An Improved Ant Colony Optimization Algorithm for the Detection of SNP-SNP Interactions

  • Yingxia Sun
  • Junliang Shang
  • JinXing Liu
  • Shengjun Li
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9773)

Abstract

An increasing number of studies have found that one of the most important factors for emergence and development of complex diseases is the interactions between SNPs, that is to say, epistasis or epistatic interactions. Though many efforts have been made for the detection of SNP-SNP interactions, the algorithm of such studies is still ongoing due to the computational and statistical complexities. In this work, we proposed an algorithm IACO based on ant colony optimization and a novel introduced fitness function Svalue, which combined both Bayesian networks and mutual information, for detecting SNP-SNP interactions. Furthermore, a memory based strategy is also employed to improve the performance of IACO, which effectively avoids ignoring the optimal solutions that have already been identified. Experiments of IACO are performed on both simulation data sets and a real data set of age-related macular degeneration (AMD). Results show that IACO is promising in detecting SNP-SNP interactions, and might be an alternative to existing methods for inferring epistatic interactions. The software package is available online at http://www.bdmb-web.cn/index.php?m=content&c=index&a=show&catid=37&id=98.

Keywords

SNP-SNP interaction Bayesian network Mutual information Ant colony Optimization 

Notes

Acknowledgments

This work was in part supported by the National Natural Science Foundation of China (61502272, 61572284, 61572283), the Scientific Research Reward Foundation for Excellent Young and Middle-age Scientists of Shandong Province (BS2014DX004), the Science and Technology Planning Project of Qufu Normal University (xkj201410), the Opening Laboratory Fund of Qufu Normal University (sk201416), the Scientific Research Foundation of Qufu Normal University (BSQD20130119), The Innovation and Entrepreneurship Training Project for College Students of China (201510446044), The Innovation and Entrepreneurship Training Project for College Students of Qufu Normal University (2015A058, 2015A059).

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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Yingxia Sun
    • 1
  • Junliang Shang
    • 1
    • 2
  • JinXing Liu
    • 1
  • Shengjun Li
    • 1
  1. 1.School of Information Science and EngineeringQufu Normal UniversityRizhaoChina
  2. 2.Institute of Network ComputingQufu Normal UniversityRizhaoChina

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