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Originally published as Genetics Published Articles Ahead of Print on May 16, 2007.

Genetics, Vol. 176, 1845-1854, July 2007, Copyright © 2007
doi:10.1534/genetics.106.068031

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Locating Multiple Interacting Quantitative Trait Loci Using Rank-Based Model Selection

Malgorzata Zak*,1, Andreas Baierl{dagger}, Malgorzata Bogdan* and Andreas Futschik{dagger}

* Institute of Mathematics and Computer Science, Wroclaw University of Technology, 50-370 Wroclaw, Poland and {dagger} Department of Statistics, Vienna University, 1040 Vienna, Austria

1 Corresponding author: Institute of Mathematics and Computer Science, Wroclaw University of Technology, Wybrzeze Wyspianskiego 27, 50-370 Wroclaw, Poland.
E-mail: malgorzata.zak{at}pwr.wroc.pl

In previous work, a modified version of the Bayesian information criterion (mBIC) was proposed to locate multiple interacting quantitative trait loci (QTL). Simulation studies and real data analysis demonstrate good properties of the mBIC in situations where the error distribution is approximately normal. However, as with other standard techniques of QTL mapping, the performance of the mBIC strongly deteriorates when the trait distribution is heavy tailed or when the data contain a significant proportion of outliers. In the present article, we propose a suitable robust version of the mBIC that is based on ranks. We investigate the properties of the resulting method on the basis of theoretical calculations, computer simulations, and a real data analysis. Our simulation results show that for the sample sizes typically used in QTL mapping, the methods based on ranks are almost as efficient as standard techniques when the data are normal and are much better when the data come from some heavy-tailed distribution or include a proportion of outliers.




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S. Isobe, A. Nakaya, and S. Tabata
Genotype Matrix Mapping: Searching for Quantitative Trait Loci Interactions in Genetic Variation in Complex Traits
DNA Res, November 13, 2007; (2007) dsm020v1.
[Abstract] [Full Text] [PDF]


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