RNA-seq Analysis of Breast Cancer Subtypes

Project Overview

This repository contains the analysis code and results for a bulk RNA-seq study on breast cancer subtypes (HER2, TNBC, Non-TNBC) and healthy tissue samples.

The project aims to identify differentially expressed genes (DEGs) and explore enriched biological processes using functional annotation.

Pipeline Summary

The analysis pipeline includes the following steps:

1. Quality Control: Performed with FastQC and aggregated using MultiQC.

2. Read Alignment: Reads were aligned to the human reference genome (R64-1-1.112) using HISAT2.

3. Gene Counting: Gene-level read counts were obtained using featureCounts.

4. Differential Expression Analysis: Conducted with DESeq2.

5. Functional Enrichment: GO enrichment analysis was performed on DEGs.

6. Visualization: Results were visualized using various plots, including dot plots for enriched GO terms.

Repository Structure

 

├── RNASeq_V2/               # Analysis scripts for different pipeline steps 

├── report.pdf             # Full project report

└── README.md              # Project documentation

Usage Instructions

Prerequisites

To run the analysis, you need the following software and R packages:

• R (DESeq2, ggplot2, clusterProfiler, EnhancedVolcano)

• HISAT2

• featureCounts

• FastQC and MultiQC

Running the Analysis

Clone the Repository

git clone git@github.com:azertyang/RNAcours.git cd RNAcours

Execute Analysis

Run each script sequentially for data processing and analysis.