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A comprehensive LFQ benchmark dataset on modern day acquisition strategies in proteomics

Authors :
Bart Van Puyvelde
Simon Daled
Sander Willems
Ralf Gabriels
Anne Gonzalez de Peredo
Karima Chaoui
Emmanuelle Mouton-Barbosa
David BouyssiƩ
Kurt Boonen
Christopher J. Hughes
Lee A. Gethings
Yasset Perez-Riverol
Nic Bloomfield
Stephen Tate
Odile Schiltz
Lennart Martens
Dieter Deforce
Maarten Dhaenens
Source :
Scientific Data, SCIENTIFIC DATA
Publication Year :
2021
Publisher :
Cold Spring Harbor Laboratory, 2021.

Abstract

In the last decade, a revolution in liquid chromatography-mass spectrometry (LC-MS) based proteomics was unfolded with the introduction of dozens of novel instruments that incorporate additional data dimensions through innovative acquisition methodologies, in turn inspiring specialized data analysis pipelines. Simultaneously, a growing number of proteomics datasets have been made publicly available through data repositories such as ProteomeXchange, Zenodo and Skyline Panorama. However, developing algorithms to mine this data and assessing the performance on different platforms is currently hampered by the lack of a single benchmark experimental design. Therefore, we acquired a hybrid proteome mixture on different instrument platforms and in all currently available families of data acquisition. Here, we present a comprehensive Data-Dependent and Data-Independent Acquisition (DDA/DIA) dataset acquired using several of the most commonly used current day instrumental platforms. The dataset consists of over 700 LC-MS runs, including adequate replicates allowing robust statistics and covering over nearly 10 different data formats, including scanning quadrupole and ion mobility enabled acquisitions. Datasets are available via ProteomeXchange (PXD028735).

Details

ISSN :
20524463
Database :
OpenAIRE
Journal :
Scientific Data, SCIENTIFIC DATA
Accession number :
edsair.doi.dedup.....3625dab82d9b6fd7d919c0bb78e5a255
Full Text :
https://doi.org/10.1101/2021.11.24.469852