ScanRanker: Quality Assessment of Tandem Mass Spectra via Sequence Tagging

In shotgun proteomics, protein identification by tandem mass spectrometry relies on bioinformatics tools. Despite recent improvements in identification algorithms, a significant number of high quality spectra remain unidentified for various reasons. Here we present ScanRanker, an open-source tool th...

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Bibliographic Details
Published in:Journal of proteome research 2011-07, Vol.10 (7), p.2896-2904
Main Authors: Ma, Ze-Qiang, Chambers, Matthew C, Ham, Amy-Joan L, Cheek, Kristin L, Whitwell, Corbin W, Aerni, Hans-Rudolf, Schilling, Birgit, Miller, Aaron W, Caprioli, Richard M, Tabb, David L
Format: Article
Language:English
Subjects:
Algorithms
Animals
Chromatography, Liquid
Computational Biology
Databases, Protein
Humans
Peptide Fragments - analysis
Peptide Fragments - chemistry
Proteins - analysis
Proteins - chemistry
Proteomics - methods
Research Design
Sequence Analysis, Protein
Tandem Mass Spectrometry - methods
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Summary:In shotgun proteomics, protein identification by tandem mass spectrometry relies on bioinformatics tools. Despite recent improvements in identification algorithms, a significant number of high quality spectra remain unidentified for various reasons. Here we present ScanRanker, an open-source tool that evaluates the quality of tandem mass spectra via sequence tagging with reliable performance in data from different instruments. The superior performance of ScanRanker enables it not only to find unassigned high quality spectra that evade identification through database search but also to select spectra for de novo sequencing and cross-linking analysis. In addition, we demonstrate that the distribution of ScanRanker scores predicts the richness of identifiable spectra among multiple LC–MS/MS runs in an experiment, and ScanRanker scores assist the process of peptide assignment validation to increase confident spectrum identifications. The source code and executable versions of ScanRanker are available from http://fenchurch.mc.vanderbilt.edu.
ISSN:1535-3893
1535-3907
DOI:10.1021/pr200118r