title: Extensions to gene set enrichment.
abstract: BACKGROUND
  Gene Set Enrichment Analysis (GSEA) has been developed recently to capture changes in the expression of pre-defined sets of genes. We propose number of extensions to GSEA, including the use of different statistics to describe the association between genes and phenotypes of interest. We make use of dimension reduction procedures, such as principle component analysis, to identify gene sets with correlated expression. We also address issues that arise when gene sets overlap.
  
  
  RESULTS
  Our proposals extend the range of applicability of GSEA and allow for adjustments based on other covariates. We have provided a well-defined procedure to address interpretation issues that can raise when gene sets have substantial overlap. We have shown how standard dimension reduction methods, such as PCA, can be used to help further interpret GSEA.
  
  
  BACKGROUND
  Supplementary data are available at Bioinformatics online.
authors.affiliation: Computational Biology, 1100 Fairview Avenue. N. M2-B876, PO Box 19024, Seattle, WA 98109-1024, USA. zjiang@fhcrc.org
authors.forename: Zhen
authors.initials: Z
authors.lastname: Jiang
authors.forename: Robert
authors.initials: R
authors.lastname: Gentleman
mesh_terms: D000465:Algorithms; D002468:Cell Physiological Phenomena; D015870:Gene Expression / Q000502:physiology*; D020869:Gene Expression Profiling / Q000379:methods*; D005786:Gene Expression Regulation / Q000502:physiology*; D020411:Oligonucleotide Array Sequence Analysis / Q000379:methods*; D020543:Proteome / Q000378:metabolism*
chemical_list: D020543:Proteome