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首页> 外文期刊>BMC Medical Genomics >Region-based interaction detection in genome-wide case-control studies
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Region-based interaction detection in genome-wide case-control studies

机译：基于区域的基因组案例控制研究中的相互作用检测

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In genome-wide association study (GWAS), conventional interaction detection methods such as BOOST are mostly based on SNP-SNP interactions. Although single nucleotides are the building blocks of human genome, single nucleotide polymorphisms (SNPs) are not necessarily the smallest functional unit for complex phenotypes. Region-based strategies have been proved to be successful in studies aiming at marginal effects. We propose a novel region-region interaction detection method named RRIntCC (region-region interaction detection for case-control studies). RRIntCC uses the correlations between individual SNP-SNP interactions based on linkage disequilibrium (LD) contrast test. Simulation experiments showed that our method can achieve a higher power than conventional SNP-based methods with similar type-I-error rates. When applied to two real datasets, RRIntCC was able to find several significant regions, while BOOST failed to identify any significant results. The source code and the sample data of RRIntCC are available at http://bioinformatics.ust.hk/RRIntCC.html. In this paper, a new region-based interaction detection method with better performance than SNP-based interaction detection methods has been proposed.
机译：在基因组 - 宽协会研究（GWAS）中，诸如升压的常规相互作用检测方法主要基于SNP-SNP相互作用。虽然单核苷酸是人类基因组的构建块，但单核苷酸多态性（SNP）不一定是复杂表型的最小功能单元。已证明基于地区的策略在旨在旨在边际效应的研究中取得成功。我们提出了一种名为RRINTCC的新型区域区相互作用检测方法（区别对照研究的区域区相互作用检测）。 RRINTCC使用基于连杆不平衡（LD）对比度测试的各个SNP-SNP相互作用之间的相关性。仿真实验表明，我们的方法可以实现比具有类似类型-I误差率的传统SNP的方法更高的功率。当应用于两个真实数据集时，RRINTCC能够找到几个重要地区，而Boost无法识别任何显着的结果。源代码和RRINTCC的示例数据可在http://bioinformatics.ust.hk/rrintcc.html上获得。在本文中，已经提出了一种新的基于区域的相互作用检测方法，具有比基于SNP的相互作用检测方法更好的性能。

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