Description Usage Arguments Details Value Author(s) See Also Examples
The function dissects transcribed regions (transcripts) genome-wide and performs expression level quantification.
1 2 3 4 5 6 7 | detectTranscripts(object, coverage.cutoff, gap.dist, estimate.params = TRUE,
total.reads, combine.by.annot = FALSE, annot)
## S4 method for signature 'TranscriptionDataSet'
detectTranscripts(object, coverage.cutoff,
gap.dist, estimate.params = TRUE, total.reads, combine.by.annot = FALSE,
annot)
|
object |
A |
coverage.cutoff |
|
gap.dist |
|
estimate.params |
|
total.reads |
|
combine.by.annot |
|
annot |
|
The function uses two parameters to identify transcribed regions:
coverage.cutoff
and gap.dist
as calculated by the
estimateBackground
and estimateGapDistance
,
respectively and stored in the TranscriptionDataSet
object.
Alternatively, the user may specify his/her own values to be passed to
the function. By increasing the gap.dist
, fewer transcripts of
longer size will be identified, and an increase in the coverage.cutoff
will result in fewer transcripts of shorter size (a typical transcript tends
to have a lower fragments coverage at the 3' end, and thus, the
coverage.cutoff
value will have an impact on the resulting length of
the detected transcript).
If estimate.params
is set TRUE, the following metrics are estimated for
each transcript:
length
- transcript length (in base pairs).
bases.covered
- the number of bases covered by the
sequencing fragments.
coverage
- the proportion of transcript length covered by
fragments. Value in the range (0, 1].
fragments
- total number of fragments per transcript.
fpkm
- Fragments Per Kilobase of transcript per Million
mapped reads.
The coverage
is a measure of how densely the transcript is covered by
the sequencing fragments. Modestly/highly expressed transcripts will have
a value close to 1, whereas lowly expressed transcripts will have a
value close to 0, indicating the sparse distribution of sequencing
fragments along the transcript body.
The slot transcripts
of the provided
TranscriptionDataSet
object will be updated by the
GRanges
object, containing detected
transcripts and, if estimated, corresponding expression levels.
Armen R. Karapetyan
1 2 3 4 5 6 7 8 9 10 11 12 | ### Load TranscriptionDataSet object
data(tds)
### 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)
### View detected transcripts
getTranscripts(tds)
|
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