mvFit: Estimate expression magnitude variance as a function of...

In JEFworks/badger: Bayesian approach for detecting copy number alterations from single cell RNA-seq data

Description

Estimate expression magnitude variance as a function of number of genes

Usage

mvFit(gexp, num.genes = seq(5, 100, by = 5), rep = 1000, plot = FALSE)

Arguments

gexp	Normalized gene expression matrix, preferably restricted to region of known neutral copy number
num.genes	List of number of genes for random sampling. Default: seq(5, 100, by=5)
rep	Number of replicates. Default: 1000
plot	Boolean of whether to plot. Default: FALSE

Value

Fit for variance around mean normalized gene expression as a function of the number of genes for each cell

Examples

data('MM16.counts')
mat <- log2(MM16.counts + 1)
data('Normal.counts')
mat.ref <- log2(Normal.counts + 1)
mats <- normalizedExpression(mat, mat.ref)
gexp <- mats[[1]]
fits <- mvFit(gexp)

JEFworks/badger documentation built on May 7, 2019, 7:40 a.m.