sugam2001/deseq2-python-example

This repository contains an example implementation of DESeq2 in Python.

DESeq2 Example in Python

This repository contains an example of using DESeq2 in Python for differential gene expression analysis.

Table of Contents

• Introduction
• Installation
• Usage
• Files
• References
• Contributing
• Contact
• Acknowledgements
• License

Introduction

DESeq2 is a widely used tool for differential gene expression (DGE) analysis in RNA-Seq data, and it is mainly implemented in R. However, you can use rpy2, a Python library that allows you to run R code. If you're interested in learning more about RNA-seq analysis, I highly recommend visiting RNA-seqlopedia. This comprehensive resource provides valuable insights into RNA-seq, covering everything from basic concepts to advanced techniques. It's an excellent starting point for anyone looking to deepen their understanding of RNA-seq analysis.

Installation

To run the DESeq2 example in Python, Ensure you have installed R on your system, and install the required packages. Follow these steps:

1. Install required packages:

   pip install -r requirements.txt

2. Install DESeq2:

   # Open R and run the following command to install DESeq2
   if (!requireNamespace("BiocManager", quietly = TRUE))
       install.packages("BiocManager")
   BiocManager::install("DESeq2")

Usage

To run the DESeq2 analysis, follow these steps:

1. Prepare your count data: Ensure your count data is in a CSV file format. An example file is provided in the repository.

2. Run the DESeq2 script:

   python run_deseq2.py 

3. Analyze the results: The results will be saved in your provided path or directory. You can use the provided analyze_results.py script to generate plots and interpret results.

   python analyze_results.py 

Files

• Data/filtered_gene_expression_counts.csv: Example count data for DESeq2 analysis.
• Data/deseq2_results.csv: Example of the result.
• Code/run_deseq2.py: Script to run DESeq2 analysis.
• Code/analyze_results.py: Script to analyze DESeq2 results and generate plots.
• requirements.txt: List of Python dependencies.
• README.md: This file.

References

• DESeq2 Documentation
• Bioconductor
• rpy2

Contributing

If you would like to contribute to this project, please fork the repository and submit a pull request. For major changes, please open an issue to discuss what you would like to change.

Contact

Thanks for visiting this repository! If you have any questions or feedback, feel free to contact me at [[email protected]].

Acknowledgements

Thank you for visiting this repository. Your feedback and contributions are greatly appreciated. Feel free to reach out if you have any suggestions for improvements or new features.

License

This repository is licensed under the MIT License. See the LICENSE file for details.