Addressing the Challenge of Defining Valid Proteomic Biomarkers and Classifiers

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Title: Addressing the Challenge of Defining Valid Proteomic Biomarkers and Classifiers
Authors: Dakna, Mohammed
Harris, Keith
Kalousis, Alexandros
et al.
Permanent link: http://hdl.handle.net/10197/5015
Date: 2010
Abstract: Background: The purpose of this manuscript is to provide, based on an extensive analysis of a proteomic data set, suggestions for proper statistical analysis for the discovery of sets of clinically relevant biomarkers. As tractable example we define the measurable proteomic differences between apparently healthy adult males and females. We choose urine as body-fluid of interest and CE-MS, a thoroughly validated platform technology, allowing for routine analysis of a large number of samples. The second urine of the morning was collected from apparently healthy male and female volunteers (aged 21-40) in the course of the routine medical check-up before recruitment at the Hannover Medical School. Results: We found that the Wilcoxon-test is best suited for the definition of potential biomarkers. Adjustment for multiple testing is necessary. Sample size estimation can be performed based on a small number of observations via resampling from pilot data. Machine learning algorithms appear ideally suited to generate classifiers. Assessment of any results in an independent test-set is essential. Conclusions: Valid proteomic biomarkers for diagnosis and prognosis only can be defined by applying proper statistical data mining procedures. In particular, a justification of the sample size should be part of the study design.
Type of material: Journal Article
Publisher: Springer (Biomed Central Ltd.)
Copyright (published version): 2010 Springer (Biomed Central Ltd.)
Keywords: biomarker definitionBiomarker IdentificationClinical ProteomicsWilcoxon-testproteomic biomarkers
DOI: 10.1186/1471-2105-11-594
Language: en
Status of Item: Peer reviewed
Appears in Collections:SBI Research Collection

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