4.8 Article

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

期刊

NUCLEIC ACIDS RESEARCH
卷 49, 期 W1, 页码 W388-W396

出版社

OXFORD UNIV PRESS
DOI: 10.1093/nar/gkab382

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资金

  1. Genome Canada
  2. Genome Quebec
  3. US National Institutes of Health [U01 CA235493]
  4. Natural Sciences and Engineering Research Council of Canada (NSERC)
  5. Canada Research Chairs (CRC) Program
  6. Calcul Quebec
  7. Compute Canada
  8. CANARIE
  9. Fonds de la Recherche du Quebec - Sante (FRQS)

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MetaboAnalyst version 5.0 has been introduced to facilitate comprehensive metabolomics data analysis and interpretation, with the aim of narrowing the gap from raw data to functional insights. Three new modules have been developed to assist in this goal, along with various other new functions and improvements in interface, graphics, and codebase. Users can now easily switch between compatible modules for a streamlined data analysis experience.
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.

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