def parse(fn):
hll = HLLCounter(.01, K)
lens = []
names = []
gc_len = 0
n_ambiguous = 0
for contig in ReadParser(fn):
sequence = contig.sequence
lens.append(len(sequence))
names.append(contig.name)
if DNA.match(sequence) is None:
raise RuntimeError('non-ACGTN characters not supported. '\
'Offending transcript: \n>{0}\n{1}\nbad'\
.format(contig.name, contig.sequence))
if 'N' in sequence:
sequence = sequence.replace('N', 'A')
n_ambiguous += 1
hll.consume_string(sequence)
gc_len += contig.sequence.count('C')
gc_len += contig.sequence.count('G')
S = pd.Series(lens, index=names)
try:
S.sort_values()
except AttributeError:
S.sort()
gc_perc = float(gc_len) / S.sum()
return S, hll.estimate_cardinality(), gc_perc, n_ambiguous
def get_unique_kmers(mmetsp, fasta):
print(fasta)
counter = HLLCounter(0.1, 25)
counter.consume_fasta(fasta)
unique_kmers = counter.estimate_cardinality()
print(unique_kmers)
return unique_kmers
def parse(fn):
hll = HLLCounter(.01, K)
lens = []
names = []
gc_len = 0
n_ambiguous = 0
for contig in ReadParser(fn):
sequence = contig.sequence
lens.append(len(sequence))
names.append(contig.name)
if DNA.match(sequence) is None:
raise RuntimeError('non-ACGTN characters not supported. '\
'Offending transcript: \n>{0}\n{1}\nbad'\
.format(contig.name, contig.sequence))
if 'N' in sequence:
sequence = sequence.replace('N', 'A')
n_ambiguous += 1
hll.consume_string(sequence)
gc_len += contig.sequence.count('C')
gc_len += contig.sequence.count('G')
S = pd.Series(lens, index=names)
try:
S.sort_values()
except AttributeError:
S.sort()
gc_perc = float(gc_len) / S.sum()
print('return')
return S, hll.estimate_cardinality(), gc_perc, n_ambiguous
def get_unique_kmers(sra,fasta): print fasta counter = HLLCounter(0.1,25) counter.consume_fasta(fasta) unique_kmers = counter.estimate_cardinality() print unique_kmers return unique_kmers
def parse(fn):
hll = HLLCounter(.01, K)
lens = []
names = []
gc_len = 0
for contig in ReadParser(fn):
lens.append(len(contig.sequence))
names.append(contig.name)
hll.consume_string(contig.sequence)
gc_len += contig.sequence.count('C')
gc_len += contig.sequence.count('G')
S = pd.Series(lens, index=names)
S.sort()
gc_perc = float(gc_len) / S.sum()
return S, hll.estimate_cardinality(), gc_perc
def parse(fn):
hll = HLLCounter(.01, K)
lens = []
names = []
gc_len = 0
for contig in ReadParser(fn):
lens.append(len(contig.sequence))
names.append(contig.name)
hll.consume_string(contig.sequence)
gc_len += contig.sequence.count('C')
gc_len += contig.sequence.count('G')
S = pd.Series(lens, index=names)
try:
S.sort_values()
except AttributeError:
S.sort()
gc_perc = float(gc_len) / S.sum()
return S, hll.estimate_cardinality(), gc_perc
