Phoenics: a novel statistical approach for longitudinal metabolomic pathway analysis
This method was applied to semi-synthetic NMR data and two real NMR datasets assessing the effects of antibiotics and irritable bowel syndrome on feces. Results showed that phoenics properly controls the Type I error rate and has a better ability to detect differential metabolic pathways and to extract new impacted biological functions than alternative methods. The method is implemented in the R package phoenics available on CRAN.
Authors
- Rémi Servien (ORCID: https://orcid.org/0000-0003-1270-1843)
- Camille Guilmineau
- Nathalie Vialaneix (ORCID: https://orcid.org/0000-0003-1156-0639)
- Marie Tremblay‐Franco (ORCID: https://orcid.org/0000-0003-4678-4456)
Institutions
- École Nationale Vétérinaire de Toulouse (FR)
- Université Fédérale de Toulouse Midi-Pyrénées (FR)
- Université de Montpellier (FR)
- Institut National de Recherche pour l'Agriculture, l'Alimentation et l'Environnement (FR)
- Toxicologie Alimentaire (FR)
- Laboratoire de Biotechnologie de l'Environnement (FR)
- Institut des Maladies Métaboliques et Cardiovasculaires (FR)
Publication Details
- Journal
- BMC Bioinformatics
- Published
- 2025-04-16
- DOI
- https://doi.org/10.1186/s12859-025-06118-z
- Primary Topic
- Metabolomics and Mass Spectrometry Studies
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Agence Nationale de la Recherche