LocusZoom.js: interactive and embeddable visualization of genetic association study results.

LocusZoom.js: interactive and embeddable visualization of genetic association study results.
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DOI:
10.1093/bioinformatics/btab186
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发表时间:
2021-09-29
期刊:
Bioinformatics (Oxford, England)
影响因子:
--
通讯作者:
Boehnke M
Boehnke M
中科院分区:
其他
文献类型:
--
作者:
Boughton AP;Welch RP;Flickinger M;VandeHaar P;Taliun D;Abecasis GR;Boehnke M

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LocusZoom.js是一个JavaScript库,用于创建遗传关联研究结果的交互式基于Web的可视化。它可以在相关生物数据(如基因模型和其他基因组注释)的背景下显示一个或多个性状,并允许交互式细化分析模型(通过选择连锁不平衡参考面板,识别可能的因果变异集,或与GWAS目录进行比较)。它可以嵌入到网页中,以实现数据共享和探索。视图可以自定义和扩展以显示其他数据类型,例如全表型关联研究(PheWAS)结果,染色质共可及性或eQTL测量。一个新的网络上传服务协调了数据集,添加了注释,并使其易于探索用户提供的结果集。LocusZoom.js是一个开放源码软件,在一个宽松的MIT许可证下。代码和文档可在https://github.com/statgen/locuszoom/上获得。所有版本的可安装包也通过NPM分发。额外的特性作为独立的库提供,以促进重用。在https://my.locuszoom.org/上使用您自己的GWAS结果。 补充数据可在Bioinformatics在线获得。
LocusZoom.js is a JavaScript library for creating interactive web-based visualizations of genetic association study results. It can display one or more traits in the context of relevant biological data (such as gene models and other genomic annotation), and allows interactive refinement of analysis models (by selecting linkage disequilibrium reference panels, identifying sets of likely causal variants, or comparisons to the GWAS catalog). It can be embedded in web pages to enable data sharing and exploration. Views can be customized and extended to display other data types such as phenome-wide association study (PheWAS) results, chromatin co-accessibility, or eQTL measurements. A new web upload service harmonizes datasets, adds annotations, and makes it easy to explore user-provided result sets. LocusZoom.js is open-source software under a permissive MIT license. Code and documentation are available at: https://github.com/statgen/locuszoom/. Installable packages for all versions are also distributed via NPM. Additional features are provided as standalone libraries to promote reuse. Use with your own GWAS results at https://my.locuszoom.org/. Supplementary data are available at Bioinformatics online.
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