📊 Overview This repository presents a comprehensive transcriptomic analysis of breast cancer, focusing on the identification of differentially expressed genes (DEGs) between tumor and normal tissues. The study integrates statistical modeling, visualization, and network biology to uncover potential biomarkers and therapeutic targets.
🧪 Objectives Identify key genes dysregulated in breast cancer
Visualize expression patterns using volcano plots and heatmaps.
Construct gene interaction networks to highlight the functional relationships between genes.
Detect hub genes