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, select cells to get annotation histograms, make expression violin plots and heatmaps, search for genes to color on and click clusters to show cluster-specific marker genes. It supports the usual gene expression plots, ATAC, spatial gene/ATAC, multi-modal combinations of these and trajectory lines. It comes with one-line data exporters for all common analysis formats: Seurat, Scanpy, Cellranger, Monocle and you can always use tsv/csv files to import your data. The exporters are part of Seurat 3/4 and Scanpy.

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 use the UCSC Cell Browser in your research, please cite our Bioinformatics paper. If you are also using data from a specific dataset we host, please also cite the original authors of that dataset (visible under 'Info & Download' while viewing that dataset).

If you want us to add a single cell dataset to the website http://cells.ucsc.edu, please contact us at [email protected]. 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.

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

• Alexander Misharin Lab, Northwester University, https://www.nupulmonary.org/resources/
• Accelerating Medicine Partnership Consortium, https://immunogenomics.io/cellbrowser/, used in Zhang et al. 2018 and Der et al 2018
• Ovarian Cancer Cell Laboratory, Nuffield Department of Women's & Reproductive Health, University of Oxford, https://ovariancancercell.github.io/
• Zemans Lab, Ann Arbor, https://rnabioco.github.io/lung-scrna/
• Unpublished work, unknown lab?, http://covid19ocularsurface.org/
• Chinese University of Hong Kong, Testis cis-element atlas, http://testisatlas.s3-website-us-west-2.amazonaws.com/CB.html
• Sansom Lab, Oxford, https://sansomlab.github.io (they use an older version of the Cell Browser source code, reached out to update with our bugfix but did not get reply), for Croft et al, Nature 2019
• https://www.genomique.eu/cellbrowser/HCA/ Zaragosi group at IPMC CNRS Nice, for the manuscript https://dev.biologists.org/content/early/2019/09/25/dev.177428.abstract
• Same group seems to host a COVID-19 dataset: https://www.genomique.eu/cellbrowser/COVID/
• Bin Ren lab, CAAtlas http://catlas.org/mousebrain/#!/home
• Conrad lab at Charite Berlin: http://singlecell.charite.de/
• STAB: a spatio-temporal cell atlas of the human brain from Song et al NAR 2021.
• UCLA: http://mergeomics.research.idre.ucla.edu/PVDSingleCell/
• Lako Lab at Newcastle University, UK: http://retinalstemcellresearch.co.uk/CorneaCellAtlas/ from Collins et al. 2021. The Ocular Surface.
• RNA Bioscience Initiative: https://www.pneuroonccellatlas.org/ and https://github.com/rnabioco/lung-scrna
• Paul Gontarz, WUSTL, http://regmedsrv1.wustl.edu/Public_SPACE/pgontarz/Public_html/cellbrower/Exp1/
• Dylan Farnsworth, U Oregon, https://pages.uoregon.edu/drf/browser/lens_230620/

These papers have cell browsers made at UCSC:

• organoidatlas: https://www.sciencedirect.com/science/article/pii/S221112472030053X
• dros-brain: https://elifesciences.org/articles/50354
• kidney-atlas: https://science.sciencemag.org/content/365/6460/1461.abstract
• allen-celltypes/mouse-cortex: https://www.biorxiv.org/content/10.1101/2020.03.30.015214v1.full
• organoidreportcard: https://www.nature.com/articles/s41586-020-1962-0

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 [email protected], 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.

Install and use

• 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. 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
• 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 or it can be directly used by users at the Human Cell Atlas Galaxy instance or as part of the example workflows, such as the Human Cell Atlas / Scanpy CellBrowser workflow or the EBI Single Cell Expression Atlas / Scanpy / CellBrowser workflow

This project was funded by the California Institute of Regenerative Medicine and the Chan-Zuckerberg Initiative https://www.chanzuckerberg.com/. In 2020, it was funded through a supplement to the NHGRI Genome Browser grant. Since 2023, it is funded by a grant from NIMH BRAIN.

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

Citation

If you use the UCSC Cell Browser in your work, please cite Speir et al, Biorxiv 2020