aplot: Simplifying the creation of complex graphs to visualize associations across diverse data types

Effective data visualization is crucial for researchers, revealing patterns, trends, and insights that might otherwise remain hidden. Integrating related visualizations can reveal correlations and relationships that are not evident when analyzing datasets separately. Despite increasing demand, there is a shortage of general tools to seamlessly combine diverse datasets to create complex visual representations. The <i>aplot</i> package addresses this by allowing users to independently create subplots and assemble them into a cohesive composite figure. It automatically reorders datasets for coordinate consistency, removing the need for manual adjustment. This modular approach simplifies the creation of complex visualizations, allowing customization to meet specific needs. <i>Aplot</i>'s versatility is ideal for integrating multi-omics datasets and analytical results for biological insights. The package is freely available on CRAN at https://cran.r-project.org/package=aplot, offering researchers a powerful tool for enhanced data exploration and visualizing workflows.

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Publication Details

Journal
The Innovation
Published
2025-05-22
DOI
https://doi.org/10.1016/j.xinn.2025.100958
Citations
3
Primary Topic
Data Mining Algorithms and Applications
Type
article
Field-Weighted Citation Impact
9.74

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article

aplot: Simplifying the creation of complex graphs to visualize associations across diverse data types

Shuangbin Xu, Junrui Li, Dongqiang Zeng, Chunhui Gao et al.
3 citations
The Innovation
Data Mining Algorithms and Applications
9.74
article

aplot: Simplifying the creation of complex graphs to visualize associations across diverse data types

Shuangbin Xu, Junrui Li, Dongqiang Zeng, Chunhui Gao, Lang Zhou, Shensuo Li, Guangchuang Yu, Rui Wang, Zijing Xie, Silin Tao, Shixiang Wang, Shaodi Wen, Thomas Hackl, Ming Li, Qianwen Wang, Deng Lin, Nan He
article en
3 citations

Abstract

Effective data visualization is crucial for researchers, revealing patterns, trends, and insights that might otherwise remain hidden. Integrating related visualizations can reveal correlations and relationships that are not evident when analyzing datasets separately. Despite increasing demand, there is a shortage of general tools to seamlessly combine diverse datasets to create complex visual representations. The <i>aplot</i> package addresses this by allowing users to independently create subplots and assemble them into a cohesive composite figure. It automatically reorders datasets for coordinate consistency, removing the need for manual adjustment. This modular approach simplifies the creation of complex visualizations, allowing customization to meet specific needs. <i>Aplot</i>'s versatility is ideal for integrating multi-omics datasets and analytical results for biological insights. The package is freely available on CRAN at https://cran.r-project.org/package=aplot, offering researchers a powerful tool for enhanced data exploration and visualizing workflows.

The InnovationVol. 6(9)
Central South University (CN), University of Groningen (NL), Huazhong Agricultural University (CN), Sichuan University (CN), First Affiliated Hospital of Guangzhou Medical University (CN), Nanfang Hospital (CN), Zhujiang Hospital (CN), Jiangsu Cancer Hospital (CN), State Key Laboratory of Biotherapy, Southern Medical University (CN), Nanjing Medical University (CN), Guangzhou Medical University (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 2%
Data Mining Algorithms and Applications
9.74
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