CycleVI: Isolating cell cycle variation with an interpretable deep generative model
Project description
CycleVI
Overview
This repository contains the source code for the CycleVI method, as presented in our preprint
Dependencies
- scvi-tools
- anndata
- PyTorch
Structure
- CycleVI_model: model implementation.
- Tutorial: a python notebook with ans example on how to run the model.
- Tutorial_colab: same tutorial, but ready to run on Google Colab.
Installation
pip install cyclevi
Usage
from cyclevi import CycleVI
Instructions on how to use the model are present in the Tutorial.ipynb notebook.
Feedback
For questions and comments, feel free to contact Gustavo S. Jeuken.
License
BSD 3-Clause License
Citation
If you use this model in a publication, please cite our preprint
CycleVI: Isolating cell cycle variation with an interpretable deep generative model
Pia Mozdzanowski, Marcel Tarbier, Gustavo S. Jeuken
bioRxiv 2025.11.04.686009; doi: https://doi.org/10.1101/2025.11.04.686009
Project details
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
Filter files by name, interpreter, ABI, and platform.
If you're not sure about the file name format, learn more about wheel file names.
Copy a direct link to the current filters
File details
Details for the file cyclevi-0.1.0.tar.gz.
File metadata
- Download URL: cyclevi-0.1.0.tar.gz
- Upload date:
- Size: 3.1 MB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.2.0 CPython/3.12.3
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
97fa9bbe70abbb0d9026fb53f8c74ab6b3bf5254275adeabdc0ef1b18568c11a
|
|
| MD5 |
463afa0ed13cb1918fc90aafb1b686a1
|
|
| BLAKE2b-256 |
aa8f92234d7d93440529f3150b7df122f45ede53757750c8f3a659451f3f006c
|
File details
Details for the file cyclevi-0.1.0-py3-none-any.whl.
File metadata
- Download URL: cyclevi-0.1.0-py3-none-any.whl
- Upload date:
- Size: 19.7 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.2.0 CPython/3.12.3
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
84a8c8f3146aacfb2ba356647a2abc7611a29e8f76e8b8706804755817fefff9
|
|
| MD5 |
4769cd9184fb622836ce153b706114f4
|
|
| BLAKE2b-256 |
74a02edae79f5057ac8992cc4cfbf07ec6830019d7f0a634f886a4727abed9aa
|