# syntenet \[!\[GitHub issues\](https://img.shields.io/github/issues/almeidasilvaf/syntenet)\](https://github.com/almeidasilvaf/syntenet/issues) \[!\[Lifecycle: stable\](https://img.shields.io/badge/lifecycle-stable-brightgreen.svg)\](https://lifecycle.r-lib.org/articles/stages.html#stable) \[!\[R-CMD-check-bioc\](https://github.com/almeidasilvaf/syntenet/workflows/R-CMD-check-bioc/badge.svg)\](https://github.com/almeidasilvaf/syntenet/actions) \[!\[Codecov test coverage\](https://codecov.io/gh/almeidasilvaf/syntenet/branch/devel/graph/badge.svg)\](https://codecov.io/gh/almeidasilvaf/syntenet?branch=devel) The goal of \`syntenet\` is to infer synteny networks from whole-genome protein sequence data and analyze them. Anchor pairs from synteny analyses are treated as an undirected unweighted graph (i.e., a synteny network), and users can perform: - \*\*Synteny detection\*\* using a native implementation of the \[MCScanX algorithm\](https://doi.org/10.1093/nar/gkr1293), a C++ program that has been modified and ported to R with Rcpp. This way, users do not need to install MCScanX beforehand, because \`syntenet\` has its own implementation of the same algorithm. - \*\*Synteny network inference\*\* by treating anchor pairs as edges of a graph; - \*\*Network clustering\*\* using the Infomap algorithm; - \*\*Phylogenomic profiling\*\*, which consists in identifying which species contain which clusters. This analysis can reveal highly conserved synteny clusters and taxon-specific ones (e.g., family- and order-specific clusters); - \*\*Microsynteny-based phylogeny reconstruction\*\* with maximum likelihood, which can be achieved by inferring a phylogeny from a binary matrix of phylogenomic profiles with IQTREE. ## Installation instructions Get the latest stable \`R\` release from \[CRAN\](http://cran.r-project.org/). Then install \`syntenet\` from \[Bioconductor\](http://bioconductor.org/) using the following code: \`\`\` r if (!requireNamespace("BiocManager", quietly = TRUE)) { install.packages("BiocManager") } BiocManager::install("syntenet") \`\`\` And the development version from \[GitHub\](https://github.com/almeidasilvaf/syntenet) with: \`\`\` r BiocManager::install("almeidasilvaf/syntenet") \`\`\` ## Citation Below is the citation output from using \`citation('syntenet')\` in R. Please run this yourself to check for any updates on how to cite \*\*syntenet\*\*. \`\`\` r print(citation('syntenet'), bibtex = TRUE) #> #> To cite syntenet in publications, use: #> #> Almeida-Silva, F., Zhao, T., Ullrich, K.K., Schranz, M.E. and Van de #> Peer, Y. syntenet: an R/Bioconductor package for the inference and #> analysis of synteny networks. Bioinformatics, 39(1), p.btac806\. #> (2023). https://doi.org/10.1093/bioinformatics/btac806 #> #> A BibTeX entry for LaTeX users is #> #> @Article{, #> title = {syntenet: an R/Bioconductor package for the inference and analysis of synteny networks}, #> author = {Fabricio Almeida-Silva and Tao Zhao and Kristian K. Ullrich and M. Eric Schranz and Yves {Van de Peer}}, #> journal = {Bioinformatics}, #> year = {2023}, #> volume = {39}, #> number = {1}, #> pages = {btac806}, #> url = {https://academic.oup.com/bioinformatics/article/39/1/btac806/6947985}, #> doi = {10.1093/bioinformatics/btac806}, #> } \`\`\` Please note that \`syntenet\` was only made possible thanks to many other R and bioinformatics software authors, which are cited either in the vignettes and/or the paper(s) describing this package. ## Code of Conduct Please note that the \`syntenet\` project is released with a \[Contributor Code of Conduct\](http://bioconductor.org/about/code-of-conduct/). By contributing to this project, you agree to abide by its terms. ## Development tools - Continuous code testing is possible thanks to \[GitHub actions\](https://www.tidyverse.org/blog/2020/04/usethis-1-6-0/) through \*\[usethis\](https://CRAN.R-project.org/package=usethis)\*, \*\[remotes\](https://CRAN.R-project.org/package=remotes)\*, and \*\[rcmdcheck\](https://CRAN.R-project.org/package=rcmdcheck)\* customized to use \[Bioconductor’s docker containers\](https://www.bioconductor.org/help/docker/) and \*\[BiocCheck\](https://bioconductor.org/packages/3.15/BiocCheck)\*. - Code coverage assessment is possible thanks to \[codecov\](https://codecov.io/gh) and \*\[covr\](https://CRAN.R-project.org/package=covr)\*. - The \[documentation website\](http://almeidasilvaf.github.io/syntenet) is automatically updated thanks to \*\[pkgdown\](https://CRAN.R-project.org/package=pkgdown)\*. - The code is styled automatically thanks to \*\[styler\](https://CRAN.R-project.org/package=styler)\*. - The documentation is formatted thanks to \*\[devtools\](https://CRAN.R-project.org/package=devtools)\* and \*\[roxygen2\](https://CRAN.R-project.org/package=roxygen2)\*. For more details, check the \`dev\` directory. This package was developed using \*\[biocthis\](https://bioconductor.org/packages/3.15/biocthis)\*.
\[!\[GitHub issues\](https://img.shields.io/github/issues/almeidasilvaf/syntenet)\](https://github.com/almeidasilvaf/syntenet/issues) \[!\[Lifecycle: stable\](https://img.shields.io/badge/lifecycle-stable-brightgreen.svg)\](https://lifecycle.r-lib.org/articles/stages.html#stable) \[!\[R-CMD-check-bioc\](https://github.com/almeidasilvaf/syntenet/workflows/R-CMD-check-bioc/badge.svg)\](https://github.com/almeidasilvaf/syntenet/actions) \[!\[Codecov test coverage\](https://codecov.io/gh/almeidasilvaf/syntenet/branch/devel/graph/badge.svg)\](https://codecov.io/gh/almeidasilvaf/syntenet?branch=devel) The goal of \`syntenet\` is to infer synteny networks from whole-genome protein sequence data and analyze them. Anchor pairs from synteny analyses are treated as an undirected unweighted graph (i.e., a synteny network), and users can perform: - \*\*Synteny detection\*\* using a native implementation of the \[MCScanX algorithm\](https://doi.org/10.1093/nar/gkr1293), a C++ program that has been modified and ported to R with Rcpp. This way, users do not need to install MCScanX beforehand, because \`syntenet\` has its own implementation of the same algorithm. - \*\*Synteny network inference\*\* by treating anchor pairs as edges of a graph; - \*\*Network clustering\*\* using the Infomap algorithm; - \*\*Phylogenomic profiling\*\*, which consists in identifying which species contain which clusters. This analysis can reveal highly conserved synteny clusters and taxon-specific ones (e.g., family- and order-specific clusters); - \*\*Microsynteny-based phylogeny reconstruction\*\* with maximum likelihood, which can be achieved by inferring a phylogeny from a binary matrix of phylogenomic profiles with IQTREE. ## Installation instructions Get the latest stable \`R\` release from \[CRAN\](http://cran.r-project.org/). Then install \`syntenet\` from \[Bioconductor\](http://bioconductor.org/) using the following code: \`\`\` r if (!requireNamespace("BiocManager", quietly = TRUE)) { install.packages("BiocManager") } BiocManager::install("syntenet") \`\`\` And the development version from \[GitHub\](https://github.com/almeidasilvaf/syntenet) with: \`\`\` r BiocManager::install("almeidasilvaf/syntenet") \`\`\` ## Citation Below is the citation output from using \`citation('syntenet')\` in R. Please run this yourself to check for any updates on how to cite \*\*syntenet\*\*. \`\`\` r print(citation('syntenet'), bibtex = TRUE) #> #> To cite syntenet in publications, use: #> #> Almeida-Silva, F., Zhao, T., Ullrich, K.K., Schranz, M.E. and Van de #> Peer, Y. syntenet: an R/Bioconductor package for the inference and #> analysis of synteny networks. Bioinformatics, 39(1), p.btac806\. #> (2023). https://doi.org/10.1093/bioinformatics/btac806 #> #> A BibTeX entry for LaTeX users is #> #> @Article{, #> title = {syntenet: an R/Bioconductor package for the inference and analysis of synteny networks}, #> author = {Fabricio Almeida-Silva and Tao Zhao and Kristian K. Ullrich and M. Eric Schranz and Yves {Van de Peer}}, #> journal = {Bioinformatics}, #> year = {2023}, #> volume = {39}, #> number = {1}, #> pages = {btac806}, #> url = {https://academic.oup.com/bioinformatics/article/39/1/btac806/6947985}, #> doi = {10.1093/bioinformatics/btac806}, #> } \`\`\` Please note that \`syntenet\` was only made possible thanks to many other R and bioinformatics software authors, which are cited either in the vignettes and/or the paper(s) describing this package. ## Code of Conduct Please note that the \`syntenet\` project is released with a \[Contributor Code of Conduct\](http://bioconductor.org/about/code-of-conduct/). By contributing to this project, you agree to abide by its terms. ## Development tools - Continuous code testing is possible thanks to \[GitHub actions\](https://www.tidyverse.org/blog/2020/04/usethis-1-6-0/) through \*\[usethis\](https://CRAN.R-project.org/package=usethis)\*, \*\[remotes\](https://CRAN.R-project.org/package=remotes)\*, and \*\[rcmdcheck\](https://CRAN.R-project.org/package=rcmdcheck)\* customized to use \[Bioconductor’s docker containers\](https://www.bioconductor.org/help/docker/) and \*\[BiocCheck\](https://bioconductor.org/packages/3.15/BiocCheck)\*. - Code coverage assessment is possible thanks to \[codecov\](https://codecov.io/gh) and \*\[covr\](https://CRAN.R-project.org/package=covr)\*. - The \[documentation website\](http://almeidasilvaf.github.io/syntenet) is automatically updated thanks to \*\[pkgdown\](https://CRAN.R-project.org/package=pkgdown)\*. - The code is styled automatically thanks to \*\[styler\](https://CRAN.R-project.org/package=styler)\*. - The documentation is formatted thanks to \*\[devtools\](https://CRAN.R-project.org/package=devtools)\* and \*\[roxygen2\](https://CRAN.R-project.org/package=roxygen2)\*. For more details, check the \`dev\` directory. This package was developed using \*\[biocthis\](https://bioconductor.org/packages/3.15/biocthis)\*.