• Communicating Mass Spectrometr...

Treffer: Communicating Mass Spectrometry Quality Information in mzQC with Python, R, and Java.

Title:
Communicating Mass Spectrometry Quality Information in mzQC with Python, R, and Java.
Authors:
Bielow C; Bioinformatics Solution Center, Institut für Mathematik und Informatik, Freie Universität Berlin, Takustrasse 9, 14195 Berlin, Germany., Hoffmann N; Institute for Bio- and Geosciences (IBG-5), Forschungszentrum Jülich GmbH, 52428 Jülich, Germany., Jimenez-Morales D; Department of Medicine, Stanford University School of Medicine, Stanford, California 94305, United States., Van Den Bossche T; Department of Biomolecular Medicine, Faculty of Medicine and Health Sciences, Ghent University, Technologiepark-Zwijnaarde 75, 9052 Ghent, Belgium.; VIB-UGent Center for Medical Biotechnology, VIB, Technologiepark-Zwijnaarde 75, 9052 Ghent, Belgium., Vizcaíno JA; European Molecular Biology Laboratory, EMBL-European Bioinformatics Institute (EMBL-EBI), Hinxton, Cambridge CB10 1SD, United Kingdom., Tabb DL; European Research Institute for the Biology of Ageing, University Medical Center Groningen, Groningen 9713 AV, The Netherlands., Bittremieux W; Department of Computer Science, University of Antwerp, Antwerpen 2020, Belgium., Walzer M; European Molecular Biology Laboratory, EMBL-European Bioinformatics Institute (EMBL-EBI), Hinxton, Cambridge CB10 1SD, United Kingdom.
Source:
Journal of the American Society for Mass Spectrometry [J Am Soc Mass Spectrom] 2024 Aug 07; Vol. 35 (8), pp. 1875-1882. Date of Electronic Publication: 2024 Jun 25.
Publication Type:
Journal Article
Language:
English
Journal Info:
Publisher: ACS Publications Country of Publication: United States NLM ID: 9010412 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1879-1123 (Electronic) Linking ISSN: 10440305 NLM ISO Abbreviation: J Am Soc Mass Spectrom Subsets: MEDLINE
Imprint Name(s):
Publication: 2020- : Washington, DC : ACS Publications
Original Publication: New York, NY : Elsevier, c1990-
MeSH Terms:
Software* , Programming Languages* , Mass Spectrometry*/methods , Mass Spectrometry*/standards , Quality Control* , Proteomics*/methods , Proteomics*/standards, Humans ; Workflow
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Grant Information:
United Kingdom WT_ Wellcome Trust
Entry Date(s):
Date Created: 20240626 Date Completed: 20240807 Latest Revision: 20240811
Update Code:
20250114
PubMed Central ID:
PMC11311537
DOI:
10.1021/jasms.4c00174
PMID:
38918936
Database:
MEDLINE

Weitere Informationen

Mass spectrometry is a powerful technique for analyzing molecules in complex biological samples. However, inter- and intralaboratory variability and bias can affect the data due to various factors, including sample handling and preparation, instrument calibration and performance, and data acquisition and processing. To address this issue, the Quality Control (QC) working group of the Human Proteome Organization's Proteomics Standards Initiative has established the standard mzQC file format for reporting and exchanging information relating to data quality. mzQC is based on the JavaScript Object Notation (JSON) format and provides a lightweight yet versatile file format that can be easily implemented in software. Here, we present open-source software libraries to process mzQC data in three programming languages: Python, using pymzqc; R, using rmzqc; and Java, using jmzqc. The libraries follow a common data model and provide shared functionalities, including the (de)serialization and validation of mzQC files. We demonstrate use of the software libraries in a workflow for extracting, analyzing, and visualizing QC metrics from different sources. Additionally, we show how these libraries can be integrated with each other, with existing software tools, and in automated workflows for the QC of mass spectrometry data. All software libraries are available as open source under the MS-Quality-Hub organization on GitHub (https://github.com/MS-Quality-Hub).