root_at_node {castor} | R Documentation |
Given a tree (rooted or unrooted) and a specific node, this function changes the direction of edges (tree$edge
) such that the designated node becomes the root (i.e. has no incoming edges and all other tips and nodes descend from it). The number of tips and the number of nodes remain unchanged.
root_at_node(tree, new_root_node, update_indices=TRUE)
tree |
A tree object of class "phylo". Can be unrooted or rooted. |
new_root_node |
Character or integer specifying the name or index, respectively, of the node to be turned into root. If an integer, it must be between 1 and |
update_indices |
Logical, specifying whether to update the node indices such that the new root is the first node in the list (as is common convention). This will modify |
The input tree may include an arbitrary number of incoming and outgoing edges per node (but only one edge per tip), and the direction of these edges can be arbitrary. Of course, the undirected graph defined by all edges must still be a valid tree. The asymptotic time complexity of this function is O(Nedges).
If update_indices==FALSE
, then node indices remain unchanged.
If update_indices==TRUE
(default), then node indices are modified such that the new root is the first node (i.e. with index Ntips+1 in edge
and with index 1 in node.label
). This is common convention, but it may be undesirable if, for example, you are looping through all nodes in the tree and are only temporarily designating them as root. Setting update_indices=FALSE
also reduces the computation required for rerooting. Tip indices always remain unchanged.
A tree object of class "phylo", with the edge
element modified such that the node new_root_node
is root. The elements tip.label
, edge.length
and root.edge
(if they exist) are the same as for the input tree. If update_indices==FALSE
, then the element node.label
will also remain the same.
Stilianos Louca
root_via_outgroup
,
root_at_midpoint
,
root_in_edge
# generate a random tree Ntips = 100 tree = generate_random_tree(list(birth_rate_intercept=1),max_tips=Ntips)$tree # reroot the tree at the 20-th node new_root_node = 20 tree = root_at_node(tree, new_root_node, update_indices=FALSE) # find new root index and compare with expectation cat(sprintf("New root is %d, expected at %d\n",find_root(tree),new_root_node+Ntips))