DIMet: an open-source tool for differential analysis of targeted Isotope-labeled metabolomics data

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 (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

Standort
Deutsche Nationalbibliothek Frankfurt am Main
Umfang
Online-Ressource
Sprache
Englisch
Anmerkungen
Bioinformatics. - 40, 5 (2024) , btae282, ISSN: 1367-4811

Ereignis
Veröffentlichung
(wo)
Freiburg
(wer)
Universität
(wann)
2024
Urheber
Galvis, Johanna
Guyon, Joris
Dartigues, Benjamin
Hecht, Helge
Grüning, Björn
Specque, Florian
Soueidan, Hayssam
Karkar, Slim
Daubon, Thomas
Nikolski, Macha

DOI
10.1093/bioinformatics/btae282
URN
urn:nbn:de:bsz:25-freidok-2469550
Rechteinformation
Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
Letzte Aktualisierung
25.03.2025, 13:54 MEZ

Datenpartner

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Beteiligte

  • Galvis, Johanna
  • Guyon, Joris
  • Dartigues, Benjamin
  • Hecht, Helge
  • Grüning, Björn
  • Specque, Florian
  • Soueidan, Hayssam
  • Karkar, Slim
  • Daubon, Thomas
  • Nikolski, Macha
  • Universität

Entstanden

  • 2024

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