escheR: Unified multi-dimensional visualizations with Gestalt principles

Image credit: bioRxiv

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.

Publication
Bioinformatics Advances
Louise A. Huuki-Myers
Louise A. Huuki-Myers
Research Associate 2020-2022, Staff Scientist I, Data Science 2022-ongoing, PhD Student 2024-ongoing
Leonardo Collado-Torres
Leonardo Collado-Torres
Investigator @ LIBD, Assistant Professor, Department of Biostatistics @ JHBSPH

#rstats @Bioconductor/🧠 genomics @LieberInstitute/@lcgunam @jhubiostat @jtleek @andrewejaffe alumni/@LIBDrstats @CDSBMexico co-founder