Li Jia, Tang Rui, Biernacka Joanna M, de Andrade Mariza
Department of Health Sciences Research, Mayo Clinic, 200 First Street SW, Harwick 776, Rochester, Minnesota 55905, USA.
BMC Proc. 2009 Dec 15;3 Suppl 7(Suppl 7):S78. doi: 10.1186/1753-6561-3-s7-s78.
After more than 200 genome-wide association studies, there have been some successful identifications of a single novel locus. Thus, the identification of single-nucleotide polymorphisms (SNP) with interaction effects is of interest. Using the Genetic Analysis Workshop 16 data from the North American Rheumatoid Arthritis Consortium, we propose an approach to screen for SNP-SNP interaction using a two-stage method and an approach for detecting gene-gene interactions using principal components. We selected a set of 17 rheumatoid arthritis candidate genes to assess both approaches. Our approach using principal components holds promise in detecting gene-gene interactions. However, further study is needed to evaluate the power and the feasibility for a whole genome-wide association analysis using the principal components approach.
在进行了200多项全基因组关联研究之后，已经成功鉴定出了一些单一的新基因座。因此，具有相互作用效应的单核苷酸多态性（SNP）的鉴定备受关注。利用来自北美类风湿关节炎联盟的遗传分析研讨会16的数据，我们提出了一种使用两阶段方法筛选SNP-SNP相互作用的方法，以及一种使用主成分检测基因-基因相互作用的方法。我们选择了一组17个类风湿关节炎候选基因来评估这两种方法。我们使用主成分的方法在检测基因-基因相互作用方面具有前景。然而，需要进一步研究以评估使用主成分方法进行全基因组关联分析的效能和可行性。
