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Trans-Proteomic Pipeline supports and improves analysis of electron transfer dissociation datasets

Electron transfer dissociation (ETD) is an alternative fragmentation technique to collision induced dissociation (CID) that has recently become commercially available. ETD has several advantages over CID. It is less prone to fragmenting amino acid side chains, especially those that are modified, thu...

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Bibliographic Details
Published in:Proteomics (Weinheim) 2010-03, Vol.10 (6), p.1190-1195
Main Authors: Deutsch, Eric W., Shteynberg, David, Lam, Henry, Sun, Zhi, Eng, Jimmy K., Carapito, Christine, von Haller, Priska D., Tasman, Natalie, Mendoza, Luis, Farrah, Terry, Aebersold, Ruedi
Format: Article
Language:English
Online Access:Get full text
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Summary:Electron transfer dissociation (ETD) is an alternative fragmentation technique to collision induced dissociation (CID) that has recently become commercially available. ETD has several advantages over CID. It is less prone to fragmenting amino acid side chains, especially those that are modified, thus yielding fragment ion spectra with more uniform peak intensities. Further, precursor ions of longer peptides and higher charge states can be fragmented and identified. However, analysis of ETD spectra has a few important differences that require the optimization of the software packages used for the analysis of CID data, or the development of specialized tools. We have adapted the Trans-Proteomic Pipeline (TPP) to process ETD data. Specifically, we have added support for fragment ion spectra from high charge precursors, compatibility with charge-state estimation algorithms, provisions for the use of the Lys-C protease, capabilities for ETD spectrum library building, and updates to the data formats to differentiate CID and ETD spectra. We show the results of processing datasets from several different types of ETD instruments and demonstrate that application of the ETD-enhanced TPP can increase the number of spectrum identifications at a fixed false discovery rate by as much as 100% over native output from a single sequence search engine.
ISSN:1615-9853
1615-9861
DOI:10.1002/pmic.200900567