RoarDataset-constructor: Creates a 'RoarDataset' object

Description Usage Arguments Value See Also Examples

Description

This function creates an RoarDataset object from two lists of of GAlignments and a GRanges containing a suitable annotation of alternative APA sites.

Usage

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      RoarDataset(treatmentGappedAlign, controlGappedAlign, gtfGRanges)
     

Arguments

treatmentGappedAlign

A list of GAlignments representing alignment of samples for the treatment condition (by convention it is considered the “treated” condition: this simply means that the package will compute roar values (ratios of the m/M) using this condition as the numerator) to be considered.

controlGappedAlign

A list of GAlignments representing alignment of samples for the control condition to be considered.

gtfGRanges

A GRanges object with coordinates for the portions of transcripts that has to be considered pertaining to the short (or long) isoform. This GRanges object must have a character metadata column called "gene_id" that ends with "_PRE" or "_POST" to address respectively the short and the long isoform. An element in the annotation is considered "PRE" (i.e. common to the short and long isoform of the transcript) if its gene_id ends with "_PRE". If it ends with "_POST" it is considered the portion present only in the long isoform. The prefix of gene_id should be a unique identifier for the gene and each identifier has to be associated with only one "_PRE" and one "_POST", leading to two genomic region associated to each gene_id. The GRanges object can also contain a numeric metadata column that represents the lengths of PRE and POST portions on the transcriptome. If this is omitted the lengths on the genome are used instead. Note that right now every gtf entry (or none of them) should have it.

Value

A RoarDataset object ready to be analyzed via the other methods.

See Also

RoarDatasetFromFiles

Examples

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   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)
    

vodkatad/roar documentation built on June 26, 2018, 2:10 a.m.