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RAId_aPS: MS/MS Analysis with Multiple Scoring Functions and Spectrum-Specific Statistics

Author

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  • Gelio Alves
  • Aleksey Y Ogurtsov
  • Yi-Kuo Yu

Abstract

Statistically meaningful comparison/combination of peptide identification results from various search methods is impeded by the lack of a universal statistical standard. Providing an -value calibration protocol, we demonstrated earlier the feasibility of translating either the score or heuristic -value reported by any method into the textbook-defined -value, which may serve as the universal statistical standard. This protocol, although robust, may lose spectrum-specific statistics and might require a new calibration when changes in experimental setup occur. To mitigate these issues, we developed a new MS/MS search tool, RAId_aPS, that is able to provide spectrum-specific -values for additive scoring functions. Given a selection of scoring functions out of RAId score, K-score, Hyperscore and XCorr, RAId_aPS generates the corresponding score histograms of all possible peptides using dynamic programming. Using these score histograms to assign -values enables a calibration-free protocol for accurate significance assignment for each scoring function. RAId_aPS features four different modes: (i) compute the total number of possible peptides for a given molecular mass range, (ii) generate the score histogram given a MS/MS spectrum and a scoring function, (iii) reassign -values for a list of candidate peptides given a MS/MS spectrum and the scoring functions chosen, and (iv) perform database searches using selected scoring functions. In modes (iii) and (iv), RAId_aPS is also capable of combining results from different scoring functions using spectrum-specific statistics. The web link is http://www.ncbi.nlm.nih.gov/CBBresearch/Yu/raid_aps/index.html. Relevant binaries for Linux, Windows, and Mac OS X are available from the same page.

Suggested Citation

  • Gelio Alves & Aleksey Y Ogurtsov & Yi-Kuo Yu, 2010. "RAId_aPS: MS/MS Analysis with Multiple Scoring Functions and Spectrum-Specific Statistics," PLOS ONE, Public Library of Science, vol. 5(11), pages 1-18, November.
  • Handle: RePEc:plo:pone00:0015438
    DOI: 10.1371/journal.pone.0015438
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    Cited by:

    1. Malik N Akhtar & Bruce R Southey & Per E Andrén & Jonathan V Sweedler & Sandra L Rodriguez-Zas, 2014. "Accurate Assignment of Significance to Neuropeptide Identifications Using Monte Carlo K-Permuted Decoy Databases," PLOS ONE, Public Library of Science, vol. 9(10), pages 1-13, October.

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