baySeq

Empirical Bayesian analysis of patterns of differential expression in count data

Bioconductor version: Release (3.17)

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>

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

Installation

To install this package, start R (version "4.3") 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


Reference Manual	PDF

Details

biocViews	DifferentialExpression, MultipleComparison, SAGE, Sequencing, Software
Version	2.34.0
In Bioconductor since	BioC 2.5 (R-2.10) (14 years)
License	GPL-3
Depends	R (>= 2.3.0), methods, GenomicRanges, abind, parallel
Imports	edgeR
Linking To
Suggests	BiocStyle, BiocGenerics
System Requirements
Enhances
URL

Depends On Me	clusterSeq, segmentSeq, TCC
Imports Me	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
Windows Binary
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/
Package Downloads Report	Download Stats