Single-cell Variational Inference
Project description
scVI
Single-cell Variational Inference
Free software: MIT license
Documentation: https://scvi.readthedocs.io.
Quick Start
Install Python 3.6 or later. We typically use the Miniconda Python distribution.
Install PyTorch. If you have an Nvidia GPU, be sure to install a version of PyTorch that supports it – scVI runs much faster with a discrete GPU.
Install scVI through conda (conda install scvi -c bioconda) or through pip (pip install scvi). Alternatively, you may download or clone this repository and run python setup.py install.
Follow along with our Jupyter notebooks to quickly get familiar with scVI!
References
Romain Lopez, Jeffrey Regier, Michael Cole, Michael I. Jordan, Nir Yosef. “Deep generative modeling for single-cell transcriptomics.” Nature Methods, 2018. [pdf]
History
0.1.0 (2018-06-12) 0.1.1 (2018-06-14) 0.1.2 (2018-06-16) ——————
First release on PyPI.
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