Gene Expression Analysis Scripts

This repository contains a collection of R scripts for processing and analyzing gene expression data from RNA-Seq experiments. Each script performs different tasks, ranging from differential expression analysis to more advanced downstream analyses like PCA and GO enrichment. These scripts are products of workshops conducted for the course on Genomic Statistics.

Scripts Overview

1. SingleCell_simulation

Description: This folder contains four scripts that simulate single-cell RNA sequencing data using the Splatter package and differential expression analysis.

Scripts:

• 1. Simulation_SingleCell.R
• 2. Pre-processing_differencial_exp.R
• 3. expression_analysis_methods.R
• 4. Metrics_singlecell_simulation

2. Workshops_Genomic_Statistics

Description: This script processes microarray data, including loading data, initial plotting, descriptive statistics, summarization from probes to genes, normalization, and correlation analysis.

Scripts:

• DEGs_annotation_workflow
• DESeq2_workshop_script
• microarray_workshop_script

How to Use

1. Set Up the Environment:

   • Ensure you have R and RStudio installed.
   • Install the necessary packages mentioned in each script using install.packages() or BiocManager::install().

2. Run the Scripts:

   • Open each script in RStudio.
   • Modify the setwd() function to set the working directory to where your data files are located.
   • Run the scripts line by line or as a whole to perform the analysis.

3. Data Files:

   • Ensure you have the necessary data files downloaded and placed in the appropriate directories as mentioned in the scripts.

Notes

• These scripts are designed to be modular, so you can run each analysis independently.
• Make sure to read through the comments in each script for detailed explanations of each step.

License

This project is licensed under the GPLv2 License. See the LICENSE file for details.