Gene set enrichments (GSEs) remain an important tools to link statistical results of high throughput data sets with biological reality. While the principle is simple, there is a substantial number of variations and special applications, such as combining GSEs with correlation analysis, multivariate modelling or applying to non-standard data sets (such as OLINK, Nanostring, ATAC-Seq or ChIP-Seq as well as metabolic profiling). There is a substantial number of algorithms and packages for GSEs. These are not redundant, but rather suitable for different applications.
In this tutorial, January Weiner will show simple yet effective strategies for gene set enrichment analysis in several different scenarios, including metabolomic profiling, multivariate analyses, single cell RNA-Seq, small gene universes, the strengths and weaknesses of different GSE packages and many tips and tricks. To fully take advantage of the workshop, a very basic command of the R programming language is recommended.
Last modified: Sep 18, 2022