The State of Single-Cell Atlas Data Visualization in the Biological Literature
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| Titel: | The State of Single-Cell Atlas Data Visualization in the Biological Literature |
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| Autoren: | Mark S. Keller, Eric Mörth, Thomas C. Smits, Simon Warchol, Grace Guo, Qianwen Wang, Robert Krueger, Hanspeter Pfister, Nils Gehlenborg |
| Quelle: | IEEE Computer Graphics and Applications. 45:18-34 |
| Publication Status: | Preprint |
| Verlagsinformationen: | Center for Open Science, 2025. |
| Publikationsjahr: | 2025 |
| Schlagwörter: | Cell and Developmental Biology, Computer Sciences, Graphics and Human Computer Interfaces, Physical Sciences and Mathematics, Life Sciences, Cell Biology |
| Beschreibung: | Recent advancements have enabled tissue samples to be profiled at the unprecedented level of detail of a single cell. Analysis of single-cell data has enabled life scientists to generate hypotheses and make discoveries that are relevant to understanding disease and developing therapeutics. Large-scale single-cell profiling efforts are underway with the aim to generate 'atlas' resources that catalog cellular archetypes including biomarkers and spatial locations. While the problem of visualization of cellular data is not new, the increasing size, resolution, and heterogeneity of single-cell atlas datasets presents challenges and opportunities for visualization researchers. In this report, we situate this research into the broader context of biomedical and high-dimensional data visualization and survey the usage of visualization to interpret single-cell atlas datasets by assessing over 1,800 figure panels from 45 biological publications. We intend for this report to serve as a foundational resource for the visualization community as single-cell techniques and atlas-scale datasets are emerging rapidly with aims of advancing our understanding of biological function in health and disease. |
| Publikationsart: | Article |
| ISSN: | 1558-1756 0272-1716 |
| DOI: | 10.31219/osf.io/yt3xz_v1 |
| DOI: | 10.1109/mcg.2025.3583979 |
| DOI: | 10.31219/osf.io/yt3xz_v2 |
| Rights: | CC BY IEEE Copyright |
| Dokumentencode: | edsair.doi.dedup.....1d15b79a220b384fd140b2550c10814b |
| Datenbank: | OpenAIRE |
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Nájsť tento článok vo Web of Science | Abstract: | Recent advancements have enabled tissue samples to be profiled at the unprecedented level of detail of a single cell. Analysis of single-cell data has enabled life scientists to generate hypotheses and make discoveries that are relevant to understanding disease and developing therapeutics. Large-scale single-cell profiling efforts are underway with the aim to generate 'atlas' resources that catalog cellular archetypes including biomarkers and spatial locations. While the problem of visualization of cellular data is not new, the increasing size, resolution, and heterogeneity of single-cell atlas datasets presents challenges and opportunities for visualization researchers. In this report, we situate this research into the broader context of biomedical and high-dimensional data visualization and survey the usage of visualization to interpret single-cell atlas datasets by assessing over 1,800 figure panels from 45 biological publications. We intend for this report to serve as a foundational resource for the visualization community as single-cell techniques and atlas-scale datasets are emerging rapidly with aims of advancing our understanding of biological function in health and disease. |
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| ISSN: | 15581756 02721716 |
| DOI: | 10.31219/osf.io/yt3xz_v1 |