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Open Access Methodology article

Discovering joint associations between disease and gene pairs with a novel similarity test

Wan-Yu Lin12* and Wen-Chung Lee13

Author affiliations

1 Institute of Epidemiology and Preventive Medicine, College of Public Health, National Taiwan University, No. 17, Xuzhou Rd., Taipei 100, Taiwan

2 Department of Biostatistics, University of Alabama at Birmingham, 1665 University Boulevard, Birmingham, Alabama 35294, USA

3 Research Center for Genes, Environment and Human Health, National Taiwan University, No. 17, Xuzhou Rd., Taipei 100, Taiwan

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Citation and License

BMC Genetics 2010, 11:86  doi:10.1186/1471-2156-11-86

Published: 4 October 2010

Abstract

Background

Genes in a functional pathway can have complex interactions. A gene might activate or suppress another gene, so it is of interest to test joint associations of gene pairs. To simultaneously detect the joint association between disease and two genes (or two chromosomal regions), we propose a new test with the use of genomic similarities. Our test is designed to detect epistasis in the absence of main effects, main effects in the absence of epistasis, or the presence of both main effects and epistasis.

Results

The simulation results show that our similarity test with the matching measure is more powerful than the Pearson's χ2 test when the disease mutants were introduced at common haplotypes, but is less powerful when the disease mutants were introduced at rare haplotypes. Our similarity tests with the counting measures are more sensitive to marker informativity and linkage disequilibrium patterns, and thus are often inferior to the similarity test with the matching measure and the Pearson's χ2 test.

Conclusions

In detecting joint associations between disease and gene pairs, our similarity test is a complementary method to the Pearson's χ2 test.