An article published in the Journal of Cheminformatics presents UmetaFlow: a computational workflow for untargeted metabolomics that combines algorithms for data pre-processing, spectral matching, molecular formula and structural predictions.
UmetaFlow is open-source, fast and scalable, and it allows for the combination of different tools and data integration to facilitate processing and analysis of large untargeted metabolomics datasets. It supports data generated in positive or negative mode and from most instrument types that can be converted to the mzML format .
A limitation of UmetaFlow is the requirements for basic programming skills in order to implement and adapt the Snakemake workflow, as well as access to a server, cluster or cloud environment for processing very large datasets, due to storage requirements that exceed specifications of a common PC. However, the user can delete all the interim files at the end of a run. The most computationally demanding process in the workflow is SIRIUS step, which is optional.
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