Journal of Proteome Research · 2011 · 41 citations · 29 references
Life SciencesBiochemistryBioinformaticsMass Spectrometric AnalysisProteomicsProteomics InformaticsMass Spectrometry Data AnalysisMass Spectrometry-based ProteomicsPeptide AnalysisProtein IdentificationProtein InferenceProtein QuantificationInference In Shotgun ProteomicsPeptide-protein InferencePeptide-to-protein InferenceProtein Group InferenceProtein Inference AlgorithmsProtein Quantification InferenceTandem Mass SpectrometryTandem Mass Spectrometry Analysis
When analyzing proteins in complex samples using tandem mass spectrometry of peptides generated by proteolysis, the inference of proteins can be ambiguous, even with well-validated peptides. Unresolved questions include whether to show all possible proteins vs a minimal list, what to do when proteins are inferred ambiguously, and how to quantify peptides that bridge multiple proteins, each with distinguishing evidence. Here we describe IsoformResolver, a peptide-centric protein inference algorithm that clusters proteins in two ways, one based on peptides experimentally identified from MS/MS spectra, and the other based on peptides derived from an in silico digest of the protein database. MS/MS-derived protein groups report minimal list proteins in the context of all possible proteins, without redundantly listing peptides. In silico-derived protein groups pull together functionally related proteins, providing stable identifiers. The peptide-centric grouping strategy used by IsoformResolver allows proteins to be displayed together when they share peptides in common, providing a comprehensive yet concise way to organize protein profiles. It also summarizes information on spectral counts and is especially useful for comparing results from multiple LC-MS/MS experiments. Finally, we examine the relatedness of proteins within IsoformResolver groups and compare its performance to other protein inference software.
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