This project is archived and no longer maintained.
|Description||A tool for performing model-based inference for differential gene expression, using a non-parametric Bayesian mixture probability model for the distribution of gene intensities under different conditions|
|Language||R and C|
|Platforms||Windows and Linux|
|Last updated||15th August 2003|
BayesMix is a piece of computer software, a suite of R functions and C routines with a graphical user interface, which can be used as a tool for performing model-based inference for differential gene expression, using a non-parametric Bayesian mixture probability model for the distribution of gene intensities under different conditions. For comparison purposes, Efron’s empirical Bayes method (JASA, 2001), is also implemented. The package can be employed for any general research problem that involves massive multiple comparisons with continuous outcomes.
The package produces numerous plots and tables from which the user can:
The current Un*x-based version is 0.8.8, available as of 2003/08/15. Here are some links to download various binary packages. The source package is not publicly available at this time since it’s still being written. The following are the supported platforms.
Kim-Anh Do, Peter Müller, Feng Tang (2003).
Bayesian Mixture Model for Differential Gene Expression.
Technical Report, Department of Biostatistics, University of Texas/MD Anderson Cancer Center
Bradley Efron, Robert Tibshirani, John D. Storey, Virginia Tusher (2001).
Empirical Bayes Analysis of a Microarray Experiment.
Journal of the American Statistical Association, Volume 96, Number 456, Pages 1151-116