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.

gaga

   

This package is for version 2.8 of Bioconductor; for the stable, up-to-date release version, see gaga.

GaGa hierarchical model for microarray data analysis

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")):

Installation

To install this package, start R and enter:

## try http:// if https:// URLs are not supported
source("https://bioconductor.org/biocLite.R")
biocLite("gaga")

Documentation

To view documentation for the version of this package installed in your system, start R and enter:

browseVignettes("gaga")

 

PDF gagamanual.pdf
PDF   Reference Manual

Details

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
Imports
LinkingTo
Suggests
SystemRequirements
Enhances
URL
Depends On Me
Imports Me
Suggests Me
Build Report  

Package Archives

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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