# | | | /---| /---| \-Hsa0010733 # | \---| | | | | # | | | | /---| \-Hsa0010710 # | | | | | | # | | /---| \---| \-Ptr0000001 # /---| | | | | # | | | | | \-Cfa0016699 # | | | | | # | | \---| | /-Rno0030248 # | | | \---| # | | | \-Mms0024821 # /---| | | # | | | \-Mdo0014718 # | | | # | | | /-Dre0008389 # /---| | \---| # | | | \-Fru0004507 # | | | # | | \-Cin0011238 #----| | # | \-Aga0007658 # | # |--Dme0014628 # | # \-Ddi0002240 # # Gets the best evolutionary model tree present in the phylome 1 for a given geneid winner_model, all_likelihoods, t = p.get_best_tree(geneid, 1) # As you can see, the best likelihood tree in this case was # reconstructed using a JTT model rather than the WAG matrix.
# | | | /---| /---| \-Hsa0010733 # | \---| | | | | # | | | | /---| \-Hsa0010710 # | | | | | | # | | /---| \---| \-Ptr0000001 # /---| | | | | # | | | | | \-Cfa0016699 # | | | | | # | | \---| | /-Rno0030248 # | | | \---| # | | | \-Mms0024821 # /---| | | # | | | \-Mdo0014718 # | | | # | | | /-Dre0008389 # /---| | \---| # | | | \-Fru0004507 # | | | # | | \-Cin0011238 #----| | # | \-Aga0007658 # | # |--Dme0014628 # | # \-Ddi0002240 # # Gets the best evolutionary model tree present in the phylome 1 for a given geneid winner_model, all_likelihoods, t = p.get_best_tree(geneid, 1) # As you can see, the best likelihood tree in this case was # reconstructed using a JTT model rather than the WAG matrix.
# This connects to the main phylomeDB server (default parameters)
p = PhylomeDBConnector()
PHYLOME_ID = 1
# This is the species code/age dictionary used to correctly root the
# tree in the human phylome. You can define your own, or use the
# midpoint outgroup method
species2age = {'Aga': 8, 'Ago': 9, 'Ame': 8, 'Ath': 10, 'Bta': 3, 'Cal': 9, 'Cbr': 8,\
'Cel': 8, 'Cfa': 3, 'Cgl': 9, 'Cin': 7, 'Cne': 9, 'Cre': 10, 'Ddi': 10, \
'Dha': 9, 'Dme': 8, 'Dre': 6, 'Ecu': 9, 'Fru': 6, 'Gga': 4, 'Gth': 10,\
'Gze': 9, 'Hsa': 1, 'Kla': 9, 'Lma': 10, 'Mdo': 3, 'Mms': 3, 'Mmu': 2,\
'Ncr': 9, 'Pfa': 10, 'Pte': 10, 'Ptr': 2, 'Pyo': 10, 'Rno': 3, 'Sce': 9,\
'Spb': 9, 'Tni': 6, 'Xtr': 5, 'Yli': 9 }
# Iterator over each sequence in the human proteme
for i, seqid in enumerate(p.get_seed_ids(PHYLOME_ID)):
if i > 2: break # Just process the first 2 ids
winner_model, lks, t = p.get_best_tree(seqid, PHYLOME_ID)
# If tree was sucsesfully reconstructed, runs the species overalp algorithm
if t and seqid in t:
outgroup = t.get_farthest_oldest_leaf(species2age)
# Returned outgroup is used to root the tree
t.set_outgroup(outgroup)
# Finds the node representing the seed sequence.
# We want the orthology relationships of such sequence.
seed_node = t.search_nodes(name=seqid)[0]
evol_events = seed_node.get_my_evol_events()
for ev in evol_events:
# Speciation event
if ev.etype == "S":
inparalogs = filter(lambda n: n.startswith("Hsa"), ev.in_seqs)
print 'ORTHOLOGY RELATIONSHIP:', ','.join(
inparalogs), "<===>", ','.join(ev.out_seqs)
from ete_dev import PhyloTree, PhylomeDBConnector, SeqGroup
p = PhylomeDBConnector()
w,x, t = p.get_best_tree("Hsa0000001", 1)
a, l = p.get_clean_alg("Hsa0000001", 1)
A = SeqGroup(a, "iphylip")
for s in A.id2seq:
A.id2seq[s]=A.id2seq[s][:30]
t.link_to_alignment(A)
print t.get_species()
print t
t.set_outgroup(t&"Ddi0002240")
sp = PhyloTree("(((((((((((Hsa, Ptr), Mmu), ((Mms, Rno), (Bta, Cfa))), Mdo), Gga), Xtr), (Dre, Fru))),Cin) (Dme, Aga)), Ddi);")
reconciled, evs = t.reconcile(sp)
print reconciled
reconciled.show()