calcAlleleCnvProb: Calculate posterior probability of CNVs using allele data

In JEFworks/HoneyBADGER: HMM-integrated Bayesian approach for detecting CNV and LOH events using single-cell RNA-seq data

Description

Calculate posterior probability of CNVs using allele data

Usage

calcAlleleCnvProb(r.maf, n.sc, l.maf, n.bulk, snps, geneFactor, region = NULL,
  filter = FALSE, pe = 0.1, mono = 0.7, verbose = FALSE)

Arguments

r.maf	Matrix of alt allele count in single cells.
n.sc	Matrix of site coverage count in single cells.
l.maf	Vector of alt allele count in pooled single cells or bulk.
n.bulk	Vector of site coverage count in pooled single cells or bulk.
snps	SNP annotations
geneFactor	Output of setGeneFactors
region	GenomicRanges region of interest such as expected CNV boundaries.
filter	Boolean for whether to filter out SNP sites with no coverage. (default: TRUE)
pe	Effective error rate to capture error from sequencing, etc. (default: 0.01)
mono	Rate of mono-allelic expression. (default: 0.7)
verbose	Verbosity(default: FALSE)

Examples

data(r)
data(cov.sc)
allele.mats <- setAlleleMats(r, cov.sc)
library(TxDb.Hsapiens.UCSC.hg19.knownGene)
geneFactor <- setGeneFactors(allele.mats$snps, TxDb.Hsapiens.UCSC.hg19.knownGene)
## test region known to be commonly deleted in glioblastoma
results <- calcAlleleCnvProb(allele.mats$r.maf, allele.mats$n.sc, 
    allele.mats$l.maf, allele.mats$n.bulk, allele.mats$snps, geneFactor, 
    region=GenomicRanges::GRanges('chr10', IRanges::IRanges(0,1e9)), verbose=TRUE)

JEFworks/HoneyBADGER documentation built on July 24, 2021, 3:01 p.m.