2005
DOI: 10.1073/pnas.0506580102
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Gene set enrichment analysis: A knowledge-based approach for interpreting genome-wide expression profiles

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 canc… Show more

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Cited by 42,916 publications
(40,285 citation statements)
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References 34 publications
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“…gene expression data from liver, muscle, and heart tissue using GSEA (gene set enrichment analysis) (Mootha et al ., 2003; Subramanian et al ., 2005); unfortunately, adipose gene expression information was not available from the AGEMAP study, and an insufficient number of samples were available from the Pearson et al . study for GSEA.…”
Section: Resultsmentioning
confidence: 99%
See 1 more Smart Citation
“…gene expression data from liver, muscle, and heart tissue using GSEA (gene set enrichment analysis) (Mootha et al ., 2003; Subramanian et al ., 2005); unfortunately, adipose gene expression information was not available from the AGEMAP study, and an insufficient number of samples were available from the Pearson et al . study for GSEA.…”
Section: Resultsmentioning
confidence: 99%
“…The mTOR pathway gene sets we used were obtained from the Molecular Signatures Database (MSigDB) and are listed in Table S3. The GSEA application was executed using default parameters as recommended by (Subramanian et al ., 2005). …”
Section: Methodsmentioning
confidence: 99%
“…MK was supported by the Swedish Cancer Society. The authors acknowledge the use of GSEA software and Molecular Signature Database (MSigDB)27 (http://www.broad.mit.edu/gsea/). …”
Section: Acknowledgementsmentioning
confidence: 99%
“…To determine pathways that may be preferentially targeted for DNA methylation dysregulation, candidate genes were uploaded to gene set enrichment analysis (GSEA) (Subramanian et al ., 2005) and analyzed with the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway database. The ‘GoSeq’ package (Young et al ., 2010) was utilized to normalize the genes based on number of HpaII sites per gene to eliminate bias.…”
Section: Resultsmentioning
confidence: 99%
“…To perform GSEA (Subramanian et al ., 2005), we first linked RefSeq genes (rn4) to our candidate differentially methylated loci. Differentially methylated loci overlapping candidate regulatory regions up to 10‐kb upstream of gene transcription start site and within gene bodies until transcription end site were used to link DNA methylation changes with specific genes.…”
Section: Experimental Methodsmentioning
confidence: 99%