To install this package, start R and enter:
## try http:// if https:// URLs are not supported source("https://bioconductor.org/biocLite.R") biocLite("gaga")
In most cases, you don't need to download the package archive at all.
This package is for version 2.8 of Bioconductor; for the stable, up-to-date release version, see gaga.
Bioconductor version: 2.8
This package fits Rossell's generalizations of the Gamma-Gamma hierarchical model for microarray data analysis, which substantially improve the quality of the fit at a low computational cost. The model can be fit via empirical Bayes (Expectation-Maximization and Simulated Annealing) and fully Bayesian techniques (Gibbs and Metropolis-Hastings posterior sampling). Routines are provided to perform differential expression analysis and class prediction.
Author: David Rossell <rosselldavid at gmail.com>.
Maintainer: David Rossell <rosselldavid at gmail.com>
Citation (from within R,
enter citation("gaga")
):
To install this package, start R and enter:
## try http:// if https:// URLs are not supported source("https://bioconductor.org/biocLite.R") biocLite("gaga")
To view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("gaga")
gagamanual.pdf | ||
Reference Manual |
biocViews | Bioinformatics, Classification, DifferentialExpression, Software |
Version | 1.12.0 |
In Bioconductor since | BioC 2.2 (R-2.7) (8 years) |
License | GPL (>= 2) |
Depends | R (>= 2.5.0), Biobase, coda |
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Build Report |
Follow Installation instructions to use this package in your R session.
Package Source | gaga_1.12.0.tar.gz |
Windows Binary | gaga_1.12.0.zip (32- & 64-bit) |
Mac OS X 10.6 (Snow Leopard) | |
Mac OS X 10.9 (Mavericks) | |
Subversion source | (username/password: readonly) |
Git source | https://github.com/Bioconductor-mirror/gaga/tree/release-2.8 |
Package Short Url | http://bioconductor.org/packages/gaga/ |
Package Downloads Report | Download Stats |
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