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Related Experiment Video

Updated: Sep 11, 2025

Author Spotlight: Emerging Technologies and Advanced Tools for Decoding Metabolomics Data Analysis
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SpeSpeNet: an interactive and user-friendly tool to create and explore microbial correlation networks.

Abraham L van Eijnatten1, Luc van Zon1, Eleni Manousou1

  • 1Theoretical Biology and Bioinformatics, Science4Life, Utrecht University (UU), Padualaan 8, 3584 CH Utrecht, The Netherlands.

ISME Communications
|August 13, 2025
PubMed
Summary

SpeSpeNet is a user-friendly R-shiny tool for creating and visualizing microbiome correlation networks. It helps researchers understand microbial communities and their environmental drivers without coding skills.

Keywords:
interactive webtoolmicrobial ecologymicrobiomenetworksvisualization

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Area of Science:

  • Microbiology
  • Bioinformatics
  • Ecology

Background:

  • Correlation networks are vital for exploring microbiome data, with nodes representing taxa and edges indicating abundance correlations.
  • Co-abundance clusters in these networks often signify shared responses to environmental factors, aiding system understanding.
  • Existing tools for microbiome network analysis are often not user-friendly, require coding expertise, or lack customization and focus on environmental associations.

Purpose of the Study:

  • To introduce SpeSpeNet, a practical and user-friendly R-shiny tool for constructing and visualizing microbiome correlation networks.
  • To automate data preprocessing, network construction, and visualization, making it accessible to researchers without programming skills.
  • To enable the incorporation of environmental data for a more comprehensive analysis of microbiome structure and drivers.

Main Methods:

  • Developed SpeSpeNet, an R-shiny application for generating species-species correlation networks.
  • Automated key steps including data preprocessing, network construction, and visualization.
  • Integrated customizable options for incorporating user-provided environmental data to explore taxon-environment associations.

Main Results:

  • SpeSpeNet provides an automated and user-friendly platform for microbiome correlation network analysis.
  • The tool facilitates visualization of networks and allows for the integration of environmental drivers.
  • Demonstrated the utility of SpeSpeNet through three diverse case studies.

Conclusions:

  • SpeSpeNet offers a valuable, accessible tool for microbiome researchers to construct and visualize correlation networks.
  • The tool enhances the understanding of microbial community structure and its relationship with environmental factors.
  • SpeSpeNet's user-friendliness and customization options make it a significant advancement in microbiome data analysis.