Statistical analysis of feature-based molecular networking results from non-targeted metabolomics data

Abzer K Pakkir Shah^{1

2}, Axel Walter^{1

2

3}, Filip Ottosson⁴, Francesco Russo⁴, Marcelo Navarro-Diaz², Judith Boldt^{1

5

6}, Jarmo-Charles J Kalinski^{1

7}, Eftychia Eva Kontou^{1

8}, James Elofson⁹, Alexandros Polyzois^{1

10}, Carolina González-Marín^{1

11}, Shane Farrell^{12

13}, Marie R Aggerbeck^{1

14}, Thapanee Pruksatrakul^{1

15}, Nathan Chan¹⁶, Yunshu Wang¹⁶, Magdalena Pöchhacker^{1

17}, Corinna Brungs¹⁸, Beatriz Cámara¹⁹, Andrés Mauricio Caraballo-Rodríguez²⁰, Andres Cumsille¹⁹, Fernanda de Oliveira^{20

21}, Kai Dührkop²², Yasin El Abiead²⁰, Christian Geibel², Lana G Graves^{23

24}, Martin Hansen¹⁴, Steffen Heuckeroth²⁵, Simon Knoblauch², Anastasiia Kostenko⁹, Mirte C M Kuijpers²⁶, Kevin Mildau^{1

27

28}, Stilianos Papadopoulos Lambidis², Paulo Wender Portal Gomes²⁰, Tilman Schramm^{2

29}, Karoline Steuer-Lodd^{2

29}, Paolo Stincone², Sibgha Tayyab², Giovanni Andrea Vitale², Berenike C Wagner², Shipei Xing²⁰, Marquis T Yazzie⁹, Simone Zuffa^{20

30}, Martinus de Kruijff³¹, Christine Beemelmanns^{31

32}, Hannes Link², Christoph Mayer², Justin J J van der Hooft^{1

28

33}, Tito Damiani¹⁸, Tomáš Pluskal¹⁸, Pieter Dorrestein²⁰, Jan Stanstrup³⁴, Robin Schmid^{1

18}, Mingxun Wang^{1

16}, Allegra Aron^{1

9}, Madeleine Ernst³⁵, Daniel Petras^{36

37

38}

Affiliations

¹ Virtual Multi-Omics Laboratory, The Internet, Riverside, CA, USA.
² University of Tübingen, Interfaculty Institute of Microbiology and Infection Medicine, Tübingen, Germany.
³ Applied Bioinformatics, Department of Computer Science, University of Tübingen, Tübingen, Germany.
⁴ Section for Clinical Mass Spectrometry, Danish Center for Neonatal Screening, Department of Congenital Disorders, Statens Serum Institut, Copenhagen S, Denmark.
⁵ Leibniz Institute DSMZ-German Collection of Microorganisms and Cell Cultures, Braunschweig, Germany.
⁶ German Center for Infection Research, Partner Site Braunschweig-Hannover, Braunschweig, Germany.
⁷ Department of Biochemistry and Microbiology, Rhodes University, Makhanda, South Africa.
⁸ The Novo Nordisk Foundation for Biosustainability, Technical University of Denmark, Kongens Lyngby, Denmark.
⁹ Department of Chemistry and Biochemistry, University of Denver, Denver, CO, USA.
¹⁰ Boyce Thompson Institute and Department of Chemistry and Chemical Biology, Cornell University, Ithaca, NY, USA.
¹¹ Universidad EAFIT, Medellín, Antioquia, Colombia.
¹² Bigelow Laboratory for Ocean Sciences, East Boothbay, ME, USA.
¹³ School of Marine Sciences, Darling Marine Center, University of Maine, Walpole, ME, USA.
¹⁴ Department of Environmental Science, Aarhus University, Roskilde, Denmark.
¹⁵ National Center for Genetic Engineering and Biotechnology, National Science and Technology Development Agency, Thailand Science Park, Pathum Thani, Thailand.
¹⁶ Department of Computer Science, University of California Riverside, Riverside, CA, USA.
¹⁷ Department of Food Chemistry and Toxicology, University of Vienna, Vienna, Austria.
¹⁸ Institute of Organic Chemistry and Biochemistry of the Czech Academy of Sciences, Prague, Czech Republic.
¹⁹ Laboratorio de Microbiología Molecular y Biotecnología Ambiental, Centro de Biotecnología DAL, Universidad Técnica Federico Santa María, Valparaíso, Chile.
²⁰ Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, San Diego, CA, USA.
²¹ Department of Biotechnology, Engineering School of Lorena, University of São Paulo, Lorena, São Paulo, Brazil.
²² Department of Bioinformatics, University of Jena, Jena, Germany.
²³ Department of Environmental Systems Analysis, University of Tübingen, Tübingen, Germany.
²⁴ Leibniz Institute of Freshwater Ecology and Inland Fisheries, Berlin, Germany.
²⁵ Institute of Inorganic and Analytical Chemistry, University of Münster, Münster, Germany.
²⁶ Department of Ecology, Behavior and Evolution, University of California San Diego, San Diego, CA, USA.
²⁷ Department of Analytical Chemistry, University of Vienna, Vienna, Austria.
²⁸ Bioinformatics Group, Wageningen University and Research, Wageningen, the Netherlands.
²⁹ Department of Biochemistry, University of California Riverside, Riverside, CA, USA.
³⁰ Collaborative Mass Spectrometry Innovation Center, Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, San Diego, CA, USA.
³¹ Helmholtz Institute for Pharmaceutical Research Saarland, Helmholtz Centre for Infection Research, Saarbrücken, Germany.
³² Saarland University, Saarbrücken, Germany.
³³ Department of Biochemistry, University of Johannesburg, Johannesburg, South Africa.
³⁴ Department of Nutrition, Exercise and Sports, University of Copenhagen, Frederiksberg C, Denmark.
³⁵ Section for Clinical Mass Spectrometry, Danish Center for Neonatal Screening, Department of Congenital Disorders, Statens Serum Institut, Copenhagen S, Denmark. MAET@ssi.dk.
³⁶ Virtual Multi-Omics Laboratory, The Internet, Riverside, CA, USA. dpetras@ucr.edu.
³⁷ University of Tübingen, Interfaculty Institute of Microbiology and Infection Medicine, Tübingen, Germany. dpetras@ucr.edu.
³⁸ Department of Biochemistry, University of California Riverside, Riverside, CA, USA. dpetras@ucr.edu.

PMID: 39304763
DOI: 10.1038/s41596-024-01046-3

Statistical analysis of feature-based molecular networking results from non-targeted metabolomics data

Abzer K Pakkir Shah et al. Nat Protoc. 2025 Jan.

. 2025 Jan;20(1):92-162.

doi: 10.1038/s41596-024-01046-3. Epub 2024 Sep 20.

Authors

Affiliations

¹ Virtual Multi-Omics Laboratory, The Internet, Riverside, CA, USA.
² University of Tübingen, Interfaculty Institute of Microbiology and Infection Medicine, Tübingen, Germany.
³ Applied Bioinformatics, Department of Computer Science, University of Tübingen, Tübingen, Germany.
⁴ Section for Clinical Mass Spectrometry, Danish Center for Neonatal Screening, Department of Congenital Disorders, Statens Serum Institut, Copenhagen S, Denmark.
⁵ Leibniz Institute DSMZ-German Collection of Microorganisms and Cell Cultures, Braunschweig, Germany.
⁶ German Center for Infection Research, Partner Site Braunschweig-Hannover, Braunschweig, Germany.
⁷ Department of Biochemistry and Microbiology, Rhodes University, Makhanda, South Africa.
⁸ The Novo Nordisk Foundation for Biosustainability, Technical University of Denmark, Kongens Lyngby, Denmark.
⁹ Department of Chemistry and Biochemistry, University of Denver, Denver, CO, USA.
¹⁰ Boyce Thompson Institute and Department of Chemistry and Chemical Biology, Cornell University, Ithaca, NY, USA.
¹¹ Universidad EAFIT, Medellín, Antioquia, Colombia.
¹² Bigelow Laboratory for Ocean Sciences, East Boothbay, ME, USA.
¹³ School of Marine Sciences, Darling Marine Center, University of Maine, Walpole, ME, USA.
¹⁴ Department of Environmental Science, Aarhus University, Roskilde, Denmark.
¹⁵ National Center for Genetic Engineering and Biotechnology, National Science and Technology Development Agency, Thailand Science Park, Pathum Thani, Thailand.
¹⁶ Department of Computer Science, University of California Riverside, Riverside, CA, USA.
¹⁷ Department of Food Chemistry and Toxicology, University of Vienna, Vienna, Austria.
¹⁸ Institute of Organic Chemistry and Biochemistry of the Czech Academy of Sciences, Prague, Czech Republic.
¹⁹ Laboratorio de Microbiología Molecular y Biotecnología Ambiental, Centro de Biotecnología DAL, Universidad Técnica Federico Santa María, Valparaíso, Chile.
²⁰ Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, San Diego, CA, USA.
²¹ Department of Biotechnology, Engineering School of Lorena, University of São Paulo, Lorena, São Paulo, Brazil.
²² Department of Bioinformatics, University of Jena, Jena, Germany.
²³ Department of Environmental Systems Analysis, University of Tübingen, Tübingen, Germany.
²⁴ Leibniz Institute of Freshwater Ecology and Inland Fisheries, Berlin, Germany.
²⁵ Institute of Inorganic and Analytical Chemistry, University of Münster, Münster, Germany.
²⁶ Department of Ecology, Behavior and Evolution, University of California San Diego, San Diego, CA, USA.
²⁷ Department of Analytical Chemistry, University of Vienna, Vienna, Austria.
²⁸ Bioinformatics Group, Wageningen University and Research, Wageningen, the Netherlands.
²⁹ Department of Biochemistry, University of California Riverside, Riverside, CA, USA.
³⁰ Collaborative Mass Spectrometry Innovation Center, Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, San Diego, CA, USA.
³¹ Helmholtz Institute for Pharmaceutical Research Saarland, Helmholtz Centre for Infection Research, Saarbrücken, Germany.
³² Saarland University, Saarbrücken, Germany.
³³ Department of Biochemistry, University of Johannesburg, Johannesburg, South Africa.
³⁴ Department of Nutrition, Exercise and Sports, University of Copenhagen, Frederiksberg C, Denmark.
³⁵ Section for Clinical Mass Spectrometry, Danish Center for Neonatal Screening, Department of Congenital Disorders, Statens Serum Institut, Copenhagen S, Denmark. MAET@ssi.dk.
³⁶ Virtual Multi-Omics Laboratory, The Internet, Riverside, CA, USA. dpetras@ucr.edu.
³⁷ University of Tübingen, Interfaculty Institute of Microbiology and Infection Medicine, Tübingen, Germany. dpetras@ucr.edu.
³⁸ Department of Biochemistry, University of California Riverside, Riverside, CA, USA. dpetras@ucr.edu.

PMID: 39304763
DOI: 10.1038/s41596-024-01046-3

Abstract

Feature-based molecular networking (FBMN) is a popular analysis approach for liquid chromatography-tandem mass spectrometry-based non-targeted metabolomics data. While processing liquid chromatography-tandem mass spectrometry data through FBMN is fairly streamlined, downstream data handling and statistical interrogation are often a key bottleneck. Especially users new to statistical analysis struggle to effectively handle and analyze complex data matrices. Here we provide a comprehensive guide for the statistical analysis of FBMN results, focusing on the downstream analysis of the FBMN output table. We explain the data structure and principles of data cleanup and normalization, as well as uni- and multivariate statistical analysis of FBMN results. We provide explanations and code in two scripting languages (R and Python) as well as the QIIME2 framework for all protocol steps, from data clean-up to statistical analysis. All code is shared in the form of Jupyter Notebooks ( https://github.com/Functional-Metabolomics-Lab/FBMN-STATS ). Additionally, the protocol is accompanied by a web application with a graphical user interface ( https://fbmn-statsguide.gnps2.org/ ) to lower the barrier of entry for new users and for educational purposes. Finally, we also show users how to integrate their statistical results into the molecular network using the Cytoscape visualization tool. Throughout the protocol, we use a previously published environmental metabolomics dataset for demonstration purposes. Together, the protocol, code and web application provide a complete guide and toolbox for FBMN data integration, cleanup and advanced statistical analysis, enabling new users to uncover molecular insights from their non-targeted metabolomics data. Our protocol is tailored for the seamless analysis of FBMN results from Global Natural Products Social Molecular Networking and can be easily adapted to other mass spectrometry feature detection, annotation and networking tools.

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Conflict of interest statement

Competing interests: J.J.J.v.d.H. is currently a member of the Scientific Advisory Board of Naicons Srl., Milano, Italy, and is consulting for Corteva Agriscience. P.C.D. is a scientific advisor and holds equity to Cybele and a cofounder, advisor, and holds equity in Ometa, Arome and Enveda with prior approval by UC-San Diego and consulted in 2023 for DSM animal health. M.W. is the founder of Ometa Labs. S.H., T.P. and R.S. are cofounders of mzio GmbH.

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Statistical analysis of feature-based molecular networking results from non-targeted metabolomics data

Affiliations

Statistical analysis of feature-based molecular networking results from non-targeted metabolomics data

Authors

Affiliations

Abstract

Conflict of interest statement

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