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- "text": "The \nggtree\n package extending the \nggplot2\n package. It based on grammar of graphics and takes all the good parts of \nggplot2\n. \nggtree\n is designed for not only viewing phylogenetic tree but also displaying annotation data on the tree.\n\nggtree\n is released within the \nBioconductor\n project and the source code is hosted on \n GitHub\n.\n\n\n Authors\n\n\nGuangchuang Yu and Tommy Tsan-Yuk Lam, School of Public Health, The University of Hong Kong.\n\n\n Citation\n\n\nPlease cite the following article when using \nggtree\n:\n\n\n\n\n\n\n\n\nG Yu\n, DK Smith, H Zhu, Y Guan, TTY Lam\n*\n. ggtree: an R package for visualization and annotation of phylogenetic trees with their covariates and other associated data. \nMethods in Ecology and Evolution\n. \naccepted\n.\n\n\n Featured Articles\n\n\n\n\n Find out more on \n \nFeatured Articles\n.\n\n\n Installation\n\n\nInstall \nggtree\n is easy, follow the guide on the \nBioconductor page\n:\n\n\n## try http:// if https:// URLs are not supported\nsource(\nhttps://bioconductor.org/biocLite.R\n)\n## biocLite(\nBiocUpgrade\n) ## you may need this\nbiocLite(\nggtree\n)\n\n\n\n\nIf you have problems when installing some of the dependent packages, please refer to the \nggtree-installation\n wiki page.\n\n\n Overview\n\n\n Getting tree into R\n\n\n\n\ntree parsers: bring evolution evidences to be used/analyzed in \nR\n\n\nmerge_tree\n: allows evolution evidences to be merged and compared\n\n\nfortify\n methods: convert tree objects into tidy data frame\n\n\n\n\n Tree visualization \n annotation\n\n\n\n\nparsing tree as a collection of nodes allows grammar of graphics to be supported\n\n\ngeom_tree\n: extends \nggplot2\n to support tree structure\n\n\nseveral layers and functions for tree annotation\n\n\nsupports annotating phylogenetic trees with user's own data\n\n\n\n\n Tree manipulation\n\n\n\n\nhelper functions for tree manipulation, make it possible to explore the tree visually\n\n\n\n\n Find out details and examples on \n \nDocumentation\n.\n\n\n Projects that depend on \nggtree\n\n\n Bioconductor packages\n\n\n\n\nLINC\n: co-expression of lincRNAs and protein-coding genes\n\n\nphilr\n: Phylogenetic partitioning based ILR transform for metagenomics data\n\n\n\n\n Other applications\n\n\n\n\nBreadCrumbs\n: Collection of scripts for metagenomics analysis\n\n\nDegeneratePrimerTools\n: Utilities for Creating and Validating Degenerate primers\n\n\nphyloscan\n: scan phylogenies created along a genome for patterns\n\n\n\n\n Feedback\n\n\n\n \n Please make sure you \nfollow the guide\n before posting any issue/question\n\n \n For bugs or feature requests, please post to \n \ngithub issue\n\n \n For user questions, please post to \n \ngoogle group\n\n \n We are also following every post tagged with \nggtree\n on \nBioconductor support site\n and \nBiostars\n\n \n Join the group chat on \n and",
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+ "text": "The \nggtree\n package extending the \nggplot2\n package. It based on grammar of graphics and takes all the good parts of \nggplot2\n. \nggtree\n is designed for not only viewing phylogenetic tree but also displaying annotation data on the tree.\n\nggtree\n is released within the \nBioconductor\n project and the source code is hosted on \n GitHub\n.\n\n\n Authors\n\n\nGuangchuang Yu and Tommy Tsan-Yuk Lam, School of Public Health, The University of Hong Kong.\n\n\n Citation\n\n\nPlease cite the following article when using \nggtree\n:\n\n\n\n\n\n\n\n\nG Yu\n, DK Smith, H Zhu, Y Guan, TTY Lam\n*\n. ggtree: an R package for visualization and annotation of phylogenetic trees with their covariates and other associated data. \nMethods in Ecology and Evolution\n. 2017, 8(1):28-36.\n\n\n Featured Articles\n\n\n\n\n Find out more on \n \nFeatured Articles\n.\n\n\n Installation\n\n\nInstall \nggtree\n is easy, follow the guide on the \nBioconductor page\n:\n\n\n## try http:// if https:// URLs are not supported\nsource(\"https://bioconductor.org/biocLite.R\")\n## biocLite(\"BiocUpgrade\") ## you may need this\nbiocLite(\"ggtree\")\n\n\n\n\nIf you have problems when installing some of the dependent packages, please refer to the \nggtree-installation\n wiki page.\n\n\n Overview\n\n\n Getting tree into R\n\n\n\n\ntree parsers: bring evolution evidences to be used/analyzed in \nR\n\n\nmerge_tree\n: allows evolution evidences to be merged and compared\n\n\nfortify\n methods: convert tree objects into tidy data frame\n\n\n\n\n Tree visualization & annotation\n\n\n\n\nparsing tree as a collection of nodes allows grammar of graphics to be supported\n\n\ngeom_tree\n: extends \nggplot2\n to support tree structure\n\n\nseveral layers and functions for tree annotation\n\n\nsupports annotating phylogenetic trees with user's own data\n\n\n\n\n Tree manipulation\n\n\n\n\nhelper functions for tree manipulation, make it possible to explore the tree visually\n\n\n\n\n Find out details and examples on \n \nDocumentation\n.\n\n\n Projects that depend on \nggtree\n\n\n Bioconductor packages\n\n\n\n\nLINC\n: co-expression of lincRNAs and protein-coding genes\n\n\nphilr\n: Phylogenetic partitioning based ILR transform for metagenomics data\n\n\n\n\n Other applications\n\n\n\n\nBreadCrumbs\n: Collection of scripts for metagenomics analysis\n\n\nDegeneratePrimerTools\n: Utilities for Creating and Validating Degenerate primers\n\n\nphyloscan\n: scan phylogenies created along a genome for patterns\n\n\n\n\n Feedback\n\n\n\n \n Please make sure you \nfollow the guide\n before posting any issue/question\n\n \n For bugs or feature requests, please post to \n \ngithub issue\n\n \n For user questions, please post to \n \ngoogle group\n\n \n We are also following every post tagged with \nggtree\n on \nBioconductor support site\n and \nBiostars\n\n \n Join the group chat on \n and",
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+ "text": "Install ggtree is easy, follow the guide on the Bioconductor page : ## try http:// if https:// URLs are not supported\nsource(\"https://bioconductor.org/biocLite.R\")\n## biocLite(\"BiocUpgrade\") ## you may need this\nbiocLite(\"ggtree\") If you have problems when installing some of the dependent packages, please refer to the ggtree-installation wiki page.",
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- "text": "Vignettes\n\n\n\n\nggtree\n\n\nTree Data Import\n\n\nTree Visualization\n\n\nTree Annotation\n\n\nTree Manipulation\n\n\nAdvance Tree Annotation\n\n\nggtree utilities\n\n\n\n\n Blog posts\n\n\n News and updates\n\n\n\n\nviewing and annotating phylogenetic tree with ggtree\n\n\nggtree in Bioconductor 3.1\n\n\nBioC 3.1: NEWS of my BioC packages\n\n\nBioC 3.2: NEWS of my BioC packages\n\n\nNews of ggtree\n\n\nBioC 3.3: NEWS of my BioC packages\n\n\nBioC 3.4: NEWS of my BioC packages\n\n\nggtree paper published\n\n\n\n\n Data manipulation\n\n\n\n\nsubsetting data in ggtree\n\n\nggtree supports phylip tree format\n\n\nconvert graphic object to tree object using treeio\n\n\n\n\n Tree visualization\n\n\n\n\nggtree - updating a tree view\n\n\nan example of drawing beast tree using ggtree\n\n\n\n\n Tree annotation\n\n\n\n\nlabel edge number in ggtree\n\n\nEdge coloring with user data\n\n\nsubview\n\n\nAnnotate a phylogenetic tree with insets\n\n\nggtree annotate phylogenetic tree with local images\n\n\nembed images in ggplot2 via subview and annotate a phylogenetic tree with images using inset function\n\n\nidentify method for ggtree\n\n\nfacet_plot: a general solution to associate data with phylogenetic tree\n\n\nalign genomic features with phylogenetic tree\n\n\nxlim_tree: set x axis limits for only Tree panel\n\n\nadd layer to specific panel of facet_plot output\n\n\n\n\n Tree manipulation\n\n\n\n\nflip and rotate branches in ggtree\n\n\n\n\n Application\n\n\n\n\nggtree for microbiome data\n\n\nggtree for outbreak data\n\n\nggtree version of plotTree\n\n\nreproducible logo generated by ggtree\n\n\n\n\n Funny stuff\n\n\n\n\nggtree with funny fonts\n\n\ncomic phylogenetic tree with ggtree and comicR\n\n\nuse emoji font in R\n\n\n\n\n User's feedback\n\n\n\n\ntweets of ggtree\n\n\nJoin the group chat on \n and \n\n\n\n\n Find out more on \nhttps://guangchuangyu.github.io/tags/ggtree/\n.\n\n\n Slides\n\n\n\n\nGenerating publication quality figures using R \n ggplot2\n\n\nggtree for visualization and annotation of phylogenetic trees\n\n\n\n\n Video\n\n\n\n\ninteractive clade highlighting\n\n\ninteractive rotating clades\n\n\ninteractive clade labeling\n\n\n\n\n Workflow\n\n\n\n\nrecreate a tree from a publication (\nBloom\n \net al\n, \nScience\n 2010)",
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+ "text": "Vignettes\n\n\n\n\nggtree\n\n\nTree Data Import\n\n\nTree Visualization\n\n\nTree Annotation\n\n\nTree Manipulation\n\n\nAdvance Tree Annotation\n\n\nggtree utilities\n\n\n\n\n Blog posts\n\n\n News and updates\n\n\n\n\nviewing and annotating phylogenetic tree with ggtree\n\n\nggtree in Bioconductor 3.1\n\n\nBioC 3.1: NEWS of my BioC packages\n\n\nBioC 3.2: NEWS of my BioC packages\n\n\nNews of ggtree\n\n\nBioC 3.3: NEWS of my BioC packages\n\n\nBioC 3.4: NEWS of my BioC packages\n\n\nggtree paper published\n\n\n\n\n Data manipulation\n\n\n\n\nsubsetting data in ggtree\n\n\nggtree supports phylip tree format\n\n\nconvert graphic object to tree object using treeio\n\n\n\n\n Tree visualization\n\n\n\n\nggtree - updating a tree view\n\n\nan example of drawing beast tree using ggtree\n\n\n\n\n Tree annotation\n\n\n\n\nlabel edge number in ggtree\n\n\nEdge coloring with user data\n\n\nsubview\n\n\nAnnotate a phylogenetic tree with insets\n\n\nggtree annotate phylogenetic tree with local images\n\n\nembed images in ggplot2 via subview and annotate a phylogenetic tree with images using inset function\n\n\nidentify method for ggtree\n\n\nfacet_plot: a general solution to associate data with phylogenetic tree\n\n\nalign genomic features with phylogenetic tree\n\n\nxlim_tree: set x axis limits for only Tree panel\n\n\nadd layer to specific panel of facet_plot output\n\n\n\n\n Tree manipulation\n\n\n\n\nflip and rotate branches in ggtree\n\n\n\n\n Application\n\n\n\n\nggtree for microbiome data\n\n\nggtree for outbreak data\n\n\nggtree version of plotTree\n\n\nreproducible logo generated by ggtree\n\n\n\n\n Funny stuff\n\n\n\n\nggtree with funny fonts\n\n\ncomic phylogenetic tree with ggtree and comicR\n\n\nuse emoji font in R\n\n\n\n\n User's feedback\n\n\n\n\ntweets of ggtree\n\n\nJoin the group chat on \n and \n\n\n\n\n Find out more on \nhttps://guangchuangyu.github.io/tags/ggtree/\n.\n\n\n Slides\n\n\n\n\nGenerating publication quality figures using R & ggplot2\n\n\nggtree for visualization and annotation of phylogenetic trees\n\n\n\n\n Video\n\n\n\n\ninteractive clade highlighting\n\n\ninteractive rotating clades\n\n\ninteractive clade labeling\n\n\n\n\n Workflow\n\n\n\n\nrecreate a tree from a publication (\nBloom\n \net al\n, \nScience\n 2010)",
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- "text": "Installation\n\n\n Could not find function\n\n\nIf you got \nthis error\n, please make sure you are using the latest R and \nggtree\n.\n\n\nPackages in Bioconductor, like \nggtree\n, have different release policy compare to CRAN. There are two branches, release and devel, in parallel. Release branch is more stable and only document improvement and bug fixes will commit to it. New functions will only commit to \ndevel\n branch.\n\n\nSometimes I may write blog post to introduce new functions which is not available in \nrelease\n branch, you need to install the \ndevel\n version of \nggtree\n in order to use these new functions.\n\n\nYou can download the \ndevel\n version of \nggtree\n from \nhttp://bioconductor.org/packages/devel/bioc/html/ggtree.html\n and install it, or install the github version of \nggtree\n.\n\n\nThis also applied to other of my packages, including \nGOSemSim\n, \nDOSE\n, \nclusterProfiler\n, \nReactomePA\n and \nChIPseeker\n. If you got the \ncould not find function\n error, upgrade your installation to latest release. If the error still exists after upgrading to latest release, you need to install the devel version.\n\n\n Text \n Label\n\n\n Tip label truncated\n\n\nggplot2 can't auto adjust xlim based on added text.\n\n\nlibrary(ggtree)\n## example tree from https://support.bioconductor.org/p/72398/\ntree\n-read.tree(text=\n(Organism1.006G249400.1:0.03977,(Organism2.022118m:0.01337,(Organism3.J34265.1:0.00284,Organism4.G02633.1:0.00468)0.51:0.0104):0.02469);\n)\nggtree(tree) + geom_tiplab()\n\n\n\n\nThis is because the units are in two different spaces (data and pixel). Users can use xlim to allocate more space for tip label.\n\n\nggtree(tree) + geom_tiplab() + xlim(0, 0.06)\n\n\n\n\n Modify (tip) labels\n\n\nThis could be easily done via the \n%\n+%\n operator to attach the\nmodified version of the labels and than use \ngeom_tiplab\n to display\nthe modified version.\n\n\nraxml_file \n- system.file(\nextdata/RAxML\n, \nRAxML_bipartitionsBranchLabels.H3\n, package=\nggtree\n)\nraxml \n- read.raxml(raxml_file)\n\nlb = get.tree(raxml)$tip.label\nd = data.frame(label=lb, label2 = paste(\nAA\n, substring(lb, 1, 5)))\nggtree(raxml) %\n+% d + geom_tiplab(aes(label=label2))\n\n\n\n\nsee also\n\n1\n\nand \n2\n.\n\n\n Formatting (tip) labels\n\n\nIf you want to format labels, you need to set \nparse=TRUE\n in \ngeom_text\n/\ngeom_tiplab\n and the \nlabel\n should be string that can be parsed into expression and displayed as described in \n?plotmath\n.\n\n\nFor example, the tiplabels contains two parts, species name and accession number and we want to display species name in \nitalic\n, we can use command like this:\n\n\nggtree(rtree(30)) + geom_tiplab(aes(subset=node==35), label='paste(italic(\nspecies name\n), \naccession number\n)', parse=T)\n\n\n\n\n Avoid overlapping text labels\n\n\nUser can use \nggrepel\n package to repel overlapping text labels.\n\n\nFor example:\n\n\nlibrary(ggrepel)\nlibrary(ggtree)\nraxml_file \n- system.file(\nextdata/RAxML\n, \nRAxML_bipartitionsBranchLabels.H3\n, package=\nggtree\n)\nraxml \n- read.raxml(raxml_file)\nggtree(raxml) + geom_label_repel(aes(label=bootstrap, fill=bootstrap))\n\n\n\n\nFor details, please refer to \nggrepel usage examples\n.\n\n\n bootstrap values from newick format\n\n\nIt's quite command to store \nbootstrap\n value as node label in \nnewick\n format. Visualizing node label is easy using \ngeom_text2(aes(subset = !isTip, label=label))\n.\n\n\nIf you want to only display a subset of \nbootstrap\n (e.g. bootstrap \n 80), you can't simply using \ngeom_text2(subset= (label \n 80), label=label)\n since \nlabel\n is a character vector, which contains node label (bootstrap value) and tip label (taxa name). If we use \ngeom_text2(subset=(as.numeric(label) \n 80), label=label)\n, it will also fail since \nNAs\n were introduced by coercion. We need to convert \nNAs\n to logical \nFALSE\n, this can be done by the following code:\n\n\nnwk \n- system.file(\nextdata/RAxML\n,\nRAxML_bipartitions.H3\n, package='ggtree')\ntr \n- read.tree(nwk)\nggtree(tr) + geom_text2(aes(label=label, subset = !is.na(as.numeric(label)) \n as.numeric(label) \n 80))\n\n\n\n\nAnother solution is converting the bootstrap value outside \nggtree\n as I recommended in \ngoogle group\n.\n\n\nq \n- ggtree(tr)\nd \n- q$data\nd \n- d[!d$isTip,]\nd$label \n- as.numeric(d$label)\nd \n- d[d$label \n 80,]\n\nq + geom_text(data=d, aes(label=label))\n\n\n\n\n \naesthetic\n mapping\n\n\n inherit \naes\n\n\nggtree(rtree(30)) + geom_point()\n\n\n\n\nFor example, we can add symbolic points to nodes with \ngeom_point()\n directly.\nThe magic here is we don't need to map \nx\n and \ny\n position of the points by providing \naes(x, y)\n to \ngeom_point()\n since it was already mapped by \nggtree\n function and it serves as a global mapping for all layers.\n\n\nBut what if we provide a \ndataset\n in a layer and the \ndataset\n doesn't contain column of \nx\n and/or \ny\n,\nthe layer function also try to map \nx\n and \ny\n and also others if you map them in \nggtree\n function.\nAs these variable is not available in your \ndataset\n, you will get the following error:\n\n\nError in eval(expr, envir, enclos) : object 'x' not found\n\n\n\n\nThis can be fixed by using parameter \ninherit.aes=FALSE\n which will disable inheriting mapping from \nggtree\n function.\n\n\n use \n$\n in aes\n\n\nNEVER DO THIS.\n\n\nsee the explaination in the \nggplot2 book 2ed\n:\n\n\n\n\nNever refer to a variable with \n$\n (e.g., \ndiamonds$carat\n) in \naes()\n. This breaks containment, so that the plot no longer contains everything it needs, and causes problems if ggplot2 changes the order of the rows, as it does when facetting.\n\n\n\n\nsee also\n\n1\n\nand \n2\n.\n\n\n Annotation\n\n\n colouring edges by user data\n\n\nsee my blog post:\n\nEdge coloring with user data\n\nand also my answer on \nhttps://github.com/GuangchuangYu/ggtree/issues/76\n\nand \nhttps://groups.google.com/forum/#!topic/bioc-ggtree/4GgivKqVjB8\n.",
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If you got the \ncould not find function\n error, upgrade your installation to latest release. If the error still exists after upgrading to latest release, you need to install the devel version.\n\n\n Text & Label\n\n\n Tip label truncated\n\n\nggplot2 can't auto adjust xlim based on added text.\n\n\nlibrary(ggtree)\n## example tree from https://support.bioconductor.org/p/72398/\ntree<-read.tree(text=\"(Organism1.006G249400.1:0.03977,(Organism2.022118m:0.01337,(Organism3.J34265.1:0.00284,Organism4.G02633.1:0.00468)0.51:0.0104):0.02469);\")\nggtree(tree) + geom_tiplab()\n\n\n\n\nThis is because the units are in two different spaces (data and pixel). Users can use xlim to allocate more space for tip label.\n\n\nggtree(tree) + geom_tiplab() + xlim(0, 0.06)\n\n\n\n\n Modify (tip) labels\n\n\nThis could be easily done via the \n%<+%\n operator to attach the\nmodified version of the labels and than use \ngeom_tiplab\n to display\nthe modified version.\n\n\nraxml_file <- system.file(\"extdata/RAxML\", \"RAxML_bipartitionsBranchLabels.H3\", package=\"ggtree\")\nraxml <- read.raxml(raxml_file)\n\nlb = get.tree(raxml)$tip.label\nd = data.frame(label=lb, label2 = paste(\"AA\", substring(lb, 1, 5)))\nggtree(raxml) %<+% d + geom_tiplab(aes(label=label2))\n\n\n\n\nsee also\n\n1\n\nand \n2\n.\n\n\n Formatting (tip) labels\n\n\nIf you want to format labels, you need to set \nparse=TRUE\n in \ngeom_text\n/\ngeom_tiplab\n and the \nlabel\n should be string that can be parsed into expression and displayed as described in \n?plotmath\n.\n\n\nFor example, the tiplabels contains two parts, species name and accession number and we want to display species name in \nitalic\n, we can use command like this:\n\n\nggtree(rtree(30)) + geom_tiplab(aes(subset=node==35), label='paste(italic(\"species name\"), \"accession number\")', parse=T)\n\n\n\n\n Avoid overlapping text labels\n\n\nUser can use \nggrepel\n package to repel overlapping text labels.\n\n\nFor example:\n\n\nlibrary(ggrepel)\nlibrary(ggtree)\nraxml_file <- system.file(\"extdata/RAxML\", \"RAxML_bipartitionsBranchLabels.H3\", package=\"ggtree\")\nraxml <- read.raxml(raxml_file)\nggtree(raxml) + geom_label_repel(aes(label=bootstrap, fill=bootstrap))\n\n\n\n\nFor details, please refer to \nggrepel usage examples\n.\n\n\n bootstrap values from newick format\n\n\nIt's quite command to store \nbootstrap\n value as node label in \nnewick\n format. Visualizing node label is easy using \ngeom_text2(aes(subset = !isTip, label=label))\n.\n\n\nIf you want to only display a subset of \nbootstrap\n (e.g. bootstrap > 80), you can't simply using \ngeom_text2(subset= (label > 80), label=label)\n since \nlabel\n is a character vector, which contains node label (bootstrap value) and tip label (taxa name). If we use \ngeom_text2(subset=(as.numeric(label) > 80), label=label)\n, it will also fail since \nNAs\n were introduced by coercion. We need to convert \nNAs\n to logical \nFALSE\n, this can be done by the following code:\n\n\nnwk <- system.file(\"extdata/RAxML\",\"RAxML_bipartitions.H3\", package='ggtree')\ntr <- read.tree(nwk)\nggtree(tr) + geom_text2(aes(label=label, subset = !is.na(as.numeric(label)) & as.numeric(label) > 80))\n\n\n\n\nAnother solution is converting the bootstrap value outside \nggtree\n as I recommended in \ngoogle group\n.\n\n\nq <- ggtree(tr)\nd <- q$data\nd <- d[!d$isTip,]\nd$label <- as.numeric(d$label)\nd <- d[d$label > 80,]\n\nq + geom_text(data=d, aes(label=label))\n\n\n\n\n \naesthetic\n mapping\n\n\n inherit \naes\n\n\nggtree(rtree(30)) + geom_point()\n\n\n\n\nFor example, we can add symbolic points to nodes with \ngeom_point()\n directly.\nThe magic here is we don't need to map \nx\n and \ny\n position of the points by providing \naes(x, y)\n to \ngeom_point()\n since it was already mapped by \nggtree\n function and it serves as a global mapping for all layers.\n\n\nBut what if we provide a \ndataset\n in a layer and the \ndataset\n doesn't contain column of \nx\n and/or \ny\n,\nthe layer function also try to map \nx\n and \ny\n and also others if you map them in \nggtree\n function.\nAs these variable is not available in your \ndataset\n, you will get the following error:\n\n\nError in eval(expr, envir, enclos) : object 'x' not found\n\n\n\n\nThis can be fixed by using parameter \ninherit.aes=FALSE\n which will disable inheriting mapping from \nggtree\n function.\n\n\n use \n$\n in aes\n\n\nNEVER DO THIS.\n\n\nsee the explaination in the \nggplot2 book 2ed\n:\n\n\n\n\nNever refer to a variable with \n$\n (e.g., \ndiamonds$carat\n) in \naes()\n. This breaks containment, so that the plot no longer contains everything it needs, and causes problems if ggplot2 changes the order of the rows, as it does when facetting.\n\n\n\n\nsee also\n\n1\n\nand \n2\n.\n\n\n Annotation\n\n\n colouring edges by user data\n\n\nsee my blog post:\n\nEdge coloring with user data\n\nand also my answer on \nhttps://github.com/GuangchuangYu/ggtree/issues/76\n\nand \nhttps://groups.google.com/forum/#!topic/bioc-ggtree/4GgivKqVjB8\n.",
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+ "text": "ggplot2 can't auto adjust xlim based on added text. library(ggtree)\n## example tree from https://support.bioconductor.org/p/72398/\ntree<-read.tree(text=\"(Organism1.006G249400.1:0.03977,(Organism2.022118m:0.01337,(Organism3.J34265.1:0.00284,Organism4.G02633.1:0.00468)0.51:0.0104):0.02469);\")\nggtree(tree) + geom_tiplab() This is because the units are in two different spaces (data and pixel). Users can use xlim to allocate more space for tip label. ggtree(tree) + geom_tiplab() + xlim(0, 0.06)",
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+ "text": "This could be easily done via the %<+% operator to attach the\nmodified version of the labels and than use geom_tiplab to display\nthe modified version. raxml_file <- system.file(\"extdata/RAxML\", \"RAxML_bipartitionsBranchLabels.H3\", package=\"ggtree\")\nraxml <- read.raxml(raxml_file)\n\nlb = get.tree(raxml)$tip.label\nd = data.frame(label=lb, label2 = paste(\"AA\", substring(lb, 1, 5)))\nggtree(raxml) %<+% d + geom_tiplab(aes(label=label2)) see also 1 \nand 2 .",
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+ "text": "User can use ggrepel package to repel overlapping text labels. For example: library(ggrepel)\nlibrary(ggtree)\nraxml_file <- system.file(\"extdata/RAxML\", \"RAxML_bipartitionsBranchLabels.H3\", package=\"ggtree\")\nraxml <- read.raxml(raxml_file)\nggtree(raxml) + geom_label_repel(aes(label=bootstrap, fill=bootstrap)) For details, please refer to ggrepel usage examples .",
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+ "text": "It's quite command to store bootstrap value as node label in newick format. Visualizing node label is easy using geom_text2(aes(subset = !isTip, label=label)) . If you want to only display a subset of bootstrap (e.g. bootstrap > 80), you can't simply using geom_text2(subset= (label > 80), label=label) since label is a character vector, which contains node label (bootstrap value) and tip label (taxa name). If we use geom_text2(subset=(as.numeric(label) > 80), label=label) , it will also fail since NAs were introduced by coercion. We need to convert NAs to logical FALSE , this can be done by the following code: nwk <- system.file(\"extdata/RAxML\",\"RAxML_bipartitions.H3\", package='ggtree')\ntr <- read.tree(nwk)\nggtree(tr) + geom_text2(aes(label=label, subset = !is.na(as.numeric(label)) & as.numeric(label) > 80)) Another solution is converting the bootstrap value outside ggtree as I recommended in google group . q <- ggtree(tr)\nd <- q$data\nd <- d[!d$isTip,]\nd$label <- as.numeric(d$label)\nd <- d[d$label > 80,]\n\nq + geom_text(data=d, aes(label=label))",
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- "text": "ggtree(rtree(30)) + geom_point() For example, we can add symbolic points to nodes with geom_point() directly.\nThe magic here is we don't need to map x and y position of the points by providing aes(x, y) to geom_point() since it was already mapped by ggtree function and it serves as a global mapping for all layers. But what if we provide a dataset in a layer and the dataset doesn't contain column of x and/or y ,\nthe layer function also try to map x and y and also others if you map them in ggtree function.\nAs these variable is not available in your dataset , you will get the following error: Error in eval(expr, envir, enclos) : object 'x' not found This can be fixed by using parameter inherit.aes=FALSE which will disable inheriting mapping from ggtree function.",
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+ "text": "ggtree(rtree(30)) + geom_point() For example, we can add symbolic points to nodes with geom_point() directly.\nThe magic here is we don't need to map x and y position of the points by providing aes(x, y) to geom_point() since it was already mapped by ggtree function and it serves as a global mapping for all layers. But what if we provide a dataset in a layer and the dataset doesn't contain column of x and/or y ,\nthe layer function also try to map x and y and also others if you map them in ggtree function.\nAs these variable is not available in your dataset , you will get the following error: Error in eval(expr, envir, enclos) : object 'x' not found This can be fixed by using parameter inherit.aes=FALSE which will disable inheriting mapping from ggtree function.",
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+ "text": "NEVER DO THIS. see the explaination in the ggplot2 book 2ed : Never refer to a variable with $ (e.g., diamonds$carat ) in aes() . This breaks containment, so that the plot no longer contains everything it needs, and causes problems if ggplot2 changes the order of the rows, as it does when facetting. see also 1 \nand 2 .",
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- "text": "see my blog post: Edge coloring with user data \nand also my answer on https://github.com/GuangchuangYu/ggtree/issues/76 \nand https://groups.google.com/forum/#!topic/bioc-ggtree/4GgivKqVjB8 .",
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+ "text": "see my blog post: Edge coloring with user data \nand also my answer on https://github.com/GuangchuangYu/ggtree/issues/76 \nand https://groups.google.com/forum/#!topic/bioc-ggtree/4GgivKqVjB8 .",
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- "text": "Let us know\n if you have published using \nggtree\n and your publication will be featured here.\n\n\n\n\n\n\n\n\n\n\n\n\n\n .rChart {\n display: block;\n margin-left: auto; \n margin-right: auto;\n width: 800px;\n height: 300px;\n } \n \n\n\n\n\n\n\n\n var chartParams = {\n \"element\": \"chart6b52366c186\",\n\"width\": 800,\n\"height\": 400,\n\"xkey\": \"year\",\n\"ykeys\": [\n \"cites\" \n],\n\"data\": [\n {\n \"year\": 2016,\n\"cites\": 1,\n\"pubid\": \"HtEfBTGE9r8C\" \n} \n],\n\"id\": \"chart6b52366c186\",\n\"labels\": \"cites\" \n},\n chartType = \"Bar\"\n new Morris[chartType](chartParams)\n\n\n\n\n 2016\n\n\nLack of GLYCOLATE OXIDASE 1, but not GLYCOLATE OXIDASE 2, attenuates the photorespiratory phenotype of CATALASE2-deficient \nArabidopsis\n\n\nPlant Physiology\n May. 2016 \n\n\n\n\nRange overlap drives chromosome inversion fixation in passerine birds\n\n\nbioRxiv\n May. 2016 \nhttp://dx.doi.org/10.1101/053371\n\n\n\n\nPhenotypic and Genotypic Characteristics of Shiga Toxin-Producing Escherichia coli Isolated from Surface Waters and Sediments in a Canadian Urban-Agricultural Landscape\n\n\nFront. Cell. Infect. Microbiol.\n Apr. 2016 \nhttp://dx.doi.org/10.3389%2Ffcimb.2016.00036\n\n\n\n\nWs-2\n Introgression in a Proportion of \nArabidopsis thaliana Col-0\n Stock Seed Produces Specific Phenotypes and Highlights the Importance of Routine Genetic Verification\n\n\nPlant Cell\n Mar. 2016 \nhttp://dx.doi.org/10.1105/tpc.16.00053\n\n\n\n\n 2015\n\n\nThe population genetics of drug resistance evolution in natural populations of viral, bacterial and eukaryotic pathogens\n\n\nMolecuar Ecology\n Dec. 2015 \nhttp://dx.doi.org/10.1111/mec.13474\n\n\n\n\nGenetic characterization of highly pathogenic H5 influenza viruses from poultry in Taiwan, 2015\n\n\nInfection, Genetics and Evolution\n Dec. 2015 \nhttp://dx.doi.org/10.1016/j.meegid.2015.12.006\n\n\n\n\nTrans-species polymorphism at antimicrobial innate immunity cathelicidin genes of Atlantic cod and related species\n\n\nPeerJ\n May 2015 \nhttps://doi.org/10.7717/peerj.976",
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+ "text": "Let us know\n if you have published using \nggtree\n and your publication will be featured here.\n\n\n\n\n\n\n\n\n\n\n\n\n\n .rChart {\n display: block;\n margin-left: auto; \n margin-right: auto;\n width: 800px;\n height: 300px;\n } \n \n\n\n\n\n\n\n\n var chartParams = {\n \"element\": \"chart7044272d6fbc\",\n\"width\": 800,\n\"height\": 400,\n\"xkey\": \"year\",\n\"ykeys\": [\n \"cites\" \n],\n\"data\": [\n {\n \"year\": 2016,\n\"cites\": 1,\n\"pubid\": \"HtEfBTGE9r8C\" \n} \n],\n\"id\": \"chart7044272d6fbc\",\n\"labels\": \"cites\" \n},\n chartType = \"Bar\"\n new Morris[chartType](chartParams)\n\n\n\n\n 2016\n\n\nLack of GLYCOLATE OXIDASE 1, but not GLYCOLATE OXIDASE 2, attenuates the photorespiratory phenotype of CATALASE2-deficient \nArabidopsis\n\n\nPlant Physiology\n May. 2016 \n\n\n\n\nRange overlap drives chromosome inversion fixation in passerine birds\n\n\nbioRxiv\n May. 2016 \nhttp://dx.doi.org/10.1101/053371\n\n\n\n\nPhenotypic and Genotypic Characteristics of Shiga Toxin-Producing Escherichia coli Isolated from Surface Waters and Sediments in a Canadian Urban-Agricultural Landscape\n\n\nFront. Cell. Infect. Microbiol.\n Apr. 2016 \nhttp://dx.doi.org/10.3389%2Ffcimb.2016.00036\n\n\n\n\nWs-2\n Introgression in a Proportion of \nArabidopsis thaliana Col-0\n Stock Seed Produces Specific Phenotypes and Highlights the Importance of Routine Genetic Verification\n\n\nPlant Cell\n Mar. 2016 \nhttp://dx.doi.org/10.1105/tpc.16.00053\n\n\n\n\n 2015\n\n\nThe population genetics of drug resistance evolution in natural populations of viral, bacterial and eukaryotic pathogens\n\n\nMolecuar Ecology\n Dec. 2015 \nhttp://dx.doi.org/10.1111/mec.13474\n\n\n\n\nGenetic characterization of highly pathogenic H5 influenza viruses from poultry in Taiwan, 2015\n\n\nInfection, Genetics and Evolution\n Dec. 2015 \nhttp://dx.doi.org/10.1016/j.meegid.2015.12.006\n\n\n\n\nTrans-species polymorphism at antimicrobial innate immunity cathelicidin genes of Atlantic cod and related species\n\n\nPeerJ\n May 2015 \nhttps://doi.org/10.7717/peerj.976",
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- "text": "Lack of GLYCOLATE OXIDASE 1, but not GLYCOLATE OXIDASE 2, attenuates the photorespiratory phenotype of CATALASE2-deficient Arabidopsis Plant Physiology May. 2016 Range overlap drives chromosome inversion fixation in passerine birds bioRxiv May. 2016 http://dx.doi.org/10.1101/053371 Phenotypic and Genotypic Characteristics of Shiga Toxin-Producing Escherichia coli Isolated from Surface Waters and Sediments in a Canadian Urban-Agricultural Landscape Front. Cell. Infect. Microbiol. Apr. 2016 http://dx.doi.org/10.3389%2Ffcimb.2016.00036 Ws-2 Introgression in a Proportion of Arabidopsis thaliana Col-0 Stock Seed Produces Specific Phenotypes and Highlights the Importance of Routine Genetic Verification Plant Cell Mar. 2016 http://dx.doi.org/10.1105/tpc.16.00053",
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+ "text": "Lack of GLYCOLATE OXIDASE 1, but not GLYCOLATE OXIDASE 2, attenuates the photorespiratory phenotype of CATALASE2-deficient Arabidopsis Plant Physiology May. 2016 Range overlap drives chromosome inversion fixation in passerine birds bioRxiv May. 2016 http://dx.doi.org/10.1101/053371 Phenotypic and Genotypic Characteristics of Shiga Toxin-Producing Escherichia coli Isolated from Surface Waters and Sediments in a Canadian Urban-Agricultural Landscape Front. Cell. Infect. Microbiol. Apr. 2016 http://dx.doi.org/10.3389%2Ffcimb.2016.00036 Ws-2 Introgression in a Proportion of Arabidopsis thaliana Col-0 Stock Seed Produces Specific Phenotypes and Highlights the Importance of Routine Genetic Verification Plant Cell Mar. 2016 http://dx.doi.org/10.1105/tpc.16.00053",
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- "text": "The population genetics of drug resistance evolution in natural populations of viral, bacterial and eukaryotic pathogens Molecuar Ecology Dec. 2015 http://dx.doi.org/10.1111/mec.13474 Genetic characterization of highly pathogenic H5 influenza viruses from poultry in Taiwan, 2015 Infection, Genetics and Evolution Dec. 2015 http://dx.doi.org/10.1016/j.meegid.2015.12.006 Trans-species polymorphism at antimicrobial innate immunity cathelicidin genes of Atlantic cod and related species PeerJ May 2015 https://doi.org/10.7717/peerj.976",
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+ "text": "The population genetics of drug resistance evolution in natural populations of viral, bacterial and eukaryotic pathogens Molecuar Ecology Dec. 2015 http://dx.doi.org/10.1111/mec.13474 Genetic characterization of highly pathogenic H5 influenza viruses from poultry in Taiwan, 2015 Infection, Genetics and Evolution Dec. 2015 http://dx.doi.org/10.1016/j.meegid.2015.12.006 Trans-species polymorphism at antimicrobial innate immunity cathelicidin genes of Atlantic cod and related species PeerJ May 2015 https://doi.org/10.7717/peerj.976",
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256
|
256
|
"title": "meshes"
|
|
257
|
|
- },
|
|
|
257
|
+ },
|
|
258
|
258
|
{
|
|
259
|
|
- "location": "/ReactomePA/",
|
|
260
|
|
- "text": "",
|
|
|
259
|
+ "location": "/ReactomePA/",
|
|
|
260
|
+ "text": "",
|
|
261
|
261
|
"title": "ReactomePA"
|
|
262
|
|
- },
|
|
|
262
|
+ },
|
|
263
|
263
|
{
|
|
264
|
|
- "location": "/treeio/",
|
|
265
|
|
- "text": "",
|
|
|
264
|
+ "location": "/treeio/",
|
|
|
265
|
+ "text": "",
|
|
266
|
266
|
"title": "treeio"
|
|
267
|
267
|
}
|
|
268
|
268
|
]
|
GuangchuangYu authored on 20/01/2017 05:21:52