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view corebio/seq_io/_nexus/Trees.py @ 14:778f03497adb
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author | davidmurphy |
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date | Fri, 24 Feb 2012 11:37:26 -0500 |
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# # Trees.py # # Copyright 2005 by Frank Kauff & Cymon J. Cox. All rights reserved. # This code is part of the Biopython distribution and governed by its # license. Please see the LICENSE file that should have been included # as part of this package. # # Tree class handles phylogenetic trees. Provides a set of methods to read and write newick-format tree # descriptions, get information about trees (monphyly of taxon sets, congruence between trees, common ancestors,...) # and to manipulate trees (reroot trees, split terminal nodes). # # Bug reports welcome: fkauff@duke.edu # import sys, random, sets import Nodes PRECISION_BRANCHLENGTH=6 PRECISION_SUPPORT=6 class TreeError(Exception): pass class NodeData: """Stores tree-relevant data associated with nodes (e.g. branches or otus).""" def __init__(self,taxon=None,branchlength=0.0,support=None): self.taxon=taxon self.branchlength=branchlength self.support=support class Tree(Nodes.Chain): """Represents a tree using a chain of nodes with on predecessor (=ancestor) and multiple successors (=subclades). """ # A newick tree is parsed into nested list and then converted to a node list in two stages # mostly due to historical reasons. This could be done in one swoop). Note: parentheses ( ) and # colon : are not allowed in taxon names. This is against NEXUS standard, but makes life much # easier when parsing trees. ## NOTE: Tree should store its data class in something like self.dataclass=data, ## so that nodes that are generated have easy access to the data class ## Some routines use automatically NodeData, this needs to be more concise def __init__(self,tree=None,weight=1.0,rooted=False,name='',data=NodeData,values_are_support=False,max_support=1.0): """Ntree(self,tree).""" Nodes.Chain.__init__(self) self.dataclass=data self.__values_are_support=values_are_support self.max_support=max_support self.weight=weight self.rooted=rooted self.name=name root=Nodes.Node(data()) self.add(root) self.root=root.id if tree: # use the tree we have # if Tree is called from outside Nexus parser, we need to get rid of linebreaks, etc tree=tree.strip().replace('\n','').replace('\r','') # there's discrepancy whether newick allows semicolons et the end tree=tree.rstrip(';') self._add_subtree(parent_id=root.id,tree=self._parse(tree)[0]) def _parse(self,tree): """Parses (a,b,c...)[[[xx]:]yy] into subcomponents and travels down recursively.""" if tree.count('(')!=tree.count(')'): raise TreeError, 'Parentheses do not match in (sub)tree: '+tree if tree.count('(')==0: # a leaf colon=tree.rfind(':') if colon>-1: return [tree[:colon],self._get_values(tree[colon+1:])] else: return [tree,[None]] else: closing=tree.rfind(')') val=self._get_values(tree[closing+1:]) if not val: val=[None] subtrees=[] plevel=0 prev=1 for p in range(1,closing): if tree[p]=='(': plevel+=1 elif tree[p]==')': plevel-=1 elif tree[p]==',' and plevel==0: subtrees.append(tree[prev:p]) prev=p+1 subtrees.append(tree[prev:closing]) subclades=[self._parse(subtree) for subtree in subtrees] return [subclades,val] def _add_subtree(self,parent_id=None,tree=None): """Adds leaf or tree (in newick format) to a parent_id. (self,parent_id,tree).""" if parent_id is None: raise TreeError('Need node_id to connect to.') for st in tree: if type(st[0])==list: # it's a subtree nd=self.dataclass() if len(st[1])>=2: # if there's two values, support comes first. Is that always so? nd.support=st[1][0] if st[1][1] is not None: nd.branchlength=st[1][1] elif len(st[1])==1: # otherwise it could be real branchlengths or support as branchlengths if not self.__values_are_support: # default if st[1][0] is not None: nd.branchlength=st[1][0] else: nd.support=st[1][0] sn=Nodes.Node(nd) self.add(sn,parent_id) self._add_subtree(sn.id,st[0]) else: # it's a leaf nd=self.dataclass() nd.taxon=st[0] if len(st)>1: if len(st[1])>=2: # if there's two values, support comes first. Is that always so? nd.support=st[1][0] if st[1][1] is not None: nd.branchlength=st[1][1] elif len(st[1])==1: # otherwise it could be real branchlengths or support as branchlengths if not self.__values_are_support: # default if st[1][0] is not None: nd.branchlength=st[1][0] else: nd.support=st[1][0] leaf=Nodes.Node(nd) self.add(leaf,parent_id) def _get_values(self, text): """Extracts values (support/branchlength) from xx[:yyy], xx.""" if text=='': return None return [float(t) for t in text.split(':') if t.strip()] def _walk(self,node=None): """Return all node_ids downwards from a node.""" if node is None: node=self.root for n in self.node(node).succ: yield n for sn in self._walk(n): yield sn def node(self,node_id): """Return the instance of node_id. node = node(self,node_id) """ if node_id not in self.chain: raise TreeError('Unknown node_id: %d' % node_id) return self.chain[node_id] def split(self,parent_id=None,n=2,branchlength=1.0): """Speciation: generates n (default two) descendants of a node. [new ids] = split(self,parent_id=None,n=2,branchlength=1.0): """ if parent_id is None: raise TreeError('Missing node_id.') ids=[] parent_data=self.chain[parent_id].data for i in range(n): node=Nodes.Node() if parent_data: node.data=self.dataclass() # each node has taxon and branchlength attribute if parent_data.taxon: node.data.taxon=parent_data.taxon+str(i) node.data.branchlength=branchlength ids.append(self.add(node,parent_id)) return ids def search_taxon(self,taxon): """Returns the first matching taxon in self.data.taxon. Not restricted to terminal nodes. node_id = search_taxon(self,taxon) """ for id,node in self.chain.items(): if node.data.taxon==taxon: return id return None def prune(self,taxon): """Prunes a terminal taxon from the tree. id_of_previous_node = prune(self,taxon) If taxon is from a bifurcation, the connectiong node will be collapsed and its branchlength added to remaining terminal node. This might be no longer a meaningful value' """ id=self.search_taxon(taxon) if id is None: raise TreeError('Taxon not found: %s' % taxon) elif id not in self.get_terminals(): raise TreeError('Not a terminal taxon: %s' % taxon) else: prev=self.unlink(id) self.kill(id) if not prev==self.root and len(self.node(prev).succ)==1: succ=self.node(prev).succ[0] new_bl=self.node(prev).data.branchlength+self.node(succ).data.branchlength self.collapse(prev) self.node(succ).data.branchlength=new_bl return prev def get_taxa(self,node_id=None): """Return a list of all otus downwards from a node (self, node_id). nodes = get_taxa(self,node_id=None) """ if node_id is None: node_id=self.root if node_id not in self.chain: raise TreeError('Unknown node_id: %d.' % node_id) if self.chain[node_id].succ==[]: if self.chain[node_id].data: return [self.chain[node_id].data.taxon] else: return None else: list=[] for succ in self.chain[node_id].succ: list.extend(self.get_taxa(succ)) return list def get_terminals(self): """Return a list of all terminal nodes.""" return [i for i in self.all_ids() if self.node(i).succ==[]] def sum_branchlength(self,root=None,node=None): """Adds up the branchlengths from root (default self.root) to node. sum = sum_branchlength(self,root=None,node=None) """ if root is None: root=self.root if node is None: raise TreeError('Missing node id.') blen=0.0 while node is not None and node is not root: blen+=self.node(node).data.branchlength node=self.node(node).prev return blen def set_subtree(self,node): """Return subtree as a set of nested sets. sets = set_subtree(self,node) """ if self.node(node).succ==[]: return self.node(node).data.taxon else: return sets.Set([self.set_subtree(n) for n in self.node(node).succ]) def is_identical(self,tree2): """Compare tree and tree2 for identity. result = is_identical(self,tree2) """ return self.set_subtree(self.root)==tree2.set_subtree(tree2.root) def is_compatible(self,tree2,threshold,strict=True): """Compares branches with support>threshold for compatibility. result = is_compatible(self,tree2,threshold) """ # check if both trees have the same set of taxa. strict=True enforces this. missing2=sets.Set(self.get_taxa())-sets.Set(tree2.get_taxa()) missing1=sets.Set(tree2.get_taxa())-sets.Set(self.get_taxa()) if strict and (missing1 or missing2): if missing1: print 'Taxon/taxa %s is/are missing in tree %s' % (','.join(missing1) , self.name) if missing2: print 'Taxon/taxa %s is/are missing in tree %s' % (','.join(missing2) , tree2.name) raise TreeError, 'Can\'t compare trees with different taxon compositions.' t1=[(sets.Set(self.get_taxa(n)),self.node(n).data.support) for n in self.all_ids() if \ self.node(n).succ and\ (self.node(n).data and self.node(n).data.support and self.node(n).data.support>=threshold)] t2=[(sets.Set(tree2.get_taxa(n)),tree2.node(n).data.support) for n in tree2.all_ids() if \ tree2.node(n).succ and\ (tree2.node(n).data and tree2.node(n).data.support and tree2.node(n).data.support>=threshold)] conflict=[] for (st1,sup1) in t1: for (st2,sup2) in t2: if not st1.issubset(st2) and not st2.issubset(st1): # don't hiccup on upstream nodes intersect,notin1,notin2=st1 & st2, st2-st1, st1-st2 # all three are non-empty sets # if notin1==missing1 or notin2==missing2 <==> st1.issubset(st2) or st2.issubset(st1) ??? if intersect and not (notin1.issubset(missing1) or notin2.issubset(missing2)): # omit conflicts due to missing taxa conflict.append((st1,sup1,st2,sup2,intersect,notin1,notin2)) return conflict def common_ancestor(self,node1,node2): """Return the common ancestor that connects to nodes. node_id = common_ancestor(self,node1,node2) """ l1=[self.root]+self.trace(self.root,node1) l2=[self.root]+self.trace(self.root,node2) return [n for n in l1 if n in l2][-1] def distance(self,node1,node2): """Add and return the sum of the branchlengths between two nodes. dist = distance(self,node1,node2) """ ca=self.common_ancestor(node1,node2) return self.sum_branchlength(ca,node1)+self.sum_branchlength(ca,node2) def is_monophyletic(self,taxon_list): """Return node_id of common ancestor if taxon_list is monophyletic, -1 otherwise. result = is_monophyletic(self,taxon_list) """ if isinstance(taxon_list,str): taxon_set=sets.Set([taxon_list]) else: taxon_set=sets.Set(taxon_list) node_id=self.root while 1: subclade_taxa=sets.Set(self.get_taxa(node_id)) if subclade_taxa==taxon_set: # are we there? return node_id else: # check subnodes for subnode in self.chain[node_id].succ: if sets.Set(self.get_taxa(subnode)).issuperset(taxon_set): # taxon_set is downstream node_id=subnode break # out of for loop else: return -1 # taxon set was not with successors, for loop exhausted def is_bifurcating(self,node=None): """Return True if tree downstream of node is strictly bifurcating.""" if not node: node=self.root if node==self.root and len(self.node(node).succ)==3: #root can be trifurcating, because it has no ancestor return self.is_bifurcating(self.node(node).succ[0]) and \ self.is_bifurcating(self.node(node).succ[1]) and \ self.is_bifurcating(self.node(node).succ[2]) if len(self.node(node).succ)==2: return self.is_bifurcating(self.node(node).succ[0]) and self.is_bifurcating(self.node(node).succ[1]) elif len(self.node(node).succ)==0: return True else: return False def branchlength2support(self): """Move values stored in data.branchlength to data.support, and set branchlength to 0.0 This is necessary when support has been stored as branchlength (e.g. paup), and has thus been read in as branchlength. """ for n in self.chain.keys(): self.node(n).data.support=self.node(n).data.branchlength self.node(n).data.branchlength=0.0 def convert_absolute_support(self,nrep): """Convert absolute support (clade-count) to rel. frequencies. Some software (e.g. PHYLIP consense) just calculate how often clades appear, instead of calculating relative frequencies.""" for n in self._walk(): if self.node(n).data.support: self.node(n).data.support/=float(nrep) def randomize(self,ntax=None,taxon_list=None,branchlength=1.0,branchlength_sd=None,bifurcate=True): """Generates a random tree with ntax taxa and/or taxa from taxlabels. new_tree = randomize(self,ntax=None,taxon_list=None,branchlength=1.0,branchlength_sd=None,bifurcate=True) Trees are bifurcating by default. (Polytomies not yet supported). """ if not ntax and taxon_list: ntax=len(taxon_list) elif not taxon_list and ntax: taxon_list=['taxon'+str(i+1) for i in range(ntax)] elif not ntax and not taxon_list: raise TreeError('Either numer of taxa or list of taxa must be specified.') elif ntax<>len(taxon_list): raise TreeError('Length of taxon list must correspond to ntax.') # initiate self with empty root self.__init__() terminals=self.get_terminals() # bifurcate randomly at terminal nodes until ntax is reached while len(terminals)<ntax: newsplit=random.choice(terminals) new_terminals=self.split(parent_id=newsplit,branchlength=branchlength) # if desired, give some variation to the branch length if branchlength_sd: for nt in new_terminals: bl=random.gauss(branchlength,branchlength_sd) if bl<0: bl=0 self.node(nt).data.branchlength=bl terminals.extend(new_terminals) terminals.remove(newsplit) # distribute taxon labels randomly random.shuffle(taxon_list) for (node,name) in zip(terminals,taxon_list): self.node(node).data.taxon=name def display(self): """Quick and dirty lists of all nodes.""" table=[('#','taxon','prev','succ','brlen','blen (sum)','support')] for i in self.all_ids(): n=self.node(i) if not n.data: table.append((str(i),'-',str(n.prev),str(n.succ),'-','-','-')) else: tx=n.data.taxon if not tx: tx='-' blength=n.data.branchlength if blength is None: blength='-' sum_blength='-' else: sum_blength=self.sum_branchlength(node=i) support=n.data.support if support is None: support='-' table.append((str(i),tx,str(n.prev),str(n.succ),blength,sum_blength,support)) print '\n'.join(['%3s %32s %15s %15s %8s %10s %8s' % l for l in table]) print '\nRoot: ',self.root def to_string(self,support_as_branchlengths=False,branchlengths_only=False,plain=True,plain_newick=False): """Return a paup compatible tree line. to_string(self,support_as_branchlengths=False,branchlengths_only=False,plain=True) """ # if there's a conflict in the arguments, we override plain=True if support_as_branchlengths or branchlengths_only: plain=False self.support_as_branchlengths=support_as_branchlengths self.branchlengths_only=branchlengths_only self.plain=plain def make_info_string(data,terminal=False): """Creates nicely formatted support/branchlengths.""" # CHECK FORMATTING if self.plain: # plain tree only. That's easy. return '' elif self.support_as_branchlengths: # support as branchlengths (eg. PAUP), ignore actual branchlengths if terminal: # terminal branches have 100% support return ':%1.2f' % self.max_support else: return ':%1.2f' % (data.support) elif self.branchlengths_only: # write only branchlengths, ignore support return ':%1.5f' % (data.branchlength) else: # write suport and branchlengths (e.g. .con tree of mrbayes) if terminal: return ':%1.5f' % (data.branchlength) else: if data.branchlength is not None and data.support is not None: # we have blen and suppport return '%1.2f:%1.5f' % (data.support,data.branchlength) elif data.branchlength is not None: # we have only blen return '0.00000:%1.5f' % (data.branchlength) elif data.support is not None: # we have only support return '%1.2f:0.00000' % (data.support) else: return '0.00:0.00000' def newickize(node): """Convert a node tree to a newick tree recursively.""" if not self.node(node).succ: #terminal return self.node(node).data.taxon+make_info_string(self.node(node).data,terminal=True) else: return '(%s)%s' % (','.join(map(newickize,self.node(node).succ)),make_info_string(self.node(node).data)) return subtree treeline=['tree'] if self.name: treeline.append(self.name) else: treeline.append('a_tree') treeline.append('=') if self.weight<>1: treeline.append('[&W%s]' % str(round(float(self.weight),3))) if self.rooted: treeline.append('[&R]') treeline.append('(%s)' % ','.join(map(newickize,self.node(self.root).succ))) treeline.append(';') if plain_newick: return treeline[-2] else: return ' '.join(treeline) def __str__(self): """Short version of to_string(), gives plain tree""" return self.to_string(plain=True) def unroot(self): """Defines a unrooted Tree structure, using data of a rooted Tree.""" # travel down the rooted tree structure and save all branches and the nodes they connect def _get_branches(node): branches=[] for b in self.node(node).succ: branches.append([node,b,self.node(b).data.branchlength,self.node(b).data.support]) branches.extend(_get_branches(b)) return branches self.unrooted=_get_branches(self.root) # if root is bifurcating, then it is eliminated if len(self.node(self.root).succ)==2: # find the two branches that connect to root rootbranches=[b for b in self.unrooted if self.root in b[:2]] b1=self.unrooted.pop(self.unrooted.index(rootbranches[0])) b2=self.unrooted.pop(self.unrooted.index(rootbranches[1])) # Connect them two each other. If both have support, it should be identical (or one set to None?). # If both have branchlengths, they will be added newbranch=[b1[1],b2[1],b1[2]+b2[2]] if b1[3] is None: newbranch.append(b2[3]) # either None (both rootbranches are unsupported) or some support elif b2[3] is None: newbranch.append(b1[3]) # dito elif b1[3]==b2[3]: newbranch.append(b1[3]) # identical support elif b1[3]==0 or b2[3]==0: newbranch.append(b1[3]+b2[3]) # one is 0, take the other else: raise TreeError, 'Support mismatch in bifurcating root: %f, %f' % (float(b1[3]),float(b2[3])) self.unrooted.append(newbranch) def root_with_outgroup(self,outgroup=None): def _connect_subtree(parent,child): """Hook subtree starting with node child to parent.""" for i,branch in enumerate(self.unrooted): if parent in branch[:2] and child in branch[:2]: branch=self.unrooted.pop(i) break else: raise TreeError, 'Unable to connect nodes for rooting: nodes %d and %d are not connected' % (parent,child) self.link(parent,child) self.node(child).data.branchlength=branch[2] self.node(child).data.support=branch[3] #now check if there are more branches connected to the child, and if so, connect them child_branches=[b for b in self.unrooted if child in b[:2]] for b in child_branches: if child==b[0]: succ=b[1] else: succ=b[0] _connect_subtree(child,succ) # check the outgroup we're supposed to root with if outgroup is None: return self.root outgroup_node=self.is_monophyletic(outgroup) if outgroup_node==-1: return -1 # if tree is already rooted with outgroup on a bifurcating root, # or the outgroup includes all taxa on the tree, then we're fine if (len(self.node(self.root).succ)==2 and outgroup_node in self.node(self.root).succ) or outgroup_node==self.root: return self.root self.unroot() # now we find the branch that connects outgroup and ingroup #print self.node(outgroup_node).prev for i,b in enumerate(self.unrooted): if outgroup_node in b[:2] and self.node(outgroup_node).prev in b[:2]: root_branch=self.unrooted.pop(i) break else: raise TreeError, 'Unrooted and rooted Tree do not match' if outgroup_node==root_branch[1]: ingroup_node=root_branch[0] else: ingroup_node=root_branch[1] # now we destroy the old tree structure, but keep node data. Nodes will be reconnected according to new outgroup for n in self.all_ids(): self.node(n).prev=None self.node(n).succ=[] # now we just add both subtrees (outgroup and ingroup) branch for branch root=Nodes.Node(data=NodeData()) # new root self.add(root) # add to tree description self.root=root.id # set as root self.unrooted.append([root.id,ingroup_node,root_branch[2],root_branch[3]]) # add branch to ingroup to unrooted tree self.unrooted.append([root.id,outgroup_node,0.0,0.0]) # add branch to outgroup to unrooted tree _connect_subtree(root.id,ingroup_node) # add ingroup _connect_subtree(root.id,outgroup_node) # add outgroup # if theres still a lonely node in self.chain, then it's the old root, and we delete it oldroot=[i for i in self.all_ids() if self.node(i).prev is None and i!=self.root] if len(oldroot)>1: raise TreeError, 'Isolated nodes in tree description: %s' % ','.join(oldroot) elif len(oldroot)==1: self.kill(oldroot[0]) return self.root def consensus(trees, threshold=0.5,outgroup=None): """Compute a majority rule consensus tree of all clades with relative frequency>=threshold from a list of trees.""" total=len(trees) if total==0: return None # shouldn't we make sure that it's NodeData or subclass?? dataclass=trees[0].dataclass max_support=trees[0].max_support clades={} #countclades={} alltaxa=sets.Set(trees[0].get_taxa()) # calculate calde frequencies c=0 for t in trees: c+=1 #if c%50==0: # print c if alltaxa!=sets.Set(t.get_taxa()): raise TreeError, 'Trees for consensus must contain the same taxa' t.root_with_outgroup(outgroup=outgroup) for st_node in t._walk(t.root): subclade_taxa=t.get_taxa(st_node) subclade_taxa.sort() subclade_taxa=str(subclade_taxa) # lists are not hashable if subclade_taxa in clades: clades[subclade_taxa]+=float(t.weight)/total else: clades[subclade_taxa]=float(t.weight)/total #if subclade_taxa in countclades: # countclades[subclade_taxa]+=t.weight #else: # countclades[subclade_taxa]=t.weight # weed out clades below threshold for (c,p) in clades.items(): if p<threshold: del clades[c] # create a tree with a root node consensus=Tree(name='consensus_%2.1f' % float(threshold),data=dataclass) # each clade needs a node in the new tree, add them as isolated nodes for (c,s) in clades.items(): node=Nodes.Node(data=dataclass()) node.data.support=s node.data.taxon=sets.Set(eval(c)) consensus.add(node) # set root node data consensus.node(consensus.root).data.support=None consensus.node(consensus.root).data.taxon=alltaxa # we sort the nodes by no. of taxa in the clade, so root will be the last consensus_ids=consensus.all_ids() consensus_ids.sort(lambda x,y:len(consensus.node(x).data.taxon)-len(consensus.node(y).data.taxon)) # now we just have to hook each node to the next smallest node that includes all taxa of the current for i,current in enumerate(consensus_ids[:-1]): # skip the last one which is the root #print '----' #print 'current: ',consensus.node(current).data.taxon # search remaining nodes for parent in consensus_ids[i+1:]: #print 'parent: ',consensus.node(parent).data.taxon if consensus.node(parent).data.taxon.issuperset(consensus.node(current).data.taxon): break else: sys.exit('corrupt tree structure?') # internal nodes don't have taxa if len(consensus.node(current).data.taxon)==1: consensus.node(current).data.taxon=consensus.node(current).data.taxon.pop() # reset the support for terminal nodes to maximum #consensus.node(current).data.support=max_support else: consensus.node(current).data.taxon=None consensus.link(parent,current) # eliminate root taxon name consensus.node(consensus_ids[-1]).data.taxon=None return consensus