School of Life Science and Technology, ShanghaiTech University, Shanghai 201203, China.
Shanghai Institute of Biochemistry and Cell Biology, Chinese Academy of Sciences, Shanghai 200031, China.
Bioinformatics. 2021 Jul 12;37(11):1590-1592. doi: 10.1093/bioinformatics/btaa895.
Mutational signatures are recurring DNA alteration patterns caused by distinct mutational events during the evolution of cancer. In recent years, several bioinformatics tools are available for mutational signature analysis. However, most of them focus on specific type of mutation or have limited scope of application. A pipeline tool for comprehensive mutational signature analysis is still lacking. Here we present Sigflow pipeline, which provides an one-stop solution for de novo signature extraction, reference signature fitting, signature stability analysis, sample clustering based on signature exposure in different types of genome DNA alterations including single base substitution, doublet base substitution, small insertion and deletion and copy number alteration. A Docker image is constructed to solve the complex and time-consuming installation issues, and this enables reproducible research by version control of all dependent tools along with their environments. Sigflow pipeline can be applied to both human and mouse genomes.
Sigflow is an open source software under academic free license v3.0 and it is freely available at https://github.com/ShixiangWang/sigflow or https://hub.docker.com/r/shixiangwang/sigflow.
Supplementary data are available at Bioinformatics online.
突变特征是癌症进化过程中由不同突变事件引起的反复出现的 DNA 改变模式。近年来，有几种生物信息学工具可用于突变特征分析。然而，大多数工具都侧重于特定类型的突变，或应用范围有限。仍然缺乏用于全面突变特征分析的流水线工具。本文介绍了 Sigflow 流水线，它为从头提取特征、参考特征拟合、特征稳定性分析以及基于单碱基替换、双碱基替换、小插入和缺失以及拷贝数改变等不同类型基因组 DNA 改变中特征暴露的样本聚类提供了一站式解决方案。构建了一个 Docker 镜像来解决复杂且耗时的安装问题，这通过对所有相关工具及其环境的版本控制，实现了可重复的研究。Sigflow 流水线可应用于人类和小鼠基因组。
Sigflow 是一个根据学术自由许可证 v3.0 发布的开源软件，可在 https://github.com/ShixiangWang/sigflow 或 https://hub.docker.com/r/shixiangwang/sigflow 上免费获取。
补充数据可在 Bioinformatics 在线获取。
