The State of Single-Cell Atlas Data Visualization in the Biological Literature

Recent advancements have enabled tissue samples to be profiled at the unprecedented level of detail of a single cell. Analysis of these data has enabled discoveries that are relevant to understanding disease and developing therapeutics. Large-scale profiling efforts are underway, which aim to generate "atlas" resources that catalog cellular archetypes, including biomarkers and spatial locations. While the problem of cellular data visualization is not new, the size, resolution, and heterogeneity of single-cell atlas datasets present challenges and opportunities. We survey the usage of visualization to interpret single-cell atlas datasets by assessing over 1800 figure panels from 45 biological publications. We intend for this report to serve as a foundational resource for the visualization community as atlas-scale single-cell datasets are emerging rapidly with aims of advancing our understanding of biological function in health and disease.

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Publication Details

Journal
IEEE Computer Graphics and Applications
Published
2025-06-27
DOI
https://doi.org/10.1109/mcg.2025.3583979
Citations
1
Primary Topic
Cell Image Analysis Techniques
Type
article
Field-Weighted Citation Impact
1.63

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article

The State of Single-Cell Atlas Data Visualization in the Biological Literature

Simon Warchol, Hanspeter Pfister, Thomas Chris Smits, Robert Krueger et al.
1 citations
IEEE Computer Graphics and Applications
Cell Image Analysis Techniques
1.63
article

The State of Single-Cell Atlas Data Visualization in the Biological Literature

Simon Warchol, Hanspeter Pfister, Thomas Chris Smits, Robert Krueger, Grace Guo, Nils Gehlenborg, Eric Mörth, Mark S. Keller, Qianwen Wang
article en
1 citations

Abstract

Recent advancements have enabled tissue samples to be profiled at the unprecedented level of detail of a single cell. Analysis of these data has enabled discoveries that are relevant to understanding disease and developing therapeutics. Large-scale profiling efforts are underway, which aim to generate "atlas" resources that catalog cellular archetypes, including biomarkers and spatial locations. While the problem of cellular data visualization is not new, the size, resolution, and heterogeneity of single-cell atlas datasets present challenges and opportunities. We survey the usage of visualization to interpret single-cell atlas datasets by assessing over 1800 figure panels from 45 biological publications. We intend for this report to serve as a foundational resource for the visualization community as atlas-scale single-cell datasets are emerging rapidly with aims of advancing our understanding of biological function in health and disease.

IEEE Computer Graphics and ApplicationsVol. 45(5)
University of Minnesota (US), Harvard University (US), Twin Cities Orthopedics (US), New York University (US)
National Institutes of Health
Openalex Percentile: Top 14%
Cell Image Analysis Techniques
1.63
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The State of Single-Cell Atlas Data Visualization in the Biological Literature — Simon Warchol, Hanspeter Pfister, et al. · IEEE Computer Graphics and Applications (2025) | TGRS Research Map | TGRS