细胞外DNA（cfDNA）在血液中，被视为肿瘤活检的替代方法，具有许多临床应用，包括诊断癌症、指导癌症治疗和监测治疗反应。所有这些应用都依赖于一个不可或缺但尚未完善的任务：从cfDNA中检测体细胞突变。由于cfDNA中肿瘤比例较低，因此这项任务具有挑战性。最近，我们开发了计算方法cfSNV，这是第一个全面考虑cfDNA属性用于从cfDNA中敏感检测突变的方法。cfSNV在表现上远优于传统方法，传统方法主要为从实体肿瘤组织中调用突变而开发。cfSNV可以准确检测cfDNA中的突变，即使使用中等覆盖率（例如，≥200×）测序，这使得cfDNA的全外显子组测序（WES）成为各种临床用途的可行选择。在这里，我们呈现了一个用户友好的cfSNV包，具有快速计算和便捷的用户选项。我们还建立了一个Docker镜像，旨在使具有有限计算背景的研究人员和临床医生能够轻松地在高性能计算平台和本地计算机上执行分析。从标准预处理WES数据集（约250×和约70百万个碱基对目标大小）中调用突变可以在具有8个虚拟CPU和32 GB随机访问内存的服务器上进行3小时。©2023. Springer Nature Limited.

Cell-free DNA (cfDNA) in blood, viewed as a surrogate for tumor biopsy, has many clinical applications, including diagnosing cancer, guiding cancer treatment and monitoring treatment response. All these applications depend on an indispensable, yet underdeveloped task: detecting somatic mutations from cfDNA. The task is challenging because of the low tumor fraction in cfDNA. Recently, we developed the computational method cfSNV, the first method that comprehensively considers the properties of cfDNA for the sensitive detection of mutations from cfDNA. cfSNV vastly outperformed the conventional methods that were developed primarily for calling mutations from solid tumor tissues. cfSNV can accurately detect mutations in cfDNA even with medium-coverage (e.g., ≥200×) sequencing, which makes whole-exome sequencing (WES) of cfDNA a viable option for various clinical utilities. Here, we present a user-friendly cfSNV package that exhibits fast computation and convenient user options. We also built a Docker image of it, which is designed to enable researchers and clinicians with a limited computational background to easily carry out analyses on both high-performance computing platforms and local computers. Mutation calling from a standard preprocessed WES dataset (~250× and ~70 million base pair target size) can be carried out in 3 h on a server with eight virtual CPUs and 32 GB of random access memory.© 2023. Springer Nature Limited.