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.

Version: 2.0.4
Depends: R (≥ 2.13)
Published: 2015-07-10
Author: Oscar Rueda and Ramon Diaz-Uriarte. zlib from Jean-loup Gailly and Mark Adler; see README. Function "getHostname.System" from package R.utils by Henrik Bengtsson.
Maintainer: Oscar Rueda <rueda.om at gmail.com>
License: GPL-3
URL: http://www.r-project.org
NeedsCompilation: yes
SystemRequirements: zlib headers and library.
In views: Bayesian
CRAN checks: RJaCGH results


Reference manual: RJaCGH.pdf
Package source: RJaCGH_2.0.4.tar.gz
Windows binaries: r-devel: RJaCGH_2.0.4.zip, r-release: RJaCGH_2.0.4.zip, r-oldrel: RJaCGH_2.0.4.zip
OS X binaries: r-release: RJaCGH_2.0.4.tgz, r-oldrel: RJaCGH_2.0.4.tgz
Old sources: RJaCGH archive


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