Package: cellxgene
an interactive explorer for single-cell transcriptomics dataCZ CELLxGENE Annotate (pronounced "cell-by-gene") is an interactive data explorer for single-cell datasets, such as those coming from theHuman Cell Atlas. Leveraging modern web development techniques to enable fast visualizations of at least 1 million cells, we hope to enable biologists and computational researchers to explore their data.Whether you need to visualize one thousand cells or one million, CELLxGENE Annotate helps you gain insight into your single-cell data.Getting startedThe comprehensive guide to CZ CELLxGENE AnnotateThe CZ CELLxGENE Annotate documentation is your one-stop-shop for information about CELLxGENE Annotate! You may be particularly interested in:Seeingwhat Annotate can doLearning more about AnnotateinstallationandusagePreparing your own datafor use in AnnotateChecking outour roadmapfor future developmentContributingto AnnotateQuick startTo install CELLxGENE Annotate you need Python 3.6+. We recommendinstalling Annotate into a conda or virtual environment.Install the package.pipinstallcellxgeneLaunch Annotate with an exampleanndatafilecellxgenelaunchhttps://cellxgene-example-data.czi.technology/pbmc3k.h5adTo explore more datasets already formatted for Annotate, check out theDemo dataor
seePreparing your datato learn more about formatting your own
data for CELLxGENE Annotate.Supported browsersCELLxGENE Annotate currently supports the following browsers:Google Chrome 61+Edge 15+Firefox 60+Pleasefile an issueif you would like us to add support for an unsupported browser.Finding helpWe'd love to hear from you!
For questions, suggestions, or accolades,join the#cellxgene-userschannel on the CZI Science Slackand say "hi!".For any errors,report bugs on Github.Developing with CZ CELLxGENE AnnotateContributingWe warmly welcome contributions from the community! Please see ourcontributing guideand don't hesitate to open an issue or send a pull request to improve CELLxGENE Annotate. Please see thedev_docsfor pull request suggestions, unit test details, local documentation preview, and other development specifics.This project adheres to the Contributor Covenantcode of conduct. By participating, you are expected to uphold this code. Please report unacceptable behavior toopensource@chanzuckerberg.com.ReuseThis project was started with the sole goal of empowering the scientific community to explore and understand their data.
As such, we encourage other scientific tool builders in academia or industry to adopt the patterns, tools, and code from
this project. All code is freely available for reuse under theMIT license.Before extending CELLxGENE Annotate, we encourage you to reach out to us with ideas or questions. It might be possible that an
extension could be directly contributed, which would make it available for a wider audience, or that it's on ourroadmapand under active development.See theCELLxGENE extensionssection of our documentation for examples of community use and CELLxGENE extensions.SecurityIf you believe you have found a security issue, we would appreciate notification. Please send email tosecurity@chanzuckerberg.com.InspirationWe've been heavily inspired by several other related single-cell visualization projects, including theUCSC Cell Browser,Cytoscape,Xena,ASAP,GenePattern, and many others. We hope to explore collaborations where useful as this community works together on improving interactive visualization for single-cell data.We were inspired by Mike Bostock and thecrossfilterteam for the design of our filtering implementation.We have been working closely with thescanpyteam to integrate with their awesome analysis tools. Special thanks to Alex Wolf, Fabian Theis, and the rest of the team for their help during development and for providing an example dataset.We are eager to explore integrations with other computational backends such asSeuratorBioconductor