Generating colorblind-friendly scatter plots for single-cell data

Author:

Guha Tejas1,Fertig Elana J23456ORCID,Deshpande Atul234ORCID

Affiliation:

1. Department of Electrical and Computer Engineering, A. James Clark School of Engineering, The University of Maryland

2. Department of Oncology, Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine

3. Convergence Institute, Johns Hopkins University

4. Bloomberg-Kimmel Immunotherapy Institute, Johns Hopkins University School of Medicine

5. Department of Applied Mathematics and Statistics, Johns Hopkins University

6. Department of Biomedical Engineering, Johns Hopkins University School of Medicine

Abstract

Reduced-dimension or spatial in situ scatter plots are widely employed in bioinformatics papers analyzing single-cell data to present phenomena or cell-conditions of interest in cell groups. When displaying these cell groups, color is frequently the only graphical cue used to differentiate them. However, as the complexity of the information presented in these visualizations increases, the usefulness of color as the only visual cue declines, especially for the sizable readership with color-vision deficiencies (CVDs). In this paper, we present scatterHatch, an R package that creates easily interpretable scatter plots by redundant coding of cell groups using colors as well as patterns. We give examples to demonstrate how the scatterHatch plots are more accessible than simple scatter plots when simulated for various types of CVDs.

Funder

National Cancer Institute

Publisher

eLife Sciences Publications, Ltd

Subject

General Immunology and Microbiology,General Biochemistry, Genetics and Molecular Biology,General Medicine,General Neuroscience

Reference18 articles.

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