trvaep 
Introduction
A pytorch implementation of trVAE (transfer Variational Autoencoder). trVAE is a deep generative model which learns mapping between multiple different styles (conditions). trVAE can be used for style transfer on images, predicting single-cell perturbations responses and batch removal.
Getting Started
Installation
Installation with pip
To install the latest version from PyPI, simply use the following bash script:
pip install trvaep
or install the development version via pip:
pip install git+https://github.com/theislab/trvaep.git
or you can first install flit and clone this repository:
pip install flit
git clone https://github.com/theislab/trvaep
cd trvaep
flit install
Examples
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For simple perturbation prediction and batch-removal check this example with interferon (IFN)-β stimulation from Kang et al..
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For multi condition perturbation prediction and batch-removal check this example with multiple infections from Haber et al..
Reproducing paper results:
In order to reproduce paper results visit here.
1 maintainer
Metadata
1 maintainer
Release files for trvaep 0.1.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| trvaep-0.1.0.tar.gz | 1.0 MB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| trvaep-0.1.0-py2.py3-none-any.whl | Python 3, Python 2 | none | any | Details |
Total release size: 1.1 MB
Release files / trvaep-0.1.0.tar.gz
| Download URL | trvaep-0.1.0.tar.gz |
|---|---|
| Size | 1.0 MB |
| Tags | Source |
|
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Release files / trvaep-0.1.0-py2.py3-none-any.whl
| Download URL | trvaep-0.1.0-py2.py3-none-any.whl |
|---|---|
| Size | 57.4 kB |
| Tags | Python 2 Python 3 |
|
SHA-256 checksum How to use checksums |
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No |
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python-requests/2.21.0
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