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Uniformization for Sampling Realizations of Markov Processes: Applications to Bayesian Implementations of Codon Substitution Models

Nicolas Rodrigue 1 Herve Philippe 1 Nicolas Lartillot 2
2 MAB - Méthodes et Algorithmes pour la Bioinformatique
LIRMM - Laboratoire d'Informatique de Robotique et de Microélectronique de Montpellier
Abstract : MOTIVATION: Mapping character state changes over phylogenetic trees is central to the study of evolution. However, current probabilistic methods for generating such mappings are ill-suited to certain types of evolutionary models, in particular, the widely used models of codon substitution. RESULTS: We describe a general method, based on a uniformization technique, which can be utilized to generate realizations of a Markovian substitution process conditional on an alignment of character states and a given tree topology. The method is applicable under a wide range of evolutionary models, and to illustrate its usefulness in practice, we embed it within a data augmentation-based Markov chain Monte Carlo sampler, for approximating posterior distributions under previously proposed codon substitution models. The sampler is found to be more effcient than the conventional pruning-based sampler, with decorrelation times between draws from the posterior reduced by a factor of twenty or more. CONTACT: nicolas.rodrigue@umontreal.ca.
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https://hal-lirmm.ccsd.cnrs.fr/lirmm-00193706
Contributor : Nicolas Lartillot <>
Submitted on : Tuesday, December 4, 2007 - 2:21:04 PM
Last modification on : Wednesday, October 21, 2020 - 1:54:02 PM

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  • HAL Id : lirmm-00193706, version 1

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Nicolas Rodrigue, Herve Philippe, Nicolas Lartillot. Uniformization for Sampling Realizations of Markov Processes: Applications to Bayesian Implementations of Codon Substitution Models. Bioinformatics, Oxford University Press (OUP), 2007, pp.0. ⟨lirmm-00193706⟩

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