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Lookup NU author(s): Dr Howsun Jow,
Professor Richard Boys,
Professor Darren Wilkinson
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In this paper we develop a Bayesian statistical inference approach to the unified analysis of isobaric labelled MS/MS proteomic data across multiple experiments. An explicit probabilistic model of the log-intensity of the isobaric labels' reporter ions across multiple pre-defined groups and experiments is developed. This is then used to develop a full Bayesian statistical methodology for the identification of differentially expressed proteins, with respect to a control group, across multiple groups and experiments. This methodology is implemented and then evaluated on simulated data and on two model experimental datasets (for which the differentially expressed proteins are known) that use a TMT labelling protocol.
Author(s): Jow H, Boys RJ, Wilkinson DJ
Publication type: Article
Publication status: Published
Journal: Statistical Applications in Genetics and Molecular Biology
Print publication date: 01/10/2014
Online publication date: 23/08/2014
ISSN (print): 2194-6302
ISSN (electronic): 1544-6115
Publisher: Walter de Gruyter GmbH
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