def main():
info('correct-reads.py', ['streaming'])
parser = get_parser()
args = parser.parse_args()
###
if len(set(args.input_filenames)) != len(args.input_filenames):
print >>sys.stderr, \
"Error: Cannot input the same filename multiple times."
sys.exit(1)
###
report_on_config(args)
check_valid_file_exists(args.input_filenames)
check_space(args.input_filenames, args.force)
if args.savegraph:
check_space_for_graph(
args.n_tables * args.min_tablesize, args.force)
K = args.ksize
CUTOFF = args.cutoff
NORMALIZE_LIMIT = args.normalize_to
if args.loadgraph:
print >>sys.stderr, 'loading k-mer countgraph from', args.loadgraph
ct = khmer.load_countgraph(args.loadgraph)
else:
print >>sys.stderr, 'making k-mer countgraph'
ct = khmer.new_countgraph(K, args.min_tablesize, args.n_tables)
tempdir = tempfile.mkdtemp('khmer', 'tmp', args.tempdir)
print >>sys.stderr, 'created temporary directory %s; ' \
'use -T to change location' % tempdir
aligner = khmer.ReadAligner(ct, args.cutoff, args.bits_theta)
# ### FIRST PASS ###
save_pass2_total = 0
n_bp = 0
n_reads = 0
written_bp = 0
written_reads = 0
corrected_reads = 0
pass2list = []
for filename in args.input_filenames:
pass2filename = os.path.basename(filename) + '.pass2'
pass2filename = os.path.join(tempdir, pass2filename)
if args.out is None:
corrfp = open(os.path.basename(filename) + '.corr', 'w')
else:
corrfp = args.out
pass2list.append((filename, pass2filename, corrfp))
screed_iter = screed.open(filename, parse_description=False)
pass2fp = open(pass2filename, 'w')
save_pass2 = 0
n = 0
paired_iter = broken_paired_reader(screed_iter, min_length=K,
force_single=args.ignore_pairs)
for n, is_pair, read1, read2 in paired_iter:
if n % 10000 == 0:
print >>sys.stderr, '...', n, filename, save_pass2, \
n_reads, n_bp, written_reads, written_bp
# we want to track paired reads here, to make sure that pairs
# are not split between first pass and second pass.
if is_pair:
n_reads += 2
n_bp += len(read1.sequence) + len(read2.sequence)
seq1 = read1.sequence.replace('N', 'A')
seq2 = read2.sequence.replace('N', 'A')
med1, _, _ = ct.get_median_count(seq1)
med2, _, _ = ct.get_median_count(seq2)
if med1 < NORMALIZE_LIMIT or med2 < NORMALIZE_LIMIT:
ct.consume(seq1)
ct.consume(seq2)
write_record_pair(read1, read2, pass2fp)
save_pass2 += 2
else:
is_aligned, new_seq1 = correct_sequence(aligner, seq1)
if is_aligned:
if new_seq1 != read1.sequence:
corrected_reads += 1
read1.sequence = new_seq1
if hasattr(read1, 'quality'):
fix_quality(read1)
is_aligned, new_seq2 = correct_sequence(aligner, seq2)
if is_aligned:
if new_seq2 != read2.sequence:
corrected_reads += 1
read2.sequence = new_seq2
if hasattr(read2, 'quality'):
fix_quality(read2)
write_record_pair(read1, read2, corrfp)
written_reads += 2
written_bp += len(read1)
written_bp += len(read2)
else:
n_reads += 1
n_bp += len(read1.sequence)
seq = read1.sequence.replace('N', 'A')
med, _, _ = ct.get_median_count(seq)
# has this portion of the graph saturated? if not,
# consume & save => pass2.
if med < NORMALIZE_LIMIT:
ct.consume(seq)
write_record(read1, pass2fp)
save_pass2 += 1
else: # trim!!
is_aligned, new_seq = correct_sequence(aligner, seq)
if is_aligned:
if new_seq != read1.sequence:
corrected_reads += 1
read1.sequence = new_seq
if hasattr(read1, 'quality'):
fix_quality(read1)
write_record(read1, corrfp)
written_reads += 1
written_bp += len(new_seq)
pass2fp.close()
print >>sys.stderr, '%s: kept aside %d of %d from first pass, in %s' \
% (filename, save_pass2, n, filename)
save_pass2_total += save_pass2
# ### SECOND PASS. ###
skipped_n = 0
skipped_bp = 0
for _, pass2filename, corrfp in pass2list:
print >>sys.stderr, ('second pass: looking at sequences kept aside '
'in %s') % pass2filename
# note that for this second pass, we don't care about paired
# reads - they will be output in the same order they're read in,
# so pairs will stay together if not orphaned. This is in contrast
# to the first loop.
for n, read in enumerate(screed.open(pass2filename,
parse_description=False)):
if n % 10000 == 0:
print >>sys.stderr, '... x 2', n, pass2filename, \
written_reads, written_bp
seq = read.sequence.replace('N', 'A')
med, _, _ = ct.get_median_count(seq)
# do we retain low-abundance components unchanged?
if med < NORMALIZE_LIMIT and args.variable_coverage:
write_record(read, corrfp)
written_reads += 1
written_bp += len(read.sequence)
skipped_n += 1
skipped_bp += len(read.sequence)
# otherwise, examine/correct.
else: # med >= NORMALIZE LIMIT or not args.variable_coverage
is_aligned, new_seq = correct_sequence(aligner, seq)
if is_aligned:
if new_seq != read.sequence:
corrected_reads += 1
read.sequence = new_seq
if hasattr(read, 'quality'):
fix_quality(read)
write_record(read, corrfp)
written_reads += 1
written_bp += len(new_seq)
print >>sys.stderr, 'removing %s' % pass2filename
os.unlink(pass2filename)
print >>sys.stderr, 'removing temp directory & contents (%s)' % tempdir
shutil.rmtree(tempdir)
n_passes = 1.0 + (float(save_pass2_total) / n_reads)
percent_reads_corrected = float(corrected_reads +
(n_reads - written_reads)) /\
n_reads * 100.0
print >>sys.stderr, 'read %d reads, %d bp' % (n_reads, n_bp,)
print >>sys.stderr, 'wrote %d reads, %d bp' % (written_reads, written_bp,)
print >>sys.stderr, 'looked at %d reads twice (%.2f passes)' % \
(save_pass2_total, n_passes)
print >>sys.stderr, 'removed %d reads and corrected %d reads (%.2f%%)' % \
(n_reads - written_reads, corrected_reads, percent_reads_corrected)
print >>sys.stderr, 'removed %.2f%% of bases (%d total)' % \
((1 - (written_bp / float(n_bp))) * 100.0, n_bp - written_bp)
if args.variable_coverage:
percent_reads_hicov = 100.0 * float(n_reads - skipped_n) / n_reads
print >>sys.stderr, '%d reads were high coverage (%.2f%%);' % \
(n_reads - skipped_n, percent_reads_hicov)
print >>sys.stderr, ('skipped %d reads/%d bases because of low'
'coverage') % (skipped_n, skipped_bp)
fp_rate = \
khmer.calc_expected_collisions(ct, args.force, max_false_pos=.8)
# for max_false_pos see Zhang et al., http://arxiv.org/abs/1309.2975
print >>sys.stderr, \
'fp rate estimated to be {fpr:1.3f}'.format(fpr=fp_rate)
print >>sys.stderr, 'output in *.corr'
if args.savegraph:
print >>sys.stderr, "Saving k-mer countgraph to", args.savegraph
ct.save(args.savegraph)
def main(): # pylint: disable=too-many-branches,too-many-statements
info('normalize-by-median.py', ['diginorm'])
args = get_parser().parse_args()
report_on_config(args)
report_fp = args.report
check_valid_file_exists(args.input_filenames)
check_space(args.input_filenames, args.force)
if args.savetable:
check_space_for_hashtable(args.n_tables * args.min_tablesize,
args.force)
# list to save error files along with throwing exceptions
if args.force:
corrupt_files = []
if args.loadtable:
print 'loading k-mer counting table from', args.loadtable
htable = khmer.load_counting_hash(args.loadtable)
else:
print 'making k-mer counting table'
htable = khmer.new_counting_hash(args.ksize, args.min_tablesize,
args.n_tables)
total = 0
discarded = 0
input_filename = None
if args.single_output_filename:
output_name = args.single_output_filename
if args.append:
outfp = open(args.single_output_filename, 'a')
else:
outfp = open(args.single_output_filename, 'w')
for index, input_filename in enumerate(args.input_filenames):
if not args.single_output_filename:
output_name = os.path.basename(input_filename) + '.keep'
outfp = open(output_name, 'w')
total_acc = 0
discarded_acc = 0
try:
total_acc, discarded_acc = normalize_by_median(
input_filename, outfp, htable, args, report_fp)
except IOError as err:
handle_error(err, output_name, input_filename, args.fail_save,
htable)
if not args.force:
print >> sys.stderr, '** Exiting!'
sys.exit(1)
else:
print >> sys.stderr, '*** Skipping error file, moving on...'
corrupt_files.append(input_filename)
else:
if total_acc == 0 and discarded_acc == 0:
print 'SKIPPED empty file', input_filename
else:
total += total_acc
discarded += discarded_acc
print 'DONE with {inp}; kept {kept} of {total} or {perc:2}%'\
.format(inp=input_filename, kept=total - discarded,
total=total, perc=int(100. - discarded /
float(total) * 100.))
print 'output in', output_name
if (args.dump_frequency > 0 and index > 0
and index % args.dump_frequency == 0):
print 'Backup: Saving k-mer counting file through', input_filename
if args.savetable:
hashname = args.savetable
print '...saving to', hashname
else:
hashname = 'backup.ct'
print 'Nothing given for savetable, saving to', hashname
htable.save(hashname)
if args.report_total_kmers:
print >> sys.stderr, 'Total number of unique k-mers: {0}'.format(
htable.n_unique_kmers())
if args.savetable:
print 'Saving k-mer counting table through', input_filename
print '...saving to', args.savetable
htable.save(args.savetable)
fp_rate = khmer.calc_expected_collisions(htable)
print 'fp rate estimated to be {fpr:1.3f}'.format(fpr=fp_rate)
if args.force and len(corrupt_files) > 0:
print >> sys.stderr, "** WARNING: Finished with errors!"
print >> sys.stderr, "** IOErrors occurred in the following files:"
print >> sys.stderr, "\t", " ".join(corrupt_files)
if fp_rate > MAX_FALSE_POSITIVE_RATE:
print >> sys.stderr, "**"
print >> sys.stderr, ("** ERROR: the k-mer counting table is too small"
" for this data set. Increase tablesize/# "
"tables.")
print >> sys.stderr, "**"
print >> sys.stderr, "** Do not use these results!!"
if not args.force:
sys.exit(1)
def main(): # pylint: disable=too-many-branches,too-many-statements
start_time = time.time()
parser = sanitize_help(get_parser())
args = parser.parse_args()
configure_logging(args.quiet)
report_on_config(args)
report_fp = args.report
force_single = args.force_single
# check for similar filenames
# if we're using a single output file only check for identical filenames
# otherwise, check for identical BASE names as well.
filenames = []
basenames = []
for pathfilename in args.input_filenames:
filenames.append(pathfilename)
if args.single_output_file:
continue # nothing more to worry about
basename = os.path.basename(pathfilename)
if basename in basenames:
log_error('ERROR: Duplicate filename--Cannot handle this!')
log_error('** Exiting!')
sys.exit(1)
basenames.append(basename)
# check that files exist and there is sufficient output disk space.
check_valid_file_exists(args.input_filenames)
check_space(args.input_filenames, args.force)
if args.savegraph is not None:
graphsize = calculate_graphsize(args, 'countgraph')
check_space_for_graph(args.savegraph, graphsize, args.force)
# load or create counting table.
if args.loadgraph:
log_info('loading k-mer countgraph from {graph}', graph=args.loadgraph)
countgraph1 = Countgraph.load(args.loadgraph)
# load second counting table.
if args.loadgraph2:
log_info('loading k-mer countgraph from {graph}',
graph=args.loadgraph2)
countgraph2 = Countgraph.load(args.loadgraph2)
# make a list of all filenames and if they're paired or not;
# if we don't know if they're paired, default to allowing but not
# forcing pairing.
files = []
for element in filenames:
files.append([element, args.paired])
if args.unpaired_reads:
files.append([args.unpaired_reads, False])
#
# main loop: iterate over all files given, do diginorm.
#
for filename, require_paired in files:
if not args.single_output_file:
output_name = os.path.basename(filename) + '.keep'
outfp = open(output_name, 'wb')
outfp = get_file_writer(outfp, args.gzip, args.bzip)
screed_iter = clean_input_reads(screed.open(filename))
reader = broken_paired_reader(screed_iter,
min_length=args.ksize,
force_single=force_single,
require_paired=require_paired)
# actually do diginorm
for _, is_paired, read0, read1 in reader:
for record in snarf(is_paired, read0, read1, countgraph1,
countgraph2):
if record is not None:
write_record(record, outfp)
print("--- %s seconds ---" % (time.time() - start_time))
def main(): # pylint: disable=too-many-branches,too-many-statements
info('normalize-by-median.py', ['diginorm'])
args = get_parser().parse_args()
report_on_config(args)
report_fp = args.report
# check for similar filenames
filenames = []
for pathfilename in args.input_filenames:
filename = pathfilename.split('/')[-1]
if (filename in filenames):
print >>sys.stderr, "WARNING: At least two input files are named \
%s . (The script normalize-by-median.py can not handle this, only one .keep \
file for one of the input files will be generated.)" % filename
else:
filenames.append(filename)
# check for others
check_valid_file_exists(args.input_filenames)
check_space(args.input_filenames, args.force)
if args.savetable:
check_space_for_hashtable(
args.n_tables * args.min_tablesize, args.force)
# list to save error files along with throwing exceptions
if args.force:
corrupt_files = []
if args.loadtable:
print 'loading k-mer counting table from', args.loadtable
htable = khmer.load_counting_hash(args.loadtable)
else:
print >> sys.stderr, 'making k-mer counting table'
htable = khmer.new_counting_hash(args.ksize, args.min_tablesize,
args.n_tables)
total = 0
discarded = 0
input_filename = None
if args.single_output_file:
outfp = args.single_output_file
if args.single_output_file is sys.stdout:
output_name = '/dev/stdout'
else:
output_name = args.single_output_file.name
for index, input_filename in enumerate(args.input_filenames):
if not args.single_output_file:
output_name = os.path.basename(input_filename) + '.keep'
outfp = open(output_name, 'w')
total_acc = 0
discarded_acc = 0
try:
total_acc, discarded_acc = normalize_by_median(input_filename,
outfp, htable, args,
report_fp)
except IOError as err:
handle_error(err, output_name, input_filename, args.fail_save,
htable)
if not args.force:
print >> sys.stderr, '** Exiting!'
sys.exit(1)
else:
print >> sys.stderr, '*** Skipping error file, moving on...'
corrupt_files.append(input_filename)
else:
if total_acc == 0 and discarded_acc == 0:
print >> sys.stderr, 'SKIPPED empty file', input_filename
else:
total += total_acc
discarded += discarded_acc
print >> sys.stderr, \
'DONE with {inp}; kept {kept} of {total} or {perc:2}%'\
.format(inp=input_filename, kept=total - discarded,
total=total, perc=int(100. - discarded /
float(total) * 100.))
print >> sys.stderr, 'output in', output_name
if (args.dump_frequency > 0 and
index > 0 and index % args.dump_frequency == 0):
print 'Backup: Saving k-mer counting file through', input_filename
if args.savetable:
hashname = args.savetable
print '...saving to', hashname
else:
hashname = 'backup.ct'
print 'Nothing given for savetable, saving to', hashname
htable.save(hashname)
if args.report_total_kmers:
print >> sys.stderr, 'Total number of unique k-mers: {0}'.format(
htable.n_unique_kmers())
if args.savetable:
print 'Saving k-mer counting table through', input_filename
print '...saving to', args.savetable
htable.save(args.savetable)
fp_rate = \
khmer.calc_expected_collisions(htable, args.force, max_false_pos=.8)
# for max_false_pos see Zhang et al., http://arxiv.org/abs/1309.2975
print >> sys.stderr, \
'fp rate estimated to be {fpr:1.3f}'.format(fpr=fp_rate)
if args.force and len(corrupt_files) > 0:
print >> sys.stderr, "** WARNING: Finished with errors!"
print >> sys.stderr, "** IOErrors occurred in the following files:"
print >> sys.stderr, "\t", " ".join(corrupt_files)
def main():
parser = argparse.ArgumentParser()
parser.add_argument('database')
parser.add_argument('input_filenames',
metavar='input_sequence_filename',
help='Input FAST[AQ] sequence filename.',
nargs='+')
parser.add_argument('-k', '--ksize', type=int, default=31)
parser.add_argument('-p',
'--paired',
action='store_true',
help='require that all sequences be properly paired')
parser.add_argument('--force_single',
dest='force_single',
action='store_true',
help='treat all sequences as single-ended/unpaired')
parser.add_argument('-u',
'--unpaired-reads',
metavar="unpaired_reads_filename",
help='include a file of unpaired reads to which '
'-p/--paired does not apply.')
parser.add_argument('-f',
'--force',
dest='force',
help='continue past file reading errors',
action='store_true')
args = parser.parse_args()
force_single = args.force_single
#if args.reads == '-':
# args.reads = sys.stdin
# check that input files exist
check_valid_file_exists(args.input_filenames)
filenames = []
for pathfilename in args.input_filenames:
filenames.append(pathfilename)
# make a list of all filenames and if they're paired or not;
# if we don't know if they're paired, default to allowing but not
# forcing pairing.
files = []
for element in filenames:
files.append([element, args.paired])
if args.unpaired_reads:
files.append([args.unpaired_reads, False])
# create object of Nodetable in Khmer to use its
kh = khmer.Nodetable(args.ksize, 1, 1)
# load database
mphf_filename = args.database + '.mphf'
array_filename = args.database + '.arr'
print('loading database {}'.format(args.database))
with open(array_filename, 'rb') as fp:
mphf_to_kmer, mphf_to_cdbg, family_ids, cdbg_to_family_id = pickle.load(
fp)
mphf = bbhash.load_mphf(mphf_filename)
print('done!')
def get_kmer_to_family_ids(hashval):
mphf_hash = mphf.lookup(hashval)
if mphf_hash is None:
return set()
kmer_hash = mphf_to_kmer[mphf_hash]
if kmer_hash != hashval:
return set()
cdbg_id = mphf_to_cdbg[mphf_hash]
id_list = cdbg_to_family_id[cdbg_id]
return id_list
def readFusion(read):
global n_unmatched, n_same, n_amb_same, n_clear_fusion, n_ambig_fusion, n_mutli_fusion
flag = None
lf_ids = set()
rt_ids = set()
families = []
shared_kmers = []
gaps = []
hashvals = kh.get_kmer_hashes(read.sequence)
# find a matching k-mer at the beginning of the read
lf = hashvals[0]
lf_ids = get_kmer_to_family_ids(lf)
idx = 1
while idx < len(hashvals) and len(lf_ids) == 0:
lf = hashvals[idx]
lf_ids = get_kmer_to_family_ids(lf)
idx += 1
if len(lf_ids) == 0:
#print('no single match')
n_unmatched += 1
flag = "unmatched"
elif idx == len(hashvals):
#print('same, only last kmer matched')
families.append(lf_ids)
if len(lf_ids) == 1:
n_same += 1
flag = "unique"
else:
n_amb_same += 1
flag = "ambiguous"
else: # len(lf_ids) > 0 & idx < len(hashvals)
# find a matching k-mer at the end of the read
rt = hashvals[-1]
rt_ids = get_kmer_to_family_ids(rt)
idy = len(hashvals) - 2
while idy >= idx and len(rt_ids) == 0:
rt = hashvals[idy]
rt_ids = get_kmer_to_family_ids(rt)
idy -= 1
if len(rt_ids) == 0:
#print('same, only one non-last kmer matched ')
families.append(lf_ids)
if len(lf_ids) == 1:
n_same += 1
flag = "unique"
else:
n_amb_same += 1
flag = "ambiguous"
else:
intersect_ids = lf_ids.intersection(rt_ids)
if len(intersect_ids) > 0:
families.append(intersect_ids)
if len(intersect_ids) == 1:
n_same += 1
flag = "unique"
else:
n_amb_same += 1
flag = "ambiguous"
else: # fusion to be resolved
shared_kmer = 1
gap_size = 0
gap = False
while idx <= idy + 1:
temp = hashvals[idx]
temp_ids = get_kmer_to_family_ids(temp)
if len(temp_ids) > 0:
intersect_ids = lf_ids.intersection(temp_ids)
if len(intersect_ids) > 0:
lf_ids = intersect_ids
shared_kmer += 1
gap_size = 0
else: # len(intersect_ids) == 0
families.append(lf_ids)
shared_kmers.append(shared_kmer)
lf_ids = temp_ids
shared_kmer = 1
gaps.append(gap_size)
gap_size = 0
else:
gap_size += 1
idx += 1
families.append(lf_ids)
shared_kmers.append(shared_kmer)
assert len(families) > 1
if len(families) == 2:
if len(families[0]) == 1 and len(families[1]) == 1:
n_clear_fusion += 1
flag = "clear_fusion"
else:
n_ambig_fusion += 1
flag = "ambig_fusion"
else: # len(families) > 2
n_mutli_fusion += 1
flag = "multi_fusion"
#if len(families) == 0:
# families = "-"
#if len(shared_kmers) == 0:
# shared_kmers = "-"
return flag, families, shared_kmers, gaps
fusion_filename = args.database + '_fusion.fa'
fusion_fp = open(fusion_filename, 'w')
fusionInfo_filename = args.database + '_fusion.info'
fusionInfo_fp = open(fusionInfo_filename, 'w')
print("fileName",
"recordIndex",
"whichInPair",
"align_class",
"gene_families",
"shared_kmers",
"gaps",
file=fusionInfo_fp,
sep='\t')
fusionCalc_filename = args.database + '_fusion.calc'
fusionCalc_fp = open(fusionCalc_filename, 'w')
print("fileName",
"recordIndex",
"whichInPair",
"align_class",
"familiy_A",
"familiy_B",
"no_families",
"len_families",
"shared_kmers",
"gaps",
"sorted_keys",
file=fusionCalc_fp,
sep='\t')
fusionPairs_filename = args.database + '_fusionPairs.fa'
fusPair_fp = open(fusionPairs_filename, 'w')
fusionPairsInfo_filename = args.database + '_fusionPairs.info'
fusPairInfo_fp = open(fusionPairsInfo_filename, 'w')
print("fileName",
"recordIndex",
"fusion_class",
"R1_family",
"R2_family",
file=fusPairInfo_fp,
sep='\t')
fusionPairsCalc_filename = args.database + '_fusionPairs.calc'
fusPairCalc_fp = open(fusionPairsCalc_filename, 'w')
print("fileName",
"recordIndex",
"fusion_class",
"familiy_A",
"familiy_B",
"len_families",
"sorted_keys",
file=fusPairCalc_fp,
sep='\t')
corrupt_files = []
family_names = dict(zip(family_ids.values(), family_ids.keys()))
n = 0
n_paired_fusion = 0
sameRef = ("unique", "ambiguous")
fusion = ("clear_fusion", "ambig_fusion", "multi_fusion")
for filename, require_paired in files:
with catch_io_errors(filename, fusion_fp, fusionInfo_fp, fusionCalc_fp,
fusPair_fp, fusPairInfo_fp, fusPairCalc_fp,
args.force, corrupt_files):
screed_iter = clean_input_reads(screed.open(filename))
reader = broken_paired_reader(screed_iter,
min_length=args.ksize,
force_single=force_single,
require_paired=require_paired)
for r_index, is_paired, read0, read1 in reader:
n += 1
if n % 10000 == 0:
print('...', n)
#if n > 5000:
# break
flag0, families0, shared_kmers0, gaps0 = readFusion(read0)
if not is_paired and flag0 in fusion:
#families_names0 = []
#for gp in families0:
# gp_names = []
# for family_id in gp:
# family_name = family_names[family_id]
# gp_names.append(family_name)
# families_names0.append(gp_names)
print(filename,
r_index,
"single",
flag0,
families0,
shared_kmers0,
gaps0,
file=fusionInfo_fp,
sep='\t')
write_record(read0, fusion_fp)
#i = 1
#while i < len(families0):
# for g1 in families0[i-1]:
# for g2 in families0[i]:
# print(filename, r_index, "single", flag0, sorted([g1,g2]), len(families0), len(families0[i-1]), len(families0[i]),
# shared_kmers0, gaps0, file=fusionCalc_fp, sep='\t')
# i += 1
i = len(families0) - 1
for g1 in families0[0]:
g1_name = family_names[g1]
for g2 in families0[i]:
g2_name = family_names[g2]
print(filename,
r_index,
"single",
flag0,
'{}:{}'.format(g1, g1_name),
'{}:{}'.format(g2, g2_name),
len(families0), [len(f) for f in families0],
shared_kmers0,
gaps0,
sorted([g1, g2]),
file=fusionCalc_fp,
sep='\t')
if is_paired:
flag1, families1, shared_kmers1, gaps1 = readFusion(read1)
if flag0 in fusion or flag1 in fusion:
print(filename,
r_index,
"Read_1",
flag0,
families0,
shared_kmers0,
gaps0,
file=fusionInfo_fp,
sep='\t')
write_record(read0, fusion_fp)
print(filename,
r_index,
"Read_2",
flag1,
families1,
shared_kmers1,
gaps1,
file=fusionInfo_fp,
sep='\t')
write_record(read1, fusion_fp)
if flag0 in fusion:
i = len(families0) - 1
for g1 in families0[0]:
g1_name = family_names[g1]
for g2 in families0[i]:
g2_name = family_names[g2]
print(filename,
r_index,
"Read_1",
flag0,
'{}:{}'.format(g1, g1_name),
'{}:{}'.format(g2, g2_name),
len(families0),
[len(f) for f in families0],
shared_kmers0,
gaps0,
sorted([g1, g2]),
file=fusionCalc_fp,
sep='\t')
if flag1 in fusion:
i = len(families1) - 1
for g1 in families1[0]:
g1_name = family_names[g1]
for g2 in families1[i]:
g2_name = family_names[g2]
print(filename,
r_index,
"Read_2",
flag1,
'{}:{}'.format(g1, g1_name),
'{}:{}'.format(g2, g2_name),
len(families1),
[len(f) for f in families1],
shared_kmers1,
gaps1,
sorted([g1, g2]),
file=fusionCalc_fp,
sep='\t')
elif flag0 in sameRef and flag1 in sameRef:
if len(families0[0].intersection(families1[0])) == 0:
n_paired_fusion += 1
if flag0 == "unique" and flag1 == "unique":
fusion_class = "clear_fusion"
else:
fusion_class = "ambig_fusion"
print(filename,
r_index,
fusion_class,
families0,
families1,
file=fusPairInfo_fp,
sep='\t')
write_record(read0, fusPair_fp)
write_record(read1, fusPair_fp)
for g1 in families0[0]:
g1_name = family_names[g1]
for g2 in families1[0]:
g2_name = family_names[g2]
print(filename,
r_index,
fusion_class,
'{}:{}'.format(g1, g1_name),
'{}:{}'.format(g2, g2_name), [
len(f) for f in (families0[0],
families1[0])
],
sorted([g1, g2]),
file=fusPairCalc_fp,
sep='\t')
print('No of input fragments: ', n)
print('unmatched:', n_unmatched)
print('Unique:', n_same)
print('Ambiguous:', n_amb_same)
print('Single read clear fusion:', n_clear_fusion)
print('Single read ambiguous fusion:', n_ambig_fusion)
print('Single read multi fusion:', n_mutli_fusion)
print('paired read fusion:', n_paired_fusion)
def main(): # pylint: disable=too-many-branches,too-many-statements
parser = sanitize_help(get_parser())
args = parser.parse_args()
configure_logging(args.quiet)
report_on_config(args)
report_fp = args.report
force_single = args.force_single
# check for similar filenames
# if we're using a single output file only check for identical filenames
# otherwise, check for identical BASE names as well.
filenames = []
basenames = []
for pathfilename in args.input_filenames:
filenames.append(pathfilename)
if args.single_output_file:
continue # nothing more to worry about
basename = os.path.basename(pathfilename)
if basename in basenames:
log_error('ERROR: Duplicate filename--Cannot handle this!')
log_error('** Exiting!')
sys.exit(1)
basenames.append(basename)
# check that files exist and there is sufficient output disk space.
check_valid_file_exists(args.input_filenames)
check_space(args.input_filenames, args.force)
if args.savegraph is not None:
graphsize = calculate_graphsize(args, 'countgraph')
check_space_for_graph(args.savegraph, graphsize, args.force)
# load or create counting table.
if args.loadgraph:
log_info('loading k-mer countgraph from {graph}', graph=args.loadgraph)
countgraph = khmer.load_countgraph(args.loadgraph)
else:
log_info('making countgraph')
countgraph = khmer_args.create_countgraph(args)
# create an object to handle diginorm of all files
norm = Normalizer(args.cutoff, countgraph)
with_diagnostics = WithDiagnostics(norm, report_fp, args.report_frequency)
# make a list of all filenames and if they're paired or not;
# if we don't know if they're paired, default to allowing but not
# forcing pairing.
files = []
for element in filenames:
files.append([element, args.paired])
if args.unpaired_reads:
files.append([args.unpaired_reads, False])
corrupt_files = []
outfp = None
output_name = None
if args.single_output_file:
outfp = get_file_writer(args.single_output_file, args.gzip, args.bzip)
else:
if '-' in filenames or '/dev/stdin' in filenames:
print(
"Accepting input from stdin; output filename must "
"be provided with '-o'.",
file=sys.stderr)
sys.exit(1)
#
# main loop: iterate over all files given, do diginorm.
#
for filename, require_paired in files:
if not args.single_output_file:
output_name = os.path.basename(filename) + '.keep'
outfp = open(output_name, 'wb')
outfp = get_file_writer(outfp, args.gzip, args.bzip)
# failsafe context manager in case an input file breaks
with catch_io_errors(filename, outfp, args.single_output_file,
args.force, corrupt_files):
screed_iter = clean_input_reads(screed.open(filename))
reader = broken_paired_reader(screed_iter,
min_length=args.ksize,
force_single=force_single,
require_paired=require_paired)
# actually do diginorm
for record in with_diagnostics(reader, filename):
if record is not None:
write_record(record, outfp)
log_info('output in {name}', name=describe_file_handle(outfp))
if not args.single_output_file:
outfp.close()
# finished - print out some diagnostics.
log_info('Total number of unique k-mers: {umers}',
umers=countgraph.n_unique_kmers())
if args.savegraph is not None:
log_info('...saving to {name}', name=args.savegraph)
countgraph.save(args.savegraph)
fp_rate = \
khmer.calc_expected_collisions(countgraph, False, max_false_pos=.8)
# for max_false_pos see Zhang et al., http://arxiv.org/abs/1309.2975
log_info('fp rate estimated to be {fpr:1.3f}', fpr=fp_rate)
if args.force and len(corrupt_files) > 0:
log_error("** WARNING: Finished with errors!")
log_error("** I/O Errors occurred in the following files:")
log_error("\t" + " ".join(corrupt_files))
def main(): # pylint: disable=too-many-branches,too-many-statements
info('normalize-by-median.py', ['diginorm'])
args = get_parser().parse_args()
report_on_config(args)
report_fp = args.report
force_single = args.force_single
# check for similar filenames
# if we're using a single output file only check for identical filenames
# otherwise, check for identical BASE names as well.
filenames = []
basenames = []
for pathfilename in args.input_filenames:
filenames.append(pathfilename)
if args.single_output_file:
continue # nothing more to worry about
basename = os.path.basename(pathfilename)
if basename in basenames:
print('ERROR: Duplicate filename--Cannot handle this!',
file=sys.stderr)
print('** Exiting!', file=sys.stderr)
sys.exit(1)
basenames.append(basename)
# check that files exist and there is sufficient output disk space.
check_valid_file_exists(args.input_filenames)
check_space(args.input_filenames, args.force)
if args.savetable:
check_space_for_hashtable(args, 'countgraph', args.force)
# load or create counting table.
if args.loadtable:
print('loading k-mer counting table from ' + args.loadtable,
file=sys.stderr)
htable = khmer.load_counting_hash(args.loadtable)
else:
print('making countgraph', file=sys.stderr)
htable = khmer_args.create_countgraph(args)
input_filename = None
# create an object to handle diginorm of all files
norm = Normalizer(args.cutoff, htable)
# make a list of all filenames and if they're paired or not;
# if we don't know if they're paired, default to allowing but not
# forcing pairing.
files = []
for e in filenames:
files.append([e, args.paired])
if args.unpaired_reads:
files.append([args.unpaired_reads, False])
corrupt_files = []
outfp = None
output_name = None
if args.single_output_file:
if args.single_output_file is sys.stdout:
output_name = '/dev/stdout'
else:
output_name = args.single_output_file.name
outfp = args.single_output_file
#
# main loop: iterate over all files given, do diginorm.
#
for filename, require_paired in files:
if not args.single_output_file:
output_name = os.path.basename(filename) + '.keep'
outfp = open(output_name, 'w')
# failsafe context manager in case an input file breaks
with CatchIOErrors(filename, outfp, args.single_output_file,
args.force, corrupt_files):
screed_iter = screed.open(filename, parse_description=False)
reader = broken_paired_reader(screed_iter, min_length=args.ksize,
force_single=force_single,
require_paired=require_paired)
# actually do diginorm
for record in WithDiagnostics(filename, norm, reader, report_fp):
if record is not None:
write_record(record, outfp)
print('output in ' + output_name, file=sys.stderr)
if output_name is not '/dev/stdout':
outfp.close()
# finished - print out some diagnostics.
print('Total number of unique k-mers: {0}'
.format(htable.n_unique_kmers()),
file=sys.stderr)
if args.savetable:
print('...saving to ' + args.savetable, file=sys.stderr)
htable.save(args.savetable)
fp_rate = \
khmer.calc_expected_collisions(htable, args.force, max_false_pos=.8)
# for max_false_pos see Zhang et al., http://arxiv.org/abs/1309.2975
print('fp rate estimated to be {fpr:1.3f}'.format(fpr=fp_rate),
file=sys.stderr)
if args.force and len(corrupt_files) > 0:
print("** WARNING: Finished with errors!", file=sys.stderr)
print("** I/O Errors occurred in the following files:",
file=sys.stderr)
print("\t", " ".join(corrupt_files), file=sys.stderr)
def main(): # pylint: disable=too-many-branches,too-many-statements
parser = sanitize_help(get_parser())
args = parser.parse_args()
configure_logging(args.quiet)
report_on_config(args)
report_fp = args.report
force_single = args.force_single
# check for similar filenames
# if we're using a single output file only check for identical filenames
# otherwise, check for identical BASE names as well.
filenames = []
basenames = []
for pathfilename in args.input_filenames:
filenames.append(pathfilename)
if args.single_output_file:
continue # nothing more to worry about
basename = os.path.basename(pathfilename)
if basename in basenames:
log_error('ERROR: Duplicate filename--Cannot handle this!')
log_error('** Exiting!')
sys.exit(1)
basenames.append(basename)
# check that files exist and there is sufficient output disk space.
check_valid_file_exists(args.input_filenames)
check_space(args.input_filenames, args.force)
if args.savegraph is not None:
graphsize = calculate_graphsize(args, 'countgraph')
check_space_for_graph(args.savegraph, graphsize, args.force)
# load or create counting table.
if args.loadgraph:
log_info('loading k-mer countgraph from {graph}',
graph=args.loadgraph)
countgraph = Countgraph.load(args.loadgraph)
else:
log_info('making countgraph')
countgraph = khmer_args.create_countgraph(args)
# create an object to handle diginorm of all files
norm = Normalizer(args.cutoff, countgraph)
with_diagnostics = WithDiagnostics(norm, report_fp, args.report_frequency)
# make a list of all filenames and if they're paired or not;
# if we don't know if they're paired, default to allowing but not
# forcing pairing.
files = []
for element in filenames:
files.append([element, args.paired])
if args.unpaired_reads:
files.append([args.unpaired_reads, False])
corrupt_files = []
outfp = None
output_name = None
if args.single_output_file:
outfp = get_file_writer(args.single_output_file, args.gzip, args.bzip)
else:
if '-' in filenames or '/dev/stdin' in filenames:
print("Accepting input from stdin; output filename must "
"be provided with '-o'.", file=sys.stderr)
sys.exit(1)
#
# main loop: iterate over all files given, do diginorm.
#
for filename, require_paired in files:
if not args.single_output_file:
output_name = os.path.basename(filename) + '.keep'
outfp = open(output_name, 'wb')
outfp = get_file_writer(outfp, args.gzip, args.bzip)
# failsafe context manager in case an input file breaks
with catch_io_errors(filename, outfp, args.single_output_file,
args.force, corrupt_files):
screed_iter = clean_input_reads(screed.open(filename))
reader = broken_paired_reader(screed_iter, min_length=args.ksize,
force_single=force_single,
require_paired=require_paired)
# actually do diginorm
for record in with_diagnostics(reader, filename):
if record is not None:
write_record(record, outfp)
log_info('output in {name}', name=describe_file_handle(outfp))
if not args.single_output_file:
outfp.close()
# finished - print out some diagnostics.
log_info('Total number of unique k-mers: {umers}',
umers=countgraph.n_unique_kmers())
if args.savegraph is not None:
log_info('...saving to {name}', name=args.savegraph)
countgraph.save(args.savegraph)
fp_rate = \
khmer.calc_expected_collisions(countgraph, False, max_false_pos=.8)
# for max_false_pos see Zhang et al., http://arxiv.org/abs/1309.2975
log_info('fp rate estimated to be {fpr:1.3f}', fpr=fp_rate)
if args.force and len(corrupt_files) > 0:
log_error("** WARNING: Finished with errors!")
log_error("** I/O Errors occurred in the following files:")
log_error("\t" + " ".join(corrupt_files))
def main():
parser = sanitize_help(get_parser())
args = parser.parse_args()
if not args.quiet:
info('trim-low-abund.py', ['streaming'])
configure_logging(args.quiet)
###
if len(set(args.input_filenames)) != len(args.input_filenames):
log_error("Error: Cannot input the same filename multiple times.")
sys.exit(1)
if args.trim_at_coverage != DEFAULT_TRIM_AT_COVERAGE and \
not args.variable_coverage:
log_error("Error: --trim-at-coverage/-Z given, but "
"--variable-coverage/-V not specified.")
sys.exit(1)
if args.diginorm_coverage != DEFAULT_DIGINORM_COVERAGE and \
not args.diginorm:
log_error("Error: --diginorm-coverage given, but "
"--diginorm not specified.")
sys.exit(1)
if args.diginorm and args.single_pass:
log_error("Error: --diginorm and --single-pass are incompatible!\n"
"You probably want to use normalize-by-median.py instead.")
sys.exit(1)
###
report_on_config(args)
check_valid_file_exists(args.input_filenames)
check_space(args.input_filenames, args.force)
if args.savegraph:
graphsize = calculate_graphsize(args, 'countgraph')
check_space_for_graph(args.savegraph, graphsize, args.force)
if ('-' in args.input_filenames or '/dev/stdin' in args.input_filenames) \
and not args.output:
log_error("Accepting input from stdin; output filename must "
"be provided with -o.")
sys.exit(1)
if args.loadgraph:
log_info('loading countgraph from {graph}', graph=args.loadgraph)
ct = khmer.load_countgraph(args.loadgraph)
else:
log_info('making countgraph')
ct = khmer_args.create_countgraph(args)
K = ct.ksize()
tempdir = tempfile.mkdtemp('khmer', 'tmp', args.tempdir)
log_info('created temporary directory {temp};\n'
'use -T to change location', temp=tempdir)
trimmer = Trimmer(ct, not args.variable_coverage, args.cutoff,
args.trim_at_coverage)
if args.diginorm:
trimmer.set_diginorm(args.diginorm_coverage)
# ### FIRST PASS ###
save_pass2_total = 0
written_bp = 0
written_reads = 0
# only create the file writer once if outfp is specified; otherwise,
# create it for each file.
if args.output:
trimfp = get_file_writer(args.output, args.gzip, args.bzip)
pass2list = []
for filename in args.input_filenames:
# figure out temporary filename for 2nd pass
pass2filename = os.path.basename(filename) + '.pass2'
pass2filename = os.path.join(tempdir, pass2filename)
pass2fp = open(pass2filename, 'w')
# construct output filenames
if args.output is None:
# note: this will be saved in trimfp.
outfp = open(os.path.basename(filename) + '.abundtrim', 'wb')
# get file handle w/gzip, bzip
trimfp = get_file_writer(outfp, args.gzip, args.bzip)
# record all this info
pass2list.append((filename, pass2filename, trimfp))
# input file stuff: get a broken_paired reader.
screed_iter = screed.open(filename)
paired_iter = broken_paired_reader(screed_iter, min_length=K,
force_single=args.ignore_pairs)
# main loop through the file.
n_start = trimmer.n_reads
save_start = trimmer.n_saved
watermark = REPORT_EVERY_N_READS
for read in trimmer.pass1(paired_iter, pass2fp):
if (trimmer.n_reads - n_start) > watermark:
log_info("... {filename} {n_saved} {n_reads} {n_bp} "
"{w_reads} {w_bp}", filename=filename,
n_saved=trimmer.n_saved, n_reads=trimmer.n_reads,
n_bp=trimmer.n_bp, w_reads=written_reads,
w_bp=written_bp)
watermark += REPORT_EVERY_N_READS
# write out the trimmed/etc sequences that AREN'T going to be
# revisited in a 2nd pass.
write_record(read, trimfp)
written_bp += len(read)
written_reads += 1
pass2fp.close()
log_info("{filename}: kept aside {kept} of {total} from first pass",
filename=filename, kept=trimmer.n_saved - save_start,
total=trimmer.n_reads - n_start)
# first pass goes across all the data, so record relevant stats...
n_reads = trimmer.n_reads
n_bp = trimmer.n_bp
n_skipped = trimmer.n_skipped
bp_skipped = trimmer.bp_skipped
save_pass2_total = trimmer.n_saved
# ### SECOND PASS. ###
# nothing should have been skipped yet!
assert trimmer.n_skipped == 0
assert trimmer.bp_skipped == 0
if args.single_pass:
pass2list = []
# go back through all the files again.
for _, pass2filename, trimfp in pass2list:
log_info('second pass: looking at sequences kept aside in {pass2}',
pass2=pass2filename)
# note that for this second pass, we don't care about paired
# reads - they will be output in the same order they're read in,
# so pairs will stay together if not orphaned. This is in contrast
# to the first loop. Hence, force_single=True below.
screed_iter = screed.open(pass2filename, parse_description=False)
paired_iter = broken_paired_reader(screed_iter, min_length=K,
force_single=True)
watermark = REPORT_EVERY_N_READS
for read in trimmer.pass2(paired_iter):
if (trimmer.n_reads - n_start) > watermark:
log_info('... x 2 {a} {b} {c} {d} {e} {f} {g}',
a=trimmer.n_reads - n_start,
b=pass2filename, c=trimmer.n_saved,
d=trimmer.n_reads, e=trimmer.n_bp,
f=written_reads, g=written_bp)
watermark += REPORT_EVERY_N_READS
write_record(read, trimfp)
written_reads += 1
written_bp += len(read)
log_info('removing {pass2}', pass2=pass2filename)
os.unlink(pass2filename)
# if we created our own trimfps, close 'em.
if not args.output:
trimfp.close()
log_info('removing temp directory & contents ({temp})', temp=tempdir)
shutil.rmtree(tempdir)
trimmed_reads = trimmer.trimmed_reads
n_passes = 1.0 + (float(save_pass2_total) / n_reads)
percent_reads_trimmed = float(trimmed_reads + (n_reads - written_reads)) /\
n_reads * 100.0
log_info('read {read} reads, {bp} bp', read=n_reads, bp=n_bp)
log_info('wrote {wr} reads, {wbp} bp', wr=written_reads, wbp=written_bp)
log_info('looked at {st} reads twice ({np:.2f} passes)',
st=save_pass2_total, np=n_passes)
log_info('removed {r} reads and trimmed {t} reads ({p:.2f}%)',
r=n_reads - written_reads, t=trimmed_reads,
p=percent_reads_trimmed)
log_info('trimmed or removed {p:.2f}%% of bases ({bp} total)',
p=(1 - (written_bp / float(n_bp))) * 100.0, bp=n_bp - written_bp)
if args.variable_coverage:
percent_reads_hicov = 100.0 * float(n_reads - n_skipped) / n_reads
log_info('{n} reads were high coverage ({p:.2f}%);',
n=n_reads - n_skipped, p=percent_reads_hicov)
log_info('skipped {r} reads/{bp} bases because of low coverage',
r=n_skipped, bp=bp_skipped)
fp_rate = \
khmer.calc_expected_collisions(ct, args.force, max_false_pos=.8)
# for max_false_pos see Zhang et al., http://arxiv.org/abs/1309.2975
log_info('fp rate estimated to be {fpr:1.3f}', fpr=fp_rate)
log_info('output in *.abundtrim')
if args.savegraph:
log_info("Saving k-mer countgraph to {graph}", graph=args.savegraph)
ct.save(args.savegraph)
def main():
info('correct-reads.py', ['streaming'])
args = sanitize_help(get_parser()).parse_args()
###
if len(set(args.input_filenames)) != len(args.input_filenames):
print("Error: Cannot input the same filename multiple times.",
file=sys.stderr)
sys.exit(1)
###
report_on_config(args)
check_valid_file_exists(args.input_filenames)
check_space(args.input_filenames, args.force)
tablesize = calculate_graphsize(args, 'countgraph')
if args.savegraph:
check_space_for_graph(args.savegraph, tablesize, args.force)
K = args.ksize
CUTOFF = args.cutoff
NORMALIZE_LIMIT = args.normalize_to
if args.loadgraph:
print('loading k-mer countgraph from', args.loadgraph, file=sys.stderr)
ct = Countgraph.load(args.loadgraph)
else:
print('making k-mer countgraph', file=sys.stderr)
ct = create_countgraph(args, multiplier=8 / (9. + 0.3))
tempdir = tempfile.mkdtemp('khmer', 'tmp', args.tempdir)
print('created temporary directory %s; use -T to change location' %
tempdir,
file=sys.stderr)
aligner = khmer.ReadAligner(ct, args.cutoff, args.bits_theta)
# ### FIRST PASS ###
save_pass2_total = 0
n_bp = 0
n_reads = 0
written_bp = 0
written_reads = 0
corrected_reads = 0
pass2list = []
for filename in args.input_filenames:
pass2filename = os.path.basename(filename) + '.pass2'
pass2filename = os.path.join(tempdir, pass2filename)
if args.out is None:
corrfp = open(os.path.basename(filename) + '.corr', 'w')
else:
corrfp = args.out
pass2list.append((filename, pass2filename, corrfp))
screed_iter = screed.open(filename, parse_description=False)
pass2fp = open(pass2filename, 'w')
save_pass2 = 0
n = 0
paired_iter = broken_paired_reader(screed_iter,
min_length=K,
force_single=args.ignore_pairs)
for n, is_pair, read1, read2 in paired_iter:
if n % 10000 == 0:
print('...',
n,
filename,
save_pass2,
n_reads,
n_bp,
written_reads,
written_bp,
file=sys.stderr)
# we want to track paired reads here, to make sure that pairs
# are not split between first pass and second pass.
if is_pair:
n_reads += 2
n_bp += len(read1.sequence) + len(read2.sequence)
seq1 = read1.sequence.replace('N', 'A')
seq2 = read2.sequence.replace('N', 'A')
med1, _, _ = ct.get_median_count(seq1)
med2, _, _ = ct.get_median_count(seq2)
if med1 < NORMALIZE_LIMIT or med2 < NORMALIZE_LIMIT:
ct.consume(seq1)
ct.consume(seq2)
write_record_pair(read1, read2, pass2fp)
save_pass2 += 2
else:
is_aligned, new_seq1 = correct_sequence(aligner, seq1)
if is_aligned:
if new_seq1 != read1.sequence:
corrected_reads += 1
read1.sequence = new_seq1
if hasattr(read1, 'quality'):
fix_quality(read1)
is_aligned, new_seq2 = correct_sequence(aligner, seq2)
if is_aligned:
if new_seq2 != read2.sequence:
corrected_reads += 1
read2.sequence = new_seq2
if hasattr(read2, 'quality'):
fix_quality(read2)
write_record_pair(read1, read2, corrfp)
written_reads += 2
written_bp += len(read1)
written_bp += len(read2)
else:
n_reads += 1
n_bp += len(read1.sequence)
seq = read1.sequence.replace('N', 'A')
med, _, _ = ct.get_median_count(seq)
# has this portion of the graph saturated? if not,
# consume & save => pass2.
if med < NORMALIZE_LIMIT:
ct.consume(seq)
write_record(read1, pass2fp)
save_pass2 += 1
else: # trim!!
is_aligned, new_seq = correct_sequence(aligner, seq)
if is_aligned:
if new_seq != read1.sequence:
corrected_reads += 1
read1.sequence = new_seq
if hasattr(read1, 'quality'):
fix_quality(read1)
write_record(read1, corrfp)
written_reads += 1
written_bp += len(new_seq)
pass2fp.close()
print('%s: kept aside %d of %d from first pass, in %s' %
(filename, save_pass2, n, filename),
file=sys.stderr)
save_pass2_total += save_pass2
# ### SECOND PASS. ###
skipped_n = 0
skipped_bp = 0
for _, pass2filename, corrfp in pass2list:
print(('second pass: looking at sequences kept aside in %s') %
pass2filename,
file=sys.stderr)
# note that for this second pass, we don't care about paired
# reads - they will be output in the same order they're read in,
# so pairs will stay together if not orphaned. This is in contrast
# to the first loop.
for n, read in enumerate(
screed.open(pass2filename, parse_description=False)):
if n % 10000 == 0:
print('... x 2',
n,
pass2filename,
written_reads,
written_bp,
file=sys.stderr)
seq = read.sequence.replace('N', 'A')
med, _, _ = ct.get_median_count(seq)
# do we retain low-abundance components unchanged?
if med < NORMALIZE_LIMIT and args.variable_coverage:
write_record(read, corrfp)
written_reads += 1
written_bp += len(read.sequence)
skipped_n += 1
skipped_bp += len(read.sequence)
# otherwise, examine/correct.
else: # med >= NORMALIZE LIMIT or not args.variable_coverage
is_aligned, new_seq = correct_sequence(aligner, seq)
if is_aligned:
if new_seq != read.sequence:
corrected_reads += 1
read.sequence = new_seq
if hasattr(read, 'quality'):
fix_quality(read)
write_record(read, corrfp)
written_reads += 1
written_bp += len(new_seq)
print('removing %s' % pass2filename, file=sys.stderr)
os.unlink(pass2filename)
print('removing temp directory & contents (%s)' % tempdir, file=sys.stderr)
shutil.rmtree(tempdir)
n_passes = 1.0 + (float(save_pass2_total) / n_reads)
percent_reads_corrected = float(corrected_reads +
(n_reads - written_reads)) /\
n_reads * 100.0
print('read %d reads, %d bp' % (
n_reads,
n_bp,
), file=sys.stderr)
print('wrote %d reads, %d bp' % (
written_reads,
written_bp,
),
file=sys.stderr)
print('looked at %d reads twice (%.2f passes)' %
(save_pass2_total, n_passes),
file=sys.stderr)
print('removed %d reads and corrected %d reads (%.2f%%)' %
(n_reads - written_reads, corrected_reads, percent_reads_corrected),
file=sys.stderr)
print('removed %.2f%% of bases (%d total)' %
((1 - (written_bp / float(n_bp))) * 100.0, n_bp - written_bp),
file=sys.stderr)
if args.variable_coverage:
percent_reads_hicov = 100.0 * float(n_reads - skipped_n) / n_reads
print('%d reads were high coverage (%.2f%%);' %
(n_reads - skipped_n, percent_reads_hicov),
file=sys.stderr)
print(('skipped %d reads/%d bases because of low coverage') %
(skipped_n, skipped_bp),
file=sys.stderr)
fp_rate = \
khmer.calc_expected_collisions(ct, args.force, max_false_pos=.8)
# for max_false_pos see Zhang et al., http://arxiv.org/abs/1309.2975
print('fp rate estimated to be {fpr:1.3f}'.format(fpr=fp_rate),
file=sys.stderr)
print('output in *.corr', file=sys.stderr)
if args.savegraph:
print("Saving k-mer countgraph to", args.savegraph, file=sys.stderr)
ct.save(args.savegraph)
def main(): # pylint: disable=too-many-branches,too-many-statements
info('normalize-by-median.py', ['diginorm'])
args = get_parser().parse_args()
report_on_config(args)
report_fp = args.report
force_single = args.force_single
# check for similar filenames
# if we're using a single output file only check for identical filenames
# otherwise, check for identical BASE names as well.
filenames = []
basenames = []
for pathfilename in args.input_filenames:
filenames.append(pathfilename)
if args.single_output_file:
continue # nothing more to worry about
basename = os.path.basename(pathfilename)
if basename in basenames:
print('ERROR: Duplicate filename--Cannot handle this!',
file=sys.stderr)
print('** Exiting!', file=sys.stderr)
sys.exit(1)
basenames.append(basename)
# check that files exist and there is sufficient output disk space.
check_valid_file_exists(args.input_filenames)
check_space(args.input_filenames, args.force)
if args.savetable:
check_space_for_hashtable(args.n_tables * args.min_tablesize,
args.force)
# load or create counting table.
if args.loadtable:
print('loading k-mer counting table from ' + args.loadtable,
file=sys.stderr)
htable = khmer.load_counting_hash(args.loadtable)
else:
print('making k-mer counting table', file=sys.stderr)
htable = khmer.new_counting_hash(args.ksize, args.min_tablesize,
args.n_tables)
input_filename = None
# create an object to handle diginorm of all files
norm = Normalizer(args.cutoff, htable)
# make a list of all filenames and if they're paired or not;
# if we don't know if they're paired, default to allowing but not
# forcing pairing.
files = []
for e in filenames:
files.append([e, args.paired])
if args.unpaired_reads:
files.append([args.unpaired_reads, False])
corrupt_files = []
outfp = None
output_name = None
if args.single_output_file:
if args.single_output_file is sys.stdout:
output_name = '/dev/stdout'
else:
output_name = args.single_output_file.name
outfp = args.single_output_file
#
# main loop: iterate over all files given, do diginorm.
#
for filename, require_paired in files:
if not args.single_output_file:
output_name = os.path.basename(filename) + '.keep'
outfp = open(output_name, 'w')
# failsafe context manager in case an input file breaks
with CatchIOErrors(filename, outfp, args.single_output_file,
args.force, corrupt_files):
screed_iter = screed.open(filename, parse_description=False)
reader = broken_paired_reader(screed_iter,
min_length=args.ksize,
force_single=force_single,
require_paired=require_paired)
# actually do diginorm
for record in WithDiagnostics(filename, norm, reader, report_fp):
if record is not None:
write_record(record, outfp)
print('output in ' + output_name, file=sys.stderr)
if output_name is not '/dev/stdout':
outfp.close()
# finished - print out some diagnostics.
print('Total number of unique k-mers: {0}'.format(htable.n_unique_kmers()),
file=sys.stderr)
if args.savetable:
print('...saving to ' + args.savetable, file=sys.stderr)
htable.save(args.savetable)
fp_rate = \
khmer.calc_expected_collisions(htable, args.force, max_false_pos=.8)
# for max_false_pos see Zhang et al., http://arxiv.org/abs/1309.2975
print('fp rate estimated to be {fpr:1.3f}'.format(fpr=fp_rate),
file=sys.stderr)
if args.force and len(corrupt_files) > 0:
print("** WARNING: Finished with errors!", file=sys.stderr)
print("** IOErrors occurred in the following files:", file=sys.stderr)
print("\t", " ".join(corrupt_files), file=sys.stderr)
def main(): # pylint: disable=too-many-branches,too-many-statements
info('normalize-by-median.py', ['diginorm'])
args = get_parser().parse_args()
report_on_config(args)
report_fp = args.report
check_valid_file_exists(args.input_filenames)
check_space(args.input_filenames, args.force)
if args.savetable:
check_space_for_hashtable(
args.n_tables * args.min_tablesize, args.force)
# list to save error files along with throwing exceptions
if args.force:
corrupt_files = []
if args.loadtable:
print 'loading k-mer counting table from', args.loadtable
htable = khmer.load_counting_hash(args.loadtable)
else:
print 'making k-mer counting table'
htable = khmer.new_counting_hash(args.ksize, args.min_tablesize,
args.n_tables)
total = 0
discarded = 0
input_filename = None
if args.single_output_filename:
output_name = args.single_output_filename
if args.append:
outfp = open(args.single_output_filename, 'a')
else:
outfp = open(args.single_output_filename, 'w')
for index, input_filename in enumerate(args.input_filenames):
if not args.single_output_filename:
output_name = os.path.basename(input_filename) + '.keep'
outfp = open(output_name, 'w')
total_acc = 0
discarded_acc = 0
try:
total_acc, discarded_acc = normalize_by_median(input_filename,
outfp, htable, args,
report_fp)
except IOError as err:
handle_error(err, output_name, input_filename, args.fail_save,
htable)
if not args.force:
print >> sys.stderr, '** Exiting!'
sys.exit(1)
else:
print >> sys.stderr, '*** Skipping error file, moving on...'
corrupt_files.append(input_filename)
else:
if total_acc == 0 and discarded_acc == 0:
print 'SKIPPED empty file', input_filename
else:
total += total_acc
discarded += discarded_acc
print 'DONE with {inp}; kept {kept} of {total} or {perc:2}%'\
.format(inp=input_filename, kept=total - discarded,
total=total, perc=int(100. - discarded /
float(total) * 100.))
print 'output in', output_name
if (args.dump_frequency > 0 and
index > 0 and index % args.dump_frequency == 0):
print 'Backup: Saving k-mer counting file through', input_filename
if args.savetable:
hashname = args.savetable
print '...saving to', hashname
else:
hashname = 'backup.ct'
print 'Nothing given for savetable, saving to', hashname
htable.save(hashname)
if args.report_total_kmers:
print >> sys.stderr, 'Total number of unique k-mers: {0}'.format(
htable.n_unique_kmers())
if args.savetable:
print 'Saving k-mer counting table through', input_filename
print '...saving to', args.savetable
htable.save(args.savetable)
fp_rate = khmer.calc_expected_collisions(htable)
print 'fp rate estimated to be {fpr:1.3f}'.format(fpr=fp_rate)
if args.force and len(corrupt_files) > 0:
print >> sys.stderr, "** WARNING: Finished with errors!"
print >> sys.stderr, "** IOErrors occurred in the following files:"
print >> sys.stderr, "\t", " ".join(corrupt_files)
if fp_rate > MAX_FALSE_POSITIVE_RATE:
print >> sys.stderr, "**"
print >> sys.stderr, ("** ERROR: the k-mer counting table is too small"
" for this data set. Increase tablesize/# "
"tables.")
print >> sys.stderr, "**"
print >> sys.stderr, "** Do not use these results!!"
if not args.force:
sys.exit(1)
def main(): # pylint: disable=too-many-branches,too-many-statements
info('normalize-by-median.py', ['diginorm'])
args = get_parser().parse_args()
report_on_config(args)
report_fp = args.report
# check for similar filenames
filenames = []
for pathfilename in args.input_filenames:
filename = pathfilename.split('/')[-1]
if (filename in filenames):
print >> sys.stderr, "WARNING: At least two input files are named \
%s . (The script normalize-by-median.py can not handle this, only one .keep \
file for one of the input files will be generated.)" % filename
else:
filenames.append(filename)
# check for others
check_valid_file_exists(args.input_filenames)
check_space(args.input_filenames, args.force)
if args.savetable:
check_space_for_hashtable(args.n_tables * args.min_tablesize,
args.force)
# list to save error files along with throwing exceptions
corrupt_files = []
if args.loadtable:
print 'loading k-mer counting table from', args.loadtable
htable = khmer.load_counting_hash(args.loadtable)
else:
print >> sys.stderr, 'making k-mer counting table'
htable = khmer.new_counting_hash(args.ksize, args.min_tablesize,
args.n_tables)
input_filename = None
for index, input_filename in enumerate(args.input_filenames):
total_acc, discarded_acc, corrupt_files = \
normalize_by_median_and_check(
input_filename, htable, args.single_output_file,
args.fail_save, args.paired, args.cutoff, args.force,
corrupt_files, report_fp)
if (args.dump_frequency > 0 and index > 0
and index % args.dump_frequency == 0):
print 'Backup: Saving k-mer counting file through', input_filename
if args.savetable:
hashname = args.savetable
print '...saving to', hashname
else:
hashname = 'backup.ct'
print 'Nothing given for savetable, saving to', hashname
htable.save(hashname)
if args.paired and args.unpaired_reads:
args.paired = False
output_name = args.unpaired_reads
if not args.single_output_file:
output_name = os.path.basename(args.unpaired_reads) + '.keep'
outfp = open(output_name, 'w')
total_acc, discarded_acc, corrupt_files = \
normalize_by_median_and_check(
args.unpaired_reads, htable, args.single_output_file,
args.fail_save, args.paired, args.cutoff, args.force,
corrupt_files, report_fp)
if args.report_total_kmers:
print >> sys.stderr, 'Total number of unique k-mers: {0}'.format(
htable.n_unique_kmers())
if args.savetable:
print 'Saving k-mer counting table through', input_filename
print '...saving to', args.savetable
htable.save(args.savetable)
fp_rate = \
khmer.calc_expected_collisions(htable, args.force, max_false_pos=.8)
# for max_false_pos see Zhang et al., http://arxiv.org/abs/1309.2975
print >> sys.stderr, \
'fp rate estimated to be {fpr:1.3f}'.format(fpr=fp_rate)
if args.force and len(corrupt_files) > 0:
print >> sys.stderr, "** WARNING: Finished with errors!"
print >> sys.stderr, "** IOErrors occurred in the following files:"
print >> sys.stderr, "\t", " ".join(corrupt_files)
def main(): # pylint: disable=too-many-branches,too-many-statements
info('saturate-by-median.py', ['diginorm'])
parser = sanitize_help(get_parser())
args = parser.parse_args()
report_on_config(args)
report_fp = args.report
report_frequency = args.report_frequency
check_valid_file_exists(args.input_filenames)
check_space(args.input_filenames, False)
if args.savegraph:
check_space_for_graph(args, 'countgraph', False)
# list to save error files along with throwing exceptions
if args.force:
corrupt_files = []
if args.loadgraph:
print('loading k-mer countgraph from', args.loadgraph)
htable = khmer.load_countgraph(args.loadgraph)
else:
print('making countgraph')
htable = create_countgraph(args)
total = 0
discarded = 0
for index, input_filename in enumerate(args.input_filenames):
total_acc = 0
discarded_acc = 0
try:
total_acc, discarded_acc = normalize_by_median(input_filename,
htable, args,
report_fp,
report_frequency)
except IOError as err:
handle_error(err, input_filename)
if not args.force:
print("NOTE: This can be overridden using the --force"
" argument", file=sys.stderr)
print('** Exiting!', file=sys.stderr)
sys.exit(1)
else:
print('*** Skipping error file, moving on...', file=sys.stderr)
corrupt_files.append(input_filename)
else:
if total_acc == 0 and discarded_acc == 0:
print('SKIPPED empty file', input_filename)
else:
total += total_acc
discarded += discarded_acc
print('DONE with {inp}; kept {kept} of {total} or {perc:2}%'\
.format(inp=input_filename,
kept=total - discarded, total=total,
perc=int(100. - discarded / float(total) * 100.)))
if args.savegraph:
print('Saving k-mer countgraph through', input_filename)
print('...saving to', args.savegraph)
htable.save(args.savegraph)
# re: threshold, see Zhang et al.,
# http://arxiv.org/abs/1309.2975
fp_rate = khmer.calc_expected_collisions(htable, args.force, max_false_pos=.8)
print('fp rate estimated to be {fpr:1.3f}'.format(fpr=fp_rate))
if args.force and len(corrupt_files) > 0:
print("** WARNING: Finished with errors!", file=sys.stderr)
print("** I/O Errors occurred in the following files:", file=sys.stderr)
print("\t", " ".join(corrupt_files), file=sys.stderr)
def main(): # pylint: disable=too-many-branches,too-many-statements
info('saturate-by-median.py', ['diginorm'])
args = get_parser().parse_args()
report_on_config(args)
report_fp = args.report
report_frequency = args.report_frequency
check_valid_file_exists(args.input_filenames)
check_space(args.input_filenames, False)
if args.savetable:
check_space_for_hashtable(args.n_tables * args.min_tablesize, False)
# list to save error files along with throwing exceptions
if args.force:
corrupt_files = []
if args.loadtable:
print 'loading k-mer counting table from', args.loadtable
htable = khmer.load_counting_hash(args.loadtable)
else:
print 'making k-mer counting table'
htable = khmer.new_counting_hash(args.ksize, args.min_tablesize,
args.n_tables)
total = 0
discarded = 0
for index, input_filename in enumerate(args.input_filenames):
total_acc = 0
discarded_acc = 0
try:
total_acc, discarded_acc = normalize_by_median(input_filename,
htable, args,
report_fp,
report_frequency)
except IOError as err:
handle_error(err, input_filename)
if not args.force:
print >> sys.stderr, '** Exiting!'
sys.exit(1)
else:
print >> sys.stderr, '*** Skipping error file, moving on...'
corrupt_files.append(input_filename)
else:
if total_acc == 0 and discarded_acc == 0:
print 'SKIPPED empty file', input_filename
else:
total += total_acc
discarded += discarded_acc
print 'DONE with {inp}; kept {kept} of {total} or {perc:2}%'\
.format(inp=input_filename,
kept=total - discarded, total=total,
perc=int(100. - discarded / float(total) * 100.))
if args.savetable:
print 'Saving k-mer counting table through', input_filename
print '...saving to', args.savetable
htable.save(args.savetable)
# re: threshold, see Zhang et al.,
# http://arxiv.org/abs/1309.2975
fp_rate = khmer.calc_expected_collisions(htable, args.force, max_false_pos=.8)
print 'fp rate estimated to be {fpr:1.3f}'.format(fpr=fp_rate)
if args.force and len(corrupt_files) > 0:
print >> sys.stderr, "** WARNING: Finished with errors!"
print >> sys.stderr, "** IOErrors occurred in the following files:"
print >> sys.stderr, "\t", " ".join(corrupt_files)
def main(): # pylint: disable=too-many-branches,too-many-statements
info('saturate-by-median.py', ['diginorm'])
args = get_parser().parse_args()
report_on_config(args)
report_fp = args.report
report_frequency = args.report_frequency
check_valid_file_exists(args.input_filenames)
check_space(args.input_filenames, False)
if args.savetable:
check_space_for_hashtable(args.n_tables * args.min_tablesize, False)
# list to save error files along with throwing exceptions
if args.force:
corrupt_files = []
if args.loadtable:
print 'loading k-mer counting table from', args.loadtable
htable = khmer.load_counting_hash(args.loadtable)
else:
print 'making k-mer counting table'
htable = khmer.new_counting_hash(args.ksize, args.min_tablesize,
args.n_tables)
total = 0
discarded = 0
for index, input_filename in enumerate(args.input_filenames):
total_acc = 0
discarded_acc = 0
try:
total_acc, discarded_acc = normalize_by_median(
input_filename, htable, args, report_fp, report_frequency)
except IOError as err:
handle_error(err, input_filename)
if not args.force:
print >> sys.stderr, '** Exiting!'
sys.exit(1)
else:
print >> sys.stderr, '*** Skipping error file, moving on...'
corrupt_files.append(input_filename)
else:
if total_acc == 0 and discarded_acc == 0:
print 'SKIPPED empty file', input_filename
else:
total += total_acc
discarded += discarded_acc
print 'DONE with {inp}; kept {kept} of {total} or {perc:2}%'\
.format(inp=input_filename,
kept=total - discarded, total=total,
perc=int(100. - discarded / float(total) * 100.))
if args.savetable:
print 'Saving k-mer counting table through', input_filename
print '...saving to', args.savetable
htable.save(args.savetable)
# re: threshold, see Zhang et al.,
# http://arxiv.org/abs/1309.2975
fp_rate = khmer.calc_expected_collisions(htable,
args.force,
max_false_pos=.8)
print 'fp rate estimated to be {fpr:1.3f}'.format(fpr=fp_rate)
if args.force and len(corrupt_files) > 0:
print >> sys.stderr, "** WARNING: Finished with errors!"
print >> sys.stderr, "** IOErrors occurred in the following files:"
print >> sys.stderr, "\t", " ".join(corrupt_files)
def main():
info('trim-low-abund.py', ['streaming'])
parser = get_parser()
args = parser.parse_args()
###
if len(set(args.input_filenames)) != len(args.input_filenames):
print >>sys.stderr, \
"Error: Cannot input the same filename multiple times."
sys.exit(1)
###
report_on_config(args)
check_valid_file_exists(args.input_filenames)
check_space(args.input_filenames, args.force)
if args.savetable:
check_space_for_hashtable(
args.n_tables * args.min_tablesize, args.force)
K = args.ksize
CUTOFF = args.cutoff
NORMALIZE_LIMIT = args.normalize_to
if args.loadtable:
print >>sys.stderr, 'loading k-mer counting table from', args.loadtable
ct = khmer.load_counting_hash(args.loadtable)
else:
print >>sys.stderr, 'making k-mer counting table'
ct = khmer.new_counting_hash(K, args.min_tablesize, args.n_tables)
tempdir = tempfile.mkdtemp('khmer', 'tmp', args.tempdir)
print >>sys.stderr, 'created temporary directory %s; ' \
'use -T to change location' % tempdir
# ### FIRST PASS ###
save_pass2_total = 0
n_bp = 0
n_reads = 0
written_bp = 0
written_reads = 0
trimmed_reads = 0
pass2list = []
for filename in args.input_filenames:
pass2filename = os.path.basename(filename) + '.pass2'
pass2filename = os.path.join(tempdir, pass2filename)
trimfilename = os.path.basename(filename) + '.abundtrim'
pass2list.append((filename, pass2filename, trimfilename))
screed_iter = screed.open(filename, parse_description=False)
pass2fp = open(pass2filename, 'w')
trimfp = open(trimfilename, 'w')
save_pass2 = 0
n = 0
paired_iter = broken_paired_reader(screed_iter, min_length=K,
force_single=args.ignore_pairs)
for n, is_pair, read1, read2 in paired_iter:
if n % 10000 == 0:
print >>sys.stderr, '...', n, filename, save_pass2, \
n_reads, n_bp, written_reads, written_bp
# we want to track paired reads here, to make sure that pairs
# are not split between first pass and second pass.
if is_pair:
n_reads += 2
n_bp += len(read1.sequence) + len(read2.sequence)
seq1 = read1.sequence.replace('N', 'A')
seq2 = read2.sequence.replace('N', 'A')
med1, _, _ = ct.get_median_count(seq1)
med2, _, _ = ct.get_median_count(seq2)
if med1 < NORMALIZE_LIMIT or med2 < NORMALIZE_LIMIT:
ct.consume(seq1)
ct.consume(seq2)
write_record_pair(read1, read2, pass2fp)
save_pass2 += 2
else:
_, trim_at1 = ct.trim_on_abundance(seq1, CUTOFF)
_, trim_at2 = ct.trim_on_abundance(seq2, CUTOFF)
if trim_at1 >= K:
read1 = trim_record(read1, trim_at1)
if trim_at2 >= K:
read2 = trim_record(read2, trim_at2)
if trim_at1 != len(seq1):
trimmed_reads += 1
if trim_at2 != len(seq2):
trimmed_reads += 1
write_record_pair(read1, read2, trimfp)
written_reads += 2
written_bp += trim_at1 + trim_at2
else:
n_reads += 1
n_bp += len(read1.sequence)
seq = read1.sequence.replace('N', 'A')
med, _, _ = ct.get_median_count(seq)
# has this portion of the graph saturated? if not,
# consume & save => pass2.
if med < NORMALIZE_LIMIT:
ct.consume(seq)
write_record(read1, pass2fp)
save_pass2 += 1
else: # trim!!
_, trim_at = ct.trim_on_abundance(seq, CUTOFF)
if trim_at >= K:
new_read = trim_record(read1, trim_at)
write_record(new_read, trimfp)
written_reads += 1
written_bp += trim_at
if trim_at != len(read1.sequence):
trimmed_reads += 1
pass2fp.close()
trimfp.close()
print '%s: kept aside %d of %d from first pass, in %s' % \
(filename, save_pass2, n, filename)
save_pass2_total += save_pass2
# ### SECOND PASS. ###
skipped_n = 0
skipped_bp = 0
for _, pass2filename, trimfilename in pass2list:
print 'second pass: looking at sequences kept aside in %s' % \
pass2filename
# note that for this second pass, we don't care about paired
# reads - they will be output in the same order they're read in,
# so pairs will stay together if not orphaned. This is in contrast
# to the first loop.
trimfp = open(trimfilename, 'a')
for n, read in enumerate(screed.open(pass2filename,
parse_description=False)):
if n % 10000 == 0:
print >>sys.stderr, '... x 2', n, pass2filename, \
written_reads, written_bp
seq = read.sequence.replace('N', 'A')
med, _, _ = ct.get_median_count(seq)
# do we retain low-abundance components unchanged?
if med < NORMALIZE_LIMIT and args.variable_coverage:
write_record(read, trimfp)
written_reads += 1
written_bp += len(read.sequence)
skipped_n += 1
skipped_bp += len(read.sequence)
# otherwise, examine/trim/truncate.
else: # med >= NORMALIZE LIMIT or not args.variable_coverage
_, trim_at = ct.trim_on_abundance(seq, CUTOFF)
if trim_at >= K:
new_read = trim_record(read, trim_at)
write_record(new_read, trimfp)
written_reads += 1
written_bp += trim_at
if trim_at != len(read.sequence):
trimmed_reads += 1
print >>sys.stderr, 'removing %s' % pass2filename
os.unlink(pass2filename)
print >>sys.stderr, 'removing temp directory & contents (%s)' % tempdir
shutil.rmtree(tempdir)
n_passes = 1.0 + (float(save_pass2_total) / n_reads)
percent_reads_trimmed = float(trimmed_reads + (n_reads - written_reads)) /\
n_reads * 100.0
print 'read %d reads, %d bp' % (n_reads, n_bp,)
print 'wrote %d reads, %d bp' % (written_reads, written_bp,)
print 'looked at %d reads twice (%.2f passes)' % (save_pass2_total,
n_passes)
print 'removed %d reads and trimmed %d reads (%.2f%%)' % \
(n_reads - written_reads, trimmed_reads, percent_reads_trimmed)
print 'trimmed or removed %.2f%% of bases (%d total)' % \
((1 - (written_bp / float(n_bp))) * 100.0, n_bp - written_bp)
if args.variable_coverage:
percent_reads_hicov = 100.0 * float(n_reads - skipped_n) / n_reads
print '%d reads were high coverage (%.2f%%);' % (n_reads - skipped_n,
percent_reads_hicov)
print 'skipped %d reads/%d bases because of low coverage' % \
(skipped_n, skipped_bp)
fp_rate = khmer.calc_expected_collisions(ct)
print >>sys.stderr, \
'fp rate estimated to be {fpr:1.3f}'.format(fpr=fp_rate)
if fp_rate > MAX_FALSE_POSITIVE_RATE:
print >> sys.stderr, "**"
print >> sys.stderr, ("** ERROR: the k-mer counting table is too small"
" for this data set. Increase tablesize/# "
"tables.")
print >> sys.stderr, "**"
print >> sys.stderr, "** Do not use these results!!"
sys.exit(1)
print 'output in *.abundtrim'
if args.savetable:
print >>sys.stderr, "Saving k-mer counting table to", args.savetable
ct.save(args.savetable)
def main():
info('trim-low-abund.py', ['streaming'])
parser = get_parser()
args = parser.parse_args()
###
if len(set(args.input_filenames)) != len(args.input_filenames):
print >>sys.stderr, \
"Error: Cannot input the same filename multiple times."
sys.exit(1)
###
report_on_config(args)
check_valid_file_exists(args.input_filenames)
check_space(args.input_filenames, args.force)
if args.savetable:
check_space_for_hashtable(args.n_tables * args.min_tablesize,
args.force)
K = args.ksize
CUTOFF = args.cutoff
NORMALIZE_LIMIT = args.normalize_to
if args.loadtable:
print >> sys.stderr, 'loading k-mer counting table from', args.loadtable
ct = khmer.load_counting_hash(args.loadtable)
else:
print >> sys.stderr, 'making k-mer counting table'
ct = khmer.new_counting_hash(K, args.min_tablesize, args.n_tables)
tempdir = tempfile.mkdtemp('khmer', 'tmp', args.tempdir)
print >>sys.stderr, 'created temporary directory %s; ' \
'use -T to change location' % tempdir
# ### FIRST PASS ###
save_pass2_total = 0
n_bp = 0
n_reads = 0
written_bp = 0
written_reads = 0
trimmed_reads = 0
pass2list = []
for filename in args.input_filenames:
pass2filename = os.path.basename(filename) + '.pass2'
pass2filename = os.path.join(tempdir, pass2filename)
if args.out is None:
trimfp = open(os.path.basename(filename) + '.abundtrim', 'w')
else:
trimfp = args.out
pass2list.append((filename, pass2filename, trimfp))
screed_iter = screed.open(filename, parse_description=False)
pass2fp = open(pass2filename, 'w')
save_pass2 = 0
n = 0
paired_iter = broken_paired_reader(screed_iter,
min_length=K,
force_single=args.ignore_pairs)
for n, is_pair, read1, read2 in paired_iter:
if n % 10000 == 0:
print >>sys.stderr, '...', n, filename, save_pass2, \
n_reads, n_bp, written_reads, written_bp
# we want to track paired reads here, to make sure that pairs
# are not split between first pass and second pass.
if is_pair:
n_reads += 2
n_bp += len(read1.sequence) + len(read2.sequence)
seq1 = read1.sequence.replace('N', 'A')
seq2 = read2.sequence.replace('N', 'A')
med1, _, _ = ct.get_median_count(seq1)
med2, _, _ = ct.get_median_count(seq2)
if med1 < NORMALIZE_LIMIT or med2 < NORMALIZE_LIMIT:
ct.consume(seq1)
ct.consume(seq2)
write_record_pair(read1, read2, pass2fp)
save_pass2 += 2
else:
_, trim_at1 = ct.trim_on_abundance(seq1, CUTOFF)
_, trim_at2 = ct.trim_on_abundance(seq2, CUTOFF)
if trim_at1 >= K:
read1 = trim_record(read1, trim_at1)
if trim_at2 >= K:
read2 = trim_record(read2, trim_at2)
if trim_at1 != len(seq1):
trimmed_reads += 1
if trim_at2 != len(seq2):
trimmed_reads += 1
write_record_pair(read1, read2, trimfp)
written_reads += 2
written_bp += trim_at1 + trim_at2
else:
n_reads += 1
n_bp += len(read1.sequence)
seq = read1.sequence.replace('N', 'A')
med, _, _ = ct.get_median_count(seq)
# has this portion of the graph saturated? if not,
# consume & save => pass2.
if med < NORMALIZE_LIMIT:
ct.consume(seq)
write_record(read1, pass2fp)
save_pass2 += 1
else: # trim!!
_, trim_at = ct.trim_on_abundance(seq, CUTOFF)
if trim_at >= K:
new_read = trim_record(read1, trim_at)
write_record(new_read, trimfp)
written_reads += 1
written_bp += trim_at
if trim_at != len(read1.sequence):
trimmed_reads += 1
pass2fp.close()
print >>sys.stderr, '%s: kept aside %d of %d from first pass, in %s' \
% (filename, save_pass2, n, filename)
save_pass2_total += save_pass2
# ### SECOND PASS. ###
skipped_n = 0
skipped_bp = 0
for _, pass2filename, trimfp in pass2list:
print >> sys.stderr, ('second pass: looking at sequences kept aside '
'in %s') % pass2filename
# note that for this second pass, we don't care about paired
# reads - they will be output in the same order they're read in,
# so pairs will stay together if not orphaned. This is in contrast
# to the first loop.
for n, read in enumerate(
screed.open(pass2filename, parse_description=False)):
if n % 10000 == 0:
print >>sys.stderr, '... x 2', n, pass2filename, \
written_reads, written_bp
seq = read.sequence.replace('N', 'A')
med, _, _ = ct.get_median_count(seq)
# do we retain low-abundance components unchanged?
if med < NORMALIZE_LIMIT and args.variable_coverage:
write_record(read, trimfp)
written_reads += 1
written_bp += len(read.sequence)
skipped_n += 1
skipped_bp += len(read.sequence)
# otherwise, examine/trim/truncate.
else: # med >= NORMALIZE LIMIT or not args.variable_coverage
_, trim_at = ct.trim_on_abundance(seq, CUTOFF)
if trim_at >= K:
new_read = trim_record(read, trim_at)
write_record(new_read, trimfp)
written_reads += 1
written_bp += trim_at
if trim_at != len(read.sequence):
trimmed_reads += 1
print >> sys.stderr, 'removing %s' % pass2filename
os.unlink(pass2filename)
print >> sys.stderr, 'removing temp directory & contents (%s)' % tempdir
shutil.rmtree(tempdir)
n_passes = 1.0 + (float(save_pass2_total) / n_reads)
percent_reads_trimmed = float(trimmed_reads + (n_reads - written_reads)) /\
n_reads * 100.0
print >> sys.stderr, 'read %d reads, %d bp' % (
n_reads,
n_bp,
)
print >> sys.stderr, 'wrote %d reads, %d bp' % (
written_reads,
written_bp,
)
print >>sys.stderr, 'looked at %d reads twice (%.2f passes)' % \
(save_pass2_total, n_passes)
print >>sys.stderr, 'removed %d reads and trimmed %d reads (%.2f%%)' % \
(n_reads - written_reads, trimmed_reads, percent_reads_trimmed)
print >>sys.stderr, 'trimmed or removed %.2f%% of bases (%d total)' % \
((1 - (written_bp / float(n_bp))) * 100.0, n_bp - written_bp)
if args.variable_coverage:
percent_reads_hicov = 100.0 * float(n_reads - skipped_n) / n_reads
print >>sys.stderr, '%d reads were high coverage (%.2f%%);' % \
(n_reads - skipped_n, percent_reads_hicov)
print >> sys.stderr, ('skipped %d reads/%d bases because of low'
'coverage') % (skipped_n, skipped_bp)
fp_rate = \
khmer.calc_expected_collisions(ct, args.force, max_false_pos=.8)
# for max_false_pos see Zhang et al., http://arxiv.org/abs/1309.2975
print >>sys.stderr, \
'fp rate estimated to be {fpr:1.3f}'.format(fpr=fp_rate)
print >> sys.stderr, 'output in *.abundtrim'
if args.savetable:
print >> sys.stderr, "Saving k-mer counting table to", args.savetable
ct.save(args.savetable)
def main():
info('trim-low-abund.py', ['streaming'])
parser = sanitize_help(get_parser())
args = parser.parse_args()
###
if len(set(args.input_filenames)) != len(args.input_filenames):
print("Error: Cannot input the same filename multiple times.",
file=sys.stderr)
sys.exit(1)
###
report_on_config(args)
check_valid_file_exists(args.input_filenames)
check_space(args.input_filenames, args.force)
if args.savegraph:
graphsize = calculate_graphsize(args, 'countgraph')
check_space_for_graph(args.savegraph, graphsize, args.force)
if ('-' in args.input_filenames or '/dev/stdin' in args.input_filenames) \
and not args.output:
print("Accepting input from stdin; output filename must "
"be provided with -o.", file=sys.stderr)
sys.exit(1)
if args.loadgraph:
print('loading countgraph from', args.loadgraph, file=sys.stderr)
ct = khmer.load_countgraph(args.loadgraph)
else:
print('making countgraph', file=sys.stderr)
ct = khmer_args.create_countgraph(args)
K = ct.ksize()
CUTOFF = args.cutoff
NORMALIZE_LIMIT = args.normalize_to
tempdir = tempfile.mkdtemp('khmer', 'tmp', args.tempdir)
print('created temporary directory %s; '
'use -T to change location' % tempdir, file=sys.stderr)
# ### FIRST PASS ###
save_pass2_total = 0
n_bp = 0
n_reads = 0
written_bp = 0
written_reads = 0
trimmed_reads = 0
pass2list = []
for filename in args.input_filenames:
pass2filename = os.path.basename(filename) + '.pass2'
pass2filename = os.path.join(tempdir, pass2filename)
if args.output is None:
trimfp = get_file_writer(open(os.path.basename(filename) +
'.abundtrim', 'wb'),
args.gzip, args.bzip)
else:
trimfp = get_file_writer(args.output, args.gzip, args.bzip)
pass2list.append((filename, pass2filename, trimfp))
screed_iter = screed.open(filename)
pass2fp = open(pass2filename, 'w')
save_pass2 = 0
n = 0
paired_iter = broken_paired_reader(screed_iter, min_length=K,
force_single=args.ignore_pairs)
for n, is_pair, read1, read2 in paired_iter:
if n % 10000 == 0:
print('...', n, filename, save_pass2, n_reads, n_bp,
written_reads, written_bp, file=sys.stderr)
# we want to track paired reads here, to make sure that pairs
# are not split between first pass and second pass.
if is_pair:
n_reads += 2
n_bp += len(read1.sequence) + len(read2.sequence)
seq1 = read1.sequence.replace('N', 'A')
seq2 = read2.sequence.replace('N', 'A')
med1, _, _ = ct.get_median_count(seq1)
med2, _, _ = ct.get_median_count(seq2)
if med1 < NORMALIZE_LIMIT or med2 < NORMALIZE_LIMIT:
ct.consume(seq1)
ct.consume(seq2)
write_record_pair(read1, read2, pass2fp)
save_pass2 += 2
else:
_, trim_at1 = ct.trim_on_abundance(seq1, CUTOFF)
_, trim_at2 = ct.trim_on_abundance(seq2, CUTOFF)
if trim_at1 >= K:
read1 = trim_record(read1, trim_at1)
if trim_at2 >= K:
read2 = trim_record(read2, trim_at2)
if trim_at1 != len(seq1):
trimmed_reads += 1
if trim_at2 != len(seq2):
trimmed_reads += 1
write_record_pair(read1, read2, trimfp)
written_reads += 2
written_bp += trim_at1 + trim_at2
else:
n_reads += 1
n_bp += len(read1.sequence)
seq = read1.sequence.replace('N', 'A')
med, _, _ = ct.get_median_count(seq)
# has this portion of the graph saturated? if not,
# consume & save => pass2.
if med < NORMALIZE_LIMIT:
ct.consume(seq)
write_record(read1, pass2fp)
save_pass2 += 1
else: # trim!!
_, trim_at = ct.trim_on_abundance(seq, CUTOFF)
if trim_at >= K:
new_read = trim_record(read1, trim_at)
write_record(new_read, trimfp)
written_reads += 1
written_bp += trim_at
if trim_at != len(read1.sequence):
trimmed_reads += 1
pass2fp.close()
print('%s: kept aside %d of %d from first pass, in %s' %
(filename, save_pass2, n, filename),
file=sys.stderr)
save_pass2_total += save_pass2
# ### SECOND PASS. ###
skipped_n = 0
skipped_bp = 0
for _, pass2filename, trimfp in pass2list:
print('second pass: looking at sequences kept aside in %s' %
pass2filename,
file=sys.stderr)
# note that for this second pass, we don't care about paired
# reads - they will be output in the same order they're read in,
# so pairs will stay together if not orphaned. This is in contrast
# to the first loop.
for n, read in enumerate(screed.open(pass2filename)):
if n % 10000 == 0:
print('... x 2', n, pass2filename,
written_reads, written_bp, file=sys.stderr)
seq = read.sequence.replace('N', 'A')
med, _, _ = ct.get_median_count(seq)
# do we retain low-abundance components unchanged?
if med < NORMALIZE_LIMIT and args.variable_coverage:
write_record(read, trimfp)
written_reads += 1
written_bp += len(read.sequence)
skipped_n += 1
skipped_bp += len(read.sequence)
# otherwise, examine/trim/truncate.
else: # med >= NORMALIZE LIMIT or not args.variable_coverage
_, trim_at = ct.trim_on_abundance(seq, CUTOFF)
if trim_at >= K:
new_read = trim_record(read, trim_at)
write_record(new_read, trimfp)
written_reads += 1
written_bp += trim_at
if trim_at != len(read.sequence):
trimmed_reads += 1
print('removing %s' % pass2filename, file=sys.stderr)
os.unlink(pass2filename)
print('removing temp directory & contents (%s)' % tempdir, file=sys.stderr)
shutil.rmtree(tempdir)
n_passes = 1.0 + (float(save_pass2_total) / n_reads)
percent_reads_trimmed = float(trimmed_reads + (n_reads - written_reads)) /\
n_reads * 100.0
print('read %d reads, %d bp' % (n_reads, n_bp,), file=sys.stderr)
print('wrote %d reads, %d bp' % (written_reads, written_bp,),
file=sys.stderr)
print('looked at %d reads twice (%.2f passes)' % (save_pass2_total,
n_passes),
file=sys.stderr)
print('removed %d reads and trimmed %d reads (%.2f%%)' %
(n_reads - written_reads, trimmed_reads, percent_reads_trimmed),
file=sys.stderr)
print('trimmed or removed %.2f%% of bases (%d total)' %
((1 - (written_bp / float(n_bp))) * 100.0, n_bp - written_bp),
file=sys.stderr)
if args.variable_coverage:
percent_reads_hicov = 100.0 * float(n_reads - skipped_n) / n_reads
print('%d reads were high coverage (%.2f%%);' % (n_reads - skipped_n,
percent_reads_hicov),
file=sys.stderr)
print('skipped %d reads/%d bases because of low coverage' %
(skipped_n, skipped_bp),
file=sys.stderr)
fp_rate = \
khmer.calc_expected_collisions(ct, args.force, max_false_pos=.8)
# for max_false_pos see Zhang et al., http://arxiv.org/abs/1309.2975
print('fp rate estimated to be {fpr:1.3f}'.format(fpr=fp_rate),
file=sys.stderr)
print('output in *.abundtrim', file=sys.stderr)
if args.savegraph:
print("Saving k-mer countgraph to",
args.savegraph, file=sys.stderr)
ct.save(args.savegraph)
def main():
info("sweep-reads-buffered.py", ["sweep"])
parser = sanitize_epilog(get_parser())
args = parser.parse_args()
if args.max_tablesize < MAX_HSIZE:
args.max_tablesize = MAX_HSIZE
if args.ksize < MIN_KSIZE:
args.ksize = MIN_KSIZE
report_on_config(args, graphtype="nodegraph")
K = args.ksize
HT_SIZE = args.max_tablesize
N_HT = args.n_tables
traversal_range = args.traversal_range
input_fastp = args.input_fastp
if not args.outdir:
outdir = os.path.dirname(input_fastp)
else:
outdir = args.outdir
max_buffers = args.max_buffers
output_pref = args.output_prefix
buf_size = args.buffer_size
max_reads = args.max_reads
check_input_files(args.input_fastp, args.force)
check_valid_file_exists(args.input_files)
all_input_files = [input_fastp]
all_input_files.extend(args.input_files)
# Check disk space availability
check_space(all_input_files, args.force)
# figure out input file type (FA/FQ) -- based on first file
ix = iter(screed.open(args.input_files[0]))
record = next(ix)
del ix
extension = "fa"
if hasattr(record, "quality"): # fastq!
extension = "fq"
output_buffer = ReadBufferManager(max_buffers, max_reads, buf_size, output_pref, outdir, extension)
# consume the partitioned fasta with which to label the graph
ht = khmer.GraphLabels(K, HT_SIZE, N_HT)
try:
print("consuming input sequences...", file=sys.stderr)
if args.label_by_pid:
print("...labeling by partition id (pid)", file=sys.stderr)
ht.consume_partitioned_fasta_and_tag_with_labels(input_fastp)
elif args.label_by_seq:
print("...labeling by sequence", file=sys.stderr)
for n, record in enumerate(screed.open(input_fastp)):
if n % 50000 == 0:
print("...consumed {n} sequences...".format(n=n), file=sys.stderr)
ht.consume_sequence_and_tag_with_labels(record.sequence, n)
else:
print("...labeling to create groups of size {s}".format(s=args.group_size), file=sys.stderr)
label = -1
g = 0
try:
outfp = open("{pref}_base_{g}.{ext}".format(pref=output_pref, g=g, ext=extension), "wb")
for n, record in enumerate(screed.open(input_fastp)):
if n % args.group_size == 0:
label += 1
if label > g:
g = label
outfp = open("{pref}_base_{g}.{ext}".format(pref=output_pref, g=g, ext=extension), "wb")
if n % 50000 == 0:
print("...consumed {n} sequences...".format(n=n), file=sys.stderr)
ht.consume_sequence_and_tag_with_labels(record.sequence, label)
write_record(record, outfp)
except (IOError, OSError) as e:
print("!! ERROR !!", e, file=sys.stderr)
print("...error splitting input. exiting...", file=sys.stderr)
except (IOError, OSError) as e:
print("!! ERROR: !!", e, file=sys.stderr)
print(
"...error consuming \
{i}. exiting...".format(
i=input_fastp
),
file=sys.stderr,
)
print(
"done consuming input sequence. \
added {t} tags and {l} \
labels...".format(
t=ht.graph.n_tags(), l=ht.n_labels()
)
)
label_dict = defaultdict(int)
label_number_dist = []
n_orphaned = 0
n_labeled = 0
n_mlabeled = 0
total_t = time.clock()
start_t = time.clock()
for read_file in args.input_files:
print("** sweeping {read_file} for labels...".format(read_file=read_file), file=sys.stderr)
file_t = 0.0
try:
read_fp = screed.open(read_file)
except (IOError, OSError) as error:
print("!! ERROR: !!", error, file=sys.stderr)
print("*** Could not open {fn}, skipping...".format(fn=read_file), file=sys.stderr)
else:
for _, record in enumerate(read_fp):
if _ % 50000 == 0:
end_t = time.clock()
batch_t = end_t - start_t
file_t += batch_t
print(
"\tswept {n} reads [{nc} labeled, \
{no} orphaned] \
** {sec}s ({sect}s total)".format(
n=_, nc=n_labeled, no=n_orphaned, sec=batch_t, sect=file_t
),
file=sys.stderr,
)
start_t = time.clock()
seq = record.sequence
name = record.name
try:
labels = ht.sweep_label_neighborhood(seq, traversal_range)
except ValueError as e:
pass
else:
if hasattr(record, "quality"):
seq_str = fmt_fastq(name, seq, record.quality, labels)
else:
seq_str = fmt_fasta(name, seq, labels)
label_number_dist.append(len(labels))
if labels:
n_labeled += 1
if len(labels) > 1:
output_buffer.queue(seq_str, "multi")
n_mlabeled += 1
label_dict["multi"] += 1
else:
output_buffer.queue(seq_str, labels[0])
label_dict[labels[0]] += 1
else:
n_orphaned += 1
output_buffer.queue(seq_str, "orphaned")
label_dict["orphaned"] += 1
print("** End of file {fn}...".format(fn=read_file), file=sys.stderr)
output_buffer.flush_all()
read_fp.close()
# gotta output anything left in the buffers at the end!
print("** End of run...", file=sys.stderr)
output_buffer.flush_all()
total_t = time.clock() - total_t
if output_buffer.num_write_errors > 0 or output_buffer.num_file_errors > 0:
print("! WARNING: Sweep finished with errors !", file=sys.stderr)
print("** {writee} reads not written".format(writee=output_buffer.num_write_errors), file=sys.stderr)
print("** {filee} errors opening files".format(filee=output_buffer.num_file_errors), file=sys.stderr)
print("swept {n_reads} for labels...".format(n_reads=n_labeled + n_orphaned), file=sys.stderr)
print("...with {nc} labeled and {no} orphaned".format(nc=n_labeled, no=n_orphaned), file=sys.stderr)
print("...and {nmc} multilabeled".format(nmc=n_mlabeled), file=sys.stderr)
print("** outputting label number distribution...", file=sys.stderr)
fn = os.path.join(outdir, "{pref}.dist.txt".format(pref=output_pref))
with open(fn, "w", encoding="utf-8") as outfp:
for nc in label_number_dist:
outfp.write("{nc}\n".format(nc=nc))
fn = os.path.join(outdir, "{pref}.counts.csv".format(pref=output_pref))
print("** outputting label read counts...", file=sys.stderr)
with open(fn, "w", encoding="utf-8") as outfp:
for k in label_dict:
outfp.write("{l},{c}\n".format(l=k, c=label_dict[k]))
def main():
info('sweep-reads-buffered.py', ['sweep'])
parser = get_parser()
args = parser.parse_args()
if args.min_tablesize < MIN_HSIZE:
args.min_tablesize = MIN_HSIZE
if args.ksize < MIN_KSIZE:
args.ksize = MIN_KSIZE
report_on_config(args, hashtype='hashbits')
K = args.ksize
HT_SIZE = args.min_tablesize
N_HT = args.n_tables
traversal_range = args.traversal_range
input_fastp = args.input_fastp
if not args.outdir:
outdir = os.path.dirname(input_fastp)
else:
outdir = args.outdir
max_buffers = args.max_buffers
output_pref = args.output_prefix
buf_size = args.buffer_size
max_reads = args.max_reads
check_file_status(args.input_fastp, args.force)
check_valid_file_exists(args.input_files)
all_input_files = [input_fastp]
all_input_files.extend(args.input_files)
# Check disk space availability
check_space(all_input_files, args.force)
# figure out input file type (FA/FQ) -- based on first file
ix = iter(screed.open(args.input_files[0]))
record = ix.next()
del ix
extension = 'fa'
if hasattr(record, 'accuracy'): # fastq!
extension = 'fq'
output_buffer = ReadBufferManager(
max_buffers, max_reads, buf_size, output_pref, outdir, extension)
# consume the partitioned fasta with which to label the graph
ht = khmer.LabelHash(K, HT_SIZE, N_HT)
try:
print >>sys.stderr, 'consuming input sequences...'
if args.label_by_pid:
print >>sys.stderr, '...labeling by partition id (pid)'
ht.consume_partitioned_fasta_and_tag_with_labels(input_fastp)
elif args.label_by_seq:
print >>sys.stderr, '...labeling by sequence'
for n, record in enumerate(screed.open(input_fastp)):
if n % 50000 == 0:
print >>sys.stderr, \
'...consumed {n} sequences...'.format(n=n)
ht.consume_sequence_and_tag_with_labels(record.sequence, n)
else:
print >>sys.stderr, \
'...labeling to create groups of size {s}'.format(
s=args.group_size)
label = -1
g = 0
try:
outfp = open('{pref}_base_{g}.{ext}'.format(pref=output_pref,
g=g,
ext=extension
), 'wb')
for n, record in enumerate(screed.open(input_fastp)):
if n % args.group_size == 0:
label += 1
if label > g:
g = label
outfp = open('{pref}_base_{g}.{ext}'.format(
pref=output_pref, g=g,
ext=extension), 'wb')
if n % 50000 == 0:
print >>sys.stderr, \
'...consumed {n} sequences...'.format(n=n)
ht.consume_sequence_and_tag_with_labels(record.sequence,
label)
if hasattr(record, 'accuracy'):
outfp.write('@{name}\n{seq}+{accuracy}\n'.format(
name=record.name,
seq=record.sequence,
accuracy=record.accuracy))
else:
outfp.write('>{name}\n{seq}\n'.format(
name=record.name,
seq=record.sequence))
except IOError as e:
print >>sys.stderr, '!! ERROR !!', e
print >>sys.stderr, '...error splitting input. exiting...'
except IOError as e:
print >>sys.stderr, '!! ERROR: !!', e
print >>sys.stderr, '...error consuming \
{i}. exiting...'.format(i=input_fastp)
print >>sys.stderr, 'done consuming input sequence. \
added {t} tags and {l} \
labels...'.format(t=ht.n_tags(), l=ht.n_labels())
label_dict = defaultdict(int)
label_number_dist = []
n_orphaned = 0
n_labeled = 0
n_mlabeled = 0
total_t = time.clock()
start_t = time.clock()
for read_file in args.input_files:
print >>sys.stderr, '** sweeping {read_file} for labels...'.format(
read_file=read_file)
file_t = 0.0
try:
read_fp = screed.open(read_file)
except IOError as error:
print >>sys.stderr, '!! ERROR: !!', error
print >>sys.stderr, '*** Could not open {fn}, skipping...'.format(
fn=read_file)
else:
for _, record in enumerate(read_fp):
if _ % 50000 == 0:
end_t = time.clock()
batch_t = end_t - start_t
file_t += batch_t
print >>sys.stderr, '\tswept {n} reads [{nc} labeled, \
{no} orphaned] \
** {sec}s ({sect}s total)' \
.format(n=_, nc=n_labeled,
no=n_orphaned,
sec=batch_t, sect=file_t)
start_t = time.clock()
seq = record.sequence
name = record.name
try:
labels = ht.sweep_label_neighborhood(seq, traversal_range)
except ValueError as e:
pass
else:
if hasattr(record, 'accuracy'):
seq_str = fmt_fastq(name, seq, record.accuracy, labels)
else:
seq_str = fmt_fasta(name, seq, labels)
label_number_dist.append(len(labels))
if labels:
n_labeled += 1
if len(labels) > 1:
output_buffer.queue(seq_str, 'multi')
n_mlabeled += 1
label_dict['multi'] += 1
else:
output_buffer.queue(seq_str, labels[0])
label_dict[labels[0]] += 1
else:
n_orphaned += 1
output_buffer.queue(seq_str, 'orphaned')
label_dict['orphaned'] += 1
print >>sys.stderr, '** End of file {fn}...'.format(fn=read_file)
output_buffer.flush_all()
read_fp.close()
# gotta output anything left in the buffers at the end!
print >>sys.stderr, '** End of run...'
output_buffer.flush_all()
total_t = time.clock() - total_t
if output_buffer.num_write_errors > 0 or output_buffer.num_file_errors > 0:
print >>sys.stderr, '! WARNING: Sweep finished with errors !'
print >>sys.stderr, '** {writee} reads not written'.format(
writee=output_buffer.num_write_errors)
print >>sys.stderr, '** {filee} errors opening files'.format(
filee=output_buffer.num_file_errors)
print >>sys.stderr, 'swept {n_reads} for labels...'.format(
n_reads=n_labeled + n_orphaned)
print >>sys.stderr, '...with {nc} labeled and {no} orphaned'.format(
nc=n_labeled, no=n_orphaned)
print >>sys.stderr, '...and {nmc} multilabeled'.format(nmc=n_mlabeled)
print >>sys.stderr, '** outputting label number distribution...'
fn = os.path.join(outdir, '{pref}.dist.txt'.format(pref=output_pref))
with open(fn, 'wb') as outfp:
for nc in label_number_dist:
outfp.write('{nc}\n'.format(nc=nc))
fn = os.path.join(outdir, '{pref}.counts.csv'.format(pref=output_pref))
print >>sys.stderr, '** outputting label read counts...'
with open(fn, 'wb') as outfp:
for k in label_dict:
outfp.write('{l},{c}\n'.format(l=k, c=label_dict[k]))
def main(): # pylint: disable=too-many-branches,too-many-statements
info('normalize-by-median.py', ['diginorm'])
args = get_parser().parse_args()
report_on_config(args)
report_fp = args.report
# check for similar filenames
filenames = []
for pathfilename in args.input_filenames:
filename = pathfilename.split('/')[-1]
if (filename in filenames):
print >>sys.stderr, "WARNING: At least two input files are named \
%s . (The script normalize-by-median.py can not handle this, only one .keep \
file for one of the input files will be generated.)" % filename
else:
filenames.append(filename)
# check for others
check_valid_file_exists(args.input_filenames)
check_space(args.input_filenames, args.force)
if args.savetable:
check_space_for_hashtable(
args.n_tables * args.min_tablesize, args.force)
# list to save error files along with throwing exceptions
corrupt_files = []
if args.loadtable:
print 'loading k-mer counting table from', args.loadtable
htable = khmer.load_counting_hash(args.loadtable)
else:
print >> sys.stderr, 'making k-mer counting table'
htable = khmer.new_counting_hash(args.ksize, args.min_tablesize,
args.n_tables)
input_filename = None
for index, input_filename in enumerate(args.input_filenames):
total_acc, discarded_acc, corrupt_files = \
normalize_by_median_and_check(
input_filename, htable, args.single_output_file,
args.fail_save, args.paired, args.cutoff, args.force,
corrupt_files, report_fp)
if (args.dump_frequency > 0 and
index > 0 and index % args.dump_frequency == 0):
print 'Backup: Saving k-mer counting file through', input_filename
if args.savetable:
hashname = args.savetable
print '...saving to', hashname
else:
hashname = 'backup.ct'
print 'Nothing given for savetable, saving to', hashname
htable.save(hashname)
if args.paired and args.unpaired_reads:
args.paired = False
output_name = args.unpaired_reads
if not args.single_output_file:
output_name = os.path.basename(args.unpaired_reads) + '.keep'
outfp = open(output_name, 'w')
total_acc, discarded_acc, corrupt_files = \
normalize_by_median_and_check(
args.unpaired_reads, htable, args.single_output_file,
args.fail_save, args.paired, args.cutoff, args.force,
corrupt_files, report_fp)
if args.report_total_kmers:
print >> sys.stderr, 'Total number of unique k-mers: {0}'.format(
htable.n_unique_kmers())
if args.savetable:
print 'Saving k-mer counting table through', input_filename
print '...saving to', args.savetable
htable.save(args.savetable)
fp_rate = \
khmer.calc_expected_collisions(htable, args.force, max_false_pos=.8)
# for max_false_pos see Zhang et al., http://arxiv.org/abs/1309.2975
print >> sys.stderr, \
'fp rate estimated to be {fpr:1.3f}'.format(fpr=fp_rate)
if args.force and len(corrupt_files) > 0:
print >> sys.stderr, "** WARNING: Finished with errors!"
print >> sys.stderr, "** IOErrors occurred in the following files:"
print >> sys.stderr, "\t", " ".join(corrupt_files)
def main():
parser = sanitize_help(get_parser())
args = parser.parse_args()
if not args.quiet:
info('trim-low-abund.py', ['streaming'])
configure_logging(args.quiet)
###
if len(set(args.input_filenames)) != len(args.input_filenames):
log_error("Error: Cannot input the same filename multiple times.")
sys.exit(1)
if args.trim_at_coverage != DEFAULT_TRIM_AT_COVERAGE and \
not args.variable_coverage:
log_error("Error: --trim-at-coverage/-Z given, but "
"--variable-coverage/-V not specified.")
sys.exit(1)
if args.diginorm_coverage != DEFAULT_DIGINORM_COVERAGE and \
not args.diginorm:
log_error("Error: --diginorm-coverage given, but "
"--diginorm not specified.")
sys.exit(1)
if args.diginorm and args.single_pass:
log_error("Error: --diginorm and --single-pass are incompatible!\n"
"You probably want to use normalize-by-median.py instead.")
sys.exit(1)
###
report_on_config(args)
check_valid_file_exists(args.input_filenames)
check_space(args.input_filenames, args.force)
if args.savegraph:
graphsize = calculate_graphsize(args, 'countgraph')
check_space_for_graph(args.savegraph, graphsize, args.force)
if ('-' in args.input_filenames or '/dev/stdin' in args.input_filenames) \
and not args.output:
log_error("Accepting input from stdin; output filename must "
"be provided with -o.")
sys.exit(1)
if args.loadgraph:
log_info('loading countgraph from {graph}', graph=args.loadgraph)
ct = khmer.load_countgraph(args.loadgraph)
else:
log_info('making countgraph')
ct = khmer_args.create_countgraph(args)
K = ct.ksize()
tempdir = tempfile.mkdtemp('khmer', 'tmp', args.tempdir)
log_info(
'created temporary directory {temp};\n'
'use -T to change location',
temp=tempdir)
trimmer = Trimmer(ct, not args.variable_coverage, args.cutoff,
args.trim_at_coverage)
if args.diginorm:
trimmer.set_diginorm(args.diginorm_coverage)
# ### FIRST PASS ###
save_pass2_total = 0
written_bp = 0
written_reads = 0
# only create the file writer once if outfp is specified; otherwise,
# create it for each file.
if args.output:
trimfp = get_file_writer(args.output, args.gzip, args.bzip)
pass2list = []
for filename in args.input_filenames:
# figure out temporary filename for 2nd pass
pass2filename = os.path.basename(filename) + '.pass2'
pass2filename = os.path.join(tempdir, pass2filename)
pass2fp = open(pass2filename, 'w')
# construct output filenames
if args.output is None:
# note: this will be saved in trimfp.
outfp = open(os.path.basename(filename) + '.abundtrim', 'wb')
# get file handle w/gzip, bzip
trimfp = get_file_writer(outfp, args.gzip, args.bzip)
# record all this info
pass2list.append((filename, pass2filename, trimfp))
# input file stuff: get a broken_paired reader.
screed_iter = screed.open(filename)
paired_iter = broken_paired_reader(screed_iter,
min_length=K,
force_single=args.ignore_pairs)
# main loop through the file.
n_start = trimmer.n_reads
save_start = trimmer.n_saved
watermark = REPORT_EVERY_N_READS
for read in trimmer.pass1(paired_iter, pass2fp):
if (trimmer.n_reads - n_start) > watermark:
log_info(
"... {filename} {n_saved} {n_reads} {n_bp} "
"{w_reads} {w_bp}",
filename=filename,
n_saved=trimmer.n_saved,
n_reads=trimmer.n_reads,
n_bp=trimmer.n_bp,
w_reads=written_reads,
w_bp=written_bp)
watermark += REPORT_EVERY_N_READS
# write out the trimmed/etc sequences that AREN'T going to be
# revisited in a 2nd pass.
write_record(read, trimfp)
written_bp += len(read)
written_reads += 1
pass2fp.close()
log_info("{filename}: kept aside {kept} of {total} from first pass",
filename=filename,
kept=trimmer.n_saved - save_start,
total=trimmer.n_reads - n_start)
# first pass goes across all the data, so record relevant stats...
n_reads = trimmer.n_reads
n_bp = trimmer.n_bp
n_skipped = trimmer.n_skipped
bp_skipped = trimmer.bp_skipped
save_pass2_total = trimmer.n_saved
# ### SECOND PASS. ###
# nothing should have been skipped yet!
assert trimmer.n_skipped == 0
assert trimmer.bp_skipped == 0
if args.single_pass:
pass2list = []
# go back through all the files again.
for _, pass2filename, trimfp in pass2list:
log_info('second pass: looking at sequences kept aside in {pass2}',
pass2=pass2filename)
# note that for this second pass, we don't care about paired
# reads - they will be output in the same order they're read in,
# so pairs will stay together if not orphaned. This is in contrast
# to the first loop. Hence, force_single=True below.
screed_iter = screed.open(pass2filename, parse_description=False)
paired_iter = broken_paired_reader(screed_iter,
min_length=K,
force_single=True)
watermark = REPORT_EVERY_N_READS
for read in trimmer.pass2(paired_iter):
if (trimmer.n_reads - n_start) > watermark:
log_info('... x 2 {a} {b} {c} {d} {e} {f} {g}',
a=trimmer.n_reads - n_start,
b=pass2filename,
c=trimmer.n_saved,
d=trimmer.n_reads,
e=trimmer.n_bp,
f=written_reads,
g=written_bp)
watermark += REPORT_EVERY_N_READS
write_record(read, trimfp)
written_reads += 1
written_bp += len(read)
log_info('removing {pass2}', pass2=pass2filename)
os.unlink(pass2filename)
# if we created our own trimfps, close 'em.
if not args.output:
trimfp.close()
log_info('removing temp directory & contents ({temp})', temp=tempdir)
shutil.rmtree(tempdir)
trimmed_reads = trimmer.trimmed_reads
n_passes = 1.0 + (float(save_pass2_total) / n_reads)
percent_reads_trimmed = float(trimmed_reads + (n_reads - written_reads)) /\
n_reads * 100.0
log_info('read {read} reads, {bp} bp', read=n_reads, bp=n_bp)
log_info('wrote {wr} reads, {wbp} bp', wr=written_reads, wbp=written_bp)
log_info('looked at {st} reads twice ({np:.2f} passes)',
st=save_pass2_total,
np=n_passes)
log_info('removed {r} reads and trimmed {t} reads ({p:.2f}%)',
r=n_reads - written_reads,
t=trimmed_reads,
p=percent_reads_trimmed)
log_info('trimmed or removed {p:.2f}%% of bases ({bp} total)',
p=(1 - (written_bp / float(n_bp))) * 100.0,
bp=n_bp - written_bp)
if args.variable_coverage:
percent_reads_hicov = 100.0 * float(n_reads - n_skipped) / n_reads
log_info('{n} reads were high coverage ({p:.2f}%);',
n=n_reads - n_skipped,
p=percent_reads_hicov)
log_info('skipped {r} reads/{bp} bases because of low coverage',
r=n_skipped,
bp=bp_skipped)
fp_rate = \
khmer.calc_expected_collisions(ct, args.force, max_false_pos=.8)
# for max_false_pos see Zhang et al., http://arxiv.org/abs/1309.2975
log_info('fp rate estimated to be {fpr:1.3f}', fpr=fp_rate)
log_info('output in *.abundtrim')
if args.savegraph:
log_info("Saving k-mer countgraph to {graph}", graph=args.savegraph)
ct.save(args.savegraph)
def main():
info('sweep-reads-buffered.py', ['sweep'])
parser = get_parser()
args = parser.parse_args()
if args.min_tablesize < MIN_HSIZE:
args.min_tablesize = MIN_HSIZE
if args.ksize < MIN_KSIZE:
args.ksize = MIN_KSIZE
report_on_config(args, hashtype='hashbits')
K = args.ksize
HT_SIZE = args.min_tablesize
N_HT = args.n_tables
traversal_range = args.traversal_range
input_fastp = args.input_fastp
if not args.outdir:
outdir = os.path.dirname(input_fastp)
else:
outdir = args.outdir
max_buffers = args.max_buffers
output_pref = args.output_prefix
buf_size = args.buffer_size
max_reads = args.max_reads
check_input_files(args.input_fastp, args.force)
check_valid_file_exists(args.input_files)
all_input_files = [input_fastp]
all_input_files.extend(args.input_files)
# Check disk space availability
check_space(all_input_files, args.force)
# figure out input file type (FA/FQ) -- based on first file
ix = iter(screed.open(args.input_files[0]))
record = ix.next()
del ix
extension = 'fa'
if hasattr(record, 'quality'): # fastq!
extension = 'fq'
output_buffer = ReadBufferManager(
max_buffers, max_reads, buf_size, output_pref, outdir, extension)
# consume the partitioned fasta with which to label the graph
ht = khmer.LabelHash(K, HT_SIZE, N_HT)
try:
print >>sys.stderr, 'consuming input sequences...'
if args.label_by_pid:
print >>sys.stderr, '...labeling by partition id (pid)'
ht.consume_partitioned_fasta_and_tag_with_labels(input_fastp)
elif args.label_by_seq:
print >>sys.stderr, '...labeling by sequence'
for n, record in enumerate(screed.open(input_fastp)):
if n % 50000 == 0:
print >>sys.stderr, \
'...consumed {n} sequences...'.format(n=n)
ht.consume_sequence_and_tag_with_labels(record.sequence, n)
else:
print >>sys.stderr, \
'...labeling to create groups of size {s}'.format(
s=args.group_size)
label = -1
g = 0
try:
outfp = open('{pref}_base_{g}.{ext}'.format(pref=output_pref,
g=g,
ext=extension
), 'wb')
for n, record in enumerate(screed.open(input_fastp)):
if n % args.group_size == 0:
label += 1
if label > g:
g = label
outfp = open('{pref}_base_{g}.{ext}'.format(
pref=output_pref, g=g,
ext=extension), 'wb')
if n % 50000 == 0:
print >>sys.stderr, \
'...consumed {n} sequences...'.format(n=n)
ht.consume_sequence_and_tag_with_labels(record.sequence,
label)
write_record(record, outfp)
except IOError as e:
print >>sys.stderr, '!! ERROR !!', e
print >>sys.stderr, '...error splitting input. exiting...'
except IOError as e:
print >>sys.stderr, '!! ERROR: !!', e
print >>sys.stderr, '...error consuming \
{i}. exiting...'.format(i=input_fastp)
print >>sys.stderr, 'done consuming input sequence. \
added {t} tags and {l} \
labels...'.format(t=ht.n_tags(), l=ht.n_labels())
label_dict = defaultdict(int)
label_number_dist = []
n_orphaned = 0
n_labeled = 0
n_mlabeled = 0
total_t = time.clock()
start_t = time.clock()
for read_file in args.input_files:
print >>sys.stderr, '** sweeping {read_file} for labels...'.format(
read_file=read_file)
file_t = 0.0
try:
read_fp = screed.open(read_file)
except IOError as error:
print >>sys.stderr, '!! ERROR: !!', error
print >>sys.stderr, '*** Could not open {fn}, skipping...'.format(
fn=read_file)
else:
for _, record in enumerate(read_fp):
if _ % 50000 == 0:
end_t = time.clock()
batch_t = end_t - start_t
file_t += batch_t
print >>sys.stderr, '\tswept {n} reads [{nc} labeled, \
{no} orphaned] \
** {sec}s ({sect}s total)' \
.format(n=_, nc=n_labeled,
no=n_orphaned,
sec=batch_t, sect=file_t)
start_t = time.clock()
seq = record.sequence
name = record.name
try:
labels = ht.sweep_label_neighborhood(seq, traversal_range)
except ValueError as e:
pass
else:
if hasattr(record, 'quality'):
seq_str = fmt_fastq(name, seq, record.quality, labels)
else:
seq_str = fmt_fasta(name, seq, labels)
label_number_dist.append(len(labels))
if labels:
n_labeled += 1
if len(labels) > 1:
output_buffer.queue(seq_str, 'multi')
n_mlabeled += 1
label_dict['multi'] += 1
else:
output_buffer.queue(seq_str, labels[0])
label_dict[labels[0]] += 1
else:
n_orphaned += 1
output_buffer.queue(seq_str, 'orphaned')
label_dict['orphaned'] += 1
print >>sys.stderr, '** End of file {fn}...'.format(fn=read_file)
output_buffer.flush_all()
read_fp.close()
# gotta output anything left in the buffers at the end!
print >>sys.stderr, '** End of run...'
output_buffer.flush_all()
total_t = time.clock() - total_t
if output_buffer.num_write_errors > 0 or output_buffer.num_file_errors > 0:
print >>sys.stderr, '! WARNING: Sweep finished with errors !'
print >>sys.stderr, '** {writee} reads not written'.format(
writee=output_buffer.num_write_errors)
print >>sys.stderr, '** {filee} errors opening files'.format(
filee=output_buffer.num_file_errors)
print >>sys.stderr, 'swept {n_reads} for labels...'.format(
n_reads=n_labeled + n_orphaned)
print >>sys.stderr, '...with {nc} labeled and {no} orphaned'.format(
nc=n_labeled, no=n_orphaned)
print >>sys.stderr, '...and {nmc} multilabeled'.format(nmc=n_mlabeled)
print >>sys.stderr, '** outputting label number distribution...'
fn = os.path.join(outdir, '{pref}.dist.txt'.format(pref=output_pref))
with open(fn, 'wb') as outfp:
for nc in label_number_dist:
outfp.write('{nc}\n'.format(nc=nc))
fn = os.path.join(outdir, '{pref}.counts.csv'.format(pref=output_pref))
print >>sys.stderr, '** outputting label read counts...'
with open(fn, 'wb') as outfp:
for k in label_dict:
outfp.write('{l},{c}\n'.format(l=k, c=label_dict[k]))
def main(): # pylint: disable=too-many-branches,too-many-statements
info("saturate-by-median.py", ["diginorm"])
args = get_parser().parse_args()
report_on_config(args)
report_fp = args.report
report_frequency = args.report_frequency
check_valid_file_exists(args.input_filenames)
check_space(args.input_filenames, False)
if args.savetable:
check_space_for_hashtable(args, "countgraph", False)
# list to save error files along with throwing exceptions
if args.force:
corrupt_files = []
if args.loadtable:
print("loading k-mer counting table from", args.loadtable)
htable = khmer.load_counting_hash(args.loadtable)
else:
print("making countgraph")
htable = create_countgraph(args)
total = 0
discarded = 0
for index, input_filename in enumerate(args.input_filenames):
total_acc = 0
discarded_acc = 0
try:
total_acc, discarded_acc = normalize_by_median(input_filename, htable, args, report_fp, report_frequency)
except IOError as err:
handle_error(err, input_filename)
if not args.force:
print("** Exiting!", file=sys.stderr)
sys.exit(1)
else:
print("*** Skipping error file, moving on...", file=sys.stderr)
corrupt_files.append(input_filename)
else:
if total_acc == 0 and discarded_acc == 0:
print("SKIPPED empty file", input_filename)
else:
total += total_acc
discarded += discarded_acc
print(
"DONE with {inp}; kept {kept} of {total} or {perc:2}%".format(
inp=input_filename,
kept=total - discarded,
total=total,
perc=int(100.0 - discarded / float(total) * 100.0),
)
)
if args.savetable:
print("Saving k-mer counting table through", input_filename)
print("...saving to", args.savetable)
htable.save(args.savetable)
# re: threshold, see Zhang et al.,
# http://arxiv.org/abs/1309.2975
fp_rate = khmer.calc_expected_collisions(htable, args.force, max_false_pos=0.8)
print("fp rate estimated to be {fpr:1.3f}".format(fpr=fp_rate))
if args.force and len(corrupt_files) > 0:
print("** WARNING: Finished with errors!", file=sys.stderr)
print("** I/O Errors occurred in the following files:", file=sys.stderr)
print("\t", " ".join(corrupt_files), file=sys.stderr)
