title: [Detecting interaction for quantitative trait by generalized multifactor dimensionality reduction].
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.
authors.affiliation: Department of Epidemiology and Biostatistics, School of Public Health, Peking University, the Key Laboratory of Epidemiology Ministry of Education, Beijing 100191, China.
authors.forename: Qing
authors.initials: Q
authors.lastname: Chen
authors.forename: Xun
authors.initials: X
authors.lastname: Tang
authors.forename: Yong-Hua
authors.initials: YH
authors.lastname: Hu
mesh_terms: D000465:Algorithms; D003198:Computer Simulation; D005838:Genotype; D006801:Humans; D008957:Models, Genetic; D058011:Multifactor Dimensionality Reduction; D010641:Phenotype