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bioRxiv · 10.1101/2022.03.15.484499

TidyMass: An Object-oriented Reproducible Analysis Framework for LC-MS Data

Shen, X.·Yan, H.·Wang, C.·Gao, P.·Johnson, C.·Snyder, M.
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Abstract

Reproducibility and transparency have been longstanding but significant problems for the metabolomics field. Here, we present the tidyMass project (https://www.tidymass.org/), a comprehensive computational framework that can achieve the shareable and reproducible workflow needs of data processing and analysis for LC-MS-based untargeted metabolomics. TidyMass was designed based on the following strategies to address the limitations of current tools: 1) Cross-platform utility. TidyMass can be installed on all platforms; 2) Uniformity, shareability, traceability, and reproducibility. A uniform data format has been developed, specifically designed to store and manage processed metabolomics data and processing parameters, making it possible to trace the prior analysis steps and parameters; 3) Flexibility and extensibility. The modular architecture makes tidyMass a highly flexible and extensible tool, so other users can improve it and integrate it with their own pipeline easily.

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Shen, X., Yan, H., Wang, C., Gao, P., Johnson, C., Snyder, M.. 2022-03-17. TidyMass: An Object-oriented Reproducible Analysis Framework for LC-MS Data. https://doi.org/10.1101/2022.03.15.484499

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