2007
DOI: 10.1073/pnas.0611164104
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Integration within the Felsenstein equation for improved Markov chain Monte Carlo methods in population genetics

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 parame… Show more

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Cited by 871 publications
(1,040 citation statements)
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References 35 publications
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“…A prominent set of tools for this analysis includes IM, IMa, IMa2, and IMa2p (Hey, 2010; Hey, Chung, & Sethuraman, 2015; Hey & Nielsen, 2007; Sethuraman & Hey, 2015). In general, these methods utilize a Bayesian Metropolis‐coupled Markov Chain Monte Carlo (MCMCMC) method to estimate effective population sizes, migration rates, and divergence times under the IM model from haplotypic data.…”
Section: Improving Downstream Computational Analysesmentioning
confidence: 99%
“…A prominent set of tools for this analysis includes IM, IMa, IMa2, and IMa2p (Hey, 2010; Hey, Chung, & Sethuraman, 2015; Hey & Nielsen, 2007; Sethuraman & Hey, 2015). In general, these methods utilize a Bayesian Metropolis‐coupled Markov Chain Monte Carlo (MCMCMC) method to estimate effective population sizes, migration rates, and divergence times under the IM model from haplotypic data.…”
Section: Improving Downstream Computational Analysesmentioning
confidence: 99%
“…Potential gene flow among major lineages or species was estimated using the isolation with migration (IM) model with the program IMA2 (version 8.27.2012;Hey, 2010;Hey and Nielsen, 2007). The method estimates the density functions and posterior-probability densities of the IM model parameters using a Markov chain (MCMC) method (Hey and Nielsen, 2007).…”
Section: Gene Flow Estimationmentioning
confidence: 99%
“…The method estimates the density functions and posterior-probability densities of the IM model parameters using a Markov chain (MCMC) method (Hey and Nielsen, 2007). The functions of model parameters were first estimated in M-mode with one million generations, and the first 10,0000 generations as burn-in.…”
Section: Gene Flow Estimationmentioning
confidence: 99%
“…First, we used the log-likelihood statistics of nested models, which can be assessed using a w 2 test to detect whether the data are consistent with a strict allopatric speciation model (Hey and Nielsen, 2007). Once runs had converged, we tested for the fit of the data to simpler demographic models by the 'Load-Trees' mode of IMa2.…”
Section: Between-species Divergencementioning
confidence: 99%