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The mzQuantML Data Standard for Mass Spectrometry–based Quantitative Studies in Proteomics([Image: see text])
The range of heterogeneous approaches available for quantifying protein abundance via mass spectrometry (MS) leads to considerable challenges in modeling, archiving, exchanging, or submitting experimental data sets as supplemental material to journals. To date, there has been no widely accepted form...
Autores principales: | , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
The American Society for Biochemistry and Molecular Biology
2013
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3734589/ https://www.ncbi.nlm.nih.gov/pubmed/23599424 http://dx.doi.org/10.1074/mcp.O113.028506 |
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author | Walzer, Mathias Qi, Da Mayer, Gerhard Uszkoreit, Julian Eisenacher, Martin Sachsenberg, Timo Gonzalez-Galarza, Faviel F. Fan, Jun Bessant, Conrad Deutsch, Eric W. Reisinger, Florian Vizcaíno, Juan Antonio Medina-Aunon, J. Alberto Albar, Juan Pablo Kohlbacher, Oliver Jones, Andrew R. |
author_facet | Walzer, Mathias Qi, Da Mayer, Gerhard Uszkoreit, Julian Eisenacher, Martin Sachsenberg, Timo Gonzalez-Galarza, Faviel F. Fan, Jun Bessant, Conrad Deutsch, Eric W. Reisinger, Florian Vizcaíno, Juan Antonio Medina-Aunon, J. Alberto Albar, Juan Pablo Kohlbacher, Oliver Jones, Andrew R. |
author_sort | Walzer, Mathias |
collection | PubMed |
description | The range of heterogeneous approaches available for quantifying protein abundance via mass spectrometry (MS) leads to considerable challenges in modeling, archiving, exchanging, or submitting experimental data sets as supplemental material to journals. To date, there has been no widely accepted format for capturing the evidence trail of how quantitative analysis has been performed by software, for transferring data between software packages, or for submitting to public databases. In the context of the Proteomics Standards Initiative, we have developed the mzQuantML data standard. The standard can represent quantitative data about regions in two-dimensional retention time versus mass/charge space (called features), peptides, and proteins and protein groups (where there is ambiguity regarding peptide-to-protein inference), and it offers limited support for small molecule (metabolomic) data. The format has structures for representing replicate MS runs, grouping of replicates (for example, as study variables), and capturing the parameters used by software packages to arrive at these values. The format has the capability to reference other standards such as mzML and mzIdentML, and thus the evidence trail for the MS workflow as a whole can now be described. Several software implementations are available, and we encourage other bioinformatics groups to use mzQuantML as an input, internal, or output format for quantitative software and for structuring local repositories. All project resources are available in the public domain from the HUPO Proteomics Standards Initiative http://www.psidev.info/mzquantml. |
format | Online Article Text |
id | pubmed-3734589 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2013 |
publisher | The American Society for Biochemistry and Molecular Biology |
record_format | MEDLINE/PubMed |
spelling | pubmed-37345892014-01-29 The mzQuantML Data Standard for Mass Spectrometry–based Quantitative Studies in Proteomics([Image: see text]) Walzer, Mathias Qi, Da Mayer, Gerhard Uszkoreit, Julian Eisenacher, Martin Sachsenberg, Timo Gonzalez-Galarza, Faviel F. Fan, Jun Bessant, Conrad Deutsch, Eric W. Reisinger, Florian Vizcaíno, Juan Antonio Medina-Aunon, J. Alberto Albar, Juan Pablo Kohlbacher, Oliver Jones, Andrew R. Mol Cell Proteomics Technological Innovation and Resources The range of heterogeneous approaches available for quantifying protein abundance via mass spectrometry (MS) leads to considerable challenges in modeling, archiving, exchanging, or submitting experimental data sets as supplemental material to journals. To date, there has been no widely accepted format for capturing the evidence trail of how quantitative analysis has been performed by software, for transferring data between software packages, or for submitting to public databases. In the context of the Proteomics Standards Initiative, we have developed the mzQuantML data standard. The standard can represent quantitative data about regions in two-dimensional retention time versus mass/charge space (called features), peptides, and proteins and protein groups (where there is ambiguity regarding peptide-to-protein inference), and it offers limited support for small molecule (metabolomic) data. The format has structures for representing replicate MS runs, grouping of replicates (for example, as study variables), and capturing the parameters used by software packages to arrive at these values. The format has the capability to reference other standards such as mzML and mzIdentML, and thus the evidence trail for the MS workflow as a whole can now be described. Several software implementations are available, and we encourage other bioinformatics groups to use mzQuantML as an input, internal, or output format for quantitative software and for structuring local repositories. All project resources are available in the public domain from the HUPO Proteomics Standards Initiative http://www.psidev.info/mzquantml. The American Society for Biochemistry and Molecular Biology 2013-08 2013-04-18 /pmc/articles/PMC3734589/ /pubmed/23599424 http://dx.doi.org/10.1074/mcp.O113.028506 Text en © 2013 by The American Society for Biochemistry and Molecular Biology, Inc. Author's Choice—Final version full access. |
spellingShingle | Technological Innovation and Resources Walzer, Mathias Qi, Da Mayer, Gerhard Uszkoreit, Julian Eisenacher, Martin Sachsenberg, Timo Gonzalez-Galarza, Faviel F. Fan, Jun Bessant, Conrad Deutsch, Eric W. Reisinger, Florian Vizcaíno, Juan Antonio Medina-Aunon, J. Alberto Albar, Juan Pablo Kohlbacher, Oliver Jones, Andrew R. The mzQuantML Data Standard for Mass Spectrometry–based Quantitative Studies in Proteomics([Image: see text]) |
title | The mzQuantML Data Standard for Mass Spectrometry–based Quantitative Studies in Proteomics([Image: see text]) |
title_full | The mzQuantML Data Standard for Mass Spectrometry–based Quantitative Studies in Proteomics([Image: see text]) |
title_fullStr | The mzQuantML Data Standard for Mass Spectrometry–based Quantitative Studies in Proteomics([Image: see text]) |
title_full_unstemmed | The mzQuantML Data Standard for Mass Spectrometry–based Quantitative Studies in Proteomics([Image: see text]) |
title_short | The mzQuantML Data Standard for Mass Spectrometry–based Quantitative Studies in Proteomics([Image: see text]) |
title_sort | mzquantml data standard for mass spectrometry–based quantitative studies in proteomics([image: see text]) |
topic | Technological Innovation and Resources |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3734589/ https://www.ncbi.nlm.nih.gov/pubmed/23599424 http://dx.doi.org/10.1074/mcp.O113.028506 |
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