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add acknowledgements to README (#407)
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Bruce Martin
@@ -8,19 +8,19 @@ Started in the context of the Human Cell Atlas Consortium, cellxgene hopes to bo
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## Features
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* **Visualization at scale:** built with [WebGL](https://www.khronos.org/webgl/), [React](https://reactjs.org/) & [Redux](https://redux.js.org/) to handle visualization of at least 1 million cells.
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- **Visualization at scale:** built with [WebGL](https://www.khronos.org/webgl/), [React](https://reactjs.org/) & [Redux](https://redux.js.org/) to handle visualization of at least 1 million cells.
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* **Interactive exploration:** select, cross-filter, and compare subsets of your data with performant indexing and data handling.
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* **Flexible API:** the cellxgene client-server model is designed to support a range of existing analysis packages for backend computational tasks (eg scanpy), integrated with client-side visualization via a [REST API](https://restfulapi.net/).
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- **Interactive exploration:** select, cross-filter, and compare subsets of your data with performant indexing and data handling.
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- **Flexible API:** the cellxgene client-server model is designed to support a range of existing analysis packages for backend computational tasks (eg scanpy), integrated with client-side visualization via a [REST API](https://restfulapi.net/).
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## Getting Started
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**Requirements**
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- OS: OSX, Windows, Linux -- the developers are currently testing on OSX and Windows (via WSL using Ubuntu). It should work on other platforms but if you are using something different and need help, please let us know.
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- OS: OSX, Windows, Linux -- the developers are currently testing on OSX and Windows (via WSL using Ubuntu). It should work on other platforms but if you are using something different and need help, please let us know.
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- python 3.6
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- python3 tkinter
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- python3 tkinter
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- npm
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- Google Chrome
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@@ -51,6 +51,7 @@ Started in the context of the Human Cell Atlas Consortium, cellxgene hopes to bo
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**Help**
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cellxgene --help
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_For help with the scanpy engine_
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cellxgene scanpy --help
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@@ -61,15 +62,15 @@ _For help with the scanpy engine_
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To prepare your data you will need to format your data into AnnData format using scanpy and calculate PCA and nearest neighbors and save in h5ad format.
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1. [Load data into scanpy](https://scanpy.readthedocs.io/en/latest/api/index.html#reading)
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1. [Load data into scanpy](https://scanpy.readthedocs.io/en/latest/api/index.html#reading)
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- Ensure that `obs`'s index is the cell names: `print(data.obs_names)` should show your cell indices. If it shows gene names, you may need to just call `data.transpose()`.
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- Ensure that `obs`'s index is the cell names: `print(data.obs_names)` should show your cell indices. If it shows gene names, you may need to just call `data.transpose()`.
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2. Calculate PCA
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2. Calculate PCA
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sc.pp.pca(data) ## sc is scanpy.api
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3. Calculate nearest neighbors (depending on layout algorithm)
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3. Calculate nearest neighbors (depending on layout algorithm)
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```
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# For umap layout algorithm, you need to use the "umap" method for neighbors
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@@ -79,7 +80,7 @@ To prepare your data you will need to format your data into AnnData format using
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sc.pp.neighbors(data, method="gauss", metric="euclidean", use_rep="X_pca")
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```
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4. Save file
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4. Save file
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```
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# cellxgene requires file to be named data.h5ad
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@@ -87,15 +88,24 @@ To prepare your data you will need to format your data into AnnData format using
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```
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## Contributing
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We warmly welcome contributions from the community. Please submit any bug reports and feature requests through github issues. Please submit any direct contributions via a branch + pull request.
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## Inspiration and collaboration
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We’ve been inspired by several other related efforts in this space, including the [UCSC Cell Browswer](http://cells.ucsc.edu/), [Cytoscape](http://www.cytoscape.org/), [Xena](https://xena.ucsc.edu/), [ASAP](https://asap.epfl.ch/), [Gene Pattern](http://genepattern-notebook.org/), & many others; we hope to explore collaborations where useful.
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## Help/Contact
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Have questions, suggestions, or comments? You can contact us by joining [CZI Science Slack](https://cziscience.slack.com/messages/CCTA8DF1T) and posting in the #cellxgene channel. Please submit any feature requests or bugs as an issue in github. We'd love to hear from you!
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## Reuse
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This project was started with the sole goal of empowering the scientific community to explore and understand their data. As such, we whole-heartedly encourage other scientific tool builders to adopt the patterns, tools, and code from this project, and reach out to us with ideas or questions using Github Issues or Pull Requests. All code is freely available for reuse under the [MIT license](https://opensource.org/licenses/MIT).
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*We thank Alex Wolf for the demo dataset.*
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## Acknowledgements
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cellxgene is inspired by many innovative projects. We would like to specifically thank:
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- Alex Wolf for the demo dataset.
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- Mike Bostock and the [crossfilter](https://github.com/crossfilter) team for API inspiration.
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