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This article is part of the supplement: Genetic Analysis Workshop 14: Microsatellite and single-nucleotide polymorphism

Open Access Proceedings

Haplotype-sharing analysis using Mantel statistics for combined genetic effects

Lars Beckmann1*, Christine Fischer2, Markus Obreiter1, Michael Rabes1 and Jenny Chang-Claude1

Author Affiliations

1 German Cancer Research Center DKFZ, Heidelberg, Germany

2 Institute of Human Genetics, University of Heidelberg, Heidelberg, Germany

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BMC Genetics 2005, 6(Suppl 1):S70  doi:10.1186/1471-2156-6-S1-S70

Published: 30 December 2005

Abstract

We applied a new approach based on Mantel statistics to analyze the Genetic Analysis Workshop 14 simulated data with prior knowledge of the answers. The method was developed in order to improve the power of a haplotype sharing analysis for gene mapping in complex disease. The new statistic correlates genetic similarity and phenotypic similarity across pairs of haplotypes from case-control studies. The genetic similarity is measured as the shared length between haplotype pairs around a genetic marker. The phenotypic similarity is measured as the mean corrected cross-product based on the respective phenotypes. Cases with phenotype P1 and unrelated controls were drawn from the population of Danacaa. Power to detect main effects was compared to the X2-test for association based on 3-marker haplotypes and a global permutation test for haplotype association to test for main effects. Power to detect gene × gene interaction was compared to unconditional logistic regression. The results suggest that the Mantel statistics might be more powerful than alternative tests.