normalizePeaks: normalizePeaks

In sjessa/chromswitch: An R package to detect chromatin state switches from epigenomic data

normalizePeaks

Description

Given a set of peak calls for different marks and samples, normalize all peaks genome-wide for each sample and mark by rescaling and Winsorizing, i.e. rescale the middle of the data to the range [0, 1] and bound the upper tail to 1 and the lower tail to 0, effectively replacing a fixed amount of extreme values in each tail. Similar to trimming the tails except instead of discarding the tails entirely they're bounded.

Usage

normalizePeaks(peaks, columns, tail = 0.005)

Arguments

peaks	List of GRanges objects storing peak calls for each sample, where element names correspond to sample IDs
columns	Character vector specifying the names of columns to normalize
tail	Optional: numeric, a fraction in [0, 1] specifying how much of the data to bound to 0 (for the lower tail) or 1 (for the upper tail). Default: 0.005.

Value

A list of GRanges objects storing peak calls for each sample, with columns specified in columns normalized.

See Also

winsorNorm

Examples

normalizePeaks(H3K4me3, columns = c("signalValue", "pValue", "qValue"))

sjessa/chromswitch documentation built on Feb. 4, 2024, 2:04 a.m.