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A common feature of many current functional genomics technologies, as well as many different types of bioinformatics analyses, is that they output very large lists of genes, typically in the order of hundreds or thousands. Evidently, interpreting these lists by assessing each gene individually is not practical. Therefore, Gene Set Enrichment Analysis (GSEA) has become the first step in interpreting these long lists of genes. The principle of GSEA is to search for sets of genes that are significantly over-represented in a given list of genes, compared to a background set of genes. These sets of genes consist typically, but not always, of genes that function together in a known biological pathway.
(Simillion et al., 2017) Avoiding the pitfalls of gene set enrichment analysis with SetRank. BMC Bioinformatics.