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DIA proteomics data from a UPS1-spiked E.coli protein mixture processed with six software tools

In this article, we provide a proteomic reference dataset that has been initially generated for a benchmarking of software tools for Data-Independent Acquisition (DIA) analysis. This large dataset includes 96 DIA .raw files acquired from a complex proteomic standard composed of an E.coli protein bac...

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Autores principales: Gotti, Clarisse, Roux-Dalvai, Florence, Joly-Beauparlant, Charles, Mangnier, Loïc, Leclercq, Mickaël, Droit, Arnaud
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8841991/
https://www.ncbi.nlm.nih.gov/pubmed/35198661
http://dx.doi.org/10.1016/j.dib.2022.107829
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author Gotti, Clarisse
Roux-Dalvai, Florence
Joly-Beauparlant, Charles
Mangnier, Loïc
Leclercq, Mickaël
Droit, Arnaud
author_facet Gotti, Clarisse
Roux-Dalvai, Florence
Joly-Beauparlant, Charles
Mangnier, Loïc
Leclercq, Mickaël
Droit, Arnaud
author_sort Gotti, Clarisse
collection PubMed
description In this article, we provide a proteomic reference dataset that has been initially generated for a benchmarking of software tools for Data-Independent Acquisition (DIA) analysis. This large dataset includes 96 DIA .raw files acquired from a complex proteomic standard composed of an E.coli protein background spiked-in with 8 different concentrations of 48 human proteins (UPS1 Sigma). These 8 samples were analyzed in triplicates on an Orbitrap mass spectrometer with 4 different DIA window schemes. We also provide the spectral libraries and FASTA file used for their analysis and the software outputs of the six tools used in this study: DIA-NN, Spectronaut, ScaffoldDIA, DIA-Umpire, Skyline and OpenSWATH. This dataset also contains post-processed quantification tables where the peptides and proteins have been validated, their intensities normalized and the missing values imputed with a noise value. All the files are available on ProteomeXchange. Altogether, these files represent the most comprehensive DIA reference dataset acquired on an Orbitrap instrument ever published. It will be a very useful resource to the proteomic scientists in order to assess the performance of DIA software tools or to test their processing pipelines, to the software developers to improve their tools or develop new ones and to the students for their training on proteomics data analysis.
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spelling pubmed-88419912022-02-22 DIA proteomics data from a UPS1-spiked E.coli protein mixture processed with six software tools Gotti, Clarisse Roux-Dalvai, Florence Joly-Beauparlant, Charles Mangnier, Loïc Leclercq, Mickaël Droit, Arnaud Data Brief Data Article In this article, we provide a proteomic reference dataset that has been initially generated for a benchmarking of software tools for Data-Independent Acquisition (DIA) analysis. This large dataset includes 96 DIA .raw files acquired from a complex proteomic standard composed of an E.coli protein background spiked-in with 8 different concentrations of 48 human proteins (UPS1 Sigma). These 8 samples were analyzed in triplicates on an Orbitrap mass spectrometer with 4 different DIA window schemes. We also provide the spectral libraries and FASTA file used for their analysis and the software outputs of the six tools used in this study: DIA-NN, Spectronaut, ScaffoldDIA, DIA-Umpire, Skyline and OpenSWATH. This dataset also contains post-processed quantification tables where the peptides and proteins have been validated, their intensities normalized and the missing values imputed with a noise value. All the files are available on ProteomeXchange. Altogether, these files represent the most comprehensive DIA reference dataset acquired on an Orbitrap instrument ever published. It will be a very useful resource to the proteomic scientists in order to assess the performance of DIA software tools or to test their processing pipelines, to the software developers to improve their tools or develop new ones and to the students for their training on proteomics data analysis. Elsevier 2022-01-31 /pmc/articles/PMC8841991/ /pubmed/35198661 http://dx.doi.org/10.1016/j.dib.2022.107829 Text en © 2022 The Author(s) https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Data Article
Gotti, Clarisse
Roux-Dalvai, Florence
Joly-Beauparlant, Charles
Mangnier, Loïc
Leclercq, Mickaël
Droit, Arnaud
DIA proteomics data from a UPS1-spiked E.coli protein mixture processed with six software tools
title DIA proteomics data from a UPS1-spiked E.coli protein mixture processed with six software tools
title_full DIA proteomics data from a UPS1-spiked E.coli protein mixture processed with six software tools
title_fullStr DIA proteomics data from a UPS1-spiked E.coli protein mixture processed with six software tools
title_full_unstemmed DIA proteomics data from a UPS1-spiked E.coli protein mixture processed with six software tools
title_short DIA proteomics data from a UPS1-spiked E.coli protein mixture processed with six software tools
title_sort dia proteomics data from a ups1-spiked e.coli protein mixture processed with six software tools
topic Data Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8841991/
https://www.ncbi.nlm.nih.gov/pubmed/35198661
http://dx.doi.org/10.1016/j.dib.2022.107829
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