Pathway analysis of proteomics or transcriptomics data: Part 1 Gene Set Enrichment Analysis (GSEA)
Pathway analysis of proteomics or transcriptomics data: Part 1 Gene Set Enrichment Analysis (GSEA) In-Person
Attendance in person
After running a differential analysis, no individual gene meets the threshold for statistical significance, or you have a long list of differentially expressed genes without any unifying biological theme. Then this workshop is for you.
Gene Set Enrichment Analysis (GSEA) (UC San Diego/Broad Institute) determines whether a set of genes shows statistically significant differences between two biological conditions (e.g., phenotypes). From this session/workshop you will learn how to run GSEA on your own datasets using the GSEA desktop application. During the session, we will use a tutorial dataset that will be made available to all the registrants. Attendees to this session will learn:
- how to prepare your data and files for running GSEA.
- about Molecular Signature Database (MSigDB).
- how to run GSEA analysis and the Leadin-edge analysis and results interpretation.
- how to send and visualize the results using the Enrichment Map app.
- Understand the relevance of the results statistical vs biological.