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Gene-Gene Interaction Analysis for the Survival Phenotype Based on the Kaplan-Meier Median Estimate.


ABSTRACT: In this study, we propose a simple and computationally efficient method based on the multifactor dimensional reduction algorithm to identify gene-gene interactions associated with the survival phenotype. The proposed method, referred to as KM-MDR, uses the Kaplan-Meier median survival time as a classifier. The KM-MDR method classifies multilocus genotypes into a binary attribute for high- or low-risk groups using median survival time and replaces balanced accuracy with log-rank test statistics as a score to determine the best model. Through intensive simulation studies, we compared the power of KM-MDR with that of Surv-MDR, Cox-MDR, and AFT-MDR. It was found that KM-MDR has a similar power to that of Surv-MDR, with less computing time, and has comparable power to that of Cox-MDR and AFT-MDR, even when there is a covariate effect. Furthermore, we apply KM-MDR to a real dataset of ovarian cancer patients from The Cancer Genome Atlas (TCGA).

SUBMITTER: Park M 

PROVIDER: S-EPMC7232685 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Gene-Gene Interaction Analysis for the Survival Phenotype Based on the Kaplan-Meier Median Estimate.

Park Mira M   Lee Jung Wun JW   Park Taesung T   Lee SeungYeoun S  

BioMed research international 20200509


In this study, we propose a simple and computationally efficient method based on the multifactor dimensional reduction algorithm to identify gene-gene interactions associated with the survival phenotype. The proposed method, referred to as KM-MDR, uses the Kaplan-Meier median survival time as a classifier. The KM-MDR method classifies multilocus genotypes into a binary attribute for high- or low-risk groups using median survival time and replaces balanced accuracy with log-rank test statistics a  ...[more]

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