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Cheng-Hong Yang1,2, Li-Yeh Chuang3, Yu-Da Lin1

  • 1Department of Electronic Engineering, National Kaohsiung University of Applied Sciences, Kaohsiung, Taiwan.

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|February 23, 2018
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Summary
This summary is machine-generated.

The new multiobjective multifactor dimensionality reduction (MOMDR) method improves the detection of single-nucleotide polymorphism (SNP)-SNP interactions (SSIs) for disease susceptibility. MOMDR offers higher success rates than traditional single-objective approaches.

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Area of Science:

  • Genetics and Bioinformatics
  • Computational Biology
  • Statistical Genetics

Background:

  • Single-nucleotide polymorphism (SNP)-SNP interactions (SSIs) are crucial for understanding complex disease susceptibility.
  • Current multifactor dimensionality reduction (MDR) methods often rely on a single objective function, potentially limiting SSI detection accuracy.
  • Disease complexity and model preferences can hinder the effectiveness of single-measure approaches.

Purpose of the Study:

  • To introduce a novel multiobjective MDR (MOMDR) method for enhanced SSI detection.
  • To evaluate the performance of MOMDR against single-objective MDR (SOMDR) in identifying disease-associated SSIs.
  • To provide a more robust approach for analyzing complex genetic interactions.

Main Methods:

  • Developed a multiobjective MDR (MOMDR) framework utilizing contingency tables as objective functions.
  • Incorporated multiple measures, including correct classification and likelihood rates, within the MOMDR objective function.
  • Employed set theory and cross-validation consistency for predicting optimal SSIs.

Main Results:

  • Simulation studies demonstrated that MOMDR achieved significantly higher detection success rates compared to SOMDR.
  • Analysis of the Wellcome Trust Case Control Consortium dataset identified SSIs associated with coronary artery disease using MOMDR.
  • MOMDR enables simultaneous utilization of multiple measures for more comprehensive SSI identification.

Conclusions:

  • MOMDR provides a more effective strategy for detecting single-nucleotide polymorphism (SNP)-SNP interactions (SSIs) compared to existing single-objective methods.
  • The multiobjective approach enhances the ability to uncover complex genetic associations relevant to disease susceptibility.
  • MOMDR is a valuable tool for genetic association studies, offering improved accuracy and robustness.