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中国工业与应用数学学会会刊
主管：中华人民共和国教育部
主办：西安交通大学
ISSN 1005-3085  CN 61-1269/O1
工程数学学报

工程数学学报 ›› 2018, Vol. 35 ›› Issue (5): 515-522.doi: 10.3969/j.issn.1005-3085.2018.05.003

• • 上一篇    下一篇

从多组学数据挖掘结核病关键基因的综合策略

张   旭1,   陈冬东2,   叶志强3,   李启明4,   谢建平4   

  1. 1- 西南大学数学与统计学院，重庆  400715
    2- 中国科学院植物研究所，北京  100049 
    3- 重庆师范大学初等教育学院，重庆  400700 
    4- 西南大学生命科学学院，重庆  400715
  • 收稿日期:2016-10-27 接受日期:2017-01-04 出版日期:2018-10-15 发布日期:2018-12-15
  • 通讯作者: 谢建平 E-mail: georgex@swu.edu.cn
  • 基金资助:
    国家自然科学基金(11701471)；中央高校基本科研业务费专项基金(XDJK2014C074)；重庆市基础科学与前沿技术研究项目(cstc2017jcyjAX0476)；西南大学博士基金(SWU113063).

Integrated Statistics Pipeline to Mine Key Genes Involved in Tuberculosis from Multiple-omics Data

ZHANG Xu1,   CHEN Dong-dong2,   YE Zhi-qiang3,   LI Qi-ming4,   XIE Jian-ping4   

  1. 1- School of Mathematics and Statistics, Southwest University, Chongqing 400715
    2- Institute of Plant, Chinese Academy of Sciences, Beijing 100049
    3- School of Elementary Education, Chongqing Normal University, Chongqing 400700
    4- College of Life Sciences, Southwest University, Chongqing 400715
  • Received:2016-10-27 Accepted:2017-01-04 Online:2018-10-15 Published:2018-12-15
  • Contact: J. Xie. E-mail address: georgex@swu.edu.cn
  • Supported by:
    The National Natural Science Foundation of China (11701471); the Fundamental Research Funds for the Central Universities (XDJK2014C074); the Basic Science and Frontier Technology Research Project of Chongqing (cstc2017jcyjAX0476); the Doctoral Fund of Southwest University (SWU113063).

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摘要： 如何确定参与肺结核易感性的相互作用和潜在网络的关键宿主基因是一项非常重要的任务．到目前为止，只有少数宿主基因被发现和证实与结核病有关．本文利用显著性分析及聚类等数学、统计学方法分析了两组和结核病相关的组学数据，发现 14 个可能性最大的结核病候选易感基因，其全部被文献报道参与各种重要的生物过程，更有五个被报道与结核病有关．这表明通过综合应用多种数学、统计学方法分析组学数据有助于缩小结核疾病相关基因的候选名单．

关键词: 组学数据, 基因, 显著性检验, 结核病, 聚类

Abstract: It is important to define the key host genes participate in the interaction and underlying networks for tuberculosis susceptibility. However, only a handful of host genes have been found and confirmed to date. Two sets of omics data about tuberculosis are analyzed in this paper through different statistical methods such as significance test and cluster analysis. 14 hits are found as most probable genes associated with tuberculosis. These hits were all reported to participate in a variety of important biological processes. What's more, five of them were reported to be directly related with tuberculosis. This indicates that the statistical methodology can be helpful to narrow down the shortlist for tuberculosis disease relevant genes.

Key words: omics data, gene, significance test, tuberculosis, clustering

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