Gene set enrichment analysis: Performance evaluation and usage guidelines

Jui-Hung Hung, Tun Hsiang Yang, Zhenjun Hu, Zhiping Weng*, Charles DeLisi

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

118 Scopus citations


A central goal of biology is understanding and describing the molecular basis of plasticity: the sets of genes that are combinatorially selected by exogenous and endogenous environmental changes, and the relations among the genes. The most viable current approach to this problem consists of determining whether sets of genes are connected by some common theme, e.g. genes from the same pathway are overrepresented among those whose differential expression in response to a perturbation is most pronounced. There are many approaches to this problem, and the results they produce show a fair amount of dispersion, but they all fall within a common framework consisting of a few basic components. We critically review these components, suggest best practices for carrying out each step, and propose a voting method for meeting the challenge of assessing different methods on a large number of experimental data sets in the absence of a gold standard. Published by Oxford University Press 2011.

Original languageEnglish
Article numberbbr049
Pages (from-to)281-291
Number of pages11
JournalBriefings in Bioinformatics
Issue number3
StatePublished - 1 May 2012


  • CMC
  • Controlled mutual coverage
  • Expression analysis
  • Gene set enrichment analysis
  • GSEA
  • Pathway enrichment analysis
  • Performance evaluation
  • PWEA

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