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J Proteome Res. 2011 Dec 2;10(12):5398-408. doi: 10.1021/pr200654k. Epub 2011 Nov 14.

Sense and nonsense of pathway analysis software in proteomics.

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1
Functional Proteomics, Medizinisches Proteom-Center, Ruhr-University Bochum, D-44780 Bochum, Germany. thorsten.t.mueller@rub.de

Abstract

New developments in proteomics enable scientists to examine hundreds to thousands of proteins in parallel. Quantitative proteomics allows the comparison of different proteomes of cells, tissues, or body fluids with each other. Analyzing and especially organizing these data sets is often a Herculean task. Pathway Analysis software tools aim to take over this task based on present knowledge. Companies promise that their algorithms help to understand the significance of scientist's data, but the benefit remains questionable, and a fundamental systematic evaluation of the potential of such tools has not been performed until now. Here, we tested the commercial Ingenuity Pathway Analysis tool as well as the freely available software STRING using a well-defined study design in regard to the applicability and value of their results for proteome studies. It was our goal to cover a wide range of scientific issues by simulating different established pathways including mitochondrial apoptosis, tau phosphorylation, and Insulin-, App-, and Wnt-signaling. Next to a general assessment and comparison of the pathway analysis tools, we provide recommendations for users as well as for software developers to improve the added value of a pathway study implementation in proteomic pipelines.

PMID:
21978018
DOI:
10.1021/pr200654k
[Indexed for MEDLINE]
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