Next Article in Journal
Non-Volatile Metabolites from Trichoderma spp.
Next Article in Special Issue
CFM-ID 3.0: Significantly Improved ESI-MS/MS Prediction and Compound Identification
Previous Article in Journal
Flavan-3-ols Content in Red Raspberry Leaves Increases under Blue Led-Light Irradiation
Previous Article in Special Issue
Metabolic Modeling of Human Gut Microbiota on a Genome Scale: An Overview
Article Menu
Issue 3 (March) cover image

Export Article

Open AccessFeature PaperArticle
Metabolites 2019, 9(3), 57; https://doi.org/10.3390/metabo9030057

MetaboAnalystR 2.0: From Raw Spectra to Biological Insights

1
Institute of Parasitology, McGill University, Montreal, QC H3A 0G4, Canada
2
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
  |  
PDF [1056 KB, uploaded 22 March 2019]
  |  

Abstract

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
Figures

Graphical abstract

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).

Supplementary material

SciFeed

Share & Cite This Article

MDPI and ACS Style

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

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Metabolites EISSN 2218-1989 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top