DIA-Umpire: comprehensive computational framework for data-independent acquisition proteomics
The computational workflow of DIA-Umpire allows untargeted peptide identificationdirectly from DIA (data-independent acquisition) proteomics data without dependence on a spectral library for data extraction As a result of recent improvements in mass spectrometry (MS), there is increased interest in...
Gespeichert in:
Veröffentlicht in: | Nature methods 2015-03, Vol.12 (3), p.258-264 |
---|---|
Hauptverfasser: | , , , , , , |
Format: | Artikel |
Sprache: | eng |
Schlagworte: | |
Online-Zugang: | Volltext |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
Zusammenfassung: | The computational workflow of DIA-Umpire allows untargeted peptide identificationdirectly from DIA (data-independent acquisition) proteomics data without dependence on a spectral library for data extraction
As a result of recent improvements in mass spectrometry (MS), there is increased interest in data-independent acquisition (DIA) strategies in which all peptides are systematically fragmented using wide mass-isolation windows ('multiplex fragmentation'). DIA-Umpire (
http://diaumpire.sourceforge.net/
), a comprehensive computational workflow and open-source software for DIA data, detects precursor and fragment chromatographic features and assembles them into pseudo–tandem MS spectra. These spectra can be identified with conventional database-searching and protein-inference tools, allowing sensitive, untargeted analysis of DIA data without the need for a spectral library. Quantification is done with both precursor- and fragment-ion intensities. Furthermore, DIA-Umpire enables targeted extraction of quantitative information based on peptides initially identified in only a subset of the samples, resulting in more consistent quantification across multiple samples. We demonstrated the performance of the method with control samples of varying complexity and publicly available glycoproteomics and affinity purification–MS data. |
---|---|
ISSN: | 1548-7091 1548-7105 |
DOI: | 10.1038/nmeth.3255 |