title: Bayesian random local clocks, or one rate to rule them all.
abstract: BACKGROUND
  Relaxed molecular clock models allow divergence time dating and "relaxed phylogenetic" inference, in which a time tree is estimated in the face of unequal rates across lineages. We present a new method for relaxing the assumption of a strict molecular clock using Markov chain Monte Carlo to implement Bayesian modeling averaging over random local molecular clocks. The new method approaches the problem of rate variation among lineages by proposing a series of local molecular clocks, each extending over a subregion of the full phylogeny. Each branch in a phylogeny (subtending a clade) is a possible location for a change of rate from one local clock to a new one. Thus, including both the global molecular clock and the unconstrained model results, there are a total of 2(2n-2) possible rate models available for averaging with 1, 2, ..., 2n - 2 different rate categories.
  
  
  RESULTS
  We propose an efficient method to sample this model space while simultaneously estimating the phylogeny. The new method conveniently allows a direct test of the strict molecular clock, in which one rate rules them all, against a large array of alternative local molecular clock models. We illustrate the method's utility on three example data sets involving mammal, primate and influenza evolution. Finally, we explore methods to visualize the complex posterior distribution that results from inference under such models.
  
  
  CONCLUSIONS
  The examples suggest that large sequence datasets may only require a small number of local molecular clocks to reconcile their branch lengths with a time scale. All of the analyses described here are implemented in the open access software package BEAST 1.5.4 (http://beast-mcmc.googlecode.com/).
authors.affiliation: Allan Wilson Centre for Molecular Ecology and Evolution, University of Auckland, Private Bag 92019, Auckland, New Zealand. alexei@cs.auckland.ac.nz
authors.forename: Alexei J
authors.initials: AJ
authors.lastname: Drummond
authors.forename: Marc A
authors.initials: MA
authors.lastname: Suchard
mesh_terms: D000818:Animals; D001499:Bayes Theorem; D003198:Computer Simulation; D004272:DNA, Mitochondrial / Q000235:genetics; D019143:Evolution, Molecular; D019267:Hemagglutinin Glycoproteins, Influenza Virus / Q000235:genetics; D020407:Internet; D008322:Mammals / Q000235:genetics; D008390:Markov Chains; D008957:Models, Genetic; D009010:Monte Carlo Method; D010802:Phylogeny; D012984:Software; D013997:Time Factors
chemical_list: D004272:DNA, Mitochondrial; D019267:Hemagglutinin Glycoproteins, Influenza Virus; C483468:hemagglutinin, human influenza A virus
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