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

Direct infusion-based single-cell metabolomics analysis has the potential to isolate the causes of drug resistance and cancer progression; however, processing and analyzing the data generated remains a challenge. While many packages exist for metabolomics analysis, they are not optimized for direct infusion-based single-cell measurements, which do not rely on chromatographic separation and are typically noisier than traditional population-level methods. To address this gap, the MeDUSA (Metabolomics of direct-infusion untargeted single-cell analysis) R package was developed. MeDUSA was built especially for direct infusion-based single-cell metabolomics, with modularity, noise filtering, and user-customization in mind. In this work, we introduce the package, how to use it, and implement it in a single-cell metabolomics experiment to identify the differences between two cell lines. MeDUSA compromises several functions that deal with file import, peak picking, spectral processing, statistical analysis, and feature annotation. Each function is defined with the purpose, usage, parameters, default values, and output of an example data set. MeDUSA was built to be a modular platform that aims to be a foundation to be built upon with additional modules for the single-cell metabolomics field.