The phenotype-genotype reference map: Improving biobank data science through replication
Lisa Bastarache, Sarah Delozier, Anita Pandit, Jing He, Adam Lewis, Aubrey Annis, Jonathon LeFaive, Joshua C. Denny, Robert J. Carroll, Russ B. Altman, Jacob Hughey, Matthew Zawistowski, Josh F. Peterson
Abstract
Population-scale biobanks linked to electronic health record data provide vast opportunities to extend our knowledge of human genetics and discover new phenotype-genotype associations. Given their dense phenotype data, biobanks can also facilitate replication studies on a phenome-wide scale. Here, we introduce the phenotype-genotype reference map (PGRM), a set of 5,879 genetic associations from 523 GWAS publications that can be used for high-throughput replication experiments. PGRM phenotypes are standardized as phecodes, ensuring interoperability between biobanks. We applied the PGRM to five ancestry-specific cohorts from four independent biobanks and found evidence of robust replications across a wide array of phenotypes. We show how the PGRM can be used to detect data corruption and to empirically assess parameters for phenome-wide studies. Finally, we use the PGRM to explore factors associated with replicability of GWAS results.