Webinar: Enrichment Analysis
For biologists who are eager to perform functional annotation of a set of differentially expressed genes.
Application deadline: 14 February 2025
Date: 14 March 2025
Description
Experiments designed to quantify gene expression often yield hundreds of genes that show statistically significant differences between groups of interest. Once differentially expressed genes are identified, enrichment analysis (EA) methods can be used to explore the biological functions associated with these genes. EA methods allow us to identify groups of genes (e.g. particular pathways) that are over-represented, thereby offering insights into biological mechanisms. One of the EA methods frequently used for high-throughput gene expression data analysis is Gene Set Enrichment Analysis (GSEA). This course will cover GSEA and alternative enrichment methods. Because the implementation of GSEA is directly linked to databases that annotate the function of genes in a cell, the course will also give an overview of functional annotation databases such as Gene Ontology. All course material can be found on the GitHub course web page.
Registration fees are 100 CHF for academics and 500 CHF for for-profit companies.
Requirements
You should meet the learning outcomes of First Steps with R in Life Sciences or Introduction to Statistics with R. ELIXIR Estonia offers this course too in February: https://elixir.ut.ee/news/2025/01/13/Intro_statistics_R_18-02/
In case of doubt, evaluate your R skills with this quiz before registering.
This course will be streamed. You are thus required to have an internet connection and your own computer with the latest R and RStudio versions installed.
Learning outcomes
- Distinguish available enrichment analysis methods.
- Apply GSEA and over-representation analysis using R.
- Determine whether the genes of a GO term have a statistically significant difference in expression or not.
- Learn where to find other gene sets in databases (e.g. KEGG, oncogenic gene sets) and use them in R.