Description: Pathway enrichment analysis is a powerful computational approach used to identify biological pathways that are significantly overrepresented in a given set of differentially expressed genes, or any gene list derived from -omics data. This method helps to contextualize large gene lists by linking them to known biological processes, functional modules, and disease mechanisms. While highly informative, pathway enrichment analysis requires careful interpretation and an understanding of statistical methodologies, reference databases, and potential biases in gene-set analysis. In this session, we will explore key concepts and methods for pathway enrichment analysis, and we will discuss different enrichment approaches, including over-representation analysis of a defined gene list and gene set enrichment analysis (GSEA). Participants will be offered hands-on practice in which they will use RStudio to run R/BioConductor scripts for pathway enrichment analysis as well as the Cytoscape software to visualize the results of enrichment analysis on their personal computers. Basic familiarity with R will be beneficial.
Teachers: Ruth Isserlin (Bioinformatics.ca, University of Toronto) and Veronique Voisin (Bioinformatics.ca, UHN)
Level: Intermediate
Format: Lecture + Hands-on
Certificate: Attendance
Prerequisites:
- Knowing how to open R or R-Studio and install packages.
- Basic knowledge of R (recommended).
- General knowledge of differential expression of RNA-seq or scRNA-seq data.