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This is the development version of escheR; for the stable release version, see escheR.

Unified multi-dimensional visualizations with Gestalt principles

Bioconductor version: Development (3.20)

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 < at>

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


To install this package, start R (version "4.4") and enter:

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

# The following initializes usage of Bioc devel


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 1.5.0
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
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Suggests STexampleData, BumpyMatrix, knitr, rmarkdown, BiocStyle, ggpubr, scran, scater, scuttle, Seurat, hexbin
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Depends On Me
Imports Me SpotSweeper
Suggests Me tpSVG
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Follow Installation instructions to use this package in your R session.

Source Package escheR_1.5.0.tar.gz
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macOS Binary (x86_64) escheR_1.5.0.tgz
macOS Binary (arm64) escheR_1.5.0.tgz
Source Repository git clone
Source Repository (Developer Access) git clone
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