Bioconductor 3.22 Released

baySeq

This is the development version of baySeq; for the stable release version, see baySeq.

Empirical Bayesian analysis of patterns of differential expression in count data


Bioconductor version: Development (3.23)

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] ORCID iD ORCID: 0000-0001-9245-1535

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

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

Installation

To install this package, start R (version "4.6") and enter:


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

# The following initializes usage of Bioc devel
BiocManager::install(version='devel')

BiocManager::install("baySeq")

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

Documentation

Reference Manual PDF

Details

biocViews Bayesian, Coverage, DifferentialExpression, MultipleComparison, SAGE, Sequencing, Software
Version 2.45.0
In Bioconductor since BioC 2.5 (R-2.10) (16 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
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Package Archives

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

Source Package
Windows Binary (x86_64)
macOS Binary (x86_64)
macOS Binary (arm64)
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/
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