TY - JOUR TI - Generating colorblind-friendly scatter plots for single-cell data AU - Guha, Tejas AU - Fertig, Elana J AU - Deshpande, Atul A2 - Choi, Jungmin A2 - Zaidi, Mone A2 - Bunis, Daniel G VL - 11 PY - 2022 DA - 2022/12/16 SP - e82128 C1 - eLife 2022;11:e82128 DO - 10.7554/eLife.82128 UR - https://doi.org/10.7554/eLife.82128 AB - 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. KW - visualization KW - accessibility KW - software tool KW - single-cell KW - spatial data KW - UMAP JF - eLife SN - 2050-084X PB - eLife Sciences Publications, Ltd ER -