Bayesian Phylogenetic Inference via Markov Chain Monte Carlo Methods

1999/03/01 by Bob Mau, Michael A. Newton, Bret Larget · 35 citations
Earth and Planetary Sciences · Biochemistry, Genetics and Molecular Biology · #Evolution and Paleontology Studies #Genomics and Phylogenetic Studies #Genetic diversity and population structure

paper · pdf · doi:10.1111/j.0006-341x.1999.00001.x

Abstract

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.

Citations

• Dating of the human-ape splitting by a molecular clock of mitochondrial DNA
• Evolutionary trees from DNA sequences: A maximum likelihood approach
• Statistical tests of models of DNA substitution

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