HoneyBADGER_setGexpMats: Set gene expression matrices, normalizes, and maps genes to...

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

Description

Set gene expression matrices, normalizes, and maps genes to genomic coordinates

Arguments

gexp.sc.init	Single cell gene expression matrix
gexp.ref.init	Reference gene expression matrix such as from GTEX or a match normal
mart.obj	Biomart object used for mapping genes to genomic positions
filter	Boolean of whether or not to filter genes (default: TRUE)
minMeanBoth	Minimum mean gene expression in both the single cell and reference matrices (default: 4.5)
minMeanTest	Minimum mean gene expression for the single cell expression matrix (default: 6)
minMeanRef	Minimum mean gene expression for the reference expression matrix (default: 8)
scale	Boolean of whether or not to scale by library size (default: TRUE)
id	biomaRt ID for genes c(default: 'hgnc_symbol')
verbose	Verbosity (default: TRUE)

Examples

data(gexp)
data(ref)
require(biomaRt) ## for gene coordinates
mart.obj <- useMart(biomart = "ENSEMBL_MART_ENSEMBL", 
    dataset = 'hsapiens_gene_ensembl', 
    host = "jul2015.archive.ensembl.org")
hb <- HoneyBADGER$new()
hb$setGexpMats(gexp, ref, mart.obj, filter=FALSE, scale=FALSE)

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