The polygenic scores (PGS) browser is a web-based application designed to improve precision medicine and calculate an individual’s genetic risk. The application provides users with access to a comprehensive and well-annotated database with over 3,000 PGS models. Users may select the most suitable model for their desired phenotype (e.g., disease) based on various criteria, such as model performance in European populations, concordance with phenotype definitions, year of publication, and other metadata. This database also includes PGS-PheWAS experimental results from over 10,000 studies, which associate the selected scores within the context of the phenotypic database from the FinnGen project. The database's extensive size and complexity offer a robust framework, filtering and visualization capabilities, support for ongoing research, hypothesis generation, and the identification of significant secondary associations and potential secondary risk factors that may be overlooked in hypothesis-driven association studies.

Users may upload calculated PGS values and filter them based on their placement in the desired PGS distribution (i.e. percentile). Each PGS model serves as a filtering criterion, allowing users to create complex systems of exclusion and inclusion criteria for sample filtering when certain factors (e.g., vitamin D levels or vessel density) cannot be measured. This allows researchers to subsample the desired cohort based on non-measured criteria, with a certain degree of bias, thereby making such cohort compilation procedures more accessible. The application also provides a lifelong disease risk estimate based on biological sex, age, and percentile in the PGS distribution for the studied disease. Based on these criteria, it determines an individual’s survival probability and age of onset. Disease prevalence, Bayesian posterior probability, odds ratios, and hazard ratios also contribute to a comprehensive understanding of disease sustainability and model quality. This compilation of detailed genetic reports goes beyond a typical, yet often-misleading, percentile-based or odds-ratio based genetic report.