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>.

Maintainer: David Rossell <rosselldavid at>

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PDF R Script Manual for the gaga library
PDF   Reference Manual


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

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Package Source gaga_1.12.0.tar.gz
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MacOS 10.5 (Leopard) binary gaga_1.12.0.tgz
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