Primo: integration of multiple GWAS and omics QTL summary statistics for elucidation of molecular mechanisms of trait-associated SNPs and detection of pleiotropy in complex traits

• Published in: Genome Biology Vol. 21; no. 1; p. 236
• Main Authors: Gleason, Kevin J, Yang, Fan, Pierce, Brandon L, He, Xin, Chen, Lin S
• Format: Journal Article
• Language: English
• Published: England BioMed Central 11-09-2020; BMC
• Subjects: Association analysis; Breast cancer; Breast Neoplasms - genetics; Conditional association analysis; Disease; DNA methylation; Gene expression; Genetic Pleiotropy; Genome-Wide Association Study; Genomes; GWAS; Humans; Integrative genomics; Linkage analysis; Linkage Disequilibrium; Method; Molecular mechanisms; Molecular modelling; Multi-omics; Omics QTL; Pleiotropy; Polymorphism, Single Nucleotide; Quantitative Trait Loci; Single-nucleotide polymorphism; Software; Statistical analysis; Pleiotropy; GWAS; Conditional association analysis; Omics QTL; Molecular mechanisms; Integrative genomics; Multi-omics
• ISSN: 1474-760X; 1474-7596; 1474-760X
• DOI: 10.1186/s13059-020-02125-w

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.