This package extends ggplot2 by providing advanced tools for aligning and organizing multiple plots, particularly those that automatically reorder observations, such as dendrogram. It offers fine control over layout adjustment and plot annotations, enabling you to create complex, publication-quality visualizations while still using the familiar grammar of ggplot2.
ggalign
focuses on aligning observations across multiple plots. It
leverages the "number of observations"
in the
vctrs package or
NROW()
function to maintain consistency in plot organization.
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.
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")
-
The complete tutorial is available at: https://yunuuuu.github.io/ggalign-book/
-
For the full reference documentation, visit: https://yunuuuu.github.io/ggalign/
Layout Options | ggalign |
ComplexHeatmap |
marsilea |
ggtree |
---|---|---|---|---|
Language | R | R | Python | R |
User Interface | Declarative | Functional | Declarative | Declarative |
Plot System | ggplot2 (Advanced plot system built on grid system) | grid | Matplotlib | ggplot2 (Advanced plot system built on grid system) |
Focus | Composable Visualization | Heatmap | Composable Visualization | tree Data |
Quad Layout | ✅ | Heatmap Only (discrete variables) | ✅ | ❌ |
Stack Layout | ✅ | ✅ | ✅ | ❌ |
Circle Layout | ✅ | ❌ | ❌ | ✅ |
Cross Layout | ✅ | ❌ | ❌ | ❌ |
Ease of Use | Easy for ggplot2 users | Easy for for grid user | Easy for python user | Easy for ggplot2 users |
Fully Compatible with ggplot2 | ✅ | ❌ | ❌ | Limited Geometric layers support |
Functions | ggalign |
ComplexHeatmap |
marsilea |
ggtree |
---|---|---|---|---|
Data input | Various, and can be easily extended | fixed | fixed | Various, and can be easily extended |
Plot Type | Wide variety, provided by ggplot2 | Many, but limited | Many, but limited | Limited Geometric layers support |
Reorder observations | ✅ | Heatmap Only (Cannot be used in Stack Layout) | ✅ | ✅ |
Group observations into different panels | ✅ | Heatmap Only (Cannot be used in Stack Layout) | ✅ | ❌ |
Clustering algorithm | Kmeans,Hierarchical Clustering and arbitary algorithm | Kmeans,Hierarchical Clustering, but can provide clustering group directly | ❌ | ❌ |
Legends Creation | Automatic | Limited automatic, requires manual add | Manual | Automatic |
Legends Position | Anywhere, can be controlled for a single plot | Four sides, can only be placed on one side at a time | ? | Anywhere |
Scientific Color Palettes | Many | Limited | Limited | Many |
Dendrogram | Tree from Both hclust or ape |
hclust only (Cannot be used in Stack Layout) |
hclust only |
Tree from Both hclust or ape |
Tanglegram | ✅ | ❌ | ❌ | ❌ |
3D Heatmap | ✅ | ✅ | ❌ | ❌ |
Oncoplot | ✅ | ✅ | ✅ | ❌ |
UpSet plot | ✅ | ✅ | ✅ | ❌ |
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.