Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, CA 94143, USA.
Bioinformatics. 2010 Jan 15;26(2):285-6. doi: 10.1093/bioinformatics/btp656. Epub 2009 Nov 23.
Exploratory Gene Association Networks (EGAN) is a Java desktop application that provides a point-and-click environment for contextual graph visualization of high-throughput assay results. By loading the entire network of genes, pathways, interactions, annotation terms and literature references directly into memory, EGAN allows a biologist to repeatedly query and interpret multiple experimental results without incurring additional delays for data download/integration. Other compelling features of EGAN include: support for diverse -omics technologies, a simple and interactive graph display, sortable/searchable data tables, links to external web resources including > or = 240 000 articles at PubMed, hypergeometric and GSEA-like enrichment statistics, pipeline-compatible automation via scripting and the ability to completely customize and/or supplement the network with new/proprietary data.
Runs on most operating systems via Java; downloadable from http://akt.ucsf.edu/EGAN/.
Supplementary data are available at Bioinformatics online.
探索性基因关联网络（EGAN）是一个 Java 桌面应用程序，它提供了一个点击环境，用于高吞吐量分析结果的上下文图形可视化。通过将整个基因、途径、相互作用、注释术语和文献参考的网络直接加载到内存中，EGAN 允许生物学家反复查询和解释多个实验结果，而不会因数据下载/集成而导致额外的延迟。EGAN 的其他 compelling 功能包括：支持多种组学技术、简单而交互的图形显示、可排序/可搜索的数据表、与包括 PubMed 中 >或=240000 篇文章在内的外部网络资源的链接、超几何和 GSEA 样的富集统计、通过脚本进行管道兼容的自动化，以及完全自定义和/或使用新的/专有的数据补充网络的能力。
通过 Java 在大多数操作系统上运行；可从 http://akt.ucsf.edu/EGAN/ 下载。
补充数据可在 Bioinformatics 在线获得。
