Gene set/pathway enrichment analysis

Jui-Hung Hung*

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingChapter

24 Scopus citations

Abstract

Thanks for the dramatic reduction of the costs of high-throughput techniques in modern biotechnology, searching for differentially expressed genes is already a common procedure in identifying biomarkers or signatures of phenotypic states such as diseases or compound treatments. However, in most of the cases, especially in complex diseases, even given a list of biomarkers, the underlying biological mechanisms are still obscure to us. In other words, rather than knowing what genes are involved, we are more interested in discovering the common, collective roles of all these genes. Based on the assumption that genes involved in the same biological processes, functions, or localizations present correlated behaviors in terms of expression levels, signal intensities, allele occurrences, and so on, we can therefore apply statistical tests to find perturbed pathways. Gene Set/Pathway enrichment analysis is one of such techniques; a step-by-step instruction is described in this chapter.

Original languageEnglish
Title of host publicationData Mining for Systems Biology
Subtitle of host publicationMethods and Protocols
EditorsHiroshi Mamitsuka, Minoru Kanehisa, Charles DeLisi
Pages201-213
Number of pages13
DOIs
StatePublished - 8 Jan 2013

Publication series

NameMethods in Molecular Biology
Volume939
ISSN (Print)1064-3745

Keywords

  • Biomarker
  • Gene set enrichment analysis
  • GO term analysis
  • Overrepresentation analysis
  • Pathway enrichment analysis

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  • Cite this

    Hung, J-H. (2013). Gene set/pathway enrichment analysis. In H. Mamitsuka, M. Kanehisa, & C. DeLisi (Eds.), Data Mining for Systems Biology: Methods and Protocols (pp. 201-213). (Methods in Molecular Biology; Vol. 939). https://doi.org/10.1007/978-1-62703-107-3-13