MetaboAnalystR 3.0: Toward an Optimized Workflow for Global Metabolomics.
batch effects
global metabolomics
pathway activity prediction
peak detection
Journal
Metabolites
ISSN: 2218-1989
Titre abrégé: Metabolites
Pays: Switzerland
ID NLM: 101578790
Informations de publication
Date de publication:
07 May 2020
07 May 2020
Historique:
received:
16
04
2020
revised:
30
04
2020
accepted:
03
05
2020
entrez:
13
5
2020
pubmed:
13
5
2020
medline:
13
5
2020
Statut:
epublish
Résumé
Liquid chromatography coupled to high-resolution mass spectrometry platforms are increasingly employed to comprehensively measure metabolome changes in systems biology and complex diseases. Over the past decade, several powerful computational pipelines have been developed for spectral processing, annotation, and analysis. However, significant obstacles remain with regard to parameter settings, computational efficiencies, batch effects, and functional interpretations. Here, we introduce MetaboAnalystR 3.0, a significantly improved pipeline with three key new features: (1) efficient parameter optimization for peak picking; (2) automated batch effect correction; and 3) more accurate pathway activity prediction. Our benchmark studies showed that this workflow was 20~100X faster compared to other well-established workflows and produced more biologically meaningful results. In summary, MetaboAnalystR 3.0 offers an efficient pipeline to support high-throughput global metabolomics in the open-source R environment.
Identifiants
pubmed: 32392884
pii: metabo10050186
doi: 10.3390/metabo10050186
pmc: PMC7281575
pii:
doi:
Types de publication
Journal Article
Langues
eng
Subventions
Organisme : NCI NIH HHS
ID : U01 CA235493
Pays : United States
Organisme : Genome Canada, Génome Québec, US National Institutes of Health (U01 CA235493), Natural Sciences and Engineering Research Council of Canada (NSERC), and Canada Research Chairs (CRC) Program
ID : N/A
Déclaration de conflit d'intérêts
The authors declare no conflicts of interest.
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