The function divides closely spaced transcripts into individually transcribed units using the detected active transcription start sites.
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One of the challenges for primary transcript detection concerns the
simultaneous transcription of closely spaced genes, which needs to be
properly divided into individually transcribed units.
combines RNA-seq data with ChIP-seq data of histone modifications that
mark active Transcription Start Sites (TSSs), such as, H3K4me3 or H3K9/14Ac
to overcome this challenge. The advantage of this approach over the use of,
for example, gene annotations is that this approach is data driven and
therefore able to deal also with novel and case specific events. Furthermore,
the integration of ChIP- and RNA-seq data allows the identification all
known and novel active transcription start sites within a given sample.
Transcription initiation within a peak region is investigated by comparing
RNA-seq read densities upstream and downstream of empirically determined TSSs.
Closely spaced transcripts are divided into individually transcribed units
using the detected active TSSs.
transcripts of the provided
TranscriptionDataSet object will be updated by the
GRanges object, containing transcripts and,
if estimated, corresponding expression levels.
Armen R. Karapetyan
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### Load TranscriptionDataSet object data(tds) ### Load ChipDataSet object data(cds) ### Load reference annotations (knownGene from UCSC) data(annot) ### Detect transcripts detectTranscripts(object = tds, coverage.cutoff = 5, gap.dist = 4000, estimate.params = TRUE, combine.by.annot = FALSE, annot = annot) ### Classify peaks on gene associated and background predictTssOverlap(object = cds, feature = "pileup", p = 0.75) ### Predict peak 'strand' predictStrand(cdsObj = cds, tdsObj = tds, coverage.cutoff = 5, quant.cutoff = 0.1, win.size = 2500) ### If `estimate.params = TRUE`, FPKM and coverage density will be re-calculated breakTranscriptsByPeaks(tdsObj = tds, cdsObj = cds, estimate.params = TRUE) ### View detected transcripts getTranscripts(tds)