pyOpenMS-viz: Streamlining Mass Spectrometry Data Visualization with pandas
Mass spectrometry data visualization is essential for a wide range of applications, such as validation of workflows and results, benchmarking new algorithms, and creating comprehensive quality control reports. Python offers a popular and powerful framework for analyzing and visualizing multidimensional data; however, generating commonly used mass spectrometry plots in Python can be cumbersome. Here we present pyOpenMS-viz, a versatile, unified framework for generating mass spectrometry plots. pyOpenMS-viz directly extends pandas DataFrame plotting for generating figures in a single line of code. This implementation enables easy integration across various Python-based mass spectrometry tools that already use pandas DataFrames to store MS data. pyOpenMS-viz is open-source under a BSD 3-Clause license and freely available at https://github.com/OpenMS/pyopenms_viz.
Authors
- Axel Walter (ORCID: https://orcid.org/0000-0001-9462-9712)
- Wout Bittremieux (ORCID: https://orcid.org/0000-0002-3105-1359)
- Timo T. Sachsenberg (ORCID: https://orcid.org/0000-0002-2833-6070)
- Hannes Röst (ORCID: https://orcid.org/0000-0003-0990-7488)
- Joshua Charkow (ORCID: https://orcid.org/0000-0002-4230-3646)
- Justin Sing (ORCID: https://orcid.org/0000-0003-0386-0092)
- Mingxuan Gao (ORCID: https://orcid.org/0000-0002-6619-6507)
- Tom David Müller (ORCID: https://orcid.org/0000-0003-0118-9434)
Institutions
- University of Antwerp (BE)
- University of Toronto (CA)
- Institute for Medical Informatics and Biostatistics (CH)
- University of Tübingen (DE)
Publication Details
- Journal
- Journal of Proteome Research
- Published
- 2025-02-28
- DOI
- https://doi.org/10.1021/acs.jproteome.4c00873
- Citations
- 2
- Primary Topic
- Metabolomics and Mass Spectrometry Studies
- Type
- article
- Field-Weighted Citation Impact
- 1.61
Funders
- Bundesministerium für Bildung und Forschung
- Ministerium für Wissenschaft, Forschung und Kunst Baden-Württemberg
- Canadian Institutes of Health Research