Estimating the predictive ability of genetic risk models in simulated data based on published results from genome-wide association studies.

ABSTRACT:

Background

There is increasing interest in investigating genetic risk models in empirical studies, but such studies are premature when the expected predictive ability of the risk model is low. We assessed how accurately the predictive ability of genetic risk models can be estimated in simulated data that are created based on the odds ratios (ORs) and frequencies of single-nucleotide polymorphisms (SNPs) obtained from genome-wide association studies (GWASs).

Methods

We aimed to replicate published prediction studies that reported the area under the receiver operating characteristic curve (AUC) as a measure of predictive ability. We searched GWAS articles for all SNPs included in these models and extracted ORs and risk allele frequencies to construct genotypes and disease stat

SUBMITTER: Kundu S 

PROVIDER: S-EPMC4056181 | biostudies-literature | 2014

REPOSITORIES: biostudies-literature