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

Seungyeoun Lee1, Donghee Son1, Wenbao Yu2

  • 1Department of Mathematics and Statistics, Sejong University, Seoul 05006, Korea.

Genomics & Informatics
|February 4, 2017
PubMed
Summary
This summary is machine-generated.

Investigating gene-gene interactions addresses the missing heritability in common diseases. A new method, accelerated failure time unified model-based multifactor dimensionality reduction (AFT UM-MDR), is proposed for survival phenotypes.

Keywords:
accelerated failure time modelgene-gene interactionmultifactor dimensionality reduction methodsurvival phenotype

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Area of Science:

  • Genetics and Bioinformatics
  • Statistical Genetics
  • Computational Biology

Background:

  • Genome-wide association studies (GWAS) identify genetic variants for common diseases but explain limited heritability.
  • The "missing heritability" problem necessitates exploring complex genetic architectures beyond single-locus associations.
  • Gene-gene interactions are crucial for a comprehensive understanding of disease etiology.

Purpose of the Study:

  • To propose a novel method, accelerated failure time unified model-based multifactor dimensionality reduction (AFT UM-MDR), for analyzing gene-gene interactions in survival data.
  • To extend the unified model-based multifactor dimensionality reduction (UM-MDR) approach to accommodate survival phenotypes.
  • To evaluate the performance of the proposed AFT UM-MDR method.

Main Methods:

  • The study introduces AFT UM-MDR, integrating accelerated failure time (AFT) models with UM-MDR.
  • The core of the method involves incorporating AFT-MDR into the classification step of UM-MDR.
  • The proposed method is compared against AFT-MDR using simulation studies.

Main Results:

  • Simulation studies were conducted to compare AFT UM-MDR with AFT-MDR.
  • The performance comparison aimed to assess the efficacy of the novel approach in gene-gene interaction analysis for survival data.
  • Results from simulations provide insights into the utility of AFT UM-MDR.

Conclusions:

  • The AFT UM-MDR method offers a new approach for gene-gene interaction analysis in survival phenotypes.
  • This method contributes to addressing the "missing heritability" by exploring complex genetic interactions.
  • Further discussion and validation are warranted for the proposed AFT UM-MDR method.