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Metagenomic Analysis of Silage
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MetaComp: comprehensive analysis software for comparative meta-omics including comparative metagenomics.

Peng Zhai1, Longshu Yang1,2, Xiao Guo2

  • 1State Key Laboratory for Turbulence and Complex Systems, Department of Biomedical Engineering, College of Engineering, Peking University, Beijing, 100871, China.

BMC Bioinformatics
|October 4, 2017
PubMed
Summary

MetaComp software integrates multiple meta-omics data types for microbial community analysis. It reveals environmental influences on microbes using regression analysis and offers user-friendly statistical tools.

Keywords:
Comparative meta-omicsComparative metagenomicsGraphical user interfaceStatistical analysisVisualization

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Area of Science:

  • Microbiology
  • Bioinformatics
  • Computational Biology

Background:

  • High-throughput sequencing and mass spectrometry enable multi-omics analyses (metagenomics, metatranscriptomics, metaproteomics, metabolomics) of microbial communities.
  • Comparative analyses of these data are crucial for understanding microbial diversity and interactions with environmental conditions.
  • Identifying correlations between microbial features and environmental factors is key to deciphering microbial adaptation strategies.

Purpose of the Study:

  • To develop a comprehensive software tool, MetaComp, for integrated analysis and comparison of multi-omics data from microbial communities.
  • To introduce novel statistical approaches, including regression analysis, for exploring environmental influences on microbial communities.
  • To provide a user-friendly platform for researchers without extensive statistical expertise.

Main Methods:

  • Development of MetaComp, a graphical software integrating various statistical approaches for meta-omics data comparison.
  • Implementation of multivariate statistics, hypothesis testing (two-sample, multi-sample, two-group), and a novel regression analysis of environmental factors.
  • Automated selection of appropriate two-group sample tests based on input data characteristics.

Main Results:

  • MetaComp facilitates the comparison of metagenomics, metaproteomics, and metabolomics data.
  • The software performs regression analysis to distill the influence of the living environment on microbial communities.
  • An automatically selected two-group sample test was evaluated and demonstrated superior performance.

Conclusions:

  • MetaComp is an integrative software applicable to all meta-omics data, uniquely identifying environmental influences via regression analysis.
  • Its user-friendly design, including an optimized automated statistical test selection, addresses challenges in the big data era.
  • MetaComp is available for download, promoting advanced microbial community analysis.