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January 2010 - March 2011

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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

Previous work by these researchers using MSI supercomputers has resulted in a parallel computing program for pairwise epistasis. The researchers have developed a quantitative genetics approach to extend this epistasis testing to interactions among additive, dominance, imprinting, sex, and environment factors. Using parallel computing at MSI, they conducted an analysis of a USDA/NRI funded project and analysis of the Framingham Heart Study data. They are further developing their current parallel computing tool and the data analysis of genome-wide association studies in domestic animals.

Group Member

Li Ma, Graduate Student