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Improving Peptide Probability Modeling in Scaffold 4

Improving Peptide Probability Modeling in Scaffold 4. Brian C. Searle brian.searle@proteomesoftware.com Scaffold Users Meeting, 2013. Creative Commons Attribution. Scaffold 4 Improvements. Probability Estimation using LFDR Target/Decoy Classification of multiple scores

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Improving Peptide Probability Modeling in Scaffold 4

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  1. Improving Peptide Probability Modeling in Scaffold 4 Brian C. Searle brian.searle@proteomesoftware.com Scaffold Users Meeting, 2013 Creative Commons Attribution

  2. Scaffold 4 Improvements • Probability Estimation using LFDR • Target/Decoy Classification of multiple scores • Delta Mass Error Modeling Improvements • Requires Target/Decoy analysis (1:1 … 1:10)

  3. “Incorrect” “Correct”

  4. Number of Identified Proteins Protein-Level False Discovery Rate

  5. Number of Identified Proteins Protein-Level False Discovery Rate

  6. XCorr DeltaCN % Ions Identified …

  7. XCorr DeltaCN % Ions Identified …

  8. XCorr DeltaCN % Ions Identified

  9. Naïve Bayes Classifier • Trained to each data set • Simple (can calculate with a formula, no magic!) • Robust to over-fitting

  10. Number of Identified Proteins Protein-Level False Discovery Rate

  11. Number of Identified Proteins Protein-Level False Discovery Rate

  12. Probability the ID is Correct Probability the ID is Wrong

  13. Number of Identified Proteins Protein-Level False Discovery Rate

  14. Number of Identified Proteins Protein-Level False Discovery Rate

  15. 1% Peptide FDR Number of Identified Proteins

  16. 1% Peptide FDR > 10% Protein FDR?!? Number of Identified Proteins Protein-Level FDR

  17. New Search Engines? • Difficult to add new search engines with PeptideProphet (new seeds) • Easy to add with Naïve Bayes / LFDR • mzIdentML interchange (HUPO standard)

  18. New Search Enginesin Scaffold 4 • Peaks • Byonic • Myrimatch (Tabb Lab) • SQID (Wysocki Lab) • MS-GF+ (Pevzner Lab) • MS-Amanda (Mechtler Lab, PD)

  19. New Search Enginesin Scaffold 4 • Peaks • Byonic • Myrimatch (Tabb Lab) • SQID (Wysocki Lab) • MS-GF+ (Pevzner Lab) • MS-Amanda (Mechtler Lab, PD) • ... Any engine with decoys & mzIdentML!

  20. Scaffold 4 Improvements • New Naïve Bayes / LFDR Probabilities • Probability Estimation using LFDR • Target/Decoy Classification • Delta Mass Error Modeling • “Next generation” search engine interpretation • New mzIdentML File Loading • Several newly supported search engines • Any search engine with decoys

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