def construct_header_from_reference_fasta(ref_fasta_filename):
g = FastaData(open(ref_fasta_filename).read())
#g = SequenceBasics.read_fasta_into_hash(ref_fasta_filename)
chrs = {}
for name in sorted(g.keys()):
chrs[name] = len(g[name])
sys.stderr.write(name+" is there at length "+str(len(g[name]))+"\n")
header = ''
header += "@HD\tVN:1.0\tSO:coordinate\n"
for chr in sorted(chrs):
header += "@SQ\tSN:"+chr+"\tLN:"+str(chrs[chr])+"\n"
header += "@PG\tID:SamBasics.py\tVN:1.0\n"
return header
def construct_header_from_reference_fasta(ref_fasta_filename):
g = FastaData(open(ref_fasta_filename).read())
#g = SequenceBasics.read_fasta_into_hash(ref_fasta_filename)
chrs = {}
for name in sorted(g.keys()):
chrs[name] = len(g[name])
sys.stderr.write(name + " is there at length " + str(len(g[name])) +
"\n")
header = ''
header += "@HD\tVN:1.0\tSO:coordinate\n"
for chr in sorted(chrs):
header += "@SQ\tSN:" + chr + "\tLN:" + str(chrs[chr]) + "\n"
header += "@PG\tID:SamBasics.py\tVN:1.0\n"
return header
def main():
parser = argparse.ArgumentParser(
description="", formatter_class=argparse.ArgumentDefaultsHelpFormatter)
parser.add_argument('input', help="Use - for STDIN")
parser.add_argument('-r', '--reference', help="reference genome FASTA")
parser.add_argument('--no_qual',
action='store_true',
help="dont put in quality")
args = parser.parse_args()
ref = {}
if args.reference:
ref = FastaData(open(args.reference, 'rb').read())
if args.input == '-':
args.input = sys.stdin
else:
args.input = open(args.input)
h1 = '@HD VN:1.0 SO:unsorted'
h2 = '@PG ID:FA2UN PN:FA2UN VN:2016-06-09 CL:' + ' '.join(sys.argv)
print h1
print h2
if ref:
for chr in sorted(ref.keys()):
print "@SQ\tSN:" + chr + "\t" + 'LN:' + str(len(ref[chr]))
inf = FastqHandle(args.input)
for e in inf:
o = ''
o += e.name + "\t"
o += "4\t"
o += "*\t"
o += "0\t"
o += "0\t"
o += "*\t"
o += "*\t"
o += "0\t"
o += "0\t"
o += e.seq + "\t"
if args.no_qual:
o += "*\t"
else:
o += e.qual + "\t"
o += "XO:Z:NM"
print o
def main():
parser = argparse.ArgumentParser(description="",formatter_class=argparse.ArgumentDefaultsHelpFormatter)
parser.add_argument('input',help="Use - for STDIN")
parser.add_argument('-r','--reference',help="reference genome FASTA")
parser.add_argument('--no_qual',action='store_true',help="dont put in quality")
args = parser.parse_args()
ref = {}
if args.reference:
ref = FastaData(open(args.reference,'rb').read())
if args.input == '-':
args.input = sys.stdin
else: args.input = open(args.input)
h1 = '@HD VN:1.0 SO:unsorted'
h2 = '@PG ID:FA2UN PN:FA2UN VN:2016-06-09 CL:'+' '.join(sys.argv)
print h1
print h2
if ref:
for chr in sorted(ref.keys()):
print "@SQ\tSN:"+chr+"\t"+'LN:'+str(len(ref[chr]))
inf = FastqHandle(args.input)
for e in inf:
o = ''
o += e.name+"\t"
o += "4\t"
o += "*\t"
o += "0\t"
o += "0\t"
o += "*\t"
o += "*\t"
o += "0\t"
o += "0\t"
o += e.seq+"\t"
if args.no_qual:
o+= "*\t"
else:
o += e.qual+"\t"
o += "XO:Z:NM"
print o
def main():
parser = argparse.ArgumentParser(
description="", formatter_class=argparse.ArgumentDefaultsHelpFormatter)
parser.add_argument('input', help="Use - for STDIN or specify a BAM file")
parser.add_argument('-r',
'--reference',
help="Reference fasta",
required=True)
args = parser.parse_args()
ref = None
if args.reference:
ref = FastaData(open(args.reference, 'rb').read())
if args.input == '-':
args.input = SamStream(sys.stdin, reference=ref)
else:
args.input = BAMFile(args.input, reference=ref)
for e in args.input:
if e.is_aligned():
print e.get_PSL()
def main():
parser = argparse.ArgumentParser(description="Read a sam file and output a bed file in the format of junction_color.bed")
parser.add_argument('-o','--output',help='FILENAME is output')
parser.add_argument('--min_intron_size',type=int,default=68,help='minimum intron size')
parser.add_argument('infile',help='FILENAME of sam file or "-" for STDIN')
parser.add_argument('reference_genome',help='FILENAME of the reference genome')
args = parser.parse_args()
# get our reference genome
sys.stderr.write("reading reference genome\n")
#g = SequenceBasics.read_fasta_into_hash(args.reference_genome)
g = FastaData(open(args.reference_genome).read())
sys.stderr.write("finished reading reference genome\n")
inf = sys.stdin
read_mapping_count = {}
junctions = {}
if args.infile != '-':
inf = open(args.infile)
sys.stderr.write("reading through sam file\n")
zall = 0
zn = 0
while True:
line = inf.readline()
if not line: break
line = line.rstrip()
if SamBasics.is_header(line): continue
d = SamBasics.sam_line_to_dictionary(line)
chrom = d['rname']
if chrom =='*': continue
if chrom not in g.keys():
sys.stderr.write("WARNING: "+chrom+" not in reference, skipping\n")
continue
mate = 'U'
if SamBasics.check_flag(d['flag'],int('0x4',16)): #check if its unmapped
continue # we can ignore the unmapped things for now
if SamBasics.check_flag(d['flag'],int('0x40',16)):
mate = 'L'
elif SamBasics.check_flag(d['flag'],int('0x80',16)):
mate = 'R'
actual_read = d['qname']+"\t"+mate
if actual_read not in read_mapping_count:
read_mapping_count[actual_read] = 0
read_mapping_count[actual_read] += 1
has_intron = 0
start_loc = d['pos']
current_loc = start_loc
bounds = []
for i in range(0,len(d['cigar_array'])):
ce = d['cigar_array'][i]
if ce['op'] == 'N' and ce['val'] >= args.min_intron_size:
has_intron = 1
lbound = current_loc # should be the intron start base index-1
current_loc += ce['val']
rbound = current_loc # should be the second exon start base index-1
right_size = d['cigar_array'][i+1]['val']
bounds.append([lbound,rbound,right_size])
elif ce['op'] == 'D':
current_loc += ce['val']
elif re.match('[=XMSHP]',ce['op']):
current_loc += ce['val']
if has_intron == 0: continue # there are no splices to report here
#print actual_read
#print d['cigar']
#print d
#print start_loc
#print bounds
for bound in bounds:
zall += 1
intronflank = g[chrom][bound[0]-1:bound[0]+1].upper() + '-' + \
g[chrom][bound[1]-3:bound[1]-1].upper()
strand = ''
if is_canon(intronflank): # its a positive strand
strand = '+'
elif is_revcanon(intronflank): # its a negative strand
strand = '-'
else:
# We can't deal with the non-canonical splice sorry
zn += 1
sys.stderr.write("WARNING skipping non-canonical splice ("+str(zn)+"/"+str(zall)+")\r")
continue
# If we are still in we have successfully found a splice
out_chrom = chrom
out_start = bound[0]-51
out_end = bound[1]+49
out_name = '*' # this will be done later
out_score = 50
out_strand = strand
out_thickStart = out_start
out_thickEnd = out_end
out_rgb = '0,0,0'
out_block_count = 2
out_block_sizes = '50,50'
out_block_starts = '0,'+str(bound[1]-bound[0]+50)
bed = []
bed.append(out_chrom)
bed.append(str(out_start))
bed.append(str(out_end))
bed.append(out_name)
bed.append(str(out_score))
bed.append(out_strand)
bed.append(str(out_thickStart))
bed.append(str(out_thickEnd))
bed.append(out_rgb)
bed.append(str(out_block_count))
bed.append(out_block_sizes)
bed.append(out_block_starts)
entry = "\t".join(bed)
if entry not in junctions:
junctions[entry] = {}
junctions[entry]['reads'] = set()
junctions[entry]['positions'] = set()
junctions[entry]['right_sizes'] = set()
junctions[entry]['reads'].add(actual_read)
junctions[entry]['positions'].add(d['pos'])
junctions[entry]['right_sizes'].add(bound[2])
sys.stderr.write("\n")
sys.stderr.write("finished reading sam\n")
of = sys.stdout
if args.output:
of = open(args.output,'w')
if len(junctions) > 0: # if we have stuff lets print a header
of.write("track\tname=junctions\tdescription=\"SpliceMap junctions\" itemRgb=\"On\"\n")
for entry in junctions:
nR = len(junctions[entry]['reads'])
width = max(junctions[entry]['right_sizes'])-min(junctions[entry]['right_sizes'])
nNR = len(junctions[entry]['positions'])
nUR = 0
nMR = 0
for read in junctions[entry]['reads']:
if read_mapping_count[read] == 1:
nUR += 1
elif read_mapping_count[read] > 1:
nMR += 1
else:
sys.stderr.write("ERROR: nonsense read count\n")
return
name = '('+str(nR)+')['+str(width)+'_'+str(nNR)+']('+str(nUR)+'/'+str(nMR)+')'
bed = entry.split("\t")
bed[3] = name
of.write("\t".join(bed)+"\n")
def main():
#do our inputs
args = do_inputs()
of = sys.stdout
if args.output: of = open(args.output, 'w')
inf = sys.stdin
if args.input != '-':
if args.input[-3:] == '.gz':
inf = gzip.open(args.input)
else:
inf = open(args.input)
sys.stderr.write("reading in fasta\n")
f = FastaData(open(args.reference).read())
sh = GPDStream(inf)
gc_bins = range(0, args.number_of_bins)
bin_handles = []
for i in range(0, args.number_of_bins):
fname = args.tempdir + '/' + str(i) + '.bed.gz'
cmd2 = 'bed_to_bed_depth.py - -o ' + fname
p2 = Popen(cmd2.split(), stdin=PIPE, close_fds=True)
cmd1 = 'sort -k 1,1 -k2,2n -k3,3n -T ' + args.tempdir
p1 = Popen(cmd1.split(), stdin=PIPE, stdout=p2.stdin, close_fds=True)
bin_handles.append([p1, p2, fname, i])
if args.best_X_covered:
sys.stderr.write("work out stratified data\n")
cmd3 = 'bed_depth_to_stratified_coverage.py --minimum_coverage 10 --output_key ' + args.tempdir + '/key' + ' -r ' + args.reference + ' - -o ' + args.tempdir + '/combo.bed.gz'
pstrat3 = Popen(cmd3.split(), stdin=PIPE, close_fds=True)
cmd2 = 'bed_to_bed_depth.py -'
pstrat2 = Popen(cmd2.split(),
stdin=PIPE,
stdout=pstrat3.stdin,
close_fds=True)
cmd1 = 'sort -k 1,1 -k2,2n -k3,3n -T ' + args.tempdir
pstrat1 = Popen(cmd1.split(),
stdin=PIPE,
stdout=pstrat2.stdin,
close_fds=True)
num = 0
for gpd in sh:
num += 1
if (num % 1000 == 0): sys.stderr.write(str(num) + " \r")
results = []
if args.minimum_sequence_length:
if gpd.get_length() < args.minimum_sequence_length: continue
seq = gpd.get_sequence(f).upper()
seq_obj = Seq(seq)
n_count = seq_obj.n_count()
if len(seq) - n_count < args.min_non_N: continue
gc = seq_obj.gc_content()
gc_bin = int(args.number_of_bins * gc)
if gc_bin == args.number_of_bins: gc_bin -= 1
for exon in gpd.exons:
bed_bin = [
"\t".join([str(x) for x in exon.rng.get_bed_array()]),
gc_bin
]
results.append(bed_bin)
elif args.fragment:
seqlen = gpd.get_length()
if seqlen < args.fragment: continue
sfrags = int(float(seqlen) / float(args.fragment))
sremain = seqlen % args.fragment
offset = 0
if random.random() < 0.5: offset = sremain
#print '^^^'
for i in range(0, sfrags):
gsub = gpd.subset(i * args.fragment + offset,
(i + 1) * args.fragment + offset)
seq = gsub.get_sequence(f).upper()
seq_obj = Seq(seq)
n_count = seq_obj.n_count()
if len(seq) - n_count < args.min_non_N: continue
gc = seq_obj.gc_content()
gc_bin = int(args.number_of_bins * gc)
if gc_bin == args.number_of_bins: gc_bin -= 1
for exon in gsub.exons:
bed_bin = [
"\t".join([str(x) for x in exon.rng.get_bed_array()]),
gc_bin
]
results.append(bed_bin)
for val in results:
[bed, bin] = val
bin_handles[bin][0].stdin.write(bed + "\n")
if args.best_X_covered:
pstrat1.stdin.write(bed + "\n")
#if not gc: print len(gpd.get_sequence(f))
sys.stderr.write("\n")
for v in bin_handles:
v[0].communicate()
v[1].communicate()
if args.best_X_covered:
pstrat1.communicate()
pstrat2.communicate()
pstrat3.communicate()
# If we want stratified data we should do it here
sys.stderr.write("read the key\n")
d = {}
with open(args.tempdir + '/key') as inf:
header = inf.readline()
for line in inf:
f = line.rstrip().split("\t")
d[int(f[0])] = int(f[1])
if args.best_X_covered not in d:
sys.stderr.write(
"ERROR: the number of bases you specified is probably too big you didn't make the digit begin with 1 or 5 and restof the numbers be zero\n"
)
sys.exit()
num = d[args.best_X_covered]
ninf = gzip.open(args.tempdir + '/combo.bed.gz')
nof = gzip.open(args.tempdir + '/strat.bed.gz', 'w')
for line in ninf:
f = line.rstrip().split("\t")
if int(f[3]) >= num:
nof.write("\t".join(f[:-1]) + "\n")
nof.close()
ninf.close()
for i in range(0, len(bin_handles)):
v = bin_handles[i]
fname = v[2]
fname2 = args.tempdir + '/' + str(v[3]) + '.strata.bed.gz'
gof = open(fname2, 'w')
cmd2 = 'gzip'
p2 = Popen(cmd2.split(), stdout=gof, stdin=PIPE)
cmd1 = 'bedtools intersect -a ' + fname + ' -b ' + args.tempdir + '/strat.bed.gz'
p1 = Popen(cmd1.split(), stdout=p2.stdin)
p1.communicate()
p2.communicate()
gof.close()
# lets just replace the name of the file that the final output will read from
bin_handles[i][2] = fname2
# Now we have bed depths for each bin
for v in bin_handles:
fname = v[2]
#sys.stderr.write(fname+" ... prosessing\n")
depths = {}
bin = v[3]
inf = gzip.open(fname)
for line in inf:
f = line.rstrip().split("\t")
bases = int(f[2]) - int(f[1])
depth = int(f[3])
if depth not in depths: depths[depth] = 0
depths[depth] += bases
inf.close()
for depth in sorted(depths.keys()):
of.write(
str(bin) + "\t" + str(depth) + "\t" + str(depths[depth]) +
"\n")
of.close()
# Temporary working directory step 3 of 3 - Cleanup
if not args.specific_tempdir:
rmtree(args.tempdir)
def main(args):
# make our error profile report
sys.stderr.write("Reading reference fasta\n")
ref = FastaData(open(args.reference).read())
sys.stderr.write("Reading alignments\n")
epf = ErrorProfileFactory()
if args.random:
bf = None
if args.input_index:
bf = BAMFile(args.input,
reference=ref,
index_file=args.input_index)
bf.read_index(index_file=args.input_index)
else:
bf = BAMFile(args.input, reference=ref)
bf.read_index()
if not bf.has_index():
sys.stderr.write("Random access requires an index be set\n")
z = 0
strand = 'target'
if args.query: strand = 'query'
con = 0
while True:
rname = random.choice(bf.index.get_names())
#print rname
coord = bf.index.get_longest_target_alignment_coords_by_name(rname)
#print coord
if not coord: continue
e = bf.fetch_by_coord(coord)
if e.is_aligned():
epf.add_alignment(e)
z += 1
if z % 100 == 1:
con = epf.get_min_context_count(strand)
sys.stderr.write(
str(z) + " alignments, " + str(con) +
" min context coverage\r")
if args.max_alignments <= z: break
if args.stopping_point <= con: break
else:
bf = BAMFile(args.input, reference=ref)
z = 0
strand = 'target'
if args.query: strand = 'query'
con = 0
for e in bf:
if e.is_aligned():
epf.add_alignment(e)
z += 1
if z % 100 == 1:
con = epf.get_min_context_count(strand)
sys.stderr.write(
str(z) + " alignments, " + str(con) +
" min context coverage\r")
if args.max_alignments <= z: break
if args.stopping_point <= con: break
sys.stderr.write("\n")
sys.stderr.write('working with:' + "\n")
sys.stderr.write(
str(z) + " alignments, " + str(con) + " min context coverage" + "\n")
epf.write_context_error_report(args.tempdir + '/err.txt', strand)
for ofile in args.output:
cmd = args.rscript_path + ' ' + os.path.dirname(
os.path.realpath(__file__)
) + '/plot_base_error_context.r ' + args.tempdir + '/err.txt ' + ofile + ' '
if args.scale:
cmd += ' '.join([str(x) for x in args.scale])
sys.stderr.write(cmd + "\n")
call(cmd.split())
sys.stderr.write("finished\n")
if args.output_raw:
of = open(args.output_raw, 'w')
with open(args.tempdir + "/err.txt") as inf:
for line in inf:
of.write(line)
# Temporary working directory step 3 of 3 - Cleanup
if not args.specific_tempdir:
rmtree(args.tempdir)
def main(args):
random.seed(args.seed)
sum = 0
if args.reference_genome:
ref = FastaData(open(args.reference_genome).read())
for name in ref.keys():
sum += len(ref[name])
else:
with open(args.reference_lengths) as inf:
for line in inf:
f = line.rstrip().split("\t")
sum += int(f[1])
c = args.minimum_coverage
z = 0
values = {}
while c < sum:
z += 1
values[c] = z
c = c * 5
if c >= sum: break
z += 1
values[c] = z
c = c * 2
z += 1
values[sum] = z
for c in sorted(values.keys()):
values[c] = z - values[c] + 1
### Now values contains the stratified coverage values
if args.output_key:
of = open(args.output_key, 'w')
of.write("bp_size\tstrata_label\n")
for c in sorted(values.keys()):
of.write(str(c) + "\t" + str(values[c]) + "\n")
of.close()
inf = sys.stdin
if args.input != '-':
if args.input[-3:] == '.gz': inf = gzip.open(args.input)
else: inf = open(args.input)
of = sys.stdout
if args.output:
if args.output[-3:] == '.gz': of = gzip.open(args.output, 'w')
else: of = open(args.output, 'w')
depths = {}
vals = []
z = 0
for line in inf:
z += 1
if z % 100000 == 0:
sys.stderr.write(str(z) + " bed entries read \r")
f = line.rstrip().split("\t")
addition = 0
if not args.dont_make_unique:
addition = +args.unique_scale * random.random()
vals.append([f[0], int(f[1]), int(f[2]), float(f[3]) + addition])
z = 0
sys.stderr.write("\n")
for f in vals:
z += 1
if z % 100000 == 0:
sys.stderr.write(str(z) + " bed entries read \r")
#keep track of the number of bases at each depth
depth = f[3]
cov = f[2] - f[1]
if depth not in depths: depths[depth] = 0
depths[depth] += cov
#vals.append([f[0],int(f[1]),int(f[2]),depth])
sys.stderr.write("\n")
#total_bases = sum(depths.values())
#thresh = {}
#for strata in stratas:
# pos = 0
# cur = float(i)*float(total_bases)/float(args.strata)
stratas = sorted(values.keys())
pos = 0
depth_strata = {}
for d in reversed(sorted(depths.keys())):
pos += depths[d]
while stratas[0] < pos:
stratas.pop(0)
depth_strata[d] = values[stratas[0]]
#print str(d)+"\t"+str(values[stratas[0]])
#if float(pos) > cur:
# thresh[d] = [pos,i]
# break
vals[0][3] = depth_strata[vals[0][3]]
buffer = vals[0]
for val in vals[1:]:
val[3] = depth_strata[val[3]]
if val[1] == buffer[2] and val[3] == buffer[3] and val[0] == buffer[0]:
#print 'hello'
buffer[2] = val[2]
continue
else:
of.write(buffer[0] + "\t" + str(buffer[1]) + "\t" +
str(buffer[2]) + "\t" + str(buffer[3]) + "\n")
buffer = val
of.write(buffer[0] + "\t" + str(buffer[1]) + "\t" + str(buffer[2]) + "\t" +
str(buffer[3]) + "\n")
of.close()
def main():
#do our inputs
args = do_inputs()
global of
of = sys.stdout
if args.output:
if args.output[-4:] == '.bam':
cmd = 'samtools view -Sb - -o '+args.output
p = Popen(cmd.split(),stdin=PIPE)
of = p.stdin
else:
sys.stderr.write("ERROR: stdout and .bam are the only valid output formats\n")
sys.exit()
inf = sys.stdin
if args.input != '-':
if args.input[-3:] == '.gz':
inf = gzip.open(args.input)
else: inf = open(args.input)
sys.stderr.write("reading reference genome\n")
ref = FastaData(open(args.reference).read())
#shared = manager.dict()
shared = {}
for chr in sorted(ref.keys()):
sys.stderr.write("reading "+chr+"\n")
shared[chr] = ref[chr].upper()
ref.remove(chr)
sys.stderr.write("finished reading shared memory reference\n")
sys.stderr.write("Now make the header\n")
of.write("@HD\tVN:1.0\tSO:unknown\n")
of.write("@PG\tID:SLR\n")
for chr in sorted(shared.keys()):
of.write("@SQ\tSN:"+chr+"\tLN:"+str(len(shared[chr]))+"\n")
if args.threads > 1:
poo = Pool(processes=args.threads)
buffer = []
max_buffer = 1
z = 0
for line in inf:
z += 1
if z%1000==0: sys.stderr.write(str(z)+" \r")
buffer.append(line)
if len(buffer) >= max_buffer:
if args.threads == 1:
results = do_buffer(buffer,shared,args)
do_out(results)
else:
poo.apply_async(do_buffer,args=(buffer[:],shared,args,),callback=do_out)
buffer = []
if len(buffer) > 0:
if args.threads ==1:
results = do_buffer(buffer,shared,args)
do_out(results)
else:
poo.apply_async(do_buffer,args=(buffer[:],shared,args,),callback=do_out)
if args.threads > 1:
poo.close()
poo.join()
sys.stderr.write("\n")
if args.output:
p.communicate()
else: of.close()
# Temporary working directory step 3 of 3 - Cleanup
if not args.specific_tempdir:
rmtree(args.tempdir)
def main(args):
random.seed(args.seed)
sum = 0
if args.reference_genome:
ref = FastaData(open(args.reference_genome).read())
for name in ref.keys():
sum += len(ref[name])
else:
with open(args.reference_lengths) as inf:
for line in inf:
f = line.rstrip().split("\t")
sum += int(f[1])
c = args.minimum_coverage
z = 0
values = {}
while c < sum:
z += 1
values[c] = z
c = c*5
if c >= sum: break
z += 1
values[c] = z
c = c*2
z +=1
values[sum] = z
for c in sorted(values.keys()):
values[c] = z-values[c]+1
### Now values contains the stratified coverage values
if args.output_key:
of = open(args.output_key,'w')
of.write("bp_size\tstrata_label\n")
for c in sorted(values.keys()):
of.write(str(c)+"\t"+str(values[c])+"\n")
of.close()
inf = sys.stdin
if args.input != '-':
if args.input[-3:]=='.gz': inf = gzip.open(args.input)
else: inf = open(args.input)
of = sys.stdout
if args.output:
if args.output[-3:]=='.gz': of = gzip.open(args.output,'w')
else: of = open(args.output,'w')
depths = {}
vals = []
z = 0
for line in inf:
z += 1
if z % 100000 == 0: sys.stderr.write(str(z)+" bed entries read \r")
f = line.rstrip().split("\t")
addition = 0
if not args.dont_make_unique: addition = +args.unique_scale*random.random()
vals.append([f[0],int(f[1]),int(f[2]),float(f[3])+addition])
z = 0
sys.stderr.write("\n")
for f in vals:
z += 1
if z % 100000 == 0: sys.stderr.write(str(z)+" bed entries read \r")
#keep track of the number of bases at each depth
depth = f[3]
cov = f[2]-f[1]
if depth not in depths: depths[depth] = 0
depths[depth] += cov
#vals.append([f[0],int(f[1]),int(f[2]),depth])
sys.stderr.write("\n")
#total_bases = sum(depths.values())
#thresh = {}
#for strata in stratas:
# pos = 0
# cur = float(i)*float(total_bases)/float(args.strata)
stratas = sorted(values.keys())
pos = 0
depth_strata = {}
for d in reversed(sorted(depths.keys())):
pos += depths[d]
while stratas[0] < pos:
stratas.pop(0)
depth_strata[d] = values[stratas[0]]
#print str(d)+"\t"+str(values[stratas[0]])
#if float(pos) > cur:
# thresh[d] = [pos,i]
# break
vals[0][3] = depth_strata[vals[0][3]]
buffer = vals[0]
for val in vals[1:]:
val[3] = depth_strata[val[3]]
if val[1]==buffer[2] and val[3]==buffer[3] and val[0]==buffer[0]:
#print 'hello'
buffer[2] = val[2]
continue
else:
of.write(buffer[0]+"\t"+str(buffer[1])+"\t"+str(buffer[2])+"\t"+str(buffer[3])+"\n")
buffer = val
of.write(buffer[0]+"\t"+str(buffer[1])+"\t"+str(buffer[2])+"\t"+str(buffer[3])+"\n")
of.close()
def main(args):
sys.stderr.write("Read reference fasta\n")
fasta = FastaData(open(args.reference_fasta).read())
sys.stderr.write("Read alignment file\n")
bf = BAMFile(args.bam_input,reference=fasta)
bf.read_index()
total_qualities = []
for j in range(0,100):
total_qualities.append([])
ef = ErrorProfileFactory()
mincontext = 0
alignments = 0
for i in range(0,args.max_alignments):
rname = random.choice(bf.index.get_names())
coord = bf.index.get_longest_target_alignment_coords_by_name(rname)
if not coord: continue
bam = bf.fetch_by_coord(coord)
qual = bam.value('qual')
do_qualities(total_qualities,qual)
if not bam.is_aligned(): continue
alignments += 1
ef.add_alignment(bam)
if i%100 == 0:
mincontext = ef.get_min_context_count('target')
if mincontext:
if mincontext >= args.min_context and alignments >= args.min_alignments: break
sys.stderr.write(str(i+1)+" lines "+str(alignments)+"/"+str(args.min_alignments)+" alignments "+str(mincontext)+"/"+str(args.min_context)+" mincontext \r")
sys.stderr.write("\n")
sys.stderr.write(str(mincontext)+" minimum contexts observed\n")
target_context = ef.get_target_context_error_report()
general_error_stats = ef.get_alignment_errors().get_stats()
general_error_report = ef.get_alignment_errors().get_report()
# convert report to table
general_all = [x.split("\t") for x in general_error_report.rstrip().split("\n")]
general_head = general_all[0]
#print [y for y in general_all[1:]]
general_data = [[y[0],y[1],int(y[2]),int(y[3])] for y in general_all[1:]]
general_error_report = {'head':general_head,'data':general_data}
quality_counts = []
for vals in total_qualities:
garr = []
grp = {}
for v in vals:
if v[0] not in grp: grp[v[0]] = {}# check ordinal
if v[1] not in grp[v[0]]: grp[v[0]][v[1]] = 0 # run length
grp[v[0]][v[1]]+=1
for ordval in sorted(grp.keys()):
for runlen in sorted(grp[ordval].keys()):
garr.append([ordval,runlen,grp[ordval][runlen]])
quality_counts.append(garr)
#Quailty counts now has 100 bins, each has an ordered array of
# [ordinal_quality, run_length, observation_count]
# Can prepare an output
output = {}
output['quality_counts'] = quality_counts
output['context_error'] = target_context
output['alignment_error'] = general_error_report
output['error_stats'] = general_error_stats
of = None
if args.output[-3:]=='.gz':
of = gzip.open(args.output,'w')
else: of = open(args.output,'w')
of.write(base64.b64encode(zlib.compress(json.dumps(output)))+"\n")
of.close()
# Temporary working directory step 3 of 3 - Cleanup
if not args.specific_tempdir:
rmtree(args.tempdir)
def main(args):
sys.stderr.write("Reading our reference Fasta\n")
ref = FastaData(open(args.reference, 'rb').read())
sys.stderr.write("Finished reading our reference Fasta\n")
bf = None
if args.input_index:
bf = BAMFile(args.input, reference=ref, index_file=args.input_index)
bf.read_index(index_file=args.input_index)
else:
bf = BAMFile(args.input, reference=ref)
bf.read_index()
epf = ErrorProfileFactory()
if args.random:
if not bf.has_index():
sys.stderr.write(
"Random access requires our format of index bgi to be set\n")
sys.exit()
z = 0
while True:
rname = random.choice(bf.index.get_names())
coord = bf.index.get_longest_target_alignment_coords_by_name(rname)
if not coord: continue
e = bf.fetch_by_coord(coord)
if e.is_aligned():
epf.add_alignment(e)
z += 1
#print z
if z % 100 == 1:
con = epf.get_alignment_errors().alignment_length
if args.max_length <= con: break
sys.stderr.write(
str(con) + "/" + str(args.max_length) +
" bases from " + str(z) + " alignments\r")
sys.stderr.write("\n")
else:
z = 0
for e in bf:
if e.is_aligned():
epf.add_alignment(e)
z += 1
#print z
if z % 100 == 1:
con = epf.get_alignment_errors().alignment_length
if args.max_length <= con: break
sys.stderr.write(
str(con) + "/" + str(args.max_length) +
" bases from " + str(z) + " alignments\r")
sys.stderr.write("\n")
of = open(args.tempdir + '/report.txt', 'w')
of.write(epf.get_alignment_errors().get_report())
of.close()
for ofile in args.output:
cmd = args.rscript_path + ' ' + os.path.dirname(
os.path.realpath(__file__)
) + '/plot_alignment_errors.r ' + args.tempdir + '/report.txt ' + ofile + ' '
if args.scale:
cmd += ' '.join([str(x) for x in args.scale])
sys.stderr.write(cmd + "\n")
call(cmd.split())
if args.output_raw:
of = open(args.output_raw, 'w')
with open(args.tempdir + "/report.txt") as inf:
for line in inf:
of.write(line)
of.close()
if args.output_stats:
of = open(args.output_stats, 'w')
of.write(epf.get_alignment_errors().get_stats())
of.close()
sys.stderr.write("finished\n")
# Temporary working directory step 3 of 3 - Cleanup
if not args.specific_tempdir:
rmtree(args.tempdir)
def set_reference_genome(self, ref_genome):
self.ref_genome_set = True
self.ref_genome = FastaData(open(ref_genome).read())
def main():
#do our inputs
args = do_inputs()
global of
of = sys.stdout
if args.output:
if args.output[-4:] == '.bam':
cmd = 'samtools view -Sb - -o ' + args.output
p = Popen(cmd.split(), stdin=PIPE)
of = p.stdin
else:
sys.stderr.write(
"ERROR: stdout and .bam are the only valid output formats\n")
sys.exit()
inf = sys.stdin
if args.input != '-':
if args.input[-3:] == '.gz':
inf = gzip.open(args.input)
else:
inf = open(args.input)
sys.stderr.write("reading reference genome\n")
ref = FastaData(open(args.reference).read())
#shared = manager.dict()
shared = {}
for chr in sorted(ref.keys()):
sys.stderr.write("reading " + chr + "\n")
shared[chr] = ref[chr].upper()
ref.remove(chr)
sys.stderr.write("finished reading shared memory reference\n")
sys.stderr.write("Now make the header\n")
of.write("@HD\tVN:1.0\tSO:unknown\n")
of.write("@PG\tID:SLR\n")
for chr in sorted(shared.keys()):
of.write("@SQ\tSN:" + chr + "\tLN:" + str(len(shared[chr])) + "\n")
if args.threads > 1:
poo = Pool(processes=args.threads)
buffer = []
max_buffer = 1
z = 0
for line in inf:
z += 1
if z % 1000 == 0: sys.stderr.write(str(z) + " \r")
buffer.append(line)
if len(buffer) >= max_buffer:
if args.threads == 1:
results = do_buffer(buffer, shared, args)
do_out(results)
else:
poo.apply_async(do_buffer,
args=(
buffer[:],
shared,
args,
),
callback=do_out)
buffer = []
if len(buffer) > 0:
if args.threads == 1:
results = do_buffer(buffer, shared, args)
do_out(results)
else:
poo.apply_async(do_buffer,
args=(
buffer[:],
shared,
args,
),
callback=do_out)
if args.threads > 1:
poo.close()
poo.join()
sys.stderr.write("\n")
if args.output:
p.communicate()
else:
of.close()
# Temporary working directory step 3 of 3 - Cleanup
if not args.specific_tempdir:
rmtree(args.tempdir)
