Description Usage Arguments Details Author(s) References See Also Examples
Three plotting functions for TitanCNA results. plotCNlogRByChr
plots the copy number results from log ratio data. plotAllelicRatio
plots the allelic imbalance and loss of heterozygosity (LOH) from allelic ratio data. plotClonalFrequency
plots the clonal cluster and cellular prevalence results for each data point.
1 2 3 4 5 6 7 8 9 10 11 12 13  plotAllelicRatio(dataIn, chr = c(1:22), geneAnnot = NULL, spacing = 4,
xlim = NULL, ...)
plotClonalFrequency(dataIn, chr = c(1:22), normal = NULL, geneAnnot = NULL,
spacing = 4, xlim = NULL, ...)
plotCNlogRByChr(dataIn, chr = c(1:22), segs = NULL, plotCorrectedCN = TRUE,
geneAnnot = NULL, ploidy = NULL, normal = NULL, spacing = 4, alphaVal = 1, xlim = NULL, ...)
plotSubcloneProfiles(dataIn, chr = c(1:22), geneAnnot = NULL,
spacing = 4, xlim = NULL, ...)
plotSegmentMedians(dataIn, resultType = "LogRatio", plotType = "CopyNumber", plotCorrectedCN = TRUE,
chr = c(1:22), geneAnnot = NULL, ploidy = NULL, spacing = 4, alphaVal = 1, xlim = NULL,
plot.new = FALSE, lwd = 8, ...)
plotHaplotypeFraction(dataIn, chr = c(1:22), resultType = "HaplotypeRatio", colType = "Haplotypes",
phaseBlockCol = c("#9ad0f3", "#CC79A7"), geneAnnot = NULL, spacing = 4, xlim = NULL, ...)

dataIn 
Formatted TitanCNA results output from 
chr 
Plot results for specified 
segs 

resultType 
For 
plotType 
Specify whether to plot the ‘CopyNumber’ or ‘Ratio’ values for the 
colType 
Specify the color scheme to use: ‘Haplotypes’ or ‘CopyNumber’. For ‘Haplotypes’, alternating blue and red used to illustrated the data within phased haplotype blocks. For ‘CopyNumber’, the same colors as 
plotCorrectedCN 

geneAnnot 

normal 

ploidy 

phaseBlockCol 
Twoelement vector specifying the color to plot for alternating haplotype phase blocks. 
spacing 
Number of lines of spacing for the margin spacing at the bottom of the plot. Useful if an idiogram/karogram is plot underneath. 
alphaVal 
Set an alpha value between 0 and 1 to allow transparency in the points being plot. 
xlim 
Two element vector to specify the xlim for the plot. If 
lwd 
Explicitly specify the line width for segments being plot. 
plot.new 

... 
Additional arguments used in the 
plotCNlogRByChr
plots the copy number alterations from log ratio data. The Yaxis is based on log ratios. Log ratios are computed ratios between normalized tumour and normal read depths. Data points close to 0 represent diploid, above 0 are copy gains, below 0 are deletions. ploidy
argument adjusts the baseline of the data points. Colours represent the copy number state.
Bright Green  Homozygous deletion (HOMD)
Green  Hemizygous deletion (DLOH)
Blue  Diploid heterozygous (HET), Copyneutral LOH (NLOH)
Dark Red  GAIN
Red  Allelespecific CNA (ASCNA), Unbalanced CNA (UBCNA), Balanced CNA (BCNA)
plotAllelicRatio
plots the allelic imbalance and loss of heterozygosity from allelic ratio data. The Yaxis is based on allelic ratios. Allelic ratios are computed as RefCount/Depth. Data points close to 1 represent homozygous reference base, close to 0 represent homozygous nonreference base, and close to 0.5 represent heterozygous. Normal contamination influences the divergence away from 0.5 for LOH events. No adjustments are made to the plot as the original data from dataIn
are shown. Colours represent the allelic imbalance and LOH state.
Grey  HET, BCNA
Bright Green  HOMD
Green  DLOH, ALOH
Blue  NLOH
Dark Red  GAIN
Red  ASCNA, UBCNA
plotClonalFrequency
plots the cellular prevalence and clonal clusters from the results. The Yaxis is the cellular prevalence that includes the normal proportion. Therefore, the cellular prevalence here refers to the proportion in the sample (including normal). Lines are drawn for each data point indicating the cellular prevalence. Heterozygous diploid are not shown because it is a normal genotype and is not categorized as being subclonal (this means 100% of cells are normal). The black horizontal line represents the tumour content labeled as ‘T’. Each horizontal grey line represents the cellular prevalence of the clonal clusters labeled as Z1, Z2, etc. Colours are the sames for allelic ratio plots.
plotSubcloneProfiles
plots the predicted copy number profile for individual subclones inferred by TITAN. Currently, this only works for solutions having 1 or 2 clonal clusters. The colours are the same as for plotAllelicRatio
.
plotSegmentMedians
plots the segment means for ‘LogRatio’ or ‘AllelicRatio’ data. There are also two types of plots for each of the datatypes: ‘Ratio’ or ‘CopyNumber’. For ‘Ratio’, the logRatio or allelic ratios in the output results files are plot. For ‘CopyNumber’, the yaxis is converted to the exponentiated absolute copy number levels for the easier interpretability of the results.
plotHaplotypeFraction
plots the phased SNP read count of the higher coverage haplotype, normalized by the total coverage of the haplotype. For ‘Haplotypes’, alternating colors of blue and red are used to illustrate the phased haplotype blocks provided from the input data (see loadHaplotypeAlleleCounts
).
Gavin Ha <gavinha@gmail.com>
Ha, G., Roth, A., Khattra, J., Ho, J., Yap, D., Prentice, L. M., Melnyk, N., McPherson, A., Bashashati, A., Laks, E., Biele, J., Ding, J., Le, A., Rosner, J., Shumansky, K., Marra, M. A., Huntsman, D. G., McAlpine, J. N., Aparicio, S. A. J. R., and Shah, S. P. (2014). TITAN: Inference of copy number architectures in clonal cell populations from tumour whole genome sequence data. Genome Research, 24: 18811893. (PMID: 25060187)
outputTitanResults
, runEMclonalCN
, computeSDbwIndex
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30  data(EMresults)
#### COMPUTE OPTIMAL STATE PATH USING VITERBI ####
optimalPath < viterbiClonalCN(data, convergeParams)
#### FORMAT RESULTS ####
results < outputTitanResults(data, convergeParams, optimalPath,
filename = NULL, posteriorProbs = FALSE,
correctResults = TRUE, proportionThreshold = 0.05,
proportionThresholdClonal = 0.05)
convergeParams < results$convergeParams
results < results$corrResults # use corrected results
#### PLOT RESULTS ####
norm < tail(convergeParams$n, 1)
ploidy < tail(convergeParams$phi, 1)
par(mfrow=c(4, 1))
plotCNlogRByChr(results, chr = 2, segs = NULL, ploidy = ploidy, normal = norm,
geneAnnot = NULL, ylim = c(2, 2), cex = 0.5, xlab = "",
main = "Chr 2")
plotAllelicRatio(results, chr = 2, geneAnnot = NULL, ylim = c(0, 1), cex = 0.5,
xlab = "", main = "Chr 2")
plotClonalFrequency(results, chr = 2, normal = norm, geneAnnot = NULL,
ylim = c(0, 1), cex = 0.5, xlab = "", main = "Chr 2")
plotSubcloneProfiles(results, chr = 2, cex = 2, main = "Chr 2")
segs < outputTitanSegments(results, id = "test", convergeParams)
plotSegmentMedians(segs, chr=2, resultType = "LogRatio",
plotType = "CopyNumber", plot.new = TRUE)

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