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logoENViz: A Cytoscape App for Integrated Statistical Analysis and Visualization of Sample-Matched Data with Multiple Data Types

Anya Tsalenko, Roy Navon, Israel Steinfeld, Michael Creech, Zohar Yakhini and Allan Kuchinsky

ENViz (Enrichment Analysis and Visualization) is a Cytoscape (Cline et al., 2007) app that performs joint enrichment analysis of two types of sample matched datasets in the context of systematic annotations. Such datasets may be gene expression, miRNA or other non-coding RNA expression, proteomics measurements or any other high-throughput data collected in the same set of samples. The enrichment analysis is based on the minimum hypergeometric statistics (Eden et al., 2007, 2009) and is done in the context of WikiPathway information (Kelder et al., 2011), gene ontology (GO) or any custom annotation of the data. The results of the analysis consist of significant associations between profiled elements of one of the datasets to the annotation terms. For example, miR-19 was found to be associated to the cell cycle process in a cohort of breast cancer samples (Enerly et al., 2011). The results of the enrichment analysis are visualized as an interactive Cytoscape network, and can be visually overlaid on biological pathways or GO hierarchy. ENViz is freely available through the Cytoscape App Store (

For details on recommended computer configuration, ENViz configuration, and migrating data to new versions of ENViz, see the Cy2 User Readme or the Cy3 User Readme documents.

ENViz resources:

ENViz documentation.
Sample dataset.
ENViz license.

Example of Cytoscape session with ENViz application running. (a) Interactive legend, Analysis, and Visualization control panels. The Interactive legend shows a schematic of the analysis and the overview of the data loaded into Cytoscape for ENViz analysis. The Analysis panel controls data input and analysis parameter settings. The Visualization panel controls the significance threshold for the enrichment network generation and the color coding of the annotation categories based on enrichment scores. (b) Bi-partite network for enrichment analysis of breast cancer data. Nodes in this network correspond to WikiPathways (colored yellow->red) and miRNAs (gray), and edges represent significant enrichments of genes in the pathway correlated (red) or anti-correlated (blue) to the miRNA. Blue and red edges correspond to enrichment of correlated and of anti-correlated genes, respectively. (c) Cell Cycle WikiPathway with genes color-coded according to their correlation to mir-301b. (d) GO terms enriched in genes correlated to miR-150.

  • Cline MS, Smoot M, et al. (2007), Integration of biological networks and gene expression data using Cytoscape. Nature Protocols
  • Eden E, Lipson D, Yogev S, and Yakhini, Z. (2007), Discovering Motifs in Ranked Lists of DNA sequences. PLoS Computational Biology
  • Eden E, Navon R, Steinfeld I, et al. (2009), GOrilla: A Tool For Discovery And Visualization of Enriched GO Terms in Ranked Gene Lists. BMC Bioinformatics
  • Enerly E, Steinfeld I, et al. (2011), miRNA-mRNA Integrated Analysis Reveals Roles for miRNAs in Primary Breast Tumors. PLoS One.
  • Kelder T, et al. (2011), WikiPathways: building research communities on biological pathways. NAR.