To install this package, start R and enter:
## try http:// if https:// URLs are not supported source("https://bioconductor.org/biocLite.R") biocLite("baySeq")
In most cases, you don't need to download the package archive at all.
This package is for version 2.12 of Bioconductor; for the stable, up-to-date release version, see baySeq.
Bioconductor version: 2.12
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 and enter:
## try http:// if https:// URLs are not supported source("https://bioconductor.org/biocLite.R") biocLite("baySeq")
To view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("baySeq")
R Script | baySeq | |
Reference Manual |
biocViews | Bioinformatics, DifferentialExpression, HighThroughputSequencing, MultipleComparisons, SAGE, Software |
Version | 1.14.1 |
In Bioconductor since | BioC 2.5 (R-2.10) (6.5 years) |
License | GPL-3 |
Depends | R (>= 2.3.0), methods |
Imports | |
LinkingTo | |
Suggests | snow, edgeR |
SystemRequirements | |
Enhances | |
URL | |
Depends On Me | Rcade, segmentSeq |
Imports Me | segmentSeq |
Suggests Me | oneChannelGUI |
Build Report |
Follow Installation instructions to use this package in your R session.
Package Source | baySeq_1.14.1.tar.gz |
Windows Binary | baySeq_1.14.1.zip |
Mac OS X 10.6 (Snow Leopard) | baySeq_1.14.1.tgz |
Subversion source | (username/password: readonly) |
Git source | https://github.com/Bioconductor-mirror/baySeq/tree/release-2.12 |
Package Short Url | http://bioconductor.org/packages/baySeq/ |
Package Downloads Report | Download Stats |
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