The DOI matches its Crossref record; 37 of the 37 references it cites were found in a registry or an index.
An evaluation, comparison, and accurate benchmarking of several publicly available MS/MS search algorithms: Sensitivity and specificity analysis
Open accessAbstract
MS/MS and associated database search algorithms are essential proteomic tools for identifying peptides. Due to their widespread use, it is now time to perform a systematic analysis of the various algorithms currently in use. Using blood specimens used in the HUPO Plasma Proteome Project, we have evaluated five search algorithms with respect to their sensitivity and specificity, and have also accurately benchmarked them based on specified false‐positive (FP) rates. Spectrum Mill and SEQUEST performed well in terms of sensitivity, but were inferior to MASCOT, X!Tandem, and Sonar in terms of specificity. Overall, MASCOT, a probabilistic search algorithm, correctly identified most peptides based on a specified FP rate. The rescoring algorithm, PeptideProphet, enhanced the overall performance of the SEQUEST algorithm, as well as provided predictable FP error rates. Ideally, score thresholds should be calculated for each peptide spectrum or minimally, derived from a reversed‐sequence search as demonstrated in this study based on a validated data set. The availability of open‐source search algorithms, such as X!Tandem, makes it feasible to further improve the validation process (manual or automatic) on the basis of “consensus scoring”, i.e., the use of multiple (at least two) search algorithms to reduce the number of FPs.∁
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Perkins, D. N., Pappin, D. J. C., Creasy, D. M., & Cottrell, J. S. (1999) · Electrophoresis · doi:10.1002/(sici)1522-2683(19991201)20:18<3551::aid-elps3551>3.0.co;2-2 · Cited by 8,203
Eng, J. K., McCormack, A. L., & Yates, J. R. (1994) · Journal of the American Society for Mass Spectrometry · doi:10.1016/1044-0305(94)80016-2 · Cited by 6,484
Self-citationKeller, A., Nesvizhskii, A. I., Kolker, E., & Aebersold, R. (2002) · Analytical Chemistry · doi:10.1021/ac025747h · Cited by 4,830
A Statistical Model for Identifying Proteins by Tandem Mass Spectrometry
Nesvizhskii, A. I., Keller, A., Kolker, E., & Aebersold, R. (2003) · Analytical Chemistry · doi:10.1021/ac0341261 · Cited by 4,809
Large-scale analysis of the yeast proteome by multidimensional protein identification technology
Washburn, M. P., Wolters, D., & Yates, J. R. (2001) · Nature Biotechnology · doi:10.1038/85686 · Cited by 4,752
Anderson, N. L., & Anderson, N. G. (2002) · Molecular & Cellular Proteomics · doi:10.1074/mcp.r200007-mcp200 · Cited by 4,414
TANDEM: matching proteins with tandem mass spectra
Craig, R., & Beavis, R. C. (2004) · Bioinformatics · doi:10.1093/bioinformatics/bth092 · Cited by 2,536
Direct analysis of protein complexes using mass spectrometry
Link, A. J., Eng, J., Schieltz, D. M., Carmack, E., Mize, G. J., Morris, D. R., Garvik, B. M., & Yates, J. R. (1999) · Nature Biotechnology · doi:10.1038/10890 · Cited by 2,237
Self-citationPeng, J., Elias, J. E., Thoreen, C. C., Licklider, L. J., & Gygi, S. P. (2003) · Journal of Proteome Research · doi:10.1021/pr025556v · Cited by 1,647
Rapid identification of proteins by peptide-mass fingerprinting
Pappin, D. J. C., Hojrup, P., & Bleasby, A. J. (1993) · Current Biology · doi:10.1016/0960-9822(93)90195-t · Cited by 1,615
Cited by
Shilov, I. V., Seymour, S. L., Patel, A. A., Loboda, A., Tang, W. H., Keating, S. P., Hunter, C. L., Nuwaysir, L. M., & Schaeffer, D. A. (2007) · Molecular & Cellular Proteomics · doi:10.1074/mcp.t600050-mcp200 · Cited by 1,298
Zhang, J., Xin, L., Shan, B., Chen, W., Xie, M., Yuen, D., Zhang, W., Zhang, Z., Lajoie, G. A., & Ma, B. (2012) · Molecular & Cellular Proteomics · doi:10.1074/mcp.m111.010587 · Cited by 1,081
Omenn, G. S., States, D. J., Adamski, M., Blackwell, T. W., Menon, R., Hermjakob, H., Apweiler, R., Haab, B. B., Simpson, R. J., Eddes, J. S., et al. (2005) · PROTEOMICS · doi:10.1002/pmic.200500358 · Cited by 787
Self-citationAnalysis and validation of proteomic data generated by tandem mass spectrometry
Nesvizhskii, A. I., Vitek, O., & Aebersold, R. (2007) · Nature Methods · doi:10.1038/nmeth1088 · Cited by 629
Tabb, D. L., Vega-Montoto, L., Rudnick, P. A., Variyath, A. M., Ham, A.-J. L., Bunk, D. M., Kilpatrick, L. E., Billheimer, D. D., Blackman, R. K., Cardasis, H. L., et al. (2010) · Journal of Proteome Research · doi:10.1021/pr9006365 · Cited by 551
Metadata
- Authors
- Kapp, E. A., Schütz, F., Connolly, L. M., Chakel, J. A., Meza, J. E., Miller, C. A., Fenyo, D., Eng, J. K., Adkins, J. N., Omenn, G. S., & Simpson, R. J.
- Venue
- PROTEOMICS
- Publisher
- Wiley
- Published
- 2005-08
- Volume
- 5
- Issue
- 13
- Pages
- 3475-3490
- ISSN
- 1615-9853 (ISSN-L)
- 1615-9861
- OpenAlex
- W2148632411
- Cited by
- 344
- References
- 37
- FWCI
- 15.32
- Type
- journal article
- Language
- en
- Open access
- bronze
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- Kapp, E. A., Schütz, F., Connolly, L. M., Chakel, J. A., Meza, J. E., Miller, C. A., Fenyo, D., Eng, J. K., Adkins, J. N., Omenn, G. S., & Simpson, R. J. (2005). An evaluation, comparison, and accurate benchmarking of several publicly available MS/MS search algorithms: Sensitivity and specificity analysis. PROTEOMICS. https://doi.org/10.1002/pmic.200500126
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