mzQC: a versatile way to communicate quality information for biological mass spectrometry
- 1Bioinformatics Solution Center, Institut fuer Informatik, Freie Universitaet Berlin, Takustr. 9, 14195 Berlin, Germany
Abstract
Reliable quality control (QC) is essential for reproducible biological mass spectrometry, yet QC information is still typically stored in tool-specific, poorly interoperable formats that hinder comparison, reuse, and transparent reporting. We present mzQC, a community-developed standard from the HUPO Proteomics Standards Initiative for the compact, machine-readable representation of QC metrics and their associated metadata across mass spectrometry workflows. mzQC is implemented in JSON, organized to support both individual mass spectrometry acquisitions and collections thereof, with formal QC metrics definitions supported by controlled vocabularies to ensure unambiguous metric interpretation and semantic consistency. The format is supported by validation tools and reference libraries in Python, R, and Java, facilitating integration into existing software ecosystems. We demonstrate the utility of mzQC across diverse analytical modalities and QC settings, spanning longitudinal instrument monitoring, acquisition-method evaluation, study-level quality assessment, repository-scale data characterization, and spatially resolved mass spectrometry imaging. Together, these use cases show that mzQC provides not merely a file format, but a shared foundation for interoperable QC reporting, large-scale data assessment, and more rigorous, reproducible, and reusable mass spectrometry-based research.
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BibTeX
@misc{bielow2026mzqc,
title = {{mzQC: a versatile way to communicate quality information for biological mass spectrometry}},
author = {C. Bielow and M. Walzer and N. Hoffmann and J. Uszkoreit and F. Mirzadeh Sarcheshmeh and F. Nicolaus and L. Andernach and P. Boschmann and B. Burla and E. Dogu and M. Eisenacher and Y. El Abiead and D. Jimenez-Morales and S. Neumann and Y. Perez-Riverol and T. Sachsenberg and R. M Salek and M. Strobel and S. Tenzer and T. Van Den Bossche and O. Vitek and M. Wang and D. L. Tabb and W. Bittremieux},
howpublished = {bioRxiv},
year = {2026},
month = oct,
doi = {10.64898/2026.10.02.756144},
url = {https://www.biorxiv.org/content/10.64898/2026.10.02.756144v1},
note = {CC BY},
}
RIS
TY - UNPB
TI - mzQC: a versatile way to communicate quality information for biological mass spectrometry
AU - C. Bielow
AU - M. Walzer
AU - N. Hoffmann
AU - J. Uszkoreit
AU - F. Mirzadeh Sarcheshmeh
AU - F. Nicolaus
AU - L. Andernach
AU - P. Boschmann
AU - B. Burla
AU - E. Dogu
AU - M. Eisenacher
AU - Y. El Abiead
AU - D. Jimenez-Morales
AU - S. Neumann
AU - Y. Perez-Riverol
AU - T. Sachsenberg
AU - R. M Salek
AU - M. Strobel
AU - S. Tenzer
AU - T. Van Den Bossche
AU - O. Vitek
AU - M. Wang
AU - D. L. Tabb
AU - W. Bittremieux
PY - 2026
DA - 2026/10/02
PB - bioRxiv
DO - 10.64898/2026.10.02.756144
UR - https://www.biorxiv.org/content/10.64898/2026.10.02.756144v1
AB - Reliable quality control (QC) is essential for reproducible biological mass spectrometry, yet QC information is still typically stored in tool-specific, poorly interoperable formats that hinder comparison, reuse, and transparent reporting. We present mzQC, a community-developed standard from the HUPO Proteomics Standards Initiative for the compact, machine-readable representation of QC metrics and their associated metadata across mass spectrometry workflows. mzQC is implemented in JSON, organized to support both individual mass spectrometry acquisitions and collections thereof, with formal QC metrics definitions supported by controlled vocabularies to ensure unambiguous metric interpretation and semantic consistency. The format is supported by validation tools and reference libraries in Python, R, and Java, facilitating integration into existing software ecosystems. We demonstrate the utility of mzQC across diverse analytical modalities and QC settings, spanning longitudinal instrument monitoring, acquisition-method evaluation, study-level quality assessment, repository-scale data characterization, and spatially resolved mass spectrometry imaging. Together, these use cases show that mzQC provides not merely a file format, but a shared foundation for interoperable QC reporting, large-scale data assessment, and more rigorous, reproducible, and reusable mass spectrometry-based research.
ER -