get_pairwise_mrcas {castor} | R Documentation |
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.
get_pairwise_mrcas(tree, A, B, check_input=TRUE)
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 |
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$node.label
must also exist.
The asymptotic average time complexity of this function is O(Nedges), where Nedges is the number of edges in the tree.
An integer vector of size Npairs with values in 1,..,Ntips (tips) and/or in (Ntips+1),..,(Ntips+Nnodes) (nodes), with the i-th element being the index of the MRCA of tips/nodes A[i]
and B[i]
.
Stilianos Louca
get_mrca_of_set
, get_tips_for_mrcas
# generate a random tree Ntips = 100 tree = generate_random_tree(list(birth_rate_intercept=1),Ntips)$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)