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Methods Mol Biol. 2020;2074:165-179. doi: 10.1007/978-1-4939-9873-9_13.

Perform Pathway Enrichment Analysis Using ReactomeFIViz.

Author information

1
Informatics and Biocomputing Program, Ontario Institute for Cancer Research, Toronto, ON, Canada.
2
Knight Cancer Institute, Oregon Health & Science University, Portland, OR, USA.
3
University of Michigan Medical School, Ann Arbor, MI, USA.
4
Department of Medical Informatics and Clinical Epidemiology, Oregon Health & Science University, Portland, OR, USA. guanmingwu@gmail.com.

Abstract

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.

KEYWORDS:

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

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