We have developed a rapid mixed model algorithm for exhaustive genome-wide epistatic association analysis by controlling multiple polygenic effects. Our model can simultaneously handle additive by additive epistasis, dominance by dominance epistasis and additive by dominance epistasis, and account for intrasubject fluctuations due to individuals with repeated records. Furthermore, we suggest a simple but efficient approximate algorithm, which allows the examination of all pairwise interactions in a remarkably fast manner of linear with population size. Simulation studies are performed to investigate the properties of REMMAX. Application to publicly available yeast and human data has showed that our mixed model-based method has similar performance with simple linear model on computational efficiency. It took less than 40 h for the pairwise analysis of 5000 individuals genotyped with roughly 350 000 SNPs with five threads on Intel Xeon E5 2.6 GHz CPU.

中文翻译：

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通过控制多个多基因效应的快速上位混合模型关联研究。

我们已经开发出一种快速混合模型算法，用于通过控制多种多基因效应来进行详尽的全基因组上位关联分析。我们的模型可以同时通过加性上位，加性上位和加性上位来处理加性，并考虑由于重复记录的个体而导致的受试者内部波动。此外，我们提出了一种简单但有效的近似算法，该算法允许以成对的人口数量线性快速地检查所有成对的相互作用。进行仿真研究以研究REMMAX的特性。应用于公开的酵母和人类数据表明，基于混合模型的方法在计算效率上具有与简单线性模型相似的性能。