normalizeCounts: Calculating the normalized M scores

In MDTS: Detection of de novo deletion in targeted sequencing trios

Description

This function will return a matrix of normalized M scores where ecah column is a sample, and each row is a bin.

Usage

normalizeCounts(counts, bins, GC = TRUE, map = TRUE, mc.cores = 1)

Arguments

counts	A matrix of raw coverage output by calcCounts().
bins	The set of bins determined by calcBins().
GC	Whether to loess adjust for GC. Defaults to TRUE.
map	Whether to loess adjust for mappability. Defaults to TRUE. Defaults to 1.
mc.cores	The number of cores to use for multi-threaded analysis.

Value

A data.frame of normalized counts. Each column is a sample, and each row is a entry of bins.

Examples

load(system.file("extdata", 'bins.RData', package = "MDTS"))
load(system.file("extdata", 'counts.RData', package = "MDTS"))
load(system.file("extdata", 'pD.RData', package = "MDTS"))
mCounts <- normalizeCounts(counts, bins)

MDTS documentation built on Nov. 8, 2020, 6:23 p.m.