**ENViz** is an ENrichment analysis and VisualiZation plugin for integrated analysis of multiple sample matched data sets in the context of systematic annotation. ENViz analyses a primary data set (e.g. gene expression) with respect to a pivot data set (e.g. miRNA expression, other non-coding RNA expression or proteomics measurements) and to primary data annotation (e.g. pathway or gene ontology) in the following way. For each pivot entry, we rank elements of the primary data based on the correlation to the pivot across all samples, and compute statistical enrichment of annotation elements at the top of this ranked list based on the minimum hypergeometric statistics (Eden et al, 2007, Eden et al, 2009). Significant results are represented as an enrichment network - a bipartite graph with nodes corresponding to pivot and annotation entries, and edges corresponding to pivot-annotation entry pairs with enrichment scores above the user defined threshold. Correlations of primary data and pivot data can be visually overlaid on biological pathways for significant pivot-annotation pairs using WikiPathways resource (Kelder et al, 2012). In the context of gene ontology (GO), enrichment network can be overlaid on top of GO hierarchy. Edges of the enrichment network point to potential functionally relevant mechanisms.
"ENViz: A Cytoscape App for Integrated Statistical Analysis and Visualization of Sample-Matched Data with Multiple Data Types." *Steinfeld I, Navon R, Creech ML, Yakhini Z, Tsalenko A*, Bioinformatics, Jan 2015, PMID: 25577435.