subsetRegionsBySignal: Subset regions of interest by quantiles of overlapping signal

Description Usage Arguments Value Author(s) See Also Examples

View source: R/roi_functions.R

Description

A convenience function to subset regions of interest by the amount of signal they contain, according to their quantile (i.e. their signal ranks).

Usage

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subsetRegionsBySignal(
  regions.gr,
  dataset.gr,
  quantiles = c(0.5, 1),
  field = "score",
  order.by.rank = FALSE,
  density = FALSE,
  keep.signal = FALSE,
  expand_ranges = FALSE
)

Arguments

regions.gr

A GRanges object containing regions of interest.

dataset.gr

A GRanges object in which signal is contained in metadata (typically in the "score" field).

quantiles

A value pair giving the lower quantile and upper quantile of regions to keep. Regions with signal quantiles below the lower quantile are removed, and likewise for regions with signal quantiles above the upper quantile. Quantiles must be in range (0, 1). An empty GRanges object is returned if the lower quantile is set to 1 or if the upper quantile is set to 0.

field

The metadata field of dataset.gr to be counted, typically "score".

order.by.rank

If TRUE, the output regions are sorted based on the amount of overlapping signal (in decreasing order). If FALSE (the default), genes are sorted by their positions.

density

A logical indicating whether signal counts should be normalized to the width (chromosomal length) of ranges in regions.gr. By default, no length normalization is performed.

keep.signal

Logical indicating if signal counts should be kept. If set to TRUE, the signal for each range (length-normalized if density = TRUE) are kept as a new Signal metadata column in the output GRanges object.

expand_ranges

Logical indicating if ranges in dataset.gr should be treated as descriptions of single molecules (FALSE), or if ranges should be treated as representing multiple adjacent positions with the same signal (TRUE). See getCountsByRegions.

Value

A GRanges object of length length(regions.gr) * (upper_quantile - lower_quantile).

Author(s)

Mike DeBerardine

See Also

getCountsByRegions

Examples

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data("PROseq") # load included PROseq data
data("txs_dm6_chr4") # load included transcripts

txs_dm6_chr4

#--------------------------------------------------#
# get the top 50% of transcripts by signal
#--------------------------------------------------#

subsetRegionsBySignal(txs_dm6_chr4, PROseq)

#--------------------------------------------------#
# get the middle 50% of transcripts by signal
#--------------------------------------------------#

subsetRegionsBySignal(txs_dm6_chr4, PROseq, quantiles = c(0.25, 0.75))

#--------------------------------------------------#
# get the top 10% of transcripts by signal, and sort them by highest signal
#--------------------------------------------------#

subsetRegionsBySignal(txs_dm6_chr4, PROseq, quantiles = c(0.9, 1),
                      order.by.rank = TRUE)

#--------------------------------------------------#
# remove the most extreme 10% of regions, and keep scores
#--------------------------------------------------#

subsetRegionsBySignal(txs_dm6_chr4, PROseq, quantiles = c(0.05, 0.95),
                      keep.signal = TRUE)

BRGenomics documentation built on Nov. 8, 2020, 8:03 p.m.