A graph-based approach for the visualisation and analysis of bacterial pangenomes

Background The advent of low cost, high throughput DNA sequencing has led to the availability of thousands of complete genome sequences for a wide variety of bacterial species. Examining and interpreting genetic variation on this scale represents a significant challenge to existing methods of data analysis and visualisation. Results Starting with the output of standard pangenome analysis tools, we describe the generation and analysis of interactive, 3D network graphs to explore the structure of bacterial populations, the distribution of genes across a population, and the syntenic order in which those genes occur, in the new open-source network analysis platform, Graphia. Both the analysis and the visualisation are scalable to datasets of thousands of genome sequences. Conclusions We anticipate that the approaches presented here will be of great utility to the microbial research community, allowing faster, more intuitive, and flexible interaction with pangenome datasets, thereby enhancing interpretation of these complex data.

Automated summary

This study presents the use of an open-source network analysis platform, Graphia, to generate and analyze interactive 3D network graphs for studying the structure of bacterial populations, gene distribution, and syntenic order. The scalability to large genome datasets makes it valuable for the microbial research community.