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MetaboAnalystR 4.0: a unified LC-MS workflow for global metabolomics

Author

Listed:
  • Zhiqiang Pang

    (McGill University)

  • Lei Xu

    (McGill University)

  • Charles Viau

    (McGill University)

  • Yao Lu

    (McGill University)

  • Reza Salavati

    (McGill University)

  • Niladri Basu

    (McGill University)

  • Jianguo Xia

    (McGill University
    McGill University)

Abstract

The wide applications of liquid chromatography - mass spectrometry (LC-MS) in untargeted metabolomics demand an easy-to-use, comprehensive computational workflow to support efficient and reproducible data analysis. However, current tools were primarily developed to perform specific tasks in LC-MS based metabolomics data analysis. Here we introduce MetaboAnalystR 4.0 as a streamlined pipeline covering raw spectra processing, compound identification, statistical analysis, and functional interpretation. The key features of MetaboAnalystR 4.0 includes an auto-optimized feature detection and quantification algorithm for LC-MS1 spectra processing, efficient MS2 spectra deconvolution and compound identification for data-dependent or data-independent acquisition, and more accurate functional interpretation through integrated spectral annotation. Comprehensive validation studies using LC-MS1 and MS2 spectra obtained from standards mixtures, dilution series and clinical metabolomics samples have shown its excellent performance across a wide range of common tasks such as peak picking, spectral deconvolution, and compound identification with good computing efficiency. Together with its existing statistical analysis utilities, MetaboAnalystR 4.0 represents a significant step toward a unified, end-to-end workflow for LC-MS based global metabolomics in the open-source R environment.

Suggested Citation

  • Zhiqiang Pang & Lei Xu & Charles Viau & Yao Lu & Reza Salavati & Niladri Basu & Jianguo Xia, 2024. "MetaboAnalystR 4.0: a unified LC-MS workflow for global metabolomics," Nature Communications, Nature, vol. 15(1), pages 1-15, December.
    • Handle: RePEc:nat:natcom:v:15:y:2024:i:1:d:10.1038_s41467-024-48009-6
    DOI: 10.1038/s41467-024-48009-6
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