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

被引:35247
作者
Subramanian, A
Tamayo, P
Mootha, VK
Mukherjee, S
Ebert, BL
Gillette, MA
Paulovich, A
Pomeroy, SL
Golub, TR
Lander, ES
Mesirov, JP
机构
[1] MIT, Broad Inst, Cambridge, MA 02141 USA
[2] Harvard Univ, Cambridge, MA 02141 USA
[3] Harvard Univ, Sch Med, Dept Syst Biol, Boston, MA 02446 USA
[4] Duke Univ, Inst Genome Sci & Policy, Ctr Interdisciplinary Engn Med & Appl Sci, Durham, NC 27708 USA
[5] Dana Farber Canc Inst, Dept Med Oncol, Boston, MA 02115 USA
[6] Massachusetts Gen Hosp, Div Pulm & Crit Care Med, Boston, MA 02114 USA
[7] Fred Hutchinson Canc Res Ctr, Seattle, WA 98109 USA
[8] Harvard Univ, Sch Med, Childrens Hosp, Dept Neurol, Boston, MA 02115 USA
[9] MIT, Dept Biol, Cambridge, MA 02142 USA
[10] MIT, Whitehead Inst Biomed Res, Cambridge, MA 02142 USA
关键词
microarray;
D O I
10.1073/pnas.0506580102
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
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.
引用
收藏
页码:15545 / 15550
页数:6
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