runMetaGene: Runs meta gene analysis for sense and anti-sense direction.

In omsai/groHMM: GRO-seq Analysis Pipeline

Description

Runs meta gene analysis for sense and anti-sense direction.

Usage

runMetaGene(features, reads, anchorType = "TSS", size = 100L,
  normCounts = 1L, up = 10000L, down = NULL, sampling = FALSE,
  nSampling = 1000L, samplingRatio = 0.1, BPPARAM = bpparam())

Arguments

features	GRanges A GRanges object representing a set of genomic coordinates, i.e., set of genes.
reads	GRanges of reads.
anchorType	Either 'TSS' or 'TTS'. Meta gene will be centered on the transcription start site(TSS) or transcription termination site(TTS). Default: TSS.
size	Numeric. The size of the moving window. Default: 100L
normCounts	Numeric. Normalization vector such as average reads. Default: 1L
up	Numeric. Distance upstream of each feature to align and histogram. Default: 1 kb
down	Numeric. Distance downstream of each feature to align and histogram. If NULL, down is same as up. Default: NULL
sampling	Logical. If TRUE, sub-sampling of meta gene is used. Default: FALSE
nSampling	Numeric. Number of sub-sampling. Default: 1000L
samplingRatio	Numeric. Ratio of sampling for features. Default: 0.1
BPPARAM	Registered backend for BiocParallel. Default: BiocParallel::bpparam()

Value

A list of integer-Rle for sense and anti-sense.

Author(s)

Minho Chae

Examples

library(GenomicRanges)
features <- GRanges("chr7", IRanges(start=1000:1001, width=rep(1,2)),
 strand=c("+", "-"))
reads <- GRanges("chr7", IRanges(start=c(1000:1003, 1100:1101),
 width=rep(1, 6)), strand=rep(c("+","-"), 3))
## Not run:
# mg <- runMetaGene(features, reads, size=4, up=10)

omsai/groHMM documentation built on May 24, 2019, 2:18 p.m.