stage-2-hackbio

Gene Expression Analysis with Heatmaps and Pathway Enrichment

This repository contains R code for analyzing gene expression data, including generating heatmaps and identifying upregulated and downregulated genes.

Requirements

• R (version 4.0 or later)
• Required R packages: gplots, ggplot2, RColorBrewer

Installation

Install the necessary R packages using the following commands:

install.packages(c("gplots", "RColorBrewer", "ggplot2"))

Usage

1. Load the Data

   • The script loads gene expression data from a provided URL. Ensure you have an active internet connection or download the data manually if needed.

2. Generate Heatmaps

   • The script generates various heatmaps to visualize gene expression patterns with different color palettes and clustering options.

3. Analyze Gene Expression

   • The script compares gene expression between two groups of samples. It calculates fold changes, log2 fold changes, and p-values for each gene to determine differential expression.

4. Identify Differentially Expressed Genes

   • Upregulated and downregulated genes are identified based on fold change and p-values. These genes are saved to CSV files for further analysis.

5. Visualize Pathway Enrichment

   • The script creates lollipop plots to visualize the top pathways associated with upregulated and downregulated genes using pre-processed enrichment data.

Files

• glioblastoma.csv: Gene expression data used for the analysis.
• upregulated_genes.csv: CSV file containing identified upregulated genes.
• downregulated_genes.csv: CSV file containing identified downregulated genes.
• up.csv: Enrichment data for upregulated pathways.
• down.csv: Enrichment data for downregulated pathways.

Instructions

1. place the script in your working directory.
2. Run the R script.