Graphia: a new network analysis platform for the exploration and analysis of big data

In common with many sectors, the biological sciences are awash with data. One approach gaining traction for use in its interpretation is network analysis. Graphia is a new analytical platform designed as a fast and flexible network analysis platform for big data. At its core is a powerful 3D network visualisation engine capable of rendering millions of data points, allowing users to explore data structure. Networks can be imported or generated within the tool from any numerical matrix. Graphs are rendered dynamically, with the result that they can be filtered or changed on-the-fly. It has a range of built-in analytical algorithms, e.g. clustering, PageRank, advanced options to transform and visualise networks based on node or edge attributes, link out to external databases and perform data integration.

In biology we have demonstrated its utility in the analysis of multiple types of omics data, pathway analysis and imaging data. However, its modular design means that it can be adapted to perform specific tasks associated with many different data types. I will outline its design principles and demonstrate its functionality with a range of data types.