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.
- Estimate cell-specific RNA velocity for each gene.
- Derive cell fates in embedding space.
- Estimate pseudotime for each cell in embedding space.
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, create an conda or Anaconda environment as conda create -n cellDancer python==3.7.6, and activate the new environment with conda activate cellDancer. cellDancer could be installed with pip install celldancer.
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.