To provide a comprehensive mechanistic interpretation of how known trait-associated SNPs affect complex traits, we propose a method, Primo, for integrative analysis of GWAS summary statistics with multiple sets of omics QTL summary statistics from different cellular conditions or studies. Primo examines association patterns of SNPs to complex and omics traits. In gene regions harboring known susceptibility loci, Primo performs conditional association analysis to account for linkage disequilibrium. Primo allows for unknown study heterogeneity and sample correlations. We show two applications using Primo to examine the molecular mechanisms of known susceptibility loci and to detect and interpret pleiotropic effects.

中文翻译：

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Primo：整合多个 GWAS 和组学 QTL 汇总统计数据，用于阐明性状相关 SNP 的分子机制并检测复杂性状的多效性


为了对已知的性状相关 SNP 如何影响复杂性状提供全面的机制解释，我们提出了一种方法 Primo，用于对来自不同细胞条件或研究的多组组学 QTL 摘要统计数据进行 GWAS 摘要统计数据的综合分析。 Primo 检查 SNP 与复杂组学特征的关联模式。在含有已知易感位点的基因区域中，Primo 进行条件关联分析以解释连锁不平衡。 Primo 允许未知的研究异质性和样本相关性。我们展示了两个使用 Primo 来检查已知易感位点的分子机制并检测和解释多效性效应的应用。