detectTranscripts {transcriptR} | R Documentation

## detectTranscripts

### Description

The function dissects transcribed regions (transcripts) genome-wide and performs expression level quantification.

### Usage

    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)

### Arguments

`object` | A `TranscriptionDataSet` object.
`coverage.cutoff` | `Numeric`. A cutoff value to discard regions with the low fragments coverage, representing expression noise. By default, the value stored in the `coverageCutoff` slot of the supplied `TranscriptionDataSet` object is used. The optimal cutoff value can be calculated by `estimateBackground` function call.
`gap.dist` | `Numeric`. Maximum allowed distance between transcribed regions to be merged into the one transcript. By default, the value stored in the `gapDistanceTest` slot of the supplied `TranscriptionDataSet` object is used. The optimal gap distance can be calculated by `estimateGapDistance` function call.
`estimate.params` | `Logical`. Whether to estimate expression level and coverage density of the detected transcripts. Default: TRUE.
`total.reads` | `Numeric`. Total number of reads used for the normalization, when calculating FPKM. By default, the total number of reads stored in the provided `TranscriptionDataSet` object is used.
`combine.by.annot` | `Logical`. Whether to combine transcripts overlapping the same reference annotation. Default: FALSE.
`annot` | `GRanges`. Reference annotations.

### Details

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.

### Value

The slot `transcripts` of the provided `TranscriptionDataSet` object will be updated by the `GRanges` object, containing detected transcripts and, if estimated, corresponding expression levels.

### Author(s)

Armen R. Karapetyan

### See Also

`constructTDS`

### Examples

    ### 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)

[Package transcriptR version 1.8.0 Index]