eMZed 3: flexible and interactive development of scalable LC-MS/MS data analysis workflows in Python
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| Format: | Preprint |
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2025
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| _version_ | 1866913167708258304 |
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| author | Schmitt, Uwe Hemmann, Jethro L. Zamboni, Nicola Vorholt, Julia A. Kiefer, Patrick |
| author_facet | Schmitt, Uwe Hemmann, Jethro L. Zamboni, Nicola Vorholt, Julia A. Kiefer, Patrick |
| contents | 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 highly 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2510_21484 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | eMZed 3: flexible and interactive development of scalable LC-MS/MS data analysis workflows in Python Schmitt, Uwe Hemmann, Jethro L. Zamboni, Nicola Vorholt, Julia A. Kiefer, Patrick Quantitative Methods 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 highly 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. |
| title | eMZed 3: flexible and interactive development of scalable LC-MS/MS data analysis workflows in Python |
| topic | Quantitative Methods |
| url | https://arxiv.org/abs/2510.21484 |