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False discoveries and models for gene discovery.

Edwin J C G van den Oord1, Patrick F Sullivan

  • 1Virginia Institute for Psychiatric and Behavioral Genetics, Medical College of Virginia, Virginia Commonwealth University, Richmond, VA 23298-0126, USA. ejvandenoord@vcu.edu

Trends in Genetics : TIG
|October 11, 2003
PubMed
Summary

To find true genetic effects, researchers should focus on controlling false discoveries rather than using overly strict criteria. A stepwise approach can efficiently eliminate false positives, improving gene discovery for complex traits.

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Area of Science:

  • Genetics
  • Statistical genetics
  • Bioinformatics

Background:

  • Identifying genes for complex traits often involves stringent statistical criteria to minimize false discoveries.
  • Overly strict criteria can hinder the detection of true genetic effects.

Purpose of the Study:

  • To propose optimizing procedures for eliminating and controlling false discoveries in gene association studies.
  • To evaluate the efficiency of a stepwise approach for managing false positives.

Main Methods:

  • Simulations and theoretical analysis to compare different statistical approaches for controlling false discoveries.
  • Focus on achieving an acceptable true-positive/false-positive ratio.

Main Results:

  • A stepwise approach can eliminate false discoveries more efficiently than stringent criteria.

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  • Controlling the false discovery rate may require corrections for multiple testing in candidate gene studies.
  • The proportion of true effects detected is a more significant factor in genotyping burden than the desired false discovery rate.

    • Conclusions:

    • Current gene discovery models may be overly influenced by a fear of false discoveries.
    • Optimizing the control of false discoveries can improve the efficiency of identifying true genetic effects for complex traits.