RJaCGH: Reversible Jump MCMC for the Analysis of CGH Arrays

Bayesian analysis of CGH microarrays fitting Hidden Markov Chain models. The selection of the number of states is made via their posterior probability computed by Reversible Jump Markov Chain Monte Carlo Methods. Also returns probabilistic common regions for gains/losses.

AuthorOscar Rueda <rueda.om@gmail.com> and Ramon Diaz-Uriarte <rdiaz02@gmail.com>. zlib from Jean-loup Gailly and Mark Adler; see README. Function "getHostname.System" from package R.utils by Henrik Bengtsson.
Date of publication2015-07-10 20:15:37
MaintainerOscar Rueda <rueda.om@gmail.com>

View on CRAN

Questions? Problems? Suggestions? or email at ian@mutexlabs.com.

All documentation is copyright its authors; we didn't write any of that.