Bioconductor version: Release (3.16)
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")
):
To install this package, start R (version "4.2") 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.
To view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("baySeq")
R Script | Advanced baySeq analyses | |
R Script | baySeq | |
Reference Manual |
biocViews | DifferentialExpression, MultipleComparison, SAGE, Sequencing, Software |
Version | 2.31.0 |
In Bioconductor since | BioC 2.5 (R-2.10) (13.5 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, Rcade, segmentSeq, TCC |
Imports Me | metaseqR2, riboSeqR, srnadiff |
Suggests Me | compcodeR |
Links To Me | |
Build Report |
Follow Installation instructions to use this package in your R session.
Source Package | baySeq_2.31.0.tar.gz |
Windows Binary | baySeq_2.32.0.zip |
macOS Binary (x86_64) | baySeq_2.32.0.tgz |
macOS Binary (arm64) | baySeq_2.32.0.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 |
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