Project 4: TCGA RNA-seq Data Analysis

Goal: Automate the analysis of large-scale cancer genomics data to validate biomarkers. This project analyzes Lung Adenocarcinoma (LUAD) data from The Cancer Genome Atlas (TCGA) to quantify the differential expression of the gene NKX2-1 in Primary Tumors versus Solid Tissue Normal samples.

Key Features

• Metadata Parsing: Automatically links blind data files to clinical information (Tumor vs Normal) using the GDC sample sheet.
• Automated Extraction: Uses Bash/Awk to mine specific gene targets from hundreds of RNA-seq files without manual intervention.
• Statistical Visualization: Generates publication-quality boxplots in R, applying Log2 transformation for proper expression scaling.

File Structure

File	Language	Description
box_plot.sh	Bash	The engine. Unzips data, parses gdc_sample_sheet.tsv, extracts TPM values for NKX2-1, and saves a CSV.
expression_plot.R	R	The visualizer. Reads the CSV, performs $Log_2(TPM+1)$ transformation, and plots the comparison.
gdc_sample_sheet.tsv	Data	Metadata linking File IDs to Sample Types.
tcga_data.tar.gz	Data	Compressed archive containing raw gene expression files.

Prerequisites

• Bash / Unix Environment
• R (Libraries: ggplot2)
• Standard tools: tar, awk, grep

Usage

1. Extract and Process Data

Run the Bash script to unzip the archive and mine the data.

bash box_plot.sh

Output

nkx2_1_expression_data.csv

2. Visualize Result

Rscript expression_plot.R

Output file

nkx2_1_boxplot.png