Van Krevelen diagram visualization of high resolution-mass spectrometry metabolomics data with OpenVanKrevelen

Stephen A. Brockman; Eric V. Roden; Adrian D. Hegeman

doi:10.1007/s11306-018-1343-y

Van Krevelen diagram visualization of high resolution-mass spectrometry metabolomics data with OpenVanKrevelen

Stephen A. Brockman, Eric V. Roden, Adrian D. Hegeman

Horticultural Science

Research output: Contribution to journal › Article › peer-review

29 Scopus citations

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.

Original language	English (US)
Article number	48
Journal	Metabolomics
Volume	14
Issue number	4
DOIs	https://doi.org/10.1007/s11306-018-1343-y
State	Published - Apr 1 2018

Bibliographical note

Funding Information:
Acknowledgements The authors thank Dana M. Freund, Kate A. Sam-mons, Katrina Freund Saxhaug, Nadia R. Handler and Jayanti Suresh for helpful feedback and/or advice on ease of use. We also thank Geoffrey A. Dubrow for providing test data, and the Biological Magnetic Resonance Bank for providing the database and useful feedback. We are grateful for funding provided by the National Science Foundation Plant Genome Research Program Grants IOS-0923960 and IOS-1238812 and National Science Foundation grant DBI-1458524. We thank the Minnesota Agriculture Experiment Station and the University of Minnesota, College of Food, Agricultural and Natural Resource Sciences at the University of Minnesota–Twin Cites for support.

Funding Information:
The authors thank Dana M. Freund, Kate A. Sammons, Katrina Freund Saxhaug, Nadia R. Handler and Jayanti Suresh for helpful feedback and/or advice on ease of use. We also thank Geoffrey A. Dubrow for providing test data, and the Biological Magnetic Resonance Bank for providing the database and useful feedback. We are grateful for funding provided by the National Science Foundation Plant Genome Research Program Grants IOS-0923960 and IOS-1238812 and National Science Foundation grant DBI-1458524. We thank the Minnesota Agriculture Experiment Station and the University of Minnesota, College of Food, Agricultural and Natural Resource Sciences at the University of Minnesota–Twin Cites for support.

Publisher Copyright:
© 2018, Springer Science+Business Media, LLC, part of Springer Nature.

Keywords

Mass-spectrometry
Metabolomics
Van Krevelen

Publisher link

10.1007/s11306-018-1343-y

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@article{78265bf4696c478083ea93721d1280a5,

title = "Van Krevelen diagram visualization of high resolution-mass spectrometry metabolomics data with OpenVanKrevelen",

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{\textquoteright}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.",

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author = "Brockman, {Stephen A.} and Roden, {Eric V.} and Hegeman, {Adrian D.}",

note = "Funding Information: Acknowledgements The authors thank Dana M. Freund, Kate A. Sam-mons, Katrina Freund Saxhaug, Nadia R. Handler and Jayanti Suresh for helpful feedback and/or advice on ease of use. We also thank Geoffrey A. Dubrow for providing test data, and the Biological Magnetic Resonance Bank for providing the database and useful feedback. We are grateful for funding provided by the National Science Foundation Plant Genome Research Program Grants IOS-0923960 and IOS-1238812 and National Science Foundation grant DBI-1458524. We thank the Minnesota Agriculture Experiment Station and the University of Minnesota, College of Food, Agricultural and Natural Resource Sciences at the University of Minnesota–Twin Cites for support. Funding Information: The authors thank Dana M. Freund, Kate A. Sammons, Katrina Freund Saxhaug, Nadia R. Handler and Jayanti Suresh for helpful feedback and/or advice on ease of use. We also thank Geoffrey A. Dubrow for providing test data, and the Biological Magnetic Resonance Bank for providing the database and useful feedback. We are grateful for funding provided by the National Science Foundation Plant Genome Research Program Grants IOS-0923960 and IOS-1238812 and National Science Foundation grant DBI-1458524. We thank the Minnesota Agriculture Experiment Station and the University of Minnesota, College of Food, Agricultural and Natural Resource Sciences at the University of Minnesota–Twin Cites for support. Publisher Copyright: {\textcopyright} 2018, Springer Science+Business Media, LLC, part of Springer Nature.",

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doi = "10.1007/s11306-018-1343-y",

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N2 - 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.

AB - 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.

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ER -

Van Krevelen diagram visualization of high resolution-mass spectrometry metabolomics data with OpenVanKrevelen

Abstract

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