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

研究成果: Article同行評審

摘要

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.

原文English
頁(從 - 到)4286-4292
頁數7
期刊Bioinformatics
38
發行號18
DOIs
出版狀態Published - 2022 9月 15

All Science Journal Classification (ASJC) codes

  • 統計與概率
  • 生物化學
  • 分子生物學
  • 電腦科學應用
  • 計算機理論與數學
  • 計算數學

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