R Under development (unstable) (2024-02-16 r85931 ucrt) -- "Unsuffered Consequences" Copyright (C) 2024 The R Foundation for Statistical Computing Platform: x86_64-w64-mingw32/x64 R is free software and comes with ABSOLUTELY NO WARRANTY. You are welcome to redistribute it under certain conditions. Type 'license()' or 'licence()' for distribution details. R is a collaborative project with many contributors. Type 'contributors()' for more information and 'citation()' on how to cite R or R packages in publications. Type 'demo()' for some demos, 'help()' for on-line help, or 'help.start()' for an HTML browser interface to help. Type 'q()' to quit R. > ########################################################### > # This tests: > # - segmentByPairedPSCBS(...) > # - segmentByPairedPSCBS(..., knownSegments) > # - tileChromosomes() > # - plotTracks() > ########################################################### > library("PSCBS") PSCBS v0.67.0 successfully loaded. See ?PSCBS for help. > > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - > # Load SNP microarray data > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - > data <- PSCBS::exampleData("paired.chr01") > > > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - > # Paired PSCBS segmentation > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - > # Drop single-locus outliers > dataS <- dropSegmentationOutliers(data) > > # Run light-weight tests by default > if (Sys.getenv("_R_CHECK_FULL_") == "") { + # Use only every 5th data point + dataS <- dataS[seq(from=1, to=nrow(data), by=5),] + # Number of segments (for assertion) + nSegs <- 4L + } else { + # Full tests + nSegs <- 11L + } > > str(dataS) 'data.frame': 14670 obs. of 6 variables: $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... $ x : int 1145994 2941694 3710825 4240737 4276892 4464544 4714611 5095111 5034491 5158416 ... $ CT : num 1.63 1.4 1.41 1.17 1.16 ... $ betaT : num 0.7574 0.169 0.2357 0.2604 0.0576 ... $ CN : num 2.36 2.13 2.26 2.01 2.32 ... $ betaN : num 0.8274 0.5072 0.1671 0.1609 0.0421 ... > > fig <- 1 > > > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - > # (a) Don't segment the centromere (and force a separator) > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - > knownSegments <- data.frame( + chromosome = c( 1, 1, 1), + start = c( -Inf, NA, 141510003), + end = c(120992603, NA, +Inf) + ) > > > # Paired PSCBS segmentation > fit <- segmentByPairedPSCBS(dataS, knownSegments=knownSegments, + seed=0xBEEF, verbose=-10) Segmenting paired tumor-normal signals using Paired PSCBS... Calling genotypes from normal allele B fractions... num [1:14670] 0.8274 0.5072 0.1671 0.1609 0.0421 ... Called genotypes: num [1:14670] 1 0.5 0 0 0 0 1 0 1 0.5 ... - attr(*, "modelFit")=List of 1 ..$ :List of 7 .. ..$ flavor : chr "density" .. ..$ cn : int 2 .. ..$ nbrOfGenotypeGroups: int 3 .. ..$ tau : num [1:2] 0.315 0.677 .. ..$ n : int 14640 .. ..$ fit :Classes 'PeaksAndValleys' and 'data.frame': 5 obs. of 3 variables: .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 .. ..$ fitValleys :Classes 'PeaksAndValleys' and 'data.frame': 2 obs. of 3 variables: .. .. ..$ type : chr [1:2] "valley" "valley" .. .. ..$ x : num [1:2] 0.315 0.677 .. .. ..$ density: num [1:2] 0.522 0.551 ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" muN 0 0.5 1 5221 4198 5251 Calling genotypes from normal allele B fractions...done Normalizing betaT using betaN (TumorBoost)... Normalized BAFs: num [1:14670] 0.9301 0.1667 0.0685 0.0995 0.0155 ... - attr(*, "modelFit")=List of 5 ..$ method : chr "normalizeTumorBoost" ..$ flavor : chr "v4" ..$ delta : num [1:14670] -0.17264 0.00239 0.1671 0.16085 0.04213 ... .. ..- attr(*, "modelFit")=List of 1 .. .. ..$ :List of 7 .. .. .. ..$ flavor : chr "density" .. .. .. ..$ cn : int 2 .. .. .. ..$ nbrOfGenotypeGroups: int 3 .. .. .. ..$ tau : num [1:2] 0.315 0.677 .. .. .. ..$ n : int 14640 .. .. .. ..$ fit :Classes 'PeaksAndValleys' and 'data.frame': 5 obs. of 3 variables: .. .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... .. .. .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 .. .. .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 .. .. .. ..$ fitValleys :Classes 'PeaksAndValleys' and 'data.frame': 2 obs. of 3 variables: .. .. .. .. ..$ type : chr [1:2] "valley" "valley" .. .. .. .. ..$ x : num [1:2] 0.315 0.677 .. .. .. .. ..$ density: num [1:2] 0.522 0.551 .. .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" ..$ preserveScale: logi FALSE ..$ scaleFactor : num NA Normalizing betaT using betaN (TumorBoost)...done Setup up data... 'data.frame': 14670 obs. of 7 variables: $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... $ x : num 1145994 2941694 3710825 4240737 4276892 ... $ CT : num 1.63 1.4 1.41 1.17 1.16 ... $ betaT : num 0.7574 0.169 0.2357 0.2604 0.0576 ... $ betaTN : num 0.9301 0.1667 0.0685 0.0995 0.0155 ... ..- attr(*, "modelFit")=List of 5 .. ..$ method : chr "normalizeTumorBoost" .. ..$ flavor : chr "v4" .. ..$ delta : num [1:14670] -0.17264 0.00239 0.1671 0.16085 0.04213 ... .. .. ..- attr(*, "modelFit")=List of 1 .. .. .. ..$ :List of 7 .. .. .. .. ..$ flavor : chr "density" .. .. .. .. ..$ cn : int 2 .. .. .. .. ..$ nbrOfGenotypeGroups: int 3 .. .. .. .. ..$ tau : num [1:2] 0.315 0.677 .. .. .. .. ..$ n : int 14640 .. .. .. .. ..$ fit :Classes 'PeaksAndValleys' and 'data.frame': 5 obs. of 3 variables: .. .. .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... .. .. .. .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 .. .. .. .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 .. .. .. .. ..$ fitValleys :Classes 'PeaksAndValleys' and 'data.frame': 2 obs. of 3 variables: .. .. .. .. .. ..$ type : chr [1:2] "valley" "valley" .. .. .. .. .. ..$ x : num [1:2] 0.315 0.677 .. .. .. .. .. ..$ density: num [1:2] 0.522 0.551 .. .. .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" .. ..$ preserveScale: logi FALSE .. ..$ scaleFactor : num NA $ betaN : num 0.8274 0.5072 0.1671 0.1609 0.0421 ... $ muN : num 1 0.5 0 0 0 0 1 0 1 0.5 ... ..- attr(*, "modelFit")=List of 1 .. ..$ :List of 7 .. .. ..$ flavor : chr "density" .. .. ..$ cn : int 2 .. .. ..$ nbrOfGenotypeGroups: int 3 .. .. ..$ tau : num [1:2] 0.315 0.677 .. .. ..$ n : int 14640 .. .. ..$ fit :Classes 'PeaksAndValleys' and 'data.frame': 5 obs. of 3 variables: .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... .. .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 .. .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 .. .. ..$ fitValleys :Classes 'PeaksAndValleys' and 'data.frame': 2 obs. of 3 variables: .. .. .. ..$ type : chr [1:2] "valley" "valley" .. .. .. ..$ x : num [1:2] 0.315 0.677 .. .. .. ..$ density: num [1:2] 0.522 0.551 .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" Setup up data...done Dropping loci for which TCNs are missing... Number of loci dropped: 12 Dropping loci for which TCNs are missing...done Ordering data along genome... 'data.frame': 14658 obs. of 7 variables: $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... $ x : num 554484 730720 782343 878522 916294 ... $ CT : num 1.88 1.8 1.59 1.64 1.53 ... $ betaT : num 0.0646 0.1672 0.9284 0.113 0.7209 ... $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... Ordering data along genome...done Keeping only current chromosome for 'knownSegments'... Chromosome: 1 Known segments for this chromosome: chromosome start end 1 1 -Inf 120992603 2 1 NA NA 3 1 141510003 Inf Keeping only current chromosome for 'knownSegments'...done alphaTCN: 0.009 alphaDH: 0.001 Number of loci: 14658 Calculating DHs... Number of SNPs: 14658 Number of heterozygous SNPs: 4196 (28.63%) Normalized DHs: num [1:14658] NA NA NA NA NA ... Calculating DHs...done Random seed temporarily set (seed=c(48879), kind="L'Ecuyer-CMRG") Produced 2 seeds from this stream for future usage Identification of change points by total copy numbers... Segmenting by CBS... Chromosome: 1 Segmenting multiple segments on current chromosome... Number of segments: 3 Random seed temporarily set (seed=c(10407, 1066287653, -51199871, 161854402, -1995183193, 1503453565, -747102133), kind="L'Ecuyer-CMRG") Produced 3 seeds from this stream for future usage Segmenting by CBS... Chromosome: 1 Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") Segmenting by CBS...done Segmenting by CBS... Chromosome: 1 Random seed temporarily set (seed=c(10407, -1924040949, -1632234809, -437763632, -1464377300, 676654412, 2080370711), kind="L'Ecuyer-CMRG") Segmenting by CBS...done Segmenting multiple segments on current chromosome...done Segmenting by CBS...done List of 4 $ data :'data.frame': 14658 obs. of 4 variables: ..$ chromosome: int [1:14658] 1 1 1 1 1 1 1 1 1 1 ... ..$ x : num [1:14658] 554484 730720 782343 878522 916294 ... ..$ y : num [1:14658] 1.88 1.8 1.59 1.64 1.53 ... ..$ index : int [1:14658] 1 2 3 4 5 6 7 8 9 10 ... $ output :'data.frame': 4 obs. of 6 variables: ..$ sampleName: chr [1:4] NA NA NA NA ..$ chromosome: int [1:4] 1 NA 1 1 ..$ start : num [1:4] 5.54e+05 NA 1.42e+08 1.85e+08 ..$ end : num [1:4] 1.21e+08 NA 1.85e+08 2.47e+08 ..$ nbrOfLoci : int [1:4] 7586 NA 2681 4391 ..$ mean : num [1:4] 1.39 NA 2.07 2.63 $ segRows:'data.frame': 4 obs. of 2 variables: ..$ startRow: int [1:4] 1 NA 7587 10268 ..$ endRow : int [1:4] 7586 NA 10267 14658 $ params :List of 5 ..$ alpha : num 0.009 ..$ undo : num 0 ..$ joinSegments : logi TRUE ..$ knownSegments:'data.frame': 4 obs. of 3 variables: .. ..$ chromosome: num [1:4] 1 1 2 1 .. ..$ start : num [1:4] -Inf -Inf -Inf 1.42e+08 .. ..$ end : num [1:4] 1.21e+08 Inf Inf Inf ..$ seed : int [1:7] 10407 1066287653 -51199871 161854402 -1995183193 1503453565 -747102133 - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.23 0 0.24 NA NA ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... - attr(*, "pkgDetails")= chr "DNAcopy v1.76.0" - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 Identification of change points by total copy numbers...done Restructure TCN segmentation results... chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean 1 1 554484 120992603 7586 1.3853 2 NA NA NA NA NA 3 1 141510003 185449813 2681 2.0689 4 1 185449813 247137334 4391 2.6341 Number of TCN segments: 4 Restructure TCN segmentation results...done Total CN segment #1 ([ 554484,1.20993e+08]) of 4... Number of TCN loci in segment: 7586 Locus data for TCN segment: 'data.frame': 7586 obs. of 9 variables: $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... $ x : num 554484 730720 782343 878522 916294 ... $ CT : num 1.88 1.8 1.59 1.64 1.53 ... $ betaT : num 0.0646 0.1672 0.9284 0.113 0.7209 ... $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... $ index : int 1 2 3 4 5 6 7 8 9 10 ... $ rho : num NA NA NA NA NA ... Number of loci: 7586 Number of SNPs: 2108 (27.79%) Number of heterozygous SNPs: 2108 (100.00%) Chromosome: 1 Segmenting DH signals... Segmenting by CBS... Chromosome: 1 Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") Segmenting by CBS...done List of 4 $ data :'data.frame': 7586 obs. of 4 variables: ..$ chromosome: int [1:7586] 1 1 1 1 1 1 1 1 1 1 ... ..$ x : num [1:7586] 554484 730720 782343 878522 916294 ... ..$ y : num [1:7586] NA NA NA NA NA ... ..$ index : int [1:7586] 1 2 3 4 5 6 7 8 9 10 ... $ output :'data.frame': 1 obs. of 6 variables: ..$ sampleName: chr NA ..$ chromosome: int 1 ..$ start : num 554484 ..$ end : num 1.21e+08 ..$ nbrOfLoci : int 2108 ..$ mean : num 0.512 $ segRows:'data.frame': 1 obs. of 2 variables: ..$ startRow: int 10 ..$ endRow : int 7574 $ params :List of 5 ..$ alpha : num 0.001 ..$ undo : num 0 ..$ joinSegments : logi TRUE ..$ knownSegments:'data.frame': 1 obs. of 3 variables: .. ..$ chromosome: int 1 .. ..$ start : num 554484 .. ..$ end : num 1.21e+08 ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.1 0 0.1 NA NA ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... - attr(*, "pkgDetails")= chr "DNAcopy v1.76.0" - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 DH segmentation (locally-indexed) rows: startRow endRow 1 10 7574 int [1:7586] 1 2 3 4 5 6 7 8 9 10 ... DH segmentation rows: startRow endRow 1 10 7574 Segmenting DH signals...done DH segmentation table: dhStart dhEnd dhNbrOfLoci dhMean 1 554484 120992603 2108 0.5116 startRow endRow 1 10 7574 Rows: [1] 1 TCN segmentation rows: startRow endRow 1 1 7586 TCN and DH segmentation rows: startRow endRow 1 1 7586 startRow endRow 1 10 7574 NULL TCN segmentation (expanded) rows: startRow endRow 1 1 7586 TCN and DH segmentation rows: startRow endRow 1 1 7586 2 NA NA 3 7587 10267 4 10268 14658 startRow endRow 1 10 7574 startRow endRow 1 1 7586 Total CN segmentation table (expanded): chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 1 1 554484 120992603 7586 1.3853 2108 2108 (TCN,DH) segmentation for one total CN segment: tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 1 1 1 1 554484 120992603 7586 1.3853 2108 tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 1 2108 554484 120992603 2108 0.5116 Total CN segment #1 ([ 554484,1.20993e+08]) of 4...done Total CN segment #2 ([ NA, NA]) of 4... No signals to segment. Just a "splitter" segment. Skipping. tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs NA 2 1 NA NA NA NA NA 0 tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean NA 0 NA NA 0 NA Total CN segment #2 ([ NA, NA]) of 4...done Total CN segment #3 ([1.4151e+08,1.8545e+08]) of 4... Number of TCN loci in segment: 2681 Locus data for TCN segment: 'data.frame': 2681 obs. of 9 variables: $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... $ x : num 1.43e+08 1.43e+08 1.43e+08 1.43e+08 1.44e+08 ... $ CT : num 2.27 1.55 1.47 1.5 1.81 ... $ betaT : num 0.34 0.55 0.048 0.813 0.575 ... $ betaTN : num 0.441 0.629 -0.05 0.958 0.872 ... $ betaN : num 0.3851 0.3933 0.0981 0.8552 0.7028 ... $ muN : num 0.5 0.5 0 1 1 1 1 0.5 1 1 ... $ index : int 7587 7588 7589 7590 7591 7592 7593 7594 7595 7596 ... $ rho : num 0.117 0.258 NA NA NA ... Number of loci: 2681 Number of SNPs: 777 (28.98%) Number of heterozygous SNPs: 777 (100.00%) Chromosome: 1 Segmenting DH signals... Segmenting by CBS... Chromosome: 1 Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") Segmenting by CBS...done List of 4 $ data :'data.frame': 2681 obs. of 4 variables: ..$ chromosome: int [1:2681] 1 1 1 1 1 1 1 1 1 1 ... ..$ x : num [1:2681] 1.43e+08 1.43e+08 1.43e+08 1.43e+08 1.44e+08 ... ..$ y : num [1:2681] 0.117 0.258 NA NA NA ... ..$ index : int [1:2681] 1 2 3 4 5 6 7 8 9 10 ... $ output :'data.frame': 1 obs. of 6 variables: ..$ sampleName: chr NA ..$ chromosome: int 1 ..$ start : num 1.42e+08 ..$ end : num 1.85e+08 ..$ nbrOfLoci : int 777 ..$ mean : num 0.0973 $ segRows:'data.frame': 1 obs. of 2 variables: ..$ startRow: int 1 ..$ endRow : int 2677 $ params :List of 5 ..$ alpha : num 0.001 ..$ undo : num 0 ..$ joinSegments : logi TRUE ..$ knownSegments:'data.frame': 1 obs. of 3 variables: .. ..$ chromosome: int 1 .. ..$ start : num 1.42e+08 .. ..$ end : num 1.85e+08 ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.02 0 0.01 NA NA ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... - attr(*, "pkgDetails")= chr "DNAcopy v1.76.0" - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 DH segmentation (locally-indexed) rows: startRow endRow 1 1 2677 int [1:2681] 7587 7588 7589 7590 7591 7592 7593 7594 7595 7596 ... DH segmentation rows: startRow endRow 1 7587 10263 Segmenting DH signals...done DH segmentation table: dhStart dhEnd dhNbrOfLoci dhMean 1 141510003 185449813 777 0.0973 startRow endRow 1 7587 10263 Rows: [1] 3 TCN segmentation rows: startRow endRow 3 7587 10267 TCN and DH segmentation rows: startRow endRow 3 7587 10267 startRow endRow 1 7587 10263 startRow endRow 1 1 7586 NA NA NA TCN segmentation (expanded) rows: startRow endRow 1 1 7586 NA NA NA 3 7587 10267 TCN and DH segmentation rows: startRow endRow 1 1 7586 2 NA NA 3 7587 10267 4 10268 14658 startRow endRow 1 10 7574 2 NA NA 3 7587 10263 startRow endRow 1 1 7586 2 NA NA 3 7587 10267 Total CN segmentation table (expanded): chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 3 1 141510003 185449813 2681 2.0689 777 777 (TCN,DH) segmentation for one total CN segment: tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 3 3 1 1 141510003 185449813 2681 2.0689 777 tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 3 777 141510003 185449813 777 0.0973 Total CN segment #3 ([1.4151e+08,1.8545e+08]) of 4...done Total CN segment #4 ([1.8545e+08,2.47137e+08]) of 4... Number of TCN loci in segment: 4391 Locus data for TCN segment: 'data.frame': 4391 obs. of 9 variables: $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... $ x : num 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... $ CT : num 2.93 2.15 2.82 2.93 2.46 ... $ betaT : num 0.0811 0.5154 0.9473 0.3734 0.7506 ... $ betaTN : num -0.169 0.609 1.028 0.525 0.968 ... $ betaN : num 0.25 0.38 0.919 0.34 0.783 ... $ muN : num 0 0.5 1 0.5 1 1 0 1 0 1 ... $ index : int 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... $ rho : num NA 0.2186 NA 0.0503 NA ... Number of loci: 4391 Number of SNPs: 1311 (29.86%) Number of heterozygous SNPs: 1311 (100.00%) Chromosome: 1 Segmenting DH signals... Segmenting by CBS... Chromosome: 1 Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") Segmenting by CBS...done List of 4 $ data :'data.frame': 4391 obs. of 4 variables: ..$ chromosome: int [1:4391] 1 1 1 1 1 1 1 1 1 1 ... ..$ x : num [1:4391] 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... ..$ y : num [1:4391] NA 0.2186 NA 0.0503 NA ... ..$ index : int [1:4391] 1 2 3 4 5 6 7 8 9 10 ... $ output :'data.frame': 1 obs. of 6 variables: ..$ sampleName: chr NA ..$ chromosome: int 1 ..$ start : num 1.85e+08 ..$ end : num 2.47e+08 ..$ nbrOfLoci : int 1311 ..$ mean : num 0.23 $ segRows:'data.frame': 1 obs. of 2 variables: ..$ startRow: int 2 ..$ endRow : int 4388 $ params :List of 5 ..$ alpha : num 0.001 ..$ undo : num 0 ..$ joinSegments : logi TRUE ..$ knownSegments:'data.frame': 1 obs. of 3 variables: .. ..$ chromosome: int 1 .. ..$ start : num 1.85e+08 .. ..$ end : num 2.47e+08 ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.04 0 0.03 NA NA ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... - attr(*, "pkgDetails")= chr "DNAcopy v1.76.0" - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 DH segmentation (locally-indexed) rows: startRow endRow 1 2 4388 int [1:4391] 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... DH segmentation rows: startRow endRow 1 10269 14655 Segmenting DH signals...done DH segmentation table: dhStart dhEnd dhNbrOfLoci dhMean 1 185449813 247137334 1311 0.2295 startRow endRow 1 10269 14655 Rows: [1] 4 TCN segmentation rows: startRow endRow 4 10268 14658 TCN and DH segmentation rows: startRow endRow 4 10268 14658 startRow endRow 1 10269 14655 startRow endRow 1 1 7586 2 NA NA 3 7587 10267 TCN segmentation (expanded) rows: startRow endRow 1 1 7586 2 NA NA 3 7587 10267 4 10268 14658 TCN and DH segmentation rows: startRow endRow 1 1 7586 2 NA NA 3 7587 10267 4 10268 14658 startRow endRow 1 10 7574 2 NA NA 3 7587 10263 4 10269 14655 startRow endRow 1 1 7586 2 NA NA 3 7587 10267 4 10268 14658 Total CN segmentation table (expanded): chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 4 1 185449813 247137334 4391 2.6341 1311 1311 (TCN,DH) segmentation for one total CN segment: tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 4 4 1 1 185449813 247137334 4391 2.6341 1311 tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 4 1311 185449813 247137334 1311 0.2295 Total CN segment #4 ([1.8545e+08,2.47137e+08]) of 4...done chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 1 1 1 1 554484 120992603 7586 1.3853 2108 2 NA 2 1 NA NA NA NA 0 3 1 3 1 141510003 185449813 2681 2.0689 777 4 1 4 1 185449813 247137334 4391 2.6341 1311 tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 1 2108 554484 120992603 2108 0.5116 2 0 NA NA 0 NA 3 777 141510003 185449813 777 0.0973 4 1311 185449813 247137334 1311 0.2295 Calculating (C1,C2) per segment... Calculating (C1,C2) per segment...done Number of segments: 4 Segmenting paired tumor-normal signals using Paired PSCBS...done Post-segmenting TCNs... Number of segments: 3 Number of chromosomes: 1 [1] 1 Chromosome 1 ('chr01') of 1... Rows: [1] 1 2 3 Number of segments: 3 TCN segment #1 ('1') of 3... Nothing todo. Only one DH segmentation. Skipping. TCN segment #1 ('1') of 3...done TCN segment #2 ('3') of 3... Nothing todo. Only one DH segmentation. Skipping. TCN segment #2 ('3') of 3...done TCN segment #3 ('4') of 3... Nothing todo. Only one DH segmentation. Skipping. TCN segment #3 ('4') of 3...done Chromosome 1 ('chr01') of 1...done Update (C1,C2) per segment... Update (C1,C2) per segment...done Post-segmenting TCNs...done chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 1 1 1 1 554484 120992603 7586 1.3853 2108 2 NA 2 1 NA NA NA NA 0 3 1 3 1 141510003 185449813 2681 2.0689 777 4 1 4 1 185449813 247137334 4391 2.6341 1311 tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 1 2108 554484 120992603 2108 0.5116 0.3382903 1.047010 2 0 NA NA 0 NA NA NA 3 777 141510003 185449813 777 0.0973 0.9337980 1.135102 4 1311 185449813 247137334 1311 0.2295 1.0147870 1.619313 chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 1 1 1 1 554484 120992603 7586 1.3853 2108 2 NA 2 1 NA NA NA NA 0 3 1 3 1 141510003 185449813 2681 2.0689 777 4 1 4 1 185449813 247137334 4391 2.6341 1311 tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 1 2108 554484 120992603 2108 0.5116 0.3382903 1.047010 2 0 NA NA 0 NA NA NA 3 777 141510003 185449813 777 0.0973 0.9337980 1.135102 4 1311 185449813 247137334 1311 0.2295 1.0147870 1.619313 > print(fit) chromosome tcnId dhId start end tcnNbrOfLoci tcnMean tcnNbrOfSNPs 1 1 1 1 554484 120992603 7586 1.3853 2108 2 NA 2 1 NA NA NA NA 0 3 1 3 1 141510003 185449813 2681 2.0689 777 4 1 4 1 185449813 247137334 4391 2.6341 1311 tcnNbrOfHets dhNbrOfLoci dhMean c1Mean c2Mean 1 2108 2108 0.5116 0.3382903 1.047010 2 0 0 NA NA NA 3 777 777 0.0973 0.9337980 1.135102 4 1311 1311 0.2295 1.0147870 1.619313 > > # Plot results > dev.set(2L) null device 1 > plotTracks(fit) > abline(v=c(knownSegments$start, knownSegments$end)/1e6, lty=3) > > # Sanity check > stopifnot(nbrOfSegments(fit) == nSegs) > > fit1 <- fit > > > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - > # (b) Segment also the centromere (which will become NAs) > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - > knownSegments <- data.frame( + chromosome = c( 1, 1, 1), + start = c( -Inf, 120992604, 141510003), + end = c(120992603, 141510002, +Inf) + ) > > > # Paired PSCBS segmentation > fit <- segmentByPairedPSCBS(dataS, knownSegments=knownSegments, + seed=0xBEEF, verbose=-10) Segmenting paired tumor-normal signals using Paired PSCBS... Calling genotypes from normal allele B fractions... num [1:14670] 0.8274 0.5072 0.1671 0.1609 0.0421 ... Called genotypes: num [1:14670] 1 0.5 0 0 0 0 1 0 1 0.5 ... - attr(*, "modelFit")=List of 1 ..$ :List of 7 .. ..$ flavor : chr "density" .. ..$ cn : int 2 .. ..$ nbrOfGenotypeGroups: int 3 .. ..$ tau : num [1:2] 0.315 0.677 .. ..$ n : int 14640 .. ..$ fit :Classes 'PeaksAndValleys' and 'data.frame': 5 obs. of 3 variables: .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 .. ..$ fitValleys :Classes 'PeaksAndValleys' and 'data.frame': 2 obs. of 3 variables: .. .. ..$ type : chr [1:2] "valley" "valley" .. .. ..$ x : num [1:2] 0.315 0.677 .. .. ..$ density: num [1:2] 0.522 0.551 ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" muN 0 0.5 1 5221 4198 5251 Calling genotypes from normal allele B fractions...done Normalizing betaT using betaN (TumorBoost)... Normalized BAFs: num [1:14670] 0.9301 0.1667 0.0685 0.0995 0.0155 ... - attr(*, "modelFit")=List of 5 ..$ method : chr "normalizeTumorBoost" ..$ flavor : chr "v4" ..$ delta : num [1:14670] -0.17264 0.00239 0.1671 0.16085 0.04213 ... .. ..- attr(*, "modelFit")=List of 1 .. .. ..$ :List of 7 .. .. .. ..$ flavor : chr "density" .. .. .. ..$ cn : int 2 .. .. .. ..$ nbrOfGenotypeGroups: int 3 .. .. .. ..$ tau : num [1:2] 0.315 0.677 .. .. .. ..$ n : int 14640 .. .. .. ..$ fit :Classes 'PeaksAndValleys' and 'data.frame': 5 obs. of 3 variables: .. .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... .. .. .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 .. .. .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 .. .. .. ..$ fitValleys :Classes 'PeaksAndValleys' and 'data.frame': 2 obs. of 3 variables: .. .. .. .. ..$ type : chr [1:2] "valley" "valley" .. .. .. .. ..$ x : num [1:2] 0.315 0.677 .. .. .. .. ..$ density: num [1:2] 0.522 0.551 .. .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" ..$ preserveScale: logi FALSE ..$ scaleFactor : num NA Normalizing betaT using betaN (TumorBoost)...done Setup up data... 'data.frame': 14670 obs. of 7 variables: $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... $ x : num 1145994 2941694 3710825 4240737 4276892 ... $ CT : num 1.63 1.4 1.41 1.17 1.16 ... $ betaT : num 0.7574 0.169 0.2357 0.2604 0.0576 ... $ betaTN : num 0.9301 0.1667 0.0685 0.0995 0.0155 ... ..- attr(*, "modelFit")=List of 5 .. ..$ method : chr "normalizeTumorBoost" .. ..$ flavor : chr "v4" .. ..$ delta : num [1:14670] -0.17264 0.00239 0.1671 0.16085 0.04213 ... .. .. ..- attr(*, "modelFit")=List of 1 .. .. .. ..$ :List of 7 .. .. .. .. ..$ flavor : chr "density" .. .. .. .. ..$ cn : int 2 .. .. .. .. ..$ nbrOfGenotypeGroups: int 3 .. .. .. .. ..$ tau : num [1:2] 0.315 0.677 .. .. .. .. ..$ n : int 14640 .. .. .. .. ..$ fit :Classes 'PeaksAndValleys' and 'data.frame': 5 obs. of 3 variables: .. .. .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... .. .. .. .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 .. .. .. .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 .. .. .. .. ..$ fitValleys :Classes 'PeaksAndValleys' and 'data.frame': 2 obs. of 3 variables: .. .. .. .. .. ..$ type : chr [1:2] "valley" "valley" .. .. .. .. .. ..$ x : num [1:2] 0.315 0.677 .. .. .. .. .. ..$ density: num [1:2] 0.522 0.551 .. .. .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" .. ..$ preserveScale: logi FALSE .. ..$ scaleFactor : num NA $ betaN : num 0.8274 0.5072 0.1671 0.1609 0.0421 ... $ muN : num 1 0.5 0 0 0 0 1 0 1 0.5 ... ..- attr(*, "modelFit")=List of 1 .. ..$ :List of 7 .. .. ..$ flavor : chr "density" .. .. ..$ cn : int 2 .. .. ..$ nbrOfGenotypeGroups: int 3 .. .. ..$ tau : num [1:2] 0.315 0.677 .. .. ..$ n : int 14640 .. .. ..$ fit :Classes 'PeaksAndValleys' and 'data.frame': 5 obs. of 3 variables: .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... .. .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 .. .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 .. .. ..$ fitValleys :Classes 'PeaksAndValleys' and 'data.frame': 2 obs. of 3 variables: .. .. .. ..$ type : chr [1:2] "valley" "valley" .. .. .. ..$ x : num [1:2] 0.315 0.677 .. .. .. ..$ density: num [1:2] 0.522 0.551 .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" Setup up data...done Dropping loci for which TCNs are missing... Number of loci dropped: 12 Dropping loci for which TCNs are missing...done Ordering data along genome... 'data.frame': 14658 obs. of 7 variables: $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... $ x : num 554484 730720 782343 878522 916294 ... $ CT : num 1.88 1.8 1.59 1.64 1.53 ... $ betaT : num 0.0646 0.1672 0.9284 0.113 0.7209 ... $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... Ordering data along genome...done Keeping only current chromosome for 'knownSegments'... Chromosome: 1 Known segments for this chromosome: chromosome start end 1 1 -Inf 120992603 2 1 120992604 141510002 3 1 141510003 Inf Keeping only current chromosome for 'knownSegments'...done alphaTCN: 0.009 alphaDH: 0.001 Number of loci: 14658 Calculating DHs... Number of SNPs: 14658 Number of heterozygous SNPs: 4196 (28.63%) Normalized DHs: num [1:14658] NA NA NA NA NA ... Calculating DHs...done Random seed temporarily set (seed=c(48879), kind="L'Ecuyer-CMRG") Produced 2 seeds from this stream for future usage Identification of change points by total copy numbers... Segmenting by CBS... Chromosome: 1 Segmenting multiple segments on current chromosome... Number of segments: 3 Random seed temporarily set (seed=c(10407, 1066287653, -51199871, 161854402, -1995183193, 1503453565, -747102133), kind="L'Ecuyer-CMRG") Produced 3 seeds from this stream for future usage Segmenting by CBS... Chromosome: 1 Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") Segmenting by CBS...done Segmenting by CBS... Chromosome: 1 Random seed temporarily set (seed=c(10407, -1924040949, -1632234809, -437763632, -1464377300, 676654412, 2080370711), kind="L'Ecuyer-CMRG") Segmenting by CBS...done Segmenting multiple segments on current chromosome...done Segmenting by CBS...done List of 4 $ data :'data.frame': 14658 obs. of 4 variables: ..$ chromosome: int [1:14658] 1 1 1 1 1 1 1 1 1 1 ... ..$ x : num [1:14658] 554484 730720 782343 878522 916294 ... ..$ y : num [1:14658] 1.88 1.8 1.59 1.64 1.53 ... ..$ index : int [1:14658] 1 2 3 4 5 6 7 8 9 10 ... $ output :'data.frame': 4 obs. of 6 variables: ..$ sampleName: chr [1:4] NA NA NA NA ..$ chromosome: num [1:4] 1 1 1 1 ..$ start : num [1:4] 5.54e+05 1.21e+08 1.42e+08 1.85e+08 ..$ end : num [1:4] 1.21e+08 1.42e+08 1.85e+08 2.47e+08 ..$ nbrOfLoci : int [1:4] 7586 0 2681 4391 ..$ mean : num [1:4] 1.39 NA 2.07 2.63 $ segRows:'data.frame': 4 obs. of 2 variables: ..$ startRow: int [1:4] 1 NA 7587 10268 ..$ endRow : int [1:4] 7586 NA 10267 14658 $ params :List of 5 ..$ alpha : num 0.009 ..$ undo : num 0 ..$ joinSegments : logi TRUE ..$ knownSegments:'data.frame': 4 obs. of 3 variables: .. ..$ chromosome: num [1:4] 1 1 2 1 .. ..$ start : num [1:4] -Inf -Inf -Inf 1.42e+08 .. ..$ end : num [1:4] 1.21e+08 Inf Inf Inf ..$ seed : int [1:7] 10407 1066287653 -51199871 161854402 -1995183193 1503453565 -747102133 - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.27 0 0.27 NA NA ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... - attr(*, "pkgDetails")= chr "DNAcopy v1.76.0" - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 Identification of change points by total copy numbers...done Restructure TCN segmentation results... chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean 1 1 554484 120992603 7586 1.3853 2 1 120992604 141510002 0 NA 3 1 141510003 185449813 2681 2.0689 4 1 185449813 247137334 4391 2.6341 Number of TCN segments: 4 Restructure TCN segmentation results...done Total CN segment #1 ([ 554484,1.20993e+08]) of 4... Number of TCN loci in segment: 7586 Locus data for TCN segment: 'data.frame': 7586 obs. of 9 variables: $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... $ x : num 554484 730720 782343 878522 916294 ... $ CT : num 1.88 1.8 1.59 1.64 1.53 ... $ betaT : num 0.0646 0.1672 0.9284 0.113 0.7209 ... $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... $ index : int 1 2 3 4 5 6 7 8 9 10 ... $ rho : num NA NA NA NA NA ... Number of loci: 7586 Number of SNPs: 2108 (27.79%) Number of heterozygous SNPs: 2108 (100.00%) Chromosome: 1 Segmenting DH signals... Segmenting by CBS... Chromosome: 1 Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") Segmenting by CBS...done List of 4 $ data :'data.frame': 7586 obs. of 4 variables: ..$ chromosome: int [1:7586] 1 1 1 1 1 1 1 1 1 1 ... ..$ x : num [1:7586] 554484 730720 782343 878522 916294 ... ..$ y : num [1:7586] NA NA NA NA NA ... ..$ index : int [1:7586] 1 2 3 4 5 6 7 8 9 10 ... $ output :'data.frame': 1 obs. of 6 variables: ..$ sampleName: chr NA ..$ chromosome: int 1 ..$ start : num 554484 ..$ end : num 1.21e+08 ..$ nbrOfLoci : int 2108 ..$ mean : num 0.512 $ segRows:'data.frame': 1 obs. of 2 variables: ..$ startRow: int 10 ..$ endRow : int 7574 $ params :List of 5 ..$ alpha : num 0.001 ..$ undo : num 0 ..$ joinSegments : logi TRUE ..$ knownSegments:'data.frame': 1 obs. of 3 variables: .. ..$ chromosome: int 1 .. ..$ start : num 554484 .. ..$ end : num 1.21e+08 ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.1 0 0.1 NA NA ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... - attr(*, "pkgDetails")= chr "DNAcopy v1.76.0" - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 DH segmentation (locally-indexed) rows: startRow endRow 1 10 7574 int [1:7586] 1 2 3 4 5 6 7 8 9 10 ... DH segmentation rows: startRow endRow 1 10 7574 Segmenting DH signals...done DH segmentation table: dhStart dhEnd dhNbrOfLoci dhMean 1 554484 120992603 2108 0.5116 startRow endRow 1 10 7574 Rows: [1] 1 TCN segmentation rows: startRow endRow 1 1 7586 TCN and DH segmentation rows: startRow endRow 1 1 7586 startRow endRow 1 10 7574 NULL TCN segmentation (expanded) rows: startRow endRow 1 1 7586 TCN and DH segmentation rows: startRow endRow 1 1 7586 2 NA NA 3 7587 10267 4 10268 14658 startRow endRow 1 10 7574 startRow endRow 1 1 7586 Total CN segmentation table (expanded): chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 1 1 554484 120992603 7586 1.3853 2108 2108 (TCN,DH) segmentation for one total CN segment: tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 1 1 1 1 554484 120992603 7586 1.3853 2108 tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 1 2108 554484 120992603 2108 0.5116 Total CN segment #1 ([ 554484,1.20993e+08]) of 4...done Total CN segment #2 ([1.20993e+08,1.4151e+08]) of 4... Number of TCN loci in segment: 0 Locus data for TCN segment: 'data.frame': 0 obs. of 9 variables: $ chromosome: int $ x : num $ CT : num $ betaT : num $ betaTN : num $ betaN : num $ muN : num $ index : int $ rho : num Number of loci: 0 Number of SNPs: 0 (NaN%) Number of heterozygous SNPs: 0 (NaN%) Chromosome: 1 Segmenting DH signals... Segmenting by CBS... Chromosome: NA Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") Segmenting by CBS...done List of 4 $ data :'data.frame': 0 obs. of 4 variables: ..$ chromosome: int(0) ..$ x : num(0) ..$ y : num(0) ..$ index : int(0) $ output :'data.frame': 0 obs. of 6 variables: ..$ sampleName: chr(0) ..$ chromosome: num(0) ..$ start : num(0) ..$ end : num(0) ..$ nbrOfLoci : int(0) ..$ mean : num(0) $ segRows:'data.frame': 0 obs. of 2 variables: ..$ startRow: int(0) ..$ endRow : int(0) $ params :List of 5 ..$ alpha : num 0.001 ..$ undo : num 0 ..$ joinSegments : logi TRUE ..$ knownSegments:'data.frame': 0 obs. of 3 variables: .. ..$ chromosome: int(0) .. ..$ start : num(0) .. ..$ end : num(0) ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0 0 0 NA NA ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... - attr(*, "pkgDetails")= chr "DNAcopy v1.76.0" - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 DH segmentation (locally-indexed) rows: [1] startRow endRow <0 rows> (or 0-length row.names) int(0) DH segmentation rows: [1] startRow endRow <0 rows> (or 0-length row.names) Segmenting DH signals...done DH segmentation table: dhStart dhEnd dhNbrOfLoci dhMean NA NA NA NA NA startRow endRow NA NA NA Rows: [1] 2 TCN segmentation rows: startRow endRow 2 NA NA TCN and DH segmentation rows: startRow endRow 2 NA NA startRow endRow NA NA NA startRow endRow 1 1 7586 TCN segmentation (expanded) rows: startRow endRow 1 1 7586 2 NA NA TCN and DH segmentation rows: startRow endRow 1 1 7586 2 NA NA 3 7587 10267 4 10268 14658 startRow endRow 1 10 7574 2 NA NA startRow endRow 1 1 7586 2 NA NA Total CN segmentation table (expanded): chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 2 1 120992604 141510002 0 NA 0 0 (TCN,DH) segmentation for one total CN segment: tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 2 2 1 1 120992604 141510002 0 NA 0 tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 2 0 NA NA NA NA Total CN segment #2 ([1.20993e+08,1.4151e+08]) of 4...done Total CN segment #3 ([1.4151e+08,1.8545e+08]) of 4... Number of TCN loci in segment: 2681 Locus data for TCN segment: 'data.frame': 2681 obs. of 9 variables: $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... $ x : num 1.43e+08 1.43e+08 1.43e+08 1.43e+08 1.44e+08 ... $ CT : num 2.27 1.55 1.47 1.5 1.81 ... $ betaT : num 0.34 0.55 0.048 0.813 0.575 ... $ betaTN : num 0.441 0.629 -0.05 0.958 0.872 ... $ betaN : num 0.3851 0.3933 0.0981 0.8552 0.7028 ... $ muN : num 0.5 0.5 0 1 1 1 1 0.5 1 1 ... $ index : int 7587 7588 7589 7590 7591 7592 7593 7594 7595 7596 ... $ rho : num 0.117 0.258 NA NA NA ... Number of loci: 2681 Number of SNPs: 777 (28.98%) Number of heterozygous SNPs: 777 (100.00%) Chromosome: 1 Segmenting DH signals... Segmenting by CBS... Chromosome: 1 Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") Segmenting by CBS...done List of 4 $ data :'data.frame': 2681 obs. of 4 variables: ..$ chromosome: int [1:2681] 1 1 1 1 1 1 1 1 1 1 ... ..$ x : num [1:2681] 1.43e+08 1.43e+08 1.43e+08 1.43e+08 1.44e+08 ... ..$ y : num [1:2681] 0.117 0.258 NA NA NA ... ..$ index : int [1:2681] 1 2 3 4 5 6 7 8 9 10 ... $ output :'data.frame': 1 obs. of 6 variables: ..$ sampleName: chr NA ..$ chromosome: int 1 ..$ start : num 1.42e+08 ..$ end : num 1.85e+08 ..$ nbrOfLoci : int 777 ..$ mean : num 0.0973 $ segRows:'data.frame': 1 obs. of 2 variables: ..$ startRow: int 1 ..$ endRow : int 2677 $ params :List of 5 ..$ alpha : num 0.001 ..$ undo : num 0 ..$ joinSegments : logi TRUE ..$ knownSegments:'data.frame': 1 obs. of 3 variables: .. ..$ chromosome: int 1 .. ..$ start : num 1.42e+08 .. ..$ end : num 1.85e+08 ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.02 0 0.02 NA NA ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... - attr(*, "pkgDetails")= chr "DNAcopy v1.76.0" - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 DH segmentation (locally-indexed) rows: startRow endRow 1 1 2677 int [1:2681] 7587 7588 7589 7590 7591 7592 7593 7594 7595 7596 ... DH segmentation rows: startRow endRow 1 7587 10263 Segmenting DH signals...done DH segmentation table: dhStart dhEnd dhNbrOfLoci dhMean 1 141510003 185449813 777 0.0973 startRow endRow 1 7587 10263 Rows: [1] 3 TCN segmentation rows: startRow endRow 3 7587 10267 TCN and DH segmentation rows: startRow endRow 3 7587 10267 startRow endRow 1 7587 10263 startRow endRow 1 1 7586 2 NA NA TCN segmentation (expanded) rows: startRow endRow 1 1 7586 2 NA NA 3 7587 10267 TCN and DH segmentation rows: startRow endRow 1 1 7586 2 NA NA 3 7587 10267 4 10268 14658 startRow endRow 1 10 7574 2 NA NA 3 7587 10263 startRow endRow 1 1 7586 2 NA NA 3 7587 10267 Total CN segmentation table (expanded): chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 3 1 141510003 185449813 2681 2.0689 777 777 (TCN,DH) segmentation for one total CN segment: tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 3 3 1 1 141510003 185449813 2681 2.0689 777 tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 3 777 141510003 185449813 777 0.0973 Total CN segment #3 ([1.4151e+08,1.8545e+08]) of 4...done Total CN segment #4 ([1.8545e+08,2.47137e+08]) of 4... Number of TCN loci in segment: 4391 Locus data for TCN segment: 'data.frame': 4391 obs. of 9 variables: $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... $ x : num 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... $ CT : num 2.93 2.15 2.82 2.93 2.46 ... $ betaT : num 0.0811 0.5154 0.9473 0.3734 0.7506 ... $ betaTN : num -0.169 0.609 1.028 0.525 0.968 ... $ betaN : num 0.25 0.38 0.919 0.34 0.783 ... $ muN : num 0 0.5 1 0.5 1 1 0 1 0 1 ... $ index : int 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... $ rho : num NA 0.2186 NA 0.0503 NA ... Number of loci: 4391 Number of SNPs: 1311 (29.86%) Number of heterozygous SNPs: 1311 (100.00%) Chromosome: 1 Segmenting DH signals... Segmenting by CBS... Chromosome: 1 Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") Segmenting by CBS...done List of 4 $ data :'data.frame': 4391 obs. of 4 variables: ..$ chromosome: int [1:4391] 1 1 1 1 1 1 1 1 1 1 ... ..$ x : num [1:4391] 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... ..$ y : num [1:4391] NA 0.2186 NA 0.0503 NA ... ..$ index : int [1:4391] 1 2 3 4 5 6 7 8 9 10 ... $ output :'data.frame': 1 obs. of 6 variables: ..$ sampleName: chr NA ..$ chromosome: int 1 ..$ start : num 1.85e+08 ..$ end : num 2.47e+08 ..$ nbrOfLoci : int 1311 ..$ mean : num 0.23 $ segRows:'data.frame': 1 obs. of 2 variables: ..$ startRow: int 2 ..$ endRow : int 4388 $ params :List of 5 ..$ alpha : num 0.001 ..$ undo : num 0 ..$ joinSegments : logi TRUE ..$ knownSegments:'data.frame': 1 obs. of 3 variables: .. ..$ chromosome: int 1 .. ..$ start : num 1.85e+08 .. ..$ end : num 2.47e+08 ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.03 0 0.03 NA NA ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... - attr(*, "pkgDetails")= chr "DNAcopy v1.76.0" - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 DH segmentation (locally-indexed) rows: startRow endRow 1 2 4388 int [1:4391] 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... DH segmentation rows: startRow endRow 1 10269 14655 Segmenting DH signals...done DH segmentation table: dhStart dhEnd dhNbrOfLoci dhMean 1 185449813 247137334 1311 0.2295 startRow endRow 1 10269 14655 Rows: [1] 4 TCN segmentation rows: startRow endRow 4 10268 14658 TCN and DH segmentation rows: startRow endRow 4 10268 14658 startRow endRow 1 10269 14655 startRow endRow 1 1 7586 2 NA NA 3 7587 10267 TCN segmentation (expanded) rows: startRow endRow 1 1 7586 2 NA NA 3 7587 10267 4 10268 14658 TCN and DH segmentation rows: startRow endRow 1 1 7586 2 NA NA 3 7587 10267 4 10268 14658 startRow endRow 1 10 7574 2 NA NA 3 7587 10263 4 10269 14655 startRow endRow 1 1 7586 2 NA NA 3 7587 10267 4 10268 14658 Total CN segmentation table (expanded): chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 4 1 185449813 247137334 4391 2.6341 1311 1311 (TCN,DH) segmentation for one total CN segment: tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 4 4 1 1 185449813 247137334 4391 2.6341 1311 tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 4 1311 185449813 247137334 1311 0.2295 Total CN segment #4 ([1.8545e+08,2.47137e+08]) of 4...done chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 1 1 1 1 554484 120992603 7586 1.3853 2108 2 1 2 1 120992604 141510002 0 NA 0 3 1 3 1 141510003 185449813 2681 2.0689 777 4 1 4 1 185449813 247137334 4391 2.6341 1311 tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 1 2108 554484 120992603 2108 0.5116 2 0 NA NA NA NA 3 777 141510003 185449813 777 0.0973 4 1311 185449813 247137334 1311 0.2295 Calculating (C1,C2) per segment... Calculating (C1,C2) per segment...done Number of segments: 4 Segmenting paired tumor-normal signals using Paired PSCBS...done Post-segmenting TCNs... Number of segments: 4 Number of chromosomes: 1 [1] 1 Chromosome 1 ('chr01') of 1... Rows: [1] 1 2 3 4 Number of segments: 4 TCN segment #1 ('1') of 4... Nothing todo. Only one DH segmentation. Skipping. TCN segment #1 ('1') of 4...done TCN segment #2 ('2') of 4... Nothing todo. Only one DH segmentation. Skipping. TCN segment #2 ('2') of 4...done TCN segment #3 ('3') of 4... Nothing todo. Only one DH segmentation. Skipping. TCN segment #3 ('3') of 4...done TCN segment #4 ('4') of 4... Nothing todo. Only one DH segmentation. Skipping. TCN segment #4 ('4') of 4...done Chromosome 1 ('chr01') of 1...done Update (C1,C2) per segment... Update (C1,C2) per segment...done Post-segmenting TCNs...done chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 1 1 1 1 554484 120992603 7586 1.3853 2108 2 1 2 1 120992604 141510002 0 NA 0 3 1 3 1 141510003 185449813 2681 2.0689 777 4 1 4 1 185449813 247137334 4391 2.6341 1311 tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 1 2108 554484 120992603 2108 0.5116 0.3382903 1.047010 2 0 NA NA NA NA NA NA 3 777 141510003 185449813 777 0.0973 0.9337980 1.135102 4 1311 185449813 247137334 1311 0.2295 1.0147870 1.619313 chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 1 1 1 1 554484 120992603 7586 1.3853 2108 2 1 2 1 120992604 141510002 0 NA 0 3 1 3 1 141510003 185449813 2681 2.0689 777 4 1 4 1 185449813 247137334 4391 2.6341 1311 tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 1 2108 554484 120992603 2108 0.5116 0.3382903 1.047010 2 0 NA NA NA NA NA NA 3 777 141510003 185449813 777 0.0973 0.9337980 1.135102 4 1311 185449813 247137334 1311 0.2295 1.0147870 1.619313 > print(fit) chromosome tcnId dhId start end tcnNbrOfLoci tcnMean tcnNbrOfSNPs 1 1 1 1 554484 120992603 7586 1.3853 2108 2 1 2 1 120992604 141510002 0 NA 0 3 1 3 1 141510003 185449813 2681 2.0689 777 4 1 4 1 185449813 247137334 4391 2.6341 1311 tcnNbrOfHets dhNbrOfLoci dhMean c1Mean c2Mean 1 2108 2108 0.5116 0.3382903 1.047010 2 0 NA NA NA NA 3 777 777 0.0973 0.9337980 1.135102 4 1311 1311 0.2295 1.0147870 1.619313 > > # Plot results > dev.set(3L) pdf 2 > plotTracks(fit) > abline(v=c(knownSegments$start, knownSegments$end)/1e6, lty=3) > > # Sanity check [TO FIX: See above] > stopifnot(nbrOfSegments(fit) == nSegs) > > fit2 <- fit > > > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - > # (c) Do not segment the centromere (without a separator) > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - > knownSegments <- data.frame( + chromosome = c( 1, 1), + start = c( -Inf, 141510003), + end = c(120992603, +Inf) + ) > > # Paired PSCBS segmentation > fit <- segmentByPairedPSCBS(dataS, knownSegments=knownSegments, + seed=0xBEEF, verbose=-10) Segmenting paired tumor-normal signals using Paired PSCBS... Calling genotypes from normal allele B fractions... num [1:14670] 0.8274 0.5072 0.1671 0.1609 0.0421 ... Called genotypes: num [1:14670] 1 0.5 0 0 0 0 1 0 1 0.5 ... - attr(*, "modelFit")=List of 1 ..$ :List of 7 .. ..$ flavor : chr "density" .. ..$ cn : int 2 .. ..$ nbrOfGenotypeGroups: int 3 .. ..$ tau : num [1:2] 0.315 0.677 .. ..$ n : int 14640 .. ..$ fit :Classes 'PeaksAndValleys' and 'data.frame': 5 obs. of 3 variables: .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 .. ..$ fitValleys :Classes 'PeaksAndValleys' and 'data.frame': 2 obs. of 3 variables: .. .. ..$ type : chr [1:2] "valley" "valley" .. .. ..$ x : num [1:2] 0.315 0.677 .. .. ..$ density: num [1:2] 0.522 0.551 ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" muN 0 0.5 1 5221 4198 5251 Calling genotypes from normal allele B fractions...done Normalizing betaT using betaN (TumorBoost)... Normalized BAFs: num [1:14670] 0.9301 0.1667 0.0685 0.0995 0.0155 ... - attr(*, "modelFit")=List of 5 ..$ method : chr "normalizeTumorBoost" ..$ flavor : chr "v4" ..$ delta : num [1:14670] -0.17264 0.00239 0.1671 0.16085 0.04213 ... .. ..- attr(*, "modelFit")=List of 1 .. .. ..$ :List of 7 .. .. .. ..$ flavor : chr "density" .. .. .. ..$ cn : int 2 .. .. .. ..$ nbrOfGenotypeGroups: int 3 .. .. .. ..$ tau : num [1:2] 0.315 0.677 .. .. .. ..$ n : int 14640 .. .. .. ..$ fit :Classes 'PeaksAndValleys' and 'data.frame': 5 obs. of 3 variables: .. .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... .. .. .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 .. .. .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 .. .. .. ..$ fitValleys :Classes 'PeaksAndValleys' and 'data.frame': 2 obs. of 3 variables: .. .. .. .. ..$ type : chr [1:2] "valley" "valley" .. .. .. .. ..$ x : num [1:2] 0.315 0.677 .. .. .. .. ..$ density: num [1:2] 0.522 0.551 .. .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" ..$ preserveScale: logi FALSE ..$ scaleFactor : num NA Normalizing betaT using betaN (TumorBoost)...done Setup up data... 'data.frame': 14670 obs. of 7 variables: $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... $ x : num 1145994 2941694 3710825 4240737 4276892 ... $ CT : num 1.63 1.4 1.41 1.17 1.16 ... $ betaT : num 0.7574 0.169 0.2357 0.2604 0.0576 ... $ betaTN : num 0.9301 0.1667 0.0685 0.0995 0.0155 ... ..- attr(*, "modelFit")=List of 5 .. ..$ method : chr "normalizeTumorBoost" .. ..$ flavor : chr "v4" .. ..$ delta : num [1:14670] -0.17264 0.00239 0.1671 0.16085 0.04213 ... .. .. ..- attr(*, "modelFit")=List of 1 .. .. .. ..$ :List of 7 .. .. .. .. ..$ flavor : chr "density" .. .. .. .. ..$ cn : int 2 .. .. .. .. ..$ nbrOfGenotypeGroups: int 3 .. .. .. .. ..$ tau : num [1:2] 0.315 0.677 .. .. .. .. ..$ n : int 14640 .. .. .. .. ..$ fit :Classes 'PeaksAndValleys' and 'data.frame': 5 obs. of 3 variables: .. .. .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... .. .. .. .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 .. .. .. .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 .. .. .. .. ..$ fitValleys :Classes 'PeaksAndValleys' and 'data.frame': 2 obs. of 3 variables: .. .. .. .. .. ..$ type : chr [1:2] "valley" "valley" .. .. .. .. .. ..$ x : num [1:2] 0.315 0.677 .. .. .. .. .. ..$ density: num [1:2] 0.522 0.551 .. .. .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" .. ..$ preserveScale: logi FALSE .. ..$ scaleFactor : num NA $ betaN : num 0.8274 0.5072 0.1671 0.1609 0.0421 ... $ muN : num 1 0.5 0 0 0 0 1 0 1 0.5 ... ..- attr(*, "modelFit")=List of 1 .. ..$ :List of 7 .. .. ..$ flavor : chr "density" .. .. ..$ cn : int 2 .. .. ..$ nbrOfGenotypeGroups: int 3 .. .. ..$ tau : num [1:2] 0.315 0.677 .. .. ..$ n : int 14640 .. .. ..$ fit :Classes 'PeaksAndValleys' and 'data.frame': 5 obs. of 3 variables: .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... .. .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 .. .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 .. .. ..$ fitValleys :Classes 'PeaksAndValleys' and 'data.frame': 2 obs. of 3 variables: .. .. .. ..$ type : chr [1:2] "valley" "valley" .. .. .. ..$ x : num [1:2] 0.315 0.677 .. .. .. ..$ density: num [1:2] 0.522 0.551 .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" Setup up data...done Dropping loci for which TCNs are missing... Number of loci dropped: 12 Dropping loci for which TCNs are missing...done Ordering data along genome... 'data.frame': 14658 obs. of 7 variables: $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... $ x : num 554484 730720 782343 878522 916294 ... $ CT : num 1.88 1.8 1.59 1.64 1.53 ... $ betaT : num 0.0646 0.1672 0.9284 0.113 0.7209 ... $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... Ordering data along genome...done Keeping only current chromosome for 'knownSegments'... Chromosome: 1 Known segments for this chromosome: chromosome start end 1 1 -Inf 120992603 2 1 141510003 Inf Keeping only current chromosome for 'knownSegments'...done alphaTCN: 0.009 alphaDH: 0.001 Number of loci: 14658 Calculating DHs... Number of SNPs: 14658 Number of heterozygous SNPs: 4196 (28.63%) Normalized DHs: num [1:14658] NA NA NA NA NA ... Calculating DHs...done Random seed temporarily set (seed=c(48879), kind="L'Ecuyer-CMRG") Produced 2 seeds from this stream for future usage Identification of change points by total copy numbers... Segmenting by CBS... Chromosome: 1 Segmenting multiple segments on current chromosome... Number of segments: 2 Random seed temporarily set (seed=c(10407, 1066287653, -51199871, 161854402, -1995183193, 1503453565, -747102133), kind="L'Ecuyer-CMRG") Produced 2 seeds from this stream for future usage Segmenting by CBS... Chromosome: 1 Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") Segmenting by CBS...done Segmenting by CBS... Chromosome: 1 Random seed temporarily set (seed=c(10407, -821273412, -52578226, 1415511586, 721384351, -665928286, 1316562960), kind="L'Ecuyer-CMRG") Segmenting by CBS...done Segmenting multiple segments on current chromosome...done Segmenting by CBS...done List of 4 $ data :'data.frame': 14658 obs. of 4 variables: ..$ chromosome: int [1:14658] 1 1 1 1 1 1 1 1 1 1 ... ..$ x : num [1:14658] 554484 730720 782343 878522 916294 ... ..$ y : num [1:14658] 1.88 1.8 1.59 1.64 1.53 ... ..$ index : int [1:14658] 1 2 3 4 5 6 7 8 9 10 ... $ output :'data.frame': 3 obs. of 6 variables: ..$ sampleName: chr [1:3] NA NA NA ..$ chromosome: int [1:3] 1 1 1 ..$ start : num [1:3] 5.54e+05 1.42e+08 1.85e+08 ..$ end : num [1:3] 1.21e+08 1.85e+08 2.47e+08 ..$ nbrOfLoci : int [1:3] 7586 2681 4391 ..$ mean : num [1:3] 1.39 2.07 2.63 $ segRows:'data.frame': 3 obs. of 2 variables: ..$ startRow: int [1:3] 1 7587 10268 ..$ endRow : int [1:3] 7586 10267 14658 $ params :List of 5 ..$ alpha : num 0.009 ..$ undo : num 0 ..$ joinSegments : logi TRUE ..$ knownSegments:'data.frame': 2 obs. of 3 variables: .. ..$ chromosome: num [1:2] 1 1 .. ..$ start : num [1:2] -Inf 1.42e+08 .. ..$ end : num [1:2] 1.21e+08 Inf ..$ seed : int [1:7] 10407 1066287653 -51199871 161854402 -1995183193 1503453565 -747102133 - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.25 0 0.25 NA NA ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... - attr(*, "pkgDetails")= chr "DNAcopy v1.76.0" - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 Identification of change points by total copy numbers...done Restructure TCN segmentation results... chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean 1 1 554484 120992603 7586 1.3853 2 1 141510003 185449813 2681 2.0689 3 1 185449813 247137334 4391 2.6341 Number of TCN segments: 3 Restructure TCN segmentation results...done Total CN segment #1 ([ 554484,1.20993e+08]) of 3... Number of TCN loci in segment: 7586 Locus data for TCN segment: 'data.frame': 7586 obs. of 9 variables: $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... $ x : num 554484 730720 782343 878522 916294 ... $ CT : num 1.88 1.8 1.59 1.64 1.53 ... $ betaT : num 0.0646 0.1672 0.9284 0.113 0.7209 ... $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... $ index : int 1 2 3 4 5 6 7 8 9 10 ... $ rho : num NA NA NA NA NA ... Number of loci: 7586 Number of SNPs: 2108 (27.79%) Number of heterozygous SNPs: 2108 (100.00%) Chromosome: 1 Segmenting DH signals... Segmenting by CBS... Chromosome: 1 Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") Segmenting by CBS...done List of 4 $ data :'data.frame': 7586 obs. of 4 variables: ..$ chromosome: int [1:7586] 1 1 1 1 1 1 1 1 1 1 ... ..$ x : num [1:7586] 554484 730720 782343 878522 916294 ... ..$ y : num [1:7586] NA NA NA NA NA ... ..$ index : int [1:7586] 1 2 3 4 5 6 7 8 9 10 ... $ output :'data.frame': 1 obs. of 6 variables: ..$ sampleName: chr NA ..$ chromosome: int 1 ..$ start : num 554484 ..$ end : num 1.21e+08 ..$ nbrOfLoci : int 2108 ..$ mean : num 0.512 $ segRows:'data.frame': 1 obs. of 2 variables: ..$ startRow: int 10 ..$ endRow : int 7574 $ params :List of 5 ..$ alpha : num 0.001 ..$ undo : num 0 ..$ joinSegments : logi TRUE ..$ knownSegments:'data.frame': 1 obs. of 3 variables: .. ..$ chromosome: int 1 .. ..$ start : num 554484 .. ..$ end : num 1.21e+08 ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.06 0 0.07 NA NA ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... - attr(*, "pkgDetails")= chr "DNAcopy v1.76.0" - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 DH segmentation (locally-indexed) rows: startRow endRow 1 10 7574 int [1:7586] 1 2 3 4 5 6 7 8 9 10 ... DH segmentation rows: startRow endRow 1 10 7574 Segmenting DH signals...done DH segmentation table: dhStart dhEnd dhNbrOfLoci dhMean 1 554484 120992603 2108 0.5116 startRow endRow 1 10 7574 Rows: [1] 1 TCN segmentation rows: startRow endRow 1 1 7586 TCN and DH segmentation rows: startRow endRow 1 1 7586 startRow endRow 1 10 7574 NULL TCN segmentation (expanded) rows: startRow endRow 1 1 7586 TCN and DH segmentation rows: startRow endRow 1 1 7586 2 7587 10267 3 10268 14658 startRow endRow 1 10 7574 startRow endRow 1 1 7586 Total CN segmentation table (expanded): chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 1 1 554484 120992603 7586 1.3853 2108 2108 (TCN,DH) segmentation for one total CN segment: tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 1 1 1 1 554484 120992603 7586 1.3853 2108 tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 1 2108 554484 120992603 2108 0.5116 Total CN segment #1 ([ 554484,1.20993e+08]) of 3...done Total CN segment #2 ([1.4151e+08,1.8545e+08]) of 3... Number of TCN loci in segment: 2681 Locus data for TCN segment: 'data.frame': 2681 obs. of 9 variables: $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... $ x : num 1.43e+08 1.43e+08 1.43e+08 1.43e+08 1.44e+08 ... $ CT : num 2.27 1.55 1.47 1.5 1.81 ... $ betaT : num 0.34 0.55 0.048 0.813 0.575 ... $ betaTN : num 0.441 0.629 -0.05 0.958 0.872 ... $ betaN : num 0.3851 0.3933 0.0981 0.8552 0.7028 ... $ muN : num 0.5 0.5 0 1 1 1 1 0.5 1 1 ... $ index : int 7587 7588 7589 7590 7591 7592 7593 7594 7595 7596 ... $ rho : num 0.117 0.258 NA NA NA ... Number of loci: 2681 Number of SNPs: 777 (28.98%) Number of heterozygous SNPs: 777 (100.00%) Chromosome: 1 Segmenting DH signals... Segmenting by CBS... Chromosome: 1 Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") Segmenting by CBS...done List of 4 $ data :'data.frame': 2681 obs. of 4 variables: ..$ chromosome: int [1:2681] 1 1 1 1 1 1 1 1 1 1 ... ..$ x : num [1:2681] 1.43e+08 1.43e+08 1.43e+08 1.43e+08 1.44e+08 ... ..$ y : num [1:2681] 0.117 0.258 NA NA NA ... ..$ index : int [1:2681] 1 2 3 4 5 6 7 8 9 10 ... $ output :'data.frame': 1 obs. of 6 variables: ..$ sampleName: chr NA ..$ chromosome: int 1 ..$ start : num 1.42e+08 ..$ end : num 1.85e+08 ..$ nbrOfLoci : int 777 ..$ mean : num 0.0973 $ segRows:'data.frame': 1 obs. of 2 variables: ..$ startRow: int 1 ..$ endRow : int 2677 $ params :List of 5 ..$ alpha : num 0.001 ..$ undo : num 0 ..$ joinSegments : logi TRUE ..$ knownSegments:'data.frame': 1 obs. of 3 variables: .. ..$ chromosome: int 1 .. ..$ start : num 1.42e+08 .. ..$ end : num 1.85e+08 ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.02 0 0.01 NA NA ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... - attr(*, "pkgDetails")= chr "DNAcopy v1.76.0" - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 DH segmentation (locally-indexed) rows: startRow endRow 1 1 2677 int [1:2681] 7587 7588 7589 7590 7591 7592 7593 7594 7595 7596 ... DH segmentation rows: startRow endRow 1 7587 10263 Segmenting DH signals...done DH segmentation table: dhStart dhEnd dhNbrOfLoci dhMean 1 141510003 185449813 777 0.0973 startRow endRow 1 7587 10263 Rows: [1] 2 TCN segmentation rows: startRow endRow 2 7587 10267 TCN and DH segmentation rows: startRow endRow 2 7587 10267 startRow endRow 1 7587 10263 startRow endRow 1 1 7586 TCN segmentation (expanded) rows: startRow endRow 1 1 7586 2 7587 10267 TCN and DH segmentation rows: startRow endRow 1 1 7586 2 7587 10267 3 10268 14658 startRow endRow 1 10 7574 2 7587 10263 startRow endRow 1 1 7586 2 7587 10267 Total CN segmentation table (expanded): chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 2 1 141510003 185449813 2681 2.0689 777 777 (TCN,DH) segmentation for one total CN segment: tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 2 2 1 1 141510003 185449813 2681 2.0689 777 tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 2 777 141510003 185449813 777 0.0973 Total CN segment #2 ([1.4151e+08,1.8545e+08]) of 3...done Total CN segment #3 ([1.8545e+08,2.47137e+08]) of 3... Number of TCN loci in segment: 4391 Locus data for TCN segment: 'data.frame': 4391 obs. of 9 variables: $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... $ x : num 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... $ CT : num 2.93 2.15 2.82 2.93 2.46 ... $ betaT : num 0.0811 0.5154 0.9473 0.3734 0.7506 ... $ betaTN : num -0.169 0.609 1.028 0.525 0.968 ... $ betaN : num 0.25 0.38 0.919 0.34 0.783 ... $ muN : num 0 0.5 1 0.5 1 1 0 1 0 1 ... $ index : int 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... $ rho : num NA 0.2186 NA 0.0503 NA ... Number of loci: 4391 Number of SNPs: 1311 (29.86%) Number of heterozygous SNPs: 1311 (100.00%) Chromosome: 1 Segmenting DH signals... Segmenting by CBS... Chromosome: 1 Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") Segmenting by CBS...done List of 4 $ data :'data.frame': 4391 obs. of 4 variables: ..$ chromosome: int [1:4391] 1 1 1 1 1 1 1 1 1 1 ... ..$ x : num [1:4391] 1.85e+08 1.85e+08 1.85e+08 1.86e+08 1.86e+08 ... ..$ y : num [1:4391] NA 0.2186 NA 0.0503 NA ... ..$ index : int [1:4391] 1 2 3 4 5 6 7 8 9 10 ... $ output :'data.frame': 1 obs. of 6 variables: ..$ sampleName: chr NA ..$ chromosome: int 1 ..$ start : num 1.85e+08 ..$ end : num 2.47e+08 ..$ nbrOfLoci : int 1311 ..$ mean : num 0.23 $ segRows:'data.frame': 1 obs. of 2 variables: ..$ startRow: int 2 ..$ endRow : int 4388 $ params :List of 5 ..$ alpha : num 0.001 ..$ undo : num 0 ..$ joinSegments : logi TRUE ..$ knownSegments:'data.frame': 1 obs. of 3 variables: .. ..$ chromosome: int 1 .. ..$ start : num 1.85e+08 .. ..$ end : num 2.47e+08 ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0.01 0 0.02 NA NA ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... - attr(*, "pkgDetails")= chr "DNAcopy v1.76.0" - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 DH segmentation (locally-indexed) rows: startRow endRow 1 2 4388 int [1:4391] 10268 10269 10270 10271 10272 10273 10274 10275 10276 10277 ... DH segmentation rows: startRow endRow 1 10269 14655 Segmenting DH signals...done DH segmentation table: dhStart dhEnd dhNbrOfLoci dhMean 1 185449813 247137334 1311 0.2295 startRow endRow 1 10269 14655 Rows: [1] 3 TCN segmentation rows: startRow endRow 3 10268 14658 TCN and DH segmentation rows: startRow endRow 3 10268 14658 startRow endRow 1 10269 14655 startRow endRow 1 1 7586 2 7587 10267 TCN segmentation (expanded) rows: startRow endRow 1 1 7586 2 7587 10267 3 10268 14658 TCN and DH segmentation rows: startRow endRow 1 1 7586 2 7587 10267 3 10268 14658 startRow endRow 1 10 7574 2 7587 10263 3 10269 14655 startRow endRow 1 1 7586 2 7587 10267 3 10268 14658 Total CN segmentation table (expanded): chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 3 1 185449813 247137334 4391 2.6341 1311 1311 (TCN,DH) segmentation for one total CN segment: tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 3 3 1 1 185449813 247137334 4391 2.6341 1311 tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 3 1311 185449813 247137334 1311 0.2295 Total CN segment #3 ([1.8545e+08,2.47137e+08]) of 3...done chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 1 1 1 1 554484 120992603 7586 1.3853 2108 2 1 2 1 141510003 185449813 2681 2.0689 777 3 1 3 1 185449813 247137334 4391 2.6341 1311 tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 1 2108 554484 120992603 2108 0.5116 2 777 141510003 185449813 777 0.0973 3 1311 185449813 247137334 1311 0.2295 Calculating (C1,C2) per segment... Calculating (C1,C2) per segment...done Number of segments: 3 Segmenting paired tumor-normal signals using Paired PSCBS...done Post-segmenting TCNs... Number of segments: 3 Number of chromosomes: 1 [1] 1 Chromosome 1 ('chr01') of 1... Rows: [1] 1 2 3 Number of segments: 3 TCN segment #1 ('1') of 3... Nothing todo. Only one DH segmentation. Skipping. TCN segment #1 ('1') of 3...done TCN segment #2 ('2') of 3... Nothing todo. Only one DH segmentation. Skipping. TCN segment #2 ('2') of 3...done TCN segment #3 ('3') of 3... Nothing todo. Only one DH segmentation. Skipping. TCN segment #3 ('3') of 3...done Chromosome 1 ('chr01') of 1...done Update (C1,C2) per segment... Update (C1,C2) per segment...done Post-segmenting TCNs...done chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 1 1 1 1 554484 120992603 7586 1.3853 2108 2 1 2 1 141510003 185449813 2681 2.0689 777 3 1 3 1 185449813 247137334 4391 2.6341 1311 tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 1 2108 554484 120992603 2108 0.5116 0.3382903 1.047010 2 777 141510003 185449813 777 0.0973 0.9337980 1.135102 3 1311 185449813 247137334 1311 0.2295 1.0147870 1.619313 chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 1 1 1 1 554484 120992603 7586 1.3853 2108 2 1 2 1 141510003 185449813 2681 2.0689 777 3 1 3 1 185449813 247137334 4391 2.6341 1311 tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 1 2108 554484 120992603 2108 0.5116 0.3382903 1.047010 2 777 141510003 185449813 777 0.0973 0.9337980 1.135102 3 1311 185449813 247137334 1311 0.2295 1.0147870 1.619313 > print(fit) chromosome tcnId dhId start end tcnNbrOfLoci tcnMean tcnNbrOfSNPs 1 1 1 1 554484 120992603 7586 1.3853 2108 2 1 2 1 141510003 185449813 2681 2.0689 777 3 1 3 1 185449813 247137334 4391 2.6341 1311 tcnNbrOfHets dhNbrOfLoci dhMean c1Mean c2Mean 1 2108 2108 0.5116 0.3382903 1.047010 2 777 777 0.0973 0.9337980 1.135102 3 1311 1311 0.2295 1.0147870 1.619313 > > # Plot results > dev.set(4L) pdf 2 > plotTracks(fit) > abline(v=c(knownSegments$start, knownSegments$end)/1e6, lty=3) > > # Sanity check > stopifnot(nbrOfSegments(fit) == nSegs-1L) > > fit3 <- fit > > > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - > # (d) Skip the identification of new change points > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - > knownSegments <- data.frame( + chromosome = c( 1, 1), + start = c( -Inf, 141510003), + end = c(120992603, +Inf) + ) > > # Paired PSCBS segmentation > fit <- segmentByPairedPSCBS(dataS, knownSegments=knownSegments, + undoTCN=Inf, undoDH=Inf, + seed=0xBEEF, verbose=-10) Segmenting paired tumor-normal signals using Paired PSCBS... Calling genotypes from normal allele B fractions... num [1:14670] 0.8274 0.5072 0.1671 0.1609 0.0421 ... Called genotypes: num [1:14670] 1 0.5 0 0 0 0 1 0 1 0.5 ... - attr(*, "modelFit")=List of 1 ..$ :List of 7 .. ..$ flavor : chr "density" .. ..$ cn : int 2 .. ..$ nbrOfGenotypeGroups: int 3 .. ..$ tau : num [1:2] 0.315 0.677 .. ..$ n : int 14640 .. ..$ fit :Classes 'PeaksAndValleys' and 'data.frame': 5 obs. of 3 variables: .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 .. ..$ fitValleys :Classes 'PeaksAndValleys' and 'data.frame': 2 obs. of 3 variables: .. .. ..$ type : chr [1:2] "valley" "valley" .. .. ..$ x : num [1:2] 0.315 0.677 .. .. ..$ density: num [1:2] 0.522 0.551 ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" muN 0 0.5 1 5221 4198 5251 Calling genotypes from normal allele B fractions...done Normalizing betaT using betaN (TumorBoost)... Normalized BAFs: num [1:14670] 0.9301 0.1667 0.0685 0.0995 0.0155 ... - attr(*, "modelFit")=List of 5 ..$ method : chr "normalizeTumorBoost" ..$ flavor : chr "v4" ..$ delta : num [1:14670] -0.17264 0.00239 0.1671 0.16085 0.04213 ... .. ..- attr(*, "modelFit")=List of 1 .. .. ..$ :List of 7 .. .. .. ..$ flavor : chr "density" .. .. .. ..$ cn : int 2 .. .. .. ..$ nbrOfGenotypeGroups: int 3 .. .. .. ..$ tau : num [1:2] 0.315 0.677 .. .. .. ..$ n : int 14640 .. .. .. ..$ fit :Classes 'PeaksAndValleys' and 'data.frame': 5 obs. of 3 variables: .. .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... .. .. .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 .. .. .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 .. .. .. ..$ fitValleys :Classes 'PeaksAndValleys' and 'data.frame': 2 obs. of 3 variables: .. .. .. .. ..$ type : chr [1:2] "valley" "valley" .. .. .. .. ..$ x : num [1:2] 0.315 0.677 .. .. .. .. ..$ density: num [1:2] 0.522 0.551 .. .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" ..$ preserveScale: logi FALSE ..$ scaleFactor : num NA Normalizing betaT using betaN (TumorBoost)...done Setup up data... 'data.frame': 14670 obs. of 7 variables: $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... $ x : num 1145994 2941694 3710825 4240737 4276892 ... $ CT : num 1.63 1.4 1.41 1.17 1.16 ... $ betaT : num 0.7574 0.169 0.2357 0.2604 0.0576 ... $ betaTN : num 0.9301 0.1667 0.0685 0.0995 0.0155 ... ..- attr(*, "modelFit")=List of 5 .. ..$ method : chr "normalizeTumorBoost" .. ..$ flavor : chr "v4" .. ..$ delta : num [1:14670] -0.17264 0.00239 0.1671 0.16085 0.04213 ... .. .. ..- attr(*, "modelFit")=List of 1 .. .. .. ..$ :List of 7 .. .. .. .. ..$ flavor : chr "density" .. .. .. .. ..$ cn : int 2 .. .. .. .. ..$ nbrOfGenotypeGroups: int 3 .. .. .. .. ..$ tau : num [1:2] 0.315 0.677 .. .. .. .. ..$ n : int 14640 .. .. .. .. ..$ fit :Classes 'PeaksAndValleys' and 'data.frame': 5 obs. of 3 variables: .. .. .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... .. .. .. .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 .. .. .. .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 .. .. .. .. ..$ fitValleys :Classes 'PeaksAndValleys' and 'data.frame': 2 obs. of 3 variables: .. .. .. .. .. ..$ type : chr [1:2] "valley" "valley" .. .. .. .. .. ..$ x : num [1:2] 0.315 0.677 .. .. .. .. .. ..$ density: num [1:2] 0.522 0.551 .. .. .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" .. ..$ preserveScale: logi FALSE .. ..$ scaleFactor : num NA $ betaN : num 0.8274 0.5072 0.1671 0.1609 0.0421 ... $ muN : num 1 0.5 0 0 0 0 1 0 1 0.5 ... ..- attr(*, "modelFit")=List of 1 .. ..$ :List of 7 .. .. ..$ flavor : chr "density" .. .. ..$ cn : int 2 .. .. ..$ nbrOfGenotypeGroups: int 3 .. .. ..$ tau : num [1:2] 0.315 0.677 .. .. ..$ n : int 14640 .. .. ..$ fit :Classes 'PeaksAndValleys' and 'data.frame': 5 obs. of 3 variables: .. .. .. ..$ type : chr [1:5] "peak" "valley" "peak" "valley" ... .. .. .. ..$ x : num [1:5] 0.104 0.315 0.499 0.677 0.885 .. .. .. ..$ density: num [1:5] 1.479 0.522 1.056 0.551 1.453 .. .. ..$ fitValleys :Classes 'PeaksAndValleys' and 'data.frame': 2 obs. of 3 variables: .. .. .. ..$ type : chr [1:2] "valley" "valley" .. .. .. ..$ x : num [1:2] 0.315 0.677 .. .. .. ..$ density: num [1:2] 0.522 0.551 .. ..- attr(*, "class")= chr [1:2] "NaiveGenotypeModelFit" "list" Setup up data...done Dropping loci for which TCNs are missing... Number of loci dropped: 12 Dropping loci for which TCNs are missing...done Ordering data along genome... 'data.frame': 14658 obs. of 7 variables: $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... $ x : num 554484 730720 782343 878522 916294 ... $ CT : num 1.88 1.8 1.59 1.64 1.53 ... $ betaT : num 0.0646 0.1672 0.9284 0.113 0.7209 ... $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... Ordering data along genome...done Keeping only current chromosome for 'knownSegments'... Chromosome: 1 Known segments for this chromosome: chromosome start end 1 1 -Inf 120992603 2 1 141510003 Inf Keeping only current chromosome for 'knownSegments'...done alphaTCN: 0.009 alphaDH: 0.001 Number of loci: 14658 Calculating DHs... Number of SNPs: 14658 Number of heterozygous SNPs: 4196 (28.63%) Normalized DHs: num [1:14658] NA NA NA NA NA ... Calculating DHs...done Random seed temporarily set (seed=c(48879), kind="L'Ecuyer-CMRG") Produced 2 seeds from this stream for future usage Identification of change points by total copy numbers... Segmenting by CBS... Chromosome: 1 Segmenting multiple segments on current chromosome... Number of segments: 2 Random seed temporarily set (seed=c(10407, 1066287653, -51199871, 161854402, -1995183193, 1503453565, -747102133), kind="L'Ecuyer-CMRG") Produced 2 seeds from this stream for future usage Segmenting by CBS... Chromosome: 1 Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") Segmenting by CBS...done Segmenting by CBS... Chromosome: 1 Random seed temporarily set (seed=c(10407, -821273412, -52578226, 1415511586, 721384351, -665928286, 1316562960), kind="L'Ecuyer-CMRG") Segmenting by CBS...done Segmenting multiple segments on current chromosome...done Segmenting by CBS...done List of 4 $ data :'data.frame': 14658 obs. of 4 variables: ..$ chromosome: int [1:14658] 1 1 1 1 1 1 1 1 1 1 ... ..$ x : num [1:14658] 554484 730720 782343 878522 916294 ... ..$ y : num [1:14658] 1.88 1.8 1.59 1.64 1.53 ... ..$ index : int [1:14658] 1 2 3 4 5 6 7 8 9 10 ... $ output :'data.frame': 2 obs. of 6 variables: ..$ sampleName: chr [1:2] NA NA ..$ chromosome: num [1:2] 1 1 ..$ start : num [1:2] 5.54e+05 1.42e+08 ..$ end : num [1:2] 1.21e+08 2.47e+08 ..$ nbrOfLoci : int [1:2] 7586 7072 ..$ mean : num [1:2] 1.39 2.42 $ segRows:'data.frame': 2 obs. of 2 variables: ..$ startRow: int [1:2] 1 7587 ..$ endRow : int [1:2] 7586 14658 $ params :List of 7 ..$ undo.splits : chr "sdundo" ..$ undo.SD : num Inf ..$ alpha : num 0.009 ..$ undo : num Inf ..$ joinSegments : logi TRUE ..$ knownSegments:'data.frame': 2 obs. of 3 variables: .. ..$ chromosome: num [1:2] 1 1 .. ..$ start : num [1:2] -Inf 1.42e+08 .. ..$ end : num [1:2] 1.21e+08 Inf ..$ seed : int [1:7] 10407 1066287653 -51199871 161854402 -1995183193 1503453565 -747102133 - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0 0 0 NA NA ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... - attr(*, "pkgDetails")= chr "DNAcopy v1.76.0" - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 Identification of change points by total copy numbers...done Restructure TCN segmentation results... chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean 1 1 554484 120992603 7586 1.385258 2 1 141510003 247137334 7072 2.419824 Number of TCN segments: 2 Restructure TCN segmentation results...done Total CN segment #1 ([ 554484,1.20993e+08]) of 2... Number of TCN loci in segment: 7586 Locus data for TCN segment: 'data.frame': 7586 obs. of 9 variables: $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... $ x : num 554484 730720 782343 878522 916294 ... $ CT : num 1.88 1.8 1.59 1.64 1.53 ... $ betaT : num 0.0646 0.1672 0.9284 0.113 0.7209 ... $ betaTN : num -0.0515 -0.1172 1.0194 0.031 0.8604 ... $ betaN : num 0.116 0.284 0.909 0.082 0.86 ... $ muN : num 0 0 1 0 1 1 1 0 1 0.5 ... $ index : int 1 2 3 4 5 6 7 8 9 10 ... $ rho : num NA NA NA NA NA ... Number of loci: 7586 Number of SNPs: 2108 (27.79%) Number of heterozygous SNPs: 2108 (100.00%) Chromosome: 1 Segmenting DH signals... Segmenting by CBS... Chromosome: 1 Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") Segmenting by CBS...done List of 4 $ data :'data.frame': 7586 obs. of 4 variables: ..$ chromosome: int [1:7586] 1 1 1 1 1 1 1 1 1 1 ... ..$ x : num [1:7586] 554484 730720 782343 878522 916294 ... ..$ y : num [1:7586] NA NA NA NA NA ... ..$ index : int [1:7586] 1 2 3 4 5 6 7 8 9 10 ... $ output :'data.frame': 1 obs. of 6 variables: ..$ sampleName: chr NA ..$ chromosome: int 1 ..$ start : num 554484 ..$ end : num 1.21e+08 ..$ nbrOfLoci : int 7586 ..$ mean : num 0.512 $ segRows:'data.frame': 1 obs. of 2 variables: ..$ startRow: int 1 ..$ endRow : int 7586 $ params :List of 7 ..$ undo.splits : chr "sdundo" ..$ undo.SD : num Inf ..$ alpha : num 0.001 ..$ undo : num Inf ..$ joinSegments : logi TRUE ..$ knownSegments:'data.frame': 1 obs. of 3 variables: .. ..$ chromosome: int 1 .. ..$ start : num 554484 .. ..$ end : num 1.21e+08 ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0 0 0 NA NA ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... - attr(*, "pkgDetails")= chr "DNAcopy v1.76.0" - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 DH segmentation (locally-indexed) rows: startRow endRow 1 1 7586 int [1:7586] 1 2 3 4 5 6 7 8 9 10 ... DH segmentation rows: startRow endRow 1 1 7586 Segmenting DH signals...done DH segmentation table: dhStart dhEnd dhNbrOfLoci dhMean 1 554484 120992603 7586 0.511612 startRow endRow 1 1 7586 Rows: [1] 1 TCN segmentation rows: startRow endRow 1 1 7586 TCN and DH segmentation rows: startRow endRow 1 1 7586 startRow endRow 1 1 7586 NULL TCN segmentation (expanded) rows: startRow endRow 1 1 7586 TCN and DH segmentation rows: startRow endRow 1 1 7586 2 7587 14658 startRow endRow 1 1 7586 startRow endRow 1 1 7586 Total CN segmentation table (expanded): chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs tcnNbrOfHets 1 1 554484 120992603 7586 1.385258 2108 2108 (TCN,DH) segmentation for one total CN segment: tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 1 1 1 1 554484 120992603 7586 1.385258 2108 tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 1 2108 554484 120992603 7586 0.511612 Total CN segment #1 ([ 554484,1.20993e+08]) of 2...done Total CN segment #2 ([1.4151e+08,2.47137e+08]) of 2... Number of TCN loci in segment: 7072 Locus data for TCN segment: 'data.frame': 7072 obs. of 9 variables: $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... $ x : num 1.43e+08 1.43e+08 1.43e+08 1.43e+08 1.44e+08 ... $ CT : num 2.27 1.55 1.47 1.5 1.81 ... $ betaT : num 0.34 0.55 0.048 0.813 0.575 ... $ betaTN : num 0.441 0.629 -0.05 0.958 0.872 ... $ betaN : num 0.3851 0.3933 0.0981 0.8552 0.7028 ... $ muN : num 0.5 0.5 0 1 1 1 1 0.5 1 1 ... $ index : int 7587 7588 7589 7590 7591 7592 7593 7594 7595 7596 ... $ rho : num 0.117 0.258 NA NA NA ... Number of loci: 7072 Number of SNPs: 2088 (29.52%) Number of heterozygous SNPs: 2088 (100.00%) Chromosome: 1 Segmenting DH signals... Segmenting by CBS... Chromosome: 1 Random seed temporarily set (seed=c(10407, 1797822437, 388243314, 91406689, -519578635, -1381924756, 1089253019), kind="L'Ecuyer-CMRG") Segmenting by CBS...done List of 4 $ data :'data.frame': 7072 obs. of 4 variables: ..$ chromosome: int [1:7072] 1 1 1 1 1 1 1 1 1 1 ... ..$ x : num [1:7072] 1.43e+08 1.43e+08 1.43e+08 1.43e+08 1.44e+08 ... ..$ y : num [1:7072] 0.117 0.258 NA NA NA ... ..$ index : int [1:7072] 1 2 3 4 5 6 7 8 9 10 ... $ output :'data.frame': 1 obs. of 6 variables: ..$ sampleName: chr NA ..$ chromosome: int 1 ..$ start : num 1.42e+08 ..$ end : num 2.47e+08 ..$ nbrOfLoci : int 7072 ..$ mean : num 0.18 $ segRows:'data.frame': 1 obs. of 2 variables: ..$ startRow: int 1 ..$ endRow : int 7072 $ params :List of 7 ..$ undo.splits : chr "sdundo" ..$ undo.SD : num Inf ..$ alpha : num 0.001 ..$ undo : num Inf ..$ joinSegments : logi TRUE ..$ knownSegments:'data.frame': 1 obs. of 3 variables: .. ..$ chromosome: int 1 .. ..$ start : num 1.42e+08 .. ..$ end : num 2.47e+08 ..$ seed : int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 - attr(*, "class")= chr [1:2] "CBS" "AbstractCBS" - attr(*, "processingTime")= 'proc_time' Named num [1:5] 0 0 0 NA NA ..- attr(*, "names")= chr [1:5] "user.self" "sys.self" "elapsed" "user.child" ... - attr(*, "pkgDetails")= chr "DNAcopy v1.76.0" - attr(*, "randomSeed")= int [1:7] 10407 1797822437 388243314 91406689 -519578635 -1381924756 1089253019 DH segmentation (locally-indexed) rows: startRow endRow 1 1 7072 int [1:7072] 7587 7588 7589 7590 7591 7592 7593 7594 7595 7596 ... DH segmentation rows: startRow endRow 1 7587 14658 Segmenting DH signals...done DH segmentation table: dhStart dhEnd dhNbrOfLoci dhMean 1 141510003 247137334 7072 0.1803011 startRow endRow 1 7587 14658 Rows: [1] 2 TCN segmentation rows: startRow endRow 2 7587 14658 TCN and DH segmentation rows: startRow endRow 2 7587 14658 startRow endRow 1 7587 14658 startRow endRow 1 1 7586 TCN segmentation (expanded) rows: startRow endRow 1 1 7586 2 7587 14658 TCN and DH segmentation rows: startRow endRow 1 1 7586 2 7587 14658 startRow endRow 1 1 7586 2 7587 14658 startRow endRow 1 1 7586 2 7587 14658 Total CN segmentation table (expanded): chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 2 1 141510003 247137334 7072 2.419824 2088 tcnNbrOfHets 2 2088 (TCN,DH) segmentation for one total CN segment: tcnId dhId chromosome tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 2 2 1 1 141510003 247137334 7072 2.419824 2088 tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 2 2088 141510003 247137334 7072 0.1803011 Total CN segment #2 ([1.4151e+08,2.47137e+08]) of 2...done chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 1 1 1 1 554484 120992603 7586 1.385258 2108 2 1 2 1 141510003 247137334 7072 2.419824 2088 tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean 1 2108 554484 120992603 7586 0.5116120 2 2088 141510003 247137334 7072 0.1803011 Calculating (C1,C2) per segment... Calculating (C1,C2) per segment...done Number of segments: 2 Segmenting paired tumor-normal signals using Paired PSCBS...done Post-segmenting TCNs... Number of segments: 2 Number of chromosomes: 1 [1] 1 Chromosome 1 ('chr01') of 1... Rows: [1] 1 2 Number of segments: 2 TCN segment #1 ('1') of 2... Nothing todo. Only one DH segmentation. Skipping. TCN segment #1 ('1') of 2...done TCN segment #2 ('2') of 2... Nothing todo. Only one DH segmentation. Skipping. TCN segment #2 ('2') of 2...done Chromosome 1 ('chr01') of 1...done Update (C1,C2) per segment... Update (C1,C2) per segment...done Post-segmenting TCNs...done chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 1 1 1 1 554484 120992603 7586 1.385258 2108 2 1 2 1 141510003 247137334 7072 2.419824 2088 tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 1 2108 554484 120992603 7586 0.5116120 0.3382717 1.046986 2 2088 141510003 247137334 7072 0.1803011 0.9917635 1.428060 chromosome tcnId dhId tcnStart tcnEnd tcnNbrOfLoci tcnMean tcnNbrOfSNPs 1 1 1 1 554484 120992603 7586 1.385258 2108 2 1 2 1 141510003 247137334 7072 2.419824 2088 tcnNbrOfHets dhStart dhEnd dhNbrOfLoci dhMean c1Mean c2Mean 1 2108 554484 120992603 7586 0.5116120 0.3382717 1.046986 2 2088 141510003 247137334 7072 0.1803011 0.9917635 1.428060 > print(fit) chromosome tcnId dhId start end tcnNbrOfLoci tcnMean tcnNbrOfSNPs 1 1 1 1 554484 120992603 7586 1.385258 2108 2 1 2 1 141510003 247137334 7072 2.419824 2088 tcnNbrOfHets dhNbrOfLoci dhMean c1Mean c2Mean 1 2108 7586 0.5116120 0.3382717 1.046986 2 2088 7072 0.1803011 0.9917635 1.428060 > > # Plot results > dev.set(5L) pdf 2 > plotTracks(fit) > abline(v=c(knownSegments$start, knownSegments$end)/1e6, lty=3) > > # Sanity check > stopifnot(nbrOfSegments(fit) == nrow(knownSegments)) > > fit4 <- fit > > > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - > # Tiling multiple chromosomes > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - > # Simulate multiple chromosomes > fit1 <- fit > fit2 <- renameChromosomes(fit, from=1, to=2) > fitM <- c(fit1, fit2) > > # Tile chromosomes > fitT <- tileChromosomes(fitM) > fitTb <- tileChromosomes(fitT) > stopifnot(identical(fitTb, fitT)) > > # Plotting multiple chromosomes > plotTracks(fitT) > > proc.time() user system elapsed 5.95 0.20 6.60