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mzML2ISA & nmrML2ISA: generating enriched ISA-Tab metadata files from metabolomics XML data

SUMMARY: Submission to the MetaboLights repository for metabolomics data currently places the burden of reporting instrument and acquisition parameters in ISA-Tab format on users, who have to do it manually, a process that is time consuming and prone to user input error. Since the large majority of...

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Autores principales: Larralde, Martin, Lawson, Thomas N, Weber, Ralf J M, Moreno, Pablo, Haug, Kenneth, Rocca-Serra, Philippe, Viant, Mark R, Steinbeck, Christoph, Salek, Reza M
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5870861/
https://www.ncbi.nlm.nih.gov/pubmed/28402395
http://dx.doi.org/10.1093/bioinformatics/btx169
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author Larralde, Martin
Lawson, Thomas N
Weber, Ralf J M
Moreno, Pablo
Haug, Kenneth
Rocca-Serra, Philippe
Viant, Mark R
Steinbeck, Christoph
Salek, Reza M
author_facet Larralde, Martin
Lawson, Thomas N
Weber, Ralf J M
Moreno, Pablo
Haug, Kenneth
Rocca-Serra, Philippe
Viant, Mark R
Steinbeck, Christoph
Salek, Reza M
author_sort Larralde, Martin
collection PubMed
description SUMMARY: Submission to the MetaboLights repository for metabolomics data currently places the burden of reporting instrument and acquisition parameters in ISA-Tab format on users, who have to do it manually, a process that is time consuming and prone to user input error. Since the large majority of these parameters are embedded in instrument raw data files, an opportunity exists to capture this metadata more accurately. Here we report a set of Python packages that can automatically generate ISA-Tab metadata file stubs from raw XML metabolomics data files. The parsing packages are separated into mzML2ISA (encompassing mzML and imzML formats) and nmrML2ISA (nmrML format only). Overall, the use of mzML2ISA & nmrML2ISA reduces the time needed to capture metadata substantially (capturing 90% of metadata on assay and sample levels), is much less prone to user input errors, improves compliance with minimum information reporting guidelines and facilitates more finely grained data exploration and querying of datasets. AVAILABILITY AND IMPLEMENTATION: mzML2ISA & nmrML2ISA are available under version 3 of the GNU General Public Licence at https://github.com/ISA-tools. Documentation is available from http://2isa.readthedocs.io/en/latest/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
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spelling pubmed-58708612018-03-29 mzML2ISA & nmrML2ISA: generating enriched ISA-Tab metadata files from metabolomics XML data Larralde, Martin Lawson, Thomas N Weber, Ralf J M Moreno, Pablo Haug, Kenneth Rocca-Serra, Philippe Viant, Mark R Steinbeck, Christoph Salek, Reza M Bioinformatics Applications Notes SUMMARY: Submission to the MetaboLights repository for metabolomics data currently places the burden of reporting instrument and acquisition parameters in ISA-Tab format on users, who have to do it manually, a process that is time consuming and prone to user input error. Since the large majority of these parameters are embedded in instrument raw data files, an opportunity exists to capture this metadata more accurately. Here we report a set of Python packages that can automatically generate ISA-Tab metadata file stubs from raw XML metabolomics data files. The parsing packages are separated into mzML2ISA (encompassing mzML and imzML formats) and nmrML2ISA (nmrML format only). Overall, the use of mzML2ISA & nmrML2ISA reduces the time needed to capture metadata substantially (capturing 90% of metadata on assay and sample levels), is much less prone to user input errors, improves compliance with minimum information reporting guidelines and facilitates more finely grained data exploration and querying of datasets. AVAILABILITY AND IMPLEMENTATION: mzML2ISA & nmrML2ISA are available under version 3 of the GNU General Public Licence at https://github.com/ISA-tools. Documentation is available from http://2isa.readthedocs.io/en/latest/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. Oxford University Press 2017-08-15 2017-04-07 /pmc/articles/PMC5870861/ /pubmed/28402395 http://dx.doi.org/10.1093/bioinformatics/btx169 Text en © The Author 2017. Published by Oxford University Press. http://creativecommons.org/licenses/by/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Applications Notes
Larralde, Martin
Lawson, Thomas N
Weber, Ralf J M
Moreno, Pablo
Haug, Kenneth
Rocca-Serra, Philippe
Viant, Mark R
Steinbeck, Christoph
Salek, Reza M
mzML2ISA & nmrML2ISA: generating enriched ISA-Tab metadata files from metabolomics XML data
title mzML2ISA & nmrML2ISA: generating enriched ISA-Tab metadata files from metabolomics XML data
title_full mzML2ISA & nmrML2ISA: generating enriched ISA-Tab metadata files from metabolomics XML data
title_fullStr mzML2ISA & nmrML2ISA: generating enriched ISA-Tab metadata files from metabolomics XML data
title_full_unstemmed mzML2ISA & nmrML2ISA: generating enriched ISA-Tab metadata files from metabolomics XML data
title_short mzML2ISA & nmrML2ISA: generating enriched ISA-Tab metadata files from metabolomics XML data
title_sort mzml2isa & nmrml2isa: generating enriched isa-tab metadata files from metabolomics xml data
topic Applications Notes
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5870861/
https://www.ncbi.nlm.nih.gov/pubmed/28402395
http://dx.doi.org/10.1093/bioinformatics/btx169
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