calcCombCnvProb: Calculate posterior probability of CNVs using normalized...

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 normalized expression data and allele data

Usage

calcCombCnvProb(gexp.norm, genes, mvFit, m = 0.15, r.maf, n.sc, l.maf, n.bulk,
  snps, geneFactor, region = NULL, filter = FALSE, pe = 0.1, mono = 0.7,
  verbose = FALSE)

Arguments

gexp.norm	Normalized gene expression matrix.
genes	GRanges annotation of gene names and coordinates
mvFit	Mean variance fit
m	Expression deviation due to copy number change (default: 0.15)
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	Optional GenomicRanges region of interest such as expected CNV boundaries. (default: NULL)
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)

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