Perform Pathway Enrichment Analysis Using ReactomeFIViz

  • Robin Haw
  • Fred Loney
  • Edison Ong
  • Yongqun He
  • Guanming Wu
Part of the Methods in Molecular Biology book series (MIMB, volume 2074)


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.

Key words

Biological pathway Pathway enrichment analysis GSEA Reactome ReactomeFIViz Cytoscape Gene score 


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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2020

Authors and Affiliations

  • Robin Haw
    • 1
  • Fred Loney
    • 2
  • Edison Ong
    • 3
  • Yongqun He
    • 3
  • Guanming Wu
    • 4
  1. 1.Informatics and Biocomputing ProgramOntario Institute for Cancer ResearchTorontoCanada
  2. 2.Knight Cancer InstituteOregon Health & Science UniversityPortlandUSA
  3. 3.University of Michigan Medical SchoolAnn ArborUSA
  4. 4.Department of Medical Informatics and Clinical EpidemiologyOregon Health & Science UniversityPortlandUSA

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