syntenet : an R/Bioconductor package for the inference and analysis of synteny networks
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Date
Authors
Almeida-Silva, Fabricio
Zhao, Tao
Ullrich, Kristian K.
Schranz, M. Eric
Van de Peer, Yves
Journal Title
Journal ISSN
Volume Title
Publisher
Oxford University Press
Abstract
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.
Description
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).
Keywords
syntenet, Synteny networks, Whole genome sequencing (WGS), Data preprocessing, Microsynteny-based phylogeny inference, Phylogenomic profiling, Synteny detection, Network inference, Network clustering
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Citation
Fabricio Almeida-Silva, Tao Zhao, Kristian K Ullrich, M Eric Schranz, Yves Van de Peer, syntenet: an R/Bioconductor package for the inference and analysis of synteny networks, Bioinformatics, Volume 39, Issue 1, January 2023, btac806, https://doi.org/10.1093/bioinformatics/btac806.