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Pangenome Graphs
Open accessAbstract
Low-cost whole-genome assembly has enabled the collection of haplotype-resolved pangenomes for numerous organisms. In turn, this technological change is encouraging the development of methods that can precisely address the sequence and variation described in large collections of related genomes. These approaches often use graphical models of the pangenome to support algorithms for sequence alignment, visualization, functional genomics, and association studies. The additional information provided to these methods by the pangenome allows them to achieve superior performance on a variety of bioinformatic tasks, including read alignment, variant calling, and genotyping. Pangenome graphs stand to become a ubiquitous tool in genomics. Although it is unclear whether they will replace linearreference genomes, their ability to harmoniously relate multiple sequence and coordinate systems will make them useful irrespective of which pangenomic models become most common in the future.
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“Graph-based pangenomes replace that single path with a network of alternative haplotypes, explicitly modeling variation from single-nucleotide polymorphisms to megabase-scale structural changes ( 95 ).”
From Topological Approaches in Animal Comparative Genomics (2026) · cites this paper as [95]
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In the citing paper
“Pangenomic methods have rapidly progressed over the past few years13–15 such that it is now practical to propose that common genomic analyses use a pangenome.”
From A draft human pangenome reference. (2023) · cites this paper as [14]
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“These are graph-theoretic extensions to the standard linear reference genomes that are able to capture more known variation by storing more knowledge about genomic diversity in an organism than is possible with a single genome [15].”
From <tt>SAFARI</tt> : pangenome alignment of ancient DNA using purine/pyrimidine encodings (2025) · cites this paper as [15]
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“Linear reference genomes collapse population diversity into a single path, which biases alignment and variant discovery from different individuals of the same species.”
From Topological Approaches in Animal Comparative Genomics (2026) · cites this paper as [95]
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Additional file 1 of A pan-Zea genome map for enhancing maize improvement
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Metadata
- Authors
- Eizenga, J. M., Novak, A. M., Sibbesen, J. A., Heumos, S., Ghaffaari, A., Hickey, G., Chang, X., Seaman, J. D., Rounthwaite, R., Ebler, J., Rautiainen, M., Garg, S., Paten, B., Marschall, T., Sirén, J., & Garrison, E.
- Affiliations
- University of California, Santa Cruz (US)
- Quantitative Biology Center (DE)
- Max Planck Institute for Informatics (DE)
- Queen Mary University of London (GB)
- Harvard University (US)
- Corresponding author
- Garrison, Erik
- ORCID
- Venue
- Annual Review of Genomics and Human Genetics
- Publisher
- Annual Reviews
- Published
- 2020-08-31
- Volume
- 21
- Issue
- 1
- Pages
- 139-162
- ISSN
- 1527-8204 (ISSN-L)
- 1545-293X
- PMC
- PMC8006571
- OpenAlex
- W4255836900
- Cited by
- 320
- References
- 139
- Citations by year
- 2026: 57 · 2025: 64 · 2024: 66 · 2023: 64 · 2022: 47 · 2021: 19 · 2020: 2
- FWCI
- 3.38
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Annual Review of Genomics and Human Genetics (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- eScholarship (California Digital Library) (submittedVersion)
- Funders
- W. M. Keck Foundation
- Bundesministerium für Wirtschaft und Energie
- National Institutes of Health
- Directorate for Biological Sciences
- Biotechnology and Biological Sciences Research Council (BB/S004661/1)
- National Heart, Lung, and Blood Institute (U01HL137183)
- National Human Genome Research Institute (R01HG010485, U41HG007234, U54HG007990)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Phylogenetic Studies
- Physical Sciences › Mathematics › Theoretical Computer Science › Algorithms and Data Compression
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genome Rearrangement Algorithms
- Keywords
- pangenome graphs, pangenome assembly, read mapping, variant calling, genotyping, sequence variation, haplotype structure
- MeSH terms
- Algorithms, Computer Graphics, Humans, Genome, Human, Sequence Analysis, DNA, Computational Biology, High-Throughput Nucleotide Sequencing
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