ArticleBMC genetics2010
Discovering joint associations between disease and gene pairs with a novel similarity test.
Article in BMC genetics, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- Finding genomic function for genetic associations in nicotine addiction research: the ENCODE project's role in future pharmacogenomic analysis.Pharmacology, biochemistry, and behavior · 2014Article
- Haplotype-based methods for detecting uncommon causal variants with common SNPs.Genetic epidemiology · 2012Article
- Similarity-based multimarker association tests for continuous traits.Annals of human genetics · 2012Article
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Authors and funding
2 authors.
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Abstract
backgroundGenes 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.
resultsThe 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.
conclusionsIn detecting joint associations between disease and gene pairs, our similarity test is a complementary method to the Pearson's χ² test.
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