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EBP, a program for protein identification using multiple tandem mass spectrometry datasets.

Thomas S Price·Margaret B Lucitt·Weichen Wu·David J Austin·Angel Pizarro·Anastasia K Yocum·Ian A Blair·Garret A FitzGerald·Tilo Grosser
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Abstract

MS/MS combined with database search methods can identify the proteins present in complex mixtures. High throughput methods that infer probable peptide sequences from enzymatically digested protein samples create a challenge in how best to aggregate the evidence for candidate proteins. Typically the results of multiple technical and/or biological replicate experiments must be combined to maximize sensitivity. We present a statistical method for estimating probabilities of protein expression that integrates peptide sequence identifications from multiple search algorithms and replicate experimental runs. The method was applied to create a repository of 797 non-homologous zebrafish (Danio rerio) proteins, at an empirically validated false identification rate under 1%, as a resource for the development of targeted quantitative proteomics assays. We have implemented this statistical method as an analytic module that can be integrated with an existing suite of open-source proteomics software.

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AlgorithmsAnimalsChromatography, LiquidEmbryo, NonmammalianFish ProteinsModels, StatisticalProteomicsTandem Mass SpectrometryZebrafishJournal ArticleResearch Support, N.I.H., ExtramuralResearch Support, Non-U.S. Gov't

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Thomas S Price, Margaret B Lucitt, Weichen Wu, David J Austin, Angel Pizarro, Anastasia K Yocum, Ian A Blair, Garret A FitzGerald, Tilo Grosser. 2006-12-12. EBP, a program for protein identification using multiple tandem mass spectrometry datasets.. https://doi.org/10.1074/mcp.t600049-mcp200

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