PT  - JOURNAL ARTICLE
AU  - Colin Megill
AU  - Bruce Martin
AU  - Charlotte Weaver
AU  - Sidney Bell
AU  - Lia Prins
AU  - Seve Badajoz
AU  - Brian McCandless
AU  - Angela Oliveira Pisco
AU  - Marcus Kinsella
AU  - Fiona Griffin
AU  - Justin Kiggins
AU  - Genevieve Haliburton
AU  - Arathi Mani
AU  - Matthew Weiden
AU  - Madison Dunitz
AU  - Maximilian Lombardo
AU  - Timmy Huang
AU  - Trent Smith
AU  - Signe Chambers
AU  - Jeremy Freeman
AU  - Jonah Cool
AU  - Ambrose Carr
TI  - cellxgene: a performant, scalable exploration platform for high dimensional sparse matrices
AID  - 10.1101/2021.04.05.438318
DP  - 2021 Jan 01
TA  - bioRxiv
PG  - 2021.04.05.438318
4099  - http://biorxiv.org/content/early/2021/04/06/2021.04.05.438318.short
4100  - http://biorxiv.org/content/early/2021/04/06/2021.04.05.438318.full
AB  - Quickly and flexibly exploring high-dimensional datasets, such as scRNAseq data, is underserved but critical for hypothesis generation, dataset annotation, publication, sharing, and community reuse. cellxgene is a highly generalizable, web-based interface for exploring high dimensional datasets along categorical, continuous and spatial dimensions, as well as feature annotation. cellxgene is differentiated by its ability to performantly handle millions of observations, and bridges a critical gap by enabling computational and experimental biologists to iteratively ask questions of private and public datasets. In doing so, cellxgene increases the utility and reusability of datasets across the single-cell ecosystem.The codebase can be accessed at https://github.com/chanzuckerberg/cellxgene. For questions and inquiries, please contact cellxgene{at}chanzuckerberg.com.Competing Interest StatementThe authors have declared no competing interest.