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Comparing methods for constructing and representing human pangenome graphs
BACKGROUND: As a single reference genome cannot possibly represent all the variation present across human individuals, pangenome graphs have been introduced to incorporate population diversity within a wide range of genomic analyses. Several data structures have been proposed for representing collec...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10691155/ https://www.ncbi.nlm.nih.gov/pubmed/38037131 http://dx.doi.org/10.1186/s13059-023-03098-2 |
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author | Andreace, Francesco Lechat, Pierre Dufresne, Yoann Chikhi, Rayan |
author_facet | Andreace, Francesco Lechat, Pierre Dufresne, Yoann Chikhi, Rayan |
author_sort | Andreace, Francesco |
collection | PubMed |
description | BACKGROUND: As a single reference genome cannot possibly represent all the variation present across human individuals, pangenome graphs have been introduced to incorporate population diversity within a wide range of genomic analyses. Several data structures have been proposed for representing collections of genomes as pangenomes, in particular graphs. RESULTS: In this work, we collect all publicly available high-quality human haplotypes and construct the largest human pangenome graphs to date, incorporating 52 individuals in addition to two synthetic references (CHM13 and GRCh38). We build variation graphs and de Bruijn graphs of this collection using five of the state-of-the-art tools: Bifrost, mdbg, Minigraph, Minigraph-Cactus and pggb. We examine differences in the way each of these tools represents variations between input sequences, both in terms of overall graph structure and representation of specific genetic loci. CONCLUSION: This work sheds light on key differences between pangenome graph representations, informing end-users on how to select the most appropriate graph type for their application. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13059-023-03098-2. |
format | Online Article Text |
id | pubmed-10691155 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-106911552023-12-02 Comparing methods for constructing and representing human pangenome graphs Andreace, Francesco Lechat, Pierre Dufresne, Yoann Chikhi, Rayan Genome Biol Research BACKGROUND: As a single reference genome cannot possibly represent all the variation present across human individuals, pangenome graphs have been introduced to incorporate population diversity within a wide range of genomic analyses. Several data structures have been proposed for representing collections of genomes as pangenomes, in particular graphs. RESULTS: In this work, we collect all publicly available high-quality human haplotypes and construct the largest human pangenome graphs to date, incorporating 52 individuals in addition to two synthetic references (CHM13 and GRCh38). We build variation graphs and de Bruijn graphs of this collection using five of the state-of-the-art tools: Bifrost, mdbg, Minigraph, Minigraph-Cactus and pggb. We examine differences in the way each of these tools represents variations between input sequences, both in terms of overall graph structure and representation of specific genetic loci. CONCLUSION: This work sheds light on key differences between pangenome graph representations, informing end-users on how to select the most appropriate graph type for their application. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13059-023-03098-2. BioMed Central 2023-11-30 /pmc/articles/PMC10691155/ /pubmed/38037131 http://dx.doi.org/10.1186/s13059-023-03098-2 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/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/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Andreace, Francesco Lechat, Pierre Dufresne, Yoann Chikhi, Rayan Comparing methods for constructing and representing human pangenome graphs |
title | Comparing methods for constructing and representing human pangenome graphs |
title_full | Comparing methods for constructing and representing human pangenome graphs |
title_fullStr | Comparing methods for constructing and representing human pangenome graphs |
title_full_unstemmed | Comparing methods for constructing and representing human pangenome graphs |
title_short | Comparing methods for constructing and representing human pangenome graphs |
title_sort | comparing methods for constructing and representing human pangenome graphs |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10691155/ https://www.ncbi.nlm.nih.gov/pubmed/38037131 http://dx.doi.org/10.1186/s13059-023-03098-2 |
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