Abstract #301349

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JSM 2002 Abstract #301349
Activity Number: 272
Type: Topic Contributed
Date/Time: Wednesday, August 14, 2002 : 8:30 AM to 10:20 AM
Sponsor: Section on Statistical Computing*
Abstract - #301349
Title: Identifying Quantitative Trait Loci in Experimental Crosses
Author(s): Karl Broman*+ and T. Speed
Affiliation(s): Johns Hopkins University and University of California, Berkeley
Address: 615 N Wolfe St - E3132, Baltimore, Maryland, 21205, USA
Keywords: statistical genetics ; quantitative trait loci ; model selection ; MCMC ; Bayesian information criterion ; regression
Abstract:

We consider the problem of identifying the genetic loci (called quantitative trait loci, QTLs) contributing to variation in a quantitative trait, with data on an experimental cross. A large number of different statistical approaches to this problem have been described; most make use of multiple tests of hypotheses, and many consider models allowing only a single QTL. We feel the problem is best viewed as one of model selection. We discuss the use of model selection ideas to identify QTLs in experimental crosses. We focus on a backcross experiment, with strictly additive QTLs, and concentrate on identifying QTLs, considering the estimation of their effects and precise locations of secondary importance. We present the results of a simulation study to compare the performance of a number of the more prominent methods.

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