ArticleBioinformatics (Oxford, England)2022
The phers R package: using phenotype risk scores based on electronic health records to study Mendelian disease and rare genetic variants.
Article in Bioinformatics (Oxford, England), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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7 citing papers in PubMed, 12 citations in OpenAlex.
- Developing a phenotype risk score formedRxiv : the preprint server for health sciences · 2026Article
- A perspective on genetic and polygenic risk scores-advances and limitations and overview of associated tools.Briefings in bioinformatics · 2024Review
- Proceedings from the inaugural Artificial Intelligence in Primary Immune Deficiencies (AIPID) conference.The Journal of allergy and clinical immunology · 2024Article
- A test of automated use of electronic health records to aid in diagnosis of genetic disease.Genetics in medicine : official journal of the American College of Medical Genetics · 2023Article
- Phenotypic presentation of Mendelian disease across the diagnostic trajectory in electronic health records.Genetics in medicine : official journal of the American College of Medical Genetics · 2023Article
- Phenotype Risk Score but Not Genetic Risk Score Aids in Identifying Individuals With Systemic Lupus Erythematosus in the Electronic Health Record.Arthritis & rheumatology (Hoboken, N.J.) · 2023Article
- Linking rare and common disease vocabularies by mapping between the human phenotype ontology and phecodes.JAMIA open · 2023Article
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Authors and funding
3 authors at 2 institutions in 1 country.
Funding
Abstract
summaryElectronic health record (EHR) data linked to DNA biobanks are a valuable resource for understanding the phenotypic effects of human genetic variation. We previously developed the phenotype risk score (PheRS) as an approach to quantify the extent to which a patient's clinical features resemble a given Mendelian disease. Using PheRS, we have uncovered novel associations between Mendelian disease-like phenotypes and rare genetic variants, and identified patients who may have undiagnosed Mendelian disease. Although the PheRS approach is conceptually simple, it involves multiple mapping steps and was previously only available as custom scripts, limiting the approach's usability. Thus, we developed the phers R package, a complete and user-friendly set of functions and maps for performing a PheRS-based analysis on linked clinical and genetic data. The package includes up-to-date maps between EHR-based phenotypes (i.e. ICD codes and phecodes), human phenotype ontology terms and Mendelian diseases. Starting with occurrences of ICD codes, the package enables the user to calculate PheRSs, validate the scores using case-control analyses, and perform genetic association analyses. By increasing PheRS's transparency and usability, the phers R package will help improve our understanding of the relationships between rare genetic variants and clinically meaningful human phenotypes. AVAILABILITY AND IMPLEMENTATION: The phers R package is free and open-source and available on CRAN and at https://phers.hugheylab.org. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
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