sarks

DOI: 10.18129/B9.bioc.sarks  

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

Bioconductor version: Release (3.16)

Suffix Array Kernel Smoothing (see https://academic.oup.com/bioinformatics/article-abstract/35/20/3944/5418797), or SArKS, identifies sequence motifs whose presence correlates with numeric scores (such as differential expression statistics) assigned to the sequences (such as gene promoters). SArKS smooths over sequence similarity, quantified by location within a suffix array based on the full set of input sequences. A second round of smoothing over spatial proximity within sequences reveals multi-motif domains. Discovered motifs can then be merged or extended based on adjacency within MMDs. False positive rates are estimated and controlled by permutation testing.

Author: Dennis Wylie [aut, cre]

Maintainer: Dennis Wylie <denniscwylie at gmail.com>

Installation

To install this package, start R (version "4.2") and enter:

if (!require("BiocManager", quietly = TRUE))
    install.packages("BiocManager")

BiocManager::install("sarks")

For older versions of R, please refer to the appropriate Bioconductor release.

Documentation

To view documentation for the version of this package installed in your system, start R and enter:

browseVignettes("sarks")

 

PDF	R Script	sarks-vignette
PDF		Reference Manual
Text		NEWS
Text		LICENSE

Details

biocViews	DifferentialExpression, FeatureExtraction, GeneExpression, GeneRegulation, MotifDiscovery, RNASeq, Software, Transcriptomics
Version	1.10.0
In Bioconductor since	BioC 3.11 (R-4.0) (3 years)
License	BSD_3_clause + file LICENSE
Depends	R (>= 4.0)
Imports	rJava, Biostrings, IRanges, utils, stats, cluster, binom
LinkingTo
Suggests	RUnit, BiocGenerics, ggplot2
SystemRequirements	Java (>= 1.8)
Enhances
URL	https://academic.oup.com/bioinformatics/article-abstract/35/20/3944/5418797 https://github.com/denniscwylie/sarks
BugReports	https://github.com/denniscwylie/sarks/issues
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Build Report

Package Archives

Follow Installation instructions to use this package in your R session.

Source Package	sarks_1.10.0.tar.gz
Windows Binary	sarks_1.10.0.zip (64-bit only)
macOS Binary (x86_64)	sarks_1.10.0.tgz
macOS Binary (arm64)	sarks_1.10.0.tgz
Source Repository	git clone https://git.bioconductor.org/packages/sarks
Source Repository (Developer Access)	git clone git@git.bioconductor.org:packages/sarks
Bioc Package Browser	https://code.bioconductor.org/browse/sarks/
Package Short Url	https://bioconductor.org/packages/sarks/
Package Downloads Report	Download Stats