Contributing to episode 08-gene-set-analysis

[jokergoo]

I would like to contribute to this topic. In the beginning of this month I gave a four-days workshop on gene set enrichment analysis (https://www.physalia-courses.org/courses-workshops/gse-in-r/). Also I am working on an online-book on gene set enrichment analysis (https://jokergoo.github.io/GSEA_book/index.html). I will take some pieces from my teaching materials to fit into a 1~2 hour lecture.

I think I will follow the workflow of:

gene set databases -> over-representation analysis (theory) -> use clusterProfiler to do ORA -> clusterProfiler with MsigDB -> GSEA (theory) -> cluster clusterProfiler to do GSEA -> visualization of results

[csoneson]

@jokergoo Thank you! If you would be willing to put together a proposal for the 'Questions' and 'Key points' for this episode ahead of the teaching committee meeting on March 13, that would be great.

I'm tagging @rcastelo here as well as he has written most of the initial text in this episode.

[jokergoo]

Following are some thoughts:

Questions

• What are the important gene set resources?
• How to perform over-representation analysis on gene sets
• How to perform GSEA analysis on gene sets
• How to summaries/visualize enrichment results

Key points

• Learn how to get gene sets from different resources (GO, KEGG, MSigDB) in the Bioconductor ecosystem.
• Learn how over-representation analysis is applied.
• Learn how GSAE is applied.
• Learn different visualization methods on the gene set enrichment results

[rcastelo]

Thanks @jokergoo these are all fundamental points to learn in this episode. I'd like to suggest that at the very beginning we should also introduce the term "pathway" and how a "gene set" is an approximation to that concept. I'd add a first question such as:

"What is a pathway and how to represent it using a gene set?"