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From Mythology to Methodology: Untargeted Single-Cell Metabolomics in R with MeDUSA.

Laura Ann Castaneda1, Eric Hetzel2, Fercan Gül1

  • 1Leiden University, 2333 CC Leiden, The Netherlands.

Journal of the American Society for Mass Spectrometry
|May 6, 2026
PubMed
Summary

The new MeDUSA R package simplifies direct infusion single-cell metabolomics data analysis. It addresses challenges in processing noisy, non-chromatographic data for cancer research.

Keywords:
data analysisdirect infusionmetabolomicssingle cell

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Area of Science:

  • Metabolomics
  • Bioinformatics
  • Cancer Research

Background:

  • Direct infusion single-cell metabolomics offers insights into drug resistance and cancer progression.
  • Existing metabolomics tools are not optimized for the unique challenges of direct infusion single-cell data, such as increased noise and lack of chromatographic separation.

Purpose of the Study:

  • To introduce MeDUSA (Metabolomics of direct-infusion untargeted single-cell analysis), an R package specifically designed for direct infusion single-cell metabolomics.
  • To provide a modular, user-friendly platform for processing, analyzing, and annotating single-cell metabolomics data.

Main Methods:

  • Development of the MeDUSA R package with modular functions for file import, peak picking, spectral processing, statistical analysis, and feature annotation.
  • Implementation of MeDUSA in a case study comparing two cell lines to demonstrate its utility.

Main Results:

  • MeDUSA effectively handles the complexities of direct infusion single-cell metabolomics data, including noise reduction and feature identification.
  • The package successfully identified metabolic differences between two distinct cell lines.

Conclusions:

  • MeDUSA provides a crucial tool for advancing single-cell metabolomics research, particularly in understanding cancer progression and drug resistance.
  • The modular design of MeDUSA allows for future expansion and adaptation to evolving needs in the field.