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Application of meta-analysis methods for identifying proteomic expression level differences


Correspondence: Professor Sabine Bahn, Department of Chemical Engineering and Biotechnology, University of Cambridge, Tennis Court Road, Cambridge, Cambridgeshire CB2 1QT, UK


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We present new statistical approaches for identification of proteins with expression levels that are significantly changed when applying meta-analysis to two or more independent experiments. We showed that the Euclidean distance measure has reduced risk of false positives compared to the rank product method. Our Ψ-ranking method has advantages over the traditional fold-change approach by incorporating both the fold-change direction as well as the p-value. In addition, the second novel method, Π-ranking, considers the ratio of the fold-change and thus integrates all three parameters. We further improved the latter by introducing our third technique, Σ-ranking, which combines all three parameters in a balanced nonparametric approach.

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