def process_vcf(job):
'''
wait for the annotation job to finish by continually checking the job status
'''
status = runner.job_status(RUNNER_DB, job)
if status is None:
return flask.render_template('main.html', errors=['Job not found'], form=flask.request.form)
elif status['status'] == 'F': # finished
return flask.redirect(flask.url_for("vcf_result", job=job))
else: # still in progress
return flask.render_template('process_vcf.html', job=job, status=status)
def gene_result(job, gene):
'''
find AF details for a requested gene in a job
'''
status = runner.job_status(RUNNER_DB, job) # ensure it's a real job
if status is None: # no output
return flask.render_template('main.html',
errors=['Job not found'],
form=flask.request.form)
skip = 2
# determine counts for genes
settings = json.loads(status['settings'])
result = {'x': [], 'y': [], 'pass': [], 'text': []}
for line in open(
os.path.join(app.config['UPLOAD_FOLDER'], '{}.out'.format(job)),
'r'):
if skip > 0: # skip header
if skip == 2:
cases = float(line.strip())
skip -= 1
continue
fields = line.strip('\n').split('\t')
if fields[helpers.OUTPUT_FIELDS['gene']] == gene:
ac = float(fields[helpers.OUTPUT_FIELDS['allele_count']])
an = float(fields[helpers.OUTPUT_FIELDS['allele_number']])
exac_ac = float(fields[helpers.OUTPUT_FIELDS['exac_all_pop_ac']])
exac_an = float(fields[helpers.OUTPUT_FIELDS['exac_all_pop_an']])
if an != 0:
result['y'].append(ac / an)
if exac_an != 0:
result['x'].append(exac_ac / exac_an)
else:
result['x'].append(0)
result['pass'].append(
helpers.get_vcf_match(fields, settings) > 0)
result['text'].append('AC={} {}'.format(
fields[helpers.OUTPUT_FIELDS['allele_count']],
fields[helpers.OUTPUT_FIELDS['impact_type']]))
return flask.jsonify(result)
def job_status(job):
status = runner.job_status(RUNNER_DB, job)
if status is None:
return flask.render_template('main.html', form=flask.request.form)
else: # still in progress
return flask.jsonify(status)
def vcf_result(job):
'''
redirected to this after annotation has finished
'''
status = runner.job_status(RUNNER_DB, job) # ensure it's a real job
if status is None: # no output
return flask.render_template('main.html', errors=['Job not found'], form=flask.request.form)
# determine counts for genes
settings = json.loads(status['settings'])
result = []
warnings = []
current = [None, 0]
skip = 2
for line in open(os.path.join(app.config['UPLOAD_FOLDER'], '{}.out'.format(job)), 'r'):
if skip > 0: # skip header
if skip == 2:
settings['cases'] = int(line.strip())
skip -=1
continue
fields = line.strip('\n').split('\t')
if current[0] == fields[0]: # same gene
current[1] += helpers.get_vcf_match(fields, settings)
else: # new gene
if current[0] is not None and current[1] > 0: # an actual gene
matches = helpers.get_exac_detail(query_db=query_db, gene=current[0], settings=settings)
if matches[1] is not None:
statistics = calculate.calculate_burden_statistics(case_burden=current[1], total_cases=settings['cases'], population_burden=matches[0], total_population=EXAC_POPULATION)
result.append({'gene': current[0], 'burden': current[1], 'matches': matches[0], 'protein_length': matches[1], \
'z_test': statistics[0], 'binomial_test': statistics[1], 'relative_risk': statistics[2], 'rr_conf_interval': statistics[3]})
else:
# gene is no good
warnings.append( 'Gene "{}" or variants not found in the selected database'.format(current[0]))
# start counting new gene
current = [fields[0], helpers.get_vcf_match(fields, settings)]
if current[1] > 0:
matches = helpers.get_exac_detail(query_db=query_db, gene=current[0], settings=settings)
if matches[1] is not None:
statistics = calculate.calculate_burden_statistics(case_burden=current[1], total_cases=settings['cases'], population_burden=matches[0], total_population=EXAC_POPULATION)
result.append({'gene': current[0], 'burden': current[1], 'matches': matches[0], 'protein_length': matches[1], \
'z_test': statistics[0], 'binomial_test': statistics[1], 'relative_risk': statistics[2], 'rr_conf_interval': statistics[3]})
else:
# gene is no good
warnings.append( 'Gene "{}" or variants not found in the selected database'.format(current[0]))
return flask.render_template('results.html',
result=result,
filter_type=settings['filter_type'],
filter_value=settings['filter_value'],
filter_af_pop=','.join(settings['filter_af_pop']),
filter_af_value=settings['filter_af_value'],
cases=settings['cases'],
include_impacts=', '.join(settings['include_impacts']),
gene_list = ','.join(["'{}'".format(item['gene'].replace("'", "\\'")) for item in result if item['protein_length'] is not None]),
protein_lengths = ','.join([ str(item['protein_length']) for item in result if item['protein_length'] is not None]),
binomial_pvalues = ','.join([ '{0:0.3e}'.format(item['binomial_test']) for item in result if item['protein_length'] is not None]),
relative_risk = ','.join([ '{0:0.3e}'.format(item['relative_risk']) for item in result if item['protein_length'] is not None]),
rr_conf_interval = ','.join([ str(item['rr_conf_interval']) for item in result if item['protein_length'] is not None]),
warnings = warnings,
is_vcf = True,
job = job
)