Metadata-Version: 2.1
Name: cellxgene
Version: 0.16.8
Summary: Web application for exploration of large scale scRNA-seq datasets
Home-page: https://github.com/chanzuckerberg/cellxgene
Author: Chan Zuckerberg Initiative
Author-email: cellxgene@chanzuckerberg.com
License: MIT
Description: <img src="./docs/cellxgene-logo.png" width="300">
        
        _an interactive explorer for single-cell transcriptomics data_
        
        [![DOI](https://zenodo.org/badge/105615409.svg)](https://zenodo.org/badge/latestdoi/105615409) [![PyPI](https://img.shields.io/pypi/v/cellxgene)](https://pypi.org/project/cellxgene/) [![PyPI - Downloads](https://img.shields.io/pypi/dm/cellxgene)](https://pypistats.org/packages/cellxgene) [![GitHub last commit](https://img.shields.io/github/last-commit/chanzuckerberg/cellxgene)](https://github.com/chanzuckerberg/cellxgene/pulse)
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        cellxgene (pronounced "cell-by-gene") is an interactive data explorer for single-cell transcriptomics datasets, such as those coming from the [Human Cell Atlas](https://humancellatlas.org). 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 helps you gain insight into your single-cell data.
        
        <img src="https://github.com/chanzuckerberg/cellxgene/raw/main/docs/images/crossfilter.gif" width="350" height="200" hspace="30"><img src="https://github.com/chanzuckerberg/cellxgene/raw/main/docs/images/category-breakdown.gif" width="350" height="200" hspace="30">
        
        # Getting started
        
        ### The comprehensive guide to cellxgene
        
        [The cellxgene documentation is your one-stop-shop for information about cellxgene](https://chanzuckerberg.github.io/cellxgene/)! You may be particularly interested in:
        
        - Seeing [what cellxgene can do](https://chanzuckerberg.github.io/cellxgene/posts/gallery)
        - Learning more about cellxgene [installation](https://chanzuckerberg.github.io/cellxgene/posts/install) and [usage](https://chanzuckerberg.github.io/cellxgene/posts/launch)
        - [Preparing your own data](https://chanzuckerberg.github.io/cellxgene/posts/prepare) for use in cellxgene
        - Checking out [our roadmap](https://chanzuckerberg.github.io/cellxgene/posts/roadmap) for future development
        - [Contributing](https://chanzuckerberg.github.io/cellxgene/posts/contribute) to cellxgene
        
        ### Quick start
        
        To install cellxgene you need Python 3.6+. We recommend [installing cellxgene into a conda or virtual environment.](https://chanzuckerberg.github.io/cellxgene/posts/install)
        
        Install the package.
        
        ```bash
        pip install cellxgene
        ```
        
        Launch cellxgene with an example [anndata](https://anndata.readthedocs.io/en/latest/) file
        
        ```bash
        cellxgene launch https://cellxgene-example-data.czi.technology/pbmc3k.h5ad
        ```
        
        To explore more datasets already formatted for cellxgene, check out the [Demo data](https://chanzuckerberg.github.io/cellxgene/posts/demo-data) or
        see [Preparing your data](https://chanzuckerberg.github.io/cellxgene/posts/prepare) to learn more about formatting your own
        data for cellxgene.
        
        ### Supported browsers
        
        cellxgene currently supports the following browsers:
        
        - Google Chrome 61+
        - Edge 15+
        - Firefox 60+
        - Safari 10.1+
        
        Please [file an issue](https://github.com/chanzuckerberg/cellxgene/issues/new/choose) if you would like us to add support for an unsupported browser.
        
        ### Finding help
        
        We'd love to hear from you!
        For questions, suggestions, or accolades, [join the `#cellxgene-users` channel on the CZI Science Slack](https://join-cellxgene-users.herokuapp.com/) and say "hi!".
        
        For any errors, [report bugs on Github](https://github.com/chanzuckerberg/cellxgene/issues).
        
        # Developing with cellxgene
        
        ### Contributing
        
        We warmly welcome contributions from the community! Please see our [contributing guide](https://chanzuckerberg.github.io/cellxgene/posts/contribute) and don't hesitate to open an issue or send a pull request to improve cellxgene. Please see the [dev_docs](https://github.com/chanzuckerberg/cellxgene/tree/main/dev_docs) for pull request suggestions, unit test details, local documentation preview, and other development specifics. 
        
        This project adheres to the Contributor Covenant [code of conduct](https://github.com/chanzuckerberg/.github/blob/master/CODE_OF_CONDUCT.md). By participating, you are expected to uphold this code. Please report unacceptable behavior to opensource@chanzuckerberg.com.
        
        ### Reuse
        
        This 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 the [MIT license](https://opensource.org/licenses/MIT).
        
        
        Before extending cellxgene, 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 our 
        [roadmap](./docs/posts/roadmap.md) and under active development. 
        
        See the [cellxgene extensions](./docs/posts/extensions.md) section of our documentation for examples of community use and cellxgene extensions. 
        
        ### Security
        
        If you believe you have found a security issue, we would appreciate notification. Please send email to <security@chanzuckerberg.com>.
        
        # Inspiration
        
        We've been heavily inspired by several other related single-cell visualization projects, including the [UCSC Cell Browser](http://cells.ucsc.edu/), [Cytoscape](http://www.cytoscape.org/), [Xena](https://xena.ucsc.edu/), [ASAP](https://asap.epfl.ch/), [GenePattern](http://genepattern-notebook.org/), 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 the [crossfilter](https://github.com/crossfilter) team for the design of our filtering implementation.
        
        We have been working closely with the [scanpy](https://github.com/theislab/scanpy) team 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 as [Seurat](https://github.com/satijalab/seurat) or [Bioconductor](https://github.com/Bioconductor)
        
Platform: UNKNOWN
Classifier: Framework :: Flask
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: MIT License
Classifier: Natural Language :: English
Classifier: Operating System :: POSIX
Classifier: Operating System :: Unix
Classifier: Operating System :: MacOS :: MacOS X
Classifier: Programming Language :: JavaScript
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3 :: Only
Classifier: Topic :: Scientific/Engineering :: Bio-Informatics
Description-Content-Type: text/markdown
Provides-Extra: prepare
