RoarDataset {roar} | R Documentation |
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
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
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)
[Package
roar version 1.30.0
Index]