def build_hmm_from_tree(base,tree_name,aln_name,msa_dir,hmm_dir):
'''
Reads tree and corresponding msa and create an MSA & HMM for each internal node.
'''
# Annotate internal nodes with name of corresponding HMM.
pt = PhyloTree(tree_name,alignment=aln_name,alg_format="fasta")
i_node = 0
for node in pt.traverse():
if not node.is_leaf():
node_name = 'node%s' % (str(i_node))
node.add_features(hmm=node_name)
i_node += 1
# make msa for node
msa_string = []
for leaf in node.iter_leaves():
msa_string.append(">%s" % leaf.name)
msa_string.append(str(leaf.sequence))
msa_string = '\n'.join(msa_string)
msa = open('%s%s.aln' % (msa_dir, node_name),'w'); msa.write(msa_string); msa.close()
# build HMM for node
check_call(['python', 'build_hmmer3_hmm_from_alignment.py', '--name',
'%s%s' % (hmm_dir, node_name),
'%s%s.aln' % (msa_dir, node_name)])
#concatenate HMMs into one file for Hmmscan
os.system('cat %s*.hmm > %s%s_concat.hmm' %
(hmm_dir, hmm_dir, base))
return pt
def run(args):
from ete2 import Tree, PhyloTree
for nw in args.src_tree_iterator:
if args.orthologs is not None:
t = PhyloTree(nw)
for e in t.get_descendant_evol_events():
print e.in_seqs, e.out_seqs
def run(args):
from ete2 import Tree, PhyloTree
for nw in args.src_tree_iterator:
if args.orthologs is not None:
t = PhyloTree(nw)
for e in t.get_descendant_evol_events():
print e.in_seqs, e.out_seqs
def load_tree_sequences(nwk_file, fasta_file):
'''
Load a tree with associated sequences on leaves.
'''
tree = PhyloTree(newick=nwk_file, format=1)
tree.link_to_alignment(alignment=fasta_file, alg_format='fasta')
return tree
def get_example_tree():
# Performs a tree reconciliation analysis
gene_tree_nw = '((Dme_001,Dme_002),(((Cfa_001,Mms_001),((Hsa_001,Ptr_001),Mmu_001)),(Ptr_002,(Hsa_002,Mmu_002))));'
species_tree_nw = "((((Hsa, Ptr), Mmu), (Mms, Cfa)), Dme);"
genetree = PhyloTree(gene_tree_nw)
sptree = PhyloTree(species_tree_nw)
recon_tree, events = genetree.reconcile(sptree)
recon_tree.link_to_alignment(alg)
return recon_tree, TreeStyle()
def get_example_tree():
# Performs a tree reconciliation analysis
gene_tree_nw = '((Dme_001,Dme_002),(((Cfa_001,Mms_001),((Hsa_001,Ptr_001),Mmu_001)),(Ptr_002,(Hsa_002,Mmu_002))));'
species_tree_nw = "((((Hsa, Ptr), Mmu), (Mms, Cfa)), Dme);"
genetree = PhyloTree(gene_tree_nw)
sptree = PhyloTree(species_tree_nw)
recon_tree, events = genetree.reconcile(sptree)
recon_tree.link_to_alignment(alg)
return recon_tree, TreeStyle()
def my_tree_loader(tree):
""" This function is used to load trees within the WebTreeApplication object. """
t = PhyloTree(tree, sp_naming_function=None)
#Check one leaf to see if species information is included
if t.get_leaves()[0].species == "Unknown":
t.set_species_naming_function(extract_species_code)
return t
def load_tree(f_tree, f_align):
# Tree style
ts = TreeStyle()
ts.show_leaf_name = True
ts.show_branch_length = True
ts.show_branch_support = True
ts.branch_vertical_margin = 10
# Load phylogenetic tree
tree = PhyloTree(f_tree.read())
if f_align is not None:
tree.link_to_alignment(f_align.read())
return tree, ts
def integrate_pwids_into_tree(tree, alignment):
'''Takes a tree and an alignment and returns a new tree with values of pwid added to each
node in the tree as node.pwid.'''
pt = PhyloTree(tree,alignment=alignment,alg_format="fasta")
for ind, node in enumerate(pt.traverse()):
node.node_kerf_name = 'node%s' % str(ind).zfill(3)
# For later kerf and sh functions
node.kerf_pass = False
node.sh_pass = False
if not node.is_leaf():
node.min_pwid = get_min_pwid_of_leaves(node.get_leaves())
else:
node.min_pwid = 1.0
return pt
def main():
fn=sys.argv[1]
nw=open(fn).readline()
species={}
t=PhyloTree(nw)
#set species naming function
t.set_species_naming_function(_get_spcode)
for l in t.get_leaves():
spCode=l.species
try: species[spCode]+=1
except: species[spCode] =1
for spCode in sorted( species, key=lambda x: species[x], reverse=True ):
print '%s\t%s' % ( spCode,species[spCode] )
def test_01tree_annotation(self):
t = PhyloTree( "((9598, 9606), 10090);", sp_naming_function=lambda name: name)
t.annotate_ncbi_taxa(dbfile=DATABASE_PATH)
self.assertEqual(t.sci_name, 'Euarchontoglires')
homi = (t&'9606').up
self.assertEqual(homi.sci_name, 'Homininae')
self.assertEqual(homi.taxid, 207598)
self.assertEqual(homi.rank, 'subfamily')
self.assertEqual(homi.named_lineage, [u'root', u'cellular organisms', u'Eukaryota', u'Opisthokonta', u'Metazoa', u'Eumetazoa', u'Bilateria', u'Deuterostomia', u'Chordata', u'Craniata', u'Vertebrata', u'Gnathostomata', u'Teleostomi', u'Euteleostomi', u'Sarcopterygii', u'Dipnotetrapodomorpha', u'Tetrapoda', u'Amniota', u'Mammalia', u'Theria', u'Eutheria', u'Boreoeutheria', u'Euarchontoglires', u'Primates', u'Haplorrhini', u'Simiiformes', u'Catarrhini', u'Hominoidea', u'Hominidae', u'Homininae'])
self.assertEqual(homi.lineage, [1, 131567, 2759, 33154, 33208, 6072, 33213, 33511, 7711, 89593, 7742, 7776, 117570, 117571, 8287, 1338369, 32523, 32524, 40674, 32525, 9347, 1437010, 314146, 9443, 376913, 314293, 9526, 314295, 9604, 207598] )
human = t&'9606'
self.assertEqual(human.sci_name, 'H**o sapiens')
self.assertEqual(human.taxid, 9606)
self.assertEqual(human.rank, 'species')
self.assertEqual(human.named_lineage, [u'root', u'cellular organisms', u'Eukaryota', u'Opisthokonta', u'Metazoa', u'Eumetazoa', u'Bilateria', u'Deuterostomia', u'Chordata', u'Craniata', u'Vertebrata', u'Gnathostomata', u'Teleostomi', u'Euteleostomi', u'Sarcopterygii', u'Dipnotetrapodomorpha', u'Tetrapoda', u'Amniota', u'Mammalia', u'Theria', u'Eutheria', u'Boreoeutheria', u'Euarchontoglires', u'Primates', u'Haplorrhini', u'Simiiformes', u'Catarrhini', u'Hominoidea', u'Hominidae', u'Homininae', u'H**o', u'H**o sapiens'])
self.assertEqual(human.lineage, [1, 131567, 2759, 33154, 33208, 6072, 33213, 33511, 7711, 89593, 7742, 7776, 117570, 117571, 8287, 1338369, 32523, 32524, 40674, 32525, 9347, 1437010, 314146, 9443, 376913, 314293, 9526, 314295, 9604, 207598, 9605, 9606])
def main():
fn = sys.argv[1]
nw = open(fn).readline()
species = {}
t = PhyloTree(nw)
#set species naming function
t.set_species_naming_function(_get_spcode)
for l in t.get_leaves():
spCode = l.species
try:
species[spCode] += 1
except:
species[spCode] = 1
for spCode in sorted(species, key=lambda x: species[x], reverse=True):
print '%s\t%s' % (spCode, species[spCode])
def phylomedump_tree_iterator( tarfn,verbose=0 ):
"""PhylomeDB all_trees.tar.gz dump treeobj generator."""
#open tarfile
if tarfn.endswith(".gz"):
tar = tarfile.open(tarfn, "r:gz")
else:
tar = tarfile.open(tarfn, "r")
i = k = 0
#process entries
for m in tar:
#if i>100: break
if not m.isfile():
continue
#load tree
if m.name.endswith(".nw"):
i += 1
#get nw
nw = tar.extractfile(m).readline()
t = PhyloTree(nw)
##add seedid and method info
#Phy000CWA9_YEAST.JTT.nw --> Phy000CWA9_YEAST JTT
seedid, method = os.path.basename(m.name).split(".")[:2]
t.seedid = seedid
t.method = method
#or add lk, seedid, method and lk to treeobj
elif m.name.endswith(".lk"):
seedid, method, lk = tar.extractfile(m).readline().split('\t')[:3]
t.lk = float(lk)
if not t.lk:
sys.stderr.write( " Err: Zero likelihood (%s) for: %s\n" % (t.lk, ", ".join((t.seedid, t.method))))
continue
if seedid!=t.seedid or t.method != method:
sys.stderr.write( " Err: Seedid and/or method doesn't match: %s\n" % ", ".join((seedid, t.seedid, method, t.method)))
continue
k += 1
if verbose and not i%100:
sys.stderr.write( " %6i\r" % i )
yield t
if verbose:
sys.stderr.write( " %s out of %s trees succesfully parsed [memory: %s KB]\n" % (k, i, resource.getrusage(resource.RUSAGE_SELF).ru_maxrss))
def get_tree(self, protid, method, phylome_id):
""" Returns the method-tree associated to a given protid. """
cmd = 'SELECT newick,lk FROM %s WHERE phylome_id=%s AND species="%s" AND protid="%s" AND method ="%s"' %\
(self._trees_table, phylome_id, protid[:3],protid[3:],method)
if self._SQL.execute(cmd):
entry = self._SQL.fetchone()
nw = entry[0]
lk = float(entry[1])
t = PhyloTree(nw)
else:
t = None
lk = None
return t, lk
def build_hmm_from_tree(tree_name, aln_name, msa_dir, hmm_dir):
'''
Reads tree and corresponding msa and create an MSA & HMM for each internal node.
'''
# Annotate internal nodes with name of corresponding HMM.
pt = PhyloTree(tree_name, alignment=aln_name, alg_format="fasta")
i_node = 0
for node in pt.traverse():
if not node.is_leaf():
node_name = 'node%s' % (str(i_node))
#print node_name
#print node
node.add_features(hmm=node_name)
i_node += 1
# make msa for node
msa_string = []
for leaf in node.iter_leaves():
msa_string.append(">%s" % leaf.name)
msa_string.append(str(leaf.sequence))
msa_string = '\n'.join(msa_string)
msa = open('%s%s.aln' % (msa_dir, node_name), 'w')
msa.write(msa_string)
msa.close()
# build HMM for node
check_call([
'build_hmmer3_hmm_from_alignment.py', '--name',
'%s%s' % (hmm_dir, node_name),
'%s%s.aln' % (msa_dir, node_name)
])
#concatenate HMMs into one file for Hmmscan
os.system('cat %s*.hmm > %sconcat.hmm' % (hmm_dir, hmm_dir))
return pt
def get_topology(taxids, intermediate_nodes=False, rank_limit=None):
from ete2 import PhyloTree
sp2track = {}
elem2node = {}
for sp in taxids:
track = deque()
lineage = get_sp_lineage(sp)
id2rank = get_ranks(lineage)
for elem in lineage:
node = elem2node.setdefault(elem, PhyloTree())
node.name = str(elem)
node.add_feature("rank", str(id2rank.get(int(elem), "?")))
track.append(node)
sp2track[sp] = track
# generate parent child relationships
for sp, track in sp2track.iteritems():
parent = None
for elem in track:
if parent and elem not in parent.children:
parent.add_child(elem)
if rank_limit and elem.rank == rank_limit:
break
parent = elem
root = elem2node[1]
# This fixes cases in which requested taxids are internal nodes
#for x in set(sp2track) - set([n.name for n in root.iter_leaves()]):
# new_leaf = sp2track[x][-1].copy()
# for ch in new_leaf.get_children():
# ch.detach()
# sp2track[x][-1].add_child(new_leaf)
#remove onechild-nodes
if not intermediate_nodes:
for n in root.get_descendants():
if len(n.children) == 1 and int(n.name) not in taxids:
n.delete(prevent_nondicotomic=False)
if len(root.children) == 1:
return root.children[0].detach()
else:
return root
def get_best_tree(self, protid, phylome_id):
""" Returns the winner ML tree"""
likelihoods = {}
winner_model = None
winner_lk = None
winner_newick = None
t = None
command ='SELECT newick,method,lk FROM %s WHERE phylome_id=%s AND species="%s" and protid="%s";' \
% (self._trees_table,phylome_id, protid[:3], protid[3:])
self._SQL.execute(command)
result = self._SQL.fetchall()
for r in result:
nw, m, lk = r
if lk < 0:
likelihoods[m] = lk
if winner_lk == None or lk > winner_lk:
winner_lk = lk
winner_model = m
winner_newick = nw
if winner_newick:
t = PhyloTree(winner_newick)
return winner_model, likelihoods, t
def test_01tree_annotation(self):
t = PhyloTree("((9598, 9606), 10090);", sp_naming_function=lambda name: name)
t.annotate_ncbi_taxa(dbfile=DATABASE_PATH)
self.assertEqual(t.sci_name, "Euarchontoglires")
homi = (t & "9606").up
self.assertEqual(homi.sci_name, "Homininae")
self.assertEqual(homi.taxid, 207598)
self.assertEqual(homi.rank, "subfamily")
self.assertEqual(
homi.named_lineage,
[
u"root",
u"cellular organisms",
u"Eukaryota",
u"Opisthokonta",
u"Metazoa",
u"Eumetazoa",
u"Bilateria",
u"Deuterostomia",
u"Chordata",
u"Craniata",
u"Vertebrata",
u"Gnathostomata",
u"Teleostomi",
u"Euteleostomi",
u"Sarcopterygii",
u"Dipnotetrapodomorpha",
u"Tetrapoda",
u"Amniota",
u"Mammalia",
u"Theria",
u"Eutheria",
u"Boreoeutheria",
u"Euarchontoglires",
u"Primates",
u"Haplorrhini",
u"Simiiformes",
u"Catarrhini",
u"Hominoidea",
u"Hominidae",
u"Homininae",
],
)
self.assertEqual(
homi.lineage,
[
1,
131567,
2759,
33154,
33208,
6072,
33213,
33511,
7711,
89593,
7742,
7776,
117570,
117571,
8287,
1338369,
32523,
32524,
40674,
32525,
9347,
1437010,
314146,
9443,
376913,
314293,
9526,
314295,
9604,
207598,
],
)
human = t & "9606"
self.assertEqual(human.sci_name, "H**o sapiens")
self.assertEqual(human.taxid, 9606)
self.assertEqual(human.rank, "species")
self.assertEqual(
human.named_lineage,
[
u"root",
u"cellular organisms",
u"Eukaryota",
u"Opisthokonta",
u"Metazoa",
u"Eumetazoa",
u"Bilateria",
u"Deuterostomia",
u"Chordata",
u"Craniata",
u"Vertebrata",
u"Gnathostomata",
u"Teleostomi",
u"Euteleostomi",
u"Sarcopterygii",
u"Dipnotetrapodomorpha",
u"Tetrapoda",
u"Amniota",
u"Mammalia",
u"Theria",
u"Eutheria",
u"Boreoeutheria",
u"Euarchontoglires",
u"Primates",
u"Haplorrhini",
u"Simiiformes",
u"Catarrhini",
u"Hominoidea",
u"Hominidae",
u"Homininae",
u"H**o",
u"H**o sapiens",
],
)
self.assertEqual(
human.lineage,
[
1,
131567,
2759,
33154,
33208,
6072,
33213,
33511,
7711,
89593,
7742,
7776,
117570,
117571,
8287,
1338369,
32523,
32524,
40674,
32525,
9347,
1437010,
314146,
9443,
376913,
314293,
9526,
314295,
9604,
207598,
9605,
9606,
],
)
parser.add_argument("--newick", dest="newick",
action="store_true", default="",
help=("print the extended newick format for provided tree using"
" ASCII representation and all its evolutionary events"
" before orthoXML export"))
args = parser.parse_args()
newick = args.tree[0]
SPECIES_NAME_POS = args.species_field
SPECIES_NAME_DELIMITER = args.species_delimiter
# load a phylomeDB Tree provided as a newick file in the command line
t = PhyloTree(newick, sp_naming_function=extract_spname)
if args.root:
if len(args.root) > 1:
outgroup = t.get_common_ancestor(args.root)
else:
outgroup = t & args.root[0]
t.set_outgroup(outgroup)
if not args.skip_ortholog_detection:
# detect speciation and duplication events using the species overlap
# algorithm used in phylomeDB
t.get_descendant_evol_events()
if args.ascii:
pie = PieChartFace([changes[node.name][0], changes[node.name][1]],
changes[node.name][2], changes[node.name][2],
["Green", "Red"])
pie.opacity = 0.5
#faces.add_face_to_node(name_face, node, column=0, position="branch-right")
faces.add_face_to_node(pie, node, column=0, position="float")
ts = TreeStyle()
# Do not add leaf names automatically ts.show_leaf_name = False
# Use my custom layout
ts.show_leaf_name = False
ts.layout_fn = my_layout
t = PhyloTree(
'/Volumes/MP_HD/Pm_Ts_Tf_Pf_comparison/4_spec_gene_gain_loss/eurot_gene_gain_loss/node_assignments_tree_nos_only_dbl.nwk',
format=1)
dataorder = [
'A. fumigatus', 'N. fisheri', 'A. clavatus', 'A. terreus', 'A. flavus',
'A. oryzae', 'A. niger', 'A. nidulans', 'P. decumbens', 'P. roquefortii',
'P. chrysogenum', 'P. digitatum', 'T. stipitatus', 'P. funiculosum',
'T. marneffei', 'T. flavus', 'A. dermatiditis', 'H. capsulatum',
'P. brasiliensis', 'C. immitis', 'U. reesei', 'T. equinum', 'T. tonsurans'
]
nos = [
"1", '2', '4', '6', '7', '8', '12', '14', '16', '17', '18', '19', '24',
'25', '26', '27', '32', '33', '35', '37', '38', '40', '41'
]
branch_to_node = {
def get_topology(self, taxids, intermediate_nodes=False, rank_limit=None, collapse_subspecies=False):
"""Given a list of taxid numbers, return the minimal pruned NCBI taxonomy tree
containing all of them.
:param False intermediate_nodes: If True, single child nodes
representing the complete lineage of leaf nodes are kept. Otherwise, the
tree is pruned to contain the first common ancestor of each group.
:param None rank_limit: If valid NCBI rank name is provided, the tree is
pruned at that given level. For instance, use rank="species" to get rid
of sub-species or strain leaf nodes.
"""
from ete2 import PhyloTree
sp2track = {}
elem2node = {}
for sp in taxids:
track = deque()
lineage = self.get_sp_lineage(sp)
id2rank = self.get_ranks(lineage)
for elem in lineage:
node = elem2node.setdefault(elem, PhyloTree())
node.name = str(elem)
node.add_feature("rank", str(id2rank.get(int(elem), "?")))
track.append(node)
sp2track[sp] = track
# generate parent child relationships
for sp, track in sp2track.iteritems():
parent = None
for elem in track:
if parent and elem not in parent.children:
parent.add_child(elem)
if rank_limit and elem.rank == rank_limit:
break
parent = elem
root = elem2node[1]
# This fixes cases in which requested taxids are internal nodes
#for x in set(sp2track) - set([n.name for n in root.iter_leaves()]):
# new_leaf = sp2track[x][-1].copy()
# for ch in new_leaf.get_children():
# ch.detach()
# sp2track[x][-1].add_child(new_leaf)
#remove onechild-nodes
if not intermediate_nodes:
for n in root.get_descendants():
if len(n.children) == 1 and int(n.name) not in taxids:
n.delete(prevent_nondicotomic=False)
if collapse_subspecies:
species_nodes = [n for n in t.traverse() if n.rank == "species"
if int(n.taxid) in all_taxids]
for sp_node in species_nodes:
bellow = sp_node.get_descendants()
if bellow:
# creates a copy of the species node
connector = sp_node.__class__()
for f in sp_node.features:
connector.add_feature(f, getattr(sp_node, f))
connector.name = connector.name + "{species}"
for n in bellow:
n.detach()
n.name = n.name + "{%s}" %n.rank
sp_node.add_child(n)
sp_node.add_child(connector)
sp_node.add_feature("collapse_subspecies", "1")
if len(root.children) == 1:
return root.children[0].detach()
else:
return root
def run(args):
from ete2 import Tree, PhyloTree
features = set()
for nw in args.src_tree_iterator:
if args.ncbi:
tree = PhyloTree(nw)
features.update(["taxid", "name", "rank", "bgcolor", "sci_name",
"collapse_subspecies", "named_lineage", "lineage"])
tree.annotate_ncbi_taxa(args.taxid_attr)
else:
tree = Tree(nw)
type2cast = {"str":str, "int":int, "float":float, "set":set, "list":list}
for annotation in args.feature:
aname, asource, amultiple, acast = None, None, False, str
for field in annotation:
try:
key, value = map(strip, field.split(":"))
except Exception:
raise ValueError("Invalid feature option [%s]" %field )
if key == "name":
aname = value
elif key == "source":
asource = value
elif key == "multiple":
#append
amultiple = value
elif key == "type":
try:
acast = type2cast[value]
except KeyError:
raise ValueError("Invalid feature type [%s]" %field)
else:
raise ValueError("Unknown feature option [%s]" %field)
if not aname and not asource:
ValueError('name and source are required when annotating a new feature [%s]'
% annotation)
features.add(aname)
for line in open(asource, 'rU'):
line = line.strip()
if not line or line.startswith('#'):
continue
nodenames, attr_value = map(strip, line.split('\t'))
nodenames = map(strip, nodenames.split(','))
relaxed_grouping = True
if nodenames[0].startswith('!'):
relaxed_grouping = False
nodenames[0] = nodenames[0][1:]
if len(nodenames) > 1:
target_node = tree.get_common_ancestor(nodenames)
if not relaxed_grouping:
pass
# do something
else:
target_node = tree & nodenames[0]
if hasattr(target_node, aname):
log.warning('Overwriting annotation for node" [%s]"' %nodenames)
else:
target_node.add_feature(aname, acast(attr_value))
dump(tree, features=features)
from ete2 import PhyloTree # Loads an example tree nw = """ ((Dme_001,Dme_002),(((Cfa_001,Mms_001),((Hsa_001,Ptr_001),Mmu_001)), (Ptr_002,(Hsa_002,Mmu_002)))); """ t = PhyloTree(nw) print t # /-Dme_001 # /--------| # | \-Dme_002 # | # | /-Cfa_001 # | /--------| #---------| | \-Mms_001 # | /--------| # | | | /-Hsa_001 # | | | /--------| # | | \--------| \-Ptr_001 # \--------| | # | \-Mmu_001 # | # | /-Ptr_002 # \--------| # | /-Hsa_002 # \--------| # \-Mmu_002 # # To obtain all the evolutionary events involving a given leaf node we # use get_my_evol_events method matches = t.search_nodes(name="Hsa_001")
["Green", "Red"])
pie.opacity = 0.5
#faces.add_face_to_node(name_face, node, column=0, position="branch-right")
faces.add_face_to_node(pie, node, column=0, position="float")
ts = TreeStyle()
# Do not add leaf names automatically ts.show_leaf_name = False
# Use my custom layout
ts.show_leaf_name = False
ts.layout_fn = my_layout
#t = PhyloTree('/Volumes/MP_HD/CI_GENOME_SEQ/CI_gene_coverage (generate stat for sig diff cov)/gene_copy_no_tree/CI_node_assignments_tree_nos.nwk', format=1)
t = PhyloTree(
'/Volumes/MP_HD/CI_GENOME_SEQ/CI_orthomcl_data/gain_loss_tree_frm_orthogroups/CI_badirate_branch_no_tree_no_names.nwk',
format=1)
#dataorder = ['FRR2161','FRR3841','FRR4059','FRR3840','F4','BR2SD2','BR2','BR2SD1','G09043','G11702','G11203SD4','G11203SD3','G11203','G11203SD1','G09027SD2','G09027SD1','G09027','FRR3871','FRR3482','HR2','G11012']
#nos = ["1",'2','4','5','7','10','11','13','15','17','19','20','22','24','26','27','29','32','33','35','37']
#dataorder = ['FRR2161','FRR3841','FRR3840','FRR4059','F4','BR2SD2','BR2','BR2SD1','G09043','G11702','G11203SD4','G11203SD3','G11203','G11203SD1','G09027SD2','G09027SD1','G09027','FRR3871','FRR3482','HR2','G11012']
#nos = ["1",'2','4','5','7','10','11','13','15','17','19','20','22','24','26','27','29','32','33','35','37']
#branch_to_node = {24:25,39:38,41:43,33:35,5:5,31:0,18:22,14:16,40:42,42:41,35:36,36:32,27:30,15:2,26:29,12:15,29:26,21:19,11:4,32:34,6:11,17:20,22:17,16:18,13:3,34:33,43:37,3:6,7:13,8:14,37:39,10:10,44:31,30:24,20:21,2:8,1:7,38:40,28:28,4:9,25:27,19:23,23:1,9:12}
#print branch_to_node
inchanges = open(
'/Volumes/MP_HD/CI_GENOME_SEQ/CI_orthomcl_data/gain_loss_tree_frm_orthogroups/CI_denovo_gene_gain_loss_table.txt',
'r')
def run(args):
if args.text_mode:
from ete2 import Tree
for tindex, tfile in enumerate(args.src_tree_iterator):
#print tfile
if args.raxml:
nw = re.sub(":(\d+\.\d+)\[(\d+)\]", ":\\1[&&NHX:support=\\2]", open(tfile).read())
t = Tree(nw)
else:
t = Tree(tfile)
print t.get_ascii(show_internal=args.show_internal_names,
attributes=args.show_attributes)
return
import random
import re
import colorsys
from collections import defaultdict
from ete2 import (Tree, PhyloTree, TextFace, RectFace, faces, TreeStyle,
add_face_to_node, random_color)
global FACES
if args.face:
FACES = parse_faces(args.face)
else:
FACES = []
# VISUALIZATION
ts = TreeStyle()
ts.mode = args.mode
ts.show_leaf_name = True
ts.tree_width = args.tree_width
for f in FACES:
if f["value"] == "@name":
ts.show_leaf_name = False
break
if args.as_ncbi:
ts.show_leaf_name = False
FACES.extend(parse_faces(
['value:@sci_name, size:10, fstyle:italic',
'value:@taxid, color:grey, size:6, format:" - %s"',
'value:@sci_name, color:steelblue, size:7, pos:b-top, nodetype:internal',
'value:@rank, color:indianred, size:6, pos:b-bottom, nodetype:internal',
]))
if args.alg:
FACES.extend(parse_faces(
['value:@sequence, size:10, pos:aligned, ftype:%s' %args.alg_type]
))
if args.heatmap:
FACES.extend(parse_faces(
['value:@name, size:10, pos:aligned, ftype:heatmap']
))
if args.bubbles:
for bubble in args.bubbles:
FACES.extend(parse_faces(
['value:@%s, pos:float, ftype:bubble, opacity:0.4' %bubble,
]))
ts.branch_vertical_margin = args.branch_separation
if args.show_support:
ts.show_branch_support = True
if args.show_branch_length:
ts.show_branch_length = True
if args.force_topology:
ts.force_topology = True
ts.layout_fn = lambda x: None
for tindex, tfile in enumerate(args.src_tree_iterator):
#print tfile
if args.raxml:
nw = re.sub(":(\d+\.\d+)\[(\d+)\]", ":\\1[&&NHX:support=\\2]", open(tfile).read())
t = PhyloTree(nw)
else:
t = PhyloTree(tfile)
if args.alg:
t.link_to_alignment(args.alg, alg_format=args.alg_format)
if args.heatmap:
DEFAULT_COLOR_SATURATION = 0.3
BASE_LIGHTNESS = 0.7
def gradient_color(value, max_value, saturation=0.5, hue=0.1):
def rgb2hex(rgb):
return '#%02x%02x%02x' % rgb
def hls2hex(h, l, s):
return rgb2hex( tuple(map(lambda x: int(x*255), colorsys.hls_to_rgb(h, l, s))))
lightness = 1 - (value * BASE_LIGHTNESS) / max_value
return hls2hex(hue, lightness, DEFAULT_COLOR_SATURATION)
heatmap_data = {}
max_value, min_value = None, None
for line in open(args.heatmap):
if line.startswith('#COLNAMES'):
pass
elif line.startswith('#') or not line.strip():
pass
else:
fields = line.split('\t')
name = fields[0].strip()
values = map(lambda x: float(x) if x else None, fields[1:])
maxv = max(values)
minv = min(values)
if max_value is None or maxv > max_value:
max_value = maxv
if min_value is None or minv < min_value:
min_value = minv
heatmap_data[name] = values
heatmap_center_value = 0
heatmap_color_center = "white"
heatmap_color_up = 0.3
heatmap_color_down = 0.7
heatmap_color_missing = "black"
heatmap_max_value = abs(heatmap_center_value - max_value)
heatmap_min_value = abs(heatmap_center_value - min_value)
if heatmap_center_value <= min_value:
heatmap_max_value = heatmap_min_value + heatmap_max_value
else:
heatmap_max_value = max(heatmap_min_value, heatmap_max_value)
# scale the tree
if not args.height:
args.height = None
if not args.width:
args.width = None
f2color = {}
f2last_seed = {}
for node in t.traverse():
node.img_style['size'] = 0
if len(node.children) == 1:
node.img_style['size'] = 2
node.img_style['shape'] = "square"
node.img_style['fgcolor'] = "steelblue"
ftype_pos = defaultdict(int)
for findex, f in enumerate(FACES):
if (f['nodetype'] == 'any' or
(f['nodetype'] == 'leaf' and node.is_leaf()) or
(f['nodetype'] == 'internal' and not node.is_leaf())):
# if node passes face filters
if node_matcher(node, f["filters"]):
if f["value"].startswith("@"):
fvalue = getattr(node, f["value"][1:], None)
else:
fvalue = f["value"]
# if node's attribute has content, generate face
if fvalue is not None:
fsize = f["size"]
fbgcolor = f["bgcolor"]
fcolor = f['color']
if fcolor:
# Parse color options
auto_m = re.search("auto\(([^)]*)\)", fcolor)
if auto_m:
target_attr = auto_m.groups()[0].strip()
if not target_attr :
color_keyattr = f["value"]
else:
color_keyattr = target_attr
color_keyattr = color_keyattr.lstrip('@')
color_bin = getattr(node, color_keyattr, None)
last_seed = f2last_seed.setdefault(color_keyattr, random.random())
seed = last_seed + 0.10 + random.uniform(0.1, 0.2)
f2last_seed[color_keyattr] = seed
fcolor = f2color.setdefault(color_bin, random_color(h=seed))
if fbgcolor:
# Parse color options
auto_m = re.search("auto\(([^)]*)\)", fbgcolor)
if auto_m:
target_attr = auto_m.groups()[0].strip()
if not target_attr :
color_keyattr = f["value"]
else:
color_keyattr = target_attr
color_keyattr = color_keyattr.lstrip('@')
color_bin = getattr(node, color_keyattr, None)
last_seed = f2last_seed.setdefault(color_keyattr, random.random())
seed = last_seed + 0.10 + random.uniform(0.1, 0.2)
f2last_seed[color_keyattr] = seed
fbgcolor = f2color.setdefault(color_bin, random_color(h=seed))
if f["ftype"] == "text":
if f.get("format", None):
fvalue = f["format"] % fvalue
F = TextFace(fvalue,
fsize = fsize,
fgcolor = fcolor or "black",
fstyle = f.get('fstyle', None))
elif f["ftype"] == "fullseq":
F = faces.SeqMotifFace(seq=fvalue, seq_format="seq",
seqtail_format="seq",
height=fsize)
elif f["ftype"] == "compactseq":
F = faces.SeqMotifFace(seq=fvalue, seq_format="compactseq",
seqtail_format="compactseq",
height=fsize)
elif f["ftype"] == "blockseq":
F = faces.SeqMotifFace(seq=fvalue, seq_format="blockseq",
seqtail_format="blockseq",
height=fsize,
fgcolor=fcolor or "slategrey",
bgcolor=fbgcolor or "slategrey",
scale_factor = 1.0)
fbgcolor = None
elif f["ftype"] == "bubble":
try:
v = float(fvalue)
except ValueError:
rad = fsize
else:
rad = fsize * v
F = faces.CircleFace(radius=rad, style="sphere",
color=fcolor or "steelblue")
elif f["ftype"] == "heatmap":
if not f['column']:
col = ftype_pos[f["pos"]]
else:
col = f["column"]
for i, value in enumerate(heatmap_data.get(node.name, [])):
ftype_pos[f["pos"]] += 1
if value is None:
color = heatmap_color_missing
elif value > heatmap_center_value:
color = gradient_color(abs(heatmap_center_value - value), heatmap_max_value, hue=heatmap_color_up)
elif value < heatmap_center_value:
color = gradient_color(abs(heatmap_center_value - value), heatmap_max_value, hue=heatmap_color_down)
else:
color = heatmap_color_center
node.add_face(RectFace(20, 20, color, color), position="aligned", column=col + i)
# Add header
# for i, name in enumerate(header):
# nameF = TextFace(name, fsize=7)
# nameF.rotation = -90
# tree_style.aligned_header.add_face(nameF, column=i)
F = None
elif f["ftype"] == "profile":
# internal profiles?
F = None
elif f["ftype"] == "barchart":
F = None
elif f["ftype"] == "piechart":
F = None
# Add the Face
if F:
F.opacity = f['opacity'] or 1.0
# Set face general attributes
if fbgcolor:
F.background.color = fbgcolor
if not f['column']:
col = ftype_pos[f["pos"]]
ftype_pos[f["pos"]] += 1
else:
col = f["column"]
node.add_face(F, column=col, position=f["pos"])
if args.image:
t.render("t%d.%s" %(tindex, args.image),
tree_style=ts, w=args.width, h=args.height, units=args.size_units)
else:
t.show(None, tree_style=ts)
log=open(log_file, "w")
except:
log=open("gephcort_run.log", "w")
# Logging start time
log.write("Start time: "+str(time.localtime()[0])+"-"+str(time.localtime()[2])+"-"+str(time.localtime()[1])+"\t"+str(time.localtime()[3])+":"+str(time.localtime()[4])+":"+str(time.localtime()[5])+"\n")
ape_objects={"delta.plot":"delta_plot", "dist.dna":"dist_dna", "dist.nodes":"dist_nodes", "node.depth":"node_depth",
"node.depth.edgelength":"node_depth_edgelength","node.height":"node_height", "node.height.clado":"node_height_clado",
"prop.part":"prop_part"}
ape=importr("ape", robject_translations = ape_objects) # Required for phangorn
ph=importr("phangorn") # Phylogenetic operations in R
print "All modules imported successfully"
t = PhyloTree(intree, alignment=seq, alg_format=seq_format) # Main tree containing entire sequence
dtp = PhyloTree(intree) # Dummy tree for phenotype shuffling
print "Tree file read successfully"
phenfile=open(phen, "r") # Phenotype file
phenlist=[]
for line in phenfile.readlines():
phenlist.append([line.split("\t")[0].strip(), line.split("\t")[1].strip()])
phenfile.close()
phenotype={} # Dictionary containing species names and their phenotype values
# Phenotype file should have two columns separated by tab containing taxa name
# in the first column and a numerical phenotype value in the second
#
if re.match(r"^OrAeBC5", gene): para_list += 1
if para_list > 0:
return (True)
else:
return (False)
# get tree files from directory
tree_files = os.listdir(str(sys.argv[1]))
for tree in tree_files:
if tree.startswith('RAxML_bipartitions.'):
# get orthogroup id
ortho = re.sub(r'\D', "", tree)
# load newick tree
#print(tree)
t = PhyloTree(tree)
#print(t)
evts = file('%s' '/' '%s' '.temp' % (events_dir, tree), "w")
##########################################################################################
# evolutionary events involving all taxa
##########################################################################################
# Alternatively, you can scan the whole tree topology
events = t.get_descendant_evol_events()
# print its orthology and paralogy relationships
for ev in events:
if ev.etype == "S":
evts.write(",".join(ev.in_seqs))
evts.write("<===>")
evts.write(",".join(ev.out_seqs))
evts.write("\n")
elif ev.etype == "D":
name2score[name] = "Fuzzy:%0.2f" %sim
for name in all_names:
taxid = name2id.get(name, "???")
realname = name2realname.get(name, name)
score = name2score.get(name, "Exact:1.0")
print "\t".join(map(str, [score, name, realname.capitalize(), taxid]))
if args.taxid_file:
all_taxids.extend(map(strip, open(args.taxid_file, "rU").read().split("\n")))
if args.taxid:
all_taxids.extend(args.taxid)
reftree = None
if args.reftree:
reftree = PhyloTree(args.reftree)
all_taxids.extend(list(set([n.name for n in reftree.iter_leaves()])))
if all_taxids and args.info:
log.info("Dumping %d taxid translations:" %len(all_taxids))
all_taxids = set(all_taxids)
all_taxids.discard("")
translator = get_taxid_translator(all_taxids)
for taxid, name in translator.iteritems():
lineage = get_sp_lineage(taxid)
named_lineage = ','.join(translate_to_names(lineage))
lineage = ','.join(map(str, lineage))
print "\t".join(map(str, [taxid, name, named_lineage, lineage ]))
for notfound in all_taxids - set(str(k) for k in translator.iterkeys()):
print >>sys.stderr, notfound, "NOT FOUND"
MAEAPDETIQQFMALTNVSHNIAVQYLSEFGDLNEAL--------------REEAH
"""
iphylip_txt = """
4 76
seqA MAEIPDETIQ QFMALT---H NIAVQYLSEF GDLNEALNSY YASQTDDIKD RREEAHQFMA
seqB MAEIPDATIQ QFMALTNVSH NIAVQY--EF GDLNEALNSY YAYQTDDQKD RREEAHQFMA
seqC MAEIPDATIQ ---ALTNVSH NIAVQYLSEF GDLNEALNSY YASQTDDQPD RREEAHQFMA
seqD MAEAPDETIQ QFMALTNVSH NIAVQYLSEF GDLNEAL--- ---------- -REEAHQ---
LTNVSHQFMA LTNVSH
LTNVSH---- ------
LTNVSH---- ------
-------FMA LTNVSH
"""
# Load a tree and link it to an alignment. As usual, 'alignment' can
# be the path to a file or data in text format.
t = PhyloTree("(((seqA,seqB),seqC),seqD);", alignment=fasta_txt, alg_format="fasta")
#We can now access the sequence of every leaf node
print "These are the nodes and its sequences:"
for leaf in t.iter_leaves():
print leaf.name, leaf.sequence
#seqD MAEAPDETIQQFMALTNVSHNIAVQYLSEFGDLNEAL--------------REEAH
#seqC MAEIPDATIQ---ALTNVSHNIAVQYLSEFGDLNEALNSYYASQTDDQPDRREEAH
#seqA MAEIPDETIQQFMALT---HNIAVQYLSEFGDLNEALNSYYASQTDDIKDRREEAH
#seqB MAEIPDATIQQFMALTNVSHNIAVQY--EFGDLNEALNSYYAYQTDDQKDRREEAH
#
# The associated alignment can be changed at any time
t.link_to_alignment(alignment=iphylip_txt, alg_format="iphylip")
# Let's check that sequences have changed
print "These are the nodes and its re-linked sequences:"
for leaf in t.iter_leaves():
'''
layout for CodemlTree
'''
if hasattr(node, "collapsed"):
if node.collapsed == 1:
node.img_style["draw_descendants"]= False
if node.is_leaf():
if hasattr (node, "sequence"):
seqface = MySequenceFace(node.sequence, "nt",
fsize=10,
col_w=11, interactive=True)
faces.add_face_to_node(seqface, node, 1, aligned=True)
if __name__ == "__main__":
tree = PhyloTree('(Orangutan,Human,Chimp);')
tree.link_to_alignment("""
>Chimp
HARWLNEKLRCELRTLKKLGLDGYKAVSQYVKGRA
>Orangutan
DARWINEKLRCVSRTLKKLGLDGYKGVSQYVKGRP
>Human
DARWHNVKLRCELRTLKKLGLVGFKAVSQFVIRRA
""")
nt_sequences = {"Human" : "GACGCACGGTGGCACAACGTAAAATTAAGATGTGAATTGAGAACTCTGAAAAAATTGGGACTGGTCGGCTTCAAGGCAGTAAGTCAATTCGTAATACGTCGTGCG",
"Chimp" : "CACGCCCGATGGCTCAACGAAAAGTTAAGATGCGAATTGAGAACTCTGAAAAAATTGGGACTGGACGGCTACAAGGCAGTAAGTCAGTACGTTAAAGGTCGTGCG",
"Orangutan": "GATGCACGCTGGATCAACGAAAAGTTAAGATGCGTATCGAGAACTCTGAAAAAATTGGGACTGGACGGCTACAAGGGAGTAAGTCAATACGTTAAAGGTCGTCCG"
}
for l in nt_sequences:
(tree & l).nt_sequence = nt_sequences[l]
tree.dist = 0
from ete2 import PhyloTree # Creates a gene phylogeny with several duplication events at # different levels. Note that we are using the default method for # detecting the species code of leaves (three first lettes in the node # name are considered the species code). nw = """ ((Dme_001,Dme_002),(((Cfa_001,Mms_001),((((Hsa_001,Hsa_003),Ptr_001) ,Mmu_001),((Hsa_004,Ptr_004),Mmu_004))),(Ptr_002,(Hsa_002,Mmu_002)))); """ t = PhyloTree(nw) print "Original tree:", print t # # /-Dme_001 # /--------| # | \-Dme_002 # | # | /-Cfa_001 # | /--------| # | | \-Mms_001 # | | #--| | /-Hsa_001 # | | /--------| # | /--------| /--------| \-Hsa_003 # | | | | | # | | | /--------| \-Ptr_001 # | | | | | # | | | | \-Mmu_001 # | | \--------| # \--------| | /-Hsa_004 # | | /--------|
from ete2 import PhyloTree # Loads a gene tree and its corresponding species tree. Note that # species names in sptree are the 3 firs letters of leaf nodes in # genetree. gene_tree_nw = '((Dme_001,Dme_002),(((Cfa_001,Mms_001),((Hsa_001,Ptr_001),Mmu_001)),(Ptr_002,(Hsa_002,Mmu_002))));' species_tree_nw = "((((Hsa, Ptr), Mmu), (Mms, Cfa)), Dme);" genetree = PhyloTree(gene_tree_nw) sptree = PhyloTree(species_tree_nw) print genetree # /-Dme_001 # /--------| # | \-Dme_002 # | # | /-Cfa_001 # | /--------| #---------| | \-Mms_001 # | /--------| # | | | /-Hsa_001 # | | | /--------| # | | \--------| \-Ptr_001 # \--------| | # | \-Mmu_001 # | # | /-Ptr_002 # \--------| # | /-Hsa_002 # \--------| # \-Mmu_002 # # Let's reconcile our genetree with the species tree
from ete2 import PhyloTree
# Reads a phylogenetic tree (using default species name encoding)
t = PhyloTree("(((Hsa_001,Ptr_001),(Cfa_001,Mms_001)),(Dme_001,Dme_002));")
# /-Hsa_001
# /--------|
# | \-Ptr_001
# /--------|
# | | /-Cfa_001
# | \--------|
#---------| \-Mms_001
# |
# | /-Dme_001
# \--------|
# \-Dme_002
#
# Prints current leaf names and species codes
print "Deafult mode:"
for n in t.get_leaves():
print "node:", n.name, "Species name:", n.species
# node: Dme_001 Species name: Dme
# node: Dme_002 Species name: Dme
# node: Hsa_001 Species name: Hsa
# node: Ptr_001 Species name: Ptr
# node: Cfa_001 Species name: Cfa
# node: Mms_001 Species name: Mms
#
# We can also use our own leaf name parsing function to obtain species
# names. All we need to do is create a python function that takes
# node's name as argument and return its corresponding species name.
def get_species_name(node_name_string):
# Species code is the first part of leaf name (separated by an
from Bio import SeqIO
from Bio import motifs
from Bio.Cluster import distancematrix
from Bio.Cluster import clustercentroids
records = list(SeqIO.parse("./txt/cm_perm_sequence_27_social.fasta", "fasta"))
for seq_record in SeqIO.parse("./txt/cm_perm_sequence_27_social.fasta", "fasta"):
print seq_record.id
print repr(seq_record.seq)
print len(seq_record)
from Bio.Align.Applications import ClustalwCommandline
clustalx = '/Applications/PhylogeneticAnalysis/clustalw2'
cline = ClustalwCommandline(clustalx, infile="./txt/cm_perm_sequence_27_social.fasta")
print cline
stdout, stderr = cline()
from Bio import Phylo
tree = Phylo.read("./txt/cm_perm_sequence_27_social.dnd", "newick")
tree.rooted = True
#Phylo.draw(tree)
from ete2 import Tree
from ete2 import PhyloTree
t = PhyloTree('./txt/cm_perm_sequence_27_social.dnd')
t.link_to_alignment(alignment="./txt/cm_perm_sequence_27_social.fasta", alg_format="fasta")
#from ete2 import ClusterTree
#t = ClusterTree('./txt/cm_perm_sequence_27_social.dnd')
t.show()
#t.show("heatmap")
#t.show("cluster_cbars")
#t.show("cluster_bars")
#t.show("cluster_lines")
### Add known sequences (adapters)
with open(temp_file_name, 'a') as f:
for name, seq in known_sequences.items():
f.write(">"+str(name)+"\n")
f.write(seq+"\n")
### Align
if verbose: print "aligning..."
aln_file_name = os.path.splitext(temp_file_name)[0] + ".afa"
align_muscle(temp_file_name, aln_file_name, gapopen=-1000.0)
### Build tree
if verbose: print "building tree..."
tree, aln = build_tree_FT(aln_file_name)
### Show in pretty format
pretty_tree = PhyloTree(str(tree), alignment=aln_file_name, alg_format="fasta")
pretty_tree.ladderize()
ts = TreeStyle()
pretty_tree.render(outfile, tree_style=ts)
### Clean up your mess
os.remove(temp_file_name)
os.remove(aln_file_name)
### TODO
# highlight adapter rows
# root on adapter?
import sys
from collections import defaultdict
from ete2 import PhyloTree
if len(sys.argv) > 1:
t = PhyloTree(sys.argv[1])
else:
t = PhyloTree()
#t.populate(5000, reuse_names=True, names_library=map(lambda x: "%03d" %x, range(100)))
#t.populate(5000, reuse_names=True, names_library=["aaa", "bbb", "ccc","dddd"])
#t.set_species_naming_function(lambda x: x[:3])
#t = PhyloTree("((((Kla0008018:0.226825,(Kwa0003593:0.270871,(((((((Sce0006606:0.020101,(Smi0000169:0.045626,Sku0001100:0.091634)0.9:0.021336)0.473:0.004546,Spa0001368:0)0.806:0.040152,Sba0000063:0.059101)0.967:0.124536,Sca0004780:0.57162)0.36:0.045976,Cgl0005705:0.244154)0.94:0.080608,(((Spa0003632:0.005291,Sce0012358:0.019313)0.879:0.014349,Smi0005102:0.031246)0.028:0.000541,(Sba0002319:0.027948,Sku0001858:0.037758)0.873:0.023849)0.995:0.14497)0.859:0.056767,(Sca0004490:0.235469,Kpo0005032:0.313188)0.699:0.077825)0.807:0.085287)0.523:0.049374)0.606:0.167197,Ago0006484:0.438321)0.976:0.605273,Cal0012751:1.95721)0.975:0.332581,(Cal0010356:0.478947,((Ago0007434:1.13211,Kwa0002043:1.20443)0.282:0.216219,(Skl0001126:0.276168,Cgl0008719:0.5381)0.454:0.191735)0.934:0.438082)0.975:0.332581);")
#t = PhyloTree("((((((AAA1, AAA2),((BBB1,BBB2), AAA3)D1),(CCC1,CCC2)), AAA8)D2, (((AAA5, AAA6),((BBB5,BBB6), AAA4)D3),(CCC3,CCC4)))D4, D);", format=1)
t = PhyloTree("((((((((AAA1, AAA2:0.111)a1,(((BBB1,ZZZ1)a2,MMM1)a3,AAA4)a4)a5, AAA3)a6,(AAA4, (AAA5, XXX1)a8)a9)a10,DDD)a11,DDD)a12,DDD)a13,DDD)root;", format=1)
print t.get_ascii()
ntrees, ndups, sp_trees = t.get_speciation_trees(map_features=["dist"])
for sptree in sp_trees:
print sptree.get_ascii(attributes=["dist"])
def __init__(self):
self.taxoDB = {}
self.tree = PhyloTree()
self.tree.name = "NoName"
def test_ncbi_compare(self): t = PhyloTree( "((9606, (9598, 9606)), 10090);", sp_naming_function=lambda x: x.name ) t.annotate_ncbi_taxa(dbfile=DATABASE_PATH)
#!/usr/bin/python
from __future__ import absolute_import
import sys
from ete2 import PhyloTree
if __name__ == "__main__":
t = sys.argv[1]
s = sys.argv[2]
out = sys.argv[3]
pt = PhyloTree(t)
# pt.link_to_alignment(alignment=s)
pt.render(out)
"delta.plot": "delta_plot",
"dist.dna": "dist_dna",
"dist.nodes": "dist_nodes",
"node.depth": "node_depth",
"node.depth.edgelength": "node_depth_edgelength",
"node.height": "node_height",
"node.height.clado": "node_height_clado",
"prop.part": "prop_part"
}
ape = importr("ape", robject_translations=ape_objects) # Required for phangorn
ph = importr("phangorn") # Phylogenetic operations in R
print "All modules imported successfully"
t = PhyloTree(intree, alignment=seq,
alg_format=seq_format) # Main tree containing entire sequence
dtp = PhyloTree(intree) # Dummy tree for phenotype shuffling
print "Tree file read successfully"
phenfile = open(phen, "r") # Phenotype file
phenlist = []
for line in phenfile.readlines():
phenlist.append([line.split("\t")[0].strip(), line.split("\t")[1].strip()])
phenfile.close()
phenotype = {
} # Dictionary containing species names and their phenotype values
# Phenotype file should have two columns separated by tab containing taxa name
# in the first column and a numerical phenotype value in the second
ts = TreeStyle()
# ts.mode = "c"
for i in open(in_id,"r").readlines():
i=i.strip('\n')
print i
outf = "/".join(in_id.split('/')[:-1])+"/top_hits_pm1_madss/"+i+"_blastp_hits_"+in_eval+".fasta"
no_hits = blast_gene(i,in_eval,indb,outf)
print no_hits
align_args = "/usr/local/bin/megacc -a "+ align_mao +" -o "+align_dir+" -s -d " + outf
subprocess.Popen(align_args, shell=True).wait()
sl(2)
align_lis = glob.glob(align_dir + "/*.meg")
alignpath = ''
for j in align_lis:
if i in j:
tree_args = "/usr/local/bin/megacc -a "+ tree_mao +" -o "+tree_dir+" -d " + j
subprocess.Popen(tree_args, shell=True).wait()
tree_ls = glob.glob(tree_dir + "/*.nwk")
for j in tree_ls:
if i in j and "consensus" not in j:
t = PhyloTree(j, format=1)
#t.show()
# t = Phylo.read(j,"newick")
# #t.ladderize()
# #Phylo.draw(t)
# Phylo.write(t,j.replace(".nwk",".xml"),"phyloxml")
# Phylo.draw_graphviz(t,prog="neato")
t.render(tree_dir+"/"+i+"_blastp_hits_"+in_eval+".pdf",tree_style=ts,dpi=200)
__author__ = 'mjohnpayne'
import sys
from ete2 import Tree, faces, AttrFace, TreeStyle, NodeStyle, PhyloTree, PieChartFace
import math
# infile = open('/Volumes/MP_HD/CI_GENOME_SEQ/CI_gene_coverage (generate stat for sig diff cov)/gene_copy_no_tree/CI_node_assignments_tree.nwk','r')
# outfile = open('/Volumes/MP_HD/CI_GENOME_SEQ/CI_gene_coverage (generate stat for sig diff cov)/gene_copy_no_tree/CI_node_assignments_tree_nos_only.nwk','w')
# infile = infile.read()
t = PhyloTree(
'/Volumes/MP_HD/CI_GENOME_SEQ/CI_gene_coverage (generate stat for sig diff cov)/gene_copy_no_tree/CI_node_assignments_tree.nwk',
format=1)
# ts = TreeStyle()
#
# t.show(tree_style=ts)
for node in t: #.iter_search_nodes():
# name = node.name
# name = name[name.find("_")+1:]
# node.name = name
print node.name
if node.name == "41":
node.dist = 5e-05
# t.write(outfile='/Volumes/MP_HD/CI_GENOME_SEQ/CI_gene_coverage (generate stat for sig diff cov)/gene_copy_no_tree/CI_node_assignments_tree_nos.nwk',format=1,)
ts = TreeStyle()
t.show(tree_style=ts)
def get_topology(self,
taxids,
intermediate_nodes=False,
rank_limit=None,
collapse_subspecies=False,
annotate=True):
"""Given a list of taxid numbers, return the minimal pruned NCBI taxonomy tree
containing all of them.
:param False intermediate_nodes: If True, single child nodes
representing the complete lineage of leaf nodes are kept. Otherwise, the
tree is pruned to contain the first common ancestor of each group.
:param None rank_limit: If valid NCBI rank name is provided, the tree is
pruned at that given level. For instance, use rank="species" to get rid
of sub-species or strain leaf nodes.
:param False collapse_subspecies: If True, any item under the species
rank will be collapsed into the species upper node.
"""
from ete2 import PhyloTree
sp2track = {}
elem2node = {}
for sp in taxids:
track = []
lineage = self.get_lineage(sp)
id2rank = self.get_rank(lineage)
for elem in lineage:
if elem not in elem2node:
node = elem2node.setdefault(elem, PhyloTree())
node.name = str(elem)
node.taxid = elem
node.add_feature("rank",
str(id2rank.get(int(elem), "no rank")))
else:
node = elem2node[elem]
track.append(node)
sp2track[sp] = track
# generate parent child relationships
for sp, track in sp2track.iteritems():
parent = None
for elem in track:
if parent and elem not in parent.children:
parent.add_child(elem)
if rank_limit and elem.rank == rank_limit:
break
parent = elem
root = elem2node[1]
#remove onechild-nodes
if not intermediate_nodes:
for n in root.get_descendants():
if len(n.children) == 1 and int(n.name) not in taxids:
n.delete(prevent_nondicotomic=False)
if len(root.children) == 1:
tree = root.children[0].detach()
else:
tree = root
if collapse_subspecies:
to_detach = []
for node in tree.traverse():
if node.rank == "species":
to_detach.extend(node.children)
for n in to_detach:
n.detach()
if annotate:
self.annotate_tree(tree)
return tree
realname = name2realname.get(name, name)
score = name2score.get(name, "Exact:1.0")
print "\t".join(
map(str,
[score, name, realname.capitalize(), taxid]))
if args.taxid_file:
all_taxids.extend(
map(strip,
open(args.taxid_file, "rU").read().split("\n")))
if args.taxid:
all_taxids.extend(args.taxid)
reftree = None
if args.reftree:
reftree = PhyloTree(args.reftree)
all_taxids.extend(list(set([n.name for n in reftree.iter_leaves()])))
if all_taxids and args.info:
log.info("Dumping %d taxid translations:" % len(all_taxids))
all_taxids = set(all_taxids)
all_taxids.discard("")
translator = get_taxid_translator(all_taxids)
for taxid, name in translator.iteritems():
lineage = get_sp_lineage(taxid)
named_lineage = ','.join(translate_to_names(lineage))
lineage = ','.join(map(str, lineage))
print "\t".join(map(str, [taxid, name, named_lineage, lineage]))
for notfound in all_taxids - set(
str(k) for k in translator.iterkeys()):
print >> sys.stderr, notfound, "NOT FOUND"
#!/usr/bin/python
####Python script that can take in a gene tree and detect paralogs and duplications; uses python module ete2
###linh c 6/5/2014
import sys
# Import ete2 module
from ete2 import PhyloTree
# Take in file input
file = sys.argv[1]
output = sys.argv[2]
# Load a tree structure from a newick file.
t = PhyloTree(file)
print t
# Alternatively, you can scan the whole tree topology
events = t.get_descendant_evol_events()
# Open output file
fo = open(output, "wb+")
# Print its orthology and paralogy relationships
fo.write( 'Events detected from the root of the tree,' + file + '\n')
for ev in events:
if ev.etype == "S":
fo.write ('ORTHOLOGY RELATIONSHIP:' + ','.join(ev.in_seqs) + '<====>' + ','.join(ev.out_seqs) + '\n')
elif ev.etype == "D":
exit()
# create output directory
events_dir = '%s' '/events' % (str(sys.argv[1]))
if not os.path.exists(events_dir):
os.makedirs(events_dir)
# get tree files from directory
tree_files = os.listdir(str(sys.argv[1]))
for tree in tree_files:
if re.match(r"^\d+\.fna\.aln.+\.tree", tree):
# get orthogroup id
ortho = re.sub(r'\D', "", tree)
# load newick tree
#print(tree)
t = PhyloTree(tree)
#print(t)
evts = file('%s' '/' '%s' '.temp' % (events_dir, tree), "w")
##########################################################################################
# evolutionary events involving all taxa
##########################################################################################
# Alternatively, you can scan the whole tree topology
events = t.get_descendant_evol_events()
# print its orthology and paralogy relationships
for ev in events:
if ev.etype == "S":
evts.write(",".join(ev.in_seqs))
evts.write("<===>")
evts.write(",".join(ev.out_seqs))
evts.write("\n")
elif ev.etype == "D":
def run(args):
from ete2 import Tree, PhyloTree
features = set()
for nw in args.src_tree_iterator:
if args.ncbi:
tree = PhyloTree(nw)
features.update([
"taxid", "name", "rank", "bgcolor", "sci_name",
"collapse_subspecies", "named_lineage", "lineage"
])
tree.annotate_ncbi_taxa(args.taxid_attr)
else:
tree = Tree(nw)
type2cast = {
"str": str,
"int": int,
"float": float,
"set": set,
"list": list
}
for annotation in args.feature:
aname, asource, amultiple, acast = None, None, False, str
for field in annotation:
try:
key, value = map(strip, field.split(":"))
except Exception:
raise ValueError("Invalid feature option [%s]" % field)
if key == "name":
aname = value
elif key == "source":
asource = value
elif key == "multiple":
#append
amultiple = value
elif key == "type":
try:
acast = type2cast[value]
except KeyError:
raise ValueError("Invalid feature type [%s]" % field)
else:
raise ValueError("Unknown feature option [%s]" % field)
if not aname and not asource:
ValueError(
'name and source are required when annotating a new feature [%s]'
% annotation)
features.add(aname)
for line in open(asource, 'rU'):
line = line.strip()
if not line or line.startswith('#'):
continue
nodenames, attr_value = map(strip, line.split('\t'))
nodenames = map(strip, nodenames.split(','))
relaxed_grouping = True
if nodenames[0].startswith('!'):
relaxed_grouping = False
nodenames[0] = nodenames[0][1:]
if len(nodenames) > 1:
target_node = tree.get_common_ancestor(nodenames)
if not relaxed_grouping:
pass
# do something
else:
target_node = tree & nodenames[0]
if hasattr(target_node, aname):
log.warning('Overwriting annotation for node" [%s]"' %
nodenames)
else:
target_node.add_feature(aname, acast(attr_value))
dump(tree, features=features)
