The performance of a new local false discovery rate method on tests of association between coronary artery disease (CAD) and genome-wide genetic variants

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,...

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Bibliographic Details
Published in:PloS one 2017-09, Vol.12 (9), p.e0185174-e0185174
Main Authors: Mei, Shuyan, Karimnezhad, Ali, Forest, Marie, Bickel, David R, Greenwood, Celia M T
Format: Article
Language:English
Subjects:
Analysis
Annotations
Biochemistry
Bioinformatics
Biology and Life Sciences
Cardiovascular disease
Coronary artery
Coronary artery disease
Coronary Artery Disease - genetics
Coronary heart disease
Coronary vessels
Discovery and exploration
Entropy
Epidemiology
Gene Frequency
Genetic aspects
Genetic Predisposition to Disease
Genetic testing
Genetic variation
Genetics
Genome-wide association studies
Genome-Wide Association Study - methods
Genome-Wide Association Study - statistics & numerical data
Genomes
Heart diseases
Hospitals
Humans
Hypotheses
Hypothesis testing
Immunology
Maximum entropy
Medical research
Medicine and Health Sciences
Meta-analysis
Methods
Models, Genetic
Null hypothesis
Physical Sciences
Physiological aspects
Polymorphism, Single Nucleotide
Probability
Research and Analysis Methods
Risk factors
Single-nucleotide polymorphism
Statistics
Studies
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Description
Summary: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.
ISSN:1932-6203
1932-6203
DOI:10.1371/journal.pone.0185174