Stephen A Brockman1, Eric V Roden1, Adrian D Hegeman2. 1. Microbial and Plant Genomics Institute and the Departments of Horticultural Science and Plant and Microbial Biology, University of Minnesota, Twin Cities, 1970 Folwell Avenue, St. Paul, MN, USA. 2. Microbial and Plant Genomics Institute and the Departments of Horticultural Science and Plant and Microbial Biology, University of Minnesota, Twin Cities, 1970 Folwell Avenue, St. Paul, MN, USA. hegem007@umn.edu.
Abstract
INTRODUCTION: Van Krevelen (VK) diagrams provide a promising but uncommon solution to a number of challenges associated with the visualization of metabolomics data. VK diagrams are created by plotting H:C ratios against O:C ratios of the compounds in a chemical mixture. OBJECTIVES: The aim of this manuscript is to present an open-source software tool and reference map that we have developed to make VK diagrams for visualization of metabolomics data. METHODS: Software was created with a prompt-driven command line user interface and was written using Python 2.7. We empirically derived an accompanying map by plotting where compounds from seven biomolecule types fall within the VK plot space. RESULTS: We've created an easy to use, open source software tool named OpenVanKrevelen for making a range of VK diagrams that is available on GitHub: https://github.com/HegemanLab/VanKrevelenLocal . The empirical mapping approach has produced several improvements from previously published maps. CONCLUSIONS: OpenVanKrevelen provides the metabolomics community with access to a new tool for visualization of complex metabolomics datasets.
INTRODUCTION: Van Krevelen (VK) diagrams provide a promising but uncommon solution to a number of challenges associated with the visualization of metabolomics data. VK diagrams are created by plotting H:C ratios against O:C ratios of the compounds in a chemical mixture. OBJECTIVES: The aim of this manuscript is to present an open-source software tool and reference map that we have developed to make VK diagrams for visualization of metabolomics data. METHODS: Software was created with a prompt-driven command line user interface and was written using Python 2.7. We empirically derived an accompanying map by plotting where compounds from seven biomolecule types fall within the VK plot space. RESULTS: We've created an easy to use, open source software tool named OpenVanKrevelen for making a range of VK diagrams that is available on GitHub: https://github.com/HegemanLab/VanKrevelenLocal . The empirical mapping approach has produced several improvements from previously published maps. CONCLUSIONS: OpenVanKrevelen provides the metabolomics community with access to a new tool for visualization of complex metabolomics datasets.
Entities:
Keywords:
Mass-spectrometry; Metabolomics; Van Krevelen
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