Bayesian identification of admixture events using multilocus molecular markers

Bayesian statistical methods for the estimation of hidden genetic structure of populations have gained considerable popularity in the recent years. Utilizing molecular marker data, Bayesian mixture models attempt to identify a hidden population structure by clustering individuals into genetically di...

Full description

Saved in:
Bibliographic Details
Published in:Molecular ecology 2006-09, Vol.15 (10), p.2833-2843
Main Authors: CORANDER, JUKKA, MARTTINEN, PEKKA
Format: Article
Language:English
Subjects:
admixture
Alleles
Bayes Theorem
Bayesian analysis
Bayesian modelling
Databases, Genetic
Gene loci
Genetic Markers - genetics
genetic mixture
Genomics
Humans
Internet
molecular markers
Population genetics
Population Groups
Software
stochastic optimization
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Bayesian statistical methods for the estimation of hidden genetic structure of populations have gained considerable popularity in the recent years. Utilizing molecular marker data, Bayesian mixture models attempt to identify a hidden population structure by clustering individuals into genetically divergent groups, whereas admixture models target at separating the ancestral sources of the alleles observed in different individuals. We discuss the difficulties involved in the simultaneous estimation of the number of ancestral populations and the levels of admixture in studied individuals' genomes. To resolve this issue, we introduce a computationally efficient method for the identification of admixture events in the population history. Our approach is illustrated by analyses of several challenging real and simulated data sets. The software ( [smallcapital baps]), implementing the methods introduced here, is freely available at http://www.rni.helsinki.fi/~jic/bapspage.html.
ISSN:0962-1083
1365-294X
DOI:10.1111/j.1365-294X.2006.02994.x