Addressing the Challenge of Defining Valid Proteomic Biomarkers and Classifiers

Dakna, M., Harris, K., Kalousis, A., Carpentier, S., Kolch, W., Schanstra, J. P., Haubitz, M., Vlahou, A., Mischak, H. and Girolami, M. (2010) Addressing the Challenge of Defining Valid Proteomic Biomarkers and Classifiers. BMC Bioinformatics, 11(1), p. 594. (doi: 10.1186/1471-2105-11-594)

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Publisher's URL: http://dx.doi.org/10.1186/1471-2105-11-594

Abstract

<b>Background</b><br /> 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.<p></p> <b>Results</b><br /> 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.<p></p> <b>Conclusions</b><br /> 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.<p></p>

Item Type:Articles
Status:Published
Refereed:Yes
Glasgow Author(s) Enlighten ID:Kolch, Prof Walter and Mischak, Professor Harald and Harris, Dr Keith
Authors: Dakna, M., Harris, K., Kalousis, A., Carpentier, S., Kolch, W., Schanstra, J. P., Haubitz, M., Vlahou, A., Mischak, H., and Girolami, M.
College/School:College of Medical Veterinary and Life Sciences
College of Medical Veterinary and Life Sciences > School of Cardiovascular & Metabolic Health
Journal Name:BMC Bioinformatics
Publisher:BioMed Central Ltd.
ISSN:1471-2105
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Project CodeAward NoProject NamePrincipal InvestigatorFunder's NameFunder RefLead Dept
396841Probabilistic Reconstruction of Signalling Pathways & Identification of Novel Transcription Factors Employing Heterogeneous Genome-Wide dataMark GirolamiMedical Research Council (MRC)G0401466Computing Science