Gene set enrichement analysis

Gene set enrichment analysis (GSEA) is a bioinformatic method used to find out whether certain groups of genes - so-called gene sets - are significantly altered in a given biological question.

Instead of analyzing the function of individual genes, GSEA asks: "Are certain biological functions or signaling pathways particularly active or suppressed in my condition?" The following procerde is preferred for this method:

• Input data: An ordered list of genes, usually sorted by their expression differences between two conditions (e.g. sick vs. healthy).
• Gene sets: Predefined groups of genes involved in a biological process, pathway or function (e.g. all genes involved in cell division - or all genes involved in lupus erythematosus).
• Analysis: GSEA checks whether the genes from a particular gene set are systematically up- or down-regulated.
• Statistical evaluation: The method calculates an enrichment score (ES) and a significance evaluation (usually by permutation tests) as to whether the pattern is random or not.

GSEA has the following advantages:

Individual genes can indicate biologically irrelevant changes, but entire gene sets show more robust biological effects.

GSEA helps to recognize biological correlations, not just statistically significant individual genes.

1. Subramanian A et al. (2005) Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proc Natl Acad Sci U S A 102):15545-1550.