kmerPeaks: Call k-mer peaks

In sarks: Suffix Array Kernel Smoothing for discovery of correlative sequence motifs and multi-motif domains

Description

SArKS identifies sets of short subsequences (k-mers) whose presence as substrings of sequences from the input sequence set tends to be associated with elevated sequence scores. Such k-mers are identified as “peaks” where kernel-smoothed scores exceed specified thresholds (generally set by permutation method).

Usage

kmerPeaks(sarks, filters, thresholds, peakify = TRUE, kMax = 12L)

Arguments

sarks	Sarks object to use for k-mer peak calling.
filters	output from sarksFilters function indicating what combinations of filter parameters halfWindow, spatialLength, and minGini to use.
thresholds	output from permutationThresholds specifying thresholds for k-mer peak calling.
peakify	logical value specifying whether to restrict output to only spatial positions at which the smoothed score is at least as high as either neighboring position or not.
kMax	integer value indicating the maximum k-mer length to be reported.

Value

data.frame containing called k-mer peak information.

References

Wylie, D.C., Hofmann, H.A., and Zemelman, B.V. (2019) SArKS: de novo discovery of gene expression regulatory motif sites and domains by suffix array kernel smoothing, Bioinformatics, Vol. 35(20), 3944-3952

https://academic.oup.com/bioinformatics/article-abstract/35/20/3944/5418797

Examples

data(simulatedSeqs, simulatedScores)
sarks <- Sarks(simulatedSeqs, simulatedScores, 4, 0, 1)
filters <- sarksFilters(halfWindow=4, spatialLength=0, minGini=1.1)
permDist <- permutationDistribution(sarks, 250, filters, seed=123)
thresholds <- permutationThresholds(filters, permDist, nSigma=2.0)
peaks <- kmerPeaks(sarks, filters, thresholds)

sarks documentation built on Nov. 8, 2020, 6:54 p.m.