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 limma and 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:
- Molecular phenotyping of individual samples
- Identifying and visualising higher-order phenotypes
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:
singscorevissEmsigdbemtdataedgeRlimmaGSEABaseigraph
| Activity | Time |
|---|---|
| Introduction & setup | 10m |
| Part 1. Molecular phenotyping of individual samples | 45m |
| Part 2. Identifying and visualising higher-order phenotypes | 45m |
| Q & A | 10m |
- Learn how to perform gene-set testing in R.
- Understand the results of gene-set enrichment analysis.
- Understand the importance of visualisation in bioinformatics and computational biology.
- Perform a gene-set enrichment analysis and interpret the results.
- Apply vissE to identify higher-order phenotypes and to visualise the results of any gene-set enrichment analysis.
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
Username:rstudio and Password:password.
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 4.1.
install.packages('remotes')
# Install workshop package
remotes::install_github("DavisLaboratory/GenesetAnalysisWorkflow", build_vignettes = TRUE)
# To view vignettes
library(GenesetAnalysisWorkflow)
browseVignettes("GenesetAnalysisWorkflow")