exportCoverage

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Description

RNA-seq coverage profiles for both forward and reverse DNA strand can be visualized separately in the UCSC genome browser using exportCoverage. This function can generate tracks in BigWig and bedGraph formats, which can be uploaded to the genome browser as custom tracks.

Usage

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exportCoverage(object, file, type, strand, color,
  filter.by.coverage.cutoff = FALSE, coverage.cutoff = NULL, rpm = FALSE,
  total.reads)

## S4 method for signature 'TranscriptionDataSet'
exportCoverage(object, file, type, strand,
  color, filter.by.coverage.cutoff = FALSE, coverage.cutoff = NULL,
  rpm = FALSE, total.reads)

Arguments

object

A TranscriptionDataSet object.

file

Character. A file name.

type

Character. Track type, either "bigWig" or "bedGraph". Default: "bedGraph".

strand

Character. The strand to create a track for. One of ["+", "-"].

color

Object of class "integer" representing the track color (as from col2rgb). Only works with tracks of type "bedGraph". Default: c(0L, 0L, 255L).

filter.by.coverage.cutoff

Logical. Whether to discard regions with low fragment coverage, representing expression noise from the resulting track. Default: FALSE.

coverage.cutoff

Numeric. A cutoff value to discard regions with the low fragment coverage, representing expression noise. By default, the value stored in the coverageCutoff slot of the supplied object is used. The optimal cutoff value can be calculated by estimateBackground function call. Default: NULL.

rpm

Logical. Whether to perform normalization ('Reads Per Million'). Default: FALSE.

total.reads

Numeric. Total number of reads used for normalization. By default, the total number of reads stored in the provided TranscriptionDataSet object is used.

Details

There is an option to filter coverage profiles by the coverage cutoff value, either estimated for a specific FDR via estimateBackground or a user specified value. By default, the coverage cutoff value stored in the TranscriptionDataSet object is used. In order to make an informed decision about a proper FDR level, it is useful to explore the output at different FDR levels and determine the optimal cutoff value.

Value

A file in either BigWig or bedGraph format.

Author(s)

Armen R. Karapetyan

See Also

estimateBackground UCSC genome browser BigWig

Examples

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### Load TranscriptionDataSet object
data(tds)

### Look at the coverage profile of the regions expressed above the background level
# exportCoverage(object = tds, file = "plus.bg", type = "bedGraph", strand = "+",
# filter.by.coverage.cutoff = TRUE, coverage.cutoff = 3, rpm = FALSE)

### Or check the raw coverage (all expressed regions)
# exportCoverage(object = tds, file = "plus_raw.bg", type = "bedGraph",
# strand = "+", filter.by.coverage.cutoff = FALSE, rpm = FALSE)