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:R scripts:Data processing and normalization of GEO-derived bulk RNA-Seq datasets.Differential expression analysis (DEG) using limma.Survival analysis using Cox proportional hazards modelsFunctional enrichment analysis (GO, Reactome) of overlapping DEGs to identify significant pathwaysPython scripts:Forest plot generation using Matplotlib and Seaborn to visualize the survival analysis's hazard ratios and confidence intervals.Data Source:Publicly available bulk RNA-Seq datasets from the Gene Expression Omnibus (GEO) database.