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scellop: a scalable redesign of cell population plots for single-cell data
Thomas C Smits1, Nikolay Akhmetov1, Tiffany S Liaw1
1Department of Biomedical Informatics, Harvard Medical School, Boston, MA 02115, United States.
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/scellop/) and NPM (https://www.npmjs.com/package/scellop). A demo is available at https://scellop.netlify.app/.
