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Assessment of MS/MS search algorithms with parent-protein profiling
Miin S Lin1, Justin J Cherny, Claire T Fournier
1Department of Biology and ‡Department of Mathematics and Computer Science, Wesleyan University Middletown Connecticut 06459, United States.
Abstract:
Peptide mass spectrometry relies crucially on algorithms that match peptides to spectra. We describe a method to evaluate the accuracy of these algorithms based on the masses of parent proteins before trypsin endoprotease digestion. Measurement of conformance to parent proteins provides a score for comparison of the performances of different algorithms as well as alternative parameter settings for a given algorithm. Tracking of conformance scores for spectrum matches to proteins with progressively lower expression levels revealed that conformance scores are not uniform within data sets but are significantly lower for less abundant proteins. Similarly peptides with lower algorithm peptide-spectrum match scores have lower conformance. Although peptide mass spectrometry data is typically filtered through decoy analysis to ensure a low false discovery rate, this analysis confirms that the filtered data should not be considered as having a uniform confidence. The analysis suggests that use of different algorithms and multiple standardized parameter settings of these algorithms can increase significantly the numbers of peptides identified. This data set can be used as a resource for future algorithm assessment.
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