MetaboAnalyst 5.0: narrowing the gap between raw spectra and functional insights

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ID: 289856
2021
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Abstract
Since its first release over a decade ago, the MetaboAnalyst web-based platform has become widely used for comprehensive metabolomics data analysis and interpretation. Here we introduce MetaboAnalyst version 5.0, aiming to narrow the gap from raw data to functional insights for global metabolomics based on high-resolution mass spectrometry (HRMS). Three modules have been developed to help achieve this goal, including: (i) a LC-MS Spectra Processing module which offers an easy-to-use pipeline that can perform automated parameter optimization and resumable analysis to significantly lower the barriers to LC-MS1 spectra processing; (ii) a Functional Analysis module which expands the previous MS Peaks to Pathways module to allow users to intuitively select any peak groups of interest and evaluate their enrichment of potential functions as defined by metabolic pathways and metabolite sets; (iii) a Functional Meta-Analysis module to combine multiple global metabolomics datasets obtained under complementary conditions or from similar studies to arrive at comprehensive functional insights. There are many other new functions including weighted joint-pathway analysis, data-driven network analysis, batch effect correction, merging technical replicates, improved compound name matching, etc. The web interface, graphics and underlying codebase have also been refactored to improve performance and user experience. At the end of an analysis session, users can now easily switch to other compatible modules for a more streamlined data analysis. MetaboAnalyst 5.0 is freely available at https://www.metaboanalyst.ca.
Reference Key
openalex_W3159995035 Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Zhiqiang Pang, Jasmine Chong, Guangyan Zhou, David Anderson de Lima Morais, Le Chang, M. Barrette, Carol Gauthier, Pierre‐Étienne Jacques, Shuzhao Li, Jianguo Xia
Journal Nucleic Acids Research
Year 2021
DOI
10.1093/nar/gkab382
URL
https://academic.oup.com/nar/article-pdf/49/W1/W388/38842138/gkab382.pdf
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