countsPlot {RiboProfiling} | R Documentation

## Graphs of sample read counts (quality assesment)

### Description

Graphs of sample read counts (quality assesment)

### Usage

    countsPlot(listCounts, ixCounts, log2Bool)

### Arguments

`listCounts` | a list of data.frame objects. It contains the counts on the genomic features. Each data.frame in the list should have the same number of columns.
`ixCounts` | a numeric (a vector of integers). It contains the index of the columns containing counts in the dataFrame.
`log2Bool` | a numeric, either 0 or 1. 0 (default) for no log2 transformation and 1 for log2 transformation.

### Value

A list of pairs and boxplots between the counts data in each data.frame.

### Examples

    #read the BAM file into a GAlignments object using
    #GenomicAlignments::readGAlignments
    #the GAlignments object should be similar to ctrlGAlignments
    data(ctrlGAlignments)
    aln <- ctrlGAlignments

    #transform the GAlignments object into a GRanges object (faster processing)
    alnGRanges <- readsToStartOrEnd(aln, what="start")

    #make a txdb object containing the annotations for the specified species.
    #In this case hg19.
    txdb <- TxDb.Hsapiens.UCSC.hg19.knownGene::TxDb.Hsapiens.UCSC.hg19.knownGene
    #Please make sure that seqnames of txdb correspond to
    #the seqnames of the alignment files ("chr" particle)
    #if not rename the txdb seqlevels
    #renameSeqlevels(txdb, sub("chr", "",seqlevels(txdb)))
    #get the flanking region around the promoter of the best expressed CDSs

    #get all CDSs by transcript
    cds <- GenomicFeatures::cdsBy(txdb,by="tx",use.names=TRUE)

    #get all exons by transcript
    exonGRanges <- GenomicFeatures::exonsBy(txdb,by="tx",use.names=TRUE)

    #get the per transcript relative position of start and end codons
    cdsPosTransc <- orfRelativePos(cds, exonGRanges)

    #compute the counts on the different features after applying
    #the specified shift value on the read start along the transcript
    countsData <-
       countShiftReads(
             exonGRanges[names(cdsPosTransc)],
             cdsPosTransc,
             alnGRanges,
             -14
         )

    #now make the plots
    listCountsPlots <- countsPlot(
       list(countsData[[1]]),
       grep("_counts$", colnames(countsData[[1]])),
       1
    )
    listCountsPlots

[Package RiboProfiling version 1.16.0 Index]