4.3 Review

Statistical Considerations for Analysis of Microarray Experiments

Journal

CTS-CLINICAL AND TRANSLATIONAL SCIENCE
Volume 4, Issue 6, Pages 466-477

Publisher

WILEY
DOI: 10.1111/j.1752-8062.2011.00309.x

Keywords

microarrays; preprocessing; statistical inference; multiple testing; unsupervised learning; supervised learning; overfitting; validation; pathways; clinical trials; power; software

Funding

  1. NIH [RR024128, CA142538]

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Microarray technologies enable the simultaneous interrogation of expressions from thousands of genes from a biospecimen sample taken from a patient. This large set of expressions generates a genetic profile of the patient that may be used to identify potential prognostic or predictive genes or genetic models for clinical outcomes. The aim of this article is to provide a broad overview of some of the major statistical considerations for the design and analysis of microarrays experiments conducted as correlative science studies to clinical trials. An emphasis will be placed on how the lack of understanding and improper use of statistical concepts and methods will lead to noise discovery and misinterpretation of experimental results. Clin Trans Sci 2011; Volume 4: 466477

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