TY  - JOUR
TI  - Gene set enrichment analysis: A knowledge-based approach for interpreting genome-wide expression profiles
AU  - Aravind Subramanian
AU  - Pablo Tamayo
AU  - Vamsi K. Mootha
AU  - Sayan Mukherjee
AU  - Benjamin L. Ebert
AU  - Michael A. Gillette
AU  - Amanda G. Paulovich
AU  - Scott L. Pomeroy
AU  - Todd R. Golub
AU  - Eric S. Lander
AU  - Jill P. Mesirov
PY  - 2005
JO  - Proceedings of the National Academy of Sciences
DO  - 10.1073/pnas.0506580102
UR  - https://doi.org/10.1073/pnas.0506580102
AB  - 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.
ER  -