DIMet: an open-source tool for differential analysis of targeted isotope-labeled metabolomics data
Jazyk angličtina Země Velká Británie, Anglie Médium print
Typ dokumentu časopisecké články, práce podpořená grantem
Grantová podpora
Institut National du Cancer
PubMed
38656970
PubMed Central
PMC11109473
DOI
10.1093/bioinformatics/btae282
PII: 7657698
Knihovny.cz E-zdroje
- MeSH
- glioblastom metabolismus MeSH
- izotopové značení * metody MeSH
- lidé MeSH
- metabolomika * metody MeSH
- nádorové buněčné linie MeSH
- software * MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
MOTIVATION: Many diseases, such as cancer, are characterized by an alteration of cellular metabolism allowing cells to adapt to changes in the microenvironment. Stable isotope-resolved metabolomics (SIRM) and downstream data analyses are widely used techniques for unraveling cells' metabolic activity to understand the altered functioning of metabolic pathways in the diseased state. While a number of bioinformatic solutions exist for the differential analysis of SIRM data, there is currently no available resource providing a comprehensive toolbox. RESULTS: In this work, we present DIMet, a one-stop comprehensive tool for differential analysis of targeted tracer data. DIMet accepts metabolite total abundances, isotopologue contributions, and isotopic mean enrichment, and supports differential comparison (pairwise and multi-group), time-series analyses, and labeling profile comparison. Moreover, it integrates transcriptomics and targeted metabolomics data through network-based metabolograms. We illustrate the use of DIMet in real SIRM datasets obtained from Glioblastoma P3 cell-line samples. DIMet is open-source, and is readily available for routine downstream analysis of isotope-labeled targeted metabolomics data, as it can be used both in the command line interface or as a complete toolkit in the public Galaxy Europe and Workfow4Metabolomics web platforms. AVAILABILITY AND IMPLEMENTATION: DIMet is freely available at https://github.com/cbib/DIMet, and through https://usegalaxy.eu and https://workflow4metabolomics.usegalaxy.fr. All the datasets are available at Zenodo https://zenodo.org/records/10925786.
Galaxy Europe University of Freiburg Freiburg Baden Württemberg Germany
Medical Pharmacology Department Bordeaux University Hospital Bordeaux France
RECETOX Faculty of Science Masaryk University Brno Czech Republic
University of Bordeaux Bordeaux Bioinformatics Center CBiB Bordeaux France
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