Background: The iRefIndex consolidates protein interaction data from ten databases in a rigorous manner using sequence-based hash keys. Working with consolidated interaction data comes with distinct challenges: data are redundant, overlapping, highly interconnected and may be collected and represented using different curation practices. These phenomena were quantified in our previous studies.
Results: The iRefScape plug-in for the Cytoscape graphical viewer addresses these challenges. We show how these factors impact on data-mining tasks and how our solutions resolve them in a simple and efficient manner. A uniform accession space is used to limit redundancy and support search expansion and searching on multiple accession types. Multiple node and edge features support data filtering and mining. Node colours and features supply information about search result provenance. Overlapping evidence is presented using a multi-graph and a bi-partite representation is used to distinguish binary and n-ary source data. Searching for interactions between sets of proteins is supported and specifically includes searches on disease-related genes found in OMIM. Finally, a synchronized adjacency-matrix view facilitates visualization of relationships between sets of user defined groups.
Conclusions: The iRefScape plug-in will be of interest to advanced users of interaction data. The plug-in provides access to a consolidated data set in a uniform accession space while remaining faithful to the underlying source data. Tools are provided to facilitate a range of tasks from a simple search to knowledge discovery. The plug-in uses a number of strategies that will be of interest to other plug-in developers.