correctReadDepth: Correct GC content and mappability biases in sequencing data...

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

Description

Correct GC content and mappability biases in tumour sequence read counts using Loess curve fitting. Wrapper for function in HMMcopy.

Usage

  correctReadDepth(tumWig, normWig, gcWig, mapWig, 
  			genomeStyle = "NCBI", targetedSequence = NULL)

Arguments

tumWig	File path to fixedStep WIG format file for the tumour sample. See wigToRangedData in the HMMcopy for more details.
normWig	File path to fixedStep WIG format file for the normal sample.
gcWig	File path to fixedStep WIG format file for the GC content based on the specific reference genome sequence used.
mapWig	File path to fixedStep WIG format file for the mappability scores computed on the specific reference genome used.
genomeStyle	The genome style to use for chromosomes by TitanCNA. Use one of ‘NCBI’ or ‘UCSC’. It does not matter what style is found in inCounts, genomeStyle will be the style returned.
targetedSequence	data.frame with 3 columns: chr, start position, stop position. Use this argument for exome capture sequencing or targeted deep sequencing data. This is experimental and may not work as desired.

Details

Wrapper for correctReadcount in HMMcopy package. It uses a sampling of 50000 bins to find the Loess fit. Then, the log ratio for every bin is returned as the log base 2 of the ratio between the corrected tumour read count and the corrected normal read count.

Value

data.frame containing columns:

chr	Chromosome; uses 'X' and 'Y' for sex chromosomes
start	Start genomic coordinate for bin in which read count is corrected
end	End genomic coordinate for bin in which read count is corrected
logR	Log ratio, log2(tumour:normal), for bin in which read count is corrected

Author(s)

Gavin Ha <[e-mail]>, Daniel Lai <[e-mail]>, Yikan Wang <[e-mail]>

References

Ha, G., Roth, A., Lai, D., Bashashati, A., Ding, J., Goya, R., Giuliany, R., Rosner, J., Oloumi, A., Shumansky, K., Chin, S.F., Turashvili, G., Hirst, M., Caldas, C., Marra, M. A., Aparicio, S., and Shah, S. P. (2012). Integrative analysis of genome wide loss of heterozygosity and monoallelic expression at nucleotide resolution reveals disrupted pathways in triple negative breast cancer. Genome Research, 22(10):1995,2007. (PMID: 22637570)

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

correctReadcount and wigToRangedData in the HMMcopy package. WIG: http://genome.ucsc.edu/goldenPath/help/wiggle.html

Examples

tumWig <- system.file("extdata", "test_tum_chr2.wig", package = "TitanCNA")
normWig <- system.file("extdata", "test_norm_chr2.wig", package = "TitanCNA")
gc <- system.file("extdata", "gc_chr2.wig", package = "TitanCNA")
map <- system.file("extdata", "map_chr2.wig", package = "TitanCNA")

#### GC AND MAPPABILITY CORRECTION ####
cnData <- correctReadDepth(tumWig, normWig, gc, map)

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