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README.Rmd
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---
output: github_document
params:
book: https://yunuuuu.github.io/ggalign-book/
---
<!-- README.md is generated from README.Rmd. Please edit that file -->
```{r, include = FALSE}
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>",
fig.path = "man/figures/README-",
out.width = "100%"
)
```
```{r echo=FALSE}
url <- params[["book"]]
```
# ggalign <a href="https://yunuuuu.github.io/ggalign/"><img src="man/figures/logo.png" align="right" height="139" alt="ggalign website" /></a>
<!-- badges: start -->
[](https://github.com/Yunuuuu/ggalign/actions/workflows/R-CMD-check.yaml)
[](https://app.codecov.io/gh/Yunuuuu/ggalign?branch=main)
[](https://CRAN.R-project.org/package=ggalign)
[](https://cran.r-project.org/package=ggalign)
[](https://doi.org/10.5281/zenodo.14825328)
<!-- badges: end -->
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.
## Why use `ggalign`?
`ggalign` focuses on aligning observations across multiple plots. It leverages
the `"number of observations"` in the
[vctrs](https://vctrs.r-lib.org/reference/vec_size.html) 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.
## Installation
You can install `ggalign` from `CRAN` using:
```{r, eval=FALSE}
install.packages("ggalign")
```
Alternatively, install the development version from
[r-universe](https://yunuuuu.r-universe.dev/ggalign) with:
```{r, eval=FALSE}
install.packages("ggalign",
repos = c("https://yunuuuu.r-universe.dev", "https://cloud.r-project.org")
)
```
or from [GitHub](https://github.com/Yunuuuu/ggalign) with:
```{r, eval=FALSE}
# install.packages("remotes")
remotes::install_github("Yunuuuu/ggalign")
```
## Learning ggalign
1. The complete tutorial is available at: <https://yunuuuu.github.io/ggalign-book/>
2. For the full reference documentation, visit: <https://yunuuuu.github.io/ggalign/>
## Examples
## Compare with other similar tools
```{=html}
<table class="table"><thead>
<tr>
<th colspan="2"></th>
<th> <code>ggalign</code> </th>
<th> <code>marsilea</code> </th>
<th> <code>aplot</code> </th>
<th> <code>ComplexHeatmap</code> </th>
</tr></thead>
<tbody>
<tr>
<td colspan="2"> <strong>Language</strong> </td>
<td>R</td>
<td>Python</td>
<td>R</td>
<td>R</td>
</tr>
<tr>
<td colspan="2"> <strong>User Interface</strong> </td>
<td>Declarative</td>
<td>Declarative</td>
<td>Declarative+Functional</td>
<td>Functional</td>
</tr>
<tr>
<td colspan="2"> <strong>Plot System</strong> </td>
<td>ggplot2 (Advanced plot system built on grid system)</td>
<td>Matplotlib</td>
<td>ggplot2 (Advanced plot system built on grid system)</td>
<td>grid</td>
</tr>
<tr>
<td colspan="2"> <strong>Focus</strong> </td>
<td>Composable Visualization</td>
<td>Composable Visualization</td>
<td>Composable Visualization</td>
<td>Heatmap</td>
</tr>
<tr>
<td colspan="2"> <strong>StackLayout</strong> </td>
<td>✅</td>
<td>✅</td>
<td>✅</td>
<td>✅</td>
</tr>
<tr>
<td colspan="2"> <strong>QuadLayout</strong> </td>
<td>✅</td>
<td>✅</td>
<td>✅</td>
<td>Heatmap Only (discrete variables)</td>
</tr>
<tr>
<td colspan="2"> <strong>CircleLayout</strong> </td>
<td>✅</td>
<td>❌</td>
<td>❌</td>
<td>❌</td>
</tr>
<tr>
<td rowspan="4"> <strong>Relationship</strong> </td>
<td> <strong>One-to-One</strong> </td>
<td>✅</td>
<td>✅</td>
<td>✅</td>
<td>✅</td>
</tr>
<tr>
<td> <strong>One-to-Many</strong>/<strong>Many-to-One</strong> </td>
<td>✅</td>
<td>❌</td>
<td>❌</td>
<td>❌</td>
</tr>
<tr>
<td> <strong>Many-to-Many</strong> </td>
<td>✅</td>
<td>❌</td>
<td>❌</td>
<td>❌</td>
</tr>
<tr>
<td> <strong>Crosswise</strong> </td>
<td>✅</td>
<td>❌</td>
<td>❌</td>
<td>❌</td>
</tr>
<tr>
<td colspan="2"> <strong>Annotate observations</strong> </td>
<td>✅</td>
<td>❌</td>
<td>❌</td>
<td>✅</td>
</tr>
<tr>
<td colspan="2"> <strong>Fully Compatible with ggplot2</strong> </td>
<td>✅</td>
<td>❌</td>
<td>✅</td>
<td>❌</td>
</tr>
</tbody></table>
```
## Comparison of specifications with other similar tools
| Specification | `ggalign` | `marsilea` | `aplot` | `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 | Manual | Automatic | Limited automatic, requires manual add |
| **Legends Position** | Anywhere, can be controlled for a single plot | Anywhere | Anywhere | Four sides, can only be placed on one side at a time |
| **Dendrogram** | Tree from both `hclust` or `ape` | `hclust` only | Tree from both `hclust` or `ape` | `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.