RJaCGH: Analysis of aCGH data using HMMs with Reversible Jump MCMC

Registered 2006-08-24 by Ramon Diaz-Uriarte

An R package for the analysis of array-based aCGH data using non-homogeneous Hidden Markov Models with Reversible Jump Markov Chain Monte Carlo.

The method implemented in RJaCGH allows us to incorporate distance between probes/clones (the non-homogenous in non-homogeneous HMM). We return posterior probabilities that a gene/region is altered, using Markov Chain Monte Carlo. The method does not require you to pre-specify the number of states, as we use Reversible Jump for transdimensional moves. Finally, we use Bayesian Model Averaging for incorporating model uncertainty.

The details of our method are provided in a COBRA Preprint Series article http://biostats.bepress.com/cobra/ps/art9.

RJaCGH is part of the Asterias project, and will soon be incorporated to its web-based tools.

Project information

Part of:
Asterias Project
Maintainer:
Ramon Diaz-Uriarte
Driver:
Not yet selected
Development focus:

main series 

lp:rjacgh 
Browse the code

Programming Languages:
R, C
Licences:
GNU Affero GPL v3, GNU GPL v2, GNU GPL v3
()

RDF metadata

View full history Series and milestones

RJaCGH main series is the current focus of development

Get Involved

  • warning
    Report a bug
  • warning
    Ask a question
  • warning
    Help translate

Downloads

RJaCGH does not have any download files registered with Launchpad.