baySeq

DOI: 10.18129/B9.bioc.baySeq    

Empirical Bayesian analysis of patterns of differential expression in count data

Bioconductor version: Release (3.13)

This package identifies differential expression in high-throughput 'count' data, such as that derived from next-generation sequencing machines, calculating estimated posterior likelihoods of differential expression (or more complex hypotheses) via empirical Bayesian methods.

Author: Thomas J. Hardcastle

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

Installation

To install this package, start R (version "4.1") and enter:

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

BiocManager::install("baySeq")

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("baySeq")

 

PDF	R Script	Advanced baySeq analyses
PDF	R Script	baySeq
PDF		Reference Manual

Details

biocViews	DifferentialExpression, MultipleComparison, SAGE, Sequencing, Software
Version	2.26.0
In Bioconductor since	BioC 2.5 (R-2.10) (12 years)
License	GPL-3
Depends	R (>= 2.3.0), methods, GenomicRanges, abind, parallel
Imports	edgeR
LinkingTo
Suggests	BiocStyle, BiocGenerics
SystemRequirements
Enhances
URL
Depends On Me	clusterSeq, EDDA, Rcade, segmentSeq, TCC
Imports Me	EDDA, metaseqR2, riboSeqR, srnadiff
Suggests Me	compcodeR
Links To Me
Build Report

Package Archives

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

Source Package	baySeq_2.26.0.tar.gz
Windows Binary	baySeq_2.26.0.zip
macOS 10.13 (High Sierra)	baySeq_2.26.0.tgz
Source Repository	git clone https://git.bioconductor.org/packages/baySeq
Source Repository (Developer Access)	git clone git@git.bioconductor.org:packages/baySeq
Package Short Url	https://bioconductor.org/packages/baySeq/
Package Downloads Report	Download Stats