correctCN: Compute purity and ploidy corrected log ratios; recompute...

In gavinha/TitanCNA: Subclonal copy number and LOH prediction from whole genome sequencing of tumours

Description

TitanCNA uses a finite state space that defines a maximum number of copies to model. High-level amplifications that exceed this defined maximum need to be corrected and reported as the likely copy number based on the observed data. correctIntegerCN performs two tasks: (1) correct log ratio based on purity and ploidy, and then convert to decimal CN value; (2) Correct bins (from cn) and segments (from segs) in which the original predicted integer copy number was assigned the maximum CN state; bins and segments for all of chromosome X are also corrected, if provided in the input.

Usage

correctIntegerCN(cn, segs, purity, ploidy, maxCNtoCorrect.autosomes = NULL, 
		maxCNtoCorrect.X = NULL, correctHOMD = TRUE, minPurityToCorrect = 0.2, gender = "male", 
		chrs = c(1:22, "X"))

Arguments

cn	data.table object output from the function outputTitanResults
segs	data.table object output from the function outputTitanSegments
purity	Float type of the 1 minus the normal contamination estimate from TitanCNA
ploidy	Float type of the average tumor ploidy estimate from TitanCNA
maxCNtoCorrect.autosomes	Bins and segments in autosomes with this copy number value or higher will be corrected. If NULL, then it will use the original copy number value from the input data.
maxCNtoCorrect.X	Bins and segments in chromosome X, if provided, with this copy number value or higher will be corrected. If NULL, then it will use the original copy number value from the input data.
minPurityToCorrect	If purity is less than minPurityToCorrect, then Corrected_Copy_Number will retain the same copy number values as the input copy number.
correctHOMD	If TRUE, then will correct the copy number of homozygous deletion bins and segments based on purity and ploidy corrected log ratios.
gender	data.frame containing list of centromere regions. This should contain 3 columns: chr, start, and end. If this argument is used, then data at and flanking the centromeres will be removed.
chrs	Chromosomes to consider for copy number correction.

Value

cn: data.table object that contains the same columns as the input object but also includes new columns logR_Copy_Number, Corrected_Copy_Number, Corrected_Call. segs: data.table object that contains the same columns as the input object but also includes new columns logR_Copy_Number, Corrected_Copy_Number, Corrected_Call, Corrected_MajorCN, Corrected_MinorCN. Column definitions:

logR_Copy_Number	Purity and ploidy corrected log ratios that have been converted to a decimal-based copy number value.
Corrected_Copy_Number	round(logR_Copy_Number)
Corrected_Call	String representation of Corrected_Copy_Number; HLAMP=high-level amplification is assigned to bins/segments that have been corrected.
Corrected_MajorCN	Purity and ploidy corrected integer (rounded) major copy number value.
Corrected_MinorCN	Purity and ploidy corrected integer (rounded) minor copy number value.

Author(s)

Gavin Ha <[e-mail]>

References

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: 1881-1893. (PMID: 25060187)

See Also

outputTitanResults, outputTitanSegments

Examples

data(EMresults)

#### COMPUTE OPTIMAL STATE PATH USING VITERBI ####
optimalPath <- viterbiClonalCN(data, convergeParams)

#### FORMAT RESULTS ####
results <- outputTitanResults(data, convergeParams, optimalPath,
                              filename = NULL, posteriorProbs = FALSE, 
                              subcloneProfiles = TRUE, correctResults = TRUE, 
                              proportionThreshold = 0.05, recomputeLogLik = FALSE,
                              proportionThresholdClonal = 0.05,
                              is.haplotypeData = FALSE)
## use corrected parameters
convergeParams <- results$convergeParam 
## use corrected results
results <- results$corrResults 
## get normal contamination and ploidy estimates
norm <- tail(convergeParams$n,1)
ploidy <- tail(convergeParams$phi,1)

#### OUTPUT SEGMENTS ####
segs <- outputTitanSegments(results, id = "test", convergeParams, 
  filename = NULL, igvfilename = NULL)
corrIntCN.results <- correctIntegerCN(results, segs, 1 - norm, ploidy, maxCNtoCorrect.autosomes = NULL, 
		maxCNtoCorrect.X = NULL, correctHOMD = TRUE, minPurityToCorrect = 0.2, gender = "female", chrs = 2)

gavinha/TitanCNA documentation built on April 22, 2021, 9:38 a.m.