DIMet: An open-source tool for Differential analysis of targeted Isotope-labeled Metabolomics data
Bioinformatics(2024)
摘要
Abstract 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 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 Stable Isotope-Resolved Metabolomics 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 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 Supplementary information Supplementary data are available at Bioinformatics online.
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