Sarks: Suffix Array Kernel Smoothing

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

Description

Sarks class implements suffix array kernel smoothing for de novo correlative motif discovery.

Usage

Sarks(fasta, scores, halfWindow, spatialLength = 0L, nThreads = 1L)

Arguments

fasta	specification of fasta file containing sequences to be analyzed; may also be a *named* character vector or XStringSet whose elements are sequences to be analyzed.
scores	specification of scores associated with sequences in fasta argument; can be provided as two column tab-delimited file (should have header, first column should provide sequence names identical to those in fasta argument, second column should have numeric scores) or may be a named numeric vector.
halfWindow	half-width of smoothing window (integer).
spatialLength	full length of spatial smoothing window (integer); use 0 to disable spatial smoothing.
nThreads	number of threads to use for computing permutation distributions.

Value

R representation of java Sarks object.

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)

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