Model-based Trajectory Inference for Single-Cell RNA Sequencing Using Deep Learning with a Mixture Prior
This package provides computational tools to perform trajectory inference on scRNA-seq data with Variational Autoencoders. For more details, please refer to https://github.com/jaydu1/VITAE.
Project Members
Jin-Hong Du, Tianyu Chen, Ming Gao, and Jingshu Wang
License
This project is licensed under the terms of the MIT license.
1 maintainer
Metadata
1 maintainer
Release files for pyvitae 2.1.0
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Source distribution (sdist)
| File | Size | Uploaded | Provenance | |
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| pyvitae-2.1.0.tar.gz | 37.2 kB | Without provenance | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| pyvitae-2.1.0-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 76.3 kB
Release files / pyvitae-2.1.0.tar.gz
| Download URL | pyvitae-2.1.0.tar.gz |
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| Size | 37.2 kB |
| Tags | Source |
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Release files / pyvitae-2.1.0-py3-none-any.whl
| Download URL | pyvitae-2.1.0-py3-none-any.whl |
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| Size | 39.1 kB |
| Tags | Python 3 |
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