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Proceedings of the National Academy of Sciences of the United States of America logoLink to Proceedings of the National Academy of Sciences of the United States of America
. 1996 Sep 17;93(19):10528–10532. doi: 10.1073/pnas.93.19.10528

Measurement of genetic structure within populations using Moran's spatial autocorrelation statistics.

B K Epperson 1, T Li 1
PMCID: PMC38420  PMID: 8927628

Abstract

Spatial structure of genetic variation within populations, an important interacting influence on evolutionary and ecological processes, can be analyzed in detail by using spatial autocorrelation statistics. This paper characterizes the statistical properties of spatial autocorrelation statistics in this context and develops estimators of gene dispersal based on data on standing patterns of genetic variation. Large numbers of Monte Carlo simulations and a wide variety of sampling strategies are utilized. The results show that spatial autocorrelation statistics are highly predictable and informative. Thus, strong hypothesis tests for neutral theory can be formulated. Most strikingly, robust estimators of gene dispersal can be obtained with practical sample sizes. Details about optimal sampling strategies are also described.

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Selected References

These references are in PubMed. This may not be the complete list of references from this article.

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