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MetaboAnalystR 3.0: Toward an Optimized Workflow for Global Metabolomics

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, an...

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Detalles Bibliográficos
Autores principales: Pang, Zhiqiang, Chong, Jasmine, Li, Shuzhao, Xia, Jianguo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7281575/
https://www.ncbi.nlm.nih.gov/pubmed/32392884
http://dx.doi.org/10.3390/metabo10050186
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author Pang, Zhiqiang
Chong, Jasmine
Li, Shuzhao
Xia, Jianguo
author_facet Pang, Zhiqiang
Chong, Jasmine
Li, Shuzhao
Xia, Jianguo
author_sort Pang, Zhiqiang
collection PubMed
description 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 20~100× 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.
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spelling pubmed-72815752020-06-17 MetaboAnalystR 3.0: Toward an Optimized Workflow for Global Metabolomics Pang, Zhiqiang Chong, Jasmine Li, Shuzhao Xia, Jianguo Metabolites Article 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 20~100× 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. MDPI 2020-05-07 /pmc/articles/PMC7281575/ /pubmed/32392884 http://dx.doi.org/10.3390/metabo10050186 Text en © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Pang, Zhiqiang
Chong, Jasmine
Li, Shuzhao
Xia, Jianguo
MetaboAnalystR 3.0: Toward an Optimized Workflow for Global Metabolomics
title MetaboAnalystR 3.0: Toward an Optimized Workflow for Global Metabolomics
title_full MetaboAnalystR 3.0: Toward an Optimized Workflow for Global Metabolomics
title_fullStr MetaboAnalystR 3.0: Toward an Optimized Workflow for Global Metabolomics
title_full_unstemmed MetaboAnalystR 3.0: Toward an Optimized Workflow for Global Metabolomics
title_short MetaboAnalystR 3.0: Toward an Optimized Workflow for Global Metabolomics
title_sort metaboanalystr 3.0: toward an optimized workflow for global metabolomics
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7281575/
https://www.ncbi.nlm.nih.gov/pubmed/32392884
http://dx.doi.org/10.3390/metabo10050186
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