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Mian: interactive web-based microbiome data table visualization and machine learning platform.

Boyang Tom Jin1, Feng Xu2, Raymond T Ng3

  • 1Department of Computer Science, Stanford University, Stanford, CA, USA 94305.

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|November 17, 2021
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Summary
This summary is machine-generated.

Mian is a web application for analyzing microbial datasets. It offers tools for visualizing operational taxonomic unit (OTU) or amplicon sequence variant (ASV) data, identifying taxonomic groups, and exploring diversity trends.

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Area of Science:

  • Microbiology
  • Bioinformatics
  • Computational Biology

Background:

  • Microbial community analysis generates large datasets (OTU/ASV).
  • Exploring these datasets requires integrated visualization and statistical tools.
  • Identifying key taxonomic groups and diversity trends is crucial for understanding microbial ecology.

Purpose of the Study:

  • To present Mian, a web application for interactive analysis of microbial datasets.
  • To provide tools for visualization, statistical analysis, and machine learning on OTU/ASV data.
  • To facilitate data exploration and hypothesis generation in microbial research.

Main Methods:

  • Interactive visualization of OTU/ASV data.
  • Implementation of statistical tests (e.g., Fisher's exact test).
  • Application of machine learning models (e.g., Random Forest, Deep Neural Networks) for classification and feature selection (e.g., Boruta).
  • Calculation of alpha and beta diversity metrics.

Main Results:

  • Mian enables interactive exploration of microbial datasets.
  • The platform integrates diverse analytical tools for comprehensive data analysis.
  • Users can identify key taxonomic groups, diversity trends, and composition shifts.

Conclusions:

  • Mian provides a user-friendly, open-source platform for microbial data analysis.
  • The application supports hypothesis generation and open-ended data exploration.
  • Mian is freely available for researchers to analyze their microbial datasets.