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全球基因组与健康联盟(GA4GH)表型数据包:实用指南。

GA4GH Phenopackets: A Practical Introduction.

作者信息

Ladewig Markus S, Jacobsen Julius O B, Wagner Alex H, Danis Daniel, El Kassaby Baha, Gargano Michael, Groza Tudor, Baudis Michael, Steinhaus Robin, Seelow Dominik, Bechrakis Nikolaos E, Mungall Christopher J, Schofield Paul N, Elemento Olivier, Smith Lindsay, McMurry Julie A, Munoz-Torres Monica, Haendel Melissa A, Robinson Peter N

机构信息

Department of Ophthalmology Klinikum Saarbrücken 66119 Saarbrücken Germany.

William Harvey Research Institute Charterhouse Square Barts and the London School of Medicine and Dentistry Queen Queen Mary University of London London EC1M 6BQ UK.

出版信息

Adv Genet (Hoboken). 2022 Aug 25;4(1):2200016. doi: 10.1002/ggn2.202200016. eCollection 2023 Mar.

Abstract

The Global Alliance for Genomics and Health (GA4GH) is developing a suite of coordinated standards for genomics for healthcare. The Phenopacket is a new GA4GH standard for sharing disease and phenotype information that characterizes an individual person, linking that individual to detailed phenotypic descriptions, genetic information, diagnoses, and treatments. A detailed example is presented that illustrates how to use the schema to represent the clinical course of a patient with retinoblastoma, including demographic information, the clinical diagnosis, phenotypic features and clinical measurements, an examination of the extirpated tumor, therapies, and the results of genomic analysis. The Phenopacket Schema, together with other GA4GH data and technical standards, will enable data exchange and provide a foundation for the computational analysis of disease and phenotype information to improve our ability to diagnose and conduct research on all types of disorders, including cancer and rare diseases.

摘要

全球基因组与健康联盟(GA4GH)正在为医疗保健领域的基因组学制定一套协调一致的标准。“表型数据包”是GA4GH制定的一项新的标准,用于共享描述个体特征的疾病和表型信息,将该个体与详细的表型描述、遗传信息、诊断和治疗方法联系起来。文中给出了一个详细示例,说明了如何使用该模式来表示视网膜母细胞瘤患者的临床病程,包括人口统计学信息、临床诊断、表型特征和临床测量结果、对切除肿瘤的检查、治疗方法以及基因组分析结果。“表型数据包模式”与GA4GH的其他数据和技术标准一起,将实现数据交换,并为疾病和表型信息的计算分析提供基础,以提高我们对包括癌症和罕见病在内的所有类型疾病进行诊断和开展研究的能力。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c1ab/10000265/6a8374153e0e/GGN2-4-2200016-g008.jpg

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