pyPheWAS Explorer: a visualization tool for exploratory analysis of phenome-disease associations.

Objective: To enable interactive visualization of phenome-wide association studies (PheWAS) on electronic health records (EHR).
Materials and Methods: Current PheWAS technologies require familiarity with command-line interfaces and lack end-to-end data visualizations. pyPheWAS Explorer allows users to examine group variables, test assumptions, design PheWAS models, and evaluate results in a streamlined graphical interface.
Results: A cohort of attention deficit hyperactivity disorder (ADHD) subjects and matched non-ADHD controls is examined. pyPheWAS Explorer is used to build a PheWAS model including sex and deprivation index as covariates, and the Explorer's result visualization for this model reveals known ADHD comorbidities.
Discussion: pyPheWAS Explorer may be used to rapidly investigate potentially novel EHR associations. Broader applications include deployment for clinical experts and preliminary exploration tools for institutional EHR repositories.
Conclusion: pyPheWAS Explorer provides a seamless graphical interface for designing, executing, and analyzing PheWAS experiments, emphasizing exploratory analysis of regression types and covariate selection.
Competing Interests: None declared.
(© The Author(s) 2023. Published by Oxford University Press on behalf of the American Medical Informatics Association.)