comoRbidity

comoRbidity performs systematic analysis of disease comorbidities by integrating electronic health records and genotype-phenotype data to identify clinical and molecular associations, including sex- and age-specific and temporal patterns.

Key Features:

• R package implementation: Implemented as an R package for computational analyses.
• Clinical Data Integration: Uses electronic health records (EHRs) to identify significant comorbidity patterns and supports sex- and age-stratified and temporal directionality analyses.
• Molecular Comorbidity Analysis: Incorporates genotype-phenotype information to examine shared genes among disorders and generate hypotheses about genetic mechanisms.
• Analytical and Visualization Functions: Provides a suite of analytical and visualization functions for integrative analyses of clinical and molecular comorbidities.

Scientific Applications:

• Exploration of comorbidity patterns: Identify significant disease associations from clinical data, including demographic stratification and temporal relationships.
• Investigation of genetic mechanisms: Examine shared-gene relationships using genotype-phenotype data to generate hypotheses about molecular underpinnings of comorbidities.
• Support for clinical research and healthcare management: Provide evidence to inform patient care strategies and healthcare resource management.

Methodology:

Clinical comorbidity analysis: identification of significant disease associations from clinical data with sex- and age-stratification and analyses of temporal relationships. Molecular comorbidity analysis: examination of shared genes among disorders using genotype-phenotype information.