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The rapid identification of genetic markers for multifactorial diseases from genome-wide association studies is fuelling interest in investigating the predictive ability and health care utility of genetic risk models. Various measures are available for the assessment of risk prediction models, each addressing a different aspect of performance and utility. We developed PredictABEL, a package in R that covers descriptive tables, measures and figures that are used in the analysis of risk prediction studies such as measures of model fit, predictive ability and clinical utility, and risk distributions, calibration plot and the receiver operating characteristic plot. Tables and figures are saved as separate files in a user-specified format, which include publication-quality EPS and TIFF formats. All figures are available in a ready-made layout, but they can be customized to the preferences of the user. The package has been developed for the analysis of genetic risk prediction studies, but can also be used for studies that only include non-genetic risk factors. PredictABEL is freely available at the websites of GenABEL ( http://www.genabel.org ) and CRAN ( http://cran.r-project.org/).

Original publication

DOI

10.1007/s10654-011-9567-4

Type

Journal article

Journal

European journal of epidemiology

Publication Date

04/2011

Volume

26

Pages

261 - 264

Addresses

Department of Epidemiology, Erasmus University Medical Center, PO Box 2040, 3000 CA, Rotterdam, The Netherlands.

Keywords

Humans, Genetic Predisposition to Disease, Genetic Markers, Data Interpretation, Statistical, Risk Assessment, Predictive Value of Tests, Software, Genome-Wide Association Study