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

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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 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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Parker, E. J., Billane, K. C., Austen, N., Cotton, A., George, R. M., Hopkins, D., … Cameron, D. D. (2023). Untangling the Complexities of Processing and Analysis for Untargeted LC-MS Data Using Open-Source Tools. Metabolites, 13(4). https://doi.org/10.3390/metabo13040463

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