I have a dataset comprising 12 biological samples, each with paired metabolomics and metagenomics data.

The metabolomics dataset includes: Raw abundance values of identified metabolites, Associated HMDB IDs, and Fold change (FC) values for differentially expressed metabolites.

For the metagenomics dataset, I have: Raw and relative abundance data for identified microbial taxa (species/OTUs/ASVs), and Functional pathway analysis results, including gene-level information associated with predicted pathways (e.g., KEGG orthologs, COGs).

Given this multi-layered data, how should I proceed with an integration analysis to explore interactions between microbial composition, metabolic profiles, and functional pathways?

I’m particularly interested in identifying: Functional relationships or correlations between microbial taxa and metabolite levels, Pathway-level links between microbial genes and metabolite changes, And potentially predictive or mechanistic networks of interaction.

Please explain the recommended workflow, statistical approaches, and visualisation techniques for integration, assuming an audience with a background in systems biology and multi-omics data analysis.

Thank you