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Odds ratio based multifactor-dimensionality reduction method for detecting gene-gene interactions.

Yujin Chung1, Seung Yeoun Lee, Robert C Elston

  • 1Department of Statistics, Seoul National University San 56-1 Shillim-Dong, Kwanak-Gu, Seoul 151-747, Korea.

Bioinformatics (Oxford, England)
|November 10, 2006
PubMed
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The new odds ratio based multifactor dimensionality reduction (OR MDR) method improves genetic association studies by providing a quantitative risk measure. This approach enhances accuracy in identifying disease-susceptibility genes for complex multifactorial diseases.

Area of Science:

  • Genetics
  • Biostatistics
  • Computational Biology

Background:

  • Identifying genes for complex diseases is challenging.
  • Traditional multifactor dimensionality reduction (MDR) has limitations in risk classification.
  • Existing methods are prone to errors with small sample sizes or similar case-control ratios.

Purpose of the Study:

  • To introduce a novel odds ratio based multifactor dimensionality reduction (OR MDR) method.
  • To enhance the accuracy of genetic association studies for complex diseases.
  • To provide a more quantitative measure of disease risk.

Main Methods:

  • Developed the odds ratio based multifactor dimensionality reduction (OR MDR) method.
  • Utilized odds ratio as a quantitative measure of disease risk.

Related Experiment Videos

  • Applied the method to a dataset from the CDC Chronic Fatigue Syndrome Research Group.

    • Main Results:

    • The OR MDR method provides a quantitative odds ratio for multilocus combinations.
    • It offers an ordering of combinations from highest to lowest risk.
    • Confidence intervals for odds ratios are provided, aiding in risk factor assessment.

    Conclusions:

    • The OR MDR method offers a more informative and accurate approach to genetic association studies.
    • It addresses limitations of the original MDR method, particularly in risk stratification.
    • The R program for OR MDR is publicly available for use.