Genomics Inform.  2016 Dec;14(4):166-172. 10.5808/GI.2016.14.4.166.

Gene-Gene Interaction Analysis for the Accelerated Failure Time Model Using a Unified Model-Based Multifactor Dimensionality Reduction Method

Affiliations
  • 1Department of Mathematics and Statistics, Sejong University, Seoul 05006, Korea. leesy@sejong.ac.kr
  • 2Division of Oncology and Center for Childhood Cancer Research, Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA.
  • 3Department of Statistics, Seoul National University, Seoul 08826, Korea.

Abstract

Although a large number of genetic variants have been identified to be associated with common diseases through genome-wide association studies, there still exits limitations in explaining the missing heritability. One approach to solving this missing heritability problem is to investigate gene-gene interactions, rather than a single-locus approach. For gene-gene interaction analysis, the multifactor dimensionality reduction (MDR) method has been widely applied, since the constructive induction algorithm of MDR efficiently reduces high-order dimensions into one dimension by classifying multi-level genotypes into high- and low-risk groups. The MDR method has been extended to various phenotypes and has been improved to provide a significance test for gene-gene interactions. In this paper, we propose a simple method, called accelerated failure time (AFT) UM-MDR, in which the idea of a unified model-based MDR is extended to the survival phenotype by incorporating AFT-MDR into the classification step. The proposed AFT UM-MDR method is compared with AFT-MDR through simulation studies, and a short discussion is given.

Keyword

accelerated failure time model; gene-gene interaction; multifactor dimensionality reduction method; survival phenotype

MeSH Terms

Classification
Genome-Wide Association Study
Genotype
Methods*
Multifactor Dimensionality Reduction*
Phenotype
Full Text Links
  • GNI
Actions
Cited
CITED
export Copy
Close
Share
  • Twitter
  • Facebook
Similar articles
Copyright © 2024 by Korean Association of Medical Journal Editors. All rights reserved.     E-mail: koreamed@kamje.or.kr