Perform pathway enrichment analysis using reactomeFIViz

Robin Haw, Fred Loney, Edison Ong, Yongqun He, Guanming Wu

Research output: Chapter in Book/Report/Conference proceedingChapter

9 Scopus citations


Modern large-scale biological data analysis often generates a set of significant genes, frequently associated with scores. Pathway-based approaches are routinely performed to understand the functional contexts of these genes. Reactome is the most comprehensive open-access biological pathway knowledge base, widely used in the research community, providing a solid foundation for pathway-based data analysis. ReactomeFIViz is a Cytoscape app built upon Reactome pathways to help users perform pathway- and network-based data analysis and visualization. In this chapter we describe procedures on how to perform pathway enrichment analysis using ReactomeFIViz for a gene score file. We describe two types of analysis: pathway enrichment based on a set of significant genes and GSEA analysis using gene scores without cutoff. We also describe a feature to overlay gene scores onto pathway diagrams, enabling users to understand the underlying mechanisms for up- or down- regulated pathways collected from pathway analysis.

Original languageEnglish (US)
Title of host publicationMethods in Molecular Biology
PublisherHumana Press Inc.
Number of pages15
StatePublished - 2020

Publication series

NameMethods in Molecular Biology
ISSN (Print)1064-3745
ISSN (Electronic)1940-6029


  • Biological pathway
  • Cytoscape
  • GSEA
  • Gene score
  • Pathway enrichment analysis
  • Reactome
  • ReactomeFIViz

ASJC Scopus subject areas

  • Molecular Biology
  • Genetics


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