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Updated: Jul 8, 2025

A Psychophysics Paradigm for the Collection and Analysis of Similarity Judgments
Published on: March 1, 2022
escheR: unified multi-dimensional visualizations with Gestalt principles
Boyi Guo1, Louise A Huuki-Myers2, Melissa Grant-Peters3,4
1Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, 21205, United States.
Summary:
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 an 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.
Availability And Implementation:
The open source R package escheR is freely available on Bioconductor (https://bioconductor.org/packages/escheR).
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