Bayesian models for the analysis of genetic structure when populations are correlated

Rongwei (Rochelle) Fu, Dipak K. Dey, Kent E. Holsinger

Research output: Contribution to journalArticle

15 Citations (Scopus)

Abstract

Motivation: Population allele frequencies are correlated when populations have a shared history or when they exchange genes. Unfortunately, most models for allele frequency and inference about population structure ignore this correlation. Recent analytical results show that among populations, correlations can be very high, which could affect estimates of population genetic structure. In this study, we propose a mixture beta model to characterize the allele frequency distribution among populations. This formulation incorporates the correlation among populations as well as extending the model to data with different clusters of populations. Results: Using simulated data, we show that in general, the mixture model provides a good approximation of the among-population allele frequency distribution and a good estimate of correlation among populations. Results from fitting the mixture model to a dataset of genotypes at 377 autosomal microsatellite loci from human populations indicate high correlation among populations, which may not be appropriate to neglect. Traditional measures of population structure tend to over-estimate the amount of genetic differentiation when correlation is neglected. Inference is performed in a Bayesian framework.

Original languageEnglish (US)
Pages (from-to)1516-1529
Number of pages14
JournalBioinformatics
Volume21
Issue number8
DOIs
StatePublished - Apr 15 2005

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Population Structure
Bayes Theorem
Genetic Structures
Bayesian Model
Population
Gene Frequency
Population distribution
Mixture Model
Microsatellite Repeats
Genes
Estimate
Microsatellites
Population Genetics
Genotype
Locus
Model
Tend
History
Gene
Demography

ASJC Scopus subject areas

  • Clinical Biochemistry
  • Computer Science Applications
  • Computational Theory and Mathematics

Cite this

Bayesian models for the analysis of genetic structure when populations are correlated. / Fu, Rongwei (Rochelle); Dey, Dipak K.; Holsinger, Kent E.

In: Bioinformatics, Vol. 21, No. 8, 15.04.2005, p. 1516-1529.

Research output: Contribution to journalArticle

Fu, Rongwei (Rochelle) ; Dey, Dipak K. ; Holsinger, Kent E. / Bayesian models for the analysis of genetic structure when populations are correlated. In: Bioinformatics. 2005 ; Vol. 21, No. 8. pp. 1516-1529.
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