In UPSCb/RnaSeqTutorial: RNA-Seq Tutorial

startQuest("Synthetic transcript")

    h1("Interlude")

In this chapter, we will shortly go back to computational optimisation.

    library(RnaSeqTutorial)
    bamfiles <- dir(file.path(extdata(),"BAM"),
                   pattern="*.bam$",full.names=TRUE)
    bamFileList <- BamFileList(bamfiles,yieldSize=10^6)

As you have been introduced to the GenomicAlignments functionalities to find count or summarize overlaps between reads and annotations, we can refine our prefered function. We had left it as:

    gAlns <- mclapply(bamFileList,function(bamFile){
     open(bamFile)
     gAln <- GAlignments()
     while(length(chunk <- readGAlignments(bamFile))){
       gAln <- c(gAln,chunk)
     }
     close(bamFile)
     return(gAln)
    })

Using our synthetic transcript annotation: Ptrichocarpa_v3.0_210_synthetic_transcripts.rda, implement the count by chunks.

    data("Ptrichocarpa_v3.0_210_synthetic_transcripts")
    count.list <- mclapply(bamFileList,function(bamFile,annot){
    open(bamFile)
    counts <- vector(mode="integer",length=length(annot))
    while(length(chunk <- readGAlignments(bamFile))){
       counts <- counts + assays(summarizeOverlaps(annot,
                                                   chunk,
                                                   mode="Union",
                                                   ignore.strand=TRUE))$counts
    }
    close(bamFile)
    return(counts)
    },syntheticTrx[syntheticTrx$type == "exon"])

This gives us a list of counts per sample, to get a count matrix do:

    count.table <- do.call("cbind",count.list)
    head(count.table[rowSums(count.table)>0,])

Such a count table object is the minimal input that downstream analysis softwares - e.g.: DESeq2, edgeR, uses.

A similar function to this is probably all you"ll need to process your read and get a count table from a standard Illumina based RNA-Seq experiment. However, you might want more flexibility for you projects and certainly Bioconductor offer the possibilities to do that; examples of which are given in the next chapter.