Hayley R Stoneman

Affiliations & Notes 1Department of Biomedical Informatics, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA 2Human Medical Genetics and Genomics Program, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA 3Department of Mathematical and Statistical Sciences, University of Colorado Denver, Denver, CO 80204, USA 4Colorado Center for Personalized Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA Article Info Publication...

Abstract Methods involving summary statistics in genetics can be quite powerful but can be limited in utility. For instance, many post-hoc analyses of disease studies require case and control allele frequencies (AFs), which are not always published. We present two frameworks to derive case and control AFs from GWAS summary statistics using the odds ratio, case and control sample sizes, and either the total (case and control aggregated) AF or standard error (SE).

Abstract Genetic summary data are both broadly accessible and highly useful including for risk prediction, causal inference, fine mapping, and the incorporation of external controls. Nevertheless, collapsing individual-level data into groups masks intra- and inter-sample heterogeneity (e.g., population structure), leading to confounding, reduced power, and bias. Unaccounted for substructure limits summary data usability, especially for understudied or admixed populations.