Likelihoods from summary statistics: recent divergence between species.

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2005-11

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Abstract

We describe an importance-sampling method for approximating likelihoods of population parameters based on multiple summary statistics. In this first application, we address the demographic history of closely related members of the Drosophila pseudoobscura group. We base the maximum-likelihood estimation of the time since speciation and the effective population sizes of the extant and ancestral populations on the pattern of nucleotide variation at DPS2002, a noncoding region tightly linked to a paracentric inversion that strongly contributes to reproductive isolation. Consideration of summary statistics rather than entire nucleotide sequences permits a compact description of the genealogy of the sample. We use importance sampling first to propose a genealogical and mutational history consistent with the observed array of summary statistics and then to correct the likelihood with the exact probability of the history determined from a system of recursions. Analysis of a subset of the data, for which recursive computation of the exact likelihood was feasible, indicated close agreement between the approximate and exact likelihoods. Our results for the complete data set also compare well with those obtained through Metropolis-Hastings sampling of fully resolved genealogies of entire nucleotide sequences.

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10.1534/genetics.104.040402

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Leman, Scotland C, Yuguo Chen, Jason E Stajich, Mohamed AF Noor and Marcy K Uyenoyama (2005). Likelihoods from summary statistics: recent divergence between species. Genetics, 171(3). pp. 1419–1436. 10.1534/genetics.104.040402 Retrieved from https://hdl.handle.net/10161/25955.

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Scholars@Duke

Noor

Mohamed A. F. Noor

Professor of Biology

Research in my laboratory strives to understand what genetic changes contribute to the formation of new species, what maintains fitness-related variation in natural populations, and how the process of genetic recombination affects both species formation and molecular evolution. Our approaches combine classical genetic, molecular genetic, and genomic/ bioinformatic analyses, along with occasional forays into areas like animal behavior (in relation to speciation). I am also very interested in helping develop educational activities (K-12 or college) in genetics and evolution.  See my lab webpage for more detailed information: https://sites.google.com/view/noor-lab 

Uyenoyama

Marcy K. Uyenoyama

Professor of Biology

Marcy Uyenoyama studies mechanisms of evolutionary change at the molecular and population levels. Among the questions under study include the prediction and detection of the effects of natural selection on genomic structure. A major area of research addresses the development of maximum-likelihood and Bayesian methods for inferring evolutionary processes from the pattern of molecular variation. Evolutionary processes currently under study include characterization of population structure across genomes.


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