¹Institute for Medical Biometry, Informatics and Epidemiology, University of Bonn, Bonn, Germany

Correspondence: Dr T Becker, Institute for Medical Biometry, Informatics and Epidemiology, University of Bonn, Sigmund-Freud-Str. 25, Bonn D-53105, Germany. Tel: +49 228 287 14812; Fax: +49 228 287 15854; E-mail: Tim.Becker@ukb.uni-bonn.de

Received 29 August 2008; Revised 1 December 2008; Accepted 14 January 2009; Published online 18 February 2009.

Abstract

Recent developments in genome-wide association studies (GWAS) have lead to the localization of disease genes for many complex diseases. The scrutiny of the respective publications reveals, first, that statistical analysis is restricted typically to single-marker analysis in the first step, and that, second, the presence of multiple, independently associated SNPs within the same linkage disequilibrium (LD) region is a common phenomenon. Motivated by this observation, we show through a power simulation study that a simultaneous analysis of tightly linked SNPs in the initial GWAS analysis step would lead to increased power, when compared with that in single-marker analysis. This is true for all the three approaches we considered (implementations in BEAGLE, FAMHAP and UNPHASED). The best performance was obtained using a two-marker haplotype analysis. In conclusion, we would expect additional gene findings for re-analyzing successful GWAS with a multi-marker approach.