RT Journal Article
SR Electronic
T1 cellxgene: a performant, scalable exploration platform for high dimensional sparse matrices
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 2021.04.05.438318
DO 10.1101/2021.04.05.438318
A1 Colin Megill
A1 Bruce Martin
A1 Charlotte Weaver
A1 Sidney Bell
A1 Lia Prins
A1 Seve Badajoz
A1 Brian McCandless
A1 Angela Oliveira Pisco
A1 Marcus Kinsella
A1 Fiona Griffin
A1 Justin Kiggins
A1 Genevieve Haliburton
A1 Arathi Mani
A1 Matthew Weiden
A1 Madison Dunitz
A1 Maximilian Lombardo
A1 Timmy Huang
A1 Trent Smith
A1 Signe Chambers
A1 Jeremy Freeman
A1 Jonah Cool
A1 Ambrose Carr
YR 2021
UL http://biorxiv.org/content/early/2021/04/06/2021.04.05.438318.abstract
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.