Integration within the Felsenstein equation for improved Markov chain Monte Carlo methods in population genetics

  • Hey J
  • Nielsen R
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Abstract

In 1988, Felsenstein described a framework for assessing the likelihood of a genetic data set in which all of the possible genealogical histories of the data are considered, each in proportion to their probability. Although not analytically solvable, several approaches, including Markov chain Monte Carlo methods, have been developed to find approximate solutions. Here, we describe an approach in which Markov chain Monte Carlo simulations are used to integrate over the space of genealogies, whereas other parameters are integrated out analytically. The result is an approximation to the full joint posterior density of the model parameters. For many purposes, this function can be treated as a likelihood, thereby permitting likelihood-based analyses, including likelihood ratio tests of nested models. Several examples, including an application to the divergence of chimpanzee subspecies, are provided

Author-supplied keywords

  • Animals
  • Bayes Theorem
  • Chimpanzee
  • EXAMPLE
  • Genealogy
  • Genealogy and Heraldry
  • Genetic
  • Genetics,Population
  • HISTORIES
  • History
  • MARKOV CHAIN MONTE CARLO
  • MODEL
  • Markov Chains
  • Methods
  • Models
  • Models,Genetic
  • Monte Carlo Method
  • POPULATION
  • Pan troglodytes
  • Probability
  • RATIO TEST
  • Universities
  • divergence
  • genetics
  • likelihood
  • population genetics
  • statistics & numerical data

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  • PMID: 17301231

Authors

  • J Hey

  • R Nielsen

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