From Differentially Expressed Molecules to Biological Insight (Part 1): Overrepresentation Analysis with clusterProfiler in R
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From Differentially Expressed Molecules to Biological Insight (Part 1): Overrepresentation Analysis with clusterProfiler in R In-Person
Description:
Identifying differentially expressed genes or proteins is just the beginning — the real biological insight comes from understanding what those molecules are doing. In this hands-on workshop, participants will learn how to perform Overrepresentation Analysis (ORA) by using the clusterProfiler R package alongside MSigDB gene sets via msigdbr, to determine whether specific biological pathways or gene sets are statistically enriched among a list of differentially expressed molecules.
By the end of the session, participants will have a reusable, well-structured and annotated R script they can adapt to their own datasets and will learn to:
1. Explain the principles of ORA
2. Define differentially expressed genes cutoffs
3. Select and load gene sets
4. Set an appropriate background gene list
5. Run ORA with enricher()
6. Generate and interpret multiple enrichment visualizations, including: bar plots, dot plots, heatplots, upSet plots, treeplots
Prerequisites:
Basic familiarity with R and RStudio.
Having a laptop with the latest version of RStudio installed.
- Date:
- Tuesday, August 11, 2026
- Time:
- 10:00am - 12:00pm
- Time Zone:
- Eastern Time - US & Canada (change)
- Location:
- SHM L 111, Cushing/Whitney Medical Library, 333 Cedar Street
- Campus:
- Medical School
- Categories:
- Bioinformatics
