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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.

Patch notes (v1.2.5)

  • When displaying continuous metadata, cells with value zero are drawn as if they are unselected to send them to the background.
  • Category and geneset menus now have a new menu item to include/exclude zeros from the histograms. This is useful when the distributions are super zero-inflated.

Patch notes (v1.2.3)

  • Gene sets are now grouped based on their descriptions under collapsible headers.
  • Gene sets are now more compact, displaying 10 genes at a time with buttons to flip through pages.
  • Differential expression now calculates the top 100 genes.
  • A new button in the menubar allows you to calculate marker genes for all labels in a selected category.
  • Embeddings are now indented according to their hierarchical organization, and nested embeddings are collapsible.
  • Categorical labels are now sortable based on the currently displayed continuous medatada.
  • All preprocessing and reembedding parameters now have a tooltip.
  • Added a button to display hotkey menu to the menubar.
  • Various bugfixes.

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:
pip install excellxgene

If your operating system is CentOS, then you may run into issues installing dependencies that require up-to-date gcc or g++ compilers. Please install with the following and try reinstalling excellxgene with pip:

conda install -c conda-forge gcc cxx-compiler
  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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