Journal
BIOINFORMATICS
Volume 25, Issue 15, Pages 1959-1960Publisher
OXFORD UNIV PRESS
DOI: 10.1093/bioinformatics/btp307
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Funding
- Fundacion de Investigacion Medica Mutua Madrile a, RTIC COMBIOMED [RD07/0067/0014]
- Spanish Health Ministry, Supercomputacion y Ciencia [CSD2007-00050]
- Spanish Ministry of Education and Science
- Spanish National Bioinformatics Institute
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Several methods have been proposed to detect copy number changes and recurrent regions of copy number variation from aCGH, but few methods return probabilities of alteration explicitly, which are the direct answer to the question 'is this probe/region altered?' RJaCGH fits a Non-Homogeneous Hidden Markov model to the aCGH data using Markov Chain Monte Carlo with Reversible Jump, and returns the probability that each probe is gained or lost. Using these probabilites, recurrent regions ( over sets of individuals) of copy number alteration can be found.
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