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Analysis of SNP Network Structure Based on Mutual Information of Breast Cancer Susceptibility Genes

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Bio-inspired Computing – Theories and Applications (BIC-TA 2016)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 682))

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Abstract

Genome-wide association studies (GWAS) are used to identify diseases associated with single nucleotide polymorphisms (SNPs). But many existing methods did not consider the interactions among SNPs while SNPs form a network in complex interrelated ways. In our research, we attempted to establish case and control mutual information networks based on simulation data of breast cancer associated gene BRCA2. By constructing the network and comparing the network statistics, the average degree of network is found to clearly distinguish the case and control groups. Starting from the network structure, we put forward a method to find “structural key SNPs”, and got four structural key SNPs. Two out of these four SNPs are pre-assigned causal SNPs in BRCA2. A large number of simulative experiments and results illustrate the feasibility of our proposed method.

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Acknowledgment

This work was supported by National Natural Science Foundation of China (61402187, 61502535, 61572522 and 61572523), China Postdoctoral Science Foundation funded project (2016M592267), Natural Science Foundation Project of CQ CSTC (No.cstc2012jjA40059), and Fundamental Research Funds for the Central Universities (R1607005A).

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Authors and Affiliations

  1. College of Computer and Communication Engineering, China University of Petroleum, Qingdao, 266580, Shandong, China

    Shudong Wang, Shanqiang Zhang, Xinzeng Wang, Sicheng He, Yan Zhao, Xiaodan Fan, Fayou Yuan & Xinjie Zhu

  2. School of Computer Science and Information Engineering, Chongqing Technology and Business University, Chongqing, 400067, China

    Yun Jiang

  3. Bihai Water Service Company of Qingdao West Coast New Economic District, Qingdao, 266555, Shandong, China

    Shanshan Li

Authors
  1. Shudong Wang
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  2. Shanqiang Zhang
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  3. Shanshan Li
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  4. Xinzeng Wang
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  5. Sicheng He
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  6. Yan Zhao
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  7. Xiaodan Fan
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  8. Fayou Yuan
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  9. Xinjie Zhu
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  10. Yun Jiang
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Corresponding author

Correspondence to Shanqiang Zhang .

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Editors and Affiliations

  1. Xidian University , Xi’an, China

    Maoguo Gong

  2. Huazhong University of Science and Technology, Wuhan, China

    Linqiang Pan

  3. China University of Petroleum, Qingdao, China

    Tao Song

  4. Southwest Jiaotong University , Chengdu, China

    Gexiang Zhang

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© 2016 Springer Nature Singapore Pte Ltd.

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Wang, S. et al. (2016). Analysis of SNP Network Structure Based on Mutual Information of Breast Cancer Susceptibility Genes. In: Gong, M., Pan, L., Song, T., Zhang, G. (eds) Bio-inspired Computing – Theories and Applications. BIC-TA 2016. Communications in Computer and Information Science, vol 682. Springer, Singapore. https://doi.org/10.1007/978-981-10-3614-9_52

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  • DOI: https://doi.org/10.1007/978-981-10-3614-9_52

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-3613-2

  • Online ISBN: 978-981-10-3614-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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