popari 0.0.33

Popari: a probabilistic graphical model for integrated spatial transcriptomics analysis

SpiceMix

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.

git clone https://github.com/alam-shahul/SpiceMixPlus.git

• Install pytest in your environment.

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:

python -m pytest -s tests/test_popari_shared.py

Building Documentation

Assuming you have CMake:

1. Navigate to docs/.

cd docs/

2. Install Sphinx requirements.

pip install -r requirements.txt

3. Clean and build.

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}
}