TITLE

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

AUTHOR(S)
Wan-Yu Lin; Wen-Chung Lee
PUB. DATE
January 2010
SOURCE
BMC Genetics;2010, Vol. 11, p86
SOURCE TYPE
Academic Journal
DOC. TYPE
Article
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.
ACCESSION #
55123934

 

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