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      Bayesian analysis of correlated evolution of discrete characters by reversible-jump Markov chain Monte Carlo.

      1 ,
      The American naturalist
      University of Chicago Press

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          Abstract

          We describe a Bayesian method for investigating correlated evolution of discrete binary traits on phylogenetic trees. The method fits a continuous-time Markov model to a pair of traits, seeking the best fitting models that describe their joint evolution on a phylogeny. We employ the methodology of reversible-jump (RJ) Markov chain Monte Carlo to search among the large number of possible models, some of which conform to independent evolution of the two traits, others to correlated evolution. The RJ Markov chain visits these models in proportion to their posterior probabilities, thereby directly estimating the support for the hypothesis of correlated evolution. In addition, the RJ Markov chain simultaneously estimates the posterior distributions of the rate parameters of the model of trait evolution. These posterior distributions can be used to test among alternative evolutionary scenarios to explain the observed data. All results are integrated over a sample of phylogenetic trees to account for phylogenetic uncertainty. We implement the method in a program called RJ Discrete and illustrate it by analyzing the question of whether mating system and advertisement of estrus by females have coevolved in the Old World monkeys and great apes.

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          Author and article information

          Journal
          Am Nat
          The American naturalist
          University of Chicago Press
          1537-5323
          0003-0147
          Jun 2006
          : 167
          : 6
          Affiliations
          [1 ] School of Biological Sciences, University of Reading, Reading RG6 6AJ, United Kingdom. m.pagel@rdg.ac.uk
          Article
          AN41177
          10.1086/503444
          16685633
          f466f765-1e78-4da0-bc9b-ca5e1f9d48d2
          History

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