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DBDIpy: A Python library for processing of untargeted datasets from real-time plasma ionization mass spectrometry.
Bioinformatics 39:2 (2023)
MOTIVATION: Plasma ionization is rapidly gaining popularity for mass spectrometry (MS)-based studies of volatiles and aerosols. However, data from plasma ionization are delicate to interpret as competing ionization pathways in the plasma create numerous ion species. There is no tool for detection of adducts and in-source fragments from plasma ionization data yet, which makes data evaluation ambiguous. SUMMARY: We developed DBDIpy, a Python library for processing and formal analysis of untargeted, time-sensitive plasma ionization MS datasets. Its core functionality lies in the identification of in-source fragments and identification of rivaling ionization pathways of the same analytes in time-sensitive datasets. It further contains elementary functions for processing of untargeted metabolomics data and interfaces to an established ecosystem for analysis of MS data in Python. AVAILABILITY AND IMPLEMENTATION: DBDIpy is implemented in Python (Version ≥ 3.7) and can be downloaded from PyPI the Python package repository (https://pypi.org/project/DBDIpy) or from GitHub (https://github.com/leopold-weidner/DBDIpy). SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
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Publication type
Article: Journal article
Document type
Scientific Article
ISSN (print) / ISBN
1367-4803
Journal
Bioinformatics
Quellenangaben
Volume: 39,
Issue: 2
Article Number: 2
Publisher
Oxford University Press
Publishing Place
Oxford
Non-patent literature
Publications
Reviewing status
Peer reviewed
Institute(s)
Research Unit Analytical BioGeoChemistry (BGC)
Grants
Bavarian Ministry of Economic Affairs, Regional Development and Energy