Common Errors in the Implementation and Interpretation of Microarray Studies


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Abstract

Microarray analysis is used to tackle transplant-related problems as diverse as diagnosing rejection, predicting graft loss, and determining who can safely be removed from immunosuppression. Highly accurate predictions seem to be the norm. Unfortunately, many of these studies are flawed, either through questionable experimental design or improper validation methods. In addition, results are often presented in a misleading manner which exaggerates their true worth. In this paper, we describe the most common and serious errors and misrepresentations.

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