PANGEN:用于比较和创建诊断基因面板的在线平台。

IF 4.3 3区 材料科学 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC
Ofer Isakov, Dina Marek-Yagel, Rotem Greenberg, Michal Naftali, Shay Ben-Shachar
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引用次数: 0

摘要

有针对性的基因组测序可将致病基因变异的搜索范围限制在与表型有明确关联的基因上。由于对某些基因的表型关联缺乏共识,导致不同实验室提供的同一基因组的基因组成差异很大,因此基因组的设计极具挑战性。我们开发了 PANGEN 平台,该平台提供了一个基因面板信息的集中资源,能够比较和生成新的智能诊断面板。我们从 12 个公共和商业来源(Blueprint、Cegat、Centogene、ClinGen、Fulgent、GeneDx、Health in Code、Human Phenotype Ontology、Invitae、PanelApp、Prevention genetics 和 Pronto diagnostics)收集了基因与表型的关联。基因与表型的关联根据原始源面板得出的类别分为不同等级。配对面板相似性的计算方法是将共同基因的数量除以两个面板中基因的总数。具有极端鸟嘌呤-胞嘧啶(GC)含量的区域是从 "Genome in a Bottle stratifications "数据集中收集的,假定的基因组重复则是从圣克鲁斯大学数据库中检索的。总共收集了 1533 个面板、9759 种表型和 6979 个基因。该平台提供了一个界面:(i) 探索和比较收集到的面板;(ii) 寻找相似面板;(iii) 识别具有高 GC 含量或重复水平的基因;(iv) 通过组合来自不同来源的面板生成基因面板;(v) 将生成的面板分层为具有强表型关联的基因("核心")和关联较弱的基因("扩展")。所介绍的平台是基因面板探索和比较的独特资源,可通过公共在线网络服务器生成量身定制的诊断面板。数据库网址:https://c-gc.shinyapps.io/PANGEN/。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
PANGEN: an online platform for the comparison and creation of diagnostic gene panels.

Targeted gene panel sequencing is used to limit the search for causative genetic variants solely to genes with an established association with the phenotype. The design of gene panels is challenging due to the lack of consensus regarding phenotypic associations for some genes, which results in high variation in gene composition for the same panel offered by different laboratories. We developed PANGEN, a platform that provides a centralized resource for gene panel information, with the ability to compare and generate new intelligent diagnostic panels. Gene-phenotype associations were collected from 12 public and commercial sources (Blueprint, Cegat, Centogene, ClinGen, Fulgent, GeneDx, Health in Code, Human Phenotype Ontology, Invitae, PanelApp, Prevention genetics, and Pronto diagnostics). Gene-phenotype associations are categorized into tiers according to categories derived from the original source panel. Pairwise panel similarity was calculated by dividing the number of common genes by the total number of genes in both panels. Regions with extreme guanine-cytosine (GC) content were collected from the Genome in a Bottle stratifications dataset, and putative genomic duplications were retrieved from the University of Santa Cruz database. Overall, 1533 panels, 9759 phenotypes, and 6979 genes were collected. The platform provides an interface to (i) explore and compare collected panels, (ii) find similar panels, (iii) identify genes with high GC content or duplication levels, (iv) generate gene panels by combining panels from various sources, and (v) stratify a generated panel into genes with a strong phenotype association ('core') and those with a weaker association ('extended'). The presented platform represents a unique resource for gene panel exploration and comparison that facilitates the generation of tailored diagnostic panels through a public online web server. Database URL: https://c-gc.shinyapps.io/PANGEN/.

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来源期刊
CiteScore
7.20
自引率
4.30%
发文量
567
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