MBASED (version 1.6.0)

shiftAndAttenuateProportions: Helper function to adjust proportions for pre-existing allelic bias and also to obtain estimate of proportion variance based on attenuated read counts (adding pseudocount of 0.5 to each allele in each sample).

Description

Helper function to adjust proportions for pre-existing allelic bias and also to obtain estimate of proportion variance based on attenuated read counts (adding pseudocount of 0.5 to each allele in each sample).

Usage

shiftAndAttenuateProportions(countsMat, totalsMat, probsMat, rhosMat, checkArgs = FALSE)

Arguments

countsMat

matrix of observed major allele counts. Each row represents a specific genomic locus, while each column represents a set of observed major allele counts across loci (in practice, multiple columns represent different outcomes of count simulations).

totalsMat

matrix of total read counts across both alleles. The interpretation of rows and columns is the same as for countsMat.

probsMat

matrix of underlying probabilites of observing the major allele. The interpretation of rows and columns is the same as for countsMat.

rhosMat

matrix of dispersion parameters of beta distributions for each locus. The interpretation of rows and columns is the same as for countsMat.

checkArgs

single boolean specifying whether arguments should be checked for adherence to specifications. DEFAULT: FALSE

Value

a list with 2 elements:

propsShifted

a 1-row marix of shifted major allele frequencies

propsShiftedVars

a 1-row matrix of estimated variances of obtained MAF estimates

Examples

SNVCoverageTumor=sample(10:100,10) ## 2 genes with 5 loci each
SNVAllele1CountsTumor=rbinom(length(SNVCoverageTumor), SNVCoverageTumor, 0.5)
MBASED:::shiftAndAttenuateProportions(countsMat=matrix(SNVAllele1CountsTumor, ncol=2), totalsMat=matrix(SNVCoverageTumor, ncol=2), probsMat=matrix(rep(0.5, length(SNVCoverageTumor)), ncol=2),  rhosMat=matrix(rep(0, length(SNVCoverageTumor)), ncol=2))