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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Here we provide ridegplots showing ten most enriched gene-sets when using: all significantly differential genes, significantly upregulated genes, and significantly downregulated genes. The ten-most enriched gene-sets and the strength of enrichment gives a useful snapshot as to the pathways or general areas of biology that are most affected by the differential expression, and whether they are being up or downregulated. It can be interesting to note whether different gene-sets are being up or downregulated.
