0s autopkgtest [00:02:46]: starting date and time: 2026-02-10 00:02:46+0000 0s autopkgtest [00:02:46]: git checkout: 4b346b80 nova: make wait_reboot return success even when a no-op 0s autopkgtest [00:02:46]: host juju-7f2275-prod-proposed-migration-environment-15; command line: /home/ubuntu/autopkgtest/runner/autopkgtest --output-dir /tmp/autopkgtest-work.iuyekf9_/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-arm64 --security-groups autopkgtest-juju-7f2275-prod-proposed-migration-environment-15@sto01-arm64-20.secgroup --name adt-resolute-arm64-r-cran-pscbs-20260210-000245-juju-7f2275-prod-proposed-migration-environment-15-c6a1c531-c43a-4d6b-af9b-41aee768bc4a --image adt/ubuntu-resolute-arm64-server --keyname testbed-juju-7f2275-prod-proposed-migration-environment-15 --net-id=net_prod-autopkgtest-workers-arm64 -e TERM=linux --mirror=http://ftpmaster.internal/ubuntu/ 3s Creating nova instance adt-resolute-arm64-r-cran-pscbs-20260210-000245-juju-7f2275-prod-proposed-migration-environment-15-c6a1c531-c43a-4d6b-af9b-41aee768bc4a from image adt/ubuntu-resolute-arm64-server-20260209.img (UUID 793037ca-75af-461b-82de-f8081300b2e3)... 212s autopkgtest [00:06:18]: testbed dpkg architecture: arm64 212s autopkgtest [00:06:18]: testbed apt version: 3.1.15 212s autopkgtest [00:06:18]: @@@@@@@@@@@@@@@@@@@@ test bed setup 213s autopkgtest [00:06:19]: testbed release detected to be: None 213s autopkgtest [00:06:19]: updating testbed package index (apt update) 214s Get:1 http://ftpmaster.internal/ubuntu resolute-proposed InRelease [124 kB] 214s Hit:2 http://ftpmaster.internal/ubuntu resolute InRelease 214s Hit:3 http://ftpmaster.internal/ubuntu resolute-updates InRelease 214s Hit:4 http://ftpmaster.internal/ubuntu resolute-security InRelease 214s Get:5 http://ftpmaster.internal/ubuntu resolute-proposed/universe Sources [1645 kB] 217s Get:6 http://ftpmaster.internal/ubuntu resolute-proposed/main Sources [176 kB] 217s Get:7 http://ftpmaster.internal/ubuntu resolute-proposed/multiverse Sources [29.4 kB] 217s Get:8 http://ftpmaster.internal/ubuntu resolute-proposed/main arm64 Packages [246 kB] 217s Get:9 http://ftpmaster.internal/ubuntu resolute-proposed/main arm64 c-n-f Metadata [6216 B] 217s Get:10 http://ftpmaster.internal/ubuntu resolute-proposed/restricted arm64 c-n-f Metadata [304 B] 217s Get:11 http://ftpmaster.internal/ubuntu resolute-proposed/universe arm64 Packages [1580 kB] 220s Get:12 http://ftpmaster.internal/ubuntu resolute-proposed/universe arm64 c-n-f Metadata [32.0 kB] 220s Get:13 http://ftpmaster.internal/ubuntu resolute-proposed/multiverse arm64 Packages [21.7 kB] 220s Get:14 http://ftpmaster.internal/ubuntu resolute-proposed/multiverse arm64 c-n-f Metadata [688 B] 221s Fetched 3862 kB in 6s (614 kB/s) 222s Reading package lists... 223s Hit:1 http://ftpmaster.internal/ubuntu resolute-proposed InRelease 223s Hit:2 http://ftpmaster.internal/ubuntu resolute InRelease 223s Hit:3 http://ftpmaster.internal/ubuntu resolute-updates InRelease 223s Hit:4 http://ftpmaster.internal/ubuntu resolute-security InRelease 224s Reading package lists... 224s Reading package lists... 224s Building dependency tree... 224s Reading state information... 224s Calculating upgrade... 225s The following packages will be upgraded: 225s cryptsetup-bin dracut-install iproute2 iptables libcryptsetup12 libip4tc2 225s libip6tc2 libxtables12 wget 225s 9 upgraded, 0 newly installed, 0 to remove and 0 not upgraded. 225s Need to get 2534 kB of archives. 225s After this operation, 18.4 kB of additional disk space will be used. 225s Get:1 http://ftpmaster.internal/ubuntu resolute/main arm64 iptables arm64 1.8.11-2ubuntu3 [386 kB] 225s Get:2 http://ftpmaster.internal/ubuntu resolute/main arm64 libip4tc2 arm64 1.8.11-2ubuntu3 [24.3 kB] 225s Get:3 http://ftpmaster.internal/ubuntu resolute/main arm64 libip6tc2 arm64 1.8.11-2ubuntu3 [24.7 kB] 225s Get:4 http://ftpmaster.internal/ubuntu resolute/main arm64 libxtables12 arm64 1.8.11-2ubuntu3 [36.7 kB] 225s Get:5 http://ftpmaster.internal/ubuntu resolute/main arm64 iproute2 arm64 6.18.0-1ubuntu1 [1171 kB] 227s Get:6 http://ftpmaster.internal/ubuntu resolute/main arm64 libcryptsetup12 arm64 2:2.8.0-1ubuntu3 [274 kB] 227s Get:7 http://ftpmaster.internal/ubuntu resolute/main arm64 wget arm64 1.25.0-2ubuntu4 [344 kB] 227s Get:8 http://ftpmaster.internal/ubuntu resolute/main arm64 cryptsetup-bin arm64 2:2.8.0-1ubuntu3 [227 kB] 227s Get:9 http://ftpmaster.internal/ubuntu resolute/main arm64 dracut-install arm64 109-11ubuntu1 [45.3 kB] 227s dpkg-preconfigure: unable to re-open stdin: No such file or directory 227s Fetched 2534 kB in 2s (1272 kB/s) 227s (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 ... 136597 files and directories currently installed.) 227s Preparing to unpack .../0-iptables_1.8.11-2ubuntu3_arm64.deb ... 228s Unpacking iptables (1.8.11-2ubuntu3) over (1.8.11-2ubuntu2) ... 228s Preparing to unpack .../1-libip4tc2_1.8.11-2ubuntu3_arm64.deb ... 228s Unpacking libip4tc2:arm64 (1.8.11-2ubuntu3) over (1.8.11-2ubuntu2) ... 228s Preparing to unpack .../2-libip6tc2_1.8.11-2ubuntu3_arm64.deb ... 228s Unpacking libip6tc2:arm64 (1.8.11-2ubuntu3) over (1.8.11-2ubuntu2) ... 228s Preparing to unpack .../3-libxtables12_1.8.11-2ubuntu3_arm64.deb ... 228s Unpacking libxtables12:arm64 (1.8.11-2ubuntu3) over (1.8.11-2ubuntu2) ... 228s Preparing to unpack .../4-iproute2_6.18.0-1ubuntu1_arm64.deb ... 228s Unpacking iproute2 (6.18.0-1ubuntu1) over (6.16.0-1ubuntu3) ... 228s Preparing to unpack .../5-libcryptsetup12_2%3a2.8.0-1ubuntu3_arm64.deb ... 228s Unpacking libcryptsetup12:arm64 (2:2.8.0-1ubuntu3) over (2:2.8.0-1ubuntu2) ... 229s Preparing to unpack .../6-wget_1.25.0-2ubuntu4_arm64.deb ... 229s Unpacking wget (1.25.0-2ubuntu4) over (1.25.0-2ubuntu3) ... 229s Preparing to unpack .../7-cryptsetup-bin_2%3a2.8.0-1ubuntu3_arm64.deb ... 229s Unpacking cryptsetup-bin (2:2.8.0-1ubuntu3) over (2:2.8.0-1ubuntu2) ... 229s Preparing to unpack .../8-dracut-install_109-11ubuntu1_arm64.deb ... 229s Unpacking dracut-install (109-11ubuntu1) over (109-9ubuntu1) ... 229s Setting up libip4tc2:arm64 (1.8.11-2ubuntu3) ... 229s Setting up wget (1.25.0-2ubuntu4) ... 229s Setting up libip6tc2:arm64 (1.8.11-2ubuntu3) ... 229s Setting up libxtables12:arm64 (1.8.11-2ubuntu3) ... 229s Setting up dracut-install (109-11ubuntu1) ... 229s Setting up libcryptsetup12:arm64 (2:2.8.0-1ubuntu3) ... 229s Setting up cryptsetup-bin (2:2.8.0-1ubuntu3) ... 229s Setting up iptables (1.8.11-2ubuntu3) ... 229s Setting up iproute2 (6.18.0-1ubuntu1) ... 229s Processing triggers for man-db (2.13.1-1build1) ... 231s Processing triggers for install-info (7.2-5) ... 231s Processing triggers for libc-bin (2.42-2ubuntu4) ... 231s autopkgtest [00:06:37]: upgrading testbed (apt dist-upgrade and autopurge) 231s Reading package lists... 232s Building dependency tree... 232s Reading state information... 232s Calculating upgrade... 232s 0 upgraded, 0 newly installed, 0 to remove and 0 not upgraded. 232s Reading package lists... 233s Building dependency tree... 233s Reading state information... 233s Solving dependencies... 233s 0 upgraded, 0 newly installed, 0 to remove and 0 not upgraded. 236s autopkgtest [00:06:42]: testbed running kernel: Linux 6.19.0-3-generic #3-Ubuntu SMP PREEMPT_DYNAMIC Fri Jan 23 19:46:27 UTC 2026 236s autopkgtest [00:06:42]: @@@@@@@@@@@@@@@@@@@@ apt-source r-cran-pscbs 250s Get:1 http://ftpmaster.internal/ubuntu resolute/universe r-cran-pscbs 0.68.0-1 (dsc) [2315 B] 250s Get:2 http://ftpmaster.internal/ubuntu resolute/universe r-cran-pscbs 0.68.0-1 (tar) [3591 kB] 250s Get:3 http://ftpmaster.internal/ubuntu resolute/universe r-cran-pscbs 0.68.0-1 (diff) [4040 B] 250s gpgv: Signature made Thu Jan 29 01:13:59 2026 UTC 250s gpgv: using RSA key 73471499CC60ED9EEE805946C5BD6C8F2295D502 250s gpgv: issuer "plessy@debian.org" 250s gpgv: Can't check signature: No public key 250s dpkg-source: warning: cannot verify inline signature for ./r-cran-pscbs_0.68.0-1.dsc: no acceptable signature found 250s autopkgtest [00:06:56]: testing package r-cran-pscbs version 0.68.0-1 251s autopkgtest [00:06:57]: build not needed 252s autopkgtest [00:06:58]: test run-unit-test: preparing testbed 253s Reading package lists... 253s Building dependency tree... 253s Reading state information... 253s Solving dependencies... 253s The following NEW packages will be installed: 253s fontconfig fontconfig-config fonts-dejavu-core fonts-dejavu-mono libblas3 253s libcairo2 libdatrie1 libdeflate0 libfontconfig1 libgfortran5 libgomp1 253s libgraphite2-3 libharfbuzz0b libice6 libjbig0 libjpeg-turbo8 libjpeg8 253s liblapack3 liblerc4 libpango-1.0-0 libpangocairo-1.0-0 libpangoft2-1.0-0 253s libpaper-utils libpaper2 libpixman-1-0 libsharpyuv0 libsm6 libtcl8.6 253s libthai-data libthai0 libtiff6 libtk8.6 libwebp7 libxcb-render0 libxcb-shm0 253s libxft2 libxrender1 libxss1 libxt6t64 r-base-core r-bioc-aroma.light 253s r-bioc-biocgenerics r-bioc-dnacopy r-cran-base64enc r-cran-cli 253s r-cran-codetools r-cran-digest r-cran-farver r-cran-future r-cran-ggplot2 253s r-cran-globals r-cran-glue r-cran-gtable r-cran-isoband r-cran-labeling 253s r-cran-lifecycle r-cran-listenv r-cran-matrixstats r-cran-parallelly 253s r-cran-pscbs r-cran-r.cache r-cran-r.devices r-cran-r.methodss3 r-cran-r.oo 253s r-cran-r.rsp r-cran-r.utils r-cran-r6 r-cran-rcolorbrewer r-cran-rlang 253s r-cran-s7 r-cran-scales r-cran-vctrs r-cran-viridislite r-cran-withr tcl 253s tcl8.6 unzip x11-common xdg-utils zip 254s 0 upgraded, 80 newly installed, 0 to remove and 0 not upgraded. 254s Need to get 66.6 MB of archives. 254s After this operation, 124 MB of additional disk space will be used. 254s Get:1 http://ftpmaster.internal/ubuntu resolute/main arm64 fonts-dejavu-mono all 2.37-8build1 [502 kB] 254s Get:2 http://ftpmaster.internal/ubuntu resolute/main arm64 fonts-dejavu-core all 2.37-8build1 [834 kB] 256s Get:3 http://ftpmaster.internal/ubuntu resolute/main arm64 fontconfig-config arm64 2.17.1-3ubuntu1 [38.5 kB] 256s Get:4 http://ftpmaster.internal/ubuntu resolute/main arm64 libfontconfig1 arm64 2.17.1-3ubuntu1 [144 kB] 256s Get:5 http://ftpmaster.internal/ubuntu resolute/main arm64 fontconfig arm64 2.17.1-3ubuntu1 [181 kB] 256s Get:6 http://ftpmaster.internal/ubuntu resolute/main arm64 libblas3 arm64 3.12.1-7ubuntu1 [181 kB] 256s Get:7 http://ftpmaster.internal/ubuntu resolute/main arm64 libpixman-1-0 arm64 0.46.4-1 [204 kB] 256s Get:8 http://ftpmaster.internal/ubuntu resolute/main arm64 libxcb-render0 arm64 1.17.0-2ubuntu1 [16.4 kB] 256s Get:9 http://ftpmaster.internal/ubuntu resolute/main arm64 libxcb-shm0 arm64 1.17.0-2ubuntu1 [5938 B] 256s Get:10 http://ftpmaster.internal/ubuntu resolute/main arm64 libxrender1 arm64 1:0.9.12-1 [19.5 kB] 256s Get:11 http://ftpmaster.internal/ubuntu resolute/main arm64 libcairo2 arm64 1.18.4-3 [556 kB] 257s Get:12 http://ftpmaster.internal/ubuntu resolute/main arm64 libdatrie1 arm64 0.2.14-1 [19.6 kB] 257s Get:13 http://ftpmaster.internal/ubuntu resolute/main arm64 libdeflate0 arm64 1.23-2build1 [46.8 kB] 257s Get:14 http://ftpmaster.internal/ubuntu resolute/main arm64 libgfortran5 arm64 15.2.0-12ubuntu1 [451 kB] 257s Get:15 http://ftpmaster.internal/ubuntu resolute/main arm64 libgomp1 arm64 15.2.0-12ubuntu1 [147 kB] 257s Get:16 http://ftpmaster.internal/ubuntu resolute/main arm64 libgraphite2-3 arm64 1.3.14-11ubuntu1 [72.1 kB] 257s Get:17 http://ftpmaster.internal/ubuntu resolute/main arm64 libharfbuzz0b arm64 12.3.2-1 [510 kB] 257s Get:18 http://ftpmaster.internal/ubuntu resolute/main arm64 x11-common all 1:7.7+24ubuntu1 [22.4 kB] 257s Get:19 http://ftpmaster.internal/ubuntu resolute/main arm64 libice6 arm64 2:1.1.1-1build1 [43.0 kB] 257s Get:20 http://ftpmaster.internal/ubuntu resolute/main arm64 libjpeg-turbo8 arm64 2.1.5-4ubuntu3 [161 kB] 257s Get:21 http://ftpmaster.internal/ubuntu resolute/main arm64 libjpeg8 arm64 8c-2ubuntu11 [2148 B] 257s Get:22 http://ftpmaster.internal/ubuntu resolute/main arm64 liblapack3 arm64 3.12.1-7ubuntu1 [2299 kB] 260s Get:23 http://ftpmaster.internal/ubuntu resolute/main arm64 liblerc4 arm64 4.0.0+ds-5ubuntu2 [174 kB] 260s Get:24 http://ftpmaster.internal/ubuntu resolute/main arm64 libthai-data all 0.1.30-1 [155 kB] 260s Get:25 http://ftpmaster.internal/ubuntu resolute/main arm64 libthai0 arm64 0.1.30-1 [18.3 kB] 260s Get:26 http://ftpmaster.internal/ubuntu resolute/main arm64 libpango-1.0-0 arm64 1.57.0-1 [238 kB] 260s Get:27 http://ftpmaster.internal/ubuntu resolute/main arm64 libpangoft2-1.0-0 arm64 1.57.0-1 [51.5 kB] 260s Get:28 http://ftpmaster.internal/ubuntu resolute/main arm64 libpangocairo-1.0-0 arm64 1.57.0-1 [27.9 kB] 260s Get:29 http://ftpmaster.internal/ubuntu resolute/main arm64 libpaper2 arm64 2.2.5-0.3build1 [17.3 kB] 260s Get:30 http://ftpmaster.internal/ubuntu resolute/main arm64 libpaper-utils arm64 2.2.5-0.3build1 [15.4 kB] 260s Get:31 http://ftpmaster.internal/ubuntu resolute/main arm64 libsharpyuv0 arm64 1.5.0-0.1build1 [16.7 kB] 260s Get:32 http://ftpmaster.internal/ubuntu resolute/main arm64 libsm6 arm64 2:1.2.6-1build1 [16.8 kB] 260s Get:33 http://ftpmaster.internal/ubuntu resolute/main arm64 libtcl8.6 arm64 8.6.17+dfsg-1build1 [983 kB] 262s Get:34 http://ftpmaster.internal/ubuntu resolute/main arm64 libjbig0 arm64 2.1-6.1ubuntu3 [29.2 kB] 262s Get:35 http://ftpmaster.internal/ubuntu resolute/main arm64 libwebp7 arm64 1.5.0-0.1build1 [205 kB] 262s Get:36 http://ftpmaster.internal/ubuntu resolute/main arm64 libtiff6 arm64 4.7.0-3ubuntu3 [196 kB] 262s Get:37 http://ftpmaster.internal/ubuntu resolute/main arm64 libxft2 arm64 2.3.6-1build2 [43.2 kB] 262s Get:38 http://ftpmaster.internal/ubuntu resolute/main arm64 libxss1 arm64 1:1.2.3-1build4 [7102 B] 262s Get:39 http://ftpmaster.internal/ubuntu resolute/main arm64 libtk8.6 arm64 8.6.17-1 [811 kB] 263s Get:40 http://ftpmaster.internal/ubuntu resolute/main arm64 libxt6t64 arm64 1:1.2.1-1.3 [168 kB] 263s Get:41 http://ftpmaster.internal/ubuntu resolute/main arm64 zip arm64 3.0-15ubuntu3 [170 kB] 263s Get:42 http://ftpmaster.internal/ubuntu resolute/main arm64 unzip arm64 6.0-29ubuntu1 [176 kB] 263s Get:43 http://ftpmaster.internal/ubuntu resolute/main arm64 xdg-utils all 1.2.1-2ubuntu2 [66.1 kB] 263s Get:44 http://ftpmaster.internal/ubuntu resolute/universe arm64 r-base-core arm64 4.5.2-1ubuntu2 [28.6 MB] 309s Get:45 http://ftpmaster.internal/ubuntu resolute/universe arm64 r-bioc-biocgenerics all 0.52.0-2 [624 kB] 310s Get:46 http://ftpmaster.internal/ubuntu resolute/universe arm64 r-cran-r.methodss3 all 1.8.2-1 [84.0 kB] 310s Get:47 http://ftpmaster.internal/ubuntu resolute/universe arm64 r-cran-r.oo all 1.27.1-1 [978 kB] 311s Get:48 http://ftpmaster.internal/ubuntu resolute/universe arm64 r-cran-r.utils all 2.13.0-1 [1423 kB] 313s Get:49 http://ftpmaster.internal/ubuntu resolute/universe arm64 r-cran-matrixstats arm64 1.5.0-1 [496 kB] 313s Get:50 http://ftpmaster.internal/ubuntu resolute/universe arm64 r-bioc-aroma.light all 3.36.0-2 [583 kB] 314s Get:51 http://ftpmaster.internal/ubuntu resolute/universe arm64 r-bioc-dnacopy arm64 1.80.0-2 [497 kB] 315s Get:52 http://ftpmaster.internal/ubuntu resolute/universe arm64 r-cran-base64enc arm64 0.1-3-3build1 [28.5 kB] 315s Get:53 http://ftpmaster.internal/ubuntu resolute/universe arm64 r-cran-cli arm64 3.6.4-1 [1374 kB] 318s Get:54 http://ftpmaster.internal/ubuntu resolute/universe arm64 r-cran-codetools all 0.2-20-1build1 [91.1 kB] 318s Get:55 http://ftpmaster.internal/ubuntu resolute/universe arm64 r-cran-digest arm64 0.6.39-1 [196 kB] 318s Get:56 http://ftpmaster.internal/ubuntu resolute/universe arm64 r-cran-farver arm64 2.1.2-1 [1344 kB] 320s Get:57 http://ftpmaster.internal/ubuntu resolute/universe arm64 r-cran-globals all 0.19.0-1 [160 kB] 320s Get:58 http://ftpmaster.internal/ubuntu resolute/universe arm64 r-cran-listenv all 0.10.0+dfsg-1 [113 kB] 320s Get:59 http://ftpmaster.internal/ubuntu resolute/universe arm64 r-cran-parallelly arm64 1.42.0-1 [540 kB] 320s Get:60 http://ftpmaster.internal/ubuntu resolute/universe arm64 r-cran-future all 1.34.0+dfsg-1 [646 kB] 321s Get:61 http://ftpmaster.internal/ubuntu resolute/universe arm64 r-cran-glue arm64 1.8.0-1 [163 kB] 321s Get:62 http://ftpmaster.internal/ubuntu resolute/universe arm64 r-cran-rlang arm64 1.1.5-3 [1706 kB] 324s Get:63 http://ftpmaster.internal/ubuntu resolute/universe arm64 r-cran-lifecycle all 1.0.5+dfsg-1 [120 kB] 324s Get:64 http://ftpmaster.internal/ubuntu resolute/universe arm64 r-cran-gtable all 0.3.6+dfsg-1 [199 kB] 325s Get:65 http://ftpmaster.internal/ubuntu resolute/universe arm64 r-cran-isoband arm64 0.2.7-1 [1481 kB] 327s Get:66 http://ftpmaster.internal/ubuntu resolute/universe arm64 r-cran-s7 arm64 0.2.0-1 [329 kB] 327s Get:67 http://ftpmaster.internal/ubuntu resolute/universe arm64 r-cran-labeling all 0.4.3-1 [62.1 kB] 327s Get:68 http://ftpmaster.internal/ubuntu resolute/universe arm64 r-cran-r6 all 2.6.1-1 [101 kB] 327s Get:69 http://ftpmaster.internal/ubuntu resolute/universe arm64 r-cran-rcolorbrewer all 1.1-3-1build2 [54.0 kB] 327s Get:70 http://ftpmaster.internal/ubuntu resolute/universe arm64 r-cran-viridislite all 0.4.3-1 [1088 kB] 329s Get:71 http://ftpmaster.internal/ubuntu resolute/universe arm64 r-cran-scales all 1.4.0-1 [725 kB] 330s Get:72 http://ftpmaster.internal/ubuntu resolute/universe arm64 r-cran-vctrs arm64 0.6.5-1 [1327 kB] 332s Get:73 http://ftpmaster.internal/ubuntu resolute/universe arm64 r-cran-withr all 3.0.2+dfsg-1 [214 kB] 332s Get:74 http://ftpmaster.internal/ubuntu resolute-proposed/universe arm64 r-cran-ggplot2 all 4.0.2+dfsg-1 [4941 kB] 340s Get:75 http://ftpmaster.internal/ubuntu resolute/universe arm64 r-cran-r.cache all 0.17.0-1 [117 kB] 340s Get:76 http://ftpmaster.internal/ubuntu resolute/universe arm64 r-cran-pscbs all 0.68.0-1 [4234 kB] 346s Get:77 http://ftpmaster.internal/ubuntu resolute/universe arm64 r-cran-r.devices all 2.17.3+ds-1 [400 kB] 346s Get:78 http://ftpmaster.internal/ubuntu resolute/main arm64 tcl8.6 arm64 8.6.17+dfsg-1build1 [14.8 kB] 346s Get:79 http://ftpmaster.internal/ubuntu resolute/main arm64 tcl arm64 8.6.16build1 [4200 B] 347s Get:80 http://ftpmaster.internal/ubuntu resolute/universe arm64 r-cran-r.rsp all 0.46.0+ds-1 [1412 kB] 349s Preconfiguring packages ... 349s Fetched 66.6 MB in 1min 35s (700 kB/s) 349s Selecting previously unselected package fonts-dejavu-mono. 349s (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 ... 136600 files and directories currently installed.) 349s Preparing to unpack .../00-fonts-dejavu-mono_2.37-8build1_all.deb ... 349s Unpacking fonts-dejavu-mono (2.37-8build1) ... 349s Selecting previously unselected package fonts-dejavu-core. 349s Preparing to unpack .../01-fonts-dejavu-core_2.37-8build1_all.deb ... 349s Unpacking fonts-dejavu-core (2.37-8build1) ... 349s Selecting previously unselected package fontconfig-config. 349s Preparing to unpack .../02-fontconfig-config_2.17.1-3ubuntu1_arm64.deb ... 349s Unpacking fontconfig-config (2.17.1-3ubuntu1) ... 349s Selecting previously unselected package libfontconfig1:arm64. 350s Preparing to unpack .../03-libfontconfig1_2.17.1-3ubuntu1_arm64.deb ... 350s Unpacking libfontconfig1:arm64 (2.17.1-3ubuntu1) ... 350s Selecting previously unselected package fontconfig. 350s Preparing to unpack .../04-fontconfig_2.17.1-3ubuntu1_arm64.deb ... 350s Unpacking fontconfig (2.17.1-3ubuntu1) ... 350s Selecting previously unselected package libblas3:arm64. 350s Preparing to unpack .../05-libblas3_3.12.1-7ubuntu1_arm64.deb ... 350s Unpacking libblas3:arm64 (3.12.1-7ubuntu1) ... 350s Selecting previously unselected package libpixman-1-0:arm64. 350s Preparing to unpack .../06-libpixman-1-0_0.46.4-1_arm64.deb ... 350s Unpacking libpixman-1-0:arm64 (0.46.4-1) ... 350s Selecting previously unselected package libxcb-render0:arm64. 350s Preparing to unpack .../07-libxcb-render0_1.17.0-2ubuntu1_arm64.deb ... 350s Unpacking libxcb-render0:arm64 (1.17.0-2ubuntu1) ... 350s Selecting previously unselected package libxcb-shm0:arm64. 350s Preparing to unpack .../08-libxcb-shm0_1.17.0-2ubuntu1_arm64.deb ... 350s Unpacking libxcb-shm0:arm64 (1.17.0-2ubuntu1) ... 350s Selecting previously unselected package libxrender1:arm64. 350s Preparing to unpack .../09-libxrender1_1%3a0.9.12-1_arm64.deb ... 350s Unpacking libxrender1:arm64 (1:0.9.12-1) ... 350s Selecting previously unselected package libcairo2:arm64. 350s Preparing to unpack .../10-libcairo2_1.18.4-3_arm64.deb ... 350s Unpacking libcairo2:arm64 (1.18.4-3) ... 350s Selecting previously unselected package libdatrie1:arm64. 350s Preparing to unpack .../11-libdatrie1_0.2.14-1_arm64.deb ... 350s Unpacking libdatrie1:arm64 (0.2.14-1) ... 350s Selecting previously unselected package libdeflate0:arm64. 350s Preparing to unpack .../12-libdeflate0_1.23-2build1_arm64.deb ... 350s Unpacking libdeflate0:arm64 (1.23-2build1) ... 350s Selecting previously unselected package libgfortran5:arm64. 350s Preparing to unpack .../13-libgfortran5_15.2.0-12ubuntu1_arm64.deb ... 350s Unpacking libgfortran5:arm64 (15.2.0-12ubuntu1) ... 350s Selecting previously unselected package libgomp1:arm64. 350s Preparing to unpack .../14-libgomp1_15.2.0-12ubuntu1_arm64.deb ... 350s Unpacking libgomp1:arm64 (15.2.0-12ubuntu1) ... 350s Selecting previously unselected package libgraphite2-3:arm64. 350s Preparing to unpack .../15-libgraphite2-3_1.3.14-11ubuntu1_arm64.deb ... 350s Unpacking libgraphite2-3:arm64 (1.3.14-11ubuntu1) ... 350s Selecting previously unselected package libharfbuzz0b:arm64. 350s Preparing to unpack .../16-libharfbuzz0b_12.3.2-1_arm64.deb ... 350s Unpacking libharfbuzz0b:arm64 (12.3.2-1) ... 350s Selecting previously unselected package x11-common. 350s Preparing to unpack .../17-x11-common_1%3a7.7+24ubuntu1_all.deb ... 350s Unpacking x11-common (1:7.7+24ubuntu1) ... 350s Selecting previously unselected package libice6:arm64. 350s Preparing to unpack .../18-libice6_2%3a1.1.1-1build1_arm64.deb ... 350s Unpacking libice6:arm64 (2:1.1.1-1build1) ... 350s Selecting previously unselected package libjpeg-turbo8:arm64. 350s Preparing to unpack .../19-libjpeg-turbo8_2.1.5-4ubuntu3_arm64.deb ... 350s Unpacking libjpeg-turbo8:arm64 (2.1.5-4ubuntu3) ... 350s Selecting previously unselected package libjpeg8:arm64. 350s Preparing to unpack .../20-libjpeg8_8c-2ubuntu11_arm64.deb ... 350s Unpacking libjpeg8:arm64 (8c-2ubuntu11) ... 350s Selecting previously unselected package liblapack3:arm64. 350s Preparing to unpack .../21-liblapack3_3.12.1-7ubuntu1_arm64.deb ... 350s Unpacking liblapack3:arm64 (3.12.1-7ubuntu1) ... 351s Selecting previously unselected package liblerc4:arm64. 351s Preparing to unpack .../22-liblerc4_4.0.0+ds-5ubuntu2_arm64.deb ... 351s Unpacking liblerc4:arm64 (4.0.0+ds-5ubuntu2) ... 351s Selecting previously unselected package libthai-data. 351s Preparing to unpack .../23-libthai-data_0.1.30-1_all.deb ... 351s Unpacking libthai-data (0.1.30-1) ... 351s Selecting previously unselected package libthai0:arm64. 351s Preparing to unpack .../24-libthai0_0.1.30-1_arm64.deb ... 351s Unpacking libthai0:arm64 (0.1.30-1) ... 351s Selecting previously unselected package libpango-1.0-0:arm64. 351s Preparing to unpack .../25-libpango-1.0-0_1.57.0-1_arm64.deb ... 351s Unpacking libpango-1.0-0:arm64 (1.57.0-1) ... 351s Selecting previously unselected package libpangoft2-1.0-0:arm64. 351s Preparing to unpack .../26-libpangoft2-1.0-0_1.57.0-1_arm64.deb ... 351s Unpacking libpangoft2-1.0-0:arm64 (1.57.0-1) ... 351s Selecting previously unselected package libpangocairo-1.0-0:arm64. 351s Preparing to unpack .../27-libpangocairo-1.0-0_1.57.0-1_arm64.deb ... 351s Unpacking libpangocairo-1.0-0:arm64 (1.57.0-1) ... 351s Selecting previously unselected package libpaper2:arm64. 351s Preparing to unpack .../28-libpaper2_2.2.5-0.3build1_arm64.deb ... 351s Unpacking libpaper2:arm64 (2.2.5-0.3build1) ... 351s Selecting previously unselected package libpaper-utils. 351s Preparing to unpack .../29-libpaper-utils_2.2.5-0.3build1_arm64.deb ... 351s Unpacking libpaper-utils (2.2.5-0.3build1) ... 351s Selecting previously unselected package libsharpyuv0:arm64. 351s Preparing to unpack .../30-libsharpyuv0_1.5.0-0.1build1_arm64.deb ... 351s Unpacking libsharpyuv0:arm64 (1.5.0-0.1build1) ... 351s Selecting previously unselected package libsm6:arm64. 351s Preparing to unpack .../31-libsm6_2%3a1.2.6-1build1_arm64.deb ... 351s Unpacking libsm6:arm64 (2:1.2.6-1build1) ... 351s Selecting previously unselected package libtcl8.6:arm64. 351s Preparing to unpack .../32-libtcl8.6_8.6.17+dfsg-1build1_arm64.deb ... 351s Unpacking libtcl8.6:arm64 (8.6.17+dfsg-1build1) ... 351s Selecting previously unselected package libjbig0:arm64. 351s Preparing to unpack .../33-libjbig0_2.1-6.1ubuntu3_arm64.deb ... 351s Unpacking libjbig0:arm64 (2.1-6.1ubuntu3) ... 351s Selecting previously unselected package libwebp7:arm64. 351s Preparing to unpack .../34-libwebp7_1.5.0-0.1build1_arm64.deb ... 351s Unpacking libwebp7:arm64 (1.5.0-0.1build1) ... 351s Selecting previously unselected package libtiff6:arm64. 351s Preparing to unpack .../35-libtiff6_4.7.0-3ubuntu3_arm64.deb ... 351s Unpacking libtiff6:arm64 (4.7.0-3ubuntu3) ... 351s Selecting previously unselected package libxft2:arm64. 351s Preparing to unpack .../36-libxft2_2.3.6-1build2_arm64.deb ... 351s Unpacking libxft2:arm64 (2.3.6-1build2) ... 351s Selecting previously unselected package libxss1:arm64. 351s Preparing to unpack .../37-libxss1_1%3a1.2.3-1build4_arm64.deb ... 351s Unpacking libxss1:arm64 (1:1.2.3-1build4) ... 351s Selecting previously unselected package libtk8.6:arm64. 351s Preparing to unpack .../38-libtk8.6_8.6.17-1_arm64.deb ... 351s Unpacking libtk8.6:arm64 (8.6.17-1) ... 351s Selecting previously unselected package libxt6t64:arm64. 351s Preparing to unpack .../39-libxt6t64_1%3a1.2.1-1.3_arm64.deb ... 351s Unpacking libxt6t64:arm64 (1:1.2.1-1.3) ... 351s Selecting previously unselected package zip. 351s Preparing to unpack .../40-zip_3.0-15ubuntu3_arm64.deb ... 351s Unpacking zip (3.0-15ubuntu3) ... 351s Selecting previously unselected package unzip. 352s Preparing to unpack .../41-unzip_6.0-29ubuntu1_arm64.deb ... 352s Unpacking unzip (6.0-29ubuntu1) ... 352s Selecting previously unselected package xdg-utils. 352s Preparing to unpack .../42-xdg-utils_1.2.1-2ubuntu2_all.deb ... 352s Unpacking xdg-utils (1.2.1-2ubuntu2) ... 352s Selecting previously unselected package r-base-core. 352s Preparing to unpack .../43-r-base-core_4.5.2-1ubuntu2_arm64.deb ... 352s Unpacking r-base-core (4.5.2-1ubuntu2) ... 352s Selecting previously unselected package r-bioc-biocgenerics. 352s Preparing to unpack .../44-r-bioc-biocgenerics_0.52.0-2_all.deb ... 352s Unpacking r-bioc-biocgenerics (0.52.0-2) ... 352s Selecting previously unselected package r-cran-r.methodss3. 352s Preparing to unpack .../45-r-cran-r.methodss3_1.8.2-1_all.deb ... 352s Unpacking r-cran-r.methodss3 (1.8.2-1) ... 352s Selecting previously unselected package r-cran-r.oo. 352s Preparing to unpack .../46-r-cran-r.oo_1.27.1-1_all.deb ... 352s Unpacking r-cran-r.oo (1.27.1-1) ... 352s Selecting previously unselected package r-cran-r.utils. 352s Preparing to unpack .../47-r-cran-r.utils_2.13.0-1_all.deb ... 352s Unpacking r-cran-r.utils (2.13.0-1) ... 352s Selecting previously unselected package r-cran-matrixstats. 352s Preparing to unpack .../48-r-cran-matrixstats_1.5.0-1_arm64.deb ... 352s Unpacking r-cran-matrixstats (1.5.0-1) ... 352s Selecting previously unselected package r-bioc-aroma.light. 352s Preparing to unpack .../49-r-bioc-aroma.light_3.36.0-2_all.deb ... 352s Unpacking r-bioc-aroma.light (3.36.0-2) ... 352s Selecting previously unselected package r-bioc-dnacopy. 352s Preparing to unpack .../50-r-bioc-dnacopy_1.80.0-2_arm64.deb ... 352s Unpacking r-bioc-dnacopy (1.80.0-2) ... 352s Selecting previously unselected package r-cran-base64enc. 352s Preparing to unpack .../51-r-cran-base64enc_0.1-3-3build1_arm64.deb ... 352s Unpacking r-cran-base64enc (0.1-3-3build1) ... 352s Selecting previously unselected package r-cran-cli. 352s Preparing to unpack .../52-r-cran-cli_3.6.4-1_arm64.deb ... 352s Unpacking r-cran-cli (3.6.4-1) ... 352s Selecting previously unselected package r-cran-codetools. 352s Preparing to unpack .../53-r-cran-codetools_0.2-20-1build1_all.deb ... 352s Unpacking r-cran-codetools (0.2-20-1build1) ... 352s Selecting previously unselected package r-cran-digest. 353s Preparing to unpack .../54-r-cran-digest_0.6.39-1_arm64.deb ... 353s Unpacking r-cran-digest (0.6.39-1) ... 353s Selecting previously unselected package r-cran-farver. 353s Preparing to unpack .../55-r-cran-farver_2.1.2-1_arm64.deb ... 353s Unpacking r-cran-farver (2.1.2-1) ... 353s Selecting previously unselected package r-cran-globals. 353s Preparing to unpack .../56-r-cran-globals_0.19.0-1_all.deb ... 353s Unpacking r-cran-globals (0.19.0-1) ... 353s Selecting previously unselected package r-cran-listenv. 353s Preparing to unpack .../57-r-cran-listenv_0.10.0+dfsg-1_all.deb ... 353s Unpacking r-cran-listenv (0.10.0+dfsg-1) ... 353s Selecting previously unselected package r-cran-parallelly. 353s Preparing to unpack .../58-r-cran-parallelly_1.42.0-1_arm64.deb ... 353s Unpacking r-cran-parallelly (1.42.0-1) ... 353s Selecting previously unselected package r-cran-future. 353s Preparing to unpack .../59-r-cran-future_1.34.0+dfsg-1_all.deb ... 353s Unpacking r-cran-future (1.34.0+dfsg-1) ... 353s Selecting previously unselected package r-cran-glue. 353s Preparing to unpack .../60-r-cran-glue_1.8.0-1_arm64.deb ... 353s Unpacking r-cran-glue (1.8.0-1) ... 353s Selecting previously unselected package r-cran-rlang. 353s Preparing to unpack .../61-r-cran-rlang_1.1.5-3_arm64.deb ... 353s Unpacking r-cran-rlang (1.1.5-3) ... 353s Selecting previously unselected package r-cran-lifecycle. 353s Preparing to unpack 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r-cran-rcolorbrewer. 353s Preparing to unpack .../68-r-cran-rcolorbrewer_1.1-3-1build2_all.deb ... 353s Unpacking r-cran-rcolorbrewer (1.1-3-1build2) ... 353s Selecting previously unselected package r-cran-viridislite. 353s Preparing to unpack .../69-r-cran-viridislite_0.4.3-1_all.deb ... 353s Unpacking r-cran-viridislite (0.4.3-1) ... 353s Selecting previously unselected package r-cran-scales. 353s Preparing to unpack .../70-r-cran-scales_1.4.0-1_all.deb ... 353s Unpacking r-cran-scales (1.4.0-1) ... 353s Selecting previously unselected package r-cran-vctrs. 354s Preparing to unpack .../71-r-cran-vctrs_0.6.5-1_arm64.deb ... 354s Unpacking r-cran-vctrs (0.6.5-1) ... 354s Selecting previously unselected package r-cran-withr. 354s Preparing to unpack .../72-r-cran-withr_3.0.2+dfsg-1_all.deb ... 354s Unpacking r-cran-withr (3.0.2+dfsg-1) ... 354s Selecting previously unselected package r-cran-ggplot2. 354s Preparing to unpack .../73-r-cran-ggplot2_4.0.2+dfsg-1_all.deb ... 354s Unpacking r-cran-ggplot2 (4.0.2+dfsg-1) ... 354s Selecting previously unselected package r-cran-r.cache. 354s Preparing to unpack .../74-r-cran-r.cache_0.17.0-1_all.deb ... 354s Unpacking r-cran-r.cache (0.17.0-1) ... 354s Selecting previously unselected package r-cran-pscbs. 354s Preparing to unpack .../75-r-cran-pscbs_0.68.0-1_all.deb ... 354s Unpacking r-cran-pscbs (0.68.0-1) ... 354s Selecting previously unselected package r-cran-r.devices. 354s Preparing to unpack .../76-r-cran-r.devices_2.17.3+ds-1_all.deb ... 354s Unpacking r-cran-r.devices (2.17.3+ds-1) ... 354s Selecting previously unselected package tcl8.6. 354s Preparing to unpack .../77-tcl8.6_8.6.17+dfsg-1build1_arm64.deb ... 354s Unpacking tcl8.6 (8.6.17+dfsg-1build1) ... 354s Selecting previously unselected package tcl. 354s Preparing to unpack .../78-tcl_8.6.16build1_arm64.deb ... 354s Unpacking tcl (8.6.16build1) ... 354s Selecting previously unselected package r-cran-r.rsp. 354s Preparing to unpack .../79-r-cran-r.rsp_0.46.0+ds-1_all.deb ... 354s Unpacking r-cran-r.rsp (0.46.0+ds-1) ... 354s Setting up libgraphite2-3:arm64 (1.3.14-11ubuntu1) ... 354s Setting up libpixman-1-0:arm64 (0.46.4-1) ... 354s Setting up libsharpyuv0:arm64 (1.5.0-0.1build1) ... 354s Setting up liblerc4:arm64 (4.0.0+ds-5ubuntu2) ... 354s Setting up libxrender1:arm64 (1:0.9.12-1) ... 354s Setting up libdatrie1:arm64 (0.2.14-1) ... 354s Setting up libxcb-render0:arm64 (1.17.0-2ubuntu1) ... 354s Setting up unzip (6.0-29ubuntu1) ... 354s Setting up x11-common (1:7.7+24ubuntu1) ... 355s Setting up libdeflate0:arm64 (1.23-2build1) ... 355s Setting up libxcb-shm0:arm64 (1.17.0-2ubuntu1) ... 355s Setting up libgomp1:arm64 (15.2.0-12ubuntu1) ... 355s Setting up libjbig0:arm64 (2.1-6.1ubuntu3) ... 355s Setting up zip (3.0-15ubuntu3) ... 355s Setting up libblas3:arm64 (3.12.1-7ubuntu1) ... 355s update-alternatives: using /usr/lib/aarch64-linux-gnu/blas/libblas.so.3 to provide /usr/lib/aarch64-linux-gnu/libblas.so.3 (libblas.so.3-aarch64-linux-gnu) in auto mode 355s Setting up fonts-dejavu-mono (2.37-8build1) ... 355s Setting up libtcl8.6:arm64 (8.6.17+dfsg-1build1) ... 355s Setting up fonts-dejavu-core (2.37-8build1) ... 355s Setting up libjpeg-turbo8:arm64 (2.1.5-4ubuntu3) ... 355s Setting up libgfortran5:arm64 (15.2.0-12ubuntu1) ... 355s Setting up libwebp7:arm64 (1.5.0-0.1build1) ... 355s Setting up libharfbuzz0b:arm64 (12.3.2-1) ... 355s Setting up libthai-data (0.1.30-1) ... 355s Setting up libxss1:arm64 (1:1.2.3-1build4) ... 355s Setting up libpaper2:arm64 (2.2.5-0.3build1) ... 355s Setting up xdg-utils (1.2.1-2ubuntu2) ... 355s update-alternatives: using /usr/bin/xdg-open to provide /usr/bin/open (open) in auto mode 355s Setting up libjpeg8:arm64 (8c-2ubuntu11) ... 355s Setting up libice6:arm64 (2:1.1.1-1build1) ... 355s Setting up tcl8.6 (8.6.17+dfsg-1build1) ... 355s Setting up liblapack3:arm64 (3.12.1-7ubuntu1) ... 355s update-alternatives: using /usr/lib/aarch64-linux-gnu/lapack/liblapack.so.3 to provide /usr/lib/aarch64-linux-gnu/liblapack.so.3 (liblapack.so.3-aarch64-linux-gnu) in auto mode 355s Setting up fontconfig-config (2.17.1-3ubuntu1) ... 355s Setting up libpaper-utils (2.2.5-0.3build1) ... 355s Setting up libthai0:arm64 (0.1.30-1) ... 355s Setting up libtiff6:arm64 (4.7.0-3ubuntu3) ... 355s Setting up tcl (8.6.16build1) ... 355s Setting up libfontconfig1:arm64 (2.17.1-3ubuntu1) ... 355s Setting up libsm6:arm64 (2:1.2.6-1build1) ... 355s Setting up fontconfig (2.17.1-3ubuntu1) ... 357s Regenerating fonts cache... done. 357s Setting up libxft2:arm64 (2.3.6-1build2) ... 357s Setting up libtk8.6:arm64 (8.6.17-1) ... 357s Setting up libpango-1.0-0:arm64 (1.57.0-1) ... 357s Setting up libcairo2:arm64 (1.18.4-3) ... 357s Setting up libxt6t64:arm64 (1:1.2.1-1.3) ... 357s Setting up libpangoft2-1.0-0:arm64 (1.57.0-1) ... 357s Setting up libpangocairo-1.0-0:arm64 (1.57.0-1) ... 357s Setting up r-base-core (4.5.2-1ubuntu2) ... 357s Creating config file /etc/R/Renviron with new version 357s Setting up r-cran-labeling (0.4.3-1) ... 357s Setting up r-cran-farver (2.1.2-1) ... 357s Setting up r-cran-viridislite (0.4.3-1) ... 357s Setting up r-cran-r6 (2.6.1-1) ... 357s Setting up r-cran-codetools (0.2-20-1build1) ... 357s Setting up r-bioc-biocgenerics (0.52.0-2) ... 357s Setting up r-cran-rlang (1.1.5-3) ... 357s Setting up r-cran-matrixstats (1.5.0-1) ... 357s Setting up r-cran-listenv (0.10.0+dfsg-1) ... 357s Setting up r-cran-withr (3.0.2+dfsg-1) ... 357s Setting up r-cran-base64enc (0.1-3-3build1) ... 357s Setting up r-cran-digest (0.6.39-1) ... 357s Setting up r-cran-glue (1.8.0-1) ... 357s Setting up r-cran-cli (3.6.4-1) ... 357s Setting up r-cran-lifecycle (1.0.5+dfsg-1) ... 357s Setting up r-cran-r.methodss3 (1.8.2-1) ... 357s Setting up r-cran-parallelly (1.42.0-1) ... 357s Setting up r-cran-s7 (0.2.0-1) ... 357s Setting up r-cran-rcolorbrewer (1.1-3-1build2) ... 357s Setting up r-cran-isoband (0.2.7-1) ... 357s Setting up r-cran-scales (1.4.0-1) ... 357s Setting up r-cran-gtable (0.3.6+dfsg-1) ... 357s Setting up r-bioc-dnacopy (1.80.0-2) ... 357s Setting up r-cran-globals (0.19.0-1) ... 357s Setting up r-cran-vctrs (0.6.5-1) ... 357s Setting up r-cran-ggplot2 (4.0.2+dfsg-1) ... 357s Setting up r-cran-r.oo (1.27.1-1) ... 357s Setting up r-cran-future (1.34.0+dfsg-1) ... 357s Setting up r-cran-r.utils (2.13.0-1) ... 357s Setting up r-cran-r.devices (2.17.3+ds-1) ... 357s Setting up r-bioc-aroma.light (3.36.0-2) ... 357s Setting up r-cran-r.cache (0.17.0-1) ... 357s Setting up r-cran-pscbs (0.68.0-1) ... 357s Setting up r-cran-r.rsp (0.46.0+ds-1) ... 357s Processing triggers for libc-bin (2.42-2ubuntu4) ... 357s Processing triggers for man-db (2.13.1-1build1) ... 358s Processing triggers for install-info (7.2-5) ... 359s autopkgtest [00:08:45]: test run-unit-test: [----------------------- 359s + pkg=r-cran-pscbs 359s + [ /tmp/autopkgtest.b85msM/autopkgtest_tmp = ] 359s + cd /tmp/autopkgtest.b85msM/autopkgtest_tmp 359s + 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.b85msM/autopkgtest_tmp 359s + find . -name *.gz -exec gunzip {} ; 359s + export LC_ALL=C 359s + dpkg-architecture -qDEB_HOST_ARCH 359s dpkg-architecture: warning: cannot determine CC system type, falling back to default (native compilation) 359s + hostarch=arm64 359s + [ arm64 = armhf ] 359s + ls PairedPSCBS,boot.R+ findLargeGaps.R randomSeed.Rsed s/\.R$// 359s 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 359s Begin test PairedPSCBS,boot 359s + echo Begin test PairedPSCBS,boot 359s + exitcode=0 359s + R CMD BATCH PairedPSCBS,boot.R 363s + cat PairedPSCBS,boot.Rout 363s 363s R version 4.5.2 (2025-10-31) -- "[Not] Part in a Rumble" 363s Copyright (C) 2025 The R Foundation for Statistical Computing 363s Platform: aarch64-unknown-linux-gnu 363s 363s R is free software and comes with ABSOLUTELY NO WARRANTY. 363s You are welcome to redistribute it under certain conditions. 363s Type 'license()' or 'licence()' for distribution details. 363s 363s R is a collaborative project with many contributors. 363s Type 'contributors()' for more information and 363s 'citation()' on how to cite R or R packages in publications. 363s 363s Type 'demo()' for some demos, 'help()' for on-line help, or 363s 'help.start()' for an HTML browser interface to help. 363s Type 'q()' to quit R. 363s 363s > ########################################################### 363s > # This tests: 363s > # - Bootstrapping for PairedPSCBS objects 363s > ########################################################### 363s > library("PSCBS") 363s PSCBS v0.68.0 (2025-04-18 19:40:02 UTC) successfully loaded. See ?PSCBS for help. 363s > 363s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 363s > # Load SNP microarray data 363s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 363s > data <- PSCBS::exampleData("paired.chr01") 363s > 363s > 363s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 363s > # Paired PSCBS segmentation 363s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 363s > # Drop single-locus outliers 363s > dataS <- dropSegmentationOutliers(data) 363s > dataS <- dataS[seq(from=1, to=nrow(data), by=5),] 363s > nSegs <- 4L 363s > str(dataS) 363s 'data.frame': 14670 obs. of 6 variables: 363s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 363s $ x : int 1145994 2941694 3710825 4240737 4276892 4464544 4714611 5095111 5034491 5158416 ... 363s $ CT : num 1.63 1.4 1.41 1.17 1.16 ... 363s $ betaT : num 0.7574 0.169 0.2357 0.2604 0.0576 ... 363s $ CN : num 2.36 2.13 2.26 2.01 2.32 ... 363s $ betaN : num 0.8274 0.5072 0.1671 0.1609 0.0421 ... 363s > # Segment known regions 363s > knownSegments <- data.frame( 363s + chromosome = c( 1, 1, 1), 363s + start = c( -Inf, NA, 141510003), 363s + end = c(120992603, NA, +Inf) 363s + ) 363s > fit <- segmentByPairedPSCBS(dataS, knownSegments=knownSegments, avgDH="median", seed=0xBEEF) 363s > print(fit) 363s chromosome tcnId dhId start end tcnNbrOfLoci tcnMean tcnNbrOfSNPs 363s 1 1 1 1 554484 120992603 7586 1.385258 2108 363s 2 NA 2 1 NA NA NA NA 0 363s 3 1 3 1 141510003 185449813 2681 2.068861 777 363s 4 1 4 1 185449813 247137334 4391 2.634110 1311 363s tcnNbrOfHets dhNbrOfLoci dhMean c1Mean c2Mean 363s 1 2108 2108 0.54551245 0.3147912 1.070467 363s 2 0 0 NA NA NA 363s 3 777 777 0.07132277 0.9606521 1.108209 363s 4 1311 1311 0.21663871 1.0317300 1.602380 363s > 363s > 363s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 363s > # Bootstrap 363s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 363s > B <- 1L 363s > seed <- 0xBEEF 363s > probs <- c(0.025, 0.05, 0.95, 0.975) 363s > 363s > sets <- getBootstrapLocusSets(fit, B=B, seed=seed) 363s > 363s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 363s > # Subset by first segment 363s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 363s > ss <- 1L 363s > 363s > fitT <- extractSegment(fit, ss) 363s > dataT <- getLocusData(fitT) 363s > segsT <- getSegments(fitT) 363s > 363s > # Truth 363s > bootT <- bootstrapSegmentsAndChangepoints(fitT, B=B, seed=seed) 363s > bootT1 <- bootT$segments[1L,,,drop=FALSE] 363s > types <- dimnames(bootT1)[[3L]] 363s > dim(bootT1) <- dim(bootT1)[-1L] 363s > colnames(bootT1) <- types 363s > sumsT <- apply(bootT1, MARGIN=2L, FUN=quantile, probs=probs) 363s > print(sumsT) 363s tcn dh c1 c2 363s 2.5% 1.383213 0.5466788 0.3135198 1.069693 363s 5% 1.383213 0.5466788 0.3135198 1.069693 363s 95% 1.383213 0.5466788 0.3135198 1.069693 363s 97.5% 1.383213 0.5466788 0.3135198 1.069693 363s > 363s > fitTB <- bootstrapTCNandDHByRegion(fitT, B=B, seed=seed) 363s > segsTB <- getSegments(fitTB) 363s > segsTB <- unlist(segsTB[,grep("_", colnames(segsTB))]) 363s > dim(segsTB) <- dim(sumsT) 363s > dimnames(segsTB) <- dimnames(sumsT) 363s > print(segsTB) 363s tcn dh c1 c2 363s 2.5% 1.383213 0.5466788 0.3135198 1.069693 363s 5% 1.383213 0.5466788 0.3135198 1.069693 363s 95% 1.383213 0.5466788 0.3135198 1.069693 363s 97.5% 1.383213 0.5466788 0.3135198 1.069693 363s > 363s > # Sanity check 363s > stopifnot(all.equal(segsTB, sumsT)) 363s > 363s > # Calculate summaries using the existing bootstrap samples 363s > fitTBp <- bootstrapTCNandDHByRegion(fitT, .boot=bootT) 363s > # Sanity check 363s > all.equal(fitTBp, fitTB) 363s [1] "Component \"tcn_2.5%\": Mean relative difference: 0.003070405" 363s [2] "Component \"tcn_5%\": Mean relative difference: 0.002241362" 363s [3] "Component \"tcn_95%\": Mean relative difference: 0.005458479" 363s [4] "Component \"tcn_97.5%\": Mean relative difference: 0.006030363" 363s [5] "Component \"dh_2.5%\": Mean relative difference: 0.02683423" 363s [6] "Component \"dh_5%\": Mean relative difference: 0.02409533" 363s [7] "Component \"dh_95%\": Mean relative difference: 0.0150081" 363s [8] "Component \"dh_97.5%\": Mean relative difference: 0.01826461" 363s [9] "Component \"c1_2.5%\": Mean relative difference: 0.02397349" 363s [10] "Component \"c1_5%\": Mean relative difference: 0.01800948" 363s [11] "Component \"c1_95%\": Mean relative difference: 0.0303456" 363s [12] "Component \"c1_97.5%\": Mean relative difference: 0.03420614" 363s [13] "Component \"c2_2.5%\": Mean relative difference: 0.008723378" 363s [14] "Component \"c2_5%\": Mean relative difference: 0.006834962" 363s [15] "Component \"c2_95%\": Mean relative difference: 0.00741949" 363s [16] "Component \"c2_97.5%\": Mean relative difference: 0.008743911" 363s attr(,"what") 363s [1] "getSegments()" 363s > 363s > 363s > # Bootstrap from scratch 363s > setsT <- getBootstrapLocusSets(fitT, B=B, seed=seed) 363s > lociT <- setsT$locusSet[[1L]]$bootstrap$loci 363s > idxs <- lociT$tcn 363s > tcnT <- array(dataT$CT[idxs], dim=dim(idxs)) 363s > tcnT <- apply(tcnT, MARGIN=2L, FUN=mean, na.rm=TRUE) 363s > idxs <- lociT$dh 363s > dhT <- array(dataT$rho[idxs], dim=dim(idxs)) 363s > dhT <- apply(dhT, MARGIN=2L, FUN=median, na.rm=TRUE) 363s > c1T <- (1-dhT) * tcnT / 2 363s > c2T <- tcnT - c1T 363s > bootT2 <- array(c(tcnT, dhT, c1T, c2T), dim=c(1L, 4L)) 363s > colnames(bootT2) <- colnames(bootT1) 363s > print(bootT2) 363s tcn dh c1 c2 363s [1,] 1.383213 0.5466788 0.3135198 1.069693 363s > 363s > # This comparison is only valid if B == 1L 363s > if (B == 1L) { 363s + # Sanity check 363s + stopifnot(all.equal(bootT2, bootT1)) 363s + } 363s > 363s > proc.time() 363s user system elapsed 363s 2.701 0.123 2.795 363s Test PairedPSCBS,boot passed 363s + [ 0 != 0 ] 363s + echo Test PairedPSCBS,boot passed 363s + echo 0 363s 0 363s + Begin test findLargeGaps 363s echo Begin test findLargeGaps 363s + exitcode=0 363s + R CMD BATCH findLargeGaps.R 364s + cat findLargeGaps.Rout 364s 364s R version 4.5.2 (2025-10-31) -- "[Not] Part in a Rumble" 364s Copyright (C) 2025 The R Foundation for Statistical Computing 364s Platform: aarch64-unknown-linux-gnu 364s 364s R is free software and comes with ABSOLUTELY NO WARRANTY. 364s You are welcome to redistribute it under certain conditions. 364s Type 'license()' or 'licence()' for distribution details. 364s 364s R is a collaborative project with many contributors. 364s Type 'contributors()' for more information and 364s 'citation()' on how to cite R or R packages in publications. 364s 364s Type 'demo()' for some demos, 'help()' for on-line help, or 364s 'help.start()' for an HTML browser interface to help. 364s Type 'q()' to quit R. 364s 364s [Previously saved workspace restored] 364s 364s > library("PSCBS") 364s PSCBS v0.68.0 (2025-04-18 19:40:02 UTC) successfully loaded. See ?PSCBS for help. 364s > 364s > # Simulating copy-number data 364s > set.seed(0xBEEF) 364s > 364s > # Simulate CN data 364s > J <- 1000 364s > mu <- double(J) 364s > mu[200:300] <- mu[200:300] + 1 364s > mu[350:400] <- NA # centromere 364s > mu[650:800] <- mu[650:800] - 1 364s > eps <- rnorm(J, sd=1/2) 364s > y <- mu + eps 364s > x <- seq(from=1, to=100e6, length.out=J) 364s > 364s > data <- data.frame(chromosome=0L, x=x) 364s > 364s > gaps <- findLargeGaps(x=x, minLength=1e6) 364s > print(gaps) 364s [1] start end length 364s <0 rows> (or 0-length row.names) 364s > stopifnot(is.data.frame(gaps)) 364s > stopifnot(nrow(gaps) == 0L) 364s > segs <- gapsToSegments(gaps) 364s > print(segs) 364s chromosome start end 364s 1 0 -Inf Inf 364s > stopifnot(is.data.frame(segs)) 364s > stopifnot(nrow(segs) == 1L) 364s > 364s > 364s > gaps <- findLargeGaps(data, minLength=1e6) 364s > print(gaps) 364s [1] chromosome start end 364s <0 rows> (or 0-length row.names) 364s > stopifnot(is.data.frame(gaps)) 364s > stopifnot(nrow(gaps) == 0L) 364s > segs <- gapsToSegments(gaps) 364s > print(segs) 364s chromosome start end 364s 1 0 -Inf Inf 364s > stopifnot(is.data.frame(segs)) 364s > stopifnot(nrow(segs) == 1L) 364s > 364s > 364s > ## Add missing values 364s > data2 <- data 364s > data$x[30e6 < x & x < 50e6] <- NA 364s > gaps <- findLargeGaps(data, minLength=1e6) 364s > print(gaps) 364s chromosome start end length 364s 1 0 29929932 50050050 20120118 364s > stopifnot(is.data.frame(gaps)) 364s > stopifnot(nrow(gaps) == 1L) 364s > segs <- gapsToSegments(gaps) 364s > print(segs) 364s chromosome start end length 364s 1 0 -Inf 29929931 Inf 364s 2 0 29929932 50050050 20120118 364s 3 0 50050051 Inf Inf 364s > stopifnot(is.data.frame(segs)) 364s > stopifnot(nrow(segs) == 3L) 364s > 364s > 364s > 364s > # BUG FIX: Issue #6 364s > gaps <- findLargeGaps(chromosome=rep(1,10), x=1:10, minLength=2) 364s > print(gaps) 364s [1] chromosome start end 364s <0 rows> (or 0-length row.names) 364s > stopifnot(is.data.frame(gaps)) 364s > stopifnot(nrow(gaps) == 0L) 364s > # BUG FIX: Issue #9 364s > segs <- gapsToSegments(gaps) 364s > print(segs) 364s chromosome start end 364s 1 0 -Inf Inf 364s > stopifnot(is.data.frame(segs)) 364s > stopifnot(nrow(segs) == 1L) 364s > 364s > 364s > # BUG FIX: PSCBS GitHub Issue #8 364s > gaps <- try({ 364s + findLargeGaps(chromosome=rep(1,3), x=as.numeric(1:3), minLength=1) 364s + }) 364s Error in findLargeGaps.default(chromosome = rep(1, 3), x = as.numeric(1:3), : 364s Cannot identify large gaps. Argument 'resolution' (=1) is not strictly smaller than 'minLength' (=1). 364s > stopifnot(inherits(gaps, "try-error")) 364s > 364s > proc.time() 364s user system elapsed 364s 0.446 0.066 0.497 364s Test findLargeGaps passed 364s 0 364s Begin test randomSeed 364s + [ 0 != 0 ] 364s + echo Test findLargeGaps passed 364s + echo 0 364s + echo Begin test randomSeed 364s + exitcode=0 364s + R CMD BATCH randomSeed.R 364s + cat randomSeed.Rout 364s + [ 0 != 0 ] 364s + echo Test randomSeed passed 364s + echo 0 364s + echo Begin test segmentByCBS,bug67 364s + exitcode=0 364s + R CMD BATCH segmentByCBS,bug67.R 364s 364s R version 4.5.2 (2025-10-31) -- "[Not] Part in a Rumble" 364s Copyright (C) 2025 The R Foundation for Statistical Computing 364s Platform: aarch64-unknown-linux-gnu 364s 364s R is free software and comes with ABSOLUTELY NO WARRANTY. 364s You are welcome to redistribute it under certain conditions. 364s Type 'license()' or 'licence()' for distribution details. 364s 364s R is a collaborative project with many contributors. 364s Type 'contributors()' for more information and 364s 'citation()' on how to cite R or R packages in publications. 364s 364s Type 'demo()' for some demos, 'help()' for on-line help, or 364s 'help.start()' for an HTML browser interface to help. 364s Type 'q()' to quit R. 364s 364s [Previously saved workspace restored] 364s 364s > library("PSCBS") 364s PSCBS v0.68.0 (2025-04-18 19:40:02 UTC) successfully loaded. See ?PSCBS for help. 364s > 364s > message("*** randomSeed() - setup ...") 364s *** randomSeed() - setup ... 364s > ovars <- ls(envir=globalenv()) 364s > genv <- globalenv() 364s > RNGkind("Mersenne-Twister") 364s > if (exists(".Random.seed", envir=genv, inherits=FALSE)) 364s + rm(list=".Random.seed", envir=genv, inherits=FALSE) 364s > seed0 <- genv$.Random.seed 364s > stopifnot(is.null(seed0)) 364s > okind0 <- RNGkind()[1L] 364s > 364s > sample1 <- function() { sample(0:9, size=1L) } 364s > message("*** randomSeed() - setup ... done") 364s *** randomSeed() - setup ... done 364s > 364s > 364s > message("*** randomSeed('get') ...") 364s *** randomSeed('get') ... 364s > ## Get random seed 364s > seed <- randomSeed("get") 364s > stopifnot(identical(seed, seed0)) 364s > 364s > ## Repeat after new sample 364s > y1 <- sample1() 364s > message(sprintf("Random number: %d", y1)) 364s Random number: 8 364s > seed1 <- randomSeed("get") 364s > stopifnot(!identical(seed1, seed0)) 364s > message("*** randomSeed('get') ... done") 364s *** randomSeed('get') ... done 364s > 364s > 364s > message("*** randomSeed('set', 42L) ...") 364s *** randomSeed('set', 42L) ... 364s > randomSeed("set", seed=42L) 364s > seed2 <- randomSeed("get") 364s > stopifnot(!identical(seed2, seed1)) 364s > 364s > y2 <- sample1() 364s > message(sprintf("Random number: %d (with random seed = 42L)", y2)) 364s Random number: 0 (with random seed = 42L) 364s > 364s > ## Reset to previous state 364s > randomSeed("reset") 364s > seed3 <- randomSeed("get") 364s > stopifnot(identical(seed3, seed1)) 364s > stopifnot(identical(RNGkind()[1L], okind0), 364s + identical(randomSeed("get"), seed1)) 364s > message("*** randomSeed('set', 42L) ... done") 364s *** randomSeed('set', 42L) ... done 364s > 364s > 364s > message("*** randomSeed('set', NULL) ...") 364s *** randomSeed('set', NULL) ... 364s > randomSeed("set", seed=NULL) 364s > seed4 <- randomSeed("get") 364s > stopifnot(is.null(seed4)) 364s > 364s > y3 <- sample1() 364s > message(sprintf("Random number: %d", y3)) 364s Random number: 6 364s > 364s > message("*** randomSeed('set', NULL) ... done") 364s *** randomSeed('set', NULL) ... done 364s > 364s > 364s > message("*** randomSeed('set', 42L) again ...") 364s *** randomSeed('set', 42L) again ... 364s > seed5 <- randomSeed("get") 364s > randomSeed("set", seed=42L) 364s > y4 <- sample1() 364s > message(sprintf("Random number: %d (with random seed = 42L)", y4)) 364s Random number: 0 (with random seed = 42L) 364s > stopifnot(identical(y4, y2)) 364s > 364s > randomSeed("reset") 364s > stopifnot(identical(RNGkind()[1L], okind0), 364s + identical(randomSeed("get"), seed5)) 364s > message("*** randomSeed('set', 42L) again ... done") 364s *** randomSeed('set', 42L) again ... done 364s > 364s > 364s > 364s > ## L'Ecuyer-CMRG: Random number generation for parallel processing 364s > message("*** randomSeed(): L'Ecuyer-CMRG stream ...") 364s *** randomSeed(): L'Ecuyer-CMRG stream ... 364s > 364s > okind <- RNGkind()[1L] 364s > stopifnot(identical(okind, okind0)) 364s > 364s > randomSeed("set", seed=NULL) 364s > oseed <- randomSeed("get") 364s > stopifnot(is.null(oseed)) 364s > 364s > randomSeed("set", seed=42L, kind="L'Ecuyer-CMRG") 364s > oseed2 <- randomSeed("reset") 364s > str(oseed2) 364s NULL 364s > stopifnot(identical(oseed2, oseed)) 364s > stopifnot(identical(RNGkind()[1L], okind), 364s + identical(randomSeed("get"), oseed)) 364s > 364s > randomSeed("set", seed=42L, kind="L'Ecuyer-CMRG") 364s > seed0 <- randomSeed("get") 364s > seeds0 <- lapply(1:10, FUN=function(i) randomSeed("advance")) 364s > oseed2 <- randomSeed("reset") 364s > stopifnot(identical(oseed2, oseed)) 364s > stopifnot(identical(RNGkind()[1L], okind), 364s + identical(randomSeed("get"), oseed)) 364s > 364s > 364s > ## Assert reproducible .Random.seed stream 364s > randomSeed("set", seed=42L, kind="L'Ecuyer-CMRG") 364s > seed1 <- randomSeed("get") 364s > seeds1 <- lapply(1:10, FUN=function(i) randomSeed("advance")) 364s > stopifnot(identical(seed1, seed0)) 364s > stopifnot(identical(seeds1, seeds0)) 364s > 364s > randomSeed("reset") 364s > stopifnot(identical(RNGkind()[1L], okind), 364s + identical(randomSeed("get"), oseed)) 364s > 364s > randomSeed("set", seed=42L, kind="L'Ecuyer-CMRG") 364s > seeds2 <- randomSeed("advance", n=10L) 364s > stopifnot(identical(seeds2, seeds0)) 364s > 364s > randomSeed("reset") 364s > stopifnot(identical(RNGkind()[1L], okind), 364s + identical(randomSeed("get"), oseed)) 364s > 364s > randomSeed("set", seed=seeds2[[1]], kind="L'Ecuyer-CMRG") 364s > randomSeed("reset") 364s > stopifnot(identical(RNGkind()[1L], okind), 364s + identical(randomSeed("get"), oseed)) 364s > 364s > randomSeed("set", seed=42L, kind="L'Ecuyer-CMRG") 364s > y0 <- sapply(1:10, FUN=function(ii) { 364s + randomSeed("advance") 364s + sample1() 364s + }) 364s > print(y0) 364s [1] 6 9 6 9 9 9 0 7 6 5 364s > randomSeed("reset") 364s > 364s > randomSeed("set", seed=42L, kind="L'Ecuyer-CMRG") 364s > y1 <- sapply(1:10, FUN=function(ii) { 364s + randomSeed("advance") 364s + sample1() 364s + }) 364s > print(y1) 364s [1] 6 9 6 9 9 9 0 7 6 5 364s > stopifnot(identical(y1, y0)) 364s > randomSeed("reset") 364s > 364s > stopifnot(identical(RNGkind()[1L], okind)) 364s > 364s > message("*** randomSeed(): L'Ecuyer-CMRG stream ... done") 364s *** randomSeed(): L'Ecuyer-CMRG stream ... done 364s > 364s > 364s > ## Cleanup 364s > message("*** randomSeed() - cleanup ...") 364s *** randomSeed() - cleanup ... 364s > genv <- globalenv() 364s > RNGkind("Mersenne-Twister") 364s > if (exists(".Random.seed", envir=genv, inherits=FALSE)) 364s + rm(list=".Random.seed", envir=genv, inherits=FALSE) 364s > rm(list=ovars, envir=globalenv()) 364s > message("*** randomSeed() - cleanup ... done") 364s *** randomSeed() - cleanup ... done 364s > 364s > proc.time() 364s user system elapsed 364s 0.369 0.070 0.424 364s Test randomSeed passed 364s 0 364s Begin test segmentByCBS,bug67 365s + cat segmentByCBS,bug67.Rout 365s 365s R version 4.5.2 (2025-10-31) -- "[Not] Part in a Rumble" 365s Copyright (C) 2025 The R Foundation for Statistical Computing 365s Platform: aarch64-unknown-linux-gnu 365s 365s R is free software and comes with ABSOLUTELY NO WARRANTY. 365s You are welcome to redistribute it under certain conditions. 365s Type 'license()' or 'licence()' for distribution details. 365s 365s R is a collaborative project with many contributors. 365s Type 'contributors()' for more information and 365s 'citation()' on how to cite R or R packages in publications. 365s 365s Type 'demo()' for some demos, 'help()' for on-line help, or 365s 'help.start()' for an HTML browser interface to help. 365s Type 'q()' to quit R. 365s 365s [Previously saved workspace restored] 365s 365s > set.seed(0xBEEF) 365s > 365s > # Number of loci 365s > J <- 1000 365s > 365s > mu <- double(J) 365s > mu[200:300] <- mu[200:300] + 1 365s > mu[350:400] <- NA_real_ # centromere 365s > mu[650:800] <- mu[650:800] - 1 365s > eps <- rnorm(J, sd=1/2) 365s > y <- mu + eps 365s > x <- sort(runif(length(y), max=length(y))) * 1e5 365s > 365s > knownSegments <- data.frame( 365s + chromosome=c( 0, 0), 365s + start =x[c( 1, 401)], 365s + end =x[c(349, J)] 365s + ) 365s > 365s > fit2 <- PSCBS::segmentByCBS(y, x=x, knownSegments=knownSegments) 365s > 365s > proc.time() 365s user system elapsed 365s 0.671 0.059 0.714 365s + [ 0 != 0 ] 365s + echo Test segmentByCBS,bug67 passed 365s + echo 0 365s + echo Begin test segmentByCBS,calls 365s + exitcode=0 365s + R CMD BATCH segmentByCBS,calls.R 365s Test segmentByCBS,bug67 passed 365s 0 365s Begin test segmentByCBS,calls 365s + cat segmentByCBS,calls.Rout 365s 365s R version 4.5.2 (2025-10-31) -- "[Not] Part in a Rumble" 365s Copyright (C) 2025 The R Foundation for Statistical Computing 365s Platform: aarch64-unknown-linux-gnu 365s 365s R is free software and comes with ABSOLUTELY NO WARRANTY. 365s You are welcome to redistribute it under certain conditions. 365s Type 'license()' or 'licence()' for distribution details. 365s 365s R is a collaborative project with many contributors. 365s Type 'contributors()' for more information and 365s 'citation()' on how to cite R or R packages in publications. 365s 365s Type 'demo()' for some demos, 'help()' for on-line help, or 365s 'help.start()' for an HTML browser interface to help. 365s Type 'q()' to quit R. 365s 365s [Previously saved workspace restored] 365s 365s > # This test script calls a report generator which requires 365s > # the 'ggplot2' package, which in turn will require packages 365s > # 'colorspace', 'dichromat', 'munsell', 'reshape2' and 'scales'. 365s > 365s > # Only run this test in full testing mode 365s > if (Sys.getenv("_R_CHECK_FULL_") != "") { 365s + library("PSCBS") 365s + stext <- R.utils::stext 365s + 365s + # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 365s + # Load SNP microarray data 365s + # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 365s + data <- PSCBS::exampleData("paired.chr01") 365s + str(data) 365s + 365s + data <- data.frame(chromosome=data$chromosome, x=data$x, y=data$CT) 365s + 365s + 365s + # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 365s + # CBS segmentation 365s + # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 365s + # Drop single-locus outliers 365s + dataS <- dropSegmentationOutliers(data) 365s + 365s + # Speed up example by segmenting fewer loci 365s + dataS <- dataS[seq(from=1, to=nrow(data), by=5),] 365s + 365s + str(dataS) 365s + 365s + gaps <- findLargeGaps(dataS, minLength=2e6) 365s + knownSegments <- gapsToSegments(gaps) 365s + 365s + # CBS segmentation 365s + fit <- segmentByCBS(dataS, knownSegments=knownSegments, 365s + seed=0xBEEF, verbose=-10) 365s + signalType(fit) <- "ratio" 365s + plotTracks(fit) 365s + 365s + 365s + # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 365s + # Call using the UCSF MAD caller (not recommended) 365s + # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 365s + fitC <- callGainsAndLosses(fit) 365s + plotTracks(fitC) 365s + pars <- fitC$params$callGainsAndLosses 365s + stext(side=3, pos=1/2, line=-1, substitute(sigma==x, list(x=sprintf("%.2f", pars$sigmaMAD)))) 365s + mu <- pars$muR 365s + tau <- unlist(pars[c("tauLoss", "tauGain")], use.names=FALSE) 365s + abline(h=mu, lty=2, lwd=2) 365s + abline(h=tau, lwd=2) 365s + mtext(side=4, at=tau[1], expression(Delta[LOSS]), adj=-0.2, cex=0.7, las=2, xpd=TRUE) 365s + mtext(side=4, at=tau[2], expression(Delta[GAIN]), adj=-0.2, cex=0.7, las=2, xpd=TRUE) 365s + title(main="CN caller: \"ucsf-mad\"") 365s + 365s + 365s + # Caller to be implemented 365s + deltaCN <- estimateDeltaCN(fit) 365s + tau <- mu + 1/2*c(-1,+1)*deltaCN 365s + abline(h=tau, lty=2, lwd=1, col="red") 365s + 365s + 365s + 365s + } # if (Sys.getenv("_R_CHECK_FULL_")) 365s > 365s > proc.time() 365s user system elapsed 365s 0.141 0.034 0.158 365s Test segmentByCBS,calls passed 365s 0 365s Begin test segmentByCBS,futures 365s + [ 0 != 0 ] 365s + echo Test segmentByCBS,calls passed 365s + echo 0 365s + echo Begin test segmentByCBS,futures 365s + exitcode=0 365s + R CMD BATCH segmentByCBS,futures.R 370s + cat segmentByCBS,futures.Rout 370s 370s R version 4.5.2 (2025-10-31) -- "[Not] Part in a Rumble" 370s Copyright (C) 2025 The R Foundation for Statistical Computing 370s Platform: aarch64-unknown-linux-gnu 370s 370s R is free software and comes with ABSOLUTELY NO WARRANTY. 370s You are welcome to redistribute it under certain conditions. 370s Type 'license()' or 'licence()' for distribution details. 370s 370s R is a collaborative project with many contributors. 370s Type 'contributors()' for more information and 370s 'citation()' on how to cite R or R packages in publications. 370s 370s Type 'demo()' for some demos, 'help()' for on-line help, or 370s 'help.start()' for an HTML browser interface to help. 370s Type 'q()' to quit R. 370s 370s [Previously saved workspace restored] 370s 370s > library("PSCBS") 370s PSCBS v0.68.0 (2025-04-18 19:40:02 UTC) successfully loaded. See ?PSCBS for help. 370s > 370s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 370s > # Simulating copy-number data 370s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 370s > set.seed(0xBEEF) 370s > 370s > # Number of loci 370s > J <- 1000 370s > 370s > mu <- double(J) 370s > mu[200:300] <- mu[200:300] + 1 370s > mu[350:400] <- NA # centromere 370s > mu[650:800] <- mu[650:800] - 1 370s > eps <- rnorm(J, sd=1/2) 370s > y <- mu + eps 370s > x <- sort(runif(length(y), max=length(y))) * 1e5 370s > w <- runif(J) 370s > w[650:800] <- 0.001 370s > 370s > ## Create multiple chromosomes 370s > data <- knownSegments <- list() 370s > for (cc in 1:3) { 370s + data[[cc]] <- data.frame(chromosome=cc, y=y, x=x) 370s + knownSegments[[cc]] <- data.frame( 370s + chromosome=c( cc, cc, cc), 370s + start =x[c( 1, 350, 401)], 370s + end =x[c(349, 400, J)] 370s + ) 370s + } 370s > data <- Reduce(rbind, data) 370s > str(data) 370s 'data.frame': 3000 obs. of 3 variables: 370s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 370s $ y : num 0.295 0.115 -0.194 -0.392 -0.518 ... 370s $ x : num 55168 593204 605649 630624 746896 ... 370s > knownSegments <- Reduce(rbind, knownSegments) 370s > str(knownSegments) 370s 'data.frame': 9 obs. of 3 variables: 370s $ chromosome: int 1 1 1 2 2 2 3 3 3 370s $ start : num 55168 34194740 41080533 55168 34194740 ... 370s $ end : num 34142178 41044125 99910827 34142178 41044125 ... 370s > 370s > message("*** segmentByCBS() via futures ...") 370s *** segmentByCBS() via futures ... 370s > 370s > 370s > message("*** segmentByCBS() via futures with 'future' attached ...") 370s *** segmentByCBS() via futures with 'future' attached ... 370s > library("future") 370s > oplan <- plan() 370s > 370s > strategies <- c("sequential", "multisession") 370s > 370s > ## Test 'future.batchtools' futures? 370s > pkg <- "future.batchtools" 370s > if (require(pkg, character.only=TRUE)) { 370s + strategies <- c(strategies, "batchtools_local") 370s + } 370s Loading required package: future.batchtools 370s Warning message: 370s In library(package, lib.loc = lib.loc, character.only = TRUE, logical.return = TRUE, : 370s there is no package called 'future.batchtools' 370s > 370s > message("Future strategies to test: ", paste(sQuote(strategies), collapse=", ")) 370s Future strategies to test: 'sequential', 'multisession' 370s > 370s > fits <- list() 370s > for (strategy in strategies) { 370s + message(sprintf("- segmentByCBS() using '%s' futures ...", strategy)) 370s + plan(strategy) 370s + fit <- segmentByCBS(data, seed=0xBEEF, verbose=TRUE) 370s + fits[[strategy]] <- fit 370s + stopifnot(all.equal(fit, fits[[1]])) 370s + } 370s - segmentByCBS() using 'sequential' futures ... 370s Segmenting by CBS... 370s Segmenting multiple chromosomes... 370s Number of chromosomes: 3 370s Random seed temporarily set (seed=c(48879), kind="L'Ecuyer-CMRG") 370s Produced 3 seeds from this stream for future usage 370s Chromosome #1 ('Chr01') of 3... 370s Segmenting by CBS... 370s Chromosome: 1 370s Random seed temporarily set (seed=c(10407, 1066287653, -51199871, 161854402, -1995183193, 1503453565, -747102133), kind="L'Ecuyer-CMRG") 370s Segmenting by CBS...done 370s Chromosome #1 ('Chr01') of 3...done 370s Chromosome #2 ('Chr02') of 3... 370s Segmenting by CBS... 370s Chromosome: 2 370s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 370s Segmenting by CBS...done 370s Chromosome #2 ('Chr02') of 3...done 370s Chromosome #3 ('Chr03') of 3... 370s Segmenting by CBS... 370s Chromosome: 3 370s Random seed temporarily set (seed=c(10407, -821273412, -52578226, 1415511586, 721384351, -665928286, 1316562960), kind="L'Ecuyer-CMRG") 370s Segmenting by CBS...done 370s Chromosome #3 ('Chr03') of 3...done 370s Segmenting multiple chromosomes...done 370s Segmenting by CBS...done 370s list() 370s - segmentByCBS() using 'multisession' futures ... 370s Segmenting by CBS... 370s Segmenting multiple chromosomes... 370s Number of chromosomes: 3 370s Random seed temporarily set (seed=c(48879), kind="L'Ecuyer-CMRG") 370s Produced 3 seeds from this stream for future usage 370s Chromosome #1 ('Chr01') of 3... 370s Chromosome #1 ('Chr01') of 3...done 370s Chromosome #2 ('Chr02') of 3... 370s Random seed temporarily set (seed=c(10407, 1066287653, -51199871, 161854402, -1995183193, 1503453565, -747102133), kind="L'Ecuyer-CMRG") 370s Segmenting by CBS...done 370s Chromosome #2 ('Chr02') of 3...done 370s Chromosome #3 ('Chr03') of 3... 370s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 370s Segmenting by CBS...done 370s Chromosome #3 ('Chr03') of 3...done 370s Segmenting by CBS... 370s Chromosome: 3 370s Random seed temporarily set (seed=c(10407, -821273412, -52578226, 1415511586, 721384351, -665928286, 1316562960), kind="L'Ecuyer-CMRG") 370s Segmenting by CBS...done 370s Segmenting multiple chromosomes...done 370s Segmenting by CBS...done 370s list() 370s > 370s > 370s > message("*** segmentByCBS() via futures with known segments ...") 370s *** segmentByCBS() via futures with known segments ... 370s > fits <- list() 370s > dataT <- subset(data, chromosome == 1) 370s > for (strategy in strategies) { 370s + message(sprintf("- segmentByCBS() w/ known segments using '%s' futures ...", strategy)) 370s + plan(strategy) 370s + fit <- segmentByCBS(dataT, knownSegments=knownSegments, seed=0xBEEF, verbose=TRUE) 370s + fits[[strategy]] <- fit 370s + stopifnot(all.equal(fit, fits[[1]])) 370s + } 370s - segmentByCBS() w/ known segments using 'sequential' futures ... 370s Segmenting by CBS... 370s Chromosome: 1 370s Random seed temporarily set (seed=c(48879), kind="L'Ecuyer-CMRG") 370s Produced 3 seeds from this stream for future usage 370s Segmenting by CBS...done 370s list() 370s - segmentByCBS() w/ known segments using 'multisession' futures ... 370s Segmenting by CBS... 370s Chromosome: 1 370s Random seed temporarily set (seed=c(48879), kind="L'Ecuyer-CMRG") 370s Produced 3 seeds from this stream for future usage 370s Segmenting by CBS...done 370s list() 370s > 370s > message("*** segmentByCBS() via futures ... DONE") 370s *** segmentByCBS() via futures ... DONE 370s > 370s > 370s > ## Cleanup 370s > plan(oplan) 370s > rm(list=c("fits", "dataT", "data", "fit")) 370s > 370s > 370s > proc.time() 370s user system elapsed 370s 2.034 0.198 4.898 370s Test segmentByCBS,futures passed 370s 0 370s Begin test segmentByCBS,median 370s + [ 0 != 0 ] 370s + echo Test segmentByCBS,futures passed 370s + echo 0 370s + echo Begin test segmentByCBS,median 370s + exitcode=0 370s + R CMD BATCH segmentByCBS,median.R 372s + cat segmentByCBS,median.Rout 372s 372s R version 4.5.2 (2025-10-31) -- "[Not] Part in a Rumble" 372s Copyright (C) 2025 The R Foundation for Statistical Computing 372s Platform: aarch64-unknown-linux-gnu 372s 372s R is free software and comes with ABSOLUTELY NO WARRANTY. 372s You are welcome to redistribute it under certain conditions. 372s Type 'license()' or 'licence()' for distribution details. 372s 372s R is a collaborative project with many contributors. 372s Type 'contributors()' for more information and 372s 'citation()' on how to cite R or R packages in publications. 372s 372s Type 'demo()' for some demos, 'help()' for on-line help, or 372s 'help.start()' for an HTML browser interface to help. 372s Type 'q()' to quit R. 372s 372s [Previously saved workspace restored] 372s 372s > library("PSCBS") 372s PSCBS v0.68.0 (2025-04-18 19:40:02 UTC) successfully loaded. See ?PSCBS for help. 372s > 372s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 372s > # Simulating copy-number data 372s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 372s > set.seed(0xBEEF) 372s > 372s > # Number of loci 372s > J <- 1000 372s > 372s > x <- sort(runif(J, max=J)) * 1e5 372s > 372s > mu <- double(J) 372s > mu[200:300] <- mu[200:300] + 1 372s > mu[350:400] <- NA # centromere 372s > mu[650:800] <- mu[650:800] - 1 372s > eps <- rnorm(J, sd=1/2) 372s > y <- mu + eps 372s > 372s > outliers <- seq(from=1L, to=J, length.out=0.2*J) 372s > y[outliers] <- y[outliers] + 1.5 372s > 372s > w <- rep(1.0, times=J) 372s > w[outliers] <- 0.01 372s > 372s > data <- data.frame(chromosome=1L, x=x, y=y) 372s > dataW <- cbind(data, w=w) 372s > 372s > 372s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 372s > # Single-chromosome segmentation 372s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 372s > par(mar=c(2,3,0.2,1)+0.1) 372s > # Segment without weights 372s > fit <- segmentByCBS(data) 372s > sampleName(fit) <- "CBS_Example" 372s > print(fit) 372s sampleName chromosome start end nbrOfLoci mean 372s 1 CBS_Example 1 6.066868e+02 19076007 199 0.2622 372s 2 CBS_Example 1 1.907601e+07 29630949 99 1.4289 372s 3 CBS_Example 1 2.963095e+07 63224332 299 0.2854 372s 4 CBS_Example 1 6.322433e+07 78801707 153 -0.7408 372s 5 CBS_Example 1 7.880171e+07 99917418 199 0.3541 372s > plotTracks(fit) 372s Warning message: 372s In plotTracks.CBS(fit) : 372s Setting default 'Clim' assuming the signal type is 'ratio' because signalType(fit) is unknown ('NA'). Use signalType(fit) <- 'ratio' to avoid this warning. 372s > ## Highlight outliers (they pull up the mean levels) 372s > points(x[outliers]/1e6, y[outliers], col="purple") 372s > 372s > # Segment without weights but with median 372s > fitM <- segmentByCBS(data, avg="median") 372s > sampleName(fitM) <- "CBS_Example (median)" 372s > print(fitM) 372s sampleName chromosome start end nbrOfLoci mean 372s 1 CBS_Example (median) 1 6.066868e+02 19076007 199 0.1005418 372s 2 CBS_Example (median) 1 1.907601e+07 29630949 99 1.2720955 372s 3 CBS_Example (median) 1 2.963095e+07 63224332 299 0.1337148 372s 4 CBS_Example (median) 1 6.322433e+07 78801707 153 -0.8655254 372s 5 CBS_Example (median) 1 7.880171e+07 99917418 199 0.1718179 372s > drawLevels(fitM, col="magenta", lty=3) 372s NULL 372s > 372s > # Segment with weights 372s > fitW <- segmentByCBS(dataW, avg="median") 372s > sampleName(fitW) <- "CBS_Example (weighted)" 372s > print(fitW) 372s sampleName chromosome start end nbrOfLoci mean 372s 1 CBS_Example (weighted) 1 6.066868e+02 19076007 199 -0.08745973 372s 2 CBS_Example (weighted) 1 1.907601e+07 30126128 101 1.12968951 372s 3 CBS_Example (weighted) 1 3.012613e+07 63224332 297 -0.06074638 372s 4 CBS_Example (weighted) 1 6.322433e+07 78801707 153 -1.06373835 372s 5 CBS_Example (weighted) 1 7.880171e+07 99917418 199 0.04204744 372s > drawLevels(fitW, col="red") 372s NULL 372s > 372s > # Segment with weights and median 372s > fitWM <- segmentByCBS(dataW, avg="median") 372s > sampleName(fitWM) <- "CBS_Example (weighted median)" 372s > print(fitWM) 372s sampleName chromosome start end nbrOfLoci 372s 1 CBS_Example (weighted median) 1 6.066868e+02 19076007 199 372s 2 CBS_Example (weighted median) 1 1.907601e+07 30126128 101 372s 3 CBS_Example (weighted median) 1 3.012613e+07 63224332 297 372s 4 CBS_Example (weighted median) 1 6.322433e+07 78801707 153 372s 5 CBS_Example (weighted median) 1 7.880171e+07 99917418 199 372s mean 372s 1 -0.08745973 372s 2 1.12968951 372s 3 -0.06074638 372s 4 -1.06373835 372s 5 0.04204744 372s > drawLevels(fitWM, col="orange", lty=3) 372s NULL 372s > 372s > 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)) 372s > 372s > ## Assert that weighted segment means are less biased 372s > dmean <- getSegments(fit)$mean - getSegments(fitW)$mean 372s > cat("Segment mean differences:\n") 372s Segment mean differences: 372s > print(dmean) 372s [1] 0.3496597 0.2992105 0.3461464 0.3229384 0.3120526 372s > stopifnot(all(dmean > 0, na.rm=TRUE)) 372s > 372s > dmean <- getSegments(fitM)$mean - getSegments(fitWM)$mean 372s > cat("Segment median differences:\n") 372s Segment median differences: 372s > print(dmean) 372s [1] 0.1880015 0.1424060 0.1944611 0.1982130 0.1297704 372s > stopifnot(all(dmean > 0, na.rm=TRUE)) 372s > 372s > 372s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 372s > # Multi-chromosome segmentation 372s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 372s > data2 <- data 372s > data2$chromosome <- 2L 372s > data <- rbind(data, data2) 372s > dataW <- cbind(data, w=w) 372s > 372s > par(mar=c(2,3,0.2,1)+0.1) 372s > # Segment without weights 372s > fit <- segmentByCBS(data) 372s > sampleName(fit) <- "CBS_Example" 372s > print(fit) 372s sampleName chromosome start end nbrOfLoci mean 372s 1 CBS_Example 1 6.066868e+02 19076007 199 0.2622 372s 2 CBS_Example 1 1.907601e+07 29630949 99 1.4289 372s 3 CBS_Example 1 2.963095e+07 63224332 299 0.2854 372s 4 CBS_Example 1 6.322433e+07 78801707 153 -0.7408 372s 5 CBS_Example 1 7.880171e+07 99917418 199 0.3541 372s 6 NA NA NA NA NA 372s 7 CBS_Example 2 6.066868e+02 19076007 199 0.2622 372s 8 CBS_Example 2 1.907601e+07 29630949 99 1.4289 372s 9 CBS_Example 2 2.963095e+07 63224332 299 0.2854 372s 10 CBS_Example 2 6.322433e+07 78801707 153 -0.7408 372s 11 CBS_Example 2 7.880171e+07 99917418 199 0.3541 372s > plotTracks(fit, Clim=c(-3,3)) 372s > 372s > # Segment without weights but with median 372s > fitM <- segmentByCBS(data, avg="median") 372s > sampleName(fitM) <- "CBS_Example (median)" 372s > print(fitM) 372s sampleName chromosome start end nbrOfLoci mean 372s 1 CBS_Example (median) 1 6.066868e+02 19076007 199 0.1005418 372s 2 CBS_Example (median) 1 1.907601e+07 29630949 99 1.2720955 372s 3 CBS_Example (median) 1 2.963095e+07 63224332 299 0.1337148 372s 4 CBS_Example (median) 1 6.322433e+07 78801707 153 -0.8655254 372s 5 CBS_Example (median) 1 7.880171e+07 99917418 199 0.1718179 372s 6 NA NA NA NA NA 372s 7 CBS_Example (median) 2 6.066868e+02 19076007 199 0.1005418 372s 8 CBS_Example (median) 2 1.907601e+07 29630949 99 1.2720955 372s 9 CBS_Example (median) 2 2.963095e+07 63224332 299 0.1337148 372s 10 CBS_Example (median) 2 6.322433e+07 78801707 153 -0.8655254 372s 11 CBS_Example (median) 2 7.880171e+07 99917418 199 0.1718179 372s > drawLevels(fitM, col="magenta", lty=3) 372s NULL 372s > 372s > # Segment with weights 372s > fitW <- segmentByCBS(dataW, avg="median") 372s > sampleName(fitW) <- "CBS_Example (weighted)" 372s > print(fitW) 372s sampleName chromosome start end nbrOfLoci 372s 1 CBS_Example (weighted) 1 6.066868e+02 19076007 199 372s 2 CBS_Example (weighted) 1 1.907601e+07 30126128 101 372s 3 CBS_Example (weighted) 1 3.012613e+07 63224332 297 372s 4 CBS_Example (weighted) 1 6.322433e+07 78801707 153 372s 5 CBS_Example (weighted) 1 7.880171e+07 99917418 199 372s 6 NA NA NA NA 372s 7 CBS_Example (weighted) 2 6.066868e+02 19076007 199 372s 8 CBS_Example (weighted) 2 1.907601e+07 30126128 101 372s 9 CBS_Example (weighted) 2 3.012613e+07 63224332 297 372s 10 CBS_Example (weighted) 2 6.322433e+07 78801707 153 372s 11 CBS_Example (weighted) 2 7.880171e+07 99917418 199 372s mean 372s 1 -0.08745973 372s 2 1.12968951 372s 3 -0.06074638 372s 4 -1.06373835 372s 5 0.04204744 372s 6 NA 372s 7 -0.08745973 372s 8 1.12968951 372s 9 -0.06074638 372s 10 -1.06373835 372s 11 0.04204744 372s > drawLevels(fitW, col="red") 372s NULL 372s > 372s > # Segment with weights and median 372s > fitWM <- segmentByCBS(dataW, avg="median") 372s > sampleName(fitWM) <- "CBS_Example (weighted median)" 372s > print(fitWM) 372s sampleName chromosome start end nbrOfLoci 372s 1 CBS_Example (weighted median) 1 6.066868e+02 19076007 199 372s 2 CBS_Example (weighted median) 1 1.907601e+07 30126128 101 372s 3 CBS_Example (weighted median) 1 3.012613e+07 63224332 297 372s 4 CBS_Example (weighted median) 1 6.322433e+07 78801707 153 372s 5 CBS_Example (weighted median) 1 7.880171e+07 99917418 199 372s 6 NA NA NA NA 372s 7 CBS_Example (weighted median) 2 6.066868e+02 19076007 199 372s 8 CBS_Example (weighted median) 2 1.907601e+07 30126128 101 372s 9 CBS_Example (weighted median) 2 3.012613e+07 63224332 297 372s 10 CBS_Example (weighted median) 2 6.322433e+07 78801707 153 372s 11 CBS_Example (weighted median) 2 7.880171e+07 99917418 199 372s mean 372s 1 -0.08745973 372s 2 1.12968951 372s 3 -0.06074638 372s 4 -1.06373835 372s 5 0.04204744 372s 6 NA 372s 7 -0.08745973 372s 8 1.12968951 372s 9 -0.06074638 372s 10 -1.06373835 372s 11 0.04204744 372s > drawLevels(fitWM, col="orange", lty=3) 372s NULL 372s > 372s > 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)) 372s > 372s > ## Assert that weighted segment means are less biased 372s > dmean <- getSegments(fit)$mean - getSegments(fitW)$mean 372s > cat("Segment mean differences:\n") 372s Segment mean differences: 372s > print(dmean) 372s [1] 0.3496597 0.2992105 0.3461464 0.3229384 0.3120526 NA 0.3496597 372s [8] 0.2992105 0.3461464 0.3229384 0.3120526 372s > stopifnot(all(dmean > 0, na.rm=TRUE)) 372s > 372s > dmean <- getSegments(fitM)$mean - getSegments(fitWM)$mean 372s > cat("Segment median differences:\n") 372s Segment median differences: 372s > print(dmean) 372s [1] 0.1880015 0.1424060 0.1944611 0.1982130 0.1297704 NA 0.1880015 372s [8] 0.1424060 0.1944611 0.1982130 0.1297704 372s > stopifnot(all(dmean > 0, na.rm=TRUE)) 372s > 372s > proc.time() 372s user system elapsed 372s 1.452 0.064 1.501 372s Test segmentByCBS,median passed 372s 0 372s Begin test segmentByCBS,prune 372s + [ 0 != 0 ] 372s + echo Test segmentByCBS,median passed 372s + echo 0 372s + echo Begin test segmentByCBS,prune 372s + exitcode=0 372s + R CMD BATCH segmentByCBS,prune.R 373s + cat segmentByCBS,prune.Rout 373s 373s R version 4.5.2 (2025-10-31) -- "[Not] Part in a Rumble" 373s Copyright (C) 2025 The R Foundation for Statistical Computing 373s Platform: aarch64-unknown-linux-gnu 373s 373s R is free software and comes with ABSOLUTELY NO WARRANTY. 373s You are welcome to redistribute it under certain conditions. 373s Type 'license()' or 'licence()' for distribution details. 373s 373s R is a collaborative project with many contributors. 373s Type 'contributors()' for more information and 373s 'citation()' on how to cite R or R packages in publications. 373s 373s Type 'demo()' for some demos, 'help()' for on-line help, or 373s 'help.start()' for an HTML browser interface to help. 373s Type 'q()' to quit R. 373s 373s [Previously saved workspace restored] 373s 373s > library("PSCBS") 373s PSCBS v0.68.0 (2025-04-18 19:40:02 UTC) successfully loaded. See ?PSCBS for help. 373s > 373s > ## Compare segments 373s > assertMatchingSegments <- function(fitM, fit) { 373s + chrs <- getChromosomes(fitM) 373s + segsM <- lapply(chrs, FUN=function(chr) { 373s + getSegments(extractChromosome(fitM, chr)) 373s + }) 373s + segs <- lapply(fit[chrs], FUN=getSegments) 373s + stopifnot(all.equal(segsM, segs, check.attributes=FALSE)) 373s + } 373s > 373s > ## Simulate data 373s > set.seed(0xBEEF) 373s > J <- 1000 373s > mu <- double(J) 373s > mu[200:300] <- mu[200:300] + 1 373s > mu[350:400] <- NA 373s > mu[650:800] <- mu[650:800] - 1 373s > eps <- rnorm(J, sd=1/2) 373s > y <- mu + eps 373s > x <- sort(runif(length(y), max=length(y))) * 1e5 373s > 373s > data <- list() 373s > for (chr in 1:2) { 373s + data[[chr]] <- data.frame(chromosome=chr, x=x, y=y) 373s + } 373s > data$M <- Reduce(rbind, data) 373s > 373s > ## Segment 373s > message("*** segmentByCBS()") 373s *** segmentByCBS() 373s > fit <- lapply(data, FUN=segmentByCBS) 373s > print(fit) 373s [[1]] 373s sampleName chromosome start end nbrOfLoci mean 373s 1 1 65285.65 19648927 200 0.0109 373s 2 1 19648927.46 28239656 95 0.9529 373s 3 1 28239655.99 65697742 302 -0.0126 373s 4 1 65697742.20 79729368 153 -0.9534 373s 5 1 79729368.34 99819310 199 -0.0497 373s 373s [[2]] 373s sampleName chromosome start end nbrOfLoci mean 373s 1 2 65285.65 19648927 200 0.0109 373s 2 2 19648927.46 28239656 95 0.9529 373s 3 2 28239655.99 65697742 302 -0.0126 373s 4 2 65697742.20 79729368 153 -0.9534 373s 5 2 79729368.34 99819310 199 -0.0497 373s 373s $M 373s sampleName chromosome start end nbrOfLoci mean 373s 1 1 65285.65 19648927 200 0.0109 373s 2 1 19648927.46 28239656 95 0.9529 373s 3 1 28239655.99 65697742 302 -0.0126 373s 4 1 65697742.20 79729368 153 -0.9534 373s 5 1 79729368.34 99819310 199 -0.0497 373s 6 NA NA NA NA NA 373s 7 2 65285.65 19648927 200 0.0109 373s 8 2 19648927.46 28239656 95 0.9529 373s 9 2 28239655.99 65697742 302 -0.0126 373s 10 2 65697742.20 79729368 153 -0.9534 373s 11 2 79729368.34 99819310 199 -0.0497 373s 373s > assertMatchingSegments(fit$M, fit) 373s > 373s > ## Join segments 373s > message("*** joinSegments()") 373s *** joinSegments() 373s > fitj <- lapply(fit, FUN=joinSegments) 373s > print(fitj) 373s [[1]] 373s sampleName chromosome start end nbrOfLoci mean 373s 1 1 65285.65 19648927 200 0.0109 373s 2 1 19648927.46 28239656 95 0.9529 373s 3 1 28239655.99 65697742 302 -0.0126 373s 4 1 65697742.20 79729368 153 -0.9534 373s 5 1 79729368.34 99819310 199 -0.0497 373s 373s [[2]] 373s sampleName chromosome start end nbrOfLoci mean 373s 1 2 65285.65 19648927 200 0.0109 373s 2 2 19648927.46 28239656 95 0.9529 373s 3 2 28239655.99 65697742 302 -0.0126 373s 4 2 65697742.20 79729368 153 -0.9534 373s 5 2 79729368.34 99819310 199 -0.0497 373s 373s $M 373s sampleName chromosome start end nbrOfLoci mean 373s 1 1 65285.65 19648927 200 0.0109 373s 2 1 19648927.46 28239656 95 0.9529 373s 3 1 28239655.99 65697742 302 -0.0126 373s 4 1 65697742.20 79729368 153 -0.9534 373s 5 1 79729368.34 99819310 199 -0.0497 373s 6 NA NA NA NA NA 373s 7 2 65285.65 19648927 200 0.0109 373s 8 2 19648927.46 28239656 95 0.9529 373s 9 2 28239655.99 65697742 302 -0.0126 373s 10 2 65697742.20 79729368 153 -0.9534 373s 11 2 79729368.34 99819310 199 -0.0497 373s 373s > assertMatchingSegments(fitj$M, fitj) 373s > 373s > ## Reset segments 373s > message("*** resetSegments()") 373s *** resetSegments() 373s > fitj <- lapply(fit, FUN=resetSegments) 373s > print(fitj) 373s [[1]] 373s sampleName chromosome start end nbrOfLoci mean 373s 1 1 65285.65 19648927 200 0.0109 373s 2 1 19648927.46 28239656 95 0.9529 373s 3 1 28239655.99 65697742 302 -0.0126 373s 4 1 65697742.20 79729368 153 -0.9534 373s 5 1 79729368.34 99819310 199 -0.0497 373s 373s [[2]] 373s sampleName chromosome start end nbrOfLoci mean 373s 1 2 65285.65 19648927 200 0.0109 373s 2 2 19648927.46 28239656 95 0.9529 373s 3 2 28239655.99 65697742 302 -0.0126 373s 4 2 65697742.20 79729368 153 -0.9534 373s 5 2 79729368.34 99819310 199 -0.0497 373s 373s $M 373s sampleName chromosome start end nbrOfLoci mean 373s 1 1 65285.65 19648927 200 0.0109 373s 2 1 19648927.46 28239656 95 0.9529 373s 3 1 28239655.99 65697742 302 -0.0126 373s 4 1 65697742.20 79729368 153 -0.9534 373s 5 1 79729368.34 99819310 199 -0.0497 373s 6 NA NA NA NA NA 373s 7 2 65285.65 19648927 200 0.0109 373s 8 2 19648927.46 28239656 95 0.9529 373s 9 2 28239655.99 65697742 302 -0.0126 373s 10 2 65697742.20 79729368 153 -0.9534 373s 11 2 79729368.34 99819310 199 -0.0497 373s 373s > assertMatchingSegments(fitj$M, fitj) 373s > 373s > ## Prune by SD undo 373s > message("*** pruneBySdUndo()") 373s *** pruneBySdUndo() 373s > fitp <- lapply(fit, FUN=pruneBySdUndo) 373s > print(fitp) 373s [[1]] 373s sampleName chromosome start end nbrOfLoci mean 373s 1 1 65285.65 99819310 949 -0.07045097 373s 373s [[2]] 373s sampleName chromosome start end nbrOfLoci mean 373s 1 2 65285.65 99819310 949 -0.07045097 373s 373s $M 373s sampleName chromosome start end nbrOfLoci mean 373s 1 1 65285.65 99819310 949 -0.07045097 373s 2 NA NA NA NA NA 373s 3 2 65285.65 99819310 949 -0.07045097 373s 373s > assertMatchingSegments(fitp$M, fitp) 373s > 373s > ## Prune by hierarchical clustering 373s > message("*** pruneByHClust()") 373s *** pruneByHClust() 373s > fitp <- lapply(fit, FUN=pruneByHClust, k=1L) 373s > print(fitp) 373s [[1]] 373s sampleName chromosome start end nbrOfLoci mean 373s 1 1 65285.65 99819310 949 -0.07045097 373s 373s [[2]] 373s sampleName chromosome start end nbrOfLoci mean 373s 1 2 65285.65 99819310 949 -0.07045097 373s 373s $M 373s sampleName chromosome start end nbrOfLoci mean 373s 1 1 65285.65 99819310 949 -0.07045097 373s 6 NA NA NA NA NA 373s 7 2 65285.65 99819310 949 -0.07045097 373s 373s > assertMatchingSegments(fitp$M, fitp) 373s > 373s > proc.time() 373s user system elapsed 373s 1.082 0.051 1.119 373s Test segmentByCBS,prune passed 373s 0 373s Begin test segmentByCBS,report 373s + [ 0 != 0 ] 373s + echo Test segmentByCBS,prune passed 373s + echo 0 373s + echo Begin test segmentByCBS,report 373s + exitcode=0 373s + R CMD BATCH segmentByCBS,report.R 373s + cat segmentByCBS,report.Rout 373s 373s R version 4.5.2 (2025-10-31) -- "[Not] Part in a Rumble" 373s Copyright (C) 2025 The R Foundation for Statistical Computing 373s Platform: aarch64-unknown-linux-gnu 373s 373s R is free software and comes with ABSOLUTELY NO WARRANTY. 373s You are welcome to redistribute it under certain conditions. 373s Type 'license()' or 'licence()' for distribution details. 373s 373s R is a collaborative project with many contributors. 373s Type 'contributors()' for more information and 373s 'citation()' on how to cite R or R packages in publications. 373s 373s Type 'demo()' for some demos, 'help()' for on-line help, or 373s 'help.start()' for an HTML browser interface to help. 373s Type 'q()' to quit R. 373s 373s [Previously saved workspace restored] 373s 373s > # This test script calls a report generator which requires 373s > # the 'ggplot2' package, which in turn will require packages 373s > # 'colorspace', 'dichromat', 'munsell', 'reshape2' and 'scales'. 373s > 373s > # Only run this test in full testing mode 373s > if (Sys.getenv("_R_CHECK_FULL_") != "") { 373s + library("PSCBS") 373s + 373s + # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 373s + # Load SNP microarray data 373s + # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 373s + data <- PSCBS::exampleData("paired.chr01") 373s + str(data) 373s + 373s + data <- data.frame(chromosome=data$chromosome, x=data$x, y=data$CT) 373s + 373s + 373s + # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 373s + # CBS segmentation 373s + # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 373s + # Drop single-locus outliers 373s + dataS <- dropSegmentationOutliers(data) 373s + 373s + # Speed up example by segmenting fewer loci 373s + dataS <- dataS[seq(from=1, to=nrow(data), by=5),] 373s + 373s + str(dataS) 373s + 373s + gaps <- findLargeGaps(dataS, minLength=2e6) 373s + knownSegments <- gapsToSegments(gaps) 373s + 373s + # CBS segmentation 373s + fit <- segmentByCBS(dataS, knownSegments=knownSegments, 373s + seed=0xBEEF, verbose=-10) 373s + signalType(fit) <- "ratio" 373s + 373s + # Fake a multi-chromosome segmentation 373s + fit1 <- fit 373s + fit2 <- renameChromosomes(fit, from=1, to=2) 373s + fit <- c(fit1, fit2) 373s + 373s + report(fit, sampleName="CBS", studyName="CBS-Ex", verbose=-10) 373s + 373s + } # if (Sys.getenv("_R_CHECK_FULL_")) 373s > 373s > proc.time() 373s user system elapsed 373s 0.207 0.040 0.232 373s + [ 0 != 0 ] 373s + echo Test segmentByCBS,report passed 373s + echo 0 373s + echo Begin test segmentByCBS,shiftTCN 373s + exitcode=0 373s + R CMD BATCH segmentByCBS,shiftTCN.R 373s Test segmentByCBS,report passed 373s 0 373s Begin test segmentByCBS,shiftTCN 382s 382s R version 4.5.2 (2025-10-31) -- "[Not] Part in a Rumble" 382s Copyright (C) 2025 The R Foundation for Statistical Computing 382s Platform: aarch64-unknown-linux-gnu 382s 382s R is free software and comes with ABSOLUTELY NO WARRANTY. 382s You are welcome to redistribute it under certain conditions. 382s Type 'license()' or 'licence()' for distribution details. 382s 382s R is a collaborative project with many contributors. 382s Type 'contributors()' for more information and 382s 'citation()' on how to cite R or R packages in publications. 382s 382s Type 'demo()' for some demos, 'help()' for on-line help, or 382s 'help.start()' for an HTML browser interface to help. 382s Type 'q()' to quit R. 382s 382s [Previously saved workspace restored] 382s 382s > library("PSCBS") 382s PSCBS v0.68.0 (2025-04-18 19:40:02 UTC) successfully loaded. See ?PSCBS for help. 382s > subplots <- R.utils::subplots 382s > 382s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 382s > # Simulating copy-number data 382s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 382s > set.seed(0xBEEF) 382s > 382s > # Number of loci 382s > J <- 1000 382s > 382s > mu <- double(J) 382s > eps <- rnorm(J, sd=1/2) 382s > y <- mu + eps 382s > x <- sort(runif(length(y), max=length(y))) 382s > 382s > idxs <- which(200 <= x & x < 300) 382s > y[idxs] <- y[idxs] + 1 382s > idxs <- which(350 <= x & x < 400) 382s > y[idxs] <- NA # centromere 382s > x[idxs] <- NA # centromere 382s > idxs <- which(650 <= x & x < 800) 382s > y[idxs] <- y[idxs] - 1 382s > x <- x*1e5 382s > 382s > keep <- is.finite(x) 382s > x <- x[keep] 382s > y <- y[keep] 382s > 382s > data <- list() 382s > for (chr in 1:2) { 382s + data[[chr]] <- data.frame(chromosome=chr, y=y, x=x) 382s + } 382s > data <- Reduce(rbind, data) 382s > 382s > 382s > subplots(7, ncol=1) 382s > par(mar=c(1.7,1,0.2,1)+0.1) 382s > 382s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 382s > # Segmentation 382s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 382s > fit <- segmentByCBS(data) 382s > print(fit) 382s sampleName chromosome start end nbrOfLoci mean 382s 1 1 65285.65 20169684 205 0.0124 382s 2 1 20169684.05 29980147 103 0.9477 382s 3 1 29980147.36 64779929 287 -0.0299 382s 4 1 64779929.38 80010171 163 -0.9676 382s 5 1 80010171.14 99819310 196 -0.0484 382s 6 NA NA NA NA NA 382s 7 2 65285.65 20169684 205 0.0124 382s 8 2 20169684.05 29980147 103 0.9477 382s 9 2 29980147.36 64779929 287 -0.0299 382s 10 2 64779929.38 80010171 163 -0.9676 382s 11 2 80010171.14 99819310 196 -0.0484 382s > 382s > Clim <- c(-3,3) + c(0,10) 382s > plotTracks(fit, Clim=Clim) 382s > 382s > 382s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 382s > # Shifting every other chromosome 382s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 382s > fitList <- list() 382s > chrs <- getChromosomes(fit) 382s > for (kk in seq_along(chrs)) { 382s + chr <- chrs[kk] 382s + fitKK <- extractChromosome(fit, chr) 382s + if (kk %% 2 == 0) { 382s + fitKK <- shiftTCN(fitKK, shift=+10) 382s + } 382s + fitList[[kk]] <- fitKK 382s + } # for (kk ...) 382s > fitT <- do.call(c, fitList) 382s > # Sanity check 382s > stopifnot(nbrOfSegments(fitT) == nbrOfSegments(fit)) 382s > 382s > plotTracks(fitT, Clim=Clim) 382s > 382s > 382s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 382s > # Shifting every other known segment 382s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 382s > gaps <- findLargeGaps(data, minLength=40e5) 382s > knownSegments <- gapsToSegments(gaps, dropGaps=TRUE) 382s > fit <- segmentByCBS(data, knownSegments=knownSegments) 382s > 382s > subplots(2, ncol=1) 382s > plotTracks(fit, Clim=Clim) 382s > abline(v=c(knownSegments$start, knownSegments$end)/1e6, lty=3) 382s > 382s > fitList <- list() 382s > for (kk in seq_len(nrow(knownSegments))) { 382s + seg <- knownSegments[kk,] 382s + start <- seg$start 382s + end <- seg$end 382s + fitKK <- extractChromosome(fit, seg$chromosome) 382s + segsKK <- getSegments(fitKK) 382s + idxStart <- min(which(segsKK$start >= start)) 382s + idxEnd <- max(which(segsKK$end <= end)) 382s + idxs <- idxStart:idxEnd 382s + fitKK <- extractSegments(fitKK, idxs) 382s + if (kk %% 2 == 0) { 382s + fitKK <- shiftTCN(fitKK, shift=+10) 382s + } 382s + fitList[[kk]] <- fitKK 382s + } # for (kk ...) 382s > fitT <- do.call(c, fitList) 382s > # Sanity check 382s > stopifnot(nbrOfSegments(fitT) == nbrOfSegments(fit)) 382s > 382s > plotTracks(fitT, Clim=Clim) 382s > abline(v=c(knownSegments$start, knownSegments$end)/1e6, lty=3) 382s > 382s > 382s > segList <- seqOfSegmentsByDP(fit) 382s > K <- length(segList) 382s > subplots(K, ncol=2, byrow=FALSE) 382s > par(mar=c(2,1,1,1)) 382s > for (kk in 1:K) { 382s + knownSegments <- segList[[kk]] 382s + fitKK <- resegment(fit, knownSegments=knownSegments, undo=+Inf) 382s + plotTracks(fitKK, Clim=c(-3,3)) 382s + } # for (kk ...) 382s > 382s > proc.time() 382s user system elapsed 382s 7.734 0.086 7.814 382s Test segmentByCBS,shiftTCN passed 382s 0 382s Begin test segmentByCBS,weights 382s + cat segmentByCBS,shiftTCN.Rout 382s + [ 0 != 0 ] 382s + echo Test segmentByCBS,shiftTCN passed 382s + echo 0 382s + echo Begin test segmentByCBS,weights 382s + exitcode=0 382s + R CMD BATCH segmentByCBS,weights.R 384s + cat segmentByCBS,weights.Rout 384s 384s R version 4.5.2 (2025-10-31) -- "[Not] Part in a Rumble" 384s Copyright (C) 2025 The R Foundation for Statistical Computing 384s Platform: aarch64-unknown-linux-gnu 384s 384s R is free software and comes with ABSOLUTELY NO WARRANTY. 384s You are welcome to redistribute it under certain conditions. 384s Type 'license()' or 'licence()' for distribution details. 384s 384s R is a collaborative project with many contributors. 384s Type 'contributors()' for more information and 384s 'citation()' on how to cite R or R packages in publications. 384s 384s Type 'demo()' for some demos, 'help()' for on-line help, or 384s 'help.start()' for an HTML browser interface to help. 384s Type 'q()' to quit R. 384s 384s [Previously saved workspace restored] 384s 384s > library("PSCBS") 384s PSCBS v0.68.0 (2025-04-18 19:40:02 UTC) successfully loaded. See ?PSCBS for help. 384s > 384s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 384s > # Simulating copy-number data 384s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 384s > set.seed(0xBEEF) 384s > 384s > # Number of loci 384s > J <- 1000 384s > 384s > x <- sort(runif(J, max=J)) * 1e5 384s > 384s > mu <- double(J) 384s > mu[200:300] <- mu[200:300] + 1 384s > mu[350:400] <- NA # centromere 384s > mu[650:800] <- mu[650:800] - 1 384s > eps <- rnorm(J, sd=1/2) 384s > y <- mu + eps 384s > 384s > outliers <- seq(from=1L, to=J, length.out=0.2*J) 384s > y[outliers] <- y[outliers] + 1.5 384s > 384s > w <- rep(1.0, times=J) 384s > w[outliers] <- 0.01 384s > 384s > data <- data.frame(chromosome=1L, x=x, y=y) 384s > dataW <- cbind(data, w=w) 384s > 384s > 384s > par(mar=c(2,3,0.2,1)+0.1) 384s > 384s > 384s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 384s > # Single-chromosome segmentation 384s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 384s > # Segment without weights 384s > fit <- segmentByCBS(data) 384s > sampleName(fit) <- "CBS_Example" 384s > print(fit) 384s sampleName chromosome start end nbrOfLoci mean 384s 1 CBS_Example 1 6.066868e+02 19076007 199 0.2622 384s 2 CBS_Example 1 1.907601e+07 29630949 99 1.4289 384s 3 CBS_Example 1 2.963095e+07 63224332 299 0.2854 384s 4 CBS_Example 1 6.322433e+07 78801707 153 -0.7408 384s 5 CBS_Example 1 7.880171e+07 99917418 199 0.3541 384s > plotTracks(fit) 384s Warning message: 384s In plotTracks.CBS(fit) : 384s Setting default 'Clim' assuming the signal type is 'ratio' because signalType(fit) is unknown ('NA'). Use signalType(fit) <- 'ratio' to avoid this warning. 384s > ## Highlight outliers (they pull up the mean levels) 384s > points(x[outliers]/1e6, y[outliers], col="purple") 384s > 384s > # Segment with weights 384s > fitW <- segmentByCBS(dataW) 384s > sampleName(fitW) <- "CBS_Example (weighted)" 384s > print(fitW) 384s sampleName chromosome start end nbrOfLoci mean 384s 1 CBS_Example (weighted) 1 6.066868e+02 19076007 199 -0.0610 384s 2 CBS_Example (weighted) 1 1.907601e+07 30126128 101 1.1283 384s 3 CBS_Example (weighted) 1 3.012613e+07 63224332 297 -0.0298 384s 4 CBS_Example (weighted) 1 6.322433e+07 78801707 153 -1.0436 384s 5 CBS_Example (weighted) 1 7.880171e+07 99917418 199 0.0461 384s > drawLevels(fitW, col="red") 384s NULL 384s > 384s > 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)) 384s > 384s > ## Assert that weighted segment means are less biased 384s > dmean <- getSegments(fit)$mean - getSegments(fitW)$mean 384s > cat("Segment mean differences:\n") 384s Segment mean differences: 384s > print(dmean) 384s [1] 0.3232 0.3006 0.3152 0.3028 0.3080 384s > stopifnot(all(dmean > 0, na.rm=TRUE)) 384s > 384s > 384s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 384s > # Segmentation with some known change points 384s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 384s > knownSegments <- data.frame( 384s + chromosome=c( 1, 1), 384s + start =x[c( 1, 401)], 384s + end =x[c(349, J)] 384s + ) 384s > fit2 <- segmentByCBS(dataW, knownSegments=knownSegments, verbose=TRUE) 384s Segmenting by CBS... 384s Chromosome: 1 384s Segmenting by CBS...done 384s > sampleName(fit2) <- "CBS_Example_2 (weighted)" 384s > print(fit2) 384s sampleName chromosome start end nbrOfLoci mean 384s 1 CBS_Example_2 (weighted) 1 6.066868e+02 19076007 199 -0.0610 384s 2 CBS_Example_2 (weighted) 1 1.907601e+07 30126128 101 1.1283 384s 3 CBS_Example_2 (weighted) 1 3.012613e+07 35490554 49 -0.0832 384s 4 CBS_Example_2 (weighted) 1 3.987525e+07 63224332 248 -0.0192 384s 5 CBS_Example_2 (weighted) 1 6.322433e+07 78471531 152 -1.0480 384s 6 CBS_Example_2 (weighted) 1 7.847153e+07 99917418 200 0.0427 384s > plotTracks(fit2) 384s Warning message: 384s In plotTracks.CBS(fit2) : 384s Setting default 'Clim' assuming the signal type is 'ratio' because signalType(fit2) is unknown ('NA'). Use signalType(fit2) <- 'ratio' to avoid this warning. 384s > abline(v=c(knownSegments$start, knownSegments$end)/1e6, lty=3) 384s > 384s > 384s > # Chromosome boundaries can be specified as -Inf and +Inf 384s > knownSegments <- data.frame( 384s + chromosome=c( 1, 1), 384s + start =c( -Inf, x[401]), 384s + end =c(x[349], +Inf) 384s + ) 384s > fit2b <- segmentByCBS(dataW, knownSegments=knownSegments, verbose=TRUE) 384s Segmenting by CBS... 384s Chromosome: 1 384s Segmenting by CBS...done 384s > sampleName(fit2b) <- "CBS_Example_2b (weighted)" 384s > print(fit2b) 384s sampleName chromosome start end nbrOfLoci mean 384s 1 CBS_Example_2b (weighted) 1 6.066868e+02 19076007 199 -0.0610 384s 2 CBS_Example_2b (weighted) 1 1.907601e+07 30126128 101 1.1283 384s 3 CBS_Example_2b (weighted) 1 3.012613e+07 35490554 49 -0.0832 384s 4 CBS_Example_2b (weighted) 1 3.987525e+07 63224332 248 -0.0192 384s 5 CBS_Example_2b (weighted) 1 6.322433e+07 78471531 152 -1.0480 384s 6 CBS_Example_2b (weighted) 1 7.847153e+07 99917418 200 0.0427 384s > plotTracks(fit2b) 384s Warning message: 384s In plotTracks.CBS(fit2b) : 384s Setting default 'Clim' assuming the signal type is 'ratio' because signalType(fit2b) is unknown ('NA'). Use signalType(fit2b) <- 'ratio' to avoid this warning. 384s > abline(v=c(knownSegments$start, knownSegments$end)/1e6, lty=3) 384s > 384s > 384s > # As a proof of concept, it is possible to segment just the centromere, 384s > # which contains no data. All statistics will be NAs. 384s > knownSegments <- data.frame( 384s + chromosome=c( 1), 384s + start =x[c(350)], 384s + end =x[c(400)] 384s + ) 384s > fit3 <- segmentByCBS(dataW, knownSegments=knownSegments, verbose=TRUE) 384s Segmenting by CBS... 384s Chromosome: 1 384s Segmenting by CBS...done 384s > sampleName(fit3) <- "CBS_Example_3" 384s > print(fit3) 384s sampleName chromosome start end nbrOfLoci mean 384s 1 CBS_Example_3 1 35661013 39852333 0 NA 384s > plotTracks(fit3, Clim=c(0,5), xlim=c(0,100)) 384s > abline(v=c(knownSegments$start, knownSegments$end)/1e6, lty=3) 384s > 384s > 384s > # If one specify the (empty) centromere as a segment, then its 384s > # estimated statistics will be NAs, which becomes a natural 384s > # separator between the two "independent" arms. 384s > knownSegments <- data.frame( 384s + chromosome=c( 1, 1, 1), 384s + start =x[c( 1, 350, 401)], 384s + end =x[c(349, 400, J)] 384s + ) 384s > fit4 <- segmentByCBS(dataW, knownSegments=knownSegments, verbose=TRUE) 384s Segmenting by CBS... 384s Chromosome: 1 384s Segmenting by CBS...done 384s > sampleName(fit4) <- "CBS_Example_4" 384s > print(fit4) 384s sampleName chromosome start end nbrOfLoci mean 384s 1 CBS_Example_4 1 6.066868e+02 19076007 199 -0.0610 384s 2 CBS_Example_4 1 1.907601e+07 30126128 101 1.1283 384s 3 CBS_Example_4 1 3.012613e+07 35490554 49 -0.0832 384s 4 CBS_Example_4 1 3.566101e+07 39852333 0 NA 384s 5 CBS_Example_4 1 3.987525e+07 63224332 248 -0.0192 384s 6 CBS_Example_4 1 6.322433e+07 78471531 152 -1.0480 384s 7 CBS_Example_4 1 7.847153e+07 99917418 200 0.0427 384s > plotTracks(fit4) 384s Warning message: 384s In plotTracks.CBS(fit4) : 384s Setting default 'Clim' assuming the signal type is 'ratio' because signalType(fit4) is unknown ('NA'). Use signalType(fit4) <- 'ratio' to avoid this warning. 384s > abline(v=c(knownSegments$start, knownSegments$end)/1e6, lty=3) 384s > 384s > 384s > fit5 <- segmentByCBS(dataW, knownSegments=knownSegments, undo=Inf, verbose=TRUE) 384s Segmenting by CBS... 384s Chromosome: 1 384s Segmenting by CBS...done 384s > sampleName(fit5) <- "CBS_Example_5" 384s > print(fit5) 384s sampleName chromosome start end nbrOfLoci mean 384s 1 CBS_Example_5 1 6.066868e+02 35490554 349 0.59252133 384s 2 CBS_Example_5 1 3.566101e+07 39852333 0 NA 384s 3 CBS_Example_5 1 3.987525e+07 99917418 600 0.04882396 384s > plotTracks(fit5) 384s Warning message: 384s In plotTracks.CBS(fit5) : 384s Setting default 'Clim' assuming the signal type is 'ratio' because signalType(fit5) is unknown ('NA'). Use signalType(fit5) <- 'ratio' to avoid this warning. 384s > abline(v=c(knownSegments$start, knownSegments$end)/1e6, lty=3) 384s > stopifnot(nbrOfSegments(fit5) == nrow(knownSegments)) 384s > 384s > 384s > # One can also force a separator between two segments by setting 384s > # 'start' and 'end' to NAs ('chromosome' has to be given) 384s > knownSegments <- data.frame( 384s + chromosome=c( 1, 1, 1), 384s + start =x[c( 1, NA, 401)], 384s + end =x[c(349, NA, J)] 384s + ) 384s > fit6 <- segmentByCBS(dataW, knownSegments=knownSegments, verbose=TRUE) 384s Segmenting by CBS... 384s Chromosome: 1 384s Segmenting by CBS...done 384s > sampleName(fit6) <- "CBS_Example_6" 384s > print(fit6) 384s sampleName chromosome start end nbrOfLoci mean 384s 1 CBS_Example_6 1 6.066868e+02 19076007 199 -0.0610 384s 2 CBS_Example_6 1 1.907601e+07 30126128 101 1.1283 384s 3 CBS_Example_6 1 3.012613e+07 35490554 49 -0.0832 384s 4 NA NA NA NA NA 384s 5 CBS_Example_6 1 3.987525e+07 63224332 248 -0.0192 384s 6 CBS_Example_6 1 6.322433e+07 78471531 152 -1.0480 384s 7 CBS_Example_6 1 7.847153e+07 99917418 200 0.0427 384s > plotTracks(fit6) 384s Warning message: 384s In plotTracks.CBS(fit6) : 384s Setting default 'Clim' assuming the signal type is 'ratio' because signalType(fit6) is unknown ('NA'). Use signalType(fit6) <- 'ratio' to avoid this warning. 384s > abline(v=c(knownSegments$start, knownSegments$end)/1e6, lty=3) 384s > 384s > 384s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 384s > # Multi-chromosome segmentation 384s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 384s > data2 <- data 384s > data2$chromosome <- 2L 384s > data <- rbind(data, data2) 384s > dataW <- cbind(data, w=w) 384s > 384s > par(mar=c(2,3,0.2,1)+0.1) 384s > # Segment without weights 384s > fit <- segmentByCBS(data) 384s > sampleName(fit) <- "CBS_Example" 384s > print(fit) 384s sampleName chromosome start end nbrOfLoci mean 384s 1 CBS_Example 1 6.066868e+02 19076007 199 0.2622 384s 2 CBS_Example 1 1.907601e+07 29630949 99 1.4289 384s 3 CBS_Example 1 2.963095e+07 63224332 299 0.2854 384s 4 CBS_Example 1 6.322433e+07 78801707 153 -0.7408 384s 5 CBS_Example 1 7.880171e+07 99917418 199 0.3541 384s 6 NA NA NA NA NA 384s 7 CBS_Example 2 6.066868e+02 19076007 199 0.2622 384s 8 CBS_Example 2 1.907601e+07 29630949 99 1.4289 384s 9 CBS_Example 2 2.963095e+07 63224332 299 0.2854 384s 10 CBS_Example 2 6.322433e+07 78801707 153 -0.7408 384s 11 CBS_Example 2 7.880171e+07 99917418 199 0.3541 384s > plotTracks(fit, Clim=c(-3,3)) 384s > 384s > # Segment with weights 384s > fitW <- segmentByCBS(dataW) 384s > sampleName(fitW) <- "CBS_Example (weighted)" 384s > print(fitW) 384s sampleName chromosome start end nbrOfLoci mean 384s 1 CBS_Example (weighted) 1 6.066868e+02 19076007 199 -0.0610 384s 2 CBS_Example (weighted) 1 1.907601e+07 30126128 101 1.1283 384s 3 CBS_Example (weighted) 1 3.012613e+07 63224332 297 -0.0298 384s 4 CBS_Example (weighted) 1 6.322433e+07 78801707 153 -1.0436 384s 5 CBS_Example (weighted) 1 7.880171e+07 99917418 199 0.0461 384s 6 NA NA NA NA NA 384s 7 CBS_Example (weighted) 2 6.066868e+02 19076007 199 -0.0610 384s 8 CBS_Example (weighted) 2 1.907601e+07 30126128 101 1.1283 384s 9 CBS_Example (weighted) 2 3.012613e+07 63224332 297 -0.0298 384s 10 CBS_Example (weighted) 2 6.322433e+07 78801707 153 -1.0436 384s 11 CBS_Example (weighted) 2 7.880171e+07 99917418 199 0.0461 384s > drawLevels(fitW, col="red") 384s NULL 384s > 384s > 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)) 384s > 384s > ## Assert that weighted segment means are less biased 384s > dmean <- getSegments(fit)$mean - getSegments(fitW)$mean 384s > cat("Segment mean differences:\n") 384s Segment mean differences: 384s > print(dmean) 384s [1] 0.3232 0.3006 0.3152 0.3028 0.3080 NA 0.3232 0.3006 0.3152 0.3028 384s [11] 0.3080 384s > stopifnot(all(dmean > 0, na.rm=TRUE)) 384s > 384s > proc.time() 384s user system elapsed 384s 2.520 0.080 2.589 384s Test segmentByCBS,weights passed 384s 0 384s Begin test segmentByCBS 384s + [ 0 != 0 ] 384s + echo Test segmentByCBS,weights passed 384s + echo 0 384s + echo Begin test segmentByCBS 384s + exitcode=0 384s + R CMD BATCH segmentByCBS.R 387s + cat segmentByCBS.Rout 387s 387s R version 4.5.2 (2025-10-31) -- "[Not] Part in a Rumble" 387s Copyright (C) 2025 The R Foundation for Statistical Computing 387s Platform: aarch64-unknown-linux-gnu 387s 387s R is free software and comes with ABSOLUTELY NO WARRANTY. 387s You are welcome to redistribute it under certain conditions. 387s Type 'license()' or 'licence()' for distribution details. 387s 387s R is a collaborative project with many contributors. 387s Type 'contributors()' for more information and 387s 'citation()' on how to cite R or R packages in publications. 387s 387s Type 'demo()' for some demos, 'help()' for on-line help, or 387s 'help.start()' for an HTML browser interface to help. 387s Type 'q()' to quit R. 387s 387s [Previously saved workspace restored] 387s 387s > ########################################################### 387s > # This tests: 387s > # - segmentByCBS(...) 387s > # - segmentByCBS(..., knownSegments) 387s > # - tileChromosomes() 387s > # - plotTracks() 387s > ########################################################### 387s > library("PSCBS") 387s PSCBS v0.68.0 (2025-04-18 19:40:02 UTC) successfully loaded. See ?PSCBS for help. 387s > subplots <- R.utils::subplots 387s > 387s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 387s > # Simulating copy-number data 387s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 387s > set.seed(0xBEEF) 387s > 387s > # Number of loci 387s > J <- 1000 387s > 387s > mu <- double(J) 387s > mu[200:300] <- mu[200:300] + 1 387s > mu[350:400] <- NA # centromere 387s > mu[650:800] <- mu[650:800] - 1 387s > eps <- rnorm(J, sd=1/2) 387s > y <- mu + eps 387s > x <- sort(runif(length(y), max=length(y))) * 1e5 387s > w <- runif(J) 387s > w[650:800] <- 0.001 387s > 387s > 387s > subplots(8, ncol=1L) 387s > par(mar=c(1.7,1,0.2,1)+0.1) 387s > 387s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 387s > # Segmentation 387s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 387s > fit <- segmentByCBS(y, x=x) 387s > sampleName(fit) <- "CBS_Example" 387s > print(fit) 387s sampleName chromosome start end nbrOfLoci mean 387s 1 CBS_Example 0 65285.65 19648927 200 0.0109 387s 2 CBS_Example 0 19648927.46 28239656 95 0.9529 387s 3 CBS_Example 0 28239655.99 65697742 302 -0.0126 387s 4 CBS_Example 0 65697742.20 79729368 153 -0.9534 387s 5 CBS_Example 0 79729368.34 99819310 199 -0.0497 387s > plotTracks(fit) 387s Warning message: 387s In plotTracks.CBS(fit) : 387s Setting default 'Clim' assuming the signal type is 'ratio' because signalType(fit) is unknown ('NA'). Use signalType(fit) <- 'ratio' to avoid this warning. 387s > 387s > 387s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 387s > # Segmentation with some known change points 387s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 387s > knownSegments <- data.frame( 387s + chromosome=c( 0, 0), 387s + start =x[c( 1, 401)], 387s + end =x[c(349, J)] 387s + ) 387s > fit2 <- segmentByCBS(y, x=x, knownSegments=knownSegments, verbose=TRUE) 387s Segmenting by CBS... 387s Chromosome: 0 387s Segmenting by CBS...done 387s > sampleName(fit2) <- "CBS_Example_2" 387s > print(fit2) 387s sampleName chromosome start end nbrOfLoci mean 387s 1 CBS_Example_2 0 65285.65 19648927 200 0.0109 387s 2 CBS_Example_2 0 19648927.46 28239656 95 0.9529 387s 3 CBS_Example_2 0 28239655.99 33106633 54 0.1169 387s 4 CBS_Example_2 0 38076667.59 65697742 248 -0.0408 387s 5 CBS_Example_2 0 65697742.20 79729368 153 -0.9534 387s 6 CBS_Example_2 0 79729368.34 99819310 199 -0.0497 387s > plotTracks(fit2) 387s Warning message: 387s In plotTracks.CBS(fit2) : 387s Setting default 'Clim' assuming the signal type is 'ratio' because signalType(fit2) is unknown ('NA'). Use signalType(fit2) <- 'ratio' to avoid this warning. 387s > abline(v=c(knownSegments$start, knownSegments$end)/1e6, lty=3) 387s > 387s > 387s > # Chromosome boundaries can be specified as -Inf and +Inf 387s > knownSegments <- data.frame( 387s + chromosome=c( 0, 0), 387s + start =c( -Inf, x[401]), 387s + end =c(x[349], +Inf) 387s + ) 387s > fit2b <- segmentByCBS(y, x=x, knownSegments=knownSegments, verbose=TRUE) 387s Segmenting by CBS... 387s Chromosome: 0 387s Segmenting by CBS...done 387s > sampleName(fit2b) <- "CBS_Example_2b" 387s > print(fit2b) 387s sampleName chromosome start end nbrOfLoci mean 387s 1 CBS_Example_2b 0 65285.65 19648927 200 0.0109 387s 2 CBS_Example_2b 0 19648927.46 28239656 95 0.9529 387s 3 CBS_Example_2b 0 28239655.99 33106633 54 0.1169 387s 4 CBS_Example_2b 0 38076667.59 65697742 248 -0.0408 387s 5 CBS_Example_2b 0 65697742.20 79729368 153 -0.9534 387s 6 CBS_Example_2b 0 79729368.34 99819310 199 -0.0497 387s > plotTracks(fit2b) 387s Warning message: 387s In plotTracks.CBS(fit2b) : 387s Setting default 'Clim' assuming the signal type is 'ratio' because signalType(fit2b) is unknown ('NA'). Use signalType(fit2b) <- 'ratio' to avoid this warning. 387s > abline(v=c(knownSegments$start, knownSegments$end)/1e6, lty=3) 387s > 387s > 387s > # As a proof of concept, it is possible to segment just the centromere, 387s > # which contains no data. All statistics will be NAs. 387s > knownSegments <- data.frame( 387s + chromosome=c( 0), 387s + start =x[c(350)], 387s + end =x[c(400)] 387s + ) 387s > fit3 <- segmentByCBS(y, x=x, knownSegments=knownSegments, verbose=TRUE) 387s Segmenting by CBS... 387s Chromosome: 0 387s Segmenting by CBS...done 387s > sampleName(fit3) <- "CBS_Example_3" 387s > print(fit3) 387s sampleName chromosome start end nbrOfLoci mean 387s 1 CBS_Example_3 0 33248518 37640521 0 NA 387s > plotTracks(fit3, Clim=c(0,5), xlim=c(0,100)) 387s > abline(v=c(knownSegments$start, knownSegments$end)/1e6, lty=3) 387s > 387s > 387s > 387s > # If one specify the (empty) centromere as a segment, then its 387s > # estimated statistics will be NAs, which becomes a natural 387s > # separator between the two "independent" arms. 387s > knownSegments <- data.frame( 387s + chromosome=c( 0, 0, 0), 387s + start =x[c( 1, 350, 401)], 387s + end =x[c(349, 400, J)] 387s + ) 387s > fit4 <- segmentByCBS(y, x=x, knownSegments=knownSegments, verbose=TRUE) 387s Segmenting by CBS... 387s Chromosome: 0 387s Segmenting by CBS...done 387s > sampleName(fit4) <- "CBS_Example_4" 387s > print(fit4) 387s sampleName chromosome start end nbrOfLoci mean 387s 1 CBS_Example_4 0 65285.65 19648927 200 0.0109 387s 2 CBS_Example_4 0 19648927.46 28239656 95 0.9529 387s 3 CBS_Example_4 0 28239655.99 33106633 54 0.1169 387s 4 CBS_Example_4 0 33248517.78 37640521 0 NA 387s 5 CBS_Example_4 0 38076667.59 65697742 248 -0.0408 387s 6 CBS_Example_4 0 65697742.20 79729368 153 -0.9534 387s 7 CBS_Example_4 0 79729368.34 99819310 199 -0.0497 387s > plotTracks(fit4) 387s Warning message: 387s In plotTracks.CBS(fit4) : 387s Setting default 'Clim' assuming the signal type is 'ratio' because signalType(fit4) is unknown ('NA'). Use signalType(fit4) <- 'ratio' to avoid this warning. 387s > abline(v=c(knownSegments$start, knownSegments$end)/1e6, lty=3) 387s > 387s > 387s > 387s > fit5 <- segmentByCBS(y, x=x, knownSegments=knownSegments, undo=Inf, verbose=TRUE) 387s Segmenting by CBS... 387s Chromosome: 0 387s Segmenting by CBS...done 387s > sampleName(fit5) <- "CBS_Example_5" 387s > print(fit5) 387s sampleName chromosome start end nbrOfLoci mean 387s 1 CBS_Example_5 0 65285.65 33106633 349 0.2836973 387s 2 CBS_Example_5 0 33248517.78 37640521 0 NA 387s 3 CBS_Example_5 0 38076667.59 99819310 600 -0.2764472 387s > plotTracks(fit5) 387s Warning message: 387s In plotTracks.CBS(fit5) : 387s Setting default 'Clim' assuming the signal type is 'ratio' because signalType(fit5) is unknown ('NA'). Use signalType(fit5) <- 'ratio' to avoid this warning. 387s > abline(v=c(knownSegments$start, knownSegments$end)/1e6, lty=3) 387s > stopifnot(nbrOfSegments(fit5) == nrow(knownSegments)) 387s > 387s > 387s > # One can also force a separator between two segments by setting 387s > # 'start' and 'end' to NAs ('chromosome' has to be given) 387s > knownSegments <- data.frame( 387s + chromosome=c( 0, 0, 0), 387s + start =x[c( 1, NA, 401)], 387s + end =x[c(349, NA, J)] 387s + ) 387s > fit6 <- segmentByCBS(y, x=x, knownSegments=knownSegments, verbose=TRUE) 387s Segmenting by CBS... 387s Chromosome: 0 387s Segmenting by CBS...done 387s > sampleName(fit6) <- "CBS_Example_6" 387s > print(fit6) 387s sampleName chromosome start end nbrOfLoci mean 387s 1 CBS_Example_6 0 65285.65 19648927 200 0.0109 387s 2 CBS_Example_6 0 19648927.46 28239656 95 0.9529 387s 3 CBS_Example_6 0 28239655.99 33106633 54 0.1169 387s 4 NA NA NA NA NA 387s 5 CBS_Example_6 0 38076667.59 65697742 248 -0.0408 387s 6 CBS_Example_6 0 65697742.20 79729368 153 -0.9534 387s 7 CBS_Example_6 0 79729368.34 99819310 199 -0.0497 387s > plotTracks(fit6) 387s Warning message: 387s In plotTracks.CBS(fit6) : 387s Setting default 'Clim' assuming the signal type is 'ratio' because signalType(fit6) is unknown ('NA'). Use signalType(fit6) <- 'ratio' to avoid this warning. 387s > abline(v=c(knownSegments$start, knownSegments$end)/1e6, lty=3) 387s > 387s > 387s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 387s > # Segment multiple chromosomes 387s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 387s > # Simulate multiple chromosomes 387s > fit1 <- renameChromosomes(fit, from=0, to=1) 387s > fit2 <- renameChromosomes(fit, from=0, to=2) 387s > fitM <- c(fit1, fit2) 387s > fitM <- segmentByCBS(fitM) 387s > sampleName(fitM) <- "CBS_Example_M" 387s > print(fitM) 387s sampleName chromosome start end nbrOfLoci mean 387s 1 CBS_Example_M 1 65285.65 19648927 200 0.0109 387s 2 CBS_Example_M 1 19648927.46 28239656 95 0.9529 387s 3 CBS_Example_M 1 28239655.99 65697742 302 -0.0126 387s 4 CBS_Example_M 1 65697742.20 79729368 153 -0.9534 387s 5 CBS_Example_M 1 79729368.34 99819310 199 -0.0497 387s 6 NA NA NA NA NA 387s 7 CBS_Example_M 2 65285.65 19648927 200 0.0109 387s 8 CBS_Example_M 2 19648927.46 28239656 95 0.9529 387s 9 CBS_Example_M 2 28239655.99 65697742 302 -0.0126 387s 10 CBS_Example_M 2 65697742.20 79729368 153 -0.9534 387s 11 CBS_Example_M 2 79729368.34 99819310 199 -0.0497 387s > plotTracks(fitM, Clim=c(-3,3)) 387s > 387s > 387s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 387s > # Tiling multiple chromosomes 387s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 387s > # Tile chromosomes 387s > fitT <- tileChromosomes(fitM) 387s > fitTb <- tileChromosomes(fitT) 387s > stopifnot(identical(fitTb, fitT)) 387s > 387s > 387s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 387s > # Write segmentation to file 387s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 387s > pathT <- tempdir() 387s > 387s > ## Tab-delimited file 387s > pathname <- writeSegments(fitM, path=pathT) 387s Warning message: 387s In write.table(file = pathnameT, data, append = TRUE, quote = FALSE, : 387s appending column names to file 387s > print(pathname) 387s [1] "/tmp/RtmpTe1qkk/CBS_Example_M.tsv" 387s > 387s > ## WIG file 387s > pathname <- writeWIG(fitM, path=pathT) 387s > print(pathname) 387s [1] "/tmp/RtmpTe1qkk/CBS_Example_M.wig" 387s > 387s > unlink(pathT, recursive=TRUE) 387s > 387s > proc.time() 387s user system elapsed 387s 2.430 0.078 2.519 387s Test segmentByCBS passed 387s 0 387s Begin test segmentByNonPairedPSCBS,medianDH 387s + [ 0 != 0 ] 387s + echo Test segmentByCBS passed 387s + echo 0 387s + echo Begin test segmentByNonPairedPSCBS,medianDH 387s + exitcode=0 387s + R CMD BATCH segmentByNonPairedPSCBS,medianDH.R 389s + cat segmentByNonPairedPSCBS,medianDH.Rout 389s 389s R version 4.5.2 (2025-10-31) -- "[Not] Part in a Rumble" 389s Copyright (C) 2025 The R Foundation for Statistical Computing 389s Platform: aarch64-unknown-linux-gnu 389s 389s R is free software and comes with ABSOLUTELY NO WARRANTY. 389s You are welcome to redistribute it under certain conditions. 389s Type 'license()' or 'licence()' for distribution details. 389s 389s R is a collaborative project with many contributors. 389s Type 'contributors()' for more information and 389s 'citation()' on how to cite R or R packages in publications. 389s 389s Type 'demo()' for some demos, 'help()' for on-line help, or 389s 'help.start()' for an HTML browser interface to help. 389s Type 'q()' to quit R. 389s 389s [Previously saved workspace restored] 389s 389s > library("PSCBS") 389s PSCBS v0.68.0 (2025-04-18 19:40:02 UTC) successfully loaded. See ?PSCBS for help. 389s > 389s > 389s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 389s > # Load SNP microarray data 389s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 389s > data <- PSCBS::exampleData("paired.chr01") 389s > str(data) 389s 'data.frame': 73346 obs. of 6 variables: 389s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 389s $ x : int 1145994 2224111 2319424 2543484 2926730 2941694 3084986 3155127 3292731 3695086 ... 389s $ CT : num 1.625 1.071 1.406 1.18 0.856 ... 389s $ betaT : num 0.757 0.771 0.834 0.778 0.229 ... 389s $ CN : num 2.36 2.13 2.59 1.93 1.71 ... 389s $ betaN : num 0.827 0.875 0.887 0.884 0.103 ... 389s > 389s > # Non-paired / tumor-only data 389s > data <- data[,c("chromosome", "x", "CT", "betaT")] 389s > str(data) 389s 'data.frame': 73346 obs. of 4 variables: 389s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 389s $ x : int 1145994 2224111 2319424 2543484 2926730 2941694 3084986 3155127 3292731 3695086 ... 389s $ CT : num 1.625 1.071 1.406 1.18 0.856 ... 389s $ betaT : num 0.757 0.771 0.834 0.778 0.229 ... 389s > 389s > 389s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 389s > # Paired PSCBS segmentation 389s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 389s > # Drop single-locus outliers 389s > dataS <- dropSegmentationOutliers(data) 389s > 389s > # Speed up example by segmenting fewer loci 389s > dataS <- dataS[seq(from=1, to=nrow(data), by=20),] 389s > 389s > # Fake a second chromosome 389s > dataT <- dataS 389s > dataT$chromosome <- 2L 389s > dataS <- rbind(dataS, dataT) 389s > rm(dataT) 389s > str(dataS) 389s 'data.frame': 7336 obs. of 4 variables: 389s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 389s $ x : int 1145994 4276892 5034491 6266412 8418532 11211748 13928296 14370144 15014887 16589707 ... 389s $ CT : num 1.63 1.16 1.35 1.39 1.55 ... 389s $ betaT : num 0.7574 0.0576 0.8391 0.7917 0.8141 ... 389s > 389s > # Non-Paired PSCBS segmentation 389s > fit <- segmentByNonPairedPSCBS(dataS, avgDH="median", seed=0xBEEF, verbose=-10) 389s Segmenting non-paired tumor signals using Non-paired PSCBS... 389s Number of loci: 7336 389s Number of SNPs: 7336 389s Calling "genotypes" from tumor allele B fractions... 389s num [1:7336] 0.7574 0.0576 0.8391 0.7917 0.8141 ... 389s Upper quantile: 0.475631667925522 389s Symmetric lower quantile: 0.290517384533512 389s (tauA, tauB) estimates: (%g,%g)0.2094826154664880.790517384533512 389s Homozygous treshholds: 389s [1] 0.2094826 0.7905174 389s Inferred germline genotypes (via tumor): 389s num [1:7336] 0.5 0 1 1 1 0 0 0 0.5 1 ... 389s muNx 389s 0 0.5 1 389s 2230 2910 2196 389s Calling "genotypes" from tumor allele B fractions...done 389s Segmenting non-paired tumor signals using Non-paired PSCBS...done 389s Segment using Paired PSCBS... 389s Segmenting paired tumor-normal signals using Paired PSCBS... 389s Setup up data... 389s 'data.frame': 7336 obs. of 6 variables: 389s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 389s $ x : num 1145994 4276892 5034491 6266412 8418532 ... 389s $ CT : num 1.63 1.16 1.35 1.39 1.55 ... 389s $ betaT : num 0.7574 0.0576 0.8391 0.7917 0.8141 ... 389s $ betaTN : num 0.7574 0.0576 0.8391 0.7917 0.8141 ... 389s $ muN : num 0.5 0 1 1 1 0 0 0 0.5 1 ... 389s Setup up data...done 389s Dropping loci for which TCNs are missing... 389s Number of loci dropped: 12 389s Dropping loci for which TCNs are missing...done 389s Ordering data along genome... 389s 'data.frame': 7324 obs. of 6 variables: 389s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 389s $ x : num 554484 1031563 1087198 1145994 1176365 ... 389s $ CT : num 1.88 1.64 1.77 1.63 1.59 ... 389s $ betaT : num 0.0646 0.6078 0.401 0.7574 0.645 ... 389s $ betaTN : num 0.0646 0.6078 0.401 0.7574 0.645 ... 389s $ muN : num 0 0.5 0.5 0.5 0.5 0.5 1 0.5 0.5 0.5 ... 389s Ordering data along genome...done 389s Segmenting multiple chromosomes... 389s Number of chromosomes: 2 389s Random seed temporarily set (seed=c(48879), kind="L'Ecuyer-CMRG") 389s Produced 2 seeds from this stream for future usage 389s Chromosome #1 ('Chr01') of 2... 389s 'data.frame': 3662 obs. of 7 variables: 389s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 389s $ x : num 554484 1031563 1087198 1145994 1176365 ... 389s $ CT : num 1.88 1.64 1.77 1.63 1.59 ... 389s $ betaT : num 0.0646 0.6078 0.401 0.7574 0.645 ... 389s $ betaTN : num 0.0646 0.6078 0.401 0.7574 0.645 ... 389s $ muN : num 0 0.5 0.5 0.5 0.5 0.5 1 0.5 0.5 0.5 ... 389s $ index : int 1 2 3 4 5 6 7 8 9 10 ... 389s Known segments: 389s [1] chromosome start end 389s <0 rows> (or 0-length row.names) 389s Segmenting paired tumor-normal signals using Paired PSCBS... 389s Setup up data... 389s 'data.frame': 3662 obs. of 6 variables: 389s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 389s $ x : num 554484 1031563 1087198 1145994 1176365 ... 389s $ CT : num 1.88 1.64 1.77 1.63 1.59 ... 389s $ betaT : num 0.0646 0.6078 0.401 0.7574 0.645 ... 389s $ betaTN : num 0.0646 0.6078 0.401 0.7574 0.645 ... 389s $ muN : num 0 0.5 0.5 0.5 0.5 0.5 1 0.5 0.5 0.5 ... 389s Setup up data...done 389s Ordering data along genome... 389s 'data.frame': 3662 obs. of 6 variables: 389s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 389s $ x : num 554484 1031563 1087198 1145994 1176365 ... 389s $ CT : num 1.88 1.64 1.77 1.63 1.59 ... 389s $ betaT : num 0.0646 0.6078 0.401 0.7574 0.645 ... 389s $ betaTN : num 0.0646 0.6078 0.401 0.7574 0.645 ... 389s $ muN : num 0 0.5 0.5 0.5 0.5 0.5 1 0.5 0.5 0.5 ... 389s Ordering data along genome...done 389s Keeping only current chromosome for 'knownSegments'... 389s Chromosome: 1 389s Known segments for this chromosome: 389s [1] chromosome start end 389s <0 rows> (or 0-length row.names) 389s Keeping only current chromosome for 'knownSegments'...done 389s alphaTCN: 0.009 389s alphaDH: 0.001 389s Number of loci: 3662 389s Calculating DHs... 389s Number of SNPs: 3662 389s Number of heterozygous SNPs: 1451 (39.62%) 389s Normalized DHs: 389s num [1:3662] NA 0.216 0.198 0.515 0.29 ... 389s Calculating DHs...done 389s Random seed temporarily set (seed=c(10407, 1066287653, -51199871, 161854402, -1995183193, 1503453565, -747102133), kind="L'Ecuyer-CMRG") 389s Produced 2 seeds from this stream for future usage 389s Identification of change points by total copy numbers... 389s Segmenting by CBS... 389s Chromosome: 1 389s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 389s Segmenting by CBS...done 389s List of 4 389s $ data :'data.frame': 3662 obs. of 4 variables: 389s ..$ chromosome: int [1:3662] 1 1 1 1 1 1 1 1 1 1 ... 389s ..$ x : num [1:3662] 554484 1031563 1087198 1145994 1176365 ... 389s ..$ y : num [1:3662] 1.88 1.64 1.77 1.63 1.59 ... 389s ..$ index : int [1:3662] 1 2 3 4 5 6 7 8 9 10 ... 389s $ output :'data.frame': 3 obs. of 6 variables: 389s ..$ sampleName: chr [1:3] NA NA NA 389s ..$ chromosome: int [1:3] 1 1 1 389s ..$ start : num [1:3] 5.54e+05 1.44e+08 1.85e+08 389s ..$ end : num [1:3] 1.44e+08 1.85e+08 2.47e+08 389s ..$ nbrOfLoci : int [1:3] 1880 671 1111 389s ..$ mean : num [1:3] 1.39 2.09 2.65 389s $ segRows:'data.frame': 3 obs. of 2 variables: 389s ..$ startRow: int [1:3] 1 1881 2552 389s ..$ endRow : int [1:3] 1880 2551 3662 389s $ params :List of 5 389s ..$ alpha : num 0.009 389s ..$ undo : num 0 389s ..$ joinSegments : logi TRUE 389s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 389s .. ..$ chromosome: int 1 389s .. ..$ start : num -Inf 389s .. ..$ end : num Inf 389s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 389s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 389s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.063 0 0.063 0 0 389s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 389s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 389s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 389s Identification of change points by total copy numbers...done 389s Restructure TCN segmentation results... 389s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean 389s 1 1 554484 143663981 1880 1.3916 389s 2 1 143663981 185240536 671 2.0925 389s 3 1 185240536 246679946 1111 2.6545 389s Number of TCN segments: 3 389s Restructure TCN segmentation results...done 389s TCN-only segmentation... 389s Total CN segment #1 ([ 554484,1.43664e+08]) of 3... 389s Number of TCN loci in segment: 1880 389s Locus data for TCN segment: 389s 'data.frame': 1880 obs. of 8 variables: 389s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 389s $ x : num 554484 1031563 1087198 1145994 1176365 ... 389s $ CT : num 1.88 1.64 1.77 1.63 1.59 ... 389s $ betaT : num 0.0646 0.6078 0.401 0.7574 0.645 ... 389s $ betaTN : num 0.0646 0.6078 0.401 0.7574 0.645 ... 389s $ muN : num 0 0.5 0.5 0.5 0.5 0.5 1 0.5 0.5 0.5 ... 389s $ index : int 1 2 3 4 5 6 7 8 9 10 ... 389s $ rho : num NA 0.216 0.198 0.515 0.29 ... 389s Number of loci: 1880 389s Number of SNPs: 765 (40.69%) 389s Number of heterozygous SNPs: 765 (100.00%) 389s Total CN segment #1 ([ 554484,1.43664e+08]) of 3...done 389s Total CN segment #2 ([1.43664e+08,1.85241e+08]) of 3... 389s Number of TCN loci in segment: 671 389s Locus data for TCN segment: 389s 'data.frame': 671 obs. of 8 variables: 389s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 389s $ x : num 1.44e+08 1.44e+08 1.44e+08 1.44e+08 1.44e+08 ... 389s $ CT : num 2.26 2.1 2.1 1.89 1.97 ... 389s $ betaT : num 0.958 0.19 0.909 0.13 0.141 ... 389s $ betaTN : num 0.958 0.19 0.909 0.13 0.141 ... 389s $ muN : num 1 0 1 0 0 0 0 0.5 0 1 ... 389s $ index : int 1881 1882 1883 1884 1885 1886 1887 1888 1889 1890 ... 389s $ rho : num NA NA NA NA NA ... 389s Number of loci: 671 389s Number of SNPs: 272 (40.54%) 389s Number of heterozygous SNPs: 272 (100.00%) 389s Total CN segment #2 ([1.43664e+08,1.85241e+08]) of 3...done 389s Total CN segment #3 ([1.85241e+08,2.4668e+08]) of 3... 389s Number of TCN loci in segment: 1111 389s Locus data for TCN segment: 389s 'data.frame': 1111 obs. of 8 variables: 389s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 389s $ x : num 1.85e+08 1.86e+08 1.86e+08 1.86e+08 1.86e+08 ... 389s $ CT : num 2.44 3 2.32 2.76 2.48 ... 389s $ betaT : num 0.0727 0.6845 0.2327 0.8118 0.0746 ... 389s $ betaTN : num 0.0727 0.6845 0.2327 0.8118 0.0746 ... 389s $ muN : num 0 0.5 0.5 1 0 1 0 1 1 0.5 ... 389s $ index : int 2552 2553 2554 2555 2556 2557 2558 2559 2560 2561 ... 389s $ rho : num NA 0.369 0.535 NA NA ... 389s Number of loci: 1111 389s Number of SNPs: 414 (37.26%) 389s Number of heterozygous SNPs: 414 (100.00%) 389s Total CN segment #3 ([1.85241e+08,2.4668e+08]) of 3...done 389s TCN-only segmentation...done 389s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 389s 1 1 1 1 554484 143663981 1880 1.3916 765 389s 2 1 2 1 143663981 185240536 671 2.0925 272 389s 3 1 3 1 185240536 246679946 1111 2.6545 414 389s tcnNbrOfHets dhNbrOfLoci dhStart dhEnd dhMean 389s 1 765 765 554484 143663981 0.3979122 389s 2 272 272 143663981 185240536 0.2306116 389s 3 414 414 185240536 246679946 0.2798120 389s Calculating (C1,C2) per segment... 389s Calculating (C1,C2) per segment...done 389s Number of segments: 3 389s Segmenting paired tumor-normal signals using Paired PSCBS...done 389s Updating mean level using different estimator... 389s TCN estimator: mean 389s DH estimator: median 389s Updating mean level using different estimator...done 389s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 389s 1 1 1 1 554484 143663981 1880 1.391608 765 389s 2 1 2 1 143663981 185240536 671 2.092452 272 389s 3 1 3 1 185240536 246679946 1111 2.654512 414 389s tcnNbrOfHets dhNbrOfLoci dhStart dhEnd dhMean c1Mean c2Mean 389s 1 765 765 554484 143663981 0.4206323 0.4031263 0.9884817 389s 2 272 272 143663981 185240536 0.1762428 0.8618360 1.2306156 389s 3 414 414 185240536 246679946 0.2697420 0.9692395 1.6852728 389s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 389s 1 1 1 1 554484 143663981 1880 1.391608 765 389s 2 1 2 1 143663981 185240536 671 2.092452 272 389s 3 1 3 1 185240536 246679946 1111 2.654512 414 389s tcnNbrOfHets dhNbrOfLoci dhStart dhEnd dhMean c1Mean c2Mean 389s 1 765 765 554484 143663981 0.4206323 0.4031263 0.9884817 389s 2 272 272 143663981 185240536 0.1762428 0.8618360 1.2306156 389s 3 414 414 185240536 246679946 0.2697420 0.9692395 1.6852728 389s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 389s 1 1 1 1 554484 143663981 1880 1.391608 765 389s 2 1 2 1 143663981 185240536 671 2.092452 272 389s 3 1 3 1 185240536 246679946 1111 2.654512 414 389s tcnNbrOfHets dhNbrOfLoci dhStart dhEnd dhMean c1Mean c2Mean 389s 1 765 765 554484 143663981 0.4206323 0.4031263 0.9884817 389s 2 272 272 143663981 185240536 0.1762428 0.8618360 1.2306156 389s 3 414 414 185240536 246679946 0.2697420 0.9692395 1.6852728 389s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 389s 1 1 1 1 554484 143663981 1880 1.391608 765 389s 2 1 2 1 143663981 185240536 671 2.092452 272 389s 3 1 3 1 185240536 246679946 1111 2.654512 414 389s tcnNbrOfHets dhNbrOfLoci dhStart dhEnd dhMean c1Mean c2Mean 389s 1 765 765 554484 143663981 0.4206323 0.4031263 0.9884817 389s 2 272 272 143663981 185240536 0.1762428 0.8618360 1.2306156 389s 3 414 414 185240536 246679946 0.2697420 0.9692395 1.6852728 389s Chromosome #1 ('Chr01') of 2...done 389s Chromosome #2 ('Chr02') of 2... 389s 'data.frame': 3662 obs. of 7 variables: 389s $ chromosome: int 2 2 2 2 2 2 2 2 2 2 ... 389s $ x : num 554484 1031563 1087198 1145994 1176365 ... 389s $ CT : num 1.88 1.64 1.77 1.63 1.59 ... 389s $ betaT : num 0.0646 0.6078 0.401 0.7574 0.645 ... 389s $ betaTN : num 0.0646 0.6078 0.401 0.7574 0.645 ... 389s $ muN : num 0 0.5 0.5 0.5 0.5 0.5 1 0.5 0.5 0.5 ... 389s $ index : int 3663 3664 3665 3666 3667 3668 3669 3670 3671 3672 ... 389s Known segments: 389s [1] chromosome start end 389s <0 rows> (or 0-length row.names) 389s Segmenting paired tumor-normal signals using Paired PSCBS... 389s Setup up data... 389s 'data.frame': 3662 obs. of 6 variables: 389s $ chromosome: int 2 2 2 2 2 2 2 2 2 2 ... 389s $ x : num 554484 1031563 1087198 1145994 1176365 ... 389s $ CT : num 1.88 1.64 1.77 1.63 1.59 ... 389s $ betaT : num 0.0646 0.6078 0.401 0.7574 0.645 ... 389s $ betaTN : num 0.0646 0.6078 0.401 0.7574 0.645 ... 389s $ muN : num 0 0.5 0.5 0.5 0.5 0.5 1 0.5 0.5 0.5 ... 389s Setup up data...done 389s Ordering data along genome... 389s 'data.frame': 3662 obs. of 6 variables: 389s $ chromosome: int 2 2 2 2 2 2 2 2 2 2 ... 389s $ x : num 554484 1031563 1087198 1145994 1176365 ... 389s $ CT : num 1.88 1.64 1.77 1.63 1.59 ... 389s $ betaT : num 0.0646 0.6078 0.401 0.7574 0.645 ... 389s $ betaTN : num 0.0646 0.6078 0.401 0.7574 0.645 ... 389s $ muN : num 0 0.5 0.5 0.5 0.5 0.5 1 0.5 0.5 0.5 ... 389s Ordering data along genome...done 389s Keeping only current chromosome for 'knownSegments'... 389s Chromosome: 2 389s Known segments for this chromosome: 389s [1] chromosome start end 389s <0 rows> (or 0-length row.names) 389s Keeping only current chromosome for 'knownSegments'...done 389s alphaTCN: 0.009 389s alphaDH: 0.001 389s Number of loci: 3662 389s Calculating DHs... 389s Number of SNPs: 3662 389s Number of heterozygous SNPs: 1451 (39.62%) 389s Normalized DHs: 389s num [1:3662] NA 0.216 0.198 0.515 0.29 ... 389s Calculating DHs...done 389s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 389s Produced 2 seeds from this stream for future usage 389s Identification of change points by total copy numbers... 389s Segmenting by CBS... 389s Chromosome: 2 389s Random seed temporarily set (seed=c(10407, -821273412, -52578226, 1415511586, 721384351, -665928286, 1316562960), kind="L'Ecuyer-CMRG") 389s Segmenting by CBS...done 389s List of 4 389s $ data :'data.frame': 3662 obs. of 4 variables: 389s ..$ chromosome: int [1:3662] 2 2 2 2 2 2 2 2 2 2 ... 389s ..$ x : num [1:3662] 554484 1031563 1087198 1145994 1176365 ... 389s ..$ y : num [1:3662] 1.88 1.64 1.77 1.63 1.59 ... 389s ..$ index : int [1:3662] 1 2 3 4 5 6 7 8 9 10 ... 389s $ output :'data.frame': 3 obs. of 6 variables: 389s ..$ sampleName: chr [1:3] NA NA NA 389s ..$ chromosome: int [1:3] 2 2 2 389s ..$ start : num [1:3] 5.54e+05 1.44e+08 1.85e+08 389s ..$ end : num [1:3] 1.44e+08 1.85e+08 2.47e+08 389s ..$ nbrOfLoci : int [1:3] 1880 671 1111 389s ..$ mean : num [1:3] 1.39 2.09 2.65 389s $ segRows:'data.frame': 3 obs. of 2 variables: 389s ..$ startRow: int [1:3] 1 1881 2552 389s ..$ endRow : int [1:3] 1880 2551 3662 389s $ params :List of 5 389s ..$ alpha : num 0.009 389s ..$ undo : num 0 389s ..$ joinSegments : logi TRUE 389s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 389s .. ..$ chromosome: int 2 389s .. ..$ start : num -Inf 389s .. ..$ end : num Inf 389s ..$ seed : int [1:7] 10407 -821273412 -52578226 1415511586 721384351 -665928286 1316562960 389s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 389s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.061 0 0.062 0 0 389s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 389s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 389s - attr(*, "randomSeed")= int [1:7] 10407 -821273412 -52578226 1415511586 721384351 -665928286 1316562960 389s Identification of change points by total copy numbers...done 389s Restructure TCN segmentation results... 389s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean 389s 1 2 554484 143663981 1880 1.3916 389s 2 2 143663981 185240536 671 2.0925 389s 3 2 185240536 246679946 1111 2.6545 389s Number of TCN segments: 3 389s Restructure TCN segmentation results...done 389s TCN-only segmentation... 389s Total CN segment #1 ([ 554484,1.43664e+08]) of 3... 389s Number of TCN loci in segment: 1880 389s Locus data for TCN segment: 389s 'data.frame': 1880 obs. of 8 variables: 389s $ chromosome: int 2 2 2 2 2 2 2 2 2 2 ... 389s $ x : num 554484 1031563 1087198 1145994 1176365 ... 389s $ CT : num 1.88 1.64 1.77 1.63 1.59 ... 389s $ betaT : num 0.0646 0.6078 0.401 0.7574 0.645 ... 389s $ betaTN : num 0.0646 0.6078 0.401 0.7574 0.645 ... 389s $ muN : num 0 0.5 0.5 0.5 0.5 0.5 1 0.5 0.5 0.5 ... 389s $ index : int 1 2 3 4 5 6 7 8 9 10 ... 389s $ rho : num NA 0.216 0.198 0.515 0.29 ... 389s Number of loci: 1880 389s Number of SNPs: 765 (40.69%) 389s Number of heterozygous SNPs: 765 (100.00%) 389s Total CN segment #1 ([ 554484,1.43664e+08]) of 3...done 389s Total CN segment #2 ([1.43664e+08,1.85241e+08]) of 3... 389s Number of TCN loci in segment: 671 389s Locus data for TCN segment: 389s 'data.frame': 671 obs. of 8 variables: 389s $ chromosome: int 2 2 2 2 2 2 2 2 2 2 ... 389s $ x : num 1.44e+08 1.44e+08 1.44e+08 1.44e+08 1.44e+08 ... 389s $ CT : num 2.26 2.1 2.1 1.89 1.97 ... 389s $ betaT : num 0.958 0.19 0.909 0.13 0.141 ... 389s $ betaTN : num 0.958 0.19 0.909 0.13 0.141 ... 389s $ muN : num 1 0 1 0 0 0 0 0.5 0 1 ... 389s $ index : int 1881 1882 1883 1884 1885 1886 1887 1888 1889 1890 ... 389s $ rho : num NA NA NA NA NA ... 389s Number of loci: 671 389s Number of SNPs: 272 (40.54%) 389s Number of heterozygous SNPs: 272 (100.00%) 389s Total CN segment #2 ([1.43664e+08,1.85241e+08]) of 3...done 389s Total CN segment #3 ([1.85241e+08,2.4668e+08]) of 3... 389s Number of TCN loci in segment: 1111 389s Locus data for TCN segment: 389s 'data.frame': 1111 obs. of 8 variables: 389s $ chromosome: int 2 2 2 2 2 2 2 2 2 2 ... 389s $ x : num 1.85e+08 1.86e+08 1.86e+08 1.86e+08 1.86e+08 ... 389s $ CT : num 2.44 3 2.32 2.76 2.48 ... 389s $ betaT : num 0.0727 0.6845 0.2327 0.8118 0.0746 ... 389s $ betaTN : num 0.0727 0.6845 0.2327 0.8118 0.0746 ... 389s $ muN : num 0 0.5 0.5 1 0 1 0 1 1 0.5 ... 389s $ index : int 2552 2553 2554 2555 2556 2557 2558 2559 2560 2561 ... 389s $ rho : num NA 0.369 0.535 NA NA ... 389s Number of loci: 1111 389s Number of SNPs: 414 (37.26%) 389s Number of heterozygous SNPs: 414 (100.00%) 389s Total CN segment #3 ([1.85241e+08,2.4668e+08]) of 3...done 389s TCN-only segmentation...done 389s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 389s 1 2 1 1 554484 143663981 1880 1.3916 765 389s 2 2 2 1 143663981 185240536 671 2.0925 272 389s 3 2 3 1 185240536 246679946 1111 2.6545 414 389s tcnNbrOfHets dhNbrOfLoci dhStart dhEnd dhMean 389s 1 765 765 554484 143663981 0.3979122 389s 2 272 272 143663981 185240536 0.2306116 389s 3 414 414 185240536 246679946 0.2798120 389s Calculating (C1,C2) per segment... 389s Calculating (C1,C2) per segment...done 389s Number of segments: 3 389s Segmenting paired tumor-normal signals using Paired PSCBS...done 389s Updating mean level using different estimator... 389s TCN estimator: mean 389s DH estimator: median 389s Updating mean level using different estimator...done 389s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 389s 1 2 1 1 554484 143663981 1880 1.391608 765 389s 2 2 2 1 143663981 185240536 671 2.092452 272 389s 3 2 3 1 185240536 246679946 1111 2.654512 414 389s tcnNbrOfHets dhNbrOfLoci dhStart dhEnd dhMean c1Mean c2Mean 389s 1 765 765 554484 143663981 0.4206323 0.4031263 0.9884817 389s 2 272 272 143663981 185240536 0.1762428 0.8618360 1.2306156 389s 3 414 414 185240536 246679946 0.2697420 0.9692395 1.6852728 389s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 389s 1 2 1 1 554484 143663981 1880 1.391608 765 389s 2 2 2 1 143663981 185240536 671 2.092452 272 389s 3 2 3 1 185240536 246679946 1111 2.654512 414 389s tcnNbrOfHets dhNbrOfLoci dhStart dhEnd dhMean c1Mean c2Mean 389s 1 765 765 554484 143663981 0.4206323 0.4031263 0.9884817 389s 2 272 272 143663981 185240536 0.1762428 0.8618360 1.2306156 389s 3 414 414 185240536 246679946 0.2697420 0.9692395 1.6852728 389s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 389s 1 2 1 1 554484 143663981 1880 1.391608 765 389s 2 2 2 1 143663981 185240536 671 2.092452 272 389s 3 2 3 1 185240536 246679946 1111 2.654512 414 389s tcnNbrOfHets dhNbrOfLoci dhStart dhEnd dhMean c1Mean c2Mean 389s 1 765 765 554484 143663981 0.4206323 0.4031263 0.9884817 389s 2 272 272 143663981 185240536 0.1762428 0.8618360 1.2306156 389s 3 414 414 185240536 246679946 0.2697420 0.9692395 1.6852728 389s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 389s 1 2 1 1 554484 143663981 1880 1.391608 765 389s 2 2 2 1 143663981 185240536 671 2.092452 272 389s 3 2 3 1 185240536 246679946 1111 2.654512 414 389s tcnNbrOfHets dhNbrOfLoci dhStart dhEnd dhMean c1Mean c2Mean 389s 1 765 765 554484 143663981 0.4206323 0.4031263 0.9884817 389s 2 272 272 143663981 185240536 0.1762428 0.8618360 1.2306156 389s 3 414 414 185240536 246679946 0.2697420 0.9692395 1.6852728 389s Chromosome #2 ('Chr02') of 2...done 389s Merging (independently) segmented chromosome... 389s List of 5 389s $ data :Classes 'PairedPSCNData' and 'data.frame': 7324 obs. of 7 variables: 389s ..$ chromosome: int [1:7324] 1 1 1 1 1 1 1 1 1 1 ... 389s ..$ x : num [1:7324] 554484 1031563 1087198 1145994 1176365 ... 389s ..$ CT : num [1:7324] 1.88 1.64 1.77 1.63 1.59 ... 389s ..$ betaT : num [1:7324] 0.0646 0.6078 0.401 0.7574 0.645 ... 389s ..$ betaTN : num [1:7324] 0.0646 0.6078 0.401 0.7574 0.645 ... 389s ..$ muN : num [1:7324] 0 0.5 0.5 0.5 0.5 0.5 1 0.5 0.5 0.5 ... 389s ..$ rho : num [1:7324] NA 0.216 0.198 0.515 0.29 ... 389s $ output :Classes 'PairedPSCNSegments' and 'data.frame': 7 obs. of 15 variables: 389s ..$ chromosome : int [1:7] 1 1 1 NA 2 2 2 389s ..$ tcnId : int [1:7] 1 2 3 NA 1 2 3 389s ..$ dhId : int [1:7] 1 1 1 NA 1 1 1 389s ..$ tcnStart : num [1:7] 5.54e+05 1.44e+08 1.85e+08 NA 5.54e+05 ... 389s ..$ tcnEnd : num [1:7] 1.44e+08 1.85e+08 2.47e+08 NA 1.44e+08 ... 389s ..$ tcnNbrOfLoci: int [1:7] 1880 671 1111 NA 1880 671 1111 389s ..$ tcnMean : num [1:7] 1.39 2.09 2.65 NA 1.39 ... 389s ..$ tcnNbrOfSNPs: int [1:7] 765 272 414 NA 765 272 414 389s ..$ tcnNbrOfHets: int [1:7] 765 272 414 NA 765 272 414 389s ..$ dhNbrOfLoci : int [1:7] 765 272 414 NA 765 272 414 389s ..$ dhStart : num [1:7] 5.54e+05 1.44e+08 1.85e+08 NA 5.54e+05 ... 389s ..$ dhEnd : num [1:7] 1.44e+08 1.85e+08 2.47e+08 NA 1.44e+08 ... 389s ..$ dhMean : num [1:7] 0.421 0.176 0.27 NA 0.421 ... 389s ..$ c1Mean : num [1:7] 0.403 0.862 0.969 NA 0.403 ... 389s ..$ c2Mean : num [1:7] 0.988 1.231 1.685 NA 0.988 ... 389s $ tcnSegRows:'data.frame': 7 obs. of 2 variables: 389s ..$ startRow: int [1:7] 1 1881 2552 NA 3663 5543 6214 389s ..$ endRow : int [1:7] 1880 2551 3662 NA 5542 6213 7324 389s $ dhSegRows :'data.frame': 7 obs. of 2 variables: 389s ..$ startRow: int [1:7] 2 1888 2553 NA 3664 5550 6215 389s ..$ endRow : int [1:7] 1876 2548 3659 NA 5538 6210 7321 389s $ params :List of 8 389s ..$ alphaTCN : num 0.009 389s ..$ alphaDH : num 0.001 389s ..$ flavor : chr "tcn" 389s ..$ tbn : logi FALSE 389s ..$ joinSegments : logi TRUE 389s ..$ knownSegments :'data.frame': 0 obs. of 3 variables: 389s .. ..$ chromosome: int(0) 389s .. ..$ start : int(0) 389s .. ..$ end : int(0) 389s ..$ seed : int [1:7] 10407 1066287653 -51199871 161854402 -1995183193 1503453565 -747102133 389s ..$ meanEstimators:List of 2 389s .. ..$ tcn: chr "mean" 389s .. ..$ dh : chr "median" 389s - attr(*, "class")= chr [1:3] "PairedPSCBS" "PSCBS" "AbstractCBS" 389s Merging (independently) segmented chromosome...done 389s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 389s 1 1 1 1 554484 143663981 1880 1.391608 765 389s 2 1 2 1 143663981 185240536 671 2.092452 272 389s 3 1 3 1 185240536 246679946 1111 2.654512 414 389s 4 NA NA NA NA NA NA NA NA 389s 5 2 1 1 554484 143663981 1880 1.391608 765 389s 6 2 2 1 143663981 185240536 671 2.092452 272 389s tcnNbrOfHets dhNbrOfLoci dhStart dhEnd dhMean c1Mean c2Mean 389s 1 765 765 554484 143663981 0.4206323 0.4031263 0.9884817 389s 2 272 272 143663981 185240536 0.1762428 0.8618360 1.2306156 389s 3 414 414 185240536 246679946 0.2697420 0.9692395 1.6852728 389s 4 NA NA NA NA NA NA NA 389s 5 765 765 554484 143663981 0.4206323 0.4031263 0.9884817 389s 6 272 272 143663981 185240536 0.1762428 0.8618360 1.2306156 389s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 389s 2 1 2 1 143663981 185240536 671 2.092452 272 389s 3 1 3 1 185240536 246679946 1111 2.654512 414 389s 4 NA NA NA NA NA NA NA NA 389s 5 2 1 1 554484 143663981 1880 1.391608 765 389s 6 2 2 1 143663981 185240536 671 2.092452 272 389s 7 2 3 1 185240536 246679946 1111 2.654512 414 389s tcnNbrOfHets dhNbrOfLoci dhStart dhEnd dhMean c1Mean c2Mean 389s 2 272 272 143663981 185240536 0.1762428 0.8618360 1.2306156 389s 3 414 414 185240536 246679946 0.2697420 0.9692395 1.6852728 389s 4 NA NA NA NA NA NA NA 389s 5 765 765 554484 143663981 0.4206323 0.4031263 0.9884817 389s 6 272 272 143663981 185240536 0.1762428 0.8618360 1.2306156 389s 7 414 414 185240536 246679946 0.2697420 0.9692395 1.6852728 389s Segmenting multiple chromosomes...done 389s Segmenting paired tumor-normal signals using Paired PSCBS...done 389s Segment using Paired PSCBS...done 389s Coercing to Non-Paired PSCBS results... 389s Coercing to Non-Paired PSCBS results...done 389s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 389s 1 1 1 1 554484 143663981 1880 1.391608 765 389s 2 1 2 1 143663981 185240536 671 2.092452 272 389s 3 1 3 1 185240536 246679946 1111 2.654512 414 389s 4 NA NA NA NA NA NA NA NA 389s 5 2 1 1 554484 143663981 1880 1.391608 765 389s 6 2 2 1 143663981 185240536 671 2.092452 272 389s tcnNbrOfHets dhNbrOfLoci dhStart dhEnd dhMean c1Mean c2Mean 389s 1 765 765 554484 143663981 0.4206323 0.4031263 0.9884817 389s 2 272 272 143663981 185240536 0.1762428 0.8618360 1.2306156 389s 3 414 414 185240536 246679946 0.2697420 0.9692395 1.6852728 389s 4 NA NA NA NA NA NA NA 389s 5 765 765 554484 143663981 0.4206323 0.4031263 0.9884817 389s 6 272 272 143663981 185240536 0.1762428 0.8618360 1.2306156 389s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 389s 2 1 2 1 143663981 185240536 671 2.092452 272 389s 3 1 3 1 185240536 246679946 1111 2.654512 414 389s 4 NA NA NA NA NA NA NA NA 389s 5 2 1 1 554484 143663981 1880 1.391608 765 389s 6 2 2 1 143663981 185240536 671 2.092452 272 389s 7 2 3 1 185240536 246679946 1111 2.654512 414 389s tcnNbrOfHets dhNbrOfLoci dhStart dhEnd dhMean c1Mean c2Mean 389s 2 272 272 143663981 185240536 0.1762428 0.8618360 1.2306156 389s 3 414 414 185240536 246679946 0.2697420 0.9692395 1.6852728 389s 4 NA NA NA NA NA NA NA 389s 5 765 765 554484 143663981 0.4206323 0.4031263 0.9884817 389s 6 272 272 143663981 185240536 0.1762428 0.8618360 1.2306156 389s 7 414 414 185240536 246679946 0.2697420 0.9692395 1.6852728 389s > print(fit) 389s chromosome tcnId dhId start end tcnNbrOfLoci tcnMean tcnNbrOfSNPs 389s 1 1 1 1 554484 143663981 1880 1.391608 765 389s 2 1 2 1 143663981 185240536 671 2.092452 272 389s 3 1 3 1 185240536 246679946 1111 2.654512 414 389s 4 NA NA NA NA NA NA NA NA 389s 5 2 1 1 554484 143663981 1880 1.391608 765 389s 6 2 2 1 143663981 185240536 671 2.092452 272 389s 7 2 3 1 185240536 246679946 1111 2.654512 414 389s tcnNbrOfHets dhNbrOfLoci dhMean c1Mean c2Mean 389s 1 765 765 0.4206323 0.4031263 0.9884817 389s 2 272 272 0.1762428 0.8618360 1.2306156 389s 3 414 414 0.2697420 0.9692395 1.6852728 389s 4 NA NA NA NA NA 389s 5 765 765 0.4206323 0.4031263 0.9884817 389s 6 272 272 0.1762428 0.8618360 1.2306156 389s 7 414 414 0.2697420 0.9692395 1.6852728 389s > 389s > 389s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 389s > # Bootstrap segment level estimates 389s > # (used by the AB caller, which, if skipped here, 389s > # will do it automatically) 389s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 389s > fit <- bootstrapTCNandDHByRegion(fit, B=100, verbose=-10) 389s Resample (TCN,DH) signals and re-estimate summaries for segment & changepoint... 389s Already done? 389s tcn_2.5% tcn_5% tcn_95% tcn_97.5% dh_2.5% dh_5% dh_95% dh_97.5% 389s FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE 389s c1_2.5% c1_5% c1_95% c1_97.5% c2_2.5% c2_5% c2_95% c2_97.5% 389s FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE 389s Bootstrapping (TCN,DH,C1,C2) segment mean levels... 389s Identifying heterozygous & homozygous SNPs and non-polymorphic loci... 389s Number of loci: 7324 389s Number of SNPs: 2902 389s Number of non-SNPs: 4422 389s Identifying heterozygous & homozygous SNPs and non-polymorphic loci...done 389s num [1:7, 1:100, 1:4] NA NA NA NA NA NA NA NA NA NA ... 389s - attr(*, "dimnames")=List of 3 389s ..$ : NULL 389s ..$ : NULL 389s ..$ : chr [1:4] "tcn" "dh" "c1" "c2" 389s Segment #1 (chr 1, tcnId=1, dhId=1) of 7... 389s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 389s 1 1 1 1 554484 143663981 1880 1.391608 765 389s tcnNbrOfHets dhNbrOfLoci dhStart dhEnd dhMean c1Mean c2Mean 389s 1 765 765 554484 143663981 0.4206323 0.4031263 0.9884817 389s Number of TCNs: 1880 389s Number of DHs: 765 389s int [1:1880] 1 2 3 4 5 6 7 8 9 10 ... 389s int [1:7324] 1 2 3 4 5 6 7 8 9 10 ... 389s int [1:1880] 1 2 3 4 5 6 7 8 9 10 ... 389s Identify loci used to bootstrap DH means... 389s Heterozygous SNPs to resample for DH: 389s int [1:765] 2 3 4 5 6 8 9 10 11 12 ... 389s Identify loci used to bootstrap DH means...done 389s Identify loci used to bootstrap TCN means... 389s SNPs: 389s int [1:765] 2 3 4 5 6 8 9 10 11 12 ... 389s Non-polymorphic loci: 389s int [1:1115] 1 7 15 28 30 32 34 35 36 37 ... 389s Heterozygous SNPs to resample for TCN: 389s int [1:765] 2 3 4 5 6 8 9 10 11 12 ... 389s Homozygous SNPs to resample for TCN: 389s int(0) 389s Non-polymorphic loci to resample for TCN: 389s int [1:1115] 1 7 15 28 30 32 34 35 36 37 ... 389s Heterozygous SNPs with non-DH to resample for TCN: 389s int(0) 389s Loci to resample for TCN: 389s int [1:1880] 1 2 3 4 5 6 7 8 9 10 ... 389s Identify loci used to bootstrap TCN means...done 389s Number of (#hets, #homs, #nonSNPs): (765,0,1115) 389s Bootstrapping while preserving (#hets, #homs, #nonSNPs)... 389s Number of bootstrap samples: 100 389s Bootstrapping while preserving (#hets, #homs, #nonSNPs)...done 389s Segment #1 (chr 1, tcnId=1, dhId=1) of 7...done 389s Segment #2 (chr 1, tcnId=2, dhId=1) of 7... 389s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 389s 2 1 2 1 143663981 185240536 671 2.092452 272 389s tcnNbrOfHets dhNbrOfLoci dhStart dhEnd dhMean c1Mean c2Mean 389s 2 272 272 143663981 185240536 0.1762428 0.861836 1.230616 389s Number of TCNs: 671 389s Number of DHs: 272 389s int [1:671] 1881 1882 1883 1884 1885 1886 1887 1888 1889 1890 ... 389s int [1:7324] 1 2 3 4 5 6 7 8 9 10 ... 389s int [1:671] 1881 1882 1883 1884 1885 1886 1887 1888 1889 1890 ... 389s Identify loci used to bootstrap DH means... 389s Heterozygous SNPs to resample for DH: 389s int [1:272] 1888 1893 1894 1895 1896 1897 1901 1903 1907 1908 ... 389s Identify loci used to bootstrap DH means...done 389s Identify loci used to bootstrap TCN means... 389s SNPs: 389s int [1:272] 1888 1893 1894 1895 1896 1897 1901 1903 1907 1908 ... 389s Non-polymorphic loci: 389s int [1:399] 1881 1882 1883 1884 1885 1886 1887 1889 1890 1891 ... 389s Heterozygous SNPs to resample for TCN: 389s int [1:272] 1888 1893 1894 1895 1896 1897 1901 1903 1907 1908 ... 389s Homozygous SNPs to resample for TCN: 389s int(0) 389s Non-polymorphic loci to resample for TCN: 389s int [1:399] 1881 1882 1883 1884 1885 1886 1887 1889 1890 1891 ... 389s Heterozygous SNPs with non-DH to resample for TCN: 389s int(0) 389s Loci to resample for TCN: 389s int [1:671] 1881 1882 1883 1884 1885 1886 1887 1888 1889 1890 ... 389s Identify loci used to bootstrap TCN means...done 389s Number of (#hets, #homs, #nonSNPs): (272,0,399) 389s Bootstrapping while preserving (#hets, #homs, #nonSNPs)... 389s Number of bootstrap samples: 100 389s Bootstrapping while preserving (#hets, #homs, #nonSNPs)...done 389s Segment #2 (chr 1, tcnId=2, dhId=1) of 7...done 389s Segment #3 (chr 1, tcnId=3, dhId=1) of 7... 389s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 389s 3 1 3 1 185240536 246679946 1111 2.654512 414 389s tcnNbrOfHets dhNbrOfLoci dhStart dhEnd dhMean c1Mean c2Mean 389s 3 414 414 185240536 246679946 0.269742 0.9692395 1.685273 389s Number of TCNs: 1111 389s Number of DHs: 414 389s int [1:1111] 2552 2553 2554 2555 2556 2557 2558 2559 2560 2561 ... 389s int [1:7324] 1 2 3 4 5 6 7 8 9 10 ... 389s int [1:1111] 2552 2553 2554 2555 2556 2557 2558 2559 2560 2561 ... 389s Identify loci used to bootstrap DH means... 389s Heterozygous SNPs to resample for DH: 389s int [1:414] 2553 2554 2561 2562 2563 2568 2569 2572 2573 2574 ... 389s Identify loci used to bootstrap DH means...done 389s Identify loci used to bootstrap TCN means... 389s SNPs: 389s int [1:414] 2553 2554 2561 2562 2563 2568 2569 2572 2573 2574 ... 389s Non-polymorphic loci: 389s int [1:697] 2552 2555 2556 2557 2558 2559 2560 2564 2565 2566 ... 389s Heterozygous SNPs to resample for TCN: 389s int [1:414] 2553 2554 2561 2562 2563 2568 2569 2572 2573 2574 ... 389s Homozygous SNPs to resample for TCN: 389s int(0) 389s Non-polymorphic loci to resample for TCN: 389s int [1:697] 2552 2555 2556 2557 2558 2559 2560 2564 2565 2566 ... 389s Heterozygous SNPs with non-DH to resample for TCN: 389s int(0) 389s Loci to resample for TCN: 389s int [1:1111] 2552 2553 2554 2555 2556 2557 2558 2559 2560 2561 ... 389s Identify loci used to bootstrap TCN means...done 389s Number of (#hets, #homs, #nonSNPs): (414,0,697) 389s Bootstrapping while preserving (#hets, #homs, #nonSNPs)... 389s Number of bootstrap samples: 100 389s Bootstrapping while preserving (#hets, #homs, #nonSNPs)...done 389s Segment #3 (chr 1, tcnId=3, dhId=1) of 7...done 389s Segment #5 (chr 2, tcnId=1, dhId=1) of 7... 389s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 389s 5 2 1 1 554484 143663981 1880 1.391608 765 389s tcnNbrOfHets dhNbrOfLoci dhStart dhEnd dhMean c1Mean c2Mean 389s 5 765 765 554484 143663981 0.4206323 0.4031263 0.9884817 389s Number of TCNs: 1880 389s Number of DHs: 765 389s int [1:1880] 3663 3664 3665 3666 3667 3668 3669 3670 3671 3672 ... 389s int [1:7324] 1 2 3 4 5 6 7 8 9 10 ... 389s int [1:1880] 3663 3664 3665 3666 3667 3668 3669 3670 3671 3672 ... 389s Identify loci used to bootstrap DH means... 389s Heterozygous SNPs to resample for DH: 389s int [1:765] 3664 3665 3666 3667 3668 3670 3671 3672 3673 3674 ... 389s Identify loci used to bootstrap DH means...done 389s Identify loci used to bootstrap TCN means... 389s SNPs: 389s int [1:765] 3664 3665 3666 3667 3668 3670 3671 3672 3673 3674 ... 389s Non-polymorphic loci: 389s int [1:1115] 3663 3669 3677 3690 3692 3694 3696 3697 3698 3699 ... 389s Heterozygous SNPs to resample for TCN: 389s int [1:765] 3664 3665 3666 3667 3668 3670 3671 3672 3673 3674 ... 389s Homozygous SNPs to resample for TCN: 389s int(0) 389s Non-polymorphic loci to resample for TCN: 389s int [1:1115] 3663 3669 3677 3690 3692 3694 3696 3697 3698 3699 ... 389s Heterozygous SNPs with non-DH to resample for TCN: 389s int(0) 389s Loci to resample for TCN: 389s int [1:1880] 3663 3664 3665 3666 3667 3668 3669 3670 3671 3672 ... 389s Identify loci used to bootstrap TCN means...done 389s Number of (#hets, #homs, #nonSNPs): (765,0,1115) 389s Bootstrapping while preserving (#hets, #homs, #nonSNPs)... 389s Number of bootstrap samples: 100 389s Bootstrapping while preserving (#hets, #homs, #nonSNPs)...done 389s Segment #5 (chr 2, tcnId=1, dhId=1) of 7...done 389s Segment #6 (chr 2, tcnId=2, dhId=1) of 7... 389s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 389s 6 2 2 1 143663981 185240536 671 2.092452 272 389s tcnNbrOfHets dhNbrOfLoci dhStart dhEnd dhMean c1Mean c2Mean 389s 6 272 272 143663981 185240536 0.1762428 0.861836 1.230616 389s Number of TCNs: 671 389s Number of DHs: 272 389s int [1:671] 5543 5544 5545 5546 5547 5548 5549 5550 5551 5552 ... 389s int [1:7324] 1 2 3 4 5 6 7 8 9 10 ... 389s int [1:671] 5543 5544 5545 5546 5547 5548 5549 5550 5551 5552 ... 389s Identify loci used to bootstrap DH means... 389s Heterozygous SNPs to resample for DH: 389s int [1:272] 5550 5555 5556 5557 5558 5559 5563 5565 5569 5570 ... 389s Identify loci used to bootstrap DH means...done 389s Identify loci used to bootstrap TCN means... 389s SNPs: 389s int [1:272] 5550 5555 5556 5557 5558 5559 5563 5565 5569 5570 ... 389s Non-polymorphic loci: 389s int [1:399] 5543 5544 5545 5546 5547 5548 5549 5551 5552 5553 ... 389s Heterozygous SNPs to resample for TCN: 389s int [1:272] 5550 5555 5556 5557 5558 5559 5563 5565 5569 5570 ... 389s Homozygous SNPs to resample for TCN: 389s int(0) 389s Non-polymorphic loci to resample for TCN: 389s int [1:399] 5543 5544 5545 5546 5547 5548 5549 5551 5552 5553 ... 389s Heterozygous SNPs with non-DH to resample for TCN: 389s int(0) 389s Loci to resample for TCN: 389s int [1:671] 5543 5544 5545 5546 5547 5548 5549 5550 5551 5552 ... 389s Identify loci used to bootstrap TCN means...done 389s Number of (#hets, #homs, #nonSNPs): (272,0,399) 389s Bootstrapping while preserving (#hets, #homs, #nonSNPs)... 389s Number of bootstrap samples: 100 389s Bootstrapping while preserving (#hets, #homs, #nonSNPs)...done 389s Segment #6 (chr 2, tcnId=2, dhId=1) of 7...done 389s Segment #7 (chr 2, tcnId=3, dhId=1) of 7... 389s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 389s 7 2 3 1 185240536 246679946 1111 2.654512 414 389s tcnNbrOfHets dhNbrOfLoci dhStart dhEnd dhMean c1Mean c2Mean 389s 7 414 414 185240536 246679946 0.269742 0.9692395 1.685273 389s Number of TCNs: 1111 389s Number of DHs: 414 389s int [1:1111] 6214 6215 6216 6217 6218 6219 6220 6221 6222 6223 ... 389s int [1:7324] 1 2 3 4 5 6 7 8 9 10 ... 389s int [1:1111] 6214 6215 6216 6217 6218 6219 6220 6221 6222 6223 ... 389s Identify loci used to bootstrap DH means... 389s Heterozygous SNPs to resample for DH: 389s int [1:414] 6215 6216 6223 6224 6225 6230 6231 6234 6235 6236 ... 389s Identify loci used to bootstrap DH means...done 389s Identify loci used to bootstrap TCN means... 389s SNPs: 389s int [1:414] 6215 6216 6223 6224 6225 6230 6231 6234 6235 6236 ... 389s Non-polymorphic loci: 389s int [1:697] 6214 6217 6218 6219 6220 6221 6222 6226 6227 6228 ... 389s Heterozygous SNPs to resample for TCN: 389s int [1:414] 6215 6216 6223 6224 6225 6230 6231 6234 6235 6236 ... 389s Homozygous SNPs to resample for TCN: 389s int(0) 389s Non-polymorphic loci to resample for TCN: 389s int [1:697] 6214 6217 6218 6219 6220 6221 6222 6226 6227 6228 ... 389s Heterozygous SNPs with non-DH to resample for TCN: 389s int(0) 389s Loci to resample for TCN: 389s int [1:1111] 6214 6215 6216 6217 6218 6219 6220 6221 6222 6223 ... 389s Identify loci used to bootstrap TCN means...done 389s Number of (#hets, #homs, #nonSNPs): (414,0,697) 389s Bootstrapping while preserving (#hets, #homs, #nonSNPs)... 389s Number of bootstrap samples: 100 389s Bootstrapping while preserving (#hets, #homs, #nonSNPs)...done 389s Segment #7 (chr 2, tcnId=3, dhId=1) of 7...done 389s Bootstrapped segment mean levels 389s num [1:7, 1:100, 1:4] 1.4 2.09 2.64 NA 1.39 ... 389s - attr(*, "dimnames")=List of 3 389s ..$ : NULL 389s ..$ : NULL 389s ..$ : chr [1:4] "tcn" "dh" "c1" "c2" 389s Calculating (C1,C2) mean levels from (TCN,DH) mean levels... 389s num [1:7, 1:100, 1:4] 1.4 2.09 2.64 NA 1.39 ... 389s - attr(*, "dimnames")=List of 3 389s ..$ : NULL 389s ..$ : NULL 389s ..$ : chr [1:4] "tcn" "dh" "c1" "c2" 389s Calculating (C1,C2) mean levels from (TCN,DH) mean levels...done 389s Calculating polar (alpha,radius,manhattan) for change points... 389s num [1:6, 1:100, 1:2] -0.448 -0.131 NA NA -0.477 ... 389s - attr(*, "dimnames")=List of 3 389s ..$ : NULL 389s ..$ : NULL 389s ..$ : chr [1:2] "c1" "c2" 389s Bootstrapped change points 389s num [1:6, 1:100, 1:5] -2.65 -1.87 NA NA -2.72 ... 389s - attr(*, "dimnames")=List of 3 389s ..$ : NULL 389s ..$ : NULL 389s ..$ : chr [1:5] "alpha" "radius" "manhattan" "d1" ... 389s Calculating polar (alpha,radius,manhattan) for change points...done 389s Bootstrapping (TCN,DH,C1,C2) segment mean levels...done 389s Summarizing bootstrapped segment ('tcn', 'dh', 'c1', 'c2') data... 389s num [1:7, 1:4, 1:4] NA NA NA NA NA NA NA NA NA NA ... 389s - attr(*, "dimnames")=List of 3 389s ..$ : NULL 389s ..$ : chr [1:4] "2.5%" "5%" "95%" "97.5%" 389s ..$ : chr [1:4] "tcn" "dh" "c1" "c2" 389s Field #1 ('tcn') of 4... 389s Segment #1 of 7... 389s Segment #1 of 7...done 389s Segment #2 of 7... 389s Segment #2 of 7...done 389s Segment #3 of 7... 389s Segment #3 of 7...done 389s Segment #4 of 7... 389s Segment #4 of 7...done 389s Segment #5 of 7... 389s Segment #5 of 7...done 389s Segment #6 of 7... 389s Segment #6 of 7...done 389s Segment #7 of 7... 389s Segment #7 of 7...done 389s Field #1 ('tcn') of 4...done 389s Field #2 ('dh') of 4... 389s Segment #1 of 7... 389s Segment #1 of 7...done 389s Segment #2 of 7... 389s Segment #2 of 7...done 389s Segment #3 of 7... 389s Segment #3 of 7...done 389s Segment #4 of 7... 389s Segment #4 of 7...done 389s Segment #5 of 7... 389s Segment #5 of 7...done 389s Segment #6 of 7... 389s Segment #6 of 7...done 389s Segment #7 of 7... 389s Segment #7 of 7...done 389s Field #2 ('dh') of 4...done 389s Field #3 ('c1') of 4... 389s Segment #1 of 7... 389s Segment #1 of 7...done 389s Segment #2 of 7... 389s Segment #2 of 7...done 389s Segment #3 of 7... 389s Segment #3 of 7...done 389s Segment #4 of 7... 389s Segment #4 of 7...done 389s Segment #5 of 7... 389s Segment #5 of 7...done 389s Segment #6 of 7... 389s Segment #6 of 7...done 389s Segment #7 of 7... 389s Segment #7 of 7...done 389s Field #3 ('c1') of 4...done 389s Field #4 ('c2') of 4... 389s Segment #1 of 7... 389s Segment #1 of 7...done 389s Segment #2 of 7... 389s Segment #2 of 7...done 389s Segment #3 of 7... 389s Segment #3 of 7...done 389s Segment #4 of 7... 389s Segment #4 of 7...done 389s Segment #5 of 7... 389s Segment #5 of 7...done 389s Segment #6 of 7... 389s Segment #6 of 7...done 389s Segment #7 of 7... 389s Segment #7 of 7...done 389s Field #4 ('c2') of 4...done 389s Bootstrap statistics 389s num [1:7, 1:4, 1:4] 1.38 2.07 2.63 NA 1.38 ... 389s - attr(*, "dimnames")=List of 3 389s ..$ : NULL 389s ..$ : chr [1:4] "2.5%" "5%" "95%" "97.5%" 389s ..$ : chr [1:4] "tcn" "dh" "c1" "c2" 389s Statistical sanity checks (iff B >= 100)... 389s Available summaries: 2.5%, 5%, 95%, 97.5% 389s Available quantiles: 0.025, 0.05, 0.95, 0.975 389s num [1:7, 1:4, 1:4] 1.38 2.07 2.63 NA 1.38 ... 389s - attr(*, "dimnames")=List of 3 389s ..$ : NULL 389s ..$ : chr [1:4] "2.5%" "5%" "95%" "97.5%" 389s ..$ : chr [1:4] "tcn" "dh" "c1" "c2" 389s Field #1 ('tcn') of 4... 389s Seg 1. mean=1.39161, range=[1.38025,1.40693], n=1880 389s Seg 2. mean=2.09245, range=[2.06856,2.1165], n=671 389s Seg 3. mean=2.65451, range=[2.62678,2.6834], n=1111 389s Seg 4. mean=NA, range=[NA,NA], n=NA 389s Seg 5. mean=1.39161, range=[1.37999,1.40474], n=1880 389s Seg 6. mean=2.09245, range=[2.06923,2.11747], n=671 389s Seg 7. mean=2.65451, range=[2.62867,2.68639], n=1111 389s Field #1 ('tcn') of 4...done 389s Field #2 ('dh') of 4... 389s Seg 1. mean=0.420632, range=[0.406983,0.437756], n=765 389s Seg 2. mean=0.176243, range=[0.141232,0.202975], n=272 389s Seg 3. mean=0.269742, range=[0.245337,0.292784], n=414 389s Seg 4. mean=NA, range=[NA,NA], n=NA 389s Seg 5. mean=0.420632, range=[0.406204,0.436189], n=765 389s Seg 6. mean=0.176243, range=[0.13696,0.212132], n=272 389s Seg 7. mean=0.269742, range=[0.230034,0.296763], n=414 389s Field #2 ('dh') of 4...done 389s Field #3 ('c1') of 4... 389s Seg 1. mean=0.403126, range=[0.391189,0.413437], n=765 389s Seg 2. mean=0.861836, range=[0.833296,0.900874], n=272 389s Seg 3. mean=0.969239, range=[0.937437,1.00659], n=414 389s Seg 4. mean=NA, range=[NA,NA], n=NA 389s Seg 5. mean=0.403126, range=[0.392112,0.414529], n=765 389s Seg 6. mean=0.861836, range=[0.823193,0.907577], n=272 389s Seg 7. mean=0.969239, range=[0.931951,1.01968], n=414 389s Field #3 ('c1') of 4...done 389s Field #4 ('c2') of 4... 389s Seg 1. mean=0.988482, range=[0.974501,1.00244], n=765 389s Seg 2. mean=1.23062, range=[1.18964,1.26157], n=272 389s Seg 3. mean=1.68527, range=[1.6481,1.72497], n=414 389s Seg 4. mean=NA, range=[NA,NA], n=NA 389s Seg 5. mean=0.988482, range=[0.9761,1.00076], n=765 389s Seg 6. mean=1.23062, range=[1.18936,1.26647], n=272 389s Seg 7. mean=1.68527, range=[1.63171,1.72526], n=414 389s Field #4 ('c2') of 4...done 389s Statistical sanity checks (iff B >= 100)...done 389s Summarizing bootstrapped segment ('tcn', 'dh', 'c1', 'c2') data...done 389s Summarizing bootstrapped changepoint ('alpha', 'radius', 'manhattan', 'd1', 'd2') data... 389s num [1:6, 1:4, 1:5] NA NA NA NA NA NA NA NA NA NA ... 389s - attr(*, "dimnames")=List of 3 389s ..$ : NULL 389s ..$ : chr [1:4] "2.5%" "5%" "95%" "97.5%" 389s ..$ : chr [1:5] "alpha" "radius" "manhattan" "d1" ... 389s Field #1 ('alpha') of 5... 389s Changepoint #1 of 6... 389s Changepoint #1 of 6...done 389s Changepoint #2 of 6... 389s Changepoint #2 of 6...done 389s Changepoint #3 of 6... 389s Changepoint #3 of 6...done 389s Changepoint #4 of 6... 389s Changepoint #4 of 6...done 389s Changepoint #5 of 6... 389s Changepoint #5 of 6...done 389s Changepoint #6 of 6... 389s Changepoint #6 of 6...done 389s Field #1 ('alpha') of 5...done 389s Field #2 ('radius') of 5... 389s Changepoint #1 of 6... 389s Changepoint #1 of 6...done 389s Changepoint #2 of 6... 389s Changepoint #2 of 6...done 389s Changepoint #3 of 6... 389s Changepoint #3 of 6...done 389s Changepoint #4 of 6... 389s Changepoint #4 of 6...done 389s Changepoint #5 of 6... 389s Changepoint #5 of 6...done 389s Changepoint #6 of 6... 389s Changepoint #6 of 6...done 389s Field #2 ('radius') of 5...done 389s Field #3 ('manhattan') of 5... 389s Changepoint #1 of 6... 389s Changepoint #1 of 6...done 389s Changepoint #2 of 6... 389s Changepoint #2 of 6...done 389s Changepoint #3 of 6... 389s Changepoint #3 of 6...done 389s Changepoint #4 of 6... 389s Changepoint #4 of 6...done 389s Changepoint #5 of 6... 389s Changepoint #5 of 6...done 389s Changepoint #6 of 6... 389s Changepoint #6 of 6...done 389s Field #3 ('manhattan') of 5...done 389s Field #4 ('d1') of 5... 389s Changepoint #1 of 6... 389s Changepoint #1 of 6...done 389s Changepoint #2 of 6... 389s Changepoint #2 of 6...done 389s Changepoint #3 of 6... 389s Changepoint #3 of 6...done 389s Changepoint #4 of 6... 389s Changepoint #4 of 6...done 389s Changepoint #5 of 6... 389s Changepoint #5 of 6...done 389s Changepoint #6 of 6... 389s Changepoint #6 of 6...done 389s Field #4 ('d1') of 5...done 389s Field #5 ('d2') of 5... 389s Changepoint #1 of 6... 389s Changepoint #1 of 6...done 389s Changepoint #2 of 6... 389s Changepoint #2 of 6...done 389s Changepoint #3 of 6... 389s Changepoint #3 of 6...done 389s Changepoint #4 of 6... 389s Changepoint #4 of 6...done 389s Changepoint #5 of 6... 389s Changepoint #5 of 6...done 389s Changepoint #6 of 6... 389s Changepoint #6 of 6...done 389s Field #5 ('d2') of 5...done 389s Bootstrap statistics 389s num [1:6, 1:4, 1:5] -2.76 -1.91 NA NA -2.76 ... 389s - attr(*, "dimnames")=List of 3 389s ..$ : NULL 389s ..$ : chr [1:4] "2.5%" "5%" "95%" "97.5%" 389s ..$ : chr [1:5] "alpha" "radius" "manhattan" "d1" ... 389s Summarizing bootstrapped changepoint ('alpha', 'radius', 'manhattan', 'd1', 'd2') data...done 389s Resample (TCN,DH) signals and re-estimate summaries for segment & changepoint...done 389s > print(fit) 389s chromosome tcnId dhId start end tcnNbrOfLoci tcnMean tcnNbrOfSNPs 389s 1 1 1 1 554484 143663981 1880 1.391608 765 389s 2 1 2 1 143663981 185240536 671 2.092452 272 389s 3 1 3 1 185240536 246679946 1111 2.654512 414 389s 4 NA NA NA NA NA NA NA NA 389s 5 2 1 1 554484 143663981 1880 1.391608 765 389s 6 2 2 1 143663981 185240536 671 2.092452 272 389s 7 2 3 1 185240536 246679946 1111 2.654512 414 389s tcnNbrOfHets dhNbrOfLoci dhMean c1Mean c2Mean 389s 1 765 765 0.4206323 0.4031263 0.9884817 389s 2 272 272 0.1762428 0.8618360 1.2306156 389s 3 414 414 0.2697420 0.9692395 1.6852728 389s 4 NA NA NA NA NA 389s 5 765 765 0.4206323 0.4031263 0.9884817 389s 6 272 272 0.1762428 0.8618360 1.2306156 389s 7 414 414 0.2697420 0.9692395 1.6852728 389s > 389s > 389s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 389s > # Calling segments in allelic balance (AB) 389s > # NOTE: Ideally, this should be done on whole-genome data 389s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 389s > # Explicitly estimate the threshold in DH for calling AB 389s > # (which be done by default by the caller, if skipped here) 389s > deltaAB <- estimateDeltaAB(fit, flavor="qq(DH)", verbose=-10) 389s Estimating DH threshold for calling allelic imbalances... 389s flavor: qq(DH) 389s scale: 1 389s Estimating DH threshold for AB caller... 389s quantile #1: 0.05 389s Symmetric quantile #2: 0.9 389s Number of segments: 6 389s Weighted 5% quantile of DH: 0.199618 389s Number of segments with small DH: 2 389s Number of data points: 1342 389s Number of finite data points: 544 389s Estimate of (1-0.9):th and 50% quantiles: (0.0289919,0.176243) 389s Estimate of 0.9:th "symmetric" quantile: 0.323494 389s Estimating DH threshold for AB caller...done 389s Estimated delta: 0.323 389s Estimating DH threshold for calling allelic imbalances...done 389s > print(deltaAB) 389s [1] 0.3234938 389s > 389s > fit <- callAB(fit, delta=deltaAB, verbose=-10) 389s Calling segments of allelic balance from one-sided DH bootstrap confidence intervals... 389s delta (offset adjusting for bias in DH): 0.323493772175137 389s alpha (CI quantile; significance level): 0.05 389s Calling segments... 389s Number of segments called allelic balance (AB): 4 (57.14%) of 7 389s Calling segments...done 389s Calling segments of allelic balance from one-sided DH bootstrap confidence intervals...done 389s > print(fit) 389s chromosome tcnId dhId start end tcnNbrOfLoci tcnMean tcnNbrOfSNPs 389s 1 1 1 1 554484 143663981 1880 1.391608 765 389s 2 1 2 1 143663981 185240536 671 2.092452 272 389s 3 1 3 1 185240536 246679946 1111 2.654512 414 389s 4 NA NA NA NA NA NA NA NA 389s 5 2 1 1 554484 143663981 1880 1.391608 765 389s 6 2 2 1 143663981 185240536 671 2.092452 272 389s 7 2 3 1 185240536 246679946 1111 2.654512 414 389s tcnNbrOfHets dhNbrOfLoci dhMean c1Mean c2Mean abCall 389s 1 765 765 0.4206323 0.4031263 0.9884817 FALSE 389s 2 272 272 0.1762428 0.8618360 1.2306156 TRUE 389s 3 414 414 0.2697420 0.9692395 1.6852728 TRUE 389s 4 NA NA NA NA NA NA 389s 5 765 765 0.4206323 0.4031263 0.9884817 FALSE 389s 6 272 272 0.1762428 0.8618360 1.2306156 TRUE 389s 7 414 414 0.2697420 0.9692395 1.6852728 TRUE 389s > 389s > 389s > # Even if not explicitly specified, the estimated 389s > # threshold parameter is returned by the caller 389s > stopifnot(fit$params$deltaAB == deltaAB) 389s > 389s > 389s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 389s > # Calling segments in loss-of-heterozygosity (LOH) 389s > # NOTE: Ideally, this should be done on whole-genome data 389s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 389s > # Explicitly estimate the threshold in C1 for calling LOH 389s > # (which be done by default by the caller, if skipped here) 389s > deltaLOH <- estimateDeltaLOH(fit, flavor="minC1|nonAB", verbose=-10) 389s Estimating DH threshold for calling LOH... 389s flavor: minC1|nonAB 389s Estimating DH threshold for calling LOH as the midpoint between guessed C1=0 and C1=1... 389s Argument 'midpoint': 0.5 389s Number of segments: 6 389s Number of segments in allelic balance: 4 (66.7%) of 6 389s Number of segments not in allelic balance: 2 (33.3%) of 6 389s Number of segments in allelic balance and TCN <= 3.00: 4 (66.7%) of 6 389s C: 2.09, 2.65, 2.09, 2.65 389s Corrected C1 (=C/2): 1.05, 1.33, 1.05, 1.33 389s Number of DHs: 272, 414, 272, 414 389s Weights: 0.198, 0.302, 0.198, 0.302 389s Weighted median of (corrected) C1 in allelic balance: 1.274 389s Smallest C1 among segments not in allelic balance: 0.403 389s There are 2 segments with in total 765 heterozygous SNPs with this level. 389s There are 2 segments with in total 765 heterozygous SNPs with this level. 389s Midpoint between the two: 0.839 389s Estimating DH threshold for calling LOH as the midpoint between guessed C1=0 and C1=1...done 389s delta: 0.839 389s Estimating DH threshold for calling LOH...done 389s > print(deltaLOH) 389s [1] 0.838563 389s > 389s > fit <- callLOH(fit, delta=deltaLOH, verbose=-10) 389s Calling segments of allelic balance from one-sided DH bootstrap confidence intervals... 389s delta (offset adjusting for bias in C1): 0.838562992888546 389s alpha (CI quantile; significance level): 0.05 389s Calling segments... 389s Number of segments called low C1 (LowC1, "LOH_C1"): 3 (42.86%) of 7 389s Calling segments...done 389s Calling segments of allelic balance from one-sided DH bootstrap confidence intervals...done 389s > print(fit) 389s chromosome tcnId dhId start end tcnNbrOfLoci tcnMean tcnNbrOfSNPs 389s 1 1 1 1 554484 143663981 1880 1.391608 765 389s 2 1 2 1 143663981 185240536 671 2.092452 272 389s 3 1 3 1 185240536 246679946 1111 2.654512 414 389s 4 NA NA NA NA NA NA NA NA 389s 5 2 1 1 554484 143663981 1880 1.391608 765 389s 6 2 2 1 143663981 185240536 671 2.092452 272 389s 7 2 3 1 185240536 246679946 1111 2.654512 414 389s tcnNbrOfHets dhNbrOfLoci dhMean c1Mean c2Mean abCall lohCall 389s 1 765 765 0.4206323 0.4031263 0.9884817 FALSE TRUE 389s 2 272 272 0.1762428 0.8618360 1.2306156 TRUE NA 389s 3 414 414 0.2697420 0.9692395 1.6852728 TRUE FALSE 389s 4 NA NA NA NA NA NA NA 389s 5 765 765 0.4206323 0.4031263 0.9884817 FALSE TRUE 389s 6 272 272 0.1762428 0.8618360 1.2306156 TRUE FALSE 389s 7 414 414 0.2697420 0.9692395 1.6852728 TRUE FALSE 389s > plotTracks(fit) 389s > 389s > # Even if not explicitly specified, the estimated 389s > # threshold parameter is returned by the caller 389s > stopifnot(fit$params$deltaLOH == deltaLOH) 389s > 389s > proc.time() 389s user system elapsed 389s 1.943 0.094 2.026 389s Test segmentByNonPairedPSCBS,medianDH passed 389s 0 389s Begin test segmentByPairedPSCBS,DH 389s + [ 0 != 0 ] 389s + echo Test segmentByNonPairedPSCBS,medianDH passed 389s + echo 0 389s + echo Begin test segmentByPairedPSCBS,DH 389s + exitcode=0 389s + R CMD BATCH segmentByPairedPSCBS,DH.R 392s + cat segmentByPairedPSCBS,DH.Rout 392s 392s R version 4.5.2 (2025-10-31) -- "[Not] Part in a Rumble" 392s Copyright (C) 2025 The R Foundation for Statistical Computing 392s Platform: aarch64-unknown-linux-gnu 392s 392s R is free software and comes with ABSOLUTELY NO WARRANTY. 392s You are welcome to redistribute it under certain conditions. 392s Type 'license()' or 'licence()' for distribution details. 392s 392s R is a collaborative project with many contributors. 392s Type 'contributors()' for more information and 392s 'citation()' on how to cite R or R packages in publications. 392s 392s Type 'demo()' for some demos, 'help()' for on-line help, or 392s 'help.start()' for an HTML browser interface to help. 392s Type 'q()' to quit R. 392s 392s [Previously saved workspace restored] 392s 392s > library("PSCBS") 392s PSCBS v0.68.0 (2025-04-18 19:40:02 UTC) successfully loaded. See ?PSCBS for help. 392s > 392s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 392s > # Load SNP microarray data 392s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 392s > data <- PSCBS::exampleData("paired.chr01") 392s > str(data) 392s 'data.frame': 73346 obs. of 6 variables: 392s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 392s $ x : int 1145994 2224111 2319424 2543484 2926730 2941694 3084986 3155127 3292731 3695086 ... 392s $ CT : num 1.625 1.071 1.406 1.18 0.856 ... 392s $ betaT : num 0.757 0.771 0.834 0.778 0.229 ... 392s $ CN : num 2.36 2.13 2.59 1.93 1.71 ... 392s $ betaN : num 0.827 0.875 0.887 0.884 0.103 ... 392s > 392s > # Drop single-locus outliers 392s > dataS <- dropSegmentationOutliers(data) 392s > 392s > # Run light-weight tests 392s > # Use only every 5th data point 392s > dataS <- dataS[seq(from=1, to=nrow(data), by=5),] 392s > # Number of segments (for assertion) 392s > nSegs <- 3L 392s > # Number of bootstrap samples (see below) 392s > B <- 100L 392s > 392s > str(dataS) 392s 'data.frame': 14670 obs. of 6 variables: 392s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 392s $ x : int 1145994 2941694 3710825 4240737 4276892 4464544 4714611 5095111 5034491 5158416 ... 392s $ CT : num 1.63 1.4 1.41 1.17 1.16 ... 392s $ betaT : num 0.7574 0.169 0.2357 0.2604 0.0576 ... 392s $ CN : num 2.36 2.13 2.26 2.01 2.32 ... 392s $ betaN : num 0.8274 0.5072 0.1671 0.1609 0.0421 ... 392s > R.oo::attachLocally(dataS) 392s > 392s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 392s > # Calculate DH 392s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 392s > muN <- aroma.light::callNaiveGenotypes(betaN, censorAt=c(0,1)) 392s > # SNPs are identifies as those loci that have non-missing 'betaT' & 'muN' 392s > isSnp <- (!is.na(betaT) & !is.na(muN)) 392s > isHet <- isSnp & (muN == 1/2) 392s > rho <- rep(NA_real_, length=length(muN)) 392s > rho[isHet] <- 2*abs(betaT[isHet]-1/2) 392s > 392s > 392s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 392s > # Paired PSCBS segmentation using TCN and DH only 392s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 392s > fit <- segmentByPairedPSCBS(CT, rho=rho, 392s + chromosome=chromosome, x=x, 392s + seed=0xBEEF, verbose=-10) 392s Segmenting paired tumor-normal signals using Paired PSCBS... 392s Setup up data... 392s 'data.frame': 14670 obs. of 4 variables: 392s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 392s $ x : num 1145994 2941694 3710825 4240737 4276892 ... 392s $ CT : num 1.63 1.4 1.41 1.17 1.16 ... 392s $ rho : num NA 0.662 NA NA NA ... 392s Setup up data...done 392s Dropping loci for which TCNs are missing... 392s Number of loci dropped: 12 392s Dropping loci for which TCNs are missing...done 392s Ordering data along genome... 392s 'data.frame': 14658 obs. of 4 variables: 392s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 392s $ x : num 554484 730720 782343 878522 916294 ... 392s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 392s $ rho : num NA NA NA NA NA ... 392s Ordering data along genome...done 392s Keeping only current chromosome for 'knownSegments'... 392s Chromosome: 1 392s Known segments for this chromosome: 392s [1] chromosome start end 392s <0 rows> (or 0-length row.names) 392s Keeping only current chromosome for 'knownSegments'...done 392s alphaTCN: 0.009 392s alphaDH: 0.001 392s Number of loci: 14658 392s Random seed temporarily set (seed=c(48879), kind="L'Ecuyer-CMRG") 392s Produced 2 seeds from this stream for future usage 392s Identification of change points by total copy numbers... 392s Segmenting by CBS... 392s Chromosome: 1 392s Random seed temporarily set (seed=c(10407, 1066287653, -51199871, 161854402, -1995183193, 1503453565, -747102133), kind="L'Ecuyer-CMRG") 392s Segmenting by CBS...done 392s List of 4 392s $ data :'data.frame': 14658 obs. of 4 variables: 392s ..$ chromosome: int [1:14658] 1 1 1 1 1 1 1 1 1 1 ... 392s ..$ x : num [1:14658] 554484 730720 782343 878522 916294 ... 392s ..$ y : num [1:14658] 1.88 1.8 1.59 1.64 1.53 ... 392s ..$ index : int [1:14658] 1 2 3 4 5 6 7 8 9 10 ... 392s $ output :'data.frame': 3 obs. of 6 variables: 392s ..$ sampleName: chr [1:3] NA NA NA 392s ..$ chromosome: int [1:3] 1 1 1 392s ..$ start : num [1:3] 5.54e+05 1.44e+08 1.85e+08 392s ..$ end : num [1:3] 1.44e+08 1.85e+08 2.47e+08 392s ..$ nbrOfLoci : int [1:3] 7599 2668 4391 392s ..$ mean : num [1:3] 1.39 2.07 2.63 392s $ segRows:'data.frame': 3 obs. of 2 variables: 392s ..$ startRow: int [1:3] 1 7600 10268 392s ..$ endRow : int [1:3] 7599 10267 14658 392s $ params :List of 5 392s ..$ alpha : num 0.009 392s ..$ undo : num 0 392s ..$ joinSegments : logi TRUE 392s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 392s .. ..$ chromosome: int 1 392s .. ..$ start : num -Inf 392s .. ..$ end : num Inf 392s ..$ seed : int [1:7] 10407 1066287653 -51199871 161854402 -1995183193 1503453565 -747102133 392s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 392s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.368 0 0.369 0 0 392s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 392s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 392s - attr(*, "randomSeed")= int [1:7] 10407 1066287653 -51199871 161854402 -1995183193 1503453565 -747102133 392s Identification of change points by total copy numbers...done 392s Restructure TCN segmentation results... 392s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean 392s 1 1 554484 143926517 7599 1.3859 392s 2 1 143926517 185449813 2668 2.0704 392s 3 1 185449813 247137334 4391 2.6341 392s Number of TCN segments: 3 392s Restructure TCN segmentation results...done 392s Total CN segment #1 ([ 554484,1.43927e+08]) of 3... 392s Number of TCN loci in segment: 7599 392s Locus data for TCN segment: 392s 'data.frame': 7599 obs. of 5 variables: 392s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 392s $ x : num 554484 730720 782343 878522 916294 ... 392s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 392s $ rho : num NA NA NA NA NA ... 392s $ index : int 1 2 3 4 5 6 7 8 9 10 ... 392s Number of loci: 7599 392s Number of SNPs: 2111 (27.78%) 392s Number of heterozygous SNPs: 2111 (100.00%) 392s Chromosome: 1 392s Segmenting DH signals... 392s Segmenting by CBS... 392s Chromosome: 1 392s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 392s Segmenting by CBS...done 392s List of 4 392s $ data :'data.frame': 7599 obs. of 4 variables: 392s ..$ chromosome: int [1:7599] 1 1 1 1 1 1 1 1 1 1 ... 392s ..$ x : num [1:7599] 554484 730720 782343 878522 916294 ... 392s ..$ y : num [1:7599] NA NA NA NA NA ... 392s ..$ index : int [1:7599] 1 2 3 4 5 6 7 8 9 10 ... 392s $ output :'data.frame': 1 obs. of 6 variables: 392s ..$ sampleName: chr NA 392s ..$ chromosome: int 1 392s ..$ start : num 554484 392s ..$ end : num 1.44e+08 392s ..$ nbrOfLoci : int 2111 392s ..$ mean : num 0.524 392s $ segRows:'data.frame': 1 obs. of 2 variables: 392s ..$ startRow: int 10 392s ..$ endRow : int 7594 392s $ params :List of 5 392s ..$ alpha : num 0.001 392s ..$ undo : num 0 392s ..$ joinSegments : logi TRUE 392s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 392s .. ..$ chromosome: int 1 392s .. ..$ start : num 554484 392s .. ..$ end : num 1.44e+08 392s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 392s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 392s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.026 0 0.026 0 0 392s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 392s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 392s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 392s DH segmentation (locally-indexed) rows: 392s startRow endRow 392s 1 10 7594 392s int [1:7599] 1 2 3 4 5 6 7 8 9 10 ... 392s DH segmentation rows: 392s startRow endRow 392s 1 10 7594 392s Segmenting DH signals...done 392s DH segmentation table: 392s dhStart dhEnd dhNbrOfLoci dhMean 392s 1 554484 143926517 2111 0.5237 392s startRow endRow 392s 1 10 7594 392s Rows: 392s [1] 1 392s TCN segmentation rows: 392s startRow endRow 392s 1 1 7599 392s TCN and DH segmentation rows: 392s startRow endRow 392s 1 1 7599 392s startRow endRow 392s 1 10 7594 392s NULL 392s TCN segmentation (expanded) rows: 392s startRow endRow 392s 1 1 7599 392s TCN and DH segmentation rows: 392s startRow endRow 392s 1 1 7599 392s 2 7600 10267 392s 3 10268 14658 392s startRow endRow 392s 1 10 7594 392s startRow endRow 392s 1 1 7599 392s Total CN segmentation table (expanded): 392s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 392s 1 1 554484 143926517 7599 1.3859 2111 2111 392s (TCN,DH) segmentation for one total CN segment: 392s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 392s 1 1 1 1 554484 143926517 7599 1.3859 2111 392s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 392s 1 2111 554484 143926517 2111 0.5237 392s Total CN segment #1 ([ 554484,1.43927e+08]) of 3...done 392s Total CN segment #2 ([1.43927e+08,1.8545e+08]) of 3... 392s Number of TCN loci in segment: 2668 392s Locus data for TCN segment: 392s 'data.frame': 2668 obs. of 5 variables: 392s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 392s $ x : num 1.44e+08 1.44e+08 1.44e+08 1.44e+08 1.44e+08 ... 392s $ CT : num 2.1 2.1 2.09 1.8 2.34 ... 392s $ rho : num NA NA NA NA NA NA NA NA NA NA ... 392s $ index : int 7600 7601 7602 7603 7604 7605 7606 7607 7608 7609 ... 392s Number of loci: 2668 392s Number of SNPs: 774 (29.01%) 392s Number of heterozygous SNPs: 774 (100.00%) 392s Chromosome: 1 392s Segmenting DH signals... 392s Segmenting by CBS... 392s Chromosome: 1 392s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 392s Segmenting by CBS...done 392s List of 4 392s $ data :'data.frame': 2668 obs. of 4 variables: 392s ..$ chromosome: int [1:2668] 1 1 1 1 1 1 1 1 1 1 ... 392s ..$ x : num [1:2668] 1.44e+08 1.44e+08 1.44e+08 1.44e+08 1.44e+08 ... 392s ..$ y : num [1:2668] NA NA NA NA NA NA NA NA NA NA ... 392s ..$ index : int [1:2668] 1 2 3 4 5 6 7 8 9 10 ... 392s $ output :'data.frame': 1 obs. of 6 variables: 392s ..$ sampleName: chr NA 392s ..$ chromosome: int 1 392s ..$ start : num 1.44e+08 392s ..$ end : num 1.85e+08 392s ..$ nbrOfLoci : int 774 392s ..$ mean : num 0.154 392s $ segRows:'data.frame': 1 obs. of 2 variables: 392s ..$ startRow: int 15 392s ..$ endRow : int 2664 392s $ params :List of 5 392s ..$ alpha : num 0.001 392s ..$ undo : num 0 392s ..$ joinSegments : logi TRUE 392s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 392s .. ..$ chromosome: int 1 392s .. ..$ start : num 1.44e+08 392s .. ..$ end : num 1.85e+08 392s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 392s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 392s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.009 0 0.009 0 0 392s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 392s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 392s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 392s DH segmentation (locally-indexed) rows: 392s startRow endRow 392s 1 15 2664 392s int [1:2668] 7600 7601 7602 7603 7604 7605 7606 7607 7608 7609 ... 392s DH segmentation rows: 392s startRow endRow 392s 1 7614 10263 392s Segmenting DH signals...done 392s DH segmentation table: 392s dhStart dhEnd dhNbrOfLoci dhMean 392s 1 143926517 185449813 774 0.1542 392s startRow endRow 392s 1 7614 10263 392s Rows: 392s [1] 2 392s TCN segmentation rows: 392s startRow endRow 392s 2 7600 10267 392s TCN and DH segmentation rows: 392s startRow endRow 392s 2 7600 10267 392s startRow endRow 392s 1 7614 10263 392s startRow endRow 392s 1 1 7599 392s TCN segmentation (expanded) rows: 392s startRow endRow 392s 1 1 7599 392s 2 7600 10267 392s TCN and DH segmentation rows: 392s startRow endRow 392s 1 1 7599 392s 2 7600 10267 392s 3 10268 14658 392s startRow endRow 392s 1 10 7594 392s 2 7614 10263 392s startRow endRow 392s 1 1 7599 392s 2 7600 10267 392s Total CN segmentation table (expanded): 392s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 392s 2 1 143926517 185449813 2668 2.0704 774 774 392s (TCN,DH) segmentation for one total CN segment: 392s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 392s 2 2 1 1 143926517 185449813 2668 2.0704 774 392s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 392s 2 774 143926517 185449813 774 0.1542 392s Total CN segment #2 ([1.43927e+08,1.8545e+08]) of 3...done 392s Total CN segment #3 ([1.8545e+08,2.47137e+08]) of 3... 392s Number of TCN loci in segment: 4391 392s Locus data for TCN segment: 392s 'data.frame': 4391 obs. of 5 variables: 392s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 392s $ x : num 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 392s $ CT : num 2.93 2.15 2.82 2.93 2.46 ... 392s $ rho : num NA 0.0308 NA 0.2533 NA ... 392s $ index : int 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 392s Number of loci: 4391 392s Number of SNPs: 1311 (29.86%) 392s Number of heterozygous SNPs: 1311 (100.00%) 392s Chromosome: 1 392s Segmenting DH signals... 392s Segmenting by CBS... 392s Chromosome: 1 392s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 392s Segmenting by CBS...done 392s List of 4 392s $ data :'data.frame': 4391 obs. of 4 variables: 392s ..$ chromosome: int [1:4391] 1 1 1 1 1 1 1 1 1 1 ... 392s ..$ x : num [1:4391] 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 392s ..$ y : num [1:4391] NA 0.0308 NA 0.2533 NA ... 392s ..$ index : int [1:4391] 1 2 3 4 5 6 7 8 9 10 ... 392s $ output :'data.frame': 1 obs. of 6 variables: 392s ..$ sampleName: chr NA 392s ..$ chromosome: int 1 392s ..$ start : num 1.85e+08 392s ..$ end : num 2.47e+08 392s ..$ nbrOfLoci : int 1311 392s ..$ mean : num 0.251 392s $ segRows:'data.frame': 1 obs. of 2 variables: 392s ..$ startRow: int 2 392s ..$ endRow : int 4388 392s $ params :List of 5 392s ..$ alpha : num 0.001 392s ..$ undo : num 0 392s ..$ joinSegments : logi TRUE 392s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 392s .. ..$ chromosome: int 1 392s .. ..$ start : num 1.85e+08 392s .. ..$ end : num 2.47e+08 392s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 392s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 392s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.02 0 0.02 0 0 392s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 392s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 392s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 392s DH segmentation (locally-indexed) rows: 392s startRow endRow 392s 1 2 4388 392s int [1:4391] 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 392s DH segmentation rows: 392s startRow endRow 392s 1 10269 14655 392s Segmenting DH signals...done 392s DH segmentation table: 392s dhStart dhEnd dhNbrOfLoci dhMean 392s + [ 0 != 0 ] 392s + echo Test segmentByPairedPSCBS,DH passed 392s + echo 0 392s + echo Begin test segmentByPairedPSCBS,calls 392s + exitcode=0 392s + R CMD BATCH segmentByPairedPSCBS,calls.R 392s 1 185449813 247137334 1311 0.2512 392s startRow endRow 392s 1 10269 14655 392s Rows: 392s [1] 3 392s TCN segmentation rows: 392s startRow endRow 392s 3 10268 14658 392s TCN and DH segmentation rows: 392s startRow endRow 392s 3 10268 14658 392s startRow endRow 392s 1 10269 14655 392s startRow endRow 392s 1 1 7599 392s 2 7600 10267 392s TCN segmentation (expanded) rows: 392s startRow endRow 392s 1 1 7599 392s 2 7600 10267 392s 3 10268 14658 392s TCN and DH segmentation rows: 392s startRow endRow 392s 1 1 7599 392s 2 7600 10267 392s 3 10268 14658 392s startRow endRow 392s 1 10 7594 392s 2 7614 10263 392s 3 10269 14655 392s startRow endRow 392s 1 1 7599 392s 2 7600 10267 392s 3 10268 14658 392s Total CN segmentation table (expanded): 392s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 392s 3 1 185449813 247137334 4391 2.6341 1311 1311 392s (TCN,DH) segmentation for one total CN segment: 392s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 392s 3 3 1 1 185449813 247137334 4391 2.6341 1311 392s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 392s 3 1311 185449813 247137334 1311 0.2512 392s Total CN segment #3 ([1.8545e+08,2.47137e+08]) of 3...done 392s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 392s 1 1 1 1 554484 143926517 7599 1.3859 2111 392s 2 1 2 1 143926517 185449813 2668 2.0704 774 392s 3 1 3 1 185449813 247137334 4391 2.6341 1311 392s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 392s 1 2111 554484 143926517 2111 0.5237 392s 2 774 143926517 185449813 774 0.1542 392s 3 1311 185449813 247137334 1311 0.2512 392s Calculating (C1,C2) per segment... 392s Calculating (C1,C2) per segment...done 392s Number of segments: 3 392s Segmenting paired tumor-normal signals using Paired PSCBS...done 392s Post-segmenting TCNs... 392s Number of segments: 3 392s Number of chromosomes: 1 392s [1] 1 392s Chromosome 1 ('chr01') of 1... 392s Rows: 392s [1] 1 2 3 392s Number of segments: 3 392s TCN segment #1 ('1') of 3... 392s Nothing todo. Only one DH segmentation. Skipping. 392s TCN segment #1 ('1') of 3...done 392s TCN segment #2 ('2') of 3... 392s Nothing todo. Only one DH segmentation. Skipping. 392s TCN segment #2 ('2') of 3...done 392s TCN segment #3 ('3') of 3... 392s Nothing todo. Only one DH segmentation. Skipping. 392s TCN segment #3 ('3') of 3...done 392s Chromosome 1 ('chr01') of 1...done 392s Update (C1,C2) per segment... 392s Update (C1,C2) per segment...done 392s Post-segmenting TCNs...done 392s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 392s 1 1 1 1 554484 143926517 7599 1.3859 2111 392s 2 1 2 1 143926517 185449813 2668 2.0704 774 392s 3 1 3 1 185449813 247137334 4391 2.6341 1311 392s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 392s 1 2111 554484 143926517 2111 0.5237 0.3300521 1.055848 392s 2 774 143926517 185449813 774 0.1542 0.8755722 1.194828 392s 3 1311 185449813 247137334 1311 0.2512 0.9862070 1.647893 392s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 392s 1 1 1 1 554484 143926517 7599 1.3859 2111 392s 2 1 2 1 143926517 185449813 2668 2.0704 774 392s 3 1 3 1 185449813 247137334 4391 2.6341 1311 392s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 392s 1 2111 554484 143926517 2111 0.5237 0.3300521 1.055848 392s 2 774 143926517 185449813 774 0.1542 0.8755722 1.194828 392s 3 1311 185449813 247137334 1311 0.2512 0.9862070 1.647893 392s > print(fit) 392s chromosome tcnId dhId start end tcnNbrOfLoci tcnMean tcnNbrOfSNPs 392s 1 1 1 1 554484 143926517 7599 1.3859 2111 392s 2 1 2 1 143926517 185449813 2668 2.0704 774 392s 3 1 3 1 185449813 247137334 4391 2.6341 1311 392s tcnNbrOfHets dhNbrOfLoci dhMean c1Mean c2Mean 392s 1 2111 2111 0.5237 0.3300521 1.055848 392s 2 774 774 0.1542 0.8755722 1.194828 392s 3 1311 1311 0.2512 0.9862070 1.647893 392s > 392s > # Plot results 392s > plotTracks(fit) 392s > 392s > 392s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 392s > # Bootstrap segment level estimates 392s > # (used by the AB caller, which, if skipped here, 392s > # will do it automatically) 392s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 392s > fit <- bootstrapTCNandDHByRegion(fit, B=B, verbose=-10) 392s Resample (TCN,DH) signals and re-estimate summaries for segment & changepoint... 392s Already done? 392s tcn_2.5% tcn_5% tcn_95% tcn_97.5% dh_2.5% dh_5% dh_95% dh_97.5% 392s FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE 392s c1_2.5% c1_5% c1_95% c1_97.5% c2_2.5% c2_5% c2_95% c2_97.5% 392s FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE 392s Bootstrapping (TCN,DH,C1,C2) segment mean levels... 392s Identifying heterozygous & homozygous SNPs and non-polymorphic loci... 392s Number of loci: 14658 392s Number of SNPs: 4196 392s Number of non-SNPs: 10462 392s Identifying heterozygous & homozygous SNPs and non-polymorphic loci...done 392s num [1:3, 1:100, 1:4] NA NA NA NA NA NA NA NA NA NA ... 392s - attr(*, "dimnames")=List of 3 392s ..$ : NULL 392s ..$ : NULL 392s ..$ : chr [1:4] "tcn" "dh" "c1" "c2" 392s Segment #1 (chr 1, tcnId=1, dhId=1) of 3... 392s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 392s 1 1 1 1 554484 143926517 7599 1.3859 2111 392s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 392s 1 2111 554484 143926517 2111 0.5237 0.3300521 1.055848 392s Number of TCNs: 7599 392s Number of DHs: 2111 392s int [1:7599] 1 2 3 4 5 6 7 8 9 10 ... 392s int [1:14658] 1 2 3 4 5 6 7 8 9 10 ... 392s int [1:7599] 1 2 3 4 5 6 7 8 9 10 ... 392s Identify loci used to bootstrap DH means... 392s Heterozygous SNPs to resample for DH: 392s int [1:2111] 10 12 24 28 31 33 34 39 46 48 ... 392s Identify loci used to bootstrap DH means...done 392s Identify loci used to bootstrap TCN means... 392s SNPs: 392s int [1:2111] 10 12 24 28 31 33 34 39 46 48 ... 392s Non-polymorphic loci: 392s int [1:5488] 1 2 3 4 5 6 7 8 9 11 ... 392s Heterozygous SNPs to resample for TCN: 392s int [1:2111] 10 12 24 28 31 33 34 39 46 48 ... 392s Homozygous SNPs to resample for TCN: 392s int(0) 392s Non-polymorphic loci to resample for TCN: 392s int [1:5488] 1 2 3 4 5 6 7 8 9 11 ... 392s Heterozygous SNPs with non-DH to resample for TCN: 392s int(0) 392s Loci to resample for TCN: 392s int [1:7599] 1 2 3 4 5 6 7 8 9 10 ... 392s Identify loci used to bootstrap TCN means...done 392s Number of (#hets, #homs, #nonSNPs): (2111,0,5488) 392s Bootstrapping while preserving (#hets, #homs, #nonSNPs)... 392s Number of bootstrap samples: 100 392s Bootstrapping while preserving (#hets, #homs, #nonSNPs)...done 392s Segment #1 (chr 1, tcnId=1, dhId=1) of 3...done 392s Segment #2 (chr 1, tcnId=2, dhId=1) of 3... 392s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 392s 2 1 2 1 143926517 185449813 2668 2.0704 774 392s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 392s 2 774 143926517 185449813 774 0.1542 0.8755722 1.194828 392s Number of TCNs: 2668 392s Number of DHs: 774 392s int [1:2668] 7600 7601 7602 7603 7604 7605 7606 7607 7608 7609 ... 392s int [1:14658] 1 2 3 4 5 6 7 8 9 10 ... 392s int [1:2668] 7600 7601 7602 7603 7604 7605 7606 7607 7608 7609 ... 392s Identify loci used to bootstrap DH means... 392s Heterozygous SNPs to resample for DH: 392s int [1:774] 7614 7616 7626 7627 7628 7635 7638 7639 7640 7642 ... 392s Identify loci used to bootstrap DH means...done 392s Identify loci used to bootstrap TCN means... 392s SNPs: 392s int [1:774] 7614 7616 7626 7627 7628 7635 7638 7639 7640 7642 ... 392s Non-polymorphic loci: 392s int [1:1894] 7600 7601 7602 7603 7604 7605 7606 7607 7608 7609 ... 392s Heterozygous SNPs to resample for TCN: 392s int [1:774] 7614 7616 7626 7627 7628 7635 7638 7639 7640 7642 ... 392s Homozygous SNPs to resample for TCN: 392s int(0) 392s Non-polymorphic loci to resample for TCN: 392s int [1:1894] 7600 7601 7602 7603 7604 7605 7606 7607 7608 7609 ... 392s Heterozygous SNPs with non-DH to resample for TCN: 392s int(0) 392s Loci to resample for TCN: 392s int [1:2668] 7600 7601 7602 7603 7604 7605 7606 7607 7608 7609 ... 392s Identify loci used to bootstrap TCN means...done 392s Number of (#hets, #homs, #nonSNPs): (774,0,1894) 392s Bootstrapping while preserving (#hets, #homs, #nonSNPs)... 392s Number of bootstrap samples: 100 392s Bootstrapping while preserving (#hets, #homs, #nonSNPs)...done 392s Segment #2 (chr 1, tcnId=2, dhId=1) of 3...done 392s Segment #3 (chr 1, tcnId=3, dhId=1) of 3... 392s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 392s 3 1 3 1 185449813 247137334 4391 2.6341 1311 392s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 392s 3 1311 185449813 247137334 1311 0.2512 0.986207 1.647893 392s Number of TCNs: 4391 392s Number of DHs: 1311 392s int [1:4391] 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 392s int [1:14658] 1 2 3 4 5 6 7 8 9 10 ... 392s int [1:4391] 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 392s Identify loci used to bootstrap DH means... 392s Heterozygous SNPs to resample for DH: 392s int [1:1311] 10269 10271 10281 10282 10283 10293 10295 10297 10300 10302 ... 392s Identify loci used to bootstrap DH means...done 392s Identify loci used to bootstrap TCN means... 392s SNPs: 392s int [1:1311] 10269 10271 10281 10282 10283 10293 10295 10297 10300 10302 ... 392s Non-polymorphic loci: 392s int [1:3080] 10268 10270 10272 10273 10274 10275 10276 10277 10278 10279 ... 392s Heterozygous SNPs to resample for TCN: 392s int [1:1311] 10269 10271 10281 10282 10283 10293 10295 10297 10300 10302 ... 392s Homozygous SNPs to resample for TCN: 392s int(0) 392s Non-polymorphic loci to resample for TCN: 392s int [1:3080] 10268 10270 10272 10273 10274 10275 10276 10277 10278 10279 ... 392s Heterozygous SNPs with non-DH to resample for TCN: 392s int(0) 392s Loci to resample for TCN: 392s int [1:4391] 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 392s Identify loci used to bootstrap TCN means...done 392s Number of (#hets, #homs, #nonSNPs): (1311,0,3080) 392s Bootstrapping while preserving (#hets, #homs, #nonSNPs)... 392s Number of bootstrap samples: 100 392s Bootstrapping while preserving (#hets, #homs, #nonSNPs)...done 392s Segment #3 (chr 1, tcnId=3, dhId=1) of 3...done 392s Bootstrapped segment mean levels 392s num [1:3, 1:100, 1:4] 1.38 2.08 2.63 1.38 2.07 ... 392s - attr(*, "dimnames")=List of 3 392s ..$ : NULL 392s ..$ : NULL 392s ..$ : chr [1:4] "tcn" "dh" "c1" "c2" 392s Calculating (C1,C2) mean levels from (TCN,DH) mean levels... 392s num [1:3, 1:100, 1:4] 1.38 2.08 2.63 1.38 2.07 ... 392s - attr(*, "dimnames")=List of 3 392s ..$ : NULL 392s ..$ : NULL 392s ..$ : chr [1:4] "tcn" "dh" "c1" "c2" 392s Calculating (C1,C2) mean levels from (TCN,DH) mean levels...done 392s Calculating polar (alpha,radius,manhattan) for change points... 392s num [1:2, 1:100, 1:2] -0.5588 -0.0962 -0.5365 -0.1285 -0.5378 ... 392s - attr(*, "dimnames")=List of 3 392s ..$ : NULL 392s ..$ : NULL 392s ..$ : chr [1:2] "c1" "c2" 392s Bootstrapped change points 392s num [1:2, 1:100, 1:5] -2.89 -1.78 -2.87 -1.86 -2.88 ... 392s - attr(*, "dimnames")=List of 3 392s ..$ : NULL 392s ..$ : NULL 392s ..$ : chr [1:5] "alpha" "radius" "manhattan" "d1" ... 392s Calculating polar (alpha,radius,manhattan) for change points...done 392s Bootstrapping (TCN,DH,C1,C2) segment mean levels...done 392s Summarizing bootstrapped segment ('tcn', 'dh', 'c1', 'c2') data... 392s num [1:3, 1:4, 1:4] NA NA NA NA NA NA NA NA NA NA ... 392s - attr(*, "dimnames")=List of 3 392s ..$ : NULL 392s ..$ : chr [1:4] "2.5%" "5%" "95%" "97.5%" 392s ..$ : chr [1:4] "tcn" "dh" "c1" "c2" 392s Field #1 ('tcn') of 4... 392s Segment #1 of 3... 392s Segment #1 of 3...done 392s Segment #2 of 3... 392s Segment #2 of 3...done 392s Segment #3 of 3... 392s Segment #3 of 3...done 392s Field #1 ('tcn') of 4...done 392s Field #2 ('dh') of 4... 392s Segment #1 of 3... 392s Segment #1 of 3...done 392s Segment #2 of 3... 392s Segment #2 of 3...done 392s Segment #3 of 3... 392s Segment #3 of 3...done 392s Field #2 ('dh') of 4...done 392s Field #3 ('c1') of 4... 392s Segment #1 of 3... 392s Segment #1 of 3...done 392s Segment #2 of 3... 392s Segment #2 of 3...done 392s Segment #3 of 3... 392s Segment #3 of 3...done 392s Field #3 ('c1') of 4...done 392s Field #4 ('c2') of 4... 392s Segment #1 of 3... 392s Segment #1 of 3...done 392s Segment #2 of 3... 392s Segment #2 of 3...done 392s Segment #3 of 3... 392s Segment #3 of 3...done 392s Field #4 ('c2') of 4...done 392s Bootstrap statistics 392s num [1:3, 1:4, 1:4] 1.38 2.06 2.62 1.38 2.06 ... 392s - attr(*, "dimnames")=List of 3 392s ..$ : NULL 392s ..$ : chr [1:4] "2.5%" "5%" "95%" "97.5%" 392s ..$ : chr [1:4] "tcn" "dh" "c1" "c2" 392s Statistical sanity checks (iff B >= 100)... 392s Available summaries: 2.5%, 5%, 95%, 97.5% 392s Available quantiles: 0.025, 0.05, 0.95, 0.975 392s num [1:3, 1:4, 1:4] 1.38 2.06 2.62 1.38 2.06 ... 392s - attr(*, "dimnames")=List of 3 392s ..$ : NULL 392s ..$ : chr [1:4] "2.5%" "5%" "95%" "97.5%" 392s ..$ : chr [1:4] "tcn" "dh" "c1" "c2" 392s Field #1 ('tcn') of 4... 392s Seg 1. mean=1.3859, range=[1.38092,1.3949], n=7599 392s Seg 2. mean=2.0704, range=[2.05747,2.08326], n=2668 392s Seg 3. mean=2.6341, range=[2.62068,2.64694], n=4391 392s Field #1 ('tcn') of 4...done 392s Field #2 ('dh') of 4... 392s Seg 1. mean=0.5237, range=[0.51753,0.532002], n=2111 392s Seg 2. mean=0.1542, range=[0.144468,0.16453], n=774 392s Seg 3. mean=0.2512, range=[0.242575,0.258832], n=1311 392s Field #2 ('dh') of 4...done 392s Field #3 ('c1') of 4... 392s Seg 1. mean=0.330052, range=[0.323996,0.336038], n=2111 392s Seg 2. mean=0.875572, range=[0.86318,0.887699], n=774 392s Seg 3. mean=0.986207, range=[0.975123,0.998982], n=1311 392s Field #3 ('c1') of 4...done 392s Field #4 ('c2') of 4... 392s Seg 1. mean=1.05585, range=[1.05006,1.06231], n=2111 392s Seg 2. mean=1.19483, range=[1.18417,1.2081], n=774 392s Seg 3. mean=1.64789, range=[1.63403,1.66098], n=1311 392s Field #4 ('c2') of 4...done 392s Statistical sanity checks (iff B >= 100)...done 392s Summarizing bootstrapped segment ('tcn', 'dh', 'c1', 'c2') data...done 392s Summarizing bootstrapped changepoint ('alpha', 'radius', 'manhattan', 'd1', 'd2') data... 392s num [1:2, 1:4, 1:5] NA NA NA NA NA NA NA NA NA NA ... 392s - attr(*, "dimnames")=List of 3 392s ..$ : NULL 392s ..$ : chr [1:4] "2.5%" "5%" "95%" "97.5%" 392s ..$ : chr [1:5] "alpha" "radius" "manhattan" "d1" ... 392s Field #1 ('alpha') of 5... 392s Changepoint #1 of 2... 392s Changepoint #1 of 2...done 392s Changepoint #2 of 2... 392s Changepoint #2 of 2...done 392s Field #1 ('alpha') of 5...done 392s Field #2 ('radius') of 5... 392s Changepoint #1 of 2... 392s Changepoint #1 of 2...done 392s Changepoint #2 of 2... 392s Changepoint #2 of 2...done 392s Field #2 ('radius') of 5...done 392s Field #3 ('manhattan') of 5... 392s Changepoint #1 of 2... 392s Changepoint #1 of 2...done 392s Changepoint #2 of 2... 392s Changepoint #2 of 2...done 392s Field #3 ('manhattan') of 5...done 392s Field #4 ('d1') of 5... 392s Changepoint #1 of 2... 392s Changepoint #1 of 2...done 392s Changepoint #2 of 2... 392s Changepoint #2 of 2...done 392s Field #4 ('d1') of 5...done 392s Field #5 ('d2') of 5... 392s Changepoint #1 of 2... 392s Changepoint #1 of 2...done 392s Changepoint #2 of 2... 392s Changepoint #2 of 2...done 392s Field #5 ('d2') of 5...done 392s Bootstrap statistics 392s num [1:2, 1:4, 1:5] -2.92 -1.86 -2.91 -1.85 -2.87 ... 392s - attr(*, "dimnames")=List of 3 392s ..$ : NULL 392s ..$ : chr [1:4] "2.5%" "5%" "95%" "97.5%" 392s ..$ : chr [1:5] "alpha" "radius" "manhattan" "d1" ... 392s Summarizing bootstrapped changepoint ('alpha', 'radius', 'manhattan', 'd1', 'd2') data...done 392s Resample (TCN,DH) signals and re-estimate summaries for segment & changepoint...done 392s > print(fit) 392s chromosome tcnId dhId start end tcnNbrOfLoci tcnMean tcnNbrOfSNPs 392s 1 1 1 1 554484 143926517 7599 1.3859 2111 392s 2 1 2 1 143926517 185449813 2668 2.0704 774 392s 3 1 3 1 185449813 247137334 4391 2.6341 1311 392s tcnNbrOfHets dhNbrOfLoci dhMean c1Mean c2Mean 392s 1 2111 2111 0.5237 0.3300521 1.055848 392s 2 774 774 0.1542 0.8755722 1.194828 392s 3 1311 1311 0.2512 0.9862070 1.647893 392s > plotTracks(fit) 392s > 392s > 392s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 392s > # Calling segments in allelic balance (AB) and 392s > # in loss-of-heterozygosity (LOH) 392s > # NOTE: Ideally, this should be done on whole-genome data 392s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 392s > fit <- callAB(fit, verbose=-10) 392s Calling segments of allelic balance from one-sided DH bootstrap confidence intervals... 392s delta (offset adjusting for bias in DH): 0.3466649145302 392s alpha (CI quantile; significance level): 0.05 392s Calling segments... 392s Number of segments called allelic balance (AB): 2 (66.67%) of 3 392s Calling segments...done 392s Calling segments of allelic balance from one-sided DH bootstrap confidence intervals...done 392s > fit <- callLOH(fit, verbose=-10) 392s Calling segments of allelic balance from one-sided DH bootstrap confidence intervals... 392s delta (offset adjusting for bias in C1): 0.771236438183453 392s alpha (CI quantile; significance level): 0.05 392s Calling segments... 392s Number of segments called low C1 (LowC1, "LOH_C1"): 1 (33.33%) of 3 392s Calling segments...done 392s Calling segments of allelic balance from one-sided DH bootstrap confidence intervals...done 392s > print(fit) 392s chromosome tcnId dhId start end tcnNbrOfLoci tcnMean tcnNbrOfSNPs 392s 1 1 1 1 554484 143926517 7599 1.3859 2111 392s 2 1 2 1 143926517 185449813 2668 2.0704 774 392s 3 1 3 1 185449813 247137334 4391 2.6341 1311 392s tcnNbrOfHets dhNbrOfLoci dhMean c1Mean c2Mean abCall lohCall 392s 1 2111 2111 0.5237 0.3300521 1.055848 FALSE TRUE 392s 2 774 774 0.1542 0.8755722 1.194828 TRUE FALSE 392s 3 1311 1311 0.2512 0.9862070 1.647893 TRUE FALSE 392s > plotTracks(fit) 392s > 392s > proc.time() 392s user system elapsed 392s 2.436 0.094 2.517 392s Test segmentByPairedPSCBS,DH passed 392s 0 392s Begin test segmentByPairedPSCBS,calls 397s + cat segmentByPairedPSCBS,calls.Rout 397s 397s R version 4.5.2 (2025-10-31) -- "[Not] Part in a Rumble" 397s Copyright (C) 2025 The R Foundation for Statistical Computing 397s Platform: aarch64-unknown-linux-gnu 397s 397s R is free software and comes with ABSOLUTELY NO WARRANTY. 397s You are welcome to redistribute it under certain conditions. 397s Type 'license()' or 'licence()' for distribution details. 397s 397s R is a collaborative project with many contributors. 397s Type 'contributors()' for more information and 397s 'citation()' on how to cite R or R packages in publications. 397s 397s Type 'demo()' for some demos, 'help()' for on-line help, or 397s 'help.start()' for an HTML browser interface to help. 397s Type 'q()' to quit R. 397s 397s [Previously saved workspace restored] 397s 397s > library("PSCBS") 397s PSCBS v0.68.0 (2025-04-18 19:40:02 UTC) successfully loaded. See ?PSCBS for help. 397s > 397s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 397s > # Load SNP microarray data 397s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 397s > data <- PSCBS::exampleData("paired.chr01") 397s > str(data) 397s 'data.frame': 73346 obs. of 6 variables: 397s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 397s $ x : int 1145994 2224111 2319424 2543484 2926730 2941694 3084986 3155127 3292731 3695086 ... 397s $ CT : num 1.625 1.071 1.406 1.18 0.856 ... 397s $ betaT : num 0.757 0.771 0.834 0.778 0.229 ... 397s $ CN : num 2.36 2.13 2.59 1.93 1.71 ... 397s $ betaN : num 0.827 0.875 0.887 0.884 0.103 ... 397s > 397s > 397s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 397s > # Paired PSCBS segmentation 397s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 397s > # Drop single-locus outliers 397s > dataS <- dropSegmentationOutliers(data) 397s > 397s > # Find centromere 397s > gaps <- findLargeGaps(dataS, minLength=2e6) 397s > knownSegments <- gapsToSegments(gaps) 397s > 397s > 397s > # Run light-weight tests by default 397s > if (Sys.getenv("_R_CHECK_FULL_") == "") { 397s + # Use only every 5th data point 397s + dataS <- dataS[seq(from=1, to=nrow(data), by=5),] 397s + # Number of segments (for assertion) 397s + nSegs <- 4L 397s + # Number of bootstrap samples (see below) 397s + B <- 100L 397s + } else { 397s + # Full tests 397s + nSegs <- 11L 397s + B <- 1000L 397s + } 397s > 397s > str(dataS) 397s 'data.frame': 14670 obs. of 6 variables: 397s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 397s $ x : int 1145994 2941694 3710825 4240737 4276892 4464544 4714611 5095111 5034491 5158416 ... 397s $ CT : num 1.63 1.4 1.41 1.17 1.16 ... 397s $ betaT : num 0.7574 0.169 0.2357 0.2604 0.0576 ... 397s $ CN : num 2.36 2.13 2.26 2.01 2.32 ... 397s $ betaN : num 0.8274 0.5072 0.1671 0.1609 0.0421 ... 397s > 397s > # Paired PSCBS segmentation 397s > fit <- segmentByPairedPSCBS(dataS, knownSegments=knownSegments, 397s + seed=0xBEEF, verbose=-10) 397s Segmenting paired tumor-normal signals using Paired PSCBS... 397s Calling genotypes from normal allele B fractions... 397s num [1:14670] 0.8274 0.5072 0.1671 0.1609 0.0421 ... 397s Called genotypes: 397s num [1:14670] 1 0.5 0 0 0 0 1 0 1 0.5 ... 397s - attr(*, "modelFit")=List of 1 397s ..$ :List of 7 397s .. ..$ flavor : chr "density" 397s .. ..$ cn : int 2 397s .. ..$ nbrOfGenotypeGroups: int 3 397s .. ..$ tau : num [1:2] 0.315 0.677 397s .. ..$ n : int 14640 397s .. ..$ fit :Classes 'PeaksAndValleys' and 'data.frame': 5 obs. of 3 variables: 397s .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 397s .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 397s .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 397s .. ..$ fitValleys :Classes 'PeaksAndValleys' and 'data.frame': 2 obs. of 3 variables: 397s .. .. ..$ type : chr [1:2] "valley" "valley" 397s .. .. ..$ x : num [1:2] 0.315 0.677 397s .. .. ..$ density: num [1:2] 0.522 0.551 397s ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 397s muN 397s 0 0.5 1 397s 5221 4198 5251 397s Calling genotypes from normal allele B fractions...done 397s Normalizing betaT using betaN (TumorBoost)... 397s Normalized BAFs: 397s num [1:14670] 0.9301 0.1667 0.0685 0.0995 0.0155 ... 397s - attr(*, "modelFit")=List of 5 397s ..$ method : chr "normalizeTumorBoost" 397s ..$ flavor : chr "v4" 397s ..$ delta : num [1:14670] -0.17264 0.00239 0.1671 0.16085 0.04213 ... 397s .. ..- attr(*, "modelFit")=List of 1 397s .. .. ..$ :List of 7 397s .. .. .. ..$ flavor : chr "density" 397s .. .. .. ..$ cn : int 2 397s .. .. .. ..$ nbrOfGenotypeGroups: int 3 397s .. .. .. ..$ tau : num [1:2] 0.315 0.677 397s .. .. .. ..$ n : int 14640 397s .. .. .. ..$ fit :Classes 'PeaksAndValleys' and 'data.frame': 5 obs. of 3 variables: 397s .. .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 397s .. .. .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 397s .. .. .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 397s .. .. .. ..$ fitValleys :Classes 'PeaksAndValleys' and 'data.frame': 2 obs. of 3 variables: 397s .. .. .. .. ..$ type : chr [1:2] "valley" "valley" 397s .. .. .. .. ..$ x : num [1:2] 0.315 0.677 397s .. .. .. .. ..$ density: num [1:2] 0.522 0.551 397s .. .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 397s ..$ preserveScale: logi FALSE 397s ..$ scaleFactor : num NA 397s Normalizing betaT using betaN (TumorBoost)...done 397s Setup up data... 397s 'data.frame': 14670 obs. of 7 variables: 397s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 397s $ x : num 1145994 2941694 3710825 4240737 4276892 ... 397s $ CT : num 1.63 1.4 1.41 1.17 1.16 ... 397s $ betaT : num 0.7574 0.169 0.2357 0.2604 0.0576 ... 397s $ betaTN : num 0.9301 0.1667 0.0685 0.0995 0.0155 ... 397s ..- attr(*, "modelFit")=List of 5 397s .. ..$ method : chr "normalizeTumorBoost" 397s .. ..$ flavor : chr "v4" 397s .. ..$ delta : num [1:14670] -0.17264 0.00239 0.1671 0.16085 0.04213 ... 397s .. .. ..- attr(*, "modelFit")=List of 1 397s .. .. .. ..$ :List of 7 397s .. .. .. .. ..$ flavor : chr "density" 397s .. .. .. .. ..$ cn : int 2 397s .. .. .. .. ..$ nbrOfGenotypeGroups: int 3 397s .. .. .. .. ..$ tau : num [1:2] 0.315 0.677 397s .. .. .. .. ..$ n : int 14640 397s .. .. .. .. ..$ fit :Classes 'PeaksAndValleys' and 'data.frame': 5 obs. of 3 variables: 397s .. .. .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 397s .. .. .. .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 397s .. .. .. .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 397s .. .. .. .. ..$ fitValleys :Classes 'PeaksAndValleys' and 'data.frame': 2 obs. of 3 variables: 397s .. .. .. .. .. ..$ type : chr [1:2] "valley" "valley" 397s .. .. .. .. .. ..$ x : num [1:2] 0.315 0.677 397s .. .. .. .. .. ..$ density: num [1:2] 0.522 0.551 397s .. .. .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 397s .. ..$ preserveScale: logi FALSE 397s .. ..$ scaleFactor : num NA 397s $ betaN : num 0.8274 0.5072 0.1671 0.1609 0.0421 ... 397s $ muN : num 1 0.5 0 0 0 0 1 0 1 0.5 ... 397s ..- attr(*, "modelFit")=List of 1 397s .. ..$ :List of 7 397s .. .. ..$ flavor : chr "density" 397s .. .. ..$ cn : int 2 397s .. .. ..$ nbrOfGenotypeGroups: int 3 397s .. .. ..$ tau : num [1:2] 0.315 0.677 397s .. .. ..$ n : int 14640 397s .. .. ..$ fit :Classes 'PeaksAndValleys' and 'data.frame': 5 obs. of 3 variables: 397s .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 397s .. .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 397s .. .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 397s .. .. ..$ fitValleys :Classes 'PeaksAndValleys' and 'data.frame': 2 obs. of 3 variables: 397s .. .. .. ..$ type : chr [1:2] "valley" "valley" 397s .. .. .. ..$ x : num [1:2] 0.315 0.677 397s .. .. .. ..$ density: num [1:2] 0.522 0.551 397s .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 397s Setup up data...done 397s Dropping loci for which TCNs are missing... 397s Number of loci dropped: 12 397s Dropping loci for which TCNs are missing...done 397s Ordering data along genome... 397s 'data.frame': 14658 obs. of 7 variables: 397s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 397s $ x : num 554484 730720 782343 878522 916294 ... 397s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 397s $ betaT : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 397s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 397s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 397s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 397s Ordering data along genome...done 397s Keeping only current chromosome for 'knownSegments'... 397s Chromosome: 1 397s Known segments for this chromosome: 397s chromosome start end length 397s 1 1 -Inf 120992603 Inf 397s 2 1 120992604 141510002 20517398 397s 3 1 141510003 Inf Inf 397s Keeping only current chromosome for 'knownSegments'...done 397s alphaTCN: 0.009 397s alphaDH: 0.001 397s Number of loci: 14658 397s Calculating DHs... 397s Number of SNPs: 14658 397s Number of heterozygous SNPs: 4196 (28.63%) 397s Normalized DHs: 397s num [1:14658] NA NA NA NA NA ... 397s Calculating DHs...done 397s Random seed temporarily set (seed=c(48879), kind="L'Ecuyer-CMRG") 397s Produced 2 seeds from this stream for future usage 397s Identification of change points by total copy numbers... 397s Segmenting by CBS... 397s Chromosome: 1 397s Segmenting multiple segments on current chromosome... 397s Number of segments: 3 397s Random seed temporarily set (seed=c(10407, 1066287653, -51199871, 161854402, -1995183193, 1503453565, -747102133), kind="L'Ecuyer-CMRG") 397s Produced 3 seeds from this stream for future usage 397s Segmenting by CBS... 397s Chromosome: 1 397s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 397s Segmenting by CBS...done 397s Segmenting by CBS... 397s Chromosome: 1 397s Random seed temporarily set (seed=c(10407, -1924040949, -1632234809, -437763632, -1464377300, 676654412, 2080370711), kind="L'Ecuyer-CMRG") 397s Segmenting by CBS...done 397s Segmenting multiple segments on current chromosome...done 397s Segmenting by CBS...done 397s List of 4 397s $ data :'data.frame': 14658 obs. of 4 variables: 397s ..$ chromosome: int [1:14658] 1 1 1 1 1 1 1 1 1 1 ... 397s ..$ x : num [1:14658] 554484 730720 782343 878522 916294 ... 397s ..$ y : num [1:14658] 1.88 1.8 1.59 1.64 1.53 ... 397s ..$ index : int [1:14658] 1 2 3 4 5 6 7 8 9 10 ... 397s $ output :'data.frame': 4 obs. of 6 variables: 397s ..$ sampleName: chr [1:4] NA NA NA NA 397s ..$ chromosome: int [1:4] 1 1 1 1 397s ..$ start : num [1:4] 5.54e+05 1.21e+08 1.42e+08 1.85e+08 397s ..$ end : num [1:4] 1.21e+08 1.42e+08 1.85e+08 2.47e+08 397s ..$ nbrOfLoci : int [1:4] 7586 0 2681 4391 397s ..$ mean : num [1:4] 1.39 NA 2.07 2.63 397s $ segRows:'data.frame': 4 obs. of 2 variables: 397s ..$ startRow: int [1:4] 1 NA 7587 10268 397s ..$ endRow : int [1:4] 7586 NA 10267 14658 397s $ params :List of 5 397s ..$ alpha : num 0.009 397s ..$ undo : num 0 397s ..$ joinSegments : logi TRUE 397s ..$ knownSegments:'data.frame': 4 obs. of 3 variables: 397s .. ..$ chromosome: int [1:4] 1 1 2 1 397s .. ..$ start : num [1:4] -Inf -Inf -Inf 1.42e+08 397s .. ..$ end : num [1:4] 1.21e+08 Inf Inf Inf 397s ..$ seed : int [1:7] 10407 1066287653 -51199871 161854402 -1995183193 1503453565 -747102133 397s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 397s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.127 0.001 0.128 0 0 397s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 397s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 397s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 397s Identification of change points by total copy numbers...done 397s Restructure TCN segmentation results... 397s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean 397s 1 1 554484 120992603 7586 1.3853 397s 2 1 120992604 141510002 0 NA 397s 3 1 141510003 185449813 2681 2.0689 397s 4 1 185449813 247137334 4391 2.6341 397s Number of TCN segments: 4 397s Restructure TCN segmentation results...done 397s Total CN segment #1 ([ 554484,1.20993e+08]) of 4... 397s Number of TCN loci in segment: 7586 397s Locus data for TCN segment: 397s 'data.frame': 7586 obs. of 9 variables: 397s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 397s $ x : num 554484 730720 782343 878522 916294 ... 397s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 397s $ betaT : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 397s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 397s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 397s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 397s $ index : int 1 2 3 4 5 6 7 8 9 10 ... 397s $ rho : num NA NA NA NA NA ... 397s Number of loci: 7586 397s Number of SNPs: 2108 (27.79%) 397s Number of heterozygous SNPs: 2108 (100.00%) 397s Chromosome: 1 397s Segmenting DH signals... 397s Segmenting by CBS... 397s Chromosome: 1 397s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 397s Segmenting by CBS...done 397s List of 4 397s $ data :'data.frame': 7586 obs. of 4 variables: 397s ..$ chromosome: int [1:7586] 1 1 1 1 1 1 1 1 1 1 ... 397s ..$ x : num [1:7586] 554484 730720 782343 878522 916294 ... 397s ..$ y : num [1:7586] NA NA NA NA NA ... 397s ..$ index : int [1:7586] 1 2 3 4 5 6 7 8 9 10 ... 397s $ output :'data.frame': 1 obs. of 6 variables: 397s ..$ sampleName: chr NA 397s ..$ chromosome: int 1 397s ..$ start : num 554484 397s ..$ end : num 1.21e+08 397s ..$ nbrOfLoci : int 2108 397s ..$ mean : num 0.512 397s $ segRows:'data.frame': 1 obs. of 2 variables: 397s ..$ startRow: int 10 397s ..$ endRow : int 7574 397s $ params :List of 5 397s ..$ alpha : num 0.001 397s ..$ undo : num 0 397s ..$ joinSegments : logi TRUE 397s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 397s .. ..$ chromosome: int 1 397s .. ..$ start : num 554484 397s .. ..$ end : num 1.21e+08 397s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 397s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 397s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.037 0 0.037 0 0 397s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 397s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 397s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 397s DH segmentation (locally-indexed) rows: 397s startRow endRow 397s 1 10 7574 397s int [1:7586] 1 2 3 4 5 6 7 8 9 10 ... 397s DH segmentation rows: 397s startRow endRow 397s 1 10 7574 397s Segmenting DH signals...done 397s DH segmentation table: 397s dhStart dhEnd dhNbrOfLoci dhMean 397s 1 554484 120992603 2108 0.5116 397s startRow endRow 397s 1 10 7574 397s Rows: 397s [1] 1 397s TCN segmentation rows: 397s startRow endRow 397s 1 1 7586 397s TCN and DH segmentation rows: 397s startRow endRow 397s 1 1 7586 397s startRow endRow 397s 1 10 7574 397s NULL 397s TCN segmentation (expanded) rows: 397s startRow endRow 397s 1 1 7586 397s TCN and DH segmentation rows: 397s startRow endRow 397s 1 1 7586 397s 2 NA NA 397s 3 7587 10267 397s 4 10268 14658 397s startRow endRow 397s 1 10 7574 397s startRow endRow 397s 1 1 7586 397s Total CN segmentation table (expanded): 397s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 397s 1 1 554484 120992603 7586 1.3853 2108 2108 397s (TCN,DH) segmentation for one total CN segment: 397s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 397s 1 1 1 1 554484 120992603 7586 1.3853 2108 397s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 397s 1 2108 554484 120992603 2108 0.5116 397s Total CN segment #1 ([ 554484,1.20993e+08]) of 4...done 397s Total CN segment #2 ([1.20993e+08,1.4151e+08]) of 4... 397s Number of TCN loci in segment: 0 397s Locus data for TCN segment: 397s 'data.frame': 0 obs. of 9 variables: 397s $ chromosome: int 397s $ x : num 397s $ CT : num 397s $ betaT : num 397s $ bet+ [ 0 != 0 ] 397s + echo Test segmentByPairedPSCBS,calls passed 397s + echo 0 397s + echo Begin test segmentByPairedPSCBS,futures 397s + exitcode=0 397s + R CMD BATCH segmentByPairedPSCBS,futures.R 397s aTN : num 397s $ betaN : num 397s $ muN : num 397s $ index : int 397s $ rho : num 397s Number of loci: 0 397s Number of SNPs: 0 (NaN%) 397s Number of heterozygous SNPs: 0 (NaN%) 397s Chromosome: 1 397s Segmenting DH signals... 397s Segmenting by CBS... 397s Chromosome: NA 397s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 397s Segmenting by CBS...done 397s List of 4 397s $ data :'data.frame': 0 obs. of 4 variables: 397s ..$ chromosome: int(0) 397s ..$ x : num(0) 397s ..$ y : num(0) 397s ..$ index : int(0) 397s $ output :'data.frame': 0 obs. of 6 variables: 397s ..$ sampleName: chr(0) 397s ..$ chromosome: num(0) 397s ..$ start : num(0) 397s ..$ end : num(0) 397s ..$ nbrOfLoci : int(0) 397s ..$ mean : num(0) 397s $ segRows:'data.frame': 0 obs. of 2 variables: 397s ..$ startRow: int(0) 397s ..$ endRow : int(0) 397s $ params :List of 5 397s ..$ alpha : num 0.001 397s ..$ undo : num 0 397s ..$ joinSegments : logi TRUE 397s ..$ knownSegments:'data.frame': 0 obs. of 3 variables: 397s .. ..$ chromosome: int(0) 397s .. ..$ start : num(0) 397s .. ..$ end : num(0) 397s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 397s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 397s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.002 0 0.001 0 0 397s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 397s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 397s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 397s DH segmentation (locally-indexed) rows: 397s [1] startRow endRow 397s <0 rows> (or 0-length row.names) 397s int(0) 397s DH segmentation rows: 397s [1] startRow endRow 397s <0 rows> (or 0-length row.names) 397s Segmenting DH signals...done 397s DH segmentation table: 397s dhStart dhEnd dhNbrOfLoci dhMean 397s NA NA NA NA NA 397s startRow endRow 397s NA NA NA 397s Rows: 397s [1] 2 397s TCN segmentation rows: 397s startRow endRow 397s 2 NA NA 397s TCN and DH segmentation rows: 397s startRow endRow 397s 2 NA NA 397s startRow endRow 397s NA NA NA 397s startRow endRow 397s 1 1 7586 397s TCN segmentation (expanded) rows: 397s startRow endRow 397s 1 1 7586 397s 2 NA NA 397s TCN and DH segmentation rows: 397s startRow endRow 397s 1 1 7586 397s 2 NA NA 397s 3 7587 10267 397s 4 10268 14658 397s startRow endRow 397s 1 10 7574 397s 2 NA NA 397s startRow endRow 397s 1 1 7586 397s 2 NA NA 397s Total CN segmentation table (expanded): 397s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 397s 2 1 120992604 141510002 0 NA 0 0 397s (TCN,DH) segmentation for one total CN segment: 397s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 397s 2 2 1 1 120992604 141510002 0 NA 0 397s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 397s 2 0 NA NA NA NA 397s Total CN segment #2 ([1.20993e+08,1.4151e+08]) of 4...done 397s Total CN segment #3 ([1.4151e+08,1.8545e+08]) of 4... 397s Number of TCN loci in segment: 2681 397s Locus data for TCN segment: 397s 'data.frame': 2681 obs. of 9 variables: 397s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 397s $ x : num 1.43e+08 1.43e+08 1.43e+08 1.43e+08 1.44e+08 ... 397s $ CT : num 2.27 1.55 1.47 1.5 1.81 ... 397s $ betaT : num 0.34 0.55 0.048 0.813 0.575 ... 397s $ betaTN : num 0.441 0.629 -0.05 0.958 0.872 ... 397s $ betaN : num 0.3851 0.3933 0.0981 0.8552 0.7028 ... 397s $ muN : num 0.5 0.5 0 1 1 1 1 0.5 1 1 ... 397s $ index : int 7587 7588 7589 7590 7591 7592 7593 7594 7595 7596 ... 397s $ rho : num 0.117 0.258 NA NA NA ... 397s Number of loci: 2681 397s Number of SNPs: 777 (28.98%) 397s Number of heterozygous SNPs: 777 (100.00%) 397s Chromosome: 1 397s Segmenting DH signals... 397s Segmenting by CBS... 397s Chromosome: 1 397s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 397s Segmenting by CBS...done 397s List of 4 397s $ data :'data.frame': 2681 obs. of 4 variables: 397s ..$ chromosome: int [1:2681] 1 1 1 1 1 1 1 1 1 1 ... 397s ..$ x : num [1:2681] 1.43e+08 1.43e+08 1.43e+08 1.43e+08 1.44e+08 ... 397s ..$ y : num [1:2681] 0.117 0.258 NA NA NA ... 397s ..$ index : int [1:2681] 1 2 3 4 5 6 7 8 9 10 ... 397s $ output :'data.frame': 1 obs. of 6 variables: 397s ..$ sampleName: chr NA 397s ..$ chromosome: int 1 397s ..$ start : num 1.42e+08 397s ..$ end : num 1.85e+08 397s ..$ nbrOfLoci : int 777 397s ..$ mean : num 0.0973 397s $ segRows:'data.frame': 1 obs. of 2 variables: 397s ..$ startRow: int 1 397s ..$ endRow : int 2677 397s $ params :List of 5 397s ..$ alpha : num 0.001 397s ..$ undo : num 0 397s ..$ joinSegments : logi TRUE 397s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 397s .. ..$ chromosome: int 1 397s .. ..$ start : num 1.42e+08 397s .. ..$ end : num 1.85e+08 397s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 397s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 397s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.008 0 0.008 0 0 397s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 397s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 397s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 397s DH segmentation (locally-indexed) rows: 397s startRow endRow 397s 1 1 2677 397s int [1:2681] 7587 7588 7589 7590 7591 7592 7593 7594 7595 7596 ... 397s DH segmentation rows: 397s startRow endRow 397s 1 7587 10263 397s Segmenting DH signals...done 397s DH segmentation table: 397s dhStart dhEnd dhNbrOfLoci dhMean 397s 1 141510003 185449813 777 0.0973 397s startRow endRow 397s 1 7587 10263 397s Rows: 397s [1] 3 397s TCN segmentation rows: 397s startRow endRow 397s 3 7587 10267 397s TCN and DH segmentation rows: 397s startRow endRow 397s 3 7587 10267 397s startRow endRow 397s 1 7587 10263 397s startRow endRow 397s 1 1 7586 397s 2 NA NA 397s TCN segmentation (expanded) rows: 397s startRow endRow 397s 1 1 7586 397s 2 NA NA 397s 3 7587 10267 397s TCN and DH segmentation rows: 397s startRow endRow 397s 1 1 7586 397s 2 NA NA 397s 3 7587 10267 397s 4 10268 14658 397s startRow endRow 397s 1 10 7574 397s 2 NA NA 397s 3 7587 10263 397s startRow endRow 397s 1 1 7586 397s 2 NA NA 397s 3 7587 10267 397s Total CN segmentation table (expanded): 397s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 397s 3 1 141510003 185449813 2681 2.0689 777 777 397s (TCN,DH) segmentation for one total CN segment: 397s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 397s 3 3 1 1 141510003 185449813 2681 2.0689 777 397s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 397s 3 777 141510003 185449813 777 0.0973 397s Total CN segment #3 ([1.4151e+08,1.8545e+08]) of 4...done 397s Total CN segment #4 ([1.8545e+08,2.47137e+08]) of 4... 397s Number of TCN loci in segment: 4391 397s Locus data for TCN segment: 397s 'data.frame': 4391 obs. of 9 variables: 397s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 397s $ x : num 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 397s $ CT : num 2.93 2.15 2.82 2.93 2.46 ... 397s $ betaT : num 0.0811 0.5154 0.9473 0.3734 0.7506 ... 397s $ betaTN : num -0.169 0.609 1.028 0.525 0.968 ... 397s $ betaN : num 0.25 0.38 0.919 0.34 0.783 ... 397s $ muN : num 0 0.5 1 0.5 1 1 0 1 0 1 ... 397s $ index : int 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 397s $ rho : num NA 0.2186 NA 0.0503 NA ... 397s Number of loci: 4391 397s Number of SNPs: 1311 (29.86%) 397s Number of heterozygous SNPs: 1311 (100.00%) 397s Chromosome: 1 397s Segmenting DH signals... 397s Segmenting by CBS... 397s Chromosome: 1 397s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 397s Segmenting by CBS...done 397s List of 4 397s $ data :'data.frame': 4391 obs. of 4 variables: 397s ..$ chromosome: int [1:4391] 1 1 1 1 1 1 1 1 1 1 ... 397s ..$ x : num [1:4391] 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 397s ..$ y : num [1:4391] NA 0.2186 NA 0.0503 NA ... 397s ..$ index : int [1:4391] 1 2 3 4 5 6 7 8 9 10 ... 397s $ output :'data.frame': 1 obs. of 6 variables: 397s ..$ sampleName: chr NA 397s ..$ chromosome: int 1 397s ..$ start : num 1.85e+08 397s ..$ end : num 2.47e+08 397s ..$ nbrOfLoci : int 1311 397s ..$ mean : num 0.23 397s $ segRows:'data.frame': 1 obs. of 2 variables: 397s ..$ startRow: int 2 397s ..$ endRow : int 4388 397s $ params :List of 5 397s ..$ alpha : num 0.001 397s ..$ undo : num 0 397s ..$ joinSegments : logi TRUE 397s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 397s .. ..$ chromosome: int 1 397s .. ..$ start : num 1.85e+08 397s .. ..$ end : num 2.47e+08 397s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 397s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 397s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.015 0 0.015 0 0 397s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 397s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 397s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 397s DH segmentation (locally-indexed) rows: 397s startRow endRow 397s 1 2 4388 397s int [1:4391] 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 397s DH segmentation rows: 397s startRow endRow 397s 1 10269 14655 397s Segmenting DH signals...done 397s DH segmentation table: 397s dhStart dhEnd dhNbrOfLoci dhMean 397s 1 185449813 247137334 1311 0.2295 397s startRow endRow 397s 1 10269 14655 397s Rows: 397s [1] 4 397s TCN segmentation rows: 397s startRow endRow 397s 4 10268 14658 397s TCN and DH segmentation rows: 397s startRow endRow 397s 4 10268 14658 397s startRow endRow 397s 1 10269 14655 397s startRow endRow 397s 1 1 7586 397s 2 NA NA 397s 3 7587 10267 397s TCN segmentation (expanded) rows: 397s startRow endRow 397s 1 1 7586 397s 2 NA NA 397s 3 7587 10267 397s 4 10268 14658 397s TCN and DH segmentation rows: 397s startRow endRow 397s 1 1 7586 397s 2 NA NA 397s 3 7587 10267 397s 4 10268 14658 397s startRow endRow 397s 1 10 7574 397s 2 NA NA 397s 3 7587 10263 397s 4 10269 14655 397s startRow endRow 397s 1 1 7586 397s 2 NA NA 397s 3 7587 10267 397s 4 10268 14658 397s Total CN segmentation table (expanded): 397s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 397s 4 1 185449813 247137334 4391 2.6341 1311 1311 397s (TCN,DH) segmentation for one total CN segment: 397s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 397s 4 4 1 1 185449813 247137334 4391 2.6341 1311 397s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 397s 4 1311 185449813 247137334 1311 0.2295 397s Total CN segment #4 ([1.8545e+08,2.47137e+08]) of 4...done 397s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 397s 1 1 1 1 554484 120992603 7586 1.3853 2108 397s 2 1 2 1 120992604 141510002 0 NA 0 397s 3 1 3 1 141510003 185449813 2681 2.0689 777 397s 4 1 4 1 185449813 247137334 4391 2.6341 1311 397s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 397s 1 2108 554484 120992603 2108 0.5116 397s 2 0 NA NA NA NA 397s 3 777 141510003 185449813 777 0.0973 397s 4 1311 185449813 247137334 1311 0.2295 397s Calculating (C1,C2) per segment... 397s Calculating (C1,C2) per segment...done 397s Number of segments: 4 397s Segmenting paired tumor-normal signals using Paired PSCBS...done 397s Post-segmenting TCNs... 397s Number of segments: 4 397s Number of chromosomes: 1 397s [1] 1 397s Chromosome 1 ('chr01') of 1... 397s Rows: 397s [1] 1 2 3 4 397s Number of segments: 4 397s TCN segment #1 ('1') of 4... 397s Nothing todo. Only one DH segmentation. Skipping. 397s TCN segment #1 ('1') of 4...done 397s TCN segment #2 ('2') of 4... 397s Nothing todo. Only one DH segmentation. Skipping. 397s TCN segment #2 ('2') of 4...done 397s TCN segment #3 ('3') of 4... 397s Nothing todo. Only one DH segmentation. Skipping. 397s TCN segment #3 ('3') of 4...done 397s TCN segment #4 ('4') of 4... 397s Nothing todo. Only one DH segmentation. Skipping. 397s TCN segment #4 ('4') of 4...done 397s Chromosome 1 ('chr01') of 1...done 397s Update (C1,C2) per segment... 397s Update (C1,C2) per segment...done 397s Post-segmenting TCNs...done 397s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 397s 1 1 1 1 554484 120992603 7586 1.3853 2108 397s 2 1 2 1 120992604 141510002 0 NA 0 397s 3 1 3 1 141510003 185449813 2681 2.0689 777 397s 4 1 4 1 185449813 247137334 4391 2.6341 1311 397s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 397s 1 2108 554484 120992603 2108 0.5116 0.3382903 1.047010 397s 2 0 NA NA NA NA NA NA 397s 3 777 141510003 185449813 777 0.0973 0.9337980 1.135102 397s 4 1311 185449813 247137334 1311 0.2295 1.0147870 1.619313 397s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 397s 1 1 1 1 554484 120992603 7586 1.3853 2108 397s 2 1 2 1 120992604 141510002 0 NA 0 397s 3 1 3 1 141510003 185449813 2681 2.0689 777 397s 4 1 4 1 185449813 247137334 4391 2.6341 1311 397s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 397s 1 2108 554484 120992603 2108 0.5116 0.3382903 1.047010 397s 2 0 NA NA NA NA NA NA 397s 3 777 141510003 185449813 777 0.0973 0.9337980 1.135102 397s 4 1311 185449813 247137334 1311 0.2295 1.0147870 1.619313 397s > print(fit) 397s chromosome tcnId dhId start end tcnNbrOfLoci tcnMean tcnNbrOfSNPs 397s 1 1 1 1 554484 120992603 7586 1.3853 2108 397s 2 1 2 1 120992604 141510002 0 NA 0 397s 3 1 3 1 141510003 185449813 2681 2.0689 777 397s 4 1 4 1 185449813 247137334 4391 2.6341 1311 397s tcnNbrOfHets dhNbrOfLoci dhMean c1Mean c2Mean 397s 1 2108 2108 0.5116 0.3382903 1.047010 397s 2 0 NA NA NA NA 397s 3 777 777 0.0973 0.9337980 1.135102 397s 4 1311 1311 0.2295 1.0147870 1.619313 397s > 397s > # Plot results 397s > plotTracks(fit) 397s > 397s > # Sanity check 397s > stopifnot(nbrOfSegments(fit) == nSegs) 397s > 397s > 397s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 397s > # Bootstrap segment level estimates 397s > # (used by the AB caller, which, if skipped here, 397s > # will do it automatically) 397s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 397s > fit <- bootstrapTCNandDHByRegion(fit, B=B, verbose=-10) 397s Resample (TCN,DH) signals and re-estimate summaries for segment & changepoint... 397s Already done? 397s tcn_2.5% tcn_5% tcn_95% tcn_97.5% dh_2.5% dh_5% dh_95% dh_97.5% 397s FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE 397s c1_2.5% c1_5% c1_95% c1_97.5% c2_2.5% c2_5% c2_95% c2_97.5% 397s FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE 397s Bootstrapping (TCN,DH,C1,C2) segment mean levels... 397s Identifying heterozygous & homozygous SNPs and non-polymorphic loci... 397s Number of loci: 14658 397s Number of SNPs: 4196 397s Number of non-SNPs: 10462 397s Identifying heterozygous & homozygous SNPs and non-polymorphic loci...done 397s num [1:4, 1:100, 1:4] NA NA NA NA NA NA NA NA NA NA ... 397s - attr(*, "dimnames")=List of 3 397s ..$ : NULL 397s ..$ : NULL 397s ..$ : chr [1:4] "tcn" "dh" "c1" "c2" 397s Segment #1 (chr 1, tcnId=1, dhId=1) of 4... 397s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 397s 1 1 1 1 554484 120992603 7586 1.3853 2108 397s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 397s 1 2108 554484 120992603 2108 0.5116 0.3382903 1.04701 397s Number of TCNs: 7586 397s Number of DHs: 2108 397s int [1:7586] 1 2 3 4 5 6 7 8 9 10 ... 397s int [1:14658] 1 2 3 4 5 6 7 8 9 10 ... 397s int [1:7586] 1 2 3 4 5 6 7 8 9 10 ... 397s Identify loci used to bootstrap DH means... 397s Heterozygous SNPs to resample for DH: 397s int [1:2108] 10 12 24 28 31 33 34 39 46 48 ... 397s Identify loci used to bootstrap DH means...done 397s Identify loci used to bootstrap TCN means... 397s SNPs: 397s int [1:2108] 10 12 24 28 31 33 34 39 46 48 ... 397s Non-polymorphic loci: 397s int [1:5478] 1 2 3 4 5 6 7 8 9 11 ... 397s Heterozygous SNPs to resample for TCN: 397s int [1:2108] 10 12 24 28 31 33 34 39 46 48 ... 397s Homozygous SNPs to resample for TCN: 397s int(0) 397s Non-polymorphic loci to resample for TCN: 397s int [1:5478] 1 2 3 4 5 6 7 8 9 11 ... 397s Heterozygous SNPs with non-DH to resample for TCN: 397s int(0) 397s Loci to resample for TCN: 397s int [1:7586] 1 2 3 4 5 6 7 8 9 10 ... 397s Identify loci used to bootstrap TCN means...done 397s Number of (#hets, #homs, #nonSNPs): (2108,0,5478) 397s Bootstrapping while preserving (#hets, #homs, #nonSNPs)... 397s Number of bootstrap samples: 100 397s Bootstrapping while preserving (#hets, #homs, #nonSNPs)...done 397s Segment #1 (chr 1, tcnId=1, dhId=1) of 4...done 397s Segment #2 (chr 1, tcnId=2, dhId=1) of 4... 397s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 397s 2 1 2 1 120992604 141510002 0 NA 0 397s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 397s 2 0 NA NA 0 NA NA NA 397s Number of TCNs: 0 397s Number of DHs: 0 397s int 0 397s int [1:14658] 1 2 3 4 5 6 7 8 9 10 ... 397s int(0) 397s Identify loci used to bootstrap DH means... 397s Heterozygous SNPs to resample for DH: 397s int 0 397s Identify loci used to bootstrap DH means...done 397s Identify loci used to bootstrap TCN means... 397s SNPs: 397s int(0) 397s Non-polymorphic loci: 397s int(0) 397s Heterozygous SNPs to resample for TCN: 397s int(0) 397s Homozygous SNPs to resample for TCN: 397s int(0) 397s Non-polymorphic loci to resample for TCN: 397s int(0) 397s Heterozygous SNPs with non-DH to resample for TCN: 397s int(0) 397s Loci to resample for TCN: 397s int(0) 397s Identify loci used to bootstrap TCN means...done 397s Number of (#hets, #homs, #nonSNPs): (0,0,0) 397s Bootstrapping while preserving (#hets, #homs, #nonSNPs)... 397s Number of bootstrap samples: 100 397s Bootstrapping while preserving (#hets, #homs, #nonSNPs)...done 397s Segment #2 (chr 1, tcnId=2, dhId=1) of 4...done 397s Segment #3 (chr 1, tcnId=3, dhId=1) of 4... 397s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 397s 3 1 3 1 141510003 185449813 2681 2.0689 777 397s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 397s 3 777 141510003 185449813 777 0.0973 0.933798 1.135102 397s Number of TCNs: 2681 397s Number of DHs: 777 397s int [1:2681] 7587 7588 7589 7590 7591 7592 7593 7594 7595 7596 ... 397s int [1:14658] 1 2 3 4 5 6 7 8 9 10 ... 397s int [1:2681] 7587 7588 7589 7590 7591 7592 7593 7594 7595 7596 ... 397s Identify loci used to bootstrap DH means... 397s Heterozygous SNPs to resample for DH: 397s int [1:777] 7587 7588 7594 7614 7616 7626 7627 7628 7635 7638 ... 397s Identify loci used to bootstrap DH means...done 397s Identify loci used to bootstrap TCN means... 397s SNPs: 397s int [1:777] 7587 7588 7594 7614 7616 7626 7627 7628 7635 7638 ... 397s Non-polymorphic loci: 397s int [1:1904] 7589 7590 7591 7592 7593 7595 7596 7597 7598 7599 ... 397s Heterozygous SNPs to resample for TCN: 397s int [1:777] 7587 7588 7594 7614 7616 7626 7627 7628 7635 7638 ... 397s Homozygous SNPs to resample for TCN: 397s int(0) 397s Non-polymorphic loci to resample for TCN: 397s int [1:1904] 7589 7590 7591 7592 7593 7595 7596 7597 7598 7599 ... 397s Heterozygous SNPs with non-DH to resample for TCN: 397s int(0) 397s Loci to resample for TCN: 397s int [1:2681] 7587 7588 7589 7590 7591 7592 7593 7594 7595 7596 ... 397s Identify loci used to bootstrap TCN means...done 397s Number of (#hets, #homs, #nonSNPs): (777,0,1904) 397s Bootstrapping while preserving (#hets, #homs, #nonSNPs)... 397s Number of bootstrap samples: 100 397s Bootstrapping while preserving (#hets, #homs, #nonSNPs)...done 397s Segment #3 (chr 1, tcnId=3, dhId=1) of 4...done 397s Segment #4 (chr 1, tcnId=4, dhId=1) of 4... 397s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 397s 4 1 4 1 185449813 247137334 4391 2.6341 1311 397s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 397s 4 1311 185449813 247137334 1311 0.2295 1.014787 1.619313 397s Number of TCNs: 4391 397s Number of DHs: 1311 397s int [1:4391] 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 397s int [1:14658] 1 2 3 4 5 6 7 8 9 10 ... 397s int [1:4391] 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 397s Identify loci used to bootstrap DH means... 397s Heterozygous SNPs to resample for DH: 397s int [1:1311] 10269 10271 10281 10282 10283 10293 10295 10297 10300 10302 ... 397s Identify loci used to bootstrap DH means...done 397s Identify loci used to bootstrap TCN means... 397s SNPs: 397s int [1:1311] 10269 10271 10281 10282 10283 10293 10295 10297 10300 10302 ... 397s Non-polymorphic loci: 397s int [1:3080] 10268 10270 10272 10273 10274 10275 10276 10277 10278 10279 ... 397s Heterozygous SNPs to resample for TCN: 397s int [1:1311] 10269 10271 10281 10282 10283 10293 10295 10297 10300 10302 ... 397s Homozygous SNPs to resample for TCN: 397s int(0) 397s Non-polymorphic loci to resample for TCN: 397s int [1:3080] 10268 10270 10272 10273 10274 10275 10276 10277 10278 10279 ... 397s Heterozygous SNPs with non-DH to resample for TCN: 397s int(0) 397s Loci to resample for TCN: 397s int [1:4391] 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 397s Identify loci used to bootstrap TCN means...done 397s Number of (#hets, #homs, #nonSNPs): (1311,0,3080) 397s Bootstrapping while preserving (#hets, #homs, #nonSNPs)... 397s Number of bootstrap samples: 100 397s Bootstrapping while preserving (#hets, #homs, #nonSNPs)...done 397s Segment #4 (chr 1, tcnId=4, dhId=1) of 4...done 397s Bootstrapped segment mean levels 397s num [1:4, 1:100, 1:4] 1.39 NA 2.08 2.63 1.38 ... 397s - attr(*, "dimnames")=List of 3 397s ..$ : NULL 397s ..$ : NULL 397s ..$ : chr [1:4] "tcn" "dh" "c1" "c2" 397s Calculating (C1,C2) mean levels from (TCN,DH) mean levels... 397s num [1:4, 1:100, 1:4] 1.39 NA 2.08 2.63 1.38 ... 397s - attr(*, "dimnames")=List of 3 397s ..$ : NULL 397s ..$ : NULL 397s ..$ : chr [1:4] "tcn" "dh" "c1" "c2" 397s Calculating (C1,C2) mean levels from (TCN,DH) mean levels...done 397s Calculating polar (alpha,radius,manhattan) for change points... 397s num [1:3, 1:100, 1:2] NA NA -0.0752 NA NA ... 397s - attr(*, "dimnames")=List of 3 397s ..$ : NULL 397s ..$ : NULL 397s ..$ : chr [1:2] "c1" "c2" 397s Bootstrapped change points 397s num [1:3, 1:100, 1:5] NA NA -1.73 NA NA ... 397s - attr(*, "dimnames")=List of 3 397s ..$ : NULL 397s ..$ : NULL 397s ..$ : chr [1:5] "alpha" "radius" "manhattan" "d1" ... 397s Calculating polar (alpha,radius,manhattan) for change points...done 397s Bootstrapping (TCN,DH,C1,C2) segment mean levels...done 397s Summarizing bootstrapped segment ('tcn', 'dh', 'c1', 'c2') data... 397s num [1:4, 1:4, 1:4] NA NA NA NA NA NA NA NA NA NA ... 397s - attr(*, "dimnames")=List of 3 397s ..$ : NULL 397s ..$ : chr [1:4] "2.5%" "5%" "95%" "97.5%" 397s ..$ : chr [1:4] "tcn" "dh" "c1" "c2" 397s Field #1 ('tcn') of 4... 397s Segment #1 of 4... 397s Segment #1 of 4...done 397s Segment #2 of 4... 397s Segment #2 of 4...done 397s Segment #3 of 4... 397s Segment #3 of 4...done 397s Segment #4 of 4... 397s Segment #4 of 4...done 397s Field #1 ('tcn') of 4...done 397s Field #2 ('dh') of 4... 397s Segment #1 of 4... 397s Segment #1 of 4...done 397s Segment #2 of 4... 397s Segment #2 of 4...done 397s Segment #3 of 4... 397s Segment #3 of 4...done 397s Segment #4 of 4... 397s Segment #4 of 4...done 397s Field #2 ('dh') of 4...done 397s Field #3 ('c1') of 4... 397s Segment #1 of 4... 397s Segment #1 of 4...done 397s Segment #2 of 4... 397s Segment #2 of 4...done 397s Segment #3 of 4... 397s Segment #3 of 4...done 397s Segment #4 of 4... 397s Segment #4 of 4...done 397s Field #3 ('c1') of 4...done 397s Field #4 ('c2') of 4... 397s Segment #1 of 4... 397s Segment #1 of 4...done 397s Segment #2 of 4... 397s Segment #2 of 4...done 397s Segment #3 of 4... 397s Segment #3 of 4...done 397s Segment #4 of 4... 397s Segment #4 of 4...done 397s Field #4 ('c2') of 4...done 397s Bootstrap statistics 397s num [1:4, 1:4, 1:4] 1.38 NA 2.06 2.63 1.38 ... 397s - attr(*, "dimnames")=List of 3 397s ..$ : NULL 397s ..$ : chr [1:4] "2.5%" "5%" "95%" "97.5%" 397s ..$ : chr [1:4] "tcn" "dh" "c1" "c2" 397s Statistical sanity checks (iff B >= 100)... 397s Available summaries: 2.5%, 5%, 95%, 97.5% 397s Available quantiles: 0.025, 0.05, 0.95, 0.975 397s num [1:4, 1:4, 1:4] 1.38 NA 2.06 2.63 1.38 ... 397s - attr(*, "dimnames")=List of 3 397s ..$ : NULL 397s ..$ : chr [1:4] "2.5%" "5%" "95%" "97.5%" 397s ..$ : chr [1:4] "tcn" "dh" "c1" "c2" 397s Field #1 ('tcn') of 4... 397s Seg 1. mean=1.3853, range=[1.37909,1.39287], n=7586 397s Seg 2. mean=NA, range=[NA,NA], n=0 397s Seg 3. mean=2.0689, range=[2.05903,2.079], n=2681 397s Seg 4. mean=2.6341, range=[2.62504,2.64649], n=4391 397s Field #1 ('tcn') of 4...done 397s Field #2 ('dh') of 4... 397s Seg 1. mean=0.5116, range=[0.502148,0.519941], n=2108 397s Seg 2. mean=NA, range=[NA,NA], n=NA 397s Seg 3. mean=0.0973, range=[0.0906366,0.105818], n=777 397s Seg 4. mean=0.2295, range=[0.222919,0.237005], n=1311 397s Field #2 ('dh') of 4...done 397s Field #3 ('c1') of 4... 397s Seg 1. mean=0.33829, range=[0.332209,0.345936], n=2108 397s Seg 2. mean=NA, range=[NA,NA], n=NA 397s Seg 3. mean=0.933798, range=[0.924112,0.941776], n=777 397s Seg 4. mean=1.01479, range=[1.00381,1.02461], n=1311 397s Field #3 ('c1') of 4...done 397s Field #4 ('c2') of 4... 397s Seg 1. mean=1.04701, range=[1.03882,1.05318], n=2108 397s Seg 2. mean=NA, range=[NA,NA], n=NA 397s Seg 3. mean=1.1351, range=[1.12454,1.1465], n=777 397s Seg 4. mean=1.61931, range=[1.60862,1.63328], n=1311 397s Field #4 ('c2') of 4...done 397s Statistical sanity checks (iff B >= 100)...done 397s Summarizing bootstrapped segment ('tcn', 'dh', 'c1', 'c2') data...done 397s Summarizing bootstrapped changepoint ('alpha', 'radius', 'manhattan', 'd1', 'd2') data... 397s num [1:3, 1:4, 1:5] NA NA NA NA NA NA NA NA NA NA ... 397s - attr(*, "dimnames")=List of 3 397s ..$ : NULL 397s ..$ : chr [1:4] "2.5%" "5%" "95%" "97.5%" 397s ..$ : chr [1:5] "alpha" "radius" "manhattan" "d1" ... 397s Field #1 ('alpha') of 5... 397s Changepoint #1 of 3... 397s Changepoint #1 of 3...done 397s Changepoint #2 of 3... 397s Changepoint #2 of 3...done 397s Changepoint #3 of 3... 397s Changepoint #3 of 3...done 397s Field #1 ('alpha') of 5...done 397s Field #2 ('radius') of 5... 397s Changepoint #1 of 3... 397s Changepoint #1 of 3...done 397s Changepoint #2 of 3... 397s Changepoint #2 of 3...done 397s Changepoint #3 of 3... 397s Changepoint #3 of 3...done 397s Field #2 ('radius') of 5...done 397s Field #3 ('manhattan') of 5... 397s Changepoint #1 of 3... 397s Changepoint #1 of 3...done 397s Changepoint #2 of 3... 397s Changepoint #2 of 3...done 397s Changepoint #3 of 3... 397s Changepoint #3 of 3...done 397s Field #3 ('manhattan') of 5...done 397s Field #4 ('d1') of 5... 397s Changepoint #1 of 3... 397s Changepoint #1 of 3...done 397s Changepoint #2 of 3... 397s Changepoint #2 of 3...done 397s Changepoint #3 of 3... 397s Changepoint #3 of 3...done 397s Field #4 ('d1') of 5...done 397s Field #5 ('d2') of 5... 397s Changepoint #1 of 3... 397s Changepoint #1 of 3...done 397s Changepoint #2 of 3... 397s Changepoint #2 of 3...done 397s Changepoint #3 of 3... 397s Changepoint #3 of 3...done 397s Field #5 ('d2') of 5...done 397s Bootstrap statistics 397s num [1:3, 1:4, 1:5] NA NA -1.77 NA NA ... 397s - attr(*, "dimnames")=List of 3 397s ..$ : NULL 397s ..$ : chr [1:4] "2.5%" "5%" "95%" "97.5%" 397s ..$ : chr [1:5] "alpha" "radius" "manhattan" "d1" ... 397s Summarizing bootstrapped changepoint ('alpha', 'radius', 'manhattan', 'd1', 'd2') data...done 397s Resample (TCN,DH) signals and re-estimate summaries for segment & changepoint...done 397s > print(fit) 397s chromosome tcnId dhId start end tcnNbrOfLoci tcnMean tcnNbrOfSNPs 397s 1 1 1 1 554484 120992603 7586 1.3853 2108 397s 2 1 2 1 120992604 141510002 0 NA 0 397s 3 1 3 1 141510003 185449813 2681 2.0689 777 397s 4 1 4 1 185449813 247137334 4391 2.6341 1311 397s tcnNbrOfHets dhNbrOfLoci dhMean c1Mean c2Mean 397s 1 2108 2108 0.5116 0.3382903 1.047010 397s 2 0 NA NA NA NA 397s 3 777 777 0.0973 0.9337980 1.135102 397s 4 1311 1311 0.2295 1.0147870 1.619313 397s > plotTracks(fit) 397s > 397s > 397s > 397s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 397s > # Calling segments with run of homozygosity (ROH) 397s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 397s > fit <- callROH(fit, verbose=-10) 397s Calling ROH... 397s Segment #1 of 4... 397s Calling ROH for a single segment... 397s Number of SNPs: 7586 397s Calling ROH for a single segment...done 397s Segment #1 of 4...done 397s Segment #2 of 4... 397s Calling ROH for a single segment... 397s Number of SNPs: 0 397s Calling ROH for a single segment...done 397s Segment #2 of 4...done 397s Segment #3 of 4... 397s Calling ROH for a single segment... 397s Number of SNPs: 2681 397s Calling ROH for a single segment...done 397s Segment #3 of 4...done 397s Segment #4 of 4... 397s Calling ROH for a single segment... 397s Number of SNPs: 4391 397s Calling ROH for a single segment...done 397s Segment #4 of 4...done 397s ROH calls: 397s logi [1:4] FALSE NA FALSE FALSE 397s Mode FALSE NA's 397s logical 3 1 397s Calling ROH...done 397s > print(fit) 397s chromosome tcnId dhId start end tcnNbrOfLoci tcnMean tcnNbrOfSNPs 397s 1 1 1 1 554484 120992603 7586 1.3853 2108 397s 2 1 2 1 120992604 141510002 0 NA 0 397s 3 1 3 1 141510003 185449813 2681 2.0689 777 397s 4 1 4 1 185449813 247137334 4391 2.6341 1311 397s tcnNbrOfHets dhNbrOfLoci dhMean c1Mean c2Mean rohCall 397s 1 2108 2108 0.5116 0.3382903 1.047010 FALSE 397s 2 0 NA NA NA NA NA 397s 3 777 777 0.0973 0.9337980 1.135102 FALSE 397s 4 1311 1311 0.2295 1.0147870 1.619313 FALSE 397s > plotTracks(fit) 397s > 397s > 397s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 397s > # Estimate background 397s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 397s > kappa <- estimateKappa(fit, verbose=-10) 397s Estimate global background (including normal contamination and more)... 397s Number of segments: 3 397s Estimating threshold Delta0.5 from the empirical density of C1:s... 397s adjust: 1 397s minDensity: 0.2 397s ploidy: 2 397s All peaks: 397s type x density 397s 1 peak 0.3362194 1.101242 397s 3 peak 0.9811492 1.065635 397s C1=0 and C1=1 peaks: 397s type x density 397s 1 peak 0.3362194 1.101242 397s 3 peak 0.9811492 1.065635 397s Estimate of Delta0.5: 0.65868427808456 397s Estimating threshold Delta0.5 from the empirical density of C1:s...done 397s Number of segments with C1 < Delta0.5: 1 397s Estimate of kappa: 0.33829026 397s Estimate global background (including normal contamination and more)...done 397s Warning message: 397s In density.default(c1, weights = weights, adjust = adjust, from = from, : 397s Selecting bandwidth *not* using 'weights' 397s > print(kappa) 397s [1] 0.3382903 397s > ## [1] 0.226011 397s > 397s > 397s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 397s > # Calling segments in allelic balance (AB) 397s > # NOTE: Ideally, this should be done on whole-genome data 397s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 397s > # Explicitly estimate the threshold in DH for calling AB 397s > # (which be done by default by the caller, if skipped here) 397s > deltaAB <- estimateDeltaAB(fit, flavor="qq(DH)", verbose=-10) 397s Estimating DH threshold for calling allelic imbalances... 397s flavor: qq(DH) 397s scale: 1 397s Estimating DH threshold for AB caller... 397s quantile #1: 0.05 397s Symmetric quantile #2: 0.9 397s Number of segments: 3 397s Weighted 5% quantile of DH: 0.257710 397s Number of segments with small DH: 2 397s Number of data points: 7072 397s Number of finite data points: 2088 397s Estimate of (1-0.9):th and 50% quantiles: (0.0310411,0.163658) 397s Estimate of 0.9:th "symmetric" quantile: 0.296275 397s Estimating DH threshold for AB caller...done 397s Estimated delta: 0.296 397s Estimating DH threshold for calling allelic imbalances...done 397s > if (Sys.getenv("_R_CHECK_FULL_") == "") { 397s + # Ad hoc workaround for not utilizing all of the data 397s + # in the test, which results in a poor estimate 397s + deltaAB <- 0.165 397s + } 397s > print(deltaAB) 397s [1] 0.165 397s > ## [1] 0.1657131 397s > 397s > fit <- callAB(fit, delta=deltaAB, verbose=-10) 397s Calling segments of allelic balance from one-sided DH bootstrap confidence intervals... 397s delta (offset adjusting for bias in DH): 0.165 397s alpha (CI quantile; significance level): 0.05 397s Calling segments... 397s Number of segments called allelic balance (AB): 1 (25.00%) of 4 397s Calling segments...done 397s Calling segments of allelic balance from one-sided DH bootstrap confidence intervals...done 397s > print(fit) 397s chromosome tcnId dhId start end tcnNbrOfLoci tcnMean tcnNbrOfSNPs 397s 1 1 1 1 554484 120992603 7586 1.3853 2108 397s 2 1 2 1 120992604 141510002 0 NA 0 397s 3 1 3 1 141510003 185449813 2681 2.0689 777 397s 4 1 4 1 185449813 247137334 4391 2.6341 1311 397s tcnNbrOfHets dhNbrOfLoci dhMean c1Mean c2Mean rohCall abCall 397s 1 2108 2108 0.5116 0.3382903 1.047010 FALSE FALSE 397s 2 0 NA NA NA NA NA NA 397s 3 777 777 0.0973 0.9337980 1.135102 FALSE TRUE 397s 4 1311 1311 0.2295 1.0147870 1.619313 FALSE FALSE 397s > plotTracks(fit) 397s > 397s > # Even if not explicitly specified, the estimated 397s > # threshold parameter is returned by the caller 397s > stopifnot(fit$params$deltaAB == deltaAB) 397s > 397s > 397s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 397s > # Calling segments in loss-of-heterozygosity (LOH) 397s > # NOTE: Ideally, this should be done on whole-genome data 397s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 397s > # Explicitly estimate the threshold in C1 for calling LOH 397s > # (which be done by default by the caller, if skipped here) 397s > deltaLOH <- estimateDeltaLOH(fit, flavor="minC1|nonAB", verbose=-10) 397s Estimating DH threshold for calling LOH... 397s flavor: minC1|nonAB 397s Estimating DH threshold for calling LOH as the midpoint between guessed C1=0 and C1=1... 397s Argument 'midpoint': 0.5 397s Number of segments: 4 397s Number of segments in allelic balance: 1 (25.0%) of 4 397s Number of segments not in allelic balance: 2 (50.0%) of 4 397s Number of segments in allelic balance and TCN <= 3.00: 1 (25.0%) of 4 397s C: 2.07 397s Corrected C1 (=C/2): 1.03 397s Number of DHs: 777 397s Weights: 1 397s Weighted median of (corrected) C1 in allelic balance: 1.034 397s Smallest C1 among segments not in allelic balance: 0.338 397s There are 1 segments with in total 2108 heterozygous SNPs with this level. 397s Midpoint between the two: 0.686 397s Estimating DH threshold for calling LOH as the midpoint between guessed C1=0 and C1=1...done 397s delta: 0.686 397s Estimating DH threshold for calling LOH...done 397s > print(deltaLOH) 397s [1] 0.6863701 397s > ## [1] 0.625175 397s > 397s > fit <- callLOH(fit, delta=deltaLOH, verbose=-10) 397s Calling segments of allelic balance from one-sided DH bootstrap confidence intervals... 397s delta (offset adjusting for bias in C1): 0.68637013 397s alpha (CI quantile; significance level): 0.05 397s Calling segments... 397s Number of segments called low C1 (LowC1, "LOH_C1"): 1 (25.00%) of 4 397s Calling segments...done 397s Calling segments of allelic balance from one-sided DH bootstrap confidence intervals...done 397s > print(fit) 397s chromosome tcnId dhId start end tcnNbrOfLoci tcnMean tcnNbrOfSNPs 397s 1 1 1 1 554484 120992603 7586 1.3853 2108 397s 2 1 2 1 120992604 141510002 0 NA 0 397s 3 1 3 1 141510003 185449813 2681 2.0689 777 397s 4 1 4 1 185449813 247137334 4391 2.6341 1311 397s tcnNbrOfHets dhNbrOfLoci dhMean c1Mean c2Mean rohCall abCall lohCall 397s 1 2108 2108 0.5116 0.3382903 1.047010 FALSE FALSE TRUE 397s 2 0 NA NA NA NA NA NA NA 397s 3 777 777 0.0973 0.9337980 1.135102 FALSE TRUE FALSE 397s 4 1311 1311 0.2295 1.0147870 1.619313 FALSE FALSE FALSE 397s > plotTracks(fit) 397s > 397s > # Even if not explicitly specified, the estimated 397s > # threshold parameter is returned by the caller 397s > stopifnot(fit$params$deltaLOH == deltaLOH) 397s > 397s > 397s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 397s > # Calling segments that are gained, copy neutral, and lost 397s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 397s > fit <- callGNL(fit, verbose=-10) 397s Calling gain, neutral, and loss based TCNs of AB segments... 397s Calling neutral TCNs... 397s callCopyNeutralByTCNofAB... 397s Alpha: 0.05 397s Delta CN: 0.33085487 397s Calling copy-neutral segments... 397s Retrieve TCN confidence intervals for all segments... 397s Interval: [0.025,0.975] 397s Retrieve TCN confidence intervals for all segments...done 397s Estimating TCN confidence interval of copy-neutral AB segments... 397s calcStatsForCopyNeutralABs... 397s Identifying copy neutral AB segments... 397s Number of AB segments: 1 397s Identifying segments that are copy neutral states... 397s Number of segments in allelic balance: 1 397s Identifying segments that are copy neutral states...done 397s Number of copy-neutral AB segments: 1 397s Extracting all copy neutral AB segments across all chromosomes into one big segment... 397s chromosome tcnId dhId start end tcnNbrOfLoci tcnMean tcnNbrOfSNPs 397s 3 1 3 1 141510003 185449813 2681 2.0689 777 397s tcnNbrOfHets dhNbrOfLoci dhMean c1Mean c2Mean rohCall abCall lohCall 397s 3 777 777 0.0973 0.933798 1.135102 FALSE TRUE FALSE 397s Extracting all copy neutral AB segments across all chromosomes into one big segment...done 397s Identifying copy neutral AB segments...done 397s Bootstrap the identified copy-neutral states... 397s Bootstrap the identified copy-neutral states...done 397s tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets dhNbrOfLoci dhMean c1Mean 397s 3 2681 2.0689 777 777 777 0.0973 0.933798 397s c2Mean tcn_2.5% tcn_5% tcn_95% tcn_97.5% dh_2.5% dh_5% dh_95% 397s 3 1.135102 2.055164 2.057694 2.078831 2.081454 0.08974138 0.09080508 0.1035891 397s dh_97.5% c1_2.5% c1_5% c1_95% c1_97.5% c2_2.5% c2_5% c2_95% 397s 3 0.1050478 0.923788 0.925412 0.9417056 0.9433752 1.124908 1.126631 1.143571 397s c2_97.5% 397s 3 1.145214 397s calcStatsForCopyNeutralABs...done 397s Bootstrap statistics for copy-neutral AB segments: 397s tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets dhNbrOfLoci dhMean c1Mean 397s 3 2681 2.0689 777 777 777 0.0973 0.933798 397s c2Mean tcn_2.5% tcn_5% tcn_95% tcn_97.5% dh_2.5% dh_5% dh_95% 397s 3 1.135102 2.055164 2.057694 2.078831 2.081454 0.08974138 0.09080508 0.1035891 397s dh_97.5% c1_2.5% c1_5% c1_95% c1_97.5% c2_2.5% c2_5% c2_95% 397s 3 0.1050478 0.923788 0.925412 0.9417056 0.9433752 1.124908 1.126631 1.143571 397s c2_97.5% 397s 3 1.145214 397s [1] "TCN statistics:" 397s tcnMean tcn_2.5% tcn_5% tcn_95% tcn_97.5% 397s 2.068900 2.055164 2.057694 2.078831 2.081454 397s 95%-confidence interval of TCN mean for the copy-neutral state: [2.05516,2.08145] (mean=2.0689) 397s Estimating TCN confidence interval of copy-neutral AB segments...done 397s Identify all copy-neutral segments... 397s DeltaCN: +/-0.330855 397s Call ("acceptance") region: [1.72431,2.41231] 397s Total number of segments: 4 397s Number of segments called allelic balance: 1 397s Number of segments called copy neutral: 1 397s Number of AB segments called copy neutral: 1 397s Number of non-AB segments called copy neutral: 0 397s Identify all copy-neutral segments...done 397s Calling copy-neutral segments...done 397s callCopyNeutralByTCNofAB...done 397s Calling neutral TCNs...done 397s Number of NTCN calls: 1 (25.00%) of 4 397s Mean TCN of AB segments: 2.06831 397s Calling loss... 397s Number of loss calls: 1 (25.00%) of 4 397s Calling loss...done 397s Calling gain... 397s Number of loss calls: 1 (25.00%) of 4 397s Calling gain...done 397s Calling gain, neutral, and loss based TCNs of AB segments...done 397s Warning message: 397s In density.default(c1, weights = weights, adjust = adjust, from = from, : 397s Selecting bandwidth *not* using 'weights' 397s > print(fit) 397s chromosome tcnId dhId start end tcnNbrOfLoci tcnMean tcnNbrOfSNPs 397s 1 1 1 1 554484 120992603 7586 1.3853 2108 397s 2 1 2 1 120992604 141510002 0 NA 0 397s 3 1 3 1 141510003 185449813 2681 2.0689 777 397s 4 1 4 1 185449813 247137334 4391 2.6341 1311 397s tcnNbrOfHets dhNbrOfLoci dhMean c1Mean c2Mean rohCall abCall lohCall 397s 1 2108 2108 0.5116 0.3382903 1.047010 FALSE FALSE TRUE 397s 2 0 NA NA NA NA NA NA NA 397s 3 777 777 0.0973 0.9337980 1.135102 FALSE TRUE FALSE 397s 4 1311 1311 0.2295 1.0147870 1.619313 FALSE FALSE FALSE 397s ntcnCall lossCall gainCall 397s 1 FALSE TRUE FALSE 397s 2 NA NA NA 397s 3 TRUE FALSE FALSE 397s 4 FALSE FALSE TRUE 397s > plotTracks(fit) 397s > 397s > proc.time() 397s user system elapsed 397s 3.952 0.127 4.068 397s Test segmentByPairedPSCBS,calls passed 397s 0 397s Begin test segmentByPairedPSCBS,futures 408s + cat segmentByPairedPSCBS,futures.Rout 408s 408s R version 4.5.2 (2025-10-31) -- "[Not] Part in a Rumble" 408s Copyright (C) 2025 The R Foundation for Statistical Computing 408s Platform: aarch64-unknown-linux-gnu 408s 408s R is free software and comes with ABSOLUTELY NO WARRANTY. 408s You are welcome to redistribute it under certain conditions. 408s Type 'license()' or 'licence()' for distribution details. 408s 408s R is a collaborative project with many contributors. 408s Type 'contributors()' for more information and 408s 'citation()' on how to cite R or R packages in publications. 408s 408s Type 'demo()' for some demos, 'help()' for on-line help, or 408s 'help.start()' for an HTML browser interface to help. 408s Type 'q()' to quit R. 408s 408s [Previously saved workspace restored] 408s 408s > library(PSCBS) 408s PSCBS v0.68.0 (2025-04-18 19:40:02 UTC) successfully loaded. See ?PSCBS for help. 408s > library(utils) 408s > 408s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 408s > # Load SNP microarray data 408s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 408s > data <- PSCBS::exampleData("paired.chr01") 408s > 408s > 408s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 408s > # Paired PSCBS segmentation 408s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 408s > # Drop single-locus outliers 408s > dataS <- dropSegmentationOutliers(data) 408s > 408s > # Run light-weight tests by default 408s > if (Sys.getenv("_R_CHECK_FULL_") == "") { 408s + # Use only every 5th data point 408s + dataS <- dataS[seq(from=1, to=nrow(data), by=5),] 408s + # Number of segments (for assertion) 408s + nSegs <- 4L 408s + } else { 408s + # Full tests 408s + nSegs <- 11L 408s + } 408s > 408s > str(dataS) 408s 'data.frame': 14670 obs. of 6 variables: 408s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 408s $ x : int 1145994 2941694 3710825 4240737 4276892 4464544 4714611 5095111 5034491 5158416 ... 408s $ CT : num 1.63 1.4 1.41 1.17 1.16 ... 408s $ betaT : num 0.7574 0.169 0.2357 0.2604 0.0576 ... 408s $ CN : num 2.36 2.13 2.26 2.01 2.32 ... 408s $ betaN : num 0.8274 0.5072 0.1671 0.1609 0.0421 ... 408s > 408s > 408s > ## Create multiple chromosomes 408s > data <- list() 408s > for (cc in 1:3) { 408s + dataS$chromosome <- cc 408s + data[[cc]] <- dataS 408s + } 408s > data <- Reduce(rbind, data) 408s > str(data) 408s 'data.frame': 44010 obs. of 6 variables: 408s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 408s $ x : int 1145994 2941694 3710825 4240737 4276892 4464544 4714611 5095111 5034491 5158416 ... 408s $ CT : num 1.63 1.4 1.41 1.17 1.16 ... 408s $ betaT : num 0.7574 0.169 0.2357 0.2604 0.0576 ... 408s $ CN : num 2.36 2.13 2.26 2.01 2.32 ... 408s $ betaN : num 0.8274 0.5072 0.1671 0.1609 0.0421 ... 408s > 408s > 408s > message("*** segmentByPairedPSCBS() via futures ...") 408s *** segmentByPairedPSCBS() via futures ... 408s > 408s > library("future") 408s > oplan <- plan() 408s > 408s > strategies <- c("sequential", "multisession") 408s > 408s > ## Test 'future.batchtools' futures? 408s > pkg <- "future.batchtools" 408s > if (require(pkg, character.only=TRUE)) { 408s + strategies <- c(strategies, "batchtools_local") 408s + } 408s Loading required package: future.batchtools 408s Warning message: 408s In library(package, lib.loc = lib.loc, character.only = TRUE, logical.return = TRUE, : 408s there is no package called 'future.batchtools' 408s > 408s > message("Future strategies to test: ", paste(sQuote(strategies), collapse=", ")) 408s Future strategies to test: 'sequential', 'multisession' 408s > 408s > fits <- list() 408s > for (strategy in strategies) { 408s + message(sprintf("- segmentByPairedPSCBS() using '%s' futures ...", strategy)) 408s + plan(strategy) 408s + fit <- segmentByPairedPSCBS(data, seed=0xBEEF, verbose=TRUE) 408s + fits[[strategy]] <- fit 408s + equal <- all.equal(fit, fits[[1]]) 408s + if (!equal) { 408s + str(fit) 408s + str(fits[[1]]) 408s + print(equal) 408s + stop(sprintf("segmentByPairedPSCBS() using '%s' futures does not produce the same results as when using '%s' futures", strategy, names(fits)[1])) 408s + } 408s + } 408s - segmentByPairedPSCBS() using 'sequential' futures ... 408s Segmenting paired tumor-normal signals using Paired PSCBS... 408s Calling genotypes from normal allele B fractions... 408s num [1:44010] 0.8274 0.5072 0.1671 0.1609 0.0421 ... 408s Called genotypes: 408s num [1:44010] 1 0.5 0 0 0 0 1 0 1 0.5 ... 408s - attr(*, "modelFit")=List of 1 408s ..$ :List of 7 408s .. ..$ flavor : chr "density" 408s .. ..$ cn : int 2 408s .. ..$ nbrOfGenotypeGroups: int 3 408s .. ..$ tau : num [1:2] 0.312 0.678 408s .. ..$ n : int 43920 408s .. ..$ fit :Classes 'PeaksAndValleys' and 'data.frame': 5 obs. of 3 variables: 408s .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 408s .. .. ..$ x : num [1:5] 0.0999 0.312 0.4986 0.6775 0.8922 408s .. .. ..$ density: num [1:5] 1.622 0.465 1.125 0.496 1.587 408s .. ..$ fitValleys :Classes 'PeaksAndValleys' and 'data.frame': 2 obs. of 3 variables: 408s .. .. ..$ type : chr [1:2] "valley" "valley" 408s .. .. ..$ x : num [1:2] 0.312 0.678 408s .. .. ..$ density: num [1:2] 0.465 0.496 408s ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 408s muN 408s 0 0.5 1 408s 15627 12633 15750 408s Calling genotypes from normal allele B fractions...done 408s Normalizing betaT using betaN (TumorBoost)... 408s Normalized BAFs: 408s num [1:44010] 0.9301 0.1667 0.0685 0.0995 0.0155 ... 408s - attr(*, "modelFit")=List of 5 408s ..$ method : chr "normalizeTumorBoost" 408s ..$ flavor : chr "v4" 408s ..$ delta : num [1:44010] -0.17264 0.00239 0.1671 0.16085 0.04213 ... 408s .. ..- attr(*, "modelFit")=List of 1 408s .. .. ..$ :List of 7 408s .. .. .. ..$ flavor : chr "density" 408s .. .. .. ..$ cn : int 2 408s .. .. .. ..$ nbrOfGenotypeGroups: int 3 408s .. .. .. ..$ tau : num [1:2] 0.312 0.678 408s .. .. .. ..$ n : int 43920 408s .. .. .. ..$ fit :Classes 'PeaksAndValleys' and 'data.frame': 5 obs. of 3 variables: 408s .. .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 408s .. .. .. .. ..$ x : num [1:5] 0.0999 0.312 0.4986 0.6775 0.8922 408s .. .. .. .. ..$ density: num [1:5] 1.622 0.465 1.125 0.496 1.587 408s .. .. .. ..$ fitValleys :Classes 'PeaksAndValleys' and 'data.frame': 2 obs. of 3 variables: 408s .. .. .. .. ..$ type : chr [1:2] "valley" "valley" 408s .. .. .. .. ..$ x : num [1:2] 0.312 0.678 408s .. .. .. .. ..$ density: num [1:2] 0.465 0.496 408s .. .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 408s ..$ preserveScale: logi FALSE 408s ..$ scaleFactor : num NA 408s Normalizing betaT using betaN (TumorBoost)...done 408s Setup up data... 408s 'data.frame': 44010 obs. of 7 variables: 408s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 408s $ x : num 1145994 2941694 3710825 4240737 4276892 ... 408s $ CT : num 1.63 1.4 1.41 1.17 1.16 ... 408s $ betaT : num 0.7574 0.169 0.2357 0.2604 0.0576 ... 408s $ betaTN : num 0.9301 0.1667 0.0685 0.0995 0.0155 ... 408s ..- attr(*, "modelFit")=List of 5 408s .. ..$ method : chr "normalizeTumorBoost" 408s .. ..$ flavor : chr "v4" 408s .. ..$ delta : num [1:44010] -0.17264 0.00239 0.1671 0.16085 0.04213 ... 408s .. .. ..- attr(*, "modelFit")=List of 1 408s .. .. .. ..$ :List of 7 408s .. .. .. .. ..$ flavor : chr "density" 408s .. .. .. .. ..$ cn : int 2 408s .. .. .. .. ..$ nbrOfGenotypeGroups: int 3 408s .. .. .. .. ..$ tau : num [1:2] 0.312 0.678 408s .. .. .. .. ..$ n : int 43920 408s .. .. .. .. ..$ fit :Classes 'PeaksAndValleys' and 'data.frame': 5 obs. of 3 variables: 408s .. .. .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 408s .. .. .. .. .. ..$ x : num [1:5] 0.0999 0.312 0.4986 0.6775 0.8922 408s .. .. .. .. .. ..$ density: num [1:5] 1.622 0.465 1.125 0.496 1.587 408s .. .. .. .. ..$ fitValleys :Classes 'PeaksAndValleys' and 'data.frame': 2 obs. of 3 variables: 408s .. .. .. .. .. ..$ type : chr [1:2] "valley" "valley" 408s .. .. .. .. .. ..$ x : num [1:2] 0.312 0.678 408s .. .. .. .. .. ..$ density: num [1:2] 0.465 0.496 408s .. .. .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 408s .. ..$ preserveScale: logi FALSE 408s .. ..$ scaleFactor : num NA 408s $ betaN : num 0.8274 0.5072 0.1671 0.1609 0.0421 ... 408s $ muN : num 1 0.5 0 0 0 0 1 0 1 0.5 ... 408s ..- attr(*, "modelFit")=List of 1 408s .. ..$ :List of 7 408s .. .. ..$ flavor : chr "density" 408s .. .. ..$ cn : int 2 408s .. .. ..$ nbrOfGenotypeGroups: int 3 408s .. .. ..$ tau : num [1:2] 0.312 0.678 408s .. .. ..$ n : int 43920 408s .. .. ..$ fit :Classes 'PeaksAndValleys' and 'data.frame': 5 obs. of 3 variables: 408s .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 408s .. .. .. ..$ x : num [1:5] 0.0999 0.312 0.4986 0.6775 0.8922 408s .. .. .. ..$ density: num [1:5] 1.622 0.465 1.125 0.496 1.587 408s .. .. ..$ fitValleys :Classes 'PeaksAndValleys' and 'data.frame': 2 obs. of 3 variables: 408s .. .. .. ..$ type : chr [1:2] "valley" "valley" 408s .. .. .. ..$ x : num [1:2] 0.312 0.678 408s .. .. .. ..$ density: num [1:2] 0.465 0.496 408s .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 408s Setup up data...done 408s Dropping loci for which TCNs are missing... 408s Number of loci dropped: 36 408s Dropping loci for which TCNs are missing...done 408s Ordering data along genome... 408s 'data.frame': 43974 obs. of 7 variables: 408s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 408s $ x : num 554484 730720 782343 878522 916294 ... 408s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 408s $ betaT : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 408s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 408s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 408s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 408s Ordering data along genome...done 408s Segmenting multiple chromosomes... 408s Number of chromosomes: 3 408s Random seed temporarily set (seed=c(48879), kind="L'Ecuyer-CMRG") 408s Produced 3 seeds from this stream for future usage 408s Chromosome #1 ('Chr01') of 3... 408s 'data.frame': 14658 obs. of 8 variables: 408s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 408s $ x : num 554484 730720 782343 878522 916294 ... 408s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 408s $ betaT : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 408s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 408s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 408s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 408s $ index : int 1 2 3 4 5 6 7 8 9 10 ... 408s Known segments: 408s [1] chromosome start end 408s <0 rows> (or 0-length row.names) 408s Segmenting paired tumor-normal signals using Paired PSCBS... 408s Setup up data... 408s 'data.frame': 14658 obs. of 7 variables: 408s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 408s $ x : num 554484 730720 782343 878522 916294 ... 408s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 408s $ betaT : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 408s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 408s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 408s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 408s Setup up data...done 408s Ordering data along genome... 408s 'data.frame': 14658 obs. of 7 variables: 408s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 408s $ x : num 554484 730720 782343 878522 916294 ... 408s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 408s $ betaT : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 408s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 408s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 408s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 408s Ordering data along genome...done 408s Keeping only current chromosome for 'knownSegments'... 408s Chromosome: 1 408s Known segments for this chromosome: 408s [1] chromosome start end 408s <0 rows> (or 0-length row.names) 408s Keeping only current chromosome for 'knownSegments'...done 408s alphaTCN: 0.009 408s alphaDH: 0.001 408s Number of loci: 14658 408s Calculating DHs... 408s Number of SNPs: 14658 408s Number of heterozygous SNPs: 4209 (28.71%) 408s Normalized DHs: 408s num [1:14658] NA NA NA NA NA ... 408s Calculating DHs...done 408s Random seed temporarily set (seed=c(10407, 1066287653, -51199871, 161854402, -1995183193, 1503453565, -747102133), kind="L'Ecuyer-CMRG") 408s Produced 2 seeds from this stream for future usage 408s Identification of change points by total copy numbers... 408s Segmenting by CBS... 408s Chromosome: 1 408s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 408s Segmenting by CBS...done 408s List of 4 408s $ data :'data.frame': 14658 obs. of 4 variables: 408s ..$ chromosome: int [1:14658] 1 1 1 1 1 1 1 1 1 1 ... 408s ..$ x : num [1:14658] 554484 730720 782343 878522 916294 ... 408s ..$ y : num [1:14658] 1.88 1.8 1.59 1.64 1.53 ... 408s ..$ index : int [1:14658] 1 2 3 4 5 6 7 8 9 10 ... 408s $ output :'data.frame': 3 obs. of 6 variables: 408s ..$ sampleName: chr [1:3] NA NA NA 408s ..$ chromosome: int [1:3] 1 1 1 408s ..$ start : num [1:3] 5.54e+05 1.44e+08 1.85e+08 408s ..$ end : num [1:3] 1.44e+08 1.85e+08 2.47e+08 408s ..$ nbrOfLoci : int [1:3] 7599 2668 4391 408s ..$ mean : num [1:3] 1.39 2.07 2.63 408s $ segRows:'data.frame': 3 obs. of 2 variables: 408s ..$ startRow: int [1:3] 1 7600 10268 408s ..$ endRow : int [1:3] 7599 10267 14658 408s $ params :List of 5 408s ..$ alpha : num 0.009 408s ..$ undo : num 0 408s ..$ joinSegments : logi TRUE 408s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 408s .. ..$ chromosome: int 1 408s .. ..$ start : num -Inf 408s .. ..$ end : num Inf 408s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 408s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 408s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.379 0 0.379 0 0 408s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 408s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 408s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 408s Identification of change points by total copy numbers...done 408s Restructure TCN segmentation results... 408s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean 408s 1 1 554484 143926517 7599 1.3859 408s 2 1 143926517 185449813 2668 2.0704 408s 3 1 185449813 247137334 4391 2.6341 408s Number of TCN segments: 3 408s Restructure TCN segmentation results...done 408s Total CN segment #1 ([ 554484,1.43927e+08]) of 3... 408s Number of TCN loci in segment: 7599 408s Locus data for TCN segment: 408s 'data.frame': 7599 obs. of 9 variables: 408s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 408s $ x : num 554484 730720 782343 878522 916294 ... 408s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 408s $ betaT : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 408s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 408s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 408s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 408s $ index : int 1 2 3 4 5 6 7 8 9 10 ... 408s $ rho : num NA NA NA NA NA ... 408s Number of loci: 7599 408s Number of SNPs: 2120 (27.90%) 408s Number of heterozygous SNPs: 2120 (100.00%) 408s Chromosome: 1 408s Segmenting DH signals... 408s Segmenting by CBS... 408s Chromosome: 1 408s Random seed temporarily set (seed=c(10407, -821273412, -52578226, 1415511586, 721384351, -665928286, 1316562960), kind="L'Ecuyer-CMRG") 408s Segmenting by CBS...done 408s List of 4 408s $ data :'data.frame': 7599 obs. of 4 variables: 408s ..$ chromosome: int [1:7599] 1 1 1 1 1 1 1 1 1 1 ... 408s ..$ x : num [1:7599] 554484 730720 782343 878522 916294 ... 408s ..$ y : num [1:7599] NA NA NA NA NA ... 408s ..$ index : int [1:7599] 1 2 3 4 5 6 7 8 9 10 ... 408s $ output :'data.frame': 1 obs. of 6 variables: 408s ..$ sampleName: chr NA 408s ..$ chromosome: int 1 408s ..$ start : num 554484 408s ..$ end : num 1.44e+08 408s ..$ nbrOfLoci : int 2120 408s ..$ mean : num 0.51 408s $ segRows:'data.frame': 1 obs. of 2 variables: 408s ..$ startRow: int 10 408s ..$ endRow : int 7594 408s $ params :List of 5 408s ..$ alpha : num 0.001 408s ..$ undo : num 0 408s ..$ joinSegments : logi TRUE 408s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 408s .. ..$ chromosome: int 1 408s .. ..$ start : num 554484 408s .. ..$ end : num 1.44e+08 408s ..$ seed : int [1:7] 10407 -821273412 -52578226 1415511586 721384351 -665928286 1316562960 408s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 408s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.026 0 0.025 0 0 408s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 408s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 408s - attr(*, "randomSeed")= int [1:7] 10407 -821273412 -52578226 1415511586 721384351 -665928286 1316562960 408s DH segmentation (locally-indexed) rows: 408s startRow endRow 408s 1 10 7594 408s int [1:7599] 1 2 3 4 5 6 7 8 9 10 ... 408s DH segmentation rows: 408s startRow endRow 408s 1 10 7594 408s Segmenting DH signals...done 408s DH segmentation table: 408s dhStart dhEnd dhNbrOfLoci dhMean 408s 1 554484 143926517 2120 0.5101 408s startRow endRow 408s 1 10 7594 408s Rows: 408s [1] 1 408s TCN segmentation rows: 408s startRow endRow 408s 1 1 7599 408s TCN and DH segmentation rows: 408s startRow endRow 408s 1 1 7599 408s startRow endRow 408s 1 10 7594 408s NULL 408s TCN segmentation (expanded) rows: 408s startRow endRow 408s 1 1 7599 408s TCN and DH segmentation rows: 408s startRow endRow 408s 1 1 7599 408s 2 7600 10267 408s 3 10268 14658 408s startRow endRow 408s 1 10 7594 408s startRow endRow 408s 1 1 7599 408s Total CN segmentation table (expanded): 408s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 408s 1 1 554484 143926517 7599 1.3859 2120 2120 408s (TCN,DH) segmentation for one total CN segment: 408s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 408s 1 1 1 1 554484 143926517 7599 1.3859 2120 408s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 408s 1 2120 554484 143926517 2120 0.5101 408s Total CN segment #1 ([ 554484,1.43927e+08]) of 3...done 408s Total CN segment #2 ([1.43927e+08,1.8545e+08]) of 3... 408s Number of TCN loci in segment: 2668 408s Locus data for TCN segment: 408s 'data.frame': 2668 obs. of 9 variables: 408s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 408s $ x : num 1.44e+08 1.44e+08 1.44e+08 1.44e+08 1.44e+08 ... 408s $ CT : num 2.1 2.1 2.09 1.8 2.34 ... 408s $ betaT : num 0.027542 1.030222 1.094093 0.046763 -0.000948 ... 408s $ betaTN : num 0.027542 1.030222 1.094093 0.046763 -0.000948 ... 408s $ betaN : num 0.1624 0.8788 0.8225 0.1201 0.0317 ... 408s $ muN : num 0 1 1 0 0 1 0 0 0 0 ... 408s $ index : int 7600 7601 7602 7603 7604 7605 7606 7607 7608 7609 ... 408s $ rho : num NA NA NA NA NA NA NA NA NA NA ... 408s Number of loci: 2668 408s Number of SNPs: 775 (29.05%) 408s Number of heterozygous SNPs: 775 (100.00%) 408s Chromosome: 1 408s Segmenting DH signals... 408s Segmenting by CBS... 408s Chromosome: 1 408s Random seed temporarily set (seed=c(10407, -821273412, -52578226, 1415511586, 721384351, -665928286, 1316562960), kind="L'Ecuyer-CMRG") 408s Segmenting by CBS...done 408s List of 4 408s $ data :'data.frame': 2668 obs. of 4 variables: 408s ..$ chromosome: int [1:2668] 1 1 1 1 1 1 1 1 1 1 ... 408s ..$ x : num [1:2668] 1.44e+08 1.44e+08 1.44e+08 1.44e+08 1.44e+08 ... 408s ..$ y : num [1:2668] NA NA NA NA NA NA NA NA NA NA ... 408s ..$ index : int [1:2668] 1 2 3 4 5 6 7 8 9 10 ... 408s $ output :'data.frame': 1 obs. of 6 variables: 408s ..$ sampleName: chr NA 408s ..$ chromosome: int 1 408s ..$ start : num 1.44e+08 408s ..$ end : num 1.85e+08 408s ..$ nbrOfLoci : int 775 408s ..$ mean : num 0.097 408s $ segRows:'data.frame': 1 obs. of 2 variables: 408s ..$ startRow: int 15 408s ..$ endRow : int 2664 408s $ params :List of 5 408s ..$ alpha : num 0.001 408s ..$ undo : num 0 408s ..$ joinSegments : logi TRUE 408s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 408s .. ..$ chromosome: int 1 408s .. ..$ start : num 1.44e+08 408s .. ..$ end : num 1.85e+08 408s ..$ seed : int [1:7] 10407 -821273412 -52578226 1415511586 721384351 -665928286 1316562960 408s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 408s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.008 0 0.008 0 0 408s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 408s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 408s - attr(*, "randomSeed")= int [1:7] 10407 -821273412 -52578226 1415511586 721384351 -665928286 1316562960 408s DH segmentation (locally-indexed) rows: 408s startRow endRow 408s 1 15 2664 408s int [1:2668] 7600 7601 7602 7603 7604 7605 7606 7607 7608 7609 ... 408s DH segmentation rows: 408s startRow endRow 408s 1 7614 10263 408s Segmenting DH signals...done 408s DH segmentation table: 408s dhStart dhEnd dhNbrOfLoci dhMean 408s 1 143926517 185449813 775 0.097 408s startRow endRow 408s 1 7614 10263 408s Rows: 408s [1] 2 408s TCN segmentation rows: 408s startRow endRow 408s 2 7600 10267 408s TCN and DH segmentation rows: 408s startRow endRow 408s 2 7600 10267 408s startRow endRow 408s 1 7614 10263 408s startRow endRow 408s 1 1 7599 408s TCN segmentation (expanded) rows: 408s startRow endRow 408s 1 1 7599 408s 2 7600 10267 408s TCN and DH segmentation rows: 408s startRow endRow 408s 1 1 7599 408s 2 7600 10267 408s 3 10268 14658 408s startRow endRow 408s 1 10 7594 408s 2 7614 10263 408s startRow endRow 408s 1 1 7599 408s 2 7600 10267 408s Total CN segmentation table (expanded): 408s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 408s 2 1 143926517 185449813 2668 2.0704 775 775 408s (TCN,DH) segmentation for one total CN segment: 408s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 408s 2 2 1 1 143926517 185449813 2668 2.0704 775 408s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 408s 2 775 143926517 185449813 775 0.097 408s Total CN segment #2 ([1.43927e+08,1.8545e+08]) of 3...done 408s Total CN segment #3 ([1.8545e+08,2.47137e+08]) of 3... 408s Number of TCN loci in segment: 4391 408s Locus data for TCN segment: 408s 'data.frame': 4391 obs. of 9 variables: 408s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 408s $ x : num 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 408s $ CT : num 2.93 2.15 2.82 2.93 2.46 ... 408s $ betaT : num -0.169 0.609 1.028 0.525 0.968 ... 408s $ betaTN : num -0.169 0.609 1.028 0.525 0.968 ... 408s $ betaN : num 0.25 0.38 0.919 0.34 0.783 ... 408s $ muN : num 0 0.5 1 0.5 1 1 0 1 0 1 ... 408s $ index : int 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 408s $ rho : num NA 0.2186 NA 0.0503 NA ... 408s Number of loci: 4391 408s Number of SNPs: 1314 (29.92%) 408s Number of heterozygous SNPs: 1314 (100.00%) 408s Chromosome: 1 408s Segmenting DH signals... 408s Segmenting by CBS... 408s Chromosome: 1 408s Random seed temporarily set (seed=c(10407, -821273412, -52578226, 1415511586, 721384351, -665928286, 1316562960), kind="L'Ecuyer-CMRG") 408s Segmenting by CBS...done 408s List of 4 408s $ data :'data.frame': 4391 obs. of 4 variables: 408s ..$ chromosome: int [1:4391] 1 1 1 1 1 1 1 1 1 1 ... 408s ..$ x : num [1:4391] 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 408s ..$ y : num [1:4391] NA 0.2186 NA 0.0503 NA ... 408s ..$ index : int [1:4391] 1 2 3 4 5 6 7 8 9 10 ... 408s $ output :'data.frame': 1 obs. of 6 variables: 408s ..$ sampleName: chr NA 408s ..$ chromosome: int 1 408s ..$ start : num 1.85e+08 408s ..$ end : num 2.47e+08 408s ..$ nbrOfLoci : int 1314 408s ..$ mean : num 0.23 408s $ segRows:'data.frame': 1 obs. of 2 variables: 408s ..$ startRow: int 2 408s ..$ endRow : int 4388 408s $ params :List of 5 408s ..$ alpha : num 0.001 408s ..$ undo : num 0 408s ..$ joinSegments : logi TRUE 408s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 408s .. ..$ chromosome: int 1 408s .. ..$ start : num 1.85e+08 408s .. ..$ end : num 2.47e+08 408s ..$ seed : int [1:7] 10407 -821273412 -52578226 1415511586 721384351 -665928286 1316562960 408s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 408s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.014 0 0.015 0 0 408s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 408s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 408s - attr(*, "randomSeed")= int [1:7] 10407 -821273412 -52578226 1415511586 721384351 -665928286 1316562960 408s DH segmentation (locally-indexed) rows: 408s startRow endRow 408s 1 2 4388 408s int [1:4391] 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 408s DH segmentation rows: 408s startRow endRow 408s 1 10269 14655 408s Segmenting DH signals...done 408s DH segmentation table: 408s dhStart dhEnd dhNbrOfLoci dhMean 408s 1 185449813 247137334 1314 0.2295 408s startRow endRow 408s 1 10269 14655 408s Rows: 408s [1] 3 408s TCN segmentation rows: 408s startRow endRow 408s 3 10268 14658 408s TCN and DH segmentation rows: 408s startRow endRow 408s 3 10268 14658 408s startRow endRow 408s 1 10269 14655 408s startRow endRow 408s 1 1 7599 408s 2 7600 10267 408s TCN segmentation (expanded) rows: 408s startRow endRow 408s 1 1 7599 408s 2 7600 10267 408s 3 10268 14658 408s TCN and DH segmentation rows: 408s startRow endRow 408s 1 1 7599 408s 2 7600 10267 408s 3 10268 14658 408s startRow endRow 408s 1 10 7594 408s 2 7614 10263 408s 3 10269 14655 408s startRow endRow 408s 1 1 7599 408s 2 7600 10267 408s 3 10268 14658 408s Total CN segmentation table (expanded): 408s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 408s 3 1 185449813 247137334 4391 2.6341 1314 1314 408s (TCN,DH) segmentation for one total CN segment: 408s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 408s 3 3 1 1 185449813 247137334 4391 2.6341 1314 408s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 408s 3 1314 185449813 247137334 1314 0.2295 408s Total CN segment #3 ([1.8545e+08,2.47137e+08]) of 3...done 408s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 408s 1 1 1 1 554484 143926517 7599 1.3859 2120 408s 2 1 2 1 143926517 185449813 2668 2.0704 775 408s 3 1 3 1 185449813 247137334 4391 2.6341 1314 408s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 408s 1 2120 554484 143926517 2120 0.5101 408s 2 775 143926517 185449813 775 0.0970 408s 3 1314 185449813 247137334 1314 0.2295 408s Calculating (C1,C2) per segment... 408s Calculating (C1,C2) per segment...done 408s Number of segments: 3 408s Segmenting paired tumor-normal signals using Paired PSCBS...done 408s Post-segmenting TCNs... 408s Number of segments: 3 408s Number of chromosomes: 1 408s [1] 1 408s Chromosome 1 ('chr01') of 1... 408s Rows: 408s [1] 1 2 3 408s Number of segments: 3 408s TCN segment #1 ('1') of 3... 408s Nothing todo. Only one DH segmentation. Skipping. 408s TCN segment #1 ('1') of 3...done 408s TCN segment #2 ('2') of 3... 408s Nothing todo. Only one DH segmentation. Skipping. 408s TCN segment #2 ('2') of 3...done 408s TCN segment #3 ('3') of 3... 408s Nothing todo. Only one DH segmentation. Skipping. 408s TCN segment #3 ('3') of 3...done 408s Chromosome 1 ('chr01') of 1...done 408s Update (C1,C2) per segment... 408s Update (C1,C2) per segment...done 408s Post-segmenting TCNs...done 408s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 408s 1 1 1 1 554484 143926517 7599 1.3859 2120 408s 2 1 2 1 143926517 185449813 2668 2.0704 775 408s 3 1 3 1 185449813 247137334 4391 2.6341 1314 408s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 408s 1 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 408s 2 775 143926517 185449813 775 0.0970 0.9347856 1.135614 408s 3 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 408s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 408s 1 1 1 1 554484 143926517 7599 1.3859 2120 408s 2 1 2 1 143926517 185449813 2668 2.0704 775 408s 3 1 3 1 185449813 247137334 4391 2.6341 1314 408s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 408s 1 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 408s 2 775 143926517 185449813 775 0.0970 0.9347856 1.135614 408s 3 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 408s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 408s 1 1 1 1 554484 143926517 7599 1.3859 2120 408s 2 1 2 1 143926517 185449813 2668 2.0704 775 408s 3 1 3 1 185449813 247137334 4391 2.6341 1314 408s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 408s 1 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 408s 2 775 143926517 185449813 775 0.0970 0.9347856 1.135614 408s 3 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 408s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 408s 1 1 1 1 554484 143926517 7599 1.3859 2120 408s 2 1 2 1 143926517 185449813 2668 2.0704 775 408s 3 1 3 1 185449813 247137334 4391 2.6341 1314 408s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 408s 1 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 408s 2 775 143926517 185449813 775 0.0970 0.9347856 1.135614 408s 3 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 408s Chromosome #1 ('Chr01') of 3...done 408s Chromosome #2 ('Chr02') of 3... 408s 'data.frame': 14658 obs. of 8 variables: 408s $ chromosome: int 2 2 2 2 2 2 2 2 2 2 ... 408s $ x : num 554484 730720 782343 878522 916294 ... 408s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 408s $ betaT : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 408s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 408s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 408s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 408s $ index : int 14659 14660 14661 14662 14663 14664 14665 14666 14667 14668 ... 408s Known segments: 408s [1] chromosome start end 408s <0 rows> (or 0-length row.names) 408s Segmenting paired tumor-normal signals using Paired PSCBS... 408s Setup up data... 408s 'data.frame': 14658 obs. of 7 variables: 408s $ chromosome: int 2 2 2 2 2 2 2 2 2 2 ... 408s $ x : num 554484 730720 782343 878522 916294 ... 408s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 408s $ betaT : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 408s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 408s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 408s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 408s Setup up data...done 408s Ordering data along genome... 408s 'data.frame': 14658 obs. of 7 variables: 408s $ chromosome: int 2 2 2 2 2 2 2 2 2 2 ... 408s $ x : num 554484 730720 782343 878522 916294 ... 408s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 408s $ betaT : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 408s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 408s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 408s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 408s Ordering data along genome...done 408s Keeping only current chromosome for 'knownSegments'... 408s Chromosome: 2 408s Known segments for this chromosome: 408s [1] chromosome start end 408s <0 rows> (or 0-length row.names) 408s Keeping only current chromosome for 'knownSegments'...done 408s alphaTCN: 0.009 408s alphaDH: 0.001 408s Number of loci: 14658 408s Calculating DHs... 408s Number of SNPs: 14658 408s Number of heterozygous SNPs: 4209 (28.71%) 408s Normalized DHs: 408s num [1:14658] NA NA NA NA NA ... 408s Calculating DHs...done 408s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 408s Produced 2 seeds from this stream for future usage 408s Identification of change points by total copy numbers... 408s Segmenting by CBS... 408s Chromosome: 2 408s Random seed temporarily set (seed=c(10407, -821273412, -52578226, 1415511586, 721384351, -665928286, 1316562960), kind="L'Ecuyer-CMRG") 408s Segmenting by CBS...done 408s List of 4 408s $ data :'data.frame': 14658 obs. of 4 variables: 408s ..$ chromosome: int [1:14658] 2 2 2 2 2 2 2 2 2 2 ... 408s ..$ x : num [1:14658] 554484 730720 782343 878522 916294 ... 408s ..$ y : num [1:14658] 1.88 1.8 1.59 1.64 1.53 ... 408s ..$ index : int [1:14658] 1 2 3 4 5 6 7 8 9 10 ... 408s $ output :'data.frame': 3 obs. of 6 variables: 408s ..$ sampleName: chr [1:3] NA NA NA 408s ..$ chromosome: int [1:3] 2 2 2 408s ..$ start : num [1:3] 5.54e+05 1.44e+08 1.85e+08 408s ..$ end : num [1:3] 1.44e+08 1.85e+08 2.47e+08 408s ..$ nbrOfLoci : int [1:3] 7599 2668 4391 408s ..$ mean : num [1:3] 1.39 2.07 2.63 408s $ segRows:'data.frame': 3 obs. of 2 variables: 408s ..$ startRow: int [1:3] 1 7600 10268 408s ..$ endRow : int [1:3] 7599 10267 14658 408s $ params :List of 5 408s ..$ alpha : num 0.009 408s ..$ undo : num 0 408s ..$ joinSegments : logi TRUE 408s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 408s .. ..$ chromosome: int 2 408s .. ..$ start : num -Inf 408s .. ..$ end : num Inf 408s ..$ seed : int [1:7] 10407 -821273412 -52578226 1415511586 721384351 -665928286 1316562960 408s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 408s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.401 0 0.401 0 0 408s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 408s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 408s - attr(*, "randomSeed")= int [1:7] 10407 -821273412 -52578226 1415511586 721384351 -665928286 1316562960 408s Identification of change points by total copy numbers...done 408s Restructure TCN segmentation results... 408s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean 408s 1 2 554484 143926517 7599 1.3859 408s 2 2 143926517 185449813 2668 2.0704 408s 3 2 185449813 247137334 4391 2.6341 408s Number of TCN segments: 3 408s Restructure TCN segmentation results...done 408s Total CN segment #1 ([ 554484,1.43927e+08]) of 3... 408s Number of TCN loci in segment: 7599 408s Locus data for TCN segment: 408s 'data.frame': 7599 obs. of 9 variables: 408s $ chromosome: int 2 2 2 2 2 2 2 2 2 2 ... 408s $ x : num 554484 730720 782343 878522 916294 ... 408s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 408s $ betaT : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 408s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 408s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 408s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 408s $ index : int 1 2 3 4 5 6 7 8 9 10 ... 408s $ rho : num NA NA NA NA NA ... 408s Number of loci: 7599 408s Number of SNPs: 2120 (27.90%) 408s Number of heterozygous SNPs: 2120 (100.00%) 408s Chromosome: 2 408s Segmenting DH signals... 408s Segmenting by CBS... 408s Chromosome: 2 408s Random seed temporarily set (seed=c(10407, -1924040949, -1632234809, -437763632, -1464377300, 676654412, 2080370711), kind="L'Ecuyer-CMRG") 408s Segmenting by CBS...done 408s List of 4 408s $ data :'data.frame': 7599 obs. of 4 variables: 408s ..$ chromosome: int [1:7599] 2 2 2 2 2 2 2 2 2 2 ... 408s ..$ x : num [1:7599] 554484 730720 782343 878522 916294 ... 408s ..$ y : num [1:7599] NA NA NA NA NA ... 408s ..$ index : int [1:7599] 1 2 3 4 5 6 7 8 9 10 ... 408s $ output :'data.frame': 1 obs. of 6 variables: 408s ..$ sampleName: chr NA 408s ..$ chromosome: int 2 408s ..$ start : num 554484 408s ..$ end : num 1.44e+08 408s ..$ nbrOfLoci : int 2120 408s ..$ mean : num 0.51 408s $ segRows:'data.frame': 1 obs. of 2 variables: 408s ..$ startRow: int 10 408s ..$ endRow : int 7594 408s $ params :List of 5 408s ..$ alpha : num 0.001 408s ..$ undo : num 0 408s ..$ joinSegments : logi TRUE 408s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 408s .. ..$ chromosome: int 2 408s .. ..$ start : num 554484 408s .. ..$ end : num 1.44e+08 408s ..$ seed : int [1:7] 10407 -1924040949 -1632234809 -437763632 -1464377300 676654412 2080370711 408s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 408s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.026 0 0.026 0 0 408s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 408s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 408s - attr(*, "randomSeed")= int [1:7] 10407 -1924040949 -1632234809 -437763632 -1464377300 676654412 2080370711 408s DH segmentation (locally-indexed) rows: 408s startRow endRow 408s 1 10 7594 408s int [1:7599] 1 2 3 4 5 6 7 8 9 10 ... 408s DH segmentation rows: 408s startRow endRow 408s 1 10 7594 408s Segmenting DH signals...done 408s DH segmentation table: 408s dhStart dhEnd dhNbrOfLoci dhMean 408s 1 554484 143926517 2120 0.5101 408s startRow endRow 408s 1 10 7594 408s Rows: 408s [1] 1 408s TCN segmentation rows: 408s startRow endRow 408s 1 1 7599 408s TCN and DH segmentation rows: 408s startRow endRow 408s 1 1 7599 408s startRow endRow 408s 1 10 7594 408s NULL 408s TCN segmentation (expanded) rows: 408s startRow endRow 408s 1 1 7599 408s TCN and DH segmentation rows: 408s startRow endRow 408s 1 1 7599 408s 2 7600 10267 408s 3 10268 14658 408s startRow endRow 408s 1 10 7594 408s startRow endRow 408s 1 1 7599 408s Total CN segmentation table (expanded): 408s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 408s 1 2 554484 143926517 7599 1.3859 2120 2120 408s (TCN,DH) segmentation for one total CN segment: 408s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 408s 1 1 1 2 554484 143926517 7599 1.3859 2120 408s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 408s 1 2120 554484 143926517 2120 0.5101 408s Total CN segment #1 ([ 554484,1.43927e+08]) of 3...done 408s Total CN segment #2 ([1.43927e+08,1.8545e+08]) of 3... 408s Number of TCN loci in segment: 2668 408s Locus data for TCN segment: 408s 'data.frame': 2668 obs. of 9 variables: 408s $ chromosome: int 2 2 2 2 2 2 2 2 2 2 ... 408s $ x : num 1.44e+08 1.44e+08 1.44e+08 1.44e+08 1.44e+08 ... 408s $ CT : num 2.1 2.1 2.09 1.8 2.34 ... 408s $ betaT : num 0.027542 1.030222 1.094093 0.046763 -0.000948 ... 408s $ betaTN : num 0.027542 1.030222 1.094093 0.046763 -0.000948 ... 408s $ betaN : num 0.1624 0.8788 0.8225 0.1201 0.0317 ... 408s $ muN : num 0 1 1 0 0 1 0 0 0 0 ... 408s $ index : int 7600 7601 7602 7603 7604 7605 7606 7607 7608 7609 ... 408s $ rho : num NA NA NA NA NA NA NA NA NA NA ... 408s Number of loci: 2668 408s Number of SNPs: 775 (29.05%) 408s Number of heterozygous SNPs: 775 (100.00%) 408s Chromosome: 2 408s Segmenting DH signals... 408s Segmenting by CBS... 408s Chromosome: 2 408s Random seed temporarily set (seed=c(10407, -1924040949, -1632234809, -437763632, -1464377300, 676654412, 2080370711), kind="L'Ecuyer-CMRG") 408s Segmenting by CBS...done 408s List of 4 408s $ data :'data.frame': 2668 obs. of 4 variables: 408s ..$ chromosome: int [1:2668] 2 2 2 2 2 2 2 2 2 2 ... 408s ..$ x : num [1:2668] 1.44e+08 1.44e+08 1.44e+08 1.44e+08 1.44e+08 ... 408s ..$ y : num [1:2668] NA NA NA NA NA NA NA NA NA NA ... 408s ..$ index : int [1:2668] 1 2 3 4 5 6 7 8 9 10 ... 408s $ output :'data.frame': 1 obs. of 6 variables: 408s ..$ sampleName: chr NA 408s ..$ chromosome: int 2 408s ..$ start : num 1.44e+08 408s ..$ end : num 1.85e+08 408s ..$ nbrOfLoci : int 775 408s ..$ mean : num 0.097 408s $ segRows:'data.frame': 1 obs. of 2 variables: 408s ..$ startRow: int 15 408s ..$ endRow : int 2664 408s $ params :List of 5 408s ..$ alpha : num 0.001 408s ..$ undo : num 0 408s ..$ joinSegments : logi TRUE 408s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 408s .. ..$ chromosome: int 2 408s .. ..$ start : num 1.44e+08 408s .. ..$ end : num 1.85e+08 408s ..$ seed : int [1:7] 10407 -1924040949 -1632234809 -437763632 -1464377300 676654412 2080370711 408s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 408s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.008 0 0.008 0 0 408s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 408s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 408s - attr(*, "randomSeed")= int [1:7] 10407 -1924040949 -1632234809 -437763632 -1464377300 676654412 2080370711 408s DH segmentation (locally-indexed) rows: 408s startRow endRow 408s 1 15 2664 408s int [1:2668] 7600 7601 7602 7603 7604 7605 7606 7607 7608 7609 ... 408s DH segmentation rows: 408s startRow endRow 408s 1 7614 10263 408s Segmenting DH signals...done 408s DH segmentation table: 408s dhStart dhEnd dhNbrOfLoci dhMean 408s 1 143926517 185449813 775 0.097 408s startRow endRow 408s 1 7614 10263 408s Rows: 408s [1] 2 408s TCN segmentation rows: 408s startRow endRow 408s 2 7600 10267 408s TCN and DH segmentation rows: 408s startRow endRow 408s 2 7600 10267 408s startRow endRow 408s 1 7614 10263 408s startRow endRow 408s 1 1 7599 408s TCN segmentation (expanded) rows: 408s startRow endRow 408s 1 1 7599 408s 2 7600 10267 408s TCN and DH segmentation rows: 408s startRow endRow 408s 1 1 7599 408s 2 7600 10267 408s 3 10268 14658 408s startRow endRow 408s 1 10 7594 408s 2 7614 10263 408s startRow endRow 408s 1 1 7599 408s 2 7600 10267 408s Total CN segmentation table (expanded): 408s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 408s 2 2 143926517 185449813 2668 2.0704 775 775 408s (TCN,DH) segmentation for one total CN segment: 408s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 408s 2 2 1 2 143926517 185449813 2668 2.0704 775 408s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 408s 2 775 143926517 185449813 775 0.097 408s Total CN segment #2 ([1.43927e+08,1.8545e+08]) of 3...done 408s Total CN segment #3 ([1.8545e+08,2.47137e+08]) of 3... 408s Number of TCN loci in segment: 4391 408s Locus data for TCN segment: 408s 'data.frame': 4391 obs. of 9 variables: 408s $ chromosome: int 2 2 2 2 2 2 2 2 2 2 ... 408s $ x : num 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 408s $ CT : num 2.93 2.15 2.82 2.93 2.46 ... 408s $ betaT : num -0.169 0.609 1.028 0.525 0.968 ... 408s $ betaTN : num -0.169 0.609 1.028 0.525 0.968 ... 408s $ betaN : num 0.25 0.38 0.919 0.34 0.783 ... 408s $ muN : num 0 0.5 1 0.5 1 1 0 1 0 1 ... 408s $ index : int 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 408s $ rho : num NA 0.2186 NA 0.0503 NA ... 408s Number of loci: 4391 408s Number of SNPs: 1314 (29.92%) 408s Number of heterozygous SNPs: 1314 (100.00%) 408s Chromosome: 2 408s Segmenting DH signals... 408s Segmenting by CBS... 408s Chromosome: 2 408s Random seed temporarily set (seed=c(10407, -1924040949, -1632234809, -437763632, -1464377300, 676654412, 2080370711), kind="L'Ecuyer-CMRG") 408s Segmenting by CBS...done 408s List of 4 408s $ data :'data.frame': 4391 obs. of 4 variables: 408s ..$ chromosome: int [1:4391] 2 2 2 2 2 2 2 2 2 2 ... 408s ..$ x : num [1:4391] 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 408s ..$ y : num [1:4391] NA 0.2186 NA 0.0503 NA ... 408s ..$ index : int [1:4391] 1 2 3 4 5 6 7 8 9 10 ... 408s $ output :'data.frame': 1 obs. of 6 variables: 408s ..$ sampleName: chr NA 408s ..$ chromosome: int 2 408s ..$ start : num 1.85e+08 408s ..$ end : num 2.47e+08 408s ..$ nbrOfLoci : int 1314 408s ..$ mean : num 0.23 408s $ segRows:'data.frame': 1 obs. of 2 variables: 408s ..$ startRow: int 2 408s ..$ endRow : int 4388 408s $ params :List of 5 408s ..$ alpha : num 0.001 408s ..$ undo : num 0 408s ..$ joinSegments : logi TRUE 408s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 408s .. ..$ chromosome: int 2 408s .. ..$ start : num 1.85e+08 408s .. ..$ end : num 2.47e+08 408s ..$ seed : int [1:7] 10407 -1924040949 -1632234809 -437763632 -1464377300 676654412 2080370711 408s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 408s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.014 0 0.015 0 0 408s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 408s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 408s - attr(*, "randomSeed")= int [1:7] 10407 -1924040949 -1632234809 -437763632 -1464377300 676654412 2080370711 408s DH segmentation (locally-indexed) rows: 408s startRow endRow 408s 1 2 4388 408s int [1:4391] 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 408s DH segmentation rows: 408s startRow endRow 408s 1 10269 14655 408s Segmenting DH signals...done 408s DH segmentation table: 408s dhStart dhEnd dhNbrOfLoci dhMean 408s 1 185449813 247137334 1314 0.2295 408s startRow endRow 408s 1 10269 14655 408s Rows: 408s [1] 3 408s TCN segmentation rows: 408s startRow endRow 408s 3 10268 14658 408s TCN and DH segmentation rows: 408s startRow endRow 408s 3 10268 14658 408s startRow endRow 408s 1 10269 14655 408s startRow endRow 408s 1 1 7599 408s 2 7600 10267 408s TCN segmentation (expanded) rows: 408s startRow endRow 408s 1 1 7599 408s 2 7600 10267 408s 3 10268 14658 408s TCN and DH segmentation rows: 408s startRow endRow 408s 1 1 7599 408s 2 7600 10267 408s 3 10268 14658 408s startRow endRow 408s 1 10 7594 408s 2 7614 10263 408s 3 10269 14655 408s startRow endRow 408s 1 1 7599 408s 2 7600 10267 408s 3 10268 14658 408s Total CN segmentation table (expanded): 408s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 408s 3 2 185449813 247137334 4391 2.6341 1314 1314 408s (TCN,DH) segmentation for one total CN segment: 408s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 408s 3 3 1 2 185449813 247137334 4391 2.6341 1314 408s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 408s 3 1314 185449813 247137334 1314 0.2295 408s Total CN segment #3 ([1.8545e+08,2.47137e+08]) of 3...done 408s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 408s 1 2 1 1 554484 143926517 7599 1.3859 2120 408s 2 2 2 1 143926517 185449813 2668 2.0704 775 408s 3 2 3 1 185449813 247137334 4391 2.6341 1314 408s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 408s 1 2120 554484 143926517 2120 0.5101 408s 2 775 143926517 185449813 775 0.0970 408s 3 1314 185449813 247137334 1314 0.2295 408s Calculating (C1,C2) per segment... 408s Calculating (C1,C2) per segment...done 408s Number of segments: 3 408s Segmenting paired tumor-normal signals using Paired PSCBS...done 408s Post-segmenting TCNs... 408s Number of segments: 3 408s Number of chromosomes: 1 408s [1] 2 408s Chromosome 1 ('chr02') of 1... 408s Rows: 408s [1] 1 2 3 408s Number of segments: 3 408s TCN segment #1 ('1') of 3... 408s Nothing todo. Only one DH segmentation. Skipping. 408s TCN segment #1 ('1') of 3...done 408s TCN segment #2 ('2') of 3... 408s Nothing todo. Only one DH segmentation. Skipping. 408s TCN segment #2 ('2') of 3...done 408s TCN segment #3 ('3') of 3... 408s Nothing todo. Only one DH segmentation. Skipping. 408s TCN segment #3 ('3') of 3...done 408s Chromosome 1 ('chr02') of 1...done 408s Update (C1,C2) per segment... 408s Update (C1,C2) per segment...done 408s Post-segmenting TCNs...done 408s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 408s 1 2 1 1 554484 143926517 7599 1.3859 2120 408s 2 2 2 1 143926517 185449813 2668 2.0704 775 408s 3 2 3 1 185449813 247137334 4391 2.6341 1314 408s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 408s 1 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 408s 2 775 143926517 185449813 775 0.0970 0.9347856 1.135614 408s 3 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 408s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 408s 1 2 1 1 554484 143926517 7599 1.3859 2120 408s 2 2 2 1 143926517 185449813 2668 2.0704 775 408s 3 2 3 1 185449813 247137334 4391 2.6341 1314 408s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 408s 1 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 408s 2 775 143926517 185449813 775 0.0970 0.9347856 1.135614 408s 3 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 408s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 408s 1 2 1 1 554484 143926517 7599 1.3859 2120 408s 2 2 2 1 143926517 185449813 2668 2.0704 775 408s 3 2 3 1 185449813 247137334 4391 2.6341 1314 408s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 408s 1 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 408s 2 775 143926517 185449813 775 0.0970 0.9347856 1.135614 408s 3 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 408s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 408s 1 2 1 1 554484 143926517 7599 1.3859 2120 408s 2 2 2 1 143926517 185449813 2668 2.0704 775 408s 3 2 3 1 185449813 247137334 4391 2.6341 1314 408s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 408s 1 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 408s 2 775 143926517 185449813 775 0.0970 0.9347856 1.135614 408s 3 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 408s Chromosome #2 ('Chr02') of 3...done 408s Chromosome #3 ('Chr03') of 3... 408s 'data.frame': 14658 obs. of 8 variables: 408s $ chromosome: int 3 3 3 3 3 3 3 3 3 3 ... 408s $ x : num 554484 730720 782343 878522 916294 ... 408s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 408s $ betaT : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 408s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 408s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 408s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 408s $ index : int 29317 29318 29319 29320 29321 29322 29323 29324 29325 29326 ... 408s Known segments: 408s [1] chromosome start end 408s <0 rows> (or 0-length row.names) 408s Segmenting paired tumor-normal signals using Paired PSCBS... 408s Setup up data... 408s 'data.frame': 14658 obs. of 7 variables: 408s $ chromosome: int 3 3 3 3 3 3 3 3 3 3 ... 408s $ x : num 554484 730720 782343 878522 916294 ... 408s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 408s $ betaT : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 408s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 408s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 408s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 408s Setup up data...done 408s Ordering data along genome... 408s 'data.frame': 14658 obs. of 7 variables: 408s $ chromosome: int 3 3 3 3 3 3 3 3 3 3 ... 408s $ x : num 554484 730720 782343 878522 916294 ... 408s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 408s $ betaT : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 408s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 408s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 408s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 408s Ordering data along genome...done 408s Keeping only current chromosome for 'knownSegments'... 408s Chromosome: 3 408s Known segments for this chromosome: 408s [1] chromosome start end 408s <0 rows> (or 0-length row.names) 408s Keeping only current chromosome for 'knownSegments'...done 408s alphaTCN: 0.009 408s alphaDH: 0.001 408s Number of loci: 14658 408s Calculating DHs... 408s Number of SNPs: 14658 408s Number of heterozygous SNPs: 4209 (28.71%) 408s Normalized DHs: 408s num [1:14658] NA NA NA NA NA ... 408s Calculating DHs...done 408s Random seed temporarily set (seed=c(10407, -821273412, -52578226, 1415511586, 721384351, -665928286, 1316562960), kind="L'Ecuyer-CMRG") 408s Produced 2 seeds from this stream for future usage 408s Identification of change points by total copy numbers... 408s Segmenting by CBS... 408s Chromosome: 3 408s Random seed temporarily set (seed=c(10407, -1924040949, -1632234809, -437763632, -1464377300, 676654412, 2080370711), kind="L'Ecuyer-CMRG") 408s Segmenting by CBS...done 408s List of 4 408s $ data :'data.frame': 14658 obs. of 4 variables: 408s ..$ chromosome: int [1:14658] 3 3 3 3 3 3 3 3 3 3 ... 408s ..$ x : num [1:14658] 554484 730720 782343 878522 916294 ... 408s ..$ y : num [1:14658] 1.88 1.8 1.59 1.64 1.53 ... 408s ..$ index : int [1:14658] 1 2 3 4 5 6 7 8 9 10 ... 408s $ output :'data.frame': 3 obs. of 6 variables: 408s ..$ sampleName: chr [1:3] NA NA NA 408s ..$ chromosome: int [1:3] 3 3 3 408s ..$ start : num [1:3] 5.54e+05 1.44e+08 1.85e+08 408s ..$ end : num [1:3] 1.44e+08 1.85e+08 2.47e+08 408s ..$ nbrOfLoci : int [1:3] 7599 2668 4391 408s ..$ mean : num [1:3] 1.39 2.07 2.63 408s $ segRows:'data.frame': 3 obs. of 2 variables: 408s ..$ startRow: int [1:3] 1 7600 10268 408s ..$ endRow : int [1:3] 7599 10267 14658 408s $ params :List of 5 408s ..$ alpha : num 0.009 408s ..$ undo : num 0 408s ..$ joinSegments : logi TRUE 408s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 408s .. ..$ chromosome: int 3 408s .. ..$ start : num -Inf 408s .. ..$ end : num Inf 408s ..$ seed : int [1:7] 10407 -1924040949 -1632234809 -437763632 -1464377300 676654412 2080370711 408s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 408s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.379 0.001 0.38 0 0 408s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 408s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 408s - attr(*, "randomSeed")= int [1:7] 10407 -1924040949 -1632234809 -437763632 -1464377300 676654412 2080370711 408s Identification of change points by total copy numbers...done 408s Restructure TCN segmentation results... 408s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean 408s 1 3 554484 143926517 7599 1.3859 408s 2 3 143926517 185449813 2668 2.0704 408s 3 3 185449813 247137334 4391 2.6341 408s Number of TCN segments: 3 408s Restructure TCN segmentation results...done 408s Total CN segment #1 ([ 554484,1.43927e+08]) of 3... 408s Number of TCN loci in segment: 7599 408s Locus data for TCN segment: 408s 'data.frame': 7599 obs. of 9 variables: 408s $ chromosome: int 3 3 3 3 3 3 3 3 3 3 ... 408s $ x : num 554484 730720 782343 878522 916294 ... 408s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 408s $ betaT : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 408s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 408s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 408s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 408s $ index : int 1 2 3 4 5 6 7 8 9 10 ... 408s $ rho : num NA NA NA NA NA ... 408s Number of loci: 7599 408s Number of SNPs: 2120 (27.90%) 408s Number of heterozygous SNPs: 2120 (100.00%) 408s Chromosome: 3 408s Segmenting DH signals... 408s Segmenting by CBS... 408s Chromosome: 3 408s Random seed temporarily set (seed=c(10407, -1371615447, -889757879, 1692656974, -1723952224, 1378814990, 1816467252), kind="L'Ecuyer-CMRG") 408s Segmenting by CBS...done 408s List of 4 408s $ data :'data.frame': 7599 obs. of 4 variables: 408s ..$ chromosome: int [1:7599] 3 3 3 3 3 3 3 3 3 3 ... 408s ..$ x : num [1:7599] 554484 730720 782343 878522 916294 ... 408s ..$ y : num [1:7599] NA NA NA NA NA ... 408s ..$ index : int [1:7599] 1 2 3 4 5 6 7 8 9 10 ... 408s $ output :'data.frame': 1 obs. of 6 variables: 408s ..$ sampleName: chr NA 408s ..$ chromosome: int 3 408s ..$ start : num 554484 408s ..$ end : num 1.44e+08 408s ..$ nbrOfLoci : int 2120 408s ..$ mean : num 0.51 408s $ segRows:'data.frame': 1 obs. of 2 variables: 408s ..$ startRow: int 10 408s ..$ endRow : int 7594 408s $ params :List of 5 408s ..$ alpha : num 0.001 408s ..$ undo : num 0 408s ..$ joinSegments : logi TRUE 408s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 408s .. ..$ chromosome: int 3 408s .. ..$ start : num 554484 408s .. ..$ end : num 1.44e+08 408s ..$ seed : int [1:7] 10407 -1371615447 -889757879 1692656974 -1723952224 1378814990 1816467252 408s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 408s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.025 0 0.026 0 0 408s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 408s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 408s - attr(*, "randomSeed")= int [1:7] 10407 -1371615447 -889757879 1692656974 -1723952224 1378814990 1816467252 408s DH segmentation (locally-indexed) rows: 408s startRow endRow 408s 1 10 7594 408s int [1:7599] 1 2 3 4 5 6 7 8 9 10 ... 408s DH segmentation rows: 408s startRow endRow 408s 1 10 7594 408s Segmenting DH signals...done 408s DH segmentation table: 408s dhStart dhEnd dhNbrOfLoci dhMean 408s 1 554484 143926517 2120 0.5101 408s startRow endRow 408s 1 10 7594 408s Rows: 408s [1] 1 408s TCN segmentation rows: 408s startRow endRow 408s 1 1 7599 408s TCN and DH segmentation rows: 408s startRow endRow 408s 1 1 7599 408s startRow endRow 408s 1 10 7594 408s NULL 408s TCN segmentation (expanded) rows: 408s startRow endRow 408s 1 1 7599 408s TCN and DH segmentation rows: 408s startRow endRow 408s 1 1 7599 408s 2 7600 10267 408s 3 10268 14658 408s startRow endRow 408s 1 10 7594 408s startRow endRow 408s 1 1 7599 408s Total CN segmentation table (expanded): 408s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 408s 1 3 554484 143926517 7599 1.3859 2120 2120 408s (TCN,DH) segmentation for one total CN segment: 408s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 408s 1 1 1 3 554484 143926517 7599 1.3859 2120 408s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 408s 1 2120 554484 143926517 2120 0.5101 408s Total CN segment #1 ([ 554484,1.43927e+08]) of 3...done 408s Total CN segment #2 ([1.43927e+08,1.8545e+08]) of 3... 408s Number of TCN loci in segment: 2668 408s Locus data for TCN segment: 408s 'data.frame': 2668 obs. of 9 variables: 408s $ chromosome: int 3 3 3 3 3 3 3 3 3 3 ... 408s $ x : num 1.44e+08 1.44e+08 1.44e+08 1.44e+08 1.44e+08 ... 408s $ CT : num 2.1 2.1 2.09 1.8 2.34 ... 408s $ betaT : num 0.027542 1.030222 1.094093 0.046763 -0.000948 ... 408s $ betaTN : num 0.027542 1.030222 1.094093 0.046763 -0.000948 ... 408s $ betaN : num 0.1624 0.8788 0.8225 0.1201 0.0317 ... 408s $ muN : num 0 1 1 0 0 1 0 0 0 0 ... 408s $ index : int 7600 7601 7602 7603 7604 7605 7606 7607 7608 7609 ... 408s $ rho : num NA NA NA NA NA NA NA NA NA NA ... 408s Number of loci: 2668 408s Number of SNPs: 775 (29.05%) 408s Number of heterozygous SNPs: 775 (100.00%) 408s Chromosome: 3 408s Segmenting DH signals... 408s Segmenting by CBS... 408s Chromosome: 3 408s Random seed temporarily set (seed=c(10407, -1371615447, -889757879, 1692656974, -1723952224, 1378814990, 1816467252), kind="L'Ecuyer-CMRG") 408s Segmenting by CBS...done 408s List of 4 408s $ data :'data.frame': 2668 obs. of 4 variables: 408s ..$ chromosome: int [1:2668] 3 3 3 3 3 3 3 3 3 3 ... 408s ..$ x : num [1:2668] 1.44e+08 1.44e+08 1.44e+08 1.44e+08 1.44e+08 ... 408s ..$ y : num [1:2668] NA NA NA NA NA NA NA NA NA NA ... 408s ..$ index : int [1:2668] 1 2 3 4 5 6 7 8 9 10 ... 408s $ output :'data.frame': 1 obs. of 6 variables: 408s ..$ sampleName: chr NA 408s ..$ chromosome: int 3 408s ..$ start : num 1.44e+08 408s ..$ end : num 1.85e+08 408s ..$ nbrOfLoci : int 775 408s ..$ mean : num 0.097 408s $ segRows:'data.frame': 1 obs. of 2 variables: 408s ..$ startRow: int 15 408s ..$ endRow : int 2664 408s $ params :List of 5 408s ..$ alpha : num 0.001 408s ..$ undo : num 0 408s ..$ joinSegments : logi TRUE 408s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 408s .. ..$ chromosome: int 3 408s .. ..$ start : num 1.44e+08 408s .. ..$ end : num 1.85e+08 408s ..$ seed : int [1:7] 10407 -1371615447 -889757879 1692656974 -1723952224 1378814990 1816467252 408s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 408s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.008 0 0.008 0 0 408s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 408s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 408s - attr(*, "randomSeed")= int [1:7] 10407 -1371615447 -889757879 1692656974 -1723952224 1378814990 1816467252 408s DH segmentation (locally-indexed) rows: 408s startRow endRow 408s 1 15 2664 408s int [1:2668] 7600 7601 7602 7603 7604 7605 7606 7607 7608 7609 ... 408s DH segmentation rows: 408s startRow endRow 408s 1 7614 10263 408s Segmenting DH signals...done 408s DH segmentation table: 408s dhStart dhEnd dhNbrOfLoci dhMean 408s 1 143926517 185449813 775 0.097 408s startRow endRow 408s 1 7614 10263 408s Rows: 408s [1] 2 408s TCN segmentation rows: 408s startRow endRow 408s 2 7600 10267 408s TCN and DH segmentation rows: 408s startRow endRow 408s 2 7600 10267 408s startRow endRow 408s 1 7614 10263 408s startRow endRow 408s 1 1 7599 408s TCN segmentation (expanded) rows: 408s startRow endRow 408s 1 1 7599 408s 2 7600 10267 408s TCN and DH segmentation rows: 408s startRow endRow 408s 1 1 7599 408s 2 7600 10267 408s 3 10268 14658 408s startRow endRow 408s 1 10 7594 408s 2 7614 10263 408s startRow endRow 408s 1 1 7599 408s 2 7600 10267 408s Total CN segmentation table (expanded): 408s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 408s 2 3 143926517 185449813 2668 2.0704 775 775 408s (TCN,DH) segmentation for one total CN segment: 408s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 408s 2 2 1 3 143926517 185449813 2668 2.0704 775 408s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 408s 2 775 143926517 185449813 775 0.097 408s Total CN segment #2 ([1.43927e+08,1.8545e+08]) of 3...done 408s Total CN segment #3 ([1.8545e+08,2.47137e+08]) of 3... 408s Number of TCN loci in segment: 4391 408s Locus data for TCN segment: 408s 'data.frame': 4391 obs. of 9 variables: 408s $ chromosome: int 3 3 3 3 3 3 3 3 3 3 ... 408s $ x : num 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 408s $ CT : num 2.93 2.15 2.82 2.93 2.46 ... 408s $ betaT : num -0.169 0.609 1.028 0.525 0.968 ... 408s $ betaTN : num -0.169 0.609 1.028 0.525 0.968 ... 408s $ betaN : num 0.25 0.38 0.919 0.34 0.783 ... 408s $ muN : num 0 0.5 1 0.5 1 1 0 1 0 1 ... 408s $ index : int 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 408s $ rho : num NA 0.2186 NA 0.0503 NA ... 408s Number of loci: 4391 408s Number of SNPs: 1314 (29.92%) 408s Number of heterozygous SNPs: 1314 (100.00%) 408s Chromosome: 3 408s Segmenting DH signals... 408s Segmenting by CBS... 408s Chromosome: 3 408s Random seed temporarily set (seed=c(10407, -1371615447, -889757879, 1692656974, -1723952224, 1378814990, 1816467252), kind="L'Ecuyer-CMRG") 408s Segmenting by CBS...done 408s List of 4 408s $ data :'data.frame': 4391 obs. of 4 variables: 408s ..$ chromosome: int [1:4391] 3 3 3 3 3 3 3 3 3 3 ... 408s ..$ x : num [1:4391] 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 408s ..$ y : num [1:4391] NA 0.2186 NA 0.0503 NA ... 408s ..$ index : int [1:4391] 1 2 3 4 5 6 7 8 9 10 ... 408s $ output :'data.frame': 1 obs. of 6 variables: 408s ..$ sampleName: chr NA 408s ..$ chromosome: int 3 408s ..$ start : num 1.85e+08 408s ..$ end : num 2.47e+08 408s ..$ nbrOfLoci : int 1314 408s ..$ mean : num 0.23 408s $ segRows:'data.frame': 1 obs. of 2 variables: 408s ..$ startRow: int 2 408s ..$ endRow : int 4388 408s $ params :List of 5 408s ..$ alpha : num 0.001 408s ..$ undo : num 0 408s ..$ joinSegments : logi TRUE 408s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 408s .. ..$ chromosome: int 3 408s .. ..$ start : num 1.85e+08 408s .. ..$ end : num 2.47e+08 408s ..$ seed : int [1:7] 10407 -1371615447 -889757879 1692656974 -1723952224 1378814990 1816467252 408s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 408s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.015 0 0.015 0 0 408s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 408s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 408s - attr(*, "randomSeed")= int [1:7] 10407 -1371615447 -889757879 1692656974 -1723952224 1378814990 1816467252 408s DH segmentation (locally-indexed) rows: 408s startRow endRow 408s 1 2 4388 408s int [1:4391] 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 408s DH segmentation rows: 408s startRow endRow 408s 1 10269 14655 408s Segmenting DH signals...done 408s DH segmentation table: 408s dhStart dhEnd dhNbrOfLoci dhMean 408s 1 185449813 247137334 1314 0.2295 408s startRow endRow 408s 1 10269 14655 408s Rows: 408s [1] 3 408s TCN segmentation rows: 408s startRow endRow 408s 3 10268 14658 408s TCN and DH segmentation rows: 408s startRow endRow 408s 3 10268 14658 408s startRow endRow 408s 1 10269 14655 408s startRow endRow 408s 1 1 7599 408s 2 7600 10267 408s TCN segmentation (expanded) rows: 408s startRow endRow 408s 1 1 7599 408s 2 7600 10267 408s 3 10268 14658 408s TCN and DH segmentation rows: 408s startRow endRow 408s 1 1 7599 408s 2 7600 10267 408s 3 10268 14658 408s startRow endRow 408s 1 10 7594 408s 2 7614 10263 408s 3 10269 14655 408s startRow endRow 408s 1 1 7599 408s 2 7600 10267 408s 3 10268 14658 408s Total CN segmentation table (expanded): 408s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 408s 3 3 185449813 247137334 4391 2.6341 1314 1314 408s (TCN,DH) segmentation for one total CN segment: 408s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 408s 3 3 1 3 185449813 247137334 4391 2.6341 1314 408s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 408s 3 1314 185449813 247137334 1314 0.2295 408s Total CN segment #3 ([1.8545e+08,2.47137e+08]) of 3...done 408s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 408s 1 3 1 1 554484 143926517 7599 1.3859 2120 408s 2 3 2 1 143926517 185449813 2668 2.0704 775 408s 3 3 3 1 185449813 247137334 4391 2.6341 1314 408s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 408s 1 2120 554484 143926517 2120 0.5101 408s 2 775 143926517 185449813 775 0.0970 408s 3 1314 185449813 247137334 1314 0.2295 408s Calculating (C1,C2) per segment... 408s Calculating (C1,C2) per segment...done 408s Number of segments: 3 408s Segmenting paired tumor-normal signals using Paired PSCBS...done 408s Post-segmenting TCNs... 408s Number of segments: 3 408s Number of chromosomes: 1 408s [1] 3 408s Chromosome 1 ('chr03') of 1... 408s Rows: 408s [1] 1 2 3 408s Number of segments: 3 408s TCN segment #1 ('1') of 3... 408s Nothing todo. Only one DH segmentation. Skipping. 408s TCN segment #1 ('1') of 3...done 408s TCN segment #2 ('2') of 3... 408s Nothing todo. Only one DH segmentation. Skipping. 408s TCN segment #2 ('2') of 3...done 408s TCN segment #3 ('3') of 3... 408s Nothing todo. Only one DH segmentation. Skipping. 408s TCN segment #3 ('3') of 3...done 408s Chromosome 1 ('chr03') of 1...done 408s Update (C1,C2) per segment... 408s Update (C1,C2) per segment...done 408s Post-segmenting TCNs...done 408s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 408s 1 3 1 1 554484 143926517 7599 1.3859 2120 408s 2 3 2 1 143926517 185449813 2668 2.0704 775 408s 3 3 3 1 185449813 247137334 4391 2.6341 1314 408s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 408s 1 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 408s 2 775 143926517 185449813 775 0.0970 0.9347856 1.135614 408s 3 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 408s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 408s 1 3 1 1 554484 143926517 7599 1.3859 2120 408s 2 3 2 1 143926517 185449813 2668 2.0704 775 408s 3 3 3 1 185449813 247137334 4391 2.6341 1314 408s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 408s 1 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 408s 2 775 143926517 185449813 775 0.0970 0.9347856 1.135614 408s 3 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 408s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 408s 1 3 1 1 554484 143926517 7599 1.3859 2120 408s 2 3 2 1 143926517 185449813 2668 2.0704 775 408s 3 3 3 1 185449813 247137334 4391 2.6341 1314 408s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 408s 1 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 408s 2 775 143926517 185449813 775 0.0970 0.9347856 1.135614 408s 3 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 408s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 408s 1 3 1 1 554484 143926517 7599 1.3859 2120 408s 2 3 2 1 143926517 185449813 2668 2.0704 775 408s 3 3 3 1 185449813 247137334 4391 2.6341 1314 408s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 408s 1 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 408s 2 775 143926517 185449813 775 0.0970 0.9347856 1.135614 408s 3 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 408s Chromosome #3 ('Chr03') of 3...done 408s Merging (independently) segmented chromosome... 408s List of 5 408s $ data :Classes 'PairedPSCNData' and 'data.frame': 43974 obs. of 8 variables: 408s ..$ chromosome: int [1:43974] 1 1 1 1 1 1 1 1 1 1 ... 408s ..$ x : num [1:43974] 554484 730720 782343 878522 916294 ... 408s ..$ CT : num [1:43974] 1.88 1.8 1.59 1.64 1.53 ... 408s ..$ betaT : num [1:43974] 0.0646 0.1672 0.9284 0.113 0.7209 ... 408s ..$ betaTN : num [1:43974] -0.0515 -0.1172 1.0194 0.031 0.8604 ... 408s ..$ betaN : num [1:43974] 0.116 0.284 0.909 0.082 0.86 ... 408s ..$ muN : num [1:43974] 0 0 1 0 1 1 1 0 1 0.5 ... 408s ..$ rho : num [1:43974] NA NA NA NA NA ... 408s $ output :Classes 'PairedPSCNSegments' and 'data.frame': 11 obs. of 15 variables: 408s ..$ chromosome : int [1:11] 1 1 1 NA 2 2 2 NA 3 3 ... 408s ..$ tcnId : int [1:11] 1 2 3 NA 1 2 3 NA 1 2 ... 408s ..$ dhId : int [1:11] 1 1 1 NA 1 1 1 NA 1 1 ... 408s ..$ tcnStart : num [1:11] 5.54e+05 1.44e+08 1.85e+08 NA 5.54e+05 ... 408s ..$ tcnEnd : num [1:11] 1.44e+08 1.85e+08 2.47e+08 NA 1.44e+08 ... 408s ..$ tcnNbrOfLoci: int [1:11] 7599 2668 4391 NA 7599 2668 4391 NA 7599 2668 ... 408s ..$ tcnMean : num [1:11] 1.39 2.07 2.63 NA 1.39 ... 408s ..$ tcnNbrOfSNPs: int [1:11] 2120 775 1314 NA 2120 775 1314 NA 2120 775 ... 408s ..$ tcnNbrOfHets: int [1:11] 2120 775 1314 NA 2120 775 1314 NA 2120 775 ... 408s ..$ dhStart : num [1:11] 5.54e+05 1.44e+08 1.85e+08 NA 5.54e+05 ... 408s ..$ dhEnd : num [1:11] 1.44e+08 1.85e+08 2.47e+08 NA 1.44e+08 ... 408s ..$ dhNbrOfLoci : int [1:11] 2120 775 1314 NA 2120 775 1314 NA 2120 775 ... 408s ..$ dhMean : num [1:11] 0.51 0.097 0.23 NA 0.51 ... 408s ..$ c1Mean : num [1:11] 0.339 0.935 1.015 NA 0.339 ... 408s ..$ c2Mean : num [1:11] 1.05 1.14 1.62 NA 1.05 ... 408s $ tcnSegRows:'data.frame': 11 obs. of 2 variables: 408s ..$ startRow: int [1:11] 1 7600 10268 NA 14659 22258 24926 NA 29317 36916 ... 408s ..$ endRow : int [1:11] 7599 10267 14658 NA 22257 24925 29316 NA 36915 39583 ... 408s $ dhSegRows :'data.frame': 11 obs. of 2 variables: 408s ..$ startRow: int [1:11] 10 7614 10269 NA 14668 22272 24927 NA 29326 36930 ... 408s ..$ endRow : int [1:11] 7594 10263 14655 NA 22252 24921 29313 NA 36910 39579 ... 408s $ params :List of 7 408s ..$ alphaTCN : num 0.009 408s ..$ alphaDH : num 0.001 408s ..$ flavor : chr "tcn&dh" 408s ..$ tbn : logi FALSE 408s ..$ joinSegments : logi TRUE 408s ..$ knownSegments:'data.frame': 0 obs. of 3 variables: 408s .. ..$ chromosome: int(0) 408s .. ..$ start : int(0) 408s .. ..$ end : int(0) 408s ..$ seed : int [1:7] 10407 1066287653 -51199871 161854402 -1995183193 1503453565 -747102133 408s - attr(*, "class")= chr [1:3] "PairedPSCBS" "PSCBS" "AbstractCBS" 408s Merging (independently) segmented chromosome...done 408s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 408s 1 1 1 1 554484 143926517 7599 1.3859 2120 408s 2 1 2 1 143926517 185449813 2668 2.0704 775 408s 3 1 3 1 185449813 247137334 4391 2.6341 1314 408s 4 NA NA NA NA NA NA NA NA 408s 5 2 1 1 554484 143926517 7599 1.3859 2120 408s 6 2 2 1 143926517 185449813 2668 2.0704 775 408s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 408s 1 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 408s 2 775 143926517 185449813 775 0.0970 0.9347856 1.135614 408s 3 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 408s 4 NA NA NA NA NA NA NA 408s 5 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 408s 6 775 143926517 185449813 775 0.0970 0.9347856 1.135614 408s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 408s 6 2 2 1 143926517 185449813 2668 2.0704 775 408s 7 2 3 1 185449813 247137334 4391 2.6341 1314 408s 8 NA NA NA NA NA NA NA NA 408s 9 3 1 1 554484 143926517 7599 1.3859 2120 408s 10 3 2 1 143926517 185449813 2668 2.0704 775 408s 11 3 3 1 185449813 247137334 4391 2.6341 1314 408s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 408s 6 775 143926517 185449813 775 0.0970 0.9347856 1.135614 408s 7 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 408s 8 NA NA NA NA NA NA NA 408s 9 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 408s 10 775 143926517 185449813 775 0.0970 0.9347856 1.135614 408s 11 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 408s Segmenting multiple chromosomes...done 408s Segmenting paired tumor-normal signals using Paired PSCBS...done 408s - segmentByPairedPSCBS() using 'multisession' futures ... 408s Segmenting paired tumor-normal signals using Paired PSCBS... 408s Calling genotypes from normal allele B fractions... 408s num [1:44010] 0.8274 0.5072 0.1671 0.1609 0.0421 ... 408s Called genotypes: 408s num [1:44010] 1 0.5 0 0 0 0 1 0 1 0.5 ... 408s - attr(*, "modelFit")=List of 1 408s ..$ :List of 7 408s .. ..$ flavor : chr "density" 408s .. ..$ cn : int 2 408s .. ..$ nbrOfGenotypeGroups: int 3 408s .. ..$ tau : num [1:2] 0.312 0.678 408s .. ..$ n : int 43920 408s .. ..$ fit :Classes 'PeaksAndValleys' and 'data.frame': 5 obs. of 3 variables: 408s .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 408s .. .. ..$ x : num [1:5] 0.0999 0.312 0.4986 0.6775 0.8922 408s .. .. ..$ density: num [1:5] 1.622 0.465 1.125 0.496 1.587 408s .. ..$ fitValleys :Classes 'PeaksAndValleys' and 'data.frame': 2 obs. of 3 variables: 408s .. .. ..$ type : chr [1:2] "valley" "valley" 408s .. .. ..$ x : num [1:2] 0.312 0.678 408s .. .. ..$ density: num [1:2] 0.465 0.496 408s ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 408s muN 408s 0 0.5 1 408s 15627 12633 15750 408s Calling genotypes from normal allele B fractions...done 408s Normalizing betaT using betaN (TumorBoost)... 408s Normalized BAFs: 408s num [1:44010] 0.9301 0.1667 0.0685 0.0995 0.0155 ... 408s - attr(*, "modelFit")=List of 5 408s ..$ method : chr "normalizeTumorBoost" 408s ..$ flavor : chr "v4" 408s ..$ delta : num [1:44010] -0.17264 0.00239 0.1671 0.16085 0.04213 ... 408s .. ..- attr(*, "modelFit")=List of 1 408s .. .. ..$ :List of 7 408s .. .. .. ..$ flavor : chr "density" 408s .. .. .. ..$ cn : int 2 408s .. .. .. ..$ nbrOfGenotypeGroups: int 3 408s .. .. .. ..$ tau : num [1:2] 0.312 0.678 408s .. .. .. ..$ n : int 43920 408s .. .. .. ..$ fit :Classes 'PeaksAndValleys' and 'data.frame': 5 obs. of 3 variables: 408s .. .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 408s .. .. .. .. ..$ x : num [1:5] 0.0999 0.312 0.4986 0.6775 0.8922 408s .. .. .. .. ..$ density: num [1:5] 1.622 0.465 1.125 0.496 1.587 408s .. .. .. ..$ fitValleys :Classes 'PeaksAndValleys' and 'data.frame': 2 obs. of 3 variables: 408s .. .. .. .. ..$ type : chr [1:2] "valley" "valley" 408s .. .. .. .. ..$ x : num [1:2] 0.312 0.678 408s .. .. .. .. ..$ density: num [1:2] 0.465 0.496 408s .. .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 408s ..$ preserveScale: logi FALSE 408s ..$ scaleFactor : num NA 408s Normalizing betaT using betaN (TumorBoost)...done 408s Setup up data... 408s 'data.frame': 44010 obs. of 7 variables: 408s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 408s $ x : num 1145994 2941694 3710825 4240737 4276892 ... 408s $ CT : num 1.63 1.4 1.41 1.17 1.16 ... 408s $ betaT : num 0.7574 0.169 0.2357 0.2604 0.0576 ... 408s $ betaTN : num 0.9301 0.1667 0.0685 0.0995 0.0155 ... 408s ..- attr(*, "modelFit")=List of 5 408s .. ..$ method : chr "normalizeTumorBoost" 408s .. ..$ flavor : chr "v4" 408s .. ..$ delta : num [1:44010] -0.17264 0.00239 0.1671 0.16085 0.04213 ... 408s .. .. ..- attr(*, "modelFit")=List of 1 408s .. .. .. ..$ :List of 7 408s .. .. .. .. ..$ flavor : chr "density" 408s .. .. .. .. ..$ cn : int 2 408s .. .. .. .. ..$ nbrOfGenotypeGroups: int 3 408s .. .. .. .. ..$ tau : num [1:2] 0.312 0.678 408s .. .. .. .. ..$ n : int 43920 408s .. .. .. .. ..$ fit :Classes 'PeaksAndValleys' and 'data.frame': 5 obs. of 3 variables: 408s .. .. .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 408s .. .. .. .. .. ..$ x : num [1:5] 0.0999 0.312 0.4986 0.6775 0.8922 408s .. .. .. .. .. ..$ density: num [1:5] 1.622 0.465 1.125 0.496 1.587 408s .. .. .. .. ..$ fitValleys :Classes 'PeaksAndValleys' and 'data.frame': 2 obs. of 3 variables: 408s .. .. .. .. .. ..$ type : chr [1:2] "valley" "valley" 408s .. .. .. .. .. ..$ x : num [1:2] 0.312 0.678 408s .. .. .. .. .. ..$ density: num [1:2] 0.465 0.496 408s .. .. .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 408s .. ..$ preserveScale: logi FALSE 408s .. ..$ scaleFactor : num NA 408s $ betaN : num 0.8274 0.5072 0.1671 0.1609 0.0421 ... 408s $ muN : num 1 0.5 0 0 0 0 1 0 1 0.5 ... 408s ..- attr(*, "modelFit")=List of 1 408s .. ..$ :List of 7 408s .. .. ..$ flavor : chr "density" 408s .. .. ..$ cn : int 2 408s .. .. ..$ nbrOfGenotypeGroups: int 3 408s .. .. ..$ tau : num [1:2] 0.312 0.678 408s .. .. ..$ n : int 43920 408s .. .. ..$ fit :Classes 'PeaksAndValleys' and 'data.frame': 5 obs. of 3 variables: 408s .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 408s .. .. .. ..$ x : num [1:5] 0.0999 0.312 0.4986 0.6775 0.8922 408s .. .. .. ..$ density: num [1:5] 1.622 0.465 1.125 0.496 1.587 408s .. .. ..$ fitValleys :Classes 'PeaksAndValleys' and 'data.frame': 2 obs. of 3 variables: 408s .. .. .. ..$ type : chr [1:2] "valley" "valley" 408s .. .. .. ..$ x : num [1:2] 0.312 0.678 408s .. .. .. ..$ density: num [1:2] 0.465 0.496 408s .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 408s Setup up data...done 408s Dropping loci for which TCNs are missing... 408s Number of loci dropped: 36 408s Dropping loci for which TCNs are missing...done 408s Ordering data along genome... 408s 'data.frame': 43974 obs. of 7 variables: 408s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 408s $ x : num 554484 730720 782343 878522 916294 ... 408s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 408s $ betaT : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 408s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 408s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 408s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 408s Ordering data along genome...done 408s Segmenting multiple chromosomes... 408s Number of chromosomes: 3 408s Random seed temporarily set (seed=c(48879), kind="L'Ecuyer-CMRG") 408s Produced 3 seeds from this stream for future usage 408s Chromosome #1 ('Chr01') of 3... 408s 'data.frame': 14658 obs. of 8 variables: 408s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 408s $ x : num 554484 730720 782343 878522 916294 ... 408s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 408s $ betaT : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 408s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 408s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 408s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 408s $ index : int 1 2 3 4 5 6 7 8 9 10 ... 408s Known segments: 408s [1] chromosome start end 408s <0 rows> (or 0-length row.names) 408s Chromosome #1 ('Chr01') of 3...done 408s Chromosome #2 ('Chr02') of 3... 408s 'data.frame': 14658 obs. of 8 variables: 408s $ chromosome: int 2 2 2 2 2 2 2 2 2 2 ... 408s $ x : num 554484 730720 782343 878522 916294 ... 408s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 408s $ betaT : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 408s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 408s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 408s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 408s $ index : int 14659 14660 14661 14662 14663 14664 14665 14666 14667 14668 ... 408s Known segments: 408s [1] chromosome start end 408s <0 rows> (or 0-length row.names) 408s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 408s Chromosome #2 ('Chr02') of 3...done 408s Chromosome #3 ('Chr03') of 3... 408s 'data.frame': 14658 obs. of 8 variables: 408s $ chromosome: int 3 3 3 3 3 3 3 3 3 3 ... 408s $ x : num 554484 730720 782343 878522 916294 ... 408s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 408s $ betaT : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 408s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 408s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 408s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 408s $ index : int 29317 29318 29319 29320 29321 29322 29323 29324 29325 29326 ... 408s Known segments: 408s [1] chromosome start end 408s <0 rows> (or 0-length row.names) 408s Segmenting by CBS...done 408s List of 4 408s $ data :'data.frame': 14658 obs. of 4 variables: 408s ..$ chromosome: int [1:14658] 1 1 1 1 1 1 1 1 1 1 ... 408s ..$ x : num [1:14658] 554484 730720 782343 878522 916294 ... 408s ..$ y : num [1:14658] 1.88 1.8 1.59 1.64 1.53 ... 408s ..$ index : int [1:14658] 1 2 3 4 5 6 7 8 9 10 ... 408s $ output :'data.frame': 3 obs. of 6 variables: 408s ..$ sampleName: chr [1:3] NA NA NA 408s ..$ chromosome: int [1:3] 1 1 1 408s ..$ start : num [1:3] 5.54e+05 1.44e+08 1.85e+08 408s ..$ end : num [1:3] 1.44e+08 1.85e+08 2.47e+08 408s ..$ nbrOfLoci : int [1:3] 7599 2668 4391 408s ..$ mean : num [1:3] 1.39 2.07 2.63 408s $ segRows:'data.frame': 3 obs. of 2 variables: 408s ..$ startRow: int [1:3] 1 7600 10268 408s ..$ endRow : int [1:3] 7599 10267 14658 408s $ params :List of 5 408s ..$ alpha : num 0.009 408s ..$ undo : num 0 408s ..$ joinSegments : logi TRUE 408s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 408s .. ..$ chromosome: int 1 408s .. ..$ start : num -Inf 408s .. ..$ end : num Inf 408s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 408s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 408s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.384 0.001 0.385 0 0 408s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 408s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 408s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 408s Identification of change points by total copy numbers...done 408s Restructure TCN segmentation results... 408s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean 408s 1 1 554484 143926517 7599 1.3859 408s 2 1 143926517 185449813 2668 2.0704 408s 3 1 185449813 247137334 4391 2.6341 408s Number of TCN segments: 3 408s Restructure TCN segmentation results...done 408s Total CN segment #1 ([ 554484,1.43927e+08]) of 3... 408s Number of TCN loci in segment: 7599 408s Locus data for TCN segment: 408s 'data.frame': 7599 obs. of 9 variables: 408s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 408s $ x : num 554484 730720 782343 878522 916294 ... 408s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 408s $ betaT : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 408s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 408s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 408s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 408s $ index : int 1 2 3 4 5 6 7 8 9 10 ... 408s $ rho : num NA NA NA NA NA ... 408s Number of loci: 7599 408s Number of SNPs: 2120 (27.90%) 408s Number of heterozygous SNPs: 2120 (100.00%) 408s Chromosome: 1 408s Segmenting DH signals... 408s Segmenting by CBS... 408s Chromosome: 1 408s Random seed temporarily set (seed=c(10407, -821273412, -52578226, 1415511586, 721384351, -665928286, 1316562960), kind="L'Ecuyer-CMRG") 408s Random seed temporarily set (seed=c(10407, -821273412, -52578226, 1415511586, 721384351, -665928286, 1316562960), kind="L'Ecuyer-CMRG") 408s Segmenting by CBS...done 408s List of 4 408s $ data :'data.frame': 7599 obs. of 4 variables: 408s ..$ chromosome: int [1:7599] 1 1 1 1 1 1 1 1 1 1 ... 408s ..$ x : num [1:7599] 554484 730720 782343 878522 916294 ... 408s ..$ y : num [1:7599] NA NA NA NA NA ... 408s ..$ index : int [1:7599] 1 2 3 4 5 6 7 8 9 10 ... 408s $ output :'data.frame': 1 obs. of 6 variables: 408s ..$ sampleName: chr NA 408s ..$ chromosome: int 1 408s ..$ start : num 554484 408s ..$ end : num 1.44e+08 408s ..$ nbrOfLoci : int 2120 408s ..$ mean : num 0.51 408s $ segRows:'data.frame': 1 obs. of 2 variables: 408s ..$ startRow: int 10 408s ..$ endRow : int 7594 408s $ params :List of 5 408s ..$ alpha : num 0.001 408s ..$ undo : num 0 408s ..$ joinSegments : logi TRUE 408s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 408s .. ..$ chromosome: int 1 408s .. ..$ start : num 554484 408s .. ..$ end : num 1.44e+08 408s ..$ seed : int [1:7] 10407 -821273412 -52578226 1415511586 721384351 -665928286 1316562960 408s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 408s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.026 0 0.025 0 0 408s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 408s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 408s - attr(*, "randomSeed")= int [1:7] 10407 -821273412 -52578226 1415511586 721384351 -665928286 1316562960 408s DH segmentation (locally-indexed) rows: 408s startRow endRow 408s 1 10 7594 408s int [1:7599] 1 2 3 4 5 6 7 8 9 10 ... 408s DH segmentation rows: 408s startRow endRow 408s 1 10 7594 408s Segmenting DH signals...done 408s DH segmentation table: 408s dhStart dhEnd dhNbrOfLoci dhMean 408s 1 554484 143926517 2120 0.5101 408s startRow endRow 408s 1 10 7594 408s Rows: 408s [1] 1 408s TCN segmentation rows: 408s startRow endRow 408s 1 1 7599 408s TCN and DH segmentation rows: 408s startRow endRow 408s 1 1 7599 408s startRow endRow 408s 1 10 7594 408s NULL 408s TCN segmentation (expanded) rows: 408s startRow endRow 408s 1 1 7599 408s TCN and DH segmentation rows: 408s startRow endRow 408s 1 1 7599 408s 2 7600 10267 408s 3 10268 14658 408s startRow endRow 408s 1 10 7594 408s startRow endRow 408s 1 1 7599 408s Total CN segmentation table (expanded): 408s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 408s 1 1 554484 143926517 7599 1.3859 2120 2120 408s (TCN,DH) segmentation for one total CN segment: 408s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 408s 1 1 1 1 554484 143926517 7599 1.3859 2120 408s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 408s 1 2120 554484 143926517 2120 0.5101 408s Total CN segment #1 ([ 554484,1.43927e+08]) of 3...done 408s Total CN segment #2 ([1.43927e+08,1.8545e+08]) of 3... 408s Number of TCN loci in segment: 2668 408s Locus data for TCN segment: 408s 'data.frame': 2668 obs. of 9 variables: 408s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 408s $ x : num 1.44e+08 1.44e+08 1.44e+08 1.44e+08 1.44e+08 ... 408s $ CT : num 2.1 2.1 2.09 1.8 2.34 ... 408s $ betaT : num 0.027542 1.030222 1.094093 0.046763 -0.000948 ... 408s $ betaTN : num 0.027542 1.030222 1.094093 0.046763 -0.000948 ... 408s $ betaN : num 0.1624 0.8788 0.8225 0.1201 0.0317 ... 408s $ muN : num 0 1 1 0 0 1 0 0 0 0 ... 408s $ index : int 7600 7601 7602 7603 7604 7605 7606 7607 7608 7609 ... 408s $ rho : num NA NA NA NA NA NA NA NA NA NA ... 408s Number of loci: 2668 408s Number of SNPs: 775 (29.05%) 408s Number of heterozygous SNPs: 775 (100.00%) 408s Chromosome: 1 408s Segmenting DH signals... 408s Segmenting by CBS... 408s Chromosome: 1 408s Random seed temporarily set (seed=c(10407, -821273412, -52578226, 1415511586, 721384351, -665928286, 1316562960), kind="L'Ecuyer-CMRG") 408s Segmenting by CBS...done 408s List of 4 408s $ data :'data.frame': 2668 obs. of 4 variables: 408s ..$ chromosome: int [1:2668] 1 1 1 1 1 1 1 1 1 1 ... 408s ..$ x : num [1:2668] 1.44e+08 1.44e+08 1.44e+08 1.44e+08 1.44e+08 ... 408s ..$ y : num [1:2668] NA NA NA NA NA NA NA NA NA NA ... 408s ..$ index : int [1:2668] 1 2 3 4 5 6 7 8 9 10 ... 408s $ output :'data.frame': 1 obs. of 6 variables: 408s ..$ sampleName: chr NA 408s ..$ chromosome: int 1 408s ..$ start : num 1.44e+08 408s ..$ end : num 1.85e+08 408s ..$ nbrOfLoci : int 775 408s ..$ mean : num 0.097 408s $ segRows:'data.frame': 1 obs. of 2 variables: 408s ..$ startRow: int 15 408s ..$ endRow : int 2664 408s $ params :List of 5 408s ..$ alpha : num 0.001 408s ..$ undo : num 0 408s ..$ joinSegments : logi TRUE 408s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 408s .. ..$ chromosome: int 1 408s .. ..$ start : num 1.44e+08 408s .. ..$ end : num 1.85e+08 408s ..$ seed : int [1:7] 10407 -821273412 -52578226 1415511586 721384351 -665928286 1316562960 408s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 408s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.008 0 0.008 0 0 408s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 408s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 408s - attr(*, "randomSeed")= int [1:7] 10407 -821273412 -52578226 1415511586 721384351 -665928286 1316562960 408s DH segmentation (locally-indexed) rows: 408s startRow endRow 408s 1 15 2664 408s int [1:2668] 7600 7601 7602 7603 7604 7605 7606 7607 7608 7609 ... 408s DH segmentation rows: 408s startRow endRow 408s 1 7614 10263 408s Segmenting DH signals...done 408s DH segmentation table: 408s dhStart dhEnd dhNbrOfLoci dhMean 408s 1 143926517 185449813 775 0.097 408s startRow endRow 408s 1 7614 10263 408s Rows: 408s [1] 2 408s TCN segmentation rows: 408s startRow endRow 408s 2 7600 10267 408s TCN and DH segmentation rows: 408s startRow endRow 408s 2 7600 10267 408s startRow endRow 408s 1 7614 10263 408s startRow endRow 408s 1 1 7599 408s TCN segmentation (expanded) rows: 408s startRow endRow 408s 1 1 7599 408s 2 7600 10267 408s TCN and DH segmentation rows: 408s startRow endRow 408s 1 1 7599 408s 2 7600 10267 408s 3 10268 14658 408s startRow endRow 408s 1 10 7594 408s 2 7614 10263 408s startRow endRow 408s 1 1 7599 408s 2 7600 10267 408s Total CN segmentation table (expanded): 408s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 408s 2 1 143926517 185449813 2668 2.0704 775 775 408s (TCN,DH) segmentation for one total CN segment: 408s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 408s 2 2 1 1 143926517 185449813 2668 2.0704 775 408s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 408s 2 775 143926517 185449813 775 0.097 408s Total CN segment #2 ([1.43927e+08,1.8545e+08]) of 3...done 408s Total CN segment #3 ([1.8545e+08,2.47137e+08]) of 3... 408s Number of TCN loci in segment: 4391 408s Locus data for TCN segment: 408s 'data.frame': 4391 obs. of 9 variables: 408s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 408s $ x : num 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 408s $ CT : num 2.93 2.15 2.82 2.93 2.46 ... 408s $ betaT : num -0.169 0.609 1.028 0.525 0.968 ... 408s $ betaTN : num -0.169 0.609 1.028 0.525 0.968 ... 408s $ betaN : num 0.25 0.38 0.919 0.34 0.783 ... 408s $ muN : num 0 0.5 1 0.5 1 1 0 1 0 1 ... 408s $ index : int 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 408s $ rho : num NA 0.2186 NA 0.0503 NA ... 408s Number of loci: 4391 408s Number of SNPs: 1314 (29.92%) 408s Number of heterozygous SNPs: 1314 (100.00%) 408s Chromosome: 1 408s Segmenting DH signals... 408s Segmenting by CBS... 408s Chromosome: 1 408s Random seed temporarily set (seed=c(10407, -821273412, -52578226, 1415511586, 721384351, -665928286, 1316562960), kind="L'Ecuyer-CMRG") 408s Segmenting by CBS...done 408s List of 4 408s $ data :'data.frame': 4391 obs. of 4 variables: 408s ..$ chromosome: int [1:4391] 1 1 1 1 1 1 1 1 1 1 ... 408s ..$ x : num [1:4391] 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 408s ..$ y : num [1:4391] NA 0.2186 NA 0.0503 NA ... 408s ..$ index : int [1:4391] 1 2 3 4 5 6 7 8 9 10 ... 408s $ output :'data.frame': 1 obs. of 6 variables: 408s ..$ sampleName: chr NA 408s ..$ chromosome: int 1 408s ..$ start : num 1.85e+08 408s ..$ end : num 2.47e+08 408s ..$ nbrOfLoci : int 1314 408s ..$ mean : num 0.23 408s $ segRows:'data.frame': 1 obs. of 2 variables: 408s ..$ startRow: int 2 408s ..$ endRow : int 4388 408s $ params :List of 5 408s ..$ alpha : num 0.001 408s ..$ undo : num 0 408s ..$ joinSegments : logi TRUE 408s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 408s .. ..$ chromosome: int 1 408s .. ..$ start : num 1.85e+08 408s .. ..$ end : num 2.47e+08 408s ..$ seed : int [1:7] 10407 -821273412 -52578226 1415511586 721384351 -665928286 1316562960 408s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 408s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.014 0 0.014 0 0 408s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 408s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 408s - attr(*, "randomSeed")= int [1:7] 10407 -821273412 -52578226 1415511586 721384351 -665928286 1316562960 408s DH segmentation (locally-indexed) rows: 408s startRow endRow 408s 1 2 4388 408s int [1:4391] 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 408s DH segmentation rows: 408s startRow endRow 408s 1 10269 14655 408s Segmenting DH signals...done 408s DH segmentation table: 408s dhStart dhEnd dhNbrOfLoci dhMean 408s 1 185449813 247137334 1314 0.2295 408s startRow endRow 408s 1 10269 14655 408s Rows: 408s [1] 3 408s TCN segmentation rows: 408s startRow endRow 408s 3 10268 14658 408s TCN and DH segmentation rows: 408s startRow endRow 408s 3 10268 14658 408s startRow endRow 408s 1 10269 14655 408s startRow endRow 408s 1 1 7599 408s 2 7600 10267 408s TCN segmentation (expanded) rows: 408s startRow endRow 408s 1 1 7599 408s 2 7600 10267 408s 3 10268 14658 408s TCN and DH segmentation rows: 408s startRow endRow 408s 1 1 7599 408s 2 7600 10267 408s 3 10268 14658 408s startRow endRow 408s 1 10 7594 408s 2 7614 10263 408s 3 10269 14655 408s startRow endRow 408s 1 1 7599 408s 2 7600 10267 408s 3 10268 14658 408s Total CN segmentation table (expanded): 408s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 408s 3 1 185449813 247137334 4391 2.6341 1314 1314 408s (TCN,DH) segmentation for one total CN segment: 408s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 408s 3 3 1 1 185449813 247137334 4391 2.6341 1314 408s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 408s 3 1314 185449813 247137334 1314 0.2295 408s Total CN segment #3 ([1.8545e+08,2.47137e+08]) of 3...done 408s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 408s 1 1 1 1 554484 143926517 7599 1.3859 2120 408s 2 1 2 1 143926517 185449813 2668 2.0704 775 408s 3 1 3 1 185449813 247137334 4391 2.6341 1314 408s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 408s 1 2120 554484 143926517 2120 0.5101 408s 2 775 143926517 185449813 775 0.0970 408s 3 1314 185449813 247137334 1314 0.2295 408s Calculating (C1,C2) per segment... 408s Calculating (C1,C2) per segment...done 408s Number of segments: 3 408s Segmenting paired tumor-normal signals using Paired PSCBS...done 408s Post-segmenting TCNs... 408s Number of segments: 3 408s Number of chromosomes: 1 408s [1] 1 408s Chromosome 1 ('chr01') of 1... 408s Rows: 408s [1] 1 2 3 408s Number of segments: 3 408s TCN segment #1 ('1') of 3... 408s Nothing todo. Only one DH segmentation. Skipping. 408s TCN segment #1 ('1') of 3...done 408s TCN segment #2 ('2') of 3... 408s Nothing todo. Only one DH segmentation. Skipping. 408s TCN segment #2 ('2') of 3...done 408s TCN segment #3 ('3') of 3... 408s Nothing todo. Only one DH segmentation. Skipping. 408s TCN segment #3 ('3') of 3...done 408s Chromosome 1 ('chr01') of 1...done 408s Update (C1,C2) per segment... 408s Update (C1,C2) per segment...done 408s Post-segmenting TCNs...done 408s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 408s 1 1 1 1 554484 143926517 7599 1.3859 2120 408s 2 1 2 1 143926517 185449813 2668 2.0704 775 408s 3 1 3 1 185449813 247137334 4391 2.6341 1314 408s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 408s 1 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 408s 2 775 143926517 185449813 775 0.0970 0.9347856 1.135614 408s 3 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 408s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 408s 1 1 1 1 554484 143926517 7599 1.3859 2120 408s 2 1 2 1 143926517 185449813 2668 2.0704 775 408s 3 1 3 1 185449813 247137334 4391 2.6341 1314 408s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 408s 1 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 408s 2 775 143926517 185449813 775 0.0970 0.9347856 1.135614 408s 3 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 408s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 408s 1 1 1 1 554484 143926517 7599 1.3859 2120 408s 2 1 2 1 143926517 185449813 2668 2.0704 775 408s 3 1 3 1 185449813 247137334 4391 2.6341 1314 408s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 408s 1 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 408s 2 775 143926517 185449813 775 0.0970 0.9347856 1.135614 408s 3 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 408s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 408s 1 1 1 1 554484 143926517 7599 1.3859 2120 408s 2 1 2 1 143926517 185449813 2668 2.0704 775 408s 3 1 3 1 185449813 247137334 4391 2.6341 1314 408s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 408s 1 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 408s 2 775 143926517 185449813 775 0.0970 0.9347856 1.135614 408s 3 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 408s Segmenting by CBS...done 408s List of 4 408s $ data :'data.frame': 14658 obs. of 4 variables: 408s ..$ chromosome: int [1:14658] 2 2 2 2 2 2 2 2 2 2 ... 408s ..$ x : num [1:14658] 554484 730720 782343 878522 916294 ... 408s ..$ y : num [1:14658] 1.88 1.8 1.59 1.64 1.53 ... 408s ..$ index : int [1:14658] 1 2 3 4 5 6 7 8 9 10 ... 408s $ output :'data.frame': 3 obs. of 6 variables: 408s ..$ sampleName: chr [1:3] NA NA NA 408s ..$ chromosome: int [1:3] 2 2 2 408s ..$ start : num [1:3] 5.54e+05 1.44e+08 1.85e+08 408s ..$ end : num [1:3] 1.44e+08 1.85e+08 2.47e+08 408s ..$ nbrOfLoci : int [1:3] 7599 2668 4391 408s ..$ mean : num [1:3] 1.39 2.07 2.63 408s $ segRows:'data.frame': 3 obs. of 2 variables: 408s ..$ startRow: int [1:3] 1 7600 10268 408s ..$ endRow : int [1:3] 7599 10267 14658 408s $ params :List of 5 408s ..$ alpha : num 0.009 408s ..$ undo : num 0 408s ..$ joinSegments : logi TRUE 408s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 408s .. ..$ chromosome: int 2 408s .. ..$ start : num -Inf 408s .. ..$ end : num Inf 408s ..$ seed : int [1:7] 10407 -821273412 -52578226 1415511586 721384351 -665928286 1316562960 408s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 408s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.404 0 0.428 0 0 408s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 408s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 408s - attr(*, "randomSeed")= int [1:7] 10407 -821273412 -52578226 1415511586 721384351 -665928286 1316562960 408s Identification of change points by total copy numbers...done 408s Restructure TCN segmentation results... 408s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean 408s 1 2 554484 143926517 7599 1.3859 408s 2 2 143926517 185449813 2668 2.0704 408s 3 2 185449813 247137334 4391 2.6341 408s Number of TCN segments: 3 408s Restructure TCN segmentation results...done 408s Total CN segment #1 ([ 554484,1.43927e+08]) of 3... 408s Number of TCN loci in segment: 7599 408s Locus data for TCN segment: 408s 'data.frame': 7599 obs. of 9 variables: 408s $ chromosome: int 2 2 2 2 2 2 2 2 2 2 ... 408s $ x : num 554484 730720 782343 878522 916294 ... 408s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 408s $ betaT : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 408s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 408s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 408s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 408s $ index : int 1 2 3 4 5 6 7 8 9 10 ... 408s $ rho : num NA NA NA NA NA ... 408s Number of loci: 7599 408s Number of SNPs: 2120 (27.90%) 408s Number of heterozygous SNPs: 2120 (100.00%) 408s Chromosome: 2 408s Segmenting DH signals... 408s Segmenting by CBS... 408s Chromosome: 2 408s Random seed temporarily set (seed=c(10407, -1924040949, -1632234809, -437763632, -1464377300, 676654412, 2080370711), kind="L'Ecuyer-CMRG") 408s Chromosome #3 ('Chr03') of 3...done 408s Merging (independently) segmented chromosome... 408s Segmenting by CBS...done 408s List of 4 408s $ data :'data.frame': 7599 obs. of 4 variables: 408s ..$ chromosome: int [1:7599] 2 2 2 2 2 2 2 2 2 2 ... 408s ..$ x : num [1:7599] 554484 730720 782343 878522 916294 ... 408s ..$ y : num [1:7599] NA NA NA NA NA ... 408s ..$ index : int [1:7599] 1 2 3 4 5 6 7 8 9 10 ... 408s $ output :'data.frame': 1 obs. of 6 variables: 408s ..$ sampleName: chr NA 408s ..$ chromosome: int 2 408s ..$ start : num 554484 408s ..$ end : num 1.44e+08 408s ..$ nbrOfLoci : int 2120 408s ..$ mean : num 0.51 408s $ segRows:'data.frame': 1 obs. of 2 variables: 408s ..$ startRow: int 10 408s ..$ endRow : int 7594 408s $ params :List of 5 408s ..$ alpha : num 0.001 408s ..$ undo : num 0 408s ..$ joinSegments : logi TRUE 408s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 408s .. ..$ chromosome: int 2 408s .. ..$ start : num 554484 408s .. ..$ end : num 1.44e+08 408s ..$ seed : int [1:7] 10407 -1924040949 -1632234809 -437763632 -1464377300 676654412 2080370711 408s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 408s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.026 0 0.025 0 0 408s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 408s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 408s - attr(*, "randomSeed")= int [1:7] 10407 -1924040949 -1632234809 -437763632 -1464377300 676654412 2080370711 408s DH segmentation (locally-indexed) rows: 408s startRow endRow 408s 1 10 7594 408s int [1:7599] 1 2 3 4 5 6 7 8 9 10 ... 408s DH segmentation rows: 408s startRow endRow 408s 1 10 7594 408s Segmenting DH signals...done 408s DH segmentation table: 408s dhStart dhEnd dhNbrOfLoci dhMean 408s 1 554484 143926517 2120 0.5101 408s startRow endRow 408s 1 10 7594 408s Rows: 408s [1] 1 408s TCN segmentation rows: 408s startRow endRow 408s 1 1 7599 408s TCN and DH segmentation rows: 408s startRow endRow 408s 1 1 7599 408s startRow endRow 408s 1 10 7594 408s NULL 408s TCN segmentation (expanded) rows: 408s startRow endRow 408s 1 1 7599 408s TCN and DH segmentation rows: 408s startRow endRow 408s 1 1 7599 408s 2 7600 10267 408s 3 10268 14658 408s startRow endRow 408s 1 10 7594 408s startRow endRow 408s 1 1 7599 408s Total CN segmentation table (expanded): 408s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 408s 1 2 554484 143926517 7599 1.3859 2120 2120 408s (TCN,DH) segmentation for one total CN segment: 408s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 408s 1 1 1 2 554484 143926517 7599 1.3859 2120 408s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 408s 1 2120 554484 143926517 2120 0.5101 408s Segmenting paired tumor-normal signals using Paired PSCBS... 408s Total CN segment #1 ([ 554484,1.43927e+08]) of 3...done 408s Total CN segment #2 ([1.43927e+08,1.8545e+08]) of 3... 408s Setup up data... 408s Number of TCN loci in segment: 2668 408s Locus data for TCN segment: 408s 'data.frame': 14658 obs. of 7 variables: 408s $ chromosome: int 3 3 3 3 3 3 3 3 3 3 ... 408s $ x : num 554484 730720 782343 878522 916294 ... 408s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 408s $ betaT : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 408s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 408s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 408s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 408s Setup up data...done 408s Ordering data along genome... 408s 'data.frame': 2668 obs. of 9 variables: 408s $ chromosome: int 2 2 2 2 2 2 2 2 2 2 ... 408s $ x : num 1.44e+08 1.44e+08 1.44e+08 1.44e+08 1.44e+08 ... 408s $ CT : num 2.1 2.1 2.09 1.8 2.34 ... 408s $ betaT : num 0.027542 1.030222 1.094093 0.046763 -0.000948 ... 408s $ betaTN : num 0.027542 1.030222 1.094093 0.046763 -0.000948 ... 408s $ betaN : num 0.1624 0.8788 0.8225 0.1201 0.0317 ... 408s $ muN : num 0 1 1 0 0 1 0 0 0 0 ... 408s $ index : int 7600 7601 7602 7603 7604 7605 7606 7607 7608 7609 ... 408s $ rho : num NA NA NA NA NA NA NA NA NA NA ... 408s Number of loci: 2668 408s Number of SNPs: 775 (29.05%) 408s Number of heterozygous SNPs: 775 (100.00%) 408s Chromosome: 2 408s Segmenting DH signals... 408s 'data.frame': 14658 obs. of 7 variables: 408s $ chromosome: int 3 3 3 3 3 3 3 3 3 3 ... 408s $ x : num 554484 730720 782343 878522 916294 ... 408s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 408s $ betaT : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 408s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 408s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 408s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 408s Ordering data along genome...done 408s Keeping only current chromosome for 'knownSegments'... 408s Chromosome: 3 408s Known segments for this chromosome: 408s [1] chromosome start end 408s <0 rows> (or 0-length row.names) 408s Keeping only current chromosome for 'knownSegments'...done 408s alphaTCN: 0.009 408s Segmenting by CBS... 408s Chromosome: 2 408s alphaDH: 0.001 408s Number of loci: 14658 408s Calculating DHs... 408s Number of SNPs: 14658 408s Number of heterozygous SNPs: 4209 (28.71%) 408s Normalized DHs: 408s num [1:14658] NA NA NA NA NA ... 408s Calculating DHs...done 408s Random seed temporarily set (seed=c(10407, -821273412, -52578226, 1415511586, 721384351, -665928286, 1316562960), kind="L'Ecuyer-CMRG") 408s Produced 2 seeds from this stream for future usage 408s Identification of change points by total copy numbers... 408s Segmenting by CBS... 408s Chromosome: 3 408s Random seed temporarily set (seed=c(10407, -1924040949, -1632234809, -437763632, -1464377300, 676654412, 2080370711), kind="L'Ecuyer-CMRG") 408s Random seed temporarily set (seed=c(10407, -1924040949, -1632234809, -437763632, -1464377300, 676654412, 2080370711), kind="L'Ecuyer-CMRG") 408s Segmenting by CBS...done 408s List of 4 408s $ data :'data.frame': 2668 obs. of 4 variables: 408s ..$ chromosome: int [1:2668] 2 2 2 2 2 2 2 2 2 2 ... 408s ..$ x : num [1:2668] 1.44e+08 1.44e+08 1.44e+08 1.44e+08 1.44e+08 ... 408s ..$ y : num [1:2668] NA NA NA NA NA NA NA NA NA NA ... 408s ..$ index : int [1:2668] 1 2 3 4 5 6 7 8 9 10 ... 408s $ output :'data.frame': 1 obs. of 6 variables: 408s ..$ sampleName: chr NA 408s ..$ chromosome: int 2 408s ..$ start : num 1.44e+08 408s ..$ end : num 1.85e+08 408s ..$ nbrOfLoci : int 775 408s ..$ mean : num 0.097 408s $ segRows:'data.frame': 1 obs. of 2 variables: 408s ..$ startRow: int 15 408s ..$ endRow : int 2664 408s $ params :List of 5 408s ..$ alpha : num 0.001 408s ..$ undo : num 0 408s ..$ joinSegments : logi TRUE 408s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 408s .. ..$ chromosome: int 2 408s .. ..$ start : num 1.44e+08 408s .. ..$ end : num 1.85e+08 408s ..$ seed : int [1:7] 10407 -1924040949 -1632234809 -437763632 -1464377300 676654412 2080370711 408s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 408s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.009 0 0.008 0 0 408s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 408s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 408s - attr(*, "randomSeed")= int [1:7] 10407 -1924040949 -1632234809 -437763632 -1464377300 676654412 2080370711 408s DH segmentation (locally-indexed) rows: 408s startRow endRow 408s 1 15 2664 408s int [1:2668] 7600 7601 7602 7603 7604 7605 7606 7607 7608 7609 ... 408s DH segmentation rows: 408s startRow endRow 408s 1 7614 10263 408s Segmenting DH signals...done 408s DH segmentation table: 408s dhStart dhEnd dhNbrOfLoci dhMean 408s 1 143926517 185449813 775 0.097 408s startRow endRow 408s 1 7614 10263 408s Rows: 408s [1] 2 408s TCN segmentation rows: 408s startRow endRow 408s 2 7600 10267 408s TCN and DH segmentation rows: 408s startRow endRow 408s 2 7600 10267 408s startRow endRow 408s 1 7614 10263 408s startRow endRow 408s 1 1 7599 408s TCN segmentation (expanded) rows: 408s startRow endRow 408s 1 1 7599 408s 2 7600 10267 408s TCN and DH segmentation rows: 408s startRow endRow 408s 1 1 7599 408s 2 7600 10267 408s 3 10268 14658 408s startRow endRow 408s 1 10 7594 408s 2 7614 10263 408s startRow endRow 408s 1 1 7599 408s 2 7600 10267 408s Total CN segmentation table (expanded): 408s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 408s 2 2 143926517 185449813 2668 2.0704 775 775 408s (TCN,DH) segmentation for one total CN segment: 408s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 408s 2 2 1 2 143926517 185449813 2668 2.0704 775 408s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 408s 2 775 143926517 185449813 775 0.097 408s Total CN segment #2 ([1.43927e+08,1.8545e+08]) of 3...done 408s Total CN segment #3 ([1.8545e+08,2.47137e+08]) of 3... 408s Number of TCN loci in segment: 4391 408s Locus data for TCN segment: 408s 'data.frame': 4391 obs. of 9 variables: 408s $ chromosome: int 2 2 2 2 2 2 2 2 2 2 ... 408s $ x : num 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 408s $ CT : num 2.93 2.15 2.82 2.93 2.46 ... 408s $ betaT : num -0.169 0.609 1.028 0.525 0.968 ... 408s $ betaTN : num -0.169 0.609 1.028 0.525 0.968 ... 408s $ betaN : num 0.25 0.38 0.919 0.34 0.783 ... 408s $ muN : num 0 0.5 1 0.5 1 1 0 1 0 1 ... 408s $ index : int 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 408s $ rho : num NA 0.2186 NA 0.0503 NA ... 408s Number of loci: 4391 408s Number of SNPs: 1314 (29.92%) 408s Number of heterozygous SNPs: 1314 (100.00%) 408s Chromosome: 2 408s Segmenting DH signals... 408s Segmenting by CBS... 408s Chromosome: 2 408s Random seed temporarily set (seed=c(10407, -1924040949, -1632234809, -437763632, -1464377300, 676654412, 2080370711), kind="L'Ecuyer-CMRG") 408s Segmenting by CBS...done 408s List of 4 408s $ data :'data.frame': 4391 obs. of 4 variables: 408s ..$ chromosome: int [1:4391] 2 2 2 2 2 2 2 2 2 2 ... 408s ..$ x : num [1:4391] 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 408s ..$ y : num [1:4391] NA 0.2186 NA 0.0503 NA ... 408s ..$ index : int [1:4391] 1 2 3 4 5 6 7 8 9 10 ... 408s $ output :'data.frame': 1 obs. of 6 variables: 408s ..$ sampleName: chr NA 408s ..$ chromosome: int 2 408s ..$ start : num 1.85e+08 408s ..$ end : num 2.47e+08 408s ..$ nbrOfLoci : int 1314 408s ..$ mean : num 0.23 408s $ segRows:'data.frame': 1 obs. of 2 variables: 408s ..$ startRow: int 2 408s ..$ endRow : int 4388 408s $ params :List of 5 408s ..$ alpha : num 0.001 408s ..$ undo : num 0 408s ..$ joinSegments : logi TRUE 408s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 408s .. ..$ chromosome: int 2 408s .. ..$ start : num 1.85e+08 408s .. ..$ end : num 2.47e+08 408s ..$ seed : int [1:7] 10407 -1924040949 -1632234809 -437763632 -1464377300 676654412 2080370711 408s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 408s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.015 0 0.015 0 0 408s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 408s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 408s - attr(*, "randomSeed")= int [1:7] 10407 -1924040949 -1632234809 -437763632 -1464377300 676654412 2080370711 408s DH segmentation (locally-indexed) rows: 408s startRow endRow 408s 1 2 4388 408s int [1:4391] 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 408s DH segmentation rows: 408s startRow endRow 408s 1 10269 14655 408s Segmenting DH signals...done 408s DH segmentation table: 408s dhStart dhEnd dhNbrOfLoci dhMean 408s 1 185449813 247137334 1314 0.2295 408s startRow endRow 408s 1 10269 14655 408s Rows: 408s [1] 3 408s TCN segmentation rows: 408s startRow endRow 408s 3 10268 14658 408s TCN and DH segmentation rows: 408s startRow endRow 408s 3 10268 14658 408s startRow endRow 408s 1 10269 14655 408s startRow endRow 408s 1 1 7599 408s 2 7600 10267 408s TCN segmentation (expanded) rows: 408s startRow endRow 408s 1 1 7599 408s 2 7600 10267 408s 3 10268 14658 408s TCN and DH segmentation rows: 408s startRow endRow 408s 1 1 7599 408s 2 7600 10267 408s 3 10268 14658 408s startRow endRow 408s 1 10 7594 408s 2 7614 10263 408s 3 10269 14655 408s startRow endRow 408s 1 1 7599 408s 2 7600 10267 408s 3 10268 14658 408s Total CN segmentation table (expanded): 408s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 408s 3 2 185449813 247137334 4391 2.6341 1314 1314 408s (TCN,DH) segmentation for one total CN segment: 408s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 408s 3 3 1 2 185449813 247137334 4391 2.6341 1314 408s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 408s 3 1314 185449813 247137334 1314 0.2295 408s Total CN segment #3 ([1.8545e+08,2.47137e+08]) of 3...done 408s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 408s 1 2 1 1 554484 143926517 7599 1.3859 2120 408s 2 2 2 1 143926517 185449813 2668 2.0704 775 408s 3 2 3 1 185449813 247137334 4391 2.6341 1314 408s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 408s 1 2120 554484 143926517 2120 0.5101 408s 2 775 143926517 185449813 775 0.0970 408s 3 1314 185449813 247137334 1314 0.2295 408s Calculating (C1,C2) per segment... 408s Calculating (C1,C2) per segment...done 408s Number of segments: 3 408s Segmenting paired tumor-normal signals using Paired PSCBS...done 408s Post-segmenting TCNs... 408s Number of segments: 3 408s Number of chromosomes: 1 408s [1] 2 408s Chromosome 1 ('chr02') of 1... 408s Rows: 408s [1] 1 2 3 408s Number of segments: 3 408s TCN segment #1 ('1') of 3... 408s Nothing todo. Only one DH segmentation. Skipping. 408s TCN segment #1 ('1') of 3...done 408s TCN segment #2 ('2') of 3... 408s Nothing todo. Only one DH segmentation. Skipping. 408s TCN segment #2 ('2') of 3...done 408s TCN segment #3 ('3') of 3... 408s Nothing todo. Only one DH segmentation. Skipping. 408s TCN segment #3 ('3') of 3...done 408s Chromosome 1 ('chr02') of 1...done 408s Update (C1,C2) per segment... 408s Update (C1,C2) per segment...done 408s Post-segmenting TCNs...done 408s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 408s 1 2 1 1 554484 143926517 7599 1.3859 2120 408s 2 2 2 1 143926517 185449813 2668 2.0704 775 408s 3 2 3 1 185449813 247137334 4391 2.6341 1314 408s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 408s 1 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 408s 2 775 143926517 185449813 775 0.0970 0.9347856 1.135614 408s 3 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 408s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 408s 1 2 1 1 554484 143926517 7599 1.3859 2120 408s 2 2 2 1 143926517 185449813 2668 2.0704 775 408s 3 2 3 1 185449813 247137334 4391 2.6341 1314 408s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 408s 1 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 408s 2 775 143926517 185449813 775 0.0970 0.9347856 1.135614 408s 3 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 408s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 408s 1 2 1 1 554484 143926517 7599 1.3859 2120 408s 2 2 2 1 143926517 185449813 2668 2.0704 775 408s 3 2 3 1 185449813 247137334 4391 2.6341 1314 408s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 408s 1 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 408s 2 775 143926517 185449813 775 0.0970 0.9347856 1.135614 408s 3 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 408s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 408s 1 2 1 1 554484 143926517 7599 1.3859 2120 408s 2 2 2 1 143926517 185449813 2668 2.0704 775 408s 3 2 3 1 185449813 247137334 4391 2.6341 1314 408s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 408s 1 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 408s 2 775 143926517 185449813 775 0.0970 0.9347856 1.135614 408s 3 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 408s Segmenting by CBS...done 408s List of 4 408s $ data :'data.frame': 14658 obs. of 4 variables: 408s ..$ chromosome: int [1:14658] 3 3 3 3 3 3 3 3 3 3 ... 408s ..$ x : num [1:14658] 554484 730720 782343 878522 916294 ... 408s ..$ y : num [1:14658] 1.88 1.8 1.59 1.64 1.53 ... 408s ..$ index : int [1:14658] 1 2 3 4 5 6 7 8 9 10 ... 408s $ output :'data.frame': 3 obs. of 6 variables: 408s ..$ sampleName: chr [1:3] NA NA NA 408s ..$ chromosome: int [1:3] 3 3 3 408s ..$ start : num [1:3] 5.54e+05 1.44e+08 1.85e+08 408s ..$ end : num [1:3] 1.44e+08 1.85e+08 2.47e+08 408s ..$ nbrOfLoci : int [1:3] 7599 2668 4391 408s ..$ mean : num [1:3] 1.39 2.07 2.63 408s $ segRows:'data.frame': 3 obs. of 2 variables: 408s ..$ startRow: int [1:3] 1 7600 10268 408s ..$ endRow : int [1:3] 7599 10267 14658 408s $ params :List of 5 408s ..$ alpha : num 0.009 408s ..$ undo : num 0 408s ..$ joinSegments : logi TRUE 408s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 408s .. ..$ chromosome: int 3 408s .. ..$ start : num -Inf 408s .. ..$ end : num Inf 408s ..$ seed : int [1:7] 10407 -1924040949 -1632234809 -437763632 -1464377300 676654412 2080370711 408s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 408s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.381 0 0.394 0 0 408s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 408s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 408s - attr(*, "randomSeed")= int [1:7] 10407 -1924040949 -1632234809 -437763632 -1464377300 676654412 2080370711 408s Identification of change points by total copy numbers...done 408s Restructure TCN segmentation results... 408s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean 408s 1 3 554484 143926517 7599 1.3859 408s 2 3 143926517 185449813 2668 2.0704 408s 3 3 185449813 247137334 4391 2.6341 408s Number of TCN segments: 3 408s Restructure TCN segmentation results...done 408s Total CN segment #1 ([ 554484,1.43927e+08]) of 3... 408s Number of TCN loci in segment: 7599 408s Locus data for TCN segment: 408s 'data.frame': 7599 obs. of 9 variables: 408s $ chromosome: int 3 3 3 3 3 3 3 3 3 3 ... 408s $ x : num 554484 730720 782343 878522 916294 ... 408s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 408s $ betaT : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 408s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 408s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 408s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 408s $ index : int 1 2 3 4 5 6 7 8 9 10 ... 408s $ rho : num NA NA NA NA NA ... 408s Number of loci: 7599 408s Number of SNPs: 2120 (27.90%) 408s Number of heterozygous SNPs: 2120 (100.00%) 408s Chromosome: 3 408s Segmenting DH signals... 408s Segmenting by CBS... 408s Chromosome: 3 408s Random seed temporarily set (seed=c(10407, -1371615447, -889757879, 1692656974, -1723952224, 1378814990, 1816467252), kind="L'Ecuyer-CMRG") 408s Segmenting by CBS...done 408s List of 4 408s $ data :'data.frame': 7599 obs. of 4 variables: 408s ..$ chromosome: int [1:7599] 3 3 3 3 3 3 3 3 3 3 ... 408s ..$ x : num [1:7599] 554484 730720 782343 878522 916294 ... 408s ..$ y : num [1:7599] NA NA NA NA NA ... 408s ..$ index : int [1:7599] 1 2 3 4 5 6 7 8 9 10 ... 408s $ output :'data.frame': 1 obs. of 6 variables: 408s ..$ sampleName: chr NA 408s ..$ chromosome: int 3 408s ..$ start : num 554484 408s ..$ end : num 1.44e+08 408s ..$ nbrOfLoci : int 2120 408s ..$ mean : num 0.51 408s $ segRows:'data.frame': 1 obs. of 2 variables: 408s ..$ startRow: int 10 408s ..$ endRow : int 7594 408s $ params :List of 5 408s ..$ alpha : num 0.001 408s ..$ undo : num 0 408s ..$ joinSegments : logi TRUE 408s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 408s .. ..$ chromosome: int 3 408s .. ..$ start : num 554484 408s .. ..$ end : num 1.44e+08 408s ..$ seed : int [1:7] 10407 -1371615447 -889757879 1692656974 -1723952224 1378814990 1816467252 408s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 408s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.025 0 0.025 0 0 408s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 408s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 408s - attr(*, "randomSeed")= int [1:7] 10407 -1371615447 -889757879 1692656974 -1723952224 1378814990 1816467252 408s DH segmentation (locally-indexed) rows: 408s startRow endRow 408s 1 10 7594 408s int [1:7599] 1 2 3 4 5 6 7 8 9 10 ... 408s DH segmentation rows: 408s startRow endRow 408s 1 10 7594 408s Segmenting DH signals...done 408s DH segmentation table: 408s dhStart dhEnd dhNbrOfLoci dhMean 408s 1 554484 143926517 2120 0.5101 408s startRow endRow 408s 1 10 7594 408s Rows: 408s [1] 1 408s TCN segmentation rows: 408s startRow endRow 408s 1 1 7599 408s TCN and DH segmentation rows: 408s startRow endRow 408s 1 1 7599 408s startRow endRow 408s 1 10 7594 408s NULL 408s TCN segmentation (expanded) rows: 408s startRow endRow 408s 1 1 7599 408s TCN and DH segmentation rows: 408s startRow endRow 408s 1 1 7599 408s 2 7600 10267 408s 3 10268 14658 408s startRow endRow 408s 1 10 7594 408s startRow endRow 408s 1 1 7599 408s Total CN segmentation table (expanded): 408s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 408s 1 3 554484 143926517 7599 1.3859 2120 2120 408s (TCN,DH) segmentation for one total CN segment: 408s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 408s 1 1 1 3 554484 143926517 7599 1.3859 2120 408s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 408s 1 2120 554484 143926517 2120 0.5101 408s Total CN segment #1 ([ 554484,1.43927e+08]) of 3...done 408s Total CN segment #2 ([1.43927e+08,1.8545e+08]) of 3... 408s Number of TCN loci in segment: 2668 408s Locus data for TCN segment: 408s 'data.frame': 2668 obs. of 9 variables: 408s $ chromosome: int 3 3 3 3 3 3 3 3 3 3 ... 408s $ x : num 1.44e+08 1.44e+08 1.44e+08 1.44e+08 1.44e+08 ... 408s $ CT : num 2.1 2.1 2.09 1.8 2.34 ... 408s $ betaT : num 0.027542 1.030222 1.094093 0.046763 -0.000948 ... 408s $ betaTN : num 0.027542 1.030222 1.094093 0.046763 -0.000948 ... 408s $ betaN : num 0.1624 0.8788 0.8225 0.1201 0.0317 ... 408s $ muN : num 0 1 1 0 0 1 0 0 0 0 ... 408s $ index : int 7600 7601 7602 7603 7604 7605 7606 7607 7608 7609 ... 408s $ rho : num NA NA NA NA NA NA NA NA NA NA ... 408s Number of loci: 2668 408s Number of SNPs: 775 (29.05%) 408s Number of heterozygous SNPs: 775 (100.00%) 408s Chromosome: 3 408s Segmenting DH signals... 408s Segmenting by CBS... 408s Chromosome: 3 408s Random seed temporarily set (seed=c(10407, -1371615447, -889757879, 1692656974, -1723952224, 1378814990, 1816467252), kind="L'Ecuyer-CMRG") 408s Segmenting by CBS...done 408s List of 4 408s $ data :'data.frame': 2668 obs. of 4 variables: 408s ..$ chromosome: int [1:2668] 3 3 3 3 3 3 3 3 3 3 ... 408s ..$ x : num [1:2668] 1.44e+08 1.44e+08 1.44e+08 1.44e+08 1.44e+08 ... 408s ..$ y : num [1:2668] NA NA NA NA NA NA NA NA NA NA ... 408s ..$ index : int [1:2668] 1 2 3 4 5 6 7 8 9 10 ... 408s $ output :'data.frame': 1 obs. of 6 variables: 408s ..$ sampleName: chr NA 408s ..$ chromosome: int 3 408s ..$ start : num 1.44e+08 408s ..$ end : num 1.85e+08 408s ..$ nbrOfLoci : int 775 408s ..$ mean : num 0.097 408s $ segRows:'data.frame': 1 obs. of 2 variables: 408s ..$ startRow: int 15 408s ..$ endRow : int 2664 408s $ params :List of 5 408s ..$ alpha : num 0.001 408s ..$ undo : num 0 408s ..$ joinSegments : logi TRUE 408s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 408s .. ..$ chromosome: int 3 408s .. ..$ start : num 1.44e+08 408s .. ..$ end : num 1.85e+08 408s ..$ seed : int [1:7] 10407 -1371615447 -889757879 1692656974 -1723952224 1378814990 1816467252 408s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 408s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.009 0 0.008 0 0 408s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 408s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 408s - attr(*, "randomSeed")= int [1:7] 10407 -1371615447 -889757879 1692656974 -1723952224 1378814990 1816467252 408s DH segmentation (locally-indexed) rows: 408s startRow endRow 408s 1 15 2664 408s int [1:2668] 7600 7601 7602 7603 7604 7605 7606 7607 7608 7609 ... 408s DH segmentation rows: 408s startRow endRow 408s 1 7614 10263 408s Segmenting DH signals...done 408s DH segmentation table: 408s dhStart dhEnd dhNbrOfLoci dhMean 408s 1 143926517 185449813 775 0.097 408s startRow endRow 408s 1 7614 10263 408s Rows: 408s [1] 2 408s TCN segmentation rows: 408s startRow endRow 408s 2 7600 10267 408s TCN and DH segmentation rows: 408s startRow endRow 408s 2 7600 10267 408s startRow endRow 408s 1 7614 10263 408s startRow endRow 408s 1 1 7599 408s TCN segmentation (expanded) rows: 408s startRow endRow 408s 1 1 7599 408s 2 7600 10267 408s TCN and DH segmentation rows: 408s startRow endRow 408s 1 1 7599 408s 2 7600 10267 408s 3 10268 14658 408s startRow endRow 408s 1 10 7594 408s 2 7614 10263 408s startRow endRow 408s 1 1 7599 408s 2 7600 10267 408s Total CN segmentation table (expanded): 408s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 408s 2 3 143926517 185449813 2668 2.0704 775 775 408s (TCN,DH) segmentation for one total CN segment: 408s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 408s 2 2 1 3 143926517 185449813 2668 2.0704 775 408s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 408s 2 775 143926517 185449813 775 0.097 408s Total CN segment #2 ([1.43927e+08,1.8545e+08]) of 3...done 408s Total CN segment #3 ([1.8545e+08,2.47137e+08]) of 3... 408s Number of TCN loci in segment: 4391 408s Locus data for TCN segment: 408s 'data.frame': 4391 obs. of 9 variables: 408s $ chromosome: int 3 3 3 3 3 3 3 3 3 3 ... 408s $ x : num 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 408s $ CT : num 2.93 2.15 2.82 2.93 2.46 ... 408s $ betaT : num -0.169 0.609 1.028 0.525 0.968 ... 408s $ betaTN : num -0.169 0.609 1.028 0.525 0.968 ... 408s $ betaN : num 0.25 0.38 0.919 0.34 0.783 ... 408s $ muN : num 0 0.5 1 0.5 1 1 0 1 0 1 ... 408s $ index : int 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 408s $ rho : num NA 0.2186 NA 0.0503 NA ... 408s Number of loci: 4391 408s Number of SNPs: 1314 (29.92%) 408s Number of heterozygous SNPs: 1314 (100.00%) 408s Chromosome: 3 408s Segmenting DH signals... 408s Segmenting by CBS... 408s Chromosome: 3 408s Random seed temporarily set (seed=c(10407, -1371615447, -889757879, 1692656974, -1723952224, 1378814990, 1816467252), kind="L'Ecuyer-CMRG") 408s Segmenting by CBS...done 408s List of 4 408s $ data :'data.frame': 4391 obs. of 4 variables: 408s ..$ chromosome: int [1:4391] 3 3 3 3 3 3 3 3 3 3 ... 408s ..$ x : num [1:4391] 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 408s ..$ y : num [1:4391] NA 0.2186 NA 0.0503 NA ... 408s ..$ index : int [1:4391] 1 2 3 4 5 6 7 8 9 10 ... 408s $ output :'data.frame': 1 obs. of 6 variables: 408s ..$ sampleName: chr NA 408s ..$ chromosome: int 3 408s ..$ start : num 1.85e+08 408s ..$ end : num 2.47e+08 408s ..$ nbrOfLoci : int 1314 408s ..$ mean : num 0.23 408s $ segRows:'data.frame': 1 obs. of 2 variables: 408s ..$ startRow: int 2 408s ..$ endRow : int 4388 408s $ params :List of 5 408s ..$ alpha : num 0.001 408s ..$ undo : num 0 408s ..$ joinSegments : logi TRUE 408s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 408s .. ..$ chromosome: int 3 408s .. ..$ start : num 1.85e+08 408s .. ..$ end : num 2.47e+08 408s ..$ seed : int [1:7] 10407 -1371615447 -889757879 1692656974 -1723952224 1378814990 1816467252 408s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 408s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.014 0.001 0.015 0 0 408s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 408s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 408s - attr(*, "randomSeed")= int [1:7] 10407 -1371615447 -889757879 1692656974 -1723952224 1378814990 1816467252 408s DH segmentation (locally-indexed) rows: 408s startRow endRow 408s 1 2 4388 408s int [1:4391] 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 408s DH segmentation rows: 408s startRow endRow 408s 1 10269 14655 408s Segmenting DH signals...done 408s DH segmentation table: 408s dhStart dhEnd dhNbrOfLoci dhMean 408s 1 185449813 247137334 1314 0.2295 408s startRow endRow 408s 1 10269 14655 408s Rows: 408s [1] 3 408s TCN segmentation rows: 408s startRow endRow 408s 3 10268 14658 408s TCN and DH segmentation rows: 408s startRow endRow 408s 3 10268 14658 408s startRow endRow 408s 1 10269 14655 408s startRow endRow 408s 1 1 7599 408s 2 7600 10267 408s TCN segmentation (expanded) rows: 408s startRow endRow 408s 1 1 7599 408s 2 7600 10267 408s 3 10268 14658 408s TCN and DH segmentation rows: 408s startRow endRow 408s 1 1 7599 408s 2 7600 10267 408s 3 10268 14658 408s startRow endRow 408s 1 10 7594 408s 2 7614 10263 408s 3 10269 14655 408s startRow endRow 408s 1 1 7599 408s 2 7600 10267 408s 3 10268 14658 408s Total CN segmentation table (expanded): 408s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 408s 3 3 185449813 247137334 4391 2.6341 1314 1314 408s (TCN,DH) segmentation for one total CN segment: 408s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 408s 3 3 1 3 185449813 247137334 4391 2.6341 1314 408s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 408s 3 1314 185449813 247137334 1314 0.2295 408s Total CN segment #3 ([1.8545e+08,2.47137e+08]) of 3...done 408s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 408s 1 3 1 1 554484 143926517 7599 1.3859 2120 408s 2 3 2 1 143926517 185449813 2668 2.0704 775 408s 3 3 3 1 185449813 247137334 4391 2.6341 1314 408s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 408s 1 2120 554484 143926517 2120 0.5101 408s 2 775 143926517 185449813 775 0.0970 408s 3 1314 185449813 247137334 1314 0.2295 408s Calculating (C1,C2) per segment... 408s Calculating (C1,C2) per segment...done 408s Number of segments: 3 408s Segmenting paired tumor-normal signals using Paired PSCBS...done 408s Post-segmenting TCNs... 408s Number of segments: 3 408s Number of chromosomes: 1 408s [1] 3 408s Chromosome 1 ('chr03') of 1... 408s Rows: 408s [1] 1 2 3 408s Number of segments: 3 408s TCN segment #1 ('1') of 3... 408s Nothing todo. Only one DH segmentation. Skipping. 408s TCN segment #1 ('1') of 3...done 408s TCN segment #2 ('2') of 3... 408s Nothing todo. Only one DH segmentation. Skipping. 408s TCN segment #2 ('2') of 3...done 408s TCN segment #3 ('3') of 3... 408s Nothing todo. Only one DH segmentation. Skipping. 408s TCN segment #3 ('3') of 3...done 408s Chromosome 1 ('chr03') of 1...done 408s Update (C1,C2) per segment... 408s Update (C1,C2) per segment...done 408s Post-segmenting TCNs...done 408s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 408s 1 3 1 1 554484 143926517 7599 1.3859 2120 408s 2 3 2 1 143926517 185449813 2668 2.0704 775 408s 3 3 3 1 185449813 247137334 4391 2.6341 1314 408s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 408s 1 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 408s 2 775 143926517 185449813 775 0.0970 0.9347856 1.135614 408s 3 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 408s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 408s 1 3 1 1 554484 143926517 7599 1.3859 2120 408s 2 3 2 1 143926517 185449813 2668 2.0704 775 408s 3 3 3 1 185449813 247137334 4391 2.6341 1314 408s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 408s 1 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 408s 2 775 143926517 185449813 775 0.0970 0.9347856 1.135614 408s 3 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 408s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 408s 1 3 1 1 554484 143926517 7599 1.3859 2120 408s 2 3 2 1 143926517 185449813 2668 2.0704 775 408s 3 3 3 1 185449813 247137334 4391 2.6341 1314 408s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 408s 1 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 408s 2 775 143926517 185449813 775 0.0970 0.9347856 1.135614 408s 3 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 408s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 408s 1 3 1 1 554484 143926517 7599 1.3859 2120 408s 2 3 2 1 143926517 185449813 2668 2.0704 775 408s 3 3 3 1 185449813 247137334 4391 2.6341 1314 408s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 408s 1 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 408s 2 775 143926517 185449813 775 0.0970 0.9347856 1.135614 408s 3 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 408s List of 5 408s $ data :Classes 'PairedPSCNData' and 'data.frame': 43974 obs. of 8 variables: 408s ..$ chromosome: int [1:43974] 1 1 1 1 1 1 1 1 1 1 ... 408s ..$ x : num [1:43974] 554484 730720 782343 878522 916294 ... 408s ..$ CT : num [1:43974] 1.88 1.8 1.59 1.64 1.53 ... 408s ..$ betaT : num [1:43974] 0.0646 0.1672 0.9284 0.113 0.7209 ... 408s ..$ betaTN : num [1:43974] -0.0515 -0.1172 1.0194 0.031 0.8604 ... 408s ..$ betaN : num [1:43974] 0.116 0.284 0.909 0.082 0.86 ... 408s ..$ muN : num [1:43974] 0 0 1 0 1 1 1 0 1 0.5 ... 408s ..$ rho : num [1:43974] NA NA NA NA NA ... 408s $ output :Classes 'PairedPSCNSegments' and 'data.frame': 11 obs. of 15 variables: 408s ..$ chromosome : int [1:11] 1 1 1 NA 2 2 2 NA 3 3 ... 408s ..$ tcnId : int [1:11] 1 2 3 NA 1 2 3 NA 1 2 ... 408s ..$ dhId : int [1:11] 1 1 1 NA 1 1 1 NA 1 1 ... 408s ..$ tcnStart : num [1:11] 5.54e+05 1.44e+08 1.85e+08 NA 5.54e+05 ... 408s ..$ tcnEnd : num [1:11] 1.44e+08 1.85e+08 2.47e+08 NA 1.44e+08 ... 408s ..$ tcnNbrOfLoci: int [1:11] 7599 2668 4391 NA 7599 2668 4391 NA 7599 2668 ... 408s ..$ tcnMean : num [1:11] 1.39 2.07 2.63 NA 1.39 ... 408s ..$ tcnNbrOfSNPs: int [1:11] 2120 775 1314 NA 2120 775 1314 NA 2120 775 ... 408s ..$ tcnNbrOfHets: int [1:11] 2120 775 1314 NA 2120 775 1314 NA 2120 775 ... 408s ..$ dhStart : num [1:11] 5.54e+05 1.44e+08 1.85e+08 NA 5.54e+05 ... 408s ..$ dhEnd : num [1:11] 1.44e+08 1.85e+08 2.47e+08 NA 1.44e+08 ... 408s ..$ dhNbrOfLoci : int [1:11] 2120 775 1314 NA 2120 775 1314 NA 2120 775 ... 408s ..$ dhMean : num [1:11] 0.51 0.097 0.23 NA 0.51 ... 408s ..$ c1Mean : num [1:11] 0.339 0.935 1.015 NA 0.339 ... 408s ..$ c2Mean : num [1:11] 1.05 1.14 1.62 NA 1.05 ... 408s $ tcnSegRows:'data.frame': 11 obs. of 2 variables: 408s ..$ startRow: int [1:11] 1 7600 10268 NA 14659 22258 24926 NA 29317 36916 ... 408s ..$ endRow : int [1:11] 7599 10267 14658 NA 22257 24925 29316 NA 36915 39583 ... 408s $ dhSegRows :'data.frame': 11 obs. of 2 variables: 408s ..$ startRow: int [1:11] 10 7614 10269 NA 14668 22272 24927 NA 29326 36930 ... 408s ..$ endRow : int [1:11] 7594 10263 14655 NA 22252 24921 29313 NA 36910 39579 ... 408s $ params :List of 7 408s ..$ alphaTCN : num 0.009 408s ..$ alphaDH : num 0.001 408s ..$ flavor : chr "tcn&dh" 408s ..$ tbn : logi FALSE 408s ..$ joinSegments : logi TRUE 408s ..$ knownSegments:'data.frame': 0 obs. of 3 variables: 408s .. ..$ chromosome: int(0) 408s .. ..$ start : int(0) 408s .. ..$ end : int(0) 408s ..$ seed : int [1:7] 10407 1066287653 -51199871 161854402 -1995183193 1503453565 -747102133 408s - attr(*, "class")= chr [1:3] "PairedPSCBS" "PSCBS" "AbstractCBS" 408s Merging (independently) segmented chromosome...done 408s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 408s 1 1 1 1 554484 143926517 7599 1.3859 2120 408s 2 1 2 1 143926517 185449813 2668 2.0704 775 408s 3 1 3 1 185449813 247137334 4391 2.6341 1314 408s 4 NA NA NA NA NA NA NA NA 408s 5 2 1 1 554484 143926517 7599 1.3859 2120 408s 6 2 2 1 143926517 185449813 2668 2.0704 775 408s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 408s 1 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 408s 2 775 143926517 185449813 775 0.0970 0.9347856 1.135614 408s 3 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 408s 4 NA NA NA NA NA NA NA 408s 5 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 408s 6 775 143926517 185449813 775 0.0970 0.9347856 1.135614 408s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 408s 6 2 2 1 143926517 185449813 2668 2.0704 775 408s 7 2 3 1 185449813 247137334 4391 2.6341 1314 408s 8 NA NA NA NA NA NA NA NA 408s 9 3 1 1 554484 143926517 7599 1.3859 2120 408s 10 3 2 1 143926517 185449813 2668 2.0704 775 408s 11 3 3 1 185449813 247137334 4391 2.6341 1314 408s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 408s 6 775 143926517 185449813 775 0.0970 0.9347856 1.135614 408s 7 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 408s 8 NA NA NA NA NA NA NA 408s 9 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 408s 10 775 143926517 185449813 775 0.0970 0.9347856 1.135614 408s 11 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 408s Segmenting multiple chromosomes...done 408s Segmenting paired tumor-normal signals using Paired PSCBS...done 408s > 408s > message("*** segmentByPairedPSCBS() via futures ... DONE") 408s *** segmentByPairedPSCBS() via futures ... DONE 408s > 408s > 408s > message("*** segmentByPairedPSCBS() via futures with known segments ...") 408s *** segmentByPairedPSCBS() via futures with known segments ... 408s > fits <- list() 408s > dataT <- subset(data, chromosome == 1) 408s > gaps <- findLargeGaps(dataT, minLength=2e6) 408s > knownSegments <- gapsToSegments(gaps) 408s > 408s > for (strategy in strategies) { 408s + message(sprintf("- segmentByPairedPSCBS() w/ known segments using '%s' futures ...", strategy)) 408s + plan(strategy) 408s + fit <- segmentByPairedPSCBS(dataT, knownSegments=knownSegments, seed=0xBEEF, verbose=TRUE) 408s + fits[[strategy]] <- fit 408s + equal <- all.equal(fit, fits[[1]]) 408s + if (!equal) { 408s + str(fit) 408s + str(fits[[1]]) 408s + print(equal) 408s + stop(sprintf("segmentByPairedPSCBS() w/ known segments using '%s' futures does not produce the same results as when using '%s' futures", strategy, names(fits)[1])) 408s + } 408s + } 408s - segmentByPairedPSCBS() w/ known segments using 'sequential' futures ... 408s Segmenting paired tumor-normal signals using Paired PSCBS... 408s Calling genotypes from normal allele B fractions... 408s num [1:14670] 0.8274 0.5072 0.1671 0.1609 0.0421 ... 408s Called genotypes: 408s num [1:14670] 1 0.5 0 0 0 0 1 0 1 0.5 ... 408s - attr(*, "modelFit")=List of 1 408s ..$ :List of 7 408s .. ..$ flavor : chr "density" 408s .. ..$ cn : int 2 408s .. ..$ nbrOfGenotypeGroups: int 3 408s .. ..$ tau : num [1:2] 0.315 0.677 408s .. ..$ n : int 14640 408s .. ..$ fit :Classes 'PeaksAndValleys' and 'data.frame': 5 obs. of 3 variables: 408s .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 408s .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 408s .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 408s .. ..$ fitValleys :Classes 'PeaksAndValleys' and 'data.frame': 2 obs. of 3 variables: 408s .. .. ..$ type : chr [1:2] "valley" "valley" 408s .. .. ..$ x : num [1:2] 0.315 0.677 408s .. .. ..$ density: num [1:2] 0.522 0.551 408s ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 408s muN 408s 0 0.5 1 408s 5221 4198 5251 408s Calling genotypes from normal allele B fractions...done 408s Normalizing betaT using betaN (TumorBoost)... 408s Normalized BAFs: 408s num [1:14670] 0.9301 0.1667 0.0685 0.0995 0.0155 ... 408s - attr(*, "modelFit")=List of 5 408s ..$ method : chr "normalizeTumorBoost" 408s ..$ flavor : chr "v4" 408s ..$ delta : num [1:14670] -0.17264 0.00239 0.1671 0.16085 0.04213 ... 408s .. ..- attr(*, "modelFit")=List of 1 408s .. .. ..$ :List of 7 408s .. .. .. ..$ flavor : chr "density" 408s .. .. .. ..$ cn : int 2 408s .. .. .. ..$ nbrOfGenotypeGroups: int 3 408s .. .. .. ..$ tau : num [1:2] 0.315 0.677 408s .. .. .. ..$ n : int 14640 408s .. .. .. ..$ fit :Classes 'PeaksAndValleys' and 'data.frame': 5 obs. of 3 variables: 408s .. .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 408s .. .. .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 408s .. .. .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 408s .. .. .. ..$ fitValleys :Classes 'PeaksAndValleys' and 'data.frame': 2 obs. of 3 variables: 408s .. .. .. .. ..$ type : chr [1:2] "valley" "valley" 408s .. .. .. .. ..$ x : num [1:2] 0.315 0.677 408s .. .. .. .. ..$ density: num [1:2] 0.522 0.551 408s .. .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 408s ..$ preserveScale: logi FALSE 408s ..$ scaleFactor : num NA 408s Normalizing betaT using betaN (TumorBoost)...done 408s Setup up data... 408s 'data.frame': 14670 obs. of 7 variables: 408s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 408s $ x : num 1145994 2941694 3710825 4240737 4276892 ... 408s $ CT : num 1.63 1.4 1.41 1.17 1.16 ... 408s $ betaT : num 0.7574 0.169 0.2357 0.2604 0.0576 ... 408s $ betaTN : num 0.9301 0.1667 0.0685 0.0995 0.0155 ... 408s ..- attr(*, "modelFit")=List of 5 408s .. ..$ method : chr "normalizeTumorBoost" 408s .. ..$ flavor : chr "v4" 408s .. ..$ delta : num [1:14670] -0.17264 0.00239 0.1671 0.16085 0.04213 ... 408s .. .. ..- attr(*, "modelFit")=List of 1 408s .. .. .. ..$ :List of 7 408s .. .. .. .. ..$ flavor : chr "density" 408s .. .. .. .. ..$ cn : int 2 408s .. .. .. .. ..$ nbrOfGenotypeGroups: int 3 408s .. .. .. .. ..$ tau : num [1:2] 0.315 0.677 408s .. .. .. .. ..$ n : int 14640 408s .. .. .. .. ..$ fit :Classes 'PeaksAndValleys' and 'data.frame': 5 obs. of 3 variables: 408s .. .. .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 408s .. .. .. .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 408s .. .. .. .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 408s .. .. .. .. ..$ fitValleys :Classes 'PeaksAndValleys' and 'data.frame': 2 obs. of 3 variables: 408s .. .. .. .. .. ..$ type : chr [1:2] "valley" "valley" 408s .. .. .. .. .. ..$ x : num [1:2] 0.315 0.677 408s .. .. .. .. .. ..$ density: num [1:2] 0.522 0.551 408s .. .. .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 408s .. ..$ preserveScale: logi FALSE 408s .. ..$ scaleFactor : num NA 408s $ betaN : num 0.8274 0.5072 0.1671 0.1609 0.0421 ... 408s $ muN : num 1 0.5 0 0 0 0 1 0 1 0.5 ... 408s ..- attr(*, "modelFit")=List of 1 408s .. ..$ :List of 7 408s .. .. ..$ flavor : chr "density" 408s .. .. ..$ cn : int 2 408s .. .. ..$ nbrOfGenotypeGroups: int 3 408s .. .. ..$ tau : num [1:2] 0.315 0.677 408s .. .. ..$ n : int 14640 408s .. .. ..$ fit :Classes 'PeaksAndValleys' and 'data.frame': 5 obs. of 3 variables: 408s .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 408s .. .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 408s .. .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 408s .. .. ..$ fitValleys :Classes 'PeaksAndValleys' and 'data.frame': 2 obs. of 3 variables: 408s .. .. .. ..$ type : chr [1:2] "valley" "valley" 408s .. .. .. ..$ x : num [1:2] 0.315 0.677 408s .. .. .. ..$ density: num [1:2] 0.522 0.551 408s .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 408s Setup up data...done 408s Dropping loci for which TCNs are missing... 408s Number of loci dropped: 12 408s Dropping loci for which TCNs are missing...done 408s Ordering data along genome... 408s 'data.frame': 14658 obs. of 7 variables: 408s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 408s $ x : num 554484 730720 782343 878522 916294 ... 408s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 408s $ betaT : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 408s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 408s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 408s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 408s Ordering data along genome...done 408s Keeping only current chromosome for 'knownSegments'... 408s Chromosome: 1 408s Known segments for this chromosome: 408s chromosome start end length 408s 1 1 -Inf 120908858 Inf 408s 2 1 120908859 142693887 21785028 408s 3 1 142693888 Inf Inf 408s Keeping only current chromosome for 'knownSegments'...done 408s alphaTCN: 0.009 408s alphaDH: 0.001 408s Number of loci: 14658 408s Calculating DHs... 408s Number of SNPs: 14658 408s Number of heterozygous SNPs: 4196 (28.63%) 408s Normalized DHs: 408s num [1:14658] NA NA NA NA NA ... 408s Calculating DHs...done 408s Random seed temporarily set (seed=c(48879), kind="L'Ecuyer-CMRG") 408s Produced 2 seeds from this stream for future usage 408s Identification of change points by total copy numbers... 408s Segmenting by CBS... 408s Chromosome: 1 408s Random seed temporarily set (seed=c(10407, 1066287653, -51199871, 161854402, -1995183193, 1503453565, -747102133), kind="L'Ecuyer-CMRG") 408s Produced 3 seeds from this stream for future usage 408s Segmenting by CBS...done 408s List of 4 408s $ data :'data.frame': 14658 obs. of 4 variables: 408s ..$ chromosome: int [1:14658] 1 1 1 1 1 1 1 1 1 1 ... 408s ..$ x : num [1:14658] 554484 730720 782343 878522 916294 ... 408s ..$ y : num [1:14658] 1.88 1.8 1.59 1.64 1.53 ... 408s ..$ index : int [1:14658] 1 2 3 4 5 6 7 8 9 10 ... 408s $ output :'data.frame': 4 obs. of 6 variables: 408s ..$ sampleName: chr [1:4] NA NA NA NA 408s ..$ chromosome: int [1:4] 1 1 1 1 408s ..$ start : num [1:4] 5.54e+05 1.21e+08 1.43e+08 1.85e+08 408s ..$ end : num [1:4] 1.21e+08 1.43e+08 1.85e+08 2.47e+08 408s ..$ nbrOfLoci : int [1:4] 7586 0 2681 4391 408s ..$ mean : num [1:4] 1.39 NA 2.07 2.63 408s $ segRows:'data.frame': 4 obs. of 2 variables: 408s ..$ startRow: int [1:4] 1 NA 7587 10268 408s ..$ endRow : int [1:4] 7586 NA 10267 14658 408s $ params :List of 5 408s ..$ alpha : num 0.009 408s ..$ undo : num 0 408s ..$ joinSegments : logi TRUE 408s ..$ knownSegments:'data.frame': 4 obs. of 3 variables: 408s .. ..$ chromosome: int [1:4] 1 1 2 1 408s .. ..$ start : num [1:4] -Inf -Inf -Inf 1.43e+08 408s .. ..$ end : num [1:4] 1.21e+08 Inf Inf Inf 408s ..$ seed : int [1:7] 10407 1066287653 -51199871 161854402 -1995183193 1503453565 -747102133 408s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 408s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.128 0 0.128 0 0 408s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 408s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 408s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 408s Identification of change points by total copy numbers...done 408s Restructure TCN segmentation results... 408s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean 408s 1 1 554484 120908858 7586 1.3853 408s 2 1 120908859 142693887 0 NA 408s 3 1 142693888 185449813 2681 2.0689 408s 4 1 185449813 247137334 4391 2.6341 408s Number of TCN segments: 4 408s Restructure TCN segmentation results...done 408s Total CN segment #1 ([ 554484,1.20909e+08]) of 4... 408s Number of TCN loci in segment: 7586 408s Locus data for TCN segment: 408s 'data.frame': 7586 obs. of 9 variables: 408s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 408s $ x : num 554484 730720 782343 878522 916294 ... 408s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 408s $ betaT : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 408s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 408s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 408s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 408s $ index : int 1 2 3 4 5 6 7 8 9 10 ... 408s $ rho : num NA NA NA NA NA ... 408s Number of loci: 7586 408s Number of SNPs: 2108 (27.79%) 408s Number of heterozygous SNPs: 2108 (100.00%) 408s Chromosome: 1 408s Segmenting DH signals... 408s Segmenting by CBS... 408s Chromosome: 1 408s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 408s Segmenting by CBS...done 408s List of 4 408s $ data :'data.frame': 7586 obs. of 4 variables: 408s ..$ chromosome: int [1:7586] 1 1 1 1 1 1 1 1 1 1 ... 408s ..$ x : num [1:7586] 554484 730720 782343 878522 916294 ... 408s ..$ y : num [1:7586] NA NA NA NA NA ... 408s ..$ index : int [1:7586] 1 2 3 4 5 6 7 8 9 10 ... 408s $ output :'data.frame': 1 obs. of 6 variables: 408s ..$ sampleName: chr NA 408s ..$ chromosome: int 1 408s ..$ start : num 554484 408s ..$ end : num 1.21e+08 408s ..$ nbrOfLoci : int 2108 408s ..$ mean : num 0.512 408s $ segRows:'data.frame': 1 obs. of 2 variables: 408s ..$ startRow: int 10 408s ..$ endRow : int 7574 408s $ params :List of 5 408s ..$ alpha : num 0.001 408s ..$ undo : num 0 408s ..$ joinSegments : logi TRUE 408s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 408s .. ..$ chromosome: int 1 408s .. ..$ start : num 554484 408s .. ..$ end : num 1.21e+08 408s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 408s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 408s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.037 0 0.037 0 0 408s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 408s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 408s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 408s DH segmentation (locally-indexed) rows: 408s startRow endRow 408s 1 10 7574 408s int [1:7586] 1 2 3 4 5 6 7 8 9 10 ... 408s DH segmentation rows: 408s startRow endRow 408s 1 10 7574 408s Segmenting DH signals...done 408s DH segmentation table: 408s dhStart dhEnd dhNbrOfLoci dhMean 408s 1 554484 120908858 2108 0.5116 408s startRow endRow 408s 1 10 7574 408s Rows: 408s [1] 1 408s TCN segmentation rows: 408s startRow endRow 408s 1 1 7586 408s TCN and DH segmentation rows: 408s startRow endRow 408s 1 1 7586 408s startRow endRow 408s 1 10 7574 408s NULL 408s TCN segmentation (expanded) rows: 408s startRow endRow 408s 1 1 7586 408s TCN and DH segmentation rows: 408s startRow endRow 408s 1 1 7586 408s 2 NA NA 408s 3 7587 10267 408s 4 10268 14658 408s startRow endRow 408s 1 10 7574 408s startRow endRow 408s 1 1 7586 408s Total CN segmentation table (expanded): 408s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 408s 1 1 554484 120908858 7586 1.3853 2108 2108 408s (TCN,DH) segmentation for one total CN segment: 408s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 408s 1 1 1 1 554484 120908858 7586 1.3853 2108 408s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 408s 1 2108 554484 120908858 2108 0.5116 408s Total CN segment #1 ([ 554484,1.20909e+08]) of 4...done 408s Total CN segment #2 ([1.20909e+08,1.42694e+08]) of 4... 408s Number of TCN loci in segment: 0 408s Locus data for TCN segment: 408s 'data.frame': 0 obs. of 9 variables: 408s $ chromosome: int 408s $ x : num 408s $ CT : num 408s $ betaT : num 408s $ betaTN : num 408s $ betaN : num 408s $ muN : num 408s $ index : int 408s $ rho : num 408s Number of loci: 0 408s Number of SNPs: 0 (NaN%) 408s Number of heterozygous SNPs: 0 (NaN%) 408s Chromosome: 1 408s Segmenting DH signals... 408s Segmenting by CBS... 408s Chromosome: NA 408s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 408s Segmenting by CBS...done 408s List of 4 408s $ data :'data.frame': 0 obs. of 4 variables: 408s ..$ chromosome: int(0) 408s ..$ x : num(0) 408s ..$ y : num(0) 408s ..$ index : int(0) 408s $ output :'data.frame': 0 obs. of 6 variables: 408s ..$ sampleName: chr(0) 408s ..$ chromosome: num(0) 408s ..$ start : num(0) 408s ..$ end : num(0) 408s ..$ nbrOfLoci : int(0) 408s ..$ mean : num(0) 408s $ segRows:'data.frame': 0 obs. of 2 variables: 408s ..$ startRow: int(0) 408s ..$ endRow : int(0) 408s $ params :List of 5 408s ..$ alpha : num 0.001 408s ..$ undo : num 0 408s ..$ joinSegments : logi TRUE 408s ..$ knownSegments:'data.frame': 0 obs. of 3 variables: 408s .. ..$ chromosome: int(0) 408s .. ..$ start : num(0) 408s .. ..$ end : num(0) 408s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 408s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 408s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.001 0 0.002 0 0 408s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 408s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 408s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 408s DH segmentation (locally-indexed) rows: 408s [1] startRow endRow 408s <0 rows> (or 0-length row.names) 408s int(0) 408s DH segmentation rows: 408s [1] startRow endRow 408s <0 rows> (or 0-length row.names) 408s Segmenting DH signals...done 408s DH segmentation table: 408s dhStart dhEnd dhNbrOfLoci dhMean 408s NA NA NA NA NA 408s startRow endRow 408s NA NA NA 408s Rows: 408s [1] 2 408s TCN segmentation rows: 408s startRow endRow 408s 2 NA NA 408s TCN and DH segmentation rows: 408s startRow endRow 408s 2 NA NA 408s startRow endRow 408s NA NA NA 408s startRow endRow 408s 1 1 7586 408s TCN segmentation (expanded) rows: 408s startRow endRow 408s 1 1 7586 408s 2 NA NA 408s TCN and DH segmentation rows: 408s startRow endRow 408s 1 1 7586 408s 2 NA NA 408s 3 7587 10267 408s 4 10268 14658 408s startRow endRow 408s 1 10 7574 408s 2 NA NA 408s startRow endRow 408s 1 1 7586 408s 2 NA NA 408s Total CN segmentation table (expanded): 408s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 408s 2 1 120908859 142693887 0 NA 0 0 408s (TCN,DH) segmentation for one total CN segment: 408s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 408s 2 2 1 1 120908859 142693887 0 NA 0 408s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 408s 2 0 NA NA NA NA 408s Total CN segment #2 ([1.20909e+08,1.42694e+08]) of 4...done 408s Total CN segment #3 ([1.42694e+08,1.8545e+08]) of 4... 408s Number of TCN loci in segment: 2681 408s Locus data for TCN segment: 408s 'data.frame': 2681 obs. of 9 variables: 408s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 408s $ x : num 1.43e+08 1.43e+08 1.43e+08 1.43e+08 1.44e+08 ... 408s $ CT : num 2.27 1.55 1.47 1.5 1.81 ... 408s $ betaT : num 0.34 0.55 0.048 0.813 0.575 ... 408s $ betaTN : num 0.441 0.629 -0.05 0.958 0.872 ... 408s $ betaN : num 0.3851 0.3933 0.0981 0.8552 0.7028 ... 408s $ muN : num 0.5 0.5 0 1 1 1 1 0.5 1 1 ... 408s $ index : int 7587 7588 7589 7590 7591 7592 7593 7594 7595 7596 ... 408s $ rho : num 0.117 0.258 NA NA NA ... 408s Number of loci: 2681 408s Number of SNPs: 777 (28.98%) 408s Number of heterozygous SNPs: 777 (100.00%) 408s Chromosome: 1 408s Segmenting DH signals... 408s Segmenting by CBS... 408s Chromosome: 1 408s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 408s Segmenting by CBS...done 408s List of 4 408s $ data :'data.frame': 2681 obs. of 4 variables: 408s ..$ chromosome: int [1:2681] 1 1 1 1 1 1 1 1 1 1 ... 408s ..$ x : num [1:2681] 1.43e+08 1.43e+08 1.43e+08 1.43e+08 1.44e+08 ... 408s ..$ y : num [1:2681] 0.117 0.258 NA NA NA ... 408s ..$ index : int [1:2681] 1 2 3 4 5 6 7 8 9 10 ... 408s $ output :'data.frame': 1 obs. of 6 variables: 408s ..$ sampleName: chr NA 408s ..$ chromosome: int 1 408s ..$ start : num 1.43e+08 408s ..$ end : num 1.85e+08 408s ..$ nbrOfLoci : int 777 408s ..$ mean : num 0.0973 408s $ segRows:'data.frame': 1 obs. of 2 variables: 408s ..$ startRow: int 1 408s ..$ endRow : int 2677 408s $ params :List of 5 408s ..$ alpha : num 0.001 408s ..$ undo : num 0 408s ..$ joinSegments : logi TRUE 408s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 408s .. ..$ chromosome: int 1 408s .. ..$ start : num 1.43e+08 408s .. ..$ end : num 1.85e+08 408s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 408s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 408s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.008 0 0.009 0 0 408s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 408s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 408s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 408s DH segmentation (locally-indexed) rows: 408s startRow endRow 408s 1 1 2677 408s int [1:2681] 7587 7588 7589 7590 7591 7592 7593 7594 7595 7596 ... 408s DH segmentation rows: 408s startRow endRow 408s 1 7587 10263 408s Segmenting DH signals...done 408s DH segmentation table: 408s dhStart dhEnd dhNbrOfLoci dhMean 408s 1 142693888 185449813 777 0.0973 408s startRow endRow 408s 1 7587 10263 408s Rows: 408s [1] 3 408s TCN segmentation rows: 408s startRow endRow 408s 3 7587 10267 408s TCN and DH segmentation rows: 408s startRow endRow 408s 3 7587 10267 408s startRow endRow 408s 1 7587 10263 408s startRow endRow 408s 1 1 7586 408s 2 NA NA 408s TCN segmentation (expanded) rows: 408s startRow endRow 408s 1 1 7586 408s 2 NA NA 408s 3 7587 10267 408s TCN and DH segmentation rows: 408s startRow endRow 408s 1 1 7586 408s 2 NA NA 408s 3 7587 10267 408s 4 10268 14658 408s startRow endRow 408s 1 10 7574 408s 2 NA NA 408s 3 7587 10263 408s startRow endRow 408s 1 1 7586 408s 2 NA NA 408s 3 7587 10267 408s Total CN segmentation table (expanded): 408s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 408s 3 1 142693888 185449813 2681 2.0689 777 777 408s (TCN,DH) segmentation for one total CN segment: 408s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 408s 3 3 1 1 142693888 185449813 2681 2.0689 777 408s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 408s 3 777 142693888 185449813 777 0.0973 408s Total CN segment #3 ([1.42694e+08,1.8545e+08]) of 4...done 408s Total CN segment #4 ([1.8545e+08,2.47137e+08]) of 4... 408s Number of TCN loci in segment: 4391 408s Locus data for TCN segment: 408s 'data.frame': 4391 obs. of 9 variables: 408s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 408s $ x : num 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 408s $ CT : num 2.93 2.15 2.82 2.93 2.46 ... 408s $ betaT : num 0.0811 0.5154 0.9473 0.3734 0.7506 ... 408s $ betaTN : num -0.169 0.609 1.028 0.525 0.968 ... 408s $ betaN : num 0.25 0.38 0.919 0.34 0.783 ... 408s $ muN : num 0 0.5 1 0.5 1 1 0 1 0 1 ... 408s $ index : int 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 408s $ rho : num NA 0.2186 NA 0.0503 NA ... 408s Number of loci: 4391 408s Number of SNPs: 1311 (29.86%) 408s Number of heterozygous SNPs: 1311 (100.00%) 408s Chromosome: 1 408s Segmenting DH signals... 408s Segmenting by CBS... 408s Chromosome: 1 408s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 408s Segmenting by CBS...done 408s List of 4 408s $ data :'data.frame': 4391 obs. of 4 variables: 408s ..$ chromosome: int [1:4391] 1 1 1 1 1 1 1 1 1 1 ... 408s ..$ x : num [1:4391] 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 408s ..$ y : num [1:4391] NA 0.2186 NA 0.0503 NA ... 408s ..$ index : int [1:4391] 1 2 3 4 5 6 7 8 9 10 ... 408s $ output :'data.frame': 1 obs. of 6 variables: 408s ..$ sampleName: chr NA 408s ..$ chromosome: int 1 408s ..$ start : num 1.85e+08 408s ..$ end : num 2.47e+08 408s ..$ nbrOfLoci : int 1311 408s ..$ mean : num 0.23 408s $ segRows:'data.frame': 1 obs. of 2 variables: 408s ..$ startRow: int 2 408s ..$ endRow : int 4388 408s $ params :List of 5 408s ..$ alpha : num 0.001 408s ..$ undo : num 0 408s ..$ joinSegments : logi TRUE 408s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 408s .. ..$ chromosome: int 1 408s .. ..$ start : num 1.85e+08 408s .. ..$ end : num 2.47e+08 408s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 408s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 408s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.015 0 0.015 0 0 408s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 408s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 408s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 408s DH segmentation (locally-indexed) rows: 408s startRow endRow 408s 1 2 4388 408s int [1:4391] 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 408s DH segmentation rows: 408s startRow endRow 408s 1 10269 14655 408s Segmenting DH signals...done 408s DH segmentation table: 408s dhStart dhEnd dhNbrOfLoci dhMean 408s 1 185449813 247137334 1311 0.2295 408s startRow endRow 408s 1 10269 14655 408s Rows: 408s [1] 4 408s TCN segmentation rows: 408s startRow endRow 408s 4 10268 14658 408s TCN and DH segmentation rows: 408s startRow endRow 408s 4 10268 14658 408s startRow endRow 408s 1 10269 14655 408s startRow endRow 408s 1 1 7586 408s 2 NA NA 408s 3 7587 10267 408s TCN segmentation (expanded) rows: 408s startRow endRow 408s 1 1 7586 408s 2 NA NA 408s 3 7587 10267 408s 4 10268 14658 408s TCN and DH segmentation rows: 408s startRow endRow 408s 1 1 7586 408s 2 NA NA 408s 3 7587 10267 408s 4 10268 14658 408s startRow endRow 408s 1 10 7574 408s 2 NA NA 408s 3 7587 10263 408s 4 10269 14655 408s startRow endRow 408s 1 1 7586 408s 2 NA NA 408s 3 7587 10267 408s 4 10268 14658 408s Total CN segmentation table (expanded): 408s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 408s 4 1 185449813 247137334 4391 2.6341 1311 1311 408s (TCN,DH) segmentation for one total CN segment: 408s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 408s 4 4 1 1 185449813 247137334 4391 2.6341 1311 408s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 408s 4 1311 185449813 247137334 1311 0.2295 408s Total CN segment #4 ([1.8545e+08,2.47137e+08]) of 4...done 408s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 408s 1 1 1 1 554484 120908858 7586 1.3853 2108 408s 2 1 2 1 120908859 142693887 0 NA 0 408s 3 1 3 1 142693888 185449813 2681 2.0689 777 408s 4 1 4 1 185449813 247137334 4391 2.6341 1311 408s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 408s 1 2108 554484 120908858 2108 0.5116 408s 2 0 NA NA NA NA 408s 3 777 142693888 185449813 777 0.0973 408s 4 1311 185449813 247137334 1311 0.2295 408s Calculating (C1,C2) per segment... 408s Calculating (C1,C2) per segment...done 408s Number of segments: 4 408s Segmenting paired tumor-normal signals using Paired PSCBS...done 408s Post-segmenting TCNs... 408s Number of segments: 4 408s Number of chromosomes: 1 408s [1] 1 408s Chromosome 1 ('chr01') of 1... 408s Rows: 408s [1] 1 2 3 4 408s Number of segments: 4 408s TCN segment #1 ('1') of 4... 408s Nothing todo. Only one DH segmentation. Skipping. 408s TCN segment #1 ('1') of 4...done 408s TCN segment #2 ('2') of 4... 408s Nothing todo. Only one DH segmentation. Skipping. 408s TCN segment #2 ('2') of 4...done 408s TCN segment #3 ('3') of 4... 408s Nothing todo. Only one DH segmentation. Skipping. 408s TCN segment #3 ('3') of 4...done 408s TCN segment #4 ('4') of 4... 408s Nothing todo. Only one DH segmentation. Skipping. 408s TCN segment #4 ('4') of 4...done 408s Chromosome 1 ('chr01') of 1...done 408s Update (C1,C2) per segment... 408s Update (C1,C2) per segment...done 408s Post-segmenting TCNs...done 408s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 408s 1 1 1 1 554484 120908858 7586 1.3853 2108 408s 2 1 2 1 120908859 142693887 0 NA 0 408s 3 1 3 1 142693888 185449813 2681 2.0689 777 408s 4 1 4 1 185449813 247137334 4391 2.6341 1311 408s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 408s 1 2108 554484 120908858 2108 0.5116 0.3382903 1.047010 408s 2 0 NA NA NA NA NA NA 408s 3 777 142693888 185449813 777 0.0973 0.9337980 1.135102 408s 4 1311 185449813 247137334 1311 0.2295 1.0147870 1.619313 408s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 408s 1 1 1 1 554484 120908858 7586 1.3853 2108 408s 2 1 2 1 120908859 142693887 0 NA 0 408s 3 1 3 1 142693888 185449813 2681 2.0689 777 408s 4 1 4 1 185449813 247137334 4391 2.6341 1311 408s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 408s 1 2108 554484 120908858 2108 0.5116 0.3382903 1.047010 408s 2 0 NA NA NA NA NA NA 408s 3 777 142693888 185449813 777 0.0973 0.9337980 1.135102 408s 4 1311 185449813 247137334 1311 0.2295 1.0147870 1.619313 408s - segmentByPairedPSCBS() w/ known segments using 'multisession' futures ... 408s Segmenting paired tumor-normal signals using Paired PSCBS... 408s Calling genotypes from normal allele B fractions... 408s num [1:14670] 0.8274 0.5072 0.1671 0.1609 0.0421 ... 408s Called genotypes: 408s num [1:14670] 1 0.5 0 0 0 0 1 0 1 0.5 ... 408s - attr(*, "modelFit")=List of 1 408s ..$ :List of 7 408s .. ..$ flavor : chr "density" 408s .. ..$ cn : int 2 408s .. ..$ nbrOfGenotypeGroups: int 3 408s .. ..$ tau : num [1:2] 0.315 0.677 408s .. ..$ n : int 14640 408s .. ..$ fit :Classes 'PeaksAndValleys' and 'data.frame': 5 obs. of 3 variables: 408s .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 408s .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 408s .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 408s .. ..$ fitValleys :Classes 'PeaksAndValleys' and 'data.frame': 2 obs. of 3 variables: 408s .. .. ..$ type : chr [1:2] "valley" "valley" 408s .. .. ..$ x : num [1:2] 0.315 0.677 408s .. .. ..$ density: num [1:2] 0.522 0.551 408s ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 408s muN 408s 0 0.5 1 408s 5221 4198 5251 408s Calling genotypes from normal allele B fractions...done 408s Normalizing betaT using betaN (TumorBoost)... 408s Normalized BAFs: 408s num [1:14670] 0.9301 0.1667 0.0685 0.0995 0.0155 ... 408s - attr(*, "modelFit")=List of 5 408s ..$ method : chr "normalizeTumorBoost" 408s ..$ flavor : chr "v4" 408s ..$ delta : num [1:14670] -0.17264 0.00239 0.1671 0.16085 0.04213 ... 408s .. ..- attr(*, "modelFit")=List of 1 408s .. .. ..$ :List of 7 408s .. .. .. ..$ flavor : chr "density" 408s .. .. .. ..$ cn : int 2 408s .. .. .. ..$ nbrOfGenotypeGroups: int 3 408s .. .. .. ..$ tau : num [1:2] 0.315 0.677 408s .. .. .. ..$ n : int 14640 408s .. .. .. ..$ fit :Classes 'PeaksAndValleys' and 'data.frame': 5 obs. of 3 variables: 408s .. .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 408s .. .. .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 408s .. .. .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 408s .. .. .. ..$ fitValleys :Classes 'PeaksAndValleys' and 'data.frame': 2 obs. of 3 variables: 408s .. .. .. .. ..$ type : chr [1:2] "valley" "valley" 408s .. .. .. .. ..$ x : num [1:2] 0.315 0.677 408s .. .. .. .. ..$ density: num [1:2] 0.522 0.551 408s .. .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 408s ..$ preserveScale: logi FALSE 408s ..$ scaleFactor : num NA 408s Normalizing betaT using betaN (TumorBoost)...done 408s Setup up data... 408s 'data.frame': 14670 obs. of 7 variables: 408s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 408s $ x : num 1145994 2941694 3710825 4240737 4276892 ... 408s $ CT : num 1.63 1.4 1.41 1.17 1.16 ... 408s $ betaT : num 0.7574 0.169 0.2357 0.2604 0.0576 ... 408s $ betaTN : num 0.9301 0.1667 0.0685 0.0995 0.0155 ... 408s ..- attr(*, "modelFit")=List of 5 408s .. ..$ method : chr "normalizeTumorBoost" 408s .. ..$ flavor : chr "v4" 408s .. ..$ delta : num [1:14670] -0.17264 0.00239 0.1671 0.16085 0.04213 ... 408s .. .. ..- attr(*, "modelFit")=List of 1 408s .. .. .. ..$ :List of 7 408s .. .. .. .. ..$ flavor : chr "density" 408s .. .. .. .. ..$ cn : int 2 408s .. .. .. .. ..$ nbrOfGenotypeGroups: int 3 408s .. .. .. .. ..$ tau : num [1:2] 0.315 0.677 408s .. .. .. .. ..$ n : int 14640 408s .. .. .. .. ..$ fit :Classes 'PeaksAndValleys' and 'data.frame': 5 obs. of 3 variables: 408s .. .. .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 408s .. .. .. .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 408s .. .. .. .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 408s .. .. .. .. ..$ fitValleys :Classes 'PeaksAndValleys' and 'data.frame': 2 obs. of 3 variables: 408s .. .. .. .. .. ..$ type : chr [1:2] "valley" "valley" 408s .. .. .. .. .. ..$ x : num [1:2] 0.315 0.677 408s .. .. .. .. .. ..$ density: num [1:2] 0.522 0.551 408s .. .. .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 408s .. ..$ preserveScale: logi FALSE 408s .. ..$ scaleFactor : num NA 408s $ betaN : num 0.8274 0.5072 0.1671 0.1609 0.0421 ... 408s $ muN : num 1 0.5 0 0 0 0 1 0 1 0.5 ... 408s ..- attr(*, "modelFit")=List of 1 408s .. ..$ :List of 7 408s .. .. ..$ flavor : chr "density" 408s .. .. ..$ cn : int 2 408s .. .. ..$ nbrOfGenotypeGroups: int 3 408s .. .. ..$ tau : num [1:2] 0.315 0.677 408s .. .. ..$ n : int 14640 408s .. .. ..$ fit :Classes 'PeaksAndValleys' and 'data.frame': 5 obs. of 3 variables: 408s .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 408s .. .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 408s .. .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 408s .. .. ..$ fitValleys :Classes 'PeaksAndValleys' and 'data.frame': 2 obs. of 3 variables: 408s .. .. .. ..$ type : chr [1:2] "valley" "valley" 408s .. .. .. ..$ x : num [1:2] 0.315 0.677 408s .. .. .. ..$ density: num [1:2] 0.522 0.551 408s .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 408s Setup up data...done 408s Dropping loci for which TCNs are missing... 408s Number of loci dropped: 12 408s Dropping loci for which TCNs are missing...done 408s Ordering data along genome... 408s 'data.frame': 14658 obs. of 7 variables: 408s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 408s $ x : num 554484 730720 782343 878522 916294 ... 408s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 408s $ betaT : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 408s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 408s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 408s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 408s Ordering data along genome...done 408s Keeping only current chromosome for 'knownSegments'... 408s Chromosome: 1 408s Known segments for this chromosome: 408s chromosome start end length 408s 1 1 -Inf 120908858 Inf 408s 2 1 120908859 142693887 21785028 408s 3 1 142693888 Inf Inf 408s Keeping only current chromosome for 'knownSegments'...done 408s alphaTCN: 0.009 408s alphaDH: 0.001 408s Number of loci: 14658 408s Calculating DHs... 408s Number of SNPs: 14658 408s Number of heterozygous SNPs: 4196 (28.63%) 408s Normalized DHs: 408s num [1:14658] NA NA NA NA NA ... 408s Calculating DHs...done 408s Random seed temporarily set (seed=c(48879), kind="L'Ecuyer-CMRG") 408s Produced 2 seeds from this stream for future usage 408s Identification of change points by total copy numbers... 408s Segmenting by CBS... 408s Chromosome: 1 408s Random seed temporarily set (seed=c(10407, 1066287653, -51199871, 161854402, -1995183193, 1503453565, -747102133), kind="L'Ecuyer-CMRG") 408s Produced 3 seeds from this stream for future usage 408s Segmenting by CBS...done 408s List of 4 408s $ data :'data.frame': 14658 obs. of 4 variables: 408s ..$ chromosome: int [1:14658] 1 1 1 1 1 1 1 1 1 1 ... 408s ..$ x : num [1:14658] 554484 730720 782343 878522 916294 ... 408s ..$ y : num [1:14658] 1.88 1.8 1.59 1.64 1.53 ... 408s ..$ index : int [1:14658] 1 2 3 4 5 6 7 8 9 10 ... 408s $ output :'data.frame': 4 obs. of 6 variables: 408s ..$ sampleName: chr [1:4] NA NA NA NA 408s ..$ chromosome: int [1:4] 1 1 1 1 408s ..$ start : num [1:4] 5.54e+05 1.21e+08 1.43e+08 1.85e+08 408s ..$ end : num [1:4] 1.21e+08 1.43e+08 1.85e+08 2.47e+08 408s ..$ nbrOfLoci : int [1:4] 7586 0 2681 4391 408s ..$ mean : num [1:4] 1.39 NA 2.07 2.63 408s $ segRows:'data.frame': 4 obs. of 2 variables: 408s ..$ startRow: int [1:4] 1 NA 7587 10268 408s ..$ endRow : int [1:4] 7586 NA 10267 14658 408s $ params :List of 5 408s ..$ alpha : num 0.009 408s ..$ undo : num 0 408s ..$ joinSegments : logi TRUE 408s ..$ knownSegments:'data.frame': 4 obs. of 3 variables: 408s .. ..$ chromosome: int [1:4] 1 1 2 1 408s .. ..$ start : num [1:4] -Inf -Inf -Inf 1.43e+08 408s .. ..$ end : num [1:4] 1.21e+08 Inf Inf Inf 408s ..$ seed : int [1:7] 10407 1066287653 -51199871 161854402 -1995183193 1503453565 -747102133 408s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 408s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.133 0.001 0.134 0 0 408s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 408s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 408s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 408s Identification of change points by total copy numbers...done 408s Restructure TCN segmentation results... 408s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean 408s 1 1 554484 120908858 7586 1.3853 408s 2 1 120908859 142693887 0 NA 408s 3 1 142693888 185449813 2681 2.0689 408s 4 1 185449813 247137334 4391 2.6341 408s Number of TCN segments: 4 408s Restructure TCN segmentation results...done 408s Total CN segment #1 ([ 554484,1.20909e+08]) of 4... 408s Number of TCN loci in segment: 7586 408s Locus data for TCN segment: 408s 'data.frame': 7586 obs. of 9 variables: 408s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 408s $ x : num 554484 730720 782343 878522 916294 ... 408s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 408s $ betaT : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 408s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 408s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 408s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 408s $ index : int 1 2 3 4 5 6 7 8 9 10 ... 408s $ rho : num NA NA NA NA NA ... 408s Number of loci: 7586 408s Number of SNPs: 2108 (27.79%) 408s Number of heterozygous SNPs: 2108 (100.00%) 408s Chromosome: 1 408s Segmenting DH signals... 408s Segmenting by CBS... 408s Chromosome: 1 408s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 408s Segmenting by CBS...done 408s List of 4 408s $ data :'data.frame': 7586 obs. of 4 variables: 408s ..$ chromosome: int [1:7586] 1 1 1 1 1 1 1 1 1 1 ... 408s ..$ x : num [1:7586] 554484 730720 782343 878522 916294 ... 408s ..$ y : num [1:7586] NA NA NA NA NA ... 408s ..$ index : int [1:7586] 1 2 3 4 5 6 7 8 9 10 ... 408s $ output :'data.frame': 1 obs. of 6 variables: 408s ..$ sampleName: chr NA 408s ..$ chromosome: int 1 408s ..$ start : num 554484 408s ..$ end : num 1.21e+08 408s ..$ nbrOfLoci : int 2108 408s ..$ mean : num 0.512 408s $ segRows:'data.frame': 1 obs. of 2 variables: 408s ..$ startRow: int 10 408s ..$ endRow : int 7574 408s $ params :List of 5 408s ..$ alpha : num 0.001 408s ..$ undo : num 0 408s ..$ joinSegments : logi TRUE 408s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 408s .. ..$ chromosome: int 1 408s .. ..$ start : num 554484 408s .. ..$ end : num 1.21e+08 408s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 408s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 408s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.037 0 0.037 0 0 408s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 408s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 408s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 408s DH segmentation (locally-indexed) rows: 408s startRow endRow 408s 1 10 7574 408s int [1:7586] 1 2 3 4 5 6 7 8 9 10 ... 408s DH segmentation rows: 408s startRow endRow 408s 1 10 7574 408s Segmenting DH signals...done 408s DH segmentation table: 408s dhStart dhEnd dhNbrOfLoci dhMean 408s 1 554484 120908858 2108 0.5116 408s startRow endRow 408s 1 10 7574 408s Rows: 408s [1] 1 408s TCN segmentation rows: 408s startRow endRow 408s 1 1 7586 408s TCN and DH segmentation rows: 408s startRow endRow 408s 1 1 7586 408s startRow endRow 408s 1 10 7574 408s NULL 408s TCN segmentation (expanded) rows: 408s startRow endRow 408s 1 1 7586 408s TCN and DH segmentation rows: 408s startRow endRow 408s 1 1 7586 408s 2 NA NA 408s 3 7587 10267 408s 4 10268 14658 408s startRow endRow 408s 1 10 7574 408s startRow endRow 408s 1 1 7586 408s Total CN segmentation table (expanded): 408s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 408s 1 1 554484 120908858 7586 1.3853 2108 2108 408s (TCN,DH) segmentation for one total CN segment: 408s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 408s 1 1 1 1 554484 120908858 7586 1.3853 2108 408s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 408s 1 2108 554484 120908858 2108 0.5116 408s Total CN segment #1 ([ 554484,1.20909e+08]) of 4...done 408s Total CN segment #2 ([1.20909e+08,1.42694e+08]) of 4... 408s Number of TCN loci in segment: 0 408s Locus data for TCN segment: 408s 'data.frame': 0 obs. of 9 variables: 408s $ chromosome: int 408s $ x : num 408s $ CT : num 408s $ betaT : num 408s $ betaTN : num 408s $ betaN : num 408s $ muN : num 408s $ index : int 408s $ rho : num 408s Number of loci: 0 408s Number of SNPs: 0 (NaN%) 408s Number of heterozygous SNPs: 0 (NaN%) 408s Chromosome: 1 408s Segmenting DH signals... 408s Segmenting by CBS... 408s Chromosome: NA 408s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 408s Segmenting by CBS...done 408s List of 4 408s $ data :'data.frame': 0 obs. of 4 variables: 408s ..$ chromosome: int(0) 408s ..$ x : num(0) 408s ..$ y : num(0) 408s ..$ index : int(0) 408s $ output :'data.frame': 0 obs. of 6 variables: 408s ..$ sampleName: chr(0) 408s ..$ chromosome: num(0) 408s ..$ start : num(0) 408s ..$ end : num(0) 408s ..$ nbrOfLoci : int(0) 408s ..$ mean : num(0) 408s $ segRows:'data.frame': 0 obs. of 2 variables: 408s ..$ startRow: int(0) 408s ..$ endRow : int(0) 408s $ params :List of 5 408s ..$ alpha : num 0.001 408s ..$ undo : num 0 408s ..$ joinSegments : logi TRUE 408s ..$ knownSegments:'data.frame': 0 obs. of 3 variables: 408s .. ..$ chromosome: int(0) 408s .. ..$ start : num(0) 408s .. ..$ end : num(0) 408s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 408s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 408s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.002 0 0.002 0 0 408s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 408s - attr(*, "pkgDeta+ [ 0 != 0 ] 408s + echo Test segmentByPairedPSCBS,futures passed 408s + echo 0 408s + echo Begin test segmentByPairedPSCBS,noNormalBAFs 408s + exitcode=0 408s + R CMD BATCH segmentByPairedPSCBS,noNormalBAFs.R 408s ils")= chr "DNAcopy v1.80.0" 408s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 408s DH segmentation (locally-indexed) rows: 408s [1] startRow endRow 408s <0 rows> (or 0-length row.names) 408s int(0) 408s DH segmentation rows: 408s [1] startRow endRow 408s <0 rows> (or 0-length row.names) 408s Segmenting DH signals...done 408s DH segmentation table: 408s dhStart dhEnd dhNbrOfLoci dhMean 408s NA NA NA NA NA 408s startRow endRow 408s NA NA NA 408s Rows: 408s [1] 2 408s TCN segmentation rows: 408s startRow endRow 408s 2 NA NA 408s TCN and DH segmentation rows: 408s startRow endRow 408s 2 NA NA 408s startRow endRow 408s NA NA NA 408s startRow endRow 408s 1 1 7586 408s TCN segmentation (expanded) rows: 408s startRow endRow 408s 1 1 7586 408s 2 NA NA 408s TCN and DH segmentation rows: 408s startRow endRow 408s 1 1 7586 408s 2 NA NA 408s 3 7587 10267 408s 4 10268 14658 408s startRow endRow 408s 1 10 7574 408s 2 NA NA 408s startRow endRow 408s 1 1 7586 408s 2 NA NA 408s Total CN segmentation table (expanded): 408s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 408s 2 1 120908859 142693887 0 NA 0 0 408s (TCN,DH) segmentation for one total CN segment: 408s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 408s 2 2 1 1 120908859 142693887 0 NA 0 408s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 408s 2 0 NA NA NA NA 408s Total CN segment #2 ([1.20909e+08,1.42694e+08]) of 4...done 408s Total CN segment #3 ([1.42694e+08,1.8545e+08]) of 4... 408s Number of TCN loci in segment: 2681 408s Locus data for TCN segment: 408s 'data.frame': 2681 obs. of 9 variables: 408s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 408s $ x : num 1.43e+08 1.43e+08 1.43e+08 1.43e+08 1.44e+08 ... 408s $ CT : num 2.27 1.55 1.47 1.5 1.81 ... 408s $ betaT : num 0.34 0.55 0.048 0.813 0.575 ... 408s $ betaTN : num 0.441 0.629 -0.05 0.958 0.872 ... 408s $ betaN : num 0.3851 0.3933 0.0981 0.8552 0.7028 ... 408s $ muN : num 0.5 0.5 0 1 1 1 1 0.5 1 1 ... 408s $ index : int 7587 7588 7589 7590 7591 7592 7593 7594 7595 7596 ... 408s $ rho : num 0.117 0.258 NA NA NA ... 408s Number of loci: 2681 408s Number of SNPs: 777 (28.98%) 408s Number of heterozygous SNPs: 777 (100.00%) 408s Chromosome: 1 408s Segmenting DH signals... 408s Segmenting by CBS... 408s Chromosome: 1 408s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 408s Segmenting by CBS...done 408s List of 4 408s $ data :'data.frame': 2681 obs. of 4 variables: 408s ..$ chromosome: int [1:2681] 1 1 1 1 1 1 1 1 1 1 ... 408s ..$ x : num [1:2681] 1.43e+08 1.43e+08 1.43e+08 1.43e+08 1.44e+08 ... 408s ..$ y : num [1:2681] 0.117 0.258 NA NA NA ... 408s ..$ index : int [1:2681] 1 2 3 4 5 6 7 8 9 10 ... 408s $ output :'data.frame': 1 obs. of 6 variables: 408s ..$ sampleName: chr NA 408s ..$ chromosome: int 1 408s ..$ start : num 1.43e+08 408s ..$ end : num 1.85e+08 408s ..$ nbrOfLoci : int 777 408s ..$ mean : num 0.0973 408s $ segRows:'data.frame': 1 obs. of 2 variables: 408s ..$ startRow: int 1 408s ..$ endRow : int 2677 408s $ params :List of 5 408s ..$ alpha : num 0.001 408s ..$ undo : num 0 408s ..$ joinSegments : logi TRUE 408s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 408s .. ..$ chromosome: int 1 408s .. ..$ start : num 1.43e+08 408s .. ..$ end : num 1.85e+08 408s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 408s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 408s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.008 0 0.008 0 0 408s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 408s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 408s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 408s DH segmentation (locally-indexed) rows: 408s startRow endRow 408s 1 1 2677 408s int [1:2681] 7587 7588 7589 7590 7591 7592 7593 7594 7595 7596 ... 408s DH segmentation rows: 408s startRow endRow 408s 1 7587 10263 408s Segmenting DH signals...done 408s DH segmentation table: 408s dhStart dhEnd dhNbrOfLoci dhMean 408s 1 142693888 185449813 777 0.0973 408s startRow endRow 408s 1 7587 10263 408s Rows: 408s [1] 3 408s TCN segmentation rows: 408s startRow endRow 408s 3 7587 10267 408s TCN and DH segmentation rows: 408s startRow endRow 408s 3 7587 10267 408s startRow endRow 408s 1 7587 10263 408s startRow endRow 408s 1 1 7586 408s 2 NA NA 408s TCN segmentation (expanded) rows: 408s startRow endRow 408s 1 1 7586 408s 2 NA NA 408s 3 7587 10267 408s TCN and DH segmentation rows: 408s startRow endRow 408s 1 1 7586 408s 2 NA NA 408s 3 7587 10267 408s 4 10268 14658 408s startRow endRow 408s 1 10 7574 408s 2 NA NA 408s 3 7587 10263 408s startRow endRow 408s 1 1 7586 408s 2 NA NA 408s 3 7587 10267 408s Total CN segmentation table (expanded): 408s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 408s 3 1 142693888 185449813 2681 2.0689 777 777 408s (TCN,DH) segmentation for one total CN segment: 408s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 408s 3 3 1 1 142693888 185449813 2681 2.0689 777 408s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 408s 3 777 142693888 185449813 777 0.0973 408s Total CN segment #3 ([1.42694e+08,1.8545e+08]) of 4...done 408s Total CN segment #4 ([1.8545e+08,2.47137e+08]) of 4... 408s Number of TCN loci in segment: 4391 408s Locus data for TCN segment: 408s 'data.frame': 4391 obs. of 9 variables: 408s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 408s $ x : num 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 408s $ CT : num 2.93 2.15 2.82 2.93 2.46 ... 408s $ betaT : num 0.0811 0.5154 0.9473 0.3734 0.7506 ... 408s $ betaTN : num -0.169 0.609 1.028 0.525 0.968 ... 408s $ betaN : num 0.25 0.38 0.919 0.34 0.783 ... 408s $ muN : num 0 0.5 1 0.5 1 1 0 1 0 1 ... 408s $ index : int 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 408s $ rho : num NA 0.2186 NA 0.0503 NA ... 408s Number of loci: 4391 408s Number of SNPs: 1311 (29.86%) 408s Number of heterozygous SNPs: 1311 (100.00%) 408s Chromosome: 1 408s Segmenting DH signals... 408s Segmenting by CBS... 408s Chromosome: 1 408s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 408s Segmenting by CBS...done 408s List of 4 408s $ data :'data.frame': 4391 obs. of 4 variables: 408s ..$ chromosome: int [1:4391] 1 1 1 1 1 1 1 1 1 1 ... 408s ..$ x : num [1:4391] 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 408s ..$ y : num [1:4391] NA 0.2186 NA 0.0503 NA ... 408s ..$ index : int [1:4391] 1 2 3 4 5 6 7 8 9 10 ... 408s $ output :'data.frame': 1 obs. of 6 variables: 408s ..$ sampleName: chr NA 408s ..$ chromosome: int 1 408s ..$ start : num 1.85e+08 408s ..$ end : num 2.47e+08 408s ..$ nbrOfLoci : int 1311 408s ..$ mean : num 0.23 408s $ segRows:'data.frame': 1 obs. of 2 variables: 408s ..$ startRow: int 2 408s ..$ endRow : int 4388 408s $ params :List of 5 408s ..$ alpha : num 0.001 408s ..$ undo : num 0 408s ..$ joinSegments : logi TRUE 408s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 408s .. ..$ chromosome: int 1 408s .. ..$ start : num 1.85e+08 408s .. ..$ end : num 2.47e+08 408s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 408s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 408s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.015 0 0.015 0 0 408s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 408s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 408s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 408s DH segmentation (locally-indexed) rows: 408s startRow endRow 408s 1 2 4388 408s int [1:4391] 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 408s DH segmentation rows: 408s startRow endRow 408s 1 10269 14655 408s Segmenting DH signals...done 408s DH segmentation table: 408s dhStart dhEnd dhNbrOfLoci dhMean 408s 1 185449813 247137334 1311 0.2295 408s startRow endRow 408s 1 10269 14655 408s Rows: 408s [1] 4 408s TCN segmentation rows: 408s startRow endRow 408s 4 10268 14658 408s TCN and DH segmentation rows: 408s startRow endRow 408s 4 10268 14658 408s startRow endRow 408s 1 10269 14655 408s startRow endRow 408s 1 1 7586 408s 2 NA NA 408s 3 7587 10267 408s TCN segmentation (expanded) rows: 408s startRow endRow 408s 1 1 7586 408s 2 NA NA 408s 3 7587 10267 408s 4 10268 14658 408s TCN and DH segmentation rows: 408s startRow endRow 408s 1 1 7586 408s 2 NA NA 408s 3 7587 10267 408s 4 10268 14658 408s startRow endRow 408s 1 10 7574 408s 2 NA NA 408s 3 7587 10263 408s 4 10269 14655 408s startRow endRow 408s 1 1 7586 408s 2 NA NA 408s 3 7587 10267 408s 4 10268 14658 408s Total CN segmentation table (expanded): 408s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 408s 4 1 185449813 247137334 4391 2.6341 1311 1311 408s (TCN,DH) segmentation for one total CN segment: 408s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 408s 4 4 1 1 185449813 247137334 4391 2.6341 1311 408s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 408s 4 1311 185449813 247137334 1311 0.2295 408s Total CN segment #4 ([1.8545e+08,2.47137e+08]) of 4...done 408s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 408s 1 1 1 1 554484 120908858 7586 1.3853 2108 408s 2 1 2 1 120908859 142693887 0 NA 0 408s 3 1 3 1 142693888 185449813 2681 2.0689 777 408s 4 1 4 1 185449813 247137334 4391 2.6341 1311 408s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 408s 1 2108 554484 120908858 2108 0.5116 408s 2 0 NA NA NA NA 408s 3 777 142693888 185449813 777 0.0973 408s 4 1311 185449813 247137334 1311 0.2295 408s Calculating (C1,C2) per segment... 408s Calculating (C1,C2) per segment...done 408s Number of segments: 4 408s Segmenting paired tumor-normal signals using Paired PSCBS...done 408s Post-segmenting TCNs... 408s Number of segments: 4 408s Number of chromosomes: 1 408s [1] 1 408s Chromosome 1 ('chr01') of 1... 408s Rows: 408s [1] 1 2 3 4 408s Number of segments: 4 408s TCN segment #1 ('1') of 4... 408s Nothing todo. Only one DH segmentation. Skipping. 408s TCN segment #1 ('1') of 4...done 408s TCN segment #2 ('2') of 4... 408s Nothing todo. Only one DH segmentation. Skipping. 408s TCN segment #2 ('2') of 4...done 408s TCN segment #3 ('3') of 4... 408s Nothing todo. Only one DH segmentation. Skipping. 408s TCN segment #3 ('3') of 4...done 408s TCN segment #4 ('4') of 4... 408s Nothing todo. Only one DH segmentation. Skipping. 408s TCN segment #4 ('4') of 4...done 408s Chromosome 1 ('chr01') of 1...done 408s Update (C1,C2) per segment... 408s Update (C1,C2) per segment...done 408s Post-segmenting TCNs...done 408s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 408s 1 1 1 1 554484 120908858 7586 1.3853 2108 408s 2 1 2 1 120908859 142693887 0 NA 0 408s 3 1 3 1 142693888 185449813 2681 2.0689 777 408s 4 1 4 1 185449813 247137334 4391 2.6341 1311 408s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 408s 1 2108 554484 120908858 2108 0.5116 0.3382903 1.047010 408s 2 0 NA NA NA NA NA NA 408s 3 777 142693888 185449813 777 0.0973 0.9337980 1.135102 408s 4 1311 185449813 247137334 1311 0.2295 1.0147870 1.619313 408s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 408s 1 1 1 1 554484 120908858 7586 1.3853 2108 408s 2 1 2 1 120908859 142693887 0 NA 0 408s 3 1 3 1 142693888 185449813 2681 2.0689 777 408s 4 1 4 1 185449813 247137334 4391 2.6341 1311 408s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 408s 1 2108 554484 120908858 2108 0.5116 0.3382903 1.047010 408s 2 0 NA NA NA NA NA NA 408s 3 777 142693888 185449813 777 0.0973 0.9337980 1.135102 408s 4 1311 185449813 247137334 1311 0.2295 1.0147870 1.619313 408s > 408s > message("*** segmentByPairedPSCBS() via futures ... DONE") 408s *** segmentByPairedPSCBS() via futures ... DONE 408s > 408s > 408s > ## Cleanup 408s > plan(oplan) 408s > rm(list=c("fits", "data", "fit")) 408s > 408s > proc.time() 408s user system elapsed 408s 6.356 0.189 10.684 408s Test segmentByPairedPSCBS,futures passed 408s 0 408s Begin test segmentByPairedPSCBS,noNormalBAFs 411s + cat segmentByPairedPSCBS,noNormalBAFs.Rout 411s 411s R version 4.5.2 (2025-10-31) -- "[Not] Part in a Rumble" 411s Copyright (C) 2025 The R Foundation for Statistical Computing 411s Platform: aarch64-unknown-linux-gnu 411s 411s R is free software and comes with ABSOLUTELY NO WARRANTY. 411s You are welcome to redistribute it under certain conditions. 411s Type 'license()' or 'licence()' for distribution details. 411s 411s R is a collaborative project with many contributors. 411s Type 'contributors()' for more information and 411s 'citation()' on how to cite R or R packages in publications. 411s 411s Type 'demo()' for some demos, 'help()' for on-line help, or 411s 'help.start()' for an HTML browser interface to help. 411s Type 'q()' to quit R. 411s 411s [Previously saved workspace restored] 411s 411s > library("PSCBS") 411s PSCBS v0.68.0 (2025-04-18 19:40:02 UTC) successfully loaded. See ?PSCBS for help. 411s > 411s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 411s > # Load SNP microarray data 411s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 411s > data <- PSCBS::exampleData("paired.chr01") 411s > str(data) 411s 'data.frame': 73346 obs. of 6 variables: 411s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 411s $ x : int 1145994 2224111 2319424 2543484 2926730 2941694 3084986 3155127 3292731 3695086 ... 411s $ CT : num 1.625 1.071 1.406 1.18 0.856 ... 411s $ betaT : num 0.757 0.771 0.834 0.778 0.229 ... 411s $ CN : num 2.36 2.13 2.59 1.93 1.71 ... 411s $ betaN : num 0.827 0.875 0.887 0.884 0.103 ... 411s > 411s > # Drop single-locus outliers 411s > dataS <- dropSegmentationOutliers(data) 411s > 411s > # Run light-weight tests by default 411s > if (Sys.getenv("_R_CHECK_FULL_") == "") { 411s + # Use only every 5th data point 411s + dataS <- dataS[seq(from=1, to=nrow(data), by=5),] 411s + # Number of segments (for assertion) 411s + nSegs <- 3L 411s + # Number of bootstrap samples (see below) 411s + B <- 100L 411s + } else { 411s + # Full tests 411s + nSegs <- 8L 411s + B <- 1000L 411s + } 411s > 411s > str(dataS) 411s 'data.frame': 14670 obs. of 6 variables: 411s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 411s $ x : int 1145994 2941694 3710825 4240737 4276892 4464544 4714611 5095111 5034491 5158416 ... 411s $ CT : num 1.63 1.4 1.41 1.17 1.16 ... 411s $ betaT : num 0.7574 0.169 0.2357 0.2604 0.0576 ... 411s $ CN : num 2.36 2.13 2.26 2.01 2.32 ... 411s $ betaN : num 0.8274 0.5072 0.1671 0.1609 0.0421 ... 411s > 411s > R.oo::attachLocally(dataS) 411s > 411s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 411s > # Simulate that genotypes are known by other means 411s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 411s > library("aroma.light") 411s aroma.light v3.36.0 (2024-10-29) successfully loaded. See ?aroma.light for help. 411s > muN <- aroma.light::callNaiveGenotypes(betaN, censorAt=c(0,1)) 411s > 411s > 411s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 411s > # Paired PSCBS segmentation 411s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 411s > fit <- segmentByPairedPSCBS(CT, betaT=betaT, muN=muN, tbn=FALSE, 411s + chromosome=chromosome, x=x, 411s + seed=0xBEEF, verbose=-10) 411s Segmenting paired tumor-normal signals using Paired PSCBS... 411s Setup up data... 411s 'data.frame': 14670 obs. of 6 variables: 411s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 411s $ x : num 1145994 2941694 3710825 4240737 4276892 ... 411s $ CT : num 1.63 1.4 1.41 1.17 1.16 ... 411s $ betaT : num 0.7574 0.169 0.2357 0.2604 0.0576 ... 411s $ betaTN : num 0.7574 0.169 0.2357 0.2604 0.0576 ... 411s $ muN : num 1 0.5 0 0 0 0 1 0 1 0.5 ... 411s ..- attr(*, "modelFit")=List of 1 411s .. ..$ :List of 7 411s .. .. ..$ flavor : chr "density" 411s .. .. ..$ cn : int 2 411s .. .. ..$ nbrOfGenotypeGroups: int 3 411s .. .. ..$ tau : num [1:2] 0.315 0.677 411s .. .. ..$ n : int 14640 411s .. .. ..$ fit :Classes 'PeaksAndValleys' and 'data.frame': 5 obs. of 3 variables: 411s .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 411s .. .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 411s .. .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 411s .. .. ..$ fitValleys :Classes 'PeaksAndValleys' and 'data.frame': 2 obs. of 3 variables: 411s .. .. .. ..$ type : chr [1:2] "valley" "valley" 411s .. .. .. ..$ x : num [1:2] 0.315 0.677 411s .. .. .. ..$ density: num [1:2] 0.522 0.551 411s .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 411s Setup up data...done 411s Dropping loci for which TCNs are missing... 411s Number of loci dropped: 12 411s Dropping loci for which TCNs are missing...done 411s Ordering data along genome... 411s 'data.frame': 14658 obs. of 6 variables: 411s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 411s $ x : num 554484 730720 782343 878522 916294 ... 411s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 411s $ betaT : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 411s $ betaTN : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 411s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 411s Ordering data along genome...done 411s Keeping only current chromosome for 'knownSegments'... 411s Chromosome: 1 411s Known segments for this chromosome: 411s [1] chromosome start end 411s <0 rows> (or 0-length row.names) 411s Keeping only current chromosome for 'knownSegments'...done 411s alphaTCN: 0.009 411s alphaDH: 0.001 411s Number of loci: 14658 411s Calculating DHs... 411s Number of SNPs: 14658 411s Number of heterozygous SNPs: 4196 (28.63%) 411s Normalized DHs: 411s num [1:14658] NA NA NA NA NA ... 411s Calculating DHs...done 411s Random seed temporarily set (seed=c(48879), kind="L'Ecuyer-CMRG") 411s Produced 2 seeds from this stream for future usage 411s Identification of change points by total copy numbers... 411s Segmenting by CBS... 411s Chromosome: 1 411s Random seed temporarily set (seed=c(10407, 1066287653, -51199871, 161854402, -1995183193, 1503453565, -747102133), kind="L'Ecuyer-CMRG") 411s Segmenting by CBS...done 411s List of 4 411s $ data :'data.frame': 14658 obs. of 4 variables: 411s ..$ chromosome: int [1:14658] 1 1 1 1 1 1 1 1 1 1 ... 411s ..$ x : num [1:14658] 554484 730720 782343 878522 916294 ... 411s ..$ y : num [1:14658] 1.88 1.8 1.59 1.64 1.53 ... 411s ..$ index : int [1:14658] 1 2 3 4 5 6 7 8 9 10 ... 411s $ output :'data.frame': 3 obs. of 6 variables: 411s ..$ sampleName: chr [1:3] NA NA NA 411s ..$ chromosome: int [1:3] 1 1 1 411s ..$ start : num [1:3] 5.54e+05 1.44e+08 1.85e+08 411s ..$ end : num [1:3] 1.44e+08 1.85e+08 2.47e+08 411s ..$ nbrOfLoci : int [1:3] 7599 2668 4391 411s ..$ mean : num [1:3] 1.39 2.07 2.63 411s $ segRows:'data.frame': 3 obs. of 2 variables: 411s ..$ startRow: int [1:3] 1 7600 10268 411s ..$ endRow : int [1:3] 7599 10267 14658 411s $ params :List of 5 411s ..$ alpha : num 0.009 411s ..$ undo : num 0 411s ..$ joinSegments : logi TRUE 411s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 411s .. ..$ chromosome: int 1 411s .. ..$ start : num -Inf 411s .. ..$ end : num Inf 411s ..$ seed : int [1:7] 10407 1066287653 -51199871 161854402 -1995183193 1503453565 -747102133 411s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 411s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.369 0 0.369 0 0 411s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 411s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 411s - attr(*, "randomSeed")= int [1:7] 10407 1066287653 -51199871 161854402 -1995183193 1503453565 -747102133 411s Identification of change points by total copy numbers...done 411s Restructure TCN segmentation results... 411s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean 411s 1 1 554484 143926517 7599 1.3859 411s 2 1 143926517 185449813 2668 2.0704 411s 3 1 185449813 247137334 4391 2.6341 411s Number of TCN segments: 3 411s Restructure TCN segmentation results...done 411s Total CN segment #1 ([ 554484,1.43927e+08]) of 3... 411s Number of TCN loci in segment: 7599 411s Locus data for TCN segment: 411s 'data.frame': 7599 obs. of 8 variables: 411s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 411s $ x : num 554484 730720 782343 878522 916294 ... 411s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 411s $ betaT : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 411s $ betaTN : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 411s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 411s $ index : int 1 2 3 4 5 6 7 8 9 10 ... 411s $ rho : num NA NA NA NA NA ... 411s Number of loci: 7599 411s Number of SNPs: 2111 (27.78%) 411s Number of heterozygous SNPs: 2111 (100.00%) 411s Chromosome: 1 411s Segmenting DH signals... 411s Segmenting by CBS... 411s Chromosome: 1 411s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 411s Segmenting by CBS...done 411s List of 4 411s $ data :'data.frame': 7599 obs. of 4 variables: 411s ..$ chromosome: int [1:7599] 1 1 1 1 1 1 1 1 1 1 ... 411s ..$ x : num [1:7599] 554484 730720 782343 878522 916294 ... 411s ..$ y : num [1:7599] NA NA NA NA NA ... 411s ..$ index : int [1:7599] 1 2 3 4 5 6 7 8 9 10 ... 411s $ output :'data.frame': 1 obs. of 6 variables: 411s ..$ sampleName: chr NA 411s ..$ chromosome: int 1 411s ..$ start : num 554484 411s ..$ end : num 1.44e+08 411s ..$ nbrOfLoci : int 2111 411s ..$ mean : num 0.524 411s $ segRows:'data.frame': 1 obs. of 2 variables: 411s ..$ startRow: int 10 411s ..$ endRow : int 7594 411s $ params :List of 5 411s ..$ alpha : num 0.001 411s ..$ undo : num 0 411s ..$ joinSegments : logi TRUE 411s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 411s .. ..$ chromosome: int 1 411s .. ..$ start : num 554484 411s .. ..$ end : num 1.44e+08 411s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 411s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 411s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.025 0 0.025 0 0 411s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 411s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 411s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 411s DH segmentation (locally-indexed) rows: 411s startRow endRow 411s 1 10 7594 411s int [1:7599] 1 2 3 4 5 6 7 8 9 10 ... 411s DH segmentation rows: 411s startRow endRow 411s 1 10 7594 411s Segmenting DH signals...done 411s DH segmentation table: 411s dhStart dhEnd dhNbrOfLoci dhMean 411s 1 554484 143926517 2111 0.5237 411s startRow endRow 411s 1 10 7594 411s Rows: 411s [1] 1 411s TCN segmentation rows: 411s startRow endRow 411s 1 1 7599 411s TCN and DH segmentation rows: 411s startRow endRow 411s 1 1 7599 411s startRow endRow 411s 1 10 7594 411s NULL 411s TCN segmentation (expanded) rows: 411s startRow endRow 411s 1 1 7599 411s TCN and DH segmentation rows: 411s startRow endRow 411s 1 1 7599 411s 2 7600 10267 411s 3 10268 14658 411s startRow endRow 411s 1 10 7594 411s startRow endRow 411s 1 1 7599 411s Total CN segmentation table (expanded): 411s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 411s 1 1 554484 143926517 7599 1.3859 2111 2111 411s (TCN,DH) segmentation for one total CN segment: 411s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 411s 1 1 1 1 554484 143926517 7599 1.3859 2111 411s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 411s 1 2111 554484 143926517 2111 0.5237 411s Total CN segment #1 ([ 554484,1.43927e+08]) of 3...done 411s Total CN segment #2 ([1.43927e+08,1.8545e+08]) of 3... 411s Number of TCN loci in segment: 2668 411s Locus data for TCN segment: 411s 'data.frame': 2668 obs. of 8 variables: 411s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 411s $ x : num 1.44e+08 1.44e+08 1.44e+08 1.44e+08 1.44e+08 ... 411s $ CT : num 2.1 2.1 2.09 1.8 2.34 ... 411s $ betaT : num 0.1899 0.909 0.9166 0.1668 0.0308 ... 411s $ betaTN : num 0.1899 0.909 0.9166 0.1668 0.0308 ... 411s $ muN : num 0 1 1 0 0 1 0 0 0 0 ... 411s $ index : int 7600 7601 7602 7603 7604 7605 7606 7607 7608 7609 ... 411s $ rho : num NA NA NA NA NA NA NA NA NA NA ... 411s Number of loci: 2668 411s Number of SNPs: 774 (29.01%) 411s Number of heterozygous SNPs: 774 (100.00%) 411s Chromosome: 1 411s Segmenting DH signals... 411s Segmenting by CBS... 411s Chromosome: 1 411s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 411s Segmenting by CBS...done 411s List of 4 411s $ data :'data.frame': 2668 obs. of 4 variables: 411s ..$ chromosome: int [1:2668] 1 1 1 1 1 1 1 1 1 1 ... 411s ..$ x : num [1:2668] 1.44e+08 1.44e+08 1.44e+08 1.44e+08 1.44e+08 ... 411s ..$ y : num [1:2668] NA NA NA NA NA NA NA NA NA NA ... 411s ..$ index : int [1:2668] 1 2 3 4 5 6 7 8 9 10 ... 411s $ output :'data.frame': 1 obs. of 6 variables: 411s ..$ sampleName: chr NA 411s ..$ chromosome: int 1 411s ..$ start : num 1.44e+08 411s ..$ end : num 1.85e+08 411s ..$ nbrOfLoci : int 774 411s ..$ mean : num 0.154 411s $ segRows:'data.frame': 1 obs. of 2 variables: 411s ..$ startRow: int 15 411s ..$ endRow : int 2664 411s $ params :List of 5 411s ..$ alpha : num 0.001 411s ..$ undo : num 0 411s ..$ joinSegments : logi TRUE 411s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 411s .. ..$ chromosome: int 1 411s .. ..$ start : num 1.44e+08 411s .. ..$ end : num 1.85e+08 411s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 411s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 411s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.009 0 0.009 0 0 411s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 411s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 411s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 411s DH segmentation (locally-indexed) rows: 411s startRow endRow 411s 1 15 2664 411s int [1:2668] 7600 7601 7602 7603 7604 7605 7606 7607 7608 7609 ... 411s DH segmentation rows: 411s startRow endRow 411s 1 7614 10263 411s Segmenting DH signals...done 411s DH segmentation table: 411s dhStart dhEnd dhNbrOfLoci dhMean 411s 1 143926517 185449813 774 0.1542 411s startRow endRow 411s 1 7614 10263 411s Rows: 411s [1] 2 411s TCN segmentation rows: 411s startRow endRow 411s 2 7600 10267 411s TCN and DH segmentation rows: 411s startRow endRow 411s 2 7600 10267 411s startRow endRow 411s 1 7614 10263 411s startRow endRow 411s 1 1 7599 411s TCN segmentation (expanded) rows: 411s startRow endRow 411s 1 1 7599 411s 2 7600 10267 411s TCN and DH segmentation rows: 411s startRow endRow 411s 1 1 7599 411s 2 7600 10267 411s 3 10268 14658 411s startRow endRow 411s 1 10 7594 411s 2 7614 10263 411s startRow endRow 411s 1 1 7599 411s 2 7600 10267 411s Total CN segmentation table (expanded): 411s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 411s 2 1 143926517 185449813 2668 2.0704 774 774 411s (TCN,DH) segmentation for one total CN segment: 411s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 411s 2 2 1 1 143926517 185449813 2668 2.0704 774 411s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 411s 2 774 143926517 185449813 774 0.1542 411s Total CN segment #2 ([1.43927e+08,1.8545e+08]) of 3...done 411s Total CN segment #3 ([1.8545e+08,2.47137e+08]) of 3... 411s Number of TCN loci in segment: 4391 411s Locus data for TCN segment: 411s 'data.frame': 4391 obs. of 8 variables: 411s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 411s $ x : num 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 411s $ CT : num 2.93 2.15 2.82 2.93 2.46 ... 411s $ betaT : num 0.0811 0.5154 0.9473 0.3734 0.7506 ... 411s $ betaTN : num 0.0811 0.5154 0.9473 0.3734 0.7506 ... 411s $ muN : num 0 0.5 1 0.5 1 1 0 1 0 1 ... 411s $ index : int 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 411s $ rho : num NA 0.0308 NA 0.2533 NA ... 411s Number of loci: 4391 411s Number of SNPs: 1311 (29.86%) 411s Number of heterozygous SNPs: 1311 (100.00%) 411s Chromosome: 1 411s Segmenting DH signals... 411s Segmenting by CBS... 411s Chromosome: 1 411s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 411s Segmenting by CBS...done 411s List of 4 411s $ data :'data.frame': 4391 obs. of 4 variables: 411s ..$ chromosome: int [1:4391] 1 1 1 1 1 1 1 1 1 1 ... 411s ..$ x : num [1:4391] 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 411s ..$ y : num [1:4391] NA 0.0308 NA 0.2533 NA ... 411s ..$ index : int [1:4391] 1 2 3 4 5 6 7 8 9 10 ... 411s $ output :'data.frame': 1 obs. of 6 variables: 411s ..$ sampleName: chr NA 411s ..$ chromosome: int 1 411s ..$ start : num 1.85e+08 411s ..$ end : num 2.47e+08 411s ..$ nbrOfLoci : int 1311 411s ..$ mean : num 0.251 411s $ segRows:'data.frame': 1 obs. of 2 variables: 411s ..$ startRow: int 2 411s ..$ endRow : int 4388 411s $ params :List of 5 411s ..$ alpha : num 0.001 411s ..$ undo : num 0 411s ..$ joinSegments : logi TRUE 411s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 411s .. ..$ chromosome: int 1 411s .. ..$ start : num 1.85e+08 411s .. ..$ end : num 2.47e+08 411s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 411s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 411s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.02 0 0.02 0 0 411s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 411s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 411s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 411s DH segmentation (locally-indexed) rows: 411s startRow endRow 411s 1 2 4388 411s int [1:4391] 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 411s DH segmentation rows: 411s startRow endRow 411s 1 10269 14655 411s Segmenting DH signals...done 411s DH segmentation table: 411s dhStart dhEnd dhNbrOfLoci dhMean 411s 1 185449813 247137334 1311 0.2512 411s startRow endRow 411s 1 10269 14655 411s Rows: 411s [1] 3 411s TCN segmentation rows: 411s startRow endRow 411s 3 10268 14658 411s TCN and DH segmentation rows: 411s startRow endRow 411s 3 10268 14658 411s startRow endRow 411s 1 10269 14655 411s startRow endRow 411s 1 1 7599 411s 2 7600 10267 411s TCN segmentation (expanded) rows: 411s startRow endRow 411s 1 1 7599 411s 2 7600 10267 411s 3 10268 14658 411s TCN and DH segmentation rows: 411s startRow endRow 411s 1 1 7599 411s 2 7600 10267 411s 3 10268 14658 411s startRow endRow 411s 1 10 7594 411s 2 7614 10263 411s 3 10269 14655 411s startRow endRow 411s 1 1 7599 411s 2 7600 10267 411s 3 10268 14658 411s Total CN segmentation table (expanded): 411s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 411s 3 1 185449813 247137334 4391 2.6341 1311 1311 411s (TCN,DH) segmentation for one total CN segment: 411s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 411s 3 3 1 1 185449813 247137334 4391 2.6341 1311 411s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 411s 3 1311 185449813 247137334 1311 0.2512 411s Total CN segment #3 ([1.8545e+08,2.47137e+08]) of 3...done 411s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 411s 1 1 1 1 554484 143926517 7599 1.3859 2111 411s 2 1 2 1 143926517 185449813 2668 2.0704 774 411s 3 1 3 1 185449813 247137334 4391 2.6341 1311 411s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 411s 1 2111 554484 143926517 2111 0.5237 411s 2 774 143926517 185449813 774 0.1542 411s 3 1311 185449813 247137334 1311 0.2512 411s Calculating (C1,C2) per segment... 411s Calculating (C1,C2) per segment...done 411s Number of segments: 3 411s Segmenting paired tumor-normal signals using Paired PSCBS...done 411s Post-segmenting TCNs... 411s Number of segments: 3 411s Number of chromosomes: 1 411s [1] 1 411s Chromosome 1 ('chr01') of 1... 411s Rows: 411s [1] 1 2 3 411s Number of segments: 3 411s TCN segment #1 ('1') of 3... 411s Nothing todo. Only one DH segmentation. Skipping. 411s TCN segment #1 ('1') of 3...done 411s TCN segment #2 ('2') of 3... 411s Nothing todo. Only one DH segmentation. Skipping. 411s TCN segment #2 ('2') of 3...done 411s TCN segment #3 ('3') of 3... 411s Nothing todo. Only one DH segmentation. Skipping. 411s TCN segment #3 ('3') of 3...done 411s Chromosome 1 ('chr01') of 1...done 411s Update (C1,C2) per segment... 411s Update (C1,C2) per segment...done 411s Post-segmenting TCNs...done 411s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 411s 1 1 1 1 554484 143926517 7599 1.3859 2111 411s 2 1 2 1 143926517 185449813 2668 2.0704 774 411s 3 1 3 1 185449813 247137334 4391 2.6341 1311 411s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 411s 1 2111 554484 143926517 2111 0.5237 0.3300521 1.055848 411s 2 774 143926517 185449813 774 0.1542 0.8755722 1.194828 411s 3 1311 185449813 247137334 1311 0.2512 0.9862070 1.647893 411s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 411s 1 1 1 1 554484 143926517 7599 1.3859 2111 411s 2 1 2 1 143926517 185449813 2668 2.0704 774 411s 3 1 3 1 185449813 247137334 4391 2.6341 1311 411s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 411s 1 2111 554484 143926517 2111 0.5237 0.3300521 1.055848 411s 2 774 143926517 185449813 774 0.1542 0.8755722 1.194828 411s 3 1311 185449813 247137334 1311 0.2512 0.9862070 1.647893 411s > print(fit) 411s chromosome tcnId dhId start end tcnNbrOfLoci tcnMean tcnNbrOfSNPs 411s 1 1 1 1 554484 143926517 7599 1.3859 2111 411s 2 1 2 1 143926517 185449813 2668 2.0704 774 411s 3 1 3 1 185449813 247137334 4391 2.6341 1311 411s tcnNbrOfHets dhNbrOfLoci dhMean c1Mean c2Mean 411s 1 2111 2111 0.5237 0.3300521 1.055848 411s 2 774 774 0.1542 0.8755722 1.194828 411s 3 1311 1311 0.2512 0.9862070 1.647893 411s > 411s > # Plot results 411s > plotTracks(fit) 411s > 411s > # Sanity check 411s > stopifnot(nbrOfSegments(fit) == nSegs) 411s > 411s > 411s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 411s > # Bootstrap segment level estimates 411s > # (used by the AB caller, which, if skipped here, 411s > # will do it automatically) 411s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 411s > fit <- bootstrapTCNandDHByRegion(fit, B=B, verbose=-10) 411s Resample (TCN,DH) signals and re-estimate summaries for segment & changepoint... 411s Already done? 411s tcn_2.5% tcn_5% tcn_95% tcn_97.5% dh_2.5% dh_5% dh_95% dh_97.5% 411s FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE 411s c1_2.5% c1_5% c1_95% c1_97.5% c2_2.5% c2_5% c2_95% c2_97.5% 411s FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE 411s Bootstrapping (TCN,DH,C1,C2) segment mean levels... 411s Identifying heterozygous & homozygous SNPs and non-polymorphic loci... 411s Number of loci: 14658 411s Number of SNPs: 4196 411s Number of non-SNPs: 10462 411s Identifying heterozygous & homozygous SNPs and non-polymorphic loci...done 411s num [1:3, 1:100, 1:4] NA NA NA NA NA NA NA NA NA NA ... 411s - attr(*, "dimnames")=List of 3 411s ..$ : NULL 411s ..$ : NULL 411s ..$ : chr [1:4] "tcn" "dh" "c1" "c2" 411s Segment #1 (chr 1, tcnId=1, dhId=1) of 3... 411s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 411s 1 1 1 1 554484 143926517 7599 1.3859 2111 411s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 411s 1 2111 554484 143926517 2111 0.5237 0.3300521 1.055848 411s Number of TCNs: 7599 411s Number of DHs: 2111 411s int [1:7599] 1 2 3 4 5 6 7 8 9 10 ... 411s int [1:14658] 1 2 3 4 5 6 7 8 9 10 ... 411s int [1:7599] 1 2 3 4 5 6 7 8 9 10 ... 411s Identify loci used to bootstrap DH means... 411s Heterozygous SNPs to resample for DH: 411s int [1:2111] 10 12 24 28 31 33 34 39 46 48 ... 411s Identify loci used to bootstrap DH means...done 411s Identify loci used to bootstrap TCN means... 411s SNPs: 411s int [1:2111] 10 12 24 28 31 33 34 39 46 48 ... 411s Non-polymorphic loci: 411s int [1:5488] 1 2 3 4 5 6 7 8 9 11 ... 411s Heterozygous SNPs to resample for TCN: 411s int [1:2111] 10 12 24 28 31 33 34 39 46 48 ... 411s Homozygous SNPs to resample for TCN: 411s int(0) 411s Non-polymorphic loci to resample for TCN: 411s int [1:5488] 1 2 3 4 5 6 7 8 9 11 ... 411s Heterozygous SNPs with non-DH to resample for TCN: 411s int(0) 411s Loci to resample for TCN: 411s int [1:7599] 1 2 3 4 5 6 7 8 9 10 ... 411s Identify loci used to bootstrap TCN means...done 411s Number of (#hets, #homs, #nonSNPs): (2111,0,5488) 411s Bootstrapping while preserving (#hets, #homs, #nonSNPs)... 411s Number of bootstrap samples: 100 411s Bootstrapping while preserving (#hets, #homs, #nonSNPs)...done 411s Segment #1 (chr 1, tcnId=1, dhId=1) of 3...done 411s Segment #2 (chr 1, tcnId=2, dhId=1) of 3... 411s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 411s 2 1 2 1 143926517 185449813 2668 2.0704 774 411s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 411s 2 774 143926517 185449813 774 0.1542 0.8755722 1.194828 411s Number of TCNs: 2668 411s Number of DHs: 774 411s int [1:2668] 7600 7601 7602 7603 7604 7605 7606 7607 7608 7609 ... 411s int [1:14658] 1 2 3 4 5 6 7 8 9 10 ... 411s int [1:2668] 7600 7601 7602 7603 7604 7605 7606 7607 7608 7609 ... 411s Identify loci used to bootstrap DH means... 411s Heterozygous SNPs to resample for DH: 411s int [1:774] 7614 7616 7626 7627 7628 7635 7638 7639 7640 7642 ... 411s Identify loci used to bootstrap DH means...done 411s Identify loci used to bootstrap TCN means... 411s SNPs: 411s int [1:774] 7614 7616 7626 7627 7628 7635 7638 7639 7640 7642 ... 411s Non-polymorphic loci: 411s int [1:1894] 7600 7601 7602 7603 7604 7605 7606 7607 7608 7609 ... 411s Heterozygous SNPs to resample for TCN: 411s int [1:774] 7614 7616 7626 7627 7628 7635 7638 7639 7640 7642 ... 411s Homozygous SNPs to resample for TCN: 411s int(0) 411s Non-polymorphic loci to resample for TCN: 411s int [1:1894] 7600 7601 7602 7603 7604 7605 7606 7607 7608 7609 ... 411s Heterozygous SNPs with non-DH to resample for TCN: 411s int(0) 411s Loci to resample for TCN: 411s int [1:2668] 7600 7601 7602 7603 7604 7605 7606 7607 7608 7609 ... 411s Identify loci used to bootstrap TCN means...done 411s Number of (#hets, #homs, #nonSNPs): (774,0,1894) 411s Bootstrapping while preserving (#hets, #homs, #nonSNPs)... 411s Number of bootstrap samples: 100 411s Bootstrapping while preserving (#hets, #homs, #nonSNPs)...done 411s Segment #2 (chr 1, tcnId=2, dhId=1) of 3...done 411s Segment #3 (chr 1, tcnId=3, dhId=1) of 3... 411s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 411s 3 1 3 1 185449813 247137334 4391 2.6341 1311 411s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 411s 3 1311 185449813 247137334 1311 0.2512 0.986207 1.647893 411s Number of TCNs: 4391 411s Number of DHs: 1311 411s int [1:4391] 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 411s int [1:14658] 1 2 3 4 5 6 7 8 9 10 ... 411s int [1:4391] 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 411s Identify loci used to bootstrap DH means... 411s Heterozygous SNPs to resample for DH: 411s int [1:1311] 10269 10271 10281 10282 10283 10293 10295 10297 10300 10302 ... 411s Identify loci used to bootstrap DH means...done 411s Identify loci used to bootstrap TCN means... 411s SNPs: 411s int [1:1311] 10269 10271 10281 10282 10283 10293 10295 10297 10300 10302 ... 411s Non-polymorphic loci: 411s int [1:3080] 10268 10270 10272 10273 10274 10275 10276 10277 10278 10279 ... 411s Heterozygous SNPs to resample for TCN: 411s int [1:1311] 10269 10271 10281 10282 10283 10293 10295 10297 10300 10302 ... 411s Homozygous SNPs to resample for TCN: 411s int(0) 411s Non-polymorphic loci to resample for TCN: 411s int [1:3080] 10268 10270 10272 10273 10274 10275 10276 10277 10278 10279 ... 411s Heterozygous SNPs with non-DH to resample for TCN: 411s int(0) 411s Loci to resample for TCN: 411s int [1:4391] 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 411s Identify loci used to bootstrap TCN means...done 411s Number of (#hets, #homs, #nonSNPs): (1311,0,3080) 411s Bootstrapping while preserving (#hets, #homs, #nonSNPs)... 411s Number of bootstrap samples: 100 411s Bootstrapping while preserving (#hets, #homs, #nonSNPs)...done 411s Segment #3 (chr 1, tcnId=3, dhId=1) of 3...done 411s Bootstrapped segment mean levels 411s num [1:3, 1:100, 1:4] 1.38 2.08 2.63 1.38 2.07 ... 411s - attr(*, "dimnames")=List of 3 411s ..$ : NULL 411s ..$ : NULL 411s ..$ : chr [1:4] "tcn" "dh" "c1" "c2" 411s Calculating (C1,C2) mean levels from (TCN,DH) mean levels... 411s num [1:3, 1:100, 1:4] 1.38 2.08 2.63 1.38 2.07 ... 411s - attr(*, "dimnames")=List of 3 411s ..$ : NULL 411s ..$ : NULL 411s ..$ : chr [1:4] "tcn" "dh" "c1" "c2" 411s Calculating (C1,C2) mean levels from (TCN,DH) mean levels...done 411s Calculating polar (alpha,radius,manhattan) for change points... 411s num [1:2, 1:100, 1:2] -0.5588 -0.0962 -0.5365 -0.1285 -0.5378 ... 411s - attr(*, "dimnames")=List of 3 411s ..$ : NULL 411s ..$ : NULL 411s ..$ : chr [1:2] "c1" "c2" 411s Bootstrapped change points 411s num [1:2, 1:100, 1:5] -2.89 -1.78 -2.87 -1.86 -2.88 ... 411s - attr(*, "dimnames")=List of 3 411s ..$ : NULL 411s ..$ : NULL 411s ..$ : chr [1:5] "alpha" "radius" "manhattan" "d1" ... 411s Calculating polar (alpha,radius,manhattan) for change points...done 411s Bootstrapping (TCN,DH,C1,C2) segment mean levels...done 411s Summarizing bootstrapped segment ('tcn', 'dh', 'c1', 'c2') data... 411s num [1:3, 1:4, 1:4] NA NA NA NA NA NA NA NA NA NA ... 411s - attr(*, "dimnames")=List of 3 411s ..$ : NULL 411s ..$ : chr [1:4] "2.5%" "5%" "95%" "97.5%" 411s ..$ : chr [1:4] "tcn" "dh" "c1" "c2" 411s Field #1 ('tcn') of 4... 411s Segment #1 of 3... 411s Segment #1 of 3...done 411s Segment #2 of 3... 411s Segment #2 of 3...done 411s Segment #3 of 3... 411s Segment #3 of 3...done 411s Field #1 ('tcn') of 4...done 411s Field #2 ('dh') of 4... 411s Segment #1 of 3... 411s Segment #1 of 3...done 411s Segment #2 of 3... 411s Segment #2 of 3...done 411s Segment #3 of 3... 411s Segment #3 of 3...done 411s Field #2 ('dh') of 4...done 411s Field #3 ('c1') of 4... 411s Segment #1 of 3... 411s Segment #1 of 3...done 411s Segment #2 of 3... 411s Segment #2 of 3...done 411s Segment #3 of 3... 411s Segment #3 of 3...done 411s Field #3 ('c1') of 4...done 411s Field #4 ('c2') of 4... 411s Segment #1 of 3... 411s Segment #1 of 3...done 411s Segment #2 of 3... 411s Segment #2 of 3...done 411s Segment #3 of 3... 411s Segment #3 of 3...done 411s Field #4 ('c2') of 4...done 411s Bootstrap statistics 411s num [1:3, 1:4, 1:4] 1.38 2.06 2.62 1.38 2.06 ... 411s - attr(*, "dimnames")=List of 3 411s ..$ : NULL 411s ..$ : chr [1:4] "2.5%" "5%" "95%" "97.5%" 411s ..$ : chr [1:4] "tcn" "dh" "c1" "c2" 411s Statistical sanity checks (iff B >= 100)... 411s Available summaries: 2.5%, 5%, 95%, 97.5% 411s Available quantiles: 0.025, 0.05, 0.95, 0.975 411s num [1:3, 1:4, 1:4] 1.38 2.06 2.62 1.38 2.06 ... 411s - attr(*, "dimnames")=List of 3 411s ..$ : NULL 411s ..$ : chr [1:4] "2.5%" "5%" "95%" "97.5%" 411s ..$ : chr [1:4] "tcn" "dh" "c1" "c2" 411s Field #1 ('tcn') of 4... 411s Seg 1. mean=1.3859, range=[1.38092,1.3949], n=7599 411s Seg 2. mean=2.0704, range=[2.05747,2.08326], n=2668 411s Seg 3. mean=2.6341, range=[2.62068,2.64694], n=4391 411s Field #1 ('tcn') of 4...done 411s Field #2 ('dh') of 4... 411s Seg 1. mean=0.5237, range=[0.51753,0.532002], n=2111 411s Seg 2. mean=0.1542, range=[0.144468,0.16453], n=774 411s Seg 3. mean=0.2512, range=[0.242575,0.258832], n=1311 411s Field #2 ('dh') of 4...done 411s Field #3 ('c1') of 4... 411s Seg 1. mean=0.330052, range=[0.323996,0.336038], n=2111 411s Seg 2. mean=0.875572, range=[0.86318,0.887699], n=774 411s Seg 3. mean=0.986207, range=[0.975123,0.998982], n=1311 411s Field #3 ('c1') of 4...done 411s Field #4 ('c2') of 4... 411s Seg 1. mean=1.05585, range=[1.05006,1.06231], n=2111 411s Seg 2. mean=1.19483, range=[1.18417,1.2081], n=774 411s Seg 3. mean=1.64789, range=[1.63403,1.66098], n=1311 411s Field #4 ('c2') of 4...done 411s Statistical sanity checks (iff B >= 100)...done 411s Summarizing bootstrapped segment ('tcn', 'dh', 'c1', 'c2') data...done 411s Summarizing bootstrapped changepoint ('alpha', 'radius', 'manhattan', 'd1', 'd2') data... 411s num [1:2, 1:4, 1:5] NA NA NA NA NA NA NA NA NA NA ... 411s - attr(*, "dimnames")=List of 3 411s ..$ : NULL 411s ..$ : chr [1:4] "2.5%" "5%" "95%" "97.5%" 411s ..$ : chr [1:5] "alpha" "radius" "manhattan" "d1" ... 411s Field #1 ('alpha') of 5... 411s Changepoint #1 of 2... 411s Changepoint #1 of 2...done 411s Changepoint #2 of 2... 411s Changepoint #2 of 2...done 411s Field #1 ('alpha') of 5...done 411s Field #2 ('radius') of 5... 411s Changepoint #1 of 2... 411s Changepoint #1 of 2...done 411s Changepoint #2 of 2... 411s Changepoint #2 of 2...done 411s Field #2 ('radius') of 5...done 411s Field #3 ('manhattan') of 5... 411s Changepoint #1 of 2... 411s Changepoint #1 of 2...done 411s Changepoint #2 of 2... 411s Changepoint #2 of 2...done 411s Field #3 ('manhattan') of 5...done 411s Field #4 ('d1') of 5... 411s Changepoint #1 of 2... 411s Changepoint #1 of 2...done 411s Changepoint #2 of 2... 411s Changepoint #2 of 2...done 411s Field #4 ('d1') of 5...done 411s Field #5 ('d2') of 5... 411s Changepoint #1 of 2... 411s Changepoint #1 of 2...done 411s Changepoint #2 of 2... 411s Changepoint #2 of 2...done 411s Field #5 ('d2') of 5...done 411s Bootstrap statistics 411s num [1:2, 1:4, 1:5] -2.92 -1.86 -2.91 -1.85 -2.87 ... 411s - attr(*, "dimnames")=List of 3 411s ..$ : NULL 411s ..$ : chr [1:4] "2.5%" "5%" "95%" "97.5%" 411s ..$ : chr [1:5] "alpha" "radius" "manhattan" "d1" ... 411s Summarizing bootstrapped changepoint ('alpha', 'radius', 'manhattan', 'd1', 'd2') data...done 411s Resample (TCN,DH) signals and re-estimate summaries for segment & changepoint...done 411s > print(fit) 411s chromosome tcnId dhId start end tcnNbrOfLoci tcnMean tcnNbrOfSNPs 411s 1 1 1 1 554484 143926517 7599 1.3859 2111 411s 2 1 2 1 143926517 185449813 2668 2.0704 774 411s 3 1 3 1 185449813 247137334 4391 2.6341 1311 411s tcnNbrOfHets dhNbrOfLoci dhMean c1Mean c2Mean 411s 1 2111 2111 0.5237 0.3300521 1.055848 411s 2 774 774 0.1542 0.8755722 1.194828 411s 3 1311 1311 0.2512 0.9862070 1.647893 411s > plotTracks(fit) 411s > 411s > 411s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 411s > # Calling segments in allelic balance (AB) and 411s > # in loss-of-heterozygosity (LOH) 411s > # NOTE: Ideally, this should be done on whole-genome data 411s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 411s > fit <- callAB(fit, verbose=-10) 411s Calling segments of allelic balance from one-sided DH bootstrap confidence intervals... 411s delta (offset adjusting for bias in DH): 0.3466649145302 411s alpha (CI quantile; significance level): 0.05 411s Calling segments... 411s Number of segments called allelic balance (AB): 2 (66.67%) of 3 411s Calling segments...done 411s Calling segments of allelic balance from one-sided DH bootstrap confidence intervals...done 411s > fit <- callLOH(fit, verbose=-10) 411s Calling segments of allelic balance from one-sided DH bootstrap confidence intervals... 411s delta (offset adjusting for bias in C1): 0.771236438183453 411s alpha (CI quantile; significance level): 0.05 411s Calling segments... 411s Number of segments called low C1 (LowC1, "LOH_C1"): 1 (33.33%) of 3 411s Calling segments...done 411s Calling segments of allelic balance from one-sided DH bootstrap confidence intervals...done 411s > print(fit) 411s chromosome tcnId dhId start end tcnNbrOfLoci tcnMean tcnNbrOfSNPs 411s 1 1 1 1 554484 143926517 7599 1.3859 2111 411s 2 1 2 1 143926517 185449813 2668 2.0704 774 411s 3 1 3 1 185449813 247137334 4391 2.6341 1311 411s tcnNbrOfHets dhNbrOfLoci dhMean c1Mean c2Mean abCall lohCall 411s 1 2111 2111 0.5237 0.3300521 1.055848 FALSE TRUE 411s 2 774 774 0.1542 0.8755722 1.194828 TRUE FALSE 411s 3 1311 1311 0.2512 0.9862070 1.647893 TRUE FALSE 411s > plotTracks(fit) 411s > 411s > proc.time() 411s user system elapsed 411s 2.504 0.098 2.591 411s Test segmentByPairedPSCBS,noNormalBAFs passed 411s 0 411s Begin test segmentByPairedPSCBS,report 411s + [ 0 != 0 ] 411s + echo Test segmentByPairedPSCBS,noNormalBAFs passed 411s + echo 0 411s + echo Begin test segmentByPairedPSCBS,report 411s + exitcode=0 411s + R CMD BATCH segmentByPairedPSCBS,report.R 412s + cat segmentByPairedPSCBS,report.Rout 412s 412s R version 4.5.2 (2025-10-31) -- "[Not] Part in a Rumble" 412s Copyright (C) 2025 The R Foundation for Statistical Computing 412s Platform: aarch64-unknown-linux-gnu 412s 412s R is free software and comes with ABSOLUTELY NO WARRANTY. 412s You are welcome to redistribute it under certain conditions. 412s Type 'license()' or 'licence()' for distribution details. 412s 412s R is a collaborative project with many contributors. 412s Type 'contributors()' for more information and 412s 'citation()' on how to cite R or R packages in publications. 412s 412s Type 'demo()' for some demos, 'help()' for on-line help, or 412s 'help.start()' for an HTML browser interface to help. 412s Type 'q()' to quit R. 412s 412s [Previously saved workspace restored] 412s 412s > # This test script calls a report generator which requires 412s > # the 'ggplot2' package, which in turn will require packages 412s > # 'colorspace', 'dichromat', 'munsell', 'reshape2' and 'scales'. 412s > 412s > # Only run this test in full testing mode 412s > if (Sys.getenv("_R_CHECK_FULL_") != "") { 412s + library("PSCBS") 412s + 412s + # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 412s + # Load SNP microarray data 412s + # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 412s + data <- PSCBS::exampleData("paired.chr01") 412s + str(data) 412s + 412s + 412s + # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 412s + # Paired PSCBS segmentation 412s + # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 412s + # Drop single-locus outliers 412s + dataS <- dropSegmentationOutliers(data) 412s + 412s + # Speed up example by segmenting fewer loci 412s + dataS <- dataS[seq(from=1, to=nrow(data), by=5),] 412s + 412s + str(dataS) 412s + 412s + gaps <- findLargeGaps(dataS, minLength=2e6) 412s + knownSegments <- gapsToSegments(gaps) 412s + 412s + # Paired PSCBS segmentation 412s + fit <- segmentByPairedPSCBS(dataS, knownSegments=knownSegments, 412s + seed=0xBEEF, verbose=-10) 412s + 412s + # Fake a multi-chromosome segmentation 412s + fit1 <- fit 412s + fit2 <- renameChromosomes(fit, from=1, to=2) 412s + fit <- c(fit1, fit2) 412s + 412s + report(fit, sampleName="PairedPSCBS", studyName="PSCBS-Ex", verbose=-10) 412s + 412s + } # if (Sys.getenv("_R_CHECK_FULL_")) 412s > 412s > proc.time() 412s user system elapsed 412s 0.331 0.040 0.358 412s + [ 0 != 0 ] 412s + echo Test segmentByPairedPSCBS,report passed 412s + echo 0 412s + echo Begin test segmentByPairedPSCBS,seqOfSegmentsByDP 412s + exitcode=0 412s + R CMD BATCH segmentByPairedPSCBS,seqOfSegmentsByDP.R 412s Test segmentByPairedPSCBS,report passed 412s 0 412s Begin test segmentByPairedPSCBS,seqOfSegmentsByDP 417s + cat segmentByPairedPSCBS,seqOfSegmentsByDP.Rout 417s 417s R version 4.5.2 (2025-10-31) -- "[Not] Part in a Rumble" 417s Copyright (C) 2025 The R Foundation for Statistical Computing 417s Platform: aarch64-unknown-linux-gnu 417s 417s R is free software and comes with ABSOLUTELY NO WARRANTY. 417s You are welcome to redistribute it under certain conditions. 417s Type 'license()' or 'licence()' for distribution details. 417s 417s R is a collaborative project with many contributors. 417s Type 'contributors()' for more information and 417s 'citation()' on how to cite R or R packages in publications. 417s 417s Type 'demo()' for some demos, 'help()' for on-line help, or 417s 'help.start()' for an HTML browser interface to help. 417s Type 'q()' to quit R. 417s 417s [Previously saved workspace restored] 417s 417s > library("PSCBS") 417s PSCBS v0.68.0 (2025-04-18 19:40:02 UTC) successfully loaded. See ?PSCBS for help. 417s > subplots <- R.utils::subplots 417s > stext <- R.utils::stext 417s > 417s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 417s > # Load SNP microarray data 417s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 417s > data <- PSCBS::exampleData("paired.chr01") 417s > str(data) 417s 'data.frame': 73346 obs. of 6 variables: 417s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 417s $ x : int 1145994 2224111 2319424 2543484 2926730 2941694 3084986 3155127 3292731 3695086 ... 417s $ CT : num 1.625 1.071 1.406 1.18 0.856 ... 417s $ betaT : num 0.757 0.771 0.834 0.778 0.229 ... 417s $ CN : num 2.36 2.13 2.59 1.93 1.71 ... 417s $ betaN : num 0.827 0.875 0.887 0.884 0.103 ... 417s > 417s > 417s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 417s > # Paired PSCBS segmentation 417s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 417s > # Drop single-locus outliers 417s > dataS <- dropSegmentationOutliers(data) 417s > 417s > # Run light-weight tests by default 417s > if (Sys.getenv("_R_CHECK_FULL_") == "") { 417s + # Use only every 5th data point 417s + dataS <- dataS[seq(from=1, to=nrow(data), by=5),] 417s + # Number of segments (for assertion) 417s + nSegs <- 3L 417s + # Number of bootstrap samples (see below) 417s + B <- 100L 417s + } else { 417s + # Full tests 417s + nSegs <- 12L 417s + B <- 1000L 417s + } 417s > 417s > str(dataS) 417s 'data.frame': 14670 obs. of 6 variables: 417s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 417s $ x : int 1145994 2941694 3710825 4240737 4276892 4464544 4714611 5095111 5034491 5158416 ... 417s $ CT : num 1.63 1.4 1.41 1.17 1.16 ... 417s $ betaT : num 0.7574 0.169 0.2357 0.2604 0.0576 ... 417s $ CN : num 2.36 2.13 2.26 2.01 2.32 ... 417s $ betaN : num 0.8274 0.5072 0.1671 0.1609 0.0421 ... 417s > 417s > R.oo::attachLocally(dataS) 417s > 417s > 417s > gaps <- findLargeGaps(dataS, minLength=2e6) 417s > knownSegments <- gapsToSegments(gaps, dropGaps=TRUE) 417s > 417s > # Paired PSCBS segmentation 417s > fit <- segmentByPairedPSCBS(dataS, knownSegments=knownSegments, 417s + seed=0xBEEF, verbose=-10) 417s Segmenting paired tumor-normal signals using Paired PSCBS... 417s Calling genotypes from normal allele B fractions... 417s num [1:14670] 0.8274 0.5072 0.1671 0.1609 0.0421 ... 417s Called genotypes: 417s num [1:14670] 1 0.5 0 0 0 0 1 0 1 0.5 ... 417s - attr(*, "modelFit")=List of 1 417s ..$ :List of 7 417s .. ..$ flavor : chr "density" 417s .. ..$ cn : int 2 417s .. ..$ nbrOfGenotypeGroups: int 3 417s .. ..$ tau : num [1:2] 0.315 0.677 417s .. ..$ n : int 14640 417s .. ..$ fit :Classes 'PeaksAndValleys' and 'data.frame': 5 obs. of 3 variables: 417s .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 417s .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 417s .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 417s .. ..$ fitValleys :Classes 'PeaksAndValleys' and 'data.frame': 2 obs. of 3 variables: 417s .. .. ..$ type : chr [1:2] "valley" "valley" 417s .. .. ..$ x : num [1:2] 0.315 0.677 417s .. .. ..$ density: num [1:2] 0.522 0.551 417s ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 417s muN 417s 0 0.5 1 417s 5221 4198 5251 417s Calling genotypes from normal allele B fractions...done 417s Normalizing betaT using betaN (TumorBoost)... 417s Normalized BAFs: 417s num [1:14670] 0.9301 0.1667 0.0685 0.0995 0.0155 ... 417s - attr(*, "modelFit")=List of 5 417s ..$ method : chr "normalizeTumorBoost" 417s ..$ flavor : chr "v4" 417s ..$ delta : num [1:14670] -0.17264 0.00239 0.1671 0.16085 0.04213 ... 417s .. ..- attr(*, "modelFit")=List of 1 417s .. .. ..$ :List of 7 417s .. .. .. ..$ flavor : chr "density" 417s .. .. .. ..$ cn : int 2 417s .. .. .. ..$ nbrOfGenotypeGroups: int 3 417s .. .. .. ..$ tau : num [1:2] 0.315 0.677 417s .. .. .. ..$ n : int 14640 417s .. .. .. ..$ fit :Classes 'PeaksAndValleys' and 'data.frame': 5 obs. of 3 variables: 417s .. .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 417s .. .. .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 417s .. .. .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 417s .. .. .. ..$ fitValleys :Classes 'PeaksAndValleys' and 'data.frame': 2 obs. of 3 variables: 417s .. .. .. .. ..$ type : chr [1:2] "valley" "valley" 417s .. .. .. .. ..$ x : num [1:2] 0.315 0.677 417s .. .. .. .. ..$ density: num [1:2] 0.522 0.551 417s .. .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 417s ..$ preserveScale: logi FALSE 417s ..$ scaleFactor : num NA 417s Normalizing betaT using betaN (TumorBoost)...done 417s Setup up data... 417s 'data.frame': 14670 obs. of 7 variables: 417s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 417s $ x : num 1145994 2941694 3710825 4240737 4276892 ... 417s $ CT : num 1.63 1.4 1.41 1.17 1.16 ... 417s $ betaT : num 0.7574 0.169 0.2357 0.2604 0.0576 ... 417s $ betaTN : num 0.9301 0.1667 0.0685 0.0995 0.0155 ... 417s ..- attr(*, "modelFit")=List of 5 417s .. ..$ method : chr "normalizeTumorBoost" 417s .. ..$ flavor : chr "v4" 417s .. ..$ delta : num [1:14670] -0.17264 0.00239 0.1671 0.16085 0.04213 ... 417s .. .. ..- attr(*, "modelFit")=List of 1 417s .. .. .. ..$ :List of 7 417s .. .. .. .. ..$ flavor : chr "density" 417s .. .. .. .. ..$ cn : int 2 417s .. .. .. .. ..$ nbrOfGenotypeGroups: int 3 417s .. .. .. .. ..$ tau : num [1:2] 0.315 0.677 417s .. .. .. .. ..$ n : int 14640 417s .. .. .. .. ..$ fit :Classes 'PeaksAndValleys' and 'data.frame': 5 obs. of 3 variables: 417s .. .. .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 417s .. .. .. .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 417s .. .. .. .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 417s .. .. .. .. ..$ fitValleys :Classes 'PeaksAndValleys' and 'data.frame': 2 obs. of 3 variables: 417s .. .. .. .. .. ..$ type : chr [1:2] "valley" "valley" 417s .. .. .. .. .. ..$ x : num [1:2] 0.315 0.677 417s .. .. .. .. .. ..$ density: num [1:2] 0.522 0.551 417s .. .. .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 417s .. ..$ preserveScale: logi FALSE 417s .. ..$ scaleFactor : num NA 417s $ betaN : num 0.8274 0.5072 0.1671 0.1609 0.0421 ... 417s $ muN : num 1 0.5 0 0 0 0 1 0 1 0.5 ... 417s ..- attr(*, "modelFit")=List of 1 417s .. ..$ :List of 7 417s .. .. ..$ flavor : chr "density" 417s .. .. ..$ cn : int 2 417s .. .. ..$ nbrOfGenotypeGroups: int 3 417s .. .. ..$ tau : num [1:2] 0.315 0.677 417s .. .. ..$ n : int 14640 417s .. .. ..$ fit :Classes 'PeaksAndValleys' and 'data.frame': 5 obs. of 3 variables: 417s .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 417s .. .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 417s .. .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 417s .. .. ..$ fitValleys :Classes 'PeaksAndValleys' and 'data.frame': 2 obs. of 3 variables: 417s .. .. .. ..$ type : chr [1:2] "valley" "valley" 417s .. .. .. ..$ x : num [1:2] 0.315 0.677 417s .. .. .. ..$ density: num [1:2] 0.522 0.551 417s .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 417s Setup up data...done 417s Dropping loci for which TCNs are missing... 417s Number of loci dropped: 12 417s Dropping loci for which TCNs are missing...done 417s Ordering data along genome... 417s 'data.frame': 14658 obs. of 7 variables: 417s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 417s $ x : num 554484 730720 782343 878522 916294 ... 417s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 417s $ betaT : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 417s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 417s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 417s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 417s Ordering data along genome...done 417s Keeping only current chromosome for 'knownSegments'... 417s Chromosome: 1 417s Known segments for this chromosome: 417s chromosome start end length 417s 1 1 -Inf 120908858 Inf 417s 2 1 142693888 Inf Inf 417s Keeping only current chromosome for 'knownSegments'...done 417s alphaTCN: 0.009 417s alphaDH: 0.001 417s Number of loci: 14658 417s Calculating DHs... 417s Number of SNPs: 14658 417s Number of heterozygous SNPs: 4196 (28.63%) 417s Normalized DHs: 417s num [1:14658] NA NA NA NA NA ... 417s Calculating DHs...done 417s Random seed temporarily set (seed=c(48879), kind="L'Ecuyer-CMRG") 417s Produced 2 seeds from this stream for future usage 417s Identification of change points by total copy numbers... 417s Segmenting by CBS... 417s Chromosome: 1 417s Segmenting multiple segments on current chromosome... 417s Number of segments: 2 417s Random seed temporarily set (seed=c(10407, 1066287653, -51199871, 161854402, -1995183193, 1503453565, -747102133), kind="L'Ecuyer-CMRG") 417s Produced 2 seeds from this stream for future usage 417s Segmenting by CBS... 417s Chromosome: 1 417s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 417s Segmenting by CBS...done 417s Segmenting by CBS... 417s Chromosome: 1 417s Random seed temporarily set (seed=c(10407, -821273412, -52578226, 1415511586, 721384351, -665928286, 1316562960), kind="L'Ecuyer-CMRG") 417s Segmenting by CBS...done 417s Segmenting multiple segments on current chromosome...done 417s Segmenting by CBS...done 417s List of 4 417s $ data :'data.frame': 14658 obs. of 4 variables: 417s ..$ chromosome: int [1:14658] 1 1 1 1 1 1 1 1 1 1 ... 417s ..$ x : num [1:14658] 554484 730720 782343 878522 916294 ... 417s ..$ y : num [1:14658] 1.88 1.8 1.59 1.64 1.53 ... 417s ..$ index : int [1:14658] 1 2 3 4 5 6 7 8 9 10 ... 417s $ output :'data.frame': 3 obs. of 6 variables: 417s ..$ sampleName: chr [1:3] NA NA NA 417s ..$ chromosome: int [1:3] 1 1 1 417s ..$ start : num [1:3] 5.54e+05 1.43e+08 1.85e+08 417s ..$ end : num [1:3] 1.21e+08 1.85e+08 2.47e+08 417s ..$ nbrOfLoci : int [1:3] 7586 2681 4391 417s ..$ mean : num [1:3] 1.39 2.07 2.63 417s $ segRows:'data.frame': 3 obs. of 2 variables: 417s ..$ startRow: int [1:3] 1 7587 10268 417s ..$ endRow : int [1:3] 7586 10267 14658 417s $ params :List of 5 417s ..$ alpha : num 0.009 417s ..$ undo : num 0 417s ..$ joinSegments : logi TRUE 417s ..$ knownSegments:'data.frame': 2 obs. of 3 variables: 417s .. ..$ chromosome: int [1:2] 1 1 417s .. ..$ start : num [1:2] -Inf 1.43e+08 417s .. ..$ end : num [1:2] 1.21e+08 Inf 417s ..$ seed : int [1:7] 10407 1066287653 -51199871 161854402 -1995183193 1503453565 -747102133 417s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 417s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.129 0 0.129 0 0 417s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 417s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 417s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 417s Identification of change points by total copy numbers...done 417s Restructure TCN segmentation results... 417s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean 417s 1 1 554484 120908858 7586 1.3853 417s 2 1 142693888 185449813 2681 2.0689 417s 3 1 185449813 247137334 4391 2.6341 417s Number of TCN segments: 3 417s Restructure TCN segmentation results...done 417s Total CN segment #1 ([ 554484,1.20909e+08]) of 3... 417s Number of TCN loci in segment: 7586 417s Locus data for TCN segment: 417s 'data.frame': 7586 obs. of 9 variables: 417s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 417s $ x : num 554484 730720 782343 878522 916294 ... 417s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 417s $ betaT : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 417s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 417s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 417s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 417s $ index : int 1 2 3 4 5 6 7 8 9 10 ... 417s $ rho : num NA NA NA NA NA ... 417s Number of loci: 7586 417s Number of SNPs: 2108 (27.79%) 417s Number of heterozygous SNPs: 2108 (100.00%) 417s Chromosome: 1 417s Segmenting DH signals... 417s Segmenting by CBS... 417s Chromosome: 1 417s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 417s Segmenting by CBS...done 417s List of 4 417s $ data :'data.frame': 7586 obs. of 4 variables: 417s ..$ chromosome: int [1:7586] 1 1 1 1 1 1 1 1 1 1 ... 417s ..$ x : num [1:7586] 554484 730720 782343 878522 916294 ... 417s ..$ y : num [1:7586] NA NA NA NA NA ... 417s ..$ index : int [1:7586] 1 2 3 4 5 6 7 8 9 10 ... 417s $ output :'data.frame': 1 obs. of 6 variables: 417s ..$ sampleName: chr NA 417s ..$ chromosome: int 1 417s ..$ start : num 554484 417s ..$ end : num 1.21e+08 417s ..$ nbrOfLoci : int 2108 417s ..$ mean : num 0.512 417s $ segRows:'data.frame': 1 obs. of 2 variables: 417s ..$ startRow: int 10 417s ..$ endRow : int 7574 417s $ params :List of 5 417s ..$ alpha : num 0.001 417s ..$ undo : num 0 417s ..$ joinSegments : logi TRUE 417s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 417s .. ..$ chromosome: int 1 417s .. ..$ start : num 554484 417s .. ..$ end : num 1.21e+08 417s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 417s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 417s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.037 0 0.037 0 0 417s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 417s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 417s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 417s DH segmentation (locally-indexed) rows: 417s startRow endRow 417s 1 10 7574 417s int [1:7586] 1 2 3 4 5 6 7 8 9 10 ... 417s DH segmentation rows: 417s startRow endRow 417s 1 10 7574 417s Segmenting DH signals...done 417s DH segmentation table: 417s dhStart dhEnd dhNbrOfLoci dhMean 417s 1 554484 120908858 2108 0.5116 417s startRow endRow 417s 1 10 7574 417s Rows: 417s [1] 1 417s TCN segmentation rows: 417s startRow endRow 417s 1 1 7586 417s TCN and DH segmentation rows: 417s startRow endRow 417s 1 1 7586 417s startRow endRow 417s 1 10 7574 417s NULL 417s TCN segmentation (expanded) rows: 417s startRow endRow 417s 1 1 7586 417s TCN and DH segmentation rows: 417s startRow endRow 417s 1 1 7586 417s 2 7587 10267 417s 3 10268 14658 417s startRow endRow 417s 1 10 7574 417s startRow endRow 417s 1 1 7586 417s Total CN segmentation table (expanded): 417s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 417s 1 1 554484 120908858 7586 1.3853 2108 2108 417s (TCN,DH) segmentation for one total CN segment: 417s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 417s 1 1 1 1 554484 120908858 7586 1.3853 2108 417s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 417s 1 2108 554484 120908858 2108 0.5116 417s Total CN segment #1 ([ 554484,1.20909e+08]) of 3...done 417s Total CN segment #2 ([1.42694e+08,1.8545e+08]) of 3... 417s Number of TCN loci in segment: 2681 417s Locus data for TCN segment: 417s 'data.frame': 2681 obs. of 9 variables: 417s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 417s $ x : num 1.43e+08 1.43e+08 1.43e+08 1.43e+08 1.44e+08 ... 417s $ CT : num 2.27 1.55 1.47 1.5 1.81 ... 417s $ betaT : num 0.34 0.55 0.048 0.813 0.575 ... 417s $ betaTN : num 0.441 0.629 -0.05 0.958 0.872 ... 417s $ betaN : num 0.3851 0.3933 0.0981 0.8552 0.7028 ... 417s $ muN : num 0.5 0.5 0 1 1 1 1 0.5 1 1 ... 417s $ index : int 7587 7588 7589 7590 7591 7592 7593 7594 7595 7596 ... 417s $ rho : num 0.117 0.258 NA NA NA ... 417s Number of loci: 2681 417s Number of SNPs: 777 (28.98%) 417s Number of heterozygous SNPs: 777 (100.00%) 417s Chromosome: 1 417s Segmenting DH signals... 417s Segmenting by CBS... 417s Chromosome: 1 417s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 417s Segmenting by CBS...done 417s List of 4 417s $ data :'data.frame': 2681 obs. of 4 variables: 417s ..$ chromosome: int [1:2681] 1 1 1 1 1 1 1 1 1 1 ... 417s ..$ x : num [1:2681] 1.43e+08 1.43e+08 1.43e+08 1.43e+08 1.44e+08 ... 417s ..$ y : num [1:2681] 0.117 0.258 NA NA NA ... 417s ..$ index : int [1:2681] 1 2 3 4 5 6 7 8 9 10 ... 417s $ output :'data.frame': 1 obs. of 6 variables: 417s ..$ sampleName: chr NA 417s ..$ chromosome: int 1 417s ..$ start : num 1.43e+08 417s ..$ end : num 1.85e+08 417s ..$ nbrOfLoci : int 777 417s ..$ mean : num 0.0973 417s $ segRows:'data.frame': 1 obs. of 2 variables: 417s ..$ startRow: int 1 417s ..$ endRow : int 2677 417s $ params :List of 5 417s ..$ alpha : num 0.001 417s ..$ undo : num 0 417s ..$ joinSegments : logi TRUE 417s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 417s .. ..$ chromosome: int 1 417s .. ..$ start : num 1.43e+08 417s .. ..$ end : num 1.85e+08 417s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 417s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 417s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.009 0 0.008 0 0 417s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 417s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 417s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 417s DH segmentation (locally-indexed) rows: 417s startRow endRow 417s 1 1 2677 417s int [1:2681] 7587 7588 7589 7590 7591 7592 7593 7594 7595 7596 ... 417s DH segmentation rows: 417s startRow endRow 417s 1 7587 10263 417s Segmenting DH signals...done 417s DH segmentation table: 417s dhStart dhEnd dhNbrOfLoci dhMean 417s 1 142693888 185449813 777 0.0973 417s startRow endRow 417s 1 7587 10263 417s Rows: 417s [1] 2 417s TCN segmentation rows: 417s startRow endRow 417s 2 7587 10267 417s TCN and DH segmentation rows: 417s startRow endRow 417s 2 7587 10267 417s startRow endRow 417s 1 7587 10263 417s startRow endRow 417s 1 1 7586 417s TCN segmentation (expanded) rows: 417s startRow endRow 417s 1 1 7586 417s 2 7587 10267 417s TCN and DH segmentation rows: 417s startRow endRow 417s 1 1 7586 417s 2 7587 10267 417s 3 10268 14658 417s startRow endRow 417s 1 10 7574 417s 2 7587 10263 417s startRow endRow 417s 1 1 7586 417s 2 7587 10267 417s Total CN segmentation table (expanded): 417s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 417s 2 1 142693888 185449813 2681 2.0689 777 777 417s (TCN,DH) segmentation for one total CN segment: 417s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 417s 2 2 1 1 142693888 185449813 2681 2.0689 777 417s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 417s 2 777 142693888 185449813 777 0.0973 417s Total CN segment #2 ([1.42694e+08,1.8545e+08]) of 3...done 417s Total CN segment #3 ([1.8545e+08,2.47137e+08]) of 3... 417s Number of TCN loci in segment: 4391 417s Locus data for TCN segment: 417s 'data.frame': 4391 obs. of 9 variables: 417s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 417s $ x : num 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 417s $ CT : num 2.93 2.15 2.82 2.93 2.46 ... 417s $ betaT : num 0.0811 0.5154 0.9473 0.3734 0.7506 ... 417s $ betaTN : num -0.169 0.609 1.028 0.525 0.968 ... 417s $ betaN : num 0.25 0.38 0.919 0.34 0.783 ... 417s $ muN : num 0 0.5 1 0.5 1 1 0 1 0 1 ... 417s $ index : int 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 417s $ rho : num NA 0.2186 NA 0.0503 NA ... 417s Number of loci: 4391 417s Number of SNPs: 1311 (29.86%) 417s Number of heterozygous SNPs: 1311 (100.00%) 417s Chromosome: 1 417s Segmenting DH signals... 417s Segmenting by CBS... 417s Chromosome: 1 417s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 417s Segmenting by CBS...done 417s List of 4 417s $ data :'data.frame': 4391 obs. of 4 variables: 417s ..$ chromosome: int [1:4391] 1 1 1 1 1 1 1 1 1 1 ... 417s ..$ x : num [1:4391] 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 417s ..$ y : num [1:4391] NA 0.2186 NA 0.0503 NA ... 417s ..$ index : int [1:4391] 1 2 3 4 5 6 7 8 9 10 ... 417s $ output :'data.frame': 1 obs. of 6 variables: 417s ..$ sampleName: chr NA 417s ..$ chromosome: int 1 417s ..$ start : num 1.85e+08 417s ..$ end : num 2.47e+08 417s ..$ nbrOfLoci : int 1311 417s ..$ mean : num 0.23 417s $ segRows:'data.frame': 1 obs. of 2 variables: 417s ..$ startRow: int 2 417s ..$ endRow : int 4388 417s $ params :List of 5 417s ..$ alpha : num 0.001 417s ..$ undo : num 0 417s ..$ joinSegments : logi TRUE 417s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 417s .. ..$ chromosome: int 1 417s .. ..$ start : num 1.85e+08 417s .. ..$ end : num 2.47e+08 417s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 417s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 417s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.015 0 0.015 0 0 417s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 417s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 417s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 417s DH segmentation (locally-indexed) rows: 417s startRow endRow 417s 1 2 4388 417s int [1:4391] 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 417s DH segmentation rows: 417s startRow endRow 417s 1 10269 14655 417s Segmenting DH signals...done 417s DH segmentation table: 417s dhStart dhEnd dhNbrOfLoci dhMean 417s 1 185449813 247137334 1311 0.2295 417s startRow endRow 417s 1 10269 14655 417s Rows: 417s [1] 3 417s TCN segmentation rows: 417s startRow endRow 417s 3 10268 14658 417s TCN and DH segmentation rows: 417s startRow endRow 417s 3 10268 14658 417s startRow endRow 417s 1 10269 14655 417s startRow endRow 417s 1 1 7586 417s 2 7587 10267 417s TCN segmentation (expanded) rows: 417s startRow endRow 417s 1 1 7586 417s 2 7587 10267 417s 3 10268 14658 417s TCN and DH segmentation rows: 417s startRow endRow 417s 1 1 7586 417s 2 7587 10267 417s 3 10268 14658 417s startRow endRow 417s 1 10 7574 417s 2 7587 10263 417s 3 10269 14655 417s startRow endRow 417s 1 1 7586 417s 2 7587 10267 417s 3 10268 14658 417s Total CN segmentation table (expanded): 417s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 417s 3 1 185449813 247137334 4391 2.6341 1311 1311 417s (TCN,DH) segmentation for one total CN segment: 417s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 417s 3 3 1 1 185449813 247137334 4391 2.6341 1311 417s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 417s 3 1311 185449813 247137334 1311 0.2295 417s Total CN segment #3 ([1.8545e+08,2.47137e+08]) of 3...done 417s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 417s 1 1 1 1 554484 120908858 7586 1.3853 2108 417s 2 1 2 1 142693888 185449813 2681 2.0689 777 417s 3 1 3 1 185449813 247137334 4391 2.6341 1311 417s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 417s 1 2108 554484 120908858 2108 0.5116 417s 2 777 142693888 185449813 777 0.0973 417s 3 1311 185449813 247137334 1311 0.2295 417s Calculating (C1,C2) per segment... 417s Calculating (C1,C2) per segment...done 417s Number of segments: 3 417s Segmenting paired tumor-normal signals using Paired PSCBS...done 417s Post-segmenting TCNs... 417s Number of segments: 3 417s Number of chromosomes: 1 417s [1] 1 417s Chromosome 1 ('chr01') of 1... 417s Rows: 417s [1] 1 2 3 417s Number of segments: 3 417s TCN segment #1 ('1') of 3... 417s Nothing todo. Only one DH segmentation. Skipping. 417s TCN segment #1 ('1') of 3...done 417s TCN segment #2 ('2') of 3... 417s Nothing todo. Only one DH segmentation. Skipping. 417s TCN segment #2 ('2') of 3...done 417s TCN segment #3 ('3') of 3... 417s Nothing todo. Only one DH segmentation. Skipping. 417s TCN segment #3 ('3') of 3...done 417s Chromosome 1 ('chr01') of 1...done 417s Update (C1,C2) per segment... 417s Update (C1,C2) per segment...done 417s Post-segmenting TCNs...done 417s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 417s 1 1 1 1 554484 120908858 7586 1.3853 2108 417s 2 1 2 1 142693888 185449813 2681 2.0689 777 417s 3 1 3 1 185449813 247137334 4391 2.6341 1311 417s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 417s 1 2108 554484 120908858 2108 0.5116 0.3382903 1.047010 417s 2 777 142693888 185449813 777 0.0973 0.9337980 1.135102 417s 3 1311 185449813 247137334 1311 0.2295 1.0147870 1.619313 417s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 417s 1 1 1 1 554484 120908858 7586 1.3853 2108 417s 2 1 2 1 142693888 185449813 2681 2.0689 777 417s 3 1 3 1 185449813 247137334 4391 2.6341 1311 417s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 417s 1 2108 554484 120908858 2108 0.5116 0.3382903 1.047010 417s 2 777 142693888 185449813 777 0.0973 0.9337980 1.135102 417s 3 1311 185449813 247137334 1311 0.2295 1.0147870 1.619313 417s > print(fit) 417s chromosome tcnId dhId start end tcnNbrOfLoci tcnMean tcnNbrOfSNPs 417s 1 1 1 1 554484 120908858 7586 1.3853 2108 417s 2 1 2 1 142693888 185449813 2681 2.0689 777 417s 3 1 3 1 185449813 247137334 4391 2.6341 1311 417s tcnNbrOfHets dhNbrOfLoci dhMean c1Mean c2Mean 417s 1 2108 2108 0.5116 0.3382903 1.047010 417s 2 777 777 0.0973 0.9337980 1.135102 417s 3 1311 1311 0.2295 1.0147870 1.619313 417s > 417s > fit1 <- fit 417s > fit2 <- renameChromosomes(fit1, from=1, to=2) 417s > fit <- c(fit1, fit2) 417s > knownSegments <- tileChromosomes(fit)$params$knownSegments 417s > 417s > segList <- seqOfSegmentsByDP(fit, verbose=-10) 417s Identifying optimal sets of segments via dynamic programming... 417s Shifting TCN levels for every second segment... 417s Split up into non-empty independent regions... 417s Chromosome #1 ('1') of 2... 417s Number of loci on chromosome: 14658 417s Known segments on chromosome: 417s chromosome start end 417s 1 1 -Inf 120908858 417s 2 1 142693888 Inf 417s Known segment #1 of 2... 417s chromosome start end 417s 1 1 -Inf 120908858 417s Known segment #1 of 2...done 417s Known segment #2 of 2... 417s chromosome start end 417s 2 1 142693888 Inf 417s Known segment #2 of 2...done 417s Chromosome #1 ('1') of 2...done 417s Chromosome #2 ('2') of 2... 417s Number of loci on chromosome: 14658 417s Known segments on chromosome: 417s chromosome start end 417s 3 2 -Inf 120908858 417s 4 2 142693888 Inf 417s Known segment #1 of 2... 417s chromosome start end 417s 3 2 -Inf 120908858 417s Known segment #1 of 2...done 417s Known segment #2 of 2... 417s chromosome start end 417s 4 2 142693888 Inf 417s Known segment #2 of 2...done 417s Chromosome #2 ('2') of 2...done 417s Number of independent non-empty regions: 4 417s Split up into non-empty independent regions...done 417s Shift every other region... 417s Shift every other region...done 417s Merge... 417s Merge...done 417s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 417s 1 1 1 1 554484 120908858 7586 101.3853 2108 417s 2 1 2 1 142693888 185449813 2681 2.0689 777 417s 3 1 3 1 185449813 247137334 4391 2.6341 1311 417s 4 2 1 1 554484 120908858 7586 101.3853 2108 417s 5 2 2 1 142693888 185449813 2681 2.0689 777 417s 6 2 3 1 185449813 247137334 4391 2.6341 1311 417s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 417s 1 2108 554484 120908858 2108 0.511612 24.757671 76.627587 417s 2 777 142693888 185449813 777 0.097300 0.933798 1.135102 417s 3 1311 185449813 247137334 1311 0.229500 1.014787 1.619313 417s 4 2108 554484 120908858 2108 0.511612 24.757671 76.627587 417s 5 777 142693888 185449813 777 0.097300 0.933798 1.135102 417s 6 1311 185449813 247137334 1311 0.229500 1.014787 1.619313 417s Shifting TCN levels for every second segment...done 417s Extracting signals for dynamic programming... 417s CT rho 417s Min. : 0.805 Min. :0.0002 417s 1st Qu.: 2.407 1st Qu.:0.1393 417s Median :100.927 Median :0.2934 417s Mean : 53.638 Mean :0.3467 417s 3rd Qu.:101.370 3rd Qu.:0.5566 417s Max. :103.080 Max. :1.0217 417s NA's :20924 417s Extracting signals for dynamic programming...done 417s Dynamic programming... 417s Number of "DP" change points: 5 417s int [1:5] 7586 10267 14658 22244 24925 417s List of 4 417s $ jump :List of 5 417s ..$ : num 22244 417s ..$ : num [1:2] 7586 14658 417s ..$ : num [1:3] 7586 14658 22244 417s ..$ : num [1:4] 7586 10267 14658 22244 417s ..$ : num [1:5] 7586 10267 14658 22244 24925 417s $ rse : num [1:6] 71699116 47249179 35852530 5945 5410 ... 417s $ kbest: num 4 417s $ V : num [1:6, 1:6] 1114 0 0 0 0 ... 417s Dynamic programming...done 417s Excluding cases where known segments no longer correct... 417s Number of independent non-empty regions: 4 417s List of 3 417s $ : num [1:3] 7586 14658 22244 417s $ : num [1:4] 7586 10267 14658 22244 417s $ : num [1:5] 7586 10267 14658 22244 24925 417s Excluding cases where known segments no longer correct...done 417s List of 3 417s $ :'data.frame': 4 obs. of 3 variables: 417s ..$ chromosome: int [1:4] 1 1 2 2 417s ..$ start : num [1:4] 5.54e+05 1.43e+08 5.54e+05 1.43e+08 417s ..$ end : num [1:4] 1.21e+08 2.47e+08 1.21e+08 2.47e+08 417s $ :'data.frame': 5 obs. of 3 variables: 417s ..$ chromosome: int [1:5] 1 1 1 2 2 417s ..$ start : num [1:5] 5.54e+05 1.43e+08 1.85e+08 5.54e+05 1.43e+08 417s ..$ end : num [1:5] 1.21e+08 1.85e+08 2.47e+08 1.21e+08 2.47e+08 417s $ :'data.frame': 6 obs. of 3 variables: 417s ..$ chromosome: int [1:6] 1 1 1 2 2 2 417s ..$ start : num [1:6] 5.54e+05 1.43e+08 1.85e+08 5.54e+05 1.43e+08 ... 417s ..$ end : num [1:6] 1.21e+08 1.85e+08 2.47e+08 1.21e+08 1.85e+08 ... 417s Sequence of number of "DP" change points: 417s [1] 3 4 5 417s Sequence of number of segments: 417s [1] 4 5 6 417s Sequence of number of "discovered" change points: 417s [1] 0 1 2 417s Identifying optimal sets of segments via dynamic programming...done 417s > K <- length(segList) 417s > ks <- seq(from=1, to=K, length.out=min(5,K)) 417s > subplots(length(ks), ncol=1, byrow=TRUE) 417s > par(mar=c(2,1,1,1)) 417s > for (kk in ks) { 417s + knownSegmentsKK <- segList[[kk]] 417s + fitKK <- resegment(fit, knownSegments=knownSegmentsKK, undoTCN=+Inf, undoDH=+Inf) 417s + plotTracks(fitKK, tracks="tcn,c1,c2", Clim=c(0,5), add=TRUE) 417s + abline(v=c(knownSegments$start, knownSegments$end)/1e6, lty=3) 417s + stext(side=3, pos=0, sprintf("Number of segments: %d", nrow(knownSegmentsKK))) 417s + } # for (kk ...) 417s > 417s > proc.time() 417s user system elapsed 417s 4.510 0.109 4.611 417s Test segmentByPairedPSCBS,seqOfSegmentsByDP passed 417s 0 417s Begin test segmentByPairedPSCBS 417s + [ 0 != 0 ] 417s + echo Test segmentByPairedPSCBS,seqOfSegmentsByDP passed 417s + echo 0 417s + echo Begin test segmentByPairedPSCBS 417s + exitcode=0 417s + R CMD BATCH segmentByPairedPSCBS.R 423s + cat segmentByPairedPSCBS.Rout 423s 423s R version 4.5.2 (2025-10-31) -- "[Not] Part in a Rumble" 423s Copyright (C) 2025 The R Foundation for Statistical Computing 423s Platform: aarch64-unknown-linux-gnu 423s 423s R is free software and comes with ABSOLUTELY NO WARRANTY. 423s You are welcome to redistribute it under certain conditions. 423s Type 'license()' or 'licence()' for distribution details. 423s 423s R is a collaborative project with many contributors. 423s Type 'contributors()' for more information and 423s 'citation()' on how to cite R or R packages in publications. 423s 423s Type 'demo()' for some demos, 'help()' for on-line help, or 423s 'help.start()' for an HTML browser interface to help. 423s Type 'q()' to quit R. 423s 423s [Previously saved workspace restored] 423s 423s > ########################################################### 423s > # This tests: 423s > # - segmentByPairedPSCBS(...) 423s > # - segmentByPairedPSCBS(..., knownSegments) 423s > # - tileChromosomes() 423s > # - plotTracks() 423s > ########################################################### 423s > library("PSCBS") 423s PSCBS v0.68.0 (2025-04-18 19:40:02 UTC) successfully loaded. See ?PSCBS for help. 423s > 423s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 423s > # Load SNP microarray data 423s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 423s > data <- PSCBS::exampleData("paired.chr01") 423s > 423s > 423s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 423s > # Paired PSCBS segmentation 423s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 423s > # Drop single-locus outliers 423s > dataS <- dropSegmentationOutliers(data) 423s > 423s > # Run light-weight tests by default 423s > if (Sys.getenv("_R_CHECK_FULL_") == "") { 423s + # Use only every 5th data point 423s + dataS <- dataS[seq(from=1, to=nrow(data), by=5),] 423s + # Number of segments (for assertion) 423s + nSegs <- 4L 423s + } else { 423s + # Full tests 423s + nSegs <- 11L 423s + } 423s > 423s > str(dataS) 423s 'data.frame': 14670 obs. of 6 variables: 423s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 423s $ x : int 1145994 2941694 3710825 4240737 4276892 4464544 4714611 5095111 5034491 5158416 ... 423s $ CT : num 1.63 1.4 1.41 1.17 1.16 ... 423s $ betaT : num 0.7574 0.169 0.2357 0.2604 0.0576 ... 423s $ CN : num 2.36 2.13 2.26 2.01 2.32 ... 423s $ betaN : num 0.8274 0.5072 0.1671 0.1609 0.0421 ... 423s > 423s > fig <- 1 423s > 423s > 423s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 423s > # (a) Don't segment the centromere (and force a separator) 423s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 423s > knownSegments <- data.frame( 423s + chromosome = c( 1, 1, 1), 423s + start = c( -Inf, NA, 141510003), 423s + end = c(120992603, NA, +Inf) 423s + ) 423s > 423s > 423s > # Paired PSCBS segmentation 423s > fit <- segmentByPairedPSCBS(dataS, knownSegments=knownSegments, 423s + seed=0xBEEF, verbose=-10) 423s Segmenting paired tumor-normal signals using Paired PSCBS... 423s Calling genotypes from normal allele B fractions... 423s num [1:14670] 0.8274 0.5072 0.1671 0.1609 0.0421 ... 423s Called genotypes: 423s num [1:14670] 1 0.5 0 0 0 0 1 0 1 0.5 ... 423s - attr(*, "modelFit")=List of 1 423s ..$ :List of 7 423s .. ..$ flavor : chr "density" 423s .. ..$ cn : int 2 423s .. ..$ nbrOfGenotypeGroups: int 3 423s .. ..$ tau : num [1:2] 0.315 0.677 423s .. ..$ n : int 14640 423s .. ..$ fit :Classes 'PeaksAndValleys' and 'data.frame': 5 obs. of 3 variables: 423s .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 423s .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 423s .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 423s .. ..$ fitValleys :Classes 'PeaksAndValleys' and 'data.frame': 2 obs. of 3 variables: 423s .. .. ..$ type : chr [1:2] "valley" "valley" 423s .. .. ..$ x : num [1:2] 0.315 0.677 423s .. .. ..$ density: num [1:2] 0.522 0.551 423s ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 423s muN 423s 0 0.5 1 423s 5221 4198 5251 423s Calling genotypes from normal allele B fractions...done 423s Normalizing betaT using betaN (TumorBoost)... 423s Normalized BAFs: 423s num [1:14670] 0.9301 0.1667 0.0685 0.0995 0.0155 ... 423s - attr(*, "modelFit")=List of 5 423s ..$ method : chr "normalizeTumorBoost" 423s ..$ flavor : chr "v4" 423s ..$ delta : num [1:14670] -0.17264 0.00239 0.1671 0.16085 0.04213 ... 423s .. ..- attr(*, "modelFit")=List of 1 423s .. .. ..$ :List of 7 423s .. .. .. ..$ flavor : chr "density" 423s .. .. .. ..$ cn : int 2 423s .. .. .. ..$ nbrOfGenotypeGroups: int 3 423s .. .. .. ..$ tau : num [1:2] 0.315 0.677 423s .. .. .. ..$ n : int 14640 423s .. .. .. ..$ fit :Classes 'PeaksAndValleys' and 'data.frame': 5 obs. of 3 variables: 423s .. .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 423s .. .. .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 423s .. .. .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 423s .. .. .. ..$ fitValleys :Classes 'PeaksAndValleys' and 'data.frame': 2 obs. of 3 variables: 423s .. .. .. .. ..$ type : chr [1:2] "valley" "valley" 423s .. .. .. .. ..$ x : num [1:2] 0.315 0.677 423s .. .. .. .. ..$ density: num [1:2] 0.522 0.551 423s .. .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 423s ..$ preserveScale: logi FALSE 423s ..$ scaleFactor : num NA 423s Normalizing betaT using betaN (TumorBoost)...done 423s Setup up data... 423s 'data.frame': 14670 obs. of 7 variables: 423s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 423s $ x : num 1145994 2941694 3710825 4240737 4276892 ... 423s $ CT : num 1.63 1.4 1.41 1.17 1.16 ... 423s $ betaT : num 0.7574 0.169 0.2357 0.2604 0.0576 ... 423s $ betaTN : num 0.9301 0.1667 0.0685 0.0995 0.0155 ... 423s ..- attr(*, "modelFit")=List of 5 423s .. ..$ method : chr "normalizeTumorBoost" 423s .. ..$ flavor : chr "v4" 423s .. ..$ delta : num [1:14670] -0.17264 0.00239 0.1671 0.16085 0.04213 ... 423s .. .. ..- attr(*, "modelFit")=List of 1 423s .. .. .. ..$ :List of 7 423s .. .. .. .. ..$ flavor : chr "density" 423s .. .. .. .. ..$ cn : int 2 423s .. .. .. .. ..$ nbrOfGenotypeGroups: int 3 423s .. .. .. .. ..$ tau : num [1:2] 0.315 0.677 423s .. .. .. .. ..$ n : int 14640 423s .. .. .. .. ..$ fit :Classes 'PeaksAndValleys' and 'data.frame': 5 obs. of 3 variables: 423s .. .. .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 423s .. .. .. .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 423s .. .. .. .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 423s .. .. .. .. ..$ fitValleys :Classes 'PeaksAndValleys' and 'data.frame': 2 obs. of 3 variables: 423s .. .. .. .. .. ..$ type : chr [1:2] "valley" "valley" 423s .. .. .. .. .. ..$ x : num [1:2] 0.315 0.677 423s .. .. .. .. .. ..$ density: num [1:2] 0.522 0.551 423s .. .. .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 423s .. ..$ preserveScale: logi FALSE 423s .. ..$ scaleFactor : num NA 423s $ betaN : num 0.8274 0.5072 0.1671 0.1609 0.0421 ... 423s $ muN : num 1 0.5 0 0 0 0 1 0 1 0.5 ... 423s ..- attr(*, "modelFit")=List of 1 423s .. ..$ :List of 7 423s .. .. ..$ flavor : chr "density" 423s .. .. ..$ cn : int 2 423s .. .. ..$ nbrOfGenotypeGroups: int 3 423s .. .. ..$ tau : num [1:2] 0.315 0.677 423s .. .. ..$ n : int 14640 423s .. .. ..$ fit :Classes 'PeaksAndValleys' and 'data.frame': 5 obs. of 3 variables: 423s .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 423s .. .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 423s .. .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 423s .. .. ..$ fitValleys :Classes 'PeaksAndValleys' and 'data.frame': 2 obs. of 3 variables: 423s .. .. .. ..$ type : chr [1:2] "valley" "valley" 423s .. .. .. ..$ x : num [1:2] 0.315 0.677 423s .. .. .. ..$ density: num [1:2] 0.522 0.551 423s .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 423s Setup up data...done 423s Dropping loci for which TCNs are missing... 423s Number of loci dropped: 12 423s Dropping loci for which TCNs are missing...done 423s Ordering data along genome... 423s 'data.frame': 14658 obs. of 7 variables: 423s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 423s $ x : num 554484 730720 782343 878522 916294 ... 423s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 423s $ betaT : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 423s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 423s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 423s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 423s Ordering data along genome...done 423s Keeping only current chromosome for 'knownSegments'... 423s Chromosome: 1 423s Known segments for this chromosome: 423s chromosome start end 423s 1 1 -Inf 120992603 423s 2 1 NA NA 423s 3 1 141510003 Inf 423s Keeping only current chromosome for 'knownSegments'...done 423s alphaTCN: 0.009 423s alphaDH: 0.001 423s Number of loci: 14658 423s Calculating DHs... 423s Number of SNPs: 14658 423s Number of heterozygous SNPs: 4196 (28.63%) 423s Normalized DHs: 423s num [1:14658] NA NA NA NA NA ... 423s Calculating DHs...done 423s Random seed temporarily set (seed=c(48879), kind="L'Ecuyer-CMRG") 423s Produced 2 seeds from this stream for future usage 423s Identification of change points by total copy numbers... 423s Segmenting by CBS... 423s Chromosome: 1 423s Segmenting multiple segments on current chromosome... 423s Number of segments: 3 423s Random seed temporarily set (seed=c(10407, 1066287653, -51199871, 161854402, -1995183193, 1503453565, -747102133), kind="L'Ecuyer-CMRG") 423s Produced 3 seeds from this stream for future usage 423s Segmenting by CBS... 423s Chromosome: 1 423s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 423s Segmenting by CBS...done 423s Segmenting by CBS... 423s Chromosome: 1 423s Random seed temporarily set (seed=c(10407, -1924040949, -1632234809, -437763632, -1464377300, 676654412, 2080370711), kind="L'Ecuyer-CMRG") 423s Segmenting by CBS...done 423s Segmenting multiple segments on current chromosome...done 423s Segmenting by CBS...done 423s List of 4 423s $ data :'data.frame': 14658 obs. of 4 variables: 423s ..$ chromosome: int [1:14658] 1 1 1 1 1 1 1 1 1 1 ... 423s ..$ x : num [1:14658] 554484 730720 782343 878522 916294 ... 423s ..$ y : num [1:14658] 1.88 1.8 1.59 1.64 1.53 ... 423s ..$ index : int [1:14658] 1 2 3 4 5 6 7 8 9 10 ... 423s $ output :'data.frame': 4 obs. of 6 variables: 423s ..$ sampleName: chr [1:4] NA NA NA NA 423s ..$ chromosome: int [1:4] 1 NA 1 1 423s ..$ start : num [1:4] 5.54e+05 NA 1.42e+08 1.85e+08 423s ..$ end : num [1:4] 1.21e+08 NA 1.85e+08 2.47e+08 423s ..$ nbrOfLoci : int [1:4] 7586 NA 2681 4391 423s ..$ mean : num [1:4] 1.39 NA 2.07 2.63 423s $ segRows:'data.frame': 4 obs. of 2 variables: 423s ..$ startRow: int [1:4] 1 NA 7587 10268 423s ..$ endRow : int [1:4] 7586 NA 10267 14658 423s $ params :List of 5 423s ..$ alpha : num 0.009 423s ..$ undo : num 0 423s ..$ joinSegments : logi TRUE 423s ..$ knownSegments:'data.frame': 4 obs. of 3 variables: 423s .. ..$ chromosome: num [1:4] 1 1 2 1 423s .. ..$ start : num [1:4] -Inf -Inf -Inf 1.42e+08 423s .. ..$ end : num [1:4] 1.21e+08 Inf Inf Inf 423s ..$ seed : int [1:7] 10407 1066287653 -51199871 161854402 -1995183193 1503453565 -747102133 423s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 423s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.128 0 0.128 0 0 423s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 423s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 423s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 423s Identification of change points by total copy numbers...done 423s Restructure TCN segmentation results... 423s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean 423s 1 1 554484 120992603 7586 1.3853 423s 2 NA NA NA NA NA 423s 3 1 141510003 185449813 2681 2.0689 423s 4 1 185449813 247137334 4391 2.6341 423s Number of TCN segments: 4 423s Restructure TCN segmentation results...done 423s Total CN segment #1 ([ 554484,1.20993e+08]) of 4... 423s Number of TCN loci in segment: 7586 423s Locus data for TCN segment: 423s 'data.frame': 7586 obs. of 9 variables: 423s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 423s $ x : num 554484 730720 782343 878522 916294 ... 423s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 423s $ betaT : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 423s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 423s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 423s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 423s $ index : int 1 2 3 4 5 6 7 8 9 10 ... 423s $ rho : num NA NA NA NA NA ... 423s Number of loci: 7586 423s Number of SNPs: 2108 (27.79%) 423s Number of heterozygous SNPs: 2108 (100.00%) 423s Chromosome: 1 423s Segmenting DH signals... 423s Segmenting by CBS... 423s Chromosome: 1 423s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 423s Segmenting by CBS...done 423s List of 4 423s $ data :'data.frame': 7586 obs. of 4 variables: 423s ..$ chromosome: int [1:7586] 1 1 1 1 1 1 1 1 1 1 ... 423s ..$ x : num [1:7586] 554484 730720 782343 878522 916294 ... 423s ..$ y : num [1:7586] NA NA NA NA NA ... 423s ..$ index : int [1:7586] 1 2 3 4 5 6 7 8 9 10 ... 423s $ output :'data.frame': 1 obs. of 6 variables: 423s ..$ sampleName: chr NA 423s ..$ chromosome: int 1 423s ..$ start : num 554484 423s ..$ end : num 1.21e+08 423s ..$ nbrOfLoci : int 2108 423s ..$ mean : num 0.512 423s $ segRows:'data.frame': 1 obs. of 2 variables: 423s ..$ startRow: int 10 423s ..$ endRow : int 7574 423s $ params :List of 5 423s ..$ alpha : num 0.001 423s ..$ undo : num 0 423s ..$ joinSegments : logi TRUE 423s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 423s .. ..$ chromosome: int 1 423s .. ..$ start : num 554484 423s .. ..$ end : num 1.21e+08 423s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 423s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 423s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.037 0 0.037 0 0 423s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 423s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 423s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 423s DH segmentation (locally-indexed) rows: 423s startRow endRow 423s 1 10 7574 423s int [1:7586] 1 2 3 4 5 6 7 8 9 10 ... 423s DH segmentation rows: 423s startRow endRow 423s 1 10 7574 423s Segmenting DH signals...done 423s DH segmentation table: 423s dhStart dhEnd dhNbrOfLoci dhMean 423s 1 554484 120992603 2108 0.5116 423s startRow endRow 423s 1 10 7574 423s Rows: 423s [1] 1 423s TCN segmentation rows: 423s startRow endRow 423s 1 1 7586 423s TCN and DH segmentation rows: 423s startRow endRow 423s 1 1 7586 423s startRow endRow 423s 1 10 7574 423s NULL 423s TCN segmentation (expanded) rows: 423s startRow endRow 423s 1 1 7586 423s TCN and DH segmentation rows: 423s startRow endRow 423s 1 1 7586 423s 2 NA NA 423s 3 7587 10267 423s 4 10268 14658 423s startRow endRow 423s 1 10 7574 423s startRow endRow 423s 1 1 7586 423s Total CN segmentation table (expanded): 423s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 423s 1 1 554484 120992603 7586 1.3853 2108 2108 423s (TCN,DH) segmentation for one total CN segment: 423s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 423s 1 1 1 1 554484 120992603 7586 1.3853 2108 423s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 423s 1 2108 554484 120992603 2108 0.5116 423s Total CN segment #1 ([ 554484,1.20993e+08]) of 4...done 423s Total CN segment #2 ([ NA, NA]) of 4... 423s No signals to segment. Just a "splitter" segment. Skipping. 423s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 424s NA 2 1 NA NA NA NA NA 0 424s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 424s NA 0 NA NA 0 NA 424s Total CN segment #2 ([ NA, NA]) of 4...done 424s Total CN segment #3 ([1.4151e+08,1.8545e+08]) of 4... 424s Number of TCN loci in segment: 2681 424s Locus data for TCN segment: 424s 'data.frame': 2681 obs. of 9 variables: 424s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 424s $ x : num 1.43e+08 1.43e+08 1.43e+08 1.43e+08 1.44e+08 ... 424s $ CT : num 2.27 1.55 1.47 1.5 1.81 ... 424s $ betaT : num 0.34 0.55 0.048 0.813 0.575 ... 424s $ betaTN : num 0.441 0.629 -0.05 0.958 0.872 ... 424s $ betaN : num 0.3851 0.3933 0.0981 0.8552 0.7028 ... 424s $ muN : num 0.5 0.5 0 1 1 1 1 0.5 1 1 ... 424s $ index : int 7587 7588 7589 7590 7591 7592 7593 7594 7595 7596 ... 424s $ rho : num 0.117 0.258 NA NA NA ... 424s Number of loci: 2681 424s Number of SNPs: 777 (28.98%) 424s Number of heterozygous SNPs: 777 (100.00%) 424s Chromosome: 1 424s Segmenting DH signals... 424s Segmenting by CBS... 424s Chromosome: 1 424s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 424s Segmenting by CBS...done 424s List of 4 424s $ data :'data.frame': 2681 obs. of 4 variables: 424s ..$ chromosome: int [1:2681] 1 1 1 1 1 1 1 1 1 1 ... 424s ..$ x : num [1:2681] 1.43e+08 1.43e+08 1.43e+08 1.43e+08 1.44e+08 ... 424s ..$ y : num [1:2681] 0.117 0.258 NA NA NA ... 424s ..$ index : int [1:2681] 1 2 3 4 5 6 7 8 9 10 ... 424s $ output :'data.frame': 1 obs. of 6 variables: 424s ..$ sampleName: chr NA 424s ..$ chromosome: int 1 424s ..$ start : num 1.42e+08 424s ..$ end : num 1.85e+08 424s ..$ nbrOfLoci : int 777 424s ..$ mean : num 0.0973 424s $ segRows:'data.frame': 1 obs. of 2 variables: 424s ..$ startRow: int 1 424s ..$ endRow : int 2677 424s $ params :List of 5 424s ..$ alpha : num 0.001 424s ..$ undo : num 0 424s ..$ joinSegments : logi TRUE 424s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 424s .. ..$ chromosome: int 1 424s .. ..$ start : num 1.42e+08 424s .. ..$ end : num 1.85e+08 424s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 424s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 424s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.008 0 0.008 0 0 424s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 424s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 424s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 424s DH segmentation (locally-indexed) rows: 424s startRow endRow 424s 1 1 2677 424s int [1:2681] 7587 7588 7589 7590 7591 7592 7593 7594 7595 7596 ... 424s DH segmentation rows: 424s startRow endRow 424s 1 7587 10263 424s Segmenting DH signals...done 424s DH segmentation table: 424s dhStart dhEnd dhNbrOfLoci dhMean 424s 1 141510003 185449813 777 0.0973 424s startRow endRow 424s 1 7587 10263 424s Rows: 424s [1] 3 424s TCN segmentation rows: 424s startRow endRow 424s 3 7587 10267 424s TCN and DH segmentation rows: 424s startRow endRow 424s 3 7587 10267 424s startRow endRow 424s 1 7587 10263 424s startRow endRow 424s 1 1 7586 424s NA NA NA 424s TCN segmentation (expanded) rows: 424s startRow endRow 424s 1 1 7586 424s NA NA NA 424s 3 7587 10267 424s TCN and DH segmentation rows: 424s startRow endRow 424s 1 1 7586 424s 2 NA NA 424s 3 7587 10267 424s 4 10268 14658 424s startRow endRow 424s 1 10 7574 424s 2 NA NA 424s 3 7587 10263 424s startRow endRow 424s 1 1 7586 424s 2 NA NA 424s 3 7587 10267 424s Total CN segmentation table (expanded): 424s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 424s 3 1 141510003 185449813 2681 2.0689 777 777 424s (TCN,DH) segmentation for one total CN segment: 424s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 424s 3 3 1 1 141510003 185449813 2681 2.0689 777 424s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 424s 3 777 141510003 185449813 777 0.0973 424s Total CN segment #3 ([1.4151e+08,1.8545e+08]) of 4...done 424s Total CN segment #4 ([1.8545e+08,2.47137e+08]) of 4... 424s Number of TCN loci in segment: 4391 424s Locus data for TCN segment: 424s 'data.frame': 4391 obs. of 9 variables: 424s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 424s $ x : num 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 424s $ CT : num 2.93 2.15 2.82 2.93 2.46 ... 424s $ betaT : num 0.0811 0.5154 0.9473 0.3734 0.7506 ... 424s $ betaTN : num -0.169 0.609 1.028 0.525 0.968 ... 424s $ betaN : num 0.25 0.38 0.919 0.34 0.783 ... 424s $ muN : num 0 0.5 1 0.5 1 1 0 1 0 1 ... 424s $ index : int 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 424s $ rho : num NA 0.2186 NA 0.0503 NA ... 424s Number of loci: 4391 424s Number of SNPs: 1311 (29.86%) 424s Number of heterozygous SNPs: 1311 (100.00%) 424s Chromosome: 1 424s Segmenting DH signals... 424s Segmenting by CBS... 424s Chromosome: 1 424s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 424s Segmenting by CBS...done 424s List of 4 424s $ data :'data.frame': 4391 obs. of 4 variables: 424s ..$ chromosome: int [1:4391] 1 1 1 1 1 1 1 1 1 1 ... 424s ..$ x : num [1:4391] 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 424s ..$ y : num [1:4391] NA 0.2186 NA 0.0503 NA ... 424s ..$ index : int [1:4391] 1 2 3 4 5 6 7 8 9 10 ... 424s $ output :'data.frame': 1 obs. of 6 variables: 424s ..$ sampleName: chr NA 424s ..$ chromosome: int 1 424s ..$ start : num 1.85e+08 424s ..$ end : num 2.47e+08 424s ..$ nbrOfLoci : int 1311 424s ..$ mean : num 0.23 424s $ segRows:'data.frame': 1 obs. of 2 variables: 424s ..$ startRow: int 2 424s ..$ endRow : int 4388 424s $ params :List of 5 424s ..$ alpha : num 0.001 424s ..$ undo : num 0 424s ..$ joinSegments : logi TRUE 424s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 424s .. ..$ chromosome: int 1 424s .. ..$ start : num 1.85e+08 424s .. ..$ end : num 2.47e+08 424s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 424s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 424s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.015 0 0.015 0 0 424s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 424s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 424s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 424s DH segmentation (locally-indexed) rows: 424s startRow endRow 424s 1 2 4388 424s int [1:4391] 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 424s DH segmentation rows: 424s startRow endRow 424s 1 10269 14655 424s Segmenting DH signals...done 424s DH segmentation table: 424s dhStart dhEnd dhNbrOfLoci dhMean 424s 1 185449813 247137334 1311 0.2295 424s startRow endRow 424s 1 10269 14655 424s Rows: 424s [1] 4 424s TCN segmentation rows: 424s startRow endRow 424s 4 10268 14658 424s TCN and DH segmentation rows: 424s startRow endRow 424s 4 10268 14658 424s startRow endRow 424s 1 10269 14655 424s startRow endRow 424s 1 1 7586 424s 2 NA NA 424s 3 7587 10267 424s TCN segmentation (expanded) rows: 424s startRow endRow 424s 1 1 7586 424s 2 NA NA 424s 3 7587 10267 424s 4 10268 14658 424s TCN and DH segmentation rows: 424s startRow endRow 424s 1 1 7586 424s 2 NA NA 424s 3 7587 10267 424s 4 10268 14658 424s startRow endRow 424s 1 10 7574 424s 2 NA NA 424s 3 7587 10263 424s 4 10269 14655 424s startRow endRow 424s 1 1 7586 424s 2 NA NA 424s 3 7587 10267 424s 4 10268 14658 424s Total CN segmentation table (expanded): 424s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 424s 4 1 185449813 247137334 4391 2.6341 1311 1311 424s (TCN,DH) segmentation for one total CN segment: 424s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 424s 4 4 1 1 185449813 247137334 4391 2.6341 1311 424s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 424s 4 1311 185449813 247137334 1311 0.2295 424s Total CN segment #4 ([1.8545e+08,2.47137e+08]) of 4...done 424s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 424s 1 1 1 1 554484 120992603 7586 1.3853 2108 424s 2 NA 2 1 NA NA NA NA 0 424s 3 1 3 1 141510003 185449813 2681 2.0689 777 424s 4 1 4 1 185449813 247137334 4391 2.6341 1311 424s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 424s 1 2108 554484 120992603 2108 0.5116 424s 2 0 NA NA 0 NA 424s 3 777 141510003 185449813 777 0.0973 424s 4 1311 185449813 247137334 1311 0.2295 424s Calculating (C1,C2) per segment... 424s Calculating (C1,C2) per segment...done 424s Number of segments: 4 424s Segmenting paired tumor-normal signals using Paired PSCBS...done 424s Post-segmenting TCNs... 424s Number of segments: 3 424s Number of chromosomes: 1 424s [1] 1 424s Chromosome 1 ('chr01') of 1... 424s Rows: 424s [1] 1 2 3 424s Number of segments: 3 424s TCN segment #1 ('1') of 3... 424s Nothing todo. Only one DH segmentation. Skipping. 424s TCN segment #1 ('1') of 3...done 424s TCN segment #2 ('3') of 3... 424s Nothing todo. Only one DH segmentation. Skipping. 424s TCN segment #2 ('3') of 3...done 424s TCN segment #3 ('4') of 3... 424s Nothing todo. Only one DH segmentation. Skipping. 424s TCN segment #3 ('4') of 3...done 424s Chromosome 1 ('chr01') of 1...done 424s Update (C1,C2) per segment... 424s Update (C1,C2) per segment...done 424s Post-segmenting TCNs...done 424s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 424s 1 1 1 1 554484 120992603 7586 1.3853 2108 424s 2 NA 2 1 NA NA NA NA 0 424s 3 1 3 1 141510003 185449813 2681 2.0689 777 424s 4 1 4 1 185449813 247137334 4391 2.6341 1311 424s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 424s 1 2108 554484 120992603 2108 0.5116 0.3382903 1.047010 424s 2 0 NA NA 0 NA NA NA 424s 3 777 141510003 185449813 777 0.0973 0.9337980 1.135102 424s 4 1311 185449813 247137334 1311 0.2295 1.0147870 1.619313 424s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 424s 1 1 1 1 554484 120992603 7586 1.3853 2108 424s 2 NA 2 1 NA NA NA NA 0 424s 3 1 3 1 141510003 185449813 2681 2.0689 777 424s 4 1 4 1 185449813 247137334 4391 2.6341 1311 424s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 424s 1 2108 554484 120992603 2108 0.5116 0.3382903 1.047010 424s 2 0 NA NA 0 NA NA NA 424s 3 777 141510003 185449813 777 0.0973 0.9337980 1.135102 424s 4 1311 185449813 247137334 1311 0.2295 1.0147870 1.619313 424s > print(fit) 424s chromosome tcnId dhId start end tcnNbrOfLoci tcnMean tcnNbrOfSNPs 424s 1 1 1 1 554484 120992603 7586 1.3853 2108 424s 2 NA 2 1 NA NA NA NA 0 424s 3 1 3 1 141510003 185449813 2681 2.0689 777 424s 4 1 4 1 185449813 247137334 4391 2.6341 1311 424s tcnNbrOfHets dhNbrOfLoci dhMean c1Mean c2Mean 424s 1 2108 2108 0.5116 0.3382903 1.047010 424s 2 0 0 NA NA NA 424s 3 777 777 0.0973 0.9337980 1.135102 424s 4 1311 1311 0.2295 1.0147870 1.619313 424s > 424s > # Plot results 424s > dev.set(2L) 424s null device 424s 1 424s > plotTracks(fit) 424s > abline(v=c(knownSegments$start, knownSegments$end)/1e6, lty=3) 424s > 424s > # Sanity check 424s > stopifnot(nbrOfSegments(fit) == nSegs) 424s > 424s > fit1 <- fit 424s > 424s > 424s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 424s > # (b) Segment also the centromere (which will become NAs) 424s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 424s > knownSegments <- data.frame( 424s + chromosome = c( 1, 1, 1), 424s + start = c( -Inf, 120992604, 141510003), 424s + end = c(120992603, 141510002, +Inf) 424s + ) 424s > 424s > 424s > # Paired PSCBS segmentation 424s > fit <- segmentByPairedPSCBS(dataS, knownSegments=knownSegments, 424s + seed=0xBEEF, verbose=-10) 424s Segmenting paired tumor-normal signals using Paired PSCBS... 424s Calling genotypes from normal allele B fractions... 424s num [1:14670] 0.8274 0.5072 0.1671 0.1609 0.0421 ... 424s Called genotypes: 424s num [1:14670] 1 0.5 0 0 0 0 1 0 1 0.5 ... 424s - attr(*, "modelFit")=List of 1 424s ..$ :List of 7 424s .. ..$ flavor : chr "density" 424s .. ..$ cn : int 2 424s .. ..$ nbrOfGenotypeGroups: int 3 424s .. ..$ tau : num [1:2] 0.315 0.677 424s .. ..$ n : int 14640 424s .. ..$ fit :Classes 'PeaksAndValleys' and 'data.frame': 5 obs. of 3 variables: 424s .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 424s .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 424s .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 424s .. ..$ fitValleys :Classes 'PeaksAndValleys' and 'data.frame': 2 obs. of 3 variables: 424s .. .. ..$ type : chr [1:2] "valley" "valley" 424s .. .. ..$ x : num [1:2] 0.315 0.677 424s .. .. ..$ density: num [1:2] 0.522 0.551 424s ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 424s muN 424s 0 0.5 1 424s 5221 4198 5251 424s Calling genotypes from normal allele B fractions...done 424s Normalizing betaT using betaN (TumorBoost)... 424s Normalized BAFs: 424s num [1:14670] 0.9301 0.1667 0.0685 0.0995 0.0155 ... 424s - attr(*, "modelFit")=List of 5 424s ..$ method : chr "normalizeTumorBoost" 424s ..$ flavor : chr "v4" 424s ..$ delta : num [1:14670] -0.17264 0.00239 0.1671 0.16085 0.04213 ... 424s .. ..- attr(*, "modelFit")=List of 1 424s .. .. ..$ :List of 7 424s .. .. .. ..$ flavor : chr "density" 424s .. .. .. ..$ cn : int 2 424s .. .. .. ..$ nbrOfGenotypeGroups: int 3 424s .. .. .. ..$ tau : num [1:2] 0.315 0.677 424s .. .. .. ..$ n : int 14640 424s .. .. .. ..$ fit :Classes 'PeaksAndValleys' and 'data.frame': 5 obs. of 3 variables: 424s .. .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 424s .. .. .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 424s .. .. .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 424s .. .. .. ..$ fitValleys :Classes 'PeaksAndValleys' and 'data.frame': 2 obs. of 3 variables: 424s .. .. .. .. ..$ type : chr [1:2] "valley" "valley" 424s .. .. .. .. ..$ x : num [1:2] 0.315 0.677 424s .. .. .. .. ..$ density: num [1:2] 0.522 0.551 424s .. .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 424s ..$ preserveScale: logi FALSE 424s ..$ scaleFactor : num NA 424s Normalizing betaT using betaN (TumorBoost)...done 424s Setup up data... 424s 'data.frame': 14670 obs. of 7 variables: 424s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 424s $ x : num 1145994 2941694 3710825 4240737 4276892 ... 424s $ CT : num 1.63 1.4 1.41 1.17 1.16 ... 424s $ betaT : num 0.7574 0.169 0.2357 0.2604 0.0576 ... 424s $ betaTN : num 0.9301 0.1667 0.0685 0.0995 0.0155 ... 424s ..- attr(*, "modelFit")=List of 5 424s .. ..$ method : chr "normalizeTumorBoost" 424s .. ..$ flavor : chr "v4" 424s .. ..$ delta : num [1:14670] -0.17264 0.00239 0.1671 0.16085 0.04213 ... 424s .. .. ..- attr(*, "modelFit")=List of 1 424s .. .. .. ..$ :List of 7 424s .. .. .. .. ..$ flavor : chr "density" 424s .. .. .. .. ..$ cn : int 2 424s .. .. .. .. ..$ nbrOfGenotypeGroups: int 3 424s .. .. .. .. ..$ tau : num [1:2] 0.315 0.677 424s .. .. .. .. ..$ n : int 14640 424s .. .. .. .. ..$ fit :Classes 'PeaksAndValleys' and 'data.frame': 5 obs. of 3 variables: 424s .. .. .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 424s .. .. .. .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 424s .. .. .. .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 424s .. .. .. .. ..$ fitValleys :Classes 'PeaksAndValleys' and 'data.frame': 2 obs. of 3 variables: 424s .. .. .. .. .. ..$ type : chr [1:2] "valley" "valley" 424s .. .. .. .. .. ..$ x : num [1:2] 0.315 0.677 424s .. .. .. .. .. ..$ density: num [1:2] 0.522 0.551 424s .. .. .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 424s .. ..$ preserveScale: logi FALSE 424s .. ..$ scaleFactor : num NA 424s $ betaN : num 0.8274 0.5072 0.1671 0.1609 0.0421 ... 424s $ muN : num 1 0.5 0 0 0 0 1 0 1 0.5 ... 424s ..- attr(*, "modelFit")=List of 1 424s .. ..$ :List of 7 424s .. .. ..$ flavor : chr "density" 424s .. .. ..$ cn : int 2 424s .. .. ..$ nbrOfGenotypeGroups: int 3 424s .. .. ..$ tau : num [1:2] 0.315 0.677 424s .. .. ..$ n : int 14640 424s .. .. ..$ fit :Classes 'PeaksAndValleys' and 'data.frame': 5 obs. of 3 variables: 424s .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 424s .. .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 424s .. .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 424s .. .. ..$ fitValleys :Classes 'PeaksAndValleys' and 'data.frame': 2 obs. of 3 variables: 424s .. .. .. ..$ type : chr [1:2] "valley" "valley" 424s .. .. .. ..$ x : num [1:2] 0.315 0.677 424s .. .. .. ..$ density: num [1:2] 0.522 0.551 424s .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 424s Setup up data...done 424s Dropping loci for which TCNs are missing... 424s Number of loci dropped: 12 424s Dropping loci for which TCNs are missing...done 424s Ordering data along genome... 424s 'data.frame': 14658 obs. of 7 variables: 424s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 424s $ x : num 554484 730720 782343 878522 916294 ... 424s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 424s $ betaT : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 424s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 424s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 424s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 424s Ordering data along genome...done 424s Keeping only current chromosome for 'knownSegments'... 424s Chromosome: 1 424s Known segments for this chromosome: 424s chromosome start end 424s 1 1 -Inf 120992603 424s 2 1 120992604 141510002 424s 3 1 141510003 Inf 424s Keeping only current chromosome for 'knownSegments'...done 424s alphaTCN: 0.009 424s alphaDH: 0.001 424s Number of loci: 14658 424s Calculating DHs... 424s Number of SNPs: 14658 424s Number of heterozygous SNPs: 4196 (28.63%) 424s Normalized DHs: 424s num [1:14658] NA NA NA NA NA ... 424s Calculating DHs...done 424s Random seed temporarily set (seed=c(48879), kind="L'Ecuyer-CMRG") 424s Produced 2 seeds from this stream for future usage 424s Identification of change points by total copy numbers... 424s Segmenting by CBS... 424s Chromosome: 1 424s Segmenting multiple segments on current chromosome... 424s Number of segments: 3 424s Random seed temporarily set (seed=c(10407, 1066287653, -51199871, 161854402, -1995183193, 1503453565, -747102133), kind="L'Ecuyer-CMRG") 424s Produced 3 seeds from this stream for future usage 424s Segmenting by CBS... 424s Chromosome: 1 424s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 424s Segmenting by CBS...done 424s Segmenting by CBS... 424s Chromosome: 1 424s Random seed temporarily set (seed=c(10407, -1924040949, -1632234809, -437763632, -1464377300, 676654412, 2080370711), kind="L'Ecuyer-CMRG") 424s Segmenting by CBS...done 424s Segmenting multiple segments on current chromosome...done 424s Segmenting by CBS...done 424s List of 4 424s $ data :'data.frame': 14658 obs. of 4 variables: 424s ..$ chromosome: int [1:14658] 1 1 1 1 1 1 1 1 1 1 ... 424s ..$ x : num [1:14658] 554484 730720 782343 878522 916294 ... 424s ..$ y : num [1:14658] 1.88 1.8 1.59 1.64 1.53 ... 424s ..$ index : int [1:14658] 1 2 3 4 5 6 7 8 9 10 ... 424s $ output :'data.frame': 4 obs. of 6 variables: 424s ..$ sampleName: chr [1:4] NA NA NA NA 424s ..$ chromosome: num [1:4] 1 1 1 1 424s ..$ start : num [1:4] 5.54e+05 1.21e+08 1.42e+08 1.85e+08 424s ..$ end : num [1:4] 1.21e+08 1.42e+08 1.85e+08 2.47e+08 424s ..$ nbrOfLoci : int [1:4] 7586 0 2681 4391 424s ..$ mean : num [1:4] 1.39 NA 2.07 2.63 424s $ segRows:'data.frame': 4 obs. of 2 variables: 424s ..$ startRow: int [1:4] 1 NA 7587 10268 424s ..$ endRow : int [1:4] 7586 NA 10267 14658 424s $ params :List of 5 424s ..$ alpha : num 0.009 424s ..$ undo : num 0 424s ..$ joinSegments : logi TRUE 424s ..$ knownSegments:'data.frame': 4 obs. of 3 variables: 424s .. ..$ chromosome: num [1:4] 1 1 2 1 424s .. ..$ start : num [1:4] -Inf -Inf -Inf 1.42e+08 424s .. ..$ end : num [1:4] 1.21e+08 Inf Inf Inf 424s ..$ seed : int [1:7] 10407 1066287653 -51199871 161854402 -1995183193 1503453565 -747102133 424s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 424s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.127 0 0.128 0 0 424s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 424s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 424s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 424s Identification of change points by total copy numbers...done 424s Restructure TCN segmentation results... 424s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean 424s 1 1 554484 120992603 7586 1.3853 424s 2 1 120992604 141510002 0 NA 424s 3 1 141510003 185449813 2681 2.0689 424s 4 1 185449813 247137334 4391 2.6341 424s Number of TCN segments: 4 424s Restructure TCN segmentation results...done 424s Total CN segment #1 ([ 554484,1.20993e+08]) of 4... 424s Number of TCN loci in segment: 7586 424s Locus data for TCN segment: 424s 'data.frame': 7586 obs. of 9 variables: 424s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 424s $ x : num 554484 730720 782343 878522 916294 ... 424s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 424s $ betaT : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 424s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 424s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 424s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 424s $ index : int 1 2 3 4 5 6 7 8 9 10 ... 424s $ rho : num NA NA NA NA NA ... 424s Number of loci: 7586 424s Number of SNPs: 2108 (27.79%) 424s Number of heterozygous SNPs: 2108 (100.00%) 424s Chromosome: 1 424s Segmenting DH signals... 424s Segmenting by CBS... 424s Chromosome: 1 424s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 424s Segmenting by CBS...done 424s List of 4 424s $ data :'data.frame': 7586 obs. of 4 variables: 424s ..$ chromosome: int [1:7586] 1 1 1 1 1 1 1 1 1 1 ... 424s ..$ x : num [1:7586] 554484 730720 782343 878522 916294 ... 424s ..$ y : num [1:7586] NA NA NA NA NA ... 424s ..$ index : int [1:7586] 1 2 3 4 5 6 7 8 9 10 ... 424s $ output :'data.frame': 1 obs. of 6 variables: 424s ..$ sampleName: chr NA 424s ..$ chromosome: int 1 424s ..$ start : num 554484 424s ..$ end : num 1.21e+08 424s ..$ nbrOfLoci : int 2108 424s ..$ mean : num 0.512 424s $ segRows:'data.frame': 1 obs. of 2 variables: 424s ..$ startRow: int 10 424s ..$ endRow : int 7574 424s $ params :List of 5 424s ..$ alpha : num 0.001 424s ..$ undo : num 0 424s ..$ joinSegments : logi TRUE 424s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 424s .. ..$ chromosome: int 1 424s .. ..$ start : num 554484 424s .. ..$ end : num 1.21e+08 424s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 424s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 424s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.038 0 0.038 0 0 424s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 424s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 424s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 424s DH segmentation (locally-indexed) rows: 424s startRow endRow 424s 1 10 7574 424s int [1:7586] 1 2 3 4 5 6 7 8 9 10 ... 424s DH segmentation rows: 424s startRow endRow 424s 1 10 7574 424s Segmenting DH signals...done 424s DH segmentation table: 424s dhStart dhEnd dhNbrOfLoci dhMean 424s 1 554484 120992603 2108 0.5116 424s startRow endRow 424s 1 10 7574 424s Rows: 424s [1] 1 424s TCN segmentation rows: 424s startRow endRow 424s 1 1 7586 424s TCN and DH segmentation rows: 424s startRow endRow 424s 1 1 7586 424s startRow endRow 424s 1 10 7574 424s NULL 424s TCN segmentation (expanded) rows: 424s startRow endRow 424s 1 1 7586 424s TCN and DH segmentation rows: 424s startRow endRow 424s 1 1 7586 424s 2 NA NA 424s 3 7587 10267 424s 4 10268 14658 424s startRow endRow 424s 1 10 7574 424s startRow endRow 424s 1 1 7586 424s Total CN segmentation table (expanded): 424s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 424s 1 1 554484 120992603 7586 1.3853 2108 2108 424s (TCN,DH) segmentation for one total CN segment: 424s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 424s 1 1 1 1 554484 120992603 7586 1.3853 2108 424s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 424s 1 2108 554484 120992603 2108 0.5116 424s Total CN segment #1 ([ 554484,1.20993e+08]) of 4...done 424s Total CN segment #2 ([1.20993e+08,1.4151e+08]) of 4... 424s Number of TCN loci in segment: 0 424s Locus data for TCN segment: 424s 'data.frame': 0 obs. of 9 variables: 424s $ chromosome: int 424s $ x : num 424s $ CT : num 424s $ betaT : num 424s $ betaTN : num 424s $ betaN : num 424s $ muN : num 424s $ index : int 424s $ rho : num 424s Number of loci: 0 424s Number of SNPs: 0 (NaN%) 424s Number of heterozygous SNPs: 0 (NaN%) 424s Chromosome: 1 424s Segmenting DH signals... 424s Segmenting by CBS... 424s Chromosome: NA 424s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 424s Segmenting by CBS...done 424s List of 4 424s $ data :'data.frame': 0 obs. of 4 variables: 424s ..$ chromosome: int(0) 424s ..$ x : num(0) 424s ..$ y : num(0) 424s ..$ index : int(0) 424s $ output :'data.frame': 0 obs. of 6 variables: 424s ..$ sampleName: chr(0) 424s ..$ chromosome: num(0) 424s ..$ start : num(0) 424s ..$ end : num(0) 424s ..$ nbrOfLoci : int(0) 424s ..$ mean : num(0) 424s $ segRows:'data.frame': 0 obs. of 2 variables: 424s ..$ startRow: int(0) 424s ..$ endRow : int(0) 424s $ params :List of 5 424s ..$ alpha : num 0.001 424s ..$ undo : num 0 424s ..$ joinSegments : logi TRUE 424s ..$ knownSegments:'data.frame': 0 obs. of 3 variables: 424s .. ..$ chromosome: int(0) 424s .. ..$ start : num(0) 424s .. ..$ end : num(0) 424s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 424s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 424s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.002 0 0.002 0 0 424s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 424s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 424s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 424s DH segmentation (locally-indexed) rows: 424s [1] startRow endRow 424s <0 rows> (or 0-length row.names) 424s int(0) 424s DH segmentation rows: 424s [1] startRow endRow 424s <0 rows> (or 0-length row.names) 424s Segmenting DH signals...done 424s DH segmentation table: 424s dhStart dhEnd dhNbrOfLoci dhMean 424s NA NA NA NA NA 424s startRow endRow 424s NA NA NA 424s Rows: 424s [1] 2 424s TCN segmentation rows: 424s startRow endRow 424s 2 NA NA 424s TCN and DH segmentation rows: 424s startRow endRow 424s 2 NA NA 424s startRow endRow 424s NA NA NA 424s startRow endRow 424s 1 1 7586 424s TCN segmentation (expanded) rows: 424s startRow endRow 424s 1 1 7586 424s 2 NA NA 424s TCN and DH segmentation rows: 424s startRow endRow 424s 1 1 7586 424s 2 NA NA 424s 3 7587 10267 424s 4 10268 14658 424s startRow endRow 424s 1 10 7574 424s 2 NA NA 424s startRow endRow 424s 1 1 7586 424s 2 NA NA 424s Total CN segmentation table (expanded): 424s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 424s 2 1 120992604 141510002 0 NA 0 0 424s (TCN,DH) segmentation for one total CN segment: 424s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 424s 2 2 1 1 120992604 141510002 0 NA 0 424s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 424s 2 0 NA NA NA NA 424s Total CN segment #2 ([1.20993e+08,1.4151e+08]) of 4...done 424s Total CN segment #3 ([1.4151e+08,1.8545e+08]) of 4... 424s Number of TCN loci in segment: 2681 424s Locus data for TCN segment: 424s 'data.frame': 2681 obs. of 9 variables: 424s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 424s $ x : num 1.43e+08 1.43e+08 1.43e+08 1.43e+08 1.44e+08 ... 424s $ CT : num 2.27 1.55 1.47 1.5 1.81 ... 424s $ betaT : num 0.34 0.55 0.048 0.813 0.575 ... 424s $ betaTN : num 0.441 0.629 -0.05 0.958 0.872 ... 424s $ betaN : num 0.3851 0.3933 0.0981 0.8552 0.7028 ... 424s $ muN : num 0.5 0.5 0 1 1 1 1 0.5 1 1 ... 424s $ index : int 7587 7588 7589 7590 7591 7592 7593 7594 7595 7596 ... 424s $ rho : num 0.117 0.258 NA NA NA ... 424s Number of loci: 2681 424s Number of SNPs: 777 (28.98%) 424s Number of heterozygous SNPs: 777 (100.00%) 424s Chromosome: 1 424s Segmenting DH signals... 424s Segmenting by CBS... 424s Chromosome: 1 424s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 424s Segmenting by CBS...done 424s List of 4 424s $ data :'data.frame': 2681 obs. of 4 variables: 424s ..$ chromosome: int [1:2681] 1 1 1 1 1 1 1 1 1 1 ... 424s ..$ x : num [1:2681] 1.43e+08 1.43e+08 1.43e+08 1.43e+08 1.44e+08 ... 424s ..$ y : num [1:2681] 0.117 0.258 NA NA NA ... 424s ..$ index : int [1:2681] 1 2 3 4 5 6 7 8 9 10 ... 424s $ output :'data.frame': 1 obs. of 6 variables: 424s ..$ sampleName: chr NA 424s ..$ chromosome: int 1 424s ..$ start : num 1.42e+08 424s ..$ end : num 1.85e+08 424s ..$ nbrOfLoci : int 777 424s ..$ mean : num 0.0973 424s $ segRows:'data.frame': 1 obs. of 2 variables: 424s ..$ startRow: int 1 424s ..$ endRow : int 2677 424s $ params :List of 5 424s ..$ alpha : num 0.001 424s ..$ undo : num 0 424s ..$ joinSegments : logi TRUE 424s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 424s .. ..$ chromosome: int 1 424s .. ..$ start : num 1.42e+08 424s .. ..$ end : num 1.85e+08 424s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 424s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 424s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.008 0 0.008 0 0 424s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 424s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 424s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 424s DH segmentation (locally-indexed) rows: 424s startRow endRow 424s 1 1 2677 424s int [1:2681] 7587 7588 7589 7590 7591 7592 7593 7594 7595 7596 ... 424s DH segmentation rows: 424s startRow endRow 424s 1 7587 10263 424s Segmenting DH signals...done 424s DH segmentation table: 424s dhStart dhEnd dhNbrOfLoci dhMean 424s 1 141510003 185449813 777 0.0973 424s startRow endRow 424s 1 7587 10263 424s Rows: 424s [1] 3 424s TCN segmentation rows: 424s startRow endRow 424s 3 7587 10267 424s TCN and DH segmentation rows: 424s startRow endRow 424s 3 7587 10267 424s startRow endRow 424s 1 7587 10263 424s startRow endRow 424s 1 1 7586 424s 2 NA NA 424s TCN segmentation (expanded) rows: 424s startRow endRow 424s 1 1 7586 424s 2 NA NA 424s 3 7587 10267 424s TCN and DH segmentation rows: 424s startRow endRow 424s 1 1 7586 424s 2 NA NA 424s 3 7587 10267 424s 4 10268 14658 424s startRow endRow 424s 1 10 7574 424s 2 NA NA 424s 3 7587 10263 424s startRow endRow 424s 1 1 7586 424s 2 NA NA 424s 3 7587 10267 424s Total CN segmentation table (expanded): 424s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 424s 3 1 141510003 185449813 2681 2.0689 777 777 424s (TCN,DH) segmentation for one total CN segment: 424s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 424s 3 3 1 1 141510003 185449813 2681 2.0689 777 424s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 424s 3 777 141510003 185449813 777 0.0973 424s Total CN segment #3 ([1.4151e+08,1.8545e+08]) of 4...done 424s Total CN segment #4 ([1.8545e+08,2.47137e+08]) of 4... 424s Number of TCN loci in segment: 4391 424s Locus data for TCN segment: 424s 'data.frame': 4391 obs. of 9 variables: 424s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 424s $ x : num 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 424s $ CT : num 2.93 2.15 2.82 2.93 2.46 ... 424s $ betaT : num 0.0811 0.5154 0.9473 0.3734 0.7506 ... 424s $ betaTN : num -0.169 0.609 1.028 0.525 0.968 ... 424s $ betaN : num 0.25 0.38 0.919 0.34 0.783 ... 424s $ muN : num 0 0.5 1 0.5 1 1 0 1 0 1 ... 424s $ index : int 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 424s $ rho : num NA 0.2186 NA 0.0503 NA ... 424s Number of loci: 4391 424s Number of SNPs: 1311 (29.86%) 424s Number of heterozygous SNPs: 1311 (100.00%) 424s Chromosome: 1 424s Segmenting DH signals... 424s Segmenting by CBS... 424s Chromosome: 1 424s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 424s Segmenting by CBS...done 424s List of 4 424s $ data :'data.frame': 4391 obs. of 4 variables: 424s ..$ chromosome: int [1:4391] 1 1 1 1 1 1 1 1 1 1 ... 424s ..$ x : num [1:4391] 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 424s ..$ y : num [1:4391] NA 0.2186 NA 0.0503 NA ... 424s ..$ index : int [1:4391] 1 2 3 4 5 6 7 8 9 10 ... 424s $ output :'data.frame': 1 obs. of 6 variables: 424s ..$ sampleName: chr NA 424s ..$ chromosome: int 1 424s ..$ start : num 1.85e+08 424s ..$ end : num 2.47e+08 424s ..$ nbrOfLoci : int 1311 424s ..$ mean : num 0.23 424s $ segRows:'data.frame': 1 obs. of 2 variables: 424s ..$ startRow: int 2 424s ..$ endRow : int 4388 424s $ params :List of 5 424s ..$ alpha : num 0.001 424s ..$ undo : num 0 424s ..$ joinSegments : logi TRUE 424s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 424s .. ..$ chromosome: int 1 424s .. ..$ start : num 1.85e+08 424s .. ..$ end : num 2.47e+08 424s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 424s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 424s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.015 0 0.015 0 0 424s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 424s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 424s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 424s DH segmentation (locally-indexed) rows: 424s startRow endRow 424s 1 2 4388 424s int [1:4391] 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 424s DH segmentation rows: 424s startRow endRow 424s 1 10269 14655 424s Segmenting DH signals...done 424s DH segmentation table: 424s dhStart dhEnd dhNbrOfLoci dhMean 424s 1 185449813 247137334 1311 0.2295 424s startRow endRow 424s 1 10269 14655 424s Rows: 424s [1] 4 424s TCN segmentation rows: 424s startRow endRow 424s 4 10268 14658 424s TCN and DH segmentation rows: 424s startRow endRow 424s 4 10268 14658 424s startRow endRow 424s 1 10269 14655 424s startRow endRow 424s 1 1 7586 424s 2 NA NA 424s 3 7587 10267 424s TCN segmentation (expanded) rows: 424s startRow endRow 424s 1 1 7586 424s 2 NA NA 424s 3 7587 10267 424s 4 10268 14658 424s TCN and DH segmentation rows: 424s startRow endRow 424s 1 1 7586 424s 2 NA NA 424s 3 7587 10267 424s 4 10268 14658 424s startRow endRow 424s 1 10 7574 424s 2 NA NA 424s 3 7587 10263 424s 4 10269 14655 424s startRow endRow 424s 1 1 7586 424s 2 NA NA 424s 3 7587 10267 424s 4 10268 14658 424s Total CN segmentation table (expanded): 424s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 424s 4 1 185449813 247137334 4391 2.6341 1311 1311 424s (TCN,DH) segmentation for one total CN segment: 424s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 424s 4 4 1 1 185449813 247137334 4391 2.6341 1311 424s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 424s 4 1311 185449813 247137334 1311 0.2295 424s Total CN segment #4 ([1.8545e+08,2.47137e+08]) of 4...done 424s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 424s 1 1 1 1 554484 120992603 7586 1.3853 2108 424s 2 1 2 1 120992604 141510002 0 NA 0 424s 3 1 3 1 141510003 185449813 2681 2.0689 777 424s 4 1 4 1 185449813 247137334 4391 2.6341 1311 424s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 424s 1 2108 554484 120992603 2108 0.5116 424s 2 0 NA NA NA NA 424s 3 777 141510003 185449813 777 0.0973 424s 4 1311 185449813 247137334 1311 0.2295 424s Calculating (C1,C2) per segment... 424s Calculating (C1,C2) per segment...done 424s Number of segments: 4 424s Segmenting paired tumor-normal signals using Paired PSCBS...done 424s Post-segmenting TCNs... 424s Number of segments: 4 424s Number of chromosomes: 1 424s [1] 1 424s Chromosome 1 ('chr01') of 1... 424s Rows: 424s [1] 1 2 3 4 424s Number of segments: 4 424s TCN segment #1 ('1') of 4... 424s Nothing todo. Only one DH segmentation. Skipping. 424s TCN segment #1 ('1') of 4...done 424s TCN segment #2 ('2') of 4... 424s Nothing todo. Only one DH segmentation. Skipping. 424s TCN segment #2 ('2') of 4...done 424s TCN segment #3 ('3') of 4... 424s Nothing todo. Only one DH segmentation. Skipping. 424s TCN segment #3 ('3') of 4...done 424s TCN segment #4 ('4') of 4... 424s Nothing todo. Only one DH segmentation. Skipping. 424s TCN segment #4 ('4') of 4...done 424s Chromosome 1 ('chr01') of 1...done 424s Update (C1,C2) per segment... 424s Update (C1,C2) per segment...done 424s Post-segmenting TCNs...done 424s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 424s 1 1 1 1 554484 120992603 7586 1.3853 2108 424s 2 1 2 1 120992604 141510002 0 NA 0 424s 3 1 3 1 141510003 185449813 2681 2.0689 777 424s 4 1 4 1 185449813 247137334 4391 2.6341 1311 424s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 424s 1 2108 554484 120992603 2108 0.5116 0.3382903 1.047010 424s 2 0 NA NA NA NA NA NA 424s 3 777 141510003 185449813 777 0.0973 0.9337980 1.135102 424s 4 1311 185449813 247137334 1311 0.2295 1.0147870 1.619313 424s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 424s 1 1 1 1 554484 120992603 7586 1.3853 2108 424s 2 1 2 1 120992604 141510002 0 NA 0 424s 3 1 3 1 141510003 185449813 2681 2.0689 777 424s 4 1 4 1 185449813 247137334 4391 2.6341 1311 424s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 424s 1 2108 554484 120992603 2108 0.5116 0.3382903 1.047010 424s 2 0 NA NA NA NA NA NA 424s 3 777 141510003 185449813 777 0.0973 0.9337980 1.135102 424s 4 1311 185449813 247137334 1311 0.2295 1.0147870 1.619313 424s > print(fit) 424s chromosome tcnId dhId start end tcnNbrOfLoci tcnMean tcnNbrOfSNPs 424s 1 1 1 1 554484 120992603 7586 1.3853 2108 424s 2 1 2 1 120992604 141510002 0 NA 0 424s 3 1 3 1 141510003 185449813 2681 2.0689 777 424s 4 1 4 1 185449813 247137334 4391 2.6341 1311 424s tcnNbrOfHets dhNbrOfLoci dhMean c1Mean c2Mean 424s 1 2108 2108 0.5116 0.3382903 1.047010 424s 2 0 NA NA NA NA 424s 3 777 777 0.0973 0.9337980 1.135102 424s 4 1311 1311 0.2295 1.0147870 1.619313 424s > 424s > # Plot results 424s > dev.set(3L) 424s pdf 424s 2 424s > plotTracks(fit) 424s > abline(v=c(knownSegments$start, knownSegments$end)/1e6, lty=3) 424s > 424s > # Sanity check [TO FIX: See above] 424s > stopifnot(nbrOfSegments(fit) == nSegs) 424s > 424s > fit2 <- fit 424s > 424s > 424s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 424s > # (c) Do not segment the centromere (without a separator) 424s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 424s > knownSegments <- data.frame( 424s + chromosome = c( 1, 1), 424s + start = c( -Inf, 141510003), 424s + end = c(120992603, +Inf) 424s + ) 424s > 424s > # Paired PSCBS segmentation 424s > fit <- segmentByPairedPSCBS(dataS, knownSegments=knownSegments, 424s + seed=0xBEEF, verbose=-10) 424s Segmenting paired tumor-normal signals using Paired PSCBS... 424s Calling genotypes from normal allele B fractions... 424s num [1:14670] 0.8274 0.5072 0.1671 0.1609 0.0421 ... 424s Called genotypes: 424s num [1:14670] 1 0.5 0 0 0 0 1 0 1 0.5 ... 424s - attr(*, "modelFit")=List of 1 424s ..$ :List of 7 424s .. ..$ flavor : chr "density" 424s .. ..$ cn : int 2 424s .. ..$ nbrOfGenotypeGroups: int 3 424s .. ..$ tau : num [1:2] 0.315 0.677 424s .. ..$ n : int 14640 424s .. ..$ fit :Classes 'PeaksAndValleys' and 'data.frame': 5 obs. of 3 variables: 424s .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 424s .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 424s .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 424s .. ..$ fitValleys :Classes 'PeaksAndValleys' and 'data.frame': 2 obs. of 3 variables: 424s .. .. ..$ type : chr [1:2] "valley" "valley" 424s .. .. ..$ x : num [1:2] 0.315 0.677 424s .. .. ..$ density: num [1:2] 0.522 0.551 424s ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 424s muN 424s 0 0.5 1 424s 5221 4198 5251 424s Calling genotypes from normal allele B fractions...done 424s Normalizing betaT using betaN (TumorBoost)... 424s Normalized BAFs: 424s num [1:14670] 0.9301 0.1667 0.0685 0.0995 0.0155 ... 424s - attr(*, "modelFit")=List of 5 424s ..$ method : chr "normalizeTumorBoost" 424s ..$ flavor : chr "v4" 424s ..$ delta : num [1:14670] -0.17264 0.00239 0.1671 0.16085 0.04213 ... 424s .. ..- attr(*, "modelFit")=List of 1 424s .. .. ..$ :List of 7 424s .. .. .. ..$ flavor : chr "density" 424s .. .. .. ..$ cn : int 2 424s .. .. .. ..$ nbrOfGenotypeGroups: int 3 424s .. .. .. ..$ tau : num [1:2] 0.315 0.677 424s .. .. .. ..$ n : int 14640 424s .. .. .. ..$ fit :Classes 'PeaksAndValleys' and 'data.frame': 5 obs. of 3 variables: 424s .. .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 424s .. .. .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 424s .. .. .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 424s .. .. .. ..$ fitValleys :Classes 'PeaksAndValleys' and 'data.frame': 2 obs. of 3 variables: 424s .. .. .. .. ..$ type : chr [1:2] "valley" "valley" 424s .. .. .. .. ..$ x : num [1:2] 0.315 0.677 424s .. .. .. .. ..$ density: num [1:2] 0.522 0.551 424s .. .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 424s ..$ preserveScale: logi FALSE 424s ..$ scaleFactor : num NA 424s Normalizing betaT using betaN (TumorBoost)...done 424s Setup up data... 424s 'data.frame': 14670 obs. of 7 variables: 424s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 424s $ x : num 1145994 2941694 3710825 4240737 4276892 ... 424s $ CT : num 1.63 1.4 1.41 1.17 1.16 ... 424s $ betaT : num 0.7574 0.169 0.2357 0.2604 0.0576 ... 424s $ betaTN : num 0.9301 0.1667 0.0685 0.0995 0.0155 ... 424s ..- attr(*, "modelFit")=List of 5 424s .. ..$ method : chr "normalizeTumorBoost" 424s .. ..$ flavor : chr "v4" 424s .. ..$ delta : num [1:14670] -0.17264 0.00239 0.1671 0.16085 0.04213 ... 424s .. .. ..- attr(*, "modelFit")=List of 1 424s .. .. .. ..$ :List of 7 424s .. .. .. .. ..$ flavor : chr "density" 424s .. .. .. .. ..$ cn : int 2 424s .. .. .. .. ..$ nbrOfGenotypeGroups: int 3 424s .. .. .. .. ..$ tau : num [1:2] 0.315 0.677 424s .. .. .. .. ..$ n : int 14640 424s .. .. .. .. ..$ fit :Classes 'PeaksAndValleys' and 'data.frame': 5 obs. of 3 variables: 424s .. .. .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 424s .. .. .. .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 424s .. .. .. .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 424s .. .. .. .. ..$ fitValleys :Classes 'PeaksAndValleys' and 'data.frame': 2 obs. of 3 variables: 424s .. .. .. .. .. ..$ type : chr [1:2] "valley" "valley" 424s .. .. .. .. .. ..$ x : num [1:2] 0.315 0.677 424s .. .. .. .. .. ..$ density: num [1:2] 0.522 0.551 424s .. .. .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 424s .. ..$ preserveScale: logi FALSE 424s .. ..$ scaleFactor : num NA 424s $ betaN : num 0.8274 0.5072 0.1671 0.1609 0.0421 ... 424s $ muN : num 1 0.5 0 0 0 0 1 0 1 0.5 ... 424s ..- attr(*, "modelFit")=List of 1 424s .. ..$ :List of 7 424s .. .. ..$ flavor : chr "density" 424s .. .. ..$ cn : int 2 424s .. .. ..$ nbrOfGenotypeGroups: int 3 424s .. .. ..$ tau : num [1:2] 0.315 0.677 424s .. .. ..$ n : int 14640 424s .. .. ..$ fit :Classes 'PeaksAndValleys' and 'data.frame': 5 obs. of 3 variables: 424s .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 424s .. .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 424s .. .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 424s .. .. ..$ fitValleys :Classes 'PeaksAndValleys' and 'data.frame': 2 obs. of 3 variables: 424s .. .. .. ..$ type : chr [1:2] "valley" "valley" 424s .. .. .. ..$ x : num [1:2] 0.315 0.677 424s .. .. .. ..$ density: num [1:2] 0.522 0.551 424s .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 424s Setup up data...done 424s Dropping loci for which TCNs are missing... 424s Number of loci dropped: 12 424s Dropping loci for which TCNs are missing...done 424s Ordering data along genome... 424s 'data.frame': 14658 obs. of 7 variables: 424s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 424s $ x : num 554484 730720 782343 878522 916294 ... 424s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 424s $ betaT : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 424s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 424s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 424s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 424s Ordering data along genome...done 424s Keeping only current chromosome for 'knownSegments'... 424s Chromosome: 1 424s Known segments for this chromosome: 424s chromosome start end 424s 1 1 -Inf 120992603 424s 2 1 141510003 Inf 424s Keeping only current chromosome for 'knownSegments'...done 424s alphaTCN: 0.009 424s alphaDH: 0.001 424s Number of loci: 14658 424s Calculating DHs... 424s Number of SNPs: 14658 424s Number of heterozygous SNPs: 4196 (28.63%) 424s Normalized DHs: 424s num [1:14658] NA NA NA NA NA ... 424s Calculating DHs...done 424s Random seed temporarily set (seed=c(48879), kind="L'Ecuyer-CMRG") 424s Produced 2 seeds from this stream for future usage 424s Identification of change points by total copy numbers... 424s Segmenting by CBS... 424s Chromosome: 1 424s Segmenting multiple segments on current chromosome... 424s Number of segments: 2 424s Random seed temporarily set (seed=c(10407, 1066287653, -51199871, 161854402, -1995183193, 1503453565, -747102133), kind="L'Ecuyer-CMRG") 424s Produced 2 seeds from this stream for future usage 424s Segmenting by CBS... 424s Chromosome: 1 424s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 424s Segmenting by CBS...done 424s Segmenting by CBS... 424s Chromosome: 1 424s Random seed temporarily set (seed=c(10407, -821273412, -52578226, 1415511586, 721384351, -665928286, 1316562960), kind="L'Ecuyer-CMRG") 424s Segmenting by CBS...done 424s Segmenting multiple segments on current chromosome...done 424s Segmenting by CBS...done 424s List of 4 424s $ data :'data.frame': 14658 obs. of 4 variables: 424s ..$ chromosome: int [1:14658] 1 1 1 1 1 1 1 1 1 1 ... 424s ..$ x : num [1:14658] 554484 730720 782343 878522 916294 ... 424s ..$ y : num [1:14658] 1.88 1.8 1.59 1.64 1.53 ... 424s ..$ index : int [1:14658] 1 2 3 4 5 6 7 8 9 10 ... 424s $ output :'data.frame': 3 obs. of 6 variables: 424s ..$ sampleName: chr [1:3] NA NA NA 424s ..$ chromosome: int [1:3] 1 1 1 424s ..$ start : num [1:3] 5.54e+05 1.42e+08 1.85e+08 424s ..$ end : num [1:3] 1.21e+08 1.85e+08 2.47e+08 424s ..$ nbrOfLoci : int [1:3] 7586 2681 4391 424s ..$ mean : num [1:3] 1.39 2.07 2.63 424s $ segRows:'data.frame': 3 obs. of 2 variables: 424s ..$ startRow: int [1:3] 1 7587 10268 424s ..$ endRow : int [1:3] 7586 10267 14658 424s $ params :List of 5 424s ..$ alpha : num 0.009 424s ..$ undo : num 0 424s ..$ joinSegments : logi TRUE 424s ..$ knownSegments:'data.frame': 2 obs. of 3 variables: 424s .. ..$ chromosome: num [1:2] 1 1 424s .. ..$ start : num [1:2] -Inf 1.42e+08 424s .. ..$ end : num [1:2] 1.21e+08 Inf 424s ..$ seed : int [1:7] 10407 1066287653 -51199871 161854402 -1995183193 1503453565 -747102133 424s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 424s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.127 0 0.127 0 0 424s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 424s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 424s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 424s Identification of change points by total copy numbers...done 424s Restructure TCN segmentation results... 424s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean 424s 1 1 554484 120992603 7586 1.3853 424s 2 1 141510003 185449813 2681 2.0689 424s 3 1 185449813 247137334 4391 2.6341 424s Number of TCN segments: 3 424s Restructure TCN segmentation results...done 424s Total CN segment #1 ([ 554484,1.20993e+08]) of 3... 424s Number of TCN loci in segment: 7586 424s Locus data for TCN segment: 424s 'data.frame': 7586 obs. of 9 variables: 424s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 424s $ x : num 554484 730720 782343 878522 916294 ... 424s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 424s $ betaT : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 424s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 424s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 424s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 424s $ index : int 1 2 3 4 5 6 7 8 9 10 ... 424s $ rho : num NA NA NA NA NA ... 424s Number of loci: 7586 424s Number of SNPs: 2108 (27.79%) 424s Number of heterozygous SNPs: 2108 (100.00%) 424s Chromosome: 1 424s Segmenting DH signals... 424s Segmenting by CBS... 424s Chromosome: 1 424s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 424s Segmenting by CBS...done 424s List of 4 424s $ data :'data.frame': 7586 obs. of 4 variables: 424s ..$ chromosome: int [1:7586] 1 1 1 1 1 1 1 1 1 1 ... 424s ..$ x : num [1:7586] 554484 730720 782343 878522 916294 ... 424s ..$ y : num [1:7586] NA NA NA NA NA ... 424s ..$ index : int [1:7586] 1 2 3 4 5 6 7 8 9 10 ... 424s $ output :'data.frame': 1 obs. of 6 variables: 424s ..$ sampleName: chr NA 424s ..$ chromosome: int 1 424s ..$ start : num 554484 424s ..$ end : num 1.21e+08 424s ..$ nbrOfLoci : int 2108 424s ..$ mean : num 0.512 424s $ segRows:'data.frame': 1 obs. of 2 variables: 424s ..$ startRow: int 10 424s ..$ endRow : int 7574 424s $ params :List of 5 424s ..$ alpha : num 0.001 424s ..$ undo : num 0 424s ..$ joinSegments : logi TRUE 424s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 424s .. ..$ chromosome: int 1 424s .. ..$ start : num 554484 424s .. ..$ end : num 1.21e+08 424s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 424s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 424s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.037 0 0.037 0 0 424s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 424s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 424s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 424s DH segmentation (locally-indexed) rows: 424s startRow endRow 424s 1 10 7574 424s int [1:7586] 1 2 3 4 5 6 7 8 9 10 ... 424s DH segmentation rows: 424s startRow endRow 424s 1 10 7574 424s Segmenting DH signals...done 424s DH segmentation table: 424s dhStart dhEnd dhNbrOfLoci dhMean 424s 1 554484 120992603 2108 0.5116 424s startRow endRow 424s 1 10 7574 424s Rows: 424s [1] 1 424s TCN segmentation rows: 424s startRow endRow 424s 1 1 7586 424s TCN and DH segmentation rows: 424s startRow endRow 424s 1 1 7586 424s startRow endRow 424s 1 10 7574 424s NULL 424s TCN segmentation (expanded) rows: 424s startRow endRow 424s 1 1 7586 424s TCN and DH segmentation rows: 424s startRow endRow 424s 1 1 7586 424s 2 7587 10267 424s 3 10268 14658 424s startRow endRow 424s 1 10 7574 424s startRow endRow 424s 1 1 7586 424s Total CN segmentation table (expanded): 424s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 424s 1 1 554484 120992603 7586 1.3853 2108 2108 424s (TCN,DH) segmentation for one total CN segment: 424s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 424s 1 1 1 1 554484 120992603 7586 1.3853 2108 424s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 424s 1 2108 554484 120992603 2108 0.5116 424s Total CN segment #1 ([ 554484,1.20993e+08]) of 3...done 424s Total CN segment #2 ([1.4151e+08,1.8545e+08]) of 3... 424s Number of TCN loci in segment: 2681 424s Locus data for TCN segment: 424s 'data.frame': 2681 obs. of 9 variables: 424s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 424s $ x : num 1.43e+08 1.43e+08 1.43e+08 1.43e+08 1.44e+08 ... 424s $ CT : num 2.27 1.55 1.47 1.5 1.81 ... 424s $ betaT : num 0.34 0.55 0.048 0.813 0.575 ... 424s $ betaTN : num 0.441 0.629 -0.05 0.958 0.872 ... 424s $ betaN : num 0.3851 0.3933 0.0981 0.8552 0.7028 ... 424s $ muN : num 0.5 0.5 0 1 1 1 1 0.5 1 1 ... 424s $ index : int 7587 7588 7589 7590 7591 7592 7593 7594 7595 7596 ... 424s $ rho : num 0.117 0.258 NA NA NA ... 424s Number of loci: 2681 424s Number of SNPs: 777 (28.98%) 424s Number of heterozygous SNPs: 777 (100.00%) 424s Chromosome: 1 424s Segmenting DH signals... 424s Segmenting by CBS... 424s Chromosome: 1 424s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 424s Segmenting by CBS...done 424s List of 4 424s $ data :'data.frame': 2681 obs. of 4 variables: 424s ..$ chromosome: int [1:2681] 1 1 1 1 1 1 1 1 1 1 ... 424s ..$ x : num [1:2681] 1.43e+08 1.43e+08 1.43e+08 1.43e+08 1.44e+08 ... 424s ..$ y : num [1:2681] 0.117 0.258 NA NA NA ... 424s ..$ index : int [1:2681] 1 2 3 4 5 6 7 8 9 10 ... 424s $ output :'data.frame': 1 obs. of 6 variables: 424s ..$ sampleName: chr NA 424s ..$ chromosome: int 1 424s ..$ start : num 1.42e+08 424s ..$ end : num 1.85e+08 424s ..$ nbrOfLoci : int 777 424s ..$ mean : num 0.0973 424s $ segRows:'data.frame': 1 obs. of 2 variables: 424s ..$ startRow: int 1 424s ..$ endRow : int 2677 424s $ params :List of 5 424s ..$ alpha : num 0.001 424s ..$ undo : num 0 424s ..$ joinSegments : logi TRUE 424s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 424s .. ..$ chromosome: int 1 424s .. ..$ start : num 1.42e+08 424s .. ..$ end : num 1.85e+08 424s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 424s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 424s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.008 0 0.008 0 0 424s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 424s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 424s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 424s DH segmentation (locally-indexed) rows: 424s startRow endRow 424s 1 1 2677 424s int [1:2681] 7587 7588 7589 7590 7591 7592 7593 7594 7595 7596 ... 424s DH segmentation rows: 424s startRow endRow 424s 1 7587 10263 424s Segmenting DH signals...done 424s DH segmentation table: 424s dhStart dhEnd dhNbrOfLoci dhMean 424s 1 141510003 185449813 777 0.0973 424s startRow endRow 424s 1 7587 10263 424s Rows: 424s [1] 2 424s TCN segmentation rows: 424s startRow endRow 424s 2 7587 10267 424s TCN and DH segmentation rows: 424s startRow endRow 424s 2 7587 10267 424s startRow endRow 424s 1 7587 10263 424s startRow endRow 424s 1 1 7586 424s TCN segmentation (expanded) rows: 424s startRow endRow 424s 1 1 7586 424s 2 7587 10267 424s TCN and DH segmentation rows: 424s startRow endRow 424s 1 1 7586 424s 2 7587 10267 424s 3 10268 14658 424s startRow endRow 424s 1 10 7574 424s 2 7587 10263 424s startRow endRow 424s 1 1 7586 424s 2 7587 10267 424s Total CN segmentation table (expanded): 424s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 424s 2 1 141510003 185449813 2681 2.0689 777 777 424s (TCN,DH) segmentation for one total CN segment: 424s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 424s 2 2 1 1 141510003 185449813 2681 2.0689 777 424s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 424s 2 777 141510003 185449813 777 0.0973 424s Total CN segment #2 ([1.4151e+08,1.8545e+08]) of 3...done 424s Total CN segment #3 ([1.8545e+08,2.47137e+08]) of 3... 424s Number of TCN loci in segment: 4391 424s Locus data for TCN segment: 424s 'data.frame': 4391 obs. of 9 variables: 424s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 424s $ x : num 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 424s $ CT : num 2.93 2.15 2.82 2.93 2.46 ... 424s $ betaT : num 0.0811 0.5154 0.9473 0.3734 0.7506 ... 424s $ betaTN : num -0.169 0.609 1.028 0.525 0.968 ... 424s $ betaN : num 0.25 0.38 0.919 0.34 0.783 ... 424s $ muN : num 0 0.5 1 0.5 1 1 0 1 0 1 ... 424s $ index : int 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 424s $ rho : num NA 0.2186 NA 0.0503 NA ... 424s Number of loci: 4391 424s Number of SNPs: 1311 (29.86%) 424s Number of heterozygous SNPs: 1311 (100.00%) 424s Chromosome: 1 424s Segmenting DH signals... 424s Segmenting by CBS... 424s Chromosome: 1 424s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 424s Segmenting by CBS...done 424s List of 4 424s $ data :'data.frame': 4391 obs. of 4 variables: 424s ..$ chromosome: int [1:4391] 1 1 1 1 1 1 1 1 1 1 ... 424s ..$ x : num [1:4391] 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 424s ..$ y : num [1:4391] NA 0.2186 NA 0.0503 NA ... 424s ..$ index : int [1:4391] 1 2 3 4 5 6 7 8 9 10 ... 424s $ output :'data.frame': 1 obs. of 6 variables: 424s ..$ sampleName: chr NA 424s ..$ chromosome: int 1 424s ..$ start : num 1.85e+08 424s ..$ end : num 2.47e+08 424s ..$ nbrOfLoci : int 1311 424s ..$ mean : num 0.23 424s $ segRows:'data.frame': 1 obs. of 2 variables: 424s ..$ startRow: int 2 424s ..$ endRow : int 4388 424s $ params :List of 5 424s ..$ alpha : num 0.001 424s ..$ undo : num 0 424s ..$ joinSegments : logi TRUE 424s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 424s .. ..$ chromosome: int 1 424s .. ..$ start : num 1.85e+08 424s .. ..$ end : num 2.47e+08 424s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 424s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 424s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.014 0 0.015 0 0 424s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 424s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 424s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 424s DH segmentation (locally-indexed) rows: 424s startRow endRow 424s 1 2 4388 424s int [1:4391] 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 424s DH segmentation rows: 424s startRow endRow 424s 1 10269 14655 424s Segmenting DH signals...done 424s DH segmentation table: 424s dhStart dhEnd dhNbrOfLoci dhMean 424s 1 185449813 247137334 1311 0.2295 424s startRow endRow 424s 1 10269 14655 424s Rows: 424s [1] 3 424s TCN segmentation rows: 424s startRow endRow 424s 3 10268 14658 424s TCN and DH segmentation rows: 424s startRow endRow 424s 3 10268 14658 424s startRow endRow 424s 1 10269 14655 424s startRow endRow 424s 1 1 7586 424s 2 7587 10267 424s TCN segmentation (expanded) rows: 424s startRow endRow 424s 1 1 7586 424s 2 7587 10267 424s 3 10268 14658 424s TCN and DH segmentation rows: 424s startRow endRow 424s 1 1 7586 424s 2 7587 10267 424s 3 10268 14658 424s startRow endRow 424s 1 10 7574 424s 2 7587 10263 424s 3 10269 14655 424s startRow endRow 424s 1 1 7586 424s 2 7587 10267 424s 3 10268 14658 424s Total CN segmentation table (expanded): 424s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 424s 3 1 185449813 247137334 4391 2.6341 1311 1311 424s (TCN,DH) segmentation for one total CN segment: 424s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 424s 3 3 1 1 185449813 247137334 4391 2.6341 1311 424s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 424s 3 1311 185449813 247137334 1311 0.2295 424s Total CN segment #3 ([1.8545e+08,2.47137e+08]) of 3...done 424s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 424s 1 1 1 1 554484 120992603 7586 1.3853 2108 424s 2 1 2 1 141510003 185449813 2681 2.0689 777 424s 3 1 3 1 185449813 247137334 4391 2.6341 1311 424s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 424s 1 2108 554484 120992603 2108 0.5116 424s 2 777 141510003 185449813 777 0.0973 424s 3 1311 185449813 247137334 1311 0.2295 424s Calculating (C1,C2) per segment... 424s Calculating (C1,C2) per segment...done 424s Number of segments: 3 424s Segmenting paired tumor-normal signals using Paired PSCBS...done 424s Post-segmenting TCNs... 424s Number of segments: 3 424s Number of chromosomes: 1 424s [1] 1 424s Chromosome 1 ('chr01') of 1... 424s Rows: 424s [1] 1 2 3 424s Number of segments: 3 424s TCN segment #1 ('1') of 3... 424s Nothing todo. Only one DH segmentation. Skipping. 424s TCN segment #1 ('1') of 3...done 424s TCN segment #2 ('2') of 3... 424s Nothing todo. Only one DH segmentation. Skipping. 424s TCN segment #2 ('2') of 3...done 424s TCN segment #3 ('3') of 3... 424s Nothing todo. Only one DH segmentation. Skipping. 424s TCN segment #3 ('3') of 3...done 424s Chromosome 1 ('chr01') of 1...done 424s Update (C1,C2) per segment... 424s Update (C1,C2) per segment...done 424s Post-segmenting TCNs...done 424s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 424s 1 1 1 1 554484 120992603 7586 1.3853 2108 424s 2 1 2 1 141510003 185449813 2681 2.0689 777 424s 3 1 3 1 185449813 247137334 4391 2.6341 1311 424s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 424s 1 2108 554484 120992603 2108 0.5116 0.3382903 1.047010 424s 2 777 141510003 185449813 777 0.0973 0.9337980 1.135102 424s 3 1311 185449813 247137334 1311 0.2295 1.0147870 1.619313 424s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 424s 1 1 1 1 554484 120992603 7586 1.3853 2108 424s 2 1 2 1 141510003 185449813 2681 2.0689 777 424s 3 1 3 1 185449813 247137334 4391 2.6341 1311 424s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 424s 1 2108 554484 120992603 2108 0.5116 0.3382903 1.047010 424s 2 777 141510003 185449813 777 0.0973 0.9337980 1.135102 424s 3 1311 185449813 247137334 1311 0.2295 1.0147870 1.619313 424s > print(fit) 424s chromosome tcnId dhId start end tcnNbrOfLoci tcnMean tcnNbrOfSNPs 424s 1 1 1 1 554484 120992603 7586 1.3853 2108 424s 2 1 2 1 141510003 185449813 2681 2.0689 777 424s 3 1 3 1 185449813 247137334 4391 2.6341 1311 424s tcnNbrOfHets dhNbrOfLoci dhMean c1Mean c2Mean 424s 1 2108 2108 0.5116 0.3382903 1.047010 424s 2 777 777 0.0973 0.9337980 1.135102 424s 3 1311 1311 0.2295 1.0147870 1.619313 424s > 424s > # Plot results 424s > dev.set(4L) 424s pdf 424s 2 424s > plotTracks(fit) 424s > abline(v=c(knownSegments$start, knownSegments$end)/1e6, lty=3) 424s > 424s > # Sanity check 424s > stopifnot(nbrOfSegments(fit) == nSegs-1L) 424s > 424s > fit3 <- fit 424s > 424s > 424s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 424s > # (d) Skip the identification of new change points 424s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 424s > knownSegments <- data.frame( 424s + chromosome = c( 1, 1), 424s + start = c( -Inf, 141510003), 424s + end = c(120992603, +Inf) 424s + ) 424s > 424s > # Paired PSCBS segmentation 424s > fit <- segmentByPairedPSCBS(dataS, knownSegments=knownSegments, 424s + undoTCN=Inf, undoDH=Inf, 424s + seed=0xBEEF, verbose=-10) 424s Segmenting paired tumor-normal signals using Paired PSCBS... 424s Calling genotypes from normal allele B fractions... 424s num [1:14670] 0.8274 0.5072 0.1671 0.1609 0.0421 ... 424s Called genotypes: 424s num [1:14670] 1 0.5 0 0 0 0 1 0 1 0.5 ... 424s - attr(*, "modelFit")=List of 1 424s ..$ :List of 7 424s .. ..$ flavor : chr "density" 424s .. ..$ cn : int 2 424s .. ..$ nbrOfGenotypeGroups: int 3 424s .. ..$ tau : num [1:2] 0.315 0.677 424s .. ..$ n : int 14640 424s .. ..$ fit :Classes 'PeaksAndValleys' and 'data.frame': 5 obs. of 3 variables: 424s .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 424s .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 424s .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 424s .. ..$ fitValleys :Classes 'PeaksAndValleys' and 'data.frame': 2 obs. of 3 variables: 424s .. .. ..$ type : chr [1:2] "valley" "valley" 424s .. .. ..$ x : num [1:2] 0.315 0.677 424s .. .. ..$ density: num [1:2] 0.522 0.551 424s ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 424s muN 424s 0 0.5 1 424s 5221 4198 5251 424s Calling genotypes from normal allele B fractions...done 424s Normalizing betaT using betaN (TumorBoost)... 424s Normalized BAFs: 424s num [1:14670] 0.9301 0.1667 0.0685 0.0995 0.0155 ... 424s - attr(*, "modelFit")=List of 5 424s ..$ method : chr "normalizeTumorBoost" 424s ..$ flavor : chr "v4" 424s ..$ delta : num [1:14670] -0.17264 0.00239 0.1671 0.16085 0.04213 ... 424s .. ..- attr(*, "modelFit")=List of 1 424s .. .. ..$ :List of 7 424s .. .. .. ..$ flavor : chr "density" 424s .. .. .. ..$ cn : int 2 424s .. .. .. ..$ nbrOfGenotypeGroups: int 3 424s .. .. .. ..$ tau : num [1:2] 0.315 0.677 424s .. .. .. ..$ n : int 14640 424s .. .. .. ..$ fit :Classes 'PeaksAndValleys' and 'data.frame': 5 obs. of 3 variables: 424s .. .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 424s .. .. .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 424s .. .. .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 424s .. .. .. ..$ fitValleys :Classes 'PeaksAndValleys' and 'data.frame': 2 obs. of 3 variables: 424s .. .. .. .. ..$ type : chr [1:2] "valley" "valley" 424s .. .. .. .. ..$ x : num [1:2] 0.315 0.677 424s .. .. .. .. ..$ density: num [1:2] 0.522 0.551 424s .. .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 424s ..$ preserveScale: logi FALSE 424s ..$ scaleFactor : num NA 424s Normalizing betaT using betaN (TumorBoost)...done 424s Setup up data... 424s 'data.frame': 14670 obs. of 7 variables: 424s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 424s $ x : num 1145994 2941694 3710825 4240737 4276892 ... 424s $ CT : num 1.63 1.4 1.41 1.17 1.16 ... 424s $ betaT : num 0.7574 0.169 0.2357 0.2604 0.0576 ... 424s $ betaTN : num 0.9301 0.1667 0.0685 0.0995 0.0155 ... 424s ..- attr(*, "modelFit")=List of 5 424s .. ..$ method : chr "normalizeTumorBoost" 424s .. ..$ flavor : chr "v4" 424s .. ..$ delta : num [1:14670] -0.17264 0.00239 0.1671 0.16085 0.04213 ... 424s .. .. ..- attr(*, "modelFit")=List of 1 424s .. .. .. ..$ :List of 7 424s .. .. .. .. ..$ flavor : chr "density" 424s .. .. .. .. ..$ cn : int 2 424s .. .. .. .. ..$ nbrOfGenotypeGroups: int 3 424s .. .. .. .. ..$ tau : num [1:2] 0.315 0.677 424s .. .. .. .. ..$ n : int 14640 424s .. .. .. .. ..$ fit :Classes 'PeaksAndValleys' and 'data.frame': 5 obs. of 3 variables: 424s .. .. .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 424s .. .. .. .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 424s .. .. .. .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 424s .. .. .. .. ..$ fitValleys :Classes 'PeaksAndValleys' and 'data.frame': 2 obs. of 3 variables: 424s .. .. .. .. .. ..$ type : chr [1:2] "valley" "valley" 424s .. .. .. .. .. ..$ x : num [1:2] 0.315 0.677 424s .. .. .. .. .. ..$ density: num [1:2] 0.522 0.551 424s .. .. .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 424s .. ..$ preserveScale: logi FALSE 424s .. ..$ scaleFactor : num NA 424s $ betaN : num 0.8274 0.5072 0.1671 0.1609 0.0421 ... 424s $ muN : num 1 0.5 0 0 0 0 1 0 1 0.5 ... 424s ..- attr(*, "modelFit")=List of 1 424s .. ..$ :List of 7 424s .. .. ..$ flavor : chr "density" 424s .. .. ..$ cn : int 2 424s .. .. ..$ nbrOfGenotypeGroups: int 3 424s .. .. ..$ tau : num [1:2] 0.315 0.677 424s .. .. ..$ n : int 14640 424s .. .. ..$ fit :Classes 'PeaksAndValleys' and 'data.frame': 5 obs. of 3 variables: 424s .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 424s .. .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 424s .. .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 424s .. .. ..$ fitValleys :Classes 'PeaksAndValleys' and 'data.frame': 2 obs. of 3 variables: 424s .. .. .. ..$ type : chr [1:2] "valley" "valley" 424s .. .. .. ..$ x : num [1:2] 0.315 0.677 424s .. .. .. ..$ density: num [1:2] 0.522 0.551 424s .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 424s Setup up data...done 424s Dropping loci for which TCNs are missing... 424s Number of loci dropped: 12 424s Dropping loci for which TCNs are missing...done 424s Ordering data along genome... 424s 'data.frame': 14658 obs. of 7 variables: 424s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 424s $ x : num 554484 730720 782343 878522 916294 ... 424s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 424s $ betaT : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 424s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 424s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 424s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 424s Ordering data along genome...done 424s Keeping only current chromosome for 'knownSegments'... 424s Chromosome: 1 424s Known segments for this chromosome: 424s chromosome start end 424s 1 1 -Inf 120992603 424s 2 1 141510003 Inf 424s Keeping only current chromosome for 'knownSegments'...done 424s alphaTCN: 0.009 424s alphaDH: 0.001 424s Number of loci: 14658 424s Calculating DHs... 424s Number of SNPs: 14658 424s Number of heterozygous SNPs: 4196 (28.63%) 424s Normalized DHs: 424s num [1:14658] NA NA NA NA NA ... 424s Calculating DHs...done 424s Random seed temporarily set (seed=c(48879), kind="L'Ecuyer-CMRG") 424s Produced 2 seeds from this stream for future usage 424s Identification of change points by total copy numbers... 424s Segmenting by CBS... 424s Chromosome: 1 424s Segmenting multiple segments on current chromosome... 424s Number of segments: 2 424s Random seed temporarily set (seed=c(10407, 1066287653, -51199871, 161854402, -1995183193, 1503453565, -747102133), kind="L'Ecuyer-CMRG") 424s Produced 2 seeds from this stream for future usage 424s Segmenting by CBS... 424s Chromosome: 1 424s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 424s Segmenting by CBS...done 424s Segmenting by CBS... 424s Chromosome: 1 424s Random seed temporarily set (seed=c(10407, -821273412, -52578226, 1415511586, 721384351, -665928286, 1316562960), kind="L'Ecuyer-CMRG") 424s Segmenting by CBS...done 424s Segmenting multiple segments on current chromosome...done 424s Segmenting by CBS...done 424s List of 4 424s $ data :'data.frame': 14658 obs. of 4 variables: 424s ..$ chromosome: int [1:14658] 1 1 1 1 1 1 1 1 1 1 ... 424s ..$ x : num [1:14658] 554484 730720 782343 878522 916294 ... 424s ..$ y : num [1:14658] 1.88 1.8 1.59 1.64 1.53 ... 424s ..$ index : int [1:14658] 1 2 3 4 5 6 7 8 9 10 ... 424s $ output :'data.frame': 2 obs. of 6 variables: 424s ..$ sampleName: chr [1:2] NA NA 424s ..$ chromosome: num [1:2] 1 1 424s ..$ start : num [1:2] 5.54e+05 1.42e+08 424s ..$ end : num [1:2] 1.21e+08 2.47e+08 424s ..$ nbrOfLoci : int [1:2] 7586 7072 424s ..$ mean : num [1:2] 1.39 2.42 424s $ segRows:'data.frame': 2 obs. of 2 variables: 424s ..$ startRow: int [1:2] 1 7587 424s ..$ endRow : int [1:2] 7586 14658 424s $ params :List of 7 424s ..$ undo.splits : chr "sdundo" 424s ..$ undo.SD : num Inf 424s ..$ alpha : num 0.009 424s ..$ undo : num Inf 424s ..$ joinSegments : logi TRUE 424s ..$ knownSegments:'data.frame': 2 obs. of 3 variables: 424s .. ..$ chromosome: num [1:2] 1 1 424s .. ..$ start : num [1:2] -Inf 1.42e+08 424s .. ..$ end : num [1:2] 1.21e+08 Inf 424s ..$ seed : int [1:7] 10407 1066287653 -51199871 161854402 -1995183193 1503453565 -747102133 424s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 424s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.002 0 0.002 0 0 424s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 424s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 424s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 424s Identification of change points by total copy numbers...done 424s Restructure TCN segmentation results... 424s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean 424s 1 1 554484 120992603 7586 1.385258 424s 2 1 141510003 247137334 7072 2.419824 424s Number of TCN segments: 2 424s Restructure TCN segmentation results...done 424s Total CN segment #1 ([ 554484,1.20993e+08]) of 2... 424s Number of TCN loci in segment: 7586 424s Locus data for TCN segment: 424s 'data.frame': 7586 obs. of 9 variables: 424s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 424s $ x : num 554484 730720 782343 878522 916294 ... 424s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 424s $ betaT : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 424s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 424s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 424s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 424s $ index : int 1 2 3 4 5 6 7 8 9 10 ... 424s $ rho : num NA NA NA NA NA ... 424s Number of loci: 7586 424s Number of SNPs: 2108 (27.79%) 424s Number of heterozygous SNPs: 2108 (100.00%) 424s Chromosome: 1 424s Segmenting DH signals... 424s Segmenting by CBS... 424s Chromosome: 1 424s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 424s Segmenting by CBS...done 424s List of 4 424s $ data :'data.frame': 7586 obs. of 4 variables: 424s ..$ chromosome: int [1:7586] 1 1 1 1 1 1 1 1 1 1 ... 424s ..$ x : num [1:7586] 554484 730720 782343 878522 916294 ... 424s ..$ y : num [1:7586] NA NA NA NA NA ... 424s ..$ index : int [1:7586] 1 2 3 4 5 6 7 8 9 10 ... 424s $ output :'data.frame': 1 obs. of 6 variables: 424s ..$ sampleName: chr NA 424s ..$ chromosome: int 1 424s ..$ start : num 554484 424s ..$ end : num 1.21e+08 424s ..$ nbrOfLoci : int 7586 424s ..$ mean : num 0.512 424s $ segRows:'data.frame': 1 obs. of 2 variables: 424s ..$ startRow: int 1 424s ..$ endRow : int 7586 424s $ params :List of 7 424s ..$ undo.splits : chr "sdundo" 424s ..$ undo.SD : num Inf 424s ..$ alpha : num 0.001 424s ..$ undo : num Inf 424s ..$ joinSegments : logi TRUE 424s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 424s .. ..$ chromosome: int 1 424s .. ..$ start : num 554484 424s .. ..$ end : num 1.21e+08 424s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 424s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 424s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.002 0 0.002 0 0 424s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 424s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 424s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 424s DH segmentation (locally-indexed) rows: 424s startRow endRow 424s 1 1 7586 424s int [1:7586] 1 2 3 4 5 6 7 8 9 10 ... 424s DH segmentation rows: 424s startRow endRow 424s 1 1 7586 424s Segmenting DH signals...done 424s DH segmentation table: 424s dhStart dhEnd dhNbrOfLoci dhMean 424s 1 554484 120992603 7586 0.511612 424s startRow endRow 424s 1 1 7586 424s Rows: 424s [1] 1 424s TCN segmentation rows: 424s startRow endRow 424s 1 1 7586 424s TCN and DH segmentation rows: 424s startRow endRow 424s 1 1 7586 424s startRow endRow 424s 1 1 7586 424s NULL 424s TCN segmentation (expanded) rows: 424s startRow endRow 424s 1 1 7586 424s TCN and DH segmentation rows: 424s startRow endRow 424s 1 1 7586 424s 2 7587 14658 424s startRow endRow 424s 1 1 7586 424s startRow endRow 424s 1 1 7586 424s Total CN segmentation table (expanded): 424s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 424s 1 1 554484 120992603 7586 1.385258 2108 2108 424s (TCN,DH) segmentation for one total CN segment: 424s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 424s 1 1 1 1 554484 120992603 7586 1.385258 2108 424s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 424s 1 2108 554484 120992603 7586 0.511612 424s Total CN segment #1 ([ 554484,1.20993e+08]) of 2...done 424s Total CN segment #2 ([1.4151e+08,2.47137e+08]) of 2... 424s Number of TCN loci in segment: 7072 424s Locus data for TCN segment: 424s 'data.frame': 7072 obs. of 9 variables: 424s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 424s $ x : num 1.43e+08 1.43e+08 1.43e+08 1.43e+08 1.44e+08 ... 424s $ CT : num 2.27 1.55 1.47 1.5 1.81 ... 424s $ betaT : num 0.34 0.55 0.048 0.813 0.575 ... 424s $ betaTN : num 0.441 0.629 -0.05 0.958 0.872 ... 424s $ betaN : num 0.3851 0.3933 0.0981 0.8552 0.7028 ... 424s $ muN : num 0.5 0.5 0 1 1 1 1 0.5 1 1 ... 424s $ index : int 7587 7588 7589 7590 7591 7592 7593 7594 7595 7596 ... 424s $ rho : num 0.117 0.258 NA NA NA ... 424s Number of loci: 7072 424s Number of SNPs: 2088 (29.52%) 424s Number of heterozygous SNPs: 2088 (100.00%) 424s Chromosome: 1 424s Segmenting DH signals... 424s Segmenting by CBS... 424s Chromosome: 1 424s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 424s Segmenting by CBS...done 424s List of 4 424s $ data :'data.frame': 7072 obs. of 4 variables: 424s ..$ chromosome: int [1:7072] 1 1 1 1 1 1 1 1 1 1 ... 424s ..$ x : num [1:7072] 1.43e+08 1.43e+08 1.43e+08 1.43e+08 1.44e+08 ... 424s ..$ y : num [1:7072] 0.117 0.258 NA NA NA ... 424s ..$ index : int [1:7072] 1 2 3 4 5 6 7 8 9 10 ... 424s $ output :'data.frame': 1 obs. of 6 variables: 424s ..$ sampleName: chr NA 424s ..$ chromosome: int 1 424s ..$ start : num 1.42e+08 424s ..$ end : num 2.47e+08 424s ..$ nbrOfLoci : int 7072 424s ..$ mean : num 0.18 424s $ segRows:'data.frame': 1 obs. of 2 variables: 424s ..$ startRow: int 1 424s ..$ endRow : int 7072 424s $ params :List of 7 424s ..$ undo.splits : chr "sdundo" 424s ..$ undo.SD : num Inf 424s ..$ alpha : num 0.001 424s ..$ undo : num Inf 424s ..$ joinSegments : logi TRUE 424s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 424s .. ..$ chromosome: int 1 424s .. ..$ start : num 1.42e+08 424s .. ..$ end : num 2.47e+08 424s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 424s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 424s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.002 0 0.002 0 0 424s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 424s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 424s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 424s DH segmentation (locally-indexed) rows: 424s startRow endRow 424s 1 1 7072 424s int [1:7072] 7587 7588 7589 7590 7591 7592 7593 7594 7595 7596 ... 424s DH segmentation rows: 424s startRow endRow 424s 1 7587 14658 424s Segmenting DH signals...done 424s DH segmentation table: 424s dhStart dhEnd dhNbrOfLoci dhMean 424s 1 141510003 247137334 7072 0.1803011 424s startRow endRow 424s 1 7587 14658 424s Rows: 424s [1] 2 424s TCN segmentation rows: 424s startRow endRow 424s 2 7587 14658 424s TCN and DH segmentation rows: 424s startRow endRow 424s 2 7587 14658 424s startRow endRow 424s 1 7587 14658 424s startRow endRow 424s 1 1 7586 424s TCN segmentation (expanded) rows: 424s startRow endRow 424s 1 1 7586 424s 2 7587 14658 424s TCN and DH segmentation rows: 424s startRow endRow 424s 1 1 7586 424s 2 7587 14658 424s startRow endRow 424s 1 1 7586 424s 2 7587 14658 424s startRow endRow 424s 1 1 7586 424s 2 7587 14658 424s Total CN segmentation table (expanded): 424s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 424s 2 1 141510003 247137334 7072 2.419824 2088 424s tcnNbrOfHets 424s 2 2088 424s (TCN,DH) segmentation for one total CN segment: 424s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 424s 2 2 1 1 141510003 247137334 7072 2.419824 2088 424s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 424s 2 2088 141510003 247137334 7072 0.1803011 424s Total CN segment #2 ([1.4151e+08,2.47137e+08]) of 2...done 424s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 424s 1 1 1 1 554484 120992603 7586 1.385258 2108 424s 2 1 2 1 141510003 247137334 7072 2.419824 2088 424s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 424s 1 2108 554484 120992603 7586 0.5116120 424s 2 2088 141510003 247137334 7072 0.1803011 424s Calculating (C1,C2) per segment... 424s Calculating (C1,C2) per segment...done 424s Number of segments: 2 424s Segmenting paired tumor-normal signals using Paired PSCBS...done 424s Post-segmenting TCNs... 424s Number of segments: 2 424s Number of chromosomes: 1 424s [1] 1 424s Chromosome 1 ('chr01') of 1... 424s Rows: 424s [1] 1 2 424s Number of segments: 2 424s TCN segment #1 ('1') of 2... 424s Nothing todo. Only one DH segmentation. Skipping. 424s TCN segment #1 ('1') of 2...done 424s TCN segment #2 ('2') of 2... 424s Nothing todo. Only one DH segmentation. Skipping. 424s TCN segment #2 ('2') of 2...done 424s Chromosome 1 ('chr01') of 1...done 424s Update (C1,C2) per segment... 424s Update (C1,C2) per segment...done 424s Post-segmenting TCNs...done 424s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 424s 1 1 1 1 554484 120992603 7586 1.385258 2108 424s 2 1 2 1 141510003 247137334 7072 2.419824 2088 424s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 424s 1 2108 554484 120992603 7586 0.5116120 0.3382717 1.046986 424s 2 2088 141510003 247137334 7072 0.1803011 0.9917635 1.428060 424s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 424s 1 1 1 1 554484 120992603 7586 1.385258 2108 424s 2 1 2 1 141510003 247137334 7072 2.419824 2088 424s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 424s 1 2108 554484 120992603 7586 0.5116120 0.3382717 1.046986 424s 2 2088 141510003 247137334 7072 0.1803011 0.9917635 1.428060 424s > print(fit) 424s chromosome tcnId dhId start end tcnNbrOfLoci tcnMean tcnNbrOfSNPs 424s 1 1 1 1 554484 120992603 7586 1.385258 2108 424s 2 1 2 1 141510003 247137334 7072 2.419824 2088 424s tcnNbrOfHets dhNbrOfLoci dhMean c1Mean c2Mean 424s 1 2108 7586 0.5116120 0.3382717 1.046986 424s 2 2088 7072 0.1803011 0.9917635 1.428060 424s > 424s > # Plot results 424s > dev.set(5L) 424s pdf 424s 2 424s > plotTracks(fit) 424s > abline(v=c(knownSegments$start, knownSegments$end)/1e6, lty=3) 424s > 424s > # Sanity check 424s > stopifnot(nbrOfSegments(fit) == nrow(knownSegments)) 424s > 424s > fit4 <- fit 424s > 424s > 424s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 424s > # Tiling multiple chromosomes 424s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 424s > # Simulate multiple chromosomes 424s > fit1 <- fit 424s > fit2 <- renameChromosomes(fit, from=1, to=2) 424s > fitM <- c(fit1, fit2) 424s > 424s > # Tile chromosomes 424s > fitT <- tileChromosomes(fitM) 424s > fitTb <- tileChromosomes(fitT) 424s > stopifnot(identical(fitTb, fitT)) 424s > 424s > # Plotting multiple chromosomes 424s > plotTracks(fitT) 424s > 424s > proc.time() 424s user system elapsed 424s 5.446 0.133 5.573 424s Test segmentByPairedPSCBS passed 424s 0 424s + [ 0 != 0 ] 424s + echo Test segmentByPairedPSCBS passed 424s + echo 0 424s + rm -f /tmp/autopkgtest.b85msM/autopkgtest_tmp/PairedPSCBS,boot.R /tmp/autopkgtest.b85msM/autopkgtest_tmp/PairedPSCBS,boot.Rout /tmp/autopkgtest.b85msM/autopkgtest_tmp/Rplots.pdf /tmp/autopkgtest.b85msM/autopkgtest_tmp/findLargeGaps.R /tmp/autopkgtest.b85msM/autopkgtest_tmp/findLargeGaps.Rout /tmp/autopkgtest.b85msM/autopkgtest_tmp/randomSeed.R /tmp/autopkgtest.b85msM/autopkgtest_tmp/randomSeed.Rout /tmp/autopkgtest.b85msM/autopkgtest_tmp/segmentByCBS,bug67.R /tmp/autopkgtest.b85msM/autopkgtest_tmp/segmentByCBS,bug67.Rout /tmp/autopkgtest.b85msM/autopkgtest_tmp/segmentByCBS,calls.R /tmp/autopkgtest.b85msM/autopkgtest_tmp/segmentByCBS,calls.Rout /tmp/autopkgtest.b85msM/autopkgtest_tmp/segmentByCBS,futures.R /tmp/autopkgtest.b85msM/autopkgtest_tmp/segmentByCBS,futures.Rout /tmp/autopkgtest.b85msM/autopkgtest_tmp/segmentByCBS,median.R /tmp/autopkgtest.b85msM/autopkgtest_tmp/segmentByCBS,median.Rout /tmp/autopkgtest.b85msM/autopkgtest_tmp/segmentByCBS,prune.R /tmp/autopkgtest.b85msM/autopkgtest_tmp/segmentByCBS,prune.Rout /tmp/autopkgtest.b85msM/autopkgtest_tmp/segmentByCBS,report.R /tmp/autopkgtest.b85msM/autopkgtest_tmp/segmentByCBS,report.Rout /tmp/autopkgtest.b85msM/autopkgtest_tmp/segmentByCBS,shiftTCN.R /tmp/autopkgtest.b85msM/autopkgtest_tmp/segmentByCBS,shiftTCN.Rout /tmp/autopkgtest.b85msM/autopkgtest_tmp/segmentByCBS,weights.R /tmp/autopkgtest.b85msM/autopkgtest_tmp/segmentByCBS,weights.Rout /tmp/autopkgtest.b85msM/autopkgtest_tmp/segmentByCBS.R /tmp/autopkgtest.b85msM/autopkgtest_tmp/segmentByCBS.Rout /tmp/autopkgtest.b85msM/autopkgtest_tmp/segmentByNonPairedPSCBS,medianDH.R /tmp/autopkgtest.b85msM/autopkgtest_tmp/segmentByNonPairedPSCBS,medianDH.Rout /tmp/autopkgtest.b85msM/autopkgtest_tmp/segmentByPairedPSCBS,DH.R /tmp/autopkgtest.b85msM/autopkgtest_tmp/segmentByPairedPSCBS,DH.Rout /tmp/autopkgtest.b85msM/autopkgtest_tmp/segmentByPairedPSCBS,calls.R /tmp/autopkgtest.b85msM/autopkgtest_tmp/segmentByPairedPSCBS,calls.Rout /tmp/autopkgtest.b85msM/autopkgtest_tmp/segmentByPairedPSCBS,futures.R /tmp/autopkgtest.b85msM/autopkgtest_tmp/segmentByPairedPSCBS,futures.Rout /tmp/autopkgtest.b85msM/autopkgtest_tmp/segmentByPairedPSCBS,noNormalBAFs.R /tmp/autopkgtest.b85msM/autopkgtest_tmp/segmentByPairedPSCBS,noNormalBAFs.Rout /tmp/autopkgtest.b85msM/autopkgtest_tmp/segmentByPairedPSCBS,report.R /tmp/autopkgtest.b85msM/autopkgtest_tmp/segmentByPairedPSCBS,report.Rout /tmp/autopkgtest.b85msM/autopkgtest_tmp/segmentByPairedPSCBS,seqOfSegmentsByDP.R /tmp/autopkgtest.b85msM/autopkgtest_tmp/segmentByPairedPSCBS,seqOfSegmentsByDP.Rout /tmp/autopkgtest.b85msM/autopkgtest_tmp/segmentByPairedPSCBS.R /tmp/autopkgtest.b85msM/autopkgtest_tmp/segmentByPairedPSCBS.Rout 424s autopkgtest [00:09:50]: test run-unit-test: -----------------------] 424s autopkgtest [00:09:50]: test run-unit-test: - - - - - - - - - - results - - - - - - - - - - 424s run-unit-test PASS 425s autopkgtest [00:09:51]: test pkg-r-autopkgtest: preparing testbed 443s Creating nova instance adt-resolute-arm64-r-cran-pscbs-20260210-000245-juju-7f2275-prod-proposed-migration-environment-15-c6a1c531-c43a-4d6b-af9b-41aee768bc4a from image adt/ubuntu-resolute-arm64-server-20260209.img (UUID 793037ca-75af-461b-82de-f8081300b2e3)... 558s autopkgtest [00:12:04]: testbed dpkg architecture: arm64 558s autopkgtest [00:12:04]: testbed apt version: 3.1.15 558s autopkgtest [00:12:04]: @@@@@@@@@@@@@@@@@@@@ test bed setup 558s autopkgtest [00:12:04]: testbed release detected to be: resolute 559s autopkgtest [00:12:05]: updating testbed package index (apt update) 560s Get:1 http://ftpmaster.internal/ubuntu resolute-proposed InRelease [124 kB] 560s Hit:2 http://ftpmaster.internal/ubuntu resolute InRelease 560s Hit:3 http://ftpmaster.internal/ubuntu resolute-updates InRelease 560s Hit:4 http://ftpmaster.internal/ubuntu resolute-security InRelease 560s Get:5 http://ftpmaster.internal/ubuntu resolute-proposed/multiverse Sources [29.4 kB] 560s Get:6 http://ftpmaster.internal/ubuntu resolute-proposed/main Sources [176 kB] 560s Get:7 http://ftpmaster.internal/ubuntu resolute-proposed/universe Sources [1645 kB] 563s Get:8 http://ftpmaster.internal/ubuntu resolute-proposed/main arm64 Packages [246 kB] 563s Get:9 http://ftpmaster.internal/ubuntu resolute-proposed/main arm64 c-n-f Metadata [6216 B] 563s Get:10 http://ftpmaster.internal/ubuntu resolute-proposed/restricted arm64 c-n-f Metadata [304 B] 563s Get:11 http://ftpmaster.internal/ubuntu resolute-proposed/universe arm64 Packages [1580 kB] 566s Get:12 http://ftpmaster.internal/ubuntu resolute-proposed/universe arm64 c-n-f Metadata [32.0 kB] 566s Get:13 http://ftpmaster.internal/ubuntu resolute-proposed/multiverse arm64 Packages [21.7 kB] 566s Get:14 http://ftpmaster.internal/ubuntu resolute-proposed/multiverse arm64 c-n-f Metadata [688 B] 567s Fetched 3862 kB in 6s (625 kB/s) 568s Reading package lists... 569s Hit:1 http://ftpmaster.internal/ubuntu resolute-proposed InRelease 569s Hit:2 http://ftpmaster.internal/ubuntu resolute InRelease 569s Hit:3 http://ftpmaster.internal/ubuntu resolute-updates InRelease 569s Hit:4 http://ftpmaster.internal/ubuntu resolute-security InRelease 570s Reading package lists... 570s Reading package lists... 570s Building dependency tree... 570s Reading state information... 570s Calculating upgrade... 570s The following packages will be upgraded: 570s cryptsetup-bin dracut-install iproute2 iptables libcryptsetup12 libip4tc2 570s libip6tc2 libxtables12 wget 570s 9 upgraded, 0 newly installed, 0 to remove and 0 not upgraded. 570s Need to get 2534 kB of archives. 570s After this operation, 18.4 kB of additional disk space will be used. 570s Get:1 http://ftpmaster.internal/ubuntu resolute/main arm64 iptables arm64 1.8.11-2ubuntu3 [386 kB] 570s Get:2 http://ftpmaster.internal/ubuntu resolute/main arm64 libip4tc2 arm64 1.8.11-2ubuntu3 [24.3 kB] 570s Get:3 http://ftpmaster.internal/ubuntu resolute/main arm64 libip6tc2 arm64 1.8.11-2ubuntu3 [24.7 kB] 570s Get:4 http://ftpmaster.internal/ubuntu resolute/main arm64 libxtables12 arm64 1.8.11-2ubuntu3 [36.7 kB] 571s Get:5 http://ftpmaster.internal/ubuntu resolute/main arm64 iproute2 arm64 6.18.0-1ubuntu1 [1171 kB] 572s Get:6 http://ftpmaster.internal/ubuntu resolute/main arm64 libcryptsetup12 arm64 2:2.8.0-1ubuntu3 [274 kB] 572s Get:7 http://ftpmaster.internal/ubuntu resolute/main arm64 wget arm64 1.25.0-2ubuntu4 [344 kB] 572s Get:8 http://ftpmaster.internal/ubuntu resolute/main arm64 cryptsetup-bin arm64 2:2.8.0-1ubuntu3 [227 kB] 572s Get:9 http://ftpmaster.internal/ubuntu resolute/main arm64 dracut-install arm64 109-11ubuntu1 [45.3 kB] 573s dpkg-preconfigure: unable to re-open stdin: No such file or directory 573s Fetched 2534 kB in 2s (1304 kB/s) 573s (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 ... 136597 files and directories currently installed.) 573s Preparing to unpack .../0-iptables_1.8.11-2ubuntu3_arm64.deb ... 573s Unpacking iptables (1.8.11-2ubuntu3) over (1.8.11-2ubuntu2) ... 573s Preparing to unpack .../1-libip4tc2_1.8.11-2ubuntu3_arm64.deb ... 573s Unpacking libip4tc2:arm64 (1.8.11-2ubuntu3) over (1.8.11-2ubuntu2) ... 573s Preparing to unpack .../2-libip6tc2_1.8.11-2ubuntu3_arm64.deb ... 573s Unpacking libip6tc2:arm64 (1.8.11-2ubuntu3) over (1.8.11-2ubuntu2) ... 573s Preparing to unpack .../3-libxtables12_1.8.11-2ubuntu3_arm64.deb ... 573s Unpacking libxtables12:arm64 (1.8.11-2ubuntu3) over (1.8.11-2ubuntu2) ... 573s Preparing to unpack .../4-iproute2_6.18.0-1ubuntu1_arm64.deb ... 573s Unpacking iproute2 (6.18.0-1ubuntu1) over (6.16.0-1ubuntu3) ... 574s Preparing to unpack .../5-libcryptsetup12_2%3a2.8.0-1ubuntu3_arm64.deb ... 574s Unpacking libcryptsetup12:arm64 (2:2.8.0-1ubuntu3) over (2:2.8.0-1ubuntu2) ... 574s Preparing to unpack .../6-wget_1.25.0-2ubuntu4_arm64.deb ... 574s Unpacking wget (1.25.0-2ubuntu4) over (1.25.0-2ubuntu3) ... 574s Preparing to unpack .../7-cryptsetup-bin_2%3a2.8.0-1ubuntu3_arm64.deb ... 574s Unpacking cryptsetup-bin (2:2.8.0-1ubuntu3) over (2:2.8.0-1ubuntu2) ... 574s Preparing to unpack .../8-dracut-install_109-11ubuntu1_arm64.deb ... 574s Unpacking dracut-install (109-11ubuntu1) over (109-9ubuntu1) ... 574s Setting up libip4tc2:arm64 (1.8.11-2ubuntu3) ... 574s Setting up wget (1.25.0-2ubuntu4) ... 574s Setting up libip6tc2:arm64 (1.8.11-2ubuntu3) ... 574s Setting up libxtables12:arm64 (1.8.11-2ubuntu3) ... 574s Setting up dracut-install (109-11ubuntu1) ... 574s Setting up libcryptsetup12:arm64 (2:2.8.0-1ubuntu3) ... 574s Setting up cryptsetup-bin (2:2.8.0-1ubuntu3) ... 574s Setting up iptables (1.8.11-2ubuntu3) ... 574s Setting up iproute2 (6.18.0-1ubuntu1) ... 574s Processing triggers for man-db (2.13.1-1build1) ... 575s Processing triggers for install-info (7.2-5) ... 576s Processing triggers for libc-bin (2.42-2ubuntu4) ... 576s autopkgtest [00:12:22]: upgrading testbed (apt dist-upgrade and autopurge) 576s Reading package lists... 576s Building dependency tree... 576s Reading state information... 576s Calculating upgrade... 577s 0 upgraded, 0 newly installed, 0 to remove and 0 not upgraded. 577s Reading package lists... 577s Building dependency tree... 577s Reading state information... 577s Solving dependencies... 578s 0 upgraded, 0 newly installed, 0 to remove and 0 not upgraded. 580s Reading package lists... 580s Building dependency tree... 580s Reading state information... 581s Solving dependencies... 581s The following NEW packages will be installed: 581s build-essential cpp cpp-15 cpp-15-aarch64-linux-gnu cpp-aarch64-linux-gnu 581s dctrl-tools fontconfig fontconfig-config fonts-dejavu-core fonts-dejavu-mono 581s g++ g++-15 g++-15-aarch64-linux-gnu g++-aarch64-linux-gnu gcc gcc-15 581s gcc-15-aarch64-linux-gnu gcc-aarch64-linux-gnu gfortran gfortran-15 581s gfortran-15-aarch64-linux-gnu gfortran-aarch64-linux-gnu icu-devtools 581s libasan8 libblas-dev libblas3 libbz2-dev libc-dev-bin libc6-dev libcairo2 581s libcc1-0 libcrypt-dev libdatrie1 libdeflate-dev libdeflate0 libfontconfig1 581s libgcc-15-dev libgfortran-15-dev libgfortran5 libgomp1 libgraphite2-3 581s libharfbuzz0b libhwasan0 libice6 libicu-dev libisl23 libitm1 libjbig0 581s libjpeg-dev libjpeg-turbo8 libjpeg-turbo8-dev libjpeg8 libjpeg8-dev 581s liblapack-dev liblapack3 liblerc4 liblsan0 liblzma-dev libmpc3 581s libncurses-dev libpango-1.0-0 libpangocairo-1.0-0 libpangoft2-1.0-0 581s libpaper-utils libpaper2 libpcre2-16-0 libpcre2-32-0 libpcre2-dev 581s libpcre2-posix3 libpixman-1-0 libpkgconf3 libpng-dev libreadline-dev 581s libsharpyuv0 libsm6 libstdc++-15-dev libtcl8.6 libthai-data libthai0 581s libtiff6 libtirpc-dev libtk8.6 libtsan2 libubsan1 libwebp7 libxcb-render0 581s libxcb-shm0 libxft2 libxrender1 libxss1 libxt6t64 libzstd-dev linux-libc-dev 581s pkg-r-autopkgtest pkgconf pkgconf-bin r-base-core r-base-dev 581s r-bioc-aroma.light r-bioc-biocgenerics r-bioc-dnacopy r-cran-cli 581s r-cran-codetools r-cran-digest r-cran-farver r-cran-future r-cran-ggplot2 581s r-cran-globals r-cran-glue r-cran-gtable r-cran-isoband r-cran-labeling 581s r-cran-lifecycle r-cran-listenv r-cran-matrixstats r-cran-parallelly 581s r-cran-pscbs r-cran-r.cache r-cran-r.methodss3 r-cran-r.oo r-cran-r.utils 581s r-cran-r6 r-cran-rcolorbrewer r-cran-rlang r-cran-s7 r-cran-scales 581s r-cran-vctrs r-cran-viridislite r-cran-withr rpcsvc-proto unzip x11-common 581s xdg-utils zip zlib1g-dev 581s 0 upgraded, 135 newly installed, 0 to remove and 0 not upgraded. 581s Need to get 167 MB of archives. 581s After this operation, 498 MB of additional disk space will be used. 581s Get:1 http://ftpmaster.internal/ubuntu resolute/main arm64 libc-dev-bin arm64 2.42-2ubuntu4 [22.5 kB] 581s Get:2 http://ftpmaster.internal/ubuntu resolute/main arm64 linux-libc-dev arm64 6.19.0-3.3 [1819 kB] 584s Get:3 http://ftpmaster.internal/ubuntu resolute/main arm64 libcrypt-dev arm64 1:4.5.1-1 [123 kB] 584s Get:4 http://ftpmaster.internal/ubuntu resolute/main arm64 rpcsvc-proto arm64 1.4.3-1build1 [65.6 kB] 584s Get:5 http://ftpmaster.internal/ubuntu resolute/main arm64 libc6-dev arm64 2.42-2ubuntu4 [1765 kB] 587s Get:6 http://ftpmaster.internal/ubuntu resolute/main arm64 libisl23 arm64 0.27-1build1 [676 kB] 588s Get:7 http://ftpmaster.internal/ubuntu resolute/main arm64 libmpc3 arm64 1.3.1-2 [55.6 kB] 588s Get:8 http://ftpmaster.internal/ubuntu resolute/main arm64 cpp-15-aarch64-linux-gnu arm64 15.2.0-12ubuntu1 [11.7 MB] 605s Get:9 http://ftpmaster.internal/ubuntu resolute/main arm64 cpp-15 arm64 15.2.0-12ubuntu1 [1030 B] 605s Get:10 http://ftpmaster.internal/ubuntu resolute/main arm64 cpp-aarch64-linux-gnu arm64 4:15.2.0-4ubuntu1 [5736 B] 605s Get:11 http://ftpmaster.internal/ubuntu resolute/main arm64 cpp arm64 4:15.2.0-4ubuntu1 [22.4 kB] 605s Get:12 http://ftpmaster.internal/ubuntu resolute/main arm64 libcc1-0 arm64 15.2.0-12ubuntu1 [49.0 kB] 605s Get:13 http://ftpmaster.internal/ubuntu resolute/main arm64 libgomp1 arm64 15.2.0-12ubuntu1 [147 kB] 605s Get:14 http://ftpmaster.internal/ubuntu resolute/main arm64 libitm1 arm64 15.2.0-12ubuntu1 [27.8 kB] 605s Get:15 http://ftpmaster.internal/ubuntu resolute/main arm64 libasan8 arm64 15.2.0-12ubuntu1 [2920 kB] 609s Get:16 http://ftpmaster.internal/ubuntu resolute/main arm64 liblsan0 arm64 15.2.0-12ubuntu1 [1316 kB] 611s Get:17 http://ftpmaster.internal/ubuntu resolute/main arm64 libtsan2 arm64 15.2.0-12ubuntu1 [2688 kB] 615s Get:18 http://ftpmaster.internal/ubuntu resolute/main arm64 libubsan1 arm64 15.2.0-12ubuntu1 [1175 kB] 618s Get:19 http://ftpmaster.internal/ubuntu resolute/main arm64 libhwasan0 arm64 15.2.0-12ubuntu1 [1638 kB] 620s Get:20 http://ftpmaster.internal/ubuntu resolute/main arm64 libgcc-15-dev arm64 15.2.0-12ubuntu1 [2600 kB] 624s Get:21 http://ftpmaster.internal/ubuntu resolute/main arm64 gcc-15-aarch64-linux-gnu arm64 15.2.0-12ubuntu1 [23.1 MB] 659s Get:22 http://ftpmaster.internal/ubuntu resolute/main arm64 gcc-15 arm64 15.2.0-12ubuntu1 [519 kB] 659s Get:23 http://ftpmaster.internal/ubuntu resolute/main arm64 gcc-aarch64-linux-gnu arm64 4:15.2.0-4ubuntu1 [1206 B] 659s Get:24 http://ftpmaster.internal/ubuntu resolute/main arm64 gcc arm64 4:15.2.0-4ubuntu1 [5016 B] 659s Get:25 http://ftpmaster.internal/ubuntu resolute/main arm64 libstdc++-15-dev arm64 15.2.0-12ubuntu1 [2549 kB] 663s Get:26 http://ftpmaster.internal/ubuntu resolute/main arm64 g++-15-aarch64-linux-gnu arm64 15.2.0-12ubuntu1 [13.2 MB] 683s Get:27 http://ftpmaster.internal/ubuntu resolute/main arm64 g++-15 arm64 15.2.0-12ubuntu1 [25.3 kB] 683s Get:28 http://ftpmaster.internal/ubuntu resolute/main arm64 g++-aarch64-linux-gnu arm64 4:15.2.0-4ubuntu1 [956 B] 683s Get:29 http://ftpmaster.internal/ubuntu resolute/main arm64 g++ arm64 4:15.2.0-4ubuntu1 [1080 B] 683s Get:30 http://ftpmaster.internal/ubuntu resolute/main arm64 build-essential arm64 12.12ubuntu2 [5254 B] 683s Get:31 http://ftpmaster.internal/ubuntu resolute/main arm64 dctrl-tools arm64 2.24-3build4 [102 kB] 683s Get:32 http://ftpmaster.internal/ubuntu resolute/main arm64 fonts-dejavu-mono all 2.37-8build1 [502 kB] 683s Get:33 http://ftpmaster.internal/ubuntu resolute/main arm64 fonts-dejavu-core all 2.37-8build1 [834 kB] 685s Get:34 http://ftpmaster.internal/ubuntu resolute/main arm64 fontconfig-config arm64 2.17.1-3ubuntu1 [38.5 kB] 685s Get:35 http://ftpmaster.internal/ubuntu resolute/main arm64 libfontconfig1 arm64 2.17.1-3ubuntu1 [144 kB] 685s Get:36 http://ftpmaster.internal/ubuntu resolute/main arm64 fontconfig arm64 2.17.1-3ubuntu1 [181 kB] 685s Get:37 http://ftpmaster.internal/ubuntu resolute/main arm64 libgfortran5 arm64 15.2.0-12ubuntu1 [451 kB] 685s Get:38 http://ftpmaster.internal/ubuntu resolute/main arm64 libgfortran-15-dev arm64 15.2.0-12ubuntu1 [490 kB] 685s Get:39 http://ftpmaster.internal/ubuntu resolute/main arm64 gfortran-15-aarch64-linux-gnu arm64 15.2.0-12ubuntu1 [12.5 MB] 705s Get:40 http://ftpmaster.internal/ubuntu resolute/main arm64 gfortran-15 arm64 15.2.0-12ubuntu1 [18.1 kB] 705s Get:41 http://ftpmaster.internal/ubuntu resolute/main arm64 gfortran-aarch64-linux-gnu arm64 4:15.2.0-4ubuntu1 [1022 B] 705s Get:42 http://ftpmaster.internal/ubuntu resolute/main arm64 gfortran arm64 4:15.2.0-4ubuntu1 [1160 B] 705s Get:43 http://ftpmaster.internal/ubuntu resolute/main arm64 icu-devtools arm64 78.2-1ubuntu1 [207 kB] 706s Get:44 http://ftpmaster.internal/ubuntu resolute/main arm64 libblas3 arm64 3.12.1-7ubuntu1 [181 kB] 706s Get:45 http://ftpmaster.internal/ubuntu resolute/main arm64 libblas-dev arm64 3.12.1-7ubuntu1 [160 kB] 706s Get:46 http://ftpmaster.internal/ubuntu resolute/main arm64 libbz2-dev arm64 1.0.8-6build2 [34.9 kB] 706s Get:47 http://ftpmaster.internal/ubuntu resolute/main arm64 libpixman-1-0 arm64 0.46.4-1 [204 kB] 706s Get:48 http://ftpmaster.internal/ubuntu resolute/main arm64 libxcb-render0 arm64 1.17.0-2ubuntu1 [16.4 kB] 706s Get:49 http://ftpmaster.internal/ubuntu resolute/main arm64 libxcb-shm0 arm64 1.17.0-2ubuntu1 [5938 B] 706s Get:50 http://ftpmaster.internal/ubuntu resolute/main arm64 libxrender1 arm64 1:0.9.12-1 [19.5 kB] 706s Get:51 http://ftpmaster.internal/ubuntu resolute/main arm64 libcairo2 arm64 1.18.4-3 [556 kB] 706s Get:52 http://ftpmaster.internal/ubuntu resolute/main arm64 libdatrie1 arm64 0.2.14-1 [19.6 kB] 706s Get:53 http://ftpmaster.internal/ubuntu resolute/main arm64 libdeflate0 arm64 1.23-2build1 [46.8 kB] 706s Get:54 http://ftpmaster.internal/ubuntu resolute/main arm64 libdeflate-dev arm64 1.23-2build1 [54.3 kB] 706s Get:55 http://ftpmaster.internal/ubuntu resolute/main arm64 libgraphite2-3 arm64 1.3.14-11ubuntu1 [72.1 kB] 707s Get:56 http://ftpmaster.internal/ubuntu resolute/main arm64 libharfbuzz0b arm64 12.3.2-1 [510 kB] 707s Get:57 http://ftpmaster.internal/ubuntu resolute/main arm64 x11-common all 1:7.7+24ubuntu1 [22.4 kB] 707s Get:58 http://ftpmaster.internal/ubuntu resolute/main arm64 libice6 arm64 2:1.1.1-1build1 [43.0 kB] 707s Get:59 http://ftpmaster.internal/ubuntu resolute/main arm64 libicu-dev arm64 78.2-1ubuntu1 [12.5 MB] 725s Get:60 http://ftpmaster.internal/ubuntu resolute/main arm64 libjpeg-turbo8 arm64 2.1.5-4ubuntu3 [161 kB] 725s Get:61 http://ftpmaster.internal/ubuntu resolute/main arm64 libjpeg-turbo8-dev arm64 2.1.5-4ubuntu3 [301 kB] 725s Get:62 http://ftpmaster.internal/ubuntu resolute/main arm64 libjpeg8 arm64 8c-2ubuntu11 [2148 B] 725s Get:63 http://ftpmaster.internal/ubuntu resolute/main arm64 libjpeg8-dev arm64 8c-2ubuntu11 [1484 B] 725s Get:64 http://ftpmaster.internal/ubuntu resolute/main arm64 libjpeg-dev arm64 8c-2ubuntu11 [1482 B] 725s Get:65 http://ftpmaster.internal/ubuntu resolute/main arm64 liblapack3 arm64 3.12.1-7ubuntu1 [2299 kB] 729s Get:66 http://ftpmaster.internal/ubuntu resolute/main arm64 liblapack-dev arm64 3.12.1-7ubuntu1 [4456 kB] 736s Get:67 http://ftpmaster.internal/ubuntu resolute/main arm64 liblerc4 arm64 4.0.0+ds-5ubuntu2 [174 kB] 736s Get:68 http://ftpmaster.internal/ubuntu resolute/main arm64 libncurses-dev arm64 6.6+20251231-1 [391 kB] 736s Get:69 http://ftpmaster.internal/ubuntu resolute/main arm64 libthai-data all 0.1.30-1 [155 kB] 736s Get:70 http://ftpmaster.internal/ubuntu resolute/main arm64 libthai0 arm64 0.1.30-1 [18.3 kB] 736s Get:71 http://ftpmaster.internal/ubuntu resolute/main arm64 libpango-1.0-0 arm64 1.57.0-1 [238 kB] 737s Get:72 http://ftpmaster.internal/ubuntu resolute/main arm64 libpangoft2-1.0-0 arm64 1.57.0-1 [51.5 kB] 737s Get:73 http://ftpmaster.internal/ubuntu resolute/main arm64 libpangocairo-1.0-0 arm64 1.57.0-1 [27.9 kB] 737s Get:74 http://ftpmaster.internal/ubuntu resolute/main arm64 libpaper2 arm64 2.2.5-0.3build1 [17.3 kB] 737s Get:75 http://ftpmaster.internal/ubuntu resolute/main arm64 libpaper-utils arm64 2.2.5-0.3build1 [15.4 kB] 737s Get:76 http://ftpmaster.internal/ubuntu resolute/main arm64 libpcre2-16-0 arm64 10.46-1 [225 kB] 737s Get:77 http://ftpmaster.internal/ubuntu resolute/main arm64 libpcre2-32-0 arm64 10.46-1 [213 kB] 737s Get:78 http://ftpmaster.internal/ubuntu resolute/main arm64 libpcre2-posix3 arm64 10.46-1 [7300 B] 737s Get:79 http://ftpmaster.internal/ubuntu resolute/main arm64 libpcre2-dev arm64 10.46-1 [772 kB] 738s Get:80 http://ftpmaster.internal/ubuntu resolute/main arm64 libpkgconf3 arm64 1.8.1-4build1 [33.7 kB] 738s Get:81 http://ftpmaster.internal/ubuntu resolute/main arm64 zlib1g-dev arm64 1:1.3.dfsg+really1.3.1-1ubuntu2 [899 kB] 740s Get:82 http://ftpmaster.internal/ubuntu resolute/main arm64 libpng-dev arm64 1.6.54-1 [268 kB] 740s Get:83 http://ftpmaster.internal/ubuntu resolute/main arm64 libreadline-dev arm64 8.3-3 [199 kB] 740s Get:84 http://ftpmaster.internal/ubuntu resolute/main arm64 libsharpyuv0 arm64 1.5.0-0.1build1 [16.7 kB] 740s Get:85 http://ftpmaster.internal/ubuntu resolute/main arm64 libsm6 arm64 2:1.2.6-1build1 [16.8 kB] 740s Get:86 http://ftpmaster.internal/ubuntu resolute/main arm64 libtcl8.6 arm64 8.6.17+dfsg-1build1 [983 kB] 741s Get:87 http://ftpmaster.internal/ubuntu resolute/main arm64 libjbig0 arm64 2.1-6.1ubuntu3 [29.2 kB] 741s Get:88 http://ftpmaster.internal/ubuntu resolute/main arm64 libwebp7 arm64 1.5.0-0.1build1 [205 kB] 741s Get:89 http://ftpmaster.internal/ubuntu resolute/main arm64 libtiff6 arm64 4.7.0-3ubuntu3 [196 kB] 741s Get:90 http://ftpmaster.internal/ubuntu resolute/main arm64 libxft2 arm64 2.3.6-1build2 [43.2 kB] 741s Get:91 http://ftpmaster.internal/ubuntu resolute/main arm64 libxss1 arm64 1:1.2.3-1build4 [7102 B] 741s Get:92 http://ftpmaster.internal/ubuntu resolute/main arm64 libtk8.6 arm64 8.6.17-1 [811 kB] 743s Get:93 http://ftpmaster.internal/ubuntu resolute/main arm64 libxt6t64 arm64 1:1.2.1-1.3 [168 kB] 743s Get:94 http://ftpmaster.internal/ubuntu resolute/main arm64 libzstd-dev arm64 1.5.7+dfsg-3 [349 kB] 743s Get:95 http://ftpmaster.internal/ubuntu resolute/main arm64 zip arm64 3.0-15ubuntu3 [170 kB] 743s Get:96 http://ftpmaster.internal/ubuntu resolute/main arm64 unzip arm64 6.0-29ubuntu1 [176 kB] 743s Get:97 http://ftpmaster.internal/ubuntu resolute/main arm64 xdg-utils all 1.2.1-2ubuntu2 [66.1 kB] 743s Get:98 http://ftpmaster.internal/ubuntu resolute/universe arm64 r-base-core arm64 4.5.2-1ubuntu2 [28.6 MB] 791s Get:99 http://ftpmaster.internal/ubuntu resolute/main arm64 liblzma-dev arm64 5.8.2-2 [180 kB] 791s Get:100 http://ftpmaster.internal/ubuntu resolute/main arm64 pkgconf-bin arm64 1.8.1-4build1 [21.7 kB] 791s Get:101 http://ftpmaster.internal/ubuntu resolute/main arm64 pkgconf arm64 1.8.1-4build1 [16.8 kB] 791s Get:102 http://ftpmaster.internal/ubuntu resolute/main arm64 libtirpc-dev arm64 1.3.6+ds-1 [202 kB] 791s Get:103 http://ftpmaster.internal/ubuntu resolute/universe arm64 r-base-dev all 4.5.2-1ubuntu2 [1880 B] 791s Get:104 http://ftpmaster.internal/ubuntu resolute/universe arm64 pkg-r-autopkgtest all 20250812 [6158 B] 791s Get:105 http://ftpmaster.internal/ubuntu resolute/universe arm64 r-bioc-biocgenerics all 0.52.0-2 [624 kB] 792s Get:106 http://ftpmaster.internal/ubuntu resolute/universe arm64 r-cran-r.methodss3 all 1.8.2-1 [84.0 kB] 792s Get:107 http://ftpmaster.internal/ubuntu resolute/universe arm64 r-cran-r.oo all 1.27.1-1 [978 kB] 794s Get:108 http://ftpmaster.internal/ubuntu resolute/universe arm64 r-cran-r.utils all 2.13.0-1 [1423 kB] 797s Get:109 http://ftpmaster.internal/ubuntu resolute/universe arm64 r-cran-matrixstats arm64 1.5.0-1 [496 kB] 797s Get:110 http://ftpmaster.internal/ubuntu resolute/universe arm64 r-bioc-aroma.light all 3.36.0-2 [583 kB] 798s Get:111 http://ftpmaster.internal/ubuntu resolute/universe arm64 r-bioc-dnacopy arm64 1.80.0-2 [497 kB] 799s Get:112 http://ftpmaster.internal/ubuntu resolute/universe arm64 r-cran-cli arm64 3.6.4-1 [1374 kB] 802s Get:113 http://ftpmaster.internal/ubuntu resolute/universe arm64 r-cran-codetools all 0.2-20-1build1 [91.1 kB] 802s Get:114 http://ftpmaster.internal/ubuntu resolute/universe arm64 r-cran-digest arm64 0.6.39-1 [196 kB] 802s Get:115 http://ftpmaster.internal/ubuntu resolute/universe arm64 r-cran-farver arm64 2.1.2-1 [1344 kB] 805s Get:116 http://ftpmaster.internal/ubuntu resolute/universe arm64 r-cran-globals all 0.19.0-1 [160 kB] 805s Get:117 http://ftpmaster.internal/ubuntu resolute/universe arm64 r-cran-listenv all 0.10.0+dfsg-1 [113 kB] 805s Get:118 http://ftpmaster.internal/ubuntu resolute/universe arm64 r-cran-parallelly arm64 1.42.0-1 [540 kB] 806s Get:119 http://ftpmaster.internal/ubuntu resolute/universe arm64 r-cran-future all 1.34.0+dfsg-1 [646 kB] 808s Get:120 http://ftpmaster.internal/ubuntu resolute/universe arm64 r-cran-glue arm64 1.8.0-1 [163 kB] 808s Get:121 http://ftpmaster.internal/ubuntu resolute/universe arm64 r-cran-rlang arm64 1.1.5-3 [1706 kB] 811s Get:122 http://ftpmaster.internal/ubuntu resolute/universe arm64 r-cran-lifecycle all 1.0.5+dfsg-1 [120 kB] 811s Get:123 http://ftpmaster.internal/ubuntu resolute/universe arm64 r-cran-gtable all 0.3.6+dfsg-1 [199 kB] 811s Get:124 http://ftpmaster.internal/ubuntu resolute/universe arm64 r-cran-isoband arm64 0.2.7-1 [1481 kB] 814s Get:125 http://ftpmaster.internal/ubuntu resolute/universe arm64 r-cran-s7 arm64 0.2.0-1 [329 kB] 814s Get:126 http://ftpmaster.internal/ubuntu resolute/universe arm64 r-cran-labeling all 0.4.3-1 [62.1 kB] 814s Get:127 http://ftpmaster.internal/ubuntu resolute/universe arm64 r-cran-r6 all 2.6.1-1 [101 kB] 814s Get:128 http://ftpmaster.internal/ubuntu resolute/universe arm64 r-cran-rcolorbrewer all 1.1-3-1build2 [54.0 kB] 814s Get:129 http://ftpmaster.internal/ubuntu resolute/universe arm64 r-cran-viridislite all 0.4.3-1 [1088 kB] 817s Get:130 http://ftpmaster.internal/ubuntu resolute/universe arm64 r-cran-scales all 1.4.0-1 [725 kB] 818s Get:131 http://ftpmaster.internal/ubuntu resolute/universe arm64 r-cran-vctrs arm64 0.6.5-1 [1327 kB] 820s Get:132 http://ftpmaster.internal/ubuntu resolute/universe arm64 r-cran-withr all 3.0.2+dfsg-1 [214 kB] 820s Get:133 http://ftpmaster.internal/ubuntu resolute-proposed/universe arm64 r-cran-ggplot2 all 4.0.2+dfsg-1 [4941 kB] 828s Get:134 http://ftpmaster.internal/ubuntu resolute/universe arm64 r-cran-r.cache all 0.17.0-1 [117 kB] 829s Get:135 http://ftpmaster.internal/ubuntu resolute/universe arm64 r-cran-pscbs all 0.68.0-1 [4234 kB] 836s Preconfiguring packages ... 836s Fetched 167 MB in 4min 15s (657 kB/s) 836s Selecting previously unselected package libc-dev-bin. 836s (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 ... 136600 files and directories currently installed.) 836s Preparing to unpack .../000-libc-dev-bin_2.42-2ubuntu4_arm64.deb ... 836s Unpacking libc-dev-bin (2.42-2ubuntu4) ... 836s Selecting previously unselected package linux-libc-dev:arm64. 836s Preparing to unpack .../001-linux-libc-dev_6.19.0-3.3_arm64.deb ... 836s Unpacking linux-libc-dev:arm64 (6.19.0-3.3) ... 837s Selecting previously unselected package libcrypt-dev:arm64. 837s Preparing to unpack .../002-libcrypt-dev_1%3a4.5.1-1_arm64.deb ... 837s Unpacking libcrypt-dev:arm64 (1:4.5.1-1) ... 837s Selecting previously unselected package rpcsvc-proto. 837s Preparing to unpack .../003-rpcsvc-proto_1.4.3-1build1_arm64.deb ... 837s Unpacking rpcsvc-proto (1.4.3-1build1) ... 837s Selecting previously unselected package libc6-dev:arm64. 837s Preparing to unpack .../004-libc6-dev_2.42-2ubuntu4_arm64.deb ... 837s Unpacking libc6-dev:arm64 (2.42-2ubuntu4) ... 837s Selecting previously unselected package libisl23:arm64. 837s Preparing to unpack .../005-libisl23_0.27-1build1_arm64.deb ... 837s Unpacking libisl23:arm64 (0.27-1build1) ... 837s Selecting previously unselected package libmpc3:arm64. 837s Preparing to unpack .../006-libmpc3_1.3.1-2_arm64.deb ... 837s Unpacking libmpc3:arm64 (1.3.1-2) ... 837s Selecting previously unselected package cpp-15-aarch64-linux-gnu. 837s Preparing to unpack .../007-cpp-15-aarch64-linux-gnu_15.2.0-12ubuntu1_arm64.deb ... 837s Unpacking cpp-15-aarch64-linux-gnu (15.2.0-12ubuntu1) ... 837s Selecting previously unselected package cpp-15. 837s Preparing to unpack .../008-cpp-15_15.2.0-12ubuntu1_arm64.deb ... 837s Unpacking cpp-15 (15.2.0-12ubuntu1) ... 837s Selecting previously unselected package cpp-aarch64-linux-gnu. 837s Preparing to unpack .../009-cpp-aarch64-linux-gnu_4%3a15.2.0-4ubuntu1_arm64.deb ... 837s Unpacking cpp-aarch64-linux-gnu (4:15.2.0-4ubuntu1) ... 837s Selecting previously unselected package cpp. 837s Preparing to unpack .../010-cpp_4%3a15.2.0-4ubuntu1_arm64.deb ... 837s Unpacking cpp (4:15.2.0-4ubuntu1) ... 837s Selecting previously unselected package libcc1-0:arm64. 837s Preparing to unpack .../011-libcc1-0_15.2.0-12ubuntu1_arm64.deb ... 837s Unpacking libcc1-0:arm64 (15.2.0-12ubuntu1) ... 837s Selecting previously unselected package libgomp1:arm64. 837s Preparing to unpack .../012-libgomp1_15.2.0-12ubuntu1_arm64.deb ... 837s Unpacking libgomp1:arm64 (15.2.0-12ubuntu1) ... 837s Selecting previously unselected package libitm1:arm64. 837s Preparing to unpack .../013-libitm1_15.2.0-12ubuntu1_arm64.deb ... 837s Unpacking libitm1:arm64 (15.2.0-12ubuntu1) ... 837s Selecting previously unselected package libasan8:arm64. 837s Preparing to unpack .../014-libasan8_15.2.0-12ubuntu1_arm64.deb ... 837s Unpacking libasan8:arm64 (15.2.0-12ubuntu1) ... 837s Selecting previously unselected package liblsan0:arm64. 837s Preparing to unpack .../015-liblsan0_15.2.0-12ubuntu1_arm64.deb ... 837s Unpacking liblsan0:arm64 (15.2.0-12ubuntu1) ... 837s Selecting previously unselected package libtsan2:arm64. 837s Preparing to unpack .../016-libtsan2_15.2.0-12ubuntu1_arm64.deb ... 837s Unpacking libtsan2:arm64 (15.2.0-12ubuntu1) ... 838s Selecting previously unselected package libubsan1:arm64. 838s Preparing to unpack .../017-libubsan1_15.2.0-12ubuntu1_arm64.deb ... 838s Unpacking libubsan1:arm64 (15.2.0-12ubuntu1) ... 838s Selecting previously unselected package libhwasan0:arm64. 838s Preparing to unpack .../018-libhwasan0_15.2.0-12ubuntu1_arm64.deb ... 838s Unpacking libhwasan0:arm64 (15.2.0-12ubuntu1) ... 838s Selecting previously unselected package libgcc-15-dev:arm64. 838s Preparing to unpack .../019-libgcc-15-dev_15.2.0-12ubuntu1_arm64.deb ... 838s Unpacking libgcc-15-dev:arm64 (15.2.0-12ubuntu1) ... 838s Selecting previously unselected package gcc-15-aarch64-linux-gnu. 838s Preparing to unpack .../020-gcc-15-aarch64-linux-gnu_15.2.0-12ubuntu1_arm64.deb ... 838s Unpacking gcc-15-aarch64-linux-gnu (15.2.0-12ubuntu1) ... 838s Selecting previously unselected package gcc-15. 838s Preparing to unpack .../021-gcc-15_15.2.0-12ubuntu1_arm64.deb ... 838s Unpacking gcc-15 (15.2.0-12ubuntu1) ... 838s Selecting previously unselected package gcc-aarch64-linux-gnu. 838s Preparing to unpack .../022-gcc-aarch64-linux-gnu_4%3a15.2.0-4ubuntu1_arm64.deb ... 838s Unpacking gcc-aarch64-linux-gnu (4:15.2.0-4ubuntu1) ... 838s Selecting previously unselected package gcc. 838s Preparing to unpack .../023-gcc_4%3a15.2.0-4ubuntu1_arm64.deb ... 838s Unpacking gcc (4:15.2.0-4ubuntu1) ... 838s Selecting previously unselected package libstdc++-15-dev:arm64. 838s Preparing to unpack .../024-libstdc++-15-dev_15.2.0-12ubuntu1_arm64.deb ... 838s Unpacking libstdc++-15-dev:arm64 (15.2.0-12ubuntu1) ... 838s Selecting previously unselected package g++-15-aarch64-linux-gnu. 838s Preparing to unpack .../025-g++-15-aarch64-linux-gnu_15.2.0-12ubuntu1_arm64.deb ... 838s Unpacking g++-15-aarch64-linux-gnu (15.2.0-12ubuntu1) ... 839s Selecting previously unselected package g++-15. 839s Preparing to unpack .../026-g++-15_15.2.0-12ubuntu1_arm64.deb ... 839s Unpacking g++-15 (15.2.0-12ubuntu1) ... 839s Selecting previously unselected package g++-aarch64-linux-gnu. 839s Preparing to unpack .../027-g++-aarch64-linux-gnu_4%3a15.2.0-4ubuntu1_arm64.deb ... 839s Unpacking g++-aarch64-linux-gnu (4:15.2.0-4ubuntu1) ... 839s Selecting previously unselected package g++. 839s Preparing to unpack .../028-g++_4%3a15.2.0-4ubuntu1_arm64.deb ... 839s Unpacking g++ (4:15.2.0-4ubuntu1) ... 839s Selecting previously unselected package build-essential. 839s Preparing to unpack .../029-build-essential_12.12ubuntu2_arm64.deb ... 839s Unpacking build-essential (12.12ubuntu2) ... 839s Selecting previously unselected package dctrl-tools. 839s Preparing to unpack .../030-dctrl-tools_2.24-3build4_arm64.deb ... 839s Unpacking dctrl-tools (2.24-3build4) ... 839s Selecting previously unselected package fonts-dejavu-mono. 839s Preparing to unpack .../031-fonts-dejavu-mono_2.37-8build1_all.deb ... 839s Unpacking fonts-dejavu-mono (2.37-8build1) ... 839s Selecting previously unselected package fonts-dejavu-core. 839s Preparing to unpack .../032-fonts-dejavu-core_2.37-8build1_all.deb ... 839s Unpacking fonts-dejavu-core (2.37-8build1) ... 839s Selecting previously unselected package fontconfig-config. 839s Preparing to unpack .../033-fontconfig-config_2.17.1-3ubuntu1_arm64.deb ... 839s Unpacking fontconfig-config (2.17.1-3ubuntu1) ... 839s Selecting previously unselected package libfontconfig1:arm64. 839s Preparing to unpack .../034-libfontconfig1_2.17.1-3ubuntu1_arm64.deb ... 839s Unpacking libfontconfig1:arm64 (2.17.1-3ubuntu1) ... 839s Selecting previously unselected package fontconfig. 839s Preparing to unpack .../035-fontconfig_2.17.1-3ubuntu1_arm64.deb ... 839s Unpacking fontconfig (2.17.1-3ubuntu1) ... 839s Selecting previously unselected package libgfortran5:arm64. 839s Preparing to unpack .../036-libgfortran5_15.2.0-12ubuntu1_arm64.deb ... 839s Unpacking libgfortran5:arm64 (15.2.0-12ubuntu1) ... 840s Selecting previously unselected package libgfortran-15-dev:arm64. 840s Preparing to unpack .../037-libgfortran-15-dev_15.2.0-12ubuntu1_arm64.deb ... 840s Unpacking libgfortran-15-dev:arm64 (15.2.0-12ubuntu1) ... 840s Selecting previously unselected package gfortran-15-aarch64-linux-gnu. 840s Preparing to unpack .../038-gfortran-15-aarch64-linux-gnu_15.2.0-12ubuntu1_arm64.deb ... 840s Unpacking gfortran-15-aarch64-linux-gnu (15.2.0-12ubuntu1) ... 840s Selecting previously unselected package gfortran-15. 840s Preparing to unpack .../039-gfortran-15_15.2.0-12ubuntu1_arm64.deb ... 840s Unpacking gfortran-15 (15.2.0-12ubuntu1) ... 840s Selecting previously unselected package gfortran-aarch64-linux-gnu. 840s Preparing to unpack .../040-gfortran-aarch64-linux-gnu_4%3a15.2.0-4ubuntu1_arm64.deb ... 840s Unpacking gfortran-aarch64-linux-gnu (4:15.2.0-4ubuntu1) ... 840s Selecting previously unselected package gfortran. 840s Preparing to unpack .../041-gfortran_4%3a15.2.0-4ubuntu1_arm64.deb ... 840s Unpacking gfortran (4:15.2.0-4ubuntu1) ... 840s Selecting previously unselected package icu-devtools. 840s Preparing to unpack .../042-icu-devtools_78.2-1ubuntu1_arm64.deb ... 840s Unpacking icu-devtools (78.2-1ubuntu1) ... 840s Selecting previously unselected package libblas3:arm64. 840s Preparing to unpack .../043-libblas3_3.12.1-7ubuntu1_arm64.deb ... 840s Unpacking libblas3:arm64 (3.12.1-7ubuntu1) ... 840s Selecting previously unselected package libblas-dev:arm64. 840s Preparing to unpack .../044-libblas-dev_3.12.1-7ubuntu1_arm64.deb ... 840s Unpacking libblas-dev:arm64 (3.12.1-7ubuntu1) ... 840s Selecting previously unselected package libbz2-dev:arm64. 840s Preparing to unpack .../045-libbz2-dev_1.0.8-6build2_arm64.deb ... 840s Unpacking libbz2-dev:arm64 (1.0.8-6build2) ... 840s Selecting previously unselected package libpixman-1-0:arm64. 840s Preparing to unpack .../046-libpixman-1-0_0.46.4-1_arm64.deb ... 840s Unpacking libpixman-1-0:arm64 (0.46.4-1) ... 840s Selecting previously unselected package libxcb-render0:arm64. 840s Preparing to unpack .../047-libxcb-render0_1.17.0-2ubuntu1_arm64.deb ... 840s Unpacking libxcb-render0:arm64 (1.17.0-2ubuntu1) ... 840s Selecting previously unselected package libxcb-shm0:arm64. 840s Preparing to unpack .../048-libxcb-shm0_1.17.0-2ubuntu1_arm64.deb ... 840s Unpacking libxcb-shm0:arm64 (1.17.0-2ubuntu1) ... 840s Selecting previously unselected package libxrender1:arm64. 840s Preparing to unpack .../049-libxrender1_1%3a0.9.12-1_arm64.deb ... 840s Unpacking libxrender1:arm64 (1:0.9.12-1) ... 840s Selecting previously unselected package libcairo2:arm64. 840s Preparing to unpack .../050-libcairo2_1.18.4-3_arm64.deb ... 840s Unpacking libcairo2:arm64 (1.18.4-3) ... 840s Selecting previously unselected package libdatrie1:arm64. 840s Preparing to unpack .../051-libdatrie1_0.2.14-1_arm64.deb ... 840s Unpacking libdatrie1:arm64 (0.2.14-1) ... 840s Selecting previously unselected package libdeflate0:arm64. 840s Preparing to unpack .../052-libdeflate0_1.23-2build1_arm64.deb ... 840s Unpacking libdeflate0:arm64 (1.23-2build1) ... 840s Selecting previously unselected package libdeflate-dev:arm64. 840s Preparing to unpack .../053-libdeflate-dev_1.23-2build1_arm64.deb ... 840s Unpacking libdeflate-dev:arm64 (1.23-2build1) ... 840s Selecting previously unselected package libgraphite2-3:arm64. 840s Preparing to unpack .../054-libgraphite2-3_1.3.14-11ubuntu1_arm64.deb ... 840s Unpacking libgraphite2-3:arm64 (1.3.14-11ubuntu1) ... 840s Selecting previously unselected package libharfbuzz0b:arm64. 840s Preparing to unpack .../055-libharfbuzz0b_12.3.2-1_arm64.deb ... 840s Unpacking libharfbuzz0b:arm64 (12.3.2-1) ... 840s Selecting previously unselected package x11-common. 840s Preparing to unpack .../056-x11-common_1%3a7.7+24ubuntu1_all.deb ... 840s Unpacking x11-common (1:7.7+24ubuntu1) ... 840s Selecting previously unselected package libice6:arm64. 840s Preparing to unpack .../057-libice6_2%3a1.1.1-1build1_arm64.deb ... 840s Unpacking libice6:arm64 (2:1.1.1-1build1) ... 841s Selecting previously unselected package libicu-dev:arm64. 841s Preparing to unpack .../058-libicu-dev_78.2-1ubuntu1_arm64.deb ... 841s Unpacking libicu-dev:arm64 (78.2-1ubuntu1) ... 841s Selecting previously unselected package libjpeg-turbo8:arm64. 841s Preparing to unpack .../059-libjpeg-turbo8_2.1.5-4ubuntu3_arm64.deb ... 841s Unpacking libjpeg-turbo8:arm64 (2.1.5-4ubuntu3) ... 841s Selecting previously unselected package libjpeg-turbo8-dev:arm64. 841s Preparing to unpack .../060-libjpeg-turbo8-dev_2.1.5-4ubuntu3_arm64.deb ... 841s Unpacking libjpeg-turbo8-dev:arm64 (2.1.5-4ubuntu3) ... 841s Selecting previously unselected package libjpeg8:arm64. 841s Preparing to unpack .../061-libjpeg8_8c-2ubuntu11_arm64.deb ... 841s Unpacking libjpeg8:arm64 (8c-2ubuntu11) ... 841s Selecting previously unselected package libjpeg8-dev:arm64. 841s Preparing to unpack .../062-libjpeg8-dev_8c-2ubuntu11_arm64.deb ... 841s Unpacking libjpeg8-dev:arm64 (8c-2ubuntu11) ... 841s Selecting previously unselected package libjpeg-dev:arm64. 841s Preparing to unpack .../063-libjpeg-dev_8c-2ubuntu11_arm64.deb ... 841s Unpacking libjpeg-dev:arm64 (8c-2ubuntu11) ... 841s Selecting previously unselected package liblapack3:arm64. 841s Preparing to unpack .../064-liblapack3_3.12.1-7ubuntu1_arm64.deb ... 841s Unpacking liblapack3:arm64 (3.12.1-7ubuntu1) ... 841s Selecting previously unselected package liblapack-dev:arm64. 841s Preparing to unpack .../065-liblapack-dev_3.12.1-7ubuntu1_arm64.deb ... 841s Unpacking liblapack-dev:arm64 (3.12.1-7ubuntu1) ... 841s Selecting previously unselected package liblerc4:arm64. 841s Preparing to unpack .../066-liblerc4_4.0.0+ds-5ubuntu2_arm64.deb ... 841s Unpacking liblerc4:arm64 (4.0.0+ds-5ubuntu2) ... 841s Selecting previously unselected package libncurses-dev:arm64. 841s Preparing to unpack .../067-libncurses-dev_6.6+20251231-1_arm64.deb ... 841s Unpacking libncurses-dev:arm64 (6.6+20251231-1) ... 841s Selecting previously unselected package libthai-data. 841s Preparing to unpack .../068-libthai-data_0.1.30-1_all.deb ... 841s Unpacking libthai-data (0.1.30-1) ... 841s Selecting previously unselected package libthai0:arm64. 841s Preparing to unpack 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previously unselected package zlib1g-dev:arm64. 842s Preparing to unpack .../080-zlib1g-dev_1%3a1.3.dfsg+really1.3.1-1ubuntu2_arm64.deb ... 842s Unpacking zlib1g-dev:arm64 (1:1.3.dfsg+really1.3.1-1ubuntu2) ... 842s Selecting previously unselected package libpng-dev:arm64. 842s Preparing to unpack .../081-libpng-dev_1.6.54-1_arm64.deb ... 842s Unpacking libpng-dev:arm64 (1.6.54-1) ... 842s Selecting previously unselected package libreadline-dev:arm64. 842s Preparing to unpack .../082-libreadline-dev_8.3-3_arm64.deb ... 842s Unpacking libreadline-dev:arm64 (8.3-3) ... 842s Selecting previously unselected package libsharpyuv0:arm64. 842s Preparing to unpack .../083-libsharpyuv0_1.5.0-0.1build1_arm64.deb ... 842s Unpacking libsharpyuv0:arm64 (1.5.0-0.1build1) ... 842s Selecting previously unselected package libsm6:arm64. 842s Preparing to unpack .../084-libsm6_2%3a1.2.6-1build1_arm64.deb ... 842s Unpacking libsm6:arm64 (2:1.2.6-1build1) ... 842s Selecting previously unselected package libtcl8.6:arm64. 842s Preparing to unpack .../085-libtcl8.6_8.6.17+dfsg-1build1_arm64.deb ... 842s Unpacking libtcl8.6:arm64 (8.6.17+dfsg-1build1) ... 842s Selecting previously unselected package libjbig0:arm64. 842s Preparing to unpack .../086-libjbig0_2.1-6.1ubuntu3_arm64.deb ... 842s Unpacking libjbig0:arm64 (2.1-6.1ubuntu3) ... 842s Selecting previously unselected package libwebp7:arm64. 842s Preparing to unpack .../087-libwebp7_1.5.0-0.1build1_arm64.deb ... 842s Unpacking libwebp7:arm64 (1.5.0-0.1build1) ... 842s Selecting previously unselected package libtiff6:arm64. 842s Preparing to unpack .../088-libtiff6_4.7.0-3ubuntu3_arm64.deb ... 842s Unpacking libtiff6:arm64 (4.7.0-3ubuntu3) ... 842s Selecting previously unselected package libxft2:arm64. 842s Preparing to unpack .../089-libxft2_2.3.6-1build2_arm64.deb ... 842s Unpacking libxft2:arm64 (2.3.6-1build2) ... 842s Selecting previously unselected package libxss1:arm64. 842s Preparing to unpack .../090-libxss1_1%3a1.2.3-1build4_arm64.deb ... 842s Unpacking libxss1:arm64 (1:1.2.3-1build4) ... 842s Selecting previously unselected package libtk8.6:arm64. 842s Preparing to unpack .../091-libtk8.6_8.6.17-1_arm64.deb ... 842s Unpacking libtk8.6:arm64 (8.6.17-1) ... 842s Selecting previously unselected package libxt6t64:arm64. 843s Preparing to unpack .../092-libxt6t64_1%3a1.2.1-1.3_arm64.deb ... 843s Unpacking libxt6t64:arm64 (1:1.2.1-1.3) ... 843s Selecting previously unselected package libzstd-dev:arm64. 843s Preparing to unpack .../093-libzstd-dev_1.5.7+dfsg-3_arm64.deb ... 843s Unpacking libzstd-dev:arm64 (1.5.7+dfsg-3) ... 843s Selecting previously unselected package zip. 843s Preparing to unpack .../094-zip_3.0-15ubuntu3_arm64.deb ... 843s Unpacking zip (3.0-15ubuntu3) ... 843s Selecting previously unselected package unzip. 843s Preparing to unpack .../095-unzip_6.0-29ubuntu1_arm64.deb ... 843s Unpacking unzip (6.0-29ubuntu1) ... 843s Selecting previously unselected package xdg-utils. 843s Preparing to unpack .../096-xdg-utils_1.2.1-2ubuntu2_all.deb ... 843s Unpacking xdg-utils (1.2.1-2ubuntu2) ... 843s Selecting previously unselected package r-base-core. 843s Preparing to unpack .../097-r-base-core_4.5.2-1ubuntu2_arm64.deb ... 843s Unpacking r-base-core (4.5.2-1ubuntu2) ... 843s Selecting previously unselected package liblzma-dev:arm64. 843s Preparing to unpack .../098-liblzma-dev_5.8.2-2_arm64.deb ... 843s Unpacking liblzma-dev:arm64 (5.8.2-2) ... 843s Selecting previously unselected package pkgconf-bin. 843s Preparing to unpack .../099-pkgconf-bin_1.8.1-4build1_arm64.deb ... 843s Unpacking pkgconf-bin (1.8.1-4build1) ... 843s Selecting previously unselected package pkgconf:arm64. 843s Preparing to unpack .../100-pkgconf_1.8.1-4build1_arm64.deb ... 843s Unpacking pkgconf:arm64 (1.8.1-4build1) ... 843s Selecting previously unselected package libtirpc-dev:arm64. 843s Preparing to unpack .../101-libtirpc-dev_1.3.6+ds-1_arm64.deb ... 843s Unpacking 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previously unselected package r-cran-s7. 844s Preparing to unpack .../124-r-cran-s7_0.2.0-1_arm64.deb ... 844s Unpacking r-cran-s7 (0.2.0-1) ... 844s Selecting previously unselected package r-cran-labeling. 844s Preparing to unpack .../125-r-cran-labeling_0.4.3-1_all.deb ... 844s Unpacking r-cran-labeling (0.4.3-1) ... 844s Selecting previously unselected package r-cran-r6. 844s Preparing to unpack .../126-r-cran-r6_2.6.1-1_all.deb ... 844s Unpacking r-cran-r6 (2.6.1-1) ... 845s Selecting previously unselected package r-cran-rcolorbrewer. 845s Preparing to unpack .../127-r-cran-rcolorbrewer_1.1-3-1build2_all.deb ... 845s Unpacking r-cran-rcolorbrewer (1.1-3-1build2) ... 845s Selecting previously unselected package r-cran-viridislite. 845s Preparing to unpack .../128-r-cran-viridislite_0.4.3-1_all.deb ... 845s Unpacking r-cran-viridislite (0.4.3-1) ... 845s Selecting previously unselected package r-cran-scales. 845s Preparing to unpack .../129-r-cran-scales_1.4.0-1_all.deb ... 845s 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(0.19.0-1) ... 848s Setting up r-cran-vctrs (0.6.5-1) ... 848s Setting up r-base-dev (4.5.2-1ubuntu2) ... 848s Setting up r-cran-ggplot2 (4.0.2+dfsg-1) ... 848s Setting up r-cran-r.oo (1.27.1-1) ... 848s Setting up r-cran-future (1.34.0+dfsg-1) ... 848s Setting up pkg-r-autopkgtest (20250812) ... 848s Setting up r-cran-r.utils (2.13.0-1) ... 848s Setting up r-bioc-aroma.light (3.36.0-2) ... 848s Setting up r-cran-r.cache (0.17.0-1) ... 848s Setting up r-cran-pscbs (0.68.0-1) ... 848s Processing triggers for libc-bin (2.42-2ubuntu4) ... 848s Processing triggers for man-db (2.13.1-1build1) ... 849s Processing triggers for install-info (7.2-5) ... 851s autopkgtest [00:16:57]: test pkg-r-autopkgtest: /usr/share/dh-r/pkg-r-autopkgtest 851s autopkgtest [00:16:57]: test pkg-r-autopkgtest: [----------------------- 852s Test: Try to load the R library PSCBS 852s 852s R version 4.5.2 (2025-10-31) -- "[Not] Part in a Rumble" 852s Copyright (C) 2025 The R Foundation for Statistical Computing 852s Platform: aarch64-unknown-linux-gnu 852s 852s R is free software and comes with ABSOLUTELY NO WARRANTY. 852s You are welcome to redistribute it under certain conditions. 852s Type 'license()' or 'licence()' for distribution details. 852s 852s R is a collaborative project with many contributors. 852s Type 'contributors()' for more information and 852s 'citation()' on how to cite R or R packages in publications. 852s 852s Type 'demo()' for some demos, 'help()' for on-line help, or 852s 'help.start()' for an HTML browser interface to help. 852s Type 'q()' to quit R. 852s 852s > library('PSCBS') 852s PSCBS v0.68.0 (2025-04-18 19:40:02 UTC) successfully loaded. See ?PSCBS for help. 852s > 852s Test: Run tests for PSCBS 852s Start: PairedPSCBS,boot.R 852s 852s R version 4.5.2 (2025-10-31) -- "[Not] Part in a Rumble" 852s Copyright (C) 2025 The R Foundation for Statistical Computing 852s Platform: aarch64-unknown-linux-gnu 852s 852s R is free software and comes with ABSOLUTELY NO WARRANTY. 852s You are welcome to redistribute it under certain conditions. 852s Type 'license()' or 'licence()' for distribution details. 852s 852s R is a collaborative project with many contributors. 852s Type 'contributors()' for more information and 852s 'citation()' on how to cite R or R packages in publications. 852s 852s Type 'demo()' for some demos, 'help()' for on-line help, or 852s 'help.start()' for an HTML browser interface to help. 852s Type 'q()' to quit R. 852s 852s > ########################################################### 852s > # This tests: 852s > # - Bootstrapping for PairedPSCBS objects 852s > ########################################################### 852s > library("PSCBS") 852s PSCBS v0.68.0 (2025-04-18 19:40:02 UTC) successfully loaded. See ?PSCBS for help. 852s > 852s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 852s > # Load SNP microarray data 852s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 852s > data <- PSCBS::exampleData("paired.chr01") 853s > 853s > 853s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 853s > # Paired PSCBS segmentation 853s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 853s > # Drop single-locus outliers 853s > dataS <- dropSegmentationOutliers(data) 853s > dataS <- dataS[seq(from=1, to=nrow(data), by=5),] 853s > nSegs <- 4L 853s > str(dataS) 853s 'data.frame': 14670 obs. of 6 variables: 853s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 853s $ x : int 1145994 2941694 3710825 4240737 4276892 4464544 4714611 5095111 5034491 5158416 ... 853s $ CT : num 1.63 1.4 1.41 1.17 1.16 ... 853s $ betaT : num 0.7574 0.169 0.2357 0.2604 0.0576 ... 853s $ CN : num 2.36 2.13 2.26 2.01 2.32 ... 853s $ betaN : num 0.8274 0.5072 0.1671 0.1609 0.0421 ... 853s > # Segment known regions 853s > knownSegments <- data.frame( 853s + chromosome = c( 1, 1, 1), 853s + start = c( -Inf, NA, 141510003), 853s + end = c(120992603, NA, +Inf) 853s + ) 853s > fit <- segmentByPairedPSCBS(dataS, knownSegments=knownSegments, avgDH="median", seed=0xBEEF) 854s > print(fit) 854s chromosome tcnId dhId start end tcnNbrOfLoci tcnMean tcnNbrOfSNPs 854s 1 1 1 1 554484 120992603 7586 1.385258 2108 854s 2 NA 2 1 NA NA NA NA 0 854s 3 1 3 1 141510003 185449813 2681 2.068861 777 854s 4 1 4 1 185449813 247137334 4391 2.634110 1311 854s tcnNbrOfHets dhNbrOfLoci dhMean c1Mean c2Mean 854s 1 2108 2108 0.54551245 0.3147912 1.070467 854s 2 0 0 NA NA NA 854s 3 777 777 0.07132277 0.9606521 1.108209 854s 4 1311 1311 0.21663871 1.0317300 1.602380 854s > 854s > 854s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 854s > # Bootstrap 854s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 854s > B <- 1L 854s > seed <- 0xBEEF 854s > probs <- c(0.025, 0.05, 0.95, 0.975) 854s > 854s > sets <- getBootstrapLocusSets(fit, B=B, seed=seed) 854s > 854s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 854s > # Subset by first segment 854s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 854s > ss <- 1L 854s > 854s > fitT <- extractSegment(fit, ss) 854s > dataT <- getLocusData(fitT) 854s > segsT <- getSegments(fitT) 854s > 854s > # Truth 854s > bootT <- bootstrapSegmentsAndChangepoints(fitT, B=B, seed=seed) 854s > bootT1 <- bootT$segments[1L,,,drop=FALSE] 854s > types <- dimnames(bootT1)[[3L]] 854s > dim(bootT1) <- dim(bootT1)[-1L] 854s > colnames(bootT1) <- types 854s > sumsT <- apply(bootT1, MARGIN=2L, FUN=quantile, probs=probs) 854s > print(sumsT) 854s tcn dh c1 c2 854s 2.5% 1.383213 0.5466788 0.3135198 1.069693 854s 5% 1.383213 0.5466788 0.3135198 1.069693 854s 95% 1.383213 0.5466788 0.3135198 1.069693 854s 97.5% 1.383213 0.5466788 0.3135198 1.069693 854s > 854s > fitTB <- bootstrapTCNandDHByRegion(fitT, B=B, seed=seed) 854s > segsTB <- getSegments(fitTB) 854s > segsTB <- unlist(segsTB[,grep("_", colnames(segsTB))]) 854s > dim(segsTB) <- dim(sumsT) 854s > dimnames(segsTB) <- dimnames(sumsT) 854s > print(segsTB) 854s tcn dh c1 c2 854s 2.5% 1.383213 0.5466788 0.3135198 1.069693 854s 5% 1.383213 0.5466788 0.3135198 1.069693 854s 95% 1.383213 0.5466788 0.3135198 1.069693 854s 97.5% 1.383213 0.5466788 0.3135198 1.069693 854s > 854s > # Sanity check 854s > stopifnot(all.equal(segsTB, sumsT)) 854s > 854s > # Calculate summaries using the existing bootstrap samples 854s > fitTBp <- bootstrapTCNandDHByRegion(fitT, .boot=bootT) 855s > # Sanity check 855s > all.equal(fitTBp, fitTB) 855s [1] "Component “tcn_2.5%”: Mean relative difference: 0.003070405" 855s [2] "Component “tcn_5%”: Mean relative difference: 0.002241362" 855s [3] "Component “tcn_95%”: Mean relative difference: 0.005458479" 855s [4] "Component “tcn_97.5%”: Mean relative difference: 0.006030363" 855s [5] "Component “dh_2.5%”: Mean relative difference: 0.02683423" 855s [6] "Component “dh_5%”: Mean relative difference: 0.02409533" 855s [7] "Component “dh_95%”: Mean relative difference: 0.0150081" 855s [8] "Component “dh_97.5%”: Mean relative difference: 0.01826461" 855s [9] "Component “c1_2.5%”: Mean relative difference: 0.02397349" 855s [10] "Component “c1_5%”: Mean relative difference: 0.01800948" 855s [11] "Component “c1_95%”: Mean relative difference: 0.0303456" 855s [12] "Component “c1_97.5%”: Mean relative difference: 0.03420614" 855s [13] "Component “c2_2.5%”: Mean relative difference: 0.008723378" 855s [14] "Component “c2_5%”: Mean relative difference: 0.006834962" 855s [15] "Component “c2_95%”: Mean relative difference: 0.00741949" 855s [16] "Component “c2_97.5%”: Mean relative difference: 0.008743911" 855s attr(,"what") 855s [1] "getSegments()" 855s > 855s > 855s > # Bootstrap from scratch 855s > setsT <- getBootstrapLocusSets(fitT, B=B, seed=seed) 855s > lociT <- setsT$locusSet[[1L]]$bootstrap$loci 855s > idxs <- lociT$tcn 855s > tcnT <- array(dataT$CT[idxs], dim=dim(idxs)) 855s > tcnT <- apply(tcnT, MARGIN=2L, FUN=mean, na.rm=TRUE) 855s > idxs <- lociT$dh 855s > dhT <- array(dataT$rho[idxs], dim=dim(idxs)) 855s > dhT <- apply(dhT, MARGIN=2L, FUN=median, na.rm=TRUE) 855s > c1T <- (1-dhT) * tcnT / 2 855s > c2T <- tcnT - c1T 855s > bootT2 <- array(c(tcnT, dhT, c1T, c2T), dim=c(1L, 4L)) 855s > colnames(bootT2) <- colnames(bootT1) 855s > print(bootT2) 855s tcn dh c1 c2 855s [1,] 1.383213 0.5466788 0.3135198 1.069693 855s > 855s > # This comparison is only valid if B == 1L 855s > if (B == 1L) { 855s + # Sanity check 855s + stopifnot(all.equal(bootT2, bootT1)) 855s + } 855s > 855s Start: findLargeGaps.R 855s 855s R version 4.5.2 (2025-10-31) -- "[Not] Part in a Rumble" 855s Copyright (C) 2025 The R Foundation for Statistical Computing 855s Platform: aarch64-unknown-linux-gnu 855s 855s R is free software and comes with ABSOLUTELY NO WARRANTY. 855s You are welcome to redistribute it under certain conditions. 855s Type 'license()' or 'licence()' for distribution details. 855s 855s R is a collaborative project with many contributors. 855s Type 'contributors()' for more information and 855s 'citation()' on how to cite R or R packages in publications. 855s 855s Type 'demo()' for some demos, 'help()' for on-line help, or 855s 'help.start()' for an HTML browser interface to help. 855s Type 'q()' to quit R. 855s 855s > library("PSCBS") 855s PSCBS v0.68.0 (2025-04-18 19:40:02 UTC) successfully loaded. See ?PSCBS for help. 855s > 855s > # Simulating copy-number data 855s > set.seed(0xBEEF) 855s > 855s > # Simulate CN data 855s > J <- 1000 855s > mu <- double(J) 855s > mu[200:300] <- mu[200:300] + 1 855s > mu[350:400] <- NA # centromere 855s > mu[650:800] <- mu[650:800] - 1 855s > eps <- rnorm(J, sd=1/2) 855s > y <- mu + eps 855s > x <- seq(from=1, to=100e6, length.out=J) 855s > 855s > data <- data.frame(chromosome=0L, x=x) 855s > 855s > gaps <- findLargeGaps(x=x, minLength=1e6) 855s > print(gaps) 855s [1] start end length 855s <0 rows> (or 0-length row.names) 855s > stopifnot(is.data.frame(gaps)) 855s > stopifnot(nrow(gaps) == 0L) 855s > segs <- gapsToSegments(gaps) 855s > print(segs) 855s chromosome start end 855s 1 0 -Inf Inf 855s > stopifnot(is.data.frame(segs)) 855s > stopifnot(nrow(segs) == 1L) 855s > 855s > 855s > gaps <- findLargeGaps(data, minLength=1e6) 855s > print(gaps) 855s [1] chromosome start end 855s <0 rows> (or 0-length row.names) 855s > stopifnot(is.data.frame(gaps)) 855s > stopifnot(nrow(gaps) == 0L) 855s > segs <- gapsToSegments(gaps) 855s > print(segs) 855s chromosome start end 855s 1 0 -Inf Inf 855s > stopifnot(is.data.frame(segs)) 855s > stopifnot(nrow(segs) == 1L) 855s > 855s > 855s > ## Add missing values 855s > data2 <- data 855s > data$x[30e6 < x & x < 50e6] <- NA 855s > gaps <- findLargeGaps(data, minLength=1e6) 855s > print(gaps) 855s chromosome start end length 855s 1 0 29929932 50050050 20120118 855s > stopifnot(is.data.frame(gaps)) 855s > stopifnot(nrow(gaps) == 1L) 855s > segs <- gapsToSegments(gaps) 855s > print(segs) 855s chromosome start end length 855s 1 0 -Inf 29929931 Inf 855s 2 0 29929932 50050050 20120118 855s 3 0 50050051 Inf Inf 855s > stopifnot(is.data.frame(segs)) 855s > stopifnot(nrow(segs) == 3L) 855s > 855s > 855s > 855s > # BUG FIX: Issue #6 855s > gaps <- findLargeGaps(chromosome=rep(1,10), x=1:10, minLength=2) 855s > print(gaps) 855s [1] chromosome start end 855s <0 rows> (or 0-length row.names) 855s > stopifnot(is.data.frame(gaps)) 855s > stopifnot(nrow(gaps) == 0L) 855s > # BUG FIX: Issue #9 855s > segs <- gapsToSegments(gaps) 855s > print(segs) 855s chromosome start end 855s 1 0 -Inf Inf 855s > stopifnot(is.data.frame(segs)) 855s > stopifnot(nrow(segs) == 1L) 855s > 855s > 855s > # BUG FIX: PSCBS GitHub Issue #8 855s > gaps <- try({ 855s + findLargeGaps(chromosome=rep(1,3), x=as.numeric(1:3), minLength=1) 855s + }) 855s Error in findLargeGaps.default(chromosome = rep(1, 3), x = as.numeric(1:3), : 855s Cannot identify large gaps. Argument 'resolution' (=1) is not strictly smaller than 'minLength' (=1). 855s > stopifnot(inherits(gaps, "try-error")) 855s > 855s Start: randomSeed.R 855s 855s R version 4.5.2 (2025-10-31) -- "[Not] Part in a Rumble" 855s Copyright (C) 2025 The R Foundation for Statistical Computing 855s Platform: aarch64-unknown-linux-gnu 855s 855s R is free software and comes with ABSOLUTELY NO WARRANTY. 855s You are welcome to redistribute it under certain conditions. 855s Type 'license()' or 'licence()' for distribution details. 855s 855s R is a collaborative project with many contributors. 855s Type 'contributors()' for more information and 855s 'citation()' on how to cite R or R packages in publications. 855s 855s Type 'demo()' for some demos, 'help()' for on-line help, or 855s 'help.start()' for an HTML browser interface to help. 855s Type 'q()' to quit R. 855s 855s > library("PSCBS") 856s PSCBS v0.68.0 (2025-04-18 19:40:02 UTC) successfully loaded. See ?PSCBS for help. 856s > 856s > message("*** randomSeed() - setup ...") 856s *** randomSeed() - setup ... 856s > ovars <- ls(envir=globalenv()) 856s > genv <- globalenv() 856s > RNGkind("Mersenne-Twister") 856s > if (exists(".Random.seed", envir=genv, inherits=FALSE)) 856s + rm(list=".Random.seed", envir=genv, inherits=FALSE) 856s > seed0 <- genv$.Random.seed 856s > stopifnot(is.null(seed0)) 856s > okind0 <- RNGkind()[1L] 856s > 856s > sample1 <- function() { sample(0:9, size=1L) } 856s > message("*** randomSeed() - setup ... done") 856s *** randomSeed() - setup ... done 856s > 856s > 856s > message("*** randomSeed('get') ...") 856s *** randomSeed('get') ... 856s > ## Get random seed 856s > seed <- randomSeed("get") 856s > Random number: 1 856s *** randomSeed('get') ... done 856s *** randomSeed('set', 42L) ... 856s stopifnot(identical(seed, seed0)) 856s > 856s > ## Repeat after new sample 856s > y1 <- sample1() 856s > message(sprintf("Random number: %d", y1)) 856s > seed1 <- randomSeed("get") 856s > stopifnot(!identical(seed1, seed0)) 856s > message("*** randomSeed('get') ... done") 856s > 856s > 856s > message("*** randomSeed('set', 42L) ...") 856s > randomSeed("set", seed=42L) 856s > seed2 <- randomSeed("get") 856s > stopifnot(!identical(seed2, seed1)) 856s > 856s > y2 <- sample1() 856s Random number: 0 (with random seed = 42L) 856s > message(sprintf("Random number: %d (with random seed = 42L)", y2)) 856s > 856s > ## Reset to previous state 856s > randomSeed("reset") 856s > seed3 <- randomSeed("get") 856s > stopifnot(identical(seed3, seed1)) 856s > stopifnot(identical(RNGkind()[1L], okind0), 856s + identical(randomSeed("get"), seed1)) 856s > message("*** randomSeed('set', 42L) ... done") 856s *** randomSeed('set', 42L) ... done 856s > 856s > 856s > message("*** randomSeed('set', NULL) ...") 856s *** randomSeed('set', NULL) ... 856s > randomSeed("set", seed=NULL) 856s > seed4 <- randomSeed("get") 856s > stopifnot(is.null(seed4)) 856s > 856s > y3 <- sample1() 856s > message(sprintf("Random number: %d", y3)) 856s Random number: 5 856s > 856s > message("*** randomSeed('set', NULL) ... done") 856s *** randomSeed('set', NULL) ... done 856s > 856s > 856s > message("*** randomSeed('set', 42L) again ...") 856s *** randomSeed('set', 42L) again ... 856s Random number: 0 (with random seed = 42L) 856s *** randomSeed('set', 42L) again ... done 856s *** randomSeed(): L'Ecuyer-CMRG stream ... 856s > seed5 <- randomSeed("get") 856s > randomSeed("set", seed=42L) 856s > y4 <- sample1() 856s > message(sprintf("Random number: %d (with random seed = 42L)", y4)) 856s > stopifnot(identical(y4, y2)) 856s > 856s > randomSeed("reset") 856s > stopifnot(identical(RNGkind()[1L], okind0), 856s + identical(randomSeed("get"), seed5)) 856s > message("*** randomSeed('set', 42L) again ... done") 856s > 856s > 856s > 856s > ## L'Ecuyer-CMRG: Random number generation for parallel processing 856s > message("*** randomSeed(): L'Ecuyer-CMRG stream ...") 856s > 856s > okind <- RNGkind()[1L] 856s > stopifnot(identical(okind, okind0)) 856s > 856s > randomSeed("set", seed=NULL) 856s > oseed <- randomSeed("get") 856s > stopifnot(is.null(oseed)) 856s > 856s > randomSeed("set", seed=42L, kind="L'Ecuyer-CMRG") 856s > oseed2 <- randomSeed("reset") 856s > str(oseed2) 856s NULL 856s > stopifnot(identical(oseed2, oseed)) 856s > stopifnot(identical(RNGkind()[1L], okind), 856s + identical(randomSeed("get"), oseed)) 856s > 856s > randomSeed("set", seed=42L, kind="L'Ecuyer-CMRG") 856s > seed0 <- randomSeed("get") 856s > seeds0 <- lapply(1:10, FUN=function(i) randomSeed("advance")) 856s > oseed2 <- randomSeed("reset") 856s > stopifnot(identical(oseed2, oseed)) 856s > stopifnot(identical(RNGkind()[1L], okind), 856s + identical(randomSeed("get"), oseed)) 856s > 856s > 856s > ## Assert reproducible .Random.seed stream 856s > randomSeed("set", seed=42L, kind="L'Ecuyer-CMRG") 856s > seed1 <- randomSeed("get") 856s > seeds1 <- lapply(1:10, FUN=function(i) randomSeed("advance")) 856s > stopifnot(identical(seed1, seed0)) 856s > stopifnot(identical(seeds1, seeds0)) 856s > 856s > randomSeed("reset") 856s > stopifnot(identical(RNGkind()[1L], okind), 856s + identical(randomSeed("get"), oseed)) 856s > 856s > randomSeed("set", seed=42L, kind="L'Ecuyer-CMRG") 856s > seeds2 <- randomSeed("advance", n=10L) 856s > stopifnot(identical(seeds2, seeds0)) 856s > 856s > randomSeed("reset") 856s > stopifnot(identical(RNGkind()[1L], okind), 856s + identical(randomSeed("get"), oseed)) 856s > 856s > randomSeed("set", seed=seeds2[[1]], kind="L'Ecuyer-CMRG") 856s > randomSeed("reset") 856s > stopifnot(identical(RNGkind()[1L], okind), 856s + identical(randomSeed("get"), oseed)) 856s > 856s > randomSeed("set", seed=42L, kind="L'Ecuyer-CMRG") 856s > y0 <- sapply(1:10, FUN=function(ii) { 856s + randomSeed("advance") 856s + sample1() 856s + }) 856s > print(y0) 856s [1] 6 9 6 9 9 9 0 7 6 5 856s > randomSeed("reset") 856s > 856s > randomSeed("set", seed=42L, kind="L'Ecuyer-CMRG") 856s > y1 <- sapply(1:10, FUN=function(ii) { 856s + randomSeed("advance") 856s + sample1() 856s + }) 856s > print(y1) 856s [1] 6 9 6 9 9 9 0 7 6 5 856s > stopifnot(identical(y1, y0)) 856s > randomSeed("reset") 856s > 856s > stopifnot(identical(RNGkind()[1L], okind)) 856s > 856s > message("*** randomSeed(): L'Ecuyer-CMRG stream ... done") 856s *** randomSeed(): L'Ecuyer-CMRG stream ... done 856s > 856s > 856s > ## Cleanup 856s > message("*** randomSeed() - cleanup ...") 856s *** randomSeed() - cleanup ... 856s > genv <- globalenv() 856s > RNGkind("Mersenne-Twister") 856s > if (exists(".Random.seed", envir=genv, inherits=FALSE)) 856s + rm(list=".Random.seed", envir=genv, inherits=FALSE) 856s *** randomSeed() - cleanup ... done 856s > rm(list=ovars, envir=globalenv()) 856s > message("*** randomSeed() - cleanup ... done") 856s > 856s Start: segmentByCBS,bug67.R 856s 856s R version 4.5.2 (2025-10-31) -- "[Not] Part in a Rumble" 856s Copyright (C) 2025 The R Foundation for Statistical Computing 856s Platform: aarch64-unknown-linux-gnu 856s 856s R is free software and comes with ABSOLUTELY NO WARRANTY. 856s You are welcome to redistribute it under certain conditions. 856s Type 'license()' or 'licence()' for distribution details. 856s 856s R is a collaborative project with many contributors. 856s Type 'contributors()' for more information and 856s 'citation()' on how to cite R or R packages in publications. 856s 856s Type 'demo()' for some demos, 'help()' for on-line help, or 856s 'help.start()' for an HTML browser interface to help. 856s Type 'q()' to quit R. 856s 856s > set.seed(0xBEEF) 856s > 856s > # Number of loci 856s > J <- 1000 856s > 856s > mu <- double(J) 856s > mu[200:300] <- mu[200:300] + 1 856s > mu[350:400] <- NA_real_ # centromere 856s > mu[650:800] <- mu[650:800] - 1 856s > eps <- rnorm(J, sd=1/2) 856s > y <- mu + eps 856s > x <- sort(runif(length(y), max=length(y))) * 1e5 856s > 856s > knownSegments <- data.frame( 856s + chromosome=c( 0, 0), 856s + start =x[c( 1, 401)], 856s + end =x[c(349, J)] 856s + ) 856s > 856s > fit2 <- PSCBS::segmentByCBS(y, x=x, knownSegments=knownSegments) 856s > 856s Start: segmentByCBS,calls.R 856s 856s R version 4.5.2 (2025-10-31) -- "[Not] Part in a Rumble" 856s Copyright (C) 2025 The R Foundation for Statistical Computing 856s Platform: aarch64-unknown-linux-gnu 856s 856s R is free software and comes with ABSOLUTELY NO WARRANTY. 856s You are welcome to redistribute it under certain conditions. 856s Type 'license()' or 'licence()' for distribution details. 856s 856s R is a collaborative project with many contributors. 856s Type 'contributors()' for more information and 856s 'citation()' on how to cite R or R packages in publications. 856s 856s Type 'demo()' for some demos, 'help()' for on-line help, or 856s 'help.start()' for an HTML browser interface to help. 856s Type 'q()' to quit R. 856s 857s > # This test script calls a report generator which requires 857s > # the 'ggplot2' package, which in turn will require packages 857s > # 'colorspace', 'dichromat', 'munsell', 'reshape2' and 'scales'. 857s > 857s > # Only run this test in full testing mode 857s > if (Sys.getenv("_R_CHECK_FULL_") != "") { 857s + library("PSCBS") 857s + stext <- R.utils::stext 857s + 857s + # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 857s + # Load SNP microarray data 857s + # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 857s + data <- PSCBS::exampleData("paired.chr01") 857s + str(data) 857s + 857s + data <- data.frame(chromosome=data$chromosome, x=data$x, y=data$CT) 857s + 857s + 857s + # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 857s + # CBS segmentation 857s + # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 857s + # Drop single-locus outliers 857s + dataS <- dropSegmentationOutliers(data) 857s + 857s + # Speed up example by segmenting fewer loci 857s + dataS <- dataS[seq(from=1, to=nrow(data), by=5),] 857s + 857s + str(dataS) 857s + 857s + gaps <- findLargeGaps(dataS, minLength=2e6) 857s + knownSegments <- gapsToSegments(gaps) 857s + 857s + # CBS segmentation 857s + fit <- segmentByCBS(dataS, knownSegments=knownSegments, 857s + seed=0xBEEF, verbose=-10) 857s + signalType(fit) <- "ratio" 857s + plotTracks(fit) 857s + 857s + 857s + # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 857s + # Call using the UCSF MAD caller (not recommended) 857s + # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 857s + fitC <- callGainsAndLosses(fit) 857s + plotTracks(fitC) 857s + pars <- fitC$params$callGainsAndLosses 857s + stext(side=3, pos=1/2, line=-1, substitute(sigma==x, list(x=sprintf("%.2f", pars$sigmaMAD)))) 857s + mu <- pars$muR 857s + tau <- unlist(pars[c("tauLoss", "tauGain")], use.names=FALSE) 857s + abline(h=mu, lty=2, lwd=2) 857s + abline(h=tau, lwd=2) 857s + mtext(side=4, at=tau[1], expression(Delta[LOSS]), adj=-0.2, cex=0.7, las=2, xpd=TRUE) 857s + mtext(side=4, at=tau[2], expression(Delta[GAIN]), adj=-0.2, cex=0.7, las=2, xpd=TRUE) 857s + title(main="CN caller: \"ucsf-mad\"") 857s + 857s + 857s + # Caller to be implemented 857s + deltaCN <- estimateDeltaCN(fit) 857s + tau <- mu + 1/2*c(-1,+1)*deltaCN 857s + abline(h=tau, lty=2, lwd=1, col="red") 857s + 857s + 857s + 857s + } # if (Sys.getenv("_R_CHECK_FULL_")) 857s > 857s Start: segmentByCBS,futures.R 857s 857s R version 4.5.2 (2025-10-31) -- "[Not] Part in a Rumble" 857s Copyright (C) 2025 The R Foundation for Statistical Computing 857s Platform: aarch64-unknown-linux-gnu 857s 857s R is free software and comes with ABSOLUTELY NO WARRANTY. 857s You are welcome to redistribute it under certain conditions. 857s Type 'license()' or 'licence()' for distribution details. 857s 857s R is a collaborative project with many contributors. 857s Type 'contributors()' for more information and 857s 'citation()' on how to cite R or R packages in publications. 857s 857s Type 'demo()' for some demos, 'help()' for on-line help, or 857s 'help.start()' for an HTML browser interface to help. 857s Type 'q()' to quit R. 857s 857s > library("PSCBS") 857s PSCBS v0.68.0 (2025-04-18 19:40:02 UTC) successfully loaded. See ?PSCBS for help. 857s > 857s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 857s > # Simulating copy-number data 857s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 857s > set.seed(0xBEEF) 857s > 857s > # Number of loci 857s > J <- 1000 857s > 857s > mu <- double(J) 857s > mu[200:300] <- mu[200:300] + 1 857s > mu[350:400] <- NA # centromere 857s > mu[650:800] <- mu[650:800] - 1 857s > eps <- rnorm(J, sd=1/2) 857s > y <- mu + eps 857s > x <- sort(runif(length(y), max=length(y))) * 1e5 857s > w <- runif(J) 857s > w[650:800] <- 0.001 857s > 857s > ## Create multiple chromosomes 857s > data <- knownSegments <- list() 857s > for (cc in 1:3) { 857s + data[[cc]] <- data.frame(chromosome=cc, y=y, x=x) 857s + knownSegments[[cc]] <- data.frame( 857s + chromosome=c( cc, cc, cc), 857s + start =x[c( 1, 350, 401)], 857s + end =x[c(349, 400, J)] 857s + ) 857s + } 857s > data <- Reduce(rbind, data) 857s > str(data) 857s 'data.frame': 3000 obs. of 3 variables: 857s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 857s $ y : num 0.295 0.115 -0.194 -0.392 -0.518 ... 857s $ x : num 55168 593204 605649 630624 746896 ... 857s > knownSegments <- Reduce(rbind, knownSegments) 857s > str(knownSegments) 857s 'data.frame': 9 obs. of 3 variables: 857s $ chromosome: int 1 1 1 2 2 2 3 3 3 857s $ start : num 55168 34194740 41080533 55168 34194740 ... 857s $ end : num 34142178 41044125 99910827 34142178 41044125 ... 857s > 857s > message("*** segmentByCBS() via futures ...") 857s *** segmentByCBS() via futures ... 857s > 857s > 857s > message("*** segmentByCBS() via futures with 'future' attached ...") 857s *** segmentByCBS() via futures with 'future' attached ... 857s > library("future") 857s > oplan <- plan() 857s > 857s > strategies <- c("sequential", "multisession") 857s > 857s > ## Test 'future.batchtools' futures? 857s > pkg <- "future.batchtools" 857s > if (require(pkg, character.only=TRUE)) { 857s + strategies <- c(strategies, "batchtools_local") 857s + } 857s Loading required package: future.batchtools 857s Warning message: 857s In library(package, lib.loc = lib.loc, character.only = TRUE, logical.return = TRUE, : 857s there is no package called ‘future.batchtools’ 857s > 857s > message("Future strategies to test: ", paste(sQuote(strategies), collapse=", ")) 857s Future strategies to test: ‘sequential’, ‘multisession’ 857s > 857s > fits <- list() 857s > for (strategy in strategies) { 857s + message(sprintf("- segmentByCBS() using '%s' futures ...", strategy)) 857s + plan(strategy) 857s - segmentByCBS() using 'sequential' futures ... 857s + fit <- segmentByCBS(data, seed=0xBEEF, verbose=TRUE) 857s + fits[[strategy]] <- fit 857s + stopifnot(all.equal(fit, fits[[1]])) 857s + } 857s Segmenting by CBS... 857s Segmenting multiple chromosomes... 857s Number of chromosomes: 3 857s Random seed temporarily set (seed=c(48879), kind="L'Ecuyer-CMRG") 857s Produced 3 seeds from this stream for future usage 857s Chromosome #1 ('Chr01') of 3... 857s Segmenting by CBS... 857s Chromosome: 1 857s Random seed temporarily set (seed=c(10407, 1066287653, -51199871, 161854402, -1995183193, 1503453565, -747102133), kind="L'Ecuyer-CMRG") 857s Segmenting by CBS...done 857s Chromosome #1 ('Chr01') of 3...done 857s Chromosome #2 ('Chr02') of 3... 857s Segmenting by CBS... 857s Chromosome: 2 857s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 857s Segmenting by CBS...done 857s Chromosome #2 ('Chr02') of 3...done 857s Chromosome #3 ('Chr03') of 3... 857s Segmenting by CBS... 857s Chromosome: 3 857s Random seed temporarily set (seed=c(10407, -821273412, -52578226, 1415511586, 721384351, -665928286, 1316562960), kind="L'Ecuyer-CMRG") 857s Segmenting by CBS...done 857s Chromosome #3 ('Chr03') of 3...done 857s Segmenting multiple chromosomes...done 857s Segmenting by CBS...done 857s list() 857s - segmentByCBS() using 'multisession' futures ... 858s Segmenting by CBS... 858s Segmenting multiple chromosomes... 858s Number of chromosomes: 3 858s Random seed temporarily set (seed=c(48879), kind="L'Ecuyer-CMRG") 858s Produced 3 seeds from this stream for future usage 858s Chromosome #1 ('Chr01') of 3... 858s Chromosome #1 ('Chr01') of 3...done 858s Chromosome #2 ('Chr02') of 3... 859s Random seed temporarily set (seed=c(10407, 1066287653, -51199871, 161854402, -1995183193, 1503453565, -747102133), kind="L'Ecuyer-CMRG") 859s Segmenting by CBS...done 859s Chromosome #2 ('Chr02') of 3...done 859s Chromosome #3 ('Chr03') of 3... 859s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 859s Segmenting by CBS...done 859s Chromosome #3 ('Chr03') of 3...done 859s Segmenting by CBS... 859s Chromosome: 3 859s Random seed temporarily set (seed=c(10407, -821273412, -52578226, 1415511586, 721384351, -665928286, 1316562960), kind="L'Ecuyer-CMRG") 859s Segmenting by CBS...done 859s Segmenting multiple chromosomes...done 859s Segmenting by CBS...done 859s list() 859s > 859s > 859s > message("*** segmentByCBS() via futures with known segments ...") 859s > fits <- list() 859s > dataT <- subset(data, chromosome == 1) 859s *** segmentByCBS() via futures with known segments ... 859s > for (strategy in strategies) { 859s + message(sprintf("- segmentByCBS() w/ known segments using '%s' futures ...", strategy)) 859s + plan(strategy) 859s + fit <- segmentByCBS(dataT, knownSegments=knownSegments, seed=0xBEEF, verbose=TRUE) 859s + fits[[strategy]] <- fit 859s + stopifnot(all.equal(fit, fits[[1]])) 859s + } 859s - segmentByCBS() w/ known segments using 'sequential' futures ... 859s Segmenting by CBS... 859s Chromosome: 1 859s Random seed temporarily set (seed=c(48879), kind="L'Ecuyer-CMRG") 859s Produced 3 seeds from this stream for future usage 860s Segmenting by CBS...done 860s list() 860s - segmentByCBS() w/ known segments using 'multisession' futures ... 860s Segmenting by CBS... 860s Chromosome: 1 861s Random seed temporarily set (seed=c(48879), kind="L'Ecuyer-CMRG") 861s Produced 3 seeds from this stream for future usage 861s Segmenting by CBS...done 861s list() 861s > 861s > message("*** segmentByCBS() via futures ... DONE") 861s > *** segmentByCBS() via futures ... DONE 861s 861s > 861s > ## Cleanup 861s > plan(oplan) 861s > rm(list=c("fits", "dataT", "data", "fit")) 861s > 861s > 861s Start: segmentByCBS,median.R 861s 861s R version 4.5.2 (2025-10-31) -- "[Not] Part in a Rumble" 861s Copyright (C) 2025 The R Foundation for Statistical Computing 861s Platform: aarch64-unknown-linux-gnu 861s 861s R is free software and comes with ABSOLUTELY NO WARRANTY. 861s You are welcome to redistribute it under certain conditions. 861s Type 'license()' or 'licence()' for distribution details. 861s 861s R is a collaborative project with many contributors. 861s Type 'contributors()' for more information and 861s 'citation()' on how to cite R or R packages in publications. 861s 861s Type 'demo()' for some demos, 'help()' for on-line help, or 861s 'help.start()' for an HTML browser interface to help. 861s Type 'q()' to quit R. 861s 861s > library("PSCBS") 862s PSCBS v0.68.0 (2025-04-18 19:40:02 UTC) successfully loaded. See ?PSCBS for help. 862s > 862s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 862s > # Simulating copy-number data 862s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 862s > set.seed(0xBEEF) 862s > 862s > # Number of loci 862s > J <- 1000 862s > 862s > x <- sort(runif(J, max=J)) * 1e5 862s > 862s > mu <- double(J) 862s > mu[200:300] <- mu[200:300] + 1 862s > mu[350:400] <- NA # centromere 862s > mu[650:800] <- mu[650:800] - 1 862s > eps <- rnorm(J, sd=1/2) 862s > y <- mu + eps 862s > 862s > outliers <- seq(from=1L, to=J, length.out=0.2*J) 862s > y[outliers] <- y[outliers] + 1.5 862s > 862s > w <- rep(1.0, times=J) 862s > w[outliers] <- 0.01 862s > 862s > data <- data.frame(chromosome=1L, x=x, y=y) 862s > dataW <- cbind(data, w=w) 862s > 862s > 862s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 862s > # Single-chromosome segmentation 862s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 862s > par(mar=c(2,3,0.2,1)+0.1) 862s > # Segment without weights 862s > fit <- segmentByCBS(data) 862s > sampleName(fit) <- "CBS_Example" 862s > print(fit) 862s sampleName chromosome start end nbrOfLoci mean 862s 1 CBS_Example 1 136857.7 19138391 199 0.2712 862s 2 CBS_Example 1 19138391.4 28682180 101 1.2168 862s 3 CBS_Example 1 28682180.1 64690253 298 0.3027 862s 4 CBS_Example 1 64690253.3 80738828 151 -0.7101 862s 5 CBS_Example 1 80738828.3 99932904 200 0.3655 862s > plotTracks(fit) 862s > ## Highlight outliers (they pull up the mean levels) 862s > points(x[outliers]/1e6, y[outliers], col="purple") 862s Warning message: 862s In plotTracks.CBS(fit) : 862s Setting default 'Clim' assuming the signal type is ‘ratio’ because signalType(fit) is unknown (‘NA’). Use signalType(fit) <- ‘ratio’ to avoid this warning. 862s > 862s > # Segment without weights but with median 862s > fitM <- segmentByCBS(data, avg="median") 862s > sampleName(fitM) <- "CBS_Example (median)" 862s > print(fitM) 862s sampleName chromosome start end nbrOfLoci mean 862s 1 CBS_Example (median) 1 136857.7 19138391 199 0.1203255 862s 2 CBS_Example (median) 1 19138391.4 28682180 101 0.9949202 862s 3 CBS_Example (median) 1 28682180.1 64690253 298 0.1471793 862s 4 CBS_Example (median) 1 64690253.3 80738828 151 -0.8770443 862s 5 CBS_Example (median) 1 80738828.3 99932904 200 0.2211061 862s > drawLevels(fitM, col="magenta", lty=3) 862s NULL 862s > 862s > # Segment with weights 862s > fitW <- segmentByCBS(dataW, avg="median") 862s > sampleName(fitW) <- "CBS_Example (weighted)" 862s > print(fitW) 862s sampleName chromosome start end nbrOfLoci mean 862s 1 CBS_Example (weighted) 1 136857.7 19138391 199 -0.02220950 862s 2 CBS_Example (weighted) 1 19138391.4 28682180 101 0.92421628 862s 3 CBS_Example (weighted) 1 28682180.1 64690253 298 -0.02364830 862s 4 CBS_Example (weighted) 1 64690253.3 80738828 151 -1.04750872 862s 5 CBS_Example (weighted) 1 80738828.3 99932904 200 0.08961195 862s > drawLevels(fitW, col="red") 862s NULL 862s > 862s > # Segment with weights and median 862s > fitWM <- segmentByCBS(dataW, avg="median") 862s > sampleName(fitWM) <- "CBS_Example (weighted median)" 862s > print(fitWM) 862s sampleName chromosome start end nbrOfLoci 862s 1 CBS_Example (weighted median) 1 136857.7 19138391 199 862s 2 CBS_Example (weighted median) 1 19138391.4 28682180 101 862s 3 CBS_Example (weighted median) 1 28682180.1 64690253 298 862s 4 CBS_Example (weighted median) 1 64690253.3 80738828 151 862s 5 CBS_Example (weighted median) 1 80738828.3 99932904 200 862s mean 862s 1 -0.02220950 862s 2 0.92421628 862s 3 -0.02364830 862s 4 -1.04750872 862s 5 0.08961195 862s > drawLevels(fitWM, col="orange", lty=3) 862s NULL 862s > 862s > 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)) 862s > 862s > ## Assert that weighted segment means are less biased 862s > dmean <- getSegments(fit)$mean - getSegments(fitW)$mean 862s > cat("Segment mean differences:\n") 862s Segment mean differences: 862s > print(dmean) 862s [1] 0.2934095 0.2925837 0.3263483 0.3374087 0.2758881 862s > stopifnot(all(dmean > 0, na.rm=TRUE)) 862s > 862s > dmean <- getSegments(fitM)$mean - getSegments(fitWM)$mean 862s > cat("Segment median differences:\n") 862s Segment median differences: 862s > print(dmean) 862s [1] 0.14253502 0.07070392 0.17082758 0.17046439 0.13149418 862s > stopifnot(all(dmean > 0, na.rm=TRUE)) 862s > 862s > 862s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 862s > # Multi-chromosome segmentation 862s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 862s > data2 <- data 862s > data2$chromosome <- 2L 862s > data <- rbind(data, data2) 862s > dataW <- cbind(data, w=w) 862s > 862s > par(mar=c(2,3,0.2,1)+0.1) 862s > # Segment without weights 862s > fit <- segmentByCBS(data) 862s > sampleName(fit) <- "CBS_Example" 862s > print(fit) 862s sampleName chromosome start end nbrOfLoci mean 862s 1 CBS_Example 1 136857.7 19138391 199 0.2712 862s 2 CBS_Example 1 19138391.4 28682180 101 1.2168 862s 3 CBS_Example 1 28682180.1 64690253 298 0.3027 862s 4 CBS_Example 1 64690253.3 80738828 151 -0.7101 862s 5 CBS_Example 1 80738828.3 99932904 200 0.3655 862s 6 NA NA NA NA NA 862s 7 CBS_Example 2 136857.7 19138391 199 0.2712 862s 8 CBS_Example 2 19138391.4 28682180 101 1.2168 862s 9 CBS_Example 2 28682180.1 64690253 298 0.3027 862s 10 CBS_Example 2 64690253.3 80738828 151 -0.7101 862s 11 CBS_Example 2 80738828.3 99932904 200 0.3655 862s > plotTracks(fit, Clim=c(-3,3)) 862s > 862s > # Segment without weights but with median 862s > fitM <- segmentByCBS(data, avg="median") 862s > sampleName(fitM) <- "CBS_Example (median)" 862s > print(fitM) 862s sampleName chromosome start end nbrOfLoci mean 862s 1 CBS_Example (median) 1 136857.7 19138391 199 0.1203255 862s 2 CBS_Example (median) 1 19138391.4 28682180 101 0.9949202 862s 3 CBS_Example (median) 1 28682180.1 64690253 298 0.1471793 862s 4 CBS_Example (median) 1 64690253.3 80738828 151 -0.8770443 862s 5 CBS_Example (median) 1 80738828.3 99932904 200 0.2211061 862s 6 NA NA NA NA NA 862s 7 CBS_Example (median) 2 136857.7 19138391 199 0.1203255 862s 8 CBS_Example (median) 2 19138391.4 28682180 101 0.9949202 862s 9 CBS_Example (median) 2 28682180.1 64690253 298 0.1471793 862s 10 CBS_Example (median) 2 64690253.3 80738828 151 -0.8770443 862s 11 CBS_Example (median) 2 80738828.3 99932904 200 0.2211061 862s > drawLevels(fitM, col="magenta", lty=3) 862s NULL 862s > 862s > # Segment with weights 862s > fitW <- segmentByCBS(dataW, avg="median") 863s > sampleName(fitW) <- "CBS_Example (weighted)" 863s > print(fitW) 863s sampleName chromosome start end nbrOfLoci mean 863s 1 CBS_Example (weighted) 1 136857.7 19138391 199 -0.02220950 863s 2 CBS_Example (weighted) 1 19138391.4 28682180 101 0.92421628 863s 3 CBS_Example (weighted) 1 28682180.1 64690253 298 -0.02364830 863s 4 CBS_Example (weighted) 1 64690253.3 80738828 151 -1.04750872 863s 5 CBS_Example (weighted) 1 80738828.3 99932904 200 0.08961195 863s 6 NA NA NA NA NA 863s 7 CBS_Example (weighted) 2 136857.7 19138391 199 -0.02220950 863s 8 CBS_Example (weighted) 2 19138391.4 28682180 101 0.92421628 863s 9 CBS_Example (weighted) 2 28682180.1 64690253 298 -0.02364830 863s 10 CBS_Example (weighted) 2 64690253.3 80738828 151 -1.04750872 863s 11 CBS_Example (weighted) 2 80738828.3 99932904 200 0.08961195 863s > drawLevels(fitW, col="red") 863s NULL 863s > 863s > # Segment with weights and median 863s > fitWM <- segmentByCBS(dataW, avg="median") 863s > sampleName(fitWM) <- "CBS_Example (weighted median)" 863s > print(fitWM) 863s sampleName chromosome start end nbrOfLoci 863s 1 CBS_Example (weighted median) 1 136857.7 19138391 199 863s 2 CBS_Example (weighted median) 1 19138391.4 28682180 101 863s 3 CBS_Example (weighted median) 1 28682180.1 64690253 298 863s 4 CBS_Example (weighted median) 1 64690253.3 80738828 151 863s 5 CBS_Example (weighted median) 1 80738828.3 99932904 200 863s 6 NA NA NA NA 863s 7 CBS_Example (weighted median) 2 136857.7 19138391 199 863s 8 CBS_Example (weighted median) 2 19138391.4 28682180 101 863s 9 CBS_Example (weighted median) 2 28682180.1 64690253 298 863s 10 CBS_Example (weighted median) 2 64690253.3 80738828 151 863s 11 CBS_Example (weighted median) 2 80738828.3 99932904 200 863s mean 863s 1 -0.02220950 863s 2 0.92421628 863s 3 -0.02364830 863s 4 -1.04750872 863s 5 0.08961195 863s 6 NA 863s 7 -0.02220950 863s 8 0.92421628 863s 9 -0.02364830 863s 10 -1.04750872 863s 11 0.08961195 863s > drawLevels(fitWM, col="orange", lty=3) 863s NULL 863s > 863s > 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)) 863s > 863s > ## Assert that weighted segment means are less biased 863s > dmean <- getSegments(fit)$mean - getSegments(fitW)$mean 863s > cat("Segment mean differences:\n") 863s Segment mean differences: 863s > print(dmean) 863s [1] 0.2934095 0.2925837 0.3263483 0.3374087 0.2758881 NA 0.2934095 863s [8] 0.2925837 0.3263483 0.3374087 0.2758881 863s > stopifnot(all(dmean > 0, na.rm=TRUE)) 863s > 863s > dmean <- getSegments(fitM)$mean - getSegments(fitWM)$mean 863s > cat("Segment median differences:\n") 863s Segment median differences: 863s > print(dmean) 863s [1] 0.14253502 0.07070392 0.17082758 0.17046439 0.13149418 NA 863s [7] 0.14253502 0.07070392 0.17082758 0.17046439 0.13149418 863s > stopifnot(all(dmean > 0, na.rm=TRUE)) 863s > 863s Start: segmentByCBS,prune.R 863s 863s R version 4.5.2 (2025-10-31) -- "[Not] Part in a Rumble" 863s Copyright (C) 2025 The R Foundation for Statistical Computing 863s Platform: aarch64-unknown-linux-gnu 863s 863s R is free software and comes with ABSOLUTELY NO WARRANTY. 863s You are welcome to redistribute it under certain conditions. 863s Type 'license()' or 'licence()' for distribution details. 863s 863s R is a collaborative project with many contributors. 863s Type 'contributors()' for more information and 863s 'citation()' on how to cite R or R packages in publications. 863s 863s Type 'demo()' for some demos, 'help()' for on-line help, or 863s 'help.start()' for an HTML browser interface to help. 863s Type 'q()' to quit R. 863s 863s > library("PSCBS") 863s PSCBS v0.68.0 (2025-04-18 19:40:02 UTC) successfully loaded. See ?PSCBS for help. 863s > 863s > ## Compare segments 863s > assertMatchingSegments <- function(fitM, fit) { 863s + chrs <- getChromosomes(fitM) 863s + segsM <- lapply(chrs, FUN=function(chr) { 863s + getSegments(extractChromosome(fitM, chr)) 863s + }) 863s + segs <- lapply(fit[chrs], FUN=getSegments) 863s + stopifnot(all.equal(segsM, segs, check.attributes=FALSE)) 863s + } 863s > 863s > ## Simulate data 863s > set.seed(0xBEEF) 863s > J <- 1000 863s > mu <- double(J) 863s > mu[200:300] <- mu[200:300] + 1 863s > mu[350:400] <- NA 863s > mu[650:800] <- mu[650:800] - 1 863s > eps <- rnorm(J, sd=1/2) 863s > y <- mu + eps 863s > x <- sort(runif(length(y), max=length(y))) * 1e5 863s > 863s > data <- list() 863s > for (chr in 1:2) { 863s + data[[chr]] <- data.frame(chromosome=chr, x=x, y=y) 863s + } 863s > data$M <- Reduce(rbind, data) 863s *** segmentByCBS() 863s > 863s > ## Segment 863s > message("*** segmentByCBS()") 863s > fit <- lapply(data, FUN=segmentByCBS) 864s > print(fit) 864s [[1]] 864s sampleName chromosome start end nbrOfLoci mean 864s 1 1 55167.82 20774251 201 0.0164 864s 2 1 20774250.85 29320105 99 1.0474 864s 3 1 29320104.86 65874675 298 -0.0203 864s 4 1 65874675.06 81348129 151 -1.0813 864s 5 1 81348129.20 99910827 200 -0.0612 864s 864s [[2]] 864s sampleName chromosome start end nbrOfLoci mean 864s 1 2 55167.82 20774251 201 0.0164 864s 2 2 20774250.85 29320105 99 1.0474 864s 3 2 29320104.86 65874675 298 -0.0203 864s 4 2 65874675.06 81348129 151 -1.0813 864s 5 2 81348129.20 99910827 200 -0.0612 864s 864s $M 864s sampleName chromosome start end nbrOfLoci mean 864s 1 1 55167.82 20774251 201 0.0164 864s 2 1 20774250.85 29320105 99 1.0474 864s 3 1 29320104.86 65874675 298 -0.0203 864s 4 1 65874675.06 81348129 151 -1.0813 864s 5 1 81348129.20 99910827 200 -0.0612 864s 6 NA NA NA NA NA 864s 7 2 55167.82 20774251 201 0.0164 864s 8 2 20774250.85 29320105 99 1.0474 864s 9 2 29320104.86 65874675 298 -0.0203 864s 10 2 65874675.06 81348129 151 -1.0813 864s 11 2 81348129.20 99910827 200 -0.0612 864s 864s > assertMatchingSegments(fit$M, fit) 864s *** joinSegments() 864s > 864s > ## Join segments 864s > message("*** joinSegments()") 864s > fitj <- lapply(fit, FUN=joinSegments) 864s > print(fitj) 864s [[1]] 864s sampleName chromosome start end nbrOfLoci mean 864s 1 1 55167.82 20774251 201 0.0164 864s 2 1 20774250.85 29320105 99 1.0474 864s 3 1 29320104.86 65874675 298 -0.0203 864s 4 1 65874675.06 81348129 151 -1.0813 864s 5 1 81348129.20 99910827 200 -0.0612 864s 864s [[2]] 864s sampleName chromosome start end nbrOfLoci mean 864s 1 2 55167.82 20774251 201 0.0164 864s 2 2 20774250.85 29320105 99 1.0474 864s 3 2 29320104.86 65874675 298 -0.0203 864s 4 2 65874675.06 81348129 151 -1.0813 864s 5 2 81348129.20 99910827 200 -0.0612 864s 864s $M 864s sampleName chromosome start end nbrOfLoci mean 864s 1 1 55167.82 20774251 201 0.0164 864s 2 1 20774250.85 29320105 99 1.0474 864s 3 1 29320104.86 65874675 298 -0.0203 864s 4 1 65874675.06 81348129 151 -1.0813 864s 5 1 81348129.20 99910827 200 -0.0612 864s 6 NA NA NA NA NA 864s 7 2 55167.82 20774251 201 0.0164 864s 8 2 20774250.85 29320105 99 1.0474 864s 9 2 29320104.86 65874675 298 -0.0203 864s 10 2 65874675.06 81348129 151 -1.0813 864s 11 2 81348129.20 99910827 200 -0.0612 864s 864s > assertMatchingSegments(fitj$M, fitj) 864s > 864s > ## Reset segments 864s > message("*** resetSegments()") 864s *** resetSegments() 864s > fitj <- lapply(fit, FUN=resetSegments) 864s > print(fitj) 864s [[1]] 864s sampleName chromosome start end nbrOfLoci mean 864s 1 1 55167.82 20774251 201 0.0164 864s 2 1 20774250.85 29320105 99 1.0474 864s 3 1 29320104.86 65874675 298 -0.0203 864s 4 1 65874675.06 81348129 151 -1.0813 864s 5 1 81348129.20 99910827 200 -0.0612 864s 864s [[2]] 864s sampleName chromosome start end nbrOfLoci mean 864s 1 2 55167.82 20774251 201 0.0164 864s 2 2 20774250.85 29320105 99 1.0474 864s 3 2 29320104.86 65874675 298 -0.0203 864s 4 2 65874675.06 81348129 151 -1.0813 864s 5 2 81348129.20 99910827 200 -0.0612 864s 864s $M 864s sampleName chromosome start end nbrOfLoci mean 864s 1 1 55167.82 20774251 201 0.0164 864s 2 1 20774250.85 29320105 99 1.0474 864s 3 1 29320104.86 65874675 298 -0.0203 864s 4 1 65874675.06 81348129 151 -1.0813 864s 5 1 81348129.20 99910827 200 -0.0612 864s 6 NA NA NA NA NA 864s 7 2 55167.82 20774251 201 0.0164 864s 8 2 20774250.85 29320105 99 1.0474 864s 9 2 29320104.86 65874675 298 -0.0203 864s 10 2 65874675.06 81348129 151 -1.0813 864s 11 2 81348129.20 99910827 200 -0.0612 864s 864s > assertMatchingSegments(fitj$M, fitj) 864s *** pruneBySdUndo() 864s > 864s > ## Prune by SD undo 864s > message("*** pruneBySdUndo()") 864s > fitp <- lapply(fit, FUN=pruneBySdUndo) 864s > print(fitp) 864s [[1]] 864s sampleName chromosome start end nbrOfLoci mean 864s 1 1 55167.82 99910827 949 -0.07857059 864s 864s [[2]] 864s sampleName chromosome start end nbrOfLoci mean 864s 1 2 55167.82 99910827 949 -0.07857059 864s 864s $M 864s sampleName chromosome start end nbrOfLoci mean 864s 1 1 55167.82 99910827 949 -0.07857059 864s 2 NA NA NA NA NA 864s 3 2 55167.82 99910827 949 -0.07857059 864s 864s > assertMatchingSegments(fitp$M, fitp) 864s > 864s > ## Prune by hierarchical clustering 864s > message("*** pruneByHClust()") 864s *** pruneByHClust() 864s > fitp <- lapply(fit, FUN=pruneByHClust, k=1L) 864s > print(fitp) 864s [[1]] 864s sampleName chromosome start end nbrOfLoci mean 864s 1 1 55167.82 99910827 949 -0.07857059 864s 864s [[2]] 864s sampleName chromosome start end nbrOfLoci mean 864s 1 2 55167.82 99910827 949 -0.07857059 864s 864s $M 864s sampleName chromosome start end nbrOfLoci mean 864s 1 1 55167.82 99910827 949 -0.07857059 864s 6 NA NA NA NA NA 864s 7 2 55167.82 99910827 949 -0.07857059 864s 864s > assertMatchingSegments(fitp$M, fitp) 864s > 864s Start: segmentByCBS,report.R 864s 864s R version 4.5.2 (2025-10-31) -- "[Not] Part in a Rumble" 864s Copyright (C) 2025 The R Foundation for Statistical Computing 864s Platform: aarch64-unknown-linux-gnu 864s 864s R is free software and comes with ABSOLUTELY NO WARRANTY. 864s You are welcome to redistribute it under certain conditions. 864s Type 'license()' or 'licence()' for distribution details. 864s 864s R is a collaborative project with many contributors. 864s Type 'contributors()' for more information and 864s 'citation()' on how to cite R or R packages in publications. 864s 864s Type 'demo()' for some demos, 'help()' for on-line help, or 864s 'help.start()' for an HTML browser interface to help. 864s Type 'q()' to quit R. 864s 864s > # This test script calls a report generator which requires 864s > # the 'ggplot2' package, which in turn will require packages 864s > # 'colorspace', 'dichromat', 'munsell', 'reshape2' and 'scales'. 864s > 864s > # Only run this test in full testing mode 864s > if (Sys.getenv("_R_CHECK_FULL_") != "") { 864s + library("PSCBS") 864s + 864s + # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 864s + # Load SNP microarray data 864s + # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 864s + data <- PSCBS::exampleData("paired.chr01") 864s + str(data) 864s + 864s + data <- data.frame(chromosome=data$chromosome, x=data$x, y=data$CT) 864s + 864s + 864s + # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 864s + # CBS segmentation 864s + # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 864s + # Drop single-locus outliers 864s + dataS <- dropSegmentationOutliers(data) 864s + 864s + # Speed up example by segmenting fewer loci 864s + dataS <- dataS[seq(from=1, to=nrow(data), by=5),] 864s + 864s + str(dataS) 864s + 864s + gaps <- findLargeGaps(dataS, minLength=2e6) 864s + knownSegments <- gapsToSegments(gaps) 864s + 864s + # CBS segmentation 864s + fit <- segmentByCBS(dataS, knownSegments=knownSegments, 864s + seed=0xBEEF, verbose=-10) 864s + signalType(fit) <- "ratio" 864s + 864s + # Fake a multi-chromosome segmentation 864s + fit1 <- fit 864s + fit2 <- renameChromosomes(fit, from=1, to=2) 864s + fit <- c(fit1, fit2) 864s + 864s + report(fit, sampleName="CBS", studyName="CBS-Ex", verbose=-10) 864s + 864s + } # if (Sys.getenv("_R_CHECK_FULL_")) 864s > 864s Start: segmentByCBS,shiftTCN.R 864s 864s R version 4.5.2 (2025-10-31) -- "[Not] Part in a Rumble" 864s Copyright (C) 2025 The R Foundation for Statistical Computing 864s Platform: aarch64-unknown-linux-gnu 864s 864s R is free software and comes with ABSOLUTELY NO WARRANTY. 864s You are welcome to redistribute it under certain conditions. 864s Type 'license()' or 'licence()' for distribution details. 864s 864s R is a collaborative project with many contributors. 864s Type 'contributors()' for more information and 864s 'citation()' on how to cite R or R packages in publications. 864s 864s Type 'demo()' for some demos, 'help()' for on-line help, or 864s 'help.start()' for an HTML browser interface to help. 864s Type 'q()' to quit R. 864s 864s > library("PSCBS") 865s PSCBS v0.68.0 (2025-04-18 19:40:02 UTC) successfully loaded. See ?PSCBS for help. 865s > subplots <- R.utils::subplots 865s > 865s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 865s > # Simulating copy-number data 865s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 865s > set.seed(0xBEEF) 865s > 865s > # Number of loci 865s > J <- 1000 865s > 865s > mu <- double(J) 865s > eps <- rnorm(J, sd=1/2) 865s > y <- mu + eps 865s > x <- sort(runif(length(y), max=length(y))) 865s > 865s > idxs <- which(200 <= x & x < 300) 865s > y[idxs] <- y[idxs] + 1 865s > idxs <- which(350 <= x & x < 400) 865s > y[idxs] <- NA # centromere 865s > x[idxs] <- NA # centromere 865s > idxs <- which(650 <= x & x < 800) 865s > y[idxs] <- y[idxs] - 1 865s > x <- x*1e5 865s > 865s > keep <- is.finite(x) 865s > x <- x[keep] 865s > y <- y[keep] 865s > 865s > data <- list() 865s > for (chr in 1:2) { 865s + data[[chr]] <- data.frame(chromosome=chr, y=y, x=x) 865s + } 865s > data <- Reduce(rbind, data) 865s > 865s > 865s > subplots(7, ncol=1) 865s > par(mar=c(1.7,1,0.2,1)+0.1) 865s > 865s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 865s > # Segmentation 865s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 865s > fit <- segmentByCBS(data) 865s > print(fit) 865s sampleName chromosome start end nbrOfLoci mean 865s 1 1 55167.82 20341782 195 0.0145 865s 2 1 20341781.95 29617861 108 1.0437 865s 3 1 29617861.37 64995303 299 -0.0208 865s 4 1 64995302.97 80042680 151 -1.0700 865s 5 1 80042679.86 99910827 211 -0.0568 865s 6 NA NA NA NA NA 865s 7 2 55167.82 20341782 195 0.0145 865s 8 2 20341781.95 29617861 108 1.0437 865s 9 2 29617861.37 64995303 299 -0.0208 865s 10 2 64995302.97 80042680 151 -1.0700 865s 11 2 80042679.86 99910827 211 -0.0568 865s > 865s > Clim <- c(-3,3) + c(0,10) 865s > plotTracks(fit, Clim=Clim) 865s > 865s > 865s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 865s > # Shifting every other chromosome 865s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 865s > fitList <- list() 865s > chrs <- getChromosomes(fit) 865s > for (kk in seq_along(chrs)) { 865s + chr <- chrs[kk] 865s + fitKK <- extractChromosome(fit, chr) 865s + if (kk %% 2 == 0) { 865s + fitKK <- shiftTCN(fitKK, shift=+10) 865s + } 865s + fitList[[kk]] <- fitKK 865s + } # for (kk ...) 865s > fitT <- do.call(c, fitList) 865s > # Sanity check 865s > stopifnot(nbrOfSegments(fitT) == nbrOfSegments(fit)) 865s > 865s > plotTracks(fitT, Clim=Clim) 865s > 865s > 865s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 865s > # Shifting every other known segment 865s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 865s > gaps <- findLargeGaps(data, minLength=40e5) 865s > knownSegments <- gapsToSegments(gaps, dropGaps=TRUE) 865s > fit <- segmentByCBS(data, knownSegments=knownSegments) 866s > 866s > subplots(2, ncol=1) 866s > plotTracks(fit, Clim=Clim) 866s > abline(v=c(knownSegments$start, knownSegments$end)/1e6, lty=3) 866s > 866s > fitList <- list() 866s > for (kk in seq_len(nrow(knownSegments))) { 866s + seg <- knownSegments[kk,] 866s + start <- seg$start 866s + end <- seg$end 866s + fitKK <- extractChromosome(fit, seg$chromosome) 866s + segsKK <- getSegments(fitKK) 866s + idxStart <- min(which(segsKK$start >= start)) 866s + idxEnd <- max(which(segsKK$end <= end)) 866s + idxs <- idxStart:idxEnd 866s + fitKK <- extractSegments(fitKK, idxs) 866s + if (kk %% 2 == 0) { 866s + fitKK <- shiftTCN(fitKK, shift=+10) 866s + } 866s + fitList[[kk]] <- fitKK 866s + } # for (kk ...) 866s > fitT <- do.call(c, fitList) 866s > # Sanity check 866s > stopifnot(nbrOfSegments(fitT) == nbrOfSegments(fit)) 866s > 866s > plotTracks(fitT, Clim=Clim) 866s > abline(v=c(knownSegments$start, knownSegments$end)/1e6, lty=3) 866s > 866s > 866s > segList <- seqOfSegmentsByDP(fit) 866s > K <- length(segList) 866s > subplots(K, ncol=2, byrow=FALSE) 866s > par(mar=c(2,1,1,1)) 866s > for (kk in 1:K) { 866s + knownSegments <- segList[[kk]] 866s + fitKK <- resegment(fit, knownSegments=knownSegments, undo=+Inf) 866s + plotTracks(fitKK, Clim=c(-3,3)) 866s + } # for (kk ...) 873s > 873s Start: segmentByCBS,weights.R 873s 873s R version 4.5.2 (2025-10-31) -- "[Not] Part in a Rumble" 873s Copyright (C) 2025 The R Foundation for Statistical Computing 873s Platform: aarch64-unknown-linux-gnu 873s 873s R is free software and comes with ABSOLUTELY NO WARRANTY. 873s You are welcome to redistribute it under certain conditions. 873s Type 'license()' or 'licence()' for distribution details. 873s 873s R is a collaborative project with many contributors. 873s Type 'contributors()' for more information and 873s 'citation()' on how to cite R or R packages in publications. 873s 873s Type 'demo()' for some demos, 'help()' for on-line help, or 873s 'help.start()' for an HTML browser interface to help. 873s Type 'q()' to quit R. 873s 875s > library("PSCBS") 875s > 875s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 875s > # Simulating copy-number data 875s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 875s > set.seed(0xBEEF) 875s > 875s > # Number of loci 875s > J <- 1000 875s > 875s > x <- sort(runif(J, max=J)) * 1e5 875s > 875s > mu <- double(J) 875s > mu[200:300] <- mu[200:300] + 1 875s > mu[350:400] <- NA # centromere 875s > mu[650:800] <- mu[650:800] - 1 875s > eps <- rnorm(J, sd=1/2) 875s > y <- mu + eps 875s > 875s > outliers <- seq(from=1L, to=J, length.out=0.2*J) 875s > y[outliers] <- y[outliers] + 1.5 875s > 875s > w <- rep(1.0, times=J) 875s > w[outliers] <- 0.01 875s > 875s > data <- data.frame(chromosome=1L, x=x, y=y) 875s > dataW <- cbind(data, w=w) 875s > 875s > 875s > par(mar=c(2,3,0.2,1)+0.1) 875s > 875s > 875s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 875s > # Single-chromosome segmentation 875s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 875s > # Segment without weights 875s > fit <- segmentByCBS(data) 875s > sampleName(fit) <- "CBS_Example" 875s > print(fit) 875s sampleName chromosome start end nbrOfLoci mean 875s 1 CBS_Example 1 136857.7 19138391 199 0.2712 875s 2 CBS_Example 1 19138391.4 28682180 101 1.2168 875s 3 CBS_Example 1 28682180.1 64690253 298 0.3027 875s 4 CBS_Example 1 64690253.3 80738828 151 -0.7101 875s 5 CBS_Example 1 80738828.3 99932904 200 0.3655 875s > plotTracks(fit) 875s > ## Highlight outliers (they pull up the mean levels) 875s > points(x[outliers]/1e6, y[outliers], col="purple") 875s > 875s > # Segment with weights 875s > fitW <- segmentByCBS(dataW) 875s > sampleName(fitW) <- "CBS_Example (weighted)" 875s > print(fitW) 875s sampleName chromosome start end nbrOfLoci mean 875s 1 CBS_Example (weighted) 1 136857.7 19138391 199 -0.0041 875s 2 CBS_Example (weighted) 1 19138391.4 28682180 101 0.8987 875s 3 CBS_Example (weighted) 1 28682180.1 64690253 298 0.0159 875s 4 CBS_Example (weighted) 1 64690253.3 80738828 151 -1.0215 875s 5 CBS_Example (weighted) 1 80738828.3 99932904 200 0.0653 875s > drawLevels(fitW, col="red") 875s NULL 875s > 875s > 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)) 875s > 875s > ## Assert that weighted segment means are less biased 875s > dmean <- getSegments(fit)$mean - getSegments(fitW)$mean 875s > cat("Segment mean differences:\n") 875s Segment mean differences: 875s > print(dmean) 875s [1] 0.2753 0.3181 0.2868 0.3114 0.3002 875s > stopifnot(all(dmean > 0, na.rm=TRUE)) 875s > 875s > 875s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 875s > # Segmentation with some known change points 875s > PSCBS v0.68.0 (2025-04-18 19:40:02 UTC) successfully loaded. See ?PSCBS for help. 875s Warning message: 875s In plotTracks.CBS(fit) : 875s Setting default 'Clim' assuming the signal type is ‘ratio’ because signalType(fit) is unknown (‘NA’). Use signalType(fit) <- ‘ratio’ to avoid this warning. 875s # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 875s > knownSegments <- data.frame( 875s + chromosome=c( 1, 1), 875s + start =x[c( 1, 401)], 875s + end =x[c(349, J)] 875s + ) 875s > fit2 <- segmentByCBS(dataW, knownSegments=knownSegments, verbose=TRUE) 875s > sampleName(fit2) <- "CBS_Example_2 (weighted)" 875s > print(fit2) 875s sampleName chromosome start end nbrOfLoci mean 875s 1 CBS_Example_2 (weighted) 1 136857.7 19138391 199 -0.0041 875s 2 CBS_Example_2 (weighted) 1 19138391.4 28682180 101 0.8987 875s 3 CBS_Example_2 (weighted) 1 28682180.1 34062461 49 -0.0552 875s 4 CBS_Example_2 (weighted) 1 38343432.8 64690253 249 0.0298 875s 5 CBS_Example_2 (weighted) 1 64690253.3 80738828 151 -1.0215 875s 6 CBS_Example_2 (weighted) 1 80738828.3 99932904 200 0.0653 875s > plotTracks(fit2) 875s > abline(v=c(knownSegments$start, knownSegments$end)/1e6, lty=3) 875s > 875s > 875s > # Chromosome boundaries can be specified as -Inf and +Inf 875s > knownSegments <- data.frame( 875s + chromosome=c( 1, 1), 875s + start =c( -Inf, x[401]), 875s + end =c(x[349], +Inf) 875s + ) 875s > fit2b <- segmentByCBS(dataW, knownSegments=knownSegments, verbose=TRUE) 875s > sampleName(fit2b) <- "CBS_Example_2b (weighted)" 875s > print(fit2b) 875s sampleName chromosome start end nbrOfLoci mean 875s 1 CBS_Example_2b (weighted) 1 136857.7 19138391 199 -0.0041 875s 2 CBS_Example_2b (weighted) 1 19138391.4 28682180 101 0.8987 875s 3 CBS_Example_2b (weighted) 1 28682180.1 34062461 49 -0.0552 875s 4 CBS_Example_2b (weighted) 1 38343432.8 64690253 249 0.0298 875s 5 CBS_Example_2b (weighted) 1 64690253.3 80738828 151 -1.0215 875s 6 CBS_Example_2b (weighted) 1 80738828.3 99932904 200 0.0653 875s > plotTracks(fit2b) 875s > abline(v=c(knownSegments$start, knownSegments$end)/1e6, lty=3) 875s > 875s > 875s > # As a proof of concept, it is possible to segment just the centromere, 875s > # which contains no data. All statistics will be NAs. 875s > knownSegments <- data.frame( 875s + chromosome=c( 1), 875s + start =x[c(350)], 875s + end =x[c(400)] 875s + ) 875s > fit3 <- segmentByCBS(dataW, knownSegments=knownSegments, verbose=TRUE) 875s > sampleName(fit3) <- "CBS_Example_3" 875s > print(fit3) 875s sampleName chromosome start end nbrOfLoci mean 875s 1 CBS_Example_3 1 34108010 38257409 0 NA 875s > plotTracks(fit3, Clim=c(0,5), xlim=c(0,100)) 875s > abline(v=c(knownSegments$start, knownSegments$end)/1e6, lty=3) 875s > 875s Segmenting by CBS... 875s Chromosome: 1 875s Segmenting by CBS...done 875s Warning message: 875s In plotTracks.CBS(fit2) : 875s Setting default 'Clim' assuming the signal type is ‘ratio’ because signalType(fit2) is unknown (‘NA’). Use signalType(fit2) <- ‘ratio’ to avoid this warning. 875s Segmenting by CBS... 875s Chromosome: 1 875s Segmenting by CBS...done 875s Warning message: 875s In plotTracks.CBS(fit2b) : 875s Setting default 'Clim' assuming the signal type is ‘ratio’ because signalType(fit2b) is unknown (‘NA’). Use signalType(fit2b) <- ‘ratio’ to avoid this warning. 875s Segmenting by CBS... 875s Chromosome: 1 875s Segmenting by CBS...done 875s > 875s > # If one specify the (empty) centromere as a segment, then its 875s > # estimated statistics will be NAs, which becomes a natural 875s > # separator between the two "independent" arms. 875s > knownSegments <- data.frame( 875s + chromosome=c( 1, 1, 1), 875s + start =x[c( 1, 350, 401)], 875s + end =x[c(349, 400, J)] 875s + ) 875s > fit4 <- segmentByCBS(dataW, knownSegments=knownSegments, verbose=TRUE) 875s Segmenting by CBS... 875s Chromosome: 1 875s Segmenting by CBS...done 875s > sampleName(fit4) <- "CBS_Example_4" 875s > print(fit4) 875s sampleName chromosome start end nbrOfLoci mean 875s 1 CBS_Example_4 1 136857.7 19138391 199 -0.0041 875s 2 CBS_Example_4 1 19138391.4 28682180 101 0.8987 875s 3 CBS_Example_4 1 28682180.1 34062461 49 -0.0552 875s 4 CBS_Example_4 1 34108009.8 38257409 0 NA 875s 5 CBS_Example_4 1 38343432.8 64690253 249 0.0298 875s 6 CBS_Example_4 1 64690253.3 80738828 151 -1.0215 875s 7 CBS_Example_4 1 80738828.3 99932904 200 0.0653 875s > plotTracks(fit4) 875s > abline(v=c(knownSegments$start, knownSegments$end)/1e6, lty=3) 875s > 875s > 875s > fit5 <- segmentByCBS(dataW, knownSegments=knownSegments, undo=Inf, verbose=TRUE) 875s Warning message: 875s In plotTracks.CBS(fit4) : 875s Setting default 'Clim' assuming the signal type is ‘ratio’ because signalType(fit4) is unknown (‘NA’). Use signalType(fit4) <- ‘ratio’ to avoid this warning. 875s Segmenting by CBS... 875s Chromosome: 1 875s > sampleName(fit5) <- "CBS_Example_5" 875s Segmenting by CBS...done 875s > print(fit5) 875s sampleName chromosome start end nbrOfLoci mean 875s 1 CBS_Example_5 1 136857.7 34062461 349 0.54781248 875s 2 CBS_Example_5 1 34108009.8 38257409 0 NA 875s 3 CBS_Example_5 1 38343432.8 99932904 600 0.06959745 875s > plotTracks(fit5) 875s Warning message: 875s > abline(v=c(knownSegments$start, knownSegments$end)/1e6, lty=3) 875s > stopifnot(nbrOfSegments(fit5) == nrow(knownSegments)) 875s > 875s > 875s > # One can also force a separator between two segments by setting 875s > # 'start' and 'end' to NAs ('chromosome' has to be given) 875s > knownSegments <- data.frame( 875s + chromosome=c( 1, 1, 1), 875s + start =x[c( 1, NA, 401)], 875s In plotTracks.CBS(fit5) : 875s Setting default 'Clim' assuming the signal type is ‘ratio’ because signalType(fit5) is unknown (‘NA’). Use signalType(fit5) <- ‘ratio’ to avoid this warning. 875s + end =x[c(349, NA, J)] 875s + ) 875s > fit6 <- segmentByCBS(dataW, knownSegments=knownSegments, verbose=TRUE) 875s Segmenting by CBS... 875s Chromosome: 1 875s Segmenting by CBS...done 875s > sampleName(fit6) <- "CBS_Example_6" 875s > print(fit6) 875s sampleName chromosome start end nbrOfLoci mean 875s 1 CBS_Example_6 1 136857.7 19138391 199 -0.0041 875s 2 CBS_Example_6 1 19138391.4 28682180 101 0.8987 876s 3 CBS_Example_6 1 28682180.1 34062461 49 -0.0552 876s 4 NA NA NA NA NA 876s 5 CBS_Example_6 1 38343432.8 64690253 249 0.0298 876s 6 CBS_Example_6 1 64690253.3 80738828 151 -1.0215 876s 7 CBS_Example_6 1 80738828.3 99932904 200 0.0653 876s > plotTracks(fit6) 876s Warning message: 876s In plotTracks.CBS(fit6) : 876s Setting default 'Clim' assuming the signal type is ‘ratio’ because signalType(fit6) is unknown (‘NA’). Use signalType(fit6) <- ‘ratio’ to avoid this warning. 876s > abline(v=c(knownSegments$start, knownSegments$end)/1e6, lty=3) 876s > 876s > 876s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 876s > # Multi-chromosome segmentation 876s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 876s > data2 <- data 876s > data2$chromosome <- 2L 876s > data <- rbind(data, data2) 876s > dataW <- cbind(data, w=w) 876s > 876s > par(mar=c(2,3,0.2,1)+0.1) 876s > # Segment without weights 876s > fit <- segmentByCBS(data) 876s > sampleName(fit) <- "CBS_Example" 876s > print(fit) 876s sampleName chromosome start end nbrOfLoci mean 876s 1 CBS_Example 1 136857.7 19138391 199 0.2712 876s 2 CBS_Example 1 19138391.4 28682180 101 1.2168 876s 3 CBS_Example 1 28682180.1 64690253 298 0.3027 876s 4 CBS_Example 1 64690253.3 80738828 151 -0.7101 876s 5 CBS_Example 1 80738828.3 99932904 200 0.3655 876s 6 NA NA NA NA NA 876s 7 CBS_Example 2 136857.7 19138391 199 0.2712 876s 8 CBS_Example 2 19138391.4 28682180 101 1.2168 876s 9 CBS_Example 2 28682180.1 64690253 298 0.3027 876s 10 CBS_Example 2 64690253.3 80738828 151 -0.7101 876s 11 CBS_Example 2 80738828.3 99932904 200 0.3655 876s > plotTracks(fit, Clim=c(-3,3)) 876s > 876s > # Segment with weights 876s > fitW <- segmentByCBS(dataW) 876s > sampleName(fitW) <- "CBS_Example (weighted)" 876s > print(fitW) 876s sampleName chromosome start end nbrOfLoci mean 876s 1 CBS_Example (weighted) 1 136857.7 19138391 199 -0.0041 876s 2 CBS_Example (weighted) 1 19138391.4 28682180 101 0.8987 876s 3 CBS_Example (weighted) 1 28682180.1 64690253 298 0.0159 876s 4 CBS_Example (weighted) 1 64690253.3 80738828 151 -1.0215 876s 5 CBS_Example (weighted) 1 80738828.3 99932904 200 0.0653 876s 6 NA NA NA NA NA 876s 7 CBS_Example (weighted) 2 136857.7 19138391 199 -0.0041 876s 8 CBS_Example (weighted) 2 19138391.4 28682180 101 0.8987 876s 9 CBS_Example (weighted) 2 28682180.1 64690253 298 0.0159 876s 10 CBS_Example (weighted) 2 64690253.3 80738828 151 -1.0215 876s 11 CBS_Example (weighted) 2 80738828.3 99932904 200 0.0653 876s > drawLevels(fitW, col="red") 876s NULL 876s > 876s > 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)) 876s > 876s > ## Assert that weighted segment means are less biased 876s > dmean <- getSegments(fit)$mean - getSegments(fitW)$mean 876s > cat("Segment mean differences:\n") 876s Segment mean differences: 876s > print(dmean) 876s [1] 0.2753 0.3181 0.2868 0.3114 0.3002 NA 0.2753 0.3181 0.2868 0.3114 876s [11] 0.3002 876s > stopifnot(all(dmean > 0, na.rm=TRUE)) 876s > 876s Start: segmentByCBS.R 876s 876s R version 4.5.2 (2025-10-31) -- "[Not] Part in a Rumble" 876s Copyright (C) 2025 The R Foundation for Statistical Computing 876s Platform: aarch64-unknown-linux-gnu 876s 876s R is free software and comes with ABSOLUTELY NO WARRANTY. 876s You are welcome to redistribute it under certain conditions. 876s Type 'license()' or 'licence()' for distribution details. 876s 876s R is a collaborative project with many contributors. 876s Type 'contributors()' for more information and 876s 'citation()' on how to cite R or R packages in publications. 876s 876s Type 'demo()' for some demos, 'help()' for on-line help, or 876s 'help.start()' for an HTML browser interface to help. 876s Type 'q()' to quit R. 876s 876s > ########################################################### 876s > # This tests: 876s > # - segmentByCBS(...) 876s > # - segmentByCBS(..., knownSegments) 876s > # - tileChromosomes() 876s > # - plotTracks() 876s > ########################################################### 876s > library("PSCBS") 876s PSCBS v0.68.0 (2025-04-18 19:40:02 UTC) successfully loaded. See ?PSCBS for help. 876s > subplots <- R.utils::subplots 876s > 876s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 876s > # Simulating copy-number data 876s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 876s > set.seed(0xBEEF) 876s > 876s > # Number of loci 876s > J <- 1000 876s > 876s > mu <- double(J) 876s > mu[200:300] <- mu[200:300] + 1 876s > mu[350:400] <- NA # centromere 876s > mu[650:800] <- mu[650:800] - 1 876s > eps <- rnorm(J, sd=1/2) 876s > y <- mu + eps 876s > x <- sort(runif(length(y), max=length(y))) * 1e5 876s > w <- runif(J) 876s > w[650:800] <- 0.001 876s > 876s > 876s > subplots(8, ncol=1L) 876s > par(mar=c(1.7,1,0.2,1)+0.1) 876s > 876s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 876s > # Segmentation 876s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 876s > fit <- segmentByCBS(y, x=x) 876s > sampleName(fit) <- "CBS_Example" 876s > print(fit) 876s sampleName chromosome start end nbrOfLoci mean 876s 1 CBS_Example 0 55167.82 20774251 201 0.0164 876s 2 CBS_Example 0 20774250.85 29320105 99 1.0474 876s 3 CBS_Example 0 29320104.86 65874675 298 -0.0203 876s 4 CBS_Example 0 65874675.06 81348129 151 -1.0813 876s 5 CBS_Example 0 81348129.20 99910827 200 -0.0612 876s > plotTracks(fit) 876s > 876s > 876s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 876s > # Segmentation with some known change points 876s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 876s > knownSegments <- data.frame( 876s + chromosome=c( 0, 0), 876s + start =x[c( 1, 401)], 876s Warning message: 876s In plotTracks.CBS(fit) : 876s Setting default 'Clim' assuming the signal type is ‘ratio’ because signalType(fit) is unknown (‘NA’). Use signalType(fit) <- ‘ratio’ to avoid this warning. 876s + end =x[c(349, J)] 876s + ) 876s > fit2 <- segmentByCBS(y, x=x, knownSegments=knownSegments, verbose=TRUE) 876s Segmenting by CBS... 876s Chromosome: 0 877s > sampleName(fit2) <- "CBS_Example_2" 877s Segmenting by CBS...done 877s > print(fit2) 877s sampleName chromosome start end nbrOfLoci mean 877s 1 CBS_Example_2 0 55167.82 20774251 201 0.0164 877s 2 CBS_Example_2 0 20774250.85 29320105 99 1.0474 877s 3 CBS_Example_2 0 29320104.86 34142178 49 -0.0193 877s 4 CBS_Example_2 0 41080532.92 65874675 249 -0.0205 877s 5 CBS_Example_2 0 65874675.06 81348129 151 -1.0813 877s 6 CBS_Example_2 0 81348129.20 99910827 200 -0.0612 877s > plotTracks(fit2) 877s Warning message: 877s In plotTracks.CBS(fit2) : 877s Setting default 'Clim' assuming the signal type is ‘ratio’ because signalType(fit2) is unknown (‘NA’). Use signalType(fit2) <- ‘ratio’ to avoid this warning. 877s > abline(v=c(knownSegments$start, knownSegments$end)/1e6, lty=3) 877s > 877s > 877s > # Chromosome boundaries can be specified as -Inf and +Inf 877s > knownSegments <- data.frame( 877s + chromosome=c( 0, 0), 877s + start =c( -Inf, x[401]), 877s + end =c(x[349], +Inf) 877s + ) 877s > fit2b <- segmentByCBS(y, x=x, knownSegments=knownSegments, verbose=TRUE) 877s Segmenting by CBS... 877s Chromosome: 0 877s > sampleName(fit2b) <- "CBS_Example_2b" 877s Segmenting by CBS...done 877s > print(fit2b) 877s sampleName chromosome start end nbrOfLoci mean 877s 1 CBS_Example_2b 0 55167.82 20774251 201 0.0164 877s 2 CBS_Example_2b 0 20774250.85 29320105 99 1.0474 877s 3 CBS_Example_2b 0 29320104.86 34142178 49 -0.0193 877s 4 CBS_Example_2b 0 41080532.92 65874675 249 -0.0205 877s 5 CBS_Example_2b 0 65874675.06 81348129 151 -1.0813 877s 6 CBS_Example_2b 0 81348129.20 99910827 200 -0.0612 877s > plotTracks(fit2b) 877s Warning message: 877s In plotTracks.CBS(fit2b) : 877s Setting default 'Clim' assuming the signal type is ‘ratio’ because signalType(fit2b) is unknown (‘NA’). Use signalType(fit2b) <- ‘ratio’ to avoid this warning. 877s > abline(v=c(knownSegments$start, knownSegments$end)/1e6, lty=3) 877s > 877s > 877s > # As a proof of concept, it is possible to segment just the centromere, 877s > # which contains no data. All statistics will be NAs. 877s > knownSegments <- data.frame( 877s + chromosome=c( 0), 877s + start =x[c(350)], 877s + end =x[c(400)] 877s + ) 877s > fit3 <- segmentByCBS(y, x=x, knownSegments=knownSegments, verbose=TRUE) 877s Segmenting by CBS... 877s Chromosome: 0 877s > sampleName(fit3) <- "CBS_Example_3" 877s Segmenting by CBS...done 877s > print(fit3) 877s sampleName chromosome start end nbrOfLoci mean 877s 1 CBS_Example_3 0 34194740 41044125 0 NA 877s > plotTracks(fit3, Clim=c(0,5), xlim=c(0,100)) 877s > abline(v=c(knownSegments$start, knownSegments$end)/1e6, lty=3) 877s > 877s > 877s > 877s > # If one specify the (empty) centromere as a segment, then its 877s > # estimated statistics will be NAs, which becomes a natural 877s > # separator between the two "independent" arms. 877s > knownSegments <- data.frame( 877s + chromosome=c( 0, 0, 0), 877s + start =x[c( 1, 350, 401)], 877s + end =x[c(349, 400, J)] 877s + ) 877s > fit4 <- segmentByCBS(y, x=x, knownSegments=knownSegments, verbose=TRUE) 877s Segmenting by CBS... 877s Chromosome: 0 878s Segmenting by CBS...done 878s > sampleName(fit4) <- "CBS_Example_4" 878s > print(fit4) 878s sampleName chromosome start end nbrOfLoci mean 878s 1 CBS_Example_4 0 55167.82 20774251 201 0.0164 878s 2 CBS_Example_4 0 20774250.85 29320105 99 1.0474 878s 3 CBS_Example_4 0 29320104.86 34142178 49 -0.0193 878s 4 CBS_Example_4 0 34194739.81 41044125 0 NA 878s 5 CBS_Example_4 0 41080532.92 65874675 249 -0.0205 878s 6 CBS_Example_4 0 65874675.06 81348129 151 -1.0813 878s 7 CBS_Example_4 0 81348129.20 99910827 200 -0.0612 878s Warning message: 878s In plotTracks.CBS(fit4) : 878s Setting default 'Clim' assuming the signal type is ‘ratio’ because signalType(fit4) is unknown (‘NA’). Use signalType(fit4) <- ‘ratio’ to avoid this warning. 878s > plotTracks(fit4) 878s > abline(v=c(knownSegments$start, knownSegments$end)/1e6, lty=3) 878s > 878s > 878s > 878s > fit5 <- segmentByCBS(y, x=x, knownSegments=knownSegments, undo=Inf, verbose=TRUE) 878s Segmenting by CBS... 878s Chromosome: 0 878s > sampleName(fit5) <- "CBS_Example_5" 878s Segmenting by CBS...done 878s > print(fit5) 878s sampleName chromosome start end nbrOfLoci mean 878s 1 CBS_Example_5 0 55167.82 34142178 349 0.3038785 878s 2 CBS_Example_5 0 34194739.81 41044125 0 NA 878s 3 CBS_Example_5 0 41080532.92 99910827 600 -0.3010285 878s > plotTracks(fit5) 878s > abline(v=c(knownSegments$start, knownSegments$end)/1e6, lty=3) 878s Warning message: 878s > stopifnot(nbrOfSegments(fit5) == nrow(knownSegments)) 878s In plotTracks.CBS(fit5) : 878s Setting default 'Clim' assuming the signal type is ‘ratio’ because signalType(fit5) is unknown (‘NA’). Use signalType(fit5) <- ‘ratio’ to avoid this warning. 878s > 878s > 878s > # One can also force a separator between two segments by setting 878s > # 'start' and 'end' to NAs ('chromosome' has to be given) 878s > knownSegments <- data.frame( 878s + chromosome=c( 0, 0, 0), 878s + start =x[c( 1, NA, 401)], 878s + end =x[c(349, NA, J)] 878s + ) 878s > fit6 <- segmentByCBS(y, x=x, knownSegments=knownSegments, verbose=TRUE) 878s Segmenting by CBS... 878s Chromosome: 0 878s > sampleName(fit6) <- "CBS_Example_6" 878s > print(fit6) 878s Segmenting by CBS...done 878s sampleName chromosome start end nbrOfLoci mean 878s 1 CBS_Example_6 0 55167.82 20774251 201 0.0164 878s 2 CBS_Example_6 0 20774250.85 29320105 99 1.0474 878s 3 CBS_Example_6 0 29320104.86 34142178 49 -0.0193 878s 4 NA NA NA NA NA 878s 5 CBS_Example_6 0 41080532.92 65874675 249 -0.0205 878s 6 CBS_Example_6 0 65874675.06 81348129 151 -1.0813Warning message: 878s In plotTracks.CBS(fit6) : 878s Setting default 'Clim' assuming the signal type is ‘ratio’ because signalType(fit6) is unknown (‘NA’). Use signalType(fit6) <- ‘ratio’ to avoid this warning. 878s 878s 7 CBS_Example_6 0 81348129.20 99910827 200 -0.0612 878s > plotTracks(fit6) 878s > abline(v=c(knownSegments$start, knownSegments$end)/1e6, lty=3) 878s > 878s > 878s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 878s > # Segment multiple chromosomes 878s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 878s > # Simulate multiple chromosomes 878s > fit1 <- renameChromosomes(fit, from=0, to=1) 878s > fit2 <- renameChromosomes(fit, from=0, to=2) 878s > fitM <- c(fit1, fit2) 878s > fitM <- segmentByCBS(fitM) 878s > sampleName(fitM) <- "CBS_Example_M" 878s > print(fitM) 878s sampleName chromosome start end nbrOfLoci mean 878s 1 CBS_Example_M 1 55167.82 20774251 201 0.0164 878s 2 CBS_Example_M 1 20774250.85 29320105 99 1.0474 878s 3 CBS_Example_M 1 29320104.86 65874675 298 -0.0203 878s 4 CBS_Example_M 1 65874675.06 81348129 151 -1.0813 878s 5 CBS_Example_M 1 81348129.20 99910827 200 -0.0612 878s 6 NA NA NA NA NA 878s 7 CBS_Example_M 2 55167.82 20774251 201 0.0164 878s 8 CBS_Example_M 2 20774250.85 29320105 99 1.0474 878s 9 CBS_Example_M 2 29320104.86 65874675 298 -0.0203 878s 10 CBS_Example_M 2 65874675.06 81348129 151 -1.0813 878s 11 CBS_Example_M 2 81348129.20 99910827 200 -0.0612 878s > plotTracks(fitM, Clim=c(-3,3)) 878s > 878s > 878s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 878s > # Tiling multiple chromosomes 878s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 878s > # Tile chromosomes 878s > fitT <- tileChromosomes(fitM) 879s > fitTb <- tileChromosomes(fitT) 879s > stopifnot(identical(fitTb, fitT)) 879s > 879s > 879s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 879s > # Write segmentation to file 879s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 879s > pathT <- tempdir() 879s > 879s > ## Tab-delimited file 879s > pathname <- writeSegments(fitM, path=pathT) 879s Warning message: 879s In write.table(file = pathnameT, data, append = TRUE, quote = FALSE, :> print(pathname) 879s [1] "/tmp/Rtmpae1LhK/CBS_Example_M.tsv" 879s > 879s > ## WIG file 879s > pathname <- writeWIG(fitM, path=pathT) 879s 879s appending column names to file 879s > print(pathname) 879s [1] "/tmp/Rtmpae1LhK/CBS_Example_M.wig" 879s > 879s > unlink(pathT, recursive=TRUE) 879s > 879s Start: segmentByNonPairedPSCBS,medianDH.R 879s 879s R version 4.5.2 (2025-10-31) -- "[Not] Part in a Rumble" 879s Copyright (C) 2025 The R Foundation for Statistical Computing 879s Platform: aarch64-unknown-linux-gnu 879s 879s R is free software and comes with ABSOLUTELY NO WARRANTY. 879s You are welcome to redistribute it under certain conditions. 879s Type 'license()' or 'licence()' for distribution details. 879s 879s R is a collaborative project with many contributors. 879s Type 'contributors()' for more information and 879s 'citation()' on how to cite R or R packages in publications. 879s 879s Type 'demo()' for some demos, 'help()' for on-line help, or 879s 'help.start()' for an HTML browser interface to help. 879s Type 'q()' to quit R. 879s 879s > library("PSCBS") 879s PSCBS v0.68.0 (2025-04-18 19:40:02 UTC) successfully loaded. See ?PSCBS for help. 879s > 879s > 879s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 879s > # Load SNP microarray data 879s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 879s > data <- PSCBS::exampleData("paired.chr01") 879s > str(data) 879s 'data.frame': 73346 obs. of 6 variables: 879s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 879s $ x : int 1145994 2224111 2319424 2543484 2926730 2941694 3084986 3155127 3292731 3695086 ... 879s $ CT : num 1.625 1.071 1.406 1.18 0.856 ... 879s $ betaT : num 0.757 0.771 0.834 0.778 0.229 ... 879s $ CN : num 2.36 2.13 2.59 1.93 1.71 ... 879s $ betaN : num 0.827 0.875 0.887 0.884 0.103 ... 879s > 879s > # Non-paired / tumor-only data 879s > data <- data[,c("chromosome", "x", "CT", "betaT")] 879s > str(data) 879s 'data.frame': 73346 obs. of 4 variables: 879s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 879s $ x : int 1145994 2224111 2319424 2543484 2926730 2941694 3084986 3155127 3292731 3695086 ... 879s $ CT : num 1.625 1.071 1.406 1.18 0.856 ... 879s $ betaT : num 0.757 0.771 0.834 0.778 0.229 ... 879s > 879s > 879s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 879s > # Paired PSCBS segmentation 879s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 879s > # Drop single-locus outliers 879s > dataS <- dropSegmentationOutliers(data) 879s > 879s > # Speed up example by segmenting fewer loci 879s > dataS <- dataS[seq(from=1, to=nrow(data), by=20),] 879s > 879s > # Fake a second chromosome 879s > dataT <- dataS 879s > dataT$chromosome <- 2L 879s > dataS <- rbind(dataS, dataT) 879s > rm(dataT) 879s > str(dataS) 879s 'data.frame': 7336 obs. of 4 variables: 879s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 879s $ x : int 1145994 4276892 5034491 6266412 8418532 11211748 13928296 14370144 15014887 16589707 ... 879s $ CT : num 1.63 1.16 1.35 1.39 1.55 ... 879s $ betaT : num 0.7574 0.0576 0.8391 0.7917 0.8141 ... 879s > 879s > # Non-Paired PSCBS segmentation 879s > fit <- segmentByNonPairedPSCBS(dataS, avgDH="median", seed=0xBEEF, verbose=-10) 879s Segmenting non-paired tumor signals using Non-paired PSCBS... 879s Number of loci: 7336 879s Number of SNPs: 7336 879s Calling "genotypes" from tumor allele B fractions... 879s num [1:7336] 0.7574 0.0576 0.8391 0.7917 0.8141 ... 879s Upper quantile: 0.475631667925522 879s Symmetric lower quantile: 0.290517384533512 879s (tauA, tauB) estimates: (%g,%g)0.2094826154664880.790517384533512 879s Homozygous treshholds: 879s [1] 0.2094826 0.7905174 879s Inferred germline genotypes (via tumor): 879s num [1:7336] 0.5 0 1 1 1 0 0 0 0.5 1 ... 879s muNx 879s 0 0.5 1 879s 2230 2910 2196 879s Calling "genotypes" from tumor allele B fractions...done 879s Segmenting non-paired tumor signals using Non-paired PSCBS...done 879s Segment using Paired PSCBS... 879s Segmenting paired tumor-normal signals using Paired PSCBS... 879s Setup up data... 879s 'data.frame': 7336 obs. of 6 variables: 879s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 879s $ x : num 1145994 4276892 5034491 6266412 8418532 ... 879s $ CT : num 1.63 1.16 1.35 1.39 1.55 ... 879s $ betaT : num 0.7574 0.0576 0.8391 0.7917 0.8141 ... 879s $ betaTN : num 0.7574 0.0576 0.8391 0.7917 0.8141 ... 879s $ muN : num 0.5 0 1 1 1 0 0 0 0.5 1 ... 879s Setup up data...done 879s Dropping loci for which TCNs are missing... 879s Number of loci dropped: 12 879s Dropping loci for which TCNs are missing...done 879s Ordering data along genome... 879s 'data.frame': 7324 obs. of 6 variables: 879s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 879s $ x : num 554484 1031563 1087198 1145994 1176365 ... 879s $ CT : num 1.88 1.64 1.77 1.63 1.59 ... 879s $ betaT : num 0.0646 0.6078 0.401 0.7574 0.645 ... 879s $ betaTN : num 0.0646 0.6078 0.401 0.7574 0.645 ... 879s $ muN : num 0 0.5 0.5 0.5 0.5 0.5 1 0.5 0.5 0.5 ... 879s Ordering data along genome...done 879s Segmenting multiple chromosomes... 879s Number of chromosomes: 2 879s Random seed temporarily set (seed=c(48879), kind="L'Ecuyer-CMRG") 879s Produced 2 seeds from this stream for future usage 879s Chromosome #1 ('Chr01') of 2... 879s 'data.frame': 3662 obs. of 7 variables: 879s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 879s $ x : num 554484 1031563 1087198 1145994 1176365 ... 879s $ CT : num 1.88 1.64 1.77 1.63 1.59 ... 879s $ betaT : num 0.0646 0.6078 0.401 0.7574 0.645 ... 879s $ betaTN : num 0.0646 0.6078 0.401 0.7574 0.645 ... 879s $ muN : num 0 0.5 0.5 0.5 0.5 0.5 1 0.5 0.5 0.5 ... 879s $ index : int 1 2 3 4 5 6 7 8 9 10 ... 879s Known segments: 879s [1] chromosome start end 879s <0 rows> (or 0-length row.names) 879s Segmenting paired tumor-normal signals using Paired PSCBS... 879s Setup up data... 879s 'data.frame': 3662 obs. of 6 variables: 879s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 879s $ x : num 554484 1031563 1087198 1145994 1176365 ... 879s $ CT : num 1.88 1.64 1.77 1.63 1.59 ... 879s $ betaT : num 0.0646 0.6078 0.401 0.7574 0.645 ... 879s $ betaTN : num 0.0646 0.6078 0.401 0.7574 0.645 ... 879s $ muN : num 0 0.5 0.5 0.5 0.5 0.5 1 0.5 0.5 0.5 ... 879s Setup up data...done 879s Ordering data along genome... 879s 'data.frame': 3662 obs. of 6 variables: 879s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 879s $ x : num 554484 1031563 1087198 1145994 1176365 ... 879s $ CT : num 1.88 1.64 1.77 1.63 1.59 ... 879s $ betaT : num 0.0646 0.6078 0.401 0.7574 0.645 ... 879s $ betaTN : num 0.0646 0.6078 0.401 0.7574 0.645 ... 879s $ muN : num 0 0.5 0.5 0.5 0.5 0.5 1 0.5 0.5 0.5 ... 879s Ordering data along genome...done 879s Keeping only current chromosome for 'knownSegments'... 879s Chromosome: 1 879s Known segments for this chromosome: 879s [1] chromosome start end 879s <0 rows> (or 0-length row.names) 879s Keeping only current chromosome for 'knownSegments'...done 879s alphaTCN: 0.009 879s alphaDH: 0.001 879s Number of loci: 3662 879s Calculating DHs... 879s Number of SNPs: 3662 879s Number of heterozygous SNPs: 1451 (39.62%) 879s Normalized DHs: 879s num [1:3662] NA 0.216 0.198 0.515 0.29 ... 879s Calculating DHs...done 879s Random seed temporarily set (seed=c(10407, 1066287653, -51199871, 161854402, -1995183193, 1503453565, -747102133), kind="L'Ecuyer-CMRG") 879s Produced 2 seeds from this stream for future usage 879s Identification of change points by total copy numbers... 879s Segmenting by CBS... 880s Chromosome: 1 880s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 880s Segmenting by CBS...done 880s List of 4 880s $ data :'data.frame': 3662 obs. of 4 variables: 880s ..$ chromosome: int [1:3662] 1 1 1 1 1 1 1 1 1 1 ... 880s ..$ x : num [1:3662] 554484 1031563 1087198 1145994 1176365 ... 880s ..$ y : num [1:3662] 1.88 1.64 1.77 1.63 1.59 ... 880s ..$ index : int [1:3662] 1 2 3 4 5 6 7 8 9 10 ... 880s $ output :'data.frame': 3 obs. of 6 variables: 880s ..$ sampleName: chr [1:3] NA NA NA 880s ..$ chromosome: int [1:3] 1 1 1 880s ..$ start : num [1:3] 5.54e+05 1.44e+08 1.85e+08 880s ..$ end : num [1:3] 1.44e+08 1.85e+08 2.47e+08 880s ..$ nbrOfLoci : int [1:3] 1880 671 1111 880s ..$ mean : num [1:3] 1.39 2.09 2.65 880s $ segRows:'data.frame': 3 obs. of 2 variables: 880s ..$ startRow: int [1:3] 1 1881 2552 880s ..$ endRow : int [1:3] 1880 2551 3662 880s $ params :List of 5 880s ..$ alpha : num 0.009 880s ..$ undo : num 0 880s ..$ joinSegments : logi TRUE 880s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 880s .. ..$ chromosome: int 1 880s .. ..$ start : num -Inf 880s .. ..$ end : num Inf 880s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 880s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 880s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.063 0 0.063 0 0 880s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 880s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 880s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 880s Identification of change points by total copy numbers...done 880s Restructure TCN segmentation results... 880s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean 880s 1 1 554484 143663981 1880 1.3916 880s 2 1 143663981 185240536 671 2.0925 880s 3 1 185240536 246679946 1111 2.6545 880s Number of TCN segments: 3 880s Restructure TCN segmentation results...done 880s TCN-only segmentation... 880s Total CN segment #1 ([ 554484,1.43664e+08]) of 3... 880s Number of TCN loci in segment: 1880 880s Locus data for TCN segment: 880s 'data.frame': 1880 obs. of 8 variables: 880s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 880s $ x : num 554484 1031563 1087198 1145994 1176365 ... 880s $ CT : num 1.88 1.64 1.77 1.63 1.59 ... 880s $ betaT : num 0.0646 0.6078 0.401 0.7574 0.645 ... 880s $ betaTN : num 0.0646 0.6078 0.401 0.7574 0.645 ... 880s $ muN : num 0 0.5 0.5 0.5 0.5 0.5 1 0.5 0.5 0.5 ... 880s $ index : int 1 2 3 4 5 6 7 8 9 10 ... 880s $ rho : num NA 0.216 0.198 0.515 0.29 ... 880s Number of loci: 1880 880s Number of SNPs: 765 (40.69%) 880s Number of heterozygous SNPs: 765 (100.00%) 880s Total CN segment #1 ([ 554484,1.43664e+08]) of 3...done 880s Total CN segment #2 ([1.43664e+08,1.85241e+08]) of 3... 880s Number of TCN loci in segment: 671 880s Locus data for TCN segment: 880s 'data.frame': 671 obs. of 8 variables: 880s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 880s $ x : num 1.44e+08 1.44e+08 1.44e+08 1.44e+08 1.44e+08 ... 880s $ CT : num 2.26 2.1 2.1 1.89 1.97 ... 880s $ betaT : num 0.958 0.19 0.909 0.13 0.141 ... 880s $ betaTN : num 0.958 0.19 0.909 0.13 0.141 ... 880s $ muN : num 1 0 1 0 0 0 0 0.5 0 1 ... 880s $ index : int 1881 1882 1883 1884 1885 1886 1887 1888 1889 1890 ... 880s $ rho : num NA NA NA NA NA ... 880s Number of loci: 671 880s Number of SNPs: 272 (40.54%) 880s Number of heterozygous SNPs: 272 (100.00%) 880s Total CN segment #2 ([1.43664e+08,1.85241e+08]) of 3...done 880s Total CN segment #3 ([1.85241e+08,2.4668e+08]) of 3... 880s Number of TCN loci in segment: 1111 880s Locus data for TCN segment: 880s 'data.frame': 1111 obs. of 8 variables: 880s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 880s $ x : num 1.85e+08 1.86e+08 1.86e+08 1.86e+08 1.86e+08 ... 880s $ CT : num 2.44 3 2.32 2.76 2.48 ... 880s $ betaT : num 0.0727 0.6845 0.2327 0.8118 0.0746 ... 880s $ betaTN : num 0.0727 0.6845 0.2327 0.8118 0.0746 ... 880s $ muN : num 0 0.5 0.5 1 0 1 0 1 1 0.5 ... 880s $ index : int 2552 2553 2554 2555 2556 2557 2558 2559 2560 2561 ... 880s $ rho : num NA 0.369 0.535 NA NA ... 880s Number of loci: 1111 880s Number of SNPs: 414 (37.26%) 880s Number of heterozygous SNPs: 414 (100.00%) 880s Total CN segment #3 ([1.85241e+08,2.4668e+08]) of 3...done 880s TCN-only segmentation...done 880s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 880s 1 1 1 1 554484 143663981 1880 1.3916 765 880s 2 1 2 1 143663981 185240536 671 2.0925 272 880s 3 1 3 1 185240536 246679946 1111 2.6545 414 880s tcnNbrOfHets dhNbrOfLoci dhStart dhEnd dhMean 880s 1 765 765 554484 143663981 0.3979122 880s 2 272 272 143663981 185240536 0.2306116 880s 3 414 414 185240536 246679946 0.2798120 880s Calculating (C1,C2) per segment... 880s Calculating (C1,C2) per segment...done 880s Number of segments: 3 880s Segmenting paired tumor-normal signals using Paired PSCBS...done 880s Updating mean level using different estimator... 880s TCN estimator: mean 880s DH estimator: median 880s Updating mean level using different estimator...done 880s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 880s 1 1 1 1 554484 143663981 1880 1.391608 765 880s 2 1 2 1 143663981 185240536 671 2.092452 272 880s 3 1 3 1 185240536 246679946 1111 2.654512 414 880s tcnNbrOfHets dhNbrOfLoci dhStart dhEnd dhMean c1Mean c2Mean 880s 1 765 765 554484 143663981 0.4206323 0.4031263 0.9884817 880s 2 272 272 143663981 185240536 0.1762428 0.8618360 1.2306156 880s 3 414 414 185240536 246679946 0.2697420 0.9692395 1.6852728 880s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 880s 1 1 1 1 554484 143663981 1880 1.391608 765 880s 2 1 2 1 143663981 185240536 671 2.092452 272 880s 3 1 3 1 185240536 246679946 1111 2.654512 414 880s tcnNbrOfHets dhNbrOfLoci dhStart dhEnd dhMean c1Mean c2Mean 880s 1 765 765 554484 143663981 0.4206323 0.4031263 0.9884817 880s 2 272 272 143663981 185240536 0.1762428 0.8618360 1.2306156 880s 3 414 414 185240536 246679946 0.2697420 0.9692395 1.6852728 880s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 880s 1 1 1 1 554484 143663981 1880 1.391608 765 880s 2 1 2 1 143663981 185240536 671 2.092452 272 880s 3 1 3 1 185240536 246679946 1111 2.654512 414 880s tcnNbrOfHets dhNbrOfLoci dhStart dhEnd dhMean c1Mean c2Mean 880s 1 765 765 554484 143663981 0.4206323 0.4031263 0.9884817 880s 2 272 272 143663981 185240536 0.1762428 0.8618360 1.2306156 880s 3 414 414 185240536 246679946 0.2697420 0.9692395 1.6852728 880s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 880s 1 1 1 1 554484 143663981 1880 1.391608 765 880s 2 1 2 1 143663981 185240536 671 2.092452 272 880s 3 1 3 1 185240536 246679946 1111 2.654512 414 880s tcnNbrOfHets dhNbrOfLoci dhStart dhEnd dhMean c1Mean c2Mean 880s 1 765 765 554484 143663981 0.4206323 0.4031263 0.9884817 880s 2 272 272 143663981 185240536 0.1762428 0.8618360 1.2306156 880s 3 414 414 185240536 246679946 0.2697420 0.9692395 1.6852728 880s Chromosome #1 ('Chr01') of 2...done 880s Chromosome #2 ('Chr02') of 2... 880s 'data.frame': 3662 obs. of 7 variables: 880s $ chromosome: int 2 2 2 2 2 2 2 2 2 2 ... 880s $ x : num 554484 1031563 1087198 1145994 1176365 ... 880s $ CT : num 1.88 1.64 1.77 1.63 1.59 ... 880s $ betaT : num 0.0646 0.6078 0.401 0.7574 0.645 ... 880s $ betaTN : num 0.0646 0.6078 0.401 0.7574 0.645 ... 880s $ muN : num 0 0.5 0.5 0.5 0.5 0.5 1 0.5 0.5 0.5 ... 880s $ index : int 3663 3664 3665 3666 3667 3668 3669 3670 3671 3672 ... 880s Known segments: 880s [1] chromosome start end 880s <0 rows> (or 0-length row.names) 880s Segmenting paired tumor-normal signals using Paired PSCBS... 880s Setup up data... 880s 'data.frame': 3662 obs. of 6 variables: 880s $ chromosome: int 2 2 2 2 2 2 2 2 2 2 ... 880s $ x : num 554484 1031563 1087198 1145994 1176365 ... 880s $ CT : num 1.88 1.64 1.77 1.63 1.59 ... 880s $ betaT : num 0.0646 0.6078 0.401 0.7574 0.645 ... 880s $ betaTN : num 0.0646 0.6078 0.401 0.7574 0.645 ... 880s $ muN : num 0 0.5 0.5 0.5 0.5 0.5 1 0.5 0.5 0.5 ... 880s Setup up data...done 880s Ordering data along genome... 880s 'data.frame': 3662 obs. of 6 variables: 880s $ chromosome: int 2 2 2 2 2 2 2 2 2 2 ... 880s $ x : num 554484 1031563 1087198 1145994 1176365 ... 880s $ CT : num 1.88 1.64 1.77 1.63 1.59 ... 880s $ betaT : num 0.0646 0.6078 0.401 0.7574 0.645 ... 880s $ betaTN : num 0.0646 0.6078 0.401 0.7574 0.645 ... 880s $ muN : num 0 0.5 0.5 0.5 0.5 0.5 1 0.5 0.5 0.5 ... 880s Ordering data along genome...done 880s Keeping only current chromosome for 'knownSegments'... 880s Chromosome: 2 880s Known segments for this chromosome: 880s [1] chromosome start end 880s <0 rows> (or 0-length row.names) 880s Keeping only current chromosome for 'knownSegments'...done 880s alphaTCN: 0.009 880s alphaDH: 0.001 880s Number of loci: 3662 880s Calculating DHs... 880s Number of SNPs: 3662 880s Number of heterozygous SNPs: 1451 (39.62%) 880s Normalized DHs: 880s num [1:3662] NA 0.216 0.198 0.515 0.29 ... 880s Calculating DHs...done 880s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 880s Produced 2 seeds from this stream for future usage 880s Identification of change points by total copy numbers... 880s Segmenting by CBS... 880s Chromosome: 2 880s Random seed temporarily set (seed=c(10407, -821273412, -52578226, 1415511586, 721384351, -665928286, 1316562960), kind="L'Ecuyer-CMRG") 880s Segmenting by CBS...done 880s List of 4 880s $ data :'data.frame': 3662 obs. of 4 variables: 880s ..$ chromosome: int [1:3662] 2 2 2 2 2 2 2 2 2 2 ... 880s ..$ x : num [1:3662] 554484 1031563 1087198 1145994 1176365 ... 880s ..$ y : num [1:3662] 1.88 1.64 1.77 1.63 1.59 ... 880s ..$ index : int [1:3662] 1 2 3 4 5 6 7 8 9 10 ... 880s $ output :'data.frame': 3 obs. of 6 variables: 880s ..$ sampleName: chr [1:3] NA NA NA 880s ..$ chromosome: int [1:3] 2 2 2 880s ..$ start : num [1:3] 5.54e+05 1.44e+08 1.85e+08 880s ..$ end : num [1:3] 1.44e+08 1.85e+08 2.47e+08 880s ..$ nbrOfLoci : int [1:3] 1880 671 1111 880s ..$ mean : num [1:3] 1.39 2.09 2.65 880s $ segRows:'data.frame': 3 obs. of 2 variables: 880s ..$ startRow: int [1:3] 1 1881 2552 880s ..$ endRow : int [1:3] 1880 2551 3662 880s $ params :List of 5 880s ..$ alpha : num 0.009 880s ..$ undo : num 0 880s ..$ joinSegments : logi TRUE 880s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 880s .. ..$ chromosome: int 2 880s .. ..$ start : num -Inf 880s .. ..$ end : num Inf 880s ..$ seed : int [1:7] 10407 -821273412 -52578226 1415511586 721384351 -665928286 1316562960 880s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 880s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.062 0 0.062 0 0 880s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 880s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 880s - attr(*, "randomSeed")= int [1:7] 10407 -821273412 -52578226 1415511586 721384351 -665928286 1316562960 880s Identification of change points by total copy numbers...done 880s Restructure TCN segmentation results... 880s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean 880s 1 2 554484 143663981 1880 1.3916 880s 2 2 143663981 185240536 671 2.0925 880s 3 2 185240536 246679946 1111 2.6545 880s Number of TCN segments: 3 880s Restructure TCN segmentation results...done 880s TCN-only segmentation... 880s Total CN segment #1 ([ 554484,1.43664e+08]) of 3... 880s Number of TCN loci in segment: 1880 880s Locus data for TCN segment: 880s 'data.frame': 1880 obs. of 8 variables: 880s $ chromosome: int 2 2 2 2 2 2 2 2 2 2 ... 880s $ x : num 554484 1031563 1087198 1145994 1176365 ... 880s $ CT : num 1.88 1.64 1.77 1.63 1.59 ... 880s $ betaT : num 0.0646 0.6078 0.401 0.7574 0.645 ... 880s $ betaTN : num 0.0646 0.6078 0.401 0.7574 0.645 ... 880s $ muN : num 0 0.5 0.5 0.5 0.5 0.5 1 0.5 0.5 0.5 ... 880s $ index : int 1 2 3 4 5 6 7 8 9 10 ... 880s $ rho : num NA 0.216 0.198 0.515 0.29 ... 880s Number of loci: 1880 880s Number of SNPs: 765 (40.69%) 880s Number of heterozygous SNPs: 765 (100.00%) 880s Total CN segment #1 ([ 554484,1.43664e+08]) of 3...done 880s Total CN segment #2 ([1.43664e+08,1.85241e+08]) of 3... 880s Number of TCN loci in segment: 671 880s Locus data for TCN segment: 880s 'data.frame': 671 obs. of 8 variables: 880s $ chromosome: int 2 2 2 2 2 2 2 2 2 2 ... 880s $ x : num 1.44e+08 1.44e+08 1.44e+08 1.44e+08 1.44e+08 ... 880s $ CT : num 2.26 2.1 2.1 1.89 1.97 ... 880s $ betaT : num 0.958 0.19 0.909 0.13 0.141 ... 880s $ betaTN : num 0.958 0.19 0.909 0.13 0.141 ... 880s $ muN : num 1 0 1 0 0 0 0 0.5 0 1 ... 880s $ index : int 1881 1882 1883 1884 1885 1886 1887 1888 1889 1890 ... 880s $ rho : num NA NA NA NA NA ... 880s Number of loci: 671 880s Number of SNPs: 272 (40.54%) 880s Number of heterozygous SNPs: 272 (100.00%) 880s Total CN segment #2 ([1.43664e+08,1.85241e+08]) of 3...done 880s Total CN segment #3 ([1.85241e+08,2.4668e+08]) of 3... 880s Number of TCN loci in segment: 1111 880s Locus data for TCN segment: 880s 'data.frame': 1111 obs. of 8 variables: 880s $ chromosome: int 2 2 2 2 2 2 2 2 2 2 ... 880s $ x : num 1.85e+08 1.86e+08 1.86e+08 1.86e+08 1.86e+08 ... 880s $ CT : num 2.44 3 2.32 2.76 2.48 ... 880s $ betaT : num 0.0727 0.6845 0.2327 0.8118 0.0746 ... 880s $ betaTN : num 0.0727 0.6845 0.2327 0.8118 0.0746 ... 880s $ muN : num 0 0.5 0.5 1 0 1 0 1 1 0.5 ... 880s $ index : int 2552 2553 2554 2555 2556 2557 2558 2559 2560 2561 ... 880s $ rho : num NA 0.369 0.535 NA NA ... 880s Number of loci: 1111 880s Number of SNPs: 414 (37.26%) 880s Number of heterozygous SNPs: 414 (100.00%) 880s Total CN segment #3 ([1.85241e+08,2.4668e+08]) of 3...done 880s TCN-only segmentation...done 880s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 880s 1 2 1 1 554484 143663981 1880 1.3916 765 880s 2 2 2 1 143663981 185240536 671 2.0925 272 880s 3 2 3 1 185240536 246679946 1111 2.6545 414 880s tcnNbrOfHets dhNbrOfLoci dhStart dhEnd dhMean 880s 1 765 765 554484 143663981 0.3979122 880s 2 272 272 143663981 185240536 0.2306116 880s 3 414 414 185240536 246679946 0.2798120 880s Calculating (C1,C2) per segment... 880s Calculating (C1,C2) per segment...done 880s Number of segments: 3 880s Segmenting paired tumor-normal signals using Paired PSCBS...done 880s Updating mean level using different estimator... 880s TCN estimator: mean 880s DH estimator: median 880s Updating mean level using different estimator...done 880s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 880s 1 2 1 1 554484 143663981 1880 1.391608 765 880s 2 2 2 1 143663981 185240536 671 2.092452 272 880s 3 2 3 1 185240536 246679946 1111 2.654512 414 880s tcnNbrOfHets dhNbrOfLoci dhStart dhEnd dhMean c1Mean c2Mean 880s 1 765 765 554484 143663981 0.4206323 0.4031263 0.9884817 880s 2 272 272 143663981 185240536 0.1762428 0.8618360 1.2306156 880s 3 414 414 185240536 246679946 0.2697420 0.9692395 1.6852728 880s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 880s 1 2 1 1 554484 143663981 1880 1.391608 765 880s 2 2 2 1 143663981 185240536 671 2.092452 272 880s 3 2 3 1 185240536 246679946 1111 2.654512 414 880s tcnNbrOfHets dhNbrOfLoci dhStart dhEnd dhMean c1Mean c2Mean 880s 1 765 765 554484 143663981 0.4206323 0.4031263 0.9884817 880s 2 272 272 143663981 185240536 0.1762428 0.8618360 1.2306156 880s 3 414 414 185240536 246679946 0.2697420 0.9692395 1.6852728 880s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 880s 1 2 1 1 554484 143663981 1880 1.391608 765 880s 2 2 2 1 143663981 185240536 671 2.092452 272 880s 3 2 3 1 185240536 246679946 1111 2.654512 414 880s tcnNbrOfHets dhNbrOfLoci dhStart dhEnd dhMean c1Mean c2Mean 880s 1 765 765 554484 143663981 0.4206323 0.4031263 0.9884817 880s 2 272 272 143663981 185240536 0.1762428 0.8618360 1.2306156 880s 3 414 414 185240536 246679946 0.2697420 0.9692395 1.6852728 880s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 880s 1 2 1 1 554484 143663981 1880 1.391608 765 880s 2 2 2 1 143663981 185240536 671 2.092452 272 880s 3 2 3 1 185240536 246679946 1111 2.654512 414 880s tcnNbrOfHets dhNbrOfLoci dhStart dhEnd dhMean c1Mean c2Mean 880s 1 765 765 554484 143663981 0.4206323 0.4031263 0.9884817 880s 2 272 272 143663981 185240536 0.1762428 0.8618360 1.2306156 880s 3 414 414 185240536 246679946 0.2697420 0.9692395 1.6852728 880s Chromosome #2 ('Chr02') of 2...done 880s Merging (independently) segmented chromosome... 880s List of 5 880s $ data :Classes ‘PairedPSCNData’ and 'data.frame': 7324 obs. of 7 variables: 880s ..$ chromosome: int [1:7324] 1 1 1 1 1 1 1 1 1 1 ... 880s ..$ x : num [1:7324] 554484 1031563 1087198 1145994 1176365 ... 880s ..$ CT : num [1:7324] 1.88 1.64 1.77 1.63 1.59 ... 880s ..$ betaT : num [1:7324] 0.0646 0.6078 0.401 0.7574 0.645 ... 880s ..$ betaTN : num [1:7324] 0.0646 0.6078 0.401 0.7574 0.645 ... 880s ..$ muN : num [1:7324] 0 0.5 0.5 0.5 0.5 0.5 1 0.5 0.5 0.5 ... 880s ..$ rho : num [1:7324] NA 0.216 0.198 0.515 0.29 ... 880s $ output :Classes ‘PairedPSCNSegments’ and 'data.frame': 7 obs. of 15 variables: 880s ..$ chromosome : int [1:7] 1 1 1 NA 2 2 2 880s ..$ tcnId : int [1:7] 1 2 3 NA 1 2 3 880s ..$ dhId : int [1:7] 1 1 1 NA 1 1 1 880s ..$ tcnStart : num [1:7] 5.54e+05 1.44e+08 1.85e+08 NA 5.54e+05 ... 880s ..$ tcnEnd : num [1:7] 1.44e+08 1.85e+08 2.47e+08 NA 1.44e+08 ... 880s ..$ tcnNbrOfLoci: int [1:7] 1880 671 1111 NA 1880 671 1111 880s ..$ tcnMean : num [1:7] 1.39 2.09 2.65 NA 1.39 ... 880s ..$ tcnNbrOfSNPs: int [1:7] 765 272 414 NA 765 272 414 880s ..$ tcnNbrOfHets: int [1:7] 765 272 414 NA 765 272 414 880s ..$ dhNbrOfLoci : int [1:7] 765 272 414 NA 765 272 414 880s ..$ dhStart : num [1:7] 5.54e+05 1.44e+08 1.85e+08 NA 5.54e+05 ... 880s ..$ dhEnd : num [1:7] 1.44e+08 1.85e+08 2.47e+08 NA 1.44e+08 ... 880s ..$ dhMean : num [1:7] 0.421 0.176 0.27 NA 0.421 ... 880s ..$ c1Mean : num [1:7] 0.403 0.862 0.969 NA 0.403 ... 880s ..$ c2Mean : num [1:7] 0.988 1.231 1.685 NA 0.988 ... 880s $ tcnSegRows:'data.frame': 7 obs. of 2 variables: 880s ..$ startRow: int [1:7] 1 1881 2552 NA 3663 5543 6214 880s ..$ endRow : int [1:7] 1880 2551 3662 NA 5542 6213 7324 880s $ dhSegRows :'data.frame': 7 obs. of 2 variables: 880s ..$ startRow: int [1:7] 2 1888 2553 NA 3664 5550 6215 880s ..$ endRow : int [1:7] 1876 2548 3659 NA 5538 6210 7321 880s $ params :List of 8 880s ..$ alphaTCN : num 0.009 880s ..$ alphaDH : num 0.001 880s ..$ flavor : chr "tcn" 880s ..$ tbn : logi FALSE 880s ..$ joinSegments : logi TRUE 880s ..$ knownSegments :'data.frame': 0 obs. of 3 variables: 880s .. ..$ chromosome: int(0) 880s .. ..$ start : int(0) 880s .. ..$ end : int(0) 880s ..$ seed : int [1:7] 10407 1066287653 -51199871 161854402 -1995183193 1503453565 -747102133 880s ..$ meanEstimators:List of 2 880s .. ..$ tcn: chr "mean" 880s .. ..$ dh : chr "median" 880s - attr(*, "class")= chr [1:3] "PairedPSCBS" "PSCBS" "AbstractCBS" 880s Merging (independently) segmented chromosome...done 880s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 880s 1 1 1 1 554484 143663981 1880 1.391608 765 880s 2 1 2 1 143663981 185240536 671 2.092452 272 880s 3 1 3 1 185240536 246679946 1111 2.654512 414 880s 4 NA NA NA NA NA NA NA NA 880s 5 2 1 1 554484 143663981 1880 1.391608 765 880s 6 2 2 1 143663981 185240536 671 2.092452 272 880s tcnNbrOfHets dhNbrOfLoci dhStart dhEnd dhMean c1Mean c2Mean 880s 1 765 765 554484 143663981 0.4206323 0.4031263 0.9884817 880s 2 272 272 143663981 185240536 0.1762428 0.8618360 1.2306156 880s 3 414 414 185240536 246679946 0.2697420 0.9692395 1.6852728 880s 4 NA NA NA NA NA NA NA 880s 5 765 765 554484 143663981 0.4206323 0.4031263 0.9884817 880s 6 272 272 143663981 185240536 0.1762428 0.8618360 1.2306156 880s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 880s 2 1 2 1 143663981 185240536 671 2.092452 272 880s 3 1 3 1 185240536 246679946 1111 2.654512 414 880s 4 NA NA NA NA NA NA NA NA 880s 5 2 1 1 554484 143663981 1880 1.391608 765 880s 6 2 2 1 143663981 185240536 671 2.092452 272 880s 7 2 3 1 185240536 246679946 1111 2.654512 414 880s tcnNbrOfHets dhNbrOfLoci dhStart dhEnd dhMean c1Mean c2Mean 880s 2 272 272 143663981 185240536 0.1762428 0.8618360 1.2306156 880s 3 414 414 185240536 246679946 0.2697420 0.9692395 1.6852728 880s 4 NA NA NA NA NA NA NA 880s 5 765 765 554484 143663981 0.4206323 0.4031263 0.9884817 880s 6 272 272 143663981 185240536 0.1762428 0.8618360 1.2306156 880s 7 414 414 185240536 246679946 0.2697420 0.9692395 1.6852728 880s Segmenting multiple chromosomes...done 880s Segmenting paired tumor-normal signals using Paired PSCBS...done 880s Segment using Paired PSCBS...done 880s Coercing to Non-Paired PSCBS results... 880s Coercing to Non-Paired PSCBS results...done 880s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 880s 1 1 1 1 554484 143663981 1880 1.391608 765 880s 2 1 2 1 143663981 185240536 671 2.092452 272 880s 3 1 3 1 185240536 246679946 1111 2.654512 414 880s 4 NA NA NA NA NA NA NA NA 880s 5 2 1 1 554484 143663981 1880 1.391608 765 880s 6 2 2 1 143663981 185240536 671 2.092452 272 880s tcnNbrOfHets dhNbrOfLoci dhStart dhEnd dhMean c1Mean c2Mean 880s 1 765 765 554484 143663981 0.4206323 0.4031263 0.9884817 880s 2 272 272 143663981 185240536 0.1762428 0.8618360 1.2306156 880s 3 414 414 185240536 246679946 0.2697420 0.9692395 1.6852728 880s 4 NA NA NA NA NA NA NA 880s 5 765 765 554484 143663981 0.4206323 0.4031263 0.9884817 880s 6 272 272 143663981 185240536 0.1762428 0.8618360 1.2306156 880s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 880s 2 1 2 1 143663981 185240536 671 2.092452 272 880s 3 1 3 1 185240536 246679946 1111 2.654512 414 880s 4 NA NA NA NA NA NA NA NA 880s 5 2 1 1 554484 143663981 1880 1.391608 765 880s 6 2 2 1 143663981 185240536 671 2.092452 272 880s 7 2 3 1 185240536 246679946 1111 2.654512 414 880s tcnNbrOfHets dhNbrOfLoci dhStart dhEnd dhMean c1Mean c2Mean 880s 2 272 272 143663981 185240536 0.1762428 0.8618360 1.2306156 880s 3 414 414 185240536 246679946 0.2697420 0.9692395 1.6852728 880s 4 NA NA NA NA NA NA NA 880s 5 765 765 554484 143663981 0.4206323 0.4031263 0.9884817 880s 6 272 272 143663981 185240536 0.1762428 0.8618360 1.2306156 880s 7 414 414 185240536 246679946 0.2697420 0.9692395 1.6852728 880s > print(fit) 880s chromosome tcnId dhId start end tcnNbrOfLoci tcnMean tcnNbrOfSNPs 880s 1 1 1 1 554484 143663981 1880 1.391608 765 880s 2 1 2 1 143663981 185240536 671 2.092452 272 880s 3 1 3 1 185240536 246679946 1111 2.654512 414 880s 4 NA NA NA NA NA NA NA NA 880s 5 2 1 1 554484 143663981 1880 1.391608 765 880s 6 2 2 1 143663981 185240536 671 2.092452 272 880s 7 2 3 1 185240536 246679946 1111 2.654512 414 880s tcnNbrOfHets dhNbrOfLoci dhMean c1Mean c2Mean 880s 1 765 765 0.4206323 0.4031263 0.9884817 880s 2 272 272 0.1762428 0.8618360 1.2306156 880s 3 414 414 0.2697420 0.9692395 1.6852728 880s 4 NA NA NA NA NA 880s 5 765 765 0.4206323 0.4031263 0.9884817 880s 6 272 272 0.1762428 0.8618360 1.2306156 880s 7 414 414 0.2697420 0.9692395 1.6852728 880s > 880s > 880s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 880s > # Bootstrap segment level estimates 880s > # (used by the AB caller, which, if skipped here, 880s > # will do it automatically) 880s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 880s > fit <- bootstrapTCNandDHByRegion(fit, B=100, verbose=-10) 880s Resample (TCN,DH) signals and re-estimate summaries for segment & changepoint... 880s Already done? 880s tcn_2.5% tcn_5% tcn_95% tcn_97.5% dh_2.5% dh_5% dh_95% dh_97.5% 880s FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE 880s c1_2.5% c1_5% c1_95% c1_97.5% c2_2.5% c2_5% c2_95% c2_97.5% 880s FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE 880s Bootstrapping (TCN,DH,C1,C2) segment mean levels... 880s Identifying heterozygous & homozygous SNPs and non-polymorphic loci... 880s Number of loci: 7324 880s Number of SNPs: 2902 880s Number of non-SNPs: 4422 880s Identifying heterozygous & homozygous SNPs and non-polymorphic loci...done 880s num [1:7, 1:100, 1:4] NA NA NA NA NA NA NA NA NA NA ... 880s - attr(*, "dimnames")=List of 3 880s ..$ : NULL 880s ..$ : NULL 880s ..$ : chr [1:4] "tcn" "dh" "c1" "c2" 880s Segment #1 (chr 1, tcnId=1, dhId=1) of 7... 880s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 880s 1 1 1 1 554484 143663981 1880 1.391608 765 880s tcnNbrOfHets dhNbrOfLoci dhStart dhEnd dhMean c1Mean c2Mean 880s 1 765 765 554484 143663981 0.4206323 0.4031263 0.9884817 880s Number of TCNs: 1880 880s Number of DHs: 765 880s int [1:1880] 1 2 3 4 5 6 7 8 9 10 ... 880s int [1:7324] 1 2 3 4 5 6 7 8 9 10 ... 880s int [1:1880] 1 2 3 4 5 6 7 8 9 10 ... 880s Identify loci used to bootstrap DH means... 880s Heterozygous SNPs to resample for DH: 880s int [1:765] 2 3 4 5 6 8 9 10 11 12 ... 880s Identify loci used to bootstrap DH means...done 880s Identify loci used to bootstrap TCN means... 880s SNPs: 880s int [1:765] 2 3 4 5 6 8 9 10 11 12 ... 880s Non-polymorphic loci: 880s int [1:1115] 1 7 15 28 30 32 34 35 36 37 ... 880s Heterozygous SNPs to resample for TCN: 880s int [1:765] 2 3 4 5 6 8 9 10 11 12 ... 880s Homozygous SNPs to resample for TCN: 880s int(0) 880s Non-polymorphic loci to resample for TCN: 880s int [1:1115] 1 7 15 28 30 32 34 35 36 37 ... 880s Heterozygous SNPs with non-DH to resample for TCN: 880s int(0) 880s Loci to resample for TCN: 880s int [1:1880] 1 2 3 4 5 6 7 8 9 10 ... 880s Identify loci used to bootstrap TCN means...done 880s Number of (#hets, #homs, #nonSNPs): (765,0,1115) 880s Bootstrapping while preserving (#hets, #homs, #nonSNPs)... 880s Number of bootstrap samples: 100 880s Bootstrapping while preserving (#hets, #homs, #nonSNPs)...done 880s Segment #1 (chr 1, tcnId=1, dhId=1) of 7...done 880s Segment #2 (chr 1, tcnId=2, dhId=1) of 7... 880s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 880s 2 1 2 1 143663981 185240536 671 2.092452 272 880s tcnNbrOfHets dhNbrOfLoci dhStart dhEnd dhMean c1Mean c2Mean 880s 2 272 272 143663981 185240536 0.1762428 0.861836 1.230616 880s Number of TCNs: 671 880s Number of DHs: 272 880s int [1:671] 1881 1882 1883 1884 1885 1886 1887 1888 1889 1890 ... 880s int [1:7324] 1 2 3 4 5 6 7 8 9 10 ... 880s int [1:671] 1881 1882 1883 1884 1885 1886 1887 1888 1889 1890 ... 880s Identify loci used to bootstrap DH means... 880s Heterozygous SNPs to resample for DH: 880s int [1:272] 1888 1893 1894 1895 1896 1897 1901 1903 1907 1908 ... 880s Identify loci used to bootstrap DH means...done 880s Identify loci used to bootstrap TCN means... 880s SNPs: 880s int [1:272] 1888 1893 1894 1895 1896 1897 1901 1903 1907 1908 ... 880s Non-polymorphic loci: 880s int [1:399] 1881 1882 1883 1884 1885 1886 1887 1889 1890 1891 ... 880s Heterozygous SNPs to resample for TCN: 880s int [1:272] 1888 1893 1894 1895 1896 1897 1901 1903 1907 1908 ... 880s Homozygous SNPs to resample for TCN: 880s int(0) 880s Non-polymorphic loci to resample for TCN: 880s int [1:399] 1881 1882 1883 1884 1885 1886 1887 1889 1890 1891 ... 880s Heterozygous SNPs with non-DH to resample for TCN: 880s int(0) 880s Loci to resample for TCN: 880s int [1:671] 1881 1882 1883 1884 1885 1886 1887 1888 1889 1890 ... 880s Identify loci used to bootstrap TCN means...done 880s Number of (#hets, #homs, #nonSNPs): (272,0,399) 880s Bootstrapping while preserving (#hets, #homs, #nonSNPs)... 880s Number of bootstrap samples: 100 880s Bootstrapping while preserving (#hets, #homs, #nonSNPs)...done 880s Segment #2 (chr 1, tcnId=2, dhId=1) of 7...done 880s Segment #3 (chr 1, tcnId=3, dhId=1) of 7... 880s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 880s 3 1 3 1 185240536 246679946 1111 2.654512 414 880s tcnNbrOfHets dhNbrOfLoci dhStart dhEnd dhMean c1Mean c2Mean 880s 3 414 414 185240536 246679946 0.269742 0.9692395 1.685273 880s Number of TCNs: 1111 880s Number of DHs: 414 880s int [1:1111] 2552 2553 2554 2555 2556 2557 2558 2559 2560 2561 ... 880s int [1:7324] 1 2 3 4 5 6 7 8 9 10 ... 880s int [1:1111] 2552 2553 2554 2555 2556 2557 2558 2559 2560 2561 ... 880s Identify loci used to bootstrap DH means... 880s Heterozygous SNPs to resample for DH: 880s int [1:414] 2553 2554 2561 2562 2563 2568 2569 2572 2573 2574 ... 880s Identify loci used to bootstrap DH means...done 880s Identify loci used to bootstrap TCN means... 880s SNPs: 880s int [1:414] 2553 2554 2561 2562 2563 2568 2569 2572 2573 2574 ... 880s Non-polymorphic loci: 880s int [1:697] 2552 2555 2556 2557 2558 2559 2560 2564 2565 2566 ... 880s Heterozygous SNPs to resample for TCN: 880s int [1:414] 2553 2554 2561 2562 2563 2568 2569 2572 2573 2574 ... 880s Homozygous SNPs to resample for TCN: 880s int(0) 880s Non-polymorphic loci to resample for TCN: 880s int [1:697] 2552 2555 2556 2557 2558 2559 2560 2564 2565 2566 ... 880s Heterozygous SNPs with non-DH to resample for TCN: 880s int(0) 880s Loci to resample for TCN: 880s int [1:1111] 2552 2553 2554 2555 2556 2557 2558 2559 2560 2561 ... 880s Identify loci used to bootstrap TCN means...done 880s Number of (#hets, #homs, #nonSNPs): (414,0,697) 880s Bootstrapping while preserving (#hets, #homs, #nonSNPs)... 880s Number of bootstrap samples: 100 880s Bootstrapping while preserving (#hets, #homs, #nonSNPs)...done 880s Segment #3 (chr 1, tcnId=3, dhId=1) of 7...done 880s Segment #5 (chr 2, tcnId=1, dhId=1) of 7... 880s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 880s 5 2 1 1 554484 143663981 1880 1.391608 765 880s tcnNbrOfHets dhNbrOfLoci dhStart dhEnd dhMean c1Mean c2Mean 880s 5 765 765 554484 143663981 0.4206323 0.4031263 0.9884817 880s Number of TCNs: 1880 880s Number of DHs: 765 880s int [1:1880] 3663 3664 3665 3666 3667 3668 3669 3670 3671 3672 ... 880s int [1:7324] 1 2 3 4 5 6 7 8 9 10 ... 880s int [1:1880] 3663 3664 3665 3666 3667 3668 3669 3670 3671 3672 ... 880s Identify loci used to bootstrap DH means... 880s Heterozygous SNPs to resample for DH: 880s int [1:765] 3664 3665 3666 3667 3668 3670 3671 3672 3673 3674 ... 880s Identify loci used to bootstrap DH means...done 880s Identify loci used to bootstrap TCN means... 880s SNPs: 880s int [1:765] 3664 3665 3666 3667 3668 3670 3671 3672 3673 3674 ... 880s Non-polymorphic loci: 880s int [1:1115] 3663 3669 3677 3690 3692 3694 3696 3697 3698 3699 ... 880s Heterozygous SNPs to resample for TCN: 880s int [1:765] 3664 3665 3666 3667 3668 3670 3671 3672 3673 3674 ... 880s Homozygous SNPs to resample for TCN: 880s int(0) 880s Non-polymorphic loci to resample for TCN: 880s int [1:1115] 3663 3669 3677 3690 3692 3694 3696 3697 3698 3699 ... 880s Heterozygous SNPs with non-DH to resample for TCN: 880s int(0) 880s Loci to resample for TCN: 880s int [1:1880] 3663 3664 3665 3666 3667 3668 3669 3670 3671 3672 ... 880s Identify loci used to bootstrap TCN means...done 880s Number of (#hets, #homs, #nonSNPs): (765,0,1115) 880s Bootstrapping while preserving (#hets, #homs, #nonSNPs)... 880s Number of bootstrap samples: 100 880s Bootstrapping while preserving (#hets, #homs, #nonSNPs)...done 880s Segment #5 (chr 2, tcnId=1, dhId=1) of 7...done 880s Segment #6 (chr 2, tcnId=2, dhId=1) of 7... 880s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 880s 6 2 2 1 143663981 185240536 671 2.092452 272 880s tcnNbrOfHets dhNbrOfLoci dhStart dhEnd dhMean c1Mean c2Mean 880s 6 272 272 143663981 185240536 0.1762428 0.861836 1.230616 880s Number of TCNs: 671 880s Number of DHs: 272 880s int [1:671] 5543 5544 5545 5546 5547 5548 5549 5550 5551 5552 ... 880s int [1:7324] 1 2 3 4 5 6 7 8 9 10 ... 880s int [1:671] 5543 5544 5545 5546 5547 5548 5549 5550 5551 5552 ... 880s Identify loci used to bootstrap DH means... 880s Heterozygous SNPs to resample for DH: 880s int [1:272] 5550 5555 5556 5557 5558 5559 5563 5565 5569 5570 ... 880s Identify loci used to bootstrap DH means...done 880s Identify loci used to bootstrap TCN means... 880s SNPs: 880s int [1:272] 5550 5555 5556 5557 5558 5559 5563 5565 5569 5570 ... 880s Non-polymorphic loci: 880s int [1:399] 5543 5544 5545 5546 5547 5548 5549 5551 5552 5553 ... 880s Heterozygous SNPs to resample for TCN: 880s int [1:272] 5550 5555 5556 5557 5558 5559 5563 5565 5569 5570 ... 880s Homozygous SNPs to resample for TCN: 880s int(0) 880s Non-polymorphic loci to resample for TCN: 880s int [1:399] 5543 5544 5545 5546 5547 5548 5549 5551 5552 5553 ... 880s Heterozygous SNPs with non-DH to resample for TCN: 880s int(0) 880s Loci to resample for TCN: 880s int [1:671] 5543 5544 5545 5546 5547 5548 5549 5550 5551 5552 ... 880s Identify loci used to bootstrap TCN means...done 880s Number of (#hets, #homs, #nonSNPs): (272,0,399) 880s Bootstrapping while preserving (#hets, #homs, #nonSNPs)... 880s Number of bootstrap samples: 100 880s Bootstrapping while preserving (#hets, #homs, #nonSNPs)...done 880s Segment #6 (chr 2, tcnId=2, dhId=1) of 7...done 880s Segment #7 (chr 2, tcnId=3, dhId=1) of 7... 880s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 880s 7 2 3 1 185240536 246679946 1111 2.654512 414 880s tcnNbrOfHets dhNbrOfLoci dhStart dhEnd dhMean c1Mean c2Mean 880s 7 414 414 185240536 246679946 0.269742 0.9692395 1.685273 880s Number of TCNs: 1111 880s Number of DHs: 414 880s int [1:1111] 6214 6215 6216 6217 6218 6219 6220 6221 6222 6223 ... 880s int [1:7324] 1 2 3 4 5 6 7 8 9 10 ... 880s int [1:1111] 6214 6215 6216 6217 6218 6219 6220 6221 6222 6223 ... 880s Identify loci used to bootstrap DH means... 880s Heterozygous SNPs to resample for DH: 880s int [1:414] 6215 6216 6223 6224 6225 6230 6231 6234 6235 6236 ... 880s Identify loci used to bootstrap DH means...done 880s Identify loci used to bootstrap TCN means... 880s SNPs: 880s int [1:414] 6215 6216 6223 6224 6225 6230 6231 6234 6235 6236 ... 880s Non-polymorphic loci: 880s int [1:697] 6214 6217 6218 6219 6220 6221 6222 6226 6227 6228 ... 880s Heterozygous SNPs to resample for TCN: 880s int [1:414] 6215 6216 6223 6224 6225 6230 6231 6234 6235 6236 ... 880s Homozygous SNPs to resample for TCN: 880s int(0) 880s Non-polymorphic loci to resample for TCN: 880s int [1:697] 6214 6217 6218 6219 6220 6221 6222 6226 6227 6228 ... 880s Heterozygous SNPs with non-DH to resample for TCN: 880s int(0) 880s Loci to resample for TCN: 880s int [1:1111] 6214 6215 6216 6217 6218 6219 6220 6221 6222 6223 ... 880s Identify loci used to bootstrap TCN means...done 880s Number of (#hets, #homs, #nonSNPs): (414,0,697) 880s Bootstrapping while preserving (#hets, #homs, #nonSNPs)... 880s Number of bootstrap samples: 100 880s Bootstrapping while preserving (#hets, #homs, #nonSNPs)...done 880s Segment #7 (chr 2, tcnId=3, dhId=1) of 7...done 880s Bootstrapped segment mean levels 880s num [1:7, 1:100, 1:4] 1.4 2.09 2.64 NA 1.39 ... 880s - attr(*, "dimnames")=List of 3 880s ..$ : NULL 880s ..$ : NULL 880s ..$ : chr [1:4] "tcn" "dh" "c1" "c2" 880s Calculating (C1,C2) mean levels from (TCN,DH) mean levels... 880s num [1:7, 1:100, 1:4] 1.4 2.09 2.64 NA 1.39 ... 880s - attr(*, "dimnames")=List of 3 880s ..$ : NULL 880s ..$ : NULL 880s ..$ : chr [1:4] "tcn" "dh" "c1" "c2" 880s Calculating (C1,C2) mean levels from (TCN,DH) mean levels...done 880s Calculating polar (alpha,radius,manhattan) for change points... 880s num [1:6, 1:100, 1:2] -0.448 -0.131 NA NA -0.477 ... 880s - attr(*, "dimnames")=List of 3 880s ..$ : NULL 880s ..$ : NULL 880s ..$ : chr [1:2] "c1" "c2" 880s Bootstrapped change points 880s num [1:6, 1:100, 1:5] -2.65 -1.87 NA NA -2.72 ... 880s - attr(*, "dimnames")=List of 3 880s ..$ : NULL 880s ..$ : NULL 880s ..$ : chr [1:5] "alpha" "radius" "manhattan" "d1" ... 880s Calculating polar (alpha,radius,manhattan) for change points...done 880s Bootstrapping (TCN,DH,C1,C2) segment mean levels...done 880s Summarizing bootstrapped segment (‘tcn’, ‘dh’, ‘c1’, ‘c2’) data... 880s num [1:7, 1:4, 1:4] NA NA NA NA NA NA NA NA NA NA ... 880s - attr(*, "dimnames")=List of 3 880s ..$ : NULL 880s ..$ : chr [1:4] "2.5%" "5%" "95%" "97.5%" 880s ..$ : chr [1:4] "tcn" "dh" "c1" "c2" 880s Field #1 ('tcn') of 4... 880s Segment #1 of 7... 880s Segment #1 of 7...done 880s Segment #2 of 7... 880s Segment #2 of 7...done 880s Segment #3 of 7... 880s Segment #3 of 7...done 880s Segment #4 of 7... 880s Segment #4 of 7...done 880s Segment #5 of 7... 880s Segment #5 of 7...done 880s Segment #6 of 7... 880s Segment #6 of 7...done 880s Segment #7 of 7... 880s Segment #7 of 7...done 880s Field #1 ('tcn') of 4...done 880s Field #2 ('dh') of 4... 880s Segment #1 of 7... 880s Segment #1 of 7...done 880s Segment #2 of 7... 880s Segment #2 of 7...done 880s Segment #3 of 7... 880s Segment #3 of 7...done 880s Segment #4 of 7... 880s Segment #4 of 7...done 880s Segment #5 of 7... 880s Segment #5 of 7...done 880s Segment #6 of 7... 880s Segment #6 of 7...done 880s Segment #7 of 7... 880s Segment #7 of 7...done 880s Field #2 ('dh') of 4...done 880s Field #3 ('c1') of 4... 880s Segment #1 of 7... 880s Segment #1 of 7...done 880s Segment #2 of 7... 880s Segment #2 of 7...done 880s Segment #3 of 7... 880s Segment #3 of 7...done 880s Segment #4 of 7... 880s Segment #4 of 7...done 880s Segment #5 of 7... 880s Segment #5 of 7...done 880s Segment #6 of 7... 880s Segment #6 of 7...done 880s Segment #7 of 7... 880s Segment #7 of 7...done 880s Field #3 ('c1') of 4...done 880s Field #4 ('c2') of 4... 880s Segment #1 of 7... 880s Segment #1 of 7...done 880s Segment #2 of 7... 880s Segment #2 of 7...done 880s Segment #3 of 7... 880s Segment #3 of 7...done 880s Segment #4 of 7... 880s Segment #4 of 7...done 880s Segment #5 of 7... 880s Segment #5 of 7...done 880s Segment #6 of 7... 880s Segment #6 of 7...done 880s Segment #7 of 7... 880s Segment #7 of 7...done 880s Field #4 ('c2') of 4...done 880s Bootstrap statistics 880s num [1:7, 1:4, 1:4] 1.38 2.07 2.63 NA 1.38 ... 880s - attr(*, "dimnames")=List of 3 880s ..$ : NULL 880s ..$ : chr [1:4] "2.5%" "5%" "95%" "97.5%" 880s ..$ : chr [1:4] "tcn" "dh" "c1" "c2" 880s Statistical sanity checks (iff B >= 100)... 880s Available summaries: 2.5%, 5%, 95%, 97.5% 880s Available quantiles: 0.025, 0.05, 0.95, 0.975 880s num [1:7, 1:4, 1:4] 1.38 2.07 2.63 NA 1.38 ... 880s - attr(*, "dimnames")=List of 3 880s ..$ : NULL 880s ..$ : chr [1:4] "2.5%" "5%" "95%" "97.5%" 880s ..$ : chr [1:4] "tcn" "dh" "c1" "c2" 880s Field #1 ('tcn') of 4... 880s Seg 1. mean=1.39161, range=[1.38025,1.40693], n=1880 880s Seg 2. mean=2.09245, range=[2.06856,2.1165], n=671 880s Seg 3. mean=2.65451, range=[2.62678,2.6834], n=1111 880s Seg 4. mean=NA, range=[NA,NA], n=NA 880s Seg 5. mean=1.39161, range=[1.37999,1.40474], n=1880 880s Seg 6. mean=2.09245, range=[2.06923,2.11747], n=671 880s Seg 7. mean=2.65451, range=[2.62867,2.68639], n=1111 880s Field #1 ('tcn') of 4...done 880s Field #2 ('dh') of 4... 880s Seg 1. mean=0.420632, range=[0.406983,0.437756], n=765 880s Seg 2. mean=0.176243, range=[0.141232,0.202975], n=272 880s Seg 3. mean=0.269742, range=[0.245337,0.292784], n=414 880s Seg 4. mean=NA, range=[NA,NA], n=NA 880s Seg 5. mean=0.420632, range=[0.406204,0.436189], n=765 880s Seg 6. mean=0.176243, range=[0.13696,0.212132], n=272 880s Seg 7. mean=0.269742, range=[0.230034,0.296763], n=414 880s Field #2 ('dh') of 4...done 880s Field #3 ('c1') of 4... 880s Seg 1. mean=0.403126, range=[0.391189,0.413437], n=765 880s Seg 2. mean=0.861836, range=[0.833296,0.900874], n=272 880s Seg 3. mean=0.969239, range=[0.937437,1.00659], n=414 880s Seg 4. mean=NA, range=[NA,NA], n=NA 880s Seg 5. mean=0.403126, range=[0.392112,0.414529], n=765 880s Seg 6. mean=0.861836, range=[0.823193,0.907577], n=272 880s Seg 7. mean=0.969239, range=[0.931951,1.01968], n=414 880s Field #3 ('c1') of 4...done 880s Field #4 ('c2') of 4... 880s Seg 1. mean=0.988482, range=[0.974501,1.00244], n=765 880s Seg 2. mean=1.23062, range=[1.18964,1.26157], n=272 880s Seg 3. mean=1.68527, range=[1.6481,1.72497], n=414 880s Seg 4. mean=NA, range=[NA,NA], n=NA 880s Seg 5. mean=0.988482, range=[0.9761,1.00076], n=765 880s Seg 6. mean=1.23062, range=[1.18936,1.26647], n=272 880s Seg 7. mean=1.68527, range=[1.63171,1.72526], n=414 880s Field #4 ('c2') of 4...done 880s Statistical sanity checks (iff B >= 100)...done 880s Summarizing bootstrapped segment (‘tcn’, ‘dh’, ‘c1’, ‘c2’) data...done 880s Summarizing bootstrapped changepoint (‘alpha’, ‘radius’, ‘manhattan’, ‘d1’, ‘d2’) data... 880s num [1:6, 1:4, 1:5] NA NA NA NA NA NA NA NA NA NA ... 880s - attr(*, "dimnames")=List of 3 880s ..$ : NULL 880s ..$ : chr [1:4] "2.5%" "5%" "95%" "97.5%" 880s ..$ : chr [1:5] "alpha" "radius" "manhattan" "d1" ... 880s Field #1 ('alpha') of 5... 880s Changepoint #1 of 6... 880s Changepoint #1 of 6...done 880s Changepoint #2 of 6... 880s Changepoint #2 of 6...done 880s Changepoint #3 of 6... 880s Changepoint #3 of 6...done 880s Changepoint #4 of 6... 880s Changepoint #4 of 6...done 880s Changepoint #5 of 6... 880s Changepoint #5 of 6...done 880s Changepoint #6 of 6... 880s Changepoint #6 of 6...done 880s Field #1 ('alpha') of 5...done 880s Field #2 ('radius') of 5... 880s Changepoint #1 of 6... 880s Changepoint #1 of 6...done 880s Changepoint #2 of 6... 880s Changepoint #2 of 6...done 880s Changepoint #3 of 6... 881s Changepoint #3 of 6...done 881s Changepoint #4 of 6... 881s Changepoint #4 of 6...done 881s Changepoint #5 of 6... 881s Changepoint #5 of 6...done 881s Changepoint #6 of 6... 881s Changepoint #6 of 6...done 881s Field #2 ('radius') of 5...done 881s Field #3 ('manhattan') of 5... 881s Changepoint #1 of 6... 881s Changepoint #1 of 6...done 881s Changepoint #2 of 6... 881s Changepoint #2 of 6...done 881s Changepoint #3 of 6... 881s Changepoint #3 of 6...done 881s Changepoint #4 of 6... 881s Changepoint #4 of 6...done 881s Changepoint #5 of 6... 881s Changepoint #5 of 6...done 881s Changepoint #6 of 6... 881s Changepoint #6 of 6...done 881s Field #3 ('manhattan') of 5...done 881s Field #4 ('d1') of 5... 881s Changepoint #1 of 6... 881s Changepoint #1 of 6...done 881s Changepoint #2 of 6... 881s Changepoint #2 of 6...done 881s Changepoint #3 of 6... 881s Changepoint #3 of 6...done 881s Changepoint #4 of 6... 881s Changepoint #4 of 6...done 881s Changepoint #5 of 6... 881s Changepoint #5 of 6...done 881s Changepoint #6 of 6... 881s Changepoint #6 of 6...done 881s Field #4 ('d1') of 5...done 881s Field #5 ('d2') of 5... 881s Changepoint #1 of 6... 881s Changepoint #1 of 6...done 881s Changepoint #2 of 6... 881s Changepoint #2 of 6...done 881s Changepoint #3 of 6... 881s Changepoint #3 of 6...done 881s Changepoint #4 of 6... 881s Changepoint #4 of 6...done 881s Changepoint #5 of 6... 881s Changepoint #5 of 6...done 881s Changepoint #6 of 6... 881s Changepoint #6 of 6...done 881s Field #5 ('d2') of 5...done 881s Bootstrap statistics 881s num [1:6, 1:4, 1:5] -2.76 -1.91 NA NA -2.76 ... 881s - attr(*, "dimnames")=List of 3 881s ..$ : NULL 881s ..$ : chr [1:4] "2.5%" "5%" "95%" "97.5%" 881s ..$ : chr [1:5] "alpha" "radius" "manhattan" "d1" ... 881s Summarizing bootstrapped changepoint (‘alpha’, ‘radius’, ‘manhattan’, ‘d1’, ‘d2’) data...done 881s Resample (TCN,DH) signals and re-estimate summaries for segment & changepoint...done 881s > print(fit) 881s chromosome tcnId dhId start end tcnNbrOfLoci tcnMean tcnNbrOfSNPs 881s 1 1 1 1 554484 143663981 1880 1.391608 765 881s 2 1 2 1 143663981 185240536 671 2.092452 272 881s 3 1 3 1 185240536 246679946 1111 2.654512 414 881s 4 NA NA NA NA NA NA NA NA 881s 5 2 1 1 554484 143663981 1880 1.391608 765 881s 6 2 2 1 143663981 185240536 671 2.092452 272 881s 7 2 3 1 185240536 246679946 1111 2.654512 414 881s tcnNbrOfHets dhNbrOfLoci dhMean c1Mean c2Mean 881s 1 765 765 0.4206323 0.4031263 0.9884817 881s 2 272 272 0.1762428 0.8618360 1.2306156 881s 3 414 414 0.2697420 0.9692395 1.6852728 881s 4 NA NA NA NA NA 881s 5 765 765 0.4206323 0.4031263 0.9884817 881s 6 272 272 0.1762428 0.8618360 1.2306156 881s 7 414 414 0.2697420 0.9692395 1.6852728 881s > 881s > 881s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 881s > # Calling segments in allelic balance (AB) 881s > # NOTE: Ideally, this should be done on whole-genome data 881s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 881s > # Explicitly estimate the threshold in DH for calling AB 881s > # (which be done by default by the caller, if skipped here) 881s > deltaAB <- estimateDeltaAB(fit, flavor="qq(DH)", verbose=-10) 881s Estimating DH threshold for calling allelic imbalances... 881s flavor: qq(DH) 881s scale: 1 881s Estimating DH threshold for AB caller... 881s quantile #1: 0.05 881s Symmetric quantile #2: 0.9 881s Number of segments: 6 881s Weighted 5% quantile of DH: 0.199618 881s Number of segments with small DH: 2 881s Number of data points: 1342 881s Number of finite data points: 544 881s Estimate of (1-0.9):th and 50% quantiles: (0.0289919,0.176243) 881s Estimate of 0.9:th "symmetric" quantile: 0.323494 881s Estimating DH threshold for AB caller...done 881s Estimated delta: 0.323 881s Estimating DH threshold for calling allelic imbalances...done 881s > print(deltaAB) 881s [1] 0.3234938 881s > 881s > fit <- callAB(fit, delta=deltaAB, verbose=-10) 881s Calling segments of allelic balance from one-sided DH bootstrap confidence intervals... 881s delta (offset adjusting for bias in DH): 0.323493772175137 881s alpha (CI quantile; significance level): 0.05 881s Calling segments... 881s Number of segments called allelic balance (AB): 4 (57.14%) of 7 881s Calling segments...done 881s Calling segments of allelic balance from one-sided DH bootstrap confidence intervals...done 881s > print(fit) 881s chromosome tcnId dhId start end tcnNbrOfLoci tcnMean tcnNbrOfSNPs 881s 1 1 1 1 554484 143663981 1880 1.391608 765 881s 2 1 2 1 143663981 185240536 671 2.092452 272 881s 3 1 3 1 185240536 246679946 1111 2.654512 414 881s 4 NA NA NA NA NA NA NA NA 881s 5 2 1 1 554484 143663981 1880 1.391608 765 881s 6 2 2 1 143663981 185240536 671 2.092452 272 881s 7 2 3 1 185240536 246679946 1111 2.654512 414 881s tcnNbrOfHets dhNbrOfLoci dhMean c1Mean c2Mean abCall 881s 1 765 765 0.4206323 0.4031263 0.9884817 FALSE 881s 2 272 272 0.1762428 0.8618360 1.2306156 TRUE 881s 3 414 414 0.2697420 0.9692395 1.6852728 TRUE 881s 4 NA NA NA NA NA NA 881s 5 765 765 0.4206323 0.4031263 0.9884817 FALSE 881s 6 272 272 0.1762428 0.8618360 1.2306156 TRUE 881s 7 414 414 0.2697420 0.9692395 1.6852728 TRUE 881s > 881s > 881s > # Even if not explicitly specified, the estimated 881s > # threshold parameter is returned by the caller 881s > stopifnot(fit$params$deltaAB == deltaAB) 881s > 881s > 881s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 881s > # Calling segments in loss-of-heterozygosity (LOH) 881s > # NOTE: Ideally, this should be done on whole-genome data 881s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 881s > # Explicitly estimate the threshold in C1 for calling LOH 881s > # (which be done by default by the caller, if skipped here) 881s > deltaLOH <- estimateDeltaLOH(fit, flavor="minC1|nonAB", verbose=-10) 881s Estimating DH threshold for calling LOH... 881s flavor: minC1|nonAB 881s Estimating DH threshold for calling LOH as the midpoint between guessed C1=0 and C1=1... 881s Argument 'midpoint': 0.5 881s Number of segments: 6 881s Number of segments in allelic balance: 4 (66.7%) of 6 881s Number of segments not in allelic balance: 2 (33.3%) of 6 881s Number of segments in allelic balance and TCN <= 3.00: 4 (66.7%) of 6 881s C: 2.09, 2.65, 2.09, 2.65 881s Corrected C1 (=C/2): 1.05, 1.33, 1.05, 1.33 881s Number of DHs: 272, 414, 272, 414 881s Weights: 0.198, 0.302, 0.198, 0.302 881s Weighted median of (corrected) C1 in allelic balance: 1.274 881s Smallest C1 among segments not in allelic balance: 0.403 881s There are 2 segments with in total 765 heterozygous SNPs with this level. 881s There are 2 segments with in total 765 heterozygous SNPs with this level. 881s Midpoint between the two: 0.839 881s Estimating DH threshold for calling LOH as the midpoint between guessed C1=0 and C1=1...done 881s delta: 0.839 881s Estimating DH threshold for calling LOH...done 881s > print(deltaLOH) 881s [1] 0.838563 881s > 881s > fit <- callLOH(fit, delta=deltaLOH, verbose=-10) 881s Calling segments of allelic balance from one-sided DH bootstrap confidence intervals... 881s delta (offset adjusting for bias in C1): 0.838562992888546 881s alpha (CI quantile; significance level): 0.05 881s Calling segments... 881s Number of segments called low C1 (LowC1, "LOH_C1"): 3 (42.86%) of 7 881s Calling segments...done 881s Calling segments of allelic balance from one-sided DH bootstrap confidence intervals...done 881s > print(fit) 881s chromosome tcnId dhId start end tcnNbrOfLoci tcnMean tcnNbrOfSNPs 881s 1 1 1 1 554484 143663981 1880 1.391608 765 881s 2 1 2 1 143663981 185240536 671 2.092452 272 881s 3 1 3 1 185240536 246679946 1111 2.654512 414 881s 4 NA NA NA NA NA NA NA NA 881s 5 2 1 1 554484 143663981 1880 1.391608 765 881s 6 2 2 1 143663981 185240536 671 2.092452 272 881s 7 2 3 1 185240536 246679946 1111 2.654512 414 881s tcnNbrOfHets dhNbrOfLoci dhMean c1Mean c2Mean abCall lohCall 881s 1 765 765 0.4206323 0.4031263 0.9884817 FALSE TRUE 881s 2 272 272 0.1762428 0.8618360 1.2306156 TRUE NA 881s 3 414 414 0.2697420 0.9692395 1.6852728 TRUE FALSE 881s 4 NA NA NA NA NA NA NA 881s 5 765 765 0.4206323 0.4031263 0.9884817 FALSE TRUE 881s 6 272 272 0.1762428 0.8618360 1.2306156 TRUE FALSE 881s 7 414 414 0.2697420 0.9692395 1.6852728 TRUE FALSE 881s > plotTracks(fit) 881s > 881s > # Even if not explicitly specified, the estimated 881s > # threshold parameter is returned by the caller 881s > stopifnot(fit$params$deltaLOH == deltaLOH) 881s > 881s Start: segmentByPairedPSCBS,DH.R 881s 881s R version 4.5.2 (2025-10-31) -- "[Not] Part in a Rumble" 881s Copyright (C) 2025 The R Foundation for Statistical Computing 881s Platform: aarch64-unknown-linux-gnu 881s 881s R is free software and comes with ABSOLUTELY NO WARRANTY. 881s You are welcome to redistribute it under certain conditions. 881s Type 'license()' or 'licence()' for distribution details. 881s 881s R is a collaborative project with many contributors. 881s Type 'contributors()' for more information and 881s 'citation()' on how to cite R or R packages in publications. 881s 881s Type 'demo()' for some demos, 'help()' for on-line help, or 881s 'help.start()' for an HTML browser interface to help. 881s Type 'q()' to quit R. 881s 881s > library("PSCBS") 881s PSCBS v0.68.0 (2025-04-18 19:40:02 UTC) successfully loaded. See ?PSCBS for help. 881s > 881s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 881s > # Load SNP microarray data 881s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 881s > data <- PSCBS::exampleData("paired.chr01") 881s > str(data) 881s 'data.frame': 73346 obs. of 6 variables: 881s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 881s $ x : int 1145994 2224111 2319424 2543484 2926730 2941694 3084986 3155127 3292731 3695086 ... 881s $ CT : num 1.625 1.071 1.406 1.18 0.856 ... 881s $ betaT : num 0.757 0.771 0.834 0.778 0.229 ... 881s $ CN : num 2.36 2.13 2.59 1.93 1.71 ... 881s $ betaN : num 0.827 0.875 0.887 0.884 0.103 ... 881s > 881s > # Drop single-locus outliers 881s > dataS <- dropSegmentationOutliers(data) 881s > 881s > # Run light-weight tests 881s > # Use only every 5th data point 881s > dataS <- dataS[seq(from=1, to=nrow(data), by=5),] 881s > # Number of segments (for assertion) 881s > nSegs <- 3L 881s > # Number of bootstrap samples (see below) 881s > B <- 100L 881s > 881s > str(dataS) 881s 'data.frame': 14670 obs. of 6 variables: 881s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 881s $ x : int 1145994 2941694 3710825 4240737 4276892 4464544 4714611 5095111 5034491 5158416 ... 881s $ CT : num 1.63 1.4 1.41 1.17 1.16 ... 881s $ betaT : num 0.7574 0.169 0.2357 0.2604 0.0576 ... 881s $ CN : num 2.36 2.13 2.26 2.01 2.32 ... 881s $ betaN : num 0.8274 0.5072 0.1671 0.1609 0.0421 ... 881s > R.oo::attachLocally(dataS) 881s > 881s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 881s > # Calculate DH 881s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 881s > muN <- aroma.light::callNaiveGenotypes(betaN, censorAt=c(0,1)) 881s > # SNPs are identifies as those loci that have non-missing 'betaT' & 'muN' 881s > isSnp <- (!is.na(betaT) & !is.na(muN)) 881s > isHet <- isSnp & (muN == 1/2) 881s > rho <- rep(NA_real_, length=length(muN)) 881s > rho[isHet] <- 2*abs(betaT[isHet]-1/2) 881s > 881s > 881s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 881s > # Paired PSCBS segmentation using TCN and DH only 881s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 881s > fit <- segmentByPairedPSCBS(CT, rho=rho, 881s + chromosome=chromosome, x=x, 881s + seed=0xBEEF, verbose=-10) 881s Segmenting paired tumor-normal signals using Paired PSCBS... 881s Setup up data... 881s 'data.frame': 14670 obs. of 4 variables: 881s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 881s $ x : num 1145994 2941694 3710825 4240737 4276892 ... 881s $ CT : num 1.63 1.4 1.41 1.17 1.16 ... 881s $ rho : num NA 0.662 NA NA NA ... 881s Setup up data...done 881s Dropping loci for which TCNs are missing... 881s Number of loci dropped: 12 881s Dropping loci for which TCNs are missing...done 881s Ordering data along genome... 881s 'data.frame': 14658 obs. of 4 variables: 881s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 881s $ x : num 554484 730720 782343 878522 916294 ... 881s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 881s $ rho : num NA NA NA NA NA ... 881s Ordering data along genome...done 881s Keeping only current chromosome for 'knownSegments'... 881s Chromosome: 1 881s Known segments for this chromosome: 881s [1] chromosome start end 881s <0 rows> (or 0-length row.names) 881s Keeping only current chromosome for 'knownSegments'...done 881s alphaTCN: 0.009 881s alphaDH: 0.001 881s Number of loci: 14658 881s Random seed temporarily set (seed=c(48879), kind="L'Ecuyer-CMRG") 881s Produced 2 seeds from this stream for future usage 881s Identification of change points by total copy numbers... 881s Segmenting by CBS... 881s Chromosome: 1 881s Random seed temporarily set (seed=c(10407, 1066287653, -51199871, 161854402, -1995183193, 1503453565, -747102133), kind="L'Ecuyer-CMRG") 882s Segmenting by CBS...done 882s List of 4 882s $ data :'data.frame': 14658 obs. of 4 variables: 882s ..$ chromosome: int [1:14658] 1 1 1 1 1 1 1 1 1 1 ... 882s ..$ x : num [1:14658] 554484 730720 782343 878522 916294 ... 882s ..$ y : num [1:14658] 1.88 1.8 1.59 1.64 1.53 ... 882s ..$ index : int [1:14658] 1 2 3 4 5 6 7 8 9 10 ... 882s $ output :'data.frame': 3 obs. of 6 variables: 882s ..$ sampleName: chr [1:3] NA NA NA 882s ..$ chromosome: int [1:3] 1 1 1 882s ..$ start : num [1:3] 5.54e+05 1.44e+08 1.85e+08 882s ..$ end : num [1:3] 1.44e+08 1.85e+08 2.47e+08 882s ..$ nbrOfLoci : int [1:3] 7599 2668 4391 882s ..$ mean : num [1:3] 1.39 2.07 2.63 882s $ segRows:'data.frame': 3 obs. of 2 variables: 882s ..$ startRow: int [1:3] 1 7600 10268 882s ..$ endRow : int [1:3] 7599 10267 14658 882s $ params :List of 5 882s ..$ alpha : num 0.009 882s ..$ undo : num 0 882s ..$ joinSegments : logi TRUE 882s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 882s .. ..$ chromosome: int 1 882s .. ..$ start : num -Inf 882s .. ..$ end : num Inf 882s ..$ seed : int [1:7] 10407 1066287653 -51199871 161854402 -1995183193 1503453565 -747102133 882s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 882s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.379 0 0.38 0 0 882s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 882s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 882s - attr(*, "randomSeed")= int [1:7] 10407 1066287653 -51199871 161854402 -1995183193 1503453565 -747102133 882s Identification of change points by total copy numbers...done 882s Restructure TCN segmentation results... 882s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean 882s 1 1 554484 143926517 7599 1.3859 882s 2 1 143926517 185449813 2668 2.0704 882s 3 1 185449813 247137334 4391 2.6341 882s Number of TCN segments: 3 882s Restructure TCN segmentation results...done 882s Total CN segment #1 ([ 554484,1.43927e+08]) of 3... 882s Number of TCN loci in segment: 7599 882s Locus data for TCN segment: 882s 'data.frame': 7599 obs. of 5 variables: 882s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 882s $ x : num 554484 730720 782343 878522 916294 ... 882s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 882s $ rho : num NA NA NA NA NA ... 882s $ index : int 1 2 3 4 5 6 7 8 9 10 ... 882s Number of loci: 7599 882s Number of SNPs: 2111 (27.78%) 882s Number of heterozygous SNPs: 2111 (100.00%) 882s Chromosome: 1 882s Segmenting DH signals... 882s Segmenting by CBS... 882s Chromosome: 1 882s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 882s Segmenting by CBS...done 882s List of 4 882s $ data :'data.frame': 7599 obs. of 4 variables: 882s ..$ chromosome: int [1:7599] 1 1 1 1 1 1 1 1 1 1 ... 882s ..$ x : num [1:7599] 554484 730720 782343 878522 916294 ... 882s ..$ y : num [1:7599] NA NA NA NA NA ... 882s ..$ index : int [1:7599] 1 2 3 4 5 6 7 8 9 10 ... 882s $ output :'data.frame': 1 obs. of 6 variables: 882s ..$ sampleName: chr NA 882s ..$ chromosome: int 1 882s ..$ start : num 554484 882s ..$ end : num 1.44e+08 882s ..$ nbrOfLoci : int 2111 882s ..$ mean : num 0.524 882s $ segRows:'data.frame': 1 obs. of 2 variables: 882s ..$ startRow: int 10 882s ..$ endRow : int 7594 882s $ params :List of 5 882s ..$ alpha : num 0.001 882s ..$ undo : num 0 882s ..$ joinSegments : logi TRUE 882s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 882s .. ..$ chromosome: int 1 882s .. ..$ start : num 554484 882s .. ..$ end : num 1.44e+08 882s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 882s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 882s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.026 0 0.026 0 0 882s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 882s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 882s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 882s DH segmentation (locally-indexed) rows: 882s startRow endRow 882s 1 10 7594 882s int [1:7599] 1 2 3 4 5 6 7 8 9 10 ... 882s DH segmentation rows: 882s startRow endRow 882s 1 10 7594 882s Segmenting DH signals...done 882s DH segmentation table: 882s dhStart dhEnd dhNbrOfLoci dhMean 882s 1 554484 143926517 2111 0.5237 882s startRow endRow 882s 1 10 7594 882s Rows: 882s [1] 1 882s TCN segmentation rows: 882s startRow endRow 882s 1 1 7599 882s TCN and DH segmentation rows: 882s startRow endRow 882s 1 1 7599 882s startRow endRow 882s 1 10 7594 882s NULL 882s TCN segmentation (expanded) rows: 882s startRow endRow 882s 1 1 7599 882s TCN and DH segmentation rows: 882s startRow endRow 882s 1 1 7599 882s 2 7600 10267 882s 3 10268 14658 882s startRow endRow 882s 1 10 7594 882s startRow endRow 882s 1 1 7599 882s Total CN segmentation table (expanded): 882s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 882s 1 1 554484 143926517 7599 1.3859 2111 2111 882s (TCN,DH) segmentation for one total CN segment: 882s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 882s 1 1 1 1 554484 143926517 7599 1.3859 2111 882s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 882s 1 2111 554484 143926517 2111 0.5237 882s Total CN segment #1 ([ 554484,1.43927e+08]) of 3...done 882s Total CN segment #2 ([1.43927e+08,1.8545e+08]) of 3... 882s Number of TCN loci in segment: 2668 882s Locus data for TCN segment: 882s 'data.frame': 2668 obs. of 5 variables: 882s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 882s $ x : num 1.44e+08 1.44e+08 1.44e+08 1.44e+08 1.44e+08 ... 882s $ CT : num 2.1 2.1 2.09 1.8 2.34 ... 882s $ rho : num NA NA NA NA NA NA NA NA NA NA ... 882s $ index : int 7600 7601 7602 7603 7604 7605 7606 7607 7608 7609 ... 882s Number of loci: 2668 882s Number of SNPs: 774 (29.01%) 882s Number of heterozygous SNPs: 774 (100.00%) 882s Chromosome: 1 882s Segmenting DH signals... 882s Segmenting by CBS... 882s Chromosome: 1 882s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 882s Segmenting by CBS...done 882s List of 4 882s $ data :'data.frame': 2668 obs. of 4 variables: 882s ..$ chromosome: int [1:2668] 1 1 1 1 1 1 1 1 1 1 ... 882s ..$ x : num [1:2668] 1.44e+08 1.44e+08 1.44e+08 1.44e+08 1.44e+08 ... 882s ..$ y : num [1:2668] NA NA NA NA NA NA NA NA NA NA ... 882s ..$ index : int [1:2668] 1 2 3 4 5 6 7 8 9 10 ... 882s $ output :'data.frame': 1 obs. of 6 variables: 882s ..$ sampleName: chr NA 882s ..$ chromosome: int 1 882s ..$ start : num 1.44e+08 882s ..$ end : num 1.85e+08 882s ..$ nbrOfLoci : int 774 882s ..$ mean : num 0.154 882s $ segRows:'data.frame': 1 obs. of 2 variables: 882s ..$ startRow: int 15 882s ..$ endRow : int 2664 882s $ params :List of 5 882s ..$ alpha : num 0.001 882s ..$ undo : num 0 882s ..$ joinSegments : logi TRUE 882s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 882s .. ..$ chromosome: int 1 882s .. ..$ start : num 1.44e+08 882s .. ..$ end : num 1.85e+08 882s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 882s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 882s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.009 0 0.009 0 0 882s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 882s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 882s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 882s DH segmentation (locally-indexed) rows: 882s startRow endRow 882s 1 15 2664 882s int [1:2668] 7600 7601 7602 7603 7604 7605 7606 7607 7608 7609 ... 882s DH segmentation rows: 882s startRow endRow 882s 1 7614 10263 882s Segmenting DH signals...done 882s DH segmentation table: 882s dhStart dhEnd dhNbrOfLoci dhMean 882s 1 143926517 185449813 774 0.1542 882s startRow endRow 882s 1 7614 10263 882s Rows: 882s [1] 2 882s TCN segmentation rows: 882s startRow endRow 882s 2 7600 10267 882s TCN and DH segmentation rows: 882s startRow endRow 882s 2 7600 10267 882s startRow endRow 882s 1 7614 10263 882s startRow endRow 882s 1 1 7599 882s TCN segmentation (expanded) rows: 882s startRow endRow 882s 1 1 7599 882s 2 7600 10267 882s TCN and DH segmentation rows: 882s startRow endRow 882s 1 1 7599 882s 2 7600 10267 882s 3 10268 14658 882s startRow endRow 882s 1 10 7594 882s 2 7614 10263 882s startRow endRow 882s 1 1 7599 882s 2 7600 10267 882s Total CN segmentation table (expanded): 882s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 882s 2 1 143926517 185449813 2668 2.0704 774 774 882s (TCN,DH) segmentation for one total CN segment: 882s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 882s 2 2 1 1 143926517 185449813 2668 2.0704 774 882s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 882s 2 774 143926517 185449813 774 0.1542 882s Total CN segment #2 ([1.43927e+08,1.8545e+08]) of 3...done 882s Total CN segment #3 ([1.8545e+08,2.47137e+08]) of 3... 882s Number of TCN loci in segment: 4391 882s Locus data for TCN segment: 882s 'data.frame': 4391 obs. of 5 variables: 882s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 882s $ x : num 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 882s $ CT : num 2.93 2.15 2.82 2.93 2.46 ... 882s $ rho : num NA 0.0308 NA 0.2533 NA ... 882s $ index : int 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 882s Number of loci: 4391 882s Number of SNPs: 1311 (29.86%) 882s Number of heterozygous SNPs: 1311 (100.00%) 882s Chromosome: 1 882s Segmenting DH signals... 882s Segmenting by CBS... 882s Chromosome: 1 882s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 882s Segmenting by CBS...done 882s List of 4 882s $ data :'data.frame': 4391 obs. of 4 variables: 882s ..$ chromosome: int [1:4391] 1 1 1 1 1 1 1 1 1 1 ... 882s ..$ x : num [1:4391] 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 882s ..$ y : num [1:4391] NA 0.0308 NA 0.2533 NA ... 882s ..$ index : int [1:4391] 1 2 3 4 5 6 7 8 9 10 ... 882s $ output :'data.frame': 1 obs. of 6 variables: 882s ..$ sampleName: chr NA 882s ..$ chromosome: int 1 882s ..$ start : num 1.85e+08 882s ..$ end : num 2.47e+08 882s ..$ nbrOfLoci : int 1311 882s ..$ mean : num 0.251 882s $ segRows:'data.frame': 1 obs. of 2 variables: 882s ..$ startRow: int 2 882s ..$ endRow : int 4388 882s $ params :List of 5 882s ..$ alpha : num 0.001 882s ..$ undo : num 0 882s ..$ joinSegments : logi TRUE 882s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 882s .. ..$ chromosome: int 1 882s .. ..$ start : num 1.85e+08 882s .. ..$ end : num 2.47e+08 882s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 882s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 882s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.027 0 0.027 0 0 882s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 882s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 882s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 882s DH segmentation (locally-indexed) rows: 882s startRow endRow 882s 1 2 4388 882s int [1:4391] 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 882s DH segmentation rows: 882s startRow endRow 882s 1 10269 14655 882s Segmenting DH signals...done 882s DH segmentation table: 882s dhStart dhEnd dhNbrOfLoci dhMean 882s 1 185449813 247137334 1311 0.2512 882s startRow endRow 882s 1 10269 14655 882s Rows: 882s [1] 3 882s TCN segmentation rows: 882s startRow endRow 882s 3 10268 14658 882s TCN and DH segmentation rows: 882s startRow endRow 882s 3 10268 14658 882s startRow endRow 882s 1 10269 14655 882s startRow endRow 882s 1 1 7599 882s 2 7600 10267 882s TCN segmentation (expanded) rows: 882s startRow endRow 882s 1 1 7599 882s 2 7600 10267 882s 3 10268 14658 882s TCN and DH segmentation rows: 882s startRow endRow 882s 1 1 7599 882s 2 7600 10267 882s 3 10268 14658 882s startRow endRow 882s 1 10 7594 882s 2 7614 10263 882s 3 10269 14655 882s startRow endRow 882s 1 1 7599 882s 2 7600 10267 882s 3 10268 14658 882s Total CN segmentation table (expanded): 882s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 882s 3 1 185449813 247137334 4391 2.6341 1311 1311 882s (TCN,DH) segmentation for one total CN segment: 882s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 882s 3 3 1 1 185449813 247137334 4391 2.6341 1311 882s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 882s 3 1311 185449813 247137334 1311 0.2512 882s Total CN segment #3 ([1.8545e+08,2.47137e+08]) of 3...done 882s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 882s 1 1 1 1 554484 143926517 7599 1.3859 2111 882s 2 1 2 1 143926517 185449813 2668 2.0704 774 882s 3 1 3 1 185449813 247137334 4391 2.6341 1311 882s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 882s 1 2111 554484 143926517 2111 0.5237 882s 2 774 143926517 185449813 774 0.1542 882s 3 1311 185449813 247137334 1311 0.2512 882s Calculating (C1,C2) per segment... 882s Calculating (C1,C2) per segment...done 882s Number of segments: 3 882s Segmenting paired tumor-normal signals using Paired PSCBS...done 882s Post-segmenting TCNs... 882s Number of segments: 3 882s Number of chromosomes: 1 882s [1] 1 882s Chromosome 1 ('chr01') of 1... 882s Rows: 882s [1] 1 2 3 882s Number of segments: 3 882s TCN segment #1 ('1') of 3... 882s Nothing todo. Only one DH segmentation. Skipping. 882s TCN segment #1 ('1') of 3...done 882s TCN segment #2 ('2') of 3... 882s Nothing todo. Only one DH segmentation. Skipping. 882s TCN segment #2 ('2') of 3...done 882s TCN segment #3 ('3') of 3... 882s Nothing todo. Only one DH segmentation. Skipping. 882s TCN segment #3 ('3') of 3...done 882s Chromosome 1 ('chr01') of 1...done 882s Update (C1,C2) per segment... 882s Update (C1,C2) per segment...done 882s Post-segmenting TCNs...done 882s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 882s 1 1 1 1 554484 143926517 7599 1.3859 2111 882s 2 1 2 1 143926517 185449813 2668 2.0704 774 882s 3 1 3 1 185449813 247137334 4391 2.6341 1311 882s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 882s 1 2111 554484 143926517 2111 0.5237 0.3300521 1.055848 882s 2 774 143926517 185449813 774 0.1542 0.8755722 1.194828 882s 3 1311 185449813 247137334 1311 0.2512 0.9862070 1.647893 882s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 882s 1 1 1 1 554484 143926517 7599 1.3859 2111 882s 2 1 2 1 143926517 185449813 2668 2.0704 774 882s 3 1 3 1 185449813 247137334 4391 2.6341 1311 882s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 882s 1 2111 554484 143926517 2111 0.5237 0.3300521 1.055848 882s 2 774 143926517 185449813 774 0.1542 0.8755722 1.194828 882s 3 1311 185449813 247137334 1311 0.2512 0.9862070 1.647893 882s > print(fit) 882s chromosome tcnId dhId start end tcnNbrOfLoci tcnMean tcnNbrOfSNPs 882s 1 1 1 1 554484 143926517 7599 1.3859 2111 882s 2 1 2 1 143926517 185449813 2668 2.0704 774 882s 3 1 3 1 185449813 247137334 4391 2.6341 1311 882s tcnNbrOfHets dhNbrOfLoci dhMean c1Mean c2Mean 882s 1 2111 2111 0.5237 0.3300521 1.055848 882s 2 774 774 0.1542 0.8755722 1.194828 882s 3 1311 1311 0.2512 0.9862070 1.647893 882s > 882s > # Plot results 882s > plotTracks(fit) 882s > 882s > 882s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 882s > # Bootstrap segment level estimates 882s > # (used by the AB caller, which, if skipped here, 882s > # will do it automatically) 882s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 882s > fit <- bootstrapTCNandDHByRegion(fit, B=B, verbose=-10) 882s Resample (TCN,DH) signals and re-estimate summaries for segment & changepoint... 882s Already done? 882s tcn_2.5% tcn_5% tcn_95% tcn_97.5% dh_2.5% dh_5% dh_95% dh_97.5% 882s FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE 882s c1_2.5% c1_5% c1_95% c1_97.5% c2_2.5% c2_5% c2_95% c2_97.5% 882s FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE 882s Bootstrapping (TCN,DH,C1,C2) segment mean levels... 882s Identifying heterozygous & homozygous SNPs and non-polymorphic loci... 882s Number of loci: 14658 882s Number of SNPs: 4196 882s Number of non-SNPs: 10462 882s Identifying heterozygous & homozygous SNPs and non-polymorphic loci...done 882s num [1:3, 1:100, 1:4] NA NA NA NA NA NA NA NA NA NA ... 882s - attr(*, "dimnames")=List of 3 882s ..$ : NULL 882s ..$ : NULL 882s ..$ : chr [1:4] "tcn" "dh" "c1" "c2" 882s Segment #1 (chr 1, tcnId=1, dhId=1) of 3... 882s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 882s 1 1 1 1 554484 143926517 7599 1.3859 2111 882s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 882s 1 2111 554484 143926517 2111 0.5237 0.3300521 1.055848 882s Number of TCNs: 7599 882s Number of DHs: 2111 883s int [1:7599] 1 2 3 4 5 6 7 8 9 10 ... 883s int [1:14658] 1 2 3 4 5 6 7 8 9 10 ... 883s int [1:7599] 1 2 3 4 5 6 7 8 9 10 ... 883s Identify loci used to bootstrap DH means... 883s Heterozygous SNPs to resample for DH: 883s int [1:2111] 10 12 24 28 31 33 34 39 46 48 ... 883s Identify loci used to bootstrap DH means...done 883s Identify loci used to bootstrap TCN means... 883s SNPs: 883s int [1:2111] 10 12 24 28 31 33 34 39 46 48 ... 883s Non-polymorphic loci: 883s int [1:5488] 1 2 3 4 5 6 7 8 9 11 ... 883s Heterozygous SNPs to resample for TCN: 883s int [1:2111] 10 12 24 28 31 33 34 39 46 48 ... 883s Homozygous SNPs to resample for TCN: 883s int(0) 883s Non-polymorphic loci to resample for TCN: 883s int [1:5488] 1 2 3 4 5 6 7 8 9 11 ... 883s Heterozygous SNPs with non-DH to resample for TCN: 883s int(0) 883s Loci to resample for TCN: 883s int [1:7599] 1 2 3 4 5 6 7 8 9 10 ... 883s Identify loci used to bootstrap TCN means...done 883s Number of (#hets, #homs, #nonSNPs): (2111,0,5488) 883s Bootstrapping while preserving (#hets, #homs, #nonSNPs)... 883s Number of bootstrap samples: 100 883s Bootstrapping while preserving (#hets, #homs, #nonSNPs)...done 883s Segment #1 (chr 1, tcnId=1, dhId=1) of 3...done 883s Segment #2 (chr 1, tcnId=2, dhId=1) of 3... 883s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 883s 2 1 2 1 143926517 185449813 2668 2.0704 774 883s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 883s 2 774 143926517 185449813 774 0.1542 0.8755722 1.194828 883s Number of TCNs: 2668 883s Number of DHs: 774 883s int [1:2668] 7600 7601 7602 7603 7604 7605 7606 7607 7608 7609 ... 883s int [1:14658] 1 2 3 4 5 6 7 8 9 10 ... 883s int [1:2668] 7600 7601 7602 7603 7604 7605 7606 7607 7608 7609 ... 883s Identify loci used to bootstrap DH means... 883s Heterozygous SNPs to resample for DH: 883s int [1:774] 7614 7616 7626 7627 7628 7635 7638 7639 7640 7642 ... 883s Identify loci used to bootstrap DH means...done 883s Identify loci used to bootstrap TCN means... 883s SNPs: 883s int [1:774] 7614 7616 7626 7627 7628 7635 7638 7639 7640 7642 ... 883s Non-polymorphic loci: 883s int [1:1894] 7600 7601 7602 7603 7604 7605 7606 7607 7608 7609 ... 883s Heterozygous SNPs to resample for TCN: 883s int [1:774] 7614 7616 7626 7627 7628 7635 7638 7639 7640 7642 ... 883s Homozygous SNPs to resample for TCN: 883s int(0) 883s Non-polymorphic loci to resample for TCN: 883s int [1:1894] 7600 7601 7602 7603 7604 7605 7606 7607 7608 7609 ... 883s Heterozygous SNPs with non-DH to resample for TCN: 883s int(0) 883s Loci to resample for TCN: 883s int [1:2668] 7600 7601 7602 7603 7604 7605 7606 7607 7608 7609 ... 883s Identify loci used to bootstrap TCN means...done 883s Number of (#hets, #homs, #nonSNPs): (774,0,1894) 883s Bootstrapping while preserving (#hets, #homs, #nonSNPs)... 883s Number of bootstrap samples: 100 883s Bootstrapping while preserving (#hets, #homs, #nonSNPs)...done 883s Segment #2 (chr 1, tcnId=2, dhId=1) of 3...done 883s Segment #3 (chr 1, tcnId=3, dhId=1) of 3... 883s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 883s 3 1 3 1 185449813 247137334 4391 2.6341 1311 883s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 883s 3 1311 185449813 247137334 1311 0.2512 0.986207 1.647893 883s Number of TCNs: 4391 883s Number of DHs: 1311 883s int [1:4391] 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 883s int [1:14658] 1 2 3 4 5 6 7 8 9 10 ... 883s int [1:4391] 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 883s Identify loci used to bootstrap DH means... 883s Heterozygous SNPs to resample for DH: 883s int [1:1311] 10269 10271 10281 10282 10283 10293 10295 10297 10300 10302 ... 883s Identify loci used to bootstrap DH means...done 883s Identify loci used to bootstrap TCN means... 883s SNPs: 883s int [1:1311] 10269 10271 10281 10282 10283 10293 10295 10297 10300 10302 ... 883s Non-polymorphic loci: 883s int [1:3080] 10268 10270 10272 10273 10274 10275 10276 10277 10278 10279 ... 883s Heterozygous SNPs to resample for TCN: 883s int [1:1311] 10269 10271 10281 10282 10283 10293 10295 10297 10300 10302 ... 883s Homozygous SNPs to resample for TCN: 883s int(0) 883s Non-polymorphic loci to resample for TCN: 883s int [1:3080] 10268 10270 10272 10273 10274 10275 10276 10277 10278 10279 ... 883s Heterozygous SNPs with non-DH to resample for TCN: 883s int(0) 883s Loci to resample for TCN: 883s int [1:4391] 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 883s Identify loci used to bootstrap TCN means...done 883s Number of (#hets, #homs, #nonSNPs): (1311,0,3080) 883s Bootstrapping while preserving (#hets, #homs, #nonSNPs)... 883s Number of bootstrap samples: 100 883s Bootstrapping while preserving (#hets, #homs, #nonSNPs)...done 883s Segment #3 (chr 1, tcnId=3, dhId=1) of 3...done 883s Bootstrapped segment mean levels 883s num [1:3, 1:100, 1:4] 1.38 2.08 2.63 1.38 2.07 ... 883s - attr(*, "dimnames")=List of 3 883s ..$ : NULL 883s ..$ : NULL 883s ..$ : chr [1:4] "tcn" "dh" "c1" "c2" 883s Calculating (C1,C2) mean levels from (TCN,DH) mean levels... 883s num [1:3, 1:100, 1:4] 1.38 2.08 2.63 1.38 2.07 ... 883s - attr(*, "dimnames")=List of 3 883s ..$ : NULL 883s ..$ : NULL 883s ..$ : chr [1:4] "tcn" "dh" "c1" "c2" 883s Calculating (C1,C2) mean levels from (TCN,DH) mean levels...done 883s Calculating polar (alpha,radius,manhattan) for change points... 883s num [1:2, 1:100, 1:2] -0.5588 -0.0962 -0.5365 -0.1285 -0.5378 ... 883s - attr(*, "dimnames")=List of 3 883s ..$ : NULL 883s ..$ : NULL 883s ..$ : chr [1:2] "c1" "c2" 883s Bootstrapped change points 883s num [1:2, 1:100, 1:5] -2.89 -1.78 -2.87 -1.86 -2.88 ... 883s - attr(*, "dimnames")=List of 3 883s ..$ : NULL 883s ..$ : NULL 883s ..$ : chr [1:5] "alpha" "radius" "manhattan" "d1" ... 883s Calculating polar (alpha,radius,manhattan) for change points...done 883s Bootstrapping (TCN,DH,C1,C2) segment mean levels...done 883s Summarizing bootstrapped segment (‘tcn’, ‘dh’, ‘c1’, ‘c2’) data... 883s num [1:3, 1:4, 1:4] NA NA NA NA NA NA NA NA NA NA ... 883s - attr(*, "dimnames")=List of 3 883s ..$ : NULL 883s ..$ : chr [1:4] "2.5%" "5%" "95%" "97.5%" 883s ..$ : chr [1:4] "tcn" "dh" "c1" "c2" 883s Field #1 ('tcn') of 4... 883s Segment #1 of 3... 883s Segment #1 of 3...done 883s Segment #2 of 3... 883s Segment #2 of 3...done 883s Segment #3 of 3... 883s Segment #3 of 3...done 883s Field #1 ('tcn') of 4...done 883s Field #2 ('dh') of 4... 883s Segment #1 of 3... 883s Segment #1 of 3...done 883s Segment #2 of 3... 883s Segment #2 of 3...done 883s Segment #3 of 3... 883s Segment #3 of 3...done 883s Field #2 ('dh') of 4...done 883s Field #3 ('c1') of 4... 883s Segment #1 of 3... 883s Segment #1 of 3...done 883s Segment #2 of 3... 883s Segment #2 of 3...done 883s Segment #3 of 3... 883s Segment #3 of 3...done 883s Field #3 ('c1') of 4...done 883s Field #4 ('c2') of 4... 883s Segment #1 of 3... 883s Segment #1 of 3...done 883s Segment #2 of 3... 883s Segment #2 of 3...done 883s Segment #3 of 3... 883s Segment #3 of 3...done 883s Field #4 ('c2') of 4...done 883s Bootstrap statistics 883s num [1:3, 1:4, 1:4] 1.38 2.06 2.62 1.38 2.06 ... 883s - attr(*, "dimnames")=List of 3 883s ..$ : NULL 883s ..$ : chr [1:4] "2.5%" "5%" "95%" "97.5%" 883s ..$ : chr [1:4] "tcn" "dh" "c1" "c2" 883s Statistical sanity checks (iff B >= 100)... 883s Available summaries: 2.5%, 5%, 95%, 97.5% 883s Available quantiles: 0.025, 0.05, 0.95, 0.975 883s num [1:3, 1:4, 1:4] 1.38 2.06 2.62 1.38 2.06 ... 883s - attr(*, "dimnames")=List of 3 883s ..$ : NULL 883s ..$ : chr [1:4] "2.5%" "5%" "95%" "97.5%" 883s ..$ : chr [1:4] "tcn" "dh" "c1" "c2" 883s Field #1 ('tcn') of 4... 883s Seg 1. mean=1.3859, range=[1.38092,1.3949], n=7599 883s Seg 2. mean=2.0704, range=[2.05747,2.08326], n=2668 883s Seg 3. mean=2.6341, range=[2.62068,2.64694], n=4391 883s Field #1 ('tcn') of 4...done 883s Field #2 ('dh') of 4... 883s Seg 1. mean=0.5237, range=[0.51753,0.532002], n=2111 883s Seg 2. mean=0.1542, range=[0.144468,0.16453], n=774 883s Seg 3. mean=0.2512, range=[0.242575,0.258832], n=1311 883s Field #2 ('dh') of 4...done 883s Field #3 ('c1') of 4... 883s Seg 1. mean=0.330052, range=[0.323996,0.336038], n=2111 883s Seg 2. mean=0.875572, range=[0.86318,0.887699], n=774 883s Seg 3. mean=0.986207, range=[0.975123,0.998982], n=1311 883s Field #3 ('c1') of 4...done 883s Field #4 ('c2') of 4... 883s Seg 1. mean=1.05585, range=[1.05006,1.06231], n=2111 883s Seg 2. mean=1.19483, range=[1.18417,1.2081], n=774 883s Seg 3. mean=1.64789, range=[1.63403,1.66098], n=1311 883s Field #4 ('c2') of 4...done 883s Statistical sanity checks (iff B >= 100)...done 883s Summarizing bootstrapped segment (‘tcn’, ‘dh’, ‘c1’, ‘c2’) data...done 883s Summarizing bootstrapped changepoint (‘alpha’, ‘radius’, ‘manhattan’, ‘d1’, ‘d2’) data... 883s num [1:2, 1:4, 1:5] NA NA NA NA NA NA NA NA NA NA ... 883s - attr(*, "dimnames")=List of 3 883s ..$ : NULL 883s ..$ : chr [1:4] "2.5%" "5%" "95%" "97.5%" 883s ..$ : chr [1:5] "alpha" "radius" "manhattan" "d1" ... 883s Field #1 ('alpha') of 5... 883s Changepoint #1 of 2... 883s Changepoint #1 of 2...done 883s Changepoint #2 of 2... 883s Changepoint #2 of 2...done 883s Field #1 ('alpha') of 5...done 883s Field #2 ('radius') of 5... 883s Changepoint #1 of 2... 883s Changepoint #1 of 2...done 883s Changepoint #2 of 2... 883s Changepoint #2 of 2...done 883s Field #2 ('radius') of 5...done 883s Field #3 ('manhattan') of 5... 883s Changepoint #1 of 2... 883s Changepoint #1 of 2...done 883s Changepoint #2 of 2... 883s Changepoint #2 of 2...done 883s Field #3 ('manhattan') of 5...done 883s Field #4 ('d1') of 5... 883s Changepoint #1 of 2... 883s Changepoint #1 of 2...done 883s Changepoint #2 of 2... 883s Changepoint #2 of 2...done 883s Field #4 ('d1') of 5...done 883s Field #5 ('d2') of 5... 883s Changepoint #1 of 2... 883s Changepoint #1 of 2...done 883s Changepoint #2 of 2... 883s Changepoint #2 of 2...done 883s Field #5 ('d2') of 5...done 883s Bootstrap statistics 883s num [1:2, 1:4, 1:5] -2.92 -1.86 -2.91 -1.85 -2.87 ... 883s - attr(*, "dimnames")=List of 3 883s ..$ : NULL 883s ..$ : chr [1:4] "2.5%" "5%" "95%" "97.5%" 883s ..$ : chr [1:5] "alpha" "radius" "manhattan" "d1" ... 883s Summarizing bootstrapped changepoint (‘alpha’, ‘radius’, ‘manhattan’, ‘d1’, ‘d2’) data...done 883s Resample (TCN,DH) signals and re-estimate summaries for segment & changepoint...done 883s > print(fit) 883s chromosome tcnId dhId start end tcnNbrOfLoci tcnMean tcnNbrOfSNPs 883s 1 1 1 1 554484 143926517 7599 1.3859 2111 883s 2 1 2 1 143926517 185449813 2668 2.0704 774 883s 3 1 3 1 185449813 247137334 4391 2.6341 1311 883s tcnNbrOfHets dhNbrOfLoci dhMean c1Mean c2Mean 883s 1 2111 2111 0.5237 0.3300521 1.055848 883s 2 774 774 0.1542 0.8755722 1.194828 883s 3 1311 1311 0.2512 0.9862070 1.647893 883s > plotTracks(fit) 883s > 883s > 883s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 883s > # Calling segments in allelic balance (AB) and 883s > # in loss-of-heterozygosity (LOH) 883s > # NOTE: Ideally, this should be done on whole-genome data 883s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 883s > fit <- callAB(fit, verbose=-10) 883s Calling segments of allelic balance from one-sided DH bootstrap confidence intervals... 883s delta (offset adjusting for bias in DH): 0.3466649145302 883s alpha (CI quantile; significance level): 0.05 883s Calling segments... 883s Number of segments called allelic balance (AB): 2 (66.67%) of 3 883s Calling segments...done 883s Calling segments of allelic balance from one-sided DH bootstrap confidence intervals...done 883s > fit <- callLOH(fit, verbose=-10) 883s Calling segments of allelic balance from one-sided DH bootstrap confidence intervals... 883s delta (offset adjusting for bias in C1): 0.771236438183453 883s alpha (CI quantile; significance level): 0.05 883s Calling segments... 883s Number of segments called low C1 (LowC1, "LOH_C1"): 1 (33.33%) of 3 883s Calling segments...done 883s Calling segments of allelic balance from one-sided DH bootstrap confidence intervals...done 883s > print(fit) 883s chromosome tcnId dhId start end tcnNbrOfLoci tcnMean tcnNbrOfSNPs 883s 1 1 1 1 554484 143926517 7599 1.3859 2111 883s 2 1 2 1 143926517 185449813 2668 2.0704 774 883s 3 1 3 1 185449813 247137334 4391 2.6341 1311 883s tcnNbrOfHets dhNbrOfLoci dhMean c1Mean c2Mean abCall lohCall 883s 1 2111 2111 0.5237 0.3300521 1.055848 FALSE TRUE 883s 2 774 774 0.1542 0.8755722 1.194828 TRUE FALSE 883s 3 1311 1311 0.2512 0.9862070 1.647893 TRUE FALSE 883s > plotTracks(fit) 883s > 883s Start: segmentByPairedPSCBS,calls.R 883s 883s R version 4.5.2 (2025-10-31) -- "[Not] Part in a Rumble" 883s Copyright (C) 2025 The R Foundation for Statistical Computing 883s Platform: aarch64-unknown-linux-gnu 883s 883s R is free software and comes with ABSOLUTELY NO WARRANTY. 883s You are welcome to redistribute it under certain conditions. 883s Type 'license()' or 'licence()' for distribution details. 883s 883s R is a collaborative project with many contributors. 883s Type 'contributors()' for more information and 883s 'citation()' on how to cite R or R packages in publications. 883s 883s Type 'demo()' for some demos, 'help()' for on-line help, or 883s 'help.start()' for an HTML browser interface to help. 883s Type 'q()' to quit R. 883s 884s > library("PSCBS") 884s PSCBS v0.68.0 (2025-04-18 19:40:02 UTC) successfully loaded. See ?PSCBS for help. 884s > 884s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 884s > # Load SNP microarray data 884s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 884s > data <- PSCBS::exampleData("paired.chr01") 884s > str(data) 884s 'data.frame': 73346 obs. of 6 variables: 884s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 884s $ x : int 1145994 2224111 2319424 2543484 2926730 2941694 3084986 3155127 3292731 3695086 ... 884s $ CT : num 1.625 1.071 1.406 1.18 0.856 ... 884s $ betaT : num 0.757 0.771 0.834 0.778 0.229 ... 884s $ CN : num 2.36 2.13 2.59 1.93 1.71 ... 884s $ betaN : num 0.827 0.875 0.887 0.884 0.103 ... 884s > 884s > 884s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 884s > # Paired PSCBS segmentation 884s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 884s > # Drop single-locus outliers 884s > dataS <- dropSegmentationOutliers(data) 884s > 884s > # Find centromere 884s > gaps <- findLargeGaps(dataS, minLength=2e6) 884s > knownSegments <- gapsToSegments(gaps) 884s > 884s > 884s > # Run light-weight tests by default 884s > if (Sys.getenv("_R_CHECK_FULL_") == "") { 884s + # Use only every 5th data point 884s + dataS <- dataS[seq(from=1, to=nrow(data), by=5),] 884s + # Number of segments (for assertion) 884s + nSegs <- 4L 884s + # Number of bootstrap samples (see below) 884s + B <- 100L 884s + } else { 884s + # Full tests 884s + nSegs <- 11L 884s + B <- 1000L 884s + } 884s > 884s > str(dataS) 884s 'data.frame': 14670 obs. of 6 variables: 884s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 884s $ x : int 1145994 2941694 3710825 4240737 4276892 4464544 4714611 5095111 5034491 5158416 ... 884s $ CT : num 1.63 1.4 1.41 1.17 1.16 ... 884s $ betaT : num 0.7574 0.169 0.2357 0.2604 0.0576 ... 884s $ CN : num 2.36 2.13 2.26 2.01 2.32 ... 884s $ betaN : num 0.8274 0.5072 0.1671 0.1609 0.0421 ... 884s > 884s > # Paired PSCBS segmentation 884s > fit <- segmentByPairedPSCBS(dataS, knownSegments=knownSegments, 884s + seed=0xBEEF, verbose=-10) 884s Segmenting paired tumor-normal signals using Paired PSCBS... 884s Calling genotypes from normal allele B fractions... 884s num [1:14670] 0.8274 0.5072 0.1671 0.1609 0.0421 ... 884s Called genotypes: 884s num [1:14670] 1 0.5 0 0 0 0 1 0 1 0.5 ... 884s - attr(*, "modelFit")=List of 1 884s ..$ :List of 7 884s .. ..$ flavor : chr "density" 884s .. ..$ cn : int 2 884s .. ..$ nbrOfGenotypeGroups: int 3 884s .. ..$ tau : num [1:2] 0.315 0.677 884s .. ..$ n : int 14640 884s .. ..$ fit :Classes ‘PeaksAndValleys’ and 'data.frame': 5 obs. of 3 variables: 884s .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 884s .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 884s .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 884s .. ..$ fitValleys :Classes ‘PeaksAndValleys’ and 'data.frame': 2 obs. of 3 variables: 884s .. .. ..$ type : chr [1:2] "valley" "valley" 884s .. .. ..$ x : num [1:2] 0.315 0.677 884s .. .. ..$ density: num [1:2] 0.522 0.551 884s ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 884s muN 884s 0 0.5 1 884s 5221 4198 5251 884s Calling genotypes from normal allele B fractions...done 884s Normalizing betaT using betaN (TumorBoost)... 884s Normalized BAFs: 884s num [1:14670] 0.9301 0.1667 0.0685 0.0995 0.0155 ... 884s - attr(*, "modelFit")=List of 5 884s ..$ method : chr "normalizeTumorBoost" 884s ..$ flavor : chr "v4" 884s ..$ delta : num [1:14670] -0.17264 0.00239 0.1671 0.16085 0.04213 ... 884s .. ..- attr(*, "modelFit")=List of 1 884s .. .. ..$ :List of 7 884s .. .. .. ..$ flavor : chr "density" 884s .. .. .. ..$ cn : int 2 884s .. .. .. ..$ nbrOfGenotypeGroups: int 3 884s .. .. .. ..$ tau : num [1:2] 0.315 0.677 884s .. .. .. ..$ n : int 14640 884s .. .. .. ..$ fit :Classes ‘PeaksAndValleys’ and 'data.frame': 5 obs. of 3 variables: 884s .. .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 884s .. .. .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 884s .. .. .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 884s .. .. .. ..$ fitValleys :Classes ‘PeaksAndValleys’ and 'data.frame': 2 obs. of 3 variables: 884s .. .. .. .. ..$ type : chr [1:2] "valley" "valley" 884s .. .. .. .. ..$ x : num [1:2] 0.315 0.677 884s .. .. .. .. ..$ density: num [1:2] 0.522 0.551 884s .. .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 884s ..$ preserveScale: logi FALSE 884s ..$ scaleFactor : num NA 884s Normalizing betaT using betaN (TumorBoost)...done 884s Setup up data... 884s 'data.frame': 14670 obs. of 7 variables: 884s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 884s $ x : num 1145994 2941694 3710825 4240737 4276892 ... 884s $ CT : num 1.63 1.4 1.41 1.17 1.16 ... 884s $ betaT : num 0.7574 0.169 0.2357 0.2604 0.0576 ... 884s $ betaTN : num 0.9301 0.1667 0.0685 0.0995 0.0155 ... 884s ..- attr(*, "modelFit")=List of 5 884s .. ..$ method : chr "normalizeTumorBoost" 884s .. ..$ flavor : chr "v4" 884s .. ..$ delta : num [1:14670] -0.17264 0.00239 0.1671 0.16085 0.04213 ... 884s .. .. ..- attr(*, "modelFit")=List of 1 884s .. .. .. ..$ :List of 7 884s .. .. .. .. ..$ flavor : chr "density" 884s .. .. .. .. ..$ cn : int 2 884s .. .. .. .. ..$ nbrOfGenotypeGroups: int 3 884s .. .. .. .. ..$ tau : num [1:2] 0.315 0.677 884s .. .. .. .. ..$ n : int 14640 884s .. .. .. .. ..$ fit :Classes ‘PeaksAndValleys’ and 'data.frame': 5 obs. of 3 variables: 884s .. .. .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 884s .. .. .. .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 884s .. .. .. .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 884s .. .. .. .. ..$ fitValleys :Classes ‘PeaksAndValleys’ and 'data.frame': 2 obs. of 3 variables: 884s .. .. .. .. .. ..$ type : chr [1:2] "valley" "valley" 884s .. .. .. .. .. ..$ x : num [1:2] 0.315 0.677 884s .. .. .. .. .. ..$ density: num [1:2] 0.522 0.551 884s .. .. .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 884s .. ..$ preserveScale: logi FALSE 884s .. ..$ scaleFactor : num NA 884s $ betaN : num 0.8274 0.5072 0.1671 0.1609 0.0421 ... 884s $ muN : num 1 0.5 0 0 0 0 1 0 1 0.5 ... 884s ..- attr(*, "modelFit")=List of 1 884s .. ..$ :List of 7 884s .. .. ..$ flavor : chr "density" 884s .. .. ..$ cn : int 2 884s .. .. ..$ nbrOfGenotypeGroups: int 3 884s .. .. ..$ tau : num [1:2] 0.315 0.677 884s .. .. ..$ n : int 14640 884s .. .. ..$ fit :Classes ‘PeaksAndValleys’ and 'data.frame': 5 obs. of 3 variables: 884s .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 884s .. .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 884s .. .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 884s .. .. ..$ fitValleys :Classes ‘PeaksAndValleys’ and 'data.frame': 2 obs. of 3 variables: 884s .. .. .. ..$ type : chr [1:2] "valley" "valley" 884s .. .. .. ..$ x : num [1:2] 0.315 0.677 884s .. .. .. ..$ density: num [1:2] 0.522 0.551 884s .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 884s Setup up data...done 884s Dropping loci for which TCNs are missing... 884s Number of loci dropped: 12 884s Dropping loci for which TCNs are missing...done 884s Ordering data along genome... 884s 'data.frame': 14658 obs. of 7 variables: 884s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 884s $ x : num 554484 730720 782343 878522 916294 ... 884s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 884s $ betaT : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 884s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 884s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 884s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 884s Ordering data along genome...done 884s Keeping only current chromosome for 'knownSegments'... 884s Chromosome: 1 884s Known segments for this chromosome: 884s chromosome start end length 884s 1 1 -Inf 120992603 Inf 884s 2 1 120992604 141510002 20517398 884s 3 1 141510003 Inf Inf 884s Keeping only current chromosome for 'knownSegments'...done 884s alphaTCN: 0.009 884s alphaDH: 0.001 884s Number of loci: 14658 884s Calculating DHs... 884s Number of SNPs: 14658 884s Number of heterozygous SNPs: 4196 (28.63%) 884s Normalized DHs: 884s num [1:14658] NA NA NA NA NA ... 884s Calculating DHs...done 884s Random seed temporarily set (seed=c(48879), kind="L'Ecuyer-CMRG") 884s Produced 2 seeds from this stream for future usage 884s Identification of change points by total copy numbers... 884s Segmenting by CBS... 884s Chromosome: 1 884s Segmenting multiple segments on current chromosome... 884s Number of segments: 3 884s Random seed temporarily set (seed=c(10407, 1066287653, -51199871, 161854402, -1995183193, 1503453565, -747102133), kind="L'Ecuyer-CMRG") 884s Produced 3 seeds from this stream for future usage 884s Segmenting by CBS... 884s Chromosome: 1 884s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 885s Segmenting by CBS...done 885s Segmenting by CBS... 885s Chromosome: 1 885s Random seed temporarily set (seed=c(10407, -1924040949, -1632234809, -437763632, -1464377300, 676654412, 2080370711), kind="L'Ecuyer-CMRG") 885s Segmenting by CBS...done 885s Segmenting multiple segments on current chromosome...done 885s Segmenting by CBS...done 885s List of 4 885s $ data :'data.frame': 14658 obs. of 4 variables: 885s ..$ chromosome: int [1:14658] 1 1 1 1 1 1 1 1 1 1 ... 885s ..$ x : num [1:14658] 554484 730720 782343 878522 916294 ... 885s ..$ y : num [1:14658] 1.88 1.8 1.59 1.64 1.53 ... 885s ..$ index : int [1:14658] 1 2 3 4 5 6 7 8 9 10 ... 885s $ output :'data.frame': 4 obs. of 6 variables: 885s ..$ sampleName: chr [1:4] NA NA NA NA 885s ..$ chromosome: int [1:4] 1 1 1 1 885s ..$ start : num [1:4] 5.54e+05 1.21e+08 1.42e+08 1.85e+08 885s ..$ end : num [1:4] 1.21e+08 1.42e+08 1.85e+08 2.47e+08 885s ..$ nbrOfLoci : int [1:4] 7586 0 2681 4391 885s ..$ mean : num [1:4] 1.39 NA 2.07 2.63 885s $ segRows:'data.frame': 4 obs. of 2 variables: 885s ..$ startRow: int [1:4] 1 NA 7587 10268 885s ..$ endRow : int [1:4] 7586 NA 10267 14658 885s $ params :List of 5 885s ..$ alpha : num 0.009 885s ..$ undo : num 0 885s ..$ joinSegments : logi TRUE 885s ..$ knownSegments:'data.frame': 4 obs. of 3 variables: 885s .. ..$ chromosome: int [1:4] 1 1 2 1 885s .. ..$ start : num [1:4] -Inf -Inf -Inf 1.42e+08 885s .. ..$ end : num [1:4] 1.21e+08 Inf Inf Inf 885s ..$ seed : int [1:7] 10407 1066287653 -51199871 161854402 -1995183193 1503453565 -747102133 885s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 885s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.132 0 0.132 0 0 885s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 885s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 885s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 885s Identification of change points by total copy numbers...done 885s Restructure TCN segmentation results... 885s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean 885s 1 1 554484 120992603 7586 1.3853 885s 2 1 120992604 141510002 0 NA 885s 3 1 141510003 185449813 2681 2.0689 885s 4 1 185449813 247137334 4391 2.6341 885s Number of TCN segments: 4 885s Restructure TCN segmentation results...done 885s Total CN segment #1 ([ 554484,1.20993e+08]) of 4... 885s Number of TCN loci in segment: 7586 885s Locus data for TCN segment: 885s 'data.frame': 7586 obs. of 9 variables: 885s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 885s $ x : num 554484 730720 782343 878522 916294 ... 885s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 885s $ betaT : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 885s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 885s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 885s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 885s $ index : int 1 2 3 4 5 6 7 8 9 10 ... 885s $ rho : num NA NA NA NA NA ... 885s Number of loci: 7586 885s Number of SNPs: 2108 (27.79%) 885s Number of heterozygous SNPs: 2108 (100.00%) 885s Chromosome: 1 885s Segmenting DH signals... 885s Segmenting by CBS... 885s Chromosome: 1 885s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 885s Segmenting by CBS...done 885s List of 4 885s $ data :'data.frame': 7586 obs. of 4 variables: 885s ..$ chromosome: int [1:7586] 1 1 1 1 1 1 1 1 1 1 ... 885s ..$ x : num [1:7586] 554484 730720 782343 878522 916294 ... 885s ..$ y : num [1:7586] NA NA NA NA NA ... 885s ..$ index : int [1:7586] 1 2 3 4 5 6 7 8 9 10 ... 885s $ output :'data.frame': 1 obs. of 6 variables: 885s ..$ sampleName: chr NA 885s ..$ chromosome: int 1 885s ..$ start : num 554484 885s ..$ end : num 1.21e+08 885s ..$ nbrOfLoci : int 2108 885s ..$ mean : num 0.512 885s $ segRows:'data.frame': 1 obs. of 2 variables: 885s ..$ startRow: int 10 885s ..$ endRow : int 7574 885s $ params :List of 5 885s ..$ alpha : num 0.001 885s ..$ undo : num 0 885s ..$ joinSegments : logi TRUE 885s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 885s .. ..$ chromosome: int 1 885s .. ..$ start : num 554484 885s .. ..$ end : num 1.21e+08 885s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 885s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 885s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.039 0 0.039 0 0 885s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 885s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 885s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 885s DH segmentation (locally-indexed) rows: 885s startRow endRow 885s 1 10 7574 885s int [1:7586] 1 2 3 4 5 6 7 8 9 10 ... 885s DH segmentation rows: 885s startRow endRow 885s 1 10 7574 885s Segmenting DH signals...done 885s DH segmentation table: 885s dhStart dhEnd dhNbrOfLoci dhMean 885s 1 554484 120992603 2108 0.5116 885s startRow endRow 885s 1 10 7574 885s Rows: 885s [1] 1 885s TCN segmentation rows: 885s startRow endRow 885s 1 1 7586 885s TCN and DH segmentation rows: 885s startRow endRow 885s 1 1 7586 885s startRow endRow 885s 1 10 7574 885s NULL 885s TCN segmentation (expanded) rows: 885s startRow endRow 885s 1 1 7586 885s TCN and DH segmentation rows: 885s startRow endRow 885s 1 1 7586 885s 2 NA NA 885s 3 7587 10267 885s 4 10268 14658 885s startRow endRow 885s 1 10 7574 885s startRow endRow 885s 1 1 7586 885s Total CN segmentation table (expanded): 885s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 885s 1 1 554484 120992603 7586 1.3853 2108 2108 885s (TCN,DH) segmentation for one total CN segment: 885s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 885s 1 1 1 1 554484 120992603 7586 1.3853 2108 885s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 885s 1 2108 554484 120992603 2108 0.5116 885s Total CN segment #1 ([ 554484,1.20993e+08]) of 4...done 885s Total CN segment #2 ([1.20993e+08,1.4151e+08]) of 4... 885s Number of TCN loci in segment: 0 885s Locus data for TCN segment: 885s 'data.frame': 0 obs. of 9 variables: 885s $ chromosome: int 885s $ x : num 885s $ CT : num 885s $ betaT : num 885s $ betaTN : num 885s $ betaN : num 885s $ muN : num 885s $ index : int 885s $ rho : num 885s Number of loci: 0 885s Number of SNPs: 0 (NaN%) 885s Number of heterozygous SNPs: 0 (NaN%) 885s Chromosome: 1 885s Segmenting DH signals... 885s Segmenting by CBS... 885s Chromosome: NA 885s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 885s Segmenting by CBS...done 885s List of 4 885s $ data :'data.frame': 0 obs. of 4 variables: 885s ..$ chromosome: int(0) 885s ..$ x : num(0) 885s ..$ y : num(0) 885s ..$ index : int(0) 885s $ output :'data.frame': 0 obs. of 6 variables: 885s ..$ sampleName: chr(0) 885s ..$ chromosome: num(0) 885s ..$ start : num(0) 885s ..$ end : num(0) 885s ..$ nbrOfLoci : int(0) 885s ..$ mean : num(0) 885s $ segRows:'data.frame': 0 obs. of 2 variables: 885s ..$ startRow: int(0) 885s ..$ endRow : int(0) 885s $ params :List of 5 885s ..$ alpha : num 0.001 885s ..$ undo : num 0 885s ..$ joinSegments : logi TRUE 885s ..$ knownSegments:'data.frame': 0 obs. of 3 variables: 885s .. ..$ chromosome: int(0) 885s .. ..$ start : num(0) 885s .. ..$ end : num(0) 885s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 885s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 885s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.002 0 0.002 0 0 885s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 885s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 885s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 885s DH segmentation (locally-indexed) rows: 885s [1] startRow endRow 885s <0 rows> (or 0-length row.names) 885s int(0) 885s DH segmentation rows: 885s [1] startRow endRow 885s <0 rows> (or 0-length row.names) 885s Segmenting DH signals...done 885s DH segmentation table: 885s dhStart dhEnd dhNbrOfLoci dhMean 885s NA NA NA NA NA 885s startRow endRow 885s NA NA NA 885s Rows: 885s [1] 2 885s TCN segmentation rows: 885s startRow endRow 885s 2 NA NA 885s TCN and DH segmentation rows: 885s startRow endRow 885s 2 NA NA 885s startRow endRow 885s NA NA NA 885s startRow endRow 885s 1 1 7586 885s TCN segmentation (expanded) rows: 885s startRow endRow 885s 1 1 7586 885s 2 NA NA 885s TCN and DH segmentation rows: 885s startRow endRow 885s 1 1 7586 885s 2 NA NA 885s 3 7587 10267 885s 4 10268 14658 885s startRow endRow 885s 1 10 7574 885s 2 NA NA 885s startRow endRow 885s 1 1 7586 885s 2 NA NA 885s Total CN segmentation table (expanded): 885s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 885s 2 1 120992604 141510002 0 NA 0 0 885s (TCN,DH) segmentation for one total CN segment: 885s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 885s 2 2 1 1 120992604 141510002 0 NA 0 885s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 885s 2 0 NA NA NA NA 885s Total CN segment #2 ([1.20993e+08,1.4151e+08]) of 4...done 885s Total CN segment #3 ([1.4151e+08,1.8545e+08]) of 4... 885s Number of TCN loci in segment: 2681 885s Locus data for TCN segment: 885s 'data.frame': 2681 obs. of 9 variables: 885s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 885s $ x : num 1.43e+08 1.43e+08 1.43e+08 1.43e+08 1.44e+08 ... 885s $ CT : num 2.27 1.55 1.47 1.5 1.81 ... 885s $ betaT : num 0.34 0.55 0.048 0.813 0.575 ... 885s $ betaTN : num 0.441 0.629 -0.05 0.958 0.872 ... 885s $ betaN : num 0.3851 0.3933 0.0981 0.8552 0.7028 ... 885s $ muN : num 0.5 0.5 0 1 1 1 1 0.5 1 1 ... 885s $ index : int 7587 7588 7589 7590 7591 7592 7593 7594 7595 7596 ... 885s $ rho : num 0.117 0.258 NA NA NA ... 885s Number of loci: 2681 885s Number of SNPs: 777 (28.98%) 885s Number of heterozygous SNPs: 777 (100.00%) 885s Chromosome: 1 885s Segmenting DH signals... 885s Segmenting by CBS... 885s Chromosome: 1 885s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 885s Segmenting by CBS...done 885s List of 4 885s $ data :'data.frame': 2681 obs. of 4 variables: 885s ..$ chromosome: int [1:2681] 1 1 1 1 1 1 1 1 1 1 ... 885s ..$ x : num [1:2681] 1.43e+08 1.43e+08 1.43e+08 1.43e+08 1.44e+08 ... 885s ..$ y : num [1:2681] 0.117 0.258 NA NA NA ... 885s ..$ index : int [1:2681] 1 2 3 4 5 6 7 8 9 10 ... 885s $ output :'data.frame': 1 obs. of 6 variables: 885s ..$ sampleName: chr NA 885s ..$ chromosome: int 1 885s ..$ start : num 1.42e+08 885s ..$ end : num 1.85e+08 885s ..$ nbrOfLoci : int 777 885s ..$ mean : num 0.0973 885s $ segRows:'data.frame': 1 obs. of 2 variables: 885s ..$ startRow: int 1 885s ..$ endRow : int 2677 885s $ params :List of 5 885s ..$ alpha : num 0.001 885s ..$ undo : num 0 885s ..$ joinSegments : logi TRUE 885s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 885s .. ..$ chromosome: int 1 885s .. ..$ start : num 1.42e+08 885s .. ..$ end : num 1.85e+08 885s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 885s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 885s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.009 0 0.008 0 0 885s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 885s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 885s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 885s DH segmentation (locally-indexed) rows: 885s startRow endRow 885s 1 1 2677 885s int [1:2681] 7587 7588 7589 7590 7591 7592 7593 7594 7595 7596 ... 885s DH segmentation rows: 885s startRow endRow 885s 1 7587 10263 885s Segmenting DH signals...done 885s DH segmentation table: 885s dhStart dhEnd dhNbrOfLoci dhMean 885s 1 141510003 185449813 777 0.0973 885s startRow endRow 885s 1 7587 10263 885s Rows: 885s [1] 3 885s TCN segmentation rows: 885s startRow endRow 885s 3 7587 10267 885s TCN and DH segmentation rows: 885s startRow endRow 885s 3 7587 10267 885s startRow endRow 885s 1 7587 10263 885s startRow endRow 885s 1 1 7586 885s 2 NA NA 885s TCN segmentation (expanded) rows: 885s startRow endRow 885s 1 1 7586 885s 2 NA NA 885s 3 7587 10267 885s TCN and DH segmentation rows: 885s startRow endRow 885s 1 1 7586 885s 2 NA NA 885s 3 7587 10267 885s 4 10268 14658 885s startRow endRow 885s 1 10 7574 885s 2 NA NA 885s 3 7587 10263 885s startRow endRow 885s 1 1 7586 885s 2 NA NA 885s 3 7587 10267 885s Total CN segmentation table (expanded): 885s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 885s 3 1 141510003 185449813 2681 2.0689 777 777 885s (TCN,DH) segmentation for one total CN segment: 885s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 885s 3 3 1 1 141510003 185449813 2681 2.0689 777 885s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 885s 3 777 141510003 185449813 777 0.0973 885s Total CN segment #3 ([1.4151e+08,1.8545e+08]) of 4...done 885s Total CN segment #4 ([1.8545e+08,2.47137e+08]) of 4... 885s Number of TCN loci in segment: 4391 885s Locus data for TCN segment: 885s 'data.frame': 4391 obs. of 9 variables: 885s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 885s $ x : num 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 885s $ CT : num 2.93 2.15 2.82 2.93 2.46 ... 885s $ betaT : num 0.0811 0.5154 0.9473 0.3734 0.7506 ... 885s $ betaTN : num -0.169 0.609 1.028 0.525 0.968 ... 885s $ betaN : num 0.25 0.38 0.919 0.34 0.783 ... 885s $ muN : num 0 0.5 1 0.5 1 1 0 1 0 1 ... 885s $ index : int 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 885s $ rho : num NA 0.2186 NA 0.0503 NA ... 885s Number of loci: 4391 885s Number of SNPs: 1311 (29.86%) 885s Number of heterozygous SNPs: 1311 (100.00%) 885s Chromosome: 1 885s Segmenting DH signals... 885s Segmenting by CBS... 885s Chromosome: 1 885s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 885s Segmenting by CBS...done 885s List of 4 885s $ data :'data.frame': 4391 obs. of 4 variables: 885s ..$ chromosome: int [1:4391] 1 1 1 1 1 1 1 1 1 1 ... 885s ..$ x : num [1:4391] 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 885s ..$ y : num [1:4391] NA 0.2186 NA 0.0503 NA ... 885s ..$ index : int [1:4391] 1 2 3 4 5 6 7 8 9 10 ... 885s $ output :'data.frame': 1 obs. of 6 variables: 885s ..$ sampleName: chr NA 885s ..$ chromosome: int 1 885s ..$ start : num 1.85e+08 885s ..$ end : num 2.47e+08 885s ..$ nbrOfLoci : int 1311 885s ..$ mean : num 0.23 885s $ segRows:'data.frame': 1 obs. of 2 variables: 885s ..$ startRow: int 2 885s ..$ endRow : int 4388 885s $ params :List of 5 885s ..$ alpha : num 0.001 885s ..$ undo : num 0 885s ..$ joinSegments : logi TRUE 885s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 885s .. ..$ chromosome: int 1 885s .. ..$ start : num 1.85e+08 885s .. ..$ end : num 2.47e+08 885s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 885s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 885s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.016 0 0.016 0 0 885s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 885s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 885s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 885s DH segmentation (locally-indexed) rows: 885s startRow endRow 885s 1 2 4388 885s int [1:4391] 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 885s DH segmentation rows: 885s startRow endRow 885s 1 10269 14655 885s Segmenting DH signals...done 885s DH segmentation table: 885s dhStart dhEnd dhNbrOfLoci dhMean 885s 1 185449813 247137334 1311 0.2295 885s startRow endRow 885s 1 10269 14655 885s Rows: 885s [1] 4 885s TCN segmentation rows: 885s startRow endRow 885s 4 10268 14658 885s TCN and DH segmentation rows: 885s startRow endRow 885s 4 10268 14658 885s startRow endRow 885s 1 10269 14655 885s startRow endRow 885s 1 1 7586 885s 2 NA NA 885s 3 7587 10267 885s TCN segmentation (expanded) rows: 885s startRow endRow 885s 1 1 7586 885s 2 NA NA 885s 3 7587 10267 885s 4 10268 14658 885s TCN and DH segmentation rows: 885s startRow endRow 885s 1 1 7586 885s 2 NA NA 885s 3 7587 10267 885s 4 10268 14658 885s startRow endRow 885s 1 10 7574 885s 2 NA NA 885s 3 7587 10263 885s 4 10269 14655 885s startRow endRow 885s 1 1 7586 885s 2 NA NA 885s 3 7587 10267 885s 4 10268 14658 885s Total CN segmentation table (expanded): 885s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 885s 4 1 185449813 247137334 4391 2.6341 1311 1311 885s (TCN,DH) segmentation for one total CN segment: 885s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 885s 4 4 1 1 185449813 247137334 4391 2.6341 1311 885s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 885s 4 1311 185449813 247137334 1311 0.2295 885s Total CN segment #4 ([1.8545e+08,2.47137e+08]) of 4...done 885s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 885s 1 1 1 1 554484 120992603 7586 1.3853 2108 885s 2 1 2 1 120992604 141510002 0 NA 0 885s 3 1 3 1 141510003 185449813 2681 2.0689 777 885s 4 1 4 1 185449813 247137334 4391 2.6341 1311 885s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 885s 1 2108 554484 120992603 2108 0.5116 885s 2 0 NA NA NA NA 885s 3 777 141510003 185449813 777 0.0973 885s 4 1311 185449813 247137334 1311 0.2295 885s Calculating (C1,C2) per segment... 885s Calculating (C1,C2) per segment...done 885s Number of segments: 4 885s Segmenting paired tumor-normal signals using Paired PSCBS...done 885s Post-segmenting TCNs... 885s Number of segments: 4 885s Number of chromosomes: 1 885s [1] 1 885s Chromosome 1 ('chr01') of 1... 885s Rows: 885s [1] 1 2 3 4 885s Number of segments: 4 885s TCN segment #1 ('1') of 4... 885s Nothing todo. Only one DH segmentation. Skipping. 885s TCN segment #1 ('1') of 4...done 885s TCN segment #2 ('2') of 4... 885s Nothing todo. Only one DH segmentation. Skipping. 885s TCN segment #2 ('2') of 4...done 885s TCN segment #3 ('3') of 4... 885s Nothing todo. Only one DH segmentation. Skipping. 885s TCN segment #3 ('3') of 4...done 885s TCN segment #4 ('4') of 4... 885s Nothing todo. Only one DH segmentation. Skipping. 885s TCN segment #4 ('4') of 4...done 885s Chromosome 1 ('chr01') of 1...done 885s Update (C1,C2) per segment... 885s Update (C1,C2) per segment...done 885s Post-segmenting TCNs...done 885s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 885s 1 1 1 1 554484 120992603 7586 1.3853 2108 885s 2 1 2 1 120992604 141510002 0 NA 0 885s 3 1 3 1 141510003 185449813 2681 2.0689 777 885s 4 1 4 1 185449813 247137334 4391 2.6341 1311 885s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 885s 1 2108 554484 120992603 2108 0.5116 0.3382903 1.047010 885s 2 0 NA NA NA NA NA NA 885s 3 777 141510003 185449813 777 0.0973 0.9337980 1.135102 885s 4 1311 185449813 247137334 1311 0.2295 1.0147870 1.619313 885s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 885s 1 1 1 1 554484 120992603 7586 1.3853 2108 885s 2 1 2 1 120992604 141510002 0 NA 0 885s 3 1 3 1 141510003 185449813 2681 2.0689 777 885s 4 1 4 1 185449813 247137334 4391 2.6341 1311 885s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 885s 1 2108 554484 120992603 2108 0.5116 0.3382903 1.047010 885s 2 0 NA NA NA NA NA NA 885s 3 777 141510003 185449813 777 0.0973 0.9337980 1.135102 885s 4 1311 185449813 247137334 1311 0.2295 1.0147870 1.619313 885s > print(fit) 885s chromosome tcnId dhId start end tcnNbrOfLoci tcnMean tcnNbrOfSNPs 885s 1 1 1 1 554484 120992603 7586 1.3853 2108 885s 2 1 2 1 120992604 141510002 0 NA 0 885s 3 1 3 1 141510003 185449813 2681 2.0689 777 885s 4 1 4 1 185449813 247137334 4391 2.6341 1311 885s tcnNbrOfHets dhNbrOfLoci dhMean c1Mean c2Mean 885s 1 2108 2108 0.5116 0.3382903 1.047010 885s 2 0 NA NA NA NA 885s 3 777 777 0.0973 0.9337980 1.135102 885s 4 1311 1311 0.2295 1.0147870 1.619313 885s > 885s > # Plot results 885s > plotTracks(fit) 885s > 885s > # Sanity check 885s > stopifnot(nbrOfSegments(fit) == nSegs) 885s > 885s > 885s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 885s > # Bootstrap segment level estimates 885s > # (used by the AB caller, which, if skipped here, 885s > # will do it automatically) 885s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 885s > fit <- bootstrapTCNandDHByRegion(fit, B=B, verbose=-10) 885s Resample (TCN,DH) signals and re-estimate summaries for segment & changepoint... 885s Already done? 885s tcn_2.5% tcn_5% tcn_95% tcn_97.5% dh_2.5% dh_5% dh_95% dh_97.5% 885s FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE 885s c1_2.5% c1_5% c1_95% c1_97.5% c2_2.5% c2_5% c2_95% c2_97.5% 885s FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE 885s Bootstrapping (TCN,DH,C1,C2) segment mean levels... 886s Identifying heterozygous & homozygous SNPs and non-polymorphic loci... 886s Number of loci: 14658 886s Number of SNPs: 4196 886s Number of non-SNPs: 10462 886s Identifying heterozygous & homozygous SNPs and non-polymorphic loci...done 886s num [1:4, 1:100, 1:4] NA NA NA NA NA NA NA NA NA NA ... 886s - attr(*, "dimnames")=List of 3 886s ..$ : NULL 886s ..$ : NULL 886s ..$ : chr [1:4] "tcn" "dh" "c1" "c2" 886s Segment #1 (chr 1, tcnId=1, dhId=1) of 4... 886s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 886s 1 1 1 1 554484 120992603 7586 1.3853 2108 886s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 886s 1 2108 554484 120992603 2108 0.5116 0.3382903 1.04701 886s Number of TCNs: 7586 886s Number of DHs: 2108 886s int [1:7586] 1 2 3 4 5 6 7 8 9 10 ... 886s int [1:14658] 1 2 3 4 5 6 7 8 9 10 ... 886s int [1:7586] 1 2 3 4 5 6 7 8 9 10 ... 886s Identify loci used to bootstrap DH means... 886s Heterozygous SNPs to resample for DH: 886s int [1:2108] 10 12 24 28 31 33 34 39 46 48 ... 886s Identify loci used to bootstrap DH means...done 886s Identify loci used to bootstrap TCN means... 886s SNPs: 886s int [1:2108] 10 12 24 28 31 33 34 39 46 48 ... 886s Non-polymorphic loci: 886s int [1:5478] 1 2 3 4 5 6 7 8 9 11 ... 886s Heterozygous SNPs to resample for TCN: 886s int [1:2108] 10 12 24 28 31 33 34 39 46 48 ... 886s Homozygous SNPs to resample for TCN: 886s int(0) 886s Non-polymorphic loci to resample for TCN: 886s int [1:5478] 1 2 3 4 5 6 7 8 9 11 ... 886s Heterozygous SNPs with non-DH to resample for TCN: 886s int(0) 886s Loci to resample for TCN: 886s int [1:7586] 1 2 3 4 5 6 7 8 9 10 ... 886s Identify loci used to bootstrap TCN means...done 886s Number of (#hets, #homs, #nonSNPs): (2108,0,5478) 886s Bootstrapping while preserving (#hets, #homs, #nonSNPs)... 886s Number of bootstrap samples: 100 886s Bootstrapping while preserving (#hets, #homs, #nonSNPs)...done 886s Segment #1 (chr 1, tcnId=1, dhId=1) of 4...done 886s Segment #2 (chr 1, tcnId=2, dhId=1) of 4... 886s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 886s 2 1 2 1 120992604 141510002 0 NA 0 886s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 886s 2 0 NA NA 0 NA NA NA 886s Number of TCNs: 0 886s Number of DHs: 0 886s int 0 886s int [1:14658] 1 2 3 4 5 6 7 8 9 10 ... 886s int(0) 886s Identify loci used to bootstrap DH means... 886s Heterozygous SNPs to resample for DH: 886s int 0 886s Identify loci used to bootstrap DH means...done 886s Identify loci used to bootstrap TCN means... 886s SNPs: 886s int(0) 886s Non-polymorphic loci: 886s int(0) 886s Heterozygous SNPs to resample for TCN: 886s int(0) 886s Homozygous SNPs to resample for TCN: 886s int(0) 886s Non-polymorphic loci to resample for TCN: 886s int(0) 886s Heterozygous SNPs with non-DH to resample for TCN: 886s int(0) 886s Loci to resample for TCN: 886s int(0) 886s Identify loci used to bootstrap TCN means...done 886s Number of (#hets, #homs, #nonSNPs): (0,0,0) 886s Bootstrapping while preserving (#hets, #homs, #nonSNPs)... 886s Number of bootstrap samples: 100 886s Bootstrapping while preserving (#hets, #homs, #nonSNPs)...done 886s Segment #2 (chr 1, tcnId=2, dhId=1) of 4...done 886s Segment #3 (chr 1, tcnId=3, dhId=1) of 4... 886s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 886s 3 1 3 1 141510003 185449813 2681 2.0689 777 886s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 886s 3 777 141510003 185449813 777 0.0973 0.933798 1.135102 886s Number of TCNs: 2681 886s Number of DHs: 777 886s int [1:2681] 7587 7588 7589 7590 7591 7592 7593 7594 7595 7596 ... 886s int [1:14658] 1 2 3 4 5 6 7 8 9 10 ... 886s int [1:2681] 7587 7588 7589 7590 7591 7592 7593 7594 7595 7596 ... 886s Identify loci used to bootstrap DH means... 886s Heterozygous SNPs to resample for DH: 886s int [1:777] 7587 7588 7594 7614 7616 7626 7627 7628 7635 7638 ... 886s Identify loci used to bootstrap DH means...done 886s Identify loci used to bootstrap TCN means... 886s SNPs: 886s int [1:777] 7587 7588 7594 7614 7616 7626 7627 7628 7635 7638 ... 886s Non-polymorphic loci: 886s int [1:1904] 7589 7590 7591 7592 7593 7595 7596 7597 7598 7599 ... 886s Heterozygous SNPs to resample for TCN: 886s int [1:777] 7587 7588 7594 7614 7616 7626 7627 7628 7635 7638 ... 886s Homozygous SNPs to resample for TCN: 886s int(0) 886s Non-polymorphic loci to resample for TCN: 886s int [1:1904] 7589 7590 7591 7592 7593 7595 7596 7597 7598 7599 ... 886s Heterozygous SNPs with non-DH to resample for TCN: 886s int(0) 886s Loci to resample for TCN: 886s int [1:2681] 7587 7588 7589 7590 7591 7592 7593 7594 7595 7596 ... 886s Identify loci used to bootstrap TCN means...done 886s Number of (#hets, #homs, #nonSNPs): (777,0,1904) 886s Bootstrapping while preserving (#hets, #homs, #nonSNPs)... 886s Number of bootstrap samples: 100 886s Bootstrapping while preserving (#hets, #homs, #nonSNPs)...done 886s Segment #3 (chr 1, tcnId=3, dhId=1) of 4...done 886s Segment #4 (chr 1, tcnId=4, dhId=1) of 4... 886s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 886s 4 1 4 1 185449813 247137334 4391 2.6341 1311 886s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 886s 4 1311 185449813 247137334 1311 0.2295 1.014787 1.619313 886s Number of TCNs: 4391 886s Number of DHs: 1311 886s int [1:4391] 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 886s int [1:14658] 1 2 3 4 5 6 7 8 9 10 ... 886s int [1:4391] 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 886s Identify loci used to bootstrap DH means... 886s Heterozygous SNPs to resample for DH: 886s int [1:1311] 10269 10271 10281 10282 10283 10293 10295 10297 10300 10302 ... 886s Identify loci used to bootstrap DH means...done 886s Identify loci used to bootstrap TCN means... 886s SNPs: 886s int [1:1311] 10269 10271 10281 10282 10283 10293 10295 10297 10300 10302 ... 886s Non-polymorphic loci: 886s int [1:3080] 10268 10270 10272 10273 10274 10275 10276 10277 10278 10279 ... 886s Heterozygous SNPs to resample for TCN: 886s int [1:1311] 10269 10271 10281 10282 10283 10293 10295 10297 10300 10302 ... 886s Homozygous SNPs to resample for TCN: 886s int(0) 886s Non-polymorphic loci to resample for TCN: 886s int [1:3080] 10268 10270 10272 10273 10274 10275 10276 10277 10278 10279 ... 886s Heterozygous SNPs with non-DH to resample for TCN: 886s int(0) 886s Loci to resample for TCN: 886s int [1:4391] 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 886s Identify loci used to bootstrap TCN means...done 886s Number of (#hets, #homs, #nonSNPs): (1311,0,3080) 886s Bootstrapping while preserving (#hets, #homs, #nonSNPs)... 886s Number of bootstrap samples: 100 886s Bootstrapping while preserving (#hets, #homs, #nonSNPs)...done 886s Segment #4 (chr 1, tcnId=4, dhId=1) of 4...done 886s Bootstrapped segment mean levels 886s num [1:4, 1:100, 1:4] 1.39 NA 2.08 2.63 1.38 ... 886s - attr(*, "dimnames")=List of 3 886s ..$ : NULL 886s ..$ : NULL 886s ..$ : chr [1:4] "tcn" "dh" "c1" "c2" 886s Calculating (C1,C2) mean levels from (TCN,DH) mean levels... 886s num [1:4, 1:100, 1:4] 1.39 NA 2.08 2.63 1.38 ... 886s - attr(*, "dimnames")=List of 3 886s ..$ : NULL 886s ..$ : NULL 886s ..$ : chr [1:4] "tcn" "dh" "c1" "c2" 886s Calculating (C1,C2) mean levels from (TCN,DH) mean levels...done 886s Calculating polar (alpha,radius,manhattan) for change points... 886s num [1:3, 1:100, 1:2] NA NA -0.0752 NA NA ... 886s - attr(*, "dimnames")=List of 3 886s ..$ : NULL 886s ..$ : NULL 886s ..$ : chr [1:2] "c1" "c2" 886s Bootstrapped change points 886s num [1:3, 1:100, 1:5] NA NA -1.73 NA NA ... 886s - attr(*, "dimnames")=List of 3 886s ..$ : NULL 886s ..$ : NULL 886s ..$ : chr [1:5] "alpha" "radius" "manhattan" "d1" ... 886s Calculating polar (alpha,radius,manhattan) for change points...done 886s Bootstrapping (TCN,DH,C1,C2) segment mean levels...done 886s Summarizing bootstrapped segment (‘tcn’, ‘dh’, ‘c1’, ‘c2’) data... 886s num [1:4, 1:4, 1:4] NA NA NA NA NA NA NA NA NA NA ... 886s - attr(*, "dimnames")=List of 3 886s ..$ : NULL 886s ..$ : chr [1:4] "2.5%" "5%" "95%" "97.5%" 886s ..$ : chr [1:4] "tcn" "dh" "c1" "c2" 886s Field #1 ('tcn') of 4... 886s Segment #1 of 4... 886s Segment #1 of 4...done 886s Segment #2 of 4... 886s Segment #2 of 4...done 886s Segment #3 of 4... 886s Segment #3 of 4...done 886s Segment #4 of 4... 886s Segment #4 of 4...done 886s Field #1 ('tcn') of 4...done 886s Field #2 ('dh') of 4... 886s Segment #1 of 4... 886s Segment #1 of 4...done 886s Segment #2 of 4... 886s Segment #2 of 4...done 886s Segment #3 of 4... 886s Segment #3 of 4...done 886s Segment #4 of 4... 886s Segment #4 of 4...done 886s Field #2 ('dh') of 4...done 886s Field #3 ('c1') of 4... 886s Segment #1 of 4... 886s Segment #1 of 4...done 886s Segment #2 of 4... 886s Segment #2 of 4...done 886s Segment #3 of 4... 886s Segment #3 of 4...done 886s Segment #4 of 4... 886s Segment #4 of 4...done 886s Field #3 ('c1') of 4...done 886s Field #4 ('c2') of 4... 886s Segment #1 of 4... 886s Segment #1 of 4...done 886s Segment #2 of 4... 886s Segment #2 of 4...done 886s Segment #3 of 4... 886s Segment #3 of 4...done 886s Segment #4 of 4... 886s Segment #4 of 4...done 886s Field #4 ('c2') of 4...done 886s Bootstrap statistics 886s num [1:4, 1:4, 1:4] 1.38 NA 2.06 2.63 1.38 ... 886s - attr(*, "dimnames")=List of 3 886s ..$ : NULL 886s ..$ : chr [1:4] "2.5%" "5%" "95%" "97.5%" 886s ..$ : chr [1:4] "tcn" "dh" "c1" "c2" 886s Statistical sanity checks (iff B >= 100)... 886s Available summaries: 2.5%, 5%, 95%, 97.5% 886s Available quantiles: 0.025, 0.05, 0.95, 0.975 886s num [1:4, 1:4, 1:4] 1.38 NA 2.06 2.63 1.38 ... 886s - attr(*, "dimnames")=List of 3 886s ..$ : NULL 886s ..$ : chr [1:4] "2.5%" "5%" "95%" "97.5%" 886s ..$ : chr [1:4] "tcn" "dh" "c1" "c2" 886s Field #1 ('tcn') of 4... 886s Seg 1. mean=1.3853, range=[1.37909,1.39287], n=7586 886s Seg 2. mean=NA, range=[NA,NA], n=0 886s Seg 3. mean=2.0689, range=[2.05903,2.079], n=2681 886s Seg 4. mean=2.6341, range=[2.62504,2.64649], n=4391 886s Field #1 ('tcn') of 4...done 886s Field #2 ('dh') of 4... 886s Seg 1. mean=0.5116, range=[0.502148,0.519941], n=2108 886s Seg 2. mean=NA, range=[NA,NA], n=NA 886s Seg 3. mean=0.0973, range=[0.0906366,0.105818], n=777 886s Seg 4. mean=0.2295, range=[0.222919,0.237005], n=1311 886s Field #2 ('dh') of 4...done 886s Field #3 ('c1') of 4... 886s Seg 1. mean=0.33829, range=[0.332209,0.345936], n=2108 886s Seg 2. mean=NA, range=[NA,NA], n=NA 886s Seg 3. mean=0.933798, range=[0.924112,0.941776], n=777 886s Seg 4. mean=1.01479, range=[1.00381,1.02461], n=1311 886s Field #3 ('c1') of 4...done 886s Field #4 ('c2') of 4... 886s Seg 1. mean=1.04701, range=[1.03882,1.05318], n=2108 886s Seg 2. mean=NA, range=[NA,NA], n=NA 886s Seg 3. mean=1.1351, range=[1.12454,1.1465], n=777 886s Seg 4. mean=1.61931, range=[1.60862,1.63328], n=1311 886s Field #4 ('c2') of 4...done 886s Statistical sanity checks (iff B >= 100)...done 886s Summarizing bootstrapped segment (‘tcn’, ‘dh’, ‘c1’, ‘c2’) data...done 886s Summarizing bootstrapped changepoint (‘alpha’, ‘radius’, ‘manhattan’, ‘d1’, ‘d2’) data... 886s num [1:3, 1:4, 1:5] NA NA NA NA NA NA NA NA NA NA ... 886s - attr(*, "dimnames")=List of 3 886s ..$ : NULL 886s ..$ : chr [1:4] "2.5%" "5%" "95%" "97.5%" 886s ..$ : chr [1:5] "alpha" "radius" "manhattan" "d1" ... 886s Field #1 ('alpha') of 5... 886s Changepoint #1 of 3... 886s Changepoint #1 of 3...done 886s Changepoint #2 of 3... 886s Changepoint #2 of 3...done 886s Changepoint #3 of 3... 886s Changepoint #3 of 3...done 886s Field #1 ('alpha') of 5...done 886s Field #2 ('radius') of 5... 886s Changepoint #1 of 3... 886s Changepoint #1 of 3...done 886s Changepoint #2 of 3... 886s Changepoint #2 of 3...done 886s Changepoint #3 of 3... 886s Changepoint #3 of 3...done 886s Field #2 ('radius') of 5...done 886s Field #3 ('manhattan') of 5... 886s Changepoint #1 of 3... 886s Changepoint #1 of 3...done 886s Changepoint #2 of 3... 886s Changepoint #2 of 3...done 886s Changepoint #3 of 3... 886s Changepoint #3 of 3...done 886s Field #3 ('manhattan') of 5...done 886s Field #4 ('d1') of 5... 886s Changepoint #1 of 3... 886s Changepoint #1 of 3...done 886s Changepoint #2 of 3... 886s Changepoint #2 of 3...done 886s Changepoint #3 of 3... 886s Changepoint #3 of 3...done 886s Field #4 ('d1') of 5...done 886s Field #5 ('d2') of 5... 886s Changepoint #1 of 3... 886s Changepoint #1 of 3...done 886s Changepoint #2 of 3... 886s Changepoint #2 of 3...done 886s Changepoint #3 of 3... 886s Changepoint #3 of 3...done 886s Field #5 ('d2') of 5...done 886s Bootstrap statistics 886s num [1:3, 1:4, 1:5] NA NA -1.77 NA NA ... 886s - attr(*, "dimnames")=List of 3 886s ..$ : NULL 886s ..$ : chr [1:4] "2.5%" "5%" "95%" "97.5%" 886s ..$ : chr [1:5] "alpha" "radius" "manhattan" "d1" ... 886s Summarizing bootstrapped changepoint (‘alpha’, ‘radius’, ‘manhattan’, ‘d1’, ‘d2’) data...done 886s Resample (TCN,DH) signals and re-estimate summaries for segment & changepoint...done 886s > print(fit) 886s chromosome tcnId dhId start end tcnNbrOfLoci tcnMean tcnNbrOfSNPs 886s 1 1 1 1 554484 120992603 7586 1.3853 2108 886s 2 1 2 1 120992604 141510002 0 NA 0 886s 3 1 3 1 141510003 185449813 2681 2.0689 777 886s 4 1 4 1 185449813 247137334 4391 2.6341 1311 886s tcnNbrOfHets dhNbrOfLoci dhMean c1Mean c2Mean 886s 1 2108 2108 0.5116 0.3382903 1.047010 886s 2 0 NA NA NA NA 886s 3 777 777 0.0973 0.9337980 1.135102 886s 4 1311 1311 0.2295 1.0147870 1.619313 886s > plotTracks(fit) 886s > 886s > 886s > 886s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 886s > # Calling segments with run of homozygosity (ROH) 886s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 886s > fit <- callROH(fit, verbose=-10) 886s Calling ROH... 886s Segment #1 of 4... 886s Calling ROH for a single segment... 886s Number of SNPs: 7586 886s Calling ROH for a single segment...done 886s Segment #1 of 4...done 886s Segment #2 of 4... 886s Calling ROH for a single segment... 886s Number of SNPs: 0 886s Calling ROH for a single segment...done 886s Segment #2 of 4...done 886s Segment #3 of 4... 886s Calling ROH for a single segment... 886s Number of SNPs: 2681 886s Calling ROH for a single segment...done 886s Segment #3 of 4...done 886s Segment #4 of 4... 886s Calling ROH for a single segment... 886s Number of SNPs: 4391 886s Calling ROH for a single segment...done 886s Segment #4 of 4...done 886s ROH calls: 886s logi [1:4] FALSE NA FALSE FALSE 886s Mode FALSE NA's 886s logical 3 1 886s Calling ROH...done 886s > print(fit) 886s chromosome tcnId dhId start end tcnNbrOfLoci tcnMean tcnNbrOfSNPs 886s 1 1 1 1 554484 120992603 7586 1.3853 2108 886s 2 1 2 1 120992604 141510002 0 NA 0 886s 3 1 3 1 141510003 185449813 2681 2.0689 777 886s 4 1 4 1 185449813 247137334 4391 2.6341 1311 886s tcnNbrOfHets dhNbrOfLoci dhMean c1Mean c2Mean rohCall 886s 1 2108 2108 0.5116 0.3382903 1.047010 FALSE 886s 2 0 NA NA NA NA NA 886s 3 777 777 0.0973 0.9337980 1.135102 FALSE 886s 4 1311 1311 0.2295 1.0147870 1.619313 FALSE 886s > plotTracks(fit) 886s > 886s > 886s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 886s > # Estimate background 886s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 886s > kappa <- estimateKappa(fit, verbose=-10) 886s Estimate global background (including normal contamination and more)... 886s Number of segments: 3 886s Estimating threshold Delta0.5 from the empirical density of C1:s... 886s adjust: 1 886s minDensity: 0.2 886s ploidy: 2 886s All peaks: 886s type x density 886s 1 peak 0.3362194 1.101242 886s 3 peak 0.9811492 1.065635 886s C1=0 and C1=1 peaks: 886s type x density 886s 1 peak 0.3362194 1.101242 886s 3 peak 0.9811492 1.065635 886s Estimate of Delta0.5: 0.65868427808456 886s Estimating threshold Delta0.5 from the empirical density of C1:s...done 886s Number of segments with C1 < Delta0.5: 1 886s > print(kappa) 886s [1] 0.3382903 886s > ## [1] 0.226011 886s > 886s > 886s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 886s > # Calling segments in allelic balance (AB) 886s > # NOTE: Ideally, this should be done on whole-genome data 886s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 886s > # Explicitly estimate the threshold in DH for calling AB 886s > # (which be done by default by the caller, if skipped here) 886s > deltaAB <- estimateDeltaAB(fit, flavor="qq(DH)", verbose=-10) 886s Estimate of kappa: 0.33829026 886s Estimate global background (including normal contamination and more)...done 886s Warning message: 886s In density.default(c1, weights = weights, adjust = adjust, from = from, : 886s Selecting bandwidth *not* using 'weights' 886s Estimating DH threshold for calling allelic imbalances... 886s flavor: qq(DH) 886s scale: 1 886s Estimating DH threshold for AB caller... 886s quantile #1: 0.05 886s Symmetric quantile #2: 0.9 886s Number of segments: 3 886s Weighted 5% quantile of DH: 0.257710 886s Number of segments with small DH: 2 886s Number of data points: 7072 886s Number of finite data points: 2088 886s Estimate of (1-0.9):th and 50% quantiles: (0.0310411,0.163658) 886s Estimate of 0.9:th "symmetric" quantile: 0.296275 886s Estimating DH threshold for AB caller...done 886s Estimated delta: 0.296 886s > Estimating DH threshold for calling allelic imbalances...done 886s if (Sys.getenv("_R_CHECK_FULL_") == "") { 886s + # Ad hoc workaround for not utilizing all of the data 886s + # in the test, which results in a poor estimate 886s + deltaAB <- 0.165 886s + } 886s > print(deltaAB) 886s [1] 0.165 886s > ## [1] 0.1657131 886s > 886s > fit <- callAB(fit, delta=deltaAB, verbose=-10) 886s Calling segments of allelic balance from one-sided DH bootstrap confidence intervals... 886s delta (offset adjusting for bias in DH): 0.165 886s alpha (CI quantile; significance level): 0.05 886s Calling segments... 886s Number of segments called allelic balance (AB): 1 (25.00%) of 4 886s Calling segments...done 886s Calling segments of allelic balance from one-sided DH bootstrap confidence intervals...done 886s > print(fit) 886s chromosome tcnId dhId start end tcnNbrOfLoci tcnMean tcnNbrOfSNPs 886s 1 1 1 1 554484 120992603 7586 1.3853 2108 886s 2 1 2 1 120992604 141510002 0 NA 0 886s 3 1 3 1 141510003 185449813 2681 2.0689 777 886s 4 1 4 1 185449813 247137334 4391 2.6341 1311 886s tcnNbrOfHets dhNbrOfLoci dhMean c1Mean c2Mean rohCall abCall 886s 1 2108 2108 0.5116 0.3382903 1.047010 FALSE FALSE 886s 2 0 NA NA NA NA NA NA 886s 3 777 777 0.0973 0.9337980 1.135102 FALSE TRUE 886s 4 1311 1311 0.2295 1.0147870 1.619313 FALSE FALSE 886s > plotTracks(fit) 887s > 887s > # Even if not explicitly specified, the estimated 887s > # threshold parameter is returned by the caller 887s > stopifnot(fit$params$deltaAB == deltaAB) 887s > 887s > 887s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 887s > # Calling segments in loss-of-heterozygosity (LOH) 887s > # NOTE: Ideally, this should be done on whole-genome data 887s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 887s > # Explicitly estimate the threshold in C1 for calling LOH 887s > # (which be done by default by the caller, if skipped here) 887s > deltaLOH <- estimateDeltaLOH(fit, flavor="minC1|nonAB", verbose=-10) 887s Estimating DH threshold for calling LOH... 887s flavor: minC1|nonAB 887s Estimating DH threshold for calling LOH as the midpoint between guessed C1=0 and C1=1... 887s Argument 'midpoint': 0.5 887s Number of segments: 4 887s Number of segments in allelic balance: 1 (25.0%) of 4 887s Number of segments not in allelic balance: 2 (50.0%) of 4 887s Number of segments in allelic balance and TCN <= 3.00: 1 (25.0%) of 4 887s C: 2.07 887s Corrected C1 (=C/2): 1.03 887s Number of DHs: 777 887s Weights: 1 887s Weighted median of (corrected) C1 in allelic balance: 1.034 887s Smallest C1 among segments not in allelic balance: 0.338 887s There are 1 segments with in total 2108 heterozygous SNPs with this level. 887s Midpoint between the two: 0.686 887s Estimating DH threshold for calling LOH as the midpoint between guessed C1=0 and C1=1...done 887s delta: 0.686 887s > print(deltaLOH) 887s [1] 0.6863701 887s > ## [1] 0.625175 887s > 887s > fit <- callLOH(fit, delta=deltaLOH, verbose=-10) 887s Estimating DH threshold for calling LOH...done 887s Calling segments of allelic balance from one-sided DH bootstrap confidence intervals... 887s delta (offset adjusting for bias in C1): 0.68637013 887s alpha (CI quantile; significance level): 0.05 887s Calling segments... 887s Number of segments called low C1 (LowC1, "LOH_C1"): 1 (25.00%) of 4 887s Calling segments...done 887s Calling segments of allelic balance from one-sided DH bootstrap confidence intervals...done 887s > print(fit) 887s chromosome tcnId dhId start end tcnNbrOfLoci tcnMean tcnNbrOfSNPs 887s 1 1 1 1 554484 120992603 7586 1.3853 2108 887s 2 1 2 1 120992604 141510002 0 NA 0 887s 3 1 3 1 141510003 185449813 2681 2.0689 777 887s 4 1 4 1 185449813 247137334 4391 2.6341 1311 887s tcnNbrOfHets dhNbrOfLoci dhMean c1Mean c2Mean rohCall abCall lohCall 887s 1 2108 2108 0.5116 0.3382903 1.047010 FALSE FALSE TRUE 887s 2 0 NA NA NA NA NA NA NA 887s 3 777 777 0.0973 0.9337980 1.135102 FALSE TRUE FALSE 887s 4 1311 1311 0.2295 1.0147870 1.619313 FALSE FALSE FALSE 887s > plotTracks(fit) 887s > 887s > # Even if not explicitly specified, the estimated 887s > # threshold parameter is returned by the caller 887s > stopifnot(fit$params$deltaLOH == deltaLOH) 887s > 887s > 887s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 887s > # Calling segments that are gained, copy neutral, and lost 887s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 887s > fit <- callGNL(fit, verbose=-10) 887s Calling gain, neutral, and loss based TCNs of AB segments... 887s Calling neutral TCNs... 887s callCopyNeutralByTCNofAB... 887s Alpha: 0.05 887s Delta CN: 0.33085487 887s Calling copy-neutral segments... 887s Retrieve TCN confidence intervals for all segments... 887s Interval: [0.025,0.975] 887s Retrieve TCN confidence intervals for all segments...done 887s Estimating TCN confidence interval of copy-neutral AB segments... 887s calcStatsForCopyNeutralABs... 887s Identifying copy neutral AB segments... 887s Number of AB segments: 1 887s Identifying segments that are copy neutral states... 887s Number of segments in allelic balance: 1 887s Identifying segments that are copy neutral states...done 887s Number of copy-neutral AB segments: 1 887s Extracting all copy neutral AB segments across all chromosomes into one big segment... 887s chromosome tcnId dhId start end tcnNbrOfLoci tcnMean tcnNbrOfSNPs 887s 3 1 3 1 141510003 185449813 2681 2.0689 777 887s tcnNbrOfHets dhNbrOfLoci dhMean c1Mean c2Mean rohCall abCall lohCall 887s 3 777 777 0.0973 0.933798 1.135102 FALSE TRUE FALSE 887s Extracting all copy neutral AB segments across all chromosomes into one big segment...done 887s Identifying copy neutral AB segments...done 887s Bootstrap the identified copy-neutral states... 887s Bootstrap the identified copy-neutral states...done 887s tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets dhNbrOfLoci dhMean c1Mean 887s 3 2681 2.0689 777 777 777 0.0973 0.933798 887s c2Mean tcn_2.5% tcn_5% tcn_95% tcn_97.5% dh_2.5% dh_5% dh_95% 887s 3 1.135102 2.055164 2.057694 2.078831 2.081454 0.08974138 0.09080508 0.1035891 887s dh_97.5% c1_2.5% c1_5% c1_95% c1_97.5% c2_2.5% c2_5% c2_95% 887s 3 0.1050478 0.923788 0.925412 0.9417056 0.9433752 1.124908 1.126631 1.143571 887s c2_97.5% 887s 3 1.145214 887s calcStatsForCopyNeutralABs...done 887s Bootstrap statistics for copy-neutral AB segments: 887s tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets dhNbrOfLoci dhMean c1Mean 887s 3 2681 2.0689 777 777 777 0.0973 0.933798 887s c2Mean tcn_2.5% tcn_5% tcn_95% tcn_97.5% dh_2.5% dh_5% dh_95% 887s 3 1.135102 2.055164 2.057694 2.078831 2.081454 0.08974138 0.09080508 0.1035891 887s dh_97.5% c1_2.5% c1_5% c1_95% c1_97.5% c2_2.5% c2_5% c2_95% 887s 3 0.1050478 0.923788 0.925412 0.9417056 0.9433752 1.124908 1.126631 1.143571 887s c2_97.5% 887s 3 1.145214 887s [1] "TCN statistics:" 887s tcnMean tcn_2.5% tcn_5% tcn_95% tcn_97.5% 887s 2.068900 2.055164 2.057694 2.078831 2.081454 887s 95%-confidence interval of TCN mean for the copy-neutral state: [2.05516,2.08145] (mean=2.0689) 887s Estimating TCN confidence interval of copy-neutral AB segments...done 887s Identify all copy-neutral segments... 887s DeltaCN: +/-0.330855 887s Call ("acceptance") region: [1.72431,2.41231] 887s Total number of segments: 4 887s Number of segments called allelic balance: 1 887s Number of segments called copy neutral: 1 887s Number of AB segments called copy neutral: 1 887s Number of non-AB segments called copy neutral: 0 887s Identify all copy-neutral segments...done 887s Calling copy-neutral segments...done 887s callCopyNeutralByTCNofAB...done 887s Calling neutral TCNs...done 887s Number of NTCN calls: 1 (25.00%) of 4 887s Mean TCN of AB segments: 2.06831 887s Calling loss... 887s Number of loss calls: 1 (25.00%) of 4 887s Calling loss...done 887s Calling gain... 887s Number of loss calls: 1 (25.00%) of 4 887s Calling gain...done 887s > print(fit) 887s chromosome tcnId dhId start end tcnNbrOfLoci tcnMean tcnNbrOfSNPs 887s 1 1 1 1 554484 120992603 7586 1.3853 2108 887s 2 1 2 1 120992604 141510002 0 NA 0 887s 3 1 3 1 141510003 185449813 2681Calling gain, neutral, and loss based TCNs of AB segments...done 887s Warning message: 887s In density.default(c1, weights = weights, adjust = adjust, from = from, : 887s Selecting bandwidth *not* using 'weights' 887s 2.0689 777 887s 4 1 4 1 185449813 247137334 4391 2.6341 1311 887s tcnNbrOfHets dhNbrOfLoci dhMean c1Mean c2Mean rohCall abCall lohCall 887s 1 2108 2108 0.5116 0.3382903 1.047010 FALSE FALSE TRUE 887s 2 0 NA NA NA NA NA NA NA 887s 3 777 777 0.0973 0.9337980 1.135102 FALSE TRUE FALSE 887s 4 1311 1311 0.2295 1.0147870 1.619313 FALSE FALSE FALSE 887s ntcnCall lossCall gainCall 887s 1 FALSE TRUE FALSE 887s 2 NA NA NA 887s 3 TRUE FALSE FALSE 887s 4 FALSE FALSE TRUE 887s > plotTracks(fit) 887s > 888s Start: segmentByPairedPSCBS,futures.R 888s 888s R version 4.5.2 (2025-10-31) -- "[Not] Part in a Rumble" 888s Copyright (C) 2025 The R Foundation for Statistical Computing 888s Platform: aarch64-unknown-linux-gnu 888s 888s R is free software and comes with ABSOLUTELY NO WARRANTY. 888s You are welcome to redistribute it under certain conditions. 888s Type 'license()' or 'licence()' for distribution details. 888s 888s R is a collaborative project with many contributors. 888s Type 'contributors()' for more information and 888s 'citation()' on how to cite R or R packages in publications. 888s 888s Type 'demo()' for some demos, 'help()' for on-line help, or 888s 'help.start()' for an HTML browser interface to help. 888s Type 'q()' to quit R. 888s 888s > library(PSCBS) 888s PSCBS v0.68.0 (2025-04-18 19:40:02 UTC) successfully loaded. See ?PSCBS for help. 888s > library(utils) 888s > 888s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 888s > # Load SNP microarray data 888s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 888s > data <- PSCBS::exampleData("paired.chr01") 888s > 888s > 888s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 888s > # Paired PSCBS segmentation 888s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 888s > # Drop single-locus outliers 888s > dataS <- dropSegmentationOutliers(data) 888s > 888s > # Run light-weight tests by default 888s > if (Sys.getenv("_R_CHECK_FULL_") == "") { 888s + # Use only every 5th data point 888s + dataS <- dataS[seq(from=1, to=nrow(data), by=5),] 888s + # Number of segments (for assertion) 888s + nSegs <- 4L 888s + } else { 888s + # Full tests 888s + nSegs <- 11L 888s + } 888s > 888s > str(dataS) 888s 'data.frame': 14670 obs. of 6 variables: 888s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 888s $ x : int 1145994 2941694 3710825 4240737 4276892 4464544 4714611 5095111 5034491 5158416 ... 888s $ CT : num 1.63 1.4 1.41 1.17 1.16 ... 888s $ betaT : num 0.7574 0.169 0.2357 0.2604 0.0576 ... 888s $ CN : num 2.36 2.13 2.26 2.01 2.32 ... 888s $ betaN : num 0.8274 0.5072 0.1671 0.1609 0.0421 ... 888s > 888s > 888s > ## Create multiple chromosomes 888s > data <- list() 888s > for (cc in 1:3) { 888s + dataS$chromosome <- cc 888s + data[[cc]] <- dataS 888s + } 888s > data <- Reduce(rbind, data) 888s > str(data) 888s 'data.frame': 44010 obs. of 6 variables: 888s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 888s $ x : int 1145994 2941694 3710825 4240737 4276892 4464544 4714611 5095111 5034491 5158416 ... 888s $ CT : num 1.63 1.4 1.41 1.17 1.16 ... 888s $ betaT : num 0.7574 0.169 0.2357 0.2604 0.0576 ... 888s $ CN : num 2.36 2.13 2.26 2.01 2.32 ... 888s $ betaN : num 0.8274 0.5072 0.1671 0.1609 0.0421 ... 888s > 888s > 888s > message("*** segmentByPairedPSCBS() via futures ...") 888s *** segmentByPairedPSCBS() via futures ... 888s > 888s > library("future") 888s > oplan <- plan() 888s > 888s > strategies <- c("sequential", "multisession") 888s > 888s > ## Test 'future.batchtools' futures? 888s > pkg <- "future.batchtools" 888s > if (require(pkg, character.only=TRUE)) { 888s + strategies <- c(strategies, "batchtools_local") 888s + } 888s Loading required package: future.batchtools 888s Warning message: 888s In library(package, lib.loc = lib.loc, character.only = TRUE, logical.return = TRUE, : 888s there is no package called ‘future.batchtools’ 888s > 888s > message("Future strategies to test: ", paste(sQuote(strategies), collapse=", ")) 888s Future strategies to test: ‘sequential’, ‘multisession’ 888s > 888s > fits <- list() 888s > for (strategy in strategies) { 888s + message(sprintf("- segmentByPairedPSCBS() using '%s' futures ...", strategy)) 888s + plan(strategy) 888s + fit <- segmentByPairedPSCBS(data, seed=0xBEEF, verbose=TRUE) 888s + fits[[strategy]] <- fit 888s + equal <- all.equal(fit, fits[[1]]) 888s + if (!equal) { 888s + str(fit) 888s + str(fits[[1]]) 888s + print(equal) 888s + stop(sprintf("segmentByPairedPSCBS() using '%s' futures does not produce the same results as when using '%s' futures", strategy, names(fits)[1])) 888s + } 888s + } 888s - segmentByPairedPSCBS() using 'sequential' futures ... 888s Segmenting paired tumor-normal signals using Paired PSCBS... 888s Calling genotypes from normal allele B fractions... 888s num [1:44010] 0.8274 0.5072 0.1671 0.1609 0.0421 ... 888s Called genotypes: 888s num [1:44010] 1 0.5 0 0 0 0 1 0 1 0.5 ... 888s - attr(*, "modelFit")=List of 1 888s ..$ :List of 7 888s .. ..$ flavor : chr "density" 888s .. ..$ cn : int 2 888s .. ..$ nbrOfGenotypeGroups: int 3 888s .. ..$ tau : num [1:2] 0.312 0.678 888s .. ..$ n : int 43920 888s .. ..$ fit :Classes ‘PeaksAndValleys’ and 'data.frame': 5 obs. of 3 variables: 888s .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 888s .. .. ..$ x : num [1:5] 0.0999 0.312 0.4986 0.6775 0.8922 888s .. .. ..$ density: num [1:5] 1.622 0.465 1.125 0.496 1.587 888s .. ..$ fitValleys :Classes ‘PeaksAndValleys’ and 'data.frame': 2 obs. of 3 variables: 888s .. .. ..$ type : chr [1:2] "valley" "valley" 888s .. .. ..$ x : num [1:2] 0.312 0.678 888s .. .. ..$ density: num [1:2] 0.465 0.496 888s ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 888s muN 888s 0 0.5 1 888s 15627 12633 15750 888s Calling genotypes from normal allele B fractions...done 888s Normalizing betaT using betaN (TumorBoost)... 888s Normalized BAFs: 888s num [1:44010] 0.9301 0.1667 0.0685 0.0995 0.0155 ... 888s - attr(*, "modelFit")=List of 5 888s ..$ method : chr "normalizeTumorBoost" 888s ..$ flavor : chr "v4" 888s ..$ delta : num [1:44010] -0.17264 0.00239 0.1671 0.16085 0.04213 ... 888s .. ..- attr(*, "modelFit")=List of 1 888s .. .. ..$ :List of 7 888s .. .. .. ..$ flavor : chr "density" 888s .. .. .. ..$ cn : int 2 888s .. .. .. ..$ nbrOfGenotypeGroups: int 3 888s .. .. .. ..$ tau : num [1:2] 0.312 0.678 888s .. .. .. ..$ n : int 43920 888s .. .. .. ..$ fit :Classes ‘PeaksAndValleys’ and 'data.frame': 5 obs. of 3 variables: 888s .. .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 888s .. .. .. .. ..$ x : num [1:5] 0.0999 0.312 0.4986 0.6775 0.8922 888s .. .. .. .. ..$ density: num [1:5] 1.622 0.465 1.125 0.496 1.587 888s .. .. .. ..$ fitValleys :Classes ‘PeaksAndValleys’ and 'data.frame': 2 obs. of 3 variables: 888s .. .. .. .. ..$ type : chr [1:2] "valley" "valley" 888s .. .. .. .. ..$ x : num [1:2] 0.312 0.678 888s .. .. .. .. ..$ density: num [1:2] 0.465 0.496 888s .. .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 888s ..$ preserveScale: logi FALSE 888s ..$ scaleFactor : num NA 888s Normalizing betaT using betaN (TumorBoost)...done 888s Setup up data... 888s 'data.frame': 44010 obs. of 7 variables: 888s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 888s $ x : num 1145994 2941694 3710825 4240737 4276892 ... 888s $ CT : num 1.63 1.4 1.41 1.17 1.16 ... 888s $ betaT : num 0.7574 0.169 0.2357 0.2604 0.0576 ... 888s $ betaTN : num 0.9301 0.1667 0.0685 0.0995 0.0155 ... 888s ..- attr(*, "modelFit")=List of 5 888s .. ..$ method : chr "normalizeTumorBoost" 888s .. ..$ flavor : chr "v4" 888s .. ..$ delta : num [1:44010] -0.17264 0.00239 0.1671 0.16085 0.04213 ... 888s .. .. ..- attr(*, "modelFit")=List of 1 888s .. .. .. ..$ :List of 7 888s .. .. .. .. ..$ flavor : chr "density" 888s .. .. .. .. ..$ cn : int 2 888s .. .. .. .. ..$ nbrOfGenotypeGroups: int 3 888s .. .. .. .. ..$ tau : num [1:2] 0.312 0.678 888s .. .. .. .. ..$ n : int 43920 888s .. .. .. .. ..$ fit :Classes ‘PeaksAndValleys’ and 'data.frame': 5 obs. of 3 variables: 888s .. .. .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 888s .. .. .. .. .. ..$ x : num [1:5] 0.0999 0.312 0.4986 0.6775 0.8922 888s .. .. .. .. .. ..$ density: num [1:5] 1.622 0.465 1.125 0.496 1.587 888s .. .. .. .. ..$ fitValleys :Classes ‘PeaksAndValleys’ and 'data.frame': 2 obs. of 3 variables: 888s .. .. .. .. .. ..$ type : chr [1:2] "valley" "valley" 888s .. .. .. .. .. ..$ x : num [1:2] 0.312 0.678 888s .. .. .. .. .. ..$ density: num [1:2] 0.465 0.496 888s .. .. .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 888s .. ..$ preserveScale: logi FALSE 888s .. ..$ scaleFactor : num NA 888s $ betaN : num 0.8274 0.5072 0.1671 0.1609 0.0421 ... 888s $ muN : num 1 0.5 0 0 0 0 1 0 1 0.5 ... 888s ..- attr(*, "modelFit")=List of 1 888s .. ..$ :List of 7 888s .. .. ..$ flavor : chr "density" 888s .. .. ..$ cn : int 2 888s .. .. ..$ nbrOfGenotypeGroups: int 3 888s .. .. ..$ tau : num [1:2] 0.312 0.678 888s .. .. ..$ n : int 43920 888s .. .. ..$ fit :Classes ‘PeaksAndValleys’ and 'data.frame': 5 obs. of 3 variables: 888s .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 888s .. .. .. ..$ x : num [1:5] 0.0999 0.312 0.4986 0.6775 0.8922 888s .. .. .. ..$ density: num [1:5] 1.622 0.465 1.125 0.496 1.587 888s .. .. ..$ fitValleys :Classes ‘PeaksAndValleys’ and 'data.frame': 2 obs. of 3 variables: 888s .. .. .. ..$ type : chr [1:2] "valley" "valley" 888s .. .. .. ..$ x : num [1:2] 0.312 0.678 888s .. .. .. ..$ density: num [1:2] 0.465 0.496 888s .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 888s Setup up data...done 888s Dropping loci for which TCNs are missing... 888s Number of loci dropped: 36 888s Dropping loci for which TCNs are missing...done 888s Ordering data along genome... 888s 'data.frame': 43974 obs. of 7 variables: 888s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 888s $ x : num 554484 730720 782343 878522 916294 ... 888s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 888s $ betaT : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 888s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 888s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 888s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 888s Ordering data along genome...done 888s Segmenting multiple chromosomes... 888s Number of chromosomes: 3 888s Random seed temporarily set (seed=c(48879), kind="L'Ecuyer-CMRG") 888s Produced 3 seeds from this stream for future usage 888s Chromosome #1 ('Chr01') of 3... 888s 'data.frame': 14658 obs. of 8 variables: 888s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 888s $ x : num 554484 730720 782343 878522 916294 ... 888s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 888s $ betaT : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 888s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 888s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 888s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 888s $ index : int 1 2 3 4 5 6 7 8 9 10 ... 888s Known segments: 888s [1] chromosome start end 888s <0 rows> (or 0-length row.names) 888s Segmenting paired tumor-normal signals using Paired PSCBS... 888s Setup up data... 888s 'data.frame': 14658 obs. of 7 variables: 888s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 888s $ x : num 554484 730720 782343 878522 916294 ... 888s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 888s $ betaT : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 888s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 888s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 888s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 888s Setup up data...done 888s Ordering data along genome... 888s 'data.frame': 14658 obs. of 7 variables: 888s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 888s $ x : num 554484 730720 782343 878522 916294 ... 888s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 888s $ betaT : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 888s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 888s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 888s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 888s Ordering data along genome...done 888s Keeping only current chromosome for 'knownSegments'... 888s Chromosome: 1 888s Known segments for this chromosome: 888s [1] chromosome start end 888s <0 rows> (or 0-length row.names) 888s Keeping only current chromosome for 'knownSegments'...done 888s alphaTCN: 0.009 888s alphaDH: 0.001 888s Number of loci: 14658 888s Calculating DHs... 888s Number of SNPs: 14658 888s Number of heterozygous SNPs: 4209 (28.71%) 888s Normalized DHs: 888s num [1:14658] NA NA NA NA NA ... 888s Calculating DHs...done 888s Random seed temporarily set (seed=c(10407, 1066287653, -51199871, 161854402, -1995183193, 1503453565, -747102133), kind="L'Ecuyer-CMRG") 888s Produced 2 seeds from this stream for future usage 888s Identification of change points by total copy numbers... 888s Segmenting by CBS... 888s Chromosome: 1 889s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 889s Segmenting by CBS...done 889s List of 4 889s $ data :'data.frame': 14658 obs. of 4 variables: 889s ..$ chromosome: int [1:14658] 1 1 1 1 1 1 1 1 1 1 ... 889s ..$ x : num [1:14658] 554484 730720 782343 878522 916294 ... 889s ..$ y : num [1:14658] 1.88 1.8 1.59 1.64 1.53 ... 889s ..$ index : int [1:14658] 1 2 3 4 5 6 7 8 9 10 ... 889s $ output :'data.frame': 3 obs. of 6 variables: 889s ..$ sampleName: chr [1:3] NA NA NA 889s ..$ chromosome: int [1:3] 1 1 1 889s ..$ start : num [1:3] 5.54e+05 1.44e+08 1.85e+08 889s ..$ end : num [1:3] 1.44e+08 1.85e+08 2.47e+08 889s ..$ nbrOfLoci : int [1:3] 7599 2668 4391 889s ..$ mean : num [1:3] 1.39 2.07 2.63 889s $ segRows:'data.frame': 3 obs. of 2 variables: 889s ..$ startRow: int [1:3] 1 7600 10268 889s ..$ endRow : int [1:3] 7599 10267 14658 889s $ params :List of 5 889s ..$ alpha : num 0.009 889s ..$ undo : num 0 889s ..$ joinSegments : logi TRUE 889s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 889s .. ..$ chromosome: int 1 889s .. ..$ start : num -Inf 889s .. ..$ end : num Inf 889s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 889s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 889s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.38 0 0.381 0 0 889s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 889s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 889s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 889s Identification of change points by total copy numbers...done 889s Restructure TCN segmentation results... 889s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean 889s 1 1 554484 143926517 7599 1.3859 889s 2 1 143926517 185449813 2668 2.0704 889s 3 1 185449813 247137334 4391 2.6341 889s Number of TCN segments: 3 889s Restructure TCN segmentation results...done 889s Total CN segment #1 ([ 554484,1.43927e+08]) of 3... 889s Number of TCN loci in segment: 7599 889s Locus data for TCN segment: 889s 'data.frame': 7599 obs. of 9 variables: 889s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 889s $ x : num 554484 730720 782343 878522 916294 ... 889s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 889s $ betaT : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 889s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 889s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 889s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 889s $ index : int 1 2 3 4 5 6 7 8 9 10 ... 889s $ rho : num NA NA NA NA NA ... 889s Number of loci: 7599 889s Number of SNPs: 2120 (27.90%) 889s Number of heterozygous SNPs: 2120 (100.00%) 889s Chromosome: 1 889s Segmenting DH signals... 889s Segmenting by CBS... 889s Chromosome: 1 889s Random seed temporarily set (seed=c(10407, -821273412, -52578226, 1415511586, 721384351, -665928286, 1316562960), kind="L'Ecuyer-CMRG") 889s Segmenting by CBS...done 889s List of 4 889s $ data :'data.frame': 7599 obs. of 4 variables: 889s ..$ chromosome: int [1:7599] 1 1 1 1 1 1 1 1 1 1 ... 889s ..$ x : num [1:7599] 554484 730720 782343 878522 916294 ... 889s ..$ y : num [1:7599] NA NA NA NA NA ... 889s ..$ index : int [1:7599] 1 2 3 4 5 6 7 8 9 10 ... 889s $ output :'data.frame': 1 obs. of 6 variables: 889s ..$ sampleName: chr NA 889s ..$ chromosome: int 1 889s ..$ start : num 554484 889s ..$ end : num 1.44e+08 889s ..$ nbrOfLoci : int 2120 889s ..$ mean : num 0.51 889s $ segRows:'data.frame': 1 obs. of 2 variables: 889s ..$ startRow: int 10 889s ..$ endRow : int 7594 889s $ params :List of 5 889s ..$ alpha : num 0.001 889s ..$ undo : num 0 889s ..$ joinSegments : logi TRUE 889s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 889s .. ..$ chromosome: int 1 889s .. ..$ start : num 554484 889s .. ..$ end : num 1.44e+08 889s ..$ seed : int [1:7] 10407 -821273412 -52578226 1415511586 721384351 -665928286 1316562960 889s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 889s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.026 0 0.025 0 0 889s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 889s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 889s - attr(*, "randomSeed")= int [1:7] 10407 -821273412 -52578226 1415511586 721384351 -665928286 1316562960 889s DH segmentation (locally-indexed) rows: 889s startRow endRow 889s 1 10 7594 889s int [1:7599] 1 2 3 4 5 6 7 8 9 10 ... 889s DH segmentation rows: 889s startRow endRow 889s 1 10 7594 889s Segmenting DH signals...done 889s DH segmentation table: 889s dhStart dhEnd dhNbrOfLoci dhMean 889s 1 554484 143926517 2120 0.5101 889s startRow endRow 889s 1 10 7594 889s Rows: 889s [1] 1 889s TCN segmentation rows: 889s startRow endRow 889s 1 1 7599 889s TCN and DH segmentation rows: 889s startRow endRow 889s 1 1 7599 889s startRow endRow 889s 1 10 7594 889s NULL 889s TCN segmentation (expanded) rows: 889s startRow endRow 889s 1 1 7599 889s TCN and DH segmentation rows: 889s startRow endRow 889s 1 1 7599 889s 2 7600 10267 889s 3 10268 14658 889s startRow endRow 889s 1 10 7594 889s startRow endRow 889s 1 1 7599 889s Total CN segmentation table (expanded): 889s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 889s 1 1 554484 143926517 7599 1.3859 2120 2120 889s (TCN,DH) segmentation for one total CN segment: 889s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 889s 1 1 1 1 554484 143926517 7599 1.3859 2120 889s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 889s 1 2120 554484 143926517 2120 0.5101 889s Total CN segment #1 ([ 554484,1.43927e+08]) of 3...done 889s Total CN segment #2 ([1.43927e+08,1.8545e+08]) of 3... 889s Number of TCN loci in segment: 2668 889s Locus data for TCN segment: 889s 'data.frame': 2668 obs. of 9 variables: 889s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 889s $ x : num 1.44e+08 1.44e+08 1.44e+08 1.44e+08 1.44e+08 ... 889s $ CT : num 2.1 2.1 2.09 1.8 2.34 ... 889s $ betaT : num 0.027542 1.030222 1.094093 0.046763 -0.000948 ... 889s $ betaTN : num 0.027542 1.030222 1.094093 0.046763 -0.000948 ... 889s $ betaN : num 0.1624 0.8788 0.8225 0.1201 0.0317 ... 889s $ muN : num 0 1 1 0 0 1 0 0 0 0 ... 889s $ index : int 7600 7601 7602 7603 7604 7605 7606 7607 7608 7609 ... 889s $ rho : num NA NA NA NA NA NA NA NA NA NA ... 889s Number of loci: 2668 889s Number of SNPs: 775 (29.05%) 889s Number of heterozygous SNPs: 775 (100.00%) 889s Chromosome: 1 889s Segmenting DH signals... 889s Segmenting by CBS... 889s Chromosome: 1 889s Random seed temporarily set (seed=c(10407, -821273412, -52578226, 1415511586, 721384351, -665928286, 1316562960), kind="L'Ecuyer-CMRG") 889s Segmenting by CBS...done 889s List of 4 889s $ data :'data.frame': 2668 obs. of 4 variables: 889s ..$ chromosome: int [1:2668] 1 1 1 1 1 1 1 1 1 1 ... 889s ..$ x : num [1:2668] 1.44e+08 1.44e+08 1.44e+08 1.44e+08 1.44e+08 ... 889s ..$ y : num [1:2668] NA NA NA NA NA NA NA NA NA NA ... 889s ..$ index : int [1:2668] 1 2 3 4 5 6 7 8 9 10 ... 889s $ output :'data.frame': 1 obs. of 6 variables: 889s ..$ sampleName: chr NA 889s ..$ chromosome: int 1 889s ..$ start : num 1.44e+08 889s ..$ end : num 1.85e+08 889s ..$ nbrOfLoci : int 775 889s ..$ mean : num 0.097 889s $ segRows:'data.frame': 1 obs. of 2 variables: 889s ..$ startRow: int 15 889s ..$ endRow : int 2664 889s $ params :List of 5 889s ..$ alpha : num 0.001 889s ..$ undo : num 0 889s ..$ joinSegments : logi TRUE 889s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 889s .. ..$ chromosome: int 1 889s .. ..$ start : num 1.44e+08 889s .. ..$ end : num 1.85e+08 889s ..$ seed : int [1:7] 10407 -821273412 -52578226 1415511586 721384351 -665928286 1316562960 889s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 889s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.008 0 0.009 0 0 889s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 889s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 889s - attr(*, "randomSeed")= int [1:7] 10407 -821273412 -52578226 1415511586 721384351 -665928286 1316562960 889s DH segmentation (locally-indexed) rows: 889s startRow endRow 889s 1 15 2664 889s int [1:2668] 7600 7601 7602 7603 7604 7605 7606 7607 7608 7609 ... 889s DH segmentation rows: 889s startRow endRow 889s 1 7614 10263 889s Segmenting DH signals...done 889s DH segmentation table: 889s dhStart dhEnd dhNbrOfLoci dhMean 889s 1 143926517 185449813 775 0.097 889s startRow endRow 889s 1 7614 10263 889s Rows: 889s [1] 2 889s TCN segmentation rows: 889s startRow endRow 889s 2 7600 10267 889s TCN and DH segmentation rows: 889s startRow endRow 889s 2 7600 10267 889s startRow endRow 889s 1 7614 10263 889s startRow endRow 889s 1 1 7599 889s TCN segmentation (expanded) rows: 889s startRow endRow 889s 1 1 7599 889s 2 7600 10267 889s TCN and DH segmentation rows: 889s startRow endRow 889s 1 1 7599 889s 2 7600 10267 889s 3 10268 14658 889s startRow endRow 889s 1 10 7594 889s 2 7614 10263 889s startRow endRow 889s 1 1 7599 889s 2 7600 10267 889s Total CN segmentation table (expanded): 889s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 889s 2 1 143926517 185449813 2668 2.0704 775 775 889s (TCN,DH) segmentation for one total CN segment: 889s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 889s 2 2 1 1 143926517 185449813 2668 2.0704 775 889s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 889s 2 775 143926517 185449813 775 0.097 889s Total CN segment #2 ([1.43927e+08,1.8545e+08]) of 3...done 889s Total CN segment #3 ([1.8545e+08,2.47137e+08]) of 3... 889s Number of TCN loci in segment: 4391 889s Locus data for TCN segment: 889s 'data.frame': 4391 obs. of 9 variables: 889s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 889s $ x : num 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 889s $ CT : num 2.93 2.15 2.82 2.93 2.46 ... 889s $ betaT : num -0.169 0.609 1.028 0.525 0.968 ... 889s $ betaTN : num -0.169 0.609 1.028 0.525 0.968 ... 889s $ betaN : num 0.25 0.38 0.919 0.34 0.783 ... 889s $ muN : num 0 0.5 1 0.5 1 1 0 1 0 1 ... 889s $ index : int 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 889s $ rho : num NA 0.2186 NA 0.0503 NA ... 889s Number of loci: 4391 889s Number of SNPs: 1314 (29.92%) 889s Number of heterozygous SNPs: 1314 (100.00%) 889s Chromosome: 1 889s Segmenting DH signals... 889s Segmenting by CBS... 889s Chromosome: 1 889s Random seed temporarily set (seed=c(10407, -821273412, -52578226, 1415511586, 721384351, -665928286, 1316562960), kind="L'Ecuyer-CMRG") 889s Segmenting by CBS...done 889s List of 4 889s $ data :'data.frame': 4391 obs. of 4 variables: 889s ..$ chromosome: int [1:4391] 1 1 1 1 1 1 1 1 1 1 ... 889s ..$ x : num [1:4391] 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 889s ..$ y : num [1:4391] NA 0.2186 NA 0.0503 NA ... 889s ..$ index : int [1:4391] 1 2 3 4 5 6 7 8 9 10 ... 889s $ output :'data.frame': 1 obs. of 6 variables: 889s ..$ sampleName: chr NA 889s ..$ chromosome: int 1 889s ..$ start : num 1.85e+08 889s ..$ end : num 2.47e+08 889s ..$ nbrOfLoci : int 1314 889s ..$ mean : num 0.23 889s $ segRows:'data.frame': 1 obs. of 2 variables: 889s ..$ startRow: int 2 889s ..$ endRow : int 4388 889s $ params :List of 5 889s ..$ alpha : num 0.001 889s ..$ undo : num 0 889s ..$ joinSegments : logi TRUE 889s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 889s .. ..$ chromosome: int 1 889s .. ..$ start : num 1.85e+08 889s .. ..$ end : num 2.47e+08 889s ..$ seed : int [1:7] 10407 -821273412 -52578226 1415511586 721384351 -665928286 1316562960 889s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 889s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.015 0 0.015 0 0 889s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 889s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 889s - attr(*, "randomSeed")= int [1:7] 10407 -821273412 -52578226 1415511586 721384351 -665928286 1316562960 889s DH segmentation (locally-indexed) rows: 889s startRow endRow 889s 1 2 4388 889s int [1:4391] 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 889s DH segmentation rows: 889s startRow endRow 889s 1 10269 14655 889s Segmenting DH signals...done 889s DH segmentation table: 889s dhStart dhEnd dhNbrOfLoci dhMean 889s 1 185449813 247137334 1314 0.2295 889s startRow endRow 889s 1 10269 14655 889s Rows: 889s [1] 3 889s TCN segmentation rows: 889s startRow endRow 889s 3 10268 14658 889s TCN and DH segmentation rows: 889s startRow endRow 889s 3 10268 14658 889s startRow endRow 889s 1 10269 14655 889s startRow endRow 889s 1 1 7599 889s 2 7600 10267 889s TCN segmentation (expanded) rows: 889s startRow endRow 889s 1 1 7599 889s 2 7600 10267 889s 3 10268 14658 889s TCN and DH segmentation rows: 889s startRow endRow 889s 1 1 7599 889s 2 7600 10267 889s 3 10268 14658 889s startRow endRow 889s 1 10 7594 889s 2 7614 10263 889s 3 10269 14655 889s startRow endRow 889s 1 1 7599 889s 2 7600 10267 889s 3 10268 14658 889s Total CN segmentation table (expanded): 889s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 889s 3 1 185449813 247137334 4391 2.6341 1314 1314 889s (TCN,DH) segmentation for one total CN segment: 889s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 889s 3 3 1 1 185449813 247137334 4391 2.6341 1314 889s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 889s 3 1314 185449813 247137334 1314 0.2295 889s Total CN segment #3 ([1.8545e+08,2.47137e+08]) of 3...done 889s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 889s 1 1 1 1 554484 143926517 7599 1.3859 2120 889s 2 1 2 1 143926517 185449813 2668 2.0704 775 889s 3 1 3 1 185449813 247137334 4391 2.6341 1314 889s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 889s 1 2120 554484 143926517 2120 0.5101 889s 2 775 143926517 185449813 775 0.0970 889s 3 1314 185449813 247137334 1314 0.2295 889s Calculating (C1,C2) per segment... 889s Calculating (C1,C2) per segment...done 889s Number of segments: 3 889s Segmenting paired tumor-normal signals using Paired PSCBS...done 889s Post-segmenting TCNs... 889s Number of segments: 3 889s Number of chromosomes: 1 889s [1] 1 889s Chromosome 1 ('chr01') of 1... 889s Rows: 889s [1] 1 2 3 889s Number of segments: 3 889s TCN segment #1 ('1') of 3... 889s Nothing todo. Only one DH segmentation. Skipping. 889s TCN segment #1 ('1') of 3...done 889s TCN segment #2 ('2') of 3... 889s Nothing todo. Only one DH segmentation. Skipping. 889s TCN segment #2 ('2') of 3...done 889s TCN segment #3 ('3') of 3... 889s Nothing todo. Only one DH segmentation. Skipping. 889s TCN segment #3 ('3') of 3...done 889s Chromosome 1 ('chr01') of 1...done 889s Update (C1,C2) per segment... 889s Update (C1,C2) per segment...done 889s Post-segmenting TCNs...done 889s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 889s 1 1 1 1 554484 143926517 7599 1.3859 2120 889s 2 1 2 1 143926517 185449813 2668 2.0704 775 889s 3 1 3 1 185449813 247137334 4391 2.6341 1314 889s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 889s 1 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 889s 2 775 143926517 185449813 775 0.0970 0.9347856 1.135614 889s 3 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 889s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 889s 1 1 1 1 554484 143926517 7599 1.3859 2120 889s 2 1 2 1 143926517 185449813 2668 2.0704 775 889s 3 1 3 1 185449813 247137334 4391 2.6341 1314 889s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 889s 1 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 889s 2 775 143926517 185449813 775 0.0970 0.9347856 1.135614 889s 3 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 889s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 889s 1 1 1 1 554484 143926517 7599 1.3859 2120 889s 2 1 2 1 143926517 185449813 2668 2.0704 775 889s 3 1 3 1 185449813 247137334 4391 2.6341 1314 889s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 889s 1 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 889s 2 775 143926517 185449813 775 0.0970 0.9347856 1.135614 889s 3 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 889s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 889s 1 1 1 1 554484 143926517 7599 1.3859 2120 889s 2 1 2 1 143926517 185449813 2668 2.0704 775 889s 3 1 3 1 185449813 247137334 4391 2.6341 1314 889s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 889s 1 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 889s 2 775 143926517 185449813 775 0.0970 0.9347856 1.135614 889s 3 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 889s Chromosome #1 ('Chr01') of 3...done 889s Chromosome #2 ('Chr02') of 3... 889s 'data.frame': 14658 obs. of 8 variables: 889s $ chromosome: int 2 2 2 2 2 2 2 2 2 2 ... 889s $ x : num 554484 730720 782343 878522 916294 ... 889s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 889s $ betaT : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 889s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 889s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 889s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 889s $ index : int 14659 14660 14661 14662 14663 14664 14665 14666 14667 14668 ... 889s Known segments: 889s [1] chromosome start end 889s <0 rows> (or 0-length row.names) 889s Segmenting paired tumor-normal signals using Paired PSCBS... 889s Setup up data... 889s 'data.frame': 14658 obs. of 7 variables: 889s $ chromosome: int 2 2 2 2 2 2 2 2 2 2 ... 889s $ x : num 554484 730720 782343 878522 916294 ... 889s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 889s $ betaT : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 889s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 889s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 889s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 889s Setup up data...done 889s Ordering data along genome... 889s 'data.frame': 14658 obs. of 7 variables: 889s $ chromosome: int 2 2 2 2 2 2 2 2 2 2 ... 889s $ x : num 554484 730720 782343 878522 916294 ... 889s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 889s $ betaT : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 889s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 889s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 889s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 889s Ordering data along genome...done 889s Keeping only current chromosome for 'knownSegments'... 889s Chromosome: 2 889s Known segments for this chromosome: 889s [1] chromosome start end 889s <0 rows> (or 0-length row.names) 889s Keeping only current chromosome for 'knownSegments'...done 889s alphaTCN: 0.009 889s alphaDH: 0.001 889s Number of loci: 14658 889s Calculating DHs... 889s Number of SNPs: 14658 889s Number of heterozygous SNPs: 4209 (28.71%) 889s Normalized DHs: 889s num [1:14658] NA NA NA NA NA ... 889s Calculating DHs...done 889s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 889s Produced 2 seeds from this stream for future usage 889s Identification of change points by total copy numbers... 889s Segmenting by CBS... 889s Chromosome: 2 889s Random seed temporarily set (seed=c(10407, -821273412, -52578226, 1415511586, 721384351, -665928286, 1316562960), kind="L'Ecuyer-CMRG") 890s Segmenting by CBS...done 890s List of 4 890s $ data :'data.frame': 14658 obs. of 4 variables: 890s ..$ chromosome: int [1:14658] 2 2 2 2 2 2 2 2 2 2 ... 890s ..$ x : num [1:14658] 554484 730720 782343 878522 916294 ... 890s ..$ y : num [1:14658] 1.88 1.8 1.59 1.64 1.53 ... 890s ..$ index : int [1:14658] 1 2 3 4 5 6 7 8 9 10 ... 890s $ output :'data.frame': 3 obs. of 6 variables: 890s ..$ sampleName: chr [1:3] NA NA NA 890s ..$ chromosome: int [1:3] 2 2 2 890s ..$ start : num [1:3] 5.54e+05 1.44e+08 1.85e+08 890s ..$ end : num [1:3] 1.44e+08 1.85e+08 2.47e+08 890s ..$ nbrOfLoci : int [1:3] 7599 2668 4391 890s ..$ mean : num [1:3] 1.39 2.07 2.63 890s $ segRows:'data.frame': 3 obs. of 2 variables: 890s ..$ startRow: int [1:3] 1 7600 10268 890s ..$ endRow : int [1:3] 7599 10267 14658 890s $ params :List of 5 890s ..$ alpha : num 0.009 890s ..$ undo : num 0 890s ..$ joinSegments : logi TRUE 890s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 890s .. ..$ chromosome: int 2 890s .. ..$ start : num -Inf 890s .. ..$ end : num Inf 890s ..$ seed : int [1:7] 10407 -821273412 -52578226 1415511586 721384351 -665928286 1316562960 890s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 890s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.403 0 0.403 0 0 890s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 890s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 890s - attr(*, "randomSeed")= int [1:7] 10407 -821273412 -52578226 1415511586 721384351 -665928286 1316562960 890s Identification of change points by total copy numbers...done 890s Restructure TCN segmentation results... 890s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean 890s 1 2 554484 143926517 7599 1.3859 890s 2 2 143926517 185449813 2668 2.0704 890s 3 2 185449813 247137334 4391 2.6341 890s Number of TCN segments: 3 890s Restructure TCN segmentation results...done 890s Total CN segment #1 ([ 554484,1.43927e+08]) of 3... 890s Number of TCN loci in segment: 7599 890s Locus data for TCN segment: 890s 'data.frame': 7599 obs. of 9 variables: 890s $ chromosome: int 2 2 2 2 2 2 2 2 2 2 ... 890s $ x : num 554484 730720 782343 878522 916294 ... 890s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 890s $ betaT : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 890s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 890s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 890s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 890s $ index : int 1 2 3 4 5 6 7 8 9 10 ... 890s $ rho : num NA NA NA NA NA ... 890s Number of loci: 7599 890s Number of SNPs: 2120 (27.90%) 890s Number of heterozygous SNPs: 2120 (100.00%) 890s Chromosome: 2 890s Segmenting DH signals... 890s Segmenting by CBS... 890s Chromosome: 2 890s Random seed temporarily set (seed=c(10407, -1924040949, -1632234809, -437763632, -1464377300, 676654412, 2080370711), kind="L'Ecuyer-CMRG") 890s Segmenting by CBS...done 890s List of 4 890s $ data :'data.frame': 7599 obs. of 4 variables: 890s ..$ chromosome: int [1:7599] 2 2 2 2 2 2 2 2 2 2 ... 890s ..$ x : num [1:7599] 554484 730720 782343 878522 916294 ... 890s ..$ y : num [1:7599] NA NA NA NA NA ... 890s ..$ index : int [1:7599] 1 2 3 4 5 6 7 8 9 10 ... 890s $ output :'data.frame': 1 obs. of 6 variables: 890s ..$ sampleName: chr NA 890s ..$ chromosome: int 2 890s ..$ start : num 554484 890s ..$ end : num 1.44e+08 890s ..$ nbrOfLoci : int 2120 890s ..$ mean : num 0.51 890s $ segRows:'data.frame': 1 obs. of 2 variables: 890s ..$ startRow: int 10 890s ..$ endRow : int 7594 890s $ params :List of 5 890s ..$ alpha : num 0.001 890s ..$ undo : num 0 890s ..$ joinSegments : logi TRUE 890s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 890s .. ..$ chromosome: int 2 890s .. ..$ start : num 554484 890s .. ..$ end : num 1.44e+08 890s ..$ seed : int [1:7] 10407 -1924040949 -1632234809 -437763632 -1464377300 676654412 2080370711 890s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 890s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.025 0 0.025 0 0 890s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 890s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 890s - attr(*, "randomSeed")= int [1:7] 10407 -1924040949 -1632234809 -437763632 -1464377300 676654412 2080370711 890s DH segmentation (locally-indexed) rows: 890s startRow endRow 890s 1 10 7594 890s int [1:7599] 1 2 3 4 5 6 7 8 9 10 ... 890s DH segmentation rows: 890s startRow endRow 890s 1 10 7594 890s Segmenting DH signals...done 890s DH segmentation table: 890s dhStart dhEnd dhNbrOfLoci dhMean 890s 1 554484 143926517 2120 0.5101 890s startRow endRow 890s 1 10 7594 890s Rows: 890s [1] 1 890s TCN segmentation rows: 890s startRow endRow 890s 1 1 7599 890s TCN and DH segmentation rows: 890s startRow endRow 890s 1 1 7599 890s startRow endRow 890s 1 10 7594 890s NULL 890s TCN segmentation (expanded) rows: 890s startRow endRow 890s 1 1 7599 890s TCN and DH segmentation rows: 890s startRow endRow 890s 1 1 7599 890s 2 7600 10267 890s 3 10268 14658 890s startRow endRow 890s 1 10 7594 890s startRow endRow 890s 1 1 7599 890s Total CN segmentation table (expanded): 890s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 890s 1 2 554484 143926517 7599 1.3859 2120 2120 890s (TCN,DH) segmentation for one total CN segment: 890s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 890s 1 1 1 2 554484 143926517 7599 1.3859 2120 890s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 890s 1 2120 554484 143926517 2120 0.5101 890s Total CN segment #1 ([ 554484,1.43927e+08]) of 3...done 890s Total CN segment #2 ([1.43927e+08,1.8545e+08]) of 3... 890s Number of TCN loci in segment: 2668 890s Locus data for TCN segment: 890s 'data.frame': 2668 obs. of 9 variables: 890s $ chromosome: int 2 2 2 2 2 2 2 2 2 2 ... 890s $ x : num 1.44e+08 1.44e+08 1.44e+08 1.44e+08 1.44e+08 ... 890s $ CT : num 2.1 2.1 2.09 1.8 2.34 ... 890s $ betaT : num 0.027542 1.030222 1.094093 0.046763 -0.000948 ... 890s $ betaTN : num 0.027542 1.030222 1.094093 0.046763 -0.000948 ... 890s $ betaN : num 0.1624 0.8788 0.8225 0.1201 0.0317 ... 890s $ muN : num 0 1 1 0 0 1 0 0 0 0 ... 890s $ index : int 7600 7601 7602 7603 7604 7605 7606 7607 7608 7609 ... 890s $ rho : num NA NA NA NA NA NA NA NA NA NA ... 890s Number of loci: 2668 890s Number of SNPs: 775 (29.05%) 890s Number of heterozygous SNPs: 775 (100.00%) 890s Chromosome: 2 890s Segmenting DH signals... 890s Segmenting by CBS... 890s Chromosome: 2 890s Random seed temporarily set (seed=c(10407, -1924040949, -1632234809, -437763632, -1464377300, 676654412, 2080370711), kind="L'Ecuyer-CMRG") 890s Segmenting by CBS...done 890s List of 4 890s $ data :'data.frame': 2668 obs. of 4 variables: 890s ..$ chromosome: int [1:2668] 2 2 2 2 2 2 2 2 2 2 ... 890s ..$ x : num [1:2668] 1.44e+08 1.44e+08 1.44e+08 1.44e+08 1.44e+08 ... 890s ..$ y : num [1:2668] NA NA NA NA NA NA NA NA NA NA ... 890s ..$ index : int [1:2668] 1 2 3 4 5 6 7 8 9 10 ... 890s $ output :'data.frame': 1 obs. of 6 variables: 890s ..$ sampleName: chr NA 890s ..$ chromosome: int 2 890s ..$ start : num 1.44e+08 890s ..$ end : num 1.85e+08 890s ..$ nbrOfLoci : int 775 890s ..$ mean : num 0.097 890s $ segRows:'data.frame': 1 obs. of 2 variables: 890s ..$ startRow: int 15 890s ..$ endRow : int 2664 890s $ params :List of 5 890s ..$ alpha : num 0.001 890s ..$ undo : num 0 890s ..$ joinSegments : logi TRUE 890s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 890s .. ..$ chromosome: int 2 890s .. ..$ start : num 1.44e+08 890s .. ..$ end : num 1.85e+08 890s ..$ seed : int [1:7] 10407 -1924040949 -1632234809 -437763632 -1464377300 676654412 2080370711 890s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 890s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.008 0 0.008 0 0 890s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 890s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 890s - attr(*, "randomSeed")= int [1:7] 10407 -1924040949 -1632234809 -437763632 -1464377300 676654412 2080370711 890s DH segmentation (locally-indexed) rows: 890s startRow endRow 890s 1 15 2664 890s int [1:2668] 7600 7601 7602 7603 7604 7605 7606 7607 7608 7609 ... 890s DH segmentation rows: 890s startRow endRow 890s 1 7614 10263 890s Segmenting DH signals...done 890s DH segmentation table: 890s dhStart dhEnd dhNbrOfLoci dhMean 890s 1 143926517 185449813 775 0.097 890s startRow endRow 890s 1 7614 10263 890s Rows: 890s [1] 2 890s TCN segmentation rows: 890s startRow endRow 890s 2 7600 10267 890s TCN and DH segmentation rows: 890s startRow endRow 890s 2 7600 10267 890s startRow endRow 890s 1 7614 10263 890s startRow endRow 890s 1 1 7599 890s TCN segmentation (expanded) rows: 890s startRow endRow 890s 1 1 7599 890s 2 7600 10267 890s TCN and DH segmentation rows: 890s startRow endRow 890s 1 1 7599 890s 2 7600 10267 890s 3 10268 14658 890s startRow endRow 890s 1 10 7594 890s 2 7614 10263 890s startRow endRow 890s 1 1 7599 890s 2 7600 10267 890s Total CN segmentation table (expanded): 890s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 890s 2 2 143926517 185449813 2668 2.0704 775 775 890s (TCN,DH) segmentation for one total CN segment: 890s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 890s 2 2 1 2 143926517 185449813 2668 2.0704 775 890s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 890s 2 775 143926517 185449813 775 0.097 890s Total CN segment #2 ([1.43927e+08,1.8545e+08]) of 3...done 890s Total CN segment #3 ([1.8545e+08,2.47137e+08]) of 3... 890s Number of TCN loci in segment: 4391 890s Locus data for TCN segment: 890s 'data.frame': 4391 obs. of 9 variables: 890s $ chromosome: int 2 2 2 2 2 2 2 2 2 2 ... 890s $ x : num 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 890s $ CT : num 2.93 2.15 2.82 2.93 2.46 ... 890s $ betaT : num -0.169 0.609 1.028 0.525 0.968 ... 890s $ betaTN : num -0.169 0.609 1.028 0.525 0.968 ... 890s $ betaN : num 0.25 0.38 0.919 0.34 0.783 ... 890s $ muN : num 0 0.5 1 0.5 1 1 0 1 0 1 ... 890s $ index : int 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 890s $ rho : num NA 0.2186 NA 0.0503 NA ... 890s Number of loci: 4391 890s Number of SNPs: 1314 (29.92%) 890s Number of heterozygous SNPs: 1314 (100.00%) 890s Chromosome: 2 890s Segmenting DH signals... 890s Segmenting by CBS... 890s Chromosome: 2 890s Random seed temporarily set (seed=c(10407, -1924040949, -1632234809, -437763632, -1464377300, 676654412, 2080370711), kind="L'Ecuyer-CMRG") 890s Segmenting by CBS...done 890s List of 4 890s $ data :'data.frame': 4391 obs. of 4 variables: 890s ..$ chromosome: int [1:4391] 2 2 2 2 2 2 2 2 2 2 ... 890s ..$ x : num [1:4391] 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 890s ..$ y : num [1:4391] NA 0.2186 NA 0.0503 NA ... 890s ..$ index : int [1:4391] 1 2 3 4 5 6 7 8 9 10 ... 890s $ output :'data.frame': 1 obs. of 6 variables: 890s ..$ sampleName: chr NA 890s ..$ chromosome: int 2 890s ..$ start : num 1.85e+08 890s ..$ end : num 2.47e+08 890s ..$ nbrOfLoci : int 1314 890s ..$ mean : num 0.23 890s $ segRows:'data.frame': 1 obs. of 2 variables: 890s ..$ startRow: int 2 890s ..$ endRow : int 4388 890s $ params :List of 5 890s ..$ alpha : num 0.001 890s ..$ undo : num 0 890s ..$ joinSegments : logi TRUE 890s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 890s .. ..$ chromosome: int 2 890s .. ..$ start : num 1.85e+08 890s .. ..$ end : num 2.47e+08 890s ..$ seed : int [1:7] 10407 -1924040949 -1632234809 -437763632 -1464377300 676654412 2080370711 890s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 890s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.015 0 0.015 0 0 890s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 890s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 890s - attr(*, "randomSeed")= int [1:7] 10407 -1924040949 -1632234809 -437763632 -1464377300 676654412 2080370711 890s DH segmentation (locally-indexed) rows: 890s startRow endRow 890s 1 2 4388 890s int [1:4391] 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 890s DH segmentation rows: 890s startRow endRow 890s 1 10269 14655 890s Segmenting DH signals...done 890s DH segmentation table: 890s dhStart dhEnd dhNbrOfLoci dhMean 890s 1 185449813 247137334 1314 0.2295 890s startRow endRow 890s 1 10269 14655 890s Rows: 890s [1] 3 890s TCN segmentation rows: 890s startRow endRow 890s 3 10268 14658 890s TCN and DH segmentation rows: 890s startRow endRow 890s 3 10268 14658 890s startRow endRow 890s 1 10269 14655 890s startRow endRow 890s 1 1 7599 890s 2 7600 10267 890s TCN segmentation (expanded) rows: 890s startRow endRow 890s 1 1 7599 890s 2 7600 10267 890s 3 10268 14658 890s TCN and DH segmentation rows: 890s startRow endRow 890s 1 1 7599 890s 2 7600 10267 890s 3 10268 14658 890s startRow endRow 890s 1 10 7594 890s 2 7614 10263 890s 3 10269 14655 890s startRow endRow 890s 1 1 7599 890s 2 7600 10267 890s 3 10268 14658 890s Total CN segmentation table (expanded): 890s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 890s 3 2 185449813 247137334 4391 2.6341 1314 1314 890s (TCN,DH) segmentation for one total CN segment: 890s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 890s 3 3 1 2 185449813 247137334 4391 2.6341 1314 890s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 890s 3 1314 185449813 247137334 1314 0.2295 890s Total CN segment #3 ([1.8545e+08,2.47137e+08]) of 3...done 890s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 890s 1 2 1 1 554484 143926517 7599 1.3859 2120 890s 2 2 2 1 143926517 185449813 2668 2.0704 775 890s 3 2 3 1 185449813 247137334 4391 2.6341 1314 890s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 890s 1 2120 554484 143926517 2120 0.5101 890s 2 775 143926517 185449813 775 0.0970 890s 3 1314 185449813 247137334 1314 0.2295 890s Calculating (C1,C2) per segment... 890s Calculating (C1,C2) per segment...done 890s Number of segments: 3 890s Segmenting paired tumor-normal signals using Paired PSCBS...done 890s Post-segmenting TCNs... 890s Number of segments: 3 890s Number of chromosomes: 1 890s [1] 2 890s Chromosome 1 ('chr02') of 1... 890s Rows: 890s [1] 1 2 3 890s Number of segments: 3 890s TCN segment #1 ('1') of 3... 890s Nothing todo. Only one DH segmentation. Skipping. 890s TCN segment #1 ('1') of 3...done 890s TCN segment #2 ('2') of 3... 890s Nothing todo. Only one DH segmentation. Skipping. 890s TCN segment #2 ('2') of 3...done 890s TCN segment #3 ('3') of 3... 890s Nothing todo. Only one DH segmentation. Skipping. 890s TCN segment #3 ('3') of 3...done 890s Chromosome 1 ('chr02') of 1...done 890s Update (C1,C2) per segment... 890s Update (C1,C2) per segment...done 890s Post-segmenting TCNs...done 890s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 890s 1 2 1 1 554484 143926517 7599 1.3859 2120 890s 2 2 2 1 143926517 185449813 2668 2.0704 775 890s 3 2 3 1 185449813 247137334 4391 2.6341 1314 890s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 890s 1 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 890s 2 775 143926517 185449813 775 0.0970 0.9347856 1.135614 890s 3 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 890s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 890s 1 2 1 1 554484 143926517 7599 1.3859 2120 890s 2 2 2 1 143926517 185449813 2668 2.0704 775 890s 3 2 3 1 185449813 247137334 4391 2.6341 1314 890s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 890s 1 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 890s 2 775 143926517 185449813 775 0.0970 0.9347856 1.135614 890s 3 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 890s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 890s 1 2 1 1 554484 143926517 7599 1.3859 2120 890s 2 2 2 1 143926517 185449813 2668 2.0704 775 890s 3 2 3 1 185449813 247137334 4391 2.6341 1314 890s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 890s 1 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 890s 2 775 143926517 185449813 775 0.0970 0.9347856 1.135614 890s 3 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 890s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 890s 1 2 1 1 554484 143926517 7599 1.3859 2120 890s 2 2 2 1 143926517 185449813 2668 2.0704 775 890s 3 2 3 1 185449813 247137334 4391 2.6341 1314 890s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 890s 1 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 890s 2 775 143926517 185449813 775 0.0970 0.9347856 1.135614 890s 3 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 890s Chromosome #2 ('Chr02') of 3...done 890s Chromosome #3 ('Chr03') of 3... 890s 'data.frame': 14658 obs. of 8 variables: 890s $ chromosome: int 3 3 3 3 3 3 3 3 3 3 ... 890s $ x : num 554484 730720 782343 878522 916294 ... 890s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 890s $ betaT : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 890s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 890s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 890s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 890s $ index : int 29317 29318 29319 29320 29321 29322 29323 29324 29325 29326 ... 890s Known segments: 890s [1] chromosome start end 890s <0 rows> (or 0-length row.names) 890s Segmenting paired tumor-normal signals using Paired PSCBS... 890s Setup up data... 890s 'data.frame': 14658 obs. of 7 variables: 890s $ chromosome: int 3 3 3 3 3 3 3 3 3 3 ... 890s $ x : num 554484 730720 782343 878522 916294 ... 890s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 890s $ betaT : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 890s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 890s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 890s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 890s Setup up data...done 890s Ordering data along genome... 890s 'data.frame': 14658 obs. of 7 variables: 890s $ chromosome: int 3 3 3 3 3 3 3 3 3 3 ... 890s $ x : num 554484 730720 782343 878522 916294 ... 890s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 890s $ betaT : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 890s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 890s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 890s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 890s Ordering data along genome...done 890s Keeping only current chromosome for 'knownSegments'... 890s Chromosome: 3 890s Known segments for this chromosome: 890s [1] chromosome start end 890s <0 rows> (or 0-length row.names) 890s Keeping only current chromosome for 'knownSegments'...done 890s alphaTCN: 0.009 890s alphaDH: 0.001 890s Number of loci: 14658 890s Calculating DHs... 890s Number of SNPs: 14658 890s Number of heterozygous SNPs: 4209 (28.71%) 890s Normalized DHs: 890s num [1:14658] NA NA NA NA NA ... 890s Calculating DHs...done 890s Random seed temporarily set (seed=c(10407, -821273412, -52578226, 1415511586, 721384351, -665928286, 1316562960), kind="L'Ecuyer-CMRG") 890s Produced 2 seeds from this stream for future usage 890s Identification of change points by total copy numbers... 890s Segmenting by CBS... 890s Chromosome: 3 890s Random seed temporarily set (seed=c(10407, -1924040949, -1632234809, -437763632, -1464377300, 676654412, 2080370711), kind="L'Ecuyer-CMRG") 891s Segmenting by CBS...done 891s List of 4 891s $ data :'data.frame': 14658 obs. of 4 variables: 891s ..$ chromosome: int [1:14658] 3 3 3 3 3 3 3 3 3 3 ... 891s ..$ x : num [1:14658] 554484 730720 782343 878522 916294 ... 891s ..$ y : num [1:14658] 1.88 1.8 1.59 1.64 1.53 ... 891s ..$ index : int [1:14658] 1 2 3 4 5 6 7 8 9 10 ... 891s $ output :'data.frame': 3 obs. of 6 variables: 891s ..$ sampleName: chr [1:3] NA NA NA 891s ..$ chromosome: int [1:3] 3 3 3 891s ..$ start : num [1:3] 5.54e+05 1.44e+08 1.85e+08 891s ..$ end : num [1:3] 1.44e+08 1.85e+08 2.47e+08 891s ..$ nbrOfLoci : int [1:3] 7599 2668 4391 891s ..$ mean : num [1:3] 1.39 2.07 2.63 891s $ segRows:'data.frame': 3 obs. of 2 variables: 891s ..$ startRow: int [1:3] 1 7600 10268 891s ..$ endRow : int [1:3] 7599 10267 14658 891s $ params :List of 5 891s ..$ alpha : num 0.009 891s ..$ undo : num 0 891s ..$ joinSegments : logi TRUE 891s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 891s .. ..$ chromosome: int 3 891s .. ..$ start : num -Inf 891s .. ..$ end : num Inf 891s ..$ seed : int [1:7] 10407 -1924040949 -1632234809 -437763632 -1464377300 676654412 2080370711 891s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 891s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.383 0 0.383 0 0 891s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 891s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 891s - attr(*, "randomSeed")= int [1:7] 10407 -1924040949 -1632234809 -437763632 -1464377300 676654412 2080370711 891s Identification of change points by total copy numbers...done 891s Restructure TCN segmentation results... 891s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean 891s 1 3 554484 143926517 7599 1.3859 891s 2 3 143926517 185449813 2668 2.0704 891s 3 3 185449813 247137334 4391 2.6341 891s Number of TCN segments: 3 891s Restructure TCN segmentation results...done 891s Total CN segment #1 ([ 554484,1.43927e+08]) of 3... 891s Number of TCN loci in segment: 7599 891s Locus data for TCN segment: 891s 'data.frame': 7599 obs. of 9 variables: 891s $ chromosome: int 3 3 3 3 3 3 3 3 3 3 ... 891s $ x : num 554484 730720 782343 878522 916294 ... 891s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 891s $ betaT : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 891s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 891s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 891s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 891s $ index : int 1 2 3 4 5 6 7 8 9 10 ... 891s $ rho : num NA NA NA NA NA ... 891s Number of loci: 7599 891s Number of SNPs: 2120 (27.90%) 891s Number of heterozygous SNPs: 2120 (100.00%) 891s Chromosome: 3 891s Segmenting DH signals... 891s Segmenting by CBS... 891s Chromosome: 3 891s Random seed temporarily set (seed=c(10407, -1371615447, -889757879, 1692656974, -1723952224, 1378814990, 1816467252), kind="L'Ecuyer-CMRG") 891s Segmenting by CBS...done 891s List of 4 891s $ data :'data.frame': 7599 obs. of 4 variables: 891s ..$ chromosome: int [1:7599] 3 3 3 3 3 3 3 3 3 3 ... 891s ..$ x : num [1:7599] 554484 730720 782343 878522 916294 ... 891s ..$ y : num [1:7599] NA NA NA NA NA ... 891s ..$ index : int [1:7599] 1 2 3 4 5 6 7 8 9 10 ... 891s $ output :'data.frame': 1 obs. of 6 variables: 891s ..$ sampleName: chr NA 891s ..$ chromosome: int 3 891s ..$ start : num 554484 891s ..$ end : num 1.44e+08 891s ..$ nbrOfLoci : int 2120 891s ..$ mean : num 0.51 891s $ segRows:'data.frame': 1 obs. of 2 variables: 891s ..$ startRow: int 10 891s ..$ endRow : int 7594 891s $ params :List of 5 891s ..$ alpha : num 0.001 891s ..$ undo : num 0 891s ..$ joinSegments : logi TRUE 891s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 891s .. ..$ chromosome: int 3 891s .. ..$ start : num 554484 891s .. ..$ end : num 1.44e+08 891s ..$ seed : int [1:7] 10407 -1371615447 -889757879 1692656974 -1723952224 1378814990 1816467252 891s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 891s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.025 0 0.025 0 0 891s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 891s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 891s - attr(*, "randomSeed")= int [1:7] 10407 -1371615447 -889757879 1692656974 -1723952224 1378814990 1816467252 891s DH segmentation (locally-indexed) rows: 891s startRow endRow 891s 1 10 7594 891s int [1:7599] 1 2 3 4 5 6 7 8 9 10 ... 891s DH segmentation rows: 891s startRow endRow 891s 1 10 7594 891s Segmenting DH signals...done 891s DH segmentation table: 891s dhStart dhEnd dhNbrOfLoci dhMean 891s 1 554484 143926517 2120 0.5101 891s startRow endRow 891s 1 10 7594 891s Rows: 891s [1] 1 891s TCN segmentation rows: 891s startRow endRow 891s 1 1 7599 891s TCN and DH segmentation rows: 891s startRow endRow 891s 1 1 7599 891s startRow endRow 891s 1 10 7594 891s NULL 891s TCN segmentation (expanded) rows: 891s startRow endRow 891s 1 1 7599 891s TCN and DH segmentation rows: 891s startRow endRow 891s 1 1 7599 891s 2 7600 10267 891s 3 10268 14658 891s startRow endRow 891s 1 10 7594 891s startRow endRow 891s 1 1 7599 891s Total CN segmentation table (expanded): 891s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 891s 1 3 554484 143926517 7599 1.3859 2120 2120 891s (TCN,DH) segmentation for one total CN segment: 891s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 891s 1 1 1 3 554484 143926517 7599 1.3859 2120 891s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 891s 1 2120 554484 143926517 2120 0.5101 891s Total CN segment #1 ([ 554484,1.43927e+08]) of 3...done 891s Total CN segment #2 ([1.43927e+08,1.8545e+08]) of 3... 891s Number of TCN loci in segment: 2668 891s Locus data for TCN segment: 891s 'data.frame': 2668 obs. of 9 variables: 891s $ chromosome: int 3 3 3 3 3 3 3 3 3 3 ... 891s $ x : num 1.44e+08 1.44e+08 1.44e+08 1.44e+08 1.44e+08 ... 891s $ CT : num 2.1 2.1 2.09 1.8 2.34 ... 891s $ betaT : num 0.027542 1.030222 1.094093 0.046763 -0.000948 ... 891s $ betaTN : num 0.027542 1.030222 1.094093 0.046763 -0.000948 ... 891s $ betaN : num 0.1624 0.8788 0.8225 0.1201 0.0317 ... 891s $ muN : num 0 1 1 0 0 1 0 0 0 0 ... 891s $ index : int 7600 7601 7602 7603 7604 7605 7606 7607 7608 7609 ... 891s $ rho : num NA NA NA NA NA NA NA NA NA NA ... 891s Number of loci: 2668 891s Number of SNPs: 775 (29.05%) 891s Number of heterozygous SNPs: 775 (100.00%) 891s Chromosome: 3 891s Segmenting DH signals... 891s Segmenting by CBS... 891s Chromosome: 3 891s Random seed temporarily set (seed=c(10407, -1371615447, -889757879, 1692656974, -1723952224, 1378814990, 1816467252), kind="L'Ecuyer-CMRG") 891s Segmenting by CBS...done 891s List of 4 891s $ data :'data.frame': 2668 obs. of 4 variables: 891s ..$ chromosome: int [1:2668] 3 3 3 3 3 3 3 3 3 3 ... 891s ..$ x : num [1:2668] 1.44e+08 1.44e+08 1.44e+08 1.44e+08 1.44e+08 ... 891s ..$ y : num [1:2668] NA NA NA NA NA NA NA NA NA NA ... 891s ..$ index : int [1:2668] 1 2 3 4 5 6 7 8 9 10 ... 891s $ output :'data.frame': 1 obs. of 6 variables: 891s ..$ sampleName: chr NA 891s ..$ chromosome: int 3 891s ..$ start : num 1.44e+08 891s ..$ end : num 1.85e+08 891s ..$ nbrOfLoci : int 775 891s ..$ mean : num 0.097 891s $ segRows:'data.frame': 1 obs. of 2 variables: 891s ..$ startRow: int 15 891s ..$ endRow : int 2664 891s $ params :List of 5 891s ..$ alpha : num 0.001 891s ..$ undo : num 0 891s ..$ joinSegments : logi TRUE 891s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 891s .. ..$ chromosome: int 3 891s .. ..$ start : num 1.44e+08 891s .. ..$ end : num 1.85e+08 891s ..$ seed : int [1:7] 10407 -1371615447 -889757879 1692656974 -1723952224 1378814990 1816467252 891s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 891s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.008 0 0.008 0 0 891s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 891s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 891s - attr(*, "randomSeed")= int [1:7] 10407 -1371615447 -889757879 1692656974 -1723952224 1378814990 1816467252 891s DH segmentation (locally-indexed) rows: 891s startRow endRow 891s 1 15 2664 891s int [1:2668] 7600 7601 7602 7603 7604 7605 7606 7607 7608 7609 ... 891s DH segmentation rows: 891s startRow endRow 891s 1 7614 10263 891s Segmenting DH signals...done 891s DH segmentation table: 891s dhStart dhEnd dhNbrOfLoci dhMean 891s 1 143926517 185449813 775 0.097 891s startRow endRow 891s 1 7614 10263 891s Rows: 891s [1] 2 891s TCN segmentation rows: 891s startRow endRow 891s 2 7600 10267 891s TCN and DH segmentation rows: 891s startRow endRow 891s 2 7600 10267 891s startRow endRow 891s 1 7614 10263 891s startRow endRow 891s 1 1 7599 891s TCN segmentation (expanded) rows: 891s startRow endRow 891s 1 1 7599 891s 2 7600 10267 891s TCN and DH segmentation rows: 891s startRow endRow 891s 1 1 7599 891s 2 7600 10267 891s 3 10268 14658 891s startRow endRow 891s 1 10 7594 891s 2 7614 10263 891s startRow endRow 891s 1 1 7599 891s 2 7600 10267 891s Total CN segmentation table (expanded): 891s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 891s 2 3 143926517 185449813 2668 2.0704 775 775 891s (TCN,DH) segmentation for one total CN segment: 891s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 891s 2 2 1 3 143926517 185449813 2668 2.0704 775 891s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 891s 2 775 143926517 185449813 775 0.097 891s Total CN segment #2 ([1.43927e+08,1.8545e+08]) of 3...done 891s Total CN segment #3 ([1.8545e+08,2.47137e+08]) of 3... 891s Number of TCN loci in segment: 4391 891s Locus data for TCN segment: 891s 'data.frame': 4391 obs. of 9 variables: 891s $ chromosome: int 3 3 3 3 3 3 3 3 3 3 ... 891s $ x : num 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 891s $ CT : num 2.93 2.15 2.82 2.93 2.46 ... 891s $ betaT : num -0.169 0.609 1.028 0.525 0.968 ... 891s $ betaTN : num -0.169 0.609 1.028 0.525 0.968 ... 891s $ betaN : num 0.25 0.38 0.919 0.34 0.783 ... 891s $ muN : num 0 0.5 1 0.5 1 1 0 1 0 1 ... 891s $ index : int 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 891s $ rho : num NA 0.2186 NA 0.0503 NA ... 891s Number of loci: 4391 891s Number of SNPs: 1314 (29.92%) 891s Number of heterozygous SNPs: 1314 (100.00%) 891s Chromosome: 3 891s Segmenting DH signals... 891s Segmenting by CBS... 891s Chromosome: 3 891s Random seed temporarily set (seed=c(10407, -1371615447, -889757879, 1692656974, -1723952224, 1378814990, 1816467252), kind="L'Ecuyer-CMRG") 891s Segmenting by CBS...done 891s List of 4 891s $ data :'data.frame': 4391 obs. of 4 variables: 891s ..$ chromosome: int [1:4391] 3 3 3 3 3 3 3 3 3 3 ... 891s ..$ x : num [1:4391] 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 891s ..$ y : num [1:4391] NA 0.2186 NA 0.0503 NA ... 891s ..$ index : int [1:4391] 1 2 3 4 5 6 7 8 9 10 ... 891s $ output :'data.frame': 1 obs. of 6 variables: 891s ..$ sampleName: chr NA 891s ..$ chromosome: int 3 891s ..$ start : num 1.85e+08 891s ..$ end : num 2.47e+08 891s ..$ nbrOfLoci : int 1314 891s ..$ mean : num 0.23 891s $ segRows:'data.frame': 1 obs. of 2 variables: 891s ..$ startRow: int 2 891s ..$ endRow : int 4388 891s $ params :List of 5 891s ..$ alpha : num 0.001 891s ..$ undo : num 0 891s ..$ joinSegments : logi TRUE 891s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 891s .. ..$ chromosome: int 3 891s .. ..$ start : num 1.85e+08 891s .. ..$ end : num 2.47e+08 891s ..$ seed : int [1:7] 10407 -1371615447 -889757879 1692656974 -1723952224 1378814990 1816467252 891s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 891s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.015 0 0.015 0 0 891s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 891s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 891s - attr(*, "randomSeed")= int [1:7] 10407 -1371615447 -889757879 1692656974 -1723952224 1378814990 1816467252 891s DH segmentation (locally-indexed) rows: 891s startRow endRow 891s 1 2 4388 891s int [1:4391] 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 891s DH segmentation rows: 891s startRow endRow 891s 1 10269 14655 891s Segmenting DH signals...done 891s DH segmentation table: 891s dhStart dhEnd dhNbrOfLoci dhMean 891s 1 185449813 247137334 1314 0.2295 891s startRow endRow 891s 1 10269 14655 891s Rows: 891s [1] 3 891s TCN segmentation rows: 891s startRow endRow 891s 3 10268 14658 891s TCN and DH segmentation rows: 891s startRow endRow 891s 3 10268 14658 891s startRow endRow 891s 1 10269 14655 891s startRow endRow 891s 1 1 7599 891s 2 7600 10267 891s TCN segmentation (expanded) rows: 891s startRow endRow 891s 1 1 7599 891s 2 7600 10267 891s 3 10268 14658 891s TCN and DH segmentation rows: 891s startRow endRow 891s 1 1 7599 891s 2 7600 10267 891s 3 10268 14658 891s startRow endRow 891s 1 10 7594 891s 2 7614 10263 891s 3 10269 14655 891s startRow endRow 891s 1 1 7599 891s 2 7600 10267 891s 3 10268 14658 891s Total CN segmentation table (expanded): 891s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 891s 3 3 185449813 247137334 4391 2.6341 1314 1314 891s (TCN,DH) segmentation for one total CN segment: 891s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 891s 3 3 1 3 185449813 247137334 4391 2.6341 1314 891s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 891s 3 1314 185449813 247137334 1314 0.2295 891s Total CN segment #3 ([1.8545e+08,2.47137e+08]) of 3...done 891s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 891s 1 3 1 1 554484 143926517 7599 1.3859 2120 891s 2 3 2 1 143926517 185449813 2668 2.0704 775 891s 3 3 3 1 185449813 247137334 4391 2.6341 1314 891s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 891s 1 2120 554484 143926517 2120 0.5101 891s 2 775 143926517 185449813 775 0.0970 891s 3 1314 185449813 247137334 1314 0.2295 891s Calculating (C1,C2) per segment... 891s Calculating (C1,C2) per segment...done 891s Number of segments: 3 891s Segmenting paired tumor-normal signals using Paired PSCBS...done 891s Post-segmenting TCNs... 891s Number of segments: 3 891s Number of chromosomes: 1 891s [1] 3 891s Chromosome 1 ('chr03') of 1... 891s Rows: 891s [1] 1 2 3 891s Number of segments: 3 891s TCN segment #1 ('1') of 3... 891s Nothing todo. Only one DH segmentation. Skipping. 891s TCN segment #1 ('1') of 3...done 891s TCN segment #2 ('2') of 3... 891s Nothing todo. Only one DH segmentation. Skipping. 891s TCN segment #2 ('2') of 3...done 891s TCN segment #3 ('3') of 3... 891s Nothing todo. Only one DH segmentation. Skipping. 891s TCN segment #3 ('3') of 3...done 891s Chromosome 1 ('chr03') of 1...done 891s Update (C1,C2) per segment... 891s Update (C1,C2) per segment...done 891s Post-segmenting TCNs...done 891s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 891s 1 3 1 1 554484 143926517 7599 1.3859 2120 891s 2 3 2 1 143926517 185449813 2668 2.0704 775 891s 3 3 3 1 185449813 247137334 4391 2.6341 1314 891s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 891s 1 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 891s 2 775 143926517 185449813 775 0.0970 0.9347856 1.135614 891s 3 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 891s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 891s 1 3 1 1 554484 143926517 7599 1.3859 2120 891s 2 3 2 1 143926517 185449813 2668 2.0704 775 891s 3 3 3 1 185449813 247137334 4391 2.6341 1314 891s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 891s 1 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 891s 2 775 143926517 185449813 775 0.0970 0.9347856 1.135614 891s 3 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 891s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 891s 1 3 1 1 554484 143926517 7599 1.3859 2120 891s 2 3 2 1 143926517 185449813 2668 2.0704 775 891s 3 3 3 1 185449813 247137334 4391 2.6341 1314 891s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 891s 1 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 891s 2 775 143926517 185449813 775 0.0970 0.9347856 1.135614 891s 3 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 891s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 891s 1 3 1 1 554484 143926517 7599 1.3859 2120 891s 2 3 2 1 143926517 185449813 2668 2.0704 775 891s 3 3 3 1 185449813 247137334 4391 2.6341 1314 891s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 891s 1 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 891s 2 775 143926517 185449813 775 0.0970 0.9347856 1.135614 891s 3 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 891s Chromosome #3 ('Chr03') of 3...done 891s Merging (independently) segmented chromosome... 891s List of 5 891s $ data :Classes ‘PairedPSCNData’ and 'data.frame': 43974 obs. of 8 variables: 891s ..$ chromosome: int [1:43974] 1 1 1 1 1 1 1 1 1 1 ... 891s ..$ x : num [1:43974] 554484 730720 782343 878522 916294 ... 891s ..$ CT : num [1:43974] 1.88 1.8 1.59 1.64 1.53 ... 891s ..$ betaT : num [1:43974] 0.0646 0.1672 0.9284 0.113 0.7209 ... 891s ..$ betaTN : num [1:43974] -0.0515 -0.1172 1.0194 0.031 0.8604 ... 891s ..$ betaN : num [1:43974] 0.116 0.284 0.909 0.082 0.86 ... 891s ..$ muN : num [1:43974] 0 0 1 0 1 1 1 0 1 0.5 ... 891s ..$ rho : num [1:43974] NA NA NA NA NA ... 891s $ output :Classes ‘PairedPSCNSegments’ and 'data.frame': 11 obs. of 15 variables: 891s ..$ chromosome : int [1:11] 1 1 1 NA 2 2 2 NA 3 3 ... 891s ..$ tcnId : int [1:11] 1 2 3 NA 1 2 3 NA 1 2 ... 891s ..$ dhId : int [1:11] 1 1 1 NA 1 1 1 NA 1 1 ... 891s ..$ tcnStart : num [1:11] 5.54e+05 1.44e+08 1.85e+08 NA 5.54e+05 ... 891s ..$ tcnEnd : num [1:11] 1.44e+08 1.85e+08 2.47e+08 NA 1.44e+08 ... 891s ..$ tcnNbrOfLoci: int [1:11] 7599 2668 4391 NA 7599 2668 4391 NA 7599 2668 ... 891s ..$ tcnMean : num [1:11] 1.39 2.07 2.63 NA 1.39 ... 891s ..$ tcnNbrOfSNPs: int [1:11] 2120 775 1314 NA 2120 775 1314 NA 2120 775 ... 891s ..$ tcnNbrOfHets: int [1:11] 2120 775 1314 NA 2120 775 1314 NA 2120 775 ... 891s ..$ dhStart : num [1:11] 5.54e+05 1.44e+08 1.85e+08 NA 5.54e+05 ... 891s ..$ dhEnd : num [1:11] 1.44e+08 1.85e+08 2.47e+08 NA 1.44e+08 ... 891s ..$ dhNbrOfLoci : int [1:11] 2120 775 1314 NA 2120 775 1314 NA 2120 775 ... 891s ..$ dhMean : num [1:11] 0.51 0.097 0.23 NA 0.51 ... 891s ..$ c1Mean : num [1:11] 0.339 0.935 1.015 NA 0.339 ... 891s ..$ c2Mean : num [1:11] 1.05 1.14 1.62 NA 1.05 ... 891s $ tcnSegRows:'data.frame': 11 obs. of 2 variables: 891s ..$ startRow: int [1:11] 1 7600 10268 NA 14659 22258 24926 NA 29317 36916 ... 891s ..$ endRow : int [1:11] 7599 10267 14658 NA 22257 24925 29316 NA 36915 39583 ... 891s $ dhSegRows :'data.frame': 11 obs. of 2 variables: 891s ..$ startRow: int [1:11] 10 7614 10269 NA 14668 22272 24927 NA 29326 36930 ... 891s ..$ endRow : int [1:11] 7594 10263 14655 NA 22252 24921 29313 NA 36910 39579 ... 891s $ params :List of 7 891s ..$ alphaTCN : num 0.009 891s ..$ alphaDH : num 0.001 891s ..$ flavor : chr "tcn&dh" 891s ..$ tbn : logi FALSE 891s ..$ joinSegments : logi TRUE 891s ..$ knownSegments:'data.frame': 0 obs. of 3 variables: 891s .. ..$ chromosome: int(0) 891s .. ..$ start : int(0) 891s .. ..$ end : int(0) 891s ..$ seed : int [1:7] 10407 1066287653 -51199871 161854402 -1995183193 1503453565 -747102133 891s - attr(*, "class")= chr [1:3] "PairedPSCBS" "PSCBS" "AbstractCBS" 891s Merging (independently) segmented chromosome...done 891s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 891s 1 1 1 1 554484 143926517 7599 1.3859 2120 891s 2 1 2 1 143926517 185449813 2668 2.0704 775 891s 3 1 3 1 185449813 247137334 4391 2.6341 1314 891s 4 NA NA NA NA NA NA NA NA 891s 5 2 1 1 554484 143926517 7599 1.3859 2120 891s 6 2 2 1 143926517 185449813 2668 2.0704 775 891s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 891s 1 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 891s 2 775 143926517 185449813 775 0.0970 0.9347856 1.135614 891s 3 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 891s 4 NA NA NA NA NA NA NA 891s 5 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 891s 6 775 143926517 185449813 775 0.0970 0.9347856 1.135614 891s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 891s 6 2 2 1 143926517 185449813 2668 2.0704 775 891s 7 2 3 1 185449813 247137334 4391 2.6341 1314 891s 8 NA NA NA NA NA NA NA NA 891s 9 3 1 1 554484 143926517 7599 1.3859 2120 891s 10 3 2 1 143926517 185449813 2668 2.0704 775 891s 11 3 3 1 185449813 247137334 4391 2.6341 1314 891s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 891s 6 775 143926517 185449813 775 0.0970 0.9347856 1.135614 891s 7 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 891s 8 NA NA NA NA NA NA NA 891s 9 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 891s 10 775 143926517 185449813 775 0.0970 0.9347856 1.135614 891s 11 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 891s Segmenting multiple chromosomes...done 891s Segmenting paired tumor-normal signals using Paired PSCBS...done 891s - segmentByPairedPSCBS() using 'multisession' futures ... 892s Segmenting paired tumor-normal signals using Paired PSCBS... 892s Calling genotypes from normal allele B fractions... 892s num [1:44010] 0.8274 0.5072 0.1671 0.1609 0.0421 ... 892s Called genotypes: 892s num [1:44010] 1 0.5 0 0 0 0 1 0 1 0.5 ... 892s - attr(*, "modelFit")=List of 1 892s ..$ :List of 7 892s .. ..$ flavor : chr "density" 892s .. ..$ cn : int 2 892s .. ..$ nbrOfGenotypeGroups: int 3 892s .. ..$ tau : num [1:2] 0.312 0.678 892s .. ..$ n : int 43920 892s .. ..$ fit :Classes ‘PeaksAndValleys’ and 'data.frame': 5 obs. of 3 variables: 892s .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 892s .. .. ..$ x : num [1:5] 0.0999 0.312 0.4986 0.6775 0.8922 892s .. .. ..$ density: num [1:5] 1.622 0.465 1.125 0.496 1.587 892s .. ..$ fitValleys :Classes ‘PeaksAndValleys’ and 'data.frame': 2 obs. of 3 variables: 892s .. .. ..$ type : chr [1:2] "valley" "valley" 892s .. .. ..$ x : num [1:2] 0.312 0.678 892s .. .. ..$ density: num [1:2] 0.465 0.496 892s ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 892s muN 892s 0 0.5 1 892s 15627 12633 15750 892s Calling genotypes from normal allele B fractions...done 892s Normalizing betaT using betaN (TumorBoost)... 892s Normalized BAFs: 892s num [1:44010] 0.9301 0.1667 0.0685 0.0995 0.0155 ... 892s - attr(*, "modelFit")=List of 5 892s ..$ method : chr "normalizeTumorBoost" 892s ..$ flavor : chr "v4" 892s ..$ delta : num [1:44010] -0.17264 0.00239 0.1671 0.16085 0.04213 ... 892s .. ..- attr(*, "modelFit")=List of 1 892s .. .. ..$ :List of 7 892s .. .. .. ..$ flavor : chr "density" 892s .. .. .. ..$ cn : int 2 892s .. .. .. ..$ nbrOfGenotypeGroups: int 3 892s .. .. .. ..$ tau : num [1:2] 0.312 0.678 892s .. .. .. ..$ n : int 43920 892s .. .. .. ..$ fit :Classes ‘PeaksAndValleys’ and 'data.frame': 5 obs. of 3 variables: 892s .. .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 892s .. .. .. .. ..$ x : num [1:5] 0.0999 0.312 0.4986 0.6775 0.8922 892s .. .. .. .. ..$ density: num [1:5] 1.622 0.465 1.125 0.496 1.587 892s .. .. .. ..$ fitValleys :Classes ‘PeaksAndValleys’ and 'data.frame': 2 obs. of 3 variables: 892s .. .. .. .. ..$ type : chr [1:2] "valley" "valley" 892s .. .. .. .. ..$ x : num [1:2] 0.312 0.678 892s .. .. .. .. ..$ density: num [1:2] 0.465 0.496 892s .. .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 892s ..$ preserveScale: logi FALSE 892s ..$ scaleFactor : num NA 892s Normalizing betaT using betaN (TumorBoost)...done 892s Setup up data... 892s 'data.frame': 44010 obs. of 7 variables: 892s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 892s $ x : num 1145994 2941694 3710825 4240737 4276892 ... 892s $ CT : num 1.63 1.4 1.41 1.17 1.16 ... 892s $ betaT : num 0.7574 0.169 0.2357 0.2604 0.0576 ... 892s $ betaTN : num 0.9301 0.1667 0.0685 0.0995 0.0155 ... 892s ..- attr(*, "modelFit")=List of 5 892s .. ..$ method : chr "normalizeTumorBoost" 892s .. ..$ flavor : chr "v4" 892s .. ..$ delta : num [1:44010] -0.17264 0.00239 0.1671 0.16085 0.04213 ... 892s .. .. ..- attr(*, "modelFit")=List of 1 892s .. .. .. ..$ :List of 7 892s .. .. .. .. ..$ flavor : chr "density" 892s .. .. .. .. ..$ cn : int 2 892s .. .. .. .. ..$ nbrOfGenotypeGroups: int 3 892s .. .. .. .. ..$ tau : num [1:2] 0.312 0.678 892s .. .. .. .. ..$ n : int 43920 892s .. .. .. .. ..$ fit :Classes ‘PeaksAndValleys’ and 'data.frame': 5 obs. of 3 variables: 892s .. .. .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 892s .. .. .. .. .. ..$ x : num [1:5] 0.0999 0.312 0.4986 0.6775 0.8922 892s .. .. .. .. .. ..$ density: num [1:5] 1.622 0.465 1.125 0.496 1.587 892s .. .. .. .. ..$ fitValleys :Classes ‘PeaksAndValleys’ and 'data.frame': 2 obs. of 3 variables: 892s .. .. .. .. .. ..$ type : chr [1:2] "valley" "valley" 892s .. .. .. .. .. ..$ x : num [1:2] 0.312 0.678 892s .. .. .. .. .. ..$ density: num [1:2] 0.465 0.496 892s .. .. .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 892s .. ..$ preserveScale: logi FALSE 892s .. ..$ scaleFactor : num NA 892s $ betaN : num 0.8274 0.5072 0.1671 0.1609 0.0421 ... 892s $ muN : num 1 0.5 0 0 0 0 1 0 1 0.5 ... 892s ..- attr(*, "modelFit")=List of 1 892s .. ..$ :List of 7 892s .. .. ..$ flavor : chr "density" 892s .. .. ..$ cn : int 2 892s .. .. ..$ nbrOfGenotypeGroups: int 3 892s .. .. ..$ tau : num [1:2] 0.312 0.678 892s .. .. ..$ n : int 43920 892s .. .. ..$ fit :Classes ‘PeaksAndValleys’ and 'data.frame': 5 obs. of 3 variables: 892s .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 892s .. .. .. ..$ x : num [1:5] 0.0999 0.312 0.4986 0.6775 0.8922 892s .. .. .. ..$ density: num [1:5] 1.622 0.465 1.125 0.496 1.587 892s .. .. ..$ fitValleys :Classes ‘PeaksAndValleys’ and 'data.frame': 2 obs. of 3 variables: 892s .. .. .. ..$ type : chr [1:2] "valley" "valley" 892s .. .. .. ..$ x : num [1:2] 0.312 0.678 892s .. .. .. ..$ density: num [1:2] 0.465 0.496 892s .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 892s Setup up data...done 892s Dropping loci for which TCNs are missing... 892s Number of loci dropped: 36 892s Dropping loci for which TCNs are missing...done 892s Ordering data along genome... 892s 'data.frame': 43974 obs. of 7 variables: 892s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 892s $ x : num 554484 730720 782343 878522 916294 ... 892s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 892s $ betaT : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 892s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 892s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 892s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 892s Ordering data along genome...done 892s Segmenting multiple chromosomes... 892s Number of chromosomes: 3 892s Random seed temporarily set (seed=c(48879), kind="L'Ecuyer-CMRG") 892s Produced 3 seeds from this stream for future usage 892s Chromosome #1 ('Chr01') of 3... 892s 'data.frame': 14658 obs. of 8 variables: 892s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 892s $ x : num 554484 730720 782343 878522 916294 ... 892s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 892s $ betaT : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 892s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 892s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 892s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 892s $ index : int 1 2 3 4 5 6 7 8 9 10 ... 892s Known segments: 892s [1] chromosome start end 892s <0 rows> (or 0-length row.names) 892s Chromosome #1 ('Chr01') of 3...done 892s Chromosome #2 ('Chr02') of 3... 892s 'data.frame': 14658 obs. of 8 variables: 892s $ chromosome: int 2 2 2 2 2 2 2 2 2 2 ... 892s $ x : num 554484 730720 782343 878522 916294 ... 892s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 892s $ betaT : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 892s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 892s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 892s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 892s $ index : int 14659 14660 14661 14662 14663 14664 14665 14666 14667 14668 ... 892s Known segments: 892s [1] chromosome start end 892s <0 rows> (or 0-length row.names) 892s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 893s Chromosome #2 ('Chr02') of 3...done 893s Chromosome #3 ('Chr03') of 3... 893s 'data.frame': 14658 obs. of 8 variables: 893s $ chromosome: int 3 3 3 3 3 3 3 3 3 3 ... 893s $ x : num 554484 730720 782343 878522 916294 ... 893s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 893s $ betaT : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 893s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 893s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 893s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 893s $ index : int 29317 29318 29319 29320 29321 29322 29323 29324 29325 29326 ... 893s Known segments: 893s [1] chromosome start end 893s <0 rows> (or 0-length row.names) 893s Segmenting by CBS...done 893s Random seed temporarily set (seed=c(10407, -821273412, -52578226, 1415511586, 721384351, -665928286, 1316562960), kind="L'Ecuyer-CMRG") 893s List of 4 893s $ data :'data.frame': 14658 obs. of 4 variables: 893s ..$ chromosome: int [1:14658] 1 1 1 1 1 1 1 1 1 1 ... 893s ..$ x : num [1:14658] 554484 730720 782343 878522 916294 ... 893s ..$ y : num [1:14658] 1.88 1.8 1.59 1.64 1.53 ... 893s ..$ index : int [1:14658] 1 2 3 4 5 6 7 8 9 10 ... 893s $ output :'data.frame': 3 obs. of 6 variables: 893s ..$ sampleName: chr [1:3] NA NA NA 893s ..$ chromosome: int [1:3] 1 1 1 893s ..$ start : num [1:3] 5.54e+05 1.44e+08 1.85e+08 893s ..$ end : num [1:3] 1.44e+08 1.85e+08 2.47e+08 893s ..$ nbrOfLoci : int [1:3] 7599 2668 4391 893s ..$ mean : num [1:3] 1.39 2.07 2.63 893s $ segRows:'data.frame': 3 obs. of 2 variables: 893s ..$ startRow: int [1:3] 1 7600 10268 893s ..$ endRow : int [1:3] 7599 10267 14658 893s $ params :List of 5 893s ..$ alpha : num 0.009 893s ..$ undo : num 0 893s ..$ joinSegments : logi TRUE 893s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 893s .. ..$ chromosome: int 1 893s .. ..$ start : num -Inf 893s .. ..$ end : num Inf 893s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 893s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 893s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.379 0.003 0.382 0 0 893s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 893s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 893s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 893s Identification of change points by total copy numbers...done 893s Restructure TCN segmentation results... 893s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean 893s 1 1 554484 143926517 7599 1.3859 893s 2 1 143926517 185449813 2668 2.0704 893s 3 1 185449813 247137334 4391 2.6341 893s Number of TCN segments: 3 893s Restructure TCN segmentation results...done 893s Total CN segment #1 ([ 554484,1.43927e+08]) of 3... 893s Number of TCN loci in segment: 7599 893s Locus data for TCN segment: 893s 'data.frame': 7599 obs. of 9 variables: 893s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 893s $ x : num 554484 730720 782343 878522 916294 ... 893s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 893s $ betaT : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 893s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 893s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 893s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 893s $ index : int 1 2 3 4 5 6 7 8 9 10 ... 893s $ rho : num NA NA NA NA NA ... 893s Number of loci: 7599 893s Number of SNPs: 2120 (27.90%) 893s Number of heterozygous SNPs: 2120 (100.00%) 893s Chromosome: 1 893s Segmenting DH signals... 893s Segmenting by CBS... 893s Chromosome: 1 893s Random seed temporarily set (seed=c(10407, -821273412, -52578226, 1415511586, 721384351, -665928286, 1316562960), kind="L'Ecuyer-CMRG") 893s Segmenting by CBS...done 893s List of 4 893s $ data :'data.frame': 7599 obs. of 4 variables: 893s ..$ chromosome: int [1:7599] 1 1 1 1 1 1 1 1 1 1 ... 893s ..$ x : num [1:7599] 554484 730720 782343 878522 916294 ... 893s ..$ y : num [1:7599] NA NA NA NA NA ... 893s ..$ index : int [1:7599] 1 2 3 4 5 6 7 8 9 10 ... 893s $ output :'data.frame': 1 obs. of 6 variables: 893s ..$ sampleName: chr NA 893s ..$ chromosome: int 1 893s ..$ start : num 554484 893s ..$ end : num 1.44e+08 893s ..$ nbrOfLoci : int 2120 893s ..$ mean : num 0.51 893s $ segRows:'data.frame': 1 obs. of 2 variables: 893s ..$ startRow: int 10 893s ..$ endRow : int 7594 893s $ params :List of 5 893s ..$ alpha : num 0.001 893s ..$ undo : num 0 893s ..$ joinSegments : logi TRUE 893s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 893s .. ..$ chromosome: int 1 893s .. ..$ start : num 554484 893s .. ..$ end : num 1.44e+08 893s ..$ seed : int [1:7] 10407 -821273412 -52578226 1415511586 721384351 -665928286 1316562960 893s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 893s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.026 0 0.025 0 0 893s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 893s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 893s - attr(*, "randomSeed")= int [1:7] 10407 -821273412 -52578226 1415511586 721384351 -665928286 1316562960 893s DH segmentation (locally-indexed) rows: 893s startRow endRow 893s 1 10 7594 893s int [1:7599] 1 2 3 4 5 6 7 8 9 10 ... 893s DH segmentation rows: 893s startRow endRow 893s 1 10 7594 893s Segmenting DH signals...done 893s DH segmentation table: 893s dhStart dhEnd dhNbrOfLoci dhMean 893s 1 554484 143926517 2120 0.5101 893s startRow endRow 893s 1 10 7594 893s Rows: 893s [1] 1 893s TCN segmentation rows: 893s startRow endRow 893s 1 1 7599 893s TCN and DH segmentation rows: 893s startRow endRow 893s 1 1 7599 893s startRow endRow 893s 1 10 7594 893s NULL 893s TCN segmentation (expanded) rows: 893s startRow endRow 893s 1 1 7599 893s TCN and DH segmentation rows: 893s startRow endRow 893s 1 1 7599 893s 2 7600 10267 893s 3 10268 14658 893s startRow endRow 893s 1 10 7594 893s startRow endRow 893s 1 1 7599 893s Total CN segmentation table (expanded): 893s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 893s 1 1 554484 143926517 7599 1.3859 2120 2120 893s (TCN,DH) segmentation for one total CN segment: 893s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 893s 1 1 1 1 554484 143926517 7599 1.3859 2120 893s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 893s 1 2120 554484 143926517 2120 0.5101 893s Total CN segment #1 ([ 554484,1.43927e+08]) of 3...done 893s Total CN segment #2 ([1.43927e+08,1.8545e+08]) of 3... 893s Number of TCN loci in segment: 2668 893s Locus data for TCN segment: 893s 'data.frame': 2668 obs. of 9 variables: 893s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 893s $ x : num 1.44e+08 1.44e+08 1.44e+08 1.44e+08 1.44e+08 ... 893s $ CT : num 2.1 2.1 2.09 1.8 2.34 ... 893s $ betaT : num 0.027542 1.030222 1.094093 0.046763 -0.000948 ... 893s $ betaTN : num 0.027542 1.030222 1.094093 0.046763 -0.000948 ... 893s $ betaN : num 0.1624 0.8788 0.8225 0.1201 0.0317 ... 893s $ muN : num 0 1 1 0 0 1 0 0 0 0 ... 893s $ index : int 7600 7601 7602 7603 7604 7605 7606 7607 7608 7609 ... 893s $ rho : num NA NA NA NA NA NA NA NA NA NA ... 893s Number of loci: 2668 893s Number of SNPs: 775 (29.05%) 893s Number of heterozygous SNPs: 775 (100.00%) 893s Chromosome: 1 893s Segmenting DH signals... 893s Segmenting by CBS... 893s Chromosome: 1 893s Random seed temporarily set (seed=c(10407, -821273412, -52578226, 1415511586, 721384351, -665928286, 1316562960), kind="L'Ecuyer-CMRG") 893s Segmenting by CBS...done 893s List of 4 893s $ data :'data.frame': 2668 obs. of 4 variables: 893s ..$ chromosome: int [1:2668] 1 1 1 1 1 1 1 1 1 1 ... 893s ..$ x : num [1:2668] 1.44e+08 1.44e+08 1.44e+08 1.44e+08 1.44e+08 ... 893s ..$ y : num [1:2668] NA NA NA NA NA NA NA NA NA NA ... 893s ..$ index : int [1:2668] 1 2 3 4 5 6 7 8 9 10 ... 893s $ output :'data.frame': 1 obs. of 6 variables: 893s ..$ sampleName: chr NA 893s ..$ chromosome: int 1 893s ..$ start : num 1.44e+08 893s ..$ end : num 1.85e+08 893s ..$ nbrOfLoci : int 775 893s ..$ mean : num 0.097 893s $ segRows:'data.frame': 1 obs. of 2 variables: 893s ..$ startRow: int 15 893s ..$ endRow : int 2664 893s $ params :List of 5 893s ..$ alpha : num 0.001 893s ..$ undo : num 0 893s ..$ joinSegments : logi TRUE 893s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 893s .. ..$ chromosome: int 1 893s .. ..$ start : num 1.44e+08 893s .. ..$ end : num 1.85e+08 893s ..$ seed : int [1:7] 10407 -821273412 -52578226 1415511586 721384351 -665928286 1316562960 893s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 893s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.009 0 0.008 0 0 893s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 893s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 893s - attr(*, "randomSeed")= int [1:7] 10407 -821273412 -52578226 1415511586 721384351 -665928286 1316562960 893s DH segmentation (locally-indexed) rows: 893s startRow endRow 893s 1 15 2664 893s int [1:2668] 7600 7601 7602 7603 7604 7605 7606 7607 7608 7609 ... 893s DH segmentation rows: 893s startRow endRow 893s 1 7614 10263 893s Segmenting DH signals...done 893s DH segmentation table: 893s dhStart dhEnd dhNbrOfLoci dhMean 893s 1 143926517 185449813 775 0.097 893s startRow endRow 893s 1 7614 10263 893s Rows: 893s [1] 2 893s TCN segmentation rows: 893s startRow endRow 893s 2 7600 10267 893s TCN and DH segmentation rows: 893s startRow endRow 893s 2 7600 10267 893s startRow endRow 893s 1 7614 10263 893s startRow endRow 893s 1 1 7599 893s TCN segmentation (expanded) rows: 893s startRow endRow 893s 1 1 7599 893s 2 7600 10267 893s TCN and DH segmentation rows: 893s startRow endRow 893s 1 1 7599 893s 2 7600 10267 893s 3 10268 14658 893s startRow endRow 893s 1 10 7594 893s 2 7614 10263 893s startRow endRow 893s 1 1 7599 893s 2 7600 10267 893s Total CN segmentation table (expanded): 893s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 893s 2 1 143926517 185449813 2668 2.0704 775 775 893s (TCN,DH) segmentation for one total CN segment: 893s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 893s 2 2 1 1 143926517 185449813 2668 2.0704 775 893s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 893s 2 775 143926517 185449813 775 0.097 893s Total CN segment #2 ([1.43927e+08,1.8545e+08]) of 3...done 893s Total CN segment #3 ([1.8545e+08,2.47137e+08]) of 3... 893s Number of TCN loci in segment: 4391 893s Locus data for TCN segment: 893s 'data.frame': 4391 obs. of 9 variables: 893s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 893s $ x : num 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 893s $ CT : num 2.93 2.15 2.82 2.93 2.46 ... 893s $ betaT : num -0.169 0.609 1.028 0.525 0.968 ... 893s $ betaTN : num -0.169 0.609 1.028 0.525 0.968 ... 893s $ betaN : num 0.25 0.38 0.919 0.34 0.783 ... 893s $ muN : num 0 0.5 1 0.5 1 1 0 1 0 1 ... 893s $ index : int 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 893s $ rho : num NA 0.2186 NA 0.0503 NA ... 893s Number of loci: 4391 893s Number of SNPs: 1314 (29.92%) 893s Number of heterozygous SNPs: 1314 (100.00%) 893s Chromosome: 1 893s Segmenting DH signals... 893s Segmenting by CBS... 893s Chromosome: 1 893s Random seed temporarily set (seed=c(10407, -821273412, -52578226, 1415511586, 721384351, -665928286, 1316562960), kind="L'Ecuyer-CMRG") 893s Segmenting by CBS...done 893s List of 4 893s $ data :'data.frame': 4391 obs. of 4 variables: 893s ..$ chromosome: int [1:4391] 1 1 1 1 1 1 1 1 1 1 ... 893s ..$ x : num [1:4391] 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 893s ..$ y : num [1:4391] NA 0.2186 NA 0.0503 NA ... 893s ..$ index : int [1:4391] 1 2 3 4 5 6 7 8 9 10 ... 893s $ output :'data.frame': 1 obs. of 6 variables: 893s ..$ sampleName: chr NA 893s ..$ chromosome: int 1 893s ..$ start : num 1.85e+08 893s ..$ end : num 2.47e+08 893s ..$ nbrOfLoci : int 1314 893s ..$ mean : num 0.23 893s $ segRows:'data.frame': 1 obs. of 2 variables: 893s ..$ startRow: int 2 893s ..$ endRow : int 4388 893s $ params :List of 5 893s ..$ alpha : num 0.001 893s ..$ undo : num 0 893s ..$ joinSegments : logi TRUE 893s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 893s .. ..$ chromosome: int 1 893s .. ..$ start : num 1.85e+08 893s .. ..$ end : num 2.47e+08 893s ..$ seed : int [1:7] 10407 -821273412 -52578226 1415511586 721384351 -665928286 1316562960 893s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 893s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.015 0 0.014 0 0 893s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 893s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 893s - attr(*, "randomSeed")= int [1:7] 10407 -821273412 -52578226 1415511586 721384351 -665928286 1316562960 893s DH segmentation (locally-indexed) rows: 893s startRow endRow 893s 1 2 4388 893s int [1:4391] 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 893s DH segmentation rows: 893s startRow endRow 893s 1 10269 14655 893s Segmenting DH signals...done 893s DH segmentation table: 893s dhStart dhEnd dhNbrOfLoci dhMean 893s 1 185449813 247137334 1314 0.2295 893s startRow endRow 893s 1 10269 14655 893s Rows: 893s [1] 3 893s TCN segmentation rows: 893s startRow endRow 893s 3 10268 14658 893s TCN and DH segmentation rows: 893s startRow endRow 893s 3 10268 14658 893s startRow endRow 893s 1 10269 14655 893s startRow endRow 893s 1 1 7599 893s 2 7600 10267 893s TCN segmentation (expanded) rows: 893s startRow endRow 893s 1 1 7599 893s 2 7600 10267 893s 3 10268 14658 893s TCN and DH segmentation rows: 893s startRow endRow 893s 1 1 7599 893s 2 7600 10267 893s 3 10268 14658 893s startRow endRow 893s 1 10 7594 893s 2 7614 10263 893s 3 10269 14655 893s startRow endRow 893s 1 1 7599 893s 2 7600 10267 893s 3 10268 14658 893s Total CN segmentation table (expanded): 893s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 893s 3 1 185449813 247137334 4391 2.6341 1314 1314 893s (TCN,DH) segmentation for one total CN segment: 893s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 893s 3 3 1 1 185449813 247137334 4391 2.6341 1314 893s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 893s 3 1314 185449813 247137334 1314 0.2295 893s Total CN segment #3 ([1.8545e+08,2.47137e+08]) of 3...done 893s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 893s 1 1 1 1 554484 143926517 7599 1.3859 2120 893s 2 1 2 1 143926517 185449813 2668 2.0704 775 893s 3 1 3 1 185449813 247137334 4391 2.6341 1314 893s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 893s 1 2120 554484 143926517 2120 0.5101 893s 2 775 143926517 185449813 775 0.0970 893s 3 1314 185449813 247137334 1314 0.2295 893s Calculating (C1,C2) per segment... 893s Calculating (C1,C2) per segment...done 893s Number of segments: 3 893s Segmenting paired tumor-normal signals using Paired PSCBS...done 893s Post-segmenting TCNs... 893s Number of segments: 3 893s Number of chromosomes: 1 893s [1] 1 893s Chromosome 1 ('chr01') of 1... 893s Rows: 893s [1] 1 2 3 893s Number of segments: 3 893s TCN segment #1 ('1') of 3... 893s Nothing todo. Only one DH segmentation. Skipping. 893s TCN segment #1 ('1') of 3...done 893s TCN segment #2 ('2') of 3... 893s Nothing todo. Only one DH segmentation. Skipping. 893s TCN segment #2 ('2') of 3...done 893s TCN segment #3 ('3') of 3... 893s Nothing todo. Only one DH segmentation. Skipping. 893s TCN segment #3 ('3') of 3...done 893s Chromosome 1 ('chr01') of 1...done 893s Update (C1,C2) per segment... 893s Update (C1,C2) per segment...done 893s Post-segmenting TCNs...done 893s Segmenting by CBS...done 893s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 893s 1 1 1 1 554484 143926517 7599 1.3859 2120 893s 2 1 2 1 143926517 185449813 2668 2.0704 775 893s 3 1 3 1 185449813 247137334 4391 2.6341 1314 893s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 893s 1 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 893s 2 775 143926517 185449813 775 0.0970 0.9347856 1.135614 893s 3 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 893s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 893s 1 1 1 1 554484 143926517 7599 1.3859 2120 893s 2 1 2 1 143926517 185449813 2668 2.0704 775 893s 3 1 3 1 185449813 247137334 4391 2.6341 1314 893s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 893s 1 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 893s 2 775 143926517 185449813 775 0.0970 0.9347856 1.135614 893s 3 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 893s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 893s 1 1 1 1 554484 143926517 7599 1.3859 2120 893s 2 1 2 1 143926517 185449813 2668 2.0704 775 893s 3 1 3 1 185449813 247137334 4391 2.6341 1314 893s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 893s 1 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 893s 2 775 143926517 185449813 775 0.0970 0.9347856 1.135614 893s 3 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 893s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 893s 1 1 1 1 554484 143926517 7599 1.3859 2120 893s 2 1 2 1 143926517 185449813 2668 2.0704 775 893s 3 1 3 1 185449813 247137334 4391 2.6341 1314 893s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 893s 1 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 893s 2 775 143926517 185449813 775 0.0970 0.9347856 1.135614 893s 3 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 893s List of 4 893s $ data :'data.frame': 14658 obs. of 4 variables: 893s ..$ chromosome: int [1:14658] 2 2 2 2 2 2 2 2 2 2 ... 893s ..$ x : num [1:14658] 554484 730720 782343 878522 916294 ... 893s ..$ y : num [1:14658] 1.88 1.8 1.59 1.64 1.53 ... 893s ..$ index : int [1:14658] 1 2 3 4 5 6 7 8 9 10 ... 893s $ output :'data.frame': 3 obs. of 6 variables: 893s ..$ sampleName: chr [1:3] NA NA NA 893s ..$ chromosome: int [1:3] 2 2 2 893s ..$ start : num [1:3] 5.54e+05 1.44e+08 1.85e+08 893s ..$ end : num [1:3] 1.44e+08 1.85e+08 2.47e+08 893s ..$ nbrOfLoci : int [1:3] 7599 2668 4391 893s ..$ mean : num [1:3] 1.39 2.07 2.63 893s $ segRows:'data.frame': 3 obs. of 2 variables: 893s ..$ startRow: int [1:3] 1 7600 10268 893s ..$ endRow : int [1:3] 7599 10267 14658 893s $ params :List of 5 893s ..$ alpha : num 0.009 893s ..$ undo : num 0 893s ..$ joinSegments : logi TRUE 893s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 893s .. ..$ chromosome: int 2 893s .. ..$ start : num -Inf 893s .. ..$ end : num Inf 893s ..$ seed : int [1:7] 10407 -821273412 -52578226 1415511586 721384351 -665928286 1316562960 893s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 893s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.407 0 0.428 0 0 893s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 893s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 893s - attr(*, "randomSeed")= int [1:7] 10407 -821273412 -52578226 1415511586 721384351 -665928286 1316562960 893s Identification of change points by total copy numbers...done 893s Restructure TCN segmentation results... 893s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean 893s 1 2 554484 143926517 7599 1.3859 893s 2 2 143926517 185449813 2668 2.0704 893s 3 2 185449813 247137334 4391 2.6341 893s Number of TCN segments: 3 893s Restructure TCN segmentation results...done 893s Total CN segment #1 ([ 554484,1.43927e+08]) of 3... 893s Number of TCN loci in segment: 7599 893s Locus data for TCN segment: 893s 'data.frame': 7599 obs. of 9 variables: 893s $ chromosome: int 2 2 2 2 2 2 2 2 2 2 ... 893s $ x : num 554484 730720 782343 878522 916294 ... 893s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 893s $ betaT : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 893s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 893s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 893s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 893s $ index : int 1 2 3 4 5 6 7 8 9 10 ... 893s $ rho : num NA NA NA NA NA ... 893s Number of loci: 7599 893s Number of SNPs: 2120 (27.90%) 893s Number of heterozygous SNPs: 2120 (100.00%) 893s Chromosome: 2 893s Segmenting DH signals... 893s Segmenting by CBS... 893s Chromosome: 2 893s Random seed temporarily set (seed=c(10407, -1924040949, -1632234809, -437763632, -1464377300, 676654412, 2080370711), kind="L'Ecuyer-CMRG") 893s Segmenting by CBS...done 893s List of 4 893s $ data :'data.frame': 7599 obs. of 4 variables: 893s ..$ chromosome: int [1:7599] 2 2 2 2 2 2 2 2 2 2 ... 893s ..$ x : num [1:7599] 554484 730720 782343 878522 916294 ... 893s ..$ y : num [1:7599] NA NA NA NA NA ... 893s ..$ index : int [1:7599] 1 2 3 4 5 6 7 8 9 10 ... 893s $ output :'data.frame': 1 obs. of 6 variables: 893s ..$ sampleName: chr NA 893s ..$ chromosome: int 2 893s ..$ start : num 554484 893s ..$ end : num 1.44e+08 893s ..$ nbrOfLoci : int 2120 893s ..$ mean : num 0.51 893s $ segRows:'data.frame': 1 obs. of 2 variables: 893s ..$ startRow: int 10 893s ..$ endRow : int 7594 893s $ params :List of 5 893s ..$ alpha : num 0.001 893s ..$ undo : num 0 893s ..$ joinSegments : logi TRUE 893s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 893s .. ..$ chromosome: int 2 893s .. ..$ start : num 554484 893s .. ..$ end : num 1.44e+08 893s ..$ seed : int [1:7] 10407 -1924040949 -1632234809 -437763632 -1464377300 676654412 2080370711 893s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 893s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.026 0 0.025 0 0 893s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 893s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 893s - attr(*, "randomSeed")= int [1:7] 10407 -1924040949 -1632234809 -437763632 -1464377300 676654412 2080370711 893s DH segmentation (locally-indexed) rows: 893s startRow endRow 893s 1 10 7594 893s int [1:7599] 1 2 3 4 5 6 7 8 9 10 ... 893s DH segmentation rows: 893s startRow endRow 893s 1 10 7594 893s Segmenting DH signals...done 893s DH segmentation table: 893s dhStart dhEnd dhNbrOfLoci dhMean 893s 1 554484 143926517 2120 0.5101 893s startRow endRow 893s 1 10 7594 893s Rows: 893s [1] 1 893s TCN segmentation rows: 893s startRow endRow 893s 1 1 7599 893s TCN and DH segmentation rows: 893s startRow endRow 893s 1 1 7599 893s startRow endRow 893s 1 10 7594 893s NULL 893s TCN segmentation (expanded) rows: 893s startRow endRow 893s 1 1 7599 893s TCN and DH segmentation rows: 893s startRow endRow 893s 1 1 7599 893s 2 7600 10267 893s 3 10268 14658 893s startRow endRow 893s 1 10 7594 893s startRow endRow 893s 1 1 7599 893s Total CN segmentation table (expanded): 893s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 893s 1 2 554484 143926517 7599 1.3859 2120 2120 893s (TCN,DH) segmentation for one total CN segment: 893s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 893s 1 1 1 2 554484 143926517 7599 1.3859 2120 893s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 893s 1 2120 554484 143926517 2120 0.5101 893s Total CN segment #1 ([ 554484,1.43927e+08]) of 3...done 893s Total CN segment #2 ([1.43927e+08,1.8545e+08]) of 3... 893s Number of TCN loci in segment: 2668 893s Locus data for TCN segment: 893s 'data.frame': 2668 obs. of 9 variables: 893s $ chromosome: int 2 2 2 2 2 2 2 2 2 2 ... 893s $ x : num 1.44e+08 1.44e+08 1.44e+08 1.44e+08 1.44e+08 ... 893s $ CT : num 2.1 2.1 2.09 1.8 2.34 ... 893s $ betaT : num 0.027542 1.030222 1.094093 0.046763 -0.000948 ... 893s $ betaTN : num 0.027542 1.030222 1.094093 0.046763 -0.000948 ... 893s $ betaN : num 0.1624 0.8788 0.8225 0.1201 0.0317 ... 893s $ muN : num 0 1 1 0 0 1 0 0 0 0 ... 893s $ index : int 7600 7601 7602 7603 7604 7605 7606 7607 7608 7609 ... 893s $ rho : num NA NA NA NA NA NA NA NA NA NA ... 893s Number of loci: 2668 893s Number of SNPs: 775 (29.05%) 893s Number of heterozygous SNPs: 775 (100.00%) 893s Chromosome: 2 893s Segmenting DH signals... 893s Segmenting by CBS... 893s Chromosome: 2 894s Random seed temporarily set (seed=c(10407, -1924040949, -1632234809, -437763632, -1464377300, 676654412, 2080370711), kind="L'Ecuyer-CMRG") 894s Chromosome #3 ('Chr03') of 3...done 894s Merging (independently) segmented chromosome... 894s Segmenting by CBS...done 894s List of 4 894s $ data :'data.frame': 2668 obs. of 4 variables: 894s ..$ chromosome: int [1:2668] 2 2 2 2 2 2 2 2 2 2 ... 894s ..$ x : num [1:2668] 1.44e+08 1.44e+08 1.44e+08 1.44e+08 1.44e+08 ... 894s ..$ y : num [1:2668] NA NA NA NA NA NA NA NA NA NA ... 894s ..$ index : int [1:2668] 1 2 3 4 5 6 7 8 9 10 ... 894s $ output :'data.frame': 1 obs. of 6 variables: 894s ..$ sampleName: chr NA 894s ..$ chromosome: int 2 894s ..$ start : num 1.44e+08 894s ..$ end : num 1.85e+08 894s ..$ nbrOfLoci : int 775 894s ..$ mean : num 0.097 894s $ segRows:'data.frame': 1 obs. of 2 variables: 894s ..$ startRow: int 15 894s ..$ endRow : int 2664 894s $ params :List of 5 894s ..$ alpha : num 0.001 894s ..$ undo : num 0 894s ..$ joinSegments : logi TRUE 894s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 894s .. ..$ chromosome: int 2 894s .. ..$ start : num 1.44e+08 894s .. ..$ end : num 1.85e+08 894s ..$ seed : int [1:7] 10407 -1924040949 -1632234809 -437763632 -1464377300 676654412 2080370711 894s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 894s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.008 0 0.01 0 0 894s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 894s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 894s - attr(*, "randomSeed")= int [1:7] 10407 -1924040949 -1632234809 -437763632 -1464377300 676654412 2080370711 894s DH segmentation (locally-indexed) rows: 894s startRow endRow 894s 1 15 2664 894s int [1:2668] 7600 7601 7602 7603 7604 7605 7606 7607 7608 7609 ... 894s DH segmentation rows: 894s startRow endRow 894s 1 7614 10263 894s Segmenting DH signals...done 894s DH segmentation table: 894s dhStart dhEnd dhNbrOfLoci dhMean 894s 1 143926517 185449813 775 0.097 894s startRow endRow 894s 1 7614 10263 894s Rows: 894s [1] 2 894s TCN segmentation rows: 894s startRow endRow 894s 2 7600 10267 894s TCN and DH segmentation rows: 894s startRow endRow 894s 2 7600 10267 894s startRow endRow 894s 1 7614 10263 894s startRow endRow 894s 1 1 7599 894s TCN segmentation (expanded) rows: 894s startRow endRow 894s 1 1 7599 894s 2 7600 10267 894s TCN and DH segmentation rows: 894s Segmenting paired tumor-normal signals using Paired PSCBS... 894s Setup up data... 894s startRow endRow 894s 1 1 7599 894s 2 7600 10267 894s 3 10268 14658 894s startRow endRow 894s 1 10 7594 894s 2 7614 10263 894s startRow endRow 894s 1 1 7599 894s 2 7600 10267 894s Total CN segmentation table (expanded): 894s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 894s 2 2 143926517 185449813 2668 2.0704 775 775 894s (TCN,DH) segmentation for one total CN segment: 894s 'data.frame': 14658 obs. of 7 variables: 894s $ chromosome: int 3 3 3 3 3 3 3 3 3 3 ... 894s $ x : num 554484 730720 782343 878522 916294 ... 894s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 894s $ betaT : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 894s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 894s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 894s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 894s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 894s 2 2 1 2 143926517 185449813 2668 2.0704 775 894s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 894s 2 775 143926517 185449813 775 0.097 894s Setup up data...done 894s Total CN segment #2 ([1.43927e+08,1.8545e+08]) of 3...done 894s Ordering data along genome... 894s Total CN segment #3 ([1.8545e+08,2.47137e+08]) of 3... 894s Number of TCN loci in segment: 4391 894s Locus data for TCN segment: 894s 'data.frame': 14658 obs. of 7 variables: 894s $ chromosome: int 3 3 3 3 3 3 3 3 3 3 ... 894s $ x : num 554484 730720 782343 878522 916294 ... 894s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 894s $ betaT : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 894s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 894s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 894s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 894s Ordering data along genome...done 894s 'data.frame': 4391 obs. of 9 variables: 894s $ chromosome: int 2 2 2 2 2 2 2 2 2 2 ... 894s $ x : num 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 894s $ CT : num 2.93 2.15 2.82 2.93 2.46 ... 894s $ betaT : num -0.169 0.609 1.028 0.525 0.968 ... 894s $ betaTN : num -0.169 0.609 1.028 0.525 0.968 ... 894s $ betaN : num 0.25 0.38 0.919 0.34 0.783 ... 894s $ muN : num 0 0.5 1 0.5 1 1 0 1 0 1 ... 894s $ index : int 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 894s $ rho : num NA 0.2186 NA 0.0503 NA ... 894s Keeping only current chromosome for 'knownSegments'... 894s Number of loci: 4391 894s Number of SNPs: 1314 (29.92%) 894s Chromosome: 3 894s Number of heterozygous SNPs: 1314 (100.00%) 894s Chromosome: 2 894s Known segments for this chromosome: 894s [1] chromosome start end 894s <0 rows> (or 0-length row.names) 894s Segmenting DH signals... 894s Keeping only current chromosome for 'knownSegments'...done 894s alphaTCN: 0.009 894s alphaDH: 0.001 894s Number of loci: 14658 894s Calculating DHs... 894s Number of SNPs: 14658 894s Number of heterozygous SNPs: 4209 (28.71%) 894s Normalized DHs: 894s num [1:14658] NA NA NA NA NA ... 894s Segmenting by CBS... 894s Calculating DHs...done 894s Random seed temporarily set (seed=c(10407, -821273412, -52578226, 1415511586, 721384351, -665928286, 1316562960), kind="L'Ecuyer-CMRG") 894s Produced 2 seeds from this stream for future usage 894s Identification of change points by total copy numbers... 894s Chromosome: 2 894s Segmenting by CBS... 894s Chromosome: 3 894s Random seed temporarily set (seed=c(10407, -1924040949, -1632234809, -437763632, -1464377300, 676654412, 2080370711), kind="L'Ecuyer-CMRG") 894s Random seed temporarily set (seed=c(10407, -1924040949, -1632234809, -437763632, -1464377300, 676654412, 2080370711), kind="L'Ecuyer-CMRG") 894s Segmenting by CBS...done 894s List of 4 894s $ data :'data.frame': 4391 obs. of 4 variables: 894s ..$ chromosome: int [1:4391] 2 2 2 2 2 2 2 2 2 2 ... 894s ..$ x : num [1:4391] 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 894s ..$ y : num [1:4391] NA 0.2186 NA 0.0503 NA ... 894s ..$ index : int [1:4391] 1 2 3 4 5 6 7 8 9 10 ... 894s $ output :'data.frame': 1 obs. of 6 variables: 894s ..$ sampleName: chr NA 894s ..$ chromosome: int 2 894s ..$ start : num 1.85e+08 894s ..$ end : num 2.47e+08 894s ..$ nbrOfLoci : int 1314 894s ..$ mean : num 0.23 894s $ segRows:'data.frame': 1 obs. of 2 variables: 894s ..$ startRow: int 2 894s ..$ endRow : int 4388 894s $ params :List of 5 894s ..$ alpha : num 0.001 894s ..$ undo : num 0 894s ..$ joinSegments : logi TRUE 894s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 894s .. ..$ chromosome: int 2 894s .. ..$ start : num 1.85e+08 894s .. ..$ end : num 2.47e+08 894s ..$ seed : int [1:7] 10407 -1924040949 -1632234809 -437763632 -1464377300 676654412 2080370711 894s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 894s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.018 0 0.018 0 0 894s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 894s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 894s - attr(*, "randomSeed")= int [1:7] 10407 -1924040949 -1632234809 -437763632 -1464377300 676654412 2080370711 894s DH segmentation (locally-indexed) rows: 894s startRow endRow 894s 1 2 4388 894s int [1:4391] 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 894s DH segmentation rows: 894s startRow endRow 894s 1 10269 14655 894s Segmenting DH signals...done 894s DH segmentation table: 894s dhStart dhEnd dhNbrOfLoci dhMean 894s 1 185449813 247137334 1314 0.2295 894s startRow endRow 894s 1 10269 14655 894s Rows: 894s [1] 3 894s TCN segmentation rows: 894s startRow endRow 894s 3 10268 14658 894s TCN and DH segmentation rows: 894s startRow endRow 894s 3 10268 14658 894s startRow endRow 894s 1 10269 14655 894s startRow endRow 894s 1 1 7599 894s 2 7600 10267 894s TCN segmentation (expanded) rows: 894s startRow endRow 894s 1 1 7599 894s 2 7600 10267 894s 3 10268 14658 894s TCN and DH segmentation rows: 894s startRow endRow 894s 1 1 7599 894s 2 7600 10267 894s 3 10268 14658 894s startRow endRow 894s 1 10 7594 894s 2 7614 10263 894s 3 10269 14655 894s startRow endRow 894s 1 1 7599 894s 2 7600 10267 894s 3 10268 14658 894s Total CN segmentation table (expanded): 894s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 894s 3 2 185449813 247137334 4391 2.6341 1314 1314 894s (TCN,DH) segmentation for one total CN segment: 894s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 894s 3 3 1 2 185449813 247137334 4391 2.6341 1314 894s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 894s 3 1314 185449813 247137334 1314 0.2295 894s Total CN segment #3 ([1.8545e+08,2.47137e+08]) of 3...done 894s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 894s 1 2 1 1 554484 143926517 7599 1.3859 2120 894s 2 2 2 1 143926517 185449813 2668 2.0704 775 894s 3 2 3 1 185449813 247137334 4391 2.6341 1314 894s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 894s 1 2120 554484 143926517 2120 0.5101 894s 2 775 143926517 185449813 775 0.0970 894s 3 1314 185449813 247137334 1314 0.2295 894s Calculating (C1,C2) per segment... 894s Calculating (C1,C2) per segment...done 894s Number of segments: 3 894s Segmenting paired tumor-normal signals using Paired PSCBS...done 894s Post-segmenting TCNs... 894s Number of segments: 3 894s Number of chromosomes: 1 894s [1] 2 894s Chromosome 1 ('chr02') of 1... 894s Rows: 894s [1] 1 2 3 894s Number of segments: 3 894s TCN segment #1 ('1') of 3... 894s Nothing todo. Only one DH segmentation. Skipping. 894s TCN segment #1 ('1') of 3...done 894s TCN segment #2 ('2') of 3... 894s Nothing todo. Only one DH segmentation. Skipping. 894s TCN segment #2 ('2') of 3...done 894s TCN segment #3 ('3') of 3... 894s Nothing todo. Only one DH segmentation. Skipping. 894s TCN segment #3 ('3') of 3...done 894s Chromosome 1 ('chr02') of 1...done 894s Update (C1,C2) per segment... 894s Update (C1,C2) per segment...done 894s Post-segmenting TCNs...done 894s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 894s 1 2 1 1 554484 143926517 7599 1.3859 2120 894s 2 2 2 1 143926517 185449813 2668 2.0704 775 894s 3 2 3 1 185449813 247137334 4391 2.6341 1314 894s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 894s 1 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 894s 2 775 143926517 185449813 775 0.0970 0.9347856 1.135614 894s 3 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 894s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 894s 1 2 1 1 554484 143926517 7599 1.3859 2120 894s 2 2 2 1 143926517 185449813 2668 2.0704 775 894s 3 2 3 1 185449813 247137334 4391 2.6341 1314 894s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 894s 1 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 894s 2 775 143926517 185449813 775 0.0970 0.9347856 1.135614 894s 3 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 894s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 894s 1 2 1 1 554484 143926517 7599 1.3859 2120 894s 2 2 2 1 143926517 185449813 2668 2.0704 775 894s 3 2 3 1 185449813 247137334 4391 2.6341 1314 894s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 894s 1 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 894s 2 775 143926517 185449813 775 0.0970 0.9347856 1.135614 894s 3 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 894s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 894s 1 2 1 1 554484 143926517 7599 1.3859 2120 894s 2 2 2 1 143926517 185449813 2668 2.0704 775 894s 3 2 3 1 185449813 247137334 4391 2.6341 1314 894s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 894s 1 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 894s 2 775 143926517 185449813 775 0.0970 0.9347856 1.135614 894s 3 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 894s Segmenting by CBS...done 894s List of 4 894s $ data :'data.frame': 14658 obs. of 4 variables: 894s ..$ chromosome: int [1:14658] 3 3 3 3 3 3 3 3 3 3 ... 894s ..$ x : num [1:14658] 554484 730720 782343 878522 916294 ... 894s ..$ y : num [1:14658] 1.88 1.8 1.59 1.64 1.53 ... 894s ..$ index : int [1:14658] 1 2 3 4 5 6 7 8 9 10 ... 894s $ output :'data.frame': 3 obs. of 6 variables: 894s ..$ sampleName: chr [1:3] NA NA NA 894s ..$ chromosome: int [1:3] 3 3 3 894s ..$ start : num [1:3] 5.54e+05 1.44e+08 1.85e+08 894s ..$ end : num [1:3] 1.44e+08 1.85e+08 2.47e+08 894s ..$ nbrOfLoci : int [1:3] 7599 2668 4391 894s ..$ mean : num [1:3] 1.39 2.07 2.63 894s $ segRows:'data.frame': 3 obs. of 2 variables: 894s ..$ startRow: int [1:3] 1 7600 10268 894s ..$ endRow : int [1:3] 7599 10267 14658 894s $ params :List of 5 894s ..$ alpha : num 0.009 894s ..$ undo : num 0 894s ..$ joinSegments : logi TRUE 894s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 894s .. ..$ chromosome: int 3 894s .. ..$ start : num -Inf 894s .. ..$ end : num Inf 894s ..$ seed : int [1:7] 10407 -1924040949 -1632234809 -437763632 -1464377300 676654412 2080370711 894s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 894s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.384 0.002 0.395 0 0 894s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 894s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 894s - attr(*, "randomSeed")= int [1:7] 10407 -1924040949 -1632234809 -437763632 -1464377300 676654412 2080370711 894s Identification of change points by total copy numbers...done 894s Restructure TCN segmentation results... 894s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean 894s 1 3 554484 143926517 7599 1.3859 894s 2 3 143926517 185449813 2668 2.0704 894s 3 3 185449813 247137334 4391 2.6341 894s Number of TCN segments: 3 894s Restructure TCN segmentation results...done 894s Total CN segment #1 ([ 554484,1.43927e+08]) of 3... 894s Number of TCN loci in segment: 7599 894s Locus data for TCN segment: 894s 'data.frame': 7599 obs. of 9 variables: 894s $ chromosome: int 3 3 3 3 3 3 3 3 3 3 ... 894s $ x : num 554484 730720 782343 878522 916294 ... 894s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 894s $ betaT : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 894s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 894s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 894s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 894s $ index : int 1 2 3 4 5 6 7 8 9 10 ... 894s $ rho : num NA NA NA NA NA ... 894s Number of loci: 7599 894s Number of SNPs: 2120 (27.90%) 894s Number of heterozygous SNPs: 2120 (100.00%) 894s Chromosome: 3 894s Segmenting DH signals... 894s Segmenting by CBS... 894s Chromosome: 3 894s Random seed temporarily set (seed=c(10407, -1371615447, -889757879, 1692656974, -1723952224, 1378814990, 1816467252), kind="L'Ecuyer-CMRG") 894s Segmenting by CBS...done 894s List of 4 894s $ data :'data.frame': 7599 obs. of 4 variables: 894s ..$ chromosome: int [1:7599] 3 3 3 3 3 3 3 3 3 3 ... 894s ..$ x : num [1:7599] 554484 730720 782343 878522 916294 ... 894s ..$ y : num [1:7599] NA NA NA NA NA ... 894s ..$ index : int [1:7599] 1 2 3 4 5 6 7 8 9 10 ... 894s $ output :'data.frame': 1 obs. of 6 variables: 894s ..$ sampleName: chr NA 894s ..$ chromosome: int 3 894s ..$ start : num 554484 894s ..$ end : num 1.44e+08 894s ..$ nbrOfLoci : int 2120 894s ..$ mean : num 0.51 894s $ segRows:'data.frame': 1 obs. of 2 variables: 894s ..$ startRow: int 10 894s ..$ endRow : int 7594 894s $ params :List of 5 894s ..$ alpha : num 0.001 894s ..$ undo : num 0 894s ..$ joinSegments : logi TRUE 894s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 894s .. ..$ chromosome: int 3 894s .. ..$ start : num 554484 894s .. ..$ end : num 1.44e+08 894s ..$ seed : int [1:7] 10407 -1371615447 -889757879 1692656974 -1723952224 1378814990 1816467252 894s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 894s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.026 0 0.026 0 0 894s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 894s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 894s - attr(*, "randomSeed")= int [1:7] 10407 -1371615447 -889757879 1692656974 -1723952224 1378814990 1816467252 894s DH segmentation (locally-indexed) rows: 894s startRow endRow 894s 1 10 7594 894s int [1:7599] 1 2 3 4 5 6 7 8 9 10 ... 894s DH segmentation rows: 894s startRow endRow 894s 1 10 7594 894s Segmenting DH signals...done 894s DH segmentation table: 894s dhStart dhEnd dhNbrOfLoci dhMean 894s 1 554484 143926517 2120 0.5101 894s startRow endRow 894s 1 10 7594 894s Rows: 894s [1] 1 894s TCN segmentation rows: 894s startRow endRow 894s 1 1 7599 894s TCN and DH segmentation rows: 894s startRow endRow 894s 1 1 7599 894s startRow endRow 894s 1 10 7594 894s NULL 894s TCN segmentation (expanded) rows: 894s startRow endRow 894s 1 1 7599 894s TCN and DH segmentation rows: 894s startRow endRow 894s 1 1 7599 894s 2 7600 10267 894s 3 10268 14658 894s startRow endRow 894s 1 10 7594 894s startRow endRow 894s 1 1 7599 894s Total CN segmentation table (expanded): 894s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 894s 1 3 554484 143926517 7599 1.3859 2120 2120 894s (TCN,DH) segmentation for one total CN segment: 894s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 894s 1 1 1 3 554484 143926517 7599 1.3859 2120 894s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 894s 1 2120 554484 143926517 2120 0.5101 894s Total CN segment #1 ([ 554484,1.43927e+08]) of 3...done 894s Total CN segment #2 ([1.43927e+08,1.8545e+08]) of 3... 894s Number of TCN loci in segment: 2668 894s Locus data for TCN segment: 894s 'data.frame': 2668 obs. of 9 variables: 894s $ chromosome: int 3 3 3 3 3 3 3 3 3 3 ... 894s $ x : num 1.44e+08 1.44e+08 1.44e+08 1.44e+08 1.44e+08 ... 894s $ CT : num 2.1 2.1 2.09 1.8 2.34 ... 894s $ betaT : num 0.027542 1.030222 1.094093 0.046763 -0.000948 ... 894s $ betaTN : num 0.027542 1.030222 1.094093 0.046763 -0.000948 ... 894s $ betaN : num 0.1624 0.8788 0.8225 0.1201 0.0317 ... 894s $ muN : num 0 1 1 0 0 1 0 0 0 0 ... 894s $ index : int 7600 7601 7602 7603 7604 7605 7606 7607 7608 7609 ... 894s $ rho : num NA NA NA NA NA NA NA NA NA NA ... 894s Number of loci: 2668 894s Number of SNPs: 775 (29.05%) 894s Number of heterozygous SNPs: 775 (100.00%) 894s Chromosome: 3 894s Segmenting DH signals... 894s Segmenting by CBS... 894s Chromosome: 3 894s Random seed temporarily set (seed=c(10407, -1371615447, -889757879, 1692656974, -1723952224, 1378814990, 1816467252), kind="L'Ecuyer-CMRG") 894s Segmenting by CBS...done 894s List of 4 894s $ data :'data.frame': 2668 obs. of 4 variables: 894s ..$ chromosome: int [1:2668] 3 3 3 3 3 3 3 3 3 3 ... 894s ..$ x : num [1:2668] 1.44e+08 1.44e+08 1.44e+08 1.44e+08 1.44e+08 ... 894s ..$ y : num [1:2668] NA NA NA NA NA NA NA NA NA NA ... 894s ..$ index : int [1:2668] 1 2 3 4 5 6 7 8 9 10 ... 894s $ output :'data.frame': 1 obs. of 6 variables: 894s ..$ sampleName: chr NA 894s ..$ chromosome: int 3 894s ..$ start : num 1.44e+08 894s ..$ end : num 1.85e+08 894s ..$ nbrOfLoci : int 775 894s ..$ mean : num 0.097 894s $ segRows:'data.frame': 1 obs. of 2 variables: 894s ..$ startRow: int 15 894s ..$ endRow : int 2664 894s $ params :List of 5 894s ..$ alpha : num 0.001 894s ..$ undo : num 0 894s ..$ joinSegments : logi TRUE 894s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 894s .. ..$ chromosome: int 3 894s .. ..$ start : num 1.44e+08 894s .. ..$ end : num 1.85e+08 894s ..$ seed : int [1:7] 10407 -1371615447 -889757879 1692656974 -1723952224 1378814990 1816467252 894s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 894s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.008 0 0.009 0 0 894s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 894s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 894s - attr(*, "randomSeed")= int [1:7] 10407 -1371615447 -889757879 1692656974 -1723952224 1378814990 1816467252 894s DH segmentation (locally-indexed) rows: 894s startRow endRow 894s 1 15 2664 894s int [1:2668] 7600 7601 7602 7603 7604 7605 7606 7607 7608 7609 ... 894s DH segmentation rows: 894s startRow endRow 894s 1 7614 10263 894s Segmenting DH signals...done 894s DH segmentation table: 894s dhStart dhEnd dhNbrOfLoci dhMean 894s 1 143926517 185449813 775 0.097 894s startRow endRow 894s 1 7614 10263 894s Rows: 894s [1] 2 894s TCN segmentation rows: 894s startRow endRow 894s 2 7600 10267 894s TCN and DH segmentation rows: 894s startRow endRow 894s 2 7600 10267 894s startRow endRow 894s 1 7614 10263 894s startRow endRow 894s 1 1 7599 894s TCN segmentation (expanded) rows: 894s startRow endRow 894s 1 1 7599 894s 2 7600 10267 894s TCN and DH segmentation rows: 894s startRow endRow 894s 1 1 7599 894s 2 7600 10267 894s 3 10268 14658 894s startRow endRow 894s 1 10 7594 894s 2 7614 10263 894s startRow endRow 894s 1 1 7599 894s 2 7600 10267 894s Total CN segmentation table (expanded): 894s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 894s 2 3 143926517 185449813 2668 2.0704 775 775 894s (TCN,DH) segmentation for one total CN segment: 894s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 894s 2 2 1 3 143926517 185449813 2668 2.0704 775 894s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 894s 2 775 143926517 185449813 775 0.097 894s Total CN segment #2 ([1.43927e+08,1.8545e+08]) of 3...done 894s Total CN segment #3 ([1.8545e+08,2.47137e+08]) of 3... 894s Number of TCN loci in segment: 4391 894s Locus data for TCN segment: 894s 'data.frame': 4391 obs. of 9 variables: 894s $ chromosome: int 3 3 3 3 3 3 3 3 3 3 ... 894s $ x : num 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 894s $ CT : num 2.93 2.15 2.82 2.93 2.46 ... 894s $ betaT : num -0.169 0.609 1.028 0.525 0.968 ... 894s $ betaTN : num -0.169 0.609 1.028 0.525 0.968 ... 894s $ betaN : num 0.25 0.38 0.919 0.34 0.783 ... 894s $ muN : num 0 0.5 1 0.5 1 1 0 1 0 1 ... 894s $ index : int 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 894s $ rho : num NA 0.2186 NA 0.0503 NA ... 894s Number of loci: 4391 894s Number of SNPs: 1314 (29.92%) 894s Number of heterozygous SNPs: 1314 (100.00%) 894s Chromosome: 3 894s Segmenting DH signals... 894s Segmenting by CBS... 894s Chromosome: 3 894s Random seed temporarily set (seed=c(10407, -1371615447, -889757879, 1692656974, -1723952224, 1378814990, 1816467252), kind="L'Ecuyer-CMRG") 894s Segmenting by CBS...done 894s List of 4 894s $ data :'data.frame': 4391 obs. of 4 variables: 894s ..$ chromosome: int [1:4391] 3 3 3 3 3 3 3 3 3 3 ... 894s ..$ x : num [1:4391] 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 894s ..$ y : num [1:4391] NA 0.2186 NA 0.0503 NA ... 894s ..$ index : int [1:4391] 1 2 3 4 5 6 7 8 9 10 ... 894s $ output :'data.frame': 1 obs. of 6 variables: 894s ..$ sampleName: chr NA 894s ..$ chromosome: int 3 894s ..$ start : num 1.85e+08 894s ..$ end : num 2.47e+08 894s ..$ nbrOfLoci : int 1314 894s ..$ mean : num 0.23 894s $ segRows:'data.frame': 1 obs. of 2 variables: 894s ..$ startRow: int 2 894s ..$ endRow : int 4388 894s $ params :List of 5 894s ..$ alpha : num 0.001 894s ..$ undo : num 0 894s ..$ joinSegments : logi TRUE 894s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 894s .. ..$ chromosome: int 3 894s .. ..$ start : num 1.85e+08 894s .. ..$ end : num 2.47e+08 894s ..$ seed : int [1:7] 10407 -1371615447 -889757879 1692656974 -1723952224 1378814990 1816467252 894s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 894s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.016 0 0.016 0 0 894s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 894s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 894s - attr(*, "randomSeed")= int [1:7] 10407 -1371615447 -889757879 1692656974 -1723952224 1378814990 1816467252 894s DH segmentation (locally-indexed) rows: 894s startRow endRow 894s 1 2 4388 894s int [1:4391] 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 894s DH segmentation rows: 894s startRow endRow 894s 1 10269 14655 894s Segmenting DH signals...done 894s DH segmentation table: 894s dhStart dhEnd dhNbrOfLoci dhMean 894s 1 185449813 247137334 1314 0.2295 894s startRow endRow 894s 1 10269 14655 894s Rows: 894s [1] 3 894s TCN segmentation rows: 894s startRow endRow 894s 3 10268 14658 894s TCN and DH segmentation rows: 894s startRow endRow 894s 3 10268 14658 894s startRow endRow 894s 1 10269 14655 894s startRow endRow 894s 1 1 7599 894s 2 7600 10267 894s TCN segmentation (expanded) rows: 894s startRow endRow 894s 1 1 7599 894s 2 7600 10267 894s 3 10268 14658 894s TCN and DH segmentation rows: 894s startRow endRow 894s 1 1 7599 894s 2 7600 10267 894s 3 10268 14658 894s startRow endRow 894s 1 10 7594 894s 2 7614 10263 894s 3 10269 14655 894s startRow endRow 894s 1 1 7599 894s 2 7600 10267 894s 3 10268 14658 894s Total CN segmentation table (expanded): 894s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 894s 3 3 185449813 247137334 4391 2.6341 1314 1314 894s (TCN,DH) segmentation for one total CN segment: 894s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 894s 3 3 1 3 185449813 247137334 4391 2.6341 1314 894s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 894s 3 1314 185449813 247137334 1314 0.2295 894s Total CN segment #3 ([1.8545e+08,2.47137e+08]) of 3...done 894s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 894s 1 3 1 1 554484 143926517 7599 1.3859 2120 894s 2 3 2 1 143926517 185449813 2668 2.0704 775 894s 3 3 3 1 185449813 247137334 4391 2.6341 1314 894s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 894s 1 2120 554484 143926517 2120 0.5101 894s 2 775 143926517 185449813 775 0.0970 894s 3 1314 185449813 247137334 1314 0.2295 894s Calculating (C1,C2) per segment... 894s Calculating (C1,C2) per segment...done 894s Number of segments: 3 894s Segmenting paired tumor-normal signals using Paired PSCBS...done 894s Post-segmenting TCNs... 894s Number of segments: 3 894s Number of chromosomes: 1 894s [1] 3 894s Chromosome 1 ('chr03') of 1... 894s Rows: 894s [1] 1 2 3 894s Number of segments: 3 894s TCN segment #1 ('1') of 3... 894s Nothing todo. Only one DH segmentation. Skipping. 894s TCN segment #1 ('1') of 3...done 894s TCN segment #2 ('2') of 3... 894s Nothing todo. Only one DH segmentation. Skipping. 894s TCN segment #2 ('2') of 3...done 894s TCN segment #3 ('3') of 3... 894s Nothing todo. Only one DH segmentation. Skipping. 894s TCN segment #3 ('3') of 3...done 894s Chromosome 1 ('chr03') of 1...done 894s Update (C1,C2) per segment... 894s Update (C1,C2) per segment...done 894s Post-segmenting TCNs...done 894s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 894s 1 3 1 1 554484 143926517 7599 1.3859 2120 894s 2 3 2 1 143926517 185449813 2668 2.0704 775 894s 3 3 3 1 185449813 247137334 4391 2.6341 1314 894s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 894s 1 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 894s 2 775 143926517 185449813 775 0.0970 0.9347856 1.135614 894s 3 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 894s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 894s 1 3 1 1 554484 143926517 7599 1.3859 2120 894s 2 3 2 1 143926517 185449813 2668 2.0704 775 894s 3 3 3 1 185449813 247137334 4391 2.6341 1314 894s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 894s 1 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 894s 2 775 143926517 185449813 775 0.0970 0.9347856 1.135614 894s 3 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 894s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 894s 1 3 1 1 554484 143926517 7599 1.3859 2120 894s 2 3 2 1 143926517 185449813 2668 2.0704 775 894s 3 3 3 1 185449813 247137334 4391 2.6341 1314 894s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 894s 1 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 894s 2 775 143926517 185449813 775 0.0970 0.9347856 1.135614 894s 3 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 894s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 894s 1 3 1 1 554484 143926517 7599 1.3859 2120 894s 2 3 2 1 143926517 185449813 2668 2.0704 775 894s 3 3 3 1 185449813 247137334 4391 2.6341 1314 894s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 894s 1 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 894s 2 775 143926517 185449813 775 0.0970 0.9347856 1.135614 894s 3 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 895s List of 5 895s $ data :Classes ‘PairedPSCNData’ and 'data.frame': 43974 obs. of 8 variables: 895s ..$ chromosome: int [1:43974] 1 1 1 1 1 1 1 1 1 1 ... 895s ..$ x : num [1:43974] 554484 730720 782343 878522 916294 ... 895s ..$ CT : num [1:43974] 1.88 1.8 1.59 1.64 1.53 ... 895s ..$ betaT : num [1:43974] 0.0646 0.1672 0.9284 0.113 0.7209 ... 895s ..$ betaTN : num [1:43974] -0.0515 -0.1172 1.0194 0.031 0.8604 ... 895s ..$ betaN : num [1:43974] 0.116 0.284 0.909 0.082 0.86 ... 895s ..$ muN : num [1:43974] 0 0 1 0 1 1 1 0 1 0.5 ... 895s ..$ rho : num [1:43974] NA NA NA NA NA ... 895s $ output :Classes ‘PairedPSCNSegments’ and 'data.frame': 11 obs. of 15 variables: 895s ..$ chromosome : int [1:11] 1 1 1 NA 2 2 2 NA 3 3 ... 895s ..$ tcnId : int [1:11] 1 2 3 NA 1 2 3 NA 1 2 ... 895s ..$ dhId : int [1:11] 1 1 1 NA 1 1 1 NA 1 1 ... 895s ..$ tcnStart : num [1:11] 5.54e+05 1.44e+08 1.85e+08 NA 5.54e+05 ... 895s ..$ tcnEnd : num [1:11] 1.44e+08 1.85e+08 2.47e+08 NA 1.44e+08 ... 895s ..$ tcnNbrOfLoci: int [1:11] 7599 2668 4391 NA 7599 2668 4391 NA 7599 2668 ... 895s ..$ tcnMean : num [1:11] 1.39 2.07 2.63 NA 1.39 ... 895s ..$ tcnNbrOfSNPs: int [1:11] 2120 775 1314 NA 2120 775 1314 NA 2120 775 ... 895s ..$ tcnNbrOfHets: int [1:11] 2120 775 1314 NA 2120 775 1314 NA 2120 775 ... 895s ..$ dhStart : num [1:11] 5.54e+05 1.44e+08 1.85e+08 NA 5.54e+05 ... 895s ..$ dhEnd : num [1:11] 1.44e+08 1.85e+08 2.47e+08 NA 1.44e+08 ... 895s ..$ dhNbrOfLoci : int [1:11] 2120 775 1314 NA 2120 775 1314 NA 2120 775 ... 895s ..$ dhMean : num [1:11] 0.51 0.097 0.23 NA 0.51 ... 895s ..$ c1Mean : num [1:11] 0.339 0.935 1.015 NA 0.339 ... 895s ..$ c2Mean : num [1:11] 1.05 1.14 1.62 NA 1.05 ... 895s $ tcnSegRows:'data.frame': 11 obs. of 2 variables: 895s ..$ startRow: int [1:11] 1 7600 10268 NA 14659 22258 24926 NA 29317 36916 ... 895s ..$ endRow : int [1:11] 7599 10267 14658 NA 22257 24925 29316 NA 36915 39583 ... 895s $ dhSegRows :'data.frame': 11 obs. of 2 variables: 895s ..$ startRow: int [1:11] 10 7614 10269 NA 14668 22272 24927 NA 29326 36930 ... 895s ..$ endRow : int [1:11] 7594 10263 14655 NA 22252 24921 29313 NA 36910 39579 ... 895s $ params :List of 7 895s ..$ alphaTCN : num 0.009 895s ..$ alphaDH : num 0.001 895s ..$ flavor : chr "tcn&dh" 895s ..$ tbn : logi FALSE 895s ..$ joinSegments : logi TRUE 895s ..$ knownSegments:'data.frame': 0 obs. of 3 variables: 895s .. ..$ chromosome: int(0) 895s .. ..$ start : int(0) 895s .. ..$ end : int(0) 895s ..$ seed : int [1:7] 10407 1066287653 -51199871 161854402 -1995183193 1503453565 -747102133 895s - attr(*, "class")= chr [1:3] "PairedPSCBS" "PSCBS" "AbstractCBS" 895s Merging (independently) segmented chromosome...done 895s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 895s 1 1 1 1 554484 143926517 7599 1.3859 2120 895s 2 1 2 1 143926517 185449813 2668 2.0704 775 895s 3 1 3 1 185449813 247137334 4391 2.6341 1314 895s 4 NA NA NA NA NA NA NA NA 895s 5 2 1 1 554484 143926517 7599 1.3859 2120 895s 6 2 2 1 143926517 185449813 2668 2.0704 775 895s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 895s 1 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 895s 2 775 143926517 185449813 775 0.0970 0.9347856 1.135614 895s 3 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 895s 4 NA NA NA NA NA NA NA 895s 5 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 895s 6 775 143926517 185449813 775 0.0970 0.9347856 1.135614 895s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 895s 6 2 2 1 143926517 185449813 2668 2.0704 775 895s 7 2 3 1 185449813 247137334 4391 2.6341 1314 895s 8 NA NA NA NA NA NA NA NA 895s 9 3 1 1 554484 143926517 7599 1.3859 2120 895s 10 3 2 1 143926517 185449813 2668 2.0704 775 895s 11 3 3 1 185449813 247137334 4391 2.6341 1314 895s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 895s 6 775 143926517 185449813 775 0.0970 0.9347856 1.135614 895s 7 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 895s 8 NA NA NA NA NA NA NA 895s 9 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 895s 10 775 143926517 185449813 775 0.0970 0.9347856 1.135614 895s 11 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 895s Segmenting multiple chromosomes...done 895s Segmenting paired tumor-normal signals using Paired PSCBS...done 895s > 895s > message("*** segmentByPairedPSCBS() via futures ... DONE") 895s > 895s > 895s > message("*** segmentByPairedPSCBS() via futures with known segments ...") 895s *** segmentByPairedPSCBS() via futures ... DONE 895s > fits <- list() 895s > dataT <- subset(data, chromosome == 1) 895s *** segmentByPairedPSCBS() via futures with known segments ... 895s > gaps <- findLargeGaps(dataT, minLength=2e6) 895s > knownSegments <- gapsToSegments(gaps) 895s > 895s > for (strategy in strategies) { 895s + message(sprintf("- segmentByPairedPSCBS() w/ known segments using '%s' futures ...", strategy)) 895s + plan(strategy) 895s + fit <- segmentByPairedPSCBS(dataT, knownSegments=knownSegments, seed=0xBEEF, verbose=TRUE) 895s + fits[[strategy]] <- fit 895s + equal <- all.equal(fit, fits[[1]]) 895s + if (!equal) { 895s + str(fit) 895s + str(fits[[1]]) 895s + print(equal) 895s + stop(sprintf("segmentByPairedPSCBS() w/ known segments using '%s' futures does not produce the same results as when using '%s' futures", strategy, names(fits)[1])) 895s + } 895s + } 895s - segmentByPairedPSCBS() w/ known segments using 'sequential' futures ... 895s Segmenting paired tumor-normal signals using Paired PSCBS... 895s Calling genotypes from normal allele B fractions... 895s num [1:14670] 0.8274 0.5072 0.1671 0.1609 0.0421 ... 895s Called genotypes: 895s num [1:14670] 1 0.5 0 0 0 0 1 0 1 0.5 ... 895s - attr(*, "modelFit")=List of 1 895s ..$ :List of 7 895s .. ..$ flavor : chr "density" 895s .. ..$ cn : int 2 895s .. ..$ nbrOfGenotypeGroups: int 3 895s .. ..$ tau : num [1:2] 0.315 0.677 895s .. ..$ n : int 14640 895s .. ..$ fit :Classes ‘PeaksAndValleys’ and 'data.frame': 5 obs. of 3 variables: 895s .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 895s .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 895s .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 895s .. ..$ fitValleys :Classes ‘PeaksAndValleys’ and 'data.frame': 2 obs. of 3 variables: 895s .. .. ..$ type : chr [1:2] "valley" "valley" 895s .. .. ..$ x : num [1:2] 0.315 0.677 895s .. .. ..$ density: num [1:2] 0.522 0.551 895s ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 895s muN 895s 0 0.5 1 895s 5221 4198 5251 895s Calling genotypes from normal allele B fractions...done 895s Normalizing betaT using betaN (TumorBoost)... 895s Normalized BAFs: 895s num [1:14670] 0.9301 0.1667 0.0685 0.0995 0.0155 ... 895s - attr(*, "modelFit")=List of 5 895s ..$ method : chr "normalizeTumorBoost" 895s ..$ flavor : chr "v4" 895s ..$ delta : num [1:14670] -0.17264 0.00239 0.1671 0.16085 0.04213 ... 895s .. ..- attr(*, "modelFit")=List of 1 895s .. .. ..$ :List of 7 895s .. .. .. ..$ flavor : chr "density" 895s .. .. .. ..$ cn : int 2 895s .. .. .. ..$ nbrOfGenotypeGroups: int 3 895s .. .. .. ..$ tau : num [1:2] 0.315 0.677 895s .. .. .. ..$ n : int 14640 895s .. .. .. ..$ fit :Classes ‘PeaksAndValleys’ and 'data.frame': 5 obs. of 3 variables: 895s .. .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 895s .. .. .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 895s .. .. .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 895s .. .. .. ..$ fitValleys :Classes ‘PeaksAndValleys’ and 'data.frame': 2 obs. of 3 variables: 895s .. .. .. .. ..$ type : chr [1:2] "valley" "valley" 895s .. .. .. .. ..$ x : num [1:2] 0.315 0.677 895s .. .. .. .. ..$ density: num [1:2] 0.522 0.551 895s .. .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 895s ..$ preserveScale: logi FALSE 895s ..$ scaleFactor : num NA 895s Normalizing betaT using betaN (TumorBoost)...done 895s Setup up data... 895s 'data.frame': 14670 obs. of 7 variables: 895s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 895s $ x : num 1145994 2941694 3710825 4240737 4276892 ... 895s $ CT : num 1.63 1.4 1.41 1.17 1.16 ... 895s $ betaT : num 0.7574 0.169 0.2357 0.2604 0.0576 ... 895s $ betaTN : num 0.9301 0.1667 0.0685 0.0995 0.0155 ... 895s ..- attr(*, "modelFit")=List of 5 895s .. ..$ method : chr "normalizeTumorBoost" 895s .. ..$ flavor : chr "v4" 895s .. ..$ delta : num [1:14670] -0.17264 0.00239 0.1671 0.16085 0.04213 ... 895s .. .. ..- attr(*, "modelFit")=List of 1 895s .. .. .. ..$ :List of 7 895s .. .. .. .. ..$ flavor : chr "density" 895s .. .. .. .. ..$ cn : int 2 895s .. .. .. .. ..$ nbrOfGenotypeGroups: int 3 895s .. .. .. .. ..$ tau : num [1:2] 0.315 0.677 895s .. .. .. .. ..$ n : int 14640 895s .. .. .. .. ..$ fit :Classes ‘PeaksAndValleys’ and 'data.frame': 5 obs. of 3 variables: 895s .. .. .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 895s .. .. .. .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 895s .. .. .. .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 895s .. .. .. .. ..$ fitValleys :Classes ‘PeaksAndValleys’ and 'data.frame': 2 obs. of 3 variables: 895s .. .. .. .. .. ..$ type : chr [1:2] "valley" "valley" 895s .. .. .. .. .. ..$ x : num [1:2] 0.315 0.677 895s .. .. .. .. .. ..$ density: num [1:2] 0.522 0.551 895s .. .. .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 895s .. ..$ preserveScale: logi FALSE 895s .. ..$ scaleFactor : num NA 895s $ betaN : num 0.8274 0.5072 0.1671 0.1609 0.0421 ... 895s $ muN : num 1 0.5 0 0 0 0 1 0 1 0.5 ... 895s ..- attr(*, "modelFit")=List of 1 895s .. ..$ :List of 7 895s .. .. ..$ flavor : chr "density" 895s .. .. ..$ cn : int 2 895s .. .. ..$ nbrOfGenotypeGroups: int 3 895s .. .. ..$ tau : num [1:2] 0.315 0.677 895s .. .. ..$ n : int 14640 895s .. .. ..$ fit :Classes ‘PeaksAndValleys’ and 'data.frame': 5 obs. of 3 variables: 895s .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 895s .. .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 895s .. .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 895s .. .. ..$ fitValleys :Classes ‘PeaksAndValleys’ and 'data.frame': 2 obs. of 3 variables: 895s .. .. .. ..$ type : chr [1:2] "valley" "valley" 895s .. .. .. ..$ x : num [1:2] 0.315 0.677 895s .. .. .. ..$ density: num [1:2] 0.522 0.551 895s .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 895s Setup up data...done 895s Dropping loci for which TCNs are missing... 895s Number of loci dropped: 12 895s Dropping loci for which TCNs are missing...done 895s Ordering data along genome... 895s 'data.frame': 14658 obs. of 7 variables: 895s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 895s $ x : num 554484 730720 782343 878522 916294 ... 895s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 895s $ betaT : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 895s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 895s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 895s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 895s Ordering data along genome...done 895s Keeping only current chromosome for 'knownSegments'... 895s Chromosome: 1 895s Known segments for this chromosome: 895s chromosome start end length 895s 1 1 -Inf 120908858 Inf 895s 2 1 120908859 142693887 21785028 895s 3 1 142693888 Inf Inf 895s Keeping only current chromosome for 'knownSegments'...done 895s alphaTCN: 0.009 895s alphaDH: 0.001 895s Number of loci: 14658 895s Calculating DHs... 895s Number of SNPs: 14658 895s Number of heterozygous SNPs: 4196 (28.63%) 895s Normalized DHs: 895s num [1:14658] NA NA NA NA NA ... 895s Calculating DHs...done 895s Random seed temporarily set (seed=c(48879), kind="L'Ecuyer-CMRG") 895s Produced 2 seeds from this stream for future usage 895s Identification of change points by total copy numbers... 895s Segmenting by CBS... 895s Chromosome: 1 895s Random seed temporarily set (seed=c(10407, 1066287653, -51199871, 161854402, -1995183193, 1503453565, -747102133), kind="L'Ecuyer-CMRG") 895s Produced 3 seeds from this stream for future usage 895s Segmenting by CBS...done 895s List of 4 895s $ data :'data.frame': 14658 obs. of 4 variables: 895s ..$ chromosome: int [1:14658] 1 1 1 1 1 1 1 1 1 1 ... 895s ..$ x : num [1:14658] 554484 730720 782343 878522 916294 ... 895s ..$ y : num [1:14658] 1.88 1.8 1.59 1.64 1.53 ... 895s ..$ index : int [1:14658] 1 2 3 4 5 6 7 8 9 10 ... 895s $ output :'data.frame': 4 obs. of 6 variables: 895s ..$ sampleName: chr [1:4] NA NA NA NA 895s ..$ chromosome: int [1:4] 1 1 1 1 895s ..$ start : num [1:4] 5.54e+05 1.21e+08 1.43e+08 1.85e+08 895s ..$ end : num [1:4] 1.21e+08 1.43e+08 1.85e+08 2.47e+08 895s ..$ nbrOfLoci : int [1:4] 7586 0 2681 4391 895s ..$ mean : num [1:4] 1.39 NA 2.07 2.63 895s $ segRows:'data.frame': 4 obs. of 2 variables: 895s ..$ startRow: int [1:4] 1 NA 7587 10268 895s ..$ endRow : int [1:4] 7586 NA 10267 14658 895s $ params :List of 5 895s ..$ alpha : num 0.009 895s ..$ undo : num 0 895s ..$ joinSegments : logi TRUE 895s ..$ knownSegments:'data.frame': 4 obs. of 3 variables: 895s .. ..$ chromosome: int [1:4] 1 1 2 1 895s .. ..$ start : num [1:4] -Inf -Inf -Inf 1.43e+08 895s .. ..$ end : num [1:4] 1.21e+08 Inf Inf Inf 895s ..$ seed : int [1:7] 10407 1066287653 -51199871 161854402 -1995183193 1503453565 -747102133 895s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 895s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.128 0 0.128 0 0 895s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 895s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 895s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 895s Identification of change points by total copy numbers...done 895s Restructure TCN segmentation results... 895s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean 895s 1 1 554484 120908858 7586 1.3853 895s 2 1 120908859 142693887 0 NA 895s 3 1 142693888 185449813 2681 2.0689 895s 4 1 185449813 247137334 4391 2.6341 895s Number of TCN segments: 4 895s Restructure TCN segmentation results...done 895s Total CN segment #1 ([ 554484,1.20909e+08]) of 4... 895s Number of TCN loci in segment: 7586 895s Locus data for TCN segment: 895s 'data.frame': 7586 obs. of 9 variables: 895s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 895s $ x : num 554484 730720 782343 878522 916294 ... 895s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 895s $ betaT : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 895s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 895s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 895s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 895s $ index : int 1 2 3 4 5 6 7 8 9 10 ... 895s $ rho : num NA NA NA NA NA ... 895s Number of loci: 7586 895s Number of SNPs: 2108 (27.79%) 895s Number of heterozygous SNPs: 2108 (100.00%) 895s Chromosome: 1 895s Segmenting DH signals... 895s Segmenting by CBS... 895s Chromosome: 1 895s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 895s Segmenting by CBS...done 895s List of 4 895s $ data :'data.frame': 7586 obs. of 4 variables: 895s ..$ chromosome: int [1:7586] 1 1 1 1 1 1 1 1 1 1 ... 895s ..$ x : num [1:7586] 554484 730720 782343 878522 916294 ... 895s ..$ y : num [1:7586] NA NA NA NA NA ... 895s ..$ index : int [1:7586] 1 2 3 4 5 6 7 8 9 10 ... 895s $ output :'data.frame': 1 obs. of 6 variables: 895s ..$ sampleName: chr NA 895s ..$ chromosome: int 1 895s ..$ start : num 554484 895s ..$ end : num 1.21e+08 895s ..$ nbrOfLoci : int 2108 895s ..$ mean : num 0.512 895s $ segRows:'data.frame': 1 obs. of 2 variables: 895s ..$ startRow: int 10 895s ..$ endRow : int 7574 895s $ params :List of 5 895s ..$ alpha : num 0.001 895s ..$ undo : num 0 895s ..$ joinSegments : logi TRUE 895s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 895s .. ..$ chromosome: int 1 895s .. ..$ start : num 554484 895s .. ..$ end : num 1.21e+08 895s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 895s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 895s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.038 0 0.037 0 0 895s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 895s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 895s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 895s DH segmentation (locally-indexed) rows: 895s startRow endRow 895s 1 10 7574 895s int [1:7586] 1 2 3 4 5 6 7 8 9 10 ... 895s DH segmentation rows: 895s startRow endRow 895s 1 10 7574 895s Segmenting DH signals...done 895s DH segmentation table: 895s dhStart dhEnd dhNbrOfLoci dhMean 895s 1 554484 120908858 2108 0.5116 895s startRow endRow 895s 1 10 7574 895s Rows: 895s [1] 1 895s TCN segmentation rows: 895s startRow endRow 895s 1 1 7586 895s TCN and DH segmentation rows: 895s startRow endRow 895s 1 1 7586 895s startRow endRow 895s 1 10 7574 895s NULL 895s TCN segmentation (expanded) rows: 895s startRow endRow 895s 1 1 7586 895s TCN and DH segmentation rows: 895s startRow endRow 895s 1 1 7586 895s 2 NA NA 895s 3 7587 10267 895s 4 10268 14658 895s startRow endRow 895s 1 10 7574 895s startRow endRow 895s 1 1 7586 895s Total CN segmentation table (expanded): 896s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 896s 1 1 554484 120908858 7586 1.3853 2108 2108 896s (TCN,DH) segmentation for one total CN segment: 896s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 896s 1 1 1 1 554484 120908858 7586 1.3853 2108 896s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 896s 1 2108 554484 120908858 2108 0.5116 896s Total CN segment #1 ([ 554484,1.20909e+08]) of 4...done 896s Total CN segment #2 ([1.20909e+08,1.42694e+08]) of 4... 896s Number of TCN loci in segment: 0 896s Locus data for TCN segment: 896s 'data.frame': 0 obs. of 9 variables: 896s $ chromosome: int 896s $ x : num 896s $ CT : num 896s $ betaT : num 896s $ betaTN : num 896s $ betaN : num 896s $ muN : num 896s $ index : int 896s $ rho : num 896s Number of loci: 0 896s Number of SNPs: 0 (NaN%) 896s Number of heterozygous SNPs: 0 (NaN%) 896s Chromosome: 1 896s Segmenting DH signals... 896s Segmenting by CBS... 896s Chromosome: NA 896s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 896s Segmenting by CBS...done 896s List of 4 896s $ data :'data.frame': 0 obs. of 4 variables: 896s ..$ chromosome: int(0) 896s ..$ x : num(0) 896s ..$ y : num(0) 896s ..$ index : int(0) 896s $ output :'data.frame': 0 obs. of 6 variables: 896s ..$ sampleName: chr(0) 896s ..$ chromosome: num(0) 896s ..$ start : num(0) 896s ..$ end : num(0) 896s ..$ nbrOfLoci : int(0) 896s ..$ mean : num(0) 896s $ segRows:'data.frame': 0 obs. of 2 variables: 896s ..$ startRow: int(0) 896s ..$ endRow : int(0) 896s $ params :List of 5 896s ..$ alpha : num 0.001 896s ..$ undo : num 0 896s ..$ joinSegments : logi TRUE 896s ..$ knownSegments:'data.frame': 0 obs. of 3 variables: 896s .. ..$ chromosome: int(0) 896s .. ..$ start : num(0) 896s .. ..$ end : num(0) 896s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 896s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 896s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.002 0 0.002 0 0 896s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 896s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 896s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 896s DH segmentation (locally-indexed) rows: 896s [1] startRow endRow 896s <0 rows> (or 0-length row.names) 896s int(0) 896s DH segmentation rows: 896s [1] startRow endRow 896s <0 rows> (or 0-length row.names) 896s Segmenting DH signals...done 896s DH segmentation table: 896s dhStart dhEnd dhNbrOfLoci dhMean 896s NA NA NA NA NA 896s startRow endRow 896s NA NA NA 896s Rows: 896s [1] 2 896s TCN segmentation rows: 896s startRow endRow 896s 2 NA NA 896s TCN and DH segmentation rows: 896s startRow endRow 896s 2 NA NA 896s startRow endRow 896s NA NA NA 896s startRow endRow 896s 1 1 7586 896s TCN segmentation (expanded) rows: 896s startRow endRow 896s 1 1 7586 896s 2 NA NA 896s TCN and DH segmentation rows: 896s startRow endRow 896s 1 1 7586 896s 2 NA NA 896s 3 7587 10267 896s 4 10268 14658 896s startRow endRow 896s 1 10 7574 896s 2 NA NA 896s startRow endRow 896s 1 1 7586 896s 2 NA NA 896s Total CN segmentation table (expanded): 896s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 896s 2 1 120908859 142693887 0 NA 0 0 896s (TCN,DH) segmentation for one total CN segment: 896s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 896s 2 2 1 1 120908859 142693887 0 NA 0 896s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 896s 2 0 NA NA NA NA 896s Total CN segment #2 ([1.20909e+08,1.42694e+08]) of 4...done 896s Total CN segment #3 ([1.42694e+08,1.8545e+08]) of 4... 896s Number of TCN loci in segment: 2681 896s Locus data for TCN segment: 896s 'data.frame': 2681 obs. of 9 variables: 896s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 896s $ x : num 1.43e+08 1.43e+08 1.43e+08 1.43e+08 1.44e+08 ... 896s $ CT : num 2.27 1.55 1.47 1.5 1.81 ... 896s $ betaT : num 0.34 0.55 0.048 0.813 0.575 ... 896s $ betaTN : num 0.441 0.629 -0.05 0.958 0.872 ... 896s $ betaN : num 0.3851 0.3933 0.0981 0.8552 0.7028 ... 896s $ muN : num 0.5 0.5 0 1 1 1 1 0.5 1 1 ... 896s $ index : int 7587 7588 7589 7590 7591 7592 7593 7594 7595 7596 ... 896s $ rho : num 0.117 0.258 NA NA NA ... 896s Number of loci: 2681 896s Number of SNPs: 777 (28.98%) 896s Number of heterozygous SNPs: 777 (100.00%) 896s Chromosome: 1 896s Segmenting DH signals... 896s Segmenting by CBS... 896s Chromosome: 1 896s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 896s Segmenting by CBS...done 896s List of 4 896s $ data :'data.frame': 2681 obs. of 4 variables: 896s ..$ chromosome: int [1:2681] 1 1 1 1 1 1 1 1 1 1 ... 896s ..$ x : num [1:2681] 1.43e+08 1.43e+08 1.43e+08 1.43e+08 1.44e+08 ... 896s ..$ y : num [1:2681] 0.117 0.258 NA NA NA ... 896s ..$ index : int [1:2681] 1 2 3 4 5 6 7 8 9 10 ... 896s $ output :'data.frame': 1 obs. of 6 variables: 896s ..$ sampleName: chr NA 896s ..$ chromosome: int 1 896s ..$ start : num 1.43e+08 896s ..$ end : num 1.85e+08 896s ..$ nbrOfLoci : int 777 896s ..$ mean : num 0.0973 896s $ segRows:'data.frame': 1 obs. of 2 variables: 896s ..$ startRow: int 1 896s ..$ endRow : int 2677 896s $ params :List of 5 896s ..$ alpha : num 0.001 896s ..$ undo : num 0 896s ..$ joinSegments : logi TRUE 896s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 896s .. ..$ chromosome: int 1 896s .. ..$ start : num 1.43e+08 896s .. ..$ end : num 1.85e+08 896s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 896s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 896s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.008 0 0.008 0 0 896s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 896s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 896s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 896s DH segmentation (locally-indexed) rows: 896s startRow endRow 896s 1 1 2677 896s int [1:2681] 7587 7588 7589 7590 7591 7592 7593 7594 7595 7596 ... 896s DH segmentation rows: 896s startRow endRow 896s 1 7587 10263 896s Segmenting DH signals...done 896s DH segmentation table: 896s dhStart dhEnd dhNbrOfLoci dhMean 896s 1 142693888 185449813 777 0.0973 896s startRow endRow 896s 1 7587 10263 896s Rows: 896s [1] 3 896s TCN segmentation rows: 896s startRow endRow 896s 3 7587 10267 896s TCN and DH segmentation rows: 896s startRow endRow 896s 3 7587 10267 896s startRow endRow 896s 1 7587 10263 896s startRow endRow 896s 1 1 7586 896s 2 NA NA 896s TCN segmentation (expanded) rows: 896s startRow endRow 896s 1 1 7586 896s 2 NA NA 896s 3 7587 10267 896s TCN and DH segmentation rows: 896s startRow endRow 896s 1 1 7586 896s 2 NA NA 896s 3 7587 10267 896s 4 10268 14658 896s startRow endRow 896s 1 10 7574 896s 2 NA NA 896s 3 7587 10263 896s startRow endRow 896s 1 1 7586 896s 2 NA NA 896s 3 7587 10267 896s Total CN segmentation table (expanded): 896s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 896s 3 1 142693888 185449813 2681 2.0689 777 777 896s (TCN,DH) segmentation for one total CN segment: 896s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 896s 3 3 1 1 142693888 185449813 2681 2.0689 777 896s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 896s 3 777 142693888 185449813 777 0.0973 896s Total CN segment #3 ([1.42694e+08,1.8545e+08]) of 4...done 896s Total CN segment #4 ([1.8545e+08,2.47137e+08]) of 4... 896s Number of TCN loci in segment: 4391 896s Locus data for TCN segment: 896s 'data.frame': 4391 obs. of 9 variables: 896s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 896s $ x : num 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 896s $ CT : num 2.93 2.15 2.82 2.93 2.46 ... 896s $ betaT : num 0.0811 0.5154 0.9473 0.3734 0.7506 ... 896s $ betaTN : num -0.169 0.609 1.028 0.525 0.968 ... 896s $ betaN : num 0.25 0.38 0.919 0.34 0.783 ... 896s $ muN : num 0 0.5 1 0.5 1 1 0 1 0 1 ... 896s $ index : int 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 896s $ rho : num NA 0.2186 NA 0.0503 NA ... 896s Number of loci: 4391 896s Number of SNPs: 1311 (29.86%) 896s Number of heterozygous SNPs: 1311 (100.00%) 896s Chromosome: 1 896s Segmenting DH signals... 896s Segmenting by CBS... 896s Chromosome: 1 896s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 896s Segmenting by CBS...done 896s List of 4 896s $ data :'data.frame': 4391 obs. of 4 variables: 896s ..$ chromosome: int [1:4391] 1 1 1 1 1 1 1 1 1 1 ... 896s ..$ x : num [1:4391] 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 896s ..$ y : num [1:4391] NA 0.2186 NA 0.0503 NA ... 896s ..$ index : int [1:4391] 1 2 3 4 5 6 7 8 9 10 ... 896s $ output :'data.frame': 1 obs. of 6 variables: 896s ..$ sampleName: chr NA 896s ..$ chromosome: int 1 896s ..$ start : num 1.85e+08 896s ..$ end : num 2.47e+08 896s ..$ nbrOfLoci : int 1311 896s ..$ mean : num 0.23 896s $ segRows:'data.frame': 1 obs. of 2 variables: 896s ..$ startRow: int 2 896s ..$ endRow : int 4388 896s $ params :List of 5 896s ..$ alpha : num 0.001 896s ..$ undo : num 0 896s ..$ joinSegments : logi TRUE 896s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 896s .. ..$ chromosome: int 1 896s .. ..$ start : num 1.85e+08 896s .. ..$ end : num 2.47e+08 896s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 896s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 896s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.015 0 0.015 0 0 896s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 896s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 896s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 896s DH segmentation (locally-indexed) rows: 896s startRow endRow 896s 1 2 4388 896s int [1:4391] 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 896s DH segmentation rows: 896s startRow endRow 896s 1 10269 14655 896s Segmenting DH signals...done 896s DH segmentation table: 896s dhStart dhEnd dhNbrOfLoci dhMean 896s 1 185449813 247137334 1311 0.2295 896s startRow endRow 896s 1 10269 14655 896s Rows: 896s [1] 4 896s TCN segmentation rows: 896s startRow endRow 896s 4 10268 14658 896s TCN and DH segmentation rows: 896s startRow endRow 896s 4 10268 14658 896s startRow endRow 896s 1 10269 14655 896s startRow endRow 896s 1 1 7586 896s 2 NA NA 896s 3 7587 10267 896s TCN segmentation (expanded) rows: 896s startRow endRow 896s 1 1 7586 896s 2 NA NA 896s 3 7587 10267 896s 4 10268 14658 896s TCN and DH segmentation rows: 896s startRow endRow 896s 1 1 7586 896s 2 NA NA 896s 3 7587 10267 896s 4 10268 14658 896s startRow endRow 896s 1 10 7574 896s 2 NA NA 896s 3 7587 10263 896s 4 10269 14655 896s startRow endRow 896s 1 1 7586 896s 2 NA NA 896s 3 7587 10267 896s 4 10268 14658 896s Total CN segmentation table (expanded): 896s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 896s 4 1 185449813 247137334 4391 2.6341 1311 1311 896s (TCN,DH) segmentation for one total CN segment: 896s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 896s 4 4 1 1 185449813 247137334 4391 2.6341 1311 896s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 896s 4 1311 185449813 247137334 1311 0.2295 896s Total CN segment #4 ([1.8545e+08,2.47137e+08]) of 4...done 896s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 896s 1 1 1 1 554484 120908858 7586 1.3853 2108 896s 2 1 2 1 120908859 142693887 0 NA 0 896s 3 1 3 1 142693888 185449813 2681 2.0689 777 896s 4 1 4 1 185449813 247137334 4391 2.6341 1311 896s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 896s 1 2108 554484 120908858 2108 0.5116 896s 2 0 NA NA NA NA 896s 3 777 142693888 185449813 777 0.0973 896s 4 1311 185449813 247137334 1311 0.2295 896s Calculating (C1,C2) per segment... 896s Calculating (C1,C2) per segment...done 896s Number of segments: 4 896s Segmenting paired tumor-normal signals using Paired PSCBS...done 896s Post-segmenting TCNs... 896s Number of segments: 4 896s Number of chromosomes: 1 896s [1] 1 896s Chromosome 1 ('chr01') of 1... 896s Rows: 896s [1] 1 2 3 4 896s Number of segments: 4 896s TCN segment #1 ('1') of 4... 896s Nothing todo. Only one DH segmentation. Skipping. 896s TCN segment #1 ('1') of 4...done 896s TCN segment #2 ('2') of 4... 896s Nothing todo. Only one DH segmentation. Skipping. 896s TCN segment #2 ('2') of 4...done 896s TCN segment #3 ('3') of 4... 896s Nothing todo. Only one DH segmentation. Skipping. 896s TCN segment #3 ('3') of 4...done 896s TCN segment #4 ('4') of 4... 896s Nothing todo. Only one DH segmentation. Skipping. 896s TCN segment #4 ('4') of 4...done 896s Chromosome 1 ('chr01') of 1...done 896s Update (C1,C2) per segment... 896s Update (C1,C2) per segment...done 896s Post-segmenting TCNs...done 896s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 896s 1 1 1 1 554484 120908858 7586 1.3853 2108 896s 2 1 2 1 120908859 142693887 0 NA 0 896s 3 1 3 1 142693888 185449813 2681 2.0689 777 896s 4 1 4 1 185449813 247137334 4391 2.6341 1311 896s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 896s 1 2108 554484 120908858 2108 0.5116 0.3382903 1.047010 896s 2 0 NA NA NA NA NA NA 896s 3 777 142693888 185449813 777 0.0973 0.9337980 1.135102 896s 4 1311 185449813 247137334 1311 0.2295 1.0147870 1.619313 896s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 896s 1 1 1 1 554484 120908858 7586 1.3853 2108 896s 2 1 2 1 120908859 142693887 0 NA 0 896s 3 1 3 1 142693888 185449813 2681 2.0689 777 896s 4 1 4 1 185449813 247137334 4391 2.6341 1311 896s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 896s 1 2108 554484 120908858 2108 0.5116 0.3382903 1.047010 896s 2 0 NA NA NA NA NA NA 896s 3 777 142693888 185449813 777 0.0973 0.9337980 1.135102 896s 4 1311 185449813 247137334 1311 0.2295 1.0147870 1.619313 896s - segmentByPairedPSCBS() w/ known segments using 'multisession' futures ... 896s Segmenting paired tumor-normal signals using Paired PSCBS... 896s Calling genotypes from normal allele B fractions... 896s num [1:14670] 0.8274 0.5072 0.1671 0.1609 0.0421 ... 896s Called genotypes: 896s num [1:14670] 1 0.5 0 0 0 0 1 0 1 0.5 ... 896s - attr(*, "modelFit")=List of 1 896s ..$ :List of 7 896s .. ..$ flavor : chr "density" 896s .. ..$ cn : int 2 896s .. ..$ nbrOfGenotypeGroups: int 3 896s .. ..$ tau : num [1:2] 0.315 0.677 896s .. ..$ n : int 14640 896s .. ..$ fit :Classes ‘PeaksAndValleys’ and 'data.frame': 5 obs. of 3 variables: 896s .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 896s .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 896s .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 896s .. ..$ fitValleys :Classes ‘PeaksAndValleys’ and 'data.frame': 2 obs. of 3 variables: 896s .. .. ..$ type : chr [1:2] "valley" "valley" 896s .. .. ..$ x : num [1:2] 0.315 0.677 896s .. .. ..$ density: num [1:2] 0.522 0.551 896s ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 896s muN 896s 0 0.5 1 896s 5221 4198 5251 896s Calling genotypes from normal allele B fractions...done 896s Normalizing betaT using betaN (TumorBoost)... 896s Normalized BAFs: 896s num [1:14670] 0.9301 0.1667 0.0685 0.0995 0.0155 ... 896s - attr(*, "modelFit")=List of 5 896s ..$ method : chr "normalizeTumorBoost" 896s ..$ flavor : chr "v4" 896s ..$ delta : num [1:14670] -0.17264 0.00239 0.1671 0.16085 0.04213 ... 896s .. ..- attr(*, "modelFit")=List of 1 896s .. .. ..$ :List of 7 896s .. .. .. ..$ flavor : chr "density" 896s .. .. .. ..$ cn : int 2 896s .. .. .. ..$ nbrOfGenotypeGroups: int 3 896s .. .. .. ..$ tau : num [1:2] 0.315 0.677 896s .. .. .. ..$ n : int 14640 896s .. .. .. ..$ fit :Classes ‘PeaksAndValleys’ and 'data.frame': 5 obs. of 3 variables: 896s .. .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 896s .. .. .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 896s .. .. .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 896s .. .. .. ..$ fitValleys :Classes ‘PeaksAndValleys’ and 'data.frame': 2 obs. of 3 variables: 896s .. .. .. .. ..$ type : chr [1:2] "valley" "valley" 896s .. .. .. .. ..$ x : num [1:2] 0.315 0.677 896s .. .. .. .. ..$ density: num [1:2] 0.522 0.551 896s .. .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 896s ..$ preserveScale: logi FALSE 896s ..$ scaleFactor : num NA 896s Normalizing betaT using betaN (TumorBoost)...done 896s Setup up data... 896s 'data.frame': 14670 obs. of 7 variables: 896s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 896s $ x : num 1145994 2941694 3710825 4240737 4276892 ... 896s $ CT : num 1.63 1.4 1.41 1.17 1.16 ... 896s $ betaT : num 0.7574 0.169 0.2357 0.2604 0.0576 ... 896s $ betaTN : num 0.9301 0.1667 0.0685 0.0995 0.0155 ... 896s ..- attr(*, "modelFit")=List of 5 896s .. ..$ method : chr "normalizeTumorBoost" 896s .. ..$ flavor : chr "v4" 896s .. ..$ delta : num [1:14670] -0.17264 0.00239 0.1671 0.16085 0.04213 ... 896s .. .. ..- attr(*, "modelFit")=List of 1 896s .. .. .. ..$ :List of 7 896s .. .. .. .. ..$ flavor : chr "density" 896s .. .. .. .. ..$ cn : int 2 896s .. .. .. .. ..$ nbrOfGenotypeGroups: int 3 896s .. .. .. .. ..$ tau : num [1:2] 0.315 0.677 896s .. .. .. .. ..$ n : int 14640 896s .. .. .. .. ..$ fit :Classes ‘PeaksAndValleys’ and 'data.frame': 5 obs. of 3 variables: 896s .. .. .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 896s .. .. .. .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 896s .. .. .. .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 896s .. .. .. .. ..$ fitValleys :Classes ‘PeaksAndValleys’ and 'data.frame': 2 obs. of 3 variables: 896s .. .. .. .. .. ..$ type : chr [1:2] "valley" "valley" 896s .. .. .. .. .. ..$ x : num [1:2] 0.315 0.677 896s .. .. .. .. .. ..$ density: num [1:2] 0.522 0.551 896s .. .. .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 896s .. ..$ preserveScale: logi FALSE 896s .. ..$ scaleFactor : num NA 896s $ betaN : num 0.8274 0.5072 0.1671 0.1609 0.0421 ... 896s $ muN : num 1 0.5 0 0 0 0 1 0 1 0.5 ... 896s ..- attr(*, "modelFit")=List of 1 896s .. ..$ :List of 7 896s .. .. ..$ flavor : chr "density" 896s .. .. ..$ cn : int 2 896s .. .. ..$ nbrOfGenotypeGroups: int 3 896s .. .. ..$ tau : num [1:2] 0.315 0.677 896s .. .. ..$ n : int 14640 896s .. .. ..$ fit :Classes ‘PeaksAndValleys’ and 'data.frame': 5 obs. of 3 variables: 896s .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 896s .. .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 896s .. .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 896s .. .. ..$ fitValleys :Classes ‘PeaksAndValleys’ and 'data.frame': 2 obs. of 3 variables: 896s .. .. .. ..$ type : chr [1:2] "valley" "valley" 896s .. .. .. ..$ x : num [1:2] 0.315 0.677 896s .. .. .. ..$ density: num [1:2] 0.522 0.551 896s .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 896s Setup up data...done 896s Dropping loci for which TCNs are missing... 896s Number of loci dropped: 12 896s Dropping loci for which TCNs are missing...done 896s Ordering data along genome... 896s 'data.frame': 14658 obs. of 7 variables: 896s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 896s $ x : num 554484 730720 782343 878522 916294 ... 896s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 896s $ betaT : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 896s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 896s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 896s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 896s Ordering data along genome...done 896s Keeping only current chromosome for 'knownSegments'... 896s Chromosome: 1 896s Known segments for this chromosome: 896s chromosome start end length 896s 1 1 -Inf 120908858 Inf 896s 2 1 120908859 142693887 21785028 896s 3 1 142693888 Inf Inf 896s Keeping only current chromosome for 'knownSegments'...done 896s alphaTCN: 0.009 896s alphaDH: 0.001 896s Number of loci: 14658 896s Calculating DHs... 896s Number of SNPs: 14658 896s Number of heterozygous SNPs: 4196 (28.63%) 896s Normalized DHs: 896s num [1:14658] NA NA NA NA NA ... 896s Calculating DHs...done 896s Random seed temporarily set (seed=c(48879), kind="L'Ecuyer-CMRG") 896s Produced 2 seeds from this stream for future usage 896s Identification of change points by total copy numbers... 896s Segmenting by CBS... 896s Chromosome: 1 897s Random seed temporarily set (seed=c(10407, 1066287653, -51199871, 161854402, -1995183193, 1503453565, -747102133), kind="L'Ecuyer-CMRG") 897s Produced 3 seeds from this stream for future usage 898s Segmenting by CBS...done 898s List of 4 898s $ data :'data.frame': 14658 obs. of 4 variables: 898s ..$ chromosome: int [1:14658] 1 1 1 1 1 1 1 1 1 1 ... 898s ..$ x : num [1:14658] 554484 730720 782343 878522 916294 ... 898s ..$ y : num [1:14658] 1.88 1.8 1.59 1.64 1.53 ... 898s ..$ index : int [1:14658] 1 2 3 4 5 6 7 8 9 10 ... 898s $ output :'data.frame': 4 obs. of 6 variables: 898s ..$ sampleName: chr [1:4] NA NA NA NA 898s ..$ chromosome: int [1:4] 1 1 1 1 898s ..$ start : num [1:4] 5.54e+05 1.21e+08 1.43e+08 1.85e+08 898s ..$ end : num [1:4] 1.21e+08 1.43e+08 1.85e+08 2.47e+08 898s ..$ nbrOfLoci : int [1:4] 7586 0 2681 4391 898s ..$ mean : num [1:4] 1.39 NA 2.07 2.63 898s $ segRows:'data.frame': 4 obs. of 2 variables: 898s ..$ startRow: int [1:4] 1 NA 7587 10268 898s ..$ endRow : int [1:4] 7586 NA 10267 14658 898s $ params :List of 5 898s ..$ alpha : num 0.009 898s ..$ undo : num 0 898s ..$ joinSegments : logi TRUE 898s ..$ knownSegments:'data.frame': 4 obs. of 3 variables: 898s .. ..$ chromosome: int [1:4] 1 1 2 1 898s .. ..$ start : num [1:4] -Inf -Inf -Inf 1.43e+08 898s .. ..$ end : num [1:4] 1.21e+08 Inf Inf Inf 898s ..$ seed : int [1:7] 10407 1066287653 -51199871 161854402 -1995183193 1503453565 -747102133 898s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 898s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.133 0.002 0.137 0 0 898s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 898s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 898s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 898s Identification of change points by total copy numbers...done 898s Restructure TCN segmentation results... 898s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean 898s 1 1 554484 120908858 7586 1.3853 898s 2 1 120908859 142693887 0 NA 898s 3 1 142693888 185449813 2681 2.0689 898s 4 1 185449813 247137334 4391 2.6341 898s Number of TCN segments: 4 898s Restructure TCN segmentation results...done 898s Total CN segment #1 ([ 554484,1.20909e+08]) of 4... 898s Number of TCN loci in segment: 7586 898s Locus data for TCN segment: 898s 'data.frame': 7586 obs. of 9 variables: 898s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 898s $ x : num 554484 730720 782343 878522 916294 ... 898s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 898s $ betaT : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 898s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 898s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 898s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 898s $ index : int 1 2 3 4 5 6 7 8 9 10 ... 898s $ rho : num NA NA NA NA NA ... 898s Number of loci: 7586 898s Number of SNPs: 2108 (27.79%) 898s Number of heterozygous SNPs: 2108 (100.00%) 898s Chromosome: 1 898s Segmenting DH signals... 898s Segmenting by CBS... 898s Chromosome: 1 898s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 898s Segmenting by CBS...done 898s List of 4 898s $ data :'data.frame': 7586 obs. of 4 variables: 898s ..$ chromosome: int [1:7586] 1 1 1 1 1 1 1 1 1 1 ... 898s ..$ x : num [1:7586] 554484 730720 782343 878522 916294 ... 898s ..$ y : num [1:7586] NA NA NA NA NA ... 898s ..$ index : int [1:7586] 1 2 3 4 5 6 7 8 9 10 ... 898s $ output :'data.frame': 1 obs. of 6 variables: 898s ..$ sampleName: chr NA 898s ..$ chromosome: int 1 898s ..$ start : num 554484 898s ..$ end : num 1.21e+08 898s ..$ nbrOfLoci : int 2108 898s ..$ mean : num 0.512 898s $ segRows:'data.frame': 1 obs. of 2 variables: 898s ..$ startRow: int 10 898s ..$ endRow : int 7574 898s $ params :List of 5 898s ..$ alpha : num 0.001 898s ..$ undo : num 0 898s ..$ joinSegments : logi TRUE 898s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 898s .. ..$ chromosome: int 1 898s .. ..$ start : num 554484 898s .. ..$ end : num 1.21e+08 898s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 898s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 898s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.038 0 0.037 0 0 898s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 898s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 898s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 898s DH segmentation (locally-indexed) rows: 898s startRow endRow 898s 1 10 7574 898s int [1:7586] 1 2 3 4 5 6 7 8 9 10 ... 898s DH segmentation rows: 898s startRow endRow 898s 1 10 7574 898s Segmenting DH signals...done 898s DH segmentation table: 898s dhStart dhEnd dhNbrOfLoci dhMean 898s 1 554484 120908858 2108 0.5116 898s startRow endRow 898s 1 10 7574 898s Rows: 898s [1] 1 898s TCN segmentation rows: 898s startRow endRow 898s 1 1 7586 898s TCN and DH segmentation rows: 898s startRow endRow 898s 1 1 7586 898s startRow endRow 898s 1 10 7574 898s NULL 898s TCN segmentation (expanded) rows: 898s startRow endRow 898s 1 1 7586 898s TCN and DH segmentation rows: 898s startRow endRow 898s 1 1 7586 898s 2 NA NA 898s 3 7587 10267 898s 4 10268 14658 898s startRow endRow 898s 1 10 7574 898s startRow endRow 898s 1 1 7586 898s Total CN segmentation table (expanded): 898s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 898s 1 1 554484 120908858 7586 1.3853 2108 2108 898s (TCN,DH) segmentation for one total CN segment: 898s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 898s 1 1 1 1 554484 120908858 7586 1.3853 2108 898s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 898s 1 2108 554484 120908858 2108 0.5116 898s Total CN segment #1 ([ 554484,1.20909e+08]) of 4...done 898s Total CN segment #2 ([1.20909e+08,1.42694e+08]) of 4... 898s Number of TCN loci in segment: 0 898s Locus data for TCN segment: 898s 'data.frame': 0 obs. of 9 variables: 898s $ chromosome: int 898s $ x : num 898s $ CT : num 898s $ betaT : num 898s $ betaTN : num 898s $ betaN : num 898s $ muN : num 898s $ index : int 898s $ rho : num 898s Number of loci: 0 898s Number of SNPs: 0 (NaN%) 898s Number of heterozygous SNPs: 0 (NaN%) 898s Chromosome: 1 898s Segmenting DH signals... 898s Segmenting by CBS... 898s Chromosome: NA 898s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 898s Segmenting by CBS...done 898s List of 4 898s $ data :'data.frame': 0 obs. of 4 variables: 898s ..$ chromosome: int(0) 898s ..$ x : num(0) 898s ..$ y : num(0) 898s ..$ index : int(0) 898s $ output :'data.frame': 0 obs. of 6 variables: 898s ..$ sampleName: chr(0) 898s ..$ chromosome: num(0) 898s ..$ start : num(0) 898s ..$ end : num(0) 898s ..$ nbrOfLoci : int(0) 898s ..$ mean : num(0) 898s $ segRows:'data.frame': 0 obs. of 2 variables: 898s ..$ startRow: int(0) 898s ..$ endRow : int(0) 898s $ params :List of 5 898s ..$ alpha : num 0.001 898s ..$ undo : num 0 898s ..$ joinSegments : logi TRUE 898s ..$ knownSegments:'data.frame': 0 obs. of 3 variables: 898s .. ..$ chromosome: int(0) 898s .. ..$ start : num(0) 898s .. ..$ end : num(0) 898s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 898s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 898s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.002 0 0.002 0 0 898s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 898s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 898s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 898s DH segmentation (locally-indexed) rows: 898s [1] startRow endRow 898s <0 rows> (or 0-length row.names) 898s int(0) 898s DH segmentation rows: 898s [1] startRow endRow 898s <0 rows> (or 0-length row.names) 898s Segmenting DH signals...done 898s DH segmentation table: 898s dhStart dhEnd dhNbrOfLoci dhMean 898s NA NA NA NA NA 898s startRow endRow 898s NA NA NA 898s Rows: 898s [1] 2 898s TCN segmentation rows: 898s startRow endRow 898s 2 NA NA 898s TCN and DH segmentation rows: 898s startRow endRow 898s 2 NA NA 898s startRow endRow 898s NA NA NA 898s startRow endRow 898s 1 1 7586 898s TCN segmentation (expanded) rows: 898s startRow endRow 898s 1 1 7586 898s 2 NA NA 898s TCN and DH segmentation rows: 898s startRow endRow 898s 1 1 7586 898s 2 NA NA 898s 3 7587 10267 898s 4 10268 14658 898s startRow endRow 898s 1 10 7574 898s 2 NA NA 898s startRow endRow 898s 1 1 7586 898s 2 NA NA 898s Total CN segmentation table (expanded): 898s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 898s 2 1 120908859 142693887 0 NA 0 0 898s (TCN,DH) segmentation for one total CN segment: 898s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 898s 2 2 1 1 120908859 142693887 0 NA 0 898s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 898s 2 0 NA NA NA NA 898s Total CN segment #2 ([1.20909e+08,1.42694e+08]) of 4...done 898s Total CN segment #3 ([1.42694e+08,1.8545e+08]) of 4... 898s Number of TCN loci in segment: 2681 898s Locus data for TCN segment: 898s 'data.frame': 2681 obs. of 9 variables: 898s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 898s $ x : num 1.43e+08 1.43e+08 1.43e+08 1.43e+08 1.44e+08 ... 898s $ CT : num 2.27 1.55 1.47 1.5 1.81 ... 898s $ betaT : num 0.34 0.55 0.048 0.813 0.575 ... 898s $ betaTN : num 0.441 0.629 -0.05 0.958 0.872 ... 898s $ betaN : num 0.3851 0.3933 0.0981 0.8552 0.7028 ... 898s $ muN : num 0.5 0.5 0 1 1 1 1 0.5 1 1 ... 898s $ index : int 7587 7588 7589 7590 7591 7592 7593 7594 7595 7596 ... 898s $ rho : num 0.117 0.258 NA NA NA ... 898s Number of loci: 2681 898s Number of SNPs: 777 (28.98%) 898s Number of heterozygous SNPs: 777 (100.00%) 898s Chromosome: 1 898s Segmenting DH signals... 898s Segmenting by CBS... 898s Chromosome: 1 898s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 898s Segmenting by CBS...done 898s List of 4 898s $ data :'data.frame': 2681 obs. of 4 variables: 898s ..$ chromosome: int [1:2681] 1 1 1 1 1 1 1 1 1 1 ... 898s ..$ x : num [1:2681] 1.43e+08 1.43e+08 1.43e+08 1.43e+08 1.44e+08 ... 898s ..$ y : num [1:2681] 0.117 0.258 NA NA NA ... 898s ..$ index : int [1:2681] 1 2 3 4 5 6 7 8 9 10 ... 898s $ output :'data.frame': 1 obs. of 6 variables: 898s ..$ sampleName: chr NA 898s ..$ chromosome: int 1 898s ..$ start : num 1.43e+08 898s ..$ end : num 1.85e+08 898s ..$ nbrOfLoci : int 777 898s ..$ mean : num 0.0973 898s $ segRows:'data.frame': 1 obs. of 2 variables: 898s ..$ startRow: int 1 898s ..$ endRow : int 2677 898s $ params :List of 5 898s ..$ alpha : num 0.001 898s ..$ undo : num 0 898s ..$ joinSegments : logi TRUE 898s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 898s .. ..$ chromosome: int 1 898s .. ..$ start : num 1.43e+08 898s .. ..$ end : num 1.85e+08 898s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 898s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 898s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.008 0 0.008 0 0 898s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 898s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 898s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 898s DH segmentation (locally-indexed) rows: 898s startRow endRow 898s 1 1 2677 898s int [1:2681] 7587 7588 7589 7590 7591 7592 7593 7594 7595 7596 ... 898s DH segmentation rows: 898s startRow endRow 898s 1 7587 10263 898s Segmenting DH signals...done 898s DH segmentation table: 898s dhStart dhEnd dhNbrOfLoci dhMean 898s 1 142693888 185449813 777 0.0973 898s startRow endRow 898s 1 7587 10263 898s Rows: 898s [1] 3 898s TCN segmentation rows: 898s startRow endRow 898s 3 7587 10267 898s TCN and DH segmentation rows: 898s startRow endRow 898s 3 7587 10267 898s startRow endRow 898s 1 7587 10263 898s startRow endRow 898s 1 1 7586 898s 2 NA NA 898s TCN segmentation (expanded) rows: 898s startRow endRow 898s 1 1 7586 898s 2 NA NA 898s 3 7587 10267 898s TCN and DH segmentation rows: 898s startRow endRow 898s 1 1 7586 898s 2 NA NA 898s 3 7587 10267 898s 4 10268 14658 898s startRow endRow 898s 1 10 7574 898s 2 NA NA 898s 3 7587 10263 898s startRow endRow 898s 1 1 7586 898s 2 NA NA 898s 3 7587 10267 898s Total CN segmentation table (expanded): 898s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 898s 3 1 142693888 185449813 2681 2.0689 777 777 898s (TCN,DH) segmentation for one total CN segment: 898s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 898s 3 3 1 1 142693888 185449813 2681 2.0689 777 898s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 898s 3 777 142693888 185449813 777 0.0973 898s Total CN segment #3 ([1.42694e+08,1.8545e+08]) of 4...done 898s Total CN segment #4 ([1.8545e+08,2.47137e+08]) of 4... 898s Number of TCN loci in segment: 4391 898s Locus data for TCN segment: 898s 'data.frame': 4391 obs. of 9 variables: 898s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 898s $ x : num 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 898s $ CT : num 2.93 2.15 2.82 2.93 2.46 ... 898s $ betaT : num 0.0811 0.5154 0.9473 0.3734 0.7506 ... 898s $ betaTN : num -0.169 0.609 1.028 0.525 0.968 ... 898s $ betaN : num 0.25 0.38 0.919 0.34 0.783 ... 898s $ muN : num 0 0.5 1 0.5 1 1 0 1 0 1 ... 898s $ index : int 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 898s $ rho : num NA 0.2186 NA 0.0503 NA ... 898s Number of loci: 4391 898s Number of SNPs: 1311 (29.86%) 898s Number of heterozygous SNPs: 1311 (100.00%) 898s Chromosome: 1 898s Segmenting DH signals... 898s Segmenting by CBS... 898s Chromosome: 1 898s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 898s Segmenting by CBS...done 898s List of 4 898s $ data :'data.frame': 4391 obs. of 4 variables: 898s ..$ chromosome: int [1:4391] 1 1 1 1 1 1 1 1 1 1 ... 898s ..$ x : num [1:4391] 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 898s ..$ y : num [1:4391] NA 0.2186 NA 0.0503 NA ... 898s ..$ index : int [1:4391] 1 2 3 4 5 6 7 8 9 10 ... 898s $ output :'data.frame': 1 obs. of 6 variables: 898s ..$ sampleName: chr NA 898s ..$ chromosome: int 1 898s ..$ start : num 1.85e+08 898s ..$ end : num 2.47e+08 898s ..$ nbrOfLoci : int 1311 898s ..$ mean : num 0.23 898s $ segRows:'data.frame': 1 obs. of 2 variables: 898s ..$ startRow: int 2 898s ..$ endRow : int 4388 898s $ params :List of 5 898s ..$ alpha : num 0.001 898s ..$ undo : num 0 898s ..$ joinSegments : logi TRUE 898s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 898s .. ..$ chromosome: int 1 898s .. ..$ start : num 1.85e+08 898s .. ..$ end : num 2.47e+08 898s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 898s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 898s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.015 0 0.015 0 0 898s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 898s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 898s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 898s DH segmentation (locally-indexed) rows: 898s startRow endRow 898s 1 2 4388 898s int [1:4391] 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 898s DH segmentation rows: 898s startRow endRow 898s 1 10269 14655 898s Segmenting DH signals...done 898s DH segmentation table: 898s dhStart dhEnd dhNbrOfLoci dhMean 898s 1 185449813 247137334 1311 0.2295 898s startRow endRow 898s 1 10269 14655 898s Rows: 898s [1] 4 898s TCN segmentation rows: 898s startRow endRow 898s 4 10268 14658 898s TCN and DH segmentation rows: 898s startRow endRow 898s 4 10268 14658 898s startRow endRow 898s 1 10269 14655 898s startRow endRow 898s 1 1 7586 898s 2 NA NA 898s 3 7587 10267 898s TCN segmentation (expanded) rows: 898s startRow endRow 898s 1 1 7586 898s 2 NA NA 898s 3 7587 10267 898s 4 10268 14658 898s TCN and DH segmentation rows: 898s startRow endRow 898s 1 1 7586 898s 2 NA NA 898s 3 7587 10267 898s 4 10268 14658 898s startRow endRow 898s 1 10 7574 898s 2 NA NA 898s 3 7587 10263 898s 4 10269 14655 898s startRow endRow 898s 1 1 7586 898s 2 NA NA 898s 3 7587 10267 898s 4 10268 14658 898s Total CN segmentation table (expanded): 898s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 898s 4 1 185449813 247137334 4391 2.6341 1311 1311 898s (TCN,DH) segmentation for one total CN segment: 898s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 898s 4 4 1 1 185449813 247137334 4391 2.6341 1311 898s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 898s 4 1311 185449813 247137334 1311 0.2295 898s Total CN segment #4 ([1.8545e+08,2.47137e+08]) of 4...done 898s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 898s 1 1 1 1 554484 120908858 7586 1.3853 2108 898s 2 1 2 1 120908859 142693887 0 NA 0 898s 3 1 3 1 142693888 185449813 2681 2.0689 777 898s 4 1 4 1 185449813 247137334 4391 2.6341 1311 898s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 898s 1 2108 554484 120908858 2108 0.5116 898s 2 0 NA NA NA NA 898s 3 777 142693888 185449813 777 0.0973 898s 4 1311 185449813 247137334 1311 0.2295 898s Calculating (C1,C2) per segment... 898s Calculating (C1,C2) per segment...done 898s Number of segments: 4 898s Segmenting paired tumor-normal signals using Paired PSCBS...done 898s Post-segmenting TCNs... 898s Number of segments: 4 898s Number of chromosomes: 1 898s [1] 1 898s Chromosome 1 ('chr01') of 1... 898s Rows: 898s [1] 1 2 3 4 898s Number of segments: 4 898s TCN segment #1 ('1') of 4... 898s Nothing todo. Only one DH segmentation. Skipping. 898s TCN segment #1 ('1') of 4...done 898s TCN segment #2 ('2') of 4... 898s Nothing todo. Only one DH segmentation. Skipping. 898s TCN segment #2 ('2') of 4...done 898s TCN segment #3 ('3') of 4... 898s Nothing todo. Only one DH segmentation. Skipping. 898s TCN segment #3 ('3') of 4...done 898s TCN segment #4 ('4') of 4... 898s Nothing todo. Only one DH segmentation. Skipping. 898s TCN segment #4 ('4') of 4...done 898s Chromosome 1 ('chr01') of 1...done 898s Update (C1,C2) per segment... 898s Update (C1,C2) per segment...done 898s Post-segmenting TCNs...done 898s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 898s 1 1 1 1 554484 120908858 7586 1.3853 2108 898s 2 1 2 1 120908859 142693887 0 NA 0 898s 3 1 3 1 142693888 185449813 2681 2.0689 777 898s 4 1 4 1 185449813 247137334 4391 2.6341 1311 898s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 898s 1 2108 554484 120908858 2108 0.5116 0.3382903 1.047010 898s 2 0 NA NA NA NA NA NA 898s 3 777 142693888 185449813 777 0.0973 0.9337980 1.135102 898s 4 1311 185449813 247137334 1311 0.2295 1.0147870 1.619313 898s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 898s 1 1 1 1 554484 120908858 7586 1.3853 2108 898s 2 1 2 1 120908859 142693887 0 NA 0 898s 3 1 3 1 142693888 185449813 2681 2.0689 777 898s 4 1 4 1 185449813 247137334 4391 2.6341 1311 898s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 898s 1 2108 554484 120908858 2108 0.5116 0.3382903 1.047010 898s 2 0 NA NA NA NA NA NA 898s 3 777 142693888 185449813 777 0.0973 0.9337980 1.135102 898s 4 1311 185449813 247137334 1311 0.2295 1.0147870 1.619313 898s *** segmentByPairedPSCBS() via futures ... DONE 898s > 898s > message("*** segmentByPairedPSCBS() via futures ... DONE") 898s > 898s > 898s > ## Cleanup 898s > plan(oplan) 898s > rm(list=c("fits", "data", "fit")) 898s > 898s Start: segmentByPairedPSCBS,noNormalBAFs.R 898s 898s R version 4.5.2 (2025-10-31) -- "[Not] Part in a Rumble" 898s Copyright (C) 2025 The R Foundation for Statistical Computing 898s Platform: aarch64-unknown-linux-gnu 898s 898s R is free software and comes with ABSOLUTELY NO WARRANTY. 898s You are welcome to redistribute it under certain conditions. 898s Type 'license()' or 'licence()' for distribution details. 898s 898s R is a collaborative project with many contributors. 898s Type 'contributors()' for more information and 898s 'citation()' on how to cite R or R packages in publications. 898s 898s Type 'demo()' for some demos, 'help()' for on-line help, or 898s 'help.start()' for an HTML browser interface to help. 898s Type 'q()' to quit R. 898s 899s > library("PSCBS") 899s PSCBS v0.68.0 (2025-04-18 19:40:02 UTC) successfully loaded. See ?PSCBS for help. 899s > 899s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 899s > # Load SNP microarray data 899s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 899s > data <- PSCBS::exampleData("paired.chr01") 899s > str(data) 899s 'data.frame': 73346 obs. of 6 variables: 899s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 899s $ x : int 1145994 2224111 2319424 2543484 2926730 2941694 3084986 3155127 3292731 3695086 ... 899s $ CT : num 1.625 1.071 1.406 1.18 0.856 ... 899s $ betaT : num 0.757 0.771 0.834 0.778 0.229 ... 899s $ CN : num 2.36 2.13 2.59 1.93 1.71 ... 899s $ betaN : num 0.827 0.875 0.887 0.884 0.103 ... 899s > 899s > # Drop single-locus outliers 899s > dataS <- dropSegmentationOutliers(data) 899s > 899s > # Run light-weight tests by default 899s > if (Sys.getenv("_R_CHECK_FULL_") == "") { 899s + # Use only every 5th data point 899s + dataS <- dataS[seq(from=1, to=nrow(data), by=5),] 899s + # Number of segments (for assertion) 899s + nSegs <- 3L 899s + # Number of bootstrap samples (see below) 899s + B <- 100L 899s + } else { 899s + # Full tests 899s + nSegs <- 8L 899s + B <- 1000L 899s + } 899s > 899s > str(dataS) 899s 'data.frame': 14670 obs. of 6 variables: 899s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 899s $ x : int 1145994 2941694 3710825 4240737 4276892 4464544 4714611 5095111 5034491 5158416 ... 899s $ CT : num 1.63 1.4 1.41 1.17 1.16 ... 899s $ betaT : num 0.7574 0.169 0.2357 0.2604 0.0576 ... 899s $ CN : num 2.36 2.13 2.26 2.01 2.32 ... 899s $ betaN : num 0.8274 0.5072 0.1671 0.1609 0.0421 ... 899s > 899s > R.oo::attachLocally(dataS) 899s > 899s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 899s > # Simulate that genotypes are known by other means 899s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 899s > library("aroma.light") 899s aroma.light v3.36.0 (2024-10-29) successfully loaded. See ?aroma.light for help. 899s > muN <- aroma.light::callNaiveGenotypes(betaN, censorAt=c(0,1)) 899s > 899s > 899s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 899s > # Paired PSCBS segmentation 899s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 899s > fit <- segmentByPairedPSCBS(CT, betaT=betaT, muN=muN, tbn=FALSE, 899s + chromosome=chromosome, x=x, 899s + seed=0xBEEF, verbose=-10) 899s Segmenting paired tumor-normal signals using Paired PSCBS... 899s Setup up data... 899s 'data.frame': 14670 obs. of 6 variables: 899s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 899s $ x : num 1145994 2941694 3710825 4240737 4276892 ... 899s $ CT : num 1.63 1.4 1.41 1.17 1.16 ... 899s $ betaT : num 0.7574 0.169 0.2357 0.2604 0.0576 ... 899s $ betaTN : num 0.7574 0.169 0.2357 0.2604 0.0576 ... 899s $ muN : num 1 0.5 0 0 0 0 1 0 1 0.5 ... 899s ..- attr(*, "modelFit")=List of 1 899s .. ..$ :List of 7 899s .. .. ..$ flavor : chr "density" 899s .. .. ..$ cn : int 2 899s .. .. ..$ nbrOfGenotypeGroups: int 3 899s .. .. ..$ tau : num [1:2] 0.315 0.677 899s .. .. ..$ n : int 14640 899s .. .. ..$ fit :Classes ‘PeaksAndValleys’ and 'data.frame': 5 obs. of 3 variables: 899s .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 899s .. .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 899s .. .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 899s .. .. ..$ fitValleys :Classes ‘PeaksAndValleys’ and 'data.frame': 2 obs. of 3 variables: 899s .. .. .. ..$ type : chr [1:2] "valley" "valley" 899s .. .. .. ..$ x : num [1:2] 0.315 0.677 899s .. .. .. ..$ density: num [1:2] 0.522 0.551 899s .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 899s Setup up data...done 899s Dropping loci for which TCNs are missing... 899s Number of loci dropped: 12 899s Dropping loci for which TCNs are missing...done 899s Ordering data along genome... 899s 'data.frame': 14658 obs. of 6 variables: 899s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 899s $ x : num 554484 730720 782343 878522 916294 ... 899s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 899s $ betaT : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 899s $ betaTN : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 899s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 899s Ordering data along genome...done 899s Keeping only current chromosome for 'knownSegments'... 899s Chromosome: 1 899s Known segments for this chromosome: 899s [1] chromosome start end 899s <0 rows> (or 0-length row.names) 899s Keeping only current chromosome for 'knownSegments'...done 899s alphaTCN: 0.009 899s alphaDH: 0.001 899s Number of loci: 14658 899s Calculating DHs... 899s Number of SNPs: 14658 899s Number of heterozygous SNPs: 4196 (28.63%) 899s Normalized DHs: 899s num [1:14658] NA NA NA NA NA ... 899s Calculating DHs...done 899s Random seed temporarily set (seed=c(48879), kind="L'Ecuyer-CMRG") 899s Produced 2 seeds from this stream for future usage 899s Identification of change points by total copy numbers... 899s Segmenting by CBS... 899s Chromosome: 1 899s Random seed temporarily set (seed=c(10407, 1066287653, -51199871, 161854402, -1995183193, 1503453565, -747102133), kind="L'Ecuyer-CMRG") 899s Segmenting by CBS...done 899s List of 4 899s $ data :'data.frame': 14658 obs. of 4 variables: 899s ..$ chromosome: int [1:14658] 1 1 1 1 1 1 1 1 1 1 ... 899s ..$ x : num [1:14658] 554484 730720 782343 878522 916294 ... 899s ..$ y : num [1:14658] 1.88 1.8 1.59 1.64 1.53 ... 899s ..$ index : int [1:14658] 1 2 3 4 5 6 7 8 9 10 ... 899s $ output :'data.frame': 3 obs. of 6 variables: 899s ..$ sampleName: chr [1:3] NA NA NA 899s ..$ chromosome: int [1:3] 1 1 1 899s ..$ start : num [1:3] 5.54e+05 1.44e+08 1.85e+08 899s ..$ end : num [1:3] 1.44e+08 1.85e+08 2.47e+08 899s ..$ nbrOfLoci : int [1:3] 7599 2668 4391 899s ..$ mean : num [1:3] 1.39 2.07 2.63 899s $ segRows:'data.frame': 3 obs. of 2 variables: 899s ..$ startRow: int [1:3] 1 7600 10268 899s ..$ endRow : int [1:3] 7599 10267 14658 899s $ params :List of 5 899s ..$ alpha : num 0.009 899s ..$ undo : num 0 899s ..$ joinSegments : logi TRUE 899s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 899s .. ..$ chromosome: int 1 899s .. ..$ start : num -Inf 899s .. ..$ end : num Inf 899s ..$ seed : int [1:7] 10407 1066287653 -51199871 161854402 -1995183193 1503453565 -747102133 899s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 899s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.37 0 0.371 0 0 899s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 899s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 899s - attr(*, "randomSeed")= int [1:7] 10407 1066287653 -51199871 161854402 -1995183193 1503453565 -747102133 899s Identification of change points by total copy numbers...done 899s Restructure TCN segmentation results... 899s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean 899s 1 1 554484 143926517 7599 1.3859 899s 2 1 143926517 185449813 2668 2.0704 899s 3 1 185449813 247137334 4391 2.6341 899s Number of TCN segments: 3 899s Restructure TCN segmentation results...done 899s Total CN segment #1 ([ 554484,1.43927e+08]) of 3... 899s Number of TCN loci in segment: 7599 899s Locus data for TCN segment: 899s 'data.frame': 7599 obs. of 8 variables: 899s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 899s $ x : num 554484 730720 782343 878522 916294 ... 899s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 899s $ betaT : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 899s $ betaTN : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 899s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 899s $ index : int 1 2 3 4 5 6 7 8 9 10 ... 899s $ rho : num NA NA NA NA NA ... 899s Number of loci: 7599 899s Number of SNPs: 2111 (27.78%) 899s Number of heterozygous SNPs: 2111 (100.00%) 899s Chromosome: 1 899s Segmenting DH signals... 900s Segmenting by CBS... 900s Chromosome: 1 900s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 900s Segmenting by CBS...done 900s List of 4 900s $ data :'data.frame': 7599 obs. of 4 variables: 900s ..$ chromosome: int [1:7599] 1 1 1 1 1 1 1 1 1 1 ... 900s ..$ x : num [1:7599] 554484 730720 782343 878522 916294 ... 900s ..$ y : num [1:7599] NA NA NA NA NA ... 900s ..$ index : int [1:7599] 1 2 3 4 5 6 7 8 9 10 ... 900s $ output :'data.frame': 1 obs. of 6 variables: 900s ..$ sampleName: chr NA 900s ..$ chromosome: int 1 900s ..$ start : num 554484 900s ..$ end : num 1.44e+08 900s ..$ nbrOfLoci : int 2111 900s ..$ mean : num 0.524 900s $ segRows:'data.frame': 1 obs. of 2 variables: 900s ..$ startRow: int 10 900s ..$ endRow : int 7594 900s $ params :List of 5 900s ..$ alpha : num 0.001 900s ..$ undo : num 0 900s ..$ joinSegments : logi TRUE 900s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 900s .. ..$ chromosome: int 1 900s .. ..$ start : num 554484 900s .. ..$ end : num 1.44e+08 900s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 900s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 900s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.025 0.001 0.025 0 0 900s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 900s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 900s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 900s DH segmentation (locally-indexed) rows: 900s startRow endRow 900s 1 10 7594 900s int [1:7599] 1 2 3 4 5 6 7 8 9 10 ... 900s DH segmentation rows: 900s startRow endRow 900s 1 10 7594 900s Segmenting DH signals...done 900s DH segmentation table: 900s dhStart dhEnd dhNbrOfLoci dhMean 900s 1 554484 143926517 2111 0.5237 900s startRow endRow 900s 1 10 7594 900s Rows: 900s [1] 1 900s TCN segmentation rows: 900s startRow endRow 900s 1 1 7599 900s TCN and DH segmentation rows: 900s startRow endRow 900s 1 1 7599 900s startRow endRow 900s 1 10 7594 900s NULL 900s TCN segmentation (expanded) rows: 900s startRow endRow 900s 1 1 7599 900s TCN and DH segmentation rows: 900s startRow endRow 900s 1 1 7599 900s 2 7600 10267 900s 3 10268 14658 900s startRow endRow 900s 1 10 7594 900s startRow endRow 900s 1 1 7599 900s Total CN segmentation table (expanded): 900s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 900s 1 1 554484 143926517 7599 1.3859 2111 2111 900s (TCN,DH) segmentation for one total CN segment: 900s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 900s 1 1 1 1 554484 143926517 7599 1.3859 2111 900s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 900s 1 2111 554484 143926517 2111 0.5237 900s Total CN segment #1 ([ 554484,1.43927e+08]) of 3...done 900s Total CN segment #2 ([1.43927e+08,1.8545e+08]) of 3... 900s Number of TCN loci in segment: 2668 900s Locus data for TCN segment: 900s 'data.frame': 2668 obs. of 8 variables: 900s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 900s $ x : num 1.44e+08 1.44e+08 1.44e+08 1.44e+08 1.44e+08 ... 900s $ CT : num 2.1 2.1 2.09 1.8 2.34 ... 900s $ betaT : num 0.1899 0.909 0.9166 0.1668 0.0308 ... 900s $ betaTN : num 0.1899 0.909 0.9166 0.1668 0.0308 ... 900s $ muN : num 0 1 1 0 0 1 0 0 0 0 ... 900s $ index : int 7600 7601 7602 7603 7604 7605 7606 7607 7608 7609 ... 900s $ rho : num NA NA NA NA NA NA NA NA NA NA ... 900s Number of loci: 2668 900s Number of SNPs: 774 (29.01%) 900s Number of heterozygous SNPs: 774 (100.00%) 900s Chromosome: 1 900s Segmenting DH signals... 900s Segmenting by CBS... 900s Chromosome: 1 900s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 900s Segmenting by CBS...done 900s List of 4 900s $ data :'data.frame': 2668 obs. of 4 variables: 900s ..$ chromosome: int [1:2668] 1 1 1 1 1 1 1 1 1 1 ... 900s ..$ x : num [1:2668] 1.44e+08 1.44e+08 1.44e+08 1.44e+08 1.44e+08 ... 900s ..$ y : num [1:2668] NA NA NA NA NA NA NA NA NA NA ... 900s ..$ index : int [1:2668] 1 2 3 4 5 6 7 8 9 10 ... 900s $ output :'data.frame': 1 obs. of 6 variables: 900s ..$ sampleName: chr NA 900s ..$ chromosome: int 1 900s ..$ start : num 1.44e+08 900s ..$ end : num 1.85e+08 900s ..$ nbrOfLoci : int 774 900s ..$ mean : num 0.154 900s $ segRows:'data.frame': 1 obs. of 2 variables: 900s ..$ startRow: int 15 900s ..$ endRow : int 2664 900s $ params :List of 5 900s ..$ alpha : num 0.001 900s ..$ undo : num 0 900s ..$ joinSegments : logi TRUE 900s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 900s .. ..$ chromosome: int 1 900s .. ..$ start : num 1.44e+08 900s .. ..$ end : num 1.85e+08 900s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 900s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 900s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.009 0 0.009 0 0 900s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 900s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 900s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 900s DH segmentation (locally-indexed) rows: 900s startRow endRow 900s 1 15 2664 900s int [1:2668] 7600 7601 7602 7603 7604 7605 7606 7607 7608 7609 ... 900s DH segmentation rows: 900s startRow endRow 900s 1 7614 10263 900s Segmenting DH signals...done 900s DH segmentation table: 900s dhStart dhEnd dhNbrOfLoci dhMean 900s 1 143926517 185449813 774 0.1542 900s startRow endRow 900s 1 7614 10263 900s Rows: 900s [1] 2 900s TCN segmentation rows: 900s startRow endRow 900s 2 7600 10267 900s TCN and DH segmentation rows: 900s startRow endRow 900s 2 7600 10267 900s startRow endRow 900s 1 7614 10263 900s startRow endRow 900s 1 1 7599 900s TCN segmentation (expanded) rows: 900s startRow endRow 900s 1 1 7599 900s 2 7600 10267 900s TCN and DH segmentation rows: 900s startRow endRow 900s 1 1 7599 900s 2 7600 10267 900s 3 10268 14658 900s startRow endRow 900s 1 10 7594 900s 2 7614 10263 900s startRow endRow 900s 1 1 7599 900s 2 7600 10267 900s Total CN segmentation table (expanded): 900s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 900s 2 1 143926517 185449813 2668 2.0704 774 774 900s (TCN,DH) segmentation for one total CN segment: 900s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 900s 2 2 1 1 143926517 185449813 2668 2.0704 774 900s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 900s 2 774 143926517 185449813 774 0.1542 900s Total CN segment #2 ([1.43927e+08,1.8545e+08]) of 3...done 900s Total CN segment #3 ([1.8545e+08,2.47137e+08]) of 3... 900s Number of TCN loci in segment: 4391 900s Locus data for TCN segment: 900s 'data.frame': 4391 obs. of 8 variables: 900s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 900s $ x : num 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 900s $ CT : num 2.93 2.15 2.82 2.93 2.46 ... 900s $ betaT : num 0.0811 0.5154 0.9473 0.3734 0.7506 ... 900s $ betaTN : num 0.0811 0.5154 0.9473 0.3734 0.7506 ... 900s $ muN : num 0 0.5 1 0.5 1 1 0 1 0 1 ... 900s $ index : int 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 900s $ rho : num NA 0.0308 NA 0.2533 NA ... 900s Number of loci: 4391 900s Number of SNPs: 1311 (29.86%) 900s Number of heterozygous SNPs: 1311 (100.00%) 900s Chromosome: 1 900s Segmenting DH signals... 900s Segmenting by CBS... 900s Chromosome: 1 900s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 900s Segmenting by CBS...done 900s List of 4 900s $ data :'data.frame': 4391 obs. of 4 variables: 900s ..$ chromosome: int [1:4391] 1 1 1 1 1 1 1 1 1 1 ... 900s ..$ x : num [1:4391] 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 900s ..$ y : num [1:4391] NA 0.0308 NA 0.2533 NA ... 900s ..$ index : int [1:4391] 1 2 3 4 5 6 7 8 9 10 ... 900s $ output :'data.frame': 1 obs. of 6 variables: 900s ..$ sampleName: chr NA 900s ..$ chromosome: int 1 900s ..$ start : num 1.85e+08 900s ..$ end : num 2.47e+08 900s ..$ nbrOfLoci : int 1311 900s ..$ mean : num 0.251 900s $ segRows:'data.frame': 1 obs. of 2 variables: 900s ..$ startRow: int 2 900s ..$ endRow : int 4388 900s $ params :List of 5 900s ..$ alpha : num 0.001 900s ..$ undo : num 0 900s ..$ joinSegments : logi TRUE 900s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 900s .. ..$ chromosome: int 1 900s .. ..$ start : num 1.85e+08 900s .. ..$ end : num 2.47e+08 900s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 900s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 900s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.02 0 0.019 0 0 900s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 900s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 900s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 900s DH segmentation (locally-indexed) rows: 900s startRow endRow 900s 1 2 4388 900s int [1:4391] 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 900s DH segmentation rows: 900s startRow endRow 900s 1 10269 14655 900s Segmenting DH signals...done 900s DH segmentation table: 900s dhStart dhEnd dhNbrOfLoci dhMean 900s 1 185449813 247137334 1311 0.2512 900s startRow endRow 900s 1 10269 14655 900s Rows: 900s [1] 3 900s TCN segmentation rows: 900s startRow endRow 900s 3 10268 14658 900s TCN and DH segmentation rows: 900s startRow endRow 900s 3 10268 14658 900s startRow endRow 900s 1 10269 14655 900s startRow endRow 900s 1 1 7599 900s 2 7600 10267 900s TCN segmentation (expanded) rows: 900s startRow endRow 900s 1 1 7599 900s 2 7600 10267 900s 3 10268 14658 900s TCN and DH segmentation rows: 900s startRow endRow 900s 1 1 7599 900s 2 7600 10267 900s 3 10268 14658 900s startRow endRow 900s 1 10 7594 900s 2 7614 10263 900s 3 10269 14655 900s startRow endRow 900s 1 1 7599 900s 2 7600 10267 900s 3 10268 14658 900s Total CN segmentation table (expanded): 900s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 900s 3 1 185449813 247137334 4391 2.6341 1311 1311 900s (TCN,DH) segmentation for one total CN segment: 900s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 900s 3 3 1 1 185449813 247137334 4391 2.6341 1311 900s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 900s 3 1311 185449813 247137334 1311 0.2512 900s Total CN segment #3 ([1.8545e+08,2.47137e+08]) of 3...done 900s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 900s 1 1 1 1 554484 143926517 7599 1.3859 2111 900s 2 1 2 1 143926517 185449813 2668 2.0704 774 900s 3 1 3 1 185449813 247137334 4391 2.6341 1311 900s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 900s 1 2111 554484 143926517 2111 0.5237 900s 2 774 143926517 185449813 774 0.1542 900s 3 1311 185449813 247137334 1311 0.2512 900s Calculating (C1,C2) per segment... 900s Calculating (C1,C2) per segment...done 900s Number of segments: 3 900s Segmenting paired tumor-normal signals using Paired PSCBS...done 900s Post-segmenting TCNs... 900s Number of segments: 3 900s Number of chromosomes: 1 900s [1] 1 900s Chromosome 1 ('chr01') of 1... 900s Rows: 900s [1] 1 2 3 900s Number of segments: 3 900s TCN segment #1 ('1') of 3... 900s Nothing todo. Only one DH segmentation. Skipping. 900s TCN segment #1 ('1') of 3...done 900s TCN segment #2 ('2') of 3... 900s Nothing todo. Only one DH segmentation. Skipping. 900s TCN segment #2 ('2') of 3...done 900s TCN segment #3 ('3') of 3... 900s Nothing todo. Only one DH segmentation. Skipping. 900s TCN segment #3 ('3') of 3...done 900s Chromosome 1 ('chr01') of 1...done 900s Update (C1,C2) per segment... 900s Update (C1,C2) per segment...done 900s Post-segmenting TCNs...done 900s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 900s 1 1 1 1 554484 143926517 7599 1.3859 2111 900s 2 1 2 1 143926517 185449813 2668 2.0704 774 900s 3 1 3 1 185449813 247137334 4391 2.6341 1311 900s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 900s 1 2111 554484 143926517 2111 0.5237 0.3300521 1.055848 900s 2 774 143926517 185449813 774 0.1542 0.8755722 1.194828 900s 3 1311 185449813 247137334 1311 0.2512 0.9862070 1.647893 900s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 900s 1 1 1 1 554484 143926517 7599 1.3859 2111 900s 2 1 2 1 143926517 185449813 2668 2.0704 774 900s 3 1 3 1 185449813 247137334 4391 2.6341 1311 900s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 900s 1 2111 554484 143926517 2111 0.5237 0.3300521 1.055848 900s 2 774 143926517 185449813 774 0.1542 0.8755722 1.194828 900s 3 1311 185449813 247137334 1311 0.2512 0.9862070 1.647893 900s > print(fit) 900s chromosome tcnId dhId start end tcnNbrOfLoci tcnMean tcnNbrOfSNPs 900s 1 1 1 1 554484 143926517 7599 1.3859 2111 900s 2 1 2 1 143926517 185449813 2668 2.0704 774 900s 3 1 3 1 185449813 247137334 4391 2.6341 1311 900s tcnNbrOfHets dhNbrOfLoci dhMean c1Mean c2Mean 900s 1 2111 2111 0.5237 0.3300521 1.055848 900s 2 774 774 0.1542 0.8755722 1.194828 900s 3 1311 1311 0.2512 0.9862070 1.647893 900s > 900s > # Plot results 900s > plotTracks(fit) 900s > 900s > # Sanity check 900s > stopifnot(nbrOfSegments(fit) == nSegs) 900s > 900s > 900s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 900s > # Bootstrap segment level estimates 900s > # (used by the AB caller, which, if skipped here, 900s > # will do it automatically) 900s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 900s > fit <- bootstrapTCNandDHByRegion(fit, B=B, verbose=-10) 900s Resample (TCN,DH) signals and re-estimate summaries for segment & changepoint... 900s Already done? 900s tcn_2.5% tcn_5% tcn_95% tcn_97.5% dh_2.5% dh_5% dh_95% dh_97.5% 900s FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE 900s c1_2.5% c1_5% c1_95% c1_97.5% c2_2.5% c2_5% c2_95% c2_97.5% 900s FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE 900s Bootstrapping (TCN,DH,C1,C2) segment mean levels... 900s Identifying heterozygous & homozygous SNPs and non-polymorphic loci... 900s Number of loci: 14658 900s Number of SNPs: 4196 900s Number of non-SNPs: 10462 900s Identifying heterozygous & homozygous SNPs and non-polymorphic loci...done 900s num [1:3, 1:100, 1:4] NA NA NA NA NA NA NA NA NA NA ... 900s - attr(*, "dimnames")=List of 3 900s ..$ : NULL 900s ..$ : NULL 900s ..$ : chr [1:4] "tcn" "dh" "c1" "c2" 900s Segment #1 (chr 1, tcnId=1, dhId=1) of 3... 900s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 900s 1 1 1 1 554484 143926517 7599 1.3859 2111 900s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 900s 1 2111 554484 143926517 2111 0.5237 0.3300521 1.055848 900s Number of TCNs: 7599 900s Number of DHs: 2111 900s int [1:7599] 1 2 3 4 5 6 7 8 9 10 ... 900s int [1:14658] 1 2 3 4 5 6 7 8 9 10 ... 900s int [1:7599] 1 2 3 4 5 6 7 8 9 10 ... 900s Identify loci used to bootstrap DH means... 900s Heterozygous SNPs to resample for DH: 900s int [1:2111] 10 12 24 28 31 33 34 39 46 48 ... 900s Identify loci used to bootstrap DH means...done 900s Identify loci used to bootstrap TCN means... 900s SNPs: 900s int [1:2111] 10 12 24 28 31 33 34 39 46 48 ... 900s Non-polymorphic loci: 900s int [1:5488] 1 2 3 4 5 6 7 8 9 11 ... 900s Heterozygous SNPs to resample for TCN: 900s int [1:2111] 10 12 24 28 31 33 34 39 46 48 ... 900s Homozygous SNPs to resample for TCN: 900s int(0) 900s Non-polymorphic loci to resample for TCN: 900s int [1:5488] 1 2 3 4 5 6 7 8 9 11 ... 900s Heterozygous SNPs with non-DH to resample for TCN: 900s int(0) 900s Loci to resample for TCN: 900s int [1:7599] 1 2 3 4 5 6 7 8 9 10 ... 900s Identify loci used to bootstrap TCN means...done 900s Number of (#hets, #homs, #nonSNPs): (2111,0,5488) 900s Bootstrapping while preserving (#hets, #homs, #nonSNPs)... 900s Number of bootstrap samples: 100 900s Bootstrapping while preserving (#hets, #homs, #nonSNPs)...done 900s Segment #1 (chr 1, tcnId=1, dhId=1) of 3...done 900s Segment #2 (chr 1, tcnId=2, dhId=1) of 3... 900s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 900s 2 1 2 1 143926517 185449813 2668 2.0704 774 900s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 900s 2 774 143926517 185449813 774 0.1542 0.8755722 1.194828 900s Number of TCNs: 2668 900s Number of DHs: 774 900s int [1:2668] 7600 7601 7602 7603 7604 7605 7606 7607 7608 7609 ... 900s int [1:14658] 1 2 3 4 5 6 7 8 9 10 ... 900s int [1:2668] 7600 7601 7602 7603 7604 7605 7606 7607 7608 7609 ... 900s Identify loci used to bootstrap DH means... 900s Heterozygous SNPs to resample for DH: 900s int [1:774] 7614 7616 7626 7627 7628 7635 7638 7639 7640 7642 ... 900s Identify loci used to bootstrap DH means...done 900s Identify loci used to bootstrap TCN means... 900s SNPs: 900s int [1:774] 7614 7616 7626 7627 7628 7635 7638 7639 7640 7642 ... 900s Non-polymorphic loci: 900s int [1:1894] 7600 7601 7602 7603 7604 7605 7606 7607 7608 7609 ... 900s Heterozygous SNPs to resample for TCN: 900s int [1:774] 7614 7616 7626 7627 7628 7635 7638 7639 7640 7642 ... 900s Homozygous SNPs to resample for TCN: 900s int(0) 900s Non-polymorphic loci to resample for TCN: 900s int [1:1894] 7600 7601 7602 7603 7604 7605 7606 7607 7608 7609 ... 900s Heterozygous SNPs with non-DH to resample for TCN: 900s int(0) 900s Loci to resample for TCN: 900s int [1:2668] 7600 7601 7602 7603 7604 7605 7606 7607 7608 7609 ... 900s Identify loci used to bootstrap TCN means...done 900s Number of (#hets, #homs, #nonSNPs): (774,0,1894) 900s Bootstrapping while preserving (#hets, #homs, #nonSNPs)... 900s Number of bootstrap samples: 100 900s Bootstrapping while preserving (#hets, #homs, #nonSNPs)...done 900s Segment #2 (chr 1, tcnId=2, dhId=1) of 3...done 900s Segment #3 (chr 1, tcnId=3, dhId=1) of 3... 900s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 900s 3 1 3 1 185449813 247137334 4391 2.6341 1311 900s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 900s 3 1311 185449813 247137334 1311 0.2512 0.986207 1.647893 900s Number of TCNs: 4391 900s Number of DHs: 1311 900s int [1:4391] 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 900s int [1:14658] 1 2 3 4 5 6 7 8 9 10 ... 900s int [1:4391] 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 900s Identify loci used to bootstrap DH means... 900s Heterozygous SNPs to resample for DH: 900s int [1:1311] 10269 10271 10281 10282 10283 10293 10295 10297 10300 10302 ... 900s Identify loci used to bootstrap DH means...done 900s Identify loci used to bootstrap TCN means... 900s SNPs: 900s int [1:1311] 10269 10271 10281 10282 10283 10293 10295 10297 10300 10302 ... 900s Non-polymorphic loci: 900s int [1:3080] 10268 10270 10272 10273 10274 10275 10276 10277 10278 10279 ... 900s Heterozygous SNPs to resample for TCN: 900s int [1:1311] 10269 10271 10281 10282 10283 10293 10295 10297 10300 10302 ... 900s Homozygous SNPs to resample for TCN: 900s int(0) 900s Non-polymorphic loci to resample for TCN: 900s int [1:3080] 10268 10270 10272 10273 10274 10275 10276 10277 10278 10279 ... 900s Heterozygous SNPs with non-DH to resample for TCN: 900s int(0) 900s Loci to resample for TCN: 900s int [1:4391] 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 900s Identify loci used to bootstrap TCN means...done 900s Number of (#hets, #homs, #nonSNPs): (1311,0,3080) 900s Bootstrapping while preserving (#hets, #homs, #nonSNPs)... 900s Number of bootstrap samples: 100 901s Bootstrapping while preserving (#hets, #homs, #nonSNPs)...done 901s Segment #3 (chr 1, tcnId=3, dhId=1) of 3...done 901s Bootstrapped segment mean levels 901s num [1:3, 1:100, 1:4] 1.38 2.08 2.63 1.38 2.07 ... 901s - attr(*, "dimnames")=List of 3 901s ..$ : NULL 901s ..$ : NULL 901s ..$ : chr [1:4] "tcn" "dh" "c1" "c2" 901s Calculating (C1,C2) mean levels from (TCN,DH) mean levels... 901s num [1:3, 1:100, 1:4] 1.38 2.08 2.63 1.38 2.07 ... 901s - attr(*, "dimnames")=List of 3 901s ..$ : NULL 901s ..$ : NULL 901s ..$ : chr [1:4] "tcn" "dh" "c1" "c2" 901s Calculating (C1,C2) mean levels from (TCN,DH) mean levels...done 901s Calculating polar (alpha,radius,manhattan) for change points... 901s num [1:2, 1:100, 1:2] -0.5588 -0.0962 -0.5365 -0.1285 -0.5378 ... 901s - attr(*, "dimnames")=List of 3 901s ..$ : NULL 901s ..$ : NULL 901s ..$ : chr [1:2] "c1" "c2" 901s Bootstrapped change points 901s num [1:2, 1:100, 1:5] -2.89 -1.78 -2.87 -1.86 -2.88 ... 901s - attr(*, "dimnames")=List of 3 901s ..$ : NULL 901s ..$ : NULL 901s ..$ : chr [1:5] "alpha" "radius" "manhattan" "d1" ... 901s Calculating polar (alpha,radius,manhattan) for change points...done 901s Bootstrapping (TCN,DH,C1,C2) segment mean levels...done 901s Summarizing bootstrapped segment (‘tcn’, ‘dh’, ‘c1’, ‘c2’) data... 901s num [1:3, 1:4, 1:4] NA NA NA NA NA NA NA NA NA NA ... 901s - attr(*, "dimnames")=List of 3 901s ..$ : NULL 901s ..$ : chr [1:4] "2.5%" "5%" "95%" "97.5%" 901s ..$ : chr [1:4] "tcn" "dh" "c1" "c2" 901s Field #1 ('tcn') of 4... 901s Segment #1 of 3... 901s Segment #1 of 3...done 901s Segment #2 of 3... 901s Segment #2 of 3...done 901s Segment #3 of 3... 901s Segment #3 of 3...done 901s Field #1 ('tcn') of 4...done 901s Field #2 ('dh') of 4... 901s Segment #1 of 3... 901s Segment #1 of 3...done 901s Segment #2 of 3... 901s Segment #2 of 3...done 901s Segment #3 of 3... 901s Segment #3 of 3...done 901s Field #2 ('dh') of 4...done 901s Field #3 ('c1') of 4... 901s Segment #1 of 3... 901s Segment #1 of 3...done 901s Segment #2 of 3... 901s Segment #2 of 3...done 901s Segment #3 of 3... 901s Segment #3 of 3...done 901s Field #3 ('c1') of 4...done 901s Field #4 ('c2') of 4... 901s Segment #1 of 3... 901s Segment #1 of 3...done 901s Segment #2 of 3... 901s Segment #2 of 3...done 901s Segment #3 of 3... 901s Segment #3 of 3...done 901s Field #4 ('c2') of 4...done 901s Bootstrap statistics 901s num [1:3, 1:4, 1:4] 1.38 2.06 2.62 1.38 2.06 ... 901s - attr(*, "dimnames")=List of 3 901s ..$ : NULL 901s ..$ : chr [1:4] "2.5%" "5%" "95%" "97.5%" 901s ..$ : chr [1:4] "tcn" "dh" "c1" "c2" 901s Statistical sanity checks (iff B >= 100)... 901s Available summaries: 2.5%, 5%, 95%, 97.5% 901s Available quantiles: 0.025, 0.05, 0.95, 0.975 901s num [1:3, 1:4, 1:4] 1.38 2.06 2.62 1.38 2.06 ... 901s - attr(*, "dimnames")=List of 3 901s ..$ : NULL 901s ..$ : chr [1:4] "2.5%" "5%" "95%" "97.5%" 901s ..$ : chr [1:4] "tcn" "dh" "c1" "c2" 901s Field #1 ('tcn') of 4... 901s Seg 1. mean=1.3859, range=[1.38092,1.3949], n=7599 901s Seg 2. mean=2.0704, range=[2.05747,2.08326], n=2668 901s Seg 3. mean=2.6341, range=[2.62068,2.64694], n=4391 901s Field #1 ('tcn') of 4...done 901s Field #2 ('dh') of 4... 901s Seg 1. mean=0.5237, range=[0.51753,0.532002], n=2111 901s Seg 2. mean=0.1542, range=[0.144468,0.16453], n=774 901s Seg 3. mean=0.2512, range=[0.242575,0.258832], n=1311 901s Field #2 ('dh') of 4...done 901s Field #3 ('c1') of 4... 901s Seg 1. mean=0.330052, range=[0.323996,0.336038], n=2111 901s Seg 2. mean=0.875572, range=[0.86318,0.887699], n=774 901s Seg 3. mean=0.986207, range=[0.975123,0.998982], n=1311 901s Field #3 ('c1') of 4...done 901s Field #4 ('c2') of 4... 901s Seg 1. mean=1.05585, range=[1.05006,1.06231], n=2111 901s Seg 2. mean=1.19483, range=[1.18417,1.2081], n=774 901s Seg 3. mean=1.64789, range=[1.63403,1.66098], n=1311 901s Field #4 ('c2') of 4...done 901s Statistical sanity checks (iff B >= 100)...done 901s Summarizing bootstrapped segment (‘tcn’, ‘dh’, ‘c1’, ‘c2’) data...done 901s Summarizing bootstrapped changepoint (‘alpha’, ‘radius’, ‘manhattan’, ‘d1’, ‘d2’) data... 901s num [1:2, 1:4, 1:5] NA NA NA NA NA NA NA NA NA NA ... 901s - attr(*, "dimnames")=List of 3 901s ..$ : NULL 901s ..$ : chr [1:4] "2.5%" "5%" "95%" "97.5%" 901s ..$ : chr [1:5] "alpha" "radius" "manhattan" "d1" ... 901s Field #1 ('alpha') of 5... 901s Changepoint #1 of 2... 901s Changepoint #1 of 2...done 901s Changepoint #2 of 2... 901s Changepoint #2 of 2...done 901s Field #1 ('alpha') of 5...done 901s Field #2 ('radius') of 5... 901s Changepoint #1 of 2... 901s Changepoint #1 of 2...done 901s Changepoint #2 of 2... 901s Changepoint #2 of 2...done 901s Field #2 ('radius') of 5...done 901s Field #3 ('manhattan') of 5... 901s Changepoint #1 of 2... 901s Changepoint #1 of 2...done 901s Changepoint #2 of 2... 901s Changepoint #2 of 2...done 901s Field #3 ('manhattan') of 5...done 901s Field #4 ('d1') of 5... 901s Changepoint #1 of 2... 901s Changepoint #1 of 2...done 901s Changepoint #2 of 2... 901s Changepoint #2 of 2...done 901s Field #4 ('d1') of 5...done 901s Field #5 ('d2') of 5... 901s Changepoint #1 of 2... 901s Changepoint #1 of 2...done 901s Changepoint #2 of 2... 901s Changepoint #2 of 2...done 901s Field #5 ('d2') of 5...done 901s Bootstrap statistics 901s num [1:2, 1:4, 1:5] -2.92 -1.86 -2.91 -1.85 -2.87 ... 901s - attr(*, "dimnames")=List of 3 901s ..$ : NULL 901s ..$ : chr [1:4] "2.5%" "5%" "95%" "97.5%" 901s ..$ : chr [1:5] "alpha" "radius" "manhattan" "d1" ... 901s Summarizing bootstrapped changepoint (‘alpha’, ‘radius’, ‘manhattan’, ‘d1’, ‘d2’) data...done 901s Resample (TCN,DH) signals and re-estimate summaries for segment & changepoint...done 901s > print(fit) 901s chromosome tcnId dhId start end tcnNbrOfLoci tcnMean tcnNbrOfSNPs 901s 1 1 1 1 554484 143926517 7599 1.3859 2111 901s 2 1 2 1 143926517 185449813 2668 2.0704 774 901s 3 1 3 1 185449813 247137334 4391 2.6341 1311 901s tcnNbrOfHets dhNbrOfLoci dhMean c1Mean c2Mean 901s 1 2111 2111 0.5237 0.3300521 1.055848 901s 2 774 774 0.1542 0.8755722 1.194828 901s 3 1311 1311 0.2512 0.9862070 1.647893 901s > plotTracks(fit) 901s > 901s > 901s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 901s > # Calling segments in allelic balance (AB) and 901s > # in loss-of-heterozygosity (LOH) 901s > # NOTE: Ideally, this should be done on whole-genome data 901s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 901s > fit <- callAB(fit, verbose=-10) 901s Calling segments of allelic balance from one-sided DH bootstrap confidence intervals... 901s delta (offset adjusting for bias in DH): 0.3466649145302 901s alpha (CI quantile; significance level): 0.05 901s Calling segments... 901s Number of segments called allelic balance (AB): 2 (66.67%) of 3 901s Calling segments...done 901s Calling segments of allelic balance from one-sided DH bootstrap confidence intervals...done 901s > fit <- callLOH(fit, verbose=-10) 901s Calling segments of allelic balance from one-sided DH bootstrap confidence intervals... 901s delta (offset adjusting for bias in C1): 0.771236438183453 901s alpha (CI quantile; significance level): 0.05 901s Calling segments... 901s Number of segments called low C1 (LowC1, "LOH_C1"): 1 (33.33%) of 3 901s Calling segments...done 901s Calling segments of allelic balance from one-sided DH bootstrap confidence intervals...done 901s > print(fit) 901s chromosome tcnId dhId start end tcnNbrOfLoci tcnMean tcnNbrOfSNPs 901s 1 1 1 1 554484 143926517 7599 1.3859 2111 901s 2 1 2 1 143926517 185449813 2668 2.0704 774 901s 3 1 3 1 185449813 247137334 4391 2.6341 1311 901s tcnNbrOfHets dhNbrOfLoci dhMean c1Mean c2Mean abCall lohCall 901s 1 2111 2111 0.5237 0.3300521 1.055848 FALSE TRUE 901s 2 774 774 0.1542 0.8755722 1.194828 TRUE FALSE 901s 3 1311 1311 0.2512 0.9862070 1.647893 TRUE FALSE 901s > plotTracks(fit) 901s > 901s Start: segmentByPairedPSCBS,report.R 901s 901s R version 4.5.2 (2025-10-31) -- "[Not] Part in a Rumble" 901s Copyright (C) 2025 The R Foundation for Statistical Computing 901s Platform: aarch64-unknown-linux-gnu 901s 901s R is free software and comes with ABSOLUTELY NO WARRANTY. 901s You are welcome to redistribute it under certain conditions. 901s Type 'license()' or 'licence()' for distribution details. 901s 901s R is a collaborative project with many contributors. 901s Type 'contributors()' for more information and 901s 'citation()' on how to cite R or R packages in publications. 901s 901s Type 'demo()' for some demos, 'help()' for on-line help, or 901s 'help.start()' for an HTML browser interface to help. 901s Type 'q()' to quit R. 901s 901s > # This test script calls a report generator which requires 901s > # the 'ggplot2' package, which in turn will require packages 901s > # 'colorspace', 'dichromat', 'munsell', 'reshape2' and 'scales'. 901s > 901s > # Only run this test in full testing mode 901s > if (Sys.getenv("_R_CHECK_FULL_") != "") { 901s + library("PSCBS") 901s + 901s + # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 901s + # Load SNP microarray data 901s + # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 901s + data <- PSCBS::exampleData("paired.chr01") 901s + str(data) 901s + 901s + 901s + # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 901s + # Paired PSCBS segmentation 901s + # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 901s + # Drop single-locus outliers 901s + dataS <- dropSegmentationOutliers(data) 901s + 901s + # Speed up example by segmenting fewer loci 901s + dataS <- dataS[seq(from=1, to=nrow(data), by=5),] 901s + 901s + str(dataS) 901s + 901s + gaps <- findLargeGaps(dataS, minLength=2e6) 901s + knownSegments <- gapsToSegments(gaps) 901s + 901s + # Paired PSCBS segmentation 901s + fit <- segmentByPairedPSCBS(dataS, knownSegments=knownSegments, 901s + seed=0xBEEF, verbose=-10) 901s + 901s + # Fake a multi-chromosome segmentation 901s + fit1 <- fit 901s + fit2 <- renameChromosomes(fit, from=1, to=2) 901s + fit <- c(fit1, fit2) 901s + 901s + report(fit, sampleName="PairedPSCBS", studyName="PSCBS-Ex", verbose=-10) 901s + 901s + } # if (Sys.getenv("_R_CHECK_FULL_")) 901s > 901s Start: segmentByPairedPSCBS,seqOfSegmentsByDP.R 901s 901s R version 4.5.2 (2025-10-31) -- "[Not] Part in a Rumble" 901s Copyright (C) 2025 The R Foundation for Statistical Computing 901s Platform: aarch64-unknown-linux-gnu 901s 901s R is free software and comes with ABSOLUTELY NO WARRANTY. 901s You are welcome to redistribute it under certain conditions. 901s Type 'license()' or 'licence()' for distribution details. 901s 901s R is a collaborative project with many contributors. 901s Type 'contributors()' for more information and 901s 'citation()' on how to cite R or R packages in publications. 901s 901s Type 'demo()' for some demos, 'help()' for on-line help, or 901s 'help.start()' for an HTML browser interface to help. 901s Type 'q()' to quit R. 901s 901s > library("PSCBS") 902s PSCBS v0.68.0 (2025-04-18 19:40:02 UTC) successfully loaded. See ?PSCBS for help. 902s > subplots <- R.utils::subplots 902s > stext <- R.utils::stext 902s > 902s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 902s > # Load SNP microarray data 902s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 902s > data <- PSCBS::exampleData("paired.chr01") 902s > str(data) 902s 'data.frame': 73346 obs. of 6 variables: 902s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 902s $ x : int 1145994 2224111 2319424 2543484 2926730 2941694 3084986 3155127 3292731 3695086 ... 902s $ CT : num 1.625 1.071 1.406 1.18 0.856 ... 902s $ betaT : num 0.757 0.771 0.834 0.778 0.229 ... 902s $ CN : num 2.36 2.13 2.59 1.93 1.71 ... 902s $ betaN : num 0.827 0.875 0.887 0.884 0.103 ... 902s > 902s > 902s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 902s > # Paired PSCBS segmentation 902s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 902s > # Drop single-locus outliers 902s > dataS <- dropSegmentationOutliers(data) 902s > 902s > # Run light-weight tests by default 902s > if (Sys.getenv("_R_CHECK_FULL_") == "") { 902s + # Use only every 5th data point 902s + dataS <- dataS[seq(from=1, to=nrow(data), by=5),] 902s + # Number of segments (for assertion) 902s + nSegs <- 3L 902s + # Number of bootstrap samples (see below) 902s + B <- 100L 902s + } else { 902s + # Full tests 902s + nSegs <- 12L 902s + B <- 1000L 902s + } 902s > 902s > str(dataS) 902s 'data.frame': 14670 obs. of 6 variables: 902s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 902s $ x : int 1145994 2941694 3710825 4240737 4276892 4464544 4714611 5095111 5034491 5158416 ... 902s $ CT : num 1.63 1.4 1.41 1.17 1.16 ... 902s $ betaT : num 0.7574 0.169 0.2357 0.2604 0.0576 ... 902s $ CN : num 2.36 2.13 2.26 2.01 2.32 ... 902s $ betaN : num 0.8274 0.5072 0.1671 0.1609 0.0421 ... 902s > 902s > R.oo::attachLocally(dataS) 902s > 902s > 902s > gaps <- findLargeGaps(dataS, minLength=2e6) 902s > knownSegments <- gapsToSegments(gaps, dropGaps=TRUE) 902s > 902s > # Paired PSCBS segmentation 902s > fit <- segmentByPairedPSCBS(dataS, knownSegments=knownSegments, 902s + seed=0xBEEF, verbose=-10) 902s Segmenting paired tumor-normal signals using Paired PSCBS... 902s Calling genotypes from normal allele B fractions... 902s num [1:14670] 0.8274 0.5072 0.1671 0.1609 0.0421 ... 902s Called genotypes: 902s num [1:14670] 1 0.5 0 0 0 0 1 0 1 0.5 ... 902s - attr(*, "modelFit")=List of 1 902s ..$ :List of 7 902s .. ..$ flavor : chr "density" 902s .. ..$ cn : int 2 902s .. ..$ nbrOfGenotypeGroups: int 3 902s .. ..$ tau : num [1:2] 0.315 0.677 902s .. ..$ n : int 14640 902s .. ..$ fit :Classes ‘PeaksAndValleys’ and 'data.frame': 5 obs. of 3 variables: 902s .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 902s .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 902s .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 902s .. ..$ fitValleys :Classes ‘PeaksAndValleys’ and 'data.frame': 2 obs. of 3 variables: 902s .. .. ..$ type : chr [1:2] "valley" "valley" 902s .. .. ..$ x : num [1:2] 0.315 0.677 902s .. .. ..$ density: num [1:2] 0.522 0.551 902s ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 902s muN 902s 0 0.5 1 902s 5221 4198 5251 902s Calling genotypes from normal allele B fractions...done 902s Normalizing betaT using betaN (TumorBoost)... 902s Normalized BAFs: 902s num [1:14670] 0.9301 0.1667 0.0685 0.0995 0.0155 ... 902s - attr(*, "modelFit")=List of 5 902s ..$ method : chr "normalizeTumorBoost" 902s ..$ flavor : chr "v4" 902s ..$ delta : num [1:14670] -0.17264 0.00239 0.1671 0.16085 0.04213 ... 902s .. ..- attr(*, "modelFit")=List of 1 902s .. .. ..$ :List of 7 902s .. .. .. ..$ flavor : chr "density" 902s .. .. .. ..$ cn : int 2 902s .. .. .. ..$ nbrOfGenotypeGroups: int 3 902s .. .. .. ..$ tau : num [1:2] 0.315 0.677 902s .. .. .. ..$ n : int 14640 902s .. .. .. ..$ fit :Classes ‘PeaksAndValleys’ and 'data.frame': 5 obs. of 3 variables: 902s .. .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 902s .. .. .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 902s .. .. .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 902s .. .. .. ..$ fitValleys :Classes ‘PeaksAndValleys’ and 'data.frame': 2 obs. of 3 variables: 902s .. .. .. .. ..$ type : chr [1:2] "valley" "valley" 902s .. .. .. .. ..$ x : num [1:2] 0.315 0.677 902s .. .. .. .. ..$ density: num [1:2] 0.522 0.551 902s .. .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 902s ..$ preserveScale: logi FALSE 902s ..$ scaleFactor : num NA 902s Normalizing betaT using betaN (TumorBoost)...done 902s Setup up data... 902s 'data.frame': 14670 obs. of 7 variables: 902s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 902s $ x : num 1145994 2941694 3710825 4240737 4276892 ... 902s $ CT : num 1.63 1.4 1.41 1.17 1.16 ... 902s $ betaT : num 0.7574 0.169 0.2357 0.2604 0.0576 ... 902s $ betaTN : num 0.9301 0.1667 0.0685 0.0995 0.0155 ... 902s ..- attr(*, "modelFit")=List of 5 902s .. ..$ method : chr "normalizeTumorBoost" 902s .. ..$ flavor : chr "v4" 902s .. ..$ delta : num [1:14670] -0.17264 0.00239 0.1671 0.16085 0.04213 ... 902s .. .. ..- attr(*, "modelFit")=List of 1 902s .. .. .. ..$ :List of 7 902s .. .. .. .. ..$ flavor : chr "density" 902s .. .. .. .. ..$ cn : int 2 902s .. .. .. .. ..$ nbrOfGenotypeGroups: int 3 902s .. .. .. .. ..$ tau : num [1:2] 0.315 0.677 902s .. .. .. .. ..$ n : int 14640 902s .. .. .. .. ..$ fit :Classes ‘PeaksAndValleys’ and 'data.frame': 5 obs. of 3 variables: 902s .. .. .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 902s .. .. .. .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 902s .. .. .. .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 902s .. .. .. .. ..$ fitValleys :Classes ‘PeaksAndValleys’ and 'data.frame': 2 obs. of 3 variables: 902s .. .. .. .. .. ..$ type : chr [1:2] "valley" "valley" 902s .. .. .. .. .. ..$ x : num [1:2] 0.315 0.677 902s .. .. .. .. .. ..$ density: num [1:2] 0.522 0.551 902s .. .. .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 902s .. ..$ preserveScale: logi FALSE 902s .. ..$ scaleFactor : num NA 902s $ betaN : num 0.8274 0.5072 0.1671 0.1609 0.0421 ... 902s $ muN : num 1 0.5 0 0 0 0 1 0 1 0.5 ... 902s ..- attr(*, "modelFit")=List of 1 902s .. ..$ :List of 7 902s .. .. ..$ flavor : chr "density" 902s .. .. ..$ cn : int 2 902s .. .. ..$ nbrOfGenotypeGroups: int 3 902s .. .. ..$ tau : num [1:2] 0.315 0.677 902s .. .. ..$ n : int 14640 902s .. .. ..$ fit :Classes ‘PeaksAndValleys’ and 'data.frame': 5 obs. of 3 variables: 902s .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 902s .. .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 902s .. .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 902s .. .. ..$ fitValleys :Classes ‘PeaksAndValleys’ and 'data.frame': 2 obs. of 3 variables: 902s .. .. .. ..$ type : chr [1:2] "valley" "valley" 902s .. .. .. ..$ x : num [1:2] 0.315 0.677 902s .. .. .. ..$ density: num [1:2] 0.522 0.551 902s .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 902s Setup up data...done 902s Dropping loci for which TCNs are missing... 902s Number of loci dropped: 12 902s Dropping loci for which TCNs are missing...done 902s Ordering data along genome... 902s 'data.frame': 14658 obs. of 7 variables: 902s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 902s $ x : num 554484 730720 782343 878522 916294 ... 902s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 902s $ betaT : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 902s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 902s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 902s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 902s Ordering data along genome...done 902s Keeping only current chromosome for 'knownSegments'... 902s Chromosome: 1 902s Known segments for this chromosome: 902s chromosome start end length 902s 1 1 -Inf 120908858 Inf 902s 2 1 142693888 Inf Inf 902s Keeping only current chromosome for 'knownSegments'...done 902s alphaTCN: 0.009 902s alphaDH: 0.001 902s Number of loci: 14658 902s Calculating DHs... 902s Number of SNPs: 14658 902s Number of heterozygous SNPs: 4196 (28.63%) 902s Normalized DHs: 902s num [1:14658] NA NA NA NA NA ... 902s Calculating DHs...done 902s Random seed temporarily set (seed=c(48879), kind="L'Ecuyer-CMRG") 902s Produced 2 seeds from this stream for future usage 902s Identification of change points by total copy numbers... 902s Segmenting by CBS... 902s Chromosome: 1 902s Segmenting multiple segments on current chromosome... 902s Number of segments: 2 902s Random seed temporarily set (seed=c(10407, 1066287653, -51199871, 161854402, -1995183193, 1503453565, -747102133), kind="L'Ecuyer-CMRG") 902s Produced 2 seeds from this stream for future usage 902s Segmenting by CBS... 902s Chromosome: 1 902s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 902s Segmenting by CBS...done 902s Segmenting by CBS... 902s Chromosome: 1 902s Random seed temporarily set (seed=c(10407, -821273412, -52578226, 1415511586, 721384351, -665928286, 1316562960), kind="L'Ecuyer-CMRG") 903s Segmenting by CBS...done 903s Segmenting multiple segments on current chromosome...done 903s Segmenting by CBS...done 903s List of 4 903s $ data :'data.frame': 14658 obs. of 4 variables: 903s ..$ chromosome: int [1:14658] 1 1 1 1 1 1 1 1 1 1 ... 903s ..$ x : num [1:14658] 554484 730720 782343 878522 916294 ... 903s ..$ y : num [1:14658] 1.88 1.8 1.59 1.64 1.53 ... 903s ..$ index : int [1:14658] 1 2 3 4 5 6 7 8 9 10 ... 903s $ output :'data.frame': 3 obs. of 6 variables: 903s ..$ sampleName: chr [1:3] NA NA NA 903s ..$ chromosome: int [1:3] 1 1 1 903s ..$ start : num [1:3] 5.54e+05 1.43e+08 1.85e+08 903s ..$ end : num [1:3] 1.21e+08 1.85e+08 2.47e+08 903s ..$ nbrOfLoci : int [1:3] 7586 2681 4391 903s ..$ mean : num [1:3] 1.39 2.07 2.63 903s $ segRows:'data.frame': 3 obs. of 2 variables: 903s ..$ startRow: int [1:3] 1 7587 10268 903s ..$ endRow : int [1:3] 7586 10267 14658 903s $ params :List of 5 903s ..$ alpha : num 0.009 903s ..$ undo : num 0 903s ..$ joinSegments : logi TRUE 903s ..$ knownSegments:'data.frame': 2 obs. of 3 variables: 903s .. ..$ chromosome: int [1:2] 1 1 903s .. ..$ start : num [1:2] -Inf 1.43e+08 903s .. ..$ end : num [1:2] 1.21e+08 Inf 903s ..$ seed : int [1:7] 10407 1066287653 -51199871 161854402 -1995183193 1503453565 -747102133 903s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 903s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.129 0.001 0.129 0 0 903s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 903s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 903s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 903s Identification of change points by total copy numbers...done 903s Restructure TCN segmentation results... 903s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean 903s 1 1 554484 120908858 7586 1.3853 903s 2 1 142693888 185449813 2681 2.0689 903s 3 1 185449813 247137334 4391 2.6341 903s Number of TCN segments: 3 903s Restructure TCN segmentation results...done 903s Total CN segment #1 ([ 554484,1.20909e+08]) of 3... 903s Number of TCN loci in segment: 7586 903s Locus data for TCN segment: 903s 'data.frame': 7586 obs. of 9 variables: 903s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 903s $ x : num 554484 730720 782343 878522 916294 ... 903s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 903s $ betaT : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 903s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 903s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 903s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 903s $ index : int 1 2 3 4 5 6 7 8 9 10 ... 903s $ rho : num NA NA NA NA NA ... 903s Number of loci: 7586 903s Number of SNPs: 2108 (27.79%) 903s Number of heterozygous SNPs: 2108 (100.00%) 903s Chromosome: 1 903s Segmenting DH signals... 903s Segmenting by CBS... 903s Chromosome: 1 903s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 903s Segmenting by CBS...done 903s List of 4 903s $ data :'data.frame': 7586 obs. of 4 variables: 903s ..$ chromosome: int [1:7586] 1 1 1 1 1 1 1 1 1 1 ... 903s ..$ x : num [1:7586] 554484 730720 782343 878522 916294 ... 903s ..$ y : num [1:7586] NA NA NA NA NA ... 903s ..$ index : int [1:7586] 1 2 3 4 5 6 7 8 9 10 ... 903s $ output :'data.frame': 1 obs. of 6 variables: 903s ..$ sampleName: chr NA 903s ..$ chromosome: int 1 903s ..$ start : num 554484 903s ..$ end : num 1.21e+08 903s ..$ nbrOfLoci : int 2108 903s ..$ mean : num 0.512 903s $ segRows:'data.frame': 1 obs. of 2 variables: 903s ..$ startRow: int 10 903s ..$ endRow : int 7574 903s $ params :List of 5 903s ..$ alpha : num 0.001 903s ..$ undo : num 0 903s ..$ joinSegments : logi TRUE 903s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 903s .. ..$ chromosome: int 1 903s .. ..$ start : num 554484 903s .. ..$ end : num 1.21e+08 903s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 903s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 903s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.037 0 0.037 0 0 903s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 903s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 903s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 903s DH segmentation (locally-indexed) rows: 903s startRow endRow 903s 1 10 7574 903s int [1:7586] 1 2 3 4 5 6 7 8 9 10 ... 903s DH segmentation rows: 903s startRow endRow 903s 1 10 7574 903s Segmenting DH signals...done 903s DH segmentation table: 903s dhStart dhEnd dhNbrOfLoci dhMean 903s 1 554484 120908858 2108 0.5116 903s startRow endRow 903s 1 10 7574 903s Rows: 903s [1] 1 903s TCN segmentation rows: 903s startRow endRow 903s 1 1 7586 903s TCN and DH segmentation rows: 903s startRow endRow 903s 1 1 7586 903s startRow endRow 903s 1 10 7574 903s NULL 903s TCN segmentation (expanded) rows: 903s startRow endRow 903s 1 1 7586 903s TCN and DH segmentation rows: 903s startRow endRow 903s 1 1 7586 903s 2 7587 10267 903s 3 10268 14658 903s startRow endRow 903s 1 10 7574 903s startRow endRow 903s 1 1 7586 903s Total CN segmentation table (expanded): 903s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 903s 1 1 554484 120908858 7586 1.3853 2108 2108 903s (TCN,DH) segmentation for one total CN segment: 903s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 903s 1 1 1 1 554484 120908858 7586 1.3853 2108 903s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 903s 1 2108 554484 120908858 2108 0.5116 903s Total CN segment #1 ([ 554484,1.20909e+08]) of 3...done 903s Total CN segment #2 ([1.42694e+08,1.8545e+08]) of 3... 903s Number of TCN loci in segment: 2681 903s Locus data for TCN segment: 903s 'data.frame': 2681 obs. of 9 variables: 903s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 903s $ x : num 1.43e+08 1.43e+08 1.43e+08 1.43e+08 1.44e+08 ... 903s $ CT : num 2.27 1.55 1.47 1.5 1.81 ... 903s $ betaT : num 0.34 0.55 0.048 0.813 0.575 ... 903s $ betaTN : num 0.441 0.629 -0.05 0.958 0.872 ... 903s $ betaN : num 0.3851 0.3933 0.0981 0.8552 0.7028 ... 903s $ muN : num 0.5 0.5 0 1 1 1 1 0.5 1 1 ... 903s $ index : int 7587 7588 7589 7590 7591 7592 7593 7594 7595 7596 ... 903s $ rho : num 0.117 0.258 NA NA NA ... 903s Number of loci: 2681 903s Number of SNPs: 777 (28.98%) 903s Number of heterozygous SNPs: 777 (100.00%) 903s Chromosome: 1 903s Segmenting DH signals... 903s Segmenting by CBS... 903s Chromosome: 1 903s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 903s Segmenting by CBS...done 903s List of 4 903s $ data :'data.frame': 2681 obs. of 4 variables: 903s ..$ chromosome: int [1:2681] 1 1 1 1 1 1 1 1 1 1 ... 903s ..$ x : num [1:2681] 1.43e+08 1.43e+08 1.43e+08 1.43e+08 1.44e+08 ... 903s ..$ y : num [1:2681] 0.117 0.258 NA NA NA ... 903s ..$ index : int [1:2681] 1 2 3 4 5 6 7 8 9 10 ... 903s $ output :'data.frame': 1 obs. of 6 variables: 903s ..$ sampleName: chr NA 903s ..$ chromosome: int 1 903s ..$ start : num 1.43e+08 903s ..$ end : num 1.85e+08 903s ..$ nbrOfLoci : int 777 903s ..$ mean : num 0.0973 903s $ segRows:'data.frame': 1 obs. of 2 variables: 903s ..$ startRow: int 1 903s ..$ endRow : int 2677 903s $ params :List of 5 903s ..$ alpha : num 0.001 903s ..$ undo : num 0 903s ..$ joinSegments : logi TRUE 903s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 903s .. ..$ chromosome: int 1 903s .. ..$ start : num 1.43e+08 903s .. ..$ end : num 1.85e+08 903s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 903s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 903s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.007 0.001 0.008 0 0 903s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 903s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 903s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 903s DH segmentation (locally-indexed) rows: 903s startRow endRow 903s 1 1 2677 903s int [1:2681] 7587 7588 7589 7590 7591 7592 7593 7594 7595 7596 ... 903s DH segmentation rows: 903s startRow endRow 903s 1 7587 10263 903s Segmenting DH signals...done 903s DH segmentation table: 903s dhStart dhEnd dhNbrOfLoci dhMean 903s 1 142693888 185449813 777 0.0973 903s startRow endRow 903s 1 7587 10263 903s Rows: 903s [1] 2 903s TCN segmentation rows: 903s startRow endRow 903s 2 7587 10267 903s TCN and DH segmentation rows: 903s startRow endRow 903s 2 7587 10267 903s startRow endRow 903s 1 7587 10263 903s startRow endRow 903s 1 1 7586 903s TCN segmentation (expanded) rows: 903s startRow endRow 903s 1 1 7586 903s 2 7587 10267 903s TCN and DH segmentation rows: 903s startRow endRow 903s 1 1 7586 903s 2 7587 10267 903s 3 10268 14658 903s startRow endRow 903s 1 10 7574 903s 2 7587 10263 903s startRow endRow 903s 1 1 7586 903s 2 7587 10267 903s Total CN segmentation table (expanded): 903s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 903s 2 1 142693888 185449813 2681 2.0689 777 777 903s (TCN,DH) segmentation for one total CN segment: 903s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 903s 2 2 1 1 142693888 185449813 2681 2.0689 777 903s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 903s 2 777 142693888 185449813 777 0.0973 903s Total CN segment #2 ([1.42694e+08,1.8545e+08]) of 3...done 903s Total CN segment #3 ([1.8545e+08,2.47137e+08]) of 3... 903s Number of TCN loci in segment: 4391 903s Locus data for TCN segment: 903s 'data.frame': 4391 obs. of 9 variables: 903s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 903s $ x : num 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 903s $ CT : num 2.93 2.15 2.82 2.93 2.46 ... 903s $ betaT : num 0.0811 0.5154 0.9473 0.3734 0.7506 ... 903s $ betaTN : num -0.169 0.609 1.028 0.525 0.968 ... 903s $ betaN : num 0.25 0.38 0.919 0.34 0.783 ... 903s $ muN : num 0 0.5 1 0.5 1 1 0 1 0 1 ... 903s $ index : int 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 903s $ rho : num NA 0.2186 NA 0.0503 NA ... 903s Number of loci: 4391 903s Number of SNPs: 1311 (29.86%) 903s Number of heterozygous SNPs: 1311 (100.00%) 903s Chromosome: 1 903s Segmenting DH signals... 903s Segmenting by CBS... 903s Chromosome: 1 903s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 903s Segmenting by CBS...done 903s List of 4 903s $ data :'data.frame': 4391 obs. of 4 variables: 903s ..$ chromosome: int [1:4391] 1 1 1 1 1 1 1 1 1 1 ... 903s ..$ x : num [1:4391] 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 903s ..$ y : num [1:4391] NA 0.2186 NA 0.0503 NA ... 903s ..$ index : int [1:4391] 1 2 3 4 5 6 7 8 9 10 ... 903s $ output :'data.frame': 1 obs. of 6 variables: 903s ..$ sampleName: chr NA 903s ..$ chromosome: int 1 903s ..$ start : num 1.85e+08 903s ..$ end : num 2.47e+08 903s ..$ nbrOfLoci : int 1311 903s ..$ mean : num 0.23 903s $ segRows:'data.frame': 1 obs. of 2 variables: 903s ..$ startRow: int 2 903s ..$ endRow : int 4388 903s $ params :List of 5 903s ..$ alpha : num 0.001 903s ..$ undo : num 0 903s ..$ joinSegments : logi TRUE 903s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 903s .. ..$ chromosome: int 1 903s .. ..$ start : num 1.85e+08 903s .. ..$ end : num 2.47e+08 903s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 903s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 903s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.015 0 0.015 0 0 903s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 903s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 903s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 903s DH segmentation (locally-indexed) rows: 903s startRow endRow 903s 1 2 4388 903s int [1:4391] 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 903s DH segmentation rows: 903s startRow endRow 903s 1 10269 14655 903s Segmenting DH signals...done 903s DH segmentation table: 903s dhStart dhEnd dhNbrOfLoci dhMean 903s 1 185449813 247137334 1311 0.2295 903s startRow endRow 903s 1 10269 14655 903s Rows: 903s [1] 3 903s TCN segmentation rows: 903s startRow endRow 903s 3 10268 14658 903s TCN and DH segmentation rows: 903s startRow endRow 903s 3 10268 14658 903s startRow endRow 903s 1 10269 14655 903s startRow endRow 903s 1 1 7586 903s 2 7587 10267 903s TCN segmentation (expanded) rows: 903s startRow endRow 903s 1 1 7586 903s 2 7587 10267 903s 3 10268 14658 903s TCN and DH segmentation rows: 903s startRow endRow 903s 1 1 7586 903s 2 7587 10267 903s 3 10268 14658 903s startRow endRow 903s 1 10 7574 903s 2 7587 10263 903s 3 10269 14655 903s startRow endRow 903s 1 1 7586 903s 2 7587 10267 903s 3 10268 14658 903s Total CN segmentation table (expanded): 903s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 903s 3 1 185449813 247137334 4391 2.6341 1311 1311 903s (TCN,DH) segmentation for one total CN segment: 903s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 903s 3 3 1 1 185449813 247137334 4391 2.6341 1311 903s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 903s 3 1311 185449813 247137334 1311 0.2295 903s Total CN segment #3 ([1.8545e+08,2.47137e+08]) of 3...done 903s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 903s 1 1 1 1 554484 120908858 7586 1.3853 2108 903s 2 1 2 1 142693888 185449813 2681 2.0689 777 903s 3 1 3 1 185449813 247137334 4391 2.6341 1311 903s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 903s 1 2108 554484 120908858 2108 0.5116 903s 2 777 142693888 185449813 777 0.0973 903s 3 1311 185449813 247137334 1311 0.2295 903s Calculating (C1,C2) per segment... 903s Calculating (C1,C2) per segment...done 903s Number of segments: 3 903s Segmenting paired tumor-normal signals using Paired PSCBS...done 903s Post-segmenting TCNs... 903s Number of segments: 3 903s Number of chromosomes: 1 903s [1] 1 903s Chromosome 1 ('chr01') of 1... 903s Rows: 903s [1] 1 2 3 903s Number of segments: 3 903s TCN segment #1 ('1') of 3... 903s Nothing todo. Only one DH segmentation. Skipping. 903s TCN segment #1 ('1') of 3...done 903s TCN segment #2 ('2') of 3... 903s Nothing todo. Only one DH segmentation. Skipping. 903s TCN segment #2 ('2') of 3...done 903s TCN segment #3 ('3') of 3... 903s Nothing todo. Only one DH segmentation. Skipping. 903s TCN segment #3 ('3') of 3...done 903s Chromosome 1 ('chr01') of 1...done 903s Update (C1,C2) per segment... 903s Update (C1,C2) per segment...done 903s Post-segmenting TCNs...done 903s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 903s 1 1 1 1 554484 120908858 7586 1.3853 2108 903s 2 1 2 1 142693888 185449813 2681 2.0689 777 903s 3 1 3 1 185449813 247137334 4391 2.6341 1311 903s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 903s 1 2108 554484 120908858 2108 0.5116 0.3382903 1.047010 903s 2 777 142693888 185449813 777 0.0973 0.9337980 1.135102 903s 3 1311 185449813 247137334 1311 0.2295 1.0147870 1.619313 903s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 903s 1 1 1 1 554484 120908858 7586 1.3853 2108 903s 2 1 2 1 142693888 185449813 2681 2.0689 777 903s 3 1 3 1 185449813 247137334 4391 2.6341 1311 903s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 903s 1 2108 554484 120908858 2108 0.5116 0.3382903 1.047010 903s 2 777 142693888 185449813 777 0.0973 0.9337980 1.135102 903s 3 1311 185449813 247137334 1311 0.2295 1.0147870 1.619313 903s > print(fit) 903s chromosome tcnId dhId start end tcnNbrOfLoci tcnMean tcnNbrOfSNPs 903s 1 1 1 1 554484 120908858 7586 1.3853 2108 903s 2 1 2 1 142693888 185449813 2681 2.0689 777 903s 3 1 3 1 185449813 247137334 4391 2.6341 1311 903s tcnNbrOfHets dhNbrOfLoci dhMean c1Mean c2Mean 903s 1 2108 2108 0.5116 0.3382903 1.047010 903s 2 777 777 0.0973 0.9337980 1.135102 903s 3 1311 1311 0.2295 1.0147870 1.619313 903s > 903s > fit1 <- fit 903s > fit2 <- renameChromosomes(fit1, from=1, to=2) 903s > fit <- c(fit1, fit2) 903s > knownSegments <- tileChromosomes(fit)$params$knownSegments 903s > 903s > segList <- seqOfSegmentsByDP(fit, verbose=-10) 903s Identifying optimal sets of segments via dynamic programming... 903s Shifting TCN levels for every second segment... 903s Split up into non-empty independent regions... 903s Chromosome #1 ('1') of 2... 903s Number of loci on chromosome: 14658 903s Known segments on chromosome: 903s chromosome start end 903s 1 1 -Inf 120908858 903s 2 1 142693888 Inf 903s Known segment #1 of 2... 903s chromosome start end 903s 1 1 -Inf 120908858 903s Known segment #1 of 2...done 903s Known segment #2 of 2... 903s chromosome start end 903s 2 1 142693888 Inf 903s Known segment #2 of 2...done 903s Chromosome #1 ('1') of 2...done 903s Chromosome #2 ('2') of 2... 903s Number of loci on chromosome: 14658 903s Known segments on chromosome: 903s chromosome start end 903s 3 2 -Inf 120908858 903s 4 2 142693888 Inf 903s Known segment #1 of 2... 903s chromosome start end 903s 3 2 -Inf 120908858 903s Known segment #1 of 2...done 903s Known segment #2 of 2... 903s chromosome start end 903s 4 2 142693888 Inf 903s Known segment #2 of 2...done 903s Chromosome #2 ('2') of 2...done 903s Number of independent non-empty regions: 4 903s Split up into non-empty independent regions...done 903s Shift every other region... 903s Shift every other region...done 903s Merge... 903s Merge...done 903s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 903s 1 1 1 1 554484 120908858 7586 101.3853 2108 903s 2 1 2 1 142693888 185449813 2681 2.0689 777 903s 3 1 3 1 185449813 247137334 4391 2.6341 1311 903s 4 2 1 1 554484 120908858 7586 101.3853 2108 903s 5 2 2 1 142693888 185449813 2681 2.0689 777 903s 6 2 3 1 185449813 247137334 4391 2.6341 1311 903s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 903s 1 2108 554484 120908858 2108 0.511612 24.757671 76.627587 903s 2 777 142693888 185449813 777 0.097300 0.933798 1.135102 903s 3 1311 185449813 247137334 1311 0.229500 1.014787 1.619313 903s 4 2108 554484 120908858 2108 0.511612 24.757671 76.627587 903s 5 777 142693888 185449813 777 0.097300 0.933798 1.135102 903s 6 1311 185449813 247137334 1311 0.229500 1.014787 1.619313 903s Shifting TCN levels for every second segment...done 903s Extracting signals for dynamic programming... 903s CT rho 903s Min. : 0.805 Min. :0.0002 903s 1st Qu.: 2.407 1st Qu.:0.1393 903s Median :100.927 Median :0.2934 903s Mean : 53.638 Mean :0.3467 903s 3rd Qu.:101.370 3rd Qu.:0.5566 903s Max. :103.080 Max. :1.0217 903s NA's :20924 903s Extracting signals for dynamic programming...done 903s Dynamic programming... 903s Number of "DP" change points: 5 903s int [1:5] 7586 10267 14658 22244 24925 903s List of 4 903s $ jump :List of 5 903s ..$ : num 22244 903s ..$ : num [1:2] 7586 14658 903s ..$ : num [1:3] 7586 14658 22244 903s ..$ : num [1:4] 7586 10267 14658 22244 903s ..$ : num [1:5] 7586 10267 14658 22244 24925 903s $ rse : num [1:6] 71699116 47249179 35852530 5945 5410 ... 903s $ kbest: num 4 903s $ V : num [1:6, 1:6] 1114 0 0 0 0 ... 903s Dynamic programming...done 903s Excluding cases where known segments no longer correct... 903s Number of independent non-empty regions: 4 903s List of 3 903s $ : num [1:3] 7586 14658 22244 903s $ : num [1:4] 7586 10267 14658 22244 903s $ : num [1:5] 7586 10267 14658 22244 24925 903s Excluding cases where known segments no longer correct...done 903s List of 3 903s $ :'data.frame': 4 obs. of 3 variables: 903s ..$ chromosome: int [1:4] 1 1 2 2 903s ..$ start : num [1:4] 5.54e+05 1.43e+08 5.54e+05 1.43e+08 903s ..$ end : num [1:4] 1.21e+08 2.47e+08 1.21e+08 2.47e+08 903s $ :'data.frame': 5 obs. of 3 variables: 903s ..$ chromosome: int [1:5] 1 1 1 2 2 903s ..$ start : num [1:5] 5.54e+05 1.43e+08 1.85e+08 5.54e+05 1.43e+08 903s ..$ end : num [1:5] 1.21e+08 1.85e+08 2.47e+08 1.21e+08 2.47e+08 903s $ :'data.frame': 6 obs. of 3 variables: 903s ..$ chromosome: int [1:6] 1 1 1 2 2 2 903s ..$ start : num [1:6] 5.54e+05 1.43e+08 1.85e+08 5.54e+05 1.43e+08 ... 903s ..$ end : num [1:6] 1.21e+08 1.85e+08 2.47e+08 1.21e+08 1.85e+08 ... 903s Sequence of number of "DP" change points: 903s [1] 3 4 5 903s Sequence of number of segments: 903s [1] 4 5 6 903s Sequence of number of "discovered" change points: 903s [1] 0 1 2 903s Identifying optimal sets of segments via dynamic programming...done 903s > K <- length(segList) 903s > ks <- seq(from=1, to=K, length.out=min(5,K)) 903s > subplots(length(ks), ncol=1, byrow=TRUE) 903s > par(mar=c(2,1,1,1)) 903s > for (kk in ks) { 903s + knownSegmentsKK <- segList[[kk]] 903s + fitKK <- resegment(fit, knownSegments=knownSegmentsKK, undoTCN=+Inf, undoDH=+Inf) 903s + plotTracks(fitKK, tracks="tcn,c1,c2", Clim=c(0,5), add=TRUE) 903s + abline(v=c(knownSegments$start, knownSegments$end)/1e6, lty=3) 903s + stext(side=3, pos=0, sprintf("Number of segments: %d", nrow(knownSegmentsKK))) 903s + } # for (kk ...) 906s > 906s Start: segmentByPairedPSCBS.R 906s 906s R version 4.5.2 (2025-10-31) -- "[Not] Part in a Rumble" 906s Copyright (C) 2025 The R Foundation for Statistical Computing 906s Platform: aarch64-unknown-linux-gnu 906s 906s R is free software and comes with ABSOLUTELY NO WARRANTY. 906s You are welcome to redistribute it under certain conditions. 906s Type 'license()' or 'licence()' for distribution details. 906s 906s R is a collaborative project with many contributors. 906s Type 'contributors()' for more information and 906s 'citation()' on how to cite R or R packages in publications. 906s 906s Type 'demo()' for some demos, 'help()' for on-line help, or 906s 'help.start()' for an HTML browser interface to help. 906s Type 'q()' to quit R. 906s 906s > ########################################################### 906s > # This tests: 906s > # - segmentByPairedPSCBS(...) 906s > # - segmentByPairedPSCBS(..., knownSegments) 906s > # - tileChromosomes() 906s > # - plotTracks() 906s > ########################################################### 906s > library("PSCBS") 906s PSCBS v0.68.0 (2025-04-18 19:40:02 UTC) successfully loaded. See ?PSCBS for help. 906s > 906s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 906s > # Load SNP microarray data 906s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 906s > data <- PSCBS::exampleData("paired.chr01") 906s > 906s > 906s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 906s > # Paired PSCBS segmentation 906s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 906s > # Drop single-locus outliers 906s > dataS <- dropSegmentationOutliers(data) 906s > 906s > # Run light-weight tests by default 906s > if (Sys.getenv("_R_CHECK_FULL_") == "") { 906s + # Use only every 5th data point 906s + dataS <- dataS[seq(from=1, to=nrow(data), by=5),] 906s + # Number of segments (for assertion) 906s + nSegs <- 4L 906s + } else { 906s + # Full tests 906s + nSegs <- 11L 906s + } 906s > 906s > str(dataS) 906s 'data.frame': 14670 obs. of 6 variables: 906s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 906s $ x : int 1145994 2941694 3710825 4240737 4276892 4464544 4714611 5095111 5034491 5158416 ... 906s $ CT : num 1.63 1.4 1.41 1.17 1.16 ... 906s $ betaT : num 0.7574 0.169 0.2357 0.2604 0.0576 ... 906s $ CN : num 2.36 2.13 2.26 2.01 2.32 ... 906s $ betaN : num 0.8274 0.5072 0.1671 0.1609 0.0421 ... 906s > 906s > fig <- 1 906s > 906s > 906s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 906s > # (a) Don't segment the centromere (and force a separator) 906s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 906s > knownSegments <- data.frame( 906s + chromosome = c( 1, 1, 1), 906s + start = c( -Inf, NA, 141510003), 906s + end = c(120992603, NA, +Inf) 906s + ) 906s > 906s > 906s > # Paired PSCBS segmentation 906s > fit <- segmentByPairedPSCBS(dataS, knownSegments=knownSegments, 906s + seed=0xBEEF, verbose=-10) 906s Segmenting paired tumor-normal signals using Paired PSCBS... 906s Calling genotypes from normal allele B fractions... 906s num [1:14670] 0.8274 0.5072 0.1671 0.1609 0.0421 ... 906s Called genotypes: 906s num [1:14670] 1 0.5 0 0 0 0 1 0 1 0.5 ... 906s - attr(*, "modelFit")=List of 1 906s ..$ :List of 7 906s .. ..$ flavor : chr "density" 906s .. ..$ cn : int 2 906s .. ..$ nbrOfGenotypeGroups: int 3 906s .. ..$ tau : num [1:2] 0.315 0.677 906s .. ..$ n : int 14640 906s .. ..$ fit :Classes ‘PeaksAndValleys’ and 'data.frame': 5 obs. of 3 variables: 906s .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 906s .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 906s .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 906s .. ..$ fitValleys :Classes ‘PeaksAndValleys’ and 'data.frame': 2 obs. of 3 variables: 906s .. .. ..$ type : chr [1:2] "valley" "valley" 906s .. .. ..$ x : num [1:2] 0.315 0.677 906s .. .. ..$ density: num [1:2] 0.522 0.551 906s ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 906s muN 906s 0 0.5 1 906s 5221 4198 5251 906s Calling genotypes from normal allele B fractions...done 906s Normalizing betaT using betaN (TumorBoost)... 906s Normalized BAFs: 906s num [1:14670] 0.9301 0.1667 0.0685 0.0995 0.0155 ... 906s - attr(*, "modelFit")=List of 5 906s ..$ method : chr "normalizeTumorBoost" 906s ..$ flavor : chr "v4" 906s ..$ delta : num [1:14670] -0.17264 0.00239 0.1671 0.16085 0.04213 ... 906s .. ..- attr(*, "modelFit")=List of 1 906s .. .. ..$ :List of 7 906s .. .. .. ..$ flavor : chr "density" 906s .. .. .. ..$ cn : int 2 906s .. .. .. ..$ nbrOfGenotypeGroups: int 3 906s .. .. .. ..$ tau : num [1:2] 0.315 0.677 906s .. .. .. ..$ n : int 14640 906s .. .. .. ..$ fit :Classes ‘PeaksAndValleys’ and 'data.frame': 5 obs. of 3 variables: 906s .. .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 906s .. .. .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 906s .. .. .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 906s .. .. .. ..$ fitValleys :Classes ‘PeaksAndValleys’ and 'data.frame': 2 obs. of 3 variables: 906s .. .. .. .. ..$ type : chr [1:2] "valley" "valley" 906s .. .. .. .. ..$ x : num [1:2] 0.315 0.677 906s .. .. .. .. ..$ density: num [1:2] 0.522 0.551 906s .. .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 906s ..$ preserveScale: logi FALSE 906s ..$ scaleFactor : num NA 906s Normalizing betaT using betaN (TumorBoost)...done 906s Setup up data... 906s 'data.frame': 14670 obs. of 7 variables: 906s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 906s $ x : num 1145994 2941694 3710825 4240737 4276892 ... 906s $ CT : num 1.63 1.4 1.41 1.17 1.16 ... 906s $ betaT : num 0.7574 0.169 0.2357 0.2604 0.0576 ... 906s $ betaTN : num 0.9301 0.1667 0.0685 0.0995 0.0155 ... 906s ..- attr(*, "modelFit")=List of 5 906s .. ..$ method : chr "normalizeTumorBoost" 906s .. ..$ flavor : chr "v4" 906s .. ..$ delta : num [1:14670] -0.17264 0.00239 0.1671 0.16085 0.04213 ... 906s .. .. ..- attr(*, "modelFit")=List of 1 906s .. .. .. ..$ :List of 7 906s .. .. .. .. ..$ flavor : chr "density" 906s .. .. .. .. ..$ cn : int 2 906s .. .. .. .. ..$ nbrOfGenotypeGroups: int 3 906s .. .. .. .. ..$ tau : num [1:2] 0.315 0.677 906s .. .. .. .. ..$ n : int 14640 906s .. .. .. .. ..$ fit :Classes ‘PeaksAndValleys’ and 'data.frame': 5 obs. of 3 variables: 906s .. .. .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 906s .. .. .. .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 906s .. .. .. .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 906s .. .. .. .. ..$ fitValleys :Classes ‘PeaksAndValleys’ and 'data.frame': 2 obs. of 3 variables: 906s .. .. .. .. .. ..$ type : chr [1:2] "valley" "valley" 906s .. .. .. .. .. ..$ x : num [1:2] 0.315 0.677 906s .. .. .. .. .. ..$ density: num [1:2] 0.522 0.551 906s .. .. .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 906s .. ..$ preserveScale: logi FALSE 906s .. ..$ scaleFactor : num NA 906s $ betaN : num 0.8274 0.5072 0.1671 0.1609 0.0421 ... 906s $ muN : num 1 0.5 0 0 0 0 1 0 1 0.5 ... 906s ..- attr(*, "modelFit")=List of 1 906s .. ..$ :List of 7 906s .. .. ..$ flavor : chr "density" 906s .. .. ..$ cn : int 2 906s .. .. ..$ nbrOfGenotypeGroups: int 3 906s .. .. ..$ tau : num [1:2] 0.315 0.677 906s .. .. ..$ n : int 14640 906s .. .. ..$ fit :Classes ‘PeaksAndValleys’ and 'data.frame': 5 obs. of 3 variables: 906s .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 906s .. .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 906s .. .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 906s .. .. ..$ fitValleys :Classes ‘PeaksAndValleys’ and 'data.frame': 2 obs. of 3 variables: 906s .. .. .. ..$ type : chr [1:2] "valley" "valley" 906s .. .. .. ..$ x : num [1:2] 0.315 0.677 906s .. .. .. ..$ density: num [1:2] 0.522 0.551 906s .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 906s Setup up data...done 906s Dropping loci for which TCNs are missing... 906s Number of loci dropped: 12 906s Dropping loci for which TCNs are missing...done 906s Ordering data along genome... 906s 'data.frame': 14658 obs. of 7 variables: 906s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 906s $ x : num 554484 730720 782343 878522 916294 ... 906s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 906s $ betaT : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 906s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 906s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 906s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 906s Ordering data along genome...done 906s Keeping only current chromosome for 'knownSegments'... 906s Chromosome: 1 906s Known segments for this chromosome: 906s chromosome start end 906s 1 1 -Inf 120992603 906s 2 1 NA NA 906s 3 1 141510003 Inf 906s Keeping only current chromosome for 'knownSegments'...done 906s alphaTCN: 0.009 906s alphaDH: 0.001 906s Number of loci: 14658 906s Calculating DHs... 906s Number of SNPs: 14658 906s Number of heterozygous SNPs: 4196 (28.63%) 906s Normalized DHs: 906s num [1:14658] NA NA NA NA NA ... 906s Calculating DHs...done 906s Random seed temporarily set (seed=c(48879), kind="L'Ecuyer-CMRG") 906s Produced 2 seeds from this stream for future usage 906s Identification of change points by total copy numbers... 906s Segmenting by CBS... 906s Chromosome: 1 906s Segmenting multiple segments on current chromosome... 906s Number of segments: 3 907s Random seed temporarily set (seed=c(10407, 1066287653, -51199871, 161854402, -1995183193, 1503453565, -747102133), kind="L'Ecuyer-CMRG") 907s Produced 3 seeds from this stream for future usage 907s Segmenting by CBS... 907s Chromosome: 1 907s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 907s Segmenting by CBS...done 907s Segmenting by CBS... 907s Chromosome: 1 907s Random seed temporarily set (seed=c(10407, -1924040949, -1632234809, -437763632, -1464377300, 676654412, 2080370711), kind="L'Ecuyer-CMRG") 907s Segmenting by CBS...done 907s Segmenting multiple segments on current chromosome...done 907s Segmenting by CBS...done 907s List of 4 907s $ data :'data.frame': 14658 obs. of 4 variables: 907s ..$ chromosome: int [1:14658] 1 1 1 1 1 1 1 1 1 1 ... 907s ..$ x : num [1:14658] 554484 730720 782343 878522 916294 ... 907s ..$ y : num [1:14658] 1.88 1.8 1.59 1.64 1.53 ... 907s ..$ index : int [1:14658] 1 2 3 4 5 6 7 8 9 10 ... 907s $ output :'data.frame': 4 obs. of 6 variables: 907s ..$ sampleName: chr [1:4] NA NA NA NA 907s ..$ chromosome: int [1:4] 1 NA 1 1 907s ..$ start : num [1:4] 5.54e+05 NA 1.42e+08 1.85e+08 907s ..$ end : num [1:4] 1.21e+08 NA 1.85e+08 2.47e+08 907s ..$ nbrOfLoci : int [1:4] 7586 NA 2681 4391 907s ..$ mean : num [1:4] 1.39 NA 2.07 2.63 907s $ segRows:'data.frame': 4 obs. of 2 variables: 907s ..$ startRow: int [1:4] 1 NA 7587 10268 907s ..$ endRow : int [1:4] 7586 NA 10267 14658 907s $ params :List of 5 907s ..$ alpha : num 0.009 907s ..$ undo : num 0 907s ..$ joinSegments : logi TRUE 907s ..$ knownSegments:'data.frame': 4 obs. of 3 variables: 907s .. ..$ chromosome: num [1:4] 1 1 2 1 907s .. ..$ start : num [1:4] -Inf -Inf -Inf 1.42e+08 907s .. ..$ end : num [1:4] 1.21e+08 Inf Inf Inf 907s ..$ seed : int [1:7] 10407 1066287653 -51199871 161854402 -1995183193 1503453565 -747102133 907s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 907s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.128 0.001 0.13 0 0 907s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 907s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 907s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 907s Identification of change points by total copy numbers...done 907s Restructure TCN segmentation results... 907s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean 907s 1 1 554484 120992603 7586 1.3853 907s 2 NA NA NA NA NA 907s 3 1 141510003 185449813 2681 2.0689 907s 4 1 185449813 247137334 4391 2.6341 907s Number of TCN segments: 4 907s Restructure TCN segmentation results...done 907s Total CN segment #1 ([ 554484,1.20993e+08]) of 4... 907s Number of TCN loci in segment: 7586 907s Locus data for TCN segment: 907s 'data.frame': 7586 obs. of 9 variables: 907s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 907s $ x : num 554484 730720 782343 878522 916294 ... 907s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 907s $ betaT : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 907s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 907s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 907s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 907s $ index : int 1 2 3 4 5 6 7 8 9 10 ... 907s $ rho : num NA NA NA NA NA ... 907s Number of loci: 7586 907s Number of SNPs: 2108 (27.79%) 907s Number of heterozygous SNPs: 2108 (100.00%) 907s Chromosome: 1 907s Segmenting DH signals... 907s Segmenting by CBS... 907s Chromosome: 1 907s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 907s Segmenting by CBS...done 907s List of 4 907s $ data :'data.frame': 7586 obs. of 4 variables: 907s ..$ chromosome: int [1:7586] 1 1 1 1 1 1 1 1 1 1 ... 907s ..$ x : num [1:7586] 554484 730720 782343 878522 916294 ... 907s ..$ y : num [1:7586] NA NA NA NA NA ... 907s ..$ index : int [1:7586] 1 2 3 4 5 6 7 8 9 10 ... 907s $ output :'data.frame': 1 obs. of 6 variables: 907s ..$ sampleName: chr NA 907s ..$ chromosome: int 1 907s ..$ start : num 554484 907s ..$ end : num 1.21e+08 907s ..$ nbrOfLoci : int 2108 907s ..$ mean : num 0.512 907s $ segRows:'data.frame': 1 obs. of 2 variables: 907s ..$ startRow: int 10 907s ..$ endRow : int 7574 907s $ params :List of 5 907s ..$ alpha : num 0.001 907s ..$ undo : num 0 907s ..$ joinSegments : logi TRUE 907s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 907s .. ..$ chromosome: int 1 907s .. ..$ start : num 554484 907s .. ..$ end : num 1.21e+08 907s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 907s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 907s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.037 0 0.037 0 0 907s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 907s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 907s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 907s DH segmentation (locally-indexed) rows: 907s startRow endRow 907s 1 10 7574 907s int [1:7586] 1 2 3 4 5 6 7 8 9 10 ... 907s DH segmentation rows: 907s startRow endRow 907s 1 10 7574 907s Segmenting DH signals...done 907s DH segmentation table: 907s dhStart dhEnd dhNbrOfLoci dhMean 907s 1 554484 120992603 2108 0.5116 907s startRow endRow 907s 1 10 7574 907s Rows: 907s [1] 1 907s TCN segmentation rows: 907s startRow endRow 907s 1 1 7586 907s TCN and DH segmentation rows: 907s startRow endRow 907s 1 1 7586 907s startRow endRow 907s 1 10 7574 907s NULL 907s TCN segmentation (expanded) rows: 907s startRow endRow 907s 1 1 7586 907s TCN and DH segmentation rows: 907s startRow endRow 907s 1 1 7586 907s 2 NA NA 907s 3 7587 10267 907s 4 10268 14658 907s startRow endRow 907s 1 10 7574 907s startRow endRow 907s 1 1 7586 907s Total CN segmentation table (expanded): 907s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 907s 1 1 554484 120992603 7586 1.3853 2108 2108 907s (TCN,DH) segmentation for one total CN segment: 907s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 907s 1 1 1 1 554484 120992603 7586 1.3853 2108 907s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 907s 1 2108 554484 120992603 2108 0.5116 907s Total CN segment #1 ([ 554484,1.20993e+08]) of 4...done 907s Total CN segment #2 ([ NA, NA]) of 4... 907s No signals to segment. Just a "splitter" segment. Skipping. 907s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 907s NA 2 1 NA NA NA NA NA 0 907s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 907s NA 0 NA NA 0 NA 907s Total CN segment #2 ([ NA, NA]) of 4...done 907s Total CN segment #3 ([1.4151e+08,1.8545e+08]) of 4... 907s Number of TCN loci in segment: 2681 907s Locus data for TCN segment: 907s 'data.frame': 2681 obs. of 9 variables: 907s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 907s $ x : num 1.43e+08 1.43e+08 1.43e+08 1.43e+08 1.44e+08 ... 907s $ CT : num 2.27 1.55 1.47 1.5 1.81 ... 907s $ betaT : num 0.34 0.55 0.048 0.813 0.575 ... 907s $ betaTN : num 0.441 0.629 -0.05 0.958 0.872 ... 907s $ betaN : num 0.3851 0.3933 0.0981 0.8552 0.7028 ... 907s $ muN : num 0.5 0.5 0 1 1 1 1 0.5 1 1 ... 907s $ index : int 7587 7588 7589 7590 7591 7592 7593 7594 7595 7596 ... 907s $ rho : num 0.117 0.258 NA NA NA ... 907s Number of loci: 2681 907s Number of SNPs: 777 (28.98%) 907s Number of heterozygous SNPs: 777 (100.00%) 907s Chromosome: 1 907s Segmenting DH signals... 907s Segmenting by CBS... 907s Chromosome: 1 907s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 907s Segmenting by CBS...done 907s List of 4 907s $ data :'data.frame': 2681 obs. of 4 variables: 907s ..$ chromosome: int [1:2681] 1 1 1 1 1 1 1 1 1 1 ... 907s ..$ x : num [1:2681] 1.43e+08 1.43e+08 1.43e+08 1.43e+08 1.44e+08 ... 907s ..$ y : num [1:2681] 0.117 0.258 NA NA NA ... 907s ..$ index : int [1:2681] 1 2 3 4 5 6 7 8 9 10 ... 907s $ output :'data.frame': 1 obs. of 6 variables: 907s ..$ sampleName: chr NA 907s ..$ chromosome: int 1 907s ..$ start : num 1.42e+08 907s ..$ end : num 1.85e+08 907s ..$ nbrOfLoci : int 777 907s ..$ mean : num 0.0973 907s $ segRows:'data.frame': 1 obs. of 2 variables: 907s ..$ startRow: int 1 907s ..$ endRow : int 2677 907s $ params :List of 5 907s ..$ alpha : num 0.001 907s ..$ undo : num 0 907s ..$ joinSegments : logi TRUE 907s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 907s .. ..$ chromosome: int 1 907s .. ..$ start : num 1.42e+08 907s .. ..$ end : num 1.85e+08 907s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 907s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 907s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.008 0 0.008 0 0 907s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 907s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 907s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 907s DH segmentation (locally-indexed) rows: 907s startRow endRow 907s 1 1 2677 907s int [1:2681] 7587 7588 7589 7590 7591 7592 7593 7594 7595 7596 ... 907s DH segmentation rows: 907s startRow endRow 907s 1 7587 10263 907s Segmenting DH signals...done 907s DH segmentation table: 907s dhStart dhEnd dhNbrOfLoci dhMean 907s 1 141510003 185449813 777 0.0973 907s startRow endRow 907s 1 7587 10263 907s Rows: 907s [1] 3 907s TCN segmentation rows: 907s startRow endRow 907s 3 7587 10267 907s TCN and DH segmentation rows: 907s startRow endRow 907s 3 7587 10267 907s startRow endRow 907s 1 7587 10263 907s startRow endRow 907s 1 1 7586 907s NA NA NA 907s TCN segmentation (expanded) rows: 907s startRow endRow 907s 1 1 7586 907s NA NA NA 907s 3 7587 10267 907s TCN and DH segmentation rows: 907s startRow endRow 907s 1 1 7586 907s 2 NA NA 907s 3 7587 10267 907s 4 10268 14658 907s startRow endRow 907s 1 10 7574 907s 2 NA NA 907s 3 7587 10263 907s startRow endRow 907s 1 1 7586 907s 2 NA NA 907s 3 7587 10267 907s Total CN segmentation table (expanded): 907s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 907s 3 1 141510003 185449813 2681 2.0689 777 777 907s (TCN,DH) segmentation for one total CN segment: 907s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 907s 3 3 1 1 141510003 185449813 2681 2.0689 777 907s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 907s 3 777 141510003 185449813 777 0.0973 907s Total CN segment #3 ([1.4151e+08,1.8545e+08]) of 4...done 907s Total CN segment #4 ([1.8545e+08,2.47137e+08]) of 4... 907s Number of TCN loci in segment: 4391 907s Locus data for TCN segment: 907s 'data.frame': 4391 obs. of 9 variables: 907s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 907s $ x : num 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 907s $ CT : num 2.93 2.15 2.82 2.93 2.46 ... 907s $ betaT : num 0.0811 0.5154 0.9473 0.3734 0.7506 ... 907s $ betaTN : num -0.169 0.609 1.028 0.525 0.968 ... 907s $ betaN : num 0.25 0.38 0.919 0.34 0.783 ... 907s $ muN : num 0 0.5 1 0.5 1 1 0 1 0 1 ... 907s $ index : int 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 907s $ rho : num NA 0.2186 NA 0.0503 NA ... 907s Number of loci: 4391 907s Number of SNPs: 1311 (29.86%) 907s Number of heterozygous SNPs: 1311 (100.00%) 907s Chromosome: 1 907s Segmenting DH signals... 907s Segmenting by CBS... 908s Chromosome: 1 908s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 908s Segmenting by CBS...done 908s List of 4 908s $ data :'data.frame': 4391 obs. of 4 variables: 908s ..$ chromosome: int [1:4391] 1 1 1 1 1 1 1 1 1 1 ... 908s ..$ x : num [1:4391] 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 908s ..$ y : num [1:4391] NA 0.2186 NA 0.0503 NA ... 908s ..$ index : int [1:4391] 1 2 3 4 5 6 7 8 9 10 ... 908s $ output :'data.frame': 1 obs. of 6 variables: 908s ..$ sampleName: chr NA 908s ..$ chromosome: int 1 908s ..$ start : num 1.85e+08 908s ..$ end : num 2.47e+08 908s ..$ nbrOfLoci : int 1311 908s ..$ mean : num 0.23 908s $ segRows:'data.frame': 1 obs. of 2 variables: 908s ..$ startRow: int 2 908s ..$ endRow : int 4388 908s $ params :List of 5 908s ..$ alpha : num 0.001 908s ..$ undo : num 0 908s ..$ joinSegments : logi TRUE 908s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 908s .. ..$ chromosome: int 1 908s .. ..$ start : num 1.85e+08 908s .. ..$ end : num 2.47e+08 908s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 908s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 908s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.015 0 0.016 0 0 908s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 908s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 908s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 908s DH segmentation (locally-indexed) rows: 908s startRow endRow 908s 1 2 4388 908s int [1:4391] 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 908s DH segmentation rows: 908s startRow endRow 908s 1 10269 14655 908s Segmenting DH signals...done 908s DH segmentation table: 908s dhStart dhEnd dhNbrOfLoci dhMean 908s 1 185449813 247137334 1311 0.2295 908s startRow endRow 908s 1 10269 14655 908s Rows: 908s [1] 4 908s TCN segmentation rows: 908s startRow endRow 908s 4 10268 14658 908s TCN and DH segmentation rows: 908s startRow endRow 908s 4 10268 14658 908s startRow endRow 908s 1 10269 14655 908s startRow endRow 908s 1 1 7586 908s 2 NA NA 908s 3 7587 10267 908s TCN segmentation (expanded) rows: 908s startRow endRow 908s 1 1 7586 908s 2 NA NA 908s 3 7587 10267 908s 4 10268 14658 908s TCN and DH segmentation rows: 908s startRow endRow 908s 1 1 7586 908s 2 NA NA 908s 3 7587 10267 908s 4 10268 14658 908s startRow endRow 908s 1 10 7574 908s 2 NA NA 908s 3 7587 10263 908s 4 10269 14655 908s startRow endRow 908s 1 1 7586 908s 2 NA NA 908s 3 7587 10267 908s 4 10268 14658 908s Total CN segmentation table (expanded): 908s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 908s 4 1 185449813 247137334 4391 2.6341 1311 1311 908s (TCN,DH) segmentation for one total CN segment: 908s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 908s 4 4 1 1 185449813 247137334 4391 2.6341 1311 908s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 908s 4 1311 185449813 247137334 1311 0.2295 908s Total CN segment #4 ([1.8545e+08,2.47137e+08]) of 4...done 908s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 908s 1 1 1 1 554484 120992603 7586 1.3853 2108 908s 2 NA 2 1 NA NA NA NA 0 908s 3 1 3 1 141510003 185449813 2681 2.0689 777 908s 4 1 4 1 185449813 247137334 4391 2.6341 1311 908s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 908s 1 2108 554484 120992603 2108 0.5116 908s 2 0 NA NA 0 NA 908s 3 777 141510003 185449813 777 0.0973 908s 4 1311 185449813 247137334 1311 0.2295 908s Calculating (C1,C2) per segment... 908s Calculating (C1,C2) per segment...done 908s Number of segments: 4 908s Segmenting paired tumor-normal signals using Paired PSCBS...done 908s Post-segmenting TCNs... 908s Number of segments: 3 908s Number of chromosomes: 1 908s [1] 1 908s Chromosome 1 ('chr01') of 1... 908s Rows: 908s [1] 1 2 3 908s Number of segments: 3 908s TCN segment #1 ('1') of 3... 908s Nothing todo. Only one DH segmentation. Skipping. 908s TCN segment #1 ('1') of 3...done 908s TCN segment #2 ('3') of 3... 908s Nothing todo. Only one DH segmentation. Skipping. 908s TCN segment #2 ('3') of 3...done 908s TCN segment #3 ('4') of 3... 908s Nothing todo. Only one DH segmentation. Skipping. 908s TCN segment #3 ('4') of 3...done 908s Chromosome 1 ('chr01') of 1...done 908s Update (C1,C2) per segment... 908s Update (C1,C2) per segment...done 908s Post-segmenting TCNs...done 908s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 908s 1 1 1 1 554484 120992603 7586 1.3853 2108 908s 2 NA 2 1 NA NA NA NA 0 908s 3 1 3 1 141510003 185449813 2681 2.0689 777 908s 4 1 4 1 185449813 247137334 4391 2.6341 1311 908s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 908s 1 2108 554484 120992603 2108 0.5116 0.3382903 1.047010 908s 2 0 NA NA 0 NA NA NA 908s 3 777 141510003 185449813 777 0.0973 0.9337980 1.135102 908s 4 1311 185449813 247137334 1311 0.2295 1.0147870 1.619313 908s > print(fit) 908s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 908s 1 1 1 1 554484 120992603 7586 1.3853 2108 908s 2 NA 2 1 NA NA NA NA 0 908s 3 1 3 1 141510003 185449813 2681 2.0689 777 908s 4 1 4 1 185449813 247137334 4391 2.6341 1311 908s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 908s 1 2108 554484 120992603 2108 0.5116 0.3382903 1.047010 908s 2 0 NA NA 0 NA NA NA 908s 3 777 141510003 185449813 777 0.0973 0.9337980 1.135102 908s 4 1311 185449813 247137334 1311 0.2295 1.0147870 1.619313 908s chromosome tcnId dhId start end tcnNbrOfLoci tcnMean tcnNbrOfSNPs 908s 1 1 1 1 554484 120992603 7586 1.3853 2108 908s 2 NA 2 1 NA NA NA NA 0 908s 3 1 3 1 141510003 185449813 2681 2.0689 777 908s 4 1 4 1 185449813 247137334 4391 2.6341 1311 908s tcnNbrOfHets dhNbrOfLoci dhMean c1Mean c2Mean 908s 1 2108 2108 0.5116 0.3382903 1.047010 908s 2 0 0 NA NA NA 908s 3 777 777 0.0973 0.9337980 1.135102 908s 4 1311 1311 0.2295 1.0147870 1.619313 908s > 908s > # Plot results 908s > dev.set(2L) 908s null device 908s 1 908s > plotTracks(fit) 908s > abline(v=c(knownSegments$start, knownSegments$end)/1e6, lty=3) 908s > 908s > # Sanity check 908s > stopifnot(nbrOfSegments(fit) == nSegs) 908s > 908s > fit1 <- fit 908s > 908s > 908s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 908s > # (b) Segment also the centromere (which will become NAs) 908s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 908s > knownSegments <- data.frame( 908s + chromosome = c( 1, 1, 1), 908s + start = c( -Inf, 120992604, 141510003), 908s + end = c(120992603, 141510002, +Inf) 908s + ) 908s > 908s > 908s > # Paired PSCBS segmentation 908s > fit <- segmentByPairedPSCBS(dataS, knownSegments=knownSegments, 908s + seed=0xBEEF, verbose=-10) 908s Segmenting paired tumor-normal signals using Paired PSCBS... 908s Calling genotypes from normal allele B fractions... 908s num [1:14670] 0.8274 0.5072 0.1671 0.1609 0.0421 ... 908s Called genotypes: 908s num [1:14670] 1 0.5 0 0 0 0 1 0 1 0.5 ... 908s - attr(*, "modelFit")=List of 1 908s ..$ :List of 7 908s .. ..$ flavor : chr "density" 908s .. ..$ cn : int 2 908s .. ..$ nbrOfGenotypeGroups: int 3 908s .. ..$ tau : num [1:2] 0.315 0.677 908s .. ..$ n : int 14640 908s .. ..$ fit :Classes ‘PeaksAndValleys’ and 'data.frame': 5 obs. of 3 variables: 908s .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 908s .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 908s .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 908s .. ..$ fitValleys :Classes ‘PeaksAndValleys’ and 'data.frame': 2 obs. of 3 variables: 908s .. .. ..$ type : chr [1:2] "valley" "valley" 908s .. .. ..$ x : num [1:2] 0.315 0.677 908s .. .. ..$ density: num [1:2] 0.522 0.551 908s ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 908s muN 908s 0 0.5 1 908s 5221 4198 5251 908s Calling genotypes from normal allele B fractions...done 908s Normalizing betaT using betaN (TumorBoost)... 908s Normalized BAFs: 908s num [1:14670] 0.9301 0.1667 0.0685 0.0995 0.0155 ... 908s - attr(*, "modelFit")=List of 5 908s ..$ method : chr "normalizeTumorBoost" 908s ..$ flavor : chr "v4" 908s ..$ delta : num [1:14670] -0.17264 0.00239 0.1671 0.16085 0.04213 ... 908s .. ..- attr(*, "modelFit")=List of 1 908s .. .. ..$ :List of 7 908s .. .. .. ..$ flavor : chr "density" 908s .. .. .. ..$ cn : int 2 908s .. .. .. ..$ nbrOfGenotypeGroups: int 3 908s .. .. .. ..$ tau : num [1:2] 0.315 0.677 908s .. .. .. ..$ n : int 14640 908s .. .. .. ..$ fit :Classes ‘PeaksAndValleys’ and 'data.frame': 5 obs. of 3 variables: 908s .. .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 908s .. .. .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 908s .. .. .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 908s .. .. .. ..$ fitValleys :Classes ‘PeaksAndValleys’ and 'data.frame': 2 obs. of 3 variables: 908s .. .. .. .. ..$ type : chr [1:2] "valley" "valley" 908s .. .. .. .. ..$ x : num [1:2] 0.315 0.677 908s .. .. .. .. ..$ density: num [1:2] 0.522 0.551 908s .. .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 908s ..$ preserveScale: logi FALSE 908s ..$ scaleFactor : num NA 908s Normalizing betaT using betaN (TumorBoost)...done 908s Setup up data... 908s 'data.frame': 14670 obs. of 7 variables: 908s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 908s $ x : num 1145994 2941694 3710825 4240737 4276892 ... 908s $ CT : num 1.63 1.4 1.41 1.17 1.16 ... 908s $ betaT : num 0.7574 0.169 0.2357 0.2604 0.0576 ... 908s $ betaTN : num 0.9301 0.1667 0.0685 0.0995 0.0155 ... 908s ..- attr(*, "modelFit")=List of 5 908s .. ..$ method : chr "normalizeTumorBoost" 908s .. ..$ flavor : chr "v4" 908s .. ..$ delta : num [1:14670] -0.17264 0.00239 0.1671 0.16085 0.04213 ... 908s .. .. ..- attr(*, "modelFit")=List of 1 908s .. .. .. ..$ :List of 7 908s .. .. .. .. ..$ flavor : chr "density" 908s .. .. .. .. ..$ cn : int 2 908s .. .. .. .. ..$ nbrOfGenotypeGroups: int 3 908s .. .. .. .. ..$ tau : num [1:2] 0.315 0.677 908s .. .. .. .. ..$ n : int 14640 908s .. .. .. .. ..$ fit :Classes ‘PeaksAndValleys’ and 'data.frame': 5 obs. of 3 variables: 908s .. .. .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 908s .. .. .. .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 908s .. .. .. .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 908s .. .. .. .. ..$ fitValleys :Classes ‘PeaksAndValleys’ and 'data.frame': 2 obs. of 3 variables: 908s .. .. .. .. .. ..$ type : chr [1:2] "valley" "valley" 908s .. .. .. .. .. ..$ x : num [1:2] 0.315 0.677 908s .. .. .. .. .. ..$ density: num [1:2] 0.522 0.551 908s .. .. .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 908s .. ..$ preserveScale: logi FALSE 908s .. ..$ scaleFactor : num NA 908s $ betaN : num 0.8274 0.5072 0.1671 0.1609 0.0421 ... 908s $ muN : num 1 0.5 0 0 0 0 1 0 1 0.5 ... 908s ..- attr(*, "modelFit")=List of 1 908s .. ..$ :List of 7 908s .. .. ..$ flavor : chr "density" 908s .. .. ..$ cn : int 2 908s .. .. ..$ nbrOfGenotypeGroups: int 3 908s .. .. ..$ tau : num [1:2] 0.315 0.677 908s .. .. ..$ n : int 14640 908s .. .. ..$ fit :Classes ‘PeaksAndValleys’ and 'data.frame': 5 obs. of 3 variables: 908s .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 908s .. .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 908s .. .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 908s .. .. ..$ fitValleys :Classes ‘PeaksAndValleys’ and 'data.frame': 2 obs. of 3 variables: 908s .. .. .. ..$ type : chr [1:2] "valley" "valley" 908s .. .. .. ..$ x : num [1:2] 0.315 0.677 908s .. .. .. ..$ density: num [1:2] 0.522 0.551 908s .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 908s Setup up data...done 908s Dropping loci for which TCNs are missing... 908s Number of loci dropped: 12 908s Dropping loci for which TCNs are missing...done 908s Ordering data along genome... 908s 'data.frame': 14658 obs. of 7 variables: 908s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 908s $ x : num 554484 730720 782343 878522 916294 ... 908s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 908s $ betaT : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 908s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 908s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 908s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 908s Ordering data along genome...done 908s Keeping only current chromosome for 'knownSegments'... 908s Chromosome: 1 908s Known segments for this chromosome: 908s chromosome start end 908s 1 1 -Inf 120992603 908s 2 1 120992604 141510002 908s 3 1 141510003 Inf 908s Keeping only current chromosome for 'knownSegments'...done 908s alphaTCN: 0.009 908s alphaDH: 0.001 908s Number of loci: 14658 908s Calculating DHs... 908s Number of SNPs: 14658 908s Number of heterozygous SNPs: 4196 (28.63%) 908s Normalized DHs: 908s num [1:14658] NA NA NA NA NA ... 908s Calculating DHs...done 908s Random seed temporarily set (seed=c(48879), kind="L'Ecuyer-CMRG") 908s Produced 2 seeds from this stream for future usage 908s Identification of change points by total copy numbers... 908s Segmenting by CBS... 908s Chromosome: 1 908s Segmenting multiple segments on current chromosome... 908s Number of segments: 3 908s Random seed temporarily set (seed=c(10407, 1066287653, -51199871, 161854402, -1995183193, 1503453565, -747102133), kind="L'Ecuyer-CMRG") 908s Produced 3 seeds from this stream for future usage 908s Segmenting by CBS... 908s Chromosome: 1 908s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 908s Segmenting by CBS...done 908s Segmenting by CBS... 908s Chromosome: 1 908s Random seed temporarily set (seed=c(10407, -1924040949, -1632234809, -437763632, -1464377300, 676654412, 2080370711), kind="L'Ecuyer-CMRG") 909s Segmenting by CBS...done 909s Segmenting multiple segments on current chromosome...done 909s Segmenting by CBS...done 909s List of 4 909s $ data :'data.frame': 14658 obs. of 4 variables: 909s ..$ chromosome: int [1:14658] 1 1 1 1 1 1 1 1 1 1 ... 909s ..$ x : num [1:14658] 554484 730720 782343 878522 916294 ... 909s ..$ y : num [1:14658] 1.88 1.8 1.59 1.64 1.53 ... 909s ..$ index : int [1:14658] 1 2 3 4 5 6 7 8 9 10 ... 909s $ output :'data.frame': 4 obs. of 6 variables: 909s ..$ sampleName: chr [1:4] NA NA NA NA 909s ..$ chromosome: num [1:4] 1 1 1 1 909s ..$ start : num [1:4] 5.54e+05 1.21e+08 1.42e+08 1.85e+08 909s ..$ end : num [1:4] 1.21e+08 1.42e+08 1.85e+08 2.47e+08 909s ..$ nbrOfLoci : int [1:4] 7586 0 2681 4391 909s ..$ mean : num [1:4] 1.39 NA 2.07 2.63 909s $ segRows:'data.frame': 4 obs. of 2 variables: 909s ..$ startRow: int [1:4] 1 NA 7587 10268 909s ..$ endRow : int [1:4] 7586 NA 10267 14658 909s $ params :List of 5 909s ..$ alpha : num 0.009 909s ..$ undo : num 0 909s ..$ joinSegments : logi TRUE 909s ..$ knownSegments:'data.frame': 4 obs. of 3 variables: 909s .. ..$ chromosome: num [1:4] 1 1 2 1 909s .. ..$ start : num [1:4] -Inf -Inf -Inf 1.42e+08 909s .. ..$ end : num [1:4] 1.21e+08 Inf Inf Inf 909s ..$ seed : int [1:7] 10407 1066287653 -51199871 161854402 -1995183193 1503453565 -747102133 909s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 909s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.129 0 0.129 0 0 909s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 909s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 909s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 909s Identification of change points by total copy numbers...done 909s Restructure TCN segmentation results... 909s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean 909s 1 1 554484 120992603 7586 1.3853 909s 2 1 120992604 141510002 0 NA 909s 3 1 141510003 185449813 2681 2.0689 909s 4 1 185449813 247137334 4391 2.6341 909s Number of TCN segments: 4 909s Restructure TCN segmentation results...done 909s Total CN segment #1 ([ 554484,1.20993e+08]) of 4... 909s Number of TCN loci in segment: 7586 909s Locus data for TCN segment: 909s 'data.frame': 7586 obs. of 9 variables: 909s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 909s $ x : num 554484 730720 782343 878522 916294 ... 909s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 909s $ betaT : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 909s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 909s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 909s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 909s $ index : int 1 2 3 4 5 6 7 8 9 10 ... 909s $ rho : num NA NA NA NA NA ... 909s Number of loci: 7586 909s Number of SNPs: 2108 (27.79%) 909s Number of heterozygous SNPs: 2108 (100.00%) 909s Chromosome: 1 909s Segmenting DH signals... 909s Segmenting by CBS... 909s Chromosome: 1 909s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 909s Segmenting by CBS...done 909s List of 4 909s $ data :'data.frame': 7586 obs. of 4 variables: 909s ..$ chromosome: int [1:7586] 1 1 1 1 1 1 1 1 1 1 ... 909s ..$ x : num [1:7586] 554484 730720 782343 878522 916294 ... 909s ..$ y : num [1:7586] NA NA NA NA NA ... 909s ..$ index : int [1:7586] 1 2 3 4 5 6 7 8 9 10 ... 909s $ output :'data.frame': 1 obs. of 6 variables: 909s ..$ sampleName: chr NA 909s ..$ chromosome: int 1 909s ..$ start : num 554484 909s ..$ end : num 1.21e+08 909s ..$ nbrOfLoci : int 2108 909s ..$ mean : num 0.512 909s $ segRows:'data.frame': 1 obs. of 2 variables: 909s ..$ startRow: int 10 909s ..$ endRow : int 7574 909s $ params :List of 5 909s ..$ alpha : num 0.001 909s ..$ undo : num 0 909s ..$ joinSegments : logi TRUE 909s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 909s .. ..$ chromosome: int 1 909s .. ..$ start : num 554484 909s .. ..$ end : num 1.21e+08 909s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 909s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 909s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.037 0 0.037 0 0 909s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 909s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 909s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 909s DH segmentation (locally-indexed) rows: 909s startRow endRow 909s 1 10 7574 909s int [1:7586] 1 2 3 4 5 6 7 8 9 10 ... 909s DH segmentation rows: 909s startRow endRow 909s 1 10 7574 909s Segmenting DH signals...done 909s DH segmentation table: 909s dhStart dhEnd dhNbrOfLoci dhMean 909s 1 554484 120992603 2108 0.5116 909s startRow endRow 909s 1 10 7574 909s Rows: 909s [1] 1 909s TCN segmentation rows: 909s startRow endRow 909s 1 1 7586 909s TCN and DH segmentation rows: 909s startRow endRow 909s 1 1 7586 909s startRow endRow 909s 1 10 7574 909s NULL 909s TCN segmentation (expanded) rows: 909s startRow endRow 909s 1 1 7586 909s TCN and DH segmentation rows: 909s startRow endRow 909s 1 1 7586 909s 2 NA NA 909s 3 7587 10267 909s 4 10268 14658 909s startRow endRow 909s 1 10 7574 909s startRow endRow 909s 1 1 7586 909s Total CN segmentation table (expanded): 909s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 909s 1 1 554484 120992603 7586 1.3853 2108 2108 909s (TCN,DH) segmentation for one total CN segment: 909s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 909s 1 1 1 1 554484 120992603 7586 1.3853 2108 909s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 909s 1 2108 554484 120992603 2108 0.5116 909s Total CN segment #1 ([ 554484,1.20993e+08]) of 4...done 909s Total CN segment #2 ([1.20993e+08,1.4151e+08]) of 4... 909s Number of TCN loci in segment: 0 909s Locus data for TCN segment: 909s 'data.frame': 0 obs. of 9 variables: 909s $ chromosome: int 909s $ x : num 909s $ CT : num 909s $ betaT : num 909s $ betaTN : num 909s $ betaN : num 909s $ muN : num 909s $ index : int 909s $ rho : num 909s Number of loci: 0 909s Number of SNPs: 0 (NaN%) 909s Number of heterozygous SNPs: 0 (NaN%) 909s Chromosome: 1 909s Segmenting DH signals... 909s Segmenting by CBS... 909s Chromosome: NA 909s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 909s Segmenting by CBS...done 909s List of 4 909s $ data :'data.frame': 0 obs. of 4 variables: 909s ..$ chromosome: int(0) 909s ..$ x : num(0) 909s ..$ y : num(0) 909s ..$ index : int(0) 909s $ output :'data.frame': 0 obs. of 6 variables: 909s ..$ sampleName: chr(0) 909s ..$ chromosome: num(0) 909s ..$ start : num(0) 909s ..$ end : num(0) 909s ..$ nbrOfLoci : int(0) 909s ..$ mean : num(0) 909s $ segRows:'data.frame': 0 obs. of 2 variables: 909s ..$ startRow: int(0) 909s ..$ endRow : int(0) 909s $ params :List of 5 909s ..$ alpha : num 0.001 909s ..$ undo : num 0 909s ..$ joinSegments : logi TRUE 909s ..$ knownSegments:'data.frame': 0 obs. of 3 variables: 909s .. ..$ chromosome: int(0) 909s .. ..$ start : num(0) 909s .. ..$ end : num(0) 909s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 909s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 909s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.002 0 0.002 0 0 909s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 909s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 909s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 909s DH segmentation (locally-indexed) rows: 909s [1] startRow endRow 909s <0 rows> (or 0-length row.names) 909s int(0) 909s DH segmentation rows: 909s [1] startRow endRow 909s <0 rows> (or 0-length row.names) 909s Segmenting DH signals...done 909s DH segmentation table: 909s dhStart dhEnd dhNbrOfLoci dhMean 909s NA NA NA NA NA 909s startRow endRow 909s NA NA NA 909s Rows: 909s [1] 2 909s TCN segmentation rows: 909s startRow endRow 909s 2 NA NA 909s TCN and DH segmentation rows: 909s startRow endRow 909s 2 NA NA 909s startRow endRow 909s NA NA NA 909s startRow endRow 909s 1 1 7586 909s TCN segmentation (expanded) rows: 909s startRow endRow 909s 1 1 7586 909s 2 NA NA 909s TCN and DH segmentation rows: 909s startRow endRow 909s 1 1 7586 909s 2 NA NA 909s 3 7587 10267 909s 4 10268 14658 909s startRow endRow 909s 1 10 7574 909s 2 NA NA 909s startRow endRow 909s 1 1 7586 909s 2 NA NA 909s Total CN segmentation table (expanded): 909s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 909s 2 1 120992604 141510002 0 NA 0 0 909s (TCN,DH) segmentation for one total CN segment: 909s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 909s 2 2 1 1 120992604 141510002 0 NA 0 909s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 909s 2 0 NA NA NA NA 909s Total CN segment #2 ([1.20993e+08,1.4151e+08]) of 4...done 909s Total CN segment #3 ([1.4151e+08,1.8545e+08]) of 4... 909s Number of TCN loci in segment: 2681 909s Locus data for TCN segment: 909s 'data.frame': 2681 obs. of 9 variables: 909s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 909s $ x : num 1.43e+08 1.43e+08 1.43e+08 1.43e+08 1.44e+08 ... 909s $ CT : num 2.27 1.55 1.47 1.5 1.81 ... 909s $ betaT : num 0.34 0.55 0.048 0.813 0.575 ... 909s $ betaTN : num 0.441 0.629 -0.05 0.958 0.872 ... 909s $ betaN : num 0.3851 0.3933 0.0981 0.8552 0.7028 ... 909s $ muN : num 0.5 0.5 0 1 1 1 1 0.5 1 1 ... 909s $ index : int 7587 7588 7589 7590 7591 7592 7593 7594 7595 7596 ... 909s $ rho : num 0.117 0.258 NA NA NA ... 909s Number of loci: 2681 909s Number of SNPs: 777 (28.98%) 909s Number of heterozygous SNPs: 777 (100.00%) 909s Chromosome: 1 909s Segmenting DH signals... 909s Segmenting by CBS... 909s Chromosome: 1 909s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 909s Segmenting by CBS...done 909s List of 4 909s $ data :'data.frame': 2681 obs. of 4 variables: 909s ..$ chromosome: int [1:2681] 1 1 1 1 1 1 1 1 1 1 ... 909s ..$ x : num [1:2681] 1.43e+08 1.43e+08 1.43e+08 1.43e+08 1.44e+08 ... 909s ..$ y : num [1:2681] 0.117 0.258 NA NA NA ... 909s ..$ index : int [1:2681] 1 2 3 4 5 6 7 8 9 10 ... 909s $ output :'data.frame': 1 obs. of 6 variables: 909s ..$ sampleName: chr NA 909s ..$ chromosome: int 1 909s ..$ start : num 1.42e+08 909s ..$ end : num 1.85e+08 909s ..$ nbrOfLoci : int 777 909s ..$ mean : num 0.0973 909s $ segRows:'data.frame': 1 obs. of 2 variables: 909s ..$ startRow: int 1 909s ..$ endRow : int 2677 909s $ params :List of 5 909s ..$ alpha : num 0.001 909s ..$ undo : num 0 909s ..$ joinSegments : logi TRUE 909s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 909s .. ..$ chromosome: int 1 909s .. ..$ start : num 1.42e+08 909s .. ..$ end : num 1.85e+08 909s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 909s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 909s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.009 0 0.008 0 0 909s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 909s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 909s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 909s DH segmentation (locally-indexed) rows: 909s startRow endRow 909s 1 1 2677 909s int [1:2681] 7587 7588 7589 7590 7591 7592 7593 7594 7595 7596 ... 909s DH segmentation rows: 909s startRow endRow 909s 1 7587 10263 909s Segmenting DH signals...done 909s DH segmentation table: 909s dhStart dhEnd dhNbrOfLoci dhMean 909s 1 141510003 185449813 777 0.0973 909s startRow endRow 909s 1 7587 10263 909s Rows: 909s [1] 3 909s TCN segmentation rows: 909s startRow endRow 909s 3 7587 10267 909s TCN and DH segmentation rows: 909s startRow endRow 909s 3 7587 10267 909s startRow endRow 909s 1 7587 10263 909s startRow endRow 909s 1 1 7586 909s 2 NA NA 909s TCN segmentation (expanded) rows: 909s startRow endRow 909s 1 1 7586 909s 2 NA NA 909s 3 7587 10267 909s TCN and DH segmentation rows: 909s startRow endRow 909s 1 1 7586 909s 2 NA NA 909s 3 7587 10267 909s 4 10268 14658 909s startRow endRow 909s 1 10 7574 909s 2 NA NA 909s 3 7587 10263 909s startRow endRow 909s 1 1 7586 909s 2 NA NA 909s 3 7587 10267 909s Total CN segmentation table (expanded): 909s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 909s 3 1 141510003 185449813 2681 2.0689 777 777 909s (TCN,DH) segmentation for one total CN segment: 909s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 909s 3 3 1 1 141510003 185449813 2681 2.0689 777 909s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 909s 3 777 141510003 185449813 777 0.0973 909s Total CN segment #3 ([1.4151e+08,1.8545e+08]) of 4...done 909s Total CN segment #4 ([1.8545e+08,2.47137e+08]) of 4... 909s Number of TCN loci in segment: 4391 909s Locus data for TCN segment: 909s 'data.frame': 4391 obs. of 9 variables: 909s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 909s $ x : num 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 909s $ CT : num 2.93 2.15 2.82 2.93 2.46 ... 909s $ betaT : num 0.0811 0.5154 0.9473 0.3734 0.7506 ... 909s $ betaTN : num -0.169 0.609 1.028 0.525 0.968 ... 909s $ betaN : num 0.25 0.38 0.919 0.34 0.783 ... 909s $ muN : num 0 0.5 1 0.5 1 1 0 1 0 1 ... 909s $ index : int 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 909s $ rho : num NA 0.2186 NA 0.0503 NA ... 909s Number of loci: 4391 909s Number of SNPs: 1311 (29.86%) 909s Number of heterozygous SNPs: 1311 (100.00%) 909s Chromosome: 1 909s Segmenting DH signals... 909s Segmenting by CBS... 909s Chromosome: 1 909s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 909s Segmenting by CBS...done 909s List of 4 909s $ data :'data.frame': 4391 obs. of 4 variables: 909s ..$ chromosome: int [1:4391] 1 1 1 1 1 1 1 1 1 1 ... 909s ..$ x : num [1:4391] 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 909s ..$ y : num [1:4391] NA 0.2186 NA 0.0503 NA ... 909s ..$ index : int [1:4391] 1 2 3 4 5 6 7 8 9 10 ... 909s $ output :'data.frame': 1 obs. of 6 variables: 909s ..$ sampleName: chr NA 909s ..$ chromosome: int 1 909s ..$ start : num 1.85e+08 909s ..$ end : num 2.47e+08 909s ..$ nbrOfLoci : int 1311 909s ..$ mean : num 0.23 909s $ segRows:'data.frame': 1 obs. of 2 variables: 909s ..$ startRow: int 2 909s ..$ endRow : int 4388 909s $ params :List of 5 909s ..$ alpha : num 0.001 909s ..$ undo : num 0 909s ..$ joinSegments : logi TRUE 909s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 909s .. ..$ chromosome: int 1 909s .. ..$ start : num 1.85e+08 909s .. ..$ end : num 2.47e+08 909s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 909s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 909s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.015 0 0.015 0 0 909s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 909s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 909s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 909s DH segmentation (locally-indexed) rows: 909s startRow endRow 909s 1 2 4388 909s int [1:4391] 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 909s DH segmentation rows: 909s startRow endRow 909s 1 10269 14655 909s Segmenting DH signals...done 909s DH segmentation table: 909s dhStart dhEnd dhNbrOfLoci dhMean 909s 1 185449813 247137334 1311 0.2295 909s startRow endRow 909s 1 10269 14655 909s Rows: 909s [1] 4 909s TCN segmentation rows: 909s startRow endRow 909s 4 10268 14658 909s TCN and DH segmentation rows: 909s startRow endRow 909s 4 10268 14658 909s startRow endRow 909s 1 10269 14655 909s startRow endRow 909s 1 1 7586 909s 2 NA NA 909s 3 7587 10267 909s TCN segmentation (expanded) rows: 909s startRow endRow 909s 1 1 7586 909s 2 NA NA 909s 3 7587 10267 909s 4 10268 14658 909s TCN and DH segmentation rows: 909s startRow endRow 909s 1 1 7586 909s 2 NA NA 909s 3 7587 10267 909s 4 10268 14658 909s startRow endRow 909s 1 10 7574 909s 2 NA NA 909s 3 7587 10263 909s 4 10269 14655 909s startRow endRow 909s 1 1 7586 909s 2 NA NA 909s 3 7587 10267 909s 4 10268 14658 909s Total CN segmentation table (expanded): 909s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 909s 4 1 185449813 247137334 4391 2.6341 1311 1311 909s (TCN,DH) segmentation for one total CN segment: 909s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 909s 4 4 1 1 185449813 247137334 4391 2.6341 1311 909s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 909s 4 1311 185449813 247137334 1311 0.2295 909s Total CN segment #4 ([1.8545e+08,2.47137e+08]) of 4...done 909s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 909s 1 1 1 1 554484 120992603 7586 1.3853 2108 909s 2 1 2 1 120992604 141510002 0 NA 0 909s 3 1 3 1 141510003 185449813 2681 2.0689 777 909s 4 1 4 1 185449813 247137334 4391 2.6341 1311 909s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 909s 1 2108 554484 120992603 2108 0.5116 909s 2 0 NA NA NA NA 909s 3 777 141510003 185449813 777 0.0973 909s 4 1311 185449813 247137334 1311 0.2295 909s Calculating (C1,C2) per segment... 909s Calculating (C1,C2) per segment...done 909s Number of segments: 4 909s Segmenting paired tumor-normal signals using Paired PSCBS...done 909s Post-segmenting TCNs... 909s Number of segments: 4 909s Number of chromosomes: 1 909s [1] 1 909s Chromosome 1 ('chr01') of 1... 909s Rows: 909s [1] 1 2 3 4 909s Number of segments: 4 909s TCN segment #1 ('1') of 4... 909s Nothing todo. Only one DH segmentation. Skipping. 909s TCN segment #1 ('1') of 4...done 909s TCN segment #2 ('2') of 4... 909s Nothing todo. Only one DH segmentation. Skipping. 909s TCN segment #2 ('2') of 4...done 909s TCN segment #3 ('3') of 4... 909s Nothing todo. Only one DH segmentation. Skipping. 909s TCN segment #3 ('3') of 4...done 909s TCN segment #4 ('4') of 4... 909s Nothing todo. Only one DH segmentation. Skipping. 909s TCN segment #4 ('4') of 4...done 909s Chromosome 1 ('chr01') of 1...done 909s Update (C1,C2) per segment... 909s Update (C1,C2) per segment...done 909s Post-segmenting TCNs...done 909s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 909s 1 1 1 1 554484 120992603 7586 1.3853 2108 909s 2 1 2 1 120992604 141510002 0 NA 0 909s 3 1 3 1 141510003 185449813 2681 2.0689 777 909s 4 1 4 1 185449813 247137334 4391 2.6341 1311 909s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 909s 1 2108 554484 120992603 2108 0.5116 0.3382903 1.047010 909s 2 0 NA NA NA NA NA NA 909s 3 777 141510003 185449813 777 0.0973 0.9337980 1.135102 909s 4 1311 185449813 247137334 1311 0.2295 1.0147870 1.619313 909s > print(fit) 909s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 909s 1 1 1 1 554484 120992603 7586 1.3853 2108 909s 2 1 2 1 120992604 141510002 0 NA 0 909s 3 1 3 1 141510003 185449813 2681 2.0689 777 909s 4 1 4 1 185449813 247137334 4391 2.6341 1311 909s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 909s 1 2108 554484 120992603 2108 0.5116 0.3382903 1.047010 909s 2 0 NA NA NA NA NA NA 909s 3 777 141510003 185449813 777 0.0973 0.9337980 1.135102 909s 4 1311 185449813 247137334 1311 0.2295 1.0147870 1.619313 909s chromosome tcnId dhId start end tcnNbrOfLoci tcnMean tcnNbrOfSNPs 909s 1 1 1 1 554484 120992603 7586 1.3853 2108 909s 2 1 2 1 120992604 141510002 0 NA 0 909s 3 1 3 1 141510003 185449813 2681 2.0689 777 909s 4 1 4 1 185449813 247137334 4391 2.6341 1311 909s tcnNbrOfHets dhNbrOfLoci dhMean c1Mean c2Mean 909s 1 2108 2108 0.5116 0.3382903 1.047010 909s 2 0 NA NA NA NA 909s 3 777 777 0.0973 0.9337980 1.135102 909s 4 1311 1311 0.2295 1.0147870 1.619313 909s > 909s > # Plot results 909s > dev.set(3L) 909s pdf 909s 2 909s > plotTracks(fit) 909s > abline(v=c(knownSegments$start, knownSegments$end)/1e6, lty=3) 909s > 909s > # Sanity check [TO FIX: See above] 909s > stopifnot(nbrOfSegments(fit) == nSegs) 909s > 909s > fit2 <- fit 909s > 909s > 909s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 909s > # (c) Do not segment the centromere (without a separator) 909s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 909s > knownSegments <- data.frame( 909s + chromosome = c( 1, 1), 909s + start = c( -Inf, 141510003), 909s + end = c(120992603, +Inf) 909s + ) 909s > 909s > # Paired PSCBS segmentation 909s > fit <- segmentByPairedPSCBS(dataS, knownSegments=knownSegments, 909s + seed=0xBEEF, verbose=-10) 909s Segmenting paired tumor-normal signals using Paired PSCBS... 909s Calling genotypes from normal allele B fractions... 909s num [1:14670] 0.8274 0.5072 0.1671 0.1609 0.0421 ... 909s Called genotypes: 909s num [1:14670] 1 0.5 0 0 0 0 1 0 1 0.5 ... 909s - attr(*, "modelFit")=List of 1 909s ..$ :List of 7 909s .. ..$ flavor : chr "density" 909s .. ..$ cn : int 2 909s .. ..$ nbrOfGenotypeGroups: int 3 909s .. ..$ tau : num [1:2] 0.315 0.677 909s .. ..$ n : int 14640 909s .. ..$ fit :Classes ‘PeaksAndValleys’ and 'data.frame': 5 obs. of 3 variables: 909s .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 909s .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 909s .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 909s .. ..$ fitValleys :Classes ‘PeaksAndValleys’ and 'data.frame': 2 obs. of 3 variables: 909s .. .. ..$ type : chr [1:2] "valley" "valley" 909s .. .. ..$ x : num [1:2] 0.315 0.677 909s .. .. ..$ density: num [1:2] 0.522 0.551 909s ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 909s muN 909s 0 0.5 1 909s 5221 4198 5251 909s Calling genotypes from normal allele B fractions...done 909s Normalizing betaT using betaN (TumorBoost)... 909s Normalized BAFs: 909s num [1:14670] 0.9301 0.1667 0.0685 0.0995 0.0155 ... 909s - attr(*, "modelFit")=List of 5 909s ..$ method : chr "normalizeTumorBoost" 909s ..$ flavor : chr "v4" 909s ..$ delta : num [1:14670] -0.17264 0.00239 0.1671 0.16085 0.04213 ... 909s .. ..- attr(*, "modelFit")=List of 1 909s .. .. ..$ :List of 7 909s .. .. .. ..$ flavor : chr "density" 909s .. .. .. ..$ cn : int 2 909s .. .. .. ..$ nbrOfGenotypeGroups: int 3 909s .. .. .. ..$ tau : num [1:2] 0.315 0.677 909s .. .. .. ..$ n : int 14640 909s .. .. .. ..$ fit :Classes ‘PeaksAndValleys’ and 'data.frame': 5 obs. of 3 variables: 909s .. .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 909s .. .. .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 909s .. .. .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 909s .. .. .. ..$ fitValleys :Classes ‘PeaksAndValleys’ and 'data.frame': 2 obs. of 3 variables: 909s .. .. .. .. ..$ type : chr [1:2] "valley" "valley" 909s .. .. .. .. ..$ x : num [1:2] 0.315 0.677 909s .. .. .. .. ..$ density: num [1:2] 0.522 0.551 909s .. .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 909s ..$ preserveScale: logi FALSE 909s ..$ scaleFactor : num NA 909s Normalizing betaT using betaN (TumorBoost)...done 909s Setup up data... 909s 'data.frame': 14670 obs. of 7 variables: 909s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 909s $ x : num 1145994 2941694 3710825 4240737 4276892 ... 909s $ CT : num 1.63 1.4 1.41 1.17 1.16 ... 909s $ betaT : num 0.7574 0.169 0.2357 0.2604 0.0576 ... 909s $ betaTN : num 0.9301 0.1667 0.0685 0.0995 0.0155 ... 909s ..- attr(*, "modelFit")=List of 5 909s .. ..$ method : chr "normalizeTumorBoost" 909s .. ..$ flavor : chr "v4" 909s .. ..$ delta : num [1:14670] -0.17264 0.00239 0.1671 0.16085 0.04213 ... 909s .. .. ..- attr(*, "modelFit")=List of 1 909s .. .. .. ..$ :List of 7 909s .. .. .. .. ..$ flavor : chr "density" 909s .. .. .. .. ..$ cn : int 2 909s .. .. .. .. ..$ nbrOfGenotypeGroups: int 3 909s .. .. .. .. ..$ tau : num [1:2] 0.315 0.677 909s .. .. .. .. ..$ n : int 14640 909s .. .. .. .. ..$ fit :Classes ‘PeaksAndValleys’ and 'data.frame': 5 obs. of 3 variables: 909s .. .. .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 909s .. .. .. .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 909s .. .. .. .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 909s .. .. .. .. ..$ fitValleys :Classes ‘PeaksAndValleys’ and 'data.frame': 2 obs. of 3 variables: 909s .. .. .. .. .. ..$ type : chr [1:2] "valley" "valley" 909s .. .. .. .. .. ..$ x : num [1:2] 0.315 0.677 909s .. .. .. .. .. ..$ density: num [1:2] 0.522 0.551 909s .. .. .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 909s .. ..$ preserveScale: logi FALSE 909s .. ..$ scaleFactor : num NA 909s $ betaN : num 0.8274 0.5072 0.1671 0.1609 0.0421 ... 909s $ muN : num 1 0.5 0 0 0 0 1 0 1 0.5 ... 909s ..- attr(*, "modelFit")=List of 1 909s .. ..$ :List of 7 909s .. .. ..$ flavor : chr "density" 909s .. .. ..$ cn : int 2 909s .. .. ..$ nbrOfGenotypeGroups: int 3 909s .. .. ..$ tau : num [1:2] 0.315 0.677 909s .. .. ..$ n : int 14640 909s .. .. ..$ fit :Classes ‘PeaksAndValleys’ and 'data.frame': 5 obs. of 3 variables: 909s .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 909s .. .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 909s .. .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 909s .. .. ..$ fitValleys :Classes ‘PeaksAndValleys’ and 'data.frame': 2 obs. of 3 variables: 909s .. .. .. ..$ type : chr [1:2] "valley" "valley" 909s .. .. .. ..$ x : num [1:2] 0.315 0.677 909s .. .. .. ..$ density: num [1:2] 0.522 0.551 909s .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 909s Setup up data...done 909s Dropping loci for which TCNs are missing... 909s Number of loci dropped: 12 909s Dropping loci for which TCNs are missing...done 909s Ordering data along genome... 909s 'data.frame': 14658 obs. of 7 variables: 909s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 909s $ x : num 554484 730720 782343 878522 916294 ... 909s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 909s $ betaT : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 909s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 909s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 909s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 909s Ordering data along genome...done 909s Keeping only current chromosome for 'knownSegments'... 909s Chromosome: 1 909s Known segments for this chromosome: 909s chromosome start end 909s 1 1 -Inf 120992603 909s 2 1 141510003 Inf 909s Keeping only current chromosome for 'knownSegments'...done 909s alphaTCN: 0.009 909s alphaDH: 0.001 909s Number of loci: 14658 909s Calculating DHs... 909s Number of SNPs: 14658 909s Number of heterozygous SNPs: 4196 (28.63%) 909s Normalized DHs: 909s num [1:14658] NA NA NA NA NA ... 909s Calculating DHs...done 909s Random seed temporarily set (seed=c(48879), kind="L'Ecuyer-CMRG") 909s Produced 2 seeds from this stream for future usage 909s Identification of change points by total copy numbers... 909s Segmenting by CBS... 909s Chromosome: 1 909s Segmenting multiple segments on current chromosome... 909s Number of segments: 2 909s Random seed temporarily set (seed=c(10407, 1066287653, -51199871, 161854402, -1995183193, 1503453565, -747102133), kind="L'Ecuyer-CMRG") 909s Produced 2 seeds from this stream for future usage 909s Segmenting by CBS... 909s Chromosome: 1 909s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 910s Segmenting by CBS...done 910s Segmenting by CBS... 910s Chromosome: 1 910s Random seed temporarily set (seed=c(10407, -821273412, -52578226, 1415511586, 721384351, -665928286, 1316562960), kind="L'Ecuyer-CMRG") 910s Segmenting by CBS...done 910s Segmenting multiple segments on current chromosome...done 910s Segmenting by CBS...done 910s List of 4 910s $ data :'data.frame': 14658 obs. of 4 variables: 910s ..$ chromosome: int [1:14658] 1 1 1 1 1 1 1 1 1 1 ... 910s ..$ x : num [1:14658] 554484 730720 782343 878522 916294 ... 910s ..$ y : num [1:14658] 1.88 1.8 1.59 1.64 1.53 ... 910s ..$ index : int [1:14658] 1 2 3 4 5 6 7 8 9 10 ... 910s $ output :'data.frame': 3 obs. of 6 variables: 910s ..$ sampleName: chr [1:3] NA NA NA 910s ..$ chromosome: int [1:3] 1 1 1 910s ..$ start : num [1:3] 5.54e+05 1.42e+08 1.85e+08 910s ..$ end : num [1:3] 1.21e+08 1.85e+08 2.47e+08 910s ..$ nbrOfLoci : int [1:3] 7586 2681 4391 910s ..$ mean : num [1:3] 1.39 2.07 2.63 910s $ segRows:'data.frame': 3 obs. of 2 variables: 910s ..$ startRow: int [1:3] 1 7587 10268 910s ..$ endRow : int [1:3] 7586 10267 14658 910s $ params :List of 5 910s ..$ alpha : num 0.009 910s ..$ undo : num 0 910s ..$ joinSegments : logi TRUE 910s ..$ knownSegments:'data.frame': 2 obs. of 3 variables: 910s .. ..$ chromosome: num [1:2] 1 1 910s .. ..$ start : num [1:2] -Inf 1.42e+08 910s .. ..$ end : num [1:2] 1.21e+08 Inf 910s ..$ seed : int [1:7] 10407 1066287653 -51199871 161854402 -1995183193 1503453565 -747102133 910s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 910s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.128 0 0.128 0 0 910s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 910s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 910s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 910s Identification of change points by total copy numbers...done 910s Restructure TCN segmentation results... 910s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean 910s 1 1 554484 120992603 7586 1.3853 910s 2 1 141510003 185449813 2681 2.0689 910s 3 1 185449813 247137334 4391 2.6341 910s Number of TCN segments: 3 910s Restructure TCN segmentation results...done 910s Total CN segment #1 ([ 554484,1.20993e+08]) of 3... 910s Number of TCN loci in segment: 7586 910s Locus data for TCN segment: 910s 'data.frame': 7586 obs. of 9 variables: 910s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 910s $ x : num 554484 730720 782343 878522 916294 ... 910s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 910s $ betaT : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 910s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 910s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 910s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 910s $ index : int 1 2 3 4 5 6 7 8 9 10 ... 910s $ rho : num NA NA NA NA NA ... 910s Number of loci: 7586 910s Number of SNPs: 2108 (27.79%) 910s Number of heterozygous SNPs: 2108 (100.00%) 910s Chromosome: 1 910s Segmenting DH signals... 910s Segmenting by CBS... 910s Chromosome: 1 910s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 910s Segmenting by CBS...done 910s List of 4 910s $ data :'data.frame': 7586 obs. of 4 variables: 910s ..$ chromosome: int [1:7586] 1 1 1 1 1 1 1 1 1 1 ... 910s ..$ x : num [1:7586] 554484 730720 782343 878522 916294 ... 910s ..$ y : num [1:7586] NA NA NA NA NA ... 910s ..$ index : int [1:7586] 1 2 3 4 5 6 7 8 9 10 ... 910s $ output :'data.frame': 1 obs. of 6 variables: 910s ..$ sampleName: chr NA 910s ..$ chromosome: int 1 910s ..$ start : num 554484 910s ..$ end : num 1.21e+08 910s ..$ nbrOfLoci : int 2108 910s ..$ mean : num 0.512 910s $ segRows:'data.frame': 1 obs. of 2 variables: 910s ..$ startRow: int 10 910s ..$ endRow : int 7574 910s $ params :List of 5 910s ..$ alpha : num 0.001 910s ..$ undo : num 0 910s ..$ joinSegments : logi TRUE 910s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 910s .. ..$ chromosome: int 1 910s .. ..$ start : num 554484 910s .. ..$ end : num 1.21e+08 910s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 910s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 910s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.036 0.001 0.038 0 0 910s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 910s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 910s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 910s DH segmentation (locally-indexed) rows: 910s startRow endRow 910s 1 10 7574 910s int [1:7586] 1 2 3 4 5 6 7 8 9 10 ... 910s DH segmentation rows: 910s startRow endRow 910s 1 10 7574 910s Segmenting DH signals...done 910s DH segmentation table: 910s dhStart dhEnd dhNbrOfLoci dhMean 910s 1 554484 120992603 2108 0.5116 910s startRow endRow 910s 1 10 7574 910s Rows: 910s [1] 1 910s TCN segmentation rows: 910s startRow endRow 910s 1 1 7586 910s TCN and DH segmentation rows: 910s startRow endRow 910s 1 1 7586 910s startRow endRow 910s 1 10 7574 910s NULL 910s TCN segmentation (expanded) rows: 910s startRow endRow 910s 1 1 7586 910s TCN and DH segmentation rows: 910s startRow endRow 910s 1 1 7586 910s 2 7587 10267 910s 3 10268 14658 910s startRow endRow 910s 1 10 7574 910s startRow endRow 910s 1 1 7586 910s Total CN segmentation table (expanded): 910s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 910s 1 1 554484 120992603 7586 1.3853 2108 2108 910s (TCN,DH) segmentation for one total CN segment: 910s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 910s 1 1 1 1 554484 120992603 7586 1.3853 2108 910s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 910s 1 2108 554484 120992603 2108 0.5116 910s Total CN segment #1 ([ 554484,1.20993e+08]) of 3...done 910s Total CN segment #2 ([1.4151e+08,1.8545e+08]) of 3... 910s Number of TCN loci in segment: 2681 910s Locus data for TCN segment: 910s 'data.frame': 2681 obs. of 9 variables: 910s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 910s $ x : num 1.43e+08 1.43e+08 1.43e+08 1.43e+08 1.44e+08 ... 910s $ CT : num 2.27 1.55 1.47 1.5 1.81 ... 910s $ betaT : num 0.34 0.55 0.048 0.813 0.575 ... 910s $ betaTN : num 0.441 0.629 -0.05 0.958 0.872 ... 910s $ betaN : num 0.3851 0.3933 0.0981 0.8552 0.7028 ... 910s $ muN : num 0.5 0.5 0 1 1 1 1 0.5 1 1 ... 910s $ index : int 7587 7588 7589 7590 7591 7592 7593 7594 7595 7596 ... 910s $ rho : num 0.117 0.258 NA NA NA ... 910s Number of loci: 2681 910s Number of SNPs: 777 (28.98%) 910s Number of heterozygous SNPs: 777 (100.00%) 910s Chromosome: 1 910s Segmenting DH signals... 910s Segmenting by CBS... 910s Chromosome: 1 910s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 910s Segmenting by CBS...done 910s List of 4 910s $ data :'data.frame': 2681 obs. of 4 variables: 910s ..$ chromosome: int [1:2681] 1 1 1 1 1 1 1 1 1 1 ... 910s ..$ x : num [1:2681] 1.43e+08 1.43e+08 1.43e+08 1.43e+08 1.44e+08 ... 910s ..$ y : num [1:2681] 0.117 0.258 NA NA NA ... 910s ..$ index : int [1:2681] 1 2 3 4 5 6 7 8 9 10 ... 910s $ output :'data.frame': 1 obs. of 6 variables: 910s ..$ sampleName: chr NA 910s ..$ chromosome: int 1 910s ..$ start : num 1.42e+08 910s ..$ end : num 1.85e+08 910s ..$ nbrOfLoci : int 777 910s ..$ mean : num 0.0973 910s $ segRows:'data.frame': 1 obs. of 2 variables: 910s ..$ startRow: int 1 910s ..$ endRow : int 2677 910s $ params :List of 5 910s ..$ alpha : num 0.001 910s ..$ undo : num 0 910s ..$ joinSegments : logi TRUE 910s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 910s .. ..$ chromosome: int 1 910s .. ..$ start : num 1.42e+08 910s .. ..$ end : num 1.85e+08 910s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 910s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 910s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.008 0 0.008 0 0 910s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 910s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 910s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 910s DH segmentation (locally-indexed) rows: 910s startRow endRow 910s 1 1 2677 910s int [1:2681] 7587 7588 7589 7590 7591 7592 7593 7594 7595 7596 ... 910s DH segmentation rows: 910s startRow endRow 910s 1 7587 10263 910s Segmenting DH signals...done 910s DH segmentation table: 910s dhStart dhEnd dhNbrOfLoci dhMean 910s 1 141510003 185449813 777 0.0973 910s startRow endRow 910s 1 7587 10263 910s Rows: 910s [1] 2 910s TCN segmentation rows: 910s startRow endRow 910s 2 7587 10267 910s TCN and DH segmentation rows: 910s startRow endRow 910s 2 7587 10267 910s startRow endRow 910s 1 7587 10263 910s startRow endRow 910s 1 1 7586 910s TCN segmentation (expanded) rows: 910s startRow endRow 910s 1 1 7586 910s 2 7587 10267 910s TCN and DH segmentation rows: 910s startRow endRow 910s 1 1 7586 910s 2 7587 10267 910s 3 10268 14658 910s startRow endRow 910s 1 10 7574 910s 2 7587 10263 910s startRow endRow 910s 1 1 7586 910s 2 7587 10267 910s Total CN segmentation table (expanded): 910s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 910s 2 1 141510003 185449813 2681 2.0689 777 777 910s (TCN,DH) segmentation for one total CN segment: 910s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 910s 2 2 1 1 141510003 185449813 2681 2.0689 777 910s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 910s 2 777 141510003 185449813 777 0.0973 910s Total CN segment #2 ([1.4151e+08,1.8545e+08]) of 3...done 910s Total CN segment #3 ([1.8545e+08,2.47137e+08]) of 3... 910s Number of TCN loci in segment: 4391 910s Locus data for TCN segment: 910s 'data.frame': 4391 obs. of 9 variables: 910s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 910s $ x : num 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 910s $ CT : num 2.93 2.15 2.82 2.93 2.46 ... 910s $ betaT : num 0.0811 0.5154 0.9473 0.3734 0.7506 ... 910s $ betaTN : num -0.169 0.609 1.028 0.525 0.968 ... 910s $ betaN : num 0.25 0.38 0.919 0.34 0.783 ... 910s $ muN : num 0 0.5 1 0.5 1 1 0 1 0 1 ... 910s $ index : int 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 910s $ rho : num NA 0.2186 NA 0.0503 NA ... 910s Number of loci: 4391 910s Number of SNPs: 1311 (29.86%) 910s Number of heterozygous SNPs: 1311 (100.00%) 910s Chromosome: 1 910s Segmenting DH signals... 910s Segmenting by CBS... 910s Chromosome: 1 910s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 910s Segmenting by CBS...done 910s List of 4 910s $ data :'data.frame': 4391 obs. of 4 variables: 910s ..$ chromosome: int [1:4391] 1 1 1 1 1 1 1 1 1 1 ... 910s ..$ x : num [1:4391] 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 910s ..$ y : num [1:4391] NA 0.2186 NA 0.0503 NA ... 910s ..$ index : int [1:4391] 1 2 3 4 5 6 7 8 9 10 ... 910s $ output :'data.frame': 1 obs. of 6 variables: 910s ..$ sampleName: chr NA 910s ..$ chromosome: int 1 910s ..$ start : num 1.85e+08 910s ..$ end : num 2.47e+08 910s ..$ nbrOfLoci : int 1311 910s ..$ mean : num 0.23 910s $ segRows:'data.frame': 1 obs. of 2 variables: 910s ..$ startRow: int 2 910s ..$ endRow : int 4388 910s $ params :List of 5 910s ..$ alpha : num 0.001 910s ..$ undo : num 0 910s ..$ joinSegments : logi TRUE 910s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 910s .. ..$ chromosome: int 1 910s .. ..$ start : num 1.85e+08 910s .. ..$ end : num 2.47e+08 910s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 910s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 910s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.015 0 0.015 0 0 910s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 910s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 910s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 910s DH segmentation (locally-indexed) rows: 910s startRow endRow 910s 1 2 4388 910s int [1:4391] 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 910s DH segmentation rows: 910s startRow endRow 910s 1 10269 14655 910s Segmenting DH signals...done 910s DH segmentation table: 910s dhStart dhEnd dhNbrOfLoci dhMean 910s 1 185449813 247137334 1311 0.2295 910s startRow endRow 910s 1 10269 14655 910s Rows: 910s [1] 3 910s TCN segmentation rows: 910s startRow endRow 910s 3 10268 14658 910s TCN and DH segmentation rows: 910s startRow endRow 910s 3 10268 14658 910s startRow endRow 910s 1 10269 14655 910s startRow endRow 910s 1 1 7586 910s 2 7587 10267 910s TCN segmentation (expanded) rows: 910s startRow endRow 910s 1 1 7586 910s 2 7587 10267 910s 3 10268 14658 910s TCN and DH segmentation rows: 910s startRow endRow 910s 1 1 7586 910s 2 7587 10267 910s 3 10268 14658 910s startRow endRow 910s 1 10 7574 910s 2 7587 10263 910s 3 10269 14655 910s startRow endRow 910s 1 1 7586 910s 2 7587 10267 910s 3 10268 14658 910s Total CN segmentation table (expanded): 910s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 910s 3 1 185449813 247137334 4391 2.6341 1311 1311 910s (TCN,DH) segmentation for one total CN segment: 910s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 910s 3 3 1 1 185449813 247137334 4391 2.6341 1311 910s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 910s 3 1311 185449813 247137334 1311 0.2295 910s Total CN segment #3 ([1.8545e+08,2.47137e+08]) of 3...done 910s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 910s 1 1 1 1 554484 120992603 7586 1.3853 2108 910s 2 1 2 1 141510003 185449813 2681 2.0689 777 910s 3 1 3 1 185449813 247137334 4391 2.6341 1311 910s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 910s 1 2108 554484 120992603 2108 0.5116 910s 2 777 141510003 185449813 777 0.0973 910s 3 1311 185449813 247137334 1311 0.2295 910s Calculating (C1,C2) per segment... 910s Calculating (C1,C2) per segment...done 910s Number of segments: 3 910s Segmenting paired tumor-normal signals using Paired PSCBS...done 910s Post-segmenting TCNs... 910s Number of segments: 3 910s Number of chromosomes: 1 910s [1] 1 910s Chromosome 1 ('chr01') of 1... 910s Rows: 910s [1] 1 2 3 910s Number of segments: 3 910s TCN segment #1 ('1') of 3... 910s Nothing todo. Only one DH segmentation. Skipping. 910s TCN segment #1 ('1') of 3...done 910s TCN segment #2 ('2') of 3... 910s Nothing todo. Only one DH segmentation. Skipping. 910s TCN segment #2 ('2') of 3...done 910s TCN segment #3 ('3') of 3... 910s Nothing todo. Only one DH segmentation. Skipping. 910s TCN segment #3 ('3') of 3...done 910s Chromosome 1 ('chr01') of 1...done 910s Update (C1,C2) per segment... 910s Update (C1,C2) per segment...done 910s Post-segmenting TCNs...done 910s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 910s 1 1 1 1 554484 120992603 7586 1.3853 2108 910s 2 1 2 1 141510003 185449813 2681 2.0689 777 910s 3 1 3 1 185449813 247137334 4391 2.6341 1311 910s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 910s 1 2108 554484 120992603 2108 0.5116 0.3382903 1.047010 910s 2 777 141510003 185449813 777 0.0973 0.9337980 1.135102 910s 3 1311 185449813 247137334 1311 0.2295 1.0147870 1.619313 910s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 910s 1 1 1 1 554484 120992603 7586 1.3853 2108 910s 2 1 2 1 141510003 185449813 2681 2.0689 777 910s 3 1 3 1 185449813 247137334 4391 2.6341 1311 910s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 910s 1 2108 554484 120992603 2108 0.5116 0.3382903 1.047010 910s 2 777 141510003 185449813 777 0.0973 0.9337980 1.135102 910s 3 1311 185449813 247137334 1311 0.2295 1.0147870 1.619313 910s > print(fit) 910s chromosome tcnId dhId start end tcnNbrOfLoci tcnMean tcnNbrOfSNPs 910s 1 1 1 1 554484 120992603 7586 1.3853 2108 910s 2 1 2 1 141510003 185449813 2681 2.0689 777 910s 3 1 3 1 185449813 247137334 4391 2.6341 1311 910s tcnNbrOfHets dhNbrOfLoci dhMean c1Mean c2Mean 910s 1 2108 2108 0.5116 0.3382903 1.047010 910s 2 777 777 0.0973 0.9337980 1.135102 910s 3 1311 1311 0.2295 1.0147870 1.619313 910s > 910s > # Plot results 910s > dev.set(4L) 910s pdf 910s 2 910s > plotTracks(fit) 910s > abline(v=c(knownSegments$start, knownSegments$end)/1e6, lty=3) 910s > 910s > # Sanity check 910s > stopifnot(nbrOfSegments(fit) == nSegs-1L) 910s > 910s > fit3 <- fit 910s > 910s > 910s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 910s > # (d) Skip the identification of new change points 910s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 910s > knownSegments <- data.frame( 910s + chromosome = c( 1, 1), 910s + start = c( -Inf, 141510003), 910s + end = c(120992603, +Inf) 910s + ) 910s > 910s > # Paired PSCBS segmentation 910s > fit <- segmentByPairedPSCBS(dataS, knownSegments=knownSegments, 910s + undoTCN=Inf, undoDH=Inf, 910s + seed=0xBEEF, verbose=-10) 910s Segmenting paired tumor-normal signals using Paired PSCBS... 910s Calling genotypes from normal allele B fractions... 910s num [1:14670] 0.8274 0.5072 0.1671 0.1609 0.0421 ... 910s Called genotypes: 910s num [1:14670] 1 0.5 0 0 0 0 1 0 1 0.5 ... 910s - attr(*, "modelFit")=List of 1 910s ..$ :List of 7 910s .. ..$ flavor : chr "density" 910s .. ..$ cn : int 2 910s .. ..$ nbrOfGenotypeGroups: int 3 910s .. ..$ tau : num [1:2] 0.315 0.677 910s .. ..$ n : int 14640 910s .. ..$ fit :Classes ‘PeaksAndValleys’ and 'data.frame': 5 obs. of 3 variables: 910s .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 910s .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 910s .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 910s .. ..$ fitValleys :Classes ‘PeaksAndValleys’ and 'data.frame': 2 obs. of 3 variables: 910s .. .. ..$ type : chr [1:2] "valley" "valley" 910s .. .. ..$ x : num [1:2] 0.315 0.677 910s .. .. ..$ density: num [1:2] 0.522 0.551 910s ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 910s muN 910s 0 0.5 1 910s 5221 4198 5251 910s Calling genotypes from normal allele B fractions...done 910s Normalizing betaT using betaN (TumorBoost)... 910s Normalized BAFs: 910s num [1:14670] 0.9301 0.1667 0.0685 0.0995 0.0155 ... 910s - attr(*, "modelFit")=List of 5 910s ..$ method : chr "normalizeTumorBoost" 910s ..$ flavor : chr "v4" 910s ..$ delta : num [1:14670] -0.17264 0.00239 0.1671 0.16085 0.04213 ... 910s .. ..- attr(*, "modelFit")=List of 1 910s .. .. ..$ :List of 7 910s .. .. .. ..$ flavor : chr "density" 910s .. .. .. ..$ cn : int 2 910s .. .. .. ..$ nbrOfGenotypeGroups: int 3 910s .. .. .. ..$ tau : num [1:2] 0.315 0.677 910s .. .. .. ..$ n : int 14640 910s .. .. .. ..$ fit :Classes ‘PeaksAndValleys’ and 'data.frame': 5 obs. of 3 variables: 910s .. .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 910s .. .. .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 910s .. .. .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 910s .. .. .. ..$ fitValleys :Classes ‘PeaksAndValleys’ and 'data.frame': 2 obs. of 3 variables: 910s .. .. .. .. ..$ type : chr [1:2] "valley" "valley" 910s .. .. .. .. ..$ x : num [1:2] 0.315 0.677 910s .. .. .. .. ..$ density: num [1:2] 0.522 0.551 910s .. .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 910s ..$ preserveScale: logi FALSE 910s ..$ scaleFactor : num NA 910s Normalizing betaT using betaN (TumorBoost)...done 910s Setup up data... 911s 'data.frame': 14670 obs. of 7 variables: 911s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 911s $ x : num 1145994 2941694 3710825 4240737 4276892 ... 911s $ CT : num 1.63 1.4 1.41 1.17 1.16 ... 911s $ betaT : num 0.7574 0.169 0.2357 0.2604 0.0576 ... 911s $ betaTN : num 0.9301 0.1667 0.0685 0.0995 0.0155 ... 911s ..- attr(*, "modelFit")=List of 5 911s .. ..$ method : chr "normalizeTumorBoost" 911s .. ..$ flavor : chr "v4" 911s .. ..$ delta : num [1:14670] -0.17264 0.00239 0.1671 0.16085 0.04213 ... 911s .. .. ..- attr(*, "modelFit")=List of 1 911s .. .. .. ..$ :List of 7 911s .. .. .. .. ..$ flavor : chr "density" 911s .. .. .. .. ..$ cn : int 2 911s .. .. .. .. ..$ nbrOfGenotypeGroups: int 3 911s .. .. .. .. ..$ tau : num [1:2] 0.315 0.677 911s .. .. .. .. ..$ n : int 14640 911s .. .. .. .. ..$ fit :Classes ‘PeaksAndValleys’ and 'data.frame': 5 obs. of 3 variables: 911s .. .. .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 911s .. .. .. .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 911s .. .. .. .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 911s .. .. .. .. ..$ fitValleys :Classes ‘PeaksAndValleys’ and 'data.frame': 2 obs. of 3 variables: 911s .. .. .. .. .. ..$ type : chr [1:2] "valley" "valley" 911s .. .. .. .. .. ..$ x : num [1:2] 0.315 0.677 911s .. .. .. .. .. ..$ density: num [1:2] 0.522 0.551 911s .. .. .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 911s .. ..$ preserveScale: logi FALSE 911s .. ..$ scaleFactor : num NA 911s $ betaN : num 0.8274 0.5072 0.1671 0.1609 0.0421 ... 911s $ muN : num 1 0.5 0 0 0 0 1 0 1 0.5 ... 911s ..- attr(*, "modelFit")=List of 1 911s .. ..$ :List of 7 911s .. .. ..$ flavor : chr "density" 911s .. .. ..$ cn : int 2 911s .. .. ..$ nbrOfGenotypeGroups: int 3 911s .. .. ..$ tau : num [1:2] 0.315 0.677 911s .. .. ..$ n : int 14640 911s .. .. ..$ fit :Classes ‘PeaksAndValleys’ and 'data.frame': 5 obs. of 3 variables: 911s .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 911s .. .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 911s .. .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 911s .. .. ..$ fitValleys :Classes ‘PeaksAndValleys’ and 'data.frame': 2 obs. of 3 variables: 911s .. .. .. ..$ type : chr [1:2] "valley" "valley" 911s .. .. .. ..$ x : num [1:2] 0.315 0.677 911s .. .. .. ..$ density: num [1:2] 0.522 0.551 911s .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 911s Setup up data...done 911s Dropping loci for which TCNs are missing... 911s Number of loci dropped: 12 911s Dropping loci for which TCNs are missing...done 911s Ordering data along genome... 911s 'data.frame': 14658 obs. of 7 variables: 911s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 911s $ x : num 554484 730720 782343 878522 916294 ... 911s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 911s $ betaT : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 911s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 911s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 911s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 911s Ordering data along genome...done 911s Keeping only current chromosome for 'knownSegments'... 911s Chromosome: 1 911s Known segments for this chromosome: 911s chromosome start end 911s 1 1 -Inf 120992603 911s 2 1 141510003 Inf 911s Keeping only current chromosome for 'knownSegments'...done 911s alphaTCN: 0.009 911s alphaDH: 0.001 911s Number of loci: 14658 911s Calculating DHs... 911s Number of SNPs: 14658 911s Number of heterozygous SNPs: 4196 (28.63%) 911s Normalized DHs: 911s num [1:14658] NA NA NA NA NA ... 911s Calculating DHs...done 911s Random seed temporarily set (seed=c(48879), kind="L'Ecuyer-CMRG") 911s Produced 2 seeds from this stream for future usage 911s Identification of change points by total copy numbers... 911s Segmenting by CBS... 911s Chromosome: 1 911s Segmenting multiple segments on current chromosome... 911s Number of segments: 2 911s Random seed temporarily set (seed=c(10407, 1066287653, -51199871, 161854402, -1995183193, 1503453565, -747102133), kind="L'Ecuyer-CMRG") 911s Produced 2 seeds from this stream for future usage 911s Segmenting by CBS... 911s Chromosome: 1 911s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 911s Segmenting by CBS...done 911s Segmenting by CBS... 911s Chromosome: 1 911s Random seed temporarily set (seed=c(10407, -821273412, -52578226, 1415511586, 721384351, -665928286, 1316562960), kind="L'Ecuyer-CMRG") 911s Segmenting by CBS...done 911s Segmenting multiple segments on current chromosome...done 911s Segmenting by CBS...done 911s List of 4 911s $ data :'data.frame': 14658 obs. of 4 variables: 911s ..$ chromosome: int [1:14658] 1 1 1 1 1 1 1 1 1 1 ... 911s ..$ x : num [1:14658] 554484 730720 782343 878522 916294 ... 911s ..$ y : num [1:14658] 1.88 1.8 1.59 1.64 1.53 ... 911s ..$ index : int [1:14658] 1 2 3 4 5 6 7 8 9 10 ... 911s $ output :'data.frame': 2 obs. of 6 variables: 911s ..$ sampleName: chr [1:2] NA NA 911s ..$ chromosome: num [1:2] 1 1 911s ..$ start : num [1:2] 5.54e+05 1.42e+08 911s ..$ end : num [1:2] 1.21e+08 2.47e+08 911s ..$ nbrOfLoci : int [1:2] 7586 7072 911s ..$ mean : num [1:2] 1.39 2.42 911s $ segRows:'data.frame': 2 obs. of 2 variables: 911s ..$ startRow: int [1:2] 1 7587 911s ..$ endRow : int [1:2] 7586 14658 911s $ params :List of 7 911s ..$ undo.splits : chr "sdundo" 911s ..$ undo.SD : num Inf 911s ..$ alpha : num 0.009 911s ..$ undo : num Inf 911s ..$ joinSegments : logi TRUE 911s ..$ knownSegments:'data.frame': 2 obs. of 3 variables: 911s .. ..$ chromosome: num [1:2] 1 1 911s .. ..$ start : num [1:2] -Inf 1.42e+08 911s .. ..$ end : num [1:2] 1.21e+08 Inf 911s ..$ seed : int [1:7] 10407 1066287653 -51199871 161854402 -1995183193 1503453565 -747102133 911s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 911s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.002 0 0.002 0 0 911s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 911s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 911s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 911s Identification of change points by total copy numbers...done 911s Restructure TCN segmentation results... 911s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean 911s 1 1 554484 120992603 7586 1.385258 911s 2 1 141510003 247137334 7072 2.419824 911s Number of TCN segments: 2 911s Restructure TCN segmentation results...done 911s Total CN segment #1 ([ 554484,1.20993e+08]) of 2... 911s Number of TCN loci in segment: 7586 911s Locus data for TCN segment: 911s 'data.frame': 7586 obs. of 9 variables: 911s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 911s $ x : num 554484 730720 782343 878522 916294 ... 911s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 911s $ betaT : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 911s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 911s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 911s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 911s $ index : int 1 2 3 4 5 6 7 8 9 10 ... 911s $ rho : num NA NA NA NA NA ... 911s Number of loci: 7586 911s Number of SNPs: 2108 (27.79%) 911s Number of heterozygous SNPs: 2108 (100.00%) 911s Chromosome: 1 911s Segmenting DH signals... 911s Segmenting by CBS... 911s Chromosome: 1 911s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 911s Segmenting by CBS...done 911s List of 4 911s $ data :'data.frame': 7586 obs. of 4 variables: 911s ..$ chromosome: int [1:7586] 1 1 1 1 1 1 1 1 1 1 ... 911s ..$ x : num [1:7586] 554484 730720 782343 878522 916294 ... 911s ..$ y : num [1:7586] NA NA NA NA NA ... 911s ..$ index : int [1:7586] 1 2 3 4 5 6 7 8 9 10 ... 911s $ output :'data.frame': 1 obs. of 6 variables: 911s ..$ sampleName: chr NA 911s ..$ chromosome: int 1 911s ..$ start : num 554484 911s ..$ end : num 1.21e+08 911s ..$ nbrOfLoci : int 7586 911s ..$ mean : num 0.512 911s $ segRows:'data.frame': 1 obs. of 2 variables: 911s ..$ startRow: int 1 911s ..$ endRow : int 7586 911s $ params :List of 7 911s ..$ undo.splits : chr "sdundo" 911s ..$ undo.SD : num Inf 911s ..$ alpha : num 0.001 911s ..$ undo : num Inf 911s ..$ joinSegments : logi TRUE 911s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 911s .. ..$ chromosome: int 1 911s .. ..$ start : num 554484 911s .. ..$ end : num 1.21e+08 911s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 911s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 911s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.001 0 0.002 0 0 911s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 911s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 911s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 911s DH segmentation (locally-indexed) rows: 911s startRow endRow 911s 1 1 7586 911s int [1:7586] 1 2 3 4 5 6 7 8 9 10 ... 911s DH segmentation rows: 911s startRow endRow 911s 1 1 7586 911s Segmenting DH signals...done 911s DH segmentation table: 911s dhStart dhEnd dhNbrOfLoci dhMean 911s 1 554484 120992603 7586 0.511612 911s startRow endRow 911s 1 1 7586 911s Rows: 911s [1] 1 911s TCN segmentation rows: 911s startRow endRow 911s 1 1 7586 911s TCN and DH segmentation rows: 911s startRow endRow 911s 1 1 7586 911s startRow endRow 911s 1 1 7586 911s NULL 911s TCN segmentation (expanded) rows: 911s startRow endRow 911s 1 1 7586 911s TCN and DH segmentation rows: 911s startRow endRow 911s 1 1 7586 911s 2 7587 14658 911s startRow endRow 911s 1 1 7586 911s startRow endRow 911s 1 1 7586 911s Total CN segmentation table (expanded): 911s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 911s 1 1 554484 120992603 7586 1.385258 2108 2108 911s (TCN,DH) segmentation for one total CN segment: 911s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 911s 1 1 1 1 554484 120992603 7586 1.385258 2108 911s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 911s 1 2108 554484 120992603 7586 0.511612 911s Total CN segment #1 ([ 554484,1.20993e+08]) of 2...done 911s Total CN segment #2 ([1.4151e+08,2.47137e+08]) of 2... 911s Number of TCN loci in segment: 7072 911s Locus data for TCN segment: 911s 'data.frame': 7072 obs. of 9 variables: 911s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 911s $ x : num 1.43e+08 1.43e+08 1.43e+08 1.43e+08 1.44e+08 ... 911s $ CT : num 2.27 1.55 1.47 1.5 1.81 ... 911s $ betaT : num 0.34 0.55 0.048 0.813 0.575 ... 911s $ betaTN : num 0.441 0.629 -0.05 0.958 0.872 ... 911s $ betaN : num 0.3851 0.3933 0.0981 0.8552 0.7028 ... 911s $ muN : num 0.5 0.5 0 1 1 1 1 0.5 1 1 ... 911s $ index : int 7587 7588 7589 7590 7591 7592 7593 7594 7595 7596 ... 911s $ rho : num 0.117 0.258 NA NA NA ... 911s Number of loci: 7072 911s Number of SNPs: 2088 (29.52%) 911s Number of heterozygous SNPs: 2088 (100.00%) 911s Chromosome: 1 911s Segmenting DH signals... 911s Segmenting by CBS... 911s Chromosome: 1 911s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 911s Segmenting by CBS...done 911s List of 4 911s $ data :'data.frame': 7072 obs. of 4 variables: 911s ..$ chromosome: int [1:7072] 1 1 1 1 1 1 1 1 1 1 ... 911s ..$ x : num [1:7072] 1.43e+08 1.43e+08 1.43e+08 1.43e+08 1.44e+08 ... 911s ..$ y : num [1:7072] 0.117 0.258 NA NA NA ... 911s ..$ index : int [1:7072] 1 2 3 4 5 6 7 8 9 10 ... 911s $ output :'data.frame': 1 obs. of 6 variables: 911s ..$ sampleName: chr NA 911s ..$ chromosome: int 1 911s ..$ start : num 1.42e+08 911s ..$ end : num 2.47e+08 911s ..$ nbrOfLoci : int 7072 911s ..$ mean : num 0.18 911s $ segRows:'data.frame': 1 obs. of 2 variables: 911s ..$ startRow: int 1 911s ..$ endRow : int 7072 911s $ params :List of 7 911s ..$ undo.splits : chr "sdundo" 911s ..$ undo.SD : num Inf 911s ..$ alpha : num 0.001 911s ..$ undo : num Inf 911s ..$ joinSegments : logi TRUE 911s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 911s .. ..$ chromosome: int 1 911s .. ..$ start : num 1.42e+08 911s .. ..$ end : num 2.47e+08 911s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 911s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 911s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.002 0 0.002 0 0 911s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 911s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 911s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 911s DH segmentation (locally-indexed) rows: 911s startRow endRow 911s 1 1 7072 911s int [1:7072] 7587 7588 7589 7590 7591 7592 7593 7594 7595 7596 ... 911s DH segmentation rows: 911s startRow endRow 911s 1 7587 14658 911s Segmenting DH signals...done 911s DH segmentation table: 911s dhStart dhEnd dhNbrOfLoci dhMean 911s 1 141510003 247137334 7072 0.1803011 911s startRow endRow 911s 1 7587 14658 911s Rows: 911s [1] 2 911s TCN segmentation rows: 911s startRow endRow 911s 2 7587 14658 911s TCN and DH segmentation rows: 911s startRow endRow 911s 2 7587 14658 911s startRow endRow 911s 1 7587 14658 911s startRow endRow 911s 1 1 7586 911s TCN segmentation (expanded) rows: 911s startRow endRow 911s 1 1 7586 911s 2 7587 14658 911s TCN and DH segmentation rows: 911s startRow endRow 911s 1 1 7586 911s 2 7587 14658 911s startRow endRow 911s 1 1 7586 911s 2 7587 14658 911s startRow endRow 911s 1 1 7586 911s 2 7587 14658 911s Total CN segmentation table (expanded): 911s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 911s 2 1 141510003 247137334 7072 2.419824 2088 911s tcnNbrOfHets 911s 2 2088 911s (TCN,DH) segmentation for one total CN segment: 911s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 911s 2 2 1 1 141510003 247137334 7072 2.419824 2088 911s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 911s 2 2088 141510003 247137334 7072 0.1803011 911s Total CN segment #2 ([1.4151e+08,2.47137e+08]) of 2...done 911s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 911s 1 1 1 1 554484 120992603 7586 1.385258 2108 911s 2 1 2 1 141510003 247137334 7072 2.419824 2088 911s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 911s 1 2108 554484 120992603 7586 0.5116120 911s 2 2088 141510003 247137334 7072 0.1803011 911s Calculating (C1,C2) per segment... 911s Calculating (C1,C2) per segment...done 911s Number of segments: 2 911s Segmenting paired tumor-normal signals using Paired PSCBS...done 911s Post-segmenting TCNs... 911s Number of segments: 2 911s Number of chromosomes: 1 911s [1] 1 911s Chromosome 1 ('chr01') of 1... 911s Rows: 911s [1] 1 2 911s Number of segments: 2 911s TCN segment #1 ('1') of 2... 911s Nothing todo. Only one DH segmentation. Skipping. 911s TCN segment #1 ('1') of 2...done 911s TCN segment #2 ('2') of 2... 911s Nothing todo. Only one DH segmentation. Skipping. 911s TCN segment #2 ('2') of 2...done 911s Chromosome 1 ('chr01') of 1...done 911s Update (C1,C2) per segment... 911s Update (C1,C2) per segment...done 911s Post-segmenting TCNs...done 911s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 911s 1 1 1 1 554484 120992603 7586 1.385258 2108 911s 2 1 2 1 141510003 247137334 7072 2.419824 2088 911s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 911s 1 2108 554484 120992603 7586 0.5116120 0.3382717 1.046986 911s 2 2088 141510003 247137334 7072 0.1803011 0.9917635 1.428060 911s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 911s 1 1 1 1 554484 120992603 7586 1.385258 2108 911s 2 1 2 1 141510003 247137334 7072 2.419824 2088 911s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 911s 1 2108 554484 120992603 7586 0.5116120 0.3382717 1.046986 911s 2 2088 141510003 247137334 7072 0.1803011 0.9917635 1.428060 911s > print(fit) 911s chromosome tcnId dhId start end tcnNbrOfLoci tcnMean tcnNbrOfSNPs 911s 1 1 1 1 554484 120992603 7586 1.385258 2108 911s 2 1 2 1 141510003 247137334 7072 2.419824 2088 911s tcnNbrOfHets dhNbrOfLoci dhMean c1Mean c2Mean 911s 1 2108 7586 0.5116120 0.3382717 1.046986 911s 2 2088 7072 0.1803011 0.9917635 1.428060 911s > 911s > # Plot results 911s > dev.set(5L) 911s pdf 911s 2 911s > plotTracks(fit) 911s > abline(v=c(knownSegments$start, knownSegments$end)/1e6, lty=3) 911s > 911s > # Sanity check 911s > stopifnot(nbrOfSegments(fit) == nrow(knownSegments)) 911s > 911s > fit4 <- fit 911s > 911s > 911s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 911s > # Tiling multiple chromosomes 911s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 911s > # Simulate multiple chromosomes 911s > fit1 <- fit 911s > fit2 <- renameChromosomes(fit, from=1, to=2) 911s > fitM <- c(fit1, fit2) 911s > 911s > # Tile chromosomes 911s > fitT <- tileChromosomes(fitM) 911s > fitTb <- tileChromosomes(fitT) 911s > stopifnot(identical(fitTb, fitT)) 911s > 911s > # Plotting multiple chromosomes 911s > plotTracks(fitT) 911s > 912s autopkgtest [00:17:58]: test pkg-r-autopkgtest: -----------------------] 912s autopkgtest [00:17:58]: test pkg-r-autopkgtest: - - - - - - - - - - results - - - - - - - - - - 912s pkg-r-autopkgtest PASS 912s autopkgtest [00:17:58]: @@@@@@@@@@@@@@@@@@@@ summary 912s run-unit-test PASS 912s pkg-r-autopkgtest PASS