Stepwise mutation likelihood computation by sequential importance sampling in subdivided population models.

Maria De Iorio; Robert C Griffiths; Raphael Leblois; François Rousset

doi:10.1016/j.tpb.2005.02.001

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Stepwise mutation likelihood computation by sequential importance sampling in subdivided population models.

Maria De Iorio·Robert C Griffiths·Raphael Leblois·François Rousset

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Abstract

An importance sampling algorithm for computing the likelihood of a sample of genes at loci under a stepwise mutation model in a subdivided population is developed. This allows maximum likelihood estimation of migration rates between subpopulations. The time to the most recent common ancestor of the sample can also be computed. The technique is illustrated by an analysis of a data set of Australian red fox populations.

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Algorithms Animal Migration Animals Computer Simulation Foxes Genetics, Population Likelihood Functions Microsatellite Repeats Models, Genetic Mutation Journal Article Research Support, Non-U.S. Gov't

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Maria De Iorio, Robert C Griffiths, Raphael Leblois, François Rousset. 2005. Stepwise mutation likelihood computation by sequential importance sampling in subdivided population models.. https://doi.org/10.1016/j.tpb.2005.02.001

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