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https://github.com/maayanlab/clustergrammer
An interactive heatmap visualization built using D3.js
https://github.com/maayanlab/clustergrammer
biology clustering d3 heatmap jupyter-notebook jupyter-widget python visualization
Last synced: 28 days ago
JSON representation
An interactive heatmap visualization built using D3.js
- Host: GitHub
- URL: https://github.com/maayanlab/clustergrammer
- Owner: MaayanLab
- License: mit
- Created: 2015-07-30T15:07:25.000Z (over 9 years ago)
- Default Branch: master
- Last Pushed: 2023-01-16T11:42:48.000Z (almost 2 years ago)
- Last Synced: 2024-10-10T19:31:33.174Z (29 days ago)
- Topics: biology, clustering, d3, heatmap, jupyter-notebook, jupyter-widget, python, visualization
- Language: JavaScript
- Homepage: http://maayanlab.github.io/clustergrammer/scrolling_tour
- Size: 74.2 MB
- Stars: 230
- Watchers: 24
- Forks: 85
- Open Issues: 31
-
Metadata Files:
- Readme: README.md
- License: LICENSE
- Code of conduct: CODE_OF_CONDUCT.md
Awesome Lists containing this project
- awesome-single-cell - Clustergrammer - [Python, JavaScript] - Interative web-based heatmap for visualizing and analyzing high dimensional biological data, including single-cell RNA-seq. Clustergrammer can be used within a Jupyter notebook as an interative widget that can be shared using GitHub and NBviewer, see [example notebook](http://nbviewer.jupyter.org/github/MaayanLab/CCLE_Clustergrammer/blob/master/notebooks/Clustergrammer_CCLE_Notebook.ipynb). (Software packages / RNA-seq)
README
[](https://www.npmjs.com/package/clustergrammer)
[](https://github.com/MaayanLab/clustergrammer/blob/master/LICENSES/LICENSE)
Clustergrammer is a web-based tool for visualizing high-dimensional data (e.g. a matrix) as an interactive and shareable hierarchically clustered heatmap. Clustergrammer's front end ([Clustergrammer-JS](http://clustergrammer.readthedocs.io/clustergrammer_js.html#clustergrammer-js)) is built using [D3.js](https://d3js.org/) and its back-end ([Clustergrammer-PY](http://clustergrammer.readthedocs.io/clustergrammer_py.html#clustergrammer-py)) is built using Python. Clustergrammer produces highly interactive visualizations that enable intuitive exploration of high-dimensional data and has several biology-specific features (e.g. enrichment analysis, see [Biology-Specific Features](http://clustergrammer.readthedocs.io/biology_specific_features.html#biology-specific-features)) to facilitate the exploration of gene-level biological data. Click the screenshot below to view an interactive tutorial:
[](http://maayanlab.github.io/clustergrammer/scrolling_tour)
Clustergrammer's interacive features include:
- [Zooming and Panning](http://clustergrammer.readthedocs.io/interacting_with_viz.html#zooming-and-panning)
- [Row and Column Reordering](http://clustergrammer.readthedocs.io/interacting_with_viz.html#row-col-reordering)
- [Interactive Dendrogram](http://clustergrammer.readthedocs.io/interacting_with_viz.html#interactive-dendrogram)
- [Interactive Dimensionality Reduction](http://clustergrammer.readthedocs.io/interacting_with_viz.html#interactive-dim-reduction)
- [Interactive Categories](http://clustergrammer.readthedocs.io/interacting_with_viz.html#interactive-categories)
- [Cropping](http://clustergrammer.readthedocs.io/interacting_with_viz.html#crop)
- [Row Searching](http://clustergrammer.readthedocs.io/interacting_with_viz.html#search)
- [Biology-Specific Features](http://clustergrammer.readthedocs.io/biology_specific_features.html)
Clustergrammer can be used in three main ways (this repo contains the source code for [Clustergrammer-JS](http://clustergrammer.readthedocs.io/clustergrammer_js.html#clustergrammer-js)):
- [Clustergrammer Web App](http://clustergrammer.readthedocs.io/clustergrammer_web.html#clustergrammer-web) ([http://amp.pharm.mssm.edu/clustergrammer/](http://amp.pharm.mssm.edu/clustergrammer/))
- [Clustergrammer Jupyter Widget](http://clustergrammer.readthedocs.io/clustergrammer_widget.html#clustergrammer-widget)
- [Clustergrammer-JS](http://clustergrammer.readthedocs.io/clustergrammer_js.html#clustergrammer-js) and [Clustergrammer-PY](http://clustergrammer.readthedocs.io/clustergrammer_py.html#clustergrammer-py) libraries
For information about building a webpage or app using Clustergrammer see: [Web-Development with Clustergrammer](http://clustergrammer.readthedocs.io/building_webpage.html)
# What's New
## Clustergrammer2
[](https://mybinder.org/v2/gh/ismms-himc/clustergrammer2-notebooks/master?filepath=notebooks%2F1.0_Running_Clustergrammer2.ipynb) [](https://nbviewer.jupyter.org/github/ismms-himc/clustergrammer2-notebooks/blob/master/notebooks/1.0_Running_Clustergrammer2.ipynb)
[](http://www.youtube.com/watch?v=UgO5LLvcfB0)
Clustergrammer is being re-built using the WebGL library [regl](http://regl.party/). The new in-development front-end is [Clustergrammer-GL](https://github.com/ismms-himc/clustergrammer-gl) and the new in-development Jupyter widget is [Clustergrammer2](https://github.com/ismms-himc/clustergrammer2). The above notebook shows how Clustergrammer2 can be used to load a small dataset and visualize a large random DataFrame. By running the notebook on MyBinder using [Jupyter Lab](https://mybinder.org/v2/gh/ismms-himc/clustergrammer2_examples/master?urlpath=lab) it can also be used to visualize a user uploaded dataset. Please see the video tutorial above for more information.
For additional examples and tutorials please see:
* [Case Studies and Tutorials](https://clustergrammer.readthedocs.io/case_studies.html)
* [Clustergrammer2-Notebooks](https://github.com/ismms-himc/clustergrammer2-notebooks) GitHub repository
## JupyterCon 2018 Presentation
[](http://www.youtube.com/watch?v=82epZkmfkrE)
Clustergrammer was recently presented at JupyterCon 2018 (see [slides](http://bit.ly/clustergrammer-jupytercon)).
# Using Clustergrammer
Pleae see Clustergramer's [documentation](http://clustergrammer.readthedocs.io/) for detailed information or select a specific topic below:
- [Getting Started](http://clustergrammer.readthedocs.io/getting_started.html)
- [Interacting with the Visualization](http://clustergrammer.readthedocs.io/interacting_with_viz.html)
- [Web-Development with Clustergrammer](http://clustergrammer.readthedocs.io/building_webpage.html) ([example pages](http://clustergrammer.readthedocs.io/clustergrammer_js.html#example-pages))
- [Clustergrammer Web App](http://clustergrammer.readthedocs.io/clustergrammer_web.html#clustergrammer-web) and [Clustergrammer Jupyter Widget](http://clustergrammer.readthedocs.io/clustergrammer_widget.html#clustergrammer-widget)
- [Matrix Formats and Input/Output](http://clustergrammer.readthedocs.io/matrix_format_io.html)
- Core libraries: [Clustergrammer-JS](http://clustergrammer.readthedocs.io/clustergrammer_js.html) and [Clustergrammer-PY](http://clustergrammer.readthedocs.io/clustergrammer_py.html)
- [App Integration Examples](http://clustergrammer.readthedocs.io/app_integration.html)
- [Case Studies and Examples](https://clustergrammer.readthedocs.io/case_studies.html)
- [Biology-Specific Features](https://clustergrammer.readthedocs.io/biology_specific_features.html)
- [Developing Clustergrammer](https://clustergrammer.readthedocs.io/developing_with_clustergrammer.html)
## Citing Clustergrammer
Please consider supporting Clustergrammer by citing our publication:
Fernandez, N. F. et al. Clustergrammer, a web-based heatmap visualization and analysis tool for high-dimensional biological data. Sci. Data 4:170151 doi: [10.1038/sdata.2017.151](https://www.nature.com/articles/sdata2017151 ) (2017).
## Licensing
Clustergrammer was developed by the [Ma'ayan lab](http://labs.icahn.mssm.edu/maayanlab/) at the [Icahn School of Medicine at Mount Sinai](http://icahn.mssm.edu/) for the [BD2K-LINCS DCIC](http://lincs-dcic.org/#/) and the [KMC-IDG](http://commonfund.nih.gov/idg/overview). Clustergrammer's license and third-party licenses are in the LICENSES directory and more information can be found at [Clustergrammer License](https://clustergrammer.readthedocs.io/license.html).
Please [contact us](http://clustergrammer.readthedocs.io/#funding-and-contact) for support, licensing questions, comments, and suggestions.