DIMet: an open-source tool for differential analysis of targeted isotope-labeled metabolomics data
| Autoři | |
|---|---|
| Rok publikování | 2024 |
| Druh | Článek v odborném periodiku |
| Časopis / Zdroj | Bioinformatics |
| Fakulta / Pracoviště MU | |
| Citace | |
| www | https://academic.oup.com/bioinformatics/article/40/5/btae282/7657698?login=true |
| Doi | http://dx.doi.org/10.1093/bioinformatics/btae282 |
| Klíčová slova | DIMet; Stable isotope-resolved metabolomics; metabolomics data |
| Přiložené soubory | |
| Popis | 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. |
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