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Bioinformatics AdvancesBioinformaticsPeer-reviewed journal article

escheR: Unified multi-dimensional visualizations with Gestalt principles

Boyi GuoiD, Louise A. Huuki-MyersiD, Melissa Grant‐PetersiD, Leonardo Collado‐TorresiD, Stephanie C. HicksiD

PDFDOIPreprint

Abstract

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 implementationThe open source R package escheR is freely available on Bioconductor (bioconductor.org/packages/escheR).

Citations
13
FWCI
1.18
Field percentile
top 21%

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