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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.

Original publication

DOI

10.1002/pmic.201300034

Type

Journal article

Journal

Proteomics

Publication Date

07/2013

Volume

13

Pages

2072 - 2076

Addresses

Department of Chemical Engineering and Biotechnology, University of Cambridge, Cambridge, UK.

Keywords

Humans, Blood Proteins, Immunoassay, Statistics, Nonparametric, Case-Control Studies, Bipolar Disorder, Proteomics, Models, Theoretical, Research Design, Meta-Analysis as Topic