syntenet : an R/Bioconductor package for the inference and analysis of synteny networks

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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.