Computational Dissection of Plant Regeneration: An Integrative Framework for Identifying Regenerative Cells in Arabidopsis thaliana scRNA-seq Data

The project focuses on applying advanced computational methods to analyze single-cell RNA sequencing (scRNA-seq) data of Arabidopsis thaliana to identify regenerative cells.

Project Goal: To develop and implement an integrative computational framework for identifying regenerative cells in Arabidopsis thaliana scRNA-seq data.

⚙️ Dependencies

This project utilizes the following key software dependencies:

• scVAE: A command-line tool for modeling single-cell transcript counts using variational autoencoders. Used as an external library for the VMF Distribution implementations.
• ScanPy: A scalable Python toolkit for analyzing single-cell gene expression data.

For a complete list of dependencies, please refer to the requirements.txt file.

🛠️ Installation

To set up the project, follow these steps:

1. Clone the repository: Make sure to clone recursively to include submodules.

   git clone --recurse-submodules https://github.com/cemalahmet/arabidopsis-regeneration.git
   cd arabidopsis-regeneration

2. Install dependencies: Use pip to install the required Python packages from the requirements.txt file.

   pip install -r requirements.txt

🚀 Usage

The analysis is currently primarily conducted through Jupyter Notebooks located in the src directory. Please refer to the notebooks for detailed steps and code execution.

jupyter notebook

🎓 Contact

For questions or issues, please contact:

Ahmet Cemal Alıcıoğlu

• Master's Student, Bioinformatics Group
• Department of Computer Science, University of Freiburg
• Email: alicioga@informatik.uni-freiburg.de

Sven Hauns

• PHD Student, Bioinformatics Group
• Department of Computer Science, University of Freiburg
• Email: haunss@informatik.uni-freiburg.de