Binary Classifier for Computing Posterior Error Probabilities in MetaMorpheus

MetaMorpheus 中用于计算后验误差概率的二元分类器

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作者:Michael R Shortreed, Robert J Millikin, Lei Liu, Zach Rolfs, Rachel M Miller, Leah V Schaffer, Brian L Frey, Lloyd M Smith

Abstract

MetaMorpheus is a free, open-source software program for the identification of peptides and proteoforms from data-dependent acquisition tandem MS experiments. There is inherent uncertainty in these assignments for several reasons, including the limited overlap between experimental and theoretical peaks, the m/z uncertainty, and noise peaks or peaks from coisolated peptides that produce false matches. False discovery rates provide only a set-wise approximation for incorrect spectrum matches. Here we implemented a binary decision tree calculation within MetaMorpheus to compute a posterior error probability, which provides a measure of uncertainty for each peptide-spectrum match. We demonstrate its utility for increasing identifications and resolving ambiguities in bottom-up, top-down, proteogenomic, and nonspecific digestion searches.

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