Gene Expression Heatmap and Boxplot Analysis

This project was completed as part of the R for Data Science course during the MSc Bioinformatics programme at the University of Edinburgh (2024).

Description

The analysis explores gene expression patterns across treatment groups using:

• Heatmaps (genes clustered, samples clustered)
• Boxplots (expression grouped by treatment)
• Expression data and annotations

Inputs

Place all required files inside the /data directory:

File name	Description
data_all.csv	Gene expression matrix
gene_annotation.csv	Metadata for genes (names, types)
sample_annotation.csv	Sample-level metadata (treatment groups)
genelist.txt	List of gene IDs to include in analysis

Output

Knit the RMarkdown file to generate the report:

• analysis.pdf (or HTML/Word, based on output format)

How to Run

1. Open the .Rmd file in RStudio
2. Ensure all /data files are present
3. Change knit output to the ouput version you prefer.
4. Click Knit or use:

rmarkdown::render("analysis.Rmd", output_format = "pdf_document")

📌 Notes

Data is log₂ transformed to stabilize variance

Annotations link expression to gene types (XA/XB/XC) and treatments (1–4)

Boxplots reveal inter-group expression differences

License

This code is intended for educational use only.