Inductive determination of allele frequency spectrum probabilities in structured populations.

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2019-10

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Abstract

We present a method for inductively determining exact allele frequency spectrum (AFS) probabilities for samples derived from a population comprising two demes under the infinite-allele model of mutation. This method builds on a labeled coalescent argument to extend the Ewens sampling formula (ESF) to structured populations. A key departure from the panmictic case is that the AFS conditioned on the number of alleles in the sample is no longer independent of the scaled mutation rate (θ). In particular, biallelic site frequency spectra, widely-used in explorations of genome-wide patterns of variation, depend on the mutation rate in structured populations. Variation in the rate of substitution across loci and through time may contribute to apparent distortions of site frequency spectra exhibited by samples derived from structured populations.

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10.1016/j.tpb.2018.10.004

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Uyenoyama, Marcy K, Naoki Takebayashi and Seiji Kumagai (2019). Inductive determination of allele frequency spectrum probabilities in structured populations. Theoretical population biology, 129. pp. 148–159. 10.1016/j.tpb.2018.10.004 Retrieved from https://hdl.handle.net/10161/21885.

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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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