get_tips_for_mrcas {castor}

Find tips with specific most recent common ancestors.

Description

Given a rooted phylogenetic tree and a list of nodes ("MRCA nodes"), for each MRCA node find a set of descending tips ("MRCA-defining tips") such that their most recent common ancestor (MRCA) is that node. This may be useful for cases where nodes need to be described as MRCAs of tip pairs for input to certain phylogenetics algorithms (e.g., for tree dating).

Usage

get_tips_for_mrcas(tree, mrca_nodes, check_input=TRUE)

Arguments

tree

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

mrca_nodes

Either an integer vector or a character vector, listing the nodes for each of which an MRCA-defining set of tips is to be found. If an integer vector, it should list node indices (i.e. from 1 to Nnodes). If a character vector, it should list node names; in that case tree$node.label must exist.

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.

Details

At most 2 MRCA-defining tips are assigned to each MRCA node. This function assumes that each of the mrca_nodes has at least two children or has a child that is a tip (otherwise the problem is not well-defined). The tree may include multi-furcations as well as mono-furcations (i.e. nodes with only one child).

The asymptotic time complexity of this function is O(Ntips+Nnodes) + O(Nmrcas), where Ntips is the number of tips, Nnodes is the number of nodes in the tree and Nmrcas is equal to length(mrca_nodes).

Value

A list of the same size as mrca_nodes, whose n-th element is an integer vector of tip indices (i.e. with values in 1,..,Ntips) whose MRCA is the n-th node listed in mrca_nodes.

Author(s)

Stilianos Louca

See Also

get_pairwise_mrcas, get_mrca_of_set

Examples

# generate a random tree
Ntips = 1000
tree = generate_random_tree(list(birth_rate_intercept=1),Ntips)$tree

# pick random nodes
focal_nodes = sample.int(n=tree$Nnode, size=3, replace=FALSE)

# get tips for mrcas
tips_per_focal_node = get_tips_for_mrcas(tree, focal_nodes);

# check correctness (i.e. calculate actual MRCAs of tips)
for(n in 1:length(focal_nodes)){
  mrca = get_mrca_of_set(tree, tips_per_focal_node[[n]])
  cat(sprintf("Focal node = %d, should match mrca of tips = %d\n",focal_nodes[n],mrca-Ntips))
}