Scripts for Breast Cancer Bulk RNA-Seq Differential Expression, Survival, and Enrichment Analyses Using GEO Data

This repository contains R and Python scripts used to analyze bulk RNA-Seq datasets from the Gene Expression Omnibus (GEO) related to breast, prostate, endometrial, lung, and colorectal cancer. The workflow includes differential expression analysis, survival analysis, functional enrichment, and visualization.Included workflows:<b>R scripts:</b><b>Data processing and normalization</b> of GEO-derived bulk RNA-Seq datasets.<b>Differential expression analysis</b> (DEG) using limma.<b>Survival analysis</b> using Cox proportional hazards models<b>Functional enrichment analysis</b> (GO, Reactome) of overlapping DEGs to identify significant pathways<b>Python scripts:</b><b>Forest plot generation</b> using Matplotlib and Seaborn to visualize the survival analysis's hazard ratios and confidence intervals.<b>Data Source:</b>Publicly available bulk RNA-Seq datasets from the <b>Gene Expression Omnibus (GEO)</b> database.