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Weidner, L. ; Hemmler, D. ; Rychlik, M.* ; Schmitt-Kopplin, P.

DBDIpy: A Python library for processing of untargeted datasets from real-time plasma ionization mass spectrometry.

Bioinformatics 39:2 (2023)
Verlagsversion DOI PMC
Creative Commons Lizenzvertrag
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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Publikationstyp Artikel: Journalartikel
Dokumenttyp Wissenschaftlicher Artikel
Korrespondenzautor
ISSN (print) / ISBN 1367-4803
Zeitschrift Bioinformatics
Quellenangaben Band: 39, Heft: 2 Seiten: , Artikelnummer: 2 Supplement: ,
Verlag Oxford University Press
Verlagsort Oxford
Nichtpatentliteratur Publikationen
Begutachtungsstatus Peer reviewed
Institut(e) Research Unit Analytical BioGeoChemistry (BGC)
Förderungen Bavarian Ministry of Economic Affairs, Regional Development and Energy