Large Scale Comparative Visualisation of Regulatory Networks with TRNDiff

The advent of Next Generation Sequencing (NGS) technologies has seen explosive growth in genomic datasets, and dense coverage of related organisms, supporting study of subtle, strain-specific variations as a determinant of function. Such data collections present fresh and complex challenges for bioinformatics, those of comparing models of complex relationships across hundreds and even thousands of sequences. Transcriptional Regulatory Network (TRN) structures document the influence of regulatory proteins called Transcription Factors (TFs) on associated Target Genes (TGs). TRNs are routinely inferred from model systems or iterative search, and analysis at these scales requires simultaneous displays of multiple networks well beyond those of existing network visualisation tools [1]. In this paper we describe TRNDiff, an open source system supporting the comparative analysis and visualization of TRNs (and similarly structured data) from many genomes, allowing rapid identification of functional variations within species. The approach is demonstrated through a small scale multiple TRN analysis of the Fur iron-uptake system of Yersinia, suggesting a number of candidate virulence factors; and through a larger study exploiting integration with the RegPrecise database (http://regprecise.lbl.gov; [2]) - a collection of hundreds of manually curated and predicted transcription factor regulons drawn from across the entire spectrum of prokaryotic organisms.Availability: TRNDiff is presently available in two versions, as a single client js script allowing browser based visualization of data files (here denoted V1) and as a scalable Node.js application with web service integration to RegPrecise (The QCloud Regulon Browser or V2). Information on TRNDiff ma be found at the dedicated site http://trndiff.org, which includes example data, short tutorials and links to demonstration installations of both the stand-alone system and the integrated regulon browser. Additional views from the standalone client, and support for clustering and touch-based interactivity are being incorporated into the Node.js version. Source code for both versions is freely available under a non-restrictive Apache 2.0 licence from the authors’ repository at http://bitbucket.org/biovisml, and contributions and feature requests are encouraged.