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. 2023 May 10;617(7960):312–324. doi: 10.1038/s41586-023-05896-x

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© The Author(s) 2023

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

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Extended Data Fig. 3 — a, Two haplotypes (H₁ and H₂) vary in copy number of a chromosomal segment S. The S₁, S₂, and S₃ segments are highly similar with only a SNP or a small indel. b, Pangenome graph structures for Minigraph, MC, and PGGB. Minigraph used H₁ as an initial backbone and then augmented with SVs (≥50 bp) from H₂, such that the SNP in S₂ is not represented in the pangenome graph. MC added small variants (<50 bp) to the pangenome graph constructed by Minigraph. PGGB used a symmetric, all-by-all alignment of haplotypes to build a pangenome graph whose structure is not affected by the order of inputs (unlike Minigraph and MC). The critical difference in graph construction is that, due to ambiguous pairwise relationships of paralogs, PGGB tends to collapse copy-number polymorphic loci like segmental duplications and VNTRs into a single copy through which haplotypes loop, while Minigraph and MC do not.