Addressing the challenge of defining valid proteomic biomarkers and classifiers.

Mohammed Dakna 1 Keith Harris 2 Alexandros Kalousis 3 Sebastien Carpentier 4 Walter Kolch 5, 6 Joost Schanstra 7 Marion Haubitz 8 Antonia Vlahou 9 Harald Mischak 1, 10, * Mark Girolami 11
* Auteur correspondant
1 Mosaiques diagnostics and therapeutics
2 Water and Environment Research Group
3 Computer Science Department
4 Laboratory of Tropical Crop Improvement
5 The Beatson Institute for Cancer Research
6 Systems Biology Ireland
7 I2MR - Institut de médecine moléculaire de Rangueil
8 MHH - Department of Nephrology
9 Research Foundation
10 BHF GCRC - Glasgow Cardiovascular Research Centre
11 Department of Statistical Science
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.
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Article dans une revue
BMC Bioinformatics, BioMed Central, 2010, 11 (1), pp.594. 〈10.1186/1471-2105-11-594〉
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Soumis le : lundi 19 septembre 2011 - 17:42:19
Dernière modification le : jeudi 13 septembre 2018 - 10:26:05
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Mohammed Dakna, Keith Harris, Alexandros Kalousis, Sebastien Carpentier, Walter Kolch, et al.. Addressing the challenge of defining valid proteomic biomarkers and classifiers.. BMC Bioinformatics, BioMed Central, 2010, 11 (1), pp.594. 〈10.1186/1471-2105-11-594〉. 〈inserm-00624800〉

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