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

Jun Jie Zheng, Po Wen Wang, Tzu Wen Huang, Yao Jong Yang, Hua Sheng Chiu, Pavel Sumazin, Ting Wen Chen

Research output: Contribution to journalArticlepeer-review

3 Citations (Scopus)

Abstract

MOTIVATION: Microbiota analyses have important implications for health and science. These analyses make use of 16S/18S rRNA gene sequencing to identify taxa and predict species diversity. However, most available tools for analyzing microbiota data require adept programming skills and in-depth statistical knowledge for proper implementation. While long-read amplicon sequencing can lead to more accurate taxa predictions and is quickly becoming more common, practitioners have no easily accessible tools with which to perform their analyses. RESULTS: We present MOCHI, a GUI tool for microbiota amplicon sequencing analysis. MOCHI preprocesses sequences, assigns taxonomy, identifies different abundant species and predicts species diversity and function. It takes either taxonomic count table or FASTQ of partial 16S/18S rRNA or full-length 16S rRNA gene as input. It performs analyses in real time and visualizes data in both tabular and graphical formats. AVAILABILITY AND IMPLEMENTATION: MOCHI can be installed to run locally or accessed as a web tool at https://mochi.life.nctu.edu.tw. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Original languageEnglish
Pages (from-to)4286-4292
Number of pages7
JournalBioinformatics (Oxford, England)
Volume38
Issue number18
DOIs
Publication statusPublished - Sept 15 2022

ASJC Scopus subject areas

  • Statistics and Probability
  • Biochemistry
  • Molecular Biology
  • Computer Science Applications
  • Computational Theory and Mathematics
  • Computational Mathematics

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