OLAV-PMF: a novel scoring scheme for high-throughput peptide mass fingerprinting.
ABSTRACT We propose a new type of probabilistic scoring scheme framework for protein identification from peptide masses. We first introduce the framework itself and explain its requirements. In a second part, we describe a particular implementation and test it on a data set of more than 8000 MALDI-TOF spectra with known contents. Doing so, we also compare its performance to two widely used scoring schemes, thereby demonstrating the potential of the proposed approach.
Article: Charge prediction machine: tool for inferring precursor charge states of electron transfer dissociation tandem mass spectra.[show abstract] [hide abstract]
ABSTRACT: Electron transfer dissociation (ETD) can dissociate highly charged ions. Efficient analysis of ions dissociated with ETD requires accurate determination of charge states for calculation of molecular weight. We created an algorithm to assign the charge state of ions often used for ETD. The program, Charge Prediction Machine (CPM), uses Bayesian decision theory to account for different charge reduction processes encountered in ETD and can also handle multiplex spectra. CPM correctly assigned charge states to 98% of the 13,097 MS2 spectra from a combined data set of four experiments. In a comparison between CPM and a competing program, Charger (ThermoFisher), CPM produced half the mistakes.Analytical Chemistry 03/2009; 81(5):1996-2003. · 5.86 Impact Factor
Article: Evaluation of the Consensus of Four Peptide Identification Algorithms for Tandem Mass Spectrometry Based Proteomics.[show abstract] [hide abstract]
ABSTRACT: The availability of different scoring schemes and filter settings of protein database search algorithms has greatly expanded the number of search methods for identifying candidate peptides from MS/MS spectra. We have previously shown that consensus-based methods that combine three search algorithms yield higher sensitivity and specificity compared to the use of a single search engine (individual method). We hypothesized that union of four search engines (Sequest, Mascot, X!Tandem and Phenyx) can further enhance sensitivity and specificity. ROC plots were generated to measure the sensitivity and specificity of 5460 consensus methods derived from the same dataset. We found that Mascot outperformed individual methods for sensitivity and specificity, while Phenyx performed the worst. The union consensus methods generally produced much higher sensitivity, while the intersection consensus methods gave much higher specificity. The union methods from four search algorithms modestly improved sensitivity, but not specificity, compared to union methods that used three search engines. This suggests that a strategy based on specific combination of search algorithms, instead of merely 'as many search engines as possible', may be key strategy for success with peptide identification. Lastly, we provide strategies for optimizing sensitivity or specificity of peptide identification in MS/MS spectra for different user-specific conditions.Journal of Proteomics & Bioinformatics 02/2010; 3:39-47.
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ABSTRACT: Protein identification by mass spectrometry is widely used in biological research. Here, we describe how the global proteome machine (GPM) can be used for protein identification and for validation of the results. We cover identification by searching protein sequence collections and spectral libraries as well as validation of the results using expectation values, rho-diagrams, and spectrum databases.Methods in molecular biology (Clifton, N.J.) 01/2010; 673:189-202.