TPQCI: A topology potential-based method to quantify functional influence of copy number variations

作者全名："Liu, Yusong; Ye, Xiufen; Zhan, Xiaohui; Yu, Christina Y.; Zhang, Jie; Huang, Kun"

作者地址："[Liu, Yusong; Ye, Xiufen] Harbin Engn Univ, Coll Intelligent Syst Sci & Engn, Harbin 150001, Heilongjiang, Peoples R China; [Liu, Yusong; Zhan, Xiaohui; Yu, Christina Y.; Zhang, Jie; Huang, Kun] Indiana Univ Sch Med, Indianapolis, IN 46202 USA; [Huang, Kun] Regenstrief Inst Hlth Care, Indianapolis, IN 46202 USA; [Zhan, Xiaohui] Shenzhen Univ, Hlth Sci Ctr, Sch Biomed Engn, Natl Reg Key Technol Engn Lab Med Ultrasound,Guan, Shenzhen 518037, Peoples R China; [Yu, Christina Y.] Ohio State Univ, Dept Biomed Informat, Columbus, OH 43210 USA; [Zhan, Xiaohui] Chongqing Med Univ, Sch Basic Med, Dept Bioinformat, Chongqing 400016, Peoples R China"

通信作者："Huang, K (corresponding author), Indiana Univ Sch Med, Dept Biostat & Hlth Data Sci, Indianapolis, IN 46202 USA."

来源：METHODS

ESI学科分类：BIOLOGY & BIOCHEMISTRY

WOS号：WOS:000668951700006

JCR分区：Q1

影响因子：4.8

年份：2021

卷号：192

期号：　

开始页：46

结束页：56

文献类型：Article

关键词：Gene module detection; Functional influence of CNV; Protein-protein interaction network; Copy number variation; Topology potential; Multi-omics data integration

摘要："Copy number variation (CNV) is a major type of chromosomal structural variation that play important roles in many diseases including cancers. Due to genome instability, a large number of CNV events can be detected in diseases such as cancer. Therefore, it is important to identify the functionally important CNVs in diseases, which currently still poses a challenge in genomics. One of the critical steps to solve the problem is to define the influence of CNV. In this paper, we provide a topology potential based method, TPQCI, to quantify this kind of influence by integrating statistics, gene regulatory associations, and biological function information. We used this metric to detect functionally enriched genes on genomic segments with CNV in breast cancer and multiple myeloma and discovered biological functions influenced by CNV. Our results demonstrate that, by using our proposed TPQCI metric, we can detect disease-specific genes that are influenced by CNVs. Source codes of TPQCI are provided in Github (https://github.com/usos/TPQCI)."

基金机构："Indiana University Precision Health Initiative; State Key Program of National Natural Science Foundation of ChinaNational Natural Science Foundation of China (NSFC) [61633004]; National key research and development program of China [2018YFC0310102, 2017YFC0306001]; Development Project of Applied Technology in Harbin [2016RAXXJ071]; China Scholarship CouncilChina Scholarship Council [201806680029]"

基金资助正文："Funds This work is partially supported by the Indiana University Precision Health Initiative (to Kun Huang and Jie Zhang) , the State Key Program of National Natural Science Foundation of China (Grant No.61633004, to Xiufen Ye) , the National key research and development program of China (Grant No. 2018YFC0310102 and 2017YFC0306001, to Xiufen Ye) , the Development Project of Applied Technology in Harbin (Grant No.2016RAXXJ071, to Xiufen Ye) and China Scholarship Council (No. 201806680029 to Yusong Liu) ."