def parse_hsps(self, hit_placeholders):
"""Parse a HMMER2 hsp block, beginning with the hsp table."""
# HSPs may occur in different order than the hits
# so store Hit objects separately first
unordered_hits = {}
while self.read_next():
if (
self.line.startswith("Alignments")
or self.line.startswith("Histogram")
or self.line == "//"
):
break
if (
self.line.startswith("Model")
or self.line.startswith("Sequence")
or self.line.startswith("--------")
):
continue
id_, domain, seq_f, seq_t, seq_compl, hmm_f, hmm_t, hmm_compl, score, evalue = (
self.line.split()
)
frag = HSPFragment(id_, self.qresult.id)
frag.alphabet = generic_protein
if self._meta["program"] == "hmmpfam":
frag.hit_start = int(hmm_f) - 1
frag.hit_end = int(hmm_t)
frag.query_start = int(seq_f) - 1
frag.query_end = int(seq_t)
elif self._meta["program"] == "hmmsearch":
frag.query_start = int(hmm_f) - 1
frag.query_end = int(hmm_t)
frag.hit_start = int(seq_f) - 1
frag.hit_end = int(seq_t)
hsp = HSP([frag])
hsp.evalue = float(evalue)
hsp.bitscore = float(score)
hsp.domain_index = int(domain.split("/")[0])
if self._meta["program"] == "hmmpfam":
hsp.hit_endtype = hmm_compl
hsp.query_endtype = seq_compl
elif self._meta["program"] == "hmmsearch":
hsp.query_endtype = hmm_compl
hsp.hit_endtype = seq_compl
if id_ not in unordered_hits:
placeholder = [p for p in hit_placeholders if p.id_ == id_][0]
hit = placeholder.createHit([hsp])
unordered_hits[id_] = hit
else:
hit = unordered_hits[id_]
hsp.hit_description = hit.description
hit.append(hsp)
# The placeholder list is in the correct order, so use that order for
# the Hit objects in the qresult
for p in hit_placeholders:
self.qresult.append(unordered_hits[p.id_])
def parse_hsps(self, hit_placeholders):
"""Parse a HMMER2 hsp block, beginning with the hsp table."""
# HSPs may occur in different order than the hits
# so store Hit objects separately first
unordered_hits = {}
while self.read_next():
if self.line.startswith('Alignments') or \
self.line.startswith('Histogram') or \
self.line == '//':
break
if self.line.startswith('Model') or \
self.line.startswith('Sequence') or \
self.line.startswith('--------'):
continue
id_, domain, seq_f, seq_t, seq_compl, hmm_f, hmm_t, hmm_compl, \
score, evalue = self.line.split()
frag = HSPFragment(id_, self.qresult.id)
frag.alphabet = generic_protein
if self._meta['program'] == 'hmmpfam':
frag.hit_start = int(hmm_f) - 1
frag.hit_end = int(hmm_t)
frag.query_start = int(seq_f) - 1
frag.query_end = int(seq_t)
elif self._meta['program'] == 'hmmsearch':
frag.query_start = int(hmm_f) - 1
frag.query_end = int(hmm_t)
frag.hit_start = int(seq_f) - 1
frag.hit_end = int(seq_t)
hsp = HSP([frag])
hsp.evalue = float(evalue)
hsp.bitscore = float(score)
hsp.domain_index = int(domain.split('/')[0])
if self._meta['program'] == 'hmmpfam':
hsp.hit_endtype = hmm_compl
hsp.query_endtype = seq_compl
elif self._meta['program'] == 'hmmsearch':
hsp.query_endtype = hmm_compl
hsp.hit_endtype = seq_compl
if id_ not in unordered_hits:
placeholder = [ p for p in hit_placeholders if p.id_ == id_][0]
hit = placeholder.createHit([hsp])
unordered_hits[id_] = hit
else:
hit = unordered_hits[id_]
hsp.hit_description = hit.description
hit.append(hsp)
# The placeholder list is in the correct order, so use that order for
# the Hit objects in the qresult
for p in hit_placeholders:
self.qresult.append(unordered_hits[p.id_])
def _create_qresult(self, hit_blocks):
"""Create the Biopython data structures from the parsed data (PRIVATE)."""
query_id = self.query_id
hit_dict = OrderedDict()
for output_index, block in enumerate(hit_blocks):
hit_id = block['hit_id']
frag = HSPFragment(hit_id, query_id)
# frag.alphabet = generic_protein
if block['query_start']:
frag.query_start = block['query_start'] - 1
else:
frag.query_start = block['query_start']
frag.query_end = block['query_end']
if block['hit_start']:
frag.hit_start = block['hit_start'] - 1
else:
frag.hit_start = block['hit_start']
frag.hit_end = block['hit_end']
frag.hit = block['hit_seq']
frag.query = block['query_seq']
hsp = HSP([frag])
hsp.hit_id = hit_id
hsp.output_index = output_index
hsp.query_id = query_id
hsp.hit_description = block['description']
is_included = True # Should everything should be included?
hsp.is_included = is_included
hsp.evalue = block['evalue']
hsp.score = block['score']
hsp.prob = block['prob']
hsp.hit_seq_len = block['hit_seq_len']
hsp.text = block['text']
if hit_id not in hit_dict:
hit = Hit([hsp], hit_id)
hit.description = block['description']
hit.is_included = is_included
hit.evalue = block['evalue']
hit.score = block['score']
hit_dict[hit_id] = hit
else:
hit_dict[hit_id].append(hsp)
qresult = QueryResult(hit_dict.values(), query_id)
qresult.program = _PROGRAM
qresult.seq_len = self.seq_len
return [qresult]
def _create_qresult(self, hit_blocks):
"""Create the Biopython data structures from the parsed data (PRIVATE)."""
query_id = self.query_id
hit_dict = OrderedDict()
for output_index, block in enumerate(hit_blocks):
hit_id = block["hit_id"]
frag = HSPFragment(hit_id, query_id)
frag.molecule_type = "protein"
frag.query_start = block["query_start"] - 1
frag.query_end = block["query_end"]
frag.hit_start = block["hit_start"] - 1
frag.hit_end = block["hit_end"]
frag.hit = block["hit_seq"]
frag.query = block["query_seq"]
hsp = HSP([frag])
hsp.hit_id = hit_id
hsp.output_index = output_index
hsp.query_id = query_id
hsp.hit_description = block["description"]
is_included = True # Should everything should be included?
hsp.is_included = is_included
hsp.evalue = block["evalue"]
hsp.score = block["score"]
hsp.prob = block["prob"]
if hit_id not in hit_dict:
hit = Hit([hsp], hit_id)
hit.description = block["description"]
hit.is_included = is_included
hit.evalue = block["evalue"]
hit.score = block["score"]
hit_dict[hit_id] = hit
else:
hit_dict[hit_id].append(hsp)
qresult = QueryResult(hit_dict.values(), query_id)
qresult.program = _PROGRAM
qresult.seq_len = self.seq_len
return [qresult]
def _create_qresult(self, hit_blocks):
"""Create the Biopython data structures from the parsed data (PRIVATE)."""
query_id = self.query_id
hit_dict = OrderedDict()
for output_index, block in enumerate(hit_blocks):
hit_id = block['hit_id']
frag = HSPFragment(hit_id, query_id)
frag.alphabet = generic_protein
frag.query_start = block['query_start'] - 1
frag.query_end = block['query_end']
frag.hit_start = block['hit_start'] - 1
frag.hit_end = block['hit_end']
frag.hit = block['hit_seq']
frag.query = block['query_seq']
hsp = HSP([frag])
hsp.hit_id = hit_id
hsp.output_index = output_index
hsp.query_id = query_id
hsp.hit_description = block['description']
is_included = True # Should everything should be included?
hsp.is_included = is_included
hsp.evalue = block['evalue']
hsp.score = block['score']
hsp.prob = block['prob']
if hit_id not in hit_dict:
hit = Hit([hsp], hit_id)
hit.description = block['description']
hit.is_included = is_included
hit.evalue = block['evalue']
hit.score = block['score']
hit_dict[hit_id] = hit
else:
hit_dict[hit_id].append(hsp)
qresult = QueryResult(hit_dict.values(), query_id)
qresult.program = _PROGRAM
qresult.seq_len = self.seq_len
return [qresult]
def _create_hits(self, hit_attrs, qid, qdesc):
"""Parses a HMMER3 hsp block, beginning with the hsp table."""
# read through until the beginning of the hsp block
self._read_until(lambda line: line.startswith('Internal pipeline')
or line.startswith('>>'))
# start parsing the hsp block
hit_list = []
while True:
if self.line.startswith('Internal pipeline'):
# by this time we should've emptied the hit attr list
assert len(hit_attrs) == 0
return hit_list
assert self.line.startswith('>>')
hid, hdesc = self.line[len('>> '):].split(' ', 1)
# read through the hsp table header and move one more line
self._read_until(lambda line:
line.startswith(' --- ------ ----- --------') or
line.startswith(' [No individual domains'))
self.line = read_forward(self.handle)
# parse the hsp table for the current hit
hsp_list = []
while True:
# break out of hsp parsing if there are no hits, it's the last hsp
# or it's the start of a new hit
if self.line.startswith(' [No targets detected that satisfy') or \
self.line.startswith(' [No individual domains') or \
self.line.startswith('Internal pipeline statistics summary:') or \
self.line.startswith(' Alignments for each domain:') or \
self.line.startswith('>>'):
hit_attr = hit_attrs.pop(0)
hit = Hit(hsp_list)
for attr, value in hit_attr.items():
setattr(hit, attr, value)
if not hit:
hit.query_description = qdesc
hit_list.append(hit)
break
parsed = [x for x in self.line.strip().split(' ') if x]
assert len(parsed) == 16
# parsed column order:
# index, is_included, bitscore, bias, evalue_cond, evalue
# hmmfrom, hmmto, query_ends, hit_ends, alifrom, alito,
# envfrom, envto, acc_avg
frag = HSPFragment(hid, qid)
# HMMER3 alphabets are always protein alphabets
frag.alphabet = generic_protein
# depending on whether the program is hmmsearch, hmmscan, or phmmer
# {hmm,ali}{from,to} can either be hit_{from,to} or query_{from,to}
# for hmmscan, hit is the hmm profile, query is the sequence
if self._meta.get('program') == 'hmmscan':
# adjust 'from' and 'to' coordinates to 0-based ones
frag.hit_start = int(parsed[6]) - 1
frag.hit_end = int(parsed[7])
frag.query_start = int(parsed[9]) - 1
frag.query_end = int(parsed[10])
elif self._meta.get('program') in ['hmmsearch', 'phmmer']:
# adjust 'from' and 'to' coordinates to 0-based ones
frag.hit_start = int(parsed[9]) - 1
frag.hit_end = int(parsed[10])
frag.query_start = int(parsed[6]) - 1
frag.query_end = int(parsed[7])
# strand is always 0, since HMMER now only handles protein
frag.hit_strand = frag.query_strand = 0
hsp = HSP([frag])
hsp.domain_index = int(parsed[0])
hsp.is_included = parsed[1] == '!'
hsp.bitscore = float(parsed[2])
hsp.bias = float(parsed[3])
hsp.evalue_cond = float(parsed[4])
hsp.evalue = float(parsed[5])
if self._meta.get('program') == 'hmmscan':
# adjust 'from' and 'to' coordinates to 0-based ones
hsp.hit_endtype = parsed[8]
hsp.query_endtype = parsed[11]
elif self._meta.get('program') in ['hmmsearch', 'phmmer']:
# adjust 'from' and 'to' coordinates to 0-based ones
hsp.hit_endtype = parsed[11]
hsp.query_endtype = parsed[8]
# adjust 'from' and 'to' coordinates to 0-based ones
hsp.env_start = int(parsed[12]) - 1
hsp.env_end = int(parsed[13])
hsp.env_endtype = parsed[14]
hsp.acc_avg = float(parsed[15])
hsp_list.append(hsp)
self.line = read_forward(self.handle)
# parse the hsp alignments
if self.line.startswith(' Alignments for each domain:'):
self._parse_aln_block(hid, hit.hsps)
def _create_hits(self, hit_attrs, qid, qdesc):
"""Parses a HMMER3 hsp block, beginning with the hsp table."""
# read through until the beginning of the hsp block
self._read_until(lambda line: line.startswith('Internal pipeline')
or line.startswith('>>'))
# start parsing the hsp block
hit_list = []
while True:
if self.line.startswith('Internal pipeline'):
# by this time we should've emptied the hit attr list
assert len(hit_attrs) == 0
return hit_list
assert self.line.startswith('>>')
hid, hdesc = self.line[len('>> '):].split(' ', 1)
hdesc = hdesc.strip()
# read through the hsp table header and move one more line
self._read_until(lambda line:
line.startswith(' --- ------ ----- --------') or
line.startswith(' [No individual domains'))
self.line = read_forward(self.handle)
# parse the hsp table for the current hit
hsp_list = []
while True:
# break out of hsp parsing if there are no hits, it's the last hsp
# or it's the start of a new hit
if self.line.startswith(' [No targets detected that satisfy') or \
self.line.startswith(' [No individual domains') or \
self.line.startswith('Internal pipeline statistics summary:') or \
self.line.startswith(' Alignments for each domain:') or \
self.line.startswith('>>'):
hit_attr = hit_attrs.pop(0)
hit = Hit(hsp_list)
for attr, value in hit_attr.items():
if attr == "description":
cur_val = getattr(hit, attr)
if cur_val and value and cur_val.startswith(value):
continue
setattr(hit, attr, value)
if not hit:
hit.query_description = qdesc
hit_list.append(hit)
break
parsed = [x for x in self.line.strip().split(' ') if x]
assert len(parsed) == 16
# parsed column order:
# index, is_included, bitscore, bias, evalue_cond, evalue
# hmmfrom, hmmto, query_ends, hit_ends, alifrom, alito,
# envfrom, envto, acc_avg
frag = HSPFragment(hid, qid)
# set query and hit descriptions if they are defined / nonempty string
if qdesc:
frag.query_description = qdesc
if hdesc:
frag.hit_description = hdesc
# HMMER3 alphabets are always protein alphabets
frag.alphabet = generic_protein
# depending on whether the program is hmmsearch, hmmscan, or phmmer
# {hmm,ali}{from,to} can either be hit_{from,to} or query_{from,to}
# for hmmscan, hit is the hmm profile, query is the sequence
if self._meta.get('program') == 'hmmscan':
# adjust 'from' and 'to' coordinates to 0-based ones
frag.hit_start = int(parsed[6]) - 1
frag.hit_end = int(parsed[7])
frag.query_start = int(parsed[9]) - 1
frag.query_end = int(parsed[10])
elif self._meta.get('program') in ['hmmsearch', 'phmmer']:
# adjust 'from' and 'to' coordinates to 0-based ones
frag.hit_start = int(parsed[9]) - 1
frag.hit_end = int(parsed[10])
frag.query_start = int(parsed[6]) - 1
frag.query_end = int(parsed[7])
# strand is always 0, since HMMER now only handles protein
frag.hit_strand = frag.query_strand = 0
hsp = HSP([frag])
hsp.domain_index = int(parsed[0])
hsp.is_included = parsed[1] == '!'
hsp.bitscore = float(parsed[2])
hsp.bias = float(parsed[3])
hsp.evalue_cond = float(parsed[4])
hsp.evalue = float(parsed[5])
if self._meta.get('program') == 'hmmscan':
# adjust 'from' and 'to' coordinates to 0-based ones
hsp.hit_endtype = parsed[8]
hsp.query_endtype = parsed[11]
elif self._meta.get('program') in ['hmmsearch', 'phmmer']:
# adjust 'from' and 'to' coordinates to 0-based ones
hsp.hit_endtype = parsed[11]
hsp.query_endtype = parsed[8]
# adjust 'from' and 'to' coordinates to 0-based ones
hsp.env_start = int(parsed[12]) - 1
hsp.env_end = int(parsed[13])
hsp.env_endtype = parsed[14]
hsp.acc_avg = float(parsed[15])
hsp_list.append(hsp)
self.line = read_forward(self.handle)
# parse the hsp alignments
if self.line.startswith(' Alignments for each domain:'):
self._parse_aln_block(hid, hit.hsps)
def __iter__(self):
for rec in self.blast_iter:
# set attributes to SearchIO's
# get id and desc
if rec.query.startswith('>'):
rec.query = rec.query[1:]
try:
qid, qdesc = rec.query.split(' ', 1)
except ValueError:
qid, qdesc = rec.query, ''
qdesc = qdesc.replace('\n', '').replace('\r', '')
qresult = QueryResult(id=qid)
qresult.program = rec.application.lower()
qresult.target = rec.database
qresult.seq_len = rec.query_letters
qresult.version = rec.version
# determine alphabet based on program
if qresult.program == 'blastn':
alphabet = generic_dna
elif qresult.program in ['blastp', 'blastx', 'tblastn', 'tblastx']:
alphabet = generic_protein
# iterate over the 'alignments' (hits) and the hit table
for idx, aln in enumerate(rec.alignments):
# get id and desc
if aln.title.startswith('> '):
aln.title = aln.title[2:]
elif aln.title.startswith('>'):
aln.title = aln.title[1:]
try:
hid, hdesc = aln.title.split(' ', 1)
except ValueError:
hid, hdesc = aln.title, ''
hdesc = hdesc.replace('\n', '').replace('\r', '')
# iterate over the hsps and group them in a list
hsp_list = []
for bhsp in aln.hsps:
frag = HSPFragment(hid, qid)
frag.alphabet = alphabet
# set alignment length
frag.aln_span = bhsp.identities[1]
# set frames
try:
frag.query_frame = int(bhsp.frame[0])
except IndexError:
if qresult.program in ('blastp', 'tblastn'):
frag.query_frame = 0
else:
frag.query_frame = 1
try:
frag.hit_frame = int(bhsp.frame[1])
except IndexError:
if qresult.program in ('blastp', 'tblastn'):
frag.hit_frame = 0
else:
frag.hit_frame = 1
# set query coordinates
frag.query_start = min(bhsp.query_start,
bhsp.query_end) - 1
frag.query_end = max(bhsp.query_start, bhsp.query_end)
# set hit coordinates
frag.hit_start = min(bhsp.sbjct_start, bhsp.sbjct_end) - 1
frag.hit_end = max(bhsp.sbjct_start, bhsp.sbjct_end)
# set query, hit sequences and its annotation
qseq = ''
hseq = ''
midline = ''
for seqtrio in zip(bhsp.query, bhsp.sbjct, bhsp.match):
qchar, hchar, mchar = seqtrio
if qchar == ' ' or hchar == ' ':
assert all(' ' == x for x in seqtrio)
else:
qseq += qchar
hseq += hchar
midline += mchar
frag.query, frag.hit = qseq, hseq
frag.aln_annotation['similarity'] = midline
# create HSP object with the fragment
hsp = HSP([frag])
hsp.evalue = bhsp.expect
hsp.bitscore = bhsp.bits
hsp.bitscore_raw = bhsp.score
# set gap
try:
hsp.gap_num = bhsp.gaps[0]
except IndexError:
hsp.gap_num = 0
# set identity
hsp.ident_num = bhsp.identities[0]
hsp.pos_num = bhsp.positives[0]
if hsp.pos_num is None:
hsp.pos_num = hsp[0].aln_span
hsp_list.append(hsp)
hit = Hit(hsp_list)
hit.seq_len = aln.length
hit.description = hdesc
qresult.append(hit)
qresult.description = qdesc
yield qresult
def __iter__(self):
for rec in self.blast_iter:
# set attributes to SearchIO's
# get id and desc
if rec.query.startswith('>'):
rec.query = rec.query[1:]
try:
qid, qdesc = rec.query.split(' ', 1)
except ValueError:
qid, qdesc = rec.query, ''
qdesc = qdesc.replace('\n', '').replace('\r', '')
qresult = QueryResult(id=qid)
qresult.program = rec.application.lower()
qresult.target = rec.database
qresult.seq_len = rec.query_letters
qresult.version = rec.version
# determine alphabet based on program
if qresult.program == 'blastn':
alphabet = generic_dna
elif qresult.program in ['blastp', 'blastx', 'tblastn', 'tblastx']:
alphabet = generic_protein
# iterate over the 'alignments' (hits) and the hit table
for idx, aln in enumerate(rec.alignments):
# get id and desc
if aln.title.startswith('> '):
aln.title = aln.title[2:]
elif aln.title.startswith('>'):
aln.title = aln.title[1:]
try:
hid, hdesc = aln.title.split(' ', 1)
except ValueError:
hid, hdesc = aln.title, ''
hdesc = hdesc.replace('\n', '').replace('\r', '')
# iterate over the hsps and group them in a list
hsp_list = []
for bhsp in aln.hsps:
frag = HSPFragment(hid, qid)
frag.alphabet = alphabet
# set alignment length
frag.aln_span = bhsp.identities[1]
# set frames
try:
frag.query_frame = int(bhsp.frame[0])
except IndexError:
if qresult.program in ('blastp', 'tblastn'):
frag.query_frame = 0
else:
frag.query_frame = 1
try:
frag.hit_frame = int(bhsp.frame[1])
except IndexError:
if qresult.program in ('blastp', 'tblastn'):
frag.hit_frame = 0
else:
frag.hit_frame = 1
# set query coordinates
frag.query_start = min(bhsp.query_start,
bhsp.query_end) - 1
frag.query_end = max(bhsp.query_start, bhsp.query_end)
# set hit coordinates
frag.hit_start = min(bhsp.sbjct_start,
bhsp.sbjct_end) - 1
frag.hit_end = max(bhsp.sbjct_start, bhsp.sbjct_end)
# set query, hit sequences and its annotation
qseq = ''
hseq = ''
midline = ''
for seqtrio in zip(bhsp.query, bhsp.sbjct, bhsp.match):
qchar, hchar, mchar = seqtrio
if qchar == ' ' or hchar == ' ':
assert all(' ' == x for x in seqtrio)
else:
qseq += qchar
hseq += hchar
midline += mchar
frag.query, frag.hit = qseq, hseq
frag.aln_annotation['similarity'] = midline
# create HSP object with the fragment
hsp = HSP([frag])
hsp.evalue = bhsp.expect
hsp.bitscore = bhsp.bits
hsp.bitscore_raw = bhsp.score
# set gap
try:
hsp.gap_num = bhsp.gaps[0]
except IndexError:
hsp.gap_num = 0
# set identity
hsp.ident_num = bhsp.identities[0]
hsp.pos_num = bhsp.positives[0]
if hsp.pos_num is None:
hsp.pos_num = hsp[0].aln_span
hsp_list.append(hsp)
hit = Hit(hsp_list)
hit.seq_len = aln.length
hit.description = hdesc
qresult.append(hit)
qresult.description = qdesc
yield qresult
def _create_hits(self, hit_attrs, qid, qdesc):
"""Parse a HMMER3 hsp block, beginning with the hsp table (PRIVATE)."""
# read through until the beginning of the hsp block
self._read_until(lambda line: line.startswith("Internal pipeline") or
line.startswith(">>"))
# start parsing the hsp block
hit_list = []
while True:
if self.line.startswith("Internal pipeline"):
# by this time we should've emptied the hit attr list
assert len(hit_attrs) == 0
return hit_list
assert self.line.startswith(">>")
hid, hdesc = self.line[len(">> "):].split(" ", 1)
hdesc = hdesc.strip()
# read through the hsp table header and move one more line
self._read_until(
lambda line: line.startswith(" --- ------ ----- --------") or
line.startswith(" [No individual domains"))
self.line = read_forward(self.handle)
# parse the hsp table for the current hit
hsp_list = []
while True:
# break out of hsp parsing if there are no hits, it's the last hsp
# or it's the start of a new hit
if (self.line.startswith(
" [No targets detected that satisfy")
or self.line.startswith(" [No individual domains")
or self.line.startswith(
"Internal pipeline statistics summary:") or
self.line.startswith(" Alignments for each domain:")
or self.line.startswith(">>")):
hit_attr = hit_attrs.pop(0)
hit = Hit(hsp_list)
for attr, value in hit_attr.items():
if attr == "description":
cur_val = getattr(hit, attr)
if cur_val and value and cur_val.startswith(value):
continue
setattr(hit, attr, value)
if not hit:
hit.query_description = qdesc
hit_list.append(hit)
break
parsed = [x for x in self.line.strip().split(" ") if x]
assert len(parsed) == 16
# parsed column order:
# index, is_included, bitscore, bias, evalue_cond, evalue
# hmmfrom, hmmto, query_ends, hit_ends, alifrom, alito,
# envfrom, envto, acc_avg
frag = HSPFragment(hid, qid)
# set query and hit descriptions if they are defined / nonempty string
if qdesc:
frag.query_description = qdesc
if hdesc:
frag.hit_description = hdesc
# HMMER3 results are always protein
frag.molecule_type = "protein"
# depending on whether the program is hmmsearch, hmmscan, or phmmer
# {hmm,ali}{from,to} can either be hit_{from,to} or query_{from,to}
# for hmmscan, hit is the hmm profile, query is the sequence
if self._meta.get("program") == "hmmscan":
# adjust 'from' and 'to' coordinates to 0-based ones
frag.hit_start = int(parsed[6]) - 1
frag.hit_end = int(parsed[7])
frag.query_start = int(parsed[9]) - 1
frag.query_end = int(parsed[10])
elif self._meta.get("program") in ["hmmsearch", "phmmer"]:
# adjust 'from' and 'to' coordinates to 0-based ones
frag.hit_start = int(parsed[9]) - 1
frag.hit_end = int(parsed[10])
frag.query_start = int(parsed[6]) - 1
frag.query_end = int(parsed[7])
# strand is always 0, since HMMER now only handles protein
frag.hit_strand = frag.query_strand = 0
hsp = HSP([frag])
hsp.domain_index = int(parsed[0])
hsp.is_included = parsed[1] == "!"
hsp.bitscore = float(parsed[2])
hsp.bias = float(parsed[3])
hsp.evalue_cond = float(parsed[4])
hsp.evalue = float(parsed[5])
if self._meta.get("program") == "hmmscan":
# adjust 'from' and 'to' coordinates to 0-based ones
hsp.hit_endtype = parsed[8]
hsp.query_endtype = parsed[11]
elif self._meta.get("program") in ["hmmsearch", "phmmer"]:
# adjust 'from' and 'to' coordinates to 0-based ones
hsp.hit_endtype = parsed[11]
hsp.query_endtype = parsed[8]
# adjust 'from' and 'to' coordinates to 0-based ones
hsp.env_start = int(parsed[12]) - 1
hsp.env_end = int(parsed[13])
hsp.env_endtype = parsed[14]
hsp.acc_avg = float(parsed[15])
hsp_list.append(hsp)
self.line = read_forward(self.handle)
# parse the hsp alignments
if self.line.startswith(" Alignments for each domain:"):
self._parse_aln_block(hid, hit.hsps)
def __iter__(self):
"""Iterate over BlastTextParser, yields query results."""
for rec in self.blast_iter:
# set attributes to SearchIO's
# get id and desc
if rec.query.startswith(">"):
rec.query = rec.query[1:]
try:
qid, qdesc = rec.query.split(" ", 1)
except ValueError:
qid, qdesc = rec.query, ""
qdesc = qdesc.replace("\n", "").replace("\r", "")
qresult = QueryResult(id=qid)
qresult.program = rec.application.lower()
qresult.target = rec.database
qresult.seq_len = rec.query_letters
qresult.version = rec.version
# determine molecule_type based on program
if qresult.program == "blastn":
molecule_type = "DNA"
elif qresult.program in ["blastp", "blastx", "tblastn", "tblastx"]:
molecule_type = "protein"
# iterate over the 'alignments' (hits) and the hit table
for idx, aln in enumerate(rec.alignments):
# get id and desc
if aln.title.startswith("> "):
aln.title = aln.title[2:]
elif aln.title.startswith(">"):
aln.title = aln.title[1:]
try:
hid, hdesc = aln.title.split(" ", 1)
except ValueError:
hid, hdesc = aln.title, ""
hdesc = hdesc.replace("\n", "").replace("\r", "")
# iterate over the hsps and group them in a list
hsp_list = []
for bhsp in aln.hsps:
frag = HSPFragment(hid, qid)
frag.molecule_type = molecule_type
# set alignment length
frag.aln_span = bhsp.identities[1]
# set frames
try:
frag.query_frame = int(bhsp.frame[0])
except IndexError:
if qresult.program in ("blastp", "tblastn"):
frag.query_frame = 0
else:
frag.query_frame = 1
try:
frag.hit_frame = int(bhsp.frame[1])
except IndexError:
if qresult.program in ("blastp", "tblastn"):
frag.hit_frame = 0
else:
frag.hit_frame = 1
# set query coordinates
frag.query_start = min(bhsp.query_start, bhsp.query_end) - 1
frag.query_end = max(bhsp.query_start, bhsp.query_end)
# set hit coordinates
frag.hit_start = min(bhsp.sbjct_start, bhsp.sbjct_end) - 1
frag.hit_end = max(bhsp.sbjct_start, bhsp.sbjct_end)
# set query, hit sequences and its annotation
qseq = ""
hseq = ""
midline = ""
for seqtrio in zip(bhsp.query, bhsp.sbjct, bhsp.match):
qchar, hchar, mchar = seqtrio
if qchar == " " or hchar == " ":
assert all(" " == x for x in seqtrio)
else:
qseq += qchar
hseq += hchar
midline += mchar
frag.query, frag.hit = qseq, hseq
frag.aln_annotation["similarity"] = midline
# create HSP object with the fragment
hsp = HSP([frag])
hsp.evalue = bhsp.expect
hsp.bitscore = bhsp.bits
hsp.bitscore_raw = bhsp.score
# set gap
try:
hsp.gap_num = bhsp.gaps[0]
except IndexError:
hsp.gap_num = 0
# set identity
hsp.ident_num = bhsp.identities[0]
hsp.pos_num = bhsp.positives[0]
if hsp.pos_num is None:
hsp.pos_num = hsp[0].aln_span
hsp_list.append(hsp)
hit = Hit(hsp_list)
hit.seq_len = aln.length
hit.description = hdesc
qresult.append(hit)
qresult.description = qdesc
yield qresult
