Comprehensive evaluation of computational methods for predicting cancer driver genes

doi:10.1093/bib/bbab548

	Comprehensive evaluation of computational methods for predicting cancer driver genes
	Shi, Xiaohui 6; Teng, Huajing 7; Shi, Leisheng 8; Bi, Wenjian 2; Wei, Wenqing 3; Mao, Fengbiao 4; Sun, Zhongsheng 5
刊名	BRIEFINGS IN BIOINFORMATICS
	2022-03-10
卷号	23
关键词	TCGA computational method cancer driver gene performance evaluation Pan-cancer analysis
ISSN号	1467-5463
DOI	10.1093/bib/bbab548
通讯作者	Mao, Fengbiao(maofengbiao@126.com) ; Sun, Zhongsheng(sunzs@biols.ac.cn)
英文摘要	Optimal methods could effectively improve the accuracy of predicting and identifying candidate driver genes. Various computational methods based on mutational frequency, network and function approaches have been developed to identify mutation driver genes in cancer genomes. However, a comprehensive evaluation of the performance levels of network-, function- and frequency-based methods is lacking. In the present study, we assessed and compared eight performance criteria for eight network-based, one function-based and three frequency-based algorithms using eight benchmark datasets. Under different conditions, the performance of approaches varied in terms of network, measurement and sample size. The frequency-based driverMAPS and network-based HotNet2 methods showed the best overall performance. Network-based algorithms using protein-protein interaction networks outperformed the function- and the frequency-based approaches. Precision, F1 score and Matthews correlation coefficient were low for most approaches. Thus, most of these algorithms require stringent cutoffs to correctly distinguish driver and non-driver genes. We constructed a website named Cancer Driver Catalog (http://159.226.67.237/sun/cancer_driver/), wherein we integrated the gene scores predicted by the foregoing software programs. This resource provides valuable guidance for cancer researchers and clinical oncologists prioritizing cancer driver gene candidates by using an optimal tool.
资助项目	National Natural Science Foundation of China[32170650] ; National Natural Science Foundation of China[31911530148] ; National Natural Science Foundation of China[32170656] ; Guangzhou and Guangdong Key Project[202007030002] ; Guangzhou and Guangdong Key Project[2018B030335001] ; Clinical Medicine Plus X -Young Scholars Project, Peking University ; Fundamental Research Funds for the Central Universities[PKU2021LCXQ015] ; Peking University Third Hospital[BYSYYZD2021001]
WOS关键词	SOMATIC MUTATIONS ; NETWORK ; GENOME ; DISCOVERY
WOS研究方向	Biochemistry & Molecular Biology ; Mathematical & Computational Biology
语种	英语
出版者	OXFORD UNIV PRESS
WOS记录号	WOS:000804196500042
资助机构	National Natural Science Foundation of China ; Guangzhou and Guangdong Key Project ; Clinical Medicine Plus X -Young Scholars Project, Peking University ; Fundamental Research Funds for the Central Universities ; Peking University Third Hospital
内容类型	期刊论文
源URL	[http://ir.hfcas.ac.cn:8080/handle/334002/131331]
专题	中国科学院合肥物质科学研究院
通讯作者	Mao, Fengbiao; Sun, Zhongsheng
作者单位	1.Univ Chinese Acad Sci, Beijing Inst Life Sci, Chinese Acad Sci, CAS Ctr Excellence Biot Interact, Beijing, Peoples R China 2.Peking Univ, Sch Basic Med Sci, Dept Med Genet, Beijing, Peoples R China 3.Beijing Inst Life Sci, Chinese Acad Sci, Beichen West Rd, Beijing 100101, Peoples R China 4.Peking Univ Third Hosp, Inst Med Innovat & Res, Huayuan North Rd, Beijing 100080, Peoples R China 5.Univ Chinese Acad Sci, State Key Lab Integrated Management Pest Insects, Inst Genom Med,Zhejiang Canc Hosp,Inst Basic Med, Wenzhou Med Univ,IBMC BGI Ctr,Canc Hosp, Beijing, Peoples R China 6.Univ Chinese Acad Sci, Beijing Inst Life Sci, Chinese Acad Sci, Beijing, Peoples R China 7.Peking Univ, Canc Hosp & Inst, Dept Radiat Oncol, Key LAb Carcinogenesis & Translat Res,Minist Educ, Beijing, Peoples R China 8.Beijing Inst Genom, Chinese Acad Sci, Key Lab Genom & Precis Med, Beijing, Peoples R China
推荐引用方式 GB/T 7714	Shi, Xiaohui,Teng, Huajing,Shi, Leisheng,et al. Comprehensive evaluation of computational methods for predicting cancer driver genes[J]. BRIEFINGS IN BIOINFORMATICS,2022,23.
APA	Shi, Xiaohui.,Teng, Huajing.,Shi, Leisheng.,Bi, Wenjian.,Wei, Wenqing.,...&Sun, Zhongsheng.(2022).Comprehensive evaluation of computational methods for predicting cancer driver genes.BRIEFINGS IN BIOINFORMATICS,23.
MLA	Shi, Xiaohui,et al."Comprehensive evaluation of computational methods for predicting cancer driver genes".BRIEFINGS IN BIOINFORMATICS 23(2022).