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. 2023 Dec 6;3(1):vbad179.
doi: 10.1093/bioadv/vbad179. eCollection 2023.

escheR: unified multi-dimensional visualizations with Gestalt principles

Boyi Guo  1 , Louise A Huuki-Myers  2 , Melissa Grant-Peters  3   4 , Leonardo Collado-Torres  1   2 , Stephanie C Hicks  1   5   6   7
Affiliations

escheR: unified multi-dimensional visualizations with Gestalt principles

Boyi Guo et al. Bioinform Adv. .

Abstract

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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Conflict of interest statement

None declared.

Figures

Figure 1.
Figure 1.
escheR enables multidimensional spatial visualizations following the Gestalt principles of design. (A and B) The traditional visualization displays the colocalization plot of the expression of two genes EFNA5 and EPHA5 (A) and the spatial domains from the dorsolateral prefrontal cortex in postmortem human brain (Huuki-Myers et al. 2023) (B) side-by-side, creating challenges to cognitively connecting colocalization status to spatial domains. (C) The watercolor effect enables displaying spatial domains by color-coding only outlines of circles. (D) escheR enables the multidimensional in situ visualization that simultaneously displays the cortex layers and the colocalization status, substantially improving interpretability.
Figure 2.
Figure 2.
escheR improves multidimensional embedding visualizations. The gene expression of POMGNT1 among peripheral blood mononuclear cells (Hansen et al., 2022) under the UMAP representation. (A) The schex R/Bioconductor package uses color-coded convex hulls to annotate data-driven cell types, creating confusion when interpreting hexagons in overlapping hulls. (B) escheR plots hexagon-specific membership to avoid substantial overlapping of cluster membership. Due to the binning strategy, cautions in interpretation are needed due to possible cluster intermixing within each hexagon.
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References

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