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Unified multi-dimensional visualizations with Gestalt principles

Bioconductor version: Release (3.18)

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.

Author: Boyi Guo [aut, cre] , Stephanie C. Hicks [aut] , Erik D. Nelson [ctb]

Maintainer: Boyi Guo <boyi.guo.work at gmail.com>

Citation (from within R, enter citation("escheR")):


To install this package, start R (version "4.3") and enter:

if (!require("BiocManager", quietly = TRUE))


For older versions of R, please refer to the appropriate Bioconductor release.


To view documentation for the version of this package installed in your system, start R and enter:

beyond_visium HTML R Script
Getting Start with `escheR` HTML R Script
Reference Manual PDF


biocViews SingleCell, Software, Spatial, Transcriptomics, Visualization
Version 1.2.0
In Bioconductor since BioC 3.17 (R-4.3) (1 year)
License MIT + file LICENSE
Depends ggplot2, R (>= 4.3)
Imports SpatialExperiment(>= 1.6.1), SingleCellExperiment, rlang, SummarizedExperiment
System Requirements
URL https://github.com/boyiguo1/escheR
Bug Reports https://github.com/boyiguo1/escheR/issues
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Suggests STexampleData, BumpyMatrix, knitr, rmarkdown, BiocStyle, ggpubr, scran, scater, scuttle, Seurat
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Package Archives

Follow Installation instructions to use this package in your R session.

Source Package escheR_1.2.0.tar.gz
Windows Binary escheR_1.2.0.zip
macOS Binary (x86_64) escheR_1.2.0.tgz
macOS Binary (arm64) escheR_1.2.0.tgz
Source Repository git clone https://git.bioconductor.org/packages/escheR
Source Repository (Developer Access) git clone git@git.bioconductor.org:packages/escheR
Bioc Package Browser https://code.bioconductor.org/browse/escheR/
Package Short Url https://bioconductor.org/packages/escheR/
Package Downloads Report Download Stats