cellDancer is a modularized, parallelized, and scalable tool based on a deep learning framework for the RNA velocity analysis of scRNA-seq. Our website of tutorials is available at cellDancer Website.
Cite
Shengyu Li#, Pengzhi Zhang#, Weiqing Chen, Lingqun Ye, Kristopher W. Brannan, Nhat-Tu Le, Jun-ichi Abe, John P. Cooke, Guangyu Wang. A relay velocity model infers cell-dependent RNA velocity. Nature Biotechnology (2023) https://doi.org/10.1038/s41587-023-01728-5
- Enable accurate inference of dynamic cell state transitions in heterogeneous cell populations.
- Estimate cell-specific transcription (α), splicing (β) and degradation (γ) rates for each gene and reveal RNA turnover strategies.
- Improves downstream analysis such as vector field predictions.
- [ ] Update an anndata-compatible version.
cellDancer is updated to v1.1.7
- Added progress bar for adata_to_df_with_embed() and adata_to_raw().
- Added try except to catch genes with low quality in velocity().
cellDancer requires Python version >= 3.7.6 to run.
To run cellDancer locally, we recommend to create a conda environment: conda create -n cellDancer python==3.7.6. Then activate the new environment with conda activate cellDancer. cellDancer package could be installed from pypi with pip install celldancer.
Python 3.7 is not compatible with M1 Mac, conda create -n cellDancer python==3.9.16 is the version that compatible with M1 Mac that has been well tested to run cellDancer.
To install the latest version from GitHub, run:
pip install git+https://github.com/GuangyuWangLab2021/cellDancer.git
To install cellDancer from source code, run:
pip install 'your_path/Source Code/cellDancer'.
For M1 Mac users if you encountered a problem while installing bezier. Please refer to the following link: https://bezier.readthedocs.io/en/2021.2.12/#installing
If any other dependency could not be installed with pip install celldancer, try pip install --no-deps celldancer. Then install the dependencies by pip install -r requirements.txt or manually install each package in requirements.txt.
To be compatible with Dynamo (optional), after first pip install celldancer and then pip install dynamo-release, installing Dynamo will update numpy to 1.24.0, and we can downgrade numpy back to 1.20.0 with pip install numpy==1.20.0 to let them be compatible.
Q: How should I prepare the input for my own data?
A: The Data Preparation page introduces the details of how to prepare and pre-process your own data.
Check more frequently asked questions at FAQ in our website. If you have any other question related to your specific contition, welcome to post it in our github issue page or email to sli5@houstonmethodist.org
Welcome bug reports and suggestions to our GitHub issue page!