ArticleBMC bioinformatics2008
Testing gene set enrichment for subset of genes: Sub-GSE.
Article in BMC bioinformatics, 2008. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed, 18 citations in OpenAlex.
- Drug target inference through pathway analysis of genomics data.Advanced drug delivery reviews · 2013Review
- A microarray analysis of gnotobiotic mice indicating that microbial exposure during the neonatal period plays an essential role in immune system development.BMC genomics · 2012Article
- Sensitive detection of pathway perturbations in cancers.BMC bioinformatics · 2012Article
- A network-based gene-weighting approach for pathway analysis.Cell research · 2012Article
- The core mouse response to infection by neospora caninum defined by gene set enrichment analyses.Bioinformatics and biology insights · 2012Article
- Revealing functionally coherent subsets using a spectral clustering and an information integration approach.BMC systems biology · 2012Article
- Variable set enrichment analysis in genome-wide association studies.European journal of human genetics : EJHG · 2011Article
- COSINE: COndition-SpecIfic sub-NEtwork identification using a global optimization method.Bioinformatics (Oxford, England) · 2011Article
- Analyzing the regulation of metabolic pathways in human breast cancer.BMC medical genomics · 2010Article
- Article
- Heirarchical clustering and beyond in PCOS endometrium: brave new world.The Journal of clinical endocrinology and metabolism · 2009Article
- Gene set analyses for interpreting microarray experiments on prokaryotic organisms.BMC bioinformatics · 2008Article
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Authors and funding
2 authors at 1 institution in 1 country.
Funding
Abstract
backgroundMany methods have been developed to test the enrichment of genes related to certain phenotypes or cell states in gene sets. These approaches usually combine gene expression data with functionally related gene sets as defined in databases such as GeneOntology (GO), KEGG, or BioCarta. The results based on gene set analysis are generally more biologically interpretable, accurate and robust than the results based on individual gene analysis. However, while most available methods for gene set enrichment analysis test the enrichment of the entire gene set, it is more likely that only a subset of the genes in the gene set may be related to the phenotypes of interest.
resultsIn this paper, we develop a novel method, termed Sub-GSE, which measures the enrichment of a predefined gene set, or pathway, by testing its subsets. The application of Sub-GSE to two simulated and two real datasets shows Sub-GSE to be more sensitive than previous methods, such as GSEA, GSA, and SigPath, in detecting gene sets assiated with a phenotype of interest. This is particularly true for cases in which only a fraction of the genes in the gene set are associated with the phenotypes. Furthermore, the application of Sub-GSE to two real data sets demonstrates that it can detect more biologically meaningful gene sets than GSEA.
conclusionWe developed a new method to measure the gene set enrichment. Applications to two simulated datasets and two real datasets show that this method is sensitive to the associations between gene sets and phenotype. The program Sub-GSE can be downloaded from http://www-rcf.usc.edu/~fsun.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.