Metadata-Version: 2.1
Name: popari
Version: 0.0.39
Summary: Popari: a probabilistic graphical model for integrated spatial transcriptomics analysis
Project-URL: Homepage, https://github.com/alam-shahul/popari
Project-URL: Bug Tracker, https://github.com/alam-shahul/popari/issues
Author-email: Shahul Alam <alam.shahul@gmail.com.com>
License: MIT License
        
        Copyright (c) 2020 Ma Lab at CMU
        
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License-File: LICENSE
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 3
Requires-Python: >=3.8
Requires-Dist: anndata>=0.8.0
Requires-Dist: louvain>=0.8.0
Requires-Dist: matplotlib>=3.7.0
Requires-Dist: numpy>=1.20.1
Requires-Dist: pandas>=1.5.2
Requires-Dist: scanpy>=1.9.2
Requires-Dist: scikit-learn>=0.24.1
Requires-Dist: scipy>=1.7.1
Requires-Dist: seaborn>=0.11.1
Requires-Dist: squidpy>=1.2.3
Requires-Dist: torch>=1.13.0
Requires-Dist: tqdm>=4.60.0
Requires-Dist: umap-learn>=0.5.1
Provides-Extra: mlflow
Requires-Dist: mlflow; extra == 'mlflow'
Provides-Extra: simulation
Requires-Dist: ipycanvas; extra == 'simulation'
Requires-Dist: jupyterlab; extra == 'simulation'
Description-Content-Type: text/markdown

# SpiceMix

![overview](./SpiceMix_overview.png)

SpiceMix is an unsupervised tool for analyzing data of the spatial transcriptome. SpiceMix models the observed expression of genes within a cell as a mixture of latent factors. These factors are assumed to have some spatial affinity between neighboring cells. The factors and affinities are not known a priori, but are learned by SpiceMix directly from the data, by an alternating optimization method that seeks to maximize their posterior probability given the observed gene expression. In this way, SpiceMix learns a more expressive representation of the identity of cells from their spatial transcriptome data than other available methods. 

SpiceMix can be applied to any type of spatial transcriptomics data, including MERFISH, seqFISH, HDST, and Slide-seq.

## Install

```
pip install popari
```

## Publishing

```
pip install hatch
pip install keyrings.alt

hatch build
hatch publish
```
Username: `__token__`
Password: `{API token for PyPI}`

## Tests

To run the provided tests and ensure that SpiceMix can run on your platform, follow the instructions below:

- Download this repo.
```console
git clone https://github.com/alam-shahul/SpiceMixPlus.git
```
- Install `pytest` in your environment.
```console
pip install pytest
```
- Navigate to the root directory of this repo.
- Run the following command. With GPU resources, this test should execute without errors in ~2.5 minutes:
```console
python -m pytest -s tests/test_popari_shared.py
```
## Building Documentation

Assuming you have CMake:

1. Navigate to `docs/`.
```console
cd docs/
```
2. Install Sphinx requirements.
```console
pip install -r requirements.txt
```
3. Clean and build.
```console
make clean
make html
```
4. Push to GitHub, and documentation will automatically build.


## Cite

Cite our paper:

```
@article{chidester2020spicemix,
  title={SPICEMIX: Integrative single-cell spatial modeling for inferring cell identity},
  author={Chidester, Benjamin and Zhou, Tianming and Ma, Jian},
  journal={bioRxiv},
  year={2020},
  publisher={Cold Spring Harbor Laboratory}
}
```

![paper](./paper.png)
