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

Jody Hey, Rasmus Nielsen

766 Citations (Scopus)

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.
Original languageEnglish
JournalProceedings of the National Academy of Science of the United States of America
Volume104
Issue number8
Pages (from-to)2785-90
Number of pages5
ISSN0027-8424
DOIs
Publication statusPublished - 2007

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