One of the core aims of differential expression analysis is to understand which pathways and areas of biology any differentially expressed genes represent. One method to determine this is Over Representation Analysis (ORA). In ORA the significantly different genes are compared to a database (e.g. GO terms, KEGG) of pre-defined lists of genes (gene-sets) - each of which represents a specific pathway or area of biology (e.g. Cell Cycle, TNF signalling). A hyper-geometric test is then used to determine whether each gene-set is enriched or not for the significantly differential genes. The most enriched gene-sets have the lowest p-values.
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As well as understanding what biology is different between to sample groups, it can sometimes be useful to understand what biology is not different. More specifically using HGSEA it is possible to identify gene sets that are underenriched. I.e. gene-sets that are less differential than they should be given the number of significantly differential genes. This can give an indication as to the types of biology that the cell / tissue is actively maintaining. Here we provide bar charts showing the most underenriched gene-sets for: all significantly differential genes, significantly upregulated genes and significantly downregulated genes.
