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MOCHI: a comprehensive cross-platform tool for amplicon-based microbiota analysis.

Jun-Jie Zheng1, Po-Wen Wang1, Tzu-Wen Huang2

  • 1Institute of Bioinformatics and Systems Biology, National Yang Ming Chiao Tung University, Hsinchu 30068, Taiwan.

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Summary

MOCHI is a new GUI tool simplifying microbiota amplicon sequencing analysis. It enables accurate taxa prediction and diversity analysis, making complex data accessible to more researchers.

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Area of Science:

  • Microbiology
  • Bioinformatics
  • Genomics

Background:

  • Microbiota analysis is crucial for health and scientific research.
  • 16S/18S rRNA gene sequencing is commonly used for taxa identification and diversity prediction.
  • Existing tools often require advanced programming and statistical expertise, limiting accessibility.

Purpose of the Study:

  • To develop an accessible tool for microbiota amplicon sequencing analysis.
  • To address the need for user-friendly software supporting long-read sequencing data.
  • To facilitate accurate taxa prediction and species diversity analysis.

Main Methods:

  • Developed MOCHI, a Graphical User Interface (GUI) tool.
  • MOCHI preprocesses sequences, assigns taxonomy, and predicts species diversity and function.
  • Accepts taxonomic count tables or FASTQ files for partial or full-length 16S/18S rRNA genes.

Main Results:

  • MOCHI provides real-time analysis and visualizes data in tabular and graphical formats.
  • The tool supports both local installation and web access.
  • Enables accurate taxa prediction and functional analysis from amplicon sequencing data.

Conclusions:

  • MOCHI democratizes microbiota analysis by offering an intuitive and powerful platform.
  • The tool enhances the accessibility of complex amplicon sequencing data analysis.
  • Facilitates broader research applications in microbiology and related fields.