Description Usage Format Value Examples
A QDNAseq-object with segmented copy number data of two tumor samples: 'sample1' and 'sample2'
1 | data("copyNumbersSegmented")
|
A QDNAseqCopyNumbers S4 object with 3113 features (bins), each represented by copy number values and segment values of two samples
copyNumbersSegmented@assayData$copynumber
copy number data saved in a matrix, rownames are bins (chr:start-end), colnames are sampleNames
copyNumbersSegmented@assayData$segmented
segment values saved in a matrix, the rownames are bins (chr:start-end), colnames are sampleNames
A QDNAseqCopyNumbers S4 object
1 2 3 4 5 6 7 | data("copyNumbersSegmented")
## ploidyplotloop(copyNumbersSegmented, currentdir = ".")
singlemodel(copyNumbersSegmented, QDNAseqobjectsample = 1)
singleplot(copyNumbersSegmented, 1, cellularity = 0.79)
model2 <- singlemodel(copyNumbersSegmented, QDNAseqobjectsample = 2)
singleplot(copyNumbersSegmented, 2, cellularity = with(model2,
minima[which(rerror==min(rerror))]))
|
$ploidy
[1] 2
$standard
[1] 1.003617
$method
[1] "RMSE"
$penalty
[1] 0
$minima
[1] 0.08 0.13 0.16 0.20 0.26 0.40 0.79
$rerror
[1] 0.1721531 0.2041887 0.2037072 0.2037072 0.2041887 0.2037072 0.2010687
$errorlist
[1] 0.054790782 0.036541644 0.018969380 0.009432403 0.010619254 0.010625251
[7] 0.011305857 0.013675446 0.011187660 0.014402033 0.013362744 0.011161278
[13] 0.015672733 0.017174978 0.012400050 0.011161278 0.014402033 0.020057280
[19] 0.021781059 0.017174978 0.013362744 0.011187660 0.011609577 0.014402033
[25] 0.018522218 0.023275401 0.028344907 0.030074462 0.026774371 0.023414312
[31] 0.020189131 0.017174978 0.014504020 0.012400050 0.011187660 0.011161278
[37] 0.012328519 0.014402033 0.017054400 0.020057280 0.023275401 0.026630846
[43] 0.030077691 0.033587810 0.037143267 0.040732192 0.044346461 0.047222193
[49] 0.048676459 0.048133708 0.046314261 0.044499097 0.042688763 0.040883901
[55] 0.039085268 0.037293765 0.035510473 0.033736692 0.031974006 0.030224356
[61] 0.028490145 0.026774371 0.025080819 0.023414312 0.021781059 0.020189131
[67] 0.018649114 0.017174978 0.015785191 0.014504020 0.013362744 0.012400050
[73] 0.011660253 0.011187660 0.011016712 0.011161278 0.011609577 0.012328519
[79] 0.013274204 0.014402033 0.015672733 0.017054400 0.018522218 0.020057280
[85] 0.021645286 0.023275401 0.024939369 0.026630846 0.028344907 0.030077691
[91] 0.031826141 0.033587810 0.035360722 0.037143267 0.038934123 0.040732192
$errorplot
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