Because phenotype information for BioMe participants is derived by algorithms from comprehensive electronic medical records, BioMe phenotype data is highly versatile. Together with genome-wide genotype data, this information supports numerous internal and external research studies of genotype-phenotype associations.
A number of innovative exploratory research studies are underway exploiting the extraordinary richness of electronic medical records clinical information. These apply novel techniques to address pleiotropy (when one gene affects more than one phenotype), multiscale biology (integrating multiple data sources in advanced computational models), PheWAS (phenome-wide association studies), and topic modeling (a New Agnostic Machine Learning Approach To Mine Abstract Complex Medical Data). We anticipate that our innovative research approaches will generate breakthroughs in our understanding of how genetic variation and environmental exposure interact to influence personal health or response to treatment.