A toolbox for single cell topic models
Project description
scTM is a package for spatial transcriptomics for single cell that uses topic modelling, solved with stochastic variational infernce. The interesting part is with the formulation of topic models, we can get interpretable embedding which are useful for downstream analysis.
Currently available modules: STAMP
Free software: MIT license
Documentation: https://JinmiaoChenLab.github.io/scTM/.
Features
STAMP: A spatially-aware dimensional reduction designed for spatial data.
Minimal Installation
pip install scTMor
conda create --name sctm python=3.8
git clone https://github.com/JinmiaoChenLab/scTM.git
conda activate sctm
cd scTM
pip install .Basic Usage
Check out our usage of STAMP in the documentation at https://jinmiaochenlab.github.io/scTM/notebooks/stamp/example1/
Credits
This package was created with Cookiecutter and the audreyr/cookiecutter-pypackage project template.
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