CCLHunter:用于癌细胞系验证的有效工具包。
CCLHunter: An efficient toolkit for cancer cell line authentication.
发表日期:2023
作者:
Congfan Bu, Xinchang Zheng, Jialin Mai, Zhi Nie, Jingyao Zeng, Qiheng Qian, Tianyi Xu, Yanling Sun, Yiming Bao, Jingfa Xiao
来源:
Computational and Structural Biotechnology Journal
摘要:
癌细胞系在癌症研究中至关重要,但准确鉴定这些细胞系可能具有挑战性,特别是对于具有密切遗传相似性的近亲细胞系。我们引入了一种新的癌细胞系猎人(CCLHunter)方法来应对这一挑战。该方法利用单核苷酸多态性、表达谱和亲缘拓扑信息来准确鉴定 1389 个人类癌细胞系。 CCLHunter 可以精确有效地鉴定来自近亲谱系的细胞系和来自同一个体其他组织的细胞系。我们的评估结果表明,CCLHunter 的完全准确率为 93.27%,即使对于近亲细胞系,准确率也高达 89.28%,优于现有方法。此外,我们还通过独立软件和 Web 服务器提供对 CCLHunter 的便捷访问:https://ngdc.cncb.ac.cn/cclhunter。© 2023 作者。
Cancer cell lines are essential in cancer research, yet accurate authentication of these cell lines can be challenging, particularly for consanguineous cell lines with close genetic similarities. We introduce a new Cancer Cell Line Hunter (CCLHunter) method to tackle this challenge. This approach utilizes the information of single nucleotide polymorphisms, expression profiles, and kindred topology to authenticate 1389 human cancer cell lines accurately. CCLHunter can precisely and efficiently authenticate cell lines from consanguineous lineages and those derived from other tissues of the same individual. Our evaluation results indicate that CCLHunter has a complete accuracy rate of 93.27%, with an accuracy of 89.28% even for consanguineous cell lines, outperforming existing methods. Additionally, we provide convenient access to CCLHunter through standalone software and a web server at https://ngdc.cncb.ac.cn/cclhunter.© 2023 The Authors.