用人类表型本体编码临床数据用于计算鉴别诊断

Sebastian Köhler, N. Christine Øien, Orion J. Buske, Tudor Groza, Julius O. B. Jacobsen, Craig McNamara, Nicole Vasilevsky, Leigh C. Carmody, J. P. Gourdine, Michael Gargano, Julie A. McMurry, Daniel Danis, Christopher J. Mungall, Damian Smedley, Melissa Haendel, Peter N. Robinson
{"title":"用人类表型本体编码临床数据用于计算鉴别诊断","authors":"Sebastian Köhler,&nbsp;N. Christine Øien,&nbsp;Orion J. Buske,&nbsp;Tudor Groza,&nbsp;Julius O. B. Jacobsen,&nbsp;Craig McNamara,&nbsp;Nicole Vasilevsky,&nbsp;Leigh C. Carmody,&nbsp;J. P. Gourdine,&nbsp;Michael Gargano,&nbsp;Julie A. McMurry,&nbsp;Daniel Danis,&nbsp;Christopher J. Mungall,&nbsp;Damian Smedley,&nbsp;Melissa Haendel,&nbsp;Peter N. Robinson","doi":"10.1002/cphg.92","DOIUrl":null,"url":null,"abstract":"<p>The Human Phenotype Ontology (HPO) is a standardized set of phenotypic terms that are organized in a hierarchical fashion. It is a widely used resource for capturing human disease phenotypes for computational analysis to support differential diagnostics. The HPO is frequently used to create a set of terms that accurately describe the observed clinical abnormalities of an individual being evaluated for suspected rare genetic disease. This profile is compared with computational disease profiles in the HPO database with the aim of identifying genetic diseases with comparable phenotypic profiles. The computational analysis can be coupled with the analysis of whole-exome or whole-genome sequencing data through applications such as Exomiser. This article explains how to choose an optimal set of HPO terms for these cases and enter them with software, such as PhenoTips and PatientArchive, and demonstrates how to use Phenomizer and Exomiser to generate a computational differential diagnosis. © 2019 by John Wiley &amp; Sons, Inc.</p>","PeriodicalId":40007,"journal":{"name":"Current Protocols in Human Genetics","volume":"103 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2019-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1002/cphg.92","citationCount":"29","resultStr":"{\"title\":\"Encoding Clinical Data with the Human Phenotype Ontology for Computational Differential Diagnostics\",\"authors\":\"Sebastian Köhler,&nbsp;N. Christine Øien,&nbsp;Orion J. Buske,&nbsp;Tudor Groza,&nbsp;Julius O. B. Jacobsen,&nbsp;Craig McNamara,&nbsp;Nicole Vasilevsky,&nbsp;Leigh C. Carmody,&nbsp;J. P. Gourdine,&nbsp;Michael Gargano,&nbsp;Julie A. McMurry,&nbsp;Daniel Danis,&nbsp;Christopher J. Mungall,&nbsp;Damian Smedley,&nbsp;Melissa Haendel,&nbsp;Peter N. Robinson\",\"doi\":\"10.1002/cphg.92\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>The Human Phenotype Ontology (HPO) is a standardized set of phenotypic terms that are organized in a hierarchical fashion. It is a widely used resource for capturing human disease phenotypes for computational analysis to support differential diagnostics. The HPO is frequently used to create a set of terms that accurately describe the observed clinical abnormalities of an individual being evaluated for suspected rare genetic disease. This profile is compared with computational disease profiles in the HPO database with the aim of identifying genetic diseases with comparable phenotypic profiles. The computational analysis can be coupled with the analysis of whole-exome or whole-genome sequencing data through applications such as Exomiser. This article explains how to choose an optimal set of HPO terms for these cases and enter them with software, such as PhenoTips and PatientArchive, and demonstrates how to use Phenomizer and Exomiser to generate a computational differential diagnosis. © 2019 by John Wiley &amp; Sons, Inc.</p>\",\"PeriodicalId\":40007,\"journal\":{\"name\":\"Current Protocols in Human Genetics\",\"volume\":\"103 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-07-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1002/cphg.92\",\"citationCount\":\"29\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Current Protocols in Human Genetics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://onlinelibrary.wiley.com/doi/10.1002/cphg.92\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Current Protocols in Human Genetics","FirstCategoryId":"1085","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/cphg.92","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 29

摘要

人类表型本体(Human Phenotype Ontology, HPO)是以分层方式组织的一组标准化的表型术语。它是一种广泛使用的资源,用于捕获人类疾病表型的计算分析,以支持鉴别诊断。HPO经常用于创建一组术语,准确描述正在评估疑似罕见遗传疾病的个体的观察到的临床异常。该档案与HPO数据库中的计算疾病档案进行比较,目的是确定具有可比表型档案的遗传疾病。计算分析可以通过Exomiser等应用程序与全外显子组或全基因组测序数据的分析相结合。本文解释了如何为这些病例选择一组最佳的HPO术语,并使用软件(如PhenoTips和PatientArchive)输入它们,并演示了如何使用Phenomizer和Exomiser生成计算性鉴别诊断。©2019 by John Wiley &儿子,Inc。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Encoding Clinical Data with the Human Phenotype Ontology for Computational Differential Diagnostics

The Human Phenotype Ontology (HPO) is a standardized set of phenotypic terms that are organized in a hierarchical fashion. It is a widely used resource for capturing human disease phenotypes for computational analysis to support differential diagnostics. The HPO is frequently used to create a set of terms that accurately describe the observed clinical abnormalities of an individual being evaluated for suspected rare genetic disease. This profile is compared with computational disease profiles in the HPO database with the aim of identifying genetic diseases with comparable phenotypic profiles. The computational analysis can be coupled with the analysis of whole-exome or whole-genome sequencing data through applications such as Exomiser. This article explains how to choose an optimal set of HPO terms for these cases and enter them with software, such as PhenoTips and PatientArchive, and demonstrates how to use Phenomizer and Exomiser to generate a computational differential diagnosis. © 2019 by John Wiley & Sons, Inc.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Current Protocols in Human Genetics
Current Protocols in Human Genetics Biochemistry, Genetics and Molecular Biology-Genetics
自引率
0.00%
发文量
0
期刊介绍: Current Protocols in Human Genetics is the resource for designing and running successful research projects in all branches of human genetics.
期刊最新文献
Issue Information Resolving Breakpoints of Chromosomal Rearrangements at the Nucleotide Level Using Sanger Sequencing Informed Consent for Genetic and Genomic Research A Guide to Using ClinTAD for Interpretation of DNA Copy Number Variants in the Context of Topologically Associated Domains The AD Knowledge Portal: A Repository for Multi-Omic Data on Alzheimer's Disease and Aging
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1