0s autopkgtest [13:37:31]: starting date and time: 2024-03-23 13:37:31+0000 0s autopkgtest [13:37:31]: git checkout: 4a1cd702 l/adt_testbed: don't blame the testbed for unsolvable build deps 0s autopkgtest [13:37:31]: host juju-7f2275-prod-proposed-migration-environment-2; command line: /home/ubuntu/autopkgtest/runner/autopkgtest --output-dir /tmp/autopkgtest-work.a_1_sltx/out --timeout-copy=6000 -a i386 --setup-commands /home/ubuntu/autopkgtest-cloud/worker-config-production/setup-canonical.sh --setup-commands /home/ubuntu/autopkgtest/setup-commands/setup-testbed --apt-pocket=proposed=src:r-base --apt-upgrade r-cran-pscbs --timeout-short=300 --timeout-copy=20000 --timeout-build=20000 --env=ADT_TEST_TRIGGERS=r-base/4.3.3-2build1 -- ssh -s /home/ubuntu/autopkgtest/ssh-setup/nova -- --flavor autopkgtest --security-groups autopkgtest-juju-7f2275-prod-proposed-migration-environment-2@lcy02-9.secgroup --name adt-noble-i386-r-cran-pscbs-20240323-133731-juju-7f2275-prod-proposed-migration-environment-2 --image adt/ubuntu-noble-amd64-server --keyname testbed-juju-7f2275-prod-proposed-migration-environment-2 --net-id=net_prod-proposed-migration -e TERM=linux -e ''"'"'http_proxy=http://squid.internal:3128'"'"'' -e ''"'"'https_proxy=http://squid.internal:3128'"'"'' -e ''"'"'no_proxy=127.0.0.1,127.0.1.1,login.ubuntu.com,localhost,localdomain,novalocal,internal,archive.ubuntu.com,ports.ubuntu.com,security.ubuntu.com,ddebs.ubuntu.com,changelogs.ubuntu.com,launchpadlibrarian.net,launchpadcontent.net,launchpad.net,10.24.0.0/24,keystone.ps5.canonical.com,objectstorage.prodstack5.canonical.com'"'"'' --mirror=http://ftpmaster.internal/ubuntu/ 353s autopkgtest [13:43:24]: testbed dpkg architecture: amd64 353s autopkgtest [13:43:24]: testbed apt version: 2.7.12 353s autopkgtest [13:43:24]: test architecture: i386 353s autopkgtest [13:43:24]: @@@@@@@@@@@@@@@@@@@@ test bed setup 354s Get:1 http://ftpmaster.internal/ubuntu noble-proposed InRelease [117 kB] 354s Get:2 http://ftpmaster.internal/ubuntu noble-proposed/universe Sources [3992 kB] 354s Get:3 http://ftpmaster.internal/ubuntu noble-proposed/main Sources [494 kB] 354s Get:4 http://ftpmaster.internal/ubuntu noble-proposed/multiverse Sources [56.9 kB] 354s Get:5 http://ftpmaster.internal/ubuntu noble-proposed/restricted Sources [6540 B] 354s Get:6 http://ftpmaster.internal/ubuntu noble-proposed/main i386 Packages [451 kB] 354s Get:7 http://ftpmaster.internal/ubuntu noble-proposed/main amd64 Packages [686 kB] 354s Get:8 http://ftpmaster.internal/ubuntu noble-proposed/main amd64 c-n-f Metadata [3508 B] 354s Get:9 http://ftpmaster.internal/ubuntu noble-proposed/restricted i386 Packages [6700 B] 354s Get:10 http://ftpmaster.internal/ubuntu noble-proposed/restricted amd64 Packages [30.5 kB] 354s Get:11 http://ftpmaster.internal/ubuntu noble-proposed/restricted amd64 c-n-f Metadata [116 B] 354s Get:12 http://ftpmaster.internal/ubuntu noble-proposed/universe i386 Packages [1299 kB] 354s Get:13 http://ftpmaster.internal/ubuntu noble-proposed/universe amd64 Packages [4402 kB] 354s Get:14 http://ftpmaster.internal/ubuntu noble-proposed/universe amd64 c-n-f Metadata [9396 B] 354s Get:15 http://ftpmaster.internal/ubuntu noble-proposed/multiverse amd64 Packages [96.1 kB] 354s Get:16 http://ftpmaster.internal/ubuntu noble-proposed/multiverse i386 Packages [27.1 kB] 354s Get:17 http://ftpmaster.internal/ubuntu noble-proposed/multiverse amd64 c-n-f Metadata [196 B] 357s Fetched 11.7 MB in 2s (7295 kB/s) 358s Reading package lists... 359s Reading package lists... 360s Building dependency tree... 360s Reading state information... 360s Calculating upgrade... 360s The following packages will be upgraded: 360s libc-bin libc6 locales 360s 3 upgraded, 0 newly installed, 0 to remove and 0 not upgraded. 360s Need to get 8176 kB of archives. 360s After this operation, 2048 B of additional disk space will be used. 360s Get:1 http://ftpmaster.internal/ubuntu noble/main amd64 libc6 amd64 2.39-0ubuntu6 [3262 kB] 360s Get:2 http://ftpmaster.internal/ubuntu noble/main amd64 libc-bin amd64 2.39-0ubuntu6 [682 kB] 360s Get:3 http://ftpmaster.internal/ubuntu noble/main amd64 locales all 2.39-0ubuntu6 [4232 kB] 361s Preconfiguring packages ... 361s Fetched 8176 kB in 0s (47.9 MB/s) 361s (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 ... 71864 files and directories currently installed.) 361s Preparing to unpack .../libc6_2.39-0ubuntu6_amd64.deb ... 361s Unpacking libc6:amd64 (2.39-0ubuntu6) over (2.39-0ubuntu2) ... 361s Setting up libc6:amd64 (2.39-0ubuntu6) ... 362s (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 ... 71864 files and directories currently installed.) 362s Preparing to unpack .../libc-bin_2.39-0ubuntu6_amd64.deb ... 362s Unpacking libc-bin (2.39-0ubuntu6) over (2.39-0ubuntu2) ... 362s Setting up libc-bin (2.39-0ubuntu6) ... 362s (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 ... 71864 files and directories currently installed.) 362s Preparing to unpack .../locales_2.39-0ubuntu6_all.deb ... 362s Unpacking locales (2.39-0ubuntu6) over (2.39-0ubuntu2) ... 362s Setting up locales (2.39-0ubuntu6) ... 363s Generating locales (this might take a while)... 365s en_US.UTF-8... done 365s Generation complete. 365s Processing triggers for man-db (2.12.0-3) ... 366s Reading package lists... 367s Building dependency tree... 367s Reading state information... 367s 0 upgraded, 0 newly installed, 0 to remove and 0 not upgraded. 367s sh: Attempting to set up Debian/Ubuntu apt sources automatically 367s sh: Distribution appears to be Ubuntu 368s Reading package lists... 368s Building dependency tree... 368s Reading state information... 368s eatmydata is already the newest version (131-1). 368s 0 upgraded, 0 newly installed, 0 to remove and 0 not upgraded. 368s Reading package lists... 368s Building dependency tree... 368s Reading state information... 369s dbus is already the newest version (1.14.10-4ubuntu1). 369s 0 upgraded, 0 newly installed, 0 to remove and 0 not upgraded. 369s Reading package lists... 369s Building dependency tree... 369s Reading state information... 369s rng-tools-debian is already the newest version (2.4). 369s 0 upgraded, 0 newly installed, 0 to remove and 0 not upgraded. 370s Reading package lists... 370s Building dependency tree... 370s Reading state information... 370s The following packages will be REMOVED: 370s cloud-init* python3-configobj* python3-debconf* 370s 0 upgraded, 0 newly installed, 3 to remove and 0 not upgraded. 370s After this operation, 3256 kB disk space will be freed. 370s (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 ... 71864 files and directories currently installed.) 370s Removing cloud-init (24.1.2-0ubuntu1) ... 373s Removing python3-configobj (5.0.8-3) ... 373s Removing python3-debconf (1.5.86) ... 373s Processing triggers for man-db (2.12.0-3) ... 373s (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 ... 71475 files and directories currently installed.) 373s Purging configuration files for cloud-init (24.1.2-0ubuntu1) ... 373s dpkg: warning: while removing cloud-init, directory '/etc/cloud/cloud.cfg.d' not empty so not removed 373s Processing triggers for rsyslog (8.2312.0-3ubuntu3) ... 373s invoke-rc.d: policy-rc.d denied execution of try-restart. 373s Reading package lists... 373s Building dependency tree... 373s Reading state information... 373s linux-generic is already the newest version (6.8.0-11.11+1). 373s 0 upgraded, 0 newly installed, 0 to remove and 0 not upgraded. 373s Hit:1 http://ftpmaster.internal/ubuntu noble InRelease 373s Hit:2 http://ftpmaster.internal/ubuntu noble-updates InRelease 373s Hit:3 http://ftpmaster.internal/ubuntu noble-security InRelease 375s Reading package lists... 375s Reading package lists... 375s Building dependency tree... 375s Reading state information... 376s Calculating upgrade... 376s 0 upgraded, 0 newly installed, 0 to remove and 0 not upgraded. 376s Reading package lists... 376s Building dependency tree... 376s Reading state information... 376s 0 upgraded, 0 newly installed, 0 to remove and 0 not upgraded. 376s autopkgtest [13:43:47]: rebooting testbed after setup commands that affected boot 404s autopkgtest [13:44:15]: testbed running kernel: Linux 6.8.0-11-generic #11-Ubuntu SMP PREEMPT_DYNAMIC Wed Feb 14 00:29:05 UTC 2024 404s autopkgtest [13:44:15]: @@@@@@@@@@@@@@@@@@@@ apt-source r-cran-pscbs 405s Get:1 http://ftpmaster.internal/ubuntu noble/universe r-cran-pscbs 0.66.0-2 (dsc) [2361 B] 405s Get:2 http://ftpmaster.internal/ubuntu noble/universe r-cran-pscbs 0.66.0-2 (tar) [3692 kB] 405s Get:3 http://ftpmaster.internal/ubuntu noble/universe r-cran-pscbs 0.66.0-2 (diff) [3744 B] 405s gpgv: Signature made Mon Nov 1 20:33:04 2021 UTC 405s gpgv: using RSA key 3E99A526F5DCC0CBBF1CEEA600BAE74B343369F1 405s gpgv: issuer "nilesh@debian.org" 405s gpgv: Can't check signature: No public key 405s dpkg-source: warning: cannot verify inline signature for ./r-cran-pscbs_0.66.0-2.dsc: no acceptable signature found 406s autopkgtest [13:44:17]: testing package r-cran-pscbs version 0.66.0-2 406s autopkgtest [13:44:17]: build not needed 406s autopkgtest [13:44:17]: test run-unit-test: preparing testbed 409s Note, using file '/tmp/autopkgtest.KUoiFr/1-autopkgtest-satdep.dsc' to get the build dependencies 409s Reading package lists... 409s Building dependency tree... 409s Reading state information... 409s Starting pkgProblemResolver with broken count: 0 409s Starting 2 pkgProblemResolver with broken count: 0 409s Done 410s The following NEW packages will be installed: 410s build-essential cpp cpp-13 cpp-13-x86-64-linux-gnu cpp-x86-64-linux-gnu 410s fontconfig fontconfig-config fonts-dejavu-core fonts-dejavu-mono 410s fonts-font-awesome fonts-glyphicons-halflings fonts-mathjax g++ g++-13 410s g++-13-x86-64-linux-gnu g++-x86-64-linux-gnu gcc gcc-13 410s gcc-13-x86-64-linux-gnu gcc-x86-64-linux-gnu javascript-common libasan8 410s libatomic1 libblas3 libc-dev-bin libc6-dev libcairo2 libcc1-0 libcrypt-dev 410s libdatrie1 libdeflate0 libfontconfig1 libgcc-13-dev libgfortran5 libgomp1 410s libgraphite2-3 libharfbuzz0b libhwasan0 libice6 libisl23 libitm1 libjbig0 410s libjpeg-turbo8 libjpeg8 libjs-bootstrap libjs-bootstrap4 libjs-d3 410s libjs-es5-shim libjs-highlight.js libjs-jquery libjs-jquery-datatables 410s libjs-jquery-selectize.js libjs-jquery-ui libjs-json libjs-mathjax 410s libjs-microplugin.js libjs-modernizr libjs-popper.js libjs-prettify 410s libjs-sifter.js libjs-twitter-bootstrap-datepicker liblapack3 liblerc4 410s liblsan0 liblua5.4-0 libmpc3 libpango-1.0-0 libpangocairo-1.0-0 410s libpangoft2-1.0-0 libpaper-utils libpaper1 libpixman-1-0 libquadmath0 410s libsharpyuv0 libsm6 libstdc++-13-dev libtcl8.6 libthai-data libthai0 410s libtiff6 libtk8.6 libtsan2 libubsan1 libwebp7 libxcb-render0 libxcb-shm0 410s libxft2 libxrender1 libxss1 libxt6 linux-libc-dev littler 410s node-bootstrap-sass node-html5shiv node-normalize.css pandoc pandoc-data 410s r-base-core r-bioc-aroma.light r-bioc-biocgenerics r-bioc-dnacopy 410s r-cran-acepack r-cran-backports r-cran-base64enc r-cran-bslib r-cran-cachem 410s r-cran-checkmate r-cran-chron r-cran-cli r-cran-cluster r-cran-codetools 410s r-cran-colorspace r-cran-commonmark r-cran-cpp11 r-cran-crayon 410s r-cran-data.table r-cran-deldir r-cran-digest r-cran-dplyr r-cran-ellipsis 410s r-cran-evaluate r-cran-fansi r-cran-farver r-cran-fastmap r-cran-fontawesome 410s r-cran-foreign r-cran-formula r-cran-fs r-cran-future r-cran-generics 410s r-cran-ggplot2 r-cran-globals r-cran-glue r-cran-gridextra r-cran-gtable 410s r-cran-highr r-cran-hmisc r-cran-htmltable r-cran-htmltools 410s r-cran-htmlwidgets r-cran-httpuv r-cran-interp r-cran-isoband r-cran-jpeg 410s r-cran-jquerylib r-cran-jsonlite r-cran-knitr r-cran-labeling r-cran-later 410s r-cran-lattice r-cran-latticeextra r-cran-lifecycle r-cran-listenv 410s r-cran-littler r-cran-magrittr r-cran-mass r-cran-matrix r-cran-matrixstats 410s r-cran-memoise r-cran-mgcv r-cran-mime r-cran-munsell r-cran-nlme 410s r-cran-nnet r-cran-parallelly r-cran-pillar r-cran-pkgconfig 410s r-cran-pkgkitten r-cran-png r-cran-promises r-cran-pscbs r-cran-purrr 410s r-cran-r.cache r-cran-r.methodss3 r-cran-r.oo r-cran-r.utils r-cran-r6 410s r-cran-rappdirs r-cran-rcolorbrewer r-cran-rcpp r-cran-rcppeigen 410s r-cran-rlang r-cran-rmarkdown r-cran-rpart r-cran-rstudioapi r-cran-sass 410s r-cran-scales r-cran-shiny r-cran-sourcetools r-cran-stringi r-cran-stringr 410s r-cran-survival r-cran-tibble r-cran-tidyr r-cran-tidyselect r-cran-tinytex 410s r-cran-utf8 r-cran-vctrs r-cran-viridis r-cran-viridislite r-cran-withr 410s r-cran-xfun r-cran-xtable r-cran-yaml rpcsvc-proto unzip x11-common 410s xdg-utils zip 410s 0 upgraded, 209 newly installed, 0 to remove and 0 not upgraded. 410s Need to get 229 MB of archives. 410s After this operation, 739 MB of additional disk space will be used. 410s Get:1 http://ftpmaster.internal/ubuntu noble/main amd64 libc-dev-bin amd64 2.39-0ubuntu6 [20.4 kB] 410s Get:2 http://ftpmaster.internal/ubuntu noble/main amd64 linux-libc-dev amd64 6.8.0-11.11 [1595 kB] 410s Get:3 http://ftpmaster.internal/ubuntu noble/main amd64 libcrypt-dev amd64 1:4.4.36-4 [128 kB] 410s Get:4 http://ftpmaster.internal/ubuntu noble/main amd64 rpcsvc-proto amd64 1.4.2-0ubuntu6 [68.5 kB] 410s Get:5 http://ftpmaster.internal/ubuntu noble/main amd64 libc6-dev amd64 2.39-0ubuntu6 [2126 kB] 410s Get:6 http://ftpmaster.internal/ubuntu noble/main amd64 libisl23 amd64 0.26-3 [741 kB] 410s Get:7 http://ftpmaster.internal/ubuntu noble/main amd64 libmpc3 amd64 1.3.1-1 [54.1 kB] 410s Get:8 http://ftpmaster.internal/ubuntu noble/main amd64 cpp-13-x86-64-linux-gnu amd64 13.2.0-17ubuntu2 [11.2 MB] 410s Get:9 http://ftpmaster.internal/ubuntu noble/main amd64 cpp-13 amd64 13.2.0-17ubuntu2 [1030 B] 410s Get:10 http://ftpmaster.internal/ubuntu noble/main amd64 cpp-x86-64-linux-gnu amd64 4:13.2.0-7ubuntu1 [5326 B] 410s Get:11 http://ftpmaster.internal/ubuntu noble/main amd64 cpp amd64 4:13.2.0-7ubuntu1 [22.4 kB] 410s Get:12 http://ftpmaster.internal/ubuntu noble/main amd64 libcc1-0 amd64 14-20240303-1ubuntu1 [47.7 kB] 410s Get:13 http://ftpmaster.internal/ubuntu noble/main amd64 libgomp1 amd64 14-20240303-1ubuntu1 [147 kB] 410s Get:14 http://ftpmaster.internal/ubuntu noble/main amd64 libitm1 amd64 14-20240303-1ubuntu1 [29.1 kB] 410s Get:15 http://ftpmaster.internal/ubuntu noble/main amd64 libatomic1 amd64 14-20240303-1ubuntu1 [10.4 kB] 410s Get:16 http://ftpmaster.internal/ubuntu noble/main amd64 libasan8 amd64 14-20240303-1ubuntu1 [3026 kB] 410s Get:17 http://ftpmaster.internal/ubuntu noble/main amd64 liblsan0 amd64 14-20240303-1ubuntu1 [1310 kB] 410s Get:18 http://ftpmaster.internal/ubuntu noble/main amd64 libtsan2 amd64 14-20240303-1ubuntu1 [2732 kB] 410s Get:19 http://ftpmaster.internal/ubuntu noble/main amd64 libubsan1 amd64 14-20240303-1ubuntu1 [1172 kB] 410s Get:20 http://ftpmaster.internal/ubuntu noble/main amd64 libhwasan0 amd64 14-20240303-1ubuntu1 [1629 kB] 410s Get:21 http://ftpmaster.internal/ubuntu noble/main amd64 libquadmath0 amd64 14-20240303-1ubuntu1 [155 kB] 410s Get:22 http://ftpmaster.internal/ubuntu noble/main amd64 libgcc-13-dev amd64 13.2.0-17ubuntu2 [2687 kB] 410s Get:23 http://ftpmaster.internal/ubuntu noble/main amd64 gcc-13-x86-64-linux-gnu amd64 13.2.0-17ubuntu2 [21.9 MB] 410s Get:24 http://ftpmaster.internal/ubuntu noble/main amd64 gcc-13 amd64 13.2.0-17ubuntu2 [477 kB] 410s Get:25 http://ftpmaster.internal/ubuntu noble/main amd64 gcc-x86-64-linux-gnu amd64 4:13.2.0-7ubuntu1 [1212 B] 410s Get:26 http://ftpmaster.internal/ubuntu noble/main amd64 gcc amd64 4:13.2.0-7ubuntu1 [5018 B] 410s Get:27 http://ftpmaster.internal/ubuntu noble/main amd64 libstdc++-13-dev amd64 13.2.0-17ubuntu2 [2340 kB] 410s Get:28 http://ftpmaster.internal/ubuntu noble/main amd64 g++-13-x86-64-linux-gnu amd64 13.2.0-17ubuntu2 [12.5 MB] 410s Get:29 http://ftpmaster.internal/ubuntu noble/main amd64 g++-13 amd64 13.2.0-17ubuntu2 [14.5 kB] 410s Get:30 http://ftpmaster.internal/ubuntu noble/main amd64 g++-x86-64-linux-gnu amd64 4:13.2.0-7ubuntu1 [964 B] 410s Get:31 http://ftpmaster.internal/ubuntu noble/main amd64 g++ amd64 4:13.2.0-7ubuntu1 [1100 B] 410s Get:32 http://ftpmaster.internal/ubuntu noble/main amd64 build-essential amd64 12.10ubuntu1 [4928 B] 410s Get:33 http://ftpmaster.internal/ubuntu noble/main amd64 fonts-dejavu-mono all 2.37-8 [502 kB] 410s Get:34 http://ftpmaster.internal/ubuntu noble/main amd64 fonts-dejavu-core all 2.37-8 [835 kB] 410s Get:35 http://ftpmaster.internal/ubuntu noble/main amd64 fontconfig-config amd64 2.15.0-1ubuntu1 [36.9 kB] 410s Get:36 http://ftpmaster.internal/ubuntu noble/main amd64 libfontconfig1 amd64 2.15.0-1ubuntu1 [139 kB] 410s Get:37 http://ftpmaster.internal/ubuntu noble/main amd64 fontconfig amd64 2.15.0-1ubuntu1 [180 kB] 410s Get:38 http://ftpmaster.internal/ubuntu noble/main amd64 fonts-font-awesome all 5.0.10+really4.7.0~dfsg-4.1 [516 kB] 410s Get:39 http://ftpmaster.internal/ubuntu noble/universe amd64 fonts-glyphicons-halflings all 1.009~3.4.1+dfsg-3 [118 kB] 410s Get:40 http://ftpmaster.internal/ubuntu noble/main amd64 fonts-mathjax all 2.7.9+dfsg-1 [2208 kB] 410s Get:41 http://ftpmaster.internal/ubuntu noble/main amd64 javascript-common all 11+nmu1 [5936 B] 410s Get:42 http://ftpmaster.internal/ubuntu noble/main amd64 libblas3 amd64 3.12.0-3 [238 kB] 410s Get:43 http://ftpmaster.internal/ubuntu noble/main amd64 libpixman-1-0 amd64 0.42.2-1 [268 kB] 410s Get:44 http://ftpmaster.internal/ubuntu noble/main amd64 libxcb-render0 amd64 1.15-1 [16.3 kB] 410s Get:45 http://ftpmaster.internal/ubuntu noble/main amd64 libxcb-shm0 amd64 1.15-1 [5740 B] 410s Get:46 http://ftpmaster.internal/ubuntu noble/main amd64 libxrender1 amd64 1:0.9.10-1.1 [20.0 kB] 410s Get:47 http://ftpmaster.internal/ubuntu noble/main amd64 libcairo2 amd64 1.18.0-1 [572 kB] 410s Get:48 http://ftpmaster.internal/ubuntu noble/main amd64 libdatrie1 amd64 0.2.13-3 [20.9 kB] 410s Get:49 http://ftpmaster.internal/ubuntu noble/main amd64 libdeflate0 amd64 1.19-1 [43.7 kB] 410s Get:50 http://ftpmaster.internal/ubuntu noble/main amd64 libgfortran5 amd64 14-20240303-1ubuntu1 [924 kB] 410s Get:51 http://ftpmaster.internal/ubuntu noble/main amd64 libgraphite2-3 amd64 1.3.14-2 [83.1 kB] 410s Get:52 http://ftpmaster.internal/ubuntu noble/main amd64 libharfbuzz0b amd64 8.3.0-2 [469 kB] 410s Get:53 http://ftpmaster.internal/ubuntu noble/main amd64 x11-common all 1:7.7+23ubuntu2 [23.4 kB] 410s Get:54 http://ftpmaster.internal/ubuntu noble/main amd64 libice6 amd64 2:1.0.10-1build2 [42.6 kB] 410s Get:55 http://ftpmaster.internal/ubuntu noble/main amd64 libjpeg-turbo8 amd64 2.1.5-2ubuntu1 [147 kB] 410s Get:56 http://ftpmaster.internal/ubuntu noble/main amd64 libjpeg8 amd64 8c-2ubuntu11 [2148 B] 410s Get:57 http://ftpmaster.internal/ubuntu noble/universe amd64 libjs-bootstrap all 3.4.1+dfsg-3 [129 kB] 410s Get:58 http://ftpmaster.internal/ubuntu noble/universe amd64 libjs-popper.js all 1.16.1+ds-6 [54.1 kB] 410s Get:59 http://ftpmaster.internal/ubuntu noble/universe amd64 libjs-bootstrap4 all 4.6.1+dfsg1-4 [537 kB] 410s Get:60 http://ftpmaster.internal/ubuntu noble/universe amd64 libjs-d3 all 3.5.17-4 [132 kB] 410s Get:61 http://ftpmaster.internal/ubuntu noble/universe amd64 libjs-es5-shim all 4.6.7-2 [39.8 kB] 410s Get:62 http://ftpmaster.internal/ubuntu noble/universe amd64 libjs-highlight.js all 9.18.5+dfsg1-2 [385 kB] 410s Get:63 http://ftpmaster.internal/ubuntu noble/main amd64 libjs-jquery all 3.6.1+dfsg+~3.5.14-1 [328 kB] 410s Get:64 http://ftpmaster.internal/ubuntu noble/universe amd64 libjs-jquery-datatables all 1.11.5+dfsg-2 [146 kB] 410s Get:65 http://ftpmaster.internal/ubuntu noble/universe amd64 libjs-sifter.js all 0.6.0+dfsg-3 [12.6 kB] 410s Get:66 http://ftpmaster.internal/ubuntu noble/universe amd64 libjs-microplugin.js all 0.0.3+dfsg-1.1 [3712 B] 410s Get:67 http://ftpmaster.internal/ubuntu noble/universe amd64 libjs-jquery-selectize.js all 0.12.6+dfsg-1.1 [51.0 kB] 410s Get:68 http://ftpmaster.internal/ubuntu noble/universe amd64 libjs-jquery-ui all 1.13.2+dfsg-1 [252 kB] 410s Get:69 http://ftpmaster.internal/ubuntu noble/universe amd64 libjs-json all 0~20221030+~1.0.8-1 [20.6 kB] 410s Get:70 http://ftpmaster.internal/ubuntu noble/universe amd64 libjs-prettify all 2015.12.04+dfsg-1.1 [39.3 kB] 410s Get:71 http://ftpmaster.internal/ubuntu noble/main amd64 liblapack3 amd64 3.12.0-3 [2649 kB] 410s Get:72 http://ftpmaster.internal/ubuntu noble/main amd64 liblerc4 amd64 4.0.0+ds-4ubuntu1 [184 kB] 410s Get:73 http://ftpmaster.internal/ubuntu noble/main amd64 liblua5.4-0 amd64 5.4.6-3 [166 kB] 410s Get:74 http://ftpmaster.internal/ubuntu noble/main amd64 libthai-data all 0.1.29-2 [158 kB] 410s Get:75 http://ftpmaster.internal/ubuntu noble/main amd64 libthai0 amd64 0.1.29-2 [18.8 kB] 410s Get:76 http://ftpmaster.internal/ubuntu noble/main amd64 libpango-1.0-0 amd64 1.51.0+ds-4 [228 kB] 410s Get:77 http://ftpmaster.internal/ubuntu noble/main amd64 libpangoft2-1.0-0 amd64 1.51.0+ds-4 [42.1 kB] 410s Get:78 http://ftpmaster.internal/ubuntu noble/main amd64 libpangocairo-1.0-0 amd64 1.51.0+ds-4 [29.0 kB] 410s Get:79 http://ftpmaster.internal/ubuntu noble/main amd64 libpaper1 amd64 1.1.29 [13.4 kB] 410s Get:80 http://ftpmaster.internal/ubuntu noble/main amd64 libpaper-utils amd64 1.1.29 [8658 B] 410s Get:81 http://ftpmaster.internal/ubuntu noble/main amd64 libsharpyuv0 amd64 1.3.2-0.4 [15.6 kB] 410s Get:82 http://ftpmaster.internal/ubuntu noble/main amd64 libsm6 amd64 2:1.2.3-1build2 [16.7 kB] 410s Get:83 http://ftpmaster.internal/ubuntu noble/main amd64 libtcl8.6 amd64 8.6.13+dfsg-2 [984 kB] 410s Get:84 http://ftpmaster.internal/ubuntu noble/main amd64 libjbig0 amd64 2.1-6.1ubuntu1 [29.3 kB] 410s Get:85 http://ftpmaster.internal/ubuntu noble/main amd64 libwebp7 amd64 1.3.2-0.4 [230 kB] 410s Get:86 http://ftpmaster.internal/ubuntu noble/main amd64 libtiff6 amd64 4.5.1+git230720-3ubuntu1 [232 kB] 410s Get:87 http://ftpmaster.internal/ubuntu noble/main amd64 libxft2 amd64 2.3.6-1 [44.5 kB] 410s Get:88 http://ftpmaster.internal/ubuntu noble/main amd64 libxss1 amd64 1:1.2.3-1build2 [8476 B] 410s Get:89 http://ftpmaster.internal/ubuntu noble/main amd64 libtk8.6 amd64 8.6.14-1 [779 kB] 410s Get:90 http://ftpmaster.internal/ubuntu noble/main amd64 libxt6 amd64 1:1.2.1-1.1 [173 kB] 410s Get:91 http://ftpmaster.internal/ubuntu noble/main amd64 zip amd64 3.0-13 [176 kB] 410s Get:92 http://ftpmaster.internal/ubuntu noble/main amd64 unzip amd64 6.0-28ubuntu3 [174 kB] 410s Get:93 http://ftpmaster.internal/ubuntu noble/main amd64 xdg-utils all 1.1.3-4.1ubuntu3 [62.0 kB] 410s Get:94 http://ftpmaster.internal/ubuntu noble/universe amd64 r-base-core amd64 4.3.2-1build1 [27.0 MB] 411s Get:95 http://ftpmaster.internal/ubuntu noble/universe amd64 r-cran-littler amd64 0.3.19-1 [94.1 kB] 411s Get:96 http://ftpmaster.internal/ubuntu noble/universe amd64 littler all 0.3.19-1 [2472 B] 411s Get:97 http://ftpmaster.internal/ubuntu noble/universe amd64 node-bootstrap-sass all 3.4.3-2 [187 kB] 411s Get:98 http://ftpmaster.internal/ubuntu noble/universe amd64 node-html5shiv all 3.7.3+dfsg-5 [13.5 kB] 411s Get:99 http://ftpmaster.internal/ubuntu noble/universe amd64 node-normalize.css all 8.0.1-5 [10.8 kB] 411s Get:100 http://ftpmaster.internal/ubuntu noble/universe amd64 pandoc-data all 3.1.3-1 [92.4 kB] 411s Get:101 http://ftpmaster.internal/ubuntu noble/universe amd64 pandoc amd64 3.1.3+ds-2 [26.9 MB] 411s Get:102 http://ftpmaster.internal/ubuntu noble/universe amd64 r-bioc-biocgenerics all 0.48.1-2 [595 kB] 411s Get:103 http://ftpmaster.internal/ubuntu noble/universe amd64 r-cran-r.methodss3 all 1.8.2-1 [84.0 kB] 411s Get:104 http://ftpmaster.internal/ubuntu noble/universe amd64 r-cran-r.oo all 1.26.0-1 [955 kB] 411s Get:105 http://ftpmaster.internal/ubuntu noble/universe amd64 r-cran-r.utils all 2.12.3-1 [1386 kB] 411s Get:106 http://ftpmaster.internal/ubuntu noble/universe amd64 r-cran-matrixstats amd64 1.2.0-1 [488 kB] 411s Get:107 http://ftpmaster.internal/ubuntu noble/universe amd64 r-bioc-aroma.light all 3.32.0-1 [576 kB] 411s Get:108 http://ftpmaster.internal/ubuntu noble/universe amd64 r-bioc-dnacopy amd64 1.76.0-1 [380 kB] 411s Get:109 http://ftpmaster.internal/ubuntu noble/universe amd64 r-cran-acepack amd64 1.4.2-1 [61.3 kB] 411s Get:110 http://ftpmaster.internal/ubuntu noble/universe amd64 r-cran-backports amd64 1.4.1-1 [101 kB] 411s Get:111 http://ftpmaster.internal/ubuntu noble/universe amd64 r-cran-base64enc amd64 0.1-3-3 [27.6 kB] 411s Get:112 http://ftpmaster.internal/ubuntu noble/universe amd64 r-cran-rlang amd64 1.1.3-1 [1663 kB] 411s Get:113 http://ftpmaster.internal/ubuntu noble/universe amd64 r-cran-fastmap amd64 1.1.1-1 [70.5 kB] 411s Get:114 http://ftpmaster.internal/ubuntu noble/universe amd64 r-cran-cachem amd64 1.0.8-1 [72.1 kB] 411s Get:115 http://ftpmaster.internal/ubuntu noble/universe amd64 r-cran-digest amd64 0.6.34-1 [186 kB] 411s Get:116 http://ftpmaster.internal/ubuntu noble/universe amd64 r-cran-ellipsis amd64 0.3.2-2 [35.6 kB] 411s Get:117 http://ftpmaster.internal/ubuntu noble/universe amd64 r-cran-htmltools amd64 0.5.7-1 [369 kB] 411s Get:118 http://ftpmaster.internal/ubuntu noble/universe amd64 r-cran-jquerylib all 0.1.4+dfsg-4 [13.5 kB] 411s Get:119 http://ftpmaster.internal/ubuntu noble/universe amd64 r-cran-jsonlite amd64 1.8.8+dfsg-1 [441 kB] 411s Get:120 http://ftpmaster.internal/ubuntu noble/universe amd64 r-cran-cli amd64 3.6.2-1 [1380 kB] 411s Get:121 http://ftpmaster.internal/ubuntu noble/universe amd64 r-cran-glue amd64 1.7.0-1 [154 kB] 411s Get:122 http://ftpmaster.internal/ubuntu noble/universe amd64 r-cran-lifecycle all 1.0.4+dfsg-1 [110 kB] 411s Get:123 http://ftpmaster.internal/ubuntu noble/universe amd64 r-cran-memoise all 2.0.1-1 [53.9 kB] 411s Get:124 http://ftpmaster.internal/ubuntu noble/universe amd64 r-cran-mime amd64 0.12-1 [35.8 kB] 411s Get:125 http://ftpmaster.internal/ubuntu noble/universe amd64 r-cran-fs amd64 1.6.3+dfsg-1 [229 kB] 411s Get:126 http://ftpmaster.internal/ubuntu noble/universe amd64 r-cran-r6 all 2.5.1-1 [99.0 kB] 411s Get:127 http://ftpmaster.internal/ubuntu noble/universe amd64 r-cran-rappdirs amd64 0.3.3-1 [47.5 kB] 411s Get:128 http://ftpmaster.internal/ubuntu noble/universe amd64 r-cran-sass amd64 0.4.8+dfsg-1 [996 kB] 411s Get:129 http://ftpmaster.internal/ubuntu noble/universe amd64 r-cran-bslib all 0.6.1+dfsg-1 [5138 kB] 411s Get:130 http://ftpmaster.internal/ubuntu noble/universe amd64 r-cran-checkmate amd64 2.3.1-1 [713 kB] 411s Get:131 http://ftpmaster.internal/ubuntu noble/universe amd64 r-cran-chron amd64 2.3-61-2 [186 kB] 411s Get:132 http://ftpmaster.internal/ubuntu noble/universe amd64 r-cran-cluster amd64 2.1.6-1 [554 kB] 411s Get:133 http://ftpmaster.internal/ubuntu noble/universe amd64 r-cran-codetools all 0.2-19-1 [90.5 kB] 411s Get:134 http://ftpmaster.internal/ubuntu noble/universe amd64 r-cran-colorspace amd64 2.1-0+dfsg-1 [1541 kB] 411s Get:135 http://ftpmaster.internal/ubuntu noble/universe amd64 r-cran-commonmark amd64 1.9.1-1 [131 kB] 411s Get:136 http://ftpmaster.internal/ubuntu noble/universe amd64 r-cran-cpp11 all 0.4.7-1 [266 kB] 411s Get:137 http://ftpmaster.internal/ubuntu noble/universe amd64 r-cran-crayon all 1.5.2-1 [164 kB] 411s Get:138 http://ftpmaster.internal/ubuntu noble/universe amd64 r-cran-data.table amd64 1.14.10+dfsg-1 [1837 kB] 411s Get:139 http://ftpmaster.internal/ubuntu noble/universe amd64 r-cran-deldir amd64 2.0-4-1 [270 kB] 411s Get:140 http://ftpmaster.internal/ubuntu noble/universe amd64 r-cran-generics all 0.1.3-1 [81.3 kB] 411s Get:141 http://ftpmaster.internal/ubuntu noble/universe amd64 r-cran-magrittr amd64 2.0.3-1 [154 kB] 411s Get:142 http://ftpmaster.internal/ubuntu noble/universe amd64 r-cran-fansi amd64 1.0.5-1 [619 kB] 411s Get:143 http://ftpmaster.internal/ubuntu noble/universe amd64 r-cran-utf8 amd64 1.2.4-1 [140 kB] 411s Get:144 http://ftpmaster.internal/ubuntu noble/universe amd64 r-cran-vctrs amd64 0.6.5-1 [1335 kB] 411s Get:145 http://ftpmaster.internal/ubuntu noble/universe amd64 r-cran-pillar all 1.9.0+dfsg-1 [464 kB] 411s Get:146 http://ftpmaster.internal/ubuntu noble/universe amd64 r-cran-pkgconfig all 2.0.3-2build1 [19.7 kB] 411s Get:147 http://ftpmaster.internal/ubuntu noble/universe amd64 r-cran-tibble amd64 3.2.1+dfsg-2 [415 kB] 411s Get:148 http://ftpmaster.internal/ubuntu noble/universe amd64 r-cran-withr all 2.5.0-1 [225 kB] 411s Get:149 http://ftpmaster.internal/ubuntu noble/universe amd64 r-cran-tidyselect amd64 1.2.0+dfsg-1 [218 kB] 411s Get:150 http://ftpmaster.internal/ubuntu noble/universe amd64 r-cran-dplyr amd64 1.1.4-1 [1515 kB] 411s Get:151 http://ftpmaster.internal/ubuntu noble/universe amd64 r-cran-evaluate all 0.23-1 [90.2 kB] 411s Get:152 http://ftpmaster.internal/ubuntu noble/universe amd64 r-cran-farver amd64 2.1.1-1 [1353 kB] 411s Get:153 http://ftpmaster.internal/ubuntu noble/universe amd64 r-cran-fontawesome all 0.5.2-1 [1300 kB] 411s Get:154 http://ftpmaster.internal/ubuntu noble/universe amd64 r-cran-foreign amd64 0.8.86-1 [242 kB] 411s Get:155 http://ftpmaster.internal/ubuntu noble/universe amd64 r-cran-formula all 1.2-5-1 [158 kB] 411s Get:156 http://ftpmaster.internal/ubuntu noble/universe amd64 r-cran-globals all 0.16.2-1 [117 kB] 411s Get:157 http://ftpmaster.internal/ubuntu noble/universe amd64 r-cran-listenv all 0.9.1+dfsg-1 [112 kB] 411s Get:158 http://ftpmaster.internal/ubuntu noble/universe amd64 r-cran-parallelly amd64 1.37.1-1 [365 kB] 411s Get:159 http://ftpmaster.internal/ubuntu noble/universe amd64 r-cran-future all 1.33.1+dfsg-1 [634 kB] 411s Get:160 http://ftpmaster.internal/ubuntu noble/universe amd64 r-cran-gtable all 0.3.4+dfsg-1 [191 kB] 411s Get:161 http://ftpmaster.internal/ubuntu noble/universe amd64 r-cran-isoband amd64 0.2.7-1 [1481 kB] 411s Get:162 http://ftpmaster.internal/ubuntu noble/universe amd64 r-cran-mass amd64 7.3-60.0.1-1 [1119 kB] 411s Get:163 http://ftpmaster.internal/ubuntu noble/universe amd64 r-cran-lattice amd64 0.22-5-1 [1342 kB] 411s Get:164 http://ftpmaster.internal/ubuntu noble/universe amd64 r-cran-nlme amd64 3.1.164-1 [2260 kB] 411s Get:165 http://ftpmaster.internal/ubuntu noble/universe amd64 r-cran-matrix amd64 1.6-5-1 [3830 kB] 411s Get:166 http://ftpmaster.internal/ubuntu noble/universe amd64 r-cran-mgcv amd64 1.9-1-1 [3252 kB] 411s Get:167 http://ftpmaster.internal/ubuntu noble/universe amd64 r-cran-labeling all 0.4.3-1 [62.1 kB] 411s Get:168 http://ftpmaster.internal/ubuntu noble/universe amd64 r-cran-munsell all 0.5.0-2build1 [208 kB] 411s Get:169 http://ftpmaster.internal/ubuntu noble/universe amd64 r-cran-rcolorbrewer all 1.1-3-1build1 [55.4 kB] 411s Get:170 http://ftpmaster.internal/ubuntu noble/universe amd64 r-cran-viridislite all 0.4.2-2 [1088 kB] 411s Get:171 http://ftpmaster.internal/ubuntu noble/universe amd64 r-cran-scales all 1.3.0-1 [603 kB] 411s Get:172 http://ftpmaster.internal/ubuntu noble/universe amd64 r-cran-ggplot2 all 3.4.4+dfsg-1 [3411 kB] 411s Get:173 http://ftpmaster.internal/ubuntu noble/universe amd64 r-cran-gridextra all 2.3-3build1 [1024 kB] 411s Get:174 http://ftpmaster.internal/ubuntu noble/universe amd64 r-cran-xfun amd64 0.41+dfsg-1 [415 kB] 411s Get:175 http://ftpmaster.internal/ubuntu noble/universe amd64 r-cran-highr all 0.10+dfsg-1 [38.3 kB] 411s Get:176 http://ftpmaster.internal/ubuntu noble/universe amd64 r-cran-survival amd64 3.5-8-1 [6120 kB] 411s Get:177 http://ftpmaster.internal/ubuntu noble/universe amd64 r-cran-rpart amd64 4.1.23-1 [661 kB] 411s Get:178 http://ftpmaster.internal/ubuntu noble/universe amd64 r-cran-nnet amd64 7.3-19-2 [112 kB] 411s Get:179 http://ftpmaster.internal/ubuntu noble/universe amd64 r-cran-stringi amd64 1.8.3-1 [873 kB] 411s Get:180 http://ftpmaster.internal/ubuntu noble/universe amd64 r-cran-stringr all 1.5.1-1 [290 kB] 411s Get:181 http://ftpmaster.internal/ubuntu noble/universe amd64 r-cran-yaml amd64 2.3.8-1 [108 kB] 411s Get:182 http://ftpmaster.internal/ubuntu noble/main amd64 libjs-mathjax all 2.7.9+dfsg-1 [5665 kB] 411s Get:183 http://ftpmaster.internal/ubuntu noble/universe amd64 r-cran-knitr all 1.45+dfsg-1 [917 kB] 411s Get:184 http://ftpmaster.internal/ubuntu noble/universe amd64 r-cran-tinytex all 0.49-1 [141 kB] 411s Get:185 http://ftpmaster.internal/ubuntu noble/universe amd64 libjs-modernizr all 2.6.2+ds1-5 [48.3 kB] 411s Get:186 http://ftpmaster.internal/ubuntu noble/universe amd64 r-cran-pkgkitten all 0.2.3-1 [25.1 kB] 411s Get:187 http://ftpmaster.internal/ubuntu noble/universe amd64 r-cran-rcpp amd64 1.0.12-1 [1981 kB] 411s Get:188 http://ftpmaster.internal/ubuntu noble/universe amd64 r-cran-later amd64 1.3.2+dfsg-1 [123 kB] 411s Get:189 http://ftpmaster.internal/ubuntu noble/universe amd64 r-cran-promises amd64 1.2.1+dfsg-1 [284 kB] 411s Get:190 http://ftpmaster.internal/ubuntu noble/universe amd64 r-cran-httpuv amd64 1.6.14+dfsg-1 [510 kB] 411s Get:191 http://ftpmaster.internal/ubuntu noble/universe amd64 r-cran-xtable all 1:1.8-4-2 [689 kB] 411s Get:192 http://ftpmaster.internal/ubuntu noble/universe amd64 r-cran-sourcetools amd64 0.1.7-1-1 [48.1 kB] 411s Get:193 http://ftpmaster.internal/ubuntu noble/universe amd64 libjs-twitter-bootstrap-datepicker all 1.3.1+dfsg1-4.1 [28.5 kB] 411s Get:194 http://ftpmaster.internal/ubuntu noble/universe amd64 r-cran-shiny all 1.8.0+dfsg-1 [2762 kB] 411s Get:195 http://ftpmaster.internal/ubuntu noble/universe amd64 r-cran-rmarkdown all 2.25+dfsg-3 [1481 kB] 411s Get:196 http://ftpmaster.internal/ubuntu noble/universe amd64 r-cran-htmlwidgets all 1.6.4+dfsg-1 [123 kB] 411s Get:197 http://ftpmaster.internal/ubuntu noble/universe amd64 r-cran-rstudioapi all 0.15.0-1 [277 kB] 411s Get:198 http://ftpmaster.internal/ubuntu noble/universe amd64 r-cran-purrr amd64 1.0.2-1 [502 kB] 411s Get:199 http://ftpmaster.internal/ubuntu noble/universe amd64 r-cran-tidyr amd64 1.3.1-1 [1156 kB] 411s Get:200 http://ftpmaster.internal/ubuntu noble/universe amd64 r-cran-htmltable all 2.4.2-1 [381 kB] 411s Get:201 http://ftpmaster.internal/ubuntu noble/universe amd64 r-cran-viridis all 0.6.5-1 [2770 kB] 411s Get:202 http://ftpmaster.internal/ubuntu noble/universe amd64 r-cran-png amd64 0.1-8-1 [40.5 kB] 411s Get:203 http://ftpmaster.internal/ubuntu noble/universe amd64 r-cran-jpeg amd64 0.1-10-1 [31.4 kB] 411s Get:204 http://ftpmaster.internal/ubuntu noble/universe amd64 r-cran-rcppeigen amd64 0.3.3.9.4-1 [1189 kB] 412s Get:205 http://ftpmaster.internal/ubuntu noble/universe amd64 r-cran-interp amd64 1.1-6-1 [1454 kB] 412s Get:206 http://ftpmaster.internal/ubuntu noble/universe amd64 r-cran-latticeextra all 0.6-30-1 [2198 kB] 412s Get:207 http://ftpmaster.internal/ubuntu noble/universe amd64 r-cran-hmisc amd64 5.1-1-1 [3491 kB] 412s Get:208 http://ftpmaster.internal/ubuntu noble/universe amd64 r-cran-r.cache all 0.16.0-1 [113 kB] 412s Get:209 http://ftpmaster.internal/ubuntu noble/universe amd64 r-cran-pscbs all 0.66.0-2 [4345 kB] 412s Preconfiguring packages ... 412s Fetched 229 MB in 2s (112 MB/s) 412s Selecting previously unselected package libc-dev-bin. 412s (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 ... 71420 files and directories currently installed.) 412s Preparing to unpack .../000-libc-dev-bin_2.39-0ubuntu6_amd64.deb ... 412s Unpacking libc-dev-bin (2.39-0ubuntu6) ... 412s Selecting previously unselected package linux-libc-dev:amd64. 412s Preparing to unpack .../001-linux-libc-dev_6.8.0-11.11_amd64.deb ... 412s Unpacking linux-libc-dev:amd64 (6.8.0-11.11) ... 413s Selecting previously unselected package libcrypt-dev:amd64. 413s Preparing to unpack .../002-libcrypt-dev_1%3a4.4.36-4_amd64.deb ... 413s Unpacking libcrypt-dev:amd64 (1:4.4.36-4) ... 413s Selecting previously unselected package rpcsvc-proto. 413s Preparing to unpack .../003-rpcsvc-proto_1.4.2-0ubuntu6_amd64.deb ... 413s Unpacking rpcsvc-proto (1.4.2-0ubuntu6) ... 413s Selecting previously unselected package libc6-dev:amd64. 413s Preparing to unpack .../004-libc6-dev_2.39-0ubuntu6_amd64.deb ... 413s Unpacking libc6-dev:amd64 (2.39-0ubuntu6) ... 413s Selecting previously unselected package libisl23:amd64. 413s Preparing to unpack .../005-libisl23_0.26-3_amd64.deb ... 413s Unpacking libisl23:amd64 (0.26-3) ... 413s Selecting previously unselected package libmpc3:amd64. 413s Preparing to unpack .../006-libmpc3_1.3.1-1_amd64.deb ... 413s Unpacking libmpc3:amd64 (1.3.1-1) ... 413s Selecting previously unselected package cpp-13-x86-64-linux-gnu. 413s Preparing to unpack .../007-cpp-13-x86-64-linux-gnu_13.2.0-17ubuntu2_amd64.deb ... 413s Unpacking cpp-13-x86-64-linux-gnu (13.2.0-17ubuntu2) ... 413s Selecting previously unselected package cpp-13. 413s Preparing to unpack .../008-cpp-13_13.2.0-17ubuntu2_amd64.deb ... 413s Unpacking cpp-13 (13.2.0-17ubuntu2) ... 413s Selecting previously unselected package cpp-x86-64-linux-gnu. 413s Preparing to unpack .../009-cpp-x86-64-linux-gnu_4%3a13.2.0-7ubuntu1_amd64.deb ... 413s Unpacking cpp-x86-64-linux-gnu (4:13.2.0-7ubuntu1) ... 413s Selecting previously unselected package cpp. 413s Preparing to unpack .../010-cpp_4%3a13.2.0-7ubuntu1_amd64.deb ... 413s Unpacking cpp (4:13.2.0-7ubuntu1) ... 413s Selecting previously unselected package libcc1-0:amd64. 413s Preparing to unpack .../011-libcc1-0_14-20240303-1ubuntu1_amd64.deb ... 413s Unpacking libcc1-0:amd64 (14-20240303-1ubuntu1) ... 413s Selecting previously unselected package libgomp1:amd64. 413s Preparing to unpack .../012-libgomp1_14-20240303-1ubuntu1_amd64.deb ... 413s Unpacking libgomp1:amd64 (14-20240303-1ubuntu1) ... 413s Selecting previously unselected package libitm1:amd64. 413s Preparing to unpack .../013-libitm1_14-20240303-1ubuntu1_amd64.deb ... 413s Unpacking libitm1:amd64 (14-20240303-1ubuntu1) ... 413s Selecting previously unselected package libatomic1:amd64. 413s Preparing to unpack .../014-libatomic1_14-20240303-1ubuntu1_amd64.deb ... 413s Unpacking libatomic1:amd64 (14-20240303-1ubuntu1) ... 413s Selecting previously unselected package libasan8:amd64. 413s Preparing to unpack .../015-libasan8_14-20240303-1ubuntu1_amd64.deb ... 413s Unpacking libasan8:amd64 (14-20240303-1ubuntu1) ... 413s Selecting previously unselected package liblsan0:amd64. 413s Preparing to unpack .../016-liblsan0_14-20240303-1ubuntu1_amd64.deb ... 413s Unpacking liblsan0:amd64 (14-20240303-1ubuntu1) ... 413s Selecting previously unselected package libtsan2:amd64. 413s Preparing to unpack .../017-libtsan2_14-20240303-1ubuntu1_amd64.deb ... 413s Unpacking libtsan2:amd64 (14-20240303-1ubuntu1) ... 414s Selecting previously unselected package libubsan1:amd64. 414s Preparing to unpack .../018-libubsan1_14-20240303-1ubuntu1_amd64.deb ... 414s Unpacking libubsan1:amd64 (14-20240303-1ubuntu1) ... 414s Selecting previously unselected package libhwasan0:amd64. 414s Preparing to unpack .../019-libhwasan0_14-20240303-1ubuntu1_amd64.deb ... 414s Unpacking libhwasan0:amd64 (14-20240303-1ubuntu1) ... 414s Selecting previously unselected package libquadmath0:amd64. 414s Preparing to unpack .../020-libquadmath0_14-20240303-1ubuntu1_amd64.deb ... 414s Unpacking libquadmath0:amd64 (14-20240303-1ubuntu1) ... 414s Selecting previously unselected package libgcc-13-dev:amd64. 414s Preparing to unpack .../021-libgcc-13-dev_13.2.0-17ubuntu2_amd64.deb ... 414s Unpacking libgcc-13-dev:amd64 (13.2.0-17ubuntu2) ... 414s Selecting previously unselected package gcc-13-x86-64-linux-gnu. 414s Preparing to unpack .../022-gcc-13-x86-64-linux-gnu_13.2.0-17ubuntu2_amd64.deb ... 414s Unpacking gcc-13-x86-64-linux-gnu (13.2.0-17ubuntu2) ... 414s Selecting previously unselected package gcc-13. 414s Preparing to unpack .../023-gcc-13_13.2.0-17ubuntu2_amd64.deb ... 414s Unpacking gcc-13 (13.2.0-17ubuntu2) ... 414s Selecting previously unselected package gcc-x86-64-linux-gnu. 414s Preparing to unpack .../024-gcc-x86-64-linux-gnu_4%3a13.2.0-7ubuntu1_amd64.deb ... 414s Unpacking gcc-x86-64-linux-gnu (4:13.2.0-7ubuntu1) ... 414s Selecting previously unselected package gcc. 414s Preparing to unpack .../025-gcc_4%3a13.2.0-7ubuntu1_amd64.deb ... 414s Unpacking gcc (4:13.2.0-7ubuntu1) ... 414s Selecting previously unselected package libstdc++-13-dev:amd64. 414s Preparing to unpack .../026-libstdc++-13-dev_13.2.0-17ubuntu2_amd64.deb ... 414s Unpacking libstdc++-13-dev:amd64 (13.2.0-17ubuntu2) ... 414s Selecting previously unselected package g++-13-x86-64-linux-gnu. 414s Preparing to unpack .../027-g++-13-x86-64-linux-gnu_13.2.0-17ubuntu2_amd64.deb ... 414s Unpacking g++-13-x86-64-linux-gnu (13.2.0-17ubuntu2) ... 415s Selecting previously unselected package g++-13. 415s Preparing to unpack .../028-g++-13_13.2.0-17ubuntu2_amd64.deb ... 415s Unpacking g++-13 (13.2.0-17ubuntu2) ... 415s Selecting previously unselected package g++-x86-64-linux-gnu. 415s Preparing to unpack .../029-g++-x86-64-linux-gnu_4%3a13.2.0-7ubuntu1_amd64.deb ... 415s Unpacking g++-x86-64-linux-gnu (4:13.2.0-7ubuntu1) ... 415s Selecting previously unselected package g++. 415s Preparing to unpack .../030-g++_4%3a13.2.0-7ubuntu1_amd64.deb ... 415s Unpacking g++ (4:13.2.0-7ubuntu1) ... 415s Selecting previously unselected package build-essential. 415s Preparing to unpack .../031-build-essential_12.10ubuntu1_amd64.deb ... 415s Unpacking build-essential (12.10ubuntu1) ... 415s Selecting previously unselected package fonts-dejavu-mono. 415s Preparing to unpack .../032-fonts-dejavu-mono_2.37-8_all.deb ... 415s Unpacking fonts-dejavu-mono (2.37-8) ... 415s Selecting previously unselected package fonts-dejavu-core. 415s Preparing to unpack .../033-fonts-dejavu-core_2.37-8_all.deb ... 415s Unpacking fonts-dejavu-core (2.37-8) ... 415s Selecting previously unselected package fontconfig-config. 415s Preparing to unpack .../034-fontconfig-config_2.15.0-1ubuntu1_amd64.deb ... 415s Unpacking fontconfig-config (2.15.0-1ubuntu1) ... 415s Selecting previously unselected package libfontconfig1:amd64. 415s Preparing to unpack .../035-libfontconfig1_2.15.0-1ubuntu1_amd64.deb ... 415s Unpacking libfontconfig1:amd64 (2.15.0-1ubuntu1) ... 415s Selecting previously unselected package fontconfig. 415s Preparing to unpack .../036-fontconfig_2.15.0-1ubuntu1_amd64.deb ... 415s Unpacking fontconfig (2.15.0-1ubuntu1) ... 415s Selecting previously unselected package fonts-font-awesome. 415s Preparing to unpack .../037-fonts-font-awesome_5.0.10+really4.7.0~dfsg-4.1_all.deb ... 415s Unpacking fonts-font-awesome (5.0.10+really4.7.0~dfsg-4.1) ... 415s Selecting previously unselected package fonts-glyphicons-halflings. 415s Preparing to unpack .../038-fonts-glyphicons-halflings_1.009~3.4.1+dfsg-3_all.deb ... 415s Unpacking fonts-glyphicons-halflings (1.009~3.4.1+dfsg-3) ... 415s Selecting previously unselected package fonts-mathjax. 415s Preparing to unpack .../039-fonts-mathjax_2.7.9+dfsg-1_all.deb ... 415s Unpacking fonts-mathjax (2.7.9+dfsg-1) ... 415s Selecting previously unselected package javascript-common. 415s Preparing to unpack .../040-javascript-common_11+nmu1_all.deb ... 415s Unpacking javascript-common (11+nmu1) ... 415s Selecting previously unselected package libblas3:amd64. 415s Preparing to unpack .../041-libblas3_3.12.0-3_amd64.deb ... 415s Unpacking libblas3:amd64 (3.12.0-3) ... 415s Selecting previously unselected package libpixman-1-0:amd64. 415s Preparing to unpack .../042-libpixman-1-0_0.42.2-1_amd64.deb ... 415s Unpacking libpixman-1-0:amd64 (0.42.2-1) ... 416s Selecting previously unselected package libxcb-render0:amd64. 416s Preparing to unpack .../043-libxcb-render0_1.15-1_amd64.deb ... 416s Unpacking libxcb-render0:amd64 (1.15-1) ... 416s Selecting previously unselected package libxcb-shm0:amd64. 416s Preparing to unpack .../044-libxcb-shm0_1.15-1_amd64.deb ... 416s Unpacking libxcb-shm0:amd64 (1.15-1) ... 416s Selecting previously unselected package libxrender1:amd64. 416s Preparing to unpack .../045-libxrender1_1%3a0.9.10-1.1_amd64.deb ... 416s Unpacking libxrender1:amd64 (1:0.9.10-1.1) ... 416s Selecting previously unselected package libcairo2:amd64. 416s Preparing to unpack .../046-libcairo2_1.18.0-1_amd64.deb ... 416s Unpacking libcairo2:amd64 (1.18.0-1) ... 416s Selecting previously unselected package libdatrie1:amd64. 416s Preparing to unpack .../047-libdatrie1_0.2.13-3_amd64.deb ... 416s Unpacking libdatrie1:amd64 (0.2.13-3) ... 416s Selecting previously unselected package libdeflate0:amd64. 416s Preparing to unpack .../048-libdeflate0_1.19-1_amd64.deb ... 416s Unpacking libdeflate0:amd64 (1.19-1) ... 416s Selecting previously unselected package libgfortran5:amd64. 416s Preparing to unpack .../049-libgfortran5_14-20240303-1ubuntu1_amd64.deb ... 416s Unpacking libgfortran5:amd64 (14-20240303-1ubuntu1) ... 416s Selecting previously unselected package libgraphite2-3:amd64. 416s Preparing to unpack .../050-libgraphite2-3_1.3.14-2_amd64.deb ... 416s Unpacking libgraphite2-3:amd64 (1.3.14-2) ... 416s Selecting previously unselected package libharfbuzz0b:amd64. 416s Preparing to unpack .../051-libharfbuzz0b_8.3.0-2_amd64.deb ... 416s Unpacking libharfbuzz0b:amd64 (8.3.0-2) ... 416s Selecting previously unselected package x11-common. 416s Preparing to unpack .../052-x11-common_1%3a7.7+23ubuntu2_all.deb ... 416s Unpacking x11-common (1:7.7+23ubuntu2) ... 416s Selecting previously unselected package libice6:amd64. 416s Preparing to unpack .../053-libice6_2%3a1.0.10-1build2_amd64.deb ... 416s Unpacking libice6:amd64 (2:1.0.10-1build2) ... 416s Selecting previously unselected package libjpeg-turbo8:amd64. 416s Preparing to unpack .../054-libjpeg-turbo8_2.1.5-2ubuntu1_amd64.deb ... 416s Unpacking libjpeg-turbo8:amd64 (2.1.5-2ubuntu1) ... 416s Selecting previously unselected package libjpeg8:amd64. 416s Preparing to unpack .../055-libjpeg8_8c-2ubuntu11_amd64.deb ... 416s Unpacking libjpeg8:amd64 (8c-2ubuntu11) ... 416s Selecting previously unselected package libjs-bootstrap. 416s Preparing to unpack .../056-libjs-bootstrap_3.4.1+dfsg-3_all.deb ... 416s Unpacking libjs-bootstrap (3.4.1+dfsg-3) ... 416s Selecting previously unselected package libjs-popper.js. 416s Preparing to unpack .../057-libjs-popper.js_1.16.1+ds-6_all.deb ... 416s Unpacking libjs-popper.js (1.16.1+ds-6) ... 416s Selecting previously unselected package libjs-bootstrap4. 416s Preparing to unpack .../058-libjs-bootstrap4_4.6.1+dfsg1-4_all.deb ... 416s Unpacking libjs-bootstrap4 (4.6.1+dfsg1-4) ... 416s Selecting previously unselected package libjs-d3. 416s Preparing to unpack .../059-libjs-d3_3.5.17-4_all.deb ... 416s Unpacking libjs-d3 (3.5.17-4) ... 416s Selecting previously unselected package libjs-es5-shim. 416s Preparing to unpack .../060-libjs-es5-shim_4.6.7-2_all.deb ... 416s Unpacking libjs-es5-shim (4.6.7-2) ... 416s Selecting previously unselected package libjs-highlight.js. 416s Preparing to unpack .../061-libjs-highlight.js_9.18.5+dfsg1-2_all.deb ... 416s Unpacking libjs-highlight.js (9.18.5+dfsg1-2) ... 416s Selecting previously unselected package libjs-jquery. 416s Preparing to unpack .../062-libjs-jquery_3.6.1+dfsg+~3.5.14-1_all.deb ... 416s Unpacking libjs-jquery (3.6.1+dfsg+~3.5.14-1) ... 416s Selecting previously unselected package libjs-jquery-datatables. 416s Preparing to unpack .../063-libjs-jquery-datatables_1.11.5+dfsg-2_all.deb ... 416s Unpacking libjs-jquery-datatables (1.11.5+dfsg-2) ... 416s Selecting previously unselected package libjs-sifter.js. 416s Preparing to unpack .../064-libjs-sifter.js_0.6.0+dfsg-3_all.deb ... 416s Unpacking libjs-sifter.js (0.6.0+dfsg-3) ... 416s Selecting previously unselected package libjs-microplugin.js. 416s Preparing to unpack .../065-libjs-microplugin.js_0.0.3+dfsg-1.1_all.deb ... 416s Unpacking libjs-microplugin.js (0.0.3+dfsg-1.1) ... 416s Selecting previously unselected package libjs-jquery-selectize.js. 416s Preparing to unpack .../066-libjs-jquery-selectize.js_0.12.6+dfsg-1.1_all.deb ... 416s Unpacking libjs-jquery-selectize.js (0.12.6+dfsg-1.1) ... 416s Selecting previously unselected package libjs-jquery-ui. 416s Preparing to unpack .../067-libjs-jquery-ui_1.13.2+dfsg-1_all.deb ... 416s Unpacking libjs-jquery-ui (1.13.2+dfsg-1) ... 416s Selecting previously unselected package libjs-json. 416s Preparing to unpack .../068-libjs-json_0~20221030+~1.0.8-1_all.deb ... 416s Unpacking libjs-json (0~20221030+~1.0.8-1) ... 416s Selecting previously unselected package libjs-prettify. 416s Preparing to unpack .../069-libjs-prettify_2015.12.04+dfsg-1.1_all.deb ... 416s Unpacking libjs-prettify (2015.12.04+dfsg-1.1) ... 416s Selecting previously unselected package liblapack3:amd64. 416s Preparing to unpack .../070-liblapack3_3.12.0-3_amd64.deb ... 416s Unpacking liblapack3:amd64 (3.12.0-3) ... 416s Selecting previously unselected package liblerc4:amd64. 417s Preparing to unpack .../071-liblerc4_4.0.0+ds-4ubuntu1_amd64.deb ... 417s Unpacking liblerc4:amd64 (4.0.0+ds-4ubuntu1) ... 417s Selecting previously unselected package liblua5.4-0:amd64. 417s Preparing to unpack .../072-liblua5.4-0_5.4.6-3_amd64.deb ... 417s Unpacking liblua5.4-0:amd64 (5.4.6-3) ... 417s Selecting previously unselected package libthai-data. 417s Preparing to unpack .../073-libthai-data_0.1.29-2_all.deb ... 417s Unpacking libthai-data (0.1.29-2) ... 417s Selecting previously unselected package libthai0:amd64. 417s Preparing to unpack .../074-libthai0_0.1.29-2_amd64.deb ... 417s Unpacking libthai0:amd64 (0.1.29-2) ... 417s Selecting previously unselected package libpango-1.0-0:amd64. 417s Preparing to unpack .../075-libpango-1.0-0_1.51.0+ds-4_amd64.deb ... 417s Unpacking libpango-1.0-0:amd64 (1.51.0+ds-4) ... 417s Selecting previously unselected package libpangoft2-1.0-0:amd64. 417s Preparing to unpack .../076-libpangoft2-1.0-0_1.51.0+ds-4_amd64.deb ... 417s Unpacking libpangoft2-1.0-0:amd64 (1.51.0+ds-4) ... 417s Selecting previously unselected package libpangocairo-1.0-0:amd64. 417s Preparing to unpack .../077-libpangocairo-1.0-0_1.51.0+ds-4_amd64.deb ... 417s Unpacking libpangocairo-1.0-0:amd64 (1.51.0+ds-4) ... 417s Selecting previously unselected package libpaper1:amd64. 417s Preparing to unpack .../078-libpaper1_1.1.29_amd64.deb ... 417s Unpacking libpaper1:amd64 (1.1.29) ... 417s Selecting previously unselected package libpaper-utils. 417s Preparing to unpack .../079-libpaper-utils_1.1.29_amd64.deb ... 417s Unpacking libpaper-utils (1.1.29) ... 417s Selecting previously unselected package libsharpyuv0:amd64. 417s Preparing to unpack .../080-libsharpyuv0_1.3.2-0.4_amd64.deb ... 417s Unpacking libsharpyuv0:amd64 (1.3.2-0.4) ... 417s Selecting previously unselected package libsm6:amd64. 417s Preparing to unpack .../081-libsm6_2%3a1.2.3-1build2_amd64.deb ... 417s Unpacking libsm6:amd64 (2:1.2.3-1build2) ... 417s Selecting previously unselected package libtcl8.6:amd64. 417s Preparing to unpack .../082-libtcl8.6_8.6.13+dfsg-2_amd64.deb ... 417s Unpacking libtcl8.6:amd64 (8.6.13+dfsg-2) ... 417s Selecting previously unselected package libjbig0:amd64. 417s Preparing to unpack .../083-libjbig0_2.1-6.1ubuntu1_amd64.deb ... 417s Unpacking libjbig0:amd64 (2.1-6.1ubuntu1) ... 417s Selecting previously unselected package libwebp7:amd64. 417s Preparing to unpack .../084-libwebp7_1.3.2-0.4_amd64.deb ... 417s Unpacking libwebp7:amd64 (1.3.2-0.4) ... 417s Selecting previously unselected package libtiff6:amd64. 417s Preparing to unpack .../085-libtiff6_4.5.1+git230720-3ubuntu1_amd64.deb ... 417s Unpacking libtiff6:amd64 (4.5.1+git230720-3ubuntu1) ... 417s Selecting previously unselected package libxft2:amd64. 417s Preparing to unpack .../086-libxft2_2.3.6-1_amd64.deb ... 417s Unpacking libxft2:amd64 (2.3.6-1) ... 417s Selecting previously unselected package libxss1:amd64. 417s Preparing to unpack .../087-libxss1_1%3a1.2.3-1build2_amd64.deb ... 417s Unpacking libxss1:amd64 (1:1.2.3-1build2) ... 417s Selecting previously unselected package libtk8.6:amd64. 417s Preparing to unpack .../088-libtk8.6_8.6.14-1_amd64.deb ... 417s Unpacking libtk8.6:amd64 (8.6.14-1) ... 417s Selecting previously unselected package libxt6:amd64. 417s Preparing to unpack .../089-libxt6_1%3a1.2.1-1.1_amd64.deb ... 417s Unpacking libxt6:amd64 (1:1.2.1-1.1) ... 417s Selecting previously unselected package zip. 417s Preparing to unpack .../090-zip_3.0-13_amd64.deb ... 417s Unpacking zip (3.0-13) ... 417s Selecting previously unselected package unzip. 417s Preparing to unpack .../091-unzip_6.0-28ubuntu3_amd64.deb ... 417s Unpacking unzip (6.0-28ubuntu3) ... 417s Selecting previously unselected package xdg-utils. 417s Preparing to unpack .../092-xdg-utils_1.1.3-4.1ubuntu3_all.deb ... 417s Unpacking xdg-utils (1.1.3-4.1ubuntu3) ... 417s Selecting previously unselected package r-base-core. 417s Preparing to unpack .../093-r-base-core_4.3.2-1build1_amd64.deb ... 417s Unpacking r-base-core (4.3.2-1build1) ... 417s Selecting previously unselected package r-cran-littler. 417s Preparing to unpack .../094-r-cran-littler_0.3.19-1_amd64.deb ... 417s Unpacking r-cran-littler (0.3.19-1) ... 418s Selecting previously unselected package littler. 418s Preparing to unpack .../095-littler_0.3.19-1_all.deb ... 418s Unpacking littler (0.3.19-1) ... 418s Selecting previously unselected package node-bootstrap-sass. 418s Preparing to unpack .../096-node-bootstrap-sass_3.4.3-2_all.deb ... 418s Unpacking node-bootstrap-sass (3.4.3-2) ... 418s Selecting previously unselected package node-html5shiv. 418s Preparing to unpack .../097-node-html5shiv_3.7.3+dfsg-5_all.deb ... 418s Unpacking node-html5shiv (3.7.3+dfsg-5) ... 418s Selecting previously unselected package node-normalize.css. 418s Preparing to unpack .../098-node-normalize.css_8.0.1-5_all.deb ... 418s Unpacking node-normalize.css (8.0.1-5) ... 418s Selecting previously unselected package pandoc-data. 418s Preparing to unpack .../099-pandoc-data_3.1.3-1_all.deb ... 418s Unpacking pandoc-data (3.1.3-1) ... 418s Selecting previously unselected package pandoc. 418s Preparing to unpack .../100-pandoc_3.1.3+ds-2_amd64.deb ... 418s Unpacking pandoc (3.1.3+ds-2) ... 419s Selecting previously unselected package r-bioc-biocgenerics. 419s Preparing to unpack .../101-r-bioc-biocgenerics_0.48.1-2_all.deb ... 419s Unpacking r-bioc-biocgenerics (0.48.1-2) ... 419s Selecting previously unselected package r-cran-r.methodss3. 419s Preparing to unpack .../102-r-cran-r.methodss3_1.8.2-1_all.deb ... 419s Unpacking r-cran-r.methodss3 (1.8.2-1) ... 419s Selecting previously unselected package r-cran-r.oo. 419s Preparing to unpack .../103-r-cran-r.oo_1.26.0-1_all.deb ... 419s Unpacking r-cran-r.oo (1.26.0-1) ... 419s Selecting previously unselected package r-cran-r.utils. 419s Preparing to unpack .../104-r-cran-r.utils_2.12.3-1_all.deb ... 419s Unpacking r-cran-r.utils (2.12.3-1) ... 419s Selecting previously unselected package r-cran-matrixstats. 419s Preparing to unpack .../105-r-cran-matrixstats_1.2.0-1_amd64.deb ... 419s Unpacking r-cran-matrixstats (1.2.0-1) ... 419s Selecting previously unselected package r-bioc-aroma.light. 419s Preparing to unpack .../106-r-bioc-aroma.light_3.32.0-1_all.deb ... 419s Unpacking r-bioc-aroma.light (3.32.0-1) ... 419s Selecting previously unselected package r-bioc-dnacopy. 419s Preparing to unpack .../107-r-bioc-dnacopy_1.76.0-1_amd64.deb ... 419s Unpacking r-bioc-dnacopy (1.76.0-1) ... 419s Selecting previously unselected package r-cran-acepack. 419s Preparing to unpack .../108-r-cran-acepack_1.4.2-1_amd64.deb ... 419s Unpacking r-cran-acepack (1.4.2-1) ... 419s Selecting previously unselected package r-cran-backports. 419s Preparing to unpack .../109-r-cran-backports_1.4.1-1_amd64.deb ... 419s Unpacking r-cran-backports (1.4.1-1) ... 419s Selecting previously unselected package r-cran-base64enc. 419s Preparing to unpack .../110-r-cran-base64enc_0.1-3-3_amd64.deb ... 419s Unpacking r-cran-base64enc (0.1-3-3) ... 419s Selecting previously unselected package r-cran-rlang. 419s Preparing to unpack .../111-r-cran-rlang_1.1.3-1_amd64.deb ... 419s Unpacking r-cran-rlang (1.1.3-1) ... 419s Selecting previously unselected package r-cran-fastmap. 419s Preparing to unpack .../112-r-cran-fastmap_1.1.1-1_amd64.deb ... 419s Unpacking r-cran-fastmap (1.1.1-1) ... 419s Selecting previously unselected package r-cran-cachem. 419s Preparing to unpack .../113-r-cran-cachem_1.0.8-1_amd64.deb ... 419s Unpacking r-cran-cachem (1.0.8-1) ... 419s Selecting previously unselected package r-cran-digest. 419s Preparing to unpack .../114-r-cran-digest_0.6.34-1_amd64.deb ... 419s Unpacking r-cran-digest (0.6.34-1) ... 419s Selecting previously unselected package r-cran-ellipsis. 419s Preparing to unpack .../115-r-cran-ellipsis_0.3.2-2_amd64.deb ... 419s Unpacking r-cran-ellipsis (0.3.2-2) ... 419s Selecting previously unselected package r-cran-htmltools. 419s Preparing to unpack .../116-r-cran-htmltools_0.5.7-1_amd64.deb ... 419s Unpacking r-cran-htmltools (0.5.7-1) ... 419s Selecting previously unselected package r-cran-jquerylib. 419s Preparing to unpack .../117-r-cran-jquerylib_0.1.4+dfsg-4_all.deb ... 419s Unpacking r-cran-jquerylib (0.1.4+dfsg-4) ... 419s Selecting previously unselected package r-cran-jsonlite. 419s Preparing to unpack .../118-r-cran-jsonlite_1.8.8+dfsg-1_amd64.deb ... 419s Unpacking r-cran-jsonlite (1.8.8+dfsg-1) ... 419s Selecting previously unselected package r-cran-cli. 419s Preparing to unpack .../119-r-cran-cli_3.6.2-1_amd64.deb ... 419s Unpacking r-cran-cli (3.6.2-1) ... 419s Selecting previously unselected package r-cran-glue. 419s Preparing to unpack .../120-r-cran-glue_1.7.0-1_amd64.deb ... 419s Unpacking r-cran-glue (1.7.0-1) ... 419s Selecting previously unselected package r-cran-lifecycle. 419s Preparing to unpack .../121-r-cran-lifecycle_1.0.4+dfsg-1_all.deb ... 419s Unpacking r-cran-lifecycle (1.0.4+dfsg-1) ... 419s Selecting previously unselected package r-cran-memoise. 419s Preparing to unpack .../122-r-cran-memoise_2.0.1-1_all.deb ... 419s Unpacking r-cran-memoise (2.0.1-1) ... 419s Selecting previously unselected package r-cran-mime. 419s Preparing to unpack .../123-r-cran-mime_0.12-1_amd64.deb ... 419s Unpacking r-cran-mime (0.12-1) ... 419s Selecting previously unselected package r-cran-fs. 419s Preparing to unpack .../124-r-cran-fs_1.6.3+dfsg-1_amd64.deb ... 419s Unpacking r-cran-fs (1.6.3+dfsg-1) ... 419s Selecting previously unselected package r-cran-r6. 419s Preparing to unpack .../125-r-cran-r6_2.5.1-1_all.deb ... 419s Unpacking r-cran-r6 (2.5.1-1) ... 419s Selecting previously unselected package r-cran-rappdirs. 419s Preparing to unpack .../126-r-cran-rappdirs_0.3.3-1_amd64.deb ... 419s Unpacking r-cran-rappdirs (0.3.3-1) ... 419s Selecting previously unselected package r-cran-sass. 419s Preparing to unpack .../127-r-cran-sass_0.4.8+dfsg-1_amd64.deb ... 419s Unpacking r-cran-sass (0.4.8+dfsg-1) ... 419s Selecting previously unselected package r-cran-bslib. 419s Preparing to unpack .../128-r-cran-bslib_0.6.1+dfsg-1_all.deb ... 419s Unpacking r-cran-bslib (0.6.1+dfsg-1) ... 420s Selecting previously unselected package r-cran-checkmate. 420s Preparing to unpack .../129-r-cran-checkmate_2.3.1-1_amd64.deb ... 420s Unpacking r-cran-checkmate (2.3.1-1) ... 420s Selecting previously unselected package r-cran-chron. 420s Preparing to unpack .../130-r-cran-chron_2.3-61-2_amd64.deb ... 420s Unpacking r-cran-chron (2.3-61-2) ... 420s Selecting previously unselected package r-cran-cluster. 420s Preparing to unpack .../131-r-cran-cluster_2.1.6-1_amd64.deb ... 420s Unpacking r-cran-cluster (2.1.6-1) ... 420s Selecting previously unselected package r-cran-codetools. 420s Preparing to unpack .../132-r-cran-codetools_0.2-19-1_all.deb ... 420s Unpacking r-cran-codetools (0.2-19-1) ... 420s Selecting previously unselected package r-cran-colorspace. 420s Preparing to unpack .../133-r-cran-colorspace_2.1-0+dfsg-1_amd64.deb ... 420s Unpacking r-cran-colorspace (2.1-0+dfsg-1) ... 420s Selecting previously unselected package r-cran-commonmark. 420s Preparing to unpack .../134-r-cran-commonmark_1.9.1-1_amd64.deb ... 420s Unpacking r-cran-commonmark (1.9.1-1) ... 420s Selecting previously unselected package r-cran-cpp11. 420s Preparing to unpack .../135-r-cran-cpp11_0.4.7-1_all.deb ... 420s Unpacking r-cran-cpp11 (0.4.7-1) ... 420s Selecting previously unselected package r-cran-crayon. 420s Preparing to unpack .../136-r-cran-crayon_1.5.2-1_all.deb ... 420s Unpacking r-cran-crayon (1.5.2-1) ... 420s Selecting previously unselected package r-cran-data.table. 420s Preparing to unpack .../137-r-cran-data.table_1.14.10+dfsg-1_amd64.deb ... 420s Unpacking r-cran-data.table (1.14.10+dfsg-1) ... 420s Selecting previously unselected package r-cran-deldir. 420s Preparing to unpack .../138-r-cran-deldir_2.0-4-1_amd64.deb ... 420s Unpacking r-cran-deldir (2.0-4-1) ... 420s Selecting previously unselected package r-cran-generics. 420s Preparing to unpack .../139-r-cran-generics_0.1.3-1_all.deb ... 420s Unpacking r-cran-generics (0.1.3-1) ... 420s Selecting previously unselected package r-cran-magrittr. 420s Preparing to unpack .../140-r-cran-magrittr_2.0.3-1_amd64.deb ... 420s Unpacking r-cran-magrittr (2.0.3-1) ... 420s Selecting previously unselected package r-cran-fansi. 420s Preparing to unpack .../141-r-cran-fansi_1.0.5-1_amd64.deb ... 420s Unpacking r-cran-fansi (1.0.5-1) ... 420s Selecting previously unselected package r-cran-utf8. 420s Preparing to unpack .../142-r-cran-utf8_1.2.4-1_amd64.deb ... 420s Unpacking r-cran-utf8 (1.2.4-1) ... 420s Selecting previously unselected package r-cran-vctrs. 420s Preparing to unpack .../143-r-cran-vctrs_0.6.5-1_amd64.deb ... 420s Unpacking r-cran-vctrs (0.6.5-1) ... 420s Selecting previously unselected package r-cran-pillar. 420s Preparing to unpack .../144-r-cran-pillar_1.9.0+dfsg-1_all.deb ... 420s Unpacking r-cran-pillar (1.9.0+dfsg-1) ... 420s Selecting previously unselected package r-cran-pkgconfig. 420s Preparing to unpack .../145-r-cran-pkgconfig_2.0.3-2build1_all.deb ... 420s Unpacking r-cran-pkgconfig (2.0.3-2build1) ... 420s Selecting previously unselected package r-cran-tibble. 420s Preparing to unpack .../146-r-cran-tibble_3.2.1+dfsg-2_amd64.deb ... 420s Unpacking r-cran-tibble (3.2.1+dfsg-2) ... 420s Selecting previously unselected package r-cran-withr. 420s Preparing to unpack .../147-r-cran-withr_2.5.0-1_all.deb ... 420s Unpacking r-cran-withr (2.5.0-1) ... 420s Selecting previously unselected package r-cran-tidyselect. 420s Preparing to unpack .../148-r-cran-tidyselect_1.2.0+dfsg-1_amd64.deb ... 420s Unpacking r-cran-tidyselect (1.2.0+dfsg-1) ... 420s Selecting previously unselected package r-cran-dplyr. 420s Preparing to unpack .../149-r-cran-dplyr_1.1.4-1_amd64.deb ... 420s Unpacking r-cran-dplyr (1.1.4-1) ... 420s Selecting previously unselected package r-cran-evaluate. 420s Preparing to unpack .../150-r-cran-evaluate_0.23-1_all.deb ... 420s Unpacking r-cran-evaluate (0.23-1) ... 420s Selecting previously unselected package r-cran-farver. 420s Preparing to unpack .../151-r-cran-farver_2.1.1-1_amd64.deb ... 420s Unpacking r-cran-farver (2.1.1-1) ... 420s Selecting previously unselected package r-cran-fontawesome. 420s Preparing to unpack .../152-r-cran-fontawesome_0.5.2-1_all.deb ... 420s Unpacking r-cran-fontawesome (0.5.2-1) ... 420s Selecting previously unselected package r-cran-foreign. 420s Preparing to unpack .../153-r-cran-foreign_0.8.86-1_amd64.deb ... 420s Unpacking r-cran-foreign (0.8.86-1) ... 421s Selecting previously unselected package r-cran-formula. 421s Preparing to unpack .../154-r-cran-formula_1.2-5-1_all.deb ... 421s Unpacking r-cran-formula (1.2-5-1) ... 421s Selecting previously unselected package r-cran-globals. 421s Preparing to unpack .../155-r-cran-globals_0.16.2-1_all.deb ... 421s Unpacking r-cran-globals (0.16.2-1) ... 421s Selecting previously unselected package r-cran-listenv. 421s Preparing to unpack .../156-r-cran-listenv_0.9.1+dfsg-1_all.deb ... 421s Unpacking r-cran-listenv (0.9.1+dfsg-1) ... 421s Selecting previously unselected package r-cran-parallelly. 421s Preparing to unpack .../157-r-cran-parallelly_1.37.1-1_amd64.deb ... 421s Unpacking r-cran-parallelly (1.37.1-1) ... 421s Selecting previously unselected package r-cran-future. 421s Preparing to unpack .../158-r-cran-future_1.33.1+dfsg-1_all.deb ... 421s Unpacking r-cran-future (1.33.1+dfsg-1) ... 421s Selecting previously unselected package r-cran-gtable. 421s Preparing to unpack .../159-r-cran-gtable_0.3.4+dfsg-1_all.deb ... 421s Unpacking r-cran-gtable (0.3.4+dfsg-1) ... 421s Selecting previously unselected package r-cran-isoband. 421s Preparing to unpack .../160-r-cran-isoband_0.2.7-1_amd64.deb ... 421s Unpacking r-cran-isoband (0.2.7-1) ... 421s Selecting previously unselected package r-cran-mass. 421s Preparing to unpack .../161-r-cran-mass_7.3-60.0.1-1_amd64.deb ... 421s Unpacking r-cran-mass (7.3-60.0.1-1) ... 421s Selecting previously unselected package r-cran-lattice. 421s Preparing to unpack .../162-r-cran-lattice_0.22-5-1_amd64.deb ... 421s Unpacking r-cran-lattice (0.22-5-1) ... 421s Selecting previously unselected package r-cran-nlme. 421s Preparing to unpack .../163-r-cran-nlme_3.1.164-1_amd64.deb ... 421s Unpacking r-cran-nlme (3.1.164-1) ... 421s Selecting previously unselected package r-cran-matrix. 421s Preparing to unpack .../164-r-cran-matrix_1.6-5-1_amd64.deb ... 421s Unpacking r-cran-matrix (1.6-5-1) ... 421s Selecting previously unselected package r-cran-mgcv. 421s Preparing to unpack .../165-r-cran-mgcv_1.9-1-1_amd64.deb ... 421s Unpacking r-cran-mgcv (1.9-1-1) ... 421s Selecting previously unselected package r-cran-labeling. 421s Preparing to unpack .../166-r-cran-labeling_0.4.3-1_all.deb ... 421s Unpacking r-cran-labeling (0.4.3-1) ... 421s Selecting previously unselected package r-cran-munsell. 421s Preparing to unpack .../167-r-cran-munsell_0.5.0-2build1_all.deb ... 421s Unpacking r-cran-munsell (0.5.0-2build1) ... 421s Selecting previously unselected package r-cran-rcolorbrewer. 421s Preparing to unpack .../168-r-cran-rcolorbrewer_1.1-3-1build1_all.deb ... 421s Unpacking r-cran-rcolorbrewer (1.1-3-1build1) ... 421s Selecting previously unselected package r-cran-viridislite. 421s Preparing to unpack .../169-r-cran-viridislite_0.4.2-2_all.deb ... 421s Unpacking r-cran-viridislite (0.4.2-2) ... 421s Selecting previously unselected package r-cran-scales. 421s Preparing to unpack .../170-r-cran-scales_1.3.0-1_all.deb ... 421s Unpacking r-cran-scales (1.3.0-1) ... 421s Selecting previously unselected package r-cran-ggplot2. 421s Preparing to unpack .../171-r-cran-ggplot2_3.4.4+dfsg-1_all.deb ... 421s Unpacking r-cran-ggplot2 (3.4.4+dfsg-1) ... 421s Selecting previously unselected package r-cran-gridextra. 421s Preparing to unpack .../172-r-cran-gridextra_2.3-3build1_all.deb ... 421s Unpacking r-cran-gridextra (2.3-3build1) ... 421s Selecting previously unselected package r-cran-xfun. 421s Preparing to unpack .../173-r-cran-xfun_0.41+dfsg-1_amd64.deb ... 421s Unpacking r-cran-xfun (0.41+dfsg-1) ... 421s Selecting previously unselected package r-cran-highr. 421s Preparing to unpack .../174-r-cran-highr_0.10+dfsg-1_all.deb ... 421s Unpacking r-cran-highr (0.10+dfsg-1) ... 422s Selecting previously unselected package r-cran-survival. 422s Preparing to unpack .../175-r-cran-survival_3.5-8-1_amd64.deb ... 422s Unpacking r-cran-survival (3.5-8-1) ... 422s Selecting previously unselected package r-cran-rpart. 422s Preparing to unpack .../176-r-cran-rpart_4.1.23-1_amd64.deb ... 422s Unpacking r-cran-rpart (4.1.23-1) ... 422s Selecting previously unselected package r-cran-nnet. 422s Preparing to unpack .../177-r-cran-nnet_7.3-19-2_amd64.deb ... 422s Unpacking r-cran-nnet (7.3-19-2) ... 422s Selecting previously unselected package r-cran-stringi. 422s Preparing to unpack .../178-r-cran-stringi_1.8.3-1_amd64.deb ... 422s Unpacking r-cran-stringi (1.8.3-1) ... 422s Selecting previously unselected package r-cran-stringr. 422s Preparing to unpack .../179-r-cran-stringr_1.5.1-1_all.deb ... 422s Unpacking r-cran-stringr (1.5.1-1) ... 422s Selecting previously unselected package r-cran-yaml. 422s Preparing to unpack .../180-r-cran-yaml_2.3.8-1_amd64.deb ... 422s Unpacking r-cran-yaml (2.3.8-1) ... 422s Selecting previously unselected package libjs-mathjax. 422s Preparing to unpack .../181-libjs-mathjax_2.7.9+dfsg-1_all.deb ... 422s Unpacking libjs-mathjax (2.7.9+dfsg-1) ... 422s Selecting previously unselected package r-cran-knitr. 422s Preparing to unpack .../182-r-cran-knitr_1.45+dfsg-1_all.deb ... 422s Unpacking r-cran-knitr (1.45+dfsg-1) ... 423s Selecting previously unselected package r-cran-tinytex. 423s Preparing to unpack .../183-r-cran-tinytex_0.49-1_all.deb ... 423s Unpacking r-cran-tinytex (0.49-1) ... 423s Selecting previously unselected package libjs-modernizr. 423s Preparing to unpack .../184-libjs-modernizr_2.6.2+ds1-5_all.deb ... 423s Unpacking libjs-modernizr (2.6.2+ds1-5) ... 423s Selecting previously unselected package r-cran-pkgkitten. 423s Preparing to unpack .../185-r-cran-pkgkitten_0.2.3-1_all.deb ... 423s Unpacking r-cran-pkgkitten (0.2.3-1) ... 423s Selecting previously unselected package r-cran-rcpp. 423s Preparing to unpack .../186-r-cran-rcpp_1.0.12-1_amd64.deb ... 423s Unpacking r-cran-rcpp (1.0.12-1) ... 423s Selecting previously unselected package r-cran-later. 423s Preparing to unpack .../187-r-cran-later_1.3.2+dfsg-1_amd64.deb ... 423s Unpacking r-cran-later (1.3.2+dfsg-1) ... 423s Selecting previously unselected package r-cran-promises. 423s Preparing to unpack .../188-r-cran-promises_1.2.1+dfsg-1_amd64.deb ... 423s Unpacking r-cran-promises (1.2.1+dfsg-1) ... 423s Selecting previously unselected package r-cran-httpuv. 423s Preparing to unpack .../189-r-cran-httpuv_1.6.14+dfsg-1_amd64.deb ... 423s Unpacking r-cran-httpuv (1.6.14+dfsg-1) ... 423s Selecting previously unselected package r-cran-xtable. 423s Preparing to unpack .../190-r-cran-xtable_1%3a1.8-4-2_all.deb ... 423s Unpacking r-cran-xtable (1:1.8-4-2) ... 423s Selecting previously unselected package r-cran-sourcetools. 423s Preparing to unpack .../191-r-cran-sourcetools_0.1.7-1-1_amd64.deb ... 423s Unpacking r-cran-sourcetools (0.1.7-1-1) ... 423s Selecting previously unselected package libjs-twitter-bootstrap-datepicker. 423s Preparing to unpack .../192-libjs-twitter-bootstrap-datepicker_1.3.1+dfsg1-4.1_all.deb ... 423s Unpacking libjs-twitter-bootstrap-datepicker (1.3.1+dfsg1-4.1) ... 423s Selecting previously unselected package r-cran-shiny. 423s Preparing to unpack .../193-r-cran-shiny_1.8.0+dfsg-1_all.deb ... 423s Unpacking r-cran-shiny (1.8.0+dfsg-1) ... 423s Selecting previously unselected package r-cran-rmarkdown. 423s Preparing to unpack .../194-r-cran-rmarkdown_2.25+dfsg-3_all.deb ... 423s Unpacking r-cran-rmarkdown (2.25+dfsg-3) ... 423s Selecting previously unselected package r-cran-htmlwidgets. 423s Preparing to unpack .../195-r-cran-htmlwidgets_1.6.4+dfsg-1_all.deb ... 423s Unpacking r-cran-htmlwidgets (1.6.4+dfsg-1) ... 423s Selecting previously unselected package r-cran-rstudioapi. 423s Preparing to unpack .../196-r-cran-rstudioapi_0.15.0-1_all.deb ... 423s Unpacking r-cran-rstudioapi (0.15.0-1) ... 423s Selecting previously unselected package r-cran-purrr. 423s Preparing to unpack .../197-r-cran-purrr_1.0.2-1_amd64.deb ... 423s Unpacking r-cran-purrr (1.0.2-1) ... 423s Selecting previously unselected package r-cran-tidyr. 423s Preparing to unpack .../198-r-cran-tidyr_1.3.1-1_amd64.deb ... 423s Unpacking r-cran-tidyr (1.3.1-1) ... 423s Selecting previously unselected package r-cran-htmltable. 423s Preparing to unpack .../199-r-cran-htmltable_2.4.2-1_all.deb ... 423s Unpacking r-cran-htmltable (2.4.2-1) ... 423s Selecting previously unselected package r-cran-viridis. 423s Preparing to unpack .../200-r-cran-viridis_0.6.5-1_all.deb ... 423s Unpacking r-cran-viridis (0.6.5-1) ... 423s Selecting previously unselected package r-cran-png. 423s Preparing to unpack .../201-r-cran-png_0.1-8-1_amd64.deb ... 423s Unpacking r-cran-png (0.1-8-1) ... 423s Selecting previously unselected package r-cran-jpeg. 424s Preparing to unpack .../202-r-cran-jpeg_0.1-10-1_amd64.deb ... 424s Unpacking r-cran-jpeg (0.1-10-1) ... 424s Selecting previously unselected package r-cran-rcppeigen. 424s Preparing to unpack .../203-r-cran-rcppeigen_0.3.3.9.4-1_amd64.deb ... 424s Unpacking r-cran-rcppeigen (0.3.3.9.4-1) ... 424s Selecting previously unselected package r-cran-interp. 424s Preparing to unpack .../204-r-cran-interp_1.1-6-1_amd64.deb ... 424s Unpacking r-cran-interp (1.1-6-1) ... 424s Selecting previously unselected package r-cran-latticeextra. 424s Preparing to unpack .../205-r-cran-latticeextra_0.6-30-1_all.deb ... 424s Unpacking r-cran-latticeextra (0.6-30-1) ... 424s Selecting previously unselected package r-cran-hmisc. 424s Preparing to unpack .../206-r-cran-hmisc_5.1-1-1_amd64.deb ... 424s Unpacking r-cran-hmisc (5.1-1-1) ... 424s Selecting previously unselected package r-cran-r.cache. 424s Preparing to unpack .../207-r-cran-r.cache_0.16.0-1_all.deb ... 424s Unpacking r-cran-r.cache (0.16.0-1) ... 424s Selecting previously unselected package r-cran-pscbs. 424s Preparing to unpack .../208-r-cran-pscbs_0.66.0-2_all.deb ... 424s Unpacking r-cran-pscbs (0.66.0-2) ... 424s Setting up libjs-json (0~20221030+~1.0.8-1) ... 424s Setting up javascript-common (11+nmu1) ... 424s Setting up libgraphite2-3:amd64 (1.3.14-2) ... 424s Setting up libpixman-1-0:amd64 (0.42.2-1) ... 424s Setting up libsharpyuv0:amd64 (1.3.2-0.4) ... 424s Setting up libpaper1:amd64 (1.1.29) ... 424s 424s Creating config file /etc/papersize with new version 424s Setting up fonts-mathjax (2.7.9+dfsg-1) ... 424s Setting up liblerc4:amd64 (4.0.0+ds-4ubuntu1) ... 424s Setting up libjs-mathjax (2.7.9+dfsg-1) ... 424s Setting up libxrender1:amd64 (1:0.9.10-1.1) ... 424s Setting up libdatrie1:amd64 (0.2.13-3) ... 424s Setting up libjs-popper.js (1.16.1+ds-6) ... 424s Setting up libxcb-render0:amd64 (1.15-1) ... 424s Setting up libjs-sifter.js (0.6.0+dfsg-3) ... 424s Setting up fonts-glyphicons-halflings (1.009~3.4.1+dfsg-3) ... 424s Setting up unzip (6.0-28ubuntu3) ... 424s Setting up x11-common (1:7.7+23ubuntu2) ... 424s Setting up node-html5shiv (3.7.3+dfsg-5) ... 424s Setting up libdeflate0:amd64 (1.19-1) ... 424s Setting up linux-libc-dev:amd64 (6.8.0-11.11) ... 424s Setting up libjs-microplugin.js (0.0.3+dfsg-1.1) ... 424s Setting up libxcb-shm0:amd64 (1.15-1) ... 424s Setting up libpaper-utils (1.1.29) ... 424s Setting up libgomp1:amd64 (14-20240303-1ubuntu1) ... 424s Setting up libjs-modernizr (2.6.2+ds1-5) ... 424s Setting up libjbig0:amd64 (2.1-6.1ubuntu1) ... 424s Setting up libjs-es5-shim (4.6.7-2) ... 424s Setting up zip (3.0-13) ... 424s Setting up libblas3:amd64 (3.12.0-3) ... 424s update-alternatives: using /usr/lib/x86_64-linux-gnu/blas/libblas.so.3 to provide /usr/lib/x86_64-linux-gnu/libblas.so.3 (libblas.so.3-x86_64-linux-gnu) in auto mode 424s Setting up rpcsvc-proto (1.4.2-0ubuntu6) ... 424s Setting up libquadmath0:amd64 (14-20240303-1ubuntu1) ... 424s Setting up libjs-d3 (3.5.17-4) ... 424s Setting up fonts-dejavu-mono (2.37-8) ... 424s Setting up libmpc3:amd64 (1.3.1-1) ... 424s Setting up libatomic1:amd64 (14-20240303-1ubuntu1) ... 424s Setting up libtcl8.6:amd64 (8.6.13+dfsg-2) ... 424s Setting up fonts-dejavu-core (2.37-8) ... 425s Setting up libjpeg-turbo8:amd64 (2.1.5-2ubuntu1) ... 425s Setting up libgfortran5:amd64 (14-20240303-1ubuntu1) ... 425s Setting up libwebp7:amd64 (1.3.2-0.4) ... 425s Setting up libubsan1:amd64 (14-20240303-1ubuntu1) ... 425s Setting up libjs-highlight.js (9.18.5+dfsg1-2) ... 425s Setting up libhwasan0:amd64 (14-20240303-1ubuntu1) ... 425s Setting up libcrypt-dev:amd64 (1:4.4.36-4) ... 425s Setting up libasan8:amd64 (14-20240303-1ubuntu1) ... 425s Setting up liblua5.4-0:amd64 (5.4.6-3) ... 425s Setting up libharfbuzz0b:amd64 (8.3.0-2) ... 425s Setting up libthai-data (0.1.29-2) ... 425s Setting up node-bootstrap-sass (3.4.3-2) ... 425s Setting up libjs-prettify (2015.12.04+dfsg-1.1) ... 425s Setting up libxss1:amd64 (1:1.2.3-1build2) ... 425s Setting up libjs-bootstrap4 (4.6.1+dfsg1-4) ... 425s Setting up pandoc-data (3.1.3-1) ... 425s Setting up libtsan2:amd64 (14-20240303-1ubuntu1) ... 425s Setting up libjs-jquery (3.6.1+dfsg+~3.5.14-1) ... 425s Setting up libisl23:amd64 (0.26-3) ... 425s Setting up libc-dev-bin (2.39-0ubuntu6) ... 425s Setting up node-normalize.css (8.0.1-5) ... 425s Setting up fonts-font-awesome (5.0.10+really4.7.0~dfsg-4.1) ... 425s Setting up xdg-utils (1.1.3-4.1ubuntu3) ... 425s update-alternatives: using /usr/bin/xdg-open to provide /usr/bin/open (open) in auto mode 425s Setting up libcc1-0:amd64 (14-20240303-1ubuntu1) ... 425s Setting up liblsan0:amd64 (14-20240303-1ubuntu1) ... 425s Setting up libjs-bootstrap (3.4.1+dfsg-3) ... 425s Setting up libitm1:amd64 (14-20240303-1ubuntu1) ... 425s Setting up libjs-jquery-selectize.js (0.12.6+dfsg-1.1) ... 425s Setting up libjpeg8:amd64 (8c-2ubuntu11) ... 425s Setting up libice6:amd64 (2:1.0.10-1build2) ... 425s Setting up liblapack3:amd64 (3.12.0-3) ... 425s update-alternatives: using /usr/lib/x86_64-linux-gnu/lapack/liblapack.so.3 to provide /usr/lib/x86_64-linux-gnu/liblapack.so.3 (liblapack.so.3-x86_64-linux-gnu) in auto mode 425s Setting up cpp-13-x86-64-linux-gnu (13.2.0-17ubuntu2) ... 425s Setting up fontconfig-config (2.15.0-1ubuntu1) ... 425s Setting up libjs-twitter-bootstrap-datepicker (1.3.1+dfsg1-4.1) ... 425s Setting up libjs-jquery-datatables (1.11.5+dfsg-2) ... 425s Setting up libthai0:amd64 (0.1.29-2) ... 425s Setting up libjs-jquery-ui (1.13.2+dfsg-1) ... 425s Setting up pandoc (3.1.3+ds-2) ... 425s Setting up libgcc-13-dev:amd64 (13.2.0-17ubuntu2) ... 425s Setting up libtiff6:amd64 (4.5.1+git230720-3ubuntu1) ... 425s Setting up libc6-dev:amd64 (2.39-0ubuntu6) ... 425s Setting up libfontconfig1:amd64 (2.15.0-1ubuntu1) ... 425s Setting up libsm6:amd64 (2:1.2.3-1build2) ... 425s Setting up libstdc++-13-dev:amd64 (13.2.0-17ubuntu2) ... 425s Setting up cpp-x86-64-linux-gnu (4:13.2.0-7ubuntu1) ... 425s Setting up fontconfig (2.15.0-1ubuntu1) ... 427s Regenerating fonts cache... done. 427s Setting up libxft2:amd64 (2.3.6-1) ... 427s Setting up cpp-13 (13.2.0-17ubuntu2) ... 427s Setting up gcc-13-x86-64-linux-gnu (13.2.0-17ubuntu2) ... 427s Setting up libtk8.6:amd64 (8.6.14-1) ... 427s Setting up libpango-1.0-0:amd64 (1.51.0+ds-4) ... 427s Setting up libcairo2:amd64 (1.18.0-1) ... 427s Setting up gcc-13 (13.2.0-17ubuntu2) ... 427s Setting up libxt6:amd64 (1:1.2.1-1.1) ... 427s Setting up cpp (4:13.2.0-7ubuntu1) ... 427s Setting up libpangoft2-1.0-0:amd64 (1.51.0+ds-4) ... 427s Setting up libpangocairo-1.0-0:amd64 (1.51.0+ds-4) ... 427s Setting up g++-13-x86-64-linux-gnu (13.2.0-17ubuntu2) ... 427s Setting up gcc-x86-64-linux-gnu (4:13.2.0-7ubuntu1) ... 427s Setting up gcc (4:13.2.0-7ubuntu1) ... 427s Setting up r-base-core (4.3.2-1build1) ... 427s 427s Creating config file /etc/R/Renviron with new version 427s Setting up r-cran-crayon (1.5.2-1) ... 427s Setting up r-cran-labeling (0.4.3-1) ... 427s Setting up r-cran-sourcetools (0.1.7-1-1) ... 427s Setting up r-cran-lattice (0.22-5-1) ... 427s Setting up r-cran-nlme (3.1.164-1) ... 427s Setting up r-cran-farver (2.1.1-1) ... 427s Setting up r-cran-formula (1.2-5-1) ... 427s Setting up r-cran-viridislite (0.4.2-2) ... 427s Setting up r-cran-cluster (2.1.6-1) ... 427s Setting up g++-x86-64-linux-gnu (4:13.2.0-7ubuntu1) ... 427s Setting up r-cran-nnet (7.3-19-2) ... 427s Setting up r-cran-commonmark (1.9.1-1) ... 427s Setting up r-cran-r6 (2.5.1-1) ... 427s Setting up r-cran-pkgkitten (0.2.3-1) ... 427s Setting up r-cran-jpeg (0.1-10-1) ... 427s Setting up r-cran-chron (2.3-61-2) ... 427s Setting up r-cran-magrittr (2.0.3-1) ... 427s Setting up r-cran-rappdirs (0.3.3-1) ... 427s Setting up r-cran-littler (0.3.19-1) ... 427s Setting up r-cran-fs (1.6.3+dfsg-1) ... 427s Setting up r-cran-rcpp (1.0.12-1) ... 427s Setting up r-cran-codetools (0.2-19-1) ... 427s Setting up g++-13 (13.2.0-17ubuntu2) ... 427s Setting up r-bioc-biocgenerics (0.48.1-2) ... 427s Setting up r-cran-rlang (1.1.3-1) ... 427s Setting up r-cran-matrixstats (1.2.0-1) ... 427s Setting up r-cran-listenv (0.9.1+dfsg-1) ... 427s Setting up littler (0.3.19-1) ... 427s Setting up r-cran-xfun (0.41+dfsg-1) ... 427s Setting up r-cran-withr (2.5.0-1) ... 427s Setting up r-cran-backports (1.4.1-1) ... 427s Setting up r-cran-mime (0.12-1) ... 427s Setting up r-cran-generics (0.1.3-1) ... 427s Setting up r-cran-base64enc (0.1-3-3) ... 427s Setting up r-cran-digest (0.6.34-1) ... 427s Setting up r-cran-yaml (2.3.8-1) ... 427s Setting up r-cran-evaluate (0.23-1) ... 427s Setting up r-cran-highr (0.10+dfsg-1) ... 427s Setting up r-cran-fansi (1.0.5-1) ... 427s Setting up r-cran-mass (7.3-60.0.1-1) ... 427s Setting up r-cran-checkmate (2.3.1-1) ... 427s Setting up r-cran-acepack (1.4.2-1) ... 427s Setting up r-cran-data.table (1.14.10+dfsg-1) ... 427s Setting up r-cran-glue (1.7.0-1) ... 427s Setting up r-cran-foreign (0.8.86-1) ... 427s Setting up r-cran-xtable (1:1.8-4-2) ... 427s Setting up r-cran-cli (3.6.2-1) ... 427s Setting up r-cran-lifecycle (1.0.4+dfsg-1) ... 427s Setting up r-cran-deldir (2.0-4-1) ... 427s Setting up r-cran-fastmap (1.1.1-1) ... 427s Setting up r-cran-png (0.1-8-1) ... 427s Setting up r-cran-r.methodss3 (1.8.2-1) ... 427s Setting up r-cran-jsonlite (1.8.8+dfsg-1) ... 427s Setting up r-cran-rstudioapi (0.15.0-1) ... 427s Setting up r-cran-pkgconfig (2.0.3-2build1) ... 427s Setting up r-cran-utf8 (1.2.4-1) ... 427s Setting up r-cran-colorspace (2.1-0+dfsg-1) ... 427s Setting up r-cran-parallelly (1.37.1-1) ... 427s Setting up r-cran-stringi (1.8.3-1) ... 427s Setting up r-cran-cpp11 (0.4.7-1) ... 427s Setting up r-cran-rcolorbrewer (1.1-3-1build1) ... 427s Setting up r-cran-isoband (0.2.7-1) ... 427s Setting up r-cran-gtable (0.3.4+dfsg-1) ... 427s Setting up r-cran-later (1.3.2+dfsg-1) ... 427s Setting up r-cran-matrix (1.6-5-1) ... 427s Setting up r-cran-tinytex (0.49-1) ... 427s Setting up r-cran-knitr (1.45+dfsg-1) ... 427s Setting up r-cran-mgcv (1.9-1-1) ... 427s Setting up g++ (4:13.2.0-7ubuntu1) ... 427s update-alternatives: using /usr/bin/g++ to provide /usr/bin/c++ (c++) in auto mode 427s Setting up r-bioc-dnacopy (1.76.0-1) ... 427s Setting up r-cran-cachem (1.0.8-1) ... 427s Setting up build-essential (12.10ubuntu1) ... 427s Setting up r-cran-globals (0.16.2-1) ... 427s Setting up r-cran-vctrs (0.6.5-1) ... 427s Setting up r-cran-rcppeigen (0.3.3.9.4-1) ... 427s Setting up r-cran-pillar (1.9.0+dfsg-1) ... 427s Setting up r-cran-ellipsis (0.3.2-2) ... 427s Setting up r-cran-stringr (1.5.1-1) ... 427s Setting up r-cran-munsell (0.5.0-2build1) ... 427s Setting up r-cran-tibble (3.2.1+dfsg-2) ... 427s Setting up r-cran-survival (3.5-8-1) ... 427s Setting up r-cran-r.oo (1.26.0-1) ... 427s Setting up r-cran-future (1.33.1+dfsg-1) ... 427s Setting up r-cran-tidyselect (1.2.0+dfsg-1) ... 427s Setting up r-cran-interp (1.1-6-1) ... 427s Setting up r-cran-gridextra (2.3-3build1) ... 427s Setting up r-cran-scales (1.3.0-1) ... 427s Setting up r-cran-memoise (2.0.1-1) ... 427s Setting up r-cran-promises (1.2.1+dfsg-1) ... 427s Setting up r-cran-purrr (1.0.2-1) ... 427s Setting up r-cran-htmltools (0.5.7-1) ... 427s Setting up r-cran-sass (0.4.8+dfsg-1) ... 427s Setting up r-cran-dplyr (1.1.4-1) ... 427s Setting up r-cran-r.utils (2.12.3-1) ... 427s Setting up r-cran-ggplot2 (3.4.4+dfsg-1) ... 427s Setting up r-cran-httpuv (1.6.14+dfsg-1) ... 427s Setting up r-cran-rpart (4.1.23-1) ... 427s Setting up r-cran-fontawesome (0.5.2-1) ... 427s Setting up r-cran-latticeextra (0.6-30-1) ... 427s Setting up r-cran-jquerylib (0.1.4+dfsg-4) ... 427s Setting up r-cran-viridis (0.6.5-1) ... 427s Setting up r-cran-bslib (0.6.1+dfsg-1) ... 427s Setting up r-cran-tidyr (1.3.1-1) ... 427s Setting up r-bioc-aroma.light (3.32.0-1) ... 427s Setting up r-cran-r.cache (0.16.0-1) ... 427s Setting up r-cran-shiny (1.8.0+dfsg-1) ... 427s Setting up r-cran-pscbs (0.66.0-2) ... 427s Setting up r-cran-rmarkdown (2.25+dfsg-3) ... 427s Setting up r-cran-htmlwidgets (1.6.4+dfsg-1) ... 427s Setting up r-cran-htmltable (2.4.2-1) ... 427s Setting up r-cran-hmisc (5.1-1-1) ... 427s Processing triggers for man-db (2.12.0-3) ... 428s Processing triggers for install-info (7.1-3) ... 428s Processing triggers for libc-bin (2.39-0ubuntu6) ... 430s Reading package lists... 431s Building dependency tree... 431s Reading state information... 431s Starting pkgProblemResolver with broken count: 0 431s Starting 2 pkgProblemResolver with broken count: 0 431s Done 432s The following NEW packages will be installed: 432s autopkgtest-satdep 432s 0 upgraded, 1 newly installed, 0 to remove and 0 not upgraded. 432s Need to get 0 B/696 B of archives. 432s After this operation, 0 B of additional disk space will be used. 432s Get:1 /tmp/autopkgtest.KUoiFr/2-autopkgtest-satdep.deb autopkgtest-satdep amd64 0 [696 B] 432s Selecting previously unselected package autopkgtest-satdep. 432s (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 ... 93360 files and directories currently installed.) 432s Preparing to unpack .../2-autopkgtest-satdep.deb ... 432s Unpacking autopkgtest-satdep (0) ... 432s Setting up autopkgtest-satdep (0) ... 434s (Reading database ... 93360 files and directories currently installed.) 434s Removing autopkgtest-satdep (0) ... 434s autopkgtest [13:44:45]: test run-unit-test: [----------------------- 434s + pkg=r-cran-pscbs 434s + [ /tmp/autopkgtest.KUoiFr/autopkgtest_tmp = ] 434s + cd /tmp/autopkgtest.KUoiFr/autopkgtest_tmp 434s + 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,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 /usr/share/doc/r-cran-pscbs/tests/weightedQuantile.R /tmp/autopkgtest.KUoiFr/autopkgtest_tmp 434s + find . -name *.gz -exec gunzip {} ; 434s + export LC_ALL=C 434s + dpkg-architecture -qDEB_HOST_ARCH 434s + hostarch=i386 434s + [ i386 = armhf ] 434s + ls PairedPSCBS,boot.R findLargeGaps.R randomSeed.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 weightedQuantile.R 434s + sed s/\.R$// 434s + echo Begin test PairedPSCBS,boot 434s + exitcode=0 434s + R CMD BATCH PairedPSCBS,boot.R 434s Begin test PairedPSCBS,boot 437s + cat PairedPSCBS,boot.Rout 437s 437s R version 4.3.2 (2023-10-31) -- "Eye Holes" 437s Copyright (C) 2023 The R Foundation for Statistical Computing 437s Platform: x86_64-pc-linux-gnu (64-bit) 437s 437s R is free software and comes with ABSOLUTELY NO WARRANTY. 437s You are welcome to redistribute it under certain conditions. 437s Type 'license()' or 'licence()' for distribution details. 437s 437s R is a collaborative project with many contributors. 437s Type 'contributors()' for more information and 437s 'citation()' on how to cite R or R packages in publications. 437s 437s Type 'demo()' for some demos, 'help()' for on-line help, or 437s 'help.start()' for an HTML browser interface to help. 437s Type 'q()' to quit R. 437s 437s > ########################################################### 437s > # This tests: 437s > # - Bootstrapping for PairedPSCBS objects 437s > ########################################################### 437s > library("PSCBS") 437s PSCBS v0.66.0 (2021-10-23 07:40:02 UTC) successfully loaded. See ?PSCBS for help. 437s 437s Attaching package: 'PSCBS' 437s 437s The following objects are masked from 'package:base': 437s 437s append, load 437s 437s > 437s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 437s > # Load SNP microarray data 437s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 437s > data <- PSCBS::exampleData("paired.chr01") 437s > 437s > 437s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 437s > # Paired PSCBS segmentation 437s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 437s > # Drop single-locus outliers 437s > dataS <- dropSegmentationOutliers(data) 437s > dataS <- dataS[seq(from=1, to=nrow(data), by=5),] 437s > nSegs <- 4L 437s > str(dataS) 437s 'data.frame': 14670 obs. of 6 variables: 437s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 437s $ x : int 1145994 2941694 3710825 4240737 4276892 4464544 4714611 5095111 5034491 5158416 ... 437s $ CT : num 1.63 1.4 1.41 1.17 1.16 ... 437s $ betaT : num 0.7574 0.169 0.2357 0.2604 0.0576 ... 437s $ CN : num 2.36 2.13 2.26 2.01 2.32 ... 437s $ betaN : num 0.8274 0.5072 0.1671 0.1609 0.0421 ... 437s > # Segment known regions 437s > knownSegments <- data.frame( 437s + chromosome = c( 1, 1, 1), 437s + start = c( -Inf, NA, 141510003), 437s + end = c(120992603, NA, +Inf) 437s + ) 437s > fit <- segmentByPairedPSCBS(dataS, knownSegments=knownSegments, avgDH="median", seed=0xBEEF) 437s > print(fit) 437s chromosome tcnId dhId start end tcnNbrOfLoci tcnMean tcnNbrOfSNPs 437s 1 1 1 1 554484 120992603 7586 1.385258 2108 437s 2 NA 2 1 NA NA NA NA 0 437s 3 1 3 1 141510003 185449813 2681 2.068861 777 437s 4 1 4 1 185449813 247137334 4391 2.634110 1311 437s tcnNbrOfHets dhNbrOfLoci dhMean c1Mean c2Mean 437s 1 2108 2108 0.54551245 0.3147912 1.070467 437s 2 0 0 NA NA NA 437s 3 777 777 0.07132277 0.9606521 1.108209 437s 4 1311 1311 0.21663871 1.0317300 1.602380 437s > 437s > 437s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 437s > # Bootstrap 437s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 437s > B <- 1L 437s > seed <- 0xBEEF 437s > probs <- c(0.025, 0.05, 0.95, 0.975) 437s > 437s > sets <- getBootstrapLocusSets(fit, B=B, seed=seed) 437s > 437s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 437s > # Subset by first segment 437s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 437s > ss <- 1L 437s > 437s > fitT <- extractSegment(fit, ss) 437s > dataT <- getLocusData(fitT) 437s > segsT <- getSegments(fitT) 437s > 437s > # Truth 437s > bootT <- bootstrapSegmentsAndChangepoints(fitT, B=B, seed=seed) 437s > bootT1 <- bootT$segments[1L,,,drop=FALSE] 437s > types <- dimnames(bootT1)[[3L]] 437s > dim(bootT1) <- dim(bootT1)[-1L] 437s > colnames(bootT1) <- types 437s > sumsT <- apply(bootT1, MARGIN=2L, FUN=quantile, probs=probs) 437s > print(sumsT) 437s tcn dh c1 c2 437s 2.5% 1.383213 0.5466788 0.3135198 1.069693 437s 5% 1.383213 0.5466788 0.3135198 1.069693 437s 95% 1.383213 0.5466788 0.3135198 1.069693 437s 97.5% 1.383213 0.5466788 0.3135198 1.069693 437s > 437s > fitTB <- bootstrapTCNandDHByRegion(fitT, B=B, seed=seed) 437s > segsTB <- getSegments(fitTB) 437s > segsTB <- unlist(segsTB[,grep("_", colnames(segsTB))]) 437s > dim(segsTB) <- dim(sumsT) 437s > dimnames(segsTB) <- dimnames(sumsT) 437s > print(segsTB) 437s tcn dh c1 c2 437s 2.5% 1.383213 0.5466788 0.3135198 1.069693 437s 5% 1.383213 0.5466788 0.3135198 1.069693 437s 95% 1.383213 0.5466788 0.3135198 1.069693 437s 97.5% 1.383213 0.5466788 0.3135198 1.069693 437s > 437s > # Sanity check 437s > stopifnot(all.equal(segsTB, sumsT)) 437s > 437s > # Calculate summaries using the existing bootstrap samples 437s > fitTBp <- bootstrapTCNandDHByRegion(fitT, .boot=bootT) 437s > # Sanity check 437s > all.equal(fitTBp, fitTB) 437s [1] "Component \"tcn_2.5%\": Mean relative difference: 0.003070405" 437s [2] "Component \"tcn_5%\": Mean relative difference: 0.002241362" 437s [3] "Component \"tcn_95%\": Mean relative difference: 0.005458479" 437s [4] "Component \"tcn_97.5%\": Mean relative difference: 0.006030363" 437s [5] "Component \"dh_2.5%\": Mean relative difference: 0.02683423" 437s [6] "Component \"dh_5%\": Mean relative difference: 0.02409533" 437s [7] "Component \"dh_95%\": Mean relative difference: 0.0150081" 437s [8] "Component \"dh_97.5%\": Mean relative difference: 0.01826461" 437s [9] "Component \"c1_2.5%\": Mean relative difference: 0.02397349" 437s [10] "Component \"c1_5%\": Mean relative difference: 0.01800948" 437s [11] "Component \"c1_95%\": Mean relative difference: 0.0303456" 437s [12] "Component \"c1_97.5%\": Mean relative difference: 0.03420614" 437s [13] "Component \"c2_2.5%\": Mean relative difference: 0.008723378" 437s [14] "Component \"c2_5%\": Mean relative difference: 0.006834962" 437s [15] "Component \"c2_95%\": Mean relative difference: 0.00741949" 437s [16] "Component \"c2_97.5%\": Mean relative difference: 0.008743911" 437s attr(,"what") 437s [1] "getSegments()" 437s > 437s > 437s > # Bootstrap from scratch 437s > setsT <- getBootstrapLocusSets(fitT, B=B, seed=seed) 437s > lociT <- setsT$locusSet[[1L]]$bootstrap$loci 437s > idxs <- lociT$tcn 437s > tcnT <- array(dataT$CT[idxs], dim=dim(idxs)) 437s > tcnT <- apply(tcnT, MARGIN=2L, FUN=mean, na.rm=TRUE) 437s > idxs <- lociT$dh 437s > dhT <- array(dataT$rho[idxs], dim=dim(idxs)) 437s > dhT <- apply(dhT, MARGIN=2L, FUN=median, na.rm=TRUE) 437s > c1T <- (1-dhT) * tcnT / 2 437s > c2T <- tcnT - c1T 437s > bootT2 <- array(c(tcnT, dhT, c1T, c2T), dim=c(1L, 4L)) 437s > colnames(bootT2) <- colnames(bootT1) 437s > print(bootT2) 437s tcn dh c1 c2 437s [1,] 1.383213 0.5466788 0.3135198 1.069693 437s > 437s > # This comparison is only valid if B == 1L 437s > if (B == 1L) { 437s + # Sanity check 437s + stopifnot(all.equal(bootT2, bootT1)) 437s + } 437s > 437s > proc.time() 437s user system elapsed 437s 2.182 0.151 2.284 437s Test PairedPSCBS,boot passed 437s 0 437s Begin test findLargeGaps 437s + [ 0 != 0 ] 437s + echo Test PairedPSCBS,boot passed 437s + echo 0 437s + echo Begin test findLargeGaps 437s + exitcode=0 437s + R CMD BATCH findLargeGaps.R 438s + cat findLargeGaps.Rout 438s 438s R version 4.3.2 (2023-10-31) -- "Eye Holes" 438s Copyright (C) 2023 The R Foundation for Statistical Computing 438s Platform: x86_64-pc-linux-gnu (64-bit) 438s 438s R is free software and comes with ABSOLUTELY NO WARRANTY. 438s You are welcome to redistribute it under certain conditions. 438s Type 'license()' or 'licence()' for distribution details. 438s 438s R is a collaborative project with many contributors. 438s Type 'contributors()' for more information and 438s 'citation()' on how to cite R or R packages in publications. 438s 438s Type 'demo()' for some demos, 'help()' for on-line help, or 438s 'help.start()' for an HTML browser interface to help. 438s Type 'q()' to quit R. 438s 438s [Previously saved workspace restored] 438s 438s > library("PSCBS") 438s PSCBS v0.66.0 (2021-10-23 07:40:02 UTC) successfully loaded. See ?PSCBS for help. 438s 438s Attaching package: 'PSCBS' 438s 438s The following objects are masked from 'package:base': 438s 438s append, load 438s 438s > 438s > # Simulating copy-number data 438s > set.seed(0xBEEF) 438s > 438s > # Simulate CN data 438s > J <- 1000 438s > mu <- double(J) 438s > mu[200:300] <- mu[200:300] + 1 438s > mu[350:400] <- NA # centromere 438s > mu[650:800] <- mu[650:800] - 1 438s > eps <- rnorm(J, sd=1/2) 438s > y <- mu + eps 438s > x <- seq(from=1, to=100e6, length.out=J) 438s > 438s > data <- data.frame(chromosome=0L, x=x) 438s > 438s > gaps <- findLargeGaps(x=x, minLength=1e6) 438s > print(gaps) 438s [1] start end length 438s <0 rows> (or 0-length row.names) 438s > stopifnot(is.data.frame(gaps)) 438s > stopifnot(nrow(gaps) == 0L) 438s > segs <- gapsToSegments(gaps) 438s > print(segs) 438s chromosome start end 438s 1 0 -Inf Inf 438s > stopifnot(is.data.frame(segs)) 438s > stopifnot(nrow(segs) == 1L) 438s > 438s > 438s > gaps <- findLargeGaps(data, minLength=1e6) 438s > print(gaps) 438s [1] chromosome start end 438s <0 rows> (or 0-length row.names) 438s > stopifnot(is.data.frame(gaps)) 438s > stopifnot(nrow(gaps) == 0L) 438s > segs <- gapsToSegments(gaps) 438s > print(segs) 438s chromosome start end 438s 1 0 -Inf Inf 438s > stopifnot(is.data.frame(segs)) 438s > stopifnot(nrow(segs) == 1L) 438s > 438s > 438s > ## Add missing values 438s > data2 <- data 438s > data$x[30e6 < x & x < 50e6] <- NA 438s > gaps <- findLargeGaps(data, minLength=1e6) 438s > print(gaps) 438s chromosome start end length 438s 1 0 29929932 50050050 20120118 438s > stopifnot(is.data.frame(gaps)) 438s > stopifnot(nrow(gaps) == 1L) 438s > segs <- gapsToSegments(gaps) 438s > print(segs) 438s chromosome start end length 438s 1 0 -Inf 29929931 Inf 438s 2 0 29929932 50050050 20120118 438s 3 0 50050051 Inf Inf 438s > stopifnot(is.data.frame(segs)) 438s > stopifnot(nrow(segs) == 3L) 438s > 438s > 438s > 438s > # BUG FIX: Issue #6 438s > gaps <- findLargeGaps(chromosome=rep(1,10), x=1:10, minLength=2) 438s > print(gaps) 438s [1] chromosome start end 438s <0 rows> (or 0-length row.names) 438s > stopifnot(is.data.frame(gaps)) 438s > stopifnot(nrow(gaps) == 0L) 438s > # BUG FIX: Issue #9 438s > segs <- gapsToSegments(gaps) 438s > print(segs) 438s chromosome start end 438s 1 0 -Inf Inf 438s > stopifnot(is.data.frame(segs)) 438s > stopifnot(nrow(segs) == 1L) 438s > 438s > 438s > # BUG FIX: PSCBS GitHub Issue #8 438s > gaps <- try({ 438s + findLargeGaps(chromosome=rep(1,3), x=as.numeric(1:3), minLength=1) 438s + }) 438s Error in findLargeGaps.default(chromosome = rep(1, 3), x = as.numeric(1:3), : 438s Cannot identify large gaps. Argument 'resolution' (=1) is not strictly smaller than 'minLength' (=1). 438s > stopifnot(inherits(gaps, "try-error")) 438s > 438s > proc.time() 438s user system elapsed 438s 0.391 0.046 0.420 438s + [ 0 != 0 ] 438s + echo Test findLargeGaps passed 438s + echo 0 438s + echo Begin test randomSeed 438s + exitcode=0 438s + R CMD BATCH randomSeed.R 438s Test findLargeGaps passed 438s 0 438s Begin test randomSeed 438s + cat randomSeed.Rout 438s 438s R version 4.3.2 (2023-10-31) -- "Eye Holes" 438s Copyright (C) 2023 The R Foundation for Statistical Computing 438s Platform: x86_64-pc-linux-gnu (64-bit) 438s 438s R is free software and comes with ABSOLUTELY NO WARRANTY. 438s You are welcome to redistribute it under certain conditions. 438s Type 'license()' or 'licence()' for distribution details. 438s 438s R is a collaborative project with many contributors. 438s Type 'contributors()' for more information and 438s 'citation()' on how to cite R or R packages in publications. 438s 438s Type 'demo()' for some demos, 'help()' for on-line help, or 438s 'help.start()' for an HTML browser interface to help. 438s Type 'q()' to quit R. 438s 438s [Previously saved workspace restored] 438s 438s > library("PSCBS") 438s PSCBS v0.66.0 (2021-10-23 07:40:02 UTC) successfully loaded. See ?PSCBS for help. 438s 438s Attaching package: 'PSCBS' 438s 438s The following objects are masked from 'package:base': 438s 438s append, load 438s 438s > 438s > message("*** randomSeed() - setup ...") 438s *** randomSeed() - setup ... 438s > ovars <- ls(envir=globalenv()) 438s > genv <- globalenv() 438s > RNGkind("Mersenne-Twister") 438s > if (exists(".Random.seed", envir=genv, inherits=FALSE)) 438s + rm(list=".Random.seed", envir=genv, inherits=FALSE) 438s > seed0 <- genv$.Random.seed 438s > stopifnot(is.null(seed0)) 438s > okind0 <- RNGkind()[1L] 438s > 438s > sample1 <- function() { sample(0:9, size=1L) } 438s > message("*** randomSeed() - setup ... done") 438s *** randomSeed() - setup ... done 438s > 438s > 438s > message("*** randomSeed('get') ...") 438s *** randomSeed('get') ... 438s > ## Get random seed 438s > seed <- randomSeed("get") 438s > stopifnot(identical(seed, seed0)) 438s > 438s > ## Repeat after new sample 438s > y1 <- sample1() 438s > message(sprintf("Random number: %d", y1)) 438s Random number: 6 438s > seed1 <- randomSeed("get") 438s > stopifnot(!identical(seed1, seed0)) 438s > message("*** randomSeed('get') ... done") 438s *** randomSeed('get') ... done 438s > 438s > 438s > message("*** randomSeed('set', 42L) ...") 438s *** randomSeed('set', 42L) ... 438s > randomSeed("set", seed=42L) 438s > seed2 <- randomSeed("get") 438s > stopifnot(!identical(seed2, seed1)) 438s > 438s > y2 <- sample1() 438s > message(sprintf("Random number: %d (with random seed = 42L)", y2)) 438s Random number: 0 (with random seed = 42L) 438s > 438s > ## Reset to previous state 438s > randomSeed("reset") 438s > seed3 <- randomSeed("get") 438s > stopifnot(identical(seed3, seed1)) 438s > stopifnot(identical(RNGkind()[1L], okind0), 438s + identical(randomSeed("get"), seed1)) 438s > message("*** randomSeed('set', 42L) ... done") 438s *** randomSeed('set', 42L) ... done 438s > 438s > 438s > message("*** randomSeed('set', NULL) ...") 438s *** randomSeed('set', NULL) ... 438s > randomSeed("set", seed=NULL) 438s > seed4 <- randomSeed("get") 438s > stopifnot(is.null(seed4)) 438s > 438s > y3 <- sample1() 438s > message(sprintf("Random number: %d", y3)) 438s Random number: 7 438s > 438s > message("*** randomSeed('set', NULL) ... done") 438s *** randomSeed('set', NULL) ... done 438s > 438s > 438s > message("*** randomSeed('set', 42L) again ...") 438s *** randomSeed('set', 42L) again ... 438s > seed5 <- randomSeed("get") 438s > randomSeed("set", seed=42L) 438s > y4 <- sample1() 438s > message(sprintf("Random number: %d (with random seed = 42L)", y4)) 438s Random number: 0 (with random seed = 42L) 438s > stopifnot(identical(y4, y2)) 438s > 438s > randomSeed("reset") 438s > stopifnot(identical(RNGkind()[1L], okind0), 438s + identical(randomSeed("get"), seed5)) 438s > message("*** randomSeed('set', 42L) again ... done") 438s *** randomSeed('set', 42L) again ... done 438s > 438s > 438s > 438s > ## L'Ecuyer-CMRG: Random number generation for parallel processing 438s > message("*** randomSeed(): L'Ecuyer-CMRG stream ...") 438s *** randomSeed(): L'Ecuyer-CMRG stream ... 438s > 438s > okind <- RNGkind()[1L] 438s > stopifnot(identical(okind, okind0)) 438s > 438s > randomSeed("set", seed=NULL) 438s > oseed <- randomSeed("get") 438s > stopifnot(is.null(oseed)) 438s > 438s > randomSeed("set", seed=42L, kind="L'Ecuyer-CMRG") 438s > oseed2 <- randomSeed("reset") 438s > str(oseed2) 438s NULL 438s > stopifnot(identical(oseed2, oseed)) 438s > stopifnot(identical(RNGkind()[1L], okind), 438s + identical(randomSeed("get"), oseed)) 438s > 438s > randomSeed("set", seed=42L, kind="L'Ecuyer-CMRG") 438s > seed0 <- randomSeed("get") 438s > seeds0 <- lapply(1:10, FUN=function(i) randomSeed("advance")) 438s > oseed2 <- randomSeed("reset") 438s > stopifnot(identical(oseed2, oseed)) 438s > stopifnot(identical(RNGkind()[1L], okind), 438s + identical(randomSeed("get"), oseed)) 438s > 438s > 438s > ## Assert reproducible .Random.seed stream 438s > randomSeed("set", seed=42L, kind="L'Ecuyer-CMRG") 438s > seed1 <- randomSeed("get") 438s > seeds1 <- lapply(1:10, FUN=function(i) randomSeed("advance")) 438s > stopifnot(identical(seed1, seed0)) 438s > stopifnot(identical(seeds1, seeds0)) 438s > 438s > randomSeed("reset") 438s > stopifnot(identical(RNGkind()[1L], okind), 438s + identical(randomSeed("get"), oseed)) 438s > 438s > randomSeed("set", seed=42L, kind="L'Ecuyer-CMRG") 438s > seeds2 <- randomSeed("advance", n=10L) 438s > stopifnot(identical(seeds2, seeds0)) 438s > 438s > randomSeed("reset") 438s > stopifnot(identical(RNGkind()[1L], okind), 438s + identical(randomSeed("get"), oseed)) 438s > 438s > randomSeed("set", seed=seeds2[[1]], kind="L'Ecuyer-CMRG") 438s > randomSeed("reset") 438s > stopifnot(identical(RNGkind()[1L], okind), 438s + identical(randomSeed("get"), oseed)) 438s > 438s > randomSeed("set", seed=42L, kind="L'Ecuyer-CMRG") 438s > y0 <- sapply(1:10, FUN=function(ii) { 438s + randomSeed("advance") 438s + sample1() 438s + }) 438s > print(y0) 438s [1] 6 9 6 9 9 9 0 7 6 5 438s > randomSeed("reset") 438s > 438s > randomSeed("set", seed=42L, kind="L'Ecuyer-CMRG") 438s > y1 <- sapply(1:10, FUN=function(ii) { 438s + randomSeed("advance") 438s + sample1() 438s + }) 438s > print(y1) 438s [1] 6 9 6 9 9 9 0 7 6 5 438s > stopifnot(identical(y1, y0)) 438s > randomSeed("reset") 438s > 438s > stopifnot(identical(RNGkind()[1L], okind)) 438s > 438s > message("*** randomSeed(): L'Ecuyer-CMRG stream ... done") 438s *** randomSeed(): L'Ecuyer-CMRG stream ... done 438s > 438s > 438s > ## Cleanup 438s > message("*** randomSeed() - cleanup ...") 438s *** randomSeed() - cleanup ... 438s > genv <- globalenv() 438s > RNGkind("Mersenne-Twister") 438s > if (exists(".Random.seed", envir=genv, inherits=FALSE)) 438s + rm(list=".Random.seed", envir=genv, inherits=FALSE) 438s > rm(list=ovars, envir=globalenv()) 438s > message("*** randomSeed() - cleanup ... done") 438s *** randomSeed() - cleanup ... done 438s > 438s > proc.time() 438s user system elapsed 438s 0.321 0.071 0.376 438s Test randomSeed passed 438s 0 438s Begin test segmentByCBS,calls 438s + [ 0 != 0 ] 438s + echo Test randomSeed passed 438s + echo 0 438s + echo Begin test segmentByCBS,calls 438s + exitcode=0 438s + R CMD BATCH segmentByCBS,calls.R 438s 438s R version 4.3.2 (2023-10-31) -- "Eye Holes" 438s Copyright (C) 2023 The R Foundation for Statistical Computing 438s Platform: x86_64-pc-linux-gnu (64-bit) 438s 438s R is free software and comes with ABSOLUTELY NO WARRANTY. 438s You are welcome to redistribute it under certain conditions. 438s Type 'license()' or 'licence()' for distribution details. 438s 438s R is a collaborative project with many contributors. 438s Type 'contributors()' for more information and 438s 'citation()' on how to cite R or R packages in publications. 438s 438s Type 'demo()' for some demos, 'help()' for on-line help, or 438s 'help.start()' for an HTML browser interface to help. 438s Type 'q()' to quit R. 438s 438s [Previously saved workspace restored] 438s 438s > # This test script calls a report generator which requires 438s > # the 'ggplot2' package, which in turn will require packages 438s > # 'colorspace', 'dichromat', 'munsell', 'reshape2' and 'scales'. 438s > 438s > # Only run this test in full testing mode 438s > if (Sys.getenv("_R_CHECK_FULL_") != "") { 438s + library("PSCBS") 438s + stext <- R.utils::stext 438s + 438s + # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 438s + # Load SNP microarray data 438s + # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 438s + data <- PSCBS::exampleData("paired.chr01") 438s + str(data) 438s + 438s + data <- data.frame(chromosome=data$chromosome, x=data$x, y=data$CT) 438s + 438s + 438s + # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 438s + # CBS segmentation 438s + # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 438s + # Drop single-locus outliers 438s + dataS <- dropSegmentationOutliers(data) 438s + 438s + # Speed up example by segmenting fewer loci 438s + dataS <- dataS[seq(from=1, to=nrow(data), by=5),] 438s + 438s + str(dataS) 438s + 438s + gaps <- findLargeGaps(dataS, minLength=2e6) 438s + knownSegments <- gapsToSegments(gaps) 438s + 438s + # CBS segmentation 438s + fit <- segmentByCBS(dataS, knownSegments=knownSegments, 438s + seed=0xBEEF, verbose=-10) 438s + signalType(fit) <- "ratio" 438s + plotTracks(fit) 438s + 438s + 438s + # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 438s + # Call using the UCSF MAD caller (not recommended) 438s + # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 438s + fitC <- callGainsAndLosses(fit) 438s + plotTracks(fitC) 438s + pars <- fitC$params$callGainsAndLosses 438s + stext(side=3, pos=1/2, line=-1, substitute(sigma==x, list(x=sprintf("%.2f", pars$sigmaMAD)))) 438s + mu <- pars$muR 438s + tau <- unlist(pars[c("tauLoss", "tauGain")], use.names=FALSE) 438s + abline(h=mu, lty=2, lwd=2) 438s + abline(h=tau, lwd=2) 438s + mtext(side=4, at=tau[1], expression(Delta[LOSS]), adj=-0.2, cex=0.7, las=2, xpd=TRUE) 438s + mtext(side=4, at=tau[2], expression(Delta[GAIN]), adj=-0.2, cex=0.7, las=2, xpd=TRUE) 438s + title(main="CN caller: \"ucsf-mad\"") 438s + 438s + 438s + # Caller to be implemented 438s + deltaCN <- estimateDeltaCN(fit) 438s + tau <- mu + 1/2*c(-1,+1)*deltaCN 438s + abline(h=tau, lty=2, lwd=1, col="red") 438s + 438s + 438s + 438s + } # if (Sys.getenv("_R_CHECK_FULL_")) 438s > 438s > proc.time() 438s user system elapsed 438s 0.127 0.029 0.144 438s Test segmentByCBS,calls passed 438s 0 438s Begin test segmentByCBS,futures 438s + cat segmentByCBS,calls.Rout 438s + [ 0 != 0 ] 438s + echo Test segmentByCBS,calls passed 438s + echo 0 438s + echo Begin test segmentByCBS,futures 438s + exitcode=0 438s + R CMD BATCH segmentByCBS,futures.R 442s + cat segmentByCBS,futures.Rout 442s 442s R version 4.3.2 (2023-10-31) -- "Eye Holes" 442s Copyright (C) 2023 The R Foundation for Statistical Computing 442s Platform: x86_64-pc-linux-gnu (64-bit) 442s 442s R is free software and comes with ABSOLUTELY NO WARRANTY. 442s You are welcome to redistribute it under certain conditions. 442s Type 'license()' or 'licence()' for distribution details. 442s 442s R is a collaborative project with many contributors. 442s Type 'contributors()' for more information and 442s 'citation()' on how to cite R or R packages in publications. 442s 442s Type 'demo()' for some demos, 'help()' for on-line help, or 442s 'help.start()' for an HTML browser interface to help. 442s Type 'q()' to quit R. 442s 442s [Previously saved workspace restored] 442s 442s > library("PSCBS") 442s PSCBS v0.66.0 (2021-10-23 07:40:02 UTC) successfully loaded. See ?PSCBS for help. 442s 442s Attaching package: 'PSCBS' 442s 442s The following objects are masked from 'package:base': 442s 442s append, load 442s 442s > 442s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 442s > # Simulating copy-number data 442s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 442s > set.seed(0xBEEF) 442s > 442s > # Number of loci 442s > J <- 1000 442s > 442s > mu <- double(J) 442s > mu[200:300] <- mu[200:300] + 1 442s > mu[350:400] <- NA # centromere 442s > mu[650:800] <- mu[650:800] - 1 442s > eps <- rnorm(J, sd=1/2) 442s > y <- mu + eps 442s > x <- sort(runif(length(y), max=length(y))) * 1e5 442s > w <- runif(J) 442s > w[650:800] <- 0.001 442s > 442s > ## Create multiple chromosomes 442s > data <- knownSegments <- list() 442s > for (cc in 1:3) { 442s + data[[cc]] <- data.frame(chromosome=cc, y=y, x=x) 442s + knownSegments[[cc]] <- data.frame( 442s + chromosome=c( cc, cc, cc), 442s + start =x[c( 1, 350, 401)], 442s + end =x[c(349, 400, J)] 442s + ) 442s + } 442s > data <- Reduce(rbind, data) 442s > str(data) 442s 'data.frame': 3000 obs. of 3 variables: 442s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 442s $ y : num 0.295 0.115 -0.194 -0.392 -0.518 ... 442s $ x : num 55168 593204 605649 630624 746896 ... 442s > knownSegments <- Reduce(rbind, knownSegments) 442s > str(knownSegments) 442s 'data.frame': 9 obs. of 3 variables: 442s $ chromosome: int 1 1 1 2 2 2 3 3 3 442s $ start : num 55168 34194740 41080533 55168 34194740 ... 442s $ end : num 34142178 41044125 99910827 34142178 41044125 ... 442s > 442s > message("*** segmentByCBS() via futures ...") 442s *** segmentByCBS() via futures ... 442s > 442s > 442s > message("*** segmentByCBS() via futures with 'future' attached ...") 442s *** segmentByCBS() via futures with 'future' attached ... 442s > library("future") 442s > oplan <- plan() 442s > 442s > strategies <- c("sequential", "multisession") 442s > 442s > ## Test 'future.batchtools' futures? 442s > pkg <- "future.batchtools" 442s > if (require(pkg, character.only=TRUE)) { 442s + strategies <- c(strategies, "batchtools_local") 442s + } 442s Loading required package: future.batchtools 442s Warning message: 442s In library(package, lib.loc = lib.loc, character.only = TRUE, logical.return = TRUE, : 442s there is no package called 'future.batchtools' 442s > 442s > message("Future strategies to test: ", paste(sQuote(strategies), collapse=", ")) 442s Future strategies to test: 'sequential', 'multisession' 442s > 442s > fits <- list() 442s > for (strategy in strategies) { 442s + message(sprintf("- segmentByCBS() using '%s' futures ...", strategy)) 442s + plan(strategy) 442s + fit <- segmentByCBS(data, seed=0xBEEF, verbose=TRUE) 442s + fits[[strategy]] <- fit 442s + stopifnot(all.equal(fit, fits[[1]])) 442s + } 442s - segmentByCBS() using 'sequential' futures ... 442s Segmenting by CBS... 442s Segmenting multiple chromosomes... 442s Number of chromosomes: 3 442s Random seed temporarily set (seed=c(48879), kind="L'Ecuyer-CMRG") 442s Produced 3 seeds from this stream for future usage 442s Chromosome #1 ('Chr01') of 3... 442s Segmenting by CBS... 442s Chromosome: 1 442s Random seed temporarily set (seed=c(10407, 1066287653, -51199871, 161854402, -1995183193, 1503453565, -747102133), kind="L'Ecuyer-CMRG") 442s Segmenting by CBS...done 442s Chromosome #1 ('Chr01') of 3...done 442s Chromosome #2 ('Chr02') of 3... 442s Segmenting by CBS... 442s Chromosome: 2 442s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 442s Segmenting by CBS...done 442s Chromosome #2 ('Chr02') of 3...done 442s Chromosome #3 ('Chr03') of 3... 442s Segmenting by CBS... 442s Chromosome: 3 442s Random seed temporarily set (seed=c(10407, -821273412, -52578226, 1415511586, 721384351, -665928286, 1316562960), kind="L'Ecuyer-CMRG") 442s Segmenting by CBS...done 442s Chromosome #3 ('Chr03') of 3...done 442s Segmenting multiple chromosomes...done 442s Segmenting by CBS...done 442s list() 442s - segmentByCBS() using 'multisession' futures ... 442s Segmenting by CBS... 442s Segmenting multiple chromosomes... 442s Number of chromosomes: 3 442s Random seed temporarily set (seed=c(48879), kind="L'Ecuyer-CMRG") 442s Produced 3 seeds from this stream for future usage 442s Chromosome #1 ('Chr01') of 3... 442s Chromosome #1 ('Chr01') of 3...done 442s Chromosome #2 ('Chr02') of 3... 442s Random seed temporarily set (seed=c(10407, 1066287653, -51199871, 161854402, -1995183193, 1503453565, -747102133), kind="L'Ecuyer-CMRG") 442s Segmenting by CBS...done 442s Chromosome #2 ('Chr02') of 3...done 442s Chromosome #3 ('Chr03') of 3... 442s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 442s Segmenting by CBS...done 442s Chromosome #3 ('Chr03') of 3...done 442s Segmenting by CBS... 442s Chromosome: 3 442s Random seed temporarily set (seed=c(10407, -821273412, -52578226, 1415511586, 721384351, -665928286, 1316562960), kind="L'Ecuyer-CMRG") 442s Segmenting by CBS...done 442s Segmenting multiple chromosomes...done 442s Segmenting by CBS...done 442s list() 442s > 442s > 442s > message("*** segmentByCBS() via futures with known segments ...") 442s *** segmentByCBS() via futures with known segments ... 442s > fits <- list() 442s > dataT <- subset(data, chromosome == 1) 442s > for (strategy in strategies) { 442s + message(sprintf("- segmentByCBS() w/ known segments using '%s' futures ...", strategy)) 442s + plan(strategy) 442s + fit <- segmentByCBS(dataT, knownSegments=knownSegments, seed=0xBEEF, verbose=TRUE) 442s + fits[[strategy]] <- fit 442s + stopifnot(all.equal(fit, fits[[1]])) 442s + } 442s - segmentByCBS() w/ known segments using 'sequential' futures ... 442s Segmenting by CBS... 442s Chromosome: 1 442s Random seed temporarily set (seed=c(48879), kind="L'Ecuyer-CMRG") 442s Produced 3 seeds from this stream for future usage 442s Segmenting by CBS...done 442s list() 442s - segmentByCBS() w/ known segments using 'multisession' futures ... 442s Segmenting by CBS... 442s Chromosome: 1 442s Random seed temporarily set (seed=c(48879), kind="L'Ecuyer-CMRG") 442s Produced 3 seeds from this stream for future usage 442s Segmenting by CBS...done 442s list() 442s > 442s > message("*** segmentByCBS() via futures ... DONE") 442s *** segmentByCBS() via futures ... DONE 442s > 442s > 442s > ## Cleanup 442s > plan(oplan) 442s > rm(list=c("fits", "dataT", "data", "fit")) 442s > 442s > 442s > proc.time() 442s user system elapsed 442s 1.645 0.110 4.208 442s Test segmentByCBS,futures passed 442s 0 442s + [ 0 != 0 ] 442s + echo Test segmentByCBS,futures passed 442s + echo 0 442s + echo Begin test segmentByCBS,median 442s + exitcode=0 442s + R CMD BATCH segmentByCBS,median.R 442s Begin test segmentByCBS,median 445s + cat segmentByCBS,median.Rout 445s 445s R version 4.3.2 (2023-10-31) -- "Eye Holes" 445s Copyright (C) 2023 The R Foundation for Statistical Computing 445s Platform: x86_64-pc-linux-gnu (64-bit) 445s 445s R is free software and comes with ABSOLUTELY NO WARRANTY. 445s You are welcome to redistribute it under certain conditions. 445s Type 'license()' or 'licence()' for distribution details. 445s 445s R is a collaborative project with many contributors. 445s Type 'contributors()' for more information and 445s 'citation()' on how to cite R or R packages in publications. 445s 445s Type 'demo()' for some demos, 'help()' for on-line help, or 445s 'help.start()' for an HTML browser interface to help. 445s Type 'q()' to quit R. 445s 445s [Previously saved workspace restored] 445s 445s > library("PSCBS") 445s PSCBS v0.66.0 (2021-10-23 07:40:02 UTC) successfully loaded. See ?PSCBS for help. 445s 445s Attaching package: 'PSCBS' 445s 445s The following objects are masked from 'package:base': 445s 445s append, load 445s 445s > 445s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 445s > # Simulating copy-number data 445s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 445s > set.seed(0xBEEF) 445s > 445s > # Number of loci 445s > J <- 1000 445s > 445s > x <- sort(runif(J, max=J)) * 1e5 445s > 445s > mu <- double(J) 445s > mu[200:300] <- mu[200:300] + 1 445s > mu[350:400] <- NA # centromere 445s > mu[650:800] <- mu[650:800] - 1 445s > eps <- rnorm(J, sd=1/2) 445s > y <- mu + eps 445s > 445s > outliers <- seq(from=1L, to=J, length.out=0.2*J) 445s > y[outliers] <- y[outliers] + 1.5 445s > 445s > w <- rep(1.0, times=J) 445s > w[outliers] <- 0.01 445s > 445s > data <- data.frame(chromosome=1L, x=x, y=y) 445s > dataW <- cbind(data, w=w) 445s > 445s > 445s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 445s > # Single-chromosome segmentation 445s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 445s > par(mar=c(2,3,0.2,1)+0.1) 445s > # Segment without weights 445s > fit <- segmentByCBS(data) 445s > sampleName(fit) <- "CBS_Example" 445s > print(fit) 445s sampleName chromosome start end nbrOfLoci mean 445s 1 CBS_Example 1 6.066868e+02 19076007 199 0.2622 445s 2 CBS_Example 1 1.907601e+07 29630949 99 1.4289 445s 3 CBS_Example 1 2.963095e+07 63224332 299 0.2854 445s 4 CBS_Example 1 6.322433e+07 78801707 153 -0.7408 445s 5 CBS_Example 1 7.880171e+07 99917418 199 0.3541 445s > plotTracks(fit) 445s Warning message: 445s In plotTracks.CBS(fit) : 445s Setting default 'Clim' assuming the signal type is 'ratio' because signalType(fit) is unknown ('NA'). Use signalType(fit) <- 'ratio' to avoid this warning. 445s > ## Highlight outliers (they pull up the mean levels) 445s > points(x[outliers]/1e6, y[outliers], col="purple") 445s > 445s > # Segment without weights but with median 445s > fitM <- segmentByCBS(data, avg="median") 445s > sampleName(fitM) <- "CBS_Example (median)" 445s > print(fitM) 445s sampleName chromosome start end nbrOfLoci mean 445s 1 CBS_Example (median) 1 6.066868e+02 19076007 199 0.1005418 445s 2 CBS_Example (median) 1 1.907601e+07 29630949 99 1.2720955 445s 3 CBS_Example (median) 1 2.963095e+07 63224332 299 0.1337148 445s 4 CBS_Example (median) 1 6.322433e+07 78801707 153 -0.8655254 445s 5 CBS_Example (median) 1 7.880171e+07 99917418 199 0.1718179 445s > drawLevels(fitM, col="magenta", lty=3) 445s NULL 445s > 445s > # Segment with weights 445s > fitW <- segmentByCBS(dataW, avg="median") 445s > sampleName(fitW) <- "CBS_Example (weighted)" 445s > print(fitW) 445s sampleName chromosome start end nbrOfLoci mean 445s 1 CBS_Example (weighted) 1 6.066868e+02 19076007 199 -0.08745973 445s 2 CBS_Example (weighted) 1 1.907601e+07 30126128 101 1.12968951 445s 3 CBS_Example (weighted) 1 3.012613e+07 63224332 297 -0.06074638 445s 4 CBS_Example (weighted) 1 6.322433e+07 78801707 153 -1.06373835 445s 5 CBS_Example (weighted) 1 7.880171e+07 99917418 199 0.04204744 445s > drawLevels(fitW, col="red") 445s NULL 445s > 445s > # Segment with weights and median 445s > fitWM <- segmentByCBS(dataW, avg="median") 445s > sampleName(fitWM) <- "CBS_Example (weighted median)" 445s > print(fitWM) 445s sampleName chromosome start end nbrOfLoci 445s 1 CBS_Example (weighted median) 1 6.066868e+02 19076007 199 445s 2 CBS_Example (weighted median) 1 1.907601e+07 30126128 101 445s 3 CBS_Example (weighted median) 1 3.012613e+07 63224332 297 445s 4 CBS_Example (weighted median) 1 6.322433e+07 78801707 153 445s 5 CBS_Example (weighted median) 1 7.880171e+07 99917418 199 445s mean 445s 1 -0.08745973 445s 2 1.12968951 445s 3 -0.06074638 445s 4 -1.06373835 445s 5 0.04204744 445s > drawLevels(fitWM, col="orange", lty=3) 445s NULL 445s > 445s > 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)) 445s > 445s > ## Assert that weighted segment means are less biased 445s > dmean <- getSegments(fit)$mean - getSegments(fitW)$mean 445s > cat("Segment mean differences:\n") 445s Segment mean differences: 445s > print(dmean) 445s [1] 0.3496597 0.2992105 0.3461464 0.3229384 0.3120526 445s > stopifnot(all(dmean > 0, na.rm=TRUE)) 445s > 445s > dmean <- getSegments(fitM)$mean - getSegments(fitWM)$mean 445s > cat("Segment median differences:\n") 445s Segment median differences: 445s > print(dmean) 445s [1] 0.1880015 0.1424060 0.1944611 0.1982130 0.1297704 445s > stopifnot(all(dmean > 0, na.rm=TRUE)) 445s > 445s > 445s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 445s > # Multi-chromosome segmentation 445s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 445s > data2 <- data 445s > data2$chromosome <- 2L 445s > data <- rbind(data, data2) 445s > dataW <- cbind(data, w=w) 445s > 445s > par(mar=c(2,3,0.2,1)+0.1) 445s > # Segment without weights 445s > fit <- segmentByCBS(data) 445s > sampleName(fit) <- "CBS_Example" 445s > print(fit) 445s sampleName chromosome start end nbrOfLoci mean 445s 1 CBS_Example 1 6.066868e+02 19076007 199 0.2622 445s 2 CBS_Example 1 1.907601e+07 29630949 99 1.4289 445s 3 CBS_Example 1 2.963095e+07 63224332 299 0.2854 445s 4 CBS_Example 1 6.322433e+07 78801707 153 -0.7408 445s 5 CBS_Example 1 7.880171e+07 99917418 199 0.3541 445s 6 NA NA NA NA NA 445s 7 CBS_Example 2 6.066868e+02 19076007 199 0.2622 445s 8 CBS_Example 2 1.907601e+07 29630949 99 1.4289 445s 9 CBS_Example 2 2.963095e+07 63224332 299 0.2854 445s 10 CBS_Example 2 6.322433e+07 78801707 153 -0.7408 445s 11 CBS_Example 2 7.880171e+07 99917418 199 0.3541 445s > plotTracks(fit, Clim=c(-3,3)) 445s > 445s > # Segment without weights but with median 445s > fitM <- segmentByCBS(data, avg="median") 445s > sampleName(fitM) <- "CBS_Example (median)" 445s > print(fitM) 445s sampleName chromosome start end nbrOfLoci mean 445s 1 CBS_Example (median) 1 6.066868e+02 19076007 199 0.1005418 445s 2 CBS_Example (median) 1 1.907601e+07 29630949 99 1.2720955 445s 3 CBS_Example (median) 1 2.963095e+07 63224332 299 0.1337148 445s 4 CBS_Example (median) 1 6.322433e+07 78801707 153 -0.8655254 445s 5 CBS_Example (median) 1 7.880171e+07 99917418 199 0.1718179 445s 6 NA NA NA NA NA 445s 7 CBS_Example (median) 2 6.066868e+02 19076007 199 0.1005418 445s 8 CBS_Example (median) 2 1.907601e+07 29630949 99 1.2720955 445s 9 CBS_Example (median) 2 2.963095e+07 63224332 299 0.1337148 445s 10 CBS_Example (median) 2 6.322433e+07 78801707 153 -0.8655254 445s 11 CBS_Example (median) 2 7.880171e+07 99917418 199 0.1718179 445s > drawLevels(fitM, col="magenta", lty=3) 445s NULL 445s > 445s > # Segment with weights 445s > fitW <- segmentByCBS(dataW, avg="median") 445s > sampleName(fitW) <- "CBS_Example (weighted)" 445s > print(fitW) 445s sampleName chromosome start end nbrOfLoci 445s 1 CBS_Example (weighted) 1 6.066868e+02 19076007 199 445s 2 CBS_Example (weighted) 1 1.907601e+07 30126128 101 445s 3 CBS_Example (weighted) 1 3.012613e+07 63224332 297 445s 4 CBS_Example (weighted) 1 6.322433e+07 78801707 153 445s 5 CBS_Example (weighted) 1 7.880171e+07 99917418 199 445s 6 NA NA NA NA 445s 7 CBS_Example (weighted) 2 6.066868e+02 19076007 199 445s 8 CBS_Example (weighted) 2 1.907601e+07 30126128 101 445s 9 CBS_Example (weighted) 2 3.012613e+07 63224332 297 445s 10 CBS_Example (weighted) 2 6.322433e+07 78801707 153 445s 11 CBS_Example (weighted) 2 7.880171e+07 99917418 199 445s mean 445s 1 -0.08745973 445s 2 1.12968951 445s 3 -0.06074638 445s 4 -1.06373835 445s 5 0.04204744 445s 6 NA 445s 7 -0.08745973 445s 8 1.12968951 445s 9 -0.06074638 445s 10 -1.06373835 445s 11 0.04204744 445s > drawLevels(fitW, col="red") 445s NULL 445s > 445s > # Segment with weights and median 445s > fitWM <- segmentByCBS(dataW, avg="median") 445s > sampleName(fitWM) <- "CBS_Example (weighted median)" 445s > print(fitWM) 445s sampleName chromosome start end nbrOfLoci 445s 1 CBS_Example (weighted median) 1 6.066868e+02 19076007 199 445s 2 CBS_Example (weighted median) 1 1.907601e+07 30126128 101 445s 3 CBS_Example (weighted median) 1 3.012613e+07 63224332 297 445s 4 CBS_Example (weighted median) 1 6.322433e+07 78801707 153 445s 5 CBS_Example (weighted median) 1 7.880171e+07 99917418 199 445s 6 NA NA NA NA 445s 7 CBS_Example (weighted median) 2 6.066868e+02 19076007 199 445s 8 CBS_Example (weighted median) 2 1.907601e+07 30126128 101 445s 9 CBS_Example (weighted median) 2 3.012613e+07 63224332 297 445s 10 CBS_Example (weighted median) 2 6.322433e+07 78801707 153 445s 11 CBS_Example (weighted median) 2 7.880171e+07 99917418 199 445s mean 445s 1 -0.08745973 445s 2 1.12968951 445s 3 -0.06074638 445s 4 -1.06373835 445s 5 0.04204744 445s 6 NA 445s 7 -0.08745973 445s 8 1.12968951 445s 9 -0.06074638 445s 10 -1.06373835 445s 11 0.04204744 445s > drawLevels(fitWM, col="orange", lty=3) 445s NULL 445s > 445s > 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)) 445s > 445s > ## Assert that weighted segment means are less biased 445s > dmean <- getSegments(fit)$mean - getSegments(fitW)$mean 445s > cat("Segment mean differences:\n") 445s Segment mean differences: 445s > print(dmean) 445s [1] 0.3496597 0.2992105 0.3461464 0.3229384 0.3120526 NA 0.3496597 445s [8] 0.2992105 0.3461464 0.3229384 0.3120526 445s > stopifnot(all(dmean > 0, na.rm=TRUE)) 445s > 445s > dmean <- getSegments(fitM)$mean - getSegments(fitWM)$mean 445s > cat("Segment median differences:\n") 445s Segment median differences: 445s > print(dmean) 445s [1] 0.1880015 0.1424060 0.1944611 0.1982130 0.1297704 NA 0.1880015 445s [8] 0.1424060 0.1944611 0.1982130 0.1297704 445s > stopifnot(all(dmean > 0, na.rm=TRUE)) 445s > 445s > proc.time() 445s user system elapsed 445s 1.152 0.069 1.204 445s Test segmentByCBS,median passed 445s 0 445s Begin test segmentByCBS,prune 445s 445s R version 4.3.2 (2023-10-31) -- "Eye Holes" 445s Copyright (C) 2023 The R Foundation for Statistical Computing 445s Platform: x86_64-pc-linux-gnu (64-bit) 445s 445s R is free software and comes with ABSOLUTELY NO WARRANTY. 445s You are welcome to redistribute it under certain conditions. 445s Type 'license()' or 'licence()' for distribution details. 445s 445s R is a collaborative project with many contributors. 445s Type 'contributors()' for more information and 445s 'citation()' on how to cite R or R packages in publications. 445s 445s Type 'demo()' for some demos, 'help()' for on-line help, or 445s 'help.start()' for an HTML browser interface to help. 445s Type 'q()' to quit R. 445s 445s [Previously saved workspace restored] 445s 445s > library("PSCBS") 445s PSCBS v0.66.0 (2021-10-23 07:40:02 UTC) successfully loaded. See ?PSCBS for help. 445s 445s Attaching package: 'PSCBS' 445s 445s The following objects are masked from 'package:base': 445s 445s append, load 445s 445s > 445s > ## Compare segments 445s > assertMatchingSegments <- function(fitM, fit) { 445s + chrs <- getChromosomes(fitM) 445s + segsM <- lapply(chrs, FUN=function(chr) { 445s + getSegments(extractChromosome(fitM, chr)) 445s + }) 445s + segs <- lapply(fit[chrs], FUN=getSegments) 445s + stopifnot(all.equal(segsM, segs, check.attributes=FALSE)) 445s + } 445s > 445s > ## Simulate data 445s > set.seed(0xBEEF) 445s > J <- 1000 445s > mu <- double(J) 445s > mu[200:300] <- mu[200:300] + 1 445s > mu[350:400] <- NA 445s > mu[650:800] <- mu[650:800] - 1 445s > eps <- rnorm(J, sd=1/2) 445s > y <- mu + eps 445s > x <- sort(runif(length(y), max=length(y))) * 1e5 445s > 445s > data <- list() 445s > for (chr in 1:2) { 445s + data[[chr]] <- data.frame(chromosome=chr, x=x, y=y) 445s + } 445s > data$M <- Reduce(rbind, data) 445s > 445s > ## Segment 445s > message("*** segmentByCBS()") 445s *** segmentByCBS() 445s > fit <- lapply(data, FUN=segmentByCBS) 445s > print(fit) 445s [[1]] 445s sampleName chromosome start end nbrOfLoci mean 445s 1 1 65285.65 19648927 200 0.0109 445s 2 1 19648927.46 28239656 95 0.9529 445s 3 1 28239655.99 65697742 302 -0.0126 445s 4 1 65697742.20 79729368 153 -0.9534 445s 5 1 79729368.34 99819310 199 -0.0497 445s 445s [[2]] 445s sampleName chromosome start end nbrOfLoci mean 445s 1 2 65285.65 19648927 200 0.0109 445s 2 2 19648927.46 28239656 95 0.9529 445s 3 2 28239655.99 65697742 302 -0.0126 445s 4 2 65697742.20 79729368 153 -0.9534 445s 5 2 79729368.34 99819310 199 -0.0497 445s 445s $M 445s sampleName chromosome start end nbrOfLoci mean 445s 1 1 65285.65 19648927 200 0.0109 445s 2 1 19648927.46 28239656 95 0.9529 445s 3 1 28239655.99 65697742 302 -0.0126 445s 4 1 65697742.20 79729368 153 -0.9534 445s 5 1 79729368.34 99819310 199 -0.0497 445s 6 NA NA NA NA NA 445s 7 2 65285.65 19648927 200 0.0109 445s 8 2 19648927.46 28239656 95 0.9529 445s 9 2 28239655.99 65697742 302 -0.0126 445s 10 2 65697742.20 79729368 153 -0.9534 445s 11 2 79729368.34 99819310 199 -0.0497 445s 445s > assertMatchingSegments(fit$M, fit) 445s > 445s > ## Join segments 445s > message("*** joinSegments()") 445s *** joinSegments() 445s > fitj <- lapply(fit, FUN=joinSegments) 445s > print(fitj) 445s [[1]] 445s sampleName chromosome start end nbrOfLoci mean 445s 1 1 65285.65 19648927 200 0.0109 445s 2 1 19648927.46 28239656 95 0.9529 445s 3 1 28239655.99 65697742 302 -0.0126 445s 4 1 65697742.20 79729368 153 -0.9534 445s 5 1 79729368.34 99819310 199 -0.0497 445s 445s [[2]] 445s sampleName chromosome start end nbrOfLoci mean 445s 1 2 65285.65 19648927 200 0.0109 445s 2 2 19648927.46 28239656 95 0.9529 445s 3 2 28239655.99 65697742 302 -0.0126 445s 4 2 65697742.20 79729368 153 -+ [ 0 != 0 ] 445s + echo Test segmentByCBS,median passed 445s + echo 0 445s + echo Begin test segmentByCBS,prune 445s + exitcode=0 445s + R CMD BATCH segmentByCBS,prune.R 445s + cat segmentByCBS,prune.Rout 445s + [ 0 != 0 ] 445s + echo Test segmentByCBS,prune passed 445s + echo 0 445s + echo Begin test segmentByCBS,report 445s + exitcode=0 445s + R CMD BATCH segmentByCBS,report.R 445s 0.9534 445s 5 2 79729368.34 99819310 199 -0.0497 445s 445s $M 445s sampleName chromosome start end nbrOfLoci mean 445s 1 1 65285.65 19648927 200 0.0109 445s 2 1 19648927.46 28239656 95 0.9529 445s 3 1 28239655.99 65697742 302 -0.0126 445s 4 1 65697742.20 79729368 153 -0.9534 445s 5 1 79729368.34 99819310 199 -0.0497 445s 6 NA NA NA NA NA 445s 7 2 65285.65 19648927 200 0.0109 445s 8 2 19648927.46 28239656 95 0.9529 445s 9 2 28239655.99 65697742 302 -0.0126 445s 10 2 65697742.20 79729368 153 -0.9534 445s 11 2 79729368.34 99819310 199 -0.0497 445s 445s > assertMatchingSegments(fitj$M, fitj) 445s > 445s > ## Reset segments 445s > message("*** resetSegments()") 445s *** resetSegments() 445s > fitj <- lapply(fit, FUN=resetSegments) 445s > print(fitj) 445s [[1]] 445s sampleName chromosome start end nbrOfLoci mean 445s 1 1 65285.65 19648927 200 0.0109 445s 2 1 19648927.46 28239656 95 0.9529 445s 3 1 28239655.99 65697742 302 -0.0126 445s 4 1 65697742.20 79729368 153 -0.9534 445s 5 1 79729368.34 99819310 199 -0.0497 445s 445s [[2]] 445s sampleName chromosome start end nbrOfLoci mean 445s 1 2 65285.65 19648927 200 0.0109 445s 2 2 19648927.46 28239656 95 0.9529 445s 3 2 28239655.99 65697742 302 -0.0126 445s 4 2 65697742.20 79729368 153 -0.9534 445s 5 2 79729368.34 99819310 199 -0.0497 445s 445s $M 445s sampleName chromosome start end nbrOfLoci mean 445s 1 1 65285.65 19648927 200 0.0109 445s 2 1 19648927.46 28239656 95 0.9529 445s 3 1 28239655.99 65697742 302 -0.0126 445s 4 1 65697742.20 79729368 153 -0.9534 445s 5 1 79729368.34 99819310 199 -0.0497 445s 6 NA NA NA NA NA 445s 7 2 65285.65 19648927 200 0.0109 445s 8 2 19648927.46 28239656 95 0.9529 445s 9 2 28239655.99 65697742 302 -0.0126 445s 10 2 65697742.20 79729368 153 -0.9534 445s 11 2 79729368.34 99819310 199 -0.0497 445s 445s > assertMatchingSegments(fitj$M, fitj) 445s > 445s > ## Prune by SD undo 445s > message("*** pruneBySdUndo()") 445s *** pruneBySdUndo() 445s > fitp <- lapply(fit, FUN=pruneBySdUndo) 445s > print(fitp) 445s [[1]] 445s sampleName chromosome start end nbrOfLoci mean 445s 1 1 65285.65 99819310 949 -0.07045097 445s 445s [[2]] 445s sampleName chromosome start end nbrOfLoci mean 445s 1 2 65285.65 99819310 949 -0.07045097 445s 445s $M 445s sampleName chromosome start end nbrOfLoci mean 445s 1 1 65285.65 99819310 949 -0.07045097 445s 2 NA NA NA NA NA 445s 3 2 65285.65 99819310 949 -0.07045097 445s 445s > assertMatchingSegments(fitp$M, fitp) 445s > 445s > ## Prune by hierarchical clustering 445s > message("*** pruneByHClust()") 445s *** pruneByHClust() 445s > fitp <- lapply(fit, FUN=pruneByHClust, k=1L) 445s > print(fitp) 445s [[1]] 445s sampleName chromosome start end nbrOfLoci mean 445s 1 1 65285.65 99819310 949 -0.07045097 445s 445s [[2]] 445s sampleName chromosome start end nbrOfLoci mean 445s 1 2 65285.65 99819310 949 -0.07045097 445s 445s $M 445s sampleName chromosome start end nbrOfLoci mean 445s 1 1 65285.65 99819310 949 -0.07045097 445s 6 NA NA NA NA NA 445s 7 2 65285.65 99819310 949 -0.07045097 445s 445s > assertMatchingSegments(fitp$M, fitp) 445s > 445s > proc.time() 445s user system elapsed 445s 0.927 0.074 0.985 445s Test segmentByCBS,prune passed 445s 0 445s Begin test segmentByCBS,report 445s + cat segmentByCBS,report.Rout 445s 445s R version 4.3.2 (2023-10-31) -- "Eye Holes" 445s Copyright (C) 2023 The R Foundation for Statistical Computing 445s Platform: x86_64-pc-linux-gnu (64-bit) 445s 445s R is free software and comes with ABSOLUTELY NO WARRANTY. 445s You are welcome to redistribute it under certain conditions. 445s Type 'license()' or 'licence()' for distribution details. 445s 445s R is a collaborative project with many contributors. 445s Type 'contributors()' for more information and 445s 'citation()' on how to cite R or R packages in publications. 445s 445s Type 'demo()' for some demos, 'help()' for on-line help, or 445s 'help.start()' for an HTML browser interface to help. 445s Type 'q()' to quit R. 445s 445s [Previously saved workspace restored] 445s 445s > # This test script calls a report generator which requires 445s > # the 'ggplot2' package, which in turn will require packages 445s > # 'colorspace', 'dichromat', 'munsell', 'reshape2' and 'scales'. 445s > 445s > # Only run this test in full testing mode 445s > if (Sys.getenv("_R_CHECK_FULL_") != "") { 445s + library("PSCBS") 445s + 445s + # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 445s + # Load SNP microarray data 445s + # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 445s + data <- PSCBS::exampleData("paired.chr01") 445s + str(data) 445s + 445s + data <- data.frame(chromosome=data$chromosome, x=data$x, y=data$CT) 445s + 445s + 445s + # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 445s + # CBS segmentation 445s + # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 445s + # Drop single-locus outliers 445s + dataS <- dropSegmentationOutliers(data) 445s + 445s + # Speed up example by segmenting fewer loci 445s + dataS <- dataS[seq(from=1, to=nrow(data), by=5),] 445s + 445s + str(dataS) 445s + 445s + gaps <- findLargeGaps(dataS, minLength=2e6) 445s + knownSegments <- gapsToSegments(gaps) 445s + 445s + # CBS segmentation 445s + fit <- segmentByCBS(dataS, knownSegments=knownSegments, 445s + seed=0xBEEF, verbose=-10) 445s + signalType(fit) <- "ratio" 445s + 445s + # Fake a multi-chromosome segmentation 445s + fit1 <- fit 445s + fit2 <- renameChromosomes(fit, from=1, to=2) 445s + fit <- c(fit1, fit2) 445s + 445s + report(fit, sampleName="CBS", studyName="CBS-Ex", verbose=-10) 445s + 445s + } # if (Sys.getenv("_R_CHECK_FULL_")) 445s > 445s > proc.time() 445s user system elapsed 445s 0.176 0.053 0.218 445s Test segmentByCBS,report passed 445s 0 445s Begin test segmentByCBS,shiftTCN 445s + [ 0 != 0 ] 445s + echo Test segmentByCBS,report passed 445s + echo 0 445s + echo Begin test segmentByCBS,shiftTCN 445s + exitcode=0 445s + R CMD BATCH segmentByCBS,shiftTCN.R 452s 452s R version 4.3.2 (2023-10-31) -- "Eye Holes" 452s Copyright (C) 2023 The R Foundation for Statistical Computing 452s Platform: x86_64-pc-linux-gnu (64-bit) 452s 452s R is free software and comes with ABSOLUTELY NO WARRANTY. 452s You are welcome to redistribute it under certain conditions. 452s Type 'license()' or 'licence()' for distribution details. 452s 452s R is a collaborative project with many contributors. 452s Type 'contributors()' for more information and 452s 'citation()' on how to cite R or R packages in publications. 452s 452s Type 'demo()' for some demos, 'help()' for on-line help, or 452s 'help.start()' for an HTML browser interface to help. 452s Type 'q()' to quit R. 452s 452s [Previously saved workspace restored] 452s 452s > library("PSCBS") 452s PSCBS v0.66.0 (2021-10-23 07:40:02 UTC) successfully loaded. See ?PSCBS for help. 452s 452s Attaching package: 'PSCBS' 452s 452s The following objects are masked from 'package:base': 452s 452s append, load 452s 452s > subplots <- R.utils::subplots 452s > 452s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 452s > # Simulating copy-number data 452s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 452s > set.seed(0xBEEF) 452s > 452s > # Number of loci 452s > J <- 1000 452s > 452s > mu <- double(J) 452s > eps <- rnorm(J, sd=1/2) 452s > y <- mu + eps 452s > x <- sort(runif(length(y), max=length(y))) 452s > 452s > idxs <- which(200 <= x & x < 300) 452s > y[idxs] <- y[idxs] + 1 452s > idxs <- which(350 <= x & x < 400) 452s > y[idxs] <- NA # centromere 452s > x[idxs] <- NA # centromere 452s > idxs <- which(650 <= x & x < 800) 452s > y[idxs] <- y[idxs] - 1 452s > x <- x*1e5 452s > 452s > keep <- is.finite(x) 452s > x <- x[keep] 452s > y <- y[keep] 452s > 452s > data <- list() 452s > for (chr in 1:2) { 452s + data[[chr]] <- data.frame(chromosome=chr, y=y, x=x) 452s + } 452s > data <- Reduce(rbind, data) 452s > 452s > 452s > subplots(7, ncol=1) 452s > par(mar=c(1.7,1,0.2,1)+0.1) 452s > 452s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 452s > # Segmentation 452s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 452s > fit <- segmentByCBS(data) 452s > print(fit) 452s sampleName chromosome start end nbrOfLoci mean 452s 1 1 65285.65 20169684 205 0.0124 452s 2 1 20169684.05 29980147 103 0.9477 452s 3 1 29980147.36 64779929 287 -0.0299 452s 4 1 64779929.38 80010171 163 -0.9676 452s 5 1 80010171.14 99819310 196 -0.0484 452s 6 NA NA NA NA NA 452s 7 2 65285.65 20169684 205 0.0124 452s 8 2 20169684.05 29980147 103 0.9477 452s 9 2 29980147.36 64779929 287 -0.0299 452s 10 2 64779929.38 80010171 163 -0.9676 452s 11 2 80010171.14 99819310 196 -0.0484 452s > 452s > Clim <- c(-3,3) + c(0,10) 452s > plotTracks(fit, Clim=Clim) 452s > 452s > 452s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 452s > # Shifting every other chromosome 452s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 452s > fitList <- list() 452s > chrs <- getChromosomes(fit) 452s > for (kk in seq_along(chrs)) { 452s + chr <- chrs[kk] 452s + fitKK <- extractChromosome(fit, chr) 452s + if (kk %% 2 == 0) { 452s + fitKK <- shiftTCN(fitKK, shift=+10) 452s + } 452s + fitList[[kk]] <- fitKK 452s + } # for (kk ...) 452s > fitT <- do.call(c, fitList) 452s > # Sanity check 452s > stopifnot(nbrOfSegments(fitT) == nbrOfSegments(fit)) 452s > 452s > plotTracks(fitT, Clim=Clim) 452s > 452s > 452s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 452s > # Shifting every other known segment 452s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 452s > gaps <- findLargeGaps(data, minLength=40e5) 452s > knownSegments <- gapsToSegments(gaps, dropGaps=TRUE) 452s > fit <- segmentByCBS(data, knownSegments=knownSegments) 452s > 452s > subplots(2, ncol=1) 452s > plotTracks(fit, Clim=Clim) 452s > abline(v=c(knownSegments$start, knownSegments$end)/1e6, lty=3) 452s > 452s > fitList <- list() 452s > for (kk in seq_len(nrow(knownSegments))) { 452s + seg <- knownSegments[kk,] 452s + start <- seg$start 452s + end <- seg$end 452s + fitKK <- extractChromosome(fit, seg$chromosome) 452s + segsKK <- getSegments(fitKK) 452s + idxStart <- min(which(segsKK$start >= start)) 452s + idxEnd <- max(which(segsKK$end <= end)) 452s + idxs <- idxStart:idxEnd 452s + fitKK <- extractSegments(fitKK, idxs) 452s + if (kk %% 2 == 0) { 452s + fitKK <- shiftTCN(fitKK, shift=+10) 452s + } 452s + fitList[[kk]] <- fitKK 452s + } # for (kk ...) 452s > fitT <- do.call(c, fitList) 452s > # Sanity check 452s > stopifnot(nbrOfSegments(fitT) == nbrOfSegments(fit)) 452s > 452s > plotTracks(fitT, Clim=Clim) 452s > abline(v=c(knownSegments$start, knownSegments$end)/1e6, lty=3) 452s > 452s > 452s > segList <- seqOfSegmentsByDP(fit) 452s > K <- length(segList) 452s > subplots(K, ncol=2, byrow=FALSE) 452s > par(mar=c(2,1,1,1)) 452s > for (kk in 1:K) { 452s + knownSegments <- segList[[kk]] 452s + fitKK <- resegment(fit, knownSegments=knownSegments, undo=+Inf) 452s + plotTracks(fitKK, Clim=c(-3,3)) 452s + } # for (kk ...) 452s > 452s > proc.time() 452s user system elapsed 452s 6.127 0.102 6.210 452s Test segmentByCBS,shiftTCN passed 452s 0 452s Begin test segmentByCBS,weights 452s + cat segmentByCBS,shiftTCN.Rout 452s + [ 0 != 0 ] 452s + echo Test segmentByCBS,shiftTCN passed 452s + echo 0 452s + echo Begin test segmentByCBS,weights 452s + exitcode=0 452s + R CMD BATCH segmentByCBS,weights.R 454s + cat segmentByCBS,weights.Rout 454s 454s R version 4.3.2 (2023-10-31) -- "Eye Holes" 454s Copyright (C) 2023 The R Foundation for Statistical Computing 454s Platform: x86_64-pc-linux-gnu (64-bit) 454s 454s R is free software and comes with ABSOLUTELY NO WARRANTY. 454s You are welcome to redistribute it under certain conditions. 454s Type 'license()' or 'licence()' for distribution details. 454s 454s R is a collaborative project with many contributors. 454s Type 'contributors()' for more information and 454s 'citation()' on how to cite R or R packages in publications. 454s 454s Type 'demo()' for some demos, 'help()' for on-line help, or 454s 'help.start()' for an HTML browser interface to help. 454s Type 'q()' to quit R. 454s 454s [Previously saved workspace restored] 454s 454s > library("PSCBS") 454s PSCBS v0.66.0 (2021-10-23 07:40:02 UTC) successfully loaded. See ?PSCBS for help. 454s 454s Attaching package: 'PSCBS' 454s 454s The following objects are masked from 'package:base': 454s 454s append, load 454s 454s > 454s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 454s > # Simulating copy-number data 454s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 454s > set.seed(0xBEEF) 454s > 454s > # Number of loci 454s > J <- 1000 454s > 454s > x <- sort(runif(J, max=J)) * 1e5 454s > 454s > mu <- double(J) 454s > mu[200:300] <- mu[200:300] + 1 454s > mu[350:400] <- NA # centromere 454s > mu[650:800] <- mu[650:800] - 1 454s > eps <- rnorm(J, sd=1/2) 454s > y <- mu + eps 454s > 454s > outliers <- seq(from=1L, to=J, length.out=0.2*J) 454s > y[outliers] <- y[outliers] + 1.5 454s > 454s > w <- rep(1.0, times=J) 454s > w[outliers] <- 0.01 454s > 454s > data <- data.frame(chromosome=1L, x=x, y=y) 454s > dataW <- cbind(data, w=w) 454s > 454s > 454s > par(mar=c(2,3,0.2,1)+0.1) 454s > 454s > 454s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 454s > # Single-chromosome segmentation 454s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 454s > # Segment without weights 454s > fit <- segmentByCBS(data) 454s > sampleName(fit) <- "CBS_Example" 454s > print(fit) 454s sampleName chromosome start end nbrOfLoci mean 454s 1 CBS_Example 1 6.066868e+02 19076007 199 0.2622 454s 2 CBS_Example 1 1.907601e+07 29630949 99 1.4289 454s 3 CBS_Example 1 2.963095e+07 63224332 299 0.2854 454s 4 CBS_Example 1 6.322433e+07 78801707 153 -0.7408 454s 5 CBS_Example 1 7.880171e+07 99917418 199 0.3541 454s > plotTracks(fit) 454s Warning message: 454s In plotTracks.CBS(fit) : 454s Setting default 'Clim' assuming the signal type is 'ratio' because signalType(fit) is unknown ('NA'). Use signalType(fit) <- 'ratio' to avoid this warning. 454s > ## Highlight outliers (they pull up the mean levels) 454s > points(x[outliers]/1e6, y[outliers], col="purple") 454s > 454s > # Segment with weights 454s > fitW <- segmentByCBS(dataW) 454s > sampleName(fitW) <- "CBS_Example (weighted)" 454s > print(fitW) 454s sampleName chromosome start end nbrOfLoci mean 454s 1 CBS_Example (weighted) 1 6.066868e+02 19076007 199 -0.0610 454s 2 CBS_Example (weighted) 1 1.907601e+07 30126128 101 1.1283 454s 3 CBS_Example (weighted) 1 3.012613e+07 63224332 297 -0.0298 454s 4 CBS_Example (weighted) 1 6.322433e+07 78801707 153 -1.0436 454s 5 CBS_Example (weighted) 1 7.880171e+07 99917418 199 0.0461 454s > drawLevels(fitW, col="red") 454s NULL 454s > 454s > 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)) 454s > 454s > ## Assert that weighted segment means are less biased 454s > dmean <- getSegments(fit)$mean - getSegments(fitW)$mean 454s > cat("Segment mean differences:\n") 454s Segment mean differences: 454s > print(dmean) 454s [1] 0.3232 0.3006 0.3152 0.3028 0.3080 454s > stopifnot(all(dmean > 0, na.rm=TRUE)) 454s > 454s > 454s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 454s > # Segmentation with some known change points 454s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 454s > knownSegments <- data.frame( 454s + chromosome=c( 1, 1), 454s + start =x[c( 1, 401)], 454s + end =x[c(349, J)] 454s + ) 454s > fit2 <- segmentByCBS(dataW, knownSegments=knownSegments, verbose=TRUE) 454s Segmenting by CBS... 454s Chromosome: 1 454s Segmenting by CBS...done 454s > sampleName(fit2) <- "CBS_Example_2 (weighted)" 454s > print(fit2) 454s sampleName chromosome start end nbrOfLoci mean 454s 1 CBS_Example_2 (weighted) 1 6.066868e+02 19076007 199 -0.0610 454s 2 CBS_Example_2 (weighted) 1 1.907601e+07 30126128 101 1.1283 454s 3 CBS_Example_2 (weighted) 1 3.012613e+07 35490554 49 -0.0832 454s 4 CBS_Example_2 (weighted) 1 3.987525e+07 63224332 248 -0.0192 454s 5 CBS_Example_2 (weighted) 1 6.322433e+07 78471531 152 -1.0480 454s 6 CBS_Example_2 (weighted) 1 7.847153e+07 99917418 200 0.0427 454s > plotTracks(fit2) 454s Warning message: 454s In plotTracks.CBS(fit2) : 454s Setting default 'Clim' assuming the signal type is 'ratio' because signalType(fit2) is unknown ('NA'). Use signalType(fit2) <- 'ratio' to avoid this warning. 454s > abline(v=c(knownSegments$start, knownSegments$end)/1e6, lty=3) 454s > 454s > 454s > # Chromosome boundaries can be specified as -Inf and +Inf 454s > knownSegments <- data.frame( 454s + chromosome=c( 1, 1), 454s + start =c( -Inf, x[401]), 454s + end =c(x[349], +Inf) 454s + ) 454s > fit2b <- segmentByCBS(dataW, knownSegments=knownSegments, verbose=TRUE) 454s Segmenting by CBS... 454s Chromosome: 1 454s Segmenting by CBS...done 454s > sampleName(fit2b) <- "CBS_Example_2b (weighted)" 454s > print(fit2b) 454s sampleName chromosome start end nbrOfLoci mean 454s 1 CBS_Example_2b (weighted) 1 6.066868e+02 19076007 199 -0.0610 454s 2 CBS_Example_2b (weighted) 1 1.907601e+07 30126128 101 1.1283 454s 3 CBS_Example_2b (weighted) 1 3.012613e+07 35490554 49 -0.0832 454s 4 CBS_Example_2b (weighted) 1 3.987525e+07 63224332 248 -0.0192 454s 5 CBS_Example_2b (weighted) 1 6.322433e+07 78471531 152 -1.0480 454s 6 CBS_Example_2b (weighted) 1 7.847153e+07 99917418 200 0.0427 454s > plotTracks(fit2b) 454s Warning message: 454s In plotTracks.CBS(fit2b) : 454s Setting default 'Clim' assuming the signal type is 'ratio' because signalType(fit2b) is unknown ('NA'). Use signalType(fit2b) <- 'ratio' to avoid this warning. 454s > abline(v=c(knownSegments$start, knownSegments$end)/1e6, lty=3) 454s > 454s > 454s > # As a proof of concept, it is possible to segment just the centromere, 454s > # which contains no data. All statistics will be NAs. 454s > knownSegments <- data.frame( 454s + chromosome=c( 1), 454s + start =x[c(350)], 454s + end =x[c(400)] 454s + ) 454s > fit3 <- segmentByCBS(dataW, knownSegments=knownSegments, verbose=TRUE) 454s Segmenting by CBS... 454s Chromosome: 1 454s Segmenting by CBS...done 454s > sampleName(fit3) <- "CBS_Example_3" 454s > print(fit3) 454s sampleName chromosome start end nbrOfLoci mean 454s 1 CBS_Example_3 1 35661013 39852333 0 NA 454s > plotTracks(fit3, Clim=c(0,5), xlim=c(0,100)) 454s > abline(v=c(knownSegments$start, knownSegments$end)/1e6, lty=3) 454s > 454s > 454s > # If one specify the (empty) centromere as a segment, then its 454s > # estimated statistics will be NAs, which becomes a natural 454s > # separator between the two "independent" arms. 454s > knownSegments <- data.frame( 454s + chromosome=c( 1, 1, 1), 454s + start =x[c( 1, 350, 401)], 454s + end =x[c(349, 400, J)] 454s + ) 454s > fit4 <- segmentByCBS(dataW, knownSegments=knownSegments, verbose=TRUE) 454s Segmenting by CBS... 454s Chromosome: 1 454s Segmenting by CBS...done 454s > sampleName(fit4) <- "CBS_Example_4" 454s > print(fit4) 454s sampleName chromosome start end nbrOfLoci mean 454s 1 CBS_Example_4 1 6.066868e+02 19076007 199 -0.0610 454s 2 CBS_Example_4 1 1.907601e+07 30126128 101 1.1283 454s 3 CBS_Example_4 1 3.012613e+07 35490554 49 -0.0832 454s 4 CBS_Example_4 1 3.566101e+07 39852333 0 NA 454s 5 CBS_Example_4 1 3.987525e+07 63224332 248 -0.0192 454s 6 CBS_Example_4 1 6.322433e+07 78471531 152 -1.0480 454s 7 CBS_Example_4 1 7.847153e+07 99917418 200 0.0427 454s > plotTracks(fit4) 454s Warning message: 454s In plotTracks.CBS(fit4) : 454s Setting default 'Clim' assuming the signal type is 'ratio' because signalType(fit4) is unknown ('NA'). Use signalType(fit4) <- 'ratio' to avoid this warning. 454s > abline(v=c(knownSegments$start, knownSegments$end)/1e6, lty=3) 454s > 454s > 454s > fit5 <- segmentByCBS(dataW, knownSegments=knownSe+ [ 0 != 0 ] 454s + echo Test segmentByCBS,weights passed 454s + echo 0 454s + echo Begin test segmentByCBS 454s + exitcode=0 454s + R CMD BATCH segmentByCBS.R 454s gments, undo=Inf, verbose=TRUE) 454s Segmenting by CBS... 454s Chromosome: 1 454s Segmenting by CBS...done 454s > sampleName(fit5) <- "CBS_Example_5" 454s > print(fit5) 454s sampleName chromosome start end nbrOfLoci mean 454s 1 CBS_Example_5 1 6.066868e+02 35490554 349 0.59252133 454s 2 CBS_Example_5 1 3.566101e+07 39852333 0 NA 454s 3 CBS_Example_5 1 3.987525e+07 99917418 600 0.04882396 454s > plotTracks(fit5) 454s Warning message: 454s In plotTracks.CBS(fit5) : 454s Setting default 'Clim' assuming the signal type is 'ratio' because signalType(fit5) is unknown ('NA'). Use signalType(fit5) <- 'ratio' to avoid this warning. 454s > abline(v=c(knownSegments$start, knownSegments$end)/1e6, lty=3) 454s > stopifnot(nbrOfSegments(fit5) == nrow(knownSegments)) 454s > 454s > 454s > # One can also force a separator between two segments by setting 454s > # 'start' and 'end' to NAs ('chromosome' has to be given) 454s > knownSegments <- data.frame( 454s + chromosome=c( 1, 1, 1), 454s + start =x[c( 1, NA, 401)], 454s + end =x[c(349, NA, J)] 454s + ) 454s > fit6 <- segmentByCBS(dataW, knownSegments=knownSegments, verbose=TRUE) 454s Segmenting by CBS... 454s Chromosome: 1 454s Segmenting by CBS...done 454s > sampleName(fit6) <- "CBS_Example_6" 454s > print(fit6) 454s sampleName chromosome start end nbrOfLoci mean 454s 1 CBS_Example_6 1 6.066868e+02 19076007 199 -0.0610 454s 2 CBS_Example_6 1 1.907601e+07 30126128 101 1.1283 454s 3 CBS_Example_6 1 3.012613e+07 35490554 49 -0.0832 454s 4 NA NA NA NA NA 454s 5 CBS_Example_6 1 3.987525e+07 63224332 248 -0.0192 454s 6 CBS_Example_6 1 6.322433e+07 78471531 152 -1.0480 454s 7 CBS_Example_6 1 7.847153e+07 99917418 200 0.0427 454s > plotTracks(fit6) 454s Warning message: 454s In plotTracks.CBS(fit6) : 454s Setting default 'Clim' assuming the signal type is 'ratio' because signalType(fit6) is unknown ('NA'). Use signalType(fit6) <- 'ratio' to avoid this warning. 454s > abline(v=c(knownSegments$start, knownSegments$end)/1e6, lty=3) 454s > 454s > 454s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 454s > # Multi-chromosome segmentation 454s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 454s > data2 <- data 454s > data2$chromosome <- 2L 454s > data <- rbind(data, data2) 454s > dataW <- cbind(data, w=w) 454s > 454s > par(mar=c(2,3,0.2,1)+0.1) 454s > # Segment without weights 454s > fit <- segmentByCBS(data) 454s > sampleName(fit) <- "CBS_Example" 454s > print(fit) 454s sampleName chromosome start end nbrOfLoci mean 454s 1 CBS_Example 1 6.066868e+02 19076007 199 0.2622 454s 2 CBS_Example 1 1.907601e+07 29630949 99 1.4289 454s 3 CBS_Example 1 2.963095e+07 63224332 299 0.2854 454s 4 CBS_Example 1 6.322433e+07 78801707 153 -0.7408 454s 5 CBS_Example 1 7.880171e+07 99917418 199 0.3541 454s 6 NA NA NA NA NA 454s 7 CBS_Example 2 6.066868e+02 19076007 199 0.2622 454s 8 CBS_Example 2 1.907601e+07 29630949 99 1.4289 454s 9 CBS_Example 2 2.963095e+07 63224332 299 0.2854 454s 10 CBS_Example 2 6.322433e+07 78801707 153 -0.7408 454s 11 CBS_Example 2 7.880171e+07 99917418 199 0.3541 454s > plotTracks(fit, Clim=c(-3,3)) 454s > 454s > # Segment with weights 454s > fitW <- segmentByCBS(dataW) 454s > sampleName(fitW) <- "CBS_Example (weighted)" 454s > print(fitW) 454s sampleName chromosome start end nbrOfLoci mean 454s 1 CBS_Example (weighted) 1 6.066868e+02 19076007 199 -0.0610 454s 2 CBS_Example (weighted) 1 1.907601e+07 30126128 101 1.1283 454s 3 CBS_Example (weighted) 1 3.012613e+07 63224332 297 -0.0298 454s 4 CBS_Example (weighted) 1 6.322433e+07 78801707 153 -1.0436 454s 5 CBS_Example (weighted) 1 7.880171e+07 99917418 199 0.0461 454s 6 NA NA NA NA NA 454s 7 CBS_Example (weighted) 2 6.066868e+02 19076007 199 -0.0610 454s 8 CBS_Example (weighted) 2 1.907601e+07 30126128 101 1.1283 454s 9 CBS_Example (weighted) 2 3.012613e+07 63224332 297 -0.0298 454s 10 CBS_Example (weighted) 2 6.322433e+07 78801707 153 -1.0436 454s 11 CBS_Example (weighted) 2 7.880171e+07 99917418 199 0.0461 454s > drawLevels(fitW, col="red") 454s NULL 454s > 454s > 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)) 454s > 454s > ## Assert that weighted segment means are less biased 454s > dmean <- getSegments(fit)$mean - getSegments(fitW)$mean 454s > cat("Segment mean differences:\n") 454s Segment mean differences: 454s > print(dmean) 454s [1] 0.3232 0.3006 0.3152 0.3028 0.3080 NA 0.3232 0.3006 0.3152 0.3028 454s [11] 0.3080 454s > stopifnot(all(dmean > 0, na.rm=TRUE)) 454s > 454s > proc.time() 454s user system elapsed 454s 2.067 0.087 2.147 454s Test segmentByCBS,weights passed 454s 0 454s Begin test segmentByCBS 456s + cat segmentByCBS.Rout 456s + [ 0 != 0 ] 456s + echo Test segmentByCBS passed 456s + echo 0 456s + echo Begin test segmentByNonPairedPSCBS,medianDH 456s + exitcode=0 456s + R CMD BATCH segmentByNonPairedPSCBS,medianDH.R 456s 456s R version 4.3.2 (2023-10-31) -- "Eye Holes" 456s Copyright (C) 2023 The R Foundation for Statistical Computing 456s Platform: x86_64-pc-linux-gnu (64-bit) 456s 456s R is free software and comes with ABSOLUTELY NO WARRANTY. 456s You are welcome to redistribute it under certain conditions. 456s Type 'license()' or 'licence()' for distribution details. 456s 456s R is a collaborative project with many contributors. 456s Type 'contributors()' for more information and 456s 'citation()' on how to cite R or R packages in publications. 456s 456s Type 'demo()' for some demos, 'help()' for on-line help, or 456s 'help.start()' for an HTML browser interface to help. 456s Type 'q()' to quit R. 456s 456s [Previously saved workspace restored] 456s 456s > ########################################################### 456s > # This tests: 456s > # - segmentByCBS(...) 456s > # - segmentByCBS(..., knownSegments) 456s > # - tileChromosomes() 456s > # - plotTracks() 456s > ########################################################### 456s > library("PSCBS") 456s PSCBS v0.66.0 (2021-10-23 07:40:02 UTC) successfully loaded. See ?PSCBS for help. 456s 456s Attaching package: 'PSCBS' 456s 456s The following objects are masked from 'package:base': 456s 456s append, load 456s 456s > subplots <- R.utils::subplots 456s > 456s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 456s > # Simulating copy-number data 456s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 456s > set.seed(0xBEEF) 456s > 456s > # Number of loci 456s > J <- 1000 456s > 456s > mu <- double(J) 456s > mu[200:300] <- mu[200:300] + 1 456s > mu[350:400] <- NA # centromere 456s > mu[650:800] <- mu[650:800] - 1 456s > eps <- rnorm(J, sd=1/2) 456s > y <- mu + eps 456s > x <- sort(runif(length(y), max=length(y))) * 1e5 456s > w <- runif(J) 456s > w[650:800] <- 0.001 456s > 456s > 456s > subplots(8, ncol=1L) 456s > par(mar=c(1.7,1,0.2,1)+0.1) 456s > 456s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 456s > # Segmentation 456s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 456s > fit <- segmentByCBS(y, x=x) 456s > sampleName(fit) <- "CBS_Example" 456s > print(fit) 456s sampleName chromosome start end nbrOfLoci mean 456s 1 CBS_Example 0 65285.65 19648927 200 0.0109 456s 2 CBS_Example 0 19648927.46 28239656 95 0.9529 456s 3 CBS_Example 0 28239655.99 65697742 302 -0.0126 456s 4 CBS_Example 0 65697742.20 79729368 153 -0.9534 456s 5 CBS_Example 0 79729368.34 99819310 199 -0.0497 456s > plotTracks(fit) 456s Warning message: 456s In plotTracks.CBS(fit) : 456s Setting default 'Clim' assuming the signal type is 'ratio' because signalType(fit) is unknown ('NA'). Use signalType(fit) <- 'ratio' to avoid this warning. 456s > 456s > 456s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 456s > # Segmentation with some known change points 456s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 456s > knownSegments <- data.frame( 456s + chromosome=c( 0, 0), 456s + start =x[c( 1, 401)], 456s + end =x[c(349, J)] 456s + ) 456s > fit2 <- segmentByCBS(y, x=x, knownSegments=knownSegments, verbose=TRUE) 456s Segmenting by CBS... 456s Chromosome: 0 456s Segmenting by CBS...done 456s > sampleName(fit2) <- "CBS_Example_2" 456s > print(fit2) 456s sampleName chromosome start end nbrOfLoci mean 456s 1 CBS_Example_2 0 65285.65 19648927 200 0.0109 456s 2 CBS_Example_2 0 19648927.46 28239656 95 0.9529 456s 3 CBS_Example_2 0 28239655.99 33106633 54 0.1169 456s 4 CBS_Example_2 0 38076667.59 65697742 248 -0.0408 456s 5 CBS_Example_2 0 65697742.20 79729368 153 -0.9534 456s 6 CBS_Example_2 0 79729368.34 99819310 199 -0.0497 456s > plotTracks(fit2) 456s Warning message: 456s In plotTracks.CBS(fit2) : 456s Setting default 'Clim' assuming the signal type is 'ratio' because signalType(fit2) is unknown ('NA'). Use signalType(fit2) <- 'ratio' to avoid this warning. 456s > abline(v=c(knownSegments$start, knownSegments$end)/1e6, lty=3) 456s > 456s > 456s > # Chromosome boundaries can be specified as -Inf and +Inf 456s > knownSegments <- data.frame( 456s + chromosome=c( 0, 0), 456s + start =c( -Inf, x[401]), 456s + end =c(x[349], +Inf) 456s + ) 456s > fit2b <- segmentByCBS(y, x=x, knownSegments=knownSegments, verbose=TRUE) 456s Segmenting by CBS... 456s Chromosome: 0 456s Segmenting by CBS...done 456s > sampleName(fit2b) <- "CBS_Example_2b" 456s > print(fit2b) 456s sampleName chromosome start end nbrOfLoci mean 456s 1 CBS_Example_2b 0 65285.65 19648927 200 0.0109 456s 2 CBS_Example_2b 0 19648927.46 28239656 95 0.9529 456s 3 CBS_Example_2b 0 28239655.99 33106633 54 0.1169 456s 4 CBS_Example_2b 0 38076667.59 65697742 248 -0.0408 456s 5 CBS_Example_2b 0 65697742.20 79729368 153 -0.9534 456s 6 CBS_Example_2b 0 79729368.34 99819310 199 -0.0497 456s > plotTracks(fit2b) 456s Warning message: 456s In plotTracks.CBS(fit2b) : 456s Setting default 'Clim' assuming the signal type is 'ratio' because signalType(fit2b) is unknown ('NA'). Use signalType(fit2b) <- 'ratio' to avoid this warning. 456s > abline(v=c(knownSegments$start, knownSegments$end)/1e6, lty=3) 456s > 456s > 456s > # As a proof of concept, it is possible to segment just the centromere, 456s > # which contains no data. All statistics will be NAs. 456s > knownSegments <- data.frame( 456s + chromosome=c( 0), 456s + start =x[c(350)], 456s + end =x[c(400)] 456s + ) 456s > fit3 <- segmentByCBS(y, x=x, knownSegments=knownSegments, verbose=TRUE) 456s Segmenting by CBS... 456s Chromosome: 0 456s Segmenting by CBS...done 456s > sampleName(fit3) <- "CBS_Example_3" 456s > print(fit3) 456s sampleName chromosome start end nbrOfLoci mean 456s 1 CBS_Example_3 0 33248518 37640521 0 NA 456s > plotTracks(fit3, Clim=c(0,5), xlim=c(0,100)) 456s > abline(v=c(knownSegments$start, knownSegments$end)/1e6, lty=3) 456s > 456s > 456s > 456s > # If one specify the (empty) centromere as a segment, then its 456s > # estimated statistics will be NAs, which becomes a natural 456s > # separator between the two "independent" arms. 456s > knownSegments <- data.frame( 456s + chromosome=c( 0, 0, 0), 456s + start =x[c( 1, 350, 401)], 456s + end =x[c(349, 400, J)] 456s + ) 456s > fit4 <- segmentByCBS(y, x=x, knownSegments=knownSegments, verbose=TRUE) 456s Segmenting by CBS... 456s Chromosome: 0 456s Segmenting by CBS...done 456s > sampleName(fit4) <- "CBS_Example_4" 456s > print(fit4) 456s sampleName chromosome start end nbrOfLoci mean 456s 1 CBS_Example_4 0 65285.65 19648927 200 0.0109 456s 2 CBS_Example_4 0 19648927.46 28239656 95 0.9529 456s 3 CBS_Example_4 0 28239655.99 33106633 54 0.1169 456s 4 CBS_Example_4 0 33248517.78 37640521 0 NA 456s 5 CBS_Example_4 0 38076667.59 65697742 248 -0.0408 456s 6 CBS_Example_4 0 65697742.20 79729368 153 -0.9534 456s 7 CBS_Example_4 0 79729368.34 99819310 199 -0.0497 456s > plotTracks(fit4) 456s Warning message: 456s In plotTracks.CBS(fit4) : 456s Setting default 'Clim' assuming the signal type is 'ratio' because signalType(fit4) is unknown ('NA'). Use signalType(fit4) <- 'ratio' to avoid this warning. 456s > abline(v=c(knownSegments$start, knownSegments$end)/1e6, lty=3) 456s > 456s > 456s > 456s > fit5 <- segmentByCBS(y, x=x, knownSegments=knownSegments, undo=Inf, verbose=TRUE) 456s Segmenting by CBS... 456s Chromosome: 0 456s Segmenting by CBS...done 456s > sampleName(fit5) <- "CBS_Example_5" 456s > print(fit5) 456s sampleName chromosome start end nbrOfLoci mean 456s 1 CBS_Example_5 0 65285.65 33106633 349 0.2836973 456s 2 CBS_Example_5 0 33248517.78 37640521 0 NA 456s 3 CBS_Example_5 0 38076667.59 99819310 600 -0.2764472 456s > plotTracks(fit5) 456s Warning message: 456s In plotTracks.CBS(fit5) : 456s Setting default 'Clim' assuming the signal type is 'ratio' because signalType(fit5) is unknown ('NA'). Use signalType(fit5) <- 'ratio' to avoid this warning. 456s > abline(v=c(knownSegments$start, knownSegments$end)/1e6, lty=3) 456s > stopifnot(nbrOfSegments(fit5) == nrow(knownSegments)) 456s > 456s > 456s > # One can also force a separator between two segments by setting 456s > # 'start' and 'end' to NAs ('chromosome' has to be given) 456s > knownSegments <- data.frame( 456s + chromosome=c( 0, 0, 0), 456s + start =x[c( 1, NA, 401)], 456s + end =x[c(349, NA, J)] 456s + ) 456s > fit6 <- segmentByCBS(y, x=x, knownSegments=knownSegments, verbose=TRUE) 456s Segmenting by CBS... 456s Chromosome: 0 456s Segmenting by CBS...done 456s > sampleName(fit6) <- "CBS_Example_6" 456s > print(fit6) 456s sampleName chromosome start end nbrOfLoci mean 456s 1 CBS_Example_6 0 65285.65 19648927 200 0.0109 456s 2 CBS_Example_6 0 19648927.46 28239656 95 0.9529 456s 3 CBS_Example_6 0 28239655.99 33106633 54 0.1169 456s 4 NA NA NA NA NA 456s 5 CBS_Example_6 0 38076667.59 65697742 248 -0.0408 456s 6 CBS_Example_6 0 65697742.20 79729368 153 -0.9534 456s 7 CBS_Example_6 0 79729368.34 99819310 199 -0.0497 456s > plotTracks(fit6) 456s Warning message: 456s In plotTracks.CBS(fit6) : 456s Setting default 'Clim' assuming the signal type is 'ratio' because signalType(fit6) is unknown ('NA'). Use signalType(fit6) <- 'ratio' to avoid this warning. 456s > abline(v=c(knownSegments$start, knownSegments$end)/1e6, lty=3) 456s > 456s > 456s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 456s > # Segment multiple chromosomes 456s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 456s > # Simulate multiple chromosomes 456s > fit1 <- renameChromosomes(fit, from=0, to=1) 456s > fit2 <- renameChromosomes(fit, from=0, to=2) 456s > fitM <- c(fit1, fit2) 456s > fitM <- segmentByCBS(fitM) 456s > sampleName(fitM) <- "CBS_Example_M" 456s > print(fitM) 456s sampleName chromosome start end nbrOfLoci mean 456s 1 CBS_Example_M 1 65285.65 19648927 200 0.0109 456s 2 CBS_Example_M 1 19648927.46 28239656 95 0.9529 456s 3 CBS_Example_M 1 28239655.99 65697742 302 -0.0126 456s 4 CBS_Example_M 1 65697742.20 79729368 153 -0.9534 456s 5 CBS_Example_M 1 79729368.34 99819310 199 -0.0497 456s 6 NA NA NA NA NA 456s 7 CBS_Example_M 2 65285.65 19648927 200 0.0109 456s 8 CBS_Example_M 2 19648927.46 28239656 95 0.9529 456s 9 CBS_Example_M 2 28239655.99 65697742 302 -0.0126 456s 10 CBS_Example_M 2 65697742.20 79729368 153 -0.9534 456s 11 CBS_Example_M 2 79729368.34 99819310 199 -0.0497 456s > plotTracks(fitM, Clim=c(-3,3)) 456s > 456s > 456s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 456s > # Tiling multiple chromosomes 456s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 456s > # Tile chromosomes 456s > fitT <- tileChromosomes(fitM) 456s > fitTb <- tileChromosomes(fitT) 456s > stopifnot(identical(fitTb, fitT)) 456s > 456s > 456s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 456s > # Write segmentation to file 456s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 456s > pathT <- tempdir() 456s > 456s > ## Tab-delimited file 456s > pathname <- writeSegments(fitM, path=pathT) 456s Warning message: 456s In write.table(file = pathnameT, data, append = TRUE, quote = FALSE, : 456s appending column names to file 456s > print(pathname) 456s [1] "/tmp/RtmpQUPfwA/CBS_Example_M.tsv" 456s > 456s > ## WIG file 456s > pathname <- writeWIG(fitM, path=pathT) 456s > print(pathname) 456s [1] "/tmp/RtmpQUPfwA/CBS_Example_M.wig" 456s > 456s > unlink(pathT, recursive=TRUE) 456s > 456s > proc.time() 456s user system elapsed 456s 1.866 0.085 1.942 456s Test segmentByCBS passed 456s 0 456s Begin test segmentByNonPairedPSCBS,medianDH 458s + cat segmentByNonPairedPSCBS,medianDH.Rout 458s 458s R version 4.3.2 (2023-10-31) -- "Eye Holes" 458s Copyright (C) 2023 The R Foundation for Statistical Computing 458s Platform: x86_64-pc-linux-gnu (64-bit) 458s 458s R is free software and comes with ABSOLUTELY NO WARRANTY. 458s You are welcome to redistribute it under certain conditions. 458s Type 'license()' or 'licence()' for distribution details. 458s 458s R is a collaborative project with many contributors. 458s Type 'contributors()' for more information and 458s 'citation()' on how to cite R or R packages in publications. 458s 458s Type 'demo()' for some demos, 'help()' for on-line help, or 458s 'help.start()' for an HTML browser interface to help. 458s Type 'q()' to quit R. 458s 458s [Previously saved workspace restored] 458s 458s > library("PSCBS") 458s PSCBS v0.66.0 (2021-10-23 07:40:02 UTC) successfully loaded. See ?PSCBS for help. 458s 458s Attaching package: 'PSCBS' 458s 458s The following objects are masked from 'package:base': 458s 458s append, load 458s 458s > 458s > 458s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 458s > # Load SNP microarray data 458s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 458s > data <- PSCBS::exampleData("paired.chr01") 458s > str(data) 458s 'data.frame': 73346 obs. of 6 variables: 458s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 458s $ x : int 1145994 2224111 2319424 2543484 2926730 2941694 3084986 3155127 3292731 3695086 ... 458s $ CT : num 1.625 1.071 1.406 1.18 0.856 ... 458s $ betaT : num 0.757 0.771 0.834 0.778 0.229 ... 458s $ CN : num 2.36 2.13 2.59 1.93 1.71 ... 458s $ betaN : num 0.827 0.875 0.887 0.884 0.103 ... 458s > 458s > # Non-paired / tumor-only data 458s > data <- data[,c("chromosome", "x", "CT", "betaT")] 458s > str(data) 458s 'data.frame': 73346 obs. of 4 variables: 458s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 458s $ x : int 1145994 2224111 2319424 2543484 2926730 2941694 3084986 3155127 3292731 3695086 ... 458s $ CT : num 1.625 1.071 1.406 1.18 0.856 ... 458s $ betaT : num 0.757 0.771 0.834 0.778 0.229 ... 458s > 458s > 458s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 458s > # Paired PSCBS segmentation 458s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 458s > # Drop single-locus outliers 458s > dataS <- dropSegmentationOutliers(data) 458s > 458s > # Speed up example by segmenting fewer loci 458s > dataS <- dataS[seq(from=1, to=nrow(data), by=20),] 458s > 458s > # Fake a second chromosome 458s > dataT <- dataS 458s > dataT$chromosome <- 2L 458s > dataS <- rbind(dataS, dataT) 458s > rm(dataT) 458s > str(dataS) 458s 'data.frame': 7336 obs. of 4 variables: 458s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 458s $ x : int 1145994 4276892 5034491 6266412 8418532 11211748 13928296 14370144 15014887 16589707 ... 458s $ CT : num 1.63 1.16 1.35 1.39 1.55 ... 458s $ betaT : num 0.7574 0.0576 0.8391 0.7917 0.8141 ... 458s > 458s > # Non-Paired PSCBS segmentation 458s > fit <- segmentByNonPairedPSCBS(dataS, avgDH="median", seed=0xBEEF, verbose=-10) 458s Segmenting non-paired tumor signals using Non-paired PSCBS... 458s Number of loci: 7336 458s Number of SNPs: 7336 458s Calling "genotypes" from tumor allele B fractions... 458s num [1:7336] 0.7574 0.0576 0.8391 0.7917 0.8141 ... 458s Upper quantile: 0.475631667925522 458s Symmetric lower quantile: 0.290517384533512 458s (tauA, tauB) estimates: (%g,%g)0.2094826154664880.790517384533512 458s Homozygous treshholds: 458s [1] 0.2094826 0.7905174 458s Inferred germline genotypes (via tumor): 458s num [1:7336] 0.5 0 1 1 1 0 0 0 0.5 1 ... 458s muNx 458s 0 0.5 1 458s 2230 2910 2196 458s Calling "genotypes" from tumor allele B fractions...done 458s Segmenting non-paired tumor signals using Non-paired PSCBS...done 458s Segment using Paired PSCBS... 458s Segmenting paired tumor-normal signals using Paired PSCBS... 458s Setup up data... 458s 'data.frame': 7336 obs. of 6 variables: 458s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 458s $ x : num 1145994 4276892 5034491 6266412 8418532 ... 458s $ CT : num 1.63 1.16 1.35 1.39 1.55 ... 458s $ betaT : num 0.7574 0.0576 0.8391 0.7917 0.8141 ... 458s $ betaTN : num 0.7574 0.0576 0.8391 0.7917 0.8141 ... 458s $ muN : num 0.5 0 1 1 1 0 0 0 0.5 1 ... 458s Setup up data...done 458s Dropping loci for which TCNs are missing... 458s Number of loci dropped: 12 458s Dropping loci for which TCNs are missing...done 458s Ordering data along genome... 458s 'data.frame': 7324 obs. of 6 variables: 458s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 458s $ x : num 554484 1031563 1087198 1145994 1176365 ... 458s $ CT : num 1.88 1.64 1.77 1.63 1.59 ... 458s $ betaT : num 0.0646 0.6078 0.401 0.7574 0.645 ... 458s $ betaTN : num 0.0646 0.6078 0.401 0.7574 0.645 ... 458s $ muN : num 0 0.5 0.5 0.5 0.5 0.5 1 0.5 0.5 0.5 ... 458s Ordering data along genome...done 458s Segmenting multiple chromosomes... 458s Number of chromosomes: 2 458s Random seed temporarily set (seed=c(48879), kind="L'Ecuyer-CMRG") 458s Produced 2 seeds from this stream for future usage 458s Chromosome #1 ('Chr01') of 2... 458s 'data.frame': 3662 obs. of 7 variables: 458s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 458s $ x : num 554484 1031563 1087198 1145994 1176365 ... 458s $ CT : num 1.88 1.64 1.77 1.63 1.59 ... 458s $ betaT : num 0.0646 0.6078 0.401 0.7574 0.645 ... 458s $ betaTN : num 0.0646 0.6078 0.401 0.7574 0.645 ... 458s $ muN : num 0 0.5 0.5 0.5 0.5 0.5 1 0.5 0.5 0.5 ... 458s $ index : int 1 2 3 4 5 6 7 8 9 10 ... 458s Known segments: 458s [1] chromosome start end 458s <0 rows> (or 0-length row.names) 458s Segmenting paired tumor-normal signals using Paired PSCBS... 458s Setup up data... 458s 'data.frame': 3662 obs. of 6 variables: 458s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 458s $ x : num 554484 1031563 1087198 1145994 1176365 ... 458s $ CT : num 1.88 1.64 1.77 1.63 1.59 ... 458s $ betaT : num 0.0646 0.6078 0.401 0.7574 0.645 ... 458s $ betaTN : num 0.0646 0.6078 0.401 0.7574 0.645 ... 458s $ muN : num 0 0.5 0.5 0.5 0.5 0.5 1 0.5 0.5 0.5 ... 458s Setup up data...done 458s Ordering data along genome... 458s 'data.frame': 3662 obs. of 6 variables: 458s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 458s $ x : num 554484 1031563 1087198 1145994 1176365 ... 458s $ CT : num 1.88 1.64 1.77 1.63 1.59 ... 458s $ betaT : num 0.0646 0.6078 0.401 0.7574 0.645 ... 458s $ betaTN : num 0.0646 0.6078 0.401 0.7574 0.645 ... 458s $ muN : num 0 0.5 0.5 0.5 0.5 0.5 1 0.5 0.5 0.5 ... 458s Ordering data along genome...done 458s Keeping only current chromosome for 'knownSegments'... 458s Chromosome: 1 458s Known segments for this chromosome: 458s [1] chromosome start end 458s <0 rows> (or 0-length row.names) 458s Keeping only current chromosome for 'knownSegments'...done 458s alphaTCN: 0.009 458s alphaDH: 0.001 458s Number of loci: 3662 458s Calculating DHs... 458s Number of SNPs: 3662 458s Number of heterozygous SNPs: 1451 (39.62%) 458s Normalized DHs: 458s num [1:3662] NA 0.216 0.198 0.515 0.29 ... 458s Calculating DHs...done 458s Random seed temporarily set (seed=c(10407, 1066287653, -51199871, 161854402, -1995183193, 1503453565, -747102133), kind="L'Ecuyer-CMRG") 458s Produced 2 seeds from this stream for future usage 458s Identification of change points by total copy numbers... 458s Segmenting by CBS... 458s Chromosome: 1 458s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 458s Segmenting by CBS...done 458s List of 4 458s $ data :'data.frame': 3662 obs. of 4 variables: 458s ..$ chromosome: int [1:3662] 1 1 1 1 1 1 1 1 1 1 ... 458s ..$ x : num [1:3662] 554484 1031563 1087198 1145994 1176365 ... 458s ..$ y : num [1:3662] 1.88 1.64 1.77 1.63 1.59 ... 458s ..$ index : int [1:3662] 1 2 3 4 5 6 7 8 9 10 ... 458s $ output :'data.frame': 3 obs. of 6 variables: 458s ..$ sampleName: chr [1:3] NA NA NA 458s ..$ chromosome: int [1:3] 1 1 1 458s ..$ start : num [1:3] 5.54e+05 1.44e+08 1.85e+08 458s ..$ end : num [1:3] 1.44e+08 1.85e+08 2.47e+08 458s ..$ nbrOfLoci : int [1:3] 1880 671 1111 458s ..$ mean : num [1:3] 1.39 2.09 2.65 458s $ segRows:'data.frame': 3 obs. of 2 variables: 458s ..$ startRow: int [1:3] 1 1881 2552 458s ..$ endRow : int [1:3] 1880 2551 3662 458s $ params :List of 5 458s ..$ alpha : num 0.009 458s ..$ undo : num 0 458s ..$ joinSegments : logi TRUE 458s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 458s .. ..$ chromosome: int 1 458s .. ..$ start : num -Inf 458s .. ..$ end : num Inf 458s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 458s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 458s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.061 0 0.06 0 0 458s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 458s - attr(*, "pkgDetails")= chr "DNAcopy v1.76.0" 458s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 458s Identification of change points by total copy numbers...done 458s Restructure TCN segmentation results... 458s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean 458s 1 1 554484 143663981 1880 1.3916 458s 2 1 143663981 185240536 671 2.0925 458s 3 1 185240536 246679946 1111 2.6545 458s Number of TCN segments: 3 458s Restructure TCN segmentation results...done 458s TCN-only segmentation... 458s Total CN segment #1 ([ 554484,1.43664e+08]) of 3... 458s Number of TCN loci in segment: 1880 458s Locus data for TCN segment: 458s 'data.frame': 1880 obs. of 8 variables: 458s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 458s $ x : num 554484 1031563 1087198 1145994 1176365 ... 458s $ CT : num 1.88 1.64 1.77 1.63 1.59 ... 458s $ betaT : num 0.0646 0.6078 0.401 0.7574 0.645 ... 458s $ betaTN : num 0.0646 0.6078 0.401 0.7574 0.645 ... 458s $ muN : num 0 0.5 0.5 0.5 0.5 0.5 1 0.5 0.5 0.5 ... 458s $ index : int 1 2 3 4 5 6 7 8 9 10 ... 458s $ rho : num NA 0.216 0.198 0.515 0.29 ... 458s Number of loci: 1880 458s Number of SNPs: 765 (40.69%) 458s Number of heterozygous SNPs: 765 (100.00%) 458s Total CN segment #1 ([ 554484,1.43664e+08]) of 3...done 458s Total CN segment #2 ([1.43664e+08,1.85241e+08]) of 3... 458s Number of TCN loci in segment: 671 458s Locus data for TCN segment: 458s 'data.frame': 671 obs. of 8 variables: 458s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 458s $ x : num 1.44e+08 1.44e+08 1.44e+08 1.44e+08 1.44e+08 ... 458s $ CT : num 2.26 2.1 2.1 1.89 1.97 ... 458s $ betaT : num 0.958 0.19 0.909 0.13 0.141 ... 458s $ betaTN : num 0.958 0.19 0.909 0.13 0.141 ... 458s $ muN : num 1 0 1 0 0 0 0 0.5 0 1 ... 458s $ index : int 1881 1882 1883 1884 1885 1886 1887 1888 1889 1890 ... 458s $ rho : num NA NA NA NA NA ... 458s Number of loci: 671 458s Number of SNPs: 272 (40.54%) 458s Number of heterozygous SNPs: 272 (100.00%) 458s Total CN segment #2 ([1.43664e+08,1.85241e+08]) of 3...done 458s Total CN segment #3 ([1.85241e+08,2.4668e+08]) of 3... 458s Number of TCN loci in segment: 1111 458s Locus data for TCN segment: 458s 'data.frame': 1111 obs. of 8 variables: 458s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 458s $ x : num 1.85e+08 1.86e+08 1.86e+08 1.86e+08 1.86e+08 ... 458s $ CT : num 2.44 3 2.32 2.76 2.48 ... 458s $ betaT : num 0.0727 0.6845 0.2327 0.8118 0.0746 ... 458s $ betaTN : num 0.0727 0.6845 0.2327 0.8118 0.0746 ... 458s $ muN : num 0 0.5 0.5 1 0 1 0 1 1 0.5 ... 458s $ index : int 2552 2553 2554 2555 2556 2557 2558 2559 2560 2561 ... 458s $ rho : num NA 0.369 0.535 NA NA ... 458s Number of loci: 1111 458s Number of SNPs: 414 (37.26%) 458s Number of heterozygous SNPs: 414 (100.00%) 458s Total CN segment #3 ([1.85241e+08,2.4668e+08]) of 3...done 458s TCN-only segmentation...done 458s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 458s 1 1 1 1 554484 143663981 1880 1.3916 765 458s 2 1 2 1 143663981 185240536 671 2.0925 272 458s 3 1 3 1 185240536 246679946 1111 2.6545 414 458s tcnNbrOfHets dhNbrOfLoci dhStart dhEnd dhMean 458s 1 765 765 554484 143663981 0.3979122 458s 2 272 272 143663981 185240536 0.2306116 458s 3 414 414 185240536 246679946 0.2798120 458s Calculating (C1,C2) per segment... 458s Calculating (C1,C2) per segment...done 458s Number of segments: 3 458s Segmenting paired tumor-normal signals using Paired PSCBS...done 458s Updating mean level using different estimator... 458s TCN estimator: mean 458s DH estimator: median 458s Updating mean level using different estimator...done 458s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 458s 1 1 1 1 554484 143663981 1880 1.391608 765 458s 2 1 2 1 143663981 185240536 671 2.092452 272 458s 3 1 3 1 185240536 246679946 1111 2.654512 414 458s tcnNbrOfHets dhNbrOfLoci dhStart dhEnd dhMean c1Mean c2Mean 458s 1 765 765 554484 143663981 0.4206323 0.4031263 0.9884817 458s 2 272 272 143663981 185240536 0.1762428 0.8618360 1.2306156 458s 3 414 414 185240536 246679946 0.2697420 0.9692395 1.6852728 458s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 458s 1 1 1 1 554484 143663981 1880 1.391608 765 458s 2 1 2 1 143663981 185240536 671 2.092452 272 458s 3 1 3 1 185240536 246679946 1111 2.654512 414 458s tcnNbrOfHets dhNbrOfLoci dhStart dhEnd dhMean c1Mean c2Mean 458s 1 765 765 554484 143663981 0.4206323 0.4031263 0.9884817 458s 2 272 272 143663981 185240536 0.1762428 0.8618360 1.2306156 458s 3 414 414 185240536 246679946 0.2697420 0.9692395 1.6852728 458s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 458s 1 1 1 1 554484 143663981 1880 1.391608 765 458s 2 1 2 1 143663981 185240536 671 2.092452 272 458s 3 1 3 1 185240536 246679946 1111 2.654512 414 458s tcnNbrOfHets dhNbrOfLoci dhStart dhEnd dhMean c1Mean c2Mean 458s 1 765 765 554484 143663981 0.4206323 0.4031263 0.9884817 458s 2 272 272 143663981 185240536 0.1762428 0.8618360 1.2306156 458s 3 414 414 185240536 246679946 0.2697420 0.9692395 1.6852728 458s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 458s 1 1 1 1 554484 143663981 1880 1.391608 765 458s 2 1 2 1 143663981 185240536 671 2.092452 272 458s 3 1 3 1 185240536 246679946 1111 2.654512 414 458s tcnNbrOfHets dhNbrOfLoci dhStart dhEnd dhMean c1Mean c2Mean 458s 1 765 765 554484 143663981 0.4206323 0.4031263 0.9884817 458s 2 272 272 143663981 185240536 0.1762428 0.8618360 1.2306156 458s 3 414 414 185240536 246679946 0.2697420 0.9692395 1.6852728 458s Chromosome #1 ('Chr01') of 2...done 458s Chromosome #2 ('Chr02') of 2... 458s 'data.frame': 3662 obs. of 7 variables: 458s $ chromosome: int 2 2 2 2 2 2 2 2 2 2 ... 458s $ x : num 554484 1031563 1087198 1145994 1176365 ... 458s $ CT : num 1.88 1.64 1.77 1.63 1.59 ... 458s $ betaT : num 0.0646 0.6078 0.401 0.7574 0.645 ... 458s $ betaTN : num 0.0646 0.6078 0.401 0.7574 0.645 ... 458s $ muN : num 0 0.5 0.5 0.5 0.5 0.5 1 0.5 0.5 0.5 ... 458s $ index : int 3663 3664 3665 3666 3667 3668 3669 3670 3671 3672 ... 458s Known segments: 458s [1] chromosome start end 458s <0 rows> (or 0-length row.names) 458s Segmenting paired tumor-normal signals using Paired PSCBS... 458s Setup up data... 458s 'data.frame': 3662 obs. of 6 variables: 458s + [ 0 != 0 ] 458s + echo Test segmentByNonPairedPSCBS,medianDH passed 458s + echo 0 458s + echo Begin test segmentByPairedPSCBS,DH 458s + exitcode=0 458s + R CMD BATCH segmentByPairedPSCBS,DH.R 458s $ chromosome: int 2 2 2 2 2 2 2 2 2 2 ... 458s $ x : num 554484 1031563 1087198 1145994 1176365 ... 458s $ CT : num 1.88 1.64 1.77 1.63 1.59 ... 458s $ betaT : num 0.0646 0.6078 0.401 0.7574 0.645 ... 458s $ betaTN : num 0.0646 0.6078 0.401 0.7574 0.645 ... 458s $ muN : num 0 0.5 0.5 0.5 0.5 0.5 1 0.5 0.5 0.5 ... 458s Setup up data...done 458s Ordering data along genome... 458s 'data.frame': 3662 obs. of 6 variables: 458s $ chromosome: int 2 2 2 2 2 2 2 2 2 2 ... 458s $ x : num 554484 1031563 1087198 1145994 1176365 ... 458s $ CT : num 1.88 1.64 1.77 1.63 1.59 ... 458s $ betaT : num 0.0646 0.6078 0.401 0.7574 0.645 ... 458s $ betaTN : num 0.0646 0.6078 0.401 0.7574 0.645 ... 458s $ muN : num 0 0.5 0.5 0.5 0.5 0.5 1 0.5 0.5 0.5 ... 458s Ordering data along genome...done 458s Keeping only current chromosome for 'knownSegments'... 458s Chromosome: 2 458s Known segments for this chromosome: 458s [1] chromosome start end 458s <0 rows> (or 0-length row.names) 458s Keeping only current chromosome for 'knownSegments'...done 458s alphaTCN: 0.009 458s alphaDH: 0.001 458s Number of loci: 3662 458s Calculating DHs... 458s Number of SNPs: 3662 458s Number of heterozygous SNPs: 1451 (39.62%) 458s Normalized DHs: 458s num [1:3662] NA 0.216 0.198 0.515 0.29 ... 458s Calculating DHs...done 458s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 458s Produced 2 seeds from this stream for future usage 458s Identification of change points by total copy numbers... 458s Segmenting by CBS... 458s Chromosome: 2 458s Random seed temporarily set (seed=c(10407, -821273412, -52578226, 1415511586, 721384351, -665928286, 1316562960), kind="L'Ecuyer-CMRG") 458s Segmenting by CBS...done 458s List of 4 458s $ data :'data.frame': 3662 obs. of 4 variables: 458s ..$ chromosome: int [1:3662] 2 2 2 2 2 2 2 2 2 2 ... 458s ..$ x : num [1:3662] 554484 1031563 1087198 1145994 1176365 ... 458s ..$ y : num [1:3662] 1.88 1.64 1.77 1.63 1.59 ... 458s ..$ index : int [1:3662] 1 2 3 4 5 6 7 8 9 10 ... 458s $ output :'data.frame': 3 obs. of 6 variables: 458s ..$ sampleName: chr [1:3] NA NA NA 458s ..$ chromosome: int [1:3] 2 2 2 458s ..$ start : num [1:3] 5.54e+05 1.44e+08 1.85e+08 458s ..$ end : num [1:3] 1.44e+08 1.85e+08 2.47e+08 458s ..$ nbrOfLoci : int [1:3] 1880 671 1111 458s ..$ mean : num [1:3] 1.39 2.09 2.65 458s $ segRows:'data.frame': 3 obs. of 2 variables: 458s ..$ startRow: int [1:3] 1 1881 2552 458s ..$ endRow : int [1:3] 1880 2551 3662 458s $ params :List of 5 458s ..$ alpha : num 0.009 458s ..$ undo : num 0 458s ..$ joinSegments : logi TRUE 458s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 458s .. ..$ chromosome: int 2 458s .. ..$ start : num -Inf 458s .. ..$ end : num Inf 458s ..$ seed : int [1:7] 10407 -821273412 -52578226 1415511586 721384351 -665928286 1316562960 458s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 458s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.06 0 0.061 0 0 458s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 458s - attr(*, "pkgDetails")= chr "DNAcopy v1.76.0" 458s - attr(*, "randomSeed")= int [1:7] 10407 -821273412 -52578226 1415511586 721384351 -665928286 1316562960 458s Identification of change points by total copy numbers...done 458s Restructure TCN segmentation results... 458s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean 458s 1 2 554484 143663981 1880 1.3916 458s 2 2 143663981 185240536 671 2.0925 458s 3 2 185240536 246679946 1111 2.6545 458s Number of TCN segments: 3 458s Restructure TCN segmentation results...done 458s TCN-only segmentation... 458s Total CN segment #1 ([ 554484,1.43664e+08]) of 3... 458s Number of TCN loci in segment: 1880 458s Locus data for TCN segment: 458s 'data.frame': 1880 obs. of 8 variables: 458s $ chromosome: int 2 2 2 2 2 2 2 2 2 2 ... 458s $ x : num 554484 1031563 1087198 1145994 1176365 ... 458s $ CT : num 1.88 1.64 1.77 1.63 1.59 ... 458s $ betaT : num 0.0646 0.6078 0.401 0.7574 0.645 ... 458s $ betaTN : num 0.0646 0.6078 0.401 0.7574 0.645 ... 458s $ muN : num 0 0.5 0.5 0.5 0.5 0.5 1 0.5 0.5 0.5 ... 458s $ index : int 1 2 3 4 5 6 7 8 9 10 ... 458s $ rho : num NA 0.216 0.198 0.515 0.29 ... 458s Number of loci: 1880 458s Number of SNPs: 765 (40.69%) 458s Number of heterozygous SNPs: 765 (100.00%) 458s Total CN segment #1 ([ 554484,1.43664e+08]) of 3...done 458s Total CN segment #2 ([1.43664e+08,1.85241e+08]) of 3... 458s Number of TCN loci in segment: 671 458s Locus data for TCN segment: 458s 'data.frame': 671 obs. of 8 variables: 458s $ chromosome: int 2 2 2 2 2 2 2 2 2 2 ... 458s $ x : num 1.44e+08 1.44e+08 1.44e+08 1.44e+08 1.44e+08 ... 458s $ CT : num 2.26 2.1 2.1 1.89 1.97 ... 458s $ betaT : num 0.958 0.19 0.909 0.13 0.141 ... 458s $ betaTN : num 0.958 0.19 0.909 0.13 0.141 ... 458s $ muN : num 1 0 1 0 0 0 0 0.5 0 1 ... 458s $ index : int 1881 1882 1883 1884 1885 1886 1887 1888 1889 1890 ... 458s $ rho : num NA NA NA NA NA ... 458s Number of loci: 671 458s Number of SNPs: 272 (40.54%) 458s Number of heterozygous SNPs: 272 (100.00%) 458s Total CN segment #2 ([1.43664e+08,1.85241e+08]) of 3...done 458s Total CN segment #3 ([1.85241e+08,2.4668e+08]) of 3... 458s Number of TCN loci in segment: 1111 458s Locus data for TCN segment: 458s 'data.frame': 1111 obs. of 8 variables: 458s $ chromosome: int 2 2 2 2 2 2 2 2 2 2 ... 458s $ x : num 1.85e+08 1.86e+08 1.86e+08 1.86e+08 1.86e+08 ... 458s $ CT : num 2.44 3 2.32 2.76 2.48 ... 458s $ betaT : num 0.0727 0.6845 0.2327 0.8118 0.0746 ... 458s $ betaTN : num 0.0727 0.6845 0.2327 0.8118 0.0746 ... 458s $ muN : num 0 0.5 0.5 1 0 1 0 1 1 0.5 ... 458s $ index : int 2552 2553 2554 2555 2556 2557 2558 2559 2560 2561 ... 458s $ rho : num NA 0.369 0.535 NA NA ... 458s Number of loci: 1111 458s Number of SNPs: 414 (37.26%) 458s Number of heterozygous SNPs: 414 (100.00%) 458s Total CN segment #3 ([1.85241e+08,2.4668e+08]) of 3...done 458s TCN-only segmentation...done 458s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 458s 1 2 1 1 554484 143663981 1880 1.3916 765 458s 2 2 2 1 143663981 185240536 671 2.0925 272 458s 3 2 3 1 185240536 246679946 1111 2.6545 414 458s tcnNbrOfHets dhNbrOfLoci dhStart dhEnd dhMean 458s 1 765 765 554484 143663981 0.3979122 458s 2 272 272 143663981 185240536 0.2306116 458s 3 414 414 185240536 246679946 0.2798120 458s Calculating (C1,C2) per segment... 458s Calculating (C1,C2) per segment...done 458s Number of segments: 3 458s Segmenting paired tumor-normal signals using Paired PSCBS...done 458s Updating mean level using different estimator... 458s TCN estimator: mean 458s DH estimator: median 458s Updating mean level using different estimator...done 458s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 458s 1 2 1 1 554484 143663981 1880 1.391608 765 458s 2 2 2 1 143663981 185240536 671 2.092452 272 458s 3 2 3 1 185240536 246679946 1111 2.654512 414 458s tcnNbrOfHets dhNbrOfLoci dhStart dhEnd dhMean c1Mean c2Mean 458s 1 765 765 554484 143663981 0.4206323 0.4031263 0.9884817 458s 2 272 272 143663981 185240536 0.1762428 0.8618360 1.2306156 458s 3 414 414 185240536 246679946 0.2697420 0.9692395 1.6852728 458s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 458s 1 2 1 1 554484 143663981 1880 1.391608 765 458s 2 2 2 1 143663981 185240536 671 2.092452 272 458s 3 2 3 1 185240536 246679946 1111 2.654512 414 458s tcnNbrOfHets dhNbrOfLoci dhStart dhEnd dhMean c1Mean c2Mean 458s 1 765 765 554484 143663981 0.4206323 0.4031263 0.9884817 458s 2 272 272 143663981 185240536 0.1762428 0.8618360 1.2306156 458s 3 414 414 185240536 246679946 0.2697420 0.9692395 1.6852728 458s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 458s 1 2 1 1 554484 143663981 1880 1.391608 765 458s 2 2 2 1 143663981 185240536 671 2.092452 272 458s 3 2 3 1 185240536 246679946 1111 2.654512 414 458s tcnNbrOfHets dhNbrOfLoci dhStart dhEnd dhMean c1Mean c2Mean 458s 1 765 765 554484 143663981 0.4206323 0.4031263 0.9884817 458s 2 272 272 143663981 185240536 0.1762428 0.8618360 1.2306156 458s 3 414 414 185240536 246679946 0.2697420 0.9692395 1.6852728 458s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 458s 1 2 1 1 554484 143663981 1880 1.391608 765 458s 2 2 2 1 143663981 185240536 671 2.092452 272 458s 3 2 3 1 185240536 246679946 1111 2.654512 414 458s tcnNbrOfHets dhNbrOfLoci dhStart dhEnd dhMean c1Mean c2Mean 458s 1 765 765 554484 143663981 0.4206323 0.4031263 0.9884817 458s 2 272 272 143663981 185240536 0.1762428 0.8618360 1.2306156 458s 3 414 414 185240536 246679946 0.2697420 0.9692395 1.6852728 458s Chromosome #2 ('Chr02') of 2...done 458s Merging (independently) segmented chromosome... 458s List of 5 458s $ data :Classes 'PairedPSCNData' and 'data.frame': 7324 obs. of 7 variables: 458s ..$ chromosome: int [1:7324] 1 1 1 1 1 1 1 1 1 1 ... 458s ..$ x : num [1:7324] 554484 1031563 1087198 1145994 1176365 ... 458s ..$ CT : num [1:7324] 1.88 1.64 1.77 1.63 1.59 ... 458s ..$ betaT : num [1:7324] 0.0646 0.6078 0.401 0.7574 0.645 ... 458s ..$ betaTN : num [1:7324] 0.0646 0.6078 0.401 0.7574 0.645 ... 458s ..$ muN : num [1:7324] 0 0.5 0.5 0.5 0.5 0.5 1 0.5 0.5 0.5 ... 458s ..$ rho : num [1:7324] NA 0.216 0.198 0.515 0.29 ... 458s $ output :Classes 'PairedPSCNSegments' and 'data.frame': 7 obs. of 15 variables: 458s ..$ chromosome : int [1:7] 1 1 1 NA 2 2 2 458s ..$ tcnId : int [1:7] 1 2 3 NA 1 2 3 458s ..$ dhId : int [1:7] 1 1 1 NA 1 1 1 458s ..$ tcnStart : num [1:7] 5.54e+05 1.44e+08 1.85e+08 NA 5.54e+05 ... 458s ..$ tcnEnd : num [1:7] 1.44e+08 1.85e+08 2.47e+08 NA 1.44e+08 ... 458s ..$ tcnNbrOfLoci: int [1:7] 1880 671 1111 NA 1880 671 1111 458s ..$ tcnMean : num [1:7] 1.39 2.09 2.65 NA 1.39 ... 458s ..$ tcnNbrOfSNPs: int [1:7] 765 272 414 NA 765 272 414 458s ..$ tcnNbrOfHets: int [1:7] 765 272 414 NA 765 272 414 458s ..$ dhNbrOfLoci : int [1:7] 765 272 414 NA 765 272 414 458s ..$ dhStart : num [1:7] 5.54e+05 1.44e+08 1.85e+08 NA 5.54e+05 ... 458s ..$ dhEnd : num [1:7] 1.44e+08 1.85e+08 2.47e+08 NA 1.44e+08 ... 458s ..$ dhMean : num [1:7] 0.421 0.176 0.27 NA 0.421 ... 458s ..$ c1Mean : num [1:7] 0.403 0.862 0.969 NA 0.403 ... 458s ..$ c2Mean : num [1:7] 0.988 1.231 1.685 NA 0.988 ... 458s $ tcnSegRows:'data.frame': 7 obs. of 2 variables: 458s ..$ startRow: int [1:7] 1 1881 2552 NA 3663 5543 6214 458s ..$ endRow : int [1:7] 1880 2551 3662 NA 5542 6213 7324 458s $ dhSegRows :'data.frame': 7 obs. of 2 variables: 458s ..$ startRow: int [1:7] 2 1888 2553 NA 3664 5550 6215 458s ..$ endRow : int [1:7] 1876 2548 3659 NA 5538 6210 7321 458s $ params :List of 8 458s ..$ alphaTCN : num 0.009 458s ..$ alphaDH : num 0.001 458s ..$ flavor : chr "tcn" 458s ..$ tbn : logi FALSE 458s ..$ joinSegments : logi TRUE 458s ..$ knownSegments :'data.frame': 0 obs. of 3 variables: 458s .. ..$ chromosome: int(0) 458s .. ..$ start : int(0) 458s .. ..$ end : int(0) 458s ..$ seed : int [1:7] 10407 1066287653 -51199871 161854402 -1995183193 1503453565 -747102133 458s ..$ meanEstimators:List of 2 458s .. ..$ tcn: chr "mean" 458s .. ..$ dh : chr "median" 458s - attr(*, "class")= chr [1:3] "PairedPSCBS" "PSCBS" "AbstractCBS" 458s Merging (independently) segmented chromosome...done 458s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 458s 1 1 1 1 554484 143663981 1880 1.391608 765 458s 2 1 2 1 143663981 185240536 671 2.092452 272 458s 3 1 3 1 185240536 246679946 1111 2.654512 414 458s 4 NA NA NA NA NA NA NA NA 458s 5 2 1 1 554484 143663981 1880 1.391608 765 458s 6 2 2 1 143663981 185240536 671 2.092452 272 458s tcnNbrOfHets dhNbrOfLoci dhStart dhEnd dhMean c1Mean c2Mean 458s 1 765 765 554484 143663981 0.4206323 0.4031263 0.9884817 458s 2 272 272 143663981 185240536 0.1762428 0.8618360 1.2306156 458s 3 414 414 185240536 246679946 0.2697420 0.9692395 1.6852728 458s 4 NA NA NA NA NA NA NA 458s 5 765 765 554484 143663981 0.4206323 0.4031263 0.9884817 458s 6 272 272 143663981 185240536 0.1762428 0.8618360 1.2306156 458s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 458s 2 1 2 1 143663981 185240536 671 2.092452 272 458s 3 1 3 1 185240536 246679946 1111 2.654512 414 458s 4 NA NA NA NA NA NA NA NA 458s 5 2 1 1 554484 143663981 1880 1.391608 765 458s 6 2 2 1 143663981 185240536 671 2.092452 272 458s 7 2 3 1 185240536 246679946 1111 2.654512 414 458s tcnNbrOfHets dhNbrOfLoci dhStart dhEnd dhMean c1Mean c2Mean 458s 2 272 272 143663981 185240536 0.1762428 0.8618360 1.2306156 458s 3 414 414 185240536 246679946 0.2697420 0.9692395 1.6852728 458s 4 NA NA NA NA NA NA NA 458s 5 765 765 554484 143663981 0.4206323 0.4031263 0.9884817 458s 6 272 272 143663981 185240536 0.1762428 0.8618360 1.2306156 458s 7 414 414 185240536 246679946 0.2697420 0.9692395 1.6852728 458s Segmenting multiple chromosomes...done 458s Segmenting paired tumor-normal signals using Paired PSCBS...done 458s Segment using Paired PSCBS...done 458s Coercing to Non-Paired PSCBS results... 458s Coercing to Non-Paired PSCBS results...done 458s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 458s 1 1 1 1 554484 143663981 1880 1.391608 765 458s 2 1 2 1 143663981 185240536 671 2.092452 272 458s 3 1 3 1 185240536 246679946 1111 2.654512 414 458s 4 NA NA NA NA NA NA NA NA 458s 5 2 1 1 554484 143663981 1880 1.391608 765 458s 6 2 2 1 143663981 185240536 671 2.092452 272 458s tcnNbrOfHets dhNbrOfLoci dhStart dhEnd dhMean c1Mean c2Mean 458s 1 765 765 554484 143663981 0.4206323 0.4031263 0.9884817 458s 2 272 272 143663981 185240536 0.1762428 0.8618360 1.2306156 458s 3 414 414 185240536 246679946 0.2697420 0.9692395 1.6852728 458s 4 NA NA NA NA NA NA NA 458s 5 765 765 554484 143663981 0.4206323 0.4031263 0.9884817 458s 6 272 272 143663981 185240536 0.1762428 0.8618360 1.2306156 458s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 458s 2 1 2 1 143663981 185240536 671 2.092452 272 458s 3 1 3 1 185240536 246679946 1111 2.654512 414 458s 4 NA NA NA NA NA NA NA NA 458s 5 2 1 1 554484 143663981 1880 1.391608 765 458s 6 2 2 1 143663981 185240536 671 2.092452 272 458s 7 2 3 1 185240536 246679946 1111 2.654512 414 458s tcnNbrOfHets dhNbrOfLoci dhStart dhEnd dhMean c1Mean c2Mean 458s 2 272 272 143663981 185240536 0.1762428 0.8618360 1.2306156 458s 3 414 414 185240536 246679946 0.2697420 0.9692395 1.6852728 458s 4 NA NA NA NA NA NA NA 458s 5 765 765 554484 143663981 0.4206323 0.4031263 0.9884817 458s 6 272 272 143663981 185240536 0.1762428 0.8618360 1.2306156 458s 7 414 414 185240536 246679946 0.2697420 0.9692395 1.6852728 458s > print(fit) 458s chromosome tcnId dhId start end tcnNbrOfLoci tcnMean tcnNbrOfSNPs 458s 1 1 1 1 554484 143663981 1880 1.391608 765 458s 2 1 2 1 143663981 185240536 671 2.092452 272 458s 3 1 3 1 185240536 246679946 1111 2.654512 414 458s 4 NA NA NA NA NA NA NA NA 458s 5 2 1 1 554484 143663981 1880 1.391608 765 458s 6 2 2 1 143663981 185240536 671 2.092452 272 458s 7 2 3 1 185240536 246679946 1111 2.654512 414 458s tcnNbrOfHets dhNbrOfLoci dhMean c1Mean c2Mean 458s 1 765 765 0.4206323 0.4031263 0.9884817 458s 2 272 272 0.1762428 0.8618360 1.2306156 458s 3 414 414 0.2697420 0.9692395 1.6852728 458s 4 NA NA NA NA NA 458s 5 765 765 0.4206323 0.4031263 0.9884817 458s 6 272 272 0.1762428 0.8618360 1.2306156 458s 7 414 414 0.2697420 0.9692395 1.6852728 458s > 458s > 458s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 458s > # Bootstrap segment level estimates 458s > # (used by the AB caller, which, if skipped here, 458s > # will do it automatically) 458s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 458s > fit <- bootstrapTCNandDHByRegion(fit, B=100, verbose=-10) 458s Resample (TCN,DH) signals and re-estimate summaries for segment & changepoint... 458s Already done? 458s tcn_2.5% tcn_5% tcn_95% tcn_97.5% dh_2.5% dh_5% dh_95% dh_97.5% 458s FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE 458s c1_2.5% c1_5% c1_95% c1_97.5% c2_2.5% c2_5% c2_95% c2_97.5% 458s FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE 458s Bootstrapping (TCN,DH,C1,C2) segment mean levels... 458s Identifying heterozygous & homozygous SNPs and non-polymorphic loci... 458s Number of loci: 7324 458s Number of SNPs: 2902 458s Number of non-SNPs: 4422 458s Identifying heterozygous & homozygous SNPs and non-polymorphic loci...done 458s num [1:7, 1:100, 1:4] NA NA NA NA NA NA NA NA NA NA ... 458s - attr(*, "dimnames")=List of 3 458s ..$ : NULL 458s ..$ : NULL 458s ..$ : chr [1:4] "tcn" "dh" "c1" "c2" 458s Segment #1 (chr 1, tcnId=1, dhId=1) of 7... 458s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 458s 1 1 1 1 554484 143663981 1880 1.391608 765 458s tcnNbrOfHets dhNbrOfLoci dhStart dhEnd dhMean c1Mean c2Mean 458s 1 765 765 554484 143663981 0.4206323 0.4031263 0.9884817 458s Number of TCNs: 1880 458s Number of DHs: 765 458s int [1:1880] 1 2 3 4 5 6 7 8 9 10 ... 458s int [1:7324] 1 2 3 4 5 6 7 8 9 10 ... 458s int [1:1880] 1 2 3 4 5 6 7 8 9 10 ... 458s Identify loci used to bootstrap DH means... 458s Heterozygous SNPs to resample for DH: 458s int [1:765] 2 3 4 5 6 8 9 10 11 12 ... 458s Identify loci used to bootstrap DH means...done 458s Identify loci used to bootstrap TCN means... 458s SNPs: 458s int [1:765] 2 3 4 5 6 8 9 10 11 12 ... 458s Non-polymorphic loci: 458s int [1:1115] 1 7 15 28 30 32 34 35 36 37 ... 458s Heterozygous SNPs to resample for TCN: 458s int [1:765] 2 3 4 5 6 8 9 10 11 12 ... 458s Homozygous SNPs to resample for TCN: 458s int(0) 458s Non-polymorphic loci to resample for TCN: 458s int [1:1115] 1 7 15 28 30 32 34 35 36 37 ... 458s Heterozygous SNPs with non-DH to resample for TCN: 458s int(0) 458s Loci to resample for TCN: 458s int [1:1880] 1 2 3 4 5 6 7 8 9 10 ... 458s Identify loci used to bootstrap TCN means...done 458s Number of (#hets, #homs, #nonSNPs): (765,0,1115) 458s Bootstrapping while preserving (#hets, #homs, #nonSNPs)... 458s Number of bootstrap samples: 100 458s Bootstrapping while preserving (#hets, #homs, #nonSNPs)...done 458s Segment #1 (chr 1, tcnId=1, dhId=1) of 7...done 458s Segment #2 (chr 1, tcnId=2, dhId=1) of 7... 458s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 458s 2 1 2 1 143663981 185240536 671 2.092452 272 458s tcnNbrOfHets dhNbrOfLoci dhStart dhEnd dhMean c1Mean c2Mean 458s 2 272 272 143663981 185240536 0.1762428 0.861836 1.230616 458s Number of TCNs: 671 458s Number of DHs: 272 458s int [1:671] 1881 1882 1883 1884 1885 1886 1887 1888 1889 1890 ... 458s int [1:7324] 1 2 3 4 5 6 7 8 9 10 ... 458s int [1:671] 1881 1882 1883 1884 1885 1886 1887 1888 1889 1890 ... 458s Identify loci used to bootstrap DH means... 458s Heterozygous SNPs to resample for DH: 458s int [1:272] 1888 1893 1894 1895 1896 1897 1901 1903 1907 1908 ... 458s Identify loci used to bootstrap DH means...done 458s Identify loci used to bootstrap TCN means... 458s SNPs: 458s int [1:272] 1888 1893 1894 1895 1896 1897 1901 1903 1907 1908 ... 458s Non-polymorphic loci: 458s int [1:399] 1881 1882 1883 1884 1885 1886 1887 1889 1890 1891 ... 458s Heterozygous SNPs to resample for TCN: 458s int [1:272] 1888 1893 1894 1895 1896 1897 1901 1903 1907 1908 ... 458s Homozygous SNPs to resample for TCN: 458s int(0) 458s Non-polymorphic loci to resample for TCN: 458s int [1:399] 1881 1882 1883 1884 1885 1886 1887 1889 1890 1891 ... 458s Heterozygous SNPs with non-DH to resample for TCN: 458s int(0) 458s Loci to resample for TCN: 458s int [1:671] 1881 1882 1883 1884 1885 1886 1887 1888 1889 1890 ... 458s Identify loci used to bootstrap TCN means...done 458s Number of (#hets, #homs, #nonSNPs): (272,0,399) 458s Bootstrapping while preserving (#hets, #homs, #nonSNPs)... 458s Number of bootstrap samples: 100 458s Bootstrapping while preserving (#hets, #homs, #nonSNPs)...done 458s Segment #2 (chr 1, tcnId=2, dhId=1) of 7...done 458s Segment #3 (chr 1, tcnId=3, dhId=1) of 7... 458s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 458s 3 1 3 1 185240536 246679946 1111 2.654512 414 458s tcnNbrOfHets dhNbrOfLoci dhStart dhEnd dhMean c1Mean c2Mean 458s 3 414 414 185240536 246679946 0.269742 0.9692395 1.685273 458s Number of TCNs: 1111 458s Number of DHs: 414 458s int [1:1111] 2552 2553 2554 2555 2556 2557 2558 2559 2560 2561 ... 458s int [1:7324] 1 2 3 4 5 6 7 8 9 10 ... 458s int [1:1111] 2552 2553 2554 2555 2556 2557 2558 2559 2560 2561 ... 458s Identify loci used to bootstrap DH means... 458s Heterozygous SNPs to resample for DH: 458s int [1:414] 2553 2554 2561 2562 2563 2568 2569 2572 2573 2574 ... 458s Identify loci used to bootstrap DH means...done 458s Identify loci used to bootstrap TCN means... 458s SNPs: 458s int [1:414] 2553 2554 2561 2562 2563 2568 2569 2572 2573 2574 ... 458s Non-polymorphic loci: 458s int [1:697] 2552 2555 2556 2557 2558 2559 2560 2564 2565 2566 ... 458s Heterozygous SNPs to resample for TCN: 458s int [1:414] 2553 2554 2561 2562 2563 2568 2569 2572 2573 2574 ... 458s Homozygous SNPs to resample for TCN: 458s int(0) 458s Non-polymorphic loci to resample for TCN: 458s int [1:697] 2552 2555 2556 2557 2558 2559 2560 2564 2565 2566 ... 458s Heterozygous SNPs with non-DH to resample for TCN: 458s int(0) 458s Loci to resample for TCN: 458s int [1:1111] 2552 2553 2554 2555 2556 2557 2558 2559 2560 2561 ... 458s Identify loci used to bootstrap TCN means...done 458s Number of (#hets, #homs, #nonSNPs): (414,0,697) 458s Bootstrapping while preserving (#hets, #homs, #nonSNPs)... 458s Number of bootstrap samples: 100 458s Bootstrapping while preserving (#hets, #homs, #nonSNPs)...done 458s Segment #3 (chr 1, tcnId=3, dhId=1) of 7...done 458s Segment #5 (chr 2, tcnId=1, dhId=1) of 7... 458s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 458s 5 2 1 1 554484 143663981 1880 1.391608 765 458s tcnNbrOfHets dhNbrOfLoci dhStart dhEnd dhMean c1Mean c2Mean 458s 5 765 765 554484 143663981 0.4206323 0.4031263 0.9884817 458s Number of TCNs: 1880 458s Number of DHs: 765 458s int [1:1880] 3663 3664 3665 3666 3667 3668 3669 3670 3671 3672 ... 458s int [1:7324] 1 2 3 4 5 6 7 8 9 10 ... 458s int [1:1880] 3663 3664 3665 3666 3667 3668 3669 3670 3671 3672 ... 458s Identify loci used to bootstrap DH means... 458s Heterozygous SNPs to resample for DH: 458s int [1:765] 3664 3665 3666 3667 3668 3670 3671 3672 3673 3674 ... 458s Identify loci used to bootstrap DH means...done 458s Identify loci used to bootstrap TCN means... 458s SNPs: 458s int [1:765] 3664 3665 3666 3667 3668 3670 3671 3672 3673 3674 ... 458s Non-polymorphic loci: 458s int [1:1115] 3663 3669 3677 3690 3692 3694 3696 3697 3698 3699 ... 458s Heterozygous SNPs to resample for TCN: 458s int [1:765] 3664 3665 3666 3667 3668 3670 3671 3672 3673 3674 ... 458s Homozygous SNPs to resample for TCN: 458s int(0) 458s Non-polymorphic loci to resample for TCN: 458s int [1:1115] 3663 3669 3677 3690 3692 3694 3696 3697 3698 3699 ... 458s Heterozygous SNPs with non-DH to resample for TCN: 458s int(0) 458s Loci to resample for TCN: 458s int [1:1880] 3663 3664 3665 3666 3667 3668 3669 3670 3671 3672 ... 458s Identify loci used to bootstrap TCN means...done 458s Number of (#hets, #homs, #nonSNPs): (765,0,1115) 458s Bootstrapping while preserving (#hets, #homs, #nonSNPs)... 458s Number of bootstrap samples: 100 458s Bootstrapping while preserving (#hets, #homs, #nonSNPs)...done 458s Segment #5 (chr 2, tcnId=1, dhId=1) of 7...done 458s Segment #6 (chr 2, tcnId=2, dhId=1) of 7... 458s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 458s 6 2 2 1 143663981 185240536 671 2.092452 272 458s tcnNbrOfHets dhNbrOfLoci dhStart dhEnd dhMean c1Mean c2Mean 458s 6 272 272 143663981 185240536 0.1762428 0.861836 1.230616 458s Number of TCNs: 671 458s Number of DHs: 272 458s int [1:671] 5543 5544 5545 5546 5547 5548 5549 5550 5551 5552 ... 458s int [1:7324] 1 2 3 4 5 6 7 8 9 10 ... 458s int [1:671] 5543 5544 5545 5546 5547 5548 5549 5550 5551 5552 ... 458s Identify loci used to bootstrap DH means... 458s Heterozygous SNPs to resample for DH: 458s int [1:272] 5550 5555 5556 5557 5558 5559 5563 5565 5569 5570 ... 458s Identify loci used to bootstrap DH means...done 458s Identify loci used to bootstrap TCN means... 458s SNPs: 458s int [1:272] 5550 5555 5556 5557 5558 5559 5563 5565 5569 5570 ... 458s Non-polymorphic loci: 458s int [1:399] 5543 5544 5545 5546 5547 5548 5549 5551 5552 5553 ... 458s Heterozygous SNPs to resample for TCN: 458s int [1:272] 5550 5555 5556 5557 5558 5559 5563 5565 5569 5570 ... 458s Homozygous SNPs to resample for TCN: 458s int(0) 458s Non-polymorphic loci to resample for TCN: 458s int [1:399] 5543 5544 5545 5546 5547 5548 5549 5551 5552 5553 ... 458s Heterozygous SNPs with non-DH to resample for TCN: 458s int(0) 458s Loci to resample for TCN: 458s int [1:671] 5543 5544 5545 5546 5547 5548 5549 5550 5551 5552 ... 458s Identify loci used to bootstrap TCN means...done 458s Number of (#hets, #homs, #nonSNPs): (272,0,399) 458s Bootstrapping while preserving (#hets, #homs, #nonSNPs)... 458s Number of bootstrap samples: 100 458s Bootstrapping while preserving (#hets, #homs, #nonSNPs)...done 458s Segment #6 (chr 2, tcnId=2, dhId=1) of 7...done 458s Segment #7 (chr 2, tcnId=3, dhId=1) of 7... 458s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 458s 7 2 3 1 185240536 246679946 1111 2.654512 414 458s tcnNbrOfHets dhNbrOfLoci dhStart dhEnd dhMean c1Mean c2Mean 458s 7 414 414 185240536 246679946 0.269742 0.9692395 1.685273 458s Number of TCNs: 1111 458s Number of DHs: 414 458s int [1:1111] 6214 6215 6216 6217 6218 6219 6220 6221 6222 6223 ... 458s int [1:7324] 1 2 3 4 5 6 7 8 9 10 ... 458s int [1:1111] 6214 6215 6216 6217 6218 6219 6220 6221 6222 6223 ... 458s Identify loci used to bootstrap DH means... 458s Heterozygous SNPs to resample for DH: 458s int [1:414] 6215 6216 6223 6224 6225 6230 6231 6234 6235 6236 ... 458s Identify loci used to bootstrap DH means...done 458s Identify loci used to bootstrap TCN means... 458s SNPs: 458s int [1:414] 6215 6216 6223 6224 6225 6230 6231 6234 6235 6236 ... 458s Non-polymorphic loci: 458s int [1:697] 6214 6217 6218 6219 6220 6221 6222 6226 6227 6228 ... 458s Heterozygous SNPs to resample for TCN: 458s int [1:414] 6215 6216 6223 6224 6225 6230 6231 6234 6235 6236 ... 458s Homozygous SNPs to resample for TCN: 458s int(0) 458s Non-polymorphic loci to resample for TCN: 458s int [1:697] 6214 6217 6218 6219 6220 6221 6222 6226 6227 6228 ... 458s Heterozygous SNPs with non-DH to resample for TCN: 458s int(0) 458s Loci to resample for TCN: 458s int [1:1111] 6214 6215 6216 6217 6218 6219 6220 6221 6222 6223 ... 458s Identify loci used to bootstrap TCN means...done 458s Number of (#hets, #homs, #nonSNPs): (414,0,697) 458s Bootstrapping while preserving (#hets, #homs, #nonSNPs)... 458s Number of bootstrap samples: 100 458s Bootstrapping while preserving (#hets, #homs, #nonSNPs)...done 458s Segment #7 (chr 2, tcnId=3, dhId=1) of 7...done 458s Bootstrapped segment mean levels 458s num [1:7, 1:100, 1:4] 1.4 2.09 2.64 NA 1.39 ... 458s - attr(*, "dimnames")=List of 3 458s ..$ : NULL 458s ..$ : NULL 458s ..$ : chr [1:4] "tcn" "dh" "c1" "c2" 458s Calculating (C1,C2) mean levels from (TCN,DH) mean levels... 458s num [1:7, 1:100, 1:4] 1.4 2.09 2.64 NA 1.39 ... 458s - attr(*, "dimnames")=List of 3 458s ..$ : NULL 458s ..$ : NULL 458s ..$ : chr [1:4] "tcn" "dh" "c1" "c2" 458s Calculating (C1,C2) mean levels from (TCN,DH) mean levels...done 458s Calculating polar (alpha,radius,manhattan) for change points... 458s num [1:6, 1:100, 1:2] -0.448 -0.131 NA NA -0.477 ... 458s - attr(*, "dimnames")=List of 3 458s ..$ : NULL 458s ..$ : NULL 458s ..$ : chr [1:2] "c1" "c2" 458s Bootstrapped change points 458s num [1:6, 1:100, 1:5] -2.65 -1.87 NA NA -2.72 ... 458s - attr(*, "dimnames")=List of 3 458s ..$ : NULL 458s ..$ : NULL 458s ..$ : chr [1:5] "alpha" "radius" "manhattan" "d1" ... 458s Calculating polar (alpha,radius,manhattan) for change points...done 458s Bootstrapping (TCN,DH,C1,C2) segment mean levels...done 458s Summarizing bootstrapped segment ('tcn', 'dh', 'c1', 'c2') data... 458s num [1:7, 1:4, 1:4] NA NA NA NA NA NA NA NA NA NA ... 458s - attr(*, "dimnames")=List of 3 458s ..$ : NULL 458s ..$ : chr [1:4] "2.5%" "5%" "95%" "97.5%" 458s ..$ : chr [1:4] "tcn" "dh" "c1" "c2" 458s Field #1 ('tcn') of 4... 458s Segment #1 of 7... 458s Segment #1 of 7...done 458s Segment #2 of 7... 458s Segment #2 of 7...done 458s Segment #3 of 7... 458s Segment #3 of 7...done 458s Segment #4 of 7... 458s Segment #4 of 7...done 458s Segment #5 of 7... 458s Segment #5 of 7...done 458s Segment #6 of 7... 458s Segment #6 of 7...done 458s Segment #7 of 7... 458s Segment #7 of 7...done 458s Field #1 ('tcn') of 4...done 458s Field #2 ('dh') of 4... 458s Segment #1 of 7... 458s Segment #1 of 7...done 458s Segment #2 of 7... 458s Segment #2 of 7...done 458s Segment #3 of 7... 458s Segment #3 of 7...done 458s Segment #4 of 7... 458s Segment #4 of 7...done 458s Segment #5 of 7... 458s Segment #5 of 7...done 458s Segment #6 of 7... 458s Segment #6 of 7...done 458s Segment #7 of 7... 458s Segment #7 of 7...done 458s Field #2 ('dh') of 4...done 458s Field #3 ('c1') of 4... 458s Segment #1 of 7... 458s Segment #1 of 7...done 458s Segment #2 of 7... 458s Segment #2 of 7...done 458s Segment #3 of 7... 458s Segment #3 of 7...done 458s Segment #4 of 7... 458s Segment #4 of 7...done 458s Segment #5 of 7... 458s Segment #5 of 7...done 458s Segment #6 of 7... 458s Segment #6 of 7...done 458s Segment #7 of 7... 458s Segment #7 of 7...done 458s Field #3 ('c1') of 4...done 458s Field #4 ('c2') of 4... 458s Segment #1 of 7... 458s Segment #1 of 7...done 458s Segment #2 of 7... 458s Segment #2 of 7...done 458s Segment #3 of 7... 458s Segment #3 of 7...done 458s Segment #4 of 7... 458s Segment #4 of 7...done 458s Segment #5 of 7... 458s Segment #5 of 7...done 458s Segment #6 of 7... 458s Segment #6 of 7...done 458s Segment #7 of 7... 458s Segment #7 of 7...done 458s Field #4 ('c2') of 4...done 458s Bootstrap statistics 458s num [1:7, 1:4, 1:4] 1.38 2.07 2.63 NA 1.38 ... 458s - attr(*, "dimnames")=List of 3 458s ..$ : NULL 458s ..$ : chr [1:4] "2.5%" "5%" "95%" "97.5%" 458s ..$ : chr [1:4] "tcn" "dh" "c1" "c2" 458s Statistical sanity checks (iff B >= 100)... 458s Available summaries: 2.5%, 5%, 95%, 97.5% 458s Available quantiles: 0.025, 0.05, 0.95, 0.975 458s num [1:7, 1:4, 1:4] 1.38 2.07 2.63 NA 1.38 ... 458s - attr(*, "dimnames")=List of 3 458s ..$ : NULL 458s ..$ : chr [1:4] "2.5%" "5%" "95%" "97.5%" 458s ..$ : chr [1:4] "tcn" "dh" "c1" "c2" 458s Field #1 ('tcn') of 4... 458s Seg 1. mean=1.39161, range=[1.38025,1.40693], n=1880 458s Seg 2. mean=2.09245, range=[2.06856,2.1165], n=671 458s Seg 3. mean=2.65451, range=[2.62678,2.6834], n=1111 458s Seg 4. mean=NA, range=[NA,NA], n=NA 458s Seg 5. mean=1.39161, range=[1.37999,1.40474], n=1880 458s Seg 6. mean=2.09245, range=[2.06923,2.11747], n=671 458s Seg 7. mean=2.65451, range=[2.62867,2.68639], n=1111 458s Field #1 ('tcn') of 4...done 458s Field #2 ('dh') of 4... 458s Seg 1. mean=0.420632, range=[0.406983,0.437756], n=765 458s Seg 2. mean=0.176243, range=[0.141232,0.202975], n=272 458s Seg 3. mean=0.269742, range=[0.245337,0.292784], n=414 458s Seg 4. mean=NA, range=[NA,NA], n=NA 458s Seg 5. mean=0.420632, range=[0.406204,0.436189], n=765 458s Seg 6. mean=0.176243, range=[0.13696,0.212132], n=272 458s Seg 7. mean=0.269742, range=[0.230034,0.296763], n=414 458s Field #2 ('dh') of 4...done 458s Field #3 ('c1') of 4... 458s Seg 1. mean=0.403126, range=[0.391189,0.413437], n=765 458s Seg 2. mean=0.861836, range=[0.833296,0.900874], n=272 458s Seg 3. mean=0.969239, range=[0.937437,1.00659], n=414 458s Seg 4. mean=NA, range=[NA,NA], n=NA 458s Seg 5. mean=0.403126, range=[0.392112,0.414529], n=765 458s Seg 6. mean=0.861836, range=[0.823193,0.907577], n=272 458s Seg 7. mean=0.969239, range=[0.931951,1.01968], n=414 458s Field #3 ('c1') of 4...done 458s Field #4 ('c2') of 4... 458s Seg 1. mean=0.988482, range=[0.974501,1.00244], n=765 458s Seg 2. mean=1.23062, range=[1.18964,1.26157], n=272 458s Seg 3. mean=1.68527, range=[1.6481,1.72497], n=414 458s Seg 4. mean=NA, range=[NA,NA], n=NA 458s Seg 5. mean=0.988482, range=[0.9761,1.00076], n=765 458s Seg 6. mean=1.23062, range=[1.18936,1.26647], n=272 458s Seg 7. mean=1.68527, range=[1.63171,1.72526], n=414 458s Field #4 ('c2') of 4...done 458s Statistical sanity checks (iff B >= 100)...done 458s Summarizing bootstrapped segment ('tcn', 'dh', 'c1', 'c2') data...done 458s Summarizing bootstrapped changepoint ('alpha', 'radius', 'manhattan', 'd1', 'd2') data... 458s num [1:6, 1:4, 1:5] NA NA NA NA NA NA NA NA NA NA ... 458s - attr(*, "dimnames")=List of 3 458s ..$ : NULL 458s ..$ : chr [1:4] "2.5%" "5%" "95%" "97.5%" 458s ..$ : chr [1:5] "alpha" "radius" "manhattan" "d1" ... 458s Field #1 ('alpha') of 5... 458s Changepoint #1 of 6... 458s Changepoint #1 of 6...done 458s Changepoint #2 of 6... 458s Changepoint #2 of 6...done 458s Changepoint #3 of 6... 458s Changepoint #3 of 6...done 458s Changepoint #4 of 6... 458s Changepoint #4 of 6...done 458s Changepoint #5 of 6... 458s Changepoint #5 of 6...done 458s Changepoint #6 of 6... 458s Changepoint #6 of 6...done 458s Field #1 ('alpha') of 5...done 458s Field #2 ('radius') of 5... 458s Changepoint #1 of 6... 458s Changepoint #1 of 6...done 458s Changepoint #2 of 6... 458s Changepoint #2 of 6...done 458s Changepoint #3 of 6... 458s Changepoint #3 of 6...done 458s Changepoint #4 of 6... 458s Changepoint #4 of 6...done 458s Changepoint #5 of 6... 458s Changepoint #5 of 6...done 458s Changepoint #6 of 6... 458s Changepoint #6 of 6...done 458s Field #2 ('radius') of 5...done 458s Field #3 ('manhattan') of 5... 458s Changepoint #1 of 6... 458s Changepoint #1 of 6...done 458s Changepoint #2 of 6... 458s Changepoint #2 of 6...done 458s Changepoint #3 of 6... 458s Changepoint #3 of 6...done 458s Changepoint #4 of 6... 458s Changepoint #4 of 6...done 458s Changepoint #5 of 6... 458s Changepoint #5 of 6...done 458s Changepoint #6 of 6... 458s Changepoint #6 of 6...done 458s Field #3 ('manhattan') of 5...done 458s Field #4 ('d1') of 5... 458s Changepoint #1 of 6... 458s Changepoint #1 of 6...done 458s Changepoint #2 of 6... 458s Changepoint #2 of 6...done 458s Changepoint #3 of 6... 458s Changepoint #3 of 6...done 458s Changepoint #4 of 6... 458s Changepoint #4 of 6...done 458s Changepoint #5 of 6... 458s Changepoint #5 of 6...done 458s Changepoint #6 of 6... 458s Changepoint #6 of 6...done 458s Field #4 ('d1') of 5...done 458s Field #5 ('d2') of 5... 458s Changepoint #1 of 6... 458s Changepoint #1 of 6...done 458s Changepoint #2 of 6... 458s Changepoint #2 of 6...done 458s Changepoint #3 of 6... 458s Changepoint #3 of 6...done 458s Changepoint #4 of 6... 458s Changepoint #4 of 6...done 458s Changepoint #5 of 6... 458s Changepoint #5 of 6...done 458s Changepoint #6 of 6... 458s Changepoint #6 of 6...done 458s Field #5 ('d2') of 5...done 458s Bootstrap statistics 458s num [1:6, 1:4, 1:5] -2.76 -1.91 NA NA -2.76 ... 458s - attr(*, "dimnames")=List of 3 458s ..$ : NULL 458s ..$ : chr [1:4] "2.5%" "5%" "95%" "97.5%" 458s ..$ : chr [1:5] "alpha" "radius" "manhattan" "d1" ... 458s Summarizing bootstrapped changepoint ('alpha', 'radius', 'manhattan', 'd1', 'd2') data...done 458s Resample (TCN,DH) signals and re-estimate summaries for segment & changepoint...done 458s > print(fit) 458s chromosome tcnId dhId start end tcnNbrOfLoci tcnMean tcnNbrOfSNPs 458s 1 1 1 1 554484 143663981 1880 1.391608 765 458s 2 1 2 1 143663981 185240536 671 2.092452 272 458s 3 1 3 1 185240536 246679946 1111 2.654512 414 458s 4 NA NA NA NA NA NA NA NA 458s 5 2 1 1 554484 143663981 1880 1.391608 765 458s 6 2 2 1 143663981 185240536 671 2.092452 272 458s 7 2 3 1 185240536 246679946 1111 2.654512 414 458s tcnNbrOfHets dhNbrOfLoci dhMean c1Mean c2Mean 458s 1 765 765 0.4206323 0.4031263 0.9884817 458s 2 272 272 0.1762428 0.8618360 1.2306156 458s 3 414 414 0.2697420 0.9692395 1.6852728 458s 4 NA NA NA NA NA 458s 5 765 765 0.4206323 0.4031263 0.9884817 458s 6 272 272 0.1762428 0.8618360 1.2306156 458s 7 414 414 0.2697420 0.9692395 1.6852728 458s > 458s > 458s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 458s > # Calling segments in allelic balance (AB) 458s > # NOTE: Ideally, this should be done on whole-genome data 458s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 458s > # Explicitly estimate the threshold in DH for calling AB 458s > # (which be done by default by the caller, if skipped here) 458s > deltaAB <- estimateDeltaAB(fit, flavor="qq(DH)", verbose=-10) 458s Estimating DH threshold for calling allelic imbalances... 458s flavor: qq(DH) 458s scale: 1 458s Estimating DH threshold for AB caller... 458s quantile #1: 0.05 458s Symmetric quantile #2: 0.9 458s Number of segments: 6 458s Weighted 5% quantile of DH: 0.199618 458s Number of segments with small DH: 2 458s Number of data points: 1342 458s Number of finite data points: 544 458s Estimate of (1-0.9):th and 50% quantiles: (0.0289919,0.176243) 458s Estimate of 0.9:th "symmetric" quantile: 0.323494 458s Estimating DH threshold for AB caller...done 458s Estimated delta: 0.323 458s Estimating DH threshold for calling allelic imbalances...done 458s > print(deltaAB) 458s [1] 0.3234938 458s > 458s > fit <- callAB(fit, delta=deltaAB, verbose=-10) 458s Calling segments of allelic balance from one-sided DH bootstrap confidence intervals... 458s delta (offset adjusting for bias in DH): 0.323493772175137 458s alpha (CI quantile; significance level): 0.05 458s Calling segments... 458s Number of segments called allelic balance (AB): 4 (57.14%) of 7 458s Calling segments...done 458s Calling segments of allelic balance from one-sided DH bootstrap confidence intervals...done 458s > print(fit) 458s chromosome tcnId dhId start end tcnNbrOfLoci tcnMean tcnNbrOfSNPs 458s 1 1 1 1 554484 143663981 1880 1.391608 765 458s 2 1 2 1 143663981 185240536 671 2.092452 272 458s 3 1 3 1 185240536 246679946 1111 2.654512 414 458s 4 NA NA NA NA NA NA NA NA 458s 5 2 1 1 554484 143663981 1880 1.391608 765 458s 6 2 2 1 143663981 185240536 671 2.092452 272 458s 7 2 3 1 185240536 246679946 1111 2.654512 414 458s tcnNbrOfHets dhNbrOfLoci dhMean c1Mean c2Mean abCall 458s 1 765 765 0.4206323 0.4031263 0.9884817 FALSE 458s 2 272 272 0.1762428 0.8618360 1.2306156 TRUE 458s 3 414 414 0.2697420 0.9692395 1.6852728 TRUE 458s 4 NA NA NA NA NA NA 458s 5 765 765 0.4206323 0.4031263 0.9884817 FALSE 458s 6 272 272 0.1762428 0.8618360 1.2306156 TRUE 458s 7 414 414 0.2697420 0.9692395 1.6852728 TRUE 458s > 458s > 458s > # Even if not explicitly specified, the estimated 458s > # threshold parameter is returned by the caller 458s > stopifnot(fit$params$deltaAB == deltaAB) 458s > 458s > 458s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 458s > # Calling segments in loss-of-heterozygosity (LOH) 458s > # NOTE: Ideally, this should be done on whole-genome data 458s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 458s > # Explicitly estimate the threshold in C1 for calling LOH 458s > # (which be done by default by the caller, if skipped here) 458s > deltaLOH <- estimateDeltaLOH(fit, flavor="minC1|nonAB", verbose=-10) 458s Estimating DH threshold for calling LOH... 458s flavor: minC1|nonAB 458s Estimating DH threshold for calling LOH as the midpoint between guessed C1=0 and C1=1... 458s Argument 'midpoint': 0.5 458s Number of segments: 6 458s Number of segments in allelic balance: 4 (66.7%) of 6 458s Number of segments not in allelic balance: 2 (33.3%) of 6 458s Number of segments in allelic balance and TCN <= 3.00: 4 (66.7%) of 6 458s C: 2.09, 2.65, 2.09, 2.65 458s Corrected C1 (=C/2): 1.05, 1.33, 1.05, 1.33 458s Number of DHs: 272, 414, 272, 414 458s Weights: 0.198, 0.302, 0.198, 0.302 458s Weighted median of (corrected) C1 in allelic balance: 1.274 458s Smallest C1 among segments not in allelic balance: 0.403 458s There are 2 segments with in total 765 heterozygous SNPs with this level. 458s There are 2 segments with in total 765 heterozygous SNPs with this level. 458s Midpoint between the two: 0.839 458s Estimating DH threshold for calling LOH as the midpoint between guessed C1=0 and C1=1...done 458s delta: 0.839 458s Estimating DH threshold for calling LOH...done 458s > print(deltaLOH) 458s [1] 0.838563 458s > 458s > fit <- callLOH(fit, delta=deltaLOH, verbose=-10) 458s Calling segments of allelic balance from one-sided DH bootstrap confidence intervals... 458s delta (offset adjusting for bias in C1): 0.838562992888546 458s alpha (CI quantile; significance level): 0.05 458s Calling segments... 458s Number of segments called low C1 (LowC1, "LOH_C1"): 3 (42.86%) of 7 458s Calling segments...done 458s Calling segments of allelic balance from one-sided DH bootstrap confidence intervals...done 458s > print(fit) 458s chromosome tcnId dhId start end tcnNbrOfLoci tcnMean tcnNbrOfSNPs 458s 1 1 1 1 554484 143663981 1880 1.391608 765 458s 2 1 2 1 143663981 185240536 671 2.092452 272 458s 3 1 3 1 185240536 246679946 1111 2.654512 414 458s 4 NA NA NA NA NA NA NA NA 458s 5 2 1 1 554484 143663981 1880 1.391608 765 458s 6 2 2 1 143663981 185240536 671 2.092452 272 458s 7 2 3 1 185240536 246679946 1111 2.654512 414 458s tcnNbrOfHets dhNbrOfLoci dhMean c1Mean c2Mean abCall lohCall 458s 1 765 765 0.4206323 0.4031263 0.9884817 FALSE TRUE 458s 2 272 272 0.1762428 0.8618360 1.2306156 TRUE NA 458s 3 414 414 0.2697420 0.9692395 1.6852728 TRUE FALSE 458s 4 NA NA NA NA NA NA NA 458s 5 765 765 0.4206323 0.4031263 0.9884817 FALSE TRUE 458s 6 272 272 0.1762428 0.8618360 1.2306156 TRUE FALSE 458s 7 414 414 0.2697420 0.9692395 1.6852728 TRUE FALSE 458s > plotTracks(fit) 458s > 458s > # Even if not explicitly specified, the estimated 458s > # threshold parameter is returned by the caller 458s > stopifnot(fit$params$deltaLOH == deltaLOH) 458s > 458s > proc.time() 458s user system elapsed 458s 1.619 0.121 1.730 458s Test segmentByNonPairedPSCBS,medianDH passed 458s 0 458s Begin test segmentByPairedPSCBS,DH 461s + cat segmentByPairedPSCBS,DH.Rout 461s + [ 0 != 0 ] 461s + echo Test segmentByPairedPSCBS,DH passed 461s + echo 0 461s + echo Begin test segmentByPairedPSCBS,calls 461s + exitcode=0 461s + R CMD BATCH segmentByPairedPSCBS,calls.R 461s 461s R version 4.3.2 (2023-10-31) -- "Eye Holes" 461s Copyright (C) 2023 The R Foundation for Statistical Computing 461s Platform: x86_64-pc-linux-gnu (64-bit) 461s 461s R is free software and comes with ABSOLUTELY NO WARRANTY. 461s You are welcome to redistribute it under certain conditions. 461s Type 'license()' or 'licence()' for distribution details. 461s 461s R is a collaborative project with many contributors. 461s Type 'contributors()' for more information and 461s 'citation()' on how to cite R or R packages in publications. 461s 461s Type 'demo()' for some demos, 'help()' for on-line help, or 461s 'help.start()' for an HTML browser interface to help. 461s Type 'q()' to quit R. 461s 461s [Previously saved workspace restored] 461s 461s > library("PSCBS") 461s PSCBS v0.66.0 (2021-10-23 07:40:02 UTC) successfully loaded. See ?PSCBS for help. 461s 461s Attaching package: 'PSCBS' 461s 461s The following objects are masked from 'package:base': 461s 461s append, load 461s 461s > 461s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 461s > # Load SNP microarray data 461s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 461s > data <- PSCBS::exampleData("paired.chr01") 461s > str(data) 461s 'data.frame': 73346 obs. of 6 variables: 461s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 461s $ x : int 1145994 2224111 2319424 2543484 2926730 2941694 3084986 3155127 3292731 3695086 ... 461s $ CT : num 1.625 1.071 1.406 1.18 0.856 ... 461s $ betaT : num 0.757 0.771 0.834 0.778 0.229 ... 461s $ CN : num 2.36 2.13 2.59 1.93 1.71 ... 461s $ betaN : num 0.827 0.875 0.887 0.884 0.103 ... 461s > 461s > # Drop single-locus outliers 461s > dataS <- dropSegmentationOutliers(data) 461s > 461s > # Run light-weight tests 461s > # Use only every 5th data point 461s > dataS <- dataS[seq(from=1, to=nrow(data), by=5),] 461s > # Number of segments (for assertion) 461s > nSegs <- 3L 461s > # Number of bootstrap samples (see below) 461s > B <- 100L 461s > 461s > str(dataS) 461s 'data.frame': 14670 obs. of 6 variables: 461s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 461s $ x : int 1145994 2941694 3710825 4240737 4276892 4464544 4714611 5095111 5034491 5158416 ... 461s $ CT : num 1.63 1.4 1.41 1.17 1.16 ... 461s $ betaT : num 0.7574 0.169 0.2357 0.2604 0.0576 ... 461s $ CN : num 2.36 2.13 2.26 2.01 2.32 ... 461s $ betaN : num 0.8274 0.5072 0.1671 0.1609 0.0421 ... 461s > R.oo::attachLocally(dataS) 461s > 461s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 461s > # Calculate DH 461s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 461s > muN <- aroma.light::callNaiveGenotypes(betaN, censorAt=c(0,1)) 461s > # SNPs are identifies as those loci that have non-missing 'betaT' & 'muN' 461s > isSnp <- (!is.na(betaT) & !is.na(muN)) 461s > isHet <- isSnp & (muN == 1/2) 461s > rho <- rep(NA_real_, length=length(muN)) 461s > rho[isHet] <- 2*abs(betaT[isHet]-1/2) 461s > 461s > 461s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 461s > # Paired PSCBS segmentation using TCN and DH only 461s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 461s > fit <- segmentByPairedPSCBS(CT, rho=rho, 461s + chromosome=chromosome, x=x, 461s + seed=0xBEEF, verbose=-10) 461s Segmenting paired tumor-normal signals using Paired PSCBS... 461s Setup up data... 461s 'data.frame': 14670 obs. of 4 variables: 461s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 461s $ x : num 1145994 2941694 3710825 4240737 4276892 ... 461s $ CT : num 1.63 1.4 1.41 1.17 1.16 ... 461s $ rho : num NA 0.662 NA NA NA ... 461s Setup up data...done 461s Dropping loci for which TCNs are missing... 461s Number of loci dropped: 12 461s Dropping loci for which TCNs are missing...done 461s Ordering data along genome... 461s 'data.frame': 14658 obs. of 4 variables: 461s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 461s $ x : num 554484 730720 782343 878522 916294 ... 461s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 461s $ rho : num NA NA NA NA NA ... 461s Ordering data along genome...done 461s Keeping only current chromosome for 'knownSegments'... 461s Chromosome: 1 461s Known segments for this chromosome: 461s [1] chromosome start end 461s <0 rows> (or 0-length row.names) 461s Keeping only current chromosome for 'knownSegments'...done 461s alphaTCN: 0.009 461s alphaDH: 0.001 461s Number of loci: 14658 461s Random seed temporarily set (seed=c(48879), kind="L'Ecuyer-CMRG") 461s Produced 2 seeds from this stream for future usage 461s Identification of change points by total copy numbers... 461s Segmenting by CBS... 461s Chromosome: 1 461s Random seed temporarily set (seed=c(10407, 1066287653, -51199871, 161854402, -1995183193, 1503453565, -747102133), kind="L'Ecuyer-CMRG") 461s Segmenting by CBS...done 461s List of 4 461s $ data :'data.frame': 14658 obs. of 4 variables: 461s ..$ chromosome: int [1:14658] 1 1 1 1 1 1 1 1 1 1 ... 461s ..$ x : num [1:14658] 554484 730720 782343 878522 916294 ... 461s ..$ y : num [1:14658] 1.88 1.8 1.59 1.64 1.53 ... 461s ..$ index : int [1:14658] 1 2 3 4 5 6 7 8 9 10 ... 461s $ output :'data.frame': 3 obs. of 6 variables: 461s ..$ sampleName: chr [1:3] NA NA NA 461s ..$ chromosome: int [1:3] 1 1 1 461s ..$ start : num [1:3] 5.54e+05 1.44e+08 1.85e+08 461s ..$ end : num [1:3] 1.44e+08 1.85e+08 2.47e+08 461s ..$ nbrOfLoci : int [1:3] 7599 2668 4391 461s ..$ mean : num [1:3] 1.39 2.07 2.63 461s $ segRows:'data.frame': 3 obs. of 2 variables: 461s ..$ startRow: int [1:3] 1 7600 10268 461s ..$ endRow : int [1:3] 7599 10267 14658 461s $ params :List of 5 461s ..$ alpha : num 0.009 461s ..$ undo : num 0 461s ..$ joinSegments : logi TRUE 461s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 461s .. ..$ chromosome: int 1 461s .. ..$ start : num -Inf 461s .. ..$ end : num Inf 461s ..$ seed : int [1:7] 10407 1066287653 -51199871 161854402 -1995183193 1503453565 -747102133 461s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 461s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.406 0 0.406 0 0 461s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 461s - attr(*, "pkgDetails")= chr "DNAcopy v1.76.0" 461s - attr(*, "randomSeed")= int [1:7] 10407 1066287653 -51199871 161854402 -1995183193 1503453565 -747102133 461s Identification of change points by total copy numbers...done 461s Restructure TCN segmentation results... 461s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean 461s 1 1 554484 143926517 7599 1.3859 461s 2 1 143926517 185449813 2668 2.0704 461s 3 1 185449813 247137334 4391 2.6341 461s Number of TCN segments: 3 461s Restructure TCN segmentation results...done 461s Total CN segment #1 ([ 554484,1.43927e+08]) of 3... 461s Number of TCN loci in segment: 7599 461s Locus data for TCN segment: 461s 'data.frame': 7599 obs. of 5 variables: 461s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 461s $ x : num 554484 730720 782343 878522 916294 ... 461s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 461s $ rho : num NA NA NA NA NA ... 461s $ index : int 1 2 3 4 5 6 7 8 9 10 ... 461s Number of loci: 7599 461s Number of SNPs: 2111 (27.78%) 461s Number of heterozygous SNPs: 2111 (100.00%) 461s Chromosome: 1 461s Segmenting DH signals... 461s Segmenting by CBS... 461s Chromosome: 1 461s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 461s Segmenting by CBS...done 461s List of 4 461s $ data :'data.frame': 7599 obs. of 4 variables: 461s ..$ chromosome: int [1:7599] 1 1 1 1 1 1 1 1 1 1 ... 461s ..$ x : num [1:7599] 554484 730720 782343 878522 916294 ... 461s ..$ y : num [1:7599] NA NA NA NA NA ... 461s ..$ index : int [1:7599] 1 2 3 4 5 6 7 8 9 10 ... 461s $ output :'data.frame': 1 obs. of 6 variables: 461s ..$ sampleName: chr NA 461s ..$ chromosome: int 1 461s ..$ start : num 554484 461s ..$ end : num 1.44e+08 461s ..$ nbrOfLoci : int 2111 461s ..$ mean : num 0.524 461s $ segRows:'data.frame': 1 obs. of 2 variables: 461s ..$ startRow: int 10 461s ..$ endRow : int 7594 461s $ params :List of 5 461s ..$ alpha : num 0.001 461s ..$ undo : num 0 461s ..$ joinSegments : logi TRUE 461s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 461s .. ..$ chromosome: int 1 461s .. ..$ start : num 554484 461s .. ..$ end : num 1.44e+08 461s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 461s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 461s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.024 0 0.024 0 0 461s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 461s - attr(*, "pkgDetails")= chr "DNAcopy v1.76.0" 461s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 461s DH segmentation (locally-indexed) rows: 461s startRow endRow 461s 1 10 7594 461s int [1:7599] 1 2 3 4 5 6 7 8 9 10 ... 461s DH segmentation rows: 461s startRow endRow 461s 1 10 7594 461s Segmenting DH signals...done 461s DH segmentation table: 461s dhStart dhEnd dhNbrOfLoci dhMean 461s 1 554484 143926517 2111 0.5237 461s startRow endRow 461s 1 10 7594 461s Rows: 461s [1] 1 461s TCN segmentation rows: 461s startRow endRow 461s 1 1 7599 461s TCN and DH segmentation rows: 461s startRow endRow 461s 1 1 7599 461s startRow endRow 461s 1 10 7594 461s NULL 461s TCN segmentation (expanded) rows: 461s startRow endRow 461s 1 1 7599 461s TCN and DH segmentation rows: 461s startRow endRow 461s 1 1 7599 461s 2 7600 10267 461s 3 10268 14658 461s startRow endRow 461s 1 10 7594 461s startRow endRow 461s 1 1 7599 461s Total CN segmentation table (expanded): 461s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 461s 1 1 554484 143926517 7599 1.3859 2111 2111 461s (TCN,DH) segmentation for one total CN segment: 461s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 461s 1 1 1 1 554484 143926517 7599 1.3859 2111 461s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 461s 1 2111 554484 143926517 2111 0.5237 461s Total CN segment #1 ([ 554484,1.43927e+08]) of 3...done 461s Total CN segment #2 ([1.43927e+08,1.8545e+08]) of 3... 461s Number of TCN loci in segment: 2668 461s Locus data for TCN segment: 461s 'data.frame': 2668 obs. of 5 variables: 461s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 461s $ x : num 1.44e+08 1.44e+08 1.44e+08 1.44e+08 1.44e+08 ... 461s $ CT : num 2.1 2.1 2.09 1.8 2.34 ... 461s $ rho : num NA NA NA NA NA NA NA NA NA NA ... 461s $ index : int 7600 7601 7602 7603 7604 7605 7606 7607 7608 7609 ... 461s Number of loci: 2668 461s Number of SNPs: 774 (29.01%) 461s Number of heterozygous SNPs: 774 (100.00%) 461s Chromosome: 1 461s Segmenting DH signals... 461s Segmenting by CBS... 461s Chromosome: 1 461s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 461s Segmenting by CBS...done 461s List of 4 461s $ data :'data.frame': 2668 obs. of 4 variables: 461s ..$ chromosome: int [1:2668] 1 1 1 1 1 1 1 1 1 1 ... 461s ..$ x : num [1:2668] 1.44e+08 1.44e+08 1.44e+08 1.44e+08 1.44e+08 ... 461s ..$ y : num [1:2668] NA NA NA NA NA NA NA NA NA NA ... 461s ..$ index : int [1:2668] 1 2 3 4 5 6 7 8 9 10 ... 461s $ output :'data.frame': 1 obs. of 6 variables: 461s ..$ sampleName: chr NA 461s ..$ chromosome: int 1 461s ..$ start : num 1.44e+08 461s ..$ end : num 1.85e+08 461s ..$ nbrOfLoci : int 774 461s ..$ mean : num 0.154 461s $ segRows:'data.frame': 1 obs. of 2 variables: 461s ..$ startRow: int 15 461s ..$ endRow : int 2664 461s $ params :List of 5 461s ..$ alpha : num 0.001 461s ..$ undo : num 0 461s ..$ joinSegments : logi TRUE 461s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 461s .. ..$ chromosome: int 1 461s .. ..$ start : num 1.44e+08 461s .. ..$ end : num 1.85e+08 461s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 461s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 461s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.008 0 0.008 0 0 461s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 461s - attr(*, "pkgDetails")= chr "DNAcopy v1.76.0" 461s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 461s DH segmentation (locally-indexed) rows: 461s startRow endRow 461s 1 15 2664 461s int [1:2668] 7600 7601 7602 7603 7604 7605 7606 7607 7608 7609 ... 461s DH segmentation rows: 461s startRow endRow 461s 1 7614 10263 461s Segmenting DH signals...done 461s DH segmentation table: 461s dhStart dhEnd dhNbrOfLoci dhMean 461s 1 143926517 185449813 774 0.1542 461s startRow endRow 461s 1 7614 10263 461s Rows: 461s [1] 2 461s TCN segmentation rows: 461s startRow endRow 461s 2 7600 10267 461s TCN and DH segmentation rows: 461s startRow endRow 461s 2 7600 10267 461s startRow endRow 461s 1 7614 10263 461s startRow endRow 461s 1 1 7599 461s TCN segmentation (expanded) rows: 461s startRow endRow 461s 1 1 7599 461s 2 7600 10267 461s TCN and DH segmentation rows: 461s startRow endRow 461s 1 1 7599 461s 2 7600 10267 461s 3 10268 14658 461s startRow endRow 461s 1 10 7594 461s 2 7614 10263 461s startRow endRow 461s 1 1 7599 461s 2 7600 10267 461s Total CN segmentation table (expanded): 461s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 461s 2 1 143926517 185449813 2668 2.0704 774 774 461s (TCN,DH) segmentation for one total CN segment: 461s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 461s 2 2 1 1 143926517 185449813 2668 2.0704 774 461s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 461s 2 774 143926517 185449813 774 0.1542 461s Total CN segment #2 ([1.43927e+08,1.8545e+08]) of 3...done 461s Total CN segment #3 ([1.8545e+08,2.47137e+08]) of 3... 461s Number of TCN loci in segment: 4391 461s Locus data for TCN segment: 461s 'data.frame': 4391 obs. of 5 variables: 461s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 461s $ x : num 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 461s $ CT : num 2.93 2.15 2.82 2.93 2.46 ... 461s $ rho : num NA 0.0308 NA 0.2533 NA ... 461s $ index : int 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 461s Number of loci: 4391 461s Number of SNPs: 1311 (29.86%) 461s Number of heterozygous SNPs: 1311 (100.00%) 461s Chromosome: 1 461s Segmenting DH signals... 461s Segmenting by CBS... 461s Chromosome: 1 461s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 461s Segmenting by CBS...done 461s List of 4 461s $ data :'data.frame': 4391 obs. of 4 variables: 461s ..$ chromosome: int [1:4391] 1 1 1 1 1 1 1 1 1 1 ... 461s ..$ x : num [1:4391] 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 461s ..$ y : num [1:4391] NA 0.0308 NA 0.2533 NA ... 461s ..$ index : int [1:4391] 1 2 3 4 5 6 7 8 9 10 ... 461s $ output :'data.frame': 1 obs. of 6 variables: 461s ..$ sampleName: chr NA 461s ..$ chromosome: int 1 461s ..$ start : num 1.85e+08 461s ..$ end : num 2.47e+08 461s ..$ nbrOfLoci : int 1311 461s ..$ mean : num 0.251 461s $ segRows:'data.frame': 1 obs. of 2 variables: 461s ..$ startRow: int 2 461s ..$ endRow : int 4388 461s $ params :List of 5 461s ..$ alpha : num 0.001 461s ..$ undo : num 0 461s ..$ joinSegments : logi TRUE 461s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 461s .. ..$ chromosome: int 1 461s .. ..$ start : num 1.85e+08 461s .. ..$ end : num 2.47e+08 461s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 461s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 461s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.019 0 0.019 0 0 461s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 461s - attr(*, "pkgDetails")= chr "DNAcopy v1.76.0" 461s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 461s DH segmentation (locally-indexed) rows: 461s startRow endRow 461s 1 2 4388 461s int [1:4391] 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 461s DH segmentation rows: 461s startRow endRow 461s 1 10269 14655 461s Segmenting DH signals...done 461s DH segmentation table: 461s dhStart dhEnd dhNbrOfLoci dhMean 461s 1 185449813 247137334 1311 0.2512 461s startRow endRow 461s 1 10269 14655 461s Rows: 461s [1] 3 461s TCN segmentation rows: 461s startRow endRow 461s 3 10268 14658 461s TCN and DH segmentation rows: 461s startRow endRow 461s 3 10268 14658 461s startRow endRow 461s 1 10269 14655 461s startRow endRow 461s 1 1 7599 461s 2 7600 10267 461s TCN segmentation (expanded) rows: 461s startRow endRow 461s 1 1 7599 461s 2 7600 10267 461s 3 10268 14658 461s TCN and DH segmentation rows: 461s startRow endRow 461s 1 1 7599 461s 2 7600 10267 461s 3 10268 14658 461s startRow endRow 461s 1 10 7594 461s 2 7614 10263 461s 3 10269 14655 461s startRow endRow 461s 1 1 7599 461s 2 7600 10267 461s 3 10268 14658 461s Total CN segmentation table (expanded): 461s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 461s 3 1 185449813 247137334 4391 2.6341 1311 1311 461s (TCN,DH) segmentation for one total CN segment: 461s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 461s 3 3 1 1 185449813 247137334 4391 2.6341 1311 461s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 461s 3 1311 185449813 247137334 1311 0.2512 461s Total CN segment #3 ([1.8545e+08,2.47137e+08]) of 3...done 461s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 461s 1 1 1 1 554484 143926517 7599 1.3859 2111 461s 2 1 2 1 143926517 185449813 2668 2.0704 774 461s 3 1 3 1 185449813 247137334 4391 2.6341 1311 461s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 461s 1 2111 554484 143926517 2111 0.5237 461s 2 774 143926517 185449813 774 0.1542 461s 3 1311 185449813 247137334 1311 0.2512 461s Calculating (C1,C2) per segment... 461s Calculating (C1,C2) per segment...done 461s Number of segments: 3 461s Segmenting paired tumor-normal signals using Paired PSCBS...done 461s Post-segmenting TCNs... 461s Number of segments: 3 461s Number of chromosomes: 1 461s [1] 1 461s Chromosome 1 ('chr01') of 1... 461s Rows: 461s [1] 1 2 3 461s Number of segments: 3 461s TCN segment #1 ('1') of 3... 461s Nothing todo. Only one DH segmentation. Skipping. 461s TCN segment #1 ('1') of 3...done 461s TCN segment #2 ('2') of 3... 461s Nothing todo. Only one DH segmentation. Skipping. 461s TCN segment #2 ('2') of 3...done 461s TCN segment #3 ('3') of 3... 461s Nothing todo. Only one DH segmentation. Skipping. 461s TCN segment #3 ('3') of 3...done 461s Chromosome 1 ('chr01') of 1...done 461s Update (C1,C2) per segment... 461s Update (C1,C2) per segment...done 461s Post-segmenting TCNs...done 461s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 461s 1 1 1 1 554484 143926517 7599 1.3859 2111 461s 2 1 2 1 143926517 185449813 2668 2.0704 774 461s 3 1 3 1 185449813 247137334 4391 2.6341 1311 461s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 461s 1 2111 554484 143926517 2111 0.5237 0.3300521 1.055848 461s 2 774 143926517 185449813 774 0.1542 0.8755722 1.194828 461s 3 1311 185449813 247137334 1311 0.2512 0.9862070 1.647893 461s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 461s 1 1 1 1 554484 143926517 7599 1.3859 2111 461s 2 1 2 1 143926517 185449813 2668 2.0704 774 461s 3 1 3 1 185449813 247137334 4391 2.6341 1311 461s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 461s 1 2111 554484 143926517 2111 0.5237 0.3300521 1.055848 461s 2 774 143926517 185449813 774 0.1542 0.8755722 1.194828 461s 3 1311 185449813 247137334 1311 0.2512 0.9862070 1.647893 461s > print(fit) 461s chromosome tcnId dhId start end tcnNbrOfLoci tcnMean tcnNbrOfSNPs 461s 1 1 1 1 554484 143926517 7599 1.3859 2111 461s 2 1 2 1 143926517 185449813 2668 2.0704 774 461s 3 1 3 1 185449813 247137334 4391 2.6341 1311 461s tcnNbrOfHets dhNbrOfLoci dhMean c1Mean c2Mean 461s 1 2111 2111 0.5237 0.3300521 1.055848 461s 2 774 774 0.1542 0.8755722 1.194828 461s 3 1311 1311 0.2512 0.9862070 1.647893 461s > 461s > # Plot results 461s > plotTracks(fit) 461s > 461s > 461s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 461s > # Bootstrap segment level estimates 461s > # (used by the AB caller, which, if skipped here, 461s > # will do it automatically) 461s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 461s > fit <- bootstrapTCNandDHByRegion(fit, B=B, verbose=-10) 461s Resample (TCN,DH) signals and re-estimate summaries for segment & changepoint... 461s Already done? 461s tcn_2.5% tcn_5% tcn_95% tcn_97.5% dh_2.5% dh_5% dh_95% dh_97.5% 461s FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE 461s c1_2.5% c1_5% c1_95% c1_97.5% c2_2.5% c2_5% c2_95% c2_97.5% 461s FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE 461s Bootstrapping (TCN,DH,C1,C2) segment mean levels... 461s Identifying heterozygous & homozygous SNPs and non-polymorphic loci... 461s Number of loci: 14658 461s Number of SNPs: 4196 461s Number of non-SNPs: 10462 461s Identifying heterozygous & homozygous SNPs and non-polymorphic loci...done 461s num [1:3, 1:100, 1:4] NA NA NA NA NA NA NA NA NA NA ... 461s - attr(*, "dimnames")=List of 3 461s ..$ : NULL 461s ..$ : NULL 461s ..$ : chr [1:4] "tcn" "dh" "c1" "c2" 461s Segment #1 (chr 1, tcnId=1, dhId=1) of 3... 461s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 461s 1 1 1 1 554484 143926517 7599 1.3859 2111 461s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 461s 1 2111 554484 143926517 2111 0.5237 0.3300521 1.055848 461s Number of TCNs: 7599 461s Number of DHs: 2111 461s int [1:7599] 1 2 3 4 5 6 7 8 9 10 ... 461s int [1:14658] 1 2 3 4 5 6 7 8 9 10 ... 461s int [1:7599] 1 2 3 4 5 6 7 8 9 10 ... 461s Identify loci used to bootstrap DH means... 461s Heterozygous SNPs to resample for DH: 461s int [1:2111] 10 12 24 28 31 33 34 39 46 48 ... 461s Identify loci used to bootstrap DH means...done 461s Identify loci used to bootstrap TCN means... 461s SNPs: 461s int [1:2111] 10 12 24 28 31 33 34 39 46 48 ... 461s Non-polymorphic loci: 461s int [1:5488] 1 2 3 4 5 6 7 8 9 11 ... 461s Heterozygous SNPs to resample for TCN: 461s int [1:2111] 10 12 24 28 31 33 34 39 46 48 ... 461s Homozygous SNPs to resample for TCN: 461s int(0) 461s Non-polymorphic loci to resample for TCN: 461s int [1:5488] 1 2 3 4 5 6 7 8 9 11 ... 461s Heterozygous SNPs with non-DH to resample for TCN: 461s int(0) 461s Loci to resample for TCN: 461s int [1:7599] 1 2 3 4 5 6 7 8 9 10 ... 461s Identify loci used to bootstrap TCN means...done 461s Number of (#hets, #homs, #nonSNPs): (2111,0,5488) 461s Bootstrapping while preserving (#hets, #homs, #nonSNPs)... 461s Number of bootstrap samples: 100 461s Bootstrapping while preserving (#hets, #homs, #nonSNPs)...done 461s Segment #1 (chr 1, tcnId=1, dhId=1) of 3...done 461s Segment #2 (chr 1, tcnId=2, dhId=1) of 3... 461s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 461s 2 1 2 1 143926517 185449813 2668 2.0704 774 461s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 461s 2 774 143926517 185449813 774 0.1542 0.8755722 1.194828 461s Number of TCNs: 2668 461s Number of DHs: 774 461s int [1:2668] 7600 7601 7602 7603 7604 7605 7606 7607 7608 7609 ... 461s int [1:14658] 1 2 3 4 5 6 7 8 9 10 ... 461s int [1:2668] 7600 7601 7602 7603 7604 7605 7606 7607 7608 7609 ... 461s Identify loci used to bootstrap DH means... 461s Heterozygous SNPs to resample for DH: 461s int [1:774] 7614 7616 7626 7627 7628 7635 7638 7639 7640 7642 ... 461s Identify loci used to bootstrap DH means...done 461s Identify loci used to bootstrap TCN means... 461s SNPs: 461s int [1:774] 7614 7616 7626 7627 7628 7635 7638 7639 7640 7642 ... 461s Non-polymorphic loci: 461s int [1:1894] 7600 7601 7602 7603 7604 7605 7606 7607 7608 7609 ... 461s Heterozygous SNPs to resample for TCN: 461s int [1:774] 7614 7616 7626 7627 7628 7635 7638 7639 7640 7642 ... 461s Homozygous SNPs to resample for TCN: 461s int(0) 461s Non-polymorphic loci to resample for TCN: 461s int [1:1894] 7600 7601 7602 7603 7604 7605 7606 7607 7608 7609 ... 461s Heterozygous SNPs with non-DH to resample for TCN: 461s int(0) 461s Loci to resample for TCN: 461s int [1:2668] 7600 7601 7602 7603 7604 7605 7606 7607 7608 7609 ... 461s Identify loci used to bootstrap TCN means...done 461s Number of (#hets, #homs, #nonSNPs): (774,0,1894) 461s Bootstrapping while preserving (#hets, #homs, #nonSNPs)... 461s Number of bootstrap samples: 100 461s Bootstrapping while preserving (#hets, #homs, #nonSNPs)...done 461s Segment #2 (chr 1, tcnId=2, dhId=1) of 3...done 461s Segment #3 (chr 1, tcnId=3, dhId=1) of 3... 461s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 461s 3 1 3 1 185449813 247137334 4391 2.6341 1311 461s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 461s 3 1311 185449813 247137334 1311 0.2512 0.986207 1.647893 461s Number of TCNs: 4391 461s Number of DHs: 1311 461s int [1:4391] 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 461s int [1:14658] 1 2 3 4 5 6 7 8 9 10 ... 461s int [1:4391] 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 461s Identify loci used to bootstrap DH means... 461s Heterozygous SNPs to resample for DH: 461s int [1:1311] 10269 10271 10281 10282 10283 10293 10295 10297 10300 10302 ... 461s Identify loci used to bootstrap DH means...done 461s Identify loci used to bootstrap TCN means... 461s SNPs: 461s int [1:1311] 10269 10271 10281 10282 10283 10293 10295 10297 10300 10302 ... 461s Non-polymorphic loci: 461s int [1:3080] 10268 10270 10272 10273 10274 10275 10276 10277 10278 10279 ... 461s Heterozygous SNPs to resample for TCN: 461s int [1:1311] 10269 10271 10281 10282 10283 10293 10295 10297 10300 10302 ... 461s Homozygous SNPs to resample for TCN: 461s int(0) 461s Non-polymorphic loci to resample for TCN: 461s int [1:3080] 10268 10270 10272 10273 10274 10275 10276 10277 10278 10279 ... 461s Heterozygous SNPs with non-DH to resample for TCN: 461s int(0) 461s Loci to resample for TCN: 461s int [1:4391] 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 461s Identify loci used to bootstrap TCN means...done 461s Number of (#hets, #homs, #nonSNPs): (1311,0,3080) 461s Bootstrapping while preserving (#hets, #homs, #nonSNPs)... 461s Number of bootstrap samples: 100 461s Bootstrapping while preserving (#hets, #homs, #nonSNPs)...done 461s Segment #3 (chr 1, tcnId=3, dhId=1) of 3...done 461s Bootstrapped segment mean levels 461s num [1:3, 1:100, 1:4] 1.38 2.08 2.63 1.38 2.07 ... 461s - attr(*, "dimnames")=List of 3 461s ..$ : NULL 461s ..$ : NULL 461s ..$ : chr [1:4] "tcn" "dh" "c1" "c2" 461s Calculating (C1,C2) mean levels from (TCN,DH) mean levels... 461s num [1:3, 1:100, 1:4] 1.38 2.08 2.63 1.38 2.07 ... 461s - attr(*, "dimnames")=List of 3 461s ..$ : NULL 461s ..$ : NULL 461s ..$ : chr [1:4] "tcn" "dh" "c1" "c2" 461s Calculating (C1,C2) mean levels from (TCN,DH) mean levels...done 461s Calculating polar (alpha,radius,manhattan) for change points... 461s num [1:2, 1:100, 1:2] -0.5588 -0.0962 -0.5365 -0.1285 -0.5378 ... 461s - attr(*, "dimnames")=List of 3 461s ..$ : NULL 461s ..$ : NULL 461s ..$ : chr [1:2] "c1" "c2" 461s Bootstrapped change points 461s num [1:2, 1:100, 1:5] -2.89 -1.78 -2.87 -1.86 -2.88 ... 461s - attr(*, "dimnames")=List of 3 461s ..$ : NULL 461s ..$ : NULL 461s ..$ : chr [1:5] "alpha" "radius" "manhattan" "d1" ... 461s Calculating polar (alpha,radius,manhattan) for change points...done 461s Bootstrapping (TCN,DH,C1,C2) segment mean levels...done 461s Summarizing bootstrapped segment ('tcn', 'dh', 'c1', 'c2') data... 461s num [1:3, 1:4, 1:4] NA NA NA NA NA NA NA NA NA NA ... 461s - attr(*, "dimnames")=List of 3 461s ..$ : NULL 461s ..$ : chr [1:4] "2.5%" "5%" "95%" "97.5%" 461s ..$ : chr [1:4] "tcn" "dh" "c1" "c2" 461s Field #1 ('tcn') of 4... 461s Segment #1 of 3... 461s Segment #1 of 3...done 461s Segment #2 of 3... 461s Segment #2 of 3...done 461s Segment #3 of 3... 461s Segment #3 of 3...done 461s Field #1 ('tcn') of 4...done 461s Field #2 ('dh') of 4... 461s Segment #1 of 3... 461s Segment #1 of 3...done 461s Segment #2 of 3... 461s Segment #2 of 3...done 461s Segment #3 of 3... 461s Segment #3 of 3...done 461s Field #2 ('dh') of 4...done 461s Field #3 ('c1') of 4... 461s Segment #1 of 3... 461s Segment #1 of 3...done 461s Segment #2 of 3... 461s Segment #2 of 3...done 461s Segment #3 of 3... 461s Segment #3 of 3...done 461s Field #3 ('c1') of 4...done 461s Field #4 ('c2') of 4... 461s Segment #1 of 3... 461s Segment #1 of 3...done 461s Segment #2 of 3... 461s Segment #2 of 3...done 461s Segment #3 of 3... 461s Segment #3 of 3...done 461s Field #4 ('c2') of 4...done 461s Bootstrap statistics 461s num [1:3, 1:4, 1:4] 1.38 2.06 2.62 1.38 2.06 ... 461s - attr(*, "dimnames")=List of 3 461s ..$ : NULL 461s ..$ : chr [1:4] "2.5%" "5%" "95%" "97.5%" 461s ..$ : chr [1:4] "tcn" "dh" "c1" "c2" 461s Statistical sanity checks (iff B >= 100)... 461s Available summaries: 2.5%, 5%, 95%, 97.5% 461s Available quantiles: 0.025, 0.05, 0.95, 0.975 461s num [1:3, 1:4, 1:4] 1.38 2.06 2.62 1.38 2.06 ... 461s - attr(*, "dimnames")=List of 3 461s ..$ : NULL 461s ..$ : chr [1:4] "2.5%" "5%" "95%" "97.5%" 461s ..$ : chr [1:4] "tcn" "dh" "c1" "c2" 461s Field #1 ('tcn') of 4... 461s Seg 1. mean=1.3859, range=[1.38092,1.3949], n=7599 461s Seg 2. mean=2.0704, range=[2.05747,2.08326], n=2668 461s Seg 3. mean=2.6341, range=[2.62068,2.64694], n=4391 461s Field #1 ('tcn') of 4...done 461s Field #2 ('dh') of 4... 461s Seg 1. mean=0.5237, range=[0.51753,0.532002], n=2111 461s Seg 2. mean=0.1542, range=[0.144468,0.16453], n=774 461s Seg 3. mean=0.2512, range=[0.242575,0.258832], n=1311 461s Field #2 ('dh') of 4...done 461s Field #3 ('c1') of 4... 461s Seg 1. mean=0.330052, range=[0.323996,0.336038], n=2111 461s Seg 2. mean=0.875572, range=[0.86318,0.887699], n=774 461s Seg 3. mean=0.986207, range=[0.975123,0.998982], n=1311 461s Field #3 ('c1') of 4...done 461s Field #4 ('c2') of 4... 461s Seg 1. mean=1.05585, range=[1.05006,1.06231], n=2111 461s Seg 2. mean=1.19483, range=[1.18417,1.2081], n=774 461s Seg 3. mean=1.64789, range=[1.63403,1.66098], n=1311 461s Field #4 ('c2') of 4...done 461s Statistical sanity checks (iff B >= 100)...done 461s Summarizing bootstrapped segment ('tcn', 'dh', 'c1', 'c2') data...done 461s Summarizing bootstrapped changepoint ('alpha', 'radius', 'manhattan', 'd1', 'd2') data... 461s num [1:2, 1:4, 1:5] NA NA NA NA NA NA NA NA NA NA ... 461s - attr(*, "dimnames")=List of 3 461s ..$ : NULL 461s ..$ : chr [1:4] "2.5%" "5%" "95%" "97.5%" 461s ..$ : chr [1:5] "alpha" "radius" "manhattan" "d1" ... 461s Field #1 ('alpha') of 5... 461s Changepoint #1 of 2... 461s Changepoint #1 of 2...done 461s Changepoint #2 of 2... 461s Changepoint #2 of 2...done 461s Field #1 ('alpha') of 5...done 461s Field #2 ('radius') of 5... 461s Changepoint #1 of 2... 461s Changepoint #1 of 2...done 461s Changepoint #2 of 2... 461s Changepoint #2 of 2...done 461s Field #2 ('radius') of 5...done 461s Field #3 ('manhattan') of 5... 461s Changepoint #1 of 2... 461s Changepoint #1 of 2...done 461s Changepoint #2 of 2... 461s Changepoint #2 of 2...done 461s Field #3 ('manhattan') of 5...done 461s Field #4 ('d1') of 5... 461s Changepoint #1 of 2... 461s Changepoint #1 of 2...done 461s Changepoint #2 of 2... 461s Changepoint #2 of 2...done 461s Field #4 ('d1') of 5...done 461s Field #5 ('d2') of 5... 461s Changepoint #1 of 2... 461s Changepoint #1 of 2...done 461s Changepoint #2 of 2... 461s Changepoint #2 of 2...done 461s Field #5 ('d2') of 5...done 461s Bootstrap statistics 461s num [1:2, 1:4, 1:5] -2.92 -1.86 -2.91 -1.85 -2.87 ... 461s - attr(*, "dimnames")=List of 3 461s ..$ : NULL 461s ..$ : chr [1:4] "2.5%" "5%" "95%" "97.5%" 461s ..$ : chr [1:5] "alpha" "radius" "manhattan" "d1" ... 461s Summarizing bootstrapped changepoint ('alpha', 'radius', 'manhattan', 'd1', 'd2') data...done 461s Resample (TCN,DH) signals and re-estimate summaries for segment & changepoint...done 461s > print(fit) 461s chromosome tcnId dhId start end tcnNbrOfLoci tcnMean tcnNbrOfSNPs 461s 1 1 1 1 554484 143926517 7599 1.3859 2111 461s 2 1 2 1 143926517 185449813 2668 2.0704 774 461s 3 1 3 1 185449813 247137334 4391 2.6341 1311 461s tcnNbrOfHets dhNbrOfLoci dhMean c1Mean c2Mean 461s 1 2111 2111 0.5237 0.3300521 1.055848 461s 2 774 774 0.1542 0.8755722 1.194828 461s 3 1311 1311 0.2512 0.9862070 1.647893 461s > plotTracks(fit) 461s > 461s > 461s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 461s > # Calling segments in allelic balance (AB) and 461s > # in loss-of-heterozygosity (LOH) 461s > # NOTE: Ideally, this should be done on whole-genome data 461s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 461s > fit <- callAB(fit, verbose=-10) 461s Calling segments of allelic balance from one-sided DH bootstrap confidence intervals... 461s delta (offset adjusting for bias in DH): 0.3466649145302 461s alpha (CI quantile; significance level): 0.05 461s Calling segments... 461s Number of segments called allelic balance (AB): 2 (66.67%) of 3 461s Calling segments...done 461s Calling segments of allelic balance from one-sided DH bootstrap confidence intervals...done 461s > fit <- callLOH(fit, verbose=-10) 461s Calling segments of allelic balance from one-sided DH bootstrap confidence intervals... 461s delta (offset adjusting for bias in C1): 0.771236438183453 461s alpha (CI quantile; significance level): 0.05 461s Calling segments... 461s Number of segments called low C1 (LowC1, "LOH_C1"): 1 (33.33%) of 3 461s Calling segments...done 461s Calling segments of allelic balance from one-sided DH bootstrap confidence intervals...done 461s > print(fit) 461s chromosome tcnId dhId start end tcnNbrOfLoci tcnMean tcnNbrOfSNPs 461s 1 1 1 1 554484 143926517 7599 1.3859 2111 461s 2 1 2 1 143926517 185449813 2668 2.0704 774 461s 3 1 3 1 185449813 247137334 4391 2.6341 1311 461s tcnNbrOfHets dhNbrOfLoci dhMean c1Mean c2Mean abCall lohCall 461s 1 2111 2111 0.5237 0.3300521 1.055848 FALSE TRUE 461s 2 774 774 0.1542 0.8755722 1.194828 TRUE FALSE 461s 3 1311 1311 0.2512 0.9862070 1.647893 TRUE FALSE 461s > plotTracks(fit) 461s > 461s > proc.time() 461s user system elapsed 461s 2.026 0.125 2.143 461s Test segmentByPairedPSCBS,DH passed 461s 0 461s Begin test segmentByPairedPSCBS,calls 465s + cat segmentByPairedPSCBS,calls.Rout 465s + [ 0 != 0 ] 465s + echo Test segmentByPairedPSCBS,calls passed 465s + echo 0 465s + echo Begin test segmentByPairedPSCBS,futures 465s + exitcode=0 465s + R CMD BATCH segmentByPairedPSCBS,futures.R 465s 465s R version 4.3.2 (2023-10-31) -- "Eye Holes" 465s Copyright (C) 2023 The R Foundation for Statistical Computing 465s Platform: x86_64-pc-linux-gnu (64-bit) 465s 465s R is free software and comes with ABSOLUTELY NO WARRANTY. 465s You are welcome to redistribute it under certain conditions. 465s Type 'license()' or 'licence()' for distribution details. 465s 465s R is a collaborative project with many contributors. 465s Type 'contributors()' for more information and 465s 'citation()' on how to cite R or R packages in publications. 465s 465s Type 'demo()' for some demos, 'help()' for on-line help, or 465s 'help.start()' for an HTML browser interface to help. 465s Type 'q()' to quit R. 465s 465s [Previously saved workspace restored] 465s 465s > library("PSCBS") 465s PSCBS v0.66.0 (2021-10-23 07:40:02 UTC) successfully loaded. See ?PSCBS for help. 465s 465s Attaching package: 'PSCBS' 465s 465s The following objects are masked from 'package:base': 465s 465s append, load 465s 465s > 465s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 465s > # Load SNP microarray data 465s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 465s > data <- PSCBS::exampleData("paired.chr01") 465s > str(data) 465s 'data.frame': 73346 obs. of 6 variables: 465s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 465s $ x : int 1145994 2224111 2319424 2543484 2926730 2941694 3084986 3155127 3292731 3695086 ... 465s $ CT : num 1.625 1.071 1.406 1.18 0.856 ... 465s $ betaT : num 0.757 0.771 0.834 0.778 0.229 ... 465s $ CN : num 2.36 2.13 2.59 1.93 1.71 ... 465s $ betaN : num 0.827 0.875 0.887 0.884 0.103 ... 465s > 465s > 465s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 465s > # Paired PSCBS segmentation 465s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 465s > # Drop single-locus outliers 465s > dataS <- dropSegmentationOutliers(data) 465s > 465s > # Find centromere 465s > gaps <- findLargeGaps(dataS, minLength=2e6) 465s > knownSegments <- gapsToSegments(gaps) 465s > 465s > 465s > # Run light-weight tests by default 465s > if (Sys.getenv("_R_CHECK_FULL_") == "") { 465s + # Use only every 5th data point 465s + dataS <- dataS[seq(from=1, to=nrow(data), by=5),] 465s + # Number of segments (for assertion) 465s + nSegs <- 4L 465s + # Number of bootstrap samples (see below) 465s + B <- 100L 465s + } else { 465s + # Full tests 465s + nSegs <- 11L 465s + B <- 1000L 465s + } 465s > 465s > str(dataS) 465s 'data.frame': 14670 obs. of 6 variables: 465s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 465s $ x : int 1145994 2941694 3710825 4240737 4276892 4464544 4714611 5095111 5034491 5158416 ... 465s $ CT : num 1.63 1.4 1.41 1.17 1.16 ... 465s $ betaT : num 0.7574 0.169 0.2357 0.2604 0.0576 ... 465s $ CN : num 2.36 2.13 2.26 2.01 2.32 ... 465s $ betaN : num 0.8274 0.5072 0.1671 0.1609 0.0421 ... 465s > 465s > # Paired PSCBS segmentation 465s > fit <- segmentByPairedPSCBS(dataS, knownSegments=knownSegments, 465s + seed=0xBEEF, verbose=-10) 465s Segmenting paired tumor-normal signals using Paired PSCBS... 465s Calling genotypes from normal allele B fractions... 465s num [1:14670] 0.8274 0.5072 0.1671 0.1609 0.0421 ... 465s Called genotypes: 465s num [1:14670] 1 0.5 0 0 0 0 1 0 1 0.5 ... 465s - attr(*, "modelFit")=List of 1 465s ..$ :List of 7 465s .. ..$ flavor : chr "density" 465s .. ..$ cn : int 2 465s .. ..$ nbrOfGenotypeGroups: int 3 465s .. ..$ tau : num [1:2] 0.315 0.677 465s .. ..$ n : int 14640 465s .. ..$ fit :Classes 'PeaksAndValleys' and 'data.frame': 5 obs. of 3 variables: 465s .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 465s .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 465s .. .. ..$ density: num [1:5] 1.48 0.522 1.056 0.552 1.454 465s .. ..$ fitValleys :Classes 'PeaksAndValleys' and 'data.frame': 2 obs. of 3 variables: 465s .. .. ..$ type : chr [1:2] "valley" "valley" 465s .. .. ..$ x : num [1:2] 0.315 0.677 465s .. .. ..$ density: num [1:2] 0.522 0.552 465s ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 465s muN 465s 0 0.5 1 465s 5221 4198 5251 465s Calling genotypes from normal allele B fractions...done 465s Normalizing betaT using betaN (TumorBoost)... 465s Normalized BAFs: 465s num [1:14670] 0.9301 0.1667 0.0685 0.0995 0.0155 ... 465s - attr(*, "modelFit")=List of 5 465s ..$ method : chr "normalizeTumorBoost" 465s ..$ flavor : chr "v4" 465s ..$ delta : num [1:14670] -0.17264 0.00239 0.1671 0.16085 0.04213 ... 465s .. ..- attr(*, "modelFit")=List of 1 465s .. .. ..$ :List of 7 465s .. .. .. ..$ flavor : chr "density" 465s .. .. .. ..$ cn : int 2 465s .. .. .. ..$ nbrOfGenotypeGroups: int 3 465s .. .. .. ..$ tau : num [1:2] 0.315 0.677 465s .. .. .. ..$ n : int 14640 465s .. .. .. ..$ fit :Classes 'PeaksAndValleys' and 'data.frame': 5 obs. of 3 variables: 465s .. .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 465s .. .. .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 465s .. .. .. .. ..$ density: num [1:5] 1.48 0.522 1.056 0.552 1.454 465s .. .. .. ..$ fitValleys :Classes 'PeaksAndValleys' and 'data.frame': 2 obs. of 3 variables: 465s .. .. .. .. ..$ type : chr [1:2] "valley" "valley" 465s .. .. .. .. ..$ x : num [1:2] 0.315 0.677 465s .. .. .. .. ..$ density: num [1:2] 0.522 0.552 465s .. .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 465s ..$ preserveScale: logi FALSE 465s ..$ scaleFactor : num NA 465s Normalizing betaT using betaN (TumorBoost)...done 465s Setup up data... 465s 'data.frame': 14670 obs. of 7 variables: 465s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 465s $ x : num 1145994 2941694 3710825 4240737 4276892 ... 465s $ CT : num 1.63 1.4 1.41 1.17 1.16 ... 465s $ betaT : num 0.7574 0.169 0.2357 0.2604 0.0576 ... 465s $ betaTN : num 0.9301 0.1667 0.0685 0.0995 0.0155 ... 465s ..- attr(*, "modelFit")=List of 5 465s .. ..$ method : chr "normalizeTumorBoost" 465s .. ..$ flavor : chr "v4" 465s .. ..$ delta : num [1:14670] -0.17264 0.00239 0.1671 0.16085 0.04213 ... 465s .. .. ..- attr(*, "modelFit")=List of 1 465s .. .. .. ..$ :List of 7 465s .. .. .. .. ..$ flavor : chr "density" 465s .. .. .. .. ..$ cn : int 2 465s .. .. .. .. ..$ nbrOfGenotypeGroups: int 3 465s .. .. .. .. ..$ tau : num [1:2] 0.315 0.677 465s .. .. .. .. ..$ n : int 14640 465s .. .. .. .. ..$ fit :Classes 'PeaksAndValleys' and 'data.frame': 5 obs. of 3 variables: 465s .. .. .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 465s .. .. .. .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 465s .. .. .. .. .. ..$ density: num [1:5] 1.48 0.522 1.056 0.552 1.454 465s .. .. .. .. ..$ fitValleys :Classes 'PeaksAndValleys' and 'data.frame': 2 obs. of 3 variables: 465s .. .. .. .. .. ..$ type : chr [1:2] "valley" "valley" 465s .. .. .. .. .. ..$ x : num [1:2] 0.315 0.677 465s .. .. .. .. .. ..$ density: num [1:2] 0.522 0.552 465s .. .. .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 465s .. ..$ preserveScale: logi FALSE 465s .. ..$ scaleFactor : num NA 465s $ betaN : num 0.8274 0.5072 0.1671 0.1609 0.0421 ... 465s $ muN : num 1 0.5 0 0 0 0 1 0 1 0.5 ... 465s ..- attr(*, "modelFit")=List of 1 465s .. ..$ :List of 7 465s .. .. ..$ flavor : chr "density" 465s .. .. ..$ cn : int 2 465s .. .. ..$ nbrOfGenotypeGroups: int 3 465s .. .. ..$ tau : num [1:2] 0.315 0.677 465s .. .. ..$ n : int 14640 465s .. .. ..$ fit :Classes 'PeaksAndValleys' and 'data.frame': 5 obs. of 3 variables: 465s .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 465s .. .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 465s .. .. .. ..$ density: num [1:5] 1.48 0.522 1.056 0.552 1.454 465s .. .. ..$ fitValleys :Classes 'PeaksAndValleys' and 'data.frame': 2 obs. of 3 variables: 465s .. .. .. ..$ type : chr [1:2] "valley" "valley" 465s .. .. .. ..$ x : num [1:2] 0.315 0.677 465s .. .. .. ..$ density: num [1:2] 0.522 0.552 465s .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 465s Setup up data...done 465s Dropping loci for which TCNs are missing... 465s Number of loci dropped: 12 465s Dropping loci for which TCNs are missing...done 465s Ordering data along genome... 465s 'data.frame': 14658 obs. of 7 variables: 465s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 465s $ x : num 554484 730720 782343 878522 916294 ... 465s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 465s $ betaT : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 465s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 465s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 465s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 465s Ordering data along genome...done 465s Keeping only current chromosome for 'knownSegments'... 465s Chromosome: 1 465s Known segments for this chromosome: 465s chromosome start end length 465s 1 1 -Inf 120992603 Inf 465s 2 1 120992604 141510002 20517398 465s 3 1 141510003 Inf Inf 465s Keeping only current chromosome for 'knownSegments'...done 465s alphaTCN: 0.009 465s alphaDH: 0.001 465s Number of loci: 14658 465s Calculating DHs... 465s Number of SNPs: 14658 465s Number of heterozygous SNPs: 4196 (28.63%) 465s Normalized DHs: 465s num [1:14658] NA NA NA NA NA ... 465s Calculating DHs...done 465s Random seed temporarily set (seed=c(48879), kind="L'Ecuyer-CMRG") 465s Produced 2 seeds from this stream for future usage 465s Identification of change points by total copy numbers... 465s Segmenting by CBS... 465s Chromosome: 1 465s Segmenting multiple segments on current chromosome... 465s Number of segments: 3 465s Random seed temporarily set (seed=c(10407, 1066287653, -51199871, 161854402, -1995183193, 1503453565, -747102133), kind="L'Ecuyer-CMRG") 465s Produced 3 seeds from this stream for future usage 465s Segmenting by CBS... 465s Chromosome: 1 465s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 465s Segmenting by CBS...done 465s Segmenting by CBS... 465s Chromosome: 1 465s Random seed temporarily set (seed=c(10407, -1924040949, -1632234809, -437763632, -1464377300, 676654412, 2080370711), kind="L'Ecuyer-CMRG") 465s Segmenting by CBS...done 465s Segmenting multiple segments on current chromosome...done 465s Segmenting by CBS...done 465s List of 4 465s $ data :'data.frame': 14658 obs. of 4 variables: 465s ..$ chromosome: int [1:14658] 1 1 1 1 1 1 1 1 1 1 ... 465s ..$ x : num [1:14658] 554484 730720 782343 878522 916294 ... 465s ..$ y : num [1:14658] 1.88 1.8 1.59 1.64 1.53 ... 465s ..$ index : int [1:14658] 1 2 3 4 5 6 7 8 9 10 ... 465s $ output :'data.frame': 4 obs. of 6 variables: 465s ..$ sampleName: chr [1:4] NA NA NA NA 465s ..$ chromosome: int [1:4] 1 1 1 1 465s ..$ start : num [1:4] 5.54e+05 1.21e+08 1.42e+08 1.85e+08 465s ..$ end : num [1:4] 1.21e+08 1.42e+08 1.85e+08 2.47e+08 465s ..$ nbrOfLoci : int [1:4] 7586 0 2681 4391 465s ..$ mean : num [1:4] 1.39 NA 2.07 2.63 465s $ segRows:'data.frame': 4 obs. of 2 variables: 465s ..$ startRow: int [1:4] 1 NA 7587 10268 465s ..$ endRow : int [1:4] 7586 NA 10267 14658 465s $ params :List of 5 465s ..$ alpha : num 0.009 465s ..$ undo : num 0 465s ..$ joinSegments : logi TRUE 465s ..$ knownSegments:'data.frame': 4 obs. of 3 variables: 465s .. ..$ chromosome: int [1:4] 1 1 2 1 465s .. ..$ start : num [1:4] -Inf -Inf -Inf 1.42e+08 465s .. ..$ end : num [1:4] 1.21e+08 Inf Inf Inf 465s ..$ seed : int [1:7] 10407 1066287653 -51199871 161854402 -1995183193 1503453565 -747102133 465s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 465s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.133 0 0.133 0 0 465s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 465s - attr(*, "pkgDetails")= chr "DNAcopy v1.76.0" 465s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 465s Identification of change points by total copy numbers...done 465s Restructure TCN segmentation results... 465s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean 465s 1 1 554484 120992603 7586 1.3853 465s 2 1 120992604 141510002 0 NA 465s 3 1 141510003 185449813 2681 2.0689 465s 4 1 185449813 247137334 4391 2.6341 465s Number of TCN segments: 4 465s Restructure TCN segmentation results...done 465s Total CN segment #1 ([ 554484,1.20993e+08]) of 4... 465s Number of TCN loci in segment: 7586 465s Locus data for TCN segment: 465s 'data.frame': 7586 obs. of 9 variables: 465s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 465s $ x : num 554484 730720 782343 878522 916294 ... 465s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 465s $ betaT : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 465s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 465s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 465s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 465s $ index : int 1 2 3 4 5 6 7 8 9 10 ... 465s $ rho : num NA NA NA NA NA ... 465s Number of loci: 7586 465s Number of SNPs: 2108 (27.79%) 465s Number of heterozygous SNPs: 2108 (100.00%) 465s Chromosome: 1 465s Segmenting DH signals... 465s Segmenting by CBS... 465s Chromosome: 1 465s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 465s Segmenting by CBS...done 465s List of 4 465s $ data :'data.frame': 7586 obs. of 4 variables: 465s ..$ chromosome: int [1:7586] 1 1 1 1 1 1 1 1 1 1 ... 465s ..$ x : num [1:7586] 554484 730720 782343 878522 916294 ... 465s ..$ y : num [1:7586] NA NA NA NA NA ... 465s ..$ index : int [1:7586] 1 2 3 4 5 6 7 8 9 10 ... 465s $ output :'data.frame': 1 obs. of 6 variables: 465s ..$ sampleName: chr NA 465s ..$ chromosome: int 1 465s ..$ start : num 554484 465s ..$ end : num 1.21e+08 465s ..$ nbrOfLoci : int 2108 465s ..$ mean : num 0.512 465s $ segRows:'data.frame': 1 obs. of 2 variables: 465s ..$ startRow: int 10 465s ..$ endRow : int 7574 465s $ params :List of 5 465s ..$ alpha : num 0.001 465s ..$ undo : num 0 465s ..$ joinSegments : logi TRUE 465s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 465s .. ..$ chromosome: int 1 465s .. ..$ start : num 554484 465s .. ..$ end : num 1.21e+08 465s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 465s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 465s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.035 0 0.035 0 0 465s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 465s - attr(*, "pkgDetails")= chr "DNAcopy v1.76.0" 465s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 465s DH segmentation (locally-indexed) rows: 465s startRow endRow 465s 1 10 7574 465s int [1:7586] 1 2 3 4 5 6 7 8 9 10 ... 465s DH segmentation rows: 465s startRow endRow 465s 1 10 7574 465s Segmenting DH signals...done 465s DH segmentation table: 465s dhStart dhEnd dhNbrOfLoci dhMean 465s 1 554484 120992603 2108 0.5116 465s startRow endRow 465s 1 10 7574 465s Rows: 465s [1] 1 465s TCN segmentation rows: 465s startRow endRow 465s 1 1 7586 465s TCN and DH segmentation rows: 465s startRow endRow 465s 1 1 7586 465s startRow endRow 465s 1 10 7574 465s NULL 465s TCN segmentation (expanded) rows: 465s startRow endRow 465s 1 1 7586 465s TCN and DH segmentation rows: 465s startRow endRow 465s 1 1 7586 465s 2 NA NA 465s 3 7587 10267 465s 4 10268 14658 465s startRow endRow 465s 1 10 7574 465s startRow endRow 465s 1 1 7586 465s Total CN segmentation table (expanded): 465s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 465s 1 1 554484 120992603 7586 1.3853 2108 2108 465s (TCN,DH) segmentation for one total CN segment: 465s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 465s 1 1 1 1 554484 120992603 7586 1.3853 2108 465s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 465s 1 2108 554484 120992603 2108 0.5116 465s Total CN segment #1 ([ 554484,1.20993e+08]) of 4...done 465s Total CN segment #2 ([1.20993e+08,1.4151e+08]) of 4... 465s Number of TCN loci in segment: 0 465s Locus data for TCN segment: 465s 'data.frame': 0 obs. of 9 variables: 465s $ chromosome: int 465s $ x : num 465s $ CT : num 465s $ betaT : num 465s $ betaTN : num 465s $ betaN : num 465s $ muN : num 465s $ index : int 465s $ rho : num 465s Number of loci: 0 465s Number of SNPs: 0 (NaN%) 465s Number of heterozygous SNPs: 0 (NaN%) 465s Chromosome: 1 465s Segmenting DH signals... 465s Segmenting by CBS... 465s Chromosome: NA 465s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 465s Segmenting by CBS...done 465s List of 4 465s $ data :'data.frame': 0 obs. of 4 variables: 465s ..$ chromosome: int(0) 465s ..$ x : num(0) 465s ..$ y : num(0) 465s ..$ index : int(0) 465s $ output :'data.frame': 0 obs. of 6 variables: 465s ..$ sampleName: chr(0) 465s ..$ chromosome: num(0) 465s ..$ start : num(0) 465s ..$ end : num(0) 465s ..$ nbrOfLoci : int(0) 465s ..$ mean : num(0) 465s $ segRows:'data.frame': 0 obs. of 2 variables: 465s ..$ startRow: int(0) 465s ..$ endRow : int(0) 465s $ params :List of 5 465s ..$ alpha : num 0.001 465s ..$ undo : num 0 465s ..$ joinSegments : logi TRUE 465s ..$ knownSegments:'data.frame': 0 obs. of 3 variables: 465s .. ..$ chromosome: int(0) 465s .. ..$ start : num(0) 465s .. ..$ end : num(0) 465s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 465s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 465s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.001 0 0.001 0 0 465s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 465s - attr(*, "pkgDetails")= chr "DNAcopy v1.76.0" 465s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 465s DH segmentation (locally-indexed) rows: 465s [1] startRow endRow 465s <0 rows> (or 0-length row.names) 465s int(0) 465s DH segmentation rows: 465s [1] startRow endRow 465s <0 rows> (or 0-length row.names) 465s Segmenting DH signals...done 465s DH segmentation table: 465s dhStart dhEnd dhNbrOfLoci dhMean 465s NA NA NA NA NA 465s startRow endRow 465s NA NA NA 465s Rows: 465s [1] 2 465s TCN segmentation rows: 465s startRow endRow 465s 2 NA NA 465s TCN and DH segmentation rows: 465s startRow endRow 465s 2 NA NA 465s startRow endRow 465s NA NA NA 465s startRow endRow 465s 1 1 7586 465s TCN segmentation (expanded) rows: 465s startRow endRow 465s 1 1 7586 465s 2 NA NA 465s TCN and DH segmentation rows: 465s startRow endRow 465s 1 1 7586 465s 2 NA NA 465s 3 7587 10267 465s 4 10268 14658 465s startRow endRow 465s 1 10 7574 465s 2 NA NA 465s startRow endRow 465s 1 1 7586 465s 2 NA NA 465s Total CN segmentation table (expanded): 465s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 465s 2 1 120992604 141510002 0 NA 0 0 465s (TCN,DH) segmentation for one total CN segment: 465s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 465s 2 2 1 1 120992604 141510002 0 NA 0 465s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 465s 2 0 NA NA NA NA 465s Total CN segment #2 ([1.20993e+08,1.4151e+08]) of 4...done 465s Total CN segment #3 ([1.4151e+08,1.8545e+08]) of 4... 465s Number of TCN loci in segment: 2681 465s Locus data for TCN segment: 465s 'data.frame': 2681 obs. of 9 variables: 465s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 465s $ x : num 1.43e+08 1.43e+08 1.43e+08 1.43e+08 1.44e+08 ... 465s $ CT : num 2.27 1.55 1.47 1.5 1.81 ... 465s $ betaT : num 0.34 0.55 0.048 0.813 0.575 ... 465s $ betaTN : num 0.441 0.629 -0.05 0.958 0.872 ... 465s $ betaN : num 0.3851 0.3933 0.0981 0.8552 0.7028 ... 465s $ muN : num 0.5 0.5 0 1 1 1 1 0.5 1 1 ... 465s $ index : int 7587 7588 7589 7590 7591 7592 7593 7594 7595 7596 ... 465s $ rho : num 0.117 0.258 NA NA NA ... 465s Number of loci: 2681 465s Number of SNPs: 777 (28.98%) 465s Number of heterozygous SNPs: 777 (100.00%) 465s Chromosome: 1 465s Segmenting DH signals... 465s Segmenting by CBS... 465s Chromosome: 1 465s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 465s Segmenting by CBS...done 465s List of 4 465s $ data :'data.frame': 2681 obs. of 4 variables: 465s ..$ chromosome: int [1:2681] 1 1 1 1 1 1 1 1 1 1 ... 465s ..$ x : num [1:2681] 1.43e+08 1.43e+08 1.43e+08 1.43e+08 1.44e+08 ... 465s ..$ y : num [1:2681] 0.117 0.258 NA NA NA ... 465s ..$ index : int [1:2681] 1 2 3 4 5 6 7 8 9 10 ... 465s $ output :'data.frame': 1 obs. of 6 variables: 465s ..$ sampleName: chr NA 465s ..$ chromosome: int 1 465s ..$ start : num 1.42e+08 465s ..$ end : num 1.85e+08 465s ..$ nbrOfLoci : int 777 465s ..$ mean : num 0.0973 465s $ segRows:'data.frame': 1 obs. of 2 variables: 465s ..$ startRow: int 1 465s ..$ endRow : int 2677 465s $ params :List of 5 465s ..$ alpha : num 0.001 465s ..$ undo : num 0 465s ..$ joinSegments : logi TRUE 465s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 465s .. ..$ chromosome: int 1 465s .. ..$ start : num 1.42e+08 465s .. ..$ end : num 1.85e+08 465s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 465s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 465s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.007 0 0.008 0 0 465s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 465s - attr(*, "pkgDetails")= chr "DNAcopy v1.76.0" 465s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 465s DH segmentation (locally-indexed) rows: 465s startRow endRow 465s 1 1 2677 465s int [1:2681] 7587 7588 7589 7590 7591 7592 7593 7594 7595 7596 ... 465s DH segmentation rows: 465s startRow endRow 465s 1 7587 10263 465s Segmenting DH signals...done 465s DH segmentation table: 465s dhStart dhEnd dhNbrOfLoci dhMean 465s 1 141510003 185449813 777 0.0973 465s startRow endRow 465s 1 7587 10263 465s Rows: 465s [1] 3 465s TCN segmentation rows: 465s startRow endRow 465s 3 7587 10267 465s TCN and DH segmentation rows: 465s startRow endRow 465s 3 7587 10267 465s startRow endRow 465s 1 7587 10263 465s startRow endRow 465s 1 1 7586 465s 2 NA NA 465s TCN segmentation (expanded) rows: 465s startRow endRow 465s 1 1 7586 465s 2 NA NA 465s 3 7587 10267 465s TCN and DH segmentation rows: 465s startRow endRow 465s 1 1 7586 465s 2 NA NA 465s 3 7587 10267 465s 4 10268 14658 465s startRow endRow 465s 1 10 7574 465s 2 NA NA 465s 3 7587 10263 465s startRow endRow 465s 1 1 7586 465s 2 NA NA 465s 3 7587 10267 465s Total CN segmentation table (expanded): 465s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 465s 3 1 141510003 185449813 2681 2.0689 777 777 465s (TCN,DH) segmentation for one total CN segment: 465s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 465s 3 3 1 1 141510003 185449813 2681 2.0689 777 465s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 465s 3 777 141510003 185449813 777 0.0973 465s Total CN segment #3 ([1.4151e+08,1.8545e+08]) of 4...done 465s Total CN segment #4 ([1.8545e+08,2.47137e+08]) of 4... 465s Number of TCN loci in segment: 4391 465s Locus data for TCN segment: 465s 'data.frame': 4391 obs. of 9 variables: 465s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 465s $ x : num 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 465s $ CT : num 2.93 2.15 2.82 2.93 2.46 ... 465s $ betaT : num 0.0811 0.5154 0.9473 0.3734 0.7506 ... 465s $ betaTN : num -0.169 0.609 1.028 0.525 0.968 ... 465s $ betaN : num 0.25 0.38 0.919 0.34 0.783 ... 465s $ muN : num 0 0.5 1 0.5 1 1 0 1 0 1 ... 465s $ index : int 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 465s $ rho : num NA 0.2186 NA 0.0503 NA ... 465s Number of loci: 4391 465s Number of SNPs: 1311 (29.86%) 465s Number of heterozygous SNPs: 1311 (100.00%) 465s Chromosome: 1 465s Segmenting DH signals... 465s Segmenting by CBS... 465s Chromosome: 1 465s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 465s Segmenting by CBS...done 465s List of 4 465s $ data :'data.frame': 4391 obs. of 4 variables: 465s ..$ chromosome: int [1:4391] 1 1 1 1 1 1 1 1 1 1 ... 465s ..$ x : num [1:4391] 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 465s ..$ y : num [1:4391] NA 0.2186 NA 0.0503 NA ... 465s ..$ index : int [1:4391] 1 2 3 4 5 6 7 8 9 10 ... 465s $ output :'data.frame': 1 obs. of 6 variables: 465s ..$ sampleName: chr NA 465s ..$ chromosome: int 1 465s ..$ start : num 1.85e+08 465s ..$ end : num 2.47e+08 465s ..$ nbrOfLoci : int 1311 465s ..$ mean : num 0.23 465s $ segRows:'data.frame': 1 obs. of 2 variables: 465s ..$ startRow: int 2 465s ..$ endRow : int 4388 465s $ params :List of 5 465s ..$ alpha : num 0.001 465s ..$ undo : num 0 465s ..$ joinSegments : logi TRUE 465s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 465s .. ..$ chromosome: int 1 465s .. ..$ start : num 1.85e+08 465s .. ..$ end : num 2.47e+08 465s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 465s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 465s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.014 0 0.014 0 0 465s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 465s - attr(*, "pkgDetails")= chr "DNAcopy v1.76.0" 465s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 465s DH segmentation (locally-indexed) rows: 465s startRow endRow 465s 1 2 4388 465s int [1:4391] 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 465s DH segmentation rows: 465s startRow endRow 465s 1 10269 14655 465s Segmenting DH signals...done 465s DH segmentation table: 465s dhStart dhEnd dhNbrOfLoci dhMean 465s 1 185449813 247137334 1311 0.2295 465s startRow endRow 465s 1 10269 14655 465s Rows: 465s [1] 4 465s TCN segmentation rows: 465s startRow endRow 465s 4 10268 14658 465s TCN and DH segmentation rows: 465s startRow endRow 465s 4 10268 14658 465s startRow endRow 465s 1 10269 14655 465s startRow endRow 465s 1 1 7586 465s 2 NA NA 465s 3 7587 10267 465s TCN segmentation (expanded) rows: 465s startRow endRow 465s 1 1 7586 465s 2 NA NA 465s 3 7587 10267 465s 4 10268 14658 465s TCN and DH segmentation rows: 465s startRow endRow 465s 1 1 7586 465s 2 NA NA 465s 3 7587 10267 465s 4 10268 14658 465s startRow endRow 465s 1 10 7574 465s 2 NA NA 465s 3 7587 10263 465s 4 10269 14655 465s startRow endRow 465s 1 1 7586 465s 2 NA NA 465s 3 7587 10267 465s 4 10268 14658 465s Total CN segmentation table (expanded): 465s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 465s 4 1 185449813 247137334 4391 2.6341 1311 1311 465s (TCN,DH) segmentation for one total CN segment: 465s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 465s 4 4 1 1 185449813 247137334 4391 2.6341 1311 465s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 465s 4 1311 185449813 247137334 1311 0.2295 465s Total CN segment #4 ([1.8545e+08,2.47137e+08]) of 4...done 465s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 465s 1 1 1 1 554484 120992603 7586 1.3853 2108 465s 2 1 2 1 120992604 141510002 0 NA 0 465s 3 1 3 1 141510003 185449813 2681 2.0689 777 465s 4 1 4 1 185449813 247137334 4391 2.6341 1311 465s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 465s 1 2108 554484 120992603 2108 0.5116 465s 2 0 NA NA NA NA 465s 3 777 141510003 185449813 777 0.0973 465s 4 1311 185449813 247137334 1311 0.2295 465s Calculating (C1,C2) per segment... 465s Calculating (C1,C2) per segment...done 465s Number of segments: 4 465s Segmenting paired tumor-normal signals using Paired PSCBS...done 465s Post-segmenting TCNs... 465s Number of segments: 4 465s Number of chromosomes: 1 465s [1] 1 465s Chromosome 1 ('chr01') of 1... 465s Rows: 465s [1] 1 2 3 4 465s Number of segments: 4 465s TCN segment #1 ('1') of 4... 465s Nothing todo. Only one DH segmentation. Skipping. 465s TCN segment #1 ('1') of 4...done 465s TCN segment #2 ('2') of 4... 465s Nothing todo. Only one DH segmentation. Skipping. 465s TCN segment #2 ('2') of 4...done 465s TCN segment #3 ('3') of 4... 465s Nothing todo. Only one DH segmentation. Skipping. 465s TCN segment #3 ('3') of 4...done 465s TCN segment #4 ('4') of 4... 465s Nothing todo. Only one DH segmentation. Skipping. 465s TCN segment #4 ('4') of 4...done 465s Chromosome 1 ('chr01') of 1...done 465s Update (C1,C2) per segment... 465s Update (C1,C2) per segment...done 465s Post-segmenting TCNs...done 465s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 465s 1 1 1 1 554484 120992603 7586 1.3853 2108 465s 2 1 2 1 120992604 141510002 0 NA 0 465s 3 1 3 1 141510003 185449813 2681 2.0689 777 465s 4 1 4 1 185449813 247137334 4391 2.6341 1311 465s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 465s 1 2108 554484 120992603 2108 0.5116 0.3382903 1.047010 465s 2 0 NA NA NA NA NA NA 465s 3 777 141510003 185449813 777 0.0973 0.9337980 1.135102 465s 4 1311 185449813 247137334 1311 0.2295 1.0147870 1.619313 465s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 465s 1 1 1 1 554484 120992603 7586 1.3853 2108 465s 2 1 2 1 120992604 141510002 0 NA 0 465s 3 1 3 1 141510003 185449813 2681 2.0689 777 465s 4 1 4 1 185449813 247137334 4391 2.6341 1311 465s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 465s 1 2108 554484 120992603 2108 0.5116 0.3382903 1.047010 465s 2 0 NA NA NA NA NA NA 465s 3 777 141510003 185449813 777 0.0973 0.9337980 1.135102 465s 4 1311 185449813 247137334 1311 0.2295 1.0147870 1.619313 465s > print(fit) 465s chromosome tcnId dhId start end tcnNbrOfLoci tcnMean tcnNbrOfSNPs 465s 1 1 1 1 554484 120992603 7586 1.3853 2108 465s 2 1 2 1 120992604 141510002 0 NA 0 465s 3 1 3 1 141510003 185449813 2681 2.0689 777 465s 4 1 4 1 185449813 247137334 4391 2.6341 1311 465s tcnNbrOfHets dhNbrOfLoci dhMean c1Mean c2Mean 465s 1 2108 2108 0.5116 0.3382903 1.047010 465s 2 0 NA NA NA NA 465s 3 777 777 0.0973 0.9337980 1.135102 465s 4 1311 1311 0.2295 1.0147870 1.619313 465s > 465s > # Plot results 465s > plotTracks(fit) 465s > 465s > # Sanity check 465s > stopifnot(nbrOfSegments(fit) == nSegs) 465s > 465s > 465s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 465s > # Bootstrap segment level estimates 465s > # (used by the AB caller, which, if skipped here, 465s > # will do it automatically) 465s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 465s > fit <- bootstrapTCNandDHByRegion(fit, B=B, verbose=-10) 465s Resample (TCN,DH) signals and re-estimate summaries for segment & changepoint... 465s Already done? 465s tcn_2.5% tcn_5% tcn_95% tcn_97.5% dh_2.5% dh_5% dh_95% dh_97.5% 465s FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE 465s c1_2.5% c1_5% c1_95% c1_97.5% c2_2.5% c2_5% c2_95% c2_97.5% 465s FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE 465s Bootstrapping (TCN,DH,C1,C2) segment mean levels... 465s Identifying heterozygous & homozygous SNPs and non-polymorphic loci... 465s Number of loci: 14658 465s Number of SNPs: 4196 465s Number of non-SNPs: 10462 465s Identifying heterozygous & homozygous SNPs and non-polymorphic loci...done 465s num [1:4, 1:100, 1:4] NA NA NA NA NA NA NA NA NA NA ... 465s - attr(*, "dimnames")=List of 3 465s ..$ : NULL 465s ..$ : NULL 465s ..$ : chr [1:4] "tcn" "dh" "c1" "c2" 465s Segment #1 (chr 1, tcnId=1, dhId=1) of 4... 465s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 465s 1 1 1 1 554484 120992603 7586 1.3853 2108 465s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 465s 1 2108 554484 120992603 2108 0.5116 0.3382903 1.04701 465s Number of TCNs: 7586 465s Number of DHs: 2108 465s int [1:7586] 1 2 3 4 5 6 7 8 9 10 ... 465s int [1:14658] 1 2 3 4 5 6 7 8 9 10 ... 465s int [1:7586] 1 2 3 4 5 6 7 8 9 10 ... 465s Identify loci used to bootstrap DH means... 465s Heterozygous SNPs to resample for DH: 465s int [1:2108] 10 12 24 28 31 33 34 39 46 48 ... 465s Identify loci used to bootstrap DH means...done 465s Identify loci used to bootstrap TCN means... 465s SNPs: 465s int [1:2108] 10 12 24 28 31 33 34 39 46 48 ... 465s Non-polymorphic loci: 465s int [1:5478] 1 2 3 4 5 6 7 8 9 11 ... 465s Heterozygous SNPs to resample for TCN: 465s int [1:2108] 10 12 24 28 31 33 34 39 46 48 ... 465s Homozygous SNPs to resample for TCN: 465s int(0) 465s Non-polymorphic loci to resample for TCN: 465s int [1:5478] 1 2 3 4 5 6 7 8 9 11 ... 465s Heterozygous SNPs with non-DH to resample for TCN: 465s int(0) 465s Loci to resample for TCN: 465s int [1:7586] 1 2 3 4 5 6 7 8 9 10 ... 465s Identify loci used to bootstrap TCN means...done 465s Number of (#hets, #homs, #nonSNPs): (2108,0,5478) 465s Bootstrapping while preserving (#hets, #homs, #nonSNPs)... 465s Number of bootstrap samples: 100 465s Bootstrapping while preserving (#hets, #homs, #nonSNPs)...done 465s Segment #1 (chr 1, tcnId=1, dhId=1) of 4...done 465s Segment #2 (chr 1, tcnId=2, dhId=1) of 4... 465s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 465s 2 1 2 1 120992604 141510002 0 NA 0 465s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 465s 2 0 NA NA 0 NA NA NA 465s Number of TCNs: 0 465s Number of DHs: 0 465s int 0 465s int [1:14658] 1 2 3 4 5 6 7 8 9 10 ... 465s int(0) 465s Identify loci used to bootstrap DH means... 465s Heterozygous SNPs to resample for DH: 465s int 0 465s Identify loci used to bootstrap DH means...done 465s Identify loci used to bootstrap TCN means... 465s SNPs: 465s int(0) 465s Non-polymorphic loci: 465s int(0) 465s Heterozygous SNPs to resample for TCN: 465s int(0) 465s Homozygous SNPs to resample for TCN: 465s int(0) 465s Non-polymorphic loci to resample for TCN: 465s int(0) 465s Heterozygous SNPs with non-DH to resample for TCN: 465s int(0) 465s Loci to resample for TCN: 465s int(0) 465s Identify loci used to bootstrap TCN means...done 465s Number of (#hets, #homs, #nonSNPs): (0,0,0) 465s Bootstrapping while preserving (#hets, #homs, #nonSNPs)... 465s Number of bootstrap samples: 100 465s Bootstrapping while preserving (#hets, #homs, #nonSNPs)...done 465s Segment #2 (chr 1, tcnId=2, dhId=1) of 4...done 465s Segment #3 (chr 1, tcnId=3, dhId=1) of 4... 465s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 465s 3 1 3 1 141510003 185449813 2681 2.0689 777 465s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 465s 3 777 141510003 185449813 777 0.0973 0.933798 1.135102 465s Number of TCNs: 2681 465s Number of DHs: 777 465s int [1:2681] 7587 7588 7589 7590 7591 7592 7593 7594 7595 7596 ... 465s int [1:14658] 1 2 3 4 5 6 7 8 9 10 ... 465s int [1:2681] 7587 7588 7589 7590 7591 7592 7593 7594 7595 7596 ... 465s Identify loci used to bootstrap DH means... 465s Heterozygous SNPs to resample for DH: 465s int [1:777] 7587 7588 7594 7614 7616 7626 7627 7628 7635 7638 ... 465s Identify loci used to bootstrap DH means...done 465s Identify loci used to bootstrap TCN means... 465s SNPs: 465s int [1:777] 7587 7588 7594 7614 7616 7626 7627 7628 7635 7638 ... 465s Non-polymorphic loci: 465s int [1:1904] 7589 7590 7591 7592 7593 7595 7596 7597 7598 7599 ... 465s Heterozygous SNPs to resample for TCN: 465s int [1:777] 7587 7588 7594 7614 7616 7626 7627 7628 7635 7638 ... 465s Homozygous SNPs to resample for TCN: 465s int(0) 465s Non-polymorphic loci to resample for TCN: 465s int [1:1904] 7589 7590 7591 7592 7593 7595 7596 7597 7598 7599 ... 465s Heterozygous SNPs with non-DH to resample for TCN: 465s int(0) 465s Loci to resample for TCN: 465s int [1:2681] 7587 7588 7589 7590 7591 7592 7593 7594 7595 7596 ... 465s Identify loci used to bootstrap TCN means...done 465s Number of (#hets, #homs, #nonSNPs): (777,0,1904) 465s Bootstrapping while preserving (#hets, #homs, #nonSNPs)... 465s Number of bootstrap samples: 100 465s Bootstrapping while preserving (#hets, #homs, #nonSNPs)...done 465s Segment #3 (chr 1, tcnId=3, dhId=1) of 4...done 465s Segment #4 (chr 1, tcnId=4, dhId=1) of 4... 465s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 465s 4 1 4 1 185449813 247137334 4391 2.6341 1311 465s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 465s 4 1311 185449813 247137334 1311 0.2295 1.014787 1.619313 465s Number of TCNs: 4391 465s Number of DHs: 1311 465s int [1:4391] 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 465s int [1:14658] 1 2 3 4 5 6 7 8 9 10 ... 465s int [1:4391] 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 465s Identify loci used to bootstrap DH means... 465s Heterozygous SNPs to resample for DH: 465s int [1:1311] 10269 10271 10281 10282 10283 10293 10295 10297 10300 10302 ... 465s Identify loci used to bootstrap DH means...done 465s Identify loci used to bootstrap TCN means... 465s SNPs: 465s int [1:1311] 10269 10271 10281 10282 10283 10293 10295 10297 10300 10302 ... 465s Non-polymorphic loci: 465s int [1:3080] 10268 10270 10272 10273 10274 10275 10276 10277 10278 10279 ... 465s Heterozygous SNPs to resample for TCN: 465s int [1:1311] 10269 10271 10281 10282 10283 10293 10295 10297 10300 10302 ... 465s Homozygous SNPs to resample for TCN: 465s int(0) 465s Non-polymorphic loci to resample for TCN: 465s int [1:3080] 10268 10270 10272 10273 10274 10275 10276 10277 10278 10279 ... 465s Heterozygous SNPs with non-DH to resample for TCN: 465s int(0) 465s Loci to resample for TCN: 465s int [1:4391] 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 465s Identify loci used to bootstrap TCN means...done 465s Number of (#hets, #homs, #nonSNPs): (1311,0,3080) 465s Bootstrapping while preserving (#hets, #homs, #nonSNPs)... 465s Number of bootstrap samples: 100 465s Bootstrapping while preserving (#hets, #homs, #nonSNPs)...done 465s Segment #4 (chr 1, tcnId=4, dhId=1) of 4...done 465s Bootstrapped segment mean levels 465s num [1:4, 1:100, 1:4] 1.39 NA 2.08 2.63 1.38 ... 465s - attr(*, "dimnames")=List of 3 465s ..$ : NULL 465s ..$ : NULL 465s ..$ : chr [1:4] "tcn" "dh" "c1" "c2" 465s Calculating (C1,C2) mean levels from (TCN,DH) mean levels... 465s num [1:4, 1:100, 1:4] 1.39 NA 2.08 2.63 1.38 ... 465s - attr(*, "dimnames")=List of 3 465s ..$ : NULL 465s ..$ : NULL 465s ..$ : chr [1:4] "tcn" "dh" "c1" "c2" 465s Calculating (C1,C2) mean levels from (TCN,DH) mean levels...done 465s Calculating polar (alpha,radius,manhattan) for change points... 465s num [1:3, 1:100, 1:2] NA NA -0.0752 NA NA ... 465s - attr(*, "dimnames")=List of 3 465s ..$ : NULL 465s ..$ : NULL 465s ..$ : chr [1:2] "c1" "c2" 465s Bootstrapped change points 465s num [1:3, 1:100, 1:5] NA NA -1.73 NA NA ... 465s - attr(*, "dimnames")=List of 3 465s ..$ : NULL 465s ..$ : NULL 465s ..$ : chr [1:5] "alpha" "radius" "manhattan" "d1" ... 465s Calculating polar (alpha,radius,manhattan) for change points...done 465s Bootstrapping (TCN,DH,C1,C2) segment mean levels...done 465s Summarizing bootstrapped segment ('tcn', 'dh', 'c1', 'c2') data... 465s num [1:4, 1:4, 1:4] NA NA NA NA NA NA NA NA NA NA ... 465s - attr(*, "dimnames")=List of 3 465s ..$ : NULL 465s ..$ : chr [1:4] "2.5%" "5%" "95%" "97.5%" 465s ..$ : chr [1:4] "tcn" "dh" "c1" "c2" 465s Field #1 ('tcn') of 4... 465s Segment #1 of 4... 465s Segment #1 of 4...done 465s Segment #2 of 4... 465s Segment #2 of 4...done 465s Segment #3 of 4... 465s Segment #3 of 4...done 465s Segment #4 of 4... 465s Segment #4 of 4...done 465s Field #1 ('tcn') of 4...done 465s Field #2 ('dh') of 4... 465s Segment #1 of 4... 465s Segment #1 of 4...done 465s Segment #2 of 4... 465s Segment #2 of 4...done 465s Segment #3 of 4... 465s Segment #3 of 4...done 465s Segment #4 of 4... 465s Segment #4 of 4...done 465s Field #2 ('dh') of 4...done 465s Field #3 ('c1') of 4... 465s Segment #1 of 4... 465s Segment #1 of 4...done 465s Segment #2 of 4... 465s Segment #2 of 4...done 465s Segment #3 of 4... 465s Segment #3 of 4...done 465s Segment #4 of 4... 465s Segment #4 of 4...done 465s Field #3 ('c1') of 4...done 465s Field #4 ('c2') of 4... 465s Segment #1 of 4... 465s Segment #1 of 4...done 465s Segment #2 of 4... 465s Segment #2 of 4...done 465s Segment #3 of 4... 465s Segment #3 of 4...done 465s Segment #4 of 4... 465s Segment #4 of 4...done 465s Field #4 ('c2') of 4...done 465s Bootstrap statistics 465s num [1:4, 1:4, 1:4] 1.38 NA 2.06 2.63 1.38 ... 465s - attr(*, "dimnames")=List of 3 465s ..$ : NULL 465s ..$ : chr [1:4] "2.5%" "5%" "95%" "97.5%" 465s ..$ : chr [1:4] "tcn" "dh" "c1" "c2" 465s Statistical sanity checks (iff B >= 100)... 465s Available summaries: 2.5%, 5%, 95%, 97.5% 465s Available quantiles: 0.025, 0.05, 0.95, 0.975 465s num [1:4, 1:4, 1:4] 1.38 NA 2.06 2.63 1.38 ... 465s - attr(*, "dimnames")=List of 3 465s ..$ : NULL 465s ..$ : chr [1:4] "2.5%" "5%" "95%" "97.5%" 465s ..$ : chr [1:4] "tcn" "dh" "c1" "c2" 465s Field #1 ('tcn') of 4... 465s Seg 1. mean=1.3853, range=[1.37909,1.39287], n=7586 465s Seg 2. mean=NA, range=[NA,NA], n=0 465s Seg 3. mean=2.0689, range=[2.05903,2.079], n=2681 465s Seg 4. mean=2.6341, range=[2.62504,2.64649], n=4391 465s Field #1 ('tcn') of 4...done 465s Field #2 ('dh') of 4... 465s Seg 1. mean=0.5116, range=[0.502148,0.519941], n=2108 465s Seg 2. mean=NA, range=[NA,NA], n=NA 465s Seg 3. mean=0.0973, range=[0.0906366,0.105818], n=777 465s Seg 4. mean=0.2295, range=[0.222919,0.237005], n=1311 465s Field #2 ('dh') of 4...done 465s Field #3 ('c1') of 4... 465s Seg 1. mean=0.33829, range=[0.332209,0.345936], n=2108 465s Seg 2. mean=NA, range=[NA,NA], n=NA 465s Seg 3. mean=0.933798, range=[0.924112,0.941776], n=777 465s Seg 4. mean=1.01479, range=[1.00381,1.02461], n=1311 465s Field #3 ('c1') of 4...done 465s Field #4 ('c2') of 4... 465s Seg 1. mean=1.04701, range=[1.03882,1.05318], n=2108 465s Seg 2. mean=NA, range=[NA,NA], n=NA 465s Seg 3. mean=1.1351, range=[1.12454,1.1465], n=777 465s Seg 4. mean=1.61931, range=[1.60862,1.63328], n=1311 465s Field #4 ('c2') of 4...done 465s Statistical sanity checks (iff B >= 100)...done 465s Summarizing bootstrapped segment ('tcn', 'dh', 'c1', 'c2') data...done 465s Summarizing bootstrapped changepoint ('alpha', 'radius', 'manhattan', 'd1', 'd2') data... 465s num [1:3, 1:4, 1:5] NA NA NA NA NA NA NA NA NA NA ... 465s - attr(*, "dimnames")=List of 3 465s ..$ : NULL 465s ..$ : chr [1:4] "2.5%" "5%" "95%" "97.5%" 465s ..$ : chr [1:5] "alpha" "radius" "manhattan" "d1" ... 465s Field #1 ('alpha') of 5... 465s Changepoint #1 of 3... 465s Changepoint #1 of 3...done 465s Changepoint #2 of 3... 465s Changepoint #2 of 3...done 465s Changepoint #3 of 3... 465s Changepoint #3 of 3...done 465s Field #1 ('alpha') of 5...done 465s Field #2 ('radius') of 5... 465s Changepoint #1 of 3... 465s Changepoint #1 of 3...done 465s Changepoint #2 of 3... 465s Changepoint #2 of 3...done 465s Changepoint #3 of 3... 465s Changepoint #3 of 3...done 465s Field #2 ('radius') of 5...done 465s Field #3 ('manhattan') of 5... 465s Changepoint #1 of 3... 465s Changepoint #1 of 3...done 465s Changepoint #2 of 3... 465s Changepoint #2 of 3...done 465s Changepoint #3 of 3... 465s Changepoint #3 of 3...done 465s Field #3 ('manhattan') of 5...done 465s Field #4 ('d1') of 5... 465s Changepoint #1 of 3... 465s Changepoint #1 of 3...done 465s Changepoint #2 of 3... 465s Changepoint #2 of 3...done 465s Changepoint #3 of 3... 465s Changepoint #3 of 3...done 465s Field #4 ('d1') of 5...done 465s Field #5 ('d2') of 5... 465s Changepoint #1 of 3... 465s Changepoint #1 of 3...done 465s Changepoint #2 of 3... 465s Changepoint #2 of 3...done 465s Changepoint #3 of 3... 465s Changepoint #3 of 3...done 465s Field #5 ('d2') of 5...done 465s Bootstrap statistics 465s num [1:3, 1:4, 1:5] NA NA -1.77 NA NA ... 465s - attr(*, "dimnames")=List of 3 465s ..$ : NULL 465s ..$ : chr [1:4] "2.5%" "5%" "95%" "97.5%" 465s ..$ : chr [1:5] "alpha" "radius" "manhattan" "d1" ... 465s Summarizing bootstrapped changepoint ('alpha', 'radius', 'manhattan', 'd1', 'd2') data...done 465s Resample (TCN,DH) signals and re-estimate summaries for segment & changepoint...done 465s > print(fit) 465s chromosome tcnId dhId start end tcnNbrOfLoci tcnMean tcnNbrOfSNPs 465s 1 1 1 1 554484 120992603 7586 1.3853 2108 465s 2 1 2 1 120992604 141510002 0 NA 0 465s 3 1 3 1 141510003 185449813 2681 2.0689 777 465s 4 1 4 1 185449813 247137334 4391 2.6341 1311 465s tcnNbrOfHets dhNbrOfLoci dhMean c1Mean c2Mean 465s 1 2108 2108 0.5116 0.3382903 1.047010 465s 2 0 NA NA NA NA 465s 3 777 777 0.0973 0.9337980 1.135102 465s 4 1311 1311 0.2295 1.0147870 1.619313 465s > plotTracks(fit) 465s > 465s > 465s > 465s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 465s > # Calling segments with run of homozygosity (ROH) 465s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 465s > fit <- callROH(fit, verbose=-10) 465s Calling ROH... 465s Segment #1 of 4... 465s Calling ROH for a single segment... 465s Number of SNPs: 7586 465s Calling ROH for a single segment...done 465s Segment #1 of 4...done 465s Segment #2 of 4... 465s Calling ROH for a single segment... 465s Number of SNPs: 0 465s Calling ROH for a single segment...done 465s Segment #2 of 4...done 465s Segment #3 of 4... 465s Calling ROH for a single segment... 465s Number of SNPs: 2681 465s Calling ROH for a single segment...done 465s Segment #3 of 4...done 465s Segment #4 of 4... 465s Calling ROH for a single segment... 465s Number of SNPs: 4391 465s Calling ROH for a single segment...done 465s Segment #4 of 4...done 465s ROH calls: 465s logi [1:4] FALSE NA FALSE FALSE 465s Mode FALSE NA's 465s logical 3 1 465s Calling ROH...done 465s > print(fit) 465s chromosome tcnId dhId start end tcnNbrOfLoci tcnMean tcnNbrOfSNPs 465s 1 1 1 1 554484 120992603 7586 1.3853 2108 465s 2 1 2 1 120992604 141510002 0 NA 0 465s 3 1 3 1 141510003 185449813 2681 2.0689 777 465s 4 1 4 1 185449813 247137334 4391 2.6341 1311 465s tcnNbrOfHets dhNbrOfLoci dhMean c1Mean c2Mean rohCall 465s 1 2108 2108 0.5116 0.3382903 1.047010 FALSE 465s 2 0 NA NA NA NA NA 465s 3 777 777 0.0973 0.9337980 1.135102 FALSE 465s 4 1311 1311 0.2295 1.0147870 1.619313 FALSE 465s > plotTracks(fit) 465s > 465s > 465s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 465s > # Estimate background 465s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 465s > kappa <- estimateKappa(fit, verbose=-10) 465s Estimate global background (including normal contamination and more)... 465s Number of segments: 3 465s Estimating threshold Delta0.5 from the empirical density of C1:s... 465s adjust: 1 465s minDensity: 0.2 465s ploidy: 2 465s All peaks: 465s type x density 465s 1 peak 0.3362194 1.101272 465s 3 peak 0.9811492 1.065711 465s C1=0 and C1=1 peaks: 465s type x density 465s 1 peak 0.3362194 1.101272 465s 3 peak 0.9811492 1.065711 465s Estimate of Delta0.5: 0.65868427808456 465s Estimating threshold Delta0.5 from the empirical density of C1:s...done 465s Number of segments with C1 < Delta0.5: 1 465s Estimate of kappa: 0.33829026 465s Estimate global background (including normal contamination and more)...done 465s Warning message: 465s In density.default(c1, weights = weights, adjust = adjust, from = from, : 465s Selecting bandwidth *not* using 'weights' 465s > print(kappa) 465s [1] 0.3382903 465s > ## [1] 0.226011 465s > 465s > 465s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 465s > # Calling segments in allelic balance (AB) 465s > # NOTE: Ideally, this should be done on whole-genome data 465s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 465s > # Explicitly estimate the threshold in DH for calling AB 465s > # (which be done by default by the caller, if skipped here) 465s > deltaAB <- estimateDeltaAB(fit, flavor="qq(DH)", verbose=-10) 465s Estimating DH threshold for calling allelic imbalances... 465s flavor: qq(DH) 465s scale: 1 465s Estimating DH threshold for AB caller... 465s quantile #1: 0.05 465s Symmetric quantile #2: 0.9 465s Number of segments: 3 465s Weighted 5% quantile of DH: 0.257710 465s Number of segments with small DH: 2 465s Number of data points: 7072 465s Number of finite data points: 2088 465s Estimate of (1-0.9):th and 50% quantiles: (0.0310411,0.163658) 465s Estimate of 0.9:th "symmetric" quantile: 0.296275 465s Estimating DH threshold for AB caller...done 465s Estimated delta: 0.296 465s Estimating DH threshold for calling allelic imbalances...done 465s > if (Sys.getenv("_R_CHECK_FULL_") == "") { 465s + # Ad hoc workaround for not utilizing all of the data 465s + # in the test, which results in a poor estimate 465s + deltaAB <- 0.165 465s + } 465s > print(deltaAB) 465s [1] 0.165 465s > ## [1] 0.1657131 465s > 465s > fit <- callAB(fit, delta=deltaAB, verbose=-10) 465s Calling segments of allelic balance from one-sided DH bootstrap confidence intervals... 465s delta (offset adjusting for bias in DH): 0.165 465s alpha (CI quantile; significance level): 0.05 465s Calling segments... 465s Number of segments called allelic balance (AB): 1 (25.00%) of 4 465s Calling segments...done 465s Calling segments of allelic balance from one-sided DH bootstrap confidence intervals...done 465s > print(fit) 465s chromosome tcnId dhId start end tcnNbrOfLoci tcnMean tcnNbrOfSNPs 465s 1 1 1 1 554484 120992603 7586 1.3853 2108 465s 2 1 2 1 120992604 141510002 0 NA 0 465s 3 1 3 1 141510003 185449813 2681 2.0689 777 465s 4 1 4 1 185449813 247137334 4391 2.6341 1311 465s tcnNbrOfHets dhNbrOfLoci dhMean c1Mean c2Mean rohCall abCall 465s 1 2108 2108 0.5116 0.3382903 1.047010 FALSE FALSE 465s 2 0 NA NA NA NA NA NA 465s 3 777 777 0.0973 0.9337980 1.135102 FALSE TRUE 465s 4 1311 1311 0.2295 1.0147870 1.619313 FALSE FALSE 465s > plotTracks(fit) 465s > 465s > # Even if not explicitly specified, the estimated 465s > # threshold parameter is returned by the caller 465s > stopifnot(fit$params$deltaAB == deltaAB) 465s > 465s > 465s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 465s > # Calling segments in loss-of-heterozygosity (LOH) 465s > # NOTE: Ideally, this should be done on whole-genome data 465s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 465s > # Explicitly estimate the threshold in C1 for calling LOH 465s > # (which be done by default by the caller, if skipped here) 465s > deltaLOH <- estimateDeltaLOH(fit, flavor="minC1|nonAB", verbose=-10) 465s Estimating DH threshold for calling LOH... 465s flavor: minC1|nonAB 465s Estimating DH threshold for calling LOH as the midpoint between guessed C1=0 and C1=1... 465s Argument 'midpoint': 0.5 465s Number of segments: 4 465s Number of segments in allelic balance: 1 (25.0%) of 4 465s Number of segments not in allelic balance: 2 (50.0%) of 4 465s Number of segments in allelic balance and TCN <= 3.00: 1 (25.0%) of 4 465s C: 2.07 465s Corrected C1 (=C/2): 1.03 465s Number of DHs: 777 465s Weights: 1 465s Weighted median of (corrected) C1 in allelic balance: 1.034 465s Smallest C1 among segments not in allelic balance: 0.338 465s There are 1 segments with in total 2108 heterozygous SNPs with this level. 465s Midpoint between the two: 0.686 465s Estimating DH threshold for calling LOH as the midpoint between guessed C1=0 and C1=1...done 465s delta: 0.686 465s Estimating DH threshold for calling LOH...done 465s > print(deltaLOH) 465s [1] 0.6863701 465s > ## [1] 0.625175 465s > 465s > fit <- callLOH(fit, delta=deltaLOH, verbose=-10) 465s Calling segments of allelic balance from one-sided DH bootstrap confidence intervals... 465s delta (offset adjusting for bias in C1): 0.68637013 465s alpha (CI quantile; significance level): 0.05 465s Calling segments... 465s Number of segments called low C1 (LowC1, "LOH_C1"): 1 (25.00%) of 4 465s Calling segments...done 465s Calling segments of allelic balance from one-sided DH bootstrap confidence intervals...done 465s > print(fit) 465s chromosome tcnId dhId start end tcnNbrOfLoci tcnMean tcnNbrOfSNPs 465s 1 1 1 1 554484 120992603 7586 1.3853 2108 465s 2 1 2 1 120992604 141510002 0 NA 0 465s 3 1 3 1 141510003 185449813 2681 2.0689 777 465s 4 1 4 1 185449813 247137334 4391 2.6341 1311 465s tcnNbrOfHets dhNbrOfLoci dhMean c1Mean c2Mean rohCall abCall lohCall 465s 1 2108 2108 0.5116 0.3382903 1.047010 FALSE FALSE TRUE 465s 2 0 NA NA NA NA NA NA NA 465s 3 777 777 0.0973 0.9337980 1.135102 FALSE TRUE FALSE 465s 4 1311 1311 0.2295 1.0147870 1.619313 FALSE FALSE FALSE 465s > plotTracks(fit) 465s > 465s > # Even if not explicitly specified, the estimated 465s > # threshold parameter is returned by the caller 465s > stopifnot(fit$params$deltaLOH == deltaLOH) 465s > 465s > 465s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 465s > # Calling segments that are gained, copy neutral, and lost 465s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 465s > fit <- callGNL(fit, verbose=-10) 465s Calling gain, neutral, and loss based TCNs of AB segments... 465s Calling neutral TCNs... 465s callCopyNeutralByTCNofAB... 465s Alpha: 0.05 465s Delta CN: 0.33085487 465s Calling copy-neutral segments... 465s Retrieve TCN confidence intervals for all segments... 465s Interval: [0.025,0.975] 465s Retrieve TCN confidence intervals for all segments...done 465s Estimating TCN confidence interval of copy-neutral AB segments... 465s calcStatsForCopyNeutralABs... 465s Identifying copy neutral AB segments... 465s Number of AB segments: 1 465s Identifying segments that are copy neutral states... 465s Number of segments in allelic balance: 1 465s Identifying segments that are copy neutral states...done 465s Number of copy-neutral AB segments: 1 465s Extracting all copy neutral AB segments across all chromosomes into one big segment... 465s chromosome tcnId dhId start end tcnNbrOfLoci tcnMean tcnNbrOfSNPs 465s 3 1 3 1 141510003 185449813 2681 2.0689 777 465s tcnNbrOfHets dhNbrOfLoci dhMean c1Mean c2Mean rohCall abCall lohCall 465s 3 777 777 0.0973 0.933798 1.135102 FALSE TRUE FALSE 465s Extracting all copy neutral AB segments across all chromosomes into one big segment...done 465s Identifying copy neutral AB segments...done 465s Bootstrap the identified copy-neutral states... 465s Bootstrap the identified copy-neutral states...done 465s tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets dhNbrOfLoci dhMean c1Mean 465s 3 2681 2.0689 777 777 777 0.0973 0.933798 465s c2Mean tcn_2.5% tcn_5% tcn_95% tcn_97.5% dh_2.5% dh_5% dh_95% 465s 3 1.135102 2.055164 2.057694 2.078831 2.081454 0.08974138 0.09080508 0.1035891 465s dh_97.5% c1_2.5% c1_5% c1_95% c1_97.5% c2_2.5% c2_5% c2_95% 465s 3 0.1050478 0.923788 0.925412 0.9417056 0.9433752 1.124908 1.126631 1.143571 465s c2_97.5% 465s 3 1.145214 465s calcStatsForCopyNeutralABs...done 465s Bootstrap statistics for copy-neutral AB segments: 465s tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets dhNbrOfLoci dhMean c1Mean 465s 3 2681 2.0689 777 777 777 0.0973 0.933798 465s c2Mean tcn_2.5% tcn_5% tcn_95% tcn_97.5% dh_2.5% dh_5% dh_95% 465s 3 1.135102 2.055164 2.057694 2.078831 2.081454 0.08974138 0.09080508 0.1035891 465s dh_97.5% c1_2.5% c1_5% c1_95% c1_97.5% c2_2.5% c2_5% c2_95% 465s 3 0.1050478 0.923788 0.925412 0.9417056 0.9433752 1.124908 1.126631 1.143571 465s c2_97.5% 465s 3 1.145214 465s [1] "TCN statistics:" 465s tcnMean tcn_2.5% tcn_5% tcn_95% tcn_97.5% 465s 2.068900 2.055164 2.057694 2.078831 2.081454 465s 95%-confidence interval of TCN mean for the copy-neutral state: [2.05516,2.08145] (mean=2.0689) 465s Estimating TCN confidence interval of copy-neutral AB segments...done 465s Identify all copy-neutral segments... 465s DeltaCN: +/-0.330855 465s Call ("acceptance") region: [1.72431,2.41231] 465s Total number of segments: 4 465s Number of segments called allelic balance: 1 465s Number of segments called copy neutral: 1 465s Number of AB segments called copy neutral: 1 465s Number of non-AB segments called copy neutral: 0 465s Identify all copy-neutral segments...done 465s Calling copy-neutral segments...done 465s callCopyNeutralByTCNofAB...done 465s Calling neutral TCNs...done 465s Number of NTCN calls: 1 (25.00%) of 4 465s Mean TCN of AB segments: 2.06831 465s Calling loss... 465s Number of loss calls: 1 (25.00%) of 4 465s Calling loss...done 465s Calling gain... 465s Number of loss calls: 1 (25.00%) of 4 465s Calling gain...done 465s Calling gain, neutral, and loss based TCNs of AB segments...done 465s Warning message: 465s In density.default(c1, weights = weights, adjust = adjust, from = from, : 465s Selecting bandwidth *not* using 'weights' 465s > print(fit) 465s chromosome tcnId dhId start end tcnNbrOfLoci tcnMean tcnNbrOfSNPs 465s 1 1 1 1 554484 120992603 7586 1.3853 2108 465s 2 1 2 1 120992604 141510002 0 NA 0 465s 3 1 3 1 141510003 185449813 2681 2.0689 777 465s 4 1 4 1 185449813 247137334 4391 2.6341 1311 465s tcnNbrOfHets dhNbrOfLoci dhMean c1Mean c2Mean rohCall abCall lohCall 465s 1 2108 2108 0.5116 0.3382903 1.047010 FALSE FALSE TRUE 465s 2 0 NA NA NA NA NA NA NA 465s 3 777 777 0.0973 0.9337980 1.135102 FALSE TRUE FALSE 465s 4 1311 1311 0.2295 1.0147870 1.619313 FALSE FALSE FALSE 465s ntcnCall lossCall gainCall 465s 1 FALSE TRUE FALSE 465s 2 NA NA NA 465s 3 TRUE FALSE FALSE 465s 4 FALSE FALSE TRUE 465s > plotTracks(fit) 465s > 465s > proc.time() 465s user system elapsed 465s 3.200 0.129 3.332 465s Test segmentByPairedPSCBS,calls passed 465s 0 465s Begin test segmentByPairedPSCBS,futures 475s + cat segmentByPairedPSCBS,futures.Rout 475s 475s R version 4.3.2 (2023-10-31) -- "Eye Holes" 475s Copyright (C) 2023 The R Foundation for Statistical Computing 475s Platform: x86_64-pc-linux-gnu (64-bit) 475s 475s R is free software and comes with ABSOLUTELY NO WARRANTY. 475s You are welcome to redistribute it under certain conditions. 475s Type 'license()' or 'licence()' for distribution details. 475s 475s R is a collaborative project with many contributors. 475s Type 'contributors()' for more information and 475s 'citation()' on how to cite R or R packages in publications. 475s 475s Type 'demo()' for some demos, 'help()' for on-line help, or 475s 'help.start()' for an HTML browser interface to help. 475s Type 'q()' to quit R. 475s 475s [Previously saved workspace restored] 475s 475s > library(PSCBS) 475s PSCBS v0.66.0 (2021-10-23 07:40:02 UTC) successfully loaded. See ?PSCBS for help. 475s 475s Attaching package: 'PSCBS' 475s 475s The following objects are masked from 'package:base': 475s 475s append, load 475s 475s > library(utils) 475s > 475s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 475s > # Load SNP microarray data 475s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 475s > data <- PSCBS::exampleData("paired.chr01") 475s > 475s > 475s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 475s > # Paired PSCBS segmentation 475s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 475s > # Drop single-locus outliers 475s > dataS <- dropSegmentationOutliers(data) 475s > 475s > # Run light-weight tests by default 475s > if (Sys.getenv("_R_CHECK_FULL_") == "") { 475s + # Use only every 5th data point 475s + dataS <- dataS[seq(from=1, to=nrow(data), by=5),] 475s + # Number of segments (for assertion) 475s + nSegs <- 4L 475s + } else { 475s + # Full tests 475s + nSegs <- 11L 475s + } 475s > 475s > str(dataS) 475s 'data.frame': 14670 obs. of 6 variables: 475s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 475s $ x : int 1145994 2941694 3710825 4240737 4276892 4464544 4714611 5095111 5034491 5158416 ... 475s $ CT : num 1.63 1.4 1.41 1.17 1.16 ... 475s $ betaT : num 0.7574 0.169 0.2357 0.2604 0.0576 ... 475s $ CN : num 2.36 2.13 2.26 2.01 2.32 ... 475s $ betaN : num 0.8274 0.5072 0.1671 0.1609 0.0421 ... 475s > 475s > 475s > ## Create multiple chromosomes 475s > data <- list() 475s > for (cc in 1:3) { 475s + dataS$chromosome <- cc 475s + data[[cc]] <- dataS 475s + } 475s > data <- Reduce(rbind, data) 475s > str(data) 475s 'data.frame': 44010 obs. of 6 variables: 475s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 475s $ x : int 1145994 2941694 3710825 4240737 4276892 4464544 4714611 5095111 5034491 5158416 ... 475s $ CT : num 1.63 1.4 1.41 1.17 1.16 ... 475s $ betaT : num 0.7574 0.169 0.2357 0.2604 0.0576 ... 475s $ CN : num 2.36 2.13 2.26 2.01 2.32 ... 475s $ betaN : num 0.8274 0.5072 0.1671 0.1609 0.0421 ... 475s > 475s > 475s > message("*** segmentByPairedPSCBS() via futures ...") 475s *** segmentByPairedPSCBS() via futures ... 475s > 475s > library("future") 475s > oplan <- plan() 475s > 475s > strategies <- c("sequential", "multisession") 475s > 475s > ## Test 'future.batchtools' futures? 475s > pkg <- "future.batchtools" 475s > if (require(pkg, character.only=TRUE)) { 475s + strategies <- c(strategies, "batchtools_local") 475s + } 475s Loading required package: future.batchtools 475s Warning message: 475s In library(package, lib.loc = lib.loc, character.only = TRUE, logical.return = TRUE, : 475s there is no package called 'future.batchtools' 475s > 475s > message("Future strategies to test: ", paste(sQuote(strategies), collapse=", ")) 475s Future strategies to test: 'sequential', 'multisession' 475s > 475s > fits <- list() 475s > for (strategy in strategies) { 475s + message(sprintf("- segmentByPairedPSCBS() using '%s' futures ...", strategy)) 475s + plan(strategy) 475s + fit <- segmentByPairedPSCBS(data, seed=0xBEEF, verbose=TRUE) 475s + fits[[strategy]] <- fit 475s + equal <- all.equal(fit, fits[[1]]) 475s + if (!equal) { 475s + str(fit) 475s + str(fits[[1]]) 475s + print(equal) 475s + stop(sprintf("segmentByPairedPSCBS() using '%s' futures does not produce the same results as when using '%s' futures", strategy, names(fits)[1])) 475s + } 475s + } 475s - segmentByPairedPSCBS() using 'sequential' futures ... 475s Segmenting paired tumor-normal signals using Paired PSCBS... 475s Calling genotypes from normal allele B fractions... 475s num [1:44010] 0.8274 0.5072 0.1671 0.1609 0.0421 ... 475s Called genotypes: 475s num [1:44010] 1 0.5 0 0 0 0 1 0 1 0.5 ... 475s - attr(*, "modelFit")=List of 1 475s ..$ :List of 7 475s .. ..$ flavor : chr "density" 475s .. ..$ cn : int 2 475s .. ..$ nbrOfGenotypeGroups: int 3 475s .. ..$ tau : num [1:2] 0.312 0.678 475s .. ..$ n : int 43920 475s .. ..$ fit :Classes 'PeaksAndValleys' and 'data.frame': 5 obs. of 3 variables: 475s .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 475s .. .. ..$ x : num [1:5] 0.0999 0.312 0.4986 0.6775 0.8922 475s .. .. ..$ density: num [1:5] 1.623 0.465 1.126 0.497 1.588 475s .. ..$ fitValleys :Classes 'PeaksAndValleys' and 'data.frame': 2 obs. of 3 variables: 475s .. .. ..$ type : chr [1:2] "valley" "valley" 475s .. .. ..$ x : num [1:2] 0.312 0.678 475s .. .. ..$ density: num [1:2] 0.465 0.497 475s ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 475s muN 475s 0 0.5 1 475s 15627 12633 15750 475s Calling genotypes from normal allele B fractions...done 475s Normalizing betaT using betaN (TumorBoost)... 475s Normalized BAFs: 475s num [1:44010] 0.9301 0.1667 0.0685 0.0995 0.0155 ... 475s - attr(*, "modelFit")=List of 5 475s ..$ method : chr "normalizeTumorBoost" 475s ..$ flavor : chr "v4" 475s ..$ delta : num [1:44010] -0.17264 0.00239 0.1671 0.16085 0.04213 ... 475s .. ..- attr(*, "modelFit")=List of 1 475s .. .. ..$ :List of 7 475s .. .. .. ..$ flavor : chr "density" 475s .. .. .. ..$ cn : int 2 475s .. .. .. ..$ nbrOfGenotypeGroups: int 3 475s .. .. .. ..$ tau : num [1:2] 0.312 0.678 475s .. .. .. ..$ n : int 43920 475s .. .. .. ..$ fit :Classes 'PeaksAndValleys' and 'data.frame': 5 obs. of 3 variables: 475s .. .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 475s .. .. .. .. ..$ x : num [1:5] 0.0999 0.312 0.4986 0.6775 0.8922 475s .. .. .. .. ..$ density: num [1:5] 1.623 0.465 1.126 0.497 1.588 475s .. .. .. ..$ fitValleys :Classes 'PeaksAndValleys' and 'data.frame': 2 obs. of 3 variables: 475s .. .. .. .. ..$ type : chr [1:2] "valley" "valley" 475s .. .. .. .. ..$ x : num [1:2] 0.312 0.678 475s .. .. .. .. ..$ density: num [1:2] 0.465 0.497 475s .. .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 475s ..$ preserveScale: logi FALSE 475s ..$ scaleFactor : num NA 475s Normalizing betaT using betaN (TumorBoost)...done 475s Setup up data... 475s 'data.frame': 44010 obs. of 7 variables: 475s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 475s $ x : num 1145994 2941694 3710825 4240737 4276892 ... 475s $ CT : num 1.63 1.4 1.41 1.17 1.16 ... 475s $ betaT : num 0.7574 0.169 0.2357 0.2604 0.0576 ... 475s $ betaTN : num 0.9301 0.1667 0.0685 0.0995 0.0155 ... 475s ..- attr(*, "modelFit")=List of 5 475s .. ..$ method : chr "normalizeTumorBoost" 475s .. ..$ flavor : chr "v4" 475s .. ..$ delta : num [1:44010] -0.17264 0.00239 0.1671 0.16085 0.04213 ... 475s .. .. ..- attr(*, "modelFit")=List of 1 475s .. .. .. ..$ :List of 7 475s .. .. .. .. ..$ flavor : chr "density" 475s .. .. .. .. ..$ cn : int 2 475s .. .. .. .. ..$ nbrOfGenotypeGroups: int 3 475s .. .. .. .. ..$ tau : num [1:2] 0.312 0.678 475s .. .. .. .. ..$ n : int 43920 475s .. .. .. .. ..$ fit :Classes 'PeaksAndValleys' and 'data.frame': 5 obs. of 3 variables: 475s .. .. .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 475s .. .. .. .. .. ..$ x : num [1:5] 0.0999 0.312 0.4986 0.6775 0.8922 475s .. .. .. .. .. ..$ density: num [1:5] 1.623 0.465 1.126 0.497 1.588 475s .. .. .. .. ..$ fitValleys :Classes 'PeaksAndValleys' and 'data.frame': 2 obs. of 3 variables: 475s .. .. .. .. .. ..$ type : chr [1:2] "valley" "valley" 475s .. .. .. .. .. ..$ x : num [1:2] 0.312 0.678 475s .. .. .. .. .. ..$ density: num [1:2] 0.465 0.497 475s .. .. .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 475s .. ..$ preserveScale: logi FALSE 475s .. ..$ scaleFactor : num NA 475s $ betaN : num 0.8274 0.5072 0.1671 0.1609 0.0421 ... 475s $ muN : num 1 0.5 0 0 0 0 1 0 1 0.5 ... 475s ..- attr(*, "modelFit")=List of 1 475s .. ..$ :List of 7 475s .. .. ..$ flavor : chr "density" 475s .. .. ..$ cn : int 2 475s .. .. ..$ nbrOfGenotypeGroups: int 3 475s .. .. ..$ tau : num [1:2] 0.312 0.678 475s .. .. ..$ n : int 43920 475s .. .. ..$ fit :Classes 'PeaksAndValleys' and 'data.frame': 5 obs. of 3 variables: 475s .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 475s .. .. .. ..$ x : num [1:5] 0.0999 0.312 0.4986 0.6775 0.8922 475s .. .. .. ..$ density: num [1:5] 1.623 0.465 1.126 0.497 1.588 475s .. .. ..$ fitValleys :Classes 'PeaksAndValleys' and 'data.frame': 2 obs. of 3 variables: 475s .. .. .. ..$ type : chr [1:2] "valley" "valley" 475s .. .. .. ..$ x : num [1:2] 0.312 0.678 475s .. .. .. ..$ density: num [1:2] 0.465 0.497 475s .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 475s Setup up data...done 475s Dropping loci for which TCNs are missing... 475s Number of loci dropped: 36 475s Dropping loci for which TCNs are missing...done 475s Ordering data along genome... 475s 'data.frame': 43974 obs. of 7 variables: 475s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 475s $ x : num 554484 730720 782343 878522 916294 ... 475s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 475s $ betaT : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 475s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 475s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 475s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 475s Ordering data along genome...done 475s Segmenting multiple chromosomes... 475s Number of chromosomes: 3 475s Random seed temporarily set (seed=c(48879), kind="L'Ecuyer-CMRG") 475s Produced 3 seeds from this stream for future usage 475s Chromosome #1 ('Chr01') of 3... 475s 'data.frame': 14658 obs. of 8 variables: 475s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 475s $ x : num 554484 730720 782343 878522 916294 ... 475s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 475s $ betaT : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 475s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 475s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 475s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 475s $ index : int 1 2 3 4 5 6 7 8 9 10 ... 475s Known segments: 475s [1] chromosome start end 475s <0 rows> (or 0-length row.names) 475s Segmenting paired tumor-normal signals using Paired PSCBS... 475s Setup up data... 475s 'data.frame': 14658 obs. of 7 variables: 475s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 475s $ x : num 554484 730720 782343 878522 916294 ... 475s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 475s $ betaT : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 475s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 475s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 475s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 475s Setup up data...done 475s Ordering data along genome... 475s 'data.frame': 14658 obs. of 7 variables: 475s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 475s $ x : num 554484 730720 782343 878522 916294 ... 475s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 475s $ betaT : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 475s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 475s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 475s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 475s Ordering data along genome...done 475s Keeping only current chromosome for 'knownSegments'... 475s Chromosome: 1 475s Known segments for this chromosome: 475s [1] chromosome start end 475s <0 rows> (or 0-length row.names) 475s Keeping only current chromosome for 'knownSegments'...done 475s alphaTCN: 0.009 475s alphaDH: 0.001 475s Number of loci: 14658 475s Calculating DHs... 475s Number of SNPs: 14658 475s Number of heterozygous SNPs: 4209 (28.71%) 475s Normalized DHs: 475s num [1:14658] NA NA NA NA NA ... 475s Calculating DHs...done 475s Random seed temporarily set (seed=c(10407, 1066287653, -51199871, 161854402, -1995183193, 1503453565, -747102133), kind="L'Ecuyer-CMRG") 475s Produced 2 seeds from this stream for future usage 475s Identification of change points by total copy numbers... 475s Segmenting by CBS... 475s Chromosome: 1 475s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 475s Segmenting by CBS...done 475s List of 4 475s $ data :'data.frame': 14658 obs. of 4 variables: 475s ..$ chromosome: int [1:14658] 1 1 1 1 1 1 1 1 1 1 ... 475s ..$ x : num [1:14658] 554484 730720 782343 878522 916294 ... 475s ..$ y : num [1:14658] 1.88 1.8 1.59 1.64 1.53 ... 475s ..$ index : int [1:14658] 1 2 3 4 5 6 7 8 9 10 ... 475s $ output :'data.frame': 3 obs. of 6 variables: 475s ..$ sampleName: chr [1:3] NA NA NA 475s ..$ chromosome: int [1:3] 1 1 1 475s ..$ start : num [1:3] 5.54e+05 1.44e+08 1.85e+08 475s ..$ end : num [1:3] 1.44e+08 1.85e+08 2.47e+08 475s ..$ nbrOfLoci : int [1:3] 7599 2668 4391 475s ..$ mean : num [1:3] 1.39 2.07 2.63 475s $ segRows:'data.frame': 3 obs. of 2 variables: 475s ..$ startRow: int [1:3] 1 7600 10268 475s ..$ endRow : int [1:3] 7599 10267 14658 475s $ params :List of 5 475s ..$ alpha : num 0.009 475s ..$ undo : num 0 475s ..$ joinSegments : logi TRUE 475s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 475s .. ..$ chromosome: int 1 475s .. ..$ start : num -Inf 475s .. ..$ end : num Inf 475s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 475s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 475s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.412 0 0.412 0 0 475s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 475s - attr(*, "pkgDetails")= chr "DNAcopy v1.76.0" 475s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 475s Identification of change points by total copy numbers...done 475s Restructure TCN segmentation results... 475s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean 475s 1 1 554484 143926517 7599 1.3859 475s 2 1 143926517 185449813 2668 2.0704 475s 3 1 185449813 247137334 4391 2.6341 475s Number of TCN segments: 3 475s Restructure TCN segmentation results...done 475s Total CN segment #1 ([ 554484,1.43927e+08]) of 3... 475s Number of TCN loci in segment: 7599 475s Locus data for TCN segment: 475s 'data.frame': 7599 obs. of 9 variables: 475s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 475s $ x : num 554484 730720 782343 878522 916294 ... 475s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 475s $ betaT : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 475s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 475s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 475s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 475s $ index : int 1 2 3 4 5 6 7 8 9 10 ... 475s $ rho : num NA NA NA NA NA ... 475s Number of loci: 7599 475s Number of SNPs: 2120 (27.90%) 475s Number of heterozygous SNPs: 2120 (100.00%) 475s Chromosome: 1 475s Segmenting DH signals... 475s Segmenting by CBS... 475s Chromosome: 1 475s Random seed temporarily set (seed=c(10407, -821273412, -52578226, 1415511586, 721384351, -665928286, 1316562960), kind="L'Ecuyer-CMRG") 475s Segmenting by CBS...done 475s List of 4 475s $ data :'data.frame': 7599 obs. of 4 variables: 475s ..$ chromosome: int [1:7599] 1 1 1 1 1 1 1 1 1 1 ... 475s ..$ x : num [1:7599] 554484 730720 782343 878522 916294 ... 475s ..$ y : num [1:7599] NA NA NA NA NA ... 475s ..$ index : int [1:7599] 1 2 3 4 5 6 7 8 9 10 ... 475s $ output :'data.frame': 1 obs. of 6 variables: 475s ..$ sampleName: chr NA 475s ..$ chromosome: int 1 475s ..$ start : num 554484 475s ..$ end : num 1.44e+08 475s ..$ nbrOfLoci : int 2120 475s ..$ mean : num 0.51 475s $ segRows:'data.frame': 1 obs. of 2 variables: 475s ..$ startRow: int 10 475s ..$ endRow : int 7594 475s $ params :List of 5 475s ..$ alpha : num 0.001 475s ..$ undo : num 0 475s ..$ joinSegments : logi TRUE 475s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 475s .. ..$ chromosome: int 1 475s .. ..$ start : num 554484 475s .. ..$ end : num 1.44e+08 475s ..$ seed : int [1:7] 10407 -821273412 -52578226 1415511586 721384351 -665928286 1316562960 475s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 475s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.023 0 0.023 0 0 475s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 475s - attr(*, "pkgDetails")= chr "DNAcopy v1.76.0" 475s - attr(*, "randomSeed")= int [1:7] 10407 -821273412 -52578226 1415511586 721384351 -665928286 1316562960 475s DH segmentation (locally-indexed) rows: 475s startRow endRow 475s 1 10 7594 475s int [1:7599] 1 2 3 4 5 6 7 8 9 10 ... 475s DH segmentation rows: 475s startRow endRow 475s 1 10 7594 475s Segmenting DH signals...done 475s DH segmentation table: 475s dhStart dhEnd dhNbrOfLoci dhMean 475s 1 554484 143926517 2120 0.5101 475s startRow endRow 475s 1 10 7594 475s Rows: 475s [1] 1 475s TCN segmentation rows: 475s startRow endRow 475s 1 1 7599 475s TCN and DH segmentation rows: 475s startRow endRow 475s 1 1 7599 475s startRow endRow 475s 1 10 7594 475s NULL 475s TCN segmentation (expanded) rows: 475s startRow endRow 475s 1 1 7599 475s TCN and DH segmentation rows: 475s startRow endRow 475s 1 1 7599 475s 2 7600 10267 475s 3 10268 14658 475s startRow endRow 475s 1 10 7594 475s startRow endRow 475s 1 1 7599 475s Total CN segmentation table (expanded): 475s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 475s 1 1 554484 143926517 7599 1.3859 2120 2120 475s (TCN,DH) segmentation for one total CN segment: 475s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 475s 1 1 1 1 554484 143926517 7599 1.3859 2120 475s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 475s 1 2120 554484 143926517 2120 0.5101 475s Total CN segment #1 ([ 554484,1.43927e+08]) of 3...done 475s Total CN segment #2 ([1.43927e+08,1.8545e+08]) of 3... 475s Number of TCN loci in segment: 2668 475s Locus data for TCN segment: 475s 'data.frame': 2668 obs. of 9 variables: 475s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 475s $ x : num 1.44e+08 1.44e+08 1.44e+08 1.44e+08 1.44e+08 ... 475s $ CT : num 2.1 2.1 2.09 1.8 2.34 ... 475s $ betaT : num 0.027542 1.030222 1.094093 0.046763 -0.000948 ... 475s $ betaTN : num 0.027542 1.030222 1.094093 0.046763 -0.000948 ... 475s $ betaN : num 0.1624 0.8788 0.8225 0.1201 0.0317 ... 475s $ muN : num 0 1 1 0 0 1 0 0 0 0 ... 475s $ index : int 7600 7601 7602 7603 7604 7605 7606 7607 7608 7609 ... 475s $ rho : num NA NA NA NA NA NA NA NA NA NA ... 475s Number of loci: 2668 475s Number of SNPs: 775 (29.05%) 475s Number of heterozygous SNPs: 775 (100.00%) 475s Chromosome: 1 475s Segmenting DH signals... 475s Segmenting by CBS... 475s Chromosome: 1 475s Random seed temporarily set (seed=c(10407, -821273412, -52578226, 1415511586, 721384351, -665928286, 1316562960), kind="L'Ecuyer-CMRG") 475s Segmenting by CBS...done 475s List of 4 475s $ data :'data.frame': 2668 obs. of 4 variables: 475s ..$ chromosome: int [1:2668] 1 1 1 1 1 1 1 1 1 1 ... 475s ..$ x : num [1:2668] 1.44e+08 1.44e+08 1.44e+08 1.44e+08 1.44e+08 ... 475s ..$ y : num [1:2668] NA NA NA NA NA NA NA NA NA NA ... 475s ..$ index : int [1:2668] 1 2 3 4 5 6 7 8 9 10 ... 475s $ output :'data.frame': 1 obs. of 6 variables: 475s ..$ sampleName: chr NA 475s ..$ chromosome: int 1 475s ..$ start : num 1.44e+08 475s ..$ end : num 1.85e+08 475s ..$ nbrOfLoci : int 775 475s ..$ mean : num 0.097 475s $ segRows:'data.frame': 1 obs. of 2 variables: 475s ..$ startRow: int 15 475s ..$ endRow : int 2664 475s $ params :List of 5 475s ..$ alpha : num 0.001 475s ..$ undo : num 0 475s ..$ joinSegments : logi TRUE 475s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 475s .. ..$ chromosome: int 1 475s .. ..$ start : num 1.44e+08 475s .. ..$ end : num 1.85e+08 475s ..$ seed : int [1:7] 10407 -821273412 -52578226 1415511586 721384351 -665928286 1316562960 475s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 475s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.007 0 0.008 0 0 475s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 475s - attr(*, "pkgDetails")= chr "DNAcopy v1.76.0" 475s - attr(*, "randomSeed")= int [1:7] 10407 -821273412 -52578226 1415511586 721384351 -665928286 1316562960 475s DH segmentation (locally-indexed) rows: 475s startRow endRow 475s 1 15 2664 475s int [1:2668] 7600 7601 7602 7603 7604 7605 7606 7607 7608 7609 ... 475s DH segmentation rows: 475s startRow endRow 475s 1 7614 10263 475s Segmenting DH signals...done 475s DH segmentation table: 475s dhStart dhEnd dhNbrOfLoci dhMean 475s 1 143926517 185449813 775 0.097 475s startRow endRow 475s 1 7614 10263 475s Rows: 475s [1] 2 475s TCN segmentation rows: 475s startRow endRow 475s 2 7600 10267 475s TCN and DH segmentation rows: 475s startRow endRow 475s 2 7600 10267 475s startRow endRow 475s 1 7614 10263 475s startRow endRow 475s 1 1 7599 475s TCN segmentation (expanded) rows: 475s startRow endRow 475s 1 1 7599 475s 2 7600 10267 475s TCN and DH segmentation rows: 475s startRow endRow 475s 1 1 7599 475s 2 7600 10267 475s 3 10268 14658 475s startRow endRow 475s 1 10 7594 475s 2 7614 10263 475s startRow endRow 475s 1 1 7599 475s 2 7600 10267 475s Total CN segmentation table (expanded): 475s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 475s 2 1 143926517 185449813 2668 2.0704 775 775 475s (TCN,DH) segmentation for one total CN segment: 475s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 475s 2 2 1 1 143926517 185449813 2668 2.0704 775 475s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 475s 2 775 143926517 185449813 775 0.097 475s Total CN segment #2 ([1.43927e+08,1.8545e+08]) of 3...done 475s Total CN segment #3 ([1.8545e+08,2.47137e+08]) of 3... 475s Number of TCN loci in segment: 4391 475s Locus data for TCN segment: 475s 'data.frame': 4391 obs. of 9 variables: 475s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 475s $ x : num 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 475s $ CT : num 2.93 2.15 2.82 2.93 2.46 ... 475s $ betaT : num -0.169 0.609 1.028 0.525 0.968 ... 475s $ betaTN : num -0.169 0.609 1.028 0.525 0.968 ... 475s $ betaN : num 0.25 0.38 0.919 0.34 0.783 ... 475s $ muN : num 0 0.5 1 0.5 1 1 0 1 0 1 ... 475s $ index : int 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 475s $ rho : num NA 0.2186 NA 0.0503 NA ... 475s Number of loci: 4391 475s Number of SNPs: 1314 (29.92%) 475s Number of heterozygous SNPs: 1314 (100.00%) 475s Chromosome: 1 475s Segmenting DH signals... 475s Segmenting by CBS... 475s Chromosome: 1 475s Random seed temporarily set (seed=c(10407, -821273412, -52578226, 1415511586, 721384351, -665928286, 1316562960), kind="L'Ecuyer-CMRG") 475s Segmenting by CBS...done 475s List of 4 475s $ data :'data.frame': 4391 obs. of 4 variables: 475s ..$ chromosome: int [1:4391] 1 1 1 1 1 1 1 1 1 1 ... 475s ..$ x : num [1:4391] 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 475s ..$ y : num [1:4391] NA 0.2186 NA 0.0503 NA ... 475s ..$ index : int [1:4391] 1 2 3 4 5 6 7 8 9 10 ... 475s $ output :'data.frame': 1 obs. of 6 variables: 475s ..$ sampleName: chr NA 475s ..$ chromosome: int 1 475s ..$ start : num 1.85e+08 475s ..$ end : num 2.47e+08 475s ..$ nbrOfLoci : int 1314 475s ..$ mean : num 0.23 475s $ segRows:'data.frame': 1 obs. of 2 variables: 475s ..$ startRow: int 2 475s ..$ endRow : int 4388 475s $ params :List of 5 475s ..$ alpha : num 0.001 475s ..$ undo : num 0 475s ..$ joinSegments : logi TRUE 475s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 475s .. ..$ chromosome: int 1 475s .. ..$ start : num 1.85e+08 475s .. ..$ end : num 2.47e+08 475s ..$ seed : int [1:7] 10407 -821273412 -52578226 1415511586 721384351 -665928286 1316562960 475s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 475s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.012 0 0.013 0 0 475s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 475s - attr(*, "pkgDetails")= chr "DNAcopy v1.76.0" 475s - attr(*, "randomSeed")= int [1:7] 10407 -821273412 -52578226 1415511586 721384351 -665928286 1316562960 475s DH segmentation (locally-indexed) rows: 475s startRow endRow 475s 1 2 4388 475s int [1:4391] 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 475s DH segmentation rows: 475s startRow endRow 475s 1 10269 14655 475s Segmenting DH signals...done 475s DH segmentation table: 475s dhStart dhEnd dhNbrOfLoci dhMean 475s 1 185449813 247137334 1314 0.2295 475s startRow endRow 475s 1 10269 14655 475s Rows: 475s [1] 3 475s TCN segmentation rows: 475s startRow endRow 475s 3 10268 14658 475s TCN and DH segmentation rows: 475s startRow endRow 475s 3 10268 14658 475s startRow endRow 475s 1 10269 14655 475s startRow endRow 475s 1 1 7599 475s 2 7600 10267 475s TCN segmentation (expanded) rows: 475s startRow endRow 475s 1 1 7599 475s 2 7600 10267 475s 3 10268 14658 475s TCN and DH segmentation rows: 475s startRow endRow 475s 1 1 7599 475s 2 7600 10267 475s 3 10268 14658 475s startRow endRow 475s 1 10 7594 475s 2 7614 10263 475s 3 10269 14655 475s startRow endRow 475s 1 1 7599 475s 2 7600 10267 475s 3 10268 14658 475s Total CN segmentation table (expanded): 475s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 475s 3 1 185449813 247137334 4391 2.6341 1314 1314 475s (TCN,DH) segmentation for one total CN segment: 475s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 475s 3 3 1 1 185449813 247137334 4391 2.6341 1314 475s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 475s 3 1314 185449813 247137334 1314 0.2295 475s Total CN segment #3 ([1.8545e+08,2.47137e+08]) of 3...done 475s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 475s 1 1 1 1 554484 143926517 7599 1.3859 2120 475s 2 1 2 1 143926517 185449813 2668 2.0704 775 475s 3 1 3 1 185449813 247137334 4391 2.6341 1314 475s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 475s 1 2120 554484 143926517 2120 0.5101 475s 2 775 143926517 185449813 775 0.0970 475s 3 1314 185449813 247137334 1314 0.2295 475s Calculating (C1,C2) per segment... 475s Calculating (C1,C2) per segment...done 475s Number of segments: 3 475s Segmenting paired tumor-normal signals using Paired PSCBS...done 475s Post-segmenting TCNs... 475s Number of segments: 3 475s Number of chromosomes: 1 475s [1] 1 475s Chromosome 1 ('chr01') of 1... 475s Rows: 475s [1] 1 2 3 475s Number of segments: 3 475s TCN segment #1 ('1') of 3... 475s Nothing todo. Only one DH segmenta+ [ 0 != 0 ] 475s + echo Test segmentByPairedPSCBS,futures passed 475s + echo 0 475s + echo Begin test segmentByPairedPSCBS,noNormalBAFs 475s + exitcode=0 475s + R CMD BATCH segmentByPairedPSCBS,noNormalBAFs.R 475s tion. Skipping. 475s TCN segment #1 ('1') of 3...done 475s TCN segment #2 ('2') of 3... 475s Nothing todo. Only one DH segmentation. Skipping. 475s TCN segment #2 ('2') of 3...done 475s TCN segment #3 ('3') of 3... 475s Nothing todo. Only one DH segmentation. Skipping. 475s TCN segment #3 ('3') of 3...done 475s Chromosome 1 ('chr01') of 1...done 475s Update (C1,C2) per segment... 475s Update (C1,C2) per segment...done 475s Post-segmenting TCNs...done 475s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 475s 1 1 1 1 554484 143926517 7599 1.3859 2120 475s 2 1 2 1 143926517 185449813 2668 2.0704 775 475s 3 1 3 1 185449813 247137334 4391 2.6341 1314 475s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 475s 1 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 475s 2 775 143926517 185449813 775 0.0970 0.9347856 1.135614 475s 3 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 475s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 475s 1 1 1 1 554484 143926517 7599 1.3859 2120 475s 2 1 2 1 143926517 185449813 2668 2.0704 775 475s 3 1 3 1 185449813 247137334 4391 2.6341 1314 475s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 475s 1 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 475s 2 775 143926517 185449813 775 0.0970 0.9347856 1.135614 475s 3 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 475s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 475s 1 1 1 1 554484 143926517 7599 1.3859 2120 475s 2 1 2 1 143926517 185449813 2668 2.0704 775 475s 3 1 3 1 185449813 247137334 4391 2.6341 1314 475s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 475s 1 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 475s 2 775 143926517 185449813 775 0.0970 0.9347856 1.135614 475s 3 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 475s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 475s 1 1 1 1 554484 143926517 7599 1.3859 2120 475s 2 1 2 1 143926517 185449813 2668 2.0704 775 475s 3 1 3 1 185449813 247137334 4391 2.6341 1314 475s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 475s 1 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 475s 2 775 143926517 185449813 775 0.0970 0.9347856 1.135614 475s 3 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 475s Chromosome #1 ('Chr01') of 3...done 475s Chromosome #2 ('Chr02') of 3... 475s 'data.frame': 14658 obs. of 8 variables: 475s $ chromosome: int 2 2 2 2 2 2 2 2 2 2 ... 475s $ x : num 554484 730720 782343 878522 916294 ... 475s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 475s $ betaT : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 475s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 475s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 475s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 475s $ index : int 14659 14660 14661 14662 14663 14664 14665 14666 14667 14668 ... 475s Known segments: 475s [1] chromosome start end 475s <0 rows> (or 0-length row.names) 475s Segmenting paired tumor-normal signals using Paired PSCBS... 475s Setup up data... 475s 'data.frame': 14658 obs. of 7 variables: 475s $ chromosome: int 2 2 2 2 2 2 2 2 2 2 ... 475s $ x : num 554484 730720 782343 878522 916294 ... 475s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 475s $ betaT : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 475s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 475s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 475s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 475s Setup up data...done 475s Ordering data along genome... 475s 'data.frame': 14658 obs. of 7 variables: 475s $ chromosome: int 2 2 2 2 2 2 2 2 2 2 ... 475s $ x : num 554484 730720 782343 878522 916294 ... 475s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 475s $ betaT : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 475s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 475s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 475s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 475s Ordering data along genome...done 475s Keeping only current chromosome for 'knownSegments'... 475s Chromosome: 2 475s Known segments for this chromosome: 475s [1] chromosome start end 475s <0 rows> (or 0-length row.names) 475s Keeping only current chromosome for 'knownSegments'...done 475s alphaTCN: 0.009 475s alphaDH: 0.001 475s Number of loci: 14658 475s Calculating DHs... 475s Number of SNPs: 14658 475s Number of heterozygous SNPs: 4209 (28.71%) 475s Normalized DHs: 475s num [1:14658] NA NA NA NA NA ... 475s Calculating DHs...done 475s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 475s Produced 2 seeds from this stream for future usage 475s Identification of change points by total copy numbers... 475s Segmenting by CBS... 475s Chromosome: 2 475s Random seed temporarily set (seed=c(10407, -821273412, -52578226, 1415511586, 721384351, -665928286, 1316562960), kind="L'Ecuyer-CMRG") 475s Segmenting by CBS...done 475s List of 4 475s $ data :'data.frame': 14658 obs. of 4 variables: 475s ..$ chromosome: int [1:14658] 2 2 2 2 2 2 2 2 2 2 ... 475s ..$ x : num [1:14658] 554484 730720 782343 878522 916294 ... 475s ..$ y : num [1:14658] 1.88 1.8 1.59 1.64 1.53 ... 475s ..$ index : int [1:14658] 1 2 3 4 5 6 7 8 9 10 ... 475s $ output :'data.frame': 3 obs. of 6 variables: 475s ..$ sampleName: chr [1:3] NA NA NA 475s ..$ chromosome: int [1:3] 2 2 2 475s ..$ start : num [1:3] 5.54e+05 1.44e+08 1.85e+08 475s ..$ end : num [1:3] 1.44e+08 1.85e+08 2.47e+08 475s ..$ nbrOfLoci : int [1:3] 7599 2668 4391 475s ..$ mean : num [1:3] 1.39 2.07 2.63 475s $ segRows:'data.frame': 3 obs. of 2 variables: 475s ..$ startRow: int [1:3] 1 7600 10268 475s ..$ endRow : int [1:3] 7599 10267 14658 475s $ params :List of 5 475s ..$ alpha : num 0.009 475s ..$ undo : num 0 475s ..$ joinSegments : logi TRUE 475s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 475s .. ..$ chromosome: int 2 475s .. ..$ start : num -Inf 475s .. ..$ end : num Inf 475s ..$ seed : int [1:7] 10407 -821273412 -52578226 1415511586 721384351 -665928286 1316562960 475s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 475s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.438 0 0.438 0 0 475s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 475s - attr(*, "pkgDetails")= chr "DNAcopy v1.76.0" 475s - attr(*, "randomSeed")= int [1:7] 10407 -821273412 -52578226 1415511586 721384351 -665928286 1316562960 475s Identification of change points by total copy numbers...done 475s Restructure TCN segmentation results... 475s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean 475s 1 2 554484 143926517 7599 1.3859 475s 2 2 143926517 185449813 2668 2.0704 475s 3 2 185449813 247137334 4391 2.6341 475s Number of TCN segments: 3 475s Restructure TCN segmentation results...done 475s Total CN segment #1 ([ 554484,1.43927e+08]) of 3... 475s Number of TCN loci in segment: 7599 475s Locus data for TCN segment: 475s 'data.frame': 7599 obs. of 9 variables: 475s $ chromosome: int 2 2 2 2 2 2 2 2 2 2 ... 475s $ x : num 554484 730720 782343 878522 916294 ... 475s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 475s $ betaT : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 475s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 475s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 475s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 475s $ index : int 1 2 3 4 5 6 7 8 9 10 ... 475s $ rho : num NA NA NA NA NA ... 475s Number of loci: 7599 475s Number of SNPs: 2120 (27.90%) 475s Number of heterozygous SNPs: 2120 (100.00%) 475s Chromosome: 2 475s Segmenting DH signals... 475s Segmenting by CBS... 475s Chromosome: 2 475s Random seed temporarily set (seed=c(10407, -1924040949, -1632234809, -437763632, -1464377300, 676654412, 2080370711), kind="L'Ecuyer-CMRG") 475s Segmenting by CBS...done 475s List of 4 475s $ data :'data.frame': 7599 obs. of 4 variables: 475s ..$ chromosome: int [1:7599] 2 2 2 2 2 2 2 2 2 2 ... 475s ..$ x : num [1:7599] 554484 730720 782343 878522 916294 ... 475s ..$ y : num [1:7599] NA NA NA NA NA ... 475s ..$ index : int [1:7599] 1 2 3 4 5 6 7 8 9 10 ... 475s $ output :'data.frame': 1 obs. of 6 variables: 475s ..$ sampleName: chr NA 475s ..$ chromosome: int 2 475s ..$ start : num 554484 475s ..$ end : num 1.44e+08 475s ..$ nbrOfLoci : int 2120 475s ..$ mean : num 0.51 475s $ segRows:'data.frame': 1 obs. of 2 variables: 475s ..$ startRow: int 10 475s ..$ endRow : int 7594 475s $ params :List of 5 475s ..$ alpha : num 0.001 475s ..$ undo : num 0 475s ..$ joinSegments : logi TRUE 475s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 475s .. ..$ chromosome: int 2 475s .. ..$ start : num 554484 475s .. ..$ end : num 1.44e+08 475s ..$ seed : int [1:7] 10407 -1924040949 -1632234809 -437763632 -1464377300 676654412 2080370711 475s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 475s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.024 0 0.024 0 0 475s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 475s - attr(*, "pkgDetails")= chr "DNAcopy v1.76.0" 475s - attr(*, "randomSeed")= int [1:7] 10407 -1924040949 -1632234809 -437763632 -1464377300 676654412 2080370711 475s DH segmentation (locally-indexed) rows: 475s startRow endRow 475s 1 10 7594 475s int [1:7599] 1 2 3 4 5 6 7 8 9 10 ... 475s DH segmentation rows: 475s startRow endRow 475s 1 10 7594 475s Segmenting DH signals...done 475s DH segmentation table: 475s dhStart dhEnd dhNbrOfLoci dhMean 475s 1 554484 143926517 2120 0.5101 475s startRow endRow 475s 1 10 7594 475s Rows: 475s [1] 1 475s TCN segmentation rows: 475s startRow endRow 475s 1 1 7599 475s TCN and DH segmentation rows: 475s startRow endRow 475s 1 1 7599 475s startRow endRow 475s 1 10 7594 475s NULL 475s TCN segmentation (expanded) rows: 475s startRow endRow 475s 1 1 7599 475s TCN and DH segmentation rows: 475s startRow endRow 475s 1 1 7599 475s 2 7600 10267 475s 3 10268 14658 475s startRow endRow 475s 1 10 7594 475s startRow endRow 475s 1 1 7599 475s Total CN segmentation table (expanded): 475s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 475s 1 2 554484 143926517 7599 1.3859 2120 2120 475s (TCN,DH) segmentation for one total CN segment: 475s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 475s 1 1 1 2 554484 143926517 7599 1.3859 2120 475s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 475s 1 2120 554484 143926517 2120 0.5101 475s Total CN segment #1 ([ 554484,1.43927e+08]) of 3...done 475s Total CN segment #2 ([1.43927e+08,1.8545e+08]) of 3... 475s Number of TCN loci in segment: 2668 475s Locus data for TCN segment: 475s 'data.frame': 2668 obs. of 9 variables: 475s $ chromosome: int 2 2 2 2 2 2 2 2 2 2 ... 475s $ x : num 1.44e+08 1.44e+08 1.44e+08 1.44e+08 1.44e+08 ... 475s $ CT : num 2.1 2.1 2.09 1.8 2.34 ... 475s $ betaT : num 0.027542 1.030222 1.094093 0.046763 -0.000948 ... 475s $ betaTN : num 0.027542 1.030222 1.094093 0.046763 -0.000948 ... 475s $ betaN : num 0.1624 0.8788 0.8225 0.1201 0.0317 ... 475s $ muN : num 0 1 1 0 0 1 0 0 0 0 ... 475s $ index : int 7600 7601 7602 7603 7604 7605 7606 7607 7608 7609 ... 475s $ rho : num NA NA NA NA NA NA NA NA NA NA ... 475s Number of loci: 2668 475s Number of SNPs: 775 (29.05%) 475s Number of heterozygous SNPs: 775 (100.00%) 475s Chromosome: 2 475s Segmenting DH signals... 475s Segmenting by CBS... 475s Chromosome: 2 475s Random seed temporarily set (seed=c(10407, -1924040949, -1632234809, -437763632, -1464377300, 676654412, 2080370711), kind="L'Ecuyer-CMRG") 475s Segmenting by CBS...done 475s List of 4 475s $ data :'data.frame': 2668 obs. of 4 variables: 475s ..$ chromosome: int [1:2668] 2 2 2 2 2 2 2 2 2 2 ... 475s ..$ x : num [1:2668] 1.44e+08 1.44e+08 1.44e+08 1.44e+08 1.44e+08 ... 475s ..$ y : num [1:2668] NA NA NA NA NA NA NA NA NA NA ... 475s ..$ index : int [1:2668] 1 2 3 4 5 6 7 8 9 10 ... 475s $ output :'data.frame': 1 obs. of 6 variables: 475s ..$ sampleName: chr NA 475s ..$ chromosome: int 2 475s ..$ start : num 1.44e+08 475s ..$ end : num 1.85e+08 475s ..$ nbrOfLoci : int 775 475s ..$ mean : num 0.097 475s $ segRows:'data.frame': 1 obs. of 2 variables: 475s ..$ startRow: int 15 475s ..$ endRow : int 2664 475s $ params :List of 5 475s ..$ alpha : num 0.001 475s ..$ undo : num 0 475s ..$ joinSegments : logi TRUE 475s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 475s .. ..$ chromosome: int 2 475s .. ..$ start : num 1.44e+08 475s .. ..$ end : num 1.85e+08 475s ..$ seed : int [1:7] 10407 -1924040949 -1632234809 -437763632 -1464377300 676654412 2080370711 475s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 475s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.007 0 0.007 0 0 475s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 475s - attr(*, "pkgDetails")= chr "DNAcopy v1.76.0" 475s - attr(*, "randomSeed")= int [1:7] 10407 -1924040949 -1632234809 -437763632 -1464377300 676654412 2080370711 475s DH segmentation (locally-indexed) rows: 475s startRow endRow 475s 1 15 2664 475s int [1:2668] 7600 7601 7602 7603 7604 7605 7606 7607 7608 7609 ... 475s DH segmentation rows: 475s startRow endRow 475s 1 7614 10263 475s Segmenting DH signals...done 475s DH segmentation table: 475s dhStart dhEnd dhNbrOfLoci dhMean 475s 1 143926517 185449813 775 0.097 475s startRow endRow 475s 1 7614 10263 475s Rows: 475s [1] 2 475s TCN segmentation rows: 475s startRow endRow 475s 2 7600 10267 475s TCN and DH segmentation rows: 475s startRow endRow 475s 2 7600 10267 475s startRow endRow 475s 1 7614 10263 475s startRow endRow 475s 1 1 7599 475s TCN segmentation (expanded) rows: 475s startRow endRow 475s 1 1 7599 475s 2 7600 10267 475s TCN and DH segmentation rows: 475s startRow endRow 475s 1 1 7599 475s 2 7600 10267 475s 3 10268 14658 475s startRow endRow 475s 1 10 7594 475s 2 7614 10263 475s startRow endRow 475s 1 1 7599 475s 2 7600 10267 475s Total CN segmentation table (expanded): 475s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 475s 2 2 143926517 185449813 2668 2.0704 775 775 475s (TCN,DH) segmentation for one total CN segment: 475s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 475s 2 2 1 2 143926517 185449813 2668 2.0704 775 475s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 475s 2 775 143926517 185449813 775 0.097 475s Total CN segment #2 ([1.43927e+08,1.8545e+08]) of 3...done 475s Total CN segment #3 ([1.8545e+08,2.47137e+08]) of 3... 475s Number of TCN loci in segment: 4391 475s Locus data for TCN segment: 475s 'data.frame': 4391 obs. of 9 variables: 475s $ chromosome: int 2 2 2 2 2 2 2 2 2 2 ... 475s $ x : num 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 475s $ CT : num 2.93 2.15 2.82 2.93 2.46 ... 475s $ betaT : num -0.169 0.609 1.028 0.525 0.968 ... 475s $ betaTN : num -0.169 0.609 1.028 0.525 0.968 ... 475s $ betaN : num 0.25 0.38 0.919 0.34 0.783 ... 475s $ muN : num 0 0.5 1 0.5 1 1 0 1 0 1 ... 475s $ index : int 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 475s $ rho : num NA 0.2186 NA 0.0503 NA ... 475s Number of loci: 4391 475s Number of SNPs: 1314 (29.92%) 475s Number of heterozygous SNPs: 1314 (100.00%) 475s Chromosome: 2 475s Segmenting DH signals... 475s Segmenting by CBS... 475s Chromosome: 2 475s Random seed temporarily set (seed=c(10407, -1924040949, -1632234809, -437763632, -1464377300, 676654412, 2080370711), kind="L'Ecuyer-CMRG") 475s Segmenting by CBS...done 475s List of 4 475s $ data :'data.frame': 4391 obs. of 4 variables: 475s ..$ chromosome: int [1:4391] 2 2 2 2 2 2 2 2 2 2 ... 475s ..$ x : num [1:4391] 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 475s ..$ y : num [1:4391] NA 0.2186 NA 0.0503 NA ... 475s ..$ index : int [1:4391] 1 2 3 4 5 6 7 8 9 10 ... 475s $ output :'data.frame': 1 obs. of 6 variables: 475s ..$ sampleName: chr NA 475s ..$ chromosome: int 2 475s ..$ start : num 1.85e+08 475s ..$ end : num 2.47e+08 475s ..$ nbrOfLoci : int 1314 475s ..$ mean : num 0.23 475s $ segRows:'data.frame': 1 obs. of 2 variables: 475s ..$ startRow: int 2 475s ..$ endRow : int 4388 475s $ params :List of 5 475s ..$ alpha : num 0.001 475s ..$ undo : num 0 475s ..$ joinSegments : logi TRUE 475s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 475s .. ..$ chromosome: int 2 475s .. ..$ start : num 1.85e+08 475s .. ..$ end : num 2.47e+08 475s ..$ seed : int [1:7] 10407 -1924040949 -1632234809 -437763632 -1464377300 676654412 2080370711 475s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 475s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.013 0 0.013 0 0 475s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 475s - attr(*, "pkgDetails")= chr "DNAcopy v1.76.0" 475s - attr(*, "randomSeed")= int [1:7] 10407 -1924040949 -1632234809 -437763632 -1464377300 676654412 2080370711 475s DH segmentation (locally-indexed) rows: 475s startRow endRow 475s 1 2 4388 475s int [1:4391] 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 475s DH segmentation rows: 475s startRow endRow 475s 1 10269 14655 475s Segmenting DH signals...done 475s DH segmentation table: 475s dhStart dhEnd dhNbrOfLoci dhMean 475s 1 185449813 247137334 1314 0.2295 475s startRow endRow 475s 1 10269 14655 475s Rows: 475s [1] 3 475s TCN segmentation rows: 475s startRow endRow 475s 3 10268 14658 475s TCN and DH segmentation rows: 475s startRow endRow 475s 3 10268 14658 475s startRow endRow 475s 1 10269 14655 475s startRow endRow 475s 1 1 7599 475s 2 7600 10267 475s TCN segmentation (expanded) rows: 475s startRow endRow 475s 1 1 7599 475s 2 7600 10267 475s 3 10268 14658 475s TCN and DH segmentation rows: 475s startRow endRow 475s 1 1 7599 475s 2 7600 10267 475s 3 10268 14658 475s startRow endRow 475s 1 10 7594 475s 2 7614 10263 475s 3 10269 14655 475s startRow endRow 475s 1 1 7599 475s 2 7600 10267 475s 3 10268 14658 475s Total CN segmentation table (expanded): 475s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 475s 3 2 185449813 247137334 4391 2.6341 1314 1314 475s (TCN,DH) segmentation for one total CN segment: 475s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 475s 3 3 1 2 185449813 247137334 4391 2.6341 1314 475s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 475s 3 1314 185449813 247137334 1314 0.2295 475s Total CN segment #3 ([1.8545e+08,2.47137e+08]) of 3...done 475s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 475s 1 2 1 1 554484 143926517 7599 1.3859 2120 475s 2 2 2 1 143926517 185449813 2668 2.0704 775 475s 3 2 3 1 185449813 247137334 4391 2.6341 1314 475s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 475s 1 2120 554484 143926517 2120 0.5101 475s 2 775 143926517 185449813 775 0.0970 475s 3 1314 185449813 247137334 1314 0.2295 475s Calculating (C1,C2) per segment... 475s Calculating (C1,C2) per segment...done 475s Number of segments: 3 475s Segmenting paired tumor-normal signals using Paired PSCBS...done 475s Post-segmenting TCNs... 475s Number of segments: 3 475s Number of chromosomes: 1 475s [1] 2 475s Chromosome 1 ('chr02') of 1... 475s Rows: 475s [1] 1 2 3 475s Number of segments: 3 475s TCN segment #1 ('1') of 3... 475s Nothing todo. Only one DH segmentation. Skipping. 475s TCN segment #1 ('1') of 3...done 475s TCN segment #2 ('2') of 3... 475s Nothing todo. Only one DH segmentation. Skipping. 475s TCN segment #2 ('2') of 3...done 475s TCN segment #3 ('3') of 3... 475s Nothing todo. Only one DH segmentation. Skipping. 475s TCN segment #3 ('3') of 3...done 475s Chromosome 1 ('chr02') of 1...done 475s Update (C1,C2) per segment... 475s Update (C1,C2) per segment...done 475s Post-segmenting TCNs...done 475s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 475s 1 2 1 1 554484 143926517 7599 1.3859 2120 475s 2 2 2 1 143926517 185449813 2668 2.0704 775 475s 3 2 3 1 185449813 247137334 4391 2.6341 1314 475s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 475s 1 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 475s 2 775 143926517 185449813 775 0.0970 0.9347856 1.135614 475s 3 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 475s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 475s 1 2 1 1 554484 143926517 7599 1.3859 2120 475s 2 2 2 1 143926517 185449813 2668 2.0704 775 475s 3 2 3 1 185449813 247137334 4391 2.6341 1314 475s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 475s 1 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 475s 2 775 143926517 185449813 775 0.0970 0.9347856 1.135614 475s 3 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 475s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 475s 1 2 1 1 554484 143926517 7599 1.3859 2120 475s 2 2 2 1 143926517 185449813 2668 2.0704 775 475s 3 2 3 1 185449813 247137334 4391 2.6341 1314 475s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 475s 1 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 475s 2 775 143926517 185449813 775 0.0970 0.9347856 1.135614 475s 3 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 475s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 475s 1 2 1 1 554484 143926517 7599 1.3859 2120 475s 2 2 2 1 143926517 185449813 2668 2.0704 775 475s 3 2 3 1 185449813 247137334 4391 2.6341 1314 475s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 475s 1 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 475s 2 775 143926517 185449813 775 0.0970 0.9347856 1.135614 475s 3 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 475s Chromosome #2 ('Chr02') of 3...done 475s Chromosome #3 ('Chr03') of 3... 475s 'data.frame': 14658 obs. of 8 variables: 475s $ chromosome: int 3 3 3 3 3 3 3 3 3 3 ... 475s $ x : num 554484 730720 782343 878522 916294 ... 475s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 475s $ betaT : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 475s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 475s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 475s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 475s $ index : int 29317 29318 29319 29320 29321 29322 29323 29324 29325 29326 ... 475s Known segments: 475s [1] chromosome start end 475s <0 rows> (or 0-length row.names) 475s Segmenting paired tumor-normal signals using Paired PSCBS... 475s Setup up data... 475s 'data.frame': 14658 obs. of 7 variables: 475s $ chromosome: int 3 3 3 3 3 3 3 3 3 3 ... 475s $ x : num 554484 730720 782343 878522 916294 ... 475s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 475s $ betaT : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 475s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 475s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 475s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 475s Setup up data...done 475s Ordering data along genome... 475s 'data.frame': 14658 obs. of 7 variables: 475s $ chromosome: int 3 3 3 3 3 3 3 3 3 3 ... 475s $ x : num 554484 730720 782343 878522 916294 ... 475s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 475s $ betaT : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 475s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 475s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 475s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 475s Ordering data along genome...done 475s Keeping only current chromosome for 'knownSegments'... 475s Chromosome: 3 475s Known segments for this chromosome: 475s [1] chromosome start end 475s <0 rows> (or 0-length row.names) 475s Keeping only current chromosome for 'knownSegments'...done 475s alphaTCN: 0.009 475s alphaDH: 0.001 475s Number of loci: 14658 475s Calculating DHs... 475s Number of SNPs: 14658 475s Number of heterozygous SNPs: 4209 (28.71%) 475s Normalized DHs: 475s num [1:14658] NA NA NA NA NA ... 475s Calculating DHs...done 475s Random seed temporarily set (seed=c(10407, -821273412, -52578226, 1415511586, 721384351, -665928286, 1316562960), kind="L'Ecuyer-CMRG") 475s Produced 2 seeds from this stream for future usage 475s Identification of change points by total copy numbers... 475s Segmenting by CBS... 475s Chromosome: 3 475s Random seed temporarily set (seed=c(10407, -1924040949, -1632234809, -437763632, -1464377300, 676654412, 2080370711), kind="L'Ecuyer-CMRG") 475s Segmenting by CBS...done 475s List of 4 475s $ data :'data.frame': 14658 obs. of 4 variables: 475s ..$ chromosome: int [1:14658] 3 3 3 3 3 3 3 3 3 3 ... 475s ..$ x : num [1:14658] 554484 730720 782343 878522 916294 ... 475s ..$ y : num [1:14658] 1.88 1.8 1.59 1.64 1.53 ... 475s ..$ index : int [1:14658] 1 2 3 4 5 6 7 8 9 10 ... 475s $ output :'data.frame': 3 obs. of 6 variables: 475s ..$ sampleName: chr [1:3] NA NA NA 475s ..$ chromosome: int [1:3] 3 3 3 475s ..$ start : num [1:3] 5.54e+05 1.44e+08 1.85e+08 475s ..$ end : num [1:3] 1.44e+08 1.85e+08 2.47e+08 475s ..$ nbrOfLoci : int [1:3] 7599 2668 4391 475s ..$ mean : num [1:3] 1.39 2.07 2.63 475s $ segRows:'data.frame': 3 obs. of 2 variables: 475s ..$ startRow: int [1:3] 1 7600 10268 475s ..$ endRow : int [1:3] 7599 10267 14658 475s $ params :List of 5 475s ..$ alpha : num 0.009 475s ..$ undo : num 0 475s ..$ joinSegments : logi TRUE 475s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 475s .. ..$ chromosome: int 3 475s .. ..$ start : num -Inf 475s .. ..$ end : num Inf 475s ..$ seed : int [1:7] 10407 -1924040949 -1632234809 -437763632 -1464377300 676654412 2080370711 475s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 475s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.416 0 0.415 0 0 475s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 475s - attr(*, "pkgDetails")= chr "DNAcopy v1.76.0" 475s - attr(*, "randomSeed")= int [1:7] 10407 -1924040949 -1632234809 -437763632 -1464377300 676654412 2080370711 475s Identification of change points by total copy numbers...done 475s Restructure TCN segmentation results... 475s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean 475s 1 3 554484 143926517 7599 1.3859 475s 2 3 143926517 185449813 2668 2.0704 475s 3 3 185449813 247137334 4391 2.6341 475s Number of TCN segments: 3 475s Restructure TCN segmentation results...done 475s Total CN segment #1 ([ 554484,1.43927e+08]) of 3... 475s Number of TCN loci in segment: 7599 475s Locus data for TCN segment: 475s 'data.frame': 7599 obs. of 9 variables: 475s $ chromosome: int 3 3 3 3 3 3 3 3 3 3 ... 475s $ x : num 554484 730720 782343 878522 916294 ... 475s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 475s $ betaT : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 475s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 475s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 475s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 475s $ index : int 1 2 3 4 5 6 7 8 9 10 ... 475s $ rho : num NA NA NA NA NA ... 475s Number of loci: 7599 475s Number of SNPs: 2120 (27.90%) 475s Number of heterozygous SNPs: 2120 (100.00%) 475s Chromosome: 3 475s Segmenting DH signals... 475s Segmenting by CBS... 475s Chromosome: 3 475s Random seed temporarily set (seed=c(10407, -1371615447, -889757879, 1692656974, -1723952224, 1378814990, 1816467252), kind="L'Ecuyer-CMRG") 475s Segmenting by CBS...done 475s List of 4 475s $ data :'data.frame': 7599 obs. of 4 variables: 475s ..$ chromosome: int [1:7599] 3 3 3 3 3 3 3 3 3 3 ... 475s ..$ x : num [1:7599] 554484 730720 782343 878522 916294 ... 475s ..$ y : num [1:7599] NA NA NA NA NA ... 475s ..$ index : int [1:7599] 1 2 3 4 5 6 7 8 9 10 ... 475s $ output :'data.frame': 1 obs. of 6 variables: 475s ..$ sampleName: chr NA 475s ..$ chromosome: int 3 475s ..$ start : num 554484 475s ..$ end : num 1.44e+08 475s ..$ nbrOfLoci : int 2120 475s ..$ mean : num 0.51 475s $ segRows:'data.frame': 1 obs. of 2 variables: 475s ..$ startRow: int 10 475s ..$ endRow : int 7594 475s $ params :List of 5 475s ..$ alpha : num 0.001 475s ..$ undo : num 0 475s ..$ joinSegments : logi TRUE 475s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 475s .. ..$ chromosome: int 3 475s .. ..$ start : num 554484 475s .. ..$ end : num 1.44e+08 475s ..$ seed : int [1:7] 10407 -1371615447 -889757879 1692656974 -1723952224 1378814990 1816467252 475s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 475s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.02 0.004 0.024 0 0 475s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 475s - attr(*, "pkgDetails")= chr "DNAcopy v1.76.0" 475s - attr(*, "randomSeed")= int [1:7] 10407 -1371615447 -889757879 1692656974 -1723952224 1378814990 1816467252 475s DH segmentation (locally-indexed) rows: 475s startRow endRow 475s 1 10 7594 475s int [1:7599] 1 2 3 4 5 6 7 8 9 10 ... 475s DH segmentation rows: 475s startRow endRow 475s 1 10 7594 475s Segmenting DH signals...done 475s DH segmentation table: 475s dhStart dhEnd dhNbrOfLoci dhMean 475s 1 554484 143926517 2120 0.5101 475s startRow endRow 475s 1 10 7594 475s Rows: 475s [1] 1 475s TCN segmentation rows: 475s startRow endRow 475s 1 1 7599 475s TCN and DH segmentation rows: 475s startRow endRow 475s 1 1 7599 475s startRow endRow 475s 1 10 7594 475s NULL 475s TCN segmentation (expanded) rows: 475s startRow endRow 475s 1 1 7599 475s TCN and DH segmentation rows: 475s startRow endRow 475s 1 1 7599 475s 2 7600 10267 475s 3 10268 14658 475s startRow endRow 475s 1 10 7594 475s startRow endRow 475s 1 1 7599 475s Total CN segmentation table (expanded): 475s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 475s 1 3 554484 143926517 7599 1.3859 2120 2120 475s (TCN,DH) segmentation for one total CN segment: 475s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 475s 1 1 1 3 554484 143926517 7599 1.3859 2120 475s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 475s 1 2120 554484 143926517 2120 0.5101 475s Total CN segment #1 ([ 554484,1.43927e+08]) of 3...done 475s Total CN segment #2 ([1.43927e+08,1.8545e+08]) of 3... 475s Number of TCN loci in segment: 2668 475s Locus data for TCN segment: 475s 'data.frame': 2668 obs. of 9 variables: 475s $ chromosome: int 3 3 3 3 3 3 3 3 3 3 ... 475s $ x : num 1.44e+08 1.44e+08 1.44e+08 1.44e+08 1.44e+08 ... 475s $ CT : num 2.1 2.1 2.09 1.8 2.34 ... 475s $ betaT : num 0.027542 1.030222 1.094093 0.046763 -0.000948 ... 475s $ betaTN : num 0.027542 1.030222 1.094093 0.046763 -0.000948 ... 475s $ betaN : num 0.1624 0.8788 0.8225 0.1201 0.0317 ... 475s $ muN : num 0 1 1 0 0 1 0 0 0 0 ... 475s $ index : int 7600 7601 7602 7603 7604 7605 7606 7607 7608 7609 ... 475s $ rho : num NA NA NA NA NA NA NA NA NA NA ... 475s Number of loci: 2668 475s Number of SNPs: 775 (29.05%) 475s Number of heterozygous SNPs: 775 (100.00%) 475s Chromosome: 3 475s Segmenting DH signals... 475s Segmenting by CBS... 475s Chromosome: 3 475s Random seed temporarily set (seed=c(10407, -1371615447, -889757879, 1692656974, -1723952224, 1378814990, 1816467252), kind="L'Ecuyer-CMRG") 475s Segmenting by CBS...done 475s List of 4 475s $ data :'data.frame': 2668 obs. of 4 variables: 475s ..$ chromosome: int [1:2668] 3 3 3 3 3 3 3 3 3 3 ... 475s ..$ x : num [1:2668] 1.44e+08 1.44e+08 1.44e+08 1.44e+08 1.44e+08 ... 475s ..$ y : num [1:2668] NA NA NA NA NA NA NA NA NA NA ... 475s ..$ index : int [1:2668] 1 2 3 4 5 6 7 8 9 10 ... 475s $ output :'data.frame': 1 obs. of 6 variables: 475s ..$ sampleName: chr NA 475s ..$ chromosome: int 3 475s ..$ start : num 1.44e+08 475s ..$ end : num 1.85e+08 475s ..$ nbrOfLoci : int 775 475s ..$ mean : num 0.097 475s $ segRows:'data.frame': 1 obs. of 2 variables: 475s ..$ startRow: int 15 475s ..$ endRow : int 2664 475s $ params :List of 5 475s ..$ alpha : num 0.001 475s ..$ undo : num 0 475s ..$ joinSegments : logi TRUE 475s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 475s .. ..$ chromosome: int 3 475s .. ..$ start : num 1.44e+08 475s .. ..$ end : num 1.85e+08 475s ..$ seed : int [1:7] 10407 -1371615447 -889757879 1692656974 -1723952224 1378814990 1816467252 475s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 475s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.007 0 0.007 0 0 475s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 475s - attr(*, "pkgDetails")= chr "DNAcopy v1.76.0" 475s - attr(*, "randomSeed")= int [1:7] 10407 -1371615447 -889757879 1692656974 -1723952224 1378814990 1816467252 475s DH segmentation (locally-indexed) rows: 475s startRow endRow 475s 1 15 2664 475s int [1:2668] 7600 7601 7602 7603 7604 7605 7606 7607 7608 7609 ... 475s DH segmentation rows: 475s startRow endRow 475s 1 7614 10263 475s Segmenting DH signals...done 475s DH segmentation table: 475s dhStart dhEnd dhNbrOfLoci dhMean 475s 1 143926517 185449813 775 0.097 475s startRow endRow 475s 1 7614 10263 475s Rows: 475s [1] 2 475s TCN segmentation rows: 475s startRow endRow 475s 2 7600 10267 475s TCN and DH segmentation rows: 475s startRow endRow 475s 2 7600 10267 475s startRow endRow 475s 1 7614 10263 475s startRow endRow 475s 1 1 7599 475s TCN segmentation (expanded) rows: 475s startRow endRow 475s 1 1 7599 475s 2 7600 10267 475s TCN and DH segmentation rows: 475s startRow endRow 475s 1 1 7599 475s 2 7600 10267 475s 3 10268 14658 475s startRow endRow 475s 1 10 7594 475s 2 7614 10263 475s startRow endRow 475s 1 1 7599 475s 2 7600 10267 475s Total CN segmentation table (expanded): 475s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 475s 2 3 143926517 185449813 2668 2.0704 775 775 475s (TCN,DH) segmentation for one total CN segment: 475s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 475s 2 2 1 3 143926517 185449813 2668 2.0704 775 475s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 475s 2 775 143926517 185449813 775 0.097 475s Total CN segment #2 ([1.43927e+08,1.8545e+08]) of 3...done 475s Total CN segment #3 ([1.8545e+08,2.47137e+08]) of 3... 475s Number of TCN loci in segment: 4391 475s Locus data for TCN segment: 475s 'data.frame': 4391 obs. of 9 variables: 475s $ chromosome: int 3 3 3 3 3 3 3 3 3 3 ... 475s $ x : num 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 475s $ CT : num 2.93 2.15 2.82 2.93 2.46 ... 475s $ betaT : num -0.169 0.609 1.028 0.525 0.968 ... 475s $ betaTN : num -0.169 0.609 1.028 0.525 0.968 ... 475s $ betaN : num 0.25 0.38 0.919 0.34 0.783 ... 475s $ muN : num 0 0.5 1 0.5 1 1 0 1 0 1 ... 475s $ index : int 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 475s $ rho : num NA 0.2186 NA 0.0503 NA ... 475s Number of loci: 4391 475s Number of SNPs: 1314 (29.92%) 475s Number of heterozygous SNPs: 1314 (100.00%) 475s Chromosome: 3 475s Segmenting DH signals... 475s Segmenting by CBS... 475s Chromosome: 3 475s Random seed temporarily set (seed=c(10407, -1371615447, -889757879, 1692656974, -1723952224, 1378814990, 1816467252), kind="L'Ecuyer-CMRG") 475s Segmenting by CBS...done 475s List of 4 475s $ data :'data.frame': 4391 obs. of 4 variables: 475s ..$ chromosome: int [1:4391] 3 3 3 3 3 3 3 3 3 3 ... 475s ..$ x : num [1:4391] 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 475s ..$ y : num [1:4391] NA 0.2186 NA 0.0503 NA ... 475s ..$ index : int [1:4391] 1 2 3 4 5 6 7 8 9 10 ... 475s $ output :'data.frame': 1 obs. of 6 variables: 475s ..$ sampleName: chr NA 475s ..$ chromosome: int 3 475s ..$ start : num 1.85e+08 475s ..$ end : num 2.47e+08 475s ..$ nbrOfLoci : int 1314 475s ..$ mean : num 0.23 475s $ segRows:'data.frame': 1 obs. of 2 variables: 475s ..$ startRow: int 2 475s ..$ endRow : int 4388 475s $ params :List of 5 475s ..$ alpha : num 0.001 475s ..$ undo : num 0 475s ..$ joinSegments : logi TRUE 475s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 475s .. ..$ chromosome: int 3 475s .. ..$ start : num 1.85e+08 475s .. ..$ end : num 2.47e+08 475s ..$ seed : int [1:7] 10407 -1371615447 -889757879 1692656974 -1723952224 1378814990 1816467252 475s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 475s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.014 0 0.014 0 0 475s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 475s - attr(*, "pkgDetails")= chr "DNAcopy v1.76.0" 475s - attr(*, "randomSeed")= int [1:7] 10407 -1371615447 -889757879 1692656974 -1723952224 1378814990 1816467252 475s DH segmentation (locally-indexed) rows: 475s startRow endRow 475s 1 2 4388 475s int [1:4391] 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 475s DH segmentation rows: 475s startRow endRow 475s 1 10269 14655 475s Segmenting DH signals...done 475s DH segmentation table: 475s dhStart dhEnd dhNbrOfLoci dhMean 475s 1 185449813 247137334 1314 0.2295 475s startRow endRow 475s 1 10269 14655 475s Rows: 475s [1] 3 475s TCN segmentation rows: 475s startRow endRow 475s 3 10268 14658 475s TCN and DH segmentation rows: 475s startRow endRow 475s 3 10268 14658 475s startRow endRow 475s 1 10269 14655 475s startRow endRow 475s 1 1 7599 475s 2 7600 10267 475s TCN segmentation (expanded) rows: 475s startRow endRow 475s 1 1 7599 475s 2 7600 10267 475s 3 10268 14658 475s TCN and DH segmentation rows: 475s startRow endRow 475s 1 1 7599 475s 2 7600 10267 475s 3 10268 14658 475s startRow endRow 475s 1 10 7594 475s 2 7614 10263 475s 3 10269 14655 475s startRow endRow 475s 1 1 7599 475s 2 7600 10267 475s 3 10268 14658 475s Total CN segmentation table (expanded): 475s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 475s 3 3 185449813 247137334 4391 2.6341 1314 1314 475s (TCN,DH) segmentation for one total CN segment: 475s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 475s 3 3 1 3 185449813 247137334 4391 2.6341 1314 475s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 475s 3 1314 185449813 247137334 1314 0.2295 475s Total CN segment #3 ([1.8545e+08,2.47137e+08]) of 3...done 475s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 475s 1 3 1 1 554484 143926517 7599 1.3859 2120 475s 2 3 2 1 143926517 185449813 2668 2.0704 775 475s 3 3 3 1 185449813 247137334 4391 2.6341 1314 475s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 475s 1 2120 554484 143926517 2120 0.5101 475s 2 775 143926517 185449813 775 0.0970 475s 3 1314 185449813 247137334 1314 0.2295 475s Calculating (C1,C2) per segment... 475s Calculating (C1,C2) per segment...done 475s Number of segments: 3 475s Segmenting paired tumor-normal signals using Paired PSCBS...done 475s Post-segmenting TCNs... 475s Number of segments: 3 475s Number of chromosomes: 1 475s [1] 3 475s Chromosome 1 ('chr03') of 1... 475s Rows: 475s [1] 1 2 3 475s Number of segments: 3 475s TCN segment #1 ('1') of 3... 475s Nothing todo. Only one DH segmentation. Skipping. 475s TCN segment #1 ('1') of 3...done 475s TCN segment #2 ('2') of 3... 475s Nothing todo. Only one DH segmentation. Skipping. 475s TCN segment #2 ('2') of 3...done 475s TCN segment #3 ('3') of 3... 475s Nothing todo. Only one DH segmentation. Skipping. 475s TCN segment #3 ('3') of 3...done 475s Chromosome 1 ('chr03') of 1...done 475s Update (C1,C2) per segment... 475s Update (C1,C2) per segment...done 475s Post-segmenting TCNs...done 475s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 475s 1 3 1 1 554484 143926517 7599 1.3859 2120 475s 2 3 2 1 143926517 185449813 2668 2.0704 775 475s 3 3 3 1 185449813 247137334 4391 2.6341 1314 475s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 475s 1 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 475s 2 775 143926517 185449813 775 0.0970 0.9347856 1.135614 475s 3 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 475s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 475s 1 3 1 1 554484 143926517 7599 1.3859 2120 475s 2 3 2 1 143926517 185449813 2668 2.0704 775 475s 3 3 3 1 185449813 247137334 4391 2.6341 1314 475s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 475s 1 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 475s 2 775 143926517 185449813 775 0.0970 0.9347856 1.135614 475s 3 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 475s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 475s 1 3 1 1 554484 143926517 7599 1.3859 2120 475s 2 3 2 1 143926517 185449813 2668 2.0704 775 475s 3 3 3 1 185449813 247137334 4391 2.6341 1314 475s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 475s 1 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 475s 2 775 143926517 185449813 775 0.0970 0.9347856 1.135614 475s 3 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 475s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 475s 1 3 1 1 554484 143926517 7599 1.3859 2120 475s 2 3 2 1 143926517 185449813 2668 2.0704 775 475s 3 3 3 1 185449813 247137334 4391 2.6341 1314 475s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 475s 1 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 475s 2 775 143926517 185449813 775 0.0970 0.9347856 1.135614 475s 3 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 475s Chromosome #3 ('Chr03') of 3...done 475s Merging (independently) segmented chromosome... 475s List of 5 475s $ data :Classes 'PairedPSCNData' and 'data.frame': 43974 obs. of 8 variables: 475s ..$ chromosome: int [1:43974] 1 1 1 1 1 1 1 1 1 1 ... 475s ..$ x : num [1:43974] 554484 730720 782343 878522 916294 ... 475s ..$ CT : num [1:43974] 1.88 1.8 1.59 1.64 1.53 ... 475s ..$ betaT : num [1:43974] 0.0646 0.1672 0.9284 0.113 0.7209 ... 475s ..$ betaTN : num [1:43974] -0.0515 -0.1172 1.0194 0.031 0.8604 ... 475s ..$ betaN : num [1:43974] 0.116 0.284 0.909 0.082 0.86 ... 475s ..$ muN : num [1:43974] 0 0 1 0 1 1 1 0 1 0.5 ... 475s ..$ rho : num [1:43974] NA NA NA NA NA ... 475s $ output :Classes 'PairedPSCNSegments' and 'data.frame': 11 obs. of 15 variables: 475s ..$ chromosome : int [1:11] 1 1 1 NA 2 2 2 NA 3 3 ... 475s ..$ tcnId : int [1:11] 1 2 3 NA 1 2 3 NA 1 2 ... 475s ..$ dhId : int [1:11] 1 1 1 NA 1 1 1 NA 1 1 ... 475s ..$ tcnStart : num [1:11] 5.54e+05 1.44e+08 1.85e+08 NA 5.54e+05 ... 475s ..$ tcnEnd : num [1:11] 1.44e+08 1.85e+08 2.47e+08 NA 1.44e+08 ... 475s ..$ tcnNbrOfLoci: int [1:11] 7599 2668 4391 NA 7599 2668 4391 NA 7599 2668 ... 475s ..$ tcnMean : num [1:11] 1.39 2.07 2.63 NA 1.39 ... 475s ..$ tcnNbrOfSNPs: int [1:11] 2120 775 1314 NA 2120 775 1314 NA 2120 775 ... 475s ..$ tcnNbrOfHets: int [1:11] 2120 775 1314 NA 2120 775 1314 NA 2120 775 ... 475s ..$ dhStart : num [1:11] 5.54e+05 1.44e+08 1.85e+08 NA 5.54e+05 ... 475s ..$ dhEnd : num [1:11] 1.44e+08 1.85e+08 2.47e+08 NA 1.44e+08 ... 475s ..$ dhNbrOfLoci : int [1:11] 2120 775 1314 NA 2120 775 1314 NA 2120 775 ... 475s ..$ dhMean : num [1:11] 0.51 0.097 0.23 NA 0.51 ... 475s ..$ c1Mean : num [1:11] 0.339 0.935 1.015 NA 0.339 ... 475s ..$ c2Mean : num [1:11] 1.05 1.14 1.62 NA 1.05 ... 475s $ tcnSegRows:'data.frame': 11 obs. of 2 variables: 475s ..$ startRow: int [1:11] 1 7600 10268 NA 14659 22258 24926 NA 29317 36916 ... 475s ..$ endRow : int [1:11] 7599 10267 14658 NA 22257 24925 29316 NA 36915 39583 ... 475s $ dhSegRows :'data.frame': 11 obs. of 2 variables: 475s ..$ startRow: int [1:11] 10 7614 10269 NA 14668 22272 24927 NA 29326 36930 ... 475s ..$ endRow : int [1:11] 7594 10263 14655 NA 22252 24921 29313 NA 36910 39579 ... 475s $ params :List of 7 475s ..$ alphaTCN : num 0.009 475s ..$ alphaDH : num 0.001 475s ..$ flavor : chr "tcn&dh" 475s ..$ tbn : logi FALSE 475s ..$ joinSegments : logi TRUE 475s ..$ knownSegments:'data.frame': 0 obs. of 3 variables: 475s .. ..$ chromosome: int(0) 475s .. ..$ start : int(0) 475s .. ..$ end : int(0) 475s ..$ seed : int [1:7] 10407 1066287653 -51199871 161854402 -1995183193 1503453565 -747102133 475s - attr(*, "class")= chr [1:3] "PairedPSCBS" "PSCBS" "AbstractCBS" 475s Merging (independently) segmented chromosome...done 475s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 475s 1 1 1 1 554484 143926517 7599 1.3859 2120 475s 2 1 2 1 143926517 185449813 2668 2.0704 775 475s 3 1 3 1 185449813 247137334 4391 2.6341 1314 475s 4 NA NA NA NA NA NA NA NA 475s 5 2 1 1 554484 143926517 7599 1.3859 2120 475s 6 2 2 1 143926517 185449813 2668 2.0704 775 475s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 475s 1 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 475s 2 775 143926517 185449813 775 0.0970 0.9347856 1.135614 475s 3 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 475s 4 NA NA NA NA NA NA NA 475s 5 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 475s 6 775 143926517 185449813 775 0.0970 0.9347856 1.135614 475s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 475s 6 2 2 1 143926517 185449813 2668 2.0704 775 475s 7 2 3 1 185449813 247137334 4391 2.6341 1314 475s 8 NA NA NA NA NA NA NA NA 475s 9 3 1 1 554484 143926517 7599 1.3859 2120 475s 10 3 2 1 143926517 185449813 2668 2.0704 775 475s 11 3 3 1 185449813 247137334 4391 2.6341 1314 475s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 475s 6 775 143926517 185449813 775 0.0970 0.9347856 1.135614 475s 7 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 475s 8 NA NA NA NA NA NA NA 475s 9 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 475s 10 775 143926517 185449813 775 0.0970 0.9347856 1.135614 475s 11 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 475s Segmenting multiple chromosomes...done 475s Segmenting paired tumor-normal signals using Paired PSCBS...done 475s - segmentByPairedPSCBS() using 'multisession' futures ... 475s Segmenting paired tumor-normal signals using Paired PSCBS... 475s Calling genotypes from normal allele B fractions... 475s num [1:44010] 0.8274 0.5072 0.1671 0.1609 0.0421 ... 475s Called genotypes: 475s num [1:44010] 1 0.5 0 0 0 0 1 0 1 0.5 ... 475s - attr(*, "modelFit")=List of 1 475s ..$ :List of 7 475s .. ..$ flavor : chr "density" 475s .. ..$ cn : int 2 475s .. ..$ nbrOfGenotypeGroups: int 3 475s .. ..$ tau : num [1:2] 0.312 0.678 475s .. ..$ n : int 43920 475s .. ..$ fit :Classes 'PeaksAndValleys' and 'data.frame': 5 obs. of 3 variables: 475s .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 475s .. .. ..$ x : num [1:5] 0.0999 0.312 0.4986 0.6775 0.8922 475s .. .. ..$ density: num [1:5] 1.623 0.465 1.126 0.497 1.588 475s .. ..$ fitValleys :Classes 'PeaksAndValleys' and 'data.frame': 2 obs. of 3 variables: 475s .. .. ..$ type : chr [1:2] "valley" "valley" 475s .. .. ..$ x : num [1:2] 0.312 0.678 475s .. .. ..$ density: num [1:2] 0.465 0.497 475s ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 475s muN 475s 0 0.5 1 475s 15627 12633 15750 475s Calling genotypes from normal allele B fractions...done 475s Normalizing betaT using betaN (TumorBoost)... 475s Normalized BAFs: 475s num [1:44010] 0.9301 0.1667 0.0685 0.0995 0.0155 ... 475s - attr(*, "modelFit")=List of 5 475s ..$ method : chr "normalizeTumorBoost" 475s ..$ flavor : chr "v4" 475s ..$ delta : num [1:44010] -0.17264 0.00239 0.1671 0.16085 0.04213 ... 475s .. ..- attr(*, "modelFit")=List of 1 475s .. .. ..$ :List of 7 475s .. .. .. ..$ flavor : chr "density" 475s .. .. .. ..$ cn : int 2 475s .. .. .. ..$ nbrOfGenotypeGroups: int 3 475s .. .. .. ..$ tau : num [1:2] 0.312 0.678 475s .. .. .. ..$ n : int 43920 475s .. .. .. ..$ fit :Classes 'PeaksAndValleys' and 'data.frame': 5 obs. of 3 variables: 475s .. .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 475s .. .. .. .. ..$ x : num [1:5] 0.0999 0.312 0.4986 0.6775 0.8922 475s .. .. .. .. ..$ density: num [1:5] 1.623 0.465 1.126 0.497 1.588 475s .. .. .. ..$ fitValleys :Classes 'PeaksAndValleys' and 'data.frame': 2 obs. of 3 variables: 475s .. .. .. .. ..$ type : chr [1:2] "valley" "valley" 475s .. .. .. .. ..$ x : num [1:2] 0.312 0.678 475s .. .. .. .. ..$ density: num [1:2] 0.465 0.497 475s .. .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 475s ..$ preserveScale: logi FALSE 475s ..$ scaleFactor : num NA 475s Normalizing betaT using betaN (TumorBoost)...done 475s Setup up data... 475s 'data.frame': 44010 obs. of 7 variables: 475s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 475s $ x : num 1145994 2941694 3710825 4240737 4276892 ... 475s $ CT : num 1.63 1.4 1.41 1.17 1.16 ... 475s $ betaT : num 0.7574 0.169 0.2357 0.2604 0.0576 ... 475s $ betaTN : num 0.9301 0.1667 0.0685 0.0995 0.0155 ... 475s ..- attr(*, "modelFit")=List of 5 475s .. ..$ method : chr "normalizeTumorBoost" 475s .. ..$ flavor : chr "v4" 475s .. ..$ delta : num [1:44010] -0.17264 0.00239 0.1671 0.16085 0.04213 ... 475s .. .. ..- attr(*, "modelFit")=List of 1 475s .. .. .. ..$ :List of 7 475s .. .. .. .. ..$ flavor : chr "density" 475s .. .. .. .. ..$ cn : int 2 475s .. .. .. .. ..$ nbrOfGenotypeGroups: int 3 475s .. .. .. .. ..$ tau : num [1:2] 0.312 0.678 475s .. .. .. .. ..$ n : int 43920 475s .. .. .. .. ..$ fit :Classes 'PeaksAndValleys' and 'data.frame': 5 obs. of 3 variables: 475s .. .. .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 475s .. .. .. .. .. ..$ x : num [1:5] 0.0999 0.312 0.4986 0.6775 0.8922 475s .. .. .. .. .. ..$ density: num [1:5] 1.623 0.465 1.126 0.497 1.588 475s .. .. .. .. ..$ fitValleys :Classes 'PeaksAndValleys' and 'data.frame': 2 obs. of 3 variables: 475s .. .. .. .. .. ..$ type : chr [1:2] "valley" "valley" 475s .. .. .. .. .. ..$ x : num [1:2] 0.312 0.678 475s .. .. .. .. .. ..$ density: num [1:2] 0.465 0.497 475s .. .. .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 475s .. ..$ preserveScale: logi FALSE 475s .. ..$ scaleFactor : num NA 475s $ betaN : num 0.8274 0.5072 0.1671 0.1609 0.0421 ... 475s $ muN : num 1 0.5 0 0 0 0 1 0 1 0.5 ... 475s ..- attr(*, "modelFit")=List of 1 475s .. ..$ :List of 7 475s .. .. ..$ flavor : chr "density" 475s .. .. ..$ cn : int 2 475s .. .. ..$ nbrOfGenotypeGroups: int 3 475s .. .. ..$ tau : num [1:2] 0.312 0.678 475s .. .. ..$ n : int 43920 475s .. .. ..$ fit :Classes 'PeaksAndValleys' and 'data.frame': 5 obs. of 3 variables: 475s .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 475s .. .. .. ..$ x : num [1:5] 0.0999 0.312 0.4986 0.6775 0.8922 475s .. .. .. ..$ density: num [1:5] 1.623 0.465 1.126 0.497 1.588 475s .. .. ..$ fitValleys :Classes 'PeaksAndValleys' and 'data.frame': 2 obs. of 3 variables: 475s .. .. .. ..$ type : chr [1:2] "valley" "valley" 475s .. .. .. ..$ x : num [1:2] 0.312 0.678 475s .. .. .. ..$ density: num [1:2] 0.465 0.497 475s .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 475s Setup up data...done 475s Dropping loci for which TCNs are missing... 475s Number of loci dropped: 36 475s Dropping loci for which TCNs are missing...done 475s Ordering data along genome... 475s 'data.frame': 43974 obs. of 7 variables: 475s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 475s $ x : num 554484 730720 782343 878522 916294 ... 475s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 475s $ betaT : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 475s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 475s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 475s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 475s Ordering data along genome...done 475s Segmenting multiple chromosomes... 475s Number of chromosomes: 3 475s Random seed temporarily set (seed=c(48879), kind="L'Ecuyer-CMRG") 475s Produced 3 seeds from this stream for future usage 475s Chromosome #1 ('Chr01') of 3... 475s 'data.frame': 14658 obs. of 8 variables: 475s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 475s $ x : num 554484 730720 782343 878522 916294 ... 475s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 475s $ betaT : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 475s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 475s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 475s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 475s $ index : int 1 2 3 4 5 6 7 8 9 10 ... 475s Known segments: 475s [1] chromosome start end 475s <0 rows> (or 0-length row.names) 475s Chromosome #1 ('Chr01') of 3...done 475s Chromosome #2 ('Chr02') of 3... 475s 'data.frame': 14658 obs. of 8 variables: 475s $ chromosome: int 2 2 2 2 2 2 2 2 2 2 ... 475s $ x : num 554484 730720 782343 878522 916294 ... 475s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 475s $ betaT : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 475s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 475s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 475s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 475s $ index : int 14659 14660 14661 14662 14663 14664 14665 14666 14667 14668 ... 475s Known segments: 475s [1] chromosome start end 475s <0 rows> (or 0-length row.names) 475s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 475s Chromosome #2 ('Chr02') of 3...done 475s Chromosome #3 ('Chr03') of 3... 475s 'data.frame': 14658 obs. of 8 variables: 475s $ chromosome: int 3 3 3 3 3 3 3 3 3 3 ... 475s $ x : num 554484 730720 782343 878522 916294 ... 475s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 475s $ betaT : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 475s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 475s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 475s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 475s $ index : int 29317 29318 29319 29320 29321 29322 29323 29324 29325 29326 ... 475s Known segments: 475s [1] chromosome start end 475s <0 rows> (or 0-length row.names) 475s Random seed temporarily set (seed=c(10407, -821273412, -52578226, 1415511586, 721384351, -665928286, 1316562960), kind="L'Ecuyer-CMRG") 475s Segmenting by CBS...done 475s List of 4 475s $ data :'data.frame': 14658 obs. of 4 variables: 475s ..$ chromosome: int [1:14658] 1 1 1 1 1 1 1 1 1 1 ... 475s ..$ x : num [1:14658] 554484 730720 782343 878522 916294 ... 475s ..$ y : num [1:14658] 1.88 1.8 1.59 1.64 1.53 ... 475s ..$ index : int [1:14658] 1 2 3 4 5 6 7 8 9 10 ... 475s $ output :'data.frame': 3 obs. of 6 variables: 475s ..$ sampleName: chr [1:3] NA NA NA 475s ..$ chromosome: int [1:3] 1 1 1 475s ..$ start : num [1:3] 5.54e+05 1.44e+08 1.85e+08 475s ..$ end : num [1:3] 1.44e+08 1.85e+08 2.47e+08 475s ..$ nbrOfLoci : int [1:3] 7599 2668 4391 475s ..$ mean : num [1:3] 1.39 2.07 2.63 475s $ segRows:'data.frame': 3 obs. of 2 variables: 475s ..$ startRow: int [1:3] 1 7600 10268 475s ..$ endRow : int [1:3] 7599 10267 14658 475s $ params :List of 5 475s ..$ alpha : num 0.009 475s ..$ undo : num 0 475s ..$ joinSegments : logi TRUE 475s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 475s .. ..$ chromosome: int 1 475s .. ..$ start : num -Inf 475s .. ..$ end : num Inf 475s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 475s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 475s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.421 0 0.454 0 0 475s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 475s - attr(*, "pkgDetails")= chr "DNAcopy v1.76.0" 475s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 475s Identification of change points by total copy numbers...done 475s Restructure TCN segmentation results... 475s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean 475s 1 1 554484 143926517 7599 1.3859 475s 2 1 143926517 185449813 2668 2.0704 475s 3 1 185449813 247137334 4391 2.6341 475s Number of TCN segments: 3 475s Restructure TCN segmentation results...done 475s Total CN segment #1 ([ 554484,1.43927e+08]) of 3... 475s Number of TCN loci in segment: 7599 475s Locus data for TCN segment: 475s 'data.frame': 7599 obs. of 9 variables: 475s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 475s $ x : num 554484 730720 782343 878522 916294 ... 475s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 475s $ betaT : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 475s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 475s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 475s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 475s $ index : int 1 2 3 4 5 6 7 8 9 10 ... 475s $ rho : num NA NA NA NA NA ... 475s Number of loci: 7599 475s Number of SNPs: 2120 (27.90%) 475s Number of heterozygous SNPs: 2120 (100.00%) 475s Chromosome: 1 475s Segmenting DH signals... 475s Segmenting by CBS... 475s Chromosome: 1 475s Random seed temporarily set (seed=c(10407, -821273412, -52578226, 1415511586, 721384351, -665928286, 1316562960), kind="L'Ecuyer-CMRG") 475s Segmenting by CBS...done 475s List of 4 475s $ data :'data.frame': 7599 obs. of 4 variables: 475s ..$ chromosome: int [1:7599] 1 1 1 1 1 1 1 1 1 1 ... 475s ..$ x : num [1:7599] 554484 730720 782343 878522 916294 ... 475s ..$ y : num [1:7599] NA NA NA NA NA ... 475s ..$ index : int [1:7599] 1 2 3 4 5 6 7 8 9 10 ... 475s $ output :'data.frame': 1 obs. of 6 variables: 475s ..$ sampleName: chr NA 475s ..$ chromosome: int 1 475s ..$ start : num 554484 475s ..$ end : num 1.44e+08 475s ..$ nbrOfLoci : int 2120 475s ..$ mean : num 0.51 475s $ segRows:'data.frame': 1 obs. of 2 variables: 475s ..$ startRow: int 10 475s ..$ endRow : int 7594 475s $ params :List of 5 475s ..$ alpha : num 0.001 475s ..$ undo : num 0 475s ..$ joinSegments : logi TRUE 475s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 475s .. ..$ chromosome: int 1 475s .. ..$ start : num 554484 475s .. ..$ end : num 1.44e+08 475s ..$ seed : int [1:7] 10407 -821273412 -52578226 1415511586 721384351 -665928286 1316562960 475s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 475s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.024 0 0.025 0 0 475s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 475s - attr(*, "pkgDetails")= chr "DNAcopy v1.76.0" 475s - attr(*, "randomSeed")= int [1:7] 10407 -821273412 -52578226 1415511586 721384351 -665928286 1316562960 475s DH segmentation (locally-indexed) rows: 475s startRow endRow 475s 1 10 7594 475s int [1:7599] 1 2 3 4 5 6 7 8 9 10 ... 475s DH segmentation rows: 475s startRow endRow 475s 1 10 7594 475s Segmenting DH signals...done 475s DH segmentation table: 475s dhStart dhEnd dhNbrOfLoci dhMean 475s 1 554484 143926517 2120 0.5101 475s startRow endRow 475s 1 10 7594 475s Rows: 475s [1] 1 475s TCN segmentation rows: 475s startRow endRow 475s 1 1 7599 475s TCN and DH segmentation rows: 475s startRow endRow 475s 1 1 7599 475s startRow endRow 475s 1 10 7594 475s NULL 475s TCN segmentation (expanded) rows: 475s startRow endRow 475s 1 1 7599 475s TCN and DH segmentation rows: 475s startRow endRow 475s 1 1 7599 475s 2 7600 10267 475s 3 10268 14658 475s startRow endRow 475s 1 10 7594 475s startRow endRow 475s 1 1 7599 475s Total CN segmentation table (expanded): 475s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 475s 1 1 554484 143926517 7599 1.3859 2120 2120 475s (TCN,DH) segmentation for one total CN segment: 475s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 475s 1 1 1 1 554484 143926517 7599 1.3859 2120 475s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 475s 1 2120 554484 143926517 2120 0.5101 475s Total CN segment #1 ([ 554484,1.43927e+08]) of 3...done 475s Total CN segment #2 ([1.43927e+08,1.8545e+08]) of 3... 475s Number of TCN loci in segment: 2668 475s Locus data for TCN segment: 475s 'data.frame': 2668 obs. of 9 variables: 475s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 475s $ x : num 1.44e+08 1.44e+08 1.44e+08 1.44e+08 1.44e+08 ... 475s $ CT : num 2.1 2.1 2.09 1.8 2.34 ... 475s $ betaT : num 0.027542 1.030222 1.094093 0.046763 -0.000948 ... 475s $ betaTN : num 0.027542 1.030222 1.094093 0.046763 -0.000948 ... 475s $ betaN : num 0.1624 0.8788 0.8225 0.1201 0.0317 ... 475s $ muN : num 0 1 1 0 0 1 0 0 0 0 ... 475s $ index : int 7600 7601 7602 7603 7604 7605 7606 7607 7608 7609 ... 475s $ rho : num NA NA NA NA NA NA NA NA NA NA ... 475s Number of loci: 2668 475s Number of SNPs: 775 (29.05%) 475s Number of heterozygous SNPs: 775 (100.00%) 475s Chromosome: 1 475s Segmenting DH signals... 475s Segmenting by CBS... 475s Chromosome: 1 475s Random seed temporarily set (seed=c(10407, -821273412, -52578226, 1415511586, 721384351, -665928286, 1316562960), kind="L'Ecuyer-CMRG") 475s Segmenting by CBS...done 475s List of 4 475s $ data :'data.frame': 2668 obs. of 4 variables: 475s ..$ chromosome: int [1:2668] 1 1 1 1 1 1 1 1 1 1 ... 475s ..$ x : num [1:2668] 1.44e+08 1.44e+08 1.44e+08 1.44e+08 1.44e+08 ... 475s ..$ y : num [1:2668] NA NA NA NA NA NA NA NA NA NA ... 475s ..$ index : int [1:2668] 1 2 3 4 5 6 7 8 9 10 ... 475s $ output :'data.frame': 1 obs. of 6 variables: 475s ..$ sampleName: chr NA 475s ..$ chromosome: int 1 475s ..$ start : num 1.44e+08 475s ..$ end : num 1.85e+08 475s ..$ nbrOfLoci : int 775 475s ..$ mean : num 0.097 475s $ segRows:'data.frame': 1 obs. of 2 variables: 475s ..$ startRow: int 15 475s ..$ endRow : int 2664 475s $ params :List of 5 475s ..$ alpha : num 0.001 475s ..$ undo : num 0 475s ..$ joinSegments : logi TRUE 475s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 475s .. ..$ chromosome: int 1 475s .. ..$ start : num 1.44e+08 475s .. ..$ end : num 1.85e+08 475s ..$ seed : int [1:7] 10407 -821273412 -52578226 1415511586 721384351 -665928286 1316562960 475s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 475s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.047 0 0.048 0 0 475s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 475s - attr(*, "pkgDetails")= chr "DNAcopy v1.76.0" 475s - attr(*, "randomSeed")= int [1:7] 10407 -821273412 -52578226 1415511586 721384351 -665928286 1316562960 475s DH segmentation (locally-indexed) rows: 475s startRow endRow 475s 1 15 2664 475s int [1:2668] 7600 7601 7602 7603 7604 7605 7606 7607 7608 7609 ... 475s DH segmentation rows: 475s startRow endRow 475s 1 7614 10263 475s Segmenting DH signals...done 475s DH segmentation table: 475s dhStart dhEnd dhNbrOfLoci dhMean 475s 1 143926517 185449813 775 0.097 475s startRow endRow 475s 1 7614 10263 475s Rows: 475s [1] 2 475s TCN segmentation rows: 475s startRow endRow 475s 2 7600 10267 475s TCN and DH segmentation rows: 475s startRow endRow 475s 2 7600 10267 475s startRow endRow 475s 1 7614 10263 475s startRow endRow 475s 1 1 7599 475s TCN segmentation (expanded) rows: 475s startRow endRow 475s 1 1 7599 475s 2 7600 10267 475s TCN and DH segmentation rows: 475s startRow endRow 475s 1 1 7599 475s 2 7600 10267 475s 3 10268 14658 475s startRow endRow 475s 1 10 7594 475s 2 7614 10263 475s startRow endRow 475s 1 1 7599 475s 2 7600 10267 475s Total CN segmentation table (expanded): 475s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 475s 2 1 143926517 185449813 2668 2.0704 775 775 475s (TCN,DH) segmentation for one total CN segment: 475s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 475s 2 2 1 1 143926517 185449813 2668 2.0704 775 475s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 475s 2 775 143926517 185449813 775 0.097 475s Total CN segment #2 ([1.43927e+08,1.8545e+08]) of 3...done 475s Total CN segment #3 ([1.8545e+08,2.47137e+08]) of 3... 475s Number of TCN loci in segment: 4391 475s Locus data for TCN segment: 475s 'data.frame': 4391 obs. of 9 variables: 475s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 475s $ x : num 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 475s $ CT : num 2.93 2.15 2.82 2.93 2.46 ... 475s $ betaT : num -0.169 0.609 1.028 0.525 0.968 ... 475s $ betaTN : num -0.169 0.609 1.028 0.525 0.968 ... 475s $ betaN : num 0.25 0.38 0.919 0.34 0.783 ... 475s $ muN : num 0 0.5 1 0.5 1 1 0 1 0 1 ... 475s $ index : int 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 475s $ rho : num NA 0.2186 NA 0.0503 NA ... 475s Number of loci: 4391 475s Number of SNPs: 1314 (29.92%) 475s Number of heterozygous SNPs: 1314 (100.00%) 475s Chromosome: 1 475s Segmenting DH signals... 475s Segmenting by CBS... 475s Chromosome: 1 475s Segmenting by CBS...done 475s Random seed temporarily set (seed=c(10407, -821273412, -52578226, 1415511586, 721384351, -665928286, 1316562960), kind="L'Ecuyer-CMRG") 475s List of 4 475s $ data :'data.frame': 14658 obs. of 4 variables: 475s ..$ chromosome: int [1:14658] 2 2 2 2 2 2 2 2 2 2 ... 475s ..$ x : num [1:14658] 554484 730720 782343 878522 916294 ... 475s ..$ y : num [1:14658] 1.88 1.8 1.59 1.64 1.53 ... 475s ..$ index : int [1:14658] 1 2 3 4 5 6 7 8 9 10 ... 475s $ output :'data.frame': 3 obs. of 6 variables: 475s ..$ sampleName: chr [1:3] NA NA NA 475s ..$ chromosome: int [1:3] 2 2 2 475s ..$ start : num [1:3] 5.54e+05 1.44e+08 1.85e+08 475s ..$ end : num [1:3] 1.44e+08 1.85e+08 2.47e+08 475s ..$ nbrOfLoci : int [1:3] 7599 2668 4391 475s ..$ mean : num [1:3] 1.39 2.07 2.63 475s $ segRows:'data.frame': 3 obs. of 2 variables: 475s ..$ startRow: int [1:3] 1 7600 10268 475s ..$ endRow : int [1:3] 7599 10267 14658 475s $ params :List of 5 475s ..$ alpha : num 0.009 475s ..$ undo : num 0 475s ..$ joinSegments : logi TRUE 475s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 475s .. ..$ chromosome: int 2 475s .. ..$ start : num -Inf 475s .. ..$ end : num Inf 475s ..$ seed : int [1:7] 10407 -821273412 -52578226 1415511586 721384351 -665928286 1316562960 475s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 475s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.446 0 0.447 0 0 475s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 475s - attr(*, "pkgDetails")= chr "DNAcopy v1.76.0" 475s - attr(*, "randomSeed")= int [1:7] 10407 -821273412 -52578226 1415511586 721384351 -665928286 1316562960 475s Identification of change points by total copy numbers...done 475s Restructure TCN segmentation results... 475s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean 475s 1 2 554484 143926517 7599 1.3859 475s 2 2 143926517 185449813 2668 2.0704 475s 3 2 185449813 247137334 4391 2.6341 475s Number of TCN segments: 3 475s Restructure TCN segmentation results...done 475s Total CN segment #1 ([ 554484,1.43927e+08]) of 3... 475s Number of TCN loci in segment: 7599 475s Locus data for TCN segment: 475s 'data.frame': 7599 obs. of 9 variables: 475s $ chromosome: int 2 2 2 2 2 2 2 2 2 2 ... 475s $ x : num 554484 730720 782343 878522 916294 ... 475s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 475s $ betaT : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 475s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 475s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 475s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 475s $ index : int 1 2 3 4 5 6 7 8 9 10 ... 475s $ rho : num NA NA NA NA NA ... 475s Number of loci: 7599 475s Number of SNPs: 2120 (27.90%) 475s Number of heterozygous SNPs: 2120 (100.00%) 475s Chromosome: 2 475s Segmenting DH signals... 475s Segmenting by CBS...done 475s Segmenting by CBS... 475s Chromosome: 2 475s List of 4 475s $ data :'data.frame': 4391 obs. of 4 variables: 475s ..$ chromosome: int [1:4391] 1 1 1 1 1 1 1 1 1 1 ... 475s ..$ x : num [1:4391] 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 475s ..$ y : num [1:4391] NA 0.2186 NA 0.0503 NA ... 475s ..$ index : int [1:4391] 1 2 3 4 5 6 7 8 9 10 ... 475s $ output :'data.frame': 1 obs. of 6 variables: 475s ..$ sampleName: chr NA 475s ..$ chromosome: int 1 475s ..$ start : num 1.85e+08 475s ..$ end : num 2.47e+08 475s ..$ nbrOfLoci : int 1314 475s ..$ mean : num 0.23 475s $ segRows:'data.frame': 1 obs. of 2 variables: 475s ..$ startRow: int 2 475s ..$ endRow : int 4388 475s $ params :List of 5 475s ..$ alpha : num 0.001 475s ..$ undo : num 0 475s ..$ joinSegments : logi TRUE 475s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 475s .. ..$ chromosome: int 1 475s .. ..$ start : num 1.85e+08 475s .. ..$ end : num 2.47e+08 475s ..$ seed : int [1:7] 10407 -821273412 -52578226 1415511586 721384351 -665928286 1316562960 475s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 475s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.014 0 0.015 0 0 475s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 475s - attr(*, "pkgDetails")= chr "DNAcopy v1.76.0" 475s - attr(*, "randomSeed")= int [1:7] 10407 -821273412 -52578226 1415511586 721384351 -665928286 1316562960 475s DH segmentation (locally-indexed) rows: 475s Random seed temporarily set (seed=c(10407, -1924040949, -1632234809, -437763632, -1464377300, 676654412, 2080370711), kind="L'Ecuyer-CMRG") 475s startRow endRow 475s 1 2 4388 475s int [1:4391] 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 475s DH segmentation rows: 475s startRow endRow 475s 1 10269 14655 475s Segmenting DH signals...done 475s DH segmentation table: 475s dhStart dhEnd dhNbrOfLoci dhMean 475s 1 185449813 247137334 1314 0.2295 475s startRow endRow 475s 1 10269 14655 475s Rows: 475s [1] 3 475s TCN segmentation rows: 475s startRow endRow 475s 3 10268 14658 475s TCN and DH segmentation rows: 475s startRow endRow 475s 3 10268 14658 475s startRow endRow 475s 1 10269 14655 475s startRow endRow 475s 1 1 7599 475s 2 7600 10267 475s TCN segmentation (expanded) rows: 475s startRow endRow 475s 1 1 7599 475s 2 7600 10267 475s 3 10268 14658 475s TCN and DH segmentation rows: 475s startRow endRow 475s 1 1 7599 475s 2 7600 10267 475s 3 10268 14658 475s startRow endRow 475s 1 10 7594 475s 2 7614 10263 475s 3 10269 14655 475s startRow endRow 475s 1 1 7599 475s 2 7600 10267 475s 3 10268 14658 475s Total CN segmentation table (expanded): 475s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 475s 3 1 185449813 247137334 4391 2.6341 1314 1314 475s (TCN,DH) segmentation for one total CN segment: 475s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 475s 3 3 1 1 185449813 247137334 4391 2.6341 1314 475s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 475s 3 1314 185449813 247137334 1314 0.2295 475s Total CN segment #3 ([1.8545e+08,2.47137e+08]) of 3...done 475s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 475s 1 1 1 1 554484 143926517 7599 1.3859 2120 475s 2 1 2 1 143926517 185449813 2668 2.0704 775 475s 3 1 3 1 185449813 247137334 4391 2.6341 1314 475s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 475s 1 2120 554484 143926517 2120 0.5101 475s 2 775 143926517 185449813 775 0.0970 475s 3 1314 185449813 247137334 1314 0.2295 475s Calculating (C1,C2) per segment... 475s Calculating (C1,C2) per segment...done 475s Number of segments: 3 475s Segmenting paired tumor-normal signals using Paired PSCBS...done 475s Post-segmenting TCNs... 475s Number of segments: 3 475s Number of chromosomes: 1 475s [1] 1 475s Chromosome 1 ('chr01') of 1... 475s Rows: 475s [1] 1 2 3 475s Number of segments: 3 475s TCN segment #1 ('1') of 3... 475s Nothing todo. Only one DH segmentation. Skipping. 475s TCN segment #1 ('1') of 3...done 475s TCN segment #2 ('2') of 3... 475s Nothing todo. Only one DH segmentation. Skipping. 475s TCN segment #2 ('2') of 3...done 475s TCN segment #3 ('3') of 3... 475s Nothing todo. Only one DH segmentation. Skipping. 475s TCN segment #3 ('3') of 3...done 475s Chromosome 1 ('chr01') of 1...done 475s Segmenting by CBS...done 475s Update (C1,C2) per segment... 475s Update (C1,C2) per segment...done 475s Post-segmenting TCNs...done 475s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 475s 1 1 1 1 554484 143926517 7599 1.3859 2120 475s 2 1 2 1 143926517 185449813 2668 2.0704 775 475s 3 1 3 1 185449813 247137334 4391 2.6341 1314 475s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 475s 1 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 475s 2 775 143926517 185449813 775 0.0970 0.9347856 1.135614 475s 3 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 475s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 475s 1 1 1 1 554484 143926517 7599 1.3859 2120 475s 2 1 2 1 143926517 185449813 2668 2.0704 775 475s 3 1 3 1 185449813 247137334 4391 2.6341 1314 475s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 475s 1 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 475s 2 775 143926517 185449813 775 0.0970 0.9347856 1.135614 475s 3 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 475s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 475s 1 1 1 1 554484 143926517 7599 1.3859 2120 475s 2 1 2 1 143926517 185449813 2668 2.0704 775 475s 3 1 3 1 185449813 247137334 4391 2.6341 1314 475s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 475s 1 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 475s 2 775 143926517 185449813 775 0.0970 0.9347856 1.135614 475s 3 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 475s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 475s 1 1 1 1 554484 143926517 7599 1.3859 2120 475s 2 1 2 1 143926517 185449813 2668 2.0704 775 475s 3 1 3 1 185449813 247137334 4391 2.6341 1314 475s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 475s 1 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 475s 2 775 143926517 185449813 775 0.0970 0.9347856 1.135614 475s 3 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 475s List of 4 475s $ data :'data.frame': 7599 obs. of 4 variables: 475s ..$ chromosome: int [1:7599] 2 2 2 2 2 2 2 2 2 2 ... 475s ..$ x : num [1:7599] 554484 730720 782343 878522 916294 ... 475s ..$ y : num [1:7599] NA NA NA NA NA ... 475s ..$ index : int [1:7599] 1 2 3 4 5 6 7 8 9 10 ... 475s $ output :'data.frame': 1 obs. of 6 variables: 475s ..$ sampleName: chr NA 475s ..$ chromosome: int 2 475s ..$ start : num 554484 475s ..$ end : num 1.44e+08 475s ..$ nbrOfLoci : int 2120 475s ..$ mean : num 0.51 475s $ segRows:'data.frame': 1 obs. of 2 variables: 475s ..$ startRow: int 10 475s ..$ endRow : int 7594 475s $ params :List of 5 475s ..$ alpha : num 0.001 475s ..$ undo : num 0 475s ..$ joinSegments : logi TRUE 475s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 475s .. ..$ chromosome: int 2 475s .. ..$ start : num 554484 475s .. ..$ end : num 1.44e+08 475s ..$ seed : int [1:7] 10407 -1924040949 -1632234809 -437763632 -1464377300 676654412 2080370711 475s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 475s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.024 0 0.024 0 0 475s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 475s - attr(*, "pkgDetails")= chr "DNAcopy v1.76.0" 475s - attr(*, "randomSeed")= int [1:7] 10407 -1924040949 -1632234809 -437763632 -1464377300 676654412 2080370711 475s DH segmentation (locally-indexed) rows: 475s startRow endRow 475s 1 10 7594 475s int [1:7599] 1 2 3 4 5 6 7 8 9 10 ... 475s DH segmentation rows: 475s startRow endRow 475s 1 10 7594 475s Segmenting DH signals...done 475s DH segmentation table: 475s dhStart dhEnd dhNbrOfLoci dhMean 475s 1 554484 143926517 2120 0.5101 475s startRow endRow 475s 1 10 7594 475s Rows: 475s [1] 1 475s TCN segmentation rows: 475s startRow endRow 475s 1 1 7599 475s TCN and DH segmentation rows: 475s startRow endRow 475s 1 1 7599 475s startRow endRow 475s 1 10 7594 475s NULL 475s TCN segmentation (expanded) rows: 475s startRow endRow 475s 1 1 7599 475s TCN and DH segmentation rows: 475s startRow endRow 475s 1 1 7599 475s 2 7600 10267 475s 3 10268 14658 475s startRow endRow 475s 1 10 7594 475s startRow endRow 475s 1 1 7599 475s Total CN segmentation table (expanded): 475s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 475s 1 2 554484 143926517 7599 1.3859 2120 2120 475s (TCN,DH) segmentation for one total CN segment: 475s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 475s 1 1 1 2 554484 143926517 7599 1.3859 2120 475s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 475s 1 2120 554484 143926517 2120 0.5101 475s Total CN segment #1 ([ 554484,1.43927e+08]) of 3...done 475s Total CN segment #2 ([1.43927e+08,1.8545e+08]) of 3... 475s Number of TCN loci in segment: 2668 475s Locus data for TCN segment: 475s 'data.frame': 2668 obs. of 9 variables: 475s $ chromosome: int 2 2 2 2 2 2 2 2 2 2 ... 475s $ x : num 1.44e+08 1.44e+08 1.44e+08 1.44e+08 1.44e+08 ... 475s $ CT : num 2.1 2.1 2.09 1.8 2.34 ... 475s $ betaT : num 0.027542 1.030222 1.094093 0.046763 -0.000948 ... 475s $ betaTN : num 0.027542 1.030222 1.094093 0.046763 -0.000948 ... 475s $ betaN : num 0.1624 0.8788 0.8225 0.1201 0.0317 ... 475s $ muN : num 0 1 1 0 0 1 0 0 0 0 ... 475s $ index : int 7600 7601 7602 7603 7604 7605 7606 7607 7608 7609 ... 475s $ rho : num NA NA NA NA NA NA NA NA NA NA ... 475s Number of loci: 2668 475s Number of SNPs: 775 (29.05%) 475s Number of heterozygous SNPs: 775 (100.00%) 475s Chromosome: 2 475s Segmenting DH signals... 475s Segmenting by CBS... 475s Chromosome: 2 475s Random seed temporarily set (seed=c(10407, -1924040949, -1632234809, -437763632, -1464377300, 676654412, 2080370711), kind="L'Ecuyer-CMRG") 475s Segmenting by CBS...done 475s List of 4 475s $ data :'data.frame': 2668 obs. of 4 variables: 475s ..$ chromosome: int [1:2668] 2 2 2 2 2 2 2 2 2 2 ... 475s ..$ x : num [1:2668] 1.44e+08 1.44e+08 1.44e+08 1.44e+08 1.44e+08 ... 475s ..$ y : num [1:2668] NA NA NA NA NA NA NA NA NA NA ... 475s ..$ index : int [1:2668] 1 2 3 4 5 6 7 8 9 10 ... 475s $ output :'data.frame': 1 obs. of 6 variables: 475s ..$ sampleName: chr NA 475s ..$ chromosome: int 2 475s ..$ start : num 1.44e+08 475s ..$ end : num 1.85e+08 475s ..$ nbrOfLoci : int 775 475s ..$ mean : num 0.097 475s $ segRows:'data.frame': 1 obs. of 2 variables: 475s ..$ startRow: int 15 475s ..$ endRow : int 2664 475s $ params :List of 5 475s ..$ alpha : num 0.001 475s ..$ undo : num 0 475s ..$ joinSegments : logi TRUE 475s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 475s .. ..$ chromosome: int 2 475s .. ..$ start : num 1.44e+08 475s .. ..$ end : num 1.85e+08 475s ..$ seed : int [1:7] 10407 -1924040949 -1632234809 -437763632 -1464377300 676654412 2080370711 475s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 475s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.007 0 0.007 0 0 475s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 475s - attr(*, "pkgDetails")= chr "DNAcopy v1.76.0" 475s - attr(*, "randomSeed")= int [1:7] 10407 -1924040949 -1632234809 -437763632 -1464377300 676654412 2080370711 475s DH segmentation (locally-indexed) rows: 475s startRow endRow 475s 1 15 2664 475s int [1:2668] 7600 7601 7602 7603 7604 7605 7606 7607 7608 7609 ... 475s DH segmentation rows: 475s startRow endRow 475s 1 7614 10263 475s Segmenting DH signals...done 475s DH segmentation table: 475s dhStart dhEnd dhNbrOfLoci dhMean 475s 1 143926517 185449813 775 0.097 475s startRow endRow 475s 1 7614 10263 475s Rows: 475s [1] 2 475s TCN segmentation rows: 475s startRow endRow 475s 2 7600 10267 475s TCN and DH segmentation rows: 475s startRow endRow 475s 2 7600 10267 475s startRow endRow 475s 1 7614 10263 475s startRow endRow 475s 1 1 7599 475s TCN segmentation (expanded) rows: 475s startRow endRow 475s 1 1 7599 475s 2 7600 10267 475s TCN and DH segmentation rows: 475s startRow endRow 475s 1 1 7599 475s 2 7600 10267 475s 3 10268 14658 475s startRow endRow 475s 1 10 7594 475s 2 7614 10263 475s startRow endRow 475s 1 1 7599 475s 2 7600 10267 475s Total CN segmentation table (expanded): 475s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 475s 2 2 143926517 185449813 2668 2.0704 775 775 475s (TCN,DH) segmentation for one total CN segment: 475s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 475s 2 2 1 2 143926517 185449813 2668 2.0704 775 475s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 475s 2 775 143926517 185449813 775 0.097 475s Total CN segment #2 ([1.43927e+08,1.8545e+08]) of 3...done 475s Total CN segment #3 ([1.8545e+08,2.47137e+08]) of 3... 475s Number of TCN loci in segment: 4391 475s Locus data for TCN segment: 475s 'data.frame': 4391 obs. of 9 variables: 475s $ chromosome: int 2 2 2 2 2 2 2 2 2 2 ... 475s $ x : num 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 475s $ CT : num 2.93 2.15 2.82 2.93 2.46 ... 475s $ betaT : num -0.169 0.609 1.028 0.525 0.968 ... 475s $ betaTN : num -0.169 0.609 1.028 0.525 0.968 ... 475s $ betaN : num 0.25 0.38 0.919 0.34 0.783 ... 475s $ muN : num 0 0.5 1 0.5 1 1 0 1 0 1 ... 475s $ index : int 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 475s $ rho : num NA 0.2186 NA 0.0503 NA ... 475s Number of loci: 4391 475s Number of SNPs: 1314 (29.92%) 475s Number of heterozygous SNPs: 1314 (100.00%) 475s Chromosome: 2 475s Segmenting DH signals... 475s Segmenting by CBS... 475s Chromosome: 2 475s Random seed temporarily set (seed=c(10407, -1924040949, -1632234809, -437763632, -1464377300, 676654412, 2080370711), kind="L'Ecuyer-CMRG") 475s Segmenting by CBS...done 475s List of 4 475s $ data :'data.frame': 4391 obs. of 4 variables: 475s ..$ chromosome: int [1:4391] 2 2 2 2 2 2 2 2 2 2 ... 475s ..$ x : num [1:4391] 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 475s ..$ y : num [1:4391] NA 0.2186 NA 0.0503 NA ... 475s ..$ index : int [1:4391] 1 2 3 4 5 6 7 8 9 10 ... 475s $ output :'data.frame': 1 obs. of 6 variables: 475s ..$ sampleName: chr NA 475s ..$ chromosome: int 2 475s ..$ start : num 1.85e+08 475s ..$ end : num 2.47e+08 475s ..$ nbrOfLoci : int 1314 475s ..$ mean : num 0.23 475s $ segRows:'data.frame': 1 obs. of 2 variables: 475s ..$ startRow: int 2 475s ..$ endRow : int 4388 475s $ params :List of 5 475s ..$ alpha : num 0.001 475s ..$ undo : num 0 475s ..$ joinSegments : logi TRUE 475s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 475s .. ..$ chromosome: int 2 475s .. ..$ start : num 1.85e+08 475s .. ..$ end : num 2.47e+08 475s ..$ seed : int [1:7] 10407 -1924040949 -1632234809 -437763632 -1464377300 676654412 2080370711 475s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 475s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.015 0 0.015 0 0 475s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 475s - attr(*, "pkgDetails")= chr "DNAcopy v1.76.0" 475s - attr(*, "randomSeed")= int [1:7] 10407 -1924040949 -1632234809 -437763632 -1464377300 676654412 2080370711 475s DH segmentation (locally-indexed) rows: 475s startRow endRow 475s 1 2 4388 475s int [1:4391] 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 475s DH segmentation rows: 475s startRow endRow 475s 1 10269 14655 475s Segmenting DH signals...done 475s DH segmentation table: 475s dhStart dhEnd dhNbrOfLoci dhMean 475s 1 185449813 247137334 1314 0.2295 475s startRow endRow 475s 1 10269 14655 475s Rows: 475s [1] 3 475s TCN segmentation rows: 475s startRow endRow 475s 3 10268 14658 475s TCN and DH segmentation rows: 475s startRow endRow 475s 3 10268 14658 475s startRow endRow 475s 1 10269 14655 475s startRow endRow 475s 1 1 7599 475s 2 7600 10267 475s TCN segmentation (expanded) rows: 475s startRow endRow 475s 1 1 7599 475s 2 7600 10267 475s 3 10268 14658 475s TCN and DH segmentation rows: 475s startRow endRow 475s 1 1 7599 475s 2 7600 10267 475s 3 10268 14658 475s startRow endRow 475s 1 10 7594 475s 2 7614 10263 475s 3 10269 14655 475s startRow endRow 475s 1 1 7599 475s 2 7600 10267 475s 3 10268 14658 475s Total CN segmentation table (expanded): 475s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 475s 3 2 185449813 247137334 4391 2.6341 1314 1314 475s (TCN,DH) segmentation for one total CN segment: 475s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 475s 3 3 1 2 185449813 247137334 4391 2.6341 1314 475s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 475s 3 1314 185449813 247137334 1314 0.2295 475s Total CN segment #3 ([1.8545e+08,2.47137e+08]) of 3...done 475s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 475s 1 2 1 1 554484 143926517 7599 1.3859 2120 475s 2 2 2 1 143926517 185449813 2668 2.0704 775 475s 3 2 3 1 185449813 247137334 4391 2.6341 1314 475s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 475s 1 2120 554484 143926517 2120 0.5101 475s 2 775 143926517 185449813 775 0.0970 475s 3 1314 185449813 247137334 1314 0.2295 475s Calculating (C1,C2) per segment... 475s Calculating (C1,C2) per segment...done 475s Number of segments: 3 475s Segmenting paired tumor-normal signals using Paired PSCBS...done 475s Post-segmenting TCNs... 475s Number of segments: 3 475s Number of chromosomes: 1 475s [1] 2 475s Chromosome 1 ('chr02') of 1... 475s Rows: 475s [1] 1 2 3 475s Number of segments: 3 475s TCN segment #1 ('1') of 3... 475s Nothing todo. Only one DH segmentation. Skipping. 475s TCN segment #1 ('1') of 3...done 475s TCN segment #2 ('2') of 3... 475s Nothing todo. Only one DH segmentation. Skipping. 475s TCN segment #2 ('2') of 3...done 475s TCN segment #3 ('3') of 3... 475s Nothing todo. Only one DH segmentation. Skipping. 475s TCN segment #3 ('3') of 3...done 475s Chromosome 1 ('chr02') of 1...done 475s Update (C1,C2) per segment... 475s Update (C1,C2) per segment...done 475s Post-segmenting TCNs...done 475s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 475s 1 2 1 1 554484 143926517 7599 1.3859 2120 475s 2 2 2 1 143926517 185449813 2668 2.0704 775 475s 3 2 3 1 185449813 247137334 4391 2.6341 1314 475s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 475s 1 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 475s 2 775 143926517 185449813 775 0.0970 0.9347856 1.135614 475s 3 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 475s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 475s 1 2 1 1 554484 143926517 7599 1.3859 2120 475s 2 2 2 1 143926517 185449813 2668 2.0704 775 475s 3 2 3 1 185449813 247137334 4391 2.6341 1314 475s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 475s 1 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 475s 2 775 143926517 185449813 775 0.0970 0.9347856 1.135614 475s 3 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 475s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 475s 1 2 1 1 554484 143926517 7599 1.3859 2120 475s 2 2 2 1 143926517 185449813 2668 2.0704 775 475s 3 2 3 1 185449813 247137334 4391 2.6341 1314 475s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 475s 1 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 475s 2 775 143926517 185449813 775 0.0970 0.9347856 1.135614 475s 3 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 475s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 475s 1 2 1 1 554484 143926517 7599 1.3859 2120 475s 2 2 2 1 143926517 185449813 2668 2.0704 775 475s 3 2 3 1 185449813 247137334 4391 2.6341 1314 475s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 475s 1 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 475s 2 775 143926517 185449813 775 0.0970 0.9347856 1.135614 475s 3 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 475s Chromosome #3 ('Chr03') of 3...done 475s Merging (independently) segmented chromosome... 475s Segmenting paired tumor-normal signals using Paired PSCBS... 475s Setup up data... 475s 'data.frame': 14658 obs. of 7 variables: 475s $ chromosome: int 3 3 3 3 3 3 3 3 3 3 ... 475s $ x : num 554484 730720 782343 878522 916294 ... 475s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 475s $ betaT : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 475s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 475s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 475s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 475s Setup up data...done 475s Ordering data along genome... 475s 'data.frame': 14658 obs. of 7 variables: 475s $ chromosome: int 3 3 3 3 3 3 3 3 3 3 ... 475s $ x : num 554484 730720 782343 878522 916294 ... 475s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 475s $ betaT : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 475s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 475s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 475s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 475s Ordering data along genome...done 475s Keeping only current chromosome for 'knownSegments'... 475s Chromosome: 3 475s Known segments for this chromosome: 475s [1] chromosome start end 475s <0 rows> (or 0-length row.names) 475s Keeping only current chromosome for 'knownSegments'...done 475s alphaTCN: 0.009 475s alphaDH: 0.001 475s Number of loci: 14658 475s Calculating DHs... 475s Number of SNPs: 14658 475s Number of heterozygous SNPs: 4209 (28.71%) 475s Normalized DHs: 475s num [1:14658] NA NA NA NA NA ... 475s Calculating DHs...done 475s Random seed temporarily set (seed=c(10407, -821273412, -52578226, 1415511586, 721384351, -665928286, 1316562960), kind="L'Ecuyer-CMRG") 475s Produced 2 seeds from this stream for future usage 475s Identification of change points by total copy numbers... 475s Segmenting by CBS... 475s Chromosome: 3 475s Random seed temporarily set (seed=c(10407, -1924040949, -1632234809, -437763632, -1464377300, 676654412, 2080370711), kind="L'Ecuyer-CMRG") 475s Segmenting by CBS...done 475s List of 4 475s $ data :'data.frame': 14658 obs. of 4 variables: 475s ..$ chromosome: int [1:14658] 3 3 3 3 3 3 3 3 3 3 ... 475s ..$ x : num [1:14658] 554484 730720 782343 878522 916294 ... 475s ..$ y : num [1:14658] 1.88 1.8 1.59 1.64 1.53 ... 475s ..$ index : int [1:14658] 1 2 3 4 5 6 7 8 9 10 ... 475s $ output :'data.frame': 3 obs. of 6 variables: 475s ..$ sampleName: chr [1:3] NA NA NA 475s ..$ chromosome: int [1:3] 3 3 3 475s ..$ start : num [1:3] 5.54e+05 1.44e+08 1.85e+08 475s ..$ end : num [1:3] 1.44e+08 1.85e+08 2.47e+08 475s ..$ nbrOfLoci : int [1:3] 7599 2668 4391 475s ..$ mean : num [1:3] 1.39 2.07 2.63 475s $ segRows:'data.frame': 3 obs. of 2 variables: 475s ..$ startRow: int [1:3] 1 7600 10268 475s ..$ endRow : int [1:3] 7599 10267 14658 475s $ params :List of 5 475s ..$ alpha : num 0.009 475s ..$ undo : num 0 475s ..$ joinSegments : logi TRUE 475s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 475s .. ..$ chromosome: int 3 475s .. ..$ start : num -Inf 475s .. ..$ end : num Inf 475s ..$ seed : int [1:7] 10407 -1924040949 -1632234809 -437763632 -1464377300 676654412 2080370711 475s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 475s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.423 0 0.423 0 0 475s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 475s - attr(*, "pkgDetails")= chr "DNAcopy v1.76.0" 475s - attr(*, "randomSeed")= int [1:7] 10407 -1924040949 -1632234809 -437763632 -1464377300 676654412 2080370711 475s Identification of change points by total copy numbers...done 475s Restructure TCN segmentation results... 475s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean 475s 1 3 554484 143926517 7599 1.3859 475s 2 3 143926517 185449813 2668 2.0704 475s 3 3 185449813 247137334 4391 2.6341 475s Number of TCN segments: 3 475s Restructure TCN segmentation results...done 475s Total CN segment #1 ([ 554484,1.43927e+08]) of 3... 475s Number of TCN loci in segment: 7599 475s Locus data for TCN segment: 475s 'data.frame': 7599 obs. of 9 variables: 475s $ chromosome: int 3 3 3 3 3 3 3 3 3 3 ... 475s $ x : num 554484 730720 782343 878522 916294 ... 475s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 475s $ betaT : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 475s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 475s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 475s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 475s $ index : int 1 2 3 4 5 6 7 8 9 10 ... 475s $ rho : num NA NA NA NA NA ... 475s Number of loci: 7599 475s Number of SNPs: 2120 (27.90%) 475s Number of heterozygous SNPs: 2120 (100.00%) 475s Chromosome: 3 475s Segmenting DH signals... 475s Segmenting by CBS... 475s Chromosome: 3 475s Random seed temporarily set (seed=c(10407, -1371615447, -889757879, 1692656974, -1723952224, 1378814990, 1816467252), kind="L'Ecuyer-CMRG") 475s Segmenting by CBS...done 475s List of 4 475s $ data :'data.frame': 7599 obs. of 4 variables: 475s ..$ chromosome: int [1:7599] 3 3 3 3 3 3 3 3 3 3 ... 475s ..$ x : num [1:7599] 554484 730720 782343 878522 916294 ... 475s ..$ y : num [1:7599] NA NA NA NA NA ... 475s ..$ index : int [1:7599] 1 2 3 4 5 6 7 8 9 10 ... 475s $ output :'data.frame': 1 obs. of 6 variables: 475s ..$ sampleName: chr NA 475s ..$ chromosome: int 3 475s ..$ start : num 554484 475s ..$ end : num 1.44e+08 475s ..$ nbrOfLoci : int 2120 475s ..$ mean : num 0.51 475s $ segRows:'data.frame': 1 obs. of 2 variables: 475s ..$ startRow: int 10 475s ..$ endRow : int 7594 475s $ params :List of 5 475s ..$ alpha : num 0.001 475s ..$ undo : num 0 475s ..$ joinSegments : logi TRUE 475s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 475s .. ..$ chromosome: int 3 475s .. ..$ start : num 554484 475s .. ..$ end : num 1.44e+08 475s ..$ seed : int [1:7] 10407 -1371615447 -889757879 1692656974 -1723952224 1378814990 1816467252 475s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 475s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.023 0 0.024 0 0 475s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 475s - attr(*, "pkgDetails")= chr "DNAcopy v1.76.0" 475s - attr(*, "randomSeed")= int [1:7] 10407 -1371615447 -889757879 1692656974 -1723952224 1378814990 1816467252 475s DH segmentation (locally-indexed) rows: 475s startRow endRow 475s 1 10 7594 475s int [1:7599] 1 2 3 4 5 6 7 8 9 10 ... 475s DH segmentation rows: 475s startRow endRow 475s 1 10 7594 475s Segmenting DH signals...done 475s DH segmentation table: 475s dhStart dhEnd dhNbrOfLoci dhMean 475s 1 554484 143926517 2120 0.5101 475s startRow endRow 475s 1 10 7594 475s Rows: 475s [1] 1 475s TCN segmentation rows: 475s startRow endRow 475s 1 1 7599 475s TCN and DH segmentation rows: 475s startRow endRow 475s 1 1 7599 475s startRow endRow 475s 1 10 7594 475s NULL 475s TCN segmentation (expanded) rows: 475s startRow endRow 475s 1 1 7599 475s TCN and DH segmentation rows: 475s startRow endRow 475s 1 1 7599 475s 2 7600 10267 475s 3 10268 14658 475s startRow endRow 475s 1 10 7594 475s startRow endRow 475s 1 1 7599 475s Total CN segmentation table (expanded): 475s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 475s 1 3 554484 143926517 7599 1.3859 2120 2120 475s (TCN,DH) segmentation for one total CN segment: 475s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 475s 1 1 1 3 554484 143926517 7599 1.3859 2120 475s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 475s 1 2120 554484 143926517 2120 0.5101 475s Total CN segment #1 ([ 554484,1.43927e+08]) of 3...done 475s Total CN segment #2 ([1.43927e+08,1.8545e+08]) of 3... 475s Number of TCN loci in segment: 2668 475s Locus data for TCN segment: 475s 'data.frame': 2668 obs. of 9 variables: 475s $ chromosome: int 3 3 3 3 3 3 3 3 3 3 ... 475s $ x : num 1.44e+08 1.44e+08 1.44e+08 1.44e+08 1.44e+08 ... 475s $ CT : num 2.1 2.1 2.09 1.8 2.34 ... 475s $ betaT : num 0.027542 1.030222 1.094093 0.046763 -0.000948 ... 475s $ betaTN : num 0.027542 1.030222 1.094093 0.046763 -0.000948 ... 475s $ betaN : num 0.1624 0.8788 0.8225 0.1201 0.0317 ... 475s $ muN : num 0 1 1 0 0 1 0 0 0 0 ... 475s $ index : int 7600 7601 7602 7603 7604 7605 7606 7607 7608 7609 ... 475s $ rho : num NA NA NA NA NA NA NA NA NA NA ... 475s Number of loci: 2668 475s Number of SNPs: 775 (29.05%) 475s Number of heterozygous SNPs: 775 (100.00%) 475s Chromosome: 3 475s Segmenting DH signals... 475s Segmenting by CBS... 475s Chromosome: 3 475s Random seed temporarily set (seed=c(10407, -1371615447, -889757879, 1692656974, -1723952224, 1378814990, 1816467252), kind="L'Ecuyer-CMRG") 475s Segmenting by CBS...done 475s List of 4 475s $ data :'data.frame': 2668 obs. of 4 variables: 475s ..$ chromosome: int [1:2668] 3 3 3 3 3 3 3 3 3 3 ... 475s ..$ x : num [1:2668] 1.44e+08 1.44e+08 1.44e+08 1.44e+08 1.44e+08 ... 475s ..$ y : num [1:2668] NA NA NA NA NA NA NA NA NA NA ... 475s ..$ index : int [1:2668] 1 2 3 4 5 6 7 8 9 10 ... 475s $ output :'data.frame': 1 obs. of 6 variables: 475s ..$ sampleName: chr NA 475s ..$ chromosome: int 3 475s ..$ start : num 1.44e+08 475s ..$ end : num 1.85e+08 475s ..$ nbrOfLoci : int 775 475s ..$ mean : num 0.097 475s $ segRows:'data.frame': 1 obs. of 2 variables: 475s ..$ startRow: int 15 475s ..$ endRow : int 2664 475s $ params :List of 5 475s ..$ alpha : num 0.001 475s ..$ undo : num 0 475s ..$ joinSegments : logi TRUE 475s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 475s .. ..$ chromosome: int 3 475s .. ..$ start : num 1.44e+08 475s .. ..$ end : num 1.85e+08 475s ..$ seed : int [1:7] 10407 -1371615447 -889757879 1692656974 -1723952224 1378814990 1816467252 475s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 475s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.007 0 0.007 0 0 475s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 475s - attr(*, "pkgDetails")= chr "DNAcopy v1.76.0" 475s - attr(*, "randomSeed")= int [1:7] 10407 -1371615447 -889757879 1692656974 -1723952224 1378814990 1816467252 475s DH segmentation (locally-indexed) rows: 475s startRow endRow 475s 1 15 2664 475s int [1:2668] 7600 7601 7602 7603 7604 7605 7606 7607 7608 7609 ... 475s DH segmentation rows: 475s startRow endRow 475s 1 7614 10263 475s Segmenting DH signals...done 475s DH segmentation table: 475s dhStart dhEnd dhNbrOfLoci dhMean 475s 1 143926517 185449813 775 0.097 475s startRow endRow 475s 1 7614 10263 475s Rows: 475s [1] 2 475s TCN segmentation rows: 475s startRow endRow 475s 2 7600 10267 475s TCN and DH segmentation rows: 475s startRow endRow 475s 2 7600 10267 475s startRow endRow 475s 1 7614 10263 475s startRow endRow 475s 1 1 7599 475s TCN segmentation (expanded) rows: 475s startRow endRow 475s 1 1 7599 475s 2 7600 10267 475s TCN and DH segmentation rows: 475s startRow endRow 475s 1 1 7599 475s 2 7600 10267 475s 3 10268 14658 475s startRow endRow 475s 1 10 7594 475s 2 7614 10263 475s startRow endRow 475s 1 1 7599 475s 2 7600 10267 475s Total CN segmentation table (expanded): 475s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 475s 2 3 143926517 185449813 2668 2.0704 775 775 475s (TCN,DH) segmentation for one total CN segment: 475s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 475s 2 2 1 3 143926517 185449813 2668 2.0704 775 475s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 475s 2 775 143926517 185449813 775 0.097 475s Total CN segment #2 ([1.43927e+08,1.8545e+08]) of 3...done 475s Total CN segment #3 ([1.8545e+08,2.47137e+08]) of 3... 475s Number of TCN loci in segment: 4391 475s Locus data for TCN segment: 475s 'data.frame': 4391 obs. of 9 variables: 475s $ chromosome: int 3 3 3 3 3 3 3 3 3 3 ... 475s $ x : num 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 475s $ CT : num 2.93 2.15 2.82 2.93 2.46 ... 475s $ betaT : num -0.169 0.609 1.028 0.525 0.968 ... 475s $ betaTN : num -0.169 0.609 1.028 0.525 0.968 ... 475s $ betaN : num 0.25 0.38 0.919 0.34 0.783 ... 475s $ muN : num 0 0.5 1 0.5 1 1 0 1 0 1 ... 475s $ index : int 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 475s $ rho : num NA 0.2186 NA 0.0503 NA ... 475s Number of loci: 4391 475s Number of SNPs: 1314 (29.92%) 475s Number of heterozygous SNPs: 1314 (100.00%) 475s Chromosome: 3 475s Segmenting DH signals... 475s Segmenting by CBS... 475s Chromosome: 3 475s Random seed temporarily set (seed=c(10407, -1371615447, -889757879, 1692656974, -1723952224, 1378814990, 1816467252), kind="L'Ecuyer-CMRG") 475s Segmenting by CBS...done 475s List of 4 475s $ data :'data.frame': 4391 obs. of 4 variables: 475s ..$ chromosome: int [1:4391] 3 3 3 3 3 3 3 3 3 3 ... 475s ..$ x : num [1:4391] 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 475s ..$ y : num [1:4391] NA 0.2186 NA 0.0503 NA ... 475s ..$ index : int [1:4391] 1 2 3 4 5 6 7 8 9 10 ... 475s $ output :'data.frame': 1 obs. of 6 variables: 475s ..$ sampleName: chr NA 475s ..$ chromosome: int 3 475s ..$ start : num 1.85e+08 475s ..$ end : num 2.47e+08 475s ..$ nbrOfLoci : int 1314 475s ..$ mean : num 0.23 475s $ segRows:'data.frame': 1 obs. of 2 variables: 475s ..$ startRow: int 2 475s ..$ endRow : int 4388 475s $ params :List of 5 475s ..$ alpha : num 0.001 475s ..$ undo : num 0 475s ..$ joinSegments : logi TRUE 475s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 475s .. ..$ chromosome: int 3 475s .. ..$ start : num 1.85e+08 475s .. ..$ end : num 2.47e+08 475s ..$ seed : int [1:7] 10407 -1371615447 -889757879 1692656974 -1723952224 1378814990 1816467252 475s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 475s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.014 0 0.014 0 0 475s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 475s - attr(*, "pkgDetails")= chr "DNAcopy v1.76.0" 475s - attr(*, "randomSeed")= int [1:7] 10407 -1371615447 -889757879 1692656974 -1723952224 1378814990 1816467252 475s DH segmentation (locally-indexed) rows: 475s startRow endRow 475s 1 2 4388 475s int [1:4391] 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 475s DH segmentation rows: 475s startRow endRow 475s 1 10269 14655 475s Segmenting DH signals...done 475s DH segmentation table: 475s dhStart dhEnd dhNbrOfLoci dhMean 475s 1 185449813 247137334 1314 0.2295 475s startRow endRow 475s 1 10269 14655 475s Rows: 475s [1] 3 475s TCN segmentation rows: 475s startRow endRow 475s 3 10268 14658 475s TCN and DH segmentation rows: 475s startRow endRow 475s 3 10268 14658 475s startRow endRow 475s 1 10269 14655 475s startRow endRow 475s 1 1 7599 475s 2 7600 10267 475s TCN segmentation (expanded) rows: 475s startRow endRow 475s 1 1 7599 475s 2 7600 10267 475s 3 10268 14658 475s TCN and DH segmentation rows: 475s startRow endRow 475s 1 1 7599 475s 2 7600 10267 475s 3 10268 14658 475s startRow endRow 475s 1 10 7594 475s 2 7614 10263 475s 3 10269 14655 475s startRow endRow 475s 1 1 7599 475s 2 7600 10267 475s 3 10268 14658 475s Total CN segmentation table (expanded): 475s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 475s 3 3 185449813 247137334 4391 2.6341 1314 1314 475s (TCN,DH) segmentation for one total CN segment: 475s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 475s 3 3 1 3 185449813 247137334 4391 2.6341 1314 475s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 475s 3 1314 185449813 247137334 1314 0.2295 475s Total CN segment #3 ([1.8545e+08,2.47137e+08]) of 3...done 475s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 475s 1 3 1 1 554484 143926517 7599 1.3859 2120 475s 2 3 2 1 143926517 185449813 2668 2.0704 775 475s 3 3 3 1 185449813 247137334 4391 2.6341 1314 475s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 475s 1 2120 554484 143926517 2120 0.5101 475s 2 775 143926517 185449813 775 0.0970 475s 3 1314 185449813 247137334 1314 0.2295 475s Calculating (C1,C2) per segment... 475s Calculating (C1,C2) per segment...done 475s Number of segments: 3 475s Segmenting paired tumor-normal signals using Paired PSCBS...done 475s Post-segmenting TCNs... 475s Number of segments: 3 475s Number of chromosomes: 1 475s [1] 3 475s Chromosome 1 ('chr03') of 1... 475s Rows: 475s [1] 1 2 3 475s Number of segments: 3 475s TCN segment #1 ('1') of 3... 475s Nothing todo. Only one DH segmentation. Skipping. 475s TCN segment #1 ('1') of 3...done 475s TCN segment #2 ('2') of 3... 475s Nothing todo. Only one DH segmentation. Skipping. 475s TCN segment #2 ('2') of 3...done 475s TCN segment #3 ('3') of 3... 475s Nothing todo. Only one DH segmentation. Skipping. 475s TCN segment #3 ('3') of 3...done 475s Chromosome 1 ('chr03') of 1...done 475s Update (C1,C2) per segment... 475s Update (C1,C2) per segment...done 475s Post-segmenting TCNs...done 475s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 475s 1 3 1 1 554484 143926517 7599 1.3859 2120 475s 2 3 2 1 143926517 185449813 2668 2.0704 775 475s 3 3 3 1 185449813 247137334 4391 2.6341 1314 475s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 475s 1 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 475s 2 775 143926517 185449813 775 0.0970 0.9347856 1.135614 475s 3 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 475s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 475s 1 3 1 1 554484 143926517 7599 1.3859 2120 475s 2 3 2 1 143926517 185449813 2668 2.0704 775 475s 3 3 3 1 185449813 247137334 4391 2.6341 1314 475s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 475s 1 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 475s 2 775 143926517 185449813 775 0.0970 0.9347856 1.135614 475s 3 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 475s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 475s 1 3 1 1 554484 143926517 7599 1.3859 2120 475s 2 3 2 1 143926517 185449813 2668 2.0704 775 475s 3 3 3 1 185449813 247137334 4391 2.6341 1314 475s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 475s 1 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 475s 2 775 143926517 185449813 775 0.0970 0.9347856 1.135614 475s 3 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 475s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 475s 1 3 1 1 554484 143926517 7599 1.3859 2120 475s 2 3 2 1 143926517 185449813 2668 2.0704 775 475s 3 3 3 1 185449813 247137334 4391 2.6341 1314 475s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 475s 1 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 475s 2 775 143926517 185449813 775 0.0970 0.9347856 1.135614 475s 3 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 475s List of 5 475s $ data :Classes 'PairedPSCNData' and 'data.frame': 43974 obs. of 8 variables: 475s ..$ chromosome: int [1:43974] 1 1 1 1 1 1 1 1 1 1 ... 475s ..$ x : num [1:43974] 554484 730720 782343 878522 916294 ... 475s ..$ CT : num [1:43974] 1.88 1.8 1.59 1.64 1.53 ... 475s ..$ betaT : num [1:43974] 0.0646 0.1672 0.9284 0.113 0.7209 ... 475s ..$ betaTN : num [1:43974] -0.0515 -0.1172 1.0194 0.031 0.8604 ... 475s ..$ betaN : num [1:43974] 0.116 0.284 0.909 0.082 0.86 ... 475s ..$ muN : num [1:43974] 0 0 1 0 1 1 1 0 1 0.5 ... 475s ..$ rho : num [1:43974] NA NA NA NA NA ... 475s $ output :Classes 'PairedPSCNSegments' and 'data.frame': 11 obs. of 15 variables: 475s ..$ chromosome : int [1:11] 1 1 1 NA 2 2 2 NA 3 3 ... 475s ..$ tcnId : int [1:11] 1 2 3 NA 1 2 3 NA 1 2 ... 475s ..$ dhId : int [1:11] 1 1 1 NA 1 1 1 NA 1 1 ... 475s ..$ tcnStart : num [1:11] 5.54e+05 1.44e+08 1.85e+08 NA 5.54e+05 ... 475s ..$ tcnEnd : num [1:11] 1.44e+08 1.85e+08 2.47e+08 NA 1.44e+08 ... 475s ..$ tcnNbrOfLoci: int [1:11] 7599 2668 4391 NA 7599 2668 4391 NA 7599 2668 ... 475s ..$ tcnMean : num [1:11] 1.39 2.07 2.63 NA 1.39 ... 475s ..$ tcnNbrOfSNPs: int [1:11] 2120 775 1314 NA 2120 775 1314 NA 2120 775 ... 475s ..$ tcnNbrOfHets: int [1:11] 2120 775 1314 NA 2120 775 1314 NA 2120 775 ... 475s ..$ dhStart : num [1:11] 5.54e+05 1.44e+08 1.85e+08 NA 5.54e+05 ... 475s ..$ dhEnd : num [1:11] 1.44e+08 1.85e+08 2.47e+08 NA 1.44e+08 ... 475s ..$ dhNbrOfLoci : int [1:11] 2120 775 1314 NA 2120 775 1314 NA 2120 775 ... 475s ..$ dhMean : num [1:11] 0.51 0.097 0.23 NA 0.51 ... 475s ..$ c1Mean : num [1:11] 0.339 0.935 1.015 NA 0.339 ... 475s ..$ c2Mean : num [1:11] 1.05 1.14 1.62 NA 1.05 ... 475s $ tcnSegRows:'data.frame': 11 obs. of 2 variables: 475s ..$ startRow: int [1:11] 1 7600 10268 NA 14659 22258 24926 NA 29317 36916 ... 475s ..$ endRow : int [1:11] 7599 10267 14658 NA 22257 24925 29316 NA 36915 39583 ... 475s $ dhSegRows :'data.frame': 11 obs. of 2 variables: 475s ..$ startRow: int [1:11] 10 7614 10269 NA 14668 22272 24927 NA 29326 36930 ... 475s ..$ endRow : int [1:11] 7594 10263 14655 NA 22252 24921 29313 NA 36910 39579 ... 475s $ params :List of 7 475s ..$ alphaTCN : num 0.009 475s ..$ alphaDH : num 0.001 475s ..$ flavor : chr "tcn&dh" 475s ..$ tbn : logi FALSE 475s ..$ joinSegments : logi TRUE 475s ..$ knownSegments:'data.frame': 0 obs. of 3 variables: 475s .. ..$ chromosome: int(0) 475s .. ..$ start : int(0) 475s .. ..$ end : int(0) 475s ..$ seed : int [1:7] 10407 1066287653 -51199871 161854402 -1995183193 1503453565 -747102133 475s - attr(*, "class")= chr [1:3] "PairedPSCBS" "PSCBS" "AbstractCBS" 475s Merging (independently) segmented chromosome...done 475s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 475s 1 1 1 1 554484 143926517 7599 1.3859 2120 475s 2 1 2 1 143926517 185449813 2668 2.0704 775 475s 3 1 3 1 185449813 247137334 4391 2.6341 1314 475s 4 NA NA NA NA NA NA NA NA 475s 5 2 1 1 554484 143926517 7599 1.3859 2120 475s 6 2 2 1 143926517 185449813 2668 2.0704 775 475s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 475s 1 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 475s 2 775 143926517 185449813 775 0.0970 0.9347856 1.135614 475s 3 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 475s 4 NA NA NA NA NA NA NA 475s 5 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 475s 6 775 143926517 185449813 775 0.0970 0.9347856 1.135614 475s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 475s 6 2 2 1 143926517 185449813 2668 2.0704 775 475s 7 2 3 1 185449813 247137334 4391 2.6341 1314 475s 8 NA NA NA NA NA NA NA NA 475s 9 3 1 1 554484 143926517 7599 1.3859 2120 475s 10 3 2 1 143926517 185449813 2668 2.0704 775 475s 11 3 3 1 185449813 247137334 4391 2.6341 1314 475s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 475s 6 775 143926517 185449813 775 0.0970 0.9347856 1.135614 475s 7 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 475s 8 NA NA NA NA NA NA NA 475s 9 2120 554484 143926517 2120 0.5101 0.3394762 1.046424 475s 10 775 143926517 185449813 775 0.0970 0.9347856 1.135614 475s 11 1314 185449813 247137334 1314 0.2295 1.0147870 1.619313 475s Segmenting multiple chromosomes...done 475s Segmenting paired tumor-normal signals using Paired PSCBS...done 475s > 475s > message("*** segmentByPairedPSCBS() via futures ... DONE") 475s *** segmentByPairedPSCBS() via futures ... DONE 475s > 475s > 475s > message("*** segmentByPairedPSCBS() via futures with known segments ...") 475s *** segmentByPairedPSCBS() via futures with known segments ... 475s > fits <- list() 475s > dataT <- subset(data, chromosome == 1) 475s > gaps <- findLargeGaps(dataT, minLength=2e6) 475s > knownSegments <- gapsToSegments(gaps) 475s > 475s > for (strategy in strategies) { 475s + message(sprintf("- segmentByPairedPSCBS() w/ known segments using '%s' futures ...", strategy)) 475s + plan(strategy) 475s + fit <- segmentByPairedPSCBS(dataT, knownSegments=knownSegments, seed=0xBEEF, verbose=TRUE) 475s + fits[[strategy]] <- fit 475s + equal <- all.equal(fit, fits[[1]]) 475s + if (!equal) { 475s + str(fit) 475s + str(fits[[1]]) 475s + print(equal) 475s + stop(sprintf("segmentByPairedPSCBS() w/ known segments using '%s' futures does not produce the same results as when using '%s' futures", strategy, names(fits)[1])) 475s + } 475s + } 475s - segmentByPairedPSCBS() w/ known segments using 'sequential' futures ... 475s Segmenting paired tumor-normal signals using Paired PSCBS... 475s Calling genotypes from normal allele B fractions... 475s num [1:14670] 0.8274 0.5072 0.1671 0.1609 0.0421 ... 475s Called genotypes: 475s num [1:14670] 1 0.5 0 0 0 0 1 0 1 0.5 ... 475s - attr(*, "modelFit")=List of 1 475s ..$ :List of 7 475s .. ..$ flavor : chr "density" 475s .. ..$ cn : int 2 475s .. ..$ nbrOfGenotypeGroups: int 3 475s .. ..$ tau : num [1:2] 0.315 0.677 475s .. ..$ n : int 14640 475s .. ..$ fit :Classes 'PeaksAndValleys' and 'data.frame': 5 obs. of 3 variables: 475s .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 475s .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 475s .. .. ..$ density: num [1:5] 1.48 0.522 1.056 0.552 1.454 475s .. ..$ fitValleys :Classes 'PeaksAndValleys' and 'data.frame': 2 obs. of 3 variables: 475s .. .. ..$ type : chr [1:2] "valley" "valley" 475s .. .. ..$ x : num [1:2] 0.315 0.677 475s .. .. ..$ density: num [1:2] 0.522 0.552 475s ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 475s muN 475s 0 0.5 1 475s 5221 4198 5251 475s Calling genotypes from normal allele B fractions...done 475s Normalizing betaT using betaN (TumorBoost)... 475s Normalized BAFs: 475s num [1:14670] 0.9301 0.1667 0.0685 0.0995 0.0155 ... 475s - attr(*, "modelFit")=List of 5 475s ..$ method : chr "normalizeTumorBoost" 475s ..$ flavor : chr "v4" 475s ..$ delta : num [1:14670] -0.17264 0.00239 0.1671 0.16085 0.04213 ... 475s .. ..- attr(*, "modelFit")=List of 1 475s .. .. ..$ :List of 7 475s .. .. .. ..$ flavor : chr "density" 475s .. .. .. ..$ cn : int 2 475s .. .. .. ..$ nbrOfGenotypeGroups: int 3 475s .. .. .. ..$ tau : num [1:2] 0.315 0.677 475s .. .. .. ..$ n : int 14640 475s .. .. .. ..$ fit :Classes 'PeaksAndValleys' and 'data.frame': 5 obs. of 3 variables: 475s .. .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 475s .. .. .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 475s .. .. .. .. ..$ density: num [1:5] 1.48 0.522 1.056 0.552 1.454 475s .. .. .. ..$ fitValleys :Classes 'PeaksAndValleys' and 'data.frame': 2 obs. of 3 variables: 475s .. .. .. .. ..$ type : chr [1:2] "valley" "valley" 475s .. .. .. .. ..$ x : num [1:2] 0.315 0.677 475s .. .. .. .. ..$ density: num [1:2] 0.522 0.552 475s .. .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 475s ..$ preserveScale: logi FALSE 475s ..$ scaleFactor : num NA 475s Normalizing betaT using betaN (TumorBoost)...done 475s Setup up data... 475s 'data.frame': 14670 obs. of 7 variables: 475s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 475s $ x : num 1145994 2941694 3710825 4240737 4276892 ... 475s $ CT : num 1.63 1.4 1.41 1.17 1.16 ... 475s $ betaT : num 0.7574 0.169 0.2357 0.2604 0.0576 ... 475s $ betaTN : num 0.9301 0.1667 0.0685 0.0995 0.0155 ... 475s ..- attr(*, "modelFit")=List of 5 475s .. ..$ method : chr "normalizeTumorBoost" 475s .. ..$ flavor : chr "v4" 475s .. ..$ delta : num [1:14670] -0.17264 0.00239 0.1671 0.16085 0.04213 ... 475s .. .. ..- attr(*, "modelFit")=List of 1 475s .. .. .. ..$ :List of 7 475s .. .. .. .. ..$ flavor : chr "density" 475s .. .. .. .. ..$ cn : int 2 475s .. .. .. .. ..$ nbrOfGenotypeGroups: int 3 475s .. .. .. .. ..$ tau : num [1:2] 0.315 0.677 475s .. .. .. .. ..$ n : int 14640 475s .. .. .. .. ..$ fit :Classes 'PeaksAndValleys' and 'data.frame': 5 obs. of 3 variables: 475s .. .. .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 475s .. .. .. .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 475s .. .. .. .. .. ..$ density: num [1:5] 1.48 0.522 1.056 0.552 1.454 475s .. .. .. .. ..$ fitValleys :Classes 'PeaksAndValleys' and 'data.frame': 2 obs. of 3 variables: 475s .. .. .. .. .. ..$ type : chr [1:2] "valley" "valley" 475s .. .. .. .. .. ..$ x : num [1:2] 0.315 0.677 475s .. .. .. .. .. ..$ density: num [1:2] 0.522 0.552 475s .. .. .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 475s .. ..$ preserveScale: logi FALSE 475s .. ..$ scaleFactor : num NA 475s $ betaN : num 0.8274 0.5072 0.1671 0.1609 0.0421 ... 475s $ muN : num 1 0.5 0 0 0 0 1 0 1 0.5 ... 475s ..- attr(*, "modelFit")=List of 1 475s .. ..$ :List of 7 475s .. .. ..$ flavor : chr "density" 475s .. .. ..$ cn : int 2 475s .. .. ..$ nbrOfGenotypeGroups: int 3 475s .. .. ..$ tau : num [1:2] 0.315 0.677 475s .. .. ..$ n : int 14640 475s .. .. ..$ fit :Classes 'PeaksAndValleys' and 'data.frame': 5 obs. of 3 variables: 475s .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 475s .. .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 475s .. .. .. ..$ density: num [1:5] 1.48 0.522 1.056 0.552 1.454 475s .. .. ..$ fitValleys :Classes 'PeaksAndValleys' and 'data.frame': 2 obs. of 3 variables: 475s .. .. .. ..$ type : chr [1:2] "valley" "valley" 475s .. .. .. ..$ x : num [1:2] 0.315 0.677 475s .. .. .. ..$ density: num [1:2] 0.522 0.552 475s .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 475s Setup up data...done 475s Dropping loci for which TCNs are missing... 475s Number of loci dropped: 12 475s Dropping loci for which TCNs are missing...done 475s Ordering data along genome... 475s 'data.frame': 14658 obs. of 7 variables: 475s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 475s $ x : num 554484 730720 782343 878522 916294 ... 475s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 475s $ betaT : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 475s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 475s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 475s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 475s Ordering data along genome...done 475s Keeping only current chromosome for 'knownSegments'... 475s Chromosome: 1 475s Known segments for this chromosome: 475s chromosome start end length 475s 1 1 -Inf 120908858 Inf 475s 2 1 120908859 142693887 21785028 475s 3 1 142693888 Inf Inf 475s Keeping only current chromosome for 'knownSegments'...done 475s alphaTCN: 0.009 475s alphaDH: 0.001 475s Number of loci: 14658 475s Calculating DHs... 475s Number of SNPs: 14658 475s Number of heterozygous SNPs: 4196 (28.63%) 475s Normalized DHs: 475s num [1:14658] NA NA NA NA NA ... 475s Calculating DHs...done 475s Random seed temporarily set (seed=c(48879), kind="L'Ecuyer-CMRG") 475s Produced 2 seeds from this stream for future usage 475s Identification of change points by total copy numbers... 475s Segmenting by CBS... 475s Chromosome: 1 475s Random seed temporarily set (seed=c(10407, 1066287653, -51199871, 161854402, -1995183193, 1503453565, -747102133), kind="L'Ecuyer-CMRG") 475s Produced 3 seeds from this stream for future usage 475s Segmenting by CBS...done 475s List of 4 475s $ data :'data.frame': 14658 obs. of 4 variables: 475s ..$ chromosome: int [1:14658] 1 1 1 1 1 1 1 1 1 1 ... 475s ..$ x : num [1:14658] 554484 730720 782343 878522 916294 ... 475s ..$ y : num [1:14658] 1.88 1.8 1.59 1.64 1.53 ... 475s ..$ index : int [1:14658] 1 2 3 4 5 6 7 8 9 10 ... 475s $ output :'data.frame': 4 obs. of 6 variables: 475s ..$ sampleName: chr [1:4] NA NA NA NA 475s ..$ chromosome: int [1:4] 1 1 1 1 475s ..$ start : num [1:4] 5.54e+05 1.21e+08 1.43e+08 1.85e+08 475s ..$ end : num [1:4] 1.21e+08 1.43e+08 1.85e+08 2.47e+08 475s ..$ nbrOfLoci : int [1:4] 7586 0 2681 4391 475s ..$ mean : num [1:4] 1.39 NA 2.07 2.63 475s $ segRows:'data.frame': 4 obs. of 2 variables: 475s ..$ startRow: int [1:4] 1 NA 7587 10268 475s ..$ endRow : int [1:4] 7586 NA 10267 14658 475s $ params :List of 5 475s ..$ alpha : num 0.009 475s ..$ undo : num 0 475s ..$ joinSegments : logi TRUE 475s ..$ knownSegments:'data.frame': 4 obs. of 3 variables: 475s .. ..$ chromosome: int [1:4] 1 1 2 1 475s .. ..$ start : num [1:4] -Inf -Inf -Inf 1.43e+08 475s .. ..$ end : num [1:4] 1.21e+08 Inf Inf Inf 475s ..$ seed : int [1:7] 10407 1066287653 -51199871 161854402 -1995183193 1503453565 -747102133 475s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 475s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.132 0 0.132 0 0 475s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 475s - attr(*, "pkgDetails")= chr "DNAcopy v1.76.0" 475s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 475s Identification of change points by total copy numbers...done 475s Restructure TCN segmentation results... 475s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean 475s 1 1 554484 120908858 7586 1.3853 475s 2 1 120908859 142693887 0 NA 475s 3 1 142693888 185449813 2681 2.0689 475s 4 1 185449813 247137334 4391 2.6341 475s Number of TCN segments: 4 475s Restructure TCN segmentation results...done 475s Total CN segment #1 ([ 554484,1.20909e+08]) of 4... 475s Number of TCN loci in segment: 7586 475s Locus data for TCN segment: 475s 'data.frame': 7586 obs. of 9 variables: 475s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 475s $ x : num 554484 730720 782343 878522 916294 ... 475s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 475s $ betaT : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 475s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 475s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 475s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 475s $ index : int 1 2 3 4 5 6 7 8 9 10 ... 475s $ rho : num NA NA NA NA NA ... 475s Number of loci: 7586 475s Number of SNPs: 2108 (27.79%) 475s Number of heterozygous SNPs: 2108 (100.00%) 475s Chromosome: 1 475s Segmenting DH signals... 475s Segmenting by CBS... 475s Chromosome: 1 475s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 475s Segmenting by CBS...done 475s List of 4 475s $ data :'data.frame': 7586 obs. of 4 variables: 475s ..$ chromosome: int [1:7586] 1 1 1 1 1 1 1 1 1 1 ... 475s ..$ x : num [1:7586] 554484 730720 782343 878522 916294 ... 475s ..$ y : num [1:7586] NA NA NA NA NA ... 475s ..$ index : int [1:7586] 1 2 3 4 5 6 7 8 9 10 ... 475s $ output :'data.frame': 1 obs. of 6 variables: 475s ..$ sampleName: chr NA 475s ..$ chromosome: int 1 475s ..$ start : num 554484 475s ..$ end : num 1.21e+08 475s ..$ nbrOfLoci : int 2108 475s ..$ mean : num 0.512 475s $ segRows:'data.frame': 1 obs. of 2 variables: 475s ..$ startRow: int 10 475s ..$ endRow : int 7574 475s $ params :List of 5 475s ..$ alpha : num 0.001 475s ..$ undo : num 0 475s ..$ joinSegments : logi TRUE 475s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 475s .. ..$ chromosome: int 1 475s .. ..$ start : num 554484 475s .. ..$ end : num 1.21e+08 475s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 475s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 475s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.035 0 0.034 0 0 475s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 475s - attr(*, "pkgDetails")= chr "DNAcopy v1.76.0" 475s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 475s DH segmentation (locally-indexed) rows: 475s startRow endRow 475s 1 10 7574 475s int [1:7586] 1 2 3 4 5 6 7 8 9 10 ... 475s DH segmentation rows: 475s startRow endRow 475s 1 10 7574 475s Segmenting DH signals...done 475s DH segmentation table: 475s dhStart dhEnd dhNbrOfLoci dhMean 475s 1 554484 120908858 2108 0.5116 475s startRow endRow 475s 1 10 7574 475s Rows: 475s [1] 1 475s TCN segmentation rows: 475s startRow endRow 475s 1 1 7586 475s TCN and DH segmentation rows: 475s startRow endRow 475s 1 1 7586 475s startRow endRow 475s 1 10 7574 475s NULL 475s TCN segmentation (expanded) rows: 475s startRow endRow 475s 1 1 7586 475s TCN and DH segmentation rows: 475s startRow endRow 475s 1 1 7586 475s 2 NA NA 475s 3 7587 10267 475s 4 10268 14658 475s startRow endRow 475s 1 10 7574 475s startRow endRow 475s 1 1 7586 475s Total CN segmentation table (expanded): 475s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 475s 1 1 554484 120908858 7586 1.3853 2108 2108 475s (TCN,DH) segmentation for one total CN segment: 475s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 475s 1 1 1 1 554484 120908858 7586 1.3853 2108 475s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 475s 1 2108 554484 120908858 2108 0.5116 475s Total CN segment #1 ([ 554484,1.20909e+08]) of 4...done 475s Total CN segment #2 ([1.20909e+08,1.42694e+08]) of 4... 475s Number of TCN loci in segment: 0 475s Locus data for TCN segment: 475s 'data.frame': 0 obs. of 9 variables: 475s $ chromosome: int 475s $ x : num 475s $ CT : num 475s $ betaT : num 475s $ betaTN : num 475s $ betaN : num 475s $ muN : num 475s $ index : int 475s $ rho : num 475s Number of loci: 0 475s Number of SNPs: 0 (NaN%) 475s Number of heterozygous SNPs: 0 (NaN%) 475s Chromosome: 1 475s Segmenting DH signals... 475s Segmenting by CBS... 475s Chromosome: NA 475s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 475s Segmenting by CBS...done 475s List of 4 475s $ data :'data.frame': 0 obs. of 4 variables: 475s ..$ chromosome: int(0) 475s ..$ x : num(0) 475s ..$ y : num(0) 475s ..$ index : int(0) 475s $ output :'data.frame': 0 obs. of 6 variables: 475s ..$ sampleName: chr(0) 475s ..$ chromosome: num(0) 475s ..$ start : num(0) 475s ..$ end : num(0) 475s ..$ nbrOfLoci : int(0) 475s ..$ mean : num(0) 475s $ segRows:'data.frame': 0 obs. of 2 variables: 475s ..$ startRow: int(0) 475s ..$ endRow : int(0) 475s $ params :List of 5 475s ..$ alpha : num 0.001 475s ..$ undo : num 0 475s ..$ joinSegments : logi TRUE 475s ..$ knownSegments:'data.frame': 0 obs. of 3 variables: 475s .. ..$ chromosome: int(0) 475s .. ..$ start : num(0) 475s .. ..$ end : num(0) 475s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 475s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 475s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.002 0 0.001 0 0 475s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 475s - attr(*, "pkgDetails")= chr "DNAcopy v1.76.0" 475s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 475s DH segmentation (locally-indexed) rows: 475s [1] startRow endRow 475s <0 rows> (or 0-length row.names) 475s int(0) 475s DH segmentation rows: 475s [1] startRow endRow 475s <0 rows> (or 0-length row.names) 475s Segmenting DH signals...done 475s DH segmentation table: 475s dhStart dhEnd dhNbrOfLoci dhMean 475s NA NA NA NA NA 475s startRow endRow 475s NA NA NA 475s Rows: 475s [1] 2 475s TCN segmentation rows: 475s startRow endRow 475s 2 NA NA 475s TCN and DH segmentation rows: 475s startRow endRow 475s 2 NA NA 475s startRow endRow 475s NA NA NA 475s startRow endRow 475s 1 1 7586 475s TCN segmentation (expanded) rows: 475s startRow endRow 475s 1 1 7586 475s 2 NA NA 475s TCN and DH segmentation rows: 475s startRow endRow 475s 1 1 7586 475s 2 NA NA 475s 3 7587 10267 475s 4 10268 14658 475s startRow endRow 475s 1 10 7574 475s 2 NA NA 475s startRow endRow 475s 1 1 7586 475s 2 NA NA 475s Total CN segmentation table (expanded): 475s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 475s 2 1 120908859 142693887 0 NA 0 0 475s (TCN,DH) segmentation for one total CN segment: 475s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 475s 2 2 1 1 120908859 142693887 0 NA 0 475s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 475s 2 0 NA NA NA NA 475s Total CN segment #2 ([1.20909e+08,1.42694e+08]) of 4...done 475s Total CN segment #3 ([1.42694e+08,1.8545e+08]) of 4... 475s Number of TCN loci in segment: 2681 475s Locus data for TCN segment: 475s 'data.frame': 2681 obs. of 9 variables: 475s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 475s $ x : num 1.43e+08 1.43e+08 1.43e+08 1.43e+08 1.44e+08 ... 475s $ CT : num 2.27 1.55 1.47 1.5 1.81 ... 475s $ betaT : num 0.34 0.55 0.048 0.813 0.575 ... 475s $ betaTN : num 0.441 0.629 -0.05 0.958 0.872 ... 475s $ betaN : num 0.3851 0.3933 0.0981 0.8552 0.7028 ... 475s $ muN : num 0.5 0.5 0 1 1 1 1 0.5 1 1 ... 475s $ index : int 7587 7588 7589 7590 7591 7592 7593 7594 7595 7596 ... 475s $ rho : num 0.117 0.258 NA NA NA ... 475s Number of loci: 2681 475s Number of SNPs: 777 (28.98%) 475s Number of heterozygous SNPs: 777 (100.00%) 475s Chromosome: 1 475s Segmenting DH signals... 475s Segmenting by CBS... 475s Chromosome: 1 475s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 475s Segmenting by CBS...done 475s List of 4 475s $ data :'data.frame': 2681 obs. of 4 variables: 475s ..$ chromosome: int [1:2681] 1 1 1 1 1 1 1 1 1 1 ... 475s ..$ x : num [1:2681] 1.43e+08 1.43e+08 1.43e+08 1.43e+08 1.44e+08 ... 475s ..$ y : num [1:2681] 0.117 0.258 NA NA NA ... 475s ..$ index : int [1:2681] 1 2 3 4 5 6 7 8 9 10 ... 475s $ output :'data.frame': 1 obs. of 6 variables: 475s ..$ sampleName: chr NA 475s ..$ chromosome: int 1 475s ..$ start : num 1.43e+08 475s ..$ end : num 1.85e+08 475s ..$ nbrOfLoci : int 777 475s ..$ mean : num 0.0973 475s $ segRows:'data.frame': 1 obs. of 2 variables: 475s ..$ startRow: int 1 475s ..$ endRow : int 2677 475s $ params :List of 5 475s ..$ alpha : num 0.001 475s ..$ undo : num 0 475s ..$ joinSegments : logi TRUE 475s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 475s .. ..$ chromosome: int 1 475s .. ..$ start : num 1.43e+08 475s .. ..$ end : num 1.85e+08 475s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 475s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 475s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.011 0 0.01 0 0 475s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 475s - attr(*, "pkgDetails")= chr "DNAcopy v1.76.0" 475s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 475s DH segmentation (locally-indexed) rows: 475s startRow endRow 475s 1 1 2677 475s int [1:2681] 7587 7588 7589 7590 7591 7592 7593 7594 7595 7596 ... 475s DH segmentation rows: 475s startRow endRow 475s 1 7587 10263 475s Segmenting DH signals...done 475s DH segmentation table: 475s dhStart dhEnd dhNbrOfLoci dhMean 475s 1 142693888 185449813 777 0.0973 475s startRow endRow 475s 1 7587 10263 475s Rows: 475s [1] 3 475s TCN segmentation rows: 475s startRow endRow 475s 3 7587 10267 475s TCN and DH segmentation rows: 475s startRow endRow 475s 3 7587 10267 475s startRow endRow 475s 1 7587 10263 475s startRow endRow 475s 1 1 7586 475s 2 NA NA 475s TCN segmentation (expanded) rows: 475s startRow endRow 475s 1 1 7586 475s 2 NA NA 475s 3 7587 10267 475s TCN and DH segmentation rows: 475s startRow endRow 475s 1 1 7586 475s 2 NA NA 475s 3 7587 10267 475s 4 10268 14658 475s startRow endRow 475s 1 10 7574 475s 2 NA NA 475s 3 7587 10263 475s startRow endRow 475s 1 1 7586 475s 2 NA NA 475s 3 7587 10267 475s Total CN segmentation table (expanded): 475s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 475s 3 1 142693888 185449813 2681 2.0689 777 777 475s (TCN,DH) segmentation for one total CN segment: 475s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 475s 3 3 1 1 142693888 185449813 2681 2.0689 777 475s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 475s 3 777 142693888 185449813 777 0.0973 475s Total CN segment #3 ([1.42694e+08,1.8545e+08]) of 4...done 475s Total CN segment #4 ([1.8545e+08,2.47137e+08]) of 4... 475s Number of TCN loci in segment: 4391 475s Locus data for TCN segment: 475s 'data.frame': 4391 obs. of 9 variables: 475s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 475s $ x : num 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 475s $ CT : num 2.93 2.15 2.82 2.93 2.46 ... 475s $ betaT : num 0.0811 0.5154 0.9473 0.3734 0.7506 ... 475s $ betaTN : num -0.169 0.609 1.028 0.525 0.968 ... 475s $ betaN : num 0.25 0.38 0.919 0.34 0.783 ... 475s $ muN : num 0 0.5 1 0.5 1 1 0 1 0 1 ... 475s $ index : int 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 475s $ rho : num NA 0.2186 NA 0.0503 NA ... 475s Number of loci: 4391 475s Number of SNPs: 1311 (29.86%) 475s Number of heterozygous SNPs: 1311 (100.00%) 475s Chromosome: 1 475s Segmenting DH signals... 475s Segmenting by CBS... 475s Chromosome: 1 475s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 475s Segmenting by CBS...done 475s List of 4 475s $ data :'data.frame': 4391 obs. of 4 variables: 475s ..$ chromosome: int [1:4391] 1 1 1 1 1 1 1 1 1 1 ... 475s ..$ x : num [1:4391] 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 475s ..$ y : num [1:4391] NA 0.2186 NA 0.0503 NA ... 475s ..$ index : int [1:4391] 1 2 3 4 5 6 7 8 9 10 ... 475s $ output :'data.frame': 1 obs. of 6 variables: 475s ..$ sampleName: chr NA 475s ..$ chromosome: int 1 475s ..$ start : num 1.85e+08 475s ..$ end : num 2.47e+08 475s ..$ nbrOfLoci : int 1311 475s ..$ mean : num 0.23 475s $ segRows:'data.frame': 1 obs. of 2 variables: 475s ..$ startRow: int 2 475s ..$ endRow : int 4388 475s $ params :List of 5 475s ..$ alpha : num 0.001 475s ..$ undo : num 0 475s ..$ joinSegments : logi TRUE 475s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 475s .. ..$ chromosome: int 1 475s .. ..$ start : num 1.85e+08 475s .. ..$ end : num 2.47e+08 475s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 475s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 475s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.014 0 0.014 0 0 475s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 475s - attr(*, "pkgDetails")= chr "DNAcopy v1.76.0" 475s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 475s DH segmentation (locally-indexed) rows: 475s startRow endRow 475s 1 2 4388 475s int [1:4391] 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 475s DH segmentation rows: 475s startRow endRow 475s 1 10269 14655 475s Segmenting DH signals...done 475s DH segmentation table: 475s dhStart dhEnd dhNbrOfLoci dhMean 475s 1 185449813 247137334 1311 0.2295 475s startRow endRow 475s 1 10269 14655 475s Rows: 475s [1] 4 475s TCN segmentation rows: 475s startRow endRow 475s 4 10268 14658 475s TCN and DH segmentation rows: 475s startRow endRow 475s 4 10268 14658 475s startRow endRow 475s 1 10269 14655 475s startRow endRow 475s 1 1 7586 475s 2 NA NA 475s 3 7587 10267 475s TCN segmentation (expanded) rows: 475s startRow endRow 475s 1 1 7586 475s 2 NA NA 475s 3 7587 10267 475s 4 10268 14658 475s TCN and DH segmentation rows: 475s startRow endRow 475s 1 1 7586 475s 2 NA NA 475s 3 7587 10267 475s 4 10268 14658 475s startRow endRow 475s 1 10 7574 475s 2 NA NA 475s 3 7587 10263 475s 4 10269 14655 475s startRow endRow 475s 1 1 7586 475s 2 NA NA 475s 3 7587 10267 475s 4 10268 14658 475s Total CN segmentation table (expanded): 475s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 475s 4 1 185449813 247137334 4391 2.6341 1311 1311 475s (TCN,DH) segmentation for one total CN segment: 475s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 475s 4 4 1 1 185449813 247137334 4391 2.6341 1311 475s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 475s 4 1311 185449813 247137334 1311 0.2295 475s Total CN segment #4 ([1.8545e+08,2.47137e+08]) of 4...done 475s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 475s 1 1 1 1 554484 120908858 7586 1.3853 2108 475s 2 1 2 1 120908859 142693887 0 NA 0 475s 3 1 3 1 142693888 185449813 2681 2.0689 777 475s 4 1 4 1 185449813 247137334 4391 2.6341 1311 475s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 475s 1 2108 554484 120908858 2108 0.5116 475s 2 0 NA NA NA NA 475s 3 777 142693888 185449813 777 0.0973 475s 4 1311 185449813 247137334 1311 0.2295 475s Calculating (C1,C2) per segment... 475s Calculating (C1,C2) per segment...done 475s Number of segments: 4 475s Segmenting paired tumor-normal signals using Paired PSCBS...done 475s Post-segmenting TCNs... 475s Number of segments: 4 475s Number of chromosomes: 1 475s [1] 1 475s Chromosome 1 ('chr01') of 1... 475s Rows: 475s [1] 1 2 3 4 475s Number of segments: 4 475s TCN segment #1 ('1') of 4... 475s Nothing todo. Only one DH segmentation. Skipping. 475s TCN segment #1 ('1') of 4...done 475s TCN segment #2 ('2') of 4... 475s Nothing todo. Only one DH segmentation. Skipping. 475s TCN segment #2 ('2') of 4...done 475s TCN segment #3 ('3') of 4... 475s Nothing todo. Only one DH segmentation. Skipping. 475s TCN segment #3 ('3') of 4...done 475s TCN segment #4 ('4') of 4... 475s Nothing todo. Only one DH segmentation. Skipping. 475s TCN segment #4 ('4') of 4...done 475s Chromosome 1 ('chr01') of 1...done 475s Update (C1,C2) per segment... 475s Update (C1,C2) per segment...done 475s Post-segmenting TCNs...done 475s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 475s 1 1 1 1 554484 120908858 7586 1.3853 2108 475s 2 1 2 1 120908859 142693887 0 NA 0 475s 3 1 3 1 142693888 185449813 2681 2.0689 777 475s 4 1 4 1 185449813 247137334 4391 2.6341 1311 475s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 475s 1 2108 554484 120908858 2108 0.5116 0.3382903 1.047010 475s 2 0 NA NA NA NA NA NA 475s 3 777 142693888 185449813 777 0.0973 0.9337980 1.135102 475s 4 1311 185449813 247137334 1311 0.2295 1.0147870 1.619313 475s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 475s 1 1 1 1 554484 120908858 7586 1.3853 2108 475s 2 1 2 1 120908859 142693887 0 NA 0 475s 3 1 3 1 142693888 185449813 2681 2.0689 777 475s 4 1 4 1 185449813 247137334 4391 2.6341 1311 475s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 475s 1 2108 554484 120908858 2108 0.5116 0.3382903 1.047010 475s 2 0 NA NA NA NA NA NA 475s 3 777 142693888 185449813 777 0.0973 0.9337980 1.135102 475s 4 1311 185449813 247137334 1311 0.2295 1.0147870 1.619313 475s - segmentByPairedPSCBS() w/ known segments using 'multisession' futures ... 475s Segmenting paired tumor-normal signals using Paired PSCBS... 475s Calling genotypes from normal allele B fractions... 475s num [1:14670] 0.8274 0.5072 0.1671 0.1609 0.0421 ... 475s Called genotypes: 475s num [1:14670] 1 0.5 0 0 0 0 1 0 1 0.5 ... 475s - attr(*, "modelFit")=List of 1 475s ..$ :List of 7 475s .. ..$ flavor : chr "density" 475s .. ..$ cn : int 2 475s .. ..$ nbrOfGenotypeGroups: int 3 475s .. ..$ tau : num [1:2] 0.315 0.677 475s .. ..$ n : int 14640 475s .. ..$ fit :Classes 'PeaksAndValleys' and 'data.frame': 5 obs. of 3 variables: 475s .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 475s .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 475s .. .. ..$ density: num [1:5] 1.48 0.522 1.056 0.552 1.454 475s .. ..$ fitValleys :Classes 'PeaksAndValleys' and 'data.frame': 2 obs. of 3 variables: 475s .. .. ..$ type : chr [1:2] "valley" "valley" 475s .. .. ..$ x : num [1:2] 0.315 0.677 475s .. .. ..$ density: num [1:2] 0.522 0.552 475s ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 475s muN 475s 0 0.5 1 475s 5221 4198 5251 475s Calling genotypes from normal allele B fractions...done 475s Normalizing betaT using betaN (TumorBoost)... 475s Normalized BAFs: 475s num [1:14670] 0.9301 0.1667 0.0685 0.0995 0.0155 ... 475s - attr(*, "modelFit")=List of 5 475s ..$ method : chr "normalizeTumorBoost" 475s ..$ flavor : chr "v4" 475s ..$ delta : num [1:14670] -0.17264 0.00239 0.1671 0.16085 0.04213 ... 475s .. ..- attr(*, "modelFit")=List of 1 475s .. .. ..$ :List of 7 475s .. .. .. ..$ flavor : chr "density" 475s .. .. .. ..$ cn : int 2 475s .. .. .. ..$ nbrOfGenotypeGroups: int 3 475s .. .. .. ..$ tau : num [1:2] 0.315 0.677 475s .. .. .. ..$ n : int 14640 475s .. .. .. ..$ fit :Classes 'PeaksAndValleys' and 'data.frame': 5 obs. of 3 variables: 475s .. .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 475s .. .. .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 475s .. .. .. .. ..$ density: num [1:5] 1.48 0.522 1.056 0.552 1.454 475s .. .. .. ..$ fitValleys :Classes 'PeaksAndValleys' and 'data.frame': 2 obs. of 3 variables: 475s .. .. .. .. ..$ type : chr [1:2] "valley" "valley" 475s .. .. .. .. ..$ x : num [1:2] 0.315 0.677 475s .. .. .. .. ..$ density: num [1:2] 0.522 0.552 475s .. .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 475s ..$ preserveScale: logi FALSE 475s ..$ scaleFactor : num NA 475s Normalizing betaT using betaN (TumorBoost)...done 475s Setup up data... 475s 'data.frame': 14670 obs. of 7 variables: 475s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 475s $ x : num 1145994 2941694 3710825 4240737 4276892 ... 475s $ CT : num 1.63 1.4 1.41 1.17 1.16 ... 475s $ betaT : num 0.7574 0.169 0.2357 0.2604 0.0576 ... 475s $ betaTN : num 0.9301 0.1667 0.0685 0.0995 0.0155 ... 475s ..- attr(*, "modelFit")=List of 5 475s .. ..$ method : chr "normalizeTumorBoost" 475s .. ..$ flavor : chr "v4" 475s .. ..$ delta : num [1:14670] -0.17264 0.00239 0.1671 0.16085 0.04213 ... 475s .. .. ..- attr(*, "modelFit")=List of 1 475s .. .. .. ..$ :List of 7 475s .. .. .. .. ..$ flavor : chr "density" 475s .. .. .. .. ..$ cn : int 2 475s .. .. .. .. ..$ nbrOfGenotypeGroups: int 3 475s .. .. .. .. ..$ tau : num [1:2] 0.315 0.677 475s .. .. .. .. ..$ n : int 14640 475s .. .. .. .. ..$ fit :Classes 'PeaksAndValleys' and 'data.frame': 5 obs. of 3 variables: 475s .. .. .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 475s .. .. .. .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 475s .. .. .. .. .. ..$ density: num [1:5] 1.48 0.522 1.056 0.552 1.454 475s .. .. .. .. ..$ fitValleys :Classes 'PeaksAndValleys' and 'data.frame': 2 obs. of 3 variables: 475s .. .. .. .. .. ..$ type : chr [1:2] "valley" "valley" 475s .. .. .. .. .. ..$ x : num [1:2] 0.315 0.677 475s .. .. .. .. .. ..$ density: num [1:2] 0.522 0.552 475s .. .. .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 475s .. ..$ preserveScale: logi FALSE 475s .. ..$ scaleFactor : num NA 475s $ betaN : num 0.8274 0.5072 0.1671 0.1609 0.0421 ... 475s $ muN : num 1 0.5 0 0 0 0 1 0 1 0.5 ... 475s ..- attr(*, "modelFit")=List of 1 475s .. ..$ :List of 7 475s .. .. ..$ flavor : chr "density" 475s .. .. ..$ cn : int 2 475s .. .. ..$ nbrOfGenotypeGroups: int 3 475s .. .. ..$ tau : num [1:2] 0.315 0.677 475s .. .. ..$ n : int 14640 475s .. .. ..$ fit :Classes 'PeaksAndValleys' and 'data.frame': 5 obs. of 3 variables: 475s .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 475s .. .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 475s .. .. .. ..$ density: num [1:5] 1.48 0.522 1.056 0.552 1.454 475s .. .. ..$ fitValleys :Classes 'PeaksAndValleys' and 'data.frame': 2 obs. of 3 variables: 475s .. .. .. ..$ type : chr [1:2] "valley" "valley" 475s .. .. .. ..$ x : num [1:2] 0.315 0.677 475s .. .. .. ..$ density: num [1:2] 0.522 0.552 475s .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 475s Setup up data...done 475s Dropping loci for which TCNs are missing... 475s Number of loci dropped: 12 475s Dropping loci for which TCNs are missing...done 475s Ordering data along genome... 475s 'data.frame': 14658 obs. of 7 variables: 475s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 475s $ x : num 554484 730720 782343 878522 916294 ... 475s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 475s $ betaT : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 475s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 475s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 475s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 475s Ordering data along genome...done 475s Keeping only current chromosome for 'knownSegments'... 475s Chromosome: 1 475s Known segments for this chromosome: 475s chromosome start end length 475s 1 1 -Inf 120908858 Inf 475s 2 1 120908859 142693887 21785028 475s 3 1 142693888 Inf Inf 475s Keeping only current chromosome for 'knownSegments'...done 475s alphaTCN: 0.009 475s alphaDH: 0.001 475s Number of loci: 14658 475s Calculating DHs... 475s Number of SNPs: 14658 475s Number of heterozygous SNPs: 4196 (28.63%) 475s Normalized DHs: 475s num [1:14658] NA NA NA NA NA ... 475s Calculating DHs...done 475s Random seed temporarily set (seed=c(48879), kind="L'Ecuyer-CMRG") 475s Produced 2 seeds from this stream for future usage 475s Identification of change points by total copy numbers... 475s Segmenting by CBS... 475s Chromosome: 1 475s Random seed temporarily set (seed=c(10407, 1066287653, -51199871, 161854402, -1995183193, 1503453565, -747102133), kind="L'Ecuyer-CMRG") 475s Produced 3 seeds from this stream for future usage 475s Segmenting by CBS...done 475s List of 4 475s $ data :'data.frame': 14658 obs. of 4 variables: 475s ..$ chromosome: int [1:14658] 1 1 1 1 1 1 1 1 1 1 ... 475s ..$ x : num [1:14658] 554484 730720 782343 878522 916294 ... 475s ..$ y : num [1:14658] 1.88 1.8 1.59 1.64 1.53 ... 475s ..$ index : int [1:14658] 1 2 3 4 5 6 7 8 9 10 ... 475s $ output :'data.frame': 4 obs. of 6 variables: 475s ..$ sampleName: chr [1:4] NA NA NA NA 475s ..$ chromosome: int [1:4] 1 1 1 1 475s ..$ start : num [1:4] 5.54e+05 1.21e+08 1.43e+08 1.85e+08 475s ..$ end : num [1:4] 1.21e+08 1.43e+08 1.85e+08 2.47e+08 475s ..$ nbrOfLoci : int [1:4] 7586 0 2681 4391 475s ..$ mean : num [1:4] 1.39 NA 2.07 2.63 475s $ segRows:'data.frame': 4 obs. of 2 variables: 475s ..$ startRow: int [1:4] 1 NA 7587 10268 475s ..$ endRow : int [1:4] 7586 NA 10267 14658 475s $ params :List of 5 475s ..$ alpha : num 0.009 475s ..$ undo : num 0 475s ..$ joinSegments : logi TRUE 475s ..$ knownSegments:'data.frame': 4 obs. of 3 variables: 475s .. ..$ chromosome: int [1:4] 1 1 2 1 475s .. ..$ start : num [1:4] -Inf -Inf -Inf 1.43e+08 475s .. ..$ end : num [1:4] 1.21e+08 Inf Inf Inf 475s ..$ seed : int [1:7] 10407 1066287653 -51199871 161854402 -1995183193 1503453565 -747102133 475s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 475s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.13 0.005 0.135 0 0 475s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 475s - attr(*, "pkgDetails")= chr "DNAcopy v1.76.0" 475s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 475s Identification of change points by total copy numbers...done 475s Restructure TCN segmentation results... 475s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean 475s 1 1 554484 120908858 7586 1.3853 475s 2 1 120908859 142693887 0 NA 475s 3 1 142693888 185449813 2681 2.0689 475s 4 1 185449813 247137334 4391 2.6341 475s Number of TCN segments: 4 475s Restructure TCN segmentation results...done 475s Total CN segment #1 ([ 554484,1.20909e+08]) of 4... 475s Number of TCN loci in segment: 7586 475s Locus data for TCN segment: 475s 'data.frame': 7586 obs. of 9 variables: 475s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 475s $ x : num 554484 730720 782343 878522 916294 ... 475s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 475s $ betaT : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 475s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 475s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 475s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 475s $ index : int 1 2 3 4 5 6 7 8 9 10 ... 475s $ rho : num NA NA NA NA NA ... 475s Number of loci: 7586 475s Number of SNPs: 2108 (27.79%) 475s Number of heterozygous SNPs: 2108 (100.00%) 475s Chromosome: 1 475s Segmenting DH signals... 475s Segmenting by CBS... 475s Chromosome: 1 475s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 475s Segmenting by CBS...done 475s List of 4 475s $ data :'data.frame': 7586 obs. of 4 variables: 475s ..$ chromosome: int [1:7586] 1 1 1 1 1 1 1 1 1 1 ... 475s ..$ x : num [1:7586] 554484 730720 782343 878522 916294 ... 475s ..$ y : num [1:7586] NA NA NA NA NA ... 475s ..$ index : int [1:7586] 1 2 3 4 5 6 7 8 9 10 ... 475s $ output :'data.frame': 1 obs. of 6 variables: 475s ..$ sampleName: chr NA 475s ..$ chromosome: int 1 475s ..$ start : num 554484 475s ..$ end : num 1.21e+08 475s ..$ nbrOfLoci : int 2108 475s ..$ mean : num 0.512 475s $ segRows:'data.frame': 1 obs. of 2 variables: 475s ..$ startRow: int 10 475s ..$ endRow : int 7574 475s $ params :List of 5 475s ..$ alpha : num 0.001 475s ..$ undo : num 0 475s ..$ joinSegments : logi TRUE 475s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 475s .. ..$ chromosome: int 1 475s .. ..$ start : num 554484 475s .. ..$ end : num 1.21e+08 475s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 475s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 475s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.035 0 0.035 0 0 475s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 475s - attr(*, "pkgDetails")= chr "DNAcopy v1.76.0" 475s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 475s DH segmentation (locally-indexed) rows: 475s startRow endRow 475s 1 10 7574 475s int [1:7586] 1 2 3 4 5 6 7 8 9 10 ... 475s DH segmentation rows: 475s startRow endRow 475s 1 10 7574 475s Segmenting DH signals...done 475s DH segmentation table: 475s dhStart dhEnd dhNbrOfLoci dhMean 475s 1 554484 120908858 2108 0.5116 475s startRow endRow 475s 1 10 7574 475s Rows: 475s [1] 1 475s TCN segmentation rows: 475s startRow endRow 475s 1 1 7586 475s TCN and DH segmentation rows: 475s startRow endRow 475s 1 1 7586 475s startRow endRow 475s 1 10 7574 475s NULL 475s TCN segmentation (expanded) rows: 475s startRow endRow 475s 1 1 7586 475s TCN and DH segmentation rows: 475s startRow endRow 475s 1 1 7586 475s 2 NA NA 475s 3 7587 10267 475s 4 10268 14658 475s startRow endRow 475s 1 10 7574 475s startRow endRow 475s 1 1 7586 475s Total CN segmentation table (expanded): 475s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 475s 1 1 554484 120908858 7586 1.3853 2108 2108 475s (TCN,DH) segmentation for one total CN segment: 475s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 475s 1 1 1 1 554484 120908858 7586 1.3853 2108 475s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 475s 1 2108 554484 120908858 2108 0.5116 475s Total CN segment #1 ([ 554484,1.20909e+08]) of 4...done 475s Total CN segment #2 ([1.20909e+08,1.42694e+08]) of 4... 475s Number of TCN loci in segment: 0 475s Locus data for TCN segment: 475s 'data.frame': 0 obs. of 9 variables: 475s $ chromosome: int 475s $ x : num 475s $ CT : num 475s $ betaT : num 475s $ betaTN : num 475s $ betaN : num 475s $ muN : num 475s $ index : int 475s $ rho : num 475s Number of loci: 0 475s Number of SNPs: 0 (NaN%) 475s Number of heterozygous SNPs: 0 (NaN%) 475s Chromosome: 1 475s Segmenting DH signals... 475s Segmenting by CBS... 475s Chromosome: NA 475s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 475s Segmenting by CBS...done 475s List of 4 475s $ data :'data.frame': 0 obs. of 4 variables: 475s ..$ chromosome: int(0) 475s ..$ x : num(0) 475s ..$ y : num(0) 475s ..$ index : int(0) 475s $ output :'data.frame': 0 obs. of 6 variables: 475s ..$ sampleName: chr(0) 475s ..$ chromosome: num(0) 475s ..$ start : num(0) 475s ..$ end : num(0) 475s ..$ nbrOfLoci : int(0) 475s ..$ mean : num(0) 475s $ segRows:'data.frame': 0 obs. of 2 variables: 475s ..$ startRow: int(0) 475s ..$ endRow : int(0) 475s $ params :List of 5 475s ..$ alpha : num 0.001 475s ..$ undo : num 0 475s ..$ joinSegments : logi TRUE 475s ..$ knownSegments:'data.frame': 0 obs. of 3 variables: 475s .. ..$ chromosome: int(0) 475s .. ..$ start : num(0) 475s .. ..$ end : num(0) 475s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 475s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 475s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.001 0 0.001 0 0 475s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 475s - attr(*, "pkgDetails")= chr "DNAcopy v1.76.0" 475s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 475s DH segmentation (locally-indexed) rows: 475s [1] startRow endRow 475s <0 rows> (or 0-length row.names) 475s int(0) 475s DH segmentation rows: 475s [1] startRow endRow 475s <0 rows> (or 0-length row.names) 475s Segmenting DH signals...done 475s DH segmentation table: 475s dhStart dhEnd dhNbrOfLoci dhMean 475s NA NA NA NA NA 475s startRow endRow 475s NA NA NA 475s Rows: 475s [1] 2 475s TCN segmentation rows: 475s startRow endRow 475s 2 NA NA 475s TCN and DH segmentation rows: 475s startRow endRow 475s 2 NA NA 475s startRow endRow 475s NA NA NA 475s startRow endRow 475s 1 1 7586 475s TCN segmentation (expanded) rows: 475s startRow endRow 475s 1 1 7586 475s 2 NA NA 475s TCN and DH segmentation rows: 475s startRow endRow 475s 1 1 7586 475s 2 NA NA 475s 3 7587 10267 475s 4 10268 14658 475s startRow endRow 475s 1 10 7574 475s 2 NA NA 475s startRow endRow 475s 1 1 7586 475s 2 NA NA 475s Total CN segmentation table (expanded): 475s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 475s 2 1 120908859 142693887 0 NA 0 0 475s (TCN,DH) segmentation for one total CN segment: 475s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 475s 2 2 1 1 120908859 142693887 0 NA 0 475s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 475s 2 0 NA NA NA NA 475s Total CN segment #2 ([1.20909e+08,1.42694e+08]) of 4...done 475s Total CN segment #3 ([1.42694e+08,1.8545e+08]) of 4... 475s Number of TCN loci in segment: 2681 475s Locus data for TCN segment: 475s 'data.frame': 2681 obs. of 9 variables: 475s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 475s $ x : num 1.43e+08 1.43e+08 1.43e+08 1.43e+08 1.44e+08 ... 475s $ CT : num 2.27 1.55 1.47 1.5 1.81 ... 475s $ betaT : num 0.34 0.55 0.048 0.813 0.575 ... 475s $ betaTN : num 0.441 0.629 -0.05 0.958 0.872 ... 475s $ betaN : num 0.3851 0.3933 0.0981 0.8552 0.7028 ... 475s $ muN : num 0.5 0.5 0 1 1 1 1 0.5 1 1 ... 475s $ index : int 7587 7588 7589 7590 7591 7592 7593 7594 7595 7596 ... 475s $ rho : num 0.117 0.258 NA NA NA ... 475s Number of loci: 2681 475s Number of SNPs: 777 (28.98%) 475s Number of heterozygous SNPs: 777 (100.00%) 475s Chromosome: 1 475s Segmenting DH signals... 475s Segmenting by CBS... 475s Chromosome: 1 475s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 475s Segmenting by CBS...done 475s List of 4 475s $ data :'data.frame': 2681 obs. of 4 variables: 475s ..$ chromosome: int [1:2681] 1 1 1 1 1 1 1 1 1 1 ... 475s ..$ x : num [1:2681] 1.43e+08 1.43e+08 1.43e+08 1.43e+08 1.44e+08 ... 475s ..$ y : num [1:2681] 0.117 0.258 NA NA NA ... 475s ..$ index : int [1:2681] 1 2 3 4 5 6 7 8 9 10 ... 475s $ output :'data.frame': 1 obs. of 6 variables: 475s ..$ sampleName: chr NA 475s ..$ chromosome: int 1 475s ..$ start : num 1.43e+08 475s ..$ end : num 1.85e+08 475s ..$ nbrOfLoci : int 777 475s ..$ mean : num 0.0973 475s $ segRows:'data.frame': 1 obs. of 2 variables: 475s ..$ startRow: int 1 475s ..$ endRow : int 2677 475s $ params :List of 5 475s ..$ alpha : num 0.001 475s ..$ undo : num 0 475s ..$ joinSegments : logi TRUE 475s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 475s .. ..$ chromosome: int 1 475s .. ..$ start : num 1.43e+08 475s .. ..$ end : num 1.85e+08 475s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 475s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 475s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.007 0 0.007 0 0 475s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 475s - attr(*, "pkgDetails")= chr "DNAcopy v1.76.0" 475s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 475s DH segmentation (locally-indexed) rows: 475s startRow endRow 475s 1 1 2677 475s int [1:2681] 7587 7588 7589 7590 7591 7592 7593 7594 7595 7596 ... 475s DH segmentation rows: 475s startRow endRow 475s 1 7587 10263 475s Segmenting DH signals...done 475s DH segmentation table: 475s dhStart dhEnd dhNbrOfLoci dhMean 475s 1 142693888 185449813 777 0.0973 475s startRow endRow 475s 1 7587 10263 475s Rows: 475s [1] 3 475s TCN segmentation rows: 475s startRow endRow 475s 3 7587 10267 475s TCN and DH segmentation rows: 475s startRow endRow 475s 3 7587 10267 475s startRow endRow 475s 1 7587 10263 475s startRow endRow 475s 1 1 7586 475s 2 NA NA 475s TCN segmentation (expanded) rows: 475s startRow endRow 475s 1 1 7586 475s 2 NA NA 475s 3 7587 10267 475s TCN and DH segmentation rows: 475s startRow endRow 475s 1 1 7586 475s 2 NA NA 475s 3 7587 10267 475s 4 10268 14658 475s startRow endRow 475s 1 10 7574 475s 2 NA NA 475s 3 7587 10263 475s startRow endRow 475s 1 1 7586 475s 2 NA NA 475s 3 7587 10267 475s Total CN segmentation table (expanded): 475s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 475s 3 1 142693888 185449813 2681 2.0689 777 777 475s (TCN,DH) segmentation for one total CN segment: 475s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 475s 3 3 1 1 142693888 185449813 2681 2.0689 777 475s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 475s 3 777 142693888 185449813 777 0.0973 475s Total CN segment #3 ([1.42694e+08,1.8545e+08]) of 4...done 475s Total CN segment #4 ([1.8545e+08,2.47137e+08]) of 4... 475s Number of TCN loci in segment: 4391 475s Locus data for TCN segment: 475s 'data.frame': 4391 obs. of 9 variables: 475s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 475s $ x : num 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 475s $ CT : num 2.93 2.15 2.82 2.93 2.46 ... 475s $ betaT : num 0.0811 0.5154 0.9473 0.3734 0.7506 ... 475s $ betaTN : num -0.169 0.609 1.028 0.525 0.968 ... 475s $ betaN : num 0.25 0.38 0.919 0.34 0.783 ... 475s $ muN : num 0 0.5 1 0.5 1 1 0 1 0 1 ... 475s $ index : int 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 475s $ rho : num NA 0.2186 NA 0.0503 NA ... 475s Number of loci: 4391 475s Number of SNPs: 1311 (29.86%) 475s Number of heterozygous SNPs: 1311 (100.00%) 475s Chromosome: 1 475s Segmenting DH signals... 475s Segmenting by CBS... 475s Chromosome: 1 475s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 475s Segmenting by CBS...done 475s List of 4 475s $ data :'data.frame': 4391 obs. of 4 variables: 475s ..$ chromosome: int [1:4391] 1 1 1 1 1 1 1 1 1 1 ... 475s ..$ x : num [1:4391] 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 475s ..$ y : num [1:4391] NA 0.2186 NA 0.0503 NA ... 475s ..$ index : int [1:4391] 1 2 3 4 5 6 7 8 9 10 ... 475s $ output :'data.frame': 1 obs. of 6 variables: 475s ..$ sampleName: chr NA 475s ..$ chromosome: int 1 475s ..$ start : num 1.85e+08 475s ..$ end : num 2.47e+08 475s ..$ nbrOfLoci : int 1311 475s ..$ mean : num 0.23 475s $ segRows:'data.frame': 1 obs. of 2 variables: 475s ..$ startRow: int 2 475s ..$ endRow : int 4388 475s $ params :List of 5 475s ..$ alpha : num 0.001 475s ..$ undo : num 0 475s ..$ joinSegments : logi TRUE 475s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 475s .. ..$ chromosome: int 1 475s .. ..$ start : num 1.85e+08 475s .. ..$ end : num 2.47e+08 475s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 475s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 475s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.014 0 0.014 0 0 475s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 475s - attr(*, "pkgDetails")= chr "DNAcopy v1.76.0" 475s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 475s DH segmentation (locally-indexed) rows: 475s startRow endRow 475s 1 2 4388 475s int [1:4391] 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 475s DH segmentation rows: 475s startRow endRow 475s 1 10269 14655 475s Segmenting DH signals...done 475s DH segmentation table: 475s dhStart dhEnd dhNbrOfLoci dhMean 475s 1 185449813 247137334 1311 0.2295 475s startRow endRow 475s 1 10269 14655 475s Rows: 475s [1] 4 475s TCN segmentation rows: 475s startRow endRow 475s 4 10268 14658 475s TCN and DH segmentation rows: 475s startRow endRow 475s 4 10268 14658 475s startRow endRow 475s 1 10269 14655 475s startRow endRow 475s 1 1 7586 475s 2 NA NA 475s 3 7587 10267 475s TCN segmentation (expanded) rows: 475s startRow endRow 475s 1 1 7586 475s 2 NA NA 475s 3 7587 10267 475s 4 10268 14658 475s TCN and DH segmentation rows: 475s startRow endRow 475s 1 1 7586 475s 2 NA NA 475s 3 7587 10267 475s 4 10268 14658 475s startRow endRow 475s 1 10 7574 475s 2 NA NA 475s 3 7587 10263 475s 4 10269 14655 475s startRow endRow 475s 1 1 7586 475s 2 NA NA 475s 3 7587 10267 475s 4 10268 14658 475s Total CN segmentation table (expanded): 475s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 475s 4 1 185449813 247137334 4391 2.6341 1311 1311 475s (TCN,DH) segmentation for one total CN segment: 475s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 475s 4 4 1 1 185449813 247137334 4391 2.6341 1311 475s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 475s 4 1311 185449813 247137334 1311 0.2295 475s Total CN segment #4 ([1.8545e+08,2.47137e+08]) of 4...done 475s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 475s 1 1 1 1 554484 120908858 7586 1.3853 2108 475s 2 1 2 1 120908859 142693887 0 NA 0 475s 3 1 3 1 142693888 185449813 2681 2.0689 777 475s 4 1 4 1 185449813 247137334 4391 2.6341 1311 475s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 475s 1 2108 554484 120908858 2108 0.5116 475s 2 0 NA NA NA NA 475s 3 777 142693888 185449813 777 0.0973 475s 4 1311 185449813 247137334 1311 0.2295 475s Calculating (C1,C2) per segment... 475s Calculating (C1,C2) per segment...done 475s Number of segments: 4 475s Segmenting paired tumor-normal signals using Paired PSCBS...done 475s Post-segmenting TCNs... 475s Number of segments: 4 475s Number of chromosomes: 1 475s [1] 1 475s Chromosome 1 ('chr01') of 1... 475s Rows: 475s [1] 1 2 3 4 475s Number of segments: 4 475s TCN segment #1 ('1') of 4... 475s Nothing todo. Only one DH segmentation. Skipping. 475s TCN segment #1 ('1') of 4...done 475s TCN segment #2 ('2') of 4... 475s Nothing todo. Only one DH segmentation. Skipping. 475s TCN segment #2 ('2') of 4...done 475s TCN segment #3 ('3') of 4... 475s Nothing todo. Only one DH segmentation. Skipping. 475s TCN segment #3 ('3') of 4...done 475s TCN segment #4 ('4') of 4... 475s Nothing todo. Only one DH segmentation. Skipping. 475s TCN segment #4 ('4') of 4...done 475s Chromosome 1 ('chr01') of 1...done 475s Update (C1,C2) per segment... 475s Update (C1,C2) per segment...done 475s Post-segmenting TCNs...done 475s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 475s 1 1 1 1 554484 120908858 7586 1.3853 2108 475s 2 1 2 1 120908859 142693887 0 NA 0 475s 3 1 3 1 142693888 185449813 2681 2.0689 777 475s 4 1 4 1 185449813 247137334 4391 2.6341 1311 475s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 475s 1 2108 554484 120908858 2108 0.5116 0.3382903 1.047010 475s 2 0 NA NA NA NA NA NA 475s 3 777 142693888 185449813 777 0.0973 0.9337980 1.135102 475s 4 1311 185449813 247137334 1311 0.2295 1.0147870 1.619313 475s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 475s 1 1 1 1 554484 120908858 7586 1.3853 2108 475s 2 1 2 1 120908859 142693887 0 NA 0 475s 3 1 3 1 142693888 185449813 2681 2.0689 777 475s 4 1 4 1 185449813 247137334 4391 2.6341 1311 475s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 475s 1 2108 554484 120908858 2108 0.5116 0.3382903 1.047010 475s 2 0 NA NA NA NA NA NA 475s 3 777 142693888 185449813 777 0.0973 0.9337980 1.135102 475s 4 1311 185449813 247137334 1311 0.2295 1.0147870 1.619313 475s > 475s > message("*** segmentByPairedPSCBS() via futures ... DONE") 475s *** segmentByPairedPSCBS() via futures ... DONE 475s > 475s > 475s > ## Cleanup 475s > plan(oplan) 475s > rm(list=c("fits", "data", "fit")) 475s > 475s > proc.time() 475s user system elapsed 475s 5.356 0.210 9.825 475s Test segmentByPairedPSCBS,futures passed 475s 0 475s Begin test segmentByPairedPSCBS,noNormalBAFs 477s + cat segmentByPairedPSCBS,noNormalBAFs.Rout 477s 477s R version 4.3.2 (2023-10-31) -- "Eye Holes" 477s Copyright (C) 2023 The R Foundation for Statistical Computing 477s Platform: x86_64-pc-linux-gnu (64-bit) 477s 477s R is free software and comes with ABSOLUTELY NO WARRANTY. 477s You are welcome to redistribute it under certain conditions. 477s Type 'license()' or 'licence()' for distribution details. 477s 477s R is a collaborative project with many contributors. 477s Type 'contributors()' for more information and 477s 'citation()' on how to cite R or R packages in publications. 477s 477s Type 'demo()' for some demos, 'help()' for on-line help, or 477s 'help.start()' for an HTML browser interface to help. 477s Type 'q()' to quit R. 477s 477s [Previously saved workspace restored] 477s 477s > library("PSCBS") 477s PSCBS v0.66.0 (2021-10-23 07:40:02 UTC) successfully loaded. See ?PSCBS for help. 477s 477s Attaching package: 'PSCBS' 477s 477s The following objects are masked from 'package:base': 477s 477s append, load 477s 477s > 477s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 477s > # Load SNP microarray data 477s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 477s > data <- PSCBS::exampleData("paired.chr01") 477s > str(data) 477s 'data.frame': 73346 obs. of 6 variables: 477s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 477s $ x : int 1145994 2224111 2319424 2543484 2926730 2941694 3084986 3155127 3292731 3695086 ... 477s $ CT : num 1.625 1.071 1.406 1.18 0.856 ... 477s $ betaT : num 0.757 0.771 0.834 0.778 0.229 ... 477s $ CN : num 2.36 2.13 2.59 1.93 1.71 ... 477s $ betaN : num 0.827 0.875 0.887 0.884 0.103 ... 477s > 477s > # Drop single-locus outliers 477s > dataS <- dropSegmentationOutliers(data) 477s > 477s > # Run light-weight tests by default 477s > if (Sys.getenv("_R_CHECK_FULL_") == "") { 477s + # Use only every 5th data point 477s + dataS <- dataS[seq(from=1, to=nrow(data), by=5),] 477s + # Number of segments (for assertion) 477s + nSegs <- 3L 477s + # Number of bootstrap samples (see below) 477s + B <- 100L 477s + } else { 477s + # Full tests 477s + nSegs <- 8L 477s + B <- 1000L 477s + } 477s > 477s > str(dataS) 477s 'data.frame': 14670 obs. of 6 variables: 477s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 477s $ x : int 1145994 2941694 3710825 4240737 4276892 4464544 4714611 5095111 5034491 5158416 ... 477s $ CT : num 1.63 1.4 1.41 1.17 1.16 ... 477s $ betaT : num 0.7574 0.169 0.2357 0.2604 0.0576 ... 477s $ CN : num 2.36 2.13 2.26 2.01 2.32 ... 477s $ betaN : num 0.8274 0.5072 0.1671 0.1609 0.0421 ... 477s > 477s > R.oo::attachLocally(dataS) 477s > 477s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 477s > # Simulate that genotypes are known by other means 477s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 477s > library("aroma.light") 477s aroma.light v3.32.0 (2023-10-24) successfully loaded. See ?aroma.light for help. 477s > muN <- aroma.light::callNaiveGenotypes(betaN, censorAt=c(0,1)) 477s > 477s > 477s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 477s > # Paired PSCBS segmentation 477s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 477s > fit <- segmentByPairedPSCBS(CT, betaT=betaT, muN=muN, tbn=FALSE, 477s + chromosome=chromosome, x=x, 477s + seed=0xBEEF, verbose=-10) 477s Segmenting paired tumor-normal signals using Paired PSCBS... 477s Setup up data... 477s 'data.frame': 14670 obs. of 6 variables: 477s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 477s $ x : num 1145994 2941694 3710825 4240737 4276892 ... 477s $ CT : num 1.63 1.4 1.41 1.17 1.16 ... 477s $ betaT : num 0.7574 0.169 0.2357 0.2604 0.0576 ... 477s $ betaTN : num 0.7574 0.169 0.2357 0.2604 0.0576 ... 477s $ muN : num 1 0.5 0 0 0 0 1 0 1 0.5 ... 477s ..- attr(*, "modelFit")=List of 1 477s .. ..$ :List of 7 477s .. .. ..$ flavor : chr "density" 477s .. .. ..$ cn : int 2 477s .. .. ..$ nbrOfGenotypeGroups: int 3 477s .. .. ..$ tau : num [1:2] 0.315 0.677 477s .. .. ..$ n : int 14640 477s .. .. ..$ fit :Classes 'PeaksAndValleys' and 'data.frame': 5 obs. of 3 variables: 477s .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 477s .. .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 477s .. .. .. ..$ density: num [1:5] 1.48 0.522 1.056 0.552 1.454 477s .. .. ..$ fitValleys :Classes 'PeaksAndValleys' and 'data.frame': 2 obs. of 3 variables: 477s .. .. .. ..$ type : chr [1:2] "valley" "valley" 477s .. .. .. ..$ x : num [1:2] 0.315 0.677 477s .. .. .. ..$ density: num [1:2] 0.522 0.552 477s .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 477s Setup up data...done 477s Dropping loci for which TCNs are missing... 477s Number of loci dropped: 12 477s Dropping loci for which TCNs are missing...done 477s Ordering data along genome... 477s 'data.frame': 14658 obs. of 6 variables: 477s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 477s $ x : num 554484 730720 782343 878522 916294 ... 477s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 477s $ betaT : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 477s $ betaTN : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 477s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 477s Ordering data along genome...done 477s Keeping only current chromosome for 'knownSegments'... 477s Chromosome: 1 477s Known segments for this chromosome: 477s [1] chromosome start end 477s <0 rows> (or 0-length row.names) 477s Keeping only current chromosome for 'knownSegments'...done 477s alphaTCN: 0.009 477s alphaDH: 0.001 477s Number of loci: 14658 477s Calculating DHs... 477s Number of SNPs: 14658 477s Number of heterozygous SNPs: 4196 (28.63%) 477s Normalized DHs: 477s num [1:14658] NA NA NA NA NA ... 477s Calculating DHs...done 477s Random seed temporarily set (seed=c(48879), kind="L'Ecuyer-CMRG") 477s Produced 2 seeds from this stream for future usage 477s Identification of change points by total copy numbers... 477s Segmenting by CBS... 477s Chromosome: 1 477s Random seed temporarily set (seed=c(10407, 1066287653, -51199871, 161854402, -1995183193, 1503453565, -747102133), kind="L'Ecuyer-CMRG") 477s Segmenting by CBS...done 477s List of 4 477s $ data :'data.frame': 14658 obs. of 4 variables: 477s ..$ chromosome: int [1:14658] 1 1 1 1 1 1 1 1 1 1 ... 477s ..$ x : num [1:14658] 554484 730720 782343 878522 916294 ... 477s ..$ y : num [1:14658] 1.88 1.8 1.59 1.64 1.53 ... 477s ..$ index : int [1:14658] 1 2 3 4 5 6 7 8 9 10 ... 477s $ output :'data.frame': 3 obs. of 6 variables: 477s ..$ sampleName: chr [1:3] NA NA NA 477s ..$ chromosome: int [1:3] 1 1 1 477s ..$ start : num [1:3] 5.54e+05 1.44e+08 1.85e+08 477s ..$ end : num [1:3] 1.44e+08 1.85e+08 2.47e+08 477s ..$ nbrOfLoci : int [1:3] 7599 2668 4391 477s ..$ mean : num [1:3] 1.39 2.07 2.63 477s $ segRows:'data.frame': 3 obs. of 2 variables: 477s ..$ startRow: int [1:3] 1 7600 10268 477s ..$ endRow : int [1:3] 7599 10267 14658 477s $ params :List of 5 477s ..$ alpha : num 0.009 477s ..$ undo : num 0 477s ..$ joinSegments : logi TRUE 477s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 477s .. ..$ chromosome: int 1 477s .. ..$ start : num -Inf 477s .. ..$ end : num Inf 477s ..$ seed : int [1:7] 10407 1066287653 -51199871 161854402 -1995183193 1503453565 -747102133 477s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 477s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.4 0 0.401 0 0 477s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 477s - attr(*, "pkgDetails")= chr "DNAcopy v1.76.0" 477s - attr(*, "randomSeed")= int [1:7] 10407 1066287653 -51199871 161854402 -1995183193 1503453565 -747102133 477s Identification of change points by total copy numbers...done 477s Restructure TCN segmentation results... 477s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean 477s 1 1 554484 143926517 7599 1.3859 477s 2 1 143926517 185449813 2668 2.0704 477s 3 1 185449813 247137334 4391 2.6341 477s Number of TCN segments: 3 477s Restructure TCN segmentation results...done 477s Total CN segment #1 ([ 554484,1.43927e+08]) of 3... 477s Number of TCN loci in segment: 7599 477s Locus data for TCN segment: 477s 'data.frame': 7599 obs. of 8 variables: 477s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 477s $ x : num 554484 730720 782343 878522 916294 ... 477s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 477s $ betaT : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 477s $ betaTN : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 477s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 477s $ index : int 1 2 3 4 5 6 7 8 9 10 ... 477s $ rho : num NA NA NA NA NA ... 477s Number of loci: 7599 477s Number of SNPs: 2111 (27.78%) 477s Number of heterozygous SNPs: 2111 (100.00%) 477s Chromosome: 1 477s Segmenting DH signals... 477s Segmenting by CBS... 477s Chromosome: 1 477s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 477s Segmenting by CBS...done 477s List of 4 477s $ data :'data.frame': 7599 obs. of 4 variables: 477s ..$ chromosome: int [1:7599] 1 1 1 1 1 1 1 1 1 1 ... 477s ..$ x : num [1:7599] 554484 730720 782343 878522 916294 ... 477s ..$ y : num [1:7599] NA NA NA NA NA ... 477s ..$ index : int [1:7599] 1 2 3 4 5 6 7 8 9 10 ... 477s $ output :'data.frame': 1 obs. of 6 variables: 477s ..$ sampleName: chr NA 477s ..$ chromosome: int 1 477s ..$ start : num 554484 477s ..$ end : num 1.44e+08 477s ..$ nbrOfLoci : int 2111 477s ..$ mean : num 0.524 477s $ segRows:'data.frame': 1 obs. of 2 variables: 477s ..$ startRow: int 10 477s ..$ endRow : int 7594 477s $ params :List of 5 477s ..$ alpha : num 0.001 477s ..$ undo : num 0 477s ..$ joinSegments : logi TRUE 477s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 477s .. ..$ chromosome: int 1 477s .. ..$ start : num 554484 477s .. ..$ end : num 1.44e+08 477s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 477s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 477s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.023 0 0.023 0 0 477s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 477s - attr(*, "pkgDetails")= chr "DNAcopy v1.76.0" 477s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 477s DH segmentation (locally-indexed) rows: 477s startRow endRow 477s 1 10 7594 477s int [1:7599] 1 2 3 4 5 6 7 8 9 10 ... 477s DH segmentation rows: 477s startRow endRow 477s 1 10 7594 477s Segmenting DH signals...done 477s DH segmentation table: 477s dhStart dhEnd dhNbrOfLoci dhMean 477s 1 554484 143926517 2111 0.5237 477s startRow endRow 477s 1 10 7594 477s Rows: 477s [1] 1 477s TCN segmentation rows: 477s startRow endRow 477s 1 1 7599 477s TCN and DH segmentation rows: 477s startRow endRow 477s 1 1 7599 477s startRow endRow 477s 1 10 7594 477s NULL 477s TCN segmentation (expanded) rows: 477s startRow endRow 477s 1 1 7599 477s TCN and DH segmentation rows: 477s startRow endRow 477s 1 1 7599 477s 2 7600 10267 477s 3 10268 14658 477s startRow endRow 477s 1 10 7594 477s startRow endRow 477s 1 1 7599 477s Total CN segmentation table (expanded): 477s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 477s 1 1 554484 143926517 7599 1.3859 2111 2111 477s (TCN,DH) segmentation for one total CN segment: 477s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 477s 1 1 1 1 554484 143926517 7599 1.3859 2111 477s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 477s 1 2111 554484 143926517 2111 0.5237 477s Total CN segment #1 ([ 554484,1.43927e+08]) of 3...done 477s Total CN segment #2 ([1.43927e+08,1.8545e+08]) of 3... 477s Number of TCN loci in segment: 2668 477s Locus data for TCN segment: 477s 'data.frame': 2668 obs. of 8 variables: 477s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 477s $ x : num 1.44e+08 1.44e+08 1.44e+08 1.44e+08 1.44e+08 ... 477s $ CT : num 2.1 2.1 2.09 1.8 2.34 ... 477s $ betaT : num 0.1899 0.909 0.9166 0.1668 0.0308 ... 477s $ betaTN : num 0.1899 0.909 0.9166 0.1668 0.0308 ... 477s $ muN : num 0 1 1 0 0 1 0 0 0 0 ... 477s $ index : int 7600 7601 7602 7603 7604 7605 7606 7607 7608 7609 ... 477s $ rho : num NA NA NA NA NA NA NA NA NA NA ... 477s Number of loci: 2668 477s Number of SNPs: 774 (29.01%) 477s Number of heterozygous SNPs: 774 (100.00%) 477s Chromosome: 1 477s Segmenting DH signals... 477s Segmenting by CBS... 477s Chromosome: 1 477s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 477s Segmenting by CBS...done 477s List of 4 477s $ data :'data.frame': 2668 obs. of 4 variables: 477s ..$ chromosome: int [1:2668] 1 1 1 1 1 1 1 1 1 1 ... 477s ..$ x : num [1:2668] 1.44e+08 1.44e+08 1.44e+08 1.44e+08 1.44e+08 ... 477s ..$ y : num [1:2668] NA NA NA NA NA NA NA NA NA NA ... 477s ..$ index : int [1:2668] 1 2 3 4 5 6 7 8 9 10 ... 477s $ output :'data.frame': 1 obs. of 6 variables: 477s ..$ sampleName: chr NA 477s ..$ chromosome: int 1 477s ..$ start : num 1.44e+08 477s ..$ end : num 1.85e+08 477s ..$ nbrOfLoci : int 774 477s ..$ mean : num 0.154 477s $ segRows:'data.frame': 1 obs. of 2 variables: 477s ..$ startRow: int 15 477s ..$ endRow : int 2664 477s $ params :List of 5 477s ..$ alpha : num 0.001 477s ..$ undo : num 0 477s ..$ joinSegments : logi TRUE 477s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 477s .. ..$ chromosome: int 1 477s .. ..$ start : num 1.44e+08 477s .. ..$ end : num 1.85e+08 477s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 477s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 477s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.008 0 0.008 0 0 477s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 477s - attr(*, "pkgDetails")= chr "DNAcopy v1.76.0" 477s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 477s DH segmentation (locally-indexed) rows: 477s startRow endRow 477s 1 15 2664 477s int [1:2668] 7600 7601 7602 7603 7604 7605 7606 7607 7608 7609 ... 477s DH segmentation rows: 477s startRow endRow 477s 1 7614 10263 477s Segmenting DH signals...done 477s DH segmentation table: 477s dhStart dhEnd dhNbrOfLoci dhMean 477s 1 143926517 185449813 774 0.1542 477s startRow endRow 477s 1 7614 10263 477s Rows: 477s [1] 2 477s TCN segmentation rows: 477s startRow endRow 477s 2 7600 10267 477s TCN and DH segmentation rows: 477s startRow endRow 477s 2 7600 10267 477s startRow endRow 477s 1 7614 10263 477s startRow endRow 477s 1 1 7599 477s TCN segmentation (expanded) rows: 477s startRow endRow 477s 1 1 7599 477s 2 7600 10267 477s TCN and DH segmentation rows: 477s startRow endRow 477s 1 1 7599 477s 2 7600 10267 477s 3 10268 14658 477s startRow endRow 477s 1 10 7594 477s 2 7614 10263 477s startRow endRow 477s 1 1 7599 477s 2 7600 10267 477s Total CN segmentation table (expanded): 477s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 477s 2 1 143926517 185449813 2668 2.0704 774 774 477s (TCN,DH) segmentation for one total CN segment: 477s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 477s 2 2 1 1 143926517 185449813 2668 2.0704 774 477s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 477s 2 774 143926517 185449813 774 0.1542 477s Total CN segment #2 ([1.43927e+08,1.8545e+08]) of 3...done 477s Total CN segment #3 ([1.8545e+08,2.47137e+08]) of 3... 477s Number of TCN loci in segment: 4391 477s Locus data for TCN segment: 477s 'data.frame': 4391 obs. of 8 variables: 477s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 477s $ x : num 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 477s $ CT : num 2.93 2.15 2.82 2.93 2.46 ... 477s $ betaT : num 0.0811 0.5154 0.9473 0.3734 0.7506 ... 477s $ betaTN : num 0.0811 0.5154 0.9473 0.3734 0.7506 ... 477s $ muN : num 0 0.5 1 0.5 1 1 0 1 0 1 ... 477s $ index : int 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 477s $ rho : num NA 0.0308 NA 0.2533 NA ... 477s Number of loci: 4391 477s Number of SNPs: 1311 (29.86%) 477s Number of heterozygous SNPs: 1311 (100.00%) 477s Chromosome: 1 477s Segmenting DH signals... 477s Segmenting by CBS... 477s Chr+ [ 0 != 0 ] 477s + echo Test segmentByPairedPSCBS,noNormalBAFs passed 477s + echo 0 477s + echo Begin test segmentByPairedPSCBS,report 477s + exitcode=0 477s + R CMD BATCH segmentByPairedPSCBS,report.R 477s omosome: 1 477s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 477s Segmenting by CBS...done 477s List of 4 477s $ data :'data.frame': 4391 obs. of 4 variables: 477s ..$ chromosome: int [1:4391] 1 1 1 1 1 1 1 1 1 1 ... 477s ..$ x : num [1:4391] 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 477s ..$ y : num [1:4391] NA 0.0308 NA 0.2533 NA ... 477s ..$ index : int [1:4391] 1 2 3 4 5 6 7 8 9 10 ... 477s $ output :'data.frame': 1 obs. of 6 variables: 477s ..$ sampleName: chr NA 477s ..$ chromosome: int 1 477s ..$ start : num 1.85e+08 477s ..$ end : num 2.47e+08 477s ..$ nbrOfLoci : int 1311 477s ..$ mean : num 0.251 477s $ segRows:'data.frame': 1 obs. of 2 variables: 477s ..$ startRow: int 2 477s ..$ endRow : int 4388 477s $ params :List of 5 477s ..$ alpha : num 0.001 477s ..$ undo : num 0 477s ..$ joinSegments : logi TRUE 477s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 477s .. ..$ chromosome: int 1 477s .. ..$ start : num 1.85e+08 477s .. ..$ end : num 2.47e+08 477s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 477s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 477s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.021 0 0.02 0 0 477s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 477s - attr(*, "pkgDetails")= chr "DNAcopy v1.76.0" 477s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 477s DH segmentation (locally-indexed) rows: 477s startRow endRow 477s 1 2 4388 477s int [1:4391] 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 477s DH segmentation rows: 477s startRow endRow 477s 1 10269 14655 477s Segmenting DH signals...done 477s DH segmentation table: 477s dhStart dhEnd dhNbrOfLoci dhMean 477s 1 185449813 247137334 1311 0.2512 477s startRow endRow 477s 1 10269 14655 477s Rows: 477s [1] 3 477s TCN segmentation rows: 477s startRow endRow 477s 3 10268 14658 477s TCN and DH segmentation rows: 477s startRow endRow 477s 3 10268 14658 477s startRow endRow 477s 1 10269 14655 477s startRow endRow 477s 1 1 7599 477s 2 7600 10267 477s TCN segmentation (expanded) rows: 477s startRow endRow 477s 1 1 7599 477s 2 7600 10267 477s 3 10268 14658 477s TCN and DH segmentation rows: 477s startRow endRow 477s 1 1 7599 477s 2 7600 10267 477s 3 10268 14658 477s startRow endRow 477s 1 10 7594 477s 2 7614 10263 477s 3 10269 14655 477s startRow endRow 477s 1 1 7599 477s 2 7600 10267 477s 3 10268 14658 477s Total CN segmentation table (expanded): 477s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 477s 3 1 185449813 247137334 4391 2.6341 1311 1311 477s (TCN,DH) segmentation for one total CN segment: 477s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 477s 3 3 1 1 185449813 247137334 4391 2.6341 1311 477s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 477s 3 1311 185449813 247137334 1311 0.2512 477s Total CN segment #3 ([1.8545e+08,2.47137e+08]) of 3...done 477s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 477s 1 1 1 1 554484 143926517 7599 1.3859 2111 477s 2 1 2 1 143926517 185449813 2668 2.0704 774 477s 3 1 3 1 185449813 247137334 4391 2.6341 1311 477s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 477s 1 2111 554484 143926517 2111 0.5237 477s 2 774 143926517 185449813 774 0.1542 477s 3 1311 185449813 247137334 1311 0.2512 477s Calculating (C1,C2) per segment... 477s Calculating (C1,C2) per segment...done 477s Number of segments: 3 477s Segmenting paired tumor-normal signals using Paired PSCBS...done 477s Post-segmenting TCNs... 477s Number of segments: 3 477s Number of chromosomes: 1 477s [1] 1 477s Chromosome 1 ('chr01') of 1... 477s Rows: 477s [1] 1 2 3 477s Number of segments: 3 477s TCN segment #1 ('1') of 3... 477s Nothing todo. Only one DH segmentation. Skipping. 477s TCN segment #1 ('1') of 3...done 477s TCN segment #2 ('2') of 3... 477s Nothing todo. Only one DH segmentation. Skipping. 477s TCN segment #2 ('2') of 3...done 477s TCN segment #3 ('3') of 3... 477s Nothing todo. Only one DH segmentation. Skipping. 477s TCN segment #3 ('3') of 3...done 477s Chromosome 1 ('chr01') of 1...done 477s Update (C1,C2) per segment... 477s Update (C1,C2) per segment...done 477s Post-segmenting TCNs...done 477s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 477s 1 1 1 1 554484 143926517 7599 1.3859 2111 477s 2 1 2 1 143926517 185449813 2668 2.0704 774 477s 3 1 3 1 185449813 247137334 4391 2.6341 1311 477s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 477s 1 2111 554484 143926517 2111 0.5237 0.3300521 1.055848 477s 2 774 143926517 185449813 774 0.1542 0.8755722 1.194828 477s 3 1311 185449813 247137334 1311 0.2512 0.9862070 1.647893 477s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 477s 1 1 1 1 554484 143926517 7599 1.3859 2111 477s 2 1 2 1 143926517 185449813 2668 2.0704 774 477s 3 1 3 1 185449813 247137334 4391 2.6341 1311 477s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 477s 1 2111 554484 143926517 2111 0.5237 0.3300521 1.055848 477s 2 774 143926517 185449813 774 0.1542 0.8755722 1.194828 477s 3 1311 185449813 247137334 1311 0.2512 0.9862070 1.647893 477s > print(fit) 477s chromosome tcnId dhId start end tcnNbrOfLoci tcnMean tcnNbrOfSNPs 477s 1 1 1 1 554484 143926517 7599 1.3859 2111 477s 2 1 2 1 143926517 185449813 2668 2.0704 774 477s 3 1 3 1 185449813 247137334 4391 2.6341 1311 477s tcnNbrOfHets dhNbrOfLoci dhMean c1Mean c2Mean 477s 1 2111 2111 0.5237 0.3300521 1.055848 477s 2 774 774 0.1542 0.8755722 1.194828 477s 3 1311 1311 0.2512 0.9862070 1.647893 477s > 477s > # Plot results 477s > plotTracks(fit) 477s > 477s > # Sanity check 477s > stopifnot(nbrOfSegments(fit) == nSegs) 477s > 477s > 477s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 477s > # Bootstrap segment level estimates 477s > # (used by the AB caller, which, if skipped here, 477s > # will do it automatically) 477s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 477s > fit <- bootstrapTCNandDHByRegion(fit, B=B, verbose=-10) 477s Resample (TCN,DH) signals and re-estimate summaries for segment & changepoint... 477s Already done? 477s tcn_2.5% tcn_5% tcn_95% tcn_97.5% dh_2.5% dh_5% dh_95% dh_97.5% 477s FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE 477s c1_2.5% c1_5% c1_95% c1_97.5% c2_2.5% c2_5% c2_95% c2_97.5% 477s FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE 477s Bootstrapping (TCN,DH,C1,C2) segment mean levels... 477s Identifying heterozygous & homozygous SNPs and non-polymorphic loci... 477s Number of loci: 14658 477s Number of SNPs: 4196 477s Number of non-SNPs: 10462 477s Identifying heterozygous & homozygous SNPs and non-polymorphic loci...done 477s num [1:3, 1:100, 1:4] NA NA NA NA NA NA NA NA NA NA ... 477s - attr(*, "dimnames")=List of 3 477s ..$ : NULL 477s ..$ : NULL 477s ..$ : chr [1:4] "tcn" "dh" "c1" "c2" 477s Segment #1 (chr 1, tcnId=1, dhId=1) of 3... 477s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 477s 1 1 1 1 554484 143926517 7599 1.3859 2111 477s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 477s 1 2111 554484 143926517 2111 0.5237 0.3300521 1.055848 477s Number of TCNs: 7599 477s Number of DHs: 2111 477s int [1:7599] 1 2 3 4 5 6 7 8 9 10 ... 477s int [1:14658] 1 2 3 4 5 6 7 8 9 10 ... 477s int [1:7599] 1 2 3 4 5 6 7 8 9 10 ... 477s Identify loci used to bootstrap DH means... 477s Heterozygous SNPs to resample for DH: 477s int [1:2111] 10 12 24 28 31 33 34 39 46 48 ... 477s Identify loci used to bootstrap DH means...done 477s Identify loci used to bootstrap TCN means... 477s SNPs: 477s int [1:2111] 10 12 24 28 31 33 34 39 46 48 ... 477s Non-polymorphic loci: 477s int [1:5488] 1 2 3 4 5 6 7 8 9 11 ... 477s Heterozygous SNPs to resample for TCN: 477s int [1:2111] 10 12 24 28 31 33 34 39 46 48 ... 477s Homozygous SNPs to resample for TCN: 477s int(0) 477s Non-polymorphic loci to resample for TCN: 477s int [1:5488] 1 2 3 4 5 6 7 8 9 11 ... 477s Heterozygous SNPs with non-DH to resample for TCN: 477s int(0) 477s Loci to resample for TCN: 477s int [1:7599] 1 2 3 4 5 6 7 8 9 10 ... 477s Identify loci used to bootstrap TCN means...done 477s Number of (#hets, #homs, #nonSNPs): (2111,0,5488) 477s Bootstrapping while preserving (#hets, #homs, #nonSNPs)... 477s Number of bootstrap samples: 100 477s Bootstrapping while preserving (#hets, #homs, #nonSNPs)...done 477s Segment #1 (chr 1, tcnId=1, dhId=1) of 3...done 477s Segment #2 (chr 1, tcnId=2, dhId=1) of 3... 477s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 477s 2 1 2 1 143926517 185449813 2668 2.0704 774 477s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 477s 2 774 143926517 185449813 774 0.1542 0.8755722 1.194828 477s Number of TCNs: 2668 477s Number of DHs: 774 477s int [1:2668] 7600 7601 7602 7603 7604 7605 7606 7607 7608 7609 ... 477s int [1:14658] 1 2 3 4 5 6 7 8 9 10 ... 477s int [1:2668] 7600 7601 7602 7603 7604 7605 7606 7607 7608 7609 ... 477s Identify loci used to bootstrap DH means... 477s Heterozygous SNPs to resample for DH: 477s int [1:774] 7614 7616 7626 7627 7628 7635 7638 7639 7640 7642 ... 477s Identify loci used to bootstrap DH means...done 477s Identify loci used to bootstrap TCN means... 477s SNPs: 477s int [1:774] 7614 7616 7626 7627 7628 7635 7638 7639 7640 7642 ... 477s Non-polymorphic loci: 477s int [1:1894] 7600 7601 7602 7603 7604 7605 7606 7607 7608 7609 ... 477s Heterozygous SNPs to resample for TCN: 477s int [1:774] 7614 7616 7626 7627 7628 7635 7638 7639 7640 7642 ... 477s Homozygous SNPs to resample for TCN: 477s int(0) 477s Non-polymorphic loci to resample for TCN: 477s int [1:1894] 7600 7601 7602 7603 7604 7605 7606 7607 7608 7609 ... 477s Heterozygous SNPs with non-DH to resample for TCN: 477s int(0) 477s Loci to resample for TCN: 477s int [1:2668] 7600 7601 7602 7603 7604 7605 7606 7607 7608 7609 ... 477s Identify loci used to bootstrap TCN means...done 477s Number of (#hets, #homs, #nonSNPs): (774,0,1894) 477s Bootstrapping while preserving (#hets, #homs, #nonSNPs)... 477s Number of bootstrap samples: 100 477s Bootstrapping while preserving (#hets, #homs, #nonSNPs)...done 477s Segment #2 (chr 1, tcnId=2, dhId=1) of 3...done 477s Segment #3 (chr 1, tcnId=3, dhId=1) of 3... 477s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 477s 3 1 3 1 185449813 247137334 4391 2.6341 1311 477s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 477s 3 1311 185449813 247137334 1311 0.2512 0.986207 1.647893 477s Number of TCNs: 4391 477s Number of DHs: 1311 477s int [1:4391] 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 477s int [1:14658] 1 2 3 4 5 6 7 8 9 10 ... 477s int [1:4391] 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 477s Identify loci used to bootstrap DH means... 477s Heterozygous SNPs to resample for DH: 477s int [1:1311] 10269 10271 10281 10282 10283 10293 10295 10297 10300 10302 ... 477s Identify loci used to bootstrap DH means...done 477s Identify loci used to bootstrap TCN means... 477s SNPs: 477s int [1:1311] 10269 10271 10281 10282 10283 10293 10295 10297 10300 10302 ... 477s Non-polymorphic loci: 477s int [1:3080] 10268 10270 10272 10273 10274 10275 10276 10277 10278 10279 ... 477s Heterozygous SNPs to resample for TCN: 477s int [1:1311] 10269 10271 10281 10282 10283 10293 10295 10297 10300 10302 ... 477s Homozygous SNPs to resample for TCN: 477s int(0) 477s Non-polymorphic loci to resample for TCN: 477s int [1:3080] 10268 10270 10272 10273 10274 10275 10276 10277 10278 10279 ... 477s Heterozygous SNPs with non-DH to resample for TCN: 477s int(0) 477s Loci to resample for TCN: 477s int [1:4391] 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 477s Identify loci used to bootstrap TCN means...done 477s Number of (#hets, #homs, #nonSNPs): (1311,0,3080) 477s Bootstrapping while preserving (#hets, #homs, #nonSNPs)... 477s Number of bootstrap samples: 100 477s Bootstrapping while preserving (#hets, #homs, #nonSNPs)...done 477s Segment #3 (chr 1, tcnId=3, dhId=1) of 3...done 477s Bootstrapped segment mean levels 477s num [1:3, 1:100, 1:4] 1.38 2.08 2.63 1.38 2.07 ... 477s - attr(*, "dimnames")=List of 3 477s ..$ : NULL 477s ..$ : NULL 477s ..$ : chr [1:4] "tcn" "dh" "c1" "c2" 477s Calculating (C1,C2) mean levels from (TCN,DH) mean levels... 477s num [1:3, 1:100, 1:4] 1.38 2.08 2.63 1.38 2.07 ... 477s - attr(*, "dimnames")=List of 3 477s ..$ : NULL 477s ..$ : NULL 477s ..$ : chr [1:4] "tcn" "dh" "c1" "c2" 477s Calculating (C1,C2) mean levels from (TCN,DH) mean levels...done 477s Calculating polar (alpha,radius,manhattan) for change points... 477s num [1:2, 1:100, 1:2] -0.5588 -0.0962 -0.5365 -0.1285 -0.5378 ... 477s - attr(*, "dimnames")=List of 3 477s ..$ : NULL 477s ..$ : NULL 477s ..$ : chr [1:2] "c1" "c2" 477s Bootstrapped change points 477s num [1:2, 1:100, 1:5] -2.89 -1.78 -2.87 -1.86 -2.88 ... 477s - attr(*, "dimnames")=List of 3 477s ..$ : NULL 477s ..$ : NULL 477s ..$ : chr [1:5] "alpha" "radius" "manhattan" "d1" ... 477s Calculating polar (alpha,radius,manhattan) for change points...done 477s Bootstrapping (TCN,DH,C1,C2) segment mean levels...done 477s Summarizing bootstrapped segment ('tcn', 'dh', 'c1', 'c2') data... 477s num [1:3, 1:4, 1:4] NA NA NA NA NA NA NA NA NA NA ... 477s - attr(*, "dimnames")=List of 3 477s ..$ : NULL 477s ..$ : chr [1:4] "2.5%" "5%" "95%" "97.5%" 477s ..$ : chr [1:4] "tcn" "dh" "c1" "c2" 477s Field #1 ('tcn') of 4... 477s Segment #1 of 3... 477s Segment #1 of 3...done 477s Segment #2 of 3... 477s Segment #2 of 3...done 477s Segment #3 of 3... 477s Segment #3 of 3...done 477s Field #1 ('tcn') of 4...done 477s Field #2 ('dh') of 4... 477s Segment #1 of 3... 477s Segment #1 of 3...done 477s Segment #2 of 3... 477s Segment #2 of 3...done 477s Segment #3 of 3... 477s Segment #3 of 3...done 477s Field #2 ('dh') of 4...done 477s Field #3 ('c1') of 4... 477s Segment #1 of 3... 477s Segment #1 of 3...done 477s Segment #2 of 3... 477s Segment #2 of 3...done 477s Segment #3 of 3... 477s Segment #3 of 3...done 477s Field #3 ('c1') of 4...done 477s Field #4 ('c2') of 4... 477s Segment #1 of 3... 477s Segment #1 of 3...done 477s Segment #2 of 3... 477s Segment #2 of 3...done 477s Segment #3 of 3... 477s Segment #3 of 3...done 477s Field #4 ('c2') of 4...done 477s Bootstrap statistics 477s num [1:3, 1:4, 1:4] 1.38 2.06 2.62 1.38 2.06 ... 477s - attr(*, "dimnames")=List of 3 477s ..$ : NULL 477s ..$ : chr [1:4] "2.5%" "5%" "95%" "97.5%" 477s ..$ : chr [1:4] "tcn" "dh" "c1" "c2" 477s Statistical sanity checks (iff B >= 100)... 477s Available summaries: 2.5%, 5%, 95%, 97.5% 477s Available quantiles: 0.025, 0.05, 0.95, 0.975 477s num [1:3, 1:4, 1:4] 1.38 2.06 2.62 1.38 2.06 ... 477s - attr(*, "dimnames")=List of 3 477s ..$ : NULL 477s ..$ : chr [1:4] "2.5%" "5%" "95%" "97.5%" 477s ..$ : chr [1:4] "tcn" "dh" "c1" "c2" 477s Field #1 ('tcn') of 4... 477s Seg 1. mean=1.3859, range=[1.38092,1.3949], n=7599 477s Seg 2. mean=2.0704, range=[2.05747,2.08326], n=2668 477s Seg 3. mean=2.6341, range=[2.62068,2.64694], n=4391 477s Field #1 ('tcn') of 4...done 477s Field #2 ('dh') of 4... 477s Seg 1. mean=0.5237, range=[0.51753,0.532002], n=2111 477s Seg 2. mean=0.1542, range=[0.144468,0.16453], n=774 477s Seg 3. mean=0.2512, range=[0.242575,0.258832], n=1311 477s Field #2 ('dh') of 4...done 477s Field #3 ('c1') of 4... 477s Seg 1. mean=0.330052, range=[0.323996,0.336038], n=2111 477s Seg 2. mean=0.875572, range=[0.86318,0.887699], n=774 477s Seg 3. mean=0.986207, range=[0.975123,0.998982], n=1311 477s Field #3 ('c1') of 4...done 477s Field #4 ('c2') of 4... 477s Seg 1. mean=1.05585, range=[1.05006,1.06231], n=2111 477s Seg 2. mean=1.19483, range=[1.18417,1.2081], n=774 477s Seg 3. mean=1.64789, range=[1.63403,1.66098], n=1311 477s Field #4 ('c2') of 4...done 477s Statistical sanity checks (iff B >= 100)...done 477s Summarizing bootstrapped segment ('tcn', 'dh', 'c1', 'c2') data...done 477s Summarizing bootstrapped changepoint ('alpha', 'radius', 'manhattan', 'd1', 'd2') data... 477s num [1:2, 1:4, 1:5] NA NA NA NA NA NA NA NA NA NA ... 477s - attr(*, "dimnames")=List of 3 477s ..$ : NULL 477s ..$ : chr [1:4] "2.5%" "5%" "95%" "97.5%" 477s ..$ : chr [1:5] "alpha" "radius" "manhattan" "d1" ... 477s Field #1 ('alpha') of 5... 477s Changepoint #1 of 2... 477s Changepoint #1 of 2...done 477s Changepoint #2 of 2... 477s Changepoint #2 of 2...done 477s Field #1 ('alpha') of 5...done 477s Field #2 ('radius') of 5... 477s Changepoint #1 of 2... 477s Changepoint #1 of 2...done 477s Changepoint #2 of 2... 477s Changepoint #2 of 2...done 477s Field #2 ('radius') of 5...done 477s Field #3 ('manhattan') of 5... 477s Changepoint #1 of 2... 477s Changepoint #1 of 2...done 477s Changepoint #2 of 2... 477s Changepoint #2 of 2...done 477s Field #3 ('manhattan') of 5...done 477s Field #4 ('d1') of 5... 477s Changepoint #1 of 2... 477s Changepoint #1 of 2...done 477s Changepoint #2 of 2... 477s Changepoint #2 of 2...done 477s Field #4 ('d1') of 5...done 477s Field #5 ('d2') of 5... 477s Changepoint #1 of 2... 477s Changepoint #1 of 2...done 477s Changepoint #2 of 2... 477s Changepoint #2 of 2...done 477s Field #5 ('d2') of 5...done 477s Bootstrap statistics 477s num [1:2, 1:4, 1:5] -2.92 -1.86 -2.91 -1.85 -2.87 ... 477s - attr(*, "dimnames")=List of 3 477s ..$ : NULL 477s ..$ : chr [1:4] "2.5%" "5%" "95%" "97.5%" 477s ..$ : chr [1:5] "alpha" "radius" "manhattan" "d1" ... 477s Summarizing bootstrapped changepoint ('alpha', 'radius', 'manhattan', 'd1', 'd2') data...done 477s Resample (TCN,DH) signals and re-estimate summaries for segment & changepoint...done 477s > print(fit) 477s chromosome tcnId dhId start end tcnNbrOfLoci tcnMean tcnNbrOfSNPs 477s 1 1 1 1 554484 143926517 7599 1.3859 2111 477s 2 1 2 1 143926517 185449813 2668 2.0704 774 477s 3 1 3 1 185449813 247137334 4391 2.6341 1311 477s tcnNbrOfHets dhNbrOfLoci dhMean c1Mean c2Mean 477s 1 2111 2111 0.5237 0.3300521 1.055848 477s 2 774 774 0.1542 0.8755722 1.194828 477s 3 1311 1311 0.2512 0.9862070 1.647893 477s > plotTracks(fit) 477s > 477s > 477s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 477s > # Calling segments in allelic balance (AB) and 477s > # in loss-of-heterozygosity (LOH) 477s > # NOTE: Ideally, this should be done on whole-genome data 477s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 477s > fit <- callAB(fit, verbose=-10) 477s Calling segments of allelic balance from one-sided DH bootstrap confidence intervals... 477s delta (offset adjusting for bias in DH): 0.3466649145302 477s alpha (CI quantile; significance level): 0.05 477s Calling segments... 477s Number of segments called allelic balance (AB): 2 (66.67%) of 3 477s Calling segments...done 477s Calling segments of allelic balance from one-sided DH bootstrap confidence intervals...done 477s > fit <- callLOH(fit, verbose=-10) 477s Calling segments of allelic balance from one-sided DH bootstrap confidence intervals... 477s delta (offset adjusting for bias in C1): 0.771236438183453 477s alpha (CI quantile; significance level): 0.05 477s Calling segments... 477s Number of segments called low C1 (LowC1, "LOH_C1"): 1 (33.33%) of 3 477s Calling segments...done 477s Calling segments of allelic balance from one-sided DH bootstrap confidence intervals...done 477s > print(fit) 477s chromosome tcnId dhId start end tcnNbrOfLoci tcnMean tcnNbrOfSNPs 477s 1 1 1 1 554484 143926517 7599 1.3859 2111 477s 2 1 2 1 143926517 185449813 2668 2.0704 774 477s 3 1 3 1 185449813 247137334 4391 2.6341 1311 477s tcnNbrOfHets dhNbrOfLoci dhMean c1Mean c2Mean abCall lohCall 477s 1 2111 2111 0.5237 0.3300521 1.055848 FALSE TRUE 477s 2 774 774 0.1542 0.8755722 1.194828 TRUE FALSE 477s 3 1311 1311 0.2512 0.9862070 1.647893 TRUE FALSE 477s > plotTracks(fit) 477s > 477s > proc.time() 477s user system elapsed 477s 1.969 0.131 2.092 477s Test segmentByPairedPSCBS,noNormalBAFs passed 477s 0 477s Begin test segmentByPairedPSCBS,report 478s + cat segmentByPairedPSCBS,report.Rout 478s 478s R version 4.3.2 (2023-10-31) -- "Eye Holes" 478s Copyright (C) 2023 The R Foundation for Statistical Computing 478s Platform: x86_64-pc-linux-gnu (64-bit) 478s 478s R is free software and comes with ABSOLUTELY NO WARRANTY. 478s You are welcome to redistribute it under certain conditions. 478s Type 'license()' or 'licence()' for distribution details. 478s 478s R is a collaborative project with many contributors. 478s Type 'contributors()' for more information and 478s 'citation()' on how to cite R or R packages in publications. 478s 478s Type 'demo()' for some demos, 'help()' for on-line help, or 478s 'help.start()' for an HTML browser interface to help. 478s Type 'q()' to quit R. 478s 478s [Previously saved workspace restored] 478s 478s > # This test script calls a report generator which requires 478s > # the 'ggplot2' package, which in turn will require packages 478s > # 'colorspace', 'dichromat', 'munsell', 'reshape2' and 'scales'. 478s > 478s > # Only run this test in full testing mode 478s > if (Sys.getenv("_R_CHECK_FULL_") != "") { 478s + library("PSCBS") 478s + 478s + # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 478s + # Load SNP microarray data 478s + # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 478s + data <- PSCBS::exampleData("paired.chr01") 478s + str(data) 478s + 478s + 478s + # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 478s + # Paired PSCBS segmentation 478s + # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 478s + # Drop single-locus outliers 478s + dataS <- dropSegmentationOutliers(data) 478s + 478s + # Speed up example by segmenting fewer loci 478s + dataS <- dataS[seq(from=1, to=nrow(data), by=5),] 478s + 478s + str(dataS) 478s + 478s + gaps <- findLargeGaps(dataS, minLength=2e6) 478s + knownSegments <- gapsToSegments(gaps) 478s + 478s + # Paired PSCBS segmentation 478s + fit <- segmentByPairedPSCBS(dataS, knownSegments=knownSegments, 478s + seed=0xBEEF, verbose=-10) 478s + 478s + # Fake a multi-chromosome segmentation 478s + fit1 <- fit 478s + fit2 <- renameChromosomes(fit, from=1, to=2) 478s + fit <- c(fit1, fit2) 478s + 478s + report(fit, sampleName="PairedPSCBS", studyName="PSCBS-Ex", verbose=-10) 478s + 478s + } # if (Sys.getenv("_R_CHECK_FULL_")) 478s > 478s > proc.time() 478s user system elapsed 478s 0.315 0.029 0.333 478s Test segmentByPairedPSCBS,report passed 478s 0 478s Begin test segmentByPairedPSCBS,seqOfSegmentsByDP 478s + [ 0 != 0 ] 478s + echo Test segmentByPairedPSCBS,report passed 478s + echo 0 478s + echo Begin test segmentByPairedPSCBS,seqOfSegmentsByDP 478s + exitcode=0 478s + R CMD BATCH segmentByPairedPSCBS,seqOfSegmentsByDP.R 483s + cat segmentByPairedPSCBS,seqOfSegmentsByDP.Rout 483s 483s R version 4.3.2 (2023-10-31) -- "Eye Holes" 483s Copyright (C) 2023 The R Foundation for Statistical Computing 483s Platform: x86_64-pc-linux-gnu (64-bit) 483s 483s R is free software and comes with ABSOLUTELY NO WARRANTY. 483s You are welcome to redistribute it under certain conditions. 483s Type 'license()' or 'licence()' for distribution details. 483s 483s R is a collaborative project with many contributors. 483s Type 'contributors()' for more information and 483s 'citation()' on how to cite R or R packages in publications. 483s 483s Type 'demo()' for some demos, 'help()' for on-line help, or 483s 'help.start()' for an HTML browser interface to help. 483s Type 'q()' to quit R. 483s 483s [Previously saved workspace restored] 483s 483s > library("PSCBS") 483s PSCBS v0.66.0 (2021-10-23 07:40:02 UTC) successfully loaded. See ?PSCBS for help. 483s 483s Attaching package: 'PSCBS' 483s 483s The following objects are masked from 'package:base': 483s 483s append, load 483s 483s > subplots <- R.utils::subplots 483s > stext <- R.utils::stext 483s > 483s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 483s > # Load SNP microarray data 483s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 483s > data <- PSCBS::exampleData("paired.chr01") 483s > str(data) 483s 'data.frame': 73346 obs. of 6 variables: 483s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 483s $ x : int 1145994 2224111 2319424 2543484 2926730 2941694 3084986 3155127 3292731 3695086 ... 483s $ CT : num 1.625 1.071 1.406 1.18 0.856 ... 483s $ betaT : num 0.757 0.771 0.834 0.778 0.229 ... 483s $ CN : num 2.36 2.13 2.59 1.93 1.71 ... 483s $ betaN : num 0.827 0.875 0.887 0.884 0.103 ... 483s > 483s > 483s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 483s > # Paired PSCBS segmentation 483s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 483s > # Drop single-locus outliers 483s > dataS <- dropSegmentationOutliers(data) 483s > 483s > # Run light-weight tests by default 483s > if (Sys.getenv("_R_CHECK_FULL_") == "") { 483s + # Use only every 5th data point 483s + dataS <- dataS[seq(from=1, to=nrow(data), by=5),] 483s + # Number of segments (for assertion) 483s + nSegs <- 3L 483s + # Number of bootstrap samples (see below) 483s + B <- 100L 483s + } else { 483s + # Full tests 483s + nSegs <- 12L 483s + B <- 1000L 483s + } 483s > 483s > str(dataS) 483s 'data.frame': 14670 obs. of 6 variables: 483s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 483s $ x : int 1145994 2941694 3710825 4240737 4276892 4464544 4714611 5095111 5034491 5158416 ... 483s $ CT : num 1.63 1.4 1.41 1.17 1.16 ... 483s $ betaT : num 0.7574 0.169 0.2357 0.2604 0.0576 ... 483s $ CN : num 2.36 2.13 2.26 2.01 2.32 ... 483s $ betaN : num 0.8274 0.5072 0.1671 0.1609 0.0421 ... 483s > 483s > R.oo::attachLocally(dataS) 483s > 483s > 483s > gaps <- findLargeGaps(dataS, minLength=2e6) 483s > knownSegments <- gapsToSegments(gaps, dropGaps=TRUE) 483s > 483s > # Paired PSCBS segmentation 483s > fit <- segmentByPairedPSCBS(dataS, knownSegments=knownSegments, 483s + seed=0xBEEF, verbose=-10) 483s Segmenting paired tumor-normal signals using Paired PSCBS... 483s Calling genotypes from normal allele B fractions... 483s num [1:14670] 0.8274 0.5072 0.1671 0.1609 0.0421 ... 483s Called genotypes: 483s num [1:14670] 1 0.5 0 0 0 0 1 0 1 0.5 ... 483s - attr(*, "modelFit")=List of 1 483s ..$ :List of 7 483s .. ..$ flavor : chr "density" 483s .. ..$ cn : int 2 483s .. ..$ nbrOfGenotypeGroups: int 3 483s .. ..$ tau : num [1:2] 0.315 0.677 483s .. ..$ n : int 14640 483s .. ..$ fit :Classes 'PeaksAndValleys' and 'data.frame': 5 obs. of 3 variables: 483s .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 483s .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 483s .. .. ..$ density: num [1:5] 1.48 0.522 1.056 0.552 1.454 483s .. ..$ fitValleys :Classes 'PeaksAndValleys' and 'data.frame': 2 obs. of 3 variables: 483s .. .. ..$ type : chr [1:2] "valley" "valley" 483s .. .. ..$ x : num [1:2] 0.315 0.677 483s .. .. ..$ density: num [1:2] 0.522 0.552 483s ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 483s muN 483s 0 0.5 1 483s 5221 4198 5251 483s Calling genotypes from normal allele B fractions...done 483s Normalizing betaT using betaN (TumorBoost)... 483s Normalized BAFs: 483s num [1:14670] 0.9301 0.1667 0.0685 0.0995 0.0155 ... 483s - attr(*, "modelFit")=List of 5 483s ..$ method : chr "normalizeTumorBoost" 483s ..$ flavor : chr "v4" 483s ..$ delta : num [1:14670] -0.17264 0.00239 0.1671 0.16085 0.04213 ... 483s .. ..- attr(*, "modelFit")=List of 1 483s .. .. ..$ :List of 7 483s .. .. .. ..$ flavor : chr "density" 483s .. .. .. ..$ cn : int 2 483s .. .. .. ..$ nbrOfGenotypeGroups: int 3 483s .. .. .. ..$ tau : num [1:2] 0.315 0.677 483s .. .. .. ..$ n : int 14640 483s .. .. .. ..$ fit :Classes 'PeaksAndValleys' and 'data.frame': 5 obs. of 3 variables: 483s .. .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 483s .. .. .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 483s .. .. .. .. ..$ density: num [1:5] 1.48 0.522 1.056 0.552 1.454 483s .. .. .. ..$ fitValleys :Classes 'PeaksAndValleys' and 'data.frame': 2 obs. of 3 variables: 483s .. .. .. .. ..$ type : chr [1:2] "valley" "valley" 483s .. .. .. .. ..$ x : num [1:2] 0.315 0.677 483s .. .. .. .. ..$ density: num [1:2] 0.522 0.552 483s .. .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 483s ..$ preserveScale: logi FALSE 483s ..$ scaleFactor : num NA 483s Normalizing betaT using betaN (TumorBoost)...done 483s Setup up data... 483s 'data.frame': 14670 obs. of 7 variables: 483s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 483s $ x : num 1145994 2941694 3710825 4240737 4276892 ... 483s $ CT : num 1.63 1.4 1.41 1.17 1.16 ... 483s $ betaT : num 0.7574 0.169 0.2357 0.2604 0.0576 ... 483s $ betaTN : num 0.9301 0.1667 0.0685 0.0995 0.0155 ... 483s ..- attr(*, "modelFit")=List of 5 483s .. ..$ method : chr "normalizeTumorBoost" 483s .. ..$ flavor : chr "v4" 483s .. ..$ delta : num [1:14670] -0.17264 0.00239 0.1671 0.16085 0.04213 ... 483s .. .. ..- attr(*, "modelFit")=List of 1 483s .. .. .. ..$ :List of 7 483s .. .. .. .. ..$ flavor : chr "density" 483s .. .. .. .. ..$ cn : int 2 483s .. .. .. .. ..$ nbrOfGenotypeGroups: int 3 483s .. .. .. .. ..$ tau : num [1:2] 0.315 0.677 483s .. .. .. .. ..$ n : int 14640 483s .. .. .. .. ..$ fit :Classes 'PeaksAndValleys' and 'data.frame': 5 obs. of 3 variables: 483s .. .. .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 483s .. .. .. .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 483s .. .. .. .. .. ..$ density: num [1:5] 1.48 0.522 1.056 0.552 1.454 483s .. .. .. .. ..$ fitValleys :Classes 'PeaksAndValleys' and 'data.frame': 2 obs. of 3 variables: 483s .. .. .. .. .. ..$ type : chr [1:2] "valley" "valley" 483s .. .. .. .. .. ..$ x : num [1:2] 0.315 0.677 483s .. .. .. .. .. ..$ density: num [1:2] 0.522 0.552 483s .. .. .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 483s .. ..$ preserveScale: logi FALSE 483s .. ..$ scaleFactor : num NA 483s $ betaN : num 0.8274 0.5072 0.1671 0.1609 0.0421 ... 483s $ muN : num 1 0.5 0 0 0 0 1 0 1 0.5 ... 483s ..- attr(*, "modelFit")=List of 1 483s .. ..$ :List of 7 483s .. .. ..$ flavor : chr "density" 483s .. .. ..$ cn : int 2 483s .. .. ..$ nbrOfGenotypeGroups: int 3 483s .. .. ..$ tau : num [1:2] 0.315 0.677 483s .. .. ..$ n : int 14640 483s .. .. ..$ fit :Classes 'PeaksAndValleys' and 'data.frame': 5 obs. of 3 variables: 483s .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 483s .. .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 483s .. .. .. ..$ density: num [1:5] 1.48 0.522 1.056 0.552 1.454 483s .. .. ..$ fitValleys :Classes 'PeaksAndValleys' and 'data.frame': 2 obs. of 3 variables: 483s .. .. .. ..$ type : chr [1:2] "valley" "valley" 483s .. .. .. ..$ x : num [1:2] 0.315 0.677 483s .. .. .. ..$ density: num [1:2] 0.522 0.552 483s .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 483s Setup up data...done 483s Dropping loci for which TCNs are missing... 483s Number of loci dropped: 12 483s Dropping loci for which TCNs are missing...done 483s Ordering data along genome... 483s 'data.frame': 14658 obs. of 7 variables: 483s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 483s $ x : num 554484 730720 782343 878522 916294 ... 483s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 483s $ betaT : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 483s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 483s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 483s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 483s Ordering data along genome...done 483s Keeping only current chromosome for 'knownSegments'... 483s Chromosome: 1 483s Known segments for this chromosome: 483s chromosome start end length 483s 1 1 -Inf 120908858 Inf 483s 2 1 142693888 Inf Inf 483s Keeping only current chromosome for 'knownSegments'...done 483s alphaTCN: 0.009 483s alphaDH: 0.001 483s Number of loci: 14658 483s Calculating DHs... 483s Number of SNPs: 14658 483s Number of heterozygous SNPs: 4196 (28.63%) 483s Normalized DHs: 483s num [1:14658] NA NA NA NA NA ... 483s Calculating DHs...done 483s Random seed temporarily set (seed=c(48879), kind="L'Ecuyer-CMRG") 483s Produced 2 seeds from this stream for future usage 483s Identification of change points by total copy numbers... 483s Segmenting by CBS... 483s Chromosome: 1 483s Segmenting multiple segments on current chromosome... 483s Number of segments: 2 483s Random seed temporarily set (seed=c(10407, 1066287653, -51199871, 161854402, -1995183193, 1503453565, -747102133), kind="L'Ecuyer-CMRG") 483s Produced 2 seeds from this stream for future usage 483s Segmenting by CBS... 483s Chromosome: 1 483s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 483s Segmenting by CBS...done 483s Segmenting by CBS... 483s Chromosome: 1 483s Random seed temporarily set (seed=c(10407, -821273412, -52578226, 1415511586, 721384351, -665928286, 1316562960), kind="L'Ecuyer-CMRG") 483s Segmenting by CBS...done 483s Segmenting multiple segments on current chromosome...done 483s Segmenting by CBS...done 483s List of 4 483s $ data :'data.frame': 14658 obs. of 4 variables: 483s ..$ chromosome: int [1:14658] 1 1 1 1 1 1 1 1 1 1 ... 483s ..$ x : num [1:14658] 554484 730720 782343 878522 916294 ... 483s ..$ y : num [1:14658] 1.88 1.8 1.59 1.64 1.53 ... 483s ..$ index : int [1:14658] 1 2 3 4 5 6 7 8 9 10 ... 483s $ output :'data.frame': 3 obs. of 6 variables: 483s ..$ sampleName: chr [1:3] NA NA NA 483s ..$ chromosome: int [1:3] 1 1 1 483s ..$ start : num [1:3] 5.54e+05 1.43e+08 1.85e+08 483s ..$ end : num [1:3] 1.21e+08 1.85e+08 2.47e+08 483s ..$ nbrOfLoci : int [1:3] 7586 2681 4391 483s ..$ mean : num [1:3] 1.39 2.07 2.63 483s $ segRows:'data.frame': 3 obs. of 2 variables: 483s ..$ startRow: int [1:3] 1 7587 10268 483s ..$ endRow : int [1:3] 7586 10267 14658 483s $ params :List of 5 483s ..$ alpha : num 0.009 483s ..$ undo : num 0 483s ..$ joinSegments : logi TRUE 483s ..$ knownSegments:'data.frame': 2 obs. of 3 variables: 483s .. ..$ chromosome: int [1:2] 1 1 483s .. ..$ start : num [1:2] -Inf 1.43e+08 483s .. ..$ end : num [1:2] 1.21e+08 Inf 483s ..$ seed : int [1:7] 10407 1066287653 -51199871 161854402 -1995183193 1503453565 -747102133 483s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 483s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.132 0 0.133 0 0 483s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 483s - attr(*, "pkgDetails")= chr "DNAcopy v1.76.0" 483s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 483s Identification of change points by total copy numbers...done 483s Restructure TCN segmentation results... 483s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean 483s 1 1 554484 120908858 7586 1.3853 483s 2 1 142693888 185449813 2681 2.0689 483s 3 1 185449813 247137334 4391 2.6341 483s Number of TCN segments: 3 483s Restructure TCN segmentation results...done 483s Total CN segment #1 ([ 554484,1.20909e+08]) of 3... 483s Number of TCN loci in segment: 7586 483s Locus data for TCN segment: 483s 'data.frame': 7586 obs. of 9 variables: 483s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 483s $ x : num 554484 730720 782343 878522 916294 ... 483s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 483s $ betaT : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 483s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 483s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 483s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 483s $ index : int 1 2 3 4 5 6 7 8 9 10 ... 483s $ rho : num NA NA NA NA NA ... 483s Number of loci: 7586 483s Number of SNPs: 2108 (27.79%) 483s Number of heterozygous SNPs: 2108 (100.00%) 483s Chromosome: 1 483s Segmenting DH signals... 483s Segmenting by CBS... 483s Chromosome: 1 483s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 483s Segmenting by CBS...done 483s List of 4 483s $ data :'data.frame': 7586 obs. of 4 variables: 483s ..$ chromosome: int [1:7586] 1 1 1 1 1 1 1 1 1 1 ... 483s ..$ x : num [1:7586] 554484 730720 782343 878522 916294 ... 483s ..$ y : num [1:7586] NA NA NA NA NA ... 483s ..$ index : int [1:7586] 1 2 3 4 5 6 7 8 9 10 ... 483s $ output :'data.frame': 1 obs. of 6 variables: 483s ..$ sampleName: chr NA 483s ..$ chromosome: int 1 483s ..$ start : num 554484 483s ..$ end : num 1.21e+08 483s ..$ nbrOfLoci : int 2108 483s ..$ mean : num 0.512 483s $ segRows:'data.frame': 1 obs. of 2 variables: 483s ..$ startRow: int 10 483s ..$ endRow : int 7574 483s $ params :List of 5 483s ..$ alpha : num 0.001 483s ..$ undo : num 0 483s ..$ joinSegments : logi TRUE 483s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 483s .. ..$ chromosome: int 1 483s .. ..$ start : num 554484 483s .. ..$ end : num 1.21e+08 483s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 483s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 483s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.034 0 0.035 0 0 483s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 483s - attr(*, "pkgDetails")= chr "DNAcopy v1.76.0" 483s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 483s DH segmentation (locally-indexed) rows: 483s startRow endRow 483s 1 10 7574 483s int [1:7586] 1 2 3 4 5 6 7 8 9 10 ... 483s DH segmentation rows: 483s startRow endRow 483s 1 10 7574 483s Segmenting DH signals...done 483s DH segmentation table: 483s dhStart dhEnd dhNbrOfLoci dhMean 483s 1 554484 120908858 2108 0.5116 483s startRow endRow 483s 1 10 7574 483s Rows: 483s [1] 1 483s TCN segmentation rows: 483s startRow endRow 483s 1 1 7586 483s TCN and DH segmentation rows: 483s startRow endRow 483s 1 1 7586 483s startRow endRow 483s 1 10 7574 483s NULL 483s TCN segmentation (expanded) rows: 483s startRow endRow 483s 1 1 7586 483s TCN and DH segmentation rows: 483s startRow endRow 483s 1 1 7586 483s 2 7587 10267 483s 3 10268 14658 483s startRow endRow 483s 1 10 7574 483s startRow endRow 483s 1 1 7586 483s Total CN segmentation table (expanded): 483s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 483s 1 1 554484 120908858 7586 1.3853 2108 2108 483s (TCN,DH) segmentation for one total CN segment: 483s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 483s 1 1 1 1 554484 120908858 7586 1.3853 2108 483s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 483s 1 2108 554484 120908858 2108 0.5116 483s Total CN segment #1 ([ 554484,1.20909e+08]) of 3...done 483s Total CN segment #2 ([1.42694e+08,1.8545e+08]) of 3... 483s Number of TCN loci in segment: 2681 483s Locus data for TCN segment: 483s 'data.frame': 2681 obs. of 9 variables: 483s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 483s $ x : num 1.43e+08 1.43e+08 1.43e+08 1.43e+08 1.44e+08 ... 483s $ CT : num 2.27 1.55 1.47 1.5 1.81 ... 483s $ betaT : num 0.34 0.55 0.048 0.813 0.575 ... 483s $ betaTN : num 0.441 0.629 -0.05 0.958 0.872 ... 483s $ betaN : num 0.3851 0.3933 0.0981 0.8552 0.7028 ... 483s $ muN : num 0.5 0.5 0 1 1 1 1 0.5 1 1 ... 483s $ index : int 7587 7588 7589 7590 7591 7592 7593 7594 7595 7596 ... 483s $ rho : num 0.117 0.258 NA NA NA ... 483s Number of loci: 2681 483s Number of SNPs: 777 (28.98%) 483s Number of heterozygous SNPs: 777 (100.00%) 483s Chromosome: 1 483s Segmenting DH signals... 483s Segmenting by CBS... 483s Chromosome: 1 483s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 483s Segmenting by CBS...done 483s List of 4 483s $ data :'data.frame': 2681 obs. of 4 variables: 483s ..$ chromosome: int [1:2681] 1 1 1 1 1 1 1 1 1 1 ... 483s ..$ x : num [1:2681] 1.43e+08 1.43e+08 1.43e+08 1.43e+08 1.44e+08 ... 483s ..$ y : num [1:2681] 0.117 0.258 NA NA NA ... 483s ..$ index : int [1:2681] 1 2 3 4 5 6 7 8 9 10 ... 483s $ output :'data.frame': 1 obs. of 6 variables: 483s ..$ sampleName: chr NA 483s ..$ chromosome: int 1 483s ..$ start : num 1.43e+08 483s ..$ end : num 1.85e+08 483s ..$ nbrOfLoci : int 777 483s ..$ mean : num 0.0973 483s $ segRows:'data.frame': 1 obs. of 2 variables: 483s ..$ startRow: int 1 483s ..$ endRow : int 2677 483s $ params :List of 5 483s ..$ alpha : num 0.001 483s ..$ undo : num 0 483s ..$ joinSegments : logi TRUE 483s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 483s .. ..$ chromosome: int 1 483s .. ..$ start : num 1.43e+08 483s .. ..$ end : num 1.85e+08 483s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 483s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 483s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.008 0 0.007 0 0 483s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 483s - attr(*, "pkgDetails")= chr "DNAcopy v1.76.0" 483s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 483s DH segmentation (locally-indexed) rows: 483s startRow endRow 483s 1 1 2677 483s int [1:2681] 7587 7588 7589 7590 7591 7592 7593 7594 7595 7596 ... 483s DH segmentation rows: 483s startRow endRow 483s 1 7587 10263 483s Segmenting DH signals...done 483s DH segmentation table: 483s dhStart dhEnd dhNbrOfLoci dhMean 483s 1 142693888 185449813 777 0.0973 483s startRow endRow 483s 1 7587 10263 483s Rows: 483s [1] 2 483s TCN segmentation rows: 483s startRow endRow 483s 2 7587 10267 483s TCN and DH segmentation rows: 483s startRow endRow 483s 2 7587 10267 483s startRow endRow 483s 1 7587 10263 483s startRow endRow 483s 1 1 7586 483s TCN segmentation (expanded) rows: 483s startRow endRow 483s 1 1 7586 483s 2 7587 10267 483s TCN and DH segmentation rows: 483s startRow endRow 483s 1 1 7586 483s 2 7587 10267 483s 3 10268 14658 483s startRow endRow 483s 1 10 7574 483s 2 7587 10263 483s startRow endRow 483s 1 1 7586 483s 2 7587 10267 483s Total CN segmentation table (expanded): 483s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 483s 2 1 142693888 185449813 2681 2.0689 777 777 483s (TCN,DH) segmentation for one total CN segment: 483s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 483s 2 2 1 1 142693888 185449813 2681 2.0689 777 483s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 483s 2 777 142693888 185449813 777 0.0973 483s Total CN segment #2 ([1.42694e+08,1.8545e+08]) of 3...done 483s Total CN segment #3 ([1.8545e+08,2.47137e+08]) of 3... 483s Number of TCN loci in segment: 4391 483s Locus data for TCN segment: 483s 'data.frame': 4391 obs. of 9 variables: 483s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 483s $ x : num 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 483s $ CT : num 2.93 2.15 2.82 2.93 2.46 ... 483s $ betaT : num 0.0811 0.5154 0.9473 0.3734 0.7506 ... 483s $ betaTN : num -0.169 0.609 1.028 0.525 0.968 ... 483s $ betaN : num 0.25 0.38 0.919 0.34 0.783 ... 483s $ muN : num 0 0.5 1 0.5 1 1 0 1 0 1 ... 483s $ index : int 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 483s $ rho : num NA 0.2186 NA 0.0503 NA ... 483s Number of loci: 4391 483s Number of SNPs: 1311 (29.86%) 483s Number of heterozygous SNPs: 1311 (100.00%) 483s Chromosome: 1 483s Segmenting DH signals... 483s Segmenting by CBS... 483s Chromosome: 1 483s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 483s Segmenting by CBS...done 483s List of 4 483s $ data :'data.frame': 4391 obs. of 4 variables: 483s ..$ chromosome: int [1:4391] 1 1 1 1 1 1 1 1 1 1 ... 483s ..$ x : num [1:4391] 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 483s ..$ y : num [1:4391] NA 0.2186 NA 0.0503 NA ... 483s ..$ index : int [1:4391] 1 2 3 4 5 6 7 8 9 10 ... 483s $ output :'data.frame': 1 obs. of 6 variables: 483s ..$ sampleName: chr NA 483s ..$ chromosome: int 1 483s ..$ start : num 1.85e+08 483s ..$ end : num 2.47e+08 483s ..$ nbrOfLoci : int 1311 483s ..$ mean : num 0.23 483s $ segRows:'data.frame': 1 obs. of 2 variables: 483s ..$ startRow: int 2 483s ..$ endRow : int 4388 483s $ params :List of 5 483s ..$ alpha : num 0.001 483s ..$ undo : num 0 483s ..$ joinSegments : logi TRUE 483s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 483s .. ..$ chromosome: int 1 483s .. ..$ start : num 1.85e+08 483s .. ..$ end : num 2.47e+08 483s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 483s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 483s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.014 0 0.014 0 0 483s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 483s - attr(*, "pkgDetails")= chr "DNAcopy v1.76.0" 483s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 483s DH segmentation (locally-indexed) rows: 483s startRow endRow 483s 1 2 4388 483s int [1:4391] 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 483s DH segmentation rows: 483s startRow endRow 483s 1 10269 14655 483s Segmenting DH signals...done 483s DH segmentation table: 483s dhStart dhEnd dhNbrOfLoci dhMean 483s 1 185449813 247137334 1311 0.2295 483s startRow endRow 483s 1 10269 14655 483s Rows: 483s [1] 3 483s TCN segmentation rows: 483s startRow endRow 483s 3 10268 14658 483s TCN and DH segmentation rows: 483s startRow endRow 483s 3 10268 14658 483s startRow endRow 483s 1 10269 14655 483s startRow endRow 483s 1 1 7586 483s 2 7587 10267 483s TCN segmentation (expanded) rows: 483s startRow endRow 483s 1 1 7586 483s 2 7587 10267 483s 3 10268 14658 483s TCN and DH segmentation rows: 483s startRow endRow 483s 1 1 7586 483s 2 7587 10267 483s 3 10268 14658 483s startRow endRow 483s 1 10 7574 483s 2 7587 10263 483s 3 10269 14655 483s startRow endRow 483s 1 1 7586 483s 2 7587 10267 483s 3 10268 14658 483s Total CN segmentation table (expanded): 483s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 483s 3 1 185449813 247137334 4391 2.6341 1311 1311 483s (TCN,DH) segmentation for one total CN segment: 483s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 483s 3 3 1 1 185449813 247137334 4391 2.6341 1311 483s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 483s 3 1311 185449813 247137334 1311 0.2295 483s Total CN segment #3 ([1.8545e+08,2.47137e+08]) of 3...done 483s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 483s 1 1 1 1 554484 120908858 7586 1.3853 2108 483s 2 1 2 1 142693888 185449813 2681 2.0689 777 483s 3 1 3 1 185449813 247137334 4391 2.6341 + [ 0 != 0 ] 483s + echo Test segmentByPairedPSCBS,seqOfSegmentsByDP passed 483s + echo 0 483s + echo Begin test segmentByPairedPSCBS 483s + exitcode=0 483s + R CMD BATCH segmentByPairedPSCBS.R 483s 1311 483s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 483s 1 2108 554484 120908858 2108 0.5116 483s 2 777 142693888 185449813 777 0.0973 483s 3 1311 185449813 247137334 1311 0.2295 483s Calculating (C1,C2) per segment... 483s Calculating (C1,C2) per segment...done 483s Number of segments: 3 483s Segmenting paired tumor-normal signals using Paired PSCBS...done 483s Post-segmenting TCNs... 483s Number of segments: 3 483s Number of chromosomes: 1 483s [1] 1 483s Chromosome 1 ('chr01') of 1... 483s Rows: 483s [1] 1 2 3 483s Number of segments: 3 483s TCN segment #1 ('1') of 3... 483s Nothing todo. Only one DH segmentation. Skipping. 483s TCN segment #1 ('1') of 3...done 483s TCN segment #2 ('2') of 3... 483s Nothing todo. Only one DH segmentation. Skipping. 483s TCN segment #2 ('2') of 3...done 483s TCN segment #3 ('3') of 3... 483s Nothing todo. Only one DH segmentation. Skipping. 483s TCN segment #3 ('3') of 3...done 483s Chromosome 1 ('chr01') of 1...done 483s Update (C1,C2) per segment... 483s Update (C1,C2) per segment...done 483s Post-segmenting TCNs...done 483s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 483s 1 1 1 1 554484 120908858 7586 1.3853 2108 483s 2 1 2 1 142693888 185449813 2681 2.0689 777 483s 3 1 3 1 185449813 247137334 4391 2.6341 1311 483s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 483s 1 2108 554484 120908858 2108 0.5116 0.3382903 1.047010 483s 2 777 142693888 185449813 777 0.0973 0.9337980 1.135102 483s 3 1311 185449813 247137334 1311 0.2295 1.0147870 1.619313 483s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 483s 1 1 1 1 554484 120908858 7586 1.3853 2108 483s 2 1 2 1 142693888 185449813 2681 2.0689 777 483s 3 1 3 1 185449813 247137334 4391 2.6341 1311 483s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 483s 1 2108 554484 120908858 2108 0.5116 0.3382903 1.047010 483s 2 777 142693888 185449813 777 0.0973 0.9337980 1.135102 483s 3 1311 185449813 247137334 1311 0.2295 1.0147870 1.619313 483s > print(fit) 483s chromosome tcnId dhId start end tcnNbrOfLoci tcnMean tcnNbrOfSNPs 483s 1 1 1 1 554484 120908858 7586 1.3853 2108 483s 2 1 2 1 142693888 185449813 2681 2.0689 777 483s 3 1 3 1 185449813 247137334 4391 2.6341 1311 483s tcnNbrOfHets dhNbrOfLoci dhMean c1Mean c2Mean 483s 1 2108 2108 0.5116 0.3382903 1.047010 483s 2 777 777 0.0973 0.9337980 1.135102 483s 3 1311 1311 0.2295 1.0147870 1.619313 483s > 483s > fit1 <- fit 483s > fit2 <- renameChromosomes(fit1, from=1, to=2) 483s > fit <- c(fit1, fit2) 483s > knownSegments <- tileChromosomes(fit)$params$knownSegments 483s > 483s > segList <- seqOfSegmentsByDP(fit, verbose=-10) 483s Identifying optimal sets of segments via dynamic programming... 483s Shifting TCN levels for every second segment... 483s Split up into non-empty independent regions... 483s Chromosome #1 ('1') of 2... 483s Number of loci on chromosome: 14658 483s Known segments on chromosome: 483s chromosome start end 483s 1 1 -Inf 120908858 483s 2 1 142693888 Inf 483s Known segment #1 of 2... 483s chromosome start end 483s 1 1 -Inf 120908858 483s Known segment #1 of 2...done 483s Known segment #2 of 2... 483s chromosome start end 483s 2 1 142693888 Inf 483s Known segment #2 of 2...done 483s Chromosome #1 ('1') of 2...done 483s Chromosome #2 ('2') of 2... 483s Number of loci on chromosome: 14658 483s Known segments on chromosome: 483s chromosome start end 483s 3 2 -Inf 120908858 483s 4 2 142693888 Inf 483s Known segment #1 of 2... 483s chromosome start end 483s 3 2 -Inf 120908858 483s Known segment #1 of 2...done 483s Known segment #2 of 2... 483s chromosome start end 483s 4 2 142693888 Inf 483s Known segment #2 of 2...done 483s Chromosome #2 ('2') of 2...done 483s Number of independent non-empty regions: 4 483s Split up into non-empty independent regions...done 483s Shift every other region... 483s Shift every other region...done 483s Merge... 483s Merge...done 483s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 483s 1 1 1 1 554484 120908858 7586 101.3853 2108 483s 2 1 2 1 142693888 185449813 2681 2.0689 777 483s 3 1 3 1 185449813 247137334 4391 2.6341 1311 483s 4 2 1 1 554484 120908858 7586 101.3853 2108 483s 5 2 2 1 142693888 185449813 2681 2.0689 777 483s 6 2 3 1 185449813 247137334 4391 2.6341 1311 483s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 483s 1 2108 554484 120908858 2108 0.511612 24.757671 76.627587 483s 2 777 142693888 185449813 777 0.097300 0.933798 1.135102 483s 3 1311 185449813 247137334 1311 0.229500 1.014787 1.619313 483s 4 2108 554484 120908858 2108 0.511612 24.757671 76.627587 483s 5 777 142693888 185449813 777 0.097300 0.933798 1.135102 483s 6 1311 185449813 247137334 1311 0.229500 1.014787 1.619313 483s Shifting TCN levels for every second segment...done 483s Extracting signals for dynamic programming... 483s CT rho 483s Min. : 0.805 Min. :0.000 483s 1st Qu.: 2.407 1st Qu.:0.139 483s Median :100.927 Median :0.293 483s Mean : 53.638 Mean :0.347 483s 3rd Qu.:101.370 3rd Qu.:0.557 483s Max. :103.080 Max. :1.022 483s NA's :20924 483s Extracting signals for dynamic programming...done 483s Dynamic programming... 483s Number of "DP" change points: 5 483s int [1:5] 7586 10267 14658 22244 24925 483s List of 4 483s $ jump :List of 5 483s ..$ : num 22244 483s ..$ : num [1:2] 7586 14658 483s ..$ : num [1:3] 7586 14658 22244 483s ..$ : num [1:4] 7586 10267 14658 22244 483s ..$ : num [1:5] 7586 10267 14658 22244 24925 483s $ rse : num [1:6] 71699116 47249179 35852530 5945 5410 ... 483s $ kbest: num 4 483s $ V : num [1:6, 1:6] 1114 0 0 0 0 ... 483s Dynamic programming...done 483s Excluding cases where known segments no longer correct... 483s Number of independent non-empty regions: 4 483s List of 3 483s $ : num [1:3] 7586 14658 22244 483s $ : num [1:4] 7586 10267 14658 22244 483s $ : num [1:5] 7586 10267 14658 22244 24925 483s Excluding cases where known segments no longer correct...done 483s List of 3 483s $ :'data.frame': 4 obs. of 3 variables: 483s ..$ chromosome: int [1:4] 1 1 2 2 483s ..$ start : num [1:4] 5.54e+05 1.43e+08 5.54e+05 1.43e+08 483s ..$ end : num [1:4] 1.21e+08 2.47e+08 1.21e+08 2.47e+08 483s $ :'data.frame': 5 obs. of 3 variables: 483s ..$ chromosome: int [1:5] 1 1 1 2 2 483s ..$ start : num [1:5] 5.54e+05 1.43e+08 1.85e+08 5.54e+05 1.43e+08 483s ..$ end : num [1:5] 1.21e+08 1.85e+08 2.47e+08 1.21e+08 2.47e+08 483s $ :'data.frame': 6 obs. of 3 variables: 483s ..$ chromosome: int [1:6] 1 1 1 2 2 2 483s ..$ start : num [1:6] 5.54e+05 1.43e+08 1.85e+08 5.54e+05 1.43e+08 ... 483s ..$ end : num [1:6] 1.21e+08 1.85e+08 2.47e+08 1.21e+08 1.85e+08 ... 483s Sequence of number of "DP" change points: 483s [1] 3 4 5 483s Sequence of number of segments: 483s [1] 4 5 6 483s Sequence of number of "discovered" change points: 483s [1] 0 1 2 483s Identifying optimal sets of segments via dynamic programming...done 483s > K <- length(segList) 483s > ks <- seq(from=1, to=K, length.out=min(5,K)) 483s > subplots(length(ks), ncol=1, byrow=TRUE) 483s > par(mar=c(2,1,1,1)) 483s > for (kk in ks) { 483s + knownSegmentsKK <- segList[[kk]] 483s + fitKK <- resegment(fit, knownSegments=knownSegmentsKK, undoTCN=+Inf, undoDH=+Inf) 483s + plotTracks(fitKK, tracks="tcn,c1,c2", Clim=c(0,5), add=TRUE) 483s + abline(v=c(knownSegments$start, knownSegments$end)/1e6, lty=3) 483s + stext(side=3, pos=0, sprintf("Number of segments: %d", nrow(knownSegmentsKK))) 483s + } # for (kk ...) 483s > 483s > proc.time() 483s user system elapsed 483s 3.557 0.108 3.656 483s Test segmentByPairedPSCBS,seqOfSegmentsByDP passed 483s 0 483s Begin test segmentByPairedPSCBS 489s + cat segmentByPairedPSCBS.Rout 489s 489s R version 4.3.2 (2023-10-31) -- "Eye Holes" 489s Copyright (C) 2023 The R Foundation for Statistical Computing 489s Platform: x86_64-pc-linux-gnu (64-bit) 489s 489s R is free software and comes with ABSOLUTELY NO WARRANTY. 489s You are welcome to redistribute it under certain conditions. 489s Type 'license()' or 'licence()' for distribution details. 489s 489s R is a collaborative project with many contributors. 489s Type 'contributors()' for more information and 489s 'citation()' on how to cite R or R packages in publications. 489s 489s Type 'demo()' for some demos, 'help()' for on-line help, or 489s 'help.start()' for an HTML browser interface to help. 489s Type 'q()' to quit R. 489s 489s [Previously saved workspace restored] 489s 489s > ########################################################### 489s > # This tests: 489s > # - segmentByPairedPSCBS(...) 489s > # - segmentByPairedPSCBS(..., knownSegments) 489s > # - tileChromosomes() 489s > # - plotTracks() 489s > ########################################################### 489s > library("PSCBS") 489s PSCBS v0.66.0 (2021-10-23 07:40:02 UTC) successfully loaded. See ?PSCBS for help. 489s 489s Attaching package: 'PSCBS' 489s 489s The following objects are masked from 'package:base': 489s 489s append, load 489s 489s > 489s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 489s > # Load SNP microarray data 489s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 489s > data <- PSCBS::exampleData("paired.chr01") 489s > 489s > 489s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 489s > # Paired PSCBS segmentation 489s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 489s > # Drop single-locus outliers 489s > dataS <- dropSegmentationOutliers(data) 489s > 489s > # Run light-weight tests by default 489s > if (Sys.getenv("_R_CHECK_FULL_") == "") { 489s + # Use only every 5th data point 489s + dataS <- dataS[seq(from=1, to=nrow(data), by=5),] 489s + # Number of segments (for assertion) 489s + nSegs <- 4L 489s + } else { 489s + # Full tests 489s + nSegs <- 11L 489s + } 489s > 489s > str(dataS) 489s 'data.frame': 14670 obs. of 6 variables: 489s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 489s $ x : int 1145994 2941694 3710825 4240737 4276892 4464544 4714611 5095111 5034491 5158416 ... 489s $ CT : num 1.63 1.4 1.41 1.17 1.16 ... 489s $ betaT : num 0.7574 0.169 0.2357 0.2604 0.0576 ... 489s $ CN : num 2.36 2.13 2.26 2.01 2.32 ... 489s $ betaN : num 0.8274 0.5072 0.1671 0.1609 0.0421 ... 489s > 489s > fig <- 1 489s > 489s > 489s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 489s > # (a) Don't segment the centromere (and force a separator) 489s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 489s > knownSegments <- data.frame( 489s + chromosome = c( 1, 1, 1), 489s + start = c( -Inf, NA, 141510003), 489s + end = c(120992603, NA, +Inf) 489s + ) 489s > 489s > 489s > # Paired PSCBS segmentation 489s > fit <- segmentByPairedPSCBS(dataS, knownSegments=knownSegments, 489s + seed=0xBEEF, verbose=-10) 489s Segmenting paired tumor-normal signals using Paired PSCBS... 489s Calling genotypes from normal allele B fractions... 489s num [1:14670] 0.8274 0.5072 0.1671 0.1609 0.0421 ... 489s Called genotypes: 489s num [1:14670] 1 0.5 0 0 0 0 1 0 1 0.5 ... 489s - attr(*, "modelFit")=List of 1 489s ..$ :List of 7 489s .. ..$ flavor : chr "density" 489s .. ..$ cn : int 2 489s .. ..$ nbrOfGenotypeGroups: int 3 489s .. ..$ tau : num [1:2] 0.315 0.677 489s .. ..$ n : int 14640 489s .. ..$ fit :Classes 'PeaksAndValleys' and 'data.frame': 5 obs. of 3 variables: 489s .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 489s .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 489s .. .. ..$ density: num [1:5] 1.48 0.522 1.056 0.552 1.454 489s .. ..$ fitValleys :Classes 'PeaksAndValleys' and 'data.frame': 2 obs. of 3 variables: 489s .. .. ..$ type : chr [1:2] "valley" "valley" 489s .. .. ..$ x : num [1:2] 0.315 0.677 489s .. .. ..$ density: num [1:2] 0.522 0.552 489s ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 489s muN 489s 0 0.5 1 489s 5221 4198 5251 489s Calling genotypes from normal allele B fractions...done 489s Normalizing betaT using betaN (TumorBoost)... 489s Normalized BAFs: 489s num [1:14670] 0.9301 0.1667 0.0685 0.0995 0.0155 ... 489s - attr(*, "modelFit")=List of 5 489s ..$ method : chr "normalizeTumorBoost" 489s ..$ flavor : chr "v4" 489s ..$ delta : num [1:14670] -0.17264 0.00239 0.1671 0.16085 0.04213 ... 489s .. ..- attr(*, "modelFit")=List of 1 489s .. .. ..$ :List of 7 489s .. .. .. ..$ flavor : chr "density" 489s .. .. .. ..$ cn : int 2 489s .. .. .. ..$ nbrOfGenotypeGroups: int 3 489s .. .. .. ..$ tau : num [1:2] 0.315 0.677 489s .. .. .. ..$ n : int 14640 489s .. .. .. ..$ fit :Classes 'PeaksAndValleys' and 'data.frame': 5 obs. of 3 variables: 489s .. .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 489s .. .. .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 489s .. .. .. .. ..$ density: num [1:5] 1.48 0.522 1.056 0.552 1.454 489s .. .. .. ..$ fitValleys :Classes 'PeaksAndValleys' and 'data.frame': 2 obs. of 3 variables: 489s .. .. .. .. ..$ type : chr [1:2] "valley" "valley" 489s .. .. .. .. ..$ x : num [1:2] 0.315 0.677 489s .. .. .. .. ..$ density: num [1:2] 0.522 0.552 489s .. .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 489s ..$ preserveScale: logi FALSE 489s ..$ scaleFactor : num NA 489s Normalizing betaT using betaN (TumorBoost)...done 489s Setup up data... 489s 'data.frame': 14670 obs. of 7 variables: 489s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 489s $ x : num 1145994 2941694 3710825 4240737 4276892 ... 489s $ CT : num 1.63 1.4 1.41 1.17 1.16 ... 489s $ betaT : num 0.7574 0.169 0.2357 0.2604 0.0576 ... 489s $ betaTN : num 0.9301 0.1667 0.0685 0.0995 0.0155 ... 489s ..- attr(*, "modelFit")=List of 5 489s .. ..$ method : chr "normalizeTumorBoost" 489s .. ..$ flavor : chr "v4" 489s .. ..$ delta : num [1:14670] -0.17264 0.00239 0.1671 0.16085 0.04213 ... 489s .. .. ..- attr(*, "modelFit")=List of 1 489s .. .. .. ..$ :List of 7 489s .. .. .. .. ..$ flavor : chr "density" 489s .. .. .. .. ..$ cn : int 2 489s .. .. .. .. ..$ nbrOfGenotypeGroups: int 3 489s .. .. .. .. ..$ tau : num [1:2] 0.315 0.677 489s .. .. .. .. ..$ n : int 14640 489s .. .. .. .. ..$ fit :Classes 'PeaksAndValleys' and 'data.frame': 5 obs. of 3 variables: 489s .. .. .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 489s .. .. .. .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 489s .. .. .. .. .. ..$ density: num [1:5] 1.48 0.522 1.056 0.552 1.454 489s .. .. .. .. ..$ fitValleys :Classes 'PeaksAndValleys' and 'data.frame': 2 obs. of 3 variables: 489s .. .. .. .. .. ..$ type : chr [1:2] "valley" "valley" 489s .. .. .. .. .. ..$ x : num [1:2] 0.315 0.677 489s .. .. .. .. .. ..$ density: num [1:2] 0.522 0.552 489s .. .. .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 489s .. ..$ preserveScale: logi FALSE 489s .. ..$ scaleFactor : num NA 489s $ betaN : num 0.8274 0.5072 0.1671 0.1609 0.0421 ... 489s $ muN : num 1 0.5 0 0 0 0 1 0 1 0.5 ... 489s ..- attr(*, "modelFit")=List of 1 489s .. ..$ :List of 7 489s .. .. ..$ flavor : chr "density" 489s .. .. ..$ cn : int 2 489s .. .. ..$ nbrOfGenotypeGroups: int 3 489s .. .. ..$ tau : num [1:2] 0.315 0.677 489s .. .. ..$ n : int 14640 489s .. .. ..$ fit :Classes 'PeaksAndValleys' and 'data.frame': 5 obs. of 3 variables: 489s .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 489s .. .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 489s .. .. .. ..$ density: num [1:5] 1.48 0.522 1.056 0.552 1.454 489s .. .. ..$ fitValleys :Classes 'PeaksAndValleys' and 'data.frame': 2 obs. of 3 variables: 489s .. .. .. ..$ type : chr [1:2] "valley" "valley" 489s .. .. .. ..$ x : num [1:2] 0.315 0.677 489s .. .. .. ..$ density: num [1:2] 0.522 0.552 489s .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 489s Setup up data...done 489s Dropping loci for which TCNs are missing... 489s Number of loci dropped: 12 489s Dropping loci for which TCNs are missing...done 489s Ordering data along genome... 489s 'data.frame': 14658 obs. of 7 variables: 489s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 489s $ x : num 554484 730720 782343 878522 916294 ... 489s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 489s $ betaT : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 489s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 489s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 489s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 489s Ordering data along genome...done 489s Keeping only current chromosome for 'knownSegments'... 489s Chromosome: 1 489s Known segments for this chromosome: 489s chromosome start end 489s 1 1 -Inf 120992603 489s 2 1 NA NA 489s 3 1 141510003 Inf 489s Keeping only current chromosome for 'knownSegments'...done 489s alphaTCN: 0.009 489s alphaDH: 0.001 489s Number of loci: 14658 489s Calculating DHs... 489s Number of SNPs: 14658 489s Number of heterozygous SNPs: 4196 (28.63%) 489s Normalized DHs: 489s num [1:14658] NA NA NA NA NA ... 489s Calculating DHs...done 489s Random seed temporarily set (seed=c(48879), kind="L'Ecuyer-CMRG") 489s Produced 2 seeds from this stream for future usage 489s Identification of change points by total copy numbers... 489s Segmenting by CBS... 489s Chromosome: 1 489s Segmenting multiple segments on current chromosome... 489s Number of segments: 3 489s Random seed temporarily set (seed=c(10407, 1066287653, -51199871, 161854402, -1995183193, 1503453565, -747102133), kind="L'Ecuyer-CMRG") 489s Produced 3 seeds from this stream for future usage 489s Segmenting by CBS... 489s Chromosome: 1 489s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 489s Segmenting by CBS...done 489s Segmenting by CBS... 489s Chromosome: 1 489s Random seed temporarily set (seed=c(10407, -1924040949, -1632234809, -437763632, -1464377300, 676654412, 2080370711), kind="L'Ecuyer-CMRG") 489s Segmenting by CBS...done 489s Segmenting multiple segments on current chromosome...done 489s Segmenting by CBS...done 489s List of 4 489s $ data :'data.frame': 14658 obs. of 4 variables: 489s ..$ chromosome: int [1:14658] 1 1 1 1 1 1 1 1 1 1 ... 489s ..$ x : num [1:14658] 554484 730720 782343 878522 916294 ... 489s ..$ y : num [1:14658] 1.88 1.8 1.59 1.64 1.53 ... 489s ..$ index : int [1:14658] 1 2 3 4 5 6 7 8 9 10 ... 489s $ output :'data.frame': 4 obs. of 6 variables: 489s ..$ sampleName: chr [1:4] NA NA NA NA 489s ..$ chromosome: int [1:4] 1 NA 1 1 489s ..$ start : num [1:4] 5.54e+05 NA 1.42e+08 1.85e+08 489s ..$ end : num [1:4] 1.21e+08 NA 1.85e+08 2.47e+08 489s ..$ nbrOfLoci : int [1:4] 7586 NA 2681 4391 489s ..$ mean : num [1:4] 1.39 NA 2.07 2.63 489s $ segRows:'data.frame': 4 obs. of 2 variables: 489s ..$ startRow: int [1:4] 1 NA 7587 10268 489s ..$ endRow : int [1:4] 7586 NA 10267 14658 489s $ params :List of 5 489s ..$ alpha : num 0.009 489s ..$ undo : num 0 489s ..$ joinSegments : logi TRUE 489s ..$ knownSegments:'data.frame': 4 obs. of 3 variables: 489s .. ..$ chromosome: num [1:4] 1 1 2 1 489s .. ..$ start : num [1:4] -Inf -Inf -Inf 1.42e+08 489s .. ..$ end : num [1:4] 1.21e+08 Inf Inf Inf 489s ..$ seed : int [1:7] 10407 1066287653 -51199871 161854402 -1995183193 1503453565 -747102133 489s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 489s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.135 0 0.135 0 0 489s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 489s - attr(*, "pkgDetails")= chr "DNAcopy v1.76.0" 489s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 489s Identification of change points by total copy numbers...done 489s Restructure TCN segmentation results... 489s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean 489s 1 1 554484 120992603 7586 1.3853 489s 2 NA NA NA NA NA 489s 3 1 141510003 185449813 2681 2.0689 489s 4 1 185449813 247137334 4391 2.6341 489s Number of TCN segments: 4 489s Restructure TCN segmentation results...done 489s Total CN segment #1 ([ 554484,1.20993e+08]) of 4... 489s Number of TCN loci in segment: 7586 489s Locus data for TCN segment: 489s 'data.frame': 7586 obs. of 9 variables: 489s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 489s $ x : num 554484 730720 782343 878522 916294 ... 489s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 489s $ betaT : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 489s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 489s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 489s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 489s $ index : int 1 2 3 4 5 6 7 8 9 10 ... 489s $ rho : num NA NA NA NA NA ... 489s Number of loci: 7586 489s Number of SNPs: 2108 (27.79%) 489s Number of heterozygous SNPs: 2108 (100.00%) 489s Chromosome: 1 489s Segmenting DH signals... 489s Segmenting by CBS... 489s Chromosome: 1 489s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 489s Segmenting by CBS...done 489s List of 4 489s $ data :'data.frame': 7586 obs. of 4 variables: 489s ..$ chromosome: int [1:7586] 1 1 1 1 1 1 1 1 1 1 ... 489s ..$ x : num [1:7586] 554484 730720 782343 878522 916294 ... 489s ..$ y : num [1:7586] NA NA NA NA NA ... 489s ..$ index : int [1:7586] 1 2 3 4 5 6 7 8 9 10 ... 489s $ output :'data.frame': 1 obs. of 6 variables: 489s ..$ sampleName: chr NA 489s ..$ chromosome: int 1 489s ..$ start : num 554484 489s ..$ end : num 1.21e+08 489s ..$ nbrOfLoci : int 2108 489s ..$ mean : num 0.512 489s $ segRows:'data.frame': 1 obs. of 2 variables: 489s ..$ startRow: int 10 489s ..$ endRow : int 7574 489s $ params :List of 5 489s ..$ alpha : num 0.001 489s ..$ undo : num 0 489s ..$ joinSegments : logi TRUE 489s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 489s .. ..$ chromosome: int 1 489s .. ..$ start : num 554484 489s .. ..$ end : num 1.21e+08 489s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 489s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 489s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.035 0.001 0.035 0 0 489s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 489s - attr(*, "pkgDetails")= chr "DNAcopy v1.76.0" 489s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 489s DH segmentation (locally-indexed) rows: 489s startRow endRow 489s 1 10 7574 489s int [1:7586] 1 2 3 4 5 6 7 8 9 10 ... 489s DH segmentation rows: 489s startRow endRow 489s 1 10 7574 489s Segmenting DH signals...done 489s DH segmentation table: 489s dhStart dhEnd dhNbrOfLoci dhMean 489s 1 554484 120992603 2108 0.5116 489s startRow endRow 489s 1 10 7574 489s Rows: 489s [1] 1 489s TCN segmentation rows: 489s startRow endRow 489s 1 1 7586 489s TCN and DH segmentation rows: 489s startRow endRow 489s 1 1 7586 489s startRow endRow 489s 1 10 7574 489s NULL 489s TCN segmentation (expanded) rows: 489s startRow endRow 489s 1 1 7586 489s TCN and DH segmentation rows: 489s startRow endRow 489s 1 1 7586 489s 2 NA NA 489s 3 7587 10267 489s 4 10268 14658 489s startRow endRow 489s 1 10 7574 489s startRow endRow 489s 1 1 7586 489s Total CN segmentation table (expanded): 489s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 489s 1 1 554484 120992603 7586 1.3853 2108 2108 489s (TCN,DH) segmentation for one total CN segment: 489s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 489s 1 1 1 1 554484 120992603 7586 1.3853 2108 489s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 489s 1 2108 554484 120992603 2108 0.5116 489s Total CN segment #1 ([ 554484,1.20993e+08]) of 4...done 489s Total CN segment #2 ([ NA, NA]) of 4... 489s No signals to segment. Just a "splitter" segment. Skipping. 489s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 489s NA 2 1 NA NA NA NA NA 0 489s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 489s NA 0 NA NA 0 NA 489s Total CN segment #2 ([ NA, NA]) of 4...done 489s Total CN segment #3 ([1.4151e+08,1.8545e+08]) of 4... 489s Number of TCN loci in segment: 2681 489s Locus data for TCN segment: 489s 'data.frame': 2681 obs. of 9 variables: 489s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 489s $ x : num 1.43e+08 1.43e+08 1.43e+08 1.43e+08 1.44e+08 ... 489s $ CT : num 2.27 1.55 1.47 1.5 1.81 ... 489s $ betaT : num 0.34 0.55 0.048 0.813 0.575 ... 489s $ betaTN : num 0.441 0.629 -0.05 0.958 0.872 ... 489s $ betaN : num 0.3851 0.3933 0.0981 0.8552 0.7028 ... 489s $ muN : num 0.5 0.5 0 1 1 1 1 0.5 1 1 ... 489s $ index : int 7587 7588 7589 7590 7591 7592 7593 7594 7595 7596 ... 489s $ rho : num 0.117 0.258 NA NA NA ... 489s Number of loci: 2681 489s Number of SNPs: 777 (28.98%) 489s Number of heterozygous SNPs: 777 (100.00%) 489s Chromosome: 1 489s Segmenting DH signals... 489s Segmenting by CBS... 489s Chromosome: 1 489s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 489s Segmenting by CBS...done 489s List of 4 489s $ data :'data.frame': 2681 obs. of 4 variables: 489s ..$ chromosome: int [1:2681] 1 1 1 1 1 1 1 1 1 1 ... 489s ..$ x : num [1:2681] 1.43e+08 1.43e+08 1.43e+08 1.43e+08 1.44e+08 ... 489s ..$ y : num [1:2681] 0.117 0.258 NA NA NA ... 489s ..$ index : int [1:2681] 1 2 3 4 5 6 7 8 9 10 ... 489s $ output :'data.frame': 1 obs. of 6 variables: 489s ..$ sampleName: chr NA 489s ..$ chromosome: int 1 489s ..$ start : num 1.42e+08 489s ..$ end : num 1.85e+08 489s ..$ nbrOfLoci : int 777 489s ..$ mean : num 0.0973 489s $ segRows:'data.frame': 1 obs. of 2 variables: 489s ..$ startRow: int 1 489s ..$ endRow : int 2677 489s $ params :List of 5 489s ..$ alpha : num 0.001 489s ..$ undo : num 0 489s ..$ joinSegments : logi TRUE 489s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 489s .. ..$ chromosome: int 1 489s .. ..$ start : num 1.42e+08 489s .. ..$ end : num 1.85e+08 489s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 489s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 489s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.007 0 0.007 0 0 489s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 489s - attr(*, "pkgDetails")= chr "DNAcopy v1.76.0" 489s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 489s DH segmentation (locally-indexed) rows: 489s startRow endRow 489s 1 1 2677 489s int [1:2681] 7587 7588 7589 7590 7591 7592 7593 7594 7595 7596 ... 489s DH segmentation rows: 489s startRow endRow 489s 1 7587 10263 489s Segmenting DH signals...done 489s DH segmentation table: 489s dhStart dhEnd dhNbrOfLoci dhMean 489s 1 141510003 185449813 777 0.0973 489s startRow endRow 489s 1 7587 10263 489s Rows: 489s [1] 3 489s TCN segmentation rows: 489s startRow endRow 489s 3 7587 10267 489s TCN and DH segmentation rows: 489s startRow endRow 489s 3 7587 10267 489s startRow endRow 489s 1 7587 10263 489s startRow endRow 489s 1 1 7586 489s NA NA NA 489s TCN segmentation (expanded) rows: 489s startRow endRow 489s 1 1 7586 489s NA NA NA 489s 3 7587 10267 489s TCN and DH segmentation rows: 489s startRow endRow 489s 1 1 7586 489s 2 NA NA 489s 3 7587 10267 489s 4 10268 14658 489s startRow endRow 489s 1 10 7574 489s 2 NA NA 489s 3 7587 10263 489s startRow endRow 489s 1 1 7586 489s 2 NA NA 489s 3 7587 10267 489s Total CN segmentation table (expanded): 489s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 489s 3 1 141510003 185449813 2681 2.0689 777 777 489s (TCN,DH) segmentation for one total CN segment: 489s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 489s 3 3 1 1 141510003 185449813 2681 2.0689 777 489s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 489s 3 777 141510003 185449813 777 0.0973 489s Total CN segment #3 ([1.4151e+08,1.8545e+08]) of 4...done 489s Total CN segment #4 ([1.8545e+08,2.47137e+08]) of 4... 489s Number of TCN loci in segment: 4391 489s Locus data for TCN segment: 489s 'data.frame': 4391 obs. of 9 variables: 489s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 489s $ x : num 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 489s $ CT : num 2.93 2.15 2.82 2.93 2.46 ... 489s $ betaT : num 0.0811 0.5154 0.9473 0.3734 0.7506 ... 489s $ betaTN : num -0.169 0.609 1.028 0.525 0.968 ... 489s $ betaN : num 0.25 0.38 0.919 0.34 0.783 ... 489s $ muN : num 0 0.5 1 0.5 1 1 0 1 0 1 ... 489s $ index : int 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 489s $ rho : num NA 0.2186 NA 0.0503 NA ... 489s Number of loci: 4391 489s Number of SNPs: 1311 (29.86%) 489s Number of heterozygous SNPs: 1311 (100.00%) 489s Chromosome: 1 489s Segmenting DH signals... 489s Segmenting by CBS... 489s Chromosome: 1 489s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 489s Segmenting by CBS...done 489s List of 4 489s $ data :'data.frame': 4391 obs. of 4 variables: 489s ..$ chromosome: int [1:4391] 1 1 1 1 1 1 1 1 1 1 ... 489s ..$ x : num [1:4391] 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 489s ..$ y : num [1:4391] NA 0.2186 NA 0.0503 NA ... 489s ..$ index : int [1:4391] 1 2 3 4 5 6 7 8 9 10 ... 489s $ output :'data.frame': 1 obs. of 6 variables: 489s ..$ sampleName: chr NA 489s ..$ chromosome: int 1 489s ..$ start : num 1.85e+08 489s ..$ end : num 2.47e+08 489s ..$ nbrOfLoci : int 1311 489s ..$ mean : num 0.23 489s $ segRows:'data.frame': 1 obs. of 2 variables: 489s ..$ startRow: int 2 489s ..$ endRow : int 4388 489s $ params :List of 5 489s ..$ alpha : num 0.001 489s ..$ undo : num 0 489s ..$ joinSegments : logi TRUE 489s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 489s .. ..$ chromosome: int 1 489s .. ..$ start : num 1.85e+08 489s .. ..$ end : num 2.47e+08 489s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 489s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 489s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.013 0 0.014 0 0 489s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 489s - attr(*, "pkgDetails")= chr "DNAcopy v1.76.0" 489s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 489s DH segmentation (locally-indexed) rows: 489s startRow endRow 489s 1 2 4388 489s int [1:4391] 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 489s DH segmentation rows: 489s startRow endRow 489s 1 10269 14655 489s Segmenting DH signals...done 489s DH segmentation table: 489s dhStart dhEnd dhNbrOfLoci dhMean 489s 1 185449813 247137334 1311 0.2295 489s startRow endRow 489s 1 10269 14655 489s Rows: 489s [1] 4 489s TCN segmentation rows: 489s startRow endRow 489s 4 10268 14658 489s TCN and DH segmentation rows: 489s startRow endRow 489s 4 10268 14658 489s startRow endRow 489s 1 10269 14655 489s startRow endRow 489s 1 1 7586 489s 2 NA NA 489s 3 7587 10267 489s TCN segmentation (expanded) rows: 489s startRow endRow 489s 1 1 7586 489s 2 NA NA 489s 3 7587 10267 489s 4 10268 14658 489s TCN and DH segmentation rows: 489s startRow endRow 489s 1 1 7586 489s 2 NA NA 489s 3 7587 10267 489s 4 10268 14658 489s startRow endRow 489s 1 10 7574 489s 2 NA NA 489s 3 7587 10263 489s 4 10269 14655 489s startRow endRow 489s 1 1 7586 489s 2 NA NA 489s 3 7587 10267 489s 4 10268 14658 489s Total CN segmentation table (expanded): 489s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 489s 4 1 185449813 247137334 4391 2.6341 1311 1311 489s (TCN,DH) segmentation for one total CN segment: 489s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 489s 4 4 1 1 185449813 247137334 4391 2.6341 1311 489s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 489s 4 1311 185449813 247137334 1311 0.2295 489s Total CN segment #4 ([1.8545e+08,2.47137e+08]) of 4...done 489s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 489s 1 1 1 1 554484 120992603 7586 1.3853 2108 489s 2 NA 2 1 NA NA NA NA 0 489s 3 1 3 1 141510003 185449813 2681 2.0689 777 489s 4 1 4 1 185449813 247137334 4391 2.6341 1311 489s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 489s 1 2108 554484 120992603 2108 0.5116 489s 2 0 NA NA 0 NA 489s 3 777 141510003 185449813 777 0.0973 489s 4 1311 185449813 247137334 1311 0.2295 489s Calculating (C1,C2) per segment... 489s Calculating (C1,C2) per segment...done 489s Number of segments: 4 489s Segmenting paired tumor-normal signals using Paired PSCBS...done 489s Post-segmenting TCNs... 489s Number of segments: 3 489s Number of chromosomes: 1 489s [1] 1 489s Chromosome 1 ('chr01') of 1... 489s Rows: 489s [1] 1 2 3 489s Number of segments: 3 489s TCN segment #1 ('1') of 3... 489s Nothing todo. Only one DH segmentation. Skipping. 489s TCN segment #1 ('1') of 3...done 489s TCN segment #2 ('3') of 3... 489s Nothing todo. Only one DH segmentation. Skipping. 489s TCN segment #2 ('3') of 3...done 489s TCN segment #3 ('4') of 3... 489s Nothing todo. Only one DH segmentation. Skipping. 489s TCN segment #3 ('4') of 3...done 489s Chromosome 1 ('chr01') of 1...done 489s Update (C1,C2) per segment... 489s Update (C1,C2) per segment...done 489s Post-segmenting TCNs...done 489s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 489s 1 1 1 1 554484 120992603 7586 1.3853 2108 489s 2 NA 2 1 NA NA NA NA 0 489s 3 1 3 1 141510003 185449813 2681 2.0689 777 489s 4 1 4 1 185449813 247137334 4391 2.6341 1311 489s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 489s 1 2108 554484 120992603 2108 0.5116 0.3382903 1.047010 489s 2 0 NA NA 0 NA NA NA 489s 3 777 141510003 185449813 777 0.0973 0.9337980 1.135102 489s 4 1311 185449813 247137334 1311 0.2295 1.0147870 1.619313 489s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 489s 1 1 1 1 554484 120992603 7586 1.3853 2108 489s 2 NA 2 1 NA NA NA NA 0 489s 3 1 3 1 141510003 185449813 2681 2.0689 777 489s 4 1 4 1 185449813 247137334 4391 2.6341 1311 489s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 489s 1 2108 554484 120992603 2108 0.5116 0.3382903 1.047010 489s 2 0 NA NA 0 NA NA NA 489s 3 777 141510003 185449813 777 0.0973 0.9337980 1.135102 489s 4 1311 185449813 247137334 1311 0.2295 1.0147870 1.619313 489s > print(fit) 489s chromosome tcnId dhId start end tcnNbrOfLoci tcnMean tcnNbrOfSNPs 489s 1 1 1 1 554484 120992603 7586 1.3853 2108 489s 2 NA 2 1 NA NA NA NA 0 489s 3 1 3 1 141510003 185449813 2681 2.0689 777 489s 4 1 4 1 185449813 247137334 4391 2.6341 1311 489s tcnNbrOfHets dhNbrOfLoci dhMean c1Mean c2Mean 489s 1 2108 2108 0.5116 0.3382903 1.047010 489s 2 0 0 NA NA NA 489s 3 777 777 0.0973 0.9337980 1.135102 489s 4 1311 1311 0.2295 1.0147870 1.619313 489s > 489s > # Plot results 489s > dev.set(2L) 489s null device 489s 1 489s > plotTracks(fit) 489s > abline(v=c(knownSegments$start, knownSegments$end)/1e6, lty=3) 489s > 489s > # Sanity check 489s > stopifnot(nbrOfSegments(fit) == nSegs) 489s > 489s > fit1 <- fit 489s > 489s > 489s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 489s > # (b) Segment also the centromere (which will become NAs) 489s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 489s > knownSegments <- data.frame( 489s + chromosome = c( 1, 1, 1), 489s + start = c( -Inf, 120992604, 141510003), 489s + end = c(120992603, 141510002, +Inf) 489s + ) 489s > 489s > 489s > # Paired PSCBS segmentation 489s > fit <- segmentByPairedPSCBS(dataS, knownSegments=knownSegments, 489s + seed=0xBEEF, verbose=-10) 489s Segmenting paired tumor-normal signals using Paired PSCBS... 489s Calling genotypes from normal allele B fractions... 489s num [1:14670] 0.8274 0.5072 0.1671 0.1609 0.0421 ... 489s Called genotypes: 489s num [1:14670] 1 0.5 0 0 0 0 1 0 1 0.5 ... 489s - attr(*, "modelFit")=List of 1 489s ..$ :List of 7 489s .. ..$ flavor : chr "density" 489s .. ..$ cn : int 2 489s .. ..$ nbrOfGenotypeGroups: int 3 489s .. ..$ tau : num [1:2] 0.315 0.677 489s .. ..$ n : int 14640 489s .. ..$ fit :Classes 'PeaksAndValleys' and 'data.frame': 5 obs. of 3 variables: 489s .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 489s .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 489s .. .. ..$ density: num [1:5] 1.48 0.522 1.056 0.552 1.454 489s .. ..$ fitValleys :Classes 'PeaksAndValleys' and 'data.frame': 2 obs. of 3 variables: 489s .. .. ..$ type : chr [1:2] "valley" "valley" 489s .. .. ..$ x : num [1:2] 0.315 0.677 489s .. .. ..$ density: num [1:2] 0.522 0.552 489s ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 489s muN 489s 0 0.5 1 489s 5221 4198 5251 489s Calling genotypes from normal allele B fractions...done 489s Normalizing betaT using betaN (TumorBoost)... 489s Normalized BAFs: 489s num [1:14670] 0.9301 0.1667 0.0685 0.0995 0.0155 ... 489s - attr(*, "modelFit")=List of 5 489s ..$ method : chr "normalizeTumorBoost" 489s ..$ flavor : chr "v4" 489s ..$ delta : num [1:14670] -0.17264 0.00239 0.1671 0.16085 0.04213 ... 489s .. ..- attr(*, "modelFit")=List of 1 489s .. .. ..$ :List of 7 489s .. .. .. ..$ flavor : chr "density" 489s .. .. .. ..$ cn : int 2 489s .. .. .. ..$ nbrOfGenotypeGroups: int 3 489s .. .. .. ..$ tau : num [1:2] 0.315 0.677 489s .. .. .. ..$ n : int 14640 489s .. .. .. ..$ fit :Classes 'PeaksAndValleys' and 'data.frame': 5 obs. of 3 variables: 489s .. .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 489s .. .. .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 489s .. .. .. .. ..$ density: num [1:5] 1.48 0.522 1.056 0.552 1.454 489s .. .. .. ..$ fitValleys :Classes 'PeaksAndValleys' and 'data.frame': 2 obs. of 3 variables: 489s .. .. .. .. ..$ type : chr [1:2] "valley" "valley" 489s .. .. .. .. ..$ x : num [1:2] 0.315 0.677 489s .. .. .. .. ..$ density: num [1:2] 0.522 0.552 489s .. .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 489s ..$ preserveScale: logi FALSE 489s ..$ scaleFactor : num NA 489s Normalizing betaT using betaN (TumorBoost)...done 489s Setup up data... 489s 'data.frame': 14670 obs. of 7 variables: 489s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 489s $ x : num 1145994 2941694 3710825 4240737 4276892 ... 489s $ CT : num 1.63 1.4 1.41 1.17 1.16 ... 489s $ betaT : num 0.7574 0.169 0.2357 0.2604 0.0576 ... 489s $ betaTN : num 0.9301 0.1667 0.0685 0.0995 0.0155 ... 489s ..- attr(*, "modelFit")=List of 5 489s .. ..$ method : chr "normalizeTumorBoost" 489s .. ..$ flavor : chr "v4" 489s .. ..$ delta : num [1:14670] -0.17264 0.00239 0.1671 0.16085 0.04213 ... 489s .. .. ..- attr(*, "modelFit")=List of 1 489s .. .. .. ..$ :List of 7 489s .. .. .. .. ..$ flavor : chr "density" 489s .. .. .. .. ..$ cn : int 2 489s + [ 0 != 0 ] 489s + echo Test segmentByPairedPSCBS passed 489s + echo 0 489s + echo Begin test weightedQuantile 489s + exitcode=0 489s + R CMD BATCH weightedQuantile.R 489s .. .. .. .. ..$ nbrOfGenotypeGroups: int 3 489s .. .. .. .. ..$ tau : num [1:2] 0.315 0.677 489s .. .. .. .. ..$ n : int 14640 489s .. .. .. .. ..$ fit :Classes 'PeaksAndValleys' and 'data.frame': 5 obs. of 3 variables: 489s .. .. .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 489s .. .. .. .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 489s .. .. .. .. .. ..$ density: num [1:5] 1.48 0.522 1.056 0.552 1.454 489s .. .. .. .. ..$ fitValleys :Classes 'PeaksAndValleys' and 'data.frame': 2 obs. of 3 variables: 489s .. .. .. .. .. ..$ type : chr [1:2] "valley" "valley" 489s .. .. .. .. .. ..$ x : num [1:2] 0.315 0.677 489s .. .. .. .. .. ..$ density: num [1:2] 0.522 0.552 489s .. .. .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 489s .. ..$ preserveScale: logi FALSE 489s .. ..$ scaleFactor : num NA 489s $ betaN : num 0.8274 0.5072 0.1671 0.1609 0.0421 ... 489s $ muN : num 1 0.5 0 0 0 0 1 0 1 0.5 ... 489s ..- attr(*, "modelFit")=List of 1 489s .. ..$ :List of 7 489s .. .. ..$ flavor : chr "density" 489s .. .. ..$ cn : int 2 489s .. .. ..$ nbrOfGenotypeGroups: int 3 489s .. .. ..$ tau : num [1:2] 0.315 0.677 489s .. .. ..$ n : int 14640 489s .. .. ..$ fit :Classes 'PeaksAndValleys' and 'data.frame': 5 obs. of 3 variables: 489s .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 489s .. .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 489s .. .. .. ..$ density: num [1:5] 1.48 0.522 1.056 0.552 1.454 489s .. .. ..$ fitValleys :Classes 'PeaksAndValleys' and 'data.frame': 2 obs. of 3 variables: 489s .. .. .. ..$ type : chr [1:2] "valley" "valley" 489s .. .. .. ..$ x : num [1:2] 0.315 0.677 489s .. .. .. ..$ density: num [1:2] 0.522 0.552 489s .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 489s Setup up data...done 489s Dropping loci for which TCNs are missing... 489s Number of loci dropped: 12 489s Dropping loci for which TCNs are missing...done 489s Ordering data along genome... 489s 'data.frame': 14658 obs. of 7 variables: 489s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 489s $ x : num 554484 730720 782343 878522 916294 ... 489s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 489s $ betaT : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 489s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 489s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 489s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 489s Ordering data along genome...done 489s Keeping only current chromosome for 'knownSegments'... 489s Chromosome: 1 489s Known segments for this chromosome: 489s chromosome start end 489s 1 1 -Inf 120992603 489s 2 1 120992604 141510002 489s 3 1 141510003 Inf 489s Keeping only current chromosome for 'knownSegments'...done 489s alphaTCN: 0.009 489s alphaDH: 0.001 489s Number of loci: 14658 489s Calculating DHs... 489s Number of SNPs: 14658 489s Number of heterozygous SNPs: 4196 (28.63%) 489s Normalized DHs: 489s num [1:14658] NA NA NA NA NA ... 489s Calculating DHs...done 489s Random seed temporarily set (seed=c(48879), kind="L'Ecuyer-CMRG") 489s Produced 2 seeds from this stream for future usage 489s Identification of change points by total copy numbers... 489s Segmenting by CBS... 489s Chromosome: 1 489s Segmenting multiple segments on current chromosome... 489s Number of segments: 3 489s Random seed temporarily set (seed=c(10407, 1066287653, -51199871, 161854402, -1995183193, 1503453565, -747102133), kind="L'Ecuyer-CMRG") 489s Produced 3 seeds from this stream for future usage 489s Segmenting by CBS... 489s Chromosome: 1 489s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 489s Segmenting by CBS...done 489s Segmenting by CBS... 489s Chromosome: 1 489s Random seed temporarily set (seed=c(10407, -1924040949, -1632234809, -437763632, -1464377300, 676654412, 2080370711), kind="L'Ecuyer-CMRG") 489s Segmenting by CBS...done 489s Segmenting multiple segments on current chromosome...done 489s Segmenting by CBS...done 489s List of 4 489s $ data :'data.frame': 14658 obs. of 4 variables: 489s ..$ chromosome: int [1:14658] 1 1 1 1 1 1 1 1 1 1 ... 489s ..$ x : num [1:14658] 554484 730720 782343 878522 916294 ... 489s ..$ y : num [1:14658] 1.88 1.8 1.59 1.64 1.53 ... 489s ..$ index : int [1:14658] 1 2 3 4 5 6 7 8 9 10 ... 489s $ output :'data.frame': 4 obs. of 6 variables: 489s ..$ sampleName: chr [1:4] NA NA NA NA 489s ..$ chromosome: num [1:4] 1 1 1 1 489s ..$ start : num [1:4] 5.54e+05 1.21e+08 1.42e+08 1.85e+08 489s ..$ end : num [1:4] 1.21e+08 1.42e+08 1.85e+08 2.47e+08 489s ..$ nbrOfLoci : int [1:4] 7586 0 2681 4391 489s ..$ mean : num [1:4] 1.39 NA 2.07 2.63 489s $ segRows:'data.frame': 4 obs. of 2 variables: 489s ..$ startRow: int [1:4] 1 NA 7587 10268 489s ..$ endRow : int [1:4] 7586 NA 10267 14658 489s $ params :List of 5 489s ..$ alpha : num 0.009 489s ..$ undo : num 0 489s ..$ joinSegments : logi TRUE 489s ..$ knownSegments:'data.frame': 4 obs. of 3 variables: 489s .. ..$ chromosome: num [1:4] 1 1 2 1 489s .. ..$ start : num [1:4] -Inf -Inf -Inf 1.42e+08 489s .. ..$ end : num [1:4] 1.21e+08 Inf Inf Inf 489s ..$ seed : int [1:7] 10407 1066287653 -51199871 161854402 -1995183193 1503453565 -747102133 489s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 489s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.133 0 0.133 0 0 489s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 489s - attr(*, "pkgDetails")= chr "DNAcopy v1.76.0" 489s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 489s Identification of change points by total copy numbers...done 489s Restructure TCN segmentation results... 489s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean 489s 1 1 554484 120992603 7586 1.3853 489s 2 1 120992604 141510002 0 NA 489s 3 1 141510003 185449813 2681 2.0689 489s 4 1 185449813 247137334 4391 2.6341 489s Number of TCN segments: 4 489s Restructure TCN segmentation results...done 489s Total CN segment #1 ([ 554484,1.20993e+08]) of 4... 489s Number of TCN loci in segment: 7586 489s Locus data for TCN segment: 489s 'data.frame': 7586 obs. of 9 variables: 489s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 489s $ x : num 554484 730720 782343 878522 916294 ... 489s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 489s $ betaT : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 489s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 489s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 489s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 489s $ index : int 1 2 3 4 5 6 7 8 9 10 ... 489s $ rho : num NA NA NA NA NA ... 489s Number of loci: 7586 489s Number of SNPs: 2108 (27.79%) 489s Number of heterozygous SNPs: 2108 (100.00%) 489s Chromosome: 1 489s Segmenting DH signals... 489s Segmenting by CBS... 489s Chromosome: 1 489s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 489s Segmenting by CBS...done 489s List of 4 489s $ data :'data.frame': 7586 obs. of 4 variables: 489s ..$ chromosome: int [1:7586] 1 1 1 1 1 1 1 1 1 1 ... 489s ..$ x : num [1:7586] 554484 730720 782343 878522 916294 ... 489s ..$ y : num [1:7586] NA NA NA NA NA ... 489s ..$ index : int [1:7586] 1 2 3 4 5 6 7 8 9 10 ... 489s $ output :'data.frame': 1 obs. of 6 variables: 489s ..$ sampleName: chr NA 489s ..$ chromosome: int 1 489s ..$ start : num 554484 489s ..$ end : num 1.21e+08 489s ..$ nbrOfLoci : int 2108 489s ..$ mean : num 0.512 489s $ segRows:'data.frame': 1 obs. of 2 variables: 489s ..$ startRow: int 10 489s ..$ endRow : int 7574 489s $ params :List of 5 489s ..$ alpha : num 0.001 489s ..$ undo : num 0 489s ..$ joinSegments : logi TRUE 489s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 489s .. ..$ chromosome: int 1 489s .. ..$ start : num 554484 489s .. ..$ end : num 1.21e+08 489s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 489s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 489s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.034 0 0.034 0 0 489s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 489s - attr(*, "pkgDetails")= chr "DNAcopy v1.76.0" 489s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 489s DH segmentation (locally-indexed) rows: 489s startRow endRow 489s 1 10 7574 489s int [1:7586] 1 2 3 4 5 6 7 8 9 10 ... 489s DH segmentation rows: 489s startRow endRow 489s 1 10 7574 489s Segmenting DH signals...done 489s DH segmentation table: 489s dhStart dhEnd dhNbrOfLoci dhMean 489s 1 554484 120992603 2108 0.5116 489s startRow endRow 489s 1 10 7574 489s Rows: 489s [1] 1 489s TCN segmentation rows: 489s startRow endRow 489s 1 1 7586 489s TCN and DH segmentation rows: 489s startRow endRow 489s 1 1 7586 489s startRow endRow 489s 1 10 7574 489s NULL 489s TCN segmentation (expanded) rows: 489s startRow endRow 489s 1 1 7586 489s TCN and DH segmentation rows: 489s startRow endRow 489s 1 1 7586 489s 2 NA NA 489s 3 7587 10267 489s 4 10268 14658 489s startRow endRow 489s 1 10 7574 489s startRow endRow 489s 1 1 7586 489s Total CN segmentation table (expanded): 489s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 489s 1 1 554484 120992603 7586 1.3853 2108 2108 489s (TCN,DH) segmentation for one total CN segment: 489s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 489s 1 1 1 1 554484 120992603 7586 1.3853 2108 489s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 489s 1 2108 554484 120992603 2108 0.5116 489s Total CN segment #1 ([ 554484,1.20993e+08]) of 4...done 489s Total CN segment #2 ([1.20993e+08,1.4151e+08]) of 4... 489s Number of TCN loci in segment: 0 489s Locus data for TCN segment: 489s 'data.frame': 0 obs. of 9 variables: 489s $ chromosome: int 489s $ x : num 489s $ CT : num 489s $ betaT : num 489s $ betaTN : num 489s $ betaN : num 489s $ muN : num 489s $ index : int 489s $ rho : num 489s Number of loci: 0 489s Number of SNPs: 0 (NaN%) 489s Number of heterozygous SNPs: 0 (NaN%) 489s Chromosome: 1 489s Segmenting DH signals... 489s Segmenting by CBS... 489s Chromosome: NA 489s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 489s Segmenting by CBS...done 489s List of 4 489s $ data :'data.frame': 0 obs. of 4 variables: 489s ..$ chromosome: int(0) 489s ..$ x : num(0) 489s ..$ y : num(0) 489s ..$ index : int(0) 489s $ output :'data.frame': 0 obs. of 6 variables: 489s ..$ sampleName: chr(0) 489s ..$ chromosome: num(0) 489s ..$ start : num(0) 489s ..$ end : num(0) 489s ..$ nbrOfLoci : int(0) 489s ..$ mean : num(0) 489s $ segRows:'data.frame': 0 obs. of 2 variables: 489s ..$ startRow: int(0) 489s ..$ endRow : int(0) 489s $ params :List of 5 489s ..$ alpha : num 0.001 489s ..$ undo : num 0 489s ..$ joinSegments : logi TRUE 489s ..$ knownSegments:'data.frame': 0 obs. of 3 variables: 489s .. ..$ chromosome: int(0) 489s .. ..$ start : num(0) 489s .. ..$ end : num(0) 489s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 489s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 489s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.001 0 0.001 0 0 489s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 489s - attr(*, "pkgDetails")= chr "DNAcopy v1.76.0" 489s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 489s DH segmentation (locally-indexed) rows: 489s [1] startRow endRow 489s <0 rows> (or 0-length row.names) 489s int(0) 489s DH segmentation rows: 489s [1] startRow endRow 489s <0 rows> (or 0-length row.names) 489s Segmenting DH signals...done 489s DH segmentation table: 489s dhStart dhEnd dhNbrOfLoci dhMean 489s NA NA NA NA NA 489s startRow endRow 489s NA NA NA 489s Rows: 489s [1] 2 489s TCN segmentation rows: 489s startRow endRow 489s 2 NA NA 489s TCN and DH segmentation rows: 489s startRow endRow 489s 2 NA NA 489s startRow endRow 489s NA NA NA 489s startRow endRow 489s 1 1 7586 489s TCN segmentation (expanded) rows: 489s startRow endRow 489s 1 1 7586 489s 2 NA NA 489s TCN and DH segmentation rows: 489s startRow endRow 489s 1 1 7586 489s 2 NA NA 489s 3 7587 10267 489s 4 10268 14658 489s startRow endRow 489s 1 10 7574 489s 2 NA NA 489s startRow endRow 489s 1 1 7586 489s 2 NA NA 489s Total CN segmentation table (expanded): 489s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 489s 2 1 120992604 141510002 0 NA 0 0 489s (TCN,DH) segmentation for one total CN segment: 489s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 489s 2 2 1 1 120992604 141510002 0 NA 0 489s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 489s 2 0 NA NA NA NA 489s Total CN segment #2 ([1.20993e+08,1.4151e+08]) of 4...done 489s Total CN segment #3 ([1.4151e+08,1.8545e+08]) of 4... 489s Number of TCN loci in segment: 2681 489s Locus data for TCN segment: 489s 'data.frame': 2681 obs. of 9 variables: 489s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 489s $ x : num 1.43e+08 1.43e+08 1.43e+08 1.43e+08 1.44e+08 ... 489s $ CT : num 2.27 1.55 1.47 1.5 1.81 ... 489s $ betaT : num 0.34 0.55 0.048 0.813 0.575 ... 489s $ betaTN : num 0.441 0.629 -0.05 0.958 0.872 ... 489s $ betaN : num 0.3851 0.3933 0.0981 0.8552 0.7028 ... 489s $ muN : num 0.5 0.5 0 1 1 1 1 0.5 1 1 ... 489s $ index : int 7587 7588 7589 7590 7591 7592 7593 7594 7595 7596 ... 489s $ rho : num 0.117 0.258 NA NA NA ... 489s Number of loci: 2681 489s Number of SNPs: 777 (28.98%) 489s Number of heterozygous SNPs: 777 (100.00%) 489s Chromosome: 1 489s Segmenting DH signals... 489s Segmenting by CBS... 489s Chromosome: 1 489s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 489s Segmenting by CBS...done 489s List of 4 489s $ data :'data.frame': 2681 obs. of 4 variables: 489s ..$ chromosome: int [1:2681] 1 1 1 1 1 1 1 1 1 1 ... 489s ..$ x : num [1:2681] 1.43e+08 1.43e+08 1.43e+08 1.43e+08 1.44e+08 ... 489s ..$ y : num [1:2681] 0.117 0.258 NA NA NA ... 489s ..$ index : int [1:2681] 1 2 3 4 5 6 7 8 9 10 ... 489s $ output :'data.frame': 1 obs. of 6 variables: 489s ..$ sampleName: chr NA 489s ..$ chromosome: int 1 489s ..$ start : num 1.42e+08 489s ..$ end : num 1.85e+08 489s ..$ nbrOfLoci : int 777 489s ..$ mean : num 0.0973 489s $ segRows:'data.frame': 1 obs. of 2 variables: 489s ..$ startRow: int 1 489s ..$ endRow : int 2677 489s $ params :List of 5 489s ..$ alpha : num 0.001 489s ..$ undo : num 0 489s ..$ joinSegments : logi TRUE 489s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 489s .. ..$ chromosome: int 1 489s .. ..$ start : num 1.42e+08 489s .. ..$ end : num 1.85e+08 489s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 489s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 489s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.008 0 0.007 0 0 489s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 489s - attr(*, "pkgDetails")= chr "DNAcopy v1.76.0" 489s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 489s DH segmentation (locally-indexed) rows: 489s startRow endRow 489s 1 1 2677 489s int [1:2681] 7587 7588 7589 7590 7591 7592 7593 7594 7595 7596 ... 489s DH segmentation rows: 489s startRow endRow 489s 1 7587 10263 489s Segmenting DH signals...done 489s DH segmentation table: 489s dhStart dhEnd dhNbrOfLoci dhMean 489s 1 141510003 185449813 777 0.0973 489s startRow endRow 489s 1 7587 10263 489s Rows: 489s [1] 3 489s TCN segmentation rows: 489s startRow endRow 489s 3 7587 10267 489s TCN and DH segmentation rows: 489s startRow endRow 489s 3 7587 10267 489s startRow endRow 489s 1 7587 10263 489s startRow endRow 489s 1 1 7586 489s 2 NA NA 489s TCN segmentation (expanded) rows: 489s startRow endRow 489s 1 1 7586 489s 2 NA NA 489s 3 7587 10267 489s TCN and DH segmentation rows: 489s startRow endRow 489s 1 1 7586 489s 2 NA NA 489s 3 7587 10267 489s 4 10268 14658 489s startRow endRow 489s 1 10 7574 489s 2 NA NA 489s 3 7587 10263 489s startRow endRow 489s 1 1 7586 489s 2 NA NA 489s 3 7587 10267 489s Total CN segmentation table (expanded): 489s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 489s 3 1 141510003 185449813 2681 2.0689 777 777 489s (TCN,DH) segmentation for one total CN segment: 489s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 489s 3 3 1 1 141510003 185449813 2681 2.0689 777 489s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 489s 3 777 141510003 185449813 777 0.0973 489s Total CN segment #3 ([1.4151e+08,1.8545e+08]) of 4...done 489s Total CN segment #4 ([1.8545e+08,2.47137e+08]) of 4... 489s Number of TCN loci in segment: 4391 489s Locus data for TCN segment: 489s 'data.frame': 4391 obs. of 9 variables: 489s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 489s $ x : num 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 489s $ CT : num 2.93 2.15 2.82 2.93 2.46 ... 489s $ betaT : num 0.0811 0.5154 0.9473 0.3734 0.7506 ... 489s $ betaTN : num -0.169 0.609 1.028 0.525 0.968 ... 489s $ betaN : num 0.25 0.38 0.919 0.34 0.783 ... 489s $ muN : num 0 0.5 1 0.5 1 1 0 1 0 1 ... 489s $ index : int 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 489s $ rho : num NA 0.2186 NA 0.0503 NA ... 489s Number of loci: 4391 489s Number of SNPs: 1311 (29.86%) 489s Number of heterozygous SNPs: 1311 (100.00%) 489s Chromosome: 1 489s Segmenting DH signals... 489s Segmenting by CBS... 489s Chromosome: 1 489s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 489s Segmenting by CBS...done 489s List of 4 489s $ data :'data.frame': 4391 obs. of 4 variables: 489s ..$ chromosome: int [1:4391] 1 1 1 1 1 1 1 1 1 1 ... 489s ..$ x : num [1:4391] 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 489s ..$ y : num [1:4391] NA 0.2186 NA 0.0503 NA ... 489s ..$ index : int [1:4391] 1 2 3 4 5 6 7 8 9 10 ... 489s $ output :'data.frame': 1 obs. of 6 variables: 489s ..$ sampleName: chr NA 489s ..$ chromosome: int 1 489s ..$ start : num 1.85e+08 489s ..$ end : num 2.47e+08 489s ..$ nbrOfLoci : int 1311 489s ..$ mean : num 0.23 489s $ segRows:'data.frame': 1 obs. of 2 variables: 489s ..$ startRow: int 2 489s ..$ endRow : int 4388 489s $ params :List of 5 489s ..$ alpha : num 0.001 489s ..$ undo : num 0 489s ..$ joinSegments : logi TRUE 489s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 489s .. ..$ chromosome: int 1 489s .. ..$ start : num 1.85e+08 489s .. ..$ end : num 2.47e+08 489s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 489s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 489s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.014 0 0.014 0 0 489s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 489s - attr(*, "pkgDetails")= chr "DNAcopy v1.76.0" 489s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 489s DH segmentation (locally-indexed) rows: 489s startRow endRow 489s 1 2 4388 489s int [1:4391] 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 489s DH segmentation rows: 489s startRow endRow 489s 1 10269 14655 489s Segmenting DH signals...done 489s DH segmentation table: 489s dhStart dhEnd dhNbrOfLoci dhMean 489s 1 185449813 247137334 1311 0.2295 489s startRow endRow 489s 1 10269 14655 489s Rows: 489s [1] 4 489s TCN segmentation rows: 489s startRow endRow 489s 4 10268 14658 489s TCN and DH segmentation rows: 489s startRow endRow 489s 4 10268 14658 489s startRow endRow 489s 1 10269 14655 489s startRow endRow 489s 1 1 7586 489s 2 NA NA 489s 3 7587 10267 489s TCN segmentation (expanded) rows: 489s startRow endRow 489s 1 1 7586 489s 2 NA NA 489s 3 7587 10267 489s 4 10268 14658 489s TCN and DH segmentation rows: 489s startRow endRow 489s 1 1 7586 489s 2 NA NA 489s 3 7587 10267 489s 4 10268 14658 489s startRow endRow 489s 1 10 7574 489s 2 NA NA 489s 3 7587 10263 489s 4 10269 14655 489s startRow endRow 489s 1 1 7586 489s 2 NA NA 489s 3 7587 10267 489s 4 10268 14658 489s Total CN segmentation table (expanded): 489s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 489s 4 1 185449813 247137334 4391 2.6341 1311 1311 489s (TCN,DH) segmentation for one total CN segment: 489s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 489s 4 4 1 1 185449813 247137334 4391 2.6341 1311 489s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 489s 4 1311 185449813 247137334 1311 0.2295 489s Total CN segment #4 ([1.8545e+08,2.47137e+08]) of 4...done 489s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 489s 1 1 1 1 554484 120992603 7586 1.3853 2108 489s 2 1 2 1 120992604 141510002 0 NA 0 489s 3 1 3 1 141510003 185449813 2681 2.0689 777 489s 4 1 4 1 185449813 247137334 4391 2.6341 1311 489s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 489s 1 2108 554484 120992603 2108 0.5116 489s 2 0 NA NA NA NA 489s 3 777 141510003 185449813 777 0.0973 489s 4 1311 185449813 247137334 1311 0.2295 489s Calculating (C1,C2) per segment... 489s Calculating (C1,C2) per segment...done 489s Number of segments: 4 489s Segmenting paired tumor-normal signals using Paired PSCBS...done 489s Post-segmenting TCNs... 489s Number of segments: 4 489s Number of chromosomes: 1 489s [1] 1 489s Chromosome 1 ('chr01') of 1... 489s Rows: 489s [1] 1 2 3 4 489s Number of segments: 4 489s TCN segment #1 ('1') of 4... 489s Nothing todo. Only one DH segmentation. Skipping. 489s TCN segment #1 ('1') of 4...done 489s TCN segment #2 ('2') of 4... 489s Nothing todo. Only one DH segmentation. Skipping. 489s TCN segment #2 ('2') of 4...done 489s TCN segment #3 ('3') of 4... 489s Nothing todo. Only one DH segmentation. Skipping. 489s TCN segment #3 ('3') of 4...done 489s TCN segment #4 ('4') of 4... 489s Nothing todo. Only one DH segmentation. Skipping. 489s TCN segment #4 ('4') of 4...done 489s Chromosome 1 ('chr01') of 1...done 489s Update (C1,C2) per segment... 489s Update (C1,C2) per segment...done 489s Post-segmenting TCNs...done 489s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 489s 1 1 1 1 554484 120992603 7586 1.3853 2108 489s 2 1 2 1 120992604 141510002 0 NA 0 489s 3 1 3 1 141510003 185449813 2681 2.0689 777 489s 4 1 4 1 185449813 247137334 4391 2.6341 1311 489s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 489s 1 2108 554484 120992603 2108 0.5116 0.3382903 1.047010 489s 2 0 NA NA NA NA NA NA 489s 3 777 141510003 185449813 777 0.0973 0.9337980 1.135102 489s 4 1311 185449813 247137334 1311 0.2295 1.0147870 1.619313 489s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 489s 1 1 1 1 554484 120992603 7586 1.3853 2108 489s 2 1 2 1 120992604 141510002 0 NA 0 489s 3 1 3 1 141510003 185449813 2681 2.0689 777 489s 4 1 4 1 185449813 247137334 4391 2.6341 1311 489s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 489s 1 2108 554484 120992603 2108 0.5116 0.3382903 1.047010 489s 2 0 NA NA NA NA NA NA 489s 3 777 141510003 185449813 777 0.0973 0.9337980 1.135102 489s 4 1311 185449813 247137334 1311 0.2295 1.0147870 1.619313 489s > print(fit) 489s chromosome tcnId dhId start end tcnNbrOfLoci tcnMean tcnNbrOfSNPs 489s 1 1 1 1 554484 120992603 7586 1.3853 2108 489s 2 1 2 1 120992604 141510002 0 NA 0 489s 3 1 3 1 141510003 185449813 2681 2.0689 777 489s 4 1 4 1 185449813 247137334 4391 2.6341 1311 489s tcnNbrOfHets dhNbrOfLoci dhMean c1Mean c2Mean 489s 1 2108 2108 0.5116 0.3382903 1.047010 489s 2 0 NA NA NA NA 489s 3 777 777 0.0973 0.9337980 1.135102 489s 4 1311 1311 0.2295 1.0147870 1.619313 489s > 489s > # Plot results 489s > dev.set(3L) 489s pdf 489s 2 489s > plotTracks(fit) 489s > abline(v=c(knownSegments$start, knownSegments$end)/1e6, lty=3) 489s > 489s > # Sanity check [TO FIX: See above] 489s > stopifnot(nbrOfSegments(fit) == nSegs) 489s > 489s > fit2 <- fit 489s > 489s > 489s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 489s > # (c) Do not segment the centromere (without a separator) 489s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 489s > knownSegments <- data.frame( 489s + chromosome = c( 1, 1), 489s + start = c( -Inf, 141510003), 489s + end = c(120992603, +Inf) 489s + ) 489s > 489s > # Paired PSCBS segmentation 489s > fit <- segmentByPairedPSCBS(dataS, knownSegments=knownSegments, 489s + seed=0xBEEF, verbose=-10) 489s Segmenting paired tumor-normal signals using Paired PSCBS... 489s Calling genotypes from normal allele B fractions... 489s num [1:14670] 0.8274 0.5072 0.1671 0.1609 0.0421 ... 489s Called genotypes: 489s num [1:14670] 1 0.5 0 0 0 0 1 0 1 0.5 ... 489s - attr(*, "modelFit")=List of 1 489s ..$ :List of 7 489s .. ..$ flavor : chr "density" 489s .. ..$ cn : int 2 489s .. ..$ nbrOfGenotypeGroups: int 3 489s .. ..$ tau : num [1:2] 0.315 0.677 489s .. ..$ n : int 14640 489s .. ..$ fit :Classes 'PeaksAndValleys' and 'data.frame': 5 obs. of 3 variables: 489s .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 489s .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 489s .. .. ..$ density: num [1:5] 1.48 0.522 1.056 0.552 1.454 489s .. ..$ fitValleys :Classes 'PeaksAndValleys' and 'data.frame': 2 obs. of 3 variables: 489s .. .. ..$ type : chr [1:2] "valley" "valley" 489s .. .. ..$ x : num [1:2] 0.315 0.677 489s .. .. ..$ density: num [1:2] 0.522 0.552 489s ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 489s muN 489s 0 0.5 1 489s 5221 4198 5251 489s Calling genotypes from normal allele B fractions...done 489s Normalizing betaT using betaN (TumorBoost)... 489s Normalized BAFs: 489s num [1:14670] 0.9301 0.1667 0.0685 0.0995 0.0155 ... 489s - attr(*, "modelFit")=List of 5 489s ..$ method : chr "normalizeTumorBoost" 489s ..$ flavor : chr "v4" 489s ..$ delta : num [1:14670] -0.17264 0.00239 0.1671 0.16085 0.04213 ... 489s .. ..- attr(*, "modelFit")=List of 1 489s .. .. ..$ :List of 7 489s .. .. .. ..$ flavor : chr "density" 489s .. .. .. ..$ cn : int 2 489s .. .. .. ..$ nbrOfGenotypeGroups: int 3 489s .. .. .. ..$ tau : num [1:2] 0.315 0.677 489s .. .. .. ..$ n : int 14640 489s .. .. .. ..$ fit :Classes 'PeaksAndValleys' and 'data.frame': 5 obs. of 3 variables: 489s .. .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 489s .. .. .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 489s .. .. .. .. ..$ density: num [1:5] 1.48 0.522 1.056 0.552 1.454 489s .. .. .. ..$ fitValleys :Classes 'PeaksAndValleys' and 'data.frame': 2 obs. of 3 variables: 489s .. .. .. .. ..$ type : chr [1:2] "valley" "valley" 489s .. .. .. .. ..$ x : num [1:2] 0.315 0.677 489s .. .. .. .. ..$ density: num [1:2] 0.522 0.552 489s .. .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 489s ..$ preserveScale: logi FALSE 489s ..$ scaleFactor : num NA 489s Normalizing betaT using betaN (TumorBoost)...done 489s Setup up data... 489s 'data.frame': 14670 obs. of 7 variables: 489s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 489s $ x : num 1145994 2941694 3710825 4240737 4276892 ... 489s $ CT : num 1.63 1.4 1.41 1.17 1.16 ... 489s $ betaT : num 0.7574 0.169 0.2357 0.2604 0.0576 ... 489s $ betaTN : num 0.9301 0.1667 0.0685 0.0995 0.0155 ... 489s ..- attr(*, "modelFit")=List of 5 489s .. ..$ method : chr "normalizeTumorBoost" 489s .. ..$ flavor : chr "v4" 489s .. ..$ delta : num [1:14670] -0.17264 0.00239 0.1671 0.16085 0.04213 ... 489s .. .. ..- attr(*, "modelFit")=List of 1 489s .. .. .. ..$ :List of 7 489s .. .. .. .. ..$ flavor : chr "density" 489s .. .. .. .. ..$ cn : int 2 489s .. .. .. .. ..$ nbrOfGenotypeGroups: int 3 489s .. .. .. .. ..$ tau : num [1:2] 0.315 0.677 489s .. .. .. .. ..$ n : int 14640 489s .. .. .. .. ..$ fit :Classes 'PeaksAndValleys' and 'data.frame': 5 obs. of 3 variables: 489s .. .. .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 489s .. .. .. .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 489s .. .. .. .. .. ..$ density: num [1:5] 1.48 0.522 1.056 0.552 1.454 489s .. .. .. .. ..$ fitValleys :Classes 'PeaksAndValleys' and 'data.frame': 2 obs. of 3 variables: 489s .. .. .. .. .. ..$ type : chr [1:2] "valley" "valley" 489s .. .. .. .. .. ..$ x : num [1:2] 0.315 0.677 489s .. .. .. .. .. ..$ density: num [1:2] 0.522 0.552 489s .. .. .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 489s .. ..$ preserveScale: logi FALSE 489s .. ..$ scaleFactor : num NA 489s $ betaN : num 0.8274 0.5072 0.1671 0.1609 0.0421 ... 489s $ muN : num 1 0.5 0 0 0 0 1 0 1 0.5 ... 489s ..- attr(*, "modelFit")=List of 1 489s .. ..$ :List of 7 489s .. .. ..$ flavor : chr "density" 489s .. .. ..$ cn : int 2 489s .. .. ..$ nbrOfGenotypeGroups: int 3 489s .. .. ..$ tau : num [1:2] 0.315 0.677 489s .. .. ..$ n : int 14640 489s .. .. ..$ fit :Classes 'PeaksAndValleys' and 'data.frame': 5 obs. of 3 variables: 489s .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 489s .. .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 489s .. .. .. ..$ density: num [1:5] 1.48 0.522 1.056 0.552 1.454 489s .. .. ..$ fitValleys :Classes 'PeaksAndValleys' and 'data.frame': 2 obs. of 3 variables: 489s .. .. .. ..$ type : chr [1:2] "valley" "valley" 489s .. .. .. ..$ x : num [1:2] 0.315 0.677 489s .. .. .. ..$ density: num [1:2] 0.522 0.552 489s .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 489s Setup up data...done 489s Dropping loci for which TCNs are missing... 489s Number of loci dropped: 12 489s Dropping loci for which TCNs are missing...done 489s Ordering data along genome... 489s 'data.frame': 14658 obs. of 7 variables: 489s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 489s $ x : num 554484 730720 782343 878522 916294 ... 489s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 489s $ betaT : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 489s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 489s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 489s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 489s Ordering data along genome...done 489s Keeping only current chromosome for 'knownSegments'... 489s Chromosome: 1 489s Known segments for this chromosome: 489s chromosome start end 489s 1 1 -Inf 120992603 489s 2 1 141510003 Inf 489s Keeping only current chromosome for 'knownSegments'...done 489s alphaTCN: 0.009 489s alphaDH: 0.001 489s Number of loci: 14658 489s Calculating DHs... 489s Number of SNPs: 14658 489s Number of heterozygous SNPs: 4196 (28.63%) 489s Normalized DHs: 489s num [1:14658] NA NA NA NA NA ... 489s Calculating DHs...done 489s Random seed temporarily set (seed=c(48879), kind="L'Ecuyer-CMRG") 489s Produced 2 seeds from this stream for future usage 489s Identification of change points by total copy numbers... 489s Segmenting by CBS... 489s Chromosome: 1 489s Segmenting multiple segments on current chromosome... 489s Number of segments: 2 489s Random seed temporarily set (seed=c(10407, 1066287653, -51199871, 161854402, -1995183193, 1503453565, -747102133), kind="L'Ecuyer-CMRG") 489s Produced 2 seeds from this stream for future usage 489s Segmenting by CBS... 489s Chromosome: 1 489s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 489s Segmenting by CBS...done 489s Segmenting by CBS... 489s Chromosome: 1 489s Random seed temporarily set (seed=c(10407, -821273412, -52578226, 1415511586, 721384351, -665928286, 1316562960), kind="L'Ecuyer-CMRG") 489s Segmenting by CBS...done 489s Segmenting multiple segments on current chromosome...done 489s Segmenting by CBS...done 489s List of 4 489s $ data :'data.frame': 14658 obs. of 4 variables: 489s ..$ chromosome: int [1:14658] 1 1 1 1 1 1 1 1 1 1 ... 489s ..$ x : num [1:14658] 554484 730720 782343 878522 916294 ... 489s ..$ y : num [1:14658] 1.88 1.8 1.59 1.64 1.53 ... 489s ..$ index : int [1:14658] 1 2 3 4 5 6 7 8 9 10 ... 489s $ output :'data.frame': 3 obs. of 6 variables: 489s ..$ sampleName: chr [1:3] NA NA NA 489s ..$ chromosome: int [1:3] 1 1 1 489s ..$ start : num [1:3] 5.54e+05 1.42e+08 1.85e+08 489s ..$ end : num [1:3] 1.21e+08 1.85e+08 2.47e+08 489s ..$ nbrOfLoci : int [1:3] 7586 2681 4391 489s ..$ mean : num [1:3] 1.39 2.07 2.63 489s $ segRows:'data.frame': 3 obs. of 2 variables: 489s ..$ startRow: int [1:3] 1 7587 10268 489s ..$ endRow : int [1:3] 7586 10267 14658 489s $ params :List of 5 489s ..$ alpha : num 0.009 489s ..$ undo : num 0 489s ..$ joinSegments : logi TRUE 489s ..$ knownSegments:'data.frame': 2 obs. of 3 variables: 489s .. ..$ chromosome: num [1:2] 1 1 489s .. ..$ start : num [1:2] -Inf 1.42e+08 489s .. ..$ end : num [1:2] 1.21e+08 Inf 489s ..$ seed : int [1:7] 10407 1066287653 -51199871 161854402 -1995183193 1503453565 -747102133 489s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 489s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.132 0 0.132 0 0 489s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 489s - attr(*, "pkgDetails")= chr "DNAcopy v1.76.0" 489s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 489s Identification of change points by total copy numbers...done 489s Restructure TCN segmentation results... 489s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean 489s 1 1 554484 120992603 7586 1.3853 489s 2 1 141510003 185449813 2681 2.0689 489s 3 1 185449813 247137334 4391 2.6341 489s Number of TCN segments: 3 489s Restructure TCN segmentation results...done 489s Total CN segment #1 ([ 554484,1.20993e+08]) of 3... 489s Number of TCN loci in segment: 7586 489s Locus data for TCN segment: 489s 'data.frame': 7586 obs. of 9 variables: 489s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 489s $ x : num 554484 730720 782343 878522 916294 ... 489s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 489s $ betaT : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 489s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 489s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 489s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 489s $ index : int 1 2 3 4 5 6 7 8 9 10 ... 489s $ rho : num NA NA NA NA NA ... 489s Number of loci: 7586 489s Number of SNPs: 2108 (27.79%) 489s Number of heterozygous SNPs: 2108 (100.00%) 489s Chromosome: 1 489s Segmenting DH signals... 489s Segmenting by CBS... 489s Chromosome: 1 489s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 489s Segmenting by CBS...done 489s List of 4 489s $ data :'data.frame': 7586 obs. of 4 variables: 489s ..$ chromosome: int [1:7586] 1 1 1 1 1 1 1 1 1 1 ... 489s ..$ x : num [1:7586] 554484 730720 782343 878522 916294 ... 489s ..$ y : num [1:7586] NA NA NA NA NA ... 489s ..$ index : int [1:7586] 1 2 3 4 5 6 7 8 9 10 ... 489s $ output :'data.frame': 1 obs. of 6 variables: 489s ..$ sampleName: chr NA 489s ..$ chromosome: int 1 489s ..$ start : num 554484 489s ..$ end : num 1.21e+08 489s ..$ nbrOfLoci : int 2108 489s ..$ mean : num 0.512 489s $ segRows:'data.frame': 1 obs. of 2 variables: 489s ..$ startRow: int 10 489s ..$ endRow : int 7574 489s $ params :List of 5 489s ..$ alpha : num 0.001 489s ..$ undo : num 0 489s ..$ joinSegments : logi TRUE 489s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 489s .. ..$ chromosome: int 1 489s .. ..$ start : num 554484 489s .. ..$ end : num 1.21e+08 489s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 489s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 489s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.035 0 0.034 0 0 489s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 489s - attr(*, "pkgDetails")= chr "DNAcopy v1.76.0" 489s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 489s DH segmentation (locally-indexed) rows: 489s startRow endRow 489s 1 10 7574 489s int [1:7586] 1 2 3 4 5 6 7 8 9 10 ... 489s DH segmentation rows: 489s startRow endRow 489s 1 10 7574 489s Segmenting DH signals...done 489s DH segmentation table: 489s dhStart dhEnd dhNbrOfLoci dhMean 489s 1 554484 120992603 2108 0.5116 489s startRow endRow 489s 1 10 7574 489s Rows: 489s [1] 1 489s TCN segmentation rows: 489s startRow endRow 489s 1 1 7586 489s TCN and DH segmentation rows: 489s startRow endRow 489s 1 1 7586 489s startRow endRow 489s 1 10 7574 489s NULL 489s TCN segmentation (expanded) rows: 489s startRow endRow 489s 1 1 7586 489s TCN and DH segmentation rows: 489s startRow endRow 489s 1 1 7586 489s 2 7587 10267 489s 3 10268 14658 489s startRow endRow 489s 1 10 7574 489s startRow endRow 489s 1 1 7586 489s Total CN segmentation table (expanded): 489s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 489s 1 1 554484 120992603 7586 1.3853 2108 2108 489s (TCN,DH) segmentation for one total CN segment: 489s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 489s 1 1 1 1 554484 120992603 7586 1.3853 2108 489s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 489s 1 2108 554484 120992603 2108 0.5116 489s Total CN segment #1 ([ 554484,1.20993e+08]) of 3...done 489s Total CN segment #2 ([1.4151e+08,1.8545e+08]) of 3... 489s Number of TCN loci in segment: 2681 489s Locus data for TCN segment: 489s 'data.frame': 2681 obs. of 9 variables: 489s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 489s $ x : num 1.43e+08 1.43e+08 1.43e+08 1.43e+08 1.44e+08 ... 489s $ CT : num 2.27 1.55 1.47 1.5 1.81 ... 489s $ betaT : num 0.34 0.55 0.048 0.813 0.575 ... 489s $ betaTN : num 0.441 0.629 -0.05 0.958 0.872 ... 489s $ betaN : num 0.3851 0.3933 0.0981 0.8552 0.7028 ... 489s $ muN : num 0.5 0.5 0 1 1 1 1 0.5 1 1 ... 489s $ index : int 7587 7588 7589 7590 7591 7592 7593 7594 7595 7596 ... 489s $ rho : num 0.117 0.258 NA NA NA ... 489s Number of loci: 2681 489s Number of SNPs: 777 (28.98%) 489s Number of heterozygous SNPs: 777 (100.00%) 489s Chromosome: 1 489s Segmenting DH signals... 489s Segmenting by CBS... 489s Chromosome: 1 489s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 489s Segmenting by CBS...done 489s List of 4 489s $ data :'data.frame': 2681 obs. of 4 variables: 489s ..$ chromosome: int [1:2681] 1 1 1 1 1 1 1 1 1 1 ... 489s ..$ x : num [1:2681] 1.43e+08 1.43e+08 1.43e+08 1.43e+08 1.44e+08 ... 489s ..$ y : num [1:2681] 0.117 0.258 NA NA NA ... 489s ..$ index : int [1:2681] 1 2 3 4 5 6 7 8 9 10 ... 489s $ output :'data.frame': 1 obs. of 6 variables: 489s ..$ sampleName: chr NA 489s ..$ chromosome: int 1 489s ..$ start : num 1.42e+08 489s ..$ end : num 1.85e+08 489s ..$ nbrOfLoci : int 777 489s ..$ mean : num 0.0973 489s $ segRows:'data.frame': 1 obs. of 2 variables: 489s ..$ startRow: int 1 489s ..$ endRow : int 2677 489s $ params :List of 5 489s ..$ alpha : num 0.001 489s ..$ undo : num 0 489s ..$ joinSegments : logi TRUE 489s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 489s .. ..$ chromosome: int 1 489s .. ..$ start : num 1.42e+08 489s .. ..$ end : num 1.85e+08 489s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 489s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 489s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.007 0 0.007 0 0 489s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 489s - attr(*, "pkgDetails")= chr "DNAcopy v1.76.0" 489s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 489s DH segmentation (locally-indexed) rows: 489s startRow endRow 489s 1 1 2677 489s int [1:2681] 7587 7588 7589 7590 7591 7592 7593 7594 7595 7596 ... 489s DH segmentation rows: 489s startRow endRow 489s 1 7587 10263 489s Segmenting DH signals...done 489s DH segmentation table: 489s dhStart dhEnd dhNbrOfLoci dhMean 489s 1 141510003 185449813 777 0.0973 489s startRow endRow 489s 1 7587 10263 489s Rows: 489s [1] 2 489s TCN segmentation rows: 489s startRow endRow 489s 2 7587 10267 489s TCN and DH segmentation rows: 489s startRow endRow 489s 2 7587 10267 489s startRow endRow 489s 1 7587 10263 489s startRow endRow 489s 1 1 7586 489s TCN segmentation (expanded) rows: 489s startRow endRow 489s 1 1 7586 489s 2 7587 10267 489s TCN and DH segmentation rows: 489s startRow endRow 489s 1 1 7586 489s 2 7587 10267 489s 3 10268 14658 489s startRow endRow 489s 1 10 7574 489s 2 7587 10263 489s startRow endRow 489s 1 1 7586 489s 2 7587 10267 489s Total CN segmentation table (expanded): 489s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 489s 2 1 141510003 185449813 2681 2.0689 777 777 489s (TCN,DH) segmentation for one total CN segment: 489s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 489s 2 2 1 1 141510003 185449813 2681 2.0689 777 489s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 489s 2 777 141510003 185449813 777 0.0973 489s Total CN segment #2 ([1.4151e+08,1.8545e+08]) of 3...done 489s Total CN segment #3 ([1.8545e+08,2.47137e+08]) of 3... 489s Number of TCN loci in segment: 4391 489s Locus data for TCN segment: 489s 'data.frame': 4391 obs. of 9 variables: 489s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 489s $ x : num 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 489s $ CT : num 2.93 2.15 2.82 2.93 2.46 ... 489s $ betaT : num 0.0811 0.5154 0.9473 0.3734 0.7506 ... 489s $ betaTN : num -0.169 0.609 1.028 0.525 0.968 ... 489s $ betaN : num 0.25 0.38 0.919 0.34 0.783 ... 489s $ muN : num 0 0.5 1 0.5 1 1 0 1 0 1 ... 489s $ index : int 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 489s $ rho : num NA 0.2186 NA 0.0503 NA ... 489s Number of loci: 4391 489s Number of SNPs: 1311 (29.86%) 489s Number of heterozygous SNPs: 1311 (100.00%) 489s Chromosome: 1 489s Segmenting DH signals... 489s Segmenting by CBS... 489s Chromosome: 1 489s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 489s Segmenting by CBS...done 489s List of 4 489s $ data :'data.frame': 4391 obs. of 4 variables: 489s ..$ chromosome: int [1:4391] 1 1 1 1 1 1 1 1 1 1 ... 489s ..$ x : num [1:4391] 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... 489s ..$ y : num [1:4391] NA 0.2186 NA 0.0503 NA ... 489s ..$ index : int [1:4391] 1 2 3 4 5 6 7 8 9 10 ... 489s $ output :'data.frame': 1 obs. of 6 variables: 489s ..$ sampleName: chr NA 489s ..$ chromosome: int 1 489s ..$ start : num 1.85e+08 489s ..$ end : num 2.47e+08 489s ..$ nbrOfLoci : int 1311 489s ..$ mean : num 0.23 489s $ segRows:'data.frame': 1 obs. of 2 variables: 489s ..$ startRow: int 2 489s ..$ endRow : int 4388 489s $ params :List of 5 489s ..$ alpha : num 0.001 489s ..$ undo : num 0 489s ..$ joinSegments : logi TRUE 489s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 489s .. ..$ chromosome: int 1 489s .. ..$ start : num 1.85e+08 489s .. ..$ end : num 2.47e+08 489s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 489s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 489s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.014 0 0.014 0 0 489s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 489s - attr(*, "pkgDetails")= chr "DNAcopy v1.76.0" 489s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 489s DH segmentation (locally-indexed) rows: 489s startRow endRow 489s 1 2 4388 489s int [1:4391] 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... 489s DH segmentation rows: 489s startRow endRow 489s 1 10269 14655 489s Segmenting DH signals...done 489s DH segmentation table: 489s dhStart dhEnd dhNbrOfLoci dhMean 489s 1 185449813 247137334 1311 0.2295 489s startRow endRow 489s 1 10269 14655 489s Rows: 489s [1] 3 489s TCN segmentation rows: 489s startRow endRow 489s 3 10268 14658 489s TCN and DH segmentation rows: 489s startRow endRow 489s 3 10268 14658 489s startRow endRow 489s 1 10269 14655 489s startRow endRow 489s 1 1 7586 489s 2 7587 10267 489s TCN segmentation (expanded) rows: 489s startRow endRow 489s 1 1 7586 489s 2 7587 10267 489s 3 10268 14658 489s TCN and DH segmentation rows: 489s startRow endRow 489s 1 1 7586 489s 2 7587 10267 489s 3 10268 14658 489s startRow endRow 489s 1 10 7574 489s 2 7587 10263 489s 3 10269 14655 489s startRow endRow 489s 1 1 7586 489s 2 7587 10267 489s 3 10268 14658 489s Total CN segmentation table (expanded): 489s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 489s 3 1 185449813 247137334 4391 2.6341 1311 1311 489s (TCN,DH) segmentation for one total CN segment: 489s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 489s 3 3 1 1 185449813 247137334 4391 2.6341 1311 489s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 489s 3 1311 185449813 247137334 1311 0.2295 489s Total CN segment #3 ([1.8545e+08,2.47137e+08]) of 3...done 489s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 489s 1 1 1 1 554484 120992603 7586 1.3853 2108 489s 2 1 2 1 141510003 185449813 2681 2.0689 777 489s 3 1 3 1 185449813 247137334 4391 2.6341 1311 489s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 489s 1 2108 554484 120992603 2108 0.5116 489s 2 777 141510003 185449813 777 0.0973 489s 3 1311 185449813 247137334 1311 0.2295 489s Calculating (C1,C2) per segment... 489s Calculating (C1,C2) per segment...done 489s Number of segments: 3 489s Segmenting paired tumor-normal signals using Paired PSCBS...done 489s Post-segmenting TCNs... 489s Number of segments: 3 489s Number of chromosomes: 1 489s [1] 1 489s Chromosome 1 ('chr01') of 1... 489s Rows: 489s [1] 1 2 3 489s Number of segments: 3 489s TCN segment #1 ('1') of 3... 489s Nothing todo. Only one DH segmentation. Skipping. 489s TCN segment #1 ('1') of 3...done 489s TCN segment #2 ('2') of 3... 489s Nothing todo. Only one DH segmentation. Skipping. 489s TCN segment #2 ('2') of 3...done 489s TCN segment #3 ('3') of 3... 489s Nothing todo. Only one DH segmentation. Skipping. 489s TCN segment #3 ('3') of 3...done 489s Chromosome 1 ('chr01') of 1...done 489s Update (C1,C2) per segment... 489s Update (C1,C2) per segment...done 489s Post-segmenting TCNs...done 489s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 489s 1 1 1 1 554484 120992603 7586 1.3853 2108 489s 2 1 2 1 141510003 185449813 2681 2.0689 777 489s 3 1 3 1 185449813 247137334 4391 2.6341 1311 489s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 489s 1 2108 554484 120992603 2108 0.5116 0.3382903 1.047010 489s 2 777 141510003 185449813 777 0.0973 0.9337980 1.135102 489s 3 1311 185449813 247137334 1311 0.2295 1.0147870 1.619313 489s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 489s 1 1 1 1 554484 120992603 7586 1.3853 2108 489s 2 1 2 1 141510003 185449813 2681 2.0689 777 489s 3 1 3 1 185449813 247137334 4391 2.6341 1311 489s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 489s 1 2108 554484 120992603 2108 0.5116 0.3382903 1.047010 489s 2 777 141510003 185449813 777 0.0973 0.9337980 1.135102 489s 3 1311 185449813 247137334 1311 0.2295 1.0147870 1.619313 489s > print(fit) 489s chromosome tcnId dhId start end tcnNbrOfLoci tcnMean tcnNbrOfSNPs 489s 1 1 1 1 554484 120992603 7586 1.3853 2108 489s 2 1 2 1 141510003 185449813 2681 2.0689 777 489s 3 1 3 1 185449813 247137334 4391 2.6341 1311 489s tcnNbrOfHets dhNbrOfLoci dhMean c1Mean c2Mean 489s 1 2108 2108 0.5116 0.3382903 1.047010 489s 2 777 777 0.0973 0.9337980 1.135102 489s 3 1311 1311 0.2295 1.0147870 1.619313 489s > 489s > # Plot results 489s > dev.set(4L) 489s pdf 489s 2 489s > plotTracks(fit) 489s > abline(v=c(knownSegments$start, knownSegments$end)/1e6, lty=3) 489s > 489s > # Sanity check 489s > stopifnot(nbrOfSegments(fit) == nSegs-1L) 489s > 489s > fit3 <- fit 489s > 489s > 489s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 489s > # (d) Skip the identification of new change points 489s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 489s > knownSegments <- data.frame( 489s + chromosome = c( 1, 1), 489s + start = c( -Inf, 141510003), 489s + end = c(120992603, +Inf) 489s + ) 489s > 489s > # Paired PSCBS segmentation 489s > fit <- segmentByPairedPSCBS(dataS, knownSegments=knownSegments, 489s + undoTCN=Inf, undoDH=Inf, 489s + seed=0xBEEF, verbose=-10) 489s Segmenting paired tumor-normal signals using Paired PSCBS... 489s Calling genotypes from normal allele B fractions... 489s num [1:14670] 0.8274 0.5072 0.1671 0.1609 0.0421 ... 489s Called genotypes: 489s num [1:14670] 1 0.5 0 0 0 0 1 0 1 0.5 ... 489s - attr(*, "modelFit")=List of 1 489s ..$ :List of 7 489s .. ..$ flavor : chr "density" 489s .. ..$ cn : int 2 489s .. ..$ nbrOfGenotypeGroups: int 3 489s .. ..$ tau : num [1:2] 0.315 0.677 489s .. ..$ n : int 14640 489s .. ..$ fit :Classes 'PeaksAndValleys' and 'data.frame': 5 obs. of 3 variables: 489s .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 489s .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 489s .. .. ..$ density: num [1:5] 1.48 0.522 1.056 0.552 1.454 489s .. ..$ fitValleys :Classes 'PeaksAndValleys' and 'data.frame': 2 obs. of 3 variables: 489s .. .. ..$ type : chr [1:2] "valley" "valley" 489s .. .. ..$ x : num [1:2] 0.315 0.677 489s .. .. ..$ density: num [1:2] 0.522 0.552 489s ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 489s muN 489s 0 0.5 1 489s 5221 4198 5251 489s Calling genotypes from normal allele B fractions...done 489s Normalizing betaT using betaN (TumorBoost)... 489s Normalized BAFs: 489s num [1:14670] 0.9301 0.1667 0.0685 0.0995 0.0155 ... 489s - attr(*, "modelFit")=List of 5 489s ..$ method : chr "normalizeTumorBoost" 489s ..$ flavor : chr "v4" 489s ..$ delta : num [1:14670] -0.17264 0.00239 0.1671 0.16085 0.04213 ... 489s .. ..- attr(*, "modelFit")=List of 1 489s .. .. ..$ :List of 7 489s .. .. .. ..$ flavor : chr "density" 489s .. .. .. ..$ cn : int 2 489s .. .. .. ..$ nbrOfGenotypeGroups: int 3 489s .. .. .. ..$ tau : num [1:2] 0.315 0.677 489s .. .. .. ..$ n : int 14640 489s .. .. .. ..$ fit :Classes 'PeaksAndValleys' and 'data.frame': 5 obs. of 3 variables: 489s .. .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 489s .. .. .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 489s .. .. .. .. ..$ density: num [1:5] 1.48 0.522 1.056 0.552 1.454 489s .. .. .. ..$ fitValleys :Classes 'PeaksAndValleys' and 'data.frame': 2 obs. of 3 variables: 489s .. .. .. .. ..$ type : chr [1:2] "valley" "valley" 489s .. .. .. .. ..$ x : num [1:2] 0.315 0.677 489s .. .. .. .. ..$ density: num [1:2] 0.522 0.552 489s .. .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 489s ..$ preserveScale: logi FALSE 489s ..$ scaleFactor : num NA 489s Normalizing betaT using betaN (TumorBoost)...done 489s Setup up data... 489s 'data.frame': 14670 obs. of 7 variables: 489s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 489s $ x : num 1145994 2941694 3710825 4240737 4276892 ... 489s $ CT : num 1.63 1.4 1.41 1.17 1.16 ... 489s $ betaT : num 0.7574 0.169 0.2357 0.2604 0.0576 ... 489s $ betaTN : num 0.9301 0.1667 0.0685 0.0995 0.0155 ... 489s ..- attr(*, "modelFit")=List of 5 489s .. ..$ method : chr "normalizeTumorBoost" 489s .. ..$ flavor : chr "v4" 489s .. ..$ delta : num [1:14670] -0.17264 0.00239 0.1671 0.16085 0.04213 ... 489s .. .. ..- attr(*, "modelFit")=List of 1 489s .. .. .. ..$ :List of 7 489s .. .. .. .. ..$ flavor : chr "density" 489s .. .. .. .. ..$ cn : int 2 489s .. .. .. .. ..$ nbrOfGenotypeGroups: int 3 489s .. .. .. .. ..$ tau : num [1:2] 0.315 0.677 489s .. .. .. .. ..$ n : int 14640 489s .. .. .. .. ..$ fit :Classes 'PeaksAndValleys' and 'data.frame': 5 obs. of 3 variables: 489s .. .. .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 489s .. .. .. .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 489s .. .. .. .. .. ..$ density: num [1:5] 1.48 0.522 1.056 0.552 1.454 489s .. .. .. .. ..$ fitValleys :Classes 'PeaksAndValleys' and 'data.frame': 2 obs. of 3 variables: 489s .. .. .. .. .. ..$ type : chr [1:2] "valley" "valley" 489s .. .. .. .. .. ..$ x : num [1:2] 0.315 0.677 489s .. .. .. .. .. ..$ density: num [1:2] 0.522 0.552 489s .. .. .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 489s .. ..$ preserveScale: logi FALSE 489s .. ..$ scaleFactor : num NA 489s $ betaN : num 0.8274 0.5072 0.1671 0.1609 0.0421 ... 489s $ muN : num 1 0.5 0 0 0 0 1 0 1 0.5 ... 489s ..- attr(*, "modelFit")=List of 1 489s .. ..$ :List of 7 489s .. .. ..$ flavor : chr "density" 489s .. .. ..$ cn : int 2 489s .. .. ..$ nbrOfGenotypeGroups: int 3 489s .. .. ..$ tau : num [1:2] 0.315 0.677 489s .. .. ..$ n : int 14640 489s .. .. ..$ fit :Classes 'PeaksAndValleys' and 'data.frame': 5 obs. of 3 variables: 489s .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... 489s .. .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 489s .. .. .. ..$ density: num [1:5] 1.48 0.522 1.056 0.552 1.454 489s .. .. ..$ fitValleys :Classes 'PeaksAndValleys' and 'data.frame': 2 obs. of 3 variables: 489s .. .. .. ..$ type : chr [1:2] "valley" "valley" 489s .. .. .. ..$ x : num [1:2] 0.315 0.677 489s .. .. .. ..$ density: num [1:2] 0.522 0.552 489s .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" 489s Setup up data...done 489s Dropping loci for which TCNs are missing... 489s Number of loci dropped: 12 489s Dropping loci for which TCNs are missing...done 489s Ordering data along genome... 489s 'data.frame': 14658 obs. of 7 variables: 489s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 489s $ x : num 554484 730720 782343 878522 916294 ... 489s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 489s $ betaT : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 489s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 489s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 489s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 489s Ordering data along genome...done 489s Keeping only current chromosome for 'knownSegments'... 489s Chromosome: 1 489s Known segments for this chromosome: 489s chromosome start end 489s 1 1 -Inf 120992603 489s 2 1 141510003 Inf 489s Keeping only current chromosome for 'knownSegments'...done 489s alphaTCN: 0.009 489s alphaDH: 0.001 489s Number of loci: 14658 489s Calculating DHs... 489s Number of SNPs: 14658 489s Number of heterozygous SNPs: 4196 (28.63%) 489s Normalized DHs: 489s num [1:14658] NA NA NA NA NA ... 489s Calculating DHs...done 489s Random seed temporarily set (seed=c(48879), kind="L'Ecuyer-CMRG") 489s Produced 2 seeds from this stream for future usage 489s Identification of change points by total copy numbers... 489s Segmenting by CBS... 489s Chromosome: 1 489s Segmenting multiple segments on current chromosome... 489s Number of segments: 2 489s Random seed temporarily set (seed=c(10407, 1066287653, -51199871, 161854402, -1995183193, 1503453565, -747102133), kind="L'Ecuyer-CMRG") 489s Produced 2 seeds from this stream for future usage 489s Segmenting by CBS... 489s Chromosome: 1 489s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 489s Segmenting by CBS...done 489s Segmenting by CBS... 489s Chromosome: 1 489s Random seed temporarily set (seed=c(10407, -821273412, -52578226, 1415511586, 721384351, -665928286, 1316562960), kind="L'Ecuyer-CMRG") 489s Segmenting by CBS...done 489s Segmenting multiple segments on current chromosome...done 489s Segmenting by CBS...done 489s List of 4 489s $ data :'data.frame': 14658 obs. of 4 variables: 489s ..$ chromosome: int [1:14658] 1 1 1 1 1 1 1 1 1 1 ... 489s ..$ x : num [1:14658] 554484 730720 782343 878522 916294 ... 489s ..$ y : num [1:14658] 1.88 1.8 1.59 1.64 1.53 ... 489s ..$ index : int [1:14658] 1 2 3 4 5 6 7 8 9 10 ... 489s $ output :'data.frame': 2 obs. of 6 variables: 489s ..$ sampleName: chr [1:2] NA NA 489s ..$ chromosome: num [1:2] 1 1 489s ..$ start : num [1:2] 5.54e+05 1.42e+08 489s ..$ end : num [1:2] 1.21e+08 2.47e+08 489s ..$ nbrOfLoci : int [1:2] 7586 7072 489s ..$ mean : num [1:2] 1.39 2.42 489s $ segRows:'data.frame': 2 obs. of 2 variables: 489s ..$ startRow: int [1:2] 1 7587 489s ..$ endRow : int [1:2] 7586 14658 489s $ params :List of 7 489s ..$ undo.splits : chr "sdundo" 489s ..$ undo.SD : num Inf 489s ..$ alpha : num 0.009 489s ..$ undo : num Inf 489s ..$ joinSegments : logi TRUE 489s ..$ knownSegments:'data.frame': 2 obs. of 3 variables: 489s .. ..$ chromosome: num [1:2] 1 1 489s .. ..$ start : num [1:2] -Inf 1.42e+08 489s .. ..$ end : num [1:2] 1.21e+08 Inf 489s ..$ seed : int [1:7] 10407 1066287653 -51199871 161854402 -1995183193 1503453565 -747102133 489s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 489s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.001 0 0.001 0 0 489s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 489s - attr(*, "pkgDetails")= chr "DNAcopy v1.76.0" 489s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 489s Identification of change points by total copy numbers...done 489s Restructure TCN segmentation results... 489s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean 489s 1 1 554484 120992603 7586 1.385258 489s 2 1 141510003 247137334 7072 2.419824 489s Number of TCN segments: 2 489s Restructure TCN segmentation results...done 489s Total CN segment #1 ([ 554484,1.20993e+08]) of 2... 489s Number of TCN loci in segment: 7586 489s Locus data for TCN segment: 489s 'data.frame': 7586 obs. of 9 variables: 489s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 489s $ x : num 554484 730720 782343 878522 916294 ... 489s $ CT : num 1.88 1.8 1.59 1.64 1.53 ... 489s $ betaT : num 0.0646 0.1672 0.9284 0.113 0.7209 ... 489s $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... 489s $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... 489s $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... 489s $ index : int 1 2 3 4 5 6 7 8 9 10 ... 489s $ rho : num NA NA NA NA NA ... 489s Number of loci: 7586 489s Number of SNPs: 2108 (27.79%) 489s Number of heterozygous SNPs: 2108 (100.00%) 489s Chromosome: 1 489s Segmenting DH signals... 489s Segmenting by CBS... 489s Chromosome: 1 489s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 489s Segmenting by CBS...done 489s List of 4 489s $ data :'data.frame': 7586 obs. of 4 variables: 489s ..$ chromosome: int [1:7586] 1 1 1 1 1 1 1 1 1 1 ... 489s ..$ x : num [1:7586] 554484 730720 782343 878522 916294 ... 489s ..$ y : num [1:7586] NA NA NA NA NA ... 489s ..$ index : int [1:7586] 1 2 3 4 5 6 7 8 9 10 ... 489s $ output :'data.frame': 1 obs. of 6 variables: 489s ..$ sampleName: chr NA 489s ..$ chromosome: int 1 489s ..$ start : num 554484 489s ..$ end : num 1.21e+08 489s ..$ nbrOfLoci : int 7586 489s ..$ mean : num 0.512 489s $ segRows:'data.frame': 1 obs. of 2 variables: 489s ..$ startRow: int 1 489s ..$ endRow : int 7586 489s $ params :List of 7 489s ..$ undo.splits : chr "sdundo" 489s ..$ undo.SD : num Inf 489s ..$ alpha : num 0.001 489s ..$ undo : num Inf 489s ..$ joinSegments : logi TRUE 489s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 489s .. ..$ chromosome: int 1 489s .. ..$ start : num 554484 489s .. ..$ end : num 1.21e+08 489s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 489s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 489s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.001 0 0.001 0 0 489s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 489s - attr(*, "pkgDetails")= chr "DNAcopy v1.76.0" 489s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 489s DH segmentation (locally-indexed) rows: 489s startRow endRow 489s 1 1 7586 489s int [1:7586] 1 2 3 4 5 6 7 8 9 10 ... 489s DH segmentation rows: 489s startRow endRow 489s 1 1 7586 489s Segmenting DH signals...done 489s DH segmentation table: 489s dhStart dhEnd dhNbrOfLoci dhMean 489s 1 554484 120992603 7586 0.511612 489s startRow endRow 489s 1 1 7586 489s Rows: 489s [1] 1 489s TCN segmentation rows: 489s startRow endRow 489s 1 1 7586 489s TCN and DH segmentation rows: 489s startRow endRow 489s 1 1 7586 489s startRow endRow 489s 1 1 7586 489s NULL 489s TCN segmentation (expanded) rows: 489s startRow endRow 489s 1 1 7586 489s TCN and DH segmentation rows: 489s startRow endRow 489s 1 1 7586 489s 2 7587 14658 489s startRow endRow 489s 1 1 7586 489s startRow endRow 489s 1 1 7586 489s Total CN segmentation table (expanded): 489s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 489s 1 1 554484 120992603 7586 1.385258 2108 2108 489s (TCN,DH) segmentation for one total CN segment: 489s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 489s 1 1 1 1 554484 120992603 7586 1.385258 2108 489s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 489s 1 2108 554484 120992603 7586 0.511612 489s Total CN segment #1 ([ 554484,1.20993e+08]) of 2...done 489s Total CN segment #2 ([1.4151e+08,2.47137e+08]) of 2... 489s Number of TCN loci in segment: 7072 489s Locus data for TCN segment: 489s 'data.frame': 7072 obs. of 9 variables: 489s $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... 489s $ x : num 1.43e+08 1.43e+08 1.43e+08 1.43e+08 1.44e+08 ... 489s $ CT : num 2.27 1.55 1.47 1.5 1.81 ... 489s $ betaT : num 0.34 0.55 0.048 0.813 0.575 ... 489s $ betaTN : num 0.441 0.629 -0.05 0.958 0.872 ... 489s $ betaN : num 0.3851 0.3933 0.0981 0.8552 0.7028 ... 489s $ muN : num 0.5 0.5 0 1 1 1 1 0.5 1 1 ... 489s $ index : int 7587 7588 7589 7590 7591 7592 7593 7594 7595 7596 ... 489s $ rho : num 0.117 0.258 NA NA NA ... 489s Number of loci: 7072 489s Number of SNPs: 2088 (29.52%) 489s Number of heterozygous SNPs: 2088 (100.00%) 489s Chromosome: 1 489s Segmenting DH signals... 489s Segmenting by CBS... 489s Chromosome: 1 489s Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") 489s Segmenting by CBS...done 489s List of 4 489s $ data :'data.frame': 7072 obs. of 4 variables: 489s ..$ chromosome: int [1:7072] 1 1 1 1 1 1 1 1 1 1 ... 489s ..$ x : num [1:7072] 1.43e+08 1.43e+08 1.43e+08 1.43e+08 1.44e+08 ... 489s ..$ y : num [1:7072] 0.117 0.258 NA NA NA ... 489s ..$ index : int [1:7072] 1 2 3 4 5 6 7 8 9 10 ... 489s $ output :'data.frame': 1 obs. of 6 variables: 489s ..$ sampleName: chr NA 489s ..$ chromosome: int 1 489s ..$ start : num 1.42e+08 489s ..$ end : num 2.47e+08 489s ..$ nbrOfLoci : int 7072 489s ..$ mean : num 0.18 489s $ segRows:'data.frame': 1 obs. of 2 variables: 489s ..$ startRow: int 1 489s ..$ endRow : int 7072 489s $ params :List of 7 489s ..$ undo.splits : chr "sdundo" 489s ..$ undo.SD : num Inf 489s ..$ alpha : num 0.001 489s ..$ undo : num Inf 489s ..$ joinSegments : logi TRUE 489s ..$ knownSegments:'data.frame': 1 obs. of 3 variables: 489s .. ..$ chromosome: int 1 489s .. ..$ start : num 1.42e+08 489s .. ..$ end : num 2.47e+08 489s ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 489s - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" 489s - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.002 0 0.001 0 0 489s ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... 489s - attr(*, "pkgDetails")= chr "DNAcopy v1.76.0" 489s - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 489s DH segmentation (locally-indexed) rows: 489s startRow endRow 489s 1 1 7072 489s int [1:7072] 7587 7588 7589 7590 7591 7592 7593 7594 7595 7596 ... 489s DH segmentation rows: 489s startRow endRow 489s 1 7587 14658 489s Segmenting DH signals...done 489s DH segmentation table: 489s dhStart dhEnd dhNbrOfLoci dhMean 489s 1 141510003 247137334 7072 0.1803011 489s startRow endRow 489s 1 7587 14658 489s Rows: 489s [1] 2 489s TCN segmentation rows: 489s startRow endRow 489s 2 7587 14658 489s TCN and DH segmentation rows: 489s startRow endRow 489s 2 7587 14658 489s startRow endRow 489s 1 7587 14658 489s startRow endRow 489s 1 1 7586 489s TCN segmentation (expanded) rows: 489s startRow endRow 489s 1 1 7586 489s 2 7587 14658 489s TCN and DH segmentation rows: 489s startRow endRow 489s 1 1 7586 489s 2 7587 14658 489s startRow endRow 489s 1 1 7586 489s 2 7587 14658 489s startRow endRow 489s 1 1 7586 489s 2 7587 14658 489s Total CN segmentation table (expanded): 489s chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 489s 2 1 141510003 247137334 7072 2.419824 2088 489s tcnNbrOfHets 489s 2 2088 489s (TCN,DH) segmentation for one total CN segment: 489s tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 489s 2 2 1 1 141510003 247137334 7072 2.419824 2088 489s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 489s 2 2088 141510003 247137334 7072 0.1803011 489s Total CN segment #2 ([1.4151e+08,2.47137e+08]) of 2...done 489s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 489s 1 1 1 1 554484 120992603 7586 1.385258 2108 489s 2 1 2 1 141510003 247137334 7072 2.419824 2088 489s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 489s 1 2108 554484 120992603 7586 0.5116120 489s 2 2088 141510003 247137334 7072 0.1803011 489s Calculating (C1,C2) per segment... 489s Calculating (C1,C2) per segment...done 489s Number of segments: 2 489s Segmenting paired tumor-normal signals using Paired PSCBS...done 489s Post-segmenting TCNs... 489s Number of segments: 2 489s Number of chromosomes: 1 489s [1] 1 489s Chromosome 1 ('chr01') of 1... 489s Rows: 489s [1] 1 2 489s Number of segments: 2 489s TCN segment #1 ('1') of 2... 489s Nothing todo. Only one DH segmentation. Skipping. 489s TCN segment #1 ('1') of 2...done 489s TCN segment #2 ('2') of 2... 489s Nothing todo. Only one DH segmentation. Skipping. 489s TCN segment #2 ('2') of 2...done 489s Chromosome 1 ('chr01') of 1...done 489s Update (C1,C2) per segment... 489s Update (C1,C2) per segment...done 489s Post-segmenting TCNs...done 489s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 489s 1 1 1 1 554484 120992603 7586 1.385258 2108 489s 2 1 2 1 141510003 247137334 7072 2.419824 2088 489s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 489s 1 2108 554484 120992603 7586 0.5116120 0.3382717 1.046986 489s 2 2088 141510003 247137334 7072 0.1803011 0.9917635 1.428060 489s chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 489s 1 1 1 1 554484 120992603 7586 1.385258 2108 489s 2 1 2 1 141510003 247137334 7072 2.419824 2088 489s tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 489s 1 2108 554484 120992603 7586 0.5116120 0.3382717 1.046986 489s 2 2088 141510003 247137334 7072 0.1803011 0.9917635 1.428060 489s > print(fit) 489s chromosome tcnId dhId start end tcnNbrOfLoci tcnMean tcnNbrOfSNPs 489s 1 1 1 1 554484 120992603 7586 1.385258 2108 489s 2 1 2 1 141510003 247137334 7072 2.419824 2088 489s tcnNbrOfHets dhNbrOfLoci dhMean c1Mean c2Mean 489s 1 2108 7586 0.5116120 0.3382717 1.046986 489s 2 2088 7072 0.1803011 0.9917635 1.428060 489s > 489s > # Plot results 489s > dev.set(5L) 489s pdf 489s 2 489s > plotTracks(fit) 489s > abline(v=c(knownSegments$start, knownSegments$end)/1e6, lty=3) 489s > 489s > # Sanity check 489s > stopifnot(nbrOfSegments(fit) == nrow(knownSegments)) 489s > 489s > fit4 <- fit 489s > 489s > 489s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 489s > # Tiling multiple chromosomes 489s > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 489s > # Simulate multiple chromosomes 489s > fit1 <- fit 489s > fit2 <- renameChromosomes(fit, from=1, to=2) 489s > fitM <- c(fit1, fit2) 489s > 489s > # Tile chromosomes 489s > fitT <- tileChromosomes(fitM) 489s > fitTb <- tileChromosomes(fitT) 489s > stopifnot(identical(fitTb, fitT)) 489s > 489s > # Plotting multiple chromosomes 489s > plotTracks(fitT) 489s > 489s > proc.time() 489s user system elapsed 489s 4.700 0.121 4.811 489s Test segmentByPairedPSCBS passed 489s 0 489s Begin test weightedQuantile 491s + cat weightedQuantile.Rout 491s + [ 0 != 0 ] 491s + echo Test weightedQuantile passed 491s + echo 0 491s 491s R version 4.3.2 (2023-10-31) -- "Eye Holes" 491s Copyright (C) 2023 The R Foundation for Statistical Computing 491s Platform: x86_64-pc-linux-gnu (64-bit) 491s 491s R is free software and comes with ABSOLUTELY NO WARRANTY. 491s You are welcome to redistribute it under certain conditions. 491s Type 'license()' or 'licence()' for distribution details. 491s 491s R is a collaborative project with many contributors. 491s Type 'contributors()' for more information and 491s 'citation()' on how to cite R or R packages in publications. 491s 491s Type 'demo()' for some demos, 'help()' for on-line help, or 491s 'help.start()' for an HTML browser interface to help. 491s Type 'q()' to quit R. 491s 491s [Previously saved workspace restored] 491s 491s > library("PSCBS") 491s PSCBS v0.66.0 (2021-10-23 07:40:02 UTC) successfully loaded. See ?PSCBS for help. 491s 491s Attaching package: 'PSCBS' 491s 491s The following objects are masked from 'package:base': 491s 491s append, load 491s 491s > library("stats") 491s > 491s > message("weightedQuantile() ...") 491s weightedQuantile() ... 491s > 491s > if (requireNamespace("Hmisc")) { 491s + message(" - assert identical results to Hmisc::wtd.quantile()") 491s + wtd.quantile <- Hmisc::wtd.quantile 491s + for (kk in 1:100) { 491s + n <- 5L + sample.int(995, size = 1L) 491s + x <- rnorm(n, mean = 0.0, sd = 1.0) 491s + w <- runif(n, min = 0.5, max = 2.0) ## Non-normalized weights 491s + probs <- c(0.0, 0.25, 0.50, 0.75, 1.0) 491s + q0 <- wtd.quantile(x, weights = w, probs = probs, normwt = TRUE) 491s + q <- weightedQuantile(x, w = w, probs = probs) 491s + if (!isTRUE(all.equal(q, q0))) { 491s + print(q0) 491s + print(q) 491s + stopifnot(all.equal(q, q0)) 491s + } 491s + } 491s + } 491s Loading required namespace: Hmisc 491s - assert identical results to Hmisc::wtd.quantile() 491s > 491s > message("weightedQuantile() ... DONE") 491s weightedQuantile() ... DONE 491s > 491s > proc.time() 491s user system elapsed 491s 1.376 0.118 1.488 491s Test weightedQuantile passed 491s 0 491s + rm -f /tmp/autopkgtest.KUoiFr/autopkgtest_tmp/PairedPSCBS,boot.R /tmp/autopkgtest.KUoiFr/autopkgtest_tmp/PairedPSCBS,boot.Rout /tmp/autopkgtest.KUoiFr/autopkgtest_tmp/Rplots.pdf /tmp/autopkgtest.KUoiFr/autopkgtest_tmp/findLargeGaps.R /tmp/autopkgtest.KUoiFr/autopkgtest_tmp/findLargeGaps.Rout /tmp/autopkgtest.KUoiFr/autopkgtest_tmp/randomSeed.R /tmp/autopkgtest.KUoiFr/autopkgtest_tmp/randomSeed.Rout /tmp/autopkgtest.KUoiFr/autopkgtest_tmp/segmentByCBS,calls.R /tmp/autopkgtest.KUoiFr/autopkgtest_tmp/segmentByCBS,calls.Rout /tmp/autopkgtest.KUoiFr/autopkgtest_tmp/segmentByCBS,futures.R /tmp/autopkgtest.KUoiFr/autopkgtest_tmp/segmentByCBS,futures.Rout /tmp/autopkgtest.KUoiFr/autopkgtest_tmp/segmentByCBS,median.R /tmp/autopkgtest.KUoiFr/autopkgtest_tmp/segmentByCBS,median.Rout /tmp/autopkgtest.KUoiFr/autopkgtest_tmp/segmentByCBS,prune.R /tmp/autopkgtest.KUoiFr/autopkgtest_tmp/segmentByCBS,prune.Rout /tmp/autopkgtest.KUoiFr/autopkgtest_tmp/segmentByCBS,report.R /tmp/autopkgtest.KUoiFr/autopkgtest_tmp/segmentByCBS,report.Rout /tmp/autopkgtest.KUoiFr/autopkgtest_tmp/segmentByCBS,shiftTCN.R /tmp/autopkgtest.KUoiFr/autopkgtest_tmp/segmentByCBS,shiftTCN.Rout /tmp/autopkgtest.KUoiFr/autopkgtest_tmp/segmentByCBS,weights.R /tmp/autopkgtest.KUoiFr/autopkgtest_tmp/segmentByCBS,weights.Rout /tmp/autopkgtest.KUoiFr/autopkgtest_tmp/segmentByCBS.R /tmp/autopkgtest.KUoiFr/autopkgtest_tmp/segmentByCBS.Rout /tmp/autopkgtest.KUoiFr/autopkgtest_tmp/segmentByNonPairedPSCBS,medianDH.R /tmp/autopkgtest.KUoiFr/autopkgtest_tmp/segmentByNonPairedPSCBS,medianDH.Rout /tmp/autopkgtest.KUoiFr/autopkgtest_tmp/segmentByPairedPSCBS,DH.R /tmp/autopkgtest.KUoiFr/autopkgtest_tmp/segmentByPairedPSCBS,DH.Rout /tmp/autopkgtest.KUoiFr/autopkgtest_tmp/segmentByPairedPSCBS,calls.R /tmp/autopkgtest.KUoiFr/autopkgtest_tmp/segmentByPairedPSCBS,calls.Rout /tmp/autopkgtest.KUoiFr/autopkgtest_tmp/segmentByPairedPSCBS,futures.R /tmp/autopkgtest.KUoiFr/autopkgtest_tmp/segmentByPairedPSCBS,futures.Rout /tmp/autopkgtest.KUoiFr/autopkgtest_tmp/segmentByPairedPSCBS,noNormalBAFs.R /tmp/autopkgtest.KUoiFr/autopkgtest_tmp/segmentByPairedPSCBS,noNormalBAFs.Rout /tmp/autopkgtest.KUoiFr/autopkgtest_tmp/segmentByPairedPSCBS,report.R /tmp/autopkgtest.KUoiFr/autopkgtest_tmp/segmentByPairedPSCBS,report.Rout /tmp/autopkgtest.KUoiFr/autopkgtest_tmp/segmentByPairedPSCBS,seqOfSegmentsByDP.R /tmp/autopkgtest.KUoiFr/autopkgtest_tmp/segmentByPairedPSCBS,seqOfSegmentsByDP.Rout /tmp/autopkgtest.KUoiFr/autopkgtest_tmp/segmentByPairedPSCBS.R /tmp/autopkgtest.KUoiFr/autopkgtest_tmp/segmentByPairedPSCBS.Rout /tmp/autopkgtest.KUoiFr/autopkgtest_tmp/weightedQuantile.R /tmp/autopkgtest.KUoiFr/autopkgtest_tmp/weightedQuantile.Rout 492s autopkgtest [13:45:42]: test run-unit-test: -----------------------] 492s run-unit-test PASS 492s autopkgtest [13:45:43]: test run-unit-test: - - - - - - - - - - results - - - - - - - - - - 492s autopkgtest [13:45:43]: @@@@@@@@@@@@@@@@@@@@ summary 492s run-unit-test PASS 503s Creating nova instance adt-noble-i386-r-cran-pscbs-20240323-133731-juju-7f2275-prod-proposed-migration-environment-2 from image adt/ubuntu-noble-amd64-server-20240323.img (UUID 5df8a563-0957-4fdd-8453-862df650aaf8)...