Bio::PhyloNetwork - Module to compute with Phylogenetic Networks
use Bio::PhyloNetwork; # Create a PhyloNetwork object from a eNewick string my $net1=Bio::PhyloNetwork->new( -eNewick=>'t0:((H1,(H2,l2)),H2); H1:((H3,l1)); H2:((H3,(l3,H1))); H3:(l4);' ); # Print all available data print $net1; # Rebuild $net1 from its mu_data my %mudata=$net1->mudata(); my $net2=Bio::PhyloNetwork->new(-mudata=>\%mudata,-numleaves=>4); print $net2; print "d=".$net1->mu_distance($net2)."\n"; # Get another one and compute distance my $net3=Bio::PhyloNetwork->new( -eNewick=>'(l2,((l1,(H1,l4)),H1))r; (l3)H1;' ); print "d=".$net1->mu_distance($net3)."\n"; # ...and find an optimal alignment w.r.t. the Manhattan distance (default) my ($weight,%alignment)=$net1->optimal_alignment($net3); print "weight:$weight\n"; foreach my $node1 (keys %alignment) { print "$node1 => ".$alignment{$node1}."\n"; } # ...or the Hamming distance my ($weightH,%alignmentH)=$net1->optimal_alignment($net3,-metric=>'Hamming'); print "weight:$weightH\n"; foreach my $node1 (keys %alignmentH) { print "$node1 => ".$alignmentH{$node1}."\n"; } # Test for time consistency of $net1 if ($net1->is_time_consistent) { print "net1 is time consistent\n" } else { print "net1 is not time consistent\n" } # create a network from the list of edges my $net4=Bio::PhyloNetwork->new(-edges=> [qw(r s r t s u s c t c t v u b u l3 u b v b v l4 b l2 c l1)]); # Test for time consistency of $net3 if ($net4->is_time_consistent) { print "net4 is time consistent\n" } else { print "net4 is not time consistent\n" } # And print all information on net4 print $net4; # Compute some tripartitions my %triparts=$net1->tripartitions(); # Now these are stored print $net1; # And can compute the tripartition error print "dtr=".$net1->tripartition_error($net3)."\n";
This is a module to work with phylogenetic networks. Phylogenetic networks have been studied over the last years as a richer model of the evolutionary history of sets of organisms than phylogenetic trees, because they take not only mutation events but also recombination and horizontal gene transfer events into account.
The natural model for describing the evolutionary history of a set of sequences under recombination events is a DAG, hence this package relies on the package Graph::Directed to represent the underlying graph of a phylogenetic network. We refer the reader to [CRV1,CRV2] for formal definitions related to phylogenetic networks.
With this package, phylogenetic networks can be given by its eNewick string. This description appeared in other packages related to phylogenetic networks (see [PhyloNet] and [NetGen]); in fact, these two packages use different descriptions. The Bio::PhyloNetwork package allows both of them, but uses the second one in its output.
The first approach [PhyloNet] goes as follows: For each hybrid node H, say with parents u_1,u_2,...,u_k and children v_1,v_2,...v_l: split H in k+1 different nodes; let each of the first k copies be a child of one of the u_1,...,u_k (one for each) and have no children (hence we will have k extra leaves); as for the last copy, let it have no parents and have v_1,...,v_l be its children. This way we get a forest; each of the trees will be rooted at either one root of the phylogenetic network or a hybrid node of it; the set of leaves (of the whole forest) will be the set of leaves of the original network together with the set of hybrid nodes (each of them repeated as many times as its in-degree). Then, the eNewick representation of the phylogenetic network will be the Newick representation of all the trees in the obtained forest, each of them with its root labeled.
The second approach [NetGen] goes as follows: For each hybrid node H, say with parents u_1,u_2,...,u_k and children v_1,v_2,...v_l: split H in k different nodes; let the first copy be a child of u_1 and have all v_1,v_2,...v_l as its children; let the other copies be child of u_2,...,u_k (one for each) and have no children. This way, we get a tree whose set of leaves is the set of leaves of the original network together with the set of hybrid nodes (possibly repeated). Then the Newick string of the obtained tree (note that some internal nodes will be labeled and some leaves will be repeated) is the eNewick string of the phylogenetic network.
For example, consider the network depicted below:
r / \ / \ U V / \ / \ 1 \ / 3 H | 2
If the first approach is taken, we get the forest:
r / \ / \ U V / \ / \ 1 H H 3 | H | 2
Hence, the eNewick string is '((1,H),(H,3))r; (2)H;'.
As for the second one, one gets the tree:
r / \ / \ U V / \ / \ 1 H | 3 H | 2
Hence, the eNewick string is '((1,H),((2)H,3))r;'.
Note: when rooting a tree, this package allows the notations '(subtree,subtree,...)root' as well as 'root:(subtree,subtree,...)', but the first one is used when writing eNewick strings.
Tree-child (TC) phylogenetic networks are a special class of phylogenetic networks for which a distance, called mu-distance, is defined [CRV2] based on certain data (mu-data) associated to every node. Moreover, this distance extends the Robinson-Foulds on phylogenetic trees. This package allows testing for a phylogenetic network if it is TC and computes mu-distances between networks over the same set of leaves.
Moreover, the mu-data allows one to define the optimal (in some precise sense) alignment between networks over the same set of leaves. This package also computes this optimal alignment.
Although tripartitions (see [CRV1] and the references therein) do not allow to define distances, this package outputs tripartitions and computes a weak form of the tripartition error.
Another useful property of Phylogenetic Networks that appears in the literature is that of time-consistency or real-time hybrids [BSS]. Roughly speaking, a network admits a temporal representation if it can be drawn in such a way that tree arcs (those whose end is a tree node) are inclined downwards, while hybridization arcs (those whose end is a hybrid node) are horizontal. This package checks for time-consistency and, if so, a temporal representation is provided.
Gabriel Cardona, gabriel(dot)cardona(at)uib(dot)es Gabriel Valiente, valiente(at)lsi(dot)upc(dot)edu
G. Cardona, F. Rossello, G. Valiente. Tripartitions do not always discriminate phylogenetic networks. arXiv:0707.2376v1 [q-bio.PE]
G. Cardona, F. Rossello, G. Valiente. A Distance Measure for Tree-Child Phylogenetic Networks. Preprint.
M.M. Morin, and B.M.E. Moret. NetGen: generating phylogenetic networks with diploid hybrids. Bioinformatics 22 (2006), 1921-1923
PhyloNet: "Phylogenetic Networks Toolkit". http://bioinfo.cs.rice.edu/phylonet
M. Baroni, C. Semple, and M. Steel. Hybrids in Real Time. Syst. Biol. 55(1):46-56, 2006
The rest of the documentation details each of the object methods.
Title : new Usage : my $obj = new Bio::PhyloNetwork(); Function: Creates a new Bio::PhyloNetwork object Returns : Bio::PhyloNetwork Args : none OR -eNewick => string OR -graph => Graph::Directed object OR -edges => reference to an array OR -tree => Bio::Tree::Tree object OR -mudata => reference to a hash, -leaves => reference to an array OR -mudata => reference to a hash, -numleaves => integer
Returns a Bio::PhyloNetwork object, created according to the data given:
creates an empty network.
creates the network whose Extended Newick representation (see description above) is the string $str.
creates the network with underlying graph given by the Graph::Directed object $graph
creates a network as a copy of the Bio::Tree::Tree object in $tree
creates the network by reconstructing it from its mu-data stored in \%mudata and with set of leaves in \@leaves.
creates the network by reconstructing it from its mu-data stored in \%mudata and with set of leaves in ("l1".."l$numleaves").
Title : is_leaf Usage : my $b=$net->is_leaf($u) Function: tests if $u is a leaf in $net Returns : boolean Args : scalar
Title : is_root Usage : my $b=$net->is_root($u) Function: tests if $u is the root of $net Returns : boolean Args : scalar
Title : is_tree_node Usage : my $b=$net->is_tree_node($u) Function: tests if $u is a tree node in $net Returns : boolean Args : scalar
Title : is_hybrid_node Usage : my $b=$net->is_hybrid_node($u) Function: tests if $u is a hybrid node in $net Returns : boolean Args : scalar
Title : is_tree_child Usage : my $b=$net->is_tree_child() Function: tests if $net is a Tree-Child phylogenetic network Returns : boolean Args : Bio::PhyloNetwork
Title : nodes Usage : my @nodes=$net->nodes() Function: returns the set of nodes of $net Returns : array Args : none
Title : leaves Usage : my @leaves=$net->leaves() Function: returns the set of leaves of $net Returns : array Args : none
Title : roots Usage : my @roots=$net->roots() Function: returns the set of roots of $net Returns : array Args : none
Title : internal_nodes Usage : my @internal_nodes=$net->internal_nodes() Function: returns the set of internal nodes of $net Returns : array Args : none
Title : tree_nodes Usage : my @tree_nodes=$net->tree_nodes() Function: returns the set of tree nodes of $net Returns : array Args : none
Title : hybrid_nodes Usage : my @hybrid_nodes=$net->hybrid_nodes() Function: returns the set of hybrid nodes of $net Returns : array Args : none
Title : graph Usage : my $graph=$net->graph() Function: returns the underlying graph of $net Returns : Graph::Directed Args : none
Title : edges Usage : my @edges=$net->edges() Function: returns the set of edges of $net Returns : array Args : none
Each element in the array is an anonimous array whose first element is the head of the edge and the second one is the tail.
Title : tree_edges Usage : my @tree_edges=$net->tree_edges() Function: returns the set of tree edges of $net (those whose tail is a tree node) Returns : array Args : none
Title : hybrid_edges Usage : my @hybrid_edges=$net->hybrid_edges() Function: returns the set of hybrid edges of $net (those whose tail is a hybrid node) Returns : array Args : none
Title : explode Usage : my @trees=$net->explode() Function: returns the representation of $net by a set of Bio::Tree:Tree objects Returns : array Args : none
Title : mudata Usage : my %mudata=$net->mudata() Function: returns the representation of $net by its mu-data Returns : hash Args : none
$net->mudata() returns a hash with keys the nodes of $net and each value is a muVector object holding its mu-vector.
Title : heights Usage : my %heights=$net->heights() Function: returns the heights of the nodes of $net Returns : hash Args : none
$net->heights() returns a hash with keys the nodes of $net and each value is its height.
Title : mu_distance Usage : my $dist=$net1->mu_distance($net2) Function: Computes the mu-distance between the networks $net1 and $net2 on the same set of leaves Returns : scalar Args : Bio::PhyloNetwork
Title : mu_distance_generalized Usage : my $dist=$net1->mu_distance($net2) Function: Computes the mu-distance between the topological restrictions of networks $net1 and $net2 on its common set of leaves Returns : scalar Args : Bio::PhyloNetwork
Title : tripartitions Usage : my %tripartitions=$net->tripartitions() Function: returns the set of tripartitions of $net Returns : hash Args : none
$net->tripartitions() returns a hash with keys the nodes of $net and each value is a string representing the tripartition of the leaves induced by the node. A string "BCA..." associated with a node u (e.g.) means, the first leaf is in the set B(u), the second one in C(u), the third one in A(u), and so on.
Title : is_time_consistent Usage : my $b=$net->is_time_consistent() Function: tests if $net is (strong) time-consistent Returns : boolean Args : none
Title : temporal_representation Usage : my %time=$net->temporal_representation() Function: returns a hash containing a temporal representation of $net, or 0 if $net is not time-consistent Returns : hash Args : none
Title : contract_elementary Usage : my ($contracted,$blocks)=$net->contract_elementary(); Function: Returns the network $contracted, obtained by contracting elementary paths of $net into edges. The reference $blocks points to a hash where, for each node of $contracted, gives the corresponding nodes of $net that have been deleted. Returns : Bio::PhyloNetwork,reference to hash Args : none
Title : optimal_alignment Usage : my ($weight,$alignment,$wgts)=$net->optimal_alignment($net2) Function: returns the total weight of an optimal alignment, the alignment itself, and partial weights between the networks $net1 and $net2 on the same set of leaves. An optional argument allows one to use the Manhattan (default) or the Hamming distance between mu-vectors. Returns : scalar,reference to hash,reference to hash Args : Bio::PhyloNetwork, -metric => string (optional)
Supported strings for the -metric parameter are 'Manhattan' or 'Hamming'.
Title : optimal_alignment_generalized Usage : my ($weight,%alignment)=$net->optimal_alignment_generalized($net2) Function: returns the wieght of an optimal alignment, and the alignment itself, between the topological restriction of the networks $net1 and $net2 on the set of common leaves. An optional argument allows one to use the Manhattan (default) or the Hamming distance between mu-vectors. Returns : scalar,hash Args : Bio::PhyloNetwork, -metric => string (optional)
Supported strings for the -metric parameter are 'Manhattan' or 'Hamming'.
Title : topological_restriction Usage : my ($netr1,$netr2)=$net1->topological_restriction($net2) Function: returns the topological restriction of $net1 and $net2 on its common set of leaves Returns : Bio::PhyloNetwork, Bio::PhyloNetwork Args : Bio::PhyloNetwork
Title : eNewick Usage : my $str=$net->eNewick() Function: returns the eNewick representation of $net without labeling internal tree nodes Returns : string Args : none
Title : eNewick_full Usage : my $str=$net->eNewick_full() Function: returns the eNewick representation of $net labeling internal tree nodes Returns : string Args : none
Title : display Usage : my $str=$net->display() Function: returns a string containing all the available information on $net Returns : string Args : none