SNP连锁不平衡下的基因隐私保护模型
作者:
作者简介:

刘海(1989-),男,贵州遵义人,博士生,主要研究领域为生物医学大数据隐私保护;彭长根(1963-),男,博士,教授,博士生导师,CCF专业会员,主要研究领域为密码学,信息安全,大数据隐私保护;吴振强(1968-),男,博士,教授,博士生导师,CCF高级会员,主要研究领域为网络与信息安全,分布式计算,数据隐私保护;雷秀娟(1975-),女,博士,教授,博士生导师,CCF高级会员,主要研究领域为生物信息计算,智能计算.

通讯作者:

吴振强,E-mail:zqiangwu@snnu.edu.cn

基金项目:

国家自然科学基金(61173190,61602290,61672334,61662009);中央高校基本科研业务费专项资金(2016CBY004,GK201704016,GK201501008);陕西省重点科技创新团队(2014KTC-18)


Genomic Privacy Preserving Framework for SNP Linkage Disequilibrium
Author:
Fund Project:

National Natural Science Foundation of China (61173190, 61602290, 61672334, 61662009); Fundamental Research Funds for the Central Universities (2016CBY004, GK201704016, GK201501008); Key Science and Technology Innovation Team in Shaanxi Province (2014KTC-18)

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    摘要:

    人类基因测序技术的快速发展,测序成本大幅降低,使基因数据得到广泛的应用,在全基因组的单核苷酸多态性与疾病关联研究中,单核苷酸多态性与患者的身份、表型和血缘关系等敏感信息相关联,单核苷酸多态性连锁不平衡容易导致患者的隐私信息泄露.为此,基于单核苷酸多态性连锁不平衡相关系数,提出矩阵差分隐私保护模型以实现基因数据和单核苷酸多态性连锁不平衡的隐私保护,同时确保基因数据具有一定的效用.该模型可以实现单核苷酸多态性连锁不平衡下全基因组关联研究中基因数据隐私与效用的权衡,并对单核苷酸多态性连锁不平衡下的基因隐私保护具有促进作用.

    Abstract:

    The cost of sequencing is substantially decreasing with the rapid development of human genome sequencing technologies. The generated genome data are supporting various applications. The genome-wide associated analysis study between the single nucleotide polymorphisms and diseases may lead to more privacy breaches for considering single nucleotide polymorphisms linkage disequilibrium, because of sensitive information related to single nucleotide polymorphisms including individual identity, phenotype, and kinship. To this end, the matrix differential privacy preserving framework is proposed based on the correlated coefficient of single nucleotide polymorphisms linkage disequilibrium. Therefore, this framework can preserve privacy of genome data and single nucleotide polymorphisms linkage disequilibrium, while ensures a certain genome data utility. And it achieves the trade-off between genome data privacy and utility for single nucleotide polymorphisms linkage disequilibrium in genome-wide association studies. Furthermore, the proposed framework plays an important role for promoting genomic privacy preserving under single nucleotide polymorphisms linkage disequilibrium.

    参考文献
    [1] Li Y, Chen L. Big biological data:Challenges and opportunities. Genomics, Proteomics & Bioinformatics, 2014,12(5):187-189.[doi:10.1016/j.gpb.2014.10.001]
    [2] Naveed M, Ayday E, Clayton EW, Fellay J, Gunter CA, Hubaux JP, Malin BA, Wang X. Privacy in the genomic era. ACM Computing Surveys (CSUR), 2015,48(1):6:1-44.[doi:10.1145/2767007]
    [3] Wagner I. Evaluating the strength of genomic privacy metrics. ACM Trans. on Privacy and Security (TOPS), 2017,20(1):2:1-34.[doi:10.1145/3020003]
    [4] Humbert M, Ayday E, Hubaux JP, Telenti A. Quantifying interdependent risks in genomic privacy. ACM Trans. on Privacy and Security (TOPS), 2017,20(1):3:1-31.[doi:10.1145/3035538]
    [5] Lin Z, Owen AB, Altman RB. Genomic research and human subject privacy. Science, 2004,305(5681):183.[doi:10.1126/science.1095019]
    [6] Homer N, Szelinger S, Redman M, Duggan D, Tembe W, Muehling J, Pearson JV, Stephan DA, Nelson SF, Craig DW. Resolving individuals contributing trace amounts of DNA to highly complex mixtures using high-density SNP genotyping microarrays. PLoS Genetics, 2008,4(8):1-9.[doi:10.1371/journal.pgen.1000167]
    [7] Gottlieb S. US employer agrees to stop genetic testing. British Medical Journal, 2001,322(7284):449.[doi:10.1136/bmj.322.7284. 449/a]
    [8] Chen F, Wang S, Jiang X, Ding S, Lu Y, Kim J, Sahinalp SC, Shimizu C, Burns JC, Wright VJ, Png E, Hibberd ML, Lloyd DD, Yang H, Telenti A, Bloss CS, Fox D, Lauter K, Ohno-Machado L. PRINCESS:Privacy-protecting rare disease international network collaboration via encryption through software guard extensions. Bioinformatics, 2017,33(6):871-878.[doi:10.1093/bioinformatics/btw758]
    [9] Ayday E. Cryptographic solutions for genomic privacy. In:Proc. of the Int'l Conf. on Financial Cryptography and Data Security. Berlin, Heidelberg:Springer-Verlag, 2016. 328-341.[doi:10.1007/978-3-662-53357-422]
    [10] Wang S, Zhang Y, Dai W, Lauter K, Kim M, Tang Y, Xiong H, Jiang X. HEALER:Homomorphic computation of exact logistic regression for secure rare disease variants analysis in GWAS. Bioinformatics, 2016,32(2):211-218.[doi:10.1093/bioinformatics/btv563]
    [11] Shimizu K, Nuida K, Rätsch G. Efficient privacy-preserving string search and an application in genomics. Bioinformatics, 2016, 32(11):1652-1661.[doi:10.1093/bioinformatics/btw050]
    [12] Wang XS, Huang Y, Zhao Y, Tang H, Wang X, Bu D. Efficient genome-wide, privacy-preserving similar patient query based on private edit distance. In:Proc. of the 22nd ACM SIGSAC Conf. on Computer and Communications Security. New York:ACM, 2015. 492-503.[doi:10.1145/2810103.2813725]
    [13] Wagner J, Paulson JN, Wang X, Bhattacharjee B, Bravo HC. Privacy-preserving microbiome analysis using secure computation. Bioinformatics, 2016,32(12):1873-1879.[doi:10.1093/bioinformatics/btw073]
    [14] Dwork C, Pottenger R. Toward practicing privacy. Journal of the American Medical Informatics Association, 2013,20(1):102-108.[doi:10.1136/amiajnl-2012-001047]
    [15] Zhao Y, Wang X, Jiang X, Ohno-Machado L, Tang H. Choosing blindly but wisely:Differentially private solicitation of DNA datasets for disease marker discovery. Journal of the American Medical Informatics Association, 2015,22(1):100-108.[doi:10. 1136/amiajnl-2014-003043]
    [16] Cai R, Hao Z, Winslett M, Xiao X, Yang Y, Zhang Z, Zhou S. Deterministic identification of specific individuals from GWAS results. Bioinformatics, 2015,31(11):1701-1707.[doi:10.1093/bioinformatics/btv018]
    [17] Tramèr F, Huang Z, Ayday E. Differential privacy with bounded priors:Reconciling utility and privacy in genome-wide association studies. In:Proc. of the 22nd ACM SIGSAC Conf. on Computer and Communications Security. New York:ACM, 2015. 1286-1297.[doi:10.1145/2810103.2813610]
    [18] Simmons S, Berger B. Realizing privacy preserving genome-wide association studies. Bioinformatics, 2016,32(9):1293-1300.[doi:10.1093/bioinformatics/btw009]
    [19] McSherry FD. Privacy integrated queries:An extensible platform for privacy-preserving data analysis. In:Proc. of the 2009 ACM SIGMOD Int'l Conf. on Management of Data. New York:ACM, 2009. 19-30.[doi:10.1145/1559845.1559850]
    [20] Dwork C, Roth A. The algorithmic foundations of differential privacy. Foundations and Trends® in Theoretical Computer Science, 2014,9(3-4):211-407.[doi:10.1561/0400000042]
    [21] NCBI retiring HapMap Resource. https://www.ncbi.nlm.nih.gov/variation/news/NCBI_retiring_HapMap/
    [22] Golub GH, Van Loan CF. Matrix Computations. 4th ed., Baltimore:The Johns Hopkins University Press, 2012. 1-104.
    [23] Samani SS, Huang Z, Ayday E, Elliot M, Fellay J, Hubaux JP, Kutalik Z. Quantifying genomic privacy via inference attack with high-order SNV correlations. In:Proc. of the 2015 IEEE Security and Privacy Workshops. IEEE, 2015. 32-40.[doi:10.1109/SPW. 2015.21]
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刘海,吴振强,彭长根,雷秀娟. SNP连锁不平衡下的基因隐私保护模型.软件学报,2019,30(4):1094-1105

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  • 收稿日期:2017-06-01
  • 最后修改日期:2017-07-13
  • 在线发布日期: 2019-04-01
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