scTM: A pacakge for topic modelling in transcriptomics data
May 1, 2024 ยท View on GitHub
=========================================================== scTM: A pacakge for topic modelling in transcriptomics data
.. image:: https://img.shields.io/pypi/v/sctm.svg :target: https://pypi.org/project/scTM
.. image:: https://readthedocs.org/projects/sctm/badge/?version=latest :target: https://JinmiaoChenLab.github.io/scTM/ :alt: Documentation Status
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
.. code-block:: python
conda create --name sctm python=3.8
conda activate sctm
pip install sctm
or
.. code-block:: python
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 with a simulated data at https://jinmiaochenlab.github.io/scTM/notebooks/stamp/Simulation.
The simulated data can be found at data/simulation.h5ad.
For more advanced usage please check the examples in our detailed tutorials.
Tested with
python == 3.8
numpy == 1.24.4
numba == 0.57.1
torch == 2.0.3
Credits
This package was created with Cookiecutter_ and the audreyr/cookiecutter-pypackage_ project template.
.. _Cookiecutter: https://github.com/audreyr/cookiecutter
.. _audreyr/cookiecutter-pypackage: https://github.com/audreyr/cookiecutter-pypackage