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.