目前，检测循环肿瘤DNA（ctDNA）中的基因组改变已广泛应用于癌症进展和治疗反应的临床监测。虽然针对小突变的分析方法已相对成熟，但检测ctDNA中的结构变异（SVs）的策略仍相对有限。此外，由于缺乏统一的工具来调用这些不同类别变异的能力，可靠地识别小规模突变、拷贝数改变和SVs在ctDNA中的存在仍具有挑战性。我们开发了一种统一的ctDNA分析流水线（PACT），能够准确检测SVs，并在模拟、细胞系和临床数据中表现出色， consistently，超过了类似工具的性能。我们提供了PACT的通用工作流程语言流水线版本，可以通过常见的工作流程管理系统在高性能计算环境中运行。PACT可以免费获得，网址为https://github.com/ChrisMaherLab/PACT.补充数据可在Bioinformatics在线获取。© 作者（们）2023. 版权归属于牛津大学出版社。

Detection of genomic alterations in circulating tumor DNA (ctDNA) is currently used for active clinical monitoring of cancer progression and treatment response. While methods for analysis of small mutations are more developed, strategies for detecting structural variants (SVs) in ctDNA are limited. Additionally, reproducibly calling small scale mutations, copy number alterations, and SVs in ctDNA is challenging due to the lack to unified tools for these different classes of variants.We developed a unified pipeline for the analysis of ctDNA (PACT) that accurately detects SVs and consistently outperformed similar tools when applied to simulated, cell line, and clinical data. We provide PACT in the form of a Common Workflow Language pipeline which can be run by popular workflow management systems in high-performance computing environments.PACT is freely available at https://github.com/ChrisMaherLab/PACT.Supplementary data are available at Bioinformatics online.© The Author(s) 2023. Published by Oxford University Press.