Department of Cell and Molecular Biology, Karolinska Institutet, 171 77 Stockholm, Sweden.
Department of Microbiology, Tumor and Cell Biology (MTC), Karolinska Institutet, Stockholm, Sweden.
Nucleic Acids Res. 2018 Jul 2;46(W1):W163-W170. doi: 10.1093/nar/gky485.
The new web resource EviNet provides an easily run interface to network enrichment analysis for exploration of novel, experimentally defined gene sets. The major advantages of this analysis are (i) applicability to any genes found in the global network rather than only to those with pathway/ontology term annotations, (ii) ability to connect genes via different molecular mechanisms rather than within one high-throughput platform, and (iii) statistical power sufficient to detect enrichment of very small sets, down to individual genes. The users' gene sets are either defined prior to upload or derived interactively from an uploaded file by differential expression criteria. The pathways and networks used in the analysis can be chosen from the collection menu. The calculation is typically done within seconds or minutes and the stable URL is provided immediately. The results are presented in both visual (network graphs) and tabular formats using jQuery libraries. Uploaded data and analysis results are kept in separated project directories not accessible by other users. EviNet is available at https://www.evinet.org/.
新的网络资源 EviNet 为网络富集分析提供了一个易于运行的界面，可用于探索新的、经过实验定义的基因集。该分析的主要优势在于：(i) 适用于全局网络中发现的任何基因，而不仅限于具有途径/本体论术语注释的基因；(ii) 能够通过不同的分子机制连接基因，而不是在一个高通量平台内；(iii) 统计能力足以检测非常小的基因集的富集，甚至可以检测到单个基因。用户的基因集可以在上传前定义，也可以通过上传文件中的差异表达标准从上传的文件中交互式地派生。用于分析的途径和网络可以从收藏菜单中选择。计算通常在几秒钟或几分钟内完成，并立即提供稳定的 URL。结果以使用 jQuery 库的可视化（网络图）和表格格式呈现。上传的数据和分析结果存储在单独的项目目录中，其他用户无法访问。EviNet 可在 https://www.evinet.org/ 上获得。
