R: Calculate relative evolutionary divergences in a tree.

get_reds {castor} | R Documentation

## Calculate relative evolutionary divergences in a tree.

### Description

Calculate the relative evolutionary divergence (RED) of each node in a rooted phylogenetic tree. The RED of a node is a measure of its relative placement between the root and the node's descending tips (Parks et al. 2018). The root's RED is always 0, the RED of each tip is 1, and the RED of each node is between 0 and 1.

### Usage

    get_reds(tree)

### Arguments

`tree` | A rooted tree of class "phylo". The root is assumed to be the unique node with no incoming edge.

### Details

The RED of a node measures its relative placement between the root and the node's descending tips (Parks et al. 2018). The root's RED is set to 0. Traversing from root to tips (preorder traversal), for each node the RED is set to P+(a/(a+b))\cdot(1-P), where P is the RED of the node's parent, a is the edge length connecting the node to its parent, and b is the average distance from the node to its descending tips. The RED of a tip would always be 1.

The RED may be useful for defining taxonomic ranks based on a molecular phylogeny (e.g. see Parks et al. 2018). This function is similar to the PhyloRank v0.0.27 script published by Parks et al. (2018).

The time complexity of this function is O(Nedges). The input tree may include multi-furcations (i.e. nodes with more than 2 children) as well as mono-furcations (i.e. nodes with only one child). If `tree$edge.length` is `NULL`, then all edges in the input tree are assumed to have length 1.

### Value

A numeric vector of length Nnodes, listing the RED of each node in the tree. The REDs of tips are not included, since these would always be equal to 1.

### Author(s)

Stilianos Louca

### References

D. H. Parks, M. Chuvochina et al. (2018). A proposal for a standardized bacterial taxonomy based on genome phylogeny. bioRxiv 256800. DOI:10.1101/256800

### Examples

    # generate a random tree
    params = list(birth_rate_intercept=1, death_rate_intercept=0.8)
    tree = generate_random_tree(params, max_time=100, coalescent=FALSE)$tree

    # calculate and print REDs
    REDs = get_reds(tree)
    print(REDs)

[Package castor version 1.6.8 Index]