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MiCoDe: a web tool for performing microbiome community detection using a Bayesian weighted stochastic block model.

Kevin C Lutz1, Shengjie Yang1, Tejasv Bedi2

  • 1Department of Health Data Science and Biostatistics, O'Donnell School of Public Health, The University of Texas Southwestern Medical Center, Dallas, TX 75390, United States.

Bioinformatics (Oxford, England)
|July 1, 2025
PubMed
Summary
This summary is machine-generated.

The Microbiome Community Detector (MiCoDe) is a free, user-friendly web tool for clustering microbial taxa into communities. It addresses challenges in high-throughput sequencing data, offering a valuable solution for microbiome community detection.

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Area of Science:

  • Microbiology
  • Bioinformatics
  • Computational Biology

Background:

  • High-throughput sequencing generates complex microbiome data.
  • Analyzing microbiome data presents challenges like high-dimensionality and compositionality.
  • Identifying distinct microbial communities is crucial for understanding ecological roles.

Purpose of the Study:

  • To introduce the Microbiome Community Detector (MiCoDe) software.
  • To provide a user-friendly tool for microbial community detection.
  • To address common challenges in microbiome data analysis.

Main Methods:

  • MiCoDe employs a Bayesian weighted stochastic block model for network clustering.
  • The software automatically filters data, handling high-dimensionality, compositionality, zero inflation, and nonlinearity.
  • Users upload taxonomic abundance data and select analysis parameters via a web interface.

Main Results:

  • MiCoDe successfully clusters microbial taxa into distinct communities.
  • The tool automates data filtering and accounts for sequencing data complexities.
  • MiCoDe provides a rigorous yet accessible method for microbiome analysis.

Conclusions:

  • MiCoDe is a free, user-friendly web tool for microbiome community detection.
  • The software simplifies complex analyses using an unsupervised learning model.
  • MiCoDe is a valuable resource for researchers studying microbial communities.