Metadata-Version: 2.1
Name: excellxgene
Version: 2.9.6
Summary: Web application for exploration of large scale scRNA-seq datasets, upgraded to enable end-to-end interactive analysis.
Home-page: https://github.com/czbiohub/excellxgene
Author: Chan Zuckerberg Biohub
Author-email: alexander.tarashansky@czbiohub.org
License: MIT
Classifier: Framework :: Flask
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: MIT License
Classifier: Natural Language :: English
Classifier: Operating System :: POSIX
Classifier: Operating System :: Unix
Classifier: Operating System :: MacOS :: MacOS X
Classifier: Programming Language :: JavaScript
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3 :: Only
Classifier: Topic :: Scientific/Engineering :: Bio-Informatics
Description-Content-Type: text/markdown

<img src="./cellxgene-logo.png" width="300">

# 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).
