DDLS 2024 Course Project

This repository contains the final project for the Data-Driven Life Science (DDLS) Course 2024.

Overview

The project aims to apply deep learning approaches, using the Geneformer model, to perform cell classification and in-silico gene perturbations to study Type 1 and Type 2 diabetes.

Notebook

The notebook DDLS_2024_final_project_OF_new.ipynb contains the following:

• Tokenizing of single-cell RNA-seq data.
• Fine-tuning of the Geneformer model for cell state classification.
• Evaluation metrics (accuracy, confusion matrix, clustered heatmap).
• In-silico gene perturbation analysis influence on cell states.

Requirements

To run this notebook, you need:

• Google Colab or a local Python environment.
• Packages such as transformers, scanpy, and torch.

How to Use

1. Clone this repository:

   git clone https://github.com/yourusername/ddls_course_2024_project.git

2. Open the notebook and run it in a Colab environment or Jupyter.

License

This project is licensed under the MIT License - see the LICENSE file for details.

Acknowledgements

This project was guided by the DDLS 2024 course, and special thanks to ChatGPT for assisting with the implementation.