A Simple and Computationally Efficient Approach to Multifactor Dimensionality Reduction Analysis of Gene-Gene Interactions for Quantitative Traits

Authors

Jiang Gui, Dartmouth CollegeFollow
Jason H. Moore, Dartmouth College
Scott M. Williams, Dartmouth College
Peter Andrews, Dartmouth CollegeFollow
Hillege, Hans L. Hillege, Hans L.
Pim van der Harst, University Medical Center Groningen
Gerjan| Navis, University Medical Center Groningen
Wiek H. Van Gilst, University Medical Center Groningen
Folkert W. Asselbergs, Dartmouth CollegeFollow
Diane| Gilbert-Diamond, Dartmouth CollegeFollow

Document Type

Article

Publication Date

6-21-2013

Publication Title

PloS One

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.

DOI

10.1371/journal.pone.0066545

Dartmouth Digital Commons Citation

Gui, Jiang; Moore, Jason H.; Williams, Scott M.; Andrews, Peter; Hillege, Hans L., Hillege, Hans L.; van der Harst, Pim; Navis, Gerjan|; Van Gilst, Wiek H.; Asselbergs, Folkert W.; and Gilbert-Diamond, Diane|, "A Simple and Computationally Efficient Approach to Multifactor Dimensionality Reduction Analysis of Gene-Gene Interactions for Quantitative Traits" (2013). Dartmouth Scholarship. 2513.
https://digitalcommons.dartmouth.edu/facoa/2513