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GASTON-Mix - A unified model of spatial gradients and domains with spatial mixture-of-experts

Overview

GASTON-Mix is a spatial mixture-of-experts (MoE) model for learning domain-specific topographic maps of a tissue slice from spatially resolved transcriptomics (SRT) data.

Installation

We will make GASTON-Mix pip-installable soon. In the meanwhile, you can directly install the conda environment from the environment.yml file:

First install conda environment from environment.yml file:

conda env create -f environment.yml

Then install GASTON using pip (will add to pypi soon!)

conda activate gaston-mix pip install -e .

Installation should take <10 minutes.

Software dependencies

  • torch
  • matplotlib
  • pandas
  • scikit-learn
  • numpy
  • jupyterlab
  • seaborn
  • tqdm
  • scipy
  • scanpy

See the environment.yml file for full list.

## Getting started Try out the Jupyter notebook tutorial: tutorial.ipynb.