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CorrectOverloadedPeaks (R package to correct APCI-HR-MS peak data)

  • Metabolomics, the analysis of potentially all small molecules within a biological system, has become a valuable tool for biomarker identification and the elucidation of biological processes. While metabolites are often present in complex mixtures at extremely different concentrations, the dynamic range of available analytical methods to capture this variance is generally limited. Here, we show that gas chromatography coupled to atmospheric pressure chemical ionization mass spectrometry (GC-APCI-MS), a state of the art analytical technology applied in metabolomics analyses, shows an average linear range (LR) of 2.39 orders of magnitude for a set of 62 metabolites from a representative compound mixture. We further developed a computational tool to extend this dynamic range on average by more than 1 order of magnitude, demonstrated with a dilution series of the compound mixture, using robust and automatic reconstruction of intensity values exceeding the detection limit. The tool is freelyMetabolomics, the analysis of potentially all small molecules within a biological system, has become a valuable tool for biomarker identification and the elucidation of biological processes. While metabolites are often present in complex mixtures at extremely different concentrations, the dynamic range of available analytical methods to capture this variance is generally limited. Here, we show that gas chromatography coupled to atmospheric pressure chemical ionization mass spectrometry (GC-APCI-MS), a state of the art analytical technology applied in metabolomics analyses, shows an average linear range (LR) of 2.39 orders of magnitude for a set of 62 metabolites from a representative compound mixture. We further developed a computational tool to extend this dynamic range on average by more than 1 order of magnitude, demonstrated with a dilution series of the compound mixture, using robust and automatic reconstruction of intensity values exceeding the detection limit. The tool is freely available as an R package (CorrectOverloadedPeaks) from CRAN (https://cran.r-project.org/) and can be incorporated in a metabolomics data processing pipeline facilitating large screening assays.zeige mehrzeige weniger

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Autor*innen:Jan LisecORCiD
Dokumenttyp:Forschungsdatensatz
Veröffentlichungsform:Graue Literatur
Sprache:Englisch
Jahr der Erstveröffentlichung:2019
Organisationseinheit der BAM:1 Analytische Chemie; Referenzmaterialien
1 Analytische Chemie; Referenzmaterialien / 1.7 Organische Spuren- und Lebensmittelanalytik
Herausgeber (Institution):Bundesanstalt für Materialforschung und -prüfung (BAM)
Verlag:GitHub
Verlagsort:San Francisco, CA, USA
DDC-Klassifikation:Naturwissenschaften und Mathematik / Chemie / Analytische Chemie
Freie Schlagwörter:Data processing; Metabolomics; R package; Software
Themenfelder/Aktivitätsfelder der BAM:Chemie und Prozesstechnik
Art der Ressource:Software
URL:https://github.com/cran/CorrectOverloadedPeaks/
Zugehöriger Identifikator:https://pubs.acs.org/doi/full/10.1021/acs.analchem.6b02515
Verfügbarkeit des Dokuments:Datei für die Öffentlichkeit verfügbar ("Open Access")
Lizenz (Deutsch):License LogoCreative Commons - CC BY - Namensnennung 4.0 International
Datum der Freischaltung:06.07.2023
Referierte Publikation:Nein
Schriftenreihen ohne Nummerierung:Forschungsdatensätze der BAM
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