Epistasis can be defined as the statistical interaction of genes during the expression of a phenotype. It is believed that it plays a fundamental role in gene expression, as individual genetic variants have reported a very small increase in disease risk in previous Genome-Wide Association Studies. The most successful approach to epistasis detection is the exhaustive method, although its exponential time complexity requires a highly parallel implementation in order to be used. This work presents Fiuncho, a program that exploits all levels of parallelism present in \textit{x86\textunderscore 64} CPU clusters in order to mitigate the complexity of this approach. It supports epistasis interactions of any order, and when compared with other exhaustive methods, it is on average 242, 7 and 3 times faster than MDR, BitEpi and MPI3SNP, respectively.
翻译：Epistasis可以被定义为在表现出一种苯型时基因的统计互动。 人们认为,它在基因表达中起着根本作用,因为个别基因变异者在以前的基因组-Wide协会研究中报告说,疾病风险略有增加。 最成功的上瘾检测方法是详尽无遗的方法,尽管其指数化的时间复杂性需要高度平行的实施才能使用。 这项工作展示了Fiuncho,这是一个利用\textit{x86\textundrescore 64} CPU集群中存在的所有层次平行现象的方案,以缓解这一方法的复杂性。 它支持任何顺序的上瘾互动,与其他详尽方法相比,它平均比MDR、BitEpi和MPI3SNP分别快242、7和3倍。
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