About the GWAS-ROCS Database

The GWAS-ROCS Database is a freely available electronic database containing the largest and most comprehensive set of SNP-derived AUROCs. All of the data is either directly from, or derived from, studies accessible through PubMed or GWAS Central — an open-access online repository of summary-level genome-wide association study (GWAS) data. The database currently houses 579 simulated populations (corresponding to 219 different conditions) and SNP data (odds ratio, risk allele frequency, and p-values) for 2886 unique SNPs. Each study simulation record (GR-Card) contains information detailing the original study as well as simulated population data (e.g. ROC curves, AUROCs, SNP-heritability scores) determined from careful population modelling to recreate individual-level GWAS data. All GWAS-ROCS data is downloadable and is intended for applications in genomics, biomarker discovery, and general education.

A GWAS-ROCS simulated population is a csv file with computer-generated individuals who are marked as either cases or controls, and given data about the presence of risk alleles (1 having the risk allele, or 0 not having the risk allele) at SNPs previously identified as being significant. Users can download these simulated populations to test their own genetic risk models, build their own simulated populations, and do much, much more!

The GWAS-ROCS Database was assembled in the hopes of accomplishing several objectives: (1) create the largest and most comprehensive set of SNP-derived AUROCs; (2) assist the scientific community in identifying conditions that appear to exhibit the best AUROC performance with multi-component SNP data; (3) identify conditions where SNP information appears to be relatively uninformative with regard to disease risk prediction; and (4) demonstrate the utility of using simulated populations to model SNP distributions and to show that these populations, along with logistic regression modelling, could be used to create multi-marker SNP profiles from publicly available GWAS data.