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

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  • Shuyan Mei
  • Ali Karimnezhad
  • Marie Forest
  • David R Bickel
  • Celia M T Greenwood

Abstract

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.

Suggested Citation

  • Shuyan Mei & Ali Karimnezhad & Marie Forest & David R Bickel & Celia M T Greenwood, 2017. "The performance of a new local false discovery rate method on tests of association between coronary artery disease (CAD) and genome-wide genetic variants," PLOS ONE, Public Library of Science, vol. 12(9), pages 1-14, September.
    • Handle: RePEc:plo:pone00:0185174
    DOI: 10.1371/journal.pone.0185174
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    1. Jie Huang & Bryan Howie & Shane McCarthy & Yasin Memari & Klaudia Walter & Josine L. Min & Petr Danecek & Giovanni Malerba & Elisabetta Trabetti & Hou-Feng Zheng & Giovanni Gambaro & J. Brent Richards, 2015. "Improved imputation of low-frequency and rare variants using the UK10K haplotype reference panel," Nature Communications, Nature, vol. 6(1), pages 1-9, November.
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    Cited by:

    1. Rubin, Mark, 2021. "When to adjust alpha during multiple testing: A consideration of disjunction, conjunction, and individual testing," MetaArXiv tj6pm, Center for Open Science.

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