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Multiple hypothesis testing strategies for genetic case-control association studies.

Philip S Rosenberg1, Anney Che, Bingshu E Chen

  • 1Biostatistics Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Department of Health and Human Services, Rockville, MD 20852-7244, USA. rosenbep@mail.nih.gov

Statistics in Medicine
|October 28, 2005
PubMed
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This study introduces a two-stage method for genetic association studies to identify disease-risk single nucleotide polymorphisms (SNPs) and haplotypes. It effectively manages multiple comparisons, improving the reliability of complex disease genetic research.

Area of Science:

  • Genetics
  • Statistical Genetics
  • Computational Biology

Background:

  • Case-control association studies are crucial for identifying genetic variants influencing complex diseases.
  • Genotyping multiple single nucleotide polymorphisms (SNPs) and haplotypes within candidate genes is common.
  • Statistical multiple comparisons pose a significant challenge in these studies.

Purpose of the Study:

  • To propose a robust two-stage statistical approach for genetic association studies.
  • To address and mitigate the problem of multiple comparisons in SNP and haplotype analysis.
  • To enhance the identification of genetic factors contributing to complex diseases.

Main Methods:

  • A two-stage analytical framework is presented.
  • Stage one involves summarizing gene association with a single p-value controlling the familywise error rate.

Related Experiment Videos

  • Stage two applies a false discovery rate (FDR) controlling procedure for multiplicity adjustment.

    • Main Results:

    • Simulation studies demonstrate the effectiveness of the proposed methods.
    • Marginal SNP analysis shows high power when SNPs confer susceptibility.
    • Haplotype analysis is more powerful when haplotypes confer susceptibility.
    • An omnibus test combines both approaches, adapting to the unknown mode of genetic influence.

    Conclusions:

    • The proposed two-stage method offers a balanced approach to statistical power and false positive control.
    • This strategy aims to reduce the incidence of false positive findings in genetic association literature.
    • The omnibus test provides a flexible and powerful tool for complex disease genetic research.