Detecting interaction for quantitative trait by generalized multifactor dimensionality reduction

VernacularTitle:应用广义多因子降维法分析数量性状的交互作用
Author: Qing CHEN ¹ ; Xun TANG ; Yong-Hua HU
Author Information

1. 北京大学
Keywords: Generalized multifactor dimensionality reduction; Quantitative trait; Interaction
From: Chinese Journal of Epidemiology 2010;31(8):938-941
CountryChina
Language:Chinese
Abstract: To introduce the application of generalized multifactor dimensionality reduction (GMDR) method for detecting interactions, especially gene-gene interactions for quantitative traits. Principles, basic steps as well as features of GMDR were discussed, illustrated with a practical research case. As an interaction analysis method, GMDR was model-free, available for studies on different outcome variables including continuous ones, and permitted adjustment for covariates to improve prediction accuracy. Evidences of its capacity had been supposed by research on different diseases, e.g. nicotine dependence. GMDR method was applicable to different types of samples and outcome variables, which was superior to other statistical approaches for continuous variables in some aspects.