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

Amess B., Kluge W., Schwarz E., Haenisch F., Alsaif M., Yolken RH., Leweke FM., Guest PC., Bahn S.

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.

DOI

10.1002/pmic.201300034

Type

Journal article

Journal

Proteomics

Publication Date

07/2013

Volume

13

Pages

2072 - 2076

Keywords

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

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