• Journal of the Korean Data and Information Science Society
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• v.25 no.5
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• pp.1057-1067
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• 2014

Many genetic variants have been identified to be associated with complex diseases such as hypertension, diabetes and cancers throughout genome-wide association studies (GWAS). However, there still exist a serious missing heritability problem since the proportion explained by genetic variants from GWAS is very weak less than 10~15%. Gene-gene interaction study may be helpful to explain the missing heritability because most of complex disease mechanisms are involved with more than one single SNP, which include multiple SNPs or gene-gene interactions. This paper focuses on gene-gene interactions with the survival phenotype by extending the multifactor dimensionality reduction (MDR) method to the accelerated failure time (AFT) model. The standardized residual from AFT model is used as a residual score for classifying multiple geno-types into high and low risk groups and algorithm of MDR is implemented. We call this method AFT-MDR and compares the power of AFT-MDR with those of Surv-MDR and Cox-MDR in simulation studies. Also a real data for leukemia Korean patients is analyzed. It was found that the power of AFT-MDR is greater than that of Surv-MDR and is comparable with that of Cox-MDR, but is very sensitive to the censoring fraction.