[Detecting interaction for quantitative trait by generalized multifactor dimensionality reduction].

Item request has been placed! ×
Item request cannot be made. ×
loading   Processing Request
Read More Add to Saved list
  • Author(s): Chen Q;Chen Q; Tang X; Hu YH
  • Source:
    Zhonghua liu xing bing xue za zhi = Zhonghua liuxingbingxue zazhi [Zhonghua Liu Xing Bing Xue Za Zhi] 2010 Aug; Vol. 31 (8), pp. 938-41.
  • Publication Type:
    Journal Article
  • Language:
    Chinese
  • Additional Information
    • Source:
      Publisher: Zhonghua yi xue hui; Zhongguo yi xue ke xue yuan Liu xing bing xue wei sheng wu xue yan jiu suo Country of Publication: China NLM ID: 8208604 Publication Model: Print Cited Medium: Print ISSN: 0254-6450 (Print) Linking ISSN: 02546450 NLM ISO Abbreviation: Zhonghua Liu Xing Bing Xue Za Zhi Subsets: MEDLINE
    • Publication Information:
      Publication: Beijing : Zhonghua yi xue hui; Zhongguo yi xue ke xue yuan Liu xing bing xue wei sheng wu xue yan jiu suo
      Original Publication: [Beijing] : Zhonghua yi xue hui; Zhongguo yi xue ke xue yuan Liu xing bing xue wei sheng wu xue yan jiu suo, [1981-
    • Subject Terms:
      Models, Genetic* ; Multifactor Dimensionality Reduction*; Algorithms ; Computer Simulation ; Genotype ; Humans ; Phenotype
    • 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.
    • Publication Date:
      Date Created: 20101218 Date Completed: 20160423 Latest Revision: 20181201
    • Publication Date:
      20240829
    • Accession Number:
      21163001