derfinder (version 1.4.0)

findRegions: Find non-zero regions in a Rle

Description

Find genomic regions for which a numeric vector is above (or below) predefined thresholds. In other words, this function finds the candidate Differentially Expressed Regions (candidate DERs). This is similar to regionFinder and is a helper function for calculatePvalues.

Usage

findRegions(position = NULL, fstats, chr, oneTable = TRUE, maxClusterGap = 300L, cutoff = quantile(fstats, 0.99), segmentIR = NULL, ...)

Arguments

position

A logical Rle of genomic positions. This is generated in loadCoverage. Note that it gets updated in preprocessCoverage if colsubset is not NULL.

fstats

A numeric Rle with the F-statistics. Usually obtained using calculateStats.

chr

A single element character vector specifying the chromosome name.

oneTable

If TRUE only one GRanges is returned. Otherwise, a GRangesList with two components is returned: one for the regions with positive values and one for the negative values.

maxClusterGap

This determines the maximum gap between candidate DERs. It should be greater than maxRegionGap (0 by default).

cutoff

Threshold applied to the fstats used to determine the #' regions.

segmentIR

An IRanges object with the genomic positions that are potentials DERs. This is used in calculatePvalues to speed up permutation calculations.

...

Arguments passed to other methods and/or advanced arguments.

Value

Either a GRanges or a GRangesList as determined by oneTable. Each of them has the following metadata variables.

value

The mean of the values of y for the given region.

area

The absolute value of the sum of the values of y for the given region.

indexStart

The start position of the region in terms of the index for y.

indexEnd

The end position of the region in terms of the index for y.

cluster

The cluser ID.

clusterL

The total length of the cluster.

Details

regionFinder adapted to Rle world.

References

Rafael A. Irizarry, Martin Aryee, Hector Corrada Bravo, Kasper D. Hansen and Harris A. Jaffee. bumphunter: Bump Hunter. R package version 1.1.10.

See Also

calculatePvalues

Examples

## Preprocess the data
prep <- preprocessCoverage(genomeData, cutoff=0, scalefac=32, chunksize=1e3,
    colsubset=NULL)

## Get the F statistics
fstats <- genomeFstats

## Find the regions
regs <- findRegions(prep$position, fstats, 'chr21', verbose=TRUE)
regs

## Not run: 
# ## Once you have the regions you can proceed to annotate them
# library('bumphunter')
# library('TxDb.Hsapiens.UCSC.hg19.knownGene')
# genes <- annotateTranscripts(TxDb.Hsapiens.UCSC.hg19.knownGene)
# annotation <- matchGenes(regs, genes)
# annotation
# ## End(Not run)