TaxaPLN: a taxonomy-aware augmentation strategy for microbiome-trait classification including metadata
TaxaPLN provides a model-based framework for augmenting microbiome datasets while preserving their ecological and clinical relevance. By integrating taxonomic structure and host metadata, it enhances predictive modeling across diverse real-world settings. To facilitate reproducible and scalable microbiome analysis using our method, TaxaPLN is released as an open-source Python package available on PyPI (plntree), with MIT-licensed source code hosted at https://github.com/AlexandreChaussard/PLNTree-package .
Authors
- Anna Bonnet (ORCID: https://orcid.org/0000-0003-0765-1706)
- Sylvain Le Corff
- Harry Sokol (ORCID: https://orcid.org/0000-0002-2914-1822)
- Alexandre Chaussard (ORCID: https://orcid.org/0009-0001-4561-3797)
Institutions
- Centre National de la Recherche Scientifique (FR)
- Inserm (FR)
- Université Paris Cité (FR)
- Sorbonne Université (FR)
- Sorbonne Paris Cité (FR)
- Assistance Publique – Hôpitaux de Paris (FR)
- Fédération Hospitalo-Universitaire, Paris Center for Microbiome Medicine (FR)
- Centre de Recherche Saint-Antoine (FR)
- Laboratoire de Probabilités et Modèles Aléatoires (FR)
Publication Details
- Journal
- BMC Bioinformatics
- Published
- 2025-11-28
- DOI
- https://doi.org/10.1186/s12859-025-06312-z
- Primary Topic
- Gut microbiota and health
- Type
- article
- Field-Weighted Citation Impact
- 0.00