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Recognizing millions of consistently unidentified spectra across hundreds of shotgun proteomics datasets.

Authors :
Griss J
Perez-Riverol Y
Lewis S
Tabb DL
Dianes JA
Del-Toro N
Rurik M
Walzer MW
Kohlbacher O
Hermjakob H
Wang R
VizcaĆ­no JA
Source :
Nature methods [Nat Methods] 2016 Aug; Vol. 13 (8), pp. 651-656. Date of Electronic Publication: 2016 Jun 27.
Publication Year :
2016

Abstract

Mass spectrometry (MS) is the main technology used in proteomics approaches. However, on average 75% of spectra analysed in an MS experiment remain unidentified. We propose to use spectrum clustering at a large-scale to shed a light on these unidentified spectra. PRoteomics IDEntifications database (PRIDE) Archive is one of the largest MS proteomics public data repositories worldwide. By clustering all tandem MS spectra publicly available in PRIDE Archive, coming from hundreds of datasets, we were able to consistently characterize three distinct groups of spectra: 1) incorrectly identified spectra, 2) spectra correctly identified but below the set scoring threshold, and 3) truly unidentified spectra. Using a multitude of complementary analysis approaches, we were able to identify less than 20% of the consistently unidentified spectra. The complete spectrum clustering results are available through the new version of the PRIDE Cluster resource (http://www.ebi.ac.uk/pride/cluster). This resource is intended, among other aims, to encourage and simplify further investigation into these unidentified spectra.<br />Competing Interests: The authors declare no competing financial interests.

Details

Language :
English
ISSN :
1548-7105
Volume :
13
Issue :
8
Database :
MEDLINE
Journal :
Nature methods
Publication Type :
Academic Journal
Accession number :
27493588
Full Text :
https://doi.org/10.1038/nmeth.3902