omu, a Metabolomics Count Data Analysis Tool for Intuitive Figures and Convenient Metadata Collection

Area of Science:

• Microbiology
• Metabolomics
• Bioinformatics

Background:

• Metabolomics offers insights into microbial functional output.
• Limited established workflows exist for post-metabolite identification analysis.
• Linking identified metabolites to specific microbial genes and enzymes is challenging.

Purpose of the Study:

• To introduce omu, a novel R package for microbial metabolomics data analysis.
• To facilitate the assignment of compound hierarchies.
• To enable linking of identified metabolites to enzyme and gene annotations.

Main Methods:

• Development of the omu R package.
• Implementation of algorithms for compound hierarchy assignment.
• Integration of databases for enzyme and gene annotation.

Main Results:

• The omu package provides a robust workflow for downstream metabolomics analysis.
• Compound hierarchies can be systematically assigned.
• Metabolites are successfully linked to relevant microbial enzymes and genes.

Conclusions:

• The omu R package enhances the functional interpretation of microbial metabolomics data.
• It addresses the need for standardized analysis workflows.
• Facilitates deeper understanding of microbiota function through metabolite-gene linkage.