Python pipeline and Javascript scatter plot library for single-cell datasets, http://cellbrowser.rtfd.org





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UCSC Single Cell Browser

The UCSC Cell Browser is a viewer for single cell data. You can click on and hover over cells to get meta information, search for genes to color on and click clusters to show cluster-specific marker genes.

To look at a list of selected single cell datasets, see http://cells.ucsc.edu

To setup your own cell browser, from Cellranger, Seurat, Scanpy or text files (tsv/csv), or just a single cell expression matrix, read the documentation at http://cellbrowser.rtfd.io

If you want us to add a single cell dataset to the website http://cells.ucsc.edu, please contact us at cells@ucsc.edu. We are happy to add any dataset.

This is a viewer for a static, precomputed layout. If you're looking for an interative layout, where you can move the cells around and run some algorithms interactively, try Chan-Zuckerberg's own cellxgene or Spring. A website with both datasets and some analysis is Scope <http://scope.aertslab.org/>_.

Many labs host their data at cells.ucsc.edu by sending it to us, but some groups have setup their own cell browsers:

These papers have cell browsers made at UCSC:

Before judging this project by the number of issue tickets or PRs, note that at UCSC we use an internal ticket system with more features and that a lot of communication with wetlab users is by email at cells@ucsc.edu, as we do not require a Github account for feedback. But we do reply to issues here, as you can see from the Github account and also use Github for source control.

Additional availability

  • The preferred installation is via pip https://pypi.org/project/cellbrowser/, for documentation see https://cellbrowser.readthedocs.io
  • Bioconda: this tool is available to install via bioconda <https://bioconda.github.io/recipes/ucsc-cell-browser/README.html>_. Note that the conda release is usually a bit outdated relative to the pip release, so use pip if possible. If you cannot use pip, please contact us.
  • Biocontainers: there is a biocontainer automatically generated from the bioconda package available here <https://quay.io/repository/biocontainers/ucsc-cell-browser>_
  • The Seurat3Wizard, demo at http://nasqar.abudhabi.nyu.edu/SeuratV3Wizard, builds a cell browser as its last step
  • Galaxy: there is a Galaxy tool for UCSC CellBrowser, which can be installed on any Galaxy instance via its Galaxy Toolshed entry <https://toolshed.g2.bx.psu.edu/view/ebi-gxa/ucsc_cell_browser> or it can be directly used by users at the Human Cell Atlas Galaxy instance <https://humancellatlas.usegalaxy.eu/root?tool_id=toolshed.g2.bx.psu.edu/repos/ebi-gxa/ucsc_cell_browser/ucsc_cell_browser> or as part of the example workflows, such as the Human Cell Atlas / Scanpy CellBrowser workflow <https://humancellatlas.usegalaxy.eu/u/pmoreno/w/humancellatlas-scanpy-cellbrowser> or the EBI Single Cell Expression Atlas / Scanpy / CellBrowser workflow <https://humancellatlas.usegalaxy.eu/u/pmoreno/w/atlas-scanpy-cellbrowser-imported-from-uploaded-file>

This project was funded by the California Institute of Regenerative Medicine and the Chan-Zuckerberg Initiative https://www.chanzuckerberg.com/. In 2020, it is funded through a supplement to the NHGRI Genome Browser grant.

This is early research software. You are likely to find bugs. Please open a Github ticket or email us at cells@ucsc.edu, we can usually fix them quickly.


If you use the UCSC Cell Browser in your work, please cite Speir et al, Biorxiv 2020 <https://www.biorxiv.org/content/10.1101/2020.10.30.361162v1>_

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