Getting poster data...
M Krzywinski, I Birol, S Jones, M Marra (Canada’s Michael Smith Genome Sciences Centre, Vancouver, Canada)Classical network visualizations (hairballs) are difficult to interpret and compare and their effectiveness is determined by the choice of layout algorithm. To visualize networks rationally we present the hive plot, a visualization method based on meaningful network properties. Nodes are assigned to one of three (or more) axes, which may be divided into segments. Nodes are ordered on a segment based on properties such as connectivity, density, centrality or quantitative annotation (e.g. expression). Edges are drawn as Bezier curves. Hive plots make possible assessing network structure because they are founded on network properties, not aesthetic layout. Visualizations of two networks are directly comparable and the degree of difference can be assessed. Any network can be represented as a hive plot (e.g. gene regulation, protein-protein interaction). When the axis segments are interpreted as sequence, the plot can show three-way alignment and conservation. If connections are drawn as ribbons, the hive plot can demonstrate ratios between elements of normalized quantities (e.g. comparison of sizes of annotation categories in different genomes).