Journal article

The Genetic Interpretation of Area under the ROC Curve in Genomic Profiling

Naomi R Wray, Jian Yang, Michael E Goddard, Peter M Visscher



Genome-wide association studies in human populations have facilitated the creation of genomic profiles which combine the effects of many associated genetic variants to predict risk of disease. The area under the receiver operator characteristic (ROC) curve is a well established measure for determining the efficacy of tests in correctly classifying diseased and non-diseased individuals. We use quantitative genetics theory to provide insight into the genetic interpretation of the area under the ROC curve (AUC) when the test classifier is a predictor of genetic risk. Even when the proportion of genetic variance explained by the test is 100%, there is a maximum value for AUC that depends on the ..

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University of Melbourne Researchers


Awarded by Australian National Health and Medical Research Council

Awarded by Australian Research Council

Funding Acknowledgements

This work was supported by the Australian National Health and Medical Research Council (grants 389892, 442915, and 496688), and by the Australian Research Council (grant DP0770096). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.