def iedb_table():
mongo = get_mongo_db()
data = []
if request.method == 'POST':
error = None
gene = request.form["gene_select"]
aa_pos_start = int(request.form["aa_pos_start"]
) if request.form["aa_pos_start"] != "" else 0
aa_pos_end = int(request.form["aa_pos_end"]
) if request.form["aa_pos_end"] != "" else 0
data = list(
mongo.db.iedb.find(
{
"Gene": gene,
"aa_pos": {
"$gt": aa_pos_start,
"$lt": aa_pos_end
}
}, {'_id': False}))
if len(data) == 0:
error = "Epitope not found."
if error:
flash(error)
return render_template('immuno/iedb_epitope_table.html',
genes=[
"E", "M", "N", "nsp01", "nsp10", "nsp11",
"nsp12", "nsp13", "nsp14", "nsp15", "nsp16",
"nsp2", "nsp3", "nsp4", "nsp5", "nsp6", "nsp7",
"nsp8", "nsp9", "orf10", "orf3a", "orf6",
"orf7a", "orf7b", "orf8", "S"
],
epitopes=data)
def hla_I_table():
mongo = get_mongo_db()
data = []
if request.method == 'POST':
gene = request.form["gene_select"]
binding_affinity = float(
request.form["binding_affinity"]
) if request.form["binding_affinity"] != "" else 0
flash((gene, binding_affinity))
data = mongo.db.hla.find({
"gene": gene,
"binding_affinity": {
"$lt": binding_affinity
}
})
return render_template('immuno/hla_I_table.html',
genes=[
"E", "M", "N", "nsp01", "nsp10", "nsp11",
"nsp12", "nsp13", "nsp14", "nsp15", "nsp16",
"nsp2", "nsp3", "nsp4", "nsp5", "nsp6", "nsp7",
"nsp8", "nsp9", "orf10", "orf3a", "orf6",
"orf7a", "orf7b", "orf8", "S"
],
epitopes=data)
def primer_result(run_id):
mongo = get_mongo_db()
parameters = mongo.db.primer_results.find_one({'_id': str(run_id)})
print({'_id': str(run_id)})
print(parameters)
return render_template('diagnostics/primer_result.html',
run_id=str(run_id),
parameters=parameters)
def primers():
mongo = get_mongo_db()
if request.method == 'POST':
uniq_id = str(uuid.uuid4())
primerF = request.form["primerF"]
primerR = request.form["primerR"]
probe = request.form["probe"]
save_dir = app.root_path+"/"+app.static_url_path+"/results/"
run_primer_conservation.delay(primerF=primerF,primerR=primerR,probe=probe,uniq_id=uniq_id, save_dir=save_dir)
return redirect(url_for('analyse.primer_result', run_id=str(uniq_id)))
return render_template('analyse/diagnostics.html')
def phylogeny():
mongo = get_mongo_db()
if request.method == 'POST':
uniq_id = str(uuid.uuid4())
if request.files['file1'].filename=="":
error = "No files found, please try again!"
filename1 = secure_filename(request.files['file1'].filename)
server_fname1 = os.path.join(app.config["UPLOAD_FOLDER"], filename1)
request.files['file1'].save(server_fname1)
run_phylogeny.delay(server_fname1,uniq_id,working_dir=app.config["APP_ROOT"]+url_for('static', filename='results'))
return redirect(url_for('analyse.phylogeny_result', run_id=uniq_id))
return render_template('analyse/phylogeny.html')
def phylogeny_result(run_id):
mongo = get_mongo_db()
file_prefix = "%s/%s" % (app.config["APP_ROOT"]+url_for('static', filename='results'), run_id)
status = {
"msa":"OK" if os.path.isfile(file_prefix+".aln") else "Processing",
"vcf": "OK" if os.path.isfile(file_prefix+".vcf.gz") else "Processing",
"variant_info": "OK" if os.path.isfile(file_prefix+".variant_info.csv") else "Processing",
"phylogeny": "OK" if os.path.isfile(file_prefix+".aln.iqtree") else "Processing",
}
print(status)
csv_data = []
if status["variant_info"]=="OK":
for row in csv.DictReader(open(file_prefix+".variant_info.csv")):
csv_data.append(row)
return render_template('analyse/phylogeny_result.html',run_id=run_id, status=status, csv_data=csv_data)
def run_result(sample_id):
mongo = get_mongo_db()
run = mongo.db.profiler_results.find_one({"_id": str(sample_id)})
if run == None:
error = "Run does not exist"
abort(404)
if run["status"] == "done":
pdb_ids = [
x.split("/")[-1].split(".")[0]
for x in os.listdir(app.config["APP_ROOT"] +
url_for('static', filename='pdb'))
if x[-4:] == ".pdb"
]
structures = defaultdict(dict)
for id in pdb_ids:
d = json.load(
open(app.config["APP_ROOT"] +
url_for('static',
filename='pdb/%s.pdb.available_residues.json' %
id)))
for key, val in d["mapping"].items():
structures[val]["pdb_code"] = id
structures[val]["pdb_file"] = url_for('static',
filename='pdb/%s.pdb' %
id)
structures[val]["chain"] = key
structures[val]["residues"] = d["residues"][val]
structure_variants = []
print(run)
for mutation in run["results"]["variants"]:
if mutation["types"] != "missense": continue
residue = int(re.match("(\d+)", mutation["changes"]).group(1))
if mutation["gene"] in structures:
if residue in structures[mutation["gene"]]["residues"]:
structure_variants.append(mutation)
return render_template('results/run_result.html',
run=run,
structures=structures,
structure_variants=structure_variants)
else:
return render_template('results/run_result.html', run=run)
def mutation(position):
db = get_db()
mongo = get_mongo_db()
mutation = mongo.db.mutations.find_one({"position": str(position)})
del mutation["_id"]
if mutation == None:
error = "Mutation does not exist"
abort(404)
tmp = json.dumps(mutation)
mutation["json_string"] = tmp
tree_text = mongo.db.tree.find_one()["tree"]
meta = mongo.db.meta.find_one()
del meta["_id"]
tree = {"newick": tree_text, "meta": json.dumps(meta), "created": "test"}
return render_template('results/mutations.html',
mutation=mutation,
tree=tree)
def profile():
mongo = get_mongo_db()
if request.method == 'POST':
cp.log("Recieved POST request with files %s\n" % (", ".join([request.files[x].filename for x in request.files])) )
error=None
# username = g.user['username'] if g.user else 'private'
username = '******'
uniq_id = str(uuid.uuid4())
sample_name = uniq_id
if request.files['file1'].filename=="":
error = "No files found, please try again!"
if "fasta_submit" in request.form and error==None:
run_sample(mongo,username,uniq_id,sample_name,"fasta",request.files['file1'])
return redirect(url_for('results.run_result', sample_id=uniq_id))
elif "fastq_submit" in request.form and error==None:
run_sample(mongo,username,uniq_id,sample_name,"fastq",request.files['file1'],request.files['file2'])
return redirect(url_for('results.run_result', sample_id=uniq_id))
flash(request.form)
flash(error)
return render_template('analyse/profile.html')
def diagnostics():
mongo = get_mongo_db()
if request.method == 'POST':
uniq_id = str(uuid.uuid4())
primerF = request.form["primerF"]
primerR = request.form["primerR"]
probe = request.form["probe"]
save_dir = app.root_path + "/" + app.static_url_path + "/results/"
mongo.db.primer_results.insert_one({
"_id": str(uniq_id),
"status": "processing",
"primerF": primerF,
"primerR": primerR,
"probe": probe
})
profile_primer.delay(primerF=primerF,
primerR=primerR,
probe=probe,
uniq_id=uniq_id,
save_dir=save_dir)
return redirect(
url_for('diagnostics.primer_result', run_id=str(uniq_id)))
return render_template('diagnostics/diagnostics.html')
def analyse():
mongo = get_mongo_db()
return render_template('analyse/analyse.html')
def primer_result(run_id):
mongo = get_mongo_db()
json_file = app.root_path+"/"+app.static_url_path+"/results/%s.plots.json" % str(run_id)
data = json.load(open(json_file)) if os.path.isfile(json_file) else None
return render_template('analyse/primer_result.html',run_id=str(run_id),data = data)
def test():
mongo = get_mongo_db()
return render_template('test/test.html')
def table(gene):
mongo = get_mongo_db()
data = mongo.db.immuno.find({"Gene": gene}, {'_id': False})
return render_template('immuno/main_table.html', data=data)
def mutation_table():
mongo = get_mongo_db()
mutations = mongo.db.mutations.find()
return render_template('results/mutation_table.html', mutations=mutations)
