0s autopkgtest [23:37:18]: starting date and time: 2026-02-09 23:37:18+0000 0s autopkgtest [23:37:18]: git checkout: 4b346b80 nova: make wait_reboot return success even when a no-op 0s autopkgtest [23:37:18]: host juju-7f2275-prod-proposed-migration-environment-2; command line: /home/ubuntu/autopkgtest/runner/autopkgtest --output-dir /tmp/autopkgtest-work.1n9rcdk9/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-ppc64el --security-groups autopkgtest-juju-7f2275-prod-proposed-migration-environment-2@sto01-ppc64el-12.secgroup --name adt-resolute-ppc64el-r-cran-pscbs-20260209-233717-juju-7f2275-prod-proposed-migration-environment-2-0e67591c-a121-4fa1-828e-6000476eb62d --image adt/ubuntu-resolute-ppc64el-server --keyname testbed-juju-7f2275-prod-proposed-migration-environment-2 --net-id=net_prod-autopkgtest-workers-ppc64el -e TERM=linux --mirror=http://ftpmaster.internal/ubuntu/ 3s Creating nova instance adt-resolute-ppc64el-r-cran-pscbs-20260209-233717-juju-7f2275-prod-proposed-migration-environment-2-0e67591c-a121-4fa1-828e-6000476eb62d from image adt/ubuntu-resolute-ppc64el-server-20260209.img (UUID f7f31435-4cd1-4090-aa55-59cfefa097ca)... 115s autopkgtest [23:39:13]: testbed dpkg architecture: ppc64el 116s autopkgtest [23:39:14]: testbed apt version: 3.1.15 116s autopkgtest [23:39:14]: @@@@@@@@@@@@@@@@@@@@ test bed setup 116s autopkgtest [23:39:14]: testbed release detected to be: None 117s autopkgtest [23:39:15]: updating testbed package index (apt update) 117s Get:1 http://ftpmaster.internal/ubuntu resolute-proposed InRelease [124 kB] 117s Hit:2 http://ftpmaster.internal/ubuntu resolute InRelease 117s Hit:3 http://ftpmaster.internal/ubuntu resolute-updates InRelease 117s Hit:4 http://ftpmaster.internal/ubuntu resolute-security InRelease 117s Get:5 http://ftpmaster.internal/ubuntu resolute-proposed/universe Sources [1645 kB] 121s Get:6 http://ftpmaster.internal/ubuntu resolute-proposed/main Sources [176 kB] 121s Get:7 http://ftpmaster.internal/ubuntu resolute-proposed/multiverse Sources [29.4 kB] 122s Get:8 http://ftpmaster.internal/ubuntu resolute-proposed/main ppc64el Packages [246 kB] 122s Get:9 http://ftpmaster.internal/ubuntu resolute-proposed/universe ppc64el Packages [1534 kB] 126s Get:10 http://ftpmaster.internal/ubuntu resolute-proposed/multiverse ppc64el Packages [19.4 kB] 126s Fetched 3774 kB in 9s (418 kB/s) 127s Reading package lists... 127s Hit:1 http://ftpmaster.internal/ubuntu resolute-proposed InRelease 127s Hit:2 http://ftpmaster.internal/ubuntu resolute InRelease 128s Hit:3 http://ftpmaster.internal/ubuntu resolute-updates InRelease 128s Hit:4 http://ftpmaster.internal/ubuntu resolute-security InRelease 128s Reading package lists... 128s Reading package lists... 129s Building dependency tree... 129s Reading state information... 129s Calculating upgrade... 129s The following packages will be upgraded: 129s cryptsetup-bin dracut-install iproute2 iptables libcryptsetup12 libip4tc2 129s libip6tc2 libxtables12 wget 129s 9 upgraded, 0 newly installed, 0 to remove and 0 not upgraded. 129s Need to get 3125 kB of archives. 129s After this operation, 78.8 kB of additional disk space will be used. 129s Get:1 http://ftpmaster.internal/ubuntu resolute/main ppc64el iptables ppc64el 1.8.11-2ubuntu3 [464 kB] 129s Get:2 http://ftpmaster.internal/ubuntu resolute/main ppc64el libip4tc2 ppc64el 1.8.11-2ubuntu3 [27.8 kB] 129s Get:3 http://ftpmaster.internal/ubuntu resolute/main ppc64el libip6tc2 ppc64el 1.8.11-2ubuntu3 [28.2 kB] 129s Get:4 http://ftpmaster.internal/ubuntu resolute/main ppc64el libxtables12 ppc64el 1.8.11-2ubuntu3 [41.2 kB] 129s Get:5 http://ftpmaster.internal/ubuntu resolute/main ppc64el iproute2 ppc64el 6.18.0-1ubuntu1 [1458 kB] 131s Get:6 http://ftpmaster.internal/ubuntu resolute/main ppc64el libcryptsetup12 ppc64el 2:2.8.0-1ubuntu3 [404 kB] 131s Get:7 http://ftpmaster.internal/ubuntu resolute/main ppc64el wget ppc64el 1.25.0-2ubuntu4 [401 kB] 131s Get:8 http://ftpmaster.internal/ubuntu resolute/main ppc64el cryptsetup-bin ppc64el 2:2.8.0-1ubuntu3 [250 kB] 131s Get:9 http://ftpmaster.internal/ubuntu resolute/main ppc64el dracut-install ppc64el 109-11ubuntu1 [51.3 kB] 132s dpkg-preconfigure: unable to re-open stdin: No such file or directory 132s Fetched 3125 kB in 3s (1242 kB/s) 132s (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 ... 122003 files and directories currently installed.) 132s Preparing to unpack .../0-iptables_1.8.11-2ubuntu3_ppc64el.deb ... 132s Unpacking iptables (1.8.11-2ubuntu3) over (1.8.11-2ubuntu2) ... 133s Preparing to unpack .../1-libip4tc2_1.8.11-2ubuntu3_ppc64el.deb ... 133s Unpacking libip4tc2:ppc64el (1.8.11-2ubuntu3) over (1.8.11-2ubuntu2) ... 133s Preparing to unpack .../2-libip6tc2_1.8.11-2ubuntu3_ppc64el.deb ... 133s Unpacking libip6tc2:ppc64el (1.8.11-2ubuntu3) over (1.8.11-2ubuntu2) ... 133s Preparing to unpack .../3-libxtables12_1.8.11-2ubuntu3_ppc64el.deb ... 133s Unpacking libxtables12:ppc64el (1.8.11-2ubuntu3) over (1.8.11-2ubuntu2) ... 133s Preparing to unpack .../4-iproute2_6.18.0-1ubuntu1_ppc64el.deb ... 133s Unpacking iproute2 (6.18.0-1ubuntu1) over (6.16.0-1ubuntu3) ... 133s Preparing to unpack .../5-libcryptsetup12_2%3a2.8.0-1ubuntu3_ppc64el.deb ... 133s Unpacking libcryptsetup12:ppc64el (2:2.8.0-1ubuntu3) over (2:2.8.0-1ubuntu2) ... 133s Preparing to unpack .../6-wget_1.25.0-2ubuntu4_ppc64el.deb ... 134s Unpacking wget (1.25.0-2ubuntu4) over (1.25.0-2ubuntu3) ... 134s Preparing to unpack .../7-cryptsetup-bin_2%3a2.8.0-1ubuntu3_ppc64el.deb ... 134s Unpacking cryptsetup-bin (2:2.8.0-1ubuntu3) over (2:2.8.0-1ubuntu2) ... 134s Preparing to unpack .../8-dracut-install_109-11ubuntu1_ppc64el.deb ... 134s Unpacking dracut-install (109-11ubuntu1) over (109-9ubuntu1) ... 134s Setting up libip4tc2:ppc64el (1.8.11-2ubuntu3) ... 134s Setting up wget (1.25.0-2ubuntu4) ... 134s Setting up libip6tc2:ppc64el (1.8.11-2ubuntu3) ... 134s Setting up libxtables12:ppc64el (1.8.11-2ubuntu3) ... 134s Setting up dracut-install (109-11ubuntu1) ... 134s Setting up libcryptsetup12:ppc64el (2:2.8.0-1ubuntu3) ... 134s Setting up cryptsetup-bin (2:2.8.0-1ubuntu3) ... 134s Setting up iptables (1.8.11-2ubuntu3) ... 134s Setting up iproute2 (6.18.0-1ubuntu1) ... 134s Processing triggers for man-db (2.13.1-1build1) ... 137s Processing triggers for install-info (7.2-5) ... 137s Processing triggers for libc-bin (2.42-2ubuntu4) ... 137s autopkgtest [23:39:35]: upgrading testbed (apt dist-upgrade and autopurge) 137s Reading package lists... 137s Building dependency tree... 137s Reading state information... 138s Calculating upgrade... 138s 0 upgraded, 0 newly installed, 0 to remove and 0 not upgraded. 138s Reading package lists... 138s Building dependency tree... 138s Reading state information... 138s Solving dependencies... 138s 0 upgraded, 0 newly installed, 0 to remove and 0 not upgraded. 140s autopkgtest [23:39:38]: testbed running kernel: Linux 6.19.0-3-generic #3-Ubuntu SMP PREEMPT_DYNAMIC Fri Jan 23 20:13:51 UTC 2026 140s autopkgtest [23:39:38]: @@@@@@@@@@@@@@@@@@@@ apt-source r-cran-pscbs 150s Get:1 http://ftpmaster.internal/ubuntu resolute/universe r-cran-pscbs 0.68.0-1 (dsc) [2315 B] 150s Get:2 http://ftpmaster.internal/ubuntu resolute/universe r-cran-pscbs 0.68.0-1 (tar) [3591 kB] 150s Get:3 http://ftpmaster.internal/ubuntu resolute/universe r-cran-pscbs 0.68.0-1 (diff) [4040 B] 150s gpgv: Signature made Thu Jan 29 01:13:59 2026 UTC 150s gpgv: using RSA key 73471499CC60ED9EEE805946C5BD6C8F2295D502 150s gpgv: issuer "plessy@debian.org" 150s gpgv: Can't check signature: No public key 150s dpkg-source: warning: cannot verify inline signature for ./r-cran-pscbs_0.68.0-1.dsc: no acceptable signature found 150s autopkgtest [23:39:48]: testing package r-cran-pscbs version 0.68.0-1 150s autopkgtest [23:39:48]: build not needed 152s autopkgtest [23:39:50]: test run-unit-test: preparing testbed 152s Reading package lists... 152s Building dependency tree... 152s Reading state information... 152s Solving dependencies... 152s The following NEW packages will be installed: 152s fontconfig fontconfig-config fonts-dejavu-core fonts-dejavu-mono libblas3 152s libcairo2 libdatrie1 libdeflate0 libfontconfig1 libgfortran5 libgomp1 152s libgraphite2-3 libharfbuzz0b libice6 libjbig0 libjpeg-turbo8 libjpeg8 152s liblapack3 liblerc4 libpango-1.0-0 libpangocairo-1.0-0 libpangoft2-1.0-0 152s libpaper-utils libpaper2 libpixman-1-0 libsharpyuv0 libsm6 libtcl8.6 152s libthai-data libthai0 libtiff6 libtk8.6 libwebp7 libxcb-render0 libxcb-shm0 152s libxft2 libxrender1 libxss1 libxt6t64 r-base-core r-bioc-aroma.light 152s r-bioc-biocgenerics r-bioc-dnacopy r-cran-base64enc r-cran-cli 152s r-cran-codetools r-cran-digest r-cran-farver r-cran-future r-cran-ggplot2 152s r-cran-globals r-cran-glue r-cran-gtable r-cran-isoband r-cran-labeling 152s r-cran-lifecycle r-cran-listenv r-cran-matrixstats r-cran-parallelly 152s r-cran-pscbs r-cran-r.cache r-cran-r.devices r-cran-r.methodss3 r-cran-r.oo 152s r-cran-r.rsp r-cran-r.utils r-cran-r6 r-cran-rcolorbrewer r-cran-rlang 152s r-cran-s7 r-cran-scales r-cran-vctrs r-cran-viridislite r-cran-withr tcl 152s tcl8.6 unzip x11-common xdg-utils zip 152s 0 upgraded, 80 newly installed, 0 to remove and 0 not upgraded. 152s Need to get 70.1 MB of archives. 152s After this operation, 137 MB of additional disk space will be used. 152s Get:1 http://ftpmaster.internal/ubuntu resolute/main ppc64el fonts-dejavu-mono all 2.37-8build1 [502 kB] 152s Get:2 http://ftpmaster.internal/ubuntu resolute/main ppc64el fonts-dejavu-core all 2.37-8build1 [834 kB] 154s Get:3 http://ftpmaster.internal/ubuntu resolute/main ppc64el fontconfig-config ppc64el 2.17.1-3ubuntu1 [38.5 kB] 154s Get:4 http://ftpmaster.internal/ubuntu resolute/main ppc64el libfontconfig1 ppc64el 2.17.1-3ubuntu1 [193 kB] 154s Get:5 http://ftpmaster.internal/ubuntu resolute/main ppc64el fontconfig ppc64el 2.17.1-3ubuntu1 [182 kB] 154s Get:6 http://ftpmaster.internal/ubuntu resolute/main ppc64el libblas3 ppc64el 3.12.1-7ubuntu1 [291 kB] 154s Get:7 http://ftpmaster.internal/ubuntu resolute/main ppc64el libpixman-1-0 ppc64el 0.46.4-1 [347 kB] 154s Get:8 http://ftpmaster.internal/ubuntu resolute/main ppc64el libxcb-render0 ppc64el 1.17.0-2ubuntu1 [17.4 kB] 154s Get:9 http://ftpmaster.internal/ubuntu resolute/main ppc64el libxcb-shm0 ppc64el 1.17.0-2ubuntu1 [6072 B] 154s Get:10 http://ftpmaster.internal/ubuntu resolute/main ppc64el libxrender1 ppc64el 1:0.9.12-1 [23.0 kB] 154s Get:11 http://ftpmaster.internal/ubuntu resolute/main ppc64el libcairo2 ppc64el 1.18.4-3 [759 kB] 155s Get:12 http://ftpmaster.internal/ubuntu resolute/main ppc64el libdatrie1 ppc64el 0.2.14-1 [22.7 kB] 155s Get:13 http://ftpmaster.internal/ubuntu resolute/main ppc64el libdeflate0 ppc64el 1.23-2build1 [64.1 kB] 155s Get:14 http://ftpmaster.internal/ubuntu resolute/main ppc64el libgfortran5 ppc64el 15.2.0-12ubuntu1 [620 kB] 156s Get:15 http://ftpmaster.internal/ubuntu resolute/main ppc64el libgomp1 ppc64el 15.2.0-12ubuntu1 [169 kB] 156s Get:16 http://ftpmaster.internal/ubuntu resolute/main ppc64el libgraphite2-3 ppc64el 1.3.14-11ubuntu1 [85.3 kB] 157s Get:17 http://ftpmaster.internal/ubuntu resolute/main ppc64el libharfbuzz0b ppc64el 12.3.2-1 [663 kB] 157s Get:18 http://ftpmaster.internal/ubuntu resolute/main ppc64el x11-common all 1:7.7+24ubuntu1 [22.4 kB] 157s Get:19 http://ftpmaster.internal/ubuntu resolute/main ppc64el libice6 ppc64el 2:1.1.1-1build1 [51.9 kB] 157s Get:20 http://ftpmaster.internal/ubuntu resolute/main ppc64el libjpeg-turbo8 ppc64el 2.1.5-4ubuntu3 [214 kB] 157s Get:21 http://ftpmaster.internal/ubuntu resolute/main ppc64el libjpeg8 ppc64el 8c-2ubuntu11 [2148 B] 158s Get:22 http://ftpmaster.internal/ubuntu resolute/main ppc64el liblapack3 ppc64el 3.12.1-7ubuntu1 [2960 kB] 162s Get:23 http://ftpmaster.internal/ubuntu resolute/main ppc64el liblerc4 ppc64el 4.0.0+ds-5ubuntu2 [315 kB] 162s Get:24 http://ftpmaster.internal/ubuntu resolute/main ppc64el libthai-data all 0.1.30-1 [155 kB] 162s Get:25 http://ftpmaster.internal/ubuntu resolute/main ppc64el libthai0 ppc64el 0.1.30-1 [22.5 kB] 162s Get:26 http://ftpmaster.internal/ubuntu resolute/main ppc64el libpango-1.0-0 ppc64el 1.57.0-1 [283 kB] 162s Get:27 http://ftpmaster.internal/ubuntu resolute/main ppc64el libpangoft2-1.0-0 ppc64el 1.57.0-1 [61.2 kB] 162s Get:28 http://ftpmaster.internal/ubuntu resolute/main ppc64el libpangocairo-1.0-0 ppc64el 1.57.0-1 [31.0 kB] 162s Get:29 http://ftpmaster.internal/ubuntu resolute/main ppc64el libpaper2 ppc64el 2.2.5-0.3build1 [18.1 kB] 162s Get:30 http://ftpmaster.internal/ubuntu resolute/main ppc64el libpaper-utils ppc64el 2.2.5-0.3build1 [15.7 kB] 162s Get:31 http://ftpmaster.internal/ubuntu resolute/main ppc64el libsharpyuv0 ppc64el 1.5.0-0.1build1 [24.7 kB] 162s Get:32 http://ftpmaster.internal/ubuntu resolute/main ppc64el libsm6 ppc64el 2:1.2.6-1build1 [18.6 kB] 162s Get:33 http://ftpmaster.internal/ubuntu resolute/main ppc64el libtcl8.6 ppc64el 8.6.17+dfsg-1build1 [1239 kB] 165s Get:34 http://ftpmaster.internal/ubuntu resolute/main ppc64el libjbig0 ppc64el 2.1-6.1ubuntu3 [37.1 kB] 165s Get:35 http://ftpmaster.internal/ubuntu resolute/main ppc64el libwebp7 ppc64el 1.5.0-0.1build1 [330 kB] 165s Get:36 http://ftpmaster.internal/ubuntu resolute/main ppc64el libtiff6 ppc64el 4.7.0-3ubuntu3 [307 kB] 165s Get:37 http://ftpmaster.internal/ubuntu resolute/main ppc64el libxft2 ppc64el 2.3.6-1build2 [61.6 kB] 165s Get:38 http://ftpmaster.internal/ubuntu resolute/main ppc64el libxss1 ppc64el 1:1.2.3-1build4 [7470 B] 165s Get:39 http://ftpmaster.internal/ubuntu resolute/main ppc64el libtk8.6 ppc64el 8.6.17-1 [968 kB] 167s Get:40 http://ftpmaster.internal/ubuntu resolute/main ppc64el libxt6t64 ppc64el 1:1.2.1-1.3 [203 kB] 167s Get:41 http://ftpmaster.internal/ubuntu resolute/main ppc64el zip ppc64el 3.0-15ubuntu3 [198 kB] 167s Get:42 http://ftpmaster.internal/ubuntu resolute/main ppc64el unzip ppc64el 6.0-29ubuntu1 [200 kB] 167s Get:43 http://ftpmaster.internal/ubuntu resolute/main ppc64el xdg-utils all 1.2.1-2ubuntu2 [66.1 kB] 167s Get:44 http://ftpmaster.internal/ubuntu resolute/universe ppc64el r-base-core ppc64el 4.5.2-1ubuntu2 [29.3 MB] 219s Get:45 http://ftpmaster.internal/ubuntu resolute/universe ppc64el r-bioc-biocgenerics all 0.52.0-2 [624 kB] 220s Get:46 http://ftpmaster.internal/ubuntu resolute/universe ppc64el r-cran-r.methodss3 all 1.8.2-1 [84.0 kB] 220s Get:47 http://ftpmaster.internal/ubuntu resolute/universe ppc64el r-cran-r.oo all 1.27.1-1 [978 kB] 221s Get:48 http://ftpmaster.internal/ubuntu resolute/universe ppc64el r-cran-r.utils all 2.13.0-1 [1423 kB] 224s Get:49 http://ftpmaster.internal/ubuntu resolute/universe ppc64el r-cran-matrixstats ppc64el 1.5.0-1 [578 kB] 225s Get:50 http://ftpmaster.internal/ubuntu resolute/universe ppc64el r-bioc-aroma.light all 3.36.0-2 [583 kB] 226s Get:51 http://ftpmaster.internal/ubuntu resolute/universe ppc64el r-bioc-dnacopy ppc64el 1.80.0-2 [504 kB] 227s Get:52 http://ftpmaster.internal/ubuntu resolute/universe ppc64el r-cran-base64enc ppc64el 0.1-3-3build1 [29.3 kB] 227s Get:53 http://ftpmaster.internal/ubuntu resolute/universe ppc64el r-cran-cli ppc64el 3.6.4-1 [1411 kB] 230s Get:54 http://ftpmaster.internal/ubuntu resolute/universe ppc64el r-cran-codetools all 0.2-20-1build1 [91.1 kB] 230s Get:55 http://ftpmaster.internal/ubuntu resolute/universe ppc64el r-cran-digest ppc64el 0.6.39-1 [238 kB] 230s Get:56 http://ftpmaster.internal/ubuntu resolute/universe ppc64el r-cran-farver ppc64el 2.1.2-1 [1389 kB] 232s Get:57 http://ftpmaster.internal/ubuntu resolute/universe ppc64el r-cran-globals all 0.19.0-1 [160 kB] 232s Get:58 http://ftpmaster.internal/ubuntu resolute/universe ppc64el r-cran-listenv all 0.10.0+dfsg-1 [113 kB] 232s Get:59 http://ftpmaster.internal/ubuntu resolute/universe ppc64el r-cran-parallelly ppc64el 1.42.0-1 [540 kB] 234s Get:60 http://ftpmaster.internal/ubuntu resolute/universe ppc64el r-cran-future all 1.34.0+dfsg-1 [646 kB] 235s Get:61 http://ftpmaster.internal/ubuntu resolute/universe ppc64el r-cran-glue ppc64el 1.8.0-1 [165 kB] 235s Get:62 http://ftpmaster.internal/ubuntu resolute/universe ppc64el r-cran-rlang ppc64el 1.1.5-3 [1738 kB] 238s Get:63 http://ftpmaster.internal/ubuntu resolute/universe ppc64el r-cran-lifecycle all 1.0.5+dfsg-1 [120 kB] 238s Get:64 http://ftpmaster.internal/ubuntu resolute/universe ppc64el r-cran-gtable all 0.3.6+dfsg-1 [199 kB] 238s Get:65 http://ftpmaster.internal/ubuntu resolute/universe ppc64el r-cran-isoband ppc64el 0.2.7-1 [1486 kB] 240s Get:66 http://ftpmaster.internal/ubuntu resolute/universe ppc64el r-cran-s7 ppc64el 0.2.0-1 [330 kB] 240s Get:67 http://ftpmaster.internal/ubuntu resolute/universe ppc64el r-cran-labeling all 0.4.3-1 [62.1 kB] 240s Get:68 http://ftpmaster.internal/ubuntu resolute/universe ppc64el r-cran-r6 all 2.6.1-1 [101 kB] 240s Get:69 http://ftpmaster.internal/ubuntu resolute/universe ppc64el r-cran-rcolorbrewer all 1.1-3-1build2 [54.0 kB] 240s Get:70 http://ftpmaster.internal/ubuntu resolute/universe ppc64el r-cran-viridislite all 0.4.3-1 [1088 kB] 243s Get:71 http://ftpmaster.internal/ubuntu resolute/universe ppc64el r-cran-scales all 1.4.0-1 [725 kB] 245s Get:72 http://ftpmaster.internal/ubuntu resolute/universe ppc64el r-cran-vctrs ppc64el 0.6.5-1 [1399 kB] 248s Get:73 http://ftpmaster.internal/ubuntu resolute/universe ppc64el r-cran-withr all 3.0.2+dfsg-1 [214 kB] 248s Get:74 http://ftpmaster.internal/ubuntu resolute-proposed/universe ppc64el r-cran-ggplot2 all 4.0.2+dfsg-1 [4941 kB] 258s Get:75 http://ftpmaster.internal/ubuntu resolute/universe ppc64el r-cran-r.cache all 0.17.0-1 [117 kB] 258s Get:76 http://ftpmaster.internal/ubuntu resolute/universe ppc64el r-cran-pscbs all 0.68.0-1 [4234 kB] 266s Get:77 http://ftpmaster.internal/ubuntu resolute/universe ppc64el r-cran-r.devices all 2.17.3+ds-1 [400 kB] 266s Get:78 http://ftpmaster.internal/ubuntu resolute/main ppc64el tcl8.6 ppc64el 8.6.17+dfsg-1build1 [14.8 kB] 266s Get:79 http://ftpmaster.internal/ubuntu resolute/main ppc64el tcl ppc64el 8.6.16build1 [4204 B] 266s Get:80 http://ftpmaster.internal/ubuntu resolute/universe ppc64el r-cran-r.rsp all 0.46.0+ds-1 [1412 kB] 269s Preconfiguring packages ... 269s Fetched 70.1 MB in 1min 56s (603 kB/s) 269s Selecting previously unselected package fonts-dejavu-mono. 269s (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 ... 122006 files and directories currently installed.) 269s Preparing to unpack .../00-fonts-dejavu-mono_2.37-8build1_all.deb ... 269s Unpacking fonts-dejavu-mono (2.37-8build1) ... 269s Selecting previously unselected package fonts-dejavu-core. 269s Preparing to unpack .../01-fonts-dejavu-core_2.37-8build1_all.deb ... 269s Unpacking fonts-dejavu-core (2.37-8build1) ... 269s Selecting previously unselected package fontconfig-config. 269s Preparing to unpack .../02-fontconfig-config_2.17.1-3ubuntu1_ppc64el.deb ... 269s Unpacking fontconfig-config (2.17.1-3ubuntu1) ... 269s Selecting previously unselected package libfontconfig1:ppc64el. 269s Preparing to unpack .../03-libfontconfig1_2.17.1-3ubuntu1_ppc64el.deb ... 269s Unpacking libfontconfig1:ppc64el (2.17.1-3ubuntu1) ... 269s Selecting previously unselected package fontconfig. 269s Preparing to unpack .../04-fontconfig_2.17.1-3ubuntu1_ppc64el.deb ... 269s Unpacking fontconfig (2.17.1-3ubuntu1) ... 269s Selecting previously unselected package libblas3:ppc64el. 269s Preparing to unpack .../05-libblas3_3.12.1-7ubuntu1_ppc64el.deb ... 269s Unpacking libblas3:ppc64el (3.12.1-7ubuntu1) ... 269s Selecting previously unselected package libpixman-1-0:ppc64el. 269s Preparing to unpack .../06-libpixman-1-0_0.46.4-1_ppc64el.deb ... 269s Unpacking libpixman-1-0:ppc64el (0.46.4-1) ... 269s Selecting previously unselected package libxcb-render0:ppc64el. 269s Preparing to unpack .../07-libxcb-render0_1.17.0-2ubuntu1_ppc64el.deb ... 269s Unpacking libxcb-render0:ppc64el (1.17.0-2ubuntu1) ... 269s Selecting previously unselected package libxcb-shm0:ppc64el. 269s Preparing to unpack .../08-libxcb-shm0_1.17.0-2ubuntu1_ppc64el.deb ... 269s Unpacking libxcb-shm0:ppc64el (1.17.0-2ubuntu1) ... 269s Selecting previously unselected package libxrender1:ppc64el. 269s Preparing to unpack .../09-libxrender1_1%3a0.9.12-1_ppc64el.deb ... 269s Unpacking libxrender1:ppc64el (1:0.9.12-1) ... 269s Selecting previously unselected package libcairo2:ppc64el. 269s Preparing to unpack .../10-libcairo2_1.18.4-3_ppc64el.deb ... 269s Unpacking libcairo2:ppc64el (1.18.4-3) ... 269s Selecting previously unselected package libdatrie1:ppc64el. 269s Preparing to unpack .../11-libdatrie1_0.2.14-1_ppc64el.deb ... 269s Unpacking libdatrie1:ppc64el (0.2.14-1) ... 269s Selecting previously unselected package libdeflate0:ppc64el. 269s Preparing to unpack .../12-libdeflate0_1.23-2build1_ppc64el.deb ... 269s Unpacking libdeflate0:ppc64el (1.23-2build1) ... 269s Selecting previously unselected package libgfortran5:ppc64el. 269s Preparing to unpack .../13-libgfortran5_15.2.0-12ubuntu1_ppc64el.deb ... 269s Unpacking libgfortran5:ppc64el (15.2.0-12ubuntu1) ... 269s Selecting previously unselected package libgomp1:ppc64el. 269s Preparing to unpack .../14-libgomp1_15.2.0-12ubuntu1_ppc64el.deb ... 269s Unpacking libgomp1:ppc64el (15.2.0-12ubuntu1) ... 269s Selecting previously unselected package libgraphite2-3:ppc64el. 269s Preparing to unpack .../15-libgraphite2-3_1.3.14-11ubuntu1_ppc64el.deb ... 269s Unpacking libgraphite2-3:ppc64el (1.3.14-11ubuntu1) ... 269s Selecting previously unselected package libharfbuzz0b:ppc64el. 269s Preparing to unpack .../16-libharfbuzz0b_12.3.2-1_ppc64el.deb ... 269s Unpacking libharfbuzz0b:ppc64el (12.3.2-1) ... 270s Selecting previously unselected package x11-common. 270s Preparing to unpack .../17-x11-common_1%3a7.7+24ubuntu1_all.deb ... 270s Unpacking x11-common (1:7.7+24ubuntu1) ... 270s Selecting previously unselected package libice6:ppc64el. 270s Preparing to unpack .../18-libice6_2%3a1.1.1-1build1_ppc64el.deb ... 270s Unpacking libice6:ppc64el (2:1.1.1-1build1) ... 270s Selecting previously unselected package libjpeg-turbo8:ppc64el. 270s Preparing to unpack .../19-libjpeg-turbo8_2.1.5-4ubuntu3_ppc64el.deb ... 270s Unpacking libjpeg-turbo8:ppc64el (2.1.5-4ubuntu3) ... 270s Selecting previously unselected package libjpeg8:ppc64el. 270s Preparing to unpack .../20-libjpeg8_8c-2ubuntu11_ppc64el.deb ... 270s Unpacking libjpeg8:ppc64el (8c-2ubuntu11) ... 270s Selecting previously unselected package liblapack3:ppc64el. 270s Preparing to unpack .../21-liblapack3_3.12.1-7ubuntu1_ppc64el.deb ... 270s Unpacking liblapack3:ppc64el (3.12.1-7ubuntu1) ... 270s Selecting previously unselected package liblerc4:ppc64el. 270s Preparing to unpack .../22-liblerc4_4.0.0+ds-5ubuntu2_ppc64el.deb ... 270s Unpacking liblerc4:ppc64el (4.0.0+ds-5ubuntu2) ... 270s Selecting previously unselected package libthai-data. 270s Preparing to unpack .../23-libthai-data_0.1.30-1_all.deb ... 270s Unpacking libthai-data (0.1.30-1) ... 270s Selecting previously unselected package libthai0:ppc64el. 270s Preparing to unpack .../24-libthai0_0.1.30-1_ppc64el.deb ... 270s Unpacking libthai0:ppc64el (0.1.30-1) ... 270s Selecting previously unselected package libpango-1.0-0:ppc64el. 270s Preparing to unpack .../25-libpango-1.0-0_1.57.0-1_ppc64el.deb ... 270s Unpacking libpango-1.0-0:ppc64el (1.57.0-1) ... 270s Selecting previously unselected package libpangoft2-1.0-0:ppc64el. 270s Preparing to unpack .../26-libpangoft2-1.0-0_1.57.0-1_ppc64el.deb ... 270s Unpacking libpangoft2-1.0-0:ppc64el (1.57.0-1) ... 270s Selecting previously unselected package libpangocairo-1.0-0:ppc64el. 270s Preparing to unpack .../27-libpangocairo-1.0-0_1.57.0-1_ppc64el.deb ... 270s Unpacking libpangocairo-1.0-0:ppc64el (1.57.0-1) ... 270s Selecting previously unselected package libpaper2:ppc64el. 270s Preparing to unpack .../28-libpaper2_2.2.5-0.3build1_ppc64el.deb ... 270s Unpacking libpaper2:ppc64el (2.2.5-0.3build1) ... 270s Selecting previously unselected package libpaper-utils. 270s Preparing to unpack .../29-libpaper-utils_2.2.5-0.3build1_ppc64el.deb ... 270s Unpacking libpaper-utils (2.2.5-0.3build1) ... 270s Selecting previously unselected package libsharpyuv0:ppc64el. 270s Preparing to unpack .../30-libsharpyuv0_1.5.0-0.1build1_ppc64el.deb ... 270s Unpacking libsharpyuv0:ppc64el (1.5.0-0.1build1) ... 270s Selecting previously unselected package libsm6:ppc64el. 270s Preparing to unpack .../31-libsm6_2%3a1.2.6-1build1_ppc64el.deb ... 270s Unpacking libsm6:ppc64el (2:1.2.6-1build1) ... 270s Selecting previously unselected package libtcl8.6:ppc64el. 270s Preparing to unpack .../32-libtcl8.6_8.6.17+dfsg-1build1_ppc64el.deb ... 270s Unpacking libtcl8.6:ppc64el (8.6.17+dfsg-1build1) ... 270s Selecting previously unselected package libjbig0:ppc64el. 270s Preparing to unpack .../33-libjbig0_2.1-6.1ubuntu3_ppc64el.deb ... 270s Unpacking libjbig0:ppc64el (2.1-6.1ubuntu3) ... 270s Selecting previously unselected package libwebp7:ppc64el. 270s Preparing to unpack .../34-libwebp7_1.5.0-0.1build1_ppc64el.deb ... 270s Unpacking libwebp7:ppc64el (1.5.0-0.1build1) ... 270s Selecting previously unselected package libtiff6:ppc64el. 270s Preparing to unpack .../35-libtiff6_4.7.0-3ubuntu3_ppc64el.deb ... 270s Unpacking libtiff6:ppc64el (4.7.0-3ubuntu3) ... 270s Selecting previously unselected package libxft2:ppc64el. 270s Preparing to unpack .../36-libxft2_2.3.6-1build2_ppc64el.deb ... 270s Unpacking libxft2:ppc64el (2.3.6-1build2) ... 270s Selecting previously unselected package libxss1:ppc64el. 270s Preparing to unpack .../37-libxss1_1%3a1.2.3-1build4_ppc64el.deb ... 270s Unpacking libxss1:ppc64el (1:1.2.3-1build4) ... 270s Selecting previously unselected package libtk8.6:ppc64el. 270s Preparing to unpack .../38-libtk8.6_8.6.17-1_ppc64el.deb ... 270s Unpacking libtk8.6:ppc64el (8.6.17-1) ... 270s Selecting previously unselected package libxt6t64:ppc64el. 270s Preparing to unpack .../39-libxt6t64_1%3a1.2.1-1.3_ppc64el.deb ... 270s Unpacking libxt6t64:ppc64el (1:1.2.1-1.3) ... 270s Selecting previously unselected package zip. 270s Preparing to unpack .../40-zip_3.0-15ubuntu3_ppc64el.deb ... 270s Unpacking zip (3.0-15ubuntu3) ... 270s Selecting previously unselected package unzip. 270s Preparing to unpack .../41-unzip_6.0-29ubuntu1_ppc64el.deb ... 270s Unpacking unzip (6.0-29ubuntu1) ... 270s Selecting previously unselected package xdg-utils. 270s Preparing to unpack .../42-xdg-utils_1.2.1-2ubuntu2_all.deb ... 270s Unpacking xdg-utils (1.2.1-2ubuntu2) ... 270s Selecting previously unselected package r-base-core. 270s Preparing to unpack .../43-r-base-core_4.5.2-1ubuntu2_ppc64el.deb ... 270s Unpacking r-base-core (4.5.2-1ubuntu2) ... 270s Selecting previously unselected package r-bioc-biocgenerics. 270s Preparing to unpack .../44-r-bioc-biocgenerics_0.52.0-2_all.deb ... 270s Unpacking r-bioc-biocgenerics (0.52.0-2) ... 270s Selecting previously unselected package r-cran-r.methodss3. 270s Preparing to unpack .../45-r-cran-r.methodss3_1.8.2-1_all.deb ... 270s Unpacking r-cran-r.methodss3 (1.8.2-1) ... 270s Selecting previously unselected package r-cran-r.oo. 270s Preparing to unpack .../46-r-cran-r.oo_1.27.1-1_all.deb ... 270s Unpacking r-cran-r.oo (1.27.1-1) ... 270s Selecting previously unselected package r-cran-r.utils. 270s Preparing to unpack .../47-r-cran-r.utils_2.13.0-1_all.deb ... 270s Unpacking r-cran-r.utils (2.13.0-1) ... 270s Selecting previously unselected package r-cran-matrixstats. 270s Preparing to unpack .../48-r-cran-matrixstats_1.5.0-1_ppc64el.deb ... 270s Unpacking r-cran-matrixstats (1.5.0-1) ... 270s Selecting previously unselected package r-bioc-aroma.light. 271s Preparing to unpack .../49-r-bioc-aroma.light_3.36.0-2_all.deb ... 271s Unpacking r-bioc-aroma.light (3.36.0-2) ... 271s Selecting previously unselected package r-bioc-dnacopy. 271s Preparing to unpack .../50-r-bioc-dnacopy_1.80.0-2_ppc64el.deb ... 271s Unpacking r-bioc-dnacopy (1.80.0-2) ... 271s Selecting previously unselected package r-cran-base64enc. 271s Preparing to unpack .../51-r-cran-base64enc_0.1-3-3build1_ppc64el.deb ... 271s Unpacking r-cran-base64enc (0.1-3-3build1) ... 271s Selecting previously unselected package r-cran-cli. 271s Preparing to unpack .../52-r-cran-cli_3.6.4-1_ppc64el.deb ... 271s Unpacking r-cran-cli (3.6.4-1) ... 271s Selecting previously unselected package r-cran-codetools. 271s Preparing to unpack .../53-r-cran-codetools_0.2-20-1build1_all.deb ... 271s Unpacking r-cran-codetools (0.2-20-1build1) ... 271s Selecting previously unselected package r-cran-digest. 271s Preparing to unpack .../54-r-cran-digest_0.6.39-1_ppc64el.deb ... 271s Unpacking r-cran-digest (0.6.39-1) ... 271s Selecting previously unselected package r-cran-farver. 271s Preparing to unpack .../55-r-cran-farver_2.1.2-1_ppc64el.deb ... 271s Unpacking r-cran-farver (2.1.2-1) ... 271s Selecting previously unselected package r-cran-globals. 271s Preparing to unpack .../56-r-cran-globals_0.19.0-1_all.deb ... 271s Unpacking r-cran-globals (0.19.0-1) ... 271s Selecting previously unselected package r-cran-listenv. 271s Preparing to unpack .../57-r-cran-listenv_0.10.0+dfsg-1_all.deb ... 271s Unpacking r-cran-listenv (0.10.0+dfsg-1) ... 271s Selecting previously unselected package r-cran-parallelly. 271s Preparing to unpack .../58-r-cran-parallelly_1.42.0-1_ppc64el.deb ... 271s Unpacking r-cran-parallelly (1.42.0-1) ... 271s Selecting previously unselected package r-cran-future. 271s Preparing to unpack .../59-r-cran-future_1.34.0+dfsg-1_all.deb ... 271s Unpacking r-cran-future (1.34.0+dfsg-1) ... 271s Selecting previously unselected package r-cran-glue. 271s Preparing to unpack .../60-r-cran-glue_1.8.0-1_ppc64el.deb ... 271s Unpacking r-cran-glue (1.8.0-1) ... 271s Selecting previously unselected package r-cran-rlang. 271s Preparing to unpack .../61-r-cran-rlang_1.1.5-3_ppc64el.deb ... 271s Unpacking r-cran-rlang (1.1.5-3) ... 271s Selecting previously unselected package r-cran-lifecycle. 271s Preparing to unpack .../62-r-cran-lifecycle_1.0.5+dfsg-1_all.deb ... 271s Unpacking r-cran-lifecycle (1.0.5+dfsg-1) ... 271s Selecting previously unselected package r-cran-gtable. 271s Preparing to unpack .../63-r-cran-gtable_0.3.6+dfsg-1_all.deb ... 271s Unpacking r-cran-gtable (0.3.6+dfsg-1) ... 271s Selecting previously unselected package r-cran-isoband. 271s Preparing to unpack .../64-r-cran-isoband_0.2.7-1_ppc64el.deb ... 271s Unpacking r-cran-isoband (0.2.7-1) ... 271s Selecting previously unselected package r-cran-s7. 271s Preparing to unpack .../65-r-cran-s7_0.2.0-1_ppc64el.deb ... 271s Unpacking r-cran-s7 (0.2.0-1) ... 271s Selecting previously unselected package r-cran-labeling. 271s Preparing to unpack .../66-r-cran-labeling_0.4.3-1_all.deb ... 271s Unpacking r-cran-labeling (0.4.3-1) ... 271s Selecting previously unselected package r-cran-r6. 271s Preparing to unpack .../67-r-cran-r6_2.6.1-1_all.deb ... 271s Unpacking r-cran-r6 (2.6.1-1) ... 271s Selecting previously unselected package r-cran-rcolorbrewer. 271s Preparing to unpack .../68-r-cran-rcolorbrewer_1.1-3-1build2_all.deb ... 271s Unpacking r-cran-rcolorbrewer (1.1-3-1build2) ... 271s Selecting previously unselected package r-cran-viridislite. 271s Preparing to unpack .../69-r-cran-viridislite_0.4.3-1_all.deb ... 271s Unpacking r-cran-viridislite (0.4.3-1) ... 271s Selecting previously unselected package r-cran-scales. 271s Preparing to unpack .../70-r-cran-scales_1.4.0-1_all.deb ... 271s Unpacking r-cran-scales (1.4.0-1) ... 271s Selecting previously unselected package r-cran-vctrs. 271s Preparing to unpack .../71-r-cran-vctrs_0.6.5-1_ppc64el.deb ... 271s Unpacking r-cran-vctrs (0.6.5-1) ... 271s Selecting previously unselected package r-cran-withr. 271s Preparing to unpack .../72-r-cran-withr_3.0.2+dfsg-1_all.deb ... 271s Unpacking r-cran-withr (3.0.2+dfsg-1) ... 271s Selecting previously unselected package r-cran-ggplot2. 271s Preparing to unpack .../73-r-cran-ggplot2_4.0.2+dfsg-1_all.deb ... 271s Unpacking r-cran-ggplot2 (4.0.2+dfsg-1) ... 271s Selecting previously unselected package r-cran-r.cache. 271s Preparing to unpack .../74-r-cran-r.cache_0.17.0-1_all.deb ... 271s Unpacking r-cran-r.cache (0.17.0-1) ... 271s Selecting previously unselected package r-cran-pscbs. 271s Preparing to unpack .../75-r-cran-pscbs_0.68.0-1_all.deb ... 271s Unpacking r-cran-pscbs (0.68.0-1) ... 271s Selecting previously unselected package r-cran-r.devices. 271s Preparing to unpack .../76-r-cran-r.devices_2.17.3+ds-1_all.deb ... 271s Unpacking r-cran-r.devices (2.17.3+ds-1) ... 271s Selecting previously unselected package tcl8.6. 271s Preparing to unpack .../77-tcl8.6_8.6.17+dfsg-1build1_ppc64el.deb ... 271s Unpacking tcl8.6 (8.6.17+dfsg-1build1) ... 271s Selecting previously unselected package tcl. 271s Preparing to unpack .../78-tcl_8.6.16build1_ppc64el.deb ... 271s Unpacking tcl (8.6.16build1) ... 271s Selecting previously unselected package r-cran-r.rsp. 271s Preparing to unpack .../79-r-cran-r.rsp_0.46.0+ds-1_all.deb ... 271s Unpacking r-cran-r.rsp (0.46.0+ds-1) ... 271s Setting up libgraphite2-3:ppc64el (1.3.14-11ubuntu1) ... 271s Setting up libpixman-1-0:ppc64el (0.46.4-1) ... 271s Setting up libsharpyuv0:ppc64el (1.5.0-0.1build1) ... 271s Setting up liblerc4:ppc64el (4.0.0+ds-5ubuntu2) ... 271s Setting up libxrender1:ppc64el (1:0.9.12-1) ... 271s Setting up libdatrie1:ppc64el (0.2.14-1) ... 271s Setting up libxcb-render0:ppc64el (1.17.0-2ubuntu1) ... 271s Setting up unzip (6.0-29ubuntu1) ... 271s Setting up x11-common (1:7.7+24ubuntu1) ... 272s Setting up libdeflate0:ppc64el (1.23-2build1) ... 272s Setting up libxcb-shm0:ppc64el (1.17.0-2ubuntu1) ... 272s Setting up libgomp1:ppc64el (15.2.0-12ubuntu1) ... 272s Setting up libjbig0:ppc64el (2.1-6.1ubuntu3) ... 272s Setting up zip (3.0-15ubuntu3) ... 272s Setting up libblas3:ppc64el (3.12.1-7ubuntu1) ... 272s update-alternatives: using /usr/lib/powerpc64le-linux-gnu/blas/libblas.so.3 to provide /usr/lib/powerpc64le-linux-gnu/libblas.so.3 (libblas.so.3-powerpc64le-linux-gnu) in auto mode 272s Setting up fonts-dejavu-mono (2.37-8build1) ... 272s Setting up libtcl8.6:ppc64el (8.6.17+dfsg-1build1) ... 272s Setting up fonts-dejavu-core (2.37-8build1) ... 272s Setting up libjpeg-turbo8:ppc64el (2.1.5-4ubuntu3) ... 272s Setting up libgfortran5:ppc64el (15.2.0-12ubuntu1) ... 272s Setting up libwebp7:ppc64el (1.5.0-0.1build1) ... 272s Setting up libharfbuzz0b:ppc64el (12.3.2-1) ... 272s Setting up libthai-data (0.1.30-1) ... 272s Setting up libxss1:ppc64el (1:1.2.3-1build4) ... 272s Setting up libpaper2:ppc64el (2.2.5-0.3build1) ... 272s Setting up xdg-utils (1.2.1-2ubuntu2) ... 272s update-alternatives: using /usr/bin/xdg-open to provide /usr/bin/open (open) in auto mode 272s Setting up libjpeg8:ppc64el (8c-2ubuntu11) ... 272s Setting up libice6:ppc64el (2:1.1.1-1build1) ... 272s Setting up tcl8.6 (8.6.17+dfsg-1build1) ... 272s Setting up liblapack3:ppc64el (3.12.1-7ubuntu1) ... 272s update-alternatives: using /usr/lib/powerpc64le-linux-gnu/lapack/liblapack.so.3 to provide /usr/lib/powerpc64le-linux-gnu/liblapack.so.3 (liblapack.so.3-powerpc64le-linux-gnu) in auto mode 272s Setting up fontconfig-config (2.17.1-3ubuntu1) ... 272s Setting up libpaper-utils (2.2.5-0.3build1) ... 272s Setting up libthai0:ppc64el (0.1.30-1) ... 272s Setting up libtiff6:ppc64el (4.7.0-3ubuntu3) ... 272s Setting up tcl (8.6.16build1) ... 272s Setting up libfontconfig1:ppc64el (2.17.1-3ubuntu1) ... 272s Setting up libsm6:ppc64el (2:1.2.6-1build1) ... 272s Setting up fontconfig (2.17.1-3ubuntu1) ... 274s Regenerating fonts cache... done. 274s Setting up libxft2:ppc64el (2.3.6-1build2) ... 274s Setting up libtk8.6:ppc64el (8.6.17-1) ... 274s Setting up libpango-1.0-0:ppc64el (1.57.0-1) ... 274s Setting up libcairo2:ppc64el (1.18.4-3) ... 274s Setting up libxt6t64:ppc64el (1:1.2.1-1.3) ... 274s Setting up libpangoft2-1.0-0:ppc64el (1.57.0-1) ... 274s Setting up libpangocairo-1.0-0:ppc64el (1.57.0-1) ... 274s Setting up r-base-core (4.5.2-1ubuntu2) ... 274s Creating config file /etc/R/Renviron with new version 275s Setting up r-cran-labeling (0.4.3-1) ... 275s Setting up r-cran-farver (2.1.2-1) ... 275s Setting up r-cran-viridislite (0.4.3-1) ... 275s Setting up r-cran-r6 (2.6.1-1) ... 275s Setting up r-cran-codetools (0.2-20-1build1) ... 275s Setting up r-bioc-biocgenerics (0.52.0-2) ... 275s Setting up r-cran-rlang (1.1.5-3) ... 275s Setting up r-cran-matrixstats (1.5.0-1) ... 275s Setting up r-cran-listenv (0.10.0+dfsg-1) ... 275s Setting up r-cran-withr (3.0.2+dfsg-1) ... 275s Setting up r-cran-base64enc (0.1-3-3build1) ... 275s Setting up r-cran-digest (0.6.39-1) ... 275s Setting up r-cran-glue (1.8.0-1) ... 275s Setting up r-cran-cli (3.6.4-1) ... 275s 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275s Processing triggers for man-db (2.13.1-1build1) ... 275s Processing triggers for install-info (7.2-5) ... 276s autopkgtest [23:41:54]: test run-unit-test: [----------------------- 277s + pkg=r-cran-pscbs 277s + [ /tmp/autopkgtest.AbkJ6s/autopkgtest_tmp = ] 277s + cd /tmp/autopkgtest.AbkJ6s/autopkgtest_tmp 277s + 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.AbkJ6s/autopkgtest_tmp 277s + find . -name *.gz -exec gunzip {} ; 277s + export LC_ALL=C 277s + dpkg-architecture -qDEB_HOST_ARCH 277s dpkg-architecture: warning: cannot determine CC system type, falling back to default (native compilation) 277s Begin test PairedPSCBS,boot 277s + hostarch=ppc64el 277s + [ ppc64el = armhf ] 277s + ls+ PairedPSCBS,boot.Rsed s/\.R$// 277s findLargeGaps.R randomSeed.R segmentByCBS,bug67.R segmentByCBS,calls.R segmentByCBS,futures.R segmentByCBS,median.R segmentByCBS,prune.R segmentByCBS,report.R segmentByCBS,shiftTCN.R segmentByCBS,weights.R segmentByCBS.R segmentByNonPairedPSCBS,medianDH.R segmentByPairedPSCBS,DH.R segmentByPairedPSCBS,calls.R segmentByPairedPSCBS,futures.R segmentByPairedPSCBS,noNormalBAFs.R segmentByPairedPSCBS,report.R segmentByPairedPSCBS,seqOfSegmentsByDP.R segmentByPairedPSCBS.R 277s + echo Begin test PairedPSCBS,boot 277s + exitcode=0 277s + R CMD BATCH PairedPSCBS,boot.R 280s + cat PairedPSCBS,boot.Rout 280s 280s R version 4.5.2 (2025-10-31) -- "[Not] Part in a Rumble" 280s Copyright (C) 2025 The R Foundation for Statistical Computing 280s Platform: powerpc64le-unknown-linux-gnu 280s 280s R is free software and comes with ABSOLUTELY NO WARRANTY. 280s You are welcome to redistribute it under certain conditions. 280s Type 'license()' or 'licence()' for distribution details. 280s 280s R is a collaborative project with many contributors. 280s Type 'contributors()' for more information and 280s 'citation()' on how to cite R or R packages in publications. 280s 280s Type 'demo()' for some demos, 'help()' for on-line help, or 280s 'help.start()' for an HTML browser interface to help. 280s Type 'q()' to quit R. 280s 280s > ########################################################### 280s > # This tests: 280s > # - Bootstrapping for PairedPSCBS objects 280s > ########################################################### 280s > library("PSCBS") 280s PSCBS v0.68.0 (2025-04-18 19:40:02 UTC) successfully loaded. See ?PSCBS for help. 280s > 280s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 280s > # Load SNP microarray data 280s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 280s > data <- PSCBS::exampleData("paired.chr01") 280s > 280s > 280s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 280s > # Paired PSCBS segmentation 280s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 280s > # Drop single-locus outliers 280s > dataS <- dropSegmentationOutliers(data) 280s > dataS <- dataS[seq(from=1, to=nrow(data), by=5),] 280s > nSegs <- 4L 280s > str(dataS) 280s 'data.frame': 14670 obs. of 6 variables: 280s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 280s $ x : int 1145994 2941694 3710825 4240737 4276892 4464544 4714611 5095111 5034491 5158416 ... 280s $ CT : num 1.63 1.4 1.41 1.17 1.16 ... 280s $ betaT : num 0.7574 0.169 0.2357 0.2604 0.0576 ... 280s $ CN : num 2.36 2.13 2.26 2.01 2.32 ... 280s $ betaN : num 0.8274 0.5072 0.1671 0.1609 0.0421 ... 280s > # Segment known regions 280s > knownSegments <- data.frame( 280s + chromosome = c( 1, 1, 1), 280s + start = c( -Inf, NA, 141510003), 280s + end = c(120992603, NA, +Inf) 280s + ) 280s > fit <- segmentByPairedPSCBS(dataS, knownSegments=knownSegments, avgDH="median", seed=0xBEEF) 280s > print(fit) 280s chromosome tcnId dhId start end tcnNbrOfLoci tcnMean tcnNbrOfSNPs 280s 1 1 1 1 554484 120992603 7586 1.385258 2108 280s 2 NA 2 1 NA NA NA NA 0 280s 3 1 3 1 141510003 185449813 2681 2.068861 777 280s 4 1 4 1 185449813 247137334 4391 2.634110 1311 280s tcnNbrOfHets dhNbrOfLoci dhMean c1Mean c2Mean 280s 1 2108 2108 0.54551245 0.3147912 1.070467 280s 2 0 0 NA NA NA 280s 3 777 777 0.07132277 0.9606521 1.108209 280s 4 1311 1311 0.21663871 1.0317300 1.602380 280s > 280s > 280s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 280s > # Bootstrap 280s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 280s > B <- 1L 280s > seed <- 0xBEEF 280s > probs <- c(0.025, 0.05, 0.95, 0.975) 280s > 280s > sets <- getBootstrapLocusSets(fit, B=B, seed=seed) 280s > 280s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 280s > # Subset by first segment 280s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 280s > ss <- 1L 280s > 280s > fitT <- extractSegment(fit, ss) 280s > dataT <- getLocusData(fitT) 280s > segsT <- getSegments(fitT) 280s > 280s > # Truth 280s > bootT <- bootstrapSegmentsAndChangepoints(fitT, B=B, seed=seed) 280s > bootT1 <- bootT$segments[1L,,,drop=FALSE] 280s > types <- dimnames(bootT1)[[3L]] 280s > dim(bootT1) <- dim(bootT1)[-1L] 280s > colnames(bootT1) <- types 280s > sumsT <- apply(bootT1, MARGIN=2L, FUN=quantile, probs=probs) 280s > print(sumsT) 280s tcn dh c1 c2 280s 2.5% 1.383213 0.5466788 0.3135198 1.069693 280s 5% 1.383213 0.5466788 0.3135198 1.069693 280s 95% 1.383213 0.5466788 0.3135198 1.069693 280s 97.5% 1.383213 0.5466788 0.3135198 1.069693 280s > 280s > fitTB <- bootstrapTCNandDHByRegion(fitT, B=B, seed=seed) 280s > segsTB <- getSegments(fitTB) 280s > segsTB <- unlist(segsTB[,grep("_", colnames(segsTB))]) 280s > dim(segsTB) <- dim(sumsT) 280s > dimnames(segsTB) <- dimnames(sumsT) 280s > print(segsTB) 280s tcn dh c1 c2 280s 2.5% 1.383213 0.5466788 0.3135198 1.069693 280s 5% 1.383213 0.5466788 0.3135198 1.069693 280s 95% 1.383213 0.5466788 0.3135198 1.069693 280s 97.5% 1.383213 0.5466788 0.3135198 1.069693 280s > 280s > # Sanity check 280s > stopifnot(all.equal(segsTB, sumsT)) 280s > 280s > # Calculate summaries using the existing bootstrap samples 280s > fitTBp <- bootstrapTCNandDHByRegion(fitT, .boot=bootT) 280s > # Sanity check 280s > all.equal(fitTBp, fitTB) 280s [1] "Component \"tcn_2.5%\": Mean relative difference: 0.003070405" 280s [2] "Component \"tcn_5%\": Mean relative difference: 0.002241362" 280s [3] "Component \"tcn_95%\": Mean relative difference: 0.005458479" 280s [4] "Component \"tcn_97.5%\": Mean relative difference: 0.006030363" 280s [5] "Component \"dh_2.5%\": Mean relative difference: 0.02683423" 280s [6] "Component \"dh_5%\": Mean relative difference: 0.02409533" 280s [7] "Component \"dh_95%\": Mean relative difference: 0.0150081" 280s [8] "Component \"dh_97.5%\": Mean relative difference: 0.01826461" 280s [9] "Component \"c1_2.5%\": Mean relative difference: 0.02397349" 280s [10] "Component \"c1_5%\": Mean relative difference: 0.01800948" 280s [11] "Component \"c1_95%\": Mean relative difference: 0.0303456" 280s [12] "Component \"c1_97.5%\": Mean relative difference: 0.03420614" 280s [13] "Component \"c2_2.5%\": Mean relative difference: 0.008723378" 280s [14] "Component \"c2_5%\": Mean relative difference: 0.006834962" 280s [15] "Component \"c2_95%\": Mean relative difference: 0.00741949" 280s [16] "Component \"c2_97.5%\": Mean relative difference: 0.008743911" 280s attr(,"what") 280s [1] "getSegments()" 280s > 280s > 280s > # Bootstrap from scratch 280s > setsT <- getBootstrapLocusSets(fitT, B=B, seed=seed) 280s > lociT <- setsT$locusSet[[1L]]$bootstrap$loci 280s > idxs <- lociT$tcn 280s > tcnT <- array(dataT$CT[idxs], dim=dim(idxs)) 280s > tcnT <- apply(tcnT, MARGIN=2L, FUN=mean, na.rm=TRUE) 280s > idxs <- lociT$dh 280s > dhT <- array(dataT$rho[idxs], dim=dim(idxs)) 280s > dhT <- apply(dhT, MARGIN=2L, FUN=median, na.rm=TRUE) 280s > c1T <- (1-dhT) * tcnT / 2 280s > c2T <- tcnT - c1T 280s > bootT2 <- array(c(tcnT, dhT, c1T, c2T), dim=c(1L, 4L)) 280s > colnames(bootT2) <- colnames(bootT1) 280s > print(bootT2) 280s tcn dh c1 c2 280s [1,] 1.383213 0.5466788 0.3135198 1.069693 280s > 280s > # This comparison is only valid if B == 1L 280s > if (B == 1L) { 280s + # Sanity check 280s + stopifnot(all.equal(bootT2, bootT1)) 280s + } 280s > 280s > proc.time() 280s user system elapsed 280s 2.417 0.071 2.493 280s + [ 0 != 0 ] 280s + echo Test PairedPSCBS,boot passedTest PairedPSCBS,boot passed 280s 0 280s Begin test findLargeGaps 280s 280s + echo 0 280s + echo Begin test findLargeGaps 280s + exitcode=0 280s + R CMD BATCH findLargeGaps.R 280s + cat findLargeGaps.Rout 280s 280s R version 4.5.2 (2025-10-31) -- "[Not] Part in a Rumble" 280s Copyright (C) 2025 The R Foundation for Statistical Computing 280s Platform: powerpc64le-unknown-linux-gnu 280s 280s R is free software and comes with ABSOLUTELY NO WARRANTY. 280s You are welcome to redistribute it under certain conditions. 280s Type 'license()' or 'licence()' for distribution details. 280s 280s R is a collaborative project with many contributors. 280s Type 'contributors()' for more information and 280s 'citation()' on how to cite R or R packages in publications. 280s 280s Type 'demo()' for some demos, 'help()' for on-line help, or 280s 'help.start()' for an HTML browser interface to help. 280s Type 'q()' to quit R. 280s 280s [Previously saved workspace restored] 280s 280s > library("PSCBS") 280s PSCBS v0.68.0 (2025-04-18 19:40:02 UTC) successfully loaded. See ?PSCBS for help. 280s > 280s > # Simulating copy-number data 280s > set.seed(0xBEEF) 280s > 280s > # Simulate CN data 280s > J <- 1000 280s > mu <- double(J) 280s > mu[200:300] <- mu[200:300] + 1 280s > mu[350:400] <- NA # centromere 280s > mu[650:800] <- mu[650:800] - 1 280s > eps <- rnorm(J, sd=1/2) 280s > y <- mu + eps 280s > x <- seq(from=1, to=100e6, length.out=J) 280s > 280s > data <- data.frame(chromosome=0L, x=x) 280s > 280s > gaps <- findLargeGaps(x=x, minLength=1e6) 280s > print(gaps) 280s [1] start end length 280s <0 rows> (or 0-length row.names) 280s > stopifnot(is.data.frame(gaps)) 280s > stopifnot(nrow(gaps) == 0L) 280s > segs <- gapsToSegments(gaps) 280s > print(segs) 280s chromosome start end 280s 1 0 -Inf Inf 280s > stopifnot(is.data.frame(segs)) 280s > stopifnot(nrow(segs) == 1L) 280s > 280s > 280s > gaps <- findLargeGaps(data, minLength=1e6) 280s > print(gaps) 280s [1] chromosome start end 280s <0 rows> (or 0-length row.names) 280s > stopifnot(is.data.frame(gaps)) 280s > stopifnot(nrow(gaps) == 0L) 280s > segs <- gapsToSegments(gaps) 280s > print(segs) 280s chromosome start end 280s 1 0 -Inf Inf 280s > stopifnot(is.data.frame(segs)) 280s > stopifnot(nrow(segs) == 1L) 280s > 280s > 280s > ## Add missing values 280s > data2 <- data 280s > data$x[30e6 < x & x < 50e6] <- NA 280s > gaps <- findLargeGaps(data, minLength=1e6) 280s > print(gaps) 280s chromosome start end length 280s 1 0 29929932 50050050 20120118 280s > stopifnot(is.data.frame(gaps)) 280s > stopifnot(nrow(gaps) == 1L) 280s > segs <- gapsToSegments(gaps) 280s > print(segs) 280s chromosome start end length 280s 1 0 -Inf 29929931 Inf 280s 2 0 29929932 50050050 20120118 280s 3 0 50050051 Inf Inf 280s > stopifnot(is.data.frame(segs)) 280s > stopifnot(nrow(segs) == 3L) 280s > 280s > 280s > 280s > # BUG FIX: Issue #6 280s > gaps <- findLargeGaps(chromosome=rep(1,10), x=1:10, minLength=2) 280s > print(gaps) 280s [1] chromosome start end 280s <0 rows> (or 0-length row.names) 280s > stopifnot(is.data.frame(gaps)) 280s > stopifnot(nrow(gaps) == 0L) 280s > # BUG FIX: Issue #9 280s > segs <- gapsToSegments(gaps) 280s > print(segs) 280s chromosome start end 280s 1 0 -Inf Inf 280s > stopifnot(is.data.frame(segs)) 280s > stopifnot(nrow(segs) == 1L) 280s > 280s > 280s > # BUG FIX: PSCBS GitHub Issue #8 280s > gaps <- try({ 280s + findLargeGaps(chromosome=rep(1,3), x=as.numeric(1:3), minLength=1) 280s + }) 280s Error in findLargeGaps.default(chromosome = rep(1, 3), x = as.numeric(1:3), : 280s Cannot identify large gaps. Argument 'resolution' (=1) is not strictly smaller than 'minLength' (=1). 280s > stopifnot(inherits(gaps, "try-error")) 280s > 280s > proc.time() 280s user system elapsed 280s 0.404 0.028 0.425 280s Test findLargeGaps passed 280s 0 280s Begin test randomSeed 280s + [ 0 != 0 ] 280s + echo Test findLargeGaps passed 280s + echo 0 280s + echo Begin test randomSeed 280s + exitcode=0 280s + R CMD BATCH randomSeed.R 281s + cat randomSeed.Rout 281s R version 4.5.2 (2025-10-31) -- "[Not] Part in a Rumble" 281s Copyright (C) 2025 The R Foundation for Statistical Computing 281s Platform: powerpc64le-unknown-linux-gnu 281s 281s R is free software and comes with ABSOLUTELY NO WARRANTY. 281s You are welcome to redistribute it under certain conditions. 281s Type 'license()' or 'licence()' for distribution details. 281s 281s R is a collaborative project with many contributors. 281s Type 'contributors()' for more information and 281s 'citation()' on how to cite R or R packages in publications. 281s 281s Type 'demo()' for some demos, 'help()' for on-line help, or 281s 'help.start()' for an HTML browser interface to help. 281s Type 'q()' to quit R. 281s 281s [Previously saved workspace restored] 281s 281s > library("PSCBS") 281s PSCBS v0.68.0 (2025-04-18 19:40:02 UTC) successfully loaded. See ?PSCBS for help. 281s > 281s > message("*** randomSeed() - setup ...") 281s *** randomSeed() - setup ... 281s > ovars <- ls(envir=globalenv()) 281s > genv <- globalenv() 281s > RNGkind("Mersenne-Twister") 281s > if (exists(".Random.seed", envir=genv, inherits=FALSE)) 281s + rm(list=".Random.seed", envir=genv, inherits=FALSE) 281s > seed0 <- genv$.Random.seed 281s > stopifnot(is.null(seed0)) 281s > okind0 <- RNGkind()[1L] 281s > 281s > sample1 <- function() { sample(0:9, size=1L) } 281s > message("*** randomSeed() - setup ... done") 281s *** randomSeed() - setup ... done 281s > 281s > 281s > message("*** randomSeed('get') ...") 281s *** randomSeed('get') ... 281s > ## Get random seed 281s > seed <- randomSeed("get") 281s > stopifnot(identical(seed, seed0)) 281s > 281s > ## Repeat after new sample 281s > y1 <- sample1() 281s > message(sprintf("Random number: %d", y1)) 281s Random number: 4 281s > seed1 <- randomSeed("get") 281s > stopifnot(!identical(seed1, seed0)) 281s > message("*** randomSeed('get') ... done") 281s *** randomSeed('get') ... done 281s > 281s > 281s > message("*** randomSeed('set', 42L) ...") 281s *** randomSeed('set', 42L) ... 281s > randomSeed("set", seed=42L) 281s > seed2 <- randomSeed("get") 281s > stopifnot(!identical(seed2, seed1)) 281s > 281s > y2 <- sample1() 281s > message(sprintf("Random number: %d (with random seed = 42L)", y2)) 281s Random number: 0 (with random seed = 42L) 281s > 281s > ## Reset to previous state 281s > randomSeed("reset") 281s > seed3 <- randomSeed("get") 281s > stopifnot(identical(seed3, seed1)) 281s > stopifnot(identical(RNGkind()[1L], okind0), 281s + identical(randomSeed("get"), seed1)) 281s > message("*** randomSeed('set', 42L) ... done") 281s *** randomSeed('set', 42L) ... done 281s > 281s > 281s > message("*** randomSeed('set', NULL) ...") 281s *** randomSeed('set', NULL) ... 281s > randomSeed("set", seed=NULL) 281s > seed4 <- randomSeed("get") 281s > stopifnot(is.null(seed4)) 281s > 281s > y3 <- sample1() 281s > message(sprintf("Random number: %d", y3)) 281s Random number: 7 281s > 281s > message("*** randomSeed('set', NULL) ... done") 281s *** randomSeed('set', NULL) ... done 281s > 281s > 281s > message("*** randomSeed('set', 42L) again ...") 281s *** randomSeed('set', 42L) again ... 281s > seed5 <- randomSeed("get") 281s > randomSeed("set", seed=42L) 281s > y4 <- sample1() 281s > message(sprintf("Random number: %d (with random seed = 42L)", y4)) 281s Random number: 0 (with random seed = 42L) 281s > stopifnot(identical(y4, y2)) 281s > 281s > randomSeed("reset") 281s > stopifnot(identical(RNGkind()[1L], okind0), 281s + identical(randomSeed("get"), seed5)) 281s > message("*** randomSeed('set', 42L) again ... done") 281s *** randomSeed('set', 42L) again ... done 281s > 281s > 281s > 281s > ## L'Ecuyer-CMRG: Random number generation for parallel processing 281s > message("*** randomSeed(): L'Ecuyer-CMRG stream ...") 281s *** randomSeed(): L'Ecuyer-CMRG stream ... 281s > 281s > okind <- RNGkind()[1L] 281s > stopifnot(identical(okind, okind0)) 281s > 281s > randomSeed("set", seed=NULL) 281s > oseed <- randomSeed("get") 281s > stopifnot(is.null(oseed)) 281s > 281s > randomSeed("set", seed=42L, kind="L'Ecuyer-CMRG") 281s > oseed2 <- randomSeed("reset") 281s > str(oseed2) 281s NULL 281s > stopifnot(identical(oseed2, oseed)) 281s > stopifnot(identical(RNGkind()[1L], okind), 281s + identical(randomSeed("get"), oseed)) 281s > 281s > randomSeed("set", seed=42L, kind="L'Ecuyer-CMRG") 281s > seed0 <- randomSeed("get") 281s > seeds0 <- lapply(1:10, FUN=function(i) randomSeed("advance")) 281s > oseed2 <- randomSeed("reset") 281s > stopifnot(identical(oseed2, oseed)) 281s > stopifnot(identical(RNGkind()[1L], okind), 281s + identical(randomSeed("get"), oseed)) 281s > 281s > 281s > ## Assert reproducible .Random.seed stream 281s > randomSeed("set", seed=42L, kind="L'Ecuyer-CMRG") 281s > seed1 <- randomSeed("get") 281s > seeds1 <- lapply(1:10, FUN=function(i) randomSeed("advance")) 281s > stopifnot(identical(seed1, seed0)) 281s > stopifnot(identical(seeds1, seeds0)) 281s > 281s > randomSeed("reset") 281s > stopifnot(identical(RNGkind()[1L], okind), 281s + identical(randomSeed("get"), oseed)) 281s > 281s > randomSeed("set", seed=42L, kind="L'Ecuyer-CMRG") 281s > seeds2 <- randomSeed("advance", n=10L) 281s > stopifnot(identical(seeds2, seeds0)) 281s > 281s > randomSeed("reset") 281s > stopifnot(identical(RNGkind()[1L], okind), 281s + identical(randomSeed("get"), oseed)) 281s > 281s > randomSeed("set", seed=seeds2[[1]], kind="L'Ecuyer-CMRG") 281s > randomSeed("reset") 281s > stopifnot(identical(RNGkind()[1L], okind), 281s + identical(randomSeed("get"), oseed)) 281s > 281s > randomSeed("set", seed=42L, kind="L'Ecuyer-CMRG") 281s > y0 <- sapply(1:10, FUN=function(ii) { 281s + randomSeed("advance") 281s + sample1() 281s + }) 281s > print(y0) 281s [1] 6 9 6 9 9 9 0 7 6 5 281s > randomSeed("reset") 281s > 281s > randomSeed("set", seed=42L, kind="L'Ecuyer-CMRG") 281s > y1 <- sapply(1:10, FUN=function(ii) { 281s + randomSeed("advance") 281s + sample1() 281s + }) 281s > print(y1) 281s [1] 6 9 6 9 9 9 0 7 6 5 281s > stopifnot(identical(y1, y0)) 281s > randomSeed("reset") 281s > 281s > stopifnot(identical(RNGkind()[1L], okind)) 281s > 281s > message("*** randomSeed(): L'Ecuyer-CMRG stream ... done") 281s *** randomSeed(): L'Ecuyer-CMRG stream ... done 281s > 281s > 281s > ## Cleanup 281s > message("*** randomSeed() - cleanup ...") 281s *** randomSeed() - cleanup ... 281s > genv <- globalenv() 281s > RNGkind("Mersenne-Twister") 281s > if (exists(".Random.seed", envir=genv, inherits=FALSE)) 281s + rm(list=".Random.seed", envir=genv, inherits=FALSE) 281s > rm(list=ovars, envir=globalenv()) 281s > message("*** randomSeed() - cleanup ... done") 281s *** randomSeed() - cleanup ... done 281s > 281s > proc.time() 281s user system elapsed 281s 0.359 0.020 0.370 281s Test randomSeed passed 281s 0 281s Begin test segmentByCBS,bug67 281s 281s + [ 0 != 0 ] 281s + echo Test randomSeed passed 281s + echo 0 281s + echo Begin test segmentByCBS,bug67 281s + exitcode=0 281s + R CMD BATCH segmentByCBS,bug67.R 282s + cat segmentByCBS,bug67.Rout 282s 282s R version 4.5.2 (2025-10-31) -- "[Not] Part in a Rumble" 282s Copyright (C) 2025 The R Foundation for Statistical Computing 282s Platform: powerpc64le-unknown-linux-gnu 282s 282s R is free software and comes with ABSOLUTELY NO WARRANTY. 282s You are welcome to redistribute it under certain conditions. 282s Type 'license()' or 'licence()' for distribution details. 282s 282s R is a collaborative project with many contributors. 282s Type 'contributors()' for more information and 282s 'citation()' on how to cite R or R packages in publications. 282s 282s Type 'demo()' for some demos, 'help()' for on-line help, or 282s 'help.start()' for an HTML browser interface to help. 282s Type 'q()' to quit R. 282s 282s [Previously saved workspace restored] 282s 282s > set.seed(0xBEEF) 282s > 282s > # Number of loci 282s > J <- 1000 282s > 282s > mu <- double(J) 282s > mu[200:300] <- mu[200:300] + 1 282s > mu[350:400] <- NA_real_ # centromere 282s > mu[650:800] <- mu[650:800] - 1 282s > eps <- rnorm(J, sd=1/2) 282s > y <- mu + eps 282s > x <- sort(runif(length(y), max=length(y))) * 1e5 282s > 282s > knownSegments <- data.frame( 282s + chromosome=c( 0, 0), 282s + start =x[c( 1, 401)], 282s + end =x[c(349, J)] 282s + ) 282s > 282s > fit2 <- PSCBS::segmentByCBS(y, x=x, knownSegments=knownSegments) 282s > 282s > proc.time() 282s user system elapsed 282s 0.613 0.025 0.629 282s Test segmentByCBS,bug67 passed 282s 0 282s Begin test segmentByCBS,calls 282s + [ 0 != 0 ] 282s + echo Test segmentByCBS,bug67 passed 282s + echo 0 282s + echo Begin test segmentByCBS,calls 282s + exitcode=0 282s + R CMD BATCH segmentByCBS,calls.R 282s 282s R version 4.5.2 (2025-10-31) -- "[Not] Part in a Rumble" 282s Copyright (C) 2025 The R Foundation for Statistical Computing 282s Platform: powerpc64le-unknown-linux-gnu 282s 282s R is free software and comes with ABSOLUTELY NO WARRANTY. 282s You are welcome to redistribute it under certain conditions. 282s Type 'license()' or 'licence()' for distribution details. 282s 282s R is a collaborative project with many contributors. 282s Type 'contributors()' for more information and 282s 'citation()' on how to cite R or R packages in publications. 282s 282s Type 'demo()' for some demos, 'help()' for on-line help, or 282s 'help.start()' for an HTML browser interface to help. 282s Type 'q()' to quit R. 282s 282s [Previously saved workspace restored] 282s 282s > # This test script calls a report generator which requires 282s > # the 'ggplot2' package, which in turn will require packages 282s > # 'colorspace', 'dichromat', 'munsell', 'reshape2' and 'scales'. 282s > 282s > # Only run this test in full testing mode 282s > if (Sys.getenv("_R_CHECK_FULL_") != "") { 282s + library("PSCBS") 282s + stext <- R.utils::stext 282s + 282s + # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 282s + # Load SNP microarray data 282s + # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 282s + data <- PSCBS::exampleData("paired.chr01") 282s + str(data) 282s + 282s + data <- data.frame(chromosome=data$chromosome, x=data$x, y=data$CT) 282s + 282s + 282s + # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 282s + # CBS segmentation 282s + # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 282s + # Drop single-locus outliers 282s + dataS <- dropSegmentationOutliers(data) 282s + 282s + # Speed up example by segmenting fewer loci 282s + dataS <- dataS[seq(from=1, to=nrow(data), by=5),] 282s + 282s + str(dataS) 282s + 282s + gaps <- findLargeGaps(dataS, minLength=2e6) 282s + knownSegments <- gapsToSegments(gaps) 282s + 282s + # CBS segmentation 282s + fit <- segmentByCBS(dataS, knownSegments=knownSegments, 282s + seed=0xBEEF, verbose=-10) 282s + signalType(fit) <- "ratio" 282s + plotTracks(fit) 282s + 282s + 282s + # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 282s + # Call using the UCSF MAD caller (not recommended) 282s + # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 282s + fitC <- callGainsAndLosses(fit) 282s + plotTracks(fitC) 282s + pars <- fitC$params$callGainsAndLosses 282s + stext(side=3, pos=1/2, line=-1, substitute(sigma==x, list(x=sprintf("%.2f", pars$sigmaMAD)))) 282s + mu <- pars$muR 282s + tau <- unlist(pars[c("tauLoss", "tauGain")], use.names=FALSE) 282s + abline(h=mu, lty=2, lwd=2) 282s + abline(h=tau, lwd=2) 282s + mtext(side=4, at=tau[1], expression(Delta[LOSS]), adj=-0.2, cex=0.7, las=2, xpd=TRUE) 282s + mtext(side=4, at=tau[2], expression(Delta[GAIN]), adj=-0.2, cex=0.7, las=2, xpd=TRUE) 282s + title(main="CN caller: \"ucsf-mad\"") 282s + 282s + 282s + # Caller to be implemented 282s + deltaCN <- estimateDeltaCN(fit) 282s + tau <- mu + 1/2*c(-1,+1)*deltaCN 282s + abline(h=tau, lty=2, lwd=1, col="red") 282s + 282s + 282s + 282s + } # if (Sys.getenv("_R_CHECK_FULL_")) 282s > 282s > proc.time() 282s user system elapsed 282s 0.136 0.009 0.137 282s Test segmentByCBS,calls passed 282s 0 282s Begin test segmentByCBS,futures 282s + cat segmentByCBS,calls.Rout 282s + [ 0 != 0 ] 282s + echo Test segmentByCBS,calls passed 282s + echo 0 282s + echo Begin test segmentByCBS,futures 282s + exitcode=0 282s + R CMD BATCH segmentByCBS,futures.R 286s + cat segmentByCBS,futures.Rout 286s 286s R version 4.5.2 (2025-10-31) -- "[Not] Part in a Rumble" 286s Copyright (C) 2025 The R Foundation for Statistical Computing 286s Platform: powerpc64le-unknown-linux-gnu 286s 286s R is free software and comes with ABSOLUTELY NO WARRANTY. 286s You are welcome to redistribute it under certain conditions. 286s Type 'license()' or 'licence()' for distribution details. 286s 286s R is a collaborative project with many contributors. 286s Type 'contributors()' for more information and 286s 'citation()' on how to cite R or R packages in publications. 286s 286s Type 'demo()' for some demos, 'help()' for on-line help, or 286s 'help.start()' for an HTML browser interface to help. 286s Type 'q()' to quit R. 286s 286s [Previously saved workspace restored] 286s 286s > library("PSCBS") 286s PSCBS v0.68.0 (2025-04-18 19:40:02 UTC) successfully loaded. See ?PSCBS for help. 286s > 286s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 286s > # Simulating copy-number data 286s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 286s > set.seed(0xBEEF) 286s > 286s > # Number of loci 286s > J <- 1000 286s > 286s > mu <- double(J) 286s > mu[200:300] <- mu[200:300] + 1 286s > mu[350:400] <- NA # centromere 286s > mu[650:800] <- mu[650:800] - 1 286s > eps <- rnorm(J, sd=1/2) 286s > y <- mu + eps 286s > x <- sort(runif(length(y), max=length(y))) * 1e5 286s > w <- runif(J) 286s > w[650:800] <- 0.001 286s > 286s > ## Create multiple chromosomes 286s > data <- knownSegments <- list() 286s > for (cc in 1:3) { 286s + data[[cc]] <- data.frame(chromosome=cc, y=y, x=x) 286s + knownSegments[[cc]] <- data.frame( 286s + chromosome=c( cc, cc, cc), 286s + start =x[c( 1, 350, 401)], 286s + end =x[c(349, 400, J)] 286s + ) 286s + } 286s > data <- Reduce(rbind, data) 286s > str(data) 286s 'data.frame': 3000 obs. of 3 variables: 286s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 286s $ y : num 0.295 0.115 -0.194 -0.392 -0.518 ... 286s $ x : num 55168 593204 605649 630624 746896 ... 286s > knownSegments <- Reduce(rbind, knownSegments) 286s > str(knownSegments) 286s 'data.frame': 9 obs. of 3 variables: 286s $ chromosome: int 1 1 1 2 2 2 3 3 3 286s $ start : num 55168 34194740 41080533 55168 34194740 ... 286s $ end : num 34142178 41044125 99910827 34142178 41044125 ... 286s > 286s > message("*** segmentByCBS() via futures ...") 286s *** segmentByCBS() via futures ... 286s > 286s > 286s > message("*** segmentByCBS() via futures with 'future' attached ...") 286s *** segmentByCBS() via futures with 'future' attached ... 286s > library("future") 286s > oplan <- plan() 286s > 286s > strategies <- c("sequential", "multisession") 286s > 286s > ## Test 'future.batchtools' futures? 286s > pkg <- "future.batchtools" 286s > if (require(pkg, character.only=TRUE)) { 286s + strategies <- c(strategies, "batchtools_local") 286s + } 286s Loading required package: future.batchtools 286s Warning message: 286s In library(package, lib.loc = lib.loc, character.only = TRUE, logical.return = TRUE, : 286s there is no package called 'future.batchtools' 286s > 286s > message("Future strategies to test: ", paste(sQuote(strategies), collapse=", ")) 286s Future strategies to test: 'sequential', 'multisession' 286s > 286s > fits <- list() 286s > for (strategy in strategies) { 286s + message(sprintf("- segmentByCBS() using '%s' futures ...", strategy)) 286s + plan(strategy) 286s + fit <- segmentByCBS(data, seed=0xBEEF, verbose=TRUE) 286s + fits[[strategy]] <- fit 286s + stopifnot(all.equal(fit, fits[[1]])) 286s + } 286s - segmentByCBS() using 'sequential' futures ... 286s Segmenting by CBS... 286s Segmenting multiple chromosomes... 286s Number of chromosomes: 3 286s Random seed temporarily set (seed=c(48879), kind="L'Ecuyer-CMRG") 286s Produced 3 seeds from this stream for future usage 286s Chromosome #1 ('Chr01') of 3... 286s Segmenting by CBS... 286s Chromosome: 1 286s Random seed temporarily set (seed=c(10407, 1066287653, -51199871, 161854402, -1995183193, 1503453565, -747102133), kind="L'Ecuyer-CMRG") 286s Segmenting by CBS...done 286s Chromosome #1 ('Chr01') of 3...done 286s Chromosome #2 ('Chr02') of 3... 286s Segmenting by CBS... 286s Chromosome: 2 286s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 286s Segmenting by CBS...done 286s Chromosome #2 ('Chr02') of 3...done 286s Chromosome #3 ('Chr03') of 3... 286s Segmenting by CBS... 286s Chromosome: 3 286s Random seed temporarily set (seed=c(10407, -821273412, -52578226, 1415511586, 721384351, -665928286, 1316562960), kind="L'Ecuyer-CMRG") 286s Segmenting by CBS...done 286s Chromosome #3 ('Chr03') of 3...done 286s Segmenting multiple chromosomes...done 286s Segmenting by CBS...done 286s list() 286s - segmentByCBS() using 'multisession' futures ... 286s Segmenting by CBS... 286s Segmenting multiple chromosomes... 286s Number of chromosomes: 3 286s Random seed temporarily set (seed=c(48879), kind="L'Ecuyer-CMRG") 286s Produced 3 seeds from this stream for future usage 286s Chromosome #1 ('Chr01') of 3... 286s Chromosome #1 ('Chr01') of 3...done 286s Chromosome #2 ('Chr02') of 3... 286s Random seed temporarily set (seed=c(10407, 1066287653, -51199871, 161854402, -1995183193, 1503453565, -747102133), kind="L'Ecuyer-CMRG") 286s Segmenting by CBS...done 286s Chromosome #2 ('Chr02') of 3...done 286s Chromosome #3 ('Chr03') of 3... 286s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 286s Segmenting by CBS...done 286s Chromosome #3 ('Chr03') of 3...done 286s Segmenting by CBS... 286s Chromosome: 3 286s Random seed temporarily set (seed=c(10407, -821273412, -52578226, 1415511586, 721384351, -665928286, 1316562960), kind="L'Ecuyer-CMRG") 286s Segmenting by CBS...done 286s Segmenting multiple chromosomes...done 286s Segmenting by CBS...done 286s list() 286s > 286s > 286s > message("*** segmentByCBS() via futures with known segments ...") 286s *** segmentByCBS() via futures with known segments ... 286s > fits <- list() 286s > dataT <- subset(data, chromosome == 1) 286s > for (strategy in strategies) { 286s + message(sprintf("- segmentByCBS() w/ known segments using '%s' futures ...", strategy)) 286s + plan(strategy) 286s + fit <- segmentByCBS(dataT, knownSegments=knownSegments, seed=0xBEEF, verbose=TRUE) 286s + fits[[strategy]] <- fit 286s + stopifnot(all.equal(fit, fits[[1]])) 286s + } 286s - segmentByCBS() w/ known segments using 'sequential' futures ... 286s Segmenting by CBS... 286s Chromosome: 1 286s Random seed temporarily set (seed=c(48879), kind="L'Ecuyer-CMRG") 286s Produced 3 seeds from this stream for future usage 286s Segmenting by CBS...done 286s list() 286s - segmentByCBS() w/ known segments using 'multisession' futures ... 286s Segmenting by CBS... 286s Chromosome: 1 286s Random seed temporarily set (seed=c(48879), kind="L'Ecuyer-CMRG") 286s Produced 3 seeds from this stream for future usage 286s Segmenting by CBS...done 286s list() 286s > 286s > message("*** segmentByCBS() via futures ... DONE") 286s *** segmentByCBS() via futures ... DONE 286s > 286s > 286s > ## Cleanup 286s > plan(oplan) 286s > rm(list=c("fits", "dataT", "data", "fit")) 286s > 286s > 286s > proc.time() 286s user system elapsed 286s 1.857 0.052 4.445 286s Test segmentByCBS,futures passed 286s + [ 0 != 0 ] 286s + echo Test segmentByCBS,futures passed 286s + echo0 286s Begin test segmentByCBS,median 286s 0 286s + echo Begin test segmentByCBS,median 286s + exitcode=0 286s + R CMD BATCH segmentByCBS,median.R 288s + cat segmentByCBS,median.Rout 288s + [ 0 != 0 ] 288s + echo Test segmentByCBS,median passed 288s + echo 0 288s + echo Begin test segmentByCBS,prune 288s + exitcode=0 288s + R CMD BATCH segmentByCBS,prune.R 288s 288s R version 4.5.2 (2025-10-31) -- "[Not] Part in a Rumble" 288s Copyright (C) 2025 The R Foundation for Statistical Computing 288s Platform: powerpc64le-unknown-linux-gnu 288s 288s R is free software and comes with ABSOLUTELY NO WARRANTY. 288s You are welcome to redistribute it under certain conditions. 288s Type 'license()' or 'licence()' for distribution details. 288s 288s R is a collaborative project with many contributors. 288s Type 'contributors()' for more information and 288s 'citation()' on how to cite R or R packages in publications. 288s 288s Type 'demo()' for some demos, 'help()' for on-line help, or 288s 'help.start()' for an HTML browser interface to help. 288s Type 'q()' to quit R. 288s 288s [Previously saved workspace restored] 288s 288s > library("PSCBS") 288s PSCBS v0.68.0 (2025-04-18 19:40:02 UTC) successfully loaded. See ?PSCBS for help. 288s > 288s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 288s > # Simulating copy-number data 288s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 288s > set.seed(0xBEEF) 288s > 288s > # Number of loci 288s > J <- 1000 288s > 288s > x <- sort(runif(J, max=J)) * 1e5 288s > 288s > mu <- double(J) 288s > mu[200:300] <- mu[200:300] + 1 288s > mu[350:400] <- NA # centromere 288s > mu[650:800] <- mu[650:800] - 1 288s > eps <- rnorm(J, sd=1/2) 288s > y <- mu + eps 288s > 288s > outliers <- seq(from=1L, to=J, length.out=0.2*J) 288s > y[outliers] <- y[outliers] + 1.5 288s > 288s > w <- rep(1.0, times=J) 288s > w[outliers] <- 0.01 288s > 288s > data <- data.frame(chromosome=1L, x=x, y=y) 288s > dataW <- cbind(data, w=w) 288s > 288s > 288s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 288s > # Single-chromosome segmentation 288s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 288s > par(mar=c(2,3,0.2,1)+0.1) 288s > # Segment without weights 288s > fit <- segmentByCBS(data) 288s > sampleName(fit) <- "CBS_Example" 288s > print(fit) 288s sampleName chromosome start end nbrOfLoci mean 288s 1 CBS_Example 1 6.066868e+02 19076007 199 0.2622 288s 2 CBS_Example 1 1.907601e+07 29630949 99 1.4289 288s 3 CBS_Example 1 2.963095e+07 63224332 299 0.2854 288s 4 CBS_Example 1 6.322433e+07 78801707 153 -0.7408 288s 5 CBS_Example 1 7.880171e+07 99917418 199 0.3541 288s > plotTracks(fit) 288s Warning message: 288s In plotTracks.CBS(fit) : 288s Setting default 'Clim' assuming the signal type is 'ratio' because signalType(fit) is unknown ('NA'). Use signalType(fit) <- 'ratio' to avoid this warning. 288s > ## Highlight outliers (they pull up the mean levels) 288s > points(x[outliers]/1e6, y[outliers], col="purple") 288s > 288s > # Segment without weights but with median 288s > fitM <- segmentByCBS(data, avg="median") 288s > sampleName(fitM) <- "CBS_Example (median)" 288s > print(fitM) 288s sampleName chromosome start end nbrOfLoci mean 288s 1 CBS_Example (median) 1 6.066868e+02 19076007 199 0.1005418 288s 2 CBS_Example (median) 1 1.907601e+07 29630949 99 1.2720955 288s 3 CBS_Example (median) 1 2.963095e+07 63224332 299 0.1337148 288s 4 CBS_Example (median) 1 6.322433e+07 78801707 153 -0.8655254 288s 5 CBS_Example (median) 1 7.880171e+07 99917418 199 0.1718179 288s > drawLevels(fitM, col="magenta", lty=3) 288s NULL 288s > 288s > # Segment with weights 288s > fitW <- segmentByCBS(dataW, avg="median") 288s > sampleName(fitW) <- "CBS_Example (weighted)" 288s > print(fitW) 288s sampleName chromosome start end nbrOfLoci mean 288s 1 CBS_Example (weighted) 1 6.066868e+02 19076007 199 -0.08745973 288s 2 CBS_Example (weighted) 1 1.907601e+07 30126128 101 1.12968951 288s 3 CBS_Example (weighted) 1 3.012613e+07 63224332 297 -0.06074638 288s 4 CBS_Example (weighted) 1 6.322433e+07 78801707 153 -1.06373835 288s 5 CBS_Example (weighted) 1 7.880171e+07 99917418 199 0.04204744 288s > drawLevels(fitW, col="red") 288s NULL 288s > 288s > # Segment with weights and median 288s > fitWM <- segmentByCBS(dataW, avg="median") 288s > sampleName(fitWM) <- "CBS_Example (weighted median)" 288s > print(fitWM) 288s sampleName chromosome start end nbrOfLoci 288s 1 CBS_Example (weighted median) 1 6.066868e+02 19076007 199 288s 2 CBS_Example (weighted median) 1 1.907601e+07 30126128 101 288s 3 CBS_Example (weighted median) 1 3.012613e+07 63224332 297 288s 4 CBS_Example (weighted median) 1 6.322433e+07 78801707 153 288s 5 CBS_Example (weighted median) 1 7.880171e+07 99917418 199 288s mean 288s 1 -0.08745973 288s 2 1.12968951 288s 3 -0.06074638 288s 4 -1.06373835 288s 5 0.04204744 288s > drawLevels(fitWM, col="orange", lty=3) 288s NULL 288s > 288s > 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)) 288s > 288s > ## Assert that weighted segment means are less biased 288s > dmean <- getSegments(fit)$mean - getSegments(fitW)$mean 288s > cat("Segment mean differences:\n") 288s Segment mean differences: 288s > print(dmean) 288s [1] 0.3496597 0.2992105 0.3461464 0.3229384 0.3120526 288s > stopifnot(all(dmean > 0, na.rm=TRUE)) 288s > 288s > dmean <- getSegments(fitM)$mean - getSegments(fitWM)$mean 288s > cat("Segment median differences:\n") 288s Segment median differences: 288s > print(dmean) 288s [1] 0.1880015 0.1424060 0.1944611 0.1982130 0.1297704 288s > stopifnot(all(dmean > 0, na.rm=TRUE)) 288s > 288s > 288s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 288s > # Multi-chromosome segmentation 288s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 288s > data2 <- data 288s > data2$chromosome <- 2L 288s > data <- rbind(data, data2) 288s > dataW <- cbind(data, w=w) 288s > 288s > par(mar=c(2,3,0.2,1)+0.1) 288s > # Segment without weights 288s > fit <- segmentByCBS(data) 288s > sampleName(fit) <- "CBS_Example" 288s > print(fit) 288s sampleName chromosome start end nbrOfLoci mean 288s 1 CBS_Example 1 6.066868e+02 19076007 199 0.2622 288s 2 CBS_Example 1 1.907601e+07 29630949 99 1.4289 288s 3 CBS_Example 1 2.963095e+07 63224332 299 0.2854 288s 4 CBS_Example 1 6.322433e+07 78801707 153 -0.7408 288s 5 CBS_Example 1 7.880171e+07 99917418 199 0.3541 288s 6 NA NA NA NA NA 288s 7 CBS_Example 2 6.066868e+02 19076007 199 0.2622 288s 8 CBS_Example 2 1.907601e+07 29630949 99 1.4289 288s 9 CBS_Example 2 2.963095e+07 63224332 299 0.2854 288s 10 CBS_Example 2 6.322433e+07 78801707 153 -0.7408 288s 11 CBS_Example 2 7.880171e+07 99917418 199 0.3541 288s > plotTracks(fit, Clim=c(-3,3)) 288s > 288s > # Segment without weights but with median 288s > fitM <- segmentByCBS(data, avg="median") 288s > sampleName(fitM) <- "CBS_Example (median)" 288s > print(fitM) 288s sampleName chromosome start end nbrOfLoci mean 288s 1 CBS_Example (median) 1 6.066868e+02 19076007 199 0.1005418 288s 2 CBS_Example (median) 1 1.907601e+07 29630949 99 1.2720955 288s 3 CBS_Example (median) 1 2.963095e+07 63224332 299 0.1337148 288s 4 CBS_Example (median) 1 6.322433e+07 78801707 153 -0.8655254 288s 5 CBS_Example (median) 1 7.880171e+07 99917418 199 0.1718179 288s 6 NA NA NA NA NA 288s 7 CBS_Example (median) 2 6.066868e+02 19076007 199 0.1005418 288s 8 CBS_Example (median) 2 1.907601e+07 29630949 99 1.2720955 288s 9 CBS_Example (median) 2 2.963095e+07 63224332 299 0.1337148 288s 10 CBS_Example (median) 2 6.322433e+07 78801707 153 -0.8655254 288s 11 CBS_Example (median) 2 7.880171e+07 99917418 199 0.1718179 288s > drawLevels(fitM, col="magenta", lty=3) 288s NULL 288s > 288s > # Segment with weights 288s > fitW <- segmentByCBS(dataW, avg="median") 288s > sampleName(fitW) <- "CBS_Example (weighted)" 288s > print(fitW) 288s sampleName chromosome start end nbrOfLoci 288s 1 CBS_Example (weighted) 1 6.066868e+02 19076007 199 288s 2 CBS_Example (weighted) 1 1.907601e+07 30126128 101 288s 3 CBS_Example (weighted) 1 3.012613e+07 63224332 297 288s 4 CBS_Example (weighted) 1 6.322433e+07 78801707 153 288s 5 CBS_Example (weighted) 1 7.880171e+07 99917418 199 288s 6 NA NA NA NA 288s 7 CBS_Example (weighted) 2 6.066868e+02 19076007 199 288s 8 CBS_Example (weighted) 2 1.907601e+07 30126128 101 288s 9 CBS_Example (weighted) 2 3.012613e+07 63224332 297 288s 10 CBS_Example (weighted) 2 6.322433e+07 78801707 153 288s 11 CBS_Example (weighted) 2 7.880171e+07 99917418 199 288s mean 288s 1 -0.08745973 288s 2 1.12968951 288s 3 -0.06074638 288s 4 -1.06373835 288s 5 0.04204744 288s 6 NA 288s 7 -0.08745973 288s 8 1.12968951 288s 9 -0.06074638 288s 10 -1.06373835 288s 11 0.04204744 288s > drawLevels(fitW, col="red") 288s NULL 288s > 288s > # Segment with weights and median 288s > fitWM <- segmentByCBS(dataW, avg="median") 288s > sampleName(fitWM) <- "CBS_Example (weighted median)" 288s > print(fitWM) 288s sampleName chromosome start end nbrOfLoci 288s 1 CBS_Example (weighted median) 1 6.066868e+02 19076007 199 288s 2 CBS_Example (weighted median) 1 1.907601e+07 30126128 101 288s 3 CBS_Example (weighted median) 1 3.012613e+07 63224332 297 288s 4 CBS_Example (weighted median) 1 6.322433e+07 78801707 153 288s 5 CBS_Example (weighted median) 1 7.880171e+07 99917418 199 288s 6 NA NA NA NA 288s 7 CBS_Example (weighted median) 2 6.066868e+02 19076007 199 288s 8 CBS_Example (weighted median) 2 1.907601e+07 30126128 101 288s 9 CBS_Example (weighted median) 2 3.012613e+07 63224332 297 288s 10 CBS_Example (weighted median) 2 6.322433e+07 78801707 153 288s 11 CBS_Example (weighted median) 2 7.880171e+07 99917418 199 288s mean 288s 1 -0.08745973 288s 2 1.12968951 288s 3 -0.06074638 288s 4 -1.06373835 288s 5 0.04204744 288s 6 NA 288s 7 -0.08745973 288s 8 1.12968951 288s 9 -0.06074638 288s 10 -1.06373835 288s 11 0.04204744 288s > drawLevels(fitWM, col="orange", lty=3) 288s NULL 288s > 288s > 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)) 288s > 288s > ## Assert that weighted segment means are less biased 288s > dmean <- getSegments(fit)$mean - getSegments(fitW)$mean 288s > cat("Segment mean differences:\n") 288s Segment mean differences: 288s > print(dmean) 288s [1] 0.3496597 0.2992105 0.3461464 0.3229384 0.3120526 NA 0.3496597 288s [8] 0.2992105 0.3461464 0.3229384 0.3120526 288s > stopifnot(all(dmean > 0, na.rm=TRUE)) 288s > 288s > dmean <- getSegments(fitM)$mean - getSegments(fitWM)$mean 288s > cat("Segment median differences:\n") 288s Segment median differences: 288s > print(dmean) 288s [1] 0.1880015 0.1424060 0.1944611 0.1982130 0.1297704 NA 0.1880015 288s [8] 0.1424060 0.1944611 0.1982130 0.1297704 288s > stopifnot(all(dmean > 0, na.rm=TRUE)) 288s > 288s > proc.time() 288s user system elapsed 288s 1.326 0.019 1.340 288s Test segmentByCBS,median passed 288s 0 288s Begin test segmentByCBS,prune 289s + cat segmentByCBS,prune.Rout 289s 289s R version 4.5.2 (2025-10-31) -- "[Not] Part in a Rumble" 289s Copyright (C) 2025 The R Foundation for Statistical Computing 289s Platform: powerpc64le-unknown-linux-gnu 289s 289s R is free software and comes with ABSOLUTELY NO WARRANTY. 289s You are welcome to redistribute it under certain conditions. 289s Type 'license()' or 'licence()' for distribution details. 289s 289s R is a collaborative project with many contributors. 289s Type 'contributors()' for more information and 289s 'citation()' on how to cite R or R packages in publications. 289s 289s Type 'demo()' for some demos, 'help()' for on-line help, or 289s 'help.start()' for an HTML browser interface to help. 289s Type 'q()' to quit R. 289s 289s [Previously saved workspace restored] 289s 289s > library("PSCBS") 289s PSCBS v0.68.0 (2025-04-18 19:40:02 UTC) successfully loaded. See ?PSCBS for help. 289s > 289s > ## Compare segments 289s > assertMatchingSegments <- function(fitM, fit) { 289s + chrs <- getChromosomes(fitM) 289s + segsM <- lapply(chrs, FUN=function(chr) { 289s + getSegments(extractChromosome(fitM, chr)) 289s + }) 289s + segs <- lapply(fit[chrs], FUN=getSegments) 289s + stopifnot(all.equal(segsM, segs, check.attributes=FALSE)) 289s + } 289s > 289s > ## Simulate data 289s > set.seed(0xBEEF) 289s > J <- 1000 289s > mu <- double(J) 289s > mu[200:300] <- mu[200:300] + 1 289s > mu[350:400] <- NA 289s > mu[650:800] <- mu[650:800] - 1 289s > eps <- rnorm(J, sd=1/2) 289s > y <- mu + eps 289s > x <- sort(runif(length(y), max=length(y))) * 1e5 289s > 289s > data <- list() 289s > for (chr in 1:2) { 289s + data[[chr]] <- data.frame(chromosome=chr, x=x, y=y) 289s + } 289s > data$M <- Reduce(rbind, data) 289s > 289s > ## Segment 289s > message("*** segmentByCBS()") 289s *** segmentByCBS() 289s > fit <- lapply(data, FUN=segmentByCBS) 289s > print(fit) 289s [[1]] 289s sampleName chromosome start end nbrOfLoci mean 289s 1 1 65285.65 19648927 200 0.0109 289s 2 1 19648927.46 28239656 95 0.9529 289s 3 1 28239655.99 65697742 302 -0.0126 289s 4 1 65697742.20 79729368 153 -0.9534 289s 5 1 79729368.34 99819310 199 -0.0497 289s 289s [[2]] 289s sampleName chromosome start end nbrOfLoci mean 289s 1 2 65285.65 19648927 200 0.0109 289s 2 2 19648927.46 28239656 95 0.9529 289s 3 2 28239655.99 65697742 302 -0.0126 289s 4 2 65697742.20 79729368 153 -0.9534 289s 5 2 79729368.34 99819310 199 -0.0497 289s 289s $M 289s sampleName chromosome start end nbrOfLoci mean 289s 1 1 65285.65 19648927 200 0.0109 289s 2 1 19648927.46 28239656 95 0.9529 289s 3 1 28239655.99 65697742 302 -0.0126 289s 4 1 65697742.20 79729368 153 -0.9534 289s 5 1 79729368.34 99819310 199 -0.0497 289s 6 NA NA NA NA NA 289s 7 2 65285.65 19648927 200 0.0109 289s 8 2 19648927.46 28239656 95 0.9529 289s 9 2 28239655.99 65697742 302 -0.0126 289s 10 2 65697742.20 79729368 153 -0.9534 289s 11 2 79729368.34 99819310 199 -0.0497 289s 289s > assertMatchingSegments(fit$M, fit) 289s > 289s > ## Join segments 289s > message("*** joinSegments()") 289s *** joinSegments() 289s > fitj <- lapply(fit, FUN=joinSegments) 289s > print(fitj) 289s [[1]] 289s sampleName chromosome start end nbrOfLoci mean 289s 1 1 65285.65 19648927 200 0.0109 289s 2 1 19648927.46 28239656 95 0.9529 289s 3 1 28239655.99 65697742 302 -0.0126 289s 4 1 65697742.20 79729368 153 -0.9534 289s 5 1 79729368.34 99819310 199 -0.0497 289s 289s [[2]] 289s sampleName chromosome start end nbrOfLoci mean 289s 1 2 65285.65 19648927 200 0.0109 289s 2 2 19648927.46 28239656 95 0.9529 289s 3 2 28239655.99 65697742 302 -0.0126 289s 4 2 65697742.20 79729368 153 -0.9534 289s 5 2 79729368.34 99819310 199 -0.0497 289s 289s $M 289s sampleName chromosome start end nbrOfLoci mean 289s 1 1 65285.65 19648927 200 0.0109 289s 2 1 19648927.46 28239656 95 0.9529 289s 3 1 28239655.99 65697742 302 -0.0126 289s 4 1 65697742.20 79729368 153 -0.9534 289s 5 1 79729368.34 99819310 199 -0.0497 289s 6 NA NA NA NA NA 289s 7 2 65285.65 19648927 200 0.0109 289s 8 2 19648927.46 28239656 95 0.9529 289s 9 2 28239655.99 65697742 302 -0.0126 289s 10 2 65697742.20 79729368 153 -0.9534 289s 11 2 79729368.34 99819310 199 -0.0497 289s 289s > assertMatchingSegments(fitj$M, fitj) 289s > 289s > ## Reset segments 289s > message("*** resetSegments()") 289s *** resetSegments() 289s > fitj <- lapply(fit, FUN=resetSegments) 289s > print(fitj) 289s [[1]] 289s sampleName chromosome start end nbrOfLoci mean 289s 1 1 65285.65 19648927 200 0.0109 289s 2 1 19648927.46 28239656 95 0.9529 289s 3 1 28239655.99 65697742 302 -0.0126 289s 4 1 65697742.20 79729368 153 -0.9534 289s 5 1 79729368.34 99819310 199 -0.0497 289s 289s [[2]] 289s sampleName chromosome start end nbrOfLoci mean 289s 1 2 65285.65 19648927 200 0.0109 289s 2 2 19648927.46 28239656 95 0.9529 289s 3 2 28239655.99 65697742 302 -0.0126 289s 4 2 65697742.20 79729368 153 -0.9534 289s 5 2 79729368.34 99819310 199 -0.0497 289s 289s $M 289s sampleName chromosome start end nbrOfLoci mean 289s 1 1 65285.65 19648927 200 0.0109 289s 2 1 19648927.46 28239656 95 0.9529 289s 3 1 28239655.99 65697742 302 -0.0126 289s 4 1 65697742.20 79729368 153 -0.9534 289s 5 1 79729368.34 99819310 199 -0.0497 289s 6 NA NA NA NA NA 289s 7 2 65285.65 19648927 200 0.0109 289s 8 2 19648927.46 28239656 95 0.9529 289s 9 2 28239655.99 65697742 302 -0.0126 289s 10 2 65697742.20 79729368 153 -0.9534 289s 11 2 79729368.34 99819310 199 -0.0497 289s 289s > assertMatchingSegments(fitj$M, fitj) 289s > 289s > ## Prune by SD undo 289s > message("*** pruneBySdUndo()") 289s *** pruneBySdUndo() 289s > fitp <- lapply(fit, FUN=pruneBySdUndo) 289s > print(fitp) 289s [[1]] 289s sampleName chromosome start end nbrOfLoci mean 289s 1 1 65285.65 99819310 949 -0.07045097 289s 289s [[2]] 289s sampleName chromosome start end nbrOfLoci mean 289s 1 2 65285.65 99819310 949 -0.07045097 289s 289s $M 289s sampleName chromosome start end nbrOfLoci mean 289s 1 1 65285.65 99819310 949 -0.07045097 289s 2 NA NA NA NA NA 289s 3 2 65285.65 99819310 949 -0.07045097 289s 289s > assertMatchingSegments(fitp$M, fitp) 289s > 289s > ## Prune by hierarchical clustering 289s > message("*** pruneByHClust()") 289s *** pruneByHClust() 289s > fitp <- lapply(fit, FUN=pruneByHClust, k=1L) 289s > print(fitp) 289s [[1]] 289s sampleName chromosome start end nbrOfLoci mean 289s 1 1 65285.65 99819310 949 -0.07045097 289s 289s [[2]] 289s sampleName chromosome start end nbrOfLoci mean 289s 1 2 65285.65 99819310 949 -0.07045097 289s 289s $M 289s sampleName chromosome start end nbrOfLoci mean 289s 1 1 65285.65 99819310 949 -0.07045097 289s 6 NA NA NA NA NA 289s 7 2 65285.65 99819310 949 -0.07045097 289s 289s > assertMatchingSegments(fitp$M, fitp) 289s > 289s > proc.time() 289s user system elapsed 289s 0.950 0.011 0.956 289s + [ 0 != 0 ] 289s + echo Test segmentByCBS,prune passed 289s + echo 0 289s + echo Begin test segmentByCBS,report 289s + exitcode=0 289s + R CMD BATCH segmentByCBS,report.R 289s Test segmentByCBS,prune passed 289s 0 289s Begin test segmentByCBS,report 289s + cat segmentByCBS,report.Rout 289s 289s R version 4.5.2 (2025-10-31) -- "[Not] Part in a Rumble" 289s Copyright (C) 2025 The R Foundation for Statistical Computing 289s Platform: powerpc64le-unknown-linux-gnu 289s 289s R is free software and comes with ABSOLUTELY NO WARRANTY. 289s You are welcome to redistribute it under certain conditions. 289s Type 'license()' or 'licence()' for distribution details. 289s 289s R is a collaborative project with many contributors. 289s Type 'contributors()' for more information and 289s 'citation()' on how to cite R or R packages in publications. 289s 289s Type 'demo()' for some demos, 'help()' for on-line help, or 289s 'help.start()' for an HTML browser interface to help. 289s Type 'q()' to quit R. 289s 289s [Previously saved workspace restored] 289s 289s > # This test script calls a report generator which requires 289s > # the 'ggplot2' package, which in turn will require packages 289s > # 'colorspace', 'dichromat', 'munsell', 'reshape2' and 'scales'. 289s > 289s > # Only run this test in full testing mode 289s > if (Sys.getenv("_R_CHECK_FULL_") != "") { 289s + library("PSCBS") 289s + 289s + # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 289s + # Load SNP microarray data 289s + # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 289s + data <- PSCBS::exampleData("paired.chr01") 289s + str(data) 289s + 289s + data <- data.frame(chromosome=data$chromosome, x=data$x, y=data$CT) 289s + 289s + 289s + # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 289s + # CBS segmentation 289s + # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 289s + # Drop single-locus outliers 289s + dataS <- dropSegmentationOutliers(data) 289s + 289s + # Speed up example by segmenting fewer loci 289s + dataS <- dataS[seq(from=1, to=nrow(data), by=5),] 289s + 289s + str(dataS) 289s + 289s + gaps <- findLargeGaps(dataS, minLength=2e6) 289s + knownSegments <- gapsToSegments(gaps) 289s + 289s + # CBS segmentation 289s + fit <- segmentByCBS(dataS, knownSegments=knownSegments, 289s + seed=0xBEEF, verbose=-10) 289s + signalType(fit) <- "ratio" 289s + 289s + # Fake a multi-chromosome segmentation 289s + fit1 <- fit 289s + fit2 <- renameChromosomes(fit, from=1, to=2) 289s + fit <- c(fit1, fit2) 289s + 289s + report(fit, sampleName="CBS", studyName="CBS-Ex", verbose=-10) 289s + 289s + } # if (Sys.getenv("_R_CHECK_FULL_")) 289s > 289s > proc.time() 289s user system elapsed 289s 0.190 0.012 0.196 289s + [ 0 != 0 ] 289s + echo Test segmentByCBS,report passed 289s + echo 0 289s + echo Begin test segmentByCBS,shiftTCN 289s + exitcode=0 289s + R CMD BATCH segmentByCBS,shiftTCN.R 289s Test segmentByCBS,report passed 289s 0 289s Begin test segmentByCBS,shiftTCN 297s 297s R version 4.5.2 (2025-10-31) -- "[Not] Part in a Rumble" 297s Copyright (C) 2025 The R Foundation for Statistical Computing 297s Platform: powerpc64le-unknown-linux-gnu 297s 297s R is free software and comes with ABSOLUTELY NO WARRANTY. 297s You are welcome to redistribute it under certain conditions. 297s Type 'license()' or 'licence()' for distribution details. 297s 297s R is a collaborative project with many contributors. 297s Type 'contributors()' for more information and 297s 'citation()' on how to cite R or R packages in publications. 297s 297s Type 'demo()' for some demos, 'help()' for on-line help, or 297s 'help.start()' for an HTML browser interface to help. 297s Type 'q()' to quit R. 297s 297s [Previously saved workspace restored] 297s 297s > library("PSCBS") 297s PSCBS v0.68.0 (2025-04-18 19:40:02 UTC) successfully loaded. See ?PSCBS for help. 297s > subplots <- R.utils::subplots 297s > 297s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 297s > # Simulating copy-number data 297s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 297s > set.seed(0xBEEF) 297s > 297s > # Number of loci 297s > J <- 1000 297s > 297s > mu <- double(J) 297s > eps <- rnorm(J, sd=1/2) 297s > y <- mu + eps 297s > x <- sort(runif(length(y), max=length(y))) 297s > 297s > idxs <- which(200 <= x & x < 300) 297s > y[idxs] <- y[idxs] + 1 297s > idxs <- which(350 <= x & x < 400) 297s > y[idxs] <- NA # centromere 297s > x[idxs] <- NA # centromere 297s > idxs <- which(650 <= x & x < 800) 297s > y[idxs] <- y[idxs] - 1 297s > x <- x*1e5 297s > 297s > keep <- is.finite(x) 297s > x <- x[keep] 297s > y <- y[keep] 297s > 297s > data <- list() 297s > for (chr in 1:2) { 297s + data[[chr]] <- data.frame(chromosome=chr, y=y, x=x) 297s + } 297s > data <- Reduce(rbind, data) 297s > 297s > 297s > subplots(7, ncol=1) 297s > par(mar=c(1.7,1,0.2,1)+0.1) 297s > 297s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 297s > # Segmentation 297s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 297s > fit <- segmentByCBS(data) 297s > print(fit) 297s sampleName chromosome start end nbrOfLoci mean 297s 1 1 65285.65 20169684 205 0.0124 297s 2 1 20169684.05 29980147 103 0.9477 297s 3 1 29980147.36 64779929 287 -0.0299 297s 4 1 64779929.38 80010171 163 -0.9676 297s 5 1 80010171.14 99819310 196 -0.0484 297s 6 NA NA NA NA NA 297s 7 2 65285.65 20169684 205 0.0124 297s 8 2 20169684.05 29980147 103 0.9477 297s 9 2 29980147.36 64779929 287 -0.0299 297s 10 2 64779929.38 80010171 163 -0.9676 297s 11 2 80010171.14 99819310 196 -0.0484 297s > 297s > Clim <- c(-3,3) + c(0,10) 297s > plotTracks(fit, Clim=Clim) 297s > 297s > 297s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 297s > # Shifting every other chromosome 297s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 297s > fitList <- list() 297s > chrs <- getChromosomes(fit) 297s > for (kk in seq_along(chrs)) { 297s + chr <- chrs[kk] 297s + fitKK <- extractChromosome(fit, chr) 297s + if (kk %% 2 == 0) { 297s + fitKK <- shiftTCN(fitKK, shift=+10) 297s + } 297s + fitList[[kk]] <- fitKK 297s + } # for (kk ...) 297s > fitT <- do.call(c, fitList) 297s > # Sanity check 297s > stopifnot(nbrOfSegments(fitT) == nbrOfSegments(fit)) 297s > 297s > plotTracks(fitT, Clim=Clim) 297s > 297s > 297s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 297s > # Shifting every other known segment 297s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 297s > gaps <- findLargeGaps(data, minLength=40e5) 297s > knownSegments <- gapsToSegments(gaps, dropGaps=TRUE) 297s > fit <- segmentByCBS(data, knownSegments=knownSegments) 297s > 297s > subplots(2, ncol=1) 297s > plotTracks(fit, Clim=Clim) 297s > abline(v=c(knownSegments$start, knownSegments$end)/1e6, lty=3) 297s > 297s > fitList <- list() 297s > for (kk in seq_len(nrow(knownSegments))) { 297s + seg <- knownSegments[kk,] 297s + start <- seg$start 297s + end <- seg$end 297s + fitKK <- extractChromosome(fit, seg$chromosome) 297s + segsKK <- getSegments(fitKK) 297s + idxStart <- min(which(segsKK$start >= start)) 297s + idxEnd <- max(which(segsKK$end <= end)) 297s + idxs <- idxStart:idxEnd 297s + fitKK <- extractSegments(fitKK, idxs) 297s + if (kk %% 2 == 0) { 297s + fitKK <- shiftTCN(fitKK, shift=+10) 297s + } 297s + fitList[[kk]] <- fitKK 297s + } # for (kk ...) 297s > fitT <- do.call(c, fitList) 297s > # Sanity check 297s > stopifnot(nbrOfSegments(fitT) == nbrOfSegments(fit)) 297s > 297s > plotTracks(fitT, Clim=Clim) 297s > abline(v=c(knownSegments$start, knownSegments$end)/1e6, lty=3) 297s > 297s > 297s > segList <- seqOfSegmentsByDP(fit) 297s > K <- length(segList) 297s > subplots(K, ncol=2, byrow=FALSE) 297s > par(mar=c(2,1,1,1)) 297s > for (kk in 1:K) { 297s + knownSegments <- segList[[kk]] 297s + fitKK <- resegment(fit, knownSegments=knownSegments, undo=+Inf) 297s + plotTracks(fitKK, Clim=c(-3,3)) 297s + } # for (kk ...) 297s > 297s > proc.time() 297s user system elapsed 297s 7.657 0.048 7.709 297s Test segmentByCBS,shiftTCN passed 297s 0 297s Begin test segmentByCBS,weights 297s + cat segmentByCBS,shiftTCN.Rout 297s + [ 0 != 0 ] 297s + echo Test segmentByCBS,shiftTCN passed 297s + echo 0 297s + echo Begin test segmentByCBS,weights 297s + exitcode=0 297s + R CMD BATCH segmentByCBS,weights.R 300s + cat segmentByCBS,weights.Rout 300s 300s R version 4.5.2 (2025-10-31) -- "[Not] Part in a Rumble" 300s Copyright (C) 2025 The R Foundation for Statistical Computing 300s Platform: powerpc64le-unknown-linux-gnu 300s 300s R is free software and comes with ABSOLUTELY NO WARRANTY. 300s You are welcome to redistribute it under certain conditions. 300s Type 'license()' or 'licence()' for distribution details. 300s 300s R is a collaborative project with many contributors. 300s Type 'contributors()' for more information and 300s 'citation()' on how to cite R or R packages in publications. 300s 300s Type 'demo()' for some demos, 'help()' for on-line help, or 300s 'help.start()' for an HTML browser interface to help. 300s Type 'q()' to quit R. 300s 300s [Previously saved workspace restored] 300s 300s > library("PSCBS") 300s PSCBS v0.68.0 (2025-04-18 19:40:02 UTC) successfully loaded. See ?PSCBS for help. 300s > 300s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 300s > # Simulating copy-number data 300s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 300s > set.seed(0xBEEF) 300s > 300s > # Number of loci 300s > J <- 1000 300s > 300s > x <- sort(runif(J, max=J)) * 1e5 300s > 300s > mu <- double(J) 300s > mu[200:300] <- mu[200:300] + 1 300s > mu[350:400] <- NA # centromere 300s > mu[650:800] <- mu[650:800] - 1 300s > eps <- rnorm(J, sd=1/2) 300s > y <- mu + eps 300s > 300s > outliers <- seq(from=1L, to=J, length.out=0.2*J) 300s > y[outliers] <- y[outliers] + 1.5 300s > 300s > w <- rep(1.0, times=J) 300s > w[outliers] <- 0.01 300s > 300s > data <- data.frame(chromosome=1L, x=x, y=y) 300s > dataW <- cbind(data, w=w) 300s > 300s > 300s > par(mar=c(2,3,0.2,1)+0.1) 300s > 300s > 300s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 300s > # Single-chromosome segmentation 300s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 300s > # Segment without weights 300s > fit <- segmentByCBS(data) 300s > sampleName(fit) <- "CBS_Example" 300s > print(fit) 300s sampleName chromosome start end nbrOfLoci mean 300s 1 CBS_Example 1 6.066868e+02 19076007 199 0.2622 300s 2 CBS_Example 1 1.907601e+07 29630949 99 1.4289 300s 3 CBS_Example 1 2.963095e+07 63224332 299 0.2854 300s 4 CBS_Example 1 6.322433e+07 78801707 153 -0.7408 300s 5 CBS_Example 1 7.880171e+07 99917418 199 0.3541 300s > plotTracks(fit) 300s Warning message: 300s In plotTracks.CBS(fit) : 300s Setting default 'Clim' assuming the signal type is 'ratio' because signalType(fit) is unknown ('NA'). Use signalType(fit) <- 'ratio' to avoid this warning. 300s > ## Highlight outliers (they pull up the mean levels) 300s > points(x[outliers]/1e6, y[outliers], col="purple") 300s > 300s > # Segment with weights 300s > fitW <- segmentByCBS(dataW) 300s > sampleName(fitW) <- "CBS_Example (weighted)" 300s > print(fitW) 300s sampleName chromosome start end nbrOfLoci mean 300s 1 CBS_Example (weighted) 1 6.066868e+02 19076007 199 -0.0610 300s 2 CBS_Example (weighted) 1 1.907601e+07 30126128 101 1.1283 300s 3 CBS_Example (weighted) 1 3.012613e+07 63224332 297 -0.0298 300s 4 CBS_Example (weighted) 1 6.322433e+07 78801707 153 -1.0436 300s 5 CBS_Example (weighted) 1 7.880171e+07 99917418 199 0.0461 300s > drawLevels(fitW, col="red") 300s NULL 300s > 300s > 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)) 300s > 300s > ## Assert that weighted segment means are less biased 300s > dmean <- getSegments(fit)$mean - getSegments(fitW)$mean 300s > cat("Segment mean differences:\n") 300s Segment mean differences: 300s > print(dmean) 300s [1] 0.3232 0.3006 0.3152 0.3028 0.3080 300s > stopifnot(all(dmean > 0, na.rm=TRUE)) 300s > 300s > 300s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 300s > # Segmentation with some known change points 300s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 300s > knownSegments <- data.frame( 300s + chromosome=c( 1, 1), 300s + start =x[c( 1, 401)], 300s + end =x[c(349, J)] 300s + ) 300s > fit2 <- segmentByCBS(dataW, knownSegments=knownSegments, verbose=TRUE) 300s Segmenting by CBS... 300s Chromosome: 1 300s Segmenting by CBS...done 300s > sampleName(fit2) <- "CBS_Example_2 (weighted)" 300s > print(fit2) 300s sampleName chromosome start end nbrOfLoci mean 300s 1 CBS_Example_2 (weighted) 1 6.066868e+02 19076007 199 -0.0610 300s 2 CBS_Example_2 (weighted) 1 1.907601e+07 30126128 101 1.1283 300s 3 CBS_Example_2 (weighted) 1 3.012613e+07 35490554 49 -0.0832 300s 4 CBS_Example_2 (weighted) 1 3.987525e+07 63224332 248 -0.0192 300s 5 CBS_Example_2 (weighted) 1 6.322433e+07 78471531 152 -1.0480 300s 6 CBS_Example_2 (weighted) 1 7.847153e+07 99917418 200 0.0427 300s > plotTracks(fit2) 300s Warning message: 300s In plotTracks.CBS(fit2) : 300s Setting default 'Clim' assuming the signal type is 'ratio' because signalType(fit2) is unknown ('NA'). Use signalType(fit2) <- 'ratio' to avoid this warning. 300s > abline(v=c(knownSegments$start, knownSegments$end)/1e6, lty=3) 300s > 300s > 300s > # Chromosome boundaries can be specified as -Inf and +Inf 300s > knownSegments <- data.frame( 300s + chromosome=c( 1, 1), 300s + start =c( -Inf, x[401]), 300s + end =c(x[349], +Inf) 300s + ) 300s > fit2b <- segmentByCBS(dataW, knownSegments=knownSegments, verbose=TRUE) 300s Segmenting by CBS... 300s Chromosome: 1 300s Segmenting by CBS...done 300s > sampleName(fit2b) <- "CBS_Example_2b (weighted)" 300s > print(fit2b) 300s sampleName chromosome start end nbrOfLoci mean 300s 1 CBS_Example_2b (weighted) 1 6.066868e+02 19076007 199 -0.0610 300s 2 CBS_Example_2b (weighted) 1 1.907601e+07 30126128 101 1.1283 300s 3 CBS_Example_2b (weighted) 1 3.012613e+07 35490554 49 -0.0832 300s 4 CBS_Example_2b (weighted) 1 3.987525e+07 63224332 248 -0.0192 300s 5 CBS_Example_2b (weighted) 1 6.322433e+07 78471531 152 -1.0480 300s 6 CBS_Example_2b (weighted) 1 7.847153e+07 99917418 200 0.0427 300s > plotTracks(fit2b) 300s Warning message: 300s In plotTracks.CBS(fit2b) : 300s Setting default 'Clim' assuming the signal type is 'ratio' because signalType(fit2b) is unknown ('NA'). Use signalType(fit2b) <- 'ratio' to avoid this warning. 300s > abline(v=c(knownSegments$start, knownSegments$end)/1e6, lty=3) 300s > 300s > 300s > # As a proof of concept, it is possible to segment just the centromere, 300s > # which contains no data. All statistics will be NAs. 300s > knownSegments <- data.frame( 300s + chromosome=c( 1), 300s + start =x[c(350)], 300s + end =x[c(400)] 300s + ) 300s > fit3 <- segmentByCBS(dataW, knownSegments=knownSegments, verbose=TRUE) 300s Segmenting by CBS... 300s Chromosome: 1 300s Segmenting by CBS...done 300s > sampleName(fit3) <- "CBS_Example_3" 300s > print(fit3) 300s sampleName chromosome start end nbrOfLoci mean 300s 1 CBS_Example_3 1 35661013 39852333 0 NA 300s > plotTracks(fit3, Clim=c(0,5), xlim=c(0,100)) 300s > abline(v=c(knownSegments$start, knownSegments$end)/1e6, lty=3) 300s > 300s > 300s > # If one specify the (empty) centromere as a segment, then its 300s > # estimated statistics will be NAs, which becomes a natural 300s > # separator between the two "independent" arms. 300s > knownSegments <- data.frame( 300s + chromosome=c( 1, 1, 1), 300s + start =x[c( 1, 350, 401)], 300s + end =x[c(349, 400, J)] 300s + ) 300s > fit4 <- segmentByCBS(dataW, knownSegments=knownSegments, verbose=TRUE) 300s Segmenting by CBS... 300s Chromosome: 1 300s Segmenting by CBS...done 300s > sampleName(fit4) <- "CBS_Example_4" 300s > print(fit4) 300s sampleName chromosome start end nbrOfLoci mean 300s 1 CBS_Example_4 1 6.066868e+02 19076007 199 -0.0610 300s 2 CBS_Example_4 1 1.907601e+07 30126128 101 1.1283 300s 3 CBS_Example_4 1 3.012613e+07 35490554 49 -0.0832 300s 4 CBS_Example_4 1 3.566101e+07 39852333 0 NA 300s 5 CBS_Example_4 1 3.987525e+07 63224332 248 -0.0192 300s 6 CBS_Example_4 1 6.322433e+07 78471531 152 -1.0480 300s 7 CBS_Example_4 1 7.847153e+07 99917418 200 0.0427 300s > plotTracks(fit4) 300s Warning message: 300s In plotTracks.CBS(fit4) : 300s Setting default 'Clim' assuming the signal type is 'ratio' because signalType(fit4) is unknown ('NA'). Use signalType(fit4) <- 'ratio' to avoid this warning. 300s > abline(v=c(knownSegments$start, knownSegments$end)/1e6, lty=3) 300s > 300s > 300s > fit5 <- segmentByCBS(dataW, knownSegments=knownSegments, undo=Inf, verbose=TRUE) 300s Segmenting by CBS... 300s Chromosome: 1 300s Segmenting by CBS...done 300s > sampleName(fit5) <- "CBS_Example_5" 300s > print(fit5) 300s sampleName chromosome start end nbrOfLoci mean 300s 1 CBS_Example_5 1 6.066868e+02 35490554 349 0.59252133 300s 2 CBS_Example_5 1 3.566101e+07 39852333 0 NA 300s 3 CBS_Example_5 1 3.987525e+07 99917418 600 0.04882396 300s > plotTracks(fit5) 300s Warning message: 300s In plotTracks.CBS(fit5) : 300s Setting default 'Clim' assuming the signal type is 'ratio' because signalType(fit5) is unknown ('NA'). Use signalType(fit5) <- 'ratio' to avoid this warning. 300s > abline(v=c(knownSegments$start, knownSegments$end)/1e6, lty=3) 300s > stopifnot(nbrOfSegments(fit5) == nrow(knownSegments)) 300s > 300s > 300s > # One can also force a separator between two segments by setting 300s > # 'start' and 'end' to NAs ('chromosome' has to be given) 300s > knownSegments <- data.frame( 300s + chromosome=c( 1, 1, 1), 300s + start =x[c( 1, NA, 401)], 300s + end =x[c(349, NA, J)] 300s + ) 300s > fit6 <- segmentByCBS(dataW, knownSegments=knownSegments, verbose=TRUE) 300s Segmenting by CBS... 300s Chromosome: 1 300s Segmenting by CBS...done 300s > sampleName(fit6) <- "CBS_Example_6" 300s > print(fit6) 300s sampleName chromosome start end nbrOfLoci mean 300s 1 CBS_Example_6 1 6.066868e+02 19076007 199 -0.0610 300s 2 CBS_Example_6 1 1.907601e+07 30126128 101 1.1283 300s 3 CBS_Example_6 1 3.012613e+07 35490554 49 -0.0832 300s 4 NA NA NA NA NA 300s 5 CBS_Example_6 1 3.987525e+07 63224332 248 -0.0192 300s 6 CBS_Example_6 1 6.322433e+07 78471531 152 -1.0480 300s 7 CBS_Example_6 1 7.847153e+07 99917418 200 0.0427 300s > plotTracks(fit6) 300s Warning message: 300s In plotTracks.CBS(fit6) : 300s Setting default 'Clim' assuming the signal type is 'ratio' because signalType(fit6) is unknown ('NA'). Use signalType(fit6) <- 'ratio' to avoid this warning. 300s > abline(v=c(knownSegments$start, knownSegments$end)/1e6, lty=3) 300s > 300s > 300s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 300s > # Multi-chromosome segmentation 300s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 300s > data2 <- data 300s > data2$chromosome <- 2L 300s > data <- rbind(data, data2) 300s > dataW <- cbind(data, w=w) 300s > 300s > par(mar=c(2,3,0.2,1)+0.1) 300s > # Segment without weights 300s > fit <- segmentByCBS(data) 300s > sampleName(fit) <- "CBS_Example" 300s > print(fit) 300s sampleName chromosome start end nbrOfLoci mean 300s 1 CBS_Example 1 6.066868e+02 19076007 199 0.2622 300s 2 CBS_Example 1 1.907601e+07 29630949 99 1.4289 300s 3 CBS_Example 1 2.963095e+07 63224332 299 0.2854 300s 4 CBS_Example 1 6.322433e+07 78801707 153 -0.7408 300s 5 CBS_Example 1 7.880171e+07 99917418 199 0.3541 300s 6 NA NA NA NA NA 300s 7 CBS_Example 2 6.066868e+02 19076007 199 0.2622 300s 8 CBS_Example 2 1.907601e+07 29630949 99 1.4289 300s 9 CBS_Example 2 2.963095e+07 63224332 299 0.2854 300s 10 CBS_Example 2 6.322433e+07 78801707 153 -0.7408 300s 11 CBS_Example 2 7.880171e+07 99917418 199 0.3541 300s > plotTracks(fit, Clim=c(-3,3)) 300s > 300s > # Segment with weights 300s > fitW <- segmentByCBS(dataW) 300s > sampleName(fitW) <- "CBS_Example (weighted)" 300s > print(fitW) 300s sampleName chromosome start end nbrOfLoci mean 300s 1 CBS_Example (weighted) 1 6.066868e+02 19076007 199 -0.0610 300s 2 CBS_Example (weighted) 1 1.907601e+07 30126128 101 1.1283 300s 3 CBS_Example (weighted) 1 3.012613e+07 63224332 297 -0.0298 300s 4 CBS_Example (weighted) 1 6.322433e+07 78801707 153 -1.0436 300s 5 CBS_Example (weighted) 1 7.880171e+07 99917418 199 0.0461 300s 6 NA NA NA NA NA 300s 7 CBS_Example (weighted) 2 6.066868e+02 19076007 199 -0.0610 300s 8 CBS_Example (weighted) 2 1.907601e+07 30126128 101 1.1283 300s 9 CBS_Example (weighted) 2 3.012613e+07 63224332 297 -0.0298 300s 10 CBS_Example (weighted) 2 6.322433e+07 78801707 153 -1.0436 300s 11 CBS_Example (weighted) 2 7.880171e+07 99917418 199 0.0461 300s > drawLevels(fitW, col="red") 300s NULL 300s > 300s > 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)) 300s > 300s > ## Assert that weighted segment means are less biased 300s > dmean <- getSegments(fit)$mean - getSegments(fitW)$mean 300s > cat("Segment mean differences:\n") 300s Segment mean differences: 300s > print(dmean) 300s [1] 0.3232 0.3006 0.3152 0.3028 0.3080 NA 0.3232 0.3006 0.3152 0.3028 300s [11] 0.3080 300s > stopifnot(all(dmean > 0, na.rm=TRUE)) 300s > 300s > proc.time() 300s user system elapsed 300s 2.562 0.033 2.592 300s Test segmentByCBS,weights passed 300s 0 300s Begin test segmentByCBS 300s + [ 0 != 0 ] 300s + echo Test segmentByCBS,weights passed 300s + echo 0 300s + echo Begin test segmentByCBS 300s + exitcode=0 300s + R CMD BATCH segmentByCBS.R 303s + cat segmentByCBS.Rout 303s 303s R version 4.5.2 (2025-10-31) -- "[Not] Part in a Rumble" 303s Copyright (C) 2025 The R Foundation for Statistical Computing 303s Platform: powerpc64le-unknown-linux-gnu 303s 303s R is free software and comes with ABSOLUTELY NO WARRANTY. 303s You are welcome to redistribute it under certain conditions. 303s Type 'license()' or 'licence()' for distribution details. 303s 303s R is a collaborative project with many contributors. 303s Type 'contributors()' for more information and 303s 'citation()' on how to cite R or R packages in publications. 303s 303s Type 'demo()' for some demos, 'help()' for on-line help, or 303s 'help.start()' for an HTML browser interface to help. 303s Type 'q()' to quit R. 303s 303s [Previously saved workspace restored] 303s 303s > ########################################################### 303s > # This tests: 303s > # - segmentByCBS(...) 303s > # - segmentByCBS(..., knownSegments) 303s > # - tileChromosomes() 303s > # - plotTracks() 303s > ########################################################### 303s > library("PSCBS") 303s PSCBS v0.68.0 (2025-04-18 19:40:02 UTC) successfully loaded. See ?PSCBS for help. 303s > subplots <- R.utils::subplots 303s > 303s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 303s > # Simulating copy-number data 303s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 303s > set.seed(0xBEEF) 303s > 303s > # Number of loci 303s > J <- 1000 303s > 303s > mu <- double(J) 303s > mu[200:300] <- mu[200:300] + 1 303s > mu[350:400] <- NA # centromere 303s > mu[650:800] <- mu[650:800] - 1 303s > eps <- rnorm(J, sd=1/2) 303s > y <- mu + eps 303s > x <- sort(runif(length(y), max=length(y))) * 1e5 303s > w <- runif(J) 303s > w[650:800] <- 0.001 303s > 303s > 303s > subplots(8, ncol=1L) 303s > par(mar=c(1.7,1,0.2,1)+0.1) 303s > 303s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 303s > # Segmentation 303s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 303s > fit <- segmentByCBS(y, x=x) 303s > sampleName(fit) <- "CBS_Example" 303s > print(fit) 303s sampleName chromosome start end nbrOfLoci mean 303s 1 CBS_Example 0 65285.65 19648927 200 0.0109 303s 2 CBS_Example 0 19648927.46 28239656 95 0.9529 303s 3 CBS_Example 0 28239655.99 65697742 302 -0.0126 303s 4 CBS_Example 0 65697742.20 79729368 153 -0.9534 303s 5 CBS_Example 0 79729368.34 99819310 199 -0.0497 303s > plotTracks(fit) 303s Warning message: 303s In plotTracks.CBS(fit) : 303s Setting default 'Clim' assuming the signal type is 'ratio' because signalType(fit) is unknown ('NA'). Use signalType(fit) <- 'ratio' to avoid this warning. 303s > 303s > 303s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 303s > # Segmentation with some known change points 303s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 303s > knownSegments <- data.frame( 303s + chromosome=c( 0, 0), 303s + start =x[c( 1, 401)], 303s + end =x[c(349, J)] 303s + ) 303s > fit2 <- segmentByCBS(y, x=x, knownSegments=knownSegments, verbose=TRUE) 303s Segmenting by CBS... 303s Chromosome: 0 303s Segmenting by CBS...done 303s > sampleName(fit2) <- "CBS_Example_2" 303s > print(fit2) 303s sampleName chromosome start end nbrOfLoci mean 303s 1 CBS_Example_2 0 65285.65 19648927 200 0.0109 303s 2 CBS_Example_2 0 19648927.46 28239656 95 0.9529 303s 3 CBS_Example_2 0 28239655.99 33106633 54 0.1169 303s 4 CBS_Example_2 0 38076667.59 65697742 248 -0.0408 303s 5 CBS_Example_2 0 65697742.20 79729368 153 -0.9534 303s 6 CBS_Example_2 0 79729368.34 99819310 199 -0.0497 303s > plotTracks(fit2) 303s Warning message: 303s In plotTracks.CBS(fit2) : 303s Setting default 'Clim' assuming the signal type is 'ratio' because signalType(fit2) is unknown ('NA'). Use signalType(fit2) <- 'ratio' to avoid this warning. 303s > abline(v=c(knownSegments$start, knownSegments$end)/1e6, lty=3) 303s > 303s > 303s > # Chromosome boundaries can be specified as -Inf and +Inf 303s > knownSegments <- data.frame( 303s + chromosome=c( 0, 0), 303s + start =c( -Inf, x[401]), 303s + end =c(x[349], +Inf) 303s + ) 303s > fit2b <- segmentByCBS(y, x=x, knownSegments=knownSegments, verbose=TRUE) 303s Segmenting by CBS... 303s Chromosome: 0 303s Segmenting by CBS...done 303s > sampleName(fit2b) <- "CBS_Example_2b" 303s > print(fit2b) 303s sampleName chromosome start end nbrOfLoci mean 303s 1 CBS_Example_2b 0 65285.65 19648927 200 0.0109 303s 2 CBS_Example_2b 0 19648927.46 28239656 95 0.9529 303s 3 CBS_Example_2b 0 28239655.99 33106633 54 0.1169 303s 4 CBS_Example_2b 0 38076667.59 65697742 248 -0.0408 303s 5 CBS_Example_2b 0 65697742.20 79729368 153 -0.9534 303s 6 CBS_Example_2b 0 79729368.34 99819310 199 -0.0497 303s > plotTracks(fit2b) 303s Warning message: 303s In plotTracks.CBS(fit2b) : 303s Setting default 'Clim' assuming the signal type is 'ratio' because signalType(fit2b) is unknown ('NA'). Use signalType(fit2b) <- 'ratio' to avoid this warning. 303s > abline(v=c(knownSegments$start, knownSegments$end)/1e6, lty=3) 303s > 303s > 303s > # As a proof of concept, it is possible to segment just the centromere, 303s > # which contains no data. All statistics will be NAs. 303s > knownSegments <- data.frame( 303s + chromosome=c( 0), 303s + start =x[c(350)], 303s + end =x[c(400)] 303s + ) 303s > fit3 <- segmentByCBS(y, x=x, knownSegments=knownSegments, verbose=TRUE) 303s Segmenting by CBS... 303s Chromosome: 0 303s Segmenting by CBS...done 303s > sampleName(fit3) <- "CBS_Example_3" 303s > print(fit3) 303s sampleName chromosome start end nbrOfLoci mean 303s 1 CBS_Example_3 0 33248518 37640521 0 NA 303s > plotTracks(fit3, Clim=c(0,5), xlim=c(0,100)) 303s > abline(v=c(knownSegments$start, knownSegments$end)/1e6, lty=3) 303s > 303s > 303s > 303s > # If one specify the (empty) centromere as a segment, then its 303s > # estimated statistics will be NAs, which becomes a natural 303s > # separator between the two "independent" arms. 303s > knownSegments <- data.frame( 303s + chromosome=c( 0, 0, 0), 303s + start =x[c( 1, 350, 401)], 303s + end =x[c(349, 400, J)] 303s + ) 303s > fit4 <- segmentByCBS(y, x=x, knownSegments=knownSegments, verbose=TRUE) 303s Segmenting by CBS... 303s Chromosome: 0 303s Segmenting by CBS...done 303s > sampleName(fit4) <- "CBS_Example_4" 303s > print(fit4) 303s sampleName chromosome start end nbrOfLoci mean 303s 1 CBS_Example_4 0 65285.65 19648927 200 0.0109 303s 2 CBS_Example_4 0 19648927.46 28239656 95 0.9529 303s 3 CBS_Example_4 0 28239655.99 33106633 54 0.1169 303s 4 CBS_Example_4 0 33248517.78 37640521 0 NA 303s 5 CBS_Example_4 0 38076667.59 65697742 248 -0.0408 303s 6 CBS_Example_4 0 65697742.20 79729368 153 -0.9534 303s 7 CBS_Example_4 0 79729368.34 99819310 199 -0.0497 303s > plotTracks(fit4) 303s Warning message: 303s In plotTracks.CBS(fit4) : 303s Setting default 'Clim' assuming the signal type is 'ratio' because signalType(fit4) is unknown ('NA'). Use signalType(fit4) <- 'ratio' to avoid this warning. 303s > abline(v=c(knownSegments$start, knownSegments$end)/1e6, lty=3) 303s > 303s > 303s > 303s > fit5 <- segmentByCBS(y, x=x, knownSegments=knownSegments, undo=Inf, verbose=TRUE) 303s Segmenting by CBS... 303s Chromosome: 0 303s Segmenting by CBS...done 303s > sampleName(fit5) <- "CBS_Example_5" 303s > print(fit5) 303s sampleName chromosome start end nbrOfLoci mean 303s 1 CBS_Example_5 0 65285.65 33106633 349 0.2836973 303s 2 CBS_Example_5 0 33248517.78 37640521 0 NA 303s 3 CBS_Example_5 0 38076667.59 99819310 600 -0.2764472 303s > plotTracks(fit5) 303s Warning message: 303s In plotTracks.CBS(fit5) : 303s Setting default 'Clim' assuming the signal type is 'ratio' because signalType(fit5) is unknown ('NA'). Use signalType(fit5) <- 'ratio' to avoid this warning. 303s > abline(v=c(knownSegments$start, knownSegments$end)/1e6, lty=3) 303s > stopifnot(nbrOfSegments(fit5) == nrow(knownSegments)) 303s > 303s > 303s > # One can also force a separator between two segments by setting 303s > # 'start' and 'end' to NAs ('chromosome' has to be given) 303s > knownSegments <- data.frame( 303s + chromosome=c( 0, 0, 0), 303s + start =x[c( 1, NA, 401)], 303s + end =x[c(349, NA, J)] 303s + ) 303s > fit6 <- segmentByCBS(y, x=x, knownSegments=knownSegments, verbose=TRUE) 303s Segmenting by CBS... 303s Chromosome: 0 303s Segmenting by CBS...done 303s > sampleName(fit6) <- "CBS_Example_6" 303s > print(fit6) 303s sampleName chromosome start end nbrOfLoci mean 303s 1 CBS_Example_6 0 65285.65 19648927 200 0.0109 303s 2 CBS_Example_6 0 19648927.46 28239656 95 0.9529 303s 3 CBS_Example_6 0 28239655.99 33106633 54 0.1169 303s 4 NA NA NA NA NA 303s 5 CBS_Example_6 0 38076667.59 65697742 248 -0.0408 303s 6 CBS_Example_6 0 65697742.20 79729368 153 -0.9534 303s 7 CBS_Example_6 0 79729368.34 99819310 199 -0.0497 303s > plotTracks(fit6) 303s Warning message: 303s In plotTracks.CBS(fit6) : 303s Setting default 'Clim' assuming the signal type is 'ratio' because signalType(fit6) is unknown ('NA'). Use signalType(fit6) <- 'ratio' to avoid this warning. 303s > abline(v=c(knownSegments$start, knownSegments$end)/1e6, lty=3) 303s > 303s > 303s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 303s > # Segment multiple chromosomes 303s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 303s > # Simulate multiple chromosomes 303s > fit1 <- renameChromosomes(fit, from=0, to=1) 303s > fit2 <- renameChromosomes(fit, from=0, to=2) 303s > fitM <- c(fit1, fit2) 303s > fitM <- segmentByCBS(fitM) 303s > sampleName(fitM) <- "CBS_Example_M" 303s > print(fitM) 303s sampleName chromosome start end nbrOfLoci mean 303s 1 CBS_Example_M 1 65285.65 19648927 200 0.0109 303s 2 CBS_Example_M 1 19648927.46 28239656 95 0.9529 303s 3 CBS_Example_M 1 28239655.99 65697742 302 -0.0126 303s 4 CBS_Example_M 1 65697742.20 79729368 153 -0.9534 303s 5 CBS_Example_M 1 79729368.34 99819310 199 -0.0497 303s 6 NA NA NA NA NA 303s 7 CBS_Example_M 2 65285.65 19648927 200 0.0109 303s 8 CBS_Example_M 2 19648927.46 28239656 95 0.9529 303s 9 CBS_Example_M 2 28239655.99 65697742 302 -0.0126 303s 10 CBS_Example_M 2 65697742.20 79729368 153 -0.9534 303s 11 CBS_Example_M 2 79729368.34 99819310 199 -0.0497 303s > plotTracks(fitM, Clim=c(-3,3)) 303s > 303s > 303s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 303s > # Tiling multiple chromosomes 303s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 303s > # Tile chromosomes 303s > fitT <- tileChromosomes(fitM) 303s > fitTb <- tileChromosomes(fitT) 303s > stopifnot(identical(fitTb, fitT)) 303s > 303s > 303s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 303s > # Write segmentation to file 303s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 303s > pathT <- tempdir() 303s > 303s > ## Tab-delimited file 303s > pathname <- writeSegments(fitM, path=pathT) 303s Warning message: 303s In write.table(file = pathnameT, data, append = TRUE, quote = FALSE, : 303s appending column names to file 303s > print(pathname) 303s [1] "/tmp/RtmpUL6KBN/CBS_Example_M.tsv" 303s > 303s > ## WIG file 303s > pathname <- writeWIG(fitM, path=pathT) 303s > print(pathname) 303s [1] "/tmp/RtmpUL6KBN/CBS_Example_M.wig" 303s > 303s > unlink(pathT, recursive=TRUE) 303s > 303s > proc.time() 303s user system elapsed 303s 2.377 0.030 2.403 303s Test segmentByCBS passed 303s 0 303s Begin test segmentByNonPairedPSCBS,medianDH 303s + [ 0 != 0 ] 303s + echo Test segmentByCBS passed 303s + echo 0 303s + echo Begin test segmentByNonPairedPSCBS,medianDH 303s + exitcode=0 303s + R CMD BATCH segmentByNonPairedPSCBS,medianDH.R 305s + cat segmentByNonPairedPSCBS,medianDH.Rout 305s 305s R version 4.5.2 (2025-10-31) -- "[Not] Part in a Rumble" 305s Copyright (C) 2025 The R Foundation for Statistical Computing 305s Platform: powerpc64le-unknown-linux-gnu 305s 305s R is free software and comes with ABSOLUTELY NO WARRANTY. 305s You are welcome to redistribute it under certain conditions. 305s Type 'license()' or 'licence()' for distribution details. 305s 305s R is a collaborative project with many contributors. 305s Type 'contributors()' for more information and 305s 'citation()' on how to cite R or R packages in publications. 305s 305s Type 'demo()' for some demos, 'help()' for on-line help, or 305s 'help.start()' for an HTML browser interface to help. 305s Type 'q()' to quit R. 305s 305s [Previously saved workspace restored] 305s 305s > library("PSCBS") 305s PSCBS v0.68.0 (2025-04-18 19:40:02 UTC) successfully loaded. See ?PSCBS for help. 305s > 305s > 305s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 305s > # Load SNP microarray data 305s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 305s > data <- PSCBS::exampleData("paired.chr01") 305s > str(data) 305s 'data.frame': 73346 obs. of 6 variables: 305s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 305s $ x : int 1145994 2224111 2319424 2543484 2926730 2941694 3084986 3155127 3292731 3695086 ... 305s $ CT : num 1.625 1.071 1.406 1.18 0.856 ... 305s $ betaT : num 0.757 0.771 0.834 0.778 0.229 ... 305s $ CN : num 2.36 2.13 2.59 1.93 1.71 ... 305s $ betaN : num 0.827 0.875 0.887 0.884 0.103 ... 305s > 305s > # Non-paired / tumor-only data 305s > data <- data[,c("chromosome", "x", "CT", "betaT")] 305s > str(data) 305s 'data.frame': 73346 obs. of 4 variables: 305s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 305s $ x : int 1145994 2224111 2319424 2543484 2926730 2941694 3084986 3155127 3292731 3695086 ... 305s $ CT : num 1.625 1.071 1.406 1.18 0.856 ... 305s $ betaT : num 0.757 0.771 0.834 0.778 0.229 ... 305s > 305s > 305s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 305s > # Paired PSCBS segmentation 305s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 305s > # Drop single-locus outliers 305s > dataS <- dropSegmentationOutliers(data) 305s > 305s > # Speed up example by segmenting fewer loci 305s > dataS <- dataS[seq(from=1, to=nrow(data), by=20),] 305s > 305s > # Fake a second chromosome 305s > dataT <- dataS 305s > dataT$chromosome <- 2L 305s > dataS <- rbind(dataS, dataT) 305s > rm(dataT) 305s > str(dataS) 305s 'data.frame': 7336 obs. of 4 variables: 305s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 305s $ x : int 1145994 4276892 5034491 6266412 8418532 11211748 13928296 14370144 15014887 16589707 ... 305s $ CT : num 1.63 1.16 1.35 1.39 1.55 ... 305s $ betaT : num 0.7574 0.0576 0.8391 0.7917 0.8141 ... 305s > 305s > # Non-Paired PSCBS segmentation 305s > fit <- segmentByNonPairedPSCBS(dataS, avgDH="median", seed=0xBEEF, verbose=-10) 305s Segmenting non-paired tumor signals using Non-paired PSCBS... 305s Number of loci: 7336 305s Number of SNPs: 7336 305s Calling "genotypes" from tumor allele B fractions... 305s num [1:7336] 0.7574 0.0576 0.8391 0.7917 0.8141 ... 305s Upper quantile: 0.475631667925522 305s Symmetric lower quantile: 0.290517384533512 305s (tauA, tauB) estimates: (%g,%g)0.2094826154664880.790517384533512 305s Homozygous treshholds: 305s [1] 0.2094826 0.7905174 305s Inferred germline genotypes (via tumor): 305s num [1:7336] 0.5 0 1 1 1 0 0 0 0.5 1 ... 305s muNx 305s 0 0.5 1 305s 2230 2910 2196 305s Calling "genotypes" from tumor allele B fractions...done 305s Segmenting non-paired tumor signals using Non-paired PSCBS...done 305s Segment using Paired PSCBS... 305s Segmenting paired tumor-normal signals using Paired PSCBS... 305s Setup up data... 305s 'data.frame': 7336 obs. of 6 variables: 305s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 305s $ x : num 1145994 4276892 5034491 6266412 8418532 ... 305s $ CT : num 1.63 1.16 1.35 1.39 1.55 ... 305s $ betaT : num 0.7574 0.0576 0.8391 0.7917 0.8141 ... 305s $ betaTN : num 0.7574 0.0576 0.8391 0.7917 0.8141 ... 305s $ muN : num 0.5 0 1 1 1 0 0 0 0.5 1 ... 305s Setup up data...done 305s Dropping loci for which TCNs are missing... 305s Number of loci dropped: 12 305s Dropping loci for which TCNs are missing...done 305s Ordering data along genome... 305s 'data.frame': 7324 obs. of 6 variables: 305s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 305s $ x : num 554484 1031563 1087198 1145994 1176365 ... 305s $ CT : num 1.88 1.64 1.77 1.63 1.59 ... 305s $ betaT : num 0.0646 0.6078 0.401 0.7574 0.645 ... 305s $ betaTN : num 0.0646 0.6078 0.401 0.7574 0.645 ... 305s $ muN : num 0 0.5 0.5 0.5 0.5 0.5 1 0.5 0.5 0.5 ... 305s Ordering data along genome...done 305s Segmenting multiple chromosomes... 305s Number of chromosomes: 2 305s Random seed temporarily set (seed=c(48879), kind="L'Ecuyer-CMRG") 305s Produced 2 seeds from this stream for future usage 305s Chromosome #1 ('Chr01') of 2... 305s 'data.frame': 3662 obs. of 7 variables: 305s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 305s $ x : num 554484 1031563 1087198 1145994 1176365 ... 305s $ CT : num 1.88 1.64 1.77 1.63 1.59 ... 305s $ betaT : num 0.0646 0.6078 0.401 0.7574 0.645 ... 305s $ betaTN : num 0.0646 0.6078 0.401 0.7574 0.645 ... 305s $ muN : num 0 0.5 0.5 0.5 0.5 0.5 1 0.5 0.5 0.5 ... 305s $ index : int 1 2 3 4 5 6 7 8 9 10 ... 305s Known segments: 305s [1] chromosome start end 305s <0 rows> (or 0-length row.names) 305s Segmenting paired tumor-normal signals using Paired PSCBS... 305s Setup up data... 305s 'data.frame': 3662 obs. of 6 variables: 305s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 305s $ x : num 554484 1031563 1087198 1145994 1176365 ... 305s $ CT : num 1.88 1.64 1.77 1.63 1.59 ... 305s $ betaT : num 0.0646 0.6078 0.401 0.7574 0.645 ... 305s $ betaTN : num 0.0646 0.6078 0.401 0.7574 0.645 ... 305s $ muN : num 0 0.5 0.5 0.5 0.5 0.5 1 0.5 0.5 0.5 ... 305s Setup up data...done 305s Ordering data along genome... 305s 'data.frame': 3662 obs. of 6 variables: 305s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 305s $ x : num 554484 1031563 1087198 1145994 1176365 ... 305s $ CT : num 1.88 1.64 1.77 1.63 1.59 ... 305s $ betaT : num 0.0646 0.6078 0.401 0.7574 0.645 ... 305s $ betaTN : num 0.0646 0.6078 0.401 0.7574 0.645 ... 305s $ muN : num 0 0.5 0.5 0.5 0.5 0.5 1 0.5 0.5 0.5 ... 305s Ordering data along genome...done 305s Keeping only current chromosome for 'knownSegments'... 305s Chromosome: 1 305s Known segments for this chromosome: 305s [1] chromosome start end 305s <0 rows> (or 0-length row.names) 305s Keeping only current chromosome for 'knownSegments'...done 305s alphaTCN: 0.009 305s alphaDH: 0.001 305s Number of loci: 3662 305s Calculating DHs... 305s Number of SNPs: 3662 305s Number of heterozygous SNPs: 1451 (39.62%) 305s Normalized DHs: 305s num [1:3662] NA 0.216 0.198 0.515 0.29 ... 305s Calculating DHs...done 305s Random seed temporarily set (seed=c(10407, 1066287653, -51199871, 161854402, -1995183193, 1503453565, -747102133), kind="L'Ecuyer-CMRG") 305s Produced 2 seeds from this stream for future usage 305s Identification of change points by total copy numbers... 305s Segmenting by CBS... 305s Chromosome: 1 305s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 305s Segmenting by CBS...done 305s List of 4 305s $ data :'data.frame': 3662 obs. of 4 variables: 305s ..$ chromosome: int [1:3662] 1 1 1 1 1 1 1 1 1 1 ... 305s ..$ x : num [1:3662] 554484 1031563 1087198 1145994 1176365 ... 305s ..$ y : num [1:3662] 1.88 1.64 1.77 1.63 1.59 ... 305s ..$ index : int [1:3662] 1 2 3 4 5 6 7 8 9 10 ... 305s $ output :'data.frame': 3 obs. of 6 variables: 305s ..$ sampleName: chr [1:3] NA NA NA 305s ..$ chromosome: int [1:3] 1 1 1 305s ..$ start : num [1:3] 5.54e+05 1.44e+08 1.85e+08 305s ..$ end : num [1:3] 1.44e+08 1.85e+08 2.47e+08 305s ..$ nbrOfLoci : int [1:3] 1880 671 1111 305s ..$ mean : num [1:3] 1.39 2.09 2.65 305s $ segRows:'data.frame': 3 obs. of 2 variables: 305s ..$ startRow: int [1:3] 1 1881 2552 305s ..$ endRow : int [1:3] 1880 2551 3662 305s $ params :List of 5 305s ..$ alpha : num 0.009 305s ..$ undo : num 0 305s ..$ joinSegments : logi TRUE 305s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 305s .. ..$ chromosome: int 1 305s .. ..$ start : num -Inf 305s .. ..$ end : num Inf 305s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 305s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 305s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.078 0 0.077 0 0 305s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 305s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 305s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 305s Identification of change points by total copy numbers...done 305s Restructure TCN segmentation results... 305s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean 305s 1 1 554484 143663981 1880 1.3916 305s 2 1 143663981 185240536 671 2.0925 305s 3 1 185240536 246679946 1111 2.6545 305s Number of TCN segments: 3 305s Restructure TCN segmentation results...done 305s TCN-only segmentation... 305s Total CN segment #1 ([ 554484,1.43664e+08]) of 3... 305s Number of TCN loci in segment: 1880 305s Locus data for TCN segment: 305s 'data.frame': 1880 obs. of 8 variables: 305s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 305s $ x : num 554484 1031563 1087198 1145994 1176365 ... 305s $ CT : num 1.88 1.64 1.77 1.63 1.59 ... 305s $ betaT : num 0.0646 0.6078 0.401 0.7574 0.645 ... 305s $ betaTN : num 0.0646 0.6078 0.401 0.7574 0.645 ... 305s $ muN : num 0 0.5 0.5 0.5 0.5 0.5 1 0.5 0.5 0.5 ... 305s $ index : int 1 2 3 4 5 6 7 8 9 10 ... 305s $ rho : num NA 0.216 0.198 0.515 0.29 ... 305s Number of loci: 1880 305s Number of SNPs: 765 (40.69%) 305s Number of heterozygous SNPs: 765 (100.00%) 305s Total CN segment #1 ([ 554484,1.43664e+08]) of 3...done 305s Total CN segment #2 ([1.43664e+08,1.85241e+08]) of 3... 305s Number of TCN loci in segment: 671 305s Locus data for TCN segment: 305s 'data.frame': 671 obs. of 8 variables: 305s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 305s $ x : num 1.44e+08 1.44e+08 1.44e+08 1.44e+08 1.44e+08 ... 305s $ CT : num 2.26 2.1 2.1 1.89 1.97 ... 305s $ betaT : num 0.958 0.19 0.909 0.13 0.141 ... 305s $ betaTN : num 0.958 0.19 0.909 0.13 0.141 ... 305s $ muN : num 1 0 1 0 0 0 0 0.5 0 1 ... 305s $ index : int 1881 1882 1883 1884 1885 1886 1887 1888 1889 1890 ... 305s $ rho : num NA NA NA NA NA ... 305s Number of loci: 671 305s Number of SNPs: 272 (40.54%) 305s Number of heterozygous SNPs: 272 (100.00%) 305s Total CN segment #2 ([1.43664e+08,1.85241e+08]) of 3...done 305s Total CN segment #3 ([1.85241e+08,2.4668e+08]) of 3... 305s Number of TCN loci in segment: 1111 305s Locus data for TCN segment: 305s 'data.frame': 1111 obs. of 8 variables: 305s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 305s $ x : num 1.85e+08 1.86e+08 1.86e+08 1.86e+08 1.86e+08 ... 305s $ CT : num 2.44 3 2.32 2.76 2.48 ... 305s $ betaT : num 0.0727 0.6845 0.2327 0.8118 0.0746 ... 305s $ betaTN : num 0.0727 0.6845 0.2327 0.8118 0.0746 ... 305s $ muN : num 0 0.5 0.5 1 0 1 0 1 1 0.5 ... 305s $ index : int 2552 2553 2554 2555 2556 2557 2558 2559 2560 2561 ... 305s $ rho : num NA 0.369 0.535 NA NA ... 305s Number of loci: 1111 305s Number of SNPs: 414 (37.26%) 305s Number of heterozygous SNPs: 414 (100.00%) 305s Total CN segment #3 ([1.85241e+08,2.4668e+08]) of 3...done 305s TCN-only segmentation...done 305s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 305s 1 1 1 1 554484 143663981 1880 1.3916 765 305s 2 1 2 1 143663981 185240536 671 2.0925 272 305s 3 1 3 1 185240536 246679946 1111 2.6545 414 305s tcnNbrOfHets dhNbrOfLoci dhStart dhEnd dhMean 305s 1 765 765 554484 143663981 0.3979122 305s 2 272 272 143663981 185240536 0.2306116 305s 3 414 414 185240536 246679946 0.2798120 305s Calculating (C1,C2) per segment... 305s Calculating (C1,C2) per segment...done 305s Number of segments: 3 305s Segmenting paired tumor-normal signals using Paired PSCBS...done 305s Updating mean level using different estimator... 305s TCN estimator: mean 305s DH estimator: median 305s Updating mean level using different estimator...done 305s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 305s 1 1 1 1 554484 143663981 1880 1.391608 765 305s 2 1 2 1 143663981 185240536 671 2.092452 272 305s 3 1 3 1 185240536 246679946 1111 2.654512 414 305s tcnNbrOfHets dhNbrOfLoci dhStart dhEnd dhMean c1Mean c2Mean 305s 1 765 765 554484 143663981 0.4206323 0.4031263 0.9884817 305s 2 272 272 143663981 185240536 0.1762428 0.8618360 1.2306156 305s 3 414 414 185240536 246679946 0.2697420 0.9692395 1.6852728 305s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 305s 1 1 1 1 554484 143663981 1880 1.391608 765 305s 2 1 2 1 143663981 185240536 671 2.092452 272 305s 3 1 3 1 185240536 246679946 1111 2.654512 414 305s tcnNbrOfHets dhNbrOfLoci dhStart dhEnd dhMean c1Mean c2Mean 305s 1 765 765 554484 143663981 0.4206323 0.4031263 0.9884817 305s 2 272 272 143663981 185240536 0.1762428 0.8618360 1.2306156 305s 3 414 414 185240536 246679946 0.2697420 0.9692395 1.6852728 305s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 305s 1 1 1 1 554484 143663981 1880 1.391608 765 305s 2 1 2 1 143663981 185240536 671 2.092452 272 305s 3 1 3 1 185240536 246679946 1111 2.654512 414 305s tcnNbrOfHets dhNbrOfLoci dhStart dhEnd dhMean c1Mean c2Mean 305s 1 765 765 554484 143663981 0.4206323 0.4031263 0.9884817 305s 2 272 272 143663981 185240536 0.1762428 0.8618360 1.2306156 305s 3 414 414 185240536 246679946 0.2697420 0.9692395 1.6852728 305s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 305s 1 1 1 1 554484 143663981 1880 1.391608 765 305s 2 1 2 1 143663981 185240536 671 2.092452 272 305s 3 1 3 1 185240536 246679946 1111 2.654512 414 305s tcnNbrOfHets dhNbrOfLoci dhStart dhEnd dhMean c1Mean c2Mean 305s 1 765 765 554484 143663981 0.4206323 0.4031263 0.9884817 305s 2 272 272 143663981 185240536 0.1762428 0.8618360 1.2306156 305s 3 414 414 185240536 246679946 0.2697420 0.9692395 1.6852728 305s Chromosome #1 ('Chr01') of 2...done 305s Chromosome #2 ('Chr02') of 2... 305s 'data.frame': 3662 obs. of 7 variables: 305s $ chromosome: int 2 2 2 2 2 2 2 2 2 2 ... 305s $ x : num 554484 1031563 1087198 1145994 1176365 ... 305s $ CT : num 1.88 1.64 1.77 1.63 1.59 ... 305s $ betaT : num 0.0646 0.6078 0.401 0.7574 0.645 ... 305s $ betaTN : num 0.0646 0.6078 0.401 0.7574 0.645 ... 305s $ muN : num 0 0.5 0.5 0.5 0.5 0.5 1 0.5 0.5 0.5 ... 305s $ index : int 3663 3664 3665 3666 3667 3668 3669 3670 3671 3672 ... 305s Known segments: 305s [1] chromosome start end 305s <0 rows> (or 0-length row.names) 305s Segmenting paired tumor-normal signals using Paired PSCBS... 305s Setup up data... 305s 'data.frame': 3662 obs. of 6 variables: 305s $ chromosome: int 2 2 2 2 2 2 2 2 2 2 ... 305s $ x : num 554484 1031563 1087198 1145994 1176365 ... 305s $ CT : num 1.88 1.64 1.77 1.63 1.59 ... 305s $ betaT : num 0.0646 0.6078 0.401 0.7574 0.645 ... 305s $ betaTN : num 0.0646 0.6078 0.401 0.7574 0.645 ... 305s $ muN : num 0 0.5 0.5 0.5 0.5 0.5 1 0.5 0.5 0.5 ... 305s Setup up data...done 305s Ordering data along genome... 305s 'data.frame': 3662 obs. of 6 variables: 305s $ chromosome: int 2 2 2 2 2 2 2 2 2 2 ... 305s $ x : num 554484 1031563 1087198 1145994 1176365 ... 305s $ CT : num 1.88 1.64 1.77 1.63 1.59 ... 305s $ betaT : num 0.0646 0.6078 0.401 0.7574 0.645 ... 305s $ betaTN : num 0.0646 0.6078 0.401 0.7574 0.645 ... 305s $ muN : num 0 0.5 0.5 0.5 0.5 0.5 1 0.5 0.5 0.5 ... 305s Ordering data along genome...done 305s Keeping only current chromosome for 'knownSegments'... 305s Chromosome: 2 305s Known segments for this chromosome: 305s [1] chromosome start end 305s <0 rows> (or 0-length row.names) 305s Keeping only current chromosome for 'knownSegments'...done 305s alphaTCN: 0.009 305s alphaDH: 0.001 305s Number of loci: 3662 305s Calculating DHs... 305s Number of SNPs: 3662 305s Number of heterozygous SNPs: 1451 (39.62%) 305s Normalized DHs: 305s num [1:3662] NA 0.216 0.198 0.515 0.29 ... 305s Calculating DHs...done 305s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 305s Produced 2 seeds from this stream for future usage 305s Identification of change points by total copy numbers... 305s Segmenting by CBS... 305s Chromosome: 2 305s Random seed temporarily set (seed=c(10407, -821273412, -52578226, 1415511586, 721384351, -665928286, 1316562960), kind="L'Ecuyer-CMRG") 305s Segmenting by CBS...done 305s List of 4 305s $ data :'data.frame': 3662 obs. of 4 variables: 305s ..$ chromosome: int [1:3662] 2 2 2 2 2 2 2 2 2 2 ... 305s ..$ x : num [1:3662] 554484 1031563 1087198 1145994 1176365 ... 305s ..$ y : num [1:3662] 1.88 1.64 1.77 1.63 1.59 ... 305s ..$ index : int [1:3662] 1 2 3 4 5 6 7 8 9 10 ... 305s $ output :'data.frame': 3 obs. of 6 variables: 305s ..$ sampleName: chr [1:3] NA NA NA 305s ..$ chromosome: int [1:3] 2 2 2 305s ..$ start : num [1:3] 5.54e+05 1.44e+08 1.85e+08 305s ..$ end : num [1:3] 1.44e+08 1.85e+08 2.47e+08 305s ..$ nbrOfLoci : int [1:3] 1880 671 1111 305s ..$ mean : num [1:3] 1.39 2.09 2.65 305s $ segRows:'data.frame': 3 obs. of 2 variables: 305s ..$ startRow: int [1:3] 1 1881 2552 305s ..$ endRow : int [1:3] 1880 2551 3662 305s $ params :List of 5 305s ..$ alpha : num 0.009 305s ..$ undo : num 0 305s ..$ joinSegments : logi TRUE 305s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 305s .. ..$ chromosome: int 2 305s .. ..$ start : num -Inf 305s .. ..$ end : num Inf 305s ..$ seed : int [1:7] 10407 -821273412 -52578226 1415511586 721384351 -665928286 1316562960 305s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 305s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.077 0 0.077 0 0 305s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 305s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 305s - attr(*, "randomSeed")= int [1:7] 10407 -821273412 -52578226 1415511586 721384351 -665928286 1316562960 305s Identification of change points by total copy numbers...done 305s Restructure TCN segmentation results... 305s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean 305s 1 2 554484 143663981 1880 1.3916 305s 2 2 143663981 185240536 671 2.0925 305s 3 2 185240536 246679946 1111 2.6545 305s Number of TCN segments: 3 305s Restructure TCN segmentation results...done 305s TCN-only segmentation... 305s Total CN segment #1 ([ 554484,1.43664e+08]) of 3... 305s Number of TCN loci in segment: 1880 305s Locus data for TCN segment: 305s 'data.frame': 1880 obs. of 8 variables: 305s $ chromosome: int 2 2 2 2 2 2 2 2 2 2 ... 305s $ x : num 554484 1031563 1087198 1145994 1176365 ... 305s $ CT : num 1.88 1.64 1.77 1.63 1.59 ... 305s $ betaT : num 0.0646 0.6078 0.401 0.7574 0.645 ... 305s $ betaTN : num 0.0646 0.6078 0.401 0.7574 0.645 ... 305s $ muN : num 0 0.5 0.5 0.5 0.5 0.5 1 0.5 0.5 0.5 ... 305s $ index : int 1 2 3 4 5 6 7 8 9 10 ... 305s $ rho : num NA 0.216 0.198 0.515 0.29 ... 305s Number of loci: 1880 305s Number of SNPs: 765 (40.69%) 305s Number of heterozygous SNPs: 765 (100.00%) 305s Total CN segment #1 ([ 554484,1.43664e+08]) of 3...done 305s Total CN segment #2 ([1.43664e+08,1.85241e+08]) of 3... 305s Number of TCN loci in segment: 671 305s Locus data for TCN segment: 305s 'data.frame': 671 obs. of 8 variables: 305s $ chromosome: int 2 2 2 2 2 2 2 2 2 2 ... 305s $ x : num 1.44e+08 1.44e+08 1.44e+08 1.44e+08 1.44e+08 ... 305s $ CT : num 2.26 2.1 2.1 1.89 1.97 ... 305s $ betaT : num 0.958 0.19 0.909 0.13 0.141 ... 305s $ betaTN : num 0.958 0.19 0.909 0.13 0.141 ... 305s $ muN : num 1 0 1 0 0 0 0 0.5 0 1 ... 305s $ index : int 1881 1882 1883 1884 1885 1886 1887 1888 1889 1890 ... 305s $ rho : num NA NA NA NA NA ... 305s Number of loci: 671 305s Number of SNPs: 272 (40.54%) 305s Number of heterozygous SNPs: 272 (100.00%) 305s Total CN segment #2 ([1.43664e+08,1.85241e+08]) of 3...done 305s Total CN segment #3 ([1.85241e+08,2.4668e+08]) of 3... 305s Number of TCN loci in segment: 1111 305s Locus data for TCN segment: 305s 'data.frame': 1111 obs. of 8 variables: 305s $ chromosome: int 2 2 2 2 2 2 2 2 2 2 ... 305s $ x : num 1.85e+08 1.86e+08 1.86e+08 1.86e+08 1.86e+08 ... 305s $ CT : num 2.44 3 2.32 2.76 2.48 ... 305s $ betaT : num 0.0727 0.6845 0.2327 0.8118 0.0746 ... 305s $ betaTN : num 0.0727 0.6845 0.2327 0.8118 0.0746 ... 305s $ muN : num 0 0.5 0.5 1 0 1 0 1 1 0.5 ... 305s $ index : int 2552 2553 2554 2555 2556 2557 2558 2559 2560 2561 ... 305s $ rho : num NA 0.369 0.535 NA NA ... 305s Number of loci: 1111 305s Number of SNPs: 414 (37.26%) 305s Number of heterozygous SNPs: 414 (100.00%) 305s Total CN segment #3 ([1.85241e+08,2.4668e+08]) of 3...done 305s TCN-only segmentation...done 305s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 305s 1 2 1 1 554484 143663981 1880 1.3916 765 305s 2 2 2 1 143663981 185240536 671 2.0925 272 305s 3 2 3 1 185240536 246679946 1111 2.6545 414 305s tcnNbrOfHets dhNbrOfLoci dhStart dhEnd dhMean 305s 1 765 765 554484 143663981 0.3979122 305s 2 272 272 143663981 185240536 0.2306116 305s 3 414 414 185240536 246679946 0.2798120 305s Calculating (C1,C2) per segment... 305s Calculating (C1,C2) per segment...done 305s Number of segments: 3 305s Segmenting paired tumor-normal signals using Paired PSCBS...done 305s Updating mean level using different estimator... 305s TCN estimator: mean 305s DH estimator: median 305s Updating mean level using different estimator...done 305s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 305s 1 2 1 1 554484 143663981 1880 1.391608 765 305s 2 2 2 1 143663981 185240536 671 2.092452 272 305s 3 2 3 1 185240536 246679946 1111 2.654512 414 305s tcnNbrOfHets dhNbrOfLoci dhStart dhEnd dhMean c1Mean c2Mean 305s 1 765 765 554484 143663981 0.4206323 0.4031263 0.9884817 305s 2 272 272 143663981 185240536 0.1762428 0.8618360 1.2306156 305s 3 414 414 185240536 246679946 0.2697420 0.9692395 1.6852728 305s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 305s 1 2 1 1 554484 143663981 1880 1.391608 765 305s 2 2 2 1 143663981 185240536 671 2.092452 272 305s 3 2 3 1 185240536 246679946 1111 2.654512 414 305s tcnNbrOfHets dhNbrOfLoci dhStart dhEnd dhMean c1Mean c2Mean 305s 1 765 765 554484 143663981 0.4206323 0.4031263 0.9884817 305s 2 272 272 143663981 185240536 0.1762428 0.8618360 1.2306156 305s 3 414 414 185240536 246679946 0.2697420 0.9692395 1.6852728 305s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 305s 1 2 1 1 554484 143663981 1880 1.391608 765 305s 2 2 2 1 143663981 185240536 671 2.092452 272 305s 3 2 3 1 185240536 246679946 1111 2.654512 414 305s tcnNbrOfHets dhNbrOfLoci dhStart dhEnd dhMean c1Mean c2Mean 305s 1 765 765 554484 143663981 0.4206323 0.4031263 0.9884817 305s 2 272 272 143663981 185240536 0.1762428 0.8618360 1.2306156 305s 3 414 414 185240536 246679946 0.2697420 0.9692395 1.6852728 305s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 305s 1 2 1 1 554484 143663981 1880 1.391608 765 305s 2 2 2 1 143663981 185240536 671 2.092452 272 305s 3 2 3 1 185240536 246679946 1111 2.654512 414 305s tcnNbrOfHets dhNbrOfLoci dhStart dhEnd dhMean c1Mean c2Mean 305s 1 765 765 554484 143663981 0.4206323 0.4031263 0.9884817 305s 2 272 272 143663981 185240536 0.1762428 0.8618360 1.2306156 305s 3 414 414 185240536 246679946 0.2697420 0.9692395 1.6852728 305s Chromosome #2 ('Chr02') of 2...done 305s Merging (independently) segmented chromosome... 305s List of 5 305s $ data :Classes 'PairedPSCNData' and 'data.frame': 7324 obs. of 7 variables: 305s ..$ chromosome: int [1:7324] 1 1 1 1 1 1 1 1 1 1 ... 305s ..$ x : num [1:7324] 554484 1031563 1087198 1145994 1176365 ... 305s ..$ CT : num [1:7324] 1.88 1.64 1.77 1.63 1.59 ... 305s ..$ betaT : num [1:7324] 0.0646 0.6078 0.401 0.7574 0.645 ... 305s ..$ betaTN : num [1:7324] 0.0646 0.6078 0.401 0.7574 0.645 ... 305s ..$ muN : num [1:7324] 0 0.5 0.5 0.5 0.5 0.5 1 0.5 0.5 0.5 ... 305s ..$ rho : num [1:7324] NA 0.216 0.198 0.515 0.29 ... 305s $ output :Classes 'PairedPSCNSegments' and 'data.frame': 7 obs. of 15 variables: 305s ..$ chromosome : int [1:7] 1 1 1 NA 2 2 2 305s ..$ tcnId : int [1:7] 1 2 3 NA 1 2 3 305s ..$ dhId : int [1:7] 1 1 1 NA 1 1 1 305s ..$ tcnStart : num [1:7] 5.54e+05 1.44e+08 1.85e+08 NA 5.54e+05 ... 305s ..$ tcnEnd : num [1:7] 1.44e+08 1.85e+08 2.47e+08 NA 1.44e+08 ... 305s ..$ tcnNbrOfLoci: int [1:7] 1880 671 1111 NA 1880 671 1111 305s ..$ tcnMean : num [1:7] 1.39 2.09 2.65 NA 1.39 ... 305s ..$ tcnNbrOfSNPs: int [1:7] 765 272 414 NA 765 272 414 305s ..$ tcnNbrOfHets: int [1:7] 765 272 414 NA 765 272 414 305s ..$ dhNbrOfLoci : int [1:7] 765 272 414 NA 765 272 414 305s ..$ dhStart : num [1:7] 5.54e+05 1.44e+08 1.85e+08 NA 5.54e+05 ... 305s ..$ dhEnd : num [1:7] 1.44e+08 1.85e+08 2.47e+08 NA 1.44e+08 ... 305s ..$ dhMean : num [1:7] 0.421 0.176 0.27 NA 0.421 ... 305s ..$ c1Mean : num [1:7] 0.403 0.862 0.969 NA 0.403 ... 305s ..$ c2Mean : num [1:7] 0.988 1.231 1.685 NA 0.988 ... 305s $ tcnSegRows:'data.frame': 7 obs. of 2 variables: 305s ..$ startRow: int [1:7] 1 1881 2552 NA 3663 5543 6214 305s ..$ endRow : int [1:7] 1880 2551 3662 NA 5542 6213 7324 305s $ dhSegRows :'data.frame': 7 obs. of 2 variables: 305s ..$ startRow: int [1:7] 2 1888 2553 NA 3664 5550 6215 305s ..$ endRow : int [1:7] 1876 2548 3659 NA 5538 6210 7321 305s $ params :List of 8 305s ..$ alphaTCN : num 0.009 305s ..$ alphaDH : num 0.001 305s ..$ flavor : chr "tcn" 305s ..$ tbn : logi FALSE 305s ..$ joinSegments : logi TRUE 305s ..$ knownSegments :'data.frame': 0 obs. of 3 variables: 305s .. ..$ chromosome: int(0) 305s .. ..$ start : int(0) 305s .. ..$ end : int(0) 305s ..$ seed : int [1:7] 10407 1066287653 -51199871 161854402 -1995183193 1503453565 -747102133 305s ..$ meanEstimators:List of 2 305s .. ..$ tcn: chr "mean" 305s .. ..$ dh : chr "median" 305s - attr(*, "class")= chr [1:3] "PairedPSCBS" "PSCBS" "AbstractCBS" 305s Merging (independently) segmented chromosome...done 305s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 305s 1 1 1 1 554484 143663981 1880 1.391608 765 305s 2 1 2 1 143663981 185240536 671 2.092452 272 305s 3 1 3 1 185240536 246679946 1111 2.654512 414 305s 4 NA NA NA NA NA NA NA NA 305s 5 2 1 1 554484 143663981 1880 1.391608 765 305s 6 2 2 1 143663981 185240536 671 2.092452 272 305s tcnNbrOfHets dhNbrOfLoci dhStart dhEnd dhMean c1Mean c2Mean 305s 1 765 765 554484 143663981 0.4206323 0.4031263 0.9884817 305s 2 272 272 143663981 185240536 0.1762428 0.8618360 1.2306156 305s 3 414 414 185240536 246679946 0.2697420 0.9692395 1.6852728 305s 4 NA NA NA NA NA NA NA 305s 5 765 765 554484 143663981 0.4206323 0.4031263 0.9884817 305s 6 272 272 143663981 185240536 0.1762428 0.8618360 1.2306156 305s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 305s 2 1 2 1 143663981 185240536 671 2.092452 272 305s 3 1 3 1 185240536 246679946 1111 2.654512 414 305s 4 NA NA NA NA NA NA NA NA 305s 5 2 1 1 554484 143663981 1880 1.391608 765 305s 6 2 2 1 143663981 185240536 671 2.092452 272 305s 7 2 3 1 185240536 246679946 1111 2.654512 414 305s tcnNbrOfHets dhNbrOfLoci dhStart dhEnd dhMean c1Mean c2Mean 305s 2 272 272 143663981 185240536 0.1762428 0.8618360 1.2306156 305s 3 414 414 185240536 246679946 0.2697420 0.9692395 1.6852728 305s 4 NA NA NA NA NA NA NA 305s 5 765 765 554484 143663981 0.4206323 0.4031263 0.9884817 305s 6 272 272 143663981 185240536 0.1762428 0.8618360 1.2306156 305s 7 414 414 185240536 246679946 0.2697420 0.9692395 1.6852728 305s Segmenting multiple chromosomes...done 305s Segmenting paired tumor-normal signals using Paired PSCBS...done 305s Segment using Paired PSCBS...done 305s Coercing to Non-Paired PSCBS results... 305s Coercing to Non-Paired PSCBS results...done 305s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 305s 1 1 1 1 554484 143663981 1880 1.391608 765 305s 2 1 2 1 143663981 185240536 671 2.092452 272 305s 3 1 3 1 185240536 246679946 1111 2.654512 414 305s 4 NA NA NA NA NA NA NA NA 305s 5 2 1 1 554484 143663981 1880 1.391608 765 305s 6 2 2 1 143663981 185240536 671 2.092452 272 305s tcnNbrOfHets dhNbrOfLoci dhStart dhEnd dhMean c1Mean c2Mean 305s 1 765 765 554484 143663981 0.4206323 0.4031263 0.9884817 305s 2 272 272 143663981 185240536 0.1762428 0.8618360 1.2306156 305s 3 414 414 185240536 246679946 0.2697420 0.9692395 1.6852728 305s 4 NA NA NA NA NA NA NA 305s 5 765 765 554484 143663981 0.4206323 0.4031263 0.9884817 305s 6 272 272 143663981 185240536 0.1762428 0.8618360 1.2306156 305s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 305s 2 1 2 1 143663981 185240536 671 2.092452 272 305s 3 1 3 1 185240536 246679946 1111 2.654512 414 305s 4 NA NA NA NA NA NA NA NA 305s 5 2 1 1 554484 143663981 1880 1.391608 765 305s 6 2 2 1 143663981 185240536 671 2.092452 272 305s 7 2 3 1 185240536 246679946 1111 2.654512 414 305s tcnNbrOfHets dhNbrOfLoci dhStart dhEnd dhMean c1Mean c2Mean 305s 2 272 272 143663981 185240536 0.1762428 0.8618360 1.2306156 305s 3 414 414 185240536 246679946 0.2697420 0.9692395 1.6852728 305s 4 NA NA NA NA NA NA NA 305s 5 765 765 554484 143663981 0.4206323 0.4031263 0.9884817 305s 6 272 272 143663981 185240536 0.1762428 0.8618360 1.2306156 305s 7 414 414 185240536 246679946 0.2697420 0.9692395 1.6852728 305s > print(fit) 305s chromosome tcnId dhId start end tcnNbrOfLoci tcnMean tcnNbrOfSNPs 305s 1 1 1 1 554484 143663981 1880 1.391608 765 305s 2 1 2 1 143663981 185240536 671 2.092452 272 305s 3 1 3 1 185240536 246679946 1111 2.654512 414 305s 4 NA NA NA NA NA NA NA NA 305s 5 2 1 1 554484 143663981 1880 1.391608 765 305s 6 2 2 1 143663981 185240536 671 2.092452 272 305s 7 2 3 1 185240536 246679946 1111 2.654512 414 305s tcnNbrOfHets dhNbrOfLoci dhMean c1Mean c2Mean 305s 1 765 765 0.4206323 0.4031263 0.9884817 305s 2 272 272 0.1762428 0.8618360 1.2306156 305s 3 414 414 0.2697420 0.9692395 1.6852728 305s 4 NA NA NA NA NA 305s 5 765 765 0.4206323 0.4031263 0.9884817 305s 6 272 272 0.1762428 0.8618360 1.2306156 305s 7 414 414 0.2697420 0.9692395 1.6852728 305s > 305s > 305s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 305s > # Bootstrap segment level estimates 305s > # (used by the AB caller, which, if skipped here, 305s > # will do it automatically) 305s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 305s > fit <- bootstrapTCNandDHByRegion(fit, B=100, verbose=-10) 305s Resample (TCN,DH) signals and re-estimate summaries for segment & changepoint... 305s Already done? 305s tcn_2.5% tcn_5% tcn_95% tcn_97.5% dh_2.5% dh_5% dh_95% dh_97.5% 305s FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE 305s c1_2.5% c1_5% c1_95% c1_97.5% c2_2.5% c2_5% c2_95% c2_97.5% 305s FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE 305s Bootstrapping (TCN,DH,C1,C2) segment mean levels... 305s Identifying heterozygous & homozygous SNPs and non-polymorphic loci... 305s Number of loci: 7324 305s Number of SNPs: 2902 305s Number of non-SNPs: 4422 305s Identifying heterozygous & homozygous SNPs and non-polymorphic loci...done 305s num [1:7, 1:100, 1:4] NA NA NA NA NA NA NA NA NA NA ... 305s - attr(*, "dimnames")=List of 3 305s ..$ : NULL 305s ..$ : NULL 305s ..$ : chr [1:4] "tcn" "dh" "c1" "c2" 305s Segment #1 (chr 1, tcnId=1, dhId=1) of 7... 305s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 305s 1 1 1 1 554484 143663981 1880 1.391608 765 305s tcnNbrOfHets dhNbrOfLoci dhStart dhEnd dhMean c1Mean c2Mean 305s 1 765 765 554484 143663981 0.4206323 0.4031263 0.9884817 305s Number of TCNs: 1880 305s Number of DHs: 765 305s int [1:1880] 1 2 3 4 5 6 7 8 9 10 ... 305s int [1:7324] 1 2 3 4 5 6 7 8 9 10 ... 305s int [1:1880] 1 2 3 4 5 6 7 8 9 10 ... 305s Identify loci used to bootstrap DH means... 305s Heterozygous SNPs to resample for DH: 305s int [1:765] 2 3 4 5 6 8 9 10 11 12 ... 305s Identify loci used to bootstrap DH means...done 305s Identify loci used to bootstrap TCN means... 305s SNPs: 305s int [1:765] 2 3 4 5 6 8 9 10 11 12 ... 305s Non-polymorphic loci: 305s int [1:1115] 1 7 15 28 30 32 34 35 36 37 ... 305s Heterozygous SNPs to resample for TCN: 305s int [1:765] 2 3 4 5 6 8 9 10 11 12 ... 305s Homozygous SNPs to resample for TCN: 305s int(0) 305s Non-polymorphic loci to resample for TCN: 305s int [1:1115] 1 7 15 28 30 32 34 35 36 37 ... 305s Heterozygous SNPs with non-DH to resample for TCN: 305s int(0) 305s Loci to resample for TCN: 305s int [1:1880] 1 2 3 4 5 6 7 8 9 10 ... 305s Identify loci used to bootstrap TCN means...done 305s Number of (#hets, #homs, #nonSNPs): (765,0,1115) 305s Bootstrapping while preserving (#hets, #homs, #nonSNPs)... 305s Number of bootstrap samples: 100 305s Bootstrapping while preserving (#hets, #homs, #nonSNPs)...done 305s Segment #1 (chr 1, tcnId=1, dhId=1) of 7...done 305s Segment #2 (chr 1, tcnId=2, dhId=1) of 7... 305s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 305s 2 1 2 1 143663981 185240536 671 2.092452 272 305s tcnNbrOfHets dhNbrOfLoci dhStart dhEnd dhMean c1Mean c2Mean 305s 2 272 272 143663981 185240536 0.1762428 0.861836 1.230616 305s Number of TCNs: 671 305s Number of DHs: 272 305s int [1:671] 1881 1882 1883 1884 1885 1886 1887 1888 1889 1890 ... 305s int [1:7324] 1 2 3 4 5 6 7 8 9 10 ... 305s int [1:671] 1881 1882 1883 1884 1885 1886 1887 1888 1889 1890 ... 305s Identify loci used to bootstrap DH means... 305s Heterozygous SNPs to resample for DH: 305s int [1:272] 1888 1893 1894 1895 1896 1897 1901 1903 1907 1908 ... 305s Identify loci used to bootstrap DH means...done 305s Identify loci used to bootstrap TCN means... 305s SNPs: 305s int [1:272] 1888 1893 1894 1895 1896 1897 1901 1903 1907 1908 ... 305s Non-polymorphic loci: 305s int [1:399] 1881 1882 1883 1884 1885 1886 1887 1889 1890 1891 ... 305s Heterozygous SNPs to resample for TCN: 305s int [1:272] 1888 1893 1894 1895 1896 1897 1901 1903 1907 1908 ... 305s Homozygous SNPs to resample for TCN: 305s int(0) 305s Non-polymorphic loci to resample for TCN: 305s int [1:399] 1881 1882 1883 1884 1885 1886 1887 1889 1890 1891 ... 305s Heterozygous SNPs with non-DH to resample for TCN: 305s int(0) 305s Loci to resample for TCN: 305s int [1:671] 1881 1882 1883 1884 1885 1886 1887 1888 1889 1890 ... 305s Identify loci used to bootstrap TCN means...done 305s Number of (#hets, #homs, #nonSNPs): (272,0,399) 305s Bootstrapping while preserving (#hets, #homs, #nonSNPs)... 305s Number of bootstrap samples: 100 305s Bootstrapping while preserving (#hets, #homs, #nonSNPs)...done 305s Segment #2 (chr 1, tcnId=2, dhId=1) of 7...done 305s Segment #3 (chr 1, tcnId=3, dhId=1) of 7... 305s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 305s 3 1 3 1 185240536 246679946 1111 2.654512 414 305s tcnNbrOfHets dhNbrOfLoci dhStart dhEnd dhMean c1Mean c2Mean 305s 3 414 414 185240536 246679946 0.269742 0.9692395 1.685273 305s Number of TCNs: 1111 305s Number of DHs: 414 305s int [1:1111] 2552 2553 2554 2555 2556 2557 2558 2559 2560 2561 ... 305s int [1:7324] 1 2 3 4 5 6 7 8 9 10 ... 305s int [1:1111] 2552 2553 2554 2555 2556 2557 2558 2559 2560 2561 ... 305s Identify loci used to bootstrap DH means... 305s Heterozygous SNPs to resample for DH: 305s int [1:414] 2553 2554 2561 2562 2563 2568 2569 2572 2573 2574 ... 305s Identify loci used to bootstrap DH means...done 305s Identify loci used to bootstrap TCN means... 305s SNPs: 305s int [1:414] 2553 2554 2561 2562 2563 2568 2569 2572 2573 2574 ... 305s Non-polymorphic loci: 305s int [1:697] 2552 2555 2556 2557 2558 2559 2560 2564 2565 2566 ... 305s Heterozygous SNPs to resample for TCN: 305s int [1:414] 2553 2554 2561 2562 2563 2568 2569 2572 2573 2574 ... 305s Homozygous SNPs to resample for TCN: 305s int(0) 305s Non-polymorphic loci to resample for TCN: 305s int [1:697] 2552 2555 2556 2557 2558 2559 2560 2564 2565 2566 ... 305s Heterozygous SNPs with non-DH to resample for TCN: 305s int(0) 305s Loci to resample for TCN: 305s int [1:1111] 2552 2553 2554 2555 2556 2557 2558 2559 2560 2561 ... 305s Identify loci used to bootstrap TCN means...done 305s Number of (#hets, #homs, #nonSNPs): (414,0,697) 305s Bootstrapping while preserving (#hets, #homs, #nonSNPs)... 305s Number of bootstrap samples: 100 305s Bootstrapping while preserving (#hets, #homs, #nonSNPs)...done 305s Segment #3 (chr 1, tcnId=3, dhId=1) of 7...done 305s Segment #5 (chr 2, tcnId=1, dhId=1) of 7... 305s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 305s 5 2 1 1 554484 143663981 1880 1.391608 765 305s tcnNbrOfHets dhNbrOfLoci dhStart dhEnd dhMean c1Mean c2Mean 305s 5 765 765 554484 143663981 0.4206323 0.4031263 0.9884817 305s Number of TCNs: 1880 305s Number of DHs: 765 305s int [1:1880] 3663 3664 3665 3666 3667 3668 3669 3670 3671 3672 ... 305s int [1:7324] 1 2 3 4 5 6 7 8 9 10 ... 305s int [1:1880] 3663 3664 3665 3666 3667 3668 3669 3670 3671 3672 ... 305s Identify loci used to bootstrap DH means... 305s Heterozygous SNPs to resample for DH: 305s int [1:765] 3664 3665 3666 3667 3668 3670 3671 3672 3673 3674 ... 305s Identify loci used to bootstrap DH means...done 305s Identify loci used to bootstrap TCN means... 305s SNPs: 305s int [1:765] 3664 3665 3666 3667 3668 3670 3671 3672 3673 3674 ... 305s Non-polymorphic loci: 305s int [1:1115] 3663 3669 3677 3690 3692 3694 3696 3697 3698 3699 ... 305s Heterozygous SNPs to resample for TCN: 305s int [1:765] 3664 3665 3666 3667 3668 3670 3671 3672 3673 3674 ... 305s Homozygous SNPs to resample for TCN: 305s int(0) 305s Non-polymorphic loci to resample for TCN: 305s int [1:1115] 3663 3669 3677 3690 3692 3694 3696 3697 3698 3699 ... 305s Heterozygous SNPs with non-DH to resample for TCN: 305s int(0) 305s Loci to resample for TCN: 305s int [1:1880] 3663 3664 3665 3666 3667 3668 3669 3670 3671 3672 ... 305s Identify loci used to bootstrap TCN means...done 305s Number of (#hets, #homs, #nonSNPs): (765,0,1115) 305s Bootstrapping while preserving (#hets, #homs, #nonSNPs)... 305s Number of bootstrap samples: 100 305s Bootstrapping while preserving (#hets, #homs, #nonSNPs)...done 305s Segment #5 (chr 2, tcnId=1, dhId=1) of 7...done 305s Segment #6 (chr 2, tcnId=2, dhId=1) of 7... 305s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 305s 6 2 2 1 143663981 185240536 671 2.092452 272 305s tcnNbrOfHets dhNbrOfLoci dhStart dhEnd dhMean c1Mean c2Mean 305s 6 272 272 143663981 185240536 0.1762428 0.861836 1.230616 305s Number of TCNs: 671 305s Number of DHs: 272 305s int [1:671] 5543 5544 5545 5546 5547 5548 5549 5550 5551 5552 ... 305s int [1:7324] 1 2 3 4 5 6 7 8 9 10 ... 305s int [1:671] 5543 5544 5545 5546 5547 5548 5549 5550 5551 5552 ... 305s Identify loci used to bootstrap DH means... 305s Heterozygous SNPs to resample for DH: 305s int [1:272] 5550 5555 5556 5557 5558 5559 5563 5565 5569 5570 ... 305s Identify loci used to bootstrap DH means...done 305s Identify loci used to bootstrap TCN means... 305s SNPs: 305s int [1:272] 5550 5555 5556 5557 5558 5559 5563 5565 5569 5570 ... 305s Non-polymorphic loci: 305s int [1:399] 5543 5544 5545 5546 5547 5548 5549 5551 5552 5553 ... 305s Heterozygous SNPs to resample for TCN: 305s int [1:272] 5550 5555 5556 5557 5558 5559 5563 5565 5569 5570 ... 305s Homozygous SNPs to resample for TCN: 305s int(0) 305s Non-polymorphic loci to resample for TCN: 305s int [1:399] 5543 5544 5545 5546 5547 5548 5549 5551 5552 5553 ... 305s Heterozygous SNPs with non-DH to resample for TCN: 305s int(0) 305s Loci to resample for TCN: 305s int [1:671] 5543 5544 5545 5546 5547 5548 5549 5550 5551 5552 ... 305s Identify loci used to bootstrap TCN means...done 305s Number of (#hets, #homs, #nonSNPs): (272,0,399) 305s Bootstrapping while preserving (#hets, #homs, #nonSNPs)... 305s Number of bootstrap samples: 100 305s Bootstrapping while preserving (#hets, #homs, #nonSNPs)...done 305s Segment #6 (chr 2, tcnId=2, dhId=1) of 7...done 305s Segment #7 (chr 2, tcnId=3, dhId=1) of 7... 305s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 305s 7 2 3 1 185240536 246679946 1111 2.654512 414 305s tcnNbrOfHets dhNbrOfLoci dhStart dhEnd dhMean c1Mean c2Mean 305s 7 414 414 185240536 246679946 0.269742 0.9692395 1.685273 305s Number of TCNs: 1111 305s Number of DHs: 414 305s int [1:1111] 6214 6215 6216 6217 6218 6219 6220 6221 6222 6223 ... 305s int [1:7324] 1 2 3 4 5 6 7 8 9 10 ... 305s int [1:1111] 6214 6215 6216 6217 6218 6219 6220 6221 6222 6223 ... 305s Identify loci used to bootstrap DH means... 305s Heterozygous SNPs to resample for DH: 305s int [1:414] 6215 6216 6223 6224 6225 6230 6231 6234 6235 6236 ... 305s Identify loci used to bootstrap DH means...done 305s Identify loci used to bootstrap TCN means... 305s SNPs: 305s int [1:414] 6215 6216 6223 6224 6225 6230 6231 6234 6235 6236 ... 305s Non-polymorphic loci: 305s int [1:697] 6214 6217 6218 6219 6220 6221 6222 6226 6227 6228 ... 305s Heterozygous SNPs to resample for TCN: 305s int [1:414] 6215 6216 6223 6224 6225 6230 6231 6234 6235 6236 ... 305s Homozygous SNPs to resample for TCN: 305s int(0) 305s Non-polymorphic loci to resample for TCN: 305s int [1:697] 6214 6217 6218 6219 6220 6221 6222 6226 6227 6228 ... 305s Heterozygous SNPs with non-DH to resample for TCN: 305s int(0) 305s Loci to resample for TCN: 305s int [1:1111] 6214 6215 6216 6217 6218 6219 6220 6221 6222 6223 ... 305s Identify loci used to bootstrap TCN means...done 305s Number of (#hets, #homs, #nonSNPs): (414,0,697) 305s Bootstrapping while preserving (#hets, #homs, #nonSNPs)... 305s Number of bootstrap samples: 100 305s Bootstrapping while preserving (#hets, #homs, #nonSNPs)...done 305s Segment #7 (chr 2, tcnId=3, dhId=1) of 7...done 305s Bootstrapped segment mean levels 305s num [1:7, 1:100, 1:4] 1.4 2.09 2.64 NA 1.39 ... 305s - attr(*, "dimnames")=List of 3 305s ..$ : NULL 305s ..$ : NULL 305s ..$ : chr [1:4] "tcn" "dh" "c1" "c2" 305s Calculating (C1,C2) mean levels from (TCN,DH) mean levels... 305s num [1:7, 1:100, 1:4] 1.4 2.09 2.64 NA 1.39 ... 305s - attr(*, "dimnames")=List of 3 305s ..$ : NULL 305s ..$ : NULL 305s ..$ : chr [1:4] "tcn" "dh" "c1" "c2" 305s Calculating (C1,C2) mean levels from (TCN,DH) mean levels...done 305s Calculating polar (alpha,radius,manhattan) for change points... 305s num [1:6, 1:100, 1:2] -0.448 -0.131 NA NA -0.477 ... 305s - attr(*, "dimnames")=List of 3 305s ..$ : NULL 305s ..$ : NULL 305s ..$ : chr [1:2] "c1" "c2" 305s Bootstrapped change points 305s num [1:6, 1:100, 1:5] -2.65 -1.87 NA NA -2.72 ... 305s - attr(*, "dimnames")=List of 3 305s ..$ : NULL 305s ..$ : NULL 305s ..$ : chr [1:5] "alpha" "radius" "manhattan" "d1" ... 305s Calculating polar (alpha,radius,manhattan) for change points...done 305s Bootstrapping (TCN,DH,C1,C2) segment mean levels...done 305s Summarizing bootstrapped segment ('tcn', 'dh', 'c1', 'c2') data... 305s num [1:7, 1:4, 1:4] NA NA NA NA NA NA NA NA NA NA ... 305s - attr(*, "dimnames")=List of 3 305s ..$ : NULL 305s ..$ : chr [1:4] "2.5%" "5%" "95%" "97.5%" 305s ..$ : chr [1:4] "tcn" "dh" "c1" "c2" 305s Field #1 ('tcn') of 4... 305s Segment #1 of 7... 305s Segment #1 of 7...done 305s Segment #2 of 7... 305s Segment #2 of 7...done 305s Segment #3 of 7... 305s Segment #3 of 7...done 305s Segment #4 of 7... 305s Segment #4 of 7...done 305s Segment #5 of 7... 305s Segment #5 of 7...done 305s Segment #6 of 7... 305s Segment #6 of 7...done 305s Segment #7 of 7... 305s Segment #7 of 7...done 305s Field #1 ('tcn') of 4...done 305s Field #2 ('dh') of 4... 305s Segment #1 of 7... 305s Segment #1 of 7...done 305s Segment #2 of 7... 305s Segment #2 of 7...done 305s Segment #3 of 7... 305s Segment #3 of 7...done 305s Segment #4 of 7... 305s Segment #4 of 7...done 305s Segment #5 of 7... 305s Segment #5 of 7...done 305s Segment #6 of 7... 305s Segment #6 of 7...done 305s Segment #7 of 7... 305s Segment #7 of 7...done 305s Field #2 ('dh') of 4...done 305s Field #3 ('c1') of 4... 305s Segment #1 of 7... 305s Segment #1 of 7...done 305s Segment #2 of 7... 305s Segment #2 of 7...done 305s Segment #3 of 7... 305s Segment #3 of 7...done 305s Segment #4 of 7... 305s Segment #4 of 7...done 305s Segment #5 of 7... 305s Segment #5 of 7...done 305s Segment #6 of 7... 305s Segment #6 of 7...done 305s Segment #7 of 7... 305s Segment #7 of 7...done 305s Field #3 ('c1') of 4...done 305s Field #4 ('c2') of 4... 305s Segment #1 of 7... 305s Segment #1 of 7...done 305s Segment #2 of 7... 305s Segment #2 of 7...done 305s Segment #3 of 7... 305s Segment #3 of 7...done 305s Segment #4 of 7... 305s Segment #4 of 7...done 305s Segment #5 of 7... 305s Segment #5 of 7...done 305s Segment #6 of 7... 305s Segment #6 of 7...done 305s Segment #7 of 7... 305s Segment #7 of 7...done 305s Field #4 ('c2') of 4...done 305s Bootstrap statistics 305s num [1:7, 1:4, 1:4] 1.38 2.07 2.63 NA 1.38 ... 305s - attr(*, "dimnames")=List of 3 305s ..$ : NULL 305s ..$ : chr [1:4] "2.5%" "5%" "95%" "97.5%" 305s ..$ : chr [1:4] "tcn" "dh" "c1" "c2" 305s Statistical sanity checks (iff B >= 100)... 305s Available summaries: 2.5%, 5%, 95%, 97.5% 305s Available quantiles: 0.025, 0.05, 0.95, 0.975 305s num [1:7, 1:4, 1:4] 1.38 2.07 2.63 NA 1.38 ... 305s - attr(*, "dimnames")=List of 3 305s ..$ : NULL 305s ..$ : chr [1:4] "2.5%" "5%" "95%" "97.5%" 305s ..$ : chr [1:4] "tcn" "dh" "c1" "c2" 305s Field #1 ('tcn') of 4... 305s Seg 1. mean=1.39161, range=[1.38025,1.40693], n=1880 305s Seg 2. mean=2.09245, range=[2.06856,2.1165], n=671 305s Seg 3. mean=2.65451, range=[2.62678,2.6834], n=1111 305s Seg 4. mean=NA, range=[NA,NA], n=NA 305s Seg 5. mean=1.39161, range=[1.37999,1.40474], n=1880 305s Seg 6. mean=2.09245, range=[2.06923,2.11747], n=671 305s Seg 7. mean=2.65451, range=[2.62867,2.68639], n=1111 305s Field #1 ('tcn') of 4...done 305s Field #2 ('dh') of 4... 305s Seg 1. mean=0.420632, range=[0.406983,0.437756], n=765 305s Seg 2. mean=0.176243, range=[0.141232,0.202975], n=272 305s Seg 3. mean=0.269742, range=[0.245337,0.292784], n=414 305s Seg 4. mean=NA, range=[NA,NA], n=NA 305s Seg 5. mean=0.420632, range=[0.406204,0.436189], n=765 305s Seg 6. mean=0.176243, range=[0.13696,0.212132], n=272 305s Seg 7. mean=0.269742, range=[0.230034,0.296763], n=414 305s Field #2 ('dh') of 4...done 305s Field #3 ('c1') of 4... 305s Seg 1. mean=0.403126, range=[0.391189,0.413437], n=765 305s Seg 2. mean=0.861836, range=[0.833296,0.900874], n=272 305s Seg 3. mean=0.969239, range=[0.937437,1.00659], n=414 305s Seg 4. mean=NA, range=[NA,NA], n=NA 305s Seg 5. mean=0.403126, range=[0.392112,0.414529], n=765 305s Seg 6. mean=0.861836, range=[0.823193,0.907577], n=272 305s Seg 7. mean=0.969239, range=[0.931951,1.01968], n=414 305s Field #3 ('c1') of 4...done 305s Field #4 ('c2') of 4... 305s Seg 1. mean=0.988482, range=[0.974501,1.00244], n=765 305s Seg 2. mean=1.23062, range=[1.18964,1.26157], n=272 305s Seg 3. mean=1.68527, range=[1.6481,1.72497], n=414 305s Seg 4. mean=NA, range=[NA,NA], n=NA 305s Seg 5. mean=0.988482, range=[0.9761,1.00076], n=765 305s Seg 6. mean=1.23062, range=[1.18936,1.26647], n=272 305s Seg 7. mean=1.68527, range=[1.63171,1.72526], n=414 305s Field #4 ('c2') of 4...done 305s Statistical sanity checks (iff B >= 100)...done 305s Summarizing bootstrapped segment ('tcn', 'dh', 'c1', 'c2') data...done 305s Summarizing bootstrapped changepoint ('alpha', 'radius', 'manhattan', 'd1', 'd2') data... 305s num [1:6, 1:4, 1:5] NA NA NA NA NA NA NA NA NA NA ... 305s - attr(*, "dimnames")=List of 3 305s ..$ : NULL 305s ..$ : chr [1:4] "2.5%" "5%" "95%" "97.5%" 305s ..$ : chr [1:5] "alpha" "radius" "manhattan" "d1" ... 305s Field #1 ('alpha') of 5... 305s Changepoint #1 of 6... 305s Changepoint #1 of 6...done 305s Changepoint #2 of 6... 305s Changepoint #2 of 6...done 305s Changepoint #3 of 6... 305s Changepoint #3 of 6...done 305s Changepoint #4 of 6... 305s Changepoint #4 of 6...done 305s Changepoint #5 of 6... 305s Changepoint #5 of 6...done 305s Changepoint #6 of 6... 305s Changepoint #6 of 6...done 305s Field #1 ('alpha') of 5...done 305s Field #2 ('radius') of 5... 305s Changepoint #1 of 6... 305s Changepoint #1 of 6...done 305s Changepoint #2 of 6... 305s Changepoint #2 of 6...done 305s Changepoint #3 of 6... 305s Changepoint #3 of 6...done 305s Changepoint #4 of 6... 305s Changepoint #4 of 6...done 305s Changepoint #5 of 6... 305s Changepoint #5 of 6...done 305s Changepoint #6 of 6... 305s Changepoint #6 of 6...done 305s Field #2 ('radius') of 5...done 305s Field #3 ('manhattan') of 5... 305s Changepoint #1 of 6... 305s Changepoint #1 of 6...done 305s Changepoint #2 of 6... 305s Changepoint #2 of 6...done 305s Changepoint #3 of 6... 305s Changepoint #3 of 6...done 305s Changepoint #4 of 6... 305s Changepoint #4 of 6...done 305s Changepoint #5 of 6... 305s Changepoint #5 of 6...done 305s Changepoint #6 of 6... 305s Changepoint #6 of 6...done 305s Field #3 ('manhattan') of 5...done 305s Field #4 ('d1') of 5... 305s Changepoint #1 of 6... 305s Changepoint #1 of 6...done 305s Changepoint #2 of 6... 305s Changepoint #2 of 6...done 305s Changepoint #3 of 6... 305s Changepoint #3 of 6...done 305s Changepoint #4 of 6... 305s Changepoint #4 of 6...done 305s Changepoint #5 of 6... 305s Changepoint #5 of 6...done 305s Changepoint #6 of 6... 305s Changepoint #6 of 6...done 305s Field #4 ('d1') of 5...done 305s Field #5 ('d2') of 5... 305s Changepoint #1 of 6... 305s Changepoint #1 of 6...done 305s Changepoint #2 of 6... 305s Changepoint #2 of 6...done 305s Changepoint #3 of 6... 305s Changepoint #3 of 6...done 305s Changepoint #4 of 6... 305s Changepoint #4 of 6...done 305s Changepoint #5 of 6... 305s Changepoint #5 of 6...done 305s Changepoint #6 of 6... 305s Changepoint #6 of 6...done 305s Field #5 ('d2') of 5...done 305s Bootstrap statistics 305s num [1:6, 1:4, 1:5] -2.76 -1.91 NA NA -2.76 ... 305s - attr(*, "dimnames")=List of 3 305s ..$ : NULL 305s ..$ : chr [1:4] "2.5%" "5%" "95%" "97.5%" 305s ..$ : chr [1:5] "alpha" "radius" "manhattan" "d1" ... 305s Summarizing bootstrapped changepoint ('alpha', 'radius', 'manhattan', 'd1', 'd2') data...done 305s Resample (TCN,DH) signals and re-estimate summaries for segment & changepoint...done 305s > print(fit) 305s chromosome tcnId dhId start end tcnNbrOfLoci tcnMean tcnNbrOfSNPs 305s 1 1 1 1 554484 143663981 1880 1.391608 765 305s 2 1 2 1 143663981 185240536 671 2.092452 272 305s 3 1 3 1 185240536 246679946 1111 2.654512 414 305s 4 NA NA NA NA NA NA NA NA 305s 5 2 1 1 554484 143663981 1880 1.391608 765 305s 6 2 2 1 143663981 185240536 671 2.092452 272 305s 7 2 3 1 185240536 246679946 1111 2.654512 414 305s tcnNbrOfHets dhNbrOfLoci dhMean c1Mean c2Mean 305s 1 765 765 0.4206323 0.4031263 0.9884817 305s 2 272 272 0.1762428 0.8618360 1.2306156 305s 3 414 414 0.2697420 0.9692395 1.6852728 305s 4 NA NA NA NA NA 305s 5 765 765 0.4206323 0.4031263 0.9884817 305s 6 272 272 0.1762428 0.8618360 1.2306156 305s 7 414 414 0.2697420 0.9692395 1.6852728 305s > 305s > 305s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 305s > # Calling segments in allelic balance (AB) 305s > # NOTE: Ideally, this should be done on whole-genome data 305s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 305s > # Explicitly estimate the threshold in DH for calling AB 305s > # (which be done by default by the caller, if skipped here) 305s > deltaAB <- estimateDeltaAB(fit, flavor="qq(DH)", verbose=-10) 305s Estimating DH threshold for calling allelic imbalances... 305s flavor: qq(DH) 305s scale: 1 305s Estimating DH threshold for AB caller... 305s quantile #1: 0.05 305s Symmetric quantile #2: 0.9 305s Number of segments: 6 305s Weighted 5% quantile of DH: 0.199618 305s Number of segments with small DH: 2 305s Number of data points: 1342 305s Number of finite data points: 544 305s Estimate of (1-0.9):th and 50% quantiles: (0.0289919,0.176243) 305s Estimate of 0.9:th "symmetric" quantile: 0.323494 305s Estimating DH threshold for AB caller...done 305s Estimated delta: 0.323 305s Estimating DH threshold for calling allelic imbalances...done 305s > print(deltaAB) 305s [1] 0.3234938 305s > 305s > fit <- callAB(fit, delta=deltaAB, verbose=-10) 305s Calling segments of allelic balance from one-sided DH bootstrap confidence intervals... 305s delta (offset adjusting for bias in DH): 0.323493772175137 305s alpha (CI quantile; significance level): 0.05 305s Calling segments... 305s Number of segments called allelic balance (AB): 4 (57.14%) of 7 305s Calling segments...done 305s Calling segments of allelic balance from one-sided DH bootstrap confidence intervals...done 305s > print(fit) 305s chromosome tcnId dhId start end tcnNbrOfLoci tcnMean tcnNbrOfSNPs 305s 1 1 1 1 554484 143663981 1880 1.391608 765 305s 2 1 2 1 143663981 185240536 671 2.092452 272 305s 3 1 3 1 185240536 246679946 1111 2.654512 414 305s 4 NA NA NA NA NA NA NA NA 305s 5 2 1 1 554484 143663981 1880 1.391608 765 305s 6 2 2 1 143663981 185240536 671 2.092452 272 305s 7 2 3 1 185240536 246679946 1111 2.654512 414 305s tcnNbrOfHets dhNbrOfLoci dhMean c1Mean c2Mean abCall 305s 1 765 765 0.4206323 0.4031263 0.9884817 FALSE 305s 2 272 272 0.1762428 0.8618360 1.2306156 TRUE 305s 3 414 414 0.2697420 0.9692395 1.6852728 TRUE 305s 4 NA NA NA NA NA NA 305s 5 765 765 0.4206323 0.4031263 0.9884817 FALSE 305s 6 272 272 0.1762428 0.8618360 1.2306156 TRUE 305s 7 414 414 0.2697420 0.9692395 1.6852728 TRUE 305s > 305s > 305s > # Even if not explicitly specified, the estimated 305s > # threshold parameter is returned by the caller 305s > stopifnot(fit$params$deltaAB == deltaAB) 305s > 305s > 305s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 305s > # Calling segments in loss-of-heterozygosity (LOH) 305s > # NOTE: Ideally, this should be done on whole-genome data 305s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 305s > # Explicitly estimate the threshold in C1 for calling LOH 305s > # (which be done by default by the caller, if skipped here) 305s > deltaLOH <- estimateDeltaLOH(fit, flavor="minC1|nonAB", verbose=-10) 305s Estimating DH threshold for calling LOH... 305s flavor: minC1|nonAB 305s Estimating DH threshold for calling LOH as the midpoint between guessed C1=0 and C1=1... 305s Argument 'midpoint': 0.5 305s Number of segments: 6 305s Number of segments in allelic balance: 4 (66.7%) of 6 305s Number of segments not in allelic balance: 2 (33.3%) of 6 305s Number of segments in allelic balance and TCN <= 3.00: 4 (66.7%) of 6 305s C: 2.09, 2.65, 2.09, 2.65 305s Corrected C1 (=C/2): 1.05, 1.33, 1.05, 1.33 305s Number of DHs: 272, 414, 272, 414 305s Weights: 0.198, 0.302, 0.198, 0.302 305s Weighted median of (corrected) C1 in allelic balance: 1.274 305s Smallest C1 among segments not in allelic balance: 0.403 305s There are 2 segments with in total 765 heterozygous SNPs with this level. 305s There are 2 segments with in total 765 heterozygous SNPs with this level. 305s Midpoint between the two: 0.839 305s Estimating DH threshold for calling LOH as the midpoint between guessed C1=0 and C1=1...done 305s delta: 0.839 305s Estimating DH threshold for calling LOH...done 305s > print(deltaLOH) 305s [1] 0.838563 305s > 305s > fit <- callLOH(fit, delta=deltaLOH, verbose=-10) 305s Calling segments of allelic balance from one-sided DH bootstrap confidence intervals... 305s delta (offset adjusting for bias in C1): 0.838562992888546 305s alpha (CI quantile; significance level): 0.05 305s Calling segments... 305s Number of segments called low C1 (LowC1, "LOH_C1"): 3 (42.86%) of 7 305s Calling segments...done 305s Calling segments of allelic balance from one-sided DH bootstrap confidence intervals...done 305s > print(fit) 305s chromosome tcnId dhId start end tcnNbrOfLoci tcnMean tcnNbrOfSNPs 305s 1 1 1 1 554484 143663981 1880 1.391608 765 305s 2 1 2 1 143663981 185240536 671 2.092452 272 305s 3 1 3 1 185240536 246679946 1111 2.654512 414 305s 4 NA NA NA NA NA NA NA NA 305s 5 2 1 1 554484 143663981 1880 1.391608 765 305s 6 2 2 1 143663981 185240536 671 2.092452 272 305s 7 2 3 1 185240536 246679946 1111 2.654512 414 305s tcnNbrOfHets dhNbrOfLoci dhMean c1Mean c2Mean abCall lohCall 305s 1 765 765 0.4206323 0.4031263 0.9884817 FALSE TRUE 305s 2 272 272 0.1762428 0.8618360 1.2306156 TRUE NA 305s 3 414 414 0.2697420 0.9692395 1.6852728 TRUE FALSE 305s 4 NA NA NA NA NA NA NA 305s 5 765 765 0.4206323 0.4031263 0.9884817 FALSE TRUE 305s 6 272 272 0.1762428 0.8618360 1.2306156 TRUE FALSE 305s 7 414 414 0.2697420 0.9692395 1.6852728 TRUE FALSE 305s > plotTracks(fit) 305s > 305s > # Even if not explicitly specified, the estimated 305s > # threshold parameter is returned by the caller 305s > stopifnot(fit$params$deltaLOH == deltaLOH) 305s > 305s > proc.time() 305s user system elapsed 305s 1.843 0.034 1.879 305s Test segmentByNonPairedPSCBS,medianDH passed 305s 0 305s Begin test segmentByPairedPSCBS,DH 305s + [ 0 != 0 ] 305s + echo Test segmentByNonPairedPSCBS,medianDH passed 305s + echo 0 305s + echo Begin test segmentByPairedPSCBS,DH 305s + exitcode=0 305s + R CMD BATCH segmentByPairedPSCBS,DH.R 308s + cat segmentByPairedPSCBS,DH.Rout 308s 308s R version 4.5.2 (2025-10-31) -- "[Not] Part in a Rumble" 308s Copyright (C) 2025 The R Foundation for Statistical Computing 308s Platform: powerpc64le-unknown-linux-gnu 308s 308s R is free software and comes with ABSOLUTELY NO WARRANTY. 308s You are welcome to redistribute it under certain conditions. 308s Type 'license()' or 'licence()' for distribution details. 308s 308s R is a collaborative project with many contributors. 308s Type 'contributors()' for more information and 308s 'citation()' on how to cite R or R packages in publications. 308s 308s Type 'demo()' for some demos, 'help()' for on-line help, or 308s 'help.start()' for an HTML browser interface to help. 308s Type 'q()' to quit R. 308s 308s [Previously saved workspace restored] 308s 308s > library("PSCBS") 308s PSCBS v0.68.0 (2025-04-18 19:40:02 UTC) successfully loaded. See ?PSCBS for help. 308s > 308s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 308s > # Load SNP microarray data 308s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 308s > data <- PSCBS::exampleData("paired.chr01") 308s > str(data) 308s 'data.frame': 73346 obs. of 6 variables: 308s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 308s $ x : int 1145994 2224111 2319424 2543484 2926730 2941694 3084986 3155127 3292731 3695086 ... 308s $ CT : num 1.625 1.071 1.406 1.18 0.856 ... 308s $ betaT : num 0.757 0.771 0.834 0.778 0.229 ... 308s $ CN : num 2.36 2.13 2.59 1.93 1.71 ... 308s $ betaN : num 0.827 0.875 0.887 0.884 0.103 ... 308s > 308s > # Drop single-locus outliers 308s > dataS <- dropSegmentationOutliers(data) 308s > 308s > # Run light-weight tests 308s > # Use only every 5th data point 308s > dataS <- dataS[seq(from=1, to=nrow(data), by=5),] 308s > # Number of segments (for assertion) 308s > nSegs <- 3L 308s > # Number of bootstrap samples (see below) 308s > B <- 100L 308s > 308s > str(dataS) 308s 'data.frame': 14670 obs. of 6 variables: 308s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 308s $ x : int 1145994 2941694 3710825 4240737 4276892 4464544 4714611 5095111 5034491 5158416 ... 308s $ CT : num 1.63 1.4 1.41 1.17 1.16 ... 308s $ betaT : num 0.7574 0.169 0.2357 0.2604 0.0576 ... 308s $ CN : num 2.36 2.13 2.26 2.01 2.32 ... 308s $ betaN : num 0.8274 0.5072 0.1671 0.1609 0.0421 ... 308s > R.oo::attachLocally(dataS) 308s > 308s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 308s > # Calculate DH 308s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 308s > muN <- aroma.light::callNaiveGenotypes(betaN, censorAt=c(0,1)) 308s > # SNPs are identifies as those loci that have non-missing 'betaT' & 'muN' 308s > isSnp <- (!is.na(betaT) & !is.na(muN)) 308s > isHet <- isSnp & (muN == 1/2) 308s > rho <- rep(NA_real_, length=length(muN)) 308s > rho[isHet] <- 2*abs(betaT[isHet]-1/2) 308s > 308s > 308s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 308s > # Paired PSCBS segmentation using TCN and DH only 308s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 308s > fit <- segmentByPairedPSCBS(CT, rho=rho, 308s + chromosome=chromosome, x=x, 308s + seed=0xBEEF, verbose=-10) 308s Segmenting paired tumor-normal signals using Paired PSCBS... 308s Setup up data... 308s 'data.frame': 14670 obs. of 4 variables: 308s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 308s $ x : num 1145994 2941694 3710825 4240737 4276892 ... 308s $ CT : num 1.63 1.4 1.41 1.17 1.16 ... 308s $ rho : num NA 0.662 NA NA NA ... 308s Setup up data...done 308s Dropping loci for which TCNs are missing... 308s Number of loci dropped: 12 308s Dropping loci for which TCNs are missing...done 308s Ordering data along genome... 308s 'data.frame': 14658 obs. of 4 variables: 308s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 308s $ x : num 554484 730720 782343 878522 916294 ... 308s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 308s $ rho : num NA NA NA NA NA ... 308s Ordering data along genome...done 308s Keeping only current chromosome for 'knownSegments'... 308s Chromosome: 1 308s Known segments for this chromosome: 308s [1] chromosome start end 308s <0 rows> (or 0-length row.names) 308s Keeping only current chromosome for 'knownSegments'...done 308s alphaTCN: 0.009 308s alphaDH: 0.001 308s Number of loci: 14658 308s Random seed temporarily set (seed=c(48879), kind="L'Ecuyer-CMRG") 308s Produced 2 seeds from this stream for future usage 308s Identification of change points by total copy numbers... 308s Segmenting by CBS... 308s Chromosome: 1 308s Random seed temporarily set (seed=c(10407, 1066287653, -51199871, 161854402, -1995183193, 1503453565, -747102133), kind="L'Ecuyer-CMRG") 308s Segmenting by CBS...done 308s List of 4 308s $ data :'data.frame': 14658 obs. of 4 variables: 308s ..$ chromosome: int [1:14658] 1 1 1 1 1 1 1 1 1 1 ... 308s ..$ x : num [1:14658] 554484 730720 782343 878522 916294 ... 308s ..$ y : num [1:14658] 1.88 1.8 1.59 1.64 1.53 ... 308s ..$ index : int [1:14658] 1 2 3 4 5 6 7 8 9 10 ... 308s $ output :'data.frame': 3 obs. of 6 variables: 308s ..$ sampleName: chr [1:3] NA NA NA 308s ..$ chromosome: int [1:3] 1 1 1 308s ..$ start : num [1:3] 5.54e+05 1.44e+08 1.85e+08 308s ..$ end : num [1:3] 1.44e+08 1.85e+08 2.47e+08 308s ..$ nbrOfLoci : int [1:3] 7599 2668 4391 308s ..$ mean : num [1:3] 1.39 2.07 2.63 308s $ segRows:'data.frame': 3 obs. of 2 variables: 308s ..$ startRow: int [1:3] 1 7600 10268 308s ..$ endRow : int [1:3] 7599 10267 14658 308s $ params :List of 5 308s ..$ alpha : num 0.009 308s ..$ undo : num 0 308s ..$ joinSegments : logi TRUE 308s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 308s .. ..$ chromosome: int 1 308s .. ..$ start : num -Inf 308s .. ..$ end : num Inf 308s ..$ seed : int [1:7] 10407 1066287653 -51199871 161854402 -1995183193 1503453565 -747102133 308s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 308s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.479 0 0.602 0 0 308s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 308s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 308s - attr(*, "randomSeed")= int [1:7] 10407 1066287653 -51199871 161854402 -1995183193 1503453565 -747102133 308s Identification of change points by total copy numbers...done 308s Restructure TCN segmentation results... 308s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean 308s 1 1 554484 143926517 7599 1.3859 308s 2 1 143926517 185449813 2668 2.0704 308s 3 1 185449813 247137334 4391 2.6341 308s Number of TCN segments: 3 308s Restructure TCN segmentation results...done 308s Total CN segment #1 ([ 554484,1.43927e+08]) of 3... 308s Number of TCN loci in segment: 7599 308s Locus data for TCN segment: 308s 'data.frame': 7599 obs. of 5 variables: 308s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 308s $ x : num 554484 730720 782343 878522 916294 ... 308s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 308s $ rho : num NA NA NA NA NA ... 308s $ index : int 1 2 3 4 5 6 7 8 9 10 ... 308s Number of loci: 7599 308s Number of SNPs: 2111 (27.78%) 308s Number of heterozygous SNPs: 2111 (100.00%) 308s Chromosome: 1 308s Segmenting DH signals... 308s Segmenting by CBS... 308s Chromosome: 1 308s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 308s Segmenting by CBS...done 308s List of 4 308s $ data :'data.frame': 7599 obs. of 4 variables: 308s ..$ chromosome: int [1:7599] 1 1 1 1 1 1 1 1 1 1 ... 308s ..$ x : num [1:7599] 554484 730720 782343 878522 916294 ... 308s ..$ y : num [1:7599] NA NA NA NA NA ... 308s ..$ index : int [1:7599] 1 2 3 4 5 6 7 8 9 10 ... 308s $ output :'data.frame': 1 obs. of 6 variables: 308s ..$ sampleName: chr NA 308s ..$ chromosome: int 1 308s ..$ start : num 554484 308s ..$ end : num 1.44e+08 308s ..$ nbrOfLoci : int 2111 308s ..$ mean : num 0.524 308s $ segRows:'data.frame': 1 obs. of 2 variables: 308s ..$ startRow: int 10 308s ..$ endRow : int 7594 308s $ params :List of 5 308s ..$ alpha : num 0.001 308s ..$ undo : num 0 308s ..$ joinSegments : logi TRUE 308s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 308s .. ..$ chromosome: int 1 308s .. ..$ start : num 554484 308s .. ..$ end : num 1.44e+08 308s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 308s - attr(*, "class")= chr [1:2] "CBS" "Abstract+ [ 0 != 0 ] 308s + echo Test segmentByPairedPSCBS,DH passed 308s + echo 0 308s + echo Begin test segmentByPairedPSCBS,calls 308s + exitcode=0 308s + R CMD BATCH segmentByPairedPSCBS,calls.R 308s CBS" 308s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.032 0 0.031 0 0 308s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 308s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 308s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 308s DH segmentation (locally-indexed) rows: 308s startRow endRow 308s 1 10 7594 308s int [1:7599] 1 2 3 4 5 6 7 8 9 10 ... 308s DH segmentation rows: 308s startRow endRow 308s 1 10 7594 308s Segmenting DH signals...done 308s DH segmentation table: 308s dhStart dhEnd dhNbrOfLoci dhMean 308s 1 554484 143926517 2111 0.5237 308s startRow endRow 308s 1 10 7594 308s Rows: 308s [1] 1 308s TCN segmentation rows: 308s startRow endRow 308s 1 1 7599 308s TCN and DH segmentation rows: 308s startRow endRow 308s 1 1 7599 308s startRow endRow 308s 1 10 7594 308s NULL 308s TCN segmentation (expanded) rows: 308s startRow endRow 308s 1 1 7599 308s TCN and DH segmentation rows: 308s startRow endRow 308s 1 1 7599 308s 2 7600 10267 308s 3 10268 14658 308s startRow endRow 308s 1 10 7594 308s startRow endRow 308s 1 1 7599 308s Total CN segmentation table (expanded): 308s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 308s 1 1 554484 143926517 7599 1.3859 2111 2111 308s (TCN,DH) segmentation for one total CN segment: 308s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 308s 1 1 1 1 554484 143926517 7599 1.3859 2111 308s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 308s 1 2111 554484 143926517 2111 0.5237 308s Total CN segment #1 ([ 554484,1.43927e+08]) of 3...done 308s Total CN segment #2 ([1.43927e+08,1.8545e+08]) of 3... 308s Number of TCN loci in segment: 2668 308s Locus data for TCN segment: 308s 'data.frame': 2668 obs. of 5 variables: 308s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 308s $ x : num 1.44e+08 1.44e+08 1.44e+08 1.44e+08 1.44e+08 ... 308s $ CT : num 2.1 2.1 2.09 1.8 2.34 ... 308s $ rho : num NA NA NA NA NA NA NA NA NA NA ... 308s $ index : int 7600 7601 7602 7603 7604 7605 7606 7607 7608 7609 ... 308s Number of loci: 2668 308s Number of SNPs: 774 (29.01%) 308s Number of heterozygous SNPs: 774 (100.00%) 308s Chromosome: 1 308s Segmenting DH signals... 308s Segmenting by CBS... 308s Chromosome: 1 308s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 308s Segmenting by CBS...done 308s List of 4 308s $ data :'data.frame': 2668 obs. of 4 variables: 308s ..$ chromosome: int [1:2668] 1 1 1 1 1 1 1 1 1 1 ... 308s ..$ x : num [1:2668] 1.44e+08 1.44e+08 1.44e+08 1.44e+08 1.44e+08 ... 308s ..$ y : num [1:2668] NA NA NA NA NA NA NA NA NA NA ... 308s ..$ index : int [1:2668] 1 2 3 4 5 6 7 8 9 10 ... 308s $ output :'data.frame': 1 obs. of 6 variables: 308s ..$ sampleName: chr NA 308s ..$ chromosome: int 1 308s ..$ start : num 1.44e+08 308s ..$ end : num 1.85e+08 308s ..$ nbrOfLoci : int 774 308s ..$ mean : num 0.154 308s $ segRows:'data.frame': 1 obs. of 2 variables: 308s ..$ startRow: int 15 308s ..$ endRow : int 2664 308s $ params :List of 5 308s ..$ alpha : num 0.001 308s ..$ undo : num 0 308s ..$ joinSegments : logi TRUE 308s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 308s .. ..$ chromosome: int 1 308s .. ..$ start : num 1.44e+08 308s .. ..$ end : num 1.85e+08 308s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 308s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 308s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.011 0 0.01 0 0 308s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 308s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 308s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 308s DH segmentation (locally-indexed) rows: 308s startRow endRow 308s 1 15 2664 308s int [1:2668] 7600 7601 7602 7603 7604 7605 7606 7607 7608 7609 ... 308s DH segmentation rows: 308s startRow endRow 308s 1 7614 10263 308s Segmenting DH signals...done 308s DH segmentation table: 308s dhStart dhEnd dhNbrOfLoci dhMean 308s 1 143926517 185449813 774 0.1542 308s startRow endRow 308s 1 7614 10263 308s Rows: 308s [1] 2 308s TCN segmentation rows: 308s startRow endRow 308s 2 7600 10267 308s TCN and DH segmentation rows: 308s startRow endRow 308s 2 7600 10267 308s startRow endRow 308s 1 7614 10263 308s startRow endRow 308s 1 1 7599 308s TCN segmentation (expanded) rows: 308s startRow endRow 308s 1 1 7599 308s 2 7600 10267 308s TCN and DH segmentation rows: 308s startRow endRow 308s 1 1 7599 308s 2 7600 10267 308s 3 10268 14658 308s startRow endRow 308s 1 10 7594 308s 2 7614 10263 308s startRow endRow 308s 1 1 7599 308s 2 7600 10267 308s Total CN segmentation table (expanded): 308s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 308s 2 1 143926517 185449813 2668 2.0704 774 774 308s (TCN,DH) segmentation for one total CN segment: 308s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 308s 2 2 1 1 143926517 185449813 2668 2.0704 774 308s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 308s 2 774 143926517 185449813 774 0.1542 308s Total CN segment #2 ([1.43927e+08,1.8545e+08]) of 3...done 308s Total CN segment #3 ([1.8545e+08,2.47137e+08]) of 3... 308s Number of TCN loci in segment: 4391 308s Locus data for TCN segment: 308s 'data.frame': 4391 obs. of 5 variables: 308s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 308s $ x : num 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 308s $ CT : num 2.93 2.15 2.82 2.93 2.46 ... 308s $ rho : num NA 0.0308 NA 0.2533 NA ... 308s $ index : int 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 308s Number of loci: 4391 308s Number of SNPs: 1311 (29.86%) 308s Number of heterozygous SNPs: 1311 (100.00%) 308s Chromosome: 1 308s Segmenting DH signals... 308s Segmenting by CBS... 308s Chromosome: 1 308s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 308s Segmenting by CBS...done 308s List of 4 308s $ data :'data.frame': 4391 obs. of 4 variables: 308s ..$ chromosome: int [1:4391] 1 1 1 1 1 1 1 1 1 1 ... 308s ..$ x : num [1:4391] 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 308s ..$ y : num [1:4391] NA 0.0308 NA 0.2533 NA ... 308s ..$ index : int [1:4391] 1 2 3 4 5 6 7 8 9 10 ... 308s $ output :'data.frame': 1 obs. of 6 variables: 308s ..$ sampleName: chr NA 308s ..$ chromosome: int 1 308s ..$ start : num 1.85e+08 308s ..$ end : num 2.47e+08 308s ..$ nbrOfLoci : int 1311 308s ..$ mean : num 0.251 308s $ segRows:'data.frame': 1 obs. of 2 variables: 308s ..$ startRow: int 2 308s ..$ endRow : int 4388 308s $ params :List of 5 308s ..$ alpha : num 0.001 308s ..$ undo : num 0 308s ..$ joinSegments : logi TRUE 308s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 308s .. ..$ chromosome: int 1 308s .. ..$ start : num 1.85e+08 308s .. ..$ end : num 2.47e+08 308s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 308s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 308s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.024 0 0.025 0 0 308s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 308s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 308s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 308s DH segmentation (locally-indexed) rows: 308s startRow endRow 308s 1 2 4388 308s int [1:4391] 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 308s DH segmentation rows: 308s startRow endRow 308s 1 10269 14655 308s Segmenting DH signals...done 308s DH segmentation table: 308s dhStart dhEnd dhNbrOfLoci dhMean 308s 1 185449813 247137334 1311 0.2512 308s startRow endRow 308s 1 10269 14655 308s Rows: 308s [1] 3 308s TCN segmentation rows: 308s startRow endRow 308s 3 10268 14658 308s TCN and DH segmentation rows: 308s startRow endRow 308s 3 10268 14658 308s startRow endRow 308s 1 10269 14655 308s startRow endRow 308s 1 1 7599 308s 2 7600 10267 308s TCN segmentation (expanded) rows: 308s startRow endRow 308s 1 1 7599 308s 2 7600 10267 308s 3 10268 14658 308s TCN and DH segmentation rows: 308s startRow endRow 308s 1 1 7599 308s 2 7600 10267 308s 3 10268 14658 308s startRow endRow 308s 1 10 7594 308s 2 7614 10263 308s 3 10269 14655 308s startRow endRow 308s 1 1 7599 308s 2 7600 10267 308s 3 10268 14658 308s Total CN segmentation table (expanded): 308s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 308s 3 1 185449813 247137334 4391 2.6341 1311 1311 308s (TCN,DH) segmentation for one total CN segment: 308s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 308s 3 3 1 1 185449813 247137334 4391 2.6341 1311 308s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 308s 3 1311 185449813 247137334 1311 0.2512 308s Total CN segment #3 ([1.8545e+08,2.47137e+08]) of 3...done 308s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 308s 1 1 1 1 554484 143926517 7599 1.3859 2111 308s 2 1 2 1 143926517 185449813 2668 2.0704 774 308s 3 1 3 1 185449813 247137334 4391 2.6341 1311 308s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 308s 1 2111 554484 143926517 2111 0.5237 308s 2 774 143926517 185449813 774 0.1542 308s 3 1311 185449813 247137334 1311 0.2512 308s Calculating (C1,C2) per segment... 308s Calculating (C1,C2) per segment...done 308s Number of segments: 3 308s Segmenting paired tumor-normal signals using Paired PSCBS...done 308s Post-segmenting TCNs... 308s Number of segments: 3 308s Number of chromosomes: 1 308s [1] 1 308s Chromosome 1 ('chr01') of 1... 308s Rows: 308s [1] 1 2 3 308s Number of segments: 3 308s TCN segment #1 ('1') of 3... 308s Nothing todo. Only one DH segmentation. Skipping. 308s TCN segment #1 ('1') of 3...done 308s TCN segment #2 ('2') of 3... 308s Nothing todo. Only one DH segmentation. Skipping. 308s TCN segment #2 ('2') of 3...done 308s TCN segment #3 ('3') of 3... 308s Nothing todo. Only one DH segmentation. Skipping. 308s TCN segment #3 ('3') of 3...done 308s Chromosome 1 ('chr01') of 1...done 308s Update (C1,C2) per segment... 308s Update (C1,C2) per segment...done 308s Post-segmenting TCNs...done 308s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 308s 1 1 1 1 554484 143926517 7599 1.3859 2111 308s 2 1 2 1 143926517 185449813 2668 2.0704 774 308s 3 1 3 1 185449813 247137334 4391 2.6341 1311 308s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 308s 1 2111 554484 143926517 2111 0.5237 0.3300521 1.055848 308s 2 774 143926517 185449813 774 0.1542 0.8755722 1.194828 308s 3 1311 185449813 247137334 1311 0.2512 0.9862070 1.647893 308s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 308s 1 1 1 1 554484 143926517 7599 1.3859 2111 308s 2 1 2 1 143926517 185449813 2668 2.0704 774 308s 3 1 3 1 185449813 247137334 4391 2.6341 1311 308s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 308s 1 2111 554484 143926517 2111 0.5237 0.3300521 1.055848 308s 2 774 143926517 185449813 774 0.1542 0.8755722 1.194828 308s 3 1311 185449813 247137334 1311 0.2512 0.9862070 1.647893 308s > print(fit) 308s chromosome tcnId dhId start end tcnNbrOfLoci tcnMean tcnNbrOfSNPs 308s 1 1 1 1 554484 143926517 7599 1.3859 2111 308s 2 1 2 1 143926517 185449813 2668 2.0704 774 308s 3 1 3 1 185449813 247137334 4391 2.6341 1311 308s tcnNbrOfHets dhNbrOfLoci dhMean c1Mean c2Mean 308s 1 2111 2111 0.5237 0.3300521 1.055848 308s 2 774 774 0.1542 0.8755722 1.194828 308s 3 1311 1311 0.2512 0.9862070 1.647893 308s > 308s > # Plot results 308s > plotTracks(fit) 308s > 308s > 308s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 308s > # Bootstrap segment level estimates 308s > # (used by the AB caller, which, if skipped here, 308s > # will do it automatically) 308s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 308s > fit <- bootstrapTCNandDHByRegion(fit, B=B, verbose=-10) 308s Resample (TCN,DH) signals and re-estimate summaries for segment & changepoint... 308s Already done? 308s tcn_2.5% tcn_5% tcn_95% tcn_97.5% dh_2.5% dh_5% dh_95% dh_97.5% 308s FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE 308s c1_2.5% c1_5% c1_95% c1_97.5% c2_2.5% c2_5% c2_95% c2_97.5% 308s FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE 308s Bootstrapping (TCN,DH,C1,C2) segment mean levels... 308s Identifying heterozygous & homozygous SNPs and non-polymorphic loci... 308s Number of loci: 14658 308s Number of SNPs: 4196 308s Number of non-SNPs: 10462 308s Identifying heterozygous & homozygous SNPs and non-polymorphic loci...done 308s num [1:3, 1:100, 1:4] NA NA NA NA NA NA NA NA NA NA ... 308s - attr(*, "dimnames")=List of 3 308s ..$ : NULL 308s ..$ : NULL 308s ..$ : chr [1:4] "tcn" "dh" "c1" "c2" 308s Segment #1 (chr 1, tcnId=1, dhId=1) of 3... 308s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 308s 1 1 1 1 554484 143926517 7599 1.3859 2111 308s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 308s 1 2111 554484 143926517 2111 0.5237 0.3300521 1.055848 308s Number of TCNs: 7599 308s Number of DHs: 2111 308s int [1:7599] 1 2 3 4 5 6 7 8 9 10 ... 308s int [1:14658] 1 2 3 4 5 6 7 8 9 10 ... 308s int [1:7599] 1 2 3 4 5 6 7 8 9 10 ... 308s Identify loci used to bootstrap DH means... 308s Heterozygous SNPs to resample for DH: 308s int [1:2111] 10 12 24 28 31 33 34 39 46 48 ... 308s Identify loci used to bootstrap DH means...done 308s Identify loci used to bootstrap TCN means... 308s SNPs: 308s int [1:2111] 10 12 24 28 31 33 34 39 46 48 ... 308s Non-polymorphic loci: 308s int [1:5488] 1 2 3 4 5 6 7 8 9 11 ... 308s Heterozygous SNPs to resample for TCN: 308s int [1:2111] 10 12 24 28 31 33 34 39 46 48 ... 308s Homozygous SNPs to resample for TCN: 308s int(0) 308s Non-polymorphic loci to resample for TCN: 308s int [1:5488] 1 2 3 4 5 6 7 8 9 11 ... 308s Heterozygous SNPs with non-DH to resample for TCN: 308s int(0) 308s Loci to resample for TCN: 308s int [1:7599] 1 2 3 4 5 6 7 8 9 10 ... 308s Identify loci used to bootstrap TCN means...done 308s Number of (#hets, #homs, #nonSNPs): (2111,0,5488) 308s Bootstrapping while preserving (#hets, #homs, #nonSNPs)... 308s Number of bootstrap samples: 100 308s Bootstrapping while preserving (#hets, #homs, #nonSNPs)...done 308s Segment #1 (chr 1, tcnId=1, dhId=1) of 3...done 308s Segment #2 (chr 1, tcnId=2, dhId=1) of 3... 308s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 308s 2 1 2 1 143926517 185449813 2668 2.0704 774 308s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 308s 2 774 143926517 185449813 774 0.1542 0.8755722 1.194828 308s Number of TCNs: 2668 308s Number of DHs: 774 308s int [1:2668] 7600 7601 7602 7603 7604 7605 7606 7607 7608 7609 ... 308s int [1:14658] 1 2 3 4 5 6 7 8 9 10 ... 308s int [1:2668] 7600 7601 7602 7603 7604 7605 7606 7607 7608 7609 ... 308s Identify loci used to bootstrap DH means... 308s Heterozygous SNPs to resample for DH: 308s int [1:774] 7614 7616 7626 7627 7628 7635 7638 7639 7640 7642 ... 308s Identify loci used to bootstrap DH means...done 308s Identify loci used to bootstrap TCN means... 308s SNPs: 308s int [1:774] 7614 7616 7626 7627 7628 7635 7638 7639 7640 7642 ... 308s Non-polymorphic loci: 308s int [1:1894] 7600 7601 7602 7603 7604 7605 7606 7607 7608 7609 ... 308s Heterozygous SNPs to resample for TCN: 308s int [1:774] 7614 7616 7626 7627 7628 7635 7638 7639 7640 7642 ... 308s Homozygous SNPs to resample for TCN: 308s int(0) 308s Non-polymorphic loci to resample for TCN: 308s int [1:1894] 7600 7601 7602 7603 7604 7605 7606 7607 7608 7609 ... 308s Heterozygous SNPs with non-DH to resample for TCN: 308s int(0) 308s Loci to resample for TCN: 308s int [1:2668] 7600 7601 7602 7603 7604 7605 7606 7607 7608 7609 ... 308s Identify loci used to bootstrap TCN means...done 308s Number of (#hets, #homs, #nonSNPs): (774,0,1894) 308s Bootstrapping while preserving (#hets, #homs, #nonSNPs)... 308s Number of bootstrap samples: 100 308s Bootstrapping while preserving (#hets, #homs, #nonSNPs)...done 308s Segment #2 (chr 1, tcnId=2, dhId=1) of 3...done 308s Segment #3 (chr 1, tcnId=3, dhId=1) of 3... 308s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 308s 3 1 3 1 185449813 247137334 4391 2.6341 1311 308s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 308s 3 1311 185449813 247137334 1311 0.2512 0.986207 1.647893 308s Number of TCNs: 4391 308s Number of DHs: 1311 308s int [1:4391] 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 308s int [1:14658] 1 2 3 4 5 6 7 8 9 10 ... 308s int [1:4391] 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 308s Identify loci used to bootstrap DH means... 308s Heterozygous SNPs to resample for DH: 308s int [1:1311] 10269 10271 10281 10282 10283 10293 10295 10297 10300 10302 ... 308s Identify loci used to bootstrap DH means...done 308s Identify loci used to bootstrap TCN means... 308s SNPs: 308s int [1:1311] 10269 10271 10281 10282 10283 10293 10295 10297 10300 10302 ... 308s Non-polymorphic loci: 308s int [1:3080] 10268 10270 10272 10273 10274 10275 10276 10277 10278 10279 ... 308s Heterozygous SNPs to resample for TCN: 308s int [1:1311] 10269 10271 10281 10282 10283 10293 10295 10297 10300 10302 ... 308s Homozygous SNPs to resample for TCN: 308s int(0) 308s Non-polymorphic loci to resample for TCN: 308s int [1:3080] 10268 10270 10272 10273 10274 10275 10276 10277 10278 10279 ... 308s Heterozygous SNPs with non-DH to resample for TCN: 308s int(0) 308s Loci to resample for TCN: 308s int [1:4391] 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 308s Identify loci used to bootstrap TCN means...done 308s Number of (#hets, #homs, #nonSNPs): (1311,0,3080) 308s Bootstrapping while preserving (#hets, #homs, #nonSNPs)... 308s Number of bootstrap samples: 100 308s Bootstrapping while preserving (#hets, #homs, #nonSNPs)...done 308s Segment #3 (chr 1, tcnId=3, dhId=1) of 3...done 308s Bootstrapped segment mean levels 308s num [1:3, 1:100, 1:4] 1.38 2.08 2.63 1.38 2.07 ... 308s - attr(*, "dimnames")=List of 3 308s ..$ : NULL 308s ..$ : NULL 308s ..$ : chr [1:4] "tcn" "dh" "c1" "c2" 308s Calculating (C1,C2) mean levels from (TCN,DH) mean levels... 308s num [1:3, 1:100, 1:4] 1.38 2.08 2.63 1.38 2.07 ... 308s - attr(*, "dimnames")=List of 3 308s ..$ : NULL 308s ..$ : NULL 308s ..$ : chr [1:4] "tcn" "dh" "c1" "c2" 308s Calculating (C1,C2) mean levels from (TCN,DH) mean levels...done 308s Calculating polar (alpha,radius,manhattan) for change points... 308s num [1:2, 1:100, 1:2] -0.5588 -0.0962 -0.5365 -0.1285 -0.5378 ... 308s - attr(*, "dimnames")=List of 3 308s ..$ : NULL 308s ..$ : NULL 308s ..$ : chr [1:2] "c1" "c2" 308s Bootstrapped change points 308s num [1:2, 1:100, 1:5] -2.89 -1.78 -2.87 -1.86 -2.88 ... 308s - attr(*, "dimnames")=List of 3 308s ..$ : NULL 308s ..$ : NULL 308s ..$ : chr [1:5] "alpha" "radius" "manhattan" "d1" ... 308s Calculating polar (alpha,radius,manhattan) for change points...done 308s Bootstrapping (TCN,DH,C1,C2) segment mean levels...done 308s Summarizing bootstrapped segment ('tcn', 'dh', 'c1', 'c2') data... 308s num [1:3, 1:4, 1:4] NA NA NA NA NA NA NA NA NA NA ... 308s - attr(*, "dimnames")=List of 3 308s ..$ : NULL 308s ..$ : chr [1:4] "2.5%" "5%" "95%" "97.5%" 308s ..$ : chr [1:4] "tcn" "dh" "c1" "c2" 308s Field #1 ('tcn') of 4... 308s Segment #1 of 3... 308s Segment #1 of 3...done 308s Segment #2 of 3... 308s Segment #2 of 3...done 308s Segment #3 of 3... 308s Segment #3 of 3...done 308s Field #1 ('tcn') of 4...done 308s Field #2 ('dh') of 4... 308s Segment #1 of 3... 308s Segment #1 of 3...done 308s Segment #2 of 3... 308s Segment #2 of 3...done 308s Segment #3 of 3... 308s Segment #3 of 3...done 308s Field #2 ('dh') of 4...done 308s Field #3 ('c1') of 4... 308s Segment #1 of 3... 308s Segment #1 of 3...done 308s Segment #2 of 3... 308s Segment #2 of 3...done 308s Segment #3 of 3... 308s Segment #3 of 3...done 308s Field #3 ('c1') of 4...done 308s Field #4 ('c2') of 4... 308s Segment #1 of 3... 308s Segment #1 of 3...done 308s Segment #2 of 3... 308s Segment #2 of 3...done 308s Segment #3 of 3... 308s Segment #3 of 3...done 308s Field #4 ('c2') of 4...done 308s Bootstrap statistics 308s num [1:3, 1:4, 1:4] 1.38 2.06 2.62 1.38 2.06 ... 308s - attr(*, "dimnames")=List of 3 308s ..$ : NULL 308s ..$ : chr [1:4] "2.5%" "5%" "95%" "97.5%" 308s ..$ : chr [1:4] "tcn" "dh" "c1" "c2" 308s Statistical sanity checks (iff B >= 100)... 308s Available summaries: 2.5%, 5%, 95%, 97.5% 308s Available quantiles: 0.025, 0.05, 0.95, 0.975 308s num [1:3, 1:4, 1:4] 1.38 2.06 2.62 1.38 2.06 ... 308s - attr(*, "dimnames")=List of 3 308s ..$ : NULL 308s ..$ : chr [1:4] "2.5%" "5%" "95%" "97.5%" 308s ..$ : chr [1:4] "tcn" "dh" "c1" "c2" 308s Field #1 ('tcn') of 4... 308s Seg 1. mean=1.3859, range=[1.38092,1.3949], n=7599 308s Seg 2. mean=2.0704, range=[2.05747,2.08326], n=2668 308s Seg 3. mean=2.6341, range=[2.62068,2.64694], n=4391 308s Field #1 ('tcn') of 4...done 308s Field #2 ('dh') of 4... 308s Seg 1. mean=0.5237, range=[0.51753,0.532002], n=2111 308s Seg 2. mean=0.1542, range=[0.144468,0.16453], n=774 308s Seg 3. mean=0.2512, range=[0.242575,0.258832], n=1311 308s Field #2 ('dh') of 4...done 308s Field #3 ('c1') of 4... 308s Seg 1. mean=0.330052, range=[0.323996,0.336038], n=2111 308s Seg 2. mean=0.875572, range=[0.86318,0.887699], n=774 308s Seg 3. mean=0.986207, range=[0.975123,0.998982], n=1311 308s Field #3 ('c1') of 4...done 308s Field #4 ('c2') of 4... 308s Seg 1. mean=1.05585, range=[1.05006,1.06231], n=2111 308s Seg 2. mean=1.19483, range=[1.18417,1.2081], n=774 308s Seg 3. mean=1.64789, range=[1.63403,1.66098], n=1311 308s Field #4 ('c2') of 4...done 308s Statistical sanity checks (iff B >= 100)...done 308s Summarizing bootstrapped segment ('tcn', 'dh', 'c1', 'c2') data...done 308s Summarizing bootstrapped changepoint ('alpha', 'radius', 'manhattan', 'd1', 'd2') data... 308s num [1:2, 1:4, 1:5] NA NA NA NA NA NA NA NA NA NA ... 308s - attr(*, "dimnames")=List of 3 308s ..$ : NULL 308s ..$ : chr [1:4] "2.5%" "5%" "95%" "97.5%" 308s ..$ : chr [1:5] "alpha" "radius" "manhattan" "d1" ... 308s Field #1 ('alpha') of 5... 308s Changepoint #1 of 2... 308s Changepoint #1 of 2...done 308s Changepoint #2 of 2... 308s Changepoint #2 of 2...done 308s Field #1 ('alpha') of 5...done 308s Field #2 ('radius') of 5... 308s Changepoint #1 of 2... 308s Changepoint #1 of 2...done 308s Changepoint #2 of 2... 308s Changepoint #2 of 2...done 308s Field #2 ('radius') of 5...done 308s Field #3 ('manhattan') of 5... 308s Changepoint #1 of 2... 308s Changepoint #1 of 2...done 308s Changepoint #2 of 2... 308s Changepoint #2 of 2...done 308s Field #3 ('manhattan') of 5...done 308s Field #4 ('d1') of 5... 308s Changepoint #1 of 2... 308s Changepoint #1 of 2...done 308s Changepoint #2 of 2... 308s Changepoint #2 of 2...done 308s Field #4 ('d1') of 5...done 308s Field #5 ('d2') of 5... 308s Changepoint #1 of 2... 308s Changepoint #1 of 2...done 308s Changepoint #2 of 2... 308s Changepoint #2 of 2...done 308s Field #5 ('d2') of 5...done 308s Bootstrap statistics 308s num [1:2, 1:4, 1:5] -2.92 -1.86 -2.91 -1.85 -2.87 ... 308s - attr(*, "dimnames")=List of 3 308s ..$ : NULL 308s ..$ : chr [1:4] "2.5%" "5%" "95%" "97.5%" 308s ..$ : chr [1:5] "alpha" "radius" "manhattan" "d1" ... 308s Summarizing bootstrapped changepoint ('alpha', 'radius', 'manhattan', 'd1', 'd2') data...done 308s Resample (TCN,DH) signals and re-estimate summaries for segment & changepoint...done 308s > print(fit) 308s chromosome tcnId dhId start end tcnNbrOfLoci tcnMean tcnNbrOfSNPs 308s 1 1 1 1 554484 143926517 7599 1.3859 2111 308s 2 1 2 1 143926517 185449813 2668 2.0704 774 308s 3 1 3 1 185449813 247137334 4391 2.6341 1311 308s tcnNbrOfHets dhNbrOfLoci dhMean c1Mean c2Mean 308s 1 2111 2111 0.5237 0.3300521 1.055848 308s 2 774 774 0.1542 0.8755722 1.194828 308s 3 1311 1311 0.2512 0.9862070 1.647893 308s > plotTracks(fit) 308s > 308s > 308s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 308s > # Calling segments in allelic balance (AB) and 308s > # in loss-of-heterozygosity (LOH) 308s > # NOTE: Ideally, this should be done on whole-genome data 308s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 308s > fit <- callAB(fit, verbose=-10) 308s Calling segments of allelic balance from one-sided DH bootstrap confidence intervals... 308s delta (offset adjusting for bias in DH): 0.3466649145302 308s alpha (CI quantile; significance level): 0.05 308s Calling segments... 308s Number of segments called allelic balance (AB): 2 (66.67%) of 3 308s Calling segments...done 308s Calling segments of allelic balance from one-sided DH bootstrap confidence intervals...done 308s > fit <- callLOH(fit, verbose=-10) 308s Calling segments of allelic balance from one-sided DH bootstrap confidence intervals... 308s delta (offset adjusting for bias in C1): 0.771236438183453 308s alpha (CI quantile; significance level): 0.05 308s Calling segments... 308s Number of segments called low C1 (LowC1, "LOH_C1"): 1 (33.33%) of 3 308s Calling segments...done 308s Calling segments of allelic balance from one-sided DH bootstrap confidence intervals...done 308s > print(fit) 308s chromosome tcnId dhId start end tcnNbrOfLoci tcnMean tcnNbrOfSNPs 308s 1 1 1 1 554484 143926517 7599 1.3859 2111 308s 2 1 2 1 143926517 185449813 2668 2.0704 774 308s 3 1 3 1 185449813 247137334 4391 2.6341 1311 308s tcnNbrOfHets dhNbrOfLoci dhMean c1Mean c2Mean abCall lohCall 308s 1 2111 2111 0.5237 0.3300521 1.055848 FALSE TRUE 308s 2 774 774 0.1542 0.8755722 1.194828 TRUE FALSE 308s 3 1311 1311 0.2512 0.9862070 1.647893 TRUE FALSE 308s > plotTracks(fit) 308s > 308s > proc.time() 308s user system elapsed 308s 2.336 0.035 2.495 308s Test segmentByPairedPSCBS,DH passed 308s 0 308s Begin test segmentByPairedPSCBS,calls 312s + cat segmentByPairedPSCBS,calls.Rout 312s 312s R version 4.5.2 (2025-10-31) -- "[Not] Part in a Rumble" 312s Copyright (C) 2025 The R Foundation for Statistical Computing 312s Platform: powerpc64le-unknown-linux-gnu 312s 312s R is free software and comes with ABSOLUTELY NO WARRANTY. 312s You are welcome to redistribute it under certain conditions. 312s Type 'license()' or 'licence()' for distribution details. 312s 312s R is a collaborative project with many contributors. 312s Type 'contributors()' for more information and 312s 'citation()' on how to cite R or R packages in publications. 312s 312s Type 'demo()' for some demos, 'help()' for on-line help, or 312s 'help.start()' for an HTML browser interface to help. 312s Type 'q()' to quit R. 312s 312s [Previously saved workspace restored] 312s 312s > library("PSCBS") 312s PSCBS v0.68.0 (2025-04-18 19:40:02 UTC) successfully loaded. See ?PSCBS for help. 312s > 312s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 312s > # Load SNP microarray data 312s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 312s > data <- PSCBS::exampleData("paired.chr01") 312s > str(data) 312s 'data.frame': 73346 obs. of 6 variables: 312s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 312s $ x : int 1145994 2224111 2319424 2543484 2926730 2941694 3084986 3155127 3292731 3695086 ... 312s $ CT : num 1.625 1.071 1.406 1.18 0.856 ... 312s $ betaT : num 0.757 0.771 0.834 0.778 0.229 ... 312s $ CN : num 2.36 2.13 2.59 1.93 1.71 ... 312s $ betaN : num 0.827 0.875 0.887 0.884 0.103 ... 312s > 312s > 312s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 312s > # Paired PSCBS segmentation 312s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 312s > # Drop single-locus outliers 312s > dataS <- dropSegmentationOutliers(data) 312s > 312s > # Find centromere 312s > gaps <- findLargeGaps(dataS, minLength=2e6) 312s > knownSegments <- gapsToSegments(gaps) 312s > 312s > 312s > # Run light-weight tests by default 312s > if (Sys.getenv("_R_CHECK_FULL_") == "") { 312s + # Use only every 5th data point 312s + dataS <- dataS[seq(from=1, to=nrow(data), by=5),] 312s + # Number of segments (for assertion) 312s + nSegs <- 4L 312s + # Number of bootstrap samples (see below) 312s + B <- 100L 312s + } else { 312s + # Full tests 312s + nSegs <- 11L 312s + B <- 1000L 312s + } 312s > 312s > str(dataS) 312s 'data.frame': 14670 obs. of 6 variables: 312s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 312s $ x : int 1145994 2941694 3710825 4240737 4276892 4464544 4714611 5095111 5034491 5158416 ... 312s $ CT : num 1.63 1.4 1.41 1.17 1.16 ... 312s $ betaT : num 0.7574 0.169 0.2357 0.2604 0.0576 ... 312s $ CN : num 2.36 2.13 2.26 2.01 2.32 ... 312s $ betaN : num 0.8274 0.5072 0.1671 0.1609 0.0421 ... 312s > 312s > # Paired PSCBS segmentation 312s > fit <- segmentByPairedPSCBS(dataS, knownSegments=knownSegments, 312s + seed=0xBEEF, verbose=-10) 312s Segmenting paired tumor-normal signals using Paired PSCBS... 312s Calling genotypes from normal allele B fractions... 312s num [1:14670] 0.8274 0.5072 0.1671 0.1609 0.0421 ... 312s Called genotypes: 312s num [1:14670] 1 0.5 0 0 0 0 1 0 1 0.5 ... 312s - attr(*, "modelFit")=List of 1 312s ..$ :List of 7 312s .. ..$ flavor : chr "density" 312s .. ..$ cn : int 2 312s .. ..$ nbrOfGenotypeGroups: int 3 312s .. ..$ tau : num [1:2] 0.315 0.677 312s .. ..$ n : int 14640 312s .. ..$ fit :Classes 'PeaksAndValleys' and 'data.frame': 5 obs. of 3 variables: 312s .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 312s .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 312s .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 312s .. ..$ fitValleys :Classes 'PeaksAndValleys' and 'data.frame': 2 obs. of 3 variables: 312s .. .. ..$ type : chr [1:2] "valley" "valley" 312s .. .. ..$ x : num [1:2] 0.315 0.677 312s .. .. ..$ density: num [1:2] 0.522 0.551 312s ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 312s muN 312s 0 0.5 1 312s 5221 4198 5251 312s Calling genotypes from normal allele B fractions...done 312s Normalizing betaT using betaN (TumorBoost)... 312s Normalized BAFs: 312s num [1:14670] 0.9301 0.1667 0.0685 0.0995 0.0155 ... 312s - attr(*, "modelFit")=List of 5 312s ..$ method : chr "normalizeTumorBoost" 312s ..$ flavor : chr "v4" 312s ..$ delta : num [1:14670] -0.17264 0.00239 0.1671 0.16085 0.04213 ... 312s .. ..- attr(*, "modelFit")=List of 1 312s .. .. ..$ :List of 7 312s .. .. .. ..$ flavor : chr "density" 312s .. .. .. ..$ cn : int 2 312s .. .. .. ..$ nbrOfGenotypeGroups: int 3 312s .. .. .. ..$ tau : num [1:2] 0.315 0.677 312s .. .. .. ..$ n : int 14640 312s .. .. .. ..$ fit :Classes 'PeaksAndValleys' and 'data.frame': 5 obs. of 3 variables: 312s .. .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 312s .. .. .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 312s .. .. .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 312s .. .. .. ..$ fitValleys :Classes 'PeaksAndValleys' and 'data.frame': 2 obs. of 3 variables: 312s .. .. .. .. ..$ type : chr [1:2] "valley" "valley" 312s .. .. .. .. ..$ x : num [1:2] 0.315 0.677 312s .. .. .. .. ..$ density: num [1:2] 0.522 0.551 312s .. .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 312s ..$ preserveScale: logi FALSE 312s ..$ scaleFactor : num NA 312s Normalizing betaT using betaN (TumorBoost)...done 312s Setup up data... 312s 'data.frame': 14670 obs. of 7 variables: 312s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 312s $ x : num 1145994 2941694 3710825 4240737 4276892 ... 312s $ CT : num 1.63 1.4 1.41 1.17 1.16 ... 312s $ betaT : num 0.7574 0.169 0.2357 0.2604 0.0576 ... 312s $ betaTN : num 0.9301 0.1667 0.0685 0.0995 0.0155 ... 312s ..- attr(*, "modelFit")=List of 5 312s .. ..$ method : chr "normalizeTumorBoost" 312s .. ..$ flavor : chr "v4" 312s .. ..$ delta : num [1:14670] -0.17264 0.00239 0.1671 0.16085 0.04213 ... 312s .. .. ..- attr(*, "modelFit")=List of 1 312s .. .. .. ..$ :List of 7 312s .. .. .. .. ..$ flavor : chr "density" 312s .. .. .. .. ..$ cn : int 2 312s .. .. .. .. ..$ nbrOfGenotypeGroups: int 3 312s .. .. .. .. ..$ tau : num [1:2] 0.315 0.677 312s .. .. .. .. ..$ n : int 14640 312s .. .. .. .. ..$ fit :Classes 'PeaksAndValleys' and 'data.frame': 5 obs. of 3 variables: 312s .. .. .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 312s .. .. .. .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 312s .. .. .. .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 312s .. .. .. .. ..$ fitValleys :Classes 'PeaksAndValleys' and 'data.frame': 2 obs. of 3 variables: 312s .. .. .. .. .. ..$ type : chr [1:2] "valley" "valley" 312s .. .. .. .. .. ..$ x : num [1:2] 0.315 0.677 312s .. .. .. .. .. ..$ density: num [1:2] 0.522 0.551 312s .. .. .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 312s .. ..$ preserveScale: logi FALSE 312s .. ..$ scaleFactor : num NA 312s $ betaN : num 0.8274 0.5072 0.1671 0.1609 0.0421 ... 312s $ muN : num 1 0.5 0 0 0 0 1 0 1 0.5 ... 312s ..- attr(*, "modelFit")=List of 1 312s .. ..$ :List of 7 312s .. .. ..$ flavor : chr "density" 312s .. .. ..$ cn : int 2 312s .. .. ..$ nbrOfGenotypeGroups: int 3 312s .. .. ..$ tau : num [1:2] 0.315 0.677 312s .. .. ..$ n : int 14640 312s .. .. ..$ fit :Classes 'PeaksAndValleys' and 'data.frame': 5 obs. of 3 variables: 312s .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 312s .. .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 312s .. .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 312s .. .. ..$ fitValleys :Classes 'PeaksAndValleys' and 'data.frame': 2 obs. of 3 variables: 312s .. .. .. ..$ type : chr [1:2] "valley" "valley" 312s .. .. .. ..$ x : num [1:2] 0.315 0.677 312s .. .. .. ..$ density: num [1:2] 0.522 0.551 312s .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 312s Setup up data...done 312s Dropping loci for which TCNs are missing... 312s Number of loci dropped: 12 312s Dropping loci for which TCNs are missing...done 312s Ordering data along genome... 312s 'data.frame': 14658 obs. of 7 variables: 312s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 312s $ x : num 554484 730720 782343 878522 916294 ... 312s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 312s $ betaT : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 312s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 312s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 312s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 312s Ordering data along genome...done 312s Keeping only current chromosome for 'knownSegments'... 312s Chromosome: 1 312s Known segments for this chromosome: 312s chromosome start end length 312s 1 1 -Inf 120992603 Inf 312s 2 1 120992604 141510002 20517398 312s 3 1 141510003 Inf Inf 312s Keeping only current chromosome for 'knownSegments'...done 312s alphaTCN: 0.009 312s alphaDH: 0.001 312s Number of loci: 14658 312s Calculating DHs... 312s Number of SNPs: 14658 312s Number of heterozygous SNPs: 4196 (28.63%) 312s Normalized DHs: 312s num [1:14658] NA NA NA NA NA ... 312s Calculating DHs...done 312s Random seed temporarily set (seed=c(48879), kind="L'Ecuyer-CMRG") 312s Produced 2 seeds from this stream for future usage 312s Identification of change points by total copy numbers... 312s Segmenting by CBS... 312s Chromosome: 1 312s Segmenting multiple segments on current chromosome... 312s Number of segments: 3 312s Random seed temporarily set (seed=c(10407, 1066287653, -51199871, 161854402, -1995183193, 1503453565, -747102133), kind="L'Ecuyer-CMRG") 312s Produced 3 seeds from this stream for future usage 312s Segmenting by CBS... 312s Chromosome: 1 312s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 312s Segmenting by CBS...done 312s Segmenting by CBS... 312s Chromosome: 1 312s Random seed temporarily set (seed=c(10407, -1924040949, -1632234809, -437763632, -1464377300, 676654412, 2080370711), kind="L'Ecuyer-CMRG") 312s Segmenting by CBS...done 312s Segmenting multiple segments on current chromosome...done 312s Segmenting by CBS...done 312s List of 4 312s $ data :'data.frame': 14658 obs. of 4 variables: 312s ..$ chromosome: int [1:14658] 1 1 1 1 1 1 1 1 1 1 ... 312s ..$ x : num [1:14658] 554484 730720 782343 878522 916294 ... 312s ..$ y : num [1:14658] 1.88 1.8 1.59 1.64 1.53 ... 312s ..$ index : int [1:14658] 1 2 3 4 5 6 7 8 9 10 ... 312s $ output :'data.frame': 4 obs. of 6 variables: 312s ..$ sampleName: chr [1:4] NA NA NA NA 312s ..$ chromosome: int [1:4] 1 1 1 1 312s ..$ start : num [1:4] 5.54e+05 1.21e+08 1.42e+08 1.85e+08 312s ..$ end : num [1:4] 1.21e+08 1.42e+08 1.85e+08 2.47e+08 312s ..$ nbrOfLoci : int [1:4] 7586 0 2681 4391 312s ..$ mean : num [1:4] 1.39 NA 2.07 2.63 312s $ segRows:'data.frame': 4 obs. of 2 variables: 312s ..$ startRow: int [1:4] 1 NA 7587 10268 312s ..$ endRow : int [1:4] 7586 NA 10267 14658 312s $ params :List of 5 312s ..$ alpha : num 0.009 312s ..$ undo : num 0 312s ..$ joinSegments : logi TRUE 312s ..$ knownSegments:'data.frame': 4 obs. of 3 variables: 312s .. ..$ chromosome: int [1:4] 1 1 2 1 312s .. ..$ start : num [1:4] -Inf -Inf -Inf 1.42e+08 312s .. ..$ end : num [1:4] 1.21e+08 Inf Inf Inf 312s ..$ seed : int [1:7] 10407 1066287653 -51199871 161854402 -1995183193 1503453565 -747102133 312s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 312s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.163 0 0.164 0 0 312s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 312s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 312s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 312s Identification of change points by total copy numbers...done 312s Restructure TCN segmentation results... 312s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean 312s 1 1 554484 120992603 7586 1.3853 312s 2 1 120992604 141510002 0 NA 312s 3 1 141510003 185449813 2681 2.0689 312s 4 1 185449813 247137334 4391 2.6341 312s Number of TCN segments: 4 312s Restructure TCN segmentation results...done 312s Total CN segment #1 ([ 554484,1.20993e+08]) of 4... 312s Number of TCN loci in segment: 7586 312s Locus data for TCN segment: 312s 'data.frame': 7586 obs. of 9 variables: 312s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 312s $ x : num 554484 730720 782343 878522 916294 ... 312s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 312s $ betaT : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 312s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 312s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 312s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 312s $ index : int 1 2 3 4 5 6 7 8 9 10 ... 312s $ rho : num NA NA NA NA NA ... 312s Number of loci: 7586 312s Number of SNPs: 2108 (27.79%) 312s Number of heterozygous SNPs: 2108 (100.00%) 312s Chromosome: 1 312s Segmenting DH signals... 312s Segmenting by CBS... 312s Chromosome: 1 312s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 312s Segmenting by CBS...done 312s List of 4 312s $ data :'data.frame': 7586 obs. of 4 variables: 312s ..$ chromosome: int [1:7586] 1 1 1 1 1 1 1 1 1 1 ... 312s ..$ x : num [1:7586] 554484 730720 782343 878522 916294 ... 312s ..$ y : num [1:7586] NA NA NA NA NA ... 312s ..$ index : int [1:7586] 1 2 3 4 5 6 7 8 9 10 ... 312s $ output :'data.frame': 1 obs. of 6 variables: 312s ..$ sampleName: chr NA 312s ..$ chromosome: int 1 312s ..$ start : num 554484 312s ..$ end : num 1.21e+08 312s ..$ nbrOfLoci : int 2108 312s ..$ mean : num 0.512 312s $ segRows:'data.frame': 1 obs. of 2 variables: 312s ..$ startRow: int 10 312s ..$ endRow : int 7574 312s $ params :List of 5 312s ..$ alpha : num 0.001 312s ..$ undo : num 0 312s ..$ joinSegments : logi TRUE 312s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 312s .. ..$ chromosome: int 1 312s .. ..$ start : num 554484 312s .. ..$ end : num 1.21e+08 312s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 312s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 312s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.046 0 0.046 0 0 312s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 312s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 312s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 312s DH segmentation (locally-indexed) rows: 312s startRow endRow 312s 1 10 7574 312s int [1:7586] 1 2 3 4 5 6 7 8 9 10 ... 312s DH segmentation rows: 312s startRow endRow 312s 1 10 7574 312s Segmenting DH signals...done 312s DH segmentation table: 312s dhStart dhEnd dhNbrOfLoci dhMean 312s 1 554484 120992603 2108 0.5116 312s startRow endRow 312s 1 10 7574 312s Rows: 312s [1] 1 312s TCN segmentation rows: 312s startRow endRow 312s 1 1 7586 312s TCN and DH segmentation rows: 312s startRow endRow 312s 1 1 7586 312s startRow endRow 312s 1 10 7574 312s NULL 312s TCN segmentation (expanded) rows: 312s startRow endRow 312s 1 1 7586 312s TCN and DH segmentation rows: 312s startRow endRow 312s 1 1 7586 312s 2 NA NA 312s 3 7587 10267 312s 4 10268 14658 312s startRow endRow 312s 1 10 7574 312s startRow endRow 312s 1 1 7586 312s Total CN segmentation table (expanded): 312s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 312s 1 1 554484 120992603 7586 1.3853 2108 2108 312s (TCN,DH) segmentation for one total CN segment: 312s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 312s 1 1 1 1 554484 120992603 7586 1.3853 2108 312s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 312s 1 2108 554484 120992603 2108 0.5116 312s Total CN segment #1 ([ 554484,1.20993e+08]) of 4...done 312s Total CN segment #2 ([1.20993e+08,1.4151e+08]) of 4... 312s Number of TCN loci in segment: 0 312s Locus data for TCN segment: 312s 'data.frame': 0 obs. of 9 variables: 312s $ chromosome: int 312s $ x : num 312s $ CT : num 312s $ betaT : num 312s + [ 0 != 0 ] 312s + echo Test segmentByPairedPSCBS,calls passed 312s + echo 0 312s + echo Begin test segmentByPairedPSCBS,futures 312s + exitcode=0 312s + R CMD BATCH segmentByPairedPSCBS,futures.R 312s $ betaTN : num 312s $ betaN : num 312s $ muN : num 312s $ index : int 312s $ rho : num 312s Number of loci: 0 312s Number of SNPs: 0 (NaN%) 312s Number of heterozygous SNPs: 0 (NaN%) 312s Chromosome: 1 312s Segmenting DH signals... 312s Segmenting by CBS... 312s Chromosome: NA 312s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 312s Segmenting by CBS...done 312s List of 4 312s $ data :'data.frame': 0 obs. of 4 variables: 312s ..$ chromosome: int(0) 312s ..$ x : num(0) 312s ..$ y : num(0) 312s ..$ index : int(0) 312s $ output :'data.frame': 0 obs. of 6 variables: 312s ..$ sampleName: chr(0) 312s ..$ chromosome: num(0) 312s ..$ start : num(0) 312s ..$ end : num(0) 312s ..$ nbrOfLoci : int(0) 312s ..$ mean : num(0) 312s $ segRows:'data.frame': 0 obs. of 2 variables: 312s ..$ startRow: int(0) 312s ..$ endRow : int(0) 312s $ params :List of 5 312s ..$ alpha : num 0.001 312s ..$ undo : num 0 312s ..$ joinSegments : logi TRUE 312s ..$ knownSegments:'data.frame': 0 obs. of 3 variables: 312s .. ..$ chromosome: int(0) 312s .. ..$ start : num(0) 312s .. ..$ end : num(0) 312s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 312s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 312s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.002 0 0.001 0 0 312s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 312s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 312s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 312s DH segmentation (locally-indexed) rows: 312s [1] startRow endRow 312s <0 rows> (or 0-length row.names) 312s int(0) 312s DH segmentation rows: 312s [1] startRow endRow 312s <0 rows> (or 0-length row.names) 312s Segmenting DH signals...done 312s DH segmentation table: 312s dhStart dhEnd dhNbrOfLoci dhMean 312s NA NA NA NA NA 312s startRow endRow 312s NA NA NA 312s Rows: 312s [1] 2 312s TCN segmentation rows: 312s startRow endRow 312s 2 NA NA 312s TCN and DH segmentation rows: 312s startRow endRow 312s 2 NA NA 312s startRow endRow 312s NA NA NA 312s startRow endRow 312s 1 1 7586 312s TCN segmentation (expanded) rows: 312s startRow endRow 312s 1 1 7586 312s 2 NA NA 312s TCN and DH segmentation rows: 312s startRow endRow 312s 1 1 7586 312s 2 NA NA 312s 3 7587 10267 312s 4 10268 14658 312s startRow endRow 312s 1 10 7574 312s 2 NA NA 312s startRow endRow 312s 1 1 7586 312s 2 NA NA 312s Total CN segmentation table (expanded): 312s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 312s 2 1 120992604 141510002 0 NA 0 0 312s (TCN,DH) segmentation for one total CN segment: 312s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 312s 2 2 1 1 120992604 141510002 0 NA 0 312s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 312s 2 0 NA NA NA NA 312s Total CN segment #2 ([1.20993e+08,1.4151e+08]) of 4...done 312s Total CN segment #3 ([1.4151e+08,1.8545e+08]) of 4... 312s Number of TCN loci in segment: 2681 312s Locus data for TCN segment: 312s 'data.frame': 2681 obs. of 9 variables: 312s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 312s $ x : num 1.43e+08 1.43e+08 1.43e+08 1.43e+08 1.44e+08 ... 312s $ CT : num 2.27 1.55 1.47 1.5 1.81 ... 312s $ betaT : num 0.34 0.55 0.048 0.813 0.575 ... 312s $ betaTN : num 0.441 0.629 -0.05 0.958 0.872 ... 312s $ betaN : num 0.3851 0.3933 0.0981 0.8552 0.7028 ... 312s $ muN : num 0.5 0.5 0 1 1 1 1 0.5 1 1 ... 312s $ index : int 7587 7588 7589 7590 7591 7592 7593 7594 7595 7596 ... 312s $ rho : num 0.117 0.258 NA NA NA ... 312s Number of loci: 2681 312s Number of SNPs: 777 (28.98%) 312s Number of heterozygous SNPs: 777 (100.00%) 312s Chromosome: 1 312s Segmenting DH signals... 312s Segmenting by CBS... 312s Chromosome: 1 312s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 312s Segmenting by CBS...done 312s List of 4 312s $ data :'data.frame': 2681 obs. of 4 variables: 312s ..$ chromosome: int [1:2681] 1 1 1 1 1 1 1 1 1 1 ... 312s ..$ x : num [1:2681] 1.43e+08 1.43e+08 1.43e+08 1.43e+08 1.44e+08 ... 312s ..$ y : num [1:2681] 0.117 0.258 NA NA NA ... 312s ..$ index : int [1:2681] 1 2 3 4 5 6 7 8 9 10 ... 312s $ output :'data.frame': 1 obs. of 6 variables: 312s ..$ sampleName: chr NA 312s ..$ chromosome: int 1 312s ..$ start : num 1.42e+08 312s ..$ end : num 1.85e+08 312s ..$ nbrOfLoci : int 777 312s ..$ mean : num 0.0973 312s $ segRows:'data.frame': 1 obs. of 2 variables: 312s ..$ startRow: int 1 312s ..$ endRow : int 2677 312s $ params :List of 5 312s ..$ alpha : num 0.001 312s ..$ undo : num 0 312s ..$ joinSegments : logi TRUE 312s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 312s .. ..$ chromosome: int 1 312s .. ..$ start : num 1.42e+08 312s .. ..$ end : num 1.85e+08 312s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 312s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 312s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.009 0 0.009 0 0 312s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 312s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 312s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 312s DH segmentation (locally-indexed) rows: 312s startRow endRow 312s 1 1 2677 312s int [1:2681] 7587 7588 7589 7590 7591 7592 7593 7594 7595 7596 ... 312s DH segmentation rows: 312s startRow endRow 312s 1 7587 10263 312s Segmenting DH signals...done 312s DH segmentation table: 312s dhStart dhEnd dhNbrOfLoci dhMean 312s 1 141510003 185449813 777 0.0973 312s startRow endRow 312s 1 7587 10263 312s Rows: 312s [1] 3 312s TCN segmentation rows: 312s startRow endRow 312s 3 7587 10267 312s TCN and DH segmentation rows: 312s startRow endRow 312s 3 7587 10267 312s startRow endRow 312s 1 7587 10263 312s startRow endRow 312s 1 1 7586 312s 2 NA NA 312s TCN segmentation (expanded) rows: 312s startRow endRow 312s 1 1 7586 312s 2 NA NA 312s 3 7587 10267 312s TCN and DH segmentation rows: 312s startRow endRow 312s 1 1 7586 312s 2 NA NA 312s 3 7587 10267 312s 4 10268 14658 312s startRow endRow 312s 1 10 7574 312s 2 NA NA 312s 3 7587 10263 312s startRow endRow 312s 1 1 7586 312s 2 NA NA 312s 3 7587 10267 312s Total CN segmentation table (expanded): 312s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 312s 3 1 141510003 185449813 2681 2.0689 777 777 312s (TCN,DH) segmentation for one total CN segment: 312s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 312s 3 3 1 1 141510003 185449813 2681 2.0689 777 312s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 312s 3 777 141510003 185449813 777 0.0973 312s Total CN segment #3 ([1.4151e+08,1.8545e+08]) of 4...done 312s Total CN segment #4 ([1.8545e+08,2.47137e+08]) of 4... 312s Number of TCN loci in segment: 4391 312s Locus data for TCN segment: 312s 'data.frame': 4391 obs. of 9 variables: 312s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 312s $ x : num 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 312s $ CT : num 2.93 2.15 2.82 2.93 2.46 ... 312s $ betaT : num 0.0811 0.5154 0.9473 0.3734 0.7506 ... 312s $ betaTN : num -0.169 0.609 1.028 0.525 0.968 ... 312s $ betaN : num 0.25 0.38 0.919 0.34 0.783 ... 312s $ muN : num 0 0.5 1 0.5 1 1 0 1 0 1 ... 312s $ index : int 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 312s $ rho : num NA 0.2186 NA 0.0503 NA ... 312s Number of loci: 4391 312s Number of SNPs: 1311 (29.86%) 312s Number of heterozygous SNPs: 1311 (100.00%) 312s Chromosome: 1 312s Segmenting DH signals... 312s Segmenting by CBS... 312s Chromosome: 1 312s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 312s Segmenting by CBS...done 312s List of 4 312s $ data :'data.frame': 4391 obs. of 4 variables: 312s ..$ chromosome: int [1:4391] 1 1 1 1 1 1 1 1 1 1 ... 312s ..$ x : num [1:4391] 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 312s ..$ y : num [1:4391] NA 0.2186 NA 0.0503 NA ... 312s ..$ index : int [1:4391] 1 2 3 4 5 6 7 8 9 10 ... 312s $ output :'data.frame': 1 obs. of 6 variables: 312s ..$ sampleName: chr NA 312s ..$ chromosome: int 1 312s ..$ start : num 1.85e+08 312s ..$ end : num 2.47e+08 312s ..$ nbrOfLoci : int 1311 312s ..$ mean : num 0.23 312s $ segRows:'data.frame': 1 obs. of 2 variables: 312s ..$ startRow: int 2 312s ..$ endRow : int 4388 312s $ params :List of 5 312s ..$ alpha : num 0.001 312s ..$ undo : num 0 312s ..$ joinSegments : logi TRUE 312s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 312s .. ..$ chromosome: int 1 312s .. ..$ start : num 1.85e+08 312s .. ..$ end : num 2.47e+08 312s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 312s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 312s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.018 0 0.018 0 0 312s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 312s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 312s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 312s DH segmentation (locally-indexed) rows: 312s startRow endRow 312s 1 2 4388 312s int [1:4391] 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 312s DH segmentation rows: 312s startRow endRow 312s 1 10269 14655 312s Segmenting DH signals...done 312s DH segmentation table: 312s dhStart dhEnd dhNbrOfLoci dhMean 312s 1 185449813 247137334 1311 0.2295 312s startRow endRow 312s 1 10269 14655 312s Rows: 312s [1] 4 312s TCN segmentation rows: 312s startRow endRow 312s 4 10268 14658 312s TCN and DH segmentation rows: 312s startRow endRow 312s 4 10268 14658 312s startRow endRow 312s 1 10269 14655 312s startRow endRow 312s 1 1 7586 312s 2 NA NA 312s 3 7587 10267 312s TCN segmentation (expanded) rows: 312s startRow endRow 312s 1 1 7586 312s 2 NA NA 312s 3 7587 10267 312s 4 10268 14658 312s TCN and DH segmentation rows: 312s startRow endRow 312s 1 1 7586 312s 2 NA NA 312s 3 7587 10267 312s 4 10268 14658 312s startRow endRow 312s 1 10 7574 312s 2 NA NA 312s 3 7587 10263 312s 4 10269 14655 312s startRow endRow 312s 1 1 7586 312s 2 NA NA 312s 3 7587 10267 312s 4 10268 14658 312s Total CN segmentation table (expanded): 312s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 312s 4 1 185449813 247137334 4391 2.6341 1311 1311 312s (TCN,DH) segmentation for one total CN segment: 312s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 312s 4 4 1 1 185449813 247137334 4391 2.6341 1311 312s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 312s 4 1311 185449813 247137334 1311 0.2295 312s Total CN segment #4 ([1.8545e+08,2.47137e+08]) of 4...done 312s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 312s 1 1 1 1 554484 120992603 7586 1.3853 2108 312s 2 1 2 1 120992604 141510002 0 NA 0 312s 3 1 3 1 141510003 185449813 2681 2.0689 777 312s 4 1 4 1 185449813 247137334 4391 2.6341 1311 312s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 312s 1 2108 554484 120992603 2108 0.5116 312s 2 0 NA NA NA NA 312s 3 777 141510003 185449813 777 0.0973 312s 4 1311 185449813 247137334 1311 0.2295 312s Calculating (C1,C2) per segment... 312s Calculating (C1,C2) per segment...done 312s Number of segments: 4 312s Segmenting paired tumor-normal signals using Paired PSCBS...done 312s Post-segmenting TCNs... 312s Number of segments: 4 312s Number of chromosomes: 1 312s [1] 1 312s Chromosome 1 ('chr01') of 1... 312s Rows: 312s [1] 1 2 3 4 312s Number of segments: 4 312s TCN segment #1 ('1') of 4... 312s Nothing todo. Only one DH segmentation. Skipping. 312s TCN segment #1 ('1') of 4...done 312s TCN segment #2 ('2') of 4... 312s Nothing todo. Only one DH segmentation. Skipping. 312s TCN segment #2 ('2') of 4...done 312s TCN segment #3 ('3') of 4... 312s Nothing todo. Only one DH segmentation. Skipping. 312s TCN segment #3 ('3') of 4...done 312s TCN segment #4 ('4') of 4... 312s Nothing todo. Only one DH segmentation. Skipping. 312s TCN segment #4 ('4') of 4...done 312s Chromosome 1 ('chr01') of 1...done 312s Update (C1,C2) per segment... 312s Update (C1,C2) per segment...done 312s Post-segmenting TCNs...done 312s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 312s 1 1 1 1 554484 120992603 7586 1.3853 2108 312s 2 1 2 1 120992604 141510002 0 NA 0 312s 3 1 3 1 141510003 185449813 2681 2.0689 777 312s 4 1 4 1 185449813 247137334 4391 2.6341 1311 312s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 312s 1 2108 554484 120992603 2108 0.5116 0.3382903 1.047010 312s 2 0 NA NA NA NA NA NA 312s 3 777 141510003 185449813 777 0.0973 0.9337980 1.135102 312s 4 1311 185449813 247137334 1311 0.2295 1.0147870 1.619313 312s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 312s 1 1 1 1 554484 120992603 7586 1.3853 2108 312s 2 1 2 1 120992604 141510002 0 NA 0 312s 3 1 3 1 141510003 185449813 2681 2.0689 777 312s 4 1 4 1 185449813 247137334 4391 2.6341 1311 312s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 312s 1 2108 554484 120992603 2108 0.5116 0.3382903 1.047010 312s 2 0 NA NA NA NA NA NA 312s 3 777 141510003 185449813 777 0.0973 0.9337980 1.135102 312s 4 1311 185449813 247137334 1311 0.2295 1.0147870 1.619313 312s > print(fit) 312s chromosome tcnId dhId start end tcnNbrOfLoci tcnMean tcnNbrOfSNPs 312s 1 1 1 1 554484 120992603 7586 1.3853 2108 312s 2 1 2 1 120992604 141510002 0 NA 0 312s 3 1 3 1 141510003 185449813 2681 2.0689 777 312s 4 1 4 1 185449813 247137334 4391 2.6341 1311 312s tcnNbrOfHets dhNbrOfLoci dhMean c1Mean c2Mean 312s 1 2108 2108 0.5116 0.3382903 1.047010 312s 2 0 NA NA NA NA 312s 3 777 777 0.0973 0.9337980 1.135102 312s 4 1311 1311 0.2295 1.0147870 1.619313 312s > 312s > # Plot results 312s > plotTracks(fit) 312s > 312s > # Sanity check 312s > stopifnot(nbrOfSegments(fit) == nSegs) 312s > 312s > 312s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 312s > # Bootstrap segment level estimates 312s > # (used by the AB caller, which, if skipped here, 312s > # will do it automatically) 312s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 312s > fit <- bootstrapTCNandDHByRegion(fit, B=B, verbose=-10) 312s Resample (TCN,DH) signals and re-estimate summaries for segment & changepoint... 312s Already done? 312s tcn_2.5% tcn_5% tcn_95% tcn_97.5% dh_2.5% dh_5% dh_95% dh_97.5% 312s FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE 312s c1_2.5% c1_5% c1_95% c1_97.5% c2_2.5% c2_5% c2_95% c2_97.5% 312s FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE 312s Bootstrapping (TCN,DH,C1,C2) segment mean levels... 312s Identifying heterozygous & homozygous SNPs and non-polymorphic loci... 312s Number of loci: 14658 312s Number of SNPs: 4196 312s Number of non-SNPs: 10462 312s Identifying heterozygous & homozygous SNPs and non-polymorphic loci...done 312s num [1:4, 1:100, 1:4] NA NA NA NA NA NA NA NA NA NA ... 312s - attr(*, "dimnames")=List of 3 312s ..$ : NULL 312s ..$ : NULL 312s ..$ : chr [1:4] "tcn" "dh" "c1" "c2" 312s Segment #1 (chr 1, tcnId=1, dhId=1) of 4... 312s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 312s 1 1 1 1 554484 120992603 7586 1.3853 2108 312s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 312s 1 2108 554484 120992603 2108 0.5116 0.3382903 1.04701 312s Number of TCNs: 7586 312s Number of DHs: 2108 312s int [1:7586] 1 2 3 4 5 6 7 8 9 10 ... 312s int [1:14658] 1 2 3 4 5 6 7 8 9 10 ... 312s int [1:7586] 1 2 3 4 5 6 7 8 9 10 ... 312s Identify loci used to bootstrap DH means... 312s Heterozygous SNPs to resample for DH: 312s int [1:2108] 10 12 24 28 31 33 34 39 46 48 ... 312s Identify loci used to bootstrap DH means...done 312s Identify loci used to bootstrap TCN means... 312s SNPs: 312s int [1:2108] 10 12 24 28 31 33 34 39 46 48 ... 312s Non-polymorphic loci: 312s int [1:5478] 1 2 3 4 5 6 7 8 9 11 ... 312s Heterozygous SNPs to resample for TCN: 312s int [1:2108] 10 12 24 28 31 33 34 39 46 48 ... 312s Homozygous SNPs to resample for TCN: 312s int(0) 312s Non-polymorphic loci to resample for TCN: 312s int [1:5478] 1 2 3 4 5 6 7 8 9 11 ... 312s Heterozygous SNPs with non-DH to resample for TCN: 312s int(0) 312s Loci to resample for TCN: 312s int [1:7586] 1 2 3 4 5 6 7 8 9 10 ... 312s Identify loci used to bootstrap TCN means...done 312s Number of (#hets, #homs, #nonSNPs): (2108,0,5478) 312s Bootstrapping while preserving (#hets, #homs, #nonSNPs)... 312s Number of bootstrap samples: 100 312s Bootstrapping while preserving (#hets, #homs, #nonSNPs)...done 312s Segment #1 (chr 1, tcnId=1, dhId=1) of 4...done 312s Segment #2 (chr 1, tcnId=2, dhId=1) of 4... 312s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 312s 2 1 2 1 120992604 141510002 0 NA 0 312s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 312s 2 0 NA NA 0 NA NA NA 312s Number of TCNs: 0 312s Number of DHs: 0 312s int 0 312s int [1:14658] 1 2 3 4 5 6 7 8 9 10 ... 312s int(0) 312s Identify loci used to bootstrap DH means... 312s Heterozygous SNPs to resample for DH: 312s int 0 312s Identify loci used to bootstrap DH means...done 312s Identify loci used to bootstrap TCN means... 312s SNPs: 312s int(0) 312s Non-polymorphic loci: 312s int(0) 312s Heterozygous SNPs to resample for TCN: 312s int(0) 312s Homozygous SNPs to resample for TCN: 312s int(0) 312s Non-polymorphic loci to resample for TCN: 312s int(0) 312s Heterozygous SNPs with non-DH to resample for TCN: 312s int(0) 312s Loci to resample for TCN: 312s int(0) 312s Identify loci used to bootstrap TCN means...done 312s Number of (#hets, #homs, #nonSNPs): (0,0,0) 312s Bootstrapping while preserving (#hets, #homs, #nonSNPs)... 312s Number of bootstrap samples: 100 312s Bootstrapping while preserving (#hets, #homs, #nonSNPs)...done 312s Segment #2 (chr 1, tcnId=2, dhId=1) of 4...done 312s Segment #3 (chr 1, tcnId=3, dhId=1) of 4... 312s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 312s 3 1 3 1 141510003 185449813 2681 2.0689 777 312s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 312s 3 777 141510003 185449813 777 0.0973 0.933798 1.135102 312s Number of TCNs: 2681 312s Number of DHs: 777 312s int [1:2681] 7587 7588 7589 7590 7591 7592 7593 7594 7595 7596 ... 312s int [1:14658] 1 2 3 4 5 6 7 8 9 10 ... 312s int [1:2681] 7587 7588 7589 7590 7591 7592 7593 7594 7595 7596 ... 312s Identify loci used to bootstrap DH means... 312s Heterozygous SNPs to resample for DH: 312s int [1:777] 7587 7588 7594 7614 7616 7626 7627 7628 7635 7638 ... 312s Identify loci used to bootstrap DH means...done 312s Identify loci used to bootstrap TCN means... 312s SNPs: 312s int [1:777] 7587 7588 7594 7614 7616 7626 7627 7628 7635 7638 ... 312s Non-polymorphic loci: 312s int [1:1904] 7589 7590 7591 7592 7593 7595 7596 7597 7598 7599 ... 312s Heterozygous SNPs to resample for TCN: 312s int [1:777] 7587 7588 7594 7614 7616 7626 7627 7628 7635 7638 ... 312s Homozygous SNPs to resample for TCN: 312s int(0) 312s Non-polymorphic loci to resample for TCN: 312s int [1:1904] 7589 7590 7591 7592 7593 7595 7596 7597 7598 7599 ... 312s Heterozygous SNPs with non-DH to resample for TCN: 312s int(0) 312s Loci to resample for TCN: 312s int [1:2681] 7587 7588 7589 7590 7591 7592 7593 7594 7595 7596 ... 312s Identify loci used to bootstrap TCN means...done 312s Number of (#hets, #homs, #nonSNPs): (777,0,1904) 312s Bootstrapping while preserving (#hets, #homs, #nonSNPs)... 312s Number of bootstrap samples: 100 312s Bootstrapping while preserving (#hets, #homs, #nonSNPs)...done 312s Segment #3 (chr 1, tcnId=3, dhId=1) of 4...done 312s Segment #4 (chr 1, tcnId=4, dhId=1) of 4... 312s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 312s 4 1 4 1 185449813 247137334 4391 2.6341 1311 312s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 312s 4 1311 185449813 247137334 1311 0.2295 1.014787 1.619313 312s Number of TCNs: 4391 312s Number of DHs: 1311 312s int [1:4391] 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 312s int [1:14658] 1 2 3 4 5 6 7 8 9 10 ... 312s int [1:4391] 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 312s Identify loci used to bootstrap DH means... 312s Heterozygous SNPs to resample for DH: 312s int [1:1311] 10269 10271 10281 10282 10283 10293 10295 10297 10300 10302 ... 312s Identify loci used to bootstrap DH means...done 312s Identify loci used to bootstrap TCN means... 312s SNPs: 312s int [1:1311] 10269 10271 10281 10282 10283 10293 10295 10297 10300 10302 ... 312s Non-polymorphic loci: 312s int [1:3080] 10268 10270 10272 10273 10274 10275 10276 10277 10278 10279 ... 312s Heterozygous SNPs to resample for TCN: 312s int [1:1311] 10269 10271 10281 10282 10283 10293 10295 10297 10300 10302 ... 312s Homozygous SNPs to resample for TCN: 312s int(0) 312s Non-polymorphic loci to resample for TCN: 312s int [1:3080] 10268 10270 10272 10273 10274 10275 10276 10277 10278 10279 ... 312s Heterozygous SNPs with non-DH to resample for TCN: 312s int(0) 312s Loci to resample for TCN: 312s int [1:4391] 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 312s Identify loci used to bootstrap TCN means...done 312s Number of (#hets, #homs, #nonSNPs): (1311,0,3080) 312s Bootstrapping while preserving (#hets, #homs, #nonSNPs)... 312s Number of bootstrap samples: 100 312s Bootstrapping while preserving (#hets, #homs, #nonSNPs)...done 312s Segment #4 (chr 1, tcnId=4, dhId=1) of 4...done 312s Bootstrapped segment mean levels 312s num [1:4, 1:100, 1:4] 1.39 NA 2.08 2.63 1.38 ... 312s - attr(*, "dimnames")=List of 3 312s ..$ : NULL 312s ..$ : NULL 312s ..$ : chr [1:4] "tcn" "dh" "c1" "c2" 312s Calculating (C1,C2) mean levels from (TCN,DH) mean levels... 312s num [1:4, 1:100, 1:4] 1.39 NA 2.08 2.63 1.38 ... 312s - attr(*, "dimnames")=List of 3 312s ..$ : NULL 312s ..$ : NULL 312s ..$ : chr [1:4] "tcn" "dh" "c1" "c2" 312s Calculating (C1,C2) mean levels from (TCN,DH) mean levels...done 312s Calculating polar (alpha,radius,manhattan) for change points... 312s num [1:3, 1:100, 1:2] NA NA -0.0752 NA NA ... 312s - attr(*, "dimnames")=List of 3 312s ..$ : NULL 312s ..$ : NULL 312s ..$ : chr [1:2] "c1" "c2" 312s Bootstrapped change points 312s num [1:3, 1:100, 1:5] NA NA -1.73 NA NA ... 312s - attr(*, "dimnames")=List of 3 312s ..$ : NULL 312s ..$ : NULL 312s ..$ : chr [1:5] "alpha" "radius" "manhattan" "d1" ... 312s Calculating polar (alpha,radius,manhattan) for change points...done 312s Bootstrapping (TCN,DH,C1,C2) segment mean levels...done 312s Summarizing bootstrapped segment ('tcn', 'dh', 'c1', 'c2') data... 312s num [1:4, 1:4, 1:4] NA NA NA NA NA NA NA NA NA NA ... 312s - attr(*, "dimnames")=List of 3 312s ..$ : NULL 312s ..$ : chr [1:4] "2.5%" "5%" "95%" "97.5%" 312s ..$ : chr [1:4] "tcn" "dh" "c1" "c2" 312s Field #1 ('tcn') of 4... 312s Segment #1 of 4... 312s Segment #1 of 4...done 312s Segment #2 of 4... 312s Segment #2 of 4...done 312s Segment #3 of 4... 312s Segment #3 of 4...done 312s Segment #4 of 4... 312s Segment #4 of 4...done 312s Field #1 ('tcn') of 4...done 312s Field #2 ('dh') of 4... 312s Segment #1 of 4... 312s Segment #1 of 4...done 312s Segment #2 of 4... 312s Segment #2 of 4...done 312s Segment #3 of 4... 312s Segment #3 of 4...done 312s Segment #4 of 4... 312s Segment #4 of 4...done 312s Field #2 ('dh') of 4...done 312s Field #3 ('c1') of 4... 312s Segment #1 of 4... 312s Segment #1 of 4...done 312s Segment #2 of 4... 312s Segment #2 of 4...done 312s Segment #3 of 4... 312s Segment #3 of 4...done 312s Segment #4 of 4... 312s Segment #4 of 4...done 312s Field #3 ('c1') of 4...done 312s Field #4 ('c2') of 4... 312s Segment #1 of 4... 312s Segment #1 of 4...done 312s Segment #2 of 4... 312s Segment #2 of 4...done 312s Segment #3 of 4... 312s Segment #3 of 4...done 312s Segment #4 of 4... 312s Segment #4 of 4...done 312s Field #4 ('c2') of 4...done 312s Bootstrap statistics 312s num [1:4, 1:4, 1:4] 1.38 NA 2.06 2.63 1.38 ... 312s - attr(*, "dimnames")=List of 3 312s ..$ : NULL 312s ..$ : chr [1:4] "2.5%" "5%" "95%" "97.5%" 312s ..$ : chr [1:4] "tcn" "dh" "c1" "c2" 312s Statistical sanity checks (iff B >= 100)... 312s Available summaries: 2.5%, 5%, 95%, 97.5% 312s Available quantiles: 0.025, 0.05, 0.95, 0.975 312s num [1:4, 1:4, 1:4] 1.38 NA 2.06 2.63 1.38 ... 312s - attr(*, "dimnames")=List of 3 312s ..$ : NULL 312s ..$ : chr [1:4] "2.5%" "5%" "95%" "97.5%" 312s ..$ : chr [1:4] "tcn" "dh" "c1" "c2" 312s Field #1 ('tcn') of 4... 312s Seg 1. mean=1.3853, range=[1.37909,1.39287], n=7586 312s Seg 2. mean=NA, range=[NA,NA], n=0 312s Seg 3. mean=2.0689, range=[2.05903,2.079], n=2681 312s Seg 4. mean=2.6341, range=[2.62504,2.64649], n=4391 312s Field #1 ('tcn') of 4...done 312s Field #2 ('dh') of 4... 312s Seg 1. mean=0.5116, range=[0.502148,0.519941], n=2108 312s Seg 2. mean=NA, range=[NA,NA], n=NA 312s Seg 3. mean=0.0973, range=[0.0906366,0.105818], n=777 312s Seg 4. mean=0.2295, range=[0.222919,0.237005], n=1311 312s Field #2 ('dh') of 4...done 312s Field #3 ('c1') of 4... 312s Seg 1. mean=0.33829, range=[0.332209,0.345936], n=2108 312s Seg 2. mean=NA, range=[NA,NA], n=NA 312s Seg 3. mean=0.933798, range=[0.924112,0.941776], n=777 312s Seg 4. mean=1.01479, range=[1.00381,1.02461], n=1311 312s Field #3 ('c1') of 4...done 312s Field #4 ('c2') of 4... 312s Seg 1. mean=1.04701, range=[1.03882,1.05318], n=2108 312s Seg 2. mean=NA, range=[NA,NA], n=NA 312s Seg 3. mean=1.1351, range=[1.12454,1.1465], n=777 312s Seg 4. mean=1.61931, range=[1.60862,1.63328], n=1311 312s Field #4 ('c2') of 4...done 312s Statistical sanity checks (iff B >= 100)...done 312s Summarizing bootstrapped segment ('tcn', 'dh', 'c1', 'c2') data...done 312s Summarizing bootstrapped changepoint ('alpha', 'radius', 'manhattan', 'd1', 'd2') data... 312s num [1:3, 1:4, 1:5] NA NA NA NA NA NA NA NA NA NA ... 312s - attr(*, "dimnames")=List of 3 312s ..$ : NULL 312s ..$ : chr [1:4] "2.5%" "5%" "95%" "97.5%" 312s ..$ : chr [1:5] "alpha" "radius" "manhattan" "d1" ... 312s Field #1 ('alpha') of 5... 312s Changepoint #1 of 3... 312s Changepoint #1 of 3...done 312s Changepoint #2 of 3... 312s Changepoint #2 of 3...done 312s Changepoint #3 of 3... 312s Changepoint #3 of 3...done 312s Field #1 ('alpha') of 5...done 312s Field #2 ('radius') of 5... 312s Changepoint #1 of 3... 312s Changepoint #1 of 3...done 312s Changepoint #2 of 3... 312s Changepoint #2 of 3...done 312s Changepoint #3 of 3... 312s Changepoint #3 of 3...done 312s Field #2 ('radius') of 5...done 312s Field #3 ('manhattan') of 5... 312s Changepoint #1 of 3... 312s Changepoint #1 of 3...done 312s Changepoint #2 of 3... 312s Changepoint #2 of 3...done 312s Changepoint #3 of 3... 312s Changepoint #3 of 3...done 312s Field #3 ('manhattan') of 5...done 312s Field #4 ('d1') of 5... 312s Changepoint #1 of 3... 312s Changepoint #1 of 3...done 312s Changepoint #2 of 3... 312s Changepoint #2 of 3...done 312s Changepoint #3 of 3... 312s Changepoint #3 of 3...done 312s Field #4 ('d1') of 5...done 312s Field #5 ('d2') of 5... 312s Changepoint #1 of 3... 312s Changepoint #1 of 3...done 312s Changepoint #2 of 3... 312s Changepoint #2 of 3...done 312s Changepoint #3 of 3... 312s Changepoint #3 of 3...done 312s Field #5 ('d2') of 5...done 312s Bootstrap statistics 312s num [1:3, 1:4, 1:5] NA NA -1.77 NA NA ... 312s - attr(*, "dimnames")=List of 3 312s ..$ : NULL 312s ..$ : chr [1:4] "2.5%" "5%" "95%" "97.5%" 312s ..$ : chr [1:5] "alpha" "radius" "manhattan" "d1" ... 312s Summarizing bootstrapped changepoint ('alpha', 'radius', 'manhattan', 'd1', 'd2') data...done 312s Resample (TCN,DH) signals and re-estimate summaries for segment & changepoint...done 312s > print(fit) 312s chromosome tcnId dhId start end tcnNbrOfLoci tcnMean tcnNbrOfSNPs 312s 1 1 1 1 554484 120992603 7586 1.3853 2108 312s 2 1 2 1 120992604 141510002 0 NA 0 312s 3 1 3 1 141510003 185449813 2681 2.0689 777 312s 4 1 4 1 185449813 247137334 4391 2.6341 1311 312s tcnNbrOfHets dhNbrOfLoci dhMean c1Mean c2Mean 312s 1 2108 2108 0.5116 0.3382903 1.047010 312s 2 0 NA NA NA NA 312s 3 777 777 0.0973 0.9337980 1.135102 312s 4 1311 1311 0.2295 1.0147870 1.619313 312s > plotTracks(fit) 312s > 312s > 312s > 312s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 312s > # Calling segments with run of homozygosity (ROH) 312s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 312s > fit <- callROH(fit, verbose=-10) 312s Calling ROH... 312s Segment #1 of 4... 312s Calling ROH for a single segment... 312s Number of SNPs: 7586 312s Calling ROH for a single segment...done 312s Segment #1 of 4...done 312s Segment #2 of 4... 312s Calling ROH for a single segment... 312s Number of SNPs: 0 312s Calling ROH for a single segment...done 312s Segment #2 of 4...done 312s Segment #3 of 4... 312s Calling ROH for a single segment... 312s Number of SNPs: 2681 312s Calling ROH for a single segment...done 312s Segment #3 of 4...done 312s Segment #4 of 4... 312s Calling ROH for a single segment... 312s Number of SNPs: 4391 312s Calling ROH for a single segment...done 312s Segment #4 of 4...done 312s ROH calls: 312s logi [1:4] FALSE NA FALSE FALSE 312s Mode FALSE NA's 312s logical 3 1 312s Calling ROH...done 312s > print(fit) 312s chromosome tcnId dhId start end tcnNbrOfLoci tcnMean tcnNbrOfSNPs 312s 1 1 1 1 554484 120992603 7586 1.3853 2108 312s 2 1 2 1 120992604 141510002 0 NA 0 312s 3 1 3 1 141510003 185449813 2681 2.0689 777 312s 4 1 4 1 185449813 247137334 4391 2.6341 1311 312s tcnNbrOfHets dhNbrOfLoci dhMean c1Mean c2Mean rohCall 312s 1 2108 2108 0.5116 0.3382903 1.047010 FALSE 312s 2 0 NA NA NA NA NA 312s 3 777 777 0.0973 0.9337980 1.135102 FALSE 312s 4 1311 1311 0.2295 1.0147870 1.619313 FALSE 312s > plotTracks(fit) 312s > 312s > 312s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 312s > # Estimate background 312s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 312s > kappa <- estimateKappa(fit, verbose=-10) 312s Estimate global background (including normal contamination and more)... 312s Number of segments: 3 312s Estimating threshold Delta0.5 from the empirical density of C1:s... 312s adjust: 1 312s minDensity: 0.2 312s ploidy: 2 312s All peaks: 312s type x density 312s 1 peak 0.3362194 1.101242 312s 3 peak 0.9811492 1.065635 312s C1=0 and C1=1 peaks: 312s type x density 312s 1 peak 0.3362194 1.101242 312s 3 peak 0.9811492 1.065635 312s Estimate of Delta0.5: 0.65868427808456 312s Estimating threshold Delta0.5 from the empirical density of C1:s...done 312s Number of segments with C1 < Delta0.5: 1 312s Estimate of kappa: 0.33829026 312s Estimate global background (including normal contamination and more)...done 312s Warning message: 312s In density.default(c1, weights = weights, adjust = adjust, from = from, : 312s Selecting bandwidth *not* using 'weights' 312s > print(kappa) 312s [1] 0.3382903 312s > ## [1] 0.226011 312s > 312s > 312s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 312s > # Calling segments in allelic balance (AB) 312s > # NOTE: Ideally, this should be done on whole-genome data 312s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 312s > # Explicitly estimate the threshold in DH for calling AB 312s > # (which be done by default by the caller, if skipped here) 312s > deltaAB <- estimateDeltaAB(fit, flavor="qq(DH)", verbose=-10) 312s Estimating DH threshold for calling allelic imbalances... 312s flavor: qq(DH) 312s scale: 1 312s Estimating DH threshold for AB caller... 312s quantile #1: 0.05 312s Symmetric quantile #2: 0.9 312s Number of segments: 3 312s Weighted 5% quantile of DH: 0.257710 312s Number of segments with small DH: 2 312s Number of data points: 7072 312s Number of finite data points: 2088 312s Estimate of (1-0.9):th and 50% quantiles: (0.0310411,0.163658) 312s Estimate of 0.9:th "symmetric" quantile: 0.296275 312s Estimating DH threshold for AB caller...done 312s Estimated delta: 0.296 312s Estimating DH threshold for calling allelic imbalances...done 312s > if (Sys.getenv("_R_CHECK_FULL_") == "") { 312s + # Ad hoc workaround for not utilizing all of the data 312s + # in the test, which results in a poor estimate 312s + deltaAB <- 0.165 312s + } 312s > print(deltaAB) 312s [1] 0.165 312s > ## [1] 0.1657131 312s > 312s > fit <- callAB(fit, delta=deltaAB, verbose=-10) 312s Calling segments of allelic balance from one-sided DH bootstrap confidence intervals... 312s delta (offset adjusting for bias in DH): 0.165 312s alpha (CI quantile; significance level): 0.05 312s Calling segments... 312s Number of segments called allelic balance (AB): 1 (25.00%) of 4 312s Calling segments...done 312s Calling segments of allelic balance from one-sided DH bootstrap confidence intervals...done 312s > print(fit) 312s chromosome tcnId dhId start end tcnNbrOfLoci tcnMean tcnNbrOfSNPs 312s 1 1 1 1 554484 120992603 7586 1.3853 2108 312s 2 1 2 1 120992604 141510002 0 NA 0 312s 3 1 3 1 141510003 185449813 2681 2.0689 777 312s 4 1 4 1 185449813 247137334 4391 2.6341 1311 312s tcnNbrOfHets dhNbrOfLoci dhMean c1Mean c2Mean rohCall abCall 312s 1 2108 2108 0.5116 0.3382903 1.047010 FALSE FALSE 312s 2 0 NA NA NA NA NA NA 312s 3 777 777 0.0973 0.9337980 1.135102 FALSE TRUE 312s 4 1311 1311 0.2295 1.0147870 1.619313 FALSE FALSE 312s > plotTracks(fit) 312s > 312s > # Even if not explicitly specified, the estimated 312s > # threshold parameter is returned by the caller 312s > stopifnot(fit$params$deltaAB == deltaAB) 312s > 312s > 312s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 312s > # Calling segments in loss-of-heterozygosity (LOH) 312s > # NOTE: Ideally, this should be done on whole-genome data 312s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 312s > # Explicitly estimate the threshold in C1 for calling LOH 312s > # (which be done by default by the caller, if skipped here) 312s > deltaLOH <- estimateDeltaLOH(fit, flavor="minC1|nonAB", verbose=-10) 312s Estimating DH threshold for calling LOH... 312s flavor: minC1|nonAB 312s Estimating DH threshold for calling LOH as the midpoint between guessed C1=0 and C1=1... 312s Argument 'midpoint': 0.5 312s Number of segments: 4 312s Number of segments in allelic balance: 1 (25.0%) of 4 312s Number of segments not in allelic balance: 2 (50.0%) of 4 312s Number of segments in allelic balance and TCN <= 3.00: 1 (25.0%) of 4 312s C: 2.07 312s Corrected C1 (=C/2): 1.03 312s Number of DHs: 777 312s Weights: 1 312s Weighted median of (corrected) C1 in allelic balance: 1.034 312s Smallest C1 among segments not in allelic balance: 0.338 312s There are 1 segments with in total 2108 heterozygous SNPs with this level. 312s Midpoint between the two: 0.686 312s Estimating DH threshold for calling LOH as the midpoint between guessed C1=0 and C1=1...done 312s delta: 0.686 312s Estimating DH threshold for calling LOH...done 312s > print(deltaLOH) 312s [1] 0.6863701 312s > ## [1] 0.625175 312s > 312s > fit <- callLOH(fit, delta=deltaLOH, verbose=-10) 312s Calling segments of allelic balance from one-sided DH bootstrap confidence intervals... 312s delta (offset adjusting for bias in C1): 0.68637013 312s alpha (CI quantile; significance level): 0.05 312s Calling segments... 312s Number of segments called low C1 (LowC1, "LOH_C1"): 1 (25.00%) of 4 312s Calling segments...done 312s Calling segments of allelic balance from one-sided DH bootstrap confidence intervals...done 312s > print(fit) 312s chromosome tcnId dhId start end tcnNbrOfLoci tcnMean tcnNbrOfSNPs 312s 1 1 1 1 554484 120992603 7586 1.3853 2108 312s 2 1 2 1 120992604 141510002 0 NA 0 312s 3 1 3 1 141510003 185449813 2681 2.0689 777 312s 4 1 4 1 185449813 247137334 4391 2.6341 1311 312s tcnNbrOfHets dhNbrOfLoci dhMean c1Mean c2Mean rohCall abCall lohCall 312s 1 2108 2108 0.5116 0.3382903 1.047010 FALSE FALSE TRUE 312s 2 0 NA NA NA NA NA NA NA 312s 3 777 777 0.0973 0.9337980 1.135102 FALSE TRUE FALSE 312s 4 1311 1311 0.2295 1.0147870 1.619313 FALSE FALSE FALSE 312s > plotTracks(fit) 312s > 312s > # Even if not explicitly specified, the estimated 312s > # threshold parameter is returned by the caller 312s > stopifnot(fit$params$deltaLOH == deltaLOH) 312s > 312s > 312s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 312s > # Calling segments that are gained, copy neutral, and lost 312s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 312s > fit <- callGNL(fit, verbose=-10) 312s Calling gain, neutral, and loss based TCNs of AB segments... 312s Calling neutral TCNs... 312s callCopyNeutralByTCNofAB... 312s Alpha: 0.05 312s Delta CN: 0.33085487 312s Calling copy-neutral segments... 312s Retrieve TCN confidence intervals for all segments... 312s Interval: [0.025,0.975] 312s Retrieve TCN confidence intervals for all segments...done 312s Estimating TCN confidence interval of copy-neutral AB segments... 312s calcStatsForCopyNeutralABs... 312s Identifying copy neutral AB segments... 312s Number of AB segments: 1 312s Identifying segments that are copy neutral states... 312s Number of segments in allelic balance: 1 312s Identifying segments that are copy neutral states...done 312s Number of copy-neutral AB segments: 1 312s Extracting all copy neutral AB segments across all chromosomes into one big segment... 312s chromosome tcnId dhId start end tcnNbrOfLoci tcnMean tcnNbrOfSNPs 312s 3 1 3 1 141510003 185449813 2681 2.0689 777 312s tcnNbrOfHets dhNbrOfLoci dhMean c1Mean c2Mean rohCall abCall lohCall 312s 3 777 777 0.0973 0.933798 1.135102 FALSE TRUE FALSE 312s Extracting all copy neutral AB segments across all chromosomes into one big segment...done 312s Identifying copy neutral AB segments...done 312s Bootstrap the identified copy-neutral states... 312s Bootstrap the identified copy-neutral states...done 312s tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets dhNbrOfLoci dhMean c1Mean 312s 3 2681 2.0689 777 777 777 0.0973 0.933798 312s c2Mean tcn_2.5% tcn_5% tcn_95% tcn_97.5% dh_2.5% dh_5% dh_95% 312s 3 1.135102 2.055164 2.057694 2.078831 2.081454 0.08974138 0.09080508 0.1035891 312s dh_97.5% c1_2.5% c1_5% c1_95% c1_97.5% c2_2.5% c2_5% c2_95% 312s 3 0.1050478 0.923788 0.925412 0.9417056 0.9433752 1.124908 1.126631 1.143571 312s c2_97.5% 312s 3 1.145214 312s calcStatsForCopyNeutralABs...done 312s Bootstrap statistics for copy-neutral AB segments: 312s tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets dhNbrOfLoci dhMean c1Mean 312s 3 2681 2.0689 777 777 777 0.0973 0.933798 312s c2Mean tcn_2.5% tcn_5% tcn_95% tcn_97.5% dh_2.5% dh_5% dh_95% 312s 3 1.135102 2.055164 2.057694 2.078831 2.081454 0.08974138 0.09080508 0.1035891 312s dh_97.5% c1_2.5% c1_5% c1_95% c1_97.5% c2_2.5% c2_5% c2_95% 312s 3 0.1050478 0.923788 0.925412 0.9417056 0.9433752 1.124908 1.126631 1.143571 312s c2_97.5% 312s 3 1.145214 312s [1] "TCN statistics:" 312s tcnMean tcn_2.5% tcn_5% tcn_95% tcn_97.5% 312s 2.068900 2.055164 2.057694 2.078831 2.081454 312s 95%-confidence interval of TCN mean for the copy-neutral state: [2.05516,2.08145] (mean=2.0689) 312s Estimating TCN confidence interval of copy-neutral AB segments...done 312s Identify all copy-neutral segments... 312s DeltaCN: +/-0.330855 312s Call ("acceptance") region: [1.72431,2.41231] 312s Total number of segments: 4 312s Number of segments called allelic balance: 1 312s Number of segments called copy neutral: 1 312s Number of AB segments called copy neutral: 1 312s Number of non-AB segments called copy neutral: 0 312s Identify all copy-neutral segments...done 312s Calling copy-neutral segments...done 312s callCopyNeutralByTCNofAB...done 312s Calling neutral TCNs...done 312s Number of NTCN calls: 1 (25.00%) of 4 312s Mean TCN of AB segments: 2.06831 312s Calling loss... 312s Number of loss calls: 1 (25.00%) of 4 312s Calling loss...done 312s Calling gain... 312s Number of loss calls: 1 (25.00%) of 4 312s Calling gain...done 312s Calling gain, neutral, and loss based TCNs of AB segments...done 312s Warning message: 312s In density.default(c1, weights = weights, adjust = adjust, from = from, : 312s Selecting bandwidth *not* using 'weights' 312s > print(fit) 312s chromosome tcnId dhId start end tcnNbrOfLoci tcnMean tcnNbrOfSNPs 312s 1 1 1 1 554484 120992603 7586 1.3853 2108 312s 2 1 2 1 120992604 141510002 0 NA 0 312s 3 1 3 1 141510003 185449813 2681 2.0689 777 312s 4 1 4 1 185449813 247137334 4391 2.6341 1311 312s tcnNbrOfHets dhNbrOfLoci dhMean c1Mean c2Mean rohCall abCall lohCall 312s 1 2108 2108 0.5116 0.3382903 1.047010 FALSE FALSE TRUE 312s 2 0 NA NA NA NA NA NA NA 312s 3 777 777 0.0973 0.9337980 1.135102 FALSE TRUE FALSE 312s 4 1311 1311 0.2295 1.0147870 1.619313 FALSE FALSE FALSE 312s ntcnCall lossCall gainCall 312s 1 FALSE TRUE FALSE 312s 2 NA NA NA 312s 3 TRUE FALSE FALSE 312s 4 FALSE FALSE TRUE 312s > plotTracks(fit) 312s > 312s > proc.time() 312s user system elapsed 312s 3.812 0.032 3.843 312s Test segmentByPairedPSCBS,calls passed 312s 0 312s Begin test segmentByPairedPSCBS,futures 323s + cat segmentByPairedPSCBS,futures.Rout 323s 323s R version 4.5.2 (2025-10-31) -- "[Not] Part in a Rumble" 323s Copyright (C) 2025 The R Foundation for Statistical Computing 323s Platform: powerpc64le-unknown-linux-gnu 323s 323s R is free software and comes with ABSOLUTELY NO WARRANTY. 323s You are welcome to redistribute it under certain conditions. 323s Type 'license()' or 'licence()' for distribution details. 323s 323s R is a collaborative project with many contributors. 323s Type 'contributors()' for more information and 323s 'citation()' on how to cite R or R packages in publications. 323s 323s Type 'demo()' for some demos, 'help()' for on-line help, or 323s 'help.start()' for an HTML browser interface to help. 323s Type 'q()' to quit R. 323s 323s [Previously saved workspace restored] 323s 323s > library(PSCBS) 323s PSCBS v0.68.0 (2025-04-18 19:40:02 UTC) successfully loaded. See ?PSCBS for help. 323s > library(utils) 323s > 323s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 323s > # Load SNP microarray data 323s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 323s > data <- PSCBS::exampleData("paired.chr01") 323s > 323s > 323s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 323s > # Paired PSCBS segmentation 323s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 323s > # Drop single-locus outliers 323s > dataS <- dropSegmentationOutliers(data) 323s > 323s > # Run light-weight tests by default 323s > if (Sys.getenv("_R_CHECK_FULL_") == "") { 323s + # Use only every 5th data point 323s + dataS <- dataS[seq(from=1, to=nrow(data), by=5),] 323s + # Number of segments (for assertion) 323s + nSegs <- 4L 323s + } else { 323s + # Full tests 323s + nSegs <- 11L 323s + } 323s > 323s > str(dataS) 323s 'data.frame': 14670 obs. of 6 variables: 323s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 323s $ x : int 1145994 2941694 3710825 4240737 4276892 4464544 4714611 5095111 5034491 5158416 ... 323s $ CT : num 1.63 1.4 1.41 1.17 1.16 ... 323s $ betaT : num 0.7574 0.169 0.2357 0.2604 0.0576 ... 323s $ CN : num 2.36 2.13 2.26 2.01 2.32 ... 323s $ betaN : num 0.8274 0.5072 0.1671 0.1609 0.0421 ... 323s > 323s > 323s > ## Create multiple chromosomes 323s > data <- list() 323s > for (cc in 1:3) { 323s + dataS$chromosome <- cc 323s + data[[cc]] <- dataS 323s + } 323s > data <- Reduce(rbind, data) 323s > str(data) 323s 'data.frame': 44010 obs. of 6 variables: 323s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 323s $ x : int 1145994 2941694 3710825 4240737 4276892 4464544 4714611 5095111 5034491 5158416 ... 323s $ CT : num 1.63 1.4 1.41 1.17 1.16 ... 323s $ betaT : num 0.7574 0.169 0.2357 0.2604 0.0576 ... 323s $ CN : num 2.36 2.13 2.26 2.01 2.32 ... 323s $ betaN : num 0.8274 0.5072 0.1671 0.1609 0.0421 ... 323s > 323s > 323s > message("*** segmentByPairedPSCBS() via futures ...") 323s *** segmentByPairedPSCBS() via futures ... 323s > 323s > library("future") 323s > oplan <- plan() 323s > 323s > strategies <- c("sequential", "multisession") 323s > 323s > ## Test 'future.batchtools' futures? 323s > pkg <- "future.batchtools" 323s > if (require(pkg, character.only=TRUE)) { 323s + strategies <- c(strategies, "batchtools_local") 323s + } 323s Loading required package: future.batchtools 323s Warning message: 323s In library(package, lib.loc = lib.loc, character.only = TRUE, logical.return = TRUE, : 323s there is no package called 'future.batchtools' 323s > 323s > message("Future strategies to test: ", paste(sQuote(strategies), collapse=", ")) 323s Future strategies to test: 'sequential', 'multisession' 323s > 323s > fits <- list() 323s > for (strategy in strategies) { 323s + message(sprintf("- segmentByPairedPSCBS() using '%s' futures ...", strategy)) 323s + plan(strategy) 323s + fit <- segmentByPairedPSCBS(data, seed=0xBEEF, verbose=TRUE) 323s + fits[[strategy]] <- fit 323s + equal <- all.equal(fit, fits[[1]]) 323s + if (!equal) { 323s + str(fit) 323s + str(fits[[1]]) 323s + print(equal) 323s + stop(sprintf("segmentByPairedPSCBS() using '%s' futures does not produce the same results as when using '%s' futures", strategy, names(fits)[1])) 323s + } 323s + } 323s - segmentByPairedPSCBS() using 'sequential' futures ... 323s Segmenting paired tumor-normal signals using Paired PSCBS... 323s Calling genotypes from normal allele B fractions... 323s num [1:44010] 0.8274 0.5072 0.1671 0.1609 0.0421 ... 323s Called genotypes: 323s num [1:44010] 1 0.5 0 0 0 0 1 0 1 0.5 ... 323s - attr(*, "modelFit")=List of 1 323s ..$ :List of 7 323s .. ..$ flavor : chr "density" 323s .. ..$ cn : int 2 323s .. ..$ nbrOfGenotypeGroups: int 3 323s .. ..$ tau : num [1:2] 0.312 0.678 323s .. ..$ n : int 43920 323s .. ..$ fit :Classes 'PeaksAndValleys' and 'data.frame': 5 obs. of 3 variables: 323s .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 323s .. .. ..$ x : num [1:5] 0.0999 0.312 0.4986 0.6775 0.8922 323s .. .. ..$ density: num [1:5] 1.622 0.465 1.125 0.496 1.587 323s .. ..$ fitValleys :Classes 'PeaksAndValleys' and 'data.frame': 2 obs. of 3 variables: 323s .. .. ..$ type : chr [1:2] "valley" "valley" 323s .. .. ..$ x : num [1:2] 0.312 0.678 323s .. .. ..$ density: num [1:2] 0.465 0.496 323s ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 323s muN 323s 0 0.5 1 323s 15627 12633 15750 323s Calling genotypes from normal allele B fractions...done 323s Normalizing betaT using betaN (TumorBoost)... 323s Normalized BAFs: 323s num [1:44010] 0.9301 0.1667 0.0685 0.0995 0.0155 ... 323s - attr(*, "modelFit")=List of 5 323s ..$ method : chr "normalizeTumorBoost" 323s ..$ flavor : chr "v4" 323s ..$ delta : num [1:44010] -0.17264 0.00239 0.1671 0.16085 0.04213 ... 323s .. ..- attr(*, "modelFit")=List of 1 323s .. .. ..$ :List of 7 323s .. .. .. ..$ flavor : chr "density" 323s .. .. .. ..$ cn : int 2 323s .. .. .. ..$ nbrOfGenotypeGroups: int 3 323s .. .. .. ..$ tau : num [1:2] 0.312 0.678 323s .. .. .. ..$ n : int 43920 323s .. .. .. ..$ fit :Classes 'PeaksAndValleys' and 'data.frame': 5 obs. of 3 variables: 323s .. .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 323s .. .. .. .. ..$ x : num [1:5] 0.0999 0.312 0.4986 0.6775 0.8922 323s .. .. .. .. ..$ density: num [1:5] 1.622 0.465 1.125 0.496 1.587 323s .. .. .. ..$ fitValleys :Classes 'PeaksAndValleys' and 'data.frame': 2 obs. of 3 variables: 323s .. .. .. .. ..$ type : chr [1:2] "valley" "valley" 323s .. .. .. .. ..$ x : num [1:2] 0.312 0.678 323s .. .. .. .. ..$ density: num [1:2] 0.465 0.496 323s .. .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 323s ..$ preserveScale: logi FALSE 323s ..$ scaleFactor : num NA 323s Normalizing betaT using betaN (TumorBoost)...done 323s Setup up data... 323s 'data.frame': 44010 obs. of 7 variables: 323s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 323s $ x : num 1145994 2941694 3710825 4240737 4276892 ... 323s $ CT : num 1.63 1.4 1.41 1.17 1.16 ... 323s $ betaT : num 0.7574 0.169 0.2357 0.2604 0.0576 ... 323s $ betaTN : num 0.9301 0.1667 0.0685 0.0995 0.0155 ... 323s ..- attr(*, "modelFit")=List of 5 323s .. ..$ method : chr "normalizeTumorBoost" 323s .. ..$ flavor : chr "v4" 323s .. ..$ delta : num [1:44010] -0.17264 0.00239 0.1671 0.16085 0.04213 ... 323s .. .. ..- attr(*, "modelFit")=List of 1 323s .. .. .. ..$ :List of 7 323s .. .. .. .. ..$ flavor : chr "density" 323s .. .. .. .. ..$ cn : int 2 323s .. .. .. .. ..$ nbrOfGenotypeGroups: int 3 323s .. .. .. .. ..$ tau : num [1:2] 0.312 0.678 323s .. .. .. .. ..$ n : int 43920 323s .. .. .. .. ..$ fit :Classes 'PeaksAndValleys' and 'data.frame': 5 obs. of 3 variables: 323s .. .. .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 323s .. .. .. .. .. ..$ x : num [1:5] 0.0999 0.312 0.4986 0.6775 0.8922 323s .. .. .. .. .. ..$ density: num [1:5] 1.622 0.465 1.125 0.496 1.587 323s .. .. .. .. ..$ fitValleys :Classes 'PeaksAndValleys' and 'data.frame': 2 obs. of 3 variables: 323s .. .. .. .. .. ..$ type : chr [1:2] "valley" "valley" 323s .. .. .. .. .. ..$ x : num [1:2] 0.312 0.678 323s .. .. .. .. .. ..$ density: num [1:2] 0.465 0.496 323s .. .. .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 323s .. ..$ preserveScale: logi FALSE 323s .. ..$ scaleFactor : num NA 323s $ betaN : num 0.8274 0.5072 0.1671 0.1609 0.0421 ... 323s $ muN : num 1 0.5 0 0 0 0 1 0 1 0.5 ... 323s ..- attr(*, "modelFit")=List of 1 323s .. ..$ :List of 7 323s .. .. ..$ flavor : chr "density" 323s .. .. ..$ cn : int 2 323s .. .. ..$ nbrOfGenotypeGroups: int 3 323s .. .. ..$ tau : num [1:2] 0.312 0.678 323s .. .. ..$ n : int 43920 323s .. .. ..$ fit :Classes 'PeaksAndValleys' and 'data.frame': 5 obs. of 3 variables: 323s .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 323s .. .. .. ..$ x : num [1:5] 0.0999 0.312 0.4986 0.6775 0.8922 323s .. .. .. ..$ density: num [1:5] 1.622 0.465 1.125 0.496 1.587 323s .. .. ..$ fitValleys :Classes 'PeaksAndValleys' and 'data.frame': 2 obs. of 3 variables: 323s .. .. .. ..$ type : chr [1:2] "valley" "valley" 323s .. .. .. ..$ x : num [1:2] 0.312 0.678 323s .. .. .. ..$ density: num [1:2] 0.465 0.496 323s .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 323s Setup up data...done 323s Dropping loci for which TCNs are missing... 323s Number of loci dropped: 36 323s Dropping loci for which TCNs are missing...done 323s Ordering data along genome... 323s 'data.frame': 43974 obs. of 7 variables: 323s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 323s $ x : num 554484 730720 782343 878522 916294 ... 323s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 323s $ betaT : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 323s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 323s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 323s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 323s Ordering data along genome...done 323s Segmenting multiple chromosomes... 323s Number of chromosomes: 3 323s Random seed temporarily set (seed=c(48879), kind="L'Ecuyer-CMRG") 323s Produced 3 seeds from this stream for future usage 323s Chromosome #1 ('Chr01') of 3... 323s 'data.frame': 14658 obs. of 8 variables: 323s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 323s $ x : num 554484 730720 782343 878522 916294 ... 323s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 323s $ betaT : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 323s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 323s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 323s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 323s $ index : int 1 2 3 4 5 6 7 8 9 10 ... 323s Known segments: 323s [1] chromosome start end 323s <0 rows> (or 0-length row.names) 323s Segmenting paired tumor-normal signals using Paired PSCBS... 323s Setup up data... 323s 'data.frame': 14658 obs. of 7 variables: 323s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 323s $ x : num 554484 730720 782343 878522 916294 ... 323s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 323s $ betaT : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 323s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 323s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 323s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 323s Setup up data...done 323s Ordering data along genome... 323s 'data.frame': 14658 obs. of 7 variables: 323s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 323s $ x : num 554484 730720 782343 878522 916294 ... 323s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 323s $ betaT : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 323s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 323s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 323s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 323s Ordering data along genome...done 323s Keeping only current chromosome for 'knownSegments'... 323s Chromosome: 1 323s Known segments for this chromosome: 323s [1] chromosome start end 323s <0 rows> (or 0-length row.names) 323s Keeping only current chromosome for 'knownSegments'...done 323s alphaTCN: 0.009 323s alphaDH: 0.001 323s Number of loci: 14658 323s Calculating DHs... 323s Number of SNPs: 14658 323s Number of heterozygous SNPs: 4209 (28.71%) 323s Normalized DHs: 323s num [1:14658] NA NA NA NA NA ... 323s Calculating DHs...done 323s Random seed temporarily set (seed=c(10407, 1066287653, -51199871, 161854402, -1995183193, 1503453565, -747102133), kind="L'Ecuyer-CMRG") 323s Produced 2 seeds from this stream for future usage 323s Identification of change points by total copy numbers... 323s Segmenting by CBS... 323s Chromosome: 1 323s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 323s Segmenting by CBS...done 323s List of 4 323s $ data :'data.frame': 14658 obs. of 4 variables: 323s ..$ chromosome: int [1:14658] 1 1 1 1 1 1 1 1 1 1 ... 323s ..$ x : num [1:14658] 554484 730720 782343 878522 916294 ... 323s ..$ y : num [1:14658] 1.88 1.8 1.59 1.64 1.53 ... 323s ..$ index : int [1:14658] 1 2 3 4 5 6 7 8 9 10 ... 323s $ output :'data.frame': 3 obs. of 6 variables: 323s ..$ sampleName: chr [1:3] NA NA NA 323s ..$ chromosome: int [1:3] 1 1 1 323s ..$ start : num [1:3] 5.54e+05 1.44e+08 1.85e+08 323s ..$ end : num [1:3] 1.44e+08 1.85e+08 2.47e+08 323s ..$ nbrOfLoci : int [1:3] 7599 2668 4391 323s ..$ mean : num [1:3] 1.39 2.07 2.63 323s $ segRows:'data.frame': 3 obs. of 2 variables: 323s ..$ startRow: int [1:3] 1 7600 10268 323s ..$ endRow : int [1:3] 7599 10267 14658 323s $ params :List of 5 323s ..$ alpha : num 0.009 323s ..$ undo : num 0 323s ..$ joinSegments : logi TRUE 323s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 323s .. ..$ chromosome: int 1 323s .. ..$ start : num -Inf 323s .. ..$ end : num Inf 323s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 323s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 323s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.497 0 0.497 0 0 323s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 323s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 323s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 323s Identification of change points by total copy numbers...done 323s Restructure TCN segmentation results... 323s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean 323s 1 1 554484 143926517 7599 1.3859 323s 2 1 143926517 185449813 2668 2.0704 323s 3 1 185449813 247137334 4391 2.6341 323s Number of TCN segments: 3 323s Restructure TCN segmentation results...done 323s Total CN segment #1 ([ 554484,1.43927e+08]) of 3... 323s Number of TCN loci in segment: 7599 323s Locus data for TCN segment: 323s 'data.frame': 7599 obs. of 9 variables: 323s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 323s $ x : num 554484 730720 782343 878522 916294 ... 323s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 323s $ betaT : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 323s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 323s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 323s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 323s $ index : int 1 2 3 4 5 6 7 8 9 10 ... 323s $ rho : num NA NA NA NA NA ... 323s Number of loci: 7599 323s Number of SNPs: 2120 (27.90%) 323s Number of heterozygous SNPs: 2120 (100.00%) 323s Chromosome: 1 323s Segmenting DH signals... 323s Segmenting by CBS... 323s Chromosome: 1 323s Random seed temporarily set (seed=c(10407, -821273412, -52578226, 1415511586, 721384351, -665928286, 1316562960), kind="L'Ecuyer-CMRG") 323s Segmenting by CBS...done 323s List of 4 323s $ data :'data.frame': 7599 obs. of 4 variables: 323s ..$ chromosome: int [1:7599] 1 1 1 1 1 1 1 1 1 1 ... 323s ..$ x : num [1:7599] 554484 730720 782343 878522 916294 ... 323s ..$ y : num [1:7599] NA NA NA NA NA ... 323s ..$ index : int [1:7599] 1 2 3 4 5 6 7 8 9 10 ... 323s $ output :'data.frame': 1 obs. of 6 variables: 323s ..$ sampleName: chr NA 323s ..$ chromosome: int 1 323s ..$ start : num 554484 323s ..$ end : num 1.44e+08 323s ..$ nbrOfLoci : int 2120 323s ..$ mean : num 0.51 323s $ segRows:'data.frame': 1 obs. of 2 variables: 323s ..$ startRow: int 10 323s ..$ endRow : int 7594 323s $ params :List of 5 323s ..$ alpha : num 0.001 323s ..$ undo : num 0 323s ..$ joinSegments : logi TRUE 323s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 323s .. ..$ chromosome: int 1 323s .. ..$ start : num 554484 323s .. ..$ end : num 1.44e+08 323s ..$ seed : int [1:7] 10407 -821273412 -52578226 1415511586 721384351 -665928286 1316562960 323s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 323s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.031 0 0.031 0 0 323s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 323s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 323s - attr(*, "randomSeed")= int [1:7] 10407 -821273412 -52578226 1415511586 721384351 -665928286 1316562960 323s DH segmentation (locally-indexed) rows: 323s startRow endRow 323s 1 10 7594 323s int [1:7599] 1 2 3 4 5 6 7 8 9 10 ... 323s DH segmentation rows: 323s startRow endRow 323s 1 10 7594 323s Segmenting DH signals...done 323s DH segmentation table: 323s dhStart dhEnd dhNbrOfLoci dhMean 323s 1 554484 143926517 2120 0.5101 323s startRow endRow 323s 1 10 7594 323s Rows: 323s [1] 1 323s TCN segmentation rows: 323s startRow endRow 323s 1 1 7599 323s TCN and DH segmentation rows: 323s startRow endRow 323s 1 1 7599 323s startRow endRow 323s 1 10 7594 323s NULL 323s TCN segmentation (expanded) rows: 323s startRow endRow 323s 1 1 7599 323s TCN and DH segmentation rows: 323s startRow endRow 323s 1 1 7599 323s 2 7600 10267 323s 3 10268 14658 323s startRow endRow 323s 1 10 7594 323s startRow endRow 323s 1 1 7599 323s Total CN segmentation table (expanded): 323s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 323s 1 1 554484 143926517 7599 1.3859 2120 2120 323s (TCN,DH) segmentation for one total CN segment: 323s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 323s 1 1 1 1 554484 143926517 7599 1.3859 2120 323s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 323s 1 2120 554484 143926517 2120 0.5101 323s Total CN segment #1 ([ 554484,1.43927e+08]) of 3...done 323s Total CN segment #2 ([1.43927e+08,1.8545e+08]) of 3... 323s Number of TCN loci in segment: 2668 323s Locus data for TCN segment: 323s 'data.frame': 2668 obs. of 9 variables: 323s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 323s $ x : num 1.44e+08 1.44e+08 1.44e+08 1.44e+08 1.44e+08 ... 323s $ CT : num 2.1 2.1 2.09 1.8 2.34 ... 323s $ betaT : num 0.027542 1.030222 1.094093 0.046763 -0.000948 ... 323s $ betaTN : num 0.027542 1.030222 1.094093 0.046763 -0.000948 ... 323s $ betaN : num 0.1624 0.8788 0.8225 0.1201 0.0317 ... 323s $ muN : num 0 1 1 0 0 1 0 0 0 0 ... 323s $ index : int 7600 7601 7602 7603 7604 7605 7606 7607 7608 7609 ... 323s $ rho : num NA NA NA NA NA NA NA NA NA NA ... 323s Number of loci: 2668 323s Number of SNPs: 775 (29.05%) 323s Number of heterozygous SNPs: 775 (100.00%) 323s Chromosome: 1 323s Segmenting DH signals... 323s Segmenting by CBS... 323s Chromosome: 1 323s Random seed temporarily set (seed=c(10407, -821273412, -52578226, 1415511586, 721384351, -665928286, 1316562960), kind="L'Ecuyer-CMRG") 323s Segmenting by CBS...done 323s List of 4 323s $ data :'data.frame': 2668 obs. of 4 variables: 323s ..$ chromosome: int [1:2668] 1 1 1 1 1 1 1 1 1 1 ... 323s ..$ x : num [1:2668] 1.44e+08 1.44e+08 1.44e+08 1.44e+08 1.44e+08 ... 323s ..$ y : num [1:2668] NA NA NA NA NA NA NA NA NA NA ... 323s ..$ index : int [1:2668] 1 2 3 4 5 6 7 8 9 10 ... 323s $ output :'data.frame': 1 obs. of 6 variables: 323s ..$ sampleName: chr NA 323s ..$ chromosome: int 1 323s ..$ start : num 1.44e+08 323s ..$ end : num 1.85e+08 323s ..$ nbrOfLoci : int 775 323s ..$ mean : num 0.097 323s $ segRows:'data.frame': 1 obs. of 2 variables: 323s ..$ startRow: int 15 323s ..$ endRow : int 2664 323s $ params :List of 5 323s ..$ alpha : num 0.001 323s ..$ undo : num 0 323s ..$ joinSegments : logi TRUE 323s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 323s .. ..$ chromosome: int 1 323s .. ..$ start : num 1.44e+08 323s .. ..$ end : num 1.85e+08 323s ..$ seed : int [1:7] 10407 -821273412 -52578226 1415511586 721384351 -665928286 1316562960 323s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 323s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.009 0 0.009 0 0 323s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 323s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 323s - attr(*, "randomSeed")= int [1:7] 10407 -821273412 -52578226 1415511586 721384351 -665928286 1316562960 323s DH segmentation (locally-indexed) rows: 323s startRow endRow 323s 1 15 2664 323s int [1:2668] 7600 7601 7602 7603 7604 7605 7606 7607 7608 7609 ... 323s DH segmentation rows: 323s startRow endRow 323s 1 7614 10263 323s Segmenting DH signals...done 323s DH segmentation table: 323s dhStart dhEnd dhNbrOfLoci dhMean 323s 1 143926517 185449813 775 0.097 323s startRow endRow 323s 1 7614 10263 323s Rows: 323s [1] 2 323s TCN segmentation rows: 323s startRow endRow 323s 2 7600 10267 323s TCN and DH segmentation rows: 323s startRow endRow 323s 2 7600 10267 323s startRow endRow 323s 1 7614 10263 323s startRow endRow 323s 1 1 7599 323s TCN segmentation (expanded) rows: 323s startRow endRow 323s 1 1 7599 323s 2 7600 10267 323s TCN and DH segmentation rows: 323s startRow endRow 323s 1 1 7599 323s 2 7600 10267 323s 3 10268 14658 323s startRow endRow 323s 1 10 7594 323s 2 7614 10263 323s startRow endRow 323s 1 1 7599 323s 2 7600 10267 323s Total CN segmentation table (expanded): 323s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 323s 2 1 143926517 185449813 2668 2.0704 775 775 323s (TCN,DH) segmentation for one total CN segment: 323s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 323s 2 2 1 1 143926517 185449813 2668 2.0704 775 323s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 323s 2 775 143926517 185449813 775 0.097 323s Total CN segment #2 ([1.43927e+08,1.8545e+08]) of 3...done 323s Total CN segment #3 ([1.8545e+08,2.47137e+08]) of 3... 323s Number of TCN loci in segment: 4391 323s Locus data for TCN segment: 323s 'data.frame': 4391 obs. of 9 variables: 323s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 323s $ x : num 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 323s $ CT : num 2.93 2.15 2.82 2.93 2.46 ... 323s $ betaT : num -0.169 0.609 1.028 0.525 0.968 ... 323s $ betaTN : num -0.169 0.609 1.028 0.525 0.968 ... 323s $ betaN : num 0.25 0.38 0.919 0.34 0.783 ... 323s $ muN : num 0 0.5 1 0.5 1 1 0 1 0 1 ... 323s $ index : int 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 323s $ rho : num NA 0.2186 NA 0.0503 NA ... 323s Number of loci: 4391 323s Number of SNPs: 1314 (29.92%) 323s Number of heterozygous SNPs: 1314 (100.00%) 323s Chromosome: 1 323s Segmenting DH signals... 323s Segmenting by CBS... 323s Chromosome: 1 323s Random seed temporarily set (seed=c(10407, -821273412, -52578226, 1415511586, 721384351, -665928286, 1316562960), kind="L'Ecuyer-CMRG") 323s Segmenting by CBS...done 323s List of 4 323s $ data :'data.frame': 4391 obs. of 4 variables: 323s ..$ chromosome: int [1:4391] 1 1 1 1 1 1 1 1 1 1 ... 323s ..$ x : num [1:4391] 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 323s ..$ y : num [1:4391] NA 0.2186 NA 0.0503 NA ... 323s ..$ index : int [1:4391] 1 2 3 4 5 6 7 8 9 10 ... 323s $ output :'data.frame': 1 obs. of 6 variables: 323s ..$ sampleName: chr NA 323s ..$ chromosome: int 1 323s ..$ start : num 1.85e+08 323s ..$ end : num 2.47e+08 323s ..$ nbrOfLoci : int 1314 323s ..$ mean : num 0.23 323s $ segRows:'data.frame': 1 obs. of 2 variables: 323s ..$ startRow: int 2 323s ..$ endRow : int 4388 323s $ params :List of 5 323s ..$ alpha : num 0.001 323s ..$ undo : num 0 323s ..$ joinSegments : logi TRUE 323s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 323s .. ..$ chromosome: int 1 323s .. ..$ start : num 1.85e+08 323s .. ..$ end : num 2.47e+08 323s ..$ seed : int [1:7] 10407 -821273412 -52578226 1415511586 721384351 -665928286 1316562960 323s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 323s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.017 0 0.017 0 0 323s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 323s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 323s - attr(*, "randomSeed")= int [1:7] 10407 -821273412 -52578226 1415511586 721384351 -665928286 1316562960 323s DH segmentation (locally-indexed) rows: 323s startRow endRow 323s 1 2 4388 323s int [1:4391] 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 323s DH segmentation rows: 323s startRow endRow 323s 1 10269 14655 323s Segmenting DH signals...done 323s DH segmentation table: 323s dhStart dhEnd dhNbrOfLoci dhMean 323s 1 185449813 247137334 1314 0.2295 323s startRow endRow 323s 1 10269 14655 323s Rows: 323s [1] 3 323s TCN segmentation rows: 323s startRow endRow 323s 3 10268 14658 323s TCN and DH segmentation rows: 323s startRow endRow 323s 3 10268 14658 323s startRow endRow 323s 1 10269 14655 323s startRow endRow 323s 1 1 7599 323s 2 7600 10267 323s TCN segmentation (expanded) rows: 323s startRow endRow 323s 1 1 7599 323s 2 7600 10267 323s 3 10268 14658 323s TCN and DH segmentation rows: 323s startRow endRow 323s 1 1 7599 323s 2 7600 10267 323s 3 10268 14658 323s startRow endRow 323s 1 10 7594 323s 2 7614 10263 323s 3 10269 14655 323s startRow endRow 323s 1 1 7599 323s 2 7600 10267 323s 3 10268 14658 323s Total CN segmentation table (expanded): 323s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 323s 3 1 185449813 247137334 4391 2.6341 1314 1314 323s (TCN,DH) segmentation for one total CN segment: 323s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 323s 3 3 1 1 185449813 247137334 4391 2.6341 1314 323s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 323s 3 1314 185449813 247137334 1314 0.2295 323s Total CN segment #3 ([1.8545e+08,2.47137e+08]) of 3...done 323s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 323s 1 1 1 1 554484 143926517 7599 1.3859 2120 323s 2 1 2 1 143926517 185449813 2668 2.0704 775 323s 3 1 3 1 185449813 247137334 4391 2.6341 1314 323s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 323s 1 2120 554484 143926517 2120 0.5101 323s 2 775 143926517 185449813 775 0.0970 323s 3 1314 185449813 247137334 1314 0.2295 323s Calculating (C1,C2) per segment... 323s Calculating (C1,C2) per segment...done 323s Number of segments: 3 323s Segmenting paired tumor-normal signals using Paired PSCBS...done 323s Post-segmenting TCNs... 323s Number of segments: 3 323s Number of chromosomes: 1 323s [1] 1 323s Chromosome 1 ('chr01') of 1... 323s Rows: 323s [1] 1 2 3 323s Number of segments: 3 323s TCN segment #1 ('1') of 3... 323s Nothing todo. Only one DH segmentation. Skipping. 323s TCN segment #1 ('1') of 3...done 323s TCN segment #2 ('2') of 3... 323s Nothing todo. Only one DH segmentation. Skipping. 323s TCN segment #2 ('2') of 3...done 323s TCN segment #3 ('3') of 3... 323s Nothing todo. Only one DH segmentation. Skipping. 323s TCN segment #3 ('3') of 3...done 323s Chromosome 1 ('chr01') of 1...done 323s Update (C1,C2) per segment... 323s Update (C1,C2) per segment...done 323s Post-segmenting TCNs...done 323s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 323s 1 1 1 1 554484 143926517 7599 1.3859 2120 323s 2 1 2 1 143926517 185449813 2668 2.0704 775 323s 3 1 3 1 185449813 247137334 4391 2.6341 1314 323s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 323s 1 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 323s 2 775 143926517 185449813 775 0.0970 0.9347856 1.135614 323s 3 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 323s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 323s 1 1 1 1 554484 143926517 7599 1.3859 2120 323s 2 1 2 1 143926517 185449813 2668 2.0704 775 323s 3 1 3 1 185449813 247137334 4391 2.6341 1314 323s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 323s 1 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 323s 2 775 143926517 185449813 775 0.0970 0.9347856 1.135614 323s 3 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 323s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 323s 1 1 1 1 554484 143926517 7599 1.3859 2120 323s 2 1 2 1 143926517 185449813 2668 2.0704 775 323s 3 1 3 1 185449813 247137334 4391 2.6341 1314 323s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 323s 1 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 323s 2 775 143926517 185449813 775 0.0970 0.9347856 1.135614 323s 3 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 323s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 323s 1 1 1 1 554484 143926517 7599 1.3859 2120 323s 2 1 2 1 143926517 185449813 2668 2.0704 775 323s 3 1 3 1 185449813 247137334 4391 2.6341 1314 323s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 323s 1 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 323s 2 775 143926517 185449813 775 0.0970 0.9347856 1.135614 323s 3 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 323s Chromosome #1 ('Chr01') of 3...done 323s Chromosome #2 ('Chr02') of 3... 323s 'data.frame': 14658 obs. of 8 variables: 323s $ chromosome: int 2 2 2 2 2 2 2 2 2 2 ... 323s $ x : num 554484 730720 782343 878522 916294 ... 323s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 323s $ betaT : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 323s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 323s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 323s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 323s $ index : int 14659 14660 14661 14662 14663 14664 14665 14666 14667 14668 ... 323s Known segments: 323s [1] chromosome start end 323s <0 rows> (or 0-length row.names) 323s Segmenting paired tumor-normal signals using Paired PSCBS... 323s Setup up data... 323s 'data.frame': 14658 obs. of 7 variables: 323s $ chromosome: int 2 2 2 2 2 2 2 2 2 2 ... 323s $ x : num 554484 730720 782343 878522 916294 ... 323s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 323s $ betaT : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 323s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 323s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 323s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 323s Setup up data...done 323s Ordering data along genome... 323s 'data.frame': 14658 obs. of 7 variables: 323s $ chromosome: int 2 2 2 2 2 2 2 2 2 2 ... 323s $ x : num 554484 730720 782343 878522 916294 ... 323s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 323s $ betaT : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 323s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 323s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 323s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 323s Ordering data along genome...done 323s Keeping only current chromosome for 'knownSegments'... 323s Chromosome: 2 323s Known segments for this chromosome: 323s [1] chromosome start end 323s <0 rows> (or 0-length row.names) 323s Keeping only current chromosome for 'knownSegments'...done 323s alphaTCN: 0.009 323s alphaDH: 0.001 323s Number of loci: 14658 323s Calculating DHs... 323s Number of SNPs: 14658 323s Number of heterozygous SNPs: 4209 (28.71%) 323s Normalized DHs: 323s num [1:14658] NA NA NA NA NA ... 323s Calculating DHs...done 323s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 323s Produced 2 seeds from this stream for future usage 323s Identification of change points by total copy numbers... 323s Segmenting by CBS... 323s Chromosome: 2 323s Random seed temporarily set (seed=c(10407, -821273412, -52578226, 1415511586, 721384351, -665928286, 1316562960), kind="L'Ecuyer-CMRG") 323s Segmenting by CBS...done 323s List of 4 323s $ data :'data.frame': 14658 obs. of 4 variables: 323s ..$ chromosome: int [1:14658] 2 2 2 2 2 2 2 2 2 2 ... 323s ..$ x : num [1:14658] 554484 730720 782343 878522 916294 ... 323s ..$ y : num [1:14658] 1.88 1.8 1.59 1.64 1.53 ... 323s ..$ index : int [1:14658] 1 2 3 4 5 6 7 8 9 10 ... 323s $ output :'data.frame': 3 obs. of 6 variables: 323s ..$ sampleName: chr [1:3] NA NA NA 323s ..$ chromosome: int [1:3] 2 2 2 323s ..$ start : num [1:3] 5.54e+05 1.44e+08 1.85e+08 323s ..$ end : num [1:3] 1.44e+08 1.85e+08 2.47e+08 323s ..$ nbrOfLoci : int [1:3] 7599 2668 4391 323s ..$ mean : num [1:3] 1.39 2.07 2.63 323s $ segRows:'data.frame': 3 obs. of 2 variables: 323s ..$ startRow: int [1:3] 1 7600 10268 323s ..$ endRow : int [1:3] 7599 10267 14658 323s $ params :List of 5 323s ..$ alpha : num 0.009 323s ..$ undo : num 0 323s ..$ joinSegments : logi TRUE 323s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 323s .. ..$ chromosome: int 2 323s .. ..$ start : num -Inf 323s .. ..$ end : num Inf 323s ..$ seed : int [1:7] 10407 -821273412 -52578226 1415511586 721384351 -665928286 1316562960 323s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 323s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.52 0 0.521 0 0 323s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 323s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 323s - attr(*, "randomSeed")= int [1:7] 10407 -821273412 -52578226 1415511586 721384351 -665928286 1316562960 323s Identification of change points by total copy numbers...done 323s Restructure TCN segmentation results... 323s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean 323s 1 2 554484 143926517 7599 1.3859 323s 2 2 143926517 185449813 2668 2.0704 323s 3 2 185449813 247137334 4391 2.6341 323s Number of TCN segments: 3 323s Restructure TCN segmentation results...done 323s Total CN segment #1 ([ 554484,1.43927e+08]) of 3... 323s Number of TCN loci in segment: 7599 323s Locus data for TCN segment: 323s 'data.frame': 7599 obs. of 9 variables: 323s $ chromosome: int 2 2 2 2 2 2 2 2 2 2 ... 323s $ x : num 554484 730720 782343 878522 916294 ... 323s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 323s $ betaT : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 323s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 323s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 323s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 323s $ index : int 1 2 3 4 5 6 7 8 9 10 ... 323s $ rho : num NA NA NA NA NA ... 323s Number of loci: 7599 323s Number of SNPs: 2120 (27.90%) 323s Number of heterozygous SNPs: 2120 (100.00%) 323s Chromosome: 2 323s Segmenting DH signals... 323s Segmenting by CBS... 323s Chromosome: 2 323s Random seed temporarily set (seed=c(10407, -1924040949, -1632234809, -437763632, -1464377300, 676654412, 2080370711), kind="L'Ecuyer-CMRG") 323s Segmenting by CBS...done 323s List of 4 323s $ data :'data.frame': 7599 obs. of 4 variables: 323s ..$ chromosome: int [1:7599] 2 2 2 2 2 2 2 2 2 2 ... 323s ..$ x : num [1:7599] 554484 730720 782343 878522 916294 ... 323s ..$ y : num [1:7599] NA NA NA NA NA ... 323s ..$ index : int [1:7599] 1 2 3 4 5 6 7 8 9 10 ... 323s $ output :'data.frame': 1 obs. of 6 variables: 323s ..$ sampleName: chr NA 323s ..$ chromosome: int 2 323s ..$ start : num 554484 323s ..$ end : num 1.44e+08 323s ..$ nbrOfLoci : int 2120 323s ..$ mean : num 0.51 323s $ segRows:'data.frame': 1 obs. of 2 variables: 323s ..$ startRow: int 10 323s ..$ endRow : int 7594 323s $ params :List of 5 323s ..$ alpha : num 0.001 323s ..$ undo : num 0 323s ..$ joinSegments : logi TRUE 323s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 323s .. ..$ chromosome: int 2 323s .. ..$ start : num 554484 323s .. ..$ end : num 1.44e+08 323s ..$ seed : int [1:7] 10407 -1924040949 -1632234809 -437763632 -1464377300 676654412 2080370711 323s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 323s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.031 0 0.03 0 0 323s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 323s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 323s - attr(*, "randomSeed")= int [1:7] 10407 -1924040949 -1632234809 -437763632 -1464377300 676654412 2080370711 323s DH segmentation (locally-indexed) rows: 323s startRow endRow 323s 1 10 7594 323s int [1:7599] 1 2 3 4 5 6 7 8 9 10 ... 323s DH segmentation rows: 323s startRow endRow 323s 1 10 7594 323s Segmenting DH signals...done 323s DH segmentation table: 323s dhStart dhEnd dhNbrOfLoci dhMean 323s 1 554484 143926517 2120 0.5101 323s startRow endRow 323s 1 10 7594 323s Rows: 323s [1] 1 323s TCN segmentation rows: 323s startRow endRow 323s 1 1 7599 323s TCN and DH segmentation rows: 323s startRow endRow 323s 1 1 7599 323s startRow endRow 323s 1 10 7594 323s NULL 323s TCN segmentation (expanded) rows: 323s startRow endRow 323s 1 1 7599 323s TCN and DH segmentation rows: 323s startRow endRow 323s 1 1 7599 323s 2 7600 10267 323s 3 10268 14658 323s startRow endRow 323s 1 10 7594 323s startRow endRow 323s 1 1 7599 323s Total CN segmentation table (expanded): 323s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 323s 1 2 554484 143926517 7599 1.3859 2120 2120 323s (TCN,DH) segmentation for one total CN segment: 323s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 323s 1 1 1 2 554484 143926517 7599 1.3859 2120 323s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 323s 1 2120 554484 143926517 2120 0.5101 323s Total CN segment #1 ([ 554484,1.43927e+08]) of 3...done 323s Total CN segment #2 ([1.43927e+08,1.8545e+08]) of 3... 323s Number of TCN loci in segment: 2668 323s Locus data for TCN segment: 323s 'data.frame': 2668 obs. of 9 variables: 323s $ chromosome: int 2 2 2 2 2 2 2 2 2 2 ... 323s $ x : num 1.44e+08 1.44e+08 1.44e+08 1.44e+08 1.44e+08 ... 323s $ CT : num 2.1 2.1 2.09 1.8 2.34 ... 323s $ betaT : num 0.027542 1.030222 1.094093 0.046763 -0.000948 ... 323s $ betaTN : num 0.027542 1.030222 1.094093 0.046763 -0.000948 ... 323s $ betaN : num 0.1624 0.8788 0.8225 0.1201 0.0317 ... 323s $ muN : num 0 1 1 0 0 1 0 0 0 0 ... 323s $ index : int 7600 7601 7602 7603 7604 7605 7606 7607 7608 7609 ... 323s $ rho : num NA NA NA NA NA NA NA NA NA NA ... 323s Number of loci: 2668 323s Number of SNPs: 775 (29.05%) 323s Number of heterozygous SNPs: 775 (100.00%) 323s Chromosome: 2 323s Segmenting DH signals... 323s Segmenting by CBS... 323s Chromosome: 2 323s Random seed temporarily set (seed=c(10407, -1924040949, -1632234809, -437763632, -1464377300, 676654412, 2080370711), kind="L'Ecuyer-CMRG") 323s Segmenting by CBS...done 323s List of 4 323s $ data :'data.frame': 2668 obs. of 4 variables: 323s ..$ chromosome: int [1:2668] 2 2 2 2 2 2 2 2 2 2 ... 323s ..$ x : num [1:2668] 1.44e+08 1.44e+08 1.44e+08 1.44e+08 1.44e+08 ... 323s ..$ y : num [1:2668] NA NA NA NA NA NA NA NA NA NA ... 323s ..$ index : int [1:2668] 1 2 3 4 5 6 7 8 9 10 ... 323s $ output :'data.frame': 1 obs. of 6 variables: 323s ..$ sampleName: chr NA 323s ..$ chromosome: int 2 323s ..$ start : num 1.44e+08 323s ..$ end : num 1.85e+08 323s ..$ nbrOfLoci : int 775 323s ..$ mean : num 0.097 323s $ segRows:'data.frame': 1 obs. of 2 variables: 323s ..$ startRow: int 15 323s ..$ endRow : int 2664 323s $ params :List of 5 323s ..$ alpha : num 0.001 323s ..$ undo : num 0 323s ..$ joinSegments : logi TRUE 323s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 323s .. ..$ chromosome: int 2 323s .. ..$ start : num 1.44e+08 323s .. ..$ end : num 1.85e+08 323s ..$ seed : int [1:7] 10407 -1924040949 -1632234809 -437763632 -1464377300 676654412 2080370711 323s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 323s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.009 0 0.009 0 0 323s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 323s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 323s - attr(*, "randomSeed")= int [1:7] 10407 -1924040949 -1632234809 -437763632 -1464377300 676654412 2080370711 323s DH segmentation (locally-indexed) rows: 323s startRow endRow 323s 1 15 2664 323s int [1:2668] 7600 7601 7602 7603 7604 7605 7606 7607 7608 7609 ... 323s DH segmentation rows: 323s startRow endRow 323s 1 7614 10263 323s Segmenting DH signals...done 323s DH segmentation table: 323s dhStart dhEnd dhNbrOfLoci dhMean 323s 1 143926517 185449813 775 0.097 323s startRow endRow 323s 1 7614 10263 323s Rows: 323s [1] 2 323s TCN segmentation rows: 323s startRow endRow 323s 2 7600 10267 323s TCN and DH segmentation rows: 323s startRow endRow 323s 2 7600 10267 323s startRow endRow 323s 1 7614 10263 323s startRow endRow 323s 1 1 7599 323s TCN segmentation (expanded) rows: 323s startRow endRow 323s 1 1 7599 323s 2 7600 10267 323s TCN and DH segmentation rows: 323s startRow endRow 323s 1 1 7599 323s 2 7600 10267 323s 3 10268 14658 323s startRow endRow 323s 1 10 7594 323s 2 7614 10263 323s startRow endRow 323s 1 1 7599 323s 2 7600 10267 323s Total CN segmentation table (expanded): 323s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 323s 2 2 143926517 185449813 2668 2.0704 775 775 323s (TCN,DH) segmentation for one total CN segment: 323s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 323s 2 2 1 2 143926517 185449813 2668 2.0704 775 323s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 323s 2 775 143926517 185449813 775 0.097 323s Total CN segment #2 ([1.43927e+08,1.8545e+08]) of 3...done 323s Total CN segment #3 ([1.8545e+08,2.47137e+08]) of 3... 323s Number of TCN loci in segment: 4391 323s Locus data for TCN segment: 323s 'data.frame': 4391 obs. of 9 variables: 323s $ chromosome: int 2 2 2 2 2 2 2 2 2 2 ... 323s $ x : num 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 323s $ CT : num 2.93 2.15 2.82 2.93 2.46 ... 323s $ betaT : num -0.169 0.609 1.028 0.525 0.968 ... 323s $ betaTN : num -0.169 0.609 1.028 0.525 0.968 ... 323s $ betaN : num 0.25 0.38 0.919 0.34 0.783 ... 323s $ muN : num 0 0.5 1 0.5 1 1 0 1 0 1 ... 323s $ index : int 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 323s $ rho : num NA 0.2186 NA 0.0503 NA ... 323s Number of loci: 4391 323s Number of SNPs: 1314 (29.92%) 323s Number of heterozygous SNPs: 1314 (100.00%) 323s Chromosome: 2 323s Segmenting DH signals... 323s Segmenting by CBS... 323s Chromosome: 2 323s Random seed temporarily set (seed=c(10407, -1924040949, -1632234809, -437763632, -1464377300, 676654412, 2080370711), kind="L'Ecuyer-CMRG") 323s Segmenting by CBS...done 323s List of 4 323s $ data :'data.frame': 4391 obs. of 4 variables: 323s ..$ chromosome: int [1:4391] 2 2 2 2 2 2 2 2 2 2 ... 323s ..$ x : num [1:4391] 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 323s ..$ y : num [1:4391] NA 0.2186 NA 0.0503 NA ... 323s ..$ index : int [1:4391] 1 2 3 4 5 6 7 8 9 10 ... 323s $ output :'data.frame': 1 obs. of 6 variables: 323s ..$ sampleName: chr NA 323s ..$ chromosome: int 2 323s ..$ start : num 1.85e+08 323s ..$ end : num 2.47e+08 323s ..$ nbrOfLoci : int 1314 323s ..$ mean : num 0.23 323s $ segRows:'data.frame': 1 obs. of 2 variables: 323s ..$ startRow: int 2 323s ..$ endRow : int 4388 323s $ params :List of 5 323s ..$ alpha : num 0.001 323s ..$ undo : num 0 323s ..$ joinSegments : logi TRUE 323s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 323s .. ..$ chromosome: int 2 323s .. ..$ start : num 1.85e+08 323s .. ..$ end : num 2.47e+08 323s ..$ seed : int [1:7] 10407 -1924040949 -1632234809 -437763632 -1464377300 676654412 2080370711 323s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 323s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.017 0 0.017 0 0 323s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 323s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 323s - attr(*, "randomSeed")= int [1:7] 10407 -1924040949 -1632234809 -437763632 -1464377300 676654412 2080370711 323s DH segmentation (locally-indexed) rows: 323s startRow endRow 323s 1 2 4388 323s int [1:4391] 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 323s DH segmentation rows: 323s startRow endRow 323s 1 10269 14655 323s Segmenting DH signals...done 323s DH segmentation table: 323s dhStart dhEnd dhNbrOfLoci dhMean 323s 1 185449813 247137334 1314 0.2295 323s startRow endRow 323s 1 10269 14655 323s Rows: 323s [1] 3 323s TCN segmentation rows: 323s startRow endRow 323s 3 10268 14658 323s TCN and DH segmentation rows: 323s startRow endRow 323s 3 10268 14658 323s startRow endRow 323s 1 10269 14655 323s startRow endRow 323s 1 1 7599 323s 2 7600 10267 323s TCN segmentation (expanded) rows: 323s startRow endRow 323s 1 1 7599 323s 2 7600 10267 323s 3 10268 14658 323s TCN and DH segmentation rows: 323s startRow endRow 323s 1 1 7599 323s 2 7600 10267 323s 3 10268 14658 323s startRow endRow 323s 1 10 7594 323s 2 7614 10263 323s 3 10269 14655 323s startRow endRow 323s 1 1 7599 323s 2 7600 10267 323s 3 10268 14658 323s Total CN segmentation table (expanded): 323s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 323s 3 2 185449813 247137334 4391 2.6341 1314 1314 323s (TCN,DH) segmentation for one total CN segment: 323s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 323s 3 3 1 2 185449813 247137334 4391 2.6341 1314 323s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 323s 3 1314 185449813 247137334 1314 0.2295 323s Total CN segment #3 ([1.8545e+08,2.47137e+08]) of 3...done 323s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 323s 1 2 1 1 554484 143926517 7599 1.3859 2120 323s 2 2 2 1 143926517 185449813 2668 2.0704 775 323s 3 2 3 1 185449813 247137334 4391 2.6341 1314 323s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 323s 1 2120 554484 143926517 2120 0.5101 323s 2 775 143926517 185449813 775 0.0970 323s 3 1314 185449813 247137334 1314 0.2295 323s Calculating (C1,C2) per segment... 323s Calculating (C1,C2) per segment...done 323s Number of segments: 3 323s Segmenting paired tumor-normal signals using Paired PSCBS...done 323s Post-segmenting TCNs... 323s Number of segments: 3 323s Number of chromosomes: 1 323s [1] 2 323s Chromosome 1 ('chr02') of 1... 323s Rows: 323s [1] 1 2 3 323s Number of segments: 3 323s TCN segment #1 ('1') of 3... 323s Nothing todo. Only one DH segmentation. Skipping. 323s TCN segment #1 ('1') of 3...done 323s TCN segment #2 ('2') of 3... 323s Nothing todo. Only one DH segmentation. Skipping. 323s TCN segment #2 ('2') of 3...done 323s TCN segment #3 ('3') of 3... 323s Nothing todo. Only one DH segmentation. Skipping. 323s TCN segment #3 ('3') of 3...done 323s Chromosome 1 ('chr02') of 1...done 323s Update (C1,C2) per segment... 323s Update (C1,C2) per segment...done 323s Post-segmenting TCNs...done 323s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 323s 1 2 1 1 554484 143926517 7599 1.3859 2120 323s 2 2 2 1 143926517 185449813 2668 2.0704 775 323s 3 2 3 1 185449813 247137334 4391 2.6341 1314 323s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 323s 1 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 323s 2 775 143926517 185449813 775 0.0970 0.9347856 1.135614 323s 3 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 323s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 323s 1 2 1 1 554484 143926517 7599 1.3859 2120 323s 2 2 2 1 143926517 185449813 2668 2.0704 775 323s 3 2 3 1 185449813 247137334 4391 2.6341 1314 323s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 323s 1 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 323s 2 775 143926517 185449813 775 0.0970 0.9347856 1.135614 323s 3 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 323s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 323s 1 2 1 1 554484 143926517 7599 1.3859 2120 323s 2 2 2 1 143926517 185449813 2668 2.0704 775 323s 3 2 3 1 185449813 247137334 4391 2.6341 1314 323s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 323s 1 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 323s 2 775 143926517 185449813 775 0.0970 0.9347856 1.135614 323s 3 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 323s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 323s 1 2 1 1 554484 143926517 7599 1.3859 2120 323s 2 2 2 1 143926517 185449813 2668 2.0704 775 323s 3 2 3 1 185449813 247137334 4391 2.6341 1314 323s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 323s 1 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 323s 2 775 143926517 185449813 775 0.0970 0.9347856 1.135614 323s 3 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 323s Chromosome #2 ('Chr02') of 3...done 323s Chromosome #3 ('Chr03') of 3... 323s 'data.frame': 14658 obs. of 8 variables: 323s $ chromosome: int 3 3 3 3 3 3 3 3 3 3 ... 323s $ x : num 554484 730720 782343 878522 916294 ... 323s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 323s $ betaT : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 323s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 323s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 323s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 323s $ index : int 29317 29318 29319 29320 29321 29322 29323 29324 29325 29326 ... 323s Known segments: 323s [1] chromosome start end 323s <0 rows> (or 0-length row.names) 323s Segmenting paired tumor-normal signals using Paired PSCBS... 323s Setup up data... 323s 'data.frame': 14658 obs. of 7 variables: 323s $ chromosome: int 3 3 3 3 3 3 3 3 3 3 ... 323s $ x : num 554484 730720 782343 878522 916294 ... 323s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 323s $ betaT : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 323s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 323s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 323s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 323s Setup up data...done 323s Ordering data along genome... 323s 'data.frame': 14658 obs. of 7 variables: 323s $ chromosome: int 3 3 3 3 3 3 3 3 3 3 ... 323s $ x : num 554484 730720 782343 878522 916294 ... 323s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 323s $ betaT : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 323s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 323s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 323s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 323s Ordering data along genome...done 323s Keeping only current chromosome for 'knownSegments'... 323s Chromosome: 3 323s Known segments for this chromosome: 323s [1] chromosome start end 323s <0 rows> (or 0-length row.names) 323s Keeping only current chromosome for 'knownSegments'...done 323s alphaTCN: 0.009 323s alphaDH: 0.001 323s Number of loci: 14658 323s Calculating DHs... 323s Number of SNPs: 14658 323s Number of heterozygous SNPs: 4209 (28.71%) 323s Normalized DHs: 323s num [1:14658] NA NA NA NA NA ... 323s Calculating DHs...done 323s Random seed temporarily set (seed=c(10407, -821273412, -52578226, 1415511586, 721384351, -665928286, 1316562960), kind="L'Ecuyer-CMRG") 323s Produced 2 seeds from this stream for future usage 323s Identification of change points by total copy numbers... 323s Segmenting by CBS... 323s Chromosome: 3 323s Random seed temporarily set (seed=c(10407, -1924040949, -1632234809, -437763632, -1464377300, 676654412, 2080370711), kind="L'Ecuyer-CMRG") 323s Segmenting by CBS...done 323s List of 4 323s $ data :'data.frame': 14658 obs. of 4 variables: 323s ..$ chromosome: int [1:14658] 3 3 3 3 3 3 3 3 3 3 ... 323s ..$ x : num [1:14658] 554484 730720 782343 878522 916294 ... 323s ..$ y : num [1:14658] 1.88 1.8 1.59 1.64 1.53 ... 323s ..$ index : int [1:14658] 1 2 3 4 5 6 7 8 9 10 ... 323s $ output :'data.frame': 3 obs. of 6 variables: 323s ..$ sampleName: chr [1:3] NA NA NA 323s ..$ chromosome: int [1:3] 3 3 3 323s ..$ start : num [1:3] 5.54e+05 1.44e+08 1.85e+08 323s ..$ end : num [1:3] 1.44e+08 1.85e+08 2.47e+08 323s ..$ nbrOfLoci : int [1:3] 7599 2668 4391 323s ..$ mean : num [1:3] 1.39 2.07 2.63 323s $ segRows:'data.frame': 3 obs. of 2 variables: 323s ..$ startRow: int [1:3] 1 7600 10268 323s ..$ endRow : int [1:3] 7599 10267 14658 323s $ params :List of 5 323s ..$ alpha : num 0.009 323s ..$ undo : num 0 323s ..$ joinSegments : logi TRUE 323s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 323s .. ..$ chromosome: int 3 323s .. ..$ start : num -Inf 323s .. ..$ end : num Inf 323s ..$ seed : int [1:7] 10407 -1924040949 -1632234809 -437763632 -1464377300 676654412 2080370711 323s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 323s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.49 0 0.49 0 0 323s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 323s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 323s - attr(*, "randomSeed")= int [1:7] 10407 -1924040949 -1632234809 -437763632 -1464377300 676654412 2080370711 323s Identification of change points by total copy numbers...done 323s Restructure TCN segmentation results... 323s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean 323s 1 3 554484 143926517 7599 1.3859 323s 2 3 143926517 185449813 2668 2.0704 323s 3 3 185449813 247137334 4391 2.6341 323s Number of TCN segments: 3 323s Restructure TCN segmentation results...done 323s Total CN segment #1 ([ 554484,1.43927e+08]) of 3... 323s Number of TCN loci in segment: 7599 323s Locus data for TCN segment: 323s 'data.frame': 7599 obs. of 9 variables: 323s $ chromosome: int 3 3 3 3 3 3 3 3 3 3 ... 323s $ x : num 554484 730720 782343 878522 916294 ... 323s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 323s $ betaT : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 323s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 323s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 323s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 323s $ index : int 1 2 3 4 5 6 7 8 9 10 ... 323s $ rho : num NA NA NA NA NA ... 323s Number of loci: 7599 323s Number of SNPs: 2120 (27.90%) 323s Number of heterozygous SNPs: 2120 (100.00%) 323s Chromosome: 3 323s Segmenting DH signals... 323s Segmenting by CBS... 323s Chromosome: 3 323s Random seed temporarily set (seed=c(10407, -1371615447, -889757879, 1692656974, -1723952224, 1378814990, 1816467252), kind="L'Ecuyer-CMRG") 323s Segmenting by CBS...done 323s List of 4 323s $ data :'data.frame': 7599 obs. of 4 variables: 323s ..$ chromosome: int [1:7599] 3 3 3 3 3 3 3 3 3 3 ... 323s ..$ x : num [1:7599] 554484 730720 782343 878522 916294 ... 323s ..$ y : num [1:7599] NA NA NA NA NA ... 323s ..$ index : int [1:7599] 1 2 3 4 5 6 7 8 9 10 ... 323s $ output :'data.frame': 1 obs. of 6 variables: 323s ..$ sampleName: chr NA 323s ..$ chromosome: int 3 323s ..$ start : num 554484 323s ..$ end : num 1.44e+08 323s ..$ nbrOfLoci : int 2120 323s ..$ mean : num 0.51 323s $ segRows:'data.frame': 1 obs. of 2 variables: 323s ..$ startRow: int 10 323s ..$ endRow : int 7594 323s $ params :List of 5 323s ..$ alpha : num 0.001 323s ..$ undo : num 0 323s ..$ joinSegments : logi TRUE 323s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 323s .. ..$ chromosome: int 3 323s .. ..$ start : num 554484 323s .. ..$ end : num 1.44e+08 323s ..$ seed : int [1:7] 10407 -1371615447 -889757879 1692656974 -1723952224 1378814990 1816467252 323s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 323s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.03 0 0.031 0 0 323s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 323s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 323s - attr(*, "randomSeed")= int [1:7] 10407 -1371615447 -889757879 1692656974 -1723952224 1378814990 1816467252 323s DH segmentation (locally-indexed) rows: 323s startRow endRow 323s 1 10 7594 323s int [1:7599] 1 2 3 4 5 6 7 8 9 10 ... 323s DH segmentation rows: 323s startRow endRow 323s 1 10 7594 323s Segmenting DH signals...done 323s DH segmentation table: 323s dhStart dhEnd dhNbrOfLoci dhMean 323s 1 554484 143926517 2120 0.5101 323s startRow endRow 323s 1 10 7594 323s Rows: 323s [1] 1 323s TCN segmentation rows: 323s startRow endRow 323s 1 1 7599 323s TCN and DH segmentation rows: 323s startRow endRow 323s 1 1 7599 323s startRow endRow 323s 1 10 7594 323s NULL 323s TCN segmentation (expanded) rows: 323s startRow endRow 323s 1 1 7599 323s TCN and DH segmentation rows: 323s startRow endRow 323s 1 1 7599 323s 2 7600 10267 323s 3 10268 14658 323s startRow endRow 323s 1 10 7594 323s startRow endRow 323s 1 1 7599 323s Total CN segmentation table (expanded): 323s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 323s 1 3 554484 143926517 7599 1.3859 2120 2120 323s (TCN,DH) segmentation for one total CN segment: 323s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 323s 1 1 1 3 554484 143926517 7599 1.3859 2120 323s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 323s 1 2120 554484 143926517 2120 0.5101 323s Total CN segment #1 ([ 554484,1.43927e+08]) of 3...done 323s Total CN segment #2 ([1.43927e+08,1.8545e+08]) of 3... 323s Number of TCN loci in segment: 2668 323s Locus data for TCN segment: 323s 'data.frame': 2668 obs. of 9 variables: 323s $ chromosome: int 3 3 3 3 3 3 3 3 3 3 ... 323s $ x : num 1.44e+08 1.44e+08 1.44e+08 1.44e+08 1.44e+08 ... 323s $ CT : num 2.1 2.1 2.09 1.8 2.34 ... 323s $ betaT : num 0.027542 1.030222 1.094093 0.046763 -0.000948 ... 323s $ betaTN : num 0.027542 1.030222 1.094093 0.046763 -0.000948 ... 323s $ betaN : num 0.1624 0.8788 0.8225 0.1201 0.0317 ... 323s $ muN : num 0 1 1 0 0 1 0 0 0 0 ... 323s $ index : int 7600 7601 7602 7603 7604 7605 7606 7607 7608 7609 ... 323s $ rho : num NA NA NA NA NA NA NA NA NA NA ... 323s Number of loci: 2668 323s Number of SNPs: 775 (29.05%) 323s Number of heterozygous SNPs: 775 (100.00%) 323s Chromosome: 3 323s Segmenting DH signals... 323s Segmenting by CBS... 323s Chromosome: 3 323s Random seed temporarily set (seed=c(10407, -1371615447, -889757879, 1692656974, -1723952224, 1378814990, 1816467252), kind="L'Ecuyer-CMRG") 323s Segmenting by CBS...done 323s List of 4 323s $ data :'data.frame': 2668 obs. of 4 variables: 323s ..$ chromosome: int [1:2668] 3 3 3 3 3 3 3 3 3 3 ... 323s ..$ x : num [1:2668] 1.44e+08 1.44e+08 1.44e+08 1.44e+08 1.44e+08 ... 323s ..$ y : num [1:2668] NA NA NA NA NA NA NA NA NA NA ... 323s ..$ index : int [1:2668] 1 2 3 4 5 6 7 8 9 10 ... 323s $ output :'data.frame': 1 obs. of 6 variables: 323s ..$ sampleName: chr NA 323s ..$ chromosome: int 3 323s ..$ start : num 1.44e+08 323s ..$ end : num 1.85e+08 323s ..$ nbrOfLoci : int 775 323s ..$ mean : num 0.097 323s $ segRows:'data.frame': 1 obs. of 2 variables: 323s ..$ startRow: int 15 323s ..$ endRow : int 2664 323s $ params :List of 5 323s ..$ alpha : num 0.001 323s ..$ undo : num 0 323s ..$ joinSegments : logi TRUE 323s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 323s .. ..$ chromosome: int 3 323s .. ..$ start : num 1.44e+08 323s .. ..$ end : num 1.85e+08 323s ..$ seed : int [1:7] 10407 -1371615447 -889757879 1692656974 -1723952224 1378814990 1816467252 323s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 323s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.01 0 0.01 0 0 323s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 323s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 323s - attr(*, "randomSeed")= int [1:7] 10407 -1371615447 -889757879 1692656974 -1723952224 1378814990 1816467252 323s DH segmentation (locally-indexed) rows: 323s startRow endRow 323s 1 15 2664 323s int [1:2668] 7600 7601 7602 7603 7604 7605 7606 7607 7608 7609 ... 323s DH segmentation rows: 323s startRow endRow 323s 1 7614 10263 323s Segmenting DH signals...done 323s DH segmentation table: 323s dhStart dhEnd dhNbrOfLoci dhMean 323s 1 143926517 185449813 775 0.097 323s startRow endRow 323s 1 7614 10263 323s Rows: 323s [1] 2 323s TCN segmentation rows: 323s startRow endRow 323s 2 7600 10267 323s TCN and DH segmentation rows: 323s startRow endRow 323s 2 7600 10267 323s startRow endRow 323s 1 7614 10263 323s startRow endRow 323s 1 1 7599 323s TCN segmentation (expanded) rows: 323s startRow endRow 323s 1 1 7599 323s 2 7600 10267 323s TCN and DH segmentation rows: 323s startRow endRow 323s 1 1 7599 323s 2 7600 10267 323s 3 10268 14658 323s startRow endRow 323s 1 10 7594 323s 2 7614 10263 323s startRow endRow 323s 1 1 7599 323s 2 7600 10267 323s Total CN segmentation table (expanded): 323s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 323s 2 3 143926517 185449813 2668 2.0704 775 775 323s (TCN,DH) segmentation for one total CN segment: 323s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 323s 2 2 1 3 143926517 185449813 2668 2.0704 775 323s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 323s 2 775 143926517 185449813 775 0.097 323s Total CN segment #2 ([1.43927e+08,1.8545e+08]) of 3...done 323s Total CN segment #3 ([1.8545e+08,2.47137e+08]) of 3... 323s Number of TCN loci in segment: 4391 323s Locus data for TCN segment: 323s 'data.frame': 4391 obs. of 9 variables: 323s $ chromosome: int 3 3 3 3 3 3 3 3 3 3 ... 323s $ x : num 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 323s $ CT : num 2.93 2.15 2.82 2.93 2.46 ... 323s $ betaT : num -0.169 0.609 1.028 0.525 0.968 ... 323s $ betaTN : num -0.169 0.609 1.028 0.525 0.968 ... 323s $ betaN : num 0.25 0.38 0.919 0.34 0.783 ... 323s $ muN : num 0 0.5 1 0.5 1 1 0 1 0 1 ... 323s $ index : int 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 323s $ rho : num NA 0.2186 NA 0.0503 NA ... 323s Number of loci: 4391 323s Number of SNPs: 1314 (29.92%) 323s Number of heterozygous SNPs: 1314 (100.00%) 323s Chromosome: 3 323s Segmenting DH signals... 323s Segmenting by CBS... 323s Chromosome: 3 323s Random seed temporarily set (seed=c(10407, -1371615447, -889757879, 1692656974, -1723952224, 1378814990, 1816467252), kind="L'Ecuyer-CMRG") 323s Segmenting by CBS...done 323s List of 4 323s $ data :'data.frame': 4391 obs. of 4 variables: 323s ..$ chromosome: int [1:4391] 3 3 3 3 3 3 3 3 3 3 ... 323s ..$ x : num [1:4391] 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 323s ..$ y : num [1:4391] NA 0.2186 NA 0.0503 NA ... 323s ..$ index : int [1:4391] 1 2 3 4 5 6 7 8 9 10 ... 323s $ output :'data.frame': 1 obs. of 6 variables: 323s ..$ sampleName: chr NA 323s ..$ chromosome: int 3 323s ..$ start : num 1.85e+08 323s ..$ end : num 2.47e+08 323s ..$ nbrOfLoci : int 1314 323s ..$ mean : num 0.23 323s $ segRows:'data.frame': 1 obs. of 2 variables: 323s ..$ startRow: int 2 323s ..$ endRow : int 4388 323s $ params :List of 5 323s ..$ alpha : num 0.001 323s ..$ undo : num 0 323s ..$ joinSegments : logi TRUE 323s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 323s .. ..$ chromosome: int 3 323s .. ..$ start : num 1.85e+08 323s .. ..$ end : num 2.47e+08 323s ..$ seed : int [1:7] 10407 -1371615447 -889757879 1692656974 -1723952224 1378814990 1816467252 323s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 323s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.018 0 0.018 0 0 323s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 323s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 323s - attr(*, "randomSeed")= int [1:7] 10407 -1371615447 -889757879 1692656974 -1723952224 1378814990 1816467252 323s DH segmentation (locally-indexed) rows: 323s startRow endRow 323s 1 2 4388 323s int [1:4391] 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 323s DH segmentation rows: 323s startRow endRow 323s 1 10269 14655 323s Segmenting DH signals...done 323s DH segmentation table: 323s dhStart dhEnd dhNbrOfLoci dhMean 323s 1 185449813 247137334 1314 0.2295 323s startRow endRow 323s 1 10269 14655 323s Rows: 323s [1] 3 323s TCN segmentation rows: 323s startRow endRow 323s 3 10268 14658 323s TCN and DH segmentation rows: 323s startRow endRow 323s 3 10268 14658 323s startRow endRow 323s 1 10269 14655 323s startRow endRow 323s 1 1 7599 323s 2 7600 10267 323s TCN segmentation (expanded) rows: 323s startRow endRow 323s 1 1 7599 323s 2 7600 10267 323s 3 10268 14658 323s TCN and DH segmentation rows: 323s startRow endRow 323s 1 1 7599 323s 2 7600 10267 323s 3 10268 14658 323s startRow endRow 323s 1 10 7594 323s 2 7614 10263 323s 3 10269 14655 323s startRow endRow 323s 1 1 7599 323s 2 7600 10267 323s 3 10268 14658 323s Total CN segmentation table (expanded): 323s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 323s 3 3 185449813 247137334 4391 2.6341 1314 1314 323s (TCN,DH) segmentation for one total CN segment: 323s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 323s 3 3 1 3 185449813 247137334 4391 2.6341 1314 323s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 323s 3 1314 185449813 247137334 1314 0.2295 323s Total CN segment #3 ([1.8545e+08,2.47137e+08]) of 3...done 323s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 323s 1 3 1 1 554484 143926517 7599 1.3859 2120 323s 2 3 2 1 143926517 185449813 2668 2.0704 775 323s 3 3 3 1 185449813 247137334 4391 2.6341 1314 323s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 323s 1 2120 554484 143926517 2120 0.5101 323s 2 775 143926517 185449813 775 0.0970 323s 3 1314 185449813 247137334 1314 0.2295 323s Calculating (C1,C2) per segment... 323s Calculating (C1,C2) per segment...done 323s Number of segments: 3 323s Segmenting paired tumor-normal signals using Paired PSCBS...done 323s Post-segmenting TCNs... 323s Number of segments: 3 323s Number of chromosomes: 1 323s [1] 3 323s Chromosome 1 ('chr03') of 1... 323s Rows: 323s [1] 1 2 3 323s Number of segments: 3 323s TCN segment #1 ('1') of 3... 323s Nothing todo. Only one DH segmentation. Skipping. 323s TCN segment #1 ('1') of 3...done 323s TCN segment #2 ('2') of 3... 323s Nothing todo. Only one DH segmentation. Skipping. 323s TCN segment #2 ('2') of 3...done 323s TCN segment #3 ('3') of 3... 323s Nothing todo. Only one DH segmentation. Skipping. 323s TCN segment #3 ('3') of 3...done 323s Chromosome 1 ('chr03') of 1...done 323s Update (C1,C2) per segment... 323s Update (C1,C2) per segment...done 323s Post-segmenting TCNs...done 323s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 323s 1 3 1 1 554484 143926517 7599 1.3859 2120 323s 2 3 2 1 143926517 185449813 2668 2.0704 775 323s 3 3 3 1 185449813 247137334 4391 2.6341 1314 323s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 323s 1 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 323s 2 775 143926517 185449813 775 0.0970 0.9347856 1.135614 323s 3 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 323s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 323s 1 3 1 1 554484 143926517 7599 1.3859 2120 323s 2 3 2 1 143926517 185449813 2668 2.0704 775 323s 3 3 3 1 185449813 247137334 4391 2.6341 1314 323s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 323s 1 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 323s 2 775 143926517 185449813 775 0.0970 0.9347856 1.135614 323s 3 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 323s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 323s 1 3 1 1 554484 143926517 7599 1.3859 2120 323s 2 3 2 1 143926517 185449813 2668 2.0704 775 323s 3 3 3 1 185449813 247137334 4391 2.6341 1314 323s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 323s 1 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 323s 2 775 143926517 185449813 775 0.0970 0.9347856 1.135614 323s 3 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 323s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 323s 1 3 1 1 554484 143926517 7599 1.3859 2120 323s 2 3 2 1 143926517 185449813 2668 2.0704 775 323s 3 3 3 1 185449813 247137334 4391 2.6341 1314 323s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 323s 1 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 323s 2 775 143926517 185449813 775 0.0970 0.9347856 1.135614 323s 3 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 323s Chromosome #3 ('Chr03') of 3...done 323s Merging (independently) segmented chromosome... 323s List of 5 323s $ data :Classes 'PairedPSCNData' and 'data.frame': 43974 obs. of 8 variables: 323s ..$ chromosome: int [1:43974] 1 1 1 1 1 1 1 1 1 1 ... 323s ..$ x : num [1:43974] 554484 730720 782343 878522 916294 ... 323s ..$ CT : num [1:43974] 1.88 1.8 1.59 1.64 1.53 ... 323s ..$ betaT : num [1:43974] 0.0646 0.1672 0.9284 0.113 0.7209 ... 323s ..$ betaTN : num [1:43974] -0.0515 -0.1172 1.0194 0.031 0.8604 ... 323s ..$ betaN : num [1:43974] 0.116 0.284 0.909 0.082 0.86 ... 323s ..$ muN : num [1:43974] 0 0 1 0 1 1 1 0 1 0.5 ... 323s ..$ rho : num [1:43974] NA NA NA NA NA ... 323s $ output :Classes 'PairedPSCNSegments' and 'data.frame': 11 obs. of 15 variables: 323s ..$ chromosome : int [1:11] 1 1 1 NA 2 2 2 NA 3 3 ... 323s ..$ tcnId : int [1:11] 1 2 3 NA 1 2 3 NA 1 2 ... 323s ..$ dhId : int [1:11] 1 1 1 NA 1 1 1 NA 1 1 ... 323s ..$ tcnStart : num [1:11] 5.54e+05 1.44e+08 1.85e+08 NA 5.54e+05 ... 323s ..$ tcnEnd : num [1:11] 1.44e+08 1.85e+08 2.47e+08 NA 1.44e+08 ... 323s ..$ tcnNbrOfLoci: int [1:11] 7599 2668 4391 NA 7599 2668 4391 NA 7599 2668 ... 323s ..$ tcnMean : num [1:11] 1.39 2.07 2.63 NA 1.39 ... 323s ..$ tcnNbrOfSNPs: int [1:11] 2120 775 1314 NA 2120 775 1314 NA 2120 775 ... 323s ..$ tcnNbrOfHets: int [1:11] 2120 775 1314 NA 2120 775 1314 NA 2120 775 ... 323s ..$ dhStart : num [1:11] 5.54e+05 1.44e+08 1.85e+08 NA 5.54e+05 ... 323s ..$ dhEnd : num [1:11] 1.44e+08 1.85e+08 2.47e+08 NA 1.44e+08 ... 323s ..$ dhNbrOfLoci : int [1:11] 2120 775 1314 NA 2120 775 1314 NA 2120 775 ... 323s ..$ dhMean : num [1:11] 0.51 0.097 0.23 NA 0.51 ... 323s ..$ c1Mean : num [1:11] 0.339 0.935 1.015 NA 0.339 ... 323s ..$ c2Mean : num [1:11] 1.05 1.14 1.62 NA 1.05 ... 323s $ tcnSegRows:'data.frame': 11 obs. of 2 variables: 323s ..$ startRow: int [1:11] 1 7600 10268 NA 14659 22258 24926 NA 29317 36916 ... 323s ..$ endRow : int [1:11] 7599 10267 14658 NA 22257 24925 29316 NA 36915 39583 ... 323s $ dhSegRows :'data.frame': 11 obs. of 2 variables: 323s ..$ startRow: int [1:11] 10 7614 10269 NA 14668 22272 24927 NA 29326 36930 ... 323s ..$ endRow : int [1:11] 7594 10263 14655 NA 22252 24921 29313 NA 36910 39579 ... 323s $ params :List of 7 323s ..$ alphaTCN : num 0.009 323s ..$ alphaDH : num 0.001 323s ..$ flavor : chr "tcn&dh" 323s ..$ tbn : logi FALSE 323s ..$ joinSegments : logi TRUE 323s ..$ knownSegments:'data.frame': 0 obs. of 3 variables: 323s .. ..$ chromosome: int(0) 323s .. ..$ start : int(0) 323s .. ..$ end : int(0) 323s ..$ seed : int [1:7] 10407 1066287653 -51199871 161854402 -1995183193 1503453565 -747102133 323s - attr(*, "class")= chr [1:3] "PairedPSCBS" "PSCBS" "AbstractCBS" 323s Merging (independently) segmented chromosome...done 323s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 323s 1 1 1 1 554484 143926517 7599 1.3859 2120 323s 2 1 2 1 143926517 185449813 2668 2.0704 775 323s 3 1 3 1 185449813 247137334 4391 2.6341 1314 323s 4 NA NA NA NA NA NA NA NA 323s 5 2 1 1 554484 143926517 7599 1.3859 2120 323s 6 2 2 1 143926517 185449813 2668 2.0704 775 323s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 323s 1 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 323s 2 775 143926517 185449813 775 0.0970 0.9347856 1.135614 323s 3 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 323s 4 NA NA NA NA NA NA NA 323s 5 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 323s 6 775 143926517 185449813 775 0.0970 0.9347856 1.135614 323s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 323s 6 2 2 1 143926517 185449813 2668 2.0704 775 323s 7 2 3 1 185449813 247137334 4391 2.6341 1314 323s 8 NA NA NA NA NA NA NA NA 323s 9 3 1 1 554484 143926517 7599 1.3859 2120 323s 10 3 2 1 143926517 185449813 2668 2.0704 775 323s 11 3 3 1 185449813 247137334 4391 2.6341 1314 323s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 323s 6 775 143926517 185449813 775 0.0970 0.9347856 1.135614 323s 7 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 323s 8 NA NA NA NA NA NA NA 323s 9 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 323s 10 775 143926517 185449813 775 0.0970 0.9347856 1.135614 323s 11 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 323s Segmenting multiple chromosomes...done 323s Segmenting paired tumor-normal signals using Paired PSCBS...done 323s - segmentByPairedPSCBS() using 'multisession' futures ... 323s Segmenting paired tumor-normal signals using Paired PSCBS... 323s Calling genotypes from normal allele B fractions... 323s num [1:44010] 0.8274 0.5072 0.1671 0.1609 0.0421 ... 323s Called genotypes: 323s num [1:44010] 1 0.5 0 0 0 0 1 0 1 0.5 ... 323s - attr(*, "modelFit")=List of 1 323s ..$ :List of 7 323s .. ..$ flavor : chr "density" 323s .. ..$ cn : int 2 323s .. ..$ nbrOfGenotypeGroups: int 3 323s .. ..$ tau : num [1:2] 0.312 0.678 323s .. ..$ n : int 43920 323s .. ..$ fit :Classes 'PeaksAndValleys' and 'data.frame': 5 obs. of 3 variables: 323s .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 323s .. .. ..$ x : num [1:5] 0.0999 0.312 0.4986 0.6775 0.8922 323s .. .. ..$ density: num [1:5] 1.622 0.465 1.125 0.496 1.587 323s .. ..$ fitValleys :Classes 'PeaksAndValleys' and 'data.frame': 2 obs. of 3 variables: 323s .. .. ..$ type : chr [1:2] "valley" "valley" 323s .. .. ..$ x : num [1:2] 0.312 0.678 323s .. .. ..$ density: num [1:2] 0.465 0.496 323s ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 323s muN 323s 0 0.5 1 323s 15627 12633 15750 323s Calling genotypes from normal allele B fractions...done 323s Normalizing betaT using betaN (TumorBoost)... 323s Normalized BAFs: 323s num [1:44010] 0.9301 0.1667 0.0685 0.0995 0.0155 ... 323s - attr(*, "modelFit")=List of 5 323s ..$ method : chr "normalizeTumorBoost" 323s ..$ flavor : chr "v4" 323s ..$ delta : num [1:44010] -0.17264 0.00239 0.1671 0.16085 0.04213 ... 323s .. ..- attr(*, "modelFit")=List of 1 323s .. .. ..$ :List of 7 323s .. .. .. ..$ flavor : chr "density" 323s .. .. .. ..$ cn : int 2 323s .. .. .. ..$ nbrOfGenotypeGroups: int 3 323s .. .. .. ..$ tau : num [1:2] 0.312 0.678 323s .. .. .. ..$ n : int 43920 323s .. .. .. ..$ fit :Classes 'PeaksAndValleys' and 'data.frame': 5 obs. of 3 variables: 323s .. .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 323s .. .. .. .. ..$ x : num [1:5] 0.0999 0.312 0.4986 0.6775 0.8922 323s .. .. .. .. ..$ density: num [1:5] 1.622 0.465 1.125 0.496 1.587 323s .. .. .. ..$ fitValleys :Classes 'PeaksAndValleys' and 'data.frame': 2 obs. of 3 variables: 323s .. .. .. .. ..$ type : chr [1:2] "valley" "valley" 323s .. .. .. .. ..$ x : num [1:2] 0.312 0.678 323s .. .. .. .. ..$ density: num [1:2] 0.465 0.496 323s .. .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 323s ..$ preserveScale: logi FALSE 323s ..$ scaleFactor : num NA 323s Normalizing betaT using betaN (TumorBoost)...done 323s Setup up data... 323s 'data.frame': 44010 obs. of 7 variables: 323s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 323s $ x : num 1145994 2941694 3710825 4240737 4276892 ... 323s $ CT : num 1.63 1.4 1.41 1.17 1.16 ... 323s $ betaT : num 0.7574 0.169 0.2357 0.2604 0.0576 ... 323s $ betaTN : num 0.9301 0.1667 0.0685 0.0995 0.0155 ... 323s ..- attr(*, "modelFit")=List of 5 323s .. ..$ method : chr "normalizeTumorBoost" 323s .. ..$ flavor : chr "v4" 323s .. ..$ delta : num [1:44010] -0.17264 0.00239 0.1671 0.16085 0.04213 ... 323s .. .. ..- attr(*, "modelFit")=List of 1 323s .. .. .. ..$ :List of 7 323s .. .. .. .. ..$ flavor : chr "density" 323s .. .. .. .. ..$ cn : int 2 323s .. .. .. .. ..$ nbrOfGenotypeGroups: int 3 323s .. .. .. .. ..$ tau : num [1:2] 0.312 0.678 323s .. .. .. .. ..$ n : int 43920 323s .. .. .. .. ..$ fit :Classes 'PeaksAndValleys' and 'data.frame': 5 obs. of 3 variables: 323s .. .. .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 323s .. .. .. .. .. ..$ x : num [1:5] 0.0999 0.312 0.4986 0.6775 0.8922 323s .. .. .. .. .. ..$ density: num [1:5] 1.622 0.465 1.125 0.496 1.587 323s .. .. .. .. ..$ fitValleys :Classes 'PeaksAndValleys' and 'data.frame': 2 obs. of 3 variables: 323s .. .. .. .. .. ..$ type : chr [1:2] "valley" "valley" 323s .. .. .. .. .. ..$ x : num [1:2] 0.312 0.678 323s .. .. .. .. .. ..$ density: num [1:2] 0.465 0.496 323s .. .. .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 323s .. ..$ preserveScale: logi FALSE 323s .. ..$ scaleFactor : num NA 323s $ betaN : num 0.8274 0.5072 0.1671 0.1609 0.0421 ... 323s $ muN : num 1 0.5 0 0 0 0 1 0 1 0.5 ... 323s ..- attr(*, "modelFit")=List of 1 323s .. ..$ :List of 7 323s .. .. ..$ flavor : chr "density" 323s .. .. ..$ cn : int 2 323s .. .. ..$ nbrOfGenotypeGroups: int 3 323s .. .. ..$ tau : num [1:2] 0.312 0.678 323s .. .. ..$ n : int 43920 323s .. .. ..$ fit :Classes 'PeaksAndValleys' and 'data.frame': 5 obs. of 3 variables: 323s .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 323s .. .. .. ..$ x : num [1:5] 0.0999 0.312 0.4986 0.6775 0.8922 323s .. .. .. ..$ density: num [1:5] 1.622 0.465 1.125 0.496 1.587 323s .. .. ..$ fitValleys :Classes 'PeaksAndValleys' and 'data.frame': 2 obs. of 3 variables: 323s .. .. .. ..$ type : chr [1:2] "valley" "valley" 323s .. .. .. ..$ x : num [1:2] 0.312 0.678 323s .. .. .. ..$ density: num [1:2] 0.465 0.496 323s .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 323s Setup up data...done 323s Dropping loci for which TCNs are missing... 323s Number of loci dropped: 36 323s Dropping loci for which TCNs are missing...done 323s Ordering data along genome... 323s 'data.frame': 43974 obs. of 7 variables: 323s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 323s $ x : num 554484 730720 782343 878522 916294 ... 323s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 323s $ betaT : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 323s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 323s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 323s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 323s Ordering data along genome...done 323s Segmenting multiple chromosomes... 323s Number of chromosomes: 3 323s Random seed temporarily set (seed=c(48879), kind="L'Ecuyer-CMRG") 323s Produced 3 seeds from this stream for future usage 323s Chromosome #1 ('Chr01') of 3... 323s 'data.frame': 14658 obs. of 8 variables: 323s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 323s $ x : num 554484 730720 782343 878522 916294 ... 323s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 323s $ betaT : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 323s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 323s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 323s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 323s $ index : int 1 2 3 4 5 6 7 8 9 10 ... 323s Known segments: 323s [1] chromosome start end 323s <0 rows> (or 0-length row.names) 323s Chromosome #1 ('Chr01') of 3...done 323s Chromosome #2 ('Chr02') of 3... 323s 'data.frame': 14658 obs. of 8 variables: 323s $ chromosome: int 2 2 2 2 2 2 2 2 2 2 ... 323s $ x : num 554484 730720 782343 878522 916294 ... 323s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 323s $ betaT : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 323s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 323s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 323s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 323s $ index : int 14659 14660 14661 14662 14663 14664 14665 14666 14667 14668 ... 323s Known segments: 323s [1] chromosome start end 323s <0 rows> (or 0-length row.names) 323s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 323s Chromosome #2 ('Chr02') of 3...done 323s Chromosome #3 ('Chr03') of 3... 323s 'data.frame': 14658 obs. of 8 variables: 323s $ chromosome: int 3 3 3 3 3 3 3 3 3 3 ... 323s $ x : num 554484 730720 782343 878522 916294 ... 323s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 323s $ betaT : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 323s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 323s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 323s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 323s $ index : int 29317 29318 29319 29320 29321 29322 29323 29324 29325 29326 ... 323s Known segments: 323s [1] chromosome start end 323s <0 rows> (or 0-length row.names) 323s Random seed temporarily set (seed=c(10407, -821273412, -52578226, 1415511586, 721384351, -665928286, 1316562960), kind="L'Ecuyer-CMRG") 323s Segmenting by CBS...done 323s List of 4 323s $ data :'data.frame': 14658 obs. of 4 variables: 323s ..$ chromosome: int [1:14658] 1 1 1 1 1 1 1 1 1 1 ... 323s ..$ x : num [1:14658] 554484 730720 782343 878522 916294 ... 323s ..$ y : num [1:14658] 1.88 1.8 1.59 1.64 1.53 ... 323s ..$ index : int [1:14658] 1 2 3 4 5 6 7 8 9 10 ... 323s $ output :'data.frame': 3 obs. of 6 variables: 323s ..$ sampleName: chr [1:3] NA NA NA 323s ..$ chromosome: int [1:3] 1 1 1 323s ..$ start : num [1:3] 5.54e+05 1.44e+08 1.85e+08 323s ..$ end : num [1:3] 1.44e+08 1.85e+08 2.47e+08 323s ..$ nbrOfLoci : int [1:3] 7599 2668 4391 323s ..$ mean : num [1:3] 1.39 2.07 2.63 323s $ segRows:'data.frame': 3 obs. of 2 variables: 323s ..$ startRow: int [1:3] 1 7600 10268 323s ..$ endRow : int [1:3] 7599 10267 14658 323s $ params :List of 5 323s ..$ alpha : num 0.009 323s ..$ undo : num 0 323s ..$ joinSegments : logi TRUE 323s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 323s .. ..$ chromosome: int 1 323s .. ..$ start : num -Inf 323s .. ..$ end : num Inf 323s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 323s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 323s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.495 0 0.495 0 0 323s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 323s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 323s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 323s Identification of change points by total copy numbers...done 323s Restructure TCN segmentation results... 323s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean 323s 1 1 554484 143926517 7599 1.3859 323s 2 1 143926517 185449813 2668 2.0704 323s 3 1 185449813 247137334 4391 2.6341 323s Number of TCN segments: 3 323s Restructure TCN segmentation results...done 323s Total CN segment #1 ([ 554484,1.43927e+08]) of 3... 323s Number of TCN loci in segment: 7599 323s Locus data for TCN segment: 323s 'data.frame': 7599 obs. of 9 variables: 323s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 323s $ x : num 554484 730720 782343 878522 916294 ... 323s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 323s $ betaT : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 323s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 323s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 323s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 323s $ index : int 1 2 3 4 5 6 7 8 9 10 ... 323s $ rho : num NA NA NA NA NA ... 323s Number of loci: 7599 323s Number of SNPs: 2120 (27.90%) 323s Number of heterozygous SNPs: 2120 (100.00%) 323s Chromosome: 1 323s Segmenting DH signals... 323s Segmenting by CBS... 323s Chromosome: 1 323s Random seed temporarily set (seed=c(10407, -821273412, -52578226, 1415511586, 721384351, -665928286, 1316562960), kind="L'Ecuyer-CMRG") 323s Segmenting by CBS...done 323s List of 4 323s $ data :'data.frame': 7599 obs. of 4 variables: 323s ..$ chromosome: int [1:7599] 1 1 1 1 1 1 1 1 1 1 ... 323s ..$ x : num [1:7599] 554484 730720 782343 878522 916294 ... 323s ..$ y : num [1:7599] NA NA NA NA NA ... 323s ..$ index : int [1:7599] 1 2 3 4 5 6 7 8 9 10 ... 323s $ output :'data.frame': 1 obs. of 6 variables: 323s ..$ sampleName: chr NA 323s ..$ chromosome: int 1 323s ..$ start : num 554484 323s ..$ end : num 1.44e+08 323s ..$ nbrOfLoci : int 2120 323s ..$ mean : num 0.51 323s $ segRows:'data.frame': 1 obs. of 2 variables: 323s ..$ startRow: int 10 323s ..$ endRow : int 7594 323s $ params :List of 5 323s ..$ alpha : num 0.001 323s ..$ undo : num 0 323s ..$ joinSegments : logi TRUE 323s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 323s .. ..$ chromosome: int 1 323s .. ..$ start : num 554484 323s .. ..$ end : num 1.44e+08 323s ..$ seed : int [1:7] 10407 -821273412 -52578226 1415511586 721384351 -665928286 1316562960 323s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 323s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.03 0 0.031 0 0 323s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 323s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 323s - attr(*, "randomSeed")= int [1:7] 10407 -821273412 -52578226 1415511586 721384351 -665928286 1316562960 323s DH segmentation (locally-indexed) rows: 323s startRow endRow 323s 1 10 7594 323s int [1:7599] 1 2 3 4 5 6 7 8 9 10 ... 323s DH segmentation rows: 323s startRow endRow 323s 1 10 7594 323s Segmenting DH signals...done 323s DH segmentation table: 323s dhStart dhEnd dhNbrOfLoci dhMean 323s 1 554484 143926517 2120 0.5101 323s startRow endRow 323s 1 10 7594 323s Rows: 323s [1] 1 323s TCN segmentation rows: 323s startRow endRow 323s 1 1 7599 323s TCN and DH segmentation rows: 323s startRow endRow 323s 1 1 7599 323s startRow endRow 323s 1 10 7594 323s NULL 323s TCN segmentation (expanded) rows: 323s startRow endRow 323s 1 1 7599 323s TCN and DH segmentation rows: 323s startRow endRow 323s 1 1 7599 323s 2 7600 10267 323s 3 10268 14658 323s startRow endRow 323s 1 10 7594 323s startRow endRow 323s 1 1 7599 323s Total CN segmentation table (expanded): 323s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 323s 1 1 554484 143926517 7599 1.3859 2120 2120 323s (TCN,DH) segmentation for one total CN segment: 323s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 323s 1 1 1 1 554484 143926517 7599 1.3859 2120 323s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 323s 1 2120 554484 143926517 2120 0.5101 323s Total CN segment #1 ([ 554484,1.43927e+08]) of 3...done 323s Total CN segment #2 ([1.43927e+08,1.8545e+08]) of 3... 323s Number of TCN loci in segment: 2668 323s Locus data for TCN segment: 323s 'data.frame': 2668 obs. of 9 variables: 323s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 323s $ x : num 1.44e+08 1.44e+08 1.44e+08 1.44e+08 1.44e+08 ... 323s $ CT : num 2.1 2.1 2.09 1.8 2.34 ... 323s $ betaT : num 0.027542 1.030222 1.094093 0.046763 -0.000948 ... 323s $ betaTN : num 0.027542 1.030222 1.094093 0.046763 -0.000948 ... 323s $ betaN : num 0.1624 0.8788 0.8225 0.1201 0.0317 ... 323s $ muN : num 0 1 1 0 0 1 0 0 0 0 ... 323s $ index : int 7600 7601 7602 7603 7604 7605 7606 7607 7608 7609 ... 323s $ rho : num NA NA NA NA NA NA NA NA NA NA ... 323s Number of loci: 2668 323s Number of SNPs: 775 (29.05%) 323s Number of heterozygous SNPs: 775 (100.00%) 323s Chromosome: 1 323s Segmenting DH signals... 323s Segmenting by CBS... 323s Chromosome: 1 323s Random seed temporarily set (seed=c(10407, -821273412, -52578226, 1415511586, 721384351, -665928286, 1316562960), kind="L'Ecuyer-CMRG") 323s Segmenting by CBS...done 323s List of 4 323s $ data :'data.frame': 2668 obs. of 4 variables: 323s ..$ chromosome: int [1:2668] 1 1 1 1 1 1 1 1 1 1 ... 323s ..$ x : num [1:2668] 1.44e+08 1.44e+08 1.44e+08 1.44e+08 1.44e+08 ... 323s ..$ y : num [1:2668] NA NA NA NA NA NA NA NA NA NA ... 323s ..$ index : int [1:2668] 1 2 3 4 5 6 7 8 9 10 ... 323s $ output :'data.frame': 1 obs. of 6 variables: 323s ..$ sampleName: chr NA 323s ..$ chromosome: int 1 323s ..$ start : num 1.44e+08 323s ..$ end : num 1.85e+08 323s ..$ nbrOfLoci : int 775 323s ..$ mean : num 0.097 323s $ segRows:'data.frame': 1 obs. of 2 variables: 323s ..$ startRow: int 15 323s ..$ endRow : int 2664 323s $ params :List of 5 323s ..$ alpha : num 0.001 323s ..$ undo : num 0 323s ..$ joinSegments : logi TRUE 323s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 323s .. ..$ chromosome: int 1 323s .. ..$ start : num 1.44e+08 323s .. ..$ end : num 1.85e+08 323s ..$ seed : int [1:7] 10407 -821273412 -52578226 1415511586 721384351 -665928286 1316562960 323s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 323s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.009 0 0.01 0 0 323s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 323s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 323s - attr(*, "randomSeed")= int [1:7] 10407 -821273412 -52578226 1415511586 721384351 -665928286 1316562960 323s DH segmentation (locally-indexed) rows: 323s startRow endRow 323s 1 15 2664 323s int [1:2668] 7600 7601 7602 7603 7604 7605 7606 7607 7608 7609 ... 323s DH segmentation rows: 323s startRow endRow 323s 1 7614 10263 323s Segmenting DH signals...done 323s DH segmentation table: 323s dhStart dhEnd dhNbrOfLoci dhMean 323s 1 143926517 185449813 775 0.097 323s startRow endRow 323s 1 7614 10263 323s Rows: 323s [1] 2 323s TCN segmentation rows: 323s startRow endRow 323s 2 7600 10267 323s TCN and DH segmentation rows: 323s startRow endRow 323s 2 7600 10267 323s startRow endRow 323s 1 7614 10263 323s startRow endRow 323s 1 1 7599 323s TCN segmentation (expanded) rows: 323s startRow endRow 323s 1 1 7599 323s 2 7600 10267 323s TCN and DH segmentation rows: 323s startRow endRow 323s 1 1 7599 323s 2 7600 10267 323s 3 10268 14658 323s startRow endRow 323s 1 10 7594 323s 2 7614 10263 323s startRow endRow 323s 1 1 7599 323s 2 7600 10267 323s Total CN segmentation table (expanded): 323s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 323s 2 1 143926517 185449813 2668 2.0704 775 775 323s (TCN,DH) segmentation for one total CN segment: 323s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 323s 2 2 1 1 143926517 185449813 2668 2.0704 775 323s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 323s 2 775 143926517 185449813 775 0.097 323s Total CN segment #2 ([1.43927e+08,1.8545e+08]) of 3...done 323s Total CN segment #3 ([1.8545e+08,2.47137e+08]) of 3... 323s Number of TCN loci in segment: 4391 323s Locus data for TCN segment: 323s 'data.frame': 4391 obs. of 9 variables: 323s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 323s $ x : num 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 323s $ CT : num 2.93 2.15 2.82 2.93 2.46 ... 323s $ betaT : num -0.169 0.609 1.028 0.525 0.968 ... 323s $ betaTN : num -0.169 0.609 1.028 0.525 0.968 ... 323s $ betaN : num 0.25 0.38 0.919 0.34 0.783 ... 323s $ muN : num 0 0.5 1 0.5 1 1 0 1 0 1 ... 323s $ index : int 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 323s $ rho : num NA 0.2186 NA 0.0503 NA ... 323s Number of loci: 4391 323s Number of SNPs: 1314 (29.92%) 323s Number of heterozygous SNPs: 1314 (100.00%) 323s Chromosome: 1 323s Segmenting DH signals... 323s Segmenting by CBS... 323s Chromosome: 1 323s Random seed temporarily set (seed=c(10407, -821273412, -52578226, 1415511586, 721384351, -665928286, 1316562960), kind="L'Ecuyer-CMRG") 323s Segmenting by CBS...done 323s List of 4 323s $ data :'data.frame': 4391 obs. of 4 variables: 323s ..$ chromosome: int [1:4391] 1 1 1 1 1 1 1 1 1 1 ... 323s ..$ x : num [1:4391] 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 323s ..$ y : num [1:4391] NA 0.2186 NA 0.0503 NA ... 323s ..$ index : int [1:4391] 1 2 3 4 5 6 7 8 9 10 ... 323s $ output :'data.frame': 1 obs. of 6 variables: 323s ..$ sampleName: chr NA 323s ..$ chromosome: int 1 323s ..$ start : num 1.85e+08 323s ..$ end : num 2.47e+08 323s ..$ nbrOfLoci : int 1314 323s ..$ mean : num 0.23 323s $ segRows:'data.frame': 1 obs. of 2 variables: 323s ..$ startRow: int 2 323s ..$ endRow : int 4388 323s $ params :List of 5 323s ..$ alpha : num 0.001 323s ..$ undo : num 0 323s ..$ joinSegments : logi TRUE 323s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 323s .. ..$ chromosome: int 1 323s .. ..$ start : num 1.85e+08 323s .. ..$ end : num 2.47e+08 323s ..$ seed : int [1:7] 10407 -821273412 -52578226 1415511586 721384351 -665928286 1316562960 323s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 323s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.016 0 0.017 0 0 323s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 323s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 323s - attr(*, "randomSeed")= int [1:7] 10407 -821273412 -52578226 1415511586 721384351 -665928286 1316562960 323s DH segmentation (locally-indexed) rows: 323s startRow endRow 323s 1 2 4388 323s int [1:4391] 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 323s DH segmentation rows: 323s startRow endRow 323s 1 10269 14655 323s Segmenting DH signals...done 323s DH segmentation table: 323s dhStart dhEnd dhNbrOfLoci dhMean 323s 1 185449813 247137334 1314 0.2295 323s startRow endRow 323s 1 10269 14655 323s Rows: 323s [1] 3 323s TCN segmentation rows: 323s startRow endRow 323s 3 10268 14658 323s TCN and DH segmentation rows: 323s startRow endRow 323s 3 10268 14658 323s startRow endRow 323s 1 10269 14655 323s startRow endRow 323s 1 1 7599 323s 2 7600 10267 323s TCN segmentation (expanded) rows: 323s startRow endRow 323s 1 1 7599 323s 2 7600 10267 323s 3 10268 14658 323s TCN and DH segmentation rows: 323s startRow endRow 323s 1 1 7599 323s 2 7600 10267 323s 3 10268 14658 323s startRow endRow 323s 1 10 7594 323s 2 7614 10263 323s 3 10269 14655 323s startRow endRow 323s 1 1 7599 323s 2 7600 10267 323s 3 10268 14658 323s Total CN segmentation table (expanded): 323s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 323s 3 1 185449813 247137334 4391 2.6341 1314 1314 323s (TCN,DH) segmentation for one total CN segment: 323s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 323s 3 3 1 1 185449813 247137334 4391 2.6341 1314 323s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 323s 3 1314 185449813 247137334 1314 0.2295 323s Total CN segment #3 ([1.8545e+08,2.47137e+08]) of 3...done 323s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 323s 1 1 1 1 554484 143926517 7599 1.3859 2120 323s 2 1 2 1 143926517 185449813 2668 2.0704 775 323s 3 1 3 1 185449813 247137334 4391 2.6341 1314 323s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 323s 1 2120 554484 143926517 2120 0.5101 323s 2 775 143926517 185449813 775 0.0970 323s 3 1314 185449813 247137334 1314 0.2295 323s Calculating (C1,C2) per segment... 323s Calculating (C1,C2) per segment...done 323s Number of segments: 3 323s Segmenting paired tumor-normal signals using Paired PSCBS...done 323s Post-segmenting TCNs... 323s Number of segments: 3 323s Number of chromosomes: 1 323s [1] 1 323s Chromosome 1 ('chr01') of 1... 323s Rows: 323s [1] 1 2 3 323s Number of segments: 3 323s TCN segment #1 ('1') of 3... 323s Nothing todo. Only one DH segmentation. Skipping. 323s TCN segment #1 ('1') of 3...done 323s TCN segment #2 ('2') of 3... 323s Nothing todo. Only one DH segmentation. Skipping. 323s TCN segment #2 ('2') of 3...done 323s TCN segment #3 ('3') of 3... 323s Nothing todo. Only one DH segmentation. Skipping. 323s TCN segment #3 ('3') of 3...done 323s Chromosome 1 ('chr01') of 1...done 323s Update (C1,C2) per segment... 323s Update (C1,C2) per segment...done 323s Post-segmenting TCNs...done 323s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 323s 1 1 1 1 554484 143926517 7599 1.3859 2120 323s 2 1 2 1 143926517 185449813 2668 2.0704 775 323s 3 1 3 1 185449813 247137334 4391 2.6341 1314 323s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 323s 1 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 323s 2 775 143926517 185449813 775 0.0970 0.9347856 1.135614 323s 3 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 323s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 323s 1 1 1 1 554484 143926517 7599 1.3859 2120 323s 2 1 2 1 143926517 185449813 2668 2.0704 775 323s 3 1 3 1 185449813 247137334 4391 2.6341 1314 323s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 323s 1 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 323s 2 775 143926517 185449813 775 0.0970 0.9347856 1.135614 323s 3 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 323s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 323s 1 1 1 1 554484 143926517 7599 1.3859 2120 323s 2 1 2 1 143926517 185449813 2668 2.0704 775 323s 3 1 3 1 185449813 247137334 4391 2.6341 1314 323s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 323s 1 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 323s 2 775 143926517 185449813 775 0.0970 0.9347856 1.135614 323s 3 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 323s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 323s 1 1 1 1 554484 143926517 7599 1.3859 2120 323s 2 1 2 1 143926517 185449813 2668 2.0704 775 323s 3 1 3 1 185449813 247137334 4391 2.6341 1314 323s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 323s 1 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 323s 2 775 143926517 185449813 775 0.0970 0.9347856 1.135614 323s 3 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 323s Segmenting by CBS...done 323s List of 4 323s $ data :'data.frame': 14658 obs. of 4 variables: 323s ..$ chromosome: int [1:14658] 2 2 2 2 2 2 2 2 2 2 ... 323s ..$ x : num [1:14658] 554484 730720 782343 878522 916294 ... 323s ..$ y : num [1:14658] 1.88 1.8 1.59 1.64 1.53 ... 323s ..$ index : int [1:14658] 1 2 3 4 5 6 7 8 9 10 ... 323s $ output :'data.frame': 3 obs. of 6 variables: 323s ..$ sampleName: chr [1:3] NA NA NA 323s ..$ chromosome: int [1:3] 2 2 2 323s ..$ start : num [1:3] 5.54e+05 1.44e+08 1.85e+08 323s ..$ end : num [1:3] 1.44e+08 1.85e+08 2.47e+08 323s ..$ nbrOfLoci : int [1:3] 7599 2668 4391 323s ..$ mean : num [1:3] 1.39 2.07 2.63 323s $ segRows:'data.frame': 3 obs. of 2 variables: 323s ..$ startRow: int [1:3] 1 7600 10268 323s ..$ endRow : int [1:3] 7599 10267 14658 323s $ params :List of 5 323s ..$ alpha : num 0.009 323s ..$ undo : num 0 323s ..$ joinSegments : logi TRUE 323s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 323s .. ..$ chromosome: int 2 323s .. ..$ start : num -Inf 323s .. ..$ end : num Inf 323s ..$ seed : int [1:7] 10407 -821273412 -52578226 1415511586 721384351 -665928286 1316562960 323s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 323s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.528 0 0.546 0 0 323s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 323s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 323s - attr(*, "randomSeed")= int [1:7] 10407 -821273412 -52578226 1415511586 721384351 -665928286 1316562960 323s Identification of change points by total copy numbers...done 323s Restructure TCN segmentation results... 323s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean 323s 1 2 554484 143926517 7599 1.3859 323s 2 2 143926517 185449813 2668 2.0704 323s 3 2 185449813 247137334 4391 2.6341 323s Number of TCN segments: 3 323s Restructure TCN segmentation results...done 323s Total CN segment #1 ([ 554484,1.43927e+08]) of 3... 323s Number of TCN loci in segment: 7599 323s Locus data for TCN segment: 323s 'data.frame': 7599 obs. of 9 variables: 323s $ chromosome: int 2 2 2 2 2 2 2 2 2 2 ... 323s $ x : num 554484 730720 782343 878522 916294 ... 323s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 323s $ betaT : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 323s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 323s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 323s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 323s $ index : int 1 2 3 4 5 6 7 8 9 10 ... 323s $ rho : num NA NA NA NA NA ... 323s Number of loci: 7599 323s Number of SNPs: 2120 (27.90%) 323s Number of heterozygous SNPs: 2120 (100.00%) 323s Chromosome: 2 323s Segmenting DH signals... 323s Segmenting by CBS... 323s Chromosome: 2 323s Random seed temporarily set (seed=c(10407, -1924040949, -1632234809, -437763632, -1464377300, 676654412, 2080370711), kind="L'Ecuyer-CMRG") 323s Segmenting by CBS...done 323s List of 4 323s $ data :'data.frame': 7599 obs. of 4 variables: 323s ..$ chromosome: int [1:7599] 2 2 2 2 2 2 2 2 2 2 ... 323s ..$ x : num [1:7599] 554484 730720 782343 878522 916294 ... 323s ..$ y : num [1:7599] NA NA NA NA NA ... 323s ..$ index : int [1:7599] 1 2 3 4 5 6 7 8 9 10 ... 323s $ output :'data.frame': 1 obs. of 6 variables: 323s ..$ sampleName: chr NA 323s ..$ chromosome: int 2 323s ..$ start : num 554484 323s ..$ end : num 1.44e+08 323s ..$ nbrOfLoci : int 2120 323s ..$ mean : num 0.51 323s $ segRows:'data.frame': 1 obs. of 2 variables: 323s ..$ startRow: int 10 323s ..$ endRow : int 7594 323s $ params :List of 5 323s ..$ alpha : num 0.001 323s ..$ undo : num 0 323s ..$ joinSegments : logi TRUE 323s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 323s .. ..$ chromosome: int 2 323s .. ..$ start : num 554484 323s .. ..$ end : num 1.44e+08 323s ..$ seed : int [1:7] 10407 -1924040949 -1632234809 -437763632 -1464377300 676654412 2080370711 323s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 323s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.031 0 0.031 0 0 323s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 323s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 323s - attr(*, "randomSeed")= int [1:7] 10407 -1924040949 -1632234809 -437763632 -1464377300 676654412 2080370711 323s DH segmentation (locally-indexed) rows: 323s startRow endRow 323s 1 10 7594 323s int [1:7599] 1 2 3 4 5 6 7 8 9 10 ... 323s DH segmentation rows: 323s startRow endRow 323s 1 10 7594 323s Segmenting DH signals...done 323s DH segmentation table: 323s dhStart dhEnd dhNbrOfLoci dhMean 323s 1 554484 143926517 2120 0.5101 323s startRow endRow 323s 1 10 7594 323s Rows: 323s [1] 1 323s TCN segmentation rows: 323s startRow endRow 323s 1 1 7599 323s TCN and DH segmentation rows: 323s startRow endRow 323s 1 1 7599 323s startRow endRow 323s 1 10 7594 323s NULL 323s TCN segmentation (expanded) rows: 323s startRow endRow 323s 1 1 7599 323s TCN and DH segmentation rows: 323s startRow endRow 323s 1 1 7599 323s 2 7600 10267 323s 3 10268 14658 323s startRow endRow 323s 1 10 7594 323s startRow endRow 323s 1 1 7599 323s Total CN segmentation table (expanded): 323s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 323s 1 2 554484 143926517 7599 1.3859 2120 2120 323s (TCN,DH) segmentation for one total CN segment: 323s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 323s 1 1 1 2 554484 143926517 7599 1.3859 2120 323s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 323s 1 2120 554484 143926517 2120 0.5101 323s Total CN segment #1 ([ 554484,1.43927e+08]) of 3...done 323s Total CN segment #2 ([1.43927e+08,1.8545e+08]) of 3... 323s Number of TCN loci in segment: 2668 323s Locus data for TCN segment: 323s 'data.frame': 2668 obs. of 9 variables: 323s $ chromosome: int 2 2 2 2 2 2 2 2 2 2 ... 323s $ x : num 1.44e+08 1.44e+08 1.44e+08 1.44e+08 1.44e+08 ... 323s $ CT : num 2.1 2.1 2.09 1.8 2.34 ... 323s $ betaT : num 0.027542 1.030222 1.094093 0.046763 -0.000948 ... 323s $ betaTN : num 0.027542 1.030222 1.094093 0.046763 -0.000948 ... 323s $ betaN : num 0.1624 0.8788 0.8225 0.1201 0.0317 ... 323s $ muN : num 0 1 1 0 0 1 0 0 0 0 ... 323s $ index : int 7600 7601 7602 7603 7604 7605 7606 7607 7608 7609 ... 323s $ rho : num NA NA NA NA NA NA NA NA NA NA ... 323s Number of loci: 2668 323s Number of SNPs: 775 (29.05%) 323s Number of heterozygous SNPs: 775 (100.00%) 323s Chromosome: 2 323s Segmenting DH signals... 323s Segmenting by CBS... 323s Chromosome: 2 323s Random seed temporarily set (seed=c(10407, -1924040949, -1632234809, -437763632, -1464377300, 676654412, 2080370711), kind="L'Ecuyer-CMRG") 323s Segmenting by CBS...done 323s List of 4 323s $ data :'data.frame': 2668 obs. of 4 variables: 323s ..$ chromosome: int [1:2668] 2 2 2 2 2 2 2 2 2 2 ... 323s ..$ x : num [1:2668] 1.44e+08 1.44e+08 1.44e+08 1.44e+08 1.44e+08 ... 323s ..$ y : num [1:2668] NA NA NA NA NA NA NA NA NA NA ... 323s ..$ index : int [1:2668] 1 2 3 4 5 6 7 8 9 10 ... 323s $ output :'data.frame': 1 obs. of 6 variables: 323s ..$ sampleName: chr NA 323s ..$ chromosome: int 2 323s ..$ start : num 1.44e+08 323s ..$ end : num 1.85e+08 323s ..$ nbrOfLoci : int 775 323s ..$ mean : num 0.097 323s $ segRows:'data.frame': 1 obs. of 2 variables: 323s ..$ startRow: int 15 323s ..$ endRow : int 2664 323s $ params :List of 5 323s ..$ alpha : num 0.001 323s ..$ undo : num 0 323s ..$ joinSegments : logi TRUE 323s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 323s .. ..$ chromosome: int 2 323s .. ..$ start : num 1.44e+08 323s .. ..$ end : num 1.85e+08 323s ..$ seed : int [1:7] 10407 -1924040949 -1632234809 -437763632 -1464377300 676654412 2080370711 323s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 323s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.01 0 0.01 0 0 323s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 323s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 323s - attr(*, "randomSeed")= int [1:7] 10407 -1924040949 -1632234809 -437763632 -1464377300 676654412 2080370711 323s DH segmentation (locally-indexed) rows: 323s startRow endRow 323s 1 15 2664 323s int [1:2668] 7600 7601 7602 7603 7604 7605 7606 7607 7608 7609 ... 323s DH segmentation rows: 323s startRow endRow 323s 1 7614 10263 323s Segmenting DH signals...done 323s DH segmentation table: 323s dhStart dhEnd dhNbrOfLoci dhMean 323s 1 143926517 185449813 775 0.097 323s startRow endRow 323s 1 7614 10263 323s Rows: 323s [1] 2 323s TCN segmentation rows: 323s startRow endRow 323s 2 7600 10267 323s TCN and DH segmentation rows: 323s startRow endRow 323s 2 7600 10267 323s startRow endRow 323s 1 7614 10263 323s startRow endRow 323s 1 1 7599 323s TCN segmentation (expanded) rows: 323s startRow endRow 323s 1 1 7599 323s 2 7600 10267 323s TCN and DH segmentation rows: 323s startRow endRow 323s 1 1 7599 323s 2 7600 10267 323s 3 10268 14658 323s startRow endRow 323s 1 10 7594 323s 2 7614 10263 323s startRow endRow 323s 1 1 7599 323s 2 7600 10267 323s Total CN segmentation table (expanded): 323s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 323s 2 2 143926517 185449813 2668 2.0704 775 775 323s (TCN,DH) segmentation for one total CN segment: 323s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 323s 2 2 1 2 143926517 185449813 2668 2.0704 775 323s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 323s 2 775 143926517 185449813 775 0.097 323s Total CN segment #2 ([1.43927e+08,1.8545e+08]) of 3...done 323s Total CN segment #3 ([1.8545e+08,2.47137e+08]) of 3... 323s Number of TCN loci in segment: 4391 323s Locus data for TCN segment: 323s 'data.frame': 4391 obs. of 9 variables: 323s $ chromosome: int 2 2 2 2 2 2 2 2 2 2 ... 323s $ x : num 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 323s $ CT : num 2.93 2.15 2.82 2.93 2.46 ... 323s $ betaT : num -0.169 0.609 1.028 0.525 0.968 ... 323s $ betaTN : num -0.169 0.609 1.028 0.525 0.968 ... 323s $ betaN : num 0.25 0.38 0.919 0.34 0.783 ... 323s $ muN : num 0 0.5 1 0.5 1 1 0 1 0 1 ... 323s $ index : int 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 323s $ rho : num NA 0.2186 NA 0.0503 NA ... 323s Number of loci: 4391 323s Number of SNPs: 1314 (29.92%) 323s Number of heterozygous SNPs: 1314 (100.00%) 323s Chromosome: 2 323s Segmenting DH signals... 323s Segmenting by CBS... 323s Chromosome: 2 323s Random seed temporarily set (seed=c(10407, -1924040949, -1632234809, -437763632, -1464377300, 676654412, 2080370711), kind="L'Ecuyer-CMRG") 323s Segmenting by CBS...done 323s List of 4 323s $ data :'data.frame': 4391 obs. of 4 variables: 323s ..$ chromosome: int [1:4391] 2 2 2 2 2 2 2 2 2 2 ... 323s ..$ x : num [1:4391] 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 323s ..$ y : num [1:4391] NA 0.2186 NA 0.0503 NA ... 323s ..$ index : int [1:4391] 1 2 3 4 5 6 7 8 9 10 ... 323s $ output :'data.frame': 1 obs. of 6 variables: 323s ..$ sampleName: chr NA 323s ..$ chromosome: int 2 323s ..$ start : num 1.85e+08 323s ..$ end : num 2.47e+08 323s ..$ nbrOfLoci : int 1314 323s ..$ mean : num 0.23 323s $ segRows:'data.frame': 1 obs. of 2 variables: 323s ..$ startRow: int 2 323s ..$ endRow : int 4388 323s $ params :List of 5 323s ..$ alpha : num 0.001 323s ..$ undo : num 0 323s ..$ joinSegments : logi TRUE 323s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 323s .. ..$ chromosome: int 2 323s .. ..$ start : num 1.85e+08 323s .. ..$ end : num 2.47e+08 323s ..$ seed : int [1:7] 10407 -1924040949 -1632234809 -437763632 -1464377300 676654412 2080370711 323s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 323s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.017 0 0.017 0 0 323s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 323s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 323s - attr(*, "randomSeed")= int [1:7] 10407 -1924040949 -1632234809 -437763632 -1464377300 676654412 2080370711 323s DH segmentation (locally-indexed) rows: 323s startRow endRow 323s 1 2 4388 323s int [1:4391] 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 323s DH segmentation rows: 323s startRow endRow 323s 1 10269 14655 323s Segmenting DH signals...done 323s DH segmentation table: 323s dhStart dhEnd dhNbrOfLoci dhMean 323s 1 185449813 247137334 1314 0.2295 323s startRow endRow 323s 1 10269 14655 323s Rows: 323s [1] 3 323s TCN segmentation rows: 323s startRow endRow 323s 3 10268 14658 323s TCN and DH segmentation rows: 323s startRow endRow 323s 3 10268 14658 323s startRow endRow 323s 1 10269 14655 323s startRow endRow 323s 1 1 7599 323s 2 7600 10267 323s TCN segmentation (expanded) rows: 323s startRow endRow 323s 1 1 7599 323s 2 7600 10267 323s 3 10268 14658 323s TCN and DH segmentation rows: 323s startRow endRow 323s 1 1 7599 323s 2 7600 10267 323s 3 10268 14658 323s startRow endRow 323s 1 10 7594 323s 2 7614 10263 323s 3 10269 14655 323s startRow endRow 323s 1 1 7599 323s 2 7600 10267 323s 3 10268 14658 323s Total CN segmentation table (expanded): 323s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 323s 3 2 185449813 247137334 4391 2.6341 1314 1314 323s (TCN,DH) segmentation for one total CN segment: 323s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 323s 3 3 1 2 185449813 247137334 4391 2.6341 1314 323s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 323s 3 1314 185449813 247137334 1314 0.2295 323s Total CN segment #3 ([1.8545e+08,2.47137e+08]) of 3...done 323s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 323s 1 2 1 1 554484 143926517 7599 1.3859 2120 323s 2 2 2 1 143926517 185449813 2668 2.0704 775 323s 3 2 3 1 185449813 247137334 4391 2.6341 1314 323s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 323s 1 2120 554484 143926517 2120 0.5101 323s 2 775 143926517 185449813 775 0.0970 323s 3 1314 185449813 247137334 1314 0.2295 323s Calculating (C1,C2) per segment... 323s Calculating (C1,C2) per segment...done 323s Number of segments: 3 323s Segmenting paired tumor-normal signals using Paired PSCBS...done 323s Post-segmenting TCNs... 323s Number of segments: 3 323s Number of chromosomes: 1 323s [1] 2 323s Chromosome 1 ('chr02') of 1... 323s Rows: 323s [1] 1 2 3 323s Number of segments: 3 323s TCN segment #1 ('1') of 3... 323s Nothing todo. Only one DH segmentation. Skipping. 323s TCN segment #1 ('1') of 3...done 323s TCN segment #2 ('2') of 3... 323s Nothing todo. Only one DH segmentation. Skipping. 323s TCN segment #2 ('2') of 3...done 323s Chromosome #3 ('Chr03') of 3...done 323s Merging (independently) segmented chromosome... 323s TCN segment #3 ('3') of 3... 323s Nothing todo. Only one DH segmentation. Skipping. 323s TCN segment #3 ('3') of 3...done 323s Chromosome 1 ('chr02') of 1...done 323s Update (C1,C2) per segment... 323s Update (C1,C2) per segment...done 323s Post-segmenting TCNs...done 323s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 323s 1 2 1 1 554484 143926517 7599 1.3859 2120 323s 2 2 2 1 143926517 185449813 2668 2.0704 775 323s 3 2 3 1 185449813 247137334 4391 2.6341 1314 323s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 323s 1 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 323s 2 775 143926517 185449813 775 0.0970 0.9347856 1.135614 323s 3 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 323s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 323s 1 2 1 1 554484 143926517 7599 1.3859 2120 323s 2 2 2 1 143926517 185449813 2668 2.0704 775 323s 3 2 3 1 185449813 247137334 4391 2.6341 1314 323s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 323s 1 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 323s 2 775 143926517 185449813 775 0.0970 0.9347856 1.135614 323s 3 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 323s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 323s 1 2 1 1 554484 143926517 7599 1.3859 2120 323s 2 2 2 1 143926517 185449813 2668 2.0704 775 323s 3 2 3 1 185449813 247137334 4391 2.6341 1314 323s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 323s 1 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 323s 2 775 143926517 185449813 775 0.0970 0.9347856 1.135614 323s 3 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 323s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 323s 1 2 1 1 554484 143926517 7599 1.3859 2120 323s 2 2 2 1 143926517 185449813 2668 2.0704 775 323s 3 2 3 1 185449813 247137334 4391 2.6341 1314 323s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 323s 1 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 323s 2 775 143926517 185449813 775 0.0970 0.9347856 1.135614 323s 3 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 323s Segmenting paired tumor-normal signals using Paired PSCBS... 323s Setup up data... 323s 'data.frame': 14658 obs. of 7 variables: 323s $ chromosome: int 3 3 3 3 3 3 3 3 3 3 ... 323s $ x : num 554484 730720 782343 878522 916294 ... 323s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 323s $ betaT : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 323s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 323s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 323s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 323s Setup up data...done 323s Ordering data along genome... 323s 'data.frame': 14658 obs. of 7 variables: 323s $ chromosome: int 3 3 3 3 3 3 3 3 3 3 ... 323s $ x : num 554484 730720 782343 878522 916294 ... 323s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 323s $ betaT : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 323s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 323s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 323s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 323s Ordering data along genome...done 323s Keeping only current chromosome for 'knownSegments'... 323s Chromosome: 3 323s Known segments for this chromosome: 323s [1] chromosome start end 323s <0 rows> (or 0-length row.names) 323s Keeping only current chromosome for 'knownSegments'...done 323s alphaTCN: 0.009 323s alphaDH: 0.001 323s Number of loci: 14658 323s Calculating DHs... 323s Number of SNPs: 14658 323s Number of heterozygous SNPs: 4209 (28.71%) 323s Normalized DHs: 323s num [1:14658] NA NA NA NA NA ... 323s Calculating DHs...done 323s Random seed temporarily set (seed=c(10407, -821273412, -52578226, 1415511586, 721384351, -665928286, 1316562960), kind="L'Ecuyer-CMRG") 323s Produced 2 seeds from this stream for future usage 323s Identification of change points by total copy numbers... 323s Segmenting by CBS... 323s Chromosome: 3 323s Random seed temporarily set (seed=c(10407, -1924040949, -1632234809, -437763632, -1464377300, 676654412, 2080370711), kind="L'Ecuyer-CMRG") 323s Segmenting by CBS...done 323s List of 4 323s $ data :'data.frame': 14658 obs. of 4 variables: 323s ..$ chromosome: int [1:14658] 3 3 3 3 3 3 3 3 3 3 ... 323s ..$ x : num [1:14658] 554484 730720 782343 878522 916294 ... 323s ..$ y : num [1:14658] 1.88 1.8 1.59 1.64 1.53 ... 323s ..$ index : int [1:14658] 1 2 3 4 5 6 7 8 9 10 ... 323s $ output :'data.frame': 3 obs. of 6 variables: 323s ..$ sampleName: chr [1:3] NA NA NA 323s ..$ chromosome: int [1:3] 3 3 3 323s ..$ start : num [1:3] 5.54e+05 1.44e+08 1.85e+08 323s ..$ end : num [1:3] 1.44e+08 1.85e+08 2.47e+08 323s ..$ nbrOfLoci : int [1:3] 7599 2668 4391 323s ..$ mean : num [1:3] 1.39 2.07 2.63 323s $ segRows:'data.frame': 3 obs. of 2 variables: 323s ..$ startRow: int [1:3] 1 7600 10268 323s ..$ endRow : int [1:3] 7599 10267 14658 323s $ params :List of 5 323s ..$ alpha : num 0.009 323s ..$ undo : num 0 323s ..$ joinSegments : logi TRUE 323s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 323s .. ..$ chromosome: int 3 323s .. ..$ start : num -Inf 323s .. ..$ end : num Inf 323s ..$ seed : int [1:7] 10407 -1924040949 -1632234809 -437763632 -1464377300 676654412 2080370711 323s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 323s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.501 0 0.512 0 0 323s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 323s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 323s - attr(*, "randomSeed")= int [1:7] 10407 -1924040949 -1632234809 -437763632 -1464377300 676654412 2080370711 323s Identification of change points by total copy numbers...done 323s Restructure TCN segmentation results... 323s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean 323s 1 3 554484 143926517 7599 1.3859 323s 2 3 143926517 185449813 2668 2.0704 323s 3 3 185449813 247137334 4391 2.6341 323s Number of TCN segments: 3 323s Restructure TCN segmentation results...done 323s Total CN segment #1 ([ 554484,1.43927e+08]) of 3... 323s Number of TCN loci in segment: 7599 323s Locus data for TCN segment: 323s 'data.frame': 7599 obs. of 9 variables: 323s $ chromosome: int 3 3 3 3 3 3 3 3 3 3 ... 323s $ x : num 554484 730720 782343 878522 916294 ... 323s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 323s $ betaT : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 323s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 323s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 323s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 323s $ index : int 1 2 3 4 5 6 7 8 9 10 ... 323s $ rho : num NA NA NA NA NA ... 323s Number of loci: 7599 323s Number of SNPs: 2120 (27.90%) 323s Number of heterozygous SNPs: 2120 (100.00%) 323s Chromosome: 3 323s Segmenting DH signals... 323s Segmenting by CBS... 323s Chromosome: 3 323s Random seed temporarily set (seed=c(10407, -1371615447, -889757879, 1692656974, -1723952224, 1378814990, 1816467252), kind="L'Ecuyer-CMRG") 323s Segmenting by CBS...done 323s List of 4 323s $ data :'data.frame': 7599 obs. of 4 variables: 323s ..$ chromosome: int [1:7599] 3 3 3 3 3 3 3 3 3 3 ... 323s ..$ x : num [1:7599] 554484 730720 782343 878522 916294 ... 323s ..$ y : num [1:7599] NA NA NA NA NA ... 323s ..$ index : int [1:7599] 1 2 3 4 5 6 7 8 9 10 ... 323s $ output :'data.frame': 1 obs. of 6 variables: 323s ..$ sampleName: chr NA 323s ..$ chromosome: int 3 323s ..$ start : num 554484 323s ..$ end : num 1.44e+08 323s ..$ nbrOfLoci : int 2120 323s ..$ mean : num 0.51 323s $ segRows:'data.frame': 1 obs. of 2 variables: 323s ..$ startRow: int 10 323s ..$ endRow : int 7594 323s $ params :List of 5 323s ..$ alpha : num 0.001 323s ..$ undo : num 0 323s ..$ joinSegments : logi TRUE 323s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 323s .. ..$ chromosome: int 3 323s .. ..$ start : num 554484 323s .. ..$ end : num 1.44e+08 323s ..$ seed : int [1:7] 10407 -1371615447 -889757879 1692656974 -1723952224 1378814990 1816467252 323s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 323s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.031 0 0.031 0 0 323s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 323s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 323s - attr(*, "randomSeed")= int [1:7] 10407 -1371615447 -889757879 1692656974 -1723952224 1378814990 1816467252 323s DH segmentation (locally-indexed) rows: 323s startRow endRow 323s 1 10 7594 323s int [1:7599] 1 2 3 4 5 6 7 8 9 10 ... 323s DH segmentation rows: 323s startRow endRow 323s 1 10 7594 323s Segmenting DH signals...done 323s DH segmentation table: 323s dhStart dhEnd dhNbrOfLoci dhMean 323s 1 554484 143926517 2120 0.5101 323s startRow endRow 323s 1 10 7594 323s Rows: 323s [1] 1 323s TCN segmentation rows: 323s startRow endRow 323s 1 1 7599 323s TCN and DH segmentation rows: 323s startRow endRow 323s 1 1 7599 323s startRow endRow 323s 1 10 7594 323s NULL 323s TCN segmentation (expanded) rows: 323s startRow endRow 323s 1 1 7599 323s TCN and DH segmentation rows: 323s startRow endRow 323s 1 1 7599 323s 2 7600 10267 323s 3 10268 14658 323s startRow endRow 323s 1 10 7594 323s startRow endRow 323s 1 1 7599 323s Total CN segmentation table (expanded): 323s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 323s 1 3 554484 143926517 7599 1.3859 2120 2120 323s (TCN,DH) segmentation for one total CN segment: 323s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 323s 1 1 1 3 554484 143926517 7599 1.3859 2120 323s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 323s 1 2120 554484 143926517 2120 0.5101 323s Total CN segment #1 ([ 554484,1.43927e+08]) of 3...done 323s Total CN segment #2 ([1.43927e+08,1.8545e+08]) of 3... 323s Number of TCN loci in segment: 2668 323s Locus data for TCN segment: 323s 'data.frame': 2668 obs. of 9 variables: 323s $ chromosome: int 3 3 3 3 3 3 3 3 3 3 ... 323s $ x : num 1.44e+08 1.44e+08 1.44e+08 1.44e+08 1.44e+08 ... 323s $ CT : num 2.1 2.1 2.09 1.8 2.34 ... 323s $ betaT : num 0.027542 1.030222 1.094093 0.046763 -0.000948 ... 323s $ betaTN : num 0.027542 1.030222 1.094093 0.046763 -0.000948 ... 323s $ betaN : num 0.1624 0.8788 0.8225 0.1201 0.0317 ... 323s $ muN : num 0 1 1 0 0 1 0 0 0 0 ... 323s $ index : int 7600 7601 7602 7603 7604 7605 7606 7607 7608 7609 ... 323s $ rho : num NA NA NA NA NA NA NA NA NA NA ... 323s Number of loci: 2668 323s Number of SNPs: 775 (29.05%) 323s Number of heterozygous SNPs: 775 (100.00%) 323s Chromosome: 3 323s Segmenting DH signals... 323s Segmenting by CBS... 323s Chromosome: 3 323s Random seed temporarily set (seed=c(10407, -1371615447, -889757879, 1692656974, -1723952224, 1378814990, 1816467252), kind="L'Ecuyer-CMRG") 323s Segmenting by CBS...done 323s List of 4 323s $ data :'data.frame': 2668 obs. of 4 variables: 323s ..$ chromosome: int [1:2668] 3 3 3 3 3 3 3 3 3 3 ... 323s ..$ x : num [1:2668] 1.44e+08 1.44e+08 1.44e+08 1.44e+08 1.44e+08 ... 323s ..$ y : num [1:2668] NA NA NA NA NA NA NA NA NA NA ... 323s ..$ index : int [1:2668] 1 2 3 4 5 6 7 8 9 10 ... 323s $ output :'data.frame': 1 obs. of 6 variables: 323s ..$ sampleName: chr NA 323s ..$ chromosome: int 3 323s ..$ start : num 1.44e+08 323s ..$ end : num 1.85e+08 323s ..$ nbrOfLoci : int 775 323s ..$ mean : num 0.097 323s $ segRows:'data.frame': 1 obs. of 2 variables: 323s ..$ startRow: int 15 323s ..$ endRow : int 2664 323s $ params :List of 5 323s ..$ alpha : num 0.001 323s ..$ undo : num 0 323s ..$ joinSegments : logi TRUE 323s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 323s .. ..$ chromosome: int 3 323s .. ..$ start : num 1.44e+08 323s .. ..$ end : num 1.85e+08 323s ..$ seed : int [1:7] 10407 -1371615447 -889757879 1692656974 -1723952224 1378814990 1816467252 323s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 323s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.009 0 0.01 0 0 323s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 323s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 323s - attr(*, "randomSeed")= int [1:7] 10407 -1371615447 -889757879 1692656974 -1723952224 1378814990 1816467252 323s DH segmentation (locally-indexed) rows: 323s startRow endRow 323s 1 15 2664 323s int [1:2668] 7600 7601 7602 7603 7604 7605 7606 7607 7608 7609 ... 323s DH segmentation rows: 323s startRow endRow 323s 1 7614 10263 323s Segmenting DH signals...done 323s DH segmentation table: 323s dhStart dhEnd dhNbrOfLoci dhMean 323s 1 143926517 185449813 775 0.097 323s startRow endRow 323s 1 7614 10263 323s Rows: 323s [1] 2 323s TCN segmentation rows: 323s startRow endRow 323s 2 7600 10267 323s TCN and DH segmentation rows: 323s startRow endRow 323s 2 7600 10267 323s startRow endRow 323s 1 7614 10263 323s startRow endRow 323s 1 1 7599 323s TCN segmentation (expanded) rows: 323s startRow endRow 323s 1 1 7599 323s 2 7600 10267 323s TCN and DH segmentation rows: 323s startRow endRow 323s 1 1 7599 323s 2 7600 10267 323s 3 10268 14658 323s startRow endRow 323s 1 10 7594 323s 2 7614 10263 323s startRow endRow 323s 1 1 7599 323s 2 7600 10267 323s Total CN segmentation table (expanded): 323s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 323s 2 3 143926517 185449813 2668 2.0704 775 775 323s (TCN,DH) segmentation for one total CN segment: 323s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 323s 2 2 1 3 143926517 185449813 2668 2.0704 775 323s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 323s 2 775 143926517 185449813 775 0.097 323s Total CN segment #2 ([1.43927e+08,1.8545e+08]) of 3...done 323s Total CN segment #3 ([1.8545e+08,2.47137e+08]) of 3... 323s Number of TCN loci in segment: 4391 323s Locus data for TCN segment: 323s 'data.frame': 4391 obs. of 9 variables: 323s $ chromosome: int 3 3 3 3 3 3 3 3 3 3 ... 323s $ x : num 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 323s $ CT : num 2.93 2.15 2.82 2.93 2.46 ... 323s $ betaT : num -0.169 0.609 1.028 0.525 0.968 ... 323s $ betaTN : num -0.169 0.609 1.028 0.525 0.968 ... 323s $ betaN : num 0.25 0.38 0.919 0.34 0.783 ... 323s $ muN : num 0 0.5 1 0.5 1 1 0 1 0 1 ... 323s $ index : int 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 323s $ rho : num NA 0.2186 NA 0.0503 NA ... 323s Number of loci: 4391 323s Number of SNPs: 1314 (29.92%) 323s Number of heterozygous SNPs: 1314 (100.00%) 323s Chromosome: 3 323s Segmenting DH signals... 323s Segmenting by CBS... 323s Chromosome: 3 323s Random seed temporarily set (seed=c(10407, -1371615447, -889757879, 1692656974, -1723952224, 1378814990, 1816467252), kind="L'Ecuyer-CMRG") 323s Segmenting by CBS...done 323s List of 4 323s $ data :'data.frame': 4391 obs. of 4 variables: 323s ..$ chromosome: int [1:4391] 3 3 3 3 3 3 3 3 3 3 ... 323s ..$ x : num [1:4391] 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 323s ..$ y : num [1:4391] NA 0.2186 NA 0.0503 NA ... 323s ..$ index : int [1:4391] 1 2 3 4 5 6 7 8 9 10 ... 323s $ output :'data.frame': 1 obs. of 6 variables: 323s ..$ sampleName: chr NA 323s ..$ chromosome: int 3 323s ..$ start : num 1.85e+08 323s ..$ end : num 2.47e+08 323s ..$ nbrOfLoci : int 1314 323s ..$ mean : num 0.23 323s $ segRows:'data.frame': 1 obs. of 2 variables: 323s ..$ startRow: int 2 323s ..$ endRow : int 4388 323s $ params :List of 5 323s ..$ alpha : num 0.001 323s ..$ undo : num 0 323s ..$ joinSegments : logi TRUE 323s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 323s .. ..$ chromosome: int 3 323s .. ..$ start : num 1.85e+08 323s .. ..$ end : num 2.47e+08 323s ..$ seed : int [1:7] 10407 -1371615447 -889757879 1692656974 -1723952224 1378814990 1816467252 323s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 323s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.019 0 0.018 0 0 323s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 323s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 323s - attr(*, "randomSeed")= int [1:7] 10407 -1371615447 -889757879 1692656974 -1723952224 1378814990 1816467252 323s DH segmentation (locally-indexed) rows: 323s startRow endRow 323s 1 2 4388 323s int [1:4391] 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 323s DH segmentation rows: 323s startRow endRow 323s 1 10269 14655 323s Segmenting DH signals...done 323s DH segmentation table: 323s dhStart dhEnd dhNbrOfLoci dhMean 323s 1 185449813 247137334 1314 0.2295 323s startRow endRow 323s 1 10269 14655 323s Rows: 323s [1] 3 323s TCN segmentation rows: 323s startRow endRow 323s 3 10268 14658 323s TCN and DH segmentation rows: 323s startRow endRow 323s 3 10268 14658 323s startRow endRow 323s 1 10269 14655 323s startRow endRow 323s 1 1 7599 323s 2 7600 10267 323s TCN segmentation (expanded) rows: 323s startRow endRow 323s 1 1 7599 323s 2 7600 10267 323s 3 10268 14658 323s TCN and DH segmentation rows: 323s startRow endRow 323s 1 1 7599 323s 2 7600 10267 323s 3 10268 14658 323s startRow endRow 323s 1 10 7594 323s 2 7614 10263 323s 3 10269 14655 323s startRow endRow 323s 1 1 7599 323s 2 7600 10267 323s 3 10268 14658 323s Total CN segmentation table (expanded): 323s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 323s 3 3 185449813 247137334 4391 2.6341 1314 1314 323s (TCN,DH) segmentation for one total CN segment: 323s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 323s 3 3 1 3 185449813 247137334 4391 2.6341 1314 323s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 323s 3 1314 185449813 247137334 1314 0.2295 323s Total CN segment #3 ([1.8545e+08,2.47137e+08]) of 3...done 323s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 323s 1 3 1 1 554484 143926517 7599 1.3859 2120 323s 2 3 2 1 143926517 185449813 2668 2.0704 775 323s 3 3 3 1 185449813 247137334 4391 2.6341 1314 323s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 323s 1 2120 554484 143926517 2120 0.5101 323s 2 775 143926517 185449813 775 0.0970 323s 3 1314 185449813 247137334 1314 0.2295 323s Calculating (C1,C2) per segment... 323s Calculating (C1,C2) per segment...done 323s Number of segments: 3 323s Segmenting paired tumor-normal signals using Paired PSCBS...done 323s Post-segmenting TCNs... 323s Number of segments: 3 323s Number of chromosomes: 1 323s [1] 3 323s Chromosome 1 ('chr03') of 1... 323s Rows: 323s [1] 1 2 3 323s Number of segments: 3 323s TCN segment #1 ('1') of 3... 323s Nothing todo. Only one DH segmentation. Skipping. 323s TCN segment #1 ('1') of 3...done 323s TCN segment #2 ('2') of 3... 323s Nothing todo. Only one DH segmentation. Skipping. 323s TCN segment #2 ('2') of 3...done 323s TCN segment #3 ('3') of 3... 323s Nothing todo. Only one DH segmentation. Skipping. 323s TCN segment #3 ('3') of 3...done 323s Chromosome 1 ('chr03') of 1...done 323s Update (C1,C2) per segment... 323s Update (C1,C2) per segment...done 323s Post-segmenting TCNs...done 323s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 323s 1 3 1 1 554484 143926517 7599 1.3859 2120 323s 2 3 2 1 143926517 185449813 2668 2.0704 775 323s 3 3 3 1 185449813 247137334 4391 2.6341 1314 323s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 323s 1 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 323s 2 775 143926517 185449813 775 0.0970 0.9347856 1.135614 323s 3 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 323s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 323s 1 3 1 1 554484 143926517 7599 1.3859 2120 323s 2 3 2 1 143926517 185449813 2668 2.0704 775 323s 3 3 3 1 185449813 247137334 4391 2.6341 1314 323s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 323s 1 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 323s 2 775 143926517 185449813 775 0.0970 0.9347856 1.135614 323s 3 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 323s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 323s 1 3 1 1 554484 143926517 7599 1.3859 2120 323s 2 3 2 1 143926517 185449813 2668 2.0704 775 323s 3 3 3 1 185449813 247137334 4391 2.6341 1314 323s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 323s 1 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 323s 2 775 143926517 185449813 775 0.0970 0.9347856 1.135614 323s 3 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 323s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 323s 1 3 1 1 554484 143926517 7599 1.3859 2120 323s 2 3 2 1 143926517 185449813 2668 2.0704 775 323s 3 3 3 1 185449813 247137334 4391 2.6341 1314 323s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 323s 1 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 323s 2 775 143926517 185449813 775 0.0970 0.9347856 1.135614 323s 3 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 323s List of 5 323s $ data :Classes 'PairedPSCNData' and 'data.frame': 43974 obs. of 8 variables: 323s ..$ chromosome: int [1:43974] 1 1 1 1 1 1 1 1 1 1 ... 323s ..$ x : num [1:43974] 554484 730720 782343 878522 916294 ... 323s ..$ CT : num [1:43974] 1.88 1.8 1.59 1.64 1.53 ... 323s ..$ betaT : num [1:43974] 0.0646 0.1672 0.9284 0.113 0.7209 ... 323s ..$ betaTN : num [1:43974] -0.0515 -0.1172 1.0194 0.031 0.8604 ... 323s ..$ betaN : num [1:43974] 0.116 0.284 0.909 0.082 0.86 ... 323s ..$ muN : num [1:43974] 0 0 1 0 1 1 1 0 1 0.5 ... 323s ..$ rho : num [1:43974] NA NA NA NA NA ... 323s $ output :Classes 'PairedPSCNSegments' and 'data.frame': 11 obs. of 15 variables: 323s ..$ chromosome : int [1:11] 1 1 1 NA 2 2 2 NA 3 3 ... 323s ..$ tcnId : int [1:11] 1 2 3 NA 1 2 3 NA 1 2 ... 323s ..$ dhId : int [1:11] 1 1 1 NA 1 1 1 NA 1 1 ... 323s ..$ tcnStart : num [1:11] 5.54e+05 1.44e+08 1.85e+08 NA 5.54e+05 ... 323s ..$ tcnEnd : num [1:11] 1.44e+08 1.85e+08 2.47e+08 NA 1.44e+08 ... 323s ..$ tcnNbrOfLoci: int [1:11] 7599 2668 4391 NA 7599 2668 4391 NA 7599 2668 ... 323s ..$ tcnMean : num [1:11] 1.39 2.07 2.63 NA 1.39 ... 323s ..$ tcnNbrOfSNPs: int [1:11] 2120 775 1314 NA 2120 775 1314 NA 2120 775 ... 323s ..$ tcnNbrOfHets: int [1:11] 2120 775 1314 NA 2120 775 1314 NA 2120 775 ... 323s ..$ dhStart : num [1:11] 5.54e+05 1.44e+08 1.85e+08 NA 5.54e+05 ... 323s ..$ dhEnd : num [1:11] 1.44e+08 1.85e+08 2.47e+08 NA 1.44e+08 ... 323s ..$ dhNbrOfLoci : int [1:11] 2120 775 1314 NA 2120 775 1314 NA 2120 775 ... 323s ..$ dhMean : num [1:11] 0.51 0.097 0.23 NA 0.51 ... 323s ..$ c1Mean : num [1:11] 0.339 0.935 1.015 NA 0.339 ... 323s ..$ c2Mean : num [1:11] 1.05 1.14 1.62 NA 1.05 ... 323s $ tcnSegRows:'data.frame': 11 obs. of 2 variables: 323s ..$ startRow: int [1:11] 1 7600 10268 NA 14659 22258 24926 NA 29317 36916 ... 323s ..$ endRow : int [1:11] 7599 10267 14658 NA 22257 24925 29316 NA 36915 39583 ... 323s $ dhSegRows :'data.frame': 11 obs. of 2 variables: 323s ..$ startRow: int [1:11] 10 7614 10269 NA 14668 22272 24927 NA 29326 36930 ... 323s ..$ endRow : int [1:11] 7594 10263 14655 NA 22252 24921 29313 NA 36910 39579 ... 323s $ params :List of 7 323s ..$ alphaTCN : num 0.009 323s ..$ alphaDH : num 0.001 323s ..$ flavor : chr "tcn&dh" 323s ..$ tbn : logi FALSE 323s ..$ joinSegments : logi TRUE 323s ..$ knownSegments:'data.frame': 0 obs. of 3 variables: 323s .. ..$ chromosome: int(0) 323s .. ..$ start : int(0) 323s .. ..$ end : int(0) 323s ..$ seed : int [1:7] 10407 1066287653 -51199871 161854402 -1995183193 1503453565 -747102133 323s - attr(*, "class")= chr [1:3] "PairedPSCBS" "PSCBS" "AbstractCBS" 323s Merging (independently) segmented chromosome...done 323s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 323s 1 1 1 1 554484 143926517 7599 1.3859 2120 323s 2 1 2 1 143926517 185449813 2668 2.0704 775 323s 3 1 3 1 185449813 247137334 4391 2.6341 1314 323s 4 NA NA NA NA NA NA NA NA 323s 5 2 1 1 554484 143926517 7599 1.3859 2120 323s 6 2 2 1 143926517 185449813 2668 2.0704 775 323s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 323s 1 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 323s 2 775 143926517 185449813 775 0.0970 0.9347856 1.135614 323s 3 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 323s 4 NA NA NA NA NA NA NA 323s 5 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 323s 6 775 143926517 185449813 775 0.0970 0.9347856 1.135614 323s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 323s 6 2 2 1 143926517 185449813 2668 2.0704 775 323s 7 2 3 1 185449813 247137334 4391 2.6341 1314 323s 8 NA NA NA NA NA NA NA NA 323s 9 3 1 1 554484 143926517 7599 1.3859 2120 323s 10 3 2 1 143926517 185449813 2668 2.0704 775 323s 11 3 3 1 185449813 247137334 4391 2.6341 1314 323s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 323s 6 775 143926517 185449813 775 0.0970 0.9347856 1.135614 323s 7 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 323s 8 NA NA NA NA NA NA NA 323s 9 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 323s 10 775 143926517 185449813 775 0.0970 0.9347856 1.135614 323s 11 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 323s Segmenting multiple chromosomes...done 323s Segmenting paired tumor-normal signals using Paired PSCBS...done 323s > 323s > message("*** segmentByPairedPSCBS() via futures ... DONE") 323s *** segmentByPairedPSCBS() via futures ... DONE 323s > 323s > 323s > message("*** segmentByPairedPSCBS() via futures with known segments ...") 323s *** segmentByPairedPSCBS() via futures with known segments ... 323s > fits <- list() 323s > dataT <- subset(data, chromosome == 1) 323s > gaps <- findLargeGaps(dataT, minLength=2e6) 323s > knownSegments <- gapsToSegments(gaps) 323s > 323s > for (strategy in strategies) { 323s + message(sprintf("- segmentByPairedPSCBS() w/ known segments using '%s' futures ...", strategy)) 323s + plan(strategy) 323s + fit <- segmentByPairedPSCBS(dataT, knownSegments=knownSegments, seed=0xBEEF, verbose=TRUE) 323s + fits[[strategy]] <- fit 323s + equal <- all.equal(fit, fits[[1]]) 323s + if (!equal) { 323s + str(fit) 323s + str(fits[[1]]) 323s + print(equal) 323s + stop(sprintf("segmentByPairedPSCBS() w/ known segments using '%s' futures does not produce the same results as when using '%s' futures", strategy, names(fits)[1])) 323s + } 323s + } 323s - segmentByPairedPSCBS() w/ known segments using 'sequential' futures ... 323s Segmenting paired tumor-normal signals using Paired PSCBS... 323s Calling genotypes from normal allele B fractions... 323s num [1:14670] 0.8274 0.5072 0.1671 0.1609 0.0421 ... 323s Called genotypes: 323s num [1:14670] 1 0.5 0 0 0 0 1 0 1 0.5 ... 323s - attr(*, "modelFit")=List of 1 323s ..$ :List of 7 323s .. ..$ flavor : chr "density" 323s .. ..$ cn : int 2 323s .. ..$ nbrOfGenotypeGroups: int 3 323s .. ..$ tau : num [1:2] 0.315 0.677 323s .. ..$ n : int 14640 323s .. ..$ fit :Classes 'PeaksAndValleys' and 'data.frame': 5 obs. of 3 variables: 323s .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 323s .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 323s .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 323s .. ..$ fitValleys :Classes 'PeaksAndValleys' and 'data.frame': 2 obs. of 3 variables: 323s .. .. ..$ type : chr [1:2] "valley" "valley" 323s .. .. ..$ x : num [1:2] 0.315 0.677 323s .. .. ..$ density: num [1:2] 0.522 0.551 323s ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 323s muN 323s 0 0.5 1 323s 5221 4198 5251 323s Calling genotypes from normal allele B fractions...done 323s Normalizing betaT using betaN (TumorBoost)... 323s Normalized BAFs: 323s num [1:14670] 0.9301 0.1667 0.0685 0.0995 0.0155 ... 323s - attr(*, "modelFit")=List of 5 323s ..$ method : chr "normalizeTumorBoost" 323s ..$ flavor : chr "v4" 323s ..$ delta : num [1:14670] -0.17264 0.00239 0.1671 0.16085 0.04213 ... 323s .. ..- attr(*, "modelFit")=List of 1 323s .. .. ..$ :List of 7 323s .. .. .. ..$ flavor : chr "density" 323s .. .. .. ..$ cn : int 2 323s .. .. .. ..$ nbrOfGenotypeGroups: int 3 323s .. .. .. ..$ tau : num [1:2] 0.315 0.677 323s .. .. .. ..$ n : int 14640 323s .. .. .. ..$ fit :Classes 'PeaksAndValleys' and 'data.frame': 5 obs. of 3 variables: 323s .. .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 323s .. .. .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 323s .. .. .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 323s .. .. .. ..$ fitValleys :Classes 'PeaksAndValleys' and 'data.frame': 2 obs. of 3 variables: 323s .. .. .. .. ..$ type : chr [1:2] "valley" "valley" 323s .. .. .. .. ..$ x : num [1:2] 0.315 0.677 323s .. .. .. .. ..$ density: num [1:2] 0.522 0.551 323s .. .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 323s ..$ preserveScale: logi FALSE 323s ..$ scaleFactor : num NA 323s Normalizing betaT using betaN (TumorBoost)...done 323s Setup up data... 323s 'data.frame': 14670 obs. of 7 variables: 323s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 323s $ x : num 1145994 2941694 3710825 4240737 4276892 ... 323s $ CT : num 1.63 1.4 1.41 1.17 1.16 ... 323s $ betaT : num 0.7574 0.169 0.2357 0.2604 0.0576 ... 323s $ betaTN : num 0.9301 0.1667 0.0685 0.0995 0.0155 ... 323s ..- attr(*, "modelFit")=List of 5 323s .. ..$ method : chr "normalizeTumorBoost" 323s .. ..$ flavor : chr "v4" 323s .. ..$ delta : num [1:14670] -0.17264 0.00239 0.1671 0.16085 0.04213 ... 323s .. .. ..- attr(*, "modelFit")=List of 1 323s .. .. .. ..$ :List of 7 323s .. .. .. .. ..$ flavor : chr "density" 323s .. .. .. .. ..$ cn : int 2 323s .. .. .. .. ..$ nbrOfGenotypeGroups: int 3 323s .. .. .. .. ..$ tau : num [1:2] 0.315 0.677 323s .. .. .. .. ..$ n : int 14640 323s .. .. .. .. ..$ fit :Classes 'PeaksAndValleys' and 'data.frame': 5 obs. of 3 variables: 323s .. .. .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 323s .. .. .. .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 323s .. .. .. .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 323s .. .. .. .. ..$ fitValleys :Classes 'PeaksAndValleys' and 'data.frame': 2 obs. of 3 variables: 323s .. .. .. .. .. ..$ type : chr [1:2] "valley" "valley" 323s .. .. .. .. .. ..$ x : num [1:2] 0.315 0.677 323s .. .. .. .. .. ..$ density: num [1:2] 0.522 0.551 323s .. .. .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 323s .. ..$ preserveScale: logi FALSE 323s .. ..$ scaleFactor : num NA 323s $ betaN : num 0.8274 0.5072 0.1671 0.1609 0.0421 ... 323s $ muN : num 1 0.5 0 0 0 0 1 0 1 0.5 ... 323s ..- attr(*, "modelFit")=List of 1 323s .. ..$ :List of 7 323s .. .. ..$ flavor : chr "density" 323s .. .. ..$ cn : int 2 323s .. .. ..$ nbrOfGenotypeGroups: int 3 323s .. .. ..$ tau : num [1:2] 0.315 0.677 323s .. .. ..$ n : int 14640 323s .. .. ..$ fit :Classes 'PeaksAndValleys' and 'data.frame': 5 obs. of 3 variables: 323s .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 323s .. .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 323s .. .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 323s .. .. ..$ fitValleys :Classes 'PeaksAndValleys' and 'data.frame': 2 obs. of 3 variables: 323s .. .. .. ..$ type : chr [1:2] "valley" "valley" 323s .. .. .. ..$ x : num [1:2] 0.315 0.677 323s .. .. .. ..$ density: num [1:2] 0.522 0.551 323s .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 323s Setup up data...done 323s Dropping loci for which TCNs are missing... 323s Number of loci dropped: 12 323s Dropping loci for which TCNs are missing...done 323s Ordering data along genome... 323s 'data.frame': 14658 obs. of 7 variables: 323s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 323s $ x : num 554484 730720 782343 878522 916294 ... 323s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 323s $ betaT : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 323s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 323s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 323s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 323s Ordering data along genome...done 323s Keeping only current chromosome for 'knownSegments'... 323s Chromosome: 1 323s Known segments for this chromosome: 323s chromosome start end length 323s 1 1 -Inf 120908858 Inf 323s 2 1 120908859 142693887 21785028 323s 3 1 142693888 Inf Inf 323s Keeping only current chromosome for 'knownSegments'...done 323s alphaTCN: 0.009 323s alphaDH: 0.001 323s Number of loci: 14658 323s Calculating DHs... 323s Number of SNPs: 14658 323s Number of heterozygous SNPs: 4196 (28.63%) 323s Normalized DHs: 323s num [1:14658] NA NA NA NA NA ... 323s Calculating DHs...done 323s Random seed temporarily set (seed=c(48879), kind="L'Ecuyer-CMRG") 323s Produced 2 seeds from this stream for future usage 323s Identification of change points by total copy numbers... 323s Segmenting by CBS... 323s Chromosome: 1 323s Random seed temporarily set (seed=c(10407, 1066287653, -51199871, 161854402, -1995183193, 1503453565, -747102133), kind="L'Ecuyer-CMRG") 323s Produced 3 seeds from this stream for future usage 323s Segmenting by CBS...done 323s List of 4 323s $ data :'data.frame': 14658 obs. of 4 variables: 323s ..$ chromosome: int [1:14658] 1 1 1 1 1 1 1 1 1 1 ... 323s ..$ x : num [1:14658] 554484 730720 782343 878522 916294 ... 323s ..$ y : num [1:14658] 1.88 1.8 1.59 1.64 1.53 ... 323s ..$ index : int [1:14658] 1 2 3 4 5 6 7 8 9 10 ... 323s $ output :'data.frame': 4 obs. of 6 variables: 323s ..$ sampleName: chr [1:4] NA NA NA NA 323s ..$ chromosome: int [1:4] 1 1 1 1 323s ..$ start : num [1:4] 5.54e+05 1.21e+08 1.43e+08 1.85e+08 323s ..$ end : num [1:4] 1.21e+08 1.43e+08 1.85e+08 2.47e+08 323s ..$ nbrOfLoci : int [1:4] 7586 0 2681 4391 323s ..$ mean : num [1:4] 1.39 NA 2.07 2.63 323s $ segRows:'data.frame': 4 obs. of 2 variables: 323s ..$ startRow: int [1:4] 1 NA 7587 10268 323s ..$ endRow : int [1:4] 7586 NA 10267 14658 323s $ params :List of 5 323s ..$ alpha : num 0.009 323s ..$ undo : num 0 323s ..$ joinSegments : logi TRUE 323s ..$ knownSegments:'data.frame': 4 obs. of 3 variables: 323s .. ..$ chromosome: int [1:4] 1 1 2 1 323s .. ..$ start : num [1:4] -Inf -Inf -Inf 1.43e+08 323s .. ..$ end : num [1:4] 1.21e+08 Inf Inf Inf 323s ..$ seed : int [1:7] 10407 1066287653 -51199871 161854402 -1995183193 1503453565 -747102133 323s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 323s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.165 0 0.165 0 0 323s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 323s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 323s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 323s Identification of change points by total copy numbers...done 323s Restructure TCN segmentation results... 323s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean 323s 1 1 554484 120908858 7586 1.3853 323s 2 1 120908859 142693887 0 NA 323s 3 1 142693888 185449813 2681 2.0689 323s 4 1 185449813 247137334 4391 2.6341 323s Number of TCN segments: 4 323s Restructure TCN segmentation results...done 323s Total CN segment #1 ([ 554484,1.20909e+08]) of 4... 323s Number of TCN loci in segment: 7586 323s Locus data for TCN segment: 323s 'data.frame': 7586 obs. of 9 variables: 323s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 323s $ x : num 554484 730720 782343 878522 916294 ... 323s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 323s $ betaT : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 323s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 323s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 323s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 323s $ index : int 1 2 3 4 5 6 7 8 9 10 ... 323s $ rho : num NA NA NA NA NA ... 323s Number of loci: 7586 323s Number of SNPs: 2108 (27.79%) 323s Number of heterozygous SNPs: 2108 (100.00%) 323s Chromosome: 1 323s Segmenting DH signals... 323s Segmenting by CBS... 323s Chromosome: 1 323s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 323s Segmenting by CBS...done 323s List of 4 323s $ data :'data.frame': 7586 obs. of 4 variables: 323s ..$ chromosome: int [1:7586] 1 1 1 1 1 1 1 1 1 1 ... 323s ..$ x : num [1:7586] 554484 730720 782343 878522 916294 ... 323s ..$ y : num [1:7586] NA NA NA NA NA ... 323s ..$ index : int [1:7586] 1 2 3 4 5 6 7 8 9 10 ... 323s $ output :'data.frame': 1 obs. of 6 variables: 323s ..$ sampleName: chr NA 323s ..$ chromosome: int 1 323s ..$ start : num 554484 323s ..$ end : num 1.21e+08 323s ..$ nbrOfLoci : int 2108 323s ..$ mean : num 0.512 323s $ segRows:'data.frame': 1 obs. of 2 variables: 323s ..$ startRow: int 10 323s ..$ endRow : int 7574 323s $ params :List of 5 323s ..$ alpha : num 0.001 323s ..$ undo : num 0 323s ..$ joinSegments : logi TRUE 323s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 323s .. ..$ chromosome: int 1 323s .. ..$ start : num 554484 323s .. ..$ end : num 1.21e+08 323s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 323s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 323s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.047 0 0.046 0 0 323s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 323s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 323s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 323s DH segmentation (locally-indexed) rows: 323s startRow endRow 323s 1 10 7574 323s int [1:7586] 1 2 3 4 5 6 7 8 9 10 ... 323s DH segmentation rows: 323s startRow endRow 323s 1 10 7574 323s Segmenting DH signals...done 323s DH segmentation table: 323s dhStart dhEnd dhNbrOfLoci dhMean 323s 1 554484 120908858 2108 0.5116 323s startRow endRow 323s 1 10 7574 323s Rows: 323s [1] 1 323s TCN segmentation rows: 323s startRow endRow 323s 1 1 7586 323s TCN and DH segmentation rows: 323s startRow endRow 323s 1 1 7586 323s startRow endRow 323s 1 10 7574 323s NULL 323s TCN segmentation (expanded) rows: 323s startRow endRow 323s 1 1 7586 323s TCN and DH segmentation rows: 323s startRow endRow 323s 1 1 7586 323s 2 NA NA 323s 3 7587 10267 323s 4 10268 14658 323s startRow endRow 323s 1 10 7574 323s startRow endRow 323s 1 1 7586 323s Total CN segmentation table (expanded): 323s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 323s 1 1 554484 120908858 7586 1.3853 2108 2108 323s (TCN,DH) segmentation for one total CN segment: 323s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 323s 1 1 1 1 554484 120908858 7586 1.3853 2108 323s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 323s 1 2108 554484 120908858 2108 0.5116 323s Total CN segment #1 ([ 554484,1.20909e+08]) of 4...done 323s Total CN segment #2 ([1.20909e+08,1.42694e+08]) of 4... 323s Number of TCN loci in segment: 0 323s Locus data for TCN segment: 323s 'data.frame': 0 obs. of 9 variables: 323s $ chromosome: int 323s $ x : num 323s $ CT : num 323s $ betaT : num 323s $ betaTN : num 323s $ betaN : num 323s $ muN : num 323s $ index : int 323s $ rho : num 323s Number of loci: 0 323s Number of SNPs: 0 (NaN%) 323s Number of heterozygous SNPs: 0 (NaN%) 323s Chromosome: 1 323s Segmenting DH signals... 323s Segmenting by CBS... 323s Chromosome: NA 323s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 323s Segmenting by CBS...done 323s List of 4 323s $ data :'data.frame': 0 obs. of 4 variables: 323s ..$ chromosome: int(0) 323s ..$ x : num(0) 323s ..$ y : num(0) 323s ..$ index : int(0) 323s $ output :'data.frame': 0 obs. of 6 variables: 323s ..$ sampleName: chr(0) 323s ..$ chromosome: num(0) 323s ..$ start : num(0) 323s ..$ end : num(0) 323s ..$ nbrOfLoci : int(0) 323s ..$ mean : num(0) 323s $ segRows:'data.frame': 0 obs. of 2 variables: 323s ..$ startRow: int(0) 323s ..$ endRow : int(0) 323s $ params :List of 5 323s ..$ alpha : num 0.001 323s ..$ undo : num 0 323s ..$ joinSegments : logi TRUE 323s ..$ knownSegments:'data.frame': 0 obs. of 3 variables: 323s .. ..$ chromosome: int(0) 323s .. ..$ start : num(0) 323s .. ..$ end : num(0) 323s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 323s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 323s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.002 0 0.002 0 0 323s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 323s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 323s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 323s DH segmentation (locally-indexed) rows: 323s [1] startRow endRow 323s <0 rows> (or 0-length row.names) 323s int(0) 323s DH segmentation rows: 323s [1] startRow endRow 323s <0 rows> (or 0-length row.names) 323s Segmenting DH signals...done 323s DH segmentation table: 323s dhStart dhEnd dhNbrOfLoci dhMean 323s NA NA NA NA NA 323s startRow endRow 323s NA NA NA 323s Rows: 323s [1] 2 323s TCN segmentation rows: 323s startRow endRow 323s 2 NA NA 323s TCN and DH segmentation rows: 323s startRow endRow 323s 2 NA NA 323s startRow endRow 323s NA NA NA 323s startRow endRow 323s 1 1 7586 323s TCN segmentation (expanded) rows: 323s startRow endRow 323s 1 1 7586 323s 2 NA NA 323s TCN and DH segmentation rows: 323s startRow endRow 323s 1 1 7586 323s 2 NA NA 323s 3 7587 10267 323s 4 10268 14658 323s startRow endRow 323s 1 10 7574 323s 2 NA NA 323s startRow endRow 323s 1 1 7586 323s 2 NA NA 323s Total CN segmentation table (expanded): 323s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 323s 2 1 120908859 142693887 0 NA 0 0 323s (TCN,DH) segmentation for one total CN segment: 323s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 323s 2 2 1 1 120908859 142693887 0 NA 0 323s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 323s 2 0 NA NA NA NA 323s Total CN segment #2 ([1.20909e+08,1.42694e+08]) of 4...done 323s Total CN segment #3 ([1.42694e+08,1.8545e+08]) of 4... 323s Number of TCN loci in segment: 2681 323s Locus data for TCN segment: 323s 'data.frame': 2681 obs. of 9 variables: 323s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 323s $ x : num 1.43e+08 1.43e+08 1.43e+08 1.43e+08 1.44e+08 ... 323s $ CT : num 2.27 1.55 1.47 1.5 1.81 ... 323s $ betaT : num 0.34 0.55 0.048 0.813 0.575 ... 323s $ betaTN : num 0.441 0.629 -0.05 0.958 0.872 ... 323s $ betaN : num 0.3851 0.3933 0.0981 0.8552 0.7028 ... 323s $ muN : num 0.5 0.5 0 1 1 1 1 0.5 1 1 ... 323s $ index : int 7587 7588 7589 7590 7591 7592 7593 7594 7595 7596 ... 323s $ rho : num 0.117 0.258 NA NA NA ... 323s Number of loci: 2681 323s Number of SNPs: 777 (28.98%) 323s Number of heterozygous SNPs: 777 (100.00%) 323s Chromosome: 1 323s Segmenting DH signals... 323s Segmenting by CBS... 323s Chromosome: 1 323s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 323s Segmenting by CBS...done 323s List of 4 323s $ data :'data.frame': 2681 obs. of 4 variables: 323s ..$ chromosome: int [1:2681] 1 1 1 1 1 1 1 1 1 1 ... 323s ..$ x : num [1:2681] 1.43e+08 1.43e+08 1.43e+08 1.43e+08 1.44e+08 ... 323s ..$ y : num [1:2681] 0.117 0.258 NA NA NA ... 323s ..$ index : int [1:2681] 1 2 3 4 5 6 7 8 9 10 ... 323s $ output :'data.frame': 1 obs. of 6 variables: 323s ..$ sampleName: chr NA 323s ..$ chromosome: int 1 323s ..$ start : num 1.43e+08 323s ..$ end : num 1.85e+08 323s ..$ nbrOfLoci : int 777 323s ..$ mean : num 0.0973 323s $ segRows:'data.frame': 1 obs. of 2 variables: 323s ..$ startRow: int 1 323s ..$ endRow : int 2677 323s $ params :List of 5 323s ..$ alpha : num 0.001 323s ..$ undo : num 0 323s ..$ joinSegments : logi TRUE 323s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 323s .. ..$ chromosome: int 1 323s .. ..$ start : num 1.43e+08 323s .. ..$ end : num 1.85e+08 323s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 323s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 323s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.009 0 0.009 0 0 323s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 323s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 323s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 323s DH segmentation (locally-indexed) rows: 323s startRow endRow 323s 1 1 2677 323s int [1:2681] 7587 7588 7589 7590 7591 7592 7593 7594 7595 7596 ... 323s DH segmentation rows: 323s startRow endRow 323s 1 7587 10263 323s Segmenting DH signals...done 323s DH segmentation table: 323s dhStart dhEnd dhNbrOfLoci dhMean 323s 1 142693888 185449813 777 0.0973 323s startRow endRow 323s 1 7587 10263 323s Rows: 323s [1] 3 323s TCN segmentation rows: 323s startRow endRow 323s 3 7587 10267 323s TCN and DH segmentation rows: 323s startRow endRow 323s 3 7587 10267 323s startRow endRow 323s 1 7587 10263 323s startRow endRow 323s 1 1 7586 323s 2 NA NA 323s TCN segmentation (expanded) rows: 323s startRow endRow 323s 1 1 7586 323s 2 NA NA 323s 3 7587 10267 323s TCN and DH segmentation rows: 323s startRow endRow 323s 1 1 7586 323s 2 NA NA 323s 3 7587 10267 323s 4 10268 14658 323s startRow endRow 323s 1 10 7574 323s 2 NA NA 323s 3 7587 10263 323s startRow endRow 323s 1 1 7586 323s 2 NA NA 323s 3 7587 10267 323s Total CN segmentation table (expanded): 323s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 323s 3 1 142693888 185449813 2681 2.0689 777 777 323s (TCN,DH) segmentation for one total CN segment: 323s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 323s 3 3 1 1 142693888 185449813 2681 2.0689 777 323s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 323s 3 777 142693888 185449813 777 0.0973 323s Total CN segment #3 ([1.42694e+08,1.8545e+08]) of 4...done 323s Total CN segment #4 ([1.8545e+08,2.47137e+08]) of 4... 323s Number of TCN loci in segment: 4391 323s Locus data for TCN segment: 323s 'data.frame': 4391 obs. of 9 variables: 323s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 323s $ x : num 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 323s $ CT : num 2.93 2.15 2.82 2.93 2.46 ... 323s $ betaT : num 0.0811 0.5154 0.9473 0.3734 0.7506 ... 323s $ betaTN : num -0.169 0.609 1.028 0.525 0.968 ... 323s $ betaN : num 0.25 0.38 0.919 0.34 0.783 ... 323s $ muN : num 0 0.5 1 0.5 1 1 0 1 0 1 ... 323s $ index : int 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 323s $ rho : num NA 0.2186 NA 0.0503 NA ... 323s Number of loci: 4391 323s Number of SNPs: 1311 (29.86%) 323s Number of heterozygous SNPs: 1311 (100.00%) 323s Chromosome: 1 323s Segmenting DH signals... 323s Segmenting by CBS... 323s Chromosome: 1 323s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 323s Segmenting by CBS...done 323s List of 4 323s $ data :'data.frame': 4391 obs. of 4 variables: 323s ..$ chromosome: int [1:4391] 1 1 1 1 1 1 1 1 1 1 ... 323s ..$ x : num [1:4391] 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 323s ..$ y : num [1:4391] NA 0.2186 NA 0.0503 NA ... 323s ..$ index : int [1:4391] 1 2 3 4 5 6 7 8 9 10 ... 323s $ output :'data.frame': 1 obs. of 6 variables: 323s ..$ sampleName: chr NA 323s ..$ chromosome: int 1 323s ..$ start : num 1.85e+08 323s ..$ end : num 2.47e+08 323s ..$ nbrOfLoci : int 1311 323s ..$ mean : num 0.23 323s $ segRows:'data.frame': 1 obs. of 2 variables: 323s ..$ startRow: int 2 323s ..$ endRow : int 4388 323s $ params :List of 5 323s ..$ alpha : num 0.001 323s ..$ undo : num 0 323s ..$ joinSegments : logi TRUE 323s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 323s .. ..$ chromosome: int 1 323s .. ..$ start : num 1.85e+08 323s .. ..$ end : num 2.47e+08 323s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 323s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 323s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.018 0 0.018 0 0 323s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 323s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 323s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 323s DH segmentation (locally-indexed) rows: 323s startRow endRow 323s 1 2 4388 323s int [1:4391] 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 323s DH segmentation rows: 323s startRow endRow 323s 1 10269 14655 323s Segmenting DH signals...done 323s DH segmentation table: 323s dhStart dhEnd dhNbrOfLoci dhMean 323s 1 185449813 247137334 1311 0.2295 323s startRow endRow 323s 1 10269 14655 323s Rows: 323s [1] 4 323s TCN segmentation rows: 323s startRow endRow 323s 4 10268 14658 323s TCN and DH segmentation rows: 323s startRow endRow 323s 4 10268 14658 323s startRow endRow 323s 1 10269 14655 323s startRow endRow 323s 1 1 7586 323s 2 NA NA 323s 3 7587 10267 323s TCN segmentation (expanded) rows: 323s startRow endRow 323s 1 1 7586 323s 2 NA NA 323s 3 7587 10267 323s 4 10268 14658 323s TCN and DH segmentation rows: 323s startRow endRow 323s 1 1 7586 323s 2 NA NA 323s 3 7587 10267 323s 4 10268 14658 323s startRow endRow 323s 1 10 7574 323s 2 NA NA 323s 3 7587 10263 323s 4 10269 14655 323s startRow endRow 323s 1 1 7586 323s 2 NA NA 323s 3 7587 10267 323s 4 10268 14658 323s Total CN segmentation table (expanded): 323s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 323s 4 1 185449813 247137334 4391 2.6341 1311 1311 323s (TCN,DH) segmentation for one total CN segment: 323s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 323s 4 4 1 1 185449813 247137334 4391 2.6341 1311 323s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 323s 4 1311 185449813 247137334 1311 0.2295 323s Total CN segment #4 ([1.8545e+08,2.47137e+08]) of 4...done 323s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 323s 1 1 1 1 554484 120908858 7586 1.3853 2108 323s 2 1 2 1 120908859 142693887 0 NA 0 323s 3 1 3 1 142693888 185449813 2681 2.0689 777 323s 4 1 4 1 185449813 247137334 4391 2.6341 1311 323s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 323s 1 2108 554484 120908858 2108 0.5116 323s 2 0 NA NA NA NA 323s 3 777 142693888 185449813 777 0.0973 323s 4 1311 185449813 247137334 1311 0.2295 323s Calculating (C1,C2) per segment... 323s Calculating (C1,C2) per segment...done 323s Number of segments: 4 323s Segmenting paired tumor-normal signals using Paired PSCBS...done 323s Post-segmenting TCNs... 323s Number of segments: 4 323s Number of chromosomes: 1 323s [1] 1 323s Chromosome 1 ('chr01') of 1... 323s Rows: 323s [1] 1 2 3 4 323s Number of segments: 4 323s TCN segment #1 ('1') of 4... 323s Nothing todo. Only one DH segmentation. Skipping. 323s TCN segment #1 ('1') of 4...done 323s TCN segment #2 ('2') of 4... 323s Nothing todo. Only one DH segmentation. Skipping. 323s TCN segment #2 ('2') of 4...done 323s TCN segment #3 ('3') of 4... 323s Nothing todo. Only one DH segmentation. Skipping. 323s TCN segment #3 ('3') of 4...done 323s TCN segment #4 ('4') of 4... 323s Nothing todo. Only one DH segmentation. Skipping. 323s TCN segment #4 ('4') of 4...done 323s Chromosome 1 ('chr01') of 1...done 323s Update (C1,C2) per segment... 323s Update (C1,C2) per segment...done 323s Post-segmenting TCNs...done 323s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 323s 1 1 1 1 554484 120908858 7586 1.3853 2108 323s 2 1 2 1 120908859 142693887 0 NA 0 323s 3 1 3 1 142693888 185449813 2681 2.0689 777 323s 4 1 4 1 185449813 247137334 4391 2.6341 1311 323s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 323s 1 2108 554484 120908858 2108 0.5116 0.3382903 1.047010 323s 2 0 NA NA NA NA NA NA 323s 3 777 142693888 185449813 777 0.0973 0.9337980 1.135102 323s 4 1311 185449813 247137334 1311 0.2295 1.0147870 1.619313 323s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 323s 1 1 1 1 554484 120908858 7586 1.3853 2108 323s 2 1 2 1 120908859 142693887 0 NA 0 323s 3 1 3 1 142693888 185449813 2681 2.0689 777 323s 4 1 4 1 185449813 247137334 4391 2.6341 1311 323s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 323s 1 2108 554484 120908858 2108 0.5116 0.3382903 1.047010 323s 2 0 NA NA NA NA NA NA 323s 3 777 142693888 185449813 777 0.0973 0.9337980 1.135102 323s 4 1311 185449813 247137334 1311 0.2295 1.0147870 1.619313 323s - segmentByPairedPSCBS() w/ known segments using 'multisession' futures ... 323s Segmenting paired tumor-normal signals using Paired PSCBS... 323s Calling genotypes from normal allele B fractions... 323s num [1:14670] 0.8274 0.5072 0.1671 0.1609 0.0421 ... 323s Called genotypes: 323s num [1:14670] 1 0.5 0 0 0 0 1 0 1 0.5 ... 323s - attr(*, "modelFit")=List of 1 323s ..$ :List of 7 323s .. ..$ flavor : chr "density" 323s .. ..$ cn : int 2 323s .. ..$ nbrOfGenotypeGroups: int 3 323s .. ..$ tau : num [1:2] 0.315 0.677 323s .. ..$ n : int 14640 323s .. ..$ fit :Classes 'PeaksAndValleys' and 'data.frame': 5 obs. of 3 variables: 323s .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 323s .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 323s .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 323s .. ..$ fitValleys :Classes 'PeaksAndValleys' and 'data.frame': 2 obs. of 3 variables: 323s .. .. ..$ type : chr [1:2] "valley" "valley" 323s .. .. ..$ x : num [1:2] 0.315 0.677 323s .. .. ..$ density: num [1:2] 0.522 0.551 323s ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 323s muN 323s 0 0.5 1 323s 5221 4198 5251 323s Calling genotypes from normal allele B fractions...done 323s Normalizing betaT using betaN (TumorBoost)... 323s Normalized BAFs: 323s num [1:14670] 0.9301 0.1667 0.0685 0.0995 0.0155 ... 323s - attr(*, "modelFit")=List of 5 323s ..$ method : chr "normalizeTumorBoost" 323s ..$ flavor : chr "v4" 323s ..$ delta : num [1:14670] -0.17264 0.00239 0.1671 0.16085 0.04213 ... 323s .. ..- attr(*, "modelFit")=List of 1 323s .. .. ..$ :List of 7 323s .. .. .. ..$ flavor : chr "density" 323s .. .. .. ..$ cn : int 2 323s .. .. .. ..$ nbrOfGenotypeGroups: int 3 323s .. .. .. ..$ tau : num [1:2] 0.315 0.677 323s .. .. .. ..$ n : int 14640 323s .. .. .. ..$ fit :Classes 'PeaksAndValleys' and 'data.frame': 5 obs. of 3 variables: 323s .. .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 323s .. .. .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 323s .. .. .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 323s .. .. .. ..$ fitValleys :Classes 'PeaksAndValleys' and 'data.frame': 2 obs. of 3 variables: 323s .. .. .. .. ..$ type : chr [1:2] "valley" "valley" 323s .. .. .. .. ..$ x : num [1:2] 0.315 0.677 323s .. .. .. .. ..$ density: num [1:2] 0.522 0.551 323s .. .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 323s ..$ preserveScale: logi FALSE 323s ..$ scaleFactor : num NA 323s Normalizing betaT using betaN (TumorBoost)...done 323s Setup up data... 323s 'data.frame': 14670 obs. of 7 variables: 323s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 323s $ x : num 1145994 2941694 3710825 4240737 4276892 ... 323s $ CT : num 1.63 1.4 1.41 1.17 1.16 ... 323s $ betaT : num 0.7574 0.169 0.2357 0.2604 0.0576 ... 323s $ betaTN : num 0.9301 0.1667 0.0685 0.0995 0.0155 ... 323s ..- attr(*, "modelFit")=List of 5 323s .. ..$ method : chr "normalizeTumorBoost" 323s .. ..$ flavor : chr "v4" 323s .. ..$ delta : num [1:14670] -0.17264 0.00239 0.1671 0.16085 0.04213 ... 323s .. .. ..- attr(*, "modelFit")=List of 1 323s .. .. .. ..$ :List of 7 323s .. .. .. .. ..$ flavor : chr "density" 323s .. .. .. .. ..$ cn : int 2 323s .. .. .. .. ..$ nbrOfGenotypeGroups: int 3 323s .. .. .. .. ..$ tau : num [1:2] 0.315 0.677 323s .. .. .. .. ..$ n : int 14640 323s .. .. .. .. ..$ fit :Classes 'PeaksAndValleys' and 'data.frame': 5 obs. of 3 variables: 323s .. .. .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 323s .. .. .. .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 323s .. .. .. .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 323s .. .. .. .. ..$ fitValleys :Classes 'PeaksAndValleys' and 'data.frame': 2 obs. of 3 variables: 323s .. .. .. .. .. ..$ type : chr [1:2] "valley" "valley" 323s .. .. .. .. .. ..$ x : num [1:2] 0.315 0.677 323s .. .. .. .. .. ..$ density: num [1:2] 0.522 0.551 323s .. .. .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 323s .. ..$ preserveScale: logi FALSE 323s .. ..$ scaleFactor : num NA 323s $ betaN : num 0.8274 0.5072 0.1671 0.1609 0.0421 ... 323s $ muN : num 1 0.5 0 0 0 0 1 0 1 0.5 ... 323s ..- attr(*, "modelFit")=List of 1 323s .. ..$ :List of 7 323s .. .. ..$ flavor : chr "density" 323s .. .. ..$ cn : int 2 323s .. .. ..$ nbrOfGenotypeGroups: int 3 323s .. .. ..$ tau : num [1:2] 0.315 0.677 323s .. .. ..$ n : int 14640 323s .. .. ..$ fit :Classes 'PeaksAndValleys' and 'data.frame': 5 obs. of 3 variables: 323s .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 323s .. .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 323s .. .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 323s .. .. ..$ fitValleys :Classes 'PeaksAndValleys' and 'data.frame': 2 obs. of 3 variables: 323s .. .. .. ..$ type : chr [1:2] "valley" "valley" 323s .. .. .. ..$ x : num [1:2] 0.315 0.677 323s .. .. .. ..$ density: num [1:2] 0.522 0.551 323s .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 323s Setup up data...done 323s Dropping loci for which TCNs are missing... 323s Number of loci dropped: 12 323s Dropping loci for which TCNs are missing...done 323s Ordering data along genome... 323s 'data.frame': 14658 obs. of 7 variables: 323s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 323s $ x : num 554484 730720 782343 878522 916294 ... 323s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 323s $ betaT : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 323s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 323s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 323s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 323s Ordering data along genome...done 323s Keeping only current chromosome for 'knownSegments'... 323s Chromosome: 1 323s Known segments for this chromosome: 323s chromosome start end length 323s 1 1 -Inf 120908858 Inf 323s 2 1 120908859 142693887 21785028 323s 3 1 142693888 Inf Inf 323s Keeping only current chromosome for 'knownSegments'...done 323s alphaTCN: 0.009 323s alphaDH: 0.001 323s Number of loci: 14658 323s Calculating DHs... 323s Number of SNPs: 14658 323s Number of heterozygous SNPs: 4196 (28.63%) 323s Normalized DHs: 323s num [1:14658] NA NA NA NA NA ... 323s Calculating DHs...done 323s Random seed temporarily set (seed=c(48879), kind="L'Ecuyer-CMRG") 323s Produced 2 seeds from this stream for future usage 323s Identification of change points by total copy numbers... 323s Segmenting by CBS... 323s Chromosome: 1 323s Random seed temporarily set (seed=c(10407, 1066287653, -51199871, 161854402, -1995183193, 1503453565, -747102133), kind="L'Ecuyer-CMRG") 323s Produced 3 seeds from this stream for future usage 323s Segmenting by CBS...done 323s List of 4 323s $ data :'data.frame': 14658 obs. of 4 variables: 323s ..$ chromosome: int [1:14658] 1 1 1 1 1 1 1 1 1 1 ... 323s ..$ x : num [1:14658] 554484 730720 782343 878522 916294 ... 323s ..$ y : num [1:14658] 1.88 1.8 1.59 1.64 1.53 ... 323s ..$ index : int [1:14658] 1 2 3 4 5 6 7 8 9 10 ... 323s $ output :'data.frame': 4 obs. of 6 variables: 323s ..$ sampleName: chr [1:4] NA NA NA NA 323s ..$ chromosome: int [1:4] 1 1 1 1 323s ..$ start : num [1:4] 5.54e+05 1.21e+08 1.43e+08 1.85e+08 323s ..$ end : num [1:4] 1.21e+08 1.43e+08 1.85e+08 2.47e+08 323s ..$ nbrOfLoci : int [1:4] 7586 0 2681 4391 323s ..$ mean : num [1:4] 1.39 NA 2.07 2.63 323s $ segRows:'data.frame': 4 obs. of 2 variables: 323s ..$ startRow: int [1:4] 1 NA 7587 10268 323s ..$ endRow : int [1:4] 7586 NA 10267 14658 323s $ params :List of 5 323s ..$ alpha : num 0.009 323s ..$ undo : num 0 323s ..$ joinSegments : logi TRUE 323s ..$ knownSegments:'data.frame': 4 obs. of 3 variables: 323s .. ..$ chromosome: int [1:4] 1 1 2 1 323s .. ..$ start : num [1:4] -Inf -Inf -Inf 1.43e+08 323s .. ..$ end : num [1:4] 1.21e+08 Inf Inf Inf 323s ..$ seed : int [1:7] 10407 1066287653 -51199871 161854402 -1995183193 1503453565 -747102133 323s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 323s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.168 0 0.17 0 0 323s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 323s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 323s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 323s Identification of change points by total copy numbers...done 323s Restructure TCN segmentation results... 323s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean 323s 1 1 554484 120908858 7586 1.3853 323s 2 1 120908859 142693887 0 NA 323s 3 1 142693888 185449813 2681 2.0689 323s 4 1 185449813 247137334 4391 2.6341 323s Number of TCN segments: 4 323s Restructure TCN segmentation results...done 323s Total CN segment #1 ([ 554484,1.20909e+08]) of 4... 323s Number of TCN loci in segment: 7586 323s Locus data for TCN segment: 323s 'data.frame': 7586 obs. of 9 variables: 323s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 323s $ x : num 554484 730720 782343 878522 916294 ... 323s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 323s $ betaT : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 323s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 323s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 323s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 323s $ index : int 1 2 3 4 5 6 7 8 9 10 ... 323s $ rho : num NA NA NA NA NA ... 323s Number of loci: 7586 323s Number of SNPs: 2108 (27.79%) 323s Number of heterozygous SNPs: 2108 (100.00%) 323s Chromosome: 1 323s Segmenting DH signals... 323s Segmenting by CBS... 323s Chromosome: 1 323s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 323s Segmenting by CBS...done 323s List of 4 323s $ data :'data.frame': 7586 obs. of 4 variables: 323s ..$ chromosome: int [1:7586] 1 1 1 1 1 1 1 1 1 1 ... 323s ..$ x : num [1:7586] 554484 730720 782343 878522 916294 ... 323s ..$ y : num [1:7586] NA NA NA NA NA ... 323s ..$ index : int [1:7586] 1 2 3 4 5 6 7 8 9 10 ... 323s $ output :'data.frame': 1 obs. of 6 variables: 323s ..$ sampleName: chr NA 323s ..$ chromosome: int 1 323s ..$ start : num 554484 323s ..$ end : num 1.21e+08 323s ..$ nbrOfLoci : int 2108 323s ..$ mean : num 0.512 323s $ segRows:'data.frame': 1 obs. of 2 variables: 323s ..$ startRow: int 10 323s ..$ endRow : int 7574 323s $ params :List of 5 323s ..$ alpha : num 0.001 323s ..$ undo : num 0 323s ..$ joinSegments : logi TRUE 323s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 323s .. ..$ chromosome: int 1 323s .. ..$ start : num 554484 323s .. ..$ end : num 1.21e+08 323s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 323s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 323s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.046 0 0.046 0 0 323s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 323s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 323s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 323s DH segmentation (locally-indexed) rows: 323s startRow endRow 323s 1 10 7574 323s int [1:7586] 1 2 3 4 5 6 7 8 9 10 ... 323s DH segmentation rows: 323s startRow endRow 323s 1 10 7574 323s Segmenting DH signals...done 323s DH segmentation table: 323s dhStart dhEnd dhNbrOfLoci dhMean 323s 1 554484 120908858 2108 0.5116 323s startRow endRow 323s 1 10 7574 323s Rows: 323s [1] 1 323s TCN segmentation rows: 323s startRow endRow 323s 1 1 7586 323s TCN and DH segmentation rows: 323s startRow endRow 323s 1 1 7586 323s startRow endRow 323s 1 10 7574 323s NULL 323s TCN segmentation (expanded) rows: 323s startRow endRow 323s 1 1 7586 323s TCN and DH segmentation rows: 323s startRow endRow 323s 1 1 7586 323s 2 NA NA 323s 3 7587 10267 323s 4 10268 14658 323s startRow endRow 323s 1 10 7574 323s startRow endRow 323s 1 1 7586 323s Total CN segmentation table (expanded): 323s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 323s 1 1 554484 120908858 7586 1.3853 2108 2108 323s (TCN,DH) segmentation for one total CN segment: 323s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 323s 1 1 1 1 554484 120908858 7586 1.3853 2108 323s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 323s 1 2108 554484 120908858 2108 0.5116 323s Total CN segment #1 ([ 554484,1.20909e+08]) of 4...done 323s Total CN segment #2 ([1.20909e+08,1.42694e+08]) of 4... 323s Number of TCN loci in segment: 0 323s Locus data for TCN segment: 323s 'data.frame': 0 obs. of 9 variables: 323s $ chromosome: int 323s $ x : num 323s $ CT : num 323s $ betaT : num 323s $ betaTN : num 323s $ betaN : num 323s $ muN : num 323s $ index : int 323s $ rho : num 323s Number of loci: 0 323s Number of SNPs: 0 (NaN%) 323s Number of heterozygous SNPs: 0 (NaN%) 323s Chromosome: 1 323s Segmenting DH signals... 323s Segmenting by CBS... 323s Chromosome: NA 323s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 323s Segmenting by CBS...done 323s List of 4 323s $ data :'data.frame': 0 obs. of 4 variables: 323s ..$ chromosome: int(0) 323s ..$ x : num(0) 323s ..$ y : num(0) 323s ..$ index : int(0) 323s $ output :'data.frame': 0 obs. of 6 variables: 323s ..$ sampleName: chr(0) 323s ..$ chromosome: num(0) 323s ..$ start : num(0) 323s ..$ end : num(0) 323s ..$ nbrOfLoci : int(0) 323s ..$ mean : num(0) 323s $ segRows:'data.frame': 0 obs. of 2 variables: 323s ..$ startRow: int(0) 323s ..$ endRow : int(0) 323s $ params :List of 5 323s ..$ alpha : num 0.001 323s ..$ undo : num 0 323s ..$ joinSegments : logi TRUE 323s ..$ knownSegments:'data.frame': 0 obs. of 3 variables: 323s .. ..$ chromosome: int(0) 323s .. ..$ start : num(0) 323s .. ..$ end : num(0) 323s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 323s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 323s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.001 0 0.002 0 0 323s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 323s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 323s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 323s DH segmentation (locally-indexed) rows: 323s [1] startRow endRow 323s <0 rows> (or 0-length row.names) 323s int(0) 323s DH segmentation rows: 323s [1] startRow endRow 323s <0 rows> (or 0-length row.names) 323s Segmenting DH signals...done 323s DH segmentation table: 323s dhStart dhEnd dhNbrOfLoci dhMean 323s NA NA NA NA NA 323s startRow endRow 323s NA NA NA 323s Rows: 323s [1] 2 323s TCN segmentation rows: 323s startRow endRow 323s 2 NA NA 323s TCN and DH segmentation rows: 323s startRow endRow 323s 2 NA NA 323s startRow endRow 323s NA NA NA 323s startRow endRow 323s 1 1 7586 323s TCN segmentation (expanded) rows: 323s startRow endRow 323s 1 1 7586 323s 2 NA NA 323s TCN and DH segmentation rows: 323s startRow endRow 323s 1 1 7586 323s 2 NA NA 323s 3 7587 10267 323s 4 10268 14658 323s startRow endRow 323s 1 10 7574 323s 2 NA NA 323s startRow endRow 323s 1 1 7586 323s 2 NA NA 323s Total CN segmentation table (expanded): 323s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 323s 2 1 120908859 142693887 0 NA 0 0 323s (TCN,DH) segmentation for one total CN segment: 323s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 323s 2 2 1 1 120908859 142693887 0 NA 0 323s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 323s 2 0 NA NA NA NA 323s Total CN segment #2 ([1.20909e+08,1.42694e+08]) of 4...done 323s Total CN segment #3 ([1.42694e+08,1.8545e+08]) of 4... 323s Number of TCN loci in segment: 2681 323s Locus data for TCN segment: 323s 'data.frame': 2681 obs. of 9 variables: 323s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 323s $ x : num 1.43e+08 1.43e+08 1.43e+08 1.43e+08 1.44e+08 ... 323s $ CT : num 2.27 1.55 1.47 1.5 1.81 ... 323s $ betaT : num 0.34 0.55 0.048 0.813 0.575 ... 323s $ betaTN : num 0.441 0.629 -0.05 0.958 0.872 ... 323s $ betaN : num 0.3851 0.3933 0.0981 0.8552 0.7028 ... 323s $ muN : num 0.5 0.5 0 1 1 1 1 0.5 1 1 ... 323s $ index : int 7587 7588 7589 7590 7591 7592 7593 7594 7595 7596 ... 323s $ rho : num 0.117 0.258 NA NA NA ... 323s Number of loci: 2681 323s Number of SNPs: 777 (28.98%) 323s Number of heterozygous SNPs: 777 (100.00%) 323s Chromosome: 1 323s Segmenting DH signals... 323s Segmenting by CBS... 323s Chromosome: 1 323s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 323s Segmenting by CBS...done 323s List of 4 323s $ data :'data.frame': 2681 obs. of 4 variables: 323s ..$ chromosome: int [1:2681] 1 1 1 1 1 1 1 1 1 1 ... 323s ..$ x : num [1:2681] 1.43e+08 1.43e+08 1.43e+08 1.43e+08 1.44e+08 ... 323s ..$ y : num [1:2681] 0.117 0.258 NA NA NA ... 323s ..$ index : int [1:2681] 1 2 3 4 5 6 7 8 9 10 ... 323s $ output :'data.frame': 1 obs. of 6 variables: 323s ..$ sampleName: chr NA 323s ..$ chromosome: int 1 323s ..$ start : num 1.43e+08 323s ..$ end : num 1.85e+08 323s ..$ nbrOfLoci : int 777 323s ..$ mean : num 0.0973 323s $ segRows:'data.frame': 1 obs. of 2 variables: 323s ..$ startRow: int 1 323s ..$ endRow : int 2677 323s $ params :List of 5 323s ..$ alpha : num 0.001 323s ..$ undo : num 0 323s ..$ joinSegments : logi TRUE 323s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 323s .. ..$ chromosome: int 1 323s .. ..$ start : num 1.43e+08 323s .. ..$ end : num 1.85e+08 323s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 323s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 323s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.009 0 0.009 0 0 323s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 323s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 323s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 323s DH segmentation (locally-indexed) rows: 323s startRow endRow 323s 1 1 2677 323s int [1:2681] 7587 7588 7589 7590 7591 7592 7593 7594 7595 7596 ... 323s DH segmentation rows: 323s startRow endRow 323s 1 7587 10263 323s Segmenting DH signals...done 323s DH segmentation table: 323s dhStart dhEnd dhNbrOfLoci dhMean 323s 1 142693888 185449813 777 0.0973 323s startRow endRow 323s 1 7587 10263 323s Rows: 323s [1] 3 323s TCN segmentation rows: 323s startRow endRow 323s 3 7587 10267 323s TCN and DH segmentation rows: 323s startRow endRow 323s 3 7587 10267 323s startRow endRow 323s 1 7587 10263 323s startRow endRow 323s 1 1 7586 323s 2 NA NA 323s TCN segmentation (expanded) rows: 323s startRow endRow 323s 1 1 7586 323s 2 NA NA 323s 3 7587 10267 323s TCN and DH segmentation rows: 323s startRow endRow 323s 1 1 7586 323s 2 NA NA 323s 3 7587 10267 323s 4 10268 14658 323s startRow endRow 323s 1 10 7574 323s 2 NA NA 323s 3 7587 10263 323s startRow endRow 323s 1 1 7586 323s 2 NA NA 323s 3 7587 10267 323s Total CN segmentation table (expanded): 323s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 323s 3 1 142693888 185449813 2681 2.0689 777 777 323s (TCN,DH) segmentation for one total CN segment: 323s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 323s 3 3 1 1 142693888 185449813 2681 2.0689 777 323s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 323s 3 777 142693888 185449813 777 0.0973 323s Total CN segment #3 ([1.42694e+08,1.8545e+08]) of 4...done 323s Total CN segment #4 ([1.8545e+08,2.47137e+08]) of 4... 323s Number of TCN loci in segment: 4391 323s Locus data for TCN segment: 323s 'data.frame': 4391 obs. of 9 variables: 323s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 323s $ x : num 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 323s $ CT : num 2.93 2.15 2.82 2.93 2.46 ... 323s $ betaT : num 0.0811 0.5154 0.9473 0.3734 0.7506 ... 323s $ betaTN : num -0.169 0.609 1.028 0.525 0.968 ... 323s $ betaN : num 0.25 0.38 0.919 0.34 0.783 ... 323s $ muN : num 0 0.5 1 0.5 1 1 0 1 0 1 ... 323s $ index : int 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 323s $ rho : num NA 0.2186 NA 0.0503 NA ... 323s Number of loci: 4391 323s Number of SNPs: 1311 (29.86%) 323s Number of heterozygous SNPs: 1311 (100.00%) 323s Chromosome: 1 323s Segmenting DH signals... 323s Segmenting by CBS... 323s Chromosome: 1 323s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 323s Segmenting by CBS...done 323s List of 4 323s $ data :'data.frame': 4391 obs. of 4 variables: 323s ..$ chromosome: int [1:4391] 1 1 1 1 1 1 1 1 1 1 ... 323s ..$ x : num [1:4391] 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 323s ..$ y : num [1:4391] NA 0.2186 NA 0.0503 NA ... 323s ..$ index : int [1:4391] 1 2 3 4 5 6 7 8 9 10 ... 323s $ output :'data.frame': 1 obs. of 6 variables: 323s ..$ sampleName: chr NA 323s ..$ chromosome: int 1 323s ..$ start : num 1.85e+08 323s ..$ end : num 2.47e+08 323s ..$ nbrOfLoci : int 1311 323s ..$ mean : num 0.23 323s $ segRows:'data.frame': 1 obs. of 2 variables: 323s ..$ startRow: int 2 323s ..$ endRow : int 4388 323s $ params :List of 5 323s ..$ alpha : num 0.001 323s ..$ undo : num 0 323s ..$ joinSegments : logi TRUE 323s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 323s .. ..$ chromosome: int 1 323s .. ..$ start : num 1.85e+08 323s .. ..$ end : num 2.47e+08 323s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 323s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 323s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.018 0 0.018 0 0 323s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 323s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 323s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 323s DH segmentation (locally-indexed) rows: 323s startRow endRow 323s 1 2 4388 323s int [1:4391] 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 323s DH segmentation rows: 323s startRow endRow 323s 1 10269 14655 323s Segmenting DH signals...done 323s DH segmentation table: 323s dhStart dhEnd dhNbrOfLoci dhMean 323s 1 185449813 247137334 1311 0.2295 323s startRow endRow 323s 1 10269 14655 323s Rows: 323s [1] 4 323s TCN segmentation rows: 323s startRow endRow 323s 4 10268 14658 323s TCN and DH segmentation rows: 323s startRow endRow 323s 4 10268 14658 323s startRow endRow 323s 1 10269 14655 323s startRow endRow 323s 1 1 7586 323s 2 NA NA 323s 3 7587 10267 323s TCN segmentation (expanded) rows: 323s startRow endRow 323s 1 1 7586 323s 2 NA NA 323s 3 7587 10267 323s 4 10268 14658 323s TCN and DH segmentation rows: 323s startRow endRow 323s 1 1 7586 323s 2 NA NA 323s 3 7587 10267 323s 4 10268 14658 323s startRow endRow 323s 1 10 7574 323s 2 NA NA 323s 3 7587 10263 323s 4 10269 14655 323s startRow endRow 323s 1 1 7586 323s 2 NA NA 323s 3 7587 10267 323s 4 10268 14658 323s Total CN segmentation table (expanded): 323s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 323s 4 1 185449813 247137334 4391 2.6341 1311 1311 323s (TCN,DH) segmentation for one total CN segment: 323s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 323s 4 4 1 1 185449813 247137334 4391 2.6341 1311 323s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 323s 4 1311 185449813 247137334 1311 0.2295 323s Total CN segment #4 ([1.8545e+08,2.47137e+08]) of 4...done 323s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 323s 1 1 1 1 554484 120908858 7586 1.3853 2108 323s 2 1 2 1 120908859 142693887 0 NA 0 323s 3 1 3 1 142693888 185449813 2681 2.0689 777 323s 4 1 4 1 185449813 247137334 4391 2.6341 1311 323s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 323s 1 2108 554484 120908858 2108 0.5116 323s 2 0 NA NA NA NA 323s 3 777 142693888 185449813 777 0.0973 323s 4 1311 185449813 247137334 1311 0.2295 323s Calculating (C1,C2) per segment... 323s Calculating (C1,C2) per segment...done 323s Number of segments: 4 323s Segmenting paired tumor-normal signals using Paired PSCBS...done 323s Post-segmenting TCNs... 323s Number of segments: 4 323s Number of chromosomes: 1 323s [1] 1 323s Chromosome 1 ('chr01') of 1... 323s Rows: 323s [1] 1 2 3 4 323s Number of segments: 4 323s TCN segment #1 ('1') of 4... 323s Nothing todo. Only one DH segmentation. Skipping. 323s TCN segment #1 ('1') of 4...done 323s TCN segment #2 ('2') of 4... 323s Nothing todo. Only one DH segmentation. Skipping. 323s TCN segment #2 ('2') of 4...done 323s TCN segment #3 ('3') of 4... 323s Nothing todo. Only one DH segmentation. Skipping. 323s TCN segment #3 ('3') of 4...done 323s TCN segment #4 ('4') of 4... 323s Nothing todo. Only one DH segmentation. Skipping. 323s TCN segment #4 ('4') of 4...done 323s Chromosome 1 ('chr01') of 1...done 323s Update (C1,C2) per segment... 323s Update (C1,C2) per segment...done 323s Post-segmenting TCNs...done 323s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 323s 1 1 1 1 554484 120908858 7586 1.3853 2108 323s 2 1 2 1 120908859 142693887 0 NA 0 323s 3 1 3 1 142693888 185449813 2681 2.0689 777 323s 4 1 4 1 185449813 247137334 4391 2.6341 1311 323s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 323s 1 2108 554484 120908858 2108 0.5116 0.3382903 1.047010 323s 2 0 NA NA NA NA NA NA 323s 3 777 142693888 185449813 777 0.0973 0.9337980 1.135102 323s 4 1311 185449813 247137334 1311 0.2295 1.0147870 1.619313 323s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 323s 1 1 1 1 554484 120908858 7586 1.3853 2108 323s 2 1 2 1 120908859 142693887 0 NA 0 323s 3 1 3 1 142693888 185449813 2681 2.0689 777 323s 4 1 4 1 185449813 247137334 4391 2.6341 1311 323s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 323s 1 2108 554484 120908858 2108 0.5116 0.3382903 1.047010 323s 2 0 NA NA NA NA NA NA 323s 3 777 142693888 185449813 777 0.0973 0.9337980 1.135102 323s 4 1311 185449813 247137334 1311 0.2295 1.0147870 1.619313 323s > 323s > message("*** segmentByPairedPSCBS() via futures ... DONE") 323s *** segmentByPairedPSCBS() via futures ... DONE 323s > 323s > 323s > ## Cleanup 323s > plan(oplan) 323s > rm(list=c("fits", "data", "fit")) 323s > 323s > proc.time() 323s user system elapsed 323s 6.515 0.064 11.010 323s Test segmentByPairedPSCBS,futures passed 323s 0 323s Begin test segmentByPairedPSCBS,noNormalBAFs 323s + [ 0 != 0 ] 323s + echo Test segmentByPairedPSCBS,futures passed 323s + echo 0 323s + echo Begin test segmentByPairedPSCBS,noNormalBAFs 323s + exitcode=0 323s + R CMD BATCH segmentByPairedPSCBS,noNormalBAFs.R 326s + cat segmentByPairedPSCBS,noNormalBAFs.Rout 326s 326s R version 4.5.2 (2025-10-31) -- "[Not] Part in a Rumble" 326s Copyright (C) 2025 The R Foundation for Statistical Computing 326s Platform: powerpc64le-unknown-linux-gnu 326s 326s R is free software and comes with ABSOLUTELY NO WARRANTY. 326s You are welcome to redistribute it under certain conditions. 326s Type 'license()' or 'licence()' for distribution details. 326s 326s R is a collaborative project with many contributors. 326s Type 'contributors()' for more information and 326s 'citation()' on how to cite R or R packages in publications. 326s 326s Type 'demo()' for some demos, 'help()' for on-line help, or 326s 'help.start()' for an HTML browser interface to help. 326s Type 'q()' to quit R. 326s 326s [Previously saved workspace restored] 326s 326s > library("PSCBS") 326s PSCBS v0.68.0 (2025-04-18 19:40:02 UTC) successfully loaded. See ?PSCBS for help. 326s > 326s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 326s > # Load SNP microarray data 326s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 326s > data <- PSCBS::exampleData("paired.chr01") 326s > str(data) 326s 'data.frame': 73346 obs. of 6 variables: 326s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 326s $ x : int 1145994 2224111 2319424 2543484 2926730 2941694 3084986 3155127 3292731 3695086 ... 326s $ CT : num 1.625 1.071 1.406 1.18 0.856 ... 326s $ betaT : num 0.757 0.771 0.834 0.778 0.229 ... 326s $ CN : num 2.36 2.13 2.59 1.93 1.71 ... 326s $ betaN : num 0.827 0.875 0.887 0.884 0.103 ... 326s > 326s > # Drop single-locus outliers 326s > dataS <- dropSegmentationOutliers(data) 326s > 326s > # Run light-weight tests by default 326s > if (Sys.getenv("_R_CHECK_FULL_") == "") { 326s + # Use only every 5th data point 326s + dataS <- dataS[seq(from=1, to=nrow(data), by=5),] 326s + # Number of segments (for assertion) 326s + nSegs <- 3L 326s + # Number of bootstrap samples (see below) 326s + B <- 100L 326s + } else { 326s + # Full tests 326s + nSegs <- 8L 326s + B <- 1000L 326s + } 326s > 326s > str(dataS) 326s 'data.frame': 14670 obs. of 6 variables: 326s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 326s $ x : int 1145994 2941694 3710825 4240737 4276892 4464544 4714611 5095111 5034491 5158416 ... 326s $ CT : num 1.63 1.4 1.41 1.17 1.16 ... 326s $ betaT : num 0.7574 0.169 0.2357 0.2604 0.0576 ... 326s $ CN : num 2.36 2.13 2.26 2.01 2.32 ... 326s $ betaN : num 0.8274 0.5072 0.1671 0.1609 0.0421 ... 326s > 326s > R.oo::attachLocally(dataS) 326s > 326s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 326s > # Simulate that genotypes are known by other means 326s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 326s > library("aroma.light") 326s aroma.light v3.36.0 (2024-10-29) successfully loaded. See ?aroma.light for help. 326s > muN <- aroma.light::callNaiveGenotypes(betaN, censorAt=c(0,1)) 326s > 326s > 326s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 326s > # Paired PSCBS segmentation 326s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 326s > fit <- segmentByPairedPSCBS(CT, betaT=betaT, muN=muN, tbn=FALSE, 326s + chromosome=chromosome, x=x, 326s + seed=0xBEEF, verbose=-10) 326s Segmenting paired tumor-normal signals using Paired PSCBS... 326s Setup up data... 326s 'data.frame': 14670 obs. of 6 variables: 326s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 326s $ x : num 1145994 2941694 3710825 4240737 4276892 ... 326s $ CT : num 1.63 1.4 1.41 1.17 1.16 ... 326s $ betaT : num 0.7574 0.169 0.2357 0.2604 0.0576 ... 326s $ betaTN : num 0.7574 0.169 0.2357 0.2604 0.0576 ... 326s $ muN : num 1 0.5 0 0 0 0 1 0 1 0.5 ... 326s ..- attr(*, "modelFit")=List of 1 326s .. ..$ :List of 7 326s .. .. ..$ flavor : chr "density" 326s .. .. ..$ cn : int 2 326s .. .. ..$ nbrOfGenotypeGroups: int 3 326s .. .. ..$ tau : num [1:2] 0.315 0.677 326s .. .. ..$ n : int 14640 326s .. .. ..$ fit :Classes 'PeaksAndValleys' and 'data.frame': 5 obs. of 3 variables: 326s .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 326s .. .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 326s .. .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 326s .. .. ..$ fitValleys :Classes 'PeaksAndValleys' and 'data.frame': 2 obs. of 3 variables: 326s .. .. .. ..$ type : chr [1:2] "valley" "valley" 326s .. .. .. ..$ x : num [1:2] 0.315 0.677 326s .. .. .. ..$ density: num [1:2] 0.522 0.551 326s .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 326s Setup up data...done 326s Dropping loci for which TCNs are missing... 326s Number of loci dropped: 12 326s Dropping loci for which TCNs are missing...done 326s Ordering data along genome... 326s 'data.frame': 14658 obs. of 6 variables: 326s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 326s $ x : num 554484 730720 782343 878522 916294 ... 326s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 326s $ betaT : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 326s $ betaTN : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 326s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 326s Ordering data along genome...done 326s Keeping only current chromosome for 'knownSegments'... 326s Chromosome: 1 326s Known segments for this chromosome: 326s [1] chromosome start end 326s <0 rows> (or 0-length row.names) 326s Keeping only current chromosome for 'knownSegments'...done 326s alphaTCN: 0.009 326s alphaDH: 0.001 326s Number of loci: 14658 326s Calculating DHs... 326s Number of SNPs: 14658 326s Number of heterozygous SNPs: 4196 (28.63%) 326s Normalized DHs: 326s num [1:14658] NA NA NA NA NA ... 326s Calculating DHs...done 326s Random seed temporarily set (seed=c(48879), kind="L'Ecuyer-CMRG") 326s Produced 2 seeds from this stream for future usage 326s Identification of change points by total copy numbers... 326s Segmenting by CBS... 326s Chromosome: 1 326s Random seed temporarily set (seed=c(10407, 1066287653, -51199871, 161854402, -1995183193, 1503453565, -747102133), kind="L'Ecuyer-CMRG") 326s Segmenting by CBS...done 326s List of 4 326s $ data :'data.frame': 14658 obs. of 4 variables: 326s ..$ chromosome: int [1:14658] 1 1 1 1 1 1 1 1 1 1 ... 326s ..$ x : num [1:14658] 554484 730720 782343 878522 916294 ... 326s ..$ y : num [1:14658] 1.88 1.8 1.59 1.64 1.53 ... 326s ..$ index : int [1:14658] 1 2 3 4 5 6 7 8 9 10 ... 326s $ output :'data.frame': 3 obs. of 6 variables: 326s ..$ sampleName: chr [1:3] NA NA NA 326s ..$ chromosome: int [1:3] 1 1 1 326s ..$ start : num [1:3] 5.54e+05 1.44e+08 1.85e+08 326s ..$ end : num [1:3] 1.44e+08 1.85e+08 2.47e+08 326s ..$ nbrOfLoci : int [1:3] 7599 2668 4391 326s ..$ mean : num [1:3] 1.39 2.07 2.63 326s $ segRows:'data.frame': 3 obs. of 2 variables: 326s ..$ startRow: int [1:3] 1 7600 10268 326s ..$ endRow : int [1:3] 7599 10267 14658 326s $ params :List of 5 326s ..$ alpha : num 0.009 326s ..$ undo : num 0 326s ..$ joinSegments : logi TRUE 326s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 326s .. ..$ chromosome: int 1 326s .. ..$ start : num -Inf 326s .. ..$ end : num Inf 326s ..$ seed : int [1:7] 10407 1066287653 -51199871 161854402 -1995183193 1503453565 -747102133 326s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 326s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.482 0 0.483 0 0 326s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 326s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 326s - attr(*, "randomSeed")= int [1:7] 10407 1066287653 -51199871 161854402 -1995183193 1503453565 -747102133 326s Identification of change points by total copy numbers...done 326s Restructure TCN segmentation results... 326s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean 326s 1 1 554484 143926517 7599 1.3859 326s 2 1 143926517 185449813 2668 2.0704 326s 3 1 185449813 247137334 4391 2.6341 326s Number of TCN segments: 3 326s Restructure TCN segmentation results...done 326s Total CN segment #1 ([ 554484,1.43927e+08]) of 3... 326s Number of TCN loci in segment: 7599 326s Locus data for TCN segment: 326s 'data.frame': 7599 obs. of 8 variables: 326s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 326s $ x : num 554484 730720 782343 878522 916294 ... 326s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 326s $ betaT : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 326s $ betaTN : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 326s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 326s $ index : int 1 2 3 4 5 6 7 8 9 10 ... 326s $ rho : num NA NA NA NA NA ... 326s Number of loci: 7599 326s Number of SNPs: 2111 (27.78%) 326s Number of heterozygous SNPs: 2111 (100.00%) 326s Chromosome: 1 326s Segmenting DH signals... 326s Segmenting by CBS... 326s Chromosome: 1 326s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 326s Segmenting by CBS...done 326s List of 4 326s $ data :'data.frame': 7599 obs. of 4 variables: 326s ..$ chromosome: int [1:7599] 1 1 1 1 1 1 1 1 1 1 ... 326s ..$ x : num [1:7599] 554484 730720 782343 878522 916294 ... 326s ..$ y : num [1:7599] NA NA NA NA NA ... 326s ..$ index : int [1:7599] 1 2 3 4 5 6 7 8 9 10 ... 326s $ output :'data.frame': 1 obs. of 6 variables: 326s ..$ sampleName: chr NA 326s ..$ chromosome: int 1 326s ..$ start : num 554484 326s ..$ end : num 1.44e+08 326s ..$ nbrOfLoci : int 2111 326s ..$ mean : num 0.524 326s $ segRows:'data.frame': 1 obs. of 2 variables: 326s ..$ startRow: int 10 326s ..$ endRow : int 7594 326s $ params :List of 5 326s ..$ alpha : num 0.001 326s ..$ undo : num 0 326s ..$ joinSegments : logi TRUE 326s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 326s .. ..$ chromosome: int 1 326s .. ..$ start : num 554484 326s .. ..$ end : num 1.44e+08 326s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 326s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 326s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.031 0 0.031 0 0 326s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 326s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 326s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 326s DH segmentation (locally-indexed) rows: 326s startRow endRow 326s 1 10 7594 326s int [1:7599] 1 2 3 4 5 6 7 8 9 10 ... 326s DH segmentation rows: 326s startRow endRow 326s 1 10 7594 326s Segmenting DH signals...done 326s DH segmentation table: 326s dhStart dhEnd dhNbrOfLoci dhMean 326s 1 554484 143926517 2111 0.5237 326s startRow endRow 326s 1 10 7594 326s Rows: 326s [1] 1 326s TCN segmentation rows: 326s startRow endRow 326s 1 1 7599 326s TCN and DH segmentation rows: 326s startRow endRow 326s 1 1 7599 326s startRow endRow 326s 1 10 7594 326s NULL 326s TCN segmentation (expanded) rows: 326s startRow endRow 326s 1 1 7599 326s TCN and DH segmentation rows: 326s startRow endRow 326s 1 1 7599 326s 2 7600 10267 326s 3 10268 14658 326s startRow endRow 326s 1 10 7594 326s startRow endRow 326s 1 1 7599 326s Total CN segmentation table (expanded): 326s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 326s 1 1 554484 143926517 7599 1.3859 2111 2111 326s (TCN,DH) segmentation for one total CN segment: 326s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 326s 1 1 1 1 554484 143926517 7599 1.3859 2111 326s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 326s 1 2111 554484 143926517 2111 0.5237 326s Total CN segment #1 ([ 554484,1.43927e+08]) of 3...done 326s Total CN segment #2 ([1.43927e+08,1.8545e+08]) of 3... 326s Number of TCN loci in segment: 2668 326s Locus data for TCN segment: 326s 'data.frame': 2668 obs. of 8 variables: 326s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 326s $ x : num 1.44e+08 1.44e+08 1.44e+08 1.44e+08 1.44e+08 ... 326s $ CT : num 2.1 2.1 2.09 1.8 2.34 ... 326s $ betaT : num 0.1899 0.909 0.9166 0.1668 0.0308 ... 326s $ betaTN : num 0.1899 0.909 0.9166 0.1668 0.0308 ... 326s $ muN : num 0 1 1 0 0 1 0 0 0 0 ... 326s $ index : int 7600 7601 7602 7603 7604 7605 7606 7607 7608 7609 ... 326s $ rho : num NA NA NA NA NA NA NA NA NA NA ... 326s Number of loci: 2668 326s Number of SNPs: 774 (29.01%) 326s Number of heterozygous SNPs: 774 (100.00%) 326s Chromosome: 1 326s Segmenting DH signals... 326s Segmenting by CBS... 326s Chromosome: 1 326s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 326s Segmenting by CBS...done 326s List of 4 326s $ data :'data.frame': 2668 obs. of 4 variables: 326s ..$ chromosome: int [1:2668] 1 1 1 1 1 1 1 1 1 1 ... 326s ..$ x : num [1:2668] 1.44e+08 1.44e+08 1.44e+08 1.44e+08 1.44e+08 ... 326s ..$ y : num [1:2668] NA NA NA NA NA NA NA NA NA NA ... 326s ..$ index : int [1:2668] 1 2 3 4 5 6 7 8 9 10 ... 326s $ output :'data.frame': 1 obs. of 6 variables: 326s ..$ sampleName: chr NA 326s ..$ chromosome: int 1 326s ..$ start : num 1.44e+08 326s ..$ end : num 1.85e+08 326s ..$ nbrOfLoci : int 774 326s ..$ mean : num 0.154 326s $ segRows:'data.frame': 1 obs. of 2 variables: 326s ..$ startRow: int 15 326s ..$ endRow : int 2664 326s $ params :List of 5 326s ..$ alpha : num 0.001 326s ..$ undo : num 0 326s ..$ joinSegments : logi TRUE 326s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 326s .. ..$ chromosome: int 1 326s .. ..$ start : num 1.44e+08 326s .. ..$ end : num 1.85e+08 326s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 326s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 326s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.01 0 0.01 0 0 326s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 326s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 326s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 326s DH segmentation (locally-indexed) rows: 326s startRow endRow 326s 1 15 2664 326s int [1:2668] 7600 7601 7602 7603 7604 7605 7606 7607 7608 7609 ... 326s DH segmentation rows: 326s startRow endRow 326s 1 7614 10263 326s Segmenting DH signals...done 326s DH segmentation table: 326s dhStart dhEnd dhNbrOfLoci dhMean 326s 1 143926517 185449813 774 0.1542 326s startRow endRow 326s 1 7614 10263 326s Rows: 326s [1] 2 326s TCN segmentation rows: 326s startRow endRow 326s 2 7600 10267 326s TCN and DH segmentation rows: 326s startRow endRow 326s 2 7600 10267 326s startRow endRow 326s 1 7614 10263 326s startRow endRow 326s 1 1 7599 326s TCN segmentation (expanded) rows: 326s startRow endRow 326s 1 1 7599 326s 2 7600 10267 326s TCN and DH segmentation rows: 326s startRow endRow 326s 1 1 7599 326s 2 7600 10267 326s 3 10268 14658 326s startRow endRow 326s 1 10 7594 326s 2 7614 10263 326s startRow endRow 326s 1 1 7599 326s 2 7600 10267 326s Total CN segmentation table (expanded): 326s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 326s 2 1 143926517 185449813 2668 2.0704 774 774 326s (TCN,DH) segmentation for one total CN segment: 326s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 326s 2 2 1 1 143926517 185449813 2668 2.0704 774 326s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 326s 2 774 143926517 185449813 774 0.1542 326s Total CN segment #2 ([1.43927e+08,1.8545e+08]) of 3...done 326s Total CN segment #3 ([1.8545e+08,2.47137e+08]) of 3... 326s Number of TCN loci in segment: 4391 326s Locus data for TCN segment: 326s 'data.frame': 4391 obs. of 8 variables: 326s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 326s $ x : num 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 326s $ CT : num 2.93 2.15 2.82 2.93 2.46 ... 326s $ betaT : num 0.0811 0.5154 0.9473 0.3734 0.7506 ... 326s $ betaTN : num 0.0811 0.5154 0.9473 0.3734 0.7506 ... 326s $ muN : num 0 0.5 1 0.5 1 1 0 1 0 1 ... 326s $ index : int 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 326s $ rho : num NA 0.0308 NA 0.2533 NA ... 326s Number of loci: 4391 326s Number of SNPs: 1311 (29.86%) 326s Number of heterozygous SNPs: 1311 (100.00%) 326s Chromosome: 1 326s Segmenting DH signals... 326s Segmenting by CBS... 326s Chromosome: 1 326s + [ 0 != 0 ] 326s + echo Test segmentByPairedPSCBS,noNormalBAFs passed 326s + echo 0 326s + echo Begin test segmentByPairedPSCBS,report 326s + exitcode=0 326s + R CMD BATCH segmentByPairedPSCBS,report.R 326s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 326s Segmenting by CBS...done 326s List of 4 326s $ data :'data.frame': 4391 obs. of 4 variables: 326s ..$ chromosome: int [1:4391] 1 1 1 1 1 1 1 1 1 1 ... 326s ..$ x : num [1:4391] 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 326s ..$ y : num [1:4391] NA 0.0308 NA 0.2533 NA ... 326s ..$ index : int [1:4391] 1 2 3 4 5 6 7 8 9 10 ... 326s $ output :'data.frame': 1 obs. of 6 variables: 326s ..$ sampleName: chr NA 326s ..$ chromosome: int 1 326s ..$ start : num 1.85e+08 326s ..$ end : num 2.47e+08 326s ..$ nbrOfLoci : int 1311 326s ..$ mean : num 0.251 326s $ segRows:'data.frame': 1 obs. of 2 variables: 326s ..$ startRow: int 2 326s ..$ endRow : int 4388 326s $ params :List of 5 326s ..$ alpha : num 0.001 326s ..$ undo : num 0 326s ..$ joinSegments : logi TRUE 326s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 326s .. ..$ chromosome: int 1 326s .. ..$ start : num 1.85e+08 326s .. ..$ end : num 2.47e+08 326s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 326s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 326s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.025 0 0.025 0 0 326s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 326s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 326s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 326s DH segmentation (locally-indexed) rows: 326s startRow endRow 326s 1 2 4388 326s int [1:4391] 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 326s DH segmentation rows: 326s startRow endRow 326s 1 10269 14655 326s Segmenting DH signals...done 326s DH segmentation table: 326s dhStart dhEnd dhNbrOfLoci dhMean 326s 1 185449813 247137334 1311 0.2512 326s startRow endRow 326s 1 10269 14655 326s Rows: 326s [1] 3 326s TCN segmentation rows: 326s startRow endRow 326s 3 10268 14658 326s TCN and DH segmentation rows: 326s startRow endRow 326s 3 10268 14658 326s startRow endRow 326s 1 10269 14655 326s startRow endRow 326s 1 1 7599 326s 2 7600 10267 326s TCN segmentation (expanded) rows: 326s startRow endRow 326s 1 1 7599 326s 2 7600 10267 326s 3 10268 14658 326s TCN and DH segmentation rows: 326s startRow endRow 326s 1 1 7599 326s 2 7600 10267 326s 3 10268 14658 326s startRow endRow 326s 1 10 7594 326s 2 7614 10263 326s 3 10269 14655 326s startRow endRow 326s 1 1 7599 326s 2 7600 10267 326s 3 10268 14658 326s Total CN segmentation table (expanded): 326s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 326s 3 1 185449813 247137334 4391 2.6341 1311 1311 326s (TCN,DH) segmentation for one total CN segment: 326s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 326s 3 3 1 1 185449813 247137334 4391 2.6341 1311 326s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 326s 3 1311 185449813 247137334 1311 0.2512 326s Total CN segment #3 ([1.8545e+08,2.47137e+08]) of 3...done 326s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 326s 1 1 1 1 554484 143926517 7599 1.3859 2111 326s 2 1 2 1 143926517 185449813 2668 2.0704 774 326s 3 1 3 1 185449813 247137334 4391 2.6341 1311 326s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 326s 1 2111 554484 143926517 2111 0.5237 326s 2 774 143926517 185449813 774 0.1542 326s 3 1311 185449813 247137334 1311 0.2512 326s Calculating (C1,C2) per segment... 326s Calculating (C1,C2) per segment...done 326s Number of segments: 3 326s Segmenting paired tumor-normal signals using Paired PSCBS...done 326s Post-segmenting TCNs... 326s Number of segments: 3 326s Number of chromosomes: 1 326s [1] 1 326s Chromosome 1 ('chr01') of 1... 326s Rows: 326s [1] 1 2 3 326s Number of segments: 3 326s TCN segment #1 ('1') of 3... 326s Nothing todo. Only one DH segmentation. Skipping. 326s TCN segment #1 ('1') of 3...done 326s TCN segment #2 ('2') of 3... 326s Nothing todo. Only one DH segmentation. Skipping. 326s TCN segment #2 ('2') of 3...done 326s TCN segment #3 ('3') of 3... 326s Nothing todo. Only one DH segmentation. Skipping. 326s TCN segment #3 ('3') of 3...done 326s Chromosome 1 ('chr01') of 1...done 326s Update (C1,C2) per segment... 326s Update (C1,C2) per segment...done 326s Post-segmenting TCNs...done 326s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 326s 1 1 1 1 554484 143926517 7599 1.3859 2111 326s 2 1 2 1 143926517 185449813 2668 2.0704 774 326s 3 1 3 1 185449813 247137334 4391 2.6341 1311 326s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 326s 1 2111 554484 143926517 2111 0.5237 0.3300521 1.055848 326s 2 774 143926517 185449813 774 0.1542 0.8755722 1.194828 326s 3 1311 185449813 247137334 1311 0.2512 0.9862070 1.647893 326s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 326s 1 1 1 1 554484 143926517 7599 1.3859 2111 326s 2 1 2 1 143926517 185449813 2668 2.0704 774 326s 3 1 3 1 185449813 247137334 4391 2.6341 1311 326s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 326s 1 2111 554484 143926517 2111 0.5237 0.3300521 1.055848 326s 2 774 143926517 185449813 774 0.1542 0.8755722 1.194828 326s 3 1311 185449813 247137334 1311 0.2512 0.9862070 1.647893 326s > print(fit) 326s chromosome tcnId dhId start end tcnNbrOfLoci tcnMean tcnNbrOfSNPs 326s 1 1 1 1 554484 143926517 7599 1.3859 2111 326s 2 1 2 1 143926517 185449813 2668 2.0704 774 326s 3 1 3 1 185449813 247137334 4391 2.6341 1311 326s tcnNbrOfHets dhNbrOfLoci dhMean c1Mean c2Mean 326s 1 2111 2111 0.5237 0.3300521 1.055848 326s 2 774 774 0.1542 0.8755722 1.194828 326s 3 1311 1311 0.2512 0.9862070 1.647893 326s > 326s > # Plot results 326s > plotTracks(fit) 326s > 326s > # Sanity check 326s > stopifnot(nbrOfSegments(fit) == nSegs) 326s > 326s > 326s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 326s > # Bootstrap segment level estimates 326s > # (used by the AB caller, which, if skipped here, 326s > # will do it automatically) 326s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 326s > fit <- bootstrapTCNandDHByRegion(fit, B=B, verbose=-10) 326s Resample (TCN,DH) signals and re-estimate summaries for segment & changepoint... 326s Already done? 326s tcn_2.5% tcn_5% tcn_95% tcn_97.5% dh_2.5% dh_5% dh_95% dh_97.5% 326s FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE 326s c1_2.5% c1_5% c1_95% c1_97.5% c2_2.5% c2_5% c2_95% c2_97.5% 326s FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE 326s Bootstrapping (TCN,DH,C1,C2) segment mean levels... 326s Identifying heterozygous & homozygous SNPs and non-polymorphic loci... 326s Number of loci: 14658 326s Number of SNPs: 4196 326s Number of non-SNPs: 10462 326s Identifying heterozygous & homozygous SNPs and non-polymorphic loci...done 326s num [1:3, 1:100, 1:4] NA NA NA NA NA NA NA NA NA NA ... 326s - attr(*, "dimnames")=List of 3 326s ..$ : NULL 326s ..$ : NULL 326s ..$ : chr [1:4] "tcn" "dh" "c1" "c2" 326s Segment #1 (chr 1, tcnId=1, dhId=1) of 3... 326s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 326s 1 1 1 1 554484 143926517 7599 1.3859 2111 326s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 326s 1 2111 554484 143926517 2111 0.5237 0.3300521 1.055848 326s Number of TCNs: 7599 326s Number of DHs: 2111 326s int [1:7599] 1 2 3 4 5 6 7 8 9 10 ... 326s int [1:14658] 1 2 3 4 5 6 7 8 9 10 ... 326s int [1:7599] 1 2 3 4 5 6 7 8 9 10 ... 326s Identify loci used to bootstrap DH means... 326s Heterozygous SNPs to resample for DH: 326s int [1:2111] 10 12 24 28 31 33 34 39 46 48 ... 326s Identify loci used to bootstrap DH means...done 326s Identify loci used to bootstrap TCN means... 326s SNPs: 326s int [1:2111] 10 12 24 28 31 33 34 39 46 48 ... 326s Non-polymorphic loci: 326s int [1:5488] 1 2 3 4 5 6 7 8 9 11 ... 326s Heterozygous SNPs to resample for TCN: 326s int [1:2111] 10 12 24 28 31 33 34 39 46 48 ... 326s Homozygous SNPs to resample for TCN: 326s int(0) 326s Non-polymorphic loci to resample for TCN: 326s int [1:5488] 1 2 3 4 5 6 7 8 9 11 ... 326s Heterozygous SNPs with non-DH to resample for TCN: 326s int(0) 326s Loci to resample for TCN: 326s int [1:7599] 1 2 3 4 5 6 7 8 9 10 ... 326s Identify loci used to bootstrap TCN means...done 326s Number of (#hets, #homs, #nonSNPs): (2111,0,5488) 326s Bootstrapping while preserving (#hets, #homs, #nonSNPs)... 326s Number of bootstrap samples: 100 326s Bootstrapping while preserving (#hets, #homs, #nonSNPs)...done 326s Segment #1 (chr 1, tcnId=1, dhId=1) of 3...done 326s Segment #2 (chr 1, tcnId=2, dhId=1) of 3... 326s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 326s 2 1 2 1 143926517 185449813 2668 2.0704 774 326s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 326s 2 774 143926517 185449813 774 0.1542 0.8755722 1.194828 326s Number of TCNs: 2668 326s Number of DHs: 774 326s int [1:2668] 7600 7601 7602 7603 7604 7605 7606 7607 7608 7609 ... 326s int [1:14658] 1 2 3 4 5 6 7 8 9 10 ... 326s int [1:2668] 7600 7601 7602 7603 7604 7605 7606 7607 7608 7609 ... 326s Identify loci used to bootstrap DH means... 326s Heterozygous SNPs to resample for DH: 326s int [1:774] 7614 7616 7626 7627 7628 7635 7638 7639 7640 7642 ... 326s Identify loci used to bootstrap DH means...done 326s Identify loci used to bootstrap TCN means... 326s SNPs: 326s int [1:774] 7614 7616 7626 7627 7628 7635 7638 7639 7640 7642 ... 326s Non-polymorphic loci: 326s int [1:1894] 7600 7601 7602 7603 7604 7605 7606 7607 7608 7609 ... 326s Heterozygous SNPs to resample for TCN: 326s int [1:774] 7614 7616 7626 7627 7628 7635 7638 7639 7640 7642 ... 326s Homozygous SNPs to resample for TCN: 326s int(0) 326s Non-polymorphic loci to resample for TCN: 326s int [1:1894] 7600 7601 7602 7603 7604 7605 7606 7607 7608 7609 ... 326s Heterozygous SNPs with non-DH to resample for TCN: 326s int(0) 326s Loci to resample for TCN: 326s int [1:2668] 7600 7601 7602 7603 7604 7605 7606 7607 7608 7609 ... 326s Identify loci used to bootstrap TCN means...done 326s Number of (#hets, #homs, #nonSNPs): (774,0,1894) 326s Bootstrapping while preserving (#hets, #homs, #nonSNPs)... 326s Number of bootstrap samples: 100 326s Bootstrapping while preserving (#hets, #homs, #nonSNPs)...done 326s Segment #2 (chr 1, tcnId=2, dhId=1) of 3...done 326s Segment #3 (chr 1, tcnId=3, dhId=1) of 3... 326s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 326s 3 1 3 1 185449813 247137334 4391 2.6341 1311 326s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 326s 3 1311 185449813 247137334 1311 0.2512 0.986207 1.647893 326s Number of TCNs: 4391 326s Number of DHs: 1311 326s int [1:4391] 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 326s int [1:14658] 1 2 3 4 5 6 7 8 9 10 ... 326s int [1:4391] 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 326s Identify loci used to bootstrap DH means... 326s Heterozygous SNPs to resample for DH: 326s int [1:1311] 10269 10271 10281 10282 10283 10293 10295 10297 10300 10302 ... 326s Identify loci used to bootstrap DH means...done 326s Identify loci used to bootstrap TCN means... 326s SNPs: 326s int [1:1311] 10269 10271 10281 10282 10283 10293 10295 10297 10300 10302 ... 326s Non-polymorphic loci: 326s int [1:3080] 10268 10270 10272 10273 10274 10275 10276 10277 10278 10279 ... 326s Heterozygous SNPs to resample for TCN: 326s int [1:1311] 10269 10271 10281 10282 10283 10293 10295 10297 10300 10302 ... 326s Homozygous SNPs to resample for TCN: 326s int(0) 326s Non-polymorphic loci to resample for TCN: 326s int [1:3080] 10268 10270 10272 10273 10274 10275 10276 10277 10278 10279 ... 326s Heterozygous SNPs with non-DH to resample for TCN: 326s int(0) 326s Loci to resample for TCN: 326s int [1:4391] 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 326s Identify loci used to bootstrap TCN means...done 326s Number of (#hets, #homs, #nonSNPs): (1311,0,3080) 326s Bootstrapping while preserving (#hets, #homs, #nonSNPs)... 326s Number of bootstrap samples: 100 326s Bootstrapping while preserving (#hets, #homs, #nonSNPs)...done 326s Segment #3 (chr 1, tcnId=3, dhId=1) of 3...done 326s Bootstrapped segment mean levels 326s num [1:3, 1:100, 1:4] 1.38 2.08 2.63 1.38 2.07 ... 326s - attr(*, "dimnames")=List of 3 326s ..$ : NULL 326s ..$ : NULL 326s ..$ : chr [1:4] "tcn" "dh" "c1" "c2" 326s Calculating (C1,C2) mean levels from (TCN,DH) mean levels... 326s num [1:3, 1:100, 1:4] 1.38 2.08 2.63 1.38 2.07 ... 326s - attr(*, "dimnames")=List of 3 326s ..$ : NULL 326s ..$ : NULL 326s ..$ : chr [1:4] "tcn" "dh" "c1" "c2" 326s Calculating (C1,C2) mean levels from (TCN,DH) mean levels...done 326s Calculating polar (alpha,radius,manhattan) for change points... 326s num [1:2, 1:100, 1:2] -0.5588 -0.0962 -0.5365 -0.1285 -0.5378 ... 326s - attr(*, "dimnames")=List of 3 326s ..$ : NULL 326s ..$ : NULL 326s ..$ : chr [1:2] "c1" "c2" 326s Bootstrapped change points 326s num [1:2, 1:100, 1:5] -2.89 -1.78 -2.87 -1.86 -2.88 ... 326s - attr(*, "dimnames")=List of 3 326s ..$ : NULL 326s ..$ : NULL 326s ..$ : chr [1:5] "alpha" "radius" "manhattan" "d1" ... 326s Calculating polar (alpha,radius,manhattan) for change points...done 326s Bootstrapping (TCN,DH,C1,C2) segment mean levels...done 326s Summarizing bootstrapped segment ('tcn', 'dh', 'c1', 'c2') data... 326s num [1:3, 1:4, 1:4] NA NA NA NA NA NA NA NA NA NA ... 326s - attr(*, "dimnames")=List of 3 326s ..$ : NULL 326s ..$ : chr [1:4] "2.5%" "5%" "95%" "97.5%" 326s ..$ : chr [1:4] "tcn" "dh" "c1" "c2" 326s Field #1 ('tcn') of 4... 326s Segment #1 of 3... 326s Segment #1 of 3...done 326s Segment #2 of 3... 326s Segment #2 of 3...done 326s Segment #3 of 3... 326s Segment #3 of 3...done 326s Field #1 ('tcn') of 4...done 326s Field #2 ('dh') of 4... 326s Segment #1 of 3... 326s Segment #1 of 3...done 326s Segment #2 of 3... 326s Segment #2 of 3...done 326s Segment #3 of 3... 326s Segment #3 of 3...done 326s Field #2 ('dh') of 4...done 326s Field #3 ('c1') of 4... 326s Segment #1 of 3... 326s Segment #1 of 3...done 326s Segment #2 of 3... 326s Segment #2 of 3...done 326s Segment #3 of 3... 326s Segment #3 of 3...done 326s Field #3 ('c1') of 4...done 326s Field #4 ('c2') of 4... 326s Segment #1 of 3... 326s Segment #1 of 3...done 326s Segment #2 of 3... 326s Segment #2 of 3...done 326s Segment #3 of 3... 326s Segment #3 of 3...done 326s Field #4 ('c2') of 4...done 326s Bootstrap statistics 326s num [1:3, 1:4, 1:4] 1.38 2.06 2.62 1.38 2.06 ... 326s - attr(*, "dimnames")=List of 3 326s ..$ : NULL 326s ..$ : chr [1:4] "2.5%" "5%" "95%" "97.5%" 326s ..$ : chr [1:4] "tcn" "dh" "c1" "c2" 326s Statistical sanity checks (iff B >= 100)... 326s Available summaries: 2.5%, 5%, 95%, 97.5% 326s Available quantiles: 0.025, 0.05, 0.95, 0.975 326s num [1:3, 1:4, 1:4] 1.38 2.06 2.62 1.38 2.06 ... 326s - attr(*, "dimnames")=List of 3 326s ..$ : NULL 326s ..$ : chr [1:4] "2.5%" "5%" "95%" "97.5%" 326s ..$ : chr [1:4] "tcn" "dh" "c1" "c2" 326s Field #1 ('tcn') of 4... 326s Seg 1. mean=1.3859, range=[1.38092,1.3949], n=7599 326s Seg 2. mean=2.0704, range=[2.05747,2.08326], n=2668 326s Seg 3. mean=2.6341, range=[2.62068,2.64694], n=4391 326s Field #1 ('tcn') of 4...done 326s Field #2 ('dh') of 4... 326s Seg 1. mean=0.5237, range=[0.51753,0.532002], n=2111 326s Seg 2. mean=0.1542, range=[0.144468,0.16453], n=774 326s Seg 3. mean=0.2512, range=[0.242575,0.258832], n=1311 326s Field #2 ('dh') of 4...done 326s Field #3 ('c1') of 4... 326s Seg 1. mean=0.330052, range=[0.323996,0.336038], n=2111 326s Seg 2. mean=0.875572, range=[0.86318,0.887699], n=774 326s Seg 3. mean=0.986207, range=[0.975123,0.998982], n=1311 326s Field #3 ('c1') of 4...done 326s Field #4 ('c2') of 4... 326s Seg 1. mean=1.05585, range=[1.05006,1.06231], n=2111 326s Seg 2. mean=1.19483, range=[1.18417,1.2081], n=774 326s Seg 3. mean=1.64789, range=[1.63403,1.66098], n=1311 326s Field #4 ('c2') of 4...done 326s Statistical sanity checks (iff B >= 100)...done 326s Summarizing bootstrapped segment ('tcn', 'dh', 'c1', 'c2') data...done 326s Summarizing bootstrapped changepoint ('alpha', 'radius', 'manhattan', 'd1', 'd2') data... 326s num [1:2, 1:4, 1:5] NA NA NA NA NA NA NA NA NA NA ... 326s - attr(*, "dimnames")=List of 3 326s ..$ : NULL 326s ..$ : chr [1:4] "2.5%" "5%" "95%" "97.5%" 326s ..$ : chr [1:5] "alpha" "radius" "manhattan" "d1" ... 326s Field #1 ('alpha') of 5... 326s Changepoint #1 of 2... 326s Changepoint #1 of 2...done 326s Changepoint #2 of 2... 326s Changepoint #2 of 2...done 326s Field #1 ('alpha') of 5...done 326s Field #2 ('radius') of 5... 326s Changepoint #1 of 2... 326s Changepoint #1 of 2...done 326s Changepoint #2 of 2... 326s Changepoint #2 of 2...done 326s Field #2 ('radius') of 5...done 326s Field #3 ('manhattan') of 5... 326s Changepoint #1 of 2... 326s Changepoint #1 of 2...done 326s Changepoint #2 of 2... 326s Changepoint #2 of 2...done 326s Field #3 ('manhattan') of 5...done 326s Field #4 ('d1') of 5... 326s Changepoint #1 of 2... 326s Changepoint #1 of 2...done 326s Changepoint #2 of 2... 326s Changepoint #2 of 2...done 326s Field #4 ('d1') of 5...done 326s Field #5 ('d2') of 5... 326s Changepoint #1 of 2... 326s Changepoint #1 of 2...done 326s Changepoint #2 of 2... 326s Changepoint #2 of 2...done 326s Field #5 ('d2') of 5...done 326s Bootstrap statistics 326s num [1:2, 1:4, 1:5] -2.92 -1.86 -2.91 -1.85 -2.87 ... 326s - attr(*, "dimnames")=List of 3 326s ..$ : NULL 326s ..$ : chr [1:4] "2.5%" "5%" "95%" "97.5%" 326s ..$ : chr [1:5] "alpha" "radius" "manhattan" "d1" ... 326s Summarizing bootstrapped changepoint ('alpha', 'radius', 'manhattan', 'd1', 'd2') data...done 326s Resample (TCN,DH) signals and re-estimate summaries for segment & changepoint...done 326s > print(fit) 326s chromosome tcnId dhId start end tcnNbrOfLoci tcnMean tcnNbrOfSNPs 326s 1 1 1 1 554484 143926517 7599 1.3859 2111 326s 2 1 2 1 143926517 185449813 2668 2.0704 774 326s 3 1 3 1 185449813 247137334 4391 2.6341 1311 326s tcnNbrOfHets dhNbrOfLoci dhMean c1Mean c2Mean 326s 1 2111 2111 0.5237 0.3300521 1.055848 326s 2 774 774 0.1542 0.8755722 1.194828 326s 3 1311 1311 0.2512 0.9862070 1.647893 326s > plotTracks(fit) 326s > 326s > 326s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 326s > # Calling segments in allelic balance (AB) and 326s > # in loss-of-heterozygosity (LOH) 326s > # NOTE: Ideally, this should be done on whole-genome data 326s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 326s > fit <- callAB(fit, verbose=-10) 326s Calling segments of allelic balance from one-sided DH bootstrap confidence intervals... 326s delta (offset adjusting for bias in DH): 0.3466649145302 326s alpha (CI quantile; significance level): 0.05 326s Calling segments... 326s Number of segments called allelic balance (AB): 2 (66.67%) of 3 326s Calling segments...done 326s Calling segments of allelic balance from one-sided DH bootstrap confidence intervals...done 326s > fit <- callLOH(fit, verbose=-10) 326s Calling segments of allelic balance from one-sided DH bootstrap confidence intervals... 326s delta (offset adjusting for bias in C1): 0.771236438183453 326s alpha (CI quantile; significance level): 0.05 326s Calling segments... 326s Number of segments called low C1 (LowC1, "LOH_C1"): 1 (33.33%) of 3 326s Calling segments...done 326s Calling segments of allelic balance from one-sided DH bootstrap confidence intervals...done 326s > print(fit) 326s chromosome tcnId dhId start end tcnNbrOfLoci tcnMean tcnNbrOfSNPs 326s 1 1 1 1 554484 143926517 7599 1.3859 2111 326s 2 1 2 1 143926517 185449813 2668 2.0704 774 326s 3 1 3 1 185449813 247137334 4391 2.6341 1311 326s tcnNbrOfHets dhNbrOfLoci dhMean c1Mean c2Mean abCall lohCall 326s 1 2111 2111 0.5237 0.3300521 1.055848 FALSE TRUE 326s 2 774 774 0.1542 0.8755722 1.194828 TRUE FALSE 326s 3 1311 1311 0.2512 0.9862070 1.647893 TRUE FALSE 326s > plotTracks(fit) 326s > 326s > proc.time() 326s user system elapsed 326s 2.359 0.041 2.398 326s Test segmentByPairedPSCBS,noNormalBAFs passed 326s 0 326s Begin test segmentByPairedPSCBS,report 327s + cat segmentByPairedPSCBS,report.Rout 327s 327s R version 4.5.2 (2025-10-31) -- "[Not] Part in a Rumble" 327s Copyright (C) 2025 The R Foundation for Statistical Computing 327s Platform: powerpc64le-unknown-linux-gnu 327s 327s R is free software and comes with ABSOLUTELY NO WARRANTY. 327s You are welcome to redistribute it under certain conditions. 327s Type 'license()' or 'licence()' for distribution details. 327s 327s R is a collaborative project with many contributors. 327s Type 'contributors()' for more information and 327s 'citation()' on how to cite R or R packages in publications. 327s 327s Type 'demo()' for some demos, 'help()' for on-line help, or 327s 'help.start()' for an HTML browser interface to help. 327s Type 'q()' to quit R. 327s 327s [Previously saved workspace restored] 327s 327s > # This test script calls a report generator which requires 327s > # the 'ggplot2' package, which in turn will require packages 327s > # 'colorspace', 'dichromat', 'munsell', 'reshape2' and 'scales'. 327s > 327s > # Only run this test in full testing mode 327s > if (Sys.getenv("_R_CHECK_FULL_") != "") { 327s + library("PSCBS") 327s + 327s + # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 327s + # Load SNP microarray data 327s + # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 327s + data <- PSCBS::exampleData("paired.chr01") 327s + str(data) 327s + 327s + 327s + # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 327s + # Paired PSCBS segmentation 327s + # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 327s + # Drop single-locus outliers 327s + dataS <- dropSegmentationOutliers(data) 327s + 327s + # Speed up example by segmenting fewer loci 327s + dataS <- dataS[seq(from=1, to=nrow(data), by=5),] 327s + 327s + str(dataS) 327s + 327s + gaps <- findLargeGaps(dataS, minLength=2e6) 327s + knownSegments <- gapsToSegments(gaps) 327s + 327s + # Paired PSCBS segmentation 327s + fit <- segmentByPairedPSCBS(dataS, knownSegments=knownSegments, 327s + seed=0xBEEF, verbose=-10) 327s + 327s + # Fake a multi-chromosome segmentation 327s + fit1 <- fit 327s + fit2 <- renameChromosomes(fit, from=1, to=2) 327s + fit <- c(fit1, fit2) 327s + 327s + report(fit, sampleName="PairedPSCBS", studyName="PSCBS-Ex", verbose=-10) 327s + 327s + } # if (Sys.getenv("_R_CHECK_FULL_")) 327s > 327s > proc.time() 327s user system elapsed 327s 0.334 0.005 0.332 327s Test segmentByPairedPSCBS,report passed 327s + [ 0 != 0 ] 327s + echo Test segmentByPairedPSCBS,report passed 327s 0 327s Begin test segmentByPairedPSCBS,seqOfSegmentsByDP 327s + echo 0 327s + echo Begin test segmentByPairedPSCBS,seqOfSegmentsByDP 327s + exitcode=0 327s + R CMD BATCH segmentByPairedPSCBS,seqOfSegmentsByDP.R 332s + cat segmentByPairedPSCBS,seqOfSegmentsByDP.Rout 332s 332s R version 4.5.2 (2025-10-31) -- "[Not] Part in a Rumble" 332s Copyright (C) 2025 The R Foundation for Statistical Computing 332s Platform: powerpc64le-unknown-linux-gnu 332s 332s R is free software and comes with ABSOLUTELY NO WARRANTY. 332s You are welcome to redistribute it under certain conditions. 332s Type 'license()' or 'licence()' for distribution details. 332s 332s R is a collaborative project with many contributors. 332s Type 'contributors()' for more information and 332s 'citation()' on how to cite R or R packages in publications. 332s 332s Type 'demo()' for some demos, 'help()' for on-line help, or 332s 'help.start()' for an HTML browser interface to help. 332s Type 'q()' to quit R. 332s 332s [Previously saved workspace restored] 332s 332s > library("PSCBS") 332s PSCBS v0.68.0 (2025-04-18 19:40:02 UTC) successfully loaded. See ?PSCBS for help. 332s > subplots <- R.utils::subplots 332s > stext <- R.utils::stext 332s > 332s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 332s > # Load SNP microarray data 332s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 332s > data <- PSCBS::exampleData("paired.chr01") 332s > str(data) 332s 'data.frame': 73346 obs. of 6 variables: 332s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 332s $ x : int 1145994 2224111 2319424 2543484 2926730 2941694 3084986 3155127 3292731 3695086 ... 332s $ CT : num 1.625 1.071 1.406 1.18 0.856 ... 332s $ betaT : num 0.757 0.771 0.834 0.778 0.229 ... 332s $ CN : num 2.36 2.13 2.59 1.93 1.71 ... 332s $ betaN : num 0.827 0.875 0.887 0.884 0.103 ... 332s > 332s > 332s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 332s > # Paired PSCBS segmentation 332s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 332s > # Drop single-locus outliers 332s > dataS <- dropSegmentationOutliers(data) 332s > 332s > # Run light-weight tests by default 332s > if (Sys.getenv("_R_CHECK_FULL_") == "") { 332s + # Use only every 5th data point 332s + dataS <- dataS[seq(from=1, to=nrow(data), by=5),] 332s + # Number of segments (for assertion) 332s + nSegs <- 3L 332s + # Number of bootstrap samples (see below) 332s + B <- 100L 332s + } else { 332s + # Full tests 332s + nSegs <- 12L 332s + B <- 1000L 332s + } 332s > 332s > str(dataS) 332s 'data.frame': 14670 obs. of 6 variables: 332s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 332s $ x : int 1145994 2941694 3710825 4240737 4276892 4464544 4714611 5095111 5034491 5158416 ... 332s $ CT : num 1.63 1.4 1.41 1.17 1.16 ... 332s $ betaT : num 0.7574 0.169 0.2357 0.2604 0.0576 ... 332s $ CN : num 2.36 2.13 2.26 2.01 2.32 ... 332s $ betaN : num 0.8274 0.5072 0.1671 0.1609 0.0421 ... 332s > 332s > R.oo::attachLocally(dataS) 332s > 332s > 332s > gaps <- findLargeGaps(dataS, minLength=2e6) 332s > knownSegments <- gapsToSegments(gaps, dropGaps=TRUE) 332s > 332s > # Paired PSCBS segmentation 332s > fit <- segmentByPairedPSCBS(dataS, knownSegments=knownSegments, 332s + seed=0xBEEF, verbose=-10) 332s Segmenting paired tumor-normal signals using Paired PSCBS... 332s Calling genotypes from normal allele B fractions... 332s num [1:14670] 0.8274 0.5072 0.1671 0.1609 0.0421 ... 332s Called genotypes: 332s num [1:14670] 1 0.5 0 0 0 0 1 0 1 0.5 ... 332s - attr(*, "modelFit")=List of 1 332s ..$ :List of 7 332s .. ..$ flavor : chr "density" 332s .. ..$ cn : int 2 332s .. ..$ nbrOfGenotypeGroups: int 3 332s .. ..$ tau : num [1:2] 0.315 0.677 332s .. ..$ n : int 14640 332s .. ..$ fit :Classes 'PeaksAndValleys' and 'data.frame': 5 obs. of 3 variables: 332s .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 332s .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 332s .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 332s .. ..$ fitValleys :Classes 'PeaksAndValleys' and 'data.frame': 2 obs. of 3 variables: 332s .. .. ..$ type : chr [1:2] "valley" "valley" 332s .. .. ..$ x : num [1:2] 0.315 0.677 332s .. .. ..$ density: num [1:2] 0.522 0.551 332s ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 332s muN 332s 0 0.5 1 332s 5221 4198 5251 332s Calling genotypes from normal allele B fractions...done 332s Normalizing betaT using betaN (TumorBoost)... 332s Normalized BAFs: 332s num [1:14670] 0.9301 0.1667 0.0685 0.0995 0.0155 ... 332s - attr(*, "modelFit")=List of 5 332s ..$ method : chr "normalizeTumorBoost" 332s ..$ flavor : chr "v4" 332s ..$ delta : num [1:14670] -0.17264 0.00239 0.1671 0.16085 0.04213 ... 332s .. ..- attr(*, "modelFit")=List of 1 332s .. .. ..$ :List of 7 332s .. .. .. ..$ flavor : chr "density" 332s .. .. .. ..$ cn : int 2 332s .. .. .. ..$ nbrOfGenotypeGroups: int 3 332s .. .. .. ..$ tau : num [1:2] 0.315 0.677 332s .. .. .. ..$ n : int 14640 332s .. .. .. ..$ fit :Classes 'PeaksAndValleys' and 'data.frame': 5 obs. of 3 variables: 332s .. .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 332s .. .. .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 332s .. .. .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 332s .. .. .. ..$ fitValleys :Classes 'PeaksAndValleys' and 'data.frame': 2 obs. of 3 variables: 332s .. .. .. .. ..$ type : chr [1:2] "valley" "valley" 332s .. .. .. .. ..$ x : num [1:2] 0.315 0.677 332s .. .. .. .. ..$ density: num [1:2] 0.522 0.551 332s .. .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 332s ..$ preserveScale: logi FALSE 332s ..$ scaleFactor : num NA 332s Normalizing betaT using betaN (TumorBoost)...done 332s Setup up data... 332s 'data.frame': 14670 obs. of 7 variables: 332s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 332s $ x : num 1145994 2941694 3710825 4240737 4276892 ... 332s $ CT : num 1.63 1.4 1.41 1.17 1.16 ... 332s $ betaT : num 0.7574 0.169 0.2357 0.2604 0.0576 ... 332s $ betaTN : num 0.9301 0.1667 0.0685 0.0995 0.0155 ... 332s ..- attr(*, "modelFit")=List of 5 332s .. ..$ method : chr "normalizeTumorBoost" 332s .. ..$ flavor : chr "v4" 332s .. ..$ delta : num [1:14670] -0.17264 0.00239 0.1671 0.16085 0.04213 ... 332s .. .. ..- attr(*, "modelFit")=List of 1 332s .. .. .. ..$ :List of 7 332s .. .. .. .. ..$ flavor : chr "density" 332s .. .. .. .. ..$ cn : int 2 332s .. .. .. .. ..$ nbrOfGenotypeGroups: int 3 332s .. .. .. .. ..$ tau : num [1:2] 0.315 0.677 332s .. .. .. .. ..$ n : int 14640 332s .. .. .. .. ..$ fit :Classes 'PeaksAndValleys' and 'data.frame': 5 obs. of 3 variables: 332s .. .. .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 332s .. .. .. .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 332s .. .. .. .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 332s .. .. .. .. ..$ fitValleys :Classes 'PeaksAndValleys' and 'data.frame': 2 obs. of 3 variables: 332s .. .. .. .. .. ..$ type : chr [1:2] "valley" "valley" 332s .. .. .. .. .. ..$ x : num [1:2] 0.315 0.677 332s .. .. .. .. .. ..$ density: num [1:2] 0.522 0.551 332s .. .. .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 332s .. ..$ preserveScale: logi FALSE 332s .. ..$ scaleFactor : num NA 332s $ betaN : num 0.8274 0.5072 0.1671 0.1609 0.0421 ... 332s $ muN : num 1 0.5 0 0 0 0 1 0 1 0.5 ... 332s ..- attr(*, "modelFit")=List of 1 332s .. ..$ :List of 7 332s .. .. ..$ flavor : chr "density" 332s .. .. ..$ cn : int 2 332s .. .. ..$ nbrOfGenotypeGroups: int 3 332s .. .. ..$ tau : num [1:2] 0.315 0.677 332s .. .. ..$ n : int 14640 332s .. .. ..$ fit :Classes 'PeaksAndValleys' and 'data.frame': 5 obs. of 3 variables: 332s .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 332s .. .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 332s .. .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 332s .. .. ..$ fitValleys :Classes 'PeaksAndValleys' and 'data.frame': 2 obs. of 3 variables: 332s .. .. .. ..$ type : chr [1:2] "valley" "valley" 332s .. .. .. ..$ x : num [1:2] 0.315 0.677 332s .. .. .. ..$ density: num [1:2] 0.522 0.551 332s .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 332s Setup up data...done 332s Dropping loci for which TCNs are missing... 332s Number of loci dropped: 12 332s Dropping loci for which TCNs are missing...done 332s Ordering data along genome... 332s 'data.frame': 14658 obs. of 7 variables: 332s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 332s $ x : num 554484 730720 782343 878522 916294 ... 332s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 332s $ betaT : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 332s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 332s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 332s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 332s Ordering data along genome...done 332s Keeping only current chromosome for 'knownSegments'... 332s Chromosome: 1 332s Known segments for this chromosome: 332s chromosome start end length 332s 1 1 -Inf 120908858 Inf 332s 2 1 142693888 Inf Inf 332s Keeping only current chromosome for 'knownSegments'...done 332s alphaTCN: 0.009 332s alphaDH: 0.001 332s Number of loci: 14658 332s Calculating DHs... 332s Number of SNPs: 14658 332s Number of heterozygous SNPs: 4196 (28.63%) 332s Normalized DHs: 332s num [1:14658] NA NA NA NA NA ... 332s Calculating DHs...done 332s Random seed temporarily set (seed=c(48879), kind="L'Ecuyer-CMRG") 332s Produced 2 seeds from this stream for future usage 332s Identification of change points by total copy numbers... 332s Segmenting by CBS... 332s Chromosome: 1 332s Segmenting multiple segments on current chromosome... 332s Number of segments: 2 332s Random seed temporarily set (seed=c(10407, 1066287653, -51199871, 161854402, -1995183193, 1503453565, -747102133), kind="L'Ecuyer-CMRG") 332s Produced 2 seeds from this stream for future usage 332s Segmenting by CBS... 332s Chromosome: 1 332s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 332s Segmenting by CBS...done 332s Segmenting by CBS... 332s Chromosome: 1 332s Random seed temporarily set (seed=c(10407, -821273412, -52578226, 1415511586, 721384351, -665928286, 1316562960), kind="L'Ecuyer-CMRG") 332s Segmenting by CBS...done 332s Segmenting multiple segments on current chromosome...done 332s Segmenting by CBS...done 332s List of 4 332s $ data :'data.frame': 14658 obs. of 4 variables: 332s ..$ chromosome: int [1:14658] 1 1 1 1 1 1 1 1 1 1 ... 332s ..$ x : num [1:14658] 554484 730720 782343 878522 916294 ... 332s ..$ y : num [1:14658] 1.88 1.8 1.59 1.64 1.53 ... 332s ..$ index : int [1:14658] 1 2 3 4 5 6 7 8 9 10 ... 332s $ output :'data.frame': 3 obs. of 6 variables: 332s ..$ sampleName: chr [1:3] NA NA NA 332s ..$ chromosome: int [1:3] 1 1 1 332s ..$ start : num [1:3] 5.54e+05 1.43e+08 1.85e+08 332s ..$ end : num [1:3] 1.21e+08 1.85e+08 2.47e+08 332s ..$ nbrOfLoci : int [1:3] 7586 2681 4391 332s ..$ mean : num [1:3] 1.39 2.07 2.63 332s $ segRows:'data.frame': 3 obs. of 2 variables: 332s ..$ startRow: int [1:3] 1 7587 10268 332s ..$ endRow : int [1:3] 7586 10267 14658 332s $ params :List of 5 332s ..$ alpha : num 0.009 332s ..$ undo : num 0 332s ..$ joinSegments : logi TRUE 332s ..$ knownSegments:'data.frame': 2 obs. of 3 variables: 332s .. ..$ chromosome: int [1:2] 1 1 332s .. ..$ start : num [1:2] -Inf 1.43e+08 332s .. ..$ end : num [1:2] 1.21e+08 Inf 332s ..$ seed : int [1:7] 10407 1066287653 -51199871 161854402 -1995183193 1503453565 -747102133 332s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 332s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.174 0 0.174 0 0 332s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 332s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 332s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 332s Identification of change points by total copy numbers...done 332s Restructure TCN segmentation results... 332s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean 332s 1 1 554484 120908858 7586 1.3853 332s 2 1 142693888 185449813 2681 2.0689 332s 3 1 185449813 247137334 4391 2.6341 332s Number of TCN segments: 3 332s Restructure TCN segmentation results...done 332s Total CN segment #1 ([ 554484,1.20909e+08]) of 3... 332s Number of TCN loci in segment: 7586 332s Locus data for TCN segment: 332s 'data.frame': 7586 obs. of 9 variables: 332s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 332s $ x : num 554484 730720 782343 878522 916294 ... 332s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 332s $ betaT : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 332s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 332s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 332s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 332s $ index : int 1 2 3 4 5 6 7 8 9 10 ... 332s $ rho : num NA NA NA NA NA ... 332s Number of loci: 7586 332s Number of SNPs: 2108 (27.79%) 332s Number of heterozygous SNPs: 2108 (100.00%) 332s Chromosome: 1 332s Segmenting DH signals... 332s Segmenting by CBS... 332s Chromosome: 1 332s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 332s Segmenting by CBS...done 332s List of 4 332s $ data :'data.frame': 7586 obs. of 4 variables: 332s ..$ chromosome: int [1:7586] 1 1 1 1 1 1 1 1 1 1 ... 332s ..$ x : num [1:7586] 554484 730720 782343 878522 916294 ... 332s ..$ y : num [1:7586] NA NA NA NA NA ... 332s ..$ index : int [1:7586] 1 2 3 4 5 6 7 8 9 10 ... 332s $ output :'data.frame': 1 obs. of 6 variables: 332s ..$ sampleName: chr NA 332s ..$ chromosome: int 1 332s ..$ start : num 554484 332s ..$ end : num 1.21e+08 332s ..$ nbrOfLoci : int 2108 332s ..$ mean : num 0.512 332s $ segRows:'data.frame': 1 obs. of 2 variables: 332s ..$ startRow: int 10 332s ..$ endRow : int 7574 332s $ params :List of 5 332s ..$ alpha : num 0.001 332s ..$ undo : num 0 332s ..$ joinSegments : logi TRUE 332s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 332s .. ..$ chromosome: int 1 332s .. ..$ start : num 554484 332s .. ..$ end : num 1.21e+08 332s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 332s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 332s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.047 0 0.047 0 0 332s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 332s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 332s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 332s DH segmentation (locally-indexed) rows: 332s startRow endRow 332s 1 10 7574 332s int [1:7586] 1 2 3 4 5 6 7 8 9 10 ... 332s DH segmentation rows: 332s startRow endRow 332s 1 10 7574 332s Segmenting DH signals...done 332s DH segmentation table: 332s dhStart dhEnd dhNbrOfLoci dhMean 332s 1 554484 120908858 2108 0.5116 332s startRow endRow 332s 1 10 7574 332s Rows: 332s [1] 1 332s TCN segmentation rows: 332s startRow endRow 332s 1 1 7586 332s TCN and DH segmentation rows: 332s startRow endRow 332s 1 1 7586 332s startRow endRow 332s 1 10 7574 332s NULL 332s TCN segmentation (expanded) rows: 332s startRow endRow 332s 1 1 7586 332s TCN and DH segmentation rows: 332s startRow endRow 332s 1 1 7586 332s 2 7587 10267 332s 3 10268 14658 332s startRow endRow 332s 1 10 7574 332s startRow endRow 332s 1 1 7586 332s Total CN segmentation table (expanded): 332s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 332s 1 1 554484 120908858 7586 1.3853 2108 2108 332s (TCN,DH) segmentation for one total CN segment: 332s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 332s 1 1 1 1 554484 120908858 7586 1.3853 2108 332s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 332s 1 2108 554484 120908858 2108 0.5116 332s Total CN segment #1 ([ 554484,1.20909e+08]) of 3...done 332s Total CN segment #2 ([1.42694e+08,1.8545e+08]) of 3... 332s Number of TCN loci in segment: 2681 332s Locus data for TCN segment: 332s 'data.frame': 2681 obs. of 9 variables: 332s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 332s $ x : num 1.43e+08 1.43e+08 1.43e+08 1.43e+08 1.44e+08 ... 332s $ CT : num 2.27 1.55 1.47 1.5 1.81 ... 332s $ betaT : num 0.34 0.55 0.048 0.813 0.575 ... 332s $ betaTN : num 0.441 0.629 -0.05 0.958 0.872 ... 332s $ betaN : num 0.3851 0.3933 0.0981 0.8552 0.7028 ... 332s $ muN : num 0.5 0.5 0 1 1 1 1 0.5 1 1 ... 332s $ index : int 7587 7588 7589 7590 7591 7592 7593 7594 7595 7596 ... 332s $ rho : num 0.117 0.258 NA NA NA ... 332s Number of loci: 2681 332s Number of SNPs: 777 (28.98%) 332s Number of heterozygous SNPs: 777 (100.00%) 332s Chromosome: 1 332s Segmenting DH signals... 332s Segmenting by CBS... 332s Chromosome: 1 332s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 332s Segmenting by CBS...done 332s List of 4 332s $ data :'data.frame': 2681 obs. of 4 variables: 332s ..$ chromosome: int [1:2681] 1 1 1 1 1 1 1 1 1 1 ... 332s ..$ x : num [1:2681] 1.43e+08 1.43e+08 1.43e+08 1.43e+08 1.44e+08 ... 332s ..$ y : num [1:2681] 0.117 0.258 NA NA NA ... 332s ..$ index : int [1:2681] 1 2 3 4 5 6 7 8 9 10 ... 332s $ output :'data.frame': 1 obs. of 6 variables: 332s ..$ sampleName: chr NA 332s ..$ chromosome: int 1 332s ..$ start : num 1.43e+08 332s ..$ end : num 1.85e+08 332s ..$ nbrOfLoci : int 777 332s ..$ mean : num 0.0973 332s $ segRows:'data.frame': 1 obs. of 2 variables: 332s ..$ startRow: int 1 332s ..$ endRow : int 2677 332s $ params :List of 5 332s ..$ alpha : num 0.001 332s ..$ undo : num 0 332s ..$ joinSegments : logi TRUE 332s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 332s .. ..$ chromosome: int 1 332s .. ..$ start : num 1.43e+08 332s .. ..$ end : num 1.85e+08 332s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 332s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 332s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.009 0 0.009 0 0 332s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 332s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 332s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 332s DH segmentation (locally-indexed) rows: 332s startRow endRow 332s 1 1 2677 332s int [1:2681] 7587 7588 7589 7590 7591 7592 7593 7594 7595 7596 ... 332s DH segmentation rows: 332s startRow endRow 332s 1 7587 10263 332s Segmenting DH signals...done 332s DH segmentation table: 332s dhStart dhEnd dhNbrOfLoci dhMean 332s 1 142693888 185449813 777 0.0973 332s startRow endRow 332s 1 7587 10263 332s Rows: 332s [1] 2 332s TCN segmentation rows: 332s startRow endRow 332s 2 7587 10267 332s TCN and DH segmentation rows: 332s startRow endRow 332s 2 7587 10267 332s startRow endRow 332s 1 7587 10263 332s startRow endRow 332s 1 1 7586 332s TCN segmentation (expanded) rows: 332s startRow endRow 332s 1 1 7586 332s 2 7587 10267 332s TCN and DH segmentation rows: 332s startRow endRow 332s 1 1 7586 332s 2 7587 10267 332s 3 10268 14658 332s startRow endRow 332s 1 10 7574 332s 2 7587 10263 332s startRow endRow 332s 1 1 7586 332s 2 7587 10267 332s Total CN segmentation table (expanded): 332s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 332s 2 1 142693888 185449813 2681 2.0689 777 777 332s (TCN,DH) segmentation for one total CN segment: 332s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 332s 2 2 1 1 142693888 185449813 2681 2.0689 777 332s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 332s 2 777 142693888 185449813 777 0.0973 332s Total CN segment #2 ([1.42694e+08,1.8545e+08]) of 3...done 332s Total CN segment #3 ([1.8545e+08,2.47137e+08]) of 3... 332s Number of TCN loci in segment: 4391 332s Locus data for TCN segment: 332s 'data.frame': 4391 obs. of 9 variables: 332s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 332s $ x : num 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 332s $ CT : num 2.93 2.15 2.82 2.93 2.46 ... 332s $ betaT : num 0.0811 0.5154 0.9473 0.3734 0.7506 ... 332s $ betaTN : num -0.169 0.609 1.028 0.525 0.968 ... 332s $ betaN : num 0.25 0.38 0.919 0.34 0.783 ... 332s $ muN : num 0 0.5 1 0.5 1 1 0 1 0 1 ... 332s $ index : int 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 332s $ rho : num NA 0.2186 NA 0.0503 NA ... 332s Number of loci: 4391 332s Number of SNPs: 1311 (29.86%) 332s Number of heterozygous SNPs: 1311 (100.00%) 332s Chromosome: 1 332s Segmenting DH signals... 332s Segmenting by CBS... 332s Chromosome: 1 332s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 332s Segmenting by CBS...done 332s List of 4 332s $ data :'data.frame': 4391 obs. of 4 variables: 332s ..$ chromosome: int [1:4391] 1 1 1 1 1 1 1 1 1 1 ... 332s ..$ x : num [1:4391] 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 332s ..$ y : num [1:4391] NA 0.2186 NA 0.0503 NA ... 332s ..$ index : int [1:4391] 1 2 3 4 5 6 7 8 9 10 ... 332s $ output :'data.frame': 1 obs. of 6 variables: 332s ..$ sampleName: chr NA 332s ..$ chromosome: int 1 332s ..$ start : num 1.85e+08 332s ..$ end : num 2.47e+08 332s ..$ nbrOfLoci : int 1311 332s ..$ mean : num 0.23 332s $ segRows:'data.frame': 1 obs. of 2 variables: 332s ..$ startRow: int 2 332s ..$ endRow : int 4388 332s $ params :List of 5 332s ..$ alpha : num 0.001 332s ..$ undo : num 0 332s ..$ joinSegments : logi TRUE 332s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 332s .. ..$ chromosome: int 1 332s .. ..$ start : num 1.85e+08 332s .. ..$ end : num 2.47e+08 332s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 332s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 332s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.018 0 0.018 0 0 332s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 332s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 332s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 332s DH segmentation (locally-indexed) rows: 332s startRow endRow 332s 1 2 4388 332s int [1:4391] 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 332s DH segmentation rows: 332s startRow endRow 332s 1 10269 14655 332s Segmenting DH signals...done 332s DH segmentation table: 332s dhStart dhEnd dhNbrOfLoci dhMean 332s 1 185449813 247137334 1311 0.2295 332s startRow endRow 332s 1 10269 14655 332s Rows: 332s [1] 3 332s TCN segmentation rows: 332s startRow endRow 332s 3 10268 14658 332s TCN and DH segmentation rows: 332s startRow endRow 332s 3 10268 14658 332s startRow endRow 332s 1 10269 14655 332s startRow endRow 332s 1 1 7586 332s 2 7587 10267 332s TCN segmentation (expanded) rows: 332s startRow endRow 332s 1 1 7586 332s 2 7587 10267 332s 3 10268 14658 332s TCN and DH segmentation rows: 332s startRow endRow 332s 1 1 7586 332s 2 7587 10267 332s 3 10268 14658 332s startRow endRow 332s 1 10 7574 332s 2 7587 10263 332s 3 10269 14655 332s startRow endRow 332s 1 1 7586 332s 2 7587 10267 332s 3 10268 14658 332s Total CN segmentation table (expanded): 332s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 332s 3 1 185449813 247137334 4391 2.6341 1311 1311 332s (TCN,DH) segmentation for one total CN segment: 332s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 332s 3 3 1 1 185449813 247137334 4391 2.6341 1311 332s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 332s 3 1311 185449813 247137334 1311 0.2295 332s Total CN segment #3 ([1.8545e+08,2.47137e+08]) of 3...done 332s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 332s 1 1 1 1 554484 120908858 7586 1.3853 2108 332s 2 1 2 1 142693888 185449813 2681 2.0689 777 332s 3 1 3 1 185449813 247137334 4391 2.6341 1311 332s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 332s 1 2108 554484 120908858 2108 0.5116 332s 2 777 142693888 185449813 777 0.0973 332s 3 1311 185449813 247137334 1311 0.2295 332s Calculating (C1,C2) per segment... 332s Calculating (C1,C2) per segment...done 332s Number of segments: 3 332s Segmenting paired tumor-normal signals using Paired PSCBS...done 332s Post-segmenting TCNs... 332s Number of segments: 3 332s Number of chromosomes: 1 332s [1] 1 332s Chromosome 1 ('chr01') of 1... 332s Rows: 332s [1] 1 2 3 332s Number of segments: 3 332s TCN segment #1 ('1') of 3... 332s Nothing todo. Only one DH segmentation. Skipping. 332s TCN segment #1 ('1') of 3...done 332s TCN segment #2 ('2') of 3... 332s Nothing todo. Only one DH segmentation. Skipping. 332s TCN segment #2 ('2') of 3...done 332s TCN segment #3 ('3') of 3... 332s Nothing todo. Only one DH segmentation. Skipping. 332s TCN segment #3 ('3') of 3...done 332s Chromosome 1 ('chr01') of 1...done 332s Update (C1,C2) per segment... 332s Update (C1,C2) per segment...done 332s Post-segmenting TCNs...done 332s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 332s 1 1 1 1 554484 120908858 7586 1.3853 2108 332s 2 1 2 1 142693888 185449813 2681 2.0689 777 332s 3 1 3 1 185449813 247137334 4391 2.6341 1311 332s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 332s 1 2108 554484 120908858 2108 0.5116 0.3382903 1.047010 332s 2 777 142693888 185449813 777 0.0973 0.9337980 1.135102 332s 3 1311 185449813 247137334 1311 0.2295 1.0147870 1.619313 332s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 332s 1 1 1 1 554484 120908858 7586 1.3853 2108 332s 2 1 2 1 142693888 185449813 2681 2.0689 777 332s 3 1 3 1 185449813 247137334 4391 2.6341 1311 332s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 332s 1 2108 554484 120908858 2108 0.5116 0.3382903 1.047010 332s 2 777 142693888 185449813 777 0.0973 0.9337980 1.135102 332s 3 1311 185449813 247137334 1311 0.2295 1.0147870 1.619313 332s > print(fit) 332s chromosome tcnId dhId start end tcnNbrOfLoci tcnMean tcnNbrOfSNPs 332s 1 1 1 1 554484 120908858 7586 1.3853 2108 332s 2 1 2 1 142693888 185449813 2681 2.0689 777 332s 3 1 3 1 185449813 247137334 4391 2.6341 1311 332s tcnNbrOfHets dhNbrOfLoci dhMean c1Mean c2Mean 332s 1 2108 2108 0.5116 0.3382903 1.047010 332s 2 777 777 0.0973 0.9337980 1.135102 332s 3 1311 1311 0.2295 1.0147870 1.619313 332s > 332s > fit1 <- fit 332s > fit2 <- renameChromosomes(fit1, from=1, to=2) 332s > fit <- c(fit1, fit2) 332s > knownSegments <- tileChromosomes(fit)$params$knownSegments 332s > 332s > segList <- seqOfSegmentsByDP(fit, verbose=-10) 332s Identifying optimal sets of segments via dynamic programming... 332s Shifting TCN levels for every second segment... 332s Split up into non-empty independent regions... 332s Chromosome #1 ('1') of 2... 332s Number of loci on chromosome: 14658 332s Known segments on chromosome: 332s chromosome start end 332s 1 1 -Inf 120908858 332s 2 1 142693888 Inf 332s Known segment #1 of 2... 332s chromosome start end 332s 1 1 -Inf 120908858 332s Known segment #1 of 2...done 332s Known segment #2 of 2... 332s chromosome start end 332s 2 1 142693888 Inf 332s Known segment #2 of 2...done 332s Chromosome #1 ('1') of 2...done 332s Chromosome #2 ('2') of 2... 332s Number of loci on chromosome: 14658 332s Known segments on chromosome: 332s chromosome start end 332s 3 2 -Inf 120908858 332s 4 2 142693888 Inf 332s Known segment #1 of 2... 332s chromosome start end 332s 3 2 -Inf 120908858 332s Known segment #1 of 2...done 332s Known segment #2 of 2... 332s chromosome start end 332s 4 2 142693888 Inf 332s Known segment #2 of 2...done 332s Chromosome #2 ('2') of 2...done 332s Number of independent non-empty regions: 4 332s Split up into non-empty independent regions...done 332s Shift every other region... 332s Shift every other region...done 332s Merge... 332s Merge...done 332s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 332s 1 1 1 1 554484 120908858 7586 101.3853 2108 332s 2 1 2 1 142693888 185449813 2681 2.0689 777 332s 3 1 3 1 185449813 247137334 4391 2.6341 1311 332s 4 2 1 1 554484 120908858 7586 101.3853 2108 332s 5 2 2 1 142693888 185449813 2681 2.0689 777 332s 6 2 3 1 185449813 247137334 4391 2.6341 1311 332s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 332s 1 2108 554484 120908858 2108 0.511612 24.757671 76.627587 332s 2 777 142693888 185449813 777 0.097300 0.933798 1.135102 332s 3 1311 185449813 247137334 1311 0.229500 1.014787 1.619313 332s 4 2108 554484 120908858 2108 0.511612 24.757671 76.627587 332s 5 777 142693888 185449813 777 0.097300 0.933798 1.135102 332s 6 1311 185449813 247137334 1311 0.229500 1.014787 1.619313 332s Shifting TCN levels for every second segment...done 332s Extracting signals for dynamic programming... 332s CT rho 332s Min. : 0.805 Min. :0.0002 332s 1st Qu.: 2.407 1st Qu.:0.1393 332s Median :100.927 Median :0.2934 332s Mean : 53.638 Mean :0.3467 332s 3rd Qu.:101.370 3rd Qu.:0.5566 332s Max. :103.080 Max. :1.0217 332s NA's :20924 332s Extracting signals for dynamic programming...done 332s Dynamic programming... 332s Number of "DP" change points: 5 332s int [1:5] 7586 10267 14658 22244 24925 332s List of 4 332s $ jump :List of 5 332s ..$ : num 22244 332s ..$ : num [1:2] 7586 14658 332s ..$ : num [1:3] 7586 14658 22244 332s ..$ : num [1:4] 7586 10267 14658 22244 332s ..$ : num [1:5] 7586 10267 14658 22244 24925 332s $ rse : num [1:6] 71699116 47249179 35852530 5945 5410 ... 332s $ kbest: num 4 332s $ V : num [1:6, 1:6] 1114 0 0 0 0 ... 332s Dynamic programming...done 332s Excluding cases where known segments no longer correct... 332s Number of independent non-empty regions: 4 332s List of 3 332s $ : num [1:3] 7586 14658 22244 332s $ : num [1:4] 7586 10267 14658 22244 332s $ : num [1:5] 7586 10267 14658 22244 24925 332s Excluding cases where known segments no longer correct...done 332s List of 3 332s $ :'data.frame': 4 obs. of 3 variables: 332s ..$ chromosome: int [1:4] 1 1 2 2 332s ..$ start : num [1:4] 5.54e+05 1.43e+08 5.54e+05 1.43e+08 332s ..$ end : num [1:4] 1.21e+08 2.47e+08 1.21e+08 2.47e+08 332s $ :'data.frame': 5 obs. of 3 variables: 332s ..$ chromosome: int [1:5] 1 1 1 2 2 332s ..$ start : num [1:5] 5.54e+05 1.43e+08 1.85e+08 5.54e+05 1.43e+08 332s ..$ end : num [1:5] 1.21e+08 1.85e+08 2.47e+08 1.21e+08 2.47e+08 332s $ :'data.frame': 6 obs. of 3 variables: 332s ..$ chromosome: int [1:6] 1 1 1 2 2 2 332s ..$ start : num [1:6] 5.54e+05 1.43e+08 1.85e+08 5.54e+05 1.43e+08 ... 332s ..$ end : num [1:6] 1.21e+08 1.85e+08 2.47e+08 1.21e+08 1.85e+08 ... 332s Sequence of number of "DP" change points: 332s [1] 3 4 5 332s Sequence of number of segments: 332s [1] 4 5 6 332s Sequence of number of "discovered" change points: 332s [1] 0 1 2 332s Identifying optimal sets of segments via dynamic programming...done 332s > K <- length(segList) 332s > ks <- seq(from=1, to=K, length.out=min(5,K)) 332s > subplots(length(ks), ncol=1, byrow=TRUE) 332s > par(mar=c(2,1,1,1)) 332s > for (kk in ks) { 332s + knownSegmentsKK <- segList[[kk]] 332s + fitKK <- resegment(fit, knownSegments=knownSegmentsKK, undoTCN=+Inf, undoDH=+Inf) 332s + plotTracks(fitKK, tracks="tcn,c1,c2", Clim=c(0,5), add=TRUE) 332s + abline(v=c(knownSegments$start, knownSegments$end)/1e6, lty=3) 332s + stext(side=3, pos=0, sprintf("Number of segments: %d", nrow(knownSegmentsKK))) 332s + } # for (kk ...) 332s > 332s > proc.time() 332s user system elapsed 332s 4.462 0.052 4.511 332s Test segmentByPairedPSCBS,seqOfSegmentsByDP passed 332s 0 332s Begin test segmentByPairedPSCBS 332s + [ 0 != 0 ] 332s + echo Test segmentByPairedPSCBS,seqOfSegmentsByDP passed 332s + echo 0 332s + echo Begin test segmentByPairedPSCBS 332s + exitcode=0 332s + R CMD BATCH segmentByPairedPSCBS.R 339s + cat segmentByPairedPSCBS.Rout 339s 339s R version 4.5.2 (2025-10-31) -- "[Not] Part in a Rumble" 339s Copyright (C) 2025 The R Foundation for Statistical Computing 339s Platform: powerpc64le-unknown-linux-gnu 339s 339s R is free software and comes with ABSOLUTELY NO WARRANTY. 339s You are welcome to redistribute it under certain conditions. 339s Type 'license()' or 'licence()' for distribution details. 339s 339s R is a collaborative project with many contributors. 339s Type 'contributors()' for more information and 339s 'citation()' on how to cite R or R packages in publications. 339s 339s Type 'demo()' for some demos, 'help()' for on-line help, or 339s 'help.start()' for an HTML browser interface to help. 339s Type 'q()' to quit R. 339s 339s [Previously saved workspace restored] 339s 339s > ########################################################### 339s > # This tests: 339s > # - segmentByPairedPSCBS(...) 339s > # - segmentByPairedPSCBS(..., knownSegments) 339s > # - tileChromosomes() 339s > # - plotTracks() 339s > ########################################################### 339s > library("PSCBS") 339s PSCBS v0.68.0 (2025-04-18 19:40:02 UTC) successfully loaded. See ?PSCBS for help. 339s > 339s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 339s > # Load SNP microarray data 339s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 339s > data <- PSCBS::exampleData("paired.chr01") 339s > 339s > 339s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 339s > # Paired PSCBS segmentation 339s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 339s > # Drop single-locus outliers 339s > dataS <- dropSegmentationOutliers(data) 339s > 339s > # Run light-weight tests by default 339s > if (Sys.getenv("_R_CHECK_FULL_") == "") { 339s + # Use only every 5th data point 339s + dataS <- dataS[seq(from=1, to=nrow(data), by=5),] 339s + # Number of segments (for assertion) 339s + nSegs <- 4L 339s + } else { 339s + # Full tests 339s + nSegs <- 11L 339s + } 339s > 339s > str(dataS) 339s 'data.frame': 14670 obs. of 6 variables: 339s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 339s $ x : int 1145994 2941694 3710825 4240737 4276892 4464544 4714611 5095111 5034491 5158416 ... 339s $ CT : num 1.63 1.4 1.41 1.17 1.16 ... 339s $ betaT : num 0.7574 0.169 0.2357 0.2604 0.0576 ... 339s $ CN : num 2.36 2.13 2.26 2.01 2.32 ... 339s $ betaN : num 0.8274 0.5072 0.1671 0.1609 0.0421 ... 339s > 339s > fig <- 1 339s > 339s > 339s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 339s > # (a) Don't segment the centromere (and force a separator) 339s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 339s > knownSegments <- data.frame( 339s + chromosome = c( 1, 1, 1), 339s + start = c( -Inf, NA, 141510003), 339s + end = c(120992603, NA, +Inf) 339s + ) 339s > 339s > 339s > # Paired PSCBS segmentation 339s > fit <- segmentByPairedPSCBS(dataS, knownSegments=knownSegments, 339s + seed=0xBEEF, verbose=-10) 339s Segmenting paired tumor-normal signals using Paired PSCBS... 339s Calling genotypes from normal allele B fractions... 339s num [1:14670] 0.8274 0.5072 0.1671 0.1609 0.0421 ... 339s Called genotypes: 339s num [1:14670] 1 0.5 0 0 0 0 1 0 1 0.5 ... 339s - attr(*, "modelFit")=List of 1 339s ..$ :List of 7 339s .. ..$ flavor : chr "density" 339s .. ..$ cn : int 2 339s .. ..$ nbrOfGenotypeGroups: int 3 339s .. ..$ tau : num [1:2] 0.315 0.677 339s .. ..$ n : int 14640 339s .. ..$ fit :Classes 'PeaksAndValleys' and 'data.frame': 5 obs. of 3 variables: 339s .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 339s .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 339s .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 339s .. ..$ fitValleys :Classes 'PeaksAndValleys' and 'data.frame': 2 obs. of 3 variables: 339s .. .. ..$ type : chr [1:2] "valley" "valley" 339s .. .. ..$ x : num [1:2] 0.315 0.677 339s .. .. ..$ density: num [1:2] 0.522 0.551 339s ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 339s muN 339s 0 0.5 1 339s 5221 4198 5251 339s Calling genotypes from normal allele B fractions...done 339s Normalizing betaT using betaN (TumorBoost)... 339s Normalized BAFs: 339s num [1:14670] 0.9301 0.1667 0.0685 0.0995 0.0155 ... 339s - attr(*, "modelFit")=List of 5 339s ..$ method : chr "normalizeTumorBoost" 339s ..$ flavor : chr "v4" 339s ..$ delta : num [1:14670] -0.17264 0.00239 0.1671 0.16085 0.04213 ... 339s .. ..- attr(*, "modelFit")=List of 1 339s .. .. ..$ :List of 7 339s .. .. .. ..$ flavor : chr "density" 339s .. .. .. ..$ cn : int 2 339s .. .. .. ..$ nbrOfGenotypeGroups: int 3 339s .. .. .. ..$ tau : num [1:2] 0.315 0.677 339s .. .. .. ..$ n : int 14640 339s .. .. .. ..$ fit :Classes 'PeaksAndValleys' and 'data.frame': 5 obs. of 3 variables: 339s .. .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 339s .. .. .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 339s .. .. .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 339s .. .. .. ..$ fitValleys :Classes 'PeaksAndValleys' and 'data.frame': 2 obs. of 3 variables: 339s .. .. .. .. ..$ type : chr [1:2] "valley" "valley" 339s .. .. .. .. ..$ x : num [1:2] 0.315 0.677 339s .. .. .. .. ..$ density: num [1:2] 0.522 0.551 339s .. .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 339s ..$ preserveScale: logi FALSE 339s ..$ scaleFactor : num NA 339s Normalizing betaT using betaN (TumorBoost)...done 339s Setup up data... 339s 'data.frame': 14670 obs. of 7 variables: 339s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 339s $ x : num 1145994 2941694 3710825 4240737 4276892 ... 339s $ CT : num 1.63 1.4 1.41 1.17 1.16 ... 339s $ betaT : num 0.7574 0.169 0.2357 0.2604 0.0576 ... 339s $ betaTN : num 0.9301 0.1667 0.0685 0.0995 0.0155 ... 339s ..- attr(*, "modelFit")=List of 5 339s .. ..$ method : chr "normalizeTumorBoost" 339s .. ..$ flavor : chr "v4" 339s .. ..$ delta : num [1:14670] -0.17264 0.00239 0.1671 0.16085 0.04213 ... 339s .. .. ..- attr(*, "modelFit")=List of 1 339s .. .. .. ..$ :List of 7 339s .. .. .. .. ..$ flavor : chr "density" 339s .. .. .. .. ..$ cn : int 2 339s .. .. .. .. ..$ nbrOfGenotypeGroups: int 3 339s .. .. .. .. ..$ tau : num [1:2] 0.315 0.677 339s .. .. .. .. ..$ n : int 14640 339s .. .. .. .. ..$ fit :Classes 'PeaksAndValleys' and 'data.frame': 5 obs. of 3 variables: 339s .. .. .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 339s .. .. .. .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 339s .. .. .. .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 339s .. .. .. .. ..$ fitValleys :Classes 'PeaksAndValleys' and 'data.frame': 2 obs. of 3 variables: 339s .. .. .. .. .. ..$ type : chr [1:2] "valley" "valley" 339s .. .. .. .. .. ..$ x : num [1:2] 0.315 0.677 339s .. .. .. .. .. ..$ density: num [1:2] 0.522 0.551 339s .. .. .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 339s .. ..$ preserveScale: logi FALSE 339s .. ..$ scaleFactor : num NA 339s $ betaN : num 0.8274 0.5072 0.1671 0.1609 0.0421 ... 339s $ muN : num 1 0.5 0 0 0 0 1 0 1 0.5 ... 339s ..- attr(*, "modelFit")=List of 1 339s .. ..$ :List of 7 339s .. .. ..$ flavor : chr "density" 339s .. .. ..$ cn : int 2 339s .. .. ..$ nbrOfGenotypeGroups: int 3 339s .. .. ..$ tau : num [1:2] 0.315 0.677 339s .. .. ..$ n : int 14640 339s .. .. ..$ fit :Classes 'PeaksAndValleys' and 'data.frame': 5 obs. of 3 variables: 339s .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 339s .. .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 339s .. .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 339s .. .. ..$ fitValleys :Classes 'PeaksAndValleys' and 'data.frame': 2 obs. of 3 variables: 339s .. .. .. ..$ type : chr [1:2] "valley" "valley" 339s .. .. .. ..$ x : num [1:2] 0.315 0.677 339s .. .. .. ..$ density: num [1:2] 0.522 0.551 339s .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 339s Setup up data...done 339s Dropping loci for which TCNs are missing... 339s Number of loci dropped: 12 339s Dropping loci for which TCNs are missing...done 339s Ordering data along genome... 339s + 'data.fra[ 0 != 0 ] 339s + echo Test segmentByPairedPSCBS passed 339s me': 14658 obs. of 7 variables: 339s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 339s $ x : num 554484 730720 782343 878522 916294 ... 339s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 339s $ betaT : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 339s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 339s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 339s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 339s Ordering data along genome...done 339s Keeping only current chromosome for 'knownSegments'... 339s Chromosome: 1 339s Known segments for this chromosome: 339s chromosome start end 339s 1 1 -Inf 120992603 339s 2 1 NA NA 339s 3 1 141510003 Inf 339s Keeping only current chromosome for 'knownSegments'...done 339s alphaTCN: 0.009 339s alphaDH: 0.001 339s Number of loci: 14658 339s Calculating DHs... 339s Number of SNPs: 14658 339s Number of heterozygous SNPs: 4196 (28.63%) 339s Normalized DHs: 339s num [1:14658] NA NA NA NA NA ... 339s Calculating DHs...done 339s Random seed temporarily set (seed=c(48879), kind="L'Ecuyer-CMRG") 339s Produced 2 seeds from this stream for future usage 339s Identification of change points by total copy numbers... 339s Segmenting by CBS... 339s Chromosome: 1 339s Segmenting multiple segments on current chromosome... 339s Number of segments: 3 339s Random seed temporarily set (seed=c(10407, 1066287653, -51199871, 161854402, -1995183193, 1503453565, -747102133), kind="L'Ecuyer-CMRG") 339s Produced 3 seeds from this stream for future usage 339s Segmenting by CBS... 339s Chromosome: 1 339s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 339s Segmenting by CBS...done 339s Segmenting by CBS... 339s Chromosome: 1 339s Random seed temporarily set (seed=c(10407, -1924040949, -1632234809, -437763632, -1464377300, 676654412, 2080370711), kind="L'Ecuyer-CMRG") 339s Segmenting by CBS...done 339s Segmenting multiple segments on current chromosome...done 339s Segmenting by CBS...done 339s List of 4 339s $ data :'data.frame': 14658 obs. of 4 variables: 339s ..$ chromosome: int [1:14658] 1 1 1 1 1 1 1 1 1 1 ... 339s ..$ x : num [1:14658] 554484 730720 782343 878522 916294 ... 339s ..$ y : num [1:14658] 1.88 1.8 1.59 1.64 1.53 ... 339s ..$ index : int [1:14658] 1 2 3 4 5 6 7 8 9 10 ... 339s $ output :'data.frame': 4 obs. of 6 variables: 339s ..$ sampleName: chr [1:4] NA NA NA NA 339s ..$ chromosome: int [1:4] 1 NA 1 1 339s ..$ start : num [1:4] 5.54e+05 NA 1.42e+08 1.85e+08 339s ..$ end : num [1:4] 1.21e+08 NA 1.85e+08 2.47e+08 339s ..$ nbrOfLoci : int [1:4] 7586 NA 2681 4391 339s ..$ mean : num [1:4] 1.39 NA 2.07 2.63 339s $ segRows:'data.frame': 4 obs. of 2 variables: 339s ..$ startRow: int [1:4] 1 NA 7587 10268 339s ..$ endRow : int [1:4] 7586 NA 10267 14658 339s $ params :List of 5 339s ..$ alpha : num 0.009 339s ..$ undo : num 0 339s ..$ joinSegments : logi TRUE 339s ..$ knownSegments:'data.frame': 4 obs. of 3 variables: 339s .. ..$ chromosome: num [1:4] 1 1 2 1 339s .. ..$ start : num [1:4] -Inf -Inf -Inf 1.42e+08 339s .. ..$ end : num [1:4] 1.21e+08 Inf Inf Inf 339s ..$ seed : int [1:7] 10407 1066287653 -51199871 161854402 -1995183193 1503453565 -747102133 339s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 339s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.168 0 0.168 0 0 339s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 339s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 339s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 339s Identification of change points by total copy numbers...done 339s Restructure TCN segmentation results... 339s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean 339s 1 1 554484 120992603 7586 1.3853 339s 2 NA NA NA NA NA 339s 3 1 141510003 185449813 2681 2.0689 339s 4 1 185449813 247137334 4391 2.6341 339s Number of TCN segments: 4 339s Restructure TCN segmentation results...done 339s Total CN segment #1 ([ 554484,1.20993e+08]) of 4... 339s Number of TCN loci in segment: 7586 339s Locus data for TCN segment: 339s 'data.frame': 7586 obs. of 9 variables: 339s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 339s $ x : num 554484 730720 782343 878522 916294 ... 339s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 339s $ betaT : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 339s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 339s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 339s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 339s $ index : int 1 2 3 4 5 6 7 8 9 10 ... 339s $ rho : num NA NA NA NA NA ... 339s Number of loci: 7586 339s Number of SNPs: 2108 (27.79%) 339s Number of heterozygous SNPs: 2108 (100.00%) 339s Chromosome: 1 339s Segmenting DH signals... 339s Segmenting by CBS... 339s Chromosome: 1 339s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 339s Segmenting by CBS...done 339s List of 4 339s $ data :'data.frame': 7586 obs. of 4 variables: 339s ..$ chromosome: int [1:7586] 1 1 1 1 1 1 1 1 1 1 ... 339s ..$ x : num [1:7586] 554484 730720 782343 878522 916294 ... 339s ..$ y : num [1:7586] NA NA NA NA NA ... 339s ..$ index : int [1:7586] 1 2 3 4 5 6 7 8 9 10 ... 339s $ output :'data.frame': 1 obs. of 6 variables: 339s ..$ sampleName: chr NA 339s ..$ chromosome: int 1 339s ..$ start : num 554484 339s ..$ end : num 1.21e+08 339s ..$ nbrOfLoci : int 2108 339s ..$ mean : num 0.512 339s $ segRows:'data.frame': 1 obs. of 2 variables: 339s ..$ startRow: int 10 339s ..$ endRow : int 7574 339s $ params :List of 5 339s ..$ alpha : num 0.001 339s ..$ undo : num 0 339s ..$ joinSegments : logi TRUE 339s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 339s .. ..$ chromosome: int 1 339s .. ..$ start : num 554484 339s .. ..$ end : num 1.21e+08 339s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 339s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 339s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.047 0 0.048 0 0 339s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 339s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 339s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 339s DH segmentation (locally-indexed) rows: 339s startRow endRow 339s 1 10 7574 339s int [1:7586] 1 2 3 4 5 6 7 8 9 10 ... 339s DH segmentation rows: 339s startRow endRow 339s 1 10 7574 339s Segmenting DH signals...done 339s DH segmentation table: 339s dhStart dhEnd dhNbrOfLoci dhMean 339s 1 554484 120992603 2108 0.5116 339s startRow endRow 339s 1 10 7574 339s Rows: 339s [1] 1 339s TCN segmentation rows: 339s startRow endRow 339s 1 1 7586 339s TCN and DH segmentation rows: 339s startRow endRow 339s 1 1 7586 339s startRow endRow 339s 1 10 7574 339s NULL 339s TCN segmentation (expanded) rows: 339s startRow endRow 339s 1 1 7586 339s TCN and DH segmentation rows: 339s startRow endRow 339s 1 1 7586 339s 2 NA NA 339s 3 7587 10267 339s 4 10268 14658 339s startRow endRow 339s 1 10 7574 339s startRow endRow 339s 1 1 7586 339s Total CN segmentation table (expanded): 339s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 339s 1 1 554484 120992603 7586 1.3853 2108 2108 339s (TCN,DH) segmentation for one total CN segment: 339s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 339s 1 1 1 1 554484 120992603 7586 1.3853 2108 339s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 339s 1 2108 554484 120992603 2108 0.5116 339s Total CN segment #1 ([ 554484,1.20993e+08]) of 4...done 339s Total CN segment #2 ([ NA, NA]) of 4... 339s No signals to segment. Just a "splitter" segment. Skipping. 339s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 339s NA 2 1 NA NA NA NA NA 0 339s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 339s NA 0 NA NA 0 NA 339s Total CN segment #2 ([ NA, NA]) of 4...done 339s Total CN segment #3 ([1.4151e+08,1.8545e+08]) of 4... 339s Number of TCN loci in segment: 2681 339s Locus data for TCN segment: 339s 'data.frame': 2681 obs. of 9 variables: 339s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 339s $ x : num 1.43e+08 1.43e+08 1.43e+08 1.43e+08 1.44e+08 ... 339s $ CT : num 2.27 1.55 1.47 1.5 1.81 ... 339s $ betaT : num 0.34 0.55 0.048 0.813 0.575 ... 339s $ betaTN : num 0.441 0.629 -0.05 0.958 0.872 ... 339s $ betaN : num 0.3851 0.3933 0.0981 0.8552 0.7028 ... 339s $ muN : num 0.5 0.5 0 1 1 1 1 0.5 1 1 ... 339s $ index : int 7587 7588 7589 7590 7591 7592 7593 7594 7595 7596 ... 339s $ rho : num 0.117 0.258 NA NA NA ... 339s Number of loci: 2681 339s Number of SNPs: 777 (28.98%) 339s Number of heterozygous SNPs: 777 (100.00%) 339s Chromosome: 1 339s Segmenting DH signals... 339s Segmenting by CBS... 339s Chromosome: 1 339s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 339s Segmenting by CBS...done 339s List of 4 339s $ data :'data.frame': 2681 obs. of 4 variables: 339s ..$ chromosome: int [1:2681] 1 1 1 1 1 1 1 1 1 1 ... 339s ..$ x : num [1:2681] 1.43e+08 1.43e+08 1.43e+08 1.43e+08 1.44e+08 ... 339s ..$ y : num [1:2681] 0.117 0.258 NA NA NA ... 339s ..$ index : int [1:2681] 1 2 3 4 5 6 7 8 9 10 ... 339s $ output :'data.frame': 1 obs. of 6 variables: 339s ..$ sampleName: chr NA 339s ..$ chromosome: int 1 339s ..$ start : num 1.42e+08 339s ..$ end : num 1.85e+08 339s ..$ nbrOfLoci : int 777 339s ..$ mean : num 0.0973 339s $ segRows:'data.frame': 1 obs. of 2 variables: 339s ..$ startRow: int 1 339s ..$ endRow : int 2677 339s $ params :List of 5 339s ..$ alpha : num 0.001 339s ..$ undo : num 0 339s ..$ joinSegments : logi TRUE 339s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 339s .. ..$ chromosome: int 1 339s .. ..$ start : num 1.42e+08 339s .. ..$ end : num 1.85e+08 339s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 339s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 339s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.009 0 0.009 0 0 339s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 339s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 339s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 339s DH segmentation (locally-indexed) rows: 339s startRow endRow 339s 1 1 2677 339s int [1:2681] 7587 7588 7589 7590 7591 7592 7593 7594 7595 7596 ... 339s DH segmentation rows: 339s startRow endRow 339s 1 7587 10263 339s Segmenting DH signals...done 339s DH segmentation table: 339s dhStart dhEnd dhNbrOfLoci dhMean 339s 1 141510003 185449813 777 0.0973 339s startRow endRow 339s 1 7587 10263 339s Rows: 339s [1] 3 339s TCN segmentation rows: 339s startRow endRow 339s 3 7587 10267 339s TCN and DH segmentation rows: 339s startRow endRow 339s 3 7587 10267 339s startRow endRow 339s 1 7587 10263 339s startRow endRow 339s 1 1 7586 339s NA NA NA 339s TCN segmentation (expanded) rows: 339s startRow endRow 339s 1 1 7586 339s NA NA NA 339s 3 7587 10267 339s TCN and DH segmentation rows: 339s startRow endRow 339s 1 1 7586 339s 2 NA NA 339s 3 7587 10267 339s 4 10268 14658 339s startRow endRow 339s 1 10 7574 339s 2 NA NA 339s 3 7587 10263 339s startRow endRow 339s 1 1 7586 339s 2 NA NA 339s 3 7587 10267 339s Total CN segmentation table (expanded): 339s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 339s 3 1 141510003 185449813 2681 2.0689 777 777 339s (TCN,DH) segmentation for one total CN segment: 339s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 339s 3 3 1 1 141510003 185449813 2681 2.0689 777 339s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 339s 3 777 141510003 185449813 777 0.0973 339s Total CN segment #3 ([1.4151e+08,1.8545e+08]) of 4...done 339s Total CN segment #4 ([1.8545e+08,2.47137e+08]) of 4... 339s Number of TCN loci in segment: 4391 339s Locus data for TCN segment: 339s 'data.frame': 4391 obs. of 9 variables: 339s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 339s $ x : num 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 339s $ CT : num 2.93 2.15 2.82 2.93 2.46 ... 339s $ betaT : num 0.0811 0.5154 0.9473 0.3734 0.7506 ... 339s $ betaTN : num -0.169 0.609 1.028 0.525 0.968 ... 339s $ betaN : num 0.25 0.38 0.919 0.34 0.783 ... 339s $ muN : num 0 0.5 1 0.5 1 1 0 1 0 1 ... 339s $ index : int 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 339s $ rho : num NA 0.2186 NA 0.0503 NA ... 339s Number of loci: 4391 339s Number of SNPs: 1311 (29.86%) 339s Number of heterozygous SNPs: 1311 (100.00%) 339s Chromosome: 1 339s Segmenting DH signals... 339s Segmenting by CBS... 339s Chromosome: 1 339s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 339s Segmenting by CBS...done 339s List of 4 339s $ data :'data.frame': 4391 obs. of 4 variables: 339s ..$ chromosome: int [1:4391] 1 1 1 1 1 1 1 1 1 1 ... 339s ..$ x : num [1:4391] 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 339s ..$ y : num [1:4391] NA 0.2186 NA 0.0503 NA ... 339s ..$ index : int [1:4391] 1 2 3 4 5 6 7 8 9 10 ... 339s $ output :'data.frame': 1 obs. of 6 variables: 339s ..$ sampleName: chr NA 339s ..$ chromosome: int 1 339s ..$ start : num 1.85e+08 339s ..$ end : num 2.47e+08 339s ..$ nbrOfLoci : int 1311 339s ..$ mean : num 0.23 339s $ segRows:'data.frame': 1 obs. of 2 variables: 339s ..$ startRow: int 2 339s ..$ endRow : int 4388 339s $ params :List of 5 339s ..$ alpha : num 0.001 339s ..$ undo : num 0 339s ..$ joinSegments : logi TRUE 339s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 339s .. ..$ chromosome: int 1 339s .. ..$ start : num 1.85e+08 339s .. ..$ end : num 2.47e+08 339s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 339s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 339s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.018 0 0.018 0 0 339s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 339s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 339s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 339s DH segmentation (locally-indexed) rows: 339s startRow endRow 339s 1 2 4388 339s int [1:4391] 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 339s DH segmentation rows: 339s startRow endRow 339s 1 10269 14655 339s Segmenting DH signals...done 339s DH segmentation table: 339s dhStart dhEnd dhNbrOfLoci dhMean 339s 1 185449813 247137334 1311 0.2295 339s startRow endRow 339s 1 10269 14655 339s Rows: 339s [1] 4 339s TCN segmentation rows: 339s startRow endRow 339s 4 10268 14658 339s TCN and DH segmentation rows: 339s startRow endRow 339s 4 10268 14658 339s startRow endRow 339s 1 10269 14655 339s startRow endRow 339s 1 1 7586 339s 2 NA NA 339s 3 7587 10267 339s TCN segmentation (expanded) rows: 339s startRow endRow 339s 1 1 7586 339s 2 NA NA 339s 3 7587 10267 339s 4 10268 14658 339s TCN and DH segmentation rows: 339s startRow endRow 339s 1 1 7586 339s 2 NA NA 339s 3 7587 10267 339s 4 10268 14658 339s startRow endRow 339s 1 10 7574 339s 2 NA NA 339s 3 7587 10263 339s 4 10269 14655 339s startRow endRow 339s 1 1 7586 339s 2 NA NA 339s 3 7587 10267 339s 4 10268 14658 339s Total CN segmentation table (expanded): 339s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 339s 4 1 185449813 247137334 4391 2.6341 1311 1311 339s (TCN,DH) segmentation for one total CN segment: 339s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 339s 4 4 1 1 185449813 247137334 4391 2.6341 1311 339s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 339s 4 1311 185449813 247137334 1311 0.2295 339s Total CN segment #4 ([1.8545e+08,2.47137e+08]) of 4...done 339s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 339s 1 1 1 1 554484 120992603 7586 1.3853 2108 339s 2 NA 2 1 NA NA NA NA 0 339s 3 1 3 1 141510003 185449813 2681 2.0689 777 339s 4 1 4 1 185449813 247137334 4391 2.6341 1311 339s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 339s 1 2108 554484 120992603 2108 0.5116 339s 2 0 NA NA 0 NA 339s 3 777 141510003 185449813 777 0.0973 339s 4 1311 185449813 247137334 1311 0.2295 339s Calculating (C1,C2) per segment... 339s Calculating (C1,C2) per segment...done 339s Number of segments: 4 339s Segmenting paired tumor-normal signals using Paired PSCBS...done 339s Post-segmenting TCNs... 339s Number of segments: 3 339s Number of chromosomes: 1 339s [1] 1 339s Chromosome 1 ('chr01') of 1... 339s Rows: 339s [1] 1 2 3 339s Number of segments: 3 339s TCN segment #1 ('1') of 3... 339s Nothing todo. Only one DH segmentation. Skipping. 339s TCN segment #1 ('1') of 3...done 339s TCN segment #2 ('3') of 3... 339s Nothing todo. Only one DH segmentation. Skipping. 339s TCN segment #2 ('3') of 3...done 339s TCN segment #3 ('4') of 3... 339s Nothing todo. Only one DH segmentation. Skipping. 339s TCN segment #3 ('4') of 3...done 339s Chromosome 1 ('chr01') of 1...done 339s Update (C1,C2) per segment... 339s Update (C1,C2) per segment...done 339s Post-segmenting TCNs...done 339s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 339s 1 1 1 1 554484 120992603 7586 1.3853 2108 339s 2 NA 2 1 NA NA NA NA 0 339s 3 1 3 1 141510003 185449813 2681 2.0689 777 339s 4 1 4 1 185449813 247137334 4391 2.6341 1311 339s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 339s 1 2108 554484 120992603 2108 0.5116 0.3382903 1.047010 339s 2 0 NA NA 0 NA NA NA 339s 3 777 141510003 185449813 777 0.0973 0.9337980 1.135102 339s 4 1311 185449813 247137334 1311 0.2295 1.0147870 1.619313 339s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 339s 1 1 1 1 554484 120992603 7586 1.3853 2108 339s 2 NA 2 1 NA NA NA NA 0 339s 3 1 3 1 141510003 185449813 2681 2.0689 777 339s 4 1 4 1 185449813 247137334 4391 2.6341 1311 339s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 339s 1 2108 554484 120992603 2108 0.5116 0.3382903 1.047010 339s 2 0 NA NA 0 NA NA NA 339s 3 777 141510003 185449813 777 0.0973 0.9337980 1.135102 339s 4 1311 185449813 247137334 1311 0.2295 1.0147870 1.619313 339s > print(fit) 339s chromosome tcnId dhId start end tcnNbrOfLoci tcnMean tcnNbrOfSNPs 339s 1 1 1 1 554484 120992603 7586 1.3853 2108 339s 2 NA 2 1 NA NA NA NA 0 339s 3 1 3 1 141510003 185449813 2681 2.0689 777 339s 4 1 4 1 185449813 247137334 4391 2.6341 1311 339s tcnNbrOfHets dhNbrOfLoci dhMean c1Mean c2Mean 339s 1 2108 2108 0.5116 0.3382903 1.047010 339s 2 0 0 NA NA NA 339s 3 777 777 0.0973 0.9337980 1.135102 339s 4 1311 1311 0.2295 1.0147870 1.619313 339s > 339s > # Plot results 339s > dev.set(2L) 339s null device 339s 1 339s > plotTracks(fit) 339s > abline(v=c(knownSegments$start, knownSegments$end)/1e6, lty=3) 339s > 339s > # Sanity check 339s > stopifnot(nbrOfSegments(fit) == nSegs) 339s > 339s > fit1 <- fit 339s > 339s > 339s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 339s > # (b) Segment also the centromere (which will become NAs) 339s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 339s > knownSegments <- data.frame( 339s + chromosome = c( 1, 1, 1), 339s + start = c( -Inf, 120992604, 141510003), 339s + end = c(120992603, 141510002, +Inf) 339s + ) 339s > 339s > 339s > # Paired PSCBS segmentation 339s > fit <- segmentByPairedPSCBS(dataS, knownSegments=knownSegments, 339s + seed=0xBEEF, verbose=-10) 339s Segmenting paired tumor-normal signals using Paired PSCBS... 339s Calling genotypes from normal allele B fractions... 339s num [1:14670] 0.8274 0.5072 0.1671 0.1609 0.0421 ... 339s Called genotypes: 339s num [1:14670] 1 0.5 0 0 0 0 1 0 1 0.5 ... 339s - attr(*, "modelFit")=List of 1 339s ..$ :List of 7 339s .. ..$ flavor : chr "density" 339s .. ..$ cn : int 2 339s .. ..$ nbrOfGenotypeGroups: int 3 339s .. ..$ tau : num [1:2] 0.315 0.677 339s .. ..$ n : int 14640 339s .. ..$ fit :Classes 'PeaksAndValleys' and 'data.frame': 5 obs. of 3 variables: 339s .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 339s .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 339s .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 339s .. ..$ fitValleys :Classes 'PeaksAndValleys' and 'data.frame': 2 obs. of 3 variables: 339s .. .. ..$ type : chr [1:2] "valley" "valley" 339s .. .. ..$ x : num [1:2] 0.315 0.677 339s .. .. ..$ density: num [1:2] 0.522 0.551 339s ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 339s muN 339s 0 0.5 1 339s 5221 4198 5251 339s Calling genotypes from normal allele B fractions...done 339s Normalizing betaT using betaN (TumorBoost)... 339s Normalized BAFs: 339s num [1:14670] 0.9301 0.1667 0.0685 0.0995 0.0155 ... 339s - attr(*, "modelFit")=List of 5 339s ..$ method : chr "normalizeTumorBoost" 339s ..$ flavor : chr "v4" 339s ..$ delta : num [1:14670] -0.17264 0.00239 0.1671 0.16085 0.04213 ... 339s .. ..- attr(*, "modelFit")=List of 1 339s .. .. ..$ :List of 7 339s .. .. .. ..$ flavor : chr "density" 339s .. .. .. ..$ cn : int 2 339s .. .. .. ..$ nbrOfGenotypeGroups: int 3 339s .. .. .. ..$ tau : num [1:2] 0.315 0.677 339s .. .. .. ..$ n : int 14640 339s .. .. .. ..$ fit :Classes 'PeaksAndValleys' and 'data.frame': 5 obs. of 3 variables: 339s .. .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 339s .. .. .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 339s .. .. .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 339s .. .. .. ..$ fitValleys :Classes 'PeaksAndValleys' and 'data.frame': 2 obs. of 3 variables: 339s .. .. .. .. ..$ type : chr [1:2] "valley" "valley" 339s .. .. .. .. ..$ x : num [1:2] 0.315 0.677 339s .. .. .. .. ..$ density: num [1:2] 0.522 0.551 339s .. .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 339s ..$ preserveScale: logi FALSE 339s ..$ scaleFactor : num NA 339s Normalizing betaT using betaN (TumorBoost)...done 339s Setup up data... 339s 'data.frame': 14670 obs. of 7 variables: 339s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 339s $ x : num 1145994 2941694 3710825 4240737 4276892 ... 339s $ CT : num 1.63 1.4 1.41 1.17 1.16 ... 339s $ betaT : num 0.7574 0.169 0.2357 0.2604 0.0576 ... 339s $ betaTN : num 0.9301 0.1667 0.0685 0.0995 0.0155 ... 339s ..- attr(*, "modelFit")=List of 5 339s .. ..$ method : chr "normalizeTumorBoost" 339s .. ..$ flavor : chr "v4" 339s .. ..$ delta : num [1:14670] -0.17264 0.00239 0.1671 0.16085 0.04213 ... 339s .. .. ..- attr(*, "modelFit")=List of 1 339s .. .. .. ..$ :List of 7 339s .. .. .. .. ..$ flavor : chr "density" 339s .. .. .. .. ..$ cn : int 2 339s .. .. .. .. ..$ nbrOfGenotypeGroups: int 3 339s .. .. .. .. ..$ tau : + echo 0num [1:2] 0.315 0.677 339s .. .. .. .. ..$ n : int 14640 339s .. .. .. .. ..$ fit :Classes 'PeaksAndValleys' and 'data.frame': 5 obs. of 3 variables: 339s .. .. .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 339s .. .. .. .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 339s .. .. .. .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 339s .. .. .. .. ..$ fitValleys :Classes 'PeaksAndValleys' and 'data.frame': 2 obs. of 3 variables: 339s .. .. .. .. .. ..$ type : chr [1:2] "valley" "valley" 339s .. .. .. .. .. ..$ x : num [1:2] 0.315 0.677 339s .. .. .. .. .. ..$ density: num [1:2] 0.522 0.551 339s .. .. .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 339s .. ..$ preserveScale: logi FALSE 339s .. ..$ scaleFactor : num NA 339s $ betaN : num 0.8274 0.5072 0.1671 0.1609 0.0421 ... 339s $ muN : num 1 0.5 0 0 0 0 1 0 1 0.5 ... 339s ..- attr(*, "modelFit")=List of 1 339s .. ..$ :List of 7 339s .. .. ..$ flavor : chr "density" 339s .. .. ..$ cn : int 2 339s .. .. ..$ nbrOfGenotypeGroups: int 3 339s .. .. ..$ tau : num [1:2] 0.315 0.677 339s .. .. ..$ n : int 14640 339s .. .. ..$ fit :Classes 'PeaksAndValleys' and 'data.frame': 5 obs. of 3 variables: 339s .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 339s .. .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 339s .. .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 339s .. .. ..$ fitValleys :Classes 'PeaksAndValleys' and 'data.frame': 2 obs. of 3 variables: 339s .. .. .. ..$ type : chr [1:2] "valley" "valley" 339s .. .. .. ..$ x : num [1:2] 0.315 0.677 339s .. .. .. ..$ density: num [1:2] 0.522 0.551 339s .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 339s Setup up data...done 339s Dropping loci for which TCNs are missing... 339s Number of loci dropped: 12 339s Dropping loci for which TCNs are missing...done 339s Ordering data along genome... 339s 'data.frame': 14658 obs. of 7 variables: 339s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 339s $ x : num 554484 730720 782343 878522 916294 ... 339s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 339s $ betaT : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 339s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 339s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 339s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 339s Ordering data along genome...done 339s Keeping only current chromosome for 'knownSegments'... 339s Chromosome: 1 339s Known segments for this chromosome: 339s chromosome start end 339s 1 1 -Inf 120992603 339s 2 1 120992604 141510002 339s 3 1 141510003 Inf 339s Keeping only current chromosome for 'knownSegments'...done 339s alphaTCN: 0.009 339s alphaDH: 0.001 339s Number of loci: 14658 339s Calculating DHs... 339s Number of SNPs: 14658 339s Number of heterozygous SNPs: 4196 (28.63%) 339s Normalized DHs: 339s num [1:14658] NA NA NA NA NA ... 339s Calculating DHs...done 339s Random seed temporarily set (seed=c(48879), kind="L'Ecuyer-CMRG") 339s Produced 2 seeds from this stream for future usage 339s Identification of change points by total copy numbers... 339s Segmenting by CBS... 339s Chromosome: 1 339s Segmenting multiple segments on current chromosome... 339s Number of segments: 3 339s Random seed temporarily set (seed=c(10407, 1066287653, -51199871, 161854402, -1995183193, 1503453565, -747102133), kind="L'Ecuyer-CMRG") 339s Produced 3 seeds from this stream for future usage 339s Segmenting by CBS... 339s Chromosome: 1 339s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 339s Segmenting by CBS...done 339s Segmenting by CBS... 339s Chromosome: 1 339s Random seed temporarily set (seed=c(10407, -1924040949, -1632234809, -437763632, -1464377300, 676654412, 2080370711), kind="L'Ecuyer-CMRG") 339s Segmenting by CBS...done 339s Segmenting multiple segments on current chromosome...done 339s Segmenting by CBS...done 339s List of 4 339s $ data :'data.frame': 14658 obs. of 4 variables: 339s ..$ chromosome: int [1:14658] 1 1 1 1 1 1 1 1 1 1 ... 339s ..$ x : num [1:14658] 554484 730720 782343 878522 916294 ... 339s ..$ y : num [1:14658] 1.88 1.8 1.59 1.64 1.53 ... 339s ..$ index : int [1:14658] 1 2 3 4 5 6 7 8 9 10 ... 339s $ output :'data.frame': 4 obs. of 6 variables: 339s ..$ sampleName: chr [1:4] NA NA NA NA 339s ..$ chromosome: num [1:4] 1 1 1 1 339s ..$ start : num [1:4] 5.54e+05 1.21e+08 1.42e+08 1.85e+08 339s ..$ end : num [1:4] 1.21e+08 1.42e+08 1.85e+08 2.47e+08 339s ..$ nbrOfLoci : int [1:4] 7586 0 2681 4391 339s ..$ mean : num [1:4] 1.39 NA 2.07 2.63 339s $ segRows:'data.frame': 4 obs. of 2 variables: 339s ..$ startRow: int [1:4] 1 NA 7587 10268 339s ..$ endRow : int [1:4] 7586 NA 10267 14658 339s $ params :List of 5 339s ..$ alpha : num 0.009 339s ..$ undo : num 0 339s ..$ joinSegments : logi TRUE 339s ..$ knownSegments:'data.frame': 4 obs. of 3 variables: 339s .. ..$ chromosome: num [1:4] 1 1 2 1 339s .. ..$ start : num [1:4] -Inf -Inf -Inf 1.42e+08 339s .. ..$ end : num [1:4] 1.21e+08 Inf Inf Inf 339s ..$ seed : int [1:7] 10407 1066287653 -51199871 161854402 -1995183193 1503453565 -747102133 339s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 339s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.165 0 0.166 0 0 339s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 339s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 339s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 339s Identification of change points by total copy numbers...done 339s Restructure TCN segmentation results... 339s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean 339s 1 1 554484 120992603 7586 1.3853 339s 2 1 120992604 141510002 0 NA 339s 3 1 141510003 185449813 2681 2.0689 339s 4 1 185449813 247137334 4391 2.6341 339s Number of TCN segments: 4 339s Restructure TCN segmentation results...done 339s Total CN segment #1 ([ 554484,1.20993e+08]) of 4... 339s Number of TCN loci in segment: 7586 339s Locus data for TCN segment: 339s 'data.frame': 7586 obs. of 9 variables: 339s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 339s $ x : num 554484 730720 782343 878522 916294 ... 339s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 339s $ betaT : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 339s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 339s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 339s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 339s $ index : int 1 2 3 4 5 6 7 8 9 10 ... 339s $ rho : num NA NA NA NA NA ... 339s Number of loci: 7586 339s Number of SNPs: 2108 (27.79%) 339s Number of heterozygous SNPs: 2108 (100.00%) 339s Chromosome: 1 339s Segmenting DH signals... 339s Segmenting by CBS... 339s Chromosome: 1 339s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 339s Segmenting by CBS...done 339s List of 4 339s $ data :'data.frame': 7586 obs. of 4 variables: 339s ..$ chromosome: int [1:7586] 1 1 1 1 1 1 1 1 1 1 ... 339s ..$ x : num [1:7586] 554484 730720 782343 878522 916294 ... 339s ..$ y : num [1:7586] NA NA NA NA NA ... 339s ..$ index : int [1:7586] 1 2 3 4 5 6 7 8 9 10 ... 339s $ output :'data.frame': 1 obs. of 6 variables: 339s ..$ sampleName: chr NA 339s ..$ chromosome: int 1 339s ..$ start : num 554484 339s ..$ end : num 1.21e+08 339s ..$ nbrOfLoci : int 2108 339s ..$ mean : num 0.512 339s $ segRows:'data.frame': 1 obs. of 2 variables: 339s ..$ startRow: int 10 339s ..$ endRow : int 7574 339s $ params :List of 5 339s ..$ alpha : num 0.001 339s ..$ undo : num 0 339s ..$ joinSegments : logi TRUE 339s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 339s .. ..$ chromosome: int 1 339s .. ..$ start : num 554484 339s .. ..$ end : num 1.21e+08 339s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 339s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 339s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.048 0 0.047 0 0 339s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 339s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 339s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 339s DH segmentation (locally-indexed) rows: 339s startRow endRow 339s 1 10 7574 339s int [1:7586] 1 2 3 4 5 6 7 8 9 10 ... 339s DH segmentation rows: 339s startRow endRow 339s 1 10 7574 339s Segmenting DH signals...done 339s DH segmentation table: 339s dhStart dhEnd dhNbrOfLoci dhMean 339s 1 554484 120992603 2108 0.5116 339s startRow endRow 339s 1 10 7574 339s Rows: 339s [1] 1 339s TCN segmentation rows: 339s startRow endRow 339s 1 1 7586 339s TCN and DH segmentation rows: 339s startRow endRow 339s 1 1 7586 339s startRow endRow 339s 1 10 7574 339s NULL 339s TCN segmentation (expanded) rows: 339s startRow endRow 339s 1 1 7586 339s TCN and DH segmentation rows: 339s startRow endRow 339s 1 1 7586 339s 2 NA NA 339s 3 7587 10267 339s 4 10268 14658 339s startRow endRow 339s 1 10 7574 339s startRow endRow 339s 1 1 7586 339s Total CN segmentation table (expanded): 339s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 339s 1 1 554484 120992603 7586 1.3853 2108 2108 339s (TCN,DH) segmentation for one total CN segment: 339s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 339s 1 1 1 1 554484 120992603 7586 1.3853 2108 339s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 339s 1 2108 554484 120992603 2108 0.5116 339s Total CN segment #1 ([ 554484,1.20993e+08]) of 4...done 339s Total CN segment #2 ([1.20993e+08,1.4151e+08]) of 4... 339s Number of TCN loci in segment: 0 339s Locus data for TCN segment: 339s 'data.frame': 0 obs. of 9 variables: 339s $ chromosome: int 339s $ x : num 339s $ CT : num 339s $ betaT : num 339s $ betaTN : num 339s $ betaN : num 339s $ muN : num 339s $ index : int 339s $ rho : num 339s Number of loci: 0 339s Number of SNPs: 0 (NaN%) 339s Number of heterozygous SNPs: 0 (NaN%) 339s Chromosome: 1 339s Segmenting DH signals... 339s Segmenting by CBS... 339s Chromosome: NA 339s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 339s Segmenting by CBS...done 339s List of 4 339s $ data :'data.frame': 0 obs. of 4 variables: 339s ..$ chromosome: int(0) 339s ..$ x : num(0) 339s ..$ y : num(0) 339s ..$ index : int(0) 339s $ output :'data.frame': 0 obs. of 6 variables: 339s ..$ sampleName: chr(0) 339s ..$ chromosome: num(0) 339s ..$ start : num(0) 339s ..$ end : num(0) 339s ..$ nbrOfLoci : int(0) 339s ..$ mean : num(0) 339s $ segRows:'data.frame': 0 obs. of 2 variables: 339s ..$ startRow: int(0) 339s ..$ endRow : int(0) 339s $ params :List of 5 339s ..$ alpha : num 0.001 339s ..$ undo : num 0 339s ..$ joinSegments : logi TRUE 339s ..$ knownSegments:'data.frame': 0 obs. of 3 variables: 339s .. ..$ chromosome: int(0) 339s .. ..$ start : num(0) 339s .. ..$ end : num(0) 339s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 339s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 339s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.001 0 0.002 0 0 339s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 339s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 339s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 339s DH segmentation (locally-indexed) rows: 339s [1] startRow endRow 339s <0 rows> (or 0-length row.names) 339s int(0) 339s DH segmentation rows: 339s [1] startRow endRow 339s <0 rows> (or 0-length row.names) 339s Segmenting DH signals...done 339s DH segmentation table: 339s dhStart dhEnd dhNbrOfLoci dhMean 339s NA NA NA NA NA 339s startRow endRow 339s NA NA NA 339s Rows: 339s [1] 2 339s TCN segmentation rows: 339s startRow endRow 339s 2 NA NA 339s TCN and DH segmentation rows: 339s startRow endRow 339s 2 NA NA 339s startRow endRow 339s NA NA NA 339s startRow endRow 339s 1 1 7586 339s TCN segmentation (expanded) rows: 339s startRow endRow 339s 1 1 7586 339s 2 NA NA 339s TCN and DH segmentation rows: 339s startRow endRow 339s 1 1 7586 339s 2 NA NA 339s 3 7587 10267 339s 4 10268 14658 339s startRow endRow 339s 1 10 7574 339s 2 NA NA 339s startRow endRow 339s 1 1 7586 339s 2 NA NA 339s Total CN segmentation table (expanded): 339s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 339s 2 1 120992604 141510002 0 NA 0 0 339s (TCN,DH) segmentation for one total CN segment: 339s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 339s 2 2 1 1 120992604 141510002 0 NA 0 339s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 339s 2 0 NA NA NA NA 339s Total CN segment #2 ([1.20993e+08,1.4151e+08]) of 4...done 339s Total CN segment #3 ([1.4151e+08,1.8545e+08]) of 4... 339s Number of TCN loci in segment: 2681 339s Locus data for TCN segment: 339s 'data.frame': 2681 obs. of 9 variables: 339s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 339s $ x : num 1.43e+08 1.43e+08 1.43e+08 1.43e+08 1.44e+08 ... 339s $ CT : num 2.27 1.55 1.47 1.5 1.81 ... 339s $ betaT : num 0.34 0.55 0.048 0.813 0.575 ... 339s $ betaTN : num 0.441 0.629 -0.05 0.958 0.872 ... 339s $ betaN : num 0.3851 0.3933 0.0981 0.8552 0.7028 ... 339s $ muN : num 0.5 0.5 0 1 1 1 1 0.5 1 1 ... 339s $ index : int 7587 7588 7589 7590 7591 7592 7593 7594 7595 7596 ... 339s $ rho : num 0.117 0.258 NA NA NA ... 339s Number of loci: 2681 339s Number of SNPs: 777 (28.98%) 339s Number of heterozygous SNPs: 777 (100.00%) 339s Chromosome: 1 339s Segmenting DH signals... 339s Segmenting by CBS... 339s Chromosome: 1 339s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 339s Segmenting by CBS...done 339s List of 4 339s $ data :'data.frame': 2681 obs. of 4 variables: 339s ..$ chromosome: int [1:2681] 1 1 1 1 1 1 1 1 1 1 ... 339s ..$ x : num [1:2681] 1.43e+08 1.43e+08 1.43e+08 1.43e+08 1.44e+08 ... 339s ..$ y : num [1:2681] 0.117 0.258 NA NA NA ... 339s ..$ index : int [1:2681] 1 2 3 4 5 6 7 8 9 10 ... 339s $ output :'data.frame': 1 obs. of 6 variables: 339s ..$ sampleName: chr NA 339s ..$ chromosome: int 1 339s ..$ start : num 1.42e+08 339s ..$ end : num 1.85e+08 339s ..$ nbrOfLoci : int 777 339s ..$ mean : num 0.0973 339s $ segRows:'data.frame': 1 obs. of 2 variables: 339s ..$ startRow: int 1 339s ..$ endRow : int 2677 339s $ params :List of 5 339s ..$ alpha : num 0.001 339s ..$ undo : num 0 339s ..$ joinSegments : logi TRUE 339s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 339s .. ..$ chromosome: int 1 339s .. ..$ start : num 1.42e+08 339s .. ..$ end : num 1.85e+08 339s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 339s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 339s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.01 0 0.009 0 0 339s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 339s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 339s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 339s DH segmentation (locally-indexed) rows: 339s startRow endRow 339s 1 1 2677 339s int [1:2681] 7587 7588 7589 7590 7591 7592 7593 7594 7595 7596 ... 339s DH segmentation rows: 339s startRow endRow 339s 1 7587 10263 339s Segmenting DH signals...done 339s DH segmentation table: 339s dhStart dhEnd dhNbrOfLoci dhMean 339s 1 141510003 185449813 777 0.0973 339s startRow endRow 339s 1 7587 10263 339s Rows: 339s + 339s [1] 3 339s TCN segmentation rows: 339s startRow endRow 339s 3 7587 10267 339s TCN and DH segmentation rows: 339s startRow endRow 339s 3 7587 10267 339s startRow endRow 339s 1 7587 10263 339s startRow endRow 339s 1 1 7586 339s 2 NA NA 339s TCN segmentation (expanded) rows: 339s startRow endRow 339s 1 1 7586 339s 2 NA NA 339s 3 7587 10267 339s TCN and DH segmentation rows: 339s startRow endRow 339s 1 1 7586 339s 2 NA NA 339s 3 7587 10267 339s 4 10268 14658 339s startRow endRow 339s 1 10 7574 339s 2 NA NA 339s 3 7587 10263 339s startRow endRow 339s 1 1 7586 339s 2 NA NA 339s 3 7587 10267 339s Total CN segmentation table (expanded): 339s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 339s 3 1 141510003 185449813 2681 2.0689 777 777 339s (TCN,DH) segmentation for one total CN segment: 339s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 339s 3 3 1 1 141510003 185449813 2681 2.0689 777 339s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 339s 3 777 141510003 185449813 777 0.0973 339s Total CN segment #3 ([1.4151e+08,1.8545e+08]) of 4...done 339s Total CN segment #4 ([1.8545e+08,2.47137e+08]) of 4... 339s Number of TCN loci in segment: 4391 339s Locus data for TCN segment: 339s 'data.frame': 4391 obs. of 9 variables: 339s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 339s $ x : num 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 339s $ CT : num 2.93 2.15 2.82 2.93 2.46 ... 339s $ betaT : num 0.0811 0.5154 0.9473 0.3734 0.7506 ... 339s $ betaTN : num -0.169 0.609 1.028 0.525 0.968 ... 339s $ betaN : num 0.25 0.38 0.919 0.34 0.783 ... 339s $ muN : num 0 0.5 1 0.5 1 1 0 1 0 1 ... 339s $ index : int 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 339s $ rho : num NA 0.2186 NA 0.0503 NA ... 339s Number of loci: 4391 339s Number of SNPs: 1311 (29.86%) 339s Number of heterozygous SNPs: 1311 (100.00%) 339s Chromosome: 1 339s Segmenting DH signals... 339s Segmenting by CBS... 339s Chromosome: 1 339s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 339s Segmenting by CBS...done 339s List of 4 339s $ data :'data.frame': 4391 obs. of 4 variables: 339s ..$ chromosome: int [1:4391] 1 1 1 1 1 1 1 1 1 1 ... 339s ..$ x : num [1:4391] 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 339s ..$ y : num [1:4391] NA 0.2186 NA 0.0503 NA ... 339s ..$ index : int [1:4391] 1 2 3 4 5 6 7 8 9 10 ... 339s $ output :'data.frame': 1 obs. of 6 variables: 339s ..$ sampleName: chr NA 339s ..$ chromosome: int 1 339s ..$ start : num 1.85e+08 339s ..$ end : num 2.47e+08 339s ..$ nbrOfLoci : int 1311 339s ..$ mean : num 0.23 339s $ segRows:'data.frame': 1 obs. of 2 variables: 339s ..$ startRow: int 2 339s ..$ endRow : int 4388 339s $ params :List of 5 339s ..$ alpha : num 0.001 339s ..$ undo : num 0 339s ..$ joinSegments : logi TRUE 339s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 339s .. ..$ chromosome: int 1 339s .. ..$ start : num 1.85e+08 339s .. ..$ end : num 2.47e+08 339s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 339s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 339s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.018 0 0.018 0 0 339s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 339s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 339s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 339s DH segmentation (locally-indexed) rows: 339s startRow endRow 339s 1 2 4388 339s int [1:4391] 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 339s DH segmentation rows: 339s startRow endRow 339s 1 10269 14655 339s Segmenting DH signals...done 339s DH segmentation table: 339s dhStart dhEnd dhNbrOfLoci dhMean 339s 1 185449813 247137334 1311 0.2295 339s startRow endRow 339s 1 10269 14655 339s Rows: 339s [1] 4 339s TCN segmentation rows: 339s startRow endRow 339s 4 10268 14658 339s TCN and DH segmentation rows: 339s startRow endRow 339s 4 10268 14658 339s startRow endRow 339s 1 10269 14655 339s startRow endRow 339s 1 1 7586 339s 2 NA NA 339s 3 7587 10267 339s TCN segmentation (expanded) rows: 339s startRow endRow 339s 1 1 7586 339s 2 NA NA 339s 3 7587 10267 339s 4 10268 14658 339s TCN and DH segmentation rows: 339s startRow endRow 339s 1 1 7586 339s 2 NA NA 339s 3 7587 10267 339s 4 10268 14658 339s startRow endRow 339s 1 10 7574 339s 2 NA NA 339s 3 7587 10263 339s 4 10269 14655 339s startRow endRow 339s 1 1 7586 339s 2 NA NA 339s 3 7587 10267 339s 4 10268 14658 339s Total CN segmentation table (expanded): 339s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 339s 4 1 185449813 247137334 4391 2.6341 1311 1311 339s (TCN,DH) segmentation for one total CN segment: 339s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 339s 4 4 1 1 185449813 247137334 4391 2.6341 1311 339s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 339s 4 1311 185449813 247137334 1311 0.2295 339s Total CN segment #4 ([1.8545e+08,2.47137e+08]) of 4...done 339s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 339s 1 1 1 1 554484 120992603 7586 1.3853 2108 339s 2 1 2 1 120992604 141510002 0 NA 0 339s 3 1 3 1 141510003 185449813 2681 2.0689 777 339s 4 1 4 1 185449813 247137334 4391 2.6341 1311 339s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 339s 1 2108 554484 120992603 2108 0.5116 339s 2 0 NA NA NA NA 339s 3 777 141510003 185449813 777 0.0973 339s 4 1311 185449813 247137334 1311 0.2295 339s Calculating (C1,C2) per segment... 339s Calculating (C1,C2) per segment...done 339s Number of segments: 4 339s Segmenting paired tumor-normal signals using Paired PSCBS...done 339s Post-segmenting TCNs... 339s Number of segments: 4 339s Number of chromosomes: 1 339s [1] 1 339s Chromosome 1 ('chr01') of 1... 339s Rows: 339s [1] 1 2 3 4 339s Number of segments: 4 339s TCN segment #1 ('1') of 4... 339s Nothing todo. Only one DH segmentation. Skipping. 339s TCN segment #1 ('1') of 4...done 339s TCN segment #2 ('2') of 4... 339s Nothing todo. Only one DH segmentation. Skipping. 339s TCN segment #2 ('2') of 4...done 339s TCN segment #3 ('3') of 4... 339s Nothing todo. Only one DH segmentation. Skipping. 339s TCN segment #3 ('3') of 4...done 339s TCN segment #4 ('4') of 4... 339s Nothing todo. Only one DH segmentation. Skipping. 339s TCN segment #4 ('4') of 4...done 339s Chromosome 1 ('chr01') of 1...done 339s Update (C1,C2) per segment... 339s Update (C1,C2) per segment...done 339s Post-segmenting TCNs...done 339s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 339s 1 1 1 1 554484 120992603 7586 1.3853 2108 339s 2 1 2 1 120992604 141510002 0 NA 0 339s 3 1 3 1 141510003 185449813 2681 2.0689 777 339s 4 1 4 1 185449813 247137334 4391 2.6341 1311 339s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 339s 1 2108 554484 120992603 2108 0.5116 0.3382903 1.047010 339s 2 0 NA NA NA NA NA NA 339s 3 777 141510003 185449813 777 0.0973 0.9337980 1.135102 339s 4 1311 185449813 247137334 1311 0.2295 1.0147870 1.619313 339s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 339s 1 1 1 1 554484 120992603 7586 1.3853 2108 339s 2 1 2 1 120992604 141510002 0 NA 0 339s 3 1 3 1 141510003 185449813 2681 2.0689 777 339s rm4 1 4 1 185449813 247137334 4391 2.6341 1311 339s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 339s 1 2108 554484 120992603 2108 0.5116 0.3382903 1.047010 339s 2 0 NA NA NA NA NA NA 339s 3 777 141510003 185449813 777 0.0973 0.9337980 1.135102 339s 4 1311 185449813 247137334 1311 0.2295 1.0147870 1.619313 339s > print(fit) 339s chromosome tcnId dhId start end tcnNbrOfLoci tcnMean tcnNbrOfSNPs 339s 1 1 1 1 554484 120992603 7586 1.3853 2108 339s 2 1 2 1 120992604 141510002 0 NA 0 339s 3 1 3 1 141510003 185449813 2681 2.0689 777 339s 4 1 4 1 185449813 247137334 4391 2.6341 1311 339s tcnNbrOfHets dhNbrOfLoci dhMean c1Mean c2Mean 339s 1 2108 2108 0.5116 0.3382903 1.047010 339s 2 0 NA NA NA NA 339s 3 777 777 0.0973 0.9337980 1.135102 339s 4 1311 1311 0.2295 1.0147870 1.619313 339s > 339s > # Plot results 339s > dev.set(3L) 339s pdf 339s 2 339s > plotTracks(fit) 339s > abline(v=c(knownSegments$start, knownSegments$end)/1e6, lty=3) 339s > 339s > # Sanity check [TO FIX: See above] 339s > stopifnot(nbrOfSegments(fit) == nSegs) 339s > 339s > fit2 <- fit 339s > 339s > 339s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 339s > # (c) Do not segment the centromere (without a separator) 339s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 339s > knownSegments <- data.frame( 339s + chromosome = c( 1, 1), 339s + start = c( -Inf, 141510003), 339s + end = c(120992603, +Inf) 339s + ) 339s > 339s > # Paired PSCBS segmentation 339s > fit <- segmentByPairedPSCBS(dataS, knownSegments=knownSegments, 339s + seed=0xBEEF, verbose=-10) 339s Segmenting paired tumor-normal signals using Paired PSCBS... 339s Calling genotypes from normal allele B fractions... 339s num [1:14670] 0.8274 0.5072 0.1671 0.1609 0.0421 ... 339s Called genotypes: 339s num [1:14670] 1 0.5 0 0 0 0 1 0 1 0.5 ... 339s - attr(*, "modelFit")=List of 1 339s ..$ :List of 7 339s .. ..$ flavor : chr "density" 339s .. ..$ cn : int 2 339s .. ..$ nbrOfGenotypeGroups: int 3 339s .. ..$ tau : num [1:2] 0.315 0.677 339s .. ..$ n : int 14640 339s .. ..$ fit :Classes 'PeaksAndValleys' and 'data.frame': 5 obs. of 3 variables: 339s .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 339s .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 339s .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 339s .. ..$ fitValleys :Classes 'PeaksAndValleys' and 'data.frame': 2 obs. of 3 variables: 339s .. .. ..$ type : chr [1:2] "valley" "valley" 339s .. .. ..$ x : num [1:2] 0.315 0.677 339s .. .. ..$ density: num [1:2] 0.522 0.551 339s ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 339s muN 339s 0 0.5 1 339s 5221 4198 5251 339s Calling genotypes from normal allele B fractions...done 339s Normalizing betaT using betaN (TumorBoost)... 339s Normalized BAFs: 339s num [1:14670] 0.9301 0.1667 0.0685 0.0995 0.0155 ... 339s - attr(*, "modelFit")=List of 5 339s ..$ method : chr "normalizeTumorBoost" 339s ..$ flavor : chr "v4" 339s ..$ delta : num [1:14670] -0.17264 0.00239 0.1671 0.16085 0.04213 ... 339s .. ..- attr(*, "modelFit")=List of 1 339s .. .. ..$ :List of 7 339s .. .. .. ..$ flavor : chr "density" 339s .. .. .. ..$ cn : int 2 339s .. .. .. ..$ nbrOfGenotypeGroups: int 3 339s .. .. .. ..$ tau : num [1:2] 0.315 0.677 339s .. .. .. ..$ n : int 14640 339s .. .. .. ..$ fit :Classes 'PeaksAndValleys' and 'data.frame': 5 obs. of 3 variables: 339s .. .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 339s .. .. .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 339s .. .. .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 339s .. .. .. ..$ fitValleys :Classes 'PeaksAndValleys' and 'data.frame': 2 obs. of 3 variables: 339s .. .. .. .. ..$ type : chr [1:2] "valley" "valley" 339s .. .. .. .. ..$ x : num [1:2] 0.315 0.677 339s .. .. .. .. ..$ density: num [1:2] 0.522 0.551 339s .. .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 339s ..$ preserveScale: logi FALSE 339s ..$ scaleFactor : num NA 339s Normalizing betaT using betaN (TumorBoost)...done 339s Setup up data... 339s 'data.frame': 14670 obs. of 7 variables: 339s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 339s $ x : num 1145994 2941694 3710825 4240737 4276892 ... 339s $ CT : num 1.63 1.4 1.41 1.17 1.16 ... 339s $ betaT : num 0.7574 0.169 0.2357 0.2604 0.0576 ... 339s $ betaTN : num 0.9301 0.1667 0.0685 0.0995 0.0155 ... 339s ..- attr(*, "modelFit")=List of 5 339s .. ..$ method : chr "normalizeTumorBoost" 339s .. ..$ flavor : chr "v4" 339s .. ..$ delta : num [1:14670] -0.17264 0.00239 0.1671 0.16085 0.04213 ... 339s .. .. ..- attr(*, "modelFit")=List of 1 339s .. .. .. ..$ :List of 7 339s .. .. .. .. ..$ flavor : chr "density" 339s .. .. .. .. ..$ cn : int 2 339s .. .. .. .. ..$ nbrOfGenotypeGroups: int 3 339s .. .. .. .. ..$ tau : num [1:2] 0.315 0.677 339s .. .. .. .. ..$ n : int 14640 339s .. .. .. .. ..$ fit :Classes 'PeaksAndValleys' and 'data.frame': 5 obs. of 3 variables: 339s .. .. .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 339s .. .. .. .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 339s .. .. .. .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 339s .. .. .. .. ..$ fitValleys :Classes 'PeaksAndValleys' and 'data.frame': 2 obs. of 3 variables: 339s .. .. .. .. .. ..$ type : chr [1:2] "valley" "valley" 339s .. .. .. .. .. ..$ x : num [1:2] 0.315 0.677 339s .. .. .. .. .. ..$ density: num [1:2] 0.522 0.551 339s .. .. .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 339s .. ..$ preserveScale: logi FALSE 339s .. ..$ scaleFactor : num NA 339s $ betaN : num 0.8274 0.5072 0.1671 0.1609 0.0421 ... 339s $ muN : num 1 0.5 0 0 0 0 1 0 1 0.5 ... 339s ..- attr(*, "modelFit")=List of 1 339s .. ..$ :List of 7 339s .. .. ..$ flavor : chr "density" 339s .. .. ..$ cn : int 2 339s .. .. ..$ nbrOfGenotypeGroups: int 3 339s .. .. ..$ tau : num [1:2] 0.315 0.677 339s .. .. ..$ n : int 14640 339s .. .. ..$ fit :Classes 'PeaksAndValleys' and 'data.frame': 5 obs. of 3 variables: 339s .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 339s .. .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 339s .. .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 339s .. .. ..$ fitValleys :Classes 'PeaksAndValleys' and 'data.frame': 2 obs. of 3 variables: 339s .. .. .. ..$ type : chr [1:2] "valley" "valley" 339s .. .. .. ..$ x : num [1:2] 0.315 0.677 339s .. .. .. ..$ density: num [1:2] 0.522 0.551 339s .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 339s Setup up data...done 339s Dropping loci for which TCNs are missing... 339s Number of loci dropped: 12 339s Dropping loci for which TCNs are missing...done 339s Ordering data along genome... 339s 'data.frame': 14658 obs. of 7 variables: 339s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 339s $ x : num 554484 730720 782343 878522 916294 ... 339s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 339s $ betaT : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 339s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 339s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 339s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 339s Ordering data along genome...done 339s Keeping only current chromosome for 'knownSegments'... 339s Chromosome: 1 339s Known segments for this chromosome: 339s chromosome start end 339s 1 1 -Inf 120992603 339s 2 1 141510003 Inf 339s Keeping only current chromosome for 'knownSegments'...done 339s alphaTCN: 0.009 339s alphaDH: 0.001 339s Number of loci: 14658 339s Calculating DHs... 339s Number of SNPs: 14658 339s Number of heterozygous SNPs: 4196 (28.63%) 339s Normalized DHs: 339s num [1:14658] NA NA NA NA NA ... 339s Calculating DHs...done 339s Random seed temporarily set (seed=c(48879), kind="L'Ecuyer-CMRG") 339s Produced 2 seeds from this stream for future usage 339s Identification of change points by total copy numbers... 339s Segmenting by CBS... 339s Chromosome: 1 339s Segmenting multiple segments on current chromosome... 339s Number of segments: 2 339s Random seed temporarily set (seed=c(10407, 1066287653, -51199871, 161854402, -1995183193, 1503453565, -747102133), kind="L'Ecuyer-CMRG") 339s Produced 2 seeds from this stream for future usage 339s Segmenting by CBS... 339s Chromosome: 1 339s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 339s Segmenting by CBS...done 339s Segmenting by CBS... 339s Chromosome: 1 339s Random seed temporarily set (seed=c(10407, -821273412, -52578226, 1415511586, 721384351, -665928286, 1316562960), kind="L'Ecuyer-CMRG") 339s Segmenting by CBS...done 339s Segmenting multiple segments on current chromosome...done 339s Segmenting by CBS...done 339s List of 4 339s $ data :'data.frame': 14658 obs. of 4 variables: 339s ..$ chromosome: int [1:14658] 1 1 1 1 1 1 1 1 1 1 ... 339s ..$ x : num [1:14658] 554484 730720 782343 878522 916294 ... 339s ..$ y : num [1:14658] 1.88 1.8 1.59 1.64 1.53 ... 339s ..$ index : int [1:14658] 1 2 3 4 5 6 7 8 9 10 ... 339s $ output :'data.frame': 3 obs. of 6 variables: 339s ..$ sampleName: chr [1:3] NA NA NA 339s ..$ chromosome: int [1:3] 1 1 1 339s ..$ start : num [1:3] 5.54e+05 1.42e+08 1.85e+08 339s ..$ end : num [1:3] 1.21e+08 1.85e+08 2.47e+08 339s ..$ nbrOfLoci : int [1:3] 7586 2681 4391 339s ..$ mean : num [1:3] 1.39 2.07 2.63 339s $ segRows:'data.frame': 3 obs. of 2 variables: 339s ..$ startRow: int [1:3] 1 7587 10268 339s ..$ endRow : int [1:3] 7586 10267 14658 339s $ params :List of 5 339s ..$ alpha : num 0.009 339s ..$ undo : num 0 339s ..$ joinSegments : logi TRUE 339s ..$ knownSegments:'data.frame': 2 obs. of 3 variables: 339s .. ..$ chromosome: num [1:2] 1 1 339s .. ..$ start : num [1:2] -Inf 1.42e+08 339s .. ..$ end : num [1:2] 1.21e+08 Inf 339s ..$ seed : int [1:7] 10407 1066287653 -51199871 161854402 -1995183193 1503453565 -747102133 339s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 339s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.168 0 0.168 0 0 339s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 339s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 339s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 339s Identification of change points by total copy numbers...done 339s Restructure TCN segmentation results... 339s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean 339s 1 1 554484 120992603 7586 1.3853 339s 2 1 141510003 185449813 2681 2.0689 339s 3 1 185449813 247137334 4391 2.6341 339s Number of TCN segments: 3 339s Restructure TCN segmentation results...done 339s Total CN segment #1 ([ 554484,1.20993e+08]) of 3... 339s Number of TCN loci in segment: 7586 339s Locus data for TCN segment: 339s 'data.frame': 7586 obs. of 9 variables: 339s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 339s $ x : num 554484 730720 782343 878522 916294 ... 339s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 339s $ betaT : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 339s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 339s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 339s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 339s $ index : int 1 2 3 4 5 6 7 8 9 10 ... 339s $ rho : num NA NA NA NA NA ... 339s Number of loci: 7586 339s Number of SNPs: 2108 (27.79%) 339s Number of heterozygous SNPs: 2108 (100.00%) 339s Chromosome: 1 339s Segmenting DH signals... 339s Segmenting by CBS... 339s Chromosome: 1 339s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 339s Segmenting by CBS...done 339s List of 4 339s $ data :'data.frame': 7586 obs. of 4 variables: 339s ..$ chromosome: int [1:7586] 1 1 1 1 1 1 1 1 1 1 ... 339s ..$ x : num [1:7586] 554484 730720 782343 878522 916294 ... 339s ..$ y : num [1:7586] NA NA NA NA NA ... 339s ..$ index : int [1:7586] 1 2 3 4 5 6 7 8 9 10 ... 339s $ output :'data.frame': 1 obs. of 6 variables: 339s ..$ sampleName: chr NA 339s ..$ chromosome: int 1 339s ..$ start : num 554484 339s ..$ end : num 1.21e+08 339s ..$ nbrOfLoci : int 2108 339s ..$ mean : num 0.512 339s $ segRows:'data.frame': 1 obs. of 2 variables: 339s ..$ startRow: int 10 339s ..$ endRow : int 7574 339s $ params :List of 5 339s ..$ alpha : num 0.001 339s ..$ undo : num 0 339s ..$ joinSegments : logi TRUE 339s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 339s .. ..$ chromosome: int 1 339s .. ..$ start : num 554484 339s .. ..$ end : num 1.21e+08 339s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 339s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 339s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.047 0 0.047 0 0 339s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 339s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 339s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 339s DH segmentation (locally-indexed) rows: 339s startRow endRow 339s 1 10 7574 339s int [1:7586] 1 2 3 4 5 6 7 8 9 10 ... 339s DH segmentation rows: 339s startRow endRow 339s 1 10 7574 339s Segmenting DH signals...done 339s DH segmentation table: 339s dhStart dhEnd dhNbrOfLoci dhMean 339s 1 554484 120992603 2108 0.5116 339s startRow endRow 339s 1 10 7574 339s Rows: 339s [1] 1 339s TCN segmentation rows: 339s startRow endRow 339s 1 1 7586 339s TCN and DH segmentation rows: 339s startRow endRow 339s 1 1 7586 339s startRow endRow 339s 1 10 7574 339s NULL 339s TCN segmentation (expanded) rows: 339s startRow endRow 339s 1 1 7586 339s TCN and DH segmentation rows: 339s startRow endRow 339s 1 1 7586 339s 2 7587 10267 339s 3 10268 14658 339s startRow endRow 339s 1 10 7574 339s startRow endRow 339s 1 1 7586 339s Total CN segmentation table (expanded): 339s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 339s 1 1 554484 120992603 7586 1.3853 2108 2108 339s (TCN,DH) segmentation for one total CN segment: 339s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 339s 1 1 1 1 554484 120992603 7586 1.3853 2108 339s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 339s 1 2108 554484 120992603 2108 0.5116 339s Total CN segment #1 ([ 554484,1.20993e+08]) of 3...done 339s Total CN segment #2 ([1.4151e+08,1.8545e+08]) of 3... 339s Number of TCN loci in segment: 2681 339s Locus data for TCN segment: 339s 'data.frame': 2681 obs. of 9 variables: 339s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 339s $ x : num 1.43e+08 1.43e+08 1.43e+08 1.43e+08 1.44e+08 ... 339s $ CT : num 2.27 1.55 1.47 1.5 1.81 ... 339s $ betaT : num 0.34 0.55 0.048 0.813 0.575 ... 339s $ betaTN : num 0.441 0.629 -0.05 0.958 0.872 ... 339s $ betaN : num 0.3851 0.3933 0.0981 0.8552 0.7028 ... 339s $ muN : num 0.5 0.5 0 1 1 1 1 0.5 1 1 ... 339s $ index : int 7587 7588 7589 7590 7591 7592 7593 7594 7595 7596 ... 339s $ rho : num 0.117 0.258 NA NA NA ... 339s Number of loci: 2681 339s Number of SNPs: 777 (28.98%) 339s Number of heterozygous SNPs: 777 (100.00%) 339s Chromosome: 1 339s Segmenting DH signals... 339s Segmenting by CBS... 339s Chromosome: 1 339s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 339s Segmenting by CBS...done 339s List of 4 339s $ data :'data.frame': 2681 obs. of 4 variables: 339s ..$ chromosome: int [1:2681] 1 1 1 1 1 1 1 1 1 1 ... 339s ..$ x : num [1:2681] 1.43e+08 1.43e+08 1.43e+08 1.43e+08 1.44e+08 ... 339s ..$ y : num [1:2681] 0.117 0.258 NA NA NA ... 339s ..$ index : int [1:2681] 1 2 3 4 5 6 7 8 9 10 ... 339s $ output :'data.frame': 1 obs. of 6 variables: 339s ..$ sampleName: chr NA 339s ..$ chromosome: int 1 339s ..$ start : num 1.42e+08 339s ..$ end : num 1.85e+08 339s ..$ nbrOfLoci : int 777 339s ..$ mean : num 0.0973 339s $ segRows:'data.frame': 1 obs. of 2 variables: 339s ..$ startRow: int 1 339s ..$ endRow : int 2677 339s $ params :List of 5 339s ..$ alpha : num 0.001 339s ..$ undo : num 0 339s ..$ joinSegments : logi TRUE 339s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 339s .. ..$ chromosome: int 1 339s .. ..$ start : num 1.42e+08 339s .. ..$ end : num 1.85e+08 339s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 339s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 339s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.01 0 0.009 0 0 339s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 339s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 339s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 339s DH segmentation (locally-indexed) rows: 339s startRow endRow 339s 1 1 2677 339s int [1:2681] 7587 7588 7589 7590 7591 7592 7593 7594 7595 7596 ... 339s DH segmentation rows: 339s startRow endRow 339s 1 7587 10263 339s Segmenting DH signals...done 339s DH segmentation table: 339s dhStart dhEnd dhNbrOfLoci dhMean 339s 1 141510003 185449813 777 0.0973 339s startRow endRow 339s 1 7587 10263 339s Rows: 339s [1] 2 339s TCN segmentation rows: 339s startRow endRow 339s 2 7587 10267 339s TCN and DH segmentation rows: 339s startRow endRow 339s 2 7587 10267 339s startRow endRow 339s 1 7587 10263 339s startRow endRow 339s 1 1 7586 339s TCN segmentation (expanded) rows: 339s startRow endRow 339s 1 1 7586 339s 2 7587 10267 339s TCN and DH segmentation rows: 339s startRow endRow 339s 1 1 7586 339s 2 7587 10267 339s 3 10268 14658 339s startRow endRow 339s 1 10 7574 339s 2 7587 10263 339s startRow endRow 339s 1 1 7586 339s 2 7587 10267 339s Total CN segmentation table (expanded): 339s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 339s 2 1 141510003 185449813 2681 2.0689 777 777 339s (TCN,DH) segmentation for one total CN segment: 339s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 339s 2 2 1 1 141510003 185449813 2681 2.0689 777 339s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 339s 2 777 141510003 185449813 777 0.0973 339s Total CN segment #2 ([1.4151e+08,1.8545e+08]) of 3...done 339s Total CN segment #3 ([1.8545e+08,2.47137e+08]) of 3... 339s Number of TCN loci in segment: 4391 339s Locus data for TCN segment: 339s 'data.frame': 4391 obs. of 9 variables: 339s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 339s $ x : num 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 339s $ CT : num 2.93 2.15 2.82 2.93 2.46 ... 339s $ betaT : num 0.0811 0.5154 0.9473 0.3734 0.7506 ... 339s $ betaTN : num -0.169 0.609 1.028 0.525 0.968 ... 339s $ betaN : num 0.25 0.38 0.919 0.34 0.783 ... 339s $ muN : num 0 0.5 1 0.5 1 1 0 1 0 1 ... 339s $ index : int 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 339s $ rho : num NA 0.2186 NA 0.0503 NA ... 339s Number of loci: 4391 339s Number of SNPs: 1311 (29.86%) 339s Number of heterozygous SNPs: 1311 (100.00%) 339s Chromosome: 1 339s Segmenting DH signals... 339s Segmenting by CBS... 339s Chromosome: 1 339s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 339s Segmenting by CBS...done 339s List of 4 339s $ data :'data.frame': 4391 obs. of 4 variables: 339s ..$ chromosome: int [1:4391] 1 1 1 1 1 1 1 1 1 1 ... 339s ..$ x : num [1:4391] 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 339s ..$ y : num [1:4391] NA 0.2186 NA 0.0503 NA ... 339s ..$ index : int [1:4391] 1 2 3 4 5 6 7 8 9 10 ... 339s $ output :'data.frame': 1 obs. of 6 variables: 339s ..$ sampleName: chr NA 339s ..$ chromosome: int 1 339s ..$ start : num 1.85e+08 339s ..$ end : num 2.47e+08 339s ..$ nbrOfLoci : int 1311 339s ..$ mean : num 0.23 339s $ segRows:'data.frame': 1 obs. of 2 variables: 339s ..$ startRow: int 2 339s ..$ endRow : int 4388 339s $ params :List of 5 339s ..$ alpha : num 0.001 339s ..$ undo : num 0 339s ..$ joinSegments : logi TRUE 339s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 339s .. ..$ chromosome: int 1 339s .. ..$ start : num 1.85e+08 339s .. ..$ end : num 2.47e+08 339s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 339s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 339s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.018 0 0.017 0 0 339s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 339s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 339s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 339s DH segmentation (locally-indexed) rows: 339s startRow endRow 339s 1 2 4388 339s int [1:4391] 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 339s DH segmentation rows: 339s startRow endRow 339s 1 10269 14655 339s Segmenting DH signals...done 339s DH segmentation table: 339s dhStart dhEnd dhNbrOfLoci dhMean 339s 1 185449813 247137334 1311 0.2295 339s startRow endRow 339s 1 10269 14655 339s Rows: 339s [1] 3 339s TCN segmentation rows: 339s startRow endRow 339s 3 10268 14658 339s TCN and DH segmentation rows: 339s startRow endRow 339s 3 10268 14658 339s startRow endRow 339s 1 10269 14655 339s startRow endRow 339s 1 1 7586 339s 2 7587 10267 339s TCN segmentation (expanded) rows: 339s startRow endRow 339s 1 1 7586 339s 2 7587 10267 339s 3 10268 14658 339s TCN and DH segmentation rows: 339s startRow endRow 339s 1 1 7586 339s 2 7587 10267 339s 3 10268 14658 339s startRow endRow 339s 1 10 7574 339s 2 7587 10263 339s 3 10269 14655 339s startRow endRow 339s 1 1 7586 339s 2 7587 10267 339s 3 10268 14658 339s Total CN segmentation table (expanded): 339s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 339s 3 1 185449813 247137334 4391 2.6341 1311 1311 339s (TCN,DH) segmentation for one total CN segment: 339s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 339s 3 3 1 1 185449813 247137334 4391 2.6341 1311 339s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 339s 3 1311 185449813 247137334 1311 0.2295 339s Total CN segment #3 ([1.8545e+08,2.47137e+08]) of 3...done 339s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 339s 1 1 1 1 554484 120992603 7586 1.3853 2108 339s 2 1 2 1 141510003 185449813 2681 2.0689 777 339s 3 1 3 1 185449813 247137334 4391 2.6341 1311 339s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 339s 1 2108 554484 120992603 2108 0.5116 339s 2 777 141510003 185449813 777 0.0973 339s 3 1311 185449813 247137334 1311 0.2295 339s Calculating (C1,C2) per segment... 339s Calculating (C1,C2) per segment...done 339s Number of segments: 3 339s Segmenting paired tumor-normal signals using Paired PSCBS...done 339s Post-segmenting TCNs... 339s Number of segments: 3 339s Number of chromosomes: 1 339s [1] 1 339s Chromosome 1 ('chr01') of 1... 339s Rows: 339s [1] 1 2 3 339s Number of segments: 3 339s TCN segment #1 ('1') of 3... 339s Nothing todo. Only one DH segmentation. Skipping. 339s TCN segment #1 ('1') of 3...done 339s TCN segment #2 ('2') of 3... 339s Nothing todo. Only one DH segmentation. Skipping. 339s TCN segment #2 ('2') of 3...done 339s TCN segment #3 ('3') of 3... 339s Nothing todo. Only one DH segmentation. Skipping. 339s TCN segment #3 ('3') of 3...done 339s Chromosome 1 ('chr01') of 1...done 339s Update (C1,C2) per segment... 339s Update (C1,C2) per segment...done 339s Post-segmenting TCNs...done 339s chromosome tcnId dhId tcnStart tcnEnd tc -f /tmp/autopkgtest.AbkJ6s/autopkgtest_tmp/PairedPSCBS,boot.R /tmp/autopkgtest.AbkJ6s/autopkgtest_tmp/PairedPSCBS,boot.Rout /tmp/autopkgtest.AbkJ6s/autopkgtest_tmp/Rplots.pdf /tmp/autopkgtest.AbkJ6s/autopkgtest_tmp/findLargeGaps.R /tmp/autopkgtest.AbkJ6s/autopkgtest_tmp/findLargeGaps.Rout /tmp/autopkgtest.AbkJ6s/autopkgtest_tmp/randomSeed.R /tmp/autopkgtest.AbkJ6s/autopkgtest_tmp/randomSeed.Rout /tmp/autopkgtest.AbkJ6s/autopkgtest_tmp/segmentByCBS,bug67.R /tmp/autopkgtest.AbkJ6s/autopkgtest_tmp/segmentByCBS,bug67.Rout /tmp/autopkgtest.AbkJ6s/autopkgtest_tmp/segmentByCBS,calls.R /tmp/autopkgtest.AbkJ6s/autopkgtest_tmp/segmentByCBS,calls.Rout /tmp/autopkgtest.AbkJ6s/autopkgtest_tmp/segmentByCBS,futures.R /tmp/autopkgtest.AbkJ6s/autopkgtest_tmp/segmentByCBS,futures.Rout /tmp/autopkgtest.AbkJ6s/autopkgtest_tmp/segmentByCBS,median.R /tmp/autopkgtest.AbkJ6s/autopkgtest_tmp/segmentByCBS,median.Rout /tmp/autopkgtest.AbkJ6s/autopkgtest_tmp/segmentByCBS,prune.R /tmp/autopkgtest.AbkJ6s/autopkgtest_tmp/segmentByCBS,prune.Rout /tmp/autopkgtest.AbkJ6s/autopkgtest_tmp/segmentByCBS,report.R /tmp/autopkgtest.AbkJ6s/autopkgtest_tmp/segmentByCBS,report.Rout /tmp/autopkgtest.AbkJ6s/autopkgtest_tmp/segmentByCBS,shiftTCN.R /tmp/autopkgtest.AbkJ6s/autopkgtest_tmp/segmentByCBS,shiftTCN.Rout /tmp/autopkgtest.AbkJ6s/autopkgtest_tmp/segmentByCBS,weights.R /tmp/autopkgtest.AbkJ6s/autopkgtest_tmp/segmentByCBS,weights.Rout /tmp/autopkgtest.AbkJ6s/autopkgtest_tmp/segmentByCBS.R /tmp/autopkgtest.AbkJ6s/autopkgtest_tmp/segmentByCBS.Rout /tmp/autopkgtest.AbkJ6s/autopkgtest_tmp/segmentByNonPairedPSCBS,medianDH.R /tmp/autopkgtest.AbkJ6s/autopkgtest_tmp/segmentByNonPairedPSCBS,medianDH.Rout /tmp/autopkgtest.AbkJ6s/autopkgtest_tmp/segmentByPairedPSCBS,DH.R /tmp/autopkgtest.AbkJ6s/autopkgtest_tmp/segmentByPairedPSCBS,DH.Rout /tmp/autopkgtest.AbkJ6s/autopkgtest_tmp/segmentByPairedPSCBS,calls.R /tmp/autopkgtest.AbkJ6s/autopkgtest_tmp/segmentByPairedPSCBS,calls.Rout /tmp/autopkgtest.AbkJ6s/autopkgtest_tmp/segmentByPairedPSCBS,futures.R /tmp/autopkgtest.AbkJ6s/autopkgtest_tmp/segmentByPairedPSCBS,futures.Rout /tmp/autopkgtest.AbkJ6s/autopkgtest_tmp/segmentByPairedPSCBS,noNormalBAFs.R /tmp/autopkgtest.AbkJ6s/autopkgtest_tmp/segmentByPairedPSCBS,noNormalBAFs.Rout /tmp/autopkgtest.AbkJ6s/autopkgtest_tmp/segmentByPairedPSCBS,report.R /tmp/autopkgtest.AbkJ6s/autopkgtest_tmp/segmentByPairedPSCBS,report.Rout /tmp/autopkgtest.AbkJ6s/autopkgtest_tmp/segmentByPairedPSCBS,seqOfSegmentsByDP.R /tmp/autopkgtest.AbkJ6s/autopkgtest_tmp/segmentByPairedPSCBS,seqOfSegmentsByDP.Rout /tmp/autopkgtest.AbkJ6s/autopkgtest_tmp/segmentByPairedPSCBS.R /tmp/autopkgtest.AbkJ6s/autopkgtest_tmp/segmentByPairedPSCBS.Rout 339s nNbrOfLoci tcnMean tcnNbrOfSNPs 339s 1 1 1 1 554484 120992603 7586 1.3853 2108 339s 2 1 2 1 141510003 185449813 2681 2.0689 777 339s 3 1 3 1 185449813 247137334 4391 2.6341 1311 339s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 339s 1 2108 554484 120992603 2108 0.5116 0.3382903 1.047010 339s 2 777 141510003 185449813 777 0.0973 0.9337980 1.135102 339s 3 1311 185449813 247137334 1311 0.2295 1.0147870 1.619313 339s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 339s 1 1 1 1 554484 120992603 7586 1.3853 2108 339s 2 1 2 1 141510003 185449813 2681 2.0689 777 339s 3 1 3 1 185449813 247137334 4391 2.6341 1311 339s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 339s 1 2108 554484 120992603 2108 0.5116 0.3382903 1.047010 339s 2 777 141510003 185449813 777 0.0973 0.9337980 1.135102 339s 3 1311 185449813 247137334 1311 0.2295 1.0147870 1.619313 339s > print(fit) 339s chromosome tcnId dhId start end tcnNbrOfLoci tcnMean tcnNbrOfSNPs 339s 1 1 1 1 554484 120992603 7586 1.3853 2108 339s 2 1 2 1 141510003 185449813 2681 2.0689 777 339s 3 1 3 1 185449813 247137334 4391 2.6341 1311 339s tcnNbrOfHets dhNbrOfLoci dhMean c1Mean c2Mean 339s 1 2108 2108 0.5116 0.3382903 1.047010 339s 2 777 777 0.0973 0.9337980 1.135102 339s 3 1311 1311 0.2295 1.0147870 1.619313 339s > 339s > # Plot results 339s > dev.set(4L) 339s pdf 339s 2 339s > plotTracks(fit) 339s > abline(v=c(knownSegments$start, knownSegments$end)/1e6, lty=3) 339s > 339s > # Sanity check 339s > stopifnot(nbrOfSegments(fit) == nSegs-1L) 339s > 339s > fit3 <- fit 339s > 339s > 339s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 339s > # (d) Skip the identification of new change points 339s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 339s > knownSegments <- data.frame( 339s + chromosome = c( 1, 1), 339s + start = c( -Inf, 141510003), 339s + end = c(120992603, +Inf) 339s + ) 339s > 339s > # Paired PSCBS segmentation 339s > fit <- segmentByPairedPSCBS(dataS, knownSegments=knownSegments, 339s + undoTCN=Inf, undoDH=Inf, 339s + seed=0xBEEF, verbose=-10) 339s Segmenting paired tumor-normal signals using Paired PSCBS... 339s Calling genotypes from normal allele B fractions... 339s num [1:14670] 0.8274 0.5072 0.1671 0.1609 0.0421 ... 339s Called genotypes: 339s num [1:14670] 1 0.5 0 0 0 0 1 0 1 0.5 ... 339s - attr(*, "modelFit")=List of 1 339s ..$ :List of 7 339s .. ..$ flavor : chr "density" 339s .. ..$ cn : int 2 339s .. ..$ nbrOfGenotypeGroups: int 3 339s .. ..$ tau : num [1:2] 0.315 0.677 339s .. ..$ n : int 14640 339s .. ..$ fit :Classes 'PeaksAndValleys' and 'data.frame': 5 obs. of 3 variables: 339s .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 339s .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 339s .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 339s .. ..$ fitValleys :Classes 'PeaksAndValleys' and 'data.frame': 2 obs. of 3 variables: 339s .. .. ..$ type : chr [1:2] "valley" "valley" 339s .. .. ..$ x : num [1:2] 0.315 0.677 339s .. .. ..$ density: num [1:2] 0.522 0.551 339s ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 339s muN 339s 0 0.5 1 339s 5221 4198 5251 339s Calling genotypes from normal allele B fractions...done 339s Normalizing betaT using betaN (TumorBoost)... 339s Normalized BAFs: 339s num [1:14670] 0.9301 0.1667 0.0685 0.0995 0.0155 ... 339s - attr(*, "modelFit")=List of 5 339s ..$ method : chr "normalizeTumorBoost" 339s ..$ flavor : chr "v4" 339s ..$ delta : num [1:14670] -0.17264 0.00239 0.1671 0.16085 0.04213 ... 339s .. ..- attr(*, "modelFit")=List of 1 339s .. .. ..$ :List of 7 339s .. .. .. ..$ flavor : chr "density" 339s .. .. .. ..$ cn : int 2 339s .. .. .. ..$ nbrOfGenotypeGroups: int 3 339s .. .. .. ..$ tau : num [1:2] 0.315 0.677 339s .. .. .. ..$ n : int 14640 339s .. .. .. ..$ fit :Classes 'PeaksAndValleys' and 'data.frame': 5 obs. of 3 variables: 339s .. .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 339s .. .. .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 339s .. .. .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 339s .. .. .. ..$ fitValleys :Classes 'PeaksAndValleys' and 'data.frame': 2 obs. of 3 variables: 339s .. .. .. .. ..$ type : chr [1:2] "valley" "valley" 339s .. .. .. .. ..$ x : num [1:2] 0.315 0.677 339s .. .. .. .. ..$ density: num [1:2] 0.522 0.551 339s .. .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 339s ..$ preserveScale: logi FALSE 339s ..$ scaleFactor : num NA 339s Normalizing betaT using betaN (TumorBoost)...done 339s Setup up data... 339s 'data.frame': 14670 obs. of 7 variables: 339s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 339s $ x : num 1145994 2941694 3710825 4240737 4276892 ... 339s $ CT : num 1.63 1.4 1.41 1.17 1.16 ... 339s $ betaT : num 0.7574 0.169 0.2357 0.2604 0.0576 ... 339s $ betaTN : num 0.9301 0.1667 0.0685 0.0995 0.0155 ... 339s ..- attr(*, "modelFit")=List of 5 339s .. ..$ method : chr "normalizeTumorBoost" 339s .. ..$ flavor : chr "v4" 339s .. ..$ delta : num [1:14670] -0.17264 0.00239 0.1671 0.16085 0.04213 ... 339s .. .. ..- attr(*, "modelFit")=List of 1 339s .. .. .. ..$ :List of 7 339s .. .. .. .. ..$ flavor : chr "density" 339s .. .. .. .. ..$ cn : int 2 339s .. .. .. .. ..$ nbrOfGenotypeGroups: int 3 339s .. .. .. .. ..$ tau : num [1:2] 0.315 0.677 339s .. .. .. .. ..$ n : int 14640 339s .. .. .. .. ..$ fit :Classes 'PeaksAndValleys' and 'data.frame': 5 obs. of 3 variables: 339s .. .. .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 339s .. .. .. .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 339s .. .. .. .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 339s .. .. .. .. ..$ fitValleys :Classes 'PeaksAndValleys' and 'data.frame': 2 obs. of 3 variables: 339s .. .. .. .. .. ..$ type : chr [1:2] "valley" "valley" 339s .. .. .. .. .. ..$ x : num [1:2] 0.315 0.677 339s .. .. .. .. .. ..$ density: num [1:2] 0.522 0.551 339s .. .. .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 339s .. ..$ preserveScale: logi FALSE 339s .. ..$ scaleFactor : num NA 339s $ betaN : num 0.8274 0.5072 0.1671 0.1609 0.0421 ... 339s $ muN : num 1 0.5 0 0 0 0 1 0 1 0.5 ... 339s ..- attr(*, "modelFit")=List of 1 339s .. ..$ :List of 7 339s .. .. ..$ flavor : chr "density" 339s .. .. ..$ cn : int 2 339s .. .. ..$ nbrOfGenotypeGroups: int 3 339s .. .. ..$ tau : num [1:2] 0.315 0.677 339s .. .. ..$ n : int 14640 339s .. .. ..$ fit :Classes 'PeaksAndValleys' and 'data.frame': 5 obs. of 3 variables: 339s .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 339s .. .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 339s .. .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 339s .. .. ..$ fitValleys :Classes 'PeaksAndValleys' and 'data.frame': 2 obs. of 3 variables: 339s .. .. .. ..$ type : chr [1:2] "valley" "valley" 339s .. .. .. ..$ x : num [1:2] 0.315 0.677 339s .. .. .. ..$ density: num [1:2] 0.522 0.551 339s .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 339s Setup up data...done 339s Dropping loci for which TCNs are missing... 339s Number of loci dropped: 12 339s Dropping loci for which TCNs are missing...done 339s Ordering data along genome... 339s 'data.frame': 14658 obs. of 7 variables: 339s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 339s $ x : num 554484 730720 782343 878522 916294 ... 339s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 339s $ betaT : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 339s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 339s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 339s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 339s Ordering data along genome...done 339s Keeping only current chromosome for 'knownSegments'... 339s Chromosome: 1 339s Known segments for this chromosome: 339s chromosome start end 339s 1 1 -Inf 120992603 339s 2 1 141510003 Inf 339s Keeping only current chromosome for 'knownSegments'...done 339s alphaTCN: 0.009 339s alphaDH: 0.001 339s Number of loci: 14658 339s Calculating DHs... 339s Number of SNPs: 14658 339s Number of heterozygous SNPs: 4196 (28.63%) 339s Normalized DHs: 339s num [1:14658] NA NA NA NA NA ... 339s Calculating DHs...done 339s Random seed temporarily set (seed=c(48879), kind="L'Ecuyer-CMRG") 339s Produced 2 seeds from this stream for future usage 339s Identification of change points by total copy numbers... 339s Segmenting by CBS... 339s Chromosome: 1 339s Segmenting multiple segments on current chromosome... 339s Number of segments: 2 339s Random seed temporarily set (seed=c(10407, 1066287653, -51199871, 161854402, -1995183193, 1503453565, -747102133), kind="L'Ecuyer-CMRG") 339s Produced 2 seeds from this stream for future usage 339s Segmenting by CBS... 339s Chromosome: 1 339s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 339s Segmenting by CBS...done 339s Segmenting by CBS... 339s Chromosome: 1 339s Random seed temporarily set (seed=c(10407, -821273412, -52578226, 1415511586, 721384351, -665928286, 1316562960), kind="L'Ecuyer-CMRG") 339s Segmenting by CBS...done 339s Segmenting multiple segments on current chromosome...done 339s Segmenting by CBS...done 339s List of 4 339s $ data :'data.frame': 14658 obs. of 4 variables: 339s ..$ chromosome: int [1:14658] 1 1 1 1 1 1 1 1 1 1 ... 339s ..$ x : num [1:14658] 554484 730720 782343 878522 916294 ... 339s ..$ y : num [1:14658] 1.88 1.8 1.59 1.64 1.53 ... 339s ..$ index : int [1:14658] 1 2 3 4 5 6 7 8 9 10 ... 339s $ output :'data.frame': 2 obs. of 6 variables: 339s ..$ sampleName: chr [1:2] NA NA 339s ..$ chromosome: num [1:2] 1 1 339s ..$ start : num [1:2] 5.54e+05 1.42e+08 339s ..$ end : num [1:2] 1.21e+08 2.47e+08 339s ..$ nbrOfLoci : int [1:2] 7586 7072 339s ..$ mean : num [1:2] 1.39 2.42 339s $ segRows:'data.frame': 2 obs. of 2 variables: 339s ..$ startRow: int [1:2] 1 7587 339s ..$ endRow : int [1:2] 7586 14658 339s $ params :List of 7 339s ..$ undo.splits : chr "sdundo" 339s ..$ undo.SD : num Inf 339s ..$ alpha : num 0.009 339s ..$ undo : num Inf 339s ..$ joinSegments : logi TRUE 339s ..$ knownSegments:'data.frame': 2 obs. of 3 variables: 339s .. ..$ chromosome: num [1:2] 1 1 339s .. ..$ start : num [1:2] -Inf 1.42e+08 339s .. ..$ end : num [1:2] 1.21e+08 Inf 339s ..$ seed : int [1:7] 10407 1066287653 -51199871 161854402 -1995183193 1503453565 -747102133 339s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 339s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.001 0 0.002 0 0 339s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 339s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 339s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 339s Identification of change points by total copy numbers...done 339s Restructure TCN segmentation results... 339s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean 339s 1 1 554484 120992603 7586 1.385258 339s 2 1 141510003 247137334 7072 2.419824 339s Number of TCN segments: 2 339s Restructure TCN segmentation results...done 339s Total CN segment #1 ([ 554484,1.20993e+08]) of 2... 339s Number of TCN loci in segment: 7586 339s Locus data for TCN segment: 339s 'data.frame': 7586 obs. of 9 variables: 339s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 339s $ x : num 554484 730720 782343 878522 916294 ... 339s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 339s $ betaT : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 339s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 339s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 339s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 339s $ index : int 1 2 3 4 5 6 7 8 9 10 ... 339s $ rho : num NA NA NA NA NA ... 339s Number of loci: 7586 339s Number of SNPs: 2108 (27.79%) 339s Number of heterozygous SNPs: 2108 (100.00%) 339s Chromosome: 1 339s Segmenting DH signals... 339s Segmenting by CBS... 339s Chromosome: 1 339s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 339s Segmenting by CBS...done 339s List of 4 339s $ data :'data.frame': 7586 obs. of 4 variables: 339s ..$ chromosome: int [1:7586] 1 1 1 1 1 1 1 1 1 1 ... 339s ..$ x : num [1:7586] 554484 730720 782343 878522 916294 ... 339s ..$ y : num [1:7586] NA NA NA NA NA ... 339s ..$ index : int [1:7586] 1 2 3 4 5 6 7 8 9 10 ... 339s $ output :'data.frame': 1 obs. of 6 variables: 339s ..$ sampleName: chr NA 339s ..$ chromosome: int 1 339s ..$ start : num 554484 339s ..$ end : num 1.21e+08 339s ..$ nbrOfLoci : int 7586 339s ..$ mean : num 0.512 339s $ segRows:'data.frame': 1 obs. of 2 variables: 339s ..$ startRow: int 1 339s ..$ endRow : int 7586 339s $ params :List of 7 339s ..$ undo.splits : chr "sdundo" 339s ..$ undo.SD : num Inf 339s ..$ alpha : num 0.001 339s ..$ undo : num Inf 339s ..$ joinSegments : logi TRUE 339s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 339s .. ..$ chromosome: int 1 339s .. ..$ start : num 554484 339s .. ..$ end : num 1.21e+08 339s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 339s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 339s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.001 0 0.002 0 0 339s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 339s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 339s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 339s DH segmentation (locally-indexed) rows: 339s startRow endRow 339s 1 1 7586 339s int [1:7586] 1 2 3 4 5 6 7 8 9 10 ... 339s DH segmentation rows: 339s startRow endRow 339s 1 1 7586 339s Segmenting DH signals...done 339s DH segmentation table: 339s dhStart dhEnd dhNbrOfLoci dhMean 339s 1 554484 120992603 7586 0.511612 339s startRow endRow 339s 1 1 7586 339s Rows: 339s [1] 1 339s TCN segmentation rows: 339s startRow endRow 339s 1 1 7586 339s TCN and DH segmentation rows: 339s startRow endRow 339s 1 1 7586 339s startRow endRow 339s 1 1 7586 339s NULL 339s TCN segmentation (expanded) rows: 339s startRow endRow 339s 1 1 7586 339s TCN and DH segmentation rows: 339s startRow endRow 339s 1 1 7586 339s 2 7587 14658 339s startRow endRow 339s 1 1 7586 339s startRow endRow 339s 1 1 7586 339s Total CN segmentation table (expanded): 339s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 339s 1 1 554484 120992603 7586 1.385258 2108 2108 339s (TCN,DH) segmentation for one total CN segment: 339s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 339s 1 1 1 1 554484 120992603 7586 1.385258 2108 339s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 339s 1 2108 554484 120992603 7586 0.511612 339s Total CN segment #1 ([ 554484,1.20993e+08]) of 2...done 339s Total CN segment #2 ([1.4151e+08,2.47137e+08]) of 2... 339s Number of TCN loci in segment: 7072 339s Locus data for TCN segment: 339s 'data.frame': 7072 obs. of 9 variables: 339s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 339s $ x : num 1.43e+08 1.43e+08 1.43e+08 1.43e+08 1.44e+08 ... 339s $ CT : num 2.27 1.55 1.47 1.5 1.81 ... 339s $ betaT : num 0.34 0.55 0.048 0.813 0.575 ... 339s $ betaTN : num 0.441 0.629 -0.05 0.958 0.872 ... 339s $ betaN : num 0.3851 0.3933 0.0981 0.8552 0.7028 ... 339s $ muN : num 0.5 0.5 0 1 1 1 1 0.5 1 1 ... 339s $ index : int 7587 7588 7589 7590 7591 7592 7593 7594 7595 7596 ... 339s $ rho : num 0.117 0.258 NA NA NA ... 339s Number of loci: 7072 339s Number of SNPs: 2088 (29.52%) 339s Number of heterozygous SNPs: 2088 (100.00%) 339s Chromosome: 1 339s Segmenting DH signals... 339s Segmenting by CBS... 339s Chromosome: 1 339s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 339s Segmenting by CBS...done 339s List of 4 339s $ data :'data.frame': 7072 obs. of 4 variables: 339s ..$ chromosome: int [1:7072] 1 1 1 1 1 1 1 1 1 1 ... 339s ..$ x : num [1:7072] 1.43e+08 1.43e+08 1.43e+08 1.43e+08 1.44e+08 ... 339s ..$ y : num [1:7072] 0.117 0.258 NA NA NA ... 339s ..$ index : int [1:7072] 1 2 3 4 5 6 7 8 9 10 ... 339s $ output :'data.frame': 1 obs. of 6 variables: 339s ..$ sampleName: chr NA 339s ..$ chromosome: int 1 339s ..$ start : num 1.42e+08 339s ..$ end : num 2.47e+08 339s ..$ nbrOfLoci : int 7072 339s ..$ mean : num 0.18 339s $ segRows:'data.frame': 1 obs. of 2 variables: 339s ..$ startRow: int 1 339s ..$ endRow : int 7072 339s $ params :List of 7 339s ..$ undo.splits : chr "sdundo" 339s ..$ undo.SD : num Inf 339s ..$ alpha : num 0.001 339s ..$ undo : num Inf 339s ..$ joinSegments : logi TRUE 339s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 339s .. ..$ chromosome: int 1 339s .. ..$ start : num 1.42e+08 339s .. ..$ end : num 2.47e+08 339s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 339s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 339s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.002 0 0.001 0 0 339s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 339s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 339s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 339s DH segmentation (locally-indexed) rows: 339s startRow endRow 339s 1 1 7072 339s int [1:7072] 7587 7588 7589 7590 7591 7592 7593 7594 7595 7596 ... 339s DH segmentation rows: 339s startRow endRow 339s 1 7587 14658 339s Segmenting DH signals...done 339s DH segmentation table: 339s dhStart dhEnd dhNbrOfLoci dhMean 339s 1 141510003 247137334 7072 0.1803011 339s startRow endRow 339s 1 7587 14658 339s Rows: 339s [1] 2 339s TCN segmentation rows: 339s startRow endRow 339s 2 7587 14658 339s TCN and DH segmentation rows: 339s startRow endRow 339s 2 7587 14658 339s startRow endRow 339s 1 7587 14658 339s startRow endRow 339s 1 1 7586 339s TCN segmentation (expanded) rows: 339s startRow endRow 339s 1 1 7586 339s 2 7587 14658 339s TCN and DH segmentation rows: 339s startRow endRow 339s 1 1 7586 339s 2 7587 14658 339s startRow endRow 339s 1 1 7586 339s 2 7587 14658 339s startRow endRow 339s 1 1 7586 339s 2 7587 14658 339s Total CN segmentation table (expanded): 339s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 339s 2 1 141510003 247137334 7072 2.419824 2088 339s tcnNbrOfHets 339s 2 2088 339s (TCN,DH) segmentation for one total CN segment: 339s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 339s 2 2 1 1 141510003 247137334 7072 2.419824 2088 339s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 339s 2 2088 141510003 247137334 7072 0.1803011 339s Total CN segment #2 ([1.4151e+08,2.47137e+08]) of 2...done 339s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 339s 1 1 1 1 554484 120992603 7586 1.385258 2108 339s 2 1 2 1 141510003 247137334 7072 2.419824 2088 339s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 339s 1 2108 554484 120992603 7586 0.5116120 339s 2 2088 141510003 247137334 7072 0.1803011 339s Calculating (C1,C2) per segment... 339s Calculating (C1,C2) per segment...done 339s Number of segments: 2 339s Segmenting paired tumor-normal signals using Paired PSCBS...done 339s Post-segmenting TCNs... 339s Number of segments: 2 339s Number of chromosomes: 1 339s [1] 1 339s Chromosome 1 ('chr01') of 1... 339s Rows: 339s [1] 1 2 339s Number of segments: 2 339s TCN segment #1 ('1') of 2... 339s Nothing todo. Only one DH segmentation. Skipping. 339s TCN segment #1 ('1') of 2...done 339s TCN segment #2 ('2') of 2... 339s Nothing todo. Only one DH segmentation. Skipping. 339s TCN segment #2 ('2') of 2...done 339s Chromosome 1 ('chr01') of 1...done 339s Update (C1,C2) per segment... 339s Update (C1,C2) per segment...done 339s Post-segmenting TCNs...done 339s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 339s 1 1 1 1 554484 120992603 7586 1.385258 2108 339s 2 1 2 1 141510003 247137334 7072 2.419824 2088 339s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 339s 1 2108 554484 120992603 7586 0.5116120 0.3382717 1.046986 339s 2 2088 141510003 247137334 7072 0.1803011 0.9917635 1.428060 339s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 339s 1 1 1 1 554484 120992603 7586 1.385258 2108 339s 2 1 2 1 141510003 247137334 7072 2.419824 2088 339s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 339s 1 2108 554484 120992603 7586 0.5116120 0.3382717 1.046986 339s 2 2088 141510003 247137334 7072 0.1803011 0.9917635 1.428060 339s > print(fit) 339s chromosome tcnId dhId start end tcnNbrOfLoci tcnMean tcnNbrOfSNPs 339s 1 1 1 1 554484 120992603 7586 1.385258 2108 339s 2 1 2 1 141510003 247137334 7072 2.419824 2088 339s tcnNbrOfHets dhNbrOfLoci dhMean c1Mean c2Mean 339s 1 2108 7586 0.5116120 0.3382717 1.046986 339s 2 2088 7072 0.1803011 0.9917635 1.428060 339s > 339s > # Plot results 339s > dev.set(5L) 339s pdf 339s 2 339s > plotTracks(fit) 339s > abline(v=c(knownSegments$start, knownSegments$end)/1e6, lty=3) 339s > 339s > # Sanity check 339s > stopifnot(nbrOfSegments(fit) == nrow(knownSegments)) 339s > 339s > fit4 <- fit 339s > 339s > 339s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 339s > # Tiling multiple chromosomes 339s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 339s > # Simulate multiple chromosomes 339s > fit1 <- fit 339s > fit2 <- renameChromosomes(fit, from=1, to=2) 339s > fitM <- c(fit1, fit2) 339s > 339s > # Tile chromosomes 339s > fitT <- tileChromosomes(fitM) 339s > fitTb <- tileChromosomes(fitT) 339s > stopifnot(identical(fitTb, fitT)) 339s > 339s > # Plotting multiple chromosomes 339s > plotTracks(fitT) 339s > 339s > proc.time() 339s user system elapsed 339s 5.790 0.055 5.847 339s Test segmentByPairedPSCBS passed 339s 0 340s autopkgtest [23:42:58]: test run-unit-test: -----------------------] 340s autopkgtest [23:42:58]: test run-unit-test: - - - - - - - - - - results - - - - - - - - - - 340s run-unit-test PASS 340s autopkgtest [23:42:58]: test pkg-r-autopkgtest: preparing testbed 348s Creating nova instance adt-resolute-ppc64el-r-cran-pscbs-20260209-233717-juju-7f2275-prod-proposed-migration-environment-2-0e67591c-a121-4fa1-828e-6000476eb62d from image adt/ubuntu-resolute-ppc64el-server-20260209.img (UUID f7f31435-4cd1-4090-aa55-59cfefa097ca)... 513s autopkgtest [23:45:51]: testbed dpkg architecture: ppc64el 513s autopkgtest [23:45:51]: testbed apt version: 3.1.15 513s autopkgtest [23:45:51]: @@@@@@@@@@@@@@@@@@@@ test bed setup 513s autopkgtest [23:45:51]: testbed release detected to be: resolute 514s autopkgtest [23:45:52]: updating testbed package index (apt update) 514s Get:1 http://ftpmaster.internal/ubuntu resolute-proposed InRelease [124 kB] 514s Hit:2 http://ftpmaster.internal/ubuntu resolute InRelease 515s Hit:3 http://ftpmaster.internal/ubuntu resolute-updates InRelease 515s Hit:4 http://ftpmaster.internal/ubuntu resolute-security InRelease 515s Get:5 http://ftpmaster.internal/ubuntu resolute-proposed/main Sources [176 kB] 515s Get:6 http://ftpmaster.internal/ubuntu resolute-proposed/universe Sources [1645 kB] 518s Get:7 http://ftpmaster.internal/ubuntu resolute-proposed/multiverse Sources [29.4 kB] 518s Get:8 http://ftpmaster.internal/ubuntu resolute-proposed/main ppc64el Packages [246 kB] 518s Get:9 http://ftpmaster.internal/ubuntu resolute-proposed/universe ppc64el Packages [1534 kB] 521s Get:10 http://ftpmaster.internal/ubuntu resolute-proposed/multiverse ppc64el Packages [19.4 kB] 521s Fetched 3774 kB in 7s (580 kB/s) 522s Reading package lists... 522s Hit:1 http://ftpmaster.internal/ubuntu resolute-proposed InRelease 522s Hit:2 http://ftpmaster.internal/ubuntu resolute InRelease 522s Hit:3 http://ftpmaster.internal/ubuntu resolute-updates InRelease 522s Hit:4 http://ftpmaster.internal/ubuntu resolute-security InRelease 523s Reading package lists... 523s Reading package lists... 523s Building dependency tree... 523s Reading state information... 524s Calculating upgrade... 524s The following packages will be upgraded: 524s cryptsetup-bin dracut-install iproute2 iptables libcryptsetup12 libip4tc2 524s libip6tc2 libxtables12 wget 524s 9 upgraded, 0 newly installed, 0 to remove and 0 not upgraded. 524s Need to get 3125 kB of archives. 524s After this operation, 78.8 kB of additional disk space will be used. 524s Get:1 http://ftpmaster.internal/ubuntu resolute/main ppc64el iptables ppc64el 1.8.11-2ubuntu3 [464 kB] 524s Get:2 http://ftpmaster.internal/ubuntu resolute/main ppc64el libip4tc2 ppc64el 1.8.11-2ubuntu3 [27.8 kB] 524s Get:3 http://ftpmaster.internal/ubuntu resolute/main ppc64el libip6tc2 ppc64el 1.8.11-2ubuntu3 [28.2 kB] 524s Get:4 http://ftpmaster.internal/ubuntu resolute/main ppc64el libxtables12 ppc64el 1.8.11-2ubuntu3 [41.2 kB] 524s Get:5 http://ftpmaster.internal/ubuntu resolute/main ppc64el iproute2 ppc64el 6.18.0-1ubuntu1 [1458 kB] 527s Get:6 http://ftpmaster.internal/ubuntu resolute/main ppc64el libcryptsetup12 ppc64el 2:2.8.0-1ubuntu3 [404 kB] 527s Get:7 http://ftpmaster.internal/ubuntu resolute/main ppc64el wget ppc64el 1.25.0-2ubuntu4 [401 kB] 527s Get:8 http://ftpmaster.internal/ubuntu resolute/main ppc64el cryptsetup-bin ppc64el 2:2.8.0-1ubuntu3 [250 kB] 527s Get:9 http://ftpmaster.internal/ubuntu resolute/main ppc64el dracut-install ppc64el 109-11ubuntu1 [51.3 kB] 527s dpkg-preconfigure: unable to re-open stdin: No such file or directory 527s Fetched 3125 kB in 3s (1054 kB/s) 527s (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 ... 122003 files and directories currently installed.) 527s Preparing to unpack .../0-iptables_1.8.11-2ubuntu3_ppc64el.deb ... 528s Unpacking iptables (1.8.11-2ubuntu3) over (1.8.11-2ubuntu2) ... 528s Preparing to unpack .../1-libip4tc2_1.8.11-2ubuntu3_ppc64el.deb ... 528s Unpacking libip4tc2:ppc64el (1.8.11-2ubuntu3) over (1.8.11-2ubuntu2) ... 528s Preparing to unpack .../2-libip6tc2_1.8.11-2ubuntu3_ppc64el.deb ... 528s Unpacking libip6tc2:ppc64el (1.8.11-2ubuntu3) over (1.8.11-2ubuntu2) ... 528s Preparing to unpack .../3-libxtables12_1.8.11-2ubuntu3_ppc64el.deb ... 528s Unpacking libxtables12:ppc64el (1.8.11-2ubuntu3) over (1.8.11-2ubuntu2) ... 529s Preparing to unpack .../4-iproute2_6.18.0-1ubuntu1_ppc64el.deb ... 529s Unpacking iproute2 (6.18.0-1ubuntu1) over (6.16.0-1ubuntu3) ... 529s Preparing to unpack .../5-libcryptsetup12_2%3a2.8.0-1ubuntu3_ppc64el.deb ... 529s Unpacking libcryptsetup12:ppc64el (2:2.8.0-1ubuntu3) over (2:2.8.0-1ubuntu2) ... 529s Preparing to unpack .../6-wget_1.25.0-2ubuntu4_ppc64el.deb ... 529s Unpacking wget (1.25.0-2ubuntu4) over (1.25.0-2ubuntu3) ... 529s Preparing to unpack .../7-cryptsetup-bin_2%3a2.8.0-1ubuntu3_ppc64el.deb ... 529s Unpacking cryptsetup-bin (2:2.8.0-1ubuntu3) over (2:2.8.0-1ubuntu2) ... 529s Preparing to unpack .../8-dracut-install_109-11ubuntu1_ppc64el.deb ... 529s Unpacking dracut-install (109-11ubuntu1) over (109-9ubuntu1) ... 529s Setting up libip4tc2:ppc64el (1.8.11-2ubuntu3) ... 530s Setting up wget (1.25.0-2ubuntu4) ... 530s Setting up libip6tc2:ppc64el (1.8.11-2ubuntu3) ... 530s Setting up libxtables12:ppc64el (1.8.11-2ubuntu3) ... 530s Setting up dracut-install (109-11ubuntu1) ... 530s Setting up libcryptsetup12:ppc64el (2:2.8.0-1ubuntu3) ... 530s Setting up cryptsetup-bin (2:2.8.0-1ubuntu3) ... 530s Setting up iptables (1.8.11-2ubuntu3) ... 530s Setting up iproute2 (6.18.0-1ubuntu1) ... 530s Processing triggers for man-db (2.13.1-1build1) ... 532s Processing triggers for install-info (7.2-5) ... 533s Processing triggers for libc-bin (2.42-2ubuntu4) ... 533s autopkgtest [23:46:11]: upgrading testbed (apt dist-upgrade and autopurge) 533s Reading package lists... 533s Building dependency tree... 533s Reading state information... 533s Calculating upgrade... 533s 0 upgraded, 0 newly installed, 0 to remove and 0 not upgraded. 533s Reading package lists... 533s Building dependency tree... 533s Reading state information... 534s Solving dependencies... 534s 0 upgraded, 0 newly installed, 0 to remove and 0 not upgraded. 536s Reading package lists... 536s Building dependency tree... 536s Reading state information... 536s Solving dependencies... 536s The following NEW packages will be installed: 536s build-essential cpp cpp-15 cpp-15-powerpc64le-linux-gnu 536s cpp-powerpc64le-linux-gnu dctrl-tools fontconfig fontconfig-config 536s fonts-dejavu-core fonts-dejavu-mono g++ g++-15 g++-15-powerpc64le-linux-gnu 536s g++-powerpc64le-linux-gnu gcc gcc-15 gcc-15-powerpc64le-linux-gnu 536s gcc-powerpc64le-linux-gnu gfortran gfortran-15 536s gfortran-15-powerpc64le-linux-gnu gfortran-powerpc64le-linux-gnu 536s icu-devtools libasan8 libblas-dev libblas3 libbz2-dev libc-dev-bin libc6-dev 536s libcairo2 libcc1-0 libcrypt-dev libdatrie1 libdeflate-dev libdeflate0 536s libfontconfig1 libgcc-15-dev libgfortran-15-dev libgfortran5 libgomp1 536s libgraphite2-3 libharfbuzz0b libice6 libicu-dev libisl23 libitm1 libjbig0 536s libjpeg-dev libjpeg-turbo8 libjpeg-turbo8-dev libjpeg8 libjpeg8-dev 536s liblapack-dev liblapack3 liblerc4 liblsan0 liblzma-dev libmpc3 536s libncurses-dev libpango-1.0-0 libpangocairo-1.0-0 libpangoft2-1.0-0 536s libpaper-utils libpaper2 libpcre2-16-0 libpcre2-32-0 libpcre2-dev 536s libpcre2-posix3 libpixman-1-0 libpkgconf3 libpng-dev libquadmath0 536s libreadline-dev libsharpyuv0 libsm6 libstdc++-15-dev libtcl8.6 libthai-data 536s libthai0 libtiff6 libtirpc-dev libtk8.6 libtsan2 libubsan1 libwebp7 536s libxcb-render0 libxcb-shm0 libxft2 libxrender1 libxss1 libxt6t64 libzstd-dev 536s linux-libc-dev pkg-r-autopkgtest pkgconf pkgconf-bin r-base-core r-base-dev 536s r-bioc-aroma.light r-bioc-biocgenerics r-bioc-dnacopy r-cran-cli 536s r-cran-codetools r-cran-digest r-cran-farver r-cran-future r-cran-ggplot2 536s r-cran-globals r-cran-glue r-cran-gtable r-cran-isoband r-cran-labeling 536s r-cran-lifecycle r-cran-listenv r-cran-matrixstats r-cran-parallelly 536s r-cran-pscbs r-cran-r.cache r-cran-r.methodss3 r-cran-r.oo r-cran-r.utils 536s r-cran-r6 r-cran-rcolorbrewer r-cran-rlang r-cran-s7 r-cran-scales 536s r-cran-vctrs r-cran-viridislite r-cran-withr rpcsvc-proto unzip x11-common 536s xdg-utils zip zlib1g-dev 537s 0 upgraded, 135 newly installed, 0 to remove and 0 not upgraded. 537s Need to get 172 MB of archives. 537s After this operation, 522 MB of additional disk space will be used. 537s Get:1 http://ftpmaster.internal/ubuntu resolute/main ppc64el libc-dev-bin ppc64el 2.42-2ubuntu4 [23.9 kB] 537s Get:2 http://ftpmaster.internal/ubuntu resolute/main ppc64el linux-libc-dev ppc64el 6.19.0-3.3 [1832 kB] 540s Get:3 http://ftpmaster.internal/ubuntu resolute/main ppc64el libcrypt-dev ppc64el 1:4.5.1-1 [162 kB] 540s Get:4 http://ftpmaster.internal/ubuntu resolute/main ppc64el rpcsvc-proto ppc64el 1.4.3-1build1 [84.2 kB] 540s Get:5 http://ftpmaster.internal/ubuntu resolute/main ppc64el libc6-dev ppc64el 2.42-2ubuntu4 [2080 kB] 544s Get:6 http://ftpmaster.internal/ubuntu resolute/main ppc64el libisl23 ppc64el 0.27-1build1 [893 kB] 546s Get:7 http://ftpmaster.internal/ubuntu resolute/main ppc64el libmpc3 ppc64el 1.3.1-2 [62.5 kB] 546s Get:8 http://ftpmaster.internal/ubuntu resolute/main ppc64el cpp-15-powerpc64le-linux-gnu ppc64el 15.2.0-12ubuntu1 [11.4 MB] 569s Get:9 http://ftpmaster.internal/ubuntu resolute/main ppc64el cpp-15 ppc64el 15.2.0-12ubuntu1 [1038 B] 569s Get:10 http://ftpmaster.internal/ubuntu resolute/main ppc64el cpp-powerpc64le-linux-gnu ppc64el 4:15.2.0-4ubuntu1 [5746 B] 569s Get:11 http://ftpmaster.internal/ubuntu resolute/main ppc64el cpp ppc64el 4:15.2.0-4ubuntu1 [22.4 kB] 569s Get:12 http://ftpmaster.internal/ubuntu resolute/main ppc64el libcc1-0 ppc64el 15.2.0-12ubuntu1 [49.0 kB] 569s Get:13 http://ftpmaster.internal/ubuntu resolute/main ppc64el libgomp1 ppc64el 15.2.0-12ubuntu1 [169 kB] 569s Get:14 http://ftpmaster.internal/ubuntu resolute/main ppc64el libitm1 ppc64el 15.2.0-12ubuntu1 [32.2 kB] 569s Get:15 http://ftpmaster.internal/ubuntu resolute/main ppc64el libasan8 ppc64el 15.2.0-12ubuntu1 [3006 kB] 575s Get:16 http://ftpmaster.internal/ubuntu resolute/main ppc64el liblsan0 ppc64el 15.2.0-12ubuntu1 [1374 kB] 578s Get:17 http://ftpmaster.internal/ubuntu resolute/main ppc64el libtsan2 ppc64el 15.2.0-12ubuntu1 [2729 kB] 582s Get:18 http://ftpmaster.internal/ubuntu resolute/main ppc64el libubsan1 ppc64el 15.2.0-12ubuntu1 [1231 kB] 587s Get:19 http://ftpmaster.internal/ubuntu resolute/main ppc64el libquadmath0 ppc64el 15.2.0-12ubuntu1 [160 kB] 587s Get:20 http://ftpmaster.internal/ubuntu resolute/main ppc64el libgcc-15-dev ppc64el 15.2.0-12ubuntu1 [1670 kB] 592s Get:21 http://ftpmaster.internal/ubuntu resolute/main ppc64el gcc-15-powerpc64le-linux-gnu ppc64el 15.2.0-12ubuntu1 [22.4 MB] 649s Get:22 http://ftpmaster.internal/ubuntu resolute/main ppc64el gcc-15 ppc64el 15.2.0-12ubuntu1 [530 kB] 650s Get:23 http://ftpmaster.internal/ubuntu resolute/main ppc64el gcc-powerpc64le-linux-gnu ppc64el 4:15.2.0-4ubuntu1 [1220 B] 650s Get:24 http://ftpmaster.internal/ubuntu resolute/main ppc64el gcc ppc64el 4:15.2.0-4ubuntu1 [5032 B] 650s Get:25 http://ftpmaster.internal/ubuntu resolute/main ppc64el libstdc++-15-dev ppc64el 15.2.0-12ubuntu1 [2747 kB] 656s Get:26 http://ftpmaster.internal/ubuntu resolute/main ppc64el g++-15-powerpc64le-linux-gnu ppc64el 15.2.0-12ubuntu1 [13.0 MB] 684s Get:27 http://ftpmaster.internal/ubuntu resolute/main ppc64el g++-15 ppc64el 15.2.0-12ubuntu1 [25.3 kB] 684s Get:28 http://ftpmaster.internal/ubuntu resolute/main ppc64el g++-powerpc64le-linux-gnu ppc64el 4:15.2.0-4ubuntu1 [970 B] 684s Get:29 http://ftpmaster.internal/ubuntu resolute/main ppc64el g++ ppc64el 4:15.2.0-4ubuntu1 [1092 B] 684s Get:30 http://ftpmaster.internal/ubuntu resolute/main ppc64el build-essential ppc64el 12.12ubuntu2 [5256 B] 684s Get:31 http://ftpmaster.internal/ubuntu resolute/main ppc64el dctrl-tools ppc64el 2.24-3build4 [108 kB] 684s Get:32 http://ftpmaster.internal/ubuntu resolute/main ppc64el fonts-dejavu-mono all 2.37-8build1 [502 kB] 684s Get:33 http://ftpmaster.internal/ubuntu resolute/main ppc64el fonts-dejavu-core all 2.37-8build1 [834 kB] 686s Get:34 http://ftpmaster.internal/ubuntu resolute/main ppc64el fontconfig-config ppc64el 2.17.1-3ubuntu1 [38.5 kB] 686s Get:35 http://ftpmaster.internal/ubuntu resolute/main ppc64el libfontconfig1 ppc64el 2.17.1-3ubuntu1 [193 kB] 686s Get:36 http://ftpmaster.internal/ubuntu resolute/main ppc64el fontconfig ppc64el 2.17.1-3ubuntu1 [182 kB] 686s Get:37 http://ftpmaster.internal/ubuntu resolute/main ppc64el libgfortran5 ppc64el 15.2.0-12ubuntu1 [620 kB] 687s Get:38 http://ftpmaster.internal/ubuntu resolute/main ppc64el libgfortran-15-dev ppc64el 15.2.0-12ubuntu1 [651 kB] 688s Get:39 http://ftpmaster.internal/ubuntu resolute/main ppc64el gfortran-15-powerpc64le-linux-gnu ppc64el 15.2.0-12ubuntu1 [12.3 MB] 714s Get:40 http://ftpmaster.internal/ubuntu resolute/main ppc64el gfortran-15 ppc64el 15.2.0-12ubuntu1 [18.1 kB] 714s Get:41 http://ftpmaster.internal/ubuntu resolute/main ppc64el gfortran-powerpc64le-linux-gnu ppc64el 4:15.2.0-4ubuntu1 [1020 B] 714s Get:42 http://ftpmaster.internal/ubuntu resolute/main ppc64el gfortran ppc64el 4:15.2.0-4ubuntu1 [1166 B] 714s Get:43 http://ftpmaster.internal/ubuntu resolute/main ppc64el icu-devtools ppc64el 78.2-1ubuntu1 [246 kB] 714s Get:44 http://ftpmaster.internal/ubuntu resolute/main ppc64el libblas3 ppc64el 3.12.1-7ubuntu1 [291 kB] 714s Get:45 http://ftpmaster.internal/ubuntu resolute/main ppc64el libblas-dev ppc64el 3.12.1-7ubuntu1 [306 kB] 714s Get:46 http://ftpmaster.internal/ubuntu resolute/main ppc64el libbz2-dev ppc64el 1.0.8-6build2 [50.0 kB] 714s Get:47 http://ftpmaster.internal/ubuntu resolute/main ppc64el libpixman-1-0 ppc64el 0.46.4-1 [347 kB] 714s Get:48 http://ftpmaster.internal/ubuntu resolute/main ppc64el libxcb-render0 ppc64el 1.17.0-2ubuntu1 [17.4 kB] 714s Get:49 http://ftpmaster.internal/ubuntu resolute/main ppc64el libxcb-shm0 ppc64el 1.17.0-2ubuntu1 [6072 B] 714s Get:50 http://ftpmaster.internal/ubuntu resolute/main ppc64el libxrender1 ppc64el 1:0.9.12-1 [23.0 kB] 714s Get:51 http://ftpmaster.internal/ubuntu resolute/main ppc64el libcairo2 ppc64el 1.18.4-3 [759 kB] 720s Get:52 http://ftpmaster.internal/ubuntu resolute/main ppc64el libdatrie1 ppc64el 0.2.14-1 [22.7 kB] 720s Get:53 http://ftpmaster.internal/ubuntu resolute/main ppc64el libdeflate0 ppc64el 1.23-2build1 [64.1 kB] 720s Get:54 http://ftpmaster.internal/ubuntu resolute/main ppc64el libdeflate-dev ppc64el 1.23-2build1 [71.8 kB] 720s Get:55 http://ftpmaster.internal/ubuntu resolute/main ppc64el libgraphite2-3 ppc64el 1.3.14-11ubuntu1 [85.3 kB] 720s Get:56 http://ftpmaster.internal/ubuntu resolute/main ppc64el libharfbuzz0b ppc64el 12.3.2-1 [663 kB] 721s Get:57 http://ftpmaster.internal/ubuntu resolute/main ppc64el x11-common all 1:7.7+24ubuntu1 [22.4 kB] 721s Get:58 http://ftpmaster.internal/ubuntu resolute/main ppc64el libice6 ppc64el 2:1.1.1-1build1 [51.9 kB] 721s Get:59 http://ftpmaster.internal/ubuntu resolute/main ppc64el libicu-dev ppc64el 78.2-1ubuntu1 [13.3 MB] 749s Get:60 http://ftpmaster.internal/ubuntu resolute/main ppc64el libjpeg-turbo8 ppc64el 2.1.5-4ubuntu3 [214 kB] 749s Get:61 http://ftpmaster.internal/ubuntu resolute/main ppc64el libjpeg-turbo8-dev ppc64el 2.1.5-4ubuntu3 [358 kB] 749s Get:62 http://ftpmaster.internal/ubuntu resolute/main ppc64el libjpeg8 ppc64el 8c-2ubuntu11 [2148 B] 749s Get:63 http://ftpmaster.internal/ubuntu resolute/main ppc64el libjpeg8-dev ppc64el 8c-2ubuntu11 [1484 B] 749s Get:64 http://ftpmaster.internal/ubuntu resolute/main ppc64el libjpeg-dev ppc64el 8c-2ubuntu11 [1486 B] 749s Get:65 http://ftpmaster.internal/ubuntu resolute/main ppc64el liblapack3 ppc64el 3.12.1-7ubuntu1 [2960 kB] 755s Get:66 http://ftpmaster.internal/ubuntu resolute/main ppc64el liblapack-dev ppc64el 3.12.1-7ubuntu1 [6357 kB] 771s Get:67 http://ftpmaster.internal/ubuntu resolute/main ppc64el liblerc4 ppc64el 4.0.0+ds-5ubuntu2 [315 kB] 771s Get:68 http://ftpmaster.internal/ubuntu resolute/main ppc64el libncurses-dev ppc64el 6.6+20251231-1 [505 kB] 771s Get:69 http://ftpmaster.internal/ubuntu resolute/main ppc64el libthai-data all 0.1.30-1 [155 kB] 771s Get:70 http://ftpmaster.internal/ubuntu resolute/main ppc64el libthai0 ppc64el 0.1.30-1 [22.5 kB] 771s Get:71 http://ftpmaster.internal/ubuntu resolute/main ppc64el libpango-1.0-0 ppc64el 1.57.0-1 [283 kB] 771s Get:72 http://ftpmaster.internal/ubuntu resolute/main ppc64el libpangoft2-1.0-0 ppc64el 1.57.0-1 [61.2 kB] 771s Get:73 http://ftpmaster.internal/ubuntu resolute/main ppc64el libpangocairo-1.0-0 ppc64el 1.57.0-1 [31.0 kB] 771s Get:74 http://ftpmaster.internal/ubuntu resolute/main ppc64el libpaper2 ppc64el 2.2.5-0.3build1 [18.1 kB] 771s Get:75 http://ftpmaster.internal/ubuntu resolute/main ppc64el libpaper-utils ppc64el 2.2.5-0.3build1 [15.7 kB] 771s Get:76 http://ftpmaster.internal/ubuntu resolute/main ppc64el libpcre2-16-0 ppc64el 10.46-1 [292 kB] 771s Get:77 http://ftpmaster.internal/ubuntu resolute/main ppc64el libpcre2-32-0 ppc64el 10.46-1 [275 kB] 771s Get:78 http://ftpmaster.internal/ubuntu resolute/main ppc64el libpcre2-posix3 ppc64el 10.46-1 [7334 B] 771s Get:79 http://ftpmaster.internal/ubuntu resolute/main ppc64el libpcre2-dev ppc64el 10.46-1 [937 kB] 773s Get:80 http://ftpmaster.internal/ubuntu resolute/main ppc64el libpkgconf3 ppc64el 1.8.1-4build1 [37.9 kB] 773s Get:81 http://ftpmaster.internal/ubuntu resolute/main ppc64el zlib1g-dev ppc64el 1:1.3.dfsg+really1.3.1-1ubuntu2 [903 kB] 775s Get:82 http://ftpmaster.internal/ubuntu resolute/main ppc64el libpng-dev ppc64el 1.6.54-1 [326 kB] 775s Get:83 http://ftpmaster.internal/ubuntu resolute/main ppc64el libreadline-dev ppc64el 8.3-3 [252 kB] 775s Get:84 http://ftpmaster.internal/ubuntu resolute/main ppc64el libsharpyuv0 ppc64el 1.5.0-0.1build1 [24.7 kB] 775s Get:85 http://ftpmaster.internal/ubuntu resolute/main ppc64el libsm6 ppc64el 2:1.2.6-1build1 [18.6 kB] 775s Get:86 http://ftpmaster.internal/ubuntu resolute/main ppc64el libtcl8.6 ppc64el 8.6.17+dfsg-1build1 [1239 kB] 778s Get:87 http://ftpmaster.internal/ubuntu resolute/main ppc64el libjbig0 ppc64el 2.1-6.1ubuntu3 [37.1 kB] 778s Get:88 http://ftpmaster.internal/ubuntu resolute/main ppc64el libwebp7 ppc64el 1.5.0-0.1build1 [330 kB] 778s Get:89 http://ftpmaster.internal/ubuntu resolute/main ppc64el libtiff6 ppc64el 4.7.0-3ubuntu3 [307 kB] 778s Get:90 http://ftpmaster.internal/ubuntu resolute/main ppc64el libxft2 ppc64el 2.3.6-1build2 [61.6 kB] 778s Get:91 http://ftpmaster.internal/ubuntu resolute/main ppc64el libxss1 ppc64el 1:1.2.3-1build4 [7470 B] 778s Get:92 http://ftpmaster.internal/ubuntu resolute/main ppc64el libtk8.6 ppc64el 8.6.17-1 [968 kB] 780s Get:93 http://ftpmaster.internal/ubuntu resolute/main ppc64el libxt6t64 ppc64el 1:1.2.1-1.3 [203 kB] 780s Get:94 http://ftpmaster.internal/ubuntu resolute/main ppc64el libzstd-dev ppc64el 1.5.7+dfsg-3 [528 kB] 781s Get:95 http://ftpmaster.internal/ubuntu resolute/main ppc64el zip ppc64el 3.0-15ubuntu3 [198 kB] 781s Get:96 http://ftpmaster.internal/ubuntu resolute/main ppc64el unzip ppc64el 6.0-29ubuntu1 [200 kB] 781s Get:97 http://ftpmaster.internal/ubuntu resolute/main ppc64el xdg-utils all 1.2.1-2ubuntu2 [66.1 kB] 781s Get:98 http://ftpmaster.internal/ubuntu resolute/universe ppc64el r-base-core ppc64el 4.5.2-1ubuntu2 [29.3 MB] 846s Get:99 http://ftpmaster.internal/ubuntu resolute/main ppc64el liblzma-dev ppc64el 5.8.2-2 [210 kB] 846s Get:100 http://ftpmaster.internal/ubuntu resolute/main ppc64el pkgconf-bin ppc64el 1.8.1-4build1 [22.7 kB] 846s Get:101 http://ftpmaster.internal/ubuntu resolute/main ppc64el pkgconf ppc64el 1.8.1-4build1 [16.8 kB] 846s Get:102 http://ftpmaster.internal/ubuntu resolute/main ppc64el libtirpc-dev ppc64el 1.3.6+ds-1 [223 kB] 846s Get:103 http://ftpmaster.internal/ubuntu resolute/universe ppc64el r-base-dev all 4.5.2-1ubuntu2 [1880 B] 846s Get:104 http://ftpmaster.internal/ubuntu resolute/universe ppc64el pkg-r-autopkgtest all 20250812 [6158 B] 846s Get:105 http://ftpmaster.internal/ubuntu resolute/universe ppc64el r-bioc-biocgenerics all 0.52.0-2 [624 kB] 848s Get:106 http://ftpmaster.internal/ubuntu resolute/universe ppc64el r-cran-r.methodss3 all 1.8.2-1 [84.0 kB] 848s Get:107 http://ftpmaster.internal/ubuntu resolute/universe ppc64el r-cran-r.oo all 1.27.1-1 [978 kB] 850s Get:108 http://ftpmaster.internal/ubuntu resolute/universe ppc64el r-cran-r.utils all 2.13.0-1 [1423 kB] 853s Get:109 http://ftpmaster.internal/ubuntu resolute/universe ppc64el r-cran-matrixstats ppc64el 1.5.0-1 [578 kB] 855s Get:110 http://ftpmaster.internal/ubuntu resolute/universe ppc64el r-bioc-aroma.light all 3.36.0-2 [583 kB] 858s Get:111 http://ftpmaster.internal/ubuntu resolute/universe ppc64el r-bioc-dnacopy ppc64el 1.80.0-2 [504 kB] 858s Get:112 http://ftpmaster.internal/ubuntu resolute/universe ppc64el r-cran-cli ppc64el 3.6.4-1 [1411 kB] 861s Get:113 http://ftpmaster.internal/ubuntu resolute/universe ppc64el r-cran-codetools all 0.2-20-1build1 [91.1 kB] 861s Get:114 http://ftpmaster.internal/ubuntu resolute/universe ppc64el r-cran-digest ppc64el 0.6.39-1 [238 kB] 861s Get:115 http://ftpmaster.internal/ubuntu resolute/universe ppc64el r-cran-farver ppc64el 2.1.2-1 [1389 kB] 865s Get:116 http://ftpmaster.internal/ubuntu resolute/universe ppc64el r-cran-globals all 0.19.0-1 [160 kB] 865s Get:117 http://ftpmaster.internal/ubuntu resolute/universe ppc64el r-cran-listenv all 0.10.0+dfsg-1 [113 kB] 865s Get:118 http://ftpmaster.internal/ubuntu resolute/universe ppc64el r-cran-parallelly ppc64el 1.42.0-1 [540 kB] 868s Get:119 http://ftpmaster.internal/ubuntu resolute/universe ppc64el r-cran-future all 1.34.0+dfsg-1 [646 kB] 870s Get:120 http://ftpmaster.internal/ubuntu resolute/universe ppc64el r-cran-glue ppc64el 1.8.0-1 [165 kB] 870s Get:121 http://ftpmaster.internal/ubuntu resolute/universe ppc64el r-cran-rlang ppc64el 1.1.5-3 [1738 kB] 878s Get:122 http://ftpmaster.internal/ubuntu resolute/universe ppc64el r-cran-lifecycle all 1.0.5+dfsg-1 [120 kB] 878s Get:123 http://ftpmaster.internal/ubuntu resolute/universe ppc64el r-cran-gtable all 0.3.6+dfsg-1 [199 kB] 879s Get:124 http://ftpmaster.internal/ubuntu resolute/universe ppc64el r-cran-isoband ppc64el 0.2.7-1 [1486 kB] 882s Get:125 http://ftpmaster.internal/ubuntu resolute/universe ppc64el r-cran-s7 ppc64el 0.2.0-1 [330 kB] 882s Get:126 http://ftpmaster.internal/ubuntu resolute/universe ppc64el r-cran-labeling all 0.4.3-1 [62.1 kB] 882s Get:127 http://ftpmaster.internal/ubuntu resolute/universe ppc64el r-cran-r6 all 2.6.1-1 [101 kB] 882s Get:128 http://ftpmaster.internal/ubuntu resolute/universe ppc64el r-cran-rcolorbrewer all 1.1-3-1build2 [54.0 kB] 882s Get:129 http://ftpmaster.internal/ubuntu resolute/universe ppc64el r-cran-viridislite all 0.4.3-1 [1088 kB] 884s Get:130 http://ftpmaster.internal/ubuntu resolute/universe ppc64el r-cran-scales all 1.4.0-1 [725 kB] 886s Get:131 http://ftpmaster.internal/ubuntu resolute/universe ppc64el r-cran-vctrs ppc64el 0.6.5-1 [1399 kB] 888s Get:132 http://ftpmaster.internal/ubuntu resolute/universe ppc64el r-cran-withr all 3.0.2+dfsg-1 [214 kB] 889s Get:133 http://ftpmaster.internal/ubuntu resolute-proposed/universe ppc64el r-cran-ggplot2 all 4.0.2+dfsg-1 [4941 kB] 899s Get:134 http://ftpmaster.internal/ubuntu resolute/universe ppc64el r-cran-r.cache all 0.17.0-1 [117 kB] 899s Get:135 http://ftpmaster.internal/ubuntu resolute/universe ppc64el r-cran-pscbs all 0.68.0-1 [4234 kB] 912s Preconfiguring packages ... 912s Fetched 172 MB in 6min 15s (458 kB/s) 912s Selecting previously unselected package libc-dev-bin. 912s (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 ... 122006 files and directories currently installed.) 912s Preparing to unpack .../000-libc-dev-bin_2.42-2ubuntu4_ppc64el.deb ... 912s Unpacking libc-dev-bin (2.42-2ubuntu4) ... 912s Selecting previously unselected package linux-libc-dev:ppc64el. 912s Preparing to unpack .../001-linux-libc-dev_6.19.0-3.3_ppc64el.deb ... 912s Unpacking linux-libc-dev:ppc64el (6.19.0-3.3) ... 912s Selecting previously unselected package libcrypt-dev:ppc64el. 912s Preparing to unpack .../002-libcrypt-dev_1%3a4.5.1-1_ppc64el.deb ... 912s Unpacking libcrypt-dev:ppc64el (1:4.5.1-1) ... 912s Selecting previously unselected package rpcsvc-proto. 912s Preparing to unpack .../003-rpcsvc-proto_1.4.3-1build1_ppc64el.deb ... 912s Unpacking rpcsvc-proto (1.4.3-1build1) ... 912s Selecting previously unselected package libc6-dev:ppc64el. 912s Preparing to unpack .../004-libc6-dev_2.42-2ubuntu4_ppc64el.deb ... 912s Unpacking libc6-dev:ppc64el (2.42-2ubuntu4) ... 913s Selecting previously unselected package libisl23:ppc64el. 913s Preparing to unpack .../005-libisl23_0.27-1build1_ppc64el.deb ... 913s Unpacking libisl23:ppc64el (0.27-1build1) ... 913s Selecting previously unselected package libmpc3:ppc64el. 913s Preparing to unpack .../006-libmpc3_1.3.1-2_ppc64el.deb ... 913s Unpacking libmpc3:ppc64el (1.3.1-2) ... 913s Selecting previously unselected package cpp-15-powerpc64le-linux-gnu. 913s Preparing to unpack .../007-cpp-15-powerpc64le-linux-gnu_15.2.0-12ubuntu1_ppc64el.deb ... 913s Unpacking cpp-15-powerpc64le-linux-gnu (15.2.0-12ubuntu1) ... 913s Selecting previously unselected package cpp-15. 913s Preparing to unpack .../008-cpp-15_15.2.0-12ubuntu1_ppc64el.deb ... 913s Unpacking cpp-15 (15.2.0-12ubuntu1) ... 913s Selecting previously unselected package cpp-powerpc64le-linux-gnu. 913s Preparing to unpack .../009-cpp-powerpc64le-linux-gnu_4%3a15.2.0-4ubuntu1_ppc64el.deb ... 913s Unpacking cpp-powerpc64le-linux-gnu (4:15.2.0-4ubuntu1) ... 913s Selecting previously unselected package cpp. 913s Preparing to unpack .../010-cpp_4%3a15.2.0-4ubuntu1_ppc64el.deb ... 913s Unpacking cpp (4:15.2.0-4ubuntu1) ... 913s Selecting previously unselected package libcc1-0:ppc64el. 913s Preparing to unpack .../011-libcc1-0_15.2.0-12ubuntu1_ppc64el.deb ... 913s Unpacking libcc1-0:ppc64el (15.2.0-12ubuntu1) ... 913s Selecting previously unselected package libgomp1:ppc64el. 913s Preparing to unpack .../012-libgomp1_15.2.0-12ubuntu1_ppc64el.deb ... 913s Unpacking libgomp1:ppc64el (15.2.0-12ubuntu1) ... 913s Selecting previously unselected package libitm1:ppc64el. 913s Preparing to unpack .../013-libitm1_15.2.0-12ubuntu1_ppc64el.deb ... 913s Unpacking libitm1:ppc64el (15.2.0-12ubuntu1) ... 913s Selecting previously unselected package libasan8:ppc64el. 913s Preparing to unpack .../014-libasan8_15.2.0-12ubuntu1_ppc64el.deb ... 913s Unpacking libasan8:ppc64el (15.2.0-12ubuntu1) ... 913s Selecting previously unselected package liblsan0:ppc64el. 913s Preparing to unpack .../015-liblsan0_15.2.0-12ubuntu1_ppc64el.deb ... 913s Unpacking liblsan0:ppc64el (15.2.0-12ubuntu1) ... 913s Selecting previously unselected package libtsan2:ppc64el. 913s Preparing to unpack .../016-libtsan2_15.2.0-12ubuntu1_ppc64el.deb ... 913s Unpacking libtsan2:ppc64el (15.2.0-12ubuntu1) ... 913s Selecting previously unselected package libubsan1:ppc64el. 913s Preparing to unpack .../017-libubsan1_15.2.0-12ubuntu1_ppc64el.deb ... 913s Unpacking libubsan1:ppc64el (15.2.0-12ubuntu1) ... 913s Selecting previously unselected package libquadmath0:ppc64el. 913s Preparing to unpack .../018-libquadmath0_15.2.0-12ubuntu1_ppc64el.deb ... 913s Unpacking libquadmath0:ppc64el (15.2.0-12ubuntu1) ... 913s Selecting previously unselected package libgcc-15-dev:ppc64el. 913s Preparing to unpack .../019-libgcc-15-dev_15.2.0-12ubuntu1_ppc64el.deb ... 913s Unpacking libgcc-15-dev:ppc64el (15.2.0-12ubuntu1) ... 913s Selecting previously unselected package gcc-15-powerpc64le-linux-gnu. 913s Preparing to unpack .../020-gcc-15-powerpc64le-linux-gnu_15.2.0-12ubuntu1_ppc64el.deb ... 913s Unpacking gcc-15-powerpc64le-linux-gnu (15.2.0-12ubuntu1) ... 913s Selecting previously unselected package gcc-15. 913s Preparing to unpack .../021-gcc-15_15.2.0-12ubuntu1_ppc64el.deb ... 913s Unpacking gcc-15 (15.2.0-12ubuntu1) ... 913s Selecting previously unselected package gcc-powerpc64le-linux-gnu. 913s Preparing to unpack .../022-gcc-powerpc64le-linux-gnu_4%3a15.2.0-4ubuntu1_ppc64el.deb ... 913s Unpacking gcc-powerpc64le-linux-gnu (4:15.2.0-4ubuntu1) ... 913s Selecting previously unselected package gcc. 913s Preparing to unpack .../023-gcc_4%3a15.2.0-4ubuntu1_ppc64el.deb ... 913s Unpacking gcc (4:15.2.0-4ubuntu1) ... 913s Selecting previously unselected package libstdc++-15-dev:ppc64el. 913s Preparing to unpack .../024-libstdc++-15-dev_15.2.0-12ubuntu1_ppc64el.deb ... 913s Unpacking libstdc++-15-dev:ppc64el (15.2.0-12ubuntu1) ... 914s Selecting previously unselected package g++-15-powerpc64le-linux-gnu. 914s Preparing to unpack .../025-g++-15-powerpc64le-linux-gnu_15.2.0-12ubuntu1_ppc64el.deb ... 914s Unpacking g++-15-powerpc64le-linux-gnu (15.2.0-12ubuntu1) ... 914s Selecting previously unselected package g++-15. 914s Preparing to unpack .../026-g++-15_15.2.0-12ubuntu1_ppc64el.deb ... 914s Unpacking g++-15 (15.2.0-12ubuntu1) ... 914s Selecting previously unselected package g++-powerpc64le-linux-gnu. 914s Preparing to unpack .../027-g++-powerpc64le-linux-gnu_4%3a15.2.0-4ubuntu1_ppc64el.deb ... 914s Unpacking g++-powerpc64le-linux-gnu (4:15.2.0-4ubuntu1) ... 914s Selecting previously unselected package g++. 914s Preparing to unpack .../028-g++_4%3a15.2.0-4ubuntu1_ppc64el.deb ... 914s Unpacking g++ (4:15.2.0-4ubuntu1) ... 914s Selecting previously unselected package build-essential. 914s Preparing to unpack .../029-build-essential_12.12ubuntu2_ppc64el.deb ... 914s Unpacking build-essential (12.12ubuntu2) ... 914s Selecting previously unselected package dctrl-tools. 914s Preparing to unpack .../030-dctrl-tools_2.24-3build4_ppc64el.deb ... 914s Unpacking dctrl-tools (2.24-3build4) ... 914s Selecting previously unselected package fonts-dejavu-mono. 914s Preparing to unpack .../031-fonts-dejavu-mono_2.37-8build1_all.deb ... 914s Unpacking fonts-dejavu-mono (2.37-8build1) ... 914s Selecting previously unselected package fonts-dejavu-core. 914s Preparing to unpack .../032-fonts-dejavu-core_2.37-8build1_all.deb ... 914s Unpacking fonts-dejavu-core (2.37-8build1) ... 914s Selecting previously unselected package fontconfig-config. 914s Preparing to unpack .../033-fontconfig-config_2.17.1-3ubuntu1_ppc64el.deb ... 914s Unpacking fontconfig-config (2.17.1-3ubuntu1) ... 914s Selecting previously unselected package libfontconfig1:ppc64el. 914s Preparing to unpack .../034-libfontconfig1_2.17.1-3ubuntu1_ppc64el.deb ... 914s Unpacking libfontconfig1:ppc64el (2.17.1-3ubuntu1) ... 914s Selecting previously unselected package fontconfig. 914s Preparing to unpack .../035-fontconfig_2.17.1-3ubuntu1_ppc64el.deb ... 914s Unpacking fontconfig (2.17.1-3ubuntu1) ... 914s Selecting previously unselected package libgfortran5:ppc64el. 914s Preparing to unpack .../036-libgfortran5_15.2.0-12ubuntu1_ppc64el.deb ... 914s Unpacking libgfortran5:ppc64el (15.2.0-12ubuntu1) ... 914s Selecting previously unselected package libgfortran-15-dev:ppc64el. 914s Preparing to unpack .../037-libgfortran-15-dev_15.2.0-12ubuntu1_ppc64el.deb ... 914s Unpacking libgfortran-15-dev:ppc64el (15.2.0-12ubuntu1) ... 914s Selecting previously unselected package gfortran-15-powerpc64le-linux-gnu. 914s Preparing to unpack .../038-gfortran-15-powerpc64le-linux-gnu_15.2.0-12ubuntu1_ppc64el.deb ... 914s Unpacking gfortran-15-powerpc64le-linux-gnu (15.2.0-12ubuntu1) ... 914s Selecting previously unselected package gfortran-15. 914s Preparing to unpack .../039-gfortran-15_15.2.0-12ubuntu1_ppc64el.deb ... 914s Unpacking gfortran-15 (15.2.0-12ubuntu1) ... 914s Selecting previously unselected package gfortran-powerpc64le-linux-gnu. 914s Preparing to unpack .../040-gfortran-powerpc64le-linux-gnu_4%3a15.2.0-4ubuntu1_ppc64el.deb ... 914s Unpacking gfortran-powerpc64le-linux-gnu (4:15.2.0-4ubuntu1) ... 915s Selecting previously unselected package gfortran. 915s Preparing to unpack .../041-gfortran_4%3a15.2.0-4ubuntu1_ppc64el.deb ... 915s Unpacking gfortran (4:15.2.0-4ubuntu1) ... 915s Selecting previously unselected package icu-devtools. 915s Preparing to unpack .../042-icu-devtools_78.2-1ubuntu1_ppc64el.deb ... 915s Unpacking icu-devtools (78.2-1ubuntu1) ... 915s Selecting previously unselected package libblas3:ppc64el. 915s Preparing to unpack .../043-libblas3_3.12.1-7ubuntu1_ppc64el.deb ... 915s Unpacking libblas3:ppc64el (3.12.1-7ubuntu1) ... 915s Selecting previously unselected package libblas-dev:ppc64el. 915s Preparing to unpack .../044-libblas-dev_3.12.1-7ubuntu1_ppc64el.deb ... 915s Unpacking libblas-dev:ppc64el (3.12.1-7ubuntu1) ... 915s Selecting previously unselected package libbz2-dev:ppc64el. 915s Preparing to unpack .../045-libbz2-dev_1.0.8-6build2_ppc64el.deb ... 915s Unpacking libbz2-dev:ppc64el (1.0.8-6build2) ... 915s Selecting previously unselected package libpixman-1-0:ppc64el. 915s Preparing to unpack .../046-libpixman-1-0_0.46.4-1_ppc64el.deb ... 915s Unpacking libpixman-1-0:ppc64el (0.46.4-1) ... 915s Selecting previously unselected package libxcb-render0:ppc64el. 915s Preparing to unpack .../047-libxcb-render0_1.17.0-2ubuntu1_ppc64el.deb ... 915s Unpacking libxcb-render0:ppc64el (1.17.0-2ubuntu1) ... 915s Selecting previously unselected package libxcb-shm0:ppc64el. 915s Preparing to unpack .../048-libxcb-shm0_1.17.0-2ubuntu1_ppc64el.deb ... 915s Unpacking libxcb-shm0:ppc64el (1.17.0-2ubuntu1) ... 915s Selecting previously unselected package libxrender1:ppc64el. 915s Preparing to unpack .../049-libxrender1_1%3a0.9.12-1_ppc64el.deb ... 915s Unpacking libxrender1:ppc64el (1:0.9.12-1) ... 915s Selecting previously unselected package libcairo2:ppc64el. 915s Preparing to unpack .../050-libcairo2_1.18.4-3_ppc64el.deb ... 915s Unpacking libcairo2:ppc64el (1.18.4-3) ... 915s Selecting previously unselected package libdatrie1:ppc64el. 915s Preparing to unpack .../051-libdatrie1_0.2.14-1_ppc64el.deb ... 915s Unpacking libdatrie1:ppc64el (0.2.14-1) ... 915s Selecting previously unselected package libdeflate0:ppc64el. 915s Preparing to unpack .../052-libdeflate0_1.23-2build1_ppc64el.deb ... 915s Unpacking libdeflate0:ppc64el (1.23-2build1) ... 915s Selecting previously unselected package libdeflate-dev:ppc64el. 915s Preparing to unpack .../053-libdeflate-dev_1.23-2build1_ppc64el.deb ... 915s Unpacking libdeflate-dev:ppc64el (1.23-2build1) ... 915s Selecting previously unselected package libgraphite2-3:ppc64el. 915s Preparing to unpack .../054-libgraphite2-3_1.3.14-11ubuntu1_ppc64el.deb ... 915s Unpacking libgraphite2-3:ppc64el (1.3.14-11ubuntu1) ... 915s Selecting previously unselected package libharfbuzz0b:ppc64el. 915s Preparing to unpack .../055-libharfbuzz0b_12.3.2-1_ppc64el.deb ... 915s Unpacking libharfbuzz0b:ppc64el (12.3.2-1) ... 915s Selecting previously unselected package x11-common. 915s Preparing to unpack .../056-x11-common_1%3a7.7+24ubuntu1_all.deb ... 915s Unpacking x11-common (1:7.7+24ubuntu1) ... 915s Selecting previously unselected package libice6:ppc64el. 915s Preparing to unpack .../057-libice6_2%3a1.1.1-1build1_ppc64el.deb ... 915s Unpacking libice6:ppc64el (2:1.1.1-1build1) ... 915s Selecting previously unselected package libicu-dev:ppc64el. 915s Preparing to unpack .../058-libicu-dev_78.2-1ubuntu1_ppc64el.deb ... 915s Unpacking libicu-dev:ppc64el (78.2-1ubuntu1) ... 915s Selecting previously unselected package libjpeg-turbo8:ppc64el. 915s Preparing to unpack .../059-libjpeg-turbo8_2.1.5-4ubuntu3_ppc64el.deb ... 915s Unpacking libjpeg-turbo8:ppc64el (2.1.5-4ubuntu3) ... 915s Selecting previously unselected package libjpeg-turbo8-dev:ppc64el. 915s Preparing to unpack .../060-libjpeg-turbo8-dev_2.1.5-4ubuntu3_ppc64el.deb ... 915s Unpacking libjpeg-turbo8-dev:ppc64el (2.1.5-4ubuntu3) ... 915s Selecting previously unselected package libjpeg8:ppc64el. 915s Preparing to unpack .../061-libjpeg8_8c-2ubuntu11_ppc64el.deb ... 915s Unpacking libjpeg8:ppc64el (8c-2ubuntu11) ... 915s Selecting previously unselected package libjpeg8-dev:ppc64el. 915s Preparing to unpack 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.../067-libncurses-dev_6.6+20251231-1_ppc64el.deb ... 916s Unpacking libncurses-dev:ppc64el (6.6+20251231-1) ... 916s Selecting previously unselected package libthai-data. 916s Preparing to unpack .../068-libthai-data_0.1.30-1_all.deb ... 916s Unpacking libthai-data (0.1.30-1) ... 916s Selecting previously unselected package libthai0:ppc64el. 916s Preparing to unpack .../069-libthai0_0.1.30-1_ppc64el.deb ... 916s Unpacking libthai0:ppc64el (0.1.30-1) ... 916s Selecting previously unselected package libpango-1.0-0:ppc64el. 916s Preparing to unpack .../070-libpango-1.0-0_1.57.0-1_ppc64el.deb ... 916s Unpacking libpango-1.0-0:ppc64el (1.57.0-1) ... 916s Selecting previously unselected package libpangoft2-1.0-0:ppc64el. 916s Preparing to unpack .../071-libpangoft2-1.0-0_1.57.0-1_ppc64el.deb ... 916s Unpacking libpangoft2-1.0-0:ppc64el (1.57.0-1) ... 916s Selecting previously unselected package libpangocairo-1.0-0:ppc64el. 916s Preparing to unpack .../072-libpangocairo-1.0-0_1.57.0-1_ppc64el.deb ... 916s Unpacking libpangocairo-1.0-0:ppc64el (1.57.0-1) ... 916s Selecting previously unselected package libpaper2:ppc64el. 916s Preparing to unpack .../073-libpaper2_2.2.5-0.3build1_ppc64el.deb ... 916s Unpacking libpaper2:ppc64el (2.2.5-0.3build1) ... 916s Selecting previously unselected package libpaper-utils. 916s Preparing to unpack .../074-libpaper-utils_2.2.5-0.3build1_ppc64el.deb ... 916s Unpacking libpaper-utils (2.2.5-0.3build1) ... 916s Selecting previously unselected package libpcre2-16-0:ppc64el. 916s Preparing to unpack .../075-libpcre2-16-0_10.46-1_ppc64el.deb ... 916s Unpacking libpcre2-16-0:ppc64el (10.46-1) ... 916s Selecting previously unselected package libpcre2-32-0:ppc64el. 916s Preparing to unpack .../076-libpcre2-32-0_10.46-1_ppc64el.deb ... 916s Unpacking libpcre2-32-0:ppc64el (10.46-1) ... 916s Selecting previously unselected package libpcre2-posix3:ppc64el. 916s Preparing to unpack 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.../082-libreadline-dev_8.3-3_ppc64el.deb ... 916s Unpacking libreadline-dev:ppc64el (8.3-3) ... 916s Selecting previously unselected package libsharpyuv0:ppc64el. 916s Preparing to unpack .../083-libsharpyuv0_1.5.0-0.1build1_ppc64el.deb ... 916s Unpacking libsharpyuv0:ppc64el (1.5.0-0.1build1) ... 916s Selecting previously unselected package libsm6:ppc64el. 916s Preparing to unpack .../084-libsm6_2%3a1.2.6-1build1_ppc64el.deb ... 916s Unpacking libsm6:ppc64el (2:1.2.6-1build1) ... 916s Selecting previously unselected package libtcl8.6:ppc64el. 916s Preparing to unpack .../085-libtcl8.6_8.6.17+dfsg-1build1_ppc64el.deb ... 916s Unpacking libtcl8.6:ppc64el (8.6.17+dfsg-1build1) ... 916s Selecting previously unselected package libjbig0:ppc64el. 916s Preparing to unpack .../086-libjbig0_2.1-6.1ubuntu3_ppc64el.deb ... 916s Unpacking libjbig0:ppc64el (2.1-6.1ubuntu3) ... 916s Selecting previously unselected package libwebp7:ppc64el. 916s Preparing to unpack .../087-libwebp7_1.5.0-0.1build1_ppc64el.deb ... 916s Unpacking libwebp7:ppc64el (1.5.0-0.1build1) ... 916s Selecting previously unselected package libtiff6:ppc64el. 916s Preparing to unpack .../088-libtiff6_4.7.0-3ubuntu3_ppc64el.deb ... 916s Unpacking libtiff6:ppc64el (4.7.0-3ubuntu3) ... 916s Selecting previously unselected package libxft2:ppc64el. 916s Preparing to unpack .../089-libxft2_2.3.6-1build2_ppc64el.deb ... 916s Unpacking libxft2:ppc64el (2.3.6-1build2) ... 916s Selecting previously unselected package libxss1:ppc64el. 916s Preparing to unpack .../090-libxss1_1%3a1.2.3-1build4_ppc64el.deb ... 916s Unpacking libxss1:ppc64el (1:1.2.3-1build4) ... 916s Selecting previously unselected package libtk8.6:ppc64el. 916s Preparing to unpack .../091-libtk8.6_8.6.17-1_ppc64el.deb ... 916s Unpacking libtk8.6:ppc64el (8.6.17-1) ... 916s Selecting previously unselected package libxt6t64:ppc64el. 916s Preparing to unpack .../092-libxt6t64_1%3a1.2.1-1.3_ppc64el.deb ... 916s Unpacking libxt6t64:ppc64el (1:1.2.1-1.3) ... 916s Selecting previously unselected package libzstd-dev:ppc64el. 916s Preparing to unpack .../093-libzstd-dev_1.5.7+dfsg-3_ppc64el.deb ... 916s Unpacking libzstd-dev:ppc64el (1.5.7+dfsg-3) ... 916s Selecting previously unselected package zip. 916s Preparing to unpack .../094-zip_3.0-15ubuntu3_ppc64el.deb ... 916s Unpacking zip (3.0-15ubuntu3) ... 916s Selecting previously unselected package unzip. 916s Preparing to unpack .../095-unzip_6.0-29ubuntu1_ppc64el.deb ... 916s Unpacking unzip (6.0-29ubuntu1) ... 916s Selecting previously unselected package xdg-utils. 916s Preparing to unpack .../096-xdg-utils_1.2.1-2ubuntu2_all.deb ... 916s Unpacking xdg-utils (1.2.1-2ubuntu2) ... 916s Selecting previously unselected package r-base-core. 916s Preparing to unpack .../097-r-base-core_4.5.2-1ubuntu2_ppc64el.deb ... 916s Unpacking r-base-core (4.5.2-1ubuntu2) ... 917s Selecting previously unselected package liblzma-dev:ppc64el. 917s Preparing to unpack .../098-liblzma-dev_5.8.2-2_ppc64el.deb ... 917s Unpacking liblzma-dev:ppc64el (5.8.2-2) ... 917s Selecting previously unselected package pkgconf-bin. 917s Preparing to unpack .../099-pkgconf-bin_1.8.1-4build1_ppc64el.deb ... 917s Unpacking pkgconf-bin (1.8.1-4build1) ... 917s Selecting previously unselected package pkgconf:ppc64el. 917s Preparing to unpack .../100-pkgconf_1.8.1-4build1_ppc64el.deb ... 917s Unpacking pkgconf:ppc64el (1.8.1-4build1) ... 917s Selecting previously unselected package libtirpc-dev:ppc64el. 917s Preparing to unpack .../101-libtirpc-dev_1.3.6+ds-1_ppc64el.deb ... 917s Unpacking libtirpc-dev:ppc64el (1.3.6+ds-1) ... 917s Selecting previously unselected package r-base-dev. 917s Preparing to unpack .../102-r-base-dev_4.5.2-1ubuntu2_all.deb ... 917s Unpacking r-base-dev (4.5.2-1ubuntu2) ... 917s Selecting previously unselected package pkg-r-autopkgtest. 917s Preparing to unpack .../103-pkg-r-autopkgtest_20250812_all.deb ... 917s Unpacking pkg-r-autopkgtest (20250812) ... 917s Selecting previously unselected package r-bioc-biocgenerics. 917s Preparing to unpack .../104-r-bioc-biocgenerics_0.52.0-2_all.deb ... 917s Unpacking r-bioc-biocgenerics (0.52.0-2) ... 917s Selecting previously unselected package r-cran-r.methodss3. 917s Preparing to unpack .../105-r-cran-r.methodss3_1.8.2-1_all.deb ... 917s Unpacking r-cran-r.methodss3 (1.8.2-1) ... 917s Selecting previously unselected package r-cran-r.oo. 917s Preparing to unpack .../106-r-cran-r.oo_1.27.1-1_all.deb ... 917s Unpacking r-cran-r.oo (1.27.1-1) ... 917s Selecting previously unselected package r-cran-r.utils. 917s Preparing to unpack .../107-r-cran-r.utils_2.13.0-1_all.deb ... 917s Unpacking r-cran-r.utils (2.13.0-1) ... 917s Selecting previously unselected package r-cran-matrixstats. 917s Preparing to unpack .../108-r-cran-matrixstats_1.5.0-1_ppc64el.deb ... 917s Unpacking r-cran-matrixstats (1.5.0-1) ... 917s Selecting previously unselected package r-bioc-aroma.light. 917s Preparing to unpack .../109-r-bioc-aroma.light_3.36.0-2_all.deb ... 917s Unpacking r-bioc-aroma.light (3.36.0-2) ... 917s Selecting previously unselected package r-bioc-dnacopy. 917s Preparing to unpack .../110-r-bioc-dnacopy_1.80.0-2_ppc64el.deb ... 917s Unpacking r-bioc-dnacopy (1.80.0-2) ... 917s Selecting previously unselected package r-cran-cli. 917s Preparing to unpack .../111-r-cran-cli_3.6.4-1_ppc64el.deb ... 917s Unpacking r-cran-cli (3.6.4-1) ... 917s Selecting previously unselected package r-cran-codetools. 917s Preparing to unpack .../112-r-cran-codetools_0.2-20-1build1_all.deb ... 917s Unpacking r-cran-codetools (0.2-20-1build1) ... 917s Selecting previously unselected package r-cran-digest. 917s Preparing to unpack .../113-r-cran-digest_0.6.39-1_ppc64el.deb ... 917s Unpacking r-cran-digest (0.6.39-1) ... 917s Selecting previously unselected package r-cran-farver. 917s Preparing to unpack .../114-r-cran-farver_2.1.2-1_ppc64el.deb ... 917s Unpacking r-cran-farver (2.1.2-1) ... 917s Selecting previously unselected package r-cran-globals. 917s Preparing to unpack .../115-r-cran-globals_0.19.0-1_all.deb ... 917s Unpacking r-cran-globals (0.19.0-1) ... 917s Selecting previously unselected package r-cran-listenv. 917s Preparing to unpack .../116-r-cran-listenv_0.10.0+dfsg-1_all.deb ... 917s Unpacking r-cran-listenv (0.10.0+dfsg-1) ... 917s Selecting previously unselected package r-cran-parallelly. 917s Preparing to unpack .../117-r-cran-parallelly_1.42.0-1_ppc64el.deb ... 917s Unpacking r-cran-parallelly (1.42.0-1) ... 917s Selecting previously unselected package r-cran-future. 917s Preparing to unpack .../118-r-cran-future_1.34.0+dfsg-1_all.deb ... 917s Unpacking r-cran-future (1.34.0+dfsg-1) ... 917s Selecting previously unselected package r-cran-glue. 917s Preparing to unpack .../119-r-cran-glue_1.8.0-1_ppc64el.deb ... 917s Unpacking r-cran-glue (1.8.0-1) ... 917s Selecting previously unselected package r-cran-rlang. 917s Preparing to unpack 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unselected package r-cran-r6. 918s Preparing to unpack .../126-r-cran-r6_2.6.1-1_all.deb ... 918s Unpacking r-cran-r6 (2.6.1-1) ... 918s Selecting previously unselected package r-cran-rcolorbrewer. 918s Preparing to unpack .../127-r-cran-rcolorbrewer_1.1-3-1build2_all.deb ... 918s Unpacking r-cran-rcolorbrewer (1.1-3-1build2) ... 918s Selecting previously unselected package r-cran-viridislite. 918s Preparing to unpack .../128-r-cran-viridislite_0.4.3-1_all.deb ... 918s Unpacking r-cran-viridislite (0.4.3-1) ... 918s Selecting previously unselected package r-cran-scales. 918s Preparing to unpack .../129-r-cran-scales_1.4.0-1_all.deb ... 918s Unpacking r-cran-scales (1.4.0-1) ... 918s Selecting previously unselected package r-cran-vctrs. 918s Preparing to unpack .../130-r-cran-vctrs_0.6.5-1_ppc64el.deb ... 918s Unpacking r-cran-vctrs (0.6.5-1) ... 918s Selecting previously unselected package r-cran-withr. 918s Preparing to unpack .../131-r-cran-withr_3.0.2+dfsg-1_all.deb ... 918s 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(1.17.0-2ubuntu1) ... 918s Setting up unzip (6.0-29ubuntu1) ... 918s Setting up x11-common (1:7.7+24ubuntu1) ... 918s Setting up libdeflate0:ppc64el (1.23-2build1) ... 918s Setting up linux-libc-dev:ppc64el (6.19.0-3.3) ... 918s Setting up libxcb-shm0:ppc64el (1.17.0-2ubuntu1) ... 918s Setting up libgomp1:ppc64el (15.2.0-12ubuntu1) ... 918s Setting up libjbig0:ppc64el (2.1-6.1ubuntu3) ... 918s Setting up libpcre2-16-0:ppc64el (10.46-1) ... 918s Setting up zip (3.0-15ubuntu3) ... 918s Setting up libpcre2-32-0:ppc64el (10.46-1) ... 918s Setting up libblas3:ppc64el (3.12.1-7ubuntu1) ... 918s update-alternatives: using /usr/lib/powerpc64le-linux-gnu/blas/libblas.so.3 to provide /usr/lib/powerpc64le-linux-gnu/libblas.so.3 (libblas.so.3-powerpc64le-linux-gnu) in auto mode 918s Setting up libtirpc-dev:ppc64el (1.3.6+ds-1) ... 918s Setting up libpkgconf3:ppc64el (1.8.1-4build1) ... 918s Setting up rpcsvc-proto (1.4.3-1build1) ... 918s Setting up libquadmath0:ppc64el (15.2.0-12ubuntu1) ... 918s Setting up fonts-dejavu-mono (2.37-8build1) ... 918s Setting up libmpc3:ppc64el (1.3.1-2) ... 918s Setting up libtcl8.6:ppc64el (8.6.17+dfsg-1build1) ... 918s Setting up icu-devtools (78.2-1ubuntu1) ... 918s Setting up fonts-dejavu-core (2.37-8build1) ... 918s Setting up pkgconf-bin (1.8.1-4build1) ... 918s Setting up libjpeg-turbo8:ppc64el (2.1.5-4ubuntu3) ... 918s Setting up libgfortran5:ppc64el (15.2.0-12ubuntu1) ... 918s Setting up libwebp7:ppc64el (1.5.0-0.1build1) ... 918s Setting up liblzma-dev:ppc64el (5.8.2-2) ... 918s Setting up libubsan1:ppc64el (15.2.0-12ubuntu1) ... 918s Setting up libpcre2-posix3:ppc64el (10.46-1) ... 918s Setting up libcrypt-dev:ppc64el (1:4.5.1-1) ... 918s Setting up libasan8:ppc64el (15.2.0-12ubuntu1) ... 918s Setting up libharfbuzz0b:ppc64el (12.3.2-1) ... 918s Setting up libthai-data (0.1.30-1) ... 918s Setting up libxss1:ppc64el (1:1.2.3-1build4) ... 918s Setting up libpaper2:ppc64el (2.2.5-0.3build1) ... 919s Setting up libtsan2:ppc64el (15.2.0-12ubuntu1) ... 919s Setting up libisl23:ppc64el (0.27-1build1) ... 919s Setting up libc-dev-bin (2.42-2ubuntu4) ... 919s Setting up libdeflate-dev:ppc64el (1.23-2build1) ... 919s Setting up xdg-utils (1.2.1-2ubuntu2) ... 919s update-alternatives: using /usr/bin/xdg-open to provide /usr/bin/open (open) in auto mode 919s Setting up libcc1-0:ppc64el (15.2.0-12ubuntu1) ... 919s Setting up liblsan0:ppc64el (15.2.0-12ubuntu1) ... 919s Setting up libblas-dev:ppc64el (3.12.1-7ubuntu1) ... 919s update-alternatives: using /usr/lib/powerpc64le-linux-gnu/blas/libblas.so to provide /usr/lib/powerpc64le-linux-gnu/libblas.so (libblas.so-powerpc64le-linux-gnu) in auto mode 919s Setting up dctrl-tools (2.24-3build4) ... 919s Setting up libitm1:ppc64el (15.2.0-12ubuntu1) ... 919s Setting up libjpeg8:ppc64el (8c-2ubuntu11) ... 919s Setting up libice6:ppc64el (2:1.1.1-1build1) ... 919s Setting up liblapack3:ppc64el (3.12.1-7ubuntu1) ... 919s update-alternatives: using 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libfontconfig1:ppc64el (2.17.1-3ubuntu1) ... 919s Setting up libsm6:ppc64el (2:1.2.6-1build1) ... 919s Setting up libicu-dev:ppc64el (78.2-1ubuntu1) ... 919s Setting up cpp-powerpc64le-linux-gnu (4:15.2.0-4ubuntu1) ... 919s Setting up libbz2-dev:ppc64el (1.0.8-6build2) ... 919s Setting up fontconfig (2.17.1-3ubuntu1) ... 921s Regenerating fonts cache... done. 921s Setting up libjpeg-turbo8-dev:ppc64el (2.1.5-4ubuntu3) ... 921s Setting up libxft2:ppc64el (2.3.6-1build2) ... 921s Setting up libncurses-dev:ppc64el (6.6+20251231-1) ... 921s Setting up libpcre2-dev:ppc64el (10.46-1) ... 921s Setting up gcc-15-powerpc64le-linux-gnu (15.2.0-12ubuntu1) ... 921s Setting up libtk8.6:ppc64el (8.6.17-1) ... 921s Setting up libpango-1.0-0:ppc64el (1.57.0-1) ... 921s Setting up libreadline-dev:ppc64el (8.3-3) ... 921s Setting up libcairo2:ppc64el (1.18.4-3) ... 921s Setting up gcc-15 (15.2.0-12ubuntu1) ... 921s Setting up libstdc++-15-dev:ppc64el (15.2.0-12ubuntu1) ... 921s Setting up gcc-powerpc64le-linux-gnu (4:15.2.0-4ubuntu1) ... 921s Setting up libxt6t64:ppc64el (1:1.2.1-1.3) ... 921s Setting up gfortran-15-powerpc64le-linux-gnu (15.2.0-12ubuntu1) ... 921s Setting up zlib1g-dev:ppc64el (1:1.3.dfsg+really1.3.1-1ubuntu2) ... 921s Setting up cpp (4:15.2.0-4ubuntu1) ... 921s Setting up libpangoft2-1.0-0:ppc64el (1.57.0-1) ... 921s Setting up libjpeg8-dev:ppc64el (8c-2ubuntu11) ... 921s Setting up gfortran-15 (15.2.0-12ubuntu1) ... 921s Setting up libpangocairo-1.0-0:ppc64el (1.57.0-1) ... 921s Setting up g++-15-powerpc64le-linux-gnu (15.2.0-12ubuntu1) ... 921s Setting up libpng-dev:ppc64el (1.6.54-1) ... 921s Setting up libjpeg-dev:ppc64el (8c-2ubuntu11) ... 921s Setting up gcc (4:15.2.0-4ubuntu1) ... 921s Setting up gfortran-powerpc64le-linux-gnu (4:15.2.0-4ubuntu1) ... 921s Setting up r-base-core (4.5.2-1ubuntu2) ... 921s Creating config file /etc/R/Renviron with new version 921s Setting up r-cran-labeling (0.4.3-1) ... 921s Setting up r-cran-farver (2.1.2-1) ... 921s Setting up r-cran-viridislite (0.4.3-1) ... 921s Setting up r-cran-r6 (2.6.1-1) ... 921s Setting up g++-15 (15.2.0-12ubuntu1) ... 921s Setting up g++-powerpc64le-linux-gnu (4:15.2.0-4ubuntu1) ... 921s Setting up r-cran-codetools (0.2-20-1build1) ... 921s Setting up r-bioc-biocgenerics (0.52.0-2) ... 921s Setting up r-cran-rlang (1.1.5-3) ... 921s Setting up r-cran-matrixstats (1.5.0-1) ... 921s Setting up r-cran-listenv (0.10.0+dfsg-1) ... 921s Setting up r-cran-withr (3.0.2+dfsg-1) ... 921s Setting up r-cran-digest (0.6.39-1) ... 921s Setting up r-cran-glue (1.8.0-1) ... 921s Setting up r-cran-cli (3.6.4-1) ... 921s Setting up gfortran (4:15.2.0-4ubuntu1) ... 921s update-alternatives: using /usr/bin/gfortran to provide /usr/bin/f95 (f95) in auto mode 921s update-alternatives: warning: skip creation of /usr/share/man/man1/f95.1.gz because associated file /usr/share/man/man1/gfortran.1.gz (of link group f95) doesn't exist 921s update-alternatives: using /usr/bin/gfortran to provide /usr/bin/f77 (f77) in auto mode 921s update-alternatives: warning: skip creation of /usr/share/man/man1/f77.1.gz because associated file /usr/share/man/man1/gfortran.1.gz (of link group f77) doesn't exist 921s Setting up r-cran-lifecycle (1.0.5+dfsg-1) ... 921s Setting up r-cran-r.methodss3 (1.8.2-1) ... 921s Setting up r-cran-parallelly (1.42.0-1) ... 921s Setting up r-cran-s7 (0.2.0-1) ... 921s Setting up r-cran-rcolorbrewer (1.1-3-1build2) ... 921s Setting up r-cran-isoband (0.2.7-1) ... 921s Setting up r-cran-scales (1.4.0-1) ... 921s Setting up r-cran-gtable (0.3.6+dfsg-1) ... 921s Setting up g++ (4:15.2.0-4ubuntu1) ... 921s update-alternatives: using /usr/bin/g++ to provide /usr/bin/c++ (c++) in auto mode 921s Setting up r-bioc-dnacopy (1.80.0-2) ... 921s Setting up build-essential (12.12ubuntu2) ... 921s Setting up r-cran-globals (0.19.0-1) ... 921s Setting up r-cran-vctrs (0.6.5-1) ... 921s Setting up r-base-dev (4.5.2-1ubuntu2) ... 921s Setting up r-cran-ggplot2 (4.0.2+dfsg-1) ... 921s Setting up r-cran-r.oo (1.27.1-1) ... 921s Setting up r-cran-future (1.34.0+dfsg-1) ... 921s Setting up pkg-r-autopkgtest (20250812) ... 921s Setting up r-cran-r.utils (2.13.0-1) ... 921s Setting up r-bioc-aroma.light (3.36.0-2) ... 921s Setting up r-cran-r.cache (0.17.0-1) ... 921s Setting up r-cran-pscbs (0.68.0-1) ... 921s Processing triggers for libc-bin (2.42-2ubuntu4) ... 921s Processing triggers for man-db (2.13.1-1build1) ... 922s Processing triggers for install-info (7.2-5) ... 925s autopkgtest [23:52:43]: test pkg-r-autopkgtest: /usr/share/dh-r/pkg-r-autopkgtest 925s autopkgtest [23:52:43]: test pkg-r-autopkgtest: [----------------------- 925s Test: Try to load the R library PSCBS 925s 925s R version 4.5.2 (2025-10-31) -- "[Not] Part in a Rumble" 925s Copyright (C) 2025 The R Foundation for Statistical Computing 925s Platform: powerpc64le-unknown-linux-gnu 925s 925s R is free software and comes with ABSOLUTELY NO WARRANTY. 925s You are welcome to redistribute it under certain conditions. 925s Type 'license()' or 'licence()' for distribution details. 925s 925s R is a collaborative project with many contributors. 925s Type 'contributors()' for more information and 925s 'citation()' on how to cite R or R packages in publications. 925s 925s Type 'demo()' for some demos, 'help()' for on-line help, or 925s 'help.start()' for an HTML browser interface to help. 925s Type 'q()' to quit R. 925s 925s > library('PSCBS') 926s PSCBS v0.68.0 (2025-04-18 19:40:02 UTC) successfully loaded. See ?PSCBS for help. 926s > 926s Test: Run tests for PSCBS 926s Start: PairedPSCBS,boot.R 926s 926s R version 4.5.2 (2025-10-31) -- "[Not] Part in a Rumble" 926s Copyright (C) 2025 The R Foundation for Statistical Computing 926s Platform: powerpc64le-unknown-linux-gnu 926s 926s R is free software and comes with ABSOLUTELY NO WARRANTY. 926s You are welcome to redistribute it under certain conditions. 926s Type 'license()' or 'licence()' for distribution details. 926s 926s R is a collaborative project with many contributors. 926s Type 'contributors()' for more information and 926s 'citation()' on how to cite R or R packages in publications. 926s 926s Type 'demo()' for some demos, 'help()' for on-line help, or 926s 'help.start()' for an HTML browser interface to help. 926s Type 'q()' to quit R. 926s 926s > ########################################################### 926s > # This tests: 926s > # - Bootstrapping for PairedPSCBS objects 926s > ########################################################### 926s > library("PSCBS") 926s PSCBS v0.68.0 (2025-04-18 19:40:02 UTC) successfully loaded. See ?PSCBS for help. 926s > 926s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 926s > # Load SNP microarray data 926s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 926s > data <- PSCBS::exampleData("paired.chr01") 926s > 926s > 926s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 926s > # Paired PSCBS segmentation 926s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 926s > # Drop single-locus outliers 926s > dataS <- dropSegmentationOutliers(data) 926s > dataS <- dataS[seq(from=1, to=nrow(data), by=5),] 926s > nSegs <- 4L 926s > str(dataS) 926s 'data.frame': 14670 obs. of 6 variables: 926s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 926s $ x : int 1145994 2941694 3710825 4240737 4276892 4464544 4714611 5095111 5034491 5158416 ... 926s $ CT : num 1.63 1.4 1.41 1.17 1.16 ... 926s $ betaT : num 0.7574 0.169 0.2357 0.2604 0.0576 ... 926s $ CN : num 2.36 2.13 2.26 2.01 2.32 ... 926s $ betaN : num 0.8274 0.5072 0.1671 0.1609 0.0421 ... 926s > # Segment known regions 926s > knownSegments <- data.frame( 926s + chromosome = c( 1, 1, 1), 926s + start = c( -Inf, NA, 141510003), 926s + end = c(120992603, NA, +Inf) 926s + ) 926s > fit <- segmentByPairedPSCBS(dataS, knownSegments=knownSegments, avgDH="median", seed=0xBEEF) 927s > print(fit) 927s chromosome tcnId dhId start end tcnNbrOfLoci tcnMean tcnNbrOfSNPs 927s 1 1 1 1 554484 120992603 7586 1.385258 2108 927s 2 NA 2 1 NA NA NA NA 0 927s 3 1 3 1 141510003 185449813 2681 2.068861 777 927s 4 1 4 1 185449813 247137334 4391 2.634110 1311 927s tcnNbrOfHets dhNbrOfLoci dhMean c1Mean c2Mean 927s 1 2108 2108 0.54551245 0.3147912 1.070467 927s 2 0 0 NA NA NA 927s 3 777 777 0.07132277 0.9606521 1.108209 927s 4 1311 1311 0.21663871 1.0317300 1.602380 927s > 927s > 927s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 927s > # Bootstrap 927s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 927s > B <- 1L 927s > seed <- 0xBEEF 927s > probs <- c(0.025, 0.05, 0.95, 0.975) 927s > 927s > sets <- getBootstrapLocusSets(fit, B=B, seed=seed) 927s > 927s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 927s > # Subset by first segment 927s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 927s > ss <- 1L 927s > 927s > fitT <- extractSegment(fit, ss) 927s > dataT <- getLocusData(fitT) 927s > segsT <- getSegments(fitT) 927s > 927s > # Truth 927s > bootT <- bootstrapSegmentsAndChangepoints(fitT, B=B, seed=seed) 927s > bootT1 <- bootT$segments[1L,,,drop=FALSE] 927s > types <- dimnames(bootT1)[[3L]] 927s > dim(bootT1) <- dim(bootT1)[-1L] 927s > colnames(bootT1) <- types 927s > sumsT <- apply(bootT1, MARGIN=2L, FUN=quantile, probs=probs) 927s > print(sumsT) 927s tcn dh c1 c2 927s 2.5% 1.383213 0.5466788 0.3135198 1.069693 927s 5% 1.383213 0.5466788 0.3135198 1.069693 927s 95% 1.383213 0.5466788 0.3135198 1.069693 927s 97.5% 1.383213 0.5466788 0.3135198 1.069693 927s > 927s > fitTB <- bootstrapTCNandDHByRegion(fitT, B=B, seed=seed) 927s > segsTB <- getSegments(fitTB) 927s > segsTB <- unlist(segsTB[,grep("_", colnames(segsTB))]) 927s > dim(segsTB) <- dim(sumsT) 927s > dimnames(segsTB) <- dimnames(sumsT) 927s > print(segsTB) 927s tcn dh c1 c2 927s 2.5% 1.383213 0.5466788 0.3135198 1.069693 927s 5% 1.383213 0.5466788 0.3135198 1.069693 927s 95% 1.383213 0.5466788 0.3135198 1.069693 927s 97.5% 1.383213 0.5466788 0.3135198 1.069693 927s > 927s > # Sanity check 927s > stopifnot(all.equal(segsTB, sumsT)) 927s > 927s > # Calculate summaries using the existing bootstrap samples 927s > fitTBp <- bootstrapTCNandDHByRegion(fitT, .boot=bootT) 928s > # Sanity check 928s > all.equal(fitTBp, fitTB) 928s [1] "Component “tcn_2.5%”: Mean relative difference: 0.003070405" 928s [2] "Component “tcn_5%”: Mean relative difference: 0.002241362" 928s [3] "Component “tcn_95%”: Mean relative difference: 0.005458479" 928s [4] "Component “tcn_97.5%”: Mean relative difference: 0.006030363" 928s [5] "Component “dh_2.5%”: Mean relative difference: 0.02683423" 928s [6] "Component “dh_5%”: Mean relative difference: 0.02409533" 928s [7] "Component “dh_95%”: Mean relative difference: 0.0150081" 928s [8] "Component “dh_97.5%”: Mean relative difference: 0.01826461" 928s [9] "Component “c1_2.5%”: Mean relative difference: 0.02397349" 928s [10] "Component “c1_5%”: Mean relative difference: 0.01800948" 928s [11] "Component “c1_95%”: Mean relative difference: 0.0303456" 928s [12] "Component “c1_97.5%”: Mean relative difference: 0.03420614" 928s [13] "Component “c2_2.5%”: Mean relative difference: 0.008723378" 928s [14] "Component “c2_5%”: Mean relative difference: 0.006834962" 928s [15] "Component “c2_95%”: Mean relative difference: 0.00741949" 928s [16] "Component “c2_97.5%”: Mean relative difference: 0.008743911" 928s attr(,"what") 928s [1] "getSegments()" 928s > 928s > 928s > # Bootstrap from scratch 928s > setsT <- getBootstrapLocusSets(fitT, B=B, seed=seed) 928s > lociT <- setsT$locusSet[[1L]]$bootstrap$loci 928s > idxs <- lociT$tcn 928s > tcnT <- array(dataT$CT[idxs], dim=dim(idxs)) 928s > tcnT <- apply(tcnT, MARGIN=2L, FUN=mean, na.rm=TRUE) 928s > idxs <- lociT$dh 928s > dhT <- array(dataT$rho[idxs], dim=dim(idxs)) 928s > dhT <- apply(dhT, MARGIN=2L, FUN=median, na.rm=TRUE) 928s > c1T <- (1-dhT) * tcnT / 2 928s > c2T <- tcnT - c1T 928s > bootT2 <- array(c(tcnT, dhT, c1T, c2T), dim=c(1L, 4L)) 928s > colnames(bootT2) <- colnames(bootT1) 928s > print(bootT2) 928s tcn dh c1 c2 928s [1,] 1.383213 0.5466788 0.3135198 1.069693 928s > 928s > # This comparison is only valid if B == 1L 928s > if (B == 1L) { 928s + # Sanity check 928s + stopifnot(all.equal(bootT2, bootT1)) 928s + } 928s > 928s Start: findLargeGaps.R 928s 928s R version 4.5.2 (2025-10-31) -- "[Not] Part in a Rumble" 928s Copyright (C) 2025 The R Foundation for Statistical Computing 928s Platform: powerpc64le-unknown-linux-gnu 928s 928s R is free software and comes with ABSOLUTELY NO WARRANTY. 928s You are welcome to redistribute it under certain conditions. 928s Type 'license()' or 'licence()' for distribution details. 928s 928s R is a collaborative project with many contributors. 928s Type 'contributors()' for more information and 928s 'citation()' on how to cite R or R packages in publications. 928s 928s Type 'demo()' for some demos, 'help()' for on-line help, or 928s 'help.start()' for an HTML browser interface to help. 928s Type 'q()' to quit R. 928s 928s > library("PSCBS") 928s > 928s > # Simulating copy-number data 928s > set.seed(0xBEEF) 928s > 928s > # Simulate CN data 928s > J <- 1000 928s > mu <- double(J) 928s > mu[200:300] <- mu[200:300] + 1 928s PSCBS v0.68.0 (2025-04-18 19:40:02 UTC) successfully loaded. See ?PSCBS for help. 928s > mu[350:400] <- NA # centromere 928s > mu[650:800] <- mu[650:800] - 1 928s > eps <- rnorm(J, sd=1/2) 928s > y <- mu + eps 928s > x <- seq(from=1, to=100e6, length.out=J) 928s > 928s > data <- data.frame(chromosome=0L, x=x) 928s > 928s > gaps <- findLargeGaps(x=x, minLength=1e6) 928s > print(gaps) 928s [1] start end length 928s <0 rows> (or 0-length row.names) 928s > stopifnot(is.data.frame(gaps)) 928s > stopifnot(nrow(gaps) == 0L) 928s > segs <- gapsToSegments(gaps) 928s > print(segs) 928s chromosome start end 928s 1 0 -Inf Inf 928s > stopifnot(is.data.frame(segs)) 928s > stopifnot(nrow(segs) == 1L) 928s > 928s > 928s > gaps <- findLargeGaps(data, minLength=1e6) 928s > print(gaps) 928s [1] chromosome start end 928s <0 rows> (or 0-length row.names) 928s > stopifnot(is.data.frame(gaps)) 928s > stopifnot(nrow(gaps) == 0L) 928s > segs <- gapsToSegments(gaps) 928s > print(segs) 928s chromosome start end 928s 1 0 -Inf Inf 928s > stopifnot(is.data.frame(segs)) 928s > stopifnot(nrow(segs) == 1L) 928s > 928s > 928s > ## Add missing values 928s > data2 <- data 928s > data$x[30e6 < x & x < 50e6] <- NA 928s > gaps <- findLargeGaps(data, minLength=1e6) 928s > print(gaps) 928s chromosome start end length 928s 1 0 29929932 50050050 20120118 928s > stopifnot(is.data.frame(gaps)) 928s > stopifnot(nrow(gaps) == 1L) 928s > segs <- gapsToSegments(gaps) 928s > print(segs) 928s chromosome start end length 928s 1 0 -Inf 29929931 Inf 928s 2 0 29929932 50050050 20120118 928s 3 0 50050051 Inf Inf 928s > stopifnot(is.data.frame(segs)) 928s > stopifnot(nrow(segs) == 3L) 928s > 928s > 928s > 928s > # BUG FIX: Issue #6 928s > gaps <- findLargeGaps(chromosome=rep(1,10), x=1:10, minLength=2) 928s > print(gaps) 928s [1] chromosome start end 928s <0 rows> (or 0-length row.names) 928s > stopifnot(is.data.frame(gaps)) 928s > stopifnot(nrow(gaps) == 0L) 928s > # BUG FIX: Issue #9 928s > segs <- gapsToSegments(gaps) 928s > print(segs) 928s chromosome start end 928s 1 0 -Inf Inf 928s > stopifnot(is.data.frame(segs)) 928s > stopifnot(nrow(segs) == 1L) 928s > 928s > 928s > # BUG FIX: PSCBS GitHub Issue #8 928s > gaps <- try({ 928s + findLargeGaps(chromosome=rep(1,3), x=as.numeric(1:3), minLength=1) 928s + }) 928s > stopifnot(inherits(gaps, "try-error")) 928s > 928s Start: randomSeed.R 928s Error in findLargeGaps.default(chromosome = rep(1, 3), x = as.numeric(1:3), : 928s Cannot identify large gaps. Argument 'resolution' (=1) is not strictly smaller than 'minLength' (=1). 928s 928s R version 4.5.2 (2025-10-31) -- "[Not] Part in a Rumble" 928s Copyright (C) 2025 The R Foundation for Statistical Computing 928s Platform: powerpc64le-unknown-linux-gnu 928s 928s R is free software and comes with ABSOLUTELY NO WARRANTY. 928s You are welcome to redistribute it under certain conditions. 928s Type 'license()' or 'licence()' for distribution details. 928s 928s R is a collaborative project with many contributors. 928s Type 'contributors()' for more information and 928s 'citation()' on how to cite R or R packages in publications. 928s 928s Type 'demo()' for some demos, 'help()' for on-line help, or 928s 'help.start()' for an HTML browser interface to help. 928s Type 'q()' to quit R. 928s 929s > library("PSCBS") 929s PSCBS v0.68.0 (2025-04-18 19:40:02 UTC) successfully loaded. See ?PSCBS for help. 929s > 929s > message("*** randomSeed() - setup ...") 929s *** randomSeed() - setup ... 929s > ovars <- ls(envir=globalenv()) 929s > genv <- globalenv() 929s > RNGkind("Mersenne-Twister") 929s > if (exists(".Random.seed", envir=genv, inherits=FALSE)) 929s + rm(list=".Random.seed", envir=genv, inherits=FALSE) 929s > seed0 <- genv$.Random.seed 929s > stopifnot(is.null(seed0)) 929s > okind0 <- RNGkind()[1L] 929s > 929s > sample1 <- function() { sample(0:9, size=1L) } 929s > message("*** randomSeed() - setup ... done") 929s *** randomSeed() - setup ... done 929s > 929s > 929s > message("*** randomSeed('get') ...") 929s *** randomSeed('get') ... 929s > ## Get random seed 929s > seed <- randomSeed("get") 929s > stopifnot(identical(seed, seed0)) 929s > 929s > ## Repeat after new sample 929s > y1 <- sample1() 929s > message(sprintf("Random number: %d", y1)) 929s Random number: 7 929s > seed1 <- randomSeed("get") 929s > stopifnot(!identical(seed1, seed0)) 929s > message("*** randomSeed('get') ... done") 929s *** randomSeed('get') ... done 929s *** randomSeed('set', 42L) ... 929s > 929s > 929s > message("*** randomSeed('set', 42L) ...") 929s > randomSeed("set", seed=42L) 929s > seed2 <- randomSeed("get") 929s > stopifnot(!identical(seed2, seed1)) 929s > 929s > y2 <- sample1() 929s > message(sprintf("Random number: %d (with random seed = 42L)", y2)) 929s Random number: 0 (with random seed = 42L) 929s > 929s > ## Reset to previous state 929s > randomSeed("reset") 929s > seed3 <- randomSeed("get") 929s > stopifnot(identical(seed3, seed1)) 929s > stopifnot(identical(RNGkind()[1L], okind0), 929s + identical(randomSeed("get"), seed1)) 929s > message("*** randomSeed('set', 42L) ... done") 929s *** randomSeed('set', 42L) ... done 929s > 929s > 929s > message("*** randomSeed('set', NULL) ...") 929s *** randomSeed('set', NULL) ... 929s > randomSeed("set", seed=NULL) 929s > seed4 <- randomSeed("get") 929s > stopifnot(is.null(seed4)) 929s > 929s > y3 <- sample1() 929s > message(sprintf("Random number: %d", y3)) 929s Random number: 8 929s > 929s > message("*** randomSeed('set', NULL) ... done") 929s *** randomSeed('set', NULL) ... done 929s *** randomSeed('set', 42L) again ... 929s > 929s > 929s > message("*** randomSeed('set', 42L) again ...") 929s > seed5 <- randomSeed("get") 929s > randomSeed("set", seed=42L) 929s Random number: 0 (with random seed = 42L) 929s > y4 <- sample1() 929s > message(sprintf("Random number: %d (with random seed = 42L)", y4)) 929s *** randomSeed('set', 42L) again ... done 929s *** randomSeed(): L'Ecuyer-CMRG stream ... 929s > stopifnot(identical(y4, y2)) 929s > 929s > randomSeed("reset") 929s > stopifnot(identical(RNGkind()[1L], okind0), 929s + identical(randomSeed("get"), seed5)) 929s > message("*** randomSeed('set', 42L) again ... done") 929s > 929s > 929s > 929s > ## L'Ecuyer-CMRG: Random number generation for parallel processing 929s > message("*** randomSeed(): L'Ecuyer-CMRG stream ...") 929s > 929s > okind <- RNGkind()[1L] 929s > stopifnot(identical(okind, okind0)) 929s > 929s > randomSeed("set", seed=NULL) 929s > oseed <- randomSeed("get") 929s > stopifnot(is.null(oseed)) 929s > 929s > randomSeed("set", seed=42L, kind="L'Ecuyer-CMRG") 929s > oseed2 <- randomSeed("reset") 929s > str(oseed2) 929s NULL 929s > stopifnot(identical(oseed2, oseed)) 929s > stopifnot(identical(RNGkind()[1L], okind), 929s + identical(randomSeed("get"), oseed)) 929s > 929s > randomSeed("set", seed=42L, kind="L'Ecuyer-CMRG") 929s > seed0 <- randomSeed("get") 929s > seeds0 <- lapply(1:10, FUN=function(i) randomSeed("advance")) 929s > oseed2 <- randomSeed("reset") 929s > stopifnot(identical(oseed2, oseed)) 929s > stopifnot(identical(RNGkind()[1L], okind), 929s + identical(randomSeed("get"), oseed)) 929s > 929s > 929s > ## Assert reproducible .Random.seed stream 929s > randomSeed("set", seed=42L, kind="L'Ecuyer-CMRG") 929s > seed1 <- randomSeed("get") 929s > seeds1 <- lapply(1:10, FUN=function(i) randomSeed("advance")) 929s > stopifnot(identical(seed1, seed0)) 929s > stopifnot(identical(seeds1, seeds0)) 929s > 929s > randomSeed("reset") 929s > stopifnot(identical(RNGkind()[1L], okind), 929s + identical(randomSeed("get"), oseed)) 929s > 929s > randomSeed("set", seed=42L, kind="L'Ecuyer-CMRG") 929s > seeds2 <- randomSeed("advance", n=10L) 929s > stopifnot(identical(seeds2, seeds0)) 929s > 929s > randomSeed("reset") 929s > stopifnot(identical(RNGkind()[1L], okind), 929s + identical(randomSeed("get"), oseed)) 929s > 929s > randomSeed("set", seed=seeds2[[1]], kind="L'Ecuyer-CMRG") 929s > randomSeed("reset") 929s > stopifnot(identical(RNGkind()[1L], okind), 929s + identical(randomSeed("get"), oseed)) 929s > 929s > randomSeed("set", seed=42L, kind="L'Ecuyer-CMRG") 929s > y0 <- sapply(1:10, FUN=function(ii) { 929s + randomSeed("advance") 929s + sample1() 929s + }) 929s > print(y0) 929s [1] 6 9 6 9 9 9 0 7 6 5 929s > randomSeed("reset") 929s > 929s > randomSeed("set", seed=42L, kind="L'Ecuyer-CMRG") 929s > y1 <- sapply(1:10, FUN=function(ii) { 929s + randomSeed("advance") 929s + sample1() 929s + }) 929s > print(y1) 929s [1] 6 9 6 9 9 9 0 7 6 5 929s > stopifnot(identical(y1, y0)) 929s > randomSeed("reset") 929s > 929s > stopifnot(identical(RNGkind()[1L], okind)) 929s > 929s > message("*** randomSeed(): L'Ecuyer-CMRG stream ... done") 929s *** randomSeed(): L'Ecuyer-CMRG stream ... done 929s *** randomSeed() - cleanup ... 929s > 929s > 929s > ## Cleanup 929s > message("*** randomSeed() - cleanup ...") 929s > genv <- globalenv() 929s > RNGkind("Mersenne-Twister") 929s > if (exists(".Random.seed", envir=genv, inherits=FALSE)) 929s + rm(list=".Random.seed", envir=genv, inherits=FALSE) 929s > rm(list=ovars, envir=globalenv()) 929s > message("*** randomSeed() - cleanup ... done") 929s *** randomSeed() - cleanup ... done 929s > 929s Start: segmentByCBS,bug67.R 929s 929s R version 4.5.2 (2025-10-31) -- "[Not] Part in a Rumble" 929s Copyright (C) 2025 The R Foundation for Statistical Computing 929s Platform: powerpc64le-unknown-linux-gnu 929s 929s R is free software and comes with ABSOLUTELY NO WARRANTY. 929s You are welcome to redistribute it under certain conditions. 929s Type 'license()' or 'licence()' for distribution details. 929s 929s R is a collaborative project with many contributors. 929s Type 'contributors()' for more information and 929s 'citation()' on how to cite R or R packages in publications. 929s 929s Type 'demo()' for some demos, 'help()' for on-line help, or 929s 'help.start()' for an HTML browser interface to help. 929s Type 'q()' to quit R. 929s 929s > set.seed(0xBEEF) 929s > 929s > # Number of loci 929s > J <- 1000 929s > 929s > mu <- double(J) 929s > mu[200:300] <- mu[200:300] + 1 929s > mu[350:400] <- NA_real_ # centromere 929s > mu[650:800] <- mu[650:800] - 1 929s > eps <- rnorm(J, sd=1/2) 929s > y <- mu + eps 929s > x <- sort(runif(length(y), max=length(y))) * 1e5 929s > 929s > knownSegments <- data.frame( 929s + chromosome=c( 0, 0), 929s + start =x[c( 1, 401)], 929s + end =x[c(349, J)] 929s + ) 929s > 929s > fit2 <- PSCBS::segmentByCBS(y, x=x, knownSegments=knownSegments) 929s > 929s Start: segmentByCBS,calls.R 929s 929s R version 4.5.2 (2025-10-31) -- "[Not] Part in a Rumble" 929s Copyright (C) 2025 The R Foundation for Statistical Computing 929s Platform: powerpc64le-unknown-linux-gnu 929s 929s R is free software and comes with ABSOLUTELY NO WARRANTY. 929s You are welcome to redistribute it under certain conditions. 929s Type 'license()' or 'licence()' for distribution details. 929s 929s R is a collaborative project with many contributors. 929s Type 'contributors()' for more information and 929s 'citation()' on how to cite R or R packages in publications. 929s 929s Type 'demo()' for some demos, 'help()' for on-line help, or 929s 'help.start()' for an HTML browser interface to help. 929s Type 'q()' to quit R. 929s 930s > # This test script calls a report generator which requires 930s > # the 'ggplot2' package, which in turn will require packages 930s > # 'colorspace', 'dichromat', 'munsell', 'reshape2' and 'scales'. 930s > 930s > # Only run this test in full testing mode 930s > if (Sys.getenv("_R_CHECK_FULL_") != "") { 930s + library("PSCBS") 930s + stext <- R.utils::stext 930s + 930s + # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 930s + # Load SNP microarray data 930s + # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 930s + data <- PSCBS::exampleData("paired.chr01") 930s + str(data) 930s + 930s + data <- data.frame(chromosome=data$chromosome, x=data$x, y=data$CT) 930s + 930s + 930s + # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 930s + # CBS segmentation 930s + # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 930s + # Drop single-locus outliers 930s + dataS <- dropSegmentationOutliers(data) 930s + 930s + # Speed up example by segmenting fewer loci 930s + dataS <- dataS[seq(from=1, to=nrow(data), by=5),] 930s + 930s + str(dataS) 930s + 930s + gaps <- findLargeGaps(dataS, minLength=2e6) 930s + knownSegments <- gapsToSegments(gaps) 930s + 930s + # CBS segmentation 930s + fit <- segmentByCBS(dataS, knownSegments=knownSegments, 930s + seed=0xBEEF, verbose=-10) 930s + signalType(fit) <- "ratio" 930s + plotTracks(fit) 930s + 930s + 930s + # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 930s + # Call using the UCSF MAD caller (not recommended) 930s + # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 930s + fitC <- callGainsAndLosses(fit) 930s + plotTracks(fitC) 930s + pars <- fitC$params$callGainsAndLosses 930s + stext(side=3, pos=1/2, line=-1, substitute(sigma==x, list(x=sprintf("%.2f", pars$sigmaMAD)))) 930s + mu <- pars$muR 930s + tau <- unlist(pars[c("tauLoss", "tauGain")], use.names=FALSE) 930s + abline(h=mu, lty=2, lwd=2) 930s + abline(h=tau, lwd=2) 930s + mtext(side=4, at=tau[1], expression(Delta[LOSS]), adj=-0.2, cex=0.7, las=2, xpd=TRUE) 930s + mtext(side=4, at=tau[2], expression(Delta[GAIN]), adj=-0.2, cex=0.7, las=2, xpd=TRUE) 930s + title(main="CN caller: \"ucsf-mad\"") 930s + 930s + 930s + # Caller to be implemented 930s + deltaCN <- estimateDeltaCN(fit) 930s + tau <- mu + 1/2*c(-1,+1)*deltaCN 930s + abline(h=tau, lty=2, lwd=1, col="red") 930s + 930s + 930s + 930s + } # if (Sys.getenv("_R_CHECK_FULL_")) 930s > 930s Start: segmentByCBS,futures.R 930s 930s R version 4.5.2 (2025-10-31) -- "[Not] Part in a Rumble" 930s Copyright (C) 2025 The R Foundation for Statistical Computing 930s Platform: powerpc64le-unknown-linux-gnu 930s 930s R is free software and comes with ABSOLUTELY NO WARRANTY. 930s You are welcome to redistribute it under certain conditions. 930s Type 'license()' or 'licence()' for distribution details. 930s 930s R is a collaborative project with many contributors. 930s Type 'contributors()' for more information and 930s 'citation()' on how to cite R or R packages in publications. 930s 930s Type 'demo()' for some demos, 'help()' for on-line help, or 930s 'help.start()' for an HTML browser interface to help. 930s Type 'q()' to quit R. 930s 930s > library("PSCBS") 930s > 930s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 930s > # Simulating copy-number data 930s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 930s > set.seed(0xBEEF) 930s > 930s > # Number of loci 930s > J <- 1000 930s PSCBS v0.68.0 (2025-04-18 19:40:02 UTC) successfully loaded. See ?PSCBS for help. 930s > 930s > mu <- double(J) 930s > mu[200:300] <- mu[200:300] + 1 930s > mu[350:400] <- NA # centromere 930s > mu[650:800] <- mu[650:800] - 1 930s > eps <- rnorm(J, sd=1/2) 930s > y <- mu + eps 930s > x <- sort(runif(length(y), max=length(y))) * 1e5 930s > w <- runif(J) 930s > w[650:800] <- 0.001 930s > 930s > ## Create multiple chromosomes 930s > data <- knownSegments <- list() 930s > for (cc in 1:3) { 930s + data[[cc]] <- data.frame(chromosome=cc, y=y, x=x) 930s + knownSegments[[cc]] <- data.frame( 930s + chromosome=c( cc, cc, cc), 930s + start =x[c( 1, 350, 401)], 930s + end =x[c(349, 400, J)] 930s + ) 930s + } 930s *** segmentByCBS() via futures ... 930s *** segmentByCBS() via futures with 'future' attached ... 930s > data <- Reduce(rbind, data) 930s > str(data) 930s 'data.frame': 3000 obs. of 3 variables: 930s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 930s $ y : num 0.295 0.115 -0.194 -0.392 -0.518 ... 930s $ x : num 55168 593204 605649 630624 746896 ... 930s > knownSegments <- Reduce(rbind, knownSegments) 930s > str(knownSegments) 930s 'data.frame': 9 obs. of 3 variables: 930s $ chromosome: int 1 1 1 2 2 2 3 3 3 930s $ start : num 55168 34194740 41080533 55168 34194740 ... 930s $ end : num 34142178 41044125 99910827 34142178 41044125 ... 930s > 930s > message("*** segmentByCBS() via futures ...") 930s > 930s > 930s > message("*** segmentByCBS() via futures with 'future' attached ...") 930s > library("future") 930s Loading required package: future.batchtools 930s Warning message: 930s In library(package, lib.loc = lib.loc, character.only = TRUE, logical.return = TRUE, : 930s there is no package called ‘future.batchtools’ 930s Future strategies to test: ‘sequential’, ‘multisession’ 930s - segmentByCBS() using 'sequential' futures ... 930s > oplan <- plan() 930s > 930s > strategies <- c("sequential", "multisession") 930s > 930s > ## Test 'future.batchtools' futures? 930s > pkg <- "future.batchtools" 930s > if (require(pkg, character.only=TRUE)) { 930s + strategies <- c(strategies, "batchtools_local") 930s + } 930s > 930s > message("Future strategies to test: ", paste(sQuote(strategies), collapse=", ")) 930s > 930s > fits <- list() 930s > for (strategy in strategies) { 930s + message(sprintf("- segmentByCBS() using '%s' futures ...", strategy)) 930s + plan(strategy) 930s + fit <- segmentByCBS(data, seed=0xBEEF, verbose=TRUE) 930s + fits[[strategy]] <- fit 930s + stopifnot(all.equal(fit, fits[[1]])) 930s + } 930s Segmenting by CBS... 930s Segmenting multiple chromosomes... 930s Number of chromosomes: 3 930s Random seed temporarily set (seed=c(48879), kind="L'Ecuyer-CMRG") 930s Produced 3 seeds from this stream for future usage 930s Chromosome #1 ('Chr01') of 3... 930s Segmenting by CBS... 930s Chromosome: 1 930s Random seed temporarily set (seed=c(10407, 1066287653, -51199871, 161854402, -1995183193, 1503453565, -747102133), kind="L'Ecuyer-CMRG") 930s Segmenting by CBS...done 930s Chromosome #1 ('Chr01') of 3...done 930s Chromosome #2 ('Chr02') of 3... 930s Segmenting by CBS... 930s Chromosome: 2 930s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 930s Segmenting by CBS...done 930s Chromosome #2 ('Chr02') of 3...done 930s Chromosome #3 ('Chr03') of 3... 930s Segmenting by CBS... 930s Chromosome: 3 930s Random seed temporarily set (seed=c(10407, -821273412, -52578226, 1415511586, 721384351, -665928286, 1316562960), kind="L'Ecuyer-CMRG") 930s Segmenting by CBS...done 930s Chromosome #3 ('Chr03') of 3...done 930s Segmenting multiple chromosomes...done 930s Segmenting by CBS...done 930s list() 930s - segmentByCBS() using 'multisession' futures ... 931s Segmenting by CBS... 931s Segmenting multiple chromosomes... 931s Number of chromosomes: 3 931s Random seed temporarily set (seed=c(48879), kind="L'Ecuyer-CMRG") 931s Produced 3 seeds from this stream for future usage 931s Chromosome #1 ('Chr01') of 3... 931s Chromosome #1 ('Chr01') of 3...done 931s Chromosome #2 ('Chr02') of 3... 931s Random seed temporarily set (seed=c(10407, 1066287653, -51199871, 161854402, -1995183193, 1503453565, -747102133), kind="L'Ecuyer-CMRG") 931s Segmenting by CBS...done 932s Chromosome #2 ('Chr02') of 3...done 932s Chromosome #3 ('Chr03') of 3... 932s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 932s Segmenting by CBS...done 932s Chromosome #3 ('Chr03') of 3...done 932s Segmenting by CBS... 932s Chromosome: 3 932s Random seed temporarily set (seed=c(10407, -821273412, -52578226, 1415511586, 721384351, -665928286, 1316562960), kind="L'Ecuyer-CMRG") 932s Segmenting by CBS...done 932s Segmenting multiple chromosomes...done 932s Segmenting by CBS...done 932s *** segmentByCBS() via futures with known segments ... 932s list() 932s > 932s > 932s > message("*** segmentByCBS() via futures with known segments ...") 932s > fits <- list() 932s > dataT <- subset(data, chromosome == 1) 932s > for (strategy in strategies) { 932s + message(sprintf("- segmentByCBS() w/ known segments using '%s' futures ...", strategy)) 932s + plan(strategy) 932s + fit <- segmentByCBS(dataT, knownSegments=knownSegments, seed=0xBEEF, verbose=TRUE) 932s + fits[[strategy]] <- fit 932s + stopifnot(all.equal(fit, fits[[1]])) 932s + } 932s - segmentByCBS() w/ known segments using 'sequential' futures ... 932s Segmenting by CBS... 932s Chromosome: 1 932s Random seed temporarily set (seed=c(48879), kind="L'Ecuyer-CMRG") 932s Produced 3 seeds from this stream for future usage 932s Segmenting by CBS...done 933s list() 933s - segmentByCBS() w/ known segments using 'multisession' futures ... 933s Segmenting by CBS... 933s Chromosome: 1 933s Random seed temporarily set (seed=c(48879), kind="L'Ecuyer-CMRG") 933s Produced 3 seeds from this stream for future usage 934s Segmenting by CBS...done 934s list() 934s > 934s > message("*** segmentByCBS() via futures ... DONE") 934s > 934s > 934s > ## Cleanup 934s > plan(oplan) 934s *** segmentByCBS() via futures ... DONE 934s > rm(list=c("fits", "dataT", "data", "fit")) 934s > 934s > 934s Start: segmentByCBS,median.R 934s 934s R version 4.5.2 (2025-10-31) -- "[Not] Part in a Rumble" 934s Copyright (C) 2025 The R Foundation for Statistical Computing 934s Platform: powerpc64le-unknown-linux-gnu 934s 934s R is free software and comes with ABSOLUTELY NO WARRANTY. 934s You are welcome to redistribute it under certain conditions. 934s Type 'license()' or 'licence()' for distribution details. 934s 934s R is a collaborative project with many contributors. 934s Type 'contributors()' for more information and 934s 'citation()' on how to cite R or R packages in publications. 934s 934s Type 'demo()' for some demos, 'help()' for on-line help, or 934s 'help.start()' for an HTML browser interface to help. 934s Type 'q()' to quit R. 934s 934s > library("PSCBS") 934s PSCBS v0.68.0 (2025-04-18 19:40:02 UTC) successfully loaded. See ?PSCBS for help. 934s > 934s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 934s > # Simulating copy-number data 934s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 934s > set.seed(0xBEEF) 934s > 934s > # Number of loci 934s > J <- 1000 934s > 934s > x <- sort(runif(J, max=J)) * 1e5 934s > 934s > mu <- double(J) 934s > mu[200:300] <- mu[200:300] + 1 934s > mu[350:400] <- NA # centromere 934s > mu[650:800] <- mu[650:800] - 1 934s > eps <- rnorm(J, sd=1/2) 934s > y <- mu + eps 934s > 934s > outliers <- seq(from=1L, to=J, length.out=0.2*J) 934s > y[outliers] <- y[outliers] + 1.5 934s > 934s > w <- rep(1.0, times=J) 934s > w[outliers] <- 0.01 934s > 934s > data <- data.frame(chromosome=1L, x=x, y=y) 934s > dataW <- cbind(data, w=w) 934s > 934s > 934s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 934s > # Single-chromosome segmentation 934s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 934s > par(mar=c(2,3,0.2,1)+0.1) 934s > # Segment without weights 934s > fit <- segmentByCBS(data) 935s > sampleName(fit) <- "CBS_Example" 935s > print(fit) 935s sampleName chromosome start end nbrOfLoci mean 935s 1 CBS_Example 1 136857.7 19138391 199 0.2712 935s 2 CBS_Example 1 19138391.4 28682180 101 1.2168 935s 3 CBS_Example 1 28682180.1 64690253 298 0.3027 935s 4 CBS_Example 1 64690253.3 80738828 151 -0.7101 935s 5 CBS_Example 1 80738828.3 99932904 200 0.3655 935s > plotTracks(fit) 935s > ## Highlight outliers (they pull up the mean levels) 935s > points(x[outliers]/1e6, y[outliers], col="purple") 935s Warning message: 935s In plotTracks.CBS(fit) : 935s Setting default 'Clim' assuming the signal type is ‘ratio’ because signalType(fit) is unknown (‘NA’). Use signalType(fit) <- ‘ratio’ to avoid this warning. 935s > 935s > # Segment without weights but with median 935s > fitM <- segmentByCBS(data, avg="median") 935s > sampleName(fitM) <- "CBS_Example (median)" 935s > print(fitM) 935s sampleName chromosome start end nbrOfLoci mean 935s 1 CBS_Example (median) 1 136857.7 19138391 199 0.1203255 935s 2 CBS_Example (median) 1 19138391.4 28682180 101 0.9949202 935s 3 CBS_Example (median) 1 28682180.1 64690253 298 0.1471793 935s 4 CBS_Example (median) 1 64690253.3 80738828 151 -0.8770443 935s 5 CBS_Example (median) 1 80738828.3 99932904 200 0.2211061 935s > drawLevels(fitM, col="magenta", lty=3) 935s NULL 935s > 935s > # Segment with weights 935s > fitW <- segmentByCBS(dataW, avg="median") 935s > sampleName(fitW) <- "CBS_Example (weighted)" 935s > print(fitW) 935s sampleName chromosome start end nbrOfLoci mean 935s 1 CBS_Example (weighted) 1 136857.7 19138391 199 -0.02220950 935s 2 CBS_Example (weighted) 1 19138391.4 28682180 101 0.92421628 935s 3 CBS_Example (weighted) 1 28682180.1 64690253 298 -0.02364830 935s 4 CBS_Example (weighted) 1 64690253.3 80738828 151 -1.04750872 935s 5 CBS_Example (weighted) 1 80738828.3 99932904 200 0.08961195 935s > drawLevels(fitW, col="red") 935s NULL 935s > 935s > # Segment with weights and median 935s > fitWM <- segmentByCBS(dataW, avg="median") 935s > sampleName(fitWM) <- "CBS_Example (weighted median)" 935s > print(fitWM) 935s sampleName chromosome start end nbrOfLoci 935s 1 CBS_Example (weighted median) 1 136857.7 19138391 199 935s 2 CBS_Example (weighted median) 1 19138391.4 28682180 101 935s 3 CBS_Example (weighted median) 1 28682180.1 64690253 298 935s 4 CBS_Example (weighted median) 1 64690253.3 80738828 151 935s 5 CBS_Example (weighted median) 1 80738828.3 99932904 200 935s mean 935s 1 -0.02220950 935s 2 0.92421628 935s 3 -0.02364830 935s 4 -1.04750872 935s 5 0.08961195 935s > drawLevels(fitWM, col="orange", lty=3) 935s NULL 935s > 935s > 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)) 935s > 935s > ## Assert that weighted segment means are less biased 935s > dmean <- getSegments(fit)$mean - getSegments(fitW)$mean 935s > cat("Segment mean differences:\n") 935s Segment mean differences: 935s > print(dmean) 935s [1] 0.2934095 0.2925837 0.3263483 0.3374087 0.2758881 935s > stopifnot(all(dmean > 0, na.rm=TRUE)) 935s > 935s > dmean <- getSegments(fitM)$mean - getSegments(fitWM)$mean 935s > cat("Segment median differences:\n") 935s Segment median differences: 935s > print(dmean) 935s [1] 0.14253502 0.07070392 0.17082758 0.17046439 0.13149418 935s > stopifnot(all(dmean > 0, na.rm=TRUE)) 935s > 935s > 935s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 935s > # Multi-chromosome segmentation 935s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 935s > data2 <- data 935s > data2$chromosome <- 2L 935s > data <- rbind(data, data2) 935s > dataW <- cbind(data, w=w) 935s > 935s > par(mar=c(2,3,0.2,1)+0.1) 935s > # Segment without weights 935s > fit <- segmentByCBS(data) 935s > sampleName(fit) <- "CBS_Example" 935s > print(fit) 935s sampleName chromosome start end nbrOfLoci mean 935s 1 CBS_Example 1 136857.7 19138391 199 0.2712 935s 2 CBS_Example 1 19138391.4 28682180 101 1.2168 935s 3 CBS_Example 1 28682180.1 64690253 298 0.3027 935s 4 CBS_Example 1 64690253.3 80738828 151 -0.7101 935s 5 CBS_Example 1 80738828.3 99932904 200 0.3655 935s 6 NA NA NA NA NA 935s 7 CBS_Example 2 136857.7 19138391 199 0.2712 935s 8 CBS_Example 2 19138391.4 28682180 101 1.2168 935s 9 CBS_Example 2 28682180.1 64690253 298 0.3027 935s 10 CBS_Example 2 64690253.3 80738828 151 -0.7101 935s 11 CBS_Example 2 80738828.3 99932904 200 0.3655 935s > plotTracks(fit, Clim=c(-3,3)) 935s > 935s > # Segment without weights but with median 935s > fitM <- segmentByCBS(data, avg="median") 935s > sampleName(fitM) <- "CBS_Example (median)" 935s > print(fitM) 935s sampleName chromosome start end nbrOfLoci mean 935s 1 CBS_Example (median) 1 136857.7 19138391 199 0.1203255 935s 2 CBS_Example (median) 1 19138391.4 28682180 101 0.9949202 935s 3 CBS_Example (median) 1 28682180.1 64690253 298 0.1471793 935s 4 CBS_Example (median) 1 64690253.3 80738828 151 -0.8770443 935s 5 CBS_Example (median) 1 80738828.3 99932904 200 0.2211061 935s 6 NA NA NA NA NA 935s 7 CBS_Example (median) 2 136857.7 19138391 199 0.1203255 935s 8 CBS_Example (median) 2 19138391.4 28682180 101 0.9949202 935s 9 CBS_Example (median) 2 28682180.1 64690253 298 0.1471793 935s 10 CBS_Example (median) 2 64690253.3 80738828 151 -0.8770443 935s 11 CBS_Example (median) 2 80738828.3 99932904 200 0.2211061 935s > drawLevels(fitM, col="magenta", lty=3) 935s NULL 935s > 935s > # Segment with weights 935s > fitW <- segmentByCBS(dataW, avg="median") 935s > sampleName(fitW) <- "CBS_Example (weighted)" 935s > print(fitW) 935s sampleName chromosome start end nbrOfLoci mean 935s 1 CBS_Example (weighted) 1 136857.7 19138391 199 -0.02220950 935s 2 CBS_Example (weighted) 1 19138391.4 28682180 101 0.92421628 935s 3 CBS_Example (weighted) 1 28682180.1 64690253 298 -0.02364830 935s 4 CBS_Example (weighted) 1 64690253.3 80738828 151 -1.04750872 935s 5 CBS_Example (weighted) 1 80738828.3 99932904 200 0.08961195 935s 6 NA NA NA NA NA 935s 7 CBS_Example (weighted) 2 136857.7 19138391 199 -0.02220950 935s 8 CBS_Example (weighted) 2 19138391.4 28682180 101 0.92421628 935s 9 CBS_Example (weighted) 2 28682180.1 64690253 298 -0.02364830 935s 10 CBS_Example (weighted) 2 64690253.3 80738828 151 -1.04750872 935s 11 CBS_Example (weighted) 2 80738828.3 99932904 200 0.08961195 935s > drawLevels(fitW, col="red") 935s NULL 935s > 935s > # Segment with weights and median 935s > fitWM <- segmentByCBS(dataW, avg="median") 936s > sampleName(fitWM) <- "CBS_Example (weighted median)" 936s > print(fitWM) 936s sampleName chromosome start end nbrOfLoci 936s 1 CBS_Example (weighted median) 1 136857.7 19138391 199 936s 2 CBS_Example (weighted median) 1 19138391.4 28682180 101 936s 3 CBS_Example (weighted median) 1 28682180.1 64690253 298 936s 4 CBS_Example (weighted median) 1 64690253.3 80738828 151 936s 5 CBS_Example (weighted median) 1 80738828.3 99932904 200 936s 6 NA NA NA NA 936s 7 CBS_Example (weighted median) 2 136857.7 19138391 199 936s 8 CBS_Example (weighted median) 2 19138391.4 28682180 101 936s 9 CBS_Example (weighted median) 2 28682180.1 64690253 298 936s 10 CBS_Example (weighted median) 2 64690253.3 80738828 151 936s 11 CBS_Example (weighted median) 2 80738828.3 99932904 200 936s mean 936s 1 -0.02220950 936s 2 0.92421628 936s 3 -0.02364830 936s 4 -1.04750872 936s 5 0.08961195 936s 6 NA 936s 7 -0.02220950 936s 8 0.92421628 936s 9 -0.02364830 936s 10 -1.04750872 936s 11 0.08961195 936s > drawLevels(fitWM, col="orange", lty=3) 936s NULL 936s > 936s > 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)) 936s > 936s > ## Assert that weighted segment means are less biased 936s > dmean <- getSegments(fit)$mean - getSegments(fitW)$mean 936s > cat("Segment mean differences:\n") 936s Segment mean differences: 936s > print(dmean) 936s [1] 0.2934095 0.2925837 0.3263483 0.3374087 0.2758881 NA 0.2934095 936s [8] 0.2925837 0.3263483 0.3374087 0.2758881 936s > stopifnot(all(dmean > 0, na.rm=TRUE)) 936s > 936s > dmean <- getSegments(fitM)$mean - getSegments(fitWM)$mean 936s > cat("Segment median differences:\n") 936s Segment median differences: 936s > print(dmean) 936s [1] 0.14253502 0.07070392 0.17082758 0.17046439 0.13149418 NA 936s [7] 0.14253502 0.07070392 0.17082758 0.17046439 0.13149418 936s > stopifnot(all(dmean > 0, na.rm=TRUE)) 936s > 936s Start: segmentByCBS,prune.R 936s 936s R version 4.5.2 (2025-10-31) -- "[Not] Part in a Rumble" 936s Copyright (C) 2025 The R Foundation for Statistical Computing 936s Platform: powerpc64le-unknown-linux-gnu 936s 936s R is free software and comes with ABSOLUTELY NO WARRANTY. 936s You are welcome to redistribute it under certain conditions. 936s Type 'license()' or 'licence()' for distribution details. 936s 936s R is a collaborative project with many contributors. 936s Type 'contributors()' for more information and 936s 'citation()' on how to cite R or R packages in publications. 936s 936s Type 'demo()' for some demos, 'help()' for on-line help, or 936s 'help.start()' for an HTML browser interface to help. 936s Type 'q()' to quit R. 936s 936s > library("PSCBS") 936s PSCBS v0.68.0 (2025-04-18 19:40:02 UTC) successfully loaded. See ?PSCBS for help. 936s > 936s > ## Compare segments 936s > assertMatchingSegments <- function(fitM, fit) { 936s + chrs <- getChromosomes(fitM) 936s + segsM <- lapply(chrs, FUN=function(chr) { 936s + getSegments(extractChromosome(fitM, chr)) 936s + }) 936s + segs <- lapply(fit[chrs], FUN=getSegments) 936s + stopifnot(all.equal(segsM, segs, check.attributes=FALSE)) 936s + } 936s > 936s > ## Simulate data 936s > set.seed(0xBEEF) 936s > J <- 1000 936s > mu <- double(J) 936s > mu[200:300] <- mu[200:300] + 1 936s > mu[350:400] <- NA 936s > mu[650:800] <- mu[650:800] - 1 936s > eps <- rnorm(J, sd=1/2) 936s > y <- mu + eps 936s > x <- sort(runif(length(y), max=length(y))) * 1e5 936s > 936s > data <- list() 936s > for (chr in 1:2) { 936s + data[[chr]] <- data.frame(chromosome=chr, x=x, y=y) 936s + } 936s > data$M <- Reduce(rbind, data) 936s > 936s > ## Segment 936s > message("*** segmentByCBS()") 936s > fit <- lapply(data, FUN=segmentByCBS) 936s *** segmentByCBS() 936s > print(fit) 936s [[1]] 936s sampleName chromosome start end nbrOfLoci mean 936s 1 1 55167.82 20774251 201 0.0164 936s 2 1 20774250.85 29320105 99 1.0474 936s 3 1 29320104.86 65874675 298 -0.0203 936s 4 1 65874675.06 81348129 151 -1.0813 936s 5 1 81348129.20 99910827 200 -0.0612 936s 936s [[2]] 936s sampleName chromosome start end nbrOfLoci mean 936s 1 2 55167.82 20774251 201 0.0164 936s 2 2 20774250.85 29320105 99 1.0474 936s 3 2 29320104.86 65874675 298 -0.0203 936s 4 2 65874675.06 81348129 151 -1.0813 936s 5 2 81348129.20 99910827 200 -0.0612 936s 936s $M 936s sampleName chromosome start end nbrOfLoci mean 936s 1 1 55167.82 20774251 201 0.0164 936s 2 1 20774250.85 29320105 99 1.0474 936s 3 1 29320104.86 65874675 298 -0.0203 936s 4 1 65874675.06 81348129 151 -1.0813 936s 5 1 81348129.20 99910827 200 -0.0612 936s 6 NA NA NA NA NA 936s 7 2 55167.82 20774251 201 0.0164 936s 8 2 20774250.85 29320105 99 1.0474 936s 9 2 29320104.86 65874675 298 -0.0203 936s 10 2 65874675.06 81348129 151 -1.0813 936s 11 2 81348129.20 99910827 200 -0.0612 936s 936s > assertMatchingSegments(fit$M, fit) 936s > 936s > ## Join segments 936s > message("*** joinSegments()") 936s > fitj <- lapply(fit, FUN=joinSegments) 936s *** joinSegments() 936s > print(fitj) 936s [[1]] 936s sampleName chromosome start end nbrOfLoci mean 936s 1 1 55167.82 20774251 201 0.0164 936s 2 1 20774250.85 29320105 99 1.0474 936s 3 1 29320104.86 65874675 298 -0.0203 936s 4 1 65874675.06 81348129 151 -1.0813 936s 5 1 81348129.20 99910827 200 -0.0612 936s 936s [[2]] 936s sampleName chromosome start end nbrOfLoci mean 936s 1 2 55167.82 20774251 201 0.0164 936s 2 2 20774250.85 29320105 99 1.0474 936s 3 2 29320104.86 65874675 298 -0.0203 936s 4 2 65874675.06 81348129 151 -1.0813 936s 5 2 81348129.20 99910827 200 -0.0612 936s 936s $M 936s sampleName chromosome start end nbrOfLoci mean 936s 1 1 55167.82 20774251 201 0.0164 936s 2 1 20774250.85 29320105 99 1.0474 936s 3 1 29320104.86 65874675 298 -0.0203 936s 4 1 65874675.06 81348129 151 -1.0813 936s 5 1 81348129.20 99910827 200 -0.0612 936s 6 NA NA NA NA NA 936s 7 2 55167.82 20774251 201 0.0164 936s 8 2 20774250.85 29320105 99 1.0474 936s 9 2 29320104.86 65874675 298 -0.0203 936s 10 2 65874675.06 81348129 151 -1.0813 936s 11 2 81348129.20 99910827 200 -0.0612 936s 936s > assertMatchingSegments(fitj$M, fitj) 936s > 936s > ## Reset segments 936s > message("*** resetSegments()") 936s > fitj <- lapply(fit, FUN=resetSegments) 936s *** resetSegments() 936s > print(fitj) 936s [[1]] 936s sampleName chromosome start end nbrOfLoci mean 936s 1 1 55167.82 20774251 201 0.0164 936s 2 1 20774250.85 29320105 99 1.0474 936s 3 1 29320104.86 65874675 298 -0.0203 936s 4 1 65874675.06 81348129 151 -1.0813 936s 5 1 81348129.20 99910827 200 -0.0612 936s 936s [[2]] 936s sampleName chromosome start end nbrOfLoci mean 936s 1 2 55167.82 20774251 201 0.0164 936s 2 2 20774250.85 29320105 99 1.0474 936s 3 2 29320104.86 65874675 298 -0.0203 936s 4 2 65874675.06 81348129 151 -1.0813 936s 5 2 81348129.20 99910827 200 -0.0612 936s 936s $M 936s sampleName chromosome start end nbrOfLoci mean 936s 1 1 55167.82 20774251 201 0.0164 936s 2 1 20774250.85 29320105 99 1.0474 936s 3 1 29320104.86 65874675 298 -0.0203 936s 4 1 65874675.06 81348129 151 -1.0813 936s 5 1 81348129.20 99910827 200 -0.0612 936s 6 NA NA NA NA NA 936s 7 2 55167.82 20774251 201 0.0164 936s 8 2 20774250.85 29320105 99 1.0474 936s 9 2 29320104.86 65874675 298 -0.0203 936s 10 2 65874675.06 81348129 151 -1.0813 936s 11 2 81348129.20 99910827 200 -0.0612 936s 936s > assertMatchingSegments(fitj$M, fitj) 936s > 936s > ## Prune by SD undo 936s > message("*** pruneBySdUndo()") 936s > fitp <- lapply(fit, FUN=pruneBySdUndo) 936s *** pruneBySdUndo() 936s > print(fitp) 936s [[1]] 936s sampleName chromosome start end nbrOfLoci mean 936s 1 1 55167.82 99910827 949 -0.07857059 936s 936s [[2]] 936s sampleName chromosome start end nbrOfLoci mean 936s 1 2 55167.82 99910827 949 -0.07857059 936s 936s $M 936s sampleName chromosome start end nbrOfLoci mean 936s 1 1 55167.82 99910827 949 -0.07857059 936s 2 NA NA NA NA NA 936s 3 2 55167.82 99910827 949 -0.07857059 936s 936s > assertMatchingSegments(fitp$M, fitp) 936s *** pruneByHClust() 936s > 936s > ## Prune by hierarchical clustering 936s > message("*** pruneByHClust()") 936s > fitp <- lapply(fit, FUN=pruneByHClust, k=1L) 937s > print(fitp) 937s [[1]] 937s sampleName chromosome start end nbrOfLoci mean 937s 1 1 55167.82 99910827 949 -0.07857059 937s 937s [[2]] 937s sampleName chromosome start end nbrOfLoci mean 937s 1 2 55167.82 99910827 949 -0.07857059 937s 937s $M 937s sampleName chromosome start end nbrOfLoci mean 937s 1 1 55167.82 99910827 949 -0.07857059 937s 6 NA NA NA NA NA 937s 7 2 55167.82 99910827 949 -0.07857059 937s 937s > assertMatchingSegments(fitp$M, fitp) 937s > 937s Start: segmentByCBS,report.R 937s 937s R version 4.5.2 (2025-10-31) -- "[Not] Part in a Rumble" 937s Copyright (C) 2025 The R Foundation for Statistical Computing 937s Platform: powerpc64le-unknown-linux-gnu 937s 937s R is free software and comes with ABSOLUTELY NO WARRANTY. 937s You are welcome to redistribute it under certain conditions. 937s Type 'license()' or 'licence()' for distribution details. 937s 937s R is a collaborative project with many contributors. 937s Type 'contributors()' for more information and 937s 'citation()' on how to cite R or R packages in publications. 937s 937s Type 'demo()' for some demos, 'help()' for on-line help, or 937s 'help.start()' for an HTML browser interface to help. 937s Type 'q()' to quit R. 937s 937s > # This test script calls a report generator which requires 937s > # the 'ggplot2' package, which in turn will require packages 937s > # 'colorspace', 'dichromat', 'munsell', 'reshape2' and 'scales'. 937s > 937s > # Only run this test in full testing mode 937s > if (Sys.getenv("_R_CHECK_FULL_") != "") { 937s + library("PSCBS") 937s + 937s + # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 937s + # Load SNP microarray data 937s + # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 937s + data <- PSCBS::exampleData("paired.chr01") 937s + str(data) 937s + 937s + data <- data.frame(chromosome=data$chromosome, x=data$x, y=data$CT) 937s + 937s + 937s + # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 937s + # CBS segmentation 937s + # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 937s + # Drop single-locus outliers 937s + dataS <- dropSegmentationOutliers(data) 937s + 937s + # Speed up example by segmenting fewer loci 937s + dataS <- dataS[seq(from=1, to=nrow(data), by=5),] 937s + 937s + str(dataS) 937s + 937s + gaps <- findLargeGaps(dataS, minLength=2e6) 937s + knownSegments <- gapsToSegments(gaps) 937s + 937s + # CBS segmentation 937s + fit <- segmentByCBS(dataS, knownSegments=knownSegments, 937s + seed=0xBEEF, verbose=-10) 937s + signalType(fit) <- "ratio" 937s + 937s + # Fake a multi-chromosome segmentation 937s + fit1 <- fit 937s + fit2 <- renameChromosomes(fit, from=1, to=2) 937s + fit <- c(fit1, fit2) 937s + 937s + report(fit, sampleName="CBS", studyName="CBS-Ex", verbose=-10) 937s + 937s + } # if (Sys.getenv("_R_CHECK_FULL_")) 937s > 937s Start: segmentByCBS,shiftTCN.R 937s 937s R version 4.5.2 (2025-10-31) -- "[Not] Part in a Rumble" 937s Copyright (C) 2025 The R Foundation for Statistical Computing 937s Platform: powerpc64le-unknown-linux-gnu 937s 937s R is free software and comes with ABSOLUTELY NO WARRANTY. 937s You are welcome to redistribute it under certain conditions. 937s Type 'license()' or 'licence()' for distribution details. 937s 937s R is a collaborative project with many contributors. 937s Type 'contributors()' for more information and 937s 'citation()' on how to cite R or R packages in publications. 937s 937s Type 'demo()' for some demos, 'help()' for on-line help, or 937s 'help.start()' for an HTML browser interface to help. 937s Type 'q()' to quit R. 937s 937s > library("PSCBS") 937s PSCBS v0.68.0 (2025-04-18 19:40:02 UTC) successfully loaded. See ?PSCBS for help. 937s > subplots <- R.utils::subplots 937s > 937s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 937s > # Simulating copy-number data 937s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 937s > set.seed(0xBEEF) 937s > 937s > # Number of loci 937s > J <- 1000 937s > 937s > mu <- double(J) 937s > eps <- rnorm(J, sd=1/2) 937s > y <- mu + eps 937s > x <- sort(runif(length(y), max=length(y))) 937s > 937s > idxs <- which(200 <= x & x < 300) 937s > y[idxs] <- y[idxs] + 1 937s > idxs <- which(350 <= x & x < 400) 937s > y[idxs] <- NA # centromere 937s > x[idxs] <- NA # centromere 937s > idxs <- which(650 <= x & x < 800) 937s > y[idxs] <- y[idxs] - 1 937s > x <- x*1e5 937s > 937s > keep <- is.finite(x) 937s > x <- x[keep] 937s > y <- y[keep] 937s > 937s > data <- list() 937s > for (chr in 1:2) { 937s + data[[chr]] <- data.frame(chromosome=chr, y=y, x=x) 937s + } 937s > data <- Reduce(rbind, data) 937s > 937s > 937s > subplots(7, ncol=1) 937s > par(mar=c(1.7,1,0.2,1)+0.1) 937s > 937s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 937s > # Segmentation 937s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 937s > fit <- segmentByCBS(data) 937s > print(fit) 937s sampleName chromosome start end nbrOfLoci mean 937s 1 1 55167.82 20341782 195 0.0145 937s 2 1 20341781.95 29617861 108 1.0437 937s 3 1 29617861.37 64995303 299 -0.0208 937s 4 1 64995302.97 80042680 151 -1.0700 937s 5 1 80042679.86 99910827 211 -0.0568 937s 6 NA NA NA NA NA 937s 7 2 55167.82 20341782 195 0.0145 937s 8 2 20341781.95 29617861 108 1.0437 937s 9 2 29617861.37 64995303 299 -0.0208 937s 10 2 64995302.97 80042680 151 -1.0700 937s 11 2 80042679.86 99910827 211 -0.0568 937s > 937s > Clim <- c(-3,3) + c(0,10) 937s > plotTracks(fit, Clim=Clim) 937s > 937s > 937s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 937s > # Shifting every other chromosome 937s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 937s > fitList <- list() 937s > chrs <- getChromosomes(fit) 937s > for (kk in seq_along(chrs)) { 937s + chr <- chrs[kk] 937s + fitKK <- extractChromosome(fit, chr) 937s + if (kk %% 2 == 0) { 937s + fitKK <- shiftTCN(fitKK, shift=+10) 937s + } 937s + fitList[[kk]] <- fitKK 937s + } # for (kk ...) 937s > fitT <- do.call(c, fitList) 937s > # Sanity check 937s > stopifnot(nbrOfSegments(fitT) == nbrOfSegments(fit)) 937s > 937s > plotTracks(fitT, Clim=Clim) 938s > 938s > 938s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 938s > # Shifting every other known segment 938s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 938s > gaps <- findLargeGaps(data, minLength=40e5) 938s > knownSegments <- gapsToSegments(gaps, dropGaps=TRUE) 938s > fit <- segmentByCBS(data, knownSegments=knownSegments) 938s > 938s > subplots(2, ncol=1) 938s > plotTracks(fit, Clim=Clim) 938s > abline(v=c(knownSegments$start, knownSegments$end)/1e6, lty=3) 938s > 938s > fitList <- list() 938s > for (kk in seq_len(nrow(knownSegments))) { 938s + seg <- knownSegments[kk,] 938s + start <- seg$start 938s + end <- seg$end 938s + fitKK <- extractChromosome(fit, seg$chromosome) 938s + segsKK <- getSegments(fitKK) 938s + idxStart <- min(which(segsKK$start >= start)) 938s + idxEnd <- max(which(segsKK$end <= end)) 938s + idxs <- idxStart:idxEnd 938s + fitKK <- extractSegments(fitKK, idxs) 938s + if (kk %% 2 == 0) { 938s + fitKK <- shiftTCN(fitKK, shift=+10) 938s + } 938s + fitList[[kk]] <- fitKK 938s + } # for (kk ...) 938s > fitT <- do.call(c, fitList) 938s > # Sanity check 938s > stopifnot(nbrOfSegments(fitT) == nbrOfSegments(fit)) 938s > 938s > plotTracks(fitT, Clim=Clim) 938s > abline(v=c(knownSegments$start, knownSegments$end)/1e6, lty=3) 938s > 938s > 938s > segList <- seqOfSegmentsByDP(fit) 938s > K <- length(segList) 938s > subplots(K, ncol=2, byrow=FALSE) 938s > par(mar=c(2,1,1,1)) 938s > for (kk in 1:K) { 938s + knownSegments <- segList[[kk]] 938s + fitKK <- resegment(fit, knownSegments=knownSegments, undo=+Inf) 938s + plotTracks(fitKK, Clim=c(-3,3)) 938s + } # for (kk ...) 945s > 945s Start: segmentByCBS,weights.R 945s 945s R version 4.5.2 (2025-10-31) -- "[Not] Part in a Rumble" 945s Copyright (C) 2025 The R Foundation for Statistical Computing 945s Platform: powerpc64le-unknown-linux-gnu 945s 945s R is free software and comes with ABSOLUTELY NO WARRANTY. 945s You are welcome to redistribute it under certain conditions. 945s Type 'license()' or 'licence()' for distribution details. 945s 945s R is a collaborative project with many contributors. 945s Type 'contributors()' for more information and 945s 'citation()' on how to cite R or R packages in publications. 945s 945s Type 'demo()' for some demos, 'help()' for on-line help, or 945s 'help.start()' for an HTML browser interface to help. 945s Type 'q()' to quit R. 945s 945s > library("PSCBS") 945s PSCBS v0.68.0 (2025-04-18 19:40:02 UTC) successfully loaded. See ?PSCBS for help. 945s > 945s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 945s > # Simulating copy-number data 945s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 945s > set.seed(0xBEEF) 945s > 945s > # Number of loci 945s > J <- 1000 945s > 945s > x <- sort(runif(J, max=J)) * 1e5 945s > 945s > mu <- double(J) 945s > mu[200:300] <- mu[200:300] + 1 945s > mu[350:400] <- NA # centromere 945s > mu[650:800] <- mu[650:800] - 1 945s > eps <- rnorm(J, sd=1/2) 945s > y <- mu + eps 945s > 945s > outliers <- seq(from=1L, to=J, length.out=0.2*J) 945s > y[outliers] <- y[outliers] + 1.5 945s > 945s > w <- rep(1.0, times=J) 945s > w[outliers] <- 0.01 945s > 945s > data <- data.frame(chromosome=1L, x=x, y=y) 945s > dataW <- cbind(data, w=w) 945s > 945s > 945s > par(mar=c(2,3,0.2,1)+0.1) 945s > 945s > 945s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 945s > # Single-chromosome segmentation 945s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 945s > # Segment without weights 945s > fit <- segmentByCBS(data) 945s > sampleName(fit) <- "CBS_Example" 945s > print(fit) 945s sampleName chromosome start end nbrOfLoci mean 945s 1 CBS_Example 1 136857.7 19138391 199 0.2712 945s 2 CBS_Example 1 19138391.4 28682180 101 1.2168 945s 3 CBS_Example 1 28682180.1 64690253 298 0.3027 945s 4 CBS_Example 1 64690253.3 80738828 151 -0.7101 945s 5 CBS_Example 1 80738828.3 99932904 200 0.3655 945s > plotTracks(fit) 945s Warning message: 945s In plotTracks.CBS(fit) : 945s Setting default 'Clim' assuming the signal type is ‘ratio’ because signalType(fit) is unknown (‘NA’). Use signalType(fit) <- ‘ratio’ to avoid this warning. 945s > ## Highlight outliers (they pull up the mean levels) 945s > points(x[outliers]/1e6, y[outliers], col="purple") 945s > 945s > # Segment with weights 945s > fitW <- segmentByCBS(dataW) 945s > sampleName(fitW) <- "CBS_Example (weighted)" 945s > print(fitW) 945s sampleName chromosome start end nbrOfLoci mean 945s 1 CBS_Example (weighted) 1 136857.7 19138391 199 -0.0041 945s 2 CBS_Example (weighted) 1 19138391.4 28682180 101 0.8987 945s 3 CBS_Example (weighted) 1 28682180.1 64690253 298 0.0159 945s 4 CBS_Example (weighted) 1 64690253.3 80738828 151 -1.0215 945s 5 CBS_Example (weighted) 1 80738828.3 99932904 200 0.0653 945s > drawLevels(fitW, col="red") 945s NULL 945s > 945s > 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)) 945s Segmenting by CBS... 945s Chromosome: 1 945s > 945s > ## Assert that weighted segment means are less biased 945s > dmean <- getSegments(fit)$mean - getSegments(fitW)$mean 945s > cat("Segment mean differences:\n") 945s Segment mean differences: 945s > print(dmean) 945s [1] 0.2753 0.3181 0.2868 0.3114 0.3002 945s > stopifnot(all(dmean > 0, na.rm=TRUE)) 945s > 945s > 945s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 945s > # Segmentation with some known change points 945s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 945s > knownSegments <- data.frame( 945s + chromosome=c( 1, 1), 945s + start =x[c( 1, 401)], 945s + end =x[c(349, J)] 945s + ) 945s > fit2 <- segmentByCBS(dataW, knownSegments=knownSegments, verbose=TRUE) 946s Segmenting by CBS...done 946s > sampleName(fit2) <- "CBS_Example_2 (weighted)" 946s > print(fit2) 946s sampleName chromosome start end nbrOfLoci mean 946s 1 CBS_Example_2 (weighted) 1 136857.7 19138391 199 -0.0041 946s 2 CBS_Example_2 (weighted) 1 19138391.4 28682180 101 0.8987 946s 3 CBS_Example_2 (weighted) 1 28682180.1 34062461 49 -0.0552 946s 4 CBS_Example_2 (weighted) 1 38343432.8 64690253 249 0.0298 946s 5 CBS_Example_2 (weighted) 1 64690253.3 80738828 151 -1.0215 946s 6 CBS_Example_2 (weighted) 1 80738828.3 99932904 200 0.0653 946s > plotTracks(fit2) 946s Warning message: 946s In plotTracks.CBS(fit2) : 946s Setting default 'Clim' assuming the signal type is ‘ratio’ because signalType(fit2) is unknown (‘NA’). Use signalType(fit2) <- ‘ratio’ to avoid this warning. 946s > abline(v=c(knownSegments$start, knownSegments$end)/1e6, lty=3) 946s > 946s > 946s > # Chromosome boundaries can be specified as -Inf and +Inf 946s > knownSegments <- data.frame( 946s + chromosome=c( 1, 1), 946s + start =c( -Inf, x[401]), 946s + end =c(x[349], +Inf) 946s + ) 946s > fit2b <- segmentByCBS(dataW, knownSegments=knownSegments, verbose=TRUE) 946s Segmenting by CBS... 946s Chromosome: 1 946s Segmenting by CBS...done 946s > sampleName(fit2b) <- "CBS_Example_2b (weighted)" 946s > print(fit2b) 946s sampleName chromosome start end nbrOfLoci mean 946s 1 CBS_Example_2b (weighted) 1 136857.7 19138391 199 -0.0041 946s 2 CBS_Example_2b (weighted) 1 19138391.4 28682180 101 0.8987 946s 3 CBS_Example_2b (weighted) 1 28682180.1 34062461 49 -0.0552 946s 4 CBS_Example_2b (weighted) 1 38343432.8 64690253 249 0.0298 946s 5 CBS_Example_2b (weighted) 1 64690253.3 80738828 151 -1.0215 946s 6 CBS_Example_2b (weighted) 1 80738828.3 99932904 200 0.0653 946s > plotTracks(fit2b) 946s Warning message: 946s In plotTracks.CBS(fit2b) : 946s Setting default 'Clim' assuming the signal type is ‘ratio’ because signalType(fit2b) is unknown (‘NA’). Use signalType(fit2b) <- ‘ratio’ to avoid this warning. 946s > abline(v=c(knownSegments$start, knownSegments$end)/1e6, lty=3) 946s > 946s > 946s > # As a proof of concept, it is possible to segment just the centromere, 946s > # which contains no data. All statistics will be NAs. 946s > knownSegments <- data.frame( 946s + chromosome=c( 1), 946s + start =x[c(350)], 946s + end =x[c(400)] 946s + ) 946s > fit3 <- segmentByCBS(dataW, knownSegments=knownSegments, verbose=TRUE) 946s Segmenting by CBS... 946s Chromosome: 1 946s Segmenting by CBS...done 946s > sampleName(fit3) <- "CBS_Example_3" 946s > print(fit3) 946s sampleName chromosome start end nbrOfLoci mean 946s 1 CBS_Example_3 1 34108010 38257409 0 NA 946s > plotTracks(fit3, Clim=c(0,5), xlim=c(0,100)) 946s Segmenting by CBS... 946s Chromosome: 1 946s > abline(v=c(knownSegments$start, knownSegments$end)/1e6, lty=3) 946s > 946s > 946s > # If one specify the (empty) centromere as a segment, then its 946s > # estimated statistics will be NAs, which becomes a natural 946s > # separator between the two "independent" arms. 946s > knownSegments <- data.frame( 946s + chromosome=c( 1, 1, 1), 946s + start =x[c( 1, 350, 401)], 946s + end =x[c(349, 400, J)] 946s + ) 946s > fit4 <- segmentByCBS(dataW, knownSegments=knownSegments, verbose=TRUE) 947s Segmenting by CBS...done 947s > sampleName(fit4) <- "CBS_Example_4" 947s > print(fit4) 947s sampleName chromosome start end nbrOfLoci mean 947s 1 CBS_Example_4 1 136857.7 19138391 199 -0.0041 947s 2 CBS_Example_4 1 19138391.4 28682180 101 0.8987 947s 3 CBS_Example_4 1 28682180.1 34062461 49 -0.0552 947s 4 CBS_Example_4 1 34108009.8 38257409 0 NA 947s 5 CBS_Example_4 1 38343432.8 64690253 249 0.0298 947s 6 CBS_Example_4 1 64690253.3 80738828 151 -1.0215 947s 7 CBS_Example_4 1 80738828.3 99932904 200 0.0653 947s > plotTracks(fit4) 947s Warning message: 947s In plotTracks.CBS(fit4) : 947s Setting default 'Clim' assuming the signal type is ‘ratio’ because signalType(fit4) is unknown (‘NA’). Use signalType(fit4) <- ‘ratio’ to avoid this warning. 947s Segmenting by CBS... 947s Chromosome: 1 947s > abline(v=c(knownSegments$start, knownSegments$end)/1e6, lty=3) 947s > 947s > 947s > fit5 <- segmentByCBS(dataW, knownSegments=knownSegments, undo=Inf, verbose=TRUE) 947s Segmenting by CBS...done 947s > sampleName(fit5) <- "CBS_Example_5" 947s > print(fit5) 947s sampleName chromosome start end nbrOfLoci mean 947s 1 CBS_Example_5 1 136857.7 34062461 349 0.54781248 947s 2 CBS_Example_5 1 34108009.8 38257409 0 NA 947s 3 CBS_Example_5 1 38343432.8 99932904 600 0.06959745 947s > plotTracks(fit5) 947s Warning message: 947s In plotTracks.CBS(fit5) : 947s Setting default 'Clim' assuming the signal type is ‘ratio’ because signalType(fit5) is unknown (‘NA’). Use signalType(fit5) <- ‘ratio’ to avoid this warning. 947s Segmenting by CBS... 947s Chromosome: 1 947s > abline(v=c(knownSegments$start, knownSegments$end)/1e6, lty=3) 947s > stopifnot(nbrOfSegments(fit5) == nrow(knownSegments)) 947s > 947s > 947s > # One can also force a separator between two segments by setting 947s > # 'start' and 'end' to NAs ('chromosome' has to be given) 947s > knownSegments <- data.frame( 947s + chromosome=c( 1, 1, 1), 947s + start =x[c( 1, NA, 401)], 947s + end =x[c(349, NA, J)] 947s + ) 947s > fit6 <- segmentByCBS(dataW, knownSegments=knownSegments, verbose=TRUE) 947s > sampleName(fit6) <- "CBS_Example_6" 947s > print(fit6) 947s sampleName chromosome start end nbrOfLoci mean 947s 1 CBS_Example_6 1 136857.7 19138391 199 -0.0041 947s 2 CBS_Example_6 1 19138391.4 28682180 101 0.8987 947s 3 CBS_Example_6 1 28682180.1 34062461 49 -0.0552 947s 4 NA NA NA NA NA 947s 5 CBS_Example_6 1 38343432.8 64690253 249 0.0298 947s 6 CBS_Example_6 1 64690253.3 80738828 151 -1.0215 947s 7 CBS_Example_6 1 80738828.3 99932904 200 0.0653 947s > plotTracks(fit6) 947s Segmenting by CBS...done 947s Warning message: 947s In plotTracks.CBS(fit6) : 947s Setting default 'Clim' assuming the signal type is ‘ratio’ because signalType(fit6) is unknown (‘NA’). Use signalType(fit6) <- ‘ratio’ to avoid this warning. 947s > abline(v=c(knownSegments$start, knownSegments$end)/1e6, lty=3) 947s > 947s > 947s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 947s > # Multi-chromosome segmentation 947s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 947s > data2 <- data 947s > data2$chromosome <- 2L 947s > data <- rbind(data, data2) 947s > dataW <- cbind(data, w=w) 947s > 947s > par(mar=c(2,3,0.2,1)+0.1) 947s > # Segment without weights 947s > fit <- segmentByCBS(data) 947s > sampleName(fit) <- "CBS_Example" 947s > print(fit) 947s sampleName chromosome start end nbrOfLoci mean 947s 1 CBS_Example 1 136857.7 19138391 199 0.2712 947s 2 CBS_Example 1 19138391.4 28682180 101 1.2168 947s 3 CBS_Example 1 28682180.1 64690253 298 0.3027 947s 4 CBS_Example 1 64690253.3 80738828 151 -0.7101 947s 5 CBS_Example 1 80738828.3 99932904 200 0.3655 947s 6 NA NA NA NA NA 947s 7 CBS_Example 2 136857.7 19138391 199 0.2712 947s 8 CBS_Example 2 19138391.4 28682180 101 1.2168 947s 9 CBS_Example 2 28682180.1 64690253 298 0.3027 947s 10 CBS_Example 2 64690253.3 80738828 151 -0.7101 947s 11 CBS_Example 2 80738828.3 99932904 200 0.3655 947s > plotTracks(fit, Clim=c(-3,3)) 947s > 947s > # Segment with weights 947s > fitW <- segmentByCBS(dataW) 948s > sampleName(fitW) <- "CBS_Example (weighted)" 948s > print(fitW) 948s sampleName chromosome start end nbrOfLoci mean 948s 1 CBS_Example (weighted) 1 136857.7 19138391 199 -0.0041 948s 2 CBS_Example (weighted) 1 19138391.4 28682180 101 0.8987 948s 3 CBS_Example (weighted) 1 28682180.1 64690253 298 0.0159 948s 4 CBS_Example (weighted) 1 64690253.3 80738828 151 -1.0215 948s 5 CBS_Example (weighted) 1 80738828.3 99932904 200 0.0653 948s 6 NA NA NA NA NA 948s 7 CBS_Example (weighted) 2 136857.7 19138391 199 -0.0041 948s 8 CBS_Example (weighted) 2 19138391.4 28682180 101 0.8987 948s 9 CBS_Example (weighted) 2 28682180.1 64690253 298 0.0159 948s 10 CBS_Example (weighted) 2 64690253.3 80738828 151 -1.0215 948s 11 CBS_Example (weighted) 2 80738828.3 99932904 200 0.0653 948s > drawLevels(fitW, col="red") 948s NULL 948s > 948s > 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)) 948s > 948s > ## Assert that weighted segment means are less biased 948s > dmean <- getSegments(fit)$mean - getSegments(fitW)$mean 948s > cat("Segment mean differences:\n") 948s Segment mean differences: 948s > print(dmean) 948s [1] 0.2753 0.3181 0.2868 0.3114 0.3002 NA 0.2753 0.3181 0.2868 0.3114 948s [11] 0.3002 948s > stopifnot(all(dmean > 0, na.rm=TRUE)) 948s > 948s Start: segmentByCBS.R 948s 948s R version 4.5.2 (2025-10-31) -- "[Not] Part in a Rumble" 948s Copyright (C) 2025 The R Foundation for Statistical Computing 948s Platform: powerpc64le-unknown-linux-gnu 948s 948s R is free software and comes with ABSOLUTELY NO WARRANTY. 948s You are welcome to redistribute it under certain conditions. 948s Type 'license()' or 'licence()' for distribution details. 948s 948s R is a collaborative project with many contributors. 948s Type 'contributors()' for more information and 948s 'citation()' on how to cite R or R packages in publications. 948s 948s Type 'demo()' for some demos, 'help()' for on-line help, or 948s 'help.start()' for an HTML browser interface to help. 948s Type 'q()' to quit R. 948s 948s > ########################################################### 948s > # This tests: 948s > # - segmentByCBS(...) 948s > # - segmentByCBS(..., knownSegments) 948s > # - tileChromosomes() 948s > # - plotTracks() 948s > ########################################################### 948s > library("PSCBS") 948s PSCBS v0.68.0 (2025-04-18 19:40:02 UTC) successfully loaded. See ?PSCBS for help. 948s > subplots <- R.utils::subplots 948s > 948s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 948s > # Simulating copy-number data 948s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 948s > set.seed(0xBEEF) 948s > 948s > # Number of loci 948s > J <- 1000 948s > 948s > mu <- double(J) 948s > mu[200:300] <- mu[200:300] + 1 948s > mu[350:400] <- NA # centromere 948s > mu[650:800] <- mu[650:800] - 1 948s > eps <- rnorm(J, sd=1/2) 948s > y <- mu + eps 948s > x <- sort(runif(length(y), max=length(y))) * 1e5 948s > w <- runif(J) 948s > w[650:800] <- 0.001 948s > 948s > 948s > subplots(8, ncol=1L) 948s > par(mar=c(1.7,1,0.2,1)+0.1) 948s > 948s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 948s > # Segmentation 948s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 948s > fit <- segmentByCBS(y, x=x) 948s > sampleName(fit) <- "CBS_Example" 948s > print(fit) 948s sampleName chromosome start end nbrOfLoci mean 948s 1 CBS_Example 0 55167.82 20774251 201 0.0164 948s 2 CBS_Example 0 20774250.85 29320105 99 1.0474 948s 3 CBS_Example 0 29320104.86 65874675 298 -0.0203 948s 4 CBS_Example 0 65874675.06 81348129 151 -1.0813 948s 5 CBS_Example 0 81348129.20 99910827 200 -0.0612 948s > plotTracks(fit) 948s Warning message: 948s In plotTracks.CBS(fit) : 948s Setting default 'Clim' assuming the signal type is ‘ratio’ because signalType(fit) is unknown (‘NA’). Use signalType(fit) <- ‘ratio’ to avoid this warning. 948s > 948s > 948s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 948s > # Segmentation with some known change points 948s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 948s > knownSegments <- data.frame( 948s + chromosome=c( 0, 0), 948s + start =x[c( 1, 401)], 948s + end =x[c(349, J)] 948s + ) 948s > fit2 <- segmentByCBS(y, x=x, knownSegments=knownSegments, verbose=TRUE) 948s Segmenting by CBS... 948s Chromosome: 0 949s > sampleName(fit2) <- "CBS_Example_2" 949s > print(fit2) 949s sampleName chromosome start end nbrOfLoci mean 949s 1 CBS_Example_2 0 55167.82 20774251 201 0.0164 949s 2 CBS_Example_2 0 20774250.85 29320105 99 1.0474 949s 3 CBS_Example_2 0 29320104.86 34142178 49 -0.0193 949s 4 CBS_Example_2 0 41080532.92 65874675 249 -0.0205 949s 5 CBS_Example_2 0 65874675.06 81348129 151 -1.0813 949s 6 CBS_Example_2 0 81348129.20 99910827 200 -0.0612 949s > plotTracks(fit2) 949s Segmenting by CBS...done 949s Warning message: 949s In plotTracks.CBS(fit2) : 949s Setting default 'Clim' assuming the signal type is ‘ratio’ because signalType(fit2) is unknown (‘NA’). Use signalType(fit2) <- ‘ratio’ to avoid this warning. 949s > abline(v=c(knownSegments$start, knownSegments$end)/1e6, lty=3) 949s > 949s > 949s > # Chromosome boundaries can be specified as -Inf and +Inf 949s > knownSegments <- data.frame( 949s + chromosome=c( 0, 0), 949s + start =c( -Inf, x[401]), 949s + end =c(x[349], +Inf) 949s + ) 949s > fit2b <- segmentByCBS(y, x=x, knownSegments=knownSegments, verbose=TRUE) 949s Segmenting by CBS... 949s Chromosome: 0 949s > sampleName(fit2b) <- "CBS_Example_2b" 949s Segmenting by CBS...done 949s > print(fit2b) 949s sampleName chromosome start end nbrOfLoci mean 949s 1 CBS_Example_2b 0 55167.82 20774251 201 0.0164 949s 2 CBS_Example_2b 0 20774250.85 29320105 99 1.0474 949s 3 CBS_Example_2b 0 29320104.86 34142178 49 -0.0193 949s 4 CBS_Example_2b 0 41080532.92 65874675 249 -0.0205 949s 5 CBS_Example_2b 0 65874675.06 81348129 151 -1.0813 949s 6 CBS_Example_2b 0 81348129.20 99910827 200 -0.0612 949s > plotTracks(fit2b) 949s Warning message: 949s In plotTracks.CBS(fit2b) : 949s Setting default 'Clim' assuming the signal type is ‘ratio’ because signalType(fit2b) is unknown (‘NA’). Use signalType(fit2b) <- ‘ratio’ to avoid this warning. 949s > abline(v=c(knownSegments$start, knownSegments$end)/1e6, lty=3) 949s > 949s > 949s > # As a proof of concept, it is possible to segment just the centromere, 949s > # which contains no data. All statistics will be NAs. 949s > knownSegments <- data.frame( 949s + chromosome=c( 0), 949s + start =x[c(350)], 949s + end =x[c(400)] 949s + ) 949s > fit3 <- segmentByCBS(y, x=x, knownSegments=knownSegments, verbose=TRUE) 949s Segmenting by CBS... 949s Chromosome: 0 949s Segmenting by CBS...done 949s > sampleName(fit3) <- "CBS_Example_3" 949s > print(fit3) 949s sampleName chromosome start end nbrOfLoci mean 949s 1 CBS_Example_3 0 34194740 41044125 0 NA 949s > plotTracks(fit3, Clim=c(0,5), xlim=c(0,100)) 949s > abline(v=c(knownSegments$start, knownSegments$end)/1e6, lty=3) 949s > 949s > 949s > 949s > # If one specify the (empty) centromere as a segment, then its 949s > # estimated statistics will be NAs, which becomes a natural 949s > # separator between the two "independent" arms. 949s > knownSegments <- data.frame( 949s + chromosome=c( 0, 0, 0), 949s + start =x[c( 1, 350, 401)], 949s + end =x[c(349, 400, J)] 949s + ) 949s > fit4 <- segmentByCBS(y, x=x, knownSegments=knownSegments, verbose=TRUE) 949s Segmenting by CBS... 949s Chromosome: 0 949s > sampleName(fit4) <- "CBS_Example_4" 949s > print(fit4) 949s Segmenting by CBS...done 949s sampleName chromosome start end nbrOfLoci mean 949s 1 CBS_Example_4 0 55167.82 20774251 201 0.0164 949s 2 CBS_Example_4 0 20774250.85 29320105 99 1.0474 949s 3 CBS_Example_4 0 29320104.86 34142178 49 -0.0193 949s 4 CBS_Example_4 0 34194739.81 41044125 0 NA 949s 5 CBS_Example_4 0 41080532.92 65874675 249 -0.0205 949s 6 CBS_Example_4 0 65874675.06 81348129 151 -1.0813 949s 7 CBS_Example_4 0 81348129.20 99910827 200 -0.0612 949s > plotTracks(fit4) 949s > abline(v=c(knownSegments$start, knownSegments$end)/1e6, lty=3) 949s > 949s > 949s > 949s > fit5 <- segmentByCBS(y, x=x, knownSegments=knownSegments, undo=Inf, verbose=TRUE) 949s Warning message: 949s In plotTracks.CBS(fit4) : 949s Setting default 'Clim' assuming the signal type is ‘ratio’ because signalType(fit4) is unknown (‘NA’). Use signalType(fit4) <- ‘ratio’ to avoid this warning. 949s Segmenting by CBS... 949s Chromosome: 0 950s > sampleName(fit5) <- "CBS_Example_5" 950s > print(fit5) 950s Segmenting by CBS...done 950s sampleName chromosome start end nbrOfLoci mean 950s 1 CBS_Example_5 0 55167.82 34142178 349 0.3038785 950s 2 CBS_Example_5 0 34194739.81 41044125 0 NA 950s 3 CBS_Example_5 0 41080532.92 99910827 600 -0.3010285 950s > plotTracks(fit5) 950s Warning message: 950s In plotTracks.CBS(fit5) : 950s Setting default 'Clim' assuming the signal type is ‘ratio’ because signalType(fit5) is unknown (‘NA’). Use signalType(fit5) <- ‘ratio’ to avoid this warning. 950s > abline(v=c(knownSegments$start, knownSegments$end)/1e6, lty=3) 950s > stopifnot(nbrOfSegments(fit5) == nrow(knownSegments)) 950s > 950s > 950s > # One can also force a separator between two segments by setting 950s > # 'start' and 'end' to NAs ('chromosome' has to be given) 950s > knownSegments <- data.frame( 950s + chromosome=c( 0, 0, 0), 950s + start =x[c( 1, NA, 401)], 950s + end =x[c(349, NA, J)] 950s + ) 950s > fit6 <- segmentByCBS(y, x=x, knownSegments=knownSegments, verbose=TRUE) 950s Segmenting by CBS... 950s Chromosome: 0 950s > sampleName(fit6) <- "CBS_Example_6" 950s Segmenting by CBS...done 950s > print(fit6) 950s sampleName chromosome start end nbrOfLoci mean 950s 1 CBS_Example_6 0 55167.82 20774251 201 0.0164 950s 2 CBS_Example_6 0 20774250.85 29320105 99 1.0474 950s 3 CBS_Example_6 0 29320104.86 34142178 49 -0.0193 950s 4 NA NA NA NA NA 950s 5 CBS_Example_6 0 41080532.92 65874675 249 -0.0205 950s 6 CBS_Example_6 0 65874675.06 81348129 151 -1.0813 950s 7 CBS_Example_6 0 81348129.20 99910827 200 -0.0612 950s > plotTracks(fit6) 950s Warning message: 950s In plotTracks.CBS(fit6) : 950s Setting default 'Clim' assuming the signal type is ‘ratio’ because signalType(fit6) is unknown (‘NA’). Use signalType(fit6) <- ‘ratio’ to avoid this warning. 950s > abline(v=c(knownSegments$start, knownSegments$end)/1e6, lty=3) 950s > 950s > 950s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 950s > # Segment multiple chromosomes 950s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 950s > # Simulate multiple chromosomes 950s > fit1 <- renameChromosomes(fit, from=0, to=1) 950s > fit2 <- renameChromosomes(fit, from=0, to=2) 950s > fitM <- c(fit1, fit2) 950s > fitM <- segmentByCBS(fitM) 950s > sampleName(fitM) <- "CBS_Example_M" 950s > print(fitM) 950s sampleName chromosome start end nbrOfLoci mean 950s 1 CBS_Example_M 1 55167.82 20774251 201 0.0164 950s 2 CBS_Example_M 1 20774250.85 29320105 99 1.0474 950s 3 CBS_Example_M 1 29320104.86 65874675 298 -0.0203 950s 4 CBS_Example_M 1 65874675.06 81348129 151 -1.0813 950s 5 CBS_Example_M 1 81348129.20 99910827 200 -0.0612 950s 6 NA NA NA NA NA 950s 7 CBS_Example_M 2 55167.82 20774251 201 0.0164 950s 8 CBS_Example_M 2 20774250.85 29320105 99 1.0474 950s 9 CBS_Example_M 2 29320104.86 65874675 298 -0.0203 950s 10 CBS_Example_M 2 65874675.06 81348129 151 -1.0813 950s 11 CBS_Example_M 2 81348129.20 99910827 200 -0.0612 950s > plotTracks(fitM, Clim=c(-3,3)) 950s > 950s > 950s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 950s > # Tiling multiple chromosomes 950s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 950s > # Tile chromosomes 950s > fitT <- tileChromosomes(fitM) 950s > fitTb <- tileChromosomes(fitT) 950s > stopifnot(identical(fitTb, fitT)) 950s > 950s > 950s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 950s > # Write segmentation to file 950s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 950s > pathT <- tempdir() 950s > 950s > ## Tab-delimited file 950s > pathname <- writeSegments(fitM, path=pathT) 950s Warning message: 950s In write.table(file = pathnameT, data, append = TRUE, quote = FALSE, : 950s appending column names to file 950s > print(pathname) 950s [1] "/tmp/RtmpNHt7KZ/CBS_Example_M.tsv" 950s > 950s > ## WIG file 950s > pathname <- writeWIG(fitM, path=pathT) 950s > print(pathname) 950s [1] "/tmp/RtmpNHt7KZ/CBS_Example_M.wig" 950s > 950s > unlink(pathT, recursive=TRUE) 950s > 950s Start: segmentByNonPairedPSCBS,medianDH.R 950s 950s R version 4.5.2 (2025-10-31) -- "[Not] Part in a Rumble" 950s Copyright (C) 2025 The R Foundation for Statistical Computing 950s Platform: powerpc64le-unknown-linux-gnu 950s 950s R is free software and comes with ABSOLUTELY NO WARRANTY. 950s You are welcome to redistribute it under certain conditions. 950s Type 'license()' or 'licence()' for distribution details. 950s 950s R is a collaborative project with many contributors. 950s Type 'contributors()' for more information and 950s 'citation()' on how to cite R or R packages in publications. 950s 950s Type 'demo()' for some demos, 'help()' for on-line help, or 950s 'help.start()' for an HTML browser interface to help. 950s Type 'q()' to quit R. 950s 951s > library("PSCBS") 951s PSCBS v0.68.0 (2025-04-18 19:40:02 UTC) successfully loaded. See ?PSCBS for help. 951s > 951s > 951s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 951s > # Load SNP microarray data 951s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 951s > data <- PSCBS::exampleData("paired.chr01") 951s > str(data) 951s 'data.frame': 73346 obs. of 6 variables: 951s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 951s $ x : int 1145994 2224111 2319424 2543484 2926730 2941694 3084986 3155127 3292731 3695086 ... 951s $ CT : num 1.625 1.071 1.406 1.18 0.856 ... 951s $ betaT : num 0.757 0.771 0.834 0.778 0.229 ... 951s $ CN : num 2.36 2.13 2.59 1.93 1.71 ... 951s $ betaN : num 0.827 0.875 0.887 0.884 0.103 ... 951s > 951s > # Non-paired / tumor-only data 951s > data <- data[,c("chromosome", "x", "CT", "betaT")] 951s > str(data) 951s 'data.frame': 73346 obs. of 4 variables: 951s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 951s $ x : int 1145994 2224111 2319424 2543484 2926730 2941694 3084986 3155127 3292731 3695086 ... 951s $ CT : num 1.625 1.071 1.406 1.18 0.856 ... 951s $ betaT : num 0.757 0.771 0.834 0.778 0.229 ... 951s > 951s > 951s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 951s > # Paired PSCBS segmentation 951s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 951s > # Drop single-locus outliers 951s > dataS <- dropSegmentationOutliers(data) 951s > 951s > # Speed up example by segmenting fewer loci 951s > dataS <- dataS[seq(from=1, to=nrow(data), by=20),] 951s > 951s > # Fake a second chromosome 951s > dataT <- dataS 951s > dataT$chromosome <- 2L 951s > dataS <- rbind(dataS, dataT) 951s > rm(dataT) 951s > str(dataS) 951s 'data.frame': 7336 obs. of 4 variables: 951s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 951s $ x : int 1145994 4276892 5034491 6266412 8418532 11211748 13928296 14370144 15014887 16589707 ... 951s $ CT : num 1.63 1.16 1.35 1.39 1.55 ... 951s $ betaT : num 0.7574 0.0576 0.8391 0.7917 0.8141 ... 951s > 951s > # Non-Paired PSCBS segmentation 951s > fit <- segmentByNonPairedPSCBS(dataS, avgDH="median", seed=0xBEEF, verbose=-10) 951s Segmenting non-paired tumor signals using Non-paired PSCBS... 951s Number of loci: 7336 951s Number of SNPs: 7336 951s Calling "genotypes" from tumor allele B fractions... 951s num [1:7336] 0.7574 0.0576 0.8391 0.7917 0.8141 ... 951s Upper quantile: 0.475631667925522 951s Symmetric lower quantile: 0.290517384533512 951s (tauA, tauB) estimates: (%g,%g)0.2094826154664880.790517384533512 951s Homozygous treshholds: 951s [1] 0.2094826 0.7905174 951s Inferred germline genotypes (via tumor): 951s num [1:7336] 0.5 0 1 1 1 0 0 0 0.5 1 ... 951s muNx 951s 0 0.5 1 951s 2230 2910 2196 951s Calling "genotypes" from tumor allele B fractions...done 951s Segmenting non-paired tumor signals using Non-paired PSCBS...done 951s Segment using Paired PSCBS... 951s Segmenting paired tumor-normal signals using Paired PSCBS... 951s Setup up data... 951s 'data.frame': 7336 obs. of 6 variables: 951s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 951s $ x : num 1145994 4276892 5034491 6266412 8418532 ... 951s $ CT : num 1.63 1.16 1.35 1.39 1.55 ... 951s $ betaT : num 0.7574 0.0576 0.8391 0.7917 0.8141 ... 951s $ betaTN : num 0.7574 0.0576 0.8391 0.7917 0.8141 ... 951s $ muN : num 0.5 0 1 1 1 0 0 0 0.5 1 ... 951s Setup up data...done 951s Dropping loci for which TCNs are missing... 951s Number of loci dropped: 12 951s Dropping loci for which TCNs are missing...done 951s Ordering data along genome... 951s 'data.frame': 7324 obs. of 6 variables: 951s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 951s $ x : num 554484 1031563 1087198 1145994 1176365 ... 951s $ CT : num 1.88 1.64 1.77 1.63 1.59 ... 951s $ betaT : num 0.0646 0.6078 0.401 0.7574 0.645 ... 951s $ betaTN : num 0.0646 0.6078 0.401 0.7574 0.645 ... 951s $ muN : num 0 0.5 0.5 0.5 0.5 0.5 1 0.5 0.5 0.5 ... 951s Ordering data along genome...done 951s Segmenting multiple chromosomes... 951s Number of chromosomes: 2 951s Random seed temporarily set (seed=c(48879), kind="L'Ecuyer-CMRG") 951s Produced 2 seeds from this stream for future usage 951s Chromosome #1 ('Chr01') of 2... 951s 'data.frame': 3662 obs. of 7 variables: 951s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 951s $ x : num 554484 1031563 1087198 1145994 1176365 ... 951s $ CT : num 1.88 1.64 1.77 1.63 1.59 ... 951s $ betaT : num 0.0646 0.6078 0.401 0.7574 0.645 ... 951s $ betaTN : num 0.0646 0.6078 0.401 0.7574 0.645 ... 951s $ muN : num 0 0.5 0.5 0.5 0.5 0.5 1 0.5 0.5 0.5 ... 951s $ index : int 1 2 3 4 5 6 7 8 9 10 ... 951s Known segments: 951s [1] chromosome start end 951s <0 rows> (or 0-length row.names) 951s Segmenting paired tumor-normal signals using Paired PSCBS... 951s Setup up data... 951s 'data.frame': 3662 obs. of 6 variables: 951s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 951s $ x : num 554484 1031563 1087198 1145994 1176365 ... 951s $ CT : num 1.88 1.64 1.77 1.63 1.59 ... 951s $ betaT : num 0.0646 0.6078 0.401 0.7574 0.645 ... 951s $ betaTN : num 0.0646 0.6078 0.401 0.7574 0.645 ... 951s $ muN : num 0 0.5 0.5 0.5 0.5 0.5 1 0.5 0.5 0.5 ... 951s Setup up data...done 951s Ordering data along genome... 951s 'data.frame': 3662 obs. of 6 variables: 951s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 951s $ x : num 554484 1031563 1087198 1145994 1176365 ... 951s $ CT : num 1.88 1.64 1.77 1.63 1.59 ... 951s $ betaT : num 0.0646 0.6078 0.401 0.7574 0.645 ... 951s $ betaTN : num 0.0646 0.6078 0.401 0.7574 0.645 ... 951s $ muN : num 0 0.5 0.5 0.5 0.5 0.5 1 0.5 0.5 0.5 ... 951s Ordering data along genome...done 951s Keeping only current chromosome for 'knownSegments'... 951s Chromosome: 1 951s Known segments for this chromosome: 951s [1] chromosome start end 951s <0 rows> (or 0-length row.names) 951s Keeping only current chromosome for 'knownSegments'...done 951s alphaTCN: 0.009 951s alphaDH: 0.001 951s Number of loci: 3662 951s Calculating DHs... 951s Number of SNPs: 3662 951s Number of heterozygous SNPs: 1451 (39.62%) 951s Normalized DHs: 951s num [1:3662] NA 0.216 0.198 0.515 0.29 ... 951s Calculating DHs...done 951s Random seed temporarily set (seed=c(10407, 1066287653, -51199871, 161854402, -1995183193, 1503453565, -747102133), kind="L'Ecuyer-CMRG") 951s Produced 2 seeds from this stream for future usage 951s Identification of change points by total copy numbers... 951s Segmenting by CBS... 951s Chromosome: 1 951s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 951s Segmenting by CBS...done 951s List of 4 951s $ data :'data.frame': 3662 obs. of 4 variables: 951s ..$ chromosome: int [1:3662] 1 1 1 1 1 1 1 1 1 1 ... 951s ..$ x : num [1:3662] 554484 1031563 1087198 1145994 1176365 ... 951s ..$ y : num [1:3662] 1.88 1.64 1.77 1.63 1.59 ... 951s ..$ index : int [1:3662] 1 2 3 4 5 6 7 8 9 10 ... 951s $ output :'data.frame': 3 obs. of 6 variables: 951s ..$ sampleName: chr [1:3] NA NA NA 951s ..$ chromosome: int [1:3] 1 1 1 951s ..$ start : num [1:3] 5.54e+05 1.44e+08 1.85e+08 951s ..$ end : num [1:3] 1.44e+08 1.85e+08 2.47e+08 951s ..$ nbrOfLoci : int [1:3] 1880 671 1111 951s ..$ mean : num [1:3] 1.39 2.09 2.65 951s $ segRows:'data.frame': 3 obs. of 2 variables: 951s ..$ startRow: int [1:3] 1 1881 2552 951s ..$ endRow : int [1:3] 1880 2551 3662 951s $ params :List of 5 951s ..$ alpha : num 0.009 951s ..$ undo : num 0 951s ..$ joinSegments : logi TRUE 951s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 951s .. ..$ chromosome: int 1 951s .. ..$ start : num -Inf 951s .. ..$ end : num Inf 951s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 951s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 951s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.077 0 0.077 0 0 951s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 951s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 951s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 951s Identification of change points by total copy numbers...done 951s Restructure TCN segmentation results... 951s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean 951s 1 1 554484 143663981 1880 1.3916 951s 2 1 143663981 185240536 671 2.0925 951s 3 1 185240536 246679946 1111 2.6545 951s Number of TCN segments: 3 951s Restructure TCN segmentation results...done 951s TCN-only segmentation... 951s Total CN segment #1 ([ 554484,1.43664e+08]) of 3... 951s Number of TCN loci in segment: 1880 951s Locus data for TCN segment: 951s 'data.frame': 1880 obs. of 8 variables: 951s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 951s $ x : num 554484 1031563 1087198 1145994 1176365 ... 951s $ CT : num 1.88 1.64 1.77 1.63 1.59 ... 951s $ betaT : num 0.0646 0.6078 0.401 0.7574 0.645 ... 951s $ betaTN : num 0.0646 0.6078 0.401 0.7574 0.645 ... 951s $ muN : num 0 0.5 0.5 0.5 0.5 0.5 1 0.5 0.5 0.5 ... 951s $ index : int 1 2 3 4 5 6 7 8 9 10 ... 951s $ rho : num NA 0.216 0.198 0.515 0.29 ... 951s Number of loci: 1880 951s Number of SNPs: 765 (40.69%) 951s Number of heterozygous SNPs: 765 (100.00%) 951s Total CN segment #1 ([ 554484,1.43664e+08]) of 3...done 951s Total CN segment #2 ([1.43664e+08,1.85241e+08]) of 3... 951s Number of TCN loci in segment: 671 951s Locus data for TCN segment: 951s 'data.frame': 671 obs. of 8 variables: 951s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 951s $ x : num 1.44e+08 1.44e+08 1.44e+08 1.44e+08 1.44e+08 ... 951s $ CT : num 2.26 2.1 2.1 1.89 1.97 ... 951s $ betaT : num 0.958 0.19 0.909 0.13 0.141 ... 951s $ betaTN : num 0.958 0.19 0.909 0.13 0.141 ... 951s $ muN : num 1 0 1 0 0 0 0 0.5 0 1 ... 951s $ index : int 1881 1882 1883 1884 1885 1886 1887 1888 1889 1890 ... 951s $ rho : num NA NA NA NA NA ... 951s Number of loci: 671 951s Number of SNPs: 272 (40.54%) 951s Number of heterozygous SNPs: 272 (100.00%) 951s Total CN segment #2 ([1.43664e+08,1.85241e+08]) of 3...done 951s Total CN segment #3 ([1.85241e+08,2.4668e+08]) of 3... 951s Number of TCN loci in segment: 1111 951s Locus data for TCN segment: 951s 'data.frame': 1111 obs. of 8 variables: 951s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 951s $ x : num 1.85e+08 1.86e+08 1.86e+08 1.86e+08 1.86e+08 ... 951s $ CT : num 2.44 3 2.32 2.76 2.48 ... 951s $ betaT : num 0.0727 0.6845 0.2327 0.8118 0.0746 ... 951s $ betaTN : num 0.0727 0.6845 0.2327 0.8118 0.0746 ... 951s $ muN : num 0 0.5 0.5 1 0 1 0 1 1 0.5 ... 951s $ index : int 2552 2553 2554 2555 2556 2557 2558 2559 2560 2561 ... 951s $ rho : num NA 0.369 0.535 NA NA ... 951s Number of loci: 1111 951s Number of SNPs: 414 (37.26%) 951s Number of heterozygous SNPs: 414 (100.00%) 951s Total CN segment #3 ([1.85241e+08,2.4668e+08]) of 3...done 951s TCN-only segmentation...done 951s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 951s 1 1 1 1 554484 143663981 1880 1.3916 765 951s 2 1 2 1 143663981 185240536 671 2.0925 272 951s 3 1 3 1 185240536 246679946 1111 2.6545 414 951s tcnNbrOfHets dhNbrOfLoci dhStart dhEnd dhMean 951s 1 765 765 554484 143663981 0.3979122 951s 2 272 272 143663981 185240536 0.2306116 951s 3 414 414 185240536 246679946 0.2798120 951s Calculating (C1,C2) per segment... 951s Calculating (C1,C2) per segment...done 951s Number of segments: 3 951s Segmenting paired tumor-normal signals using Paired PSCBS...done 951s Updating mean level using different estimator... 951s TCN estimator: mean 951s DH estimator: median 951s Updating mean level using different estimator...done 951s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 951s 1 1 1 1 554484 143663981 1880 1.391608 765 951s 2 1 2 1 143663981 185240536 671 2.092452 272 951s 3 1 3 1 185240536 246679946 1111 2.654512 414 951s tcnNbrOfHets dhNbrOfLoci dhStart dhEnd dhMean c1Mean c2Mean 951s 1 765 765 554484 143663981 0.4206323 0.4031263 0.9884817 951s 2 272 272 143663981 185240536 0.1762428 0.8618360 1.2306156 951s 3 414 414 185240536 246679946 0.2697420 0.9692395 1.6852728 951s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 951s 1 1 1 1 554484 143663981 1880 1.391608 765 951s 2 1 2 1 143663981 185240536 671 2.092452 272 951s 3 1 3 1 185240536 246679946 1111 2.654512 414 951s tcnNbrOfHets dhNbrOfLoci dhStart dhEnd dhMean c1Mean c2Mean 951s 1 765 765 554484 143663981 0.4206323 0.4031263 0.9884817 951s 2 272 272 143663981 185240536 0.1762428 0.8618360 1.2306156 951s 3 414 414 185240536 246679946 0.2697420 0.9692395 1.6852728 951s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 951s 1 1 1 1 554484 143663981 1880 1.391608 765 951s 2 1 2 1 143663981 185240536 671 2.092452 272 951s 3 1 3 1 185240536 246679946 1111 2.654512 414 951s tcnNbrOfHets dhNbrOfLoci dhStart dhEnd dhMean c1Mean c2Mean 951s 1 765 765 554484 143663981 0.4206323 0.4031263 0.9884817 951s 2 272 272 143663981 185240536 0.1762428 0.8618360 1.2306156 951s 3 414 414 185240536 246679946 0.2697420 0.9692395 1.6852728 951s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 951s 1 1 1 1 554484 143663981 1880 1.391608 765 951s 2 1 2 1 143663981 185240536 671 2.092452 272 951s 3 1 3 1 185240536 246679946 1111 2.654512 414 951s tcnNbrOfHets dhNbrOfLoci dhStart dhEnd dhMean c1Mean c2Mean 951s 1 765 765 554484 143663981 0.4206323 0.4031263 0.9884817 951s 2 272 272 143663981 185240536 0.1762428 0.8618360 1.2306156 951s 3 414 414 185240536 246679946 0.2697420 0.9692395 1.6852728 951s Chromosome #1 ('Chr01') of 2...done 951s Chromosome #2 ('Chr02') of 2... 951s 'data.frame': 3662 obs. of 7 variables: 951s $ chromosome: int 2 2 2 2 2 2 2 2 2 2 ... 951s $ x : num 554484 1031563 1087198 1145994 1176365 ... 951s $ CT : num 1.88 1.64 1.77 1.63 1.59 ... 951s $ betaT : num 0.0646 0.6078 0.401 0.7574 0.645 ... 951s $ betaTN : num 0.0646 0.6078 0.401 0.7574 0.645 ... 951s $ muN : num 0 0.5 0.5 0.5 0.5 0.5 1 0.5 0.5 0.5 ... 951s $ index : int 3663 3664 3665 3666 3667 3668 3669 3670 3671 3672 ... 951s Known segments: 951s [1] chromosome start end 951s <0 rows> (or 0-length row.names) 951s Segmenting paired tumor-normal signals using Paired PSCBS... 951s Setup up data... 951s 'data.frame': 3662 obs. of 6 variables: 951s $ chromosome: int 2 2 2 2 2 2 2 2 2 2 ... 951s $ x : num 554484 1031563 1087198 1145994 1176365 ... 951s $ CT : num 1.88 1.64 1.77 1.63 1.59 ... 951s $ betaT : num 0.0646 0.6078 0.401 0.7574 0.645 ... 951s $ betaTN : num 0.0646 0.6078 0.401 0.7574 0.645 ... 951s $ muN : num 0 0.5 0.5 0.5 0.5 0.5 1 0.5 0.5 0.5 ... 951s Setup up data...done 951s Ordering data along genome... 951s 'data.frame': 3662 obs. of 6 variables: 951s $ chromosome: int 2 2 2 2 2 2 2 2 2 2 ... 951s $ x : num 554484 1031563 1087198 1145994 1176365 ... 951s $ CT : num 1.88 1.64 1.77 1.63 1.59 ... 951s $ betaT : num 0.0646 0.6078 0.401 0.7574 0.645 ... 951s $ betaTN : num 0.0646 0.6078 0.401 0.7574 0.645 ... 951s $ muN : num 0 0.5 0.5 0.5 0.5 0.5 1 0.5 0.5 0.5 ... 951s Ordering data along genome...done 951s Keeping only current chromosome for 'knownSegments'... 951s Chromosome: 2 951s Known segments for this chromosome: 951s [1] chromosome start end 951s <0 rows> (or 0-length row.names) 951s Keeping only current chromosome for 'knownSegments'...done 951s alphaTCN: 0.009 951s alphaDH: 0.001 951s Number of loci: 3662 951s Calculating DHs... 951s Number of SNPs: 3662 951s Number of heterozygous SNPs: 1451 (39.62%) 951s Normalized DHs: 951s num [1:3662] NA 0.216 0.198 0.515 0.29 ... 951s Calculating DHs...done 951s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 951s Produced 2 seeds from this stream for future usage 951s Identification of change points by total copy numbers... 951s Segmenting by CBS... 951s Chromosome: 2 951s Random seed temporarily set (seed=c(10407, -821273412, -52578226, 1415511586, 721384351, -665928286, 1316562960), kind="L'Ecuyer-CMRG") 952s Segmenting by CBS...done 952s List of 4 952s $ data :'data.frame': 3662 obs. of 4 variables: 952s ..$ chromosome: int [1:3662] 2 2 2 2 2 2 2 2 2 2 ... 952s ..$ x : num [1:3662] 554484 1031563 1087198 1145994 1176365 ... 952s ..$ y : num [1:3662] 1.88 1.64 1.77 1.63 1.59 ... 952s ..$ index : int [1:3662] 1 2 3 4 5 6 7 8 9 10 ... 952s $ output :'data.frame': 3 obs. of 6 variables: 952s ..$ sampleName: chr [1:3] NA NA NA 952s ..$ chromosome: int [1:3] 2 2 2 952s ..$ start : num [1:3] 5.54e+05 1.44e+08 1.85e+08 952s ..$ end : num [1:3] 1.44e+08 1.85e+08 2.47e+08 952s ..$ nbrOfLoci : int [1:3] 1880 671 1111 952s ..$ mean : num [1:3] 1.39 2.09 2.65 952s $ segRows:'data.frame': 3 obs. of 2 variables: 952s ..$ startRow: int [1:3] 1 1881 2552 952s ..$ endRow : int [1:3] 1880 2551 3662 952s $ params :List of 5 952s ..$ alpha : num 0.009 952s ..$ undo : num 0 952s ..$ joinSegments : logi TRUE 952s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 952s .. ..$ chromosome: int 2 952s .. ..$ start : num -Inf 952s .. ..$ end : num Inf 952s ..$ seed : int [1:7] 10407 -821273412 -52578226 1415511586 721384351 -665928286 1316562960 952s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 952s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.076 0 0.076 0 0 952s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 952s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 952s - attr(*, "randomSeed")= int [1:7] 10407 -821273412 -52578226 1415511586 721384351 -665928286 1316562960 952s Identification of change points by total copy numbers...done 952s Restructure TCN segmentation results... 952s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean 952s 1 2 554484 143663981 1880 1.3916 952s 2 2 143663981 185240536 671 2.0925 952s 3 2 185240536 246679946 1111 2.6545 952s Number of TCN segments: 3 952s Restructure TCN segmentation results...done 952s TCN-only segmentation... 952s Total CN segment #1 ([ 554484,1.43664e+08]) of 3... 952s Number of TCN loci in segment: 1880 952s Locus data for TCN segment: 952s 'data.frame': 1880 obs. of 8 variables: 952s $ chromosome: int 2 2 2 2 2 2 2 2 2 2 ... 952s $ x : num 554484 1031563 1087198 1145994 1176365 ... 952s $ CT : num 1.88 1.64 1.77 1.63 1.59 ... 952s $ betaT : num 0.0646 0.6078 0.401 0.7574 0.645 ... 952s $ betaTN : num 0.0646 0.6078 0.401 0.7574 0.645 ... 952s $ muN : num 0 0.5 0.5 0.5 0.5 0.5 1 0.5 0.5 0.5 ... 952s $ index : int 1 2 3 4 5 6 7 8 9 10 ... 952s $ rho : num NA 0.216 0.198 0.515 0.29 ... 952s Number of loci: 1880 952s Number of SNPs: 765 (40.69%) 952s Number of heterozygous SNPs: 765 (100.00%) 952s Total CN segment #1 ([ 554484,1.43664e+08]) of 3...done 952s Total CN segment #2 ([1.43664e+08,1.85241e+08]) of 3... 952s Number of TCN loci in segment: 671 952s Locus data for TCN segment: 952s 'data.frame': 671 obs. of 8 variables: 952s $ chromosome: int 2 2 2 2 2 2 2 2 2 2 ... 952s $ x : num 1.44e+08 1.44e+08 1.44e+08 1.44e+08 1.44e+08 ... 952s $ CT : num 2.26 2.1 2.1 1.89 1.97 ... 952s $ betaT : num 0.958 0.19 0.909 0.13 0.141 ... 952s $ betaTN : num 0.958 0.19 0.909 0.13 0.141 ... 952s $ muN : num 1 0 1 0 0 0 0 0.5 0 1 ... 952s $ index : int 1881 1882 1883 1884 1885 1886 1887 1888 1889 1890 ... 952s $ rho : num NA NA NA NA NA ... 952s Number of loci: 671 952s Number of SNPs: 272 (40.54%) 952s Number of heterozygous SNPs: 272 (100.00%) 952s Total CN segment #2 ([1.43664e+08,1.85241e+08]) of 3...done 952s Total CN segment #3 ([1.85241e+08,2.4668e+08]) of 3... 952s Number of TCN loci in segment: 1111 952s Locus data for TCN segment: 952s 'data.frame': 1111 obs. of 8 variables: 952s $ chromosome: int 2 2 2 2 2 2 2 2 2 2 ... 952s $ x : num 1.85e+08 1.86e+08 1.86e+08 1.86e+08 1.86e+08 ... 952s $ CT : num 2.44 3 2.32 2.76 2.48 ... 952s $ betaT : num 0.0727 0.6845 0.2327 0.8118 0.0746 ... 952s $ betaTN : num 0.0727 0.6845 0.2327 0.8118 0.0746 ... 952s $ muN : num 0 0.5 0.5 1 0 1 0 1 1 0.5 ... 952s $ index : int 2552 2553 2554 2555 2556 2557 2558 2559 2560 2561 ... 952s $ rho : num NA 0.369 0.535 NA NA ... 952s Number of loci: 1111 952s Number of SNPs: 414 (37.26%) 952s Number of heterozygous SNPs: 414 (100.00%) 952s Total CN segment #3 ([1.85241e+08,2.4668e+08]) of 3...done 952s TCN-only segmentation...done 952s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 952s 1 2 1 1 554484 143663981 1880 1.3916 765 952s 2 2 2 1 143663981 185240536 671 2.0925 272 952s 3 2 3 1 185240536 246679946 1111 2.6545 414 952s tcnNbrOfHets dhNbrOfLoci dhStart dhEnd dhMean 952s 1 765 765 554484 143663981 0.3979122 952s 2 272 272 143663981 185240536 0.2306116 952s 3 414 414 185240536 246679946 0.2798120 952s Calculating (C1,C2) per segment... 952s Calculating (C1,C2) per segment...done 952s Number of segments: 3 952s Segmenting paired tumor-normal signals using Paired PSCBS...done 952s Updating mean level using different estimator... 952s TCN estimator: mean 952s DH estimator: median 952s Updating mean level using different estimator...done 952s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 952s 1 2 1 1 554484 143663981 1880 1.391608 765 952s 2 2 2 1 143663981 185240536 671 2.092452 272 952s 3 2 3 1 185240536 246679946 1111 2.654512 414 952s tcnNbrOfHets dhNbrOfLoci dhStart dhEnd dhMean c1Mean c2Mean 952s 1 765 765 554484 143663981 0.4206323 0.4031263 0.9884817 952s 2 272 272 143663981 185240536 0.1762428 0.8618360 1.2306156 952s 3 414 414 185240536 246679946 0.2697420 0.9692395 1.6852728 952s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 952s 1 2 1 1 554484 143663981 1880 1.391608 765 952s 2 2 2 1 143663981 185240536 671 2.092452 272 952s 3 2 3 1 185240536 246679946 1111 2.654512 414 952s tcnNbrOfHets dhNbrOfLoci dhStart dhEnd dhMean c1Mean c2Mean 952s 1 765 765 554484 143663981 0.4206323 0.4031263 0.9884817 952s 2 272 272 143663981 185240536 0.1762428 0.8618360 1.2306156 952s 3 414 414 185240536 246679946 0.2697420 0.9692395 1.6852728 952s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 952s 1 2 1 1 554484 143663981 1880 1.391608 765 952s 2 2 2 1 143663981 185240536 671 2.092452 272 952s 3 2 3 1 185240536 246679946 1111 2.654512 414 952s tcnNbrOfHets dhNbrOfLoci dhStart dhEnd dhMean c1Mean c2Mean 952s 1 765 765 554484 143663981 0.4206323 0.4031263 0.9884817 952s 2 272 272 143663981 185240536 0.1762428 0.8618360 1.2306156 952s 3 414 414 185240536 246679946 0.2697420 0.9692395 1.6852728 952s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 952s 1 2 1 1 554484 143663981 1880 1.391608 765 952s 2 2 2 1 143663981 185240536 671 2.092452 272 952s 3 2 3 1 185240536 246679946 1111 2.654512 414 952s tcnNbrOfHets dhNbrOfLoci dhStart dhEnd dhMean c1Mean c2Mean 952s 1 765 765 554484 143663981 0.4206323 0.4031263 0.9884817 952s 2 272 272 143663981 185240536 0.1762428 0.8618360 1.2306156 952s 3 414 414 185240536 246679946 0.2697420 0.9692395 1.6852728 952s Chromosome #2 ('Chr02') of 2...done 952s Merging (independently) segmented chromosome... 952s List of 5 952s $ data :Classes ‘PairedPSCNData’ and 'data.frame': 7324 obs. of 7 variables: 952s ..$ chromosome: int [1:7324] 1 1 1 1 1 1 1 1 1 1 ... 952s ..$ x : num [1:7324] 554484 1031563 1087198 1145994 1176365 ... 952s ..$ CT : num [1:7324] 1.88 1.64 1.77 1.63 1.59 ... 952s ..$ betaT : num [1:7324] 0.0646 0.6078 0.401 0.7574 0.645 ... 952s ..$ betaTN : num [1:7324] 0.0646 0.6078 0.401 0.7574 0.645 ... 952s ..$ muN : num [1:7324] 0 0.5 0.5 0.5 0.5 0.5 1 0.5 0.5 0.5 ... 952s ..$ rho : num [1:7324] NA 0.216 0.198 0.515 0.29 ... 952s $ output :Classes ‘PairedPSCNSegments’ and 'data.frame': 7 obs. of 15 variables: 952s ..$ chromosome : int [1:7] 1 1 1 NA 2 2 2 952s ..$ tcnId : int [1:7] 1 2 3 NA 1 2 3 952s ..$ dhId : int [1:7] 1 1 1 NA 1 1 1 952s ..$ tcnStart : num [1:7] 5.54e+05 1.44e+08 1.85e+08 NA 5.54e+05 ... 952s ..$ tcnEnd : num [1:7] 1.44e+08 1.85e+08 2.47e+08 NA 1.44e+08 ... 952s ..$ tcnNbrOfLoci: int [1:7] 1880 671 1111 NA 1880 671 1111 952s ..$ tcnMean : num [1:7] 1.39 2.09 2.65 NA 1.39 ... 952s ..$ tcnNbrOfSNPs: int [1:7] 765 272 414 NA 765 272 414 952s ..$ tcnNbrOfHets: int [1:7] 765 272 414 NA 765 272 414 952s ..$ dhNbrOfLoci : int [1:7] 765 272 414 NA 765 272 414 952s ..$ dhStart : num [1:7] 5.54e+05 1.44e+08 1.85e+08 NA 5.54e+05 ... 952s ..$ dhEnd : num [1:7] 1.44e+08 1.85e+08 2.47e+08 NA 1.44e+08 ... 952s ..$ dhMean : num [1:7] 0.421 0.176 0.27 NA 0.421 ... 952s ..$ c1Mean : num [1:7] 0.403 0.862 0.969 NA 0.403 ... 952s ..$ c2Mean : num [1:7] 0.988 1.231 1.685 NA 0.988 ... 952s $ tcnSegRows:'data.frame': 7 obs. of 2 variables: 952s ..$ startRow: int [1:7] 1 1881 2552 NA 3663 5543 6214 952s ..$ endRow : int [1:7] 1880 2551 3662 NA 5542 6213 7324 952s $ dhSegRows :'data.frame': 7 obs. of 2 variables: 952s ..$ startRow: int [1:7] 2 1888 2553 NA 3664 5550 6215 952s ..$ endRow : int [1:7] 1876 2548 3659 NA 5538 6210 7321 952s $ params :List of 8 952s ..$ alphaTCN : num 0.009 952s ..$ alphaDH : num 0.001 952s ..$ flavor : chr "tcn" 952s ..$ tbn : logi FALSE 952s ..$ joinSegments : logi TRUE 952s ..$ knownSegments :'data.frame': 0 obs. of 3 variables: 952s .. ..$ chromosome: int(0) 952s .. ..$ start : int(0) 952s .. ..$ end : int(0) 952s ..$ seed : int [1:7] 10407 1066287653 -51199871 161854402 -1995183193 1503453565 -747102133 952s ..$ meanEstimators:List of 2 952s .. ..$ tcn: chr "mean" 952s .. ..$ dh : chr "median" 952s - attr(*, "class")= chr [1:3] "PairedPSCBS" "PSCBS" "AbstractCBS" 952s Merging (independently) segmented chromosome...done 952s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 952s 1 1 1 1 554484 143663981 1880 1.391608 765 952s 2 1 2 1 143663981 185240536 671 2.092452 272 952s 3 1 3 1 185240536 246679946 1111 2.654512 414 952s 4 NA NA NA NA NA NA NA NA 952s 5 2 1 1 554484 143663981 1880 1.391608 765 952s 6 2 2 1 143663981 185240536 671 2.092452 272 952s tcnNbrOfHets dhNbrOfLoci dhStart dhEnd dhMean c1Mean c2Mean 952s 1 765 765 554484 143663981 0.4206323 0.4031263 0.9884817 952s 2 272 272 143663981 185240536 0.1762428 0.8618360 1.2306156 952s 3 414 414 185240536 246679946 0.2697420 0.9692395 1.6852728 952s 4 NA NA NA NA NA NA NA 952s 5 765 765 554484 143663981 0.4206323 0.4031263 0.9884817 952s 6 272 272 143663981 185240536 0.1762428 0.8618360 1.2306156 952s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 952s 2 1 2 1 143663981 185240536 671 2.092452 272 952s 3 1 3 1 185240536 246679946 1111 2.654512 414 952s 4 NA NA NA NA NA NA NA NA 952s 5 2 1 1 554484 143663981 1880 1.391608 765 952s 6 2 2 1 143663981 185240536 671 2.092452 272 952s 7 2 3 1 185240536 246679946 1111 2.654512 414 952s tcnNbrOfHets dhNbrOfLoci dhStart dhEnd dhMean c1Mean c2Mean 952s 2 272 272 143663981 185240536 0.1762428 0.8618360 1.2306156 952s 3 414 414 185240536 246679946 0.2697420 0.9692395 1.6852728 952s 4 NA NA NA NA NA NA NA 952s 5 765 765 554484 143663981 0.4206323 0.4031263 0.9884817 952s 6 272 272 143663981 185240536 0.1762428 0.8618360 1.2306156 952s 7 414 414 185240536 246679946 0.2697420 0.9692395 1.6852728 952s Segmenting multiple chromosomes...done 952s Segmenting paired tumor-normal signals using Paired PSCBS...done 952s Segment using Paired PSCBS...done 952s Coercing to Non-Paired PSCBS results... 952s Coercing to Non-Paired PSCBS results...done 952s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 952s 1 1 1 1 554484 143663981 1880 1.391608 765 952s 2 1 2 1 143663981 185240536 671 2.092452 272 952s 3 1 3 1 185240536 246679946 1111 2.654512 414 952s 4 NA NA NA NA NA NA NA NA 952s 5 2 1 1 554484 143663981 1880 1.391608 765 952s 6 2 2 1 143663981 185240536 671 2.092452 272 952s tcnNbrOfHets dhNbrOfLoci dhStart dhEnd dhMean c1Mean c2Mean 952s 1 765 765 554484 143663981 0.4206323 0.4031263 0.9884817 952s 2 272 272 143663981 185240536 0.1762428 0.8618360 1.2306156 952s 3 414 414 185240536 246679946 0.2697420 0.9692395 1.6852728 952s 4 NA NA NA NA NA NA NA 952s 5 765 765 554484 143663981 0.4206323 0.4031263 0.9884817 952s 6 272 272 143663981 185240536 0.1762428 0.8618360 1.2306156 952s > print(fit) 952s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 952s 2 1 2 1 143663981 185240536 671 2.092452 272 952s 3 1 3 1 185240536 246679946 1111 2.654512 414 952s 4 NA NA NA NA NA NA NA NA 952s 5 2 1 1 554484 143663981 1880 1.391608 765 952s 6 2 2 1 143663981 185240536 671 2.092452 272 952s 7 2 3 1 185240536 246679946 1111 2.654512 414 952s tcnNbrOfHets dhNbrOfLoci dhStart dhEnd dhMean c1Mean c2Mean 952s 2 272 272 143663981 185240536 0.1762428 0.8618360 1.2306156 952s 3 414 414 185240536 246679946 0.2697420 0.9692395 1.6852728 952s 4 NA NA NA NA NA NA NA 952s 5 765 765 554484 143663981 0.4206323 0.4031263 0.9884817 952s 6 272 272 143663981 185240536 0.1762428 0.8618360 1.2306156 952s 7 414 414 185240536 246679946 0.2697420 0.9692395 1.6852728 952s chromosome tcnId dhId start end tcnNbrOfLoci tcnMean tcnNbrOfSNPs 952s 1 1 1 1 554484 143663981 1880 1.391608 765 952s 2 1 2 1 143663981 185240536 671 2.092452 272 952s 3 1 3 1 185240536 246679946 1111 2.654512 414 952s 4 NA NA NA NA NA NA NA NA 952s 5 2 1 1 554484 143663981 1880 1.391608 765 952s 6 2 2 1 143663981 185240536 671 2.092452 272 952s 7 2 3 1 185240536 246679946 1111 2.654512 414 952s tcnNbrOfHets dhNbrOfLoci dhMean c1Mean c2Mean 952s 1 765 765 0.4206323 0.4031263 0.9884817 952s 2 272 272 0.1762428 0.8618360 1.2306156 952s 3 414 414 0.2697420 0.9692395 1.6852728 952s 4 NA NA NA NA NA 952s 5 765 765 0.4206323 0.4031263 0.9884817 952s 6 272 272 0.1762428 0.8618360 1.2306156 952s 7 414 414 0.2697420 0.9692395 1.6852728 952s > 952s > 952s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 952s > # Bootstrap segment level estimates 952s > # (used by the AB caller, which, if skipped here, 952s > # will do it automatically) 952s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 952s > fit <- bootstrapTCNandDHByRegion(fit, B=100, verbose=-10) 952s Resample (TCN,DH) signals and re-estimate summaries for segment & changepoint... 952s Already done? 952s tcn_2.5% tcn_5% tcn_95% tcn_97.5% dh_2.5% dh_5% dh_95% dh_97.5% 952s FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE 952s c1_2.5% c1_5% c1_95% c1_97.5% c2_2.5% c2_5% c2_95% c2_97.5% 952s FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE 952s Bootstrapping (TCN,DH,C1,C2) segment mean levels... 952s Identifying heterozygous & homozygous SNPs and non-polymorphic loci... 952s Number of loci: 7324 952s Number of SNPs: 2902 952s Number of non-SNPs: 4422 952s Identifying heterozygous & homozygous SNPs and non-polymorphic loci...done 952s num [1:7, 1:100, 1:4] NA NA NA NA NA NA NA NA NA NA ... 952s - attr(*, "dimnames")=List of 3 952s ..$ : NULL 952s ..$ : NULL 952s ..$ : chr [1:4] "tcn" "dh" "c1" "c2" 952s Segment #1 (chr 1, tcnId=1, dhId=1) of 7... 952s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 952s 1 1 1 1 554484 143663981 1880 1.391608 765 952s tcnNbrOfHets dhNbrOfLoci dhStart dhEnd dhMean c1Mean c2Mean 952s 1 765 765 554484 143663981 0.4206323 0.4031263 0.9884817 952s Number of TCNs: 1880 952s Number of DHs: 765 952s int [1:1880] 1 2 3 4 5 6 7 8 9 10 ... 952s int [1:7324] 1 2 3 4 5 6 7 8 9 10 ... 952s int [1:1880] 1 2 3 4 5 6 7 8 9 10 ... 952s Identify loci used to bootstrap DH means... 952s Heterozygous SNPs to resample for DH: 952s int [1:765] 2 3 4 5 6 8 9 10 11 12 ... 952s Identify loci used to bootstrap DH means...done 952s Identify loci used to bootstrap TCN means... 952s SNPs: 952s int [1:765] 2 3 4 5 6 8 9 10 11 12 ... 952s Non-polymorphic loci: 952s int [1:1115] 1 7 15 28 30 32 34 35 36 37 ... 952s Heterozygous SNPs to resample for TCN: 952s int [1:765] 2 3 4 5 6 8 9 10 11 12 ... 952s Homozygous SNPs to resample for TCN: 952s int(0) 952s Non-polymorphic loci to resample for TCN: 952s int [1:1115] 1 7 15 28 30 32 34 35 36 37 ... 952s Heterozygous SNPs with non-DH to resample for TCN: 952s int(0) 952s Loci to resample for TCN: 952s int [1:1880] 1 2 3 4 5 6 7 8 9 10 ... 952s Identify loci used to bootstrap TCN means...done 952s Number of (#hets, #homs, #nonSNPs): (765,0,1115) 952s Bootstrapping while preserving (#hets, #homs, #nonSNPs)... 952s Number of bootstrap samples: 100 952s Bootstrapping while preserving (#hets, #homs, #nonSNPs)...done 952s Segment #1 (chr 1, tcnId=1, dhId=1) of 7...done 952s Segment #2 (chr 1, tcnId=2, dhId=1) of 7... 952s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 952s 2 1 2 1 143663981 185240536 671 2.092452 272 952s tcnNbrOfHets dhNbrOfLoci dhStart dhEnd dhMean c1Mean c2Mean 952s 2 272 272 143663981 185240536 0.1762428 0.861836 1.230616 952s Number of TCNs: 671 952s Number of DHs: 272 952s int [1:671] 1881 1882 1883 1884 1885 1886 1887 1888 1889 1890 ... 952s int [1:7324] 1 2 3 4 5 6 7 8 9 10 ... 952s int [1:671] 1881 1882 1883 1884 1885 1886 1887 1888 1889 1890 ... 952s Identify loci used to bootstrap DH means... 952s Heterozygous SNPs to resample for DH: 952s int [1:272] 1888 1893 1894 1895 1896 1897 1901 1903 1907 1908 ... 952s Identify loci used to bootstrap DH means...done 952s Identify loci used to bootstrap TCN means... 952s SNPs: 952s int [1:272] 1888 1893 1894 1895 1896 1897 1901 1903 1907 1908 ... 952s Non-polymorphic loci: 952s int [1:399] 1881 1882 1883 1884 1885 1886 1887 1889 1890 1891 ... 952s Heterozygous SNPs to resample for TCN: 952s int [1:272] 1888 1893 1894 1895 1896 1897 1901 1903 1907 1908 ... 952s Homozygous SNPs to resample for TCN: 952s int(0) 952s Non-polymorphic loci to resample for TCN: 952s int [1:399] 1881 1882 1883 1884 1885 1886 1887 1889 1890 1891 ... 952s Heterozygous SNPs with non-DH to resample for TCN: 952s int(0) 952s Loci to resample for TCN: 952s int [1:671] 1881 1882 1883 1884 1885 1886 1887 1888 1889 1890 ... 952s Identify loci used to bootstrap TCN means...done 952s Number of (#hets, #homs, #nonSNPs): (272,0,399) 952s Bootstrapping while preserving (#hets, #homs, #nonSNPs)... 952s Number of bootstrap samples: 100 952s Bootstrapping while preserving (#hets, #homs, #nonSNPs)...done 952s Segment #2 (chr 1, tcnId=2, dhId=1) of 7...done 952s Segment #3 (chr 1, tcnId=3, dhId=1) of 7... 952s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 952s 3 1 3 1 185240536 246679946 1111 2.654512 414 952s tcnNbrOfHets dhNbrOfLoci dhStart dhEnd dhMean c1Mean c2Mean 952s 3 414 414 185240536 246679946 0.269742 0.9692395 1.685273 952s Number of TCNs: 1111 952s Number of DHs: 414 952s int [1:1111] 2552 2553 2554 2555 2556 2557 2558 2559 2560 2561 ... 952s int [1:7324] 1 2 3 4 5 6 7 8 9 10 ... 952s int [1:1111] 2552 2553 2554 2555 2556 2557 2558 2559 2560 2561 ... 952s Identify loci used to bootstrap DH means... 952s Heterozygous SNPs to resample for DH: 952s int [1:414] 2553 2554 2561 2562 2563 2568 2569 2572 2573 2574 ... 952s Identify loci used to bootstrap DH means...done 952s Identify loci used to bootstrap TCN means... 952s SNPs: 952s int [1:414] 2553 2554 2561 2562 2563 2568 2569 2572 2573 2574 ... 952s Non-polymorphic loci: 952s int [1:697] 2552 2555 2556 2557 2558 2559 2560 2564 2565 2566 ... 952s Heterozygous SNPs to resample for TCN: 952s int [1:414] 2553 2554 2561 2562 2563 2568 2569 2572 2573 2574 ... 952s Homozygous SNPs to resample for TCN: 952s int(0) 952s Non-polymorphic loci to resample for TCN: 952s int [1:697] 2552 2555 2556 2557 2558 2559 2560 2564 2565 2566 ... 952s Heterozygous SNPs with non-DH to resample for TCN: 952s int(0) 952s Loci to resample for TCN: 952s int [1:1111] 2552 2553 2554 2555 2556 2557 2558 2559 2560 2561 ... 952s Identify loci used to bootstrap TCN means...done 952s Number of (#hets, #homs, #nonSNPs): (414,0,697) 952s Bootstrapping while preserving (#hets, #homs, #nonSNPs)... 952s Number of bootstrap samples: 100 952s Bootstrapping while preserving (#hets, #homs, #nonSNPs)...done 952s Segment #3 (chr 1, tcnId=3, dhId=1) of 7...done 952s Segment #5 (chr 2, tcnId=1, dhId=1) of 7... 952s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 952s 5 2 1 1 554484 143663981 1880 1.391608 765 952s tcnNbrOfHets dhNbrOfLoci dhStart dhEnd dhMean c1Mean c2Mean 952s 5 765 765 554484 143663981 0.4206323 0.4031263 0.9884817 952s Number of TCNs: 1880 952s Number of DHs: 765 952s int [1:1880] 3663 3664 3665 3666 3667 3668 3669 3670 3671 3672 ... 952s int [1:7324] 1 2 3 4 5 6 7 8 9 10 ... 952s int [1:1880] 3663 3664 3665 3666 3667 3668 3669 3670 3671 3672 ... 952s Identify loci used to bootstrap DH means... 952s Heterozygous SNPs to resample for DH: 952s int [1:765] 3664 3665 3666 3667 3668 3670 3671 3672 3673 3674 ... 952s Identify loci used to bootstrap DH means...done 952s Identify loci used to bootstrap TCN means... 952s SNPs: 952s int [1:765] 3664 3665 3666 3667 3668 3670 3671 3672 3673 3674 ... 952s Non-polymorphic loci: 952s int [1:1115] 3663 3669 3677 3690 3692 3694 3696 3697 3698 3699 ... 952s Heterozygous SNPs to resample for TCN: 952s int [1:765] 3664 3665 3666 3667 3668 3670 3671 3672 3673 3674 ... 952s Homozygous SNPs to resample for TCN: 952s int(0) 952s Non-polymorphic loci to resample for TCN: 952s int [1:1115] 3663 3669 3677 3690 3692 3694 3696 3697 3698 3699 ... 952s Heterozygous SNPs with non-DH to resample for TCN: 952s int(0) 952s Loci to resample for TCN: 952s int [1:1880] 3663 3664 3665 3666 3667 3668 3669 3670 3671 3672 ... 952s Identify loci used to bootstrap TCN means...done 952s Number of (#hets, #homs, #nonSNPs): (765,0,1115) 952s Bootstrapping while preserving (#hets, #homs, #nonSNPs)... 952s Number of bootstrap samples: 100 952s Bootstrapping while preserving (#hets, #homs, #nonSNPs)...done 952s Segment #5 (chr 2, tcnId=1, dhId=1) of 7...done 952s Segment #6 (chr 2, tcnId=2, dhId=1) of 7... 952s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 952s 6 2 2 1 143663981 185240536 671 2.092452 272 952s tcnNbrOfHets dhNbrOfLoci dhStart dhEnd dhMean c1Mean c2Mean 952s 6 272 272 143663981 185240536 0.1762428 0.861836 1.230616 952s Number of TCNs: 671 952s Number of DHs: 272 952s int [1:671] 5543 5544 5545 5546 5547 5548 5549 5550 5551 5552 ... 952s int [1:7324] 1 2 3 4 5 6 7 8 9 10 ... 952s int [1:671] 5543 5544 5545 5546 5547 5548 5549 5550 5551 5552 ... 952s Identify loci used to bootstrap DH means... 952s Heterozygous SNPs to resample for DH: 952s int [1:272] 5550 5555 5556 5557 5558 5559 5563 5565 5569 5570 ... 952s Identify loci used to bootstrap DH means...done 952s Identify loci used to bootstrap TCN means... 952s SNPs: 952s int [1:272] 5550 5555 5556 5557 5558 5559 5563 5565 5569 5570 ... 952s Non-polymorphic loci: 952s int [1:399] 5543 5544 5545 5546 5547 5548 5549 5551 5552 5553 ... 952s Heterozygous SNPs to resample for TCN: 952s int [1:272] 5550 5555 5556 5557 5558 5559 5563 5565 5569 5570 ... 952s Homozygous SNPs to resample for TCN: 952s int(0) 952s Non-polymorphic loci to resample for TCN: 952s int [1:399] 5543 5544 5545 5546 5547 5548 5549 5551 5552 5553 ... 952s Heterozygous SNPs with non-DH to resample for TCN: 952s int(0) 952s Loci to resample for TCN: 952s int [1:671] 5543 5544 5545 5546 5547 5548 5549 5550 5551 5552 ... 952s Identify loci used to bootstrap TCN means...done 952s Number of (#hets, #homs, #nonSNPs): (272,0,399) 952s Bootstrapping while preserving (#hets, #homs, #nonSNPs)... 952s Number of bootstrap samples: 100 952s Bootstrapping while preserving (#hets, #homs, #nonSNPs)...done 952s Segment #6 (chr 2, tcnId=2, dhId=1) of 7...done 952s Segment #7 (chr 2, tcnId=3, dhId=1) of 7... 952s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 952s 7 2 3 1 185240536 246679946 1111 2.654512 414 952s tcnNbrOfHets dhNbrOfLoci dhStart dhEnd dhMean c1Mean c2Mean 952s 7 414 414 185240536 246679946 0.269742 0.9692395 1.685273 952s Number of TCNs: 1111 952s Number of DHs: 414 952s int [1:1111] 6214 6215 6216 6217 6218 6219 6220 6221 6222 6223 ... 952s int [1:7324] 1 2 3 4 5 6 7 8 9 10 ... 952s int [1:1111] 6214 6215 6216 6217 6218 6219 6220 6221 6222 6223 ... 952s Identify loci used to bootstrap DH means... 952s Heterozygous SNPs to resample for DH: 952s int [1:414] 6215 6216 6223 6224 6225 6230 6231 6234 6235 6236 ... 952s Identify loci used to bootstrap DH means...done 952s Identify loci used to bootstrap TCN means... 952s SNPs: 952s int [1:414] 6215 6216 6223 6224 6225 6230 6231 6234 6235 6236 ... 952s Non-polymorphic loci: 952s int [1:697] 6214 6217 6218 6219 6220 6221 6222 6226 6227 6228 ... 952s Heterozygous SNPs to resample for TCN: 952s int [1:414] 6215 6216 6223 6224 6225 6230 6231 6234 6235 6236 ... 952s Homozygous SNPs to resample for TCN: 952s int(0) 952s Non-polymorphic loci to resample for TCN: 952s int [1:697] 6214 6217 6218 6219 6220 6221 6222 6226 6227 6228 ... 952s Heterozygous SNPs with non-DH to resample for TCN: 952s int(0) 952s Loci to resample for TCN: 952s int [1:1111] 6214 6215 6216 6217 6218 6219 6220 6221 6222 6223 ... 952s Identify loci used to bootstrap TCN means...done 952s Number of (#hets, #homs, #nonSNPs): (414,0,697) 952s Bootstrapping while preserving (#hets, #homs, #nonSNPs)... 952s Number of bootstrap samples: 100 952s Bootstrapping while preserving (#hets, #homs, #nonSNPs)...done 952s Segment #7 (chr 2, tcnId=3, dhId=1) of 7...done 952s Bootstrapped segment mean levels 952s num [1:7, 1:100, 1:4] 1.4 2.09 2.64 NA 1.39 ... 952s - attr(*, "dimnames")=List of 3 952s ..$ : NULL 952s ..$ : NULL 952s ..$ : chr [1:4] "tcn" "dh" "c1" "c2" 952s Calculating (C1,C2) mean levels from (TCN,DH) mean levels... 952s num [1:7, 1:100, 1:4] 1.4 2.09 2.64 NA 1.39 ... 952s - attr(*, "dimnames")=List of 3 952s ..$ : NULL 952s ..$ : NULL 952s ..$ : chr [1:4] "tcn" "dh" "c1" "c2" 952s Calculating (C1,C2) mean levels from (TCN,DH) mean levels...done 952s Calculating polar (alpha,radius,manhattan) for change points... 952s num [1:6, 1:100, 1:2] -0.448 -0.131 NA NA -0.477 ... 952s - attr(*, "dimnames")=List of 3 952s ..$ : NULL 952s ..$ : NULL 952s ..$ : chr [1:2] "c1" "c2" 952s Bootstrapped change points 952s num [1:6, 1:100, 1:5] -2.65 -1.87 NA NA -2.72 ... 952s - attr(*, "dimnames")=List of 3 952s ..$ : NULL 952s ..$ : NULL 952s ..$ : chr [1:5] "alpha" "radius" "manhattan" "d1" ... 952s Calculating polar (alpha,radius,manhattan) for change points...done 952s Bootstrapping (TCN,DH,C1,C2) segment mean levels...done 952s Summarizing bootstrapped segment (‘tcn’, ‘dh’, ‘c1’, ‘c2’) data... 952s num [1:7, 1:4, 1:4] NA NA NA NA NA NA NA NA NA NA ... 952s - attr(*, "dimnames")=List of 3 952s ..$ : NULL 952s ..$ : chr [1:4] "2.5%" "5%" "95%" "97.5%" 952s ..$ : chr [1:4] "tcn" "dh" "c1" "c2" 952s Field #1 ('tcn') of 4... 952s Segment #1 of 7... 952s Segment #1 of 7...done 952s Segment #2 of 7... 952s Segment #2 of 7...done 952s Segment #3 of 7... 952s Segment #3 of 7...done 952s Segment #4 of 7... 952s Segment #4 of 7...done 952s Segment #5 of 7... 952s Segment #5 of 7...done 952s Segment #6 of 7... 952s Segment #6 of 7...done 952s Segment #7 of 7... 952s Segment #7 of 7...done 952s Field #1 ('tcn') of 4...done 952s Field #2 ('dh') of 4... 952s Segment #1 of 7... 952s Segment #1 of 7...done 952s Segment #2 of 7... 952s Segment #2 of 7...done 952s Segment #3 of 7... 952s Segment #3 of 7...done 952s Segment #4 of 7... 952s Segment #4 of 7...done 952s Segment #5 of 7... 952s Segment #5 of 7...done 952s Segment #6 of 7... 952s Segment #6 of 7...done 952s Segment #7 of 7... 952s Segment #7 of 7...done 952s Field #2 ('dh') of 4...done 952s Field #3 ('c1') of 4... 952s Segment #1 of 7... 952s Segment #1 of 7...done 952s Segment #2 of 7... 952s Segment #2 of 7...done 952s Segment #3 of 7... 952s Segment #3 of 7...done 952s Segment #4 of 7... 952s Segment #4 of 7...done 952s Segment #5 of 7... 952s Segment #5 of 7...done 952s Segment #6 of 7... 952s Segment #6 of 7...done 952s Segment #7 of 7... 952s Segment #7 of 7...done 952s Field #3 ('c1') of 4...done 952s Field #4 ('c2') of 4... 952s Segment #1 of 7... 952s Segment #1 of 7...done 952s Segment #2 of 7... 952s Segment #2 of 7...done 952s Segment #3 of 7... 952s Segment #3 of 7...done 952s Segment #4 of 7... 952s Segment #4 of 7...done 952s Segment #5 of 7... 952s Segment #5 of 7...done 952s Segment #6 of 7... 952s Segment #6 of 7...done 952s Segment #7 of 7... 952s Segment #7 of 7...done 952s Field #4 ('c2') of 4...done 952s Bootstrap statistics 952s num [1:7, 1:4, 1:4] 1.38 2.07 2.63 NA 1.38 ... 952s - attr(*, "dimnames")=List of 3 952s ..$ : NULL 952s ..$ : chr [1:4] "2.5%" "5%" "95%" "97.5%" 952s ..$ : chr [1:4] "tcn" "dh" "c1" "c2" 952s Statistical sanity checks (iff B >= 100)... 952s Available summaries: 2.5%, 5%, 95%, 97.5% 952s Available quantiles: 0.025, 0.05, 0.95, 0.975 952s num [1:7, 1:4, 1:4] 1.38 2.07 2.63 NA 1.38 ... 952s - attr(*, "dimnames")=List of 3 952s ..$ : NULL 952s ..$ : chr [1:4] "2.5%" "5%" "95%" "97.5%" 952s ..$ : chr [1:4] "tcn" "dh" "c1" "c2" 952s Field #1 ('tcn') of 4... 952s Seg 1. mean=1.39161, range=[1.38025,1.40693], n=1880 952s Seg 2. mean=2.09245, range=[2.06856,2.1165], n=671 952s Seg 3. mean=2.65451, range=[2.62678,2.6834], n=1111 952s Seg 4. mean=NA, range=[NA,NA], n=NA 952s Seg 5. mean=1.39161, range=[1.37999,1.40474], n=1880 952s Seg 6. mean=2.09245, range=[2.06923,2.11747], n=671 952s Seg 7. mean=2.65451, range=[2.62867,2.68639], n=1111 952s Field #1 ('tcn') of 4...done 952s Field #2 ('dh') of 4... 952s Seg 1. mean=0.420632, range=[0.406983,0.437756], n=765 952s Seg 2. mean=0.176243, range=[0.141232,0.202975], n=272 952s Seg 3. mean=0.269742, range=[0.245337,0.292784], n=414 952s Seg 4. mean=NA, range=[NA,NA], n=NA 952s Seg 5. mean=0.420632, range=[0.406204,0.436189], n=765 952s Seg 6. mean=0.176243, range=[0.13696,0.212132], n=272 952s Seg 7. mean=0.269742, range=[0.230034,0.296763], n=414 952s Field #2 ('dh') of 4...done 952s Field #3 ('c1') of 4... 952s Seg 1. mean=0.403126, range=[0.391189,0.413437], n=765 952s Seg 2. mean=0.861836, range=[0.833296,0.900874], n=272 952s Seg 3. mean=0.969239, range=[0.937437,1.00659], n=414 952s Seg 4. mean=NA, range=[NA,NA], n=NA 952s Seg 5. mean=0.403126, range=[0.392112,0.414529], n=765 952s Seg 6. mean=0.861836, range=[0.823193,0.907577], n=272 952s Seg 7. mean=0.969239, range=[0.931951,1.01968], n=414 952s Field #3 ('c1') of 4...done 952s Field #4 ('c2') of 4... 952s Seg 1. mean=0.988482, range=[0.974501,1.00244], n=765 952s Seg 2. mean=1.23062, range=[1.18964,1.26157], n=272 952s Seg 3. mean=1.68527, range=[1.6481,1.72497], n=414 952s Seg 4. mean=NA, range=[NA,NA], n=NA 952s Seg 5. mean=0.988482, range=[0.9761,1.00076], n=765 952s Seg 6. mean=1.23062, range=[1.18936,1.26647], n=272 952s Seg 7. mean=1.68527, range=[1.63171,1.72526], n=414 952s Field #4 ('c2') of 4...done 952s Statistical sanity checks (iff B >= 100)...done 952s Summarizing bootstrapped segment (‘tcn’, ‘dh’, ‘c1’, ‘c2’) data...done 952s Summarizing bootstrapped changepoint (‘alpha’, ‘radius’, ‘manhattan’, ‘d1’, ‘d2’) data... 952s num [1:6, 1:4, 1:5] NA NA NA NA NA NA NA NA NA NA ... 952s - attr(*, "dimnames")=List of 3 952s ..$ : NULL 952s ..$ : chr [1:4] "2.5%" "5%" "95%" "97.5%" 952s ..$ : chr [1:5] "alpha" "radius" "manhattan" "d1" ... 952s Field #1 ('alpha') of 5... 952s Changepoint #1 of 6... 952s Changepoint #1 of 6...done 952s Changepoint #2 of 6... 952s Changepoint #2 of 6...done 952s Changepoint #3 of 6... 952s Changepoint #3 of 6...done 952s Changepoint #4 of 6... 952s Changepoint #4 of 6...done 952s Changepoint #5 of 6... 952s Changepoint #5 of 6...done 952s Changepoint #6 of 6... 952s Changepoint #6 of 6...done 952s Field #1 ('alpha') of 5...done 952s Field #2 ('radius') of 5... 952s Changepoint #1 of 6... 952s Changepoint #1 of 6...done 952s Changepoint #2 of 6... 952s Changepoint #2 of 6...done 952s Changepoint #3 of 6... 952s Changepoint #3 of 6...done 952s Changepoint #4 of 6... 952s Changepoint #4 of 6...done 952s Changepoint #5 of 6... 952s Changepoint #5 of 6...done 952s Changepoint #6 of 6... 952s Changepoint #6 of 6...done 952s Field #2 ('radius') of 5...done 952s Field #3 ('manhattan') of 5... 952s Changepoint #1 of 6... 952s Changepoint #1 of 6...done 952s Changepoint #2 of 6... 952s Changepoint #2 of 6...done 952s Changepoint #3 of 6... 952s Changepoint #3 of 6...done 952s Changepoint #4 of 6... 952s Changepoint #4 of 6...done 952s Changepoint #5 of 6... 952s Changepoint #5 of 6...done 952s Changepoint #6 of 6... 952s Changepoint #6 of 6...done 952s Field #3 ('manhattan') of 5...done 952s Field #4 ('d1') of 5... 952s Changepoint #1 of 6... 952s Changepoint #1 of 6...done 952s Changepoint #2 of 6... 952s Changepoint #2 of 6...done 952s Changepoint #3 of 6... 952s Changepoint #3 of 6...done 952s Changepoint #4 of 6... 952s Changepoint #4 of 6...done 952s Changepoint #5 of 6... 952s Changepoint #5 of 6...done 952s Changepoint #6 of 6... 952s Changepoint #6 of 6...done 952s Field #4 ('d1') of 5...done 952s Field #5 ('d2') of 5... 952s Changepoint #1 of 6... 952s Changepoint #1 of 6...done 952s Changepoint #2 of 6... 952s Changepoint #2 of 6...done 952s Changepoint #3 of 6... 952s Changepoint #3 of 6...done 952s Changepoint #4 of 6... 952s Changepoint #4 of 6...done 952s Changepoint #5 of 6... 952s > print(fit) 952s chromosome tcnId dhId start end tcnNbrOfLoci tcnMean tcnNbrOfSNPs 952s 1 1 1 1 554484 143663981 1880 1.391608 765 952s 2 1 2 1 143663981 185240536 671 2.092452 272 952s 3 1 3 1 185240536 246679946 1111 2.654512 414 952s 4 NA NA NA NA NA NA NA NA 952s 5 2 1 1 554484 143663981 1880 1.391608 765 952s 6 2 2 1 143663981 185240536 671 2.092452 272 952s 7 2 3 1 185240536 246679946 1111 2.654512 414 952s tcnNbrOfHets dhNbrOfLoci dhMean c1Mean c2Mean 952s 1 765 765 0.4206323 0.4031263 0.9884817 952s 2 272 272 0.1762428 0.8618360 1.2306156 952s 3 414 414 0.2697420 0.9692395 1.6852728 952s 4 NA NA NA NA NA 952s 5 765 765 0.4206323 0.4031263 0.9884817 952s 6 272 272 0.1762428 0.8618360 1.2306156 952s 7 414 414 0.2697420 0.9692395 1.6852728 952s > 952s > 952s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 952s > # Calling segments in allelic balance (AB) 952s > # NOTE: Ideally, this should be done on whole-genome data 952s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 952s > # Explicitly estimate the threshold in DH for calling AB 952s > # (which be done by default by the caller, if skipped here) 952s > deltaAB <- estimateDeltaAB(fit, flavor="qq(DH)", verbose=-10) 952s Changepoint #5 of 6...done 952s Changepoint #6 of 6... 952s Changepoint #6 of 6...done 952s Field #5 ('d2') of 5...done 952s Bootstrap statistics 952s num [1:6, 1:4, 1:5] -2.76 -1.91 NA NA -2.76 ... 952s - attr(*, "dimnames")=List of 3 952s ..$ : NULL 952s ..$ : chr [1:4] "2.5%" "5%" "95%" "97.5%" 952s ..$ : chr [1:5] "alpha" "radius" "manhattan" "d1" ... 952s Summarizing bootstrapped changepoint (‘alpha’, ‘radius’, ‘manhattan’, ‘d1’, ‘d2’) data...done 952s Resample (TCN,DH) signals and re-estimate summaries for segment & changepoint...done 952s Estimating DH threshold for calling allelic imbalances... 952s flavor: qq(DH) 952s scale: 1 952s Estimating DH threshold for AB caller... 952s quantile #1: 0.05 952s Symmetric quantile #2: 0.9 952s Number of segments: 6 952s Weighted 5% quantile of DH: 0.199618 952s Number of segments with small DH: 2 952s Number of data points: 1342 952s Number of finite data points: 544 952s > print(deltaAB) 952s [1] 0.3234938 952s > 952s > fit <- callAB(fit, delta=deltaAB, verbose=-10) 952s Estimate of (1-0.9):th and 50% quantiles: (0.0289919,0.176243) 952s Estimate of 0.9:th "symmetric" quantile: 0.323494 952s Estimating DH threshold for AB caller...done 952s Estimated delta: 0.323 952s Estimating DH threshold for calling allelic imbalances...done 952s > print(fit) 952s chromosome tcnId dhId start end tcnNbrOfLoci tcnMean tcnNbrOfSNPs 952s 1 1 1 1 554484 143663981 1880 1.391608 765 952s 2 1 2 1 143663981 185240536 671 2.092452 272 952s 3 1 3 1 185240536 246679946 1111 2.654512 414 952s 4 NA NA NA NA NA NA NA NA 952s 5 2 1 1 554484 143663981 1880 1.391608 765 952s 6 2 2 1 143663981 185240536 671 2.092452 272 952s 7 2 3 1 185240536 246679946 1111 2.654512 414 952s tcnNbrOfHets dhNbrOfLoci dhMean c1Mean c2Mean abCall 952s 1 765 765 0.4206323 0.4031263 0.9884817 FALSE 952s 2 272 272 0.1762428 0.8618360 1.2306156 TRUE 952s 3 414 414 0.2697420 0.9692395 1.6852728 TRUE 952s 4 NA NA NA NA NA NA 952s 5 765 765 0.4206323 0.4031263 0.9884817 FALSE 952s 6 272 272 0.1762428 0.8618360 1.2306156 TRUE 952s 7 414 414 0.2697420 0.9692395 1.6852728 TRUE 952s > 952s > 952s > # Even if not explicitly specified, the estimated 952s > # threshold parameter is returned by the caller 952s > stopifnot(fit$params$deltaAB == deltaAB) 952s > 952s > 952s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 952s > # Calling segments in loss-of-heterozygosity (LOH) 952s > # NOTE: Ideally, this should be done on whole-genome data 952s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 952s > # Explicitly estimate the threshold in C1 for calling LOH 952s > # (which be done by default by the caller, if skipped here) 952s > deltaLOH <- estimateDeltaLOH(fit, flavor="minC1|nonAB", verbose=-10) 952s Calling segments of allelic balance from one-sided DH bootstrap confidence intervals... 952s delta (offset adjusting for bias in DH): 0.323493772175137 952s alpha (CI quantile; significance level): 0.05 952s Calling segments... 952s Number of segments called allelic balance (AB): 4 (57.14%) of 7 952s Calling segments...done 952s Calling segments of allelic balance from one-sided DH bootstrap confidence intervals...done 952s Estimating DH threshold for calling LOH... 952s flavor: minC1|nonAB 952s Estimating DH threshold for calling LOH as the midpoint between guessed C1=0 and C1=1... 952s Argument 'midpoint': 0.5 952s Number of segments: 6 952s Number of segments in allelic balance: 4 (66.7%) of 6 952s Number of segments not in allelic balance: 2 (33.3%) of 6 952s Number of segments in allelic balance and TCN <= 3.00: 4 (66.7%) of 6 952s C: 2.09, 2.65, 2.09, 2.65 952s Corrected C1 (=C/2): 1.05, 1.33, 1.05, 1.33 952s Number of DHs: 272, 414, 272, 414 952s Weights: 0.198, 0.302, 0.198, 0.302 952s Weighted median of (corrected) C1 in allelic balance: 1.274 952s Smallest C1 among segments not in allelic balance: 0.403 952s There are 2 segments with in total 765 heterozygous SNPs with this level. 952s There are 2 segments with in total 765 heterozygous SNPs with this level. 952s Midpoint between the two: 0.839 952s Estimating DH threshold for calling LOH as the midpoint between guessed C1=0 and C1=1...done 952s delta: 0.839 952s > print(deltaLOH) 952s [1] 0.838563 952s > 952s > fit <- callLOH(fit, delta=deltaLOH, verbose=-10) 952s Estimating DH threshold for calling LOH...done 952s Calling segments of allelic balance from one-sided DH bootstrap confidence intervals... 952s delta (offset adjusting for bias in C1): 0.838562992888546 952s alpha (CI quantile; significance level): 0.05 952s Calling segments... 952s Number of segments called low C1 (LowC1, "LOH_C1"): 3 (42.86%) of 7 952s Calling segments...done 952s Calling segments of allelic balance from one-sided DH bootstrap confidence intervals...done 952s > print(fit) 952s chromosome tcnId dhId start end tcnNbrOfLoci tcnMean tcnNbrOfSNPs 952s 1 1 1 1 554484 143663981 1880 1.391608 765 952s 2 1 2 1 143663981 185240536 671 2.092452 272 952s 3 1 3 1 185240536 246679946 1111 2.654512 414 952s 4 NA NA NA NA NA NA NA NA 952s 5 2 1 1 554484 143663981 1880 1.391608 765 952s 6 2 2 1 143663981 185240536 671 2.092452 272 952s 7 2 3 1 185240536 246679946 1111 2.654512 414 952s tcnNbrOfHets dhNbrOfLoci dhMean c1Mean c2Mean abCall lohCall 952s 1 765 765 0.4206323 0.4031263 0.9884817 FALSE TRUE 952s 2 272 272 0.1762428 0.8618360 1.2306156 TRUE NA 952s 3 414 414 0.2697420 0.9692395 1.6852728 TRUE FALSE 952s 4 NA NA NA NA NA NA NA 952s 5 765 765 0.4206323 0.4031263 0.9884817 FALSE TRUE 952s 6 272 272 0.1762428 0.8618360 1.2306156 TRUE FALSE 952s 7 414 414 0.2697420 0.9692395 1.6852728 TRUE FALSE 952s > plotTracks(fit) 952s > 952s > # Even if not explicitly specified, the estimated 952s > # threshold parameter is returned by the caller 952s > stopifnot(fit$params$deltaLOH == deltaLOH) 952s > 952s Start: segmentByPairedPSCBS,DH.R 952s 952s R version 4.5.2 (2025-10-31) -- "[Not] Part in a Rumble" 952s Copyright (C) 2025 The R Foundation for Statistical Computing 952s Platform: powerpc64le-unknown-linux-gnu 952s 952s R is free software and comes with ABSOLUTELY NO WARRANTY. 952s You are welcome to redistribute it under certain conditions. 952s Type 'license()' or 'licence()' for distribution details. 952s 952s R is a collaborative project with many contributors. 952s Type 'contributors()' for more information and 952s 'citation()' on how to cite R or R packages in publications. 952s 952s Type 'demo()' for some demos, 'help()' for on-line help, or 952s 'help.start()' for an HTML browser interface to help. 952s Type 'q()' to quit R. 952s 953s > library("PSCBS") 953s > 953s > PSCBS v0.68.0 (2025-04-18 19:40:02 UTC) successfully loaded. See ?PSCBS for help. 953s # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 953s > # Load SNP microarray data 953s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 953s > data <- PSCBS::exampleData("paired.chr01") 953s > str(data) 953s 'data.frame': 73346 obs. of 6 variables: 953s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 953s $ x : int 1145994 2224111 2319424 2543484 2926730 2941694 3084986 3155127 3292731 3695086 ... 953s $ CT : num 1.625 1.071 1.406 1.18 0.856 ... 953s $ betaT : num 0.757 0.771 0.834 0.778 0.229 ... 953s $ CN : num 2.36 2.13 2.59 1.93 1.71 ... 953s $ betaN : num 0.827 0.875 0.887 0.884 0.103 ... 953s > 953s > # Drop single-locus outliers 953s > dataS <- dropSegmentationOutliers(data) 953s > 953s > # Run light-weight tests 953s > # Use only every 5th data point 953s > dataS <- dataS[seq(from=1, to=nrow(data), by=5),] 953s > # Number of segments (for assertion) 953s > nSegs <- 3L 953s > # Number of bootstrap samples (see below) 953s > B <- 100L 953s > 953s > str(dataS) 953s 'data.frame': 14670 obs. of 6 variables: 953s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 953s $ x : int 1145994 2941694 3710825 4240737 4276892 4464544 4714611 5095111 5034491 5158416 ... 953s $ CT : num 1.63 1.4 1.41 1.17 1.16 ... 953s $ betaT : num 0.7574 0.169 0.2357 0.2604 0.0576 ... 953s $ CN : num 2.36 2.13 2.26 2.01 2.32 ... 953s $ betaN : num 0.8274 0.5072 0.1671 0.1609 0.0421 ... 953s > R.oo::attachLocally(dataS) 953s > 953s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 953s > # Calculate DH 953s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 953s > muN <- aroma.light::callNaiveGenotypes(betaN, censorAt=c(0,1)) 953s > # SNPs are identifies as those loci that have non-missing 'betaT' & 'muN' 953s > isSnp <- (!is.na(betaT) & !is.na(muN)) 953s > isHet <- isSnp & (muN == 1/2) 953s > rho <- rep(NA_real_, length=length(muN)) 953s > rho[isHet] <- 2*abs(betaT[isHet]-1/2) 953s > 953s > 953s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 953s > # Paired PSCBS segmentation using TCN and DH only 953s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 953s > fit <- segmentByPairedPSCBS(CT, rho=rho, 953s + chromosome=chromosome, x=x, 953s + seed=0xBEEF, verbose=-10) 953s Segmenting paired tumor-normal signals using Paired PSCBS... 953s Setup up data... 953s 'data.frame': 14670 obs. of 4 variables: 953s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 953s $ x : num 1145994 2941694 3710825 4240737 4276892 ... 953s $ CT : num 1.63 1.4 1.41 1.17 1.16 ... 953s $ rho : num NA 0.662 NA NA NA ... 953s Setup up data...done 953s Dropping loci for which TCNs are missing... 953s Number of loci dropped: 12 953s Dropping loci for which TCNs are missing...done 953s Ordering data along genome... 953s 'data.frame': 14658 obs. of 4 variables: 953s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 953s $ x : num 554484 730720 782343 878522 916294 ... 953s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 953s $ rho : num NA NA NA NA NA ... 953s Ordering data along genome...done 953s Keeping only current chromosome for 'knownSegments'... 953s Chromosome: 1 953s Known segments for this chromosome: 953s [1] chromosome start end 953s <0 rows> (or 0-length row.names) 953s Keeping only current chromosome for 'knownSegments'...done 953s alphaTCN: 0.009 953s alphaDH: 0.001 953s Number of loci: 14658 953s Random seed temporarily set (seed=c(48879), kind="L'Ecuyer-CMRG") 953s Produced 2 seeds from this stream for future usage 953s Identification of change points by total copy numbers... 953s Segmenting by CBS... 953s Chromosome: 1 953s Random seed temporarily set (seed=c(10407, 1066287653, -51199871, 161854402, -1995183193, 1503453565, -747102133), kind="L'Ecuyer-CMRG") 953s Segmenting by CBS...done 953s List of 4 953s $ data :'data.frame': 14658 obs. of 4 variables: 953s ..$ chromosome: int [1:14658] 1 1 1 1 1 1 1 1 1 1 ... 953s ..$ x : num [1:14658] 554484 730720 782343 878522 916294 ... 953s ..$ y : num [1:14658] 1.88 1.8 1.59 1.64 1.53 ... 953s ..$ index : int [1:14658] 1 2 3 4 5 6 7 8 9 10 ... 953s $ output :'data.frame': 3 obs. of 6 variables: 953s ..$ sampleName: chr [1:3] NA NA NA 953s ..$ chromosome: int [1:3] 1 1 1 953s ..$ start : num [1:3] 5.54e+05 1.44e+08 1.85e+08 953s ..$ end : num [1:3] 1.44e+08 1.85e+08 2.47e+08 953s ..$ nbrOfLoci : int [1:3] 7599 2668 4391 953s ..$ mean : num [1:3] 1.39 2.07 2.63 953s $ segRows:'data.frame': 3 obs. of 2 variables: 953s ..$ startRow: int [1:3] 1 7600 10268 953s ..$ endRow : int [1:3] 7599 10267 14658 953s $ params :List of 5 953s ..$ alpha : num 0.009 953s ..$ undo : num 0 953s ..$ joinSegments : logi TRUE 953s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 953s .. ..$ chromosome: int 1 953s .. ..$ start : num -Inf 953s .. ..$ end : num Inf 953s ..$ seed : int [1:7] 10407 1066287653 -51199871 161854402 -1995183193 1503453565 -747102133 953s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 953s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.484 0 0.485 0 0 953s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 953s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 953s - attr(*, "randomSeed")= int [1:7] 10407 1066287653 -51199871 161854402 -1995183193 1503453565 -747102133 953s Identification of change points by total copy numbers...done 953s Restructure TCN segmentation results... 953s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean 953s 1 1 554484 143926517 7599 1.3859 953s 2 1 143926517 185449813 2668 2.0704 953s 3 1 185449813 247137334 4391 2.6341 953s Number of TCN segments: 3 953s Restructure TCN segmentation results...done 953s Total CN segment #1 ([ 554484,1.43927e+08]) of 3... 953s Number of TCN loci in segment: 7599 953s Locus data for TCN segment: 953s 'data.frame': 7599 obs. of 5 variables: 953s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 953s $ x : num 554484 730720 782343 878522 916294 ... 953s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 953s $ rho : num NA NA NA NA NA ... 953s $ index : int 1 2 3 4 5 6 7 8 9 10 ... 953s Number of loci: 7599 953s Number of SNPs: 2111 (27.78%) 953s Number of heterozygous SNPs: 2111 (100.00%) 953s Chromosome: 1 953s Segmenting DH signals... 953s Segmenting by CBS... 953s Chromosome: 1 954s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 954s Segmenting by CBS...done 954s List of 4 954s $ data :'data.frame': 7599 obs. of 4 variables: 954s ..$ chromosome: int [1:7599] 1 1 1 1 1 1 1 1 1 1 ... 954s ..$ x : num [1:7599] 554484 730720 782343 878522 916294 ... 954s ..$ y : num [1:7599] NA NA NA NA NA ... 954s ..$ index : int [1:7599] 1 2 3 4 5 6 7 8 9 10 ... 954s $ output :'data.frame': 1 obs. of 6 variables: 954s ..$ sampleName: chr NA 954s ..$ chromosome: int 1 954s ..$ start : num 554484 954s ..$ end : num 1.44e+08 954s ..$ nbrOfLoci : int 2111 954s ..$ mean : num 0.524 954s $ segRows:'data.frame': 1 obs. of 2 variables: 954s ..$ startRow: int 10 954s ..$ endRow : int 7594 954s $ params :List of 5 954s ..$ alpha : num 0.001 954s ..$ undo : num 0 954s ..$ joinSegments : logi TRUE 954s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 954s .. ..$ chromosome: int 1 954s .. ..$ start : num 554484 954s .. ..$ end : num 1.44e+08 954s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 954s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 954s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.03 0 0.031 0 0 954s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 954s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 954s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 954s DH segmentation (locally-indexed) rows: 954s startRow endRow 954s 1 10 7594 954s int [1:7599] 1 2 3 4 5 6 7 8 9 10 ... 954s DH segmentation rows: 954s startRow endRow 954s 1 10 7594 954s Segmenting DH signals...done 954s DH segmentation table: 954s dhStart dhEnd dhNbrOfLoci dhMean 954s 1 554484 143926517 2111 0.5237 954s startRow endRow 954s 1 10 7594 954s Rows: 954s [1] 1 954s TCN segmentation rows: 954s startRow endRow 954s 1 1 7599 954s TCN and DH segmentation rows: 954s startRow endRow 954s 1 1 7599 954s startRow endRow 954s 1 10 7594 954s NULL 954s TCN segmentation (expanded) rows: 954s startRow endRow 954s 1 1 7599 954s TCN and DH segmentation rows: 954s startRow endRow 954s 1 1 7599 954s 2 7600 10267 954s 3 10268 14658 954s startRow endRow 954s 1 10 7594 954s startRow endRow 954s 1 1 7599 954s Total CN segmentation table (expanded): 954s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 954s 1 1 554484 143926517 7599 1.3859 2111 2111 954s (TCN,DH) segmentation for one total CN segment: 954s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 954s 1 1 1 1 554484 143926517 7599 1.3859 2111 954s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 954s 1 2111 554484 143926517 2111 0.5237 954s Total CN segment #1 ([ 554484,1.43927e+08]) of 3...done 954s Total CN segment #2 ([1.43927e+08,1.8545e+08]) of 3... 954s Number of TCN loci in segment: 2668 954s Locus data for TCN segment: 954s 'data.frame': 2668 obs. of 5 variables: 954s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 954s $ x : num 1.44e+08 1.44e+08 1.44e+08 1.44e+08 1.44e+08 ... 954s $ CT : num 2.1 2.1 2.09 1.8 2.34 ... 954s $ rho : num NA NA NA NA NA NA NA NA NA NA ... 954s $ index : int 7600 7601 7602 7603 7604 7605 7606 7607 7608 7609 ... 954s Number of loci: 2668 954s Number of SNPs: 774 (29.01%) 954s Number of heterozygous SNPs: 774 (100.00%) 954s Chromosome: 1 954s Segmenting DH signals... 954s Segmenting by CBS... 954s Chromosome: 1 954s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 954s Segmenting by CBS...done 954s List of 4 954s $ data :'data.frame': 2668 obs. of 4 variables: 954s ..$ chromosome: int [1:2668] 1 1 1 1 1 1 1 1 1 1 ... 954s ..$ x : num [1:2668] 1.44e+08 1.44e+08 1.44e+08 1.44e+08 1.44e+08 ... 954s ..$ y : num [1:2668] NA NA NA NA NA NA NA NA NA NA ... 954s ..$ index : int [1:2668] 1 2 3 4 5 6 7 8 9 10 ... 954s $ output :'data.frame': 1 obs. of 6 variables: 954s ..$ sampleName: chr NA 954s ..$ chromosome: int 1 954s ..$ start : num 1.44e+08 954s ..$ end : num 1.85e+08 954s ..$ nbrOfLoci : int 774 954s ..$ mean : num 0.154 954s $ segRows:'data.frame': 1 obs. of 2 variables: 954s ..$ startRow: int 15 954s ..$ endRow : int 2664 954s $ params :List of 5 954s ..$ alpha : num 0.001 954s ..$ undo : num 0 954s ..$ joinSegments : logi TRUE 954s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 954s .. ..$ chromosome: int 1 954s .. ..$ start : num 1.44e+08 954s .. ..$ end : num 1.85e+08 954s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 954s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 954s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.01 0 0.01 0 0 954s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 954s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 954s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 954s DH segmentation (locally-indexed) rows: 954s startRow endRow 954s 1 15 2664 954s int [1:2668] 7600 7601 7602 7603 7604 7605 7606 7607 7608 7609 ... 954s DH segmentation rows: 954s startRow endRow 954s 1 7614 10263 954s Segmenting DH signals...done 954s DH segmentation table: 954s dhStart dhEnd dhNbrOfLoci dhMean 954s 1 143926517 185449813 774 0.1542 954s startRow endRow 954s 1 7614 10263 954s Rows: 954s [1] 2 954s TCN segmentation rows: 954s startRow endRow 954s 2 7600 10267 954s TCN and DH segmentation rows: 954s startRow endRow 954s 2 7600 10267 954s startRow endRow 954s 1 7614 10263 954s startRow endRow 954s 1 1 7599 954s TCN segmentation (expanded) rows: 954s startRow endRow 954s 1 1 7599 954s 2 7600 10267 954s TCN and DH segmentation rows: 954s startRow endRow 954s 1 1 7599 954s 2 7600 10267 954s 3 10268 14658 954s startRow endRow 954s 1 10 7594 954s 2 7614 10263 954s startRow endRow 954s 1 1 7599 954s 2 7600 10267 954s Total CN segmentation table (expanded): 954s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 954s 2 1 143926517 185449813 2668 2.0704 774 774 954s (TCN,DH) segmentation for one total CN segment: 954s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 954s 2 2 1 1 143926517 185449813 2668 2.0704 774 954s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 954s 2 774 143926517 185449813 774 0.1542 954s Total CN segment #2 ([1.43927e+08,1.8545e+08]) of 3...done 954s Total CN segment #3 ([1.8545e+08,2.47137e+08]) of 3... 954s Number of TCN loci in segment: 4391 954s Locus data for TCN segment: 954s 'data.frame': 4391 obs. of 5 variables: 954s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 954s $ x : num 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 954s $ CT : num 2.93 2.15 2.82 2.93 2.46 ... 954s $ rho : num NA 0.0308 NA 0.2533 NA ... 954s $ index : int 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 954s Number of loci: 4391 954s Number of SNPs: 1311 (29.86%) 954s Number of heterozygous SNPs: 1311 (100.00%) 954s Chromosome: 1 954s Segmenting DH signals... 954s Segmenting by CBS... 954s Chromosome: 1 954s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 954s Segmenting by CBS...done 954s List of 4 954s $ data :'data.frame': 4391 obs. of 4 variables: 954s ..$ chromosome: int [1:4391] 1 1 1 1 1 1 1 1 1 1 ... 954s ..$ x : num [1:4391] 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 954s ..$ y : num [1:4391] NA 0.0308 NA 0.2533 NA ... 954s ..$ index : int [1:4391] 1 2 3 4 5 6 7 8 9 10 ... 954s $ output :'data.frame': 1 obs. of 6 variables: 954s ..$ sampleName: chr NA 954s ..$ chromosome: int 1 954s ..$ start : num 1.85e+08 954s ..$ end : num 2.47e+08 954s ..$ nbrOfLoci : int 1311 954s ..$ mean : num 0.251 954s $ segRows:'data.frame': 1 obs. of 2 variables: 954s ..$ startRow: int 2 954s ..$ endRow : int 4388 954s $ params :List of 5 954s ..$ alpha : num 0.001 954s ..$ undo : num 0 954s ..$ joinSegments : logi TRUE 954s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 954s .. ..$ chromosome: int 1 954s .. ..$ start : num 1.85e+08 954s .. ..$ end : num 2.47e+08 954s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 954s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 954s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.027 0 0.026 0 0 954s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 954s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 954s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 954s DH segmentation (locally-indexed) rows: 954s startRow endRow 954s 1 2 4388 954s int [1:4391] 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 954s DH segmentation rows: 954s startRow endRow 954s 1 10269 14655 954s Segmenting DH signals...done 954s DH segmentation table: 954s dhStart dhEnd dhNbrOfLoci dhMean 954s 1 185449813 247137334 1311 0.2512 954s startRow endRow 954s 1 10269 14655 954s Rows: 954s [1] 3 954s TCN segmentation rows: 954s startRow endRow 954s 3 10268 14658 954s TCN and DH segmentation rows: 954s startRow endRow 954s 3 10268 14658 954s startRow endRow 954s 1 10269 14655 954s startRow endRow 954s 1 1 7599 954s 2 7600 10267 954s TCN segmentation (expanded) rows: 954s startRow endRow 954s 1 1 7599 954s 2 7600 10267 954s 3 10268 14658 954s TCN and DH segmentation rows: 954s startRow endRow 954s 1 1 7599 954s 2 7600 10267 954s 3 10268 14658 954s startRow endRow 954s 1 10 7594 954s 2 7614 10263 954s 3 10269 14655 954s startRow endRow 954s 1 1 7599 954s 2 7600 10267 954s 3 10268 14658 954s Total CN segmentation table (expanded): 954s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 954s 3 1 185449813 247137334 4391 2.6341 1311 1311 954s (TCN,DH) segmentation for one total CN segment: 954s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 954s 3 3 1 1 185449813 247137334 4391 2.6341 1311 954s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 954s 3 1311 185449813 247137334 1311 0.2512 954s Total CN segment #3 ([1.8545e+08,2.47137e+08]) of 3...done 954s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 954s 1 1 1 1 554484 143926517 7599 1.3859 2111 954s 2 1 2 1 143926517 185449813 2668 2.0704 774 954s 3 1 3 1 185449813 247137334 4391 2.6341 1311 954s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 954s 1 2111 554484 143926517 2111 0.5237 954s 2 774 143926517 185449813 774 0.1542 954s 3 1311 185449813 247137334 1311 0.2512 954s Calculating (C1,C2) per segment... 954s Calculating (C1,C2) per segment...done 954s Number of segments: 3 954s Segmenting paired tumor-normal signals using Paired PSCBS...done 954s Post-segmenting TCNs... 954s Number of segments: 3 954s Number of chromosomes: 1 954s [1] 1 954s Chromosome 1 ('chr01') of 1... 954s Rows: 954s [1] 1 2 3 954s Number of segments: 3 954s TCN segment #1 ('1') of 3... 954s Nothing todo. Only one DH segmentation. Skipping. 954s TCN segment #1 ('1') of 3...done 954s TCN segment #2 ('2') of 3... 954s Nothing todo. Only one DH segmentation. Skipping. 954s TCN segment #2 ('2') of 3...done 954s TCN segment #3 ('3') of 3... 954s Nothing todo. Only one DH segmentation. Skipping. 954s TCN segment #3 ('3') of 3...done 954s Chromosome 1 ('chr01') of 1...done 954s Update (C1,C2) per segment... 954s Update (C1,C2) per segment...done 954s Post-segmenting TCNs...done 954s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 954s 1 1 1 1 554484 143926517 7599 1.3859 2111 954s 2 1 2 1 143926517 185449813 2668 2.0704 774 954s 3 1 3 1 185449813 247137334 4391 2.6341 1311 954s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 954s 1 2111 554484 143926517 2111 0.5237 0.3300521 1.055848 954s 2 774 143926517 185449813 774 0.1542 0.8755722 1.194828 954s 3 1311 185449813 247137334 1311 0.2512 0.9862070 1.647893 954s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 954s 1 1 1 1 554484 143926517 7599 1.3859 2111 954s 2 1 2 1 143926517 185449813 2668 2.0704 774 954s 3 1 3 1 185449813 247137334 4391 2.6341 1311 954s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 954s 1 2111 554484 143926517 2111 0.5237 0.3300521 1.055848 954s 2 774 143926517 185449813 774 0.1542 0.8755722 1.194828 954s 3 1311 185449813 247137334 1311 0.2512 0.9862070 1.647893 954s > print(fit) 954s chromosome tcnId dhId start end tcnNbrOfLoci tcnMean tcnNbrOfSNPs 954s 1 1 1 1 554484 143926517 7599 1.3859 2111 954s 2 1 2 1 143926517 185449813 2668 2.0704 774 954s 3 1 3 1 185449813 247137334 4391 2.6341 1311 954s tcnNbrOfHets dhNbrOfLoci dhMean c1Mean c2Mean 954s 1 2111 2111 0.5237 0.3300521 1.055848 954s 2 774 774 0.1542 0.8755722 1.194828 954s 3 1311 1311 0.2512 0.9862070 1.647893 954s > 954s > # Plot results 954s > plotTracks(fit) 954s > 954s > 954s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 954s > # Bootstrap segment level estimates 954s > # (used by the AB caller, which, if skipped here, 954s > # will do it automatically) 954s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 954s > fit <- bootstrapTCNandDHByRegion(fit, B=B, verbose=-10) 954s Resample (TCN,DH) signals and re-estimate summaries for segment & changepoint... 954s Already done? 954s tcn_2.5% tcn_5% tcn_95% tcn_97.5% dh_2.5% dh_5% dh_95% dh_97.5% 954s FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE 954s c1_2.5% c1_5% c1_95% c1_97.5% c2_2.5% c2_5% c2_95% c2_97.5% 954s FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE 954s Bootstrapping (TCN,DH,C1,C2) segment mean levels... 954s Identifying heterozygous & homozygous SNPs and non-polymorphic loci... 954s Number of loci: 14658 954s Number of SNPs: 4196 954s Number of non-SNPs: 10462 954s Identifying heterozygous & homozygous SNPs and non-polymorphic loci...done 954s num [1:3, 1:100, 1:4] NA NA NA NA NA NA NA NA NA NA ... 954s - attr(*, "dimnames")=List of 3 954s ..$ : NULL 954s ..$ : NULL 954s ..$ : chr [1:4] "tcn" "dh" "c1" "c2" 954s Segment #1 (chr 1, tcnId=1, dhId=1) of 3... 954s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 954s 1 1 1 1 554484 143926517 7599 1.3859 2111 954s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 954s 1 2111 554484 143926517 2111 0.5237 0.3300521 1.055848 954s Number of TCNs: 7599 954s Number of DHs: 2111 954s int [1:7599] 1 2 3 4 5 6 7 8 9 10 ... 954s int [1:14658] 1 2 3 4 5 6 7 8 9 10 ... 954s int [1:7599] 1 2 3 4 5 6 7 8 9 10 ... 954s Identify loci used to bootstrap DH means... 954s Heterozygous SNPs to resample for DH: 954s int [1:2111] 10 12 24 28 31 33 34 39 46 48 ... 954s Identify loci used to bootstrap DH means...done 954s Identify loci used to bootstrap TCN means... 954s SNPs: 954s int [1:2111] 10 12 24 28 31 33 34 39 46 48 ... 954s Non-polymorphic loci: 954s int [1:5488] 1 2 3 4 5 6 7 8 9 11 ... 954s Heterozygous SNPs to resample for TCN: 954s int [1:2111] 10 12 24 28 31 33 34 39 46 48 ... 954s Homozygous SNPs to resample for TCN: 954s int(0) 954s Non-polymorphic loci to resample for TCN: 954s int [1:5488] 1 2 3 4 5 6 7 8 9 11 ... 954s Heterozygous SNPs with non-DH to resample for TCN: 954s int(0) 954s Loci to resample for TCN: 954s int [1:7599] 1 2 3 4 5 6 7 8 9 10 ... 954s Identify loci used to bootstrap TCN means...done 954s Number of (#hets, #homs, #nonSNPs): (2111,0,5488) 954s Bootstrapping while preserving (#hets, #homs, #nonSNPs)... 954s Number of bootstrap samples: 100 954s Bootstrapping while preserving (#hets, #homs, #nonSNPs)...done 954s Segment #1 (chr 1, tcnId=1, dhId=1) of 3...done 954s Segment #2 (chr 1, tcnId=2, dhId=1) of 3... 954s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 954s 2 1 2 1 143926517 185449813 2668 2.0704 774 954s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 954s 2 774 143926517 185449813 774 0.1542 0.8755722 1.194828 954s Number of TCNs: 2668 954s Number of DHs: 774 954s int [1:2668] 7600 7601 7602 7603 7604 7605 7606 7607 7608 7609 ... 954s int [1:14658] 1 2 3 4 5 6 7 8 9 10 ... 954s int [1:2668] 7600 7601 7602 7603 7604 7605 7606 7607 7608 7609 ... 954s Identify loci used to bootstrap DH means... 954s Heterozygous SNPs to resample for DH: 954s int [1:774] 7614 7616 7626 7627 7628 7635 7638 7639 7640 7642 ... 954s Identify loci used to bootstrap DH means...done 954s Identify loci used to bootstrap TCN means... 954s SNPs: 954s int [1:774] 7614 7616 7626 7627 7628 7635 7638 7639 7640 7642 ... 954s Non-polymorphic loci: 954s int [1:1894] 7600 7601 7602 7603 7604 7605 7606 7607 7608 7609 ... 954s Heterozygous SNPs to resample for TCN: 954s int [1:774] 7614 7616 7626 7627 7628 7635 7638 7639 7640 7642 ... 954s Homozygous SNPs to resample for TCN: 954s int(0) 954s Non-polymorphic loci to resample for TCN: 954s int [1:1894] 7600 7601 7602 7603 7604 7605 7606 7607 7608 7609 ... 954s Heterozygous SNPs with non-DH to resample for TCN: 954s int(0) 954s Loci to resample for TCN: 954s int [1:2668] 7600 7601 7602 7603 7604 7605 7606 7607 7608 7609 ... 954s Identify loci used to bootstrap TCN means...done 954s Number of (#hets, #homs, #nonSNPs): (774,0,1894) 954s Bootstrapping while preserving (#hets, #homs, #nonSNPs)... 954s Number of bootstrap samples: 100 954s Bootstrapping while preserving (#hets, #homs, #nonSNPs)...done 954s Segment #2 (chr 1, tcnId=2, dhId=1) of 3...done 954s Segment #3 (chr 1, tcnId=3, dhId=1) of 3... 954s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 954s 3 1 3 1 185449813 247137334 4391 2.6341 1311 954s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 954s 3 1311 185449813 247137334 1311 0.2512 0.986207 1.647893 954s Number of TCNs: 4391 954s Number of DHs: 1311 954s int [1:4391] 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 954s int [1:14658] 1 2 3 4 5 6 7 8 9 10 ... 954s int [1:4391] 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 954s Identify loci used to bootstrap DH means... 954s Heterozygous SNPs to resample for DH: 954s int [1:1311] 10269 10271 10281 10282 10283 10293 10295 10297 10300 10302 ... 954s Identify loci used to bootstrap DH means...done 954s Identify loci used to bootstrap TCN means... 954s SNPs: 954s int [1:1311] 10269 10271 10281 10282 10283 10293 10295 10297 10300 10302 ... 954s Non-polymorphic loci: 954s int [1:3080] 10268 10270 10272 10273 10274 10275 10276 10277 10278 10279 ... 954s Heterozygous SNPs to resample for TCN: 954s int [1:1311] 10269 10271 10281 10282 10283 10293 10295 10297 10300 10302 ... 954s Homozygous SNPs to resample for TCN: 954s int(0) 954s Non-polymorphic loci to resample for TCN: 954s int [1:3080] 10268 10270 10272 10273 10274 10275 10276 10277 10278 10279 ... 954s Heterozygous SNPs with non-DH to resample for TCN: 954s int(0) 954s Loci to resample for TCN: 954s int [1:4391] 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 954s Identify loci used to bootstrap TCN means...done 954s Number of (#hets, #homs, #nonSNPs): (1311,0,3080) 954s Bootstrapping while preserving (#hets, #homs, #nonSNPs)... 954s Number of bootstrap samples: 100 954s Bootstrapping while preserving (#hets, #homs, #nonSNPs)...done 954s Segment #3 (chr 1, tcnId=3, dhId=1) of 3...done 954s Bootstrapped segment mean levels 954s num [1:3, 1:100, 1:4] 1.38 2.08 2.63 1.38 2.07 ... 954s - attr(*, "dimnames")=List of 3 954s ..$ : NULL 954s ..$ : NULL 954s ..$ : chr [1:4] "tcn" "dh" "c1" "c2" 954s Calculating (C1,C2) mean levels from (TCN,DH) mean levels... 954s num [1:3, 1:100, 1:4] 1.38 2.08 2.63 1.38 2.07 ... 954s - attr(*, "dimnames")=List of 3 954s ..$ : NULL 954s ..$ : NULL 954s ..$ : chr [1:4] "tcn" "dh" "c1" "c2" 954s Calculating (C1,C2) mean levels from (TCN,DH) mean levels...done 954s Calculating polar (alpha,radius,manhattan) for change points... 954s num [1:2, 1:100, 1:2] -0.5588 -0.0962 -0.5365 -0.1285 -0.5378 ... 954s - attr(*, "dimnames")=List of 3 954s ..$ : NULL 954s ..$ : NULL 954s ..$ : chr [1:2] "c1" "c2" 954s Bootstrapped change points 954s num [1:2, 1:100, 1:5] -2.89 -1.78 -2.87 -1.86 -2.88 ... 954s - attr(*, "dimnames")=List of 3 954s ..$ : NULL 954s ..$ : NULL 954s ..$ : chr [1:5] "alpha" "radius" "manhattan" "d1" ... 954s Calculating polar (alpha,radius,manhattan) for change points...done 954s Bootstrapping (TCN,DH,C1,C2) segment mean levels...done 954s Summarizing bootstrapped segment (‘tcn’, ‘dh’, ‘c1’, ‘c2’) data... 954s num [1:3, 1:4, 1:4] NA NA NA NA NA NA NA NA NA NA ... 954s - attr(*, "dimnames")=List of 3 954s ..$ : NULL 954s ..$ : chr [1:4] "2.5%" "5%" "95%" "97.5%" 954s ..$ : chr [1:4] "tcn" "dh" "c1" "c2" 954s Field #1 ('tcn') of 4... 954s Segment #1 of 3... 954s Segment #1 of 3...done 954s Segment #2 of 3... 954s Segment #2 of 3...done 954s Segment #3 of 3... 954s Segment #3 of 3...done 954s Field #1 ('tcn') of 4...done 954s Field #2 ('dh') of 4... 954s Segment #1 of 3... 954s Segment #1 of 3...done 954s Segment #2 of 3... 954s Segment #2 of 3...done 954s Segment #3 of 3... 954s Segment #3 of 3...done 954s Field #2 ('dh') of 4...done 954s Field #3 ('c1') of 4... 954s Segment #1 of 3... 954s Segment #1 of 3...done 954s Segment #2 of 3... 954s Segment #2 of 3...done 954s Segment #3 of 3... 954s Segment #3 of 3...done 954s Field #3 ('c1') of 4...done 954s Field #4 ('c2') of 4... 954s Segment #1 of 3... 954s Segment #1 of 3...done 954s Segment #2 of 3... 954s Segment #2 of 3...done 954s Segment #3 of 3... 954s Segment #3 of 3...done 954s Field #4 ('c2') of 4...done 954s Bootstrap statistics 954s num [1:3, 1:4, 1:4] 1.38 2.06 2.62 1.38 2.06 ... 954s - attr(*, "dimnames")=List of 3 954s ..$ : NULL 954s ..$ : chr [1:4] "2.5%" "5%" "95%" "97.5%" 954s ..$ : chr [1:4] "tcn" "dh" "c1" "c2" 954s Statistical sanity checks (iff B >= 100)... 954s Available summaries: 2.5%, 5%, 95%, 97.5% 954s Available quantiles: 0.025, 0.05, 0.95, 0.975 954s num [1:3, 1:4, 1:4] 1.38 2.06 2.62 1.38 2.06 ... 954s - attr(*, "dimnames")=List of 3 954s ..$ : NULL 954s ..$ : chr [1:4] "2.5%" "5%" "95%" "97.5%" 954s ..$ : chr [1:4] "tcn" "dh" "c1" "c2" 954s Field #1 ('tcn') of 4... 954s Seg 1. mean=1.3859, range=[1.38092,1.3949], n=7599 954s Seg 2. mean=2.0704, range=[2.05747,2.08326], n=2668 954s Seg 3. mean=2.6341, range=[2.62068,2.64694], n=4391 954s Field #1 ('tcn') of 4...done 954s Field #2 ('dh') of 4... 954s Seg 1. mean=0.5237, range=[0.51753,0.532002], n=2111 954s Seg 2. mean=0.1542, range=[0.144468,0.16453], n=774 954s Seg 3. mean=0.2512, range=[0.242575,0.258832], n=1311 954s Field #2 ('dh') of 4...done 954s Field #3 ('c1') of 4... 954s Seg 1. mean=0.330052, range=[0.323996,0.336038], n=2111 954s Seg 2. mean=0.875572, range=[0.86318,0.887699], n=774 954s Seg 3. mean=0.986207, range=[0.975123,0.998982], n=1311 954s Field #3 ('c1') of 4...done 954s Field #4 ('c2') of 4... 954s Seg 1. mean=1.05585, range=[1.05006,1.06231], n=2111 954s Seg 2. mean=1.19483, range=[1.18417,1.2081], n=774 954s Seg 3. mean=1.64789, range=[1.63403,1.66098], n=1311 954s Field #4 ('c2') of 4...done 954s Statistical sanity checks (iff B >= 100)...done 954s Summarizing bootstrapped segment (‘tcn’, ‘dh’, ‘c1’, ‘c2’) data...done 954s Summarizing bootstrapped changepoint (‘alpha’, ‘radius’, ‘manhattan’, ‘d1’, ‘d2’) data... 954s num [1:2, 1:4, 1:5] NA NA NA NA NA NA NA NA NA NA ... 954s - attr(*, "dimnames")=List of 3 954s ..$ : NULL 954s ..$ : chr [1:4] "2.5%" "5%" "95%" "97.5%" 954s ..$ : chr [1:5] "alpha" "radius" "manhattan" "d1" ... 954s Field #1 ('alpha') of 5... 954s Changepoint #1 of 2... 954s Changepoint #1 of 2...done 954s Changepoint #2 of 2... 954s Changepoint #2 of 2...done 954s Field #1 ('alpha') of 5...done 954s Field #2 ('radius') of 5... 954s Changepoint #1 of 2... 954s Changepoint #1 of 2...done 954s Changepoint #2 of 2... 954s Changepoint #2 of 2...done 954s Field #2 ('radius') of 5...done 954s Field #3 ('manhattan') of 5... 954s Changepoint #1 of 2... 954s Changepoint #1 of 2...done 954s Changepoint #2 of 2... 954s Changepoint #2 of 2...done 954s Field #3 ('manhattan') of 5...done 954s Field #4 ('d1') of 5... 954s Changepoint #1 of 2... 954s Changepoint #1 of 2...done 954s Changepoint #2 of 2... 954s Changepoint #2 of 2...done 954s Field #4 ('d1') of 5...done 954s Field #5 ('d2') of 5... 954s Changepoint #1 of 2... 954s Changepoint #1 of 2...done 954s Changepoint #2 of 2... 954s Changepoint #2 of 2...done 954s Field #5 ('d2') of 5...done 954s Bootstrap statistics 954s num [1:2, 1:4, 1:5] -2.92 -1.86 -2.91 -1.85 -2.87 ... 954s - attr(*, "dimnames")=List of 3 954s ..$ : NULL 954s ..$ : chr [1:4] "2.5%" "5%" "95%" "97.5%" 954s ..$ : chr [1:5] "alpha" "radius" "manhattan" "d1" ... 954s Summarizing bootstrapped changepoint (‘alpha’, ‘radius’, ‘manhattan’, ‘d1’, ‘d2’) data...done 954s Resample (TCN,DH) signals and re-estimate summaries for segment & changepoint...done 954s > print(fit) 954s chromosome tcnId dhId start end tcnNbrOfLoci tcnMean tcnNbrOfSNPs 954s 1 1 1 1 554484 143926517 7599 1.3859 2111 954s 2 1 2 1 143926517 185449813 2668 2.0704 774 954s 3 1 3 1 185449813 247137334 4391 2.6341 1311 954s tcnNbrOfHets dhNbrOfLoci dhMean c1Mean c2Mean 954s 1 2111 2111 0.5237 0.3300521 1.055848 954s 2 774 774 0.1542 0.8755722 1.194828 954s 3 1311 1311 0.2512 0.9862070 1.647893 954s > plotTracks(fit) 955s > 955s > 955s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 955s > # Calling segments in allelic balance (AB) and 955s > # in loss-of-heterozygosity (LOH) 955s > # NOTE: Ideally, this should be done on whole-genome data 955s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 955s > fit <- callAB(fit, verbose=-10) 955s Calling segments of allelic balance from one-sided DH bootstrap confidence intervals... 955s delta (offset adjusting for bias in DH): 0.3466649145302 955s alpha (CI quantile; significance level): 0.05 955s Calling segments... 955s Number of segments called allelic balance (AB): 2 (66.67%) of 3 955s Calling segments...done 955s Calling segments of allelic balance from one-sided DH bootstrap confidence intervals...done 955s > fit <- callLOH(fit, verbose=-10) 955s Calling segments of allelic balance from one-sided DH bootstrap confidence intervals... 955s delta (offset adjusting for bias in C1): 0.771236438183453 955s alpha (CI quantile; significance level): 0.05 955s Calling segments... 955s Number of segments called low C1 (LowC1, "LOH_C1"): 1 (33.33%) of 3 955s Calling segments...done 955s Calling segments of allelic balance from one-sided DH bootstrap confidence intervals...done 955s > print(fit) 955s chromosome tcnId dhId start end tcnNbrOfLoci tcnMean tcnNbrOfSNPs 955s 1 1 1 1 554484 143926517 7599 1.3859 2111 955s 2 1 2 1 143926517 185449813 2668 2.0704 774 955s 3 1 3 1 185449813 247137334 4391 2.6341 1311 955s tcnNbrOfHets dhNbrOfLoci dhMean c1Mean c2Mean abCall lohCall 955s 1 2111 2111 0.5237 0.3300521 1.055848 FALSE TRUE 955s 2 774 774 0.1542 0.8755722 1.194828 TRUE FALSE 955s 3 1311 1311 0.2512 0.9862070 1.647893 TRUE FALSE 955s > plotTracks(fit) 955s > 955s Start: segmentByPairedPSCBS,calls.R 955s 955s R version 4.5.2 (2025-10-31) -- "[Not] Part in a Rumble" 955s Copyright (C) 2025 The R Foundation for Statistical Computing 955s Platform: powerpc64le-unknown-linux-gnu 955s 955s R is free software and comes with ABSOLUTELY NO WARRANTY. 955s You are welcome to redistribute it under certain conditions. 955s Type 'license()' or 'licence()' for distribution details. 955s 955s R is a collaborative project with many contributors. 955s Type 'contributors()' for more information and 955s 'citation()' on how to cite R or R packages in publications. 955s 955s Type 'demo()' for some demos, 'help()' for on-line help, or 955s 'help.start()' for an HTML browser interface to help. 955s Type 'q()' to quit R. 955s 955s > library("PSCBS") 955s PSCBS v0.68.0 (2025-04-18 19:40:02 UTC) successfully loaded. See ?PSCBS for help. 955s > 955s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 955s > # Load SNP microarray data 955s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 955s > data <- PSCBS::exampleData("paired.chr01") 955s > str(data) 955s 'data.frame': 73346 obs. of 6 variables: 955s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 955s $ x : int 1145994 2224111 2319424 2543484 2926730 2941694 3084986 3155127 3292731 3695086 ... 955s $ CT : num 1.625 1.071 1.406 1.18 0.856 ... 955s $ betaT : num 0.757 0.771 0.834 0.778 0.229 ... 955s $ CN : num 2.36 2.13 2.59 1.93 1.71 ... 955s $ betaN : num 0.827 0.875 0.887 0.884 0.103 ... 955s > 955s > 955s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 955s > # Paired PSCBS segmentation 955s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 955s > # Drop single-locus outliers 955s > dataS <- dropSegmentationOutliers(data) 955s > 955s > # Find centromere 955s > gaps <- findLargeGaps(dataS, minLength=2e6) 955s > knownSegments <- gapsToSegments(gaps) 955s > 955s > 955s > # Run light-weight tests by default 955s > if (Sys.getenv("_R_CHECK_FULL_") == "") { 955s + # Use only every 5th data point 955s + dataS <- dataS[seq(from=1, to=nrow(data), by=5),] 955s + # Number of segments (for assertion) 955s + nSegs <- 4L 955s + # Number of bootstrap samples (see below) 955s + B <- 100L 955s + } else { 955s + # Full tests 955s + nSegs <- 11L 955s + B <- 1000L 955s + } 955s > 955s > str(dataS) 955s 'data.frame': 14670 obs. of 6 variables: 955s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 955s $ x : int 1145994 2941694 3710825 4240737 4276892 4464544 4714611 5095111 5034491 5158416 ... 955s $ CT : num 1.63 1.4 1.41 1.17 1.16 ... 955s $ betaT : num 0.7574 0.169 0.2357 0.2604 0.0576 ... 955s $ CN : num 2.36 2.13 2.26 2.01 2.32 ... 955s $ betaN : num 0.8274 0.5072 0.1671 0.1609 0.0421 ... 955s > 955s > # Paired PSCBS segmentation 955s > fit <- segmentByPairedPSCBS(dataS, knownSegments=knownSegments, 955s + seed=0xBEEF, verbose=-10) 955s Segmenting paired tumor-normal signals using Paired PSCBS... 955s Calling genotypes from normal allele B fractions... 955s num [1:14670] 0.8274 0.5072 0.1671 0.1609 0.0421 ... 955s Called genotypes: 955s num [1:14670] 1 0.5 0 0 0 0 1 0 1 0.5 ... 955s - attr(*, "modelFit")=List of 1 955s ..$ :List of 7 955s .. ..$ flavor : chr "density" 955s .. ..$ cn : int 2 955s .. ..$ nbrOfGenotypeGroups: int 3 955s .. ..$ tau : num [1:2] 0.315 0.677 955s .. ..$ n : int 14640 955s .. ..$ fit :Classes ‘PeaksAndValleys’ and 'data.frame': 5 obs. of 3 variables: 955s .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 955s .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 955s .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 955s .. ..$ fitValleys :Classes ‘PeaksAndValleys’ and 'data.frame': 2 obs. of 3 variables: 955s .. .. ..$ type : chr [1:2] "valley" "valley" 955s .. .. ..$ x : num [1:2] 0.315 0.677 955s .. .. ..$ density: num [1:2] 0.522 0.551 955s ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 955s muN 955s 0 0.5 1 955s 5221 4198 5251 955s Calling genotypes from normal allele B fractions...done 955s Normalizing betaT using betaN (TumorBoost)... 955s Normalized BAFs: 955s num [1:14670] 0.9301 0.1667 0.0685 0.0995 0.0155 ... 955s - attr(*, "modelFit")=List of 5 955s ..$ method : chr "normalizeTumorBoost" 955s ..$ flavor : chr "v4" 955s ..$ delta : num [1:14670] -0.17264 0.00239 0.1671 0.16085 0.04213 ... 955s .. ..- attr(*, "modelFit")=List of 1 955s .. .. ..$ :List of 7 955s .. .. .. ..$ flavor : chr "density" 955s .. .. .. ..$ cn : int 2 955s .. .. .. ..$ nbrOfGenotypeGroups: int 3 955s .. .. .. ..$ tau : num [1:2] 0.315 0.677 955s .. .. .. ..$ n : int 14640 955s .. .. .. ..$ fit :Classes ‘PeaksAndValleys’ and 'data.frame': 5 obs. of 3 variables: 955s .. .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 955s .. .. .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 955s .. .. .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 955s .. .. .. ..$ fitValleys :Classes ‘PeaksAndValleys’ and 'data.frame': 2 obs. of 3 variables: 955s .. .. .. .. ..$ type : chr [1:2] "valley" "valley" 955s .. .. .. .. ..$ x : num [1:2] 0.315 0.677 955s .. .. .. .. ..$ density: num [1:2] 0.522 0.551 955s .. .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 955s ..$ preserveScale: logi FALSE 955s ..$ scaleFactor : num NA 955s Normalizing betaT using betaN (TumorBoost)...done 955s Setup up data... 955s 'data.frame': 14670 obs. of 7 variables: 955s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 955s $ x : num 1145994 2941694 3710825 4240737 4276892 ... 955s $ CT : num 1.63 1.4 1.41 1.17 1.16 ... 955s $ betaT : num 0.7574 0.169 0.2357 0.2604 0.0576 ... 955s $ betaTN : num 0.9301 0.1667 0.0685 0.0995 0.0155 ... 955s ..- attr(*, "modelFit")=List of 5 955s .. ..$ method : chr "normalizeTumorBoost" 955s .. ..$ flavor : chr "v4" 955s .. ..$ delta : num [1:14670] -0.17264 0.00239 0.1671 0.16085 0.04213 ... 955s .. .. ..- attr(*, "modelFit")=List of 1 955s .. .. .. ..$ :List of 7 955s .. .. .. .. ..$ flavor : chr "density" 955s .. .. .. .. ..$ cn : int 2 955s .. .. .. .. ..$ nbrOfGenotypeGroups: int 3 955s .. .. .. .. ..$ tau : num [1:2] 0.315 0.677 955s .. .. .. .. ..$ n : int 14640 955s .. .. .. .. ..$ fit :Classes ‘PeaksAndValleys’ and 'data.frame': 5 obs. of 3 variables: 955s .. .. .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 955s .. .. .. .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 955s .. .. .. .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 955s .. .. .. .. ..$ fitValleys :Classes ‘PeaksAndValleys’ and 'data.frame': 2 obs. of 3 variables: 955s .. .. .. .. .. ..$ type : chr [1:2] "valley" "valley" 955s .. .. .. .. .. ..$ x : num [1:2] 0.315 0.677 955s .. .. .. .. .. ..$ density: num [1:2] 0.522 0.551 955s .. .. .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 955s .. ..$ preserveScale: logi FALSE 955s .. ..$ scaleFactor : num NA 955s $ betaN : num 0.8274 0.5072 0.1671 0.1609 0.0421 ... 955s $ muN : num 1 0.5 0 0 0 0 1 0 1 0.5 ... 955s ..- attr(*, "modelFit")=List of 1 955s .. ..$ :List of 7 955s .. .. ..$ flavor : chr "density" 955s .. .. ..$ cn : int 2 955s .. .. ..$ nbrOfGenotypeGroups: int 3 955s .. .. ..$ tau : num [1:2] 0.315 0.677 955s .. .. ..$ n : int 14640 955s .. .. ..$ fit :Classes ‘PeaksAndValleys’ and 'data.frame': 5 obs. of 3 variables: 955s .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 955s .. .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 955s .. .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 955s .. .. ..$ fitValleys :Classes ‘PeaksAndValleys’ and 'data.frame': 2 obs. of 3 variables: 955s .. .. .. ..$ type : chr [1:2] "valley" "valley" 955s .. .. .. ..$ x : num [1:2] 0.315 0.677 955s .. .. .. ..$ density: num [1:2] 0.522 0.551 955s .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 955s Setup up data...done 955s Dropping loci for which TCNs are missing... 955s Number of loci dropped: 12 955s Dropping loci for which TCNs are missing...done 955s Ordering data along genome... 955s 'data.frame': 14658 obs. of 7 variables: 955s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 955s $ x : num 554484 730720 782343 878522 916294 ... 955s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 955s $ betaT : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 955s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 955s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 955s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 955s Ordering data along genome...done 955s Keeping only current chromosome for 'knownSegments'... 955s Chromosome: 1 955s Known segments for this chromosome: 955s chromosome start end length 955s 1 1 -Inf 120992603 Inf 955s 2 1 120992604 141510002 20517398 955s 3 1 141510003 Inf Inf 955s Keeping only current chromosome for 'knownSegments'...done 955s alphaTCN: 0.009 955s alphaDH: 0.001 955s Number of loci: 14658 955s Calculating DHs... 955s Number of SNPs: 14658 955s Number of heterozygous SNPs: 4196 (28.63%) 955s Normalized DHs: 955s num [1:14658] NA NA NA NA NA ... 955s Calculating DHs...done 955s Random seed temporarily set (seed=c(48879), kind="L'Ecuyer-CMRG") 955s Produced 2 seeds from this stream for future usage 955s Identification of change points by total copy numbers... 955s Segmenting by CBS... 955s Chromosome: 1 955s Segmenting multiple segments on current chromosome... 955s Number of segments: 3 956s Random seed temporarily set (seed=c(10407, 1066287653, -51199871, 161854402, -1995183193, 1503453565, -747102133), kind="L'Ecuyer-CMRG") 956s Produced 3 seeds from this stream for future usage 956s Segmenting by CBS... 956s Chromosome: 1 956s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 956s Segmenting by CBS...done 956s Segmenting by CBS... 956s Chromosome: 1 956s Random seed temporarily set (seed=c(10407, -1924040949, -1632234809, -437763632, -1464377300, 676654412, 2080370711), kind="L'Ecuyer-CMRG") 956s Segmenting by CBS...done 956s Segmenting multiple segments on current chromosome...done 956s Segmenting by CBS...done 956s List of 4 956s $ data :'data.frame': 14658 obs. of 4 variables: 956s ..$ chromosome: int [1:14658] 1 1 1 1 1 1 1 1 1 1 ... 956s ..$ x : num [1:14658] 554484 730720 782343 878522 916294 ... 956s ..$ y : num [1:14658] 1.88 1.8 1.59 1.64 1.53 ... 956s ..$ index : int [1:14658] 1 2 3 4 5 6 7 8 9 10 ... 956s $ output :'data.frame': 4 obs. of 6 variables: 956s ..$ sampleName: chr [1:4] NA NA NA NA 956s ..$ chromosome: int [1:4] 1 1 1 1 956s ..$ start : num [1:4] 5.54e+05 1.21e+08 1.42e+08 1.85e+08 956s ..$ end : num [1:4] 1.21e+08 1.42e+08 1.85e+08 2.47e+08 956s ..$ nbrOfLoci : int [1:4] 7586 0 2681 4391 956s ..$ mean : num [1:4] 1.39 NA 2.07 2.63 956s $ segRows:'data.frame': 4 obs. of 2 variables: 956s ..$ startRow: int [1:4] 1 NA 7587 10268 956s ..$ endRow : int [1:4] 7586 NA 10267 14658 956s $ params :List of 5 956s ..$ alpha : num 0.009 956s ..$ undo : num 0 956s ..$ joinSegments : logi TRUE 956s ..$ knownSegments:'data.frame': 4 obs. of 3 variables: 956s .. ..$ chromosome: int [1:4] 1 1 2 1 956s .. ..$ start : num [1:4] -Inf -Inf -Inf 1.42e+08 956s .. ..$ end : num [1:4] 1.21e+08 Inf Inf Inf 956s ..$ seed : int [1:7] 10407 1066287653 -51199871 161854402 -1995183193 1503453565 -747102133 956s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 956s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.167 0 0.167 0 0 956s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 956s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 956s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 956s Identification of change points by total copy numbers...done 956s Restructure TCN segmentation results... 956s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean 956s 1 1 554484 120992603 7586 1.3853 956s 2 1 120992604 141510002 0 NA 956s 3 1 141510003 185449813 2681 2.0689 956s 4 1 185449813 247137334 4391 2.6341 956s Number of TCN segments: 4 956s Restructure TCN segmentation results...done 956s Total CN segment #1 ([ 554484,1.20993e+08]) of 4... 956s Number of TCN loci in segment: 7586 956s Locus data for TCN segment: 956s 'data.frame': 7586 obs. of 9 variables: 956s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 956s $ x : num 554484 730720 782343 878522 916294 ... 956s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 956s $ betaT : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 956s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 956s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 956s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 956s $ index : int 1 2 3 4 5 6 7 8 9 10 ... 956s $ rho : num NA NA NA NA NA ... 956s Number of loci: 7586 956s Number of SNPs: 2108 (27.79%) 956s Number of heterozygous SNPs: 2108 (100.00%) 956s Chromosome: 1 956s Segmenting DH signals... 956s Segmenting by CBS... 956s Chromosome: 1 956s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 956s Segmenting by CBS...done 956s List of 4 956s $ data :'data.frame': 7586 obs. of 4 variables: 956s ..$ chromosome: int [1:7586] 1 1 1 1 1 1 1 1 1 1 ... 956s ..$ x : num [1:7586] 554484 730720 782343 878522 916294 ... 956s ..$ y : num [1:7586] NA NA NA NA NA ... 956s ..$ index : int [1:7586] 1 2 3 4 5 6 7 8 9 10 ... 956s $ output :'data.frame': 1 obs. of 6 variables: 956s ..$ sampleName: chr NA 956s ..$ chromosome: int 1 956s ..$ start : num 554484 956s ..$ end : num 1.21e+08 956s ..$ nbrOfLoci : int 2108 956s ..$ mean : num 0.512 956s $ segRows:'data.frame': 1 obs. of 2 variables: 956s ..$ startRow: int 10 956s ..$ endRow : int 7574 956s $ params :List of 5 956s ..$ alpha : num 0.001 956s ..$ undo : num 0 956s ..$ joinSegments : logi TRUE 956s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 956s .. ..$ chromosome: int 1 956s .. ..$ start : num 554484 956s .. ..$ end : num 1.21e+08 956s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 956s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 956s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.047 0 0.047 0 0 956s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 956s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 956s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 956s DH segmentation (locally-indexed) rows: 956s startRow endRow 956s 1 10 7574 956s int [1:7586] 1 2 3 4 5 6 7 8 9 10 ... 956s DH segmentation rows: 956s startRow endRow 956s 1 10 7574 956s Segmenting DH signals...done 956s DH segmentation table: 956s dhStart dhEnd dhNbrOfLoci dhMean 956s 1 554484 120992603 2108 0.5116 956s startRow endRow 956s 1 10 7574 956s Rows: 956s [1] 1 956s TCN segmentation rows: 956s startRow endRow 956s 1 1 7586 956s TCN and DH segmentation rows: 956s startRow endRow 956s 1 1 7586 956s startRow endRow 956s 1 10 7574 956s NULL 956s TCN segmentation (expanded) rows: 956s startRow endRow 956s 1 1 7586 956s TCN and DH segmentation rows: 956s startRow endRow 956s 1 1 7586 956s 2 NA NA 956s 3 7587 10267 956s 4 10268 14658 956s startRow endRow 956s 1 10 7574 956s startRow endRow 956s 1 1 7586 956s Total CN segmentation table (expanded): 956s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 956s 1 1 554484 120992603 7586 1.3853 2108 2108 956s (TCN,DH) segmentation for one total CN segment: 956s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 956s 1 1 1 1 554484 120992603 7586 1.3853 2108 956s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 956s 1 2108 554484 120992603 2108 0.5116 956s Total CN segment #1 ([ 554484,1.20993e+08]) of 4...done 956s Total CN segment #2 ([1.20993e+08,1.4151e+08]) of 4... 956s Number of TCN loci in segment: 0 956s Locus data for TCN segment: 956s 'data.frame': 0 obs. of 9 variables: 956s $ chromosome: int 956s $ x : num 956s $ CT : num 956s $ betaT : num 956s $ betaTN : num 956s $ betaN : num 956s $ muN : num 956s $ index : int 956s $ rho : num 956s Number of loci: 0 956s Number of SNPs: 0 (NaN%) 956s Number of heterozygous SNPs: 0 (NaN%) 956s Chromosome: 1 956s Segmenting DH signals... 956s Segmenting by CBS... 956s Chromosome: NA 956s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 956s Segmenting by CBS...done 956s List of 4 956s $ data :'data.frame': 0 obs. of 4 variables: 956s ..$ chromosome: int(0) 956s ..$ x : num(0) 956s ..$ y : num(0) 956s ..$ index : int(0) 956s $ output :'data.frame': 0 obs. of 6 variables: 956s ..$ sampleName: chr(0) 956s ..$ chromosome: num(0) 956s ..$ start : num(0) 956s ..$ end : num(0) 956s ..$ nbrOfLoci : int(0) 956s ..$ mean : num(0) 956s $ segRows:'data.frame': 0 obs. of 2 variables: 956s ..$ startRow: int(0) 956s ..$ endRow : int(0) 956s $ params :List of 5 956s ..$ alpha : num 0.001 956s ..$ undo : num 0 956s ..$ joinSegments : logi TRUE 956s ..$ knownSegments:'data.frame': 0 obs. of 3 variables: 956s .. ..$ chromosome: int(0) 956s .. ..$ start : num(0) 956s .. ..$ end : num(0) 956s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 956s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 956s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.001 0 0.002 0 0 956s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 956s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 956s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 956s DH segmentation (locally-indexed) rows: 956s [1] startRow endRow 956s <0 rows> (or 0-length row.names) 956s int(0) 956s DH segmentation rows: 956s [1] startRow endRow 956s <0 rows> (or 0-length row.names) 956s Segmenting DH signals...done 956s DH segmentation table: 956s dhStart dhEnd dhNbrOfLoci dhMean 956s NA NA NA NA NA 956s startRow endRow 956s NA NA NA 956s Rows: 956s [1] 2 956s TCN segmentation rows: 956s startRow endRow 956s 2 NA NA 956s TCN and DH segmentation rows: 956s startRow endRow 956s 2 NA NA 956s startRow endRow 956s NA NA NA 956s startRow endRow 956s 1 1 7586 956s TCN segmentation (expanded) rows: 956s startRow endRow 956s 1 1 7586 956s 2 NA NA 956s TCN and DH segmentation rows: 956s startRow endRow 956s 1 1 7586 956s 2 NA NA 956s 3 7587 10267 956s 4 10268 14658 956s startRow endRow 956s 1 10 7574 956s 2 NA NA 956s startRow endRow 956s 1 1 7586 956s 2 NA NA 956s Total CN segmentation table (expanded): 956s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 956s 2 1 120992604 141510002 0 NA 0 0 956s (TCN,DH) segmentation for one total CN segment: 956s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 956s 2 2 1 1 120992604 141510002 0 NA 0 956s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 956s 2 0 NA NA NA NA 956s Total CN segment #2 ([1.20993e+08,1.4151e+08]) of 4...done 956s Total CN segment #3 ([1.4151e+08,1.8545e+08]) of 4... 956s Number of TCN loci in segment: 2681 956s Locus data for TCN segment: 956s 'data.frame': 2681 obs. of 9 variables: 956s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 956s $ x : num 1.43e+08 1.43e+08 1.43e+08 1.43e+08 1.44e+08 ... 956s $ CT : num 2.27 1.55 1.47 1.5 1.81 ... 956s $ betaT : num 0.34 0.55 0.048 0.813 0.575 ... 956s $ betaTN : num 0.441 0.629 -0.05 0.958 0.872 ... 956s $ betaN : num 0.3851 0.3933 0.0981 0.8552 0.7028 ... 956s $ muN : num 0.5 0.5 0 1 1 1 1 0.5 1 1 ... 956s $ index : int 7587 7588 7589 7590 7591 7592 7593 7594 7595 7596 ... 956s $ rho : num 0.117 0.258 NA NA NA ... 956s Number of loci: 2681 956s Number of SNPs: 777 (28.98%) 956s Number of heterozygous SNPs: 777 (100.00%) 956s Chromosome: 1 956s Segmenting DH signals... 956s Segmenting by CBS... 956s Chromosome: 1 956s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 957s Segmenting by CBS...done 957s List of 4 957s $ data :'data.frame': 2681 obs. of 4 variables: 957s ..$ chromosome: int [1:2681] 1 1 1 1 1 1 1 1 1 1 ... 957s ..$ x : num [1:2681] 1.43e+08 1.43e+08 1.43e+08 1.43e+08 1.44e+08 ... 957s ..$ y : num [1:2681] 0.117 0.258 NA NA NA ... 957s ..$ index : int [1:2681] 1 2 3 4 5 6 7 8 9 10 ... 957s $ output :'data.frame': 1 obs. of 6 variables: 957s ..$ sampleName: chr NA 957s ..$ chromosome: int 1 957s ..$ start : num 1.42e+08 957s ..$ end : num 1.85e+08 957s ..$ nbrOfLoci : int 777 957s ..$ mean : num 0.0973 957s $ segRows:'data.frame': 1 obs. of 2 variables: 957s ..$ startRow: int 1 957s ..$ endRow : int 2677 957s $ params :List of 5 957s ..$ alpha : num 0.001 957s ..$ undo : num 0 957s ..$ joinSegments : logi TRUE 957s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 957s .. ..$ chromosome: int 1 957s .. ..$ start : num 1.42e+08 957s .. ..$ end : num 1.85e+08 957s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 957s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 957s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.009 0 0.01 0 0 957s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 957s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 957s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 957s DH segmentation (locally-indexed) rows: 957s startRow endRow 957s 1 1 2677 957s int [1:2681] 7587 7588 7589 7590 7591 7592 7593 7594 7595 7596 ... 957s DH segmentation rows: 957s startRow endRow 957s 1 7587 10263 957s Segmenting DH signals...done 957s DH segmentation table: 957s dhStart dhEnd dhNbrOfLoci dhMean 957s 1 141510003 185449813 777 0.0973 957s startRow endRow 957s 1 7587 10263 957s Rows: 957s [1] 3 957s TCN segmentation rows: 957s startRow endRow 957s 3 7587 10267 957s TCN and DH segmentation rows: 957s startRow endRow 957s 3 7587 10267 957s startRow endRow 957s 1 7587 10263 957s startRow endRow 957s 1 1 7586 957s 2 NA NA 957s TCN segmentation (expanded) rows: 957s startRow endRow 957s 1 1 7586 957s 2 NA NA 957s 3 7587 10267 957s TCN and DH segmentation rows: 957s startRow endRow 957s 1 1 7586 957s 2 NA NA 957s 3 7587 10267 957s 4 10268 14658 957s startRow endRow 957s 1 10 7574 957s 2 NA NA 957s 3 7587 10263 957s startRow endRow 957s 1 1 7586 957s 2 NA NA 957s 3 7587 10267 957s Total CN segmentation table (expanded): 957s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 957s 3 1 141510003 185449813 2681 2.0689 777 777 957s (TCN,DH) segmentation for one total CN segment: 957s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 957s 3 3 1 1 141510003 185449813 2681 2.0689 777 957s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 957s 3 777 141510003 185449813 777 0.0973 957s Total CN segment #3 ([1.4151e+08,1.8545e+08]) of 4...done 957s Total CN segment #4 ([1.8545e+08,2.47137e+08]) of 4... 957s Number of TCN loci in segment: 4391 957s Locus data for TCN segment: 957s 'data.frame': 4391 obs. of 9 variables: 957s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 957s $ x : num 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 957s $ CT : num 2.93 2.15 2.82 2.93 2.46 ... 957s $ betaT : num 0.0811 0.5154 0.9473 0.3734 0.7506 ... 957s $ betaTN : num -0.169 0.609 1.028 0.525 0.968 ... 957s $ betaN : num 0.25 0.38 0.919 0.34 0.783 ... 957s $ muN : num 0 0.5 1 0.5 1 1 0 1 0 1 ... 957s $ index : int 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 957s $ rho : num NA 0.2186 NA 0.0503 NA ... 957s Number of loci: 4391 957s Number of SNPs: 1311 (29.86%) 957s Number of heterozygous SNPs: 1311 (100.00%) 957s Chromosome: 1 957s Segmenting DH signals... 957s Segmenting by CBS... 957s Chromosome: 1 957s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 957s Segmenting by CBS...done 957s List of 4 957s $ data :'data.frame': 4391 obs. of 4 variables: 957s ..$ chromosome: int [1:4391] 1 1 1 1 1 1 1 1 1 1 ... 957s ..$ x : num [1:4391] 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 957s ..$ y : num [1:4391] NA 0.2186 NA 0.0503 NA ... 957s ..$ index : int [1:4391] 1 2 3 4 5 6 7 8 9 10 ... 957s $ output :'data.frame': 1 obs. of 6 variables: 957s ..$ sampleName: chr NA 957s ..$ chromosome: int 1 957s ..$ start : num 1.85e+08 957s ..$ end : num 2.47e+08 957s ..$ nbrOfLoci : int 1311 957s ..$ mean : num 0.23 957s $ segRows:'data.frame': 1 obs. of 2 variables: 957s ..$ startRow: int 2 957s ..$ endRow : int 4388 957s $ params :List of 5 957s ..$ alpha : num 0.001 957s ..$ undo : num 0 957s ..$ joinSegments : logi TRUE 957s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 957s .. ..$ chromosome: int 1 957s .. ..$ start : num 1.85e+08 957s .. ..$ end : num 2.47e+08 957s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 957s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 957s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.018 0 0.017 0 0 957s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 957s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 957s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 957s DH segmentation (locally-indexed) rows: 957s startRow endRow 957s 1 2 4388 957s int [1:4391] 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 957s DH segmentation rows: 957s startRow endRow 957s 1 10269 14655 957s Segmenting DH signals...done 957s DH segmentation table: 957s dhStart dhEnd dhNbrOfLoci dhMean 957s 1 185449813 247137334 1311 0.2295 957s startRow endRow 957s 1 10269 14655 957s Rows: 957s [1] 4 957s TCN segmentation rows: 957s startRow endRow 957s 4 10268 14658 957s TCN and DH segmentation rows: 957s startRow endRow 957s 4 10268 14658 957s startRow endRow 957s 1 10269 14655 957s startRow endRow 957s 1 1 7586 957s 2 NA NA 957s 3 7587 10267 957s TCN segmentation (expanded) rows: 957s startRow endRow 957s 1 1 7586 957s 2 NA NA 957s 3 7587 10267 957s 4 10268 14658 957s TCN and DH segmentation rows: 957s startRow endRow 957s 1 1 7586 957s 2 NA NA 957s 3 7587 10267 957s 4 10268 14658 957s startRow endRow 957s 1 10 7574 957s 2 NA NA 957s 3 7587 10263 957s 4 10269 14655 957s startRow endRow 957s 1 1 7586 957s 2 NA NA 957s 3 7587 10267 957s 4 10268 14658 957s Total CN segmentation table (expanded): 957s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 957s 4 1 185449813 247137334 4391 2.6341 1311 1311 957s (TCN,DH) segmentation for one total CN segment: 957s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 957s 4 4 1 1 185449813 247137334 4391 2.6341 1311 957s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 957s 4 1311 185449813 247137334 1311 0.2295 957s Total CN segment #4 ([1.8545e+08,2.47137e+08]) of 4...done 957s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 957s 1 1 1 1 554484 120992603 7586 1.3853 2108 957s 2 1 2 1 120992604 141510002 0 NA 0 957s 3 1 3 1 141510003 185449813 2681 2.0689 777 957s 4 1 4 1 185449813 247137334 4391 2.6341 1311 957s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 957s 1 2108 554484 120992603 2108 0.5116 957s 2 0 NA NA NA NA 957s 3 777 141510003 185449813 777 0.0973 957s 4 1311 185449813 247137334 1311 0.2295 957s Calculating (C1,C2) per segment... 957s Calculating (C1,C2) per segment...done 957s Number of segments: 4 957s Segmenting paired tumor-normal signals using Paired PSCBS...done 957s Post-segmenting TCNs... 957s Number of segments: 4 957s Number of chromosomes: 1 957s [1] 1 957s Chromosome 1 ('chr01') of 1... 957s Rows: 957s [1] 1 2 3 4 957s Number of segments: 4 957s TCN segment #1 ('1') of 4... 957s Nothing todo. Only one DH segmentation. Skipping. 957s TCN segment #1 ('1') of 4...done 957s TCN segment #2 ('2') of 4... 957s Nothing todo. Only one DH segmentation. Skipping. 957s TCN segment #2 ('2') of 4...done 957s TCN segment #3 ('3') of 4... 957s Nothing todo. Only one DH segmentation. Skipping. 957s TCN segment #3 ('3') of 4...done 957s TCN segment #4 ('4') of 4... 957s Nothing todo. Only one DH segmentation. Skipping. 957s TCN segment #4 ('4') of 4...done 957s Chromosome 1 ('chr01') of 1...done 957s Update (C1,C2) per segment... 957s Update (C1,C2) per segment...done 957s Post-segmenting TCNs...done 957s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 957s 1 1 1 1 554484 120992603 7586 1.3853 2108 957s 2 1 2 1 120992604 141510002 0 NA 0 957s 3 1 3 1 141510003 185449813 2681 2.0689 777 957s 4 1 4 1 185449813 247137334 4391 2.6341 1311 957s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 957s 1 2108 554484 120992603 2108 0.5116 0.3382903 1.047010 957s 2 0 NA NA NA NA NA NA 957s 3 777 141510003 185449813 777 0.0973 0.9337980 1.135102 957s 4 1311 185449813 247137334 1311 0.2295 1.0147870 1.619313 957s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 957s 1 1 1 1 554484 120992603 7586 1.3853 2108 957s 2 1 2 1 120992604 141510002 0 NA 0 957s 3 1 3 1 141510003 185449813 2681 2.0689 777 957s 4 1 4 1 185449813 247137334 4391 2.6341 1311 957s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 957s 1 2108 554484 120992603 2108 0.5116 0.3382903 1.047010 957s 2 0 NA NA NA NA NA NA 957s 3 777 141510003 185449813 777 0.0973 0.9337980 1.135102 957s 4 1311 185449813 247137334 1311 0.2295 1.0147870 1.619313 957s > print(fit) 957s chromosome tcnId dhId start end tcnNbrOfLoci tcnMean tcnNbrOfSNPs 957s 1 1 1 1 554484 120992603 7586 1.3853 2108 957s 2 1 2 1 120992604 141510002 0 NA 0 957s 3 1 3 1 141510003 185449813 2681 2.0689 777 957s 4 1 4 1 185449813 247137334 4391 2.6341 1311 957s tcnNbrOfHets dhNbrOfLoci dhMean c1Mean c2Mean 957s 1 2108 2108 0.5116 0.3382903 1.047010 957s 2 0 NA NA NA NA 957s 3 777 777 0.0973 0.9337980 1.135102 957s 4 1311 1311 0.2295 1.0147870 1.619313 957s > 957s > # Plot results 957s > plotTracks(fit) 957s > 957s > # Sanity check 957s > stopifnot(nbrOfSegments(fit) == nSegs) 957s > 957s > 957s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 957s > # Bootstrap segment level estimates 957s > # (used by the AB caller, which, if skipped here, 957s > # will do it automatically) 957s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 957s > fit <- bootstrapTCNandDHByRegion(fit, B=B, verbose=-10) 957s Resample (TCN,DH) signals and re-estimate summaries for segment & changepoint... 957s Already done? 957s tcn_2.5% tcn_5% tcn_95% tcn_97.5% dh_2.5% dh_5% dh_95% dh_97.5% 957s FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE 957s c1_2.5% c1_5% c1_95% c1_97.5% c2_2.5% c2_5% c2_95% c2_97.5% 957s FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE 957s Bootstrapping (TCN,DH,C1,C2) segment mean levels... 957s Identifying heterozygous & homozygous SNPs and non-polymorphic loci... 957s Number of loci: 14658 957s Number of SNPs: 4196 957s Number of non-SNPs: 10462 957s Identifying heterozygous & homozygous SNPs and non-polymorphic loci...done 957s num [1:4, 1:100, 1:4] NA NA NA NA NA NA NA NA NA NA ... 957s - attr(*, "dimnames")=List of 3 957s ..$ : NULL 957s ..$ : NULL 957s ..$ : chr [1:4] "tcn" "dh" "c1" "c2" 957s Segment #1 (chr 1, tcnId=1, dhId=1) of 4... 957s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 957s 1 1 1 1 554484 120992603 7586 1.3853 2108 957s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 957s 1 2108 554484 120992603 2108 0.5116 0.3382903 1.04701 957s Number of TCNs: 7586 957s Number of DHs: 2108 957s int [1:7586] 1 2 3 4 5 6 7 8 9 10 ... 957s int [1:14658] 1 2 3 4 5 6 7 8 9 10 ... 957s int [1:7586] 1 2 3 4 5 6 7 8 9 10 ... 957s Identify loci used to bootstrap DH means... 957s Heterozygous SNPs to resample for DH: 957s int [1:2108] 10 12 24 28 31 33 34 39 46 48 ... 957s Identify loci used to bootstrap DH means...done 957s Identify loci used to bootstrap TCN means... 957s SNPs: 957s int [1:2108] 10 12 24 28 31 33 34 39 46 48 ... 957s Non-polymorphic loci: 957s int [1:5478] 1 2 3 4 5 6 7 8 9 11 ... 957s Heterozygous SNPs to resample for TCN: 957s int [1:2108] 10 12 24 28 31 33 34 39 46 48 ... 957s Homozygous SNPs to resample for TCN: 957s int(0) 957s Non-polymorphic loci to resample for TCN: 957s int [1:5478] 1 2 3 4 5 6 7 8 9 11 ... 957s Heterozygous SNPs with non-DH to resample for TCN: 957s int(0) 957s Loci to resample for TCN: 957s int [1:7586] 1 2 3 4 5 6 7 8 9 10 ... 957s Identify loci used to bootstrap TCN means...done 957s Number of (#hets, #homs, #nonSNPs): (2108,0,5478) 957s Bootstrapping while preserving (#hets, #homs, #nonSNPs)... 957s Number of bootstrap samples: 100 957s Bootstrapping while preserving (#hets, #homs, #nonSNPs)...done 957s Segment #1 (chr 1, tcnId=1, dhId=1) of 4...done 957s Segment #2 (chr 1, tcnId=2, dhId=1) of 4... 957s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 957s 2 1 2 1 120992604 141510002 0 NA 0 957s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 957s 2 0 NA NA 0 NA NA NA 957s Number of TCNs: 0 957s Number of DHs: 0 957s int 0 957s int [1:14658] 1 2 3 4 5 6 7 8 9 10 ... 957s int(0) 957s Identify loci used to bootstrap DH means... 957s Heterozygous SNPs to resample for DH: 957s int 0 957s Identify loci used to bootstrap DH means...done 957s Identify loci used to bootstrap TCN means... 957s SNPs: 957s int(0) 957s Non-polymorphic loci: 957s int(0) 957s Heterozygous SNPs to resample for TCN: 957s int(0) 957s Homozygous SNPs to resample for TCN: 957s int(0) 957s Non-polymorphic loci to resample for TCN: 957s int(0) 957s Heterozygous SNPs with non-DH to resample for TCN: 957s int(0) 957s Loci to resample for TCN: 957s int(0) 957s Identify loci used to bootstrap TCN means...done 957s Number of (#hets, #homs, #nonSNPs): (0,0,0) 957s Bootstrapping while preserving (#hets, #homs, #nonSNPs)... 957s Number of bootstrap samples: 100 957s Bootstrapping while preserving (#hets, #homs, #nonSNPs)...done 957s Segment #2 (chr 1, tcnId=2, dhId=1) of 4...done 957s Segment #3 (chr 1, tcnId=3, dhId=1) of 4... 957s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 957s 3 1 3 1 141510003 185449813 2681 2.0689 777 957s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 957s 3 777 141510003 185449813 777 0.0973 0.933798 1.135102 957s Number of TCNs: 2681 957s Number of DHs: 777 957s int [1:2681] 7587 7588 7589 7590 7591 7592 7593 7594 7595 7596 ... 957s int [1:14658] 1 2 3 4 5 6 7 8 9 10 ... 957s int [1:2681] 7587 7588 7589 7590 7591 7592 7593 7594 7595 7596 ... 957s Identify loci used to bootstrap DH means... 957s Heterozygous SNPs to resample for DH: 957s int [1:777] 7587 7588 7594 7614 7616 7626 7627 7628 7635 7638 ... 957s Identify loci used to bootstrap DH means...done 957s Identify loci used to bootstrap TCN means... 957s SNPs: 957s int [1:777] 7587 7588 7594 7614 7616 7626 7627 7628 7635 7638 ... 957s Non-polymorphic loci: 957s int [1:1904] 7589 7590 7591 7592 7593 7595 7596 7597 7598 7599 ... 957s Heterozygous SNPs to resample for TCN: 957s int [1:777] 7587 7588 7594 7614 7616 7626 7627 7628 7635 7638 ... 957s Homozygous SNPs to resample for TCN: 957s int(0) 957s Non-polymorphic loci to resample for TCN: 957s int [1:1904] 7589 7590 7591 7592 7593 7595 7596 7597 7598 7599 ... 957s Heterozygous SNPs with non-DH to resample for TCN: 957s int(0) 957s Loci to resample for TCN: 957s int [1:2681] 7587 7588 7589 7590 7591 7592 7593 7594 7595 7596 ... 957s Identify loci used to bootstrap TCN means...done 957s Number of (#hets, #homs, #nonSNPs): (777,0,1904) 957s Bootstrapping while preserving (#hets, #homs, #nonSNPs)... 957s Number of bootstrap samples: 100 957s Bootstrapping while preserving (#hets, #homs, #nonSNPs)...done 957s Segment #3 (chr 1, tcnId=3, dhId=1) of 4...done 957s Segment #4 (chr 1, tcnId=4, dhId=1) of 4... 957s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 957s 4 1 4 1 185449813 247137334 4391 2.6341 1311 957s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 957s 4 1311 185449813 247137334 1311 0.2295 1.014787 1.619313 957s Number of TCNs: 4391 957s Number of DHs: 1311 957s int [1:4391] 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 957s int [1:14658] 1 2 3 4 5 6 7 8 9 10 ... 957s int [1:4391] 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 957s Identify loci used to bootstrap DH means... 957s Heterozygous SNPs to resample for DH: 957s int [1:1311] 10269 10271 10281 10282 10283 10293 10295 10297 10300 10302 ... 957s Identify loci used to bootstrap DH means...done 957s Identify loci used to bootstrap TCN means... 957s SNPs: 957s int [1:1311] 10269 10271 10281 10282 10283 10293 10295 10297 10300 10302 ... 957s Non-polymorphic loci: 957s int [1:3080] 10268 10270 10272 10273 10274 10275 10276 10277 10278 10279 ... 957s Heterozygous SNPs to resample for TCN: 957s int [1:1311] 10269 10271 10281 10282 10283 10293 10295 10297 10300 10302 ... 957s Homozygous SNPs to resample for TCN: 957s int(0) 957s Non-polymorphic loci to resample for TCN: 957s int [1:3080] 10268 10270 10272 10273 10274 10275 10276 10277 10278 10279 ... 957s Heterozygous SNPs with non-DH to resample for TCN: 957s int(0) 957s Loci to resample for TCN: 957s int [1:4391] 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 957s Identify loci used to bootstrap TCN means...done 957s Number of (#hets, #homs, #nonSNPs): (1311,0,3080) 957s Bootstrapping while preserving (#hets, #homs, #nonSNPs)... 957s Number of bootstrap samples: 100 957s Bootstrapping while preserving (#hets, #homs, #nonSNPs)...done 957s Segment #4 (chr 1, tcnId=4, dhId=1) of 4...done 957s Bootstrapped segment mean levels 957s num [1:4, 1:100, 1:4] 1.39 NA 2.08 2.63 1.38 ... 957s - attr(*, "dimnames")=List of 3 957s ..$ : NULL 957s ..$ : NULL 957s ..$ : chr [1:4] "tcn" "dh" "c1" "c2" 957s Calculating (C1,C2) mean levels from (TCN,DH) mean levels... 957s num [1:4, 1:100, 1:4] 1.39 NA 2.08 2.63 1.38 ... 957s - attr(*, "dimnames")=List of 3 957s ..$ : NULL 957s ..$ : NULL 957s ..$ : chr [1:4] "tcn" "dh" "c1" "c2" 957s Calculating (C1,C2) mean levels from (TCN,DH) mean levels...done 957s Calculating polar (alpha,radius,manhattan) for change points... 957s num [1:3, 1:100, 1:2] NA NA -0.0752 NA NA ... 957s - attr(*, "dimnames")=List of 3 957s ..$ : NULL 957s ..$ : NULL 957s ..$ : chr [1:2] "c1" "c2" 957s Bootstrapped change points 957s num [1:3, 1:100, 1:5] NA NA -1.73 NA NA ... 957s - attr(*, "dimnames")=List of 3 957s ..$ : NULL 957s ..$ : NULL 957s ..$ : chr [1:5] "alpha" "radius" "manhattan" "d1" ... 957s Calculating polar (alpha,radius,manhattan) for change points...done 957s Bootstrapping (TCN,DH,C1,C2) segment mean levels...done 957s Summarizing bootstrapped segment (‘tcn’, ‘dh’, ‘c1’, ‘c2’) data... 957s num [1:4, 1:4, 1:4] NA NA NA NA NA NA NA NA NA NA ... 957s - attr(*, "dimnames")=List of 3 957s ..$ : NULL 957s ..$ : chr [1:4] "2.5%" "5%" "95%" "97.5%" 957s ..$ : chr [1:4] "tcn" "dh" "c1" "c2" 957s Field #1 ('tcn') of 4... 957s Segment #1 of 4... 957s Segment #1 of 4...done 957s Segment #2 of 4... 957s Segment #2 of 4...done 957s Segment #3 of 4... 957s Segment #3 of 4...done 957s Segment #4 of 4... 957s Segment #4 of 4...done 957s Field #1 ('tcn') of 4...done 957s Field #2 ('dh') of 4... 957s Segment #1 of 4... 957s Segment #1 of 4...done 957s Segment #2 of 4... 957s Segment #2 of 4...done 957s Segment #3 of 4... 957s Segment #3 of 4...done 957s Segment #4 of 4... 957s Segment #4 of 4...done 957s Field #2 ('dh') of 4...done 957s Field #3 ('c1') of 4... 957s Segment #1 of 4... 957s Segment #1 of 4...done 957s Segment #2 of 4... 957s Segment #2 of 4...done 957s Segment #3 of 4... 957s Segment #3 of 4...done 957s Segment #4 of 4... 957s Segment #4 of 4...done 957s Field #3 ('c1') of 4...done 957s Field #4 ('c2') of 4... 957s Segment #1 of 4... 957s Segment #1 of 4...done 957s Segment #2 of 4... 957s Segment #2 of 4...done 957s Segment #3 of 4... 957s Segment #3 of 4...done 957s Segment #4 of 4... 957s Segment #4 of 4...done 957s Field #4 ('c2') of 4...done 957s Bootstrap statistics 957s num [1:4, 1:4, 1:4] 1.38 NA 2.06 2.63 1.38 ... 957s - attr(*, "dimnames")=List of 3 957s ..$ : NULL 957s ..$ : chr [1:4] "2.5%" "5%" "95%" "97.5%" 957s ..$ : chr [1:4] "tcn" "dh" "c1" "c2" 957s Statistical sanity checks (iff B >= 100)... 957s Available summaries: 2.5%, 5%, 95%, 97.5% 957s Available quantiles: 0.025, 0.05, 0.95, 0.975 957s num [1:4, 1:4, 1:4] 1.38 NA 2.06 2.63 1.38 ... 957s - attr(*, "dimnames")=List of 3 957s ..$ : NULL 957s ..$ : chr [1:4] "2.5%" "5%" "95%" "97.5%" 957s ..$ : chr [1:4] "tcn" "dh" "c1" "c2" 957s Field #1 ('tcn') of 4... 957s Seg 1. mean=1.3853, range=[1.37909,1.39287], n=7586 957s Seg 2. mean=NA, range=[NA,NA], n=0 957s Seg 3. mean=2.0689, range=[2.05903,2.079], n=2681 957s Seg 4. mean=2.6341, range=[2.62504,2.64649], n=4391 957s Field #1 ('tcn') of 4...done 957s Field #2 ('dh') of 4... 957s Seg 1. mean=0.5116, range=[0.502148,0.519941], n=2108 957s Seg 2. mean=NA, range=[NA,NA], n=NA 957s Seg 3. mean=0.0973, range=[0.0906366,0.105818], n=777 957s Seg 4. mean=0.2295, range=[0.222919,0.237005], n=1311 957s Field #2 ('dh') of 4...done 957s Field #3 ('c1') of 4... 957s Seg 1. mean=0.33829, range=[0.332209,0.345936], n=2108 957s Seg 2. mean=NA, range=[NA,NA], n=NA 957s Seg 3. mean=0.933798, range=[0.924112,0.941776], n=777 957s Seg 4. mean=1.01479, range=[1.00381,1.02461], n=1311 957s Field #3 ('c1') of 4...done 957s Field #4 ('c2') of 4... 957s Seg 1. mean=1.04701, range=[1.03882,1.05318], n=2108 957s Seg 2. mean=NA, range=[NA,NA], n=NA 957s Seg 3. mean=1.1351, range=[1.12454,1.1465], n=777 957s Seg 4. mean=1.61931, range=[1.60862,1.63328], n=1311 957s Field #4 ('c2') of 4...done 957s Statistical sanity checks (iff B >= 100)...done 957s Summarizing bootstrapped segment (‘tcn’, ‘dh’, ‘c1’, ‘c2’) data...done 957s Summarizing bootstrapped changepoint (‘alpha’, ‘radius’, ‘manhattan’, ‘d1’, ‘d2’) data... 957s num [1:3, 1:4, 1:5] NA NA NA NA NA NA NA NA NA NA ... 957s - attr(*, "dimnames")=List of 3 957s ..$ : NULL 957s ..$ : chr [1:4] "2.5%" "5%" "95%" "97.5%" 957s ..$ : chr [1:5] "alpha" "radius" "manhattan" "d1" ... 957s Field #1 ('alpha') of 5... 957s Changepoint #1 of 3... 957s Changepoint #1 of 3...done 957s Changepoint #2 of 3... 957s Changepoint #2 of 3...done 957s Changepoint #3 of 3... 957s Changepoint #3 of 3...done 957s Field #1 ('alpha') of 5...done 957s Field #2 ('radius') of 5... 957s Changepoint #1 of 3... 957s Changepoint #1 of 3...done 957s Changepoint #2 of 3... 957s Changepoint #2 of 3...done 957s Changepoint #3 of 3... 957s Changepoint #3 of 3...done 957s Field #2 ('radius') of 5...done 957s Field #3 ('manhattan') of 5... 957s Changepoint #1 of 3... 957s Changepoint #1 of 3...done 957s Changepoint #2 of 3... 957s Changepoint #2 of 3...done 957s Changepoint #3 of 3... 957s Changepoint #3 of 3...done 957s Field #3 ('manhattan') of 5...done 957s Field #4 ('d1') of 5... 957s Changepoint #1 of 3... 957s Changepoint #1 of 3...done 957s Changepoint #2 of 3... 957s Changepoint #2 of 3...done 957s Changepoint #3 of 3... 957s Changepoint #3 of 3...done 957s Field #4 ('d1') of 5...done 957s Field #5 ('d2') of 5... 957s Changepoint #1 of 3... 957s Changepoint #1 of 3...done 957s Changepoint #2 of 3... 957s Changepoint #2 of 3...done 957s Changepoint #3 of 3... 957s Changepoint #3 of 3...done 957s Field #5 ('d2') of 5...done 957s Bootstrap statistics 957s num [1:3, 1:4, 1:5] NA NA -1.77 NA NA ... 957s - attr(*, "dimnames")=List of 3 957s ..$ : NULL 957s ..$ : chr [1:4] "2.5%" "5%" "95%" "97.5%" 957s ..$ : chr [1:5] "alpha" "radius" "manhattan" "d1" ... 957s Summarizing bootstrapped changepoint (‘alpha’, ‘radius’, ‘manhattan’, ‘d1’, ‘d2’) data...done 957s Resample (TCN,DH) signals and re-estimate summaries for segment & changepoint...done 957s > print(fit) 957s chromosome tcnId dhId start end tcnNbrOfLoci tcnMean tcnNbrOfSNPs 957s 1 1 1 1 554484 120992603 7586 1.3853 2108 957s 2 1 2 1 120992604 141510002 0 NA 0 957s 3 1 3 1 141510003 185449813 2681 2.0689 777 957s 4 1 4 1 185449813 247137334 4391 2.6341 1311 957s tcnNbrOfHets dhNbrOfLoci dhMean c1Mean c2Mean 957s 1 2108 2108 0.5116 0.3382903 1.047010 957s 2 0 NA NA NA NA 957s 3 777 777 0.0973 0.9337980 1.135102 957s 4 1311 1311 0.2295 1.0147870 1.619313 957s > plotTracks(fit) 957s > 957s > 957s > 957s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 957s > # Calling segments with run of homozygosity (ROH) 957s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 957s > fit <- callROH(fit, verbose=-10) 957s Calling ROH... 957s Segment #1 of 4... 957s Calling ROH for a single segment... 957s Number of SNPs: 7586 957s Calling ROH for a single segment...done 957s Segment #1 of 4...done 957s Segment #2 of 4... 957s Calling ROH for a single segment... 957s Number of SNPs: 0 957s Calling ROH for a single segment...done 957s Segment #2 of 4...done 957s Segment #3 of 4... 957s Calling ROH for a single segment... 957s Number of SNPs: 2681 957s Calling ROH for a single segment...done 957s Segment #3 of 4...done 957s Segment #4 of 4... 957s Calling ROH for a single segment... 957s Number of SNPs: 4391 957s Calling ROH for a single segment...done 957s Segment #4 of 4...done 957s ROH calls: 957s logi [1:4] FALSE NA FALSE FALSE 958s Mode FALSE NA's 958s logical 3 1 958s > print(fit) 958s chromosome tcnId dhId start end tcnNbrOfLoci tcnMean tcnNbrOfSNPs 958s 1 1 1 1 554484 120992603 7586 1.3853 2108 958s 2 1 2 1 120992604 141510002 0 NA 0 958s 3 1 3 1 141510003 185449813 2681 2.0689 777 958s 4 1 4 1 185449813 247137334 4391 2.6341 1311 958s tcnNbrOfHets dhNbrOfLoci dhMean c1Mean c2Mean rohCall 958s 1 2108 2108 0.5116 0.3382903 1.047010 FALSE 958s 2 0 NA NA NA NA NA 958s 3 777 777 0.0973 0.9337980 1.135102 FALSE 958s 4 1311 1311 0.2295 1.0147870 1.619313 FALSE 958s > plotTracks(fit) 958s Calling ROH...done 958s > 958s > 958s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 958s > # Estimate background 958s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 958s > kappa <- estimateKappa(fit, verbose=-10) 958s > print(kappa) 958s [1] 0.3382903 958s > ## [1] 0.226011 958s > 958s > 958s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 958s > # Calling segments in allelic balance (AB) 958s > # NOTE: Ideally, this should be done on whole-genome data 958s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 958s > # Explicitly estimate the threshold in DH for calling AB 958s > # (which be done by default by the caller, if skipped here) 958s > deltaAB <- estimateDeltaAB(fit, flavor="qq(DH)", verbose=-10) 958s Estimate global background (including normal contamination and more)... 958s Number of segments: 3 958s Estimating threshold Delta0.5 from the empirical density of C1:s... 958s adjust: 1 958s minDensity: 0.2 958s ploidy: 2 958s All peaks: 958s type x density 958s 1 peak 0.3362194 1.101242 958s 3 peak 0.9811492 1.065635 958s C1=0 and C1=1 peaks: 958s type x density 958s 1 peak 0.3362194 1.101242 958s 3 peak 0.9811492 1.065635 958s Estimate of Delta0.5: 0.65868427808456 958s Estimating threshold Delta0.5 from the empirical density of C1:s...done 958s Number of segments with C1 < Delta0.5: 1 958s Estimate of kappa: 0.33829026 958s Estimate global background (including normal contamination and more)...done 958s Warning message: 958s In density.default(c1, weights = weights, adjust = adjust, from = from, : 958s Selecting bandwidth *not* using 'weights' 958s Estimating DH threshold for calling allelic imbalances... 958s flavor: qq(DH) 958s scale: 1 958s Estimating DH threshold for AB caller... 958s quantile #1: 0.05 958s Symmetric quantile #2: 0.9 958s Number of segments: 3 958s Weighted 5% quantile of DH: 0.257710 958s Number of segments with small DH: 2 958s Number of data points: 7072 958s Number of finite data points: 2088 958s Estimate of (1-0.9):th and 50% quantiles: (0.0310411,0.163658) 958s Estimate of 0.9:th "symmetric" quantile: 0.296275 958s > if (Sys.getenv("_R_CHECK_FULL_") == "") { 958s + # Ad hoc workaround for not utilizing all of the data 958s + # in the test, which results in a poor estimate 958s + deltaAB <- 0.165 958s + } 958s > print(deltaAB) 958s [1] 0.165 958s > ## [1] 0.1657131 958s > 958s > fit <- callAB(fit, delta=deltaAB, verbose=-10) 958s Estimating DH threshold for AB caller...done 958s Estimated delta: 0.296 958s Estimating DH threshold for calling allelic imbalances...done 958s Calling segments of allelic balance from one-sided DH bootstrap confidence intervals... 958s delta (offset adjusting for bias in DH): 0.165 958s alpha (CI quantile; significance level): 0.05 958s Calling segments... 958s Number of segments called allelic balance (AB): 1 (25.00%) of 4 958s Calling segments...done 958s Calling segments of allelic balance from one-sided DH bootstrap confidence intervals...done 958s > print(fit) 958s chromosome tcnId dhId start end tcnNbrOfLoci tcnMean tcnNbrOfSNPs 958s 1 1 1 1 554484 120992603 7586 1.3853 2108 958s 2 1 2 1 120992604 141510002 0 NA 0 958s 3 1 3 1 141510003 185449813 2681 2.0689 777 958s 4 1 4 1 185449813 247137334 4391 2.6341 1311 958s tcnNbrOfHets dhNbrOfLoci dhMean c1Mean c2Mean rohCall abCall 958s 1 2108 2108 0.5116 0.3382903 1.047010 FALSE FALSE 958s 2 0 NA NA NA NA NA NA 958s 3 777 777 0.0973 0.9337980 1.135102 FALSE TRUE 958s 4 1311 1311 0.2295 1.0147870 1.619313 FALSE FALSE 958s > plotTracks(fit) 958s > 958s > # Even if not explicitly specified, the estimated 958s > # threshold parameter is returned by the caller 958s > stopifnot(fit$params$deltaAB == deltaAB) 958s > 958s > 958s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 958s > # Calling segments in loss-of-heterozygosity (LOH) 958s > # NOTE: Ideally, this should be done on whole-genome data 958s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 958s > # Explicitly estimate the threshold in C1 for calling LOH 958s > # (which be done by default by the caller, if skipped here) 958s > deltaLOH <- estimateDeltaLOH(fit, flavor="minC1|nonAB", verbose=-10) 958s Estimating DH threshold for calling LOH... 958s flavor: minC1|nonAB 958s Estimating DH threshold for calling LOH as the midpoint between guessed C1=0 and C1=1... 958s Argument 'midpoint': 0.5 958s Number of segments: 4 958s Number of segments in allelic balance: 1 (25.0%) of 4 958s Number of segments not in allelic balance: 2 (50.0%) of 4 958s Number of segments in allelic balance and TCN <= 3.00: 1 (25.0%) of 4 958s C: 2.07 958s Corrected C1 (=C/2): 1.03 958s Number of DHs: 777 958s Weights: 1 958s Weighted median of (corrected) C1 in allelic balance: 1.034 958s Smallest C1 among segments not in allelic balance: 0.338 958s There are 1 segments with in total 2108 heterozygous SNPs with this level. 958s Midpoint between the two: 0.686 958s Estimating DH threshold for calling LOH as the midpoint between guessed C1=0 and C1=1...done 958s delta: 0.686 958s > print(deltaLOH) 958s [1] 0.6863701 958s > ## [1] 0.625175 958s > 958s > fit <- callLOH(fit, delta=deltaLOH, verbose=-10) 958s Estimating DH threshold for calling LOH...done 958s Calling segments of allelic balance from one-sided DH bootstrap confidence intervals... 958s delta (offset adjusting for bias in C1): 0.68637013 958s alpha (CI quantile; significance level): 0.05 958s Calling segments... 958s Number of segments called low C1 (LowC1, "LOH_C1"): 1 (25.00%) of 4 958s Calling segments...done 958s Calling segments of allelic balance from one-sided DH bootstrap confidence intervals...done 958s > print(fit) 958s chromosome tcnId dhId start end tcnNbrOfLoci tcnMean tcnNbrOfSNPs 958s 1 1 1 1 554484 120992603 7586 1.3853 2108 958s 2 1 2 1 120992604 141510002 0 NA 0 958s 3 1 3 1 141510003 185449813 2681 2.0689 777 958s 4 1 4 1 185449813 247137334 4391 2.6341 1311 958s tcnNbrOfHets dhNbrOfLoci dhMean c1Mean c2Mean rohCall abCall lohCall 958s 1 2108 2108 0.5116 0.3382903 1.047010 FALSE FALSE TRUE 958s 2 0 NA NA NA NA NA NA NA 958s 3 777 777 0.0973 0.9337980 1.135102 FALSE TRUE FALSE 958s 4 1311 1311 0.2295 1.0147870 1.619313 FALSE FALSE FALSE 958s > plotTracks(fit) 958s > 958s > # Even if not explicitly specified, the estimated 958s > # threshold parameter is returned by the caller 958s > stopifnot(fit$params$deltaLOH == deltaLOH) 958s > 958s > 958s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 958s > # Calling segments that are gained, copy neutral, and lost 958s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 958s > fit <- callGNL(fit, verbose=-10) 958s Calling gain, neutral, and loss based TCNs of AB segments... 958s Calling neutral TCNs... 958s callCopyNeutralByTCNofAB... 958s Alpha: 0.05 958s Delta CN: 0.33085487 958s Calling copy-neutral segments... 958s Retrieve TCN confidence intervals for all segments... 958s Interval: [0.025,0.975] 958s Retrieve TCN confidence intervals for all segments...done 958s Estimating TCN confidence interval of copy-neutral AB segments... 958s calcStatsForCopyNeutralABs... 958s Identifying copy neutral AB segments... 958s Number of AB segments: 1 958s Identifying segments that are copy neutral states... 958s Number of segments in allelic balance: 1 958s Identifying segments that are copy neutral states...done 958s Number of copy-neutral AB segments: 1 958s Extracting all copy neutral AB segments across all chromosomes into one big segment... 958s chromosome tcnId dhId start end tcnNbrOfLoci tcnMean tcnNbrOfSNPs 958s 3 1 3 1 141510003 185449813 2681 2.0689 777 958s tcnNbrOfHets dhNbrOfLoci dhMean c1Mean c2Mean rohCall abCall lohCall 958s 3 777 777 0.0973 0.933798 1.135102 FALSE TRUE FALSE 958s Extracting all copy neutral AB segments across all chromosomes into one big segment...done 958s Identifying copy neutral AB segments...done 958s Bootstrap the identified copy-neutral states... 958s Bootstrap the identified copy-neutral states...done 958s tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets dhNbrOfLoci dhMean c1Mean 958s 3 2681 2.0689 777 777 777 0.0973 0.933798 958s c2Mean tcn_2.5% tcn_5% tcn_95% tcn_97.5% dh_2.5% dh_5% dh_95% 958s 3 1.135102 2.055164 2.057694 2.078831 2.081454 0.08974138 0.09080508 0.1035891 958s dh_97.5% c1_2.5% c1_5% c1_95% c1_97.5% c2_2.5% c2_5% c2_95% 958s 3 0.1050478 0.923788 0.925412 0.9417056 0.9433752 1.124908 1.126631 1.143571 958s c2_97.5% 958s 3 1.145214 958s calcStatsForCopyNeutralABs...done 958s Bootstrap statistics for copy-neutral AB segments: 958s tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets dhNbrOfLoci dhMean c1Mean 958s 3 2681 2.0689 777 777 777 0.0973 0.933798 958s c2Mean tcn_2.5% tcn_5% tcn_95% tcn_97.5% dh_2.5% dh_5% dh_95% 958s 3 1.135102 2.055164 2.057694 2.078831 2.081454 0.08974138 0.09080508 0.1035891 958s dh_97.5% c1_2.5% c1_5% c1_95% c1_97.5% c2_2.5% c2_5% c2_95% 958s 3 0.1050478 0.923788 0.925412 0.9417056 0.9433752 1.124908 1.126631 1.143571 958s c2_97.5% 958s 3 1.145214 958s [1] "TCN statistics:" 958s tcnMean tcn_2.5% tcn_5% tcn_95% tcn_97.5% 958s 2.068900 2.055164 2.057694 2.078831 2.081454 958s 95%-confidence interval of TCN mean for the copy-neutral state: [2.05516,2.08145] (mean=2.0689) 958s Estimating TCN confidence interval of copy-neutral AB segments...done 958s Identify all copy-neutral segments... 958s DeltaCN: +/-0.330855 958s Call ("acceptance") region: [1.72431,2.41231] 958s Total number of segments: 4 958s Number of segments called allelic balance: 1 958s Number of segments called copy neutral: 1 958s Number of AB segments called copy neutral: 1 958s Number of non-AB segments called copy neutral: 0 958s Identify all copy-neutral segments...done 958s Calling copy-neutral segments...done 958s callCopyNeutralByTCNofAB...done 958s Calling neutral TCNs...done 958s Number of NTCN calls: 1 (25.00%) of 4 958s Mean TCN of AB segments: 2.06831 958s Calling loss... 958s Number of loss calls: 1 (25.00%) of 4 958s Calling loss...done 958s Calling gain... 958s Number of loss calls: 1 (25.00%) of 4 958s Calling gain...done 958s Calling gain, neutral, and loss based TCNs of AB segments...done 958s Warning message: 958s In density.default(c1, weights = weights, adjust = adjust, from = from, : 958s Selecting bandwidth *not* using 'weights' 958s > print(fit) 958s chromosome tcnId dhId start end tcnNbrOfLoci tcnMean tcnNbrOfSNPs 958s 1 1 1 1 554484 120992603 7586 1.3853 2108 958s 2 1 2 1 120992604 141510002 0 NA 0 958s 3 1 3 1 141510003 185449813 2681 2.0689 777 958s 4 1 4 1 185449813 247137334 4391 2.6341 1311 958s tcnNbrOfHets dhNbrOfLoci dhMean c1Mean c2Mean rohCall abCall lohCall 958s 1 2108 2108 0.5116 0.3382903 1.047010 FALSE FALSE TRUE 958s 2 0 NA NA NA NA NA NA NA 958s 3 777 777 0.0973 0.9337980 1.135102 FALSE TRUE FALSE 958s 4 1311 1311 0.2295 1.0147870 1.619313 FALSE FALSE FALSE 958s ntcnCall lossCall gainCall 958s 1 FALSE TRUE FALSE 958s 2 NA NA NA 958s 3 TRUE FALSE FALSE 958s 4 FALSE FALSE TRUE 958s > plotTracks(fit) 959s > 959s Start: segmentByPairedPSCBS,futures.R 959s 959s R version 4.5.2 (2025-10-31) -- "[Not] Part in a Rumble" 959s Copyright (C) 2025 The R Foundation for Statistical Computing 959s Platform: powerpc64le-unknown-linux-gnu 959s 959s R is free software and comes with ABSOLUTELY NO WARRANTY. 959s You are welcome to redistribute it under certain conditions. 959s Type 'license()' or 'licence()' for distribution details. 959s 959s R is a collaborative project with many contributors. 959s Type 'contributors()' for more information and 959s 'citation()' on how to cite R or R packages in publications. 959s 959s Type 'demo()' for some demos, 'help()' for on-line help, or 959s 'help.start()' for an HTML browser interface to help. 959s Type 'q()' to quit R. 959s 959s > library(PSCBS) 959s > library(utils) 959s PSCBS v0.68.0 (2025-04-18 19:40:02 UTC) successfully loaded. See ?PSCBS for help. 959s > 959s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 959s > # Load SNP microarray data 959s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 959s > data <- PSCBS::exampleData("paired.chr01") 959s > 959s > 959s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 959s > # Paired PSCBS segmentation 959s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 959s > # Drop single-locus outliers 959s > dataS <- dropSegmentationOutliers(data) 959s > 959s > # Run light-weight tests by default 959s > if (Sys.getenv("_R_CHECK_FULL_") == "") { 959s + # Use only every 5th data point 959s + dataS <- dataS[seq(from=1, to=nrow(data), by=5),] 959s + # Number of segments (for assertion) 959s + nSegs <- 4L 959s + } else { 959s + # Full tests 959s + nSegs <- 11L 959s + } 959s > 959s > str(dataS) 959s 'data.frame': 14670 obs. of 6 variables: 959s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 959s $ x : int 1145994 2941694 3710825 4240737 4276892 4464544 4714611 5095111 5034491 5158416 ... 959s $ CT : num 1.63 1.4 1.41 1.17 1.16 ... 959s $ betaT : num 0.7574 0.169 0.2357 0.2604 0.0576 ... 959s $ CN : num 2.36 2.13 2.26 2.01 2.32 ... 959s $ betaN : num 0.8274 0.5072 0.1671 0.1609 0.0421 ... 959s > 959s > 959s > ## Create multiple chromosomes 959s > data <- list() 959s > for (cc in 1:3) { 959s + dataS$chromosome <- cc 959s + data[[cc]] <- dataS 959s + } 959s > data <- Reduce(rbind, data) 959s > str(data) 959s 'data.frame': 44010 obs. of 6 variables: 959s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 959s $ x : int 1145994 2941694 3710825 4240737 4276892 4464544 4714611 5095111 5034491 5158416 ... 959s $ CT : num 1.63 1.4 1.41 1.17 1.16 ... 959s $ betaT : num 0.7574 0.169 0.2357 0.2604 0.0576 ... 959s $ CN : num 2.36 2.13 2.26 2.01 2.32 ... 959s $ betaN : num 0.8274 0.5072 0.1671 0.1609 0.0421 ... 959s > 959s > 959s > message("*** segmentByPairedPSCBS() via futures ...") 959s > 959s > library("future") 959s *** segmentByPairedPSCBS() via futures ... 959s > oplan <- plan() 959s > 959s > strategies <- c("sequential", "multisession") 959s > 959s > ## Test 'future.batchtools' futures? 959s > pkg <- "future.batchtools" 959s > if (require(pkg, character.only=TRUE)) { 959s + strategies <- c(strategies, "batchtools_local") 959s + } 959s Loading required package: future.batchtools 959s > 959s > message("Future strategies to test: ", paste(sQuote(strategies), collapse=", ")) 959s Warning message: 959s In library(package, lib.loc = lib.loc, character.only = TRUE, logical.return = TRUE, : 959s there is no package called ‘future.batchtools’ 959s Future strategies to test: ‘sequential’, ‘multisession’ 959s > 959s > fits <- list() 959s > for (strategy in strategies) { 959s + message(sprintf("- segmentByPairedPSCBS() using '%s' futures ...", strategy)) 959s + plan(strategy) 959s + fit <- segmentByPairedPSCBS(data, seed=0xBEEF, verbose=TRUE) 959s + fits[[strategy]] <- fit 959s + equal <- all.equal(fit, fits[[1]]) 959s + if (!equal) { 959s + str(fit) 959s + str(fits[[1]]) 959s + print(equal) 959s + stop(sprintf("segmentByPairedPSCBS() using '%s' futures does not produce the same results as when using '%s' futures", strategy, names(fits)[1])) 959s + } 959s + } 959s - segmentByPairedPSCBS() using 'sequential' futures ... 959s Segmenting paired tumor-normal signals using Paired PSCBS... 959s Calling genotypes from normal allele B fractions... 959s num [1:44010] 0.8274 0.5072 0.1671 0.1609 0.0421 ... 959s Called genotypes: 959s num [1:44010] 1 0.5 0 0 0 0 1 0 1 0.5 ... 959s - attr(*, "modelFit")=List of 1 959s ..$ :List of 7 959s .. ..$ flavor : chr "density" 959s .. ..$ cn : int 2 959s .. ..$ nbrOfGenotypeGroups: int 3 959s .. ..$ tau : num [1:2] 0.312 0.678 959s .. ..$ n : int 43920 959s .. ..$ fit :Classes ‘PeaksAndValleys’ and 'data.frame': 5 obs. of 3 variables: 959s .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 959s .. .. ..$ x : num [1:5] 0.0999 0.312 0.4986 0.6775 0.8922 959s .. .. ..$ density: num [1:5] 1.622 0.465 1.125 0.496 1.587 959s .. ..$ fitValleys :Classes ‘PeaksAndValleys’ and 'data.frame': 2 obs. of 3 variables: 959s .. .. ..$ type : chr [1:2] "valley" "valley" 959s .. .. ..$ x : num [1:2] 0.312 0.678 959s .. .. ..$ density: num [1:2] 0.465 0.496 959s ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 959s muN 959s 0 0.5 1 959s 15627 12633 15750 959s Calling genotypes from normal allele B fractions...done 959s Normalizing betaT using betaN (TumorBoost)... 959s Normalized BAFs: 959s num [1:44010] 0.9301 0.1667 0.0685 0.0995 0.0155 ... 959s - attr(*, "modelFit")=List of 5 959s ..$ method : chr "normalizeTumorBoost" 959s ..$ flavor : chr "v4" 959s ..$ delta : num [1:44010] -0.17264 0.00239 0.1671 0.16085 0.04213 ... 959s .. ..- attr(*, "modelFit")=List of 1 959s .. .. ..$ :List of 7 959s .. .. .. ..$ flavor : chr "density" 959s .. .. .. ..$ cn : int 2 959s .. .. .. ..$ nbrOfGenotypeGroups: int 3 959s .. .. .. ..$ tau : num [1:2] 0.312 0.678 959s .. .. .. ..$ n : int 43920 959s .. .. .. ..$ fit :Classes ‘PeaksAndValleys’ and 'data.frame': 5 obs. of 3 variables: 959s .. .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 959s .. .. .. .. ..$ x : num [1:5] 0.0999 0.312 0.4986 0.6775 0.8922 959s .. .. .. .. ..$ density: num [1:5] 1.622 0.465 1.125 0.496 1.587 959s .. .. .. ..$ fitValleys :Classes ‘PeaksAndValleys’ and 'data.frame': 2 obs. of 3 variables: 959s .. .. .. .. ..$ type : chr [1:2] "valley" "valley" 959s .. .. .. .. ..$ x : num [1:2] 0.312 0.678 959s .. .. .. .. ..$ density: num [1:2] 0.465 0.496 959s .. .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 959s ..$ preserveScale: logi FALSE 959s ..$ scaleFactor : num NA 959s Normalizing betaT using betaN (TumorBoost)...done 959s Setup up data... 959s 'data.frame': 44010 obs. of 7 variables: 959s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 959s $ x : num 1145994 2941694 3710825 4240737 4276892 ... 959s $ CT : num 1.63 1.4 1.41 1.17 1.16 ... 959s $ betaT : num 0.7574 0.169 0.2357 0.2604 0.0576 ... 959s $ betaTN : num 0.9301 0.1667 0.0685 0.0995 0.0155 ... 959s ..- attr(*, "modelFit")=List of 5 959s .. ..$ method : chr "normalizeTumorBoost" 959s .. ..$ flavor : chr "v4" 959s .. ..$ delta : num [1:44010] -0.17264 0.00239 0.1671 0.16085 0.04213 ... 959s .. .. ..- attr(*, "modelFit")=List of 1 959s .. .. .. ..$ :List of 7 959s .. .. .. .. ..$ flavor : chr "density" 959s .. .. .. .. ..$ cn : int 2 959s .. .. .. .. ..$ nbrOfGenotypeGroups: int 3 959s .. .. .. .. ..$ tau : num [1:2] 0.312 0.678 959s .. .. .. .. ..$ n : int 43920 959s .. .. .. .. ..$ fit :Classes ‘PeaksAndValleys’ and 'data.frame': 5 obs. of 3 variables: 959s .. .. .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 959s .. .. .. .. .. ..$ x : num [1:5] 0.0999 0.312 0.4986 0.6775 0.8922 959s .. .. .. .. .. ..$ density: num [1:5] 1.622 0.465 1.125 0.496 1.587 959s .. .. .. .. ..$ fitValleys :Classes ‘PeaksAndValleys’ and 'data.frame': 2 obs. of 3 variables: 959s .. .. .. .. .. ..$ type : chr [1:2] "valley" "valley" 959s .. .. .. .. .. ..$ x : num [1:2] 0.312 0.678 959s .. .. .. .. .. ..$ density: num [1:2] 0.465 0.496 959s .. .. .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 959s .. ..$ preserveScale: logi FALSE 959s .. ..$ scaleFactor : num NA 959s $ betaN : num 0.8274 0.5072 0.1671 0.1609 0.0421 ... 959s $ muN : num 1 0.5 0 0 0 0 1 0 1 0.5 ... 959s ..- attr(*, "modelFit")=List of 1 959s .. ..$ :List of 7 959s .. .. ..$ flavor : chr "density" 959s .. .. ..$ cn : int 2 959s .. .. ..$ nbrOfGenotypeGroups: int 3 959s .. .. ..$ tau : num [1:2] 0.312 0.678 959s .. .. ..$ n : int 43920 959s .. .. ..$ fit :Classes ‘PeaksAndValleys’ and 'data.frame': 5 obs. of 3 variables: 959s .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 959s .. .. .. ..$ x : num [1:5] 0.0999 0.312 0.4986 0.6775 0.8922 959s .. .. .. ..$ density: num [1:5] 1.622 0.465 1.125 0.496 1.587 959s .. .. ..$ fitValleys :Classes ‘PeaksAndValleys’ and 'data.frame': 2 obs. of 3 variables: 959s .. .. .. ..$ type : chr [1:2] "valley" "valley" 959s .. .. .. ..$ x : num [1:2] 0.312 0.678 959s .. .. .. ..$ density: num [1:2] 0.465 0.496 959s .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 959s Setup up data...done 959s Dropping loci for which TCNs are missing... 959s Number of loci dropped: 36 959s Dropping loci for which TCNs are missing...done 959s Ordering data along genome... 959s 'data.frame': 43974 obs. of 7 variables: 959s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 959s $ x : num 554484 730720 782343 878522 916294 ... 959s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 959s $ betaT : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 959s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 959s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 959s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 959s Ordering data along genome...done 959s Segmenting multiple chromosomes... 959s Number of chromosomes: 3 959s Random seed temporarily set (seed=c(48879), kind="L'Ecuyer-CMRG") 959s Produced 3 seeds from this stream for future usage 959s Chromosome #1 ('Chr01') of 3... 959s 'data.frame': 14658 obs. of 8 variables: 959s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 959s $ x : num 554484 730720 782343 878522 916294 ... 959s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 959s $ betaT : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 959s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 959s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 959s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 959s $ index : int 1 2 3 4 5 6 7 8 9 10 ... 959s Known segments: 959s [1] chromosome start end 959s <0 rows> (or 0-length row.names) 959s Segmenting paired tumor-normal signals using Paired PSCBS... 959s Setup up data... 959s 'data.frame': 14658 obs. of 7 variables: 959s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 959s $ x : num 554484 730720 782343 878522 916294 ... 959s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 959s $ betaT : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 959s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 959s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 959s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 959s Setup up data...done 959s Ordering data along genome... 959s 'data.frame': 14658 obs. of 7 variables: 959s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 959s $ x : num 554484 730720 782343 878522 916294 ... 959s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 959s $ betaT : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 959s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 959s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 959s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 959s Ordering data along genome...done 959s Keeping only current chromosome for 'knownSegments'... 959s Chromosome: 1 959s Known segments for this chromosome: 959s [1] chromosome start end 959s <0 rows> (or 0-length row.names) 959s Keeping only current chromosome for 'knownSegments'...done 959s alphaTCN: 0.009 959s alphaDH: 0.001 959s Number of loci: 14658 959s Calculating DHs... 959s Number of SNPs: 14658 959s Number of heterozygous SNPs: 4209 (28.71%) 959s Normalized DHs: 959s num [1:14658] NA NA NA NA NA ... 959s Calculating DHs...done 959s Random seed temporarily set (seed=c(10407, 1066287653, -51199871, 161854402, -1995183193, 1503453565, -747102133), kind="L'Ecuyer-CMRG") 959s Produced 2 seeds from this stream for future usage 959s Identification of change points by total copy numbers... 959s Segmenting by CBS... 959s Chromosome: 1 960s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 960s Segmenting by CBS...done 960s List of 4 960s $ data :'data.frame': 14658 obs. of 4 variables: 960s ..$ chromosome: int [1:14658] 1 1 1 1 1 1 1 1 1 1 ... 960s ..$ x : num [1:14658] 554484 730720 782343 878522 916294 ... 960s ..$ y : num [1:14658] 1.88 1.8 1.59 1.64 1.53 ... 960s ..$ index : int [1:14658] 1 2 3 4 5 6 7 8 9 10 ... 960s $ output :'data.frame': 3 obs. of 6 variables: 960s ..$ sampleName: chr [1:3] NA NA NA 960s ..$ chromosome: int [1:3] 1 1 1 960s ..$ start : num [1:3] 5.54e+05 1.44e+08 1.85e+08 960s ..$ end : num [1:3] 1.44e+08 1.85e+08 2.47e+08 960s ..$ nbrOfLoci : int [1:3] 7599 2668 4391 960s ..$ mean : num [1:3] 1.39 2.07 2.63 960s $ segRows:'data.frame': 3 obs. of 2 variables: 960s ..$ startRow: int [1:3] 1 7600 10268 960s ..$ endRow : int [1:3] 7599 10267 14658 960s $ params :List of 5 960s ..$ alpha : num 0.009 960s ..$ undo : num 0 960s ..$ joinSegments : logi TRUE 960s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 960s .. ..$ chromosome: int 1 960s .. ..$ start : num -Inf 960s .. ..$ end : num Inf 960s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 960s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 960s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.499 0 0.499 0 0 960s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 960s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 960s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 960s Identification of change points by total copy numbers...done 960s Restructure TCN segmentation results... 960s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean 960s 1 1 554484 143926517 7599 1.3859 960s 2 1 143926517 185449813 2668 2.0704 960s 3 1 185449813 247137334 4391 2.6341 960s Number of TCN segments: 3 960s Restructure TCN segmentation results...done 960s Total CN segment #1 ([ 554484,1.43927e+08]) of 3... 960s Number of TCN loci in segment: 7599 960s Locus data for TCN segment: 960s 'data.frame': 7599 obs. of 9 variables: 960s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 960s $ x : num 554484 730720 782343 878522 916294 ... 960s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 960s $ betaT : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 960s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 960s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 960s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 960s $ index : int 1 2 3 4 5 6 7 8 9 10 ... 960s $ rho : num NA NA NA NA NA ... 960s Number of loci: 7599 960s Number of SNPs: 2120 (27.90%) 960s Number of heterozygous SNPs: 2120 (100.00%) 960s Chromosome: 1 960s Segmenting DH signals... 960s Segmenting by CBS... 960s Chromosome: 1 960s Random seed temporarily set (seed=c(10407, -821273412, -52578226, 1415511586, 721384351, -665928286, 1316562960), kind="L'Ecuyer-CMRG") 960s Segmenting by CBS...done 960s List of 4 960s $ data :'data.frame': 7599 obs. of 4 variables: 960s ..$ chromosome: int [1:7599] 1 1 1 1 1 1 1 1 1 1 ... 960s ..$ x : num [1:7599] 554484 730720 782343 878522 916294 ... 960s ..$ y : num [1:7599] NA NA NA NA NA ... 960s ..$ index : int [1:7599] 1 2 3 4 5 6 7 8 9 10 ... 960s $ output :'data.frame': 1 obs. of 6 variables: 960s ..$ sampleName: chr NA 960s ..$ chromosome: int 1 960s ..$ start : num 554484 960s ..$ end : num 1.44e+08 960s ..$ nbrOfLoci : int 2120 960s ..$ mean : num 0.51 960s $ segRows:'data.frame': 1 obs. of 2 variables: 960s ..$ startRow: int 10 960s ..$ endRow : int 7594 960s $ params :List of 5 960s ..$ alpha : num 0.001 960s ..$ undo : num 0 960s ..$ joinSegments : logi TRUE 960s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 960s .. ..$ chromosome: int 1 960s .. ..$ start : num 554484 960s .. ..$ end : num 1.44e+08 960s ..$ seed : int [1:7] 10407 -821273412 -52578226 1415511586 721384351 -665928286 1316562960 960s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 960s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.031 0 0.031 0 0 960s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 960s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 960s - attr(*, "randomSeed")= int [1:7] 10407 -821273412 -52578226 1415511586 721384351 -665928286 1316562960 960s DH segmentation (locally-indexed) rows: 960s startRow endRow 960s 1 10 7594 960s int [1:7599] 1 2 3 4 5 6 7 8 9 10 ... 960s DH segmentation rows: 960s startRow endRow 960s 1 10 7594 960s Segmenting DH signals...done 960s DH segmentation table: 960s dhStart dhEnd dhNbrOfLoci dhMean 960s 1 554484 143926517 2120 0.5101 960s startRow endRow 960s 1 10 7594 960s Rows: 960s [1] 1 960s TCN segmentation rows: 960s startRow endRow 960s 1 1 7599 960s TCN and DH segmentation rows: 960s startRow endRow 960s 1 1 7599 960s startRow endRow 960s 1 10 7594 960s NULL 960s TCN segmentation (expanded) rows: 960s startRow endRow 960s 1 1 7599 960s TCN and DH segmentation rows: 960s startRow endRow 960s 1 1 7599 960s 2 7600 10267 960s 3 10268 14658 960s startRow endRow 960s 1 10 7594 960s startRow endRow 960s 1 1 7599 960s Total CN segmentation table (expanded): 960s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 960s 1 1 554484 143926517 7599 1.3859 2120 2120 960s (TCN,DH) segmentation for one total CN segment: 960s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 960s 1 1 1 1 554484 143926517 7599 1.3859 2120 960s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 960s 1 2120 554484 143926517 2120 0.5101 960s Total CN segment #1 ([ 554484,1.43927e+08]) of 3...done 960s Total CN segment #2 ([1.43927e+08,1.8545e+08]) of 3... 960s Number of TCN loci in segment: 2668 960s Locus data for TCN segment: 960s 'data.frame': 2668 obs. of 9 variables: 960s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 960s $ x : num 1.44e+08 1.44e+08 1.44e+08 1.44e+08 1.44e+08 ... 960s $ CT : num 2.1 2.1 2.09 1.8 2.34 ... 960s $ betaT : num 0.027542 1.030222 1.094093 0.046763 -0.000948 ... 960s $ betaTN : num 0.027542 1.030222 1.094093 0.046763 -0.000948 ... 960s $ betaN : num 0.1624 0.8788 0.8225 0.1201 0.0317 ... 960s $ muN : num 0 1 1 0 0 1 0 0 0 0 ... 960s $ index : int 7600 7601 7602 7603 7604 7605 7606 7607 7608 7609 ... 960s $ rho : num NA NA NA NA NA NA NA NA NA NA ... 960s Number of loci: 2668 960s Number of SNPs: 775 (29.05%) 960s Number of heterozygous SNPs: 775 (100.00%) 960s Chromosome: 1 960s Segmenting DH signals... 960s Segmenting by CBS... 960s Chromosome: 1 960s Random seed temporarily set (seed=c(10407, -821273412, -52578226, 1415511586, 721384351, -665928286, 1316562960), kind="L'Ecuyer-CMRG") 960s Segmenting by CBS...done 960s List of 4 960s $ data :'data.frame': 2668 obs. of 4 variables: 960s ..$ chromosome: int [1:2668] 1 1 1 1 1 1 1 1 1 1 ... 960s ..$ x : num [1:2668] 1.44e+08 1.44e+08 1.44e+08 1.44e+08 1.44e+08 ... 960s ..$ y : num [1:2668] NA NA NA NA NA NA NA NA NA NA ... 960s ..$ index : int [1:2668] 1 2 3 4 5 6 7 8 9 10 ... 960s $ output :'data.frame': 1 obs. of 6 variables: 960s ..$ sampleName: chr NA 960s ..$ chromosome: int 1 960s ..$ start : num 1.44e+08 960s ..$ end : num 1.85e+08 960s ..$ nbrOfLoci : int 775 960s ..$ mean : num 0.097 960s $ segRows:'data.frame': 1 obs. of 2 variables: 960s ..$ startRow: int 15 960s ..$ endRow : int 2664 960s $ params :List of 5 960s ..$ alpha : num 0.001 960s ..$ undo : num 0 960s ..$ joinSegments : logi TRUE 960s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 960s .. ..$ chromosome: int 1 960s .. ..$ start : num 1.44e+08 960s .. ..$ end : num 1.85e+08 960s ..$ seed : int [1:7] 10407 -821273412 -52578226 1415511586 721384351 -665928286 1316562960 960s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 960s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.01 0 0.01 0 0 960s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 960s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 960s - attr(*, "randomSeed")= int [1:7] 10407 -821273412 -52578226 1415511586 721384351 -665928286 1316562960 960s DH segmentation (locally-indexed) rows: 960s startRow endRow 960s 1 15 2664 960s int [1:2668] 7600 7601 7602 7603 7604 7605 7606 7607 7608 7609 ... 960s DH segmentation rows: 960s startRow endRow 960s 1 7614 10263 960s Segmenting DH signals...done 960s DH segmentation table: 960s dhStart dhEnd dhNbrOfLoci dhMean 960s 1 143926517 185449813 775 0.097 960s startRow endRow 960s 1 7614 10263 960s Rows: 960s [1] 2 960s TCN segmentation rows: 960s startRow endRow 960s 2 7600 10267 960s TCN and DH segmentation rows: 960s startRow endRow 960s 2 7600 10267 960s startRow endRow 960s 1 7614 10263 960s startRow endRow 960s 1 1 7599 960s TCN segmentation (expanded) rows: 960s startRow endRow 960s 1 1 7599 960s 2 7600 10267 960s TCN and DH segmentation rows: 960s startRow endRow 960s 1 1 7599 960s 2 7600 10267 960s 3 10268 14658 960s startRow endRow 960s 1 10 7594 960s 2 7614 10263 960s startRow endRow 960s 1 1 7599 960s 2 7600 10267 960s Total CN segmentation table (expanded): 960s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 960s 2 1 143926517 185449813 2668 2.0704 775 775 960s (TCN,DH) segmentation for one total CN segment: 960s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 960s 2 2 1 1 143926517 185449813 2668 2.0704 775 960s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 960s 2 775 143926517 185449813 775 0.097 960s Total CN segment #2 ([1.43927e+08,1.8545e+08]) of 3...done 960s Total CN segment #3 ([1.8545e+08,2.47137e+08]) of 3... 960s Number of TCN loci in segment: 4391 960s Locus data for TCN segment: 960s 'data.frame': 4391 obs. of 9 variables: 960s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 960s $ x : num 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 960s $ CT : num 2.93 2.15 2.82 2.93 2.46 ... 960s $ betaT : num -0.169 0.609 1.028 0.525 0.968 ... 960s $ betaTN : num -0.169 0.609 1.028 0.525 0.968 ... 960s $ betaN : num 0.25 0.38 0.919 0.34 0.783 ... 960s $ muN : num 0 0.5 1 0.5 1 1 0 1 0 1 ... 960s $ index : int 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 960s $ rho : num NA 0.2186 NA 0.0503 NA ... 960s Number of loci: 4391 960s Number of SNPs: 1314 (29.92%) 960s Number of heterozygous SNPs: 1314 (100.00%) 960s Chromosome: 1 960s Segmenting DH signals... 960s Segmenting by CBS... 960s Chromosome: 1 960s Random seed temporarily set (seed=c(10407, -821273412, -52578226, 1415511586, 721384351, -665928286, 1316562960), kind="L'Ecuyer-CMRG") 960s Segmenting by CBS...done 960s List of 4 960s $ data :'data.frame': 4391 obs. of 4 variables: 960s ..$ chromosome: int [1:4391] 1 1 1 1 1 1 1 1 1 1 ... 960s ..$ x : num [1:4391] 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 960s ..$ y : num [1:4391] NA 0.2186 NA 0.0503 NA ... 960s ..$ index : int [1:4391] 1 2 3 4 5 6 7 8 9 10 ... 960s $ output :'data.frame': 1 obs. of 6 variables: 960s ..$ sampleName: chr NA 960s ..$ chromosome: int 1 960s ..$ start : num 1.85e+08 960s ..$ end : num 2.47e+08 960s ..$ nbrOfLoci : int 1314 960s ..$ mean : num 0.23 960s $ segRows:'data.frame': 1 obs. of 2 variables: 960s ..$ startRow: int 2 960s ..$ endRow : int 4388 960s $ params :List of 5 960s ..$ alpha : num 0.001 960s ..$ undo : num 0 960s ..$ joinSegments : logi TRUE 960s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 960s .. ..$ chromosome: int 1 960s .. ..$ start : num 1.85e+08 960s .. ..$ end : num 2.47e+08 960s ..$ seed : int [1:7] 10407 -821273412 -52578226 1415511586 721384351 -665928286 1316562960 960s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 960s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.017 0 0.018 0 0 960s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 960s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 960s - attr(*, "randomSeed")= int [1:7] 10407 -821273412 -52578226 1415511586 721384351 -665928286 1316562960 960s DH segmentation (locally-indexed) rows: 960s startRow endRow 960s 1 2 4388 960s int [1:4391] 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 960s DH segmentation rows: 960s startRow endRow 960s 1 10269 14655 960s Segmenting DH signals...done 960s DH segmentation table: 960s dhStart dhEnd dhNbrOfLoci dhMean 960s 1 185449813 247137334 1314 0.2295 960s startRow endRow 960s 1 10269 14655 960s Rows: 960s [1] 3 960s TCN segmentation rows: 960s startRow endRow 960s 3 10268 14658 960s TCN and DH segmentation rows: 960s startRow endRow 960s 3 10268 14658 960s startRow endRow 960s 1 10269 14655 960s startRow endRow 960s 1 1 7599 960s 2 7600 10267 960s TCN segmentation (expanded) rows: 960s startRow endRow 960s 1 1 7599 960s 2 7600 10267 960s 3 10268 14658 960s TCN and DH segmentation rows: 960s startRow endRow 960s 1 1 7599 960s 2 7600 10267 960s 3 10268 14658 960s startRow endRow 960s 1 10 7594 960s 2 7614 10263 960s 3 10269 14655 960s startRow endRow 960s 1 1 7599 960s 2 7600 10267 960s 3 10268 14658 960s Total CN segmentation table (expanded): 960s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 960s 3 1 185449813 247137334 4391 2.6341 1314 1314 960s (TCN,DH) segmentation for one total CN segment: 960s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 960s 3 3 1 1 185449813 247137334 4391 2.6341 1314 960s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 960s 3 1314 185449813 247137334 1314 0.2295 960s Total CN segment #3 ([1.8545e+08,2.47137e+08]) of 3...done 960s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 960s 1 1 1 1 554484 143926517 7599 1.3859 2120 960s 2 1 2 1 143926517 185449813 2668 2.0704 775 960s 3 1 3 1 185449813 247137334 4391 2.6341 1314 960s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 960s 1 2120 554484 143926517 2120 0.5101 960s 2 775 143926517 185449813 775 0.0970 960s 3 1314 185449813 247137334 1314 0.2295 960s Calculating (C1,C2) per segment... 960s Calculating (C1,C2) per segment...done 960s Number of segments: 3 960s Segmenting paired tumor-normal signals using Paired PSCBS...done 960s Post-segmenting TCNs... 960s Number of segments: 3 960s Number of chromosomes: 1 960s [1] 1 960s Chromosome 1 ('chr01') of 1... 960s Rows: 960s [1] 1 2 3 960s Number of segments: 3 960s TCN segment #1 ('1') of 3... 960s Nothing todo. Only one DH segmentation. Skipping. 960s TCN segment #1 ('1') of 3...done 960s TCN segment #2 ('2') of 3... 960s Nothing todo. Only one DH segmentation. Skipping. 960s TCN segment #2 ('2') of 3...done 960s TCN segment #3 ('3') of 3... 960s Nothing todo. Only one DH segmentation. Skipping. 960s TCN segment #3 ('3') of 3...done 960s Chromosome 1 ('chr01') of 1...done 960s Update (C1,C2) per segment... 960s Update (C1,C2) per segment...done 960s Post-segmenting TCNs...done 960s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 960s 1 1 1 1 554484 143926517 7599 1.3859 2120 960s 2 1 2 1 143926517 185449813 2668 2.0704 775 960s 3 1 3 1 185449813 247137334 4391 2.6341 1314 960s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 960s 1 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 960s 2 775 143926517 185449813 775 0.0970 0.9347856 1.135614 960s 3 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 960s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 960s 1 1 1 1 554484 143926517 7599 1.3859 2120 960s 2 1 2 1 143926517 185449813 2668 2.0704 775 960s 3 1 3 1 185449813 247137334 4391 2.6341 1314 960s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 960s 1 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 960s 2 775 143926517 185449813 775 0.0970 0.9347856 1.135614 960s 3 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 960s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 960s 1 1 1 1 554484 143926517 7599 1.3859 2120 960s 2 1 2 1 143926517 185449813 2668 2.0704 775 960s 3 1 3 1 185449813 247137334 4391 2.6341 1314 960s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 960s 1 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 960s 2 775 143926517 185449813 775 0.0970 0.9347856 1.135614 960s 3 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 960s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 960s 1 1 1 1 554484 143926517 7599 1.3859 2120 960s 2 1 2 1 143926517 185449813 2668 2.0704 775 960s 3 1 3 1 185449813 247137334 4391 2.6341 1314 960s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 960s 1 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 960s 2 775 143926517 185449813 775 0.0970 0.9347856 1.135614 960s 3 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 960s Chromosome #1 ('Chr01') of 3...done 960s Chromosome #2 ('Chr02') of 3... 960s 'data.frame': 14658 obs. of 8 variables: 960s $ chromosome: int 2 2 2 2 2 2 2 2 2 2 ... 960s $ x : num 554484 730720 782343 878522 916294 ... 960s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 960s $ betaT : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 960s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 960s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 960s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 960s $ index : int 14659 14660 14661 14662 14663 14664 14665 14666 14667 14668 ... 960s Known segments: 960s [1] chromosome start end 960s <0 rows> (or 0-length row.names) 960s Segmenting paired tumor-normal signals using Paired PSCBS... 960s Setup up data... 960s 'data.frame': 14658 obs. of 7 variables: 960s $ chromosome: int 2 2 2 2 2 2 2 2 2 2 ... 960s $ x : num 554484 730720 782343 878522 916294 ... 960s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 960s $ betaT : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 960s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 960s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 960s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 960s Setup up data...done 960s Ordering data along genome... 960s 'data.frame': 14658 obs. of 7 variables: 960s $ chromosome: int 2 2 2 2 2 2 2 2 2 2 ... 960s $ x : num 554484 730720 782343 878522 916294 ... 960s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 960s $ betaT : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 960s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 960s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 960s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 960s Ordering data along genome...done 960s Keeping only current chromosome for 'knownSegments'... 960s Chromosome: 2 960s Known segments for this chromosome: 960s [1] chromosome start end 960s <0 rows> (or 0-length row.names) 960s Keeping only current chromosome for 'knownSegments'...done 960s alphaTCN: 0.009 960s alphaDH: 0.001 960s Number of loci: 14658 960s Calculating DHs... 960s Number of SNPs: 14658 960s Number of heterozygous SNPs: 4209 (28.71%) 960s Normalized DHs: 960s num [1:14658] NA NA NA NA NA ... 960s Calculating DHs...done 960s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 960s Produced 2 seeds from this stream for future usage 960s Identification of change points by total copy numbers... 960s Segmenting by CBS... 960s Chromosome: 2 960s Random seed temporarily set (seed=c(10407, -821273412, -52578226, 1415511586, 721384351, -665928286, 1316562960), kind="L'Ecuyer-CMRG") 961s Segmenting by CBS...done 961s List of 4 961s $ data :'data.frame': 14658 obs. of 4 variables: 961s ..$ chromosome: int [1:14658] 2 2 2 2 2 2 2 2 2 2 ... 961s ..$ x : num [1:14658] 554484 730720 782343 878522 916294 ... 961s ..$ y : num [1:14658] 1.88 1.8 1.59 1.64 1.53 ... 961s ..$ index : int [1:14658] 1 2 3 4 5 6 7 8 9 10 ... 961s $ output :'data.frame': 3 obs. of 6 variables: 961s ..$ sampleName: chr [1:3] NA NA NA 961s ..$ chromosome: int [1:3] 2 2 2 961s ..$ start : num [1:3] 5.54e+05 1.44e+08 1.85e+08 961s ..$ end : num [1:3] 1.44e+08 1.85e+08 2.47e+08 961s ..$ nbrOfLoci : int [1:3] 7599 2668 4391 961s ..$ mean : num [1:3] 1.39 2.07 2.63 961s $ segRows:'data.frame': 3 obs. of 2 variables: 961s ..$ startRow: int [1:3] 1 7600 10268 961s ..$ endRow : int [1:3] 7599 10267 14658 961s $ params :List of 5 961s ..$ alpha : num 0.009 961s ..$ undo : num 0 961s ..$ joinSegments : logi TRUE 961s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 961s .. ..$ chromosome: int 2 961s .. ..$ start : num -Inf 961s .. ..$ end : num Inf 961s ..$ seed : int [1:7] 10407 -821273412 -52578226 1415511586 721384351 -665928286 1316562960 961s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 961s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.537 0 0.538 0 0 961s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 961s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 961s - attr(*, "randomSeed")= int [1:7] 10407 -821273412 -52578226 1415511586 721384351 -665928286 1316562960 961s Identification of change points by total copy numbers...done 961s Restructure TCN segmentation results... 961s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean 961s 1 2 554484 143926517 7599 1.3859 961s 2 2 143926517 185449813 2668 2.0704 961s 3 2 185449813 247137334 4391 2.6341 961s Number of TCN segments: 3 961s Restructure TCN segmentation results...done 961s Total CN segment #1 ([ 554484,1.43927e+08]) of 3... 961s Number of TCN loci in segment: 7599 961s Locus data for TCN segment: 961s 'data.frame': 7599 obs. of 9 variables: 961s $ chromosome: int 2 2 2 2 2 2 2 2 2 2 ... 961s $ x : num 554484 730720 782343 878522 916294 ... 961s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 961s $ betaT : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 961s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 961s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 961s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 961s $ index : int 1 2 3 4 5 6 7 8 9 10 ... 961s $ rho : num NA NA NA NA NA ... 961s Number of loci: 7599 961s Number of SNPs: 2120 (27.90%) 961s Number of heterozygous SNPs: 2120 (100.00%) 961s Chromosome: 2 961s Segmenting DH signals... 961s Segmenting by CBS... 961s Chromosome: 2 961s Random seed temporarily set (seed=c(10407, -1924040949, -1632234809, -437763632, -1464377300, 676654412, 2080370711), kind="L'Ecuyer-CMRG") 961s Segmenting by CBS...done 961s List of 4 961s $ data :'data.frame': 7599 obs. of 4 variables: 961s ..$ chromosome: int [1:7599] 2 2 2 2 2 2 2 2 2 2 ... 961s ..$ x : num [1:7599] 554484 730720 782343 878522 916294 ... 961s ..$ y : num [1:7599] NA NA NA NA NA ... 961s ..$ index : int [1:7599] 1 2 3 4 5 6 7 8 9 10 ... 961s $ output :'data.frame': 1 obs. of 6 variables: 961s ..$ sampleName: chr NA 961s ..$ chromosome: int 2 961s ..$ start : num 554484 961s ..$ end : num 1.44e+08 961s ..$ nbrOfLoci : int 2120 961s ..$ mean : num 0.51 961s $ segRows:'data.frame': 1 obs. of 2 variables: 961s ..$ startRow: int 10 961s ..$ endRow : int 7594 961s $ params :List of 5 961s ..$ alpha : num 0.001 961s ..$ undo : num 0 961s ..$ joinSegments : logi TRUE 961s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 961s .. ..$ chromosome: int 2 961s .. ..$ start : num 554484 961s .. ..$ end : num 1.44e+08 961s ..$ seed : int [1:7] 10407 -1924040949 -1632234809 -437763632 -1464377300 676654412 2080370711 961s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 961s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.031 0 0.031 0 0 961s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 961s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 961s - attr(*, "randomSeed")= int [1:7] 10407 -1924040949 -1632234809 -437763632 -1464377300 676654412 2080370711 961s DH segmentation (locally-indexed) rows: 961s startRow endRow 961s 1 10 7594 961s int [1:7599] 1 2 3 4 5 6 7 8 9 10 ... 961s DH segmentation rows: 961s startRow endRow 961s 1 10 7594 961s Segmenting DH signals...done 961s DH segmentation table: 961s dhStart dhEnd dhNbrOfLoci dhMean 961s 1 554484 143926517 2120 0.5101 961s startRow endRow 961s 1 10 7594 961s Rows: 961s [1] 1 961s TCN segmentation rows: 961s startRow endRow 961s 1 1 7599 961s TCN and DH segmentation rows: 961s startRow endRow 961s 1 1 7599 961s startRow endRow 961s 1 10 7594 961s NULL 961s TCN segmentation (expanded) rows: 961s startRow endRow 961s 1 1 7599 961s TCN and DH segmentation rows: 961s startRow endRow 961s 1 1 7599 961s 2 7600 10267 961s 3 10268 14658 961s startRow endRow 961s 1 10 7594 961s startRow endRow 961s 1 1 7599 961s Total CN segmentation table (expanded): 961s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 961s 1 2 554484 143926517 7599 1.3859 2120 2120 961s (TCN,DH) segmentation for one total CN segment: 961s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 961s 1 1 1 2 554484 143926517 7599 1.3859 2120 961s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 961s 1 2120 554484 143926517 2120 0.5101 961s Total CN segment #1 ([ 554484,1.43927e+08]) of 3...done 961s Total CN segment #2 ([1.43927e+08,1.8545e+08]) of 3... 961s Number of TCN loci in segment: 2668 961s Locus data for TCN segment: 961s 'data.frame': 2668 obs. of 9 variables: 961s $ chromosome: int 2 2 2 2 2 2 2 2 2 2 ... 961s $ x : num 1.44e+08 1.44e+08 1.44e+08 1.44e+08 1.44e+08 ... 961s $ CT : num 2.1 2.1 2.09 1.8 2.34 ... 961s $ betaT : num 0.027542 1.030222 1.094093 0.046763 -0.000948 ... 961s $ betaTN : num 0.027542 1.030222 1.094093 0.046763 -0.000948 ... 961s $ betaN : num 0.1624 0.8788 0.8225 0.1201 0.0317 ... 961s $ muN : num 0 1 1 0 0 1 0 0 0 0 ... 961s $ index : int 7600 7601 7602 7603 7604 7605 7606 7607 7608 7609 ... 961s $ rho : num NA NA NA NA NA NA NA NA NA NA ... 961s Number of loci: 2668 961s Number of SNPs: 775 (29.05%) 961s Number of heterozygous SNPs: 775 (100.00%) 961s Chromosome: 2 961s Segmenting DH signals... 961s Segmenting by CBS... 961s Chromosome: 2 961s Random seed temporarily set (seed=c(10407, -1924040949, -1632234809, -437763632, -1464377300, 676654412, 2080370711), kind="L'Ecuyer-CMRG") 961s Segmenting by CBS...done 961s List of 4 961s $ data :'data.frame': 2668 obs. of 4 variables: 961s ..$ chromosome: int [1:2668] 2 2 2 2 2 2 2 2 2 2 ... 961s ..$ x : num [1:2668] 1.44e+08 1.44e+08 1.44e+08 1.44e+08 1.44e+08 ... 961s ..$ y : num [1:2668] NA NA NA NA NA NA NA NA NA NA ... 961s ..$ index : int [1:2668] 1 2 3 4 5 6 7 8 9 10 ... 961s $ output :'data.frame': 1 obs. of 6 variables: 961s ..$ sampleName: chr NA 961s ..$ chromosome: int 2 961s ..$ start : num 1.44e+08 961s ..$ end : num 1.85e+08 961s ..$ nbrOfLoci : int 775 961s ..$ mean : num 0.097 961s $ segRows:'data.frame': 1 obs. of 2 variables: 961s ..$ startRow: int 15 961s ..$ endRow : int 2664 961s $ params :List of 5 961s ..$ alpha : num 0.001 961s ..$ undo : num 0 961s ..$ joinSegments : logi TRUE 961s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 961s .. ..$ chromosome: int 2 961s .. ..$ start : num 1.44e+08 961s .. ..$ end : num 1.85e+08 961s ..$ seed : int [1:7] 10407 -1924040949 -1632234809 -437763632 -1464377300 676654412 2080370711 961s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 961s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.009 0 0.01 0 0 961s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 961s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 961s - attr(*, "randomSeed")= int [1:7] 10407 -1924040949 -1632234809 -437763632 -1464377300 676654412 2080370711 961s DH segmentation (locally-indexed) rows: 961s startRow endRow 961s 1 15 2664 961s int [1:2668] 7600 7601 7602 7603 7604 7605 7606 7607 7608 7609 ... 961s DH segmentation rows: 961s startRow endRow 961s 1 7614 10263 961s Segmenting DH signals...done 961s DH segmentation table: 961s dhStart dhEnd dhNbrOfLoci dhMean 961s 1 143926517 185449813 775 0.097 961s startRow endRow 961s 1 7614 10263 961s Rows: 961s [1] 2 961s TCN segmentation rows: 961s startRow endRow 961s 2 7600 10267 961s TCN and DH segmentation rows: 961s startRow endRow 961s 2 7600 10267 961s startRow endRow 961s 1 7614 10263 961s startRow endRow 961s 1 1 7599 961s TCN segmentation (expanded) rows: 961s startRow endRow 961s 1 1 7599 961s 2 7600 10267 961s TCN and DH segmentation rows: 961s startRow endRow 961s 1 1 7599 961s 2 7600 10267 961s 3 10268 14658 961s startRow endRow 961s 1 10 7594 961s 2 7614 10263 961s startRow endRow 961s 1 1 7599 961s 2 7600 10267 961s Total CN segmentation table (expanded): 961s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 961s 2 2 143926517 185449813 2668 2.0704 775 775 961s (TCN,DH) segmentation for one total CN segment: 961s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 961s 2 2 1 2 143926517 185449813 2668 2.0704 775 961s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 961s 2 775 143926517 185449813 775 0.097 961s Total CN segment #2 ([1.43927e+08,1.8545e+08]) of 3...done 961s Total CN segment #3 ([1.8545e+08,2.47137e+08]) of 3... 961s Number of TCN loci in segment: 4391 961s Locus data for TCN segment: 961s 'data.frame': 4391 obs. of 9 variables: 961s $ chromosome: int 2 2 2 2 2 2 2 2 2 2 ... 961s $ x : num 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 961s $ CT : num 2.93 2.15 2.82 2.93 2.46 ... 961s $ betaT : num -0.169 0.609 1.028 0.525 0.968 ... 961s $ betaTN : num -0.169 0.609 1.028 0.525 0.968 ... 961s $ betaN : num 0.25 0.38 0.919 0.34 0.783 ... 961s $ muN : num 0 0.5 1 0.5 1 1 0 1 0 1 ... 961s $ index : int 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 961s $ rho : num NA 0.2186 NA 0.0503 NA ... 961s Number of loci: 4391 961s Number of SNPs: 1314 (29.92%) 961s Number of heterozygous SNPs: 1314 (100.00%) 961s Chromosome: 2 961s Segmenting DH signals... 961s Segmenting by CBS... 961s Chromosome: 2 961s Random seed temporarily set (seed=c(10407, -1924040949, -1632234809, -437763632, -1464377300, 676654412, 2080370711), kind="L'Ecuyer-CMRG") 961s Segmenting by CBS...done 961s List of 4 961s $ data :'data.frame': 4391 obs. of 4 variables: 961s ..$ chromosome: int [1:4391] 2 2 2 2 2 2 2 2 2 2 ... 961s ..$ x : num [1:4391] 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 961s ..$ y : num [1:4391] NA 0.2186 NA 0.0503 NA ... 961s ..$ index : int [1:4391] 1 2 3 4 5 6 7 8 9 10 ... 961s $ output :'data.frame': 1 obs. of 6 variables: 961s ..$ sampleName: chr NA 961s ..$ chromosome: int 2 961s ..$ start : num 1.85e+08 961s ..$ end : num 2.47e+08 961s ..$ nbrOfLoci : int 1314 961s ..$ mean : num 0.23 961s $ segRows:'data.frame': 1 obs. of 2 variables: 961s ..$ startRow: int 2 961s ..$ endRow : int 4388 961s $ params :List of 5 961s ..$ alpha : num 0.001 961s ..$ undo : num 0 961s ..$ joinSegments : logi TRUE 961s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 961s .. ..$ chromosome: int 2 961s .. ..$ start : num 1.85e+08 961s .. ..$ end : num 2.47e+08 961s ..$ seed : int [1:7] 10407 -1924040949 -1632234809 -437763632 -1464377300 676654412 2080370711 961s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 961s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.018 0 0.018 0 0 961s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 961s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 961s - attr(*, "randomSeed")= int [1:7] 10407 -1924040949 -1632234809 -437763632 -1464377300 676654412 2080370711 961s DH segmentation (locally-indexed) rows: 961s startRow endRow 961s 1 2 4388 961s int [1:4391] 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 961s DH segmentation rows: 961s startRow endRow 961s 1 10269 14655 961s Segmenting DH signals...done 961s DH segmentation table: 961s dhStart dhEnd dhNbrOfLoci dhMean 961s 1 185449813 247137334 1314 0.2295 961s startRow endRow 961s 1 10269 14655 961s Rows: 961s [1] 3 961s TCN segmentation rows: 961s startRow endRow 961s 3 10268 14658 961s TCN and DH segmentation rows: 961s startRow endRow 961s 3 10268 14658 961s startRow endRow 961s 1 10269 14655 961s startRow endRow 961s 1 1 7599 961s 2 7600 10267 961s TCN segmentation (expanded) rows: 961s startRow endRow 961s 1 1 7599 961s 2 7600 10267 961s 3 10268 14658 961s TCN and DH segmentation rows: 961s startRow endRow 961s 1 1 7599 961s 2 7600 10267 961s 3 10268 14658 961s startRow endRow 961s 1 10 7594 961s 2 7614 10263 961s 3 10269 14655 961s startRow endRow 961s 1 1 7599 961s 2 7600 10267 961s 3 10268 14658 961s Total CN segmentation table (expanded): 961s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 961s 3 2 185449813 247137334 4391 2.6341 1314 1314 961s (TCN,DH) segmentation for one total CN segment: 961s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 961s 3 3 1 2 185449813 247137334 4391 2.6341 1314 961s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 961s 3 1314 185449813 247137334 1314 0.2295 961s Total CN segment #3 ([1.8545e+08,2.47137e+08]) of 3...done 961s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 961s 1 2 1 1 554484 143926517 7599 1.3859 2120 961s 2 2 2 1 143926517 185449813 2668 2.0704 775 961s 3 2 3 1 185449813 247137334 4391 2.6341 1314 961s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 961s 1 2120 554484 143926517 2120 0.5101 961s 2 775 143926517 185449813 775 0.0970 961s 3 1314 185449813 247137334 1314 0.2295 961s Calculating (C1,C2) per segment... 961s Calculating (C1,C2) per segment...done 961s Number of segments: 3 961s Segmenting paired tumor-normal signals using Paired PSCBS...done 961s Post-segmenting TCNs... 961s Number of segments: 3 961s Number of chromosomes: 1 961s [1] 2 961s Chromosome 1 ('chr02') of 1... 961s Rows: 961s [1] 1 2 3 961s Number of segments: 3 961s TCN segment #1 ('1') of 3... 961s Nothing todo. Only one DH segmentation. Skipping. 961s TCN segment #1 ('1') of 3...done 961s TCN segment #2 ('2') of 3... 961s Nothing todo. Only one DH segmentation. Skipping. 961s TCN segment #2 ('2') of 3...done 961s TCN segment #3 ('3') of 3... 961s Nothing todo. Only one DH segmentation. Skipping. 961s TCN segment #3 ('3') of 3...done 961s Chromosome 1 ('chr02') of 1...done 961s Update (C1,C2) per segment... 961s Update (C1,C2) per segment...done 961s Post-segmenting TCNs...done 961s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 961s 1 2 1 1 554484 143926517 7599 1.3859 2120 961s 2 2 2 1 143926517 185449813 2668 2.0704 775 961s 3 2 3 1 185449813 247137334 4391 2.6341 1314 961s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 961s 1 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 961s 2 775 143926517 185449813 775 0.0970 0.9347856 1.135614 961s 3 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 961s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 961s 1 2 1 1 554484 143926517 7599 1.3859 2120 961s 2 2 2 1 143926517 185449813 2668 2.0704 775 961s 3 2 3 1 185449813 247137334 4391 2.6341 1314 961s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 961s 1 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 961s 2 775 143926517 185449813 775 0.0970 0.9347856 1.135614 961s 3 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 961s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 961s 1 2 1 1 554484 143926517 7599 1.3859 2120 961s 2 2 2 1 143926517 185449813 2668 2.0704 775 961s 3 2 3 1 185449813 247137334 4391 2.6341 1314 961s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 961s 1 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 961s 2 775 143926517 185449813 775 0.0970 0.9347856 1.135614 961s 3 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 961s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 961s 1 2 1 1 554484 143926517 7599 1.3859 2120 961s 2 2 2 1 143926517 185449813 2668 2.0704 775 961s 3 2 3 1 185449813 247137334 4391 2.6341 1314 961s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 961s 1 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 961s 2 775 143926517 185449813 775 0.0970 0.9347856 1.135614 961s 3 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 961s Chromosome #2 ('Chr02') of 3...done 961s Chromosome #3 ('Chr03') of 3... 961s 'data.frame': 14658 obs. of 8 variables: 961s $ chromosome: int 3 3 3 3 3 3 3 3 3 3 ... 961s $ x : num 554484 730720 782343 878522 916294 ... 961s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 961s $ betaT : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 961s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 961s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 961s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 961s $ index : int 29317 29318 29319 29320 29321 29322 29323 29324 29325 29326 ... 961s Known segments: 961s [1] chromosome start end 961s <0 rows> (or 0-length row.names) 961s Segmenting paired tumor-normal signals using Paired PSCBS... 961s Setup up data... 961s 'data.frame': 14658 obs. of 7 variables: 961s $ chromosome: int 3 3 3 3 3 3 3 3 3 3 ... 961s $ x : num 554484 730720 782343 878522 916294 ... 961s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 961s $ betaT : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 961s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 961s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 961s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 961s Setup up data...done 961s Ordering data along genome... 961s 'data.frame': 14658 obs. of 7 variables: 961s $ chromosome: int 3 3 3 3 3 3 3 3 3 3 ... 961s $ x : num 554484 730720 782343 878522 916294 ... 961s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 961s $ betaT : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 961s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 961s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 961s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 961s Ordering data along genome...done 961s Keeping only current chromosome for 'knownSegments'... 961s Chromosome: 3 961s Known segments for this chromosome: 961s [1] chromosome start end 961s <0 rows> (or 0-length row.names) 961s Keeping only current chromosome for 'knownSegments'...done 961s alphaTCN: 0.009 961s alphaDH: 0.001 961s Number of loci: 14658 961s Calculating DHs... 961s Number of SNPs: 14658 961s Number of heterozygous SNPs: 4209 (28.71%) 961s Normalized DHs: 961s num [1:14658] NA NA NA NA NA ... 961s Calculating DHs...done 961s Random seed temporarily set (seed=c(10407, -821273412, -52578226, 1415511586, 721384351, -665928286, 1316562960), kind="L'Ecuyer-CMRG") 961s Produced 2 seeds from this stream for future usage 961s Identification of change points by total copy numbers... 961s Segmenting by CBS... 961s Chromosome: 3 962s Random seed temporarily set (seed=c(10407, -1924040949, -1632234809, -437763632, -1464377300, 676654412, 2080370711), kind="L'Ecuyer-CMRG") 962s Segmenting by CBS...done 962s List of 4 962s $ data :'data.frame': 14658 obs. of 4 variables: 962s ..$ chromosome: int [1:14658] 3 3 3 3 3 3 3 3 3 3 ... 962s ..$ x : num [1:14658] 554484 730720 782343 878522 916294 ... 962s ..$ y : num [1:14658] 1.88 1.8 1.59 1.64 1.53 ... 962s ..$ index : int [1:14658] 1 2 3 4 5 6 7 8 9 10 ... 962s $ output :'data.frame': 3 obs. of 6 variables: 962s ..$ sampleName: chr [1:3] NA NA NA 962s ..$ chromosome: int [1:3] 3 3 3 962s ..$ start : num [1:3] 5.54e+05 1.44e+08 1.85e+08 962s ..$ end : num [1:3] 1.44e+08 1.85e+08 2.47e+08 962s ..$ nbrOfLoci : int [1:3] 7599 2668 4391 962s ..$ mean : num [1:3] 1.39 2.07 2.63 962s $ segRows:'data.frame': 3 obs. of 2 variables: 962s ..$ startRow: int [1:3] 1 7600 10268 962s ..$ endRow : int [1:3] 7599 10267 14658 962s $ params :List of 5 962s ..$ alpha : num 0.009 962s ..$ undo : num 0 962s ..$ joinSegments : logi TRUE 962s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 962s .. ..$ chromosome: int 3 962s .. ..$ start : num -Inf 962s .. ..$ end : num Inf 962s ..$ seed : int [1:7] 10407 -1924040949 -1632234809 -437763632 -1464377300 676654412 2080370711 962s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 962s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.498 0.001 0.5 0 0 962s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 962s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 962s - attr(*, "randomSeed")= int [1:7] 10407 -1924040949 -1632234809 -437763632 -1464377300 676654412 2080370711 962s Identification of change points by total copy numbers...done 962s Restructure TCN segmentation results... 962s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean 962s 1 3 554484 143926517 7599 1.3859 962s 2 3 143926517 185449813 2668 2.0704 962s 3 3 185449813 247137334 4391 2.6341 962s Number of TCN segments: 3 962s Restructure TCN segmentation results...done 962s Total CN segment #1 ([ 554484,1.43927e+08]) of 3... 962s Number of TCN loci in segment: 7599 962s Locus data for TCN segment: 962s 'data.frame': 7599 obs. of 9 variables: 962s $ chromosome: int 3 3 3 3 3 3 3 3 3 3 ... 962s $ x : num 554484 730720 782343 878522 916294 ... 962s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 962s $ betaT : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 962s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 962s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 962s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 962s $ index : int 1 2 3 4 5 6 7 8 9 10 ... 962s $ rho : num NA NA NA NA NA ... 962s Number of loci: 7599 962s Number of SNPs: 2120 (27.90%) 962s Number of heterozygous SNPs: 2120 (100.00%) 962s Chromosome: 3 962s Segmenting DH signals... 962s Segmenting by CBS... 962s Chromosome: 3 962s Random seed temporarily set (seed=c(10407, -1371615447, -889757879, 1692656974, -1723952224, 1378814990, 1816467252), kind="L'Ecuyer-CMRG") 962s Segmenting by CBS...done 962s List of 4 962s $ data :'data.frame': 7599 obs. of 4 variables: 962s ..$ chromosome: int [1:7599] 3 3 3 3 3 3 3 3 3 3 ... 962s ..$ x : num [1:7599] 554484 730720 782343 878522 916294 ... 962s ..$ y : num [1:7599] NA NA NA NA NA ... 962s ..$ index : int [1:7599] 1 2 3 4 5 6 7 8 9 10 ... 962s $ output :'data.frame': 1 obs. of 6 variables: 962s ..$ sampleName: chr NA 962s ..$ chromosome: int 3 962s ..$ start : num 554484 962s ..$ end : num 1.44e+08 962s ..$ nbrOfLoci : int 2120 962s ..$ mean : num 0.51 962s $ segRows:'data.frame': 1 obs. of 2 variables: 962s ..$ startRow: int 10 962s ..$ endRow : int 7594 962s $ params :List of 5 962s ..$ alpha : num 0.001 962s ..$ undo : num 0 962s ..$ joinSegments : logi TRUE 962s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 962s .. ..$ chromosome: int 3 962s .. ..$ start : num 554484 962s .. ..$ end : num 1.44e+08 962s ..$ seed : int [1:7] 10407 -1371615447 -889757879 1692656974 -1723952224 1378814990 1816467252 962s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 962s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.032 0 0.032 0 0 962s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 962s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 962s - attr(*, "randomSeed")= int [1:7] 10407 -1371615447 -889757879 1692656974 -1723952224 1378814990 1816467252 962s DH segmentation (locally-indexed) rows: 962s startRow endRow 962s 1 10 7594 962s int [1:7599] 1 2 3 4 5 6 7 8 9 10 ... 962s DH segmentation rows: 962s startRow endRow 962s 1 10 7594 962s Segmenting DH signals...done 962s DH segmentation table: 962s dhStart dhEnd dhNbrOfLoci dhMean 962s 1 554484 143926517 2120 0.5101 962s startRow endRow 962s 1 10 7594 962s Rows: 962s [1] 1 962s TCN segmentation rows: 962s startRow endRow 962s 1 1 7599 962s TCN and DH segmentation rows: 962s startRow endRow 962s 1 1 7599 962s startRow endRow 962s 1 10 7594 962s NULL 962s TCN segmentation (expanded) rows: 962s startRow endRow 962s 1 1 7599 962s TCN and DH segmentation rows: 962s startRow endRow 962s 1 1 7599 962s 2 7600 10267 962s 3 10268 14658 962s startRow endRow 962s 1 10 7594 962s startRow endRow 962s 1 1 7599 962s Total CN segmentation table (expanded): 962s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 962s 1 3 554484 143926517 7599 1.3859 2120 2120 962s (TCN,DH) segmentation for one total CN segment: 962s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 962s 1 1 1 3 554484 143926517 7599 1.3859 2120 962s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 962s 1 2120 554484 143926517 2120 0.5101 962s Total CN segment #1 ([ 554484,1.43927e+08]) of 3...done 962s Total CN segment #2 ([1.43927e+08,1.8545e+08]) of 3... 962s Number of TCN loci in segment: 2668 962s Locus data for TCN segment: 962s 'data.frame': 2668 obs. of 9 variables: 962s $ chromosome: int 3 3 3 3 3 3 3 3 3 3 ... 962s $ x : num 1.44e+08 1.44e+08 1.44e+08 1.44e+08 1.44e+08 ... 962s $ CT : num 2.1 2.1 2.09 1.8 2.34 ... 962s $ betaT : num 0.027542 1.030222 1.094093 0.046763 -0.000948 ... 962s $ betaTN : num 0.027542 1.030222 1.094093 0.046763 -0.000948 ... 962s $ betaN : num 0.1624 0.8788 0.8225 0.1201 0.0317 ... 962s $ muN : num 0 1 1 0 0 1 0 0 0 0 ... 962s $ index : int 7600 7601 7602 7603 7604 7605 7606 7607 7608 7609 ... 962s $ rho : num NA NA NA NA NA NA NA NA NA NA ... 962s Number of loci: 2668 962s Number of SNPs: 775 (29.05%) 962s Number of heterozygous SNPs: 775 (100.00%) 962s Chromosome: 3 962s Segmenting DH signals... 962s Segmenting by CBS... 962s Chromosome: 3 962s Random seed temporarily set (seed=c(10407, -1371615447, -889757879, 1692656974, -1723952224, 1378814990, 1816467252), kind="L'Ecuyer-CMRG") 962s Segmenting by CBS...done 962s List of 4 962s $ data :'data.frame': 2668 obs. of 4 variables: 962s ..$ chromosome: int [1:2668] 3 3 3 3 3 3 3 3 3 3 ... 962s ..$ x : num [1:2668] 1.44e+08 1.44e+08 1.44e+08 1.44e+08 1.44e+08 ... 962s ..$ y : num [1:2668] NA NA NA NA NA NA NA NA NA NA ... 962s ..$ index : int [1:2668] 1 2 3 4 5 6 7 8 9 10 ... 962s $ output :'data.frame': 1 obs. of 6 variables: 962s ..$ sampleName: chr NA 962s ..$ chromosome: int 3 962s ..$ start : num 1.44e+08 962s ..$ end : num 1.85e+08 962s ..$ nbrOfLoci : int 775 962s ..$ mean : num 0.097 962s $ segRows:'data.frame': 1 obs. of 2 variables: 962s ..$ startRow: int 15 962s ..$ endRow : int 2664 962s $ params :List of 5 962s ..$ alpha : num 0.001 962s ..$ undo : num 0 962s ..$ joinSegments : logi TRUE 962s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 962s .. ..$ chromosome: int 3 962s .. ..$ start : num 1.44e+08 962s .. ..$ end : num 1.85e+08 962s ..$ seed : int [1:7] 10407 -1371615447 -889757879 1692656974 -1723952224 1378814990 1816467252 962s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 962s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.01 0 0.009 0 0 962s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 962s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 962s - attr(*, "randomSeed")= int [1:7] 10407 -1371615447 -889757879 1692656974 -1723952224 1378814990 1816467252 962s DH segmentation (locally-indexed) rows: 962s startRow endRow 962s 1 15 2664 962s int [1:2668] 7600 7601 7602 7603 7604 7605 7606 7607 7608 7609 ... 962s DH segmentation rows: 962s startRow endRow 962s 1 7614 10263 962s Segmenting DH signals...done 962s DH segmentation table: 962s dhStart dhEnd dhNbrOfLoci dhMean 962s 1 143926517 185449813 775 0.097 962s startRow endRow 962s 1 7614 10263 962s Rows: 962s [1] 2 962s TCN segmentation rows: 962s startRow endRow 962s 2 7600 10267 962s TCN and DH segmentation rows: 962s startRow endRow 962s 2 7600 10267 962s startRow endRow 962s 1 7614 10263 962s startRow endRow 962s 1 1 7599 962s TCN segmentation (expanded) rows: 962s startRow endRow 962s 1 1 7599 962s 2 7600 10267 962s TCN and DH segmentation rows: 962s startRow endRow 962s 1 1 7599 962s 2 7600 10267 962s 3 10268 14658 962s startRow endRow 962s 1 10 7594 962s 2 7614 10263 962s startRow endRow 962s 1 1 7599 962s 2 7600 10267 962s Total CN segmentation table (expanded): 962s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 962s 2 3 143926517 185449813 2668 2.0704 775 775 962s (TCN,DH) segmentation for one total CN segment: 962s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 962s 2 2 1 3 143926517 185449813 2668 2.0704 775 962s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 962s 2 775 143926517 185449813 775 0.097 962s Total CN segment #2 ([1.43927e+08,1.8545e+08]) of 3...done 962s Total CN segment #3 ([1.8545e+08,2.47137e+08]) of 3... 962s Number of TCN loci in segment: 4391 962s Locus data for TCN segment: 962s 'data.frame': 4391 obs. of 9 variables: 962s $ chromosome: int 3 3 3 3 3 3 3 3 3 3 ... 962s $ x : num 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 962s $ CT : num 2.93 2.15 2.82 2.93 2.46 ... 962s $ betaT : num -0.169 0.609 1.028 0.525 0.968 ... 962s $ betaTN : num -0.169 0.609 1.028 0.525 0.968 ... 962s $ betaN : num 0.25 0.38 0.919 0.34 0.783 ... 962s $ muN : num 0 0.5 1 0.5 1 1 0 1 0 1 ... 962s $ index : int 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 962s $ rho : num NA 0.2186 NA 0.0503 NA ... 962s Number of loci: 4391 962s Number of SNPs: 1314 (29.92%) 962s Number of heterozygous SNPs: 1314 (100.00%) 962s Chromosome: 3 962s Segmenting DH signals... 962s Segmenting by CBS... 962s Chromosome: 3 962s Random seed temporarily set (seed=c(10407, -1371615447, -889757879, 1692656974, -1723952224, 1378814990, 1816467252), kind="L'Ecuyer-CMRG") 962s Segmenting by CBS...done 962s List of 4 962s $ data :'data.frame': 4391 obs. of 4 variables: 962s ..$ chromosome: int [1:4391] 3 3 3 3 3 3 3 3 3 3 ... 962s ..$ x : num [1:4391] 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 962s ..$ y : num [1:4391] NA 0.2186 NA 0.0503 NA ... 962s ..$ index : int [1:4391] 1 2 3 4 5 6 7 8 9 10 ... 962s $ output :'data.frame': 1 obs. of 6 variables: 962s ..$ sampleName: chr NA 962s ..$ chromosome: int 3 962s ..$ start : num 1.85e+08 962s ..$ end : num 2.47e+08 962s ..$ nbrOfLoci : int 1314 962s ..$ mean : num 0.23 962s $ segRows:'data.frame': 1 obs. of 2 variables: 962s ..$ startRow: int 2 962s ..$ endRow : int 4388 962s $ params :List of 5 962s ..$ alpha : num 0.001 962s ..$ undo : num 0 962s ..$ joinSegments : logi TRUE 962s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 962s .. ..$ chromosome: int 3 962s .. ..$ start : num 1.85e+08 962s .. ..$ end : num 2.47e+08 962s ..$ seed : int [1:7] 10407 -1371615447 -889757879 1692656974 -1723952224 1378814990 1816467252 962s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 962s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.018 0 0.018 0 0 962s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 962s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 962s - attr(*, "randomSeed")= int [1:7] 10407 -1371615447 -889757879 1692656974 -1723952224 1378814990 1816467252 962s DH segmentation (locally-indexed) rows: 962s startRow endRow 962s 1 2 4388 962s int [1:4391] 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 962s DH segmentation rows: 962s startRow endRow 962s 1 10269 14655 962s Segmenting DH signals...done 962s DH segmentation table: 962s dhStart dhEnd dhNbrOfLoci dhMean 962s 1 185449813 247137334 1314 0.2295 962s startRow endRow 962s 1 10269 14655 962s Rows: 962s [1] 3 962s TCN segmentation rows: 962s startRow endRow 962s 3 10268 14658 962s TCN and DH segmentation rows: 962s startRow endRow 962s 3 10268 14658 962s startRow endRow 962s 1 10269 14655 962s startRow endRow 962s 1 1 7599 962s 2 7600 10267 962s TCN segmentation (expanded) rows: 962s startRow endRow 962s 1 1 7599 962s 2 7600 10267 962s 3 10268 14658 962s TCN and DH segmentation rows: 962s startRow endRow 962s 1 1 7599 962s 2 7600 10267 962s 3 10268 14658 962s startRow endRow 962s 1 10 7594 962s 2 7614 10263 962s 3 10269 14655 962s startRow endRow 962s 1 1 7599 962s 2 7600 10267 962s 3 10268 14658 962s Total CN segmentation table (expanded): 962s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 962s 3 3 185449813 247137334 4391 2.6341 1314 1314 962s (TCN,DH) segmentation for one total CN segment: 962s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 962s 3 3 1 3 185449813 247137334 4391 2.6341 1314 962s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 962s 3 1314 185449813 247137334 1314 0.2295 962s Total CN segment #3 ([1.8545e+08,2.47137e+08]) of 3...done 962s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 962s 1 3 1 1 554484 143926517 7599 1.3859 2120 962s 2 3 2 1 143926517 185449813 2668 2.0704 775 962s 3 3 3 1 185449813 247137334 4391 2.6341 1314 962s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 962s 1 2120 554484 143926517 2120 0.5101 962s 2 775 143926517 185449813 775 0.0970 962s 3 1314 185449813 247137334 1314 0.2295 962s Calculating (C1,C2) per segment... 962s Calculating (C1,C2) per segment...done 962s Number of segments: 3 962s Segmenting paired tumor-normal signals using Paired PSCBS...done 962s Post-segmenting TCNs... 962s Number of segments: 3 962s Number of chromosomes: 1 962s [1] 3 962s Chromosome 1 ('chr03') of 1... 962s Rows: 962s [1] 1 2 3 962s Number of segments: 3 962s TCN segment #1 ('1') of 3... 962s Nothing todo. Only one DH segmentation. Skipping. 962s TCN segment #1 ('1') of 3...done 962s TCN segment #2 ('2') of 3... 962s Nothing todo. Only one DH segmentation. Skipping. 962s TCN segment #2 ('2') of 3...done 962s TCN segment #3 ('3') of 3... 962s Nothing todo. Only one DH segmentation. Skipping. 962s TCN segment #3 ('3') of 3...done 962s Chromosome 1 ('chr03') of 1...done 962s Update (C1,C2) per segment... 962s Update (C1,C2) per segment...done 962s Post-segmenting TCNs...done 962s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 962s 1 3 1 1 554484 143926517 7599 1.3859 2120 962s 2 3 2 1 143926517 185449813 2668 2.0704 775 962s 3 3 3 1 185449813 247137334 4391 2.6341 1314 962s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 962s 1 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 962s 2 775 143926517 185449813 775 0.0970 0.9347856 1.135614 962s 3 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 962s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 962s 1 3 1 1 554484 143926517 7599 1.3859 2120 962s 2 3 2 1 143926517 185449813 2668 2.0704 775 962s 3 3 3 1 185449813 247137334 4391 2.6341 1314 962s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 962s 1 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 962s 2 775 143926517 185449813 775 0.0970 0.9347856 1.135614 962s 3 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 962s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 962s 1 3 1 1 554484 143926517 7599 1.3859 2120 962s 2 3 2 1 143926517 185449813 2668 2.0704 775 962s 3 3 3 1 185449813 247137334 4391 2.6341 1314 962s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 962s 1 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 962s 2 775 143926517 185449813 775 0.0970 0.9347856 1.135614 962s 3 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 962s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 962s 1 3 1 1 554484 143926517 7599 1.3859 2120 962s 2 3 2 1 143926517 185449813 2668 2.0704 775 962s 3 3 3 1 185449813 247137334 4391 2.6341 1314 962s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 962s 1 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 962s 2 775 143926517 185449813 775 0.0970 0.9347856 1.135614 962s 3 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 962s Chromosome #3 ('Chr03') of 3...done 962s Merging (independently) segmented chromosome... 962s List of 5 962s $ data :Classes ‘PairedPSCNData’ and 'data.frame': 43974 obs. of 8 variables: 962s ..$ chromosome: int [1:43974] 1 1 1 1 1 1 1 1 1 1 ... 962s ..$ x : num [1:43974] 554484 730720 782343 878522 916294 ... 962s ..$ CT : num [1:43974] 1.88 1.8 1.59 1.64 1.53 ... 962s ..$ betaT : num [1:43974] 0.0646 0.1672 0.9284 0.113 0.7209 ... 962s ..$ betaTN : num [1:43974] -0.0515 -0.1172 1.0194 0.031 0.8604 ... 962s ..$ betaN : num [1:43974] 0.116 0.284 0.909 0.082 0.86 ... 962s ..$ muN : num [1:43974] 0 0 1 0 1 1 1 0 1 0.5 ... 962s ..$ rho : num [1:43974] NA NA NA NA NA ... 962s $ output :Classes ‘PairedPSCNSegments’ and 'data.frame': 11 obs. of 15 variables: 962s ..$ chromosome : int [1:11] 1 1 1 NA 2 2 2 NA 3 3 ... 962s ..$ tcnId : int [1:11] 1 2 3 NA 1 2 3 NA 1 2 ... 962s ..$ dhId : int [1:11] 1 1 1 NA 1 1 1 NA 1 1 ... 962s ..$ tcnStart : num [1:11] 5.54e+05 1.44e+08 1.85e+08 NA 5.54e+05 ... 962s ..$ tcnEnd : num [1:11] 1.44e+08 1.85e+08 2.47e+08 NA 1.44e+08 ... 962s ..$ tcnNbrOfLoci: int [1:11] 7599 2668 4391 NA 7599 2668 4391 NA 7599 2668 ... 962s ..$ tcnMean : num [1:11] 1.39 2.07 2.63 NA 1.39 ... 962s ..$ tcnNbrOfSNPs: int [1:11] 2120 775 1314 NA 2120 775 1314 NA 2120 775 ... 962s ..$ tcnNbrOfHets: int [1:11] 2120 775 1314 NA 2120 775 1314 NA 2120 775 ... 962s ..$ dhStart : num [1:11] 5.54e+05 1.44e+08 1.85e+08 NA 5.54e+05 ... 962s ..$ dhEnd : num [1:11] 1.44e+08 1.85e+08 2.47e+08 NA 1.44e+08 ... 962s ..$ dhNbrOfLoci : int [1:11] 2120 775 1314 NA 2120 775 1314 NA 2120 775 ... 962s ..$ dhMean : num [1:11] 0.51 0.097 0.23 NA 0.51 ... 962s ..$ c1Mean : num [1:11] 0.339 0.935 1.015 NA 0.339 ... 962s ..$ c2Mean : num [1:11] 1.05 1.14 1.62 NA 1.05 ... 962s $ tcnSegRows:'data.frame': 11 obs. of 2 variables: 962s ..$ startRow: int [1:11] 1 7600 10268 NA 14659 22258 24926 NA 29317 36916 ... 962s ..$ endRow : int [1:11] 7599 10267 14658 NA 22257 24925 29316 NA 36915 39583 ... 962s $ dhSegRows :'data.frame': 11 obs. of 2 variables: 962s ..$ startRow: int [1:11] 10 7614 10269 NA 14668 22272 24927 NA 29326 36930 ... 962s ..$ endRow : int [1:11] 7594 10263 14655 NA 22252 24921 29313 NA 36910 39579 ... 962s $ params :List of 7 962s ..$ alphaTCN : num 0.009 962s ..$ alphaDH : num 0.001 962s ..$ flavor : chr "tcn&dh" 962s ..$ tbn : logi FALSE 962s ..$ joinSegments : logi TRUE 962s ..$ knownSegments:'data.frame': 0 obs. of 3 variables: 962s .. ..$ chromosome: int(0) 962s .. ..$ start : int(0) 962s .. ..$ end : int(0) 962s ..$ seed : int [1:7] 10407 1066287653 -51199871 161854402 -1995183193 1503453565 -747102133 962s - attr(*, "class")= chr [1:3] "PairedPSCBS" "PSCBS" "AbstractCBS" 962s Merging (independently) segmented chromosome...done 962s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 962s 1 1 1 1 554484 143926517 7599 1.3859 2120 962s 2 1 2 1 143926517 185449813 2668 2.0704 775 962s 3 1 3 1 185449813 247137334 4391 2.6341 1314 962s 4 NA NA NA NA NA NA NA NA 962s 5 2 1 1 554484 143926517 7599 1.3859 2120 962s 6 2 2 1 143926517 185449813 2668 2.0704 775 962s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 962s 1 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 962s 2 775 143926517 185449813 775 0.0970 0.9347856 1.135614 962s 3 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 962s 4 NA NA NA NA NA NA NA 962s 5 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 962s 6 775 143926517 185449813 775 0.0970 0.9347856 1.135614 962s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 962s 6 2 2 1 143926517 185449813 2668 2.0704 775 962s 7 2 3 1 185449813 247137334 4391 2.6341 1314 962s 8 NA NA NA NA NA NA NA NA 962s 9 3 1 1 554484 143926517 7599 1.3859 2120 962s 10 3 2 1 143926517 185449813 2668 2.0704 775 962s 11 3 3 1 185449813 247137334 4391 2.6341 1314 962s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 962s 6 775 143926517 185449813 775 0.0970 0.9347856 1.135614 962s 7 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 962s 8 NA NA NA NA NA NA NA 962s 9 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 962s 10 775 143926517 185449813 775 0.0970 0.9347856 1.135614 962s 11 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 962s Segmenting multiple chromosomes...done 962s Segmenting paired tumor-normal signals using Paired PSCBS...done 962s - segmentByPairedPSCBS() using 'multisession' futures ... 963s Segmenting paired tumor-normal signals using Paired PSCBS... 963s Calling genotypes from normal allele B fractions... 963s num [1:44010] 0.8274 0.5072 0.1671 0.1609 0.0421 ... 963s Called genotypes: 963s num [1:44010] 1 0.5 0 0 0 0 1 0 1 0.5 ... 963s - attr(*, "modelFit")=List of 1 963s ..$ :List of 7 963s .. ..$ flavor : chr "density" 963s .. ..$ cn : int 2 963s .. ..$ nbrOfGenotypeGroups: int 3 963s .. ..$ tau : num [1:2] 0.312 0.678 963s .. ..$ n : int 43920 963s .. ..$ fit :Classes ‘PeaksAndValleys’ and 'data.frame': 5 obs. of 3 variables: 963s .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 963s .. .. ..$ x : num [1:5] 0.0999 0.312 0.4986 0.6775 0.8922 963s .. .. ..$ density: num [1:5] 1.622 0.465 1.125 0.496 1.587 963s .. ..$ fitValleys :Classes ‘PeaksAndValleys’ and 'data.frame': 2 obs. of 3 variables: 963s .. .. ..$ type : chr [1:2] "valley" "valley" 963s .. .. ..$ x : num [1:2] 0.312 0.678 963s .. .. ..$ density: num [1:2] 0.465 0.496 963s ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 963s muN 963s 0 0.5 1 963s 15627 12633 15750 963s Calling genotypes from normal allele B fractions...done 963s Normalizing betaT using betaN (TumorBoost)... 963s Normalized BAFs: 963s num [1:44010] 0.9301 0.1667 0.0685 0.0995 0.0155 ... 963s - attr(*, "modelFit")=List of 5 963s ..$ method : chr "normalizeTumorBoost" 963s ..$ flavor : chr "v4" 963s ..$ delta : num [1:44010] -0.17264 0.00239 0.1671 0.16085 0.04213 ... 963s .. ..- attr(*, "modelFit")=List of 1 963s .. .. ..$ :List of 7 963s .. .. .. ..$ flavor : chr "density" 963s .. .. .. ..$ cn : int 2 963s .. .. .. ..$ nbrOfGenotypeGroups: int 3 963s .. .. .. ..$ tau : num [1:2] 0.312 0.678 963s .. .. .. ..$ n : int 43920 963s .. .. .. ..$ fit :Classes ‘PeaksAndValleys’ and 'data.frame': 5 obs. of 3 variables: 963s .. .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 963s .. .. .. .. ..$ x : num [1:5] 0.0999 0.312 0.4986 0.6775 0.8922 963s .. .. .. .. ..$ density: num [1:5] 1.622 0.465 1.125 0.496 1.587 963s .. .. .. ..$ fitValleys :Classes ‘PeaksAndValleys’ and 'data.frame': 2 obs. of 3 variables: 963s .. .. .. .. ..$ type : chr [1:2] "valley" "valley" 963s .. .. .. .. ..$ x : num [1:2] 0.312 0.678 963s .. .. .. .. ..$ density: num [1:2] 0.465 0.496 963s .. .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 963s ..$ preserveScale: logi FALSE 963s ..$ scaleFactor : num NA 963s Normalizing betaT using betaN (TumorBoost)...done 963s Setup up data... 963s 'data.frame': 44010 obs. of 7 variables: 963s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 963s $ x : num 1145994 2941694 3710825 4240737 4276892 ... 963s $ CT : num 1.63 1.4 1.41 1.17 1.16 ... 963s $ betaT : num 0.7574 0.169 0.2357 0.2604 0.0576 ... 963s $ betaTN : num 0.9301 0.1667 0.0685 0.0995 0.0155 ... 963s ..- attr(*, "modelFit")=List of 5 963s .. ..$ method : chr "normalizeTumorBoost" 963s .. ..$ flavor : chr "v4" 963s .. ..$ delta : num [1:44010] -0.17264 0.00239 0.1671 0.16085 0.04213 ... 963s .. .. ..- attr(*, "modelFit")=List of 1 963s .. .. .. ..$ :List of 7 963s .. .. .. .. ..$ flavor : chr "density" 963s .. .. .. .. ..$ cn : int 2 963s .. .. .. .. ..$ nbrOfGenotypeGroups: int 3 963s .. .. .. .. ..$ tau : num [1:2] 0.312 0.678 963s .. .. .. .. ..$ n : int 43920 963s .. .. .. .. ..$ fit :Classes ‘PeaksAndValleys’ and 'data.frame': 5 obs. of 3 variables: 963s .. .. .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 963s .. .. .. .. .. ..$ x : num [1:5] 0.0999 0.312 0.4986 0.6775 0.8922 963s .. .. .. .. .. ..$ density: num [1:5] 1.622 0.465 1.125 0.496 1.587 963s .. .. .. .. ..$ fitValleys :Classes ‘PeaksAndValleys’ and 'data.frame': 2 obs. of 3 variables: 963s .. .. .. .. .. ..$ type : chr [1:2] "valley" "valley" 963s .. .. .. .. .. ..$ x : num [1:2] 0.312 0.678 963s .. .. .. .. .. ..$ density: num [1:2] 0.465 0.496 963s .. .. .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 963s .. ..$ preserveScale: logi FALSE 963s .. ..$ scaleFactor : num NA 963s $ betaN : num 0.8274 0.5072 0.1671 0.1609 0.0421 ... 963s $ muN : num 1 0.5 0 0 0 0 1 0 1 0.5 ... 963s ..- attr(*, "modelFit")=List of 1 963s .. ..$ :List of 7 963s .. .. ..$ flavor : chr "density" 963s .. .. ..$ cn : int 2 963s .. .. ..$ nbrOfGenotypeGroups: int 3 963s .. .. ..$ tau : num [1:2] 0.312 0.678 963s .. .. ..$ n : int 43920 963s .. .. ..$ fit :Classes ‘PeaksAndValleys’ and 'data.frame': 5 obs. of 3 variables: 963s .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 963s .. .. .. ..$ x : num [1:5] 0.0999 0.312 0.4986 0.6775 0.8922 963s .. .. .. ..$ density: num [1:5] 1.622 0.465 1.125 0.496 1.587 963s .. .. ..$ fitValleys :Classes ‘PeaksAndValleys’ and 'data.frame': 2 obs. of 3 variables: 963s .. .. .. ..$ type : chr [1:2] "valley" "valley" 963s .. .. .. ..$ x : num [1:2] 0.312 0.678 963s .. .. .. ..$ density: num [1:2] 0.465 0.496 963s .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 963s Setup up data...done 963s Dropping loci for which TCNs are missing... 963s Number of loci dropped: 36 963s Dropping loci for which TCNs are missing...done 963s Ordering data along genome... 963s 'data.frame': 43974 obs. of 7 variables: 963s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 963s $ x : num 554484 730720 782343 878522 916294 ... 963s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 963s $ betaT : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 963s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 963s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 963s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 963s Ordering data along genome...done 963s Segmenting multiple chromosomes... 963s Number of chromosomes: 3 963s Random seed temporarily set (seed=c(48879), kind="L'Ecuyer-CMRG") 963s Produced 3 seeds from this stream for future usage 963s Chromosome #1 ('Chr01') of 3... 963s 'data.frame': 14658 obs. of 8 variables: 963s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 963s $ x : num 554484 730720 782343 878522 916294 ... 963s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 963s $ betaT : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 963s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 963s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 963s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 963s $ index : int 1 2 3 4 5 6 7 8 9 10 ... 963s Known segments: 963s [1] chromosome start end 963s <0 rows> (or 0-length row.names) 963s Chromosome #1 ('Chr01') of 3...done 963s Chromosome #2 ('Chr02') of 3... 963s 'data.frame': 14658 obs. of 8 variables: 963s $ chromosome: int 2 2 2 2 2 2 2 2 2 2 ... 963s $ x : num 554484 730720 782343 878522 916294 ... 963s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 963s $ betaT : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 963s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 963s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 963s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 963s $ index : int 14659 14660 14661 14662 14663 14664 14665 14666 14667 14668 ... 964s Known segments: 964s [1] chromosome start end 964s <0 rows> (or 0-length row.names) 964s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 964s Chromosome #2 ('Chr02') of 3...done 964s Chromosome #3 ('Chr03') of 3... 964s 'data.frame': 14658 obs. of 8 variables: 964s $ chromosome: int 3 3 3 3 3 3 3 3 3 3 ... 964s $ x : num 554484 730720 782343 878522 916294 ... 964s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 964s $ betaT : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 964s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 964s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 964s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 964s $ index : int 29317 29318 29319 29320 29321 29322 29323 29324 29325 29326 ... 964s Known segments: 964s [1] chromosome start end 964s <0 rows> (or 0-length row.names) 964s Random seed temporarily set (seed=c(10407, -821273412, -52578226, 1415511586, 721384351, -665928286, 1316562960), kind="L'Ecuyer-CMRG") 964s Segmenting by CBS...done 964s List of 4 964s $ data :'data.frame': 14658 obs. of 4 variables: 964s ..$ chromosome: int [1:14658] 1 1 1 1 1 1 1 1 1 1 ... 964s ..$ x : num [1:14658] 554484 730720 782343 878522 916294 ... 964s ..$ y : num [1:14658] 1.88 1.8 1.59 1.64 1.53 ... 964s ..$ index : int [1:14658] 1 2 3 4 5 6 7 8 9 10 ... 964s $ output :'data.frame': 3 obs. of 6 variables: 964s ..$ sampleName: chr [1:3] NA NA NA 964s ..$ chromosome: int [1:3] 1 1 1 964s ..$ start : num [1:3] 5.54e+05 1.44e+08 1.85e+08 964s ..$ end : num [1:3] 1.44e+08 1.85e+08 2.47e+08 964s ..$ nbrOfLoci : int [1:3] 7599 2668 4391 964s ..$ mean : num [1:3] 1.39 2.07 2.63 964s $ segRows:'data.frame': 3 obs. of 2 variables: 964s ..$ startRow: int [1:3] 1 7600 10268 964s ..$ endRow : int [1:3] 7599 10267 14658 964s $ params :List of 5 964s ..$ alpha : num 0.009 964s ..$ undo : num 0 964s ..$ joinSegments : logi TRUE 964s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 964s .. ..$ chromosome: int 1 964s .. ..$ start : num -Inf 964s .. ..$ end : num Inf 964s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 964s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 964s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.502 0 0.503 0 0 964s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 964s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 964s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 964s Identification of change points by total copy numbers...done 964s Restructure TCN segmentation results... 964s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean 964s 1 1 554484 143926517 7599 1.3859 964s 2 1 143926517 185449813 2668 2.0704 964s 3 1 185449813 247137334 4391 2.6341 964s Number of TCN segments: 3 964s Restructure TCN segmentation results...done 964s Total CN segment #1 ([ 554484,1.43927e+08]) of 3... 964s Number of TCN loci in segment: 7599 964s Locus data for TCN segment: 964s 'data.frame': 7599 obs. of 9 variables: 964s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 964s $ x : num 554484 730720 782343 878522 916294 ... 964s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 964s $ betaT : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 964s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 964s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 964s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 964s $ index : int 1 2 3 4 5 6 7 8 9 10 ... 964s $ rho : num NA NA NA NA NA ... 964s Number of loci: 7599 964s Number of SNPs: 2120 (27.90%) 964s Number of heterozygous SNPs: 2120 (100.00%) 964s Chromosome: 1 964s Segmenting DH signals... 964s Segmenting by CBS... 964s Chromosome: 1 964s Random seed temporarily set (seed=c(10407, -821273412, -52578226, 1415511586, 721384351, -665928286, 1316562960), kind="L'Ecuyer-CMRG") 964s Segmenting by CBS...done 964s List of 4 964s $ data :'data.frame': 7599 obs. of 4 variables: 964s ..$ chromosome: int [1:7599] 1 1 1 1 1 1 1 1 1 1 ... 964s ..$ x : num [1:7599] 554484 730720 782343 878522 916294 ... 964s ..$ y : num [1:7599] NA NA NA NA NA ... 964s ..$ index : int [1:7599] 1 2 3 4 5 6 7 8 9 10 ... 964s $ output :'data.frame': 1 obs. of 6 variables: 964s ..$ sampleName: chr NA 964s ..$ chromosome: int 1 964s ..$ start : num 554484 964s ..$ end : num 1.44e+08 964s ..$ nbrOfLoci : int 2120 964s ..$ mean : num 0.51 964s $ segRows:'data.frame': 1 obs. of 2 variables: 964s ..$ startRow: int 10 964s ..$ endRow : int 7594 964s $ params :List of 5 964s ..$ alpha : num 0.001 964s ..$ undo : num 0 964s ..$ joinSegments : logi TRUE 964s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 964s .. ..$ chromosome: int 1 964s .. ..$ start : num 554484 964s .. ..$ end : num 1.44e+08 964s ..$ seed : int [1:7] 10407 -821273412 -52578226 1415511586 721384351 -665928286 1316562960 964s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 964s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.031 0 0.031 0 0 964s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 964s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 964s - attr(*, "randomSeed")= int [1:7] 10407 -821273412 -52578226 1415511586 721384351 -665928286 1316562960 964s DH segmentation (locally-indexed) rows: 964s startRow endRow 964s 1 10 7594 964s int [1:7599] 1 2 3 4 5 6 7 8 9 10 ... 964s DH segmentation rows: 964s startRow endRow 964s 1 10 7594 964s Segmenting DH signals...done 964s DH segmentation table: 964s dhStart dhEnd dhNbrOfLoci dhMean 964s 1 554484 143926517 2120 0.5101 964s startRow endRow 964s 1 10 7594 964s Rows: 964s [1] 1 964s TCN segmentation rows: 964s startRow endRow 964s 1 1 7599 964s TCN and DH segmentation rows: 964s startRow endRow 964s 1 1 7599 964s startRow endRow 964s 1 10 7594 964s NULL 964s TCN segmentation (expanded) rows: 964s startRow endRow 964s 1 1 7599 964s TCN and DH segmentation rows: 964s startRow endRow 964s 1 1 7599 964s 2 7600 10267 964s 3 10268 14658 964s startRow endRow 964s 1 10 7594 964s startRow endRow 964s 1 1 7599 964s Total CN segmentation table (expanded): 964s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 964s 1 1 554484 143926517 7599 1.3859 2120 2120 964s (TCN,DH) segmentation for one total CN segment: 964s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 964s 1 1 1 1 554484 143926517 7599 1.3859 2120 964s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 964s 1 2120 554484 143926517 2120 0.5101 964s Total CN segment #1 ([ 554484,1.43927e+08]) of 3...done 964s Total CN segment #2 ([1.43927e+08,1.8545e+08]) of 3... 964s Number of TCN loci in segment: 2668 964s Locus data for TCN segment: 964s 'data.frame': 2668 obs. of 9 variables: 964s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 964s $ x : num 1.44e+08 1.44e+08 1.44e+08 1.44e+08 1.44e+08 ... 964s $ CT : num 2.1 2.1 2.09 1.8 2.34 ... 964s $ betaT : num 0.027542 1.030222 1.094093 0.046763 -0.000948 ... 964s $ betaTN : num 0.027542 1.030222 1.094093 0.046763 -0.000948 ... 964s $ betaN : num 0.1624 0.8788 0.8225 0.1201 0.0317 ... 964s $ muN : num 0 1 1 0 0 1 0 0 0 0 ... 964s $ index : int 7600 7601 7602 7603 7604 7605 7606 7607 7608 7609 ... 964s $ rho : num NA NA NA NA NA NA NA NA NA NA ... 964s Number of loci: 2668 964s Number of SNPs: 775 (29.05%) 964s Number of heterozygous SNPs: 775 (100.00%) 964s Chromosome: 1 964s Segmenting DH signals... 964s Segmenting by CBS... 964s Chromosome: 1 964s Random seed temporarily set (seed=c(10407, -821273412, -52578226, 1415511586, 721384351, -665928286, 1316562960), kind="L'Ecuyer-CMRG") 964s Segmenting by CBS...done 964s List of 4 964s $ data :'data.frame': 2668 obs. of 4 variables: 964s ..$ chromosome: int [1:2668] 1 1 1 1 1 1 1 1 1 1 ... 964s ..$ x : num [1:2668] 1.44e+08 1.44e+08 1.44e+08 1.44e+08 1.44e+08 ... 964s ..$ y : num [1:2668] NA NA NA NA NA NA NA NA NA NA ... 964s ..$ index : int [1:2668] 1 2 3 4 5 6 7 8 9 10 ... 964s $ output :'data.frame': 1 obs. of 6 variables: 964s ..$ sampleName: chr NA 964s ..$ chromosome: int 1 964s ..$ start : num 1.44e+08 964s ..$ end : num 1.85e+08 964s ..$ nbrOfLoci : int 775 964s ..$ mean : num 0.097 964s $ segRows:'data.frame': 1 obs. of 2 variables: 964s ..$ startRow: int 15 964s ..$ endRow : int 2664 964s $ params :List of 5 964s ..$ alpha : num 0.001 964s ..$ undo : num 0 964s ..$ joinSegments : logi TRUE 964s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 964s .. ..$ chromosome: int 1 964s .. ..$ start : num 1.44e+08 964s .. ..$ end : num 1.85e+08 964s ..$ seed : int [1:7] 10407 -821273412 -52578226 1415511586 721384351 -665928286 1316562960 964s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 964s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.009 0 0.009 0 0 964s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 964s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 964s - attr(*, "randomSeed")= int [1:7] 10407 -821273412 -52578226 1415511586 721384351 -665928286 1316562960 964s DH segmentation (locally-indexed) rows: 964s startRow endRow 964s 1 15 2664 964s int [1:2668] 7600 7601 7602 7603 7604 7605 7606 7607 7608 7609 ... 964s DH segmentation rows: 964s startRow endRow 964s 1 7614 10263 964s Segmenting DH signals...done 964s DH segmentation table: 964s dhStart dhEnd dhNbrOfLoci dhMean 964s 1 143926517 185449813 775 0.097 964s startRow endRow 964s 1 7614 10263 964s Rows: 964s [1] 2 964s TCN segmentation rows: 964s startRow endRow 964s 2 7600 10267 964s TCN and DH segmentation rows: 964s startRow endRow 964s 2 7600 10267 964s startRow endRow 964s 1 7614 10263 964s startRow endRow 964s 1 1 7599 964s TCN segmentation (expanded) rows: 964s startRow endRow 964s 1 1 7599 964s 2 7600 10267 964s TCN and DH segmentation rows: 964s startRow endRow 964s 1 1 7599 964s 2 7600 10267 964s 3 10268 14658 964s startRow endRow 964s 1 10 7594 964s 2 7614 10263 964s startRow endRow 964s 1 1 7599 964s 2 7600 10267 964s Total CN segmentation table (expanded): 964s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 964s 2 1 143926517 185449813 2668 2.0704 775 775 964s (TCN,DH) segmentation for one total CN segment: 964s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 964s 2 2 1 1 143926517 185449813 2668 2.0704 775 964s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 964s 2 775 143926517 185449813 775 0.097 964s Total CN segment #2 ([1.43927e+08,1.8545e+08]) of 3...done 964s Total CN segment #3 ([1.8545e+08,2.47137e+08]) of 3... 964s Number of TCN loci in segment: 4391 964s Locus data for TCN segment: 964s 'data.frame': 4391 obs. of 9 variables: 964s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 964s $ x : num 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 964s $ CT : num 2.93 2.15 2.82 2.93 2.46 ... 964s $ betaT : num -0.169 0.609 1.028 0.525 0.968 ... 964s $ betaTN : num -0.169 0.609 1.028 0.525 0.968 ... 964s $ betaN : num 0.25 0.38 0.919 0.34 0.783 ... 964s $ muN : num 0 0.5 1 0.5 1 1 0 1 0 1 ... 964s $ index : int 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 964s $ rho : num NA 0.2186 NA 0.0503 NA ... 964s Number of loci: 4391 964s Number of SNPs: 1314 (29.92%) 964s Number of heterozygous SNPs: 1314 (100.00%) 964s Chromosome: 1 964s Segmenting DH signals... 964s Segmenting by CBS... 964s Chromosome: 1 964s Random seed temporarily set (seed=c(10407, -821273412, -52578226, 1415511586, 721384351, -665928286, 1316562960), kind="L'Ecuyer-CMRG") 964s Segmenting by CBS...done 964s List of 4 964s $ data :'data.frame': 4391 obs. of 4 variables: 964s ..$ chromosome: int [1:4391] 1 1 1 1 1 1 1 1 1 1 ... 964s ..$ x : num [1:4391] 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 964s ..$ y : num [1:4391] NA 0.2186 NA 0.0503 NA ... 964s ..$ index : int [1:4391] 1 2 3 4 5 6 7 8 9 10 ... 964s $ output :'data.frame': 1 obs. of 6 variables: 964s ..$ sampleName: chr NA 964s ..$ chromosome: int 1 964s ..$ start : num 1.85e+08 964s ..$ end : num 2.47e+08 964s ..$ nbrOfLoci : int 1314 964s ..$ mean : num 0.23 964s $ segRows:'data.frame': 1 obs. of 2 variables: 964s ..$ startRow: int 2 964s ..$ endRow : int 4388 964s $ params :List of 5 964s ..$ alpha : num 0.001 964s ..$ undo : num 0 964s ..$ joinSegments : logi TRUE 964s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 964s .. ..$ chromosome: int 1 964s .. ..$ start : num 1.85e+08 964s .. ..$ end : num 2.47e+08 964s ..$ seed : int [1:7] 10407 -821273412 -52578226 1415511586 721384351 -665928286 1316562960 964s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 964s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.017 0 0.017 0 0 964s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 964s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 964s - attr(*, "randomSeed")= int [1:7] 10407 -821273412 -52578226 1415511586 721384351 -665928286 1316562960 964s DH segmentation (locally-indexed) rows: 964s startRow endRow 964s 1 2 4388 964s int [1:4391] 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 964s DH segmentation rows: 964s startRow endRow 964s 1 10269 14655 964s Segmenting DH signals...done 964s DH segmentation table: 964s dhStart dhEnd dhNbrOfLoci dhMean 964s 1 185449813 247137334 1314 0.2295 964s startRow endRow 964s 1 10269 14655 964s Rows: 964s [1] 3 964s TCN segmentation rows: 964s startRow endRow 964s 3 10268 14658 964s TCN and DH segmentation rows: 964s startRow endRow 964s 3 10268 14658 964s startRow endRow 964s 1 10269 14655 965s startRow endRow 965s 1 1 7599 965s 2 7600 10267 965s TCN segmentation (expanded) rows: 965s startRow endRow 965s 1 1 7599 965s 2 7600 10267 965s 3 10268 14658 965s TCN and DH segmentation rows: 965s startRow endRow 965s 1 1 7599 965s 2 7600 10267 965s 3 10268 14658 965s startRow endRow 965s 1 10 7594 965s 2 7614 10263 965s 3 10269 14655 965s startRow endRow 965s 1 1 7599 965s 2 7600 10267 965s 3 10268 14658 965s Total CN segmentation table (expanded): 965s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 965s 3 1 185449813 247137334 4391 2.6341 1314 1314 965s (TCN,DH) segmentation for one total CN segment: 965s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 965s 3 3 1 1 185449813 247137334 4391 2.6341 1314 965s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 965s 3 1314 185449813 247137334 1314 0.2295 965s Total CN segment #3 ([1.8545e+08,2.47137e+08]) of 3...done 965s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 965s 1 1 1 1 554484 143926517 7599 1.3859 2120 965s 2 1 2 1 143926517 185449813 2668 2.0704 775 965s 3 1 3 1 185449813 247137334 4391 2.6341 1314 965s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 965s 1 2120 554484 143926517 2120 0.5101 965s 2 775 143926517 185449813 775 0.0970 965s 3 1314 185449813 247137334 1314 0.2295 965s Calculating (C1,C2) per segment... 965s Calculating (C1,C2) per segment...done 965s Number of segments: 3 965s Segmenting paired tumor-normal signals using Paired PSCBS...done 965s Post-segmenting TCNs... 965s Number of segments: 3 965s Number of chromosomes: 1 965s [1] 1 965s Chromosome 1 ('chr01') of 1... 965s Rows: 965s [1] 1 2 3 965s Number of segments: 3 965s TCN segment #1 ('1') of 3... 965s Nothing todo. Only one DH segmentation. Skipping. 965s TCN segment #1 ('1') of 3...done 965s TCN segment #2 ('2') of 3... 965s Nothing todo. Only one DH segmentation. Skipping. 965s TCN segment #2 ('2') of 3...done 965s TCN segment #3 ('3') of 3... 965s Nothing todo. Only one DH segmentation. Skipping. 965s TCN segment #3 ('3') of 3...done 965s Chromosome 1 ('chr01') of 1...done 965s Update (C1,C2) per segment... 965s Update (C1,C2) per segment...done 965s Post-segmenting TCNs...done 965s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 965s 1 1 1 1 554484 143926517 7599 1.3859 2120 965s 2 1 2 1 143926517 185449813 2668 2.0704 775 965s 3 1 3 1 185449813 247137334 4391 2.6341 1314 965s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 965s 1 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 965s 2 775 143926517 185449813 775 0.0970 0.9347856 1.135614 965s 3 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 965s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 965s 1 1 1 1 554484 143926517 7599 1.3859 2120 965s 2 1 2 1 143926517 185449813 2668 2.0704 775 965s 3 1 3 1 185449813 247137334 4391 2.6341 1314 965s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 965s 1 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 965s 2 775 143926517 185449813 775 0.0970 0.9347856 1.135614 965s 3 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 965s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 965s 1 1 1 1 554484 143926517 7599 1.3859 2120 965s 2 1 2 1 143926517 185449813 2668 2.0704 775 965s 3 1 3 1 185449813 247137334 4391 2.6341 1314 965s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 965s 1 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 965s 2 775 143926517 185449813 775 0.0970 0.9347856 1.135614 965s 3 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 965s Segmenting by CBS...done 965s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 965s 1 1 1 1 554484 143926517 7599 1.3859 2120 965s 2 1 2 1 143926517 185449813 2668 2.0704 775 965s 3 1 3 1 185449813 247137334 4391 2.6341 1314 965s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 965s 1 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 965s 2 775 143926517 185449813 775 0.0970 0.9347856 1.135614 965s 3 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 965s List of 4 965s $ data :'data.frame': 14658 obs. of 4 variables: 965s ..$ chromosome: int [1:14658] 2 2 2 2 2 2 2 2 2 2 ... 965s ..$ x : num [1:14658] 554484 730720 782343 878522 916294 ... 965s ..$ y : num [1:14658] 1.88 1.8 1.59 1.64 1.53 ... 965s ..$ index : int [1:14658] 1 2 3 4 5 6 7 8 9 10 ... 965s $ output :'data.frame': 3 obs. of 6 variables: 965s ..$ sampleName: chr [1:3] NA NA NA 965s ..$ chromosome: int [1:3] 2 2 2 965s ..$ start : num [1:3] 5.54e+05 1.44e+08 1.85e+08 965s ..$ end : num [1:3] 1.44e+08 1.85e+08 2.47e+08 965s ..$ nbrOfLoci : int [1:3] 7599 2668 4391 965s ..$ mean : num [1:3] 1.39 2.07 2.63 965s $ segRows:'data.frame': 3 obs. of 2 variables: 965s ..$ startRow: int [1:3] 1 7600 10268 965s ..$ endRow : int [1:3] 7599 10267 14658 965s $ params :List of 5 965s ..$ alpha : num 0.009 965s ..$ undo : num 0 965s ..$ joinSegments : logi TRUE 965s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 965s .. ..$ chromosome: int 2 965s .. ..$ start : num -Inf 965s .. ..$ end : num Inf 965s ..$ seed : int [1:7] 10407 -821273412 -52578226 1415511586 721384351 -665928286 1316562960 965s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 965s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.53 0 0.548 0 0 965s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 965s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 965s - attr(*, "randomSeed")= int [1:7] 10407 -821273412 -52578226 1415511586 721384351 -665928286 1316562960 965s Identification of change points by total copy numbers...done 965s Restructure TCN segmentation results... 965s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean 965s 1 2 554484 143926517 7599 1.3859 965s 2 2 143926517 185449813 2668 2.0704 965s 3 2 185449813 247137334 4391 2.6341 965s Number of TCN segments: 3 965s Restructure TCN segmentation results...done 965s Total CN segment #1 ([ 554484,1.43927e+08]) of 3... 965s Number of TCN loci in segment: 7599 965s Locus data for TCN segment: 965s 'data.frame': 7599 obs. of 9 variables: 965s $ chromosome: int 2 2 2 2 2 2 2 2 2 2 ... 965s $ x : num 554484 730720 782343 878522 916294 ... 965s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 965s $ betaT : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 965s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 965s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 965s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 965s $ index : int 1 2 3 4 5 6 7 8 9 10 ... 965s $ rho : num NA NA NA NA NA ... 965s Number of loci: 7599 965s Number of SNPs: 2120 (27.90%) 965s Number of heterozygous SNPs: 2120 (100.00%) 965s Chromosome: 2 965s Segmenting DH signals... 965s Segmenting by CBS... 965s Chromosome: 2 965s Random seed temporarily set (seed=c(10407, -1924040949, -1632234809, -437763632, -1464377300, 676654412, 2080370711), kind="L'Ecuyer-CMRG") 965s Segmenting by CBS...done 965s List of 4 965s $ data :'data.frame': 7599 obs. of 4 variables: 965s ..$ chromosome: int [1:7599] 2 2 2 2 2 2 2 2 2 2 ... 965s ..$ x : num [1:7599] 554484 730720 782343 878522 916294 ... 965s ..$ y : num [1:7599] NA NA NA NA NA ... 965s ..$ index : int [1:7599] 1 2 3 4 5 6 7 8 9 10 ... 965s $ output :'data.frame': 1 obs. of 6 variables: 965s ..$ sampleName: chr NA 965s ..$ chromosome: int 2 965s ..$ start : num 554484 965s ..$ end : num 1.44e+08 965s ..$ nbrOfLoci : int 2120 965s ..$ mean : num 0.51 965s $ segRows:'data.frame': 1 obs. of 2 variables: 965s ..$ startRow: int 10 965s ..$ endRow : int 7594 965s $ params :List of 5 965s ..$ alpha : num 0.001 965s ..$ undo : num 0 965s ..$ joinSegments : logi TRUE 965s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 965s .. ..$ chromosome: int 2 965s .. ..$ start : num 554484 965s .. ..$ end : num 1.44e+08 965s ..$ seed : int [1:7] 10407 -1924040949 -1632234809 -437763632 -1464377300 676654412 2080370711 965s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 965s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.031 0 0.031 0 0 965s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 965s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 965s - attr(*, "randomSeed")= int [1:7] 10407 -1924040949 -1632234809 -437763632 -1464377300 676654412 2080370711 965s DH segmentation (locally-indexed) rows: 965s startRow endRow 965s 1 10 7594 965s int [1:7599] 1 2 3 4 5 6 7 8 9 10 ... 965s DH segmentation rows: 965s startRow endRow 965s 1 10 7594 965s Segmenting DH signals...done 965s DH segmentation table: 965s dhStart dhEnd dhNbrOfLoci dhMean 965s 1 554484 143926517 2120 0.5101 965s startRow endRow 965s 1 10 7594 965s Rows: 965s [1] 1 965s TCN segmentation rows: 965s startRow endRow 965s 1 1 7599 965s TCN and DH segmentation rows: 965s startRow endRow 965s 1 1 7599 965s startRow endRow 965s 1 10 7594 965s NULL 965s TCN segmentation (expanded) rows: 965s startRow endRow 965s 1 1 7599 965s TCN and DH segmentation rows: 965s startRow endRow 965s 1 1 7599 965s 2 7600 10267 965s 3 10268 14658 965s startRow endRow 965s 1 10 7594 965s startRow endRow 965s 1 1 7599 965s Total CN segmentation table (expanded): 965s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 965s 1 2 554484 143926517 7599 1.3859 2120 2120 965s (TCN,DH) segmentation for one total CN segment: 965s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 965s 1 1 1 2 554484 143926517 7599 1.3859 2120 965s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 965s 1 2120 554484 143926517 2120 0.5101 965s Total CN segment #1 ([ 554484,1.43927e+08]) of 3...done 965s Total CN segment #2 ([1.43927e+08,1.8545e+08]) of 3... 965s Number of TCN loci in segment: 2668 965s Locus data for TCN segment: 965s 'data.frame': 2668 obs. of 9 variables: 965s $ chromosome: int 2 2 2 2 2 2 2 2 2 2 ... 965s $ x : num 1.44e+08 1.44e+08 1.44e+08 1.44e+08 1.44e+08 ... 965s $ CT : num 2.1 2.1 2.09 1.8 2.34 ... 965s $ betaT : num 0.027542 1.030222 1.094093 0.046763 -0.000948 ... 965s $ betaTN : num 0.027542 1.030222 1.094093 0.046763 -0.000948 ... 965s $ betaN : num 0.1624 0.8788 0.8225 0.1201 0.0317 ... 965s $ muN : num 0 1 1 0 0 1 0 0 0 0 ... 965s $ index : int 7600 7601 7602 7603 7604 7605 7606 7607 7608 7609 ... 965s $ rho : num NA NA NA NA NA NA NA NA NA NA ... 965s Number of loci: 2668 965s Number of SNPs: 775 (29.05%) 965s Number of heterozygous SNPs: 775 (100.00%) 965s Chromosome: 2 965s Segmenting DH signals... 965s Segmenting by CBS... 965s Chromosome: 2 965s Random seed temporarily set (seed=c(10407, -1924040949, -1632234809, -437763632, -1464377300, 676654412, 2080370711), kind="L'Ecuyer-CMRG") 965s Segmenting by CBS...done 965s List of 4 965s $ data :'data.frame': 2668 obs. of 4 variables: 965s ..$ chromosome: int [1:2668] 2 2 2 2 2 2 2 2 2 2 ... 965s ..$ x : num [1:2668] 1.44e+08 1.44e+08 1.44e+08 1.44e+08 1.44e+08 ... 965s ..$ y : num [1:2668] NA NA NA NA NA NA NA NA NA NA ... 965s ..$ index : int [1:2668] 1 2 3 4 5 6 7 8 9 10 ... 965s $ output :'data.frame': 1 obs. of 6 variables: 965s ..$ sampleName: chr NA 965s ..$ chromosome: int 2 965s ..$ start : num 1.44e+08 965s ..$ end : num 1.85e+08 965s ..$ nbrOfLoci : int 775 965s ..$ mean : num 0.097 965s $ segRows:'data.frame': 1 obs. of 2 variables: 965s ..$ startRow: int 15 965s ..$ endRow : int 2664 965s $ params :List of 5 965s ..$ alpha : num 0.001 965s ..$ undo : num 0 965s ..$ joinSegments : logi TRUE 965s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 965s .. ..$ chromosome: int 2 965s .. ..$ start : num 1.44e+08 965s .. ..$ end : num 1.85e+08 965s ..$ seed : int [1:7] 10407 -1924040949 -1632234809 -437763632 -1464377300 676654412 2080370711 965s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 965s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.009 0 0.009 0 0 965s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 965s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 965s - attr(*, "randomSeed")= int [1:7] 10407 -1924040949 -1632234809 -437763632 -1464377300 676654412 2080370711 965s DH segmentation (locally-indexed) rows: 965s startRow endRow 965s 1 15 2664 965s int [1:2668] 7600 7601 7602 7603 7604 7605 7606 7607 7608 7609 ... 965s DH segmentation rows: 965s startRow endRow 965s 1 7614 10263 965s Segmenting DH signals...done 965s DH segmentation table: 965s dhStart dhEnd dhNbrOfLoci dhMean 965s 1 143926517 185449813 775 0.097 965s startRow endRow 965s 1 7614 10263 965s Rows: 965s [1] 2 965s TCN segmentation rows: 965s startRow endRow 965s 2 7600 10267 965s TCN and DH segmentation rows: 965s startRow endRow 965s 2 7600 10267 965s startRow endRow 965s 1 7614 10263 965s startRow endRow 965s 1 1 7599 965s TCN segmentation (expanded) rows: 965s startRow endRow 965s 1 1 7599 965s 2 7600 10267 965s TCN and DH segmentation rows: 965s startRow endRow 965s 1 1 7599 965s 2 7600 10267 965s 3 10268 14658 965s startRow endRow 965s 1 10 7594 965s 2 7614 10263 965s startRow endRow 965s 1 1 7599 965s 2 7600 10267 965s Total CN segmentation table (expanded): 965s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 965s 2 2 143926517 185449813 2668 2.0704 775 775 965s (TCN,DH) segmentation for one total CN segment: 965s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 965s 2 2 1 2 143926517 185449813 2668 2.0704 775 965s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 965s 2 775 143926517 185449813 775 0.097 965s Total CN segment #2 ([1.43927e+08,1.8545e+08]) of 3...done 965s Total CN segment #3 ([1.8545e+08,2.47137e+08]) of 3... 965s Number of TCN loci in segment: 4391 965s Locus data for TCN segment: 965s 'data.frame': 4391 obs. of 9 variables: 965s $ chromosome: int 2 2 2 2 2 2 2 2 2 2 ... 965s $ x : num 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 965s $ CT : num 2.93 2.15 2.82 2.93 2.46 ... 965s $ betaT : num -0.169 0.609 1.028 0.525 0.968 ... 965s $ betaTN : num -0.169 0.609 1.028 0.525 0.968 ... 965s $ betaN : num 0.25 0.38 0.919 0.34 0.783 ... 965s $ muN : num 0 0.5 1 0.5 1 1 0 1 0 1 ... 965s $ index : int 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 965s $ rho : num NA 0.2186 NA 0.0503 NA ... 965s Number of loci: 4391 965s Number of SNPs: 1314 (29.92%) 965s Number of heterozygous SNPs: 1314 (100.00%) 965s Chromosome: 2 965s Segmenting DH signals... 965s Segmenting by CBS... 965s Chromosome: 2 965s Random seed temporarily set (seed=c(10407, -1924040949, -1632234809, -437763632, -1464377300, 676654412, 2080370711), kind="L'Ecuyer-CMRG") 965s Segmenting by CBS...done 965s List of 4 965s $ data :'data.frame': 4391 obs. of 4 variables: 965s ..$ chromosome: int [1:4391] 2 2 2 2 2 2 2 2 2 2 ... 965s ..$ x : num [1:4391] 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 965s ..$ y : num [1:4391] NA 0.2186 NA 0.0503 NA ... 965s ..$ index : int [1:4391] 1 2 3 4 5 6 7 8 9 10 ... 965s $ output :'data.frame': 1 obs. of 6 variables: 965s ..$ sampleName: chr NA 965s ..$ chromosome: int 2 965s ..$ start : num 1.85e+08 965s ..$ end : num 2.47e+08 965s ..$ nbrOfLoci : int 1314 965s ..$ mean : num 0.23 965s $ segRows:'data.frame': 1 obs. of 2 variables: 965s ..$ startRow: int 2 965s ..$ endRow : int 4388 965s $ params :List of 5 965s ..$ alpha : num 0.001 965s ..$ undo : num 0 965s ..$ joinSegments : logi TRUE 965s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 965s .. ..$ chromosome: int 2 965s .. ..$ start : num 1.85e+08 965s .. ..$ end : num 2.47e+08 965s ..$ seed : int [1:7] 10407 -1924040949 -1632234809 -437763632 -1464377300 676654412 2080370711 965s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 965s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.018 0 0.019 0 0 965s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 965s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 965s - attr(*, "randomSeed")= int [1:7] 10407 -1924040949 -1632234809 -437763632 -1464377300 676654412 2080370711 965s DH segmentation (locally-indexed) rows: 965s startRow endRow 965s 1 2 4388 965s int [1:4391] 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 965s DH segmentation rows: 965s startRow endRow 965s 1 10269 14655 965s Segmenting DH signals...done 965s DH segmentation table: 965s dhStart dhEnd dhNbrOfLoci dhMean 965s 1 185449813 247137334 1314 0.2295 965s startRow endRow 965s 1 10269 14655 965s Rows: 965s [1] 3 965s TCN segmentation rows: 965s startRow endRow 965s 3 10268 14658 965s TCN and DH segmentation rows: 965s startRow endRow 965s 3 10268 14658 965s Chromosome #3 ('Chr03') of 3...done 965s Merging (independently) segmented chromosome... 965s startRow endRow 965s 1 10269 14655 965s startRow endRow 965s 1 1 7599 965s 2 7600 10267 965s TCN segmentation (expanded) rows: 965s startRow endRow 965s 1 1 7599 965s 2 7600 10267 965s 3 10268 14658 965s TCN and DH segmentation rows: 965s startRow endRow 965s 1 1 7599 965s 2 7600 10267 965s 3 10268 14658 965s startRow endRow 965s 1 10 7594 965s 2 7614 10263 965s 3 10269 14655 965s startRow endRow 965s 1 1 7599 965s 2 7600 10267 965s 3 10268 14658 965s Total CN segmentation table (expanded): 965s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 965s 3 2 185449813 247137334 4391 2.6341 1314 1314 965s (TCN,DH) segmentation for one total CN segment: 965s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 965s 3 3 1 2 185449813 247137334 4391 2.6341 1314 965s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 965s 3 1314 185449813 247137334 1314 0.2295 965s Total CN segment #3 ([1.8545e+08,2.47137e+08]) of 3...done 965s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 965s 1 2 1 1 554484 143926517 7599 1.3859 2120 965s 2 2 2 1 143926517 185449813 2668 2.0704 775 965s 3 2 3 1 185449813 247137334 4391 2.6341 1314 965s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 965s 1 2120 554484 143926517 2120 0.5101 965s 2 775 143926517 185449813 775 0.0970 965s 3 1314 185449813 247137334 1314 0.2295 965s Calculating (C1,C2) per segment... 965s Calculating (C1,C2) per segment...done 965s Number of segments: 3 965s Segmenting paired tumor-normal signals using Paired PSCBS...done 965s Post-segmenting TCNs... 965s Number of segments: 3 965s Number of chromosomes: 1 965s [1] 2 965s Chromosome 1 ('chr02') of 1... 965s Rows: 965s [1] 1 2 3 965s Number of segments: 3 965s TCN segment #1 ('1') of 3... 965s Nothing todo. Only one DH segmentation. Skipping. 965s TCN segment #1 ('1') of 3...done 965s TCN segment #2 ('2') of 3... 965s Nothing todo. Only one DH segmentation. Skipping. 965s TCN segment #2 ('2') of 3...done 965s TCN segment #3 ('3') of 3... 965s Nothing todo. Only one DH segmentation. Skipping. 965s TCN segment #3 ('3') of 3...done 965s Chromosome 1 ('chr02') of 1...done 965s Update (C1,C2) per segment... 965s Update (C1,C2) per segment...done 965s Post-segmenting TCNs...done 965s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 965s 1 2 1 1 554484 143926517 7599 1.3859 2120 965s 2 2 2 1 143926517 185449813 2668 2.0704 775 965s 3 2 3 1 185449813 247137334 4391 2.6341 1314 965s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 965s 1 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 965s 2 775 143926517 185449813 775 0.0970 0.9347856 1.135614 965s 3 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 965s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 965s 1 2 1 1 554484 143926517 7599 1.3859 2120 965s 2 2 2 1 143926517 185449813 2668 2.0704 775 965s 3 2 3 1 185449813 247137334 4391 2.6341 1314 965s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 965s 1 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 965s 2 775 143926517 185449813 775 0.0970 0.9347856 1.135614 965s 3 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 965s Segmenting paired tumor-normal signals using Paired PSCBS... 965s Setup up data... 965s 'data.frame': 14658 obs. of 7 variables: 965s $ chromosome: int 3 3 3 3 3 3 3 3 3 3 ... 965s $ x : num 554484 730720 782343 878522 916294 ... 965s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 965s $ betaT : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 965s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 965s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 965s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 965s Setup up data...done 965s Ordering data along genome... 965s 'data.frame': 14658 obs. of 7 variables: 965s $ chromosome: int 3 3 3 3 3 3 3 3 3 3 ... 965s $ x : num 554484 730720 782343 878522 916294 ... 965s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 965s $ betaT : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 965s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 965s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 965s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 965s Ordering data along genome...done 965s Keeping only current chromosome for 'knownSegments'... 965s Chromosome: 3 965s Known segments for this chromosome: 965s [1] chromosome start end 965s <0 rows> (or 0-length row.names) 965s Keeping only current chromosome for 'knownSegments'...done 965s alphaTCN: 0.009 965s alphaDH: 0.001 965s Number of loci: 14658 965s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 965s 1 2 1 1 554484 143926517 7599 1.3859 2120 965s 2 2 2 1 143926517 185449813 2668 2.0704 775 965s 3 2 3 1 185449813 247137334 4391 2.6341 1314 965s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 965s 1 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 965s 2 775 143926517 185449813 775 0.0970 0.9347856 1.135614 965s 3 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 965s Calculating DHs... 965s Number of SNPs: 14658 965s Number of heterozygous SNPs: 4209 (28.71%) 965s Normalized DHs: 965s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 965s 1 2 1 1 554484 143926517 7599 1.3859 2120 965s 2 2 2 1 143926517 185449813 2668 2.0704 775 965s 3 2 3 1 185449813 247137334 4391 2.6341 1314 965s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 965s 1 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 965s 2 775 143926517 185449813 775 0.0970 0.9347856 1.135614 965s 3 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 965s num [1:14658] NA NA NA NA NA ... 965s Calculating DHs...done 965s Random seed temporarily set (seed=c(10407, -821273412, -52578226, 1415511586, 721384351, -665928286, 1316562960), kind="L'Ecuyer-CMRG") 965s Produced 2 seeds from this stream for future usage 965s Identification of change points by total copy numbers... 965s Segmenting by CBS... 965s Chromosome: 3 965s Random seed temporarily set (seed=c(10407, -1924040949, -1632234809, -437763632, -1464377300, 676654412, 2080370711), kind="L'Ecuyer-CMRG") 966s Segmenting by CBS...done 966s List of 4 966s $ data :'data.frame': 14658 obs. of 4 variables: 966s ..$ chromosome: int [1:14658] 3 3 3 3 3 3 3 3 3 3 ... 966s ..$ x : num [1:14658] 554484 730720 782343 878522 916294 ... 966s ..$ y : num [1:14658] 1.88 1.8 1.59 1.64 1.53 ... 966s ..$ index : int [1:14658] 1 2 3 4 5 6 7 8 9 10 ... 966s $ output :'data.frame': 3 obs. of 6 variables: 966s ..$ sampleName: chr [1:3] NA NA NA 966s ..$ chromosome: int [1:3] 3 3 3 966s ..$ start : num [1:3] 5.54e+05 1.44e+08 1.85e+08 966s ..$ end : num [1:3] 1.44e+08 1.85e+08 2.47e+08 966s ..$ nbrOfLoci : int [1:3] 7599 2668 4391 966s ..$ mean : num [1:3] 1.39 2.07 2.63 966s $ segRows:'data.frame': 3 obs. of 2 variables: 966s ..$ startRow: int [1:3] 1 7600 10268 966s ..$ endRow : int [1:3] 7599 10267 14658 966s $ params :List of 5 966s ..$ alpha : num 0.009 966s ..$ undo : num 0 966s ..$ joinSegments : logi TRUE 966s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 966s .. ..$ chromosome: int 3 966s .. ..$ start : num -Inf 966s .. ..$ end : num Inf 966s ..$ seed : int [1:7] 10407 -1924040949 -1632234809 -437763632 -1464377300 676654412 2080370711 966s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 966s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.503 0 0.504 0 0 966s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 966s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 966s - attr(*, "randomSeed")= int [1:7] 10407 -1924040949 -1632234809 -437763632 -1464377300 676654412 2080370711 966s Identification of change points by total copy numbers...done 966s Restructure TCN segmentation results... 966s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean 966s 1 3 554484 143926517 7599 1.3859 966s 2 3 143926517 185449813 2668 2.0704 966s 3 3 185449813 247137334 4391 2.6341 966s Number of TCN segments: 3 966s Restructure TCN segmentation results...done 966s Total CN segment #1 ([ 554484,1.43927e+08]) of 3... 966s Number of TCN loci in segment: 7599 966s Locus data for TCN segment: 966s 'data.frame': 7599 obs. of 9 variables: 966s $ chromosome: int 3 3 3 3 3 3 3 3 3 3 ... 966s $ x : num 554484 730720 782343 878522 916294 ... 966s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 966s $ betaT : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 966s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 966s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 966s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 966s $ index : int 1 2 3 4 5 6 7 8 9 10 ... 966s $ rho : num NA NA NA NA NA ... 966s Number of loci: 7599 966s Number of SNPs: 2120 (27.90%) 966s Number of heterozygous SNPs: 2120 (100.00%) 966s Chromosome: 3 966s Segmenting DH signals... 966s Segmenting by CBS... 966s Chromosome: 3 966s Random seed temporarily set (seed=c(10407, -1371615447, -889757879, 1692656974, -1723952224, 1378814990, 1816467252), kind="L'Ecuyer-CMRG") 966s Segmenting by CBS...done 966s List of 4 966s $ data :'data.frame': 7599 obs. of 4 variables: 966s ..$ chromosome: int [1:7599] 3 3 3 3 3 3 3 3 3 3 ... 966s ..$ x : num [1:7599] 554484 730720 782343 878522 916294 ... 966s ..$ y : num [1:7599] NA NA NA NA NA ... 966s ..$ index : int [1:7599] 1 2 3 4 5 6 7 8 9 10 ... 966s $ output :'data.frame': 1 obs. of 6 variables: 966s ..$ sampleName: chr NA 966s ..$ chromosome: int 3 966s ..$ start : num 554484 966s ..$ end : num 1.44e+08 966s ..$ nbrOfLoci : int 2120 966s ..$ mean : num 0.51 966s $ segRows:'data.frame': 1 obs. of 2 variables: 966s ..$ startRow: int 10 966s ..$ endRow : int 7594 966s $ params :List of 5 966s ..$ alpha : num 0.001 966s ..$ undo : num 0 966s ..$ joinSegments : logi TRUE 966s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 966s .. ..$ chromosome: int 3 966s .. ..$ start : num 554484 966s .. ..$ end : num 1.44e+08 966s ..$ seed : int [1:7] 10407 -1371615447 -889757879 1692656974 -1723952224 1378814990 1816467252 966s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 966s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.031 0 0.032 0 0 966s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 966s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 966s - attr(*, "randomSeed")= int [1:7] 10407 -1371615447 -889757879 1692656974 -1723952224 1378814990 1816467252 966s DH segmentation (locally-indexed) rows: 966s startRow endRow 966s 1 10 7594 966s int [1:7599] 1 2 3 4 5 6 7 8 9 10 ... 966s DH segmentation rows: 966s startRow endRow 966s 1 10 7594 966s Segmenting DH signals...done 966s DH segmentation table: 966s dhStart dhEnd dhNbrOfLoci dhMean 966s 1 554484 143926517 2120 0.5101 966s startRow endRow 966s 1 10 7594 966s Rows: 966s [1] 1 966s TCN segmentation rows: 966s startRow endRow 966s 1 1 7599 966s TCN and DH segmentation rows: 966s startRow endRow 966s 1 1 7599 966s startRow endRow 966s 1 10 7594 966s NULL 966s TCN segmentation (expanded) rows: 966s startRow endRow 966s 1 1 7599 966s TCN and DH segmentation rows: 966s startRow endRow 966s 1 1 7599 966s 2 7600 10267 966s 3 10268 14658 966s startRow endRow 966s 1 10 7594 966s startRow endRow 966s 1 1 7599 966s Total CN segmentation table (expanded): 966s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 966s 1 3 554484 143926517 7599 1.3859 2120 2120 966s (TCN,DH) segmentation for one total CN segment: 966s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 966s 1 1 1 3 554484 143926517 7599 1.3859 2120 966s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 966s 1 2120 554484 143926517 2120 0.5101 966s Total CN segment #1 ([ 554484,1.43927e+08]) of 3...done 966s Total CN segment #2 ([1.43927e+08,1.8545e+08]) of 3... 966s Number of TCN loci in segment: 2668 966s Locus data for TCN segment: 966s 'data.frame': 2668 obs. of 9 variables: 966s $ chromosome: int 3 3 3 3 3 3 3 3 3 3 ... 966s $ x : num 1.44e+08 1.44e+08 1.44e+08 1.44e+08 1.44e+08 ... 966s $ CT : num 2.1 2.1 2.09 1.8 2.34 ... 966s $ betaT : num 0.027542 1.030222 1.094093 0.046763 -0.000948 ... 966s $ betaTN : num 0.027542 1.030222 1.094093 0.046763 -0.000948 ... 966s $ betaN : num 0.1624 0.8788 0.8225 0.1201 0.0317 ... 966s $ muN : num 0 1 1 0 0 1 0 0 0 0 ... 966s $ index : int 7600 7601 7602 7603 7604 7605 7606 7607 7608 7609 ... 966s $ rho : num NA NA NA NA NA NA NA NA NA NA ... 966s Number of loci: 2668 966s Number of SNPs: 775 (29.05%) 966s Number of heterozygous SNPs: 775 (100.00%) 966s Chromosome: 3 966s Segmenting DH signals... 966s Segmenting by CBS... 966s Chromosome: 3 966s Random seed temporarily set (seed=c(10407, -1371615447, -889757879, 1692656974, -1723952224, 1378814990, 1816467252), kind="L'Ecuyer-CMRG") 966s Segmenting by CBS...done 966s List of 4 966s $ data :'data.frame': 2668 obs. of 4 variables: 966s ..$ chromosome: int [1:2668] 3 3 3 3 3 3 3 3 3 3 ... 966s ..$ x : num [1:2668] 1.44e+08 1.44e+08 1.44e+08 1.44e+08 1.44e+08 ... 966s ..$ y : num [1:2668] NA NA NA NA NA NA NA NA NA NA ... 966s ..$ index : int [1:2668] 1 2 3 4 5 6 7 8 9 10 ... 966s $ output :'data.frame': 1 obs. of 6 variables: 966s ..$ sampleName: chr NA 966s ..$ chromosome: int 3 966s ..$ start : num 1.44e+08 966s ..$ end : num 1.85e+08 966s ..$ nbrOfLoci : int 775 966s ..$ mean : num 0.097 966s $ segRows:'data.frame': 1 obs. of 2 variables: 966s ..$ startRow: int 15 966s ..$ endRow : int 2664 966s $ params :List of 5 966s ..$ alpha : num 0.001 966s ..$ undo : num 0 966s ..$ joinSegments : logi TRUE 966s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 966s .. ..$ chromosome: int 3 966s .. ..$ start : num 1.44e+08 966s .. ..$ end : num 1.85e+08 966s ..$ seed : int [1:7] 10407 -1371615447 -889757879 1692656974 -1723952224 1378814990 1816467252 966s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 966s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.009 0 0.009 0 0 966s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 966s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 966s - attr(*, "randomSeed")= int [1:7] 10407 -1371615447 -889757879 1692656974 -1723952224 1378814990 1816467252 966s DH segmentation (locally-indexed) rows: 966s startRow endRow 966s 1 15 2664 966s int [1:2668] 7600 7601 7602 7603 7604 7605 7606 7607 7608 7609 ... 966s DH segmentation rows: 966s startRow endRow 966s 1 7614 10263 966s Segmenting DH signals...done 966s DH segmentation table: 966s dhStart dhEnd dhNbrOfLoci dhMean 966s 1 143926517 185449813 775 0.097 966s startRow endRow 966s 1 7614 10263 966s Rows: 966s [1] 2 966s TCN segmentation rows: 966s startRow endRow 966s 2 7600 10267 966s TCN and DH segmentation rows: 966s startRow endRow 966s 2 7600 10267 966s startRow endRow 966s 1 7614 10263 966s startRow endRow 966s 1 1 7599 966s TCN segmentation (expanded) rows: 966s startRow endRow 966s 1 1 7599 966s 2 7600 10267 966s TCN and DH segmentation rows: 966s startRow endRow 966s 1 1 7599 966s 2 7600 10267 966s 3 10268 14658 966s startRow endRow 966s 1 10 7594 966s 2 7614 10263 966s startRow endRow 966s 1 1 7599 966s 2 7600 10267 966s Total CN segmentation table (expanded): 966s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 966s 2 3 143926517 185449813 2668 2.0704 775 775 966s (TCN,DH) segmentation for one total CN segment: 966s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 966s 2 2 1 3 143926517 185449813 2668 2.0704 775 966s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 966s 2 775 143926517 185449813 775 0.097 966s Total CN segment #2 ([1.43927e+08,1.8545e+08]) of 3...done 966s Total CN segment #3 ([1.8545e+08,2.47137e+08]) of 3... 966s Number of TCN loci in segment: 4391 966s Locus data for TCN segment: 966s 'data.frame': 4391 obs. of 9 variables: 966s $ chromosome: int 3 3 3 3 3 3 3 3 3 3 ... 966s $ x : num 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 966s $ CT : num 2.93 2.15 2.82 2.93 2.46 ... 966s $ betaT : num -0.169 0.609 1.028 0.525 0.968 ... 966s $ betaTN : num -0.169 0.609 1.028 0.525 0.968 ... 966s $ betaN : num 0.25 0.38 0.919 0.34 0.783 ... 966s $ muN : num 0 0.5 1 0.5 1 1 0 1 0 1 ... 966s $ index : int 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 966s $ rho : num NA 0.2186 NA 0.0503 NA ... 966s Number of loci: 4391 966s Number of SNPs: 1314 (29.92%) 966s Number of heterozygous SNPs: 1314 (100.00%) 966s Chromosome: 3 966s Segmenting DH signals... 966s Segmenting by CBS... 966s Chromosome: 3 966s Random seed temporarily set (seed=c(10407, -1371615447, -889757879, 1692656974, -1723952224, 1378814990, 1816467252), kind="L'Ecuyer-CMRG") 966s Segmenting by CBS...done 966s List of 4 966s $ data :'data.frame': 4391 obs. of 4 variables: 966s ..$ chromosome: int [1:4391] 3 3 3 3 3 3 3 3 3 3 ... 966s ..$ x : num [1:4391] 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 966s ..$ y : num [1:4391] NA 0.2186 NA 0.0503 NA ... 966s ..$ index : int [1:4391] 1 2 3 4 5 6 7 8 9 10 ... 966s $ output :'data.frame': 1 obs. of 6 variables: 966s ..$ sampleName: chr NA 966s ..$ chromosome: int 3 966s ..$ start : num 1.85e+08 966s ..$ end : num 2.47e+08 966s ..$ nbrOfLoci : int 1314 966s ..$ mean : num 0.23 966s $ segRows:'data.frame': 1 obs. of 2 variables: 966s ..$ startRow: int 2 966s ..$ endRow : int 4388 966s $ params :List of 5 966s ..$ alpha : num 0.001 966s ..$ undo : num 0 966s ..$ joinSegments : logi TRUE 966s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 966s .. ..$ chromosome: int 3 966s .. ..$ start : num 1.85e+08 966s .. ..$ end : num 2.47e+08 966s ..$ seed : int [1:7] 10407 -1371615447 -889757879 1692656974 -1723952224 1378814990 1816467252 966s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 966s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.018 0 0.018 0 0 966s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 966s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 966s - attr(*, "randomSeed")= int [1:7] 10407 -1371615447 -889757879 1692656974 -1723952224 1378814990 1816467252 966s DH segmentation (locally-indexed) rows: 966s startRow endRow 966s 1 2 4388 966s int [1:4391] 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 966s DH segmentation rows: 966s startRow endRow 966s 1 10269 14655 966s Segmenting DH signals...done 966s DH segmentation table: 966s dhStart dhEnd dhNbrOfLoci dhMean 966s 1 185449813 247137334 1314 0.2295 966s startRow endRow 966s 1 10269 14655 966s Rows: 966s [1] 3 966s TCN segmentation rows: 966s startRow endRow 966s 3 10268 14658 966s TCN and DH segmentation rows: 966s startRow endRow 966s 3 10268 14658 966s startRow endRow 966s 1 10269 14655 966s startRow endRow 966s 1 1 7599 966s 2 7600 10267 966s TCN segmentation (expanded) rows: 966s startRow endRow 966s 1 1 7599 966s 2 7600 10267 966s 3 10268 14658 966s TCN and DH segmentation rows: 966s startRow endRow 966s 1 1 7599 966s 2 7600 10267 966s 3 10268 14658 966s startRow endRow 966s 1 10 7594 966s 2 7614 10263 966s 3 10269 14655 966s startRow endRow 966s 1 1 7599 966s 2 7600 10267 966s 3 10268 14658 966s Total CN segmentation table (expanded): 966s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 966s 3 3 185449813 247137334 4391 2.6341 1314 1314 966s (TCN,DH) segmentation for one total CN segment: 966s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 966s 3 3 1 3 185449813 247137334 4391 2.6341 1314 966s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 966s 3 1314 185449813 247137334 1314 0.2295 966s Total CN segment #3 ([1.8545e+08,2.47137e+08]) of 3...done 966s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 966s 1 3 1 1 554484 143926517 7599 1.3859 2120 966s 2 3 2 1 143926517 185449813 2668 2.0704 775 966s 3 3 3 1 185449813 247137334 4391 2.6341 1314 966s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 966s 1 2120 554484 143926517 2120 0.5101 966s 2 775 143926517 185449813 775 0.0970 966s 3 1314 185449813 247137334 1314 0.2295 966s Calculating (C1,C2) per segment... 966s Calculating (C1,C2) per segment...done 966s Number of segments: 3 966s Segmenting paired tumor-normal signals using Paired PSCBS...done 966s Post-segmenting TCNs... 966s Number of segments: 3 966s Number of chromosomes: 1 966s [1] 3 966s Chromosome 1 ('chr03') of 1... 966s Rows: 966s [1] 1 2 3 966s Number of segments: 3 966s TCN segment #1 ('1') of 3... 966s Nothing todo. Only one DH segmentation. Skipping. 966s TCN segment #1 ('1') of 3...done 966s TCN segment #2 ('2') of 3... 966s Nothing todo. Only one DH segmentation. Skipping. 966s TCN segment #2 ('2') of 3...done 966s TCN segment #3 ('3') of 3... 966s Nothing todo. Only one DH segmentation. Skipping. 966s TCN segment #3 ('3') of 3...done 966s Chromosome 1 ('chr03') of 1...done 966s Update (C1,C2) per segment... 966s Update (C1,C2) per segment...done 966s Post-segmenting TCNs...done 966s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 966s 1 3 1 1 554484 143926517 7599 1.3859 2120 966s 2 3 2 1 143926517 185449813 2668 2.0704 775 966s 3 3 3 1 185449813 247137334 4391 2.6341 1314 966s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 966s 1 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 966s 2 775 143926517 185449813 775 0.0970 0.9347856 1.135614 966s 3 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 966s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 966s 1 3 1 1 554484 143926517 7599 1.3859 2120 966s 2 3 2 1 143926517 185449813 2668 2.0704 775 966s 3 3 3 1 185449813 247137334 4391 2.6341 1314 966s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 966s 1 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 966s 2 775 143926517 185449813 775 0.0970 0.9347856 1.135614 966s 3 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 966s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 966s 1 3 1 1 554484 143926517 7599 1.3859 2120 966s 2 3 2 1 143926517 185449813 2668 2.0704 775 966s 3 3 3 1 185449813 247137334 4391 2.6341 1314 966s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 966s 1 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 966s 2 775 143926517 185449813 775 0.0970 0.9347856 1.135614 966s 3 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 966s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 966s 1 3 1 1 554484 143926517 7599 1.3859 2120 966s 2 3 2 1 143926517 185449813 2668 2.0704 775 966s 3 3 3 1 185449813 247137334 4391 2.6341 1314 966s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 966s 1 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 966s 2 775 143926517 185449813 775 0.0970 0.9347856 1.135614 966s 3 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 966s List of 5 966s $ data :Classes ‘PairedPSCNData’ and 'data.frame': 43974 obs. of 8 variables: 966s ..$ chromosome: int [1:43974] 1 1 1 1 1 1 1 1 1 1 ... 966s ..$ x : num [1:43974] 554484 730720 782343 878522 916294 ... 966s ..$ CT : num [1:43974] 1.88 1.8 1.59 1.64 1.53 ... 966s ..$ betaT : num [1:43974] 0.0646 0.1672 0.9284 0.113 0.7209 ... 966s ..$ betaTN : num [1:43974] -0.0515 -0.1172 1.0194 0.031 0.8604 ... 966s ..$ betaN : num [1:43974] 0.116 0.284 0.909 0.082 0.86 ... 966s ..$ muN : num [1:43974] 0 0 1 0 1 1 1 0 1 0.5 ... 966s ..$ rho : num [1:43974] NA NA NA NA NA ... 966s $ output :Classes ‘PairedPSCNSegments’ and 'data.frame': 11 obs. of 15 variables: 966s ..$ chromosome : int [1:11] 1 1 1 NA 2 2 2 NA 3 3 ... 966s ..$ tcnId : int [1:11] 1 2 3 NA 1 2 3 NA 1 2 ... 966s ..$ dhId : int [1:11] 1 1 1 NA 1 1 1 NA 1 1 ... 966s ..$ tcnStart : num [1:11] 5.54e+05 1.44e+08 1.85e+08 NA 5.54e+05 ... 966s ..$ tcnEnd : num [1:11] 1.44e+08 1.85e+08 2.47e+08 NA 1.44e+08 ... 966s ..$ tcnNbrOfLoci: int [1:11] 7599 2668 4391 NA 7599 2668 4391 NA 7599 2668 ... 966s ..$ tcnMean : num [1:11] 1.39 2.07 2.63 NA 1.39 ... 966s ..$ tcnNbrOfSNPs: int [1:11] 2120 775 1314 NA 2120 775 1314 NA 2120 775 ... 966s ..$ tcnNbrOfHets: int [1:11] 2120 775 1314 NA 2120 775 1314 NA 2120 775 ... 966s ..$ dhStart : num [1:11] 5.54e+05 1.44e+08 1.85e+08 NA 5.54e+05 ... 966s ..$ dhEnd : num [1:11] 1.44e+08 1.85e+08 2.47e+08 NA 1.44e+08 ... 966s ..$ dhNbrOfLoci : int [1:11] 2120 775 1314 NA 2120 775 1314 NA 2120 775 ... 966s ..$ dhMean : num [1:11] 0.51 0.097 0.23 NA 0.51 ... 966s ..$ c1Mean : num [1:11] 0.339 0.935 1.015 NA 0.339 ... 966s ..$ c2Mean : num [1:11] 1.05 1.14 1.62 NA 1.05 ... 966s $ tcnSegRows:'data.frame': 11 obs. of 2 variables: 966s ..$ startRow: int [1:11] 1 7600 10268 NA 14659 22258 24926 NA 29317 36916 ... 966s ..$ endRow : int [1:11] 7599 10267 14658 NA 22257 24925 29316 NA 36915 39583 ... 966s $ dhSegRows :'data.frame': 11 obs. of 2 variables: 966s ..$ startRow: int [1:11] 10 7614 10269 NA 14668 22272 24927 NA 29326 36930 ... 966s ..$ endRow : int [1:11] 7594 10263 14655 NA 22252 24921 29313 NA 36910 39579 ... 966s $ params :List of 7 966s ..$ alphaTCN : num 0.009 966s ..$ alphaDH : num 0.001 966s ..$ flavor : chr "tcn&dh" 966s ..$ tbn : logi FALSE 966s ..$ joinSegments : logi TRUE 966s ..$ knownSegments:'data.frame': 0 obs. of 3 variables: 966s .. ..$ chromosome: int(0) 966s .. ..$ start : int(0) 966s .. ..$ end : int(0) 966s ..$ seed : int [1:7] 10407 1066287653 -51199871 161854402 -1995183193 1503453565 -747102133 966s - attr(*, "class")= chr [1:3] "PairedPSCBS" "PSCBS" "AbstractCBS" 966s Merging (independently) segmented chromosome...done 966s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 966s 1 1 1 1 554484 143926517 7599 1.3859 2120 966s 2 1 2 1 143926517 185449813 2668 2.0704 775 966s 3 1 3 1 185449813 247137334 4391 2.6341 1314 966s 4 NA NA NA NA NA NA NA NA 966s 5 2 1 1 554484 143926517 7599 1.3859 2120 966s 6 2 2 1 143926517 185449813 2668 2.0704 775 966s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 966s 1 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 966s 2 775 143926517 185449813 775 0.0970 0.9347856 1.135614 966s 3 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 966s 4 NA NA NA NA NA NA NA 966s 5 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 966s 6 775 143926517 185449813 775 0.0970 0.9347856 1.135614 966s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 966s 6 2 2 1 143926517 185449813 2668 2.0704 775 966s 7 2 3 1 185449813 247137334 4391 2.6341 1314 966s 8 NA NA NA NA NA NA NA NA 966s 9 3 1 1 554484 143926517 7599 1.3859 2120 966s 10 3 2 1 143926517 185449813 2668 2.0704 775 966s 11 3 3 1 185449813 247137334 4391 2.6341 1314 966s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 966s 6 775 143926517 185449813 775 0.0970 0.9347856 1.135614 966s 7 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 966s 8 NA NA NA NA NA NA NA 966s 9 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 966s 10 775 143926517 185449813 775 0.0970 0.9347856 1.135614 966s 11 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 966s Segmenting multiple chromosomes...done 966s Segmenting paired tumor-normal signals using Paired PSCBS...done 966s *** segmentByPairedPSCBS() via futures ... DONE 966s *** segmentByPairedPSCBS() via futures with known segments ... 966s > 966s > message("*** segmentByPairedPSCBS() via futures ... DONE") 966s > 966s > 966s > message("*** segmentByPairedPSCBS() via futures with known segments ...") 966s > fits <- list() 966s > dataT <- subset(data, chromosome == 1) 966s > gaps <- findLargeGaps(dataT, minLength=2e6) 966s > knownSegments <- gapsToSegments(gaps) 966s > 966s > for (strategy in strategies) { 966s + message(sprintf("- segmentByPairedPSCBS() w/ known segments using '%s' futures ...", strategy)) 966s + plan(strategy) 966s + fit <- segmentByPairedPSCBS(dataT, knownSegments=knownSegments, seed=0xBEEF, verbose=TRUE) 966s + fits[[strategy]] <- fit 966s + equal <- all.equal(fit, fits[[1]]) 966s + if (!equal) { 966s + str(fit) 966s + str(fits[[1]]) 966s + print(equal) 966s + stop(sprintf("segmentByPairedPSCBS() w/ known segments using '%s' futures does not produce the same results as when using '%s' futures", strategy, names(fits)[1])) 966s + } 966s + } 966s - segmentByPairedPSCBS() w/ known segments using 'sequential' futures ... 966s Segmenting paired tumor-normal signals using Paired PSCBS... 966s Calling genotypes from normal allele B fractions... 966s num [1:14670] 0.8274 0.5072 0.1671 0.1609 0.0421 ... 966s Called genotypes: 966s num [1:14670] 1 0.5 0 0 0 0 1 0 1 0.5 ... 966s - attr(*, "modelFit")=List of 1 966s ..$ :List of 7 966s .. ..$ flavor : chr "density" 966s .. ..$ cn : int 2 966s .. ..$ nbrOfGenotypeGroups: int 3 966s .. ..$ tau : num [1:2] 0.315 0.677 966s .. ..$ n : int 14640 966s .. ..$ fit :Classes ‘PeaksAndValleys’ and 'data.frame': 5 obs. of 3 variables: 966s .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 966s .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 966s .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 966s .. ..$ fitValleys :Classes ‘PeaksAndValleys’ and 'data.frame': 2 obs. of 3 variables: 966s .. .. ..$ type : chr [1:2] "valley" "valley" 966s .. .. ..$ x : num [1:2] 0.315 0.677 966s .. .. ..$ density: num [1:2] 0.522 0.551 966s ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 966s muN 966s 0 0.5 1 966s 5221 4198 5251 966s Calling genotypes from normal allele B fractions...done 966s Normalizing betaT using betaN (TumorBoost)... 966s Normalized BAFs: 966s num [1:14670] 0.9301 0.1667 0.0685 0.0995 0.0155 ... 966s - attr(*, "modelFit")=List of 5 966s ..$ method : chr "normalizeTumorBoost" 966s ..$ flavor : chr "v4" 966s ..$ delta : num [1:14670] -0.17264 0.00239 0.1671 0.16085 0.04213 ... 966s .. ..- attr(*, "modelFit")=List of 1 966s .. .. ..$ :List of 7 966s .. .. .. ..$ flavor : chr "density" 966s .. .. .. ..$ cn : int 2 966s .. .. .. ..$ nbrOfGenotypeGroups: int 3 966s .. .. .. ..$ tau : num [1:2] 0.315 0.677 966s .. .. .. ..$ n : int 14640 966s .. .. .. ..$ fit :Classes ‘PeaksAndValleys’ and 'data.frame': 5 obs. of 3 variables: 966s .. .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 966s .. .. .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 966s .. .. .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 966s .. .. .. ..$ fitValleys :Classes ‘PeaksAndValleys’ and 'data.frame': 2 obs. of 3 variables: 966s .. .. .. .. ..$ type : chr [1:2] "valley" "valley" 966s .. .. .. .. ..$ x : num [1:2] 0.315 0.677 966s .. .. .. .. ..$ density: num [1:2] 0.522 0.551 966s .. .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 966s ..$ preserveScale: logi FALSE 966s ..$ scaleFactor : num NA 966s Normalizing betaT using betaN (TumorBoost)...done 966s Setup up data... 966s 'data.frame': 14670 obs. of 7 variables: 966s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 966s $ x : num 1145994 2941694 3710825 4240737 4276892 ... 966s $ CT : num 1.63 1.4 1.41 1.17 1.16 ... 966s $ betaT : num 0.7574 0.169 0.2357 0.2604 0.0576 ... 966s $ betaTN : num 0.9301 0.1667 0.0685 0.0995 0.0155 ... 966s ..- attr(*, "modelFit")=List of 5 966s .. ..$ method : chr "normalizeTumorBoost" 966s .. ..$ flavor : chr "v4" 966s .. ..$ delta : num [1:14670] -0.17264 0.00239 0.1671 0.16085 0.04213 ... 966s .. .. ..- attr(*, "modelFit")=List of 1 966s .. .. .. ..$ :List of 7 966s .. .. .. .. ..$ flavor : chr "density" 966s .. .. .. .. ..$ cn : int 2 966s .. .. .. .. ..$ nbrOfGenotypeGroups: int 3 966s .. .. .. .. ..$ tau : num [1:2] 0.315 0.677 966s .. .. .. .. ..$ n : int 14640 966s .. .. .. .. ..$ fit :Classes ‘PeaksAndValleys’ and 'data.frame': 5 obs. of 3 variables: 966s .. .. .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 966s .. .. .. .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 966s .. .. .. .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 966s .. .. .. .. ..$ fitValleys :Classes ‘PeaksAndValleys’ and 'data.frame': 2 obs. of 3 variables: 966s .. .. .. .. .. ..$ type : chr [1:2] "valley" "valley" 966s .. .. .. .. .. ..$ x : num [1:2] 0.315 0.677 966s .. .. .. .. .. ..$ density: num [1:2] 0.522 0.551 966s .. .. .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 966s .. ..$ preserveScale: logi FALSE 966s .. ..$ scaleFactor : num NA 966s $ betaN : num 0.8274 0.5072 0.1671 0.1609 0.0421 ... 966s $ muN : num 1 0.5 0 0 0 0 1 0 1 0.5 ... 966s ..- attr(*, "modelFit")=List of 1 966s .. ..$ :List of 7 966s .. .. ..$ flavor : chr "density" 966s .. .. ..$ cn : int 2 966s .. .. ..$ nbrOfGenotypeGroups: int 3 966s .. .. ..$ tau : num [1:2] 0.315 0.677 966s .. .. ..$ n : int 14640 966s .. .. ..$ fit :Classes ‘PeaksAndValleys’ and 'data.frame': 5 obs. of 3 variables: 966s .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 966s .. .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 966s .. .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 966s .. .. ..$ fitValleys :Classes ‘PeaksAndValleys’ and 'data.frame': 2 obs. of 3 variables: 966s .. .. .. ..$ type : chr [1:2] "valley" "valley" 966s .. .. .. ..$ x : num [1:2] 0.315 0.677 966s .. .. .. ..$ density: num [1:2] 0.522 0.551 966s .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 966s Setup up data...done 966s Dropping loci for which TCNs are missing... 966s Number of loci dropped: 12 966s Dropping loci for which TCNs are missing...done 966s Ordering data along genome... 966s 'data.frame': 14658 obs. of 7 variables: 966s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 966s $ x : num 554484 730720 782343 878522 916294 ... 966s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 966s $ betaT : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 966s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 966s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 966s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 966s Ordering data along genome...done 966s Keeping only current chromosome for 'knownSegments'... 966s Chromosome: 1 966s Known segments for this chromosome: 966s chromosome start end length 966s 1 1 -Inf 120908858 Inf 966s 2 1 120908859 142693887 21785028 966s 3 1 142693888 Inf Inf 966s Keeping only current chromosome for 'knownSegments'...done 966s alphaTCN: 0.009 966s alphaDH: 0.001 966s Number of loci: 14658 966s Calculating DHs... 966s Number of SNPs: 14658 966s Number of heterozygous SNPs: 4196 (28.63%) 966s Normalized DHs: 966s num [1:14658] NA NA NA NA NA ... 966s Calculating DHs...done 966s Random seed temporarily set (seed=c(48879), kind="L'Ecuyer-CMRG") 966s Produced 2 seeds from this stream for future usage 966s Identification of change points by total copy numbers... 966s Segmenting by CBS... 966s Chromosome: 1 966s Random seed temporarily set (seed=c(10407, 1066287653, -51199871, 161854402, -1995183193, 1503453565, -747102133), kind="L'Ecuyer-CMRG") 966s Produced 3 seeds from this stream for future usage 967s Segmenting by CBS...done 967s List of 4 967s $ data :'data.frame': 14658 obs. of 4 variables: 967s ..$ chromosome: int [1:14658] 1 1 1 1 1 1 1 1 1 1 ... 967s ..$ x : num [1:14658] 554484 730720 782343 878522 916294 ... 967s ..$ y : num [1:14658] 1.88 1.8 1.59 1.64 1.53 ... 967s ..$ index : int [1:14658] 1 2 3 4 5 6 7 8 9 10 ... 967s $ output :'data.frame': 4 obs. of 6 variables: 967s ..$ sampleName: chr [1:4] NA NA NA NA 967s ..$ chromosome: int [1:4] 1 1 1 1 967s ..$ start : num [1:4] 5.54e+05 1.21e+08 1.43e+08 1.85e+08 967s ..$ end : num [1:4] 1.21e+08 1.43e+08 1.85e+08 2.47e+08 967s ..$ nbrOfLoci : int [1:4] 7586 0 2681 4391 967s ..$ mean : num [1:4] 1.39 NA 2.07 2.63 967s $ segRows:'data.frame': 4 obs. of 2 variables: 967s ..$ startRow: int [1:4] 1 NA 7587 10268 967s ..$ endRow : int [1:4] 7586 NA 10267 14658 967s $ params :List of 5 967s ..$ alpha : num 0.009 967s ..$ undo : num 0 967s ..$ joinSegments : logi TRUE 967s ..$ knownSegments:'data.frame': 4 obs. of 3 variables: 967s .. ..$ chromosome: int [1:4] 1 1 2 1 967s .. ..$ start : num [1:4] -Inf -Inf -Inf 1.43e+08 967s .. ..$ end : num [1:4] 1.21e+08 Inf Inf Inf 967s ..$ seed : int [1:7] 10407 1066287653 -51199871 161854402 -1995183193 1503453565 -747102133 967s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 967s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.166 0 0.167 0 0 967s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 967s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 967s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 967s Identification of change points by total copy numbers...done 967s Restructure TCN segmentation results... 967s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean 967s 1 1 554484 120908858 7586 1.3853 967s 2 1 120908859 142693887 0 NA 967s 3 1 142693888 185449813 2681 2.0689 967s 4 1 185449813 247137334 4391 2.6341 967s Number of TCN segments: 4 967s Restructure TCN segmentation results...done 967s Total CN segment #1 ([ 554484,1.20909e+08]) of 4... 967s Number of TCN loci in segment: 7586 967s Locus data for TCN segment: 967s 'data.frame': 7586 obs. of 9 variables: 967s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 967s $ x : num 554484 730720 782343 878522 916294 ... 967s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 967s $ betaT : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 967s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 967s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 967s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 967s $ index : int 1 2 3 4 5 6 7 8 9 10 ... 967s $ rho : num NA NA NA NA NA ... 967s Number of loci: 7586 967s Number of SNPs: 2108 (27.79%) 967s Number of heterozygous SNPs: 2108 (100.00%) 967s Chromosome: 1 967s Segmenting DH signals... 967s Segmenting by CBS... 967s Chromosome: 1 967s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 967s Segmenting by CBS...done 967s List of 4 967s $ data :'data.frame': 7586 obs. of 4 variables: 967s ..$ chromosome: int [1:7586] 1 1 1 1 1 1 1 1 1 1 ... 967s ..$ x : num [1:7586] 554484 730720 782343 878522 916294 ... 967s ..$ y : num [1:7586] NA NA NA NA NA ... 967s ..$ index : int [1:7586] 1 2 3 4 5 6 7 8 9 10 ... 967s $ output :'data.frame': 1 obs. of 6 variables: 967s ..$ sampleName: chr NA 967s ..$ chromosome: int 1 967s ..$ start : num 554484 967s ..$ end : num 1.21e+08 967s ..$ nbrOfLoci : int 2108 967s ..$ mean : num 0.512 967s $ segRows:'data.frame': 1 obs. of 2 variables: 967s ..$ startRow: int 10 967s ..$ endRow : int 7574 967s $ params :List of 5 967s ..$ alpha : num 0.001 967s ..$ undo : num 0 967s ..$ joinSegments : logi TRUE 967s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 967s .. ..$ chromosome: int 1 967s .. ..$ start : num 554484 967s .. ..$ end : num 1.21e+08 967s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 967s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 967s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.047 0 0.047 0 0 967s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 967s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 967s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 967s DH segmentation (locally-indexed) rows: 967s startRow endRow 967s 1 10 7574 967s int [1:7586] 1 2 3 4 5 6 7 8 9 10 ... 967s DH segmentation rows: 967s startRow endRow 967s 1 10 7574 967s Segmenting DH signals...done 967s DH segmentation table: 967s dhStart dhEnd dhNbrOfLoci dhMean 967s 1 554484 120908858 2108 0.5116 967s startRow endRow 967s 1 10 7574 967s Rows: 967s [1] 1 967s TCN segmentation rows: 967s startRow endRow 967s 1 1 7586 967s TCN and DH segmentation rows: 967s startRow endRow 967s 1 1 7586 967s startRow endRow 967s 1 10 7574 967s NULL 967s TCN segmentation (expanded) rows: 967s startRow endRow 967s 1 1 7586 967s TCN and DH segmentation rows: 967s startRow endRow 967s 1 1 7586 967s 2 NA NA 967s 3 7587 10267 967s 4 10268 14658 967s startRow endRow 967s 1 10 7574 967s startRow endRow 967s 1 1 7586 967s Total CN segmentation table (expanded): 967s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 967s 1 1 554484 120908858 7586 1.3853 2108 2108 967s (TCN,DH) segmentation for one total CN segment: 967s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 967s 1 1 1 1 554484 120908858 7586 1.3853 2108 967s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 967s 1 2108 554484 120908858 2108 0.5116 967s Total CN segment #1 ([ 554484,1.20909e+08]) of 4...done 967s Total CN segment #2 ([1.20909e+08,1.42694e+08]) of 4... 967s Number of TCN loci in segment: 0 967s Locus data for TCN segment: 967s 'data.frame': 0 obs. of 9 variables: 967s $ chromosome: int 967s $ x : num 967s $ CT : num 967s $ betaT : num 967s $ betaTN : num 967s $ betaN : num 967s $ muN : num 967s $ index : int 967s $ rho : num 967s Number of loci: 0 967s Number of SNPs: 0 (NaN%) 967s Number of heterozygous SNPs: 0 (NaN%) 967s Chromosome: 1 967s Segmenting DH signals... 967s Segmenting by CBS... 967s Chromosome: NA 967s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 967s Segmenting by CBS...done 967s List of 4 967s $ data :'data.frame': 0 obs. of 4 variables: 967s ..$ chromosome: int(0) 967s ..$ x : num(0) 967s ..$ y : num(0) 967s ..$ index : int(0) 967s $ output :'data.frame': 0 obs. of 6 variables: 967s ..$ sampleName: chr(0) 967s ..$ chromosome: num(0) 967s ..$ start : num(0) 967s ..$ end : num(0) 967s ..$ nbrOfLoci : int(0) 967s ..$ mean : num(0) 967s $ segRows:'data.frame': 0 obs. of 2 variables: 967s ..$ startRow: int(0) 967s ..$ endRow : int(0) 967s $ params :List of 5 967s ..$ alpha : num 0.001 967s ..$ undo : num 0 967s ..$ joinSegments : logi TRUE 967s ..$ knownSegments:'data.frame': 0 obs. of 3 variables: 967s .. ..$ chromosome: int(0) 967s .. ..$ start : num(0) 967s .. ..$ end : num(0) 967s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 967s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 967s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.002 0 0.001 0 0 967s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 967s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 967s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 967s DH segmentation (locally-indexed) rows: 967s [1] startRow endRow 967s <0 rows> (or 0-length row.names) 967s int(0) 967s DH segmentation rows: 967s [1] startRow endRow 967s <0 rows> (or 0-length row.names) 967s Segmenting DH signals...done 967s DH segmentation table: 967s dhStart dhEnd dhNbrOfLoci dhMean 967s NA NA NA NA NA 967s startRow endRow 967s NA NA NA 967s Rows: 967s [1] 2 967s TCN segmentation rows: 967s startRow endRow 967s 2 NA NA 967s TCN and DH segmentation rows: 967s startRow endRow 967s 2 NA NA 967s startRow endRow 967s NA NA NA 967s startRow endRow 967s 1 1 7586 967s TCN segmentation (expanded) rows: 967s startRow endRow 967s 1 1 7586 967s 2 NA NA 967s TCN and DH segmentation rows: 967s startRow endRow 967s 1 1 7586 967s 2 NA NA 967s 3 7587 10267 967s 4 10268 14658 967s startRow endRow 967s 1 10 7574 967s 2 NA NA 967s startRow endRow 967s 1 1 7586 967s 2 NA NA 967s Total CN segmentation table (expanded): 967s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 967s 2 1 120908859 142693887 0 NA 0 0 967s (TCN,DH) segmentation for one total CN segment: 967s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 967s 2 2 1 1 120908859 142693887 0 NA 0 967s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 967s 2 0 NA NA NA NA 967s Total CN segment #2 ([1.20909e+08,1.42694e+08]) of 4...done 967s Total CN segment #3 ([1.42694e+08,1.8545e+08]) of 4... 967s Number of TCN loci in segment: 2681 967s Locus data for TCN segment: 967s 'data.frame': 2681 obs. of 9 variables: 967s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 967s $ x : num 1.43e+08 1.43e+08 1.43e+08 1.43e+08 1.44e+08 ... 967s $ CT : num 2.27 1.55 1.47 1.5 1.81 ... 967s $ betaT : num 0.34 0.55 0.048 0.813 0.575 ... 967s $ betaTN : num 0.441 0.629 -0.05 0.958 0.872 ... 967s $ betaN : num 0.3851 0.3933 0.0981 0.8552 0.7028 ... 967s $ muN : num 0.5 0.5 0 1 1 1 1 0.5 1 1 ... 967s $ index : int 7587 7588 7589 7590 7591 7592 7593 7594 7595 7596 ... 967s $ rho : num 0.117 0.258 NA NA NA ... 967s Number of loci: 2681 967s Number of SNPs: 777 (28.98%) 967s Number of heterozygous SNPs: 777 (100.00%) 967s Chromosome: 1 967s Segmenting DH signals... 967s Segmenting by CBS... 967s Chromosome: 1 967s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 967s Segmenting by CBS...done 967s List of 4 967s $ data :'data.frame': 2681 obs. of 4 variables: 967s ..$ chromosome: int [1:2681] 1 1 1 1 1 1 1 1 1 1 ... 967s ..$ x : num [1:2681] 1.43e+08 1.43e+08 1.43e+08 1.43e+08 1.44e+08 ... 967s ..$ y : num [1:2681] 0.117 0.258 NA NA NA ... 967s ..$ index : int [1:2681] 1 2 3 4 5 6 7 8 9 10 ... 967s $ output :'data.frame': 1 obs. of 6 variables: 967s ..$ sampleName: chr NA 967s ..$ chromosome: int 1 967s ..$ start : num 1.43e+08 967s ..$ end : num 1.85e+08 967s ..$ nbrOfLoci : int 777 967s ..$ mean : num 0.0973 967s $ segRows:'data.frame': 1 obs. of 2 variables: 967s ..$ startRow: int 1 967s ..$ endRow : int 2677 967s $ params :List of 5 967s ..$ alpha : num 0.001 967s ..$ undo : num 0 967s ..$ joinSegments : logi TRUE 967s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 967s .. ..$ chromosome: int 1 967s .. ..$ start : num 1.43e+08 967s .. ..$ end : num 1.85e+08 967s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 967s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 967s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.009 0 0.009 0 0 967s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 967s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 967s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 967s DH segmentation (locally-indexed) rows: 967s startRow endRow 967s 1 1 2677 967s int [1:2681] 7587 7588 7589 7590 7591 7592 7593 7594 7595 7596 ... 967s DH segmentation rows: 967s startRow endRow 967s 1 7587 10263 967s Segmenting DH signals...done 967s DH segmentation table: 967s dhStart dhEnd dhNbrOfLoci dhMean 967s 1 142693888 185449813 777 0.0973 967s startRow endRow 967s 1 7587 10263 967s Rows: 967s [1] 3 967s TCN segmentation rows: 967s startRow endRow 967s 3 7587 10267 967s TCN and DH segmentation rows: 967s startRow endRow 967s 3 7587 10267 967s startRow endRow 967s 1 7587 10263 967s startRow endRow 967s 1 1 7586 967s 2 NA NA 967s TCN segmentation (expanded) rows: 967s startRow endRow 967s 1 1 7586 967s 2 NA NA 967s 3 7587 10267 967s TCN and DH segmentation rows: 967s startRow endRow 967s 1 1 7586 967s 2 NA NA 967s 3 7587 10267 967s 4 10268 14658 967s startRow endRow 967s 1 10 7574 967s 2 NA NA 967s 3 7587 10263 967s startRow endRow 967s 1 1 7586 967s 2 NA NA 967s 3 7587 10267 967s Total CN segmentation table (expanded): 967s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 967s 3 1 142693888 185449813 2681 2.0689 777 777 967s (TCN,DH) segmentation for one total CN segment: 967s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 967s 3 3 1 1 142693888 185449813 2681 2.0689 777 967s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 967s 3 777 142693888 185449813 777 0.0973 967s Total CN segment #3 ([1.42694e+08,1.8545e+08]) of 4...done 967s Total CN segment #4 ([1.8545e+08,2.47137e+08]) of 4... 967s Number of TCN loci in segment: 4391 967s Locus data for TCN segment: 967s 'data.frame': 4391 obs. of 9 variables: 967s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 967s $ x : num 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 967s $ CT : num 2.93 2.15 2.82 2.93 2.46 ... 967s $ betaT : num 0.0811 0.5154 0.9473 0.3734 0.7506 ... 967s $ betaTN : num -0.169 0.609 1.028 0.525 0.968 ... 967s $ betaN : num 0.25 0.38 0.919 0.34 0.783 ... 967s $ muN : num 0 0.5 1 0.5 1 1 0 1 0 1 ... 967s $ index : int 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 967s $ rho : num NA 0.2186 NA 0.0503 NA ... 967s Number of loci: 4391 967s Number of SNPs: 1311 (29.86%) 967s Number of heterozygous SNPs: 1311 (100.00%) 967s Chromosome: 1 967s Segmenting DH signals... 967s Segmenting by CBS... 967s Chromosome: 1 967s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 967s Segmenting by CBS...done 967s List of 4 967s $ data :'data.frame': 4391 obs. of 4 variables: 967s ..$ chromosome: int [1:4391] 1 1 1 1 1 1 1 1 1 1 ... 967s ..$ x : num [1:4391] 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 967s ..$ y : num [1:4391] NA 0.2186 NA 0.0503 NA ... 967s ..$ index : int [1:4391] 1 2 3 4 5 6 7 8 9 10 ... 967s $ output :'data.frame': 1 obs. of 6 variables: 967s ..$ sampleName: chr NA 967s ..$ chromosome: int 1 967s ..$ start : num 1.85e+08 967s ..$ end : num 2.47e+08 967s ..$ nbrOfLoci : int 1311 967s ..$ mean : num 0.23 967s $ segRows:'data.frame': 1 obs. of 2 variables: 967s ..$ startRow: int 2 967s ..$ endRow : int 4388 967s $ params :List of 5 967s ..$ alpha : num 0.001 967s ..$ undo : num 0 967s ..$ joinSegments : logi TRUE 967s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 967s .. ..$ chromosome: int 1 967s .. ..$ start : num 1.85e+08 967s .. ..$ end : num 2.47e+08 967s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 967s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 967s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.018 0 0.018 0 0 967s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 967s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 967s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 967s DH segmentation (locally-indexed) rows: 967s startRow endRow 967s 1 2 4388 967s int [1:4391] 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 967s DH segmentation rows: 967s startRow endRow 967s 1 10269 14655 967s Segmenting DH signals...done 967s DH segmentation table: 967s dhStart dhEnd dhNbrOfLoci dhMean 967s 1 185449813 247137334 1311 0.2295 967s startRow endRow 967s 1 10269 14655 967s Rows: 967s [1] 4 967s TCN segmentation rows: 967s startRow endRow 967s 4 10268 14658 967s TCN and DH segmentation rows: 967s startRow endRow 967s 4 10268 14658 967s startRow endRow 967s 1 10269 14655 967s startRow endRow 967s 1 1 7586 967s 2 NA NA 967s 3 7587 10267 967s TCN segmentation (expanded) rows: 967s startRow endRow 967s 1 1 7586 967s 2 NA NA 967s 3 7587 10267 967s 4 10268 14658 967s TCN and DH segmentation rows: 967s startRow endRow 967s 1 1 7586 967s 2 NA NA 967s 3 7587 10267 967s 4 10268 14658 967s startRow endRow 967s 1 10 7574 967s 2 NA NA 967s 3 7587 10263 967s 4 10269 14655 967s startRow endRow 967s 1 1 7586 967s 2 NA NA 967s 3 7587 10267 967s 4 10268 14658 967s Total CN segmentation table (expanded): 967s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 967s 4 1 185449813 247137334 4391 2.6341 1311 1311 967s (TCN,DH) segmentation for one total CN segment: 967s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 967s 4 4 1 1 185449813 247137334 4391 2.6341 1311 967s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 967s 4 1311 185449813 247137334 1311 0.2295 967s Total CN segment #4 ([1.8545e+08,2.47137e+08]) of 4...done 967s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 967s 1 1 1 1 554484 120908858 7586 1.3853 2108 967s 2 1 2 1 120908859 142693887 0 NA 0 967s 3 1 3 1 142693888 185449813 2681 2.0689 777 967s 4 1 4 1 185449813 247137334 4391 2.6341 1311 967s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 967s 1 2108 554484 120908858 2108 0.5116 967s 2 0 NA NA NA NA 967s 3 777 142693888 185449813 777 0.0973 967s 4 1311 185449813 247137334 1311 0.2295 967s Calculating (C1,C2) per segment... 967s Calculating (C1,C2) per segment...done 967s Number of segments: 4 967s Segmenting paired tumor-normal signals using Paired PSCBS...done 967s Post-segmenting TCNs... 967s Number of segments: 4 967s Number of chromosomes: 1 967s [1] 1 967s Chromosome 1 ('chr01') of 1... 967s Rows: 967s [1] 1 2 3 4 967s Number of segments: 4 967s TCN segment #1 ('1') of 4... 967s Nothing todo. Only one DH segmentation. Skipping. 967s TCN segment #1 ('1') of 4...done 967s TCN segment #2 ('2') of 4... 967s Nothing todo. Only one DH segmentation. Skipping. 967s TCN segment #2 ('2') of 4...done 967s TCN segment #3 ('3') of 4... 967s Nothing todo. Only one DH segmentation. Skipping. 967s TCN segment #3 ('3') of 4...done 967s TCN segment #4 ('4') of 4... 967s Nothing todo. Only one DH segmentation. Skipping. 967s TCN segment #4 ('4') of 4...done 967s Chromosome 1 ('chr01') of 1...done 967s Update (C1,C2) per segment... 967s Update (C1,C2) per segment...done 967s Post-segmenting TCNs...done 967s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 967s 1 1 1 1 554484 120908858 7586 1.3853 2108 967s 2 1 2 1 120908859 142693887 0 NA 0 967s 3 1 3 1 142693888 185449813 2681 2.0689 777 967s 4 1 4 1 185449813 247137334 4391 2.6341 1311 967s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 967s 1 2108 554484 120908858 2108 0.5116 0.3382903 1.047010 967s 2 0 NA NA NA NA NA NA 967s 3 777 142693888 185449813 777 0.0973 0.9337980 1.135102 967s 4 1311 185449813 247137334 1311 0.2295 1.0147870 1.619313 967s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 967s 1 1 1 1 554484 120908858 7586 1.3853 2108 967s 2 1 2 1 120908859 142693887 0 NA 0 967s 3 1 3 1 142693888 185449813 2681 2.0689 777 967s 4 1 4 1 185449813 247137334 4391 2.6341 1311 967s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 967s 1 2108 554484 120908858 2108 0.5116 0.3382903 1.047010 967s 2 0 NA NA NA NA NA NA 967s 3 777 142693888 185449813 777 0.0973 0.9337980 1.135102 967s 4 1311 185449813 247137334 1311 0.2295 1.0147870 1.619313 967s - segmentByPairedPSCBS() w/ known segments using 'multisession' futures ... 968s Segmenting paired tumor-normal signals using Paired PSCBS... 968s Calling genotypes from normal allele B fractions... 968s num [1:14670] 0.8274 0.5072 0.1671 0.1609 0.0421 ... 968s Called genotypes: 968s num [1:14670] 1 0.5 0 0 0 0 1 0 1 0.5 ... 968s - attr(*, "modelFit")=List of 1 968s ..$ :List of 7 968s .. ..$ flavor : chr "density" 968s .. ..$ cn : int 2 968s .. ..$ nbrOfGenotypeGroups: int 3 968s .. ..$ tau : num [1:2] 0.315 0.677 968s .. ..$ n : int 14640 968s .. ..$ fit :Classes ‘PeaksAndValleys’ and 'data.frame': 5 obs. of 3 variables: 968s .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 968s .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 968s .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 968s .. ..$ fitValleys :Classes ‘PeaksAndValleys’ and 'data.frame': 2 obs. of 3 variables: 968s .. .. ..$ type : chr [1:2] "valley" "valley" 968s .. .. ..$ x : num [1:2] 0.315 0.677 968s .. .. ..$ density: num [1:2] 0.522 0.551 968s ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 968s muN 968s 0 0.5 1 968s 5221 4198 5251 968s Calling genotypes from normal allele B fractions...done 968s Normalizing betaT using betaN (TumorBoost)... 968s Normalized BAFs: 968s num [1:14670] 0.9301 0.1667 0.0685 0.0995 0.0155 ... 968s - attr(*, "modelFit")=List of 5 968s ..$ method : chr "normalizeTumorBoost" 968s ..$ flavor : chr "v4" 968s ..$ delta : num [1:14670] -0.17264 0.00239 0.1671 0.16085 0.04213 ... 968s .. ..- attr(*, "modelFit")=List of 1 968s .. .. ..$ :List of 7 968s .. .. .. ..$ flavor : chr "density" 968s .. .. .. ..$ cn : int 2 968s .. .. .. ..$ nbrOfGenotypeGroups: int 3 968s .. .. .. ..$ tau : num [1:2] 0.315 0.677 968s .. .. .. ..$ n : int 14640 968s .. .. .. ..$ fit :Classes ‘PeaksAndValleys’ and 'data.frame': 5 obs. of 3 variables: 968s .. .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 968s .. .. .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 968s .. .. .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 968s .. .. .. ..$ fitValleys :Classes ‘PeaksAndValleys’ and 'data.frame': 2 obs. of 3 variables: 968s .. .. .. .. ..$ type : chr [1:2] "valley" "valley" 968s .. .. .. .. ..$ x : num [1:2] 0.315 0.677 968s .. .. .. .. ..$ density: num [1:2] 0.522 0.551 968s .. .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 968s ..$ preserveScale: logi FALSE 968s ..$ scaleFactor : num NA 968s Normalizing betaT using betaN (TumorBoost)...done 968s Setup up data... 968s 'data.frame': 14670 obs. of 7 variables: 968s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 968s $ x : num 1145994 2941694 3710825 4240737 4276892 ... 968s $ CT : num 1.63 1.4 1.41 1.17 1.16 ... 968s $ betaT : num 0.7574 0.169 0.2357 0.2604 0.0576 ... 968s $ betaTN : num 0.9301 0.1667 0.0685 0.0995 0.0155 ... 968s ..- attr(*, "modelFit")=List of 5 968s .. ..$ method : chr "normalizeTumorBoost" 968s .. ..$ flavor : chr "v4" 968s .. ..$ delta : num [1:14670] -0.17264 0.00239 0.1671 0.16085 0.04213 ... 968s .. .. ..- attr(*, "modelFit")=List of 1 968s .. .. .. ..$ :List of 7 968s .. .. .. .. ..$ flavor : chr "density" 968s .. .. .. .. ..$ cn : int 2 968s .. .. .. .. ..$ nbrOfGenotypeGroups: int 3 968s .. .. .. .. ..$ tau : num [1:2] 0.315 0.677 968s .. .. .. .. ..$ n : int 14640 968s .. .. .. .. ..$ fit :Classes ‘PeaksAndValleys’ and 'data.frame': 5 obs. of 3 variables: 968s .. .. .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 968s .. .. .. .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 968s .. .. .. .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 968s .. .. .. .. ..$ fitValleys :Classes ‘PeaksAndValleys’ and 'data.frame': 2 obs. of 3 variables: 968s .. .. .. .. .. ..$ type : chr [1:2] "valley" "valley" 968s .. .. .. .. .. ..$ x : num [1:2] 0.315 0.677 968s .. .. .. .. .. ..$ density: num [1:2] 0.522 0.551 968s .. .. .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 968s .. ..$ preserveScale: logi FALSE 968s .. ..$ scaleFactor : num NA 968s $ betaN : num 0.8274 0.5072 0.1671 0.1609 0.0421 ... 968s $ muN : num 1 0.5 0 0 0 0 1 0 1 0.5 ... 968s ..- attr(*, "modelFit")=List of 1 968s .. ..$ :List of 7 968s .. .. ..$ flavor : chr "density" 968s .. .. ..$ cn : int 2 968s .. .. ..$ nbrOfGenotypeGroups: int 3 968s .. .. ..$ tau : num [1:2] 0.315 0.677 968s .. .. ..$ n : int 14640 968s .. .. ..$ fit :Classes ‘PeaksAndValleys’ and 'data.frame': 5 obs. of 3 variables: 968s .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 968s .. .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 968s .. .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 968s .. .. ..$ fitValleys :Classes ‘PeaksAndValleys’ and 'data.frame': 2 obs. of 3 variables: 968s .. .. .. ..$ type : chr [1:2] "valley" "valley" 968s .. .. .. ..$ x : num [1:2] 0.315 0.677 968s .. .. .. ..$ density: num [1:2] 0.522 0.551 968s .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 968s Setup up data...done 968s Dropping loci for which TCNs are missing... 968s Number of loci dropped: 12 968s Dropping loci for which TCNs are missing...done 968s Ordering data along genome... 968s 'data.frame': 14658 obs. of 7 variables: 968s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 968s $ x : num 554484 730720 782343 878522 916294 ... 968s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 968s $ betaT : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 968s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 968s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 968s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 968s Ordering data along genome...done 968s Keeping only current chromosome for 'knownSegments'... 968s Chromosome: 1 968s Known segments for this chromosome: 968s chromosome start end length 968s 1 1 -Inf 120908858 Inf 968s 2 1 120908859 142693887 21785028 968s 3 1 142693888 Inf Inf 968s Keeping only current chromosome for 'knownSegments'...done 968s alphaTCN: 0.009 968s alphaDH: 0.001 968s Number of loci: 14658 968s Calculating DHs... 968s Number of SNPs: 14658 968s Number of heterozygous SNPs: 4196 (28.63%) 968s Normalized DHs: 968s num [1:14658] NA NA NA NA NA ... 968s Calculating DHs...done 968s Random seed temporarily set (seed=c(48879), kind="L'Ecuyer-CMRG") 968s Produced 2 seeds from this stream for future usage 968s Identification of change points by total copy numbers... 968s Segmenting by CBS... 968s Chromosome: 1 968s Random seed temporarily set (seed=c(10407, 1066287653, -51199871, 161854402, -1995183193, 1503453565, -747102133), kind="L'Ecuyer-CMRG") 968s Produced 3 seeds from this stream for future usage 969s Segmenting by CBS...done 969s List of 4 969s $ data :'data.frame': 14658 obs. of 4 variables: 969s ..$ chromosome: int [1:14658] 1 1 1 1 1 1 1 1 1 1 ... 969s ..$ x : num [1:14658] 554484 730720 782343 878522 916294 ... 969s ..$ y : num [1:14658] 1.88 1.8 1.59 1.64 1.53 ... 969s ..$ index : int [1:14658] 1 2 3 4 5 6 7 8 9 10 ... 969s $ output :'data.frame': 4 obs. of 6 variables: 969s ..$ sampleName: chr [1:4] NA NA NA NA 969s ..$ chromosome: int [1:4] 1 1 1 1 969s ..$ start : num [1:4] 5.54e+05 1.21e+08 1.43e+08 1.85e+08 969s ..$ end : num [1:4] 1.21e+08 1.43e+08 1.85e+08 2.47e+08 969s ..$ nbrOfLoci : int [1:4] 7586 0 2681 4391 969s ..$ mean : num [1:4] 1.39 NA 2.07 2.63 969s $ segRows:'data.frame': 4 obs. of 2 variables: 969s ..$ startRow: int [1:4] 1 NA 7587 10268 969s ..$ endRow : int [1:4] 7586 NA 10267 14658 969s $ params :List of 5 969s ..$ alpha : num 0.009 969s ..$ undo : num 0 969s ..$ joinSegments : logi TRUE 969s ..$ knownSegments:'data.frame': 4 obs. of 3 variables: 969s .. ..$ chromosome: int [1:4] 1 1 2 1 969s .. ..$ start : num [1:4] -Inf -Inf -Inf 1.43e+08 969s .. ..$ end : num [1:4] 1.21e+08 Inf Inf Inf 969s ..$ seed : int [1:7] 10407 1066287653 -51199871 161854402 -1995183193 1503453565 -747102133 969s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 969s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.169 0 0.17 0 0 969s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 969s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 969s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 969s Identification of change points by total copy numbers...done 969s Restructure TCN segmentation results... 969s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean 969s 1 1 554484 120908858 7586 1.3853 969s 2 1 120908859 142693887 0 NA 969s 3 1 142693888 185449813 2681 2.0689 969s 4 1 185449813 247137334 4391 2.6341 969s Number of TCN segments: 4 969s Restructure TCN segmentation results...done 969s Total CN segment #1 ([ 554484,1.20909e+08]) of 4... 969s Number of TCN loci in segment: 7586 969s Locus data for TCN segment: 969s 'data.frame': 7586 obs. of 9 variables: 969s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 969s $ x : num 554484 730720 782343 878522 916294 ... 969s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 969s $ betaT : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 969s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 969s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 969s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 969s $ index : int 1 2 3 4 5 6 7 8 9 10 ... 969s $ rho : num NA NA NA NA NA ... 969s Number of loci: 7586 969s Number of SNPs: 2108 (27.79%) 969s Number of heterozygous SNPs: 2108 (100.00%) 969s Chromosome: 1 969s Segmenting DH signals... 969s Segmenting by CBS... 969s Chromosome: 1 969s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 969s Segmenting by CBS...done 969s List of 4 969s $ data :'data.frame': 7586 obs. of 4 variables: 969s ..$ chromosome: int [1:7586] 1 1 1 1 1 1 1 1 1 1 ... 969s ..$ x : num [1:7586] 554484 730720 782343 878522 916294 ... 969s ..$ y : num [1:7586] NA NA NA NA NA ... 969s ..$ index : int [1:7586] 1 2 3 4 5 6 7 8 9 10 ... 969s $ output :'data.frame': 1 obs. of 6 variables: 969s ..$ sampleName: chr NA 969s ..$ chromosome: int 1 969s ..$ start : num 554484 969s ..$ end : num 1.21e+08 969s ..$ nbrOfLoci : int 2108 969s ..$ mean : num 0.512 969s $ segRows:'data.frame': 1 obs. of 2 variables: 969s ..$ startRow: int 10 969s ..$ endRow : int 7574 969s $ params :List of 5 969s ..$ alpha : num 0.001 969s ..$ undo : num 0 969s ..$ joinSegments : logi TRUE 969s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 969s .. ..$ chromosome: int 1 969s .. ..$ start : num 554484 969s .. ..$ end : num 1.21e+08 969s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 969s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 969s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.046 0 0.046 0 0 969s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 969s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 969s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 969s DH segmentation (locally-indexed) rows: 969s startRow endRow 969s 1 10 7574 969s int [1:7586] 1 2 3 4 5 6 7 8 9 10 ... 969s DH segmentation rows: 969s startRow endRow 969s 1 10 7574 969s Segmenting DH signals...done 969s DH segmentation table: 969s dhStart dhEnd dhNbrOfLoci dhMean 969s 1 554484 120908858 2108 0.5116 969s startRow endRow 969s 1 10 7574 969s Rows: 969s [1] 1 969s TCN segmentation rows: 969s startRow endRow 969s 1 1 7586 969s TCN and DH segmentation rows: 969s startRow endRow 969s 1 1 7586 969s startRow endRow 969s 1 10 7574 969s NULL 969s TCN segmentation (expanded) rows: 969s startRow endRow 969s 1 1 7586 969s TCN and DH segmentation rows: 969s startRow endRow 969s 1 1 7586 969s 2 NA NA 969s 3 7587 10267 969s 4 10268 14658 969s startRow endRow 969s 1 10 7574 969s startRow endRow 969s 1 1 7586 969s Total CN segmentation table (expanded): 969s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 969s 1 1 554484 120908858 7586 1.3853 2108 2108 969s (TCN,DH) segmentation for one total CN segment: 969s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 969s 1 1 1 1 554484 120908858 7586 1.3853 2108 969s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 969s 1 2108 554484 120908858 2108 0.5116 969s Total CN segment #1 ([ 554484,1.20909e+08]) of 4...done 969s Total CN segment #2 ([1.20909e+08,1.42694e+08]) of 4... 969s Number of TCN loci in segment: 0 969s Locus data for TCN segment: 969s 'data.frame': 0 obs. of 9 variables: 969s $ chromosome: int 969s $ x : num 969s $ CT : num 969s $ betaT : num 969s $ betaTN : num 969s $ betaN : num 969s $ muN : num 969s $ index : int 969s $ rho : num 969s Number of loci: 0 969s Number of SNPs: 0 (NaN%) 969s Number of heterozygous SNPs: 0 (NaN%) 969s Chromosome: 1 969s Segmenting DH signals... 969s Segmenting by CBS... 969s Chromosome: NA 969s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 970s Segmenting by CBS...done 970s List of 4 970s $ data :'data.frame': 0 obs. of 4 variables: 970s ..$ chromosome: int(0) 970s ..$ x : num(0) 970s ..$ y : num(0) 970s ..$ index : int(0) 970s $ output :'data.frame': 0 obs. of 6 variables: 970s ..$ sampleName: chr(0) 970s ..$ chromosome: num(0) 970s ..$ start : num(0) 970s ..$ end : num(0) 970s ..$ nbrOfLoci : int(0) 970s ..$ mean : num(0) 970s $ segRows:'data.frame': 0 obs. of 2 variables: 970s ..$ startRow: int(0) 970s ..$ endRow : int(0) 970s $ params :List of 5 970s ..$ alpha : num 0.001 970s ..$ undo : num 0 970s ..$ joinSegments : logi TRUE 970s ..$ knownSegments:'data.frame': 0 obs. of 3 variables: 970s .. ..$ chromosome: int(0) 970s .. ..$ start : num(0) 970s .. ..$ end : num(0) 970s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 970s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 970s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.002 0 0.002 0 0 970s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 970s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 970s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 970s DH segmentation (locally-indexed) rows: 970s [1] startRow endRow 970s <0 rows> (or 0-length row.names) 970s int(0) 970s DH segmentation rows: 970s [1] startRow endRow 970s <0 rows> (or 0-length row.names) 970s Segmenting DH signals...done 970s DH segmentation table: 970s dhStart dhEnd dhNbrOfLoci dhMean 970s NA NA NA NA NA 970s startRow endRow 970s NA NA NA 970s Rows: 970s [1] 2 970s TCN segmentation rows: 970s startRow endRow 970s 2 NA NA 970s TCN and DH segmentation rows: 970s startRow endRow 970s 2 NA NA 970s startRow endRow 970s NA NA NA 970s startRow endRow 970s 1 1 7586 970s TCN segmentation (expanded) rows: 970s startRow endRow 970s 1 1 7586 970s 2 NA NA 970s TCN and DH segmentation rows: 970s startRow endRow 970s 1 1 7586 970s 2 NA NA 970s 3 7587 10267 970s 4 10268 14658 970s startRow endRow 970s 1 10 7574 970s 2 NA NA 970s startRow endRow 970s 1 1 7586 970s 2 NA NA 970s Total CN segmentation table (expanded): 970s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 970s 2 1 120908859 142693887 0 NA 0 0 970s (TCN,DH) segmentation for one total CN segment: 970s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 970s 2 2 1 1 120908859 142693887 0 NA 0 970s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 970s 2 0 NA NA NA NA 970s Total CN segment #2 ([1.20909e+08,1.42694e+08]) of 4...done 970s Total CN segment #3 ([1.42694e+08,1.8545e+08]) of 4... 970s Number of TCN loci in segment: 2681 970s Locus data for TCN segment: 970s 'data.frame': 2681 obs. of 9 variables: 970s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 970s $ x : num 1.43e+08 1.43e+08 1.43e+08 1.43e+08 1.44e+08 ... 970s $ CT : num 2.27 1.55 1.47 1.5 1.81 ... 970s $ betaT : num 0.34 0.55 0.048 0.813 0.575 ... 970s $ betaTN : num 0.441 0.629 -0.05 0.958 0.872 ... 970s $ betaN : num 0.3851 0.3933 0.0981 0.8552 0.7028 ... 970s $ muN : num 0.5 0.5 0 1 1 1 1 0.5 1 1 ... 970s $ index : int 7587 7588 7589 7590 7591 7592 7593 7594 7595 7596 ... 970s $ rho : num 0.117 0.258 NA NA NA ... 970s Number of loci: 2681 970s Number of SNPs: 777 (28.98%) 970s Number of heterozygous SNPs: 777 (100.00%) 970s Chromosome: 1 970s Segmenting DH signals... 970s Segmenting by CBS... 970s Chromosome: 1 970s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 970s Segmenting by CBS...done 970s List of 4 970s $ data :'data.frame': 2681 obs. of 4 variables: 970s ..$ chromosome: int [1:2681] 1 1 1 1 1 1 1 1 1 1 ... 970s ..$ x : num [1:2681] 1.43e+08 1.43e+08 1.43e+08 1.43e+08 1.44e+08 ... 970s ..$ y : num [1:2681] 0.117 0.258 NA NA NA ... 970s ..$ index : int [1:2681] 1 2 3 4 5 6 7 8 9 10 ... 970s $ output :'data.frame': 1 obs. of 6 variables: 970s ..$ sampleName: chr NA 970s ..$ chromosome: int 1 970s ..$ start : num 1.43e+08 970s ..$ end : num 1.85e+08 970s ..$ nbrOfLoci : int 777 970s ..$ mean : num 0.0973 970s $ segRows:'data.frame': 1 obs. of 2 variables: 970s ..$ startRow: int 1 970s ..$ endRow : int 2677 970s $ params :List of 5 970s ..$ alpha : num 0.001 970s ..$ undo : num 0 970s ..$ joinSegments : logi TRUE 970s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 970s .. ..$ chromosome: int 1 970s .. ..$ start : num 1.43e+08 970s .. ..$ end : num 1.85e+08 970s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 970s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 970s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.009 0 0.01 0 0 970s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 970s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 970s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 970s DH segmentation (locally-indexed) rows: 970s startRow endRow 970s 1 1 2677 970s int [1:2681] 7587 7588 7589 7590 7591 7592 7593 7594 7595 7596 ... 970s DH segmentation rows: 970s startRow endRow 970s 1 7587 10263 970s Segmenting DH signals...done 970s DH segmentation table: 970s dhStart dhEnd dhNbrOfLoci dhMean 970s 1 142693888 185449813 777 0.0973 970s startRow endRow 970s 1 7587 10263 970s Rows: 970s [1] 3 970s TCN segmentation rows: 970s startRow endRow 970s 3 7587 10267 970s TCN and DH segmentation rows: 970s startRow endRow 970s 3 7587 10267 970s startRow endRow 970s 1 7587 10263 970s startRow endRow 970s 1 1 7586 970s 2 NA NA 970s TCN segmentation (expanded) rows: 970s startRow endRow 970s 1 1 7586 970s 2 NA NA 970s 3 7587 10267 970s TCN and DH segmentation rows: 970s startRow endRow 970s 1 1 7586 970s 2 NA NA 970s 3 7587 10267 970s 4 10268 14658 970s startRow endRow 970s 1 10 7574 970s 2 NA NA 970s 3 7587 10263 970s startRow endRow 970s 1 1 7586 970s 2 NA NA 970s 3 7587 10267 970s Total CN segmentation table (expanded): 970s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 970s 3 1 142693888 185449813 2681 2.0689 777 777 970s (TCN,DH) segmentation for one total CN segment: 970s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 970s 3 3 1 1 142693888 185449813 2681 2.0689 777 970s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 970s 3 777 142693888 185449813 777 0.0973 970s Total CN segment #3 ([1.42694e+08,1.8545e+08]) of 4...done 970s Total CN segment #4 ([1.8545e+08,2.47137e+08]) of 4... 970s Number of TCN loci in segment: 4391 970s Locus data for TCN segment: 970s 'data.frame': 4391 obs. of 9 variables: 970s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 970s $ x : num 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 970s $ CT : num 2.93 2.15 2.82 2.93 2.46 ... 970s $ betaT : num 0.0811 0.5154 0.9473 0.3734 0.7506 ... 970s $ betaTN : num -0.169 0.609 1.028 0.525 0.968 ... 970s $ betaN : num 0.25 0.38 0.919 0.34 0.783 ... 970s $ muN : num 0 0.5 1 0.5 1 1 0 1 0 1 ... 970s $ index : int 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 970s $ rho : num NA 0.2186 NA 0.0503 NA ... 970s Number of loci: 4391 970s Number of SNPs: 1311 (29.86%) 970s Number of heterozygous SNPs: 1311 (100.00%) 970s Chromosome: 1 970s Segmenting DH signals... 970s Segmenting by CBS... 970s Chromosome: 1 970s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 970s Segmenting by CBS...done 970s List of 4 970s $ data :'data.frame': 4391 obs. of 4 variables: 970s ..$ chromosome: int [1:4391] 1 1 1 1 1 1 1 1 1 1 ... 970s ..$ x : num [1:4391] 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 970s ..$ y : num [1:4391] NA 0.2186 NA 0.0503 NA ... 970s ..$ index : int [1:4391] 1 2 3 4 5 6 7 8 9 10 ... 970s $ output :'data.frame': 1 obs. of 6 variables: 970s ..$ sampleName: chr NA 970s ..$ chromosome: int 1 970s ..$ start : num 1.85e+08 970s ..$ end : num 2.47e+08 970s ..$ nbrOfLoci : int 1311 970s ..$ mean : num 0.23 970s $ segRows:'data.frame': 1 obs. of 2 variables: 970s ..$ startRow: int 2 970s ..$ endRow : int 4388 970s $ params :List of 5 970s ..$ alpha : num 0.001 970s ..$ undo : num 0 970s ..$ joinSegments : logi TRUE 970s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 970s .. ..$ chromosome: int 1 970s .. ..$ start : num 1.85e+08 970s .. ..$ end : num 2.47e+08 970s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 970s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 970s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.018 0 0.018 0 0 970s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 970s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 970s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 970s DH segmentation (locally-indexed) rows: 970s startRow endRow 970s 1 2 4388 970s int [1:4391] 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 970s DH segmentation rows: 970s startRow endRow 970s 1 10269 14655 970s Segmenting DH signals...done 970s DH segmentation table: 970s dhStart dhEnd dhNbrOfLoci dhMean 970s 1 185449813 247137334 1311 0.2295 970s startRow endRow 970s 1 10269 14655 970s Rows: 970s [1] 4 970s TCN segmentation rows: 970s startRow endRow 970s 4 10268 14658 970s TCN and DH segmentation rows: 970s startRow endRow 970s 4 10268 14658 970s startRow endRow 970s 1 10269 14655 970s startRow endRow 970s 1 1 7586 970s 2 NA NA 970s 3 7587 10267 970s TCN segmentation (expanded) rows: 970s startRow endRow 970s 1 1 7586 970s 2 NA NA 970s 3 7587 10267 970s 4 10268 14658 970s TCN and DH segmentation rows: 970s startRow endRow 970s 1 1 7586 970s 2 NA NA 970s 3 7587 10267 970s 4 10268 14658 970s startRow endRow 970s 1 10 7574 970s 2 NA NA 970s 3 7587 10263 970s 4 10269 14655 970s startRow endRow 970s 1 1 7586 970s 2 NA NA 970s 3 7587 10267 970s 4 10268 14658 970s Total CN segmentation table (expanded): 970s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 970s 4 1 185449813 247137334 4391 2.6341 1311 1311 970s (TCN,DH) segmentation for one total CN segment: 970s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 970s 4 4 1 1 185449813 247137334 4391 2.6341 1311 970s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 970s 4 1311 185449813 247137334 1311 0.2295 970s Total CN segment #4 ([1.8545e+08,2.47137e+08]) of 4...done 970s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 970s 1 1 1 1 554484 120908858 7586 1.3853 2108 970s 2 1 2 1 120908859 142693887 0 NA 0 970s 3 1 3 1 142693888 185449813 2681 2.0689 777 970s 4 1 4 1 185449813 247137334 4391 2.6341 1311 970s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 970s 1 2108 554484 120908858 2108 0.5116 970s 2 0 NA NA NA NA 970s 3 777 142693888 185449813 777 0.0973 970s 4 1311 185449813 247137334 1311 0.2295 970s Calculating (C1,C2) per segment... 970s Calculating (C1,C2) per segment...done 970s Number of segments: 4 970s Segmenting paired tumor-normal signals using Paired PSCBS...done 970s Post-segmenting TCNs... 970s Number of segments: 4 970s Number of chromosomes: 1 970s [1] 1 970s Chromosome 1 ('chr01') of 1... 970s Rows: 970s [1] 1 2 3 4 970s Number of segments: 4 970s TCN segment #1 ('1') of 4... 970s Nothing todo. Only one DH segmentation. Skipping. 970s TCN segment #1 ('1') of 4...done 970s TCN segment #2 ('2') of 4... 970s Nothing todo. Only one DH segmentation. Skipping. 970s TCN segment #2 ('2') of 4...done 970s TCN segment #3 ('3') of 4... 970s Nothing todo. Only one DH segmentation. Skipping. 970s TCN segment #3 ('3') of 4...done 970s TCN segment #4 ('4') of 4... 970s Nothing todo. Only one DH segmentation. Skipping. 970s TCN segment #4 ('4') of 4...done 970s Chromosome 1 ('chr01') of 1...done 970s Update (C1,C2) per segment... 970s Update (C1,C2) per segment...done 970s Post-segmenting TCNs...done 970s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 970s 1 1 1 1 554484 120908858 7586 1.3853 2108 970s 2 1 2 1 120908859 142693887 0 NA 0 970s 3 1 3 1 142693888 185449813 2681 2.0689 777 970s 4 1 4 1 185449813 247137334 4391 2.6341 1311 970s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 970s 1 2108 554484 120908858 2108 0.5116 0.3382903 1.047010 970s 2 0 NA NA NA NA NA NA 970s 3 777 142693888 185449813 777 0.0973 0.9337980 1.135102 970s 4 1311 185449813 247137334 1311 0.2295 1.0147870 1.619313 970s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 970s 1 1 1 1 554484 120908858 7586 1.3853 2108 970s 2 1 2 1 120908859 142693887 0 NA 0 970s 3 1 3 1 142693888 185449813 2681 2.0689 777 970s 4 1 4 1 185449813 247137334 4391 2.6341 1311 970s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 970s 1 2108 554484 120908858 2108 0.5116 0.3382903 1.047010 970s 2 0 NA NA NA NA NA NA 970s 3 777 142693888 185449813 777 0.0973 0.9337980 1.135102 970s 4 1311 185449813 247137334 1311 0.2295 1.0147870 1.619313 970s > 970s > message("*** segmentByPairedPSCBS() via futures ... DONE") 970s > 970s > 970s > ## Cleanup 970s > plan(oplan) 970s *** segmentByPairedPSCBS() via futures ... DONE 970s > rm(list=c("fits", "data", "fit")) 970s > 970s Start: segmentByPairedPSCBS,noNormalBAFs.R 970s 970s R version 4.5.2 (2025-10-31) -- "[Not] Part in a Rumble" 970s Copyright (C) 2025 The R Foundation for Statistical Computing 970s Platform: powerpc64le-unknown-linux-gnu 970s 970s R is free software and comes with ABSOLUTELY NO WARRANTY. 970s You are welcome to redistribute it under certain conditions. 970s Type 'license()' or 'licence()' for distribution details. 970s 970s R is a collaborative project with many contributors. 970s Type 'contributors()' for more information and 970s 'citation()' on how to cite R or R packages in publications. 970s 970s Type 'demo()' for some demos, 'help()' for on-line help, or 970s 'help.start()' for an HTML browser interface to help. 970s Type 'q()' to quit R. 970s 970s > library("PSCBS") 970s > 970s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 970s PSCBS v0.68.0 (2025-04-18 19:40:02 UTC) successfully loaded. See ?PSCBS for help. 970s > # Load SNP microarray data 970s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 970s > data <- PSCBS::exampleData("paired.chr01") 970s > str(data) 970s 'data.frame': 73346 obs. of 6 variables: 970s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 970s $ x : int 1145994 2224111 2319424 2543484 2926730 2941694 3084986 3155127 3292731 3695086 ... 970s $ CT : num 1.625 1.071 1.406 1.18 0.856 ... 970s $ betaT : num 0.757 0.771 0.834 0.778 0.229 ... 970s $ CN : num 2.36 2.13 2.59 1.93 1.71 ... 970s $ betaN : num 0.827 0.875 0.887 0.884 0.103 ... 970s > 970s > # Drop single-locus outliers 970s > dataS <- dropSegmentationOutliers(data) 970s > 970s > # Run light-weight tests by default 970s > if (Sys.getenv("_R_CHECK_FULL_") == "") { 970s + # Use only every 5th data point 970s + dataS <- dataS[seq(from=1, to=nrow(data), by=5),] 970s + # Number of segments (for assertion) 970s + nSegs <- 3L 970s + # Number of bootstrap samples (see below) 970s + B <- 100L 970s + } else { 970s + # Full tests 970s + nSegs <- 8L 970s + B <- 1000L 970s + } 970s > 970s > str(dataS) 970s 'data.frame': 14670 obs. of 6 variables: 970s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 970s $ x : int 1145994 2941694 3710825 4240737 4276892 4464544 4714611 5095111 5034491 5158416 ... 970s $ CT : num 1.63 1.4 1.41 1.17 1.16 ... 970s $ betaT : num 0.7574 0.169 0.2357 0.2604 0.0576 ... 970s $ CN : num 2.36 2.13 2.26 2.01 2.32 ... 970s $ betaN : num 0.8274 0.5072 0.1671 0.1609 0.0421 ... 970s > 970s > R.oo::attachLocally(dataS) 970s > 970s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 970s > # Simulate that genotypes are known by other means 970s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 970s > library("aroma.light") 970s aroma.light v3.36.0 (2024-10-29) successfully loaded. See ?aroma.light for help. 970s > muN <- aroma.light::callNaiveGenotypes(betaN, censorAt=c(0,1)) 970s > 970s > 970s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 970s > # Paired PSCBS segmentation 970s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 970s > fit <- segmentByPairedPSCBS(CT, betaT=betaT, muN=muN, tbn=FALSE, 970s + chromosome=chromosome, x=x, 970s + seed=0xBEEF, verbose=-10) 970s Segmenting paired tumor-normal signals using Paired PSCBS... 970s Setup up data... 970s 'data.frame': 14670 obs. of 6 variables: 970s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 970s $ x : num 1145994 2941694 3710825 4240737 4276892 ... 970s $ CT : num 1.63 1.4 1.41 1.17 1.16 ... 970s $ betaT : num 0.7574 0.169 0.2357 0.2604 0.0576 ... 970s $ betaTN : num 0.7574 0.169 0.2357 0.2604 0.0576 ... 970s $ muN : num 1 0.5 0 0 0 0 1 0 1 0.5 ... 970s ..- attr(*, "modelFit")=List of 1 970s .. ..$ :List of 7 970s .. .. ..$ flavor : chr "density" 970s .. .. ..$ cn : int 2 970s .. .. ..$ nbrOfGenotypeGroups: int 3 970s .. .. ..$ tau : num [1:2] 0.315 0.677 970s .. .. ..$ n : int 14640 970s .. .. ..$ fit :Classes ‘PeaksAndValleys’ and 'data.frame': 5 obs. of 3 variables: 970s .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 970s .. .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 970s .. .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 970s .. .. ..$ fitValleys :Classes ‘PeaksAndValleys’ and 'data.frame': 2 obs. of 3 variables: 970s .. .. .. ..$ type : chr [1:2] "valley" "valley" 970s .. .. .. ..$ x : num [1:2] 0.315 0.677 970s .. .. .. ..$ density: num [1:2] 0.522 0.551 970s .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 970s Setup up data...done 970s Dropping loci for which TCNs are missing... 970s Number of loci dropped: 12 970s Dropping loci for which TCNs are missing...done 970s Ordering data along genome... 970s 'data.frame': 14658 obs. of 6 variables: 970s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 970s $ x : num 554484 730720 782343 878522 916294 ... 970s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 970s $ betaT : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 970s $ betaTN : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 970s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 970s Ordering data along genome...done 970s Keeping only current chromosome for 'knownSegments'... 970s Chromosome: 1 970s Known segments for this chromosome: 970s [1] chromosome start end 970s <0 rows> (or 0-length row.names) 970s Keeping only current chromosome for 'knownSegments'...done 970s alphaTCN: 0.009 970s alphaDH: 0.001 970s Number of loci: 14658 970s Calculating DHs... 970s Number of SNPs: 14658 970s Number of heterozygous SNPs: 4196 (28.63%) 970s Normalized DHs: 970s num [1:14658] NA NA NA NA NA ... 970s Calculating DHs...done 970s Random seed temporarily set (seed=c(48879), kind="L'Ecuyer-CMRG") 970s Produced 2 seeds from this stream for future usage 970s Identification of change points by total copy numbers... 970s Segmenting by CBS... 970s Chromosome: 1 970s Random seed temporarily set (seed=c(10407, 1066287653, -51199871, 161854402, -1995183193, 1503453565, -747102133), kind="L'Ecuyer-CMRG") 971s Segmenting by CBS...done 971s List of 4 971s $ data :'data.frame': 14658 obs. of 4 variables: 971s ..$ chromosome: int [1:14658] 1 1 1 1 1 1 1 1 1 1 ... 971s ..$ x : num [1:14658] 554484 730720 782343 878522 916294 ... 971s ..$ y : num [1:14658] 1.88 1.8 1.59 1.64 1.53 ... 971s ..$ index : int [1:14658] 1 2 3 4 5 6 7 8 9 10 ... 971s $ output :'data.frame': 3 obs. of 6 variables: 971s ..$ sampleName: chr [1:3] NA NA NA 971s ..$ chromosome: int [1:3] 1 1 1 971s ..$ start : num [1:3] 5.54e+05 1.44e+08 1.85e+08 971s ..$ end : num [1:3] 1.44e+08 1.85e+08 2.47e+08 971s ..$ nbrOfLoci : int [1:3] 7599 2668 4391 971s ..$ mean : num [1:3] 1.39 2.07 2.63 971s $ segRows:'data.frame': 3 obs. of 2 variables: 971s ..$ startRow: int [1:3] 1 7600 10268 971s ..$ endRow : int [1:3] 7599 10267 14658 971s $ params :List of 5 971s ..$ alpha : num 0.009 971s ..$ undo : num 0 971s ..$ joinSegments : logi TRUE 971s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 971s .. ..$ chromosome: int 1 971s .. ..$ start : num -Inf 971s .. ..$ end : num Inf 971s ..$ seed : int [1:7] 10407 1066287653 -51199871 161854402 -1995183193 1503453565 -747102133 971s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 971s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.482 0 0.482 0 0 971s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 971s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 971s - attr(*, "randomSeed")= int [1:7] 10407 1066287653 -51199871 161854402 -1995183193 1503453565 -747102133 971s Identification of change points by total copy numbers...done 971s Restructure TCN segmentation results... 971s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean 971s 1 1 554484 143926517 7599 1.3859 971s 2 1 143926517 185449813 2668 2.0704 971s 3 1 185449813 247137334 4391 2.6341 971s Number of TCN segments: 3 971s Restructure TCN segmentation results...done 971s Total CN segment #1 ([ 554484,1.43927e+08]) of 3... 971s Number of TCN loci in segment: 7599 971s Locus data for TCN segment: 971s 'data.frame': 7599 obs. of 8 variables: 971s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 971s $ x : num 554484 730720 782343 878522 916294 ... 971s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 971s $ betaT : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 971s $ betaTN : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 971s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 971s $ index : int 1 2 3 4 5 6 7 8 9 10 ... 971s $ rho : num NA NA NA NA NA ... 971s Number of loci: 7599 971s Number of SNPs: 2111 (27.78%) 971s Number of heterozygous SNPs: 2111 (100.00%) 971s Chromosome: 1 971s Segmenting DH signals... 971s Segmenting by CBS... 971s Chromosome: 1 971s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 971s Segmenting by CBS...done 971s List of 4 971s $ data :'data.frame': 7599 obs. of 4 variables: 971s ..$ chromosome: int [1:7599] 1 1 1 1 1 1 1 1 1 1 ... 971s ..$ x : num [1:7599] 554484 730720 782343 878522 916294 ... 971s ..$ y : num [1:7599] NA NA NA NA NA ... 971s ..$ index : int [1:7599] 1 2 3 4 5 6 7 8 9 10 ... 971s $ output :'data.frame': 1 obs. of 6 variables: 971s ..$ sampleName: chr NA 971s ..$ chromosome: int 1 971s ..$ start : num 554484 971s ..$ end : num 1.44e+08 971s ..$ nbrOfLoci : int 2111 971s ..$ mean : num 0.524 971s $ segRows:'data.frame': 1 obs. of 2 variables: 971s ..$ startRow: int 10 971s ..$ endRow : int 7594 971s $ params :List of 5 971s ..$ alpha : num 0.001 971s ..$ undo : num 0 971s ..$ joinSegments : logi TRUE 971s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 971s .. ..$ chromosome: int 1 971s .. ..$ start : num 554484 971s .. ..$ end : num 1.44e+08 971s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 971s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 971s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.03 0 0.03 0 0 971s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 971s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 971s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 971s DH segmentation (locally-indexed) rows: 971s startRow endRow 971s 1 10 7594 971s int [1:7599] 1 2 3 4 5 6 7 8 9 10 ... 971s DH segmentation rows: 971s startRow endRow 971s 1 10 7594 971s Segmenting DH signals...done 971s DH segmentation table: 971s dhStart dhEnd dhNbrOfLoci dhMean 971s 1 554484 143926517 2111 0.5237 971s startRow endRow 971s 1 10 7594 971s Rows: 971s [1] 1 971s TCN segmentation rows: 971s startRow endRow 971s 1 1 7599 971s TCN and DH segmentation rows: 971s startRow endRow 971s 1 1 7599 971s startRow endRow 971s 1 10 7594 971s NULL 971s TCN segmentation (expanded) rows: 971s startRow endRow 971s 1 1 7599 971s TCN and DH segmentation rows: 971s startRow endRow 971s 1 1 7599 971s 2 7600 10267 971s 3 10268 14658 971s startRow endRow 971s 1 10 7594 971s startRow endRow 971s 1 1 7599 971s Total CN segmentation table (expanded): 971s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 971s 1 1 554484 143926517 7599 1.3859 2111 2111 971s (TCN,DH) segmentation for one total CN segment: 971s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 971s 1 1 1 1 554484 143926517 7599 1.3859 2111 971s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 971s 1 2111 554484 143926517 2111 0.5237 971s Total CN segment #1 ([ 554484,1.43927e+08]) of 3...done 971s Total CN segment #2 ([1.43927e+08,1.8545e+08]) of 3... 971s Number of TCN loci in segment: 2668 971s Locus data for TCN segment: 971s 'data.frame': 2668 obs. of 8 variables: 971s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 971s $ x : num 1.44e+08 1.44e+08 1.44e+08 1.44e+08 1.44e+08 ... 971s $ CT : num 2.1 2.1 2.09 1.8 2.34 ... 971s $ betaT : num 0.1899 0.909 0.9166 0.1668 0.0308 ... 971s $ betaTN : num 0.1899 0.909 0.9166 0.1668 0.0308 ... 971s $ muN : num 0 1 1 0 0 1 0 0 0 0 ... 971s $ index : int 7600 7601 7602 7603 7604 7605 7606 7607 7608 7609 ... 971s $ rho : num NA NA NA NA NA NA NA NA NA NA ... 971s Number of loci: 2668 971s Number of SNPs: 774 (29.01%) 971s Number of heterozygous SNPs: 774 (100.00%) 971s Chromosome: 1 971s Segmenting DH signals... 971s Segmenting by CBS... 971s Chromosome: 1 971s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 971s Segmenting by CBS...done 971s List of 4 971s $ data :'data.frame': 2668 obs. of 4 variables: 971s ..$ chromosome: int [1:2668] 1 1 1 1 1 1 1 1 1 1 ... 971s ..$ x : num [1:2668] 1.44e+08 1.44e+08 1.44e+08 1.44e+08 1.44e+08 ... 971s ..$ y : num [1:2668] NA NA NA NA NA NA NA NA NA NA ... 971s ..$ index : int [1:2668] 1 2 3 4 5 6 7 8 9 10 ... 971s $ output :'data.frame': 1 obs. of 6 variables: 971s ..$ sampleName: chr NA 971s ..$ chromosome: int 1 971s ..$ start : num 1.44e+08 971s ..$ end : num 1.85e+08 971s ..$ nbrOfLoci : int 774 971s ..$ mean : num 0.154 971s $ segRows:'data.frame': 1 obs. of 2 variables: 971s ..$ startRow: int 15 971s ..$ endRow : int 2664 971s $ params :List of 5 971s ..$ alpha : num 0.001 971s ..$ undo : num 0 971s ..$ joinSegments : logi TRUE 971s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 971s .. ..$ chromosome: int 1 971s .. ..$ start : num 1.44e+08 971s .. ..$ end : num 1.85e+08 971s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 971s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 971s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.011 0 0.01 0 0 971s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 971s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 971s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 971s DH segmentation (locally-indexed) rows: 971s startRow endRow 971s 1 15 2664 971s int [1:2668] 7600 7601 7602 7603 7604 7605 7606 7607 7608 7609 ... 971s DH segmentation rows: 971s startRow endRow 971s 1 7614 10263 971s Segmenting DH signals...done 971s DH segmentation table: 971s dhStart dhEnd dhNbrOfLoci dhMean 971s 1 143926517 185449813 774 0.1542 971s startRow endRow 971s 1 7614 10263 971s Rows: 971s [1] 2 971s TCN segmentation rows: 971s startRow endRow 971s 2 7600 10267 971s TCN and DH segmentation rows: 971s startRow endRow 971s 2 7600 10267 971s startRow endRow 971s 1 7614 10263 971s startRow endRow 971s 1 1 7599 971s TCN segmentation (expanded) rows: 971s startRow endRow 971s 1 1 7599 971s 2 7600 10267 971s TCN and DH segmentation rows: 971s startRow endRow 971s 1 1 7599 971s 2 7600 10267 971s 3 10268 14658 971s startRow endRow 971s 1 10 7594 971s 2 7614 10263 971s startRow endRow 971s 1 1 7599 971s 2 7600 10267 971s Total CN segmentation table (expanded): 971s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 971s 2 1 143926517 185449813 2668 2.0704 774 774 971s (TCN,DH) segmentation for one total CN segment: 971s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 971s 2 2 1 1 143926517 185449813 2668 2.0704 774 971s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 971s 2 774 143926517 185449813 774 0.1542 971s Total CN segment #2 ([1.43927e+08,1.8545e+08]) of 3...done 971s Total CN segment #3 ([1.8545e+08,2.47137e+08]) of 3... 971s Number of TCN loci in segment: 4391 971s Locus data for TCN segment: 971s 'data.frame': 4391 obs. of 8 variables: 971s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 971s $ x : num 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 971s $ CT : num 2.93 2.15 2.82 2.93 2.46 ... 971s $ betaT : num 0.0811 0.5154 0.9473 0.3734 0.7506 ... 971s $ betaTN : num 0.0811 0.5154 0.9473 0.3734 0.7506 ... 971s $ muN : num 0 0.5 1 0.5 1 1 0 1 0 1 ... 971s $ index : int 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 971s $ rho : num NA 0.0308 NA 0.2533 NA ... 971s Number of loci: 4391 971s Number of SNPs: 1311 (29.86%) 971s Number of heterozygous SNPs: 1311 (100.00%) 971s Chromosome: 1 971s Segmenting DH signals... 971s Segmenting by CBS... 971s Chromosome: 1 971s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 971s Segmenting by CBS...done 971s List of 4 971s $ data :'data.frame': 4391 obs. of 4 variables: 971s ..$ chromosome: int [1:4391] 1 1 1 1 1 1 1 1 1 1 ... 971s ..$ x : num [1:4391] 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 971s ..$ y : num [1:4391] NA 0.0308 NA 0.2533 NA ... 971s ..$ index : int [1:4391] 1 2 3 4 5 6 7 8 9 10 ... 971s $ output :'data.frame': 1 obs. of 6 variables: 971s ..$ sampleName: chr NA 971s ..$ chromosome: int 1 971s ..$ start : num 1.85e+08 971s ..$ end : num 2.47e+08 971s ..$ nbrOfLoci : int 1311 971s ..$ mean : num 0.251 971s $ segRows:'data.frame': 1 obs. of 2 variables: 971s ..$ startRow: int 2 971s ..$ endRow : int 4388 971s $ params :List of 5 971s ..$ alpha : num 0.001 971s ..$ undo : num 0 971s ..$ joinSegments : logi TRUE 971s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 971s .. ..$ chromosome: int 1 971s .. ..$ start : num 1.85e+08 971s .. ..$ end : num 2.47e+08 971s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 971s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 971s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.024 0 0.024 0 0 971s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 971s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 971s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 971s DH segmentation (locally-indexed) rows: 971s startRow endRow 971s 1 2 4388 971s int [1:4391] 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 971s DH segmentation rows: 971s startRow endRow 971s 1 10269 14655 971s Segmenting DH signals...done 971s DH segmentation table: 971s dhStart dhEnd dhNbrOfLoci dhMean 971s 1 185449813 247137334 1311 0.2512 971s startRow endRow 971s 1 10269 14655 971s Rows: 971s [1] 3 971s TCN segmentation rows: 971s startRow endRow 971s 3 10268 14658 971s TCN and DH segmentation rows: 971s startRow endRow 971s 3 10268 14658 971s startRow endRow 971s 1 10269 14655 971s startRow endRow 971s 1 1 7599 971s 2 7600 10267 971s TCN segmentation (expanded) rows: 971s startRow endRow 971s 1 1 7599 971s 2 7600 10267 971s 3 10268 14658 971s TCN and DH segmentation rows: 971s startRow endRow 971s 1 1 7599 971s 2 7600 10267 971s 3 10268 14658 971s startRow endRow 971s 1 10 7594 971s 2 7614 10263 971s 3 10269 14655 971s startRow endRow 971s 1 1 7599 971s 2 7600 10267 971s 3 10268 14658 971s Total CN segmentation table (expanded): 971s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 971s 3 1 185449813 247137334 4391 2.6341 1311 1311 971s (TCN,DH) segmentation for one total CN segment: 971s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 971s 3 3 1 1 185449813 247137334 4391 2.6341 1311 971s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 971s 3 1311 185449813 247137334 1311 0.2512 971s Total CN segment #3 ([1.8545e+08,2.47137e+08]) of 3...done 971s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 971s 1 1 1 1 554484 143926517 7599 1.3859 2111 971s 2 1 2 1 143926517 185449813 2668 2.0704 774 971s 3 1 3 1 185449813 247137334 4391 2.6341 1311 971s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 971s 1 2111 554484 143926517 2111 0.5237 971s 2 774 143926517 185449813 774 0.1542 971s 3 1311 185449813 247137334 1311 0.2512 971s Calculating (C1,C2) per segment... 971s Calculating (C1,C2) per segment...done 971s Number of segments: 3 971s Segmenting paired tumor-normal signals using Paired PSCBS...done 971s Post-segmenting TCNs... 971s Number of segments: 3 971s Number of chromosomes: 1 971s [1] 1 971s Chromosome 1 ('chr01') of 1... 971s Rows: 971s [1] 1 2 3 971s Number of segments: 3 971s TCN segment #1 ('1') of 3... 971s Nothing todo. Only one DH segmentation. Skipping. 971s TCN segment #1 ('1') of 3...done 971s TCN segment #2 ('2') of 3... 971s Nothing todo. Only one DH segmentation. Skipping. 971s TCN segment #2 ('2') of 3...done 971s TCN segment #3 ('3') of 3... 971s Nothing todo. Only one DH segmentation. Skipping. 971s TCN segment #3 ('3') of 3...done 971s Chromosome 1 ('chr01') of 1...done 971s Update (C1,C2) per segment... 971s Update (C1,C2) per segment...done 971s Post-segmenting TCNs...done 971s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 971s 1 1 1 1 554484 143926517 7599 1.3859 2111 971s 2 1 2 1 143926517 185449813 2668 2.0704 774 971s 3 1 3 1 185449813 247137334 4391 2.6341 1311 971s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 971s 1 2111 554484 143926517 2111 0.5237 0.3300521 1.055848 971s 2 774 143926517 185449813 774 0.1542 0.8755722 1.194828 971s 3 1311 185449813 247137334 1311 0.2512 0.9862070 1.647893 971s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 971s 1 1 1 1 554484 143926517 7599 1.3859 2111 971s 2 1 2 1 143926517 185449813 2668 2.0704 774 971s 3 1 3 1 185449813 247137334 4391 2.6341 1311 971s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 971s 1 2111 554484 143926517 2111 0.5237 0.3300521 1.055848 971s 2 774 143926517 185449813 774 0.1542 0.8755722 1.194828 971s 3 1311 185449813 247137334 1311 0.2512 0.9862070 1.647893 971s > print(fit) 971s chromosome tcnId dhId start end tcnNbrOfLoci tcnMean tcnNbrOfSNPs 971s 1 1 1 1 554484 143926517 7599 1.3859 2111 971s 2 1 2 1 143926517 185449813 2668 2.0704 774 971s 3 1 3 1 185449813 247137334 4391 2.6341 1311 971s tcnNbrOfHets dhNbrOfLoci dhMean c1Mean c2Mean 971s 1 2111 2111 0.5237 0.3300521 1.055848 971s 2 774 774 0.1542 0.8755722 1.194828 971s 3 1311 1311 0.2512 0.9862070 1.647893 971s > 971s > # Plot results 971s > plotTracks(fit) 971s > 971s > # Sanity check 971s > stopifnot(nbrOfSegments(fit) == nSegs) 971s > 971s > 971s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 971s > # Bootstrap segment level estimates 971s > # (used by the AB caller, which, if skipped here, 971s > # will do it automatically) 971s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 971s > fit <- bootstrapTCNandDHByRegion(fit, B=B, verbose=-10) 971s Resample (TCN,DH) signals and re-estimate summaries for segment & changepoint... 971s Already done? 971s tcn_2.5% tcn_5% tcn_95% tcn_97.5% dh_2.5% dh_5% dh_95% dh_97.5% 971s FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE 971s c1_2.5% c1_5% c1_95% c1_97.5% c2_2.5% c2_5% c2_95% c2_97.5% 971s FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE 971s Bootstrapping (TCN,DH,C1,C2) segment mean levels... 971s Identifying heterozygous & homozygous SNPs and non-polymorphic loci... 971s Number of loci: 14658 971s Number of SNPs: 4196 971s Number of non-SNPs: 10462 971s Identifying heterozygous & homozygous SNPs and non-polymorphic loci...done 971s num [1:3, 1:100, 1:4] NA NA NA NA NA NA NA NA NA NA ... 971s - attr(*, "dimnames")=List of 3 971s ..$ : NULL 971s ..$ : NULL 971s ..$ : chr [1:4] "tcn" "dh" "c1" "c2" 971s Segment #1 (chr 1, tcnId=1, dhId=1) of 3... 971s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 971s 1 1 1 1 554484 143926517 7599 1.3859 2111 971s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 971s 1 2111 554484 143926517 2111 0.5237 0.3300521 1.055848 971s Number of TCNs: 7599 971s Number of DHs: 2111 971s int [1:7599] 1 2 3 4 5 6 7 8 9 10 ... 971s int [1:14658] 1 2 3 4 5 6 7 8 9 10 ... 971s int [1:7599] 1 2 3 4 5 6 7 8 9 10 ... 971s Identify loci used to bootstrap DH means... 971s Heterozygous SNPs to resample for DH: 971s int [1:2111] 10 12 24 28 31 33 34 39 46 48 ... 971s Identify loci used to bootstrap DH means...done 971s Identify loci used to bootstrap TCN means... 971s SNPs: 971s int [1:2111] 10 12 24 28 31 33 34 39 46 48 ... 971s Non-polymorphic loci: 971s int [1:5488] 1 2 3 4 5 6 7 8 9 11 ... 971s Heterozygous SNPs to resample for TCN: 971s int [1:2111] 10 12 24 28 31 33 34 39 46 48 ... 971s Homozygous SNPs to resample for TCN: 971s int(0) 971s Non-polymorphic loci to resample for TCN: 971s int [1:5488] 1 2 3 4 5 6 7 8 9 11 ... 971s Heterozygous SNPs with non-DH to resample for TCN: 971s int(0) 971s Loci to resample for TCN: 971s int [1:7599] 1 2 3 4 5 6 7 8 9 10 ... 971s Identify loci used to bootstrap TCN means...done 971s Number of (#hets, #homs, #nonSNPs): (2111,0,5488) 971s Bootstrapping while preserving (#hets, #homs, #nonSNPs)... 971s Number of bootstrap samples: 100 972s Bootstrapping while preserving (#hets, #homs, #nonSNPs)...done 972s Segment #1 (chr 1, tcnId=1, dhId=1) of 3...done 972s Segment #2 (chr 1, tcnId=2, dhId=1) of 3... 972s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 972s 2 1 2 1 143926517 185449813 2668 2.0704 774 972s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 972s 2 774 143926517 185449813 774 0.1542 0.8755722 1.194828 972s Number of TCNs: 2668 972s Number of DHs: 774 972s int [1:2668] 7600 7601 7602 7603 7604 7605 7606 7607 7608 7609 ... 972s int [1:14658] 1 2 3 4 5 6 7 8 9 10 ... 972s int [1:2668] 7600 7601 7602 7603 7604 7605 7606 7607 7608 7609 ... 972s Identify loci used to bootstrap DH means... 972s Heterozygous SNPs to resample for DH: 972s int [1:774] 7614 7616 7626 7627 7628 7635 7638 7639 7640 7642 ... 972s Identify loci used to bootstrap DH means...done 972s Identify loci used to bootstrap TCN means... 972s SNPs: 972s int [1:774] 7614 7616 7626 7627 7628 7635 7638 7639 7640 7642 ... 972s Non-polymorphic loci: 972s int [1:1894] 7600 7601 7602 7603 7604 7605 7606 7607 7608 7609 ... 972s Heterozygous SNPs to resample for TCN: 972s int [1:774] 7614 7616 7626 7627 7628 7635 7638 7639 7640 7642 ... 972s Homozygous SNPs to resample for TCN: 972s int(0) 972s Non-polymorphic loci to resample for TCN: 972s int [1:1894] 7600 7601 7602 7603 7604 7605 7606 7607 7608 7609 ... 972s Heterozygous SNPs with non-DH to resample for TCN: 972s int(0) 972s Loci to resample for TCN: 972s int [1:2668] 7600 7601 7602 7603 7604 7605 7606 7607 7608 7609 ... 972s Identify loci used to bootstrap TCN means...done 972s Number of (#hets, #homs, #nonSNPs): (774,0,1894) 972s Bootstrapping while preserving (#hets, #homs, #nonSNPs)... 972s Number of bootstrap samples: 100 972s Bootstrapping while preserving (#hets, #homs, #nonSNPs)...done 972s Segment #2 (chr 1, tcnId=2, dhId=1) of 3...done 972s Segment #3 (chr 1, tcnId=3, dhId=1) of 3... 972s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 972s 3 1 3 1 185449813 247137334 4391 2.6341 1311 972s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 972s 3 1311 185449813 247137334 1311 0.2512 0.986207 1.647893 972s Number of TCNs: 4391 972s Number of DHs: 1311 972s int [1:4391] 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 972s int [1:14658] 1 2 3 4 5 6 7 8 9 10 ... 972s int [1:4391] 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 972s Identify loci used to bootstrap DH means... 972s Heterozygous SNPs to resample for DH: 972s int [1:1311] 10269 10271 10281 10282 10283 10293 10295 10297 10300 10302 ... 972s Identify loci used to bootstrap DH means...done 972s Identify loci used to bootstrap TCN means... 972s SNPs: 972s int [1:1311] 10269 10271 10281 10282 10283 10293 10295 10297 10300 10302 ... 972s Non-polymorphic loci: 972s int [1:3080] 10268 10270 10272 10273 10274 10275 10276 10277 10278 10279 ... 972s Heterozygous SNPs to resample for TCN: 972s int [1:1311] 10269 10271 10281 10282 10283 10293 10295 10297 10300 10302 ... 972s Homozygous SNPs to resample for TCN: 972s int(0) 972s Non-polymorphic loci to resample for TCN: 972s int [1:3080] 10268 10270 10272 10273 10274 10275 10276 10277 10278 10279 ... 972s Heterozygous SNPs with non-DH to resample for TCN: 972s int(0) 972s Loci to resample for TCN: 972s int [1:4391] 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 972s Identify loci used to bootstrap TCN means...done 972s Number of (#hets, #homs, #nonSNPs): (1311,0,3080) 972s Bootstrapping while preserving (#hets, #homs, #nonSNPs)... 972s Number of bootstrap samples: 100 972s Bootstrapping while preserving (#hets, #homs, #nonSNPs)...done 972s Segment #3 (chr 1, tcnId=3, dhId=1) of 3...done 972s Bootstrapped segment mean levels 972s num [1:3, 1:100, 1:4] 1.38 2.08 2.63 1.38 2.07 ... 972s - attr(*, "dimnames")=List of 3 972s ..$ : NULL 972s ..$ : NULL 972s ..$ : chr [1:4] "tcn" "dh" "c1" "c2" 972s Calculating (C1,C2) mean levels from (TCN,DH) mean levels... 972s num [1:3, 1:100, 1:4] 1.38 2.08 2.63 1.38 2.07 ... 972s - attr(*, "dimnames")=List of 3 972s ..$ : NULL 972s ..$ : NULL 972s ..$ : chr [1:4] "tcn" "dh" "c1" "c2" 972s Calculating (C1,C2) mean levels from (TCN,DH) mean levels...done 972s Calculating polar (alpha,radius,manhattan) for change points... 972s num [1:2, 1:100, 1:2] -0.5588 -0.0962 -0.5365 -0.1285 -0.5378 ... 972s - attr(*, "dimnames")=List of 3 972s ..$ : NULL 972s ..$ : NULL 972s ..$ : chr [1:2] "c1" "c2" 972s Bootstrapped change points 972s num [1:2, 1:100, 1:5] -2.89 -1.78 -2.87 -1.86 -2.88 ... 972s - attr(*, "dimnames")=List of 3 972s ..$ : NULL 972s ..$ : NULL 972s ..$ : chr [1:5] "alpha" "radius" "manhattan" "d1" ... 972s Calculating polar (alpha,radius,manhattan) for change points...done 972s Bootstrapping (TCN,DH,C1,C2) segment mean levels...done 972s Summarizing bootstrapped segment (‘tcn’, ‘dh’, ‘c1’, ‘c2’) data... 972s num [1:3, 1:4, 1:4] NA NA NA NA NA NA NA NA NA NA ... 972s - attr(*, "dimnames")=List of 3 972s ..$ : NULL 972s ..$ : chr [1:4] "2.5%" "5%" "95%" "97.5%" 972s ..$ : chr [1:4] "tcn" "dh" "c1" "c2" 972s Field #1 ('tcn') of 4... 972s Segment #1 of 3... 972s Segment #1 of 3...done 972s Segment #2 of 3... 972s Segment #2 of 3...done 972s Segment #3 of 3... 972s Segment #3 of 3...done 972s Field #1 ('tcn') of 4...done 972s Field #2 ('dh') of 4... 972s Segment #1 of 3... 972s Segment #1 of 3...done 972s Segment #2 of 3... 972s Segment #2 of 3...done 972s Segment #3 of 3... 972s Segment #3 of 3...done 972s Field #2 ('dh') of 4...done 972s Field #3 ('c1') of 4... 972s Segment #1 of 3... 972s Segment #1 of 3...done 972s Segment #2 of 3... 972s Segment #2 of 3...done 972s Segment #3 of 3... 972s Segment #3 of 3...done 972s Field #3 ('c1') of 4...done 972s Field #4 ('c2') of 4... 972s Segment #1 of 3... 972s Segment #1 of 3...done 972s Segment #2 of 3... 972s Segment #2 of 3...done 972s Segment #3 of 3... 972s Segment #3 of 3...done 972s Field #4 ('c2') of 4...done 972s Bootstrap statistics 972s num [1:3, 1:4, 1:4] 1.38 2.06 2.62 1.38 2.06 ... 972s - attr(*, "dimnames")=List of 3 972s ..$ : NULL 972s ..$ : chr [1:4] "2.5%" "5%" "95%" "97.5%" 972s ..$ : chr [1:4] "tcn" "dh" "c1" "c2" 972s Statistical sanity checks (iff B >= 100)... 972s Available summaries: 2.5%, 5%, 95%, 97.5% 972s Available quantiles: 0.025, 0.05, 0.95, 0.975 972s num [1:3, 1:4, 1:4] 1.38 2.06 2.62 1.38 2.06 ... 972s - attr(*, "dimnames")=List of 3 972s ..$ : NULL 972s ..$ : chr [1:4] "2.5%" "5%" "95%" "97.5%" 972s ..$ : chr [1:4] "tcn" "dh" "c1" "c2" 972s Field #1 ('tcn') of 4... 972s Seg 1. mean=1.3859, range=[1.38092,1.3949], n=7599 972s Seg 2. mean=2.0704, range=[2.05747,2.08326], n=2668 972s Seg 3. mean=2.6341, range=[2.62068,2.64694], n=4391 972s Field #1 ('tcn') of 4...done 972s Field #2 ('dh') of 4... 972s Seg 1. mean=0.5237, range=[0.51753,0.532002], n=2111 972s Seg 2. mean=0.1542, range=[0.144468,0.16453], n=774 972s Seg 3. mean=0.2512, range=[0.242575,0.258832], n=1311 972s Field #2 ('dh') of 4...done 972s Field #3 ('c1') of 4... 972s Seg 1. mean=0.330052, range=[0.323996,0.336038], n=2111 972s Seg 2. mean=0.875572, range=[0.86318,0.887699], n=774 972s Seg 3. mean=0.986207, range=[0.975123,0.998982], n=1311 972s Field #3 ('c1') of 4...done 972s Field #4 ('c2') of 4... 972s Seg 1. mean=1.05585, range=[1.05006,1.06231], n=2111 972s Seg 2. mean=1.19483, range=[1.18417,1.2081], n=774 972s Seg 3. mean=1.64789, range=[1.63403,1.66098], n=1311 972s Field #4 ('c2') of 4...done 972s Statistical sanity checks (iff B >= 100)...done 972s Summarizing bootstrapped segment (‘tcn’, ‘dh’, ‘c1’, ‘c2’) data...done 972s Summarizing bootstrapped changepoint (‘alpha’, ‘radius’, ‘manhattan’, ‘d1’, ‘d2’) data... 972s num [1:2, 1:4, 1:5] NA NA NA NA NA NA NA NA NA NA ... 972s - attr(*, "dimnames")=List of 3 972s ..$ : NULL 972s ..$ : chr [1:4] "2.5%" "5%" "95%" "97.5%" 972s ..$ : chr [1:5] "alpha" "radius" "manhattan" "d1" ... 972s Field #1 ('alpha') of 5... 972s Changepoint #1 of 2... 972s Changepoint #1 of 2...done 972s Changepoint #2 of 2... 972s Changepoint #2 of 2...done 972s Field #1 ('alpha') of 5...done 972s Field #2 ('radius') of 5... 972s Changepoint #1 of 2... 972s Changepoint #1 of 2...done 972s Changepoint #2 of 2... 972s Changepoint #2 of 2...done 972s Field #2 ('radius') of 5...done 972s Field #3 ('manhattan') of 5... 972s Changepoint #1 of 2... 972s Changepoint #1 of 2...done 972s Changepoint #2 of 2... 972s Changepoint #2 of 2...done 972s Field #3 ('manhattan') of 5...done 972s Field #4 ('d1') of 5... 972s Changepoint #1 of 2... 972s Changepoint #1 of 2...done 972s Changepoint #2 of 2... 972s Changepoint #2 of 2...done 972s Field #4 ('d1') of 5...done 972s Field #5 ('d2') of 5... 972s Changepoint #1 of 2... 972s Changepoint #1 of 2...done 972s Changepoint #2 of 2... 972s Changepoint #2 of 2...done 972s Field #5 ('d2') of 5...done 972s Bootstrap statistics 972s num [1:2, 1:4, 1:5] -2.92 -1.86 -2.91 -1.85 -2.87 ... 972s - attr(*, "dimnames")=List of 3 972s ..$ : NULL 972s ..$ : chr [1:4] "2.5%" "5%" "95%" "97.5%" 972s ..$ : chr [1:5] "alpha" "radius" "manhattan" "d1" ... 972s Summarizing bootstrapped changepoint (‘alpha’, ‘radius’, ‘manhattan’, ‘d1’, ‘d2’) data...done 972s Resample (TCN,DH) signals and re-estimate summaries for segment & changepoint...done 972s > print(fit) 972s chromosome tcnId dhId start end tcnNbrOfLoci tcnMean tcnNbrOfSNPs 972s 1 1 1 1 554484 143926517 7599 1.3859 2111 972s 2 1 2 1 143926517 185449813 2668 2.0704 774 972s 3 1 3 1 185449813 247137334 4391 2.6341 1311 972s tcnNbrOfHets dhNbrOfLoci dhMean c1Mean c2Mean 972s 1 2111 2111 0.5237 0.3300521 1.055848 972s 2 774 774 0.1542 0.8755722 1.194828 972s 3 1311 1311 0.2512 0.9862070 1.647893 972s > plotTracks(fit) 972s > 972s > 972s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 972s > # Calling segments in allelic balance (AB) and 972s > # in loss-of-heterozygosity (LOH) 972s > # NOTE: Ideally, this should be done on whole-genome data 972s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 972s > fit <- callAB(fit, verbose=-10) 972s Calling segments of allelic balance from one-sided DH bootstrap confidence intervals... 972s delta (offset adjusting for bias in DH): 0.3466649145302 972s alpha (CI quantile; significance level): 0.05 972s Calling segments... 972s Number of segments called allelic balance (AB): 2 (66.67%) of 3 972s Calling segments...done 972s Calling segments of allelic balance from one-sided DH bootstrap confidence intervals...done 972s > fit <- callLOH(fit, verbose=-10) 972s Calling segments of allelic balance from one-sided DH bootstrap confidence intervals... 972s delta (offset adjusting for bias in C1): 0.771236438183453 972s alpha (CI quantile; significance level): 0.05 972s Calling segments... 972s Number of segments called low C1 (LowC1, "LOH_C1"): 1 (33.33%) of 3 972s Calling segments...done 972s Calling segments of allelic balance from one-sided DH bootstrap confidence intervals...done 972s > print(fit) 972s chromosome tcnId dhId start end tcnNbrOfLoci tcnMean tcnNbrOfSNPs 972s 1 1 1 1 554484 143926517 7599 1.3859 2111 972s 2 1 2 1 143926517 185449813 2668 2.0704 774 972s 3 1 3 1 185449813 247137334 4391 2.6341 1311 972s tcnNbrOfHets dhNbrOfLoci dhMean c1Mean c2Mean abCall lohCall 972s 1 2111 2111 0.5237 0.3300521 1.055848 FALSE TRUE 972s 2 774 774 0.1542 0.8755722 1.194828 TRUE FALSE 972s 3 1311 1311 0.2512 0.9862070 1.647893 TRUE FALSE 972s > plotTracks(fit) 972s > 972s Start: segmentByPairedPSCBS,report.R 972s 972s R version 4.5.2 (2025-10-31) -- "[Not] Part in a Rumble" 972s Copyright (C) 2025 The R Foundation for Statistical Computing 972s Platform: powerpc64le-unknown-linux-gnu 972s 972s R is free software and comes with ABSOLUTELY NO WARRANTY. 972s You are welcome to redistribute it under certain conditions. 972s Type 'license()' or 'licence()' for distribution details. 972s 972s R is a collaborative project with many contributors. 972s Type 'contributors()' for more information and 972s 'citation()' on how to cite R or R packages in publications. 972s 972s Type 'demo()' for some demos, 'help()' for on-line help, or 972s 'help.start()' for an HTML browser interface to help. 972s Type 'q()' to quit R. 972s 972s > # This test script calls a report generator which requires 972s > # the 'ggplot2' package, which in turn will require packages 972s > # 'colorspace', 'dichromat', 'munsell', 'reshape2' and 'scales'. 972s > 972s > # Only run this test in full testing mode 972s > if (Sys.getenv("_R_CHECK_FULL_") != "") { 972s + library("PSCBS") 972s + 972s + # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 972s + # Load SNP microarray data 972s + # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 972s + data <- PSCBS::exampleData("paired.chr01") 972s + str(data) 972s + 972s + 972s + # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 972s + # Paired PSCBS segmentation 972s + # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 972s + # Drop single-locus outliers 972s + dataS <- dropSegmentationOutliers(data) 972s + 972s + # Speed up example by segmenting fewer loci 972s + dataS <- dataS[seq(from=1, to=nrow(data), by=5),] 972s + 972s + str(dataS) 972s + 972s + gaps <- findLargeGaps(dataS, minLength=2e6) 972s + knownSegments <- gapsToSegments(gaps) 972s + 972s + # Paired PSCBS segmentation 972s + fit <- segmentByPairedPSCBS(dataS, knownSegments=knownSegments, 972s + seed=0xBEEF, verbose=-10) 972s + 972s + # Fake a multi-chromosome segmentation 972s + fit1 <- fit 972s + fit2 <- renameChromosomes(fit, from=1, to=2) 972s + fit <- c(fit1, fit2) 972s + 972s + report(fit, sampleName="PairedPSCBS", studyName="PSCBS-Ex", verbose=-10) 972s + 972s + } # if (Sys.getenv("_R_CHECK_FULL_")) 972s > 972s Start: segmentByPairedPSCBS,seqOfSegmentsByDP.R 972s 972s R version 4.5.2 (2025-10-31) -- "[Not] Part in a Rumble" 972s Copyright (C) 2025 The R Foundation for Statistical Computing 972s Platform: powerpc64le-unknown-linux-gnu 972s 972s R is free software and comes with ABSOLUTELY NO WARRANTY. 972s You are welcome to redistribute it under certain conditions. 972s Type 'license()' or 'licence()' for distribution details. 972s 972s R is a collaborative project with many contributors. 972s Type 'contributors()' for more information and 972s 'citation()' on how to cite R or R packages in publications. 972s 972s Type 'demo()' for some demos, 'help()' for on-line help, or 972s 'help.start()' for an HTML browser interface to help. 972s Type 'q()' to quit R. 972s 972s > library("PSCBS") 973s PSCBS v0.68.0 (2025-04-18 19:40:02 UTC) successfully loaded. See ?PSCBS for help. 973s > subplots <- R.utils::subplots 973s > stext <- R.utils::stext 973s > 973s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 973s > # Load SNP microarray data 973s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 973s > data <- PSCBS::exampleData("paired.chr01") 973s > str(data) 973s 'data.frame': 73346 obs. of 6 variables: 973s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 973s $ x : int 1145994 2224111 2319424 2543484 2926730 2941694 3084986 3155127 3292731 3695086 ... 973s $ CT : num 1.625 1.071 1.406 1.18 0.856 ... 973s $ betaT : num 0.757 0.771 0.834 0.778 0.229 ... 973s $ CN : num 2.36 2.13 2.59 1.93 1.71 ... 973s $ betaN : num 0.827 0.875 0.887 0.884 0.103 ... 973s > 973s > 973s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 973s > # Paired PSCBS segmentation 973s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 973s > # Drop single-locus outliers 973s > dataS <- dropSegmentationOutliers(data) 973s > 973s > # Run light-weight tests by default 973s > if (Sys.getenv("_R_CHECK_FULL_") == "") { 973s + # Use only every 5th data point 973s + dataS <- dataS[seq(from=1, to=nrow(data), by=5),] 973s + # Number of segments (for assertion) 973s + nSegs <- 3L 973s + # Number of bootstrap samples (see below) 973s + B <- 100L 973s + } else { 973s + # Full tests 973s + nSegs <- 12L 973s + B <- 1000L 973s + } 973s > 973s > str(dataS) 973s 'data.frame': 14670 obs. of 6 variables: 973s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 973s $ x : int 1145994 2941694 3710825 4240737 4276892 4464544 4714611 5095111 5034491 5158416 ... 973s $ CT : num 1.63 1.4 1.41 1.17 1.16 ... 973s $ betaT : num 0.7574 0.169 0.2357 0.2604 0.0576 ... 973s $ CN : num 2.36 2.13 2.26 2.01 2.32 ... 973s $ betaN : num 0.8274 0.5072 0.1671 0.1609 0.0421 ... 973s > 973s > R.oo::attachLocally(dataS) 973s > 973s > 973s > gaps <- findLargeGaps(dataS, minLength=2e6) 973s > knownSegments <- gapsToSegments(gaps, dropGaps=TRUE) 973s > 973s > # Paired PSCBS segmentation 973s > fit <- segmentByPairedPSCBS(dataS, knownSegments=knownSegments, 973s + seed=0xBEEF, verbose=-10) 973s Segmenting paired tumor-normal signals using Paired PSCBS... 973s Calling genotypes from normal allele B fractions... 973s num [1:14670] 0.8274 0.5072 0.1671 0.1609 0.0421 ... 973s Called genotypes: 973s num [1:14670] 1 0.5 0 0 0 0 1 0 1 0.5 ... 973s - attr(*, "modelFit")=List of 1 973s ..$ :List of 7 973s .. ..$ flavor : chr "density" 973s .. ..$ cn : int 2 973s .. ..$ nbrOfGenotypeGroups: int 3 973s .. ..$ tau : num [1:2] 0.315 0.677 973s .. ..$ n : int 14640 973s .. ..$ fit :Classes ‘PeaksAndValleys’ and 'data.frame': 5 obs. of 3 variables: 973s .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 973s .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 973s .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 973s .. ..$ fitValleys :Classes ‘PeaksAndValleys’ and 'data.frame': 2 obs. of 3 variables: 973s .. .. ..$ type : chr [1:2] "valley" "valley" 973s .. .. ..$ x : num [1:2] 0.315 0.677 973s .. .. ..$ density: num [1:2] 0.522 0.551 973s ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 973s muN 973s 0 0.5 1 973s 5221 4198 5251 973s Calling genotypes from normal allele B fractions...done 973s Normalizing betaT using betaN (TumorBoost)... 973s Normalized BAFs: 973s num [1:14670] 0.9301 0.1667 0.0685 0.0995 0.0155 ... 973s - attr(*, "modelFit")=List of 5 973s ..$ method : chr "normalizeTumorBoost" 973s ..$ flavor : chr "v4" 973s ..$ delta : num [1:14670] -0.17264 0.00239 0.1671 0.16085 0.04213 ... 973s .. ..- attr(*, "modelFit")=List of 1 973s .. .. ..$ :List of 7 973s .. .. .. ..$ flavor : chr "density" 973s .. .. .. ..$ cn : int 2 973s .. .. .. ..$ nbrOfGenotypeGroups: int 3 973s .. .. .. ..$ tau : num [1:2] 0.315 0.677 973s .. .. .. ..$ n : int 14640 973s .. .. .. ..$ fit :Classes ‘PeaksAndValleys’ and 'data.frame': 5 obs. of 3 variables: 973s .. .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 973s .. .. .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 973s .. .. .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 973s .. .. .. ..$ fitValleys :Classes ‘PeaksAndValleys’ and 'data.frame': 2 obs. of 3 variables: 973s .. .. .. .. ..$ type : chr [1:2] "valley" "valley" 973s .. .. .. .. ..$ x : num [1:2] 0.315 0.677 973s .. .. .. .. ..$ density: num [1:2] 0.522 0.551 973s .. .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 973s ..$ preserveScale: logi FALSE 973s ..$ scaleFactor : num NA 973s Normalizing betaT using betaN (TumorBoost)...done 973s Setup up data... 973s 'data.frame': 14670 obs. of 7 variables: 973s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 973s $ x : num 1145994 2941694 3710825 4240737 4276892 ... 973s $ CT : num 1.63 1.4 1.41 1.17 1.16 ... 973s $ betaT : num 0.7574 0.169 0.2357 0.2604 0.0576 ... 973s $ betaTN : num 0.9301 0.1667 0.0685 0.0995 0.0155 ... 973s ..- attr(*, "modelFit")=List of 5 973s .. ..$ method : chr "normalizeTumorBoost" 973s .. ..$ flavor : chr "v4" 973s .. ..$ delta : num [1:14670] -0.17264 0.00239 0.1671 0.16085 0.04213 ... 973s .. .. ..- attr(*, "modelFit")=List of 1 973s .. .. .. ..$ :List of 7 973s .. .. .. .. ..$ flavor : chr "density" 973s .. .. .. .. ..$ cn : int 2 973s .. .. .. .. ..$ nbrOfGenotypeGroups: int 3 973s .. .. .. .. ..$ tau : num [1:2] 0.315 0.677 973s .. .. .. .. ..$ n : int 14640 973s .. .. .. .. ..$ fit :Classes ‘PeaksAndValleys’ and 'data.frame': 5 obs. of 3 variables: 973s .. .. .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 973s .. .. .. .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 973s .. .. .. .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 973s .. .. .. .. ..$ fitValleys :Classes ‘PeaksAndValleys’ and 'data.frame': 2 obs. of 3 variables: 973s .. .. .. .. .. ..$ type : chr [1:2] "valley" "valley" 973s .. .. .. .. .. ..$ x : num [1:2] 0.315 0.677 973s .. .. .. .. .. ..$ density: num [1:2] 0.522 0.551 973s .. .. .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 973s .. ..$ preserveScale: logi FALSE 973s .. ..$ scaleFactor : num NA 973s $ betaN : num 0.8274 0.5072 0.1671 0.1609 0.0421 ... 973s $ muN : num 1 0.5 0 0 0 0 1 0 1 0.5 ... 973s ..- attr(*, "modelFit")=List of 1 973s .. ..$ :List of 7 973s .. .. ..$ flavor : chr "density" 973s .. .. ..$ cn : int 2 973s .. .. ..$ nbrOfGenotypeGroups: int 3 973s .. .. ..$ tau : num [1:2] 0.315 0.677 973s .. .. ..$ n : int 14640 973s .. .. ..$ fit :Classes ‘PeaksAndValleys’ and 'data.frame': 5 obs. of 3 variables: 973s .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 973s .. .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 973s .. .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 973s .. .. ..$ fitValleys :Classes ‘PeaksAndValleys’ and 'data.frame': 2 obs. of 3 variables: 973s .. .. .. ..$ type : chr [1:2] "valley" "valley" 973s .. .. .. ..$ x : num [1:2] 0.315 0.677 973s .. .. .. ..$ density: num [1:2] 0.522 0.551 973s .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 973s Setup up data...done 973s Dropping loci for which TCNs are missing... 973s Number of loci dropped: 12 973s Dropping loci for which TCNs are missing...done 973s Ordering data along genome... 973s 'data.frame': 14658 obs. of 7 variables: 973s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 973s $ x : num 554484 730720 782343 878522 916294 ... 973s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 973s $ betaT : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 973s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 973s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 973s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 973s Ordering data along genome...done 973s Keeping only current chromosome for 'knownSegments'... 973s Chromosome: 1 973s Known segments for this chromosome: 973s chromosome start end length 973s 1 1 -Inf 120908858 Inf 973s 2 1 142693888 Inf Inf 973s Keeping only current chromosome for 'knownSegments'...done 973s alphaTCN: 0.009 973s alphaDH: 0.001 973s Number of loci: 14658 973s Calculating DHs... 973s Number of SNPs: 14658 973s Number of heterozygous SNPs: 4196 (28.63%) 973s Normalized DHs: 973s num [1:14658] NA NA NA NA NA ... 973s Calculating DHs...done 973s Random seed temporarily set (seed=c(48879), kind="L'Ecuyer-CMRG") 973s Produced 2 seeds from this stream for future usage 973s Identification of change points by total copy numbers... 973s Segmenting by CBS... 973s Chromosome: 1 973s Segmenting multiple segments on current chromosome... 973s Number of segments: 2 973s Random seed temporarily set (seed=c(10407, 1066287653, -51199871, 161854402, -1995183193, 1503453565, -747102133), kind="L'Ecuyer-CMRG") 973s Produced 2 seeds from this stream for future usage 973s Segmenting by CBS... 973s Chromosome: 1 973s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 973s Segmenting by CBS...done 973s Segmenting by CBS... 973s Chromosome: 1 973s Random seed temporarily set (seed=c(10407, -821273412, -52578226, 1415511586, 721384351, -665928286, 1316562960), kind="L'Ecuyer-CMRG") 974s Segmenting by CBS...done 974s Segmenting multiple segments on current chromosome...done 974s Segmenting by CBS...done 974s List of 4 974s $ data :'data.frame': 14658 obs. of 4 variables: 974s ..$ chromosome: int [1:14658] 1 1 1 1 1 1 1 1 1 1 ... 974s ..$ x : num [1:14658] 554484 730720 782343 878522 916294 ... 974s ..$ y : num [1:14658] 1.88 1.8 1.59 1.64 1.53 ... 974s ..$ index : int [1:14658] 1 2 3 4 5 6 7 8 9 10 ... 974s $ output :'data.frame': 3 obs. of 6 variables: 974s ..$ sampleName: chr [1:3] NA NA NA 974s ..$ chromosome: int [1:3] 1 1 1 974s ..$ start : num [1:3] 5.54e+05 1.43e+08 1.85e+08 974s ..$ end : num [1:3] 1.21e+08 1.85e+08 2.47e+08 974s ..$ nbrOfLoci : int [1:3] 7586 2681 4391 974s ..$ mean : num [1:3] 1.39 2.07 2.63 974s $ segRows:'data.frame': 3 obs. of 2 variables: 974s ..$ startRow: int [1:3] 1 7587 10268 974s ..$ endRow : int [1:3] 7586 10267 14658 974s $ params :List of 5 974s ..$ alpha : num 0.009 974s ..$ undo : num 0 974s ..$ joinSegments : logi TRUE 974s ..$ knownSegments:'data.frame': 2 obs. of 3 variables: 974s .. ..$ chromosome: int [1:2] 1 1 974s .. ..$ start : num [1:2] -Inf 1.43e+08 974s .. ..$ end : num [1:2] 1.21e+08 Inf 974s ..$ seed : int [1:7] 10407 1066287653 -51199871 161854402 -1995183193 1503453565 -747102133 974s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 974s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.165 0 0.166 0 0 974s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 974s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 974s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 974s Identification of change points by total copy numbers...done 974s Restructure TCN segmentation results... 974s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean 974s 1 1 554484 120908858 7586 1.3853 974s 2 1 142693888 185449813 2681 2.0689 974s 3 1 185449813 247137334 4391 2.6341 974s Number of TCN segments: 3 974s Restructure TCN segmentation results...done 974s Total CN segment #1 ([ 554484,1.20909e+08]) of 3... 974s Number of TCN loci in segment: 7586 974s Locus data for TCN segment: 974s 'data.frame': 7586 obs. of 9 variables: 974s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 974s $ x : num 554484 730720 782343 878522 916294 ... 974s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 974s $ betaT : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 974s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 974s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 974s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 974s $ index : int 1 2 3 4 5 6 7 8 9 10 ... 974s $ rho : num NA NA NA NA NA ... 974s Number of loci: 7586 974s Number of SNPs: 2108 (27.79%) 974s Number of heterozygous SNPs: 2108 (100.00%) 974s Chromosome: 1 974s Segmenting DH signals... 974s Segmenting by CBS... 974s Chromosome: 1 974s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 974s Segmenting by CBS...done 974s List of 4 974s $ data :'data.frame': 7586 obs. of 4 variables: 974s ..$ chromosome: int [1:7586] 1 1 1 1 1 1 1 1 1 1 ... 974s ..$ x : num [1:7586] 554484 730720 782343 878522 916294 ... 974s ..$ y : num [1:7586] NA NA NA NA NA ... 974s ..$ index : int [1:7586] 1 2 3 4 5 6 7 8 9 10 ... 974s $ output :'data.frame': 1 obs. of 6 variables: 974s ..$ sampleName: chr NA 974s ..$ chromosome: int 1 974s ..$ start : num 554484 974s ..$ end : num 1.21e+08 974s ..$ nbrOfLoci : int 2108 974s ..$ mean : num 0.512 974s $ segRows:'data.frame': 1 obs. of 2 variables: 974s ..$ startRow: int 10 974s ..$ endRow : int 7574 974s $ params :List of 5 974s ..$ alpha : num 0.001 974s ..$ undo : num 0 974s ..$ joinSegments : logi TRUE 974s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 974s .. ..$ chromosome: int 1 974s .. ..$ start : num 554484 974s .. ..$ end : num 1.21e+08 974s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 974s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 974s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.046 0 0.047 0 0 974s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 974s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 974s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 974s DH segmentation (locally-indexed) rows: 974s startRow endRow 974s 1 10 7574 974s int [1:7586] 1 2 3 4 5 6 7 8 9 10 ... 974s DH segmentation rows: 974s startRow endRow 974s 1 10 7574 974s Segmenting DH signals...done 974s DH segmentation table: 974s dhStart dhEnd dhNbrOfLoci dhMean 974s 1 554484 120908858 2108 0.5116 974s startRow endRow 974s 1 10 7574 974s Rows: 974s [1] 1 974s TCN segmentation rows: 974s startRow endRow 974s 1 1 7586 974s TCN and DH segmentation rows: 974s startRow endRow 974s 1 1 7586 974s startRow endRow 974s 1 10 7574 974s NULL 974s TCN segmentation (expanded) rows: 974s startRow endRow 974s 1 1 7586 974s TCN and DH segmentation rows: 974s startRow endRow 974s 1 1 7586 974s 2 7587 10267 974s 3 10268 14658 974s startRow endRow 974s 1 10 7574 974s startRow endRow 974s 1 1 7586 974s Total CN segmentation table (expanded): 974s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 974s 1 1 554484 120908858 7586 1.3853 2108 2108 974s (TCN,DH) segmentation for one total CN segment: 974s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 974s 1 1 1 1 554484 120908858 7586 1.3853 2108 974s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 974s 1 2108 554484 120908858 2108 0.5116 974s Total CN segment #1 ([ 554484,1.20909e+08]) of 3...done 974s Total CN segment #2 ([1.42694e+08,1.8545e+08]) of 3... 974s Number of TCN loci in segment: 2681 974s Locus data for TCN segment: 974s 'data.frame': 2681 obs. of 9 variables: 974s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 974s $ x : num 1.43e+08 1.43e+08 1.43e+08 1.43e+08 1.44e+08 ... 974s $ CT : num 2.27 1.55 1.47 1.5 1.81 ... 974s $ betaT : num 0.34 0.55 0.048 0.813 0.575 ... 974s $ betaTN : num 0.441 0.629 -0.05 0.958 0.872 ... 974s $ betaN : num 0.3851 0.3933 0.0981 0.8552 0.7028 ... 974s $ muN : num 0.5 0.5 0 1 1 1 1 0.5 1 1 ... 974s $ index : int 7587 7588 7589 7590 7591 7592 7593 7594 7595 7596 ... 974s $ rho : num 0.117 0.258 NA NA NA ... 974s Number of loci: 2681 974s Number of SNPs: 777 (28.98%) 974s Number of heterozygous SNPs: 777 (100.00%) 974s Chromosome: 1 974s Segmenting DH signals... 974s Segmenting by CBS... 974s Chromosome: 1 974s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 974s Segmenting by CBS...done 974s List of 4 974s $ data :'data.frame': 2681 obs. of 4 variables: 974s ..$ chromosome: int [1:2681] 1 1 1 1 1 1 1 1 1 1 ... 974s ..$ x : num [1:2681] 1.43e+08 1.43e+08 1.43e+08 1.43e+08 1.44e+08 ... 974s ..$ y : num [1:2681] 0.117 0.258 NA NA NA ... 974s ..$ index : int [1:2681] 1 2 3 4 5 6 7 8 9 10 ... 974s $ output :'data.frame': 1 obs. of 6 variables: 974s ..$ sampleName: chr NA 974s ..$ chromosome: int 1 974s ..$ start : num 1.43e+08 974s ..$ end : num 1.85e+08 974s ..$ nbrOfLoci : int 777 974s ..$ mean : num 0.0973 974s $ segRows:'data.frame': 1 obs. of 2 variables: 974s ..$ startRow: int 1 974s ..$ endRow : int 2677 974s $ params :List of 5 974s ..$ alpha : num 0.001 974s ..$ undo : num 0 974s ..$ joinSegments : logi TRUE 974s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 974s .. ..$ chromosome: int 1 974s .. ..$ start : num 1.43e+08 974s .. ..$ end : num 1.85e+08 974s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 974s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 974s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.009 0 0.009 0 0 974s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 974s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 974s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 974s DH segmentation (locally-indexed) rows: 974s startRow endRow 974s 1 1 2677 974s int [1:2681] 7587 7588 7589 7590 7591 7592 7593 7594 7595 7596 ... 974s DH segmentation rows: 974s startRow endRow 974s 1 7587 10263 974s Segmenting DH signals...done 974s DH segmentation table: 974s dhStart dhEnd dhNbrOfLoci dhMean 974s 1 142693888 185449813 777 0.0973 974s startRow endRow 974s 1 7587 10263 974s Rows: 974s [1] 2 974s TCN segmentation rows: 974s startRow endRow 974s 2 7587 10267 974s TCN and DH segmentation rows: 974s startRow endRow 974s 2 7587 10267 974s startRow endRow 974s 1 7587 10263 974s startRow endRow 974s 1 1 7586 974s TCN segmentation (expanded) rows: 974s startRow endRow 974s 1 1 7586 974s 2 7587 10267 974s TCN and DH segmentation rows: 974s startRow endRow 974s 1 1 7586 974s 2 7587 10267 974s 3 10268 14658 974s startRow endRow 974s 1 10 7574 974s 2 7587 10263 974s startRow endRow 974s 1 1 7586 974s 2 7587 10267 974s Total CN segmentation table (expanded): 974s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 974s 2 1 142693888 185449813 2681 2.0689 777 777 974s (TCN,DH) segmentation for one total CN segment: 974s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 974s 2 2 1 1 142693888 185449813 2681 2.0689 777 974s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 974s 2 777 142693888 185449813 777 0.0973 974s Total CN segment #2 ([1.42694e+08,1.8545e+08]) of 3...done 974s Total CN segment #3 ([1.8545e+08,2.47137e+08]) of 3... 974s Number of TCN loci in segment: 4391 974s Locus data for TCN segment: 974s 'data.frame': 4391 obs. of 9 variables: 974s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 974s $ x : num 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 974s $ CT : num 2.93 2.15 2.82 2.93 2.46 ... 974s $ betaT : num 0.0811 0.5154 0.9473 0.3734 0.7506 ... 974s $ betaTN : num -0.169 0.609 1.028 0.525 0.968 ... 974s $ betaN : num 0.25 0.38 0.919 0.34 0.783 ... 974s $ muN : num 0 0.5 1 0.5 1 1 0 1 0 1 ... 974s $ index : int 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 974s $ rho : num NA 0.2186 NA 0.0503 NA ... 974s Number of loci: 4391 974s Number of SNPs: 1311 (29.86%) 974s Number of heterozygous SNPs: 1311 (100.00%) 974s Chromosome: 1 974s Segmenting DH signals... 974s Segmenting by CBS... 974s Chromosome: 1 974s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 974s Segmenting by CBS...done 974s List of 4 974s $ data :'data.frame': 4391 obs. of 4 variables: 974s ..$ chromosome: int [1:4391] 1 1 1 1 1 1 1 1 1 1 ... 974s ..$ x : num [1:4391] 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 974s ..$ y : num [1:4391] NA 0.2186 NA 0.0503 NA ... 974s ..$ index : int [1:4391] 1 2 3 4 5 6 7 8 9 10 ... 974s $ output :'data.frame': 1 obs. of 6 variables: 974s ..$ sampleName: chr NA 974s ..$ chromosome: int 1 974s ..$ start : num 1.85e+08 974s ..$ end : num 2.47e+08 974s ..$ nbrOfLoci : int 1311 974s ..$ mean : num 0.23 974s $ segRows:'data.frame': 1 obs. of 2 variables: 974s ..$ startRow: int 2 974s ..$ endRow : int 4388 974s $ params :List of 5 974s ..$ alpha : num 0.001 974s ..$ undo : num 0 974s ..$ joinSegments : logi TRUE 974s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 974s .. ..$ chromosome: int 1 974s .. ..$ start : num 1.85e+08 974s .. ..$ end : num 2.47e+08 974s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 974s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 974s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.018 0 0.018 0 0 974s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 974s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 974s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 974s DH segmentation (locally-indexed) rows: 974s startRow endRow 974s 1 2 4388 974s int [1:4391] 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 974s DH segmentation rows: 974s startRow endRow 974s 1 10269 14655 974s Segmenting DH signals...done 974s DH segmentation table: 974s dhStart dhEnd dhNbrOfLoci dhMean 974s 1 185449813 247137334 1311 0.2295 974s startRow endRow 974s 1 10269 14655 974s Rows: 974s [1] 3 974s TCN segmentation rows: 974s startRow endRow 974s 3 10268 14658 974s TCN and DH segmentation rows: 974s startRow endRow 974s 3 10268 14658 974s startRow endRow 974s 1 10269 14655 974s startRow endRow 974s 1 1 7586 974s 2 7587 10267 974s TCN segmentation (expanded) rows: 974s startRow endRow 974s 1 1 7586 974s 2 7587 10267 974s 3 10268 14658 974s TCN and DH segmentation rows: 974s startRow endRow 974s 1 1 7586 974s 2 7587 10267 974s 3 10268 14658 974s startRow endRow 974s 1 10 7574 974s 2 7587 10263 974s 3 10269 14655 974s startRow endRow 974s 1 1 7586 974s 2 7587 10267 974s 3 10268 14658 974s Total CN segmentation table (expanded): 974s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 974s 3 1 185449813 247137334 4391 2.6341 1311 1311 974s (TCN,DH) segmentation for one total CN segment: 974s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 974s 3 3 1 1 185449813 247137334 4391 2.6341 1311 974s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 974s 3 1311 185449813 247137334 1311 0.2295 974s Total CN segment #3 ([1.8545e+08,2.47137e+08]) of 3...done 974s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 974s 1 1 1 1 554484 120908858 7586 1.3853 2108 974s 2 1 2 1 142693888 185449813 2681 2.0689 777 974s 3 1 3 1 185449813 247137334 4391 2.6341 1311 974s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 974s 1 2108 554484 120908858 2108 0.5116 974s 2 777 142693888 185449813 777 0.0973 974s 3 1311 185449813 247137334 1311 0.2295 974s Calculating (C1,C2) per segment... 974s Calculating (C1,C2) per segment...done 974s Number of segments: 3 974s Segmenting paired tumor-normal signals using Paired PSCBS...done 974s Post-segmenting TCNs... 974s Number of segments: 3 974s Number of chromosomes: 1 974s [1] 1 974s Chromosome 1 ('chr01') of 1... 974s Rows: 974s [1] 1 2 3 974s Number of segments: 3 974s TCN segment #1 ('1') of 3... 974s Nothing todo. Only one DH segmentation. Skipping. 974s TCN segment #1 ('1') of 3...done 974s TCN segment #2 ('2') of 3... 974s Nothing todo. Only one DH segmentation. Skipping. 974s TCN segment #2 ('2') of 3...done 974s TCN segment #3 ('3') of 3... 974s Nothing todo. Only one DH segmentation. Skipping. 974s TCN segment #3 ('3') of 3...done 974s Chromosome 1 ('chr01') of 1...done 974s Update (C1,C2) per segment... 974s Update (C1,C2) per segment...done 974s Post-segmenting TCNs...done 974s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 974s 1 1 1 1 554484 120908858 7586 1.3853 2108 974s 2 1 2 1 142693888 185449813 2681 2.0689 777 974s 3 1 3 1 185449813 247137334 4391 2.6341 1311 974s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 974s 1 2108 554484 120908858 2108 0.5116 0.3382903 1.047010 974s 2 777 142693888 185449813 777 0.0973 0.9337980 1.135102 974s 3 1311 185449813 247137334 1311 0.2295 1.0147870 1.619313 974s > print(fit) 974s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 974s 1 1 1 1 554484 120908858 7586 1.3853 2108 974s 2 1 2 1 142693888 185449813 2681 2.0689 777 974s 3 1 3 1 185449813 247137334 4391 2.6341 1311 974s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 974s 1 2108 554484 120908858 2108 0.5116 0.3382903 1.047010 974s 2 777 142693888 185449813 777 0.0973 0.9337980 1.135102 974s 3 1311 185449813 247137334 1311 0.2295 1.0147870 1.619313 974s chromosome tcnId dhId start end tcnNbrOfLoci tcnMean tcnNbrOfSNPs 974s 1 1 1 1 554484 120908858 7586 1.3853 2108 974s 2 1 2 1 142693888 185449813 2681 2.0689 777 974s 3 1 3 1 185449813 247137334 4391 2.6341 1311 974s tcnNbrOfHets dhNbrOfLoci dhMean c1Mean c2Mean 974s 1 2108 2108 0.5116 0.3382903 1.047010 974s 2 777 777 0.0973 0.9337980 1.135102 974s 3 1311 1311 0.2295 1.0147870 1.619313 974s > 974s > fit1 <- fit 974s > fit2 <- renameChromosomes(fit1, from=1, to=2) 974s > fit <- c(fit1, fit2) 974s > knownSegments <- tileChromosomes(fit)$params$knownSegments 974s > 974s > segList <- seqOfSegmentsByDP(fit, verbose=-10) 974s Identifying optimal sets of segments via dynamic programming... 974s Shifting TCN levels for every second segment... 974s Split up into non-empty independent regions... 974s Chromosome #1 ('1') of 2... 974s Number of loci on chromosome: 14658 974s Known segments on chromosome: 974s chromosome start end 974s 1 1 -Inf 120908858 974s 2 1 142693888 Inf 974s Known segment #1 of 2... 974s chromosome start end 974s 1 1 -Inf 120908858 974s Known segment #1 of 2...done 974s Known segment #2 of 2... 974s chromosome start end 974s 2 1 142693888 Inf 974s Known segment #2 of 2...done 974s Chromosome #1 ('1') of 2...done 974s Chromosome #2 ('2') of 2... 974s Number of loci on chromosome: 14658 974s Known segments on chromosome: 974s chromosome start end 974s 3 2 -Inf 120908858 974s 4 2 142693888 Inf 974s Known segment #1 of 2... 974s chromosome start end 974s 3 2 -Inf 120908858 974s Known segment #1 of 2...done 974s Known segment #2 of 2... 974s chromosome start end 974s 4 2 142693888 Inf 974s Known segment #2 of 2...done 974s Chromosome #2 ('2') of 2...done 974s Number of independent non-empty regions: 4 974s Split up into non-empty independent regions...done 974s Shift every other region... 974s Shift every other region...done 974s Merge... 974s Merge...done 974s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 974s 1 1 1 1 554484 120908858 7586 101.3853 2108 974s 2 1 2 1 142693888 185449813 2681 2.0689 777 974s 3 1 3 1 185449813 247137334 4391 2.6341 1311 974s 4 2 1 1 554484 120908858 7586 101.3853 2108 974s 5 2 2 1 142693888 185449813 2681 2.0689 777 974s 6 2 3 1 185449813 247137334 4391 2.6341 1311 974s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 974s 1 2108 554484 120908858 2108 0.511612 24.757671 76.627587 974s 2 777 142693888 185449813 777 0.097300 0.933798 1.135102 974s 3 1311 185449813 247137334 1311 0.229500 1.014787 1.619313 974s 4 2108 554484 120908858 2108 0.511612 24.757671 76.627587 974s 5 777 142693888 185449813 777 0.097300 0.933798 1.135102 974s 6 1311 185449813 247137334 1311 0.229500 1.014787 1.619313 974s Shifting TCN levels for every second segment...done 974s Extracting signals for dynamic programming... 974s CT rho 974s Min. : 0.805 Min. :0.0002 974s 1st Qu.: 2.407 1st Qu.:0.1393 974s Median :100.927 Median :0.2934 974s Mean : 53.638 Mean :0.3467 974s 3rd Qu.:101.370 3rd Qu.:0.5566 974s Max. :103.080 Max. :1.0217 974s NA's :20924 974s Extracting signals for dynamic programming...done 974s Dynamic programming... 974s Number of "DP" change points: 5 974s int [1:5] 7586 10267 14658 22244 24925 974s List of 4 974s $ jump :List of 5 974s ..$ : num 22244 974s ..$ : num [1:2] 7586 14658 974s ..$ : num [1:3] 7586 14658 22244 974s ..$ : num [1:4] 7586 10267 14658 22244 974s ..$ : num [1:5] 7586 10267 14658 22244 24925 974s $ rse : num [1:6] 71699116 47249179 35852530 5945 5410 ... 974s $ kbest: num 4 974s $ V : num [1:6, 1:6] 1114 0 0 0 0 ... 974s Dynamic programming...done 974s Excluding cases where known segments no longer correct... 974s Number of independent non-empty regions: 4 974s List of 3 974s $ : num [1:3] 7586 14658 22244 974s $ : num [1:4] 7586 10267 14658 22244 974s $ : num [1:5] 7586 10267 14658 22244 24925 974s Excluding cases where known segments no longer correct...done 974s > K <- length(segList) 974s > ks <- seq(from=1, to=K, length.out=min(5,K)) 974s > subplots(length(ks), ncol=1, byrow=TRUE) 974s List of 3 974s $ :'data.frame': 4 obs. of 3 variables: 974s ..$ chromosome: int [1:4] 1 1 2 2 974s ..$ start : num [1:4] 5.54e+05 1.43e+08 5.54e+05 1.43e+08 974s ..$ end : num [1:4] 1.21e+08 2.47e+08 1.21e+08 2.47e+08 974s $ :'data.frame': 5 obs. of 3 variables: 974s ..$ chromosome: int [1:5] 1 1 1 2 2 974s ..$ start : num [1:5] 5.54e+05 1.43e+08 1.85e+08 5.54e+05 1.43e+08 974s ..$ end : num [1:5] 1.21e+08 1.85e+08 2.47e+08 1.21e+08 2.47e+08 974s $ :'data.frame': 6 obs. of 3 variables: 974s ..$ chromosome: int [1:6] 1 1 1 2 2 2 974s ..$ start : num [1:6] 5.54e+05 1.43e+08 1.85e+08 5.54e+05 1.43e+08 ... 974s ..$ end : num [1:6] 1.21e+08 1.85e+08 2.47e+08 1.21e+08 1.85e+08 ... 974s Sequence of number of "DP" change points: 974s [1] 3 4 5 974s Sequence of number of segments: 974s [1] 4 5 6 974s Sequence of number of "discovered" change points: 974s [1] 0 1 2 974s Identifying optimal sets of segments via dynamic programming...done 974s > par(mar=c(2,1,1,1)) 974s > for (kk in ks) { 974s + knownSegmentsKK <- segList[[kk]] 974s + fitKK <- resegment(fit, knownSegments=knownSegmentsKK, undoTCN=+Inf, undoDH=+Inf) 974s + plotTracks(fitKK, tracks="tcn,c1,c2", Clim=c(0,5), add=TRUE) 974s + abline(v=c(knownSegments$start, knownSegments$end)/1e6, lty=3) 974s + stext(side=3, pos=0, sprintf("Number of segments: %d", nrow(knownSegmentsKK))) 974s + } # for (kk ...) 977s > 977s Start: segmentByPairedPSCBS.R 977s 977s R version 4.5.2 (2025-10-31) -- "[Not] Part in a Rumble" 977s Copyright (C) 2025 The R Foundation for Statistical Computing 977s Platform: powerpc64le-unknown-linux-gnu 977s 977s R is free software and comes with ABSOLUTELY NO WARRANTY. 977s You are welcome to redistribute it under certain conditions. 977s Type 'license()' or 'licence()' for distribution details. 977s 977s R is a collaborative project with many contributors. 977s Type 'contributors()' for more information and 977s 'citation()' on how to cite R or R packages in publications. 977s 977s Type 'demo()' for some demos, 'help()' for on-line help, or 977s 'help.start()' for an HTML browser interface to help. 977s Type 'q()' to quit R. 977s 977s > ########################################################### 977s > # This tests: 977s > # - segmentByPairedPSCBS(...) 977s > # - segmentByPairedPSCBS(..., knownSegments) 977s > # - tileChromosomes() 977s > # - plotTracks() 977s > ########################################################### 977s > library("PSCBS") 977s > 977s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 977s > # Load SNP microarray data 977s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 977s > data <- PSCBS::exampleData("paired.chr01") 977s PSCBS v0.68.0 (2025-04-18 19:40:02 UTC) successfully loaded. See ?PSCBS for help. 977s > 977s > 977s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 977s > # Paired PSCBS segmentation 977s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 977s > # Drop single-locus outliers 977s > dataS <- dropSegmentationOutliers(data) 977s > 977s > # Run light-weight tests by default 977s > if (Sys.getenv("_R_CHECK_FULL_") == "") { 977s + # Use only every 5th data point 977s + dataS <- dataS[seq(from=1, to=nrow(data), by=5),] 977s + # Number of segments (for assertion) 977s + nSegs <- 4L 977s + } else { 977s + # Full tests 977s + nSegs <- 11L 977s + } 977s > 977s > str(dataS) 977s 'data.frame': 14670 obs. of 6 variables: 977s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 977s $ x : int 1145994 2941694 3710825 4240737 4276892 4464544 4714611 5095111 5034491 5158416 ... 977s $ CT : num 1.63 1.4 1.41 1.17 1.16 ... 977s $ betaT : num 0.7574 0.169 0.2357 0.2604 0.0576 ... 977s $ CN : num 2.36 2.13 2.26 2.01 2.32 ... 977s $ betaN : num 0.8274 0.5072 0.1671 0.1609 0.0421 ... 977s > 977s > fig <- 1 977s > 977s > 977s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 977s > # (a) Don't segment the centromere (and force a separator) 977s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 977s > knownSegments <- data.frame( 977s + chromosome = c( 1, 1, 1), 977s + start = c( -Inf, NA, 141510003), 977s + end = c(120992603, NA, +Inf) 977s + ) 977s > 977s > 977s > # Paired PSCBS segmentation 977s > fit <- segmentByPairedPSCBS(dataS, knownSegments=knownSegments, 977s + seed=0xBEEF, verbose=-10) 977s Segmenting paired tumor-normal signals using Paired PSCBS... 977s Calling genotypes from normal allele B fractions... 977s num [1:14670] 0.8274 0.5072 0.1671 0.1609 0.0421 ... 977s Called genotypes: 977s num [1:14670] 1 0.5 0 0 0 0 1 0 1 0.5 ... 977s - attr(*, "modelFit")=List of 1 977s ..$ :List of 7 977s .. ..$ flavor : chr "density" 977s .. ..$ cn : int 2 977s .. ..$ nbrOfGenotypeGroups: int 3 977s .. ..$ tau : num [1:2] 0.315 0.677 977s .. ..$ n : int 14640 977s .. ..$ fit :Classes ‘PeaksAndValleys’ and 'data.frame': 5 obs. of 3 variables: 977s .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 977s .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 977s .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 977s .. ..$ fitValleys :Classes ‘PeaksAndValleys’ and 'data.frame': 2 obs. of 3 variables: 977s .. .. ..$ type : chr [1:2] "valley" "valley" 977s .. .. ..$ x : num [1:2] 0.315 0.677 977s .. .. ..$ density: num [1:2] 0.522 0.551 977s ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 977s muN 977s 0 0.5 1 977s 5221 4198 5251 977s Calling genotypes from normal allele B fractions...done 977s Normalizing betaT using betaN (TumorBoost)... 977s Normalized BAFs: 977s num [1:14670] 0.9301 0.1667 0.0685 0.0995 0.0155 ... 977s - attr(*, "modelFit")=List of 5 977s ..$ method : chr "normalizeTumorBoost" 977s ..$ flavor : chr "v4" 977s ..$ delta : num [1:14670] -0.17264 0.00239 0.1671 0.16085 0.04213 ... 977s .. ..- attr(*, "modelFit")=List of 1 977s .. .. ..$ :List of 7 977s .. .. .. ..$ flavor : chr "density" 977s .. .. .. ..$ cn : int 2 977s .. .. .. ..$ nbrOfGenotypeGroups: int 3 977s .. .. .. ..$ tau : num [1:2] 0.315 0.677 977s .. .. .. ..$ n : int 14640 977s .. .. .. ..$ fit :Classes ‘PeaksAndValleys’ and 'data.frame': 5 obs. of 3 variables: 977s .. .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 977s .. .. .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 977s .. .. .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 977s .. .. .. ..$ fitValleys :Classes ‘PeaksAndValleys’ and 'data.frame': 2 obs. of 3 variables: 977s .. .. .. .. ..$ type : chr [1:2] "valley" "valley" 977s .. .. .. .. ..$ x : num [1:2] 0.315 0.677 977s .. .. .. .. ..$ density: num [1:2] 0.522 0.551 977s .. .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 977s ..$ preserveScale: logi FALSE 977s ..$ scaleFactor : num NA 977s Normalizing betaT using betaN (TumorBoost)...done 977s Setup up data... 977s 'data.frame': 14670 obs. of 7 variables: 977s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 977s $ x : num 1145994 2941694 3710825 4240737 4276892 ... 977s $ CT : num 1.63 1.4 1.41 1.17 1.16 ... 977s $ betaT : num 0.7574 0.169 0.2357 0.2604 0.0576 ... 977s $ betaTN : num 0.9301 0.1667 0.0685 0.0995 0.0155 ... 977s ..- attr(*, "modelFit")=List of 5 977s .. ..$ method : chr "normalizeTumorBoost" 977s .. ..$ flavor : chr "v4" 977s .. ..$ delta : num [1:14670] -0.17264 0.00239 0.1671 0.16085 0.04213 ... 977s .. .. ..- attr(*, "modelFit")=List of 1 977s .. .. .. ..$ :List of 7 977s .. .. .. .. ..$ flavor : chr "density" 977s .. .. .. .. ..$ cn : int 2 977s .. .. .. .. ..$ nbrOfGenotypeGroups: int 3 977s .. .. .. .. ..$ tau : num [1:2] 0.315 0.677 977s .. .. .. .. ..$ n : int 14640 977s .. .. .. .. ..$ fit :Classes ‘PeaksAndValleys’ and 'data.frame': 5 obs. of 3 variables: 977s .. .. .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 977s .. .. .. .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 977s .. .. .. .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 977s .. .. .. .. ..$ fitValleys :Classes ‘PeaksAndValleys’ and 'data.frame': 2 obs. of 3 variables: 977s .. .. .. .. .. ..$ type : chr [1:2] "valley" "valley" 977s .. .. .. .. .. ..$ x : num [1:2] 0.315 0.677 977s .. .. .. .. .. ..$ density: num [1:2] 0.522 0.551 977s .. .. .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 977s .. ..$ preserveScale: logi FALSE 977s .. ..$ scaleFactor : num NA 977s $ betaN : num 0.8274 0.5072 0.1671 0.1609 0.0421 ... 977s $ muN : num 1 0.5 0 0 0 0 1 0 1 0.5 ... 977s ..- attr(*, "modelFit")=List of 1 977s .. ..$ :List of 7 977s .. .. ..$ flavor : chr "density" 977s .. .. ..$ cn : int 2 977s .. .. ..$ nbrOfGenotypeGroups: int 3 977s .. .. ..$ tau : num [1:2] 0.315 0.677 977s .. .. ..$ n : int 14640 977s .. .. ..$ fit :Classes ‘PeaksAndValleys’ and 'data.frame': 5 obs. of 3 variables: 977s .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 977s .. .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 977s .. .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 977s .. .. ..$ fitValleys :Classes ‘PeaksAndValleys’ and 'data.frame': 2 obs. of 3 variables: 977s .. .. .. ..$ type : chr [1:2] "valley" "valley" 977s .. .. .. ..$ x : num [1:2] 0.315 0.677 977s .. .. .. ..$ density: num [1:2] 0.522 0.551 977s .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 977s Setup up data...done 977s Dropping loci for which TCNs are missing... 977s Number of loci dropped: 12 977s Dropping loci for which TCNs are missing...done 977s Ordering data along genome... 977s 'data.frame': 14658 obs. of 7 variables: 977s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 977s $ x : num 554484 730720 782343 878522 916294 ... 977s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 977s $ betaT : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 977s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 977s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 977s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 977s Ordering data along genome...done 977s Keeping only current chromosome for 'knownSegments'... 977s Chromosome: 1 977s Known segments for this chromosome: 977s chromosome start end 977s 1 1 -Inf 120992603 977s 2 1 NA NA 977s 3 1 141510003 Inf 977s Keeping only current chromosome for 'knownSegments'...done 977s alphaTCN: 0.009 977s alphaDH: 0.001 977s Number of loci: 14658 977s Calculating DHs... 977s Number of SNPs: 14658 977s Number of heterozygous SNPs: 4196 (28.63%) 977s Normalized DHs: 977s num [1:14658] NA NA NA NA NA ... 977s Calculating DHs...done 977s Random seed temporarily set (seed=c(48879), kind="L'Ecuyer-CMRG") 977s Produced 2 seeds from this stream for future usage 977s Identification of change points by total copy numbers... 977s Segmenting by CBS... 977s Chromosome: 1 977s Segmenting multiple segments on current chromosome... 977s Number of segments: 3 978s Random seed temporarily set (seed=c(10407, 1066287653, -51199871, 161854402, -1995183193, 1503453565, -747102133), kind="L'Ecuyer-CMRG") 978s Produced 3 seeds from this stream for future usage 978s Segmenting by CBS... 978s Chromosome: 1 978s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 978s Segmenting by CBS...done 978s Segmenting by CBS... 978s Chromosome: 1 978s Random seed temporarily set (seed=c(10407, -1924040949, -1632234809, -437763632, -1464377300, 676654412, 2080370711), kind="L'Ecuyer-CMRG") 978s Segmenting by CBS...done 978s Segmenting multiple segments on current chromosome...done 978s Segmenting by CBS...done 978s List of 4 978s $ data :'data.frame': 14658 obs. of 4 variables: 978s ..$ chromosome: int [1:14658] 1 1 1 1 1 1 1 1 1 1 ... 978s ..$ x : num [1:14658] 554484 730720 782343 878522 916294 ... 978s ..$ y : num [1:14658] 1.88 1.8 1.59 1.64 1.53 ... 978s ..$ index : int [1:14658] 1 2 3 4 5 6 7 8 9 10 ... 978s $ output :'data.frame': 4 obs. of 6 variables: 978s ..$ sampleName: chr [1:4] NA NA NA NA 978s ..$ chromosome: int [1:4] 1 NA 1 1 978s ..$ start : num [1:4] 5.54e+05 NA 1.42e+08 1.85e+08 978s ..$ end : num [1:4] 1.21e+08 NA 1.85e+08 2.47e+08 978s ..$ nbrOfLoci : int [1:4] 7586 NA 2681 4391 978s ..$ mean : num [1:4] 1.39 NA 2.07 2.63 978s $ segRows:'data.frame': 4 obs. of 2 variables: 978s ..$ startRow: int [1:4] 1 NA 7587 10268 978s ..$ endRow : int [1:4] 7586 NA 10267 14658 978s $ params :List of 5 978s ..$ alpha : num 0.009 978s ..$ undo : num 0 978s ..$ joinSegments : logi TRUE 978s ..$ knownSegments:'data.frame': 4 obs. of 3 variables: 978s .. ..$ chromosome: num [1:4] 1 1 2 1 978s .. ..$ start : num [1:4] -Inf -Inf -Inf 1.42e+08 978s .. ..$ end : num [1:4] 1.21e+08 Inf Inf Inf 978s ..$ seed : int [1:7] 10407 1066287653 -51199871 161854402 -1995183193 1503453565 -747102133 978s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 978s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.165 0 0.165 0 0 978s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 978s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 978s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 978s Identification of change points by total copy numbers...done 978s Restructure TCN segmentation results... 978s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean 978s 1 1 554484 120992603 7586 1.3853 978s 2 NA NA NA NA NA 978s 3 1 141510003 185449813 2681 2.0689 978s 4 1 185449813 247137334 4391 2.6341 978s Number of TCN segments: 4 978s Restructure TCN segmentation results...done 978s Total CN segment #1 ([ 554484,1.20993e+08]) of 4... 978s Number of TCN loci in segment: 7586 978s Locus data for TCN segment: 978s 'data.frame': 7586 obs. of 9 variables: 978s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 978s $ x : num 554484 730720 782343 878522 916294 ... 978s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 978s $ betaT : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 978s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 978s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 978s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 978s $ index : int 1 2 3 4 5 6 7 8 9 10 ... 978s $ rho : num NA NA NA NA NA ... 978s Number of loci: 7586 978s Number of SNPs: 2108 (27.79%) 978s Number of heterozygous SNPs: 2108 (100.00%) 978s Chromosome: 1 978s Segmenting DH signals... 978s Segmenting by CBS... 978s Chromosome: 1 978s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 978s Segmenting by CBS...done 978s List of 4 978s $ data :'data.frame': 7586 obs. of 4 variables: 978s ..$ chromosome: int [1:7586] 1 1 1 1 1 1 1 1 1 1 ... 978s ..$ x : num [1:7586] 554484 730720 782343 878522 916294 ... 978s ..$ y : num [1:7586] NA NA NA NA NA ... 978s ..$ index : int [1:7586] 1 2 3 4 5 6 7 8 9 10 ... 978s $ output :'data.frame': 1 obs. of 6 variables: 978s ..$ sampleName: chr NA 978s ..$ chromosome: int 1 978s ..$ start : num 554484 978s ..$ end : num 1.21e+08 978s ..$ nbrOfLoci : int 2108 978s ..$ mean : num 0.512 978s $ segRows:'data.frame': 1 obs. of 2 variables: 978s ..$ startRow: int 10 978s ..$ endRow : int 7574 978s $ params :List of 5 978s ..$ alpha : num 0.001 978s ..$ undo : num 0 978s ..$ joinSegments : logi TRUE 978s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 978s .. ..$ chromosome: int 1 978s .. ..$ start : num 554484 978s .. ..$ end : num 1.21e+08 978s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 978s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 978s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.046 0 0.047 0 0 978s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 978s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 978s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 978s DH segmentation (locally-indexed) rows: 978s startRow endRow 978s 1 10 7574 978s int [1:7586] 1 2 3 4 5 6 7 8 9 10 ... 978s DH segmentation rows: 978s startRow endRow 978s 1 10 7574 978s Segmenting DH signals...done 978s DH segmentation table: 978s dhStart dhEnd dhNbrOfLoci dhMean 978s 1 554484 120992603 2108 0.5116 978s startRow endRow 978s 1 10 7574 978s Rows: 978s [1] 1 978s TCN segmentation rows: 978s startRow endRow 978s 1 1 7586 978s TCN and DH segmentation rows: 978s startRow endRow 978s 1 1 7586 978s startRow endRow 978s 1 10 7574 978s NULL 978s TCN segmentation (expanded) rows: 978s startRow endRow 978s 1 1 7586 978s TCN and DH segmentation rows: 978s startRow endRow 978s 1 1 7586 978s 2 NA NA 978s 3 7587 10267 978s 4 10268 14658 978s startRow endRow 978s 1 10 7574 978s startRow endRow 978s 1 1 7586 978s Total CN segmentation table (expanded): 978s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 978s 1 1 554484 120992603 7586 1.3853 2108 2108 978s (TCN,DH) segmentation for one total CN segment: 978s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 978s 1 1 1 1 554484 120992603 7586 1.3853 2108 978s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 978s 1 2108 554484 120992603 2108 0.5116 978s Total CN segment #1 ([ 554484,1.20993e+08]) of 4...done 978s Total CN segment #2 ([ NA, NA]) of 4... 978s No signals to segment. Just a "splitter" segment. Skipping. 978s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 978s NA 2 1 NA NA NA NA NA 0 978s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 978s NA 0 NA NA 0 NA 978s Total CN segment #2 ([ NA, NA]) of 4...done 978s Total CN segment #3 ([1.4151e+08,1.8545e+08]) of 4... 978s Number of TCN loci in segment: 2681 978s Locus data for TCN segment: 978s 'data.frame': 2681 obs. of 9 variables: 978s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 978s $ x : num 1.43e+08 1.43e+08 1.43e+08 1.43e+08 1.44e+08 ... 978s $ CT : num 2.27 1.55 1.47 1.5 1.81 ... 978s $ betaT : num 0.34 0.55 0.048 0.813 0.575 ... 978s $ betaTN : num 0.441 0.629 -0.05 0.958 0.872 ... 978s $ betaN : num 0.3851 0.3933 0.0981 0.8552 0.7028 ... 978s $ muN : num 0.5 0.5 0 1 1 1 1 0.5 1 1 ... 978s $ index : int 7587 7588 7589 7590 7591 7592 7593 7594 7595 7596 ... 978s $ rho : num 0.117 0.258 NA NA NA ... 978s Number of loci: 2681 978s Number of SNPs: 777 (28.98%) 978s Number of heterozygous SNPs: 777 (100.00%) 978s Chromosome: 1 978s Segmenting DH signals... 978s Segmenting by CBS... 978s Chromosome: 1 978s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 978s Segmenting by CBS...done 978s List of 4 978s $ data :'data.frame': 2681 obs. of 4 variables: 978s ..$ chromosome: int [1:2681] 1 1 1 1 1 1 1 1 1 1 ... 978s ..$ x : num [1:2681] 1.43e+08 1.43e+08 1.43e+08 1.43e+08 1.44e+08 ... 978s ..$ y : num [1:2681] 0.117 0.258 NA NA NA ... 978s ..$ index : int [1:2681] 1 2 3 4 5 6 7 8 9 10 ... 978s $ output :'data.frame': 1 obs. of 6 variables: 978s ..$ sampleName: chr NA 978s ..$ chromosome: int 1 978s ..$ start : num 1.42e+08 978s ..$ end : num 1.85e+08 978s ..$ nbrOfLoci : int 777 978s ..$ mean : num 0.0973 978s $ segRows:'data.frame': 1 obs. of 2 variables: 978s ..$ startRow: int 1 978s ..$ endRow : int 2677 978s $ params :List of 5 978s ..$ alpha : num 0.001 978s ..$ undo : num 0 978s ..$ joinSegments : logi TRUE 978s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 978s .. ..$ chromosome: int 1 978s .. ..$ start : num 1.42e+08 978s .. ..$ end : num 1.85e+08 978s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 978s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 978s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.01 0 0.009 0 0 978s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 978s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 978s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 978s DH segmentation (locally-indexed) rows: 978s startRow endRow 978s 1 1 2677 978s int [1:2681] 7587 7588 7589 7590 7591 7592 7593 7594 7595 7596 ... 978s DH segmentation rows: 978s startRow endRow 978s 1 7587 10263 978s Segmenting DH signals...done 978s DH segmentation table: 978s dhStart dhEnd dhNbrOfLoci dhMean 978s 1 141510003 185449813 777 0.0973 978s startRow endRow 978s 1 7587 10263 978s Rows: 978s [1] 3 978s TCN segmentation rows: 978s startRow endRow 978s 3 7587 10267 978s TCN and DH segmentation rows: 978s startRow endRow 978s 3 7587 10267 978s startRow endRow 978s 1 7587 10263 978s startRow endRow 978s 1 1 7586 978s NA NA NA 978s TCN segmentation (expanded) rows: 978s startRow endRow 978s 1 1 7586 978s NA NA NA 978s 3 7587 10267 978s TCN and DH segmentation rows: 978s startRow endRow 978s 1 1 7586 978s 2 NA NA 978s 3 7587 10267 978s 4 10268 14658 978s startRow endRow 978s 1 10 7574 978s 2 NA NA 978s 3 7587 10263 978s startRow endRow 978s 1 1 7586 978s 2 NA NA 978s 3 7587 10267 978s Total CN segmentation table (expanded): 978s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 978s 3 1 141510003 185449813 2681 2.0689 777 777 978s (TCN,DH) segmentation for one total CN segment: 978s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 978s 3 3 1 1 141510003 185449813 2681 2.0689 777 978s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 978s 3 777 141510003 185449813 777 0.0973 978s Total CN segment #3 ([1.4151e+08,1.8545e+08]) of 4...done 978s Total CN segment #4 ([1.8545e+08,2.47137e+08]) of 4... 978s Number of TCN loci in segment: 4391 978s Locus data for TCN segment: 978s 'data.frame': 4391 obs. of 9 variables: 978s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 978s $ x : num 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 978s $ CT : num 2.93 2.15 2.82 2.93 2.46 ... 978s $ betaT : num 0.0811 0.5154 0.9473 0.3734 0.7506 ... 978s $ betaTN : num -0.169 0.609 1.028 0.525 0.968 ... 978s $ betaN : num 0.25 0.38 0.919 0.34 0.783 ... 978s $ muN : num 0 0.5 1 0.5 1 1 0 1 0 1 ... 978s $ index : int 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 978s $ rho : num NA 0.2186 NA 0.0503 NA ... 978s Number of loci: 4391 978s Number of SNPs: 1311 (29.86%) 978s Number of heterozygous SNPs: 1311 (100.00%) 978s Chromosome: 1 978s Segmenting DH signals... 978s Segmenting by CBS... 978s Chromosome: 1 978s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 978s Segmenting by CBS...done 978s List of 4 978s $ data :'data.frame': 4391 obs. of 4 variables: 978s ..$ chromosome: int [1:4391] 1 1 1 1 1 1 1 1 1 1 ... 978s ..$ x : num [1:4391] 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 978s ..$ y : num [1:4391] NA 0.2186 NA 0.0503 NA ... 978s ..$ index : int [1:4391] 1 2 3 4 5 6 7 8 9 10 ... 978s $ output :'data.frame': 1 obs. of 6 variables: 978s ..$ sampleName: chr NA 978s ..$ chromosome: int 1 978s ..$ start : num 1.85e+08 978s ..$ end : num 2.47e+08 978s ..$ nbrOfLoci : int 1311 978s ..$ mean : num 0.23 978s $ segRows:'data.frame': 1 obs. of 2 variables: 978s ..$ startRow: int 2 978s ..$ endRow : int 4388 978s $ params :List of 5 978s ..$ alpha : num 0.001 978s ..$ undo : num 0 978s ..$ joinSegments : logi TRUE 978s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 978s .. ..$ chromosome: int 1 978s .. ..$ start : num 1.85e+08 978s .. ..$ end : num 2.47e+08 978s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 978s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 978s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.017 0 0.018 0 0 978s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 978s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 978s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 978s DH segmentation (locally-indexed) rows: 978s startRow endRow 978s 1 2 4388 978s int [1:4391] 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 978s DH segmentation rows: 978s startRow endRow 978s 1 10269 14655 978s Segmenting DH signals...done 978s DH segmentation table: 978s dhStart dhEnd dhNbrOfLoci dhMean 978s 1 185449813 247137334 1311 0.2295 978s startRow endRow 978s 1 10269 14655 978s Rows: 978s [1] 4 978s TCN segmentation rows: 978s startRow endRow 978s 4 10268 14658 978s TCN and DH segmentation rows: 978s startRow endRow 978s 4 10268 14658 978s startRow endRow 978s 1 10269 14655 978s startRow endRow 978s 1 1 7586 978s 2 NA NA 978s 3 7587 10267 978s TCN segmentation (expanded) rows: 979s startRow endRow 979s 1 1 7586 979s 2 NA NA 979s 3 7587 10267 979s 4 10268 14658 979s TCN and DH segmentation rows: 979s startRow endRow 979s 1 1 7586 979s 2 NA NA 979s 3 7587 10267 979s 4 10268 14658 979s startRow endRow 979s 1 10 7574 979s 2 NA NA 979s 3 7587 10263 979s 4 10269 14655 979s startRow endRow 979s 1 1 7586 979s 2 NA NA 979s 3 7587 10267 979s 4 10268 14658 979s Total CN segmentation table (expanded): 979s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 979s 4 1 185449813 247137334 4391 2.6341 1311 1311 979s (TCN,DH) segmentation for one total CN segment: 979s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 979s 4 4 1 1 185449813 247137334 4391 2.6341 1311 979s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 979s 4 1311 185449813 247137334 1311 0.2295 979s Total CN segment #4 ([1.8545e+08,2.47137e+08]) of 4...done 979s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 979s 1 1 1 1 554484 120992603 7586 1.3853 2108 979s 2 NA 2 1 NA NA NA NA 0 979s 3 1 3 1 141510003 185449813 2681 2.0689 777 979s 4 1 4 1 185449813 247137334 4391 2.6341 1311 979s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 979s 1 2108 554484 120992603 2108 0.5116 979s 2 0 NA NA 0 NA 979s 3 777 141510003 185449813 777 0.0973 979s 4 1311 185449813 247137334 1311 0.2295 979s Calculating (C1,C2) per segment... 979s Calculating (C1,C2) per segment...done 979s Number of segments: 4 979s Segmenting paired tumor-normal signals using Paired PSCBS...done 979s Post-segmenting TCNs... 979s Number of segments: 3 979s Number of chromosomes: 1 979s [1] 1 979s Chromosome 1 ('chr01') of 1... 979s Rows: 979s [1] 1 2 3 979s Number of segments: 3 979s TCN segment #1 ('1') of 3... 979s Nothing todo. Only one DH segmentation. Skipping. 979s TCN segment #1 ('1') of 3...done 979s TCN segment #2 ('3') of 3... 979s Nothing todo. Only one DH segmentation. Skipping. 979s TCN segment #2 ('3') of 3...done 979s TCN segment #3 ('4') of 3... 979s Nothing todo. Only one DH segmentation. Skipping. 979s TCN segment #3 ('4') of 3...done 979s Chromosome 1 ('chr01') of 1...done 979s Update (C1,C2) per segment... 979s Update (C1,C2) per segment...done 979s Post-segmenting TCNs...done 979s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 979s 1 1 1 1 554484 120992603 7586 1.3853 2108 979s 2 NA 2 1 NA NA NA NA 0 979s 3 1 3 1 141510003 185449813 2681 2.0689 777 979s 4 1 4 1 185449813 247137334 4391 2.6341 1311 979s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 979s 1 2108 554484 120992603 2108 0.5116 0.3382903 1.047010 979s 2 0 NA NA 0 NA NA NA 979s 3 777 141510003 185449813 777 0.0973 0.9337980 1.135102 979s 4 1311 185449813 247137334 1311 0.2295 1.0147870 1.619313 979s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 979s 1 1 1 1 554484 120992603 7586 1.3853 2108 979s 2 NA 2 1 NA NA NA NA 0 979s 3 1 3 1 141510003 185449813 2681 2.0689 777 979s 4 1 4 1 185449813 247137334 4391 2.6341 1311 979s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 979s 1 2108 554484 120992603 2108 0.5116 0.3382903 1.047010 979s 2 0 NA NA 0 NA NA NA 979s 3 777 141510003 185449813 777 0.0973 0.9337980 1.135102 979s 4 1311 185449813 247137334 1311 0.2295 1.0147870 1.619313 979s > print(fit) 979s chromosome tcnId dhId start end tcnNbrOfLoci tcnMean tcnNbrOfSNPs 979s 1 1 1 1 554484 120992603 7586 1.3853 2108 979s 2 NA 2 1 NA NA NA NA 0 979s 3 1 3 1 141510003 185449813 2681 2.0689 777 979s 4 1 4 1 185449813 247137334 4391 2.6341 1311 979s tcnNbrOfHets dhNbrOfLoci dhMean c1Mean c2Mean 979s 1 2108 2108 0.5116 0.3382903 1.047010 979s 2 0 0 NA NA NA 979s 3 777 777 0.0973 0.9337980 1.135102 979s 4 1311 1311 0.2295 1.0147870 1.619313 979s > 979s > # Plot results 979s > dev.set(2L) 979s null device 979s 1 979s > plotTracks(fit) 979s > abline(v=c(knownSegments$start, knownSegments$end)/1e6, lty=3) 979s > 979s > # Sanity check 979s > stopifnot(nbrOfSegments(fit) == nSegs) 979s > 979s > fit1 <- fit 979s > 979s > 979s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 979s > # (b) Segment also the centromere (which will become NAs) 979s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 979s > knownSegments <- data.frame( 979s + chromosome = c( 1, 1, 1), 979s + start = c( -Inf, 120992604, 141510003), 979s + end = c(120992603, 141510002, +Inf) 979s + ) 979s > 979s > 979s > # Paired PSCBS segmentation 979s > fit <- segmentByPairedPSCBS(dataS, knownSegments=knownSegments, 979s + seed=0xBEEF, verbose=-10) 979s Segmenting paired tumor-normal signals using Paired PSCBS... 979s Calling genotypes from normal allele B fractions... 979s num [1:14670] 0.8274 0.5072 0.1671 0.1609 0.0421 ... 979s Called genotypes: 979s num [1:14670] 1 0.5 0 0 0 0 1 0 1 0.5 ... 979s - attr(*, "modelFit")=List of 1 979s ..$ :List of 7 979s .. ..$ flavor : chr "density" 979s .. ..$ cn : int 2 979s .. ..$ nbrOfGenotypeGroups: int 3 979s .. ..$ tau : num [1:2] 0.315 0.677 979s .. ..$ n : int 14640 979s .. ..$ fit :Classes ‘PeaksAndValleys’ and 'data.frame': 5 obs. of 3 variables: 979s .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 979s .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 979s .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 979s .. ..$ fitValleys :Classes ‘PeaksAndValleys’ and 'data.frame': 2 obs. of 3 variables: 979s .. .. ..$ type : chr [1:2] "valley" "valley" 979s .. .. ..$ x : num [1:2] 0.315 0.677 979s .. .. ..$ density: num [1:2] 0.522 0.551 979s ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 979s muN 979s 0 0.5 1 979s 5221 4198 5251 979s Calling genotypes from normal allele B fractions...done 979s Normalizing betaT using betaN (TumorBoost)... 979s Normalized BAFs: 979s num [1:14670] 0.9301 0.1667 0.0685 0.0995 0.0155 ... 979s - attr(*, "modelFit")=List of 5 979s ..$ method : chr "normalizeTumorBoost" 979s ..$ flavor : chr "v4" 979s ..$ delta : num [1:14670] -0.17264 0.00239 0.1671 0.16085 0.04213 ... 979s .. ..- attr(*, "modelFit")=List of 1 979s .. .. ..$ :List of 7 979s .. .. .. ..$ flavor : chr "density" 979s .. .. .. ..$ cn : int 2 979s .. .. .. ..$ nbrOfGenotypeGroups: int 3 979s .. .. .. ..$ tau : num [1:2] 0.315 0.677 979s .. .. .. ..$ n : int 14640 979s .. .. .. ..$ fit :Classes ‘PeaksAndValleys’ and 'data.frame': 5 obs. of 3 variables: 979s .. .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 979s .. .. .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 979s .. .. .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 979s .. .. .. ..$ fitValleys :Classes ‘PeaksAndValleys’ and 'data.frame': 2 obs. of 3 variables: 979s .. .. .. .. ..$ type : chr [1:2] "valley" "valley" 979s .. .. .. .. ..$ x : num [1:2] 0.315 0.677 979s .. .. .. .. ..$ density: num [1:2] 0.522 0.551 979s .. .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 979s ..$ preserveScale: logi FALSE 979s ..$ scaleFactor : num NA 979s Normalizing betaT using betaN (TumorBoost)...done 979s Setup up data... 979s 'data.frame': 14670 obs. of 7 variables: 979s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 979s $ x : num 1145994 2941694 3710825 4240737 4276892 ... 979s $ CT : num 1.63 1.4 1.41 1.17 1.16 ... 979s $ betaT : num 0.7574 0.169 0.2357 0.2604 0.0576 ... 979s $ betaTN : num 0.9301 0.1667 0.0685 0.0995 0.0155 ... 979s ..- attr(*, "modelFit")=List of 5 979s .. ..$ method : chr "normalizeTumorBoost" 979s .. ..$ flavor : chr "v4" 979s .. ..$ delta : num [1:14670] -0.17264 0.00239 0.1671 0.16085 0.04213 ... 979s .. .. ..- attr(*, "modelFit")=List of 1 979s .. .. .. ..$ :List of 7 979s .. .. .. .. ..$ flavor : chr "density" 979s .. .. .. .. ..$ cn : int 2 979s .. .. .. .. ..$ nbrOfGenotypeGroups: int 3 979s .. .. .. .. ..$ tau : num [1:2] 0.315 0.677 979s .. .. .. .. ..$ n : int 14640 979s .. .. .. .. ..$ fit :Classes ‘PeaksAndValleys’ and 'data.frame': 5 obs. of 3 variables: 979s .. .. .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 979s .. .. .. .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 979s .. .. .. .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 979s .. .. .. .. ..$ fitValleys :Classes ‘PeaksAndValleys’ and 'data.frame': 2 obs. of 3 variables: 979s .. .. .. .. .. ..$ type : chr [1:2] "valley" "valley" 979s .. .. .. .. .. ..$ x : num [1:2] 0.315 0.677 979s .. .. .. .. .. ..$ density: num [1:2] 0.522 0.551 979s .. .. .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 979s .. ..$ preserveScale: logi FALSE 979s .. ..$ scaleFactor : num NA 979s $ betaN : num 0.8274 0.5072 0.1671 0.1609 0.0421 ... 979s $ muN : num 1 0.5 0 0 0 0 1 0 1 0.5 ... 979s ..- attr(*, "modelFit")=List of 1 979s .. ..$ :List of 7 979s .. .. ..$ flavor : chr "density" 979s .. .. ..$ cn : int 2 979s .. .. ..$ nbrOfGenotypeGroups: int 3 979s .. .. ..$ tau : num [1:2] 0.315 0.677 979s .. .. ..$ n : int 14640 979s .. .. ..$ fit :Classes ‘PeaksAndValleys’ and 'data.frame': 5 obs. of 3 variables: 979s .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 979s .. .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 979s .. .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 979s .. .. ..$ fitValleys :Classes ‘PeaksAndValleys’ and 'data.frame': 2 obs. of 3 variables: 979s .. .. .. ..$ type : chr [1:2] "valley" "valley" 979s .. .. .. ..$ x : num [1:2] 0.315 0.677 979s .. .. .. ..$ density: num [1:2] 0.522 0.551 979s .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 979s Setup up data...done 979s Dropping loci for which TCNs are missing... 979s Number of loci dropped: 12 979s Dropping loci for which TCNs are missing...done 979s Ordering data along genome... 979s 'data.frame': 14658 obs. of 7 variables: 979s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 979s $ x : num 554484 730720 782343 878522 916294 ... 979s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 979s $ betaT : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 979s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 979s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 979s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 979s Ordering data along genome...done 979s Keeping only current chromosome for 'knownSegments'... 979s Chromosome: 1 979s Known segments for this chromosome: 979s chromosome start end 979s 1 1 -Inf 120992603 979s 2 1 120992604 141510002 979s 3 1 141510003 Inf 979s Keeping only current chromosome for 'knownSegments'...done 979s alphaTCN: 0.009 979s alphaDH: 0.001 979s Number of loci: 14658 979s Calculating DHs... 979s Number of SNPs: 14658 979s Number of heterozygous SNPs: 4196 (28.63%) 979s Normalized DHs: 979s num [1:14658] NA NA NA NA NA ... 979s Calculating DHs...done 979s Random seed temporarily set (seed=c(48879), kind="L'Ecuyer-CMRG") 979s Produced 2 seeds from this stream for future usage 979s Identification of change points by total copy numbers... 979s Segmenting by CBS... 979s Chromosome: 1 979s Segmenting multiple segments on current chromosome... 979s Number of segments: 3 979s Random seed temporarily set (seed=c(10407, 1066287653, -51199871, 161854402, -1995183193, 1503453565, -747102133), kind="L'Ecuyer-CMRG") 979s Produced 3 seeds from this stream for future usage 979s Segmenting by CBS... 979s Chromosome: 1 979s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 979s Segmenting by CBS...done 979s Segmenting by CBS... 979s Chromosome: 1 979s Random seed temporarily set (seed=c(10407, -1924040949, -1632234809, -437763632, -1464377300, 676654412, 2080370711), kind="L'Ecuyer-CMRG") 980s Segmenting by CBS...done 980s Segmenting multiple segments on current chromosome...done 980s Segmenting by CBS...done 980s List of 4 980s $ data :'data.frame': 14658 obs. of 4 variables: 980s ..$ chromosome: int [1:14658] 1 1 1 1 1 1 1 1 1 1 ... 980s ..$ x : num [1:14658] 554484 730720 782343 878522 916294 ... 980s ..$ y : num [1:14658] 1.88 1.8 1.59 1.64 1.53 ... 980s ..$ index : int [1:14658] 1 2 3 4 5 6 7 8 9 10 ... 980s $ output :'data.frame': 4 obs. of 6 variables: 980s ..$ sampleName: chr [1:4] NA NA NA NA 980s ..$ chromosome: num [1:4] 1 1 1 1 980s ..$ start : num [1:4] 5.54e+05 1.21e+08 1.42e+08 1.85e+08 980s ..$ end : num [1:4] 1.21e+08 1.42e+08 1.85e+08 2.47e+08 980s ..$ nbrOfLoci : int [1:4] 7586 0 2681 4391 980s ..$ mean : num [1:4] 1.39 NA 2.07 2.63 980s $ segRows:'data.frame': 4 obs. of 2 variables: 980s ..$ startRow: int [1:4] 1 NA 7587 10268 980s ..$ endRow : int [1:4] 7586 NA 10267 14658 980s $ params :List of 5 980s ..$ alpha : num 0.009 980s ..$ undo : num 0 980s ..$ joinSegments : logi TRUE 980s ..$ knownSegments:'data.frame': 4 obs. of 3 variables: 980s .. ..$ chromosome: num [1:4] 1 1 2 1 980s .. ..$ start : num [1:4] -Inf -Inf -Inf 1.42e+08 980s .. ..$ end : num [1:4] 1.21e+08 Inf Inf Inf 980s ..$ seed : int [1:7] 10407 1066287653 -51199871 161854402 -1995183193 1503453565 -747102133 980s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 980s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.164 0 0.164 0 0 980s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 980s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 980s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 980s Identification of change points by total copy numbers...done 980s Restructure TCN segmentation results... 980s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean 980s 1 1 554484 120992603 7586 1.3853 980s 2 1 120992604 141510002 0 NA 980s 3 1 141510003 185449813 2681 2.0689 980s 4 1 185449813 247137334 4391 2.6341 980s Number of TCN segments: 4 980s Restructure TCN segmentation results...done 980s Total CN segment #1 ([ 554484,1.20993e+08]) of 4... 980s Number of TCN loci in segment: 7586 980s Locus data for TCN segment: 980s 'data.frame': 7586 obs. of 9 variables: 980s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 980s $ x : num 554484 730720 782343 878522 916294 ... 980s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 980s $ betaT : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 980s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 980s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 980s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 980s $ index : int 1 2 3 4 5 6 7 8 9 10 ... 980s $ rho : num NA NA NA NA NA ... 980s Number of loci: 7586 980s Number of SNPs: 2108 (27.79%) 980s Number of heterozygous SNPs: 2108 (100.00%) 980s Chromosome: 1 980s Segmenting DH signals... 980s Segmenting by CBS... 980s Chromosome: 1 980s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 980s Segmenting by CBS...done 980s List of 4 980s $ data :'data.frame': 7586 obs. of 4 variables: 980s ..$ chromosome: int [1:7586] 1 1 1 1 1 1 1 1 1 1 ... 980s ..$ x : num [1:7586] 554484 730720 782343 878522 916294 ... 980s ..$ y : num [1:7586] NA NA NA NA NA ... 980s ..$ index : int [1:7586] 1 2 3 4 5 6 7 8 9 10 ... 980s $ output :'data.frame': 1 obs. of 6 variables: 980s ..$ sampleName: chr NA 980s ..$ chromosome: int 1 980s ..$ start : num 554484 980s ..$ end : num 1.21e+08 980s ..$ nbrOfLoci : int 2108 980s ..$ mean : num 0.512 980s $ segRows:'data.frame': 1 obs. of 2 variables: 980s ..$ startRow: int 10 980s ..$ endRow : int 7574 980s $ params :List of 5 980s ..$ alpha : num 0.001 980s ..$ undo : num 0 980s ..$ joinSegments : logi TRUE 980s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 980s .. ..$ chromosome: int 1 980s .. ..$ start : num 554484 980s .. ..$ end : num 1.21e+08 980s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 980s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 980s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.046 0 0.046 0 0 980s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 980s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 980s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 980s DH segmentation (locally-indexed) rows: 980s startRow endRow 980s 1 10 7574 980s int [1:7586] 1 2 3 4 5 6 7 8 9 10 ... 980s DH segmentation rows: 980s startRow endRow 980s 1 10 7574 980s Segmenting DH signals...done 980s DH segmentation table: 980s dhStart dhEnd dhNbrOfLoci dhMean 980s 1 554484 120992603 2108 0.5116 980s startRow endRow 980s 1 10 7574 980s Rows: 980s [1] 1 980s TCN segmentation rows: 980s startRow endRow 980s 1 1 7586 980s TCN and DH segmentation rows: 980s startRow endRow 980s 1 1 7586 980s startRow endRow 980s 1 10 7574 980s NULL 980s TCN segmentation (expanded) rows: 980s startRow endRow 980s 1 1 7586 980s TCN and DH segmentation rows: 980s startRow endRow 980s 1 1 7586 980s 2 NA NA 980s 3 7587 10267 980s 4 10268 14658 980s startRow endRow 980s 1 10 7574 980s startRow endRow 980s 1 1 7586 980s Total CN segmentation table (expanded): 980s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 980s 1 1 554484 120992603 7586 1.3853 2108 2108 980s (TCN,DH) segmentation for one total CN segment: 980s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 980s 1 1 1 1 554484 120992603 7586 1.3853 2108 980s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 980s 1 2108 554484 120992603 2108 0.5116 980s Total CN segment #1 ([ 554484,1.20993e+08]) of 4...done 980s Total CN segment #2 ([1.20993e+08,1.4151e+08]) of 4... 980s Number of TCN loci in segment: 0 980s Locus data for TCN segment: 980s 'data.frame': 0 obs. of 9 variables: 980s $ chromosome: int 980s $ x : num 980s $ CT : num 980s $ betaT : num 980s $ betaTN : num 980s $ betaN : num 980s $ muN : num 980s $ index : int 980s $ rho : num 980s Number of loci: 0 980s Number of SNPs: 0 (NaN%) 980s Number of heterozygous SNPs: 0 (NaN%) 980s Chromosome: 1 980s Segmenting DH signals... 980s Segmenting by CBS... 980s Chromosome: NA 980s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 980s Segmenting by CBS...done 980s List of 4 980s $ data :'data.frame': 0 obs. of 4 variables: 980s ..$ chromosome: int(0) 980s ..$ x : num(0) 980s ..$ y : num(0) 980s ..$ index : int(0) 980s $ output :'data.frame': 0 obs. of 6 variables: 980s ..$ sampleName: chr(0) 980s ..$ chromosome: num(0) 980s ..$ start : num(0) 980s ..$ end : num(0) 980s ..$ nbrOfLoci : int(0) 980s ..$ mean : num(0) 980s $ segRows:'data.frame': 0 obs. of 2 variables: 980s ..$ startRow: int(0) 980s ..$ endRow : int(0) 980s $ params :List of 5 980s ..$ alpha : num 0.001 980s ..$ undo : num 0 980s ..$ joinSegments : logi TRUE 980s ..$ knownSegments:'data.frame': 0 obs. of 3 variables: 980s .. ..$ chromosome: int(0) 980s .. ..$ start : num(0) 980s .. ..$ end : num(0) 980s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 980s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 980s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.002 0 0.002 0 0 980s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 980s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 980s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 980s DH segmentation (locally-indexed) rows: 980s [1] startRow endRow 980s <0 rows> (or 0-length row.names) 980s int(0) 980s DH segmentation rows: 980s [1] startRow endRow 980s <0 rows> (or 0-length row.names) 980s Segmenting DH signals...done 980s DH segmentation table: 980s dhStart dhEnd dhNbrOfLoci dhMean 980s NA NA NA NA NA 980s startRow endRow 980s NA NA NA 980s Rows: 980s [1] 2 980s TCN segmentation rows: 980s startRow endRow 980s 2 NA NA 980s TCN and DH segmentation rows: 980s startRow endRow 980s 2 NA NA 980s startRow endRow 980s NA NA NA 980s startRow endRow 980s 1 1 7586 980s TCN segmentation (expanded) rows: 980s startRow endRow 980s 1 1 7586 980s 2 NA NA 980s TCN and DH segmentation rows: 980s startRow endRow 980s 1 1 7586 980s 2 NA NA 980s 3 7587 10267 980s 4 10268 14658 980s startRow endRow 980s 1 10 7574 980s 2 NA NA 980s startRow endRow 980s 1 1 7586 980s 2 NA NA 980s Total CN segmentation table (expanded): 980s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 980s 2 1 120992604 141510002 0 NA 0 0 980s (TCN,DH) segmentation for one total CN segment: 980s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 980s 2 2 1 1 120992604 141510002 0 NA 0 980s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 980s 2 0 NA NA NA NA 980s Total CN segment #2 ([1.20993e+08,1.4151e+08]) of 4...done 980s Total CN segment #3 ([1.4151e+08,1.8545e+08]) of 4... 980s Number of TCN loci in segment: 2681 980s Locus data for TCN segment: 980s 'data.frame': 2681 obs. of 9 variables: 980s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 980s $ x : num 1.43e+08 1.43e+08 1.43e+08 1.43e+08 1.44e+08 ... 980s $ CT : num 2.27 1.55 1.47 1.5 1.81 ... 980s $ betaT : num 0.34 0.55 0.048 0.813 0.575 ... 980s $ betaTN : num 0.441 0.629 -0.05 0.958 0.872 ... 980s $ betaN : num 0.3851 0.3933 0.0981 0.8552 0.7028 ... 980s $ muN : num 0.5 0.5 0 1 1 1 1 0.5 1 1 ... 980s $ index : int 7587 7588 7589 7590 7591 7592 7593 7594 7595 7596 ... 980s $ rho : num 0.117 0.258 NA NA NA ... 980s Number of loci: 2681 980s Number of SNPs: 777 (28.98%) 980s Number of heterozygous SNPs: 777 (100.00%) 980s Chromosome: 1 980s Segmenting DH signals... 980s Segmenting by CBS... 980s Chromosome: 1 980s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 980s Segmenting by CBS...done 980s List of 4 980s $ data :'data.frame': 2681 obs. of 4 variables: 980s ..$ chromosome: int [1:2681] 1 1 1 1 1 1 1 1 1 1 ... 980s ..$ x : num [1:2681] 1.43e+08 1.43e+08 1.43e+08 1.43e+08 1.44e+08 ... 980s ..$ y : num [1:2681] 0.117 0.258 NA NA NA ... 980s ..$ index : int [1:2681] 1 2 3 4 5 6 7 8 9 10 ... 980s $ output :'data.frame': 1 obs. of 6 variables: 980s ..$ sampleName: chr NA 980s ..$ chromosome: int 1 980s ..$ start : num 1.42e+08 980s ..$ end : num 1.85e+08 980s ..$ nbrOfLoci : int 777 980s ..$ mean : num 0.0973 980s $ segRows:'data.frame': 1 obs. of 2 variables: 980s ..$ startRow: int 1 980s ..$ endRow : int 2677 980s $ params :List of 5 980s ..$ alpha : num 0.001 980s ..$ undo : num 0 980s ..$ joinSegments : logi TRUE 980s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 980s .. ..$ chromosome: int 1 980s .. ..$ start : num 1.42e+08 980s .. ..$ end : num 1.85e+08 980s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 980s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 980s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.009 0 0.01 0 0 980s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 980s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 980s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 980s DH segmentation (locally-indexed) rows: 980s startRow endRow 980s 1 1 2677 980s int [1:2681] 7587 7588 7589 7590 7591 7592 7593 7594 7595 7596 ... 980s DH segmentation rows: 980s startRow endRow 980s 1 7587 10263 980s Segmenting DH signals...done 980s DH segmentation table: 980s dhStart dhEnd dhNbrOfLoci dhMean 980s 1 141510003 185449813 777 0.0973 980s startRow endRow 980s 1 7587 10263 980s Rows: 980s [1] 3 980s TCN segmentation rows: 980s startRow endRow 980s 3 7587 10267 980s TCN and DH segmentation rows: 980s startRow endRow 980s 3 7587 10267 980s startRow endRow 980s 1 7587 10263 980s startRow endRow 980s 1 1 7586 980s 2 NA NA 980s TCN segmentation (expanded) rows: 980s startRow endRow 980s 1 1 7586 980s 2 NA NA 980s 3 7587 10267 980s TCN and DH segmentation rows: 980s startRow endRow 980s 1 1 7586 980s 2 NA NA 980s 3 7587 10267 980s 4 10268 14658 980s startRow endRow 980s 1 10 7574 980s 2 NA NA 980s 3 7587 10263 980s startRow endRow 980s 1 1 7586 980s 2 NA NA 980s 3 7587 10267 980s Total CN segmentation table (expanded): 980s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 980s 3 1 141510003 185449813 2681 2.0689 777 777 980s (TCN,DH) segmentation for one total CN segment: 980s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 980s 3 3 1 1 141510003 185449813 2681 2.0689 777 980s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 980s 3 777 141510003 185449813 777 0.0973 980s Total CN segment #3 ([1.4151e+08,1.8545e+08]) of 4...done 980s Total CN segment #4 ([1.8545e+08,2.47137e+08]) of 4... 980s Number of TCN loci in segment: 4391 980s Locus data for TCN segment: 980s 'data.frame': 4391 obs. of 9 variables: 980s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 980s $ x : num 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 980s $ CT : num 2.93 2.15 2.82 2.93 2.46 ... 980s $ betaT : num 0.0811 0.5154 0.9473 0.3734 0.7506 ... 980s $ betaTN : num -0.169 0.609 1.028 0.525 0.968 ... 980s $ betaN : num 0.25 0.38 0.919 0.34 0.783 ... 980s $ muN : num 0 0.5 1 0.5 1 1 0 1 0 1 ... 980s $ index : int 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 980s $ rho : num NA 0.2186 NA 0.0503 NA ... 980s Number of loci: 4391 980s Number of SNPs: 1311 (29.86%) 980s Number of heterozygous SNPs: 1311 (100.00%) 980s Chromosome: 1 980s Segmenting DH signals... 980s Segmenting by CBS... 980s Chromosome: 1 980s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 980s Segmenting by CBS...done 980s List of 4 980s $ data :'data.frame': 4391 obs. of 4 variables: 980s ..$ chromosome: int [1:4391] 1 1 1 1 1 1 1 1 1 1 ... 980s ..$ x : num [1:4391] 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 980s ..$ y : num [1:4391] NA 0.2186 NA 0.0503 NA ... 980s ..$ index : int [1:4391] 1 2 3 4 5 6 7 8 9 10 ... 980s $ output :'data.frame': 1 obs. of 6 variables: 980s ..$ sampleName: chr NA 980s ..$ chromosome: int 1 980s ..$ start : num 1.85e+08 980s ..$ end : num 2.47e+08 980s ..$ nbrOfLoci : int 1311 980s ..$ mean : num 0.23 980s $ segRows:'data.frame': 1 obs. of 2 variables: 980s ..$ startRow: int 2 980s ..$ endRow : int 4388 980s $ params :List of 5 980s ..$ alpha : num 0.001 980s ..$ undo : num 0 980s ..$ joinSegments : logi TRUE 980s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 980s .. ..$ chromosome: int 1 980s .. ..$ start : num 1.85e+08 980s .. ..$ end : num 2.47e+08 980s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 980s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 980s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.018 0 0.018 0 0 980s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 980s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 980s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 980s DH segmentation (locally-indexed) rows: 980s startRow endRow 980s 1 2 4388 980s int [1:4391] 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 980s DH segmentation rows: 980s startRow endRow 980s 1 10269 14655 980s Segmenting DH signals...done 980s DH segmentation table: 980s dhStart dhEnd dhNbrOfLoci dhMean 980s 1 185449813 247137334 1311 0.2295 980s startRow endRow 980s 1 10269 14655 980s Rows: 980s [1] 4 980s TCN segmentation rows: 980s startRow endRow 980s 4 10268 14658 980s TCN and DH segmentation rows: 980s startRow endRow 980s 4 10268 14658 980s startRow endRow 980s 1 10269 14655 980s startRow endRow 980s 1 1 7586 980s 2 NA NA 980s 3 7587 10267 980s TCN segmentation (expanded) rows: 980s startRow endRow 980s 1 1 7586 980s 2 NA NA 980s 3 7587 10267 980s 4 10268 14658 980s TCN and DH segmentation rows: 980s startRow endRow 980s 1 1 7586 980s 2 NA NA 980s 3 7587 10267 980s 4 10268 14658 980s startRow endRow 980s 1 10 7574 980s 2 NA NA 980s 3 7587 10263 980s 4 10269 14655 980s startRow endRow 980s 1 1 7586 980s 2 NA NA 980s 3 7587 10267 980s 4 10268 14658 980s Total CN segmentation table (expanded): 980s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 980s 4 1 185449813 247137334 4391 2.6341 1311 1311 980s (TCN,DH) segmentation for one total CN segment: 980s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 980s 4 4 1 1 185449813 247137334 4391 2.6341 1311 980s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 980s 4 1311 185449813 247137334 1311 0.2295 980s Total CN segment #4 ([1.8545e+08,2.47137e+08]) of 4...done 980s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 980s 1 1 1 1 554484 120992603 7586 1.3853 2108 980s 2 1 2 1 120992604 141510002 0 NA 0 980s 3 1 3 1 141510003 185449813 2681 2.0689 777 980s 4 1 4 1 185449813 247137334 4391 2.6341 1311 980s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 980s 1 2108 554484 120992603 2108 0.5116 980s 2 0 NA NA NA NA 980s 3 777 141510003 185449813 777 0.0973 980s 4 1311 185449813 247137334 1311 0.2295 980s Calculating (C1,C2) per segment... 980s Calculating (C1,C2) per segment...done 980s Number of segments: 4 980s Segmenting paired tumor-normal signals using Paired PSCBS...done 980s Post-segmenting TCNs... 980s Number of segments: 4 980s Number of chromosomes: 1 980s [1] 1 980s Chromosome 1 ('chr01') of 1... 980s Rows: 980s [1] 1 2 3 4 980s Number of segments: 4 980s TCN segment #1 ('1') of 4... 980s Nothing todo. Only one DH segmentation. Skipping. 980s TCN segment #1 ('1') of 4...done 980s TCN segment #2 ('2') of 4... 980s Nothing todo. Only one DH segmentation. Skipping. 980s TCN segment #2 ('2') of 4...done 980s TCN segment #3 ('3') of 4... 980s Nothing todo. Only one DH segmentation. Skipping. 980s TCN segment #3 ('3') of 4...done 980s TCN segment #4 ('4') of 4... 980s Nothing todo. Only one DH segmentation. Skipping. 980s TCN segment #4 ('4') of 4...done 980s Chromosome 1 ('chr01') of 1...done 980s Update (C1,C2) per segment... 980s Update (C1,C2) per segment...done 980s Post-segmenting TCNs...done 980s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 980s 1 1 1 1 554484 120992603 7586 1.3853 2108 980s 2 1 2 1 120992604 141510002 0 NA 0 980s 3 1 3 1 141510003 185449813 2681 2.0689 777 980s 4 1 4 1 185449813 247137334 4391 2.6341 1311 980s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 980s 1 2108 554484 120992603 2108 0.5116 0.3382903 1.047010 980s 2 0 NA NA NA NA NA NA 980s 3 777 141510003 185449813 777 0.0973 0.9337980 1.135102 980s 4 1311 185449813 247137334 1311 0.2295 1.0147870 1.619313 980s > print(fit) 980s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 980s 1 1 1 1 554484 120992603 7586 1.3853 2108 980s 2 1 2 1 120992604 141510002 0 NA 0 980s 3 1 3 1 141510003 185449813 2681 2.0689 777 980s 4 1 4 1 185449813 247137334 4391 2.6341 1311 980s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 980s 1 2108 554484 120992603 2108 0.5116 0.3382903 1.047010 980s 2 0 NA NA NA NA NA NA 980s 3 777 141510003 185449813 777 0.0973 0.9337980 1.135102 980s 4 1311 185449813 247137334 1311 0.2295 1.0147870 1.619313 980s chromosome tcnId dhId start end tcnNbrOfLoci tcnMean tcnNbrOfSNPs 980s 1 1 1 1 554484 120992603 7586 1.3853 2108 980s 2 1 2 1 120992604 141510002 0 NA 0 980s 3 1 3 1 141510003 185449813 2681 2.0689 777 980s 4 1 4 1 185449813 247137334 4391 2.6341 1311 980s tcnNbrOfHets dhNbrOfLoci dhMean c1Mean c2Mean 980s 1 2108 2108 0.5116 0.3382903 1.047010 980s 2 0 NA NA NA NA 980s 3 777 777 0.0973 0.9337980 1.135102 980s 4 1311 1311 0.2295 1.0147870 1.619313 980s > 980s > # Plot results 980s > dev.set(3L) 980s pdf 980s 2 980s > plotTracks(fit) 980s > abline(v=c(knownSegments$start, knownSegments$end)/1e6, lty=3) 980s > 980s > # Sanity check [TO FIX: See above] 980s > stopifnot(nbrOfSegments(fit) == nSegs) 980s > 980s > fit2 <- fit 980s > 980s > 980s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 980s > # (c) Do not segment the centromere (without a separator) 980s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 980s > knownSegments <- data.frame( 980s + chromosome = c( 1, 1), 980s + start = c( -Inf, 141510003), 980s + end = c(120992603, +Inf) 980s + ) 980s > 980s > # Paired PSCBS segmentation 980s > fit <- segmentByPairedPSCBS(dataS, knownSegments=knownSegments, 980s + seed=0xBEEF, verbose=-10) 980s Segmenting paired tumor-normal signals using Paired PSCBS... 980s Calling genotypes from normal allele B fractions... 980s num [1:14670] 0.8274 0.5072 0.1671 0.1609 0.0421 ... 980s Called genotypes: 980s num [1:14670] 1 0.5 0 0 0 0 1 0 1 0.5 ... 980s - attr(*, "modelFit")=List of 1 980s ..$ :List of 7 980s .. ..$ flavor : chr "density" 980s .. ..$ cn : int 2 980s .. ..$ nbrOfGenotypeGroups: int 3 980s .. ..$ tau : num [1:2] 0.315 0.677 980s .. ..$ n : int 14640 980s .. ..$ fit :Classes ‘PeaksAndValleys’ and 'data.frame': 5 obs. of 3 variables: 980s .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 980s .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 980s .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 980s .. ..$ fitValleys :Classes ‘PeaksAndValleys’ and 'data.frame': 2 obs. of 3 variables: 980s .. .. ..$ type : chr [1:2] "valley" "valley" 980s .. .. ..$ x : num [1:2] 0.315 0.677 980s .. .. ..$ density: num [1:2] 0.522 0.551 980s ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 980s muN 980s 0 0.5 1 980s 5221 4198 5251 980s Calling genotypes from normal allele B fractions...done 980s Normalizing betaT using betaN (TumorBoost)... 980s Normalized BAFs: 980s num [1:14670] 0.9301 0.1667 0.0685 0.0995 0.0155 ... 980s - attr(*, "modelFit")=List of 5 980s ..$ method : chr "normalizeTumorBoost" 980s ..$ flavor : chr "v4" 980s ..$ delta : num [1:14670] -0.17264 0.00239 0.1671 0.16085 0.04213 ... 980s .. ..- attr(*, "modelFit")=List of 1 980s .. .. ..$ :List of 7 980s .. .. .. ..$ flavor : chr "density" 980s .. .. .. ..$ cn : int 2 980s .. .. .. ..$ nbrOfGenotypeGroups: int 3 980s .. .. .. ..$ tau : num [1:2] 0.315 0.677 980s .. .. .. ..$ n : int 14640 980s .. .. .. ..$ fit :Classes ‘PeaksAndValleys’ and 'data.frame': 5 obs. of 3 variables: 980s .. .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 980s .. .. .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 980s .. .. .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 980s .. .. .. ..$ fitValleys :Classes ‘PeaksAndValleys’ and 'data.frame': 2 obs. of 3 variables: 980s .. .. .. .. ..$ type : chr [1:2] "valley" "valley" 980s .. .. .. .. ..$ x : num [1:2] 0.315 0.677 980s .. .. .. .. ..$ density: num [1:2] 0.522 0.551 980s .. .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 980s ..$ preserveScale: logi FALSE 980s ..$ scaleFactor : num NA 980s Normalizing betaT using betaN (TumorBoost)...done 980s Setup up data... 980s 'data.frame': 14670 obs. of 7 variables: 980s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 980s $ x : num 1145994 2941694 3710825 4240737 4276892 ... 980s $ CT : num 1.63 1.4 1.41 1.17 1.16 ... 980s $ betaT : num 0.7574 0.169 0.2357 0.2604 0.0576 ... 980s $ betaTN : num 0.9301 0.1667 0.0685 0.0995 0.0155 ... 980s ..- attr(*, "modelFit")=List of 5 980s .. ..$ method : chr "normalizeTumorBoost" 980s .. ..$ flavor : chr "v4" 980s .. ..$ delta : num [1:14670] -0.17264 0.00239 0.1671 0.16085 0.04213 ... 980s .. .. ..- attr(*, "modelFit")=List of 1 980s .. .. .. ..$ :List of 7 980s .. .. .. .. ..$ flavor : chr "density" 980s .. .. .. .. ..$ cn : int 2 980s .. .. .. .. ..$ nbrOfGenotypeGroups: int 3 980s .. .. .. .. ..$ tau : num [1:2] 0.315 0.677 980s .. .. .. .. ..$ n : int 14640 980s .. .. .. .. ..$ fit :Classes ‘PeaksAndValleys’ and 'data.frame': 5 obs. of 3 variables: 980s .. .. .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 980s .. .. .. .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 980s .. .. .. .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 980s .. .. .. .. ..$ fitValleys :Classes ‘PeaksAndValleys’ and 'data.frame': 2 obs. of 3 variables: 980s .. .. .. .. .. ..$ type : chr [1:2] "valley" "valley" 980s .. .. .. .. .. ..$ x : num [1:2] 0.315 0.677 980s .. .. .. .. .. ..$ density: num [1:2] 0.522 0.551 980s .. .. .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 980s .. ..$ preserveScale: logi FALSE 980s .. ..$ scaleFactor : num NA 980s $ betaN : num 0.8274 0.5072 0.1671 0.1609 0.0421 ... 980s $ muN : num 1 0.5 0 0 0 0 1 0 1 0.5 ... 980s ..- attr(*, "modelFit")=List of 1 980s .. ..$ :List of 7 980s .. .. ..$ flavor : chr "density" 980s .. .. ..$ cn : int 2 980s .. .. ..$ nbrOfGenotypeGroups: int 3 980s .. .. ..$ tau : num [1:2] 0.315 0.677 980s .. .. ..$ n : int 14640 980s .. .. ..$ fit :Classes ‘PeaksAndValleys’ and 'data.frame': 5 obs. of 3 variables: 980s .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 980s .. .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 980s .. .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 980s .. .. ..$ fitValleys :Classes ‘PeaksAndValleys’ and 'data.frame': 2 obs. of 3 variables: 980s .. .. .. ..$ type : chr [1:2] "valley" "valley" 980s .. .. .. ..$ x : num [1:2] 0.315 0.677 980s .. .. .. ..$ density: num [1:2] 0.522 0.551 980s .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 980s Setup up data...done 980s Dropping loci for which TCNs are missing... 980s Number of loci dropped: 12 980s Dropping loci for which TCNs are missing...done 980s Ordering data along genome... 980s 'data.frame': 14658 obs. of 7 variables: 980s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 980s $ x : num 554484 730720 782343 878522 916294 ... 980s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 980s $ betaT : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 980s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 980s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 980s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 980s Ordering data along genome...done 980s Keeping only current chromosome for 'knownSegments'... 980s Chromosome: 1 980s Known segments for this chromosome: 980s chromosome start end 980s 1 1 -Inf 120992603 980s 2 1 141510003 Inf 980s Keeping only current chromosome for 'knownSegments'...done 980s alphaTCN: 0.009 980s alphaDH: 0.001 980s Number of loci: 14658 980s Calculating DHs... 980s Number of SNPs: 14658 980s Number of heterozygous SNPs: 4196 (28.63%) 980s Normalized DHs: 980s num [1:14658] NA NA NA NA NA ... 980s Calculating DHs...done 980s Random seed temporarily set (seed=c(48879), kind="L'Ecuyer-CMRG") 980s Produced 2 seeds from this stream for future usage 980s Identification of change points by total copy numbers... 980s Segmenting by CBS... 980s Chromosome: 1 980s Segmenting multiple segments on current chromosome... 980s Number of segments: 2 980s Random seed temporarily set (seed=c(10407, 1066287653, -51199871, 161854402, -1995183193, 1503453565, -747102133), kind="L'Ecuyer-CMRG") 980s Produced 2 seeds from this stream for future usage 980s Segmenting by CBS... 980s Chromosome: 1 980s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 981s Segmenting by CBS...done 981s Segmenting by CBS... 981s Chromosome: 1 981s Random seed temporarily set (seed=c(10407, -821273412, -52578226, 1415511586, 721384351, -665928286, 1316562960), kind="L'Ecuyer-CMRG") 981s Segmenting by CBS...done 981s Segmenting multiple segments on current chromosome...done 981s Segmenting by CBS...done 981s List of 4 981s $ data :'data.frame': 14658 obs. of 4 variables: 981s ..$ chromosome: int [1:14658] 1 1 1 1 1 1 1 1 1 1 ... 981s ..$ x : num [1:14658] 554484 730720 782343 878522 916294 ... 981s ..$ y : num [1:14658] 1.88 1.8 1.59 1.64 1.53 ... 981s ..$ index : int [1:14658] 1 2 3 4 5 6 7 8 9 10 ... 981s $ output :'data.frame': 3 obs. of 6 variables: 981s ..$ sampleName: chr [1:3] NA NA NA 981s ..$ chromosome: int [1:3] 1 1 1 981s ..$ start : num [1:3] 5.54e+05 1.42e+08 1.85e+08 981s ..$ end : num [1:3] 1.21e+08 1.85e+08 2.47e+08 981s ..$ nbrOfLoci : int [1:3] 7586 2681 4391 981s ..$ mean : num [1:3] 1.39 2.07 2.63 981s $ segRows:'data.frame': 3 obs. of 2 variables: 981s ..$ startRow: int [1:3] 1 7587 10268 981s ..$ endRow : int [1:3] 7586 10267 14658 981s $ params :List of 5 981s ..$ alpha : num 0.009 981s ..$ undo : num 0 981s ..$ joinSegments : logi TRUE 981s ..$ knownSegments:'data.frame': 2 obs. of 3 variables: 981s .. ..$ chromosome: num [1:2] 1 1 981s .. ..$ start : num [1:2] -Inf 1.42e+08 981s .. ..$ end : num [1:2] 1.21e+08 Inf 981s ..$ seed : int [1:7] 10407 1066287653 -51199871 161854402 -1995183193 1503453565 -747102133 981s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 981s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.164 0 0.165 0 0 981s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 981s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 981s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 981s Identification of change points by total copy numbers...done 981s Restructure TCN segmentation results... 981s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean 981s 1 1 554484 120992603 7586 1.3853 981s 2 1 141510003 185449813 2681 2.0689 981s 3 1 185449813 247137334 4391 2.6341 981s Number of TCN segments: 3 981s Restructure TCN segmentation results...done 981s Total CN segment #1 ([ 554484,1.20993e+08]) of 3... 981s Number of TCN loci in segment: 7586 981s Locus data for TCN segment: 981s 'data.frame': 7586 obs. of 9 variables: 981s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 981s $ x : num 554484 730720 782343 878522 916294 ... 981s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 981s $ betaT : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 981s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 981s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 981s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 981s $ index : int 1 2 3 4 5 6 7 8 9 10 ... 981s $ rho : num NA NA NA NA NA ... 981s Number of loci: 7586 981s Number of SNPs: 2108 (27.79%) 981s Number of heterozygous SNPs: 2108 (100.00%) 981s Chromosome: 1 981s Segmenting DH signals... 981s Segmenting by CBS... 981s Chromosome: 1 981s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 981s Segmenting by CBS...done 981s List of 4 981s $ data :'data.frame': 7586 obs. of 4 variables: 981s ..$ chromosome: int [1:7586] 1 1 1 1 1 1 1 1 1 1 ... 981s ..$ x : num [1:7586] 554484 730720 782343 878522 916294 ... 981s ..$ y : num [1:7586] NA NA NA NA NA ... 981s ..$ index : int [1:7586] 1 2 3 4 5 6 7 8 9 10 ... 981s $ output :'data.frame': 1 obs. of 6 variables: 981s ..$ sampleName: chr NA 981s ..$ chromosome: int 1 981s ..$ start : num 554484 981s ..$ end : num 1.21e+08 981s ..$ nbrOfLoci : int 2108 981s ..$ mean : num 0.512 981s $ segRows:'data.frame': 1 obs. of 2 variables: 981s ..$ startRow: int 10 981s ..$ endRow : int 7574 981s $ params :List of 5 981s ..$ alpha : num 0.001 981s ..$ undo : num 0 981s ..$ joinSegments : logi TRUE 981s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 981s .. ..$ chromosome: int 1 981s .. ..$ start : num 554484 981s .. ..$ end : num 1.21e+08 981s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 981s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 981s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.047 0 0.047 0 0 981s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 981s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 981s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 981s DH segmentation (locally-indexed) rows: 981s startRow endRow 981s 1 10 7574 981s int [1:7586] 1 2 3 4 5 6 7 8 9 10 ... 981s DH segmentation rows: 981s startRow endRow 981s 1 10 7574 981s Segmenting DH signals...done 981s DH segmentation table: 981s dhStart dhEnd dhNbrOfLoci dhMean 981s 1 554484 120992603 2108 0.5116 981s startRow endRow 981s 1 10 7574 981s Rows: 981s [1] 1 981s TCN segmentation rows: 981s startRow endRow 981s 1 1 7586 981s TCN and DH segmentation rows: 981s startRow endRow 981s 1 1 7586 981s startRow endRow 981s 1 10 7574 981s NULL 981s TCN segmentation (expanded) rows: 981s startRow endRow 981s 1 1 7586 981s TCN and DH segmentation rows: 981s startRow endRow 981s 1 1 7586 981s 2 7587 10267 981s 3 10268 14658 981s startRow endRow 981s 1 10 7574 981s startRow endRow 981s 1 1 7586 981s Total CN segmentation table (expanded): 981s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 981s 1 1 554484 120992603 7586 1.3853 2108 2108 981s (TCN,DH) segmentation for one total CN segment: 981s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 981s 1 1 1 1 554484 120992603 7586 1.3853 2108 981s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 981s 1 2108 554484 120992603 2108 0.5116 981s Total CN segment #1 ([ 554484,1.20993e+08]) of 3...done 981s Total CN segment #2 ([1.4151e+08,1.8545e+08]) of 3... 981s Number of TCN loci in segment: 2681 981s Locus data for TCN segment: 981s 'data.frame': 2681 obs. of 9 variables: 981s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 981s $ x : num 1.43e+08 1.43e+08 1.43e+08 1.43e+08 1.44e+08 ... 981s $ CT : num 2.27 1.55 1.47 1.5 1.81 ... 981s $ betaT : num 0.34 0.55 0.048 0.813 0.575 ... 981s $ betaTN : num 0.441 0.629 -0.05 0.958 0.872 ... 981s $ betaN : num 0.3851 0.3933 0.0981 0.8552 0.7028 ... 981s $ muN : num 0.5 0.5 0 1 1 1 1 0.5 1 1 ... 981s $ index : int 7587 7588 7589 7590 7591 7592 7593 7594 7595 7596 ... 981s $ rho : num 0.117 0.258 NA NA NA ... 981s Number of loci: 2681 981s Number of SNPs: 777 (28.98%) 981s Number of heterozygous SNPs: 777 (100.00%) 981s Chromosome: 1 981s Segmenting DH signals... 981s Segmenting by CBS... 981s Chromosome: 1 981s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 981s Segmenting by CBS...done 981s List of 4 981s $ data :'data.frame': 2681 obs. of 4 variables: 981s ..$ chromosome: int [1:2681] 1 1 1 1 1 1 1 1 1 1 ... 981s ..$ x : num [1:2681] 1.43e+08 1.43e+08 1.43e+08 1.43e+08 1.44e+08 ... 981s ..$ y : num [1:2681] 0.117 0.258 NA NA NA ... 981s ..$ index : int [1:2681] 1 2 3 4 5 6 7 8 9 10 ... 981s $ output :'data.frame': 1 obs. of 6 variables: 981s ..$ sampleName: chr NA 981s ..$ chromosome: int 1 981s ..$ start : num 1.42e+08 981s ..$ end : num 1.85e+08 981s ..$ nbrOfLoci : int 777 981s ..$ mean : num 0.0973 981s $ segRows:'data.frame': 1 obs. of 2 variables: 981s ..$ startRow: int 1 981s ..$ endRow : int 2677 981s $ params :List of 5 981s ..$ alpha : num 0.001 981s ..$ undo : num 0 981s ..$ joinSegments : logi TRUE 981s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 981s .. ..$ chromosome: int 1 981s .. ..$ start : num 1.42e+08 981s .. ..$ end : num 1.85e+08 981s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 981s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 981s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.009 0 0.009 0 0 981s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 981s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 981s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 981s DH segmentation (locally-indexed) rows: 981s startRow endRow 981s 1 1 2677 981s int [1:2681] 7587 7588 7589 7590 7591 7592 7593 7594 7595 7596 ... 981s DH segmentation rows: 981s startRow endRow 981s 1 7587 10263 981s Segmenting DH signals...done 981s DH segmentation table: 981s dhStart dhEnd dhNbrOfLoci dhMean 981s 1 141510003 185449813 777 0.0973 981s startRow endRow 981s 1 7587 10263 981s Rows: 981s [1] 2 981s TCN segmentation rows: 981s startRow endRow 981s 2 7587 10267 981s TCN and DH segmentation rows: 981s startRow endRow 981s 2 7587 10267 981s startRow endRow 981s 1 7587 10263 981s startRow endRow 981s 1 1 7586 981s TCN segmentation (expanded) rows: 981s startRow endRow 981s 1 1 7586 981s 2 7587 10267 981s TCN and DH segmentation rows: 981s startRow endRow 981s 1 1 7586 981s 2 7587 10267 981s 3 10268 14658 981s startRow endRow 981s 1 10 7574 981s 2 7587 10263 981s startRow endRow 981s 1 1 7586 981s 2 7587 10267 981s Total CN segmentation table (expanded): 981s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 981s 2 1 141510003 185449813 2681 2.0689 777 777 981s (TCN,DH) segmentation for one total CN segment: 981s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 981s 2 2 1 1 141510003 185449813 2681 2.0689 777 981s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 981s 2 777 141510003 185449813 777 0.0973 981s Total CN segment #2 ([1.4151e+08,1.8545e+08]) of 3...done 981s Total CN segment #3 ([1.8545e+08,2.47137e+08]) of 3... 981s Number of TCN loci in segment: 4391 981s Locus data for TCN segment: 981s 'data.frame': 4391 obs. of 9 variables: 981s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 981s $ x : num 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 981s $ CT : num 2.93 2.15 2.82 2.93 2.46 ... 981s $ betaT : num 0.0811 0.5154 0.9473 0.3734 0.7506 ... 981s $ betaTN : num -0.169 0.609 1.028 0.525 0.968 ... 981s $ betaN : num 0.25 0.38 0.919 0.34 0.783 ... 981s $ muN : num 0 0.5 1 0.5 1 1 0 1 0 1 ... 981s $ index : int 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 981s $ rho : num NA 0.2186 NA 0.0503 NA ... 981s Number of loci: 4391 981s Number of SNPs: 1311 (29.86%) 981s Number of heterozygous SNPs: 1311 (100.00%) 981s Chromosome: 1 981s Segmenting DH signals... 981s Segmenting by CBS... 981s Chromosome: 1 981s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 981s Segmenting by CBS...done 981s List of 4 981s $ data :'data.frame': 4391 obs. of 4 variables: 981s ..$ chromosome: int [1:4391] 1 1 1 1 1 1 1 1 1 1 ... 981s ..$ x : num [1:4391] 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 981s ..$ y : num [1:4391] NA 0.2186 NA 0.0503 NA ... 981s ..$ index : int [1:4391] 1 2 3 4 5 6 7 8 9 10 ... 981s $ output :'data.frame': 1 obs. of 6 variables: 981s ..$ sampleName: chr NA 981s ..$ chromosome: int 1 981s ..$ start : num 1.85e+08 981s ..$ end : num 2.47e+08 981s ..$ nbrOfLoci : int 1311 981s ..$ mean : num 0.23 981s $ segRows:'data.frame': 1 obs. of 2 variables: 981s ..$ startRow: int 2 981s ..$ endRow : int 4388 981s $ params :List of 5 981s ..$ alpha : num 0.001 981s ..$ undo : num 0 981s ..$ joinSegments : logi TRUE 981s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 981s .. ..$ chromosome: int 1 981s .. ..$ start : num 1.85e+08 981s .. ..$ end : num 2.47e+08 981s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 981s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 981s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.017 0 0.018 0 0 981s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 981s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 981s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 981s DH segmentation (locally-indexed) rows: 981s startRow endRow 981s 1 2 4388 981s int [1:4391] 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 981s DH segmentation rows: 981s startRow endRow 981s 1 10269 14655 981s Segmenting DH signals...done 981s DH segmentation table: 981s dhStart dhEnd dhNbrOfLoci dhMean 981s 1 185449813 247137334 1311 0.2295 981s startRow endRow 981s 1 10269 14655 981s Rows: 981s [1] 3 981s TCN segmentation rows: 981s startRow endRow 981s 3 10268 14658 981s TCN and DH segmentation rows: 981s startRow endRow 981s 3 10268 14658 981s startRow endRow 981s 1 10269 14655 981s startRow endRow 981s 1 1 7586 981s 2 7587 10267 981s TCN segmentation (expanded) rows: 981s startRow endRow 981s 1 1 7586 981s 2 7587 10267 981s 3 10268 14658 981s TCN and DH segmentation rows: 981s startRow endRow 981s 1 1 7586 981s 2 7587 10267 981s 3 10268 14658 981s startRow endRow 981s 1 10 7574 981s 2 7587 10263 981s 3 10269 14655 981s startRow endRow 981s 1 1 7586 981s 2 7587 10267 981s 3 10268 14658 981s Total CN segmentation table (expanded): 981s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 981s 3 1 185449813 247137334 4391 2.6341 1311 1311 981s (TCN,DH) segmentation for one total CN segment: 981s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 981s 3 3 1 1 185449813 247137334 4391 2.6341 1311 981s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 981s 3 1311 185449813 247137334 1311 0.2295 981s Total CN segment #3 ([1.8545e+08,2.47137e+08]) of 3...done 981s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 981s 1 1 1 1 554484 120992603 7586 1.3853 2108 981s 2 1 2 1 141510003 185449813 2681 2.0689 777 981s 3 1 3 1 185449813 247137334 4391 2.6341 1311 981s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 981s 1 2108 554484 120992603 2108 0.5116 981s 2 777 141510003 185449813 777 0.0973 981s 3 1311 185449813 247137334 1311 0.2295 981s Calculating (C1,C2) per segment... 981s Calculating (C1,C2) per segment...done 981s Number of segments: 3 981s Segmenting paired tumor-normal signals using Paired PSCBS...done 981s Post-segmenting TCNs... 981s Number of segments: 3 981s Number of chromosomes: 1 981s [1] 1 981s Chromosome 1 ('chr01') of 1... 981s Rows: 981s [1] 1 2 3 981s Number of segments: 3 981s TCN segment #1 ('1') of 3... 981s Nothing todo. Only one DH segmentation. Skipping. 981s TCN segment #1 ('1') of 3...done 981s TCN segment #2 ('2') of 3... 981s Nothing todo. Only one DH segmentation. Skipping. 981s TCN segment #2 ('2') of 3...done 981s TCN segment #3 ('3') of 3... 981s Nothing todo. Only one DH segmentation. Skipping. 981s TCN segment #3 ('3') of 3...done 981s Chromosome 1 ('chr01') of 1...done 981s Update (C1,C2) per segment... 981s Update (C1,C2) per segment...done 981s Post-segmenting TCNs...done 981s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 981s 1 1 1 1 554484 120992603 7586 1.3853 2108 981s 2 1 2 1 141510003 185449813 2681 2.0689 777 981s 3 1 3 1 185449813 247137334 4391 2.6341 1311 981s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 981s 1 2108 554484 120992603 2108 0.5116 0.3382903 1.047010 981s 2 777 141510003 185449813 777 0.0973 0.9337980 1.135102 981s 3 1311 185449813 247137334 1311 0.2295 1.0147870 1.619313 981s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 981s 1 1 1 1 554484 120992603 7586 1.3853 2108 981s 2 1 2 1 141510003 185449813 2681 2.0689 777 981s 3 1 3 1 185449813 247137334 4391 2.6341 1311 981s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 981s 1 2108 554484 120992603 2108 0.5116 0.3382903 1.047010 981s 2 777 141510003 185449813 777 0.0973 0.9337980 1.135102 981s 3 1311 185449813 247137334 1311 0.2295 1.0147870 1.619313 981s > print(fit) 981s chromosome tcnId dhId start end tcnNbrOfLoci tcnMean tcnNbrOfSNPs 981s 1 1 1 1 554484 120992603 7586 1.3853 2108 981s 2 1 2 1 141510003 185449813 2681 2.0689 777 981s 3 1 3 1 185449813 247137334 4391 2.6341 1311 981s tcnNbrOfHets dhNbrOfLoci dhMean c1Mean c2Mean 981s 1 2108 2108 0.5116 0.3382903 1.047010 981s 2 777 777 0.0973 0.9337980 1.135102 981s 3 1311 1311 0.2295 1.0147870 1.619313 981s > 981s > # Plot results 981s > dev.set(4L) 981s pdf 981s 2 981s > plotTracks(fit) 982s > abline(v=c(knownSegments$start, knownSegments$end)/1e6, lty=3) 982s > 982s > # Sanity check 982s > stopifnot(nbrOfSegments(fit) == nSegs-1L) 982s > 982s > fit3 <- fit 982s > 982s > 982s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 982s > # (d) Skip the identification of new change points 982s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 982s > knownSegments <- data.frame( 982s + chromosome = c( 1, 1), 982s + start = c( -Inf, 141510003), 982s + end = c(120992603, +Inf) 982s + ) 982s > 982s > # Paired PSCBS segmentation 982s > fit <- segmentByPairedPSCBS(dataS, knownSegments=knownSegments, 982s + undoTCN=Inf, undoDH=Inf, 982s + seed=0xBEEF, verbose=-10) 982s Segmenting paired tumor-normal signals using Paired PSCBS... 982s Calling genotypes from normal allele B fractions... 982s num [1:14670] 0.8274 0.5072 0.1671 0.1609 0.0421 ... 982s Called genotypes: 982s num [1:14670] 1 0.5 0 0 0 0 1 0 1 0.5 ... 982s - attr(*, "modelFit")=List of 1 982s ..$ :List of 7 982s .. ..$ flavor : chr "density" 982s .. ..$ cn : int 2 982s .. ..$ nbrOfGenotypeGroups: int 3 982s .. ..$ tau : num [1:2] 0.315 0.677 982s .. ..$ n : int 14640 982s .. ..$ fit :Classes ‘PeaksAndValleys’ and 'data.frame': 5 obs. of 3 variables: 982s .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 982s .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 982s .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 982s .. ..$ fitValleys :Classes ‘PeaksAndValleys’ and 'data.frame': 2 obs. of 3 variables: 982s .. .. ..$ type : chr [1:2] "valley" "valley" 982s .. .. ..$ x : num [1:2] 0.315 0.677 982s .. .. ..$ density: num [1:2] 0.522 0.551 982s ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 982s muN 982s 0 0.5 1 982s 5221 4198 5251 982s Calling genotypes from normal allele B fractions...done 982s Normalizing betaT using betaN (TumorBoost)... 982s Normalized BAFs: 982s num [1:14670] 0.9301 0.1667 0.0685 0.0995 0.0155 ... 982s - attr(*, "modelFit")=List of 5 982s ..$ method : chr "normalizeTumorBoost" 982s ..$ flavor : chr "v4" 982s ..$ delta : num [1:14670] -0.17264 0.00239 0.1671 0.16085 0.04213 ... 982s .. ..- attr(*, "modelFit")=List of 1 982s .. .. ..$ :List of 7 982s .. .. .. ..$ flavor : chr "density" 982s .. .. .. ..$ cn : int 2 982s .. .. .. ..$ nbrOfGenotypeGroups: int 3 982s .. .. .. ..$ tau : num [1:2] 0.315 0.677 982s .. .. .. ..$ n : int 14640 982s .. .. .. ..$ fit :Classes ‘PeaksAndValleys’ and 'data.frame': 5 obs. of 3 variables: 982s .. .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 982s .. .. .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 982s .. .. .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 982s .. .. .. ..$ fitValleys :Classes ‘PeaksAndValleys’ and 'data.frame': 2 obs. of 3 variables: 982s .. .. .. .. ..$ type : chr [1:2] "valley" "valley" 982s .. .. .. .. ..$ x : num [1:2] 0.315 0.677 982s .. .. .. .. ..$ density: num [1:2] 0.522 0.551 982s .. .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 982s ..$ preserveScale: logi FALSE 982s ..$ scaleFactor : num NA 982s Normalizing betaT using betaN (TumorBoost)...done 982s Setup up data... 982s 'data.frame': 14670 obs. of 7 variables: 982s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 982s $ x : num 1145994 2941694 3710825 4240737 4276892 ... 982s $ CT : num 1.63 1.4 1.41 1.17 1.16 ... 982s $ betaT : num 0.7574 0.169 0.2357 0.2604 0.0576 ... 982s $ betaTN : num 0.9301 0.1667 0.0685 0.0995 0.0155 ... 982s ..- attr(*, "modelFit")=List of 5 982s .. ..$ method : chr "normalizeTumorBoost" 982s .. ..$ flavor : chr "v4" 982s .. ..$ delta : num [1:14670] -0.17264 0.00239 0.1671 0.16085 0.04213 ... 982s .. .. ..- attr(*, "modelFit")=List of 1 982s .. .. .. ..$ :List of 7 982s .. .. .. .. ..$ flavor : chr "density" 982s .. .. .. .. ..$ cn : int 2 982s .. .. .. .. ..$ nbrOfGenotypeGroups: int 3 982s .. .. .. .. ..$ tau : num [1:2] 0.315 0.677 982s .. .. .. .. ..$ n : int 14640 982s .. .. .. .. ..$ fit :Classes ‘PeaksAndValleys’ and 'data.frame': 5 obs. of 3 variables: 982s .. .. .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 982s .. .. .. .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 982s .. .. .. .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 982s .. .. .. .. ..$ fitValleys :Classes ‘PeaksAndValleys’ and 'data.frame': 2 obs. of 3 variables: 982s .. .. .. .. .. ..$ type : chr [1:2] "valley" "valley" 982s .. .. .. .. .. ..$ x : num [1:2] 0.315 0.677 982s .. .. .. .. .. ..$ density: num [1:2] 0.522 0.551 982s .. .. .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 982s .. ..$ preserveScale: logi FALSE 982s .. ..$ scaleFactor : num NA 982s $ betaN : num 0.8274 0.5072 0.1671 0.1609 0.0421 ... 982s $ muN : num 1 0.5 0 0 0 0 1 0 1 0.5 ... 982s ..- attr(*, "modelFit")=List of 1 982s .. ..$ :List of 7 982s .. .. ..$ flavor : chr "density" 982s .. .. ..$ cn : int 2 982s .. .. ..$ nbrOfGenotypeGroups: int 3 982s .. .. ..$ tau : num [1:2] 0.315 0.677 982s .. .. ..$ n : int 14640 982s .. .. ..$ fit :Classes ‘PeaksAndValleys’ and 'data.frame': 5 obs. of 3 variables: 982s .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 982s .. .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 982s .. .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 982s .. .. ..$ fitValleys :Classes ‘PeaksAndValleys’ and 'data.frame': 2 obs. of 3 variables: 982s .. .. .. ..$ type : chr [1:2] "valley" "valley" 982s .. .. .. ..$ x : num [1:2] 0.315 0.677 982s .. .. .. ..$ density: num [1:2] 0.522 0.551 982s .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 982s Setup up data...done 982s Dropping loci for which TCNs are missing... 982s Number of loci dropped: 12 982s Dropping loci for which TCNs are missing...done 982s Ordering data along genome... 982s 'data.frame': 14658 obs. of 7 variables: 982s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 982s $ x : num 554484 730720 782343 878522 916294 ... 982s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 982s $ betaT : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 982s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 982s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 982s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 982s Ordering data along genome...done 982s Keeping only current chromosome for 'knownSegments'... 982s Chromosome: 1 982s Known segments for this chromosome: 982s chromosome start end 982s 1 1 -Inf 120992603 982s 2 1 141510003 Inf 982s Keeping only current chromosome for 'knownSegments'...done 982s alphaTCN: 0.009 982s alphaDH: 0.001 982s Number of loci: 14658 982s Calculating DHs... 982s Number of SNPs: 14658 982s Number of heterozygous SNPs: 4196 (28.63%) 982s Normalized DHs: 982s num [1:14658] NA NA NA NA NA ... 982s Calculating DHs...done 982s Random seed temporarily set (seed=c(48879), kind="L'Ecuyer-CMRG") 982s Produced 2 seeds from this stream for future usage 982s Identification of change points by total copy numbers... 982s Segmenting by CBS... 982s Chromosome: 1 982s Segmenting multiple segments on current chromosome... 982s Number of segments: 2 982s Random seed temporarily set (seed=c(10407, 1066287653, -51199871, 161854402, -1995183193, 1503453565, -747102133), kind="L'Ecuyer-CMRG") 982s Produced 2 seeds from this stream for future usage 982s Segmenting by CBS... 982s Chromosome: 1 982s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 982s Segmenting by CBS...done 982s Segmenting by CBS... 982s Chromosome: 1 982s Random seed temporarily set (seed=c(10407, -821273412, -52578226, 1415511586, 721384351, -665928286, 1316562960), kind="L'Ecuyer-CMRG") 982s Segmenting by CBS...done 982s Segmenting multiple segments on current chromosome...done 982s Segmenting by CBS...done 982s List of 4 982s $ data :'data.frame': 14658 obs. of 4 variables: 982s ..$ chromosome: int [1:14658] 1 1 1 1 1 1 1 1 1 1 ... 982s ..$ x : num [1:14658] 554484 730720 782343 878522 916294 ... 982s ..$ y : num [1:14658] 1.88 1.8 1.59 1.64 1.53 ... 982s ..$ index : int [1:14658] 1 2 3 4 5 6 7 8 9 10 ... 982s $ output :'data.frame': 2 obs. of 6 variables: 982s ..$ sampleName: chr [1:2] NA NA 982s ..$ chromosome: num [1:2] 1 1 982s ..$ start : num [1:2] 5.54e+05 1.42e+08 982s ..$ end : num [1:2] 1.21e+08 2.47e+08 982s ..$ nbrOfLoci : int [1:2] 7586 7072 982s ..$ mean : num [1:2] 1.39 2.42 982s $ segRows:'data.frame': 2 obs. of 2 variables: 982s ..$ startRow: int [1:2] 1 7587 982s ..$ endRow : int [1:2] 7586 14658 982s $ params :List of 7 982s ..$ undo.splits : chr "sdundo" 982s ..$ undo.SD : num Inf 982s ..$ alpha : num 0.009 982s ..$ undo : num Inf 982s ..$ joinSegments : logi TRUE 982s ..$ knownSegments:'data.frame': 2 obs. of 3 variables: 982s .. ..$ chromosome: num [1:2] 1 1 982s .. ..$ start : num [1:2] -Inf 1.42e+08 982s .. ..$ end : num [1:2] 1.21e+08 Inf 982s ..$ seed : int [1:7] 10407 1066287653 -51199871 161854402 -1995183193 1503453565 -747102133 982s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 982s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.001 0 0.001 0 0 982s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 982s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 982s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 982s Identification of change points by total copy numbers...done 982s Restructure TCN segmentation results... 982s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean 982s 1 1 554484 120992603 7586 1.385258 982s 2 1 141510003 247137334 7072 2.419824 982s Number of TCN segments: 2 982s Restructure TCN segmentation results...done 982s Total CN segment #1 ([ 554484,1.20993e+08]) of 2... 982s Number of TCN loci in segment: 7586 982s Locus data for TCN segment: 982s 'data.frame': 7586 obs. of 9 variables: 982s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 982s $ x : num 554484 730720 782343 878522 916294 ... 982s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 982s $ betaT : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 982s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 982s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 982s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 982s $ index : int 1 2 3 4 5 6 7 8 9 10 ... 982s $ rho : num NA NA NA NA NA ... 982s Number of loci: 7586 982s Number of SNPs: 2108 (27.79%) 982s Number of heterozygous SNPs: 2108 (100.00%) 982s Chromosome: 1 982s Segmenting DH signals... 982s Segmenting by CBS... 982s Chromosome: 1 982s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 982s Segmenting by CBS...done 982s List of 4 982s $ data :'data.frame': 7586 obs. of 4 variables: 982s ..$ chromosome: int [1:7586] 1 1 1 1 1 1 1 1 1 1 ... 982s ..$ x : num [1:7586] 554484 730720 782343 878522 916294 ... 982s ..$ y : num [1:7586] NA NA NA NA NA ... 982s ..$ index : int [1:7586] 1 2 3 4 5 6 7 8 9 10 ... 982s $ output :'data.frame': 1 obs. of 6 variables: 982s ..$ sampleName: chr NA 982s ..$ chromosome: int 1 982s ..$ start : num 554484 982s ..$ end : num 1.21e+08 982s ..$ nbrOfLoci : int 7586 982s ..$ mean : num 0.512 982s $ segRows:'data.frame': 1 obs. of 2 variables: 982s ..$ startRow: int 1 982s ..$ endRow : int 7586 982s $ params :List of 7 982s ..$ undo.splits : chr "sdundo" 982s ..$ undo.SD : num Inf 982s ..$ alpha : num 0.001 982s ..$ undo : num Inf 982s ..$ joinSegments : logi TRUE 982s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 982s .. ..$ chromosome: int 1 982s .. ..$ start : num 554484 982s .. ..$ end : num 1.21e+08 982s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 982s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 982s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.002 0 0.001 0 0 982s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 982s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 982s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 982s DH segmentation (locally-indexed) rows: 982s startRow endRow 982s 1 1 7586 982s int [1:7586] 1 2 3 4 5 6 7 8 9 10 ... 982s DH segmentation rows: 982s startRow endRow 982s 1 1 7586 982s Segmenting DH signals...done 982s DH segmentation table: 982s dhStart dhEnd dhNbrOfLoci dhMean 982s 1 554484 120992603 7586 0.511612 982s startRow endRow 982s 1 1 7586 982s Rows: 982s [1] 1 982s TCN segmentation rows: 982s startRow endRow 982s 1 1 7586 982s TCN and DH segmentation rows: 982s startRow endRow 982s 1 1 7586 982s startRow endRow 982s 1 1 7586 982s NULL 982s TCN segmentation (expanded) rows: 982s startRow endRow 982s 1 1 7586 982s TCN and DH segmentation rows: 982s startRow endRow 982s 1 1 7586 982s 2 7587 14658 982s startRow endRow 982s 1 1 7586 982s startRow endRow 982s 1 1 7586 982s Total CN segmentation table (expanded): 982s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 982s 1 1 554484 120992603 7586 1.385258 2108 2108 982s (TCN,DH) segmentation for one total CN segment: 982s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 982s 1 1 1 1 554484 120992603 7586 1.385258 2108 982s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 982s 1 2108 554484 120992603 7586 0.511612 982s Total CN segment #1 ([ 554484,1.20993e+08]) of 2...done 982s Total CN segment #2 ([1.4151e+08,2.47137e+08]) of 2... 982s Number of TCN loci in segment: 7072 982s Locus data for TCN segment: 982s 'data.frame': 7072 obs. of 9 variables: 982s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 982s $ x : num 1.43e+08 1.43e+08 1.43e+08 1.43e+08 1.44e+08 ... 982s $ CT : num 2.27 1.55 1.47 1.5 1.81 ... 982s $ betaT : num 0.34 0.55 0.048 0.813 0.575 ... 982s $ betaTN : num 0.441 0.629 -0.05 0.958 0.872 ... 982s $ betaN : num 0.3851 0.3933 0.0981 0.8552 0.7028 ... 982s $ muN : num 0.5 0.5 0 1 1 1 1 0.5 1 1 ... 982s $ index : int 7587 7588 7589 7590 7591 7592 7593 7594 7595 7596 ... 982s $ rho : num 0.117 0.258 NA NA NA ... 982s Number of loci: 7072 982s Number of SNPs: 2088 (29.52%) 982s Number of heterozygous SNPs: 2088 (100.00%) 982s Chromosome: 1 982s Segmenting DH signals... 982s Segmenting by CBS... 982s Chromosome: 1 982s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 982s Segmenting by CBS...done 982s List of 4 982s $ data :'data.frame': 7072 obs. of 4 variables: 982s ..$ chromosome: int [1:7072] 1 1 1 1 1 1 1 1 1 1 ... 982s ..$ x : num [1:7072] 1.43e+08 1.43e+08 1.43e+08 1.43e+08 1.44e+08 ... 982s ..$ y : num [1:7072] 0.117 0.258 NA NA NA ... 982s ..$ index : int [1:7072] 1 2 3 4 5 6 7 8 9 10 ... 982s $ output :'data.frame': 1 obs. of 6 variables: 982s ..$ sampleName: chr NA 982s ..$ chromosome: int 1 982s ..$ start : num 1.42e+08 982s ..$ end : num 2.47e+08 982s ..$ nbrOfLoci : int 7072 982s ..$ mean : num 0.18 982s $ segRows:'data.frame': 1 obs. of 2 variables: 982s ..$ startRow: int 1 982s ..$ endRow : int 7072 982s $ params :List of 7 982s ..$ undo.splits : chr "sdundo" 982s ..$ undo.SD : num Inf 982s ..$ alpha : num 0.001 982s ..$ undo : num Inf 982s ..$ joinSegments : logi TRUE 982s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 982s .. ..$ chromosome: int 1 982s .. ..$ start : num 1.42e+08 982s .. ..$ end : num 2.47e+08 982s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 982s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 982s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.002 0 0.001 0 0 982s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 982s - attr(*, "pkgDetails")= chr "DNAcopy v1.80.0" 982s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 982s DH segmentation (locally-indexed) rows: 982s startRow endRow 982s 1 1 7072 982s int [1:7072] 7587 7588 7589 7590 7591 7592 7593 7594 7595 7596 ... 982s DH segmentation rows: 982s startRow endRow 982s 1 7587 14658 982s Segmenting DH signals...done 982s DH segmentation table: 982s dhStart dhEnd dhNbrOfLoci dhMean 982s 1 141510003 247137334 7072 0.1803011 982s startRow endRow 982s 1 7587 14658 982s Rows: 982s [1] 2 982s TCN segmentation rows: 982s startRow endRow 982s 2 7587 14658 982s TCN and DH segmentation rows: 982s startRow endRow 982s 2 7587 14658 982s startRow endRow 982s 1 7587 14658 982s startRow endRow 982s 1 1 7586 982s TCN segmentation (expanded) rows: 982s startRow endRow 982s 1 1 7586 982s 2 7587 14658 982s TCN and DH segmentation rows: 982s startRow endRow 982s 1 1 7586 982s 2 7587 14658 982s startRow endRow 982s 1 1 7586 982s 2 7587 14658 982s startRow endRow 982s 1 1 7586 982s 2 7587 14658 982s Total CN segmentation table (expanded): 982s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 982s 2 1 141510003 247137334 7072 2.419824 2088 982s tcnNbrOfHets 982s 2 2088 982s (TCN,DH) segmentation for one total CN segment: 982s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 982s 2 2 1 1 141510003 247137334 7072 2.419824 2088 982s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 982s 2 2088 141510003 247137334 7072 0.1803011 982s Total CN segment #2 ([1.4151e+08,2.47137e+08]) of 2...done 982s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 982s 1 1 1 1 554484 120992603 7586 1.385258 2108 982s 2 1 2 1 141510003 247137334 7072 2.419824 2088 982s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 982s 1 2108 554484 120992603 7586 0.5116120 982s 2 2088 141510003 247137334 7072 0.1803011 982s Calculating (C1,C2) per segment... 982s Calculating (C1,C2) per segment...done 982s Number of segments: 2 982s Segmenting paired tumor-normal signals using Paired PSCBS...done 982s Post-segmenting TCNs... 982s Number of segments: 2 982s Number of chromosomes: 1 982s [1] 1 982s Chromosome 1 ('chr01') of 1... 982s Rows: 982s [1] 1 2 982s Number of segments: 2 982s TCN segment #1 ('1') of 2... 982s Nothing todo. Only one DH segmentation. Skipping. 982s TCN segment #1 ('1') of 2...done 982s TCN segment #2 ('2') of 2... 982s Nothing todo. Only one DH segmentation. Skipping. 982s TCN segment #2 ('2') of 2...done 982s Chromosome 1 ('chr01') of 1...done 982s Update (C1,C2) per segment... 982s Update (C1,C2) per segment...done 982s Post-segmenting TCNs...done 982s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 982s 1 1 1 1 554484 120992603 7586 1.385258 2108 982s 2 1 2 1 141510003 247137334 7072 2.419824 2088 982s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 982s 1 2108 554484 120992603 7586 0.5116120 0.3382717 1.046986 982s 2 2088 141510003 247137334 7072 0.1803011 0.9917635 1.428060 982s > print(fit) 982s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 982s 1 1 1 1 554484 120992603 7586 1.385258 2108 982s 2 1 2 1 141510003 247137334 7072 2.419824 2088 982s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 982s 1 2108 554484 120992603 7586 0.5116120 0.3382717 1.046986 982s 2 2088 141510003 247137334 7072 0.1803011 0.9917635 1.428060 982s chromosome tcnId dhId start end tcnNbrOfLoci tcnMean tcnNbrOfSNPs 982s 1 1 1 1 554484 120992603 7586 1.385258 2108 982s 2 1 2 1 141510003 247137334 7072 2.419824 2088 982s tcnNbrOfHets dhNbrOfLoci dhMean c1Mean c2Mean 982s 1 2108 7586 0.5116120 0.3382717 1.046986 982s 2 2088 7072 0.1803011 0.9917635 1.428060 982s > 982s > # Plot results 982s > dev.set(5L) 982s pdf 982s 2 982s > plotTracks(fit) 982s > abline(v=c(knownSegments$start, knownSegments$end)/1e6, lty=3) 982s > 982s > # Sanity check 982s > stopifnot(nbrOfSegments(fit) == nrow(knownSegments)) 982s > 982s > fit4 <- fit 982s > 982s > 982s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 982s > # Tiling multiple chromosomes 982s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 982s > # Simulate multiple chromosomes 982s > fit1 <- fit 982s > fit2 <- renameChromosomes(fit, from=1, to=2) 982s > fitM <- c(fit1, fit2) 982s > 982s > # Tile chromosomes 982s > fitT <- tileChromosomes(fitM) 982s > fitTb <- tileChromosomes(fitT) 982s > stopifnot(identical(fitTb, fitT)) 982s > 982s > # Plotting multiple chromosomes 982s > plotTracks(fitT) 982s > 983s autopkgtest [23:53:41]: test pkg-r-autopkgtest: -----------------------] 983s pkg-r-autopkgtest PASS 983s autopkgtest [23:53:41]: test pkg-r-autopkgtest: - - - - - - - - - - results - - - - - - - - - - 984s autopkgtest [23:53:42]: @@@@@@@@@@@@@@@@@@@@ summary 984s run-unit-test PASS 984s pkg-r-autopkgtest PASS