Dataset Information


LFQbench enables a multi-centered benchmark study demonstrating robust proteomic label-free quantification

ABSTRACT: The consistent and accurate quantification of proteins is a challenging task for mass spectrometry (MS)-based proteomics. SWATH-MS uses data-independent acquisition (DIA) for label-free quantification. Here we evaluated five software tools for processing SWATH-MS data: OpenSWATH, SWATH2.0, Skyline, Spectronaut, DIA-Umpire, in collaboration with the respective developers to ensure an optimal use of each tool. We analyzed data from hybrid proteome samples of defined quantitative composition acquired on two different MS instruments applying different SWATH isolation windows setups. Using the resulting high-complexity datasets we benchmarked precision and accuracy of quantification and evaluated identification performance, robustness and specificity of each software tool. To consistently evaluate the high complexity datasets, we developed the LFQbench R-package. LFQbench results enabled developers to improve their software tools, thereby underlining the value of the reference datasets for software development and benchmarking. All tools provided highly convergent identification and reliable quantification performance, underscoring their robustness for label-free quantitative proteomics.


ORGANISM(S): Homo Sapiens (human) Escherichia Coli Saccharomyces Cerevisiae (baker's Yeast)

SUBMITTER: Yasset Perez-Riverol  

LAB HEAD: Stefan Tenzer

PROVIDER: PXD002952 | Pride | 2016-09-27


Dataset's files

altmetric image


Consistent and accurate quantification of proteins by mass spectrometry (MS)-based proteomics depends on the performance of instruments, acquisition methods and data analysis software. In collaboration with the software developers, we evaluated OpenSWATH, SWATH 2.0, Skyline, Spectronaut and DIA-Umpire, five of the most widely used software methods for processing data from sequential window acquisition of all theoretical fragment-ion spectra (SWATH)-MS, which uses data-independent acquisition (DI  ...[more]

Similar Datasets

2019-10-21 | PXD009597 | Pride
2016-12-06 | PXD001576 | Pride
2020-10-19 | PXD019446 | Pride
2022-01-14 | PXD030778 | Pride
2016-12-06 | PXD002869 | Pride
2015-01-26 | PXD001126 | Pride
2017-03-09 | PXD003973 | Pride
2022-05-05 | PXD028618 | Pride
2017-02-28 | PXD005234 | Pride
2018-10-17 | PXD004589 | Pride