def td_contents(selfself, item, attr_list):
text = item.sequence_id
if text == 'Totals':
return Markup('<strong>' + text + '</strong>')
imgt_ref = get_imgt_reference_genes()
if item.sequence_id not in imgt_ref[
item.genotype_description.submission.species]:
text = '<em>' + text + '</em>'
if len(item.inferred_sequences) > 0:
text = '<strong>' + text + '</strong>'
return Markup(text)
def get(self, species, name):
""" Returns the sequence given the IMGT name """
imgt_ref = get_imgt_reference_genes()
imgt_ref_gapped = get_imgt_gapped_reference_genes()
if species in imgt_ref and name in imgt_ref[species]:
ungapped = str(imgt_ref[species][name])
gapped = str(imgt_ref_gapped[species][name])
return {
'species': species,
'imgt_name': name,
'sequence': ungapped,
'coding_seq_imgt': gapped
}
else:
return 'Not found', 404
def get(self, species):
""" Returns the set of IARC-affirmed sequences for the species """
imgt_ref = get_imgt_reference_genes()
if species not in imgt_ref:
return 'Not found', 404
all_species = db.session.query(Committee.species).all()
all_species = [s[0] for s in all_species]
if species not in all_species:
return []
q = db.session.query(GeneDescription).filter(
GeneDescription.status == 'published',
GeneDescription.affirmation_level != '0',
GeneDescription.species == species)
results = q.all()
dl = self.descs_to_airr(results)
return dl
def download_sequences(species, format, exc):
if format not in ['gapped','ungapped','airr']:
flash('Invalid format')
return redirect('/')
all_species = db.session.query(Committee.species).all()
all_species = [s[0] for s in all_species]
if species not in all_species:
flash('Invalid species')
return redirect('/')
q = db.session.query(GeneDescription).filter(GeneDescription.status == 'published', GeneDescription.affirmation_level != '0', GeneDescription.species == species)
results = q.all()
imgt_ref = get_imgt_reference_genes()
if species in imgt_ref and exc == 'non':
descs = []
for result in results:
if result.imgt_name == '':
descs.append(result)
results = descs
if len(results) < 1:
flash('No sequences to download')
return redirect('/')
if format == 'airr':
ad = []
for desc in results:
ad.append(vars(AIRRAlleleDescription(desc)))
dl = json.dumps(ad, default=str, indent=4)
ext = 'json'
else:
dl = descs_to_fasta(results, format)
ext = 'fa'
filename = 'affirmed_germlines_%s_%s.%s' % (species, format, ext)
return Response(dl, mimetype="application/octet-stream", headers={"Content-disposition": "attachment; filename=%s" % filename})
def get(self):
""" Returns the species for which sequences are available """
imgt_ref = get_imgt_reference_genes()
return {'species': list(imgt_ref.keys())}
def generate_stats(form):
species = form.species.data
locus = form.locus.data
sequence_type = form.sequence_type.data
imgt_ref = get_imgt_reference_genes()
if species not in imgt_ref:
return (0, None, None)
def gene_match(gene, ref):
for k,v in ref.items():
if gene in k:
return True
return False
rare_genes = form.rare_genes.data.replace(' ', '').split(',')
rare_missing = []
for gene in rare_genes:
if not gene_match(gene, imgt_ref[species]):
rare_missing.append(gene)
if len(rare_missing) > 0:
form.rare_genes.errors = ['Gene(s) %s not found in IMGT reference database' % ', '.join(rare_missing)]
very_rare_genes = form.very_rare_genes.data.replace(' ', '').split(',')
very_rare_missing = []
for gene in very_rare_genes:
if not gene_match(gene, imgt_ref[species]):
very_rare_missing.append(gene)
if len(very_rare_missing) > 0:
form.very_rare_genes.errors = ['Gene(s) %s not found in IMGT reference database' % ', '.join(very_rare_missing)]
if len(rare_missing) > 0 or len(very_rare_missing) > 0:
return (0, None, None)
ref = []
for gene in imgt_ref[species].keys():
if locus in gene and gene[3] == sequence_type:
ref.append(gene)
# Calculate thresholds for each reference gene
gene_thresh = {}
for gene in imgt_ref[species].keys():
gene_thresh[gene] = form.freq_threshold.data
for rg in rare_genes:
if rg in gene:
gene_thresh[gene] = form.rare_threshold.data
for rg in very_rare_genes:
if rg in gene:
gene_thresh[gene] = form.very_rare_threshold.data
# Get unique list of genotype descriptions that underlie affirmed inferences
genotype_descriptions = []
seqs = db.session.query(GeneDescription).filter(GeneDescription.status == 'published',
GeneDescription.species == species,
GeneDescription.locus == locus,
GeneDescription.sequence_type == sequence_type,
GeneDescription.affirmation_level != '0'
).all()
for seq in seqs:
for genotype in seq.inferred_sequences:
if genotype.genotype_description not in genotype_descriptions:
genotype_descriptions.append(genotype.genotype_description)
if len(genotype_descriptions) == 0:
return (0, None, None)
# Initialise stats
stats = {}
for name in ref:
if '/OR' not in name:
stats[name] = {'occurrences': 0, 'unmutated_freq': [], 'gene': name}
stats = OrderedDict(sorted(stats.items(), key=lambda name: parse_name(name[0])[2]))
stats = OrderedDict(sorted(stats.items(), key=lambda name: parse_name(name[0])[1]))
stats = OrderedDict(sorted(stats.items(), key=lambda name: parse_name(name[0])[0]))
raw = {}
for name in ref:
if '/OR' not in name:
raw[name] = {'gene': name}
raw = OrderedDict(sorted(raw.items(), key=lambda name: parse_name(name[0])[2]))
raw = OrderedDict(sorted(raw.items(), key=lambda name: parse_name(name[0])[1]))
raw = OrderedDict(sorted(raw.items(), key=lambda name: parse_name(name[0])[0]))
# Compose stats
gen_names = ['gene']
for desc in genotype_descriptions:
gen_name = "%s/%s" % (desc.submission.submission_id, desc.genotype_name)
gen_names.append(gen_name)
for gen in desc.genotypes:
if gen.sequence_id in stats \
and (gen.allelic_percentage is None or gen.allelic_percentage==0 or gen.allelic_percentage >= form.allelic_threshold.data) \
and (gen.assigned_unmutated_frequency is None or gen.assigned_unmutated_frequency >= form.assigned_unmutated_threshold.data) \
and (gen.unmutated_frequency is not None and gen.unmutated_frequency >= gene_thresh[gen.sequence_id]):
stats[gen.sequence_id]['occurrences'] += 1
stats[gen.sequence_id]['unmutated_freq'].append(gen.unmutated_frequency)
if gen.sequence_id in raw and (gen.allelic_percentage is None or gen.allelic_percentage >= form.allelic_threshold.data):
raw[gen.sequence_id][gen_name] = gen.unmutated_frequency
for (k, stat) in stats.items():
stats[k]['unmutated_freq'] = round(sum(stat['unmutated_freq'])/max(len(stat['unmutated_freq']),1), 2)
ret = []
for(k, stat) in stats.items():
ret.append(stat)
ro = StringIO()
writer = csv.DictWriter(ro, fieldnames=gen_names)
writer.writeheader()
for gene in raw:
writer.writerow(raw[gene])
return (len(genotype_descriptions), ret, ro)
def setup_gv_table(desc):
table = make_Genotype_full_table(desc.genotypes,
desc.locus,
False,
classes=['table-bordered'])
# table.items = list(table.items)
table._cols['sequence_id'] = GenTitleCol(
'Allele name',
tooltip=
'Identifier of the allele (either IMGT, or the name assigned by the submitter to an inferred gene)'
)
table.rotate_header = True
table.add_column(
'nt_sequence',
SeqCol('Sequence', tooltip="Click to view or download sequence"))
table.table_id = 'genotype_table'
# Add totals row
totals = Genotype()
totals.sequence_id = 'Totals'
totals.sequences = 0
totals.unmutated_sequences = 0
lh_seqs = 0
for gen in desc.genotypes:
try:
if gen.haplotyping_ratio and ':' in gen.haplotyping_ratio:
lh = int(gen.haplotyping_ratio.split(':')[0])
totals.sequences += gen.sequences
totals.unmutated_sequences += gen.unmutated_sequences
lh_seqs += lh * totals.sequences / 100
except:
pass
if lh_seqs > 0:
lh_prop = round(100 * lh_seqs / totals.sequences)
totals.haplotyping_ratio = "%d:%d" % (lh_prop, (100 - lh_prop))
totals.assigned_unmutated_frequency = round(
100 * totals.unmutated_sequences / totals.sequences, 2)
table.items.append(totals)
inferred_seqs = []
for inf in desc.inferred_sequences:
inferred_seqs.append(inf.sequence_details.sequence_id)
novel = []
imgt_ref = get_imgt_reference_genes()
for item in desc.genotypes:
if item.sequence_id != 'Totals' and (
item.sequence_id
not in imgt_ref[item.genotype_description.submission.species]
or item.sequence_id in inferred_seqs):
novel.append(item)
inferred_table = make_Genotype_novel_table(novel,
False,
classes=['table-bordered'])
inferred_table._cols['sequence_id'] = GenTitleCol(
'Allele name',
tooltip=
'Identifier of the allele (either IMGT, or the name assigned by the submitter to an inferred gene)'
)
inferred_table.add_column(
'nt_sequence',
SeqCol('Sequence', tooltip="Click to view or download sequence"))
inferred_table.rotate_header = True
return (table, inferred_table)
def td_contents(self, item, attr_list):
if not item.nt_sequence: # e.g. for totals column
return ''
imgt_ref = get_imgt_reference_genes()
imgt_ref_gapped = get_imgt_gapped_reference_genes()
ref_codon_usage = get_reference_v_codon_usage()
if item.sequence_id in imgt_ref[
item.genotype_description.submission.species]:
if item.nt_sequence.lower() == imgt_ref[
item.genotype_description.submission.species][
item.sequence_id]:
icon = 'glyphicon-ok'
colour = 'text-info'
aln_text = ' data-toggle="tooltip" title="Agrees with Reference"'
else:
icon = 'glyphicon-remove'
colour = 'text-danger'
alignments = pairwise2.align.globalms(
item.nt_sequence.lower(),
imgt_ref[item.genotype_description.submission.species][
item.sequence_id],
2,
-1,
-2,
-1,
one_alignment_only=True)
alignment = format_aln(format_alignment(*alignments[0]),
item.sequence_id, 'Reference', 50)
fasta_seqs = format_fasta_sequence(
item.sequence_id, item.nt_sequence.lower(),
50) + format_fasta_sequence(
'Reference',
imgt_ref[item.genotype_description.submission.species][
item.sequence_id], 50)
aln_text = Markup(
' id="btn_view_check" data-target="#seqModal" data-sequence="%s" data-name="%s" data-fa="%s" data-toggle="modal" title="Differs from Reference (click to view)"'
% (alignment, item.sequence_id, fasta_seqs))
bt_check = '<button type="button" class="btn btn-xs %s icon_back" %s><span class="glyphicon %s"></span> </button>' \
% (colour, aln_text, icon)
else:
bt_check = ''
bt_igpdb = ''
if item.genotype_description.submission.species == 'Human':
igpdb_genes = get_igpdb_ref()
for k, v in igpdb_genes.items():
if item.nt_sequence.lower(
) in v or v in item.nt_sequence.lower():
bt_igpdb = '<button type="button" class="btn btn-xs text-info icon_back" data-toggle="tooltip" title="Sequence matches IGPDB gene %s"><span class="glyphicon glyphicon-info-sign"></span> </button>' % k
break
bt_vdjbase = ''
if item.genotype_description.submission.species == 'Human' and item.sequence_id not in imgt_ref[
item.genotype_description.submission.species]:
vdjbase_ref = get_vdjbase_ref()
vdjbase_species = item.genotype_description.submission.species.replace(
'Human_TCR', 'Human')
locus = item.genotype_description.locus
if vdjbase_species in vdjbase_ref and locus in vdjbase_ref[
vdjbase_species]:
vdjbase_genes = vdjbase_ref[vdjbase_species][locus]
for vdjbase_name, (vdjbase_seq,
vdjbase_count) in vdjbase_genes.items():
if item.nt_sequence.lower(
) in vdjbase_seq or vdjbase_seq in item.nt_sequence.lower(
):
bt_vdjbase = '<button type="button" name="vdjbasebtn" id="vdjbasebtn" class="btn btn-xs text-info icon_back" onclick="window.open(%s)" data-toggle="tooltip" title="Sequence matches VDJbase gene %s (found in %s subjects). Click to view in VDJbase."><span class="glyphicon glyphicon-info-sign"></span> </button>' % \
(Markup("'%sgenerep/%s/%s/%s'" % (app.config['VDJBASE_URL'], vdjbase_species, locus, vdjbase_name)), vdjbase_name, vdjbase_count)
break
bt_indels = ''
bt_imgt = ''
bt_codon_usage = ''
bt_runs = ''
bt_hotspots = ''
bt_ref_found = ''
annots = []
if item.sequence_id not in imgt_ref[
item.genotype_description.submission.species]:
if item.closest_reference not in imgt_ref[
item.genotype_description.submission.species]:
bt_ref_found = '<button type="button" class="btn btn-xs text-info icon_back" data-toggle="tooltip" title="Nearest reference not found in IMGT reference set"><span class="glyphicon glyphicon-info-sign"></span> </button>'
else:
for k, v in imgt_ref[
item.genotype_description.submission.species].items():
if item.nt_sequence.lower() == v:
bt_imgt = '<button type="button" class="btn btn-xs text-info icon_back" data-toggle="tooltip" title="Sequence matches IMGT gene %s"><span class="glyphicon glyphicon-info-sign"></span> </button>' % k
break
# QA Checks
# Alignment issues
ref_nt = imgt_ref[item.genotype_description.submission.
species][item.closest_reference].upper()
seq_nt = item.nt_sequence.upper()
mismatch = 0
aligned = True
for (r, s) in zip(ref_nt, seq_nt):
if r != s:
mismatch += 1
if mismatch > 20:
aligned = False
bt_indels = '<button type="button" class="btn btn-xs text-info icon_back" data-toggle="tooltip" title="Sequence has indels/low match when compared to reference sequence"><span class="glyphicon glyphicon-info-sign"></span> </button>'
if aligned:
# Check for unusual AAs at each position
if item.genotype_description.sequence_type == 'V' and item.genotype_description.locus + 'V' in ref_codon_usage[
item.genotype_description.submission.species]:
try:
q_codons = []
ref_aa_gapped = imgt_ref_gapped[
item.genotype_description.submission.species][
item.closest_reference].upper().translate(
gap='.')
seq_aa = Seq(item.nt_sequence.upper()).translate()
seq_aa_gapped = gap_sequence(seq_aa, ref_aa_gapped)
family = find_family(item.closest_reference)
for i in range(
min(len(ref_aa_gapped),
len(seq_aa_gapped))):
if ref_aa_gapped[i] != seq_aa_gapped[
i] and '*' not in (
ref_aa_gapped[i], seq_aa_gapped[i]
) and '.' not in (ref_aa_gapped[i],
seq_aa_gapped[i]):
if seq_aa_gapped[i] not in ref_codon_usage[
item.genotype_description.
submission.species][
item.genotype_description.locus
+ 'V'][family][i + 1]:
q_codons.append(
"%s%d" % (seq_aa_gapped[i], i + 1))
j = len(seq_aa_gapped[:i].replace(
'.', ''))
annots.append((
3 * j, 3,
'%s%d previously unreported in this family'
% (seq_aa_gapped[i], i + 1)))
if len(q_codons) > 0:
bt_codon_usage = '<button type="button" class="btn btn-xs text-info icon_back" data-toggle="tooltip" title="Amino Acid(s) previously unreported in this family: %s"><span class="glyphicon glyphicon-info-sign"></span> </button>' % ", ".join(
q_codons)
except:
bt_codon_usage = '<button type="button" class="btn btn-xs text-info icon_back" data-toggle="tooltip" title="Error translating sequence: %s"><span class="glyphicon glyphicon-info-sign"></span> </button>' % sys.exc_info(
)[0]
# Check for lengthened strings of the same base
seq_qpos = [
m.start()
for m in re.finditer('(.)\\1+\\1+\\1+', str(seq_nt))
]
q_runs = []
# walk up each identified repeat of 4nt or more, flag any differences
for p in seq_qpos:
rep_c = seq_nt[p]
i = p
while i < len(seq_nt) and i < len(
ref_nt) and seq_nt[i] == rep_c:
if ref_nt[i] != rep_c:
q_runs.append("%d" % find_gapped_index(
i, item.genotype_description.submission.
species, item.closest_reference))
annots.append(
(i, 1, 'Possible repeated read error'))
break
i += 1
if len(q_runs) > 0:
bt_runs = '<button type="button" class="btn btn-xs text-info icon_back" data-toggle="tooltip" title="Possible repeated read errors at IMGT position(s) %s"><span class="glyphicon glyphicon-info-sign"></span> </button>' % ", ".join(
q_runs)
# Check for RGYW/WRCY hotspot change
ref_qpos = [
m.start()
for m in re.finditer('[AG][G][CT][AT]', str(ref_nt))
]
q_hotspots = []
for p in ref_qpos:
if seq_nt[p + 1] == 'C':
q_hotspots.append("%d" % find_gapped_index(
p + 1,
item.genotype_description.submission.species,
item.closest_reference))
annots.append(
(p + 1, 1, 'G/C SNP in RGYW hotspot'))
ref_qpos = [
m.start()
for m in re.finditer('[AT][AG][C][CT]', str(ref_nt))
]
for p in ref_qpos:
if seq_nt[p + 2] == 'G':
q_hotspots.append("%d" % find_gapped_index(
p + 2,
item.genotype_description.submission.species,
item.closest_reference))
annots.append(
(p + 2, 1, 'C/G SNP in WRCY hotspot'))
if len(q_hotspots) > 0:
bt_hotspots = '<button type="button" class="btn btn-xs text-info icon_back" data-toggle="tooltip" title="G/C SNP in RGYW/WRCY hotspot at IMGT position(s) %s"><span class="glyphicon glyphicon-info-sign"></span> </button>' % ", ".join(
q_hotspots)
bt_view = popup_seq_button(item.sequence_id,
item.nt_sequence,
item.nt_sequence_gapped,
annots=annots)
return bt_view + bt_check + bt_imgt + bt_igpdb + bt_vdjbase + bt_indels + bt_codon_usage + bt_runs + bt_hotspots + bt_ref_found