pyPheWAS Explorer

pyPheWAS Explorer performs phenome-wide association studies (PheWAS) on electronic health records (EHR) to identify associations between phenotypes and diseases.

Key Features:

• Visualization: Generates detailed visualizations of PheWAS results to display phenotype–disease associations, including comorbidity patterns.
• End-to-end workflow support: Supports the full PheWAS workflow including examination of group variables, testing statistical assumptions, model design, and result evaluation.
• Model design and covariate selection: Enables construction and adjustment of PheWAS models with covariate selection such as sex and deprivation index and supports flexible regression types for exploratory analysis.
• Result-focused visualization: Visualizes associations to aid identification of established and potentially novel phenotype–disease links, exemplified by comorbidities in attention deficit hyperactivity disorder (ADHD).

Scientific Applications:

• Exploratory analysis: Enables rapid investigation of new associations within EHR data to identify comorbidities and phenotypic patterns.
• Institutional EHR and epidemiological research: Applies PheWAS analyses to institutional EHR repositories for clinical research and epidemiological studies.
• Novel association discovery: Facilitates identification of potentially novel phenotype–disease associations relevant to genomics and personalized medicine.

Methodology:

Performs PheWAS on EHR data with model definition and adjustment using covariates (e.g., sex, deprivation index), supports testing statistical assumptions, selection of regression types, examination of group variables, and evaluation of results.