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.
%0 Journal Article
%1 Subramanian2005Genesetenrichment
%A Subramanian, Aravind
%A Tamayo, Pablo
%A Mootha, Vamsi K
%A Mukherjee, Sayan
%A Ebert, Benjamin L
%A Gillette, Michael A
%A Paulovich, Amanda
%A Pomeroy, Scott L
%A Golub, Todd R
%A Lander, Eric S
%A Mesirov, Jill P
%D 2005
%J Proc Natl Acad Sci USA
%K Acute, Analysis, Array Cell Expression Female Gene Genes: Genome, Humans, Leukemia-Lymphoma, Leukemia: Line: Lung Lymphoblastic Male, Myeloid: Neoplasms, Oligonucleotide Precursor Profiling, Sequence Tumor, p53,
%N 43
%P 15545--15550
%T Gene set enrichment analysis: a knowledge-based approach for interpreting
genome-wide expression profiles
%V 102
%X 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.
@article{Subramanian2005Genesetenrichment,
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.},
added-at = {2014-05-13T15:48:44.000+0200},
affiliation = {Broad Institute of Massachusetts Institute of Technology and Harvard,
320 Charles Street, Cambridge, MA 02141, USA.},
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},
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bdsk-url-1 = {http://dx.doi.org/10.1073/pnas.0506580102},
biburl = {https://www.bibsonomy.org/bibtex/2c5f1d84d4cab43f186711875c5f8ec99/gwotto},
date-added = {2009-05-26 19:30:16 +0200},
date-modified = {2009-05-27 18:54:28 +0200},
file = {Subramanian2005Genesetenrichment.pdf:Subramanian2005Genesetenrichment.pdf:PDF},
interhash = {6c83a69786c883de3dccc7979d6d2484},
intrahash = {c5f1d84d4cab43f186711875c5f8ec99},
journal = {Proc Natl Acad Sci USA},
keywords = {Acute, Analysis, Array Cell Expression Female Gene Genes: Genome, Humans, Leukemia-Lymphoma, Leukemia: Line: Lung Lymphoblastic Male, Myeloid: Neoplasms, Oligonucleotide Precursor Profiling, Sequence Tumor, p53,},
language = {eng},
month = Oct,
number = 43,
owner = {gotto},
pages = {15545--15550},
pii = {0506580102},
pmid = {16199517},
rating = {0},
read = {Yes},
timestamp = {2014-05-13T15:48:44.000+0200},
title = {Gene set enrichment analysis: a knowledge-based approach for interpreting
genome-wide expression profiles},
uri = {papers://18DAF7D4-A926-4C8D-AD18-6500BDA5002B/Paper/p4310},
volume = 102,
year = 2005
}