BACKGROUND Detecting single nucleotide polymorphism (SNP) interactions is an important and challenging task in genome-wide association studies (GWAS). Various efforts have been devoted to detect SNP interactions. However, the large volume of SNP datasets results in such a big number of high-order SNP combinations that restrict the power of detecting interactions. METHODS In this paper, to combat with this challenge, we propose a two-stage approach (called HiSSI) to detect high-order SNP-SNP interactions. In the screening stage, HiSSI employs a statistically significant pattern that takes into account family wise error rate, to control false positives and to effectively screen two-locus combinations candidate set. In the searching stage, HiSSI applies two different search strategies (exhaustive search and heuristic search based on differential evolution along with χ2-test) on candidate pairwise SNP combinations to detect high-order SNP interactions. RESULTS Extensive experiments on simulated datasets are conducted to evaluate HiSSI and recently proposed and related approaches on both two-locus and three-locus disease models. A real genome-wide dataset: breast cancer dataset collected from the Wellcome Trust Case Control Consortium (WTCCC) is also used to test HiSSI. CONCLUSIONS Simulated experiments on both two-locus and three-locus disease models show that HiSSI is more powerful than other related approaches. Real experiment on breast cancer dataset, in which HiSSI detects some significantly two-locus and three-locus interactions associated with breast cancer, again corroborate the effectiveness of HiSSI in high-order SNP-SNP interaction identification.

中文翻译：

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HiSSI：基于有效显着模式和差异演化的高阶SNP-SNP相互作用检测。

背景技术在全基因组关联研究（GWAS）中，检测单核苷酸多态性（SNP）相互作用是一项重要且具有挑战性的任务。已经进行了各种努力来检测SNP相互作用。但是，大量的SNP数据集导致大量的高阶SNP组合，从而限制了检测交互作用的能力。方法在本文中，为了应对这一挑战，我们提出了一种两阶段方法（称为HiSSI）来检测高阶SNP-SNP相互作用。在筛选阶段，HiSSI采用统计上显着的模式，其中考虑了家庭的错误率，以控制假阳性并有效地筛选两座位组合候选集。在搜索阶段，HiSSI对候选的成对SNP组合应用两种不同的搜索策略（穷举搜索和基于差分进化的启发式搜索以及χ2检验），以检测高阶SNP相互作用。结果在模拟数据集上进行了广泛的实验，以评估HiSSI以及最近提出的有关两基因座和三基因座疾病模型的方法。真正的全基因组数据集：从Wellcome Trust病例对照协会（WTCCC）收集的乳腺癌数据集也用于测试HiSSI。结论在两基因座和三基因座疾病模型上进行的模拟实验表明，HiSSI比其他相关方法功能更强大。在乳腺癌数据集上进行的真实实验，其中HiSSI检测到与乳腺癌相关的一些显着的两基因座和三基因座相互作用，