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ODGI: understanding pangenome graphs
MOTIVATION: Pangenome graphs provide a complete representation of the mutual alignment of collections of genomes. These models offer the opportunity to study the entire genomic diversity of a population, including structurally complex regions. Nevertheless, analyzing hundreds of gigabase-scale genom...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9237687/ https://www.ncbi.nlm.nih.gov/pubmed/35552372 http://dx.doi.org/10.1093/bioinformatics/btac308 |
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author | Guarracino, Andrea Heumos, Simon Nahnsen, Sven Prins, Pjotr Garrison, Erik |
author_facet | Guarracino, Andrea Heumos, Simon Nahnsen, Sven Prins, Pjotr Garrison, Erik |
author_sort | Guarracino, Andrea |
collection | PubMed |
description | MOTIVATION: Pangenome graphs provide a complete representation of the mutual alignment of collections of genomes. These models offer the opportunity to study the entire genomic diversity of a population, including structurally complex regions. Nevertheless, analyzing hundreds of gigabase-scale genomes using pangenome graphs is difficult as it is not well-supported by existing tools. Hence, fast and versatile software is required to ask advanced questions to such data in an efficient way. RESULTS: We wrote Optimized Dynamic Genome/Graph Implementation (ODGI), a novel suite of tools that implements scalable algorithms and has an efficient in-memory representation of DNA pangenome graphs in the form of variation graphs. ODGI supports pre-built graphs in the Graphical Fragment Assembly format. ODGI includes tools for detecting complex regions, extracting pangenomic loci, removing artifacts, exploratory analysis, manipulation, validation and visualization. Its fast parallel execution facilitates routine pangenomic tasks, as well as pipelines that can quickly answer complex biological questions of gigabase-scale pangenome graphs. AVAILABILITY AND IMPLEMENTATION: ODGI is published as free software under the MIT open source license. Source code can be downloaded from https://github.com/pangenome/odgi and documentation is available at https://odgi.readthedocs.io. ODGI can be installed via Bioconda https://bioconda.github.io/recipes/odgi/README.html or GNU Guix https://github.com/pangenome/odgi/blob/master/guix.scm. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. |
format | Online Article Text |
id | pubmed-9237687 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-92376872022-06-29 ODGI: understanding pangenome graphs Guarracino, Andrea Heumos, Simon Nahnsen, Sven Prins, Pjotr Garrison, Erik Bioinformatics Original Papers MOTIVATION: Pangenome graphs provide a complete representation of the mutual alignment of collections of genomes. These models offer the opportunity to study the entire genomic diversity of a population, including structurally complex regions. Nevertheless, analyzing hundreds of gigabase-scale genomes using pangenome graphs is difficult as it is not well-supported by existing tools. Hence, fast and versatile software is required to ask advanced questions to such data in an efficient way. RESULTS: We wrote Optimized Dynamic Genome/Graph Implementation (ODGI), a novel suite of tools that implements scalable algorithms and has an efficient in-memory representation of DNA pangenome graphs in the form of variation graphs. ODGI supports pre-built graphs in the Graphical Fragment Assembly format. ODGI includes tools for detecting complex regions, extracting pangenomic loci, removing artifacts, exploratory analysis, manipulation, validation and visualization. Its fast parallel execution facilitates routine pangenomic tasks, as well as pipelines that can quickly answer complex biological questions of gigabase-scale pangenome graphs. AVAILABILITY AND IMPLEMENTATION: ODGI is published as free software under the MIT open source license. Source code can be downloaded from https://github.com/pangenome/odgi and documentation is available at https://odgi.readthedocs.io. ODGI can be installed via Bioconda https://bioconda.github.io/recipes/odgi/README.html or GNU Guix https://github.com/pangenome/odgi/blob/master/guix.scm. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. Oxford University Press 2022-05-13 /pmc/articles/PMC9237687/ /pubmed/35552372 http://dx.doi.org/10.1093/bioinformatics/btac308 Text en © The Author(s) 2022. Published by Oxford University Press. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Original Papers Guarracino, Andrea Heumos, Simon Nahnsen, Sven Prins, Pjotr Garrison, Erik ODGI: understanding pangenome graphs |
title | ODGI: understanding pangenome graphs |
title_full | ODGI: understanding pangenome graphs |
title_fullStr | ODGI: understanding pangenome graphs |
title_full_unstemmed | ODGI: understanding pangenome graphs |
title_short | ODGI: understanding pangenome graphs |
title_sort | odgi: understanding pangenome graphs |
topic | Original Papers |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9237687/ https://www.ncbi.nlm.nih.gov/pubmed/35552372 http://dx.doi.org/10.1093/bioinformatics/btac308 |
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