roar (version 1.6.0)

countPrePost: Counts reads falling over PRE/POST portions of the given transcripts

Description

This is the first step in the Roar analyses: it counts reads overlapping with the PRE/POST portions defined in the given gtf/GRanges annotation. See RoarDataset for details on how to define these portions. Reads of the given bam annotation files that falls over this portion are accounted for with the following rules: 1- reads that align on only one of the given features are assigned to that feature, even if the overlap is not complete 2- reads that align on both a PRE and a POST feature of the same gene (spanning reads) are assigned to the POST one, considering that they have clearly been obtained from the longer isoform If the stranded argument is set to TRUE then strandness is considered when counting reads.

Usage

countPrePost(rds, stranded=FALSE)

Arguments

rds

The RoarDataset which contains the alignments and annotation informations over which counts will be performed.

stranded

A logical indicating if strandness should be considered when counting reads or not. Default=FALSE.

Value

The RoarDataset object given as rds with the counting reads phase of the analysis done. Counts will be held in the RoarDataset object itself in the case of single samples, while in two slots otherwise, but end user normally should not analyze those directly.

Examples

   library(GenomicAlignments)
   gene_id <- c("A_PRE", "A_POST", "B_PRE", "B_POST")
   features <- GRanges(
      seqnames = Rle(c("chr1", "chr1", "chr2", "chr2")),
      strand = strand(rep("+", length(gene_id))),
      ranges = IRanges(
         start=c(1000, 2000, 3000, 3600),
         width=c(1000, 900, 600, 300)),
      DataFrame(gene_id)
   )
   rd1 <- GAlignments("a", seqnames = Rle("chr1"), pos = as.integer(1000), cigar = "300M", strand = strand("+"))
   rd2 <- GAlignments("a", seqnames = Rle("chr1"), pos = as.integer(2000), cigar = "300M", strand = strand("+"))
   rd3 <- GAlignments("a", seqnames = Rle("chr2"), pos = as.integer(3000), cigar = "300M", strand = strand("+"))
   rds <- RoarDataset(list(c(rd1,rd2)), list(rd3), features)
   rds <- countPrePost(rds)