癌症基因组框内突变功能注释及计算方法比较分析  

Comparative analysis of functional annotation and computational methods for in-frame InDels in cancer genome

作　　者：刘清瑞 刘婕 岳振宇 夏俊峰 LIU Qingrui;LIU Jie;YUE Zhenyu;XIA Junfeng(Institutes of Physical Science and Information Technology,Anhui University,Hefei 230601,China;College of Information and Artificial Intelligence,Anhui Agricultural University,Hefei 230036,China)

机构地区：[1]安徽大学物质科学与信息技术研究院,合肥230601 [2]安徽农业大学信息与人工智能学院,合肥230036

出　　处：《电子科技大学学报》2025年第2期311-320,共10页Journal of University of Electronic Science and Technology of China

基　　金：国家自然科学基金(U22A2038)。

摘　　要：框内突变是编码区插入缺失突变的一种常见类型,与癌症的发生发展密切相关。然而,计算方法在癌症驱动框内突变预测方面的有效性尚缺乏明确共识。首先,系统地比较和评估了8种计算方法,证实了它们在识别癌症驱动框内突变的适用性及可靠性。然后,选用其中4种表现优异的计算方法,进一步挖掘了癌症基因组中潜在的驱动框内突变,并探究了这些突变作为癌症驱动突变的合理性。最终,构建了一个用户访问友好、集成多种预测方法及注释信息的线上数据库dbCCID,旨在为研究人员提供便利。这些工作为癌症框内突变预测方法的选择和开发提供了理论支撑。In-frame InDel is a common type of insertion and deletion mutations in coding regions,which areclosely associated with the occurrence and development of cancer.However,there is currently a lack of clearconsensus on the efficacy of computation methods for predicting cancer driver in-frame InDels.In this paper,eightcomputational methods are comprehensively and systematically compared and evaluated,confirming theirapplicability and reliability of these methods in identifying cancer driver in-frame InDels.Then,four computationalmethods with outstanding performance are selected to mine potential driver in-frame InDels in the cancer genomeand explore the rationality of these mutations as cancer driver InDels.Finally,a user-friendly online databasedbCCID that integrates multiple prediction methods and annotation information is constructed to createconvenience for researchers.It is expected this work will provide a theoretical support for the selection anddevelopment of in-frame InDel prediction methods for cancer.

关 键 词：框内突变 癌症 性能评估 数据库构建 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]