Haplotype-sharing analysis using Mantel statistics for combined genetic effects
- Lars BeckmannAffiliated withGerman Cancer Research Center DKFZ Email author
- , Christine FischerAffiliated withInstitute of Human Genetics, University of Heidelberg
- , Markus ObreiterAffiliated withGerman Cancer Research Center DKFZ
- , Michael RabesAffiliated withGerman Cancer Research Center DKFZ
- , Jenny Chang-ClaudeAffiliated withGerman Cancer Research Center DKFZ
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 X 2-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.
- Haplotype-sharing analysis using Mantel statistics for combined genetic effects
- Open Access
- Available under Open Access This content is freely available online to anyone, anywhere at any time.
- Online Date
- December 2005
- Online ISSN
- BioMed Central
- Additional Links