A probability-based approach for high-throughput protein phosphorylation analysis and site localization View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2006-10

AUTHORS

Sean A Beausoleil, Judit Villén, Scott A Gerber, John Rush, Steven P Gygi

ABSTRACT

Data analysis and interpretation remain major logistical challenges when attempting to identify large numbers of protein phosphorylation sites by nanoscale reverse-phase liquid chromatography/tandem mass spectrometry (LC-MS/MS) (Supplementary Figure 1 online). In this report we address challenges that are often only addressable by laborious manual validation, including data set error, data set sensitivity and phosphorylation site localization. We provide a large-scale phosphorylation data set with a measured error rate as determined by the target-decoy approach, we demonstrate an approach to maximize data set sensitivity by efficiently distracting incorrect peptide spectral matches (PSMs), and we present a probability-based score, the Ascore, that measures the probability of correct phosphorylation site localization based on the presence and intensity of site-determining ions in MS/MS spectra. We applied our methods in a fully automated fashion to nocodazole-arrested HeLa cell lysate where we identified 1,761 nonredundant phosphorylation sites from 491 proteins with a peptide false-positive rate of 1.3%. More... »

PAGES

1285-1292

Identifiers

URI

http://scigraph.springernature.com/pub.10.1038/nbt1240

DOI

http://dx.doi.org/10.1038/nbt1240

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1011188595

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/16964243


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