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ggkegg:使用图形语法分析和可视化KEGG数据

Noriaki Sato¹, Miho Uematsu^2,3, Kosuke Fujimoto^2,3

¹Division 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.

Bioinformatics (Oxford, England)

|October 17, 2023

概括

研究人员现在可以灵活地使用ggkegg来可视化和分析复杂的生物网络,ggkegg是一个新的R包,它将京都基因和基因组百科全书 (KEGG) 数据与高级图形工具集成在一起,以获得增强的系统生物学见解.

科学领域:

系统生物学系统生物学
生物信息学是一种生物信息学.
计算生物学计算生物学

背景情况:

基因和基因组的京都百科全书 (KEGG) 是系统生物学研究的关键资源.
目前的工具缺乏灵活性来可视化和分析复杂的KEGG路径数据.
这种限制阻碍了对生物网络的深入探索.

研究的目的:

开发一个新的R包,ggkegg,用于增强KEGG数据的可视化和网络分析.
为研究人员提供一个灵活的工具来探索复杂的生物系统.
为了促进基于KEGG的分析结果的有效展示.

主要方法:

开发了ggkegg,一个R包,将KEGG数据与ggplot2和ggraph集成在一起.
实现了用于灵活可视化KEGG路径的功能.
启用了对生物数据的网络分析功能.

主要成果:

ggkegg提供了对KEGG通路的增强可视化.
该包支持生物数据的灵活网络分析.
在单细胞,批量转录组和微生物组分析中证明有用.

结论:

ggkegg使研究人员能够分析复杂的生物网络.
"R包"有助于有效地呈现系统生物学发现.
ggkegg增强了KEGG数据库对各种研究应用的实用性.

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