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 check_seq_tax_labels(self, seq_name, orig_ranks, ranks, lws):
mislabel_lvl = -1
min_len = min(len(orig_ranks),len(ranks))
for rank_lvl in range(min_len):
if ranks[rank_lvl] != Taxonomy.EMPTY_RANK and ranks[rank_lvl] != orig_ranks[rank_lvl]:
mislabel_lvl = rank_lvl
break
if mislabel_lvl >= 0:
real_lvl = self.guess_rank_level(orig_ranks, mislabel_lvl)
mis_rec = {}
mis_rec['name'] = EpacConfig.strip_ref_prefix(seq_name)
mis_rec['orig_level'] = mislabel_lvl
mis_rec['real_level'] = real_lvl
mis_rec['level_name'] = self.rank_level_name(real_lvl)[1]
mis_rec['inv_level'] = -1 * real_lvl # just for sorting
mis_rec['orig_ranks'] = orig_ranks
mis_rec['ranks'] = ranks
mis_rec['lws'] = lws
mis_rec['conf'] = lws[mislabel_lvl]
self.mislabels.append(mis_rec)
return mis_rec
else:
return None
def get_noalign_list(self):
noalign_list = []
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)
noalign_list.append(origin_taxon_name)
return noalign_list
def setUp(self):
self.testfile_dir = os.path.join(
os.path.dirname(os.path.abspath(__file__)), "testfiles")
self.tax_fname = os.path.join(self.testfile_dir, "test_clean.tax")
self.taxonomy = Taxonomy(EpacConfig.REF_SEQ_PREFIX, self.tax_fname)
tax_map = self.taxonomy.get_map()
cfg = EpacConfig()
self.taxtree_helper = TaxTreeHelper(cfg, tax_map)
outgr_fname = os.path.join(self.testfile_dir, "outgroup.nw")
self.expected_outgr = Tree(outgr_fname)
def test_taxtree_builder(self):
cfg = EpacConfig()
testfile_dir = os.path.join(os.path.dirname(os.path.abspath(__file__)), "testfiles")
tax_fname = os.path.join(testfile_dir, "test.tax")
tax = Taxonomy(EpacConfig.REF_SEQ_PREFIX, tax_fname)
tree_fname = os.path.join(testfile_dir, "taxtree.nw")
expected_tree = Tree(tree_fname, format=8)
tb = TaxTreeBuilder(cfg, tax)
tax_tree, seq_ids = tb.build()
self.assertEqual(seq_ids, tax.get_map().keys())
self.assertEqual(tax_tree.write(format=8), expected_tree.write(format=8))
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)
jp = self.run_epa()
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"]
ranks, lws = self.classify_helper.classify_seq(edges)
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 self.cfg.check_novelty:
isnovo = self.novelty_check(place_edge=str(edges[0][0]),
ranks=ranks,
lws=lws)
output += "*" if isnovo else "o"
self.print_result_line(fo, output)
noassign_list += self.get_noalign_list()
for taxon_name in noassign_list:
output = "%s\t\t\t?" % origin_taxon_name
self.print_result_line(fo, output)
if fo:
fo.close()
#############################################
#
# EPA-PTP species delimitation
#
#############################################
if ptp:
self.run_ptp(jp)
def check_seq_ids(self):
# check that seq IDs in taxonomy and alignment correspond
self.mis_ids = []
for sid in self.taxonomy.seq_ranks_map.iterkeys():
unprefixed_sid = EpacConfig.strip_ref_prefix(sid)
if not self.alignment.has_seq(unprefixed_sid):
self.mis_ids.append(unprefixed_sid)
if len(self.mis_ids) > 0 and self.verbose:
errmsg = "ERROR: Following %d sequence(s) are missing in your alignment file:\n%s\n\n" % (len(self.mis_ids), "\n".join(self.mis_ids))
errmsg += "Please make sure sequence IDs in taxonomic annotation file and in alignment are identical!\n"
self.cfg.exit_user_error(errmsg)
return self.mis_ids
def check_seq_ids(self):
# check that seq IDs in taxonomy and alignment correspond
self.mis_ids = []
for sid in self.taxonomy.seq_ranks_map.iterkeys():
unprefixed_sid = EpacConfig.strip_ref_prefix(sid)
if not self.alignment.has_seq(unprefixed_sid):
self.mis_ids.append(unprefixed_sid)
if len(self.mis_ids) > 0 and self.verbose:
errmsg = "ERROR: Following %d sequence(s) are missing in your alignment file:\n%s\n\n" % (
len(self.mis_ids), "\n".join(self.mis_ids))
errmsg += "Please make sure sequence IDs in taxonomic annotation file and in alignment are identical!\n"
self.cfg.exit_user_error(errmsg)
return self.mis_ids
def mis_rec_to_string(self, mis_rec):
lvl = mis_rec['orig_level']
uncorr_name = EpacConfig.strip_ref_prefix(self.refjson.get_uncorr_seqid(mis_rec['name']))
uncorr_orig_ranks = self.refjson.get_uncorr_ranks(mis_rec['orig_ranks'])
uncorr_ranks = self.refjson.get_uncorr_ranks(mis_rec['ranks'])
output = uncorr_name + "\t"
if lvl >= 0:
output += "%s\t%s\t%s\t%.3f\t" % (mis_rec['level_name'],
uncorr_orig_ranks[lvl], uncorr_ranks[lvl], mis_rec['lws'][lvl])
else:
output += "%s\t%s\t%s\t%.3f\t" % (mis_rec['level_name'],
"NA", "NA", mis_rec['lws'][0])
output += Taxonomy.lineage_str(uncorr_orig_ranks) + "\t"
output += Taxonomy.lineage_str(uncorr_ranks) + "\t"
output += ";".join(["%.3f" % conf for conf in mis_rec['lws']])
if 'rank_conf' in mis_rec:
output += "\t%.3f" % mis_rec['rank_conf']
return output
def mis_rec_to_string(self, mis_rec):
lvl = mis_rec['orig_level']
uncorr_name = EpacConfig.strip_ref_prefix(
self.refjson.get_uncorr_seqid(mis_rec['name']))
uncorr_orig_ranks = self.refjson.get_uncorr_ranks(
mis_rec['orig_ranks'])
uncorr_ranks = self.refjson.get_uncorr_ranks(mis_rec['ranks'])
output = uncorr_name + "\t"
if lvl >= 0:
output += "%s\t%s\t%s\t%.3f\t" % (
mis_rec['level_name'], uncorr_orig_ranks[lvl],
uncorr_ranks[lvl], mis_rec['lws'][lvl])
else:
output += "%s\t%s\t%s\t%.3f\t" % (mis_rec['level_name'], "NA",
"NA", mis_rec['lws'][0])
output += Taxonomy.lineage_str(uncorr_orig_ranks) + "\t"
output += Taxonomy.lineage_str(uncorr_ranks) + "\t"
output += ";".join(["%.3f" % conf for conf in mis_rec['lws']])
if 'rank_conf' in mis_rec:
output += "\t%.3f" % mis_rec['rank_conf']
return output
def test_epac_config(self):
args = self.get_default_namespace()
cfg = EpacConfig(args)
self.check_common_config(cfg)
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 setUp(self):
self.cfg = EpacConfig()
self.testfile_dir = os.path.join(
os.path.dirname(os.path.abspath(__file__)), "testfiles")
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()
