gcComp: Calculate weights for GC composition

In haibol2016/InPAS: Identify Novel Alternative PolyAdenylation Sites (PAS) from RNA-seq data

Calculate weights for GC composition

Description

Calculate read weights for GC composition-based coverage correction

Usage

gcComp(genome, seqnames, window = 50, future.chunk.size = NULL)

Arguments

genome	An object of BSgenome::BSgenome
seqnames	a character(n) vector, the chromosome/scaffolds' names in the same forms of seqnames in the BSgenome
window	size of a sliding window, which optimally is set to the read length
future.chunk.size	The average number of elements per future ("chunk"). If Inf, then all elements are processed in a single future. If NULL, then argument future.scheduling = 1 is used by default. Users can set future.chunk.size = total number of elements/number of cores set for the backend. See the future.apply package for details.

Value

A list of numeric vectors containing the weight (scaffold-level GC\ / GC\ chromosome/scaffold.

Author(s)

Jianhong Ou, Haibo Liu

References

Cheung et al. Systematic bias in high-throughput sequencing data and its correction by BEADS. Nucleic Acids Res. 2011 Aug;39(15):e103.

Examples

## Not run: 
library(BSgenome.Mmusculus.UCSC.mm10)
genome <- BSgenome.Mmusculus.UCSC.mm10
InPAS:::gcComp(genome, "chr1")

## End(Not run)

haibol2016/InPAS documentation built on March 30, 2022, 10:30 a.m.