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Finding susceptible and protective interaction patterns in large-scale genetic association study

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Abstract

Interaction detection in large-scale genetic association studies has attracted intensive research interest, since many diseases have complex traits. Various approaches have been developed for finding significant genetic interactions. In this article, we propose a novel framework SRMiner to detect interacting susceptible and protective genotype patterns. SRMiner can discover not only probable combination of single nucleotide polymorphisms (SNPs) causing diseases but also the corresponding SNPs suppressing their pathogenic functions, which provides a better prospective to uncover the underlying relevance between genetic variants and complex diseases. We have performed extensive experiments on several real Wellcome Trust Case Control Consortium (WTCCC) datasets. We use the pathway-based and the protein-protein interaction (PPI) network-based evaluation methods to verify the discovered patterns. The results show that SRMiner successfully identifies many disease-related genes verified by the existing work. Furthermore, SRMiner can also infer some uncomfirmed but highly possible disease-related genes.

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Acknowledgements

This work is supported by the National Natural Science Foundation of China (Grant Nos. 61272182, 61100028, and 61173029), New Century Excellent Talents (NCET-11-0085), Key Program of National Natural Science of China (61332014, U1401256), the Fundamental Research Funds for the Central Universities (130504001, 150402002), National Science Foundation (USA) (IIS-1218036, and IIS-1162374), and CAREER National Institutes of Health (USA) (R01 HG003053, and R01 GM115833). This work was finished during Yuan Li visiting Case Western Reserve University supervised by Dr. Xiang Zhang and supported by China Scholarship Council (CSC).

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Authors and Affiliations

  1. School of Computer Science and Engineering, Northeastern University, Shenyang, 110819, China

    Yuan Li, Yuhai Zhao, Guoren Wang, Zhanghui Wang & Jun Pang

  2. Department of Electronic Engineering and Computer Science, Case Western Reserve University, Cleveland, OH, 44106, USA

    Yuan Li & Xiang Zhang

  3. Department of Epidemiology and Biostatistics, Case Western Reserve University, Cleveland, OH, 44106, USA

    Xiaofeng Zhu

Authors
  1. Yuan Li
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  2. Yuhai Zhao
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  3. Guoren Wang
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  6. Zhanghui Wang
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  7. Jun Pang
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Corresponding author

Correspondence to Yuhai Zhao.

Additional information

Yuan Li received his BE and ME degrees in computer science from Northeastern University (NEU), China in 2009 and 2011, respectively. Currently he is a PhD candidate in computer science, NEU. His major research interests include data mining and bioinformatics.

Yuhai Zhao received his BE, ME and PhD degrees in computer science from Northeastern University (NEU), China in 1999, 2004 and 2007, respectively. Currently he is an associate professor in the School of Information Science and Engineering, NEU. He is a member of IEEE ACM, and a member of CCF. His major research interests include data mining and bioinformatics.

Guoren Wang received his BS, MS and PhD degrees in computer science from Northeastern University (NEU), China in 1988, 1991 and 1996, respectively. Currently he is a professor in the School of Information Science and Engineering, NEU. His major research interests are XML data management, query processing and optimization, high-dimensional indexing, parallel database systems, P2P data management and uncertain data management.

Xiaofeng Zhu is currently a professor in the Department of Epidemiology and Biostatistics at Case Western Reserve University (CWRU), USA. He received his PhD degree in Biostatistics, Epidemiology and Biostatistics from CWRU in 1998. His research interests include genetic mapping studies of hypertension, obesity; development of statistical methods for association studies avoiding the effect of population stratification; admixture mapping.

Xiang Zhang is currently the T&D Schroeder assistant professor in the Department of Electrical Engineering and Computer Science at CaseWestern Reserve University, USA. He received his PhD degree in computer science from the University of North Carolina at Chapel Hill, USA in 2011. His research bridges the areas of data mining, database and bioinformatics.

Zhanghui Wang received his BE degree in computer science from Shenyang Institute of Aeronautical Engineering, China in 2007, and his ME degree in computer science from Northeastern University (NEU), China in 2010. Currently he is a PhD candidate in computer science, NEU. His major research interests include data mining and bioinformatics.

Jun Pang received his MS degree in computer science and technology from Wuhan University of Technology, China in 2010. Currently, he is a PhD candidate of computer software and theory in Northeastern University, China. His research interests include cloud computing and similarity join.

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Li, Y., Zhao, Y., Wang, G. et al. Finding susceptible and protective interaction patterns in large-scale genetic association study. Front. Comput. Sci. 11, 541–554 (2017). https://doi.org/10.1007/s11704-016-5300-5

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