eMZed 3: flexible and interactive development of scalable LC-MS/MS data analysis workflows in Python

Abstract Summary Liquid chromatography–mass spectrometry (LC-MS/MS) data analysis requires adaptable software solutions to meet diverse analytical needs. We present eMZed 3, a modern Python framework for flexible and interactive analysis of LC-MS/MS data. eMZed 3 enables users to develop scalable workflows tailored to their specific requirements while leveraging Python's extensive ecosystem of libraries. Building on its predecessor, eMZed 3 is now Python 3-based and includes substantial enhancements, including support for chromatogram-based LC-MS data, a new SQLite-based backend supporting optional out-of-memory processing, and rich interactive visualization tools. Compared to the previous version, eMZed 3 is now split into three packages: emzed (core functionalities), emzed-gui (interactive data visualization), and emzed-spyder (an integrated development environment). This modular architecture allows straightforward integration of the emzed core library into headless Python environments, including computational notebooks (such as Jupyter) or high-performance computing clusters. eMZed 3 incorporates well-established libraries such as OpenMS, and is suited for both targeted and untargeted metabolomics. Overall, eMZed 3 supports the efficient development of scalable and reproducible LC-MS data analysis and is accessible to both novice and advanced programmers. Availability and implementation eMZed 3 and its documentation are freely available at https://emzed.ethz.ch, the source code is hosted at https://gitlab.com/groups/emzed3. An online-executable example workflow is available on Binder at: https://mybinder.org/v2/gl/emzed3%2Femzed-example-workflow/HEAD?labpath=example.ipynb.