2007
DOI: 10.1093/bioinformatics/btm369
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GSEA-P: a desktop application for Gene Set Enrichment Analysis

Abstract: Gene Set Enrichment Analysis (GSEA) is a computational method that assesses whether an a priori defined set of genes shows statistically significant, concordant differences between two biological states. We report the availability of a new version of the Java based software (GSEA-P 2.0) that represents a major improvement on the previous release through the addition of a leading edge analysis component, seamless integration with the Molecular Signature Database (MSigDB) and an embedded browser that allows user… Show more

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Cited by 1,207 publications
(1,092 citation statements)
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References 6 publications
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“…Despite the only moderate correlation between secreted protein abundance and mRNA expression, we reasoned that Gene Set Enrichment Analysis (GSEA) [42,43] would potentially be robust enough to indicate whether BMSS gene sets are globally upregulated in bone metastasis microarray data, as GSEA is sensitive for detecting overall regulatory patterns while allowing moderate amounts of noise or even discordance in the analysis. For the first GSEA, we investigated whether the MDA231 BMSSs (both quantitative and non-quantitative) were enriched in microarray data from the Kang et al study [23] comparing in vivo-derived highly and lowly bone metastatic sublines of MDA231 cells.…”
Section: Validation Of Bmsss In Experimental and Clinical Bone Metastmentioning
confidence: 99%
“…Despite the only moderate correlation between secreted protein abundance and mRNA expression, we reasoned that Gene Set Enrichment Analysis (GSEA) [42,43] would potentially be robust enough to indicate whether BMSS gene sets are globally upregulated in bone metastasis microarray data, as GSEA is sensitive for detecting overall regulatory patterns while allowing moderate amounts of noise or even discordance in the analysis. For the first GSEA, we investigated whether the MDA231 BMSSs (both quantitative and non-quantitative) were enriched in microarray data from the Kang et al study [23] comparing in vivo-derived highly and lowly bone metastatic sublines of MDA231 cells.…”
Section: Validation Of Bmsss In Experimental and Clinical Bone Metastmentioning
confidence: 99%
“…For functional analysis and interpretation of expression data we used Gene Set Enrichment Analysis (GSEA) tool (27). This is a recently developed tool to interpret genome-wide expression profiles.…”
Section: Tissue Collection and Rna Preparationmentioning
confidence: 99%
“…The sets of genes that are related to the phenotype should show a nonrandom distribution. Based on the distribution of the genes from the lists, an enrichment score is calculated, for estimation of significance level, phenotype-based permutation test procedure is used (27). Again, nominal P values were adjusted for multiple hypotheses testing by calculating false discovery rate (FDR).…”
Section: Tissue Collection and Rna Preparationmentioning
confidence: 99%
“…increasing the numbers of study participants, collaborative studies and leveraging high-density genomic data using techniques such as imputation 135 and pathway snP analysis [136][137][138][139] will help to accelerate data acquisition to find precise candidate regions or vur-specific genes. Genomic copy-number variation (Cnv) has been shown to be an important pathogenic mechanism in many other disorders in recent years, 140 but no Cnv study in vur has been reported to date.…”
Section: N a T U R E R E V I E W S U N C O R R E C T E D P R O O Fmentioning
confidence: 99%