A model selection approach for the identification of quantitative trait loci in experimental crosses

Broman, K.W. and Speed, T.P. (2002) A model selection approach for the identification of quantitative trait loci in experimental crosses. Journal of the Royal Statistical Society, 64 (4). pp. 641-656.

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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 that 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 back-cross 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 performances of the more prominent methods.

Item Type: Article
Additional Information: SNNigam Collection
Uncontrolled Keywords: Bayesian information criterion, Composite interval mapping, Markov chain Monte Carlo methods, Model selection, Quantitative trait loci, Regression
Author Affiliation: Johns Hopkins University, Baltimore, USA
Subjects: Crop Improvement > Genetics
Divisions: Chickpea
Groundnut
Millet
Pigeonpea
Sorghum
Depositing User: Mr Arbind Seth
Date Deposited: 09 May 2013 08:19
Last Modified: 09 May 2013 08:19
Official URL: http://dx.doi.org/10.1111/1467-9868.00354
URI: http://eprints.icrisat.ac.in/id/eprint/10415

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