The expected sample allele frequencies from populations of changing size via orthogonal polynomials
Abstract
In this article, discrete and stochastic changes in (effective) population size are incorporated into the spectral representation of a biallelic diffusion process for drift and small mutation rates. A forward algorithm inspired by Hidden-Markov-Model (HMM) literature is used to compute exact sample allele frequency spectra for three demographic scenarios: single changes in (effective) population size, boom-bust dynamics, and stochastic fluctuations in (effective) population size. An approach for fully agnostic demographic inference from these sample allele spectra is explored, and sufficient statistics for stepwise changes in population size are found. Further, convergence behaviours of the polymorphic sample spectra for population size changes on different time scales are examined and discussed within the context of inference of the effective population size. Joint visual assessment of the sample spectra and the temporal coefficients of the spectral decomposition of the forward diffusion process is found to be important in determining departure from equilibrium. Stochastic changes in (effective) population size are shown to shape sample spectra particularly strongly.
Citation
Mikula , L C & Vogl , C 2024 , ' The expected sample allele frequencies from populations of changing size via orthogonal polynomials ' , Theoretical Population Biology , vol. 157 , pp. 55-85 . https://doi.org/10.1016/j.tpb.2024.03.005
Publication
Theoretical Population Biology
Status
Peer reviewed
ISSN
0040-5809Type
Journal article
Description
Funding: CV’s research was supported by the Austrian Science Fund (FWF): DK W1225-B20; LCM’s by the School of Biology at the University of St. Andrews.Collections
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