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PMID: 17246154 Published · ppublish English Journal Article

A Test of Spatial Autocorrelation Analysis Using an Isolation-by-Distance Model.

Genetics ·Vol. 105 ·No. 1 ·1983-09-00 ·Pages 219-37

Sokal RR, Wartenberg DE

Abstract

Using the isolation-by-distance model as an example, we have examined several assumptions of spatial autocorrelation analysis applied to gene frequency surfaces. Gene frequency surfaces generated by a simulation of Wright's isolation-by-distance model were shown to exhibit spatial autocorrelation, except in the panmictic case. Identical stochastic generating processes result in surfaces with characteristics that are functions of the process parameters, such as parental vagility and neighborhood size. Differences in these parameters are detectable as differences in spatial autocorrelations after only a few generations of the simulations. Separate realizations of processes with identical parameters yield similar spatial correlograms. We have examined the inferences about population structure that could have been made from these observations if they had been real, rather than simulated, populations. From such inferences, we could have drawn conclusions about the presence of selection, migration and drift in given natural systems.

Authors & Affiliations
2 authors, click to expand affiliations / ORCID
Sokal R R
Department of Ecology, State University of New York at Stony Brook, Stony Brook, New York 11794.
Wartenberg D E
References (3)
3 references, click to expand
  1. Genetic structure of human populations. I. Local differentiation of blood group gene frequencies in Japan.
    Heredity (Edinb). 1966 Feb;21(1):9-35 PMID: 5222523
  2. The detection of disease clustering and a generalized regression approach.
    Cancer Res. 1967 Feb;27(2):209-20 PMID: 6018555
  3. Bioassay of population structure under isolation by distance.
    Am J Hum Genet. 1968 Sep;20(5):411-9 PMID: 5701613
Article Info
Journal
Genetics
Abbr.
Genetics
ISSN
0016-6731
Published
1983-09-00
Pages
219-37
Language
English
Region
United States
NLM ID
0374636
PMCID
PMC1202147
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