ArticleBioinformatics (Oxford, England)2021
E-Pedigrees: a large-scale automatic family pedigree prediction application.
Article in Bioinformatics (Oxford, England), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- Identifying family structures from obituaries and matching them to patients in an electronic heath record.Journal of the American Medical Informatics Association : JAMIA · 2025Article
- Enhancing patient representation learning with inferred family pedigrees improves disease risk prediction.Journal of the American Medical Informatics Association : JAMIA · 2025Article
- Automated Family Histories Significantly Improve Risk Prediction in an EHR.AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science · 2024Article
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7 authors.
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Abstract
motivationThe 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.
resultsWe 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. AVAILABILITY AND IMPLEMENTATION: The Python 3.3+ version E-Pedigrees application is freely available on: https://github.com/xiayuan-huang/E-pedigrees.
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