Hierarchical structural component model for pathway analysis of common variants.

ABSTRACT: BACKGROUND:Genome-wide association studies (GWAS) have been widely used to identify phenotype-related genetic variants using many statistical methods, such as logistic and linear regression. However, GWAS-identified SNPs, as identified with stringent statistical significance, explain just a small portion of the overall estimated genetic heritability. To address this 'missing heritability' issue, gene- and pathway-based analysis, and biological mechanisms, have been used for many GWAS studies. However, many of these methods often neglect the correlation between genes and between pathways. METHODS:We constructed a hierarchical component model that considers correlations both between genes and between pathways. Based on this model, we propose a novel pathway analysis method for GWAS datasets,

SUBMITTER: Jiang N 

PROVIDER: S-EPMC7038534 | biostudies-literature | 2020 Feb

REPOSITORIES: biostudies-literature