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January 2009 - March 2010

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University of Minnesota Twin Cities
College of Food, Agricultural, and Natural Resource Sciences
Department of Animal Science

PI: Yang Da

Detection of Epistasis Effects in Genome-wide Associate Studies

Complex gene interaction effects have been increasingly recognized as important genetic mechanism underlying human disease and phenotypes of agricultural species. Previous work with the use of MSI supercomputers has resulted in a parallel computing program for pairwise epistasis that reduced computing times from over a year using a single-processor to within 24 hours using parallel computing for the analysis of the Framingham Heart Study data that has 500,000 SNP markers. The researchers have developed a quantitative genetics approach to extend their epistasis testing to interactions among additive, dominance, imprinting, sex, and environment factors. Using parallel computing at MSI, they have also conducted a preliminary analysis of a USDA/NRI funded project that allowed presenting their preliminary findings at international conferences. The researchers are now developing a parallel computing tool for testing complex interaction effects among the data from the Framingham Heart Study.

Group Member

Li Ma, Graduate Student