PheRS

PheRS computes phenotype risk scores (PheRS) from electronic health record (EHR) data linked to DNA biobanks to quantify how closely a patient's clinical features match specific Mendelian disease phenotypes.

Key Features:

• Phenotype risk scoring: Calculates PheRS to quantify patient similarity to specific Mendelian disease phenotypes.
• EHR and biobank integration: Leverages electronic health record (EHR) data linked to DNA biobanks for phenotype–genotype analyses.
• Phenotype mappings: Provides mappings between ICD codes, phecodes, human phenotype ontology (HPO) terms, and Mendelian diseases to translate EHR-derived phenotypes into disease-relevant terms.
• Mapping-based workflow: Begins with occurrences of ICD codes and proceeds through mapping steps to compute PheRS.
• Validation: Validates calculated PheRS using case–control analyses.
• Genetic association testing: Performs genetic association studies between PheRS and rare genetic variants.
• Discovery support: Facilitates discovery of novel phenotype–rare variant associations and identification of potential undiagnosed Mendelian disease cases.

Scientific Applications:

• Mendelian disease characterization: Quantifies resemblance of patient phenotypes to Mendelian diseases using EHR-derived data and PheRS.
• Rare variant association discovery: Identifies associations between PheRS and rare genetic variants through genetic association studies.
• Undiagnosed case identification: Flags patients whose PheRS suggest possible undiagnosed Mendelian conditions.
• Population-scale phenotype–genotype analysis: Applies PheRS across EHR-linked DNA biobanks for cohort-level investigations.

Methodology:

Maps occurrences of ICD codes and phecodes to human phenotype ontology (HPO) terms and Mendelian diseases, computes PheRS from these mappings, and supports validation via case–control analyses and genetic association studies.