PG2: algorithms and a web-based tool for effective layout and visual analysis of pangenome graphs

BACKGROUND: The advent of cost-effective whole-genome assembly has enabled the creation of comprehensive pangenomes with resolved haplotypes across various organisms. This technological leap drives the refinement of tailored methodologies to manage the intricate sequences and variations in extensive collections of related genomes. These methodologies often utilize graphical representations of pangenomes to enhance algorithms for tasks like sequence alignment, visualization, and functional genomics. Leveraging the insights provided by pangenomes, these approaches exhibit improved efficiency in bioinformatics tasks such as read mapping, variant calling, and genotyping. Pangenome graphs are positioned to become invaluable assets in genomics, offering seamless reconciliation of diverse sequence and coordinate systems. While their potential to replace linear reference genomes is uncertain, their adaptability ensures their utility in future pangenomic models. Utilizing graphs for visual representation aids in exploring critical insights and identifying key patterns, facilitating analysis by highlighting connections, trends, and patterns for improved comprehension. RESULTS: Towards this goal, we present some algorithms to effectively layout and visually analyze pangenome graphs. Then, we introduce an open-source, flexible, easy-to-use, web-based platform named PG2 (PanGenoGrapher), realizing these algorithms. CONCLUSIONS: Our primary objective here is to incorporate the capabilities of advanced visualization techniques into the analysis of pangenome graphs, thereby enhancing their utility and accessibility for researchers and practitioners in the field. The source code and user guide are openly available on GitHub at https://github.com/iVis-at-Bilkent/pangenographer. A publicly accessible sample deployment is hosted at http://pg2.cs.bilkent.edu.tr. In addition, a demonstration video illustrating the primary use cases of PG2 is available at https://www.youtube.com/watch?v=yCd7-aGY6CQ.

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Publication Details

Journal
BMC Bioinformatics
Published
2026-07-16
DOI
https://doi.org/10.1186/s12859-026-06555-4
Primary Topic
Data Visualization and Analytics
Type
article
Field-Weighted Citation Impact
0.00
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article

PG2: algorithms and a web-based tool for effective layout and visual analysis of pangenome graphs

Uğur Doğrusöz, Can Alkan, Zülal Bingöl, Gorkem Kadir Solun
BMC Bioinformatics
Data Visualization and Analytics
article

PG2: algorithms and a web-based tool for effective layout and visual analysis of pangenome graphs

Uğur Doğrusöz, Can Alkan, Zülal Bingöl, Gorkem Kadir Solun
article en

Abstract

BACKGROUND: The advent of cost-effective whole-genome assembly has enabled the creation of comprehensive pangenomes with resolved haplotypes across various organisms. This technological leap drives the refinement of tailored methodologies to manage the intricate sequences and variations in extensive collections of related genomes. These methodologies often utilize graphical representations of pangenomes to enhance algorithms for tasks like sequence alignment, visualization, and functional genomics. Leveraging the insights provided by pangenomes, these approaches exhibit improved efficiency in bioinformatics tasks such as read mapping, variant calling, and genotyping. Pangenome graphs are positioned to become invaluable assets in genomics, offering seamless reconciliation of diverse sequence and coordinate systems. While their potential to replace linear reference genomes is uncertain, their adaptability ensures their utility in future pangenomic models. Utilizing graphs for visual representation aids in exploring critical insights and identifying key patterns, facilitating analysis by highlighting connections, trends, and patterns for improved comprehension. RESULTS: Towards this goal, we present some algorithms to effectively layout and visually analyze pangenome graphs. Then, we introduce an open-source, flexible, easy-to-use, web-based platform named PG2 (PanGenoGrapher), realizing these algorithms. CONCLUSIONS: Our primary objective here is to incorporate the capabilities of advanced visualization techniques into the analysis of pangenome graphs, thereby enhancing their utility and accessibility for researchers and practitioners in the field. The source code and user guide are openly available on GitHub at https://github.com/iVis-at-Bilkent/pangenographer. A publicly accessible sample deployment is hosted at http://pg2.cs.bilkent.edu.tr. In addition, a demonstration video illustrating the primary use cases of PG2 is available at https://www.youtube.com/watch?v=yCd7-aGY6CQ.

BMC Bioinformatics
Bilkent University (TR)
Climate action
Openalex Percentile: Top 9%
Data Visualization and Analytics
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