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

Abstract

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.