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Spatial Autocorrelation for Subdivided Populations with Invariant Migration Schemes
Stockholms universitet, Naturvetenskapliga fakulteten, Matematiska institutionen.
2014 (Engelska)Ingår i: Methodology and Computing in Applied Probability, ISSN 1387-5841, E-ISSN 1573-7713, Vol. 16, nr 4, s. 777-810Artikel i tidskrift (Refereegranskat) Published
Abstract [en]

For populations with geographic substructure and selectively neutral genetic data, the short term dynamics is a balance between migration and genetic drift. Before fixation of any allele, the system enters into a quasi equilibrium (QE) state. Hossjer and Ryman (2012) developed a general QE methodology for computing approximations of spatial autocorrelations of allele frequencies between subpopulations, subpopulation differentiation (fixation indexes) and variance effective population sizes. In this paper we treat a class of models with translationally invariant migration and use Fourier transforms for computing these quantities. We show how the QE approach is related to other methods based on conditional kinship coefficients between subpopulations under mutation-migration-drift equilibrium. We also verify that QE autocorrelations of allele frequencies are closely related to the expected value of Moran's autocorrelation function and treat limits of continuous spatial location (isolation by distance) and an infinite lattice of subpopulations. The theory is illustrated with several examples including island models, circular and torus stepping stone models, von Mises models, hierarchical island models and Gaussian models. It is well known that the fixation index contains information about the effective number of migrants. The spatial autocorrelations are complementary and typically reveal the type of migration (local or global).

Ort, förlag, år, upplaga, sidor
2014. Vol. 16, nr 4, s. 777-810
Nyckelord [en]
Fixation index, Fourier transforms, Kinship coefficients, Quasi equilibrium, Spatial autocorrelations, Translationally invariant migration
Nationell ämneskategori
Matematik
Identifikatorer
URN: urn:nbn:se:su:diva-110171DOI: 10.1007/s11009-013-9321-3ISI: 000344173400001OAI: oai:DiVA.org:su-110171DiVA, id: diva2:787267
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Tillgänglig från: 2015-02-09 Skapad: 2014-12-08 Senast uppdaterad: 2017-12-04Bibliografiskt granskad

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Hössjer, Ola
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Methodology and Computing in Applied Probability
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