Müller Tom David, Siraj Arslan, Walter Axel, Kim Jihyung, Wein Samuel, von Kleist Johannes, Feroz Ayesha, Pilz Matteo, Jeong Kyowon, Sing Justin Cyril, Charkow Joshua, Röst Hannes Luc, Sachsenberg Timo
Applied Bioinformatics, Department of Computer Science, University of Tübingen, Tübingen 72074, Germany.
Institute for Bioinformatics and Medical Informatics, University of Tübingen, Tübingen 72074, Germany.
J Proteome Res. 2025 Feb 7;24(2):940-948. doi: 10.1021/acs.jproteome.4c00872. Epub 2025 Jan 29.
Liquid chromatography-mass spectrometry (LC-MS) is an indispensable analytical technique in proteomics, metabolomics, and other life sciences. While OpenMS provides advanced open-source software for MS data analysis, its complexity can be challenging for nonexperts. To address this, we have developed OpenMS WebApps, a framework for creating user-friendly MS web applications based on the Streamlit Python package. OpenMS WebApps simplifies MS data analysis through an intuitive graphical user interface, interactive result visualizations, and support for both local and online execution. Key features include workspace management, automatic generation of input widgets, and parallel execution of tools, resulting in high performance and ready-to-use solutions for online and local deployment. This framework benefits both researchers and developers: scientists can focus on their research without the burden of complex software setups, and developers can rapidly create and distribute custom WebApps with novel algorithms. Several applications built on the OpenMS WebApps template demonstrate its utility across diverse MS-related fields, enhancing the OpenMS ecosystem for developers and a wider range of users. Furthermore, it integrates seamlessly with third-party software, extending its benefits to developers beyond the OpenMS community.
液相色谱-质谱联用（LC-MS）是蛋白质组学、代谢组学及其他生命科学中不可或缺的分析技术。虽然OpenMS为质谱数据分析提供了先进的开源软件，但其复杂性对非专业人员来说可能具有挑战性。为了解决这个问题，我们开发了OpenMS WebApps，这是一个基于Streamlit Python包创建用户友好型质谱网络应用程序的框架。OpenMS WebApps通过直观的图形用户界面、交互式结果可视化以及对本地和在线执行的支持，简化了质谱数据分析。关键特性包括工作区管理、输入小部件的自动生成以及工具的并行执行，从而为在线和本地部署带来高性能且即用型的解决方案。该框架对研究人员和开发人员都有益处：科学家可以专注于研究，而无需承担复杂软件设置的负担，开发人员可以使用新颖算法快速创建和分发自定义网络应用程序。基于OpenMS WebApps模板构建的多个应用程序展示了其在不同质谱相关领域的实用性，为开发人员和更广泛的用户增强了OpenMS生态系统。此外，它与第三方软件无缝集成，将其优势扩展到OpenMS社区之外的开发人员。
