metaGene: Returns a histogram of the number of reads in each section of...

In groHMM: GRO-seq Analysis Pipeline

Description

Supports parallel processing using mclapply in the 'parallel' package. To change the number of processors, set the option 'mc.cores'.

Usage

metaGene(features, reads = NULL, plusCVG = NULL, minusCVG = NULL,
  size = 100L, up = 10000L, down = NULL, ...)

Arguments

features	A GRanges object representing a set of genomic coordinates. The meta-plot will be centered on the transcription start site (TSS)
reads	A GRanges object representing a set of mapped reads. Instead of 'reads', 'plusCVG' and 'minusCVG' can be used Default: NULL
plusCVG	An IntegerRangesList object for reads with '+' strand.
minusCVG	An IntegerRangesList object for reads with '-' strand.
size	The size of the moving window.
up	Distance upstream of each features to align and histogram. Default: 10 kb.
down	Distance downstream of each features to align and histogram. If NULL, same as up. Default: NULL.
...	Extra argument passed to mclapply

Value

Returns a integer-Rle representing the 'typical' signal centered on a point of interest.

Author(s)

Charles G. Danko and Minho Chae

Examples

features <- GRanges("chr7", IRanges(1000, 1000), strand="+")
reads <- GRanges("chr7", IRanges(start=c(1000:1004, 1100),
 width=rep(1, 6)), strand="+")
mg <- metaGene(features, reads, size=4, up=10)

groHMM documentation built on Nov. 8, 2020, 8:09 p.m.