castor (version 1.6.1)

get_pairwise_mrcas: Get most recent common ancestors of tip/node pairs.

Description

Given a rooted phylogenetic tree and one or more pairs of tips and/or nodes, for each pair of tips/nodes find the most recent common ancestor (MRCA). If one clade is descendant of the other clade, the latter will be returned as MRCA.

Usage

get_pairwise_mrcas(tree, A, B, check_input=TRUE)

Arguments

tree

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

A

An integer vector or character vector of size Npairs, specifying the first of the two members of each pair of tips/nodes for which to find the MRCA. If an integer vector, it must list indices of tips (from 1 to Ntips) and/or nodes (from Ntips+1 to Ntips+Nnodes). If a character vector, it must list tip and/or node names.

B

An integer vector or character vector of size Npairs, specifying the second of the two members of each pair of tips/nodes for which to find the MRCA. If an integer vector, it must list indices of tips (from 1 to Ntips) and/or nodes (from Ntips+1 to Ntips+Nnodes). If a character vector, it must list tip and/or node names.

check_input

Logical, whether to perform basic validations of the input data. If you know for certain that your input is valid, you can set this to FALSE to reduce computation time.

Value

An integer vector of size Npairs with values in 1,..,Ntips (tips) and/or in (Ntips+1),..,(Ntips+Nnodes) (nodes), with the i-th element being the index of the MRCA of tips/nodes A[i] and B[i].

Details

The tree may include multi-furcations as well as mono-furcations (i.e. nodes with only one child). If tree$edge.length is missing, then each edge is assumed to be of length 1. Note that in some cases the MRCA of two tips may be a tip, namely when both tips are the same.

If A and/or B is a character vector, then tree$tip.label must exist. If node names are included in A and/or B, then tree$node.label must also exist.

The asymptotic average time complexity of this function is O(Nedges), where Nedges is the number of edges in the tree.

See Also

get_mrca_of_set, get_tips_for_mrcas

Examples

# NOT RUN {
# generate a random tree
Ntips = 100
tree = generate_random_tree(list(birth_rate_intercept=1),Ntips)$tree

# pick 3 random pairs of tips or nodes
Npairs = 3
A = sample.int(n=(Ntips+tree$Nnode), size=Npairs, replace=FALSE)
B = sample.int(n=(Ntips+tree$Nnode), size=Npairs, replace=FALSE)

# calculate MRCAs
MRCAs = get_pairwise_mrcas(tree, A, B)
# }