TY - JOUR
T1 - syntenet: an R/Bioconductor package for the inference and analysis of synteny networks
AU - Almeida-Silva, Fabricio
AU - Zhao, Tao
AU - Ullrich, Kristian K.
AU - Schranz, M.E.
AU - Van de Peer, Yves
PY - 2023/1
Y1 - 2023/1
N2 - 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.
AB - 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.
U2 - 10.1093/bioinformatics/btac806
DO - 10.1093/bioinformatics/btac806
M3 - Article
SN - 1367-4803
VL - 39
JO - Bioinformatics
JF - Bioinformatics
IS - 1
M1 - btac806
ER -