Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN 37232, USA.
Program in Chemical and Physical Biology, Vanderbilt University School of Medicine, Nashville, TN 37232, USA.
Bioinformatics. 2022 Oct 31;38(21):4972-4974. doi: 10.1093/bioinformatics/btac619.
Electronic 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.
The phers R package is free and open-source and available on CRAN and at https://phers.hugheylab.org.
Supplementary data are available at Bioinformatics online.
电子健康记录 (EHR) 数据与 DNA 生物库相关联，是了解人类遗传变异表型效应的宝贵资源。我们之前开发了表型风险评分 (PheRS)，作为量化患者临床特征与给定孟德尔疾病相似程度的一种方法。使用 PheRS，我们发现了孟德尔疾病样表型与罕见遗传变异之间的新关联，并确定了可能患有未确诊孟德尔疾病的患者。尽管 PheRS 方法在概念上很简单，但它涉及多个映射步骤，并且以前仅作为自定义脚本提供，限制了该方法的可用性。因此，我们开发了 phers R 包，这是一个完整且用户友好的函数和映射集，用于对链接的临床和遗传数据执行基于 PheRS 的分析。该包包括基于 EHR 的表型（即 ICD 代码和 phecode）、人类表型本体术语和孟德尔疾病之间的最新映射。从 ICD 代码的出现开始，该包允许用户计算 PheRS，使用病例对照分析验证评分，并进行遗传关联分析。通过提高 PheRS 的透明度和可用性，phers R 包将有助于提高我们对罕见遗传变异与具有临床意义的人类表型之间关系的理解。
phers R 包是免费的、开源的，可以在 CRAN 和 https://phers.hugheylab.org 上获得。
补充数据可在 Bioinformatics 在线获得。
