Sampling phylogenetic tree space with the generalized Gibbs sampler

Keith, J. M., Adams, P., Ragan, M. A. and Bryant, D. E. (2005) Sampling phylogenetic tree space with the generalized Gibbs sampler. Molecular Phylogenetics and Evolution, 34 3: 459-468. doi:10.1016/j.ympev.2004.11.016

Author Keith, J. M.
Adams, P.
Ragan, M. A.
Bryant, D. E.
Title Sampling phylogenetic tree space with the generalized Gibbs sampler
Journal name Molecular Phylogenetics and Evolution   Check publisher's open access policy
ISSN 1055-7903
Publication date 2005-03-01
Sub-type Article (original research)
DOI 10.1016/j.ympev.2004.11.016
Volume 34
Issue 3
Start page 459
End page 468
Total pages 10
Editor Dr. Morris Goodman
Place of publication San Diego
Publisher Academic Press Inc Elsevier Science
Language eng
Subject 230202 Stochastic Analysis and Modelling
239901 Biological Mathematics
780105 Biological sciences
270208 Molecular Evolution
Abstract The generalized Gibbs sampler (GGS) is a recently developed Markov chain Monte Carlo (MCMC) technique that enables Gibbs-like sampling of state spaces that lack a convenient representation in terms of a fixed coordinate system. This paper describes a new sampler, called the tree sampler, which uses the GGS to sample from a state space consisting of phylogenetic trees. The tree sampler is useful for a wide range of phylogenetic applications, including Bayesian, maximum likelihood, and maximum parsimony methods. A fast new algorithm to search for a maximum parsimony phylogeny is presented, using the tree sampler in the context of simulated annealing. The mathematics underlying the algorithm is explained and its time complexity is analyzed. The method is tested on two large data sets consisting of 123 sequences and 500 sequences, respectively. The new algorithm is shown to compare very favorably in terms of speed and accuracy to the program DNAPARS from the PHYLIP package.
Keyword Generalized Gibbs sampler
Markov chain Monte Carlo
Phylogenetic trees
Generalized Gibbs Sampler
Phylogenetic Inference
Genetics & Heredity
Evolutionary Biology
Markov Chain Monte Carlo
Chain Monte-carlo
Biochemistry & Molecular Biology
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Created: Wed, 23 May 2007, 01:53:52 EST by Mrs Leith Woodall on behalf of School of Mathematics & Physics