@inbook{a8e4ab9c14fb47868c98eb6c0e101d57,
title = "Perform pathway enrichment analysis using reactomeFIViz",
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",
author = "Robin Haw and Fred Loney and Edison Ong and Yongqun He and Guanming Wu",
note = "Publisher Copyright: {\textcopyright} Springer Science+Business Media, LLC, part of Springer Nature 2020.",
year = "2020",
doi = "10.1007/978-1-4939-9873-9_13",
language = "English (US)",
series = "Methods in Molecular Biology",
publisher = "Humana Press Inc.",
pages = "165--179",
booktitle = "Methods in Molecular Biology",
}