ReactomeFIViz: A cytoscape app for pathway and network-based data analysis

Guanming Wu, Eric Dawson, Adrian Duong, Robin Haw, Lincoln Stein

Research output: Contribution to journalArticlepeer-review

173 Scopus citations

Abstract

High-throughput experiments are routinely performed in modern biological studies. However, extracting meaningful results from massive experimental data sets is a challenging task for biologists. Projecting data onto pathway and network contexts is a powerful way to unravel patterns embedded in seemingly scattered large data sets and assist knowledge discovery related to cancer and other complex diseases. We have developed a Cytoscape app called "ReactomeFIViz?, which utilizes a highly reliable gene functional interaction network combined with human curated pathways derived from Reactome and other pathway databases. This app provides a suite of features to assist biologists in performing pathway- and network-based data analysis in a biologically intuitive and user-friendly way. Biologists can use this app to uncover network and pathway patterns related to their studies, search for gene signatures from gene expression data sets, reveal pathways significantly enriched by genes in a list, and integrate multiple genomic data types into a pathway context using probabilistic graphical models. We believe our app will give researchers substantial power to analyze intrinsically noisy high-throughput experimental data to find biologically relevant information.

Original languageEnglish (US)
Article number4431.2
JournalF1000Research
Volume3
DOIs
StatePublished - Sep 12 2014

ASJC Scopus subject areas

  • General Immunology and Microbiology
  • General Pharmacology, Toxicology and Pharmaceutics
  • General Biochemistry, Genetics and Molecular Biology

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