UmetaFlow: an untargeted metabolomics workflow for high-throughput data processing and analysis.

ABSTRACT: Metabolomics experiments generate highly complex datasets, which are time and work-intensive, sometimes even error-prone if inspected manually. Therefore, new methods for automated, fast, reproducible, and accurate data processing and dereplication are required. Here, we present UmetaFlow, a computational workflow for untargeted metabolomics that combines algorithms for data pre-processing, spectral matching, molecular formula and structural predictions, and an integration to the GNPS workflows Feature-Based Molecular Networking and Ion Identity Molecular Networking for downstream analysis. UmetaFlow is implemented as a Snakemake workflow, making it easy to use, scalable, and reproducible. For more interactive computing, visualization, as well as development, the workflow is also implement

SUBMITTER: Kontou EE 

PROVIDER: S-EPMC10176759 | biostudies-literature | 2023 May

REPOSITORIES: biostudies-literature