Analytical and simulation methods for estimating the potential predictive ability of genetic profiling: a comparison of methods and results.

ABSTRACT: Various modeling methods have been proposed to estimate the potential predictive ability of polygenic risk variants that predispose to various common diseases. However, it is unknown whether differences between them affect their conclusions on predictive ability. We reviewed input parameters, assumptions and output of the five most common methods and compared their estimates of the area under the receiver operating characteristic (ROC) curve (AUC) using hypothetical data representing effect sizes and frequencies of genetic variants, population disease risk and number of variants. To assess the accuracy of the estimated AUCs, we aimed to reproduce the AUCs of published empirical studies. All methods assumed that the combined effect of genetic variants on disease risk followed a multiplicati

SUBMITTER: Kundu S 

PROVIDER: S-EPMC3499740 | biostudies-literature | 2012 Dec

REPOSITORIES: biostudies-literature