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Published on: July 27, 2021
A Simple and Computationally Efficient Approach to Multifactor Dimensionality Reduction Analysis of Gene-Gene
Jiang Gui1, Jason H Moore, Scott M Williams
1Institute for Quantitative Biomedical Sciences, Geisel School of Medicine, Lebanon, New Hampshire, United States of America ; Section of Biostatistics and Epidemiology, Departments of Community and Family Medicine, Geisel School of Medicine, Lebanon, New Hampshire, United States of America.
Abstract:
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.
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