Permanent URL to this publication: http://dx.doi.org/10.5167/uzh-47865
Reiter, L; Rinner, O; Picotti, P; Hüttenhain, R; Beck, M; Brusniak, M Y; Hengartner, M O; Aebersold, R (2011). mProphet: automated data processing and statistical validation for large-scale SRM experiments. Nature Methods, 8(5):430-435.
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Selected 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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|Item Type:||Journal Article, refereed, original work|
|Communities & Collections:||07 Faculty of Science > Institute of Molecular Life Sciences|
|Dewey Decimal Classification:||570 Life sciences; biology|
|Deposited On:||05 Apr 2011 15:06|
|Last Modified:||05 Apr 2016 14:54|
|Publisher:||Nature Publishing Group|
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