多模态图形:用于图形集成多omics数据集的R包.
Foziya Ahmed Mohammed1,2,3, El Hadj Malick Fall4, Kula Kekeba Tune1,2
1Department of Software Engineering, College of Electrical and Mechanical Engineering, Addis Ababa Science and Technology University, 16417, Addis Ababa, Ethiopia.
BMC bioinformatics
|October 22, 2025
概括
本研究介绍了MultiModalGraphics,这是一个用于创建注释生物数据可视化的R包. 它通过嵌入统计总结来增强定量解释,改进多主题数据分析.
科学领域:
- 生物信息学是一种生物信息学.
- 计算生物学 计算生物学
- 数据可视化 数据可视化
背景情况:
- 多模式生物数据集是高维和复杂的.
- 现有的可视化工具缺乏整合的统计和计算注释.
- 有效的多学科数据的定量解释是具有挑战性的.
研究的目的:
- 介绍MultiModalGraphics,一个用于创建注释散射图和热图的R包.
- 为了促进对多层和高维度生物数据的定量解释.
- 简化生物信息学的工作流程,从分析到可视化.
主要方法:
- 开发了一个R包,MultiModalGraphics.
- 实现统计总结的无嵌入 (折叠变化,p值,q值,标准偏差).
- 确保与生物导体包 (MultiAssayExperiment,limma,voom,iClusterPlus) 的互操作性.
主要成果:
- 多模态图允许对可视化进行直接的定量比较.
- 该软件包支持分析多维和高维生物数据.
- 案例研究证明了对现实世界数据集的实际实用性.
结论:
- 多模态图增强了复杂的生物数据的定量解释.
- 该软件包将统计注释直接集成到可视化中.
- 它为多omics数据分析和可视化工作流提供了简化的解决方案.
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