mProphet: automated data processing and statistical validation for large-scale SRM experiments

TitlemProphet: automated data processing and statistical validation for large-scale SRM experiments
Publication TypeJournal Article
Year of Publication2011
AuthorsReiter L, Rinner O, Picotti P, Huttenhain R, Beck M, Brusniak MY, Hengartner MO, Aebersold R
JournalNat Methods
Date PublishedMar 20
PMID21423193
AbstractSelected reaction monitoring (SRM) is a targeted mass spectrometric method that is increasingly used in proteomics for the detection and quantification of sets of preselected proteins at high sensitivity, reproducibility and accuracy. Currently, data from SRM measurements are mostly evaluated subjectively by manual inspection on the basis of ad hoc criteria, precluding the consistent analysis of different data sets and an objective assessment of their error rates. Here we present mProphet, a fully automated system that computes accurate error rates for the identification of targeted peptides in SRM data sets and maximizes specificity and sensitivity by combining relevant features in the data into a statistical model.

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