Major Update and Improved Validation Functionality in the mwtab Python Library and the Metabolomics Workbench File...

Area of Science:

• Metabolomics
• Bioinformatics
• Data Science

Background:

• The Metabolomics Workbench (MW) is a public repository for metabolomics data, utilizing mass spectrometry (MS) and nuclear magnetic resonance (NMR).
• MW has experienced exponential growth, with a 50% increase in datasets since April 2024, necessitating infrastructure and format updates.
• The mwTab file format and web infrastructure have undergone continuous evolution to manage this expanding data volume.

Purpose of the Study:

• To update the mwtab Python package to enhance data processing and validation for the Metabolomics Workbench.
• To improve the curation, FAIRness, and reusability of metabolomics datasets within the MW repository.
• To facilitate the use of MW datasets in meta-analyses through improved data quality and accessibility.

Main Methods:

• Updated the mwtab Python package with improved error handling for batch processing and enhanced parsing capabilities.
• Implemented extensive improvements to the validation features within the mwtab package.
• Utilized the enhanced validation features to evaluate all available datasets in the MW repository.

Main Results:

• Version 2.0.0 of the mwtab Python package has been released, offering robust data validation and parsing.
• The mwFileStatusWebsite has been updated to version 2.0.0 to complement the package improvements.
• All available MW datasets were evaluated using the enhanced validation features, leading to improved data quality.

Conclusions:

• The updated mwtab package (v2.0.0) significantly enhances the quality and usability of metabolomics data in the MW repository.
• These improvements support better data curation, adherence to FAIR principles, and facilitate large-scale meta-analyses.
• The freely available mwtab package and updated website empower researchers to more effectively utilize public metabolomics data.