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A Streamlined Approach for Mass Spectrometry-Based Proteomics Using Selected Tissue Regions
Published on: April 18, 2025
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Understanding Data Analysis Steps in Mass-Spectrometry-Based Proteomics Is Key to Transparent Reporting
Nadezhda T Doncheva1, Veit Schwämmle2, Marie Locard-Paulet3,4
1Novo Nordisk Foundation Center for Protein Research, Department of Cellular and Molecular Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, 2200 Copenhagen, Denmark.
Journal of Proteome Research
|September 3, 2025
Summary
Reporting mass spectrometry (MS)-based proteomics data analysis is crucial for reproducibility. This work outlines best practices for transparently documenting MS proteomics analysis workflows to enhance data reusability.
Area of Science:
- Proteomics
- Bioinformatics
- Data Science
Background:
- Mass spectrometry (MS)-based proteomics generates complex data requiring multi-stage analysis.
- Reproducibility and reusability of proteomics data depend on comprehensive reporting of analysis workflows.
Purpose of the Study:
- To report good practices for describing MS-based proteomics data analysis.
- To advocate for increased transparency in reporting data analysis workflows within the proteomics community.
Main Methods:
- Review and synthesis of current practices in MS-based proteomics data analysis reporting.
- Discussion of the importance of detailed workflow documentation.
Main Results:
- Identification of key stages in MS proteomics data analysis that require thorough reporting (QC, cleaning, normalization, statistical, functional analysis, visualization).
- Highlighting the challenges and potential errors in exhaustive reporting.
Conclusions:
- Adopting standardized good practices for reporting MS proteomics data analysis is essential.
- Enhanced transparency in data analysis workflows will improve data sharing and scientific collaboration.
