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 with empirical Bayes and fully Bayesian techniques. Routines are provided to perform differential expression analysis and class prediction.
To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R")
biocLite("gaga")
| Source | gaga_1.0.0.tar.gz |
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| Windows binary | gaga_1.0.0.zip |
| OS X binary | gaga_1.0.0.tgz |
| biocViews | |
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| Depends | R, Biobase, coda |
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| License | GPL (version 2 or later) |
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