quantifyCTSSs2: Quantify CAGE Transcriptions Start Sites (CTSSs)

In MalteThodberg/CAGEfightR: Analysis of Cap Analysis of Gene Expression (CAGE) data using Bioconductor

Description

This function reads in CTSS count data from a series of BigWig-files and returns a CTSS-by-library count matrix. For efficient processing, the count matrix is stored as a sparse matrix (dgCMatrix).

Usage

quantifyCTSSs2(
  plusStrand,
  minusStrand,
  design = NULL,
  genome = NULL,
  tileWidth = 100000000L
)

Arguments

plusStrand	BigWigFileList: BigWig files with plus-strand CTSS data.
minusStrand	BigWigFileList: BigWig files with minus-strand CTSS data.
design	DataFrame or data.frame: Additional information on samples.
genome	Seqinfo: Genome information. If NULL the smallest common genome will be found using bwCommonGenome.
tileWidth	integer: Size of tiles to parallelize over.

Value

RangedSummarizedExperiment, where assay is a sparse matrix (dgCMatrix) of CTSS counts..

See Also

Other Quantification functions: quantifyCTSSs(), quantifyClusters(), quantifyGenes()

Examples

## Not run: 
# Load the example data
data('exampleDesign')
# Use the BigWig-files included with the package:
bw_plus <- system.file('extdata', exampleDesign$BigWigPlus,
                       package = 'CAGEfightR')
bw_minus <- system.file('extdata', exampleDesign$BigWigMinus,
                        package = 'CAGEfightR')

# Create two named BigWigFileList-objects:
bw_plus <- BigWigFileList(bw_plus)
bw_minus <- BigWigFileList(bw_minus)
names(bw_plus) <- exampleDesign$Name
names(bw_minus) <- exampleDesign$Name

# Quantify CTSSs, by default this will use the smallest common genome:
CTSSs <- quantifyCTSSs(plusStrand=bw_plus,
                       minusStrand=bw_minus,
                       design=exampleDesign)

# Alternatively, a genome can be specified:
si <- seqinfo(bw_plus[[1]])
si <- si['chr18']
CTSSs <- quantifyCTSSs(plusStrand=bw_plus,
                       minusStrand=bw_minus,
                       design=exampleDesign,
                       genome=si)

# Quantification can be speed up by using multiple cores:
library(BiocParallel)
register(MulticoreParam(workers=3))
CTSSs <- quantifyCTSSs(plusStrand=bw_plus,
                       minusStrand=bw_minus,
                       design=exampleDesign,
                       genome=si)

## End(Not run)

MalteThodberg/CAGEfightR documentation built on Sept. 11, 2021, 4:42 a.m.