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Chunk #18 — Results — The maximum value of AUC when the test classifier is a genetic predictor depends on heritability and disease prevalence

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The genetic interpretation of area under the ROC curve in genomic profiling.
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is not exactly zero, but very close to zero); similarly for the diseases in Figure 1B. Figure 1C and 1D plot the ROC curves for the diseases considered in Figure 1A and 1B, respectively. These graphs demonstrate firstly (not unexpectedly), that for diseases with the same prevalence, genetic liability is a better predictor of disease status for diseases with higher heritability and secondly, that for diseases with the same heritability, genetic liability is a better predictor of disease status for rarer diseases, because a higher proportion of those with high genetic liability are actually diseased. For example, if we used genetic liability of ≥1 as our predictor of disease, then the TPR is 0.26 and the FPR = 0.00, when K = 0.5, compared to TPR = 0.99 and the FPR = 0.12, when K = 0.01. These graphs demonstrate that maximum value of AUC (i.e. AUCmax) when the test classifier is a genetic predictor is dependent on both and K.