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

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...

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Autores principales: Sato, Noriaki, Uematsu, Miho, Fujimoto, Kosuke, Uematsu, Satoshi, Imoto, Seiya
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10612400/
https://www.ncbi.nlm.nih.gov/pubmed/37846038
http://dx.doi.org/10.1093/bioinformatics/btad622
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author Sato, Noriaki
Uematsu, Miho
Fujimoto, Kosuke
Uematsu, Satoshi
Imoto, Seiya
author_facet Sato, Noriaki
Uematsu, Miho
Fujimoto, Kosuke
Uematsu, Satoshi
Imoto, Seiya
author_sort Sato, Noriaki
collection PubMed
description 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.
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spelling pubmed-106124002023-10-29 ggkegg: analysis and visualization of KEGG data utilizing the grammar of graphics Sato, Noriaki Uematsu, Miho Fujimoto, Kosuke Uematsu, Satoshi Imoto, Seiya Bioinformatics Applications Note 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. Oxford University Press 2023-10-16 /pmc/articles/PMC10612400/ /pubmed/37846038 http://dx.doi.org/10.1093/bioinformatics/btad622 Text en © The Author(s) 2023. Published by Oxford University Press. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Applications Note
Sato, Noriaki
Uematsu, Miho
Fujimoto, Kosuke
Uematsu, Satoshi
Imoto, Seiya
ggkegg: analysis and visualization of KEGG data utilizing the grammar of graphics
title ggkegg: analysis and visualization of KEGG data utilizing the grammar of graphics
title_full ggkegg: analysis and visualization of KEGG data utilizing the grammar of graphics
title_fullStr ggkegg: analysis and visualization of KEGG data utilizing the grammar of graphics
title_full_unstemmed ggkegg: analysis and visualization of KEGG data utilizing the grammar of graphics
title_short ggkegg: analysis and visualization of KEGG data utilizing the grammar of graphics
title_sort ggkegg: analysis and visualization of kegg data utilizing the grammar of graphics
topic Applications Note
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10612400/
https://www.ncbi.nlm.nih.gov/pubmed/37846038
http://dx.doi.org/10.1093/bioinformatics/btad622
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