Department of Biostatistics & Medical Informatics, University of Wisconsin-Madison, Madison, WI 53706, USA.
Department of Biomedical Informatics, Columbia University, New York, NY 10032, USA.
Bioinformatics. 2021 Nov 5;37(21):3966-3968. doi: 10.1093/bioinformatics/btab419.
The use and functionality of Electronic Health Records (EHR) have increased rapidly in the past few decades. EHRs are becoming an important depository of patient health information and can capture family data. Pedigree analysis is a longstanding and powerful approach that can gain insight into the underlying genetic and environmental factors in human health, but traditional approaches to identifying and recruiting families are low-throughput and labor-intensive. Therefore, high-throughput methods to automatically construct family pedigrees are needed.
We developed a stand-alone application: Electronic Pedigrees, or E-Pedigrees, which combines two validated family prediction algorithms into a single software package for high throughput pedigrees construction. The convenient platform considers patients' basic demographic information and/or emergency contact data to infer high-accuracy parent-child relationship. Importantly, E-Pedigrees allows users to layer in additional pedigree data when available and provides options for applying different logical rules to improve accuracy of inferred family relationships. This software is fast and easy to use, is compatible with different EHR data sources, and its output is a standard PED file appropriate for multiple downstream analyses.
The Python 3.3+ version E-Pedigrees application is freely available on: https://github.com/xiayuan-huang/E-pedigrees.
在过去几十年中，电子健康记录 (EHR) 的使用和功能迅速增加。EHR 正成为患者健康信息的重要存储库，并可以捕获家族数据。系谱分析是一种历史悠久且功能强大的方法，可以深入了解人类健康的潜在遗传和环境因素，但传统的识别和招募家族的方法效率低下且劳动强度大。因此，需要高通量的方法来自动构建家族系谱。
我们开发了一个独立的应用程序：电子系谱或 E-Pedigrees，它将两种经过验证的家族预测算法结合到一个软件包中，用于高通量系谱构建。该方便的平台考虑了患者的基本人口统计学信息和/或紧急联系人数据，以推断出高精度的亲子关系。重要的是，E-Pedigrees 允许用户在可用时添加额外的系谱数据，并提供应用不同逻辑规则的选项，以提高推断出的家族关系的准确性。该软件快速易用，与不同的 EHR 数据源兼容，其输出是适合多种下游分析的标准 PED 文件。
适用于 Python 3.3+ 的 E-Pedigrees 应用程序可在以下网址免费获得：https://github.com/xiayuan-huang/E-pedigrees。
