View source: R/get_pairwise_distances.R
get_pairwise_distances | R Documentation |
Calculate phylogenetic ("patristic") distances between tips or nodes in some list A and tips or nodes in a second list B of the same size.
get_pairwise_distances(tree, A, B, as_edge_counts=FALSE, 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 for which to calculate the distance. 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 for which to calculate the distance. 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 |
as_edge_counts |
Logical, specifying whether distances should be calculated in terms of edge counts, rather than cumulative edge lengths. This is the same as if all edges had length 1. |
The "patristic distance" between two tips and/or nodes is the shortest cumulative branch length that must be traversed along the tree in order to reach one tip/node from the other. Given a list of tips and/or nodes A, and a 2nd list of tips and/or nodes B of the same size, this function will calculate patristic distance between each pair (A[i], B[i]), where i=1,2,..,Npairs.
If tree$edge.length
is missing, then each edge is assumed to be of length 1; this is the same as setting as_edge_counts=TRUE
. The tree may include multi-furcations as well as mono-furcations (i.e. nodes with only one child). The input tree must be rooted at some node for technical reasons (see function root_at_node
), but the choice of the root node does not influence the result. If A
and/or B
is a character vector, then tree$tip.label
must exist. If node names are included in A
and/or B
, then tree$node.label
must also exist.
The asymptotic average time complexity of this function for a balanced binary tree is O(Ntips+Npairs*log2(Ntips)).
A numeric vector of size Npairs, with the i-th element being the patristic distance between the tips/nodes A[i] and B[i].
Stilianos Louca
get_all_distances_to_root
,
get_all_pairwise_distances
# generate a random tree
Ntips = 100
tree = generate_random_tree(list(birth_rate_intercept=1),Ntips)$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 distances
distances = get_pairwise_distances(tree, A, B)
# reroot at some other node
tree = root_at_node(tree, new_root_node=20, update_indices=FALSE)
new_distances = get_pairwise_distances(tree, A, B)
# verify that distances remained unchanged
print(distances)
print(new_distances)
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