Inductive determination of allele frequency spectrum probabilities in structured populations.
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.
Type
Journal articleSubject
HumansModels, Statistical
Probability
Genetics, Population
Gene Frequency
Models, Genetic
Mutation Rate
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https://hdl.handle.net/10161/21885Published Version (Please cite this version)
10.1016/j.tpb.2018.10.004Publication Info
Uyenoyama, Marcy K; Takebayashi, Naoki; & Kumagai, Seiji (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.This is constructed from limited available data and may be imprecise. To cite this
article, please review & use the official citation provided by the journal.
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Show full item recordScholars@Duke
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 acr

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