def report_taxa(tree_file, scheme='newick', listing=True, counting=True):
a_tree = Tree()
a_tree.read_from_path(tree_file, scheme)
if listing:
for leaf in a_tree.leaf_nodes():
print(leaf.taxon.label)
if counting:
print('Taxa #: ' + str(len(a_tree.leaf_nodes())))
def is_valid_newick(path, source_sequence_names = None):
"""Is the file located at 'path' a valid newick-formatted tree?
This method returns the tuple (True/False, error message)
if source_sequence_names != None, then the tree should contain taxa from the list of sequence names."""
retflag = False
emsg = ""
try:
test_tree = Tree()
test_tree.read_from_path(path, "newick")
except Exception as e:
emsg = e.__str__()
else:
retflag = True
return (retflag, emsg)
def get_bls(tree_path):
# clean the tree of any support values, so we're left only with BLs
bls = []
t = Tree()
t.read_from_path( tree_path, "newick" )
i = t.level_order_edge_iter()
while True:
try:
e = i.next() # in Python 2.x
len = e.length
if len != None:
bls.append( len )
except StopIteration:
break
return bls
def pretty_print_trees():
print "\n. OK, I'm reformatting the RAxML results for nice printing..."
"""Reformats the phylogeny, such that each taxon label looks like this:
trna12-AlaTCT[6/7]
. . . where 6 is the number of sequences collapsed into this sequence, and 7 is the number of total tRNAs in the databse."""
species_list = species_trna_seq.keys()
species_list.sort()
for species in species_list:
#print species_trna_dups[species]
treepath = RAXMLDIR + "/RAxML_result." + species
if False == os.path.exists( treepath ):
continue
newtreepath = TREEDIR + "/" + species + ".tree"
t = Tree()
t.read_from_path(treepath, "newick")
print " -->", treepath
trna_count = count_trna_types(species)
#print trna_count
newts = t.__str__()
for taxon in t.taxon_set:
#print "372:", taxon.label
#thisac = get_ac_from_name(taxon.label)
thisac = species_trna_mtrip[species][taxon.label]
count_this_type = trna_count[thisac]
count_dups = 0
if taxon.label in species_trna_dups[species]:
count_dups = species_trna_dups[species][taxon.label].__len__() + 1
if count_dups <= 1:
count_dups = ""
else:
count_dups = "(" + count_dups.__str__() + ")"
mark = ""
if species in species_switchedtrnas:
print "534:", species_switchedtrnas[species]
if species_switchedtrnas[species].__contains__(taxon.label):
mark = "***"
newts = re.sub( taxon.label, (taxon.label + count_dups + "[" + count_this_type.__str__()+ "]" + mark), newts)
fout = open(newtreepath, "w")
fout.write( newts + "\n" )
fout.close()
import os import sys from dendropy import Tree t1path = sys.argv[1] t2path = sys.argv[2] t1 = Tree() t1.read_from_path(t1path, "newick") t2 = Tree() t2.read_from_path(t2path, "newick") s = t1.symmetric_difference(t2) s = t2.symmetric_difference(t1) print "symmetric diff. = ", s print t1.length() print t2.length()
def read_from_path(filename, schema="newick", taxon_set=None):
t = Tree(taxon_set=taxon_set)
t.read_from_path(filename, schema)
return PhylogeneticTree(t)
import os import sys from dendropy import Tree t1path = sys.argv[1] t2path = sys.argv[2] t1 = Tree() t1.read_from_path(t1path, "newick") t2 = Tree() t2.read_from_path(t2path, "newick") s = t1.symmetric_difference(t2) s = t2.symmetric_difference(t1) print "symmetric diff. = ", s print t1.length() print t2.length()
def find_anticodon_switches():
print "\n. OK, I'm searching for switched anticodons. . ."
species_list = species_trna_seq.keys()
species_list.sort()
#print "504:", species_list
allpath = DATADIR + "/all.acswitches.txt"
allout = open(allpath, "w")
allout.write("Species\tKingdom\tswitch type\tfrom\tto\td_diff\td_same\n")
#
# FOR EACH SPECIES. . .
#
for species in species_list:
if species in species_kingdom:
this_kingdom = species_kingdom[species]
else:
this_kingdom = "???"
print species
rpath = SUMMARYDIR + "/" + species + ".acswitches.txt"
treepath = RAXMLDIR + "/RAxML_result." + species
if os.path.exists(treepath):
species_nscount[species] = 0
species_scount[species] = 0
species_ac_nscount[species] = {}
species_ac_scount[species] = {}
fout = open(rpath, "w") # a summary of found ac switches will be written here.
t = Tree()
t.read_from_path(treepath, "newick")
print "\n. Calculating all pairwise distances between sequences on tree:", treepath
pdm = treecalc.PatristicDistanceMatrix(t) # matrix of pairwise distances between taxa
asses_monophyly(t, species)
# First, sort the leaf nodes by their anticodon preference.
ac_labels = {} # key = a.c., value = list of Node objects
for i, t1 in enumerate(t.taxon_set):
#thisac = get_ac_from_name( t1.label )
thisac = species_trna_mtrip[species][t1.label]
if thisac not in ac_labels:
ac_labels[ thisac ] = []
ac_labels[ thisac ].append( t1.label )
#
# FOR EACH tRNA SEQUENCE. . .
# Goal: for each tRNA find the min. distance to another tRNA with the same
# anticodon, then find the min. distance to another tRNA that is of a different
# anticodon type.
print "\."
for i, t1 in enumerate(t.taxon_set):
min2same = None
min2diff = None
closest_diff = None # taxon label of closest same-anti-codon tRNA sequence to sequence t1.
closest_same = None
#myac = get_ac_from_name(t1.label)
myac = species_trna_mtrip[species][t1.label]
#print t1.label
if ac_labels[myac].__len__() <= 1:
continue # skip tRNAs for which they are the only representative of their AC.
ac_labels[myac].remove( t1.label )
myaa = get_aa_from_name(t1.label)
if myaa == "Met":
continue
for t2 in t.taxon_set:
if t1 == t2:
continue
#thisac = get_ac_from_name(t2.label)
thisac = species_trna_mtrip[species][t2.label]
d = pdm(t1, t2)
if myac == thisac:
if min2same == None:
min2same = d
closest_same = t2.label
elif min2same > d:
min2same = d
closest_same = t2.label
elif myac != thisac and ac_labels[thisac].__len__() > 1:
if min2diff == None:
min2diff = d
closest_diff = t2.label
elif min2diff > d:
min2diff = d
closest_diff = t2.label
if min2same == None:
min2same = 0.0 # in the event of singletons
if min2diff == None:
min2diff = 0.0 # in the event of sparse genomes with few tRNAs.
if closest_diff == None:
continue
if min2same > min2diff and min2same-min2diff > SWITCH_DIFF_THRESHOLD and min2diff != None and min2same > SWITCH_DISTANCE_THRESHOLD:
# . . . then we've identified an anticodon shift:
if species not in species_switchedtrnas:
species_switchedtrnas[species] = []
if t1.label not in species_switchedtrnas[species]:
species_switchedtrnas[species].append( t1.label )
thataa = get_aa_from_name(closest_diff)
if thataa == myaa: # synonymous shift
species_scount[species] += 1
fout.write("Synonymous" + " " + closest_diff + " -> " + t1.label + "\t" + min2diff.__str__() + "\t" + min2same.__str__() + "\n")
allout.write(species + "\t" + this_kingdom + "\tSY\t" + closest_diff + "\t" + t1.label + "\t%.4f"%min2diff + "\t%.3f"%min2same + "\n")
print " . Syn." + " " + closest_diff + " -> " + t1.label + "\t" + min2diff.__str__() + "\t" + min2same.__str__()
if myac not in species_ac_scount[species]:
species_ac_scount[species][myac] = 1
else:
species_ac_scount[species][myac] += 1
elif thataa != myaa and thataa != "Met": # nonsynonymous shift
species_nscount[species] += 1
fout.write("Nonsynonymous" + " " + closest_diff + " -> " + t1.label + "\t" + min2diff.__str__() + "\t" + min2same.__str__() + "\n")
allout.write(species + "\t" + this_kingdom + "\tNS\t" + closest_diff + "\t" + t1.label + "\t%.4f"%min2diff + "\t%.3f"%min2same + "\n")
print " . Nonsyn." + " " + closest_diff + " -> " + t1.label + "\t" + min2diff.__str__() + "\t" + min2same.__str__()
if myac not in species_ac_nscount[species]:
species_ac_nscount[species][myac] = 1
else:
species_ac_nscount[species][myac] += 1
if species_nscount[species] == 0 and species_scount[species] == 0:
fout.write("No detected switched anitcodons for " + species + "\n")
fout.close()
print ".", species, "has", species_nscount[species], "putative nonsynonymously switched anticodons."
print ".", species, "has", species_scount[species], "putative synonymously switched anticodons."
else:
print ". I skipped species", species, "because I can't find the ML tree."
allout.close()
def get_tree_length(path):
"""Input: path to newick tree. Returns the sum of branches on the tree."""
t = Tree()
t.read_from_path(path, "newick")
return t.length()
