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Below are the article matching results from the past week:
Article Abstract:
Nat Commun. 2024 May 1;15(1):3675. doi: 10.1038/s41467-024-48009-6.
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.
Below are the article matching results from the past week:
Nat Commun. 2024 May 1;15(1):3675. doi: 10.1038/s41467-024-48009-6.
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.
PMID:38693118 | DOI:10.1038/s41467-024-48009-6
Keywords: liquid chromatography, mass spectrometry, LC-MS, MetaboAnalystR 4.0, computational workflow, compound identification, statistical analysis, functional interpretation, spectra processing, open-source R environment.
Section Title: {'liquid chromatography': '## mWise', 'mass spectrometry': '## Batch effects visualization', 'LC-MS': '## pmd', 'compound identification': '## FastEI', 'statistical analysis': '## Distribution of intensity'}
One-sentence Summary: MetaboAnalystR 4.0 is a comprehensive computational workflow for LC-MS based metabolomics data analysis, featuring efficient spectra processing and compound identification, and accurate functional interpretation in the open-source R environment.
DOI: doi:10.1038/s41467-024-48009-6
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