title: Odds ratio based multifactor-dimensionality reduction method for detecting gene-gene interactions.
abstract: BACKGROUND
  The identification and characterization of genes that increase the susceptibility to common complex multifactorial diseases is a challenging task in genetic association studies. The multifactor dimensionality reduction (MDR) method has been proposed and implemented by Ritchie et al. (2001) to identify the combinations of multilocus genotypes and discrete environmental factors that are associated with a particular disease. However, the original MDR method classifies the combination of multilocus genotypes into high-risk and low-risk groups in an ad hoc manner based on a simple comparison of the ratios of the number of cases and controls. Hence, the MDR approach is prone to false positive and negative errors when the ratio of the number of cases and controls in a combination of genotypes is similar to that in the entire data, or when both the number of cases and controls is small. Hence, we propose the odds ratio based multifactor dimensionality reduction (OR MDR) method that uses the odds ratio as a new quantitative measure of disease risk.
  
  
  RESULTS
  While the original MDR method provides a simple binary measure of risk, the OR MDR method provides not only the odds ratio as a quantitative measure of risk but also the ordering of the multilocus combinations from the highest risk to lowest risk groups. Furthermore, the OR MDR method provides a confidence interval for the odds ratio for each multilocus combination, which is extremely informative in judging its importance as a risk factor. The proposed OR MDR method is illustrated using the dataset obtained from the CDC Chronic Fatigue Syndrome Research Group.
  
  
  BACKGROUND
  The program written in R is available.
authors.affiliation: Department of Statistics, Seoul National University San 56-1 Shillim-Dong, Kwanak-Gu, Seoul 151-747, Korea.
authors.forename: Yujin
authors.initials: Y
authors.lastname: Chung
authors.forename: Seung Yeoun
authors.initials: SY
authors.lastname: Lee
authors.forename: Robert C
authors.initials: RC
authors.lastname: Elston
authors.forename: Taesung
authors.initials: T
authors.lastname: Park
mesh_terms: D015673:Fatigue Syndrome, Chronic / Q000235:genetics; D014644:Genetic Variation; D006801:Humans; D026901:Membrane Transport Proteins / Q000235:genetics; D008957:Models, Genetic; D015233:Models, Statistical; D016017:Odds Ratio; D011110:Polymorphism, Genetic; D025941:Protein Interaction Mapping / Q000379:methods*; D018570:Risk Assessment; D014157:Transcription Factors / Q000032:analysis / Q000235:genetics
chemical_list: D026901:Membrane Transport Proteins; D014157:Transcription Factors