Differential Gene Expression Analysis Using edgeR

📘 Project Overview

This project performs differential gene expression (DGE) analysis using the edgeR R package.
The workflow identifies genes that are significantly differentially expressed between experimental conditions and visualizes expression patterns using heatmaps.

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📊 Analysis Tasks

• Import and preprocess raw gene expression count data
• Filter lowly expressed genes
• Normalize counts using edgeR normalization methods
• Perform differential gene expression analysis
• Save the significant DGE results (logFC, p-values, FDR) to output files
• Generate heatmaps for significant differentially expressed genes

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💡 Notes

• Raw data may not be publicly available due to client ownership or confidentiality.
• Example output plots and result files are included where possible.
• The workflow can be adapted to different experimental designs and contrasts.

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📬 Contact

Author: Nasim Rahmatpour
Email: nasimrahmatpour1@gmail.com
GitHub: https://github.com/nasimbio