ggkegg: analysis and visualization of KEGG data utilizing the grammar of graphics

Noriaki Sato; Miho Uematsu; Kosuke Fujimoto; Satoshi Uematsu; Seiya Imoto

doi:10.1093/bioinformatics/btad622

ggkegg: analysis and visualization of KEGG data utilizing the grammar of graphics

Bioinformatics. 2023 Oct 3;39(10):btad622. doi: 10.1093/bioinformatics/btad622.

Authors

Noriaki Sato¹, Miho Uematsu^{2

3}, Kosuke Fujimoto^{2

3}, Satoshi Uematsu^{2

3}, Seiya Imoto¹

Affiliations

¹ 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.
² Department of Immunology and Genomics, Graduate School of Medicine, Osaka Metropolitan University, Osaka 545-8585, Japan.
³ Division of Metagenome Medicine, Human Genome Center, The Institute of Medical Science, The University of Tokyo, Tokyo 108-8639, Japan.

Abstract

Summary: 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.

Availability and implementation: The package and user documentation are available at: https://github.com/noriakis/ggkegg.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Documentation
Genome*
Software*