Bioinformatics

Gene nomenclature

Biology

Gene

Gene expression

Function (biology)

Genome

Gene expression profiling

Set (abstract data type)

Programming language

Computer science

Nomenclature

Botany

Computational biology

Genetics

Taxonomy (biology)

Proceedings of the National Academy of Sciences

Although genomewide RNA expression analysis has become a routine tool in biomedical research, extracting biological insight from such information remains a major challenge. Here, we describe a powerful analytical method called Gene Set Enrichment Analysis (GSEA) for interpreting gene expression data. The method derives its power by focusing on gene sets, that is, groups of genes that share common biological function, chromosomal location, or regulation. We demonstrate how GSEA yields insights into several cancer-related data sets, including leukemia and lung cancer. Notably, where single-gene analysis finds little similarity between two independent studies of patient survival in lung cancer, GSEA reveals many biological pathways in common. The GSEA method is embodied in a freely available software package, together with an initial database of 1,325 biologically defined gene sets.

Gene set enrichment analysis: A knowledge-based approach for interpreting genome-wide expression profiles