Analysis of genetic diversity in geographically structured populations: A Bayesian perspective

Bayesian approaches have been widely applied to partitioning diversity with in and among levels in many different multi-level modeling contexts. In spi te of the structural similarities between these Bayesian models and hierarc hical approaches to partitioning diversity in population genetics, populati on geneticists have not explored the use of hierarchical Bayesian models to provide estimates of Wright's F-statistics. In this paper I describe and i llustrate the application of a simple multilocus, two-allele model sufficie nt for partitioning diversity within and among populations. Extenions of th e model incorporate both fixed- effect and random-effect models of populati on sampling at multiple hierarchical levels with multiple alleles per locus . The Bayesian approach developed here is closely related to previously dev eloped methods for likelihood analysis of the same problem. I illustrate th e utility of the Bayesian approach with a reanalysis of previously publishe d allozyme data from Argania spinosa.