clinical validity as diagnostic classifiers [5],[6]. The receiver operator characteristic (ROC) curve [7] is a well established tool for determining the efficacy of clinical diagnostic and prognostic tests in correctly classifying diseased and non-diseased individuals and has been used in the context of genomic profiling e.g., [6],[8],[9]. While the area under the ROC curve (AUC) is an important measure for clinical validity it does not tell the whole story as it does not differentiate between the accuracy with which the genomic profile predicts the true genetic risk of individuals and the accuracy with which true genetic risk predicts disease status, which is not under our control. We believe that the ability to differentiate between these components (i.e. the distinction between prediction of genotype and phenotype) is important for interpretation of the value of the genomic profile, particularly as the use of genomic profiles is very much in its infancy at present. Our knowledge of the genetic epidemiology of a disease means that we can know a priori that genomic profiles might not, on their own, be accurate diagnostic classifiers. For this reason, genomic profiles should judged in the first instance on the basis of their analytic validity [10] as predictors
