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Untangling the Complexities of Processing and Analysis for Untargeted LC-MS Data Using Open-Source Tools

Untargeted metabolomics is a powerful tool for measuring and understanding complex biological chemistries. However, employment, bioinformatics and downstream analysis of mass spectrometry (MS) data can be daunting for inexperienced users. Numerous open-source and free-to-use data processing and anal...

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Autores principales: Parker, Elizabeth J., Billane, Kathryn C., Austen, Nichola, Cotton, Anne, George, Rachel M., Hopkins, David, Lake, Janice A., Pitman, James K., Prout, James N., Walker, Heather J., Williams, Alex, Cameron, Duncan D.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10142740/
https://www.ncbi.nlm.nih.gov/pubmed/37110122
http://dx.doi.org/10.3390/metabo13040463
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author Parker, Elizabeth J.
Billane, Kathryn C.
Austen, Nichola
Cotton, Anne
George, Rachel M.
Hopkins, David
Lake, Janice A.
Pitman, James K.
Prout, James N.
Walker, Heather J.
Williams, Alex
Cameron, Duncan D.
author_facet Parker, Elizabeth J.
Billane, Kathryn C.
Austen, Nichola
Cotton, Anne
George, Rachel M.
Hopkins, David
Lake, Janice A.
Pitman, James K.
Prout, James N.
Walker, Heather J.
Williams, Alex
Cameron, Duncan D.
author_sort Parker, Elizabeth J.
collection PubMed
description Untargeted metabolomics is a powerful tool for measuring and understanding complex biological chemistries. However, employment, bioinformatics and downstream analysis of mass spectrometry (MS) data can be daunting for inexperienced users. Numerous open-source and free-to-use data processing and analysis tools exist for various untargeted MS approaches, including liquid chromatography (LC), but choosing the ‘correct’ pipeline isn’t straight-forward. This tutorial, in conjunction with a user-friendly online guide presents a workflow for connecting these tools to process, analyse and annotate various untargeted MS datasets. The workflow is intended to guide exploratory analysis in order to inform decision-making regarding costly and time-consuming downstream targeted MS approaches. We provide practical advice concerning experimental design, organisation of data and downstream analysis, and offer details on sharing and storing valuable MS data for posterity. The workflow is editable and modular, allowing flexibility for updated/changing methodologies and increased clarity and detail as user participation becomes more common. Hence, the authors welcome contributions and improvements to the workflow via the online repository. We believe that this workflow will streamline and condense complex mass-spectrometry approaches into easier, more manageable, analyses thereby generating opportunities for researchers previously discouraged by inaccessible and overly complicated software.
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spelling pubmed-101427402023-04-29 Untangling the Complexities of Processing and Analysis for Untargeted LC-MS Data Using Open-Source Tools Parker, Elizabeth J. Billane, Kathryn C. Austen, Nichola Cotton, Anne George, Rachel M. Hopkins, David Lake, Janice A. Pitman, James K. Prout, James N. Walker, Heather J. Williams, Alex Cameron, Duncan D. Metabolites Article Untargeted metabolomics is a powerful tool for measuring and understanding complex biological chemistries. However, employment, bioinformatics and downstream analysis of mass spectrometry (MS) data can be daunting for inexperienced users. Numerous open-source and free-to-use data processing and analysis tools exist for various untargeted MS approaches, including liquid chromatography (LC), but choosing the ‘correct’ pipeline isn’t straight-forward. This tutorial, in conjunction with a user-friendly online guide presents a workflow for connecting these tools to process, analyse and annotate various untargeted MS datasets. The workflow is intended to guide exploratory analysis in order to inform decision-making regarding costly and time-consuming downstream targeted MS approaches. We provide practical advice concerning experimental design, organisation of data and downstream analysis, and offer details on sharing and storing valuable MS data for posterity. The workflow is editable and modular, allowing flexibility for updated/changing methodologies and increased clarity and detail as user participation becomes more common. Hence, the authors welcome contributions and improvements to the workflow via the online repository. We believe that this workflow will streamline and condense complex mass-spectrometry approaches into easier, more manageable, analyses thereby generating opportunities for researchers previously discouraged by inaccessible and overly complicated software. MDPI 2023-03-23 /pmc/articles/PMC10142740/ /pubmed/37110122 http://dx.doi.org/10.3390/metabo13040463 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Parker, Elizabeth J.
Billane, Kathryn C.
Austen, Nichola
Cotton, Anne
George, Rachel M.
Hopkins, David
Lake, Janice A.
Pitman, James K.
Prout, James N.
Walker, Heather J.
Williams, Alex
Cameron, Duncan D.
Untangling the Complexities of Processing and Analysis for Untargeted LC-MS Data Using Open-Source Tools
title Untangling the Complexities of Processing and Analysis for Untargeted LC-MS Data Using Open-Source Tools
title_full Untangling the Complexities of Processing and Analysis for Untargeted LC-MS Data Using Open-Source Tools
title_fullStr Untangling the Complexities of Processing and Analysis for Untargeted LC-MS Data Using Open-Source Tools
title_full_unstemmed Untangling the Complexities of Processing and Analysis for Untargeted LC-MS Data Using Open-Source Tools
title_short Untangling the Complexities of Processing and Analysis for Untargeted LC-MS Data Using Open-Source Tools
title_sort untangling the complexities of processing and analysis for untargeted lc-ms data using open-source tools
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10142740/
https://www.ncbi.nlm.nih.gov/pubmed/37110122
http://dx.doi.org/10.3390/metabo13040463
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