Empirical Statistical Model To Estimate the Accuracy of Peptide Identifications Made by MS/MS and Database Search
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Abstract
We present a statistical model to estimate the accuracy of peptide assignments to tandem mass (MS/MS) spectra made by database search applications such as SEQUEST. Employing the expectation maximization algorithm, the analysis learns to distinguish correct from incorrect database search results, computing probabilities that peptide assignments to spectra are correct based upon database search scores and the number of tryptic termini of peptides. Using SEQUEST search results for spectra generated from a sample of known protein components, we demonstrate that the computed probabilities are accurate and have high power to discriminate between correctly and incorrectly assigned peptides. This analysis makes it…
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Topics
Keywords
- Database search engine
- Chemistry
- Filter (signal processing)
- False discovery rate
- Identification (biology)
- Tandem mass spectrometry
- Pattern recognition (psychology)
- Database
UN Sustainable Development Goals
- Reduced inequalities
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