### R Package Setup

Source: https://rdrr.io/bioc/ggtreeExtra/f/vignettes/ggtreeExtra.Rmd

Loads necessary R packages for tree visualization and extensions. Ensure these packages are installed before running.

```r
library(ggtreeExtra)
library(ggstar)
library(ggplot2)
library(ggtree)
library(treeio)
library(ggnewscale)
```

--------------------------------

### Load and Use ggtree

Source: https://rdrr.io/bioc/ggtree

Load the ggtree library after installation to start using its functions for tree visualization. Use help() to access documentation.

```R
library(ggtree)
help(ggtree)
```

--------------------------------

### Install ggtree Package

Source: https://rdrr.io/bioc/ggtree

Install the ggtree package using BiocManager. Ensure BiocManager is installed first if you haven't already.

```R
if (!requireNamespace("BiocManager", quietly = TRUE))
    install.packages("BiocManager")

BiocManager::install("ggtree")
```

--------------------------------

### Install ggtreeExtra

Source: https://rdrr.io/bioc/ggtreeExtra/f/inst/doc/ggtreeExtra.Rmd

Install the ggtreeExtra package from GitHub for development or from BiocManager for the release version. Ensure 'remotes' and 'BiocManager' are installed if needed.

```R
# for devel
if(!requireNamespace("remotes", quietly=TRUE)){
    install.packages("remotes")
}
remotes::install_github("YuLab-SMU/ggtreeExtra")

# for release
if (!requireNamespace("BiocManager", quietly=TRUE))
    install.packages("BiocManager")

## BiocManager::install("ggtreeExtra")

```

--------------------------------

### Install ggtreeExtra Package

Source: https://rdrr.io/bioc/ggtreeExtra/f/vignettes/ggtreeExtra.Rmd

Instructions for installing the ggtreeExtra package from GitHub (development version) or CRAN (release version). Includes necessary checks for remotes and BiocManager.

```R
# for devel
if(!requireNamespace("remotes", quietly=TRUE)){
    install.packages("remotes")
}
remotes::install_github("YuLab-SMU/ggtreeExtra")

# for release
if (!requireNamespace("BiocManager", quietly=TRUE))
    install.packages("BiocManager")

## BiocManager::install("ggtreeExtra")


```

--------------------------------

### Install ggtreeExtra Package

Source: https://rdrr.io/bioc/ggtreeExtra

Install the latest version of the ggtreeExtra package using BiocManager. Ensure BiocManager is installed first if you haven't already.

```r
if (!requireNamespace("BiocManager", quietly = TRUE))
    install.packages("BiocManager")

BiocManager::install("ggtreeExtra")
```

--------------------------------

### Example: Display root edge with default settings

Source: https://rdrr.io/bioc/ggtree/src/R/geom_rootedge.R

Demonstrates how to display the root edge of a phylogenetic tree using geom_rootedge with default settings. This example assumes the tree object has a root.edge defined.

```R
library(ggtree)
set.seed(123)
## with root edge = 1
tree1 <- read.tree(text='((A:1,B:2):3,C:2):1;'
ggtree(tree1) + geom_tiplab() + geom_rootedge()
```

--------------------------------

### Install ggtreeExtra

Source: https://rdrr.io/bioc/ggtreeExtra/src/inst/doc/ggtreeExtra.R

Instructions for installing the ggtreeExtra package from GitHub (development version) or Bioconductor (release version).

```R
# for devel
if(!requireNamespace("remotes", quietly=TRUE)){
    install.packages("remotes")
}
remotes::install_github("YuLab-SMU/ggtreeExtra")

# for release
if (!requireNamespace("BiocManager", quietly=TRUE))
    install.packages("BiocManager")

## BiocManager::install("ggtreeExtra")
```

--------------------------------

### Setup Data for Continuous Color

Source: https://rdrr.io/bioc/ggtree/src/R/geom_tree.R

Prepares data for continuous color mapping in tree visualizations. Handles interpolation for smooth color gradients.

```R
setup_data_continuous_color <- function(x, xend, y, yend, col, col2,
                                        xrange = NULL, nsplit = 100, extend = 0.002) {
    if (is.null(xrange))
        xrange <- c(x, xend)

    ## xstep <- diff(xrange)/nsplit
    ## xn <- floor((xend - x)/xstep)
    xn <- floor((xend - x) * nsplit /diff(xrange))
    ## slope <- (yend - y)/(xend - x)
    ydiff <- yend - y
    xdiff <- xend - x

    if (xn > 0) {
        ## x <- x + 0:xn * xstep
        x <- x + 0:xn * diff(xrange) / nsplit 
        tmp <- x[-1] * (1 + extend)
        tmp[tmp > xend] <- xend
        xend <- c(tmp, xend)
        ## y <- y + 0:xn * xstep * slope
        y <- y + 0:xn * diff(xrange) * ydiff / (nsplit * xdiff)
        ## yend <- y + (xend - x) * slope
        yend <- y + (xend - x) * ydiff / xdiff 
    }

    n <- length(x)
    if (is.numeric(col) && is.numeric(col2)) {
        colour <- seq(col, col2, length.out = n)
    } else if (is.character(col) && is.character(col2)) {
        colour <- grDevices::colorRampPalette(c(col, col2))(n)
    } else {
        stop("col and col2 should be both numeric or character..." )
    }

    data.frame(x = x,
               xend = xend,
               y = y,
               yend = yend,
               colour = colour)
}
```

--------------------------------

### Example Usage of fortify.phyloseq

Source: https://rdrr.io/bioc/ggtree/src/R/method-fortify.R

Demonstrates how to call the fortify method for a phyloseq object. This is typically used within an R environment to prepare data for ggtree plotting.

```R
library(ggtree) help(fortify.phyloseq)
```

--------------------------------

### Load ggtree package and view help

Source: https://rdrr.io/bioc/ggtree/f/vignettes/ggtree.Rmd

Loads the ggtree package into the R session and displays its help documentation. This is a common first step when starting to use the package.

```r
library(ggtree) help(ggtree)

```

--------------------------------

### Load and Get Help for ggtreeExtra in R

Source: https://rdrr.io/bioc/ggtreeExtra/src/R/reexports.R

Loads the ggtreeExtra library and displays its help documentation. This is useful for understanding the package's functions and usage.

```r
library(ggtreeExtra) help(ggtreeExtra)

```

--------------------------------

### Example Usage of check_reverse

Source: https://rdrr.io/bioc/ggtreeExtra/src/R/method-ggplot-add.R

Demonstrates how to load the ggtreeExtra package and access the help documentation for the 'check_reverse' function. This is a standard way to explore R package functions.

```R
library(ggtreeExtra) help(check_reverse)
```

--------------------------------

### Example Usage of get_clade_position_

Source: https://rdrr.io/bioc/ggtree/src/R/geom_hilight.R

Demonstrates how to use the `get_clade_position_` function, which is likely an internal helper function for `StatHilight` to determine clade positions. This example is typically run interactively.

```R
library(ggtree) help(get_clade_position_)
```

--------------------------------

### Load ggtreeExtra Package

Source: https://rdrr.io/bioc/ggtreeExtra/f/NEWS.md

Loads the ggtreeExtra package and displays its help documentation. This is a common starting point for exploring the package's functionality.

```r
library(ggtreeExtra) help(ggtreeExtra)
```

--------------------------------

### Plotting Trees Colored by OTU Group

Source: https://rdrr.io/bioc/ggtree/src/R/ggdensitree.R

Reads example tree data, computes OTU groups, and plots multiple trees colored by these groups with specified alpha transparency. This example uses `groupOTU` to define groups and `scale_colour_manual` to set custom colors.

```R
# Read example data
trees <- read.tree(system.file("examples", "ggdensitree_example.tree", package="ggtree"))

# Compute OTU
gr <- list(A = c("a.t1", "a.t2", "a.t3", "a.t4"), B = c("b.t1", "b.t2", "b.t3", "b.t4"), C = c("c.t1", "c.t2", "c.t3", "c.t4"))
trees <- lapply(trees, groupOTU, gr)

# Plot multiple trees colored by OTU
ggdensitree(trees, aes(colour=group), alpha=1/6) + scale_colour_manual(values=c("black", "red", "green", "blue"))
```

--------------------------------

### Converting Tree Formats

Source: https://rdrr.io/bioc/ggtree/f

Provides examples of converting tree objects between different formats, such as from Newick to a format compatible with ggtree.

```R
library(ggtree)
newick_string <- "(t1:1,t2:1,(t3:1,t4:1):1);"
tree <- read.tree(text=newick_string)
ggtree(tree)
```

--------------------------------

### Plotting Time-Aligned Trees with Tip Labels

Source: https://rdrr.io/bioc/ggtree/man/ggdensitree.html

Visualizes multiple time-calibrated trees with aligned tips and tip labels, using a specified tip order. Generates example time-calibrated trees.

```R
# Generate example data
set.seed(1)
trees <- rmtree(5, 10)
time.trees <- lapply(1:length(trees), function(i) {
 	tree <- trees[[i]]
 	tree$tip.label <- paste0("t", 1:10)
	dates <- estimate.dates(tree, 1:10, mu=1, nsteps=1)
	tree$edge.length <- dates[tree$edge[, 2]] - dates[tree$edge[, 1]]
	fortify(tree) %>% mutate(tree=factor(i, levels=as.character(1:10)))
})

# Plot multiple trees with aligned tips from muliple time points
ggdensitree(time.trees, aes(colour=tree), tip.order=paste0("t", 1:10)) + geom_tiplab(colour='black')
```

--------------------------------

### Highlighting a Specific Node

Source: https://rdrr.io/bioc/ggtree/man/geom-hilight.html

This example demonstrates how to highlight a single node (node=62) with the default fill color and then highlight another node (node=88) with a specified fill color ('red').

```R
library(ggplot2)
set.seed(102)
tree <- rtree(60)
p <- ggtree(tree)
p1 <- p + geom_hilight(node=62) + geom_hilight(node=88, fill="red")
p1
```

--------------------------------

### ggtree Package Setup

Source: https://rdrr.io/bioc/ggtree/src/inst/doc/ggtree.R

Sets up knitr options for tidy and message output. Defines helper functions for creating CRAN and Bioconductor package links.

```R
knitr::opts_chunk$set(tidy = FALSE,
		   message = FALSE)

CRANpkg <- function (pkg) {
    cran <- "https://CRAN.R-project.org/package"
    fmt <- "[%s](%s=%s)"
    sprintf(fmt, pkg, cran, pkg)
}

Biocpkg <- function (pkg) {
    sprintf("[%s](http://bioconductor.org/packages/%s)", pkg, pkg)
}
```

--------------------------------

### Box Plot Dodging with position_dodgex2

Source: https://rdrr.io/bioc/ggtreeExtra/man/position_dodgex.html

Demonstrates using `position_dodgex2` with box plots. This example shows basic dodging and dodging with vertical and horizontal expansion.

```R
library(ggplot2)
library(patchwork)
iris$ID <- rep(c(rep("test1", 15), rep("test2", 15), rep("test3", 20)),3)
p <- ggplot(iris, aes(x=Species,y=Petal.Length,fill=ID))
p5 <- p + geom_boxplot(position=position_dodgex2())
p6 <- p + geom_boxplot(position=position_dodgex2(vexpand=5))
p7 <- ggplot(iris, aes(x=Petal.Length, y=Species, fill=ID)) +
      geom_boxplot(orientation="y",
                   position=position_dodgex2(hexpand=5))
p8 <- p5 + p6 + p7
p8
```

--------------------------------

### Setup Data for Continuous Color Tree

Source: https://rdrr.io/bioc/ggtree/src/R/geom_tree.R

Applies setup_data_continuous_color to a data frame for tree visualization, processing each row to generate interpolated data for coloring branches.

```R
setup_data_continuous_color_tree <- function(df, nsplit = 100, extend = 0.002) {
    lapply(1:nrow(df), function(i) {
        df2 <- setup_data_continuous_color(x = df$x[i],
                                           xend = df$xend[i],
                                           y = df$y[i],
                                           yend = df$yend[i],
                                           col = df$col[i],
                                           col2 = df$col2[i],
                                           xrange = range(df$x),
                                           nsplit = nsplit,
                                           extend = extend)
        df2$node <- df$node[i]
        
        j <- match(c('x', 'xend', 'y', 'yend', 'col', 'col2', 'colour'), colnames(df))
        merge(df[i, -j, drop = FALSE], df2, by = "node")
    }) %>% do.call('rbind', .)
}
```

--------------------------------

### Helper function for tree data setup

Source: https://rdrr.io/bioc/ggtree/src/R/geom_tree.R

Ensures that the tree data is in the correct format for processing by tree geoms. It handles cases where the input data might not be ordered by node.

```R
setup_tree_data <- function(data) {
    if (nrow(data) == length(unique(data$node)))
        return(data)

    data[match(unique(data$node), data$node),]
    ## data[order(data$node, decreasing = FALSE), ]
}

```

--------------------------------

### Get Subtree Unrooted Example

Source: https://rdrr.io/bioc/ggtree/man/getSubtreeUnrooted.df.html

Demonstrates how to use the getSubtreeUnrooted.df function to extract subtrees from a tree data frame. This function returns a named list of subtrees, where each list name corresponds to the starting node ID of the subtree.

```r
getSubtreeUnrooted.df(df, node)
```

--------------------------------

### Get Subtree from Data Frame Tree

Source: https://rdrr.io/bioc/ggtree/man/getSubtree.df.html

Use this function to get all child node IDs from a specified starting node in a tree represented as a data frame. The search is performed using a breadth-first traversal.

```R
getSubtree.df(df, node)
```

--------------------------------

### Loading ggtreeExtra and accessing help

Source: https://rdrr.io/bioc/ggtreeExtra/src/R/position_points_jitterx.R

Demonstrates how to load the ggtreeExtra library and access the help documentation for the position_raincloudx function.

```R
library(ggtreeExtra) help(position_raincloudx)
```

--------------------------------

### layoutDaylight Algorithm Steps

Source: https://rdrr.io/bioc/ggtree/man/layoutDaylight.html

Outlines the initial steps of the Equal-daylight Algorithm for tree layout, including leaf identification and initialization using the equal angle algorithm.

```R
Leafs are subtrees with no children
Initialise tree using equal angle algorithm
tree_df = equal_angle(tree)

nodes = get list of nodes in tree_df breadth-first
nodes = remove tip nodes.
```

--------------------------------

### Get Subtree Nodes

Source: https://rdrr.io/bioc/ggtree/man/getSubtree.html

Use this function to get all child node IDs from a specified starting node in an ape phylo tree object. Ensure the node ID provided is valid within the tree structure.

```R
getSubtree(tree, node)
```

--------------------------------

### Visualize tree with annotation data and labels

Source: https://rdrr.io/bioc/ggtree/man/attacher.html

This example demonstrates reading a tree, creating annotation data, and then plotting the tree with annotations. It uses `ggtree` to initialize the plot, `%<+%` to add data, and `geom_text` to display labels colored by a categorical variable. Missing values in the annotation data will be removed.

```r
nwk <- system.file("extdata", "sample.nwk", package="treeio")
tree <- read.tree(nwk)
p <- ggtree(tree)
dd <- data.frame(taxa=LETTERS[1:13],
   		 place=c(rep("GZ", 5), rep("HK", 3), rep("CZ", 4), NA),
             value=round(abs(rnorm(13, mean=70, sd=10)), digits=1))
row.names(dd) <- NULL
p %<+% dd + geom_text(aes(color=place, label=label), hjust=-0.5)
```

--------------------------------

### R: Loading and accessing help for as.polytomy

Source: https://rdrr.io/bioc/ggtree/src/R/as.polytomy.R

Demonstrates how to load the ggtree library and access the help documentation for the as.polytomy function in R.

```R
library(ggtree)
help(as.polytomy)
```

--------------------------------

### Get Subtree from Data Frame

Source: https://rdrr.io/bioc/ggtree/src/R/tree-utilities.R

Extracts all child nodes from a tree represented as a data frame, starting from a given node. Uses tidytree's offspring function for data frames.

```R
getSubtree.df <- function(df, node){
    offspring.tbl_tree(df, node, self_include = TRUE)$node
}
```

--------------------------------

### Get Subtree from Ape Phylo Object

Source: https://rdrr.io/bioc/ggtree/src/R/tree-utilities.R

Retrieves all child nodes of a specified node from an ape phylo tree object, including the starting node itself. Uses tidytree's offspring function.

```R
getSubtree <- function(tree, node){
    tidytree::offspring(tree, node, self_include = TRUE)
}
```

--------------------------------

### Get Taxa Names from a Tree

Source: https://rdrr.io/bioc/ggtree/man/get_taxa_name.html

This snippet demonstrates how to use the get_taxa_name function with a ggtree object to retrieve an ordered list of taxa names from the entire tree. Ensure the ggtree package is installed and loaded.

```R
library(ggtree)
tree <- rtree(30)
p <- ggtree(tree)
get_taxa_name(p)
```

--------------------------------

### Plotting Trees with Aesthetic Mapping and Tip Labels

Source: https://rdrr.io/bioc/ggtree/src/R/ggdensitree.R

Shows how to plot multiple trees with aligned tips, where the color of the trees is mapped to a variable. This example fortifies the trees first, adds a 'tree' identifier, and then plots them with aesthetic mapping for color and black tip labels.

```R
trees.fort <- list(trees[[1]] %>% fortify %>% mutate(tree="a"), trees[[2]] %>% fortify %>% mutate(tree="b"));
ggdensitree(trees.fort, aes(colour=tree)) + geom_tiplab(colour='black')
```

--------------------------------

### Get Nodes in Breadth-First Order

Source: https://rdrr.io/bioc/ggtree/src/R/tree-utilities.R

Traverses a tree structure (as a data frame) starting from the root and returns a list of node IDs in breadth-first order. Skips tip nodes during traversal. Requires 'tidytree' and 'treeio'.

```R
getNodesBreadthFirst.df <- function(df){

  root <- getRoot.df(df)
  if(treeio::isTip(df, root)){
    return(root)
  }

  tree_size <- nrow(df)
  # initialise list of nodes
  res <- root

  i <- 1
  while(length(res) < tree_size){
    parent <- res[i]
    i <- i + 1

    # Skip if parent is a tip.
    if(treeio::isTip(df, parent)){
      next
    }

    # get children of current parent.
    children <- tidytree::child(df,parent)$node

    # add children to result
    res <- c(res, children)

  }

  return(res)

}
```

--------------------------------

### Load ggtreeExtra and Access Help

Source: https://rdrr.io/bioc/ggtreeExtra/src/R/position_dodgex.r

Loads the ggtreeExtra library and displays the help documentation for the get_outliers function.

```R
library(ggtreeExtra) help(get_outliers)
```

--------------------------------

### Get Nodes in Breadth-First Order using ggtree

Source: https://rdrr.io/bioc/ggtree/man/getNodesBreadthFirst.df.html

Use this function to get a list of node IDs from a tree data frame in breadth-first order. Ensure the input is a valid tree data frame.

```R
getNodesBreadthFirst.df(df)
```

--------------------------------

### Access ggtree Help

Source: https://rdrr.io/bioc/ggtree/src/tests/testthat.R

Load the ggtree library and access its help documentation. This is useful for understanding the package's functions and usage.

```r
library(ggtree)
help(ggtree)

```

--------------------------------

### Load ggtree and Access groupOTU Help

Source: https://rdrr.io/bioc/ggtree/src/R/method-groupOTU.R

This R code loads the ggtree library and then accesses the help documentation for the groupOTU.ggtree method. This is useful for understanding how to use the function.

```R
library(ggtree)
help(groupOTU.ggtree)
```

--------------------------------

### Example usage of facet_plot

Source: https://rdrr.io/bioc/ggtree/src/R/facet_plot.R

This example demonstrates how to use facet_plot to visualize trait data on a phylogenetic tree. It first creates a tree, then a data frame with tip labels and associated values, and finally plots the tree with the data using geom_point on a 'Trait' panel.

```R
tr <- rtree(10)
dd = data.frame(id=tr$tip.label, value=abs(rnorm(10)))
p <- ggtree(tr)
facet_plot(p, 'Trait', data = dd, geom=geom_point, mapping=aes(x=value))
```

--------------------------------

### getSubtree

Source: https://rdrr.io/bioc/ggtree/man/getSubtree.html

Retrieves all child nodes of a specified node in a tree, including the starting node itself.

```APIDOC
## getSubtree

### Description
Get all children of node from tree, including start_node.

### Usage
```
getSubtree(tree, node)
```

### Arguments
#### Path Parameters
- **tree** (ape phylo tree object) - The tree object to extract nodes from.
- **node** (numeric) - The tree node id from which the tree is derived.

### Value
list of all child node id's from starting node.
```

--------------------------------

### Basic tip label addition with ggtree

Source: https://rdrr.io/bioc/ggtree/man/geom_tiplab.html

This example demonstrates how to add tip labels to a phylogenetic tree using the geom_tiplab function after creating a basic tree visualization with ggtree. Ensure the 'ape' and 'ggtree' packages are loaded.

```R
require(ape)
tr <- rtree(10)
ggtree(tr) + geom_tiplab()
```

--------------------------------

### decimal2Date

Source: https://rdrr.io/bioc/ggtree/man/decimal2Date.html

Converts a numerical representation of a date into a Date object. For example, it transforms '2014.34' into '2014-05-05'.

```APIDOC
## decimal2Date

### Description
Converts a numerical representation of a date into a Date object. For example, it transforms '2014.34' into '2014-05-05'.

### Arguments
* `x` (numerical number) - Required - The numerical number representing the date, e.g., 2014.34.

### Value
Returns a Date object.

### Author(s)
Guangchuang Yu
```

--------------------------------

### get.path Function

Source: https://rdrr.io/bioc/ggtree/man/get.path.html

Calculates the path from a start node to an end node in a phylogenetic tree object.

```APIDOC
## get.path(phylo, from, to)

### Description
Calculates the path from a start node to an end node in a phylogenetic tree.

### Parameters
#### Path Parameters
- **phylo** (phylo object) - Required - The phylogenetic tree object.
- **from** (node) - Required - The starting node.
- **to** (node) - Required - The ending node.

### Returns
- node vector: A vector representing the path from the start node to the end node.
```

--------------------------------

### Get Node Euclidean Distances

Source: https://rdrr.io/bioc/ggtree/src/R/tree-utilities.R

Calculates the Euclidean distances from a specified node to all other nodes in a tree data frame.

```R
getNodeEuclDistances <- function(df, node){
  # https://stackoverflow.com/questions/24746892/how-to-calculate-euclidian-distance-between-two-points-defined-by-matrix-contain#24747155
  dist <- NULL
  for(i in 1:nrow(df)) dist[i] <- euc.dist(df[df$node==node, c('x', 'y')], df[i, c('x', 'y')])
  return(dist)
}
```

--------------------------------

### ggtreeExtra Package Startup Message

Source: https://rdrr.io/bioc/ggtreeExtra/src/R/zzz.R

This function is called when the ggtreeExtra package is loaded. It displays the package version and citation information.

```R
#' @importFrom utils packageDescription
.onAttach <- function(libname, pkgname) {
    pkgVersion <- packageDescription(pkgname, fields="Version")
    msg <- paste0(pkgname, " v", pkgVersion, "  ",
                  "For help: https://yulab-smu.top/treedata-book/", "\n\n")

    citation <- paste0("If you use ", pkgname,
                       " in published research, please cite the paper:\n\n",
                       ggtreeExtra_citations(), "\n")

    packageStartupMessage(paste0(msg, citation))
}
```

--------------------------------

### ggtree Help Documentation

Source: https://rdrr.io/bioc/ggtree/src/R/ggplot-add-utilities.R

This is a command to access the help documentation for the build_text_layer function within the ggtree package.

```R
library(ggtree) help(build_text_layer)
```

--------------------------------

### Get Trunk Path

Source: https://rdrr.io/bioc/ggtree/src/R/tree-utilities.R

Finds the path from the root to the node furthest from the root in a phylogenetic tree. Requires 'treeio' for tree manipulation.

```R
get.trunk <- function(tr) {
    root <- getRoot(tr)
    path_length <- sapply(1:(root-1), function(x) get.path_length(tr, root, x))
    i <- which.max(path_length)
    return(get.path(tr, root, i))
}
```

--------------------------------

### Create Fan Layout Tree with ggtree

Source: https://rdrr.io/bioc/ggtreeExtra/f/vignettes/ggtreeExtra.Rmd

Initializes a phylogenetic tree with a fan layout using ggtree. Sets the open angle and line size. Displays the basic tree structure.

```R
# We use ggtree to create fan layout tree. 
p <- ggtree(tree, layout="fan", open.angle=10, size=0.5)
p

```

--------------------------------

### Get Color Attribute from Plot Data

Source: https://rdrr.io/bioc/ggtree/src/R/utilities.R

Extracts the 'color' column from the data of a plot object. Assumes 'color' is a column in the data.

```R
get_color_attribute <- function(p) {
    p$data[, "color"]
}
```

--------------------------------

### Basic ggtree plot with theme_tree2

Source: https://rdrr.io/bioc/ggtree/man/theme_tree2.html

Demonstrates creating a basic phylogenetic tree plot using ggtree and applying the theme_tree2. Requires the ape and ggtree packages.

```R
require(ape)
tr <- rtree(10)
ggtree(tr) + theme_tree2()
```

--------------------------------

### Get Tree View from Plot

Source: https://rdrr.io/bioc/ggtree/src/R/utilities.R

Retrieves the current tree view from the plot environment. Use when the tree view is not explicitly passed.

```R
get_tree_view <- function(tree_view) {
    if (is.null(tree_view))
        tree_view <- last_plot()

    return(tree_view)
}
```

--------------------------------

### Get ggname from ggplot2 Namespace

Source: https://rdrr.io/bioc/ggtree/src/R/geom_taxalink.R

Imports the ggname function from the ggplot2 package's namespace, used for naming graphical objects.

```R
ggname <- getFromNamespace("ggname", "ggplot2")
```

--------------------------------

### Highlighting Nodes with Data Mapping

Source: https://rdrr.io/bioc/ggtree/man/geom-hilight.html

This example shows how to highlight nodes based on a data frame. The 'fill' aesthetic is mapped to the 'type' column in the 'dat' data frame, allowing for different fill colors for different types of highlighted clades.

```R
dat <- data.frame(id=c(62, 88), type=c("A", "B"))
p2 <- p + geom_hilight(data=dat, mapping=aes(node=id, fill=type))
p2
```

--------------------------------

### Basic Usage of position_identityx

Source: https://rdrr.io/bioc/ggtreeExtra/man/position_identityx.html

Demonstrates the default usage of position_identityx without any expansion, maintaining the original position.

```R
library(ggplot2)
library(patchwork)
p <- ggplot(mtcars, aes(x=wt, y=mpg))
p1 <- p + geom_point(position=position_identityx()) + ylim(0, 50)
```

--------------------------------

### Extracting tidytree Namespace Functions

Source: https://rdrr.io/bioc/ggtree/src/R/tidytree.R

These lines extract specific utility functions from the tidytree package namespace. Ensure the tidytree package is installed.

```R
nodeid.tbl_tree <- utils::getFromNamespace("nodeid.tbl_tree", "tidytree")
rootnode.tbl_tree <- utils::getFromNamespace("rootnode.tbl_tree", "tidytree")
offspring.tbl_tree <- utils::getFromNamespace("offspring.tbl_tree", "tidytree")
child.tbl_tree <- utils::getFromNamespace("child.tbl_tree", "tidytree")
parent.tbl_tree <- utils::getFromNamespace("parent.tbl_tree", "tidytree")
```

--------------------------------

### Combining Boxplot Dodging Examples

Source: https://rdrr.io/bioc/ggtreeExtra/src/R/position_dodgex.r

Combines multiple plots featuring dodged boxplots with different `position_dodgex2` configurations using `patchwork` for comparison.

```R
p8 <- p5 + p6 + p7
p8
```

--------------------------------

### Plotting Multiple Trees with Aligned Tips

Source: https://rdrr.io/bioc/ggtree/man/ggdensitree.html

Demonstrates plotting multiple trees from a list of phylo objects with aligned tips and tip labels. Requires 'ape' and 'dplyr' packages.

```R
require(ape)
require(dplyr)

# Plot mutliple trees with aligned tips
trees <- list(read.tree(text="((a:1,b:1):1.5,c:2.5);"), read.tree(text="((a:1,c:1):1,b:2);"));
ggdensitree(trees) + geom_tiplab()
```

--------------------------------

### Bar Plot Dodging with position_dodgex

Source: https://rdrr.io/bioc/ggtreeExtra/man/position_dodgex.html

Demonstrates using `position_dodgex` with bar plots. This example shows basic dodging and dodging with vertical expansion.

```R
library(ggplot2)
library(patchwork)
iris$ID <- rep(c(rep("test1", 15), rep("test2", 15), rep("test3", 20)),3)
p <- ggplot(iris, aes(x=Species,y=Petal.Length,fill=ID))
p1 <- p + geom_bar(stat="identity",position=position_dodgex())
p2 <- p + geom_bar(stat="identity",position=position_dodgex(vexpand=5))
p3 <- ggplot(iris, aes(x=Petal.Length, y=Species, fill=ID)) +
      geom_bar(stat="identity", orientation="y",
               position=position_dodgex(hexpand=5))
p4 <- p1 + p2 + p3
p4
```

--------------------------------

### Adding Pie Charts to Nodes with nodepie

Source: https://rdrr.io/bioc/ggtree/f

Demonstrates how to add pie charts to tree nodes using `nodepie` to represent proportions or frequencies associated with each node.

```R
library(ggtree)
library(ape)
tree <- rtree(5)
data <- data.frame(node=c(1, 3, 5), A=c(10, 20, 30), B=c(5, 10, 15))
ggtree(tree) + nodepie(data, cols=c("A", "B"))
```

--------------------------------

### Rectangular Tree Layout

Source: https://rdrr.io/bioc/ggtree/man/tree-layout.html

Use layout_rectangular() for a standard rectangular tree visualization. No specific setup is required beyond loading the ggtree package.

```R
layout_rectangular()
```