def call_consensus(alignment, minproportion=0.5):
pos_base = OrderedDict()
record_size = 0
for faObj in formFASTA(alignment):
name, seq = faObj
reads_count = 1
record_size += reads_count
index = 1
for base in seq:
index += 1
if index not in pos_base.keys():
pos_base[index] = defaultdict(int)
if base != "-":
pos_base[index][base] += reads_count
con_seq = ""
for pos, count in pos_base.items():
total = float(sum(count.values()))
if total / record_size >= minproportion:
maxnum = 0
maxbase = ""
for base, num in count.items():
if num > maxnum:
maxnum = num
maxbase = base
con_seq += maxbase
return con_seq, record_size
def group_reads(fa_file):
BC_UMI_seq = defaultdict(lambda: defaultdict(list))
for record in formFASTA(fa_file):
name, seq = record
BC = name.split("BC=")[1].split(" ")[0]
UMI = name.split("UMI=")[1].split(" ")[0]
BC_UMI_seq[BC][UMI].append(seq)
return BC_UMI_seq
def getCCSreadDF(CCS_result_path):
CCS_fa = open(CCS_result_path, 'r').read()
readName = []
readSeq = []
for record in formFASTA(CCS_fa):
name, seq = record
readName.append(name)
readSeq.append(seq)
# build dataframe
ccs_df = pd.DataFrame({"name": readName, "sequence": readSeq})
ccs_df["name"] = ">" + ccs_df["name"]
return ccs_df
outSta = open(options.statistics, 'w')
# write statistics header
outSta.write("{}\t{}\t{}\t{}\n".format("zwID", "BC", "UMI", "pass_filter"))
## some input parameters
P2 = options.FP
P4 = options.RP
inFP = options.inFP
inRP = options.inRP
polyAwin = options.pAw
pAmismatch = options.pMs
mismatch = options.mismatch
## get file handle
if options.format == "FASTQ":
file_handle = fqTOfa(inputFile)
elif options.format == "FASTA":
file_handle = formFASTA(inputFile.read())
## run filter
pfq = multiprocessing.Pool(options.numcpu)
for record in file_handle:
header, raw_seq = record
prf = pfq.apply_async(filterCCS,
args=(
header,
raw_seq,
P2,
P4,
inFP,
inRP,
polyAwin,
pAmismatch,
mismatch,
def main():
options = Parsers()
alignFa = open(options.align, 'r').read()
targetPos = open(options.targetpos, 'r')
### output file
output = open(os.path.join(options.dir, options.name + ".Events.txt"), 'w')
# editfre = open(os.path.join(options.dir, options.name + ".EditFrequency.txt"), 'w')
# eventcount = open(os.path.join(options.dir, options.name + ".EventCounts.txt"), 'w')
# eventcountDic = open(os.path.join(options.dir, options.name + ".EventCounts.pkl"), "wb")
next(targetPos)
tarPos = []
header = []
### parser target positions
for eachline in targetPos:
sple = eachline.strip().split('\t')
header.append(sple[0])
tarPos.append((int(sple[1]), int(sple[2])))
### build a dict to count the edit frequency in every base
# pos = list(range(1, options.len))
# Edit_fre = {}
# for p in pos:
# Edit_fre[p] = [0,0]
### write the output header
#editfre.write("{}\t{}\t{}\t{}\t{}\n".format("Position", "Insertion", "InserPercent", "Deletion", "DeletPercent"))
output.write("{}\t{}\t{}\n".format("BC", "UMI", '\t'.join(header)))
#editfre.flush()
output.flush()
### get the output data
processPool = multiprocessing.Pool(options.cpu)
results = []
all_seq = formFASTA(alignFa)
while True:
try:
_, refseq = next(all_seq)
readname, readseq = next(all_seq)
editresult = processPool.apply_async(analyzeEdit,
args=(
readname,
refseq,
readseq,
))
results.append(editresult)
except StopIteration:
break
print('waite')
processPool.close()
processPool.join()
print('done')
editEventDict = collections.OrderedDict()
for each_result in results:
rawEditlist = each_result.get()
editEventDict[rawEditlist[-1]] = rawEditlist[:-1]
#EventCounts = defaultdict(int)
#total = 0
for key, value in editEventDict.items():
#frequency = int(key.strip().split('_')[-1])
BC = key.split("BC=")[1].split(" ")[0]
UMI = key.split("UMI=")[1].split(" ")[0]
stringline = outputEdit(value, tarPos)
### write out edit events
output.write("{}\t{}\t{}\n".format(BC, UMI, stringline))
#total += 1
# for align in value:
# EventCounts[align.toEditString()] += 1
# if align.indicator == "D":
# for i in range(align.refpos, align.refpos + len(align.readbase)):
# Edit_fre[i][1] += 1
# elif align.indicator == "I":
# Edit_fre[align.refpos][0] += 1
# ### write out the edit frequency
# for k, v in Edit_fre.items():
# editfre.write("{}\t{}\t{}\t{}\t{}\n".format(k, v[0], v[0]/total, v[1], v[1]/total))
### write out the Edit events counts
# eventcount.write("{}\t{}\n".format("Editevent", "counts"))
# clean_EventCounts = {}
# for eve, num in EventCounts.items():
# if "M" not in eve:
# clean_EventCounts[eve] = num
# eventcount.write("{}\t{}\n".format(eve, num))
# pickle.dump(clean_EventCounts,eventcountDic)
#editfre.close()
output.close()