ggalign

The ggalign package provides an integrative framework for composable visualization, enabling the construction of complex multi-plot layouts—including insets, circular arrangements, and multi-panel compositions. Built on the grammar of graphics, it introduces tools to align, stack, and nest plots, making it easy to link related views, overlay clustering results, or highlight shared patterns. Designed for high-dimensional data contexts such as genomics, transcriptomics, and microbiome studies, it simplifies the creation of richly annotated, publication-ready figures from diverse visual components.

Why use `ggalign`?

ggalign focuses on aligning observations across multiple plots. If you’ve ever struggled with aligning plots with self-contained ordering (like dendrogram), or applying consistent grouping or ordering across multiple plots (e.g., with k-means clustering), ggalign is designed to make this easier. The package integrates seamlessly with ggplot2, providing the flexibility to use its geoms, scales, and other components for complex visualizations.

Installation

You can install ggalign from CRAN using:

install.packages("ggalign")

Alternatively, install the development version from r-universe with:

install.packages("ggalign",
    repos = c("https://yunuuuu.r-universe.dev", "https://cloud.r-project.org")
)

or from GitHub with:

# install.packages("remotes")
remotes::install_github("Yunuuuu/ggalign")

Learning ggalign

Full reference documentation: https://yunuuuu.github.io/ggalign/
Complete tutorial book: https://yunuuuu.github.io/ggalign-book/
Gallery of examples: https://yunuuuu.github.io/ggalign-gallery/

Design features

Examples

Comparison with other composable visualization tools

		`ggalign`	`marsilea`	`ComplexHeatmap`
Language		R	Python	R
User Interface		Declarative	Declarative	Functional
Plot System		ggplot2 (Advanced plot system built on grid system)	Matplotlib	grid
Focus		General-purpose composable visualization	Grid-based composable visualization	Heatmap
StackLayout		✅	✅	✅
QuadLayout		✅	✅	Heatmap Only (discrete variables)
CircleLayout		✅	❌	❌
Relationship	One-to-One	✅	✅	✅
	One-to-Many/Many-to-One	✅	❌	❌
	Many-to-Many	✅	❌	❌
	Crosswise	✅	❌	❌
Annotate observations		✅	❌	✅
Fully Compatible with ggplot2		✅	❌	❌

Feature and specification comparison

Specification	`ggalign`	`marsilea`	`ComplexHeatmap`
Reorder observations	✅	✅	Heatmap Only
Group observations into different panels	✅	✅	Heatmap Only
Clustering algorithm	Kmeans,Hierarchical Clustering and arbitary algorithm	❌	Kmeans,Hierarchical Clustering and arbitary algorithm
Legends Creation	Automatic	Automatic	Limited automatic, requires manual add
Legends Position	Anywhere; independently controllable per plot	Anywhere	Fixed to one of four sides
Dendrogram	Tree from both `hclust` or `ape`	`hclust` only	`hclust` only
Tanglegram	✅	❌	❌
3D Heatmap	✅	❌	✅
Oncoplot	✅	✅	✅
UpSet plot	✅	✅	✅

Acknowledgements

I would like to express my sincere gratitude to the contributors of the ggplot2 project for providing a powerful and flexible framework for data visualization in R. Their work laid the foundation for the functionality and design of this package. I would also like to thank the patchwork project, from which the core coding for the plot composer was adapted. The patchwork library provided a useful mechanism for combining and aligning plots, which was modified to suit the needs of this package. Without the contributions of these open-source projects, this package would not have been possible.

Additionally, I would like to extend my heartfelt thanks to @teunbrand, who has fulfilled my numerous feature requests, and assisted with the integration of new functions into ggplot2.