GA4GH 表型包语料库:用于基因组诊断和发现的病例级表型。

IF 3.3 Q2 GENETICS & HEREDITY
Daniel Danis, Michael J Bamshad, Yasemin Bridges, Andrés Caballero-Oteyza, Pilar Cacheiro, Leigh C Carmody, Leonardo Chimirri, Jessica X Chong, Ben Coleman, Raymond Dalgleish, Peter J Freeman, Adam S L Graefe, Tudor Groza, Peter Hansen, Julius O B Jacobsen, Adam Klocperk, Maaike Kusters, Markus S Ladewig, Anthony J Marcello, Teresa Mattina, Christopher J Mungall, Monica C Munoz-Torres, Justin T Reese, Filip Rehburg, Bárbara C S Reis, Catharina Schuetz, Damian Smedley, Timmy Strauss, Jagadish Chandrabose Sundaramurthi, Sylvia Thun, Kyran Wissink, John F Wagstaff, David Zocche, Melissa A Haendel, Peter N Robinson
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引用次数: 0

摘要

全球基因组学与健康联盟(GA4GH)于 2022 年发布了表型包模式(Phenopacket Schema),并获得国际标准化组织(ISO)批准,作为共享个人临床和基因组信息(包括表型描述、数字测量、基因信息、诊断和治疗)的标准。表型包可用作支持表型驱动的基因组诊断软件的输入文件,也可用作促进患者分类和分层以确定新疾病和治疗方法的算法的输入文件。目前非常需要收集表型包来测试软件管道和算法。在此,我们介绍 Phenopacket Store。0.1.19 版的 Phenopacket Store 包含 6668 个表型包,代表与 423 个基因和 3834 个独特致病等位基因相关的 475 种孟德尔疾病和染色体疾病,这些表型包是从 959 种不同的出版物中收集的。这是首次大规模收集病例水平的标准化表型信息,这些信息来源于文献中的病例报告,并附有详细的临床数据描述,将用于多种用途,包括开发和测试诊断基因组学中优先考虑基因和疾病的软件、临床表型数据的机器学习分析、患者分层以及基因型与表型的相关性。该语料库还提供了使用 GA4GH Phenopacket Schema 整理文献衍生数据的最佳实践范例。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A corpus of GA4GH phenopackets: Case-level phenotyping for genomic diagnostics and discovery.

The Global Alliance for Genomics and Health (GA4GH) Phenopacket Schema was released in 2022 and approved by ISO as a standard for sharing clinical and genomic information about an individual, including phenotypic descriptions, numerical measurements, genetic information, diagnoses, and treatments. A phenopacket can be used as an input file for software that supports phenotype-driven genomic diagnostics and for algorithms that facilitate patient classification and stratification for identifying new diseases and treatments. There has been a great need for a collection of phenopackets to test software pipelines and algorithms. Here, we present Phenopacket Store. Phenopacket Store v.0.1.19 includes 6,668 phenopackets representing 475 Mendelian and chromosomal diseases associated with 423 genes and 3,834 unique pathogenic alleles curated from 959 different publications. This represents the first large-scale collection of case-level, standardized phenotypic information derived from case reports in the literature with detailed descriptions of the clinical data and will be useful for many purposes, including the development and testing of software for prioritizing genes and diseases in diagnostic genomics, machine learning analysis of clinical phenotype data, patient stratification, and genotype-phenotype correlations. This corpus also provides best-practice examples for curating literature-derived data using the GA4GH Phenopacket Schema.

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来源期刊
HGG Advances
HGG Advances Biochemistry, Genetics and Molecular Biology-Molecular Medicine
CiteScore
4.30
自引率
4.50%
发文量
69
审稿时长
14 weeks
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