def get_evol_events_from_root(node, sos_thr):
""" Returns a list of **all** duplication and speciation
events detected after this node. Nodes are assumed to be
duplications when a species overlap is found between its child
linages. Method is described more detail in:
"The Human Phylome." Huerta-Cepas J, Dopazo H, Dopazo J, Gabaldon
T. Genome Biol. 2007;8(6):R109.
"""
# Get the tree's root
root = node.get_tree_root()
# Checks that is actually rooted
outgroups = root.get_children()
if len(outgroups) != 2:
raise TypeError, "Tree is not rooted"
# Cautch the smaller outgroup (will be stored as the tree outgroup)
o1 = set([n.name for n in outgroups[0].get_leaves()])
o2 = set([n.name for n in outgroups[1].get_leaves()])
if len(o2)<len(o1):
smaller_outg = outgroups[1]
else:
smaller_outg = outgroups[0]
# Get family size
fSize = len( [n for n in root.get_leaves()] )
# Clean data from previous analyses
for n in root.get_descendants()+[root]:
n.del_feature("evoltype")
# Gets Prepared to browse the tree from root to leaves
to_visit = []
current = root
all_events = []
while current:
# Gets childs and appends them to the To_visit list
childs = current.get_children()
to_visit += childs
if len(childs)>2:
raise TypeError, "nodes are expected to have two childs."
elif len(childs)==0:
pass # leaf
else:
# Get leaves and species at both sides of event
sideA_leaves= set([n for n in childs[0].get_leaves()])
sideB_leaves= set([n for n in childs[1].get_leaves()])
sideA_spcs = set([n.species for n in childs[0].get_leaves()])
sideB_spcs = set([n.species for n in childs[1].get_leaves()])
# Calculates species overlap
overlaped_spcs = sideA_spcs & sideB_spcs
all_spcs = sideA_spcs | sideB_spcs
score = float(len(overlaped_spcs))/len(all_spcs)
# Creates a new evolEvent
event = EvolEvent()
event.fam_size = fSize
event.branch_supports = [current.support, current.children[0].support, current.children[1].support]
# event.seed = leafName
# event.e_newick = current.up.get_newick() # high mem usage!!
event.sos = score
event.outgroup_spcs = smaller_outg.get_species()
event.in_seqs = set([n.name for n in sideA_leaves])
event.out_seqs = set([n.name for n in sideB_leaves])
event.inparalogs = set([n.name for n in sideA_leaves])
# If species overlap: duplication
if score >sos_thr:
event.node = current
event.etype = "D"
event.outparalogs = set([n.name for n in sideB_leaves])
event.orthologs = set([])
current.add_feature("evoltype","D")
# If NO species overlap: speciation
else:
event.node = current
event.etype = "S"
event.orthologs = set([n.name for n in sideB_leaves])
event.outparalogs = set([])
current.add_feature("evoltype","S")
all_events.append(event)
# Keep visiting nodes
try:
current = to_visit.pop(0)
except IndexError:
current = None
return all_events
def get_evol_events_from_root(node, sos_thr):
""" Returns a list of **all** duplication and speciation
events detected after this node. Nodes are assumed to be
duplications when a species overlap is found between its child
linages. Method is described more detail in:
"The Human Phylome." Huerta-Cepas J, Dopazo H, Dopazo J, Gabaldon
T. Genome Biol. 2007;8(6):R109.
"""
# Get the tree's root
root = node.get_tree_root()
# Checks that is actually rooted
outgroups = root.get_children()
if len(outgroups) != 2:
raise TypeError, "Tree is not rooted"
# Cautch the smaller outgroup (will be stored as the tree outgroup)
o1 = set([n.name for n in outgroups[0].get_leaves()])
o2 = set([n.name for n in outgroups[1].get_leaves()])
if len(o2) < len(o1):
smaller_outg = outgroups[1]
else:
smaller_outg = outgroups[0]
# Get family size
fSize = len([n for n in root.get_leaves()])
# Clean data from previous analyses
for n in root.get_descendants() + [root]:
n.del_feature("evoltype")
# Gets Prepared to browse the tree from root to leaves
to_visit = []
current = root
all_events = []
while current:
# Gets childs and appends them to the To_visit list
childs = current.get_children()
to_visit += childs
if len(childs) > 2:
raise TypeError, "nodes are expected to have two childs."
elif len(childs) == 0:
pass # leaf
else:
# Get leaves and species at both sides of event
sideA_leaves = set([n for n in childs[0].get_leaves()])
sideB_leaves = set([n for n in childs[1].get_leaves()])
sideA_spcs = set([n.species for n in childs[0].get_leaves()])
sideB_spcs = set([n.species for n in childs[1].get_leaves()])
# Calculates species overlap
overlaped_spcs = sideA_spcs & sideB_spcs
all_spcs = sideA_spcs | sideB_spcs
score = float(len(overlaped_spcs)) / len(all_spcs)
# Creates a new evolEvent
event = EvolEvent()
event.fam_size = fSize
event.branch_supports = [
current.support, current.children[0].support,
current.children[1].support
]
# event.seed = leafName
# event.e_newick = current.up.get_newick() # high mem usage!!
event.sos = score
event.outgroup_spcs = smaller_outg.get_species()
event.in_seqs = set([n.name for n in sideA_leaves])
event.out_seqs = set([n.name for n in sideB_leaves])
event.inparalogs = set([n.name for n in sideA_leaves])
# If species overlap: duplication
if score > sos_thr:
event.node = current
event.etype = "D"
event.outparalogs = set([n.name for n in sideB_leaves])
event.orthologs = set([])
current.add_feature("evoltype", "D")
# If NO species overlap: speciation
else:
event.node = current
event.etype = "S"
event.orthologs = set([n.name for n in sideB_leaves])
event.outparalogs = set([])
current.add_feature("evoltype", "S")
all_events.append(event)
# Keep visiting nodes
try:
current = to_visit.pop(0)
except IndexError:
current = None
return all_events
