gaga

GaGa hierarchical model for microarray data analysis

Bioconductor version: 2.7

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

Details

Package Downloads