Post-GWAS Prioritization Through Data Integration Provides Novel Insights on Chronic Obstructive Pulmonary Disease.

ABSTRACT: Rich collections of genomic and epigenomic annotations, availabilities of large population cohorts for genome-wide association studies (GWAS), and advancements in data integration techniques provide the unprecedented opportunity to accelerate discoveries in complex disease studies through integrative analyses. In this paper, we apply a variety of approaches to integrate GWAS summary statistics of chronic obstructive pulmonary disease (COPD) with functional annotations to illustrate how data integration could help researchers understand complex human diseases. We show that incorporating functional annotations can better prioritize GWAS signals at both the global and the local levels. Signal prioritization on severe COPD GWAS reveals multiple potential risk loci that are linked with pulmonar

SUBMITTER: Lu Q 

PROVIDER: S-EPMC5087812 | biostudies-literature | 2016

REPOSITORIES: biostudies-literature