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

被引:4
|
作者
Pang Z. [1 ]
Xu L. [1 ]
Viau C. [1 ]
Lu Y. [2 ]
Salavati R. [1 ]
Basu N. [1 ]
Xia J. [1 ,2 ]
机构
[1] Faculty of Agricultural and Environmental Sciences, McGill University, Ste-Anne-de-Bellevue, QC
[2] Department of Microbiology and Immunology, McGill University, Montreal, QC
基金
美国国家卫生研究院; 加拿大创新基金会; 加拿大自然科学与工程研究理事会;
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D O I
10.1038/s41467-024-48009-6
中图分类号
学科分类号
摘要
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. © The Author(s) 2024.
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