The performance of a new local false discovery rate method on tests of association between coronary artery disease (CAD) and genome-wide genetic variants.
Shuyan MeiAli KarimnezhadMarie ForestDavid R BickelCelia M T GreenwoodPublished in: PloS one (2017)
The maximum entropy (ME) method is a recently-developed approach for estimating local false discovery rates (LFDR) that incorporates external information allowing assignment of a subset of tests to a category with a different prior probability of following the null hypothesis. Using this ME method, we have reanalyzed the findings from a recent large genome-wide association study of coronary artery disease (CAD), incorporating biologic annotations. Our revised LFDR estimates show many large reductions in LFDR, particularly among the genetic variants belonging to annotation categories that were known to be of particular interest for CAD. However, among SNPs with rare minor allele frequencies, the reductions in LFDR were modest in size.
Keyphrases
- coronary artery disease
- genome wide
- percutaneous coronary intervention
- cardiovascular events
- genome wide association study
- coronary artery bypass grafting
- small molecule
- rheumatoid arthritis
- dna methylation
- high throughput
- gene expression
- aortic stenosis
- healthcare
- heart failure
- type diabetes
- cardiovascular disease
- social media