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>

To install this package, start R and enter:

    source("http://bioconductor.org/biocLite.R")
    biocLite("gaga")

To cite this package in a publication, start R and enter:

    citation("gaga")

Documentation

PDF R Script Manual for the gaga library
PDF   Reference Manual

Details

biocViews Bioinformatics, DifferentialExpression, Classification
Depends R (>= 2.5.0), Biobase, coda
Imports
Suggests
System Requirements
License GPL (>= 2)
URL
Depends On Me
Imports Me
Suggests Me
Version 1.12.0
Since Bioconductor 2.2 (R-2.7)

Package Downloads

Package Source gaga_1.12.0.tar.gz
Windows Binary gaga_1.12.0.zip (32- & 64-bit)
MacOS 10.5 (Leopard) binary gaga_1.12.0.tgz
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