Division of Health Medical Intelligence, Human Genome Center, The Institute of Medical Science, The University of Tokyo, 4-6-1 Shirokanedai, Minato-ku, Tokyo 108-8639, Japan.
Department of Immunology and Genomics, Graduate School of Medicine, Osaka Metropolitan University, Osaka 545-8585, Japan.
Bioinformatics. 2023 Oct 3;39(10). doi: 10.1093/bioinformatics/btad622.
The Kyoto Encyclopedia of Genes and Genomes (KEGG) database serves as a valuable systems biology resource and is widely utilized in diverse research fields. However, existing software does not allow flexible visualization and network analyses of the vast and complex KEGG data. We developed ggkegg, an R package that integrates KEGG information with ggplot2 and ggraph. ggkegg enables enhanced visualization and network analyses of KEGG data. We demonstrate the utility of the package by providing examples of its application in single-cell, bulk transcriptome, and microbiome analyses. ggkegg may empower researchers to analyze complex biological networks and present their results effectively.
The package and user documentation are available at: https://github.com/noriakis/ggkegg.
京都基因与基因组百科全书（KEGG）数据库是一个有价值的系统生物学资源，被广泛应用于多个研究领域。然而，现有的软件无法灵活地可视化和分析庞大而复杂的 KEGG 数据。我们开发了 ggkegg，这是一个 R 包，它将 KEGG 信息与 ggplot2 和 ggraph 集成在一起。ggkegg 可以增强 KEGG 数据的可视化和网络分析。我们通过提供单细胞、批量转录组和微生物组分析应用示例来展示该包的实用性。ggkegg 可以帮助研究人员分析复杂的生物网络并有效地呈现他们的结果。
该包及其用户文档可在以下网址获得：https://github.com/noriakis/ggkegg。
