Accessible and reproducible mass spectrometry imaging data analysis in Galaxy

Abstract: Background
Mass spectrometry imaging is increasingly used in biological and translational research because it has the ability to determine the spatial distribution of hundreds of analytes in a sample. Being at the interface of proteomics/metabolomics and imaging, the acquired datasets are large and complex and often analyzed with proprietary software or in-house scripts, which hinders reproducibility. Open source software solutions that enable reproducible data analysis often require programming skills and are therefore not accessible to many mass spectrometry imaging (MSI) researchers.

Findings
We have integrated 18 dedicated mass spectrometry imaging tools into the Galaxy framework to allow accessible, reproducible, and transparent data analysis. Our tools are based on Cardinal, MALDIquant, and scikit-image and enable all major MSI analysis steps such as quality control, visualization, preprocessing, statistical analysis, and image co-registration. Furthermore, we created hands-on training material for use cases in proteomics and metabolomics. To demonstrate the utility of our tools, we re-analyzed a publicly available N-linked glycan imaging dataset. By providing the entire analysis history online, we highlight how the Galaxy framework fosters transparent and reproducible research.

Conclusion
The Galaxy framework has emerged as a powerful analysis platform for the analysis of MSI data with ease of use and access, together with high levels of reproducibility and transparency

Location
Deutsche Nationalbibliothek Frankfurt am Main
Extent
Online-Ressource
Language
Englisch
Notes
GigaScience. - 8, 12 (2019) , giz143, ISSN: 2047-217X

Keyword
Massenspektrometrie
MALDI-MS
Proteomanalyse
Metabolomik

Event
Veröffentlichung
(where)
Freiburg
(who)
Universität
(when)
2020

DOI
10.1093/gigascience/giz143
URN
urn:nbn:de:bsz:25-freidok-1517194
Rights
Der Zugriff auf das Objekt ist unbeschränkt möglich.
Last update
25.03.2025, 1:46 PM CET

Data provider

This object is provided by:
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Time of origin

  • 2020

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