Description
RNA-Seq Functional Enrichment Practical
A hands-on exercise for moving from differentially expressed genes to pathways, biological processes, and meaningful interpretation
A differential expression analysis can identify genes that change between experimental groups, but a gene list alone does not explain the biological processes represented by those changes.
This practical helps you move from statistical results to biological interpretation using a structured and reproducible functional enrichment workflow.
You will begin with a realistic differential expression results table, prepare gene identifiers, define an appropriate gene list and background universe, run Gene Ontology and pathway enrichment analyses, create clear visualizations, and interpret the biological meaning of the enriched results.
The practical is designed for learners, researchers, students, and early-career analysts who want to understand not only how to run enrichment analysis, but also how to assess whether the results are statistically sound, biologically meaningful, and suitable for reporting.
What you will practise
You will work through a complete functional enrichment workflow that includes:
- importing RNA-Seq differential expression results
- checking gene identifiers and required result columns
- selecting genes using adjusted p-value and effect-size thresholds
- mapping gene symbols to Entrez identifiers
- removing missing and duplicated identifiers
- defining an appropriate background gene universe
- running Gene Ontology enrichment analysis
- examining biological process terms
- running pathway enrichment analysis
- interpreting gene ratios, adjusted p-values, and enrichment strength
- connecting enriched terms to differentially expressed genes
- creating publication-ready enrichment figures
- exporting tables and figures for reporting
Figures and outputs
During the practical, you will generate useful biological interpretation outputs such as:
- Gene Ontology enrichment result tables
- pathway enrichment result tables
- an enrichment dot plot
- a category-to-gene network plot
- a gene concept network colored by log2 fold change
- tables of mapped and unmapped gene identifiers
- organized publication-ready figures
- a structured biological interpretation statement
These outputs can support research reports, manuscripts, presentations, teaching materials, portfolio evidence, and further biological investigation.
Statistical interpretation
The practical explains key concepts that are often difficult to interpret in enrichment analysis, including:
- over-representation analysis
- the role of the background gene universe
- gene ratios and enrichment counts
- p-values and adjusted p-values
- multiple-testing correction
- redundant biological terms
- the relationship between statistical enrichment and biological relevance
- the limitations of enrichment results
You will learn why enrichment results should not be interpreted as proof of pathway activation and how to connect statistical evidence with experimental context.
Tools used
The workflow is completed in R using widely used packages, including:
- clusterProfiler
- enrichplot
- org.Hs.eg.db
- AnnotationDbi
- DOSE
- ggplot2
- dplyr
- readr
The practical begins with a differential expression results table. Raw FASTQ processing, read alignment, count generation, and differential expression modelling are covered outside this practical.
Who this practical is for
This practical is suitable for:
- undergraduate and postgraduate students
- researchers interpreting RNA-Seq findings
- bioinformatics learners
- laboratory scientists working with gene-expression results
- data analysts entering omics research
- mentors and instructors teaching biological interpretation
Basic familiarity with R and differential expression results is helpful, but the workflow is written step by step and includes reusable code, explanations, and interpretation guidance.
What you will complete
By the end of the practical, you will have:
- a reproducible functional enrichment workflow
- organized Gene Ontology and pathway results
- publication-ready enrichment figures
- a clearer understanding of enrichment statistics
- a structured biological interpretation of RNA-Seq findings
- portfolio-ready evidence of practical bioinformatics skills
This is a browser-first CDI Practical that you can follow at your own pace and return to whenever you need a practical reference for functional enrichment analysis.
