Abstract
There has been a growing acknowledgment of the involvement of the gut microbiome—the collection of microorganisms that reside in our gut—in regulating our mood and behavior. This phenomenon is referred to as the microbiome–gut–brain axis. Although our techniques to measure the presence and abundance of these microorganisms have been steadily improving, the analysis of microbiome data is non-trivial. Here we present a perspective on the concepts and foundations of data analysis and interpretation of microbiome experiments with a focus on the microbiome–gut–brain axis domain. We give an overview of foundational considerations before commencing analysis alongside the core microbiome analysis approaches of alpha diversity, beta diversity, differential feature abundance and functional inference. We emphasize the compositional data analysis paradigm. Furthermore, this Perspective features an extensive and heavily annotated microbiome analysis in R, as a resource for new and experienced bioinformaticians alike.
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Acknowledgements
We thank A.-L. Ponsonby for her expert comments on directed acyclic graphs, D. L. Dahly for his insights on statistical analysis and J. F. Cryan for his continued encouragement and excellent advice. APC Microbiome Ireland is a research center funded by Science Foundation Ireland (SFI), through the Irish Governments’ national development plan (grant no. 12/RC/2273_P2).
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Annotated demonstration of a microbiome–gut–brain axis bioinformatics analysis in R Markdown.
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Bastiaanssen, T.F.S., Quinn, T.P. & Loughman, A. Bugs as features (part 1): concepts and foundations for the compositional data analysis of the microbiome–gut–brain axis. Nat. Mental Health 1, 930–938 (2023). https://doi.org/10.1038/s44220-023-00148-3
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DOI: https://doi.org/10.1038/s44220-023-00148-3
