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https://github.com/maximilianh/cellBrowser

main repo: https://github.com/ucscGenomeBrowser/cellBrowser/ - Python pipeline and Javascript scatter plot library for single-cell datasets, http://cellbrowser.rtfd.org
https://github.com/maximilianh/cellBrowser

Last synced: 23 days ago
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main repo: https://github.com/ucscGenomeBrowser/cellBrowser/ - Python pipeline and Javascript scatter plot library for single-cell datasets, http://cellbrowser.rtfd.org

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README 

        
.. image:: https://img.shields.io/badge/install%20with-bioconda-brightgreen.svg?style=flat

   :target: http://bioconda.github.io/recipes/ucsc-cell-browser/README.html



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 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/



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.



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 `_. 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 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 [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 `_