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A multicenter study benchmarks software tools for label-free proteome quantification

Nature biotechnology. Bd. 34. H. 11. New York, NY: Nature America 2016 S. 1130 - 1136

Erscheinungsjahr: 2016

ISBN/ISSN: 1087-0156 ; 1546-1696

Publikationstyp: Zeitschriftenaufsatz

Sprache: Englisch

GeprüftBibliothek

Inhaltszusammenfassung


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 ...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 (DIA) for label-free protein quantification. We analyzed high-complexity test data sets from hybrid proteome samples of defined quantitative composition acquired on two different MS instruments using different SWATH isolation-window setups. For consistent evaluation, we developed LFQbench, an R package, to calculate metrics of precision and accuracy in label-free quantitative MS and report the identification performance, robustness and specificity of each software tool. Our reference data sets enabled developers to improve their software tools. After optimization, all tools provided highly convergent identification and reliable quantification performance, underscoring their robustness for label-free quantitative proteomics.» weiterlesen» einklappen

Autoren


Navarro, Pedro (Autor)
Kuharev, Jörg (Autor)
Gillet, Ludovic C. (Autor)
Bernhardt, Oliver M. (Autor)
MacLean, Brendan (Autor)
Röst, Hannes L. (Autor)
Tate, Stephen A. (Autor)
Tsou, Chih-Chiang (Autor)
Reiter, Lukas (Autor)
Distler, Ute (Autor)
Rosenberger, George (Autor)
Perez-Riverol, Yasset (Autor)
Nesvizhskii, Alexey I. (Autor)
Aebersold, Ruedi (Autor)
Tenzer, Stefan (Autor)

Klassifikation


DDC Sachgruppe:
Medizin