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Analysis of the resolution limitations of peptide identification algorithms

Niklaas Colaert UGent, Sven Degroeve UGent, Kenny Helsens UGent and Lennart Martens UGent (2011) JOURNAL OF PROTEOME RESEARCH. 10(12). p.5555-5561
abstract
Proteome identification using peptide-centric proteomics techniques is a routinely used analysis technique. One of the most powerful and popular methods for the identification of peptides from MS/MS spectra is protein database matching using search engines. Significance thresholding through false discovery rate (FDR) estimation by target/decoy searches is used to ensure the retention of predominantly confident assignments of MS/MS spectra to peptides. However, shortcomings have become apparent when such decoy searches are used to estimate the FDR. To study these shortcomings, we here introduce a novel kind of decoy database that contains isobaric mutated versions of the peptides that were identified in the original search. Because of the supervised way in which the entrapment sequences are generated, we call this a directed decoy database. Since the peptides found in our directed decoy database are thus specifically designed to look quite similar to the forward identifications, the limitations of the existing search algorithms in making correct calls in such strongly confusing situations can be analyzed. Interestingly, for the vast majority of confidently identified peptide identifications, a directed decoy peptide-to-spectrum match can be found that has a better or equal match score than the forward match score, highlighting an important issue in the interpretation of peptide identifications in present-day high-throughput proteomics.
Please use this url to cite or link to this publication:
author
organization
year
type
journalArticle (original)
publication status
published
subject
keyword
PARSE, RATES, STANDARD, PROTEOMICS, DECOY DATABASES, SPECTROMETRY DATA, PROTEIN IDENTIFICATION, OPEN-SOURCE LIBRARY, TANDEM MASS-SPECTRA, mass spectrometry, bioinformatics, proteomics
journal title
JOURNAL OF PROTEOME RESEARCH
J. Proteome Res.
volume
10
issue
12
pages
5555 - 5561
Web of Science type
Article
Web of Science id
000297537200027
JCR category
BIOCHEMICAL RESEARCH METHODS
JCR impact factor
5.113 (2011)
JCR rank
10/72 (2011)
JCR quartile
1 (2011)
ISSN
1535-3893
DOI
10.1021/pr200913a
project
Bioinformatics: from nucleotids to networks (N2N)
language
English
UGent publication?
yes
classification
A1
copyright statement
I have transferred the copyright for this publication to the publisher
id
1979312
handle
http://hdl.handle.net/1854/LU-1979312
date created
2012-01-05 16:35:34
date last changed
2016-12-19 15:45:28
@article{1979312,
  abstract     = {Proteome identification using peptide-centric proteomics techniques is a routinely used analysis technique. One of the most powerful and popular methods for the identification of peptides from MS/MS spectra is protein database matching using search engines. Significance thresholding through false discovery rate (FDR) estimation by target/decoy searches is used to ensure the retention of predominantly confident assignments of MS/MS spectra to peptides. However, shortcomings have become apparent when such decoy searches are used to estimate the FDR. To study these shortcomings, we here introduce a novel kind of decoy database that contains isobaric mutated versions of the peptides that were identified in the original search. Because of the supervised way in which the entrapment sequences are generated, we call this a directed decoy database. Since the peptides found in our directed decoy database are thus specifically designed to look quite similar to the forward identifications, the limitations of the existing search algorithms in making correct calls in such strongly confusing situations can be analyzed. Interestingly, for the vast majority of confidently identified peptide identifications, a directed decoy peptide-to-spectrum match can be found that has a better or equal match score than the forward match score, highlighting an important issue in the interpretation of peptide identifications in present-day high-throughput proteomics.},
  author       = {Colaert, Niklaas and Degroeve, Sven and Helsens, Kenny and Martens, Lennart},
  issn         = {1535-3893},
  journal      = {JOURNAL OF PROTEOME RESEARCH},
  keyword      = {PARSE,RATES,STANDARD,PROTEOMICS,DECOY DATABASES,SPECTROMETRY DATA,PROTEIN IDENTIFICATION,OPEN-SOURCE LIBRARY,TANDEM MASS-SPECTRA,mass spectrometry,bioinformatics,proteomics},
  language     = {eng},
  number       = {12},
  pages        = {5555--5561},
  title        = {Analysis of the resolution limitations of peptide identification algorithms},
  url          = {http://dx.doi.org/10.1021/pr200913a},
  volume       = {10},
  year         = {2011},
}

Chicago
Colaert, Niklaas, Sven Degroeve, Kenny Helsens, and Lennart Martens. 2011. “Analysis of the Resolution Limitations of Peptide Identification Algorithms.” Journal of Proteome Research 10 (12): 5555–5561.
APA
Colaert, N., Degroeve, S., Helsens, K., & Martens, L. (2011). Analysis of the resolution limitations of peptide identification algorithms. JOURNAL OF PROTEOME RESEARCH, 10(12), 5555–5561.
Vancouver
1.
Colaert N, Degroeve S, Helsens K, Martens L. Analysis of the resolution limitations of peptide identification algorithms. JOURNAL OF PROTEOME RESEARCH. 2011;10(12):5555–61.
MLA
Colaert, Niklaas, Sven Degroeve, Kenny Helsens, et al. “Analysis of the Resolution Limitations of Peptide Identification Algorithms.” JOURNAL OF PROTEOME RESEARCH 10.12 (2011): 5555–5561. Print.