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

Public summary

* Seamless with ggplot2, aplot enables unified analysis across multiple data types.

* Aplot excels at multi-omics, integrating genomics, transcriptomics, and proteomics for deeper insights.

* Its modular workflows simplify building complex figures, eliminating manual adjustments in data alignment.

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 aplot 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. Aplot’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.