def write_genepred_to_fasta(gpd_filename,ref_fasta,out_fasta):
ofile = open(out_fasta,'w')
ref = SequenceBasics.read_fasta_into_hash(ref_fasta)
with open(gpd_filename) as f:
for line in f:
if re.match('^#',line): continue
d = line_to_entry(line)
if d['chrom'] in ref:
seq = ''
for i in range(0,d['exonCount']):
seq = seq+ref[d['chrom']][d['exonStarts'][i]:d['exonEnds'][i]]
if d['strand'] == '-': seq = SequenceBasics.rc(seq)
ofile.write(">"+str(d['name'])+"\n"+seq.upper()+"\n")
ofile.close()
def convert_directionless_gpd_alignment_to_reference(sam_filename,genepred_filename,out_map):
conv = GenePredBasics.get_directionless_gpd_conversion(genepred_filename)
ofile = open(out_map,'w')
with open(sam_filename) as samfile:
for line in samfile:
line = line.rstrip()
if re.match('^@[A-Z][A-Z]\s',line): continue #skip header
d = sam_line_to_dictionary(line)
if d['rname'] == '*': continue #skip unmapped
startposition = d['pos']-1
readcoord = []
z = 0
for entry in d['cigar_array']:
if re.match('[MISX=]',entry['op']): # all the entries that map to the read
for i in range(0,entry['val']):
if re.match('[M=X]',entry['op']): #all the entries that match the reference alignment
readcoord.append(conv[d['rname']]['coordinates'][startposition+z])
z+=1
# lets ignore insertions for now
#else:
# readcoord.append('*')
if re.match('[DNH]',entry['op']):
z+= entry['val']
abbrev = conv[d['rname']]['chrom']+':'+SequenceBasics.collapse_coordinate_array(readcoord)
ofile.write(d['qname'] + "\t" + d['rname'] + "\t" + abbrev + "\n")
ofile.close()
def get_alternative_alignments(in_sam_line):
f = in_sam_line.rstrip().split("\t")
if len(f) <= 12:
return [] # move on if theres no optional tags
enstring = "\t".join(f[x] for x in range(11, len(f)))
m = re.search('XA:Z:(\S+)', enstring)
if not m:
return [] # move on if theres no SA:Z tag
secondary_alignments = m.group(1)
aligns = secondary_alignments.split(';')
bwalike = re.compile('^([^,]+),(\d+),([+-]),([^,]+),(\d+),(\d+)$')
otherlike = re.compile('^([^,]+),([+-])(\d+),([^,]+),(\d+),(\d+)$')
otherlike2 = re.compile('^([^,]+),([+-])(\d+),([^,]+),(\d+)$')
output = []
for align in aligns:
if align == '':
continue # I guess you can have empty segments and we should ignore them
m1 = bwalike.match(align)
m2 = otherlike.match(align)
m3 = otherlike2.match(align)
if m1:
chr = m1.group(1)
pos = m1.group(2)
strand = m1.group(3)
cigar = m1.group(4)
mapQ = m1.group(5)
nm = m1.group(6)
elif m2:
chr = m2.group(1)
pos = m2.group(3)
strand = m2.group(2)
cigar = m2.group(4)
mapQ = m2.group(5)
nm = m2.group(6)
elif m3:
chr = m3.group(1)
pos = m3.group(3)
strand = m3.group(2)
cigar = m3.group(4)
mapQ = m3.group(5)
nm = 0
else:
sys.stderr.write("WARNING: unable to parse secondary alignment\n" +
align + "\n")
sys.exit()
flag = '0'
seq = f[9]
phred = f[10]
if strand == '-':
flag = '16'
seq = SequenceBasics.rc(seq)
phred = phred[::-1]
samline= f[0]+"\t"+flag+"\t"+chr+"\t"+pos+"\t"+mapQ+"\t"+cigar+"\t"\
+ "*\t0\t0\t*\t*"
output.append(samline)
return output
def get_alternative_alignments(in_sam_line):
f = in_sam_line.rstrip().split("\t")
if len(f) <= 12:
return [] # move on if theres no optional tags
enstring = "\t".join(f[x] for x in range(11,len(f)))
m = re.search('XA:Z:(\S+)',enstring)
if not m:
return [] # move on if theres no SA:Z tag
secondary_alignments = m.group(1)
aligns = secondary_alignments.split(';')
bwalike = re.compile('^([^,]+),(\d+),([+-]),([^,]+),(\d+),(\d+)$')
otherlike = re.compile('^([^,]+),([+-])(\d+),([^,]+),(\d+),(\d+)$')
otherlike2 = re.compile('^([^,]+),([+-])(\d+),([^,]+),(\d+)$')
output = []
for align in aligns:
if align == '': continue # I guess you can have empty segments and we should ignore them
m1 = bwalike.match(align)
m2 = otherlike.match(align)
m3 = otherlike2.match(align)
if m1:
chr = m1.group(1)
pos = m1.group(2)
strand = m1.group(3)
cigar = m1.group(4)
mapQ = m1.group(5)
nm = m1.group(6)
elif m2:
chr = m2.group(1)
pos = m2.group(3)
strand = m2.group(2)
cigar = m2.group(4)
mapQ = m2.group(5)
nm = m2.group(6)
elif m3:
chr = m3.group(1)
pos = m3.group(3)
strand = m3.group(2)
cigar = m3.group(4)
mapQ = m3.group(5)
nm = 0
else:
sys.stderr.write("WARNING: unable to parse secondary alignment\n"+align+"\n")
sys.exit()
flag = '0'
seq = f[9]
phred = f[10]
if strand == '-':
flag = '16'
seq = SequenceBasics.rc(seq)
phred = phred[::-1]
samline= f[0]+"\t"+flag+"\t"+chr+"\t"+pos+"\t"+mapQ+"\t"+cigar+"\t"\
+ "*\t0\t0\t*\t*"
output.append(samline)
return output
def add_genepred_line(self,inline):
if not self.ref_hash:
sys.stderr.write("ERROR: Must assign a reference genome dictionary first\n")
sys.exit()
gpd = GenePredBasics.GenePredEntry(inline)
if gpd.value('name') in self.transcripts:
sys.stderr.write("WARNING: "+inline+" transcript was already set\n")
seq = ''
for i in range(0,gpd.value('exonCount')):
seq += self.ref_hash[gpd.value('chrom')][gpd.value('exonStarts')[i]:gpd.value('exonEnds')[i]].upper()
if gpd.value('strand') == '-': seq = SequenceBasics.rc(seq)
self.transcripts[gpd.value('name')] = seq
return
def set_read_fasta(self, read_fasta_file):
self.reads_set = True
gfr = SequenceBasics.GenericFastaFileReader(read_fasta_file)
self.reads = {}
while True:
e = gfr.read_entry()
if not e: break
if e['name'] in self.reads:
sys.stderr.write(
"Warning duplicate name in fasta file, could be big problems on sequence assignment.\n"
)
self.reads[e['name']] = e['seq'].upper()
gfr.close()
return
def add_genepred_line(self, inline):
if not self.ref_hash:
sys.stderr.write(
"ERROR: Must assign a reference genome dictionary first\n")
sys.exit()
gpd = GenePredBasics.GenePredEntry(inline)
if gpd.value('name') in self.transcripts:
sys.stderr.write("WARNING: " + inline +
" transcript was already set\n")
seq = ''
for i in range(0, gpd.value('exonCount')):
seq += self.ref_hash[gpd.value('chrom')][
gpd.value('exonStarts')[i]:gpd.value('exonEnds')[i]].upper()
if gpd.value('strand') == '-': seq = SequenceBasics.rc(seq)
self.transcripts[gpd.value('name')] = seq
return
def __init__(self,genomefasta,vcffile):
self.var_by_chr = {}
with open(vcffile) as inf:
for line in inf:
line = line.rstrip()
if re.match('^#',line): continue
f = line.split("\t")
chrom = f[0]
pos = int(f[1])
reference = f[3]
alternate = f[4]
if not chrom in self.var_by_chr:
self.var_by_chr[chrom] = {}
self.var_by_chr[chrom][pos] = {}
self.var_by_chr[chrom][pos]['ref'] = reference
self.var_by_chr[chrom][pos]['alt'] = alternate
self.ref_genome = SequenceBasics.read_fasta_into_hash(genomefasta)
def emit_paired_short_read(self,read_length):
[name,seq] = self.emit()
# Get the sequence name first
flipped_seq = random_flip(seq)
# Use fragmentation if its enabled
frag_seq = flipped_seq
if self.gaussian_fragmentation:
frag_len = max(self.gaussian_fragmentation['minimum'],int(random.gauss(self.gaussian_fragmentation['mu'],self.gaussian_fragmentation['sigma'])))
if frag_len == 0:
return [name, 'N'*read_length, 'N'*read_length]
frag_seq = random_fragment(flipped_seq,frag_len)
l1 = frag_seq[0:read_length]
if len(l1) < read_length:
l1 = l1 + 'N'*(read_length-len(l1))
rc_frag_seq = SequenceBasics.rc(frag_seq)
r1 = rc_frag_seq[0:read_length]
if len(r1) < read_length:
r1 = r1 + 'N'*(read_length-len(r1))
return [name,l1,r1]
def convert_directionless_gpd_alignment_to_reference(sam_filename,
genepred_filename,
out_map):
conv = GenePredBasics.get_directionless_gpd_conversion(genepred_filename)
ofile = open(out_map, 'w')
with open(sam_filename) as samfile:
for line in samfile:
line = line.rstrip()
if re.match('^@[A-Z][A-Z]\s', line): continue #skip header
d = sam_line_to_dictionary(line)
if d['rname'] == '*': continue #skip unmapped
startposition = d['pos'] - 1
readcoord = []
z = 0
for entry in d['cigar_array']:
if re.match(
'[MISX=]',
entry['op']): # all the entries that map to the read
for i in range(0, entry['val']):
if re.match(
'[M=X]', entry['op']
): #all the entries that match the reference alignment
readcoord.append(
conv[d['rname']]['coordinates'][startposition +
z])
z += 1
# lets ignore insertions for now
#else:
# readcoord.append('*')
if re.match('[DNH]', entry['op']):
z += entry['val']
abbrev = conv[d['rname']][
'chrom'] + ':' + SequenceBasics.collapse_coordinate_array(
readcoord)
ofile.write(d['qname'] + "\t" + d['rname'] + "\t" + abbrev + "\n")
ofile.close()
def set_genome(self, fasta):
self.genome = SequenceBasics.read_fasta_into_hash(fasta)
def main():
parser = argparse.ArgumentParser()
parser.add_argument("bwa_bam",
help="BAMFILE or - for sam streamed to stdin")
parser.add_argument('-o',
'--output',
help="OUTFILE or if not set use STDOUT")
group1 = parser.add_mutually_exclusive_group(required=True)
group1.add_argument("--query_fasta", help="FASTA for query sequences")
group1.add_argument("--query_fastq", help="FASTQ for query sequences")
parser.add_argument("--ref",
required=True,
help="FASTA for reference genome")
parser.add_argument(
"-S",
"--size",
help="linux sort option S, in kb if units not specified")
group2 = parser.add_mutually_exclusive_group()
group2.add_argument("--tempdir",
default='/tmp',
help="DIR to store a temp directory")
group2.add_argument("--specific_tempdir",
help="Exact DIR to work in, is not deleted")
parser.add_argument(
"--get_all_alignments",
action='store_true',
help="Be exhaustive in retrieving secondary and chimeric alignments")
args = parser.parse_args()
# Manage your tempdir
# put it into args.tempdir
if not args.specific_tempdir:
rnum = random.randint(1, 100000000)
args.tempdir = args.tempdir.rstrip('/') + '/weirathe.' + str(rnum)
else:
args.tempdir = args.specific_tempdir.rstrip('/')
if not os.path.exists(args.tempdir):
os.makedirs(args.tempdir)
inf = sys.stdin
if args.bwa_bam != '-':
p1 = subprocess.Popen(("samtools view " + args.bwa_bam).split(),
stdout=subprocess.PIPE)
inf = p1.stdout
# 1. Now we can start the process. First convert the sam to a psl
cmd = "sam_to_psl.py -"
if args.get_all_alignments:
cmd += " --get_all_alignments"
#No matter what we don't need to see the exact same alignment more than once
cmd += " | sort -T " + args.tempdir
if args.size:
cmd += " -S " + args.size
cmd += " | uniq"
#Sort the alignment based on query name
cmd += " | sort_psl.py - --tempdir " + args.tempdir
if args.size:
cmd += " -S " + args.size
#Put the fragmented alignments together
cmd += " | defragment_PSL_alignments.py - | sort_psl.py - --tempdir " + args.tempdir + " -o " + args.tempdir + "/1.psl"
if args.size:
cmd += " -S " + args.size
p2 = subprocess.Popen(cmd, shell=True, stdin=subprocess.PIPE)
for line in inf:
p2.stdin.write(line)
p2.communicate()
if args.bwa_bam != '-':
p1.communicate()
# 2. Get a sorted fasta file
cmd = "sort_fasta.py - --tempdir " + args.tempdir + " -o " + args.tempdir + '/2.query.fa'
if args.size:
cmd += " -S " + args.size
p3 = subprocess.Popen(cmd.split(), stdin=subprocess.PIPE)
if args.query_fasta:
gfr = SequenceBasics.GenericFastaFileReader(args.query_fasta)
else:
gfr = SequenceBasics.GenericFastqFileReader(args.query_fastq)
while True:
e = gfr.read_entry()
if not e: break
p3.stdin.write('>' + e['name'] + "\n" + e['seq'] + "\n")
p3.communicate()
gfr.close()
# 3. Fix the psl and output the results
of = sys.stdout
if args.output:
of = open(args.output, 'w')
cmd = "fix_psl_stats.py " + args.tempdir + '/1.psl ' + args.ref + ' ' + args.tempdir + '/2.query.fa | sort_psl.py - --tempdir ' + args.tempdir
if args.size:
cmd += " -S " + args.size
p4 = subprocess.Popen(cmd, shell=True, stdout=of)
p4.communicate()
# Clean up your temporary directory if you aren't in a specific one.
if not args.specific_tempdir:
rmtree(args.tempdir)
return
def get_sequence(self,ref_fasta_hash):
seq = ''.join([\
ref_fasta_hash[self.value('chrom')][self.value('exonStarts')[i]:self.value('exonEnds')[i]]\
for i in range(0,self.value('exonCount'))])
if self.value('strand') == '-': return SequenceBasics.rc(seq).upper()
return seq.upper()
def set_genome(self,fasta): self.genome = SequenceBasics.read_fasta_into_hash(fasta)
def random_flip(seq):
if random.random() < 0.5:
return seq
return SequenceBasics.rc(seq)
def convert_line(self,
psl_line,
query_sequence=None,
quality_sequence=None):
try:
pe = PSLBasics.line_to_entry(psl_line)
except:
sys.stderr.write("Problem parsing line:\n" + psl_line.rstrip() +
"\n")
return False
if len(pe['tStarts']) != len(pe['blockSizes']):
sys.stderr.write("Warning invalid psl entry: " + pe['qName'] +
"\n")
return False
#work on the positive strand case first
cigar = '*'
blocks = len(pe['blockSizes'])
starts = pe['qStarts']
#if pe['strand'] == '-':
# starts = [x for x in reversed(pe['qStarts_actual'])]
# print 'isrev'
q_coord_start = starts[0] + 1 # base-1 converted starting position
q_coord_end = starts[blocks -
1] + pe['blockSizes'][blocks -
1] # base-1 position
t_coord_start = pe['tStarts'][
0] + 1 # base-1 converted starting position
t_coord_end = pe['tStarts'][blocks -
1] + pe['blockSizes'][blocks -
1] # base-1 position
if pe['qName'] not in self.reads and self.reads_set is True:
sys.stderr.write("Warning: qName " + pe['qName'] +
" was not found in reads\n")
# we will clip the query sequence to begin and end from the aligned region
#q_seq = ''
#if self.reads_set:
# q_seq = self.reads[pe['qName']]
# 1. Get the new query to output
q_seq_trimmed = '*'
if self.reads_set or query_sequence:
q_seq_trimmed = query_sequence
if not query_sequence: # get it from the archive we loaded if we didn't give it
q_seq_trimmed = self.reads[pe['qName']]
if pe['strand'] == '-':
q_seq_trimmed = SequenceBasics.rc(q_seq_trimmed)
q_seq_trimmed = q_seq_trimmed[q_coord_start - 1:q_coord_end]
qual_trimmed = '*'
if self.qualities_set or quality_sequence:
qual_trimmed = quality_sequence
if not quality_sequence:
qual_trimmed = self.qualities[pe['qName']]
if pe['strand'] == '-':
qual_trimmed = qual_trimmed[::-1]
qual_trimmed = qual_trimmed[q_coord_start - 1:q_coord_end]
# 2. Get the cigar string to output
prev_diff = t_coord_start - q_coord_start
cigar = ''
#for i in range(0,blocks):
# current_diff = pe['tStarts'][i]-starts[i]
# delta = current_diff - prev_diff
# #print delta
# if delta >= self.min_intron_size:
# cigar += str(abs(delta))+'N'
# elif delta > 0: # we have a
# cigar += str(abs(delta))+'D'
# elif delta < 0: # we have a
# cigar += str(abs(delta))+'I'
# cigar += str(pe['blockSizes'][i])+'M' # our matches
# #print current_diff
# prev_diff = current_diff
qstarts = [x - pe['qStarts'][0] for x in pe['qStarts']]
tstarts = [x - pe['tStarts'][0] for x in pe['tStarts']]
query_index = 0
target_index = 0
junctions = []
for i in range(0, blocks):
qdif = qstarts[i] - query_index
tdif = tstarts[i] - target_index
if qdif > 0: # we have to insert
cigar += str(qdif) + 'I'
if tdif > self.min_intron_size: # we have an intron
cigar += str(tdif) + 'N'
junctions.append(i)
elif tdif > 0: # we have to delete
cigar += str(tdif) + 'D'
cigar += str(pe['blockSizes'][i]) + 'M'
query_index = qstarts[i] + pe['blockSizes'][i]
target_index = tstarts[i] + pe['blockSizes'][i]
### cigar done
# inspect junctions if we have a ref_genome
spliceflag_set = False
if self.ref_genome_set:
canon = 0
revcanon = 0
for i in junctions: #blocks following a junction
left_num = pe['tStarts'][i - 1] + pe['blockSizes'][i - 1]
left_val = self.ref_genome[pe['tName']][left_num:left_num +
2].upper()
right_num = pe['tStarts'][i - 1] - 2
right_val = self.ref_genome[pe['tName']][right_num:right_num +
2].upper()
junc = left_val + '-' + right_val
if junc in self.canonical: canon += 1
if junc in self.revcanonical: revcanon += 1
if canon > revcanon:
spliceflag_set = True
spliceflag = '+'
elif revcanon > canon:
spliceflag_set = True
spliceflag = '-'
# if we have junctions, and we should be setting direction but
# we can't figure out the direction skip ambiguous direction
if len(
junctions
) > 0 and self.skip_directionless_splice and spliceflag_set == False:
return False
samline = pe['qName'] + "\t" # 1. QNAME
if pe['strand'] == '-':
samline += '16' + "\t" # 2. FLAG
else:
samline += '0' + "\t"
samline += pe['tName'] + "\t" # 3. RNAME
samline += str(t_coord_start) + "\t" # 4. POS
samline += '0' + "\t" # 5. MAPQ
samline += cigar + "\t" # 6. CIGAR
samline += '*' + "\t" # 7. RNEXT
samline += '0' + "\t" # 8. PNEXT
samline += '0' + "\t" # 9. TLEN
samline += q_seq_trimmed + "\t" # 10. SEQ
samline += qual_trimmed + "\t" # 11. QUAL
if spliceflag_set:
samline += 'XS:A:' + spliceflag + "\t"
if self.ref_genome_set:
samline += 'NH:i:' + str(self.mapping_counts[pe['qName']]) + "\t"
samline += 'XC:i:' + str(len(junctions)) + "\t"
samline += 'NM:i:0'
return samline
def convert_line(self,psl_line,query_sequence=None,quality_sequence=None):
try:
pe = PSLBasics.line_to_entry(psl_line)
except:
sys.stderr.write("Problem parsing line:\n"+psl_line.rstrip()+"\n")
return False
if len(pe['tStarts']) != len(pe['blockSizes']):
sys.stderr.write("Warning invalid psl entry: "+pe['qName']+"\n")
return False
#work on the positive strand case first
cigar = '*'
blocks = len(pe['blockSizes'])
starts = pe['qStarts']
#if pe['strand'] == '-':
# starts = [x for x in reversed(pe['qStarts_actual'])]
# print 'isrev'
q_coord_start = starts[0]+1 # base-1 converted starting position
q_coord_end = starts[blocks-1]+pe['blockSizes'][blocks-1] # base-1 position
t_coord_start = pe['tStarts'][0]+1 # base-1 converted starting position
t_coord_end = pe['tStarts'][blocks-1]+pe['blockSizes'][blocks-1] # base-1 position
if pe['qName'] not in self.reads and self.reads_set is True:
sys.stderr.write("Warning: qName "+pe['qName']+" was not found in reads\n")
# we will clip the query sequence to begin and end from the aligned region
#q_seq = ''
#if self.reads_set:
# q_seq = self.reads[pe['qName']]
# 1. Get the new query to output
q_seq_trimmed = '*'
if self.reads_set or query_sequence:
q_seq_trimmed = query_sequence
if not query_sequence: # get it from the archive we loaded if we didn't give it
q_seq_trimmed = self.reads[pe['qName']]
if pe['strand'] == '-':
q_seq_trimmed = SequenceBasics.rc(q_seq_trimmed)
q_seq_trimmed = q_seq_trimmed[q_coord_start-1:q_coord_end]
qual_trimmed = '*'
if self.qualities_set or quality_sequence:
qual_trimmed = quality_sequence
if not quality_sequence:
qual_trimmed = self.qualities[pe['qName']]
if pe['strand'] == '-':
qual_trimmed = qual_trimmed[::-1]
qual_trimmed = qual_trimmed[q_coord_start-1:q_coord_end]
# 2. Get the cigar string to output
prev_diff = t_coord_start-q_coord_start
cigar = ''
#for i in range(0,blocks):
# current_diff = pe['tStarts'][i]-starts[i]
# delta = current_diff - prev_diff
# #print delta
# if delta >= self.min_intron_size:
# cigar += str(abs(delta))+'N'
# elif delta > 0: # we have a
# cigar += str(abs(delta))+'D'
# elif delta < 0: # we have a
# cigar += str(abs(delta))+'I'
# cigar += str(pe['blockSizes'][i])+'M' # our matches
# #print current_diff
# prev_diff = current_diff
qstarts = [x-pe['qStarts'][0] for x in pe['qStarts']]
tstarts = [x-pe['tStarts'][0] for x in pe['tStarts']]
query_index = 0
target_index = 0
junctions = []
for i in range(0,blocks):
qdif = qstarts[i] - query_index
tdif = tstarts[i] - target_index
if qdif > 0: # we have to insert
cigar += str(qdif) + 'I'
if tdif > self.min_intron_size: # we have an intron
cigar += str(tdif) + 'N'
junctions.append(i)
elif tdif > 0: # we have to delete
cigar += str(tdif) + 'D'
cigar += str(pe['blockSizes'][i]) + 'M'
query_index = qstarts[i]+pe['blockSizes'][i]
target_index = tstarts[i]+pe['blockSizes'][i]
### cigar done
# inspect junctions if we have a ref_genome
spliceflag_set = False
if self.ref_genome_set:
canon = 0
revcanon = 0
for i in junctions: #blocks following a junction
left_num = pe['tStarts'][i-1]+pe['blockSizes'][i-1]
left_val = self.ref_genome[pe['tName']][left_num:left_num+2].upper()
right_num = pe['tStarts'][i-1]-2
right_val = self.ref_genome[pe['tName']][right_num:right_num+2].upper()
junc = left_val + '-' + right_val
if junc in self.canonical: canon += 1
if junc in self.revcanonical: revcanon += 1
if canon > revcanon:
spliceflag_set = True
spliceflag = '+'
elif revcanon > canon:
spliceflag_set = True
spliceflag = '-'
# if we have junctions, and we should be setting direction but
# we can't figure out the direction skip ambiguous direction
if len(junctions) > 0 and self.skip_directionless_splice and spliceflag_set == False:
return False
samline = pe['qName'] + "\t" # 1. QNAME
if pe['strand'] == '-':
samline += '16' + "\t" # 2. FLAG
else:
samline += '0' + "\t"
samline += pe['tName'] + "\t" # 3. RNAME
samline += str(t_coord_start) + "\t" # 4. POS
samline += '0' + "\t" # 5. MAPQ
samline += cigar + "\t" # 6. CIGAR
samline += '*' + "\t" # 7. RNEXT
samline += '0' + "\t" # 8. PNEXT
samline += '0' + "\t" # 9. TLEN
samline += q_seq_trimmed + "\t" # 10. SEQ
samline += qual_trimmed + "\t" # 11. QUAL
if spliceflag_set:
samline += 'XS:A:'+spliceflag + "\t"
if self.ref_genome_set:
samline += 'NH:i:'+str(self.mapping_counts[pe['qName']]) + "\t"
samline += 'XC:i:'+str(len(junctions)) + "\t"
samline += 'NM:i:0'
return samline
