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Gene.iobio:一款用于多功能、临床驱动的变异体查询和优先级排序的交互式网络工具。

gene.iobio: an interactive web tool for versatile, clinically-driven variant interrogation and prioritization.

作者信息

Di Sera Tonya, Velinder Matt, Ward Alistair, Qiao Yi, Georges Stephanie, Miller Chase, Pitman Anders, Richards Will, Ekawade Aditya, Viskochil David, Carey John C, Pace Laura, Bale Jim, Clardy Stacey L, Andrews Ashley, Botto Lorenzo, Marth Gabor

出版信息

medRxiv. 2020 Nov 6:2020.11.05.20224865. doi: 10.1101/2020.11.05.20224865.


DOI:10.1101/2020.11.05.20224865
PMID:33173897
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7654889/
Abstract

With increasing utilization of comprehensive genomic data to guide clinical care, anticipated to become the standard of care in many clinical settings, the practice of diagnostic medicine is undergoing a notable shift. However, the move from single-gene or panel-based genetic testing to exome and genome sequencing has not been matched by the development of tools to enable diagnosticians to interpret increasingly complex genomic findings. A new paradigm has emerged, where genome-based tests are often evaluated by a large multi-disciplinary collaborative team, typically including a diagnostic pathologist, a bioinformatician, a genetic counselor, and often a subspeciality clinician. This team-based approach calls for new computational tools to allow every member of the clinical care provider team, at varying levels of genetic knowledge and diagnostic expertise, to quickly and easily analyze and interpret complex genomic data. Here, we present , a real-time, intuitive and interactive web application for clinically-driven variant interrogation and prioritization. We show is a novel and effective approach that significantly improves upon and reimagines existing methods. In a radical departure from existing methods that present variants and genomic data in text and table formats, provides an interactive, intuitive and visually-driven analysis environment. We demonstrate that adoption of in clinical and research settings empowers clinical care providers to interact directly with patient genomic data both for establishing clinical diagnoses and informing patient care, using sophisticated genomic analyses that previously were only accessible via complex command line tools.

摘要

随着综合基因组数据在临床护理中应用的增加,预计将在许多临床环境中成为护理标准,诊断医学实践正在经历显著转变。然而,从单基因或基于基因 panel 的基因检测转向外显子组和基因组测序的过程中,却没有相应开发出能让诊断医生解读日益复杂的基因组结果的工具。一种新的模式已经出现,基于基因组的检测通常由一个大型多学科协作团队进行评估,该团队通常包括诊断病理学家、生物信息学家、遗传咨询师,通常还有专科临床医生。这种基于团队的方法需要新的计算工具,以便临床护理提供团队中不同基因知识水平和诊断专业知识水平的每个成员,都能快速轻松地分析和解读复杂的基因组数据。在此,我们展示了 ,这是一个用于临床驱动的变异体询问和优先级排序的实时、直观且交互式的网络应用程序。我们表明 是一种新颖且有效的方法,显著改进并重新构想了现有方法。与以文本和表格形式呈现变异体和基因组数据的现有方法截然不同, 提供了一个交互式、直观且视觉驱动的分析环境。我们证明,在临床和研究环境中采用 ,能使临床护理提供者直接与患者基因组数据进行交互,既用于建立临床诊断,也用于为患者护理提供信息,使用以前只能通过复杂的命令行工具才能获取的复杂基因组分析。

相似文献

[1]
gene.iobio: an interactive web tool for versatile, clinically-driven variant interrogation and prioritization.

medRxiv. 2020-11-6

[2]
Gene.iobio: an interactive web tool for versatile, clinically-driven variant interrogation and prioritization.

Sci Rep. 2021-10-13

[3]
: A Collaborative Diagnostic Workflow to Enable Team-Based Precision Genomics.

J Pers Med. 2022-1-8

[4]
Rapid clinical diagnostic variant investigation of genomic patient sequencing data with web tools.

J Clin Transl Sci. 2017-12

[5]
Author Correction: Gene.iobio: an interactive web tool for versatile, clinically-driven variant interrogation and prioritization.

Sci Rep. 2022-4-6

[6]
Genepanel.iobio - an easy to use web tool for generating disease- and phenotype-associated gene lists.

BMC Med Genomics. 2019-12-11

[7]
Genome analysis and knowledge-driven variant interpretation with TGex.

BMC Med Genomics. 2019-12-30

[8]
The future of Cochrane Neonatal.

Early Hum Dev. 2020-11

[9]
A visual and curatorial approach to clinical variant prioritization and disease gene discovery in genome-wide diagnostics.

Genome Med. 2016-2-2

[10]
A clinically driven variant prioritization framework outperforms purely computational approaches for the diagnostic analysis of singleton WES data.

Eur J Hum Genet. 2017-11

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