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This Article Full Text Full Text (PDF) Supplemental Data All Versions of this Article: M600469-MCP200v1 6/9/1599    most recent Submit a response Alert me when this article is cited Alert me when eLetters are posted Alert me if a correction is posted Services Email this article to a friend Similar articles in this journal Similar articles in PubMed Alert me to new issues of the journal Download to citation manager Request Permissions Glossary Citing Articles Citing Articles via Google Scholar Google Scholar Articles by Balgley, B. M. Articles by Lee, C. S. Search for Related Content PubMed PubMed Citation Articles by Balgley, B. M. Articles by Lee, C. S. Social Bookmarking                      What's this?

Molecular & Cellular Proteomics 6:1599-1608, 2007.
© 2007 by The American Society for Biochemistry and Molecular Biology, Inc.

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Research

Comparative Evaluation of Tandem MS Search Algorithms Using a Target-Decoy Search Strategy^*,S

Brian M. Balgley^,, Tom Laudeman^¶, Li Yang^||, Tao Song and Cheng S. Lee^||

From the Calibrant Biosystems, Gaithersburg, Maryland 20878, ^¶ Information Technology and Communication, Academic Computing Health Sciences, University of Virginia, Charlottesville, Virginia 22908, and ^|| Department of Chemistry and Biochemistry, University of Maryland, College Park, Maryland 20742

Peptide identification of tandem mass spectra by a variety of available search algorithms forms the foundation for much of modern day mass spectrometry-based proteomics. Despite the critical importance of proper evaluation and interpretation of the results generated by these algorithms there is still little consistency in their application or understanding of their similarities and differences. A survey was conducted of four tandem mass spectrometry peptide identification search algorithms, including Mascot, Open Mass Spectrometry Search Algorithm, Sequest, and X! Tandem. The same input data, search parameters, and sequence library were used for the searches. Comparisons were based on commonly used scoring methodologies for each algorithm and on the results of a target-decoy approach to sequence library searching. The results indicated that there is little difference in the output of the algorithms so long as consistent scoring procedures are applied. The results showed that some commonly used scoring procedures may lead to excessive false discovery rates. Finally an alternative method for the determination of an optimal cutoff threshold is proposed.

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