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Web application for exploration of large scale scRNA-seq datasets, upgraded to enable end-to-end interactive analysis.

Project description

Exploratory CellxGene (ExCellxGene)

This fork implements some of the key features that have been highly requested by the data science team at CZBiohub.

Features include:

  • Hotkeys (SHIFT+? to see a tooltip describing all available hotkeys)
  • End-to-end interactive analysis and reembedding, with new embeddings hierarchically organized.
  • LIDAR graph interaction mode (the airplane) - Show an interactive tooltip describing the cells underneath your cursor. Very helpful for the color impaired or for large datasets with hundreds of labels.
  • Sankey plots
  • Leiden clustering
  • Label fusion and deletion
  • Interactive selection of data layer for expression visualization
  • Many other quality-of-life improvements.

Installation

  1. Install miniconda if conda not available already:
wget https://repo.anaconda.com/miniconda/Miniconda3-latest-MacOSX-x86_64.sh -O ~/miniconda.sh
bash ~/miniconda.sh -b -p $HOME/miniconda
  1. Create and activate a new environment:
conda create -n cxg python=3.7
conda activate cxg
  1. Install excellxgene with pip (the latest version should be 1.1.4)
pip install excellxgene
  1. Download the git repository to get the example datasets (assumes git is available, if not install it with conda install -c anaconda git)
git clone https://github.com/czbiohub/cellxgene
cd cellxgene

Datasets are stored in example-dataset

  1. Launch cellxgene with:
cellxgene launch example-dataset

This should launch a cellxgene session with all the datasets in example-datasets/ loaded in.

If you're running excellxgene remotely, please launch with:

cellxgene launch example-datasets --host 0.0.0.0

Ping me on the Biohub slack (@Alec) if you have any questions!

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