gaga

GaGa hierarchical model for microarray data analysis

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.

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

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