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

Josh Harling-Lee*, Jamie Gorzynski, Gonzalo Yebra, Tim Angus, Ross Fitzgerald, Thomas C Freeman

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract / Description of output

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.
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.
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.
Original languageEnglish
Pages (from-to)1-15
Number of pages15
JournalBMC Bioinformatics
Issue number416
Early online date8 Oct 2022
Publication statusPublished - Dec 2022

Keywords / Materials (for Non-textual outputs)

  • Bacteria
  • Pangenome
  • Accessory genes
  • Network graphs
  • Data visualisation


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