The objective of PhyloTrees.jl is to provide fast and simple tools for working with rooted phylogenetic trees in Julia.
Installation
The current release can be installed from the Julia REPL with:
pkg> add PhyloTrees
The development version (master branch) can be installed with:
pkg> add PhyloTrees#master
Usage
There are several ways to add nodes and branches to our Tree, see below for examples
> # Initialize the tree
> exampletree = Tree()
Phylogenetic tree with 0 nodes and 0 branches
> # Add a node to the tree
> addnode!(exampletree)
Phylogenetic tree with 1 nodes and 0 branches
Branches have Float64 lengths
> # Add a node, connect it to node 1 with a branch 5.0 units in length
> branch!(exampletree, 1, 5.0)
Phylogenetic tree with 2 nodes and 1 branches
> # Add 2 nodes
> addnodes!(exampletree, 2)
Phylogenetic tree with 4 nodes and 1 branches
> # Add a branch from node 2 to node 3 10.0 units in length
> addbranch!(exampletree, 2, 3, 10.0)
Phylogenetic tree with 4 nodes and 2 branches
We can quickly look at the nodes present in our Tree:
Distance between nodes can be calculated using the distance function. A node visit ordering for postorder traversal of a tree can be found with postorder.
A plot recipe is provided for Trees. The following Tree has been generated and plotted using code in READMETREE.jl.
There are many other functions available that are helpful when dealing with trees including:
changesource!,
changetarget!,
indegree,
outdegree,
isroot,
isleaf,
isinternal,
findroots,
findleaves,
findinternal,
findnonroots,
findnonleaves,
findexternal,
areconnected,
nodepath,
branchpath,
parentnode,
childnodes,
descendantnodes,
descendantcount,
leafnodes,
leafcount,
ancestorcount,
ancestornodes, and
nodetype. These work nicely with Julia's elegant function vectorization. An example of this in action can be seen in the in our plot recipe code.
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