We are happy to announce that our paper “Protocol for untargeted LC-MS/MS metabolomics annotation and differential abundance analysis using the SIRIUS Python client” is now available in STAR Protocols.
Untargeted LC-MS/MS metabolomics workflows often involve several tools and intermediate files, making complete analyses difficult to reproduce. In our new protocol, we demonstrate how to carry out an end-to-end analysis programmatically using PySirius, the Python client for SIRIUS. The workflow covers importing feature-aligned LC-MS/MS data, blank subtraction and quality filtering, followed by automated annotation of molecular formulas, structures, and compound classes. We then show how to assign samples to groups, calculate fold changes at the feature and compound-class level, and visualize the results.
All steps are combined in a single Python workflow that communicates with SIRIUS through its REST API and can easily be integrated with downstream Python libraries. As a proof of concept, we analyze a public rosemary dataset and reproduce the finding that rosmarinic acid is more abundant in old than in young rosemary leaves.
The paper is open access and includes the complete code needed to reproduce and adapt the workflow. Congrats to Jonas, Sebastian, and Markus!