This workshop will focus on performing gene-set enrichment analysis of transcriptomic data and visualising the results of enrichment analysis. We will perform single-sample gene-set enrichment using methods in the
singscore package to explore molecular phenotypes in individual samples. Following this, we will perform gene-set enrichment analysis using tools from the
edgeR packages. Finally, we will demonstrate a graph-based approach to visualise, summarise and interpret resutls of gene-set enrichment analysis.
The workshop will be organised into two broad sections:
Detailed material can be found here.
The course is aimed at PhD students, Master’s students, and third & fourth year undergraduate students. Some basic R knowledge is assumed - this is not an introduction to R course. If you are not familiar with the R statistical programming language it is compulsory that you work through an introductory R course before you attend this workshop.
The following key R packages will be used:
|Introduction & setup||10m|
|Part 1. Molecular phenotyping of individual samples||45m|
|Part 2. Identifying and visualising higher-order phenotypes||45m|
|Q & A||10m|
This is necessary in order to reproduce the code shown in the workshop. The workshop is designed for R
4.1 and can be installed using one of the two ways below.
If you’re familiar with Docker you could use the Docker image which has all the software pre-configured to the correct versions.
docker run -e PASSWORD=password -p 8787:8787 bhuvad/genesetanalysisworkflow:latest
Once running, navigate to http://localhost:8787/ and then login with
You should see the Rmarkdown file with all the workshop code which you can run.
Alternatively, you could install the workshop using the commands below in R
install.packages('remotes') # Install workshop package remotes::install_github("DavisLaboratory/GenesetAnalysisWorkflow", build_vignettes = TRUE) # To view vignettes library(GenesetAnalysisWorkflow) browseVignettes("GenesetAnalysisWorkflow")