The AUC is a statistic calculated on the observed disease scale and is a measure of the efficacy of prediction of phenotype using a test classifier. The ROC plots the true positive rate (TPR or sensitivity) against the false-positive rate (FPR or 1-specificity). TPR = probability (positive test result|diseased) and FPR = probability (positive test result|not diseased). Since these probabilities are conditional, they are not dependent on the number of cases or controls tested, except through the sampling variance associated with them. In genomic profiling the ROC is obtained by ranking a set of individuals with known disease status by their genomic profile from lowest estimated risk (i.e., profile score) to highest estimated risk and then assessing sensitivity and specificity assuming a cut-off after each rank (starting with the highest ranked individual). If nd and nd' are the numbers of diseased and not diseased individuals, and if the individual with the highest predicted genetic risk has rank r1 = nd + nd' = n, AUC can be calculated directly from the mean rank of the diseased individuals (),(2)(see example in
