HoneyBADGER_calcAlleleCnvBoundaries: Recursive HMM to identify CNV boundaries using allele data

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

Description

Recursive HMM to identify CNV boundaries using allele data

Arguments

r.sub	Optional matrix of alt allele count in single cells. If not provided, internal r.sc matrix is used.
n.sub	Optional matrix of site coverage count in single cells. If not provided, internal n.sc matrix is used.
l.sub	Optional vector of alt allele count in pooled single cells or bulk. If not provided, internal l vector is used.
n.bulk.sub	Optional vector of site coverage count in pooled single cells or bulk. If not provided, internal n.bulk vector is used.
min.traverse	Depth traversal to look for subclonal CNVs. Higher depth, potentially smaller subclones detectable. (default: 3)
t	HMM transition parameter. Higher number, more transitions. (default: 1e-6)
pd	Probability of lesser allele detection in deleted region (ie. due to error)
pn	Probability of lesser allele detection in neutral region (ie. 0.5 - error rate)
min.num.snps	Minimum number of snps in candidate CNV
trim	Trim boundary SNPs
init	Boolean whether to initialize
verbose	Verbosity(default: FALSE)
...	Additional parameters to pass to calcAlleleCnvProb

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