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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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Abstract

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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Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:07 Faculty of Science > Institute of Molecular Life Sciences
DDC:570 Life sciences; biology
Language:English
Date:2011
Deposited On:05 Apr 2011 15:06
Last Modified:16 Jul 2014 13:19
Publisher:Nature Publishing Group
ISSN:1548-7091
Publisher DOI:10.1038/nmeth.1584
PubMed ID:21423193

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