Multiple Testing for SNP-SNP Interactions

Anne-Laure Boulesteix, Sylvia Lawry Centre and Institute for Medical Statistics and Epidemiology, Technical University of Munich
Carolin Strobl, Department of Statistics, University of Munich
Stefan Weidinger, Department of Dermatology and Allergy Biederstein, Technical University of Munich
H.-Erich Wichmann, Department of Epidemiology, GSF
Stefan Wagenpfeil, Institute for Medical Statistics and Epidemiology, Technical University of Munich

Abstract

Most genetic diseases are complex, i.e. associated to combinations of SNPs rather than individual SNPs. In the last few years, this topic has often been addressed in terms of SNP-SNP interaction patterns given as expressions linked by logical operators. Methods for multiple testing in high-dimensional settings can be applied when many SNPs are considered simultaneously. However, another less well-known multiple testing problem arises within a fixed subset of SNPs when the logic expression is chosen optimally. In this article, we propose a general asymptotic approach for deriving the distribution of the maximally selected chi-square statistic in various situations. We show how this result can be used for testing logic expressions - in particular SNP-SNP interaction patterns - while controlling for multiple comparisons. Simulations show that our method provides multiple testing adjustments when the logic expression is chosen such as to maximize the statistic. Its benefit is demonstrated through an application to a real dataset from a large population-based study considering allergy and asthma in KORA. An implementation of our method is available from the Comprehensive R Archive Network (CRAN) as R package 'SNPmaxsel'.

Submitted: July 6, 2007 · Accepted: November 2, 2007 · Published: December 26, 2007

Recommended Citation

Boulesteix, Anne-Laure; Strobl, Carolin; Weidinger, Stefan; Wichmann, H.-Erich; and Wagenpfeil, Stefan (2007) "Multiple Testing for SNP-SNP Interactions," Statistical Applications in Genetics and Molecular Biology: Vol. 6 : Iss. 1, Article 37.
Available at: http://www.bepress.com/sagmb/vol6/iss1/art37

 
 
 
 

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