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Enhanced Protein Parsimony Method for Peptide Identification Sensitivity Improvement

This method selects the smallest set of proteins covering all identified peptides using a sensible principle to avoid bad consequences for FDR filtered identifications. By maximizing covered peptides and considering unique peptides per protein, it significantly improves identification sensitivity.

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Enhanced Protein Parsimony Method for Peptide Identification Sensitivity Improvement

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  1. Generalized Protein Parsimony Nathan Edwards Department of Biochemistry and Molecular & Cellular Biology Georgetown University Medical Center

  2. Traditional Protein Parsimony • Select the smallest set of proteins that cover all identified peptides. • Sensible principle, implies • Eliminate equivalent/subset proteins • Unique peptides force proteins into solution • Bad consequences for FDR filtered ids • Impact most tools, even probability based ones

  3. Must ignore some PSMs • Improving peptide identification sensitivitymakes things worse! • False PSMs don't cluster PSMs PSMs 2x Proteins 10%

  4. Must ignore some PSMs • A single additionalpeptideshould not force proteins into the solution

  5. Generalized Protein Parsimony • Weight peptides by number of PSMs • Constrainunique peptides per protein • Maximize covered peptides (PSMs) • Can match filtering FDR to uncovered PSMs • Readily solved by branch-and-bound • Reduces to traditional protein parsimony

  6. Match FDR to uncovered PSMs Traditional Parsimony at 1% FDR: 1085 (609 2+-Unique) Proteins

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