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USING THE AMOVA FRAMEWORK TO ESTIMATE A STANDARDIZED GENETIC DIFFERENTIATION MEASURE

USING THE AMOVA FRAMEWORK TO ESTIMATE A STANDARDIZED GENETIC DIFFERENTIATION MEASURE Abstract Comparison of population structure between studies can be difficult, because the value of the often‐used FST‐statistic depends on the amount of genetic variation within populations. Recently, a standardized measure of genetic differentiation was developed based on GST, which addressed this problem, though no method was provided to estimate this standardized measure without bias. Here I present a method to estimate a standardized measure of population differentiation based on the analysis of molecular variance framework. One advantage of the method is that it can be readily expanded to include different hierarchical levels in the tested population structure. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Evolution Oxford University Press

USING THE AMOVA FRAMEWORK TO ESTIMATE A STANDARDIZED GENETIC DIFFERENTIATION MEASURE

Evolution , Volume 60 (11) – Jan 1, 2006

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References (14)

Publisher
Oxford University Press
Copyright
Copyright © 2006 Wiley Subscription Services
ISSN
0014-3820
eISSN
1558-5646
DOI
10.1111/j.0014-3820.2006.tb01874.x
Publisher site
See Article on Publisher Site

Abstract

Abstract Comparison of population structure between studies can be difficult, because the value of the often‐used FST‐statistic depends on the amount of genetic variation within populations. Recently, a standardized measure of genetic differentiation was developed based on GST, which addressed this problem, though no method was provided to estimate this standardized measure without bias. Here I present a method to estimate a standardized measure of population differentiation based on the analysis of molecular variance framework. One advantage of the method is that it can be readily expanded to include different hierarchical levels in the tested population structure.

Journal

EvolutionOxford University Press

Published: Jan 1, 2006

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