Metabolite AutoPlotter - an application to process and visualise metabolite data in the web browser

Pietzke, M. and Vazquez, A. (2020) Metabolite AutoPlotter - an application to process and visualise metabolite data in the web browser. Cancer and Metabolism, 8(1), 15. (doi: 10.1186/s40170-020-00220-x) (PMID:32670572) (PMCID:PMC7350678)

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Background: Metabolomics is gaining popularity as a standard tool for the investigation of biological systems. Yet, parsing metabolomics data in the absence of in-house computational scientists can be overwhelming and time-consuming. As a consequence of manual data processing, the results are often not analysed in full depth, so potential novel findings might get lost. Methods: To tackle this problem, we developed Metabolite AutoPlotter, a tool to process and visualise quantified metabolite data. Other than with bulk data visualisations, such as heat maps, the aim of the tool is to generate single plots for each metabolite. For this purpose, it reads as input pre-processed metabolite-intensity tables and accepts different experimental designs, with respect to the number of metabolites, conditions and replicates. The code was written in the R-scripting language and wrapped into a shiny application that can be run online in a web browser on Results: We demonstrate the main features and the ease of use with two different metabolite datasets, for quantitative experiments and for stable isotope tracing experiments. We show how the plots generated by the tool can be interactively modified with respect to plot type, colours, text labels and the shown statistics. We also demonstrate the application towards 13C-tracing experiments and the seamless integration of natural abundance correction, which facilitates the better interpretation of stable isotope tracing experiments. The output of the tool is a zip-file containing one single plot for each metabolite as well as restructured tables that can be used for further analysis. Conclusion: With the help of Metabolite AutoPlotter, it is now possible to simplify data processing and visualisation for a wide audience. High-quality plots from complex data can be generated in a short time by pressing a few buttons. This offers dramatic improvements over manual analysis. It is significantly faster and allows researchers to spend more time interpreting the results or to perform follow-up experiments. Further, this eliminates potential copy-and-paste errors or tedious repetitions when things need to be changed. We are sure that this tool will help to improve and speed up scientific discoveries.

Item Type:Articles
Additional Information:This work was supported by the Cancer Research UK C596/A21140. We acknowledge the Cancer Research UK Glasgow Centre (C596/A18076). MP is currently funded by a grant from the Helmholtz program “Aging and Metabolic Programming” (AMPro).
Keywords:Methodology, Metabolites, Metabolomics, Processing, Visualisation, Graphs, Plots, Automatic
Glasgow Author(s) Enlighten ID:Vazquez, Alexei
Authors: Pietzke, M., and Vazquez, A.
College/School:College of Medical Veterinary and Life Sciences > Institute of Cancer Sciences
Journal Name:Cancer and Metabolism
Publisher:BioMed Central
ISSN (Online):2049-3002
Copyright Holders:Copyright © 2020 The Author(s)
First Published:First published in Cancer and Metabolism 8:15
Publisher Policy:Reproduced under a Creative Commons License

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Project CodeAward NoProject NamePrincipal InvestigatorFunder's NameFunder RefLead Dept
190874CR-UK Centre renewalKaren VousdenNot Applicable (NA)C596/A18076Institute of Cancer Sciences