Next-generation sequencing has allowed identification of millions of somatic mutations in human cancer cells. A key challenge in interpreting cancer genomes is to distinguish drivers of cancer development among available genetic mutations. To address this issue, we present the first web-based application, consensus cancer driver gene caller (C3), to identify the consensus driver genes using six different complementary strategies, i.e., frequency-based, machine learning-based, functional bias-based, clustering-based, statistics model-based, and network-based strategies. This application allows users to specify customized operations when calling driver genes, and provides solid statistical evaluations and interpretable visualizations on the integration results. C3 is implemented in Python and is freely available for public use at http://drivergene.rwebox.com/c3.

中文翻译：

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C3：共识癌症驱动基因调用者。

新一代测序技术已鉴定出人类癌细胞中数百万个体细胞突变。解释癌症基因组的关键挑战是在可用的基因突变中区分癌症发展的驱动因素。为了解决这个问题，我们提出了第一个基于Web的应用程序，即共识癌症驱动基因调用者（C3），使用六种不同的互补策略来识别共识驱动基因，即基于频率，基于机器学习，基于功能偏差的策略，基于群集，基于统计模型和基于网络的策略。该应用程序允许用户在调用驱动程序基因时指定自定义操作，并提供可靠的统计评估和对整合结果的可解释可视化。C3用Python实现，可从http：// drivergene免费获得公众使用。