Using MetaboAnalyst 4.0 for Comprehensive and Integrative Metabolomics Data Analysis

By Jasmine Chong, David S. Wishart, Jianguo Xia. Current Protocols in Bioinformatics, 2019

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MetaboAnalyst (https://www.metaboanalyst.ca) is an easy‐to‐use web‐based tool suite for comprehensive metabolomic data analysis, interpretation, and integration with other omics data. Since its first release in 2009, MetaboAnalyst has evolved significantly to meet the ever‐expanding bioinformatics demands from the rapidly growing metabolomics community. In addition to providing a variety of data processing and normalization procedures, MetaboAnalyst supports a wide array of functions for statistical, functional, as well as data visualization tasks. Some of the most widely used approaches include PCA (principal component analysis), PLS‐DA (partial least squares discriminant analysis), clustering analysis and visualization, MSEA (metabolite set enrichment analysis), MetPA (metabolic pathway analysis), biomarker selection via ROC (receiver operating characteristic) curve analysis, as well as time series and power analysis. The current version of MetaboAnalyst (4.0) features a complete overhaul of the user interface and significantly expanded underlying knowledge bases (compound database, pathway libraries, and metabolite sets). Three new modules have been added to support pathway activity prediction directly from mass peaks, biomarker meta‐analysis, and network‐based multi‐omics data integration. To enable more transparent and reproducible analysis of metabolomic data, we have released a companion R package (MetaboAnalystR) to complement the web‐based application. This article provides an overview of the main functional modules and the general workflow of MetaboAnalyst 4.0, followed by 12 detailed protocols: © 2019 by John Wiley & Sons, Inc.

Subfields: Molecular Biology

View Paper: https://www.semanticscholar.org/paper/0c9de4aa510659b520cd4c944ee3fb7acda91558

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In Molecular Biology

  1. David S. Wishart
  2. R. Mandal
  3. Anchi Guo
  4. R. Greiner
  5. David Arndt
  6. Helgi B. Schiöth
  7. Jianguo Xia
  8. Jasmine Chong

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