| 李娜,唐迅,陈大方,胡永华.复杂疾病病因研究中基因问交互作用分析:基于基因型传递不平衡的多因子降维法[J].Chinese journal of Epidemiology,2007,28(10):1036-1040 |
| 复杂疾病病因研究中基因问交互作用分析:基于基因型传递不平衡的多因子降维法 |
| Identification of gene-gene interactions related to the etiology of complex disease: a multifactor dimensionality reduction-genotype pedigree disequilibrium test |
| Received:February 12, 2007 |
| DOI： |
| KeyWord: 多因子降维法 核心家系 复杂疾病 基因-基因交互作用 |
| English Key Word: Multifactor dimensionality reduction Nuclear family Complex disease Gene-gene interactions |
| FundProject:国家“十五”科技攻关课题资助项目(200lBA703B02) |
| Author Name | Affiliation | E-mail | | Li Na | Department of Epidemiolagy and Biostatistics, School of Puhlic Health, Peking University, Beijing l00083, China | | | Tang Xun | Department of Epidemiolagy and Biostatistics, School of Puhlic Health, Peking University, Beijing l00083, China | | | Chen Dafang | Department of Epidemiolagy and Biostatistics, School of Puhlic Health, Peking University, Beijing l00083, China | | | Hu Yonghua | Department of Epidemiolagy and Biostatistics, School of Puhlic Health, Peking University, Beijing l00083, China | yhhu@bjmu.edu.cn |
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| Abstract: |
| 介绍复杂疾病病因研究中分析基因一基因交互作用的一种新方法:基于基因型传递不平衡的多因子降维法( MDR-PDT)。文中简述MDR-PDT的基本原理、步骤及特点，并结合研究实例说明其应用过程。MDR-PDT是原始MDR的扩展，可用于多种结构类型的核心家系资料分析基因一基因交互作用。结论MDR-PDT具有非参数、无需遗传模式的特点，并能充分利用家系中多个家庭成员的信息，在复杂疾病病因研究中分析基因一基因文互作用具有良好的效能。 |
| English Abstract: |
| To introduce the application ofa multifactor dimensianality reduction-genotype pedigree disequilibrium test (MDR-PDT) for detecting gene-gene interactions in the etiology of complex disease.A brief overview on the basic theory,implementing steps and features of MDR-PDT were desa-ibed,and a practical research case was demonstrated to application of MDR-PDT in nuclear family studies.The MDR-PDT approach was the extension or development of conventional MDR method which could be used for detecting gene-gene interactions in families of diverse structure.Conclusion MDR-PDT was a new nonparametric and model-free method which might use additional family members in the nuclear families and had a good power to identify gene-gene interactions. |
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