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Bayesian Phylogenetic Inference via Markov Chain Monte Carlo Methods

Bayesian Phylogenetic Inference via Markov Chain Monte Carlo Methods Summary. We derive a Markov chain to sample from the posterior distribution for a phylogenetic tree given sequence information from the corresponding set of organisms, a stochastic model for these data, and a prior distribution on the space of trees. A transformation of the tree into a canonical cophenetic matrix form suggests a simple and effective proposal distribution for selecting candidate trees close to the current tree in the chain. We illustrate the algorithm with restriction site data on 9 plant species, then extend to DNA sequences from 32 species of fish. The algorithm mixes well in both examples from random starting trees, generating reproducible estimates and credible sets for the path of evolution. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Biometrics Oxford University Press

Bayesian Phylogenetic Inference via Markov Chain Monte Carlo Methods

Biometrics , Volume 55 (1) – Mar 1, 1999

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References (46)

Publisher
Oxford University Press
Copyright
Copyright © 1999 Wiley Subscription Services, Inc., A Wiley Company
ISSN
0006-341X
eISSN
1541-0420
DOI
10.1111/j.0006-341x.1999.00001.x
Publisher site
See Article on Publisher Site

Abstract

Summary. We derive a Markov chain to sample from the posterior distribution for a phylogenetic tree given sequence information from the corresponding set of organisms, a stochastic model for these data, and a prior distribution on the space of trees. A transformation of the tree into a canonical cophenetic matrix form suggests a simple and effective proposal distribution for selecting candidate trees close to the current tree in the chain. We illustrate the algorithm with restriction site data on 9 plant species, then extend to DNA sequences from 32 species of fish. The algorithm mixes well in both examples from random starting trees, generating reproducible estimates and credible sets for the path of evolution.

Journal

BiometricsOxford University Press

Published: Mar 1, 1999

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