def postSeqResult():
"""Search through COBS index located in BacQuerya storage and return search results and metadata to frontend"""
if not request.json:
return "not a json post"
if request.json:
sequence_dict = request.json
query_sequence = sequence_dict['searchTerm'].replace(" ", "").upper()
# search for uploaded sequence in COBS index
sys.stderr.write("\nSearching COBS index\n")
index_name = os.path.join(gene_dir, "31_index.cobs_compact")
index = cobs.Search(index_name)
result = index.search(query_sequence, threshold=0.8)
# load metadata for identified sequences
query_length = len(query_sequence)
kmer_length = int(os.path.basename(index_name).split("_")[0])
sys.stderr.write("\nExtracting metadata for COBS result\n")
# return only unique gene names and the highest match proportion for duplicate gene names in search results
no_duplicates = {}
for res in tqdm(result):
match_count = int(res.score)
geneName = res.doc_name.split("_v")[0]
match_proportion = round(
match_count * 100 / ((query_length - kmer_length) + 1), 2)
if not geneName in no_duplicates:
no_duplicates[geneName] = match_proportion
else:
if no_duplicates[geneName] < match_proportion:
no_duplicates[geneName] = match_proportion
result_metrics = []
for key, value in no_duplicates.items():
metrics = {"geneName": key, "numberMatching": value}
result_metrics.append(metrics)
sys.stderr.write("\nPosting results to frontend\n")
response = {"resultMetrics": result_metrics}
return jsonify(response)
def test_compact_construct_query(self):
index_file = datadir + "/python_test.cobs_compact"
# construct compact index
p = cobs.CompactIndexParameters()
p.clobber = True
cobs.compact_construct(input=datadir + "/fasta",
out_file=index_file,
index_params=p)
self.assertTrue(os.path.isfile(index_file))
# run queries
s = cobs.Search(index_file)
r = s.search("AGTCAACGCTAAGGCATTTCCCCCCTGCCTCCTGCCTGCTGCCAAGCCCT")
#print(r)
self.assertEqual(len(r), 7)
self.assertEqual(r[0].doc_name, "sample1")
self.assertEqual(r[0].score, 20)
def search_index(kmer, sequence, name):
found = ''
index = cobs.Search("indexes_all/" + str(kmer) + "_index.cobs_compact")
result_zero = index.search(sequence, threshold=0.0)
result_one = index.search(sequence, threshold=0.1)
result_two = index.search(sequence, threshold=0.2)
result_three = index.search(sequence, threshold=0.3)
result_four = index.search(sequence, threshold=0.4)
result_five = index.search(sequence, threshold=0.5)
result_six = index.search(sequence, threshold=0.6)
result_seven = index.search(sequence, threshold=0.7)
result_eight = index.search(sequence, threshold=0.8)
result_nine = index.search(sequence, threshold=0.9)
result_ten = index.search(sequence, threshold=1.0)
if name == (result_zero[0][1]).split(";")[0]:
found = 1
else:
found = 0
return (found, [
result_zero, result_one, result_two, result_three, result_four,
result_five, result_six, result_seven, result_eight, result_nine,
result_ten
])
if not len(result) == 0:
result = (str(result[0]).split("'")[1]).split(";")[0]
else:
result = "[]"
#else:
# result = ""
if result == "[]":
result = "NULL"
except:
result = "ERROR"
else:
result = "LENGTH/ISOLATE"
return result
index = cobs.Search("INDEX/10_index_index.cobs_compact")
all_annotations = pd.read_csv("reference_sparc_merged/all_annotations.csv")
tqdm.pandas()
#all_annotations["COBS 75%"] = all_annotations.progress_apply(lambda row: identify(row["strand"], row["sequence"], index, 0.75, row["Isolate"]), axis = 1)
#all_annotations["COBS 80%"] = all_annotations.progress_apply(lambda row: identify(row["strand"], row["sequence"], index, 0.8, row["Isolate"]), axis = 1)
all_annotations["COBS 85%"] = all_annotations.progress_apply(
lambda row: identify(row["strand"], row["sequence"], index, 0.85, row[
"Isolate"]),
axis=1)
#all_annotations["COBS 90%"] = all_annotations.progress_apply(lambda row: identify(row["strand"], row["sequence"], index, 0.9, row["Isolate"]), axis = 1)
#all_annotations["COBS 95%"] = all_annotations.progress_apply(lambda row: identify(row["strand"], row["sequence"], index, 0.95, row["Isolate"]), axis = 1)
all_annotations.to_csv(
def search_index(kmer, sequence, name, file_dir):
found = ''
index = cobs.Search("ini_cluster_indexes/" + str(kmer) +
"_index.cobs_compact")
result_zero = index.search(sequence, threshold=0.0)
result_zero_five = index.search(sequence, threshold=0.05)
result_one = index.search(sequence, threshold=0.1)
result_one_five = index.search(sequence, threshold=0.15)
result_two = index.search(sequence, threshold=0.2)
result_two_five = index.search(sequence, threshold=0.25)
result_three = index.search(sequence, threshold=0.3)
result_three_five = index.search(sequence, threshold=0.35)
result_four = index.search(sequence, threshold=0.4)
result_four_five = index.search(sequence, threshold=0.45)
result_five = index.search(sequence, threshold=0.5)
result_five_five = index.search(sequence, threshold=0.55)
result_six = index.search(sequence, threshold=0.6)
result_six_five = index.search(sequence, threshold=0.65)
result_seven = index.search(sequence, threshold=0.7)
result_seven_five = index.search(sequence, threshold=0.75)
result_eight = index.search(sequence, threshold=0.8)
result_eight_five = index.search(sequence, threshold=0.85)
result_nine = index.search(sequence, threshold=0.9)
result_nine_five = index.search(sequence, threshold=0.95)
result_ten = index.search(sequence, threshold=1.0)
if name == (result_zero[0][1]).split(";")[0]:
found = 1
else:
found = 0
result_zero_five = get_characteristic(name, found, result_zero,
result_zero_five, sequence, file_dir)
result_one = get_characteristic(name, found, result_zero, result_one,
sequence, file_dir)
result_one_five = get_characteristic(name, found, result_zero,
result_one_five, sequence, file_dir)
result_two = get_characteristic(name, found, result_zero, result_two,
sequence, file_dir)
result_two_five = get_characteristic(name, found, result_zero,
result_two_five, sequence, file_dir)
result_three = get_characteristic(name, found, result_zero, result_three,
sequence, file_dir)
result_three_five = get_characteristic(name, found, result_zero,
result_three_five, sequence,
file_dir)
result_four = get_characteristic(name, found, result_zero, result_four,
sequence, file_dir)
result_four_five = get_characteristic(name, found, result_zero,
result_four_five, sequence, file_dir)
result_five = get_characteristic(name, found, result_zero, result_five,
sequence, file_dir)
result_five_five = get_characteristic(name, found, result_zero,
result_five_five, sequence, file_dir)
result_six = get_characteristic(name, found, result_zero, result_six,
sequence, file_dir)
result_six_five = get_characteristic(name, found, result_zero,
result_six_five, sequence, file_dir)
result_seven = get_characteristic(name, found, result_zero, result_seven,
sequence, file_dir)
result_seven_five = get_characteristic(name, found, result_zero,
result_seven_five, sequence,
file_dir)
result_eight = get_characteristic(name, found, result_zero, result_eight,
sequence, file_dir)
result_eight_five = get_characteristic(name, found, result_zero,
result_eight_five, sequence,
file_dir)
result_nine = get_characteristic(name, found, result_zero, result_nine,
sequence, file_dir)
result_nine_five = get_characteristic(name, found, result_zero,
result_nine_five, sequence, file_dir)
result_ten = get_characteristic(name, found, result_zero, result_ten,
sequence, file_dir)
result_zero = get_characteristic(name, found, result_zero, result_zero,
sequence, file_dir)
return (found, [
result_zero, result_zero_five, result_one, result_one_five, result_two,
result_two_five, result_three, result_three_five, result_four,
result_four_five, result_five, result_five_five, result_six,
result_six_five, result_seven, result_seven_five, result_eight,
result_eight_five, result_nine, result_nine_five, result_ten
])