Metadata-Version: 2.5
Name: pseudotimede-py
Version: 0.0.2
Summary: Python implementation of the PseudotimeDE algorithm for differential expression analysis on estimated pseudotimes. Uses scDesigner for simulation model estimation.
Author-email: Kris Sankaran <sankaran.kris@gmail.com>
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 3
Requires-Python: >=3.10
Requires-Dist: anndata
Requires-Dist: formulaic
Requires-Dist: numpy
Requires-Dist: pandas
Requires-Dist: scdesigner
Requires-Dist: scipy
Requires-Dist: torch
Provides-Extra: test
Requires-Dist: pytest; extra == 'test'
Description-Content-Type: text/markdown

# pseudotimede-py


[PseudotimeDE](https://doi.org/10.1186/s13059-021-02341-y) is a statistical
method for testing whether genes are differentially expression across a
pseudotime trajectory. This repository gives a python implementation following
the existing [R package](https://github.com/SONGDONGYUAN1994/PseudotimeDE).
It uses the [scDesigner](https://github.com/krisrs1128/scDesigner) package to
accelerate model fitting.

![](assets/lps_pvalues.png)

You can see an example application in this
[notebook](https://github.com/krisrs1128/pseudotimede_py/blob/main/examples/lps.ipynb).
To install the package, you can use,

```
pip install pseudotimede-py
```

If you have questions, feel free to open an [issue](https://github.com/krisrs1128/pseudotimede_py/issues) or [contact us](https://measurement-and-microbes.org/_includes/contact).