sliceCounts {riboSeqR} | R Documentation

## Slices out count data from riboCoding object for use in differential translation analyses.

### Description

For any given coding sequence, multiple lengths of reads in various frames (relative to coding start) may align. This function extracts specific size-classes and frames of ribosome footprint reads and sums them to give a single value for each coding sequence and each sequencing library, for use in downstream analysis.

### Usage

    sliceCounts(rC, lengths = 27, frames)

### Arguments

`rC` | A `riboCoding` object containing the coordinates of the coding sequences and the number of ribosomal footprint reads of various classes to be found in each.
`lengths` | Lengths of ribosome footprints to inform count data.
`frames` | Frames of ribosome footprints (relative to coding start site). If omitted, all frames are used.

### Details

Frames can be given as a single vector (which specifies the frames used for all lengths of footprints, or as a list, specifying the frame for each length given in ‘lengths’.

The count data thus acquired can be compared to counts of RNA-seq data through a beta-binomial analysis (see vignette) to discover differential translation.

### Value

A matrix containing counts of ribosomal footprint matches to coding sequences specified in riboCoding object ‘rC’.

### Author(s)

Thomas J. Hardcastle

### See Also

`rnaCounts`

### Examples

    #ribosomal footprint data
    datadir <- system.file("extdata", package = "riboSeqR")
    ribofiles <- paste(datadir,
                       "/chlamy236_plus_deNovo_plusOnly_Index", c(17,3,5,7), sep = "")
    rnafiles <- paste(datadir,
                      "/chlamy236_plus_deNovo_plusOnly_Index", c(10,12,14,16), sep = "")

    riboDat <- readRibodata(ribofiles, rnafiles, replicates = c("WT", "WT",
    "M", "M"))

    # CDS coordinates
    chlamyFasta <- paste(datadir, "/rsem_chlamy236_deNovo.transcripts.fa", sep = "")
    fastaCDS <- findCDS(fastaFile = chlamyFasta,
                        startCodon = c("ATG"),
                        stopCodon = c("TAG", "TAA", "TGA"))

    # frame calling
    fCs <- frameCounting(riboDat, fastaCDS)

    # analysis of frame shift for 27 and 28-mers.
    fS <- readingFrame(rC = fCs, lengths = 27:28)

    # filter coding sequences. 27-mers are principally in the 1-frame,
    # 28-mers are principally in the 0-frame relative to coding start (see
    # readingFrame function).

    ffCs <- filterHits(fCs, lengths = c(27, 28), frames = list(1, 0),
                       hitMean = 50, unqhitMean = 10, fS = fS)

    # Extract counts of ribosomal footprints from riboCount data.

    riboCounts <- sliceCounts(ffCs, lengths = c(27, 28), frames = list(0,
    2))

[Package riboSeqR version 1.24.0 Index]