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Metabolites 2019, 9(3), 57;

MetaboAnalystR 2.0: From Raw Spectra to Biological Insights

Institute of Parasitology, McGill University, Montreal, QC H3A 0G4, Canada
Department of Animal Science, McGill University, Montreal, QC H3A 0G4, Canada
Author to whom correspondence should be addressed.
Received: 5 March 2019 / Revised: 20 March 2019 / Accepted: 21 March 2019 / Published: 22 March 2019
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Global metabolomics based on high-resolution liquid chromatography mass spectrometry (LC-MS) has been increasingly employed in recent large-scale multi-omics studies. Processing and interpretation of these complex metabolomics datasets have become a key challenge in current computational metabolomics. Here, we introduce MetaboAnalystR 2.0 for comprehensive LC-MS data processing, statistical analysis, and functional interpretation. Compared to the previous version, this new release seamlessly integrates XCMS and CAMERA to support raw spectral processing and peak annotation, and also features high-performance implementations of mummichog and GSEA approaches for predictions of pathway activities. The application and utility of the MetaboAnalystR 2.0 workflow were demonstrated using a synthetic benchmark dataset and a clinical dataset. In summary, MetaboAnalystR 2.0 offers a unified and flexible workflow that enables end-to-end analysis of LC-MS metabolomics data within the open-source R environment. View Full-Text
Keywords: global metabolomics; LC-MS; spectra processing; pathway analysis; enrichment analysis global metabolomics; LC-MS; spectra processing; pathway analysis; enrichment analysis

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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

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Chong, J.; Yamamoto, M.; Xia, J. MetaboAnalystR 2.0: From Raw Spectra to Biological Insights. Metabolites 2019, 9, 57.

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