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, Hans L. Hillege, Pim van der Harst, Gerjan Navis, Wiek H. Van Gilst, Folkert W. Asselbergs, Diane Gilbert-Diamond

*Bijbehorende auteur voor dit werk

OnderzoeksoutputAcademicpeer review

70 Citaten (Scopus)
198 Downloads (Pure)

Samenvatting

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.

Originele taal-2English
Artikelnummere66545
Aantal pagina's7
TijdschriftPLoS ONE
Volume8
Nummer van het tijdschrift6
DOI's
StatusPublished - 21-jun-2013

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