def run_ptp(self, jp):
full_aln = SeqGroup(self.epa_alignment)
species_list = epa_2_ptp(epa_jp=jp,
ref_jp=self.refjson,
full_alignment=full_aln,
min_lw=0.5,
debug=self.cfg.debug)
self.cfg.log.debug("Species clusters:")
if fout:
fo2 = open(fout + ".species", "w")
else:
fo2 = None
for sp_cluster in species_list:
translated_taxa = []
for taxon in sp_cluster:
origin_taxon_name = EpacConfig.strip_query_prefix(taxon)
translated_taxa.append(origin_taxon_name)
s = ",".join(translated_taxa)
if fo2:
fo2.write(s + "\n")
self.cfg.log.debug(s)
if fo2:
fo2.close()
def classify(self, query_fname, fout = None, method = "1", minlw = 0.0, pv = 0.02, minp = 0.9, ptp = False):
if self.jplace_fname:
jp = EpaJsonParser(self.jplace_fname)
else:
self.checkinput(query_fname, minp)
raxml = RaxmlWrapper(config)
reftree_fname = self.cfg.tmp_fname("ref_%NAME%.tre")
self.refjson.get_raxml_readable_tree(reftree_fname)
optmod_fname = self.cfg.tmp_fname("%NAME%.opt")
self.refjson.get_binary_model(optmod_fname)
job_name = self.cfg.subst_name("epa_%NAME%")
reftree_str = self.refjson.get_raxml_readable_tree()
reftree = Tree(reftree_str)
self.reftree_size = len(reftree.get_leaves())
# IMPORTANT: set EPA heuristic rate based on tree size!
self.cfg.resolve_auto_settings(self.reftree_size)
# If we're loading the pre-optimized model, we MUST set the same rate het. mode as in the ref file
if self.cfg.epa_load_optmod:
self.cfg.raxml_model = self.refjson.get_ratehet_model()
reduced_align_fname = raxml.reduce_alignment(self.epa_alignment)
jp = raxml.run_epa(job_name, reduced_align_fname, reftree_fname, optmod_fname)
placements = jp.get_placement()
if fout:
fo = open(fout, "w")
else:
fo = None
output2 = ""
for place in placements:
output = None
taxon_name = place["n"][0]
origin_taxon_name = EpacConfig.strip_query_prefix(taxon_name)
edges = place["p"]
# edges = self.erlang_filter(edges, p = pv)
if len(edges) > 0:
ranks, lws = self.classify_helper.classify_seq(edges, method, minlw)
isnovo = self.novelty_check(place_edge = str(edges[0][0]), ranks =ranks, lws = lws, minlw = minlw)
rankout = self.print_ranks(ranks, lws, minlw)
if rankout == None:
output2 = output2 + origin_taxon_name+ "\t\t\t?\n"
else:
output = "%s\t%s\t" % (origin_taxon_name, self.print_ranks(ranks, lws, minlw))
if isnovo:
output += "*"
else:
output +="o"
if self.cfg.verbose:
print(output)
if fo:
fo.write(output + "\n")
else:
output2 = output2 + origin_taxon_name+ "\t\t\t?\n"
if os.path.exists(self.noalign):
with open(self.noalign) as fnoa:
lines = fnoa.readlines()
for line in lines:
taxon_name = line.strip()[1:]
origin_taxon_name = EpacConfig.strip_query_prefix(taxon_name)
output = "%s\t\t\t?" % origin_taxon_name
if self.cfg.verbose:
print(output)
if fo:
fo.write(output + "\n")
if self.cfg.verbose:
print(output2)
if fo:
fo.write(output2)
fo.close()
#############################################
#
# EPA-PTP species delimitation
#
#############################################
if ptp:
full_aln = SeqGroup(self.epa_alignment)
species_list = epa_2_ptp(epa_jp = jp, ref_jp = self.refjson, full_alignment = full_aln, min_lw = 0.5, debug = self.cfg.debug)
if self.cfg.verbose:
print "Species clusters:"
if fout:
fo2 = open(fout+".species", "w")
else:
fo2 = None
for sp_cluster in species_list:
translated_taxa = []
for taxon in sp_cluster:
origin_taxon_name = EpacConfig.strip_query_prefix(taxon)
translated_taxa.append(origin_taxon_name)
s = ",".join(translated_taxa)
if fo2:
fo2.write(s + "\n")
if self.cfg.verbose:
print s
if fo2:
fo2.close()
#############################################
if not self.jplace_fname:
if not self.cfg.debug:
raxml.cleanup(job_name)
FileUtils.remove_if_exists(reduced_align_fname)
FileUtils.remove_if_exists(reftree_fname)
FileUtils.remove_if_exists(optmod_fname)
def classify(self, query_fname, minp = 0.9, ptp = False):
if self.jplace_fname:
jp = EpaJsonParser(self.jplace_fname)
else:
self.checkinput(query_fname, minp)
self.cfg.log.info("Running RAxML-EPA to place %d query sequences...\n" % self.query_count)
raxml = RaxmlWrapper(config)
reftree_fname = self.cfg.tmp_fname("ref_%NAME%.tre")
self.refjson.get_raxml_readable_tree(reftree_fname)
optmod_fname = self.cfg.tmp_fname("%NAME%.opt")
self.refjson.get_binary_model(optmod_fname)
job_name = self.cfg.subst_name("epa_%NAME%")
reftree_str = self.refjson.get_raxml_readable_tree()
reftree = Tree(reftree_str)
self.reftree_size = len(reftree.get_leaves())
# IMPORTANT: set EPA heuristic rate based on tree size!
self.cfg.resolve_auto_settings(self.reftree_size)
# If we're loading the pre-optimized model, we MUST set the same rate het. mode as in the ref file
if self.cfg.epa_load_optmod:
self.cfg.raxml_model = self.refjson.get_ratehet_model()
reduced_align_fname = raxml.reduce_alignment(self.epa_alignment)
jp = raxml.run_epa(job_name, reduced_align_fname, reftree_fname, optmod_fname)
raxml.copy_epa_jplace(job_name, self.out_jplace_fname, move=True)
self.cfg.log.info("Assigning taxonomic labels based on EPA placements...\n")
placements = jp.get_placement()
if self.out_assign_fname:
fo = open(self.out_assign_fname, "w")
else:
fo = None
noassign_list = []
for place in placements:
taxon_name = place["n"][0]
origin_taxon_name = EpacConfig.strip_query_prefix(taxon_name)
edges = place["p"]
if len(edges) > 0:
ranks, lws = self.classify_helper.classify_seq(edges)
isnovo = self.novelty_check(place_edge = str(edges[0][0]), ranks=ranks, lws=lws)
rankout = self.print_ranks(ranks, lws, self.cfg.min_lhw)
if rankout == None:
noassign_list.append(origin_taxon_name)
else:
output = "%s\t%s\t" % (origin_taxon_name, rankout)
if isnovo:
output += "*"
else:
output +="o"
if self.cfg.verbose:
print(output)
if fo:
fo.write(output + "\n")
else:
noassign_list.append(origin_taxon_name)
if os.path.exists(self.noalign):
with open(self.noalign) as fnoa:
lines = fnoa.readlines()
for line in lines:
taxon_name = line.strip()[1:]
origin_taxon_name = EpacConfig.strip_query_prefix(taxon_name)
noassign_list.append(origin_taxon_name)
for taxon_name in noassign_list:
output = "%s\t\t\t?" % origin_taxon_name
if self.cfg.verbose:
print(output)
if fo:
fo.write(output + "\n")
if fo:
fo.close()
#############################################
#
# EPA-PTP species delimitation
#
#############################################
if ptp:
full_aln = SeqGroup(self.epa_alignment)
species_list = epa_2_ptp(epa_jp = jp, ref_jp = self.refjson, full_alignment = full_aln, min_lw = 0.5, debug = self.cfg.debug)
self.cfg.log.debug("Species clusters:")
if fout:
fo2 = open(fout+".species", "w")
else:
fo2 = None
for sp_cluster in species_list:
translated_taxa = []
for taxon in sp_cluster:
origin_taxon_name = EpacConfig.strip_query_prefix(taxon)
translated_taxa.append(origin_taxon_name)
s = ",".join(translated_taxa)
if fo2:
fo2.write(s + "\n")
self.cfg.log.debug(s)
if fo2:
fo2.close()
