excellxgene 2.9.6

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

Exploratory CellxGene (ExCellxGene)

V2.9.6

The latest stable version is V2.9.6. The current version of exCellxgene relies on anndata==0.7.8, so might crash with anndata objects generated with anndata==0.8.0 or above. Until we fix this bug, we recommend users to follow the installation instruction below. The key part is installing exCellxgene, then upgrading the anndata version to 0.8.0 in the "cxg" conda environment.

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

2. Create and activate a new environment:

conda create -n cxg python=3.8
conda activate cxg

3. Install excellxgene with pip:

pip install excellxgene
pip install anndata==0.8.0

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

4. 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/excellxgene
cd excellxgene

Datasets are stored in example-dataset

5. Launch excellxgene with:

excellxgene launch example-dataset

This should launch an excellxgene session with all the datasets in example-datasets/ loaded in.

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

excellxgene launch example-datasets --host 0.0.0.0

Preprint on how to do manual cell-type annotation using interactive tools:

https://www.biorxiv.org/content/10.1101/2023.07.11.548639v1

Tutorial slides highligting some use cases:

https://cellxgene.cziscience.com/docs/05__Annotate%20and%20Analyze%20Your%20Data/5_8__Multimodal%20Annotations

More tutorial slides for multi-omics datasets (RNA, ATAC, CITE-seq, spatial transcriptomics) are coming soon (Q1/Q2 2024).