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escheR: unified multi-dimensional visualizations with Gestalt principles

Guo, Boyi; Huuki-Myers, Louise A; Grant-Peters, Melissa; Collado-Torres, Leonardo; Hicks, Stephanie C; (2023) escheR: unified multi-dimensional visualizations with Gestalt principles. Bioinformatics Advances , 3 (1) , Article vbad179. 10.1093/bioadv/vbad179. Green open access

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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).

Type: Article
Title: escheR: unified multi-dimensional visualizations with Gestalt principles
Location: England
Open access status: An open access version is available from UCL Discovery
DOI: 10.1093/bioadv/vbad179
Publisher version: http://dx.doi.org/10.1093/bioadv/vbad179
Language: English
Additional information: © The Author(s) 2023. Published by Oxford University Press. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/).
UCL classification: UCL
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > UCL GOS Institute of Child Health
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > UCL GOS Institute of Child Health > Genetics and Genomic Medicine Dept
URI: https://discovery.ucl.ac.uk/id/eprint/10184733
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