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Randomization tests of disease-marker associations

A P Morris1, R N Curnow, J C Whittaker

  • 1University of Reading, Department of Applied Statistics, U.K. A.P.Morris@reading.ac.uk

Annals of Human Genetics
|January 1, 1997
PubMed
Summary

This study introduces a new method to test for disease associations with genetic markers. The proposed randomization procedure effectively addresses multiple testing issues in genetic association studies.

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Area of Science:

  • Population genetics
  • Statistical genetics
  • Genomic association studies

Background:

  • The Transmission/Disequilibrium Test (TDT) is a key method for detecting population associations between diseases and alleles at bi-allelic marker loci.
  • Extending TDT to multi-allelic loci presents statistical challenges, particularly concerning multiple testing.

Purpose of the Study:

  • To generalize the TDT for multi-allelic marker loci.
  • To develop a robust method for testing disease-marker associations while managing multiple testing problems.
  • To enable sequential analysis of individual allele associations.

Main Methods:

  • Proposed a generalized TDT statistic, TDT(max), to capture maximal association of individual alleles with disease.
  • Developed a randomization procedure to overcome multiple testing issues associated with TDT(max).

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  • Investigated the power of the proposed test and compared it to existing likelihood-based methods.

    • Main Results:

    • The TDT(max) statistic effectively identifies associations between multi-allelic markers and diseases.
    • The randomization procedure provides a valid approach to control for multiple testing.
    • The proposed test demonstrates strong power, comparable to likelihood-based linkage disequilibrium tests.
    • The test allows for sequential, one-sided analysis of individual allele associations.

    Conclusions:

    • The generalized TDT with a randomization procedure offers a powerful and flexible tool for genetic association studies.
    • This method effectively handles multi-allelic markers and addresses the challenge of multiple comparisons.
    • The sequential testing capability enhances its utility for exploring complex disease-gene interactions.