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Activity Number:
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150
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Type:
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Contributed
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Date/Time:
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Monday, August 7, 2006 : 10:30 AM to 12:20 PM
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Sponsor:
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Section on Bayesian Statistical Science
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| Abstract - #307543 |
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Title:
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Bayesian Inference of Population Structure from Dominant Markers Using Mixture of Betas
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Author(s):
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Rongwei Fu*+ and Dipak Dey and Kent E. Holsinger
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Companies:
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Oregon Health & Science University and University of Connecticut and University of Connecticut
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Address:
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3181 SW Sam Jackson Park Road, Portland, OR, 97239,
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Keywords:
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mixture of betas ; dominant markers ; population structure ; FST ; reversible jump
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Abstract:
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Hierarchical Bayesian methods provide a natural way to incorporate the hierarchical structure inherent in genetic data and have been increasingly applied to genetic samples. By assuming a common FST across all loci, Bayesian methods have been used to estimate FST directly from dominant markers. However, a common FST across all loci may not be the best representation of the data. So we assume that there are groups of loci with similar mutation rates exhibiting similar degrees of genetic differentiation, thus there is a FST for each group. We develop a model of mixture of betas to model the allele frequency and use reversible jump method to identify and estimate different FST's across loci. Uncertainty about the magnitude of inbreeding is incorporated into the estimate of FST. The model is illustrated with RAPD data from 14 populations of a North American orchid, Platanthera leucophaea.
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