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syntenet: an R/Bioconductor package for the inference and analysis of synteny networks
SUMMARY: Interpreting and visualizing synteny relationships across several genomes is a challenging task. We previously proposed a network-based approach for better visualization and interpretation of large-scale microsynteny analyses. Here, we present syntenet, an R package to infer and analyze syn...
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/PMC9825758/ https://www.ncbi.nlm.nih.gov/pubmed/36539202 http://dx.doi.org/10.1093/bioinformatics/btac806 |
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author | Almeida-Silva, Fabricio Zhao, Tao Ullrich, Kristian K Schranz, M Eric Van de Peer, Yves |
author_facet | Almeida-Silva, Fabricio Zhao, Tao Ullrich, Kristian K Schranz, M Eric Van de Peer, Yves |
author_sort | Almeida-Silva, Fabricio |
collection | PubMed |
description | SUMMARY: Interpreting and visualizing synteny relationships across several genomes is a challenging task. We previously proposed a network-based approach for better visualization and interpretation of large-scale microsynteny analyses. Here, we present syntenet, an R package to infer and analyze synteny networks from whole-genome protein sequence data. The package offers a simple and complete framework, including data preprocessing, synteny detection and network inference, network clustering and phylogenomic profiling, and microsynteny-based phylogeny inference. Graphical functions are also available to create publication-ready plots. Synteny networks inferred with syntenet can highlight taxon-specific gene clusters that likely contributed to the evolution of important traits, and microsynteny-based phylogenies can help resolve phylogenetic relationships under debate. AVAILABILITY AND IMPLEMENTATION: syntenet is available on Bioconductor (https://bioconductor.org/packages/syntenet), and the source code is available on a GitHub repository (https://github.com/almeidasilvaf/syntenet). SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. |
format | Online Article Text |
id | pubmed-9825758 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-98257582023-01-10 syntenet: an R/Bioconductor package for the inference and analysis of synteny networks Almeida-Silva, Fabricio Zhao, Tao Ullrich, Kristian K Schranz, M Eric Van de Peer, Yves Bioinformatics Applications Note SUMMARY: Interpreting and visualizing synteny relationships across several genomes is a challenging task. We previously proposed a network-based approach for better visualization and interpretation of large-scale microsynteny analyses. Here, we present syntenet, an R package to infer and analyze synteny networks from whole-genome protein sequence data. The package offers a simple and complete framework, including data preprocessing, synteny detection and network inference, network clustering and phylogenomic profiling, and microsynteny-based phylogeny inference. Graphical functions are also available to create publication-ready plots. Synteny networks inferred with syntenet can highlight taxon-specific gene clusters that likely contributed to the evolution of important traits, and microsynteny-based phylogenies can help resolve phylogenetic relationships under debate. AVAILABILITY AND IMPLEMENTATION: syntenet is available on Bioconductor (https://bioconductor.org/packages/syntenet), and the source code is available on a GitHub repository (https://github.com/almeidasilvaf/syntenet). SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. Oxford University Press 2022-12-20 /pmc/articles/PMC9825758/ /pubmed/36539202 http://dx.doi.org/10.1093/bioinformatics/btac806 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 | Applications Note Almeida-Silva, Fabricio Zhao, Tao Ullrich, Kristian K Schranz, M Eric Van de Peer, Yves syntenet: an R/Bioconductor package for the inference and analysis of synteny networks |
title | syntenet: an R/Bioconductor package for the inference and analysis of synteny networks |
title_full | syntenet: an R/Bioconductor package for the inference and analysis of synteny networks |
title_fullStr | syntenet: an R/Bioconductor package for the inference and analysis of synteny networks |
title_full_unstemmed | syntenet: an R/Bioconductor package for the inference and analysis of synteny networks |
title_short | syntenet: an R/Bioconductor package for the inference and analysis of synteny networks |
title_sort | syntenet: an r/bioconductor package for the inference and analysis of synteny networks |
topic | Applications Note |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9825758/ https://www.ncbi.nlm.nih.gov/pubmed/36539202 http://dx.doi.org/10.1093/bioinformatics/btac806 |
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