Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles.
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.
Subramanian
Aravind
A
Broad Institute of Massachusetts Institute of Technology and Harvard, 320 Charles Street, Cambridge, MA 02141, USA.
Tamayo
Pablo
P
Mootha
Vamsi K
VK
Mukherjee
Sayan
S
Ebert
Benjamin L
BL
Gillette
Michael A
MA
Paulovich
Amanda
A
Pomeroy
Scott L
SL
Golub
Todd R
TR
Lander
Eric S
ES
Mesirov
Jill P
JP
D045744:Cell Line, Tumor; D005260:Female; D020869:Gene Expression Profiling / Q000379:methods*; D016158:Genes, p53 / Q000502:physiology; D016678:Genome; D006801:Humans; D015470:Leukemia, Myeloid, Acute / Q000235:genetics; D008175:Lung Neoplasms / Q000235:genetics / Q000401:mortality; D008297:Male; D020411:Oligonucleotide Array Sequence Analysis; D054198:Precursor Cell Lymphoblastic Leukemia-Lymphoma / Q000235:genetics