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MetaDB a Data Processing Workflow in Untargeted MS-Based Metabolomics Experiments

Due to their sensitivity and speed, mass-spectrometry based analytical technologies are widely used to in metabolomics to characterize biological phenomena. To address issues like metadata organization, quality assessment, data processing, data storage, and, finally, submission to public repositorie...

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Autores principales: Franceschi, Pietro, Mylonas, Roman, Shahaf, Nir, Scholz, Matthias, Arapitsas, Panagiotis, Masuero, Domenico, Weingart, Georg, Carlin, Silvia, Vrhovsek, Urska, Mattivi, Fulvio, Wehrens, Ron
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4267269/
https://www.ncbi.nlm.nih.gov/pubmed/25566535
http://dx.doi.org/10.3389/fbioe.2014.00072
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author Franceschi, Pietro
Mylonas, Roman
Shahaf, Nir
Scholz, Matthias
Arapitsas, Panagiotis
Masuero, Domenico
Weingart, Georg
Carlin, Silvia
Vrhovsek, Urska
Mattivi, Fulvio
Wehrens, Ron
author_facet Franceschi, Pietro
Mylonas, Roman
Shahaf, Nir
Scholz, Matthias
Arapitsas, Panagiotis
Masuero, Domenico
Weingart, Georg
Carlin, Silvia
Vrhovsek, Urska
Mattivi, Fulvio
Wehrens, Ron
author_sort Franceschi, Pietro
collection PubMed
description Due to their sensitivity and speed, mass-spectrometry based analytical technologies are widely used to in metabolomics to characterize biological phenomena. To address issues like metadata organization, quality assessment, data processing, data storage, and, finally, submission to public repositories, bioinformatic pipelines of a non-interactive nature are often employed, complementing the interactive software used for initial inspection and visualization of the data. These pipelines often are created as open-source software allowing the complete and exhaustive documentation of each step, ensuring the reproducibility of the analysis of extensive and often expensive experiments. In this paper, we will review the major steps which constitute such a data processing pipeline, discussing them in the context of an open-source software for untargeted MS-based metabolomics experiments recently developed at our institute. The software has been developed by integrating our metaMS R package with a user-friendly web-based application written in Grails. MetaMS takes care of data pre-processing and annotation, while the interface deals with the creation of the sample lists, the organization of the data storage, and the generation of survey plots for quality assessment. Experimental and biological metadata are stored in the ISA-Tab format making the proposed pipeline fully integrated with the Metabolights framework.
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spelling pubmed-42672692015-01-06 MetaDB a Data Processing Workflow in Untargeted MS-Based Metabolomics Experiments Franceschi, Pietro Mylonas, Roman Shahaf, Nir Scholz, Matthias Arapitsas, Panagiotis Masuero, Domenico Weingart, Georg Carlin, Silvia Vrhovsek, Urska Mattivi, Fulvio Wehrens, Ron Front Bioeng Biotechnol Bioengineering and Biotechnology Due to their sensitivity and speed, mass-spectrometry based analytical technologies are widely used to in metabolomics to characterize biological phenomena. To address issues like metadata organization, quality assessment, data processing, data storage, and, finally, submission to public repositories, bioinformatic pipelines of a non-interactive nature are often employed, complementing the interactive software used for initial inspection and visualization of the data. These pipelines often are created as open-source software allowing the complete and exhaustive documentation of each step, ensuring the reproducibility of the analysis of extensive and often expensive experiments. In this paper, we will review the major steps which constitute such a data processing pipeline, discussing them in the context of an open-source software for untargeted MS-based metabolomics experiments recently developed at our institute. The software has been developed by integrating our metaMS R package with a user-friendly web-based application written in Grails. MetaMS takes care of data pre-processing and annotation, while the interface deals with the creation of the sample lists, the organization of the data storage, and the generation of survey plots for quality assessment. Experimental and biological metadata are stored in the ISA-Tab format making the proposed pipeline fully integrated with the Metabolights framework. Frontiers Media S.A. 2014-12-16 /pmc/articles/PMC4267269/ /pubmed/25566535 http://dx.doi.org/10.3389/fbioe.2014.00072 Text en Copyright © 2014 Franceschi, Mylonas, Shahaf, Scholz, Arapitsas, Masuero, Weingart, Carlin, Vrhovsek, Mattivi and Wehrens. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Bioengineering and Biotechnology
Franceschi, Pietro
Mylonas, Roman
Shahaf, Nir
Scholz, Matthias
Arapitsas, Panagiotis
Masuero, Domenico
Weingart, Georg
Carlin, Silvia
Vrhovsek, Urska
Mattivi, Fulvio
Wehrens, Ron
MetaDB a Data Processing Workflow in Untargeted MS-Based Metabolomics Experiments
title MetaDB a Data Processing Workflow in Untargeted MS-Based Metabolomics Experiments
title_full MetaDB a Data Processing Workflow in Untargeted MS-Based Metabolomics Experiments
title_fullStr MetaDB a Data Processing Workflow in Untargeted MS-Based Metabolomics Experiments
title_full_unstemmed MetaDB a Data Processing Workflow in Untargeted MS-Based Metabolomics Experiments
title_short MetaDB a Data Processing Workflow in Untargeted MS-Based Metabolomics Experiments
title_sort metadb a data processing workflow in untargeted ms-based metabolomics experiments
topic Bioengineering and Biotechnology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4267269/
https://www.ncbi.nlm.nih.gov/pubmed/25566535
http://dx.doi.org/10.3389/fbioe.2014.00072
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