PheWAS-ME: A web-app for interactive exploration of multimorbidity patterns in PheWAS

Abstract

AbstractSummaryElectronic health records (EHRs) linked with a DNA biobank provide unprecedented opportunities to use big data for biomedical research in precision medicine. The Phenome-wide association study (PheWAS) is a widely used technique for high-throughput evaluation of relationships between a set of genetic variants and a large collection of clinical phenotypes recorded in EHRs. PheWAS analyses are typically presented as static tables and charts of summary statistics obtained from statistical tests of association between pairs of a genetic variant and individual phenotypes. Comorbidities are common and typically lead to complex, multivariate gene-disease association signals that are challenging to interpret. Discovering and interrogating multimorbidity patterns and their influence in PheWAS is difficult and time-consuming. Here, we present a web application to visualize individual-level genotype and phenotype data side-by-side with PheWAS analysis results in an interactive dashboard, allowing researchers to explore multimorbidity patterns and their associations with a genetic variant of interest. We expect this application to enrich PheWAS analyses by illuminating clinical multimorbidity patterns present in the data.AvailabilityA demo PheWAS-ME application is publicly available at https://prod.tbilab.org/phewas_me/. A sample simulated-dataset is provided for exploration with the option to upload custom PheWAS results and corresponding individual-level data. The source code is available as an R package on GitHub (https://github.com/tbilab/multimorbidity_explorer).