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A Simple And Computationally Efficient Approach To Multifactor Dimensionality Reduction Analysis Of Gene-Gene Interactions For Quantitative Traits, Jiang Gui, Jason H. Moore, Scott M. Williams, Peter Andrews, Hillege, Hans L. Hillege, Hans L., Pim Van Der Harst, Gerjan| Navis, Wiek H. Van Gilst, Folkert W. Asselbergs, Diane| Gilbert-Diamond
A Simple And Computationally Efficient Approach To Multifactor Dimensionality Reduction Analysis Of Gene-Gene Interactions For Quantitative Traits, Jiang Gui, Jason H. Moore, Scott M. Williams, Peter Andrews, Hillege, Hans L. Hillege, Hans L., Pim Van Der Harst, Gerjan| Navis, Wiek H. Van Gilst, Folkert W. Asselbergs, Diane| Gilbert-Diamond
Dartmouth Scholarship
We present an extension of the two-class multifactor dimensionality reduction (MDR) algorithm that enables detection and characterization of epistatic SNP-SNP interactions in the context of a quantitative trait. The proposed Quantitative MDR (QMDR) method handles continuous data by modifying MDR’s constructive induction algorithm to use a T-test. QMDR replaces the balanced accuracy metric with a T-test statistic as the score to determine the best interaction model. We used a simulation to identify the empirical distribution of QMDR’s testing score. We then applied QMDR to genetic data from the ongoing prospective Prevention of Renal and Vascular End-Stage Disease (PREVEND) study.