def main():
parser = argparse.ArgumentParser(
description="Export dbNSFP scores")
cmd = DefaultCommandHelper(parser)
parser.add_argument("source_path", metavar="SOURCE",
help="The original zip file")
parser.add_argument("ensp_map_path", metavar="MAP",
help="The mapping between Ensembl protein id's and Ensembl transcript id's and Uniprot id's")
parser.add_argument("uniprot_map_path", metavar="MAP",
help="The mapping between Ensembl protein id's and Uniprot id's")
parser.add_argument("-o", "--output", dest="out_path", metavar="OUT_PATH",
help="The output file")
parser.add_argument("--temp", dest="temp_path", metavar="TEMP_PATH",
help="A temporary path for zip extraction")
parser.add_argument("--chr", dest="chr", metavar="CHROMOSOMES",
help="Chromosomes to include: list separated by commas.")
parser.add_argument("--skip-empty-scores", dest="skip_empty_scores", action="store_true", default=False,
help="Skip SNV's where all the scores are empty")
args, logger = cmd.parse_args("dbnsfp-export")
if args.out_path is None:
basename = os.path.basename(args.source_path)
prefix = os.path.splitext(basename)[0]
args.out_path = "{}.tsv.gz".format(prefix)
logger.info("Loading maps ...")
uniprot_map = {}
trs_map = {}
with tsv.open(args.ensp_map_path) as f:
for ensp, enst in tsv.lines(f, (str, str)):
if len(enst) > 0:
trs_map[enst] = ensp
with tsv.open(args.uniprot_map_path) as f:
for ensp, uniprot_id in tsv.lines(f, (str, str)):
if len(uniprot_id) > 0:
uniprot_map[uniprot_id] = ensp
logger.info("Opening {} ...".format(args.source_path))
chromosomes = None
if args.chr is not None:
chromosomes = [c.strip().upper() for c in args.chr.split(",") if len(c.strip()) > 0]
logger.info("Selected chromosomes: {}".format(", ".join(chromosomes)))
chromosomes = set(chromosomes)
name_pattern = re.compile(r"dbNSFP.+_variant.chr(.+)")
COLUMNS = [
"#chr", "pos(1-coor)", "ref", "alt", "cds_strand",
"genename", "Uniprot_id", "Uniprot_aapos", "aaref", "aaalt",
"Ensembl_geneid", "Ensembl_transcriptid", "aapos",
"SIFT_score",
"Polyphen2_HVAR_score",
"MutationAssessor_score",
"FATHMM_score",
"MutationTaster_score",
# "GERP_RS",
"GERP++_RS",
# "PhyloP_score"
"phyloP"
]
tmp_prefix = args.temp_path or tempfile.gettempdir()
if not os.path.exists(tmp_prefix):
os.makedirs(tmp_prefix)
if tmp_prefix[-1] != "/":
tmp_prefix += "/"
extract_path = tempfile.mkdtemp(prefix=tmp_prefix)
try:
logger.info("Output: {}".format(args.out_path if args.out_path != "-" else "standard output"))
total_start_time = time.time()
total_lines = 0
with ZipFile(args.source_path, "r") as zf,\
tsv.open(args.out_path, "w") as of: #,\
#tsv.open(args.noprot_path, "w") as npf:
tsv.write_line(of, "CHR", "STRAND", "START", "REF", "ALT", "TRANSCRIPT",
"PROTEIN", "AA_POS", "AA_REF", "AA_ALT",
"SIFT", "PPH2", "MA", "FATHMM", "MT", "GERPRS", "PHYLOP")
#tsv.write_line(npf, "#CHR", "POS", "ID", "REF", "ALT", "QUAL", "FILTER", "INFO")
entries = []
for entry in zf.infolist():
m = name_pattern.match(entry.filename)
if not m:
continue
chr = m.group(1)
index = CHR_INDEX[chr] if chr in CHR_INDEX else 99
if chromosomes is not None and chr not in chromosomes:
logger.debug("Skipping chromosome {} ...".format(chr))
continue
entries += [(index, chr, entry)]
for index, chr, entry in sorted(entries, key=lambda x: x[0]):
logger.info("Reading chromosome {} ...".format(chr))
zf.extract(entry, extract_path)
fpath = os.path.join(extract_path, entry.filename)
with open(fpath) as f:
# Parse header
hdr_line = f.readline()
hdr = {}
for index, name in enumerate(hdr_line.rstrip("\n").split("\t")):
hdr[name] = index
columns = [hdr[name] if name in hdr else None for name in COLUMNS]
read = set()
start_time = time.time()
partial_start_time = start_time
for line_num, line in enumerate(f, start=2):
fields = line.rstrip("\n").split("\t")
try:
fields = [fields[i] if i is not None and i < len(fields) else None for i in columns]
(chr, start, ref, alt, strand,
symbol, uniprot, uniprot_aapos, aa_ref, aa_alt,
gene, transcript, aapos,
sift, pph2, ma, fathmm,
mt, gerprs, phylop) = fields
start = safe_int(start)
ref = ref.upper() if ref is not None else None
alt = alt.upper() if alt is not None else None
aa_ref = aa_ref.upper() if aa_ref is not None else None
aa_alt = aa_alt.upper() if aa_alt is not None else None
sift = safe_float(sift)
ma = safe_float(ma)
fathmm = safe_float(fathmm)
mt = safe_float(mt)
gerprs = safe_float(gerprs)
phylop = safe_float(phylop)
if start is None or ref is None or alt is None:
logger.warn("None value for pos or ref or alt at line {}: {}".format(line_num, fields))
continue
elif ref not in BASE_INDEX or alt not in BASE_INDEX:
logger.warn("Unknown ref or alt at line {}: {}".format(line_num, fields))
continue
elif len(ref) != 1 or len(alt) != 1:
logger.warn("Length != 1 for ref or alt len at line {}: {}".format(line_num, fields))
continue
#elif aa_ref not in AA_INDEX or aa_alt not in AA_INDEX:
# logger.warn("Unknown aa_ref or aa_alt at line {}: {}".format(line_num, fields))
# continue
elif transcript is None or aapos is None or uniprot is None or uniprot_aapos is None:
logger.warn("None value for transcript or aapos or uniprot or uniprot_aapos at line {}: {}".format(line_num, fields))
continue
if aa_ref not in AA_INDEX:
aa_ref = None
if aa_alt not in AA_INDEX:
aa_alt = None
trs_values = transcript.split(";")
aapos_values = [safe_int(v) for v in aapos.split(";")]
l = len(trs_values) - len(aapos_values)
if l > 0:
aapos_values += [aapos_values[-1]] * l
uniprot_values = uniprot.split(";")
uniprot_aapos_values = [safe_int(v) for v in uniprot_aapos.split(";")]
l = len(uniprot_values) - len(uniprot_aapos_values)
if l > 0:
uniprot_aapos_values += [uniprot_aapos_values[-1]] * l
pph2_values = [safe_float(v) for v in pph2.split(";")] if pph2 is not None else [None]
l = len(uniprot_values) - len(pph2_values)
if l > 0:
pph2_values += [pph2_values[-1]] * l
uniprot_index = {}
for i, id in enumerate(uniprot_values):
if uniprot_aapos_values[i] is not None:
uniprot_index[uniprot_aapos_values[i]] = i
for i, trs in enumerate(trs_values):
pos = aapos_values[i]
if pos < 0:
pos = None
if pos is not None and pos in uniprot_index:
j = uniprot_index[pos]
uniprot_value = uniprot_values[j]
pph2_value = pph2_values[j]
else:
uniprot_value = pph2_value = None
if trs in trs_map:
prot_id = trs_map[trs]
elif uniprot_value in uniprot_map:
prot_id = uniprot_map[uniprot_value]
else:
logger.warn("Couldn't map neither protein {} or transcript {} at line {}: {}".format(uniprot_value, trs, line_num, "|".join([str(v) for v in fields])))
continue
#if pos < 0:
# logger.warn("Negative protein position at line {}: {}".format(line_num, pos))
# continue
#elif ...
if pph2_value is not None and (pph2_value < 0.0 or pph2_value > 1.0):
logger.warn("PPH2 score {} out of range at line {}: {}".format(pph2_value, line_num, fields))
continue
if aa_alt == "X": # fix stop codons having a sift score
sift = None
if args.skip_empty_scores and sift is None and pph2_value is None and ma is None \
and mt is None and gerprs is None and phylop is None:
continue
#log.info((chr, strand, start, ref, alt, aapos_values[i], aa_ref, aa_alt, trs, sift, pph2_value, ma))
if pos is None or aa_ref is None or aa_alt is None:
pass #tsv.write_line(npf, chr, start, ".", ref, alt, ".", "PASS",
# "dbNSFP={}|{}|{}|{}|{}|{}".format(trs, prot_id,
# sift or "", pph2_value or "", ma or "", fathmm or ""))
else:
tsv.write_line(of, chr, strand, start, ref, alt, trs,
prot_id, pos, aa_ref, aa_alt,
sift, pph2_value, ma, fathmm,
mt, gerprs, phylop)
except KeyboardInterrupt:
raise
except:
logger.warn("Malformed line {}: {}".format(line_num, "|".join([str(v) for v in fields])))
raise #continue
partial_time = time.time() - partial_start_time
if partial_time >= 5.0:
partial_start_time = time.time()
elapsed_time = time.time() - start_time
logger.debug(" {} lines, {:.1f} lines/second".format(hsize(line_num-1), (line_num-1) / float(elapsed_time)))
total_lines += line_num
logger.info(" > {} lines, {:.1f} lines/second".format(hsize(line_num), line_num / float(time.time() - start_time)))
logger.info(" >> {} lines, {:.1f} lines/second".format(hsize(total_lines), total_lines / float(time.time() - total_start_time)))
os.remove(fpath)
total_elapsed_time = timedelta(seconds=time.time() - total_start_time)
logger.info("Finished successfully. Elapsed time: {}".format(total_elapsed_time))
except:
return cmd.handle_error()
finally:
shutil.rmtree(extract_path)
return 0
def main():
parser = argparse.ArgumentParser(
description="Calculate Condel label")
parser.add_argument("db_path", metavar="DB_PATH",
help="Functional scores database")
parser.add_argument("weights_path", metavar="WEIGHTS",
help="File containing the scores weights and cutoffs")
parser.add_argument("-p", "--predictors", dest="predictors", metavar="PREDICTORS",
help="Comma separated list of predictors")
parser.add_argument("-u", "--updated-predictors", dest="updated_predictors", metavar="NAMES",
help="Updated predictor names")
bglogging.add_logging_arguments(parser)
args = parser.parse_args()
bglogging.initialize(args)
log = bglogging.get_logger("calculate-label")
log.info("Opening functional scores database ...")
db = FannsSQLiteDb(args.db_path)
db.open()
log.info("Loading state ...")
state = load_weights(args.weights_path)
avail_predictors, precision, step, stats = [state[k] for k in ["predictor_names", "precision", "step", "stats"]]
if args.predictors is not None:
predictors = [p for p in [p.strip() for p in args.predictors.split(",")] if p in avail_predictors]
if len(predictors) == 0:
log.error("Unknown predictors: {}".format(args.predictors))
log.error("Available predictor names are: {}".format(", ".join(avail_predictors)))
exit(-1)
else:
predictors = avail_predictors
if args.updated_predictors is not None:
updated_predictors = [p.strip() for p in args.updated_predictors.split(",")]
if len(predictors) != len(updated_predictors):
log.error("Number of updated predictors does not match with the list of number of predictors")
exit(-1)
else:
updated_predictors = ["{}_CLASS".format(p.upper()) for p in predictors]
log.info("Available predictors: {}".format(", ".join(avail_predictors)))
log.info("Selected predictors: {}".format(", ".join(predictors)))
for predictor, updated_predictor in zip(predictors, updated_predictors):
log.info("Creating predictor {} ...".format(updated_predictor))
db.add_predictor(updated_predictor, FannsDb.CALCULATED_PREDICTOR_TYPE, source=[predictor])
cutoffs = []
for predictor in predictors:
cutoff, mcc, acc = [stats[predictor][v] for v in ["cutoff", "cutoff_mcc", "cutoff_acc"]]
log.info("{}: cutoff={}, MCC={}, accuracy={}".format(predictor, cutoff, mcc, acc))
cutoffs += [cutoff]
log.info("Calculating ...")
start_time = partial_start_time = time.time()
try:
for num_rows, row in enumerate(db.query_scores(predictors=predictors), start=1):
scores = row["scores"]
d = {}
for i, predictor in enumerate(predictors):
score = scores[predictor]
if score is None:
continue
cutoff = cutoffs[i]
updated_predictor = updated_predictors[i]
d[updated_predictor] = 0.0 if score < cutoff else 1.0
db.update_scores(row["id"], d)
partial_time = time.time() - partial_start_time
if partial_time > 5.0:
partial_start_time = time.time()
elapsed_time = time.time() - start_time
log.debug(" {} rows, {:.1f} rows/second".format(hsize(num_rows), num_rows / elapsed_time))
db.commit()
except KeyboardInterrupt:
log.warn("Interrupted by Ctrl-C")
db.rollback()
except:
db.rollback()
raise
finally:
db.close()
def main():
parser = argparse.ArgumentParser(
description="Calculate Condel score")
parser.add_argument("db_path", metavar="DB_PATH",
help="Functional scores database")
parser.add_argument("weights_path", metavar="WEIGHTS",
help="File containing the scores weights and cutoffs")
parser.add_argument("-p", "--predictors", dest="predictors", metavar="PREDICTORS",
help="Comma separated list of predictors")
parser.add_argument("-u", "--updated-predictor", dest="updated_predictor", metavar="NAME",
help="Updated predictor name")
bglogging.add_logging_arguments(parser)
args = parser.parse_args()
bglogging.initialize(args)
log = bglogging.get_logger("calculate")
log.info("Opening functional scores database ...")
db = FannsSQLiteDb(args.db_path)
db.open()
updated_predictor = args.updated_predictor or "CONDEL"
predictors = set([p["id"] for p in db.predictors()])
if updated_predictor not in predictors:
log.info(" Creating predictor {} ...".format(updated_predictor))
db.add_predictor(updated_predictor, FannsDb.CALCULATED_PREDICTOR_TYPE, source=predictors)
log.info("Loading state ...")
state = load_weights(args.weights_path)
avail_predictors, precision, step, stats = [state[k] for k in ["predictor_names", "precision", "step", "stats"]]
if args.predictors is not None:
predictors = [p for p in [p.strip() for p in args.predictors.split(",")] if p in avail_predictors]
if len(predictors) == 0:
log.error("Unknown predictors: {}".format(args.predictors))
log.error("Available predictor names are: {}".format(", ".join(avail_predictors)))
exit(-1)
else:
predictors = avail_predictors
log.info("Available predictors: {}".format(", ".join(avail_predictors)))
log.info("Selected predictors: {}".format(", ".join(predictors)))
log.info("Calculating ...")
start_time = partial_start_time = time.time()
try:
for num_rows, row in enumerate(db.query_scores(predictors=predictors), start=1):
scores = row["scores"]
condel = wsum = 0
for predictor, score in scores.items():
if score is None:
continue
predictor_stats = stats[predictor]
rmin, rmax, dim, size, cdp, cdn, cutoff = [predictor_stats[k] for k in [
"rmin", "rmax", "dim", "size", "cdp", "cdn", "cutoff"]]
if predictor in PREDICTOR_TRANSFORM:
score = PREDICTOR_TRANSFORM[predictor](score)
r = (score - rmin) / dim
index = int(r * size) if score < rmax else size - 1
if score < cutoff:
w = 1 - cdn[index]
else:
w = 1 - cdp[index]
wsum += w
condel += w * score
#log.info("{}={}, w={} -> {}".format(predictor_name, score, w, score * w))
if wsum != 0:
condel /= wsum
d = {updated_predictor : condel}
db.update_scores(row["id"], d)
#log.info(">>> CONDEL={}".format(condel))
else:
log.warn("wsum = 0, condel={}, scores={}".format(condel, repr(scores)))
partial_time = time.time() - partial_start_time
if partial_time > 5.0:
partial_start_time = time.time()
elapsed_time = time.time() - start_time
log.debug(" {} rows, {:.1f} rows/second".format(hsize(num_rows), num_rows / elapsed_time))
log.info("Commit ...")
db.commit()
except KeyboardInterrupt:
log.warn("Interrupted by Ctrl-C")
db.rollback()
except:
db.rollback()
raise
finally:
db.close()