countResults-method: Returns a dataframe with results of the analysis for a...

In roar: Identify differential APA usage from RNA-seq alignments

Description

The last step of a classical Roar analyses: it returns a dataframe containing m/M values, roar values, pvalues and estimates of expression (number of reads falling over the PRE portions).

Usage

      countResults(rds)
     

Arguments

rds	The RoarDataset or the RoarDatasetMultipleAPA with all the analysis steps (countPrePost, computeRoars, computePvals) performed. If one or more steps hadn't been performed they will be called automatically.

Value

The resulting dataframe will be identical to that returned by link{totalResults} but with two columns added: "treatmentValue" and "controlValue". These columns will contain a number that indicates the level of expression of the relative gene in the treatment (or control) condition. For RoarDataset this number represents the counts (averaged across samples when applicable) obtained for the PRE portion of the gene. For RoarDatasetMultipleAPA every possible PRE choice will have its corresponding reads counts assigned and also the length of the PRE portion (counting only exonic bases). See the vignette for more details.

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, FALSE)
   rds <- computeRoars(rds)
   rds <- computePvals(rds)
   dat <- countResults(rds)
    

roar documentation built on Nov. 8, 2020, 4:50 p.m.