quantifyCTSSs2 {CAGEfightR} | R Documentation

## Quantify CAGE Transcriptions Start Sites (CTSSs)

### 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)

[Package CAGEfightR version 1.10.0 Index]