eLifeBioinformaticsPeer-reviewed journal article
scatterHatch: an R/Bioconductor package for colorblind accessible visualization of single-cell data
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.
- assay: scRNA-seq
- research focus: software / tool
- research focus: dimensionality reduction
- approach: statistical model
- Citations
- 11
- FWCI
- 0.74
- Field percentile
- top 31%
Reproducibility ledger
Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.
Sign in to file a reproducibility report.
Related papers
- Single Cell Viewer (SCV): An interactive visualization data portal for single cell RNA sequence data
Shuoguo Wang, Constance Brett, … Kandasamy Ravi·bioRxiv·Jun 12, 2019
- scSVA: an interactive tool for big data visualization and exploration in single-cell omics
Marcin Tabaka, Joshua Gould, Aviv Regev·bioRxiv·Jan 6, 2019
- scPyviewer: a Python-native interactive viewer from AnnData single-cell data
Hao Xuan, Yu Huang, … Xiangtao Liu·bioRxiv·Sep 11, 2026
- scatterbar: an R package for visualizing proportional data across spatially resolved coordinates
Dee Velazquez, Jean Fan·BioinformaticsPeer-reviewed·Jan 28, 2025
- shinyUMAP: an online tool for promoting understanding of single cell omics data visualization
Rohan Misra, Kevin O’Leary, … Deyou Zheng·bioRxiv·Aug 27, 2025
- SCelVis: Powerful explorative single cell data analysis on the desktop and in the cloud
Benedikt Obermayer, Manuel Holtgrewe, … Dieter Beule·PeerJPeer-reviewed·Feb 19, 2020