DOI: 10.1073/pnas.0506580102. Gene set enrichment analysis: A knowledge-based approach for interpreting genome-wide expression profiles

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

10.1073/pnas.0506580102

Crossref journal-article

Proceedings of the National Academy of Sciences

Proceedings of the National Academy of Sciences (341)

Abstract

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.

Bibliography

Subramanian, A., Tamayo, P., Mootha, V. K., Mukherjee, S., Ebert, B. L., Gillette, M. A., Paulovich, A., Pomeroy, S. L., Golub, T. R., Lander, E. S., & Mesirov, J. P. (2005). Gene set enrichment analysis: A knowledge-based approach for interpreting genome-wide expression profiles. Proceedings of the National Academy of Sciences, 102(43), 15545â15550.

Authors 11

Aravind Subramanian (first)
Pablo Tamayo (additional)
Vamsi K. Mootha (additional)
Sayan Mukherjee (additional)
Benjamin L. Ebert (additional)
Michael A. Gillette (additional)
Amanda Paulovich (additional)
Scott L. Pomeroy (additional)
Todd R. Golub (additional)
Eric S. Lander (additional)
Jill P. Mesirov (additional)

References 34 Referenced 43,615

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Hollander M. & Wolfe D. A. ( 1999) Nonparametric Statistical Methods (Wiley New York).
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10.1093/bioinformatics/btf877
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10.1038/nature03441
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Barbouti, A., Hoglund, M., Johansson, B., Lassen, C., Nilsson, P. G., Hagemeijer, A., Mitelman, F. & Fioretos, T. ( 2003) Cancer Res. 63, 1202–1206. 12649177 / Cancer Res. (2003)
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10.1093/bioinformatics/btg363

Dates

Type	When
Created	19 years, 11 months ago (Sept. 30, 2005, 8:33 p.m.)
Deposited	3 years, 4 months ago (April 12, 2022, 2:03 p.m.)
Indexed	9 hours, 4 minutes ago (Sept. 4, 2025, 9:56 a.m.)
Issued	19 years, 11 months ago (Sept. 30, 2005)
Published	19 years, 11 months ago (Sept. 30, 2005)
Published Online	19 years, 11 months ago (Sept. 30, 2005)
Published Print	19 years, 10 months ago (Oct. 25, 2005)

Funders 0

None

BibTeX

@article{Subramanian_2005, title={Gene set enrichment analysis: A knowledge-based approach for interpreting genome-wide expression profiles}, volume={102}, ISSN={1091-6490}, url={http://dx.doi.org/10.1073/pnas.0506580102}, DOI={10.1073/pnas.0506580102}, number={43}, journal={Proceedings of the National Academy of Sciences}, publisher={Proceedings of the National Academy of Sciences}, author={Subramanian, Aravind and Tamayo, Pablo and Mootha, Vamsi K. and Mukherjee, Sayan and Ebert, Benjamin L. and Gillette, Michael A. and Paulovich, Amanda and Pomeroy, Scott L. and Golub, Todd R. and Lander, Eric S. and Mesirov, Jill P.}, year={2005}, month=sep, pages={15545–15550} }

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