def main():
"""Program
"""
parser = get_parser()
args = parser.parse_args()
mode = args.dcc_mode
exp_id = args.exp_id
bio_rep_num = args.bio_rep_num
tech_rep_num = args.tech_rep_num
conn = Connection(mode)
rep_dico = conn.get_fastqfile_replicate_hash(exp_id)
for b in rep_dico:
if bio_rep_num and b != bio_rep_num:
continue
for t in rep_dico[b]:
if tech_rep_num and t != tech_rep_num:
continue
for read_num in rep_dico[b][t]:
for fastq_json in rep_dico[b][t][read_num]:
alias = fastq_json["aliases"][0]
print("_".join([str(b), str(t),
str(read_num)]) + "\t" + alias)
def main():
"""Program
"""
parser = get_parser()
args = parser.parse_args()
mode = args.dcc_mode
exp_id = args.exp_id
conn = Connection(mode)
exp_rep_dico = conn.get_fastqfile_replicate_hash(exp_id)
exp_json = conn.get(exp_id, ignore404=True)
controls = exp_json["possible_controls"] # A list of dicts.
# Populate a controls-lookup hash. The keys will be the ctl accessions. Each value will be
# the replicates hash (return value of conn.get_fastqfile_replicate_hash().
controls_hash = {} # A dict of dicts.
control_bio_rep_counts = []
for c in controls:
ctl_accession = c["accession"]
controls_hash[ctl_accession] = {}
ctl_rep_dico = conn.get_fastqfile_replicate_hash(ctl_accession)
controls_hash[ctl_accession]["rep_dico"] = ctl_rep_dico
control_bio_rep_counts.append(len(ctl_rep_dico.keys()))
# Make sure that all control experiments have the same number of biological replicates. There are
# no known rules to apply otherwise.
if len(set(control_bio_rep_counts)) != 1:
raise Exception(
"The controls '{controls}' have different numbers of biological replicates from one another '{rep_nums}'."
.format(controls=control_ids, rep_nums=control_bio_rep_counts))
# Make sure that the number of control bio reps equals the number of experiment bio reps:
exp_bio_rep_count = len(exp_rep_dico.keys())
if exp_bio_rep_count != control_bio_rep_counts[0]:
raise Exception(
"The number of experiment replicates '{}' doesn't equal the number of control replicates '{}'."
.format(exp_bio_rep_count, control_bio_rep_counts[0]))
# Now we'll look at each bio rep on the experiment, in numerical order of
# biological_replicate_number from least to greatest. We'll work our way all the down to the
# FASTQ files and start populating the File.controlled_by property in the following manner:
#
# For each control, we'll sort the replicates the same was as we did for the ones on the
# experiment, then for the replicate having the same ordinal index, we'll add the FASTQ File
# references.
sorted_exp_bio_reps = sorted(exp_rep_dico)
count = -1
# And now for the nastiest for-loop I've ever written ... this should be cleaned up but the logic
# is so rough to implement that it'll be ugly any way we look at it.
for b in sorted_exp_bio_reps: # biological_replicate_number
count += 1
for t in exp_rep_dico[b]: # technical_replicate_number
for read_num in exp_rep_dico[b][t]:
for fastq_json in exp_rep_dico[b][t][read_num]:
exp_file_acc = fastq_json["accession"]
controlled_by = []
for c in controls_hash:
ctl_bio_rep_num = sorted(
controls_hash[c]["rep_dico"])[count]
ctl_tech_reps = controls_hash[c]["rep_dico"][
ctl_bio_rep_num]
for ctl_tech_rep_num in ctl_tech_reps:
for ctl_encff in ctl_tech_reps[ctl_tech_rep_num][
read_num]:
controlled_by.append(ctl_encff["accession"])
conn.patch(
{
conn.ENCID_KEY: exp_file_acc,
"controlled_by": controlled_by
},
extend_array_values=False)