escheR
Unified multi-dimensional visualizations with Gestalt principles
Bioconductor version: 3.23 · Package version: 1.12.0
The creation of effective visualizations is a fundamental component of data analysis. In biomedical research, new challenges are emerging to visualize multi-dimensional data in a 2D space, but current data visualization tools have limited capabilities. To address this problem, we leverage Gestalt principles to improve the design and interpretability of multi-dimensional data in 2D data visualizations, layering aesthetics to display multiple variables. The proposed visualization can be applied to spatially-resolved transcriptomics data, but also broadly to data visualized in 2D space, such as embedding visualizations. We provide this open source R package escheR, which is built off of the state-of-the-art ggplot2 visualization framework and can be seamlessly integrated into genomics toolboxes and workflows.
Installation
if (!require("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install("escheR") Details
| Maintainer | Boyi Guo <boyi.guo.work@gmail.com> |
| Author | Boyi Guo [aut, cre] (ORCID: <https://orcid.org/0000-0003-2950-2349>), Stephanie C. Hicks [aut] (ORCID: <https://orcid.org/0000-0002-7858-0231>), Erik D. Nelson [ctb] (ORCID: <https://orcid.org/0000-0001-8477-0982>) |
| License | MIT + file LICENSE |
| URL | https://github.com/boyiguo1/escheR |
| Bug Reports | https://github.com/boyiguo1/escheR/issues |
| Downloads rank | 364 |
| Source branch | RELEASE_3_23 |
| biocViews | SingleCell, Software, Spatial, Transcriptomics, Visualization |
Documentation
Download
Dependencies
Depends: ggplot2, R (>= 4.3)
Imports: SpatialExperiment (>= 1.6.1), SingleCellExperiment, rlang, SummarizedExperiment
Suggests: STexampleData, BumpyMatrix, knitr, rmarkdown, BiocStyle, ggpubr, scran, scater, scuttle, Seurat, hexbin