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


ABSTRACT:

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.

SUBMITTER: Almeida-Silva F 

PROVIDER: S-EPMC9825758 | biostudies-literature | 2023 Jan

REPOSITORIES: biostudies-literature

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Publications

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

Almeida-Silva Fabricio F   Zhao Tao T   Ullrich Kristian K KK   Schranz M Eric ME   Van de Peer Yves Y  

Bioinformatics (Oxford, England) 20230101 1


<h4>Summary</h4>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 cluster  ...[more]

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