2 7587 10267 460s TCN and DH segmentation rows: 460s startRow endRow 460s 2 7587 10267 460s startRow endRow 460s 1 7587 10263 460s startRow endRow 460s 1 1 7586 460s TCN segmentation (expanded) rows: 460s startRow endRow 460s 1 1 7586 460s 2 7587 10267 460s TCN and DH segmentation rows: 460s startRow endRow 460s 1 1 7586 460s 2 7587 10267 460s 3 10268 14658 460s startRow endRow 460s 1 10 7574 460s 2 7587 10263 460s startRow endRow 460s 1 1 7586 460s 2 7587 10267 460s Total CN segmentation table (expanded): 460s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 460s 2 1 142693888 185449813 2681 2.0689 777 777 460s (TCN,DH) segmentation for one total CN segment: 460s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 460s 2 2 1 1 142693888 185449813 2681 2.0689 777 460s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 460s 2 777 142693888 185449813 777 0.0973 460s Total CN segment #2 ([1.42694e+08,1.8545e+08]) of 3...done 460s Total CN segment #3 ([1.8545e+08,2.47137e+08]) of 3... 460s Number of TCN loci in segment: 4391 460s Locus data for TCN segment: 460s 'data.frame': 4391 obs. of 9 variables: 460s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 460s $ x : num 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 460s $ CT : num 2.93 2.15 2.82 2.93 2.46 ... 460s $ betaT : num 0.0811 0.5154 0.9473 0.3734 0.7506 ... 460s $ betaTN : num -0.169 0.609 1.028 0.525 0.968 ... 460s $ betaN : num 0.25 0.38 0.919 0.34 0.783 ... 460s $ muN : num 0 0.5 1 0.5 1 1 0 1 0 1 ... 460s $ index : int 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 460s $ rho : num NA 0.2186 NA 0.0503 NA ... 460s Number of loci: 4391 460s Number of SNPs: 1311 (29.86%) 460s Number of heterozygous SNPs: 1311 (100.00%) 460s Chromosome: 1 460s Segmenting DH signals... 460s Segmenting by CBS... 460s Chromosome: 1 460s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 460s Segmenting by CBS...done 460s List of 4 460s $ data :'data.frame': 4391 obs. of 4 variables: 460s ..$ chromosome: int [1:4391] 1 1 1 1 1 1 1 1 1 1 ... 460s ..$ x : num [1:4391] 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 460s ..$ y : num [1:4391] NA 0.2186 NA 0.0503 NA ... 460s ..$ index : int [1:4391] 1 2 3 4 5 6 7 8 9 10 ... 460s $ output :'data.frame': 1 obs. of 6 variables: 460s ..$ sampleName: chr NA 460s ..$ chromosome: int 1 460s ..$ start : num 1.85e+08 460s ..$ end : num 2.47e+08 460s ..$ nbrOfLoci : int 1311 460s ..$ mean : num 0.23 460s $ segRows:'data.frame': 1 obs. of 2 variables: 460s ..$ startRow: int 2 460s ..$ endRow : int 4388 460s $ params :List of 5 460s ..$ alpha : num 0.001 460s ..$ undo : num 0 460s ..$ joinSegments : logi TRUE 460s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 460s .. ..$ chromosome: int 1 460s .. ..$ start : num 1.85e+08 460s .. ..$ end : num 2.47e+08 460s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 460s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 460s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.009 0 0.01 0 0 460s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 460s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 460s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 460s DH segmentation (locally-indexed) rows: 460s startRow endRow 460s 1 2 4388 460s int [1:4391] 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 460s DH segmentation rows: 460s startRow endRow 460s 1 10269 14655 460s Segmenting DH signals...done 460s DH segmentation table: 460s dhStart dhEnd dhNbrOfLoci dhMean 460s 1 185449813 247137334 1311 0.2295 460s startRow endRow 460s 1 10269 14655 460s Rows: 460s [1] 3 460s TCN segmentation rows: 460s startRow endRow 460s 3 10268 14658 460s TCN and DH segmentation rows: 460s startRow endRow 460s 3 10268 14658 460s startRow endRow 460s 1 10269 14655 460s startRow endRow 460s 1 1 7586 460s 2 7587 10267 460s TCN segmentation (expanded) rows: 460s startRow endRow 460s 1 1 7586 460s 2 7587 10267 460s 3 10268 14658 460s TCN and DH segmentation rows: 460s startRow endRow 460s 1 1 7586 460s 2 7587 10267 460s 3 10268 14658 460s startRow endRow 460s 1 10 7574 460s 2 7587 10263 460s 3 10269 14655 460s startRow endRow 460s 1 1 7586 460s 2 7587 10267 460s 3 10268 14658 460s Total CN segmentation table (expanded): 460s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 460s 3 1 185449813 247137334 4391 2.6341 1311 1311 460s (TCN,DH) segmentation for one total CN segment: 460s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 460s 3 3 1 1 185449813 247137334 4391 2.6341 1311 460s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 460s 3 1311 185449813 247137334 1311 0.2295 460s Total CN segment #3 ([1.8545e+08,2.47137e+08]) of 3...done 460s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 460s 1 1 1 1 554484 120908858 7586 1.3853 2108 460s 2 1 2 1 142693888 185449813 2681 2.0689 777 460s 3 1 3 1 185449813 247137334 4391 2.6341 1311 460s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 460s 1 2108 554484 120908858 2108 0.5116 460s 2 777 142693888 185449813 777 0.0973 460s 3 1311 185449813 247137334 1311 0.2295 460s Calculating (C1,C2) per segment... 460s Calculating (C1,C2) per segment...done 460s Number of segments: 3 460s Segmenting paired tumor-normal signals using Paired PSCBS...done 460s Post-segmenting TCNs... 460s Number of segments: 3 460s Number of chromosomes: 1 460s [1] 1 460s Chromosome 1 ('chr01') of 1... 460s Rows: 460s [1] 1 2 3 460s Number of segments: 3 460s TCN segment #1 ('1') of 3... 460s Nothing todo. Only one DH segmentation. Skipping. 460s TCN segment #1 ('1') of 3...done 460s TCN segment #2 ('2') of 3... 460s Nothing todo. Only one DH segmentation. Skipping. 460s TCN segment #2 ('2') of 3...done 460s TCN segment #3 ('3') of 3... 460s Nothing todo. Only one DH segmentation. Skipping. 460s TCN segment #3 ('3') of 3...done 460s Chromosome 1 ('chr01') of 1...done 460s Update (C1,C2) per segment... 460s Update (C1,C2) per segment...done 460s Post-segmenting TCNs...done 460s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 460s 1 1 1 1 554484 120908858 7586 1.3853 2108 460s 2 1 2 1 142693888 185449813 2681 2.0689 777 460s 3 1 3 1 185449813 247137334 4391 2.6341 1311 460s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 460s 1 2108 554484 120908858 2108 0.5116 0.3382903 1.047010 460s 2 777 142693888 185449813 777 0.0973 0.9337980 1.135102 460s 3 1311 185449813 247137334 1311 0.2295 1.0147870 1.619313 460s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 460s 1 1 1 1 554484 120908858 7586 1.3853 2108 460s 2 1 2 1 142693888 185449813 2681 2.0689 777 460s 3 1 3 1 185449813 247137334 4391 2.6341 1311 460s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 460s 1 2108 554484 120908858 2108 0.5116 0.3382903 1.047010 460s 2 777 142693888 185449813 777 0.0973 0.9337980 1.135102 460s 3 1311 185449813 247137334 1311 0.2295 1.0147870 1.619313 460s > print(fit) 460s chromosome tcnId dhId start end tcnNbrOfLoci tcnMean tcnNbrOfSNPs 460s 1 1 1 1 554484 120908858 7586 1.3853 2108 460s 2 1 2 1 142693888 185449813 2681 2.0689 777 460s 3 1 3 1 185449813 247137334 4391 2.6341 1311 460s tcnNbrOfHets dhNbrOfLoci dhMean c1Mean c2Mean 460s 1 2108 2108 0.5116 0.3382903 1.047010 460s 2 777 777 0.0973 0.9337980 1.135102 460s 3 1311 1311 0.2295 1.0147870 1.619313 460s > 460s > fit1 <- fit 460s > fit2 <- renameChromosomes(fit1, from=1, to=2) 460s > fit <- c(fit1, fit2) 460s > knownSegments <- tileChromosomes(fit)$params$knownSegments 460s > 460s > segList <- seqOfSegmentsByDP(fit, verbose=-10) 460s Identifying optimal sets of segments via dynamic programming... 460s Shifting TCN levels for every second segment... 460s Split up into non-empty independent regions... 460s Chromosome #1 ('1') of 2... 460s Number of loci on chromosome: 14658 460s Known segments on chromosome: 460s chromosome start end 460s 1 1 -Inf 120908858 460s 2 1 142693888 Inf 460s Known segment #1 of 2... 460s chromosome start end 460s 1 1 -Inf 120908858 460s Known segment #1 of 2...done 460s Known segment #2 of 2... 460s chromosome start end 460s 2 1 142693888 Inf 460s Known segment #2 of 2...done 460s Chromosome #1 ('1') of 2...done 460s Chromosome #2 ('2') of 2... 460s Number of loci on chromosome: 14658 460s Known segments on chromosome: 460s chromosome start end 460s 3 2 -Inf 120908858 460s 4 2 142693888 Inf 460s Known segment #1 of 2... 460s chromosome start end 460s 3 2 -Inf 120908858 460s Known segment #1 of 2...done 460s Known segment #2 of 2... 460s chromosome start end 460s 4 2 142693888 Inf 460s Known segment #2 of 2...done 460s Chromosome #2 ('2') of 2...done 460s Number of independent non-empty regions: 4 460s Split up into non-empty independent regions...done 460s Shift every other region... 460s Shift every other region...done 460s Merge... 460s Merge...done 460s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 460s 1 1 1 1 554484 120908858 7586 101.3853 2108 460s 2 1 2 1 142693888 185449813 2681 2.0689 777 460s 3 1 3 1 185449813 247137334 4391 2.6341 1311 460s 4 2 1 1 554484 120908858 7586 101.3853 2108 460s 5 2 2 1 142693888 185449813 2681 2.0689 777 460s 6 2 3 1 185449813 247137334 4391 2.6341 1311 460s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 460s 1 2108 554484 120908858 2108 0.511612 24.757671 76.627587 460s 2 777 142693888 185449813 777 0.097300 0.933798 1.135102 460s 3 1311 185449813 247137334 1311 0.229500 1.014787 1.619313 460s 4 2108 554484 120908858 2108 0.511612 24.757671 76.627587 460s 5 777 142693888 185449813 777 0.097300 0.933798 1.135102 460s 6 1311 185449813 247137334 1311 0.229500 1.014787 1.619313 460s Shifting TCN levels for every second segment...done 460s Extracting signals for dynamic programming... 460s CT rho 460s Min. : 0.805 Min. :0.0002 460s 1st Qu.: 2.407 1st Qu.:0.1393 460s Median :100.927 Median :0.2934 460s Mean : 53.638 Mean :0.3467 460s 3rd Qu.:101.370 3rd Qu.:0.5566 460s Max. :103.080 Max. :1.0217 460s NA's :20924 460s Extracting signals for dynamic programming...done 460s Dynamic programming... 460s Number of "DP" change points: 5 460s int [1:5] 7586 10267 14658 22244 24925 460s List of 4 460s $ jump :List of 5 460s ..$ : num 22244 460s ..$ : num [1:2] 7586 14658 460s ..$ : num [1:3] 7586 14658 22244 460s ..$ : num [1:4] 7586 10267 14658 22244 460s ..$ : num [1:5] 7586 10267 14658 22244 24925 460s $ rse : num [1:6] 71699116 47249179 35852530 5945 5410 ... 460s $ kbest: num 4 460s $ V : num [1:6, 1:6] 1114 0 0 0 0 ... 460s Dynamic programming...done 460s Excluding cases where known segments no longer correct... 460s Number of independent non-empty regions: 4 460s List of 3 460s $ : num [1:3] 7586 14658 22244 460s $ : num [1:4] 7586 10267 14658 22244 460s $ : num [1:5] 7586 10267 14658 22244 24925 460s Excluding cases where known segments no longer correct...done 460s List of 3 460s $ :'data.frame': 4 obs. of 3 variables: 460s ..$ chromosome: int [1:4] 1 1 2 2 460s ..$ start : num [1:4] 5.54e+05 1.43e+08 5.54e+05 1.43e+08 460s ..$ end : num [1:4] 1.21e+08 2.47e+08 1.21e+08 2.47e+08 460s $ :'data.frame': 5 obs. of 3 variables: 460s ..$ chromosome: int [1:5] 1 1 1 2 2 460s ..$ start : num [1:5] 5.54e+05 1.43e+08 1.85e+08 5.54e+05 1.43e+08 460s ..$ end : num [1:5] 1.21e+08 1.85e+08 2.47e+08 1.21e+08 2.47e+08 460s $ :'data.frame': 6 obs. of 3 variables: 460s ..$ chromosome: int [1:6] 1 1 1 2 2 2 460s ..$ start : num [1:6] 5.54e+05 1.43e+08 1.85e+08 5.54e+05 1.43e+08 ... 460s ..$ end : num [1:6] 1.21e+08 1.85e+08 2.47e+08 1.21e+08 1.85e+08 ... 460s Sequence of number of "DP" change points: 460s [1] 3 4 5 460s Sequence of number of segments: 460s [1] 4 5 6 460s Sequence of number of "discovered" change points: 460s [1] 0 1 2 460s Identifying optimal sets of segments via dynamic programming...done 460s > K <- length(segList) 460s > ks <- seq(from=1, to=K, length.out=min(5,K)) 460s > subplots(length(ks), ncol=1, byrow=TRUE) 461s > par(mar=c(2,1,1,1)) 461s > for (kk in ks) { 461s + knownSegmentsKK <- segList[[kk]] 461s + fitKK <- resegment(fit, knownSegments=knownSegmentsKK, undoTCN=+Inf, undoDH=+Inf) 461s + plotTracks(fitKK, tracks="tcn,c1,c2", Clim=c(0,5), add=TRUE) 461s + abline(v=c(knownSegments$start, knownSegments$end)/1e6, lty=3) 461s + stext(side=3, pos=0, sprintf("Number of segments: %d", nrow(knownSegmentsKK))) 461s + } # for (kk ...) 462s > 462s Start: segmentByPairedPSCBS.R 462s 462s R version 4.5.2 (2025-10-31) -- "[Not] Part in a Rumble" 462s Copyright (C) 2025 The R Foundation for Statistical Computing 462s Platform: x86_64-pc-linux-gnu 462s 462s R is free software and comes with ABSOLUTELY NO WARRANTY. 462s You are welcome to redistribute it under certain conditions. 462s Type 'license()' or 'licence()' for distribution details. 462s 462s R is a collaborative project with many contributors. 462s Type 'contributors()' for more information and 462s 'citation()' on how to cite R or R packages in publications. 462s 462s Type 'demo()' for some demos, 'help()' for on-line help, or 462s 'help.start()' for an HTML browser interface to help. 462s Type 'q()' to quit R. 462s 462s > ########################################################### 462s > # This tests: 462s > # - segmentByPairedPSCBS(...) 462s > # - segmentByPairedPSCBS(..., knownSegments) 462s > # - tileChromosomes() 462s > # - plotTracks() 462s > ########################################################### 462s > library("PSCBS") 462s PSCBS v0.68.0 (2025-04-18 19:40:02 UTC) successfully loaded. See ?PSCBS for help. 462s > 462s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 462s > # Load SNP microarray data 462s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 462s > data <- PSCBS::exampleData("paired.chr01") 462s > 462s > 462s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 462s > # Paired PSCBS segmentation 462s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 462s > # Drop single-locus outliers 462s > dataS <- dropSegmentationOutliers(data) 462s > 462s > # Run light-weight tests by default 462s > if (Sys.getenv("_R_CHECK_FULL_") == "") { 462s + # Use only every 5th data point 462s + dataS <- dataS[seq(from=1, to=nrow(data), by=5),] 462s + # Number of segments (for assertion) 462s + nSegs <- 4L 462s + } else { 462s + # Full tests 462s + nSegs <- 11L 462s + } 462s > 462s > str(dataS) 462s 'data.frame': 14670 obs. of 6 variables: 462s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 462s $ x : int 1145994 2941694 3710825 4240737 4276892 4464544 4714611 5095111 5034491 5158416 ... 462s $ CT : num 1.63 1.4 1.41 1.17 1.16 ... 462s $ betaT : num 0.7574 0.169 0.2357 0.2604 0.0576 ... 462s $ CN : num 2.36 2.13 2.26 2.01 2.32 ... 462s $ betaN : num 0.8274 0.5072 0.1671 0.1609 0.0421 ... 462s > 462s > fig <- 1 462s > 462s > 462s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 462s > # (a) Don't segment the centromere (and force a separator) 462s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 462s > knownSegments <- data.frame( 462s + chromosome = c( 1, 1, 1), 462s + start = c( -Inf, NA, 141510003), 462s + end = c(120992603, NA, +Inf) 462s + ) 462s > 462s > 462s > # Paired PSCBS segmentation 462s > fit <- segmentByPairedPSCBS(dataS, knownSegments=knownSegments, 462s + seed=0xBEEF, verbose=-10) 462s Segmenting paired tumor-normal signals using Paired PSCBS... 462s Calling genotypes from normal allele B fractions... 462s num [1:14670] 0.8274 0.5072 0.1671 0.1609 0.0421 ... 462s Called genotypes: 462s num [1:14670] 1 0.5 0 0 0 0 1 0 1 0.5 ... 462s - attr(*, "modelFit")=List of 1 462s ..$ :List of 7 462s .. ..$ flavor : chr "density" 462s .. ..$ cn : int 2 462s .. ..$ nbrOfGenotypeGroups: int 3 462s .. ..$ tau : num [1:2] 0.315 0.677 462s .. ..$ n : int 14640 462s .. ..$ fit :Classes ‘PeaksAndValleys’ and 'data.frame': 5 obs. of 3 variables: 462s .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 462s .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 462s .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 462s .. ..$ fitValleys :Classes ‘PeaksAndValleys’ and 'data.frame': 2 obs. of 3 variables: 462s .. .. ..$ type : chr [1:2] "valley" "valley" 462s .. .. ..$ x : num [1:2] 0.315 0.677 462s .. .. ..$ density: num [1:2] 0.522 0.551 462s ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 462s muN 462s 0 0.5 1 462s 5221 4198 5251 462s Calling genotypes from normal allele B fractions...done 462s Normalizing betaT using betaN (TumorBoost)... 462s Normalized BAFs: 462s num [1:14670] 0.9301 0.1667 0.0685 0.0995 0.0155 ... 462s - attr(*, "modelFit")=List of 5 462s ..$ method : chr "normalizeTumorBoost" 462s ..$ flavor : chr "v4" 462s ..$ delta : num [1:14670] -0.17264 0.00239 0.1671 0.16085 0.04213 ... 462s .. ..- attr(*, "modelFit")=List of 1 462s .. .. ..$ :List of 7 462s .. .. .. ..$ flavor : chr "density" 462s .. .. .. ..$ cn : int 2 462s .. .. .. ..$ nbrOfGenotypeGroups: int 3 462s .. .. .. ..$ tau : num [1:2] 0.315 0.677 462s .. .. .. ..$ n : int 14640 462s .. .. .. ..$ fit :Classes ‘PeaksAndValleys’ and 'data.frame': 5 obs. of 3 variables: 462s .. .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 462s .. .. .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 462s .. .. .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 462s .. .. .. ..$ fitValleys :Classes ‘PeaksAndValleys’ and 'data.frame': 2 obs. of 3 variables: 462s .. .. .. .. ..$ type : chr [1:2] "valley" "valley" 462s .. .. .. .. ..$ x : num [1:2] 0.315 0.677 462s .. .. .. .. ..$ density: num [1:2] 0.522 0.551 462s .. .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 462s ..$ preserveScale: logi FALSE 462s ..$ scaleFactor : num NA 462s Normalizing betaT using betaN (TumorBoost)...done 462s Setup up data... 462s 'data.frame': 14670 obs. of 7 variables: 462s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 462s $ x : num 1145994 2941694 3710825 4240737 4276892 ... 462s $ CT : num 1.63 1.4 1.41 1.17 1.16 ... 462s $ betaT : num 0.7574 0.169 0.2357 0.2604 0.0576 ... 462s $ betaTN : num 0.9301 0.1667 0.0685 0.0995 0.0155 ... 462s ..- attr(*, "modelFit")=List of 5 462s .. ..$ method : chr "normalizeTumorBoost" 462s .. ..$ flavor : chr "v4" 462s .. ..$ delta : num [1:14670] -0.17264 0.00239 0.1671 0.16085 0.04213 ... 462s .. .. ..- attr(*, "modelFit")=List of 1 462s .. .. .. ..$ :List of 7 462s .. .. .. .. ..$ flavor : chr "density" 462s .. .. .. .. ..$ cn : int 2 462s .. .. .. .. ..$ nbrOfGenotypeGroups: int 3 462s .. .. .. .. ..$ tau : num [1:2] 0.315 0.677 462s .. .. .. .. ..$ n : int 14640 462s .. .. .. .. ..$ fit :Classes ‘PeaksAndValleys’ and 'data.frame': 5 obs. of 3 variables: 462s .. .. .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 462s .. .. .. .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 462s .. .. .. .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 462s .. .. .. .. ..$ fitValleys :Classes ‘PeaksAndValleys’ and 'data.frame': 2 obs. of 3 variables: 462s .. .. .. .. .. ..$ type : chr [1:2] "valley" "valley" 462s .. .. .. .. .. ..$ x : num [1:2] 0.315 0.677 462s .. .. .. .. .. ..$ density: num [1:2] 0.522 0.551 462s .. .. .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 462s .. ..$ preserveScale: logi FALSE 462s .. ..$ scaleFactor : num NA 462s $ betaN : num 0.8274 0.5072 0.1671 0.1609 0.0421 ... 462s $ muN : num 1 0.5 0 0 0 0 1 0 1 0.5 ... 462s ..- attr(*, "modelFit")=List of 1 462s .. ..$ :List of 7 462s .. .. ..$ flavor : chr "density" 462s .. .. ..$ cn : int 2 462s .. .. ..$ nbrOfGenotypeGroups: int 3 462s .. .. ..$ tau : num [1:2] 0.315 0.677 462s .. .. ..$ n : int 14640 462s .. .. ..$ fit :Classes ‘PeaksAndValleys’ and 'data.frame': 5 obs. of 3 variables: 462s .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 462s .. .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 462s .. .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 462s .. .. ..$ fitValleys :Classes ‘PeaksAndValleys’ and 'data.frame': 2 obs. of 3 variables: 462s .. .. .. ..$ type : chr [1:2] "valley" "valley" 462s .. .. .. ..$ x : num [1:2] 0.315 0.677 462s .. .. .. ..$ density: num [1:2] 0.522 0.551 462s .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 462s Setup up data...done 462s Dropping loci for which TCNs are missing... 462s Number of loci dropped: 12 462s Dropping loci for which TCNs are missing...done 462s Ordering data along genome... 462s 'data.frame': 14658 obs. of 7 variables: 462s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 462s $ x : num 554484 730720 782343 878522 916294 ... 462s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 462s $ betaT : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 462s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 462s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 462s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 462s Ordering data along genome...done 462s Keeping only current chromosome for 'knownSegments'... 462s Chromosome: 1 462s Known segments for this chromosome: 462s chromosome start end 462s 1 1 -Inf 120992603 462s 2 1 NA NA 462s 3 1 141510003 Inf 462s Keeping only current chromosome for 'knownSegments'...done 462s alphaTCN: 0.009 462s alphaDH: 0.001 462s Number of loci: 14658 462s Calculating DHs... 462s Number of SNPs: 14658 462s Number of heterozygous SNPs: 4196 (28.63%) 462s Normalized DHs: 462s num [1:14658] NA NA NA NA NA ... 462s Calculating DHs...done 462s Random seed temporarily set (seed=c(48879), kind="L'Ecuyer-CMRG") 462s Produced 2 seeds from this stream for future usage 462s Identification of change points by total copy numbers... 462s Segmenting by CBS... 462s Chromosome: 1 462s Segmenting multiple segments on current chromosome... 462s Number of segments: 3 462s Random seed temporarily set (seed=c(10407, 1066287653, -51199871, 161854402, -1995183193, 1503453565, -747102133), kind="L'Ecuyer-CMRG") 462s Produced 3 seeds from this stream for future usage 462s Segmenting by CBS... 462s Chromosome: 1 462s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 462s Segmenting by CBS...done 462s Segmenting by CBS... 462s Chromosome: 1 462s Random seed temporarily set (seed=c(10407, -1924040949, -1632234809, -437763632, -1464377300, 676654412, 2080370711), kind="L'Ecuyer-CMRG") 463s Segmenting by CBS...done 463s Segmenting multiple segments on current chromosome...done 463s Segmenting by CBS...done 463s List of 4 463s $ data :'data.frame': 14658 obs. of 4 variables: 463s ..$ chromosome: int [1:14658] 1 1 1 1 1 1 1 1 1 1 ... 463s ..$ x : num [1:14658] 554484 730720 782343 878522 916294 ... 463s ..$ y : num [1:14658] 1.88 1.8 1.59 1.64 1.53 ... 463s ..$ index : int [1:14658] 1 2 3 4 5 6 7 8 9 10 ... 463s $ output :'data.frame': 4 obs. of 6 variables: 463s ..$ sampleName: chr [1:4] NA NA NA NA 463s ..$ chromosome: int [1:4] 1 NA 1 1 463s ..$ start : num [1:4] 5.54e+05 NA 1.42e+08 1.85e+08 463s ..$ end : num [1:4] 1.21e+08 NA 1.85e+08 2.47e+08 463s ..$ nbrOfLoci : int [1:4] 7586 NA 2681 4391 463s ..$ mean : num [1:4] 1.39 NA 2.07 2.63 463s $ segRows:'data.frame': 4 obs. of 2 variables: 463s ..$ startRow: int [1:4] 1 NA 7587 10268 463s ..$ endRow : int [1:4] 7586 NA 10267 14658 463s $ params :List of 5 463s ..$ alpha : num 0.009 463s ..$ undo : num 0 463s ..$ joinSegments : logi TRUE 463s ..$ knownSegments:'data.frame': 4 obs. of 3 variables: 463s .. ..$ chromosome: num [1:4] 1 1 2 1 463s .. ..$ start : num [1:4] -Inf -Inf -Inf 1.42e+08 463s .. ..$ end : num [1:4] 1.21e+08 Inf Inf Inf 463s ..$ seed : int [1:7] 10407 1066287653 -51199871 161854402 -1995183193 1503453565 -747102133 463s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 463s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.091 0 0.091 0 0 463s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 463s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 463s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 463s Identification of change points by total copy numbers...done 463s Restructure TCN segmentation results... 463s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean 463s 1 1 554484 120992603 7586 1.3853 463s 2 NA NA NA NA NA 463s 3 1 141510003 185449813 2681 2.0689 463s 4 1 185449813 247137334 4391 2.6341 463s Number of TCN segments: 4 463s Restructure TCN segmentation results...done 463s Total CN segment #1 ([ 554484,1.20993e+08]) of 4... 463s Number of TCN loci in segment: 7586 463s Locus data for TCN segment: 463s 'data.frame': 7586 obs. of 9 variables: 463s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 463s $ x : num 554484 730720 782343 878522 916294 ... 463s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 463s $ betaT : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 463s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 463s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 463s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 463s $ index : int 1 2 3 4 5 6 7 8 9 10 ... 463s $ rho : num NA NA NA NA NA ... 463s Number of loci: 7586 463s Number of SNPs: 2108 (27.79%) 463s Number of heterozygous SNPs: 2108 (100.00%) 463s Chromosome: 1 463s Segmenting DH signals... 463s Segmenting by CBS... 463s Chromosome: 1 463s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 463s Segmenting by CBS...done 463s List of 4 463s $ data :'data.frame': 7586 obs. of 4 variables: 463s ..$ chromosome: int [1:7586] 1 1 1 1 1 1 1 1 1 1 ... 463s ..$ x : num [1:7586] 554484 730720 782343 878522 916294 ... 463s ..$ y : num [1:7586] NA NA NA NA NA ... 463s ..$ index : int [1:7586] 1 2 3 4 5 6 7 8 9 10 ... 463s $ output :'data.frame': 1 obs. of 6 variables: 463s ..$ sampleName: chr NA 463s ..$ chromosome: int 1 463s ..$ start : num 554484 463s ..$ end : num 1.21e+08 463s ..$ nbrOfLoci : int 2108 463s ..$ mean : num 0.512 463s $ segRows:'data.frame': 1 obs. of 2 variables: 463s ..$ startRow: int 10 463s ..$ endRow : int 7574 463s $ params :List of 5 463s ..$ alpha : num 0.001 463s ..$ undo : num 0 463s ..$ joinSegments : logi TRUE 463s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 463s .. ..$ chromosome: int 1 463s .. ..$ start : num 554484 463s .. ..$ end : num 1.21e+08 463s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 463s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 463s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.026 0 0.025 0 0 463s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 463s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 463s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 463s DH segmentation (locally-indexed) rows: 463s startRow endRow 463s 1 10 7574 463s int [1:7586] 1 2 3 4 5 6 7 8 9 10 ... 463s DH segmentation rows: 463s startRow endRow 463s 1 10 7574 463s Segmenting DH signals...done 463s DH segmentation table: 463s dhStart dhEnd dhNbrOfLoci dhMean 463s 1 554484 120992603 2108 0.5116 463s startRow endRow 463s 1 10 7574 463s Rows: 463s [1] 1 463s TCN segmentation rows: 463s startRow endRow 463s 1 1 7586 463s TCN and DH segmentation rows: 463s startRow endRow 463s 1 1 7586 463s startRow endRow 463s 1 10 7574 463s NULL 463s TCN segmentation (expanded) rows: 463s startRow endRow 463s 1 1 7586 463s TCN and DH segmentation rows: 463s startRow endRow 463s 1 1 7586 463s 2 NA NA 463s 3 7587 10267 463s 4 10268 14658 463s startRow endRow 463s 1 10 7574 463s startRow endRow 463s 1 1 7586 463s Total CN segmentation table (expanded): 463s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 463s 1 1 554484 120992603 7586 1.3853 2108 2108 463s (TCN,DH) segmentation for one total CN segment: 463s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 463s 1 1 1 1 554484 120992603 7586 1.3853 2108 463s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 463s 1 2108 554484 120992603 2108 0.5116 463s Total CN segment #1 ([ 554484,1.20993e+08]) of 4...done 463s Total CN segment #2 ([ NA, NA]) of 4... 463s No signals to segment. Just a "splitter" segment. Skipping. 463s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 463s NA 2 1 NA NA NA NA NA 0 463s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 463s NA 0 NA NA 0 NA 463s Total CN segment #2 ([ NA, NA]) of 4...done 463s Total CN segment #3 ([1.4151e+08,1.8545e+08]) of 4... 463s Number of TCN loci in segment: 2681 463s Locus data for TCN segment: 463s 'data.frame': 2681 obs. of 9 variables: 463s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 463s $ x : num 1.43e+08 1.43e+08 1.43e+08 1.43e+08 1.44e+08 ... 463s $ CT : num 2.27 1.55 1.47 1.5 1.81 ... 463s $ betaT : num 0.34 0.55 0.048 0.813 0.575 ... 463s $ betaTN : num 0.441 0.629 -0.05 0.958 0.872 ... 463s $ betaN : num 0.3851 0.3933 0.0981 0.8552 0.7028 ... 463s $ muN : num 0.5 0.5 0 1 1 1 1 0.5 1 1 ... 463s $ index : int 7587 7588 7589 7590 7591 7592 7593 7594 7595 7596 ... 463s $ rho : num 0.117 0.258 NA NA NA ... 463s Number of loci: 2681 463s Number of SNPs: 777 (28.98%) 463s Number of heterozygous SNPs: 777 (100.00%) 463s Chromosome: 1 463s Segmenting DH signals... 463s Segmenting by CBS... 463s Chromosome: 1 463s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 463s Segmenting by CBS...done 463s List of 4 463s $ data :'data.frame': 2681 obs. of 4 variables: 463s ..$ chromosome: int [1:2681] 1 1 1 1 1 1 1 1 1 1 ... 463s ..$ x : num [1:2681] 1.43e+08 1.43e+08 1.43e+08 1.43e+08 1.44e+08 ... 463s ..$ y : num [1:2681] 0.117 0.258 NA NA NA ... 463s ..$ index : int [1:2681] 1 2 3 4 5 6 7 8 9 10 ... 463s $ output :'data.frame': 1 obs. of 6 variables: 463s ..$ sampleName: chr NA 463s ..$ chromosome: int 1 463s ..$ start : num 1.42e+08 463s ..$ end : num 1.85e+08 463s ..$ nbrOfLoci : int 777 463s ..$ mean : num 0.0973 463s $ segRows:'data.frame': 1 obs. of 2 variables: 463s ..$ startRow: int 1 463s ..$ endRow : int 2677 463s $ params :List of 5 463s ..$ alpha : num 0.001 463s ..$ undo : num 0 463s ..$ joinSegments : logi TRUE 463s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 463s .. ..$ chromosome: int 1 463s .. ..$ start : num 1.42e+08 463s .. ..$ end : num 1.85e+08 463s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 463s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 463s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.005 0 0.005 0 0 463s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 463s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 463s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 463s DH segmentation (locally-indexed) rows: 463s startRow endRow 463s 1 1 2677 463s int [1:2681] 7587 7588 7589 7590 7591 7592 7593 7594 7595 7596 ... 463s DH segmentation rows: 463s startRow endRow 463s 1 7587 10263 463s Segmenting DH signals...done 463s DH segmentation table: 463s dhStart dhEnd dhNbrOfLoci dhMean 463s 1 141510003 185449813 777 0.0973 463s startRow endRow 463s 1 7587 10263 463s Rows: 463s [1] 3 463s TCN segmentation rows: 463s startRow endRow 463s 3 7587 10267 463s TCN and DH segmentation rows: 463s startRow endRow 463s 3 7587 10267 463s startRow endRow 463s 1 7587 10263 463s startRow endRow 463s 1 1 7586 463s NA NA NA 463s TCN segmentation (expanded) rows: 463s startRow endRow 463s 1 1 7586 463s NA NA NA 463s 3 7587 10267 463s TCN and DH segmentation rows: 463s startRow endRow 463s 1 1 7586 463s 2 NA NA 463s 3 7587 10267 463s 4 10268 14658 463s startRow endRow 463s 1 10 7574 463s 2 NA NA 463s 3 7587 10263 463s startRow endRow 463s 1 1 7586 463s 2 NA NA 463s 3 7587 10267 463s Total CN segmentation table (expanded): 463s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 463s 3 1 141510003 185449813 2681 2.0689 777 777 463s (TCN,DH) segmentation for one total CN segment: 463s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 463s 3 3 1 1 141510003 185449813 2681 2.0689 777 463s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 463s 3 777 141510003 185449813 777 0.0973 463s Total CN segment #3 ([1.4151e+08,1.8545e+08]) of 4...done 463s Total CN segment #4 ([1.8545e+08,2.47137e+08]) of 4... 463s Number of TCN loci in segment: 4391 463s Locus data for TCN segment: 463s 'data.frame': 4391 obs. of 9 variables: 463s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 463s $ x : num 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 463s $ CT : num 2.93 2.15 2.82 2.93 2.46 ... 463s $ betaT : num 0.0811 0.5154 0.9473 0.3734 0.7506 ... 463s $ betaTN : num -0.169 0.609 1.028 0.525 0.968 ... 463s $ betaN : num 0.25 0.38 0.919 0.34 0.783 ... 463s $ muN : num 0 0.5 1 0.5 1 1 0 1 0 1 ... 463s $ index : int 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 463s $ rho : num NA 0.2186 NA 0.0503 NA ... 463s Number of loci: 4391 463s Number of SNPs: 1311 (29.86%) 463s Number of heterozygous SNPs: 1311 (100.00%) 463s Chromosome: 1 463s Segmenting DH signals... 463s Segmenting by CBS... 463s Chromosome: 1 463s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 463s Segmenting by CBS...done 463s List of 4 463s $ data :'data.frame': 4391 obs. of 4 variables: 463s ..$ chromosome: int [1:4391] 1 1 1 1 1 1 1 1 1 1 ... 463s ..$ x : num [1:4391] 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 463s ..$ y : num [1:4391] NA 0.2186 NA 0.0503 NA ... 463s ..$ index : int [1:4391] 1 2 3 4 5 6 7 8 9 10 ... 463s $ output :'data.frame': 1 obs. of 6 variables: 463s ..$ sampleName: chr NA 463s ..$ chromosome: int 1 463s ..$ start : num 1.85e+08 463s ..$ end : num 2.47e+08 463s ..$ nbrOfLoci : int 1311 463s ..$ mean : num 0.23 463s $ segRows:'data.frame': 1 obs. of 2 variables: 463s ..$ startRow: int 2 463s ..$ endRow : int 4388 463s $ params :List of 5 463s ..$ alpha : num 0.001 463s ..$ undo : num 0 463s ..$ joinSegments : logi TRUE 463s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 463s .. ..$ chromosome: int 1 463s .. ..$ start : num 1.85e+08 463s .. ..$ end : num 2.47e+08 463s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 463s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 463s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.009 0 0.01 0 0 463s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 463s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 463s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 463s DH segmentation (locally-indexed) rows: 463s startRow endRow 463s 1 2 4388 463s int [1:4391] 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 463s DH segmentation rows: 463s startRow endRow 463s 1 10269 14655 463s Segmenting DH signals...done 463s DH segmentation table: 463s dhStart dhEnd dhNbrOfLoci dhMean 463s 1 185449813 247137334 1311 0.2295 463s startRow endRow 463s 1 10269 14655 463s Rows: 463s [1] 4 463s TCN segmentation rows: 463s startRow endRow 463s 4 10268 14658 463s TCN and DH segmentation rows: 463s startRow endRow 463s 4 10268 14658 463s startRow endRow 463s 1 10269 14655 463s startRow endRow 463s 1 1 7586 463s 2 NA NA 463s 3 7587 10267 463s TCN segmentation (expanded) rows: 463s startRow endRow 463s 1 1 7586 463s 2 NA NA 463s 3 7587 10267 463s 4 10268 14658 463s TCN and DH segmentation rows: 463s startRow endRow 463s 1 1 7586 463s 2 NA NA 463s 3 7587 10267 463s 4 10268 14658 463s startRow endRow 463s 1 10 7574 463s 2 NA NA 463s 3 7587 10263 463s 4 10269 14655 463s startRow endRow 463s 1 1 7586 463s 2 NA NA 463s 3 7587 10267 463s 4 10268 14658 463s Total CN segmentation table (expanded): 463s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 463s 4 1 185449813 247137334 4391 2.6341 1311 1311 463s (TCN,DH) segmentation for one total CN segment: 463s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 463s 4 4 1 1 185449813 247137334 4391 2.6341 1311 463s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 463s 4 1311 185449813 247137334 1311 0.2295 463s Total CN segment #4 ([1.8545e+08,2.47137e+08]) of 4...done 463s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 463s 1 1 1 1 554484 120992603 7586 1.3853 2108 463s 2 NA 2 1 NA NA NA NA 0 463s 3 1 3 1 141510003 185449813 2681 2.0689 777 463s 4 1 4 1 185449813 247137334 4391 2.6341 1311 463s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 463s 1 2108 554484 120992603 2108 0.5116 463s 2 0 NA NA 0 NA 463s 3 777 141510003 185449813 777 0.0973 463s 4 1311 185449813 247137334 1311 0.2295 463s Calculating (C1,C2) per segment... 463s Calculating (C1,C2) per segment...done 463s Number of segments: 4 463s Segmenting paired tumor-normal signals using Paired PSCBS...done 463s Post-segmenting TCNs... 463s Number of segments: 3 463s Number of chromosomes: 1 463s [1] 1 463s Chromosome 1 ('chr01') of 1... 463s Rows: 463s [1] 1 2 3 463s Number of segments: 3 463s TCN segment #1 ('1') of 3... 463s Nothing todo. Only one DH segmentation. Skipping. 463s TCN segment #1 ('1') of 3...done 463s TCN segment #2 ('3') of 3... 463s Nothing todo. Only one DH segmentation. Skipping. 463s TCN segment #2 ('3') of 3...done 463s TCN segment #3 ('4') of 3... 463s Nothing todo. Only one DH segmentation. Skipping. 463s TCN segment #3 ('4') of 3...done 463s Chromosome 1 ('chr01') of 1...done 463s Update (C1,C2) per segment... 463s Update (C1,C2) per segment...done 463s Post-segmenting TCNs...done 463s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 463s 1 1 1 1 554484 120992603 7586 1.3853 2108 463s 2 NA 2 1 NA NA NA NA 0 463s 3 1 3 1 141510003 185449813 2681 2.0689 777 463s 4 1 4 1 185449813 247137334 4391 2.6341 1311 463s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 463s 1 2108 554484 120992603 2108 0.5116 0.3382903 1.047010 463s 2 0 NA NA 0 NA NA NA 463s 3 777 141510003 185449813 777 0.0973 0.9337980 1.135102 463s 4 1311 185449813 247137334 1311 0.2295 1.0147870 1.619313 463s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 463s 1 1 1 1 554484 120992603 7586 1.3853 2108 463s 2 NA 2 1 NA NA NA NA 0 463s 3 1 3 1 141510003 185449813 2681 2.0689 777 463s 4 1 4 1 185449813 247137334 4391 2.6341 1311 463s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 463s 1 2108 554484 120992603 2108 0.5116 0.3382903 1.047010 463s 2 0 NA NA 0 NA NA NA 463s 3 777 141510003 185449813 777 0.0973 0.9337980 1.135102 463s 4 1311 185449813 247137334 1311 0.2295 1.0147870 1.619313 463s > print(fit) 463s chromosome tcnId dhId start end tcnNbrOfLoci tcnMean tcnNbrOfSNPs 463s 1 1 1 1 554484 120992603 7586 1.3853 2108 463s 2 NA 2 1 NA NA NA NA 0 463s 3 1 3 1 141510003 185449813 2681 2.0689 777 463s 4 1 4 1 185449813 247137334 4391 2.6341 1311 463s tcnNbrOfHets dhNbrOfLoci dhMean c1Mean c2Mean 463s 1 2108 2108 0.5116 0.3382903 1.047010 463s 2 0 0 NA NA NA 463s 3 777 777 0.0973 0.9337980 1.135102 463s 4 1311 1311 0.2295 1.0147870 1.619313 463s > 463s > # Plot results 463s > dev.set(2L) 463s null device 463s 1 463s > plotTracks(fit) 463s > abline(v=c(knownSegments$start, knownSegments$end)/1e6, lty=3) 463s > 463s > # Sanity check 463s > stopifnot(nbrOfSegments(fit) == nSegs) 463s > 463s > fit1 <- fit 463s > 463s > 463s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 463s > # (b) Segment also the centromere (which will become NAs) 463s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 463s > knownSegments <- data.frame( 463s + chromosome = c( 1, 1, 1), 463s + start = c( -Inf, 120992604, 141510003), 463s + end = c(120992603, 141510002, +Inf) 463s + ) 463s > 463s > 463s > # Paired PSCBS segmentation 463s > fit <- segmentByPairedPSCBS(dataS, knownSegments=knownSegments, 463s + seed=0xBEEF, verbose=-10) 463s Segmenting paired tumor-normal signals using Paired PSCBS... 463s Calling genotypes from normal allele B fractions... 463s num [1:14670] 0.8274 0.5072 0.1671 0.1609 0.0421 ... 463s Called genotypes: 463s num [1:14670] 1 0.5 0 0 0 0 1 0 1 0.5 ... 463s - attr(*, "modelFit")=List of 1 463s ..$ :List of 7 463s .. ..$ flavor : chr "density" 463s .. ..$ cn : int 2 463s .. ..$ nbrOfGenotypeGroups: int 3 463s .. ..$ tau : num [1:2] 0.315 0.677 463s .. ..$ n : int 14640 463s .. ..$ fit :Classes ‘PeaksAndValleys’ and 'data.frame': 5 obs. of 3 variables: 463s .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 463s .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 463s .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 463s .. ..$ fitValleys :Classes ‘PeaksAndValleys’ and 'data.frame': 2 obs. of 3 variables: 463s .. .. ..$ type : chr [1:2] "valley" "valley" 463s .. .. ..$ x : num [1:2] 0.315 0.677 463s .. .. ..$ density: num [1:2] 0.522 0.551 463s ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 463s muN 463s 0 0.5 1 463s 5221 4198 5251 463s Calling genotypes from normal allele B fractions...done 463s Normalizing betaT using betaN (TumorBoost)... 463s Normalized BAFs: 463s num [1:14670] 0.9301 0.1667 0.0685 0.0995 0.0155 ... 463s - attr(*, "modelFit")=List of 5 463s ..$ method : chr "normalizeTumorBoost" 463s ..$ flavor : chr "v4" 463s ..$ delta : num [1:14670] -0.17264 0.00239 0.1671 0.16085 0.04213 ... 463s .. ..- attr(*, "modelFit")=List of 1 463s .. .. ..$ :List of 7 463s .. .. .. ..$ flavor : chr "density" 463s .. .. .. ..$ cn : int 2 463s .. .. .. ..$ nbrOfGenotypeGroups: int 3 463s .. .. .. ..$ tau : num [1:2] 0.315 0.677 463s .. .. .. ..$ n : int 14640 463s .. .. .. ..$ fit :Classes ‘PeaksAndValleys’ and 'data.frame': 5 obs. of 3 variables: 463s .. .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 463s .. .. .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 463s .. .. .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 463s .. .. .. ..$ fitValleys :Classes ‘PeaksAndValleys’ and 'data.frame': 2 obs. of 3 variables: 463s .. .. .. .. ..$ type : chr [1:2] "valley" "valley" 463s .. .. .. .. ..$ x : num [1:2] 0.315 0.677 463s .. .. .. .. ..$ density: num [1:2] 0.522 0.551 463s .. .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 463s ..$ preserveScale: logi FALSE 463s ..$ scaleFactor : num NA 463s Normalizing betaT using betaN (TumorBoost)...done 463s Setup up data... 463s 'data.frame': 14670 obs. of 7 variables: 463s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 463s $ x : num 1145994 2941694 3710825 4240737 4276892 ... 463s $ CT : num 1.63 1.4 1.41 1.17 1.16 ... 463s $ betaT : num 0.7574 0.169 0.2357 0.2604 0.0576 ... 463s $ betaTN : num 0.9301 0.1667 0.0685 0.0995 0.0155 ... 463s ..- attr(*, "modelFit")=List of 5 463s .. ..$ method : chr "normalizeTumorBoost" 463s .. ..$ flavor : chr "v4" 463s .. ..$ delta : num [1:14670] -0.17264 0.00239 0.1671 0.16085 0.04213 ... 463s .. .. ..- attr(*, "modelFit")=List of 1 463s .. .. .. ..$ :List of 7 463s .. .. .. .. ..$ flavor : chr "density" 463s .. .. .. .. ..$ cn : int 2 463s .. .. .. .. ..$ nbrOfGenotypeGroups: int 3 463s .. .. .. .. ..$ tau : num [1:2] 0.315 0.677 463s .. .. .. .. ..$ n : int 14640 463s .. .. .. .. ..$ fit :Classes ‘PeaksAndValleys’ and 'data.frame': 5 obs. of 3 variables: 463s .. .. .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 463s .. .. .. .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 463s .. .. .. .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 463s .. .. .. .. ..$ fitValleys :Classes ‘PeaksAndValleys’ and 'data.frame': 2 obs. of 3 variables: 463s .. .. .. .. .. ..$ type : chr [1:2] "valley" "valley" 463s .. .. .. .. .. ..$ x : num [1:2] 0.315 0.677 463s .. .. .. .. .. ..$ density: num [1:2] 0.522 0.551 463s .. .. .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 463s .. ..$ preserveScale: logi FALSE 463s .. ..$ scaleFactor : num NA 463s $ betaN : num 0.8274 0.5072 0.1671 0.1609 0.0421 ... 463s $ muN : num 1 0.5 0 0 0 0 1 0 1 0.5 ... 463s ..- attr(*, "modelFit")=List of 1 463s .. ..$ :List of 7 463s .. .. ..$ flavor : chr "density" 463s .. .. ..$ cn : int 2 463s .. .. ..$ nbrOfGenotypeGroups: int 3 463s .. .. ..$ tau : num [1:2] 0.315 0.677 463s .. .. ..$ n : int 14640 463s .. .. ..$ fit :Classes ‘PeaksAndValleys’ and 'data.frame': 5 obs. of 3 variables: 463s .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 463s .. .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 463s .. .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 463s .. .. ..$ fitValleys :Classes ‘PeaksAndValleys’ and 'data.frame': 2 obs. of 3 variables: 463s .. .. .. ..$ type : chr [1:2] "valley" "valley" 463s .. .. .. ..$ x : num [1:2] 0.315 0.677 463s .. .. .. ..$ density: num [1:2] 0.522 0.551 463s .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 463s Setup up data...done 463s Dropping loci for which TCNs are missing... 463s Number of loci dropped: 12 463s Dropping loci for which TCNs are missing...done 463s Ordering data along genome... 463s 'data.frame': 14658 obs. of 7 variables: 463s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 463s $ x : num 554484 730720 782343 878522 916294 ... 463s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 463s $ betaT : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 463s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 463s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 463s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 463s Ordering data along genome...done 463s Keeping only current chromosome for 'knownSegments'... 463s Chromosome: 1 463s Known segments for this chromosome: 463s chromosome start end 463s 1 1 -Inf 120992603 463s 2 1 120992604 141510002 463s 3 1 141510003 Inf 463s Keeping only current chromosome for 'knownSegments'...done 463s alphaTCN: 0.009 463s alphaDH: 0.001 463s Number of loci: 14658 463s Calculating DHs... 463s Number of SNPs: 14658 463s Number of heterozygous SNPs: 4196 (28.63%) 463s Normalized DHs: 463s num [1:14658] NA NA NA NA NA ... 463s Calculating DHs...done 463s Random seed temporarily set (seed=c(48879), kind="L'Ecuyer-CMRG") 463s Produced 2 seeds from this stream for future usage 463s Identification of change points by total copy numbers... 463s Segmenting by CBS... 463s Chromosome: 1 463s Segmenting multiple segments on current chromosome... 463s Number of segments: 3 463s Random seed temporarily set (seed=c(10407, 1066287653, -51199871, 161854402, -1995183193, 1503453565, -747102133), kind="L'Ecuyer-CMRG") 463s Produced 3 seeds from this stream for future usage 463s Segmenting by CBS... 463s Chromosome: 1 463s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 463s Segmenting by CBS...done 463s Segmenting by CBS... 463s Chromosome: 1 463s Random seed temporarily set (seed=c(10407, -1924040949, -1632234809, -437763632, -1464377300, 676654412, 2080370711), kind="L'Ecuyer-CMRG") 463s Segmenting by CBS...done 463s Segmenting multiple segments on current chromosome...done 463s Segmenting by CBS...done 463s List of 4 463s $ data :'data.frame': 14658 obs. of 4 variables: 463s ..$ chromosome: int [1:14658] 1 1 1 1 1 1 1 1 1 1 ... 463s ..$ x : num [1:14658] 554484 730720 782343 878522 916294 ... 463s ..$ y : num [1:14658] 1.88 1.8 1.59 1.64 1.53 ... 463s ..$ index : int [1:14658] 1 2 3 4 5 6 7 8 9 10 ... 463s $ output :'data.frame': 4 obs. of 6 variables: 463s ..$ sampleName: chr [1:4] NA NA NA NA 463s ..$ chromosome: num [1:4] 1 1 1 1 463s ..$ start : num [1:4] 5.54e+05 1.21e+08 1.42e+08 1.85e+08 463s ..$ end : num [1:4] 1.21e+08 1.42e+08 1.85e+08 2.47e+08 463s ..$ nbrOfLoci : int [1:4] 7586 0 2681 4391 463s ..$ mean : num [1:4] 1.39 NA 2.07 2.63 463s $ segRows:'data.frame': 4 obs. of 2 variables: 463s ..$ startRow: int [1:4] 1 NA 7587 10268 463s ..$ endRow : int [1:4] 7586 NA 10267 14658 463s $ params :List of 5 463s ..$ alpha : num 0.009 463s ..$ undo : num 0 463s ..$ joinSegments : logi TRUE 463s ..$ knownSegments:'data.frame': 4 obs. of 3 variables: 463s .. ..$ chromosome: num [1:4] 1 1 2 1 463s .. ..$ start : num [1:4] -Inf -Inf -Inf 1.42e+08 463s .. ..$ end : num [1:4] 1.21e+08 Inf Inf Inf 463s ..$ seed : int [1:7] 10407 1066287653 -51199871 161854402 -1995183193 1503453565 -747102133 463s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 463s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.089 0 0.088 0 0 463s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 463s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 463s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 463s Identification of change points by total copy numbers...done 463s Restructure TCN segmentation results... 463s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean 463s 1 1 554484 120992603 7586 1.3853 463s 2 1 120992604 141510002 0 NA 463s 3 1 141510003 185449813 2681 2.0689 463s 4 1 185449813 247137334 4391 2.6341 463s Number of TCN segments: 4 463s Restructure TCN segmentation results...done 463s Total CN segment #1 ([ 554484,1.20993e+08]) of 4... 463s Number of TCN loci in segment: 7586 463s Locus data for TCN segment: 463s 'data.frame': 7586 obs. of 9 variables: 463s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 463s $ x : num 554484 730720 782343 878522 916294 ... 463s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 463s $ betaT : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 463s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 463s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 463s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 463s $ index : int 1 2 3 4 5 6 7 8 9 10 ... 463s $ rho : num NA NA NA NA NA ... 463s Number of loci: 7586 463s Number of SNPs: 2108 (27.79%) 463s Number of heterozygous SNPs: 2108 (100.00%) 463s Chromosome: 1 463s Segmenting DH signals... 463s Segmenting by CBS... 463s Chromosome: 1 463s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 463s Segmenting by CBS...done 463s List of 4 463s $ data :'data.frame': 7586 obs. of 4 variables: 463s ..$ chromosome: int [1:7586] 1 1 1 1 1 1 1 1 1 1 ... 463s ..$ x : num [1:7586] 554484 730720 782343 878522 916294 ... 463s ..$ y : num [1:7586] NA NA NA NA NA ... 463s ..$ index : int [1:7586] 1 2 3 4 5 6 7 8 9 10 ... 463s $ output :'data.frame': 1 obs. of 6 variables: 463s ..$ sampleName: chr NA 463s ..$ chromosome: int 1 463s ..$ start : num 554484 463s ..$ end : num 1.21e+08 463s ..$ nbrOfLoci : int 2108 463s ..$ mean : num 0.512 463s $ segRows:'data.frame': 1 obs. of 2 variables: 463s ..$ startRow: int 10 463s ..$ endRow : int 7574 463s $ params :List of 5 463s ..$ alpha : num 0.001 463s ..$ undo : num 0 463s ..$ joinSegments : logi TRUE 463s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 463s .. ..$ chromosome: int 1 463s .. ..$ start : num 554484 463s .. ..$ end : num 1.21e+08 463s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 463s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 463s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.025 0 0.026 0 0 463s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 463s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 463s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 463s DH segmentation (locally-indexed) rows: 463s startRow endRow 463s 1 10 7574 463s int [1:7586] 1 2 3 4 5 6 7 8 9 10 ... 463s DH segmentation rows: 463s startRow endRow 463s 1 10 7574 463s Segmenting DH signals...done 463s DH segmentation table: 463s dhStart dhEnd dhNbrOfLoci dhMean 463s 1 554484 120992603 2108 0.5116 463s startRow endRow 463s 1 10 7574 463s Rows: 463s [1] 1 463s TCN segmentation rows: 463s startRow endRow 463s 1 1 7586 463s TCN and DH segmentation rows: 463s startRow endRow 463s 1 1 7586 463s startRow endRow 463s 1 10 7574 463s NULL 463s TCN segmentation (expanded) rows: 463s startRow endRow 463s 1 1 7586 463s TCN and DH segmentation rows: 463s startRow endRow 463s 1 1 7586 463s 2 NA NA 463s 3 7587 10267 463s 4 10268 14658 463s startRow endRow 463s 1 10 7574 463s startRow endRow 463s 1 1 7586 463s Total CN segmentation table (expanded): 463s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 463s 1 1 554484 120992603 7586 1.3853 2108 2108 463s (TCN,DH) segmentation for one total CN segment: 463s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 463s 1 1 1 1 554484 120992603 7586 1.3853 2108 463s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 463s 1 2108 554484 120992603 2108 0.5116 463s Total CN segment #1 ([ 554484,1.20993e+08]) of 4...done 463s Total CN segment #2 ([1.20993e+08,1.4151e+08]) of 4... 463s Number of TCN loci in segment: 0 463s Locus data for TCN segment: 463s 'data.frame': 0 obs. of 9 variables: 463s $ chromosome: int 463s $ x : num 463s $ CT : num 463s $ betaT : num 463s $ betaTN : num 463s $ betaN : num 463s $ muN : num 463s $ index : int 463s $ rho : num 463s Number of loci: 0 463s Number of SNPs: 0 (NaN%) 463s Number of heterozygous SNPs: 0 (NaN%) 463s Chromosome: 1 463s Segmenting DH signals... 463s Segmenting by CBS... 463s Chromosome: NA 463s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 463s Segmenting by CBS...done 463s List of 4 463s $ data :'data.frame': 0 obs. of 4 variables: 463s ..$ chromosome: int(0) 463s ..$ x : num(0) 463s ..$ y : num(0) 463s ..$ index : int(0) 463s $ output :'data.frame': 0 obs. of 6 variables: 463s ..$ sampleName: chr(0) 463s ..$ chromosome: num(0) 463s ..$ start : num(0) 463s ..$ end : num(0) 463s ..$ nbrOfLoci : int(0) 463s ..$ mean : num(0) 463s $ segRows:'data.frame': 0 obs. of 2 variables: 463s ..$ startRow: int(0) 463s ..$ endRow : int(0) 463s $ params :List of 5 463s ..$ alpha : num 0.001 463s ..$ undo : num 0 463s ..$ joinSegments : logi TRUE 463s ..$ knownSegments:'data.frame': 0 obs. of 3 variables: 463s .. ..$ chromosome: int(0) 463s .. ..$ start : num(0) 463s .. ..$ end : num(0) 463s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 463s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 463s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.001 0 0.001 0 0 463s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 463s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 463s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 463s DH segmentation (locally-indexed) rows: 463s [1] startRow endRow 463s <0 rows> (or 0-length row.names) 463s int(0) 463s DH segmentation rows: 463s [1] startRow endRow 463s <0 rows> (or 0-length row.names) 463s Segmenting DH signals...done 463s DH segmentation table: 463s dhStart dhEnd dhNbrOfLoci dhMean 463s NA NA NA NA NA 463s startRow endRow 463s NA NA NA 463s Rows: 463s [1] 2 463s TCN segmentation rows: 463s startRow endRow 463s 2 NA NA 463s TCN and DH segmentation rows: 463s startRow endRow 463s 2 NA NA 463s startRow endRow 463s NA NA NA 463s startRow endRow 463s 1 1 7586 463s TCN segmentation (expanded) rows: 463s startRow endRow 463s 1 1 7586 463s 2 NA NA 463s TCN and DH segmentation rows: 463s startRow endRow 463s 1 1 7586 463s 2 NA NA 463s 3 7587 10267 463s 4 10268 14658 463s startRow endRow 463s 1 10 7574 463s 2 NA NA 463s startRow endRow 463s 1 1 7586 463s 2 NA NA 463s Total CN segmentation table (expanded): 463s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 463s 2 1 120992604 141510002 0 NA 0 0 463s (TCN,DH) segmentation for one total CN segment: 463s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 463s 2 2 1 1 120992604 141510002 0 NA 0 463s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 463s 2 0 NA NA NA NA 463s Total CN segment #2 ([1.20993e+08,1.4151e+08]) of 4...done 463s Total CN segment #3 ([1.4151e+08,1.8545e+08]) of 4... 463s Number of TCN loci in segment: 2681 463s Locus data for TCN segment: 463s 'data.frame': 2681 obs. of 9 variables: 463s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 463s $ x : num 1.43e+08 1.43e+08 1.43e+08 1.43e+08 1.44e+08 ... 463s $ CT : num 2.27 1.55 1.47 1.5 1.81 ... 463s $ betaT : num 0.34 0.55 0.048 0.813 0.575 ... 463s $ betaTN : num 0.441 0.629 -0.05 0.958 0.872 ... 463s $ betaN : num 0.3851 0.3933 0.0981 0.8552 0.7028 ... 463s $ muN : num 0.5 0.5 0 1 1 1 1 0.5 1 1 ... 463s $ index : int 7587 7588 7589 7590 7591 7592 7593 7594 7595 7596 ... 463s $ rho : num 0.117 0.258 NA NA NA ... 463s Number of loci: 2681 463s Number of SNPs: 777 (28.98%) 463s Number of heterozygous SNPs: 777 (100.00%) 463s Chromosome: 1 463s Segmenting DH signals... 463s Segmenting by CBS... 463s Chromosome: 1 463s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 463s Segmenting by CBS...done 463s List of 4 463s $ data :'data.frame': 2681 obs. of 4 variables: 463s ..$ chromosome: int [1:2681] 1 1 1 1 1 1 1 1 1 1 ... 463s ..$ x : num [1:2681] 1.43e+08 1.43e+08 1.43e+08 1.43e+08 1.44e+08 ... 463s ..$ y : num [1:2681] 0.117 0.258 NA NA NA ... 463s ..$ index : int [1:2681] 1 2 3 4 5 6 7 8 9 10 ... 463s $ output :'data.frame': 1 obs. of 6 variables: 463s ..$ sampleName: chr NA 463s ..$ chromosome: int 1 463s ..$ start : num 1.42e+08 463s ..$ end : num 1.85e+08 463s ..$ nbrOfLoci : int 777 463s ..$ mean : num 0.0973 463s $ segRows:'data.frame': 1 obs. of 2 variables: 463s ..$ startRow: int 1 463s ..$ endRow : int 2677 463s $ params :List of 5 463s ..$ alpha : num 0.001 463s ..$ undo : num 0 463s ..$ joinSegments : logi TRUE 463s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 463s .. ..$ chromosome: int 1 463s .. ..$ start : num 1.42e+08 463s .. ..$ end : num 1.85e+08 463s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 463s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 463s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.006 0 0.005 0 0 463s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 463s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 463s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 463s DH segmentation (locally-indexed) rows: 463s startRow endRow 463s 1 1 2677 463s int [1:2681] 7587 7588 7589 7590 7591 7592 7593 7594 7595 7596 ... 463s DH segmentation rows: 463s startRow endRow 463s 1 7587 10263 463s Segmenting DH signals...done 463s DH segmentation table: 463s dhStart dhEnd dhNbrOfLoci dhMean 463s 1 141510003 185449813 777 0.0973 463s startRow endRow 463s 1 7587 10263 463s Rows: 463s [1] 3 463s TCN segmentation rows: 463s startRow endRow 463s 3 7587 10267 463s TCN and DH segmentation rows: 463s startRow endRow 463s 3 7587 10267 463s startRow endRow 463s 1 7587 10263 463s startRow endRow 463s 1 1 7586 463s 2 NA NA 463s TCN segmentation (expanded) rows: 463s startRow endRow 463s 1 1 7586 463s 2 NA NA 463s 3 7587 10267 463s TCN and DH segmentation rows: 463s startRow endRow 463s 1 1 7586 463s 2 NA NA 463s 3 7587 10267 463s 4 10268 14658 463s startRow endRow 463s 1 10 7574 463s 2 NA NA 463s 3 7587 10263 463s startRow endRow 463s 1 1 7586 463s 2 NA NA 463s 3 7587 10267 463s Total CN segmentation table (expanded): 463s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 463s 3 1 141510003 185449813 2681 2.0689 777 777 463s (TCN,DH) segmentation for one total CN segment: 463s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 463s 3 3 1 1 141510003 185449813 2681 2.0689 777 463s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 463s 3 777 141510003 185449813 777 0.0973 463s Total CN segment #3 ([1.4151e+08,1.8545e+08]) of 4...done 463s Total CN segment #4 ([1.8545e+08,2.47137e+08]) of 4... 463s Number of TCN loci in segment: 4391 463s Locus data for TCN segment: 463s 'data.frame': 4391 obs. of 9 variables: 463s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 463s $ x : num 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 463s $ CT : num 2.93 2.15 2.82 2.93 2.46 ... 463s $ betaT : num 0.0811 0.5154 0.9473 0.3734 0.7506 ... 463s $ betaTN : num -0.169 0.609 1.028 0.525 0.968 ... 463s $ betaN : num 0.25 0.38 0.919 0.34 0.783 ... 463s $ muN : num 0 0.5 1 0.5 1 1 0 1 0 1 ... 463s $ index : int 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 463s $ rho : num NA 0.2186 NA 0.0503 NA ... 463s Number of loci: 4391 463s Number of SNPs: 1311 (29.86%) 463s Number of heterozygous SNPs: 1311 (100.00%) 463s Chromosome: 1 463s Segmenting DH signals... 464s Segmenting by CBS... 464s Chromosome: 1 464s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 464s Segmenting by CBS...done 464s List of 4 464s $ data :'data.frame': 4391 obs. of 4 variables: 464s ..$ chromosome: int [1:4391] 1 1 1 1 1 1 1 1 1 1 ... 464s ..$ x : num [1:4391] 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 464s ..$ y : num [1:4391] NA 0.2186 NA 0.0503 NA ... 464s ..$ index : int [1:4391] 1 2 3 4 5 6 7 8 9 10 ... 464s $ output :'data.frame': 1 obs. of 6 variables: 464s ..$ sampleName: chr NA 464s ..$ chromosome: int 1 464s ..$ start : num 1.85e+08 464s ..$ end : num 2.47e+08 464s ..$ nbrOfLoci : int 1311 464s ..$ mean : num 0.23 464s $ segRows:'data.frame': 1 obs. of 2 variables: 464s ..$ startRow: int 2 464s ..$ endRow : int 4388 464s $ params :List of 5 464s ..$ alpha : num 0.001 464s ..$ undo : num 0 464s ..$ joinSegments : logi TRUE 464s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 464s .. ..$ chromosome: int 1 464s .. ..$ start : num 1.85e+08 464s .. ..$ end : num 2.47e+08 464s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 464s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 464s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.009 0 0.009 0 0 464s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 464s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 464s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 464s DH segmentation (locally-indexed) rows: 464s startRow endRow 464s 1 2 4388 464s int [1:4391] 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 464s DH segmentation rows: 464s startRow endRow 464s 1 10269 14655 464s Segmenting DH signals...done 464s DH segmentation table: 464s dhStart dhEnd dhNbrOfLoci dhMean 464s 1 185449813 247137334 1311 0.2295 464s startRow endRow 464s 1 10269 14655 464s Rows: 464s [1] 4 464s TCN segmentation rows: 464s startRow endRow 464s 4 10268 14658 464s TCN and DH segmentation rows: 464s startRow endRow 464s 4 10268 14658 464s startRow endRow 464s 1 10269 14655 464s startRow endRow 464s 1 1 7586 464s 2 NA NA 464s 3 7587 10267 464s TCN segmentation (expanded) rows: 464s startRow endRow 464s 1 1 7586 464s 2 NA NA 464s 3 7587 10267 464s 4 10268 14658 464s TCN and DH segmentation rows: 464s startRow endRow 464s 1 1 7586 464s 2 NA NA 464s 3 7587 10267 464s 4 10268 14658 464s startRow endRow 464s 1 10 7574 464s 2 NA NA 464s 3 7587 10263 464s 4 10269 14655 464s startRow endRow 464s 1 1 7586 464s 2 NA NA 464s 3 7587 10267 464s 4 10268 14658 464s Total CN segmentation table (expanded): 464s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 464s 4 1 185449813 247137334 4391 2.6341 1311 1311 464s (TCN,DH) segmentation for one total CN segment: 464s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 464s 4 4 1 1 185449813 247137334 4391 2.6341 1311 464s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 464s 4 1311 185449813 247137334 1311 0.2295 464s Total CN segment #4 ([1.8545e+08,2.47137e+08]) of 4...done 464s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 464s 1 1 1 1 554484 120992603 7586 1.3853 2108 464s 2 1 2 1 120992604 141510002 0 NA 0 464s 3 1 3 1 141510003 185449813 2681 2.0689 777 464s 4 1 4 1 185449813 247137334 4391 2.6341 1311 464s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 464s 1 2108 554484 120992603 2108 0.5116 464s 2 0 NA NA NA NA 464s 3 777 141510003 185449813 777 0.0973 464s 4 1311 185449813 247137334 1311 0.2295 464s Calculating (C1,C2) per segment... 464s Calculating (C1,C2) per segment...done 464s Number of segments: 4 464s Segmenting paired tumor-normal signals using Paired PSCBS...done 464s Post-segmenting TCNs... 464s Number of segments: 4 464s Number of chromosomes: 1 464s [1] 1 464s Chromosome 1 ('chr01') of 1... 464s Rows: 464s [1] 1 2 3 4 464s Number of segments: 4 464s TCN segment #1 ('1') of 4... 464s Nothing todo. Only one DH segmentation. Skipping. 464s TCN segment #1 ('1') of 4...done 464s TCN segment #2 ('2') of 4... 464s Nothing todo. Only one DH segmentation. Skipping. 464s TCN segment #2 ('2') of 4...done 464s TCN segment #3 ('3') of 4... 464s Nothing todo. Only one DH segmentation. Skipping. 464s TCN segment #3 ('3') of 4...done 464s TCN segment #4 ('4') of 4... 464s Nothing todo. Only one DH segmentation. Skipping. 464s TCN segment #4 ('4') of 4...done 464s Chromosome 1 ('chr01') of 1...done 464s Update (C1,C2) per segment... 464s Update (C1,C2) per segment...done 464s Post-segmenting TCNs...done 464s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 464s 1 1 1 1 554484 120992603 7586 1.3853 2108 464s 2 1 2 1 120992604 141510002 0 NA 0 464s 3 1 3 1 141510003 185449813 2681 2.0689 777 464s 4 1 4 1 185449813 247137334 4391 2.6341 1311 464s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 464s 1 2108 554484 120992603 2108 0.5116 0.3382903 1.047010 464s 2 0 NA NA NA NA NA NA 464s 3 777 141510003 185449813 777 0.0973 0.9337980 1.135102 464s 4 1311 185449813 247137334 1311 0.2295 1.0147870 1.619313 464s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 464s 1 1 1 1 554484 120992603 > print(fit) 464s chromosome tcnId dhId start end tcnNbrOfLoci tcnMean tcnNbrOfSNPs 464s 1 1 1 1 554484 120992603 7586 1.3853 2108 464s 2 1 2 1 120992604 141510002 0 NA 0 464s 3 1 3 1 141510003 185449813 2681 2.0689 777 464s 4 1 4 1 185449813 247137334 4391 2.6341 1311 464s tcnNbrOfHets dhNbrOfLoci dhMean c1Mean c2Mean 464s 1 2108 2108 0.5116 0.3382903 1.047010 464s 2 0 NA NA NA NA 464s 3 777 777 0.0973 0.9337980 1.135102 464s 4 1311 1311 0.2295 1.0147870 1.619313 464s > 464s > # Plot results 464s > dev.set(3L) 464s pdf 464s 2 464s > plotTracks(fit) 464s 7586 1.3853 2108 464s 2 1 2 1 120992604 141510002 0 NA 0 464s 3 1 3 1 141510003 185449813 2681 2.0689 777 464s 4 1 4 1 185449813 247137334 4391 2.6341 1311 464s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 464s 1 2108 554484 120992603 2108 0.5116 0.3382903 1.047010 464s 2 0 NA NA NA NA NA NA 464s 3 777 141510003 185449813 777 0.0973 0.9337980 1.135102 464s 4 1311 185449813 247137334 1311 0.2295 1.0147870 1.619313 464s > abline(v=c(knownSegments$start, knownSegments$end)/1e6, lty=3) 464s > 464s > # Sanity check [TO FIX: See above] 464s > stopifnot(nbrOfSegments(fit) == nSegs) 464s > 464s > fit2 <- fit 464s > 464s > 464s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 464s > # (c) Do not segment the centromere (without a separator) 464s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 464s > knownSegments <- data.frame( 464s + chromosome = c( 1, 1), 464s + start = c( -Inf, 141510003), 464s + end = c(120992603, +Inf) 464s + ) 464s > 464s > # Paired PSCBS segmentation 464s > fit <- segmentByPairedPSCBS(dataS, knownSegments=knownSegments, 464s + seed=0xBEEF, verbose=-10) 464s Segmenting paired tumor-normal signals using Paired PSCBS... 464s Calling genotypes from normal allele B fractions... 464s num [1:14670] 0.8274 0.5072 0.1671 0.1609 0.0421 ... 464s Called genotypes: 464s num [1:14670] 1 0.5 0 0 0 0 1 0 1 0.5 ... 464s - attr(*, "modelFit")=List of 1 464s ..$ :List of 7 464s .. ..$ flavor : chr "density" 464s .. ..$ cn : int 2 464s .. ..$ nbrOfGenotypeGroups: int 3 464s .. ..$ tau : num [1:2] 0.315 0.677 464s .. ..$ n : int 14640 464s .. ..$ fit :Classes ‘PeaksAndValleys’ and 'data.frame': 5 obs. of 3 variables: 464s .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 464s .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 464s .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 464s .. ..$ fitValleys :Classes ‘PeaksAndValleys’ and 'data.frame': 2 obs. of 3 variables: 464s .. .. ..$ type : chr [1:2] "valley" "valley" 464s .. .. ..$ x : num [1:2] 0.315 0.677 464s .. .. ..$ density: num [1:2] 0.522 0.551 464s ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 464s muN 464s 0 0.5 1 464s 5221 4198 5251 464s Calling genotypes from normal allele B fractions...done 464s Normalizing betaT using betaN (TumorBoost)... 464s Normalized BAFs: 464s num [1:14670] 0.9301 0.1667 0.0685 0.0995 0.0155 ... 464s - attr(*, "modelFit")=List of 5 464s ..$ method : chr "normalizeTumorBoost" 464s ..$ flavor : chr "v4" 464s ..$ delta : num [1:14670] -0.17264 0.00239 0.1671 0.16085 0.04213 ... 464s .. ..- attr(*, "modelFit")=List of 1 464s .. .. ..$ :List of 7 464s .. .. .. ..$ flavor : chr "density" 464s .. .. .. ..$ cn : int 2 464s .. .. .. ..$ nbrOfGenotypeGroups: int 3 464s .. .. .. ..$ tau : num [1:2] 0.315 0.677 464s .. .. .. ..$ n : int 14640 464s .. .. .. ..$ fit :Classes ‘PeaksAndValleys’ and 'data.frame': 5 obs. of 3 variables: 464s .. .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 464s .. .. .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 464s .. .. .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 464s .. .. .. ..$ fitValleys :Classes ‘PeaksAndValleys’ and 'data.frame': 2 obs. of 3 variables: 464s .. .. .. .. ..$ type : chr [1:2] "valley" "valley" 464s .. .. .. .. ..$ x : num [1:2] 0.315 0.677 464s .. .. .. .. ..$ density: num [1:2] 0.522 0.551 464s .. .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 464s ..$ preserveScale: logi FALSE 464s ..$ scaleFactor : num NA 464s Normalizing betaT using betaN (TumorBoost)...done 464s Setup up data... 464s 'data.frame': 14670 obs. of 7 variables: 464s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 464s $ x : num 1145994 2941694 3710825 4240737 4276892 ... 464s $ CT : num 1.63 1.4 1.41 1.17 1.16 ... 464s $ betaT : num 0.7574 0.169 0.2357 0.2604 0.0576 ... 464s $ betaTN : num 0.9301 0.1667 0.0685 0.0995 0.0155 ... 464s ..- attr(*, "modelFit")=List of 5 464s .. ..$ method : chr "normalizeTumorBoost" 464s .. ..$ flavor : chr "v4" 464s .. ..$ delta : num [1:14670] -0.17264 0.00239 0.1671 0.16085 0.04213 ... 464s .. .. ..- attr(*, "modelFit")=List of 1 464s .. .. .. ..$ :List of 7 464s .. .. .. .. ..$ flavor : chr "density" 464s .. .. .. .. ..$ cn : int 2 464s .. .. .. .. ..$ nbrOfGenotypeGroups: int 3 464s .. .. .. .. ..$ tau : num [1:2] 0.315 0.677 464s .. .. .. .. ..$ n : int 14640 464s .. .. .. .. ..$ fit :Classes ‘PeaksAndValleys’ and 'data.frame': 5 obs. of 3 variables: 464s .. .. .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 464s .. .. .. .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 464s .. .. .. .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 464s .. .. .. .. ..$ fitValleys :Classes ‘PeaksAndValleys’ and 'data.frame': 2 obs. of 3 variables: 464s .. .. .. .. .. ..$ type : chr [1:2] "valley" "valley" 464s .. .. .. .. .. ..$ x : num [1:2] 0.315 0.677 464s .. .. .. .. .. ..$ density: num [1:2] 0.522 0.551 464s .. .. .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 464s .. ..$ preserveScale: logi FALSE 464s .. ..$ scaleFactor : num NA 464s $ betaN : num 0.8274 0.5072 0.1671 0.1609 0.0421 ... 464s $ muN : num 1 0.5 0 0 0 0 1 0 1 0.5 ... 464s ..- attr(*, "modelFit")=List of 1 464s .. ..$ :List of 7 464s .. .. ..$ flavor : chr "density" 464s .. .. ..$ cn : int 2 464s .. .. ..$ nbrOfGenotypeGroups: int 3 464s .. .. ..$ tau : num [1:2] 0.315 0.677 464s .. .. ..$ n : int 14640 464s .. .. ..$ fit :Classes ‘PeaksAndValleys’ and 'data.frame': 5 obs. of 3 variables: 464s .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 464s .. .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 464s .. .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 464s .. .. ..$ fitValleys :Classes ‘PeaksAndValleys’ and 'data.frame': 2 obs. of 3 variables: 464s .. .. .. ..$ type : chr [1:2] "valley" "valley" 464s .. .. .. ..$ x : num [1:2] 0.315 0.677 464s .. .. .. ..$ density: num [1:2] 0.522 0.551 464s .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 464s Setup up data...done 464s Dropping loci for which TCNs are missing... 464s Number of loci dropped: 12 464s Dropping loci for which TCNs are missing...done 464s Ordering data along genome... 464s 'data.frame': 14658 obs. of 7 variables: 464s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 464s $ x : num 554484 730720 782343 878522 916294 ... 464s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 464s $ betaT : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 464s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 464s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 464s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 464s Ordering data along genome...done 464s Keeping only current chromosome for 'knownSegments'... 464s Chromosome: 1 464s Known segments for this chromosome: 464s chromosome start end 464s 1 1 -Inf 120992603 464s 2 1 141510003 Inf 464s Keeping only current chromosome for 'knownSegments'...done 464s alphaTCN: 0.009 464s alphaDH: 0.001 464s Number of loci: 14658 464s Calculating DHs... 464s Number of SNPs: 14658 464s Number of heterozygous SNPs: 4196 (28.63%) 464s Normalized DHs: 464s num [1:14658] NA NA NA NA NA ... 464s Calculating DHs...done 464s Random seed temporarily set (seed=c(48879), kind="L'Ecuyer-CMRG") 464s Produced 2 seeds from this stream for future usage 464s Identification of change points by total copy numbers... 464s Segmenting by CBS... 464s Chromosome: 1 464s Segmenting multiple segments on current chromosome... 464s Number of segments: 2 464s Random seed temporarily set (seed=c(10407, 1066287653, -51199871, 161854402, -1995183193, 1503453565, -747102133), kind="L'Ecuyer-CMRG") 464s Produced 2 seeds from this stream for future usage 464s Segmenting by CBS... 464s Chromosome: 1 464s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 464s Segmenting by CBS...done 464s Segmenting by CBS... 464s Chromosome: 1 464s Random seed temporarily set (seed=c(10407, -821273412, -52578226, 1415511586, 721384351, -665928286, 1316562960), kind="L'Ecuyer-CMRG") 464s Segmenting by CBS...done 464s Segmenting multiple segments on current chromosome...done 464s Segmenting by CBS...done 464s List of 4 464s $ data :'data.frame': 14658 obs. of 4 variables: 464s ..$ chromosome: int [1:14658] 1 1 1 1 1 1 1 1 1 1 ... 464s ..$ x : num [1:14658] 554484 730720 782343 878522 916294 ... 464s ..$ y : num [1:14658] 1.88 1.8 1.59 1.64 1.53 ... 464s ..$ index : int [1:14658] 1 2 3 4 5 6 7 8 9 10 ... 464s $ output :'data.frame': 3 obs. of 6 variables: 464s ..$ sampleName: chr [1:3] NA NA NA 464s ..$ chromosome: int [1:3] 1 1 1 464s ..$ start : num [1:3] 5.54e+05 1.42e+08 1.85e+08 464s ..$ end : num [1:3] 1.21e+08 1.85e+08 2.47e+08 464s ..$ nbrOfLoci : int [1:3] 7586 2681 4391 464s ..$ mean : num [1:3] 1.39 2.07 2.63 464s $ segRows:'data.frame': 3 obs. of 2 variables: 464s ..$ startRow: int [1:3] 1 7587 10268 464s ..$ endRow : int [1:3] 7586 10267 14658 464s $ params :List of 5 464s ..$ alpha : num 0.009 464s ..$ undo : num 0 464s ..$ joinSegments : logi TRUE 464s ..$ knownSegments:'data.frame': 2 obs. of 3 variables: 464s .. ..$ chromosome: num [1:2] 1 1 464s .. ..$ start : num [1:2] -Inf 1.42e+08 464s .. ..$ end : num [1:2] 1.21e+08 Inf 464s ..$ seed : int [1:7] 10407 1066287653 -51199871 161854402 -1995183193 1503453565 -747102133 464s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 464s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.088 0 0.087 0 0 464s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 464s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 464s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 464s Identification of change points by total copy numbers...done 464s Restructure TCN segmentation results... 464s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean 464s 1 1 554484 120992603 7586 1.3853 464s 2 1 141510003 185449813 2681 2.0689 464s 3 1 185449813 247137334 4391 2.6341 464s Number of TCN segments: 3 464s Restructure TCN segmentation results...done 464s Total CN segment #1 ([ 554484,1.20993e+08]) of 3... 464s Number of TCN loci in segment: 7586 464s Locus data for TCN segment: 464s 'data.frame': 7586 obs. of 9 variables: 464s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 464s $ x : num 554484 730720 782343 878522 916294 ... 464s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 464s $ betaT : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 464s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 464s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 464s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 464s $ index : int 1 2 3 4 5 6 7 8 9 10 ... 464s $ rho : num NA NA NA NA NA ... 464s Number of loci: 7586 464s Number of SNPs: 2108 (27.79%) 464s Number of heterozygous SNPs: 2108 (100.00%) 464s Chromosome: 1 464s Segmenting DH signals... 464s Segmenting by CBS... 464s Chromosome: 1 464s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 464s Segmenting by CBS...done 464s List of 4 464s $ data :'data.frame': 7586 obs. of 4 variables: 464s ..$ chromosome: int [1:7586] 1 1 1 1 1 1 1 1 1 1 ... 464s ..$ x : num [1:7586] 554484 730720 782343 878522 916294 ... 464s ..$ y : num [1:7586] NA NA NA NA NA ... 464s ..$ index : int [1:7586] 1 2 3 4 5 6 7 8 9 10 ... 464s $ output :'data.frame': 1 obs. of 6 variables: 464s ..$ sampleName: chr NA 464s ..$ chromosome: int 1 464s ..$ start : num 554484 464s ..$ end : num 1.21e+08 464s ..$ nbrOfLoci : int 2108 464s ..$ mean : num 0.512 464s $ segRows:'data.frame': 1 obs. of 2 variables: 464s ..$ startRow: int 10 464s ..$ endRow : int 7574 464s $ params :List of 5 464s ..$ alpha : num 0.001 464s ..$ undo : num 0 464s ..$ joinSegments : logi TRUE 464s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 464s .. ..$ chromosome: int 1 464s .. ..$ start : num 554484 464s .. ..$ end : num 1.21e+08 464s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 464s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 464s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.025 0 0.025 0 0 464s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 464s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 464s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 464s DH segmentation (locally-indexed) rows: 464s startRow endRow 464s 1 10 7574 464s int [1:7586] 1 2 3 4 5 6 7 8 9 10 ... 464s DH segmentation rows: 464s startRow endRow 464s 1 10 7574 464s Segmenting DH signals...done 464s DH segmentation table: 464s dhStart dhEnd dhNbrOfLoci dhMean 464s 1 554484 120992603 2108 0.5116 464s startRow endRow 464s 1 10 7574 464s Rows: 464s [1] 1 464s TCN segmentation rows: 464s startRow endRow 464s 1 1 7586 464s TCN and DH segmentation rows: 464s startRow endRow 464s 1 1 7586 464s startRow endRow 464s 1 10 7574 464s NULL 464s TCN segmentation (expanded) rows: 464s startRow endRow 464s 1 1 7586 464s TCN and DH segmentation rows: 464s startRow endRow 464s 1 1 7586 464s 2 7587 10267 464s 3 10268 14658 464s startRow endRow 464s 1 10 7574 464s startRow endRow 464s 1 1 7586 464s Total CN segmentation table (expanded): 464s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 464s 1 1 554484 120992603 7586 1.3853 2108 2108 464s (TCN,DH) segmentation for one total CN segment: 464s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 464s 1 1 1 1 554484 120992603 7586 1.3853 2108 464s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 464s 1 2108 554484 120992603 2108 0.5116 464s Total CN segment #1 ([ 554484,1.20993e+08]) of 3...done 464s Total CN segment #2 ([1.4151e+08,1.8545e+08]) of 3... 464s Number of TCN loci in segment: 2681 464s Locus data for TCN segment: 464s 'data.frame': 2681 obs. of 9 variables: 464s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 464s $ x : num 1.43e+08 1.43e+08 1.43e+08 1.43e+08 1.44e+08 ... 464s $ CT : num 2.27 1.55 1.47 1.5 1.81 ... 464s $ betaT : num 0.34 0.55 0.048 0.813 0.575 ... 464s $ betaTN : num 0.441 0.629 -0.05 0.958 0.872 ... 464s $ betaN : num 0.3851 0.3933 0.0981 0.8552 0.7028 ... 464s $ muN : num 0.5 0.5 0 1 1 1 1 0.5 1 1 ... 464s $ index : int 7587 7588 7589 7590 7591 7592 7593 7594 7595 7596 ... 464s $ rho : num 0.117 0.258 NA NA NA ... 464s Number of loci: 2681 464s Number of SNPs: 777 (28.98%) 464s Number of heterozygous SNPs: 777 (100.00%) 464s Chromosome: 1 464s Segmenting DH signals... 464s Segmenting by CBS... 464s Chromosome: 1 464s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 464s Segmenting by CBS...done 464s List of 4 464s $ data :'data.frame': 2681 obs. of 4 variables: 464s ..$ chromosome: int [1:2681] 1 1 1 1 1 1 1 1 1 1 ... 464s ..$ x : num [1:2681] 1.43e+08 1.43e+08 1.43e+08 1.43e+08 1.44e+08 ... 464s ..$ y : num [1:2681] 0.117 0.258 NA NA NA ... 464s ..$ index : int [1:2681] 1 2 3 4 5 6 7 8 9 10 ... 464s $ output :'data.frame': 1 obs. of 6 variables: 464s ..$ sampleName: chr NA 464s ..$ chromosome: int 1 464s ..$ start : num 1.42e+08 464s ..$ end : num 1.85e+08 464s ..$ nbrOfLoci : int 777 464s ..$ mean : num 0.0973 464s $ segRows:'data.frame': 1 obs. of 2 variables: 464s ..$ startRow: int 1 464s ..$ endRow : int 2677 464s $ params :List of 5 464s ..$ alpha : num 0.001 464s ..$ undo : num 0 464s ..$ joinSegments : logi TRUE 464s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 464s .. ..$ chromosome: int 1 464s .. ..$ start : num 1.42e+08 464s .. ..$ end : num 1.85e+08 464s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 464s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 464s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.005 0 0.005 0 0 464s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 464s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 464s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 464s DH segmentation (locally-indexed) rows: 464s startRow endRow 464s 1 1 2677 464s int [1:2681] 7587 7588 7589 7590 7591 7592 7593 7594 7595 7596 ... 464s DH segmentation rows: 464s startRow endRow 464s 1 7587 10263 464s Segmenting DH signals...done 464s DH segmentation table: 464s dhStart dhEnd dhNbrOfLoci dhMean 464s 1 141510003 185449813 777 0.0973 464s startRow endRow 464s 1 7587 10263 464s Rows: 464s [1] 2 464s TCN segmentation rows: 464s startRow endRow 464s 2 7587 10267 464s TCN and DH segmentation rows: 464s startRow endRow 464s 2 7587 10267 464s startRow endRow 464s 1 7587 10263 464s startRow endRow 464s 1 1 7586 464s TCN segmentation (expanded) rows: 464s startRow endRow 464s 1 1 7586 464s 2 7587 10267 464s TCN and DH segmentation rows: 464s startRow endRow 464s 1 1 7586 464s 2 7587 10267 464s 3 10268 14658 464s startRow endRow 464s 1 10 7574 464s 2 7587 10263 464s startRow endRow 464s 1 1 7586 464s 2 7587 10267 464s Total CN segmentation table (expanded): 464s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 464s 2 1 141510003 185449813 2681 2.0689 777 777 464s (TCN,DH) segmentation for one total CN segment: 464s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 464s 2 2 1 1 141510003 185449813 2681 2.0689 777 464s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 464s 2 777 141510003 185449813 777 0.0973 464s Total CN segment #2 ([1.4151e+08,1.8545e+08]) of 3...done 464s Total CN segment #3 ([1.8545e+08,2.47137e+08]) of 3... 464s Number of TCN loci in segment: 4391 464s Locus data for TCN segment: 464s 'data.frame': 4391 obs. of 9 variables: 464s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 464s $ x : num 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 464s $ CT : num 2.93 2.15 2.82 2.93 2.46 ... 464s $ betaT : num 0.0811 0.5154 0.9473 0.3734 0.7506 ... 464s $ betaTN : num -0.169 0.609 1.028 0.525 0.968 ... 464s $ betaN : num 0.25 0.38 0.919 0.34 0.783 ... 464s $ muN : num 0 0.5 1 0.5 1 1 0 1 0 1 ... 464s $ index : int 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 464s $ rho : num NA 0.2186 NA 0.0503 NA ... 464s Number of loci: 4391 464s Number of SNPs: 1311 (29.86%) 464s Number of heterozygous SNPs: 1311 (100.00%) 464s Chromosome: 1 464s Segmenting DH signals... 464s Segmenting by CBS... 464s Chromosome: 1 464s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 464s Segmenting by CBS...done 464s List of 4 464s $ data :'data.frame': 4391 obs. of 4 variables: 464s ..$ chromosome: int [1:4391] 1 1 1 1 1 1 1 1 1 1 ... 464s ..$ x : num [1:4391] 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 464s ..$ y : num [1:4391] NA 0.2186 NA 0.0503 NA ... 464s ..$ index : int [1:4391] 1 2 3 4 5 6 7 8 9 10 ... 464s $ output :'data.frame': 1 obs. of 6 variables: 464s ..$ sampleName: chr NA 464s ..$ chromosome: int 1 464s ..$ start : num 1.85e+08 464s ..$ end : num 2.47e+08 464s ..$ nbrOfLoci : int 1311 464s ..$ mean : num 0.23 464s $ segRows:'data.frame': 1 obs. of 2 variables: 464s ..$ startRow: int 2 464s ..$ endRow : int 4388 464s $ params :List of 5 464s ..$ alpha : num 0.001 464s ..$ undo : num 0 464s ..$ joinSegments : logi TRUE 464s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 464s .. ..$ chromosome: int 1 464s .. ..$ start : num 1.85e+08 464s .. ..$ end : num 2.47e+08 464s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 464s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 464s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.009 0 0.009 0 0 464s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 464s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 464s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 464s DH segmentation (locally-indexed) rows: 464s startRow endRow 464s 1 2 4388 464s int [1:4391] 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 464s DH segmentation rows: 464s startRow endRow 464s 1 10269 14655 464s Segmenting DH signals...done 464s DH segmentation table: 464s dhStart dhEnd dhNbrOfLoci dhMean 464s 1 185449813 247137334 1311 0.2295 464s startRow endRow 464s 1 10269 14655 464s Rows: 464s [1] 3 464s TCN segmentation rows: 464s startRow endRow 464s 3 10268 14658 464s TCN and DH segmentation rows: 464s startRow endRow 464s 3 10268 14658 464s startRow endRow 464s 1 10269 14655 464s startRow endRow 464s 1 1 7586 464s 2 7587 10267 464s TCN segmentation (expanded) rows: 464s startRow endRow 464s 1 1 7586 464s 2 7587 10267 464s 3 10268 14658 464s TCN and DH segmentation rows: 464s startRow endRow 464s 1 1 7586 464s 2 7587 10267 464s 3 10268 14658 464s startRow endRow 464s 1 10 7574 464s 2 7587 10263 464s 3 10269 14655 464s startRow endRow 464s 1 1 7586 464s 2 7587 10267 464s 3 10268 14658 464s Total CN segmentation table (expanded): 464s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 464s 3 1 185449813 247137334 4391 2.6341 1311 1311 464s (TCN,DH) segmentation for one total CN segment: 464s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 464s 3 3 1 1 185449813 247137334 4391 2.6341 1311 464s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 464s 3 1311 185449813 247137334 1311 0.2295 464s Total CN segment #3 ([1.8545e+08,2.47137e+08]) of 3...done 464s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 464s 1 1 1 1 554484 120992603 7586 1.3853 2108 464s 2 1 2 1 141510003 185449813 2681 2.0689 777 464s 3 1 3 1 185449813 247137334 4391 2.6341 1311 464s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 464s 1 2108 554484 120992603 2108 0.5116 464s 2 777 141510003 185449813 777 0.0973 464s 3 1311 185449813 247137334 1311 0.2295 464s Calculating (C1,C2) per segment... 464s Calculating (C1,C2) per segment...done 464s Number of segments: 3 464s Segmenting paired tumor-normal signals using Paired PSCBS...done 464s Post-segmenting TCNs... 464s Number of segments: 3 464s Number of chromosomes: 1 464s [1] 1 464s Chromosome 1 ('chr01') of 1... 464s Rows: 464s [1] 1 2 3 464s Number of segments: 3 464s TCN segment #1 ('1') of 3... 464s Nothing todo. Only one DH segmentation. Skipping. 464s TCN segment #1 ('1') of 3...done 464s TCN segment #2 ('2') of 3... 464s Nothing todo. Only one DH segmentation. Skipping. 464s TCN segment #2 ('2') of 3...done 464s TCN segment #3 ('3') of 3... 464s Nothing todo. Only one DH segmentation. Skipping. 464s TCN segment #3 ('3') of 3...done 464s Chromosome 1 ('chr01') of 1...done 464s Update (C1,C2) per segment... 464s Update (C1,C2) per segment...done 464s Post-segmenting TCNs...done 464s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 464s 1 1 1 1 554484 120992603 7586 1.3853 2108 464s 2 1 2 1 141510003 185449813 2681 2.0689 777 464s 3 1 3 1 185449813 247137334 4391 2.6341 1311 464s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 464s 1 2108 554484 120992603 2108 0.5116 0.3382903 1.047010 464s 2 777 141510003 185449813 777 0.0973 0.9337980 1.135102 464s 3 1311 185449813 247137334 1311 0.2295 1.0147870 1.619313 464s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 464s 1 1 1 1 554484 120992603 7586 1.3853 2108 464s 2 1 2 1 141510003 185449813 2681 2.0689 777 464s 3 1 3 1 185449813 247137334 4391 2.6341 1311 464s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 464s 1 2108 554484 120992603 2108 0.5116 0.3382903 1.047010 464s 2 777 141510003 185449813 777 0.0973 0.9337980 1.135102 464s 3 1311 185449813 247137334 1311 0.2295 1.0147870 1.619313 464s > print(fit) 464s chromosome tcnId dhId start end tcnNbrOfLoci tcnMean tcnNbrOfSNPs 464s 1 1 1 1 554484 120992603 7586 1.3853 2108 464s 2 1 2 1 141510003 185449813 2681 2.0689 777 464s 3 1 3 1 185449813 247137334 4391 2.6341 1311 464s tcnNbrOfHets dhNbrOfLoci dhMean c1Mean c2Mean 464s 1 2108 2108 0.5116 0.3382903 1.047010 464s 2 777 777 0.0973 0.9337980 1.135102 464s 3 1311 1311 0.2295 1.0147870 1.619313 464s > 464s > # Plot results 464s > dev.set(4L) 464s pdf 464s 2 464s > plotTracks(fit) 464s > abline(v=c(knownSegments$start, knownSegments$end)/1e6, lty=3) 464s > 464s > # Sanity check 464s > stopifnot(nbrOfSegments(fit) == nSegs-1L) 464s > 464s > fit3 <- fit 464s > 464s > 464s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 464s > # (d) Skip the identification of new change points 464s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 464s > knownSegments <- data.frame( 464s + chromosome = c( 1, 1), 464s + start = c( -Inf, 141510003), 464s + end = c(120992603, +Inf) 464s + ) 464s > 464s > # Paired PSCBS segmentation 464s > fit <- segmentByPairedPSCBS(dataS, knownSegments=knownSegments, 464s + undoTCN=Inf, undoDH=Inf, 464s + seed=0xBEEF, verbose=-10) 464s Segmenting paired tumor-normal signals using Paired PSCBS... 464s Calling genotypes from normal allele B fractions... 464s num [1:14670] 0.8274 0.5072 0.1671 0.1609 0.0421 ... 464s Called genotypes: 464s num [1:14670] 1 0.5 0 0 0 0 1 0 1 0.5 ... 464s - attr(*, "modelFit")=List of 1 464s ..$ :List of 7 464s .. ..$ flavor : chr "density" 464s .. ..$ cn : int 2 464s .. ..$ nbrOfGenotypeGroups: int 3 464s .. ..$ tau : num [1:2] 0.315 0.677 464s .. ..$ n : int 14640 464s .. ..$ fit :Classes ‘PeaksAndValleys’ and 'data.frame': 5 obs. of 3 variables: 464s .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 464s .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 464s .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 464s .. ..$ fitValleys :Classes ‘PeaksAndValleys’ and 'data.frame': 2 obs. of 3 variables: 464s .. .. ..$ type : chr [1:2] "valley" "valley" 464s .. .. ..$ x : num [1:2] 0.315 0.677 464s .. .. ..$ density: num [1:2] 0.522 0.551 464s ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 464s muN 464s 0 0.5 1 464s 5221 4198 5251 464s Calling genotypes from normal allele B fractions...done 464s Normalizing betaT using betaN (TumorBoost)... 464s Normalized BAFs: 464s num [1:14670] 0.9301 0.1667 0.0685 0.0995 0.0155 ... 464s - attr(*, "modelFit")=List of 5 464s ..$ method : chr "normalizeTumorBoost" 464s ..$ flavor : chr "v4" 464s ..$ delta : num [1:14670] -0.17264 0.00239 0.1671 0.16085 0.04213 ... 464s .. ..- attr(*, "modelFit")=List of 1 464s .. .. ..$ :List of 7 464s .. .. .. ..$ flavor : chr "density" 464s .. .. .. ..$ cn : int 2 464s .. .. .. ..$ nbrOfGenotypeGroups: int 3 464s .. .. .. ..$ tau : num [1:2] 0.315 0.677 464s .. .. .. ..$ n : int 14640 464s .. .. .. ..$ fit :Classes ‘PeaksAndValleys’ and 'data.frame': 5 obs. of 3 variables: 464s .. .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 464s .. .. .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 464s .. .. .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 464s .. .. .. ..$ fitValleys :Classes ‘PeaksAndValleys’ and 'data.frame': 2 obs. of 3 variables: 464s .. .. .. .. ..$ type : chr [1:2] "valley" "valley" 464s .. .. .. .. ..$ x : num [1:2] 0.315 0.677 464s .. .. .. .. ..$ density: num [1:2] 0.522 0.551 464s .. .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 464s ..$ preserveScale: logi FALSE 464s ..$ scaleFactor : num NA 464s Normalizing betaT using betaN (TumorBoost)...done 464s Setup up data... 464s 'data.frame': 14670 obs. of 7 variables: 464s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 464s $ x : num 1145994 2941694 3710825 4240737 4276892 ... 464s $ CT : num 1.63 1.4 1.41 1.17 1.16 ... 464s $ betaT : num 0.7574 0.169 0.2357 0.2604 0.0576 ... 464s $ betaTN : num 0.9301 0.1667 0.0685 0.0995 0.0155 ... 464s ..- attr(*, "modelFit")=List of 5 464s .. ..$ method : chr "normalizeTumorBoost" 464s .. ..$ flavor : chr "v4" 464s .. ..$ delta : num [1:14670] -0.17264 0.00239 0.1671 0.16085 0.04213 ... 464s .. .. ..- attr(*, "modelFit")=List of 1 464s .. .. .. ..$ :List of 7 464s .. .. .. .. ..$ flavor : chr "density" 464s .. .. .. .. ..$ cn : int 2 464s .. .. .. .. ..$ nbrOfGenotypeGroups: int 3 464s .. .. .. .. ..$ tau : num [1:2] 0.315 0.677 464s .. .. .. .. ..$ n : int 14640 464s .. .. .. .. ..$ fit :Classes ‘PeaksAndValleys’ and 'data.frame': 5 obs. of 3 variables: 464s .. .. .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 464s .. .. .. .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 464s .. .. .. .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 464s .. .. .. .. ..$ fitValleys :Classes ‘PeaksAndValleys’ and 'data.frame': 2 obs. of 3 variables: 464s .. .. .. .. .. ..$ type : chr [1:2] "valley" "valley" 464s .. .. .. .. .. ..$ x : num [1:2] 0.315 0.677 464s .. .. .. .. .. ..$ density: num [1:2] 0.522 0.551 464s .. .. .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 464s .. ..$ preserveScale: logi FALSE 464s .. ..$ scaleFactor : num NA 464s $ betaN : num 0.8274 0.5072 0.1671 0.1609 0.0421 ... 464s $ muN : num 1 0.5 0 0 0 0 1 0 1 0.5 ... 464s ..- attr(*, "modelFit")=List of 1 464s .. ..$ :List of 7 464s .. .. ..$ flavor : chr "density" 464s .. .. ..$ cn : int 2 464s .. .. ..$ nbrOfGenotypeGroups: int 3 464s .. .. ..$ tau : num [1:2] 0.315 0.677 464s .. .. ..$ n : int 14640 464s .. .. ..$ fit :Classes ‘PeaksAndValleys’ and 'data.frame': 5 obs. of 3 variables: 464s .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 464s .. .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 464s .. .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 464s .. .. ..$ fitValleys :Classes ‘PeaksAndValleys’ and 'data.frame': 2 obs. of 3 variables: 464s .. .. .. ..$ type : chr [1:2] "valley" "valley" 464s .. .. .. ..$ x : num [1:2] 0.315 0.677 464s .. .. .. ..$ density: num [1:2] 0.522 0.551 464s .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 464s Setup up data...done 464s Dropping loci for which TCNs are missing... 464s Number of loci dropped: 12 464s Dropping loci for which TCNs are missing...done 464s Ordering data along genome... 464s 'data.frame': 14658 obs. of 7 variables: 464s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 464s $ x : num 554484 730720 782343 878522 916294 ... 464s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 464s $ betaT : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 464s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 464s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 464s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 464s Ordering data along genome...done 464s Keeping only current chromosome for 'knownSegments'... 464s Chromosome: 1 464s Known segments for this chromosome: 464s chromosome start end 464s 1 1 -Inf 120992603 464s 2 1 141510003 Inf 464s Keeping only current chromosome for 'knownSegments'...done 464s alphaTCN: 0.009 464s alphaDH: 0.001 464s Number of loci: 14658 464s Calculating DHs... 464s Number of SNPs: 14658 464s Number of heterozygous SNPs: 4196 (28.63%) 464s Normalized DHs: 464s num [1:14658] NA NA NA NA NA ... 464s Calculating DHs...done 464s Random seed temporarily set (seed=c(48879), kind="L'Ecuyer-CMRG") 464s Produced 2 seeds from this stream for future usage 464s Identification of change points by total copy numbers... 464s Segmenting by CBS... 464s Chromosome: 1 464s Segmenting multiple segments on current chromosome... 464s Number of segments: 2 464s Random seed temporarily set (seed=c(10407, 1066287653, -51199871, 161854402, -1995183193, 1503453565, -747102133), kind="L'Ecuyer-CMRG") 464s Produced 2 seeds from this stream for future usage 465s Segmenting by CBS... 465s Chromosome: 1 465s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 465s Segmenting by CBS...done 465s Segmenting by CBS... 465s Chromosome: 1 465s Random seed temporarily set (seed=c(10407, -821273412, -52578226, 1415511586, 721384351, -665928286, 1316562960), kind="L'Ecuyer-CMRG") 465s Segmenting by CBS...done 465s Segmenting multiple segments on current chromosome...done 465s Segmenting by CBS...done 465s List of 4 465s $ data :'data.frame': 14658 obs. of 4 variables: 465s ..$ chromosome: int [1:14658] 1 1 1 1 1 1 1 1 1 1 ... 465s ..$ x : num [1:14658] 554484 730720 782343 878522 916294 ... 465s ..$ y : num [1:14658] 1.88 1.8 1.59 1.64 1.53 ... 465s ..$ index : int [1:14658] 1 2 3 4 5 6 7 8 9 10 ... 465s $ output :'data.frame': 2 obs. of 6 variables: 465s ..$ sampleName: chr [1:2] NA NA 465s ..$ chromosome: num [1:2] 1 1 465s ..$ start : num [1:2] 5.54e+05 1.42e+08 465s ..$ end : num [1:2] 1.21e+08 2.47e+08 465s ..$ nbrOfLoci : int [1:2] 7586 7072 465s ..$ mean : num [1:2] 1.39 2.42 465s $ segRows:'data.frame': 2 obs. of 2 variables: 465s ..$ startRow: int [1:2] 1 7587 465s ..$ endRow : int [1:2] 7586 14658 465s $ params :List of 7 465s ..$ undo.splits : chr "sdundo" 465s ..$ undo.SD : num Inf 465s ..$ alpha : num 0.009 465s ..$ undo : num Inf 465s ..$ joinSegments : logi TRUE 465s ..$ knownSegments:'data.frame': 2 obs. of 3 variables: 465s .. ..$ chromosome: num [1:2] 1 1 465s .. ..$ start : num [1:2] -Inf 1.42e+08 465s .. ..$ end : num [1:2] 1.21e+08 Inf 465s ..$ seed : int [1:7] 10407 1066287653 -51199871 161854402 -1995183193 1503453565 -747102133 465s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 465s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.001 0 0.001 0 0 465s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 465s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 465s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 465s Identification of change points by total copy numbers...done 465s Restructure TCN segmentation results... 465s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean 465s 1 1 554484 120992603 7586 1.385258 465s 2 1 141510003 247137334 7072 2.419824 465s Number of TCN segments: 2 465s Restructure TCN segmentation results...done 465s Total CN segment #1 ([ 554484,1.20993e+08]) of 2... 465s Number of TCN loci in segment: 7586 465s Locus data for TCN segment: 465s 'data.frame': 7586 obs. of 9 variables: 465s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 465s $ x : num 554484 730720 782343 878522 916294 ... 465s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 465s $ betaT : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 465s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 465s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 465s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 465s $ index : int 1 2 3 4 5 6 7 8 9 10 ... 465s $ rho : num NA NA NA NA NA ... 465s Number of loci: 7586 465s Number of SNPs: 2108 (27.79%) 465s Number of heterozygous SNPs: 2108 (100.00%) 465s Chromosome: 1 465s Segmenting DH signals... 465s Segmenting by CBS... 465s Chromosome: 1 465s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 465s Segmenting by CBS...done 465s List of 4 465s $ data :'data.frame': 7586 obs. of 4 variables: 465s ..$ chromosome: int [1:7586] 1 1 1 1 1 1 1 1 1 1 ... 465s ..$ x : num [1:7586] 554484 730720 782343 878522 916294 ... 465s ..$ y : num [1:7586] NA NA NA NA NA ... 465s ..$ index : int [1:7586] 1 2 3 4 5 6 7 8 9 10 ... 465s $ output :'data.frame': 1 obs. of 6 variables: 465s ..$ sampleName: chr NA 465s ..$ chromosome: int 1 465s ..$ start : num 554484 465s ..$ end : num 1.21e+08 465s ..$ nbrOfLoci : int 7586 465s ..$ mean : num 0.512 465s $ segRows:'data.frame': 1 obs. of 2 variables: 465s ..$ startRow: int 1 465s ..$ endRow : int 7586 465s $ params :List of 7 465s ..$ undo.splits : chr "sdundo" 465s ..$ undo.SD : num Inf 465s ..$ alpha : num 0.001 465s ..$ undo : num Inf 465s ..$ joinSegments : logi TRUE 465s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 465s .. ..$ chromosome: int 1 465s .. ..$ start : num 554484 465s .. ..$ end : num 1.21e+08 465s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 465s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 465s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.001 0 0.001 0 0 465s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 465s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 465s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 465s DH segmentation (locally-indexed) rows: 465s startRow endRow 465s 1 1 7586 465s int [1:7586] 1 2 3 4 5 6 7 8 9 10 ... 465s DH segmentation rows: 465s startRow endRow 465s 1 1 7586 465s Segmenting DH signals...done 465s DH segmentation table: 465s dhStart dhEnd dhNbrOfLoci dhMean 465s 1 554484 120992603 7586 0.511612 465s startRow endRow 465s 1 1 7586 465s Rows: 465s [1] 1 465s TCN segmentation rows: 465s startRow endRow 465s 1 1 7586 465s TCN and DH segmentation rows: 465s startRow endRow 465s 1 1 7586 465s startRow endRow 465s 1 1 7586 465s NULL 465s TCN segmentation (expanded) rows: 465s startRow endRow 465s 1 1 7586 465s TCN and DH segmentation rows: 465s startRow endRow 465s 1 1 7586 465s 2 7587 14658 465s startRow endRow 465s 1 1 7586 465s startRow endRow 465s 1 1 7586 465s Total CN segmentation table (expanded): 465s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 465s 1 1 554484 120992603 7586 1.385258 2108 2108 465s (TCN,DH) segmentation for one total CN segment: 465s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 465s 1 1 1 1 554484 120992603 7586 1.385258 2108 465s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 465s 1 2108 554484 120992603 7586 0.511612 465s Total CN segment #1 ([ 554484,1.20993e+08]) of 2...done 465s Total CN segment #2 ([1.4151e+08,2.47137e+08]) of 2... 465s Number of TCN loci in segment: 7072 465s Locus data for TCN segment: 465s 'data.frame': 7072 obs. of 9 variables: 465s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 465s $ x : num 1.43e+08 1.43e+08 1.43e+08 1.43e+08 1.44e+08 ... 465s $ CT : num 2.27 1.55 1.47 1.5 1.81 ... 465s $ betaT : num 0.34 0.55 0.048 0.813 0.575 ... 465s $ betaTN : num 0.441 0.629 -0.05 0.958 0.872 ... 465s $ betaN : num 0.3851 0.3933 0.0981 0.8552 0.7028 ... 465s $ muN : num 0.5 0.5 0 1 1 1 1 0.5 1 1 ... 465s $ index : int 7587 7588 7589 7590 7591 7592 7593 7594 7595 7596 ... 465s $ rho : num 0.117 0.258 NA NA NA ... 465s Number of loci: 7072 465s Number of SNPs: 2088 (29.52%) 465s Number of heterozygous SNPs: 2088 (100.00%) 465s Chromosome: 1 465s Segmenting DH signals... 465s Segmenting by CBS... 465s Chromosome: 1 465s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 465s Segmenting by CBS...done 465s List of 4 465s $ data :'data.frame': 7072 obs. of 4 variables: 465s ..$ chromosome: int [1:7072] 1 1 1 1 1 1 1 1 1 1 ... 465s ..$ x : num [1:7072] 1.43e+08 1.43e+08 1.43e+08 1.43e+08 1.44e+08 ... 465s ..$ y : num [1:7072] 0.117 0.258 NA NA NA ... 465s ..$ index : int [1:7072] 1 2 3 4 5 6 7 8 9 10 ... 465s $ output :'data.frame': 1 obs. of 6 variables: 465s ..$ sampleName: chr NA 465s ..$ chromosome: int 1 465s ..$ start : num 1.42e+08 465s ..$ end : num 2.47e+08 465s ..$ nbrOfLoci : int 7072 465s ..$ mean : num 0.18 465s $ segRows:'data.frame': 1 obs. of 2 variables: 465s ..$ startRow: int 1 465s ..$ endRow : int 7072 465s $ params :List of 7 465s ..$ undo.splits : chr "sdundo" 465s ..$ undo.SD : num Inf 465s ..$ alpha : num 0.001 465s ..$ undo : num Inf 465s ..$ joinSegments : logi TRUE 465s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 465s .. ..$ chromosome: int 1 465s .. ..$ start : num 1.42e+08 465s .. ..$ end : num 2.47e+08 465s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 465s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 465s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.001 0.001 0.001 0 0 465s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 465s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 465s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 465s DH segmentation (locally-indexed) rows: 465s startRow endRow 465s 1 1 7072 465s int [1:7072] 7587 7588 7589 7590 7591 7592 7593 7594 7595 7596 ... 465s DH segmentation rows: 465s startRow endRow 465s 1 7587 14658 465s Segmenting DH signals...done 465s DH segmentation table: 465s dhStart dhEnd dhNbrOfLoci dhMean 465s 1 141510003 247137334 7072 0.1803011 465s startRow endRow 465s 1 7587 14658 465s Rows: 465s [1] 2 465s TCN segmentation rows: 465s startRow endRow 465s 2 7587 14658 465s TCN and DH segmentation rows: 465s startRow endRow 465s 2 7587 14658 465s startRow endRow 465s 1 7587 14658 465s startRow endRow 465s 1 1 7586 465s TCN segmentation (expanded) rows: 465s startRow endRow 465s 1 1 7586 465s 2 7587 14658 465s TCN and DH segmentation rows: 465s startRow endRow 465s 1 1 7586 465s 2 7587 14658 465s startRow endRow 465s 1 1 7586 465s 2 7587 14658 465s startRow endRow 465s 1 1 7586 465s 2 7587 14658 465s Total CN segmentation table (expanded): 465s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 465s 2 1 141510003 247137334 7072 2.419824 2088 465s tcnNbrOfHets 465s 2 2088 465s (TCN,DH) segmentation for one total CN segment: 465s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 465s 2 2 1 1 141510003 247137334 7072 2.419824 2088 465s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 465s 2 2088 141510003 247137334 7072 0.1803011 465s Total CN segment #2 ([1.4151e+08,2.47137e+08]) of 2...done 465s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 465s 1 1 1 1 554484 120992603 7586 1.385258 2108 465s 2 1 2 1 141510003 247137334 7072 2.419824 2088 465s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 465s 1 2108 554484 120992603 7586 0.5116120 465s 2 2088 141510003 247137334 7072 0.1803011 465s Calculating (C1,C2) per segment... 465s Calculating (C1,C2) per segment...done 465s Number of segments: 2 465s Segmenting paired tumor-normal signals using Paired PSCBS...done 465s Post-segmenting TCNs... 465s Number of segments: 2 465s Number of chromosomes: 1 465s [1] 1 465s Chromosome 1 ('chr01') of 1... 465s Rows: 465s [1] 1 2 465s Number of segments: 2 465s TCN segment #1 ('1') of 2... 465s Nothing todo. Only one DH segmentation. Skipping. 465s TCN segment #1 ('1') of 2...done 465s TCN segment #2 ('2') of 2... 465s Nothing todo. Only one DH segmentation. Skipping. 465s TCN segment #2 ('2') of 2...done 465s Chromosome 1 ('chr01') of 1...done 465s Update (C1,C2) per segment... 465s Update (C1,C2) per segment...done 465s Post-segmenting TCNs...done 465s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 465s 1 1 1 1 554484 120992603 7586 1.385258 2108 465s 2 1 2 1 141510003 247137334 7072 2.419824 2088 465s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 465s 1 2108 554484 120992603 7586 0.5116120 0.3382717 1.046986 465s 2 2088 141510003 247137334 7072 0.1803011 0.9917635 1.428060 465s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 465s 1 1 1 1 554484 120992603 7586 1.385258 2108 465s 2 1 2 1 141510003 247137334 7072 2.419824 2088 465s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 465s 1 2108 554484 120992603 7586 0.5116120 0.3382717 1.046986 465s 2 2088 141510003 247137334 7072 0.1803011 0.9917635 1.428060 465s > print(fit) 465s chromosome tcnId dhId start end tcnNbrOfLoci tcnMean tcnNbrOfSNPs 465s 1 1 1 1 554484 120992603 7586 1.385258 2108 465s 2 1 2 1 141510003 247137334 7072 2.419824 2088 465s tcnNbrOfHets dhNbrOfLoci dhMean c1Mean c2Mean 465s 1 2108 7586 0.5116120 0.3382717 1.046986 465s 2 2088 7072 0.1803011 0.9917635 1.428060 465s > 465s > # Plot results 465s > dev.set(5L) 465s pdf 465s 2 465s > plotTracks(fit) 465s > abline(v=c(knownSegments$start, knownSegments$end)/1e6, lty=3) 465s > 465s > # Sanity check 465s > stopifnot(nbrOfSegments(fit) == nrow(knownSegments)) 465s > 465s > fit4 <- fit 465s > 465s > 465s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 465s > # Tiling multiple chromosomes 465s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 465s > # Simulate multiple chromosomes 465s > fit1 <- fit 465s > fit2 <- renameChromosomes(fit, from=1, to=2) 465s > fitM <- c(fit1, fit2) 465s > 465s > # Tile chromosomes 465s > fitT <- tileChromosomes(fitM) 465s > fitTb <- tileChromosomes(fitT) 465s > stopifnot(identical(fitTb, fitT)) 465s > 465s > # Plotting multiple chromosomes 465s > plotTracks(fitT) 465s > 465s autopkgtest [05:55:48]: test pkg-r-autopkgtest: -----------------------] 466s autopkgtest [05:55:49]: test pkg-r-autopkgtest: - - - - - - - - - - results - - - - - - - - - - 466s pkg-r-autopkgtest PASS 466s autopkgtest [05:55:49]: @@@@@@@@@@@@@@@@@@@@ summary 466s run-unit-test PASS 466s pkg-r-autopkgtest PASS