dependabot[bot]
db559467a2
Bumps [ini](https://github.com/isaacs/ini) from 1.3.5 to 1.3.7. <details> <summary>Commits</summary> <ul> <li><a href="https://github.com/npm/ini/commit/c74c8af35f32b801a7e82a8309eab792a95932f6"><code>c74c8af</code></a> 1.3.7</li> <li><a href="https://github.com/npm/ini/commit/024b8b55ac1c980c6225607b007714c54eb501ba"><code>024b8b5</code></a> update deps, add linting</li> <li><a href="https://github.com/npm/ini/commit/032fbaf5f0b98fce70c8cc380e0d05177a9c9073"><code>032fbaf</code></a> Use Object.create(null) to avoid default object property hazards</li> <li><a href="https://github.com/npm/ini/commit/2da90391ef70db41d10f013e3a87f9a8c5d01a72"><code>2da9039</code></a> 1.3.6</li> <li><a href="https://github.com/npm/ini/commit/cfea636f534b5ca7550d2c28b7d1a95d936d56c6"><code>cfea636</code></a> better git push script, before publish instead of after</li> <li><a href="https://github.com/npm/ini/commit/56d2805e07ccd94e2ba0984ac9240ff02d44b6f1"><code>56d2805</code></a> do not allow invalid hazardous string as section name</li> <li>See full diff in <a href="https://github.com/isaacs/ini/compare/v1.3.5...v1.3.7">compare view</a></li> </ul> </details> <details> <summary>Maintainer changes</summary> <p>This version was pushed to npm by <a href="https://www.npmjs.com/~isaacs">isaacs</a>, a new releaser for ini since your current version.</p> </details> <br /> [](https://docs.github.com/en/github/managing-security-vulnerabilities/about-dependabot-security-updates#about-compatibility-scores) Dependabot will resolve any conflicts with this PR as long as you don't alter it yourself. You can also trigger a rebase manually by commenting `@dependabot rebase`. [//]: # (dependabot-automerge-start) [//]: # (dependabot-automerge-end) --- <details> <summary>Dependabot commands and options</summary> <br /> You can trigger Dependabot actions by commenting on this PR: - `@dependabot rebase` will rebase this PR - `@dependabot recreate` will recreate this PR, overwriting any edits that have been made to it - `@dependabot merge` will merge this PR after your CI passes on it - `@dependabot squash and merge` will squash and merge this PR after your CI passes on it - `@dependabot cancel merge` will cancel a previously requested merge and block automerging - `@dependabot reopen` will reopen this PR if it is closed - `@dependabot close` will close this PR and stop Dependabot recreating it. You can achieve the same result by closing it manually - `@dependabot ignore this major version` will close this PR and stop Dependabot creating any more for this major version (unless you reopen the PR or upgrade to it yourself) - `@dependabot ignore this minor version` will close this PR and stop Dependabot creating any more for this minor version (unless you reopen the PR or upgrade to it yourself) - `@dependabot ignore this dependency` will close this PR and stop Dependabot creating any more for this dependency (unless you reopen the PR or upgrade to it yourself) - `@dependabot use these labels` will set the current labels as the default for future PRs for this repo and language - `@dependabot use these reviewers` will set the current reviewers as the default for future PRs for this repo and language - `@dependabot use these assignees` will set the current assignees as the default for future PRs for this repo and language - `@dependabot use this milestone` will set the current milestone as the default for future PRs for this repo and language You can disable automated security fix PRs for this repo from the [Security Alerts page](https://github.com/chanzuckerberg/cellxgene/network/alerts). </details>
an interactive explorer for single-cell transcriptomics data
cellxgene (pronounced "cell-by-gene") is an interactive data explorer for single-cell transcriptomics datasets, such as those coming from the Human 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 helps you gain insight into your single-cell data.
Getting started
The comprehensive guide to cellxgene
The cellxgene documentation is your one-stop-shop for information about cellxgene! You may be particularly interested in:
- Seeing what cellxgene can do
- Learning more about cellxgene installation and usage
- Preparing your own data for use in cellxgene
- Checking out our roadmap for future development
- Contributing to cellxgene
Quick start
To install cellxgene you need Python 3.6+. We recommend installing cellxgene into a conda or virtual environment.
Install the package.
pip install cellxgene
Launch cellxgene with an example anndata file
cellxgene launch https://cellxgene-example-data.czi.technology/pbmc3k.h5ad
To explore more datasets already formatted for cellxgene, check out the Demo data or see Preparing your data 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 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 and say "hi!".
For any errors, report bugs on Github.
Developing with cellxgene
Contributing
We warmly welcome contributions from the community! Please see our contributing guide and don't hesitate to open an issue or send a pull request to improve cellxgene. Please see the 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. 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, and reach out to us with ideas or questions. All code is freely available for reuse under the MIT license.
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, 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 the crossfilter team for the design of our filtering implementation.
We have been working closely with the 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 or Bioconductor