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arXiv · 2510.09554

scellop: A Scalable Redesign of Cell Population Plots for Single-Cell Data

Thomas C. Smits·Nikolay Akhmetov·Tiffany S. Liaw·Mark S. Keller·Eric Mörth·Nils Gehlenborg
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Abstract

Summary: Cell population plots are visualizations showing cell population distributions in biological samples with single-cell data, traditionally shown with stacked bar charts. Here, we address issues with this approach, particularly its limited scalability with increasing number of cell types and samples, and present scellop, a novel interactive cell population viewer combining visual encodings optimized for common user tasks in studying populations of cells across samples or conditions. Availability and Implementation: Scellop is available under the MIT licence at https://github.com/hms-dbmi/scellop, and is available on PyPI (https://pypi.org/project/cellpop/) and NPM (https://www.npmjs.com/package/cellpop). A demo is available at https://scellop.netlify.app/.

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Thomas C. Smits, Nikolay Akhmetov, Tiffany S. Liaw, Mark S. Keller, Eric Mörth, Nils Gehlenborg. 2025-10-10. scellop: A Scalable Redesign of Cell Population Plots for Single-Cell Data. https://arxiv.org/abs/2510.09554

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