Abstract
Rationale: Genome-wide association studies (GWAS) have been a successful tool in identifying variants associated with disease. A limitation of this approach is it usually fails to identify functional variants and causative gene. Studies in the past have used expression quantitative trait loci results to identify the affected gene but this approach is hampered by limited availability of tissues relevant to coronary artery disease (CAD). Here we use ENCODE (Encyclopedia of DNA Elements) data to identify putative functional variants in CAD.
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