Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

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

Εlizabeth J. Parker
* ,
Kathryn C. Billane
* ,
Nichola Austen
ORCID logo ,
Anne Cotton
,
Rachel M. George
,
David Hopkins
,
Janice A. Lake
,
James K. Pitman
,
James N. Prout
,
Heather J. Walker
ORCID logo ,
Alex Williams
,
Duncan D. Cameron
ORCID logo
Version 1 : Received: 1 February 2023 / Approved: 3 February 2023 / Online: 3 February 2023 (04:16:00 CET)

A peer-reviewed article of this Preprint also exists.

Parker, E.J.; Billane, K.C.; Austen, N.; Cotton, A.; George, R.M.; Hopkins, D.; Lake, J.A.; Pitman, J.K.; Prout, J.N.; Walker, H.J.; Williams, A.; Cameron, D.D. Untangling the Complexities of Processing and Analysis for Untargeted LC-MS Data Using Open-Source Tools. Metabolites 2023, 13, 463. Parker, E.J.; Billane, K.C.; Austen, N.; Cotton, A.; George, R.M.; Hopkins, D.; Lake, J.A.; Pitman, J.K.; Prout, J.N.; Walker, H.J.; Williams, A.; Cameron, D.D. Untangling the Complexities of Processing and Analysis for Untargeted LC-MS Data Using Open-Source Tools. Metabolites 2023, 13, 463.

Abstract

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 chro-matography (LC), but choosing the ‘correct’ pipeline isn’t straight-forward. This tutorial, in con-junction 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 explor-atory analysis in order to inform decision-making regarding costly and time-consuming down-stream 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.

Keywords

metabolomics; untargeted; mass-spectrometry; open-source; bioinformatics

Subject

Biology and Life Sciences, Biochemistry and Molecular Biology

Copyright: This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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