Walter Wencke, Sánchez-Cabo Fátima, Ricote Mercedes
Department of Cardiovascular Development and Repair and.
Bioinformatics Unit, Centro Nacional de Investigaciones Cardiovasculares (CNIC), Madrid, Spain.
Bioinformatics. 2015 Sep 1;31(17):2912-4. doi: 10.1093/bioinformatics/btv300. Epub 2015 May 11.
Despite the plethora of methods available for the functional analysis of omics data, obtaining comprehensive-yet detailed understanding of the results remains challenging. This is mainly due to the lack of publicly available tools for the visualization of this type of information. Here we present an R package called GOplot, based on ggplot2, for enhanced graphical representation. Our package takes the output of any general enrichment analysis and generates plots at different levels of detail: from a general overview to identify the most enriched categories (bar plot, bubble plot) to a more detailed view displaying different types of information for molecules in a given set of categories (circle plot, chord plot, cluster plot). The package provides a deeper insight into omics data and allows scientists to generate insightful plots with only a few lines of code to easily communicate the findings.
The R package GOplot is available via CRAN-The Comprehensive R Archive Network: http://cran.r-project.org/web/packages/GOplot. The shiny web application of the Venn diagram can be found at: https://wwalter.shinyapps.io/Venn/. A detailed manual of the package with sample figures can be found at https://wencke.github.io/
尽管有大量方法可用于组学数据的功能分析，但要全面且详细地理解结果仍具有挑战性。这主要是由于缺乏用于可视化此类信息的公开可用工具。在此，我们展示了一个基于ggplot2的名为GOplot的R包，用于增强图形表示。我们的包采用任何常规富集分析的输出，并生成不同详细程度的图：从识别最富集类别的总体概述（条形图、气泡图）到更详细的视图，显示给定类别集中分子的不同类型信息（圆形图、弦图、聚类图）。该包能更深入地洞察组学数据，并允许科学家只需几行代码就能生成有洞察力的图，以便轻松传达研究结果。
R包GOplot可通过综合R存档网络（CRAN）获取：http://cran.r-project.org/web/packages/GOplot 。维恩图的闪亮网络应用程序可在：https://wwalter.shinyapps.io/Venn/找到。带有示例图的该包详细手册可在https://wencke.github.io/找到。
