Lee Chaeyoung
Department of Bioinformatics and Life Science, Soongsil University, Seoul, South Korea.
Front Genet. 2018 Aug 21;9:341. doi: 10.3389/fgene.2018.00341. eCollection 2018.
Expression quantitative trait loci (eQTLs) are important for understanding the genetic basis of cellular activities and complex phenotypes. Genome-wide eQTL analyses can be effectively conducted by employing a mixed model. The mixed model includes random polygenic effects with variability, which can be estimated by the covariance structure of pairwise genomic similarity among individuals based on genotype information for nucleotide sequence variants. This increases the accuracy of identifying eQTLs by avoiding population stratification. Its extensive use will accelerate our understanding of the genetics of gene expression and complex phenotypes. An overview of genome-wide eQTL analyses using mixed model methodology is provided, including discussions of both theoretical and practical issues. The advantages of employing mixed models are also discussed in this review.
表达数量性状位点（eQTLs）对于理解细胞活动和复杂表型的遗传基础很重要。通过采用混合模型可以有效地进行全基因组eQTL分析。混合模型包括具有变异性的随机多基因效应，该效应可以根据个体间基于核苷酸序列变异的基因型信息的成对基因组相似性的协方差结构来估计。这通过避免群体分层提高了识别eQTL的准确性。其广泛应用将加速我们对基因表达遗传学和复杂表型的理解。本文提供了使用混合模型方法进行全基因组eQTL分析的概述，包括对理论和实际问题的讨论。本综述还讨论了采用混合模型的优势。
