Benchmarking a foundational cell model for post-perturbation RNAseq prediction

This is the official Github repository of the Benchmarking a foundational cell model for post-perturbation RNAseq prediction. This is a fork of the scGPT repository.

Repository content

• notebooks/
  • bulk_models.ipynb: train RF and EN, compares performance to scGPT and "Train Mean"
  • data_analysis.ipynb: runs data analysis and generates Figure 2
  • scgpt_mean.ipynb: runs the mean model and compares it with scGPT
  • Tutorial_PerturbationAdamson.ipynb: trains scGPT on the Adamson et al. dataset
  • Tutorial_PerturbationNorman.ipynb: trains scGPT on the Norman et al. dataset
  • Tutorial_PerturbationReplogle.ipynb: trains scGPT on the Replogle et al. dataset

Reproducibility

To reproduce the results of the paper, please follow the following steps:

1. Run git lfs pull to download the required data from Git Large File System. If lfs is not installed, pleaser refer to this guide
2. Run make setup to create the conda environment, install the ipython kernel and unzip the replogle dataset
3. Select the scgpt_yml conda environment as the Python kernel for the notebooks
4. Run data_analysis.ipynb
5. Run the Tutorial notebooks to get the results of scGPT
6. Run scgpt_mean.ipynb
7. Run bulk_models.ipynb