However, a correlation matrix can be very large, and often cannot be stored in memory, so this program saves only the relevant correlations as they are calculated. Any correlation above or below given threshold values, is displayed in Cytoscape as an 'edge' between two 'nodes' (the nodes are the two genes or conditions that are correlated). Gene expression data (loaded in via Cytoscape) can be used to create a gene or a condition correlation matrix. The ExpressionCorrelation plugin is freely available and open-source molecular profile visualization software. No statistical significance is currently implemented for the similarity network. A histogram tool is available for choosing a similarity strength threshold, in order to ease creation of a reasonably sized network. The similarity matrix is computed using the Pearson Correlation Coefficient. The plugin allows the user to select an Expression Matrix of microarray data directly from Cytoscape and convert it to a visible interaction network in Cytoscape. Links represent similarity (or correlations) between vectors of the expression levels of genes across all given conditions (gene correlation network) or the similarity between vectors of the expression levels of all genes in a single condition (condition correlation network). Nodes in a similarity network represent genes or conditions. The ExpressionCorrelation plugin computes a similarity network from either the genes or conditions in an expression matrix (where genes are rows and conditions are columns).
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