NDLI: Bayesian Quantitative Trait Locus Mapping Using Inferred Haplotypes

Content Provider	PubMed Central
Author	Durrant, Caroline Mott, Richard
Copyright Year	2010
Abstract	We describe a fast hierarchical Bayesian method for mapping quantitative trait loci by haplotype-based association, applicable when haplotypes are not observed directly but are inferred from multiple marker genotypes. The method avoids the use of a Monte Carlo Markov chain by employing priors for which the likelihood factorizes completely. It is parameterized by a single hyperparameter, the fraction of variance explained by the quantitative trait locus, compared to the frequentist fixed-effects model, which requires a parameter for the phenotypic effect of each combination of haplotypes; nevertheless it still provides estimates of haplotype effects. We use simulation to show that the method matches the power of the frequentist regression model and, when the haplotypes are inferred, exceeds it for small QTL effect sizes. The Bayesian estimates of the haplotype effects are more accurate than the frequentist estimates, for both known and inferred haplotypes, which indicates that this advantage is independent of the effect of uncertainty in haplotype inference and will hold in comparison with frequentist methods in general. We apply the method to data from a panel of recombinant inbred lines of Arabidopsis thaliana, descended from 19 inbred founders.
Related Links	http://dx.doi.org/10.1534/genetics.109.113183
Ending Page	852
Page Count	14
Starting Page	839
File Format	PDF
ISSN	00166731
e-ISSN	19432631
Journal	Genetics
Issue Number	3
Volume Number	184
Language	English
Publisher	Genetics Society of America
Publisher Date	2010-03-01
Access Restriction	Open
Rights Holder	Genetics Society of America
Subject Keyword	Genetics Research in Higher Education
Content Type	Text
Resource Type	Article
Subject	Genetics

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