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.
| Author |
David Rossell . |
| Maintainer |
David Rossell |
To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R")
biocLite("gaga")
Documentation
Details
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| License |
GPL (>=2) |
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| Development History |
Bioconductor Changelog
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Package Downloads