Joint analysis of functional genomic data and genome-wide association studies of 18 human traits.

ABSTRACT: Annotations of gene structures and regulatory elements can inform genome-wide association studies (GWASs). However, choosing the relevant annotations for interpreting an association study of a given trait remains challenging. I describe a statistical model that uses association statistics computed across the genome to identify classes of genomic elements that are enriched with or depleted of loci influencing a trait. The model naturally incorporates multiple types of annotations. I applied the model to GWASs of 18 human traits, including red blood cell traits, platelet traits, glucose levels, lipid levels, height, body mass index, and Crohn disease. For each trait, I used the model to evaluate the relevance of 450 different genomic annotations, including protein-coding genes, enhancers, an

SUBMITTER: Pickrell JK 

PROVIDER: S-EPMC3980523 | biostudies-literature | 2014 Apr

REPOSITORIES: biostudies-literature