segmentSeq

DOI: 10.18129/B9.bioc.segmentSeq    

This package is for version 3.15 of Bioconductor; for the stable, up-to-date release version, see segmentSeq.

Methods for identifying small RNA loci from high-throughput sequencing data

Bioconductor version: 3.15

High-throughput sequencing technologies allow the production of large volumes of short sequences, which can be aligned to the genome to create a set of matches to the genome. By looking for regions of the genome which to which there are high densities of matches, we can infer a segmentation of the genome into regions of biological significance. The methods in this package allow the simultaneous segmentation of data from multiple samples, taking into account replicate data, in order to create a consensus segmentation. This has obvious applications in a number of classes of sequencing experiments, particularly in the discovery of small RNA loci and novel mRNA transcriptome discovery.

Author: Thomas J. Hardcastle

Maintainer: Thomas J. Hardcastle <tjh48 at cam.ac.uk>

Installation

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

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

BiocManager::install("segmentSeq")

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("segmentSeq")

 

PDF	R Script	segmentSeq: small RNA locus detection
PDF	R Script	segmentsSeq: Methylation locus identification
PDF		Reference Manual

Details

biocViews	Alignment, DataImport, DifferentialExpression, MultipleComparison, QualityControl, Sequencing, Software
Version	2.30.0
In Bioconductor since	BioC 2.6 (R-2.11) (12.5 years)
License	GPL-3
Depends	R (>= 3.5.0), methods, baySeq(>= 2.9.0), S4Vectors, parallel, GenomicRanges, ShortRead, stats
Imports	Rsamtools, IRanges, GenomeInfoDb, graphics, grDevices, utils, abind
LinkingTo
Suggests	BiocStyle, BiocGenerics
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URL
Depends On Me
Imports Me
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Build Report

Package Archives

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

Source Package	segmentSeq_2.30.0.tar.gz
Windows Binary	segmentSeq_2.30.0.zip
macOS Binary (x86_64)	segmentSeq_2.30.0.tgz
Source Repository	git clone https://git.bioconductor.org/packages/segmentSeq
Source Repository (Developer Access)	git clone git@git.bioconductor.org:packages/segmentSeq
Package Short Url	https://bioconductor.org/packages/segmentSeq/
Package Downloads Report	Download Stats