baySeq

Empirical Bayesian analysis of patterns of differential expression in count data


Bioconductor version: Release (3.19)

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 [aut], Samuel Granjeaud [cre]

Maintainer: Samuel Granjeaud <samuel.granjeaud at inserm.fr>

Citation (from within R, enter citation("baySeq")):

Installation

To install this package, start R (version "4.4") and enter:


if (!require("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")
Advanced baySeq analyses PDF R Script
baySeq PDF R Script
Reference Manual PDF

Details

biocViews Bayesian, Coverage, DifferentialExpression, MultipleComparison, SAGE, Sequencing, Software
Version 2.38.0
In Bioconductor since BioC 2.5 (R-2.10) (15 years)
License GPL-3
Depends R (>= 2.3.0), methods
Imports edgeR, GenomicRanges, abind, parallel, graphics, stats, utils
System Requirements
URL https://github.com/samgg/baySeq
Bug Reports https://github.com/samgg/baySeq/issues
See More
Suggests BiocStyle, BiocGenerics
Linking To
Enhances
Depends On Me clusterSeq, segmentSeq
Imports Me riboSeqR
Suggests Me
Links To Me
Build Report Build Report

Package Archives

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

Source Package baySeq_2.38.0.tar.gz
Windows Binary baySeq_2.38.0.zip
macOS Binary (x86_64) baySeq_2.38.0.tgz
macOS Binary (arm64) baySeq_2.38.0.tgz
Source Repository git clone https://git.bioconductor.org/packages/baySeq
Source Repository (Developer Access) git clone git@git.bioconductor.org:packages/baySeq
Bioc Package Browser https://code.bioconductor.org/browse/baySeq/
Package Short Url https://bioconductor.org/packages/baySeq/
Package Downloads Report Download Stats