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EPIBLASTER-fast exhaustive two-locus epistasis detection strategy using graphical processing units

机译:使用图形处理单元的EPIBLASTER-快速穷举性两部位上位性检测策略

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摘要

Detection of epistatic interaction between loci has been postulated to provide a more in-depth understanding of the complex biological and biochemical pathways underlying human diseases. Studying the interaction between two loci is the natural progression following traditional and well-established single locus analysis. However, the added costs and time duration required for the computation involved have thus far deterred researchers from pursuing a genome-wide analysis of epistasis. In this paper, we propose a method allowing such analysis to be conducted very rapidly. The method, dubbed EPIBLASTER, is applicable to case–control studies and consists of a two-step process in which the difference in Pearson's correlation coefficients is computed between controls and cases across all possible SNP pairs as an indication of significant interaction warranting further analysis. For the subset of interactions deemed potentially significant, a second-stage analysis is performed using the likelihood ratio test from the logistic regression to obtain the P-value for the estimated coefficients of the individual effects and the interaction term. The algorithm is implemented using the parallel computational capability of commercially available graphical processing units to greatly reduce the computation time involved. In the current setup and example data sets (211 cases, 222 controls, 299468 SNPs; and 601 cases, 825 controls, 291095 SNPs), this coefficient evaluation stage can be completed in roughly 1 day. Our method allows for exhaustive and rapid detection of significant SNP pair interactions without imposing significant marginal effects of the single loci involved in the pair.
机译:推测基因座之间的上位性相互作用的检测可提供对人类疾病基础的复杂生物学和生化途径的更深入了解。研究两个基因座之间的相互作用是遵循传统的和公认的单一基因座分析之后的自然进展。但是,到目前为止,所涉及的计算所需的额外成本和持续时间已阻止研究人员进行全基因组上位性分析。在本文中,我们提出了一种允许快速进行此类分析的方法。该方法被称为EPIBLASTER,适用于病例对照研究,由两步过程组成,其中在所有可能的SNP对之间,在对照和病例之间计算了Pearson相关系数的差异,以表明需要进行进一步分析的重要相互作用。对于被认为潜在重要的相互作用子集,使用来自逻辑回归的似然比检验进行第二阶段分析,以获得各个效应和相互作用项的估计系数的P值。该算法使用市售图形处理单元的并行计算功能来实现,以大大减少所涉及的计算时间。在当前的设置和示例数据集中(211个案例,222个控件,299468个SNP;以及601个案例,825个控件,291095个SNP),该系数评估阶段大约可以在1天之内完成。我们的方法允许详尽而快速地检测出重要的SNP对相互作用,而不会强加涉及该对的单个基因座的显着边缘效应。

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