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COMAN: a web server for comprehensive metatranscriptomics analysis.

Yueqiong Ni1, Jun Li1, Gianni Panagiotou2

  • 1Systems Biology & Bioinformatics Group, School of Biological Sciences, The University of Hong Kong, Pokfulam Road, Hong Kong, Hong Kong.

BMC Genomics
|August 13, 2016
PubMed
Summary

Researchers can now easily analyze complex metatranscriptomic data with COMAN, a new web tool. This tool simplifies microbial ecology studies by providing comprehensive analysis and visualization of microbiota RNA-Seq data.

Keywords:
Computational biologyMetatranscriptomicsMicrobial RNA-SeqMicrobial communityWeb servers

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Area of Science:

  • Microbial ecology
  • Bioinformatics
  • Metagenomics
  • Metatranscriptomics

Background:

  • Metagenomic and metatranscriptomic sequencing have advanced the study of microbial ecology.
  • Analyzing large metatranscriptomic datasets requires significant computational power, bioinformatics tools, and programming skills.

Purpose of the Study:

  • To develop an automated, comprehensive web-based tool for metatranscriptomic data analysis.
  • To simplify the interpretation of microbiota RNA-Seq data for researchers with limited bioinformatics expertise.

Main Methods:

  • Developed COMAN (Comprehensive Metatranscriptomics Analysis), a web server.
  • Pipeline includes read quality control, non-coding RNA removal, functional annotation, comparative statistics, pathway enrichment, co-expression network analysis, and visualization.
  • Outputs data in tabular format for further analysis and integration.

Main Results:

  • COMAN provides automated, comprehensive functional analysis of metatranscriptomic data.
  • The tool translates raw reads into accessible data tables and high-quality figures.
  • A user-friendly interface with detailed instructions is available.

Conclusions:

  • COMAN is an integrated web server for functional analysis of metatranscriptomic data.
  • It aims to facilitate microbiota-related research for scientists lacking extensive bioinformatics expertise.
  • The tool enhances the accessibility and interpretation of microbiota RNA-Seq data.