def main():
info('merge-partitions.py', ['graph'])
args = sanitize_epilog(get_parser()).parse_args()
output_file = args.graphbase + '.pmap.merged'
pmap_files = glob.glob(args.graphbase + '.subset.*.pmap')
print('loading %d pmap files (first one: %s)' %
(len(pmap_files), pmap_files[0]), file=sys.stderr)
ksize = args.ksize
nodegraph = khmer.Nodegraph(ksize, 1, 1)
for _ in pmap_files:
check_input_files(_, args.force)
check_space(pmap_files, args.force)
for pmap_file in pmap_files:
print('merging', pmap_file, file=sys.stderr)
nodegraph.merge_subset_from_disk(pmap_file)
print('saving merged to', output_file, file=sys.stderr)
nodegraph.save_partitionmap(output_file)
if args.remove_subsets:
print('removing pmap files', file=sys.stderr)
for pmap_file in pmap_files:
os.unlink(pmap_file)
def main():
info('count-median.py', ['diginorm'])
args = sanitize_epilog(get_parser()).parse_args()
htfile = args.countgraph
input_filename = args.input
output = args.output
output_filename = str(output)
infiles = [htfile, input_filename]
for infile in infiles:
check_input_files(infile, args.force)
check_space(infiles, args.force)
print('loading k-mer countgraph from', htfile, file=sys.stderr)
countgraph = khmer.load_countgraph(htfile)
ksize = countgraph.ksize()
print('writing to', output_filename, file=sys.stderr)
output = csv.writer(output)
# write headers:
output.writerow(['name', 'median', 'average', 'stddev', 'seqlen'])
for record in screed.open(input_filename):
seq = record.sequence.upper()
if 'N' in seq:
seq = seq.replace('N', 'A')
if ksize <= len(seq):
medn, ave, stdev = countgraph.get_median_count(seq)
ave, stdev = [round(x, 9) for x in (ave, stdev)]
output.writerow([record.name, medn, ave, stdev, len(seq)])
def main():
info('estimate_optimal_hash.py', ['counting'])
args = sanitize_epilog(get_parser()).parse_args()
N = args.N
if args.M:
M = args.M
result = optimal_size(N, M=M)
print("number of estimated distinct k-mers: ", N, file=sys.stderr)
print("size of memory available to use: ", M, file=sys.stderr)
print("optimal number of hash tables: ", result.num_htables,
file=sys.stderr)
print("optimal size of hash tables: ", result.htable_size,
file=sys.stderr)
print("estimated false positive rate: ", result.fp_rate,
file=sys.stderr)
print("estimated usage of memory: ", result.mem_use,
file=sys.stderr)
elif args.f:
f = args.f
result = optimal_size(N, f=f)
print("number of estimated distinct k-mers: ", N, file=sys.stderr)
print("desired maximum false positive rate: ", f, file=sys.stderr)
print("optimal number of hash tables: ", result.num_htables,
file=sys.stderr)
print("optimal size of hash tables: ", result.htable_size,
file=sys.stderr)
print("estimated false positive rate: ", result.fp_rate,
file=sys.stderr)
print("estimated usage of memory: ", result.mem_use,
file=sys.stderr)
else:
get_parser().error('No action requested, add -M (size of memory available to use) or -f (desired maximum false posotive rate)')
def main():
info('make-initial-stoptags.py', ['graph'])
args = sanitize_epilog(get_parser()).parse_args()
graphbase = args.graphbase
# @RamRS: This might need some more work
infiles = [graphbase, graphbase + '.tagset']
if args.stoptags:
infiles.append(args.stoptags)
for _ in infiles:
check_input_files(_, args.force)
print('loading nodegraph %s.pt' % graphbase, file=sys.stderr)
nodegraph = khmer.load_nodegraph(graphbase)
# do we want to load stop tags, and do they exist?
if args.stoptags:
print('loading stoptags from', args.stoptags, file=sys.stderr)
nodegraph.load_stop_tags(args.stoptags)
print('loading tagset %s.tagset...' % graphbase, file=sys.stderr)
nodegraph.load_tagset(graphbase + '.tagset')
counting = khmer_args.create_countgraph(args)
# divide up into SUBSET_SIZE fragments
divvy = nodegraph.divide_tags_into_subsets(args.subset_size)
# pick off the first one
if len(divvy) == 1:
start, end = 0, 0
else:
start, end = divvy[:2]
# partition!
print('doing pre-partitioning from', start, 'to', end, file=sys.stderr)
subset = nodegraph.do_subset_partition(start, end)
# now, repartition...
print('repartitioning to find HCKs.', file=sys.stderr)
nodegraph.repartition_largest_partition(subset, counting,
EXCURSION_DISTANCE,
EXCURSION_KMER_THRESHOLD,
EXCURSION_KMER_COUNT_THRESHOLD)
print('saving stop tags', file=sys.stderr)
nodegraph.save_stop_tags(graphbase + '.stoptags')
print('wrote to:', graphbase + '.stoptags', file=sys.stderr)
def main():
info('interleave-reads.py')
args = sanitize_epilog(get_parser()).parse_args()
check_input_files(args.left, args.force)
check_input_files(args.right, args.force)
check_space([args.left, args.right], args.force)
s1_file = args.left
s2_file = args.right
fail = False
print("Interleaving:\n\t%s\n\t%s" % (s1_file, s2_file), file=sys.stderr)
outfp = get_file_writer(args.output, args.gzip, args.bzip)
counter = 0
screed_iter_1 = screed.open(s1_file)
screed_iter_2 = screed.open(s2_file)
for read1, read2 in zip_longest(screed_iter_1, screed_iter_2):
if read1 is None or read2 is None:
print(("ERROR: Input files contain different number"
" of records."), file=sys.stderr)
sys.exit(1)
if counter % 100000 == 0:
print('...', counter, 'pairs', file=sys.stderr)
counter += 1
name1 = read1.name
if not check_is_left(name1):
name1 += '/1'
name2 = read2.name
if not check_is_right(name2):
name2 += '/2'
read1.name = name1
read2.name = name2
if not check_is_pair(read1, read2):
print("ERROR: This doesn't look like paired data! "
"%s %s" % (read1.name, read2.name), file=sys.stderr)
sys.exit(1)
write_record_pair(read1, read2, outfp)
print('final: interleaved %d pairs' % counter, file=sys.stderr)
print('output written to', describe_file_handle(outfp), file=sys.stderr)
def main():
"""Main function - run when executed as a script."""
parser = sanitize_epilog(get_parser())
args = parser.parse_args()
total_bp = 0
total_seqs = 0
statistics = []
for filename in args.filenames:
try:
bps, seqs = analyze_file(filename)
except (IOError, OSError, EOFError) as exc:
print('ERROR in opening %s:' % filename, file=sys.stderr)
print(' ', str(exc), file=sys.stderr)
continue
if seqs:
statistics.append((bps, seqs, filename))
avg = bps / float(seqs)
msg = '%d bps / %d seqs; %.1f average length -- %s' % (bps,
seqs,
avg,
filename)
print('... found', msg, file=sys.stderr)
else:
print('No sequences found in %s' % filename, file=sys.stderr)
if statistics:
if args.csv:
formatter = CsvFormatter(args.outfp)
else:
formatter = StdFormatter(args.outfp)
with StatisticsOutput(formatter) as out:
for stat in statistics:
out.append(*stat)
else:
print('No sequences found in %d files' %
len(args.filenames), file=args.outfp)
def main():
info('filter-stoptags.py', ['graph'])
args = sanitize_epilog(get_parser()).parse_args()
stoptags = args.stoptags_file
infiles = args.input_filenames
for _ in infiles:
check_input_files(_, args.force)
check_space(infiles, args.force)
print('loading stop tags, with K', args.ksize, file=sys.stderr)
nodegraph = khmer.Nodegraph(args.ksize, 1, 1)
nodegraph.load_stop_tags(stoptags)
def process_fn(record):
name = record['name']
seq = record['sequence']
if 'N' in seq:
return None, None
trim_seq, trim_at = nodegraph.trim_on_stoptags(seq)
if trim_at >= args.ksize:
return name, trim_seq
return None, None
# the filtering loop
for infile in infiles:
print('filtering', infile, file=sys.stderr)
outfile = os.path.basename(infile) + '.stopfilt'
outfp = open(outfile, 'w')
tsp = ThreadedSequenceProcessor(process_fn)
tsp.start(verbose_loader(infile), outfp)
print('output in', outfile, file=sys.stderr)
def main():
info('unique-kmers.py', ['SeqAn', 'hll'])
args = sanitize_epilog(get_parser()).parse_args()
total_hll = khmer.HLLCounter(args.error_rate, args.ksize)
report_fp = args.report
input_filename = None
for index, input_filename in enumerate(args.input_filenames):
hllcpp = khmer.HLLCounter(args.error_rate, args.ksize)
hllcpp.consume_fasta(input_filename,
stream_records=args.stream_records)
cardinality = hllcpp.estimate_cardinality()
print('Estimated number of unique {0}-mers in {1}: {2}'.format(
args.ksize, input_filename, cardinality),
file=sys.stderr)
if report_fp:
print(cardinality, args.ksize, '(total)', file=report_fp)
report_fp.flush()
total_hll.merge(hllcpp)
cardinality = total_hll.estimate_cardinality()
print('Total estimated number of unique {0}-mers: {1}'.format(
args.ksize, cardinality),
file=sys.stderr)
to_print = graphsize_args_report(cardinality, args.error_rate)
if args.diagnostics:
print(to_print, file=sys.stderr)
if report_fp:
print(cardinality, args.ksize, 'total', file=report_fp)
print(to_print, file=report_fp)
report_fp.flush()
def main():
info('filter-abund-single.py', ['counting', 'SeqAn'])
args = sanitize_epilog(get_parser()).parse_args()
check_input_files(args.datafile, args.force)
check_space([args.datafile], args.force)
if args.savegraph:
tablesize = calculate_graphsize(args, 'countgraph')
check_space_for_graph(args.savegraph, tablesize, args.force)
report_on_config(args)
print('making countgraph', file=sys.stderr)
graph = khmer_args.create_countgraph(args)
# first, load reads into graph
rparser = khmer.ReadParser(args.datafile)
threads = []
print('consuming input, round 1 --', args.datafile, file=sys.stderr)
for _ in range(args.threads):
cur_thread = \
threading.Thread(
target=graph.consume_fasta_with_reads_parser,
args=(rparser, )
)
threads.append(cur_thread)
cur_thread.start()
for _ in threads:
_.join()
print('Total number of unique k-mers: {0}'.format(
graph.n_unique_kmers()), file=sys.stderr)
fp_rate = khmer.calc_expected_collisions(graph, args.force)
print('fp rate estimated to be %1.3f' % fp_rate, file=sys.stderr)
# now, trim.
# the filtering function.
def process_fn(record):
name = record.name
seq = record.sequence
seqN = seq.replace('N', 'A')
_, trim_at = graph.trim_on_abundance(seqN, args.cutoff)
if trim_at >= args.ksize:
# be sure to not to change the 'N's in the trimmed sequence -
# so, return 'seq' and not 'seqN'.
return name, seq[:trim_at]
return None, None
# the filtering loop
print('filtering', args.datafile, file=sys.stderr)
outfile = os.path.basename(args.datafile) + '.abundfilt'
outfile = open(outfile, 'wb')
outfp = get_file_writer(outfile, args.gzip, args.bzip)
tsp = ThreadedSequenceProcessor(process_fn)
tsp.start(verbose_loader(args.datafile), outfp)
print('output in', outfile, file=sys.stderr)
if args.savegraph:
print('Saving k-mer countgraph filename',
args.savegraph, file=sys.stderr)
print('...saving to', args.savegraph, file=sys.stderr)
graph.save(args.savegraph)
print('wrote to: ', outfile, file=sys.stderr)
def main(): # pylint: disable=too-many-branches,too-many-statements
info('saturate-by-median.py', ['diginorm'])
parser = sanitize_epilog(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():
info('correct-reads.py', ['streaming'])
args = sanitize_epilog(get_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():
info("sample-reads-randomly.py")
args = sanitize_epilog(get_parser()).parse_args()
for _ in args.filenames:
check_input_files(_, args.force)
# seed the random number generator?
if args.random_seed:
random.seed(args.random_seed)
# bound n_samples
num_samples = max(args.num_samples, 1)
#
# Figure out what the output filename is going to be
if args.output_file:
output_filename = args.output_file.name
if num_samples > 1:
sys.stderr.write("Error: cannot specify -o with more than one sample.")
if not args.force:
print("NOTE: This can be overridden using the --force" " argument", file=sys.stderr)
sys.exit(1)
else:
filename = args.filenames[0]
if filename in ("/dev/stdin", "-"):
print("Accepting input from stdin; output filename must " "be provided with '-o'.", file=sys.stderr)
sys.exit(1)
output_filename = os.path.basename(filename) + ".subset"
if num_samples == 1:
print("Subsampling %d reads using reservoir sampling." % args.num_reads, file=sys.stderr)
print("Subsampled reads will be placed in %s" % output_filename, file=sys.stderr)
print("", file=sys.stderr)
else: # > 1
print(
"Subsampling %d reads, %d times," % (args.num_reads, num_samples),
" using reservoir sampling.",
file=sys.stderr,
)
print("Subsampled reads will be placed in %s.N" % output_filename, file=sys.stderr)
print("", file=sys.stderr)
reads = []
for n in range(num_samples):
reads.append([])
# read through all the sequences and load/resample the reservoir
for filename in args.filenames:
print("opening", filename, "for reading", file=sys.stderr)
screed_iter = screed.open(filename)
for count, (_, ispair, rcrd1, rcrd2) in enumerate(
broken_paired_reader(screed_iter, force_single=args.force_single)
):
if count % 10000 == 0:
print("...", count, "reads scanned", file=sys.stderr)
if count >= args.max_reads:
print("reached upper limit of %d reads" % args.max_reads, "(see -M); exiting", file=sys.stderr)
break
# collect first N reads
if count < args.num_reads:
for n in range(num_samples):
reads[n].append((rcrd1, rcrd2))
else:
assert len(reads[n]) <= count
# use reservoir sampling to replace reads at random
# see http://en.wikipedia.org/wiki/Reservoir_sampling
for n in range(num_samples):
guess = random.randint(1, count)
if guess <= args.num_reads:
reads[n][guess - 1] = (rcrd1, rcrd2)
# output all the subsampled reads:
if len(reads) == 1:
print("Writing %d sequences to %s" % (len(reads[0]), output_filename), file=sys.stderr)
output_file = args.output_file
if not output_file:
output_file = open(output_filename, "wb")
output_file = get_file_writer(output_file, args.gzip, args.bzip)
for records in reads[0]:
write_record(records[0], output_file)
if records[1] is not None:
write_record(records[1], output_file)
else:
for n in range(num_samples):
n_filename = output_filename + ".%d" % n
print("Writing %d sequences to %s" % (len(reads[n]), n_filename), file=sys.stderr)
output_file = get_file_writer(open(n_filename, "wb"), args.gzip, args.bzip)
for records in reads[n]:
write_record(records[0], output_file)
if records[1] is not None:
write_record(records[1], output_file)
def main(): # pylint: disable=too-many-locals,too-many-statements
info('do-partition.py', ['graph'])
args = sanitize_epilog(get_parser()).parse_args()
report_on_config(args, graphtype='nodegraph')
for infile in args.input_filenames:
check_input_files(infile, args.force)
check_space(args.input_filenames, args.force)
print('Saving k-mer nodegraph to %s' %
args.graphbase, file=sys.stderr)
print('Loading kmers from sequences in %s' %
repr(args.input_filenames), file=sys.stderr)
print('--', file=sys.stderr)
print('SUBSET SIZE', args.subset_size, file=sys.stderr)
print('N THREADS', args.threads, file=sys.stderr)
print('--', file=sys.stderr)
# load-graph.py
print('making nodegraph', file=sys.stderr)
nodegraph = khmer_args.create_nodegraph(args)
for _, filename in enumerate(args.input_filenames):
print('consuming input', filename, file=sys.stderr)
nodegraph.consume_fasta_and_tag(filename)
# 0.18 is ACTUAL MAX. Do not change.
fp_rate = \
khmer.calc_expected_collisions(
nodegraph, args.force, max_false_pos=.15)
print('fp rate estimated to be %1.3f' % fp_rate, file=sys.stderr)
# partition-graph
# do we want to exhaustively traverse the graph?
stop_big_traversals = args.no_big_traverse
if stop_big_traversals:
print('** This script brakes for lumps: ',
'stop_big_traversals is true.', file=sys.stderr)
else:
print('** Traverse all the things:',
' stop_big_traversals is false.', file=sys.stderr)
#
# now, partition!
#
# divide the tags up into subsets
divvy = nodegraph.divide_tags_into_subsets(int(args.subset_size))
n_subsets = len(divvy)
divvy.append(0)
# build a queue of tasks:
worker_q = queue.Queue()
# break up the subsets into a list of worker tasks
for _ in range(0, n_subsets):
start = divvy[_]
end = divvy[_ + 1]
worker_q.put((nodegraph, _, start, end))
print('enqueued %d subset tasks' % n_subsets, file=sys.stderr)
open('%s.info' % args.graphbase, 'w').write('%d subsets total\n'
% (n_subsets))
if n_subsets < args.threads:
args.threads = n_subsets
# start threads!
print('starting %d threads' % args.threads, file=sys.stderr)
print('---', file=sys.stderr)
threads = []
for _ in range(args.threads):
cur_thread = threading.Thread(target=worker,
args=(worker_q, args.graphbase,
stop_big_traversals))
threads.append(cur_thread)
cur_thread.start()
assert threading.active_count() == args.threads + 1
print('done starting threads', file=sys.stderr)
# wait for threads
for _ in threads:
_.join()
print('---', file=sys.stderr)
print('done making subsets! see %s.subset.*.pmap' %
(args.graphbase,), file=sys.stderr)
# merge-partitions
pmap_files = glob.glob(args.graphbase + '.subset.*.pmap')
print('loading %d pmap files (first one: %s)' %
(len(pmap_files), pmap_files[0]), file=sys.stderr)
nodegraph = khmer.Nodegraph(args.ksize, 1, 1)
for pmap_file in pmap_files:
print('merging', pmap_file, file=sys.stderr)
nodegraph.merge_subset_from_disk(pmap_file)
if args.remove_subsets:
print('removing pmap files', file=sys.stderr)
for pmap_file in pmap_files:
os.unlink(pmap_file)
# annotate-partitions
for infile in args.input_filenames:
print('outputting partitions for', infile, file=sys.stderr)
outfile = os.path.basename(infile) + '.part'
part_count = nodegraph.output_partitions(infile, outfile)
print('output %d partitions for %s' % (
part_count, infile), file=sys.stderr)
print('partitions are in', outfile, file=sys.stderr)
def main(): # pylint: disable=too-many-locals,too-many-branches
info('extract-partitions.py', ['graph'])
args = sanitize_epilog(get_parser()).parse_args()
distfilename = args.prefix + '.dist'
n_unassigned = 0
for infile in args.part_filenames:
check_input_files(infile, args.force)
check_space(args.part_filenames, args.force)
print('---', file=sys.stderr)
print('reading partitioned files:', repr(
args.part_filenames), file=sys.stderr)
if args.output_groups:
print('outputting to files named "%s.groupN.fa"' %
args.prefix, file=sys.stderr)
print('min reads to keep a partition:',
args.min_part_size, file=sys.stderr)
print('max size of a group file:', args.max_size, file=sys.stderr)
else:
print('NOT outputting groups! Beware!', file=sys.stderr)
if args.output_unassigned:
print('outputting unassigned reads to "%s.unassigned.fa"' %
args.prefix, file=sys.stderr)
print('partition size distribution will go to %s'
% distfilename, file=sys.stderr)
print('---', file=sys.stderr)
#
suffix = 'fa'
is_fastq = False
for index, read, pid in read_partition_file(args.part_filenames[0]):
if hasattr(read, 'quality'):
suffix = 'fq'
is_fastq = True
break
for filename in args.part_filenames:
for index, read, pid in read_partition_file(filename):
if is_fastq:
assert hasattr(read, 'quality'), \
"all input files must be FASTQ if the first one is"
else:
assert not hasattr(read, 'quality'), \
"all input files must be FASTA if the first one is"
break
if args.output_unassigned:
ofile = open('%s.unassigned.%s' % (args.prefix, suffix), 'wb')
unassigned_fp = get_file_writer(ofile, args.gzip, args.bzip)
count = {}
for filename in args.part_filenames:
for index, read, pid in read_partition_file(filename):
if index % 100000 == 0:
print('...', index, file=sys.stderr)
count[pid] = count.get(pid, 0) + 1
if pid == 0:
n_unassigned += 1
if args.output_unassigned:
write_record(read, unassigned_fp)
if args.output_unassigned:
unassigned_fp.close()
if 0 in count: # eliminate unpartitioned sequences
del count[0]
# develop histogram of partition sizes
dist = {}
for pid, size in list(count.items()):
dist[size] = dist.get(size, 0) + 1
# output histogram
distfp = open(distfilename, 'w')
total = 0
wtotal = 0
for counter, index in sorted(dist.items()):
total += index
wtotal += counter * index
distfp.write('%d %d %d %d\n' % (counter, index, total, wtotal))
distfp.close()
if not args.output_groups:
sys.exit(0)
# sort groups by size
divvy = sorted(list(count.items()), key=lambda y: y[1])
divvy = [y for y in divvy if y[1] > args.min_part_size]
# divvy up into different groups, based on having max_size sequences
# in each group.
total = 0
group = set()
group_n = 0
group_d = {}
for partition_id, n_reads in divvy:
group.add(partition_id)
total += n_reads
if total > args.max_size:
for partition_id in group:
group_d[partition_id] = group_n
# print 'group_d', partition_id, group_n
group_n += 1
group = set()
total = 0
if group:
for partition_id in group:
group_d[partition_id] = group_n
# print 'group_d', partition_id, group_n
group_n += 1
print('%d groups' % group_n, file=sys.stderr)
if group_n == 0:
print('nothing to output; exiting!', file=sys.stderr)
return
# open a bunch of output files for the different groups
group_fps = {}
for index in range(group_n):
fname = '%s.group%04d.%s' % (args.prefix, index, suffix)
group_fp = get_file_writer(open(fname, 'wb'), args.gzip,
args.bzip)
group_fps[index] = group_fp
# write 'em all out!
total_seqs = 0
part_seqs = 0
toosmall_parts = 0
for filename in args.part_filenames:
for index, read, partition_id in read_partition_file(filename):
total_seqs += 1
if index % 100000 == 0:
print('...x2', index, file=sys.stderr)
if partition_id == 0:
continue
try:
group_n = group_d[partition_id]
except KeyError:
assert count[partition_id] <= args.min_part_size
toosmall_parts += 1
continue
outfp = group_fps[group_n]
write_record(read, outfp)
part_seqs += 1
print('---', file=sys.stderr)
print('Of %d total seqs,' % total_seqs, file=sys.stderr)
print('extracted %d partitioned seqs into group files,' %
part_seqs, file=sys.stderr)
print('discarded %d sequences from small partitions (see -m),' %
toosmall_parts, file=sys.stderr)
print('and found %d unpartitioned sequences (see -U).' %
n_unassigned, file=sys.stderr)
print('', file=sys.stderr)
print('Created %d group files named %s.groupXXXX.%s' %
(len(group_fps),
args.prefix,
suffix), file=sys.stderr)
def main():
info('partition-graph.py', ['graph'])
args = sanitize_epilog(get_parser()).parse_args()
basename = args.basename
filenames = [basename, basename + '.tagset']
for _ in filenames:
check_input_files(_, args.force)
print('--', file=sys.stderr)
print('SUBSET SIZE', args.subset_size, file=sys.stderr)
print('N THREADS', args.threads, file=sys.stderr)
if args.stoptags:
print('stoptag file:', args.stoptags, file=sys.stderr)
print('--', file=sys.stderr)
print('loading nodegraph %s' % basename, file=sys.stderr)
nodegraph = khmer.load_nodegraph(basename)
nodegraph.load_tagset(basename + '.tagset')
# do we want to load stop tags, and do they exist?
if args.stoptags:
print('loading stoptags from', args.stoptags, file=sys.stderr)
nodegraph.load_stop_tags(args.stoptags)
# do we want to exhaustively traverse the graph?
stop_big_traversals = args.no_big_traverse
if stop_big_traversals:
print('** This script brakes for lumps:',
' stop_big_traversals is true.', file=sys.stderr)
else:
print('** Traverse all the things:',
' stop_big_traversals is false.', file=sys.stderr)
#
# now, partition!
#
# divide the tags up into subsets
divvy = nodegraph.divide_tags_into_subsets(int(args.subset_size))
n_subsets = len(divvy)
divvy.append(0)
# build a queue of tasks:
worker_q = queue.Queue()
# break up the subsets into a list of worker tasks
for _ in range(0, n_subsets):
start = divvy[_]
end = divvy[_ + 1]
worker_q.put((nodegraph, _, start, end))
print('enqueued %d subset tasks' % n_subsets, file=sys.stderr)
open('%s.info' % basename, 'w').write('%d subsets total\n' % (n_subsets))
n_threads = args.threads
if n_subsets < n_threads:
n_threads = n_subsets
# start threads!
print('starting %d threads' % n_threads, file=sys.stderr)
print('---', file=sys.stderr)
threads = []
for _ in range(n_threads):
cur_thrd = threading.Thread(target=worker, args=(worker_q, basename,
stop_big_traversals))
threads.append(cur_thrd)
cur_thrd.start()
print('done starting threads', file=sys.stderr)
# wait for threads
for _ in threads:
_.join()
print('---', file=sys.stderr)
print('done making subsets! see %s.subset.*.pmap' %
(basename,), file=sys.stderr)
def main():
info('trim-low-abund.py', ['streaming'])
parser = sanitize_epilog(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('filter-abund.py', ['counting'])
args = sanitize_epilog(get_parser()).parse_args()
check_input_files(args.input_graph, args.force)
infiles = args.input_filename
if ('-' in infiles or '/dev/stdin' in infiles) and not \
args.single_output_file:
print("Accepting input from stdin; output filename must "
"be provided with -o.", file=sys.stderr)
sys.exit(1)
for filename in infiles:
check_input_files(filename, args.force)
check_space(infiles, args.force)
print('loading countgraph:', args.input_graph,
file=sys.stderr)
countgraph = khmer.load_countgraph(args.input_graph)
ksize = countgraph.ksize()
print("K:", ksize, file=sys.stderr)
# the filtering function.
def process_fn(record):
name = record.name
seq = record.sequence
seqN = seq.replace('N', 'A')
if args.variable_coverage: # only trim when sequence has high enough C
med, _, _ = countgraph.get_median_count(seqN)
if med < args.normalize_to:
return name, seq
_, trim_at = countgraph.trim_on_abundance(seqN, args.cutoff)
if trim_at >= ksize:
# be sure to not to change the 'N's in the trimmed sequence -
# so, return 'seq' and not 'seqN'.
return name, seq[:trim_at]
return None, None
if args.single_output_file:
outfile = args.single_output_file.name
outfp = get_file_writer(outfile, args.gzip, args.bzip)
# the filtering loop
for infile in infiles:
print('filtering', infile, file=sys.stderr)
if args.single_output_file:
outfile = args.single_output_file.name
outfp = get_file_writer(args.single_output_file, args.gzip,
args.bzip)
else:
outfile = os.path.basename(infile) + '.abundfilt'
outfp = open(outfile, 'wb')
outfp = get_file_writer(outfp, args.gzip, args.bzip)
tsp = ThreadedSequenceProcessor(process_fn, n_workers=args.threads)
tsp.start(verbose_loader(infile), outfp)
print('output in', outfile, file=sys.stderr)
def main():
info('extract-paired-reads.py')
args = sanitize_epilog(get_parser()).parse_args()
infile = args.infile
check_input_files(infile, args.force)
check_space([infile], args.force)
# decide where to put output files - specific directory? or just default?
if infile in ('/dev/stdin', '-'):
if not (args.output_paired and args.output_single):
print("Accepting input from stdin; output filenames must be "
"provided.", file=sys.stderr)
sys.exit(1)
elif args.output_dir:
if not os.path.exists(args.output_dir):
os.makedirs(args.output_dir)
out1 = args.output_dir + '/' + os.path.basename(infile) + '.se'
out2 = args.output_dir + '/' + os.path.basename(infile) + '.pe'
else:
out1 = os.path.basename(infile) + '.se'
out2 = os.path.basename(infile) + '.pe'
# OVERRIDE default output file locations with -p, -s
if args.output_paired:
paired_fp = get_file_writer(args.output_paired, args.gzip, args.bzip)
out2 = paired_fp.name
else:
# Don't override, just open the default filename from above
paired_fp = get_file_writer(open(out2, 'wb'), args.gzip, args.bzip)
if args.output_single:
single_fp = get_file_writer(args.output_single, args.gzip, args.bzip)
out1 = args.output_single.name
else:
# Don't override, just open the default filename from above
single_fp = get_file_writer(open(out1, 'wb'), args.gzip, args.bzip)
print('reading file "%s"' % infile, file=sys.stderr)
print('outputting interleaved pairs to "%s"' % out2, file=sys.stderr)
print('outputting orphans to "%s"' % out1, file=sys.stderr)
n_pe = 0
n_se = 0
screed_iter = screed.open(infile)
for index, is_pair, read1, read2 in broken_paired_reader(screed_iter):
if index % 100000 == 0 and index > 0:
print('...', index, file=sys.stderr)
if is_pair:
write_record_pair(read1, read2, paired_fp)
n_pe += 1
else:
write_record(read1, single_fp)
n_se += 1
single_fp.close()
paired_fp.close()
if n_pe == 0:
raise Exception("no paired reads!? check file formats...")
print('DONE; read %d sequences,'
' %d pairs and %d singletons' %
(n_pe * 2 + n_se, n_pe, n_se), file=sys.stderr)
print('wrote to: %s and %s' % (out2, out1),
file=sys.stderr)
def main():
info('load-into-counting.py', ['counting', 'SeqAn'])
args = sanitize_epilog(get_parser()).parse_args()
report_on_config(args)
base = args.output_countgraph_filename
filenames = args.input_sequence_filename
for name in args.input_sequence_filename:
check_input_files(name, args.force)
tablesize = calculate_graphsize(args, 'countgraph')
check_space_for_graph(args.output_countgraph_filename, tablesize,
args.force)
check_file_writable(base)
check_file_writable(base + ".info")
print('Saving k-mer countgraph to %s' % base, file=sys.stderr)
print('Loading kmers from sequences in %s' %
repr(filenames), file=sys.stderr)
# clobber the '.info' file now, as we always open in append mode below
if os.path.exists(base + '.info'):
os.remove(base + '.info')
print('making countgraph', file=sys.stderr)
countgraph = khmer_args.create_countgraph(args)
countgraph.set_use_bigcount(args.bigcount)
filename = None
total_num_reads = 0
for index, filename in enumerate(filenames):
rparser = khmer.ReadParser(filename)
threads = []
print('consuming input', filename, file=sys.stderr)
for _ in range(args.threads):
cur_thrd = \
threading.Thread(
target=countgraph.consume_fasta_with_reads_parser,
args=(rparser, )
)
threads.append(cur_thrd)
cur_thrd.start()
for thread in threads:
thread.join()
if index > 0 and index % 10 == 0:
tablesize = calculate_graphsize(args, 'countgraph')
check_space_for_graph(base, tablesize, args.force)
print('mid-save', base, file=sys.stderr)
countgraph.save(base)
with open(base + '.info', 'a') as info_fh:
print('through', filename, file=info_fh)
total_num_reads += rparser.num_reads
n_kmers = countgraph.n_unique_kmers()
print('Total number of unique k-mers:', n_kmers, file=sys.stderr)
with open(base + '.info', 'a') as info_fp:
print('Total number of unique k-mers:', n_kmers, file=info_fp)
print('saving', base, file=sys.stderr)
countgraph.save(base)
# Change max_false_pos=0.2 only if you really grok it. HINT: You don't
fp_rate = \
khmer.calc_expected_collisions(
countgraph, args.force, max_false_pos=.2)
with open(base + '.info', 'a') as info_fp:
print('fp rate estimated to be %1.3f\n' % fp_rate, file=info_fp)
if args.summary_info:
mr_fmt = args.summary_info.lower()
mr_file = base + '.info.' + mr_fmt
print("Writing summmary info to", mr_file, file=sys.stderr)
with open(mr_file, 'w') as mr_fh:
if mr_fmt == 'json':
mr_data = {
"ht_name": os.path.basename(base),
"fpr": fp_rate,
"num_kmers": n_kmers,
"files": filenames,
"mrinfo_version": "0.2.0",
"num_reads": total_num_reads,
}
json.dump(mr_data, mr_fh)
mr_fh.write('\n')
elif mr_fmt == 'tsv':
mr_fh.write("ht_name\tfpr\tnum_kmers\tnum_reads\tfiles\n")
vals = [
os.path.basename(base),
"{:1.3f}".format(fp_rate),
str(n_kmers),
str(total_num_reads),
";".join(filenames),
]
mr_fh.write("\t".join(vals) + "\n")
print('fp rate estimated to be %1.3f' % fp_rate, file=sys.stderr)
print('DONE.', file=sys.stderr)
print('wrote to:', base + '.info', file=sys.stderr)
def main():
#info('sweep-files.py', ['sweep'])
parser = sanitize_epilog(get_parser())
args = parser.parse_args()
if args.max_tablesize < MIN_HSIZE:
args.max_tablesize = MIN_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
outputs = {}
# Consume the database files and assign each a unique label in the
# de Bruin graph; open a file and output queue for each file as well.
ht = khmer.GraphLabels(K, HT_SIZE, N_HT)
try:
print('consuming and labeling input sequences...', file=sys.stderr)
for i, dbfile in enumerate(args.db):
name = args.output_prefix + os.path.basename(dbfile)
outfp = open(os.path.join(args.outdir, name) + '.sweep', 'wb')
outq = IODeque(args.max_queue_size, outfp)
outputs[i] = outq
for n, record in enumerate(screed.open(dbfile)):
if n % 50000 == 0:
print('...consumed {n} sequences...'.format(n=n), file=sys.stderr)
ht.consume_sequence_and_tag_with_labels(record.sequence, i)
except (IOError, OSError) as e:
print('!! ERROR: !!', e, file=sys.stderr)
print('...error setting up outputs. exiting...', file=sys.stderr)
print('done consuming input sequence. \
added {t} tags and {l} labels...' \
.format(t=ht.n_tags(), l=ht.n_labels()), file=sys.stderr)
n_orphaned = 0
n_labeled = 0
n_mlabeled = 0
# Iterate through all the reads and check for the labels with which they
# intersect. Queue to the corresponding label when found.
for read_file in args.query:
print('** sweeping {read_file} for labels...'.format(
read_file=read_file), file=sys.stderr)
try:
read_fp = screed.open(read_file)
except IOError as error:
print('!! ERROR: !!', error, file=sys.stderr)
print('*** Could not open {fn}, skipping...'.format(
fn=read_file), file=sys.stderr)
else:
for n, record in enumerate(read_fp):
if n % 50000 == 0 and n > 0:
print('\tswept {n} reads [{nc} labeled, {no} orphaned]' \
.format(n=n, nc=n_labeled,
no=n_orphaned), file=sys.stderr)
seq = record.sequence
try:
labels = ht.sweep_label_neighborhood(seq, traversal_range)
except ValueError as e:
# sweep_label_neighborhood throws a ValueError when
# len(seq) < K. just catch it and move on.
pass
else:
if labels:
n_labeled += 1
if len(labels) > 1:
n_mlabeled += 1
for label in labels:
outputs[label].append(record)
else:
n_orphaned += 1
print('** End of file {fn}...'.format(fn=read_file), file=sys.stderr)
read_fp.close()
# gotta output anything left in the buffers at the end!
print('** End of run...', file=sys.stderr)
for q in list(outputs.values()):
q.clear()
print('swept {n_reads}...'.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)
def main():
info('split-paired-reads.py')
args = sanitize_epilog(get_parser()).parse_args()
infile = args.infile
filenames = [infile]
check_input_files(infile, args.force)
check_space(filenames, args.force)
basename = os.path.basename(infile)
# decide where to put output files - specific directory? or just default?
if infile in ('/dev/stdin', '-'):
if not (args.output_first and args.output_second):
print("Accepting input from stdin; "
"output filenames must be provided.", file=sys.stderr)
sys.exit(1)
elif args.output_directory:
if not os.path.exists(args.output_directory):
os.makedirs(args.output_directory)
out1 = os.path.join(args.output_directory, basename + '.1')
out2 = os.path.join(args.output_directory, basename + '.2')
else:
out1 = basename + '.1'
out2 = basename + '.2'
# OVERRIDE output file locations with -1, -2
if args.output_first:
fp_out1 = get_file_writer(args.output_first, args.gzip, args.bzip)
out1 = fp_out1.name
else:
# Use default filename created above
fp_out1 = get_file_writer(open(out1, 'wb'), args.gzip, args.bzip)
if args.output_second:
fp_out2 = get_file_writer(args.output_second, args.gzip, args.bzip)
out2 = fp_out2.name
else:
# Use default filename created above
fp_out2 = get_file_writer(open(out2, 'wb'), args.gzip, args.bzip)
# put orphaned reads here, if -0!
if args.output_orphaned:
fp_out0 = get_file_writer(args.output_orphaned, args.gzip, args.bzip)
out0 = describe_file_handle(args.output_orphaned)
counter1 = 0
counter2 = 0
counter3 = 0
index = None
screed_iter = screed.open(infile)
# walk through all the reads in broken-paired mode.
paired_iter = broken_paired_reader(screed_iter,
require_paired=not args.output_orphaned)
try:
for index, is_pair, record1, record2 in paired_iter:
if index % 10000 == 0:
print('...', index, file=sys.stderr)
if is_pair:
write_record(record1, fp_out1)
counter1 += 1
write_record(record2, fp_out2)
counter2 += 1
elif args.output_orphaned:
write_record(record1, fp_out0)
counter3 += 1
except UnpairedReadsError as e:
print("Unpaired reads found starting at {name}; exiting".format(
name=e.r1.name), file=sys.stderr)
sys.exit(1)
print("DONE; split %d sequences (%d left, %d right, %d orphans)" %
(counter1 + counter2, counter1, counter2, counter3), file=sys.stderr)
print("/1 reads in %s" % out1, file=sys.stderr)
print("/2 reads in %s" % out2, file=sys.stderr)
if args.output_orphaned:
print("orphans in %s" % out0, file=sys.stderr)
def main(): # pylint: disable=too-many-branches,too-many-statements
parser = sanitize_epilog(get_parser())
parser = get_parser()
args = parser.parse_args()
configure_logging(args.quiet)
info('normalize-by-median.py', ['diginorm'])
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:
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 = 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 is_block(outfp):
outfp.close()
# finished - print out some diagnostics.
log_info('Total number of unique k-mers: {umers}',
umers=countgraph.n_unique_kmers())
if args.savegraph:
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-locals,too-many-branches
info('abundance-dist-single.py', ['counting', 'SeqAn'])
args = sanitize_epilog(get_parser()).parse_args()
report_on_config(args)
check_input_files(args.input_sequence_filename, args.force)
if args.savegraph:
graphsize = calculate_graphsize(args, 'countgraph')
check_space_for_graph(args.savegraph, graphsize, args.force)
if (not args.squash_output and
os.path.exists(args.output_histogram_filename)):
print('ERROR: %s exists; not squashing.' %
args.output_histogram_filename, file=sys.stderr)
sys.exit(1)
else:
hist_fp = open(args.output_histogram_filename, 'w')
hist_fp_csv = csv.writer(hist_fp)
# write headers:
hist_fp_csv.writerow(['abundance', 'count', 'cumulative',
'cumulative_fraction'])
print('making countgraph', file=sys.stderr)
countgraph = khmer_args.create_countgraph(args, multiplier=1.1)
countgraph.set_use_bigcount(args.bigcount)
print('building k-mer tracking graph', file=sys.stderr)
tracking = khmer_args.create_nodegraph(args, multiplier=1.1)
print('kmer_size:', countgraph.ksize(), file=sys.stderr)
print('k-mer countgraph sizes:',
countgraph.hashsizes(), file=sys.stderr)
print('outputting to', args.output_histogram_filename, file=sys.stderr)
# start loading
rparser = khmer.ReadParser(args.input_sequence_filename)
threads = []
print('consuming input, round 1 --',
args.input_sequence_filename, file=sys.stderr)
for _ in range(args.threads):
thread = \
threading.Thread(
target=countgraph.consume_fasta_with_reads_parser,
args=(rparser, )
)
threads.append(thread)
thread.start()
for thread in threads:
thread.join()
print('Total number of unique k-mers: {0}'.format(
countgraph.n_unique_kmers()), file=sys.stderr)
abundance_lists = []
def __do_abundance_dist__(read_parser):
abundances = countgraph.abundance_distribution_with_reads_parser(
read_parser, tracking)
abundance_lists.append(abundances)
print('preparing hist from %s...' %
args.input_sequence_filename, file=sys.stderr)
rparser = khmer.ReadParser(args.input_sequence_filename)
threads = []
print('consuming input, round 2 --',
args.input_sequence_filename, file=sys.stderr)
for _ in range(args.threads):
thread = \
threading.Thread(
target=__do_abundance_dist__,
args=(rparser, )
)
threads.append(thread)
thread.start()
for thread in threads:
thread.join()
assert len(abundance_lists) == args.threads, len(abundance_lists)
abundance = {}
for abundance_list in abundance_lists:
for i, count in enumerate(abundance_list):
abundance[i] = abundance.get(i, 0) + count
total = sum(abundance.values())
if 0 == total:
print("ERROR: abundance distribution is uniformly zero; "
"nothing to report.", file=sys.stderr)
print(
"\tPlease verify that the input files are valid.", file=sys.stderr)
sys.exit(1)
sofar = 0
for _, i in sorted(abundance.items()):
if i == 0 and not args.output_zero:
continue
sofar += i
frac = sofar / float(total)
hist_fp_csv.writerow([_, i, sofar, round(frac, 3)])
if sofar == total:
break
if args.savegraph:
print('Saving k-mer countgraph ', args.savegraph, file=sys.stderr)
print('...saving to', args.savegraph, file=sys.stderr)
countgraph.save(args.savegraph)
print('wrote to: ' + args.output_histogram_filename, file=sys.stderr)
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('collect-reads.py', ['counting'])
args = sanitize_epilog(get_parser()).parse_args()
report_on_config(args)
base = args.output_countgraph_filename
filenames = args.input_sequence_filename
for name in args.input_sequence_filename:
check_input_files(name, False)
check_space(args.input_sequence_filename, False)
tablesize = calculate_graphsize(args, 'countgraph')
check_space_for_graph(args.output_countgraph_filename, tablesize,
False)
print('Saving k-mer countgraph to %s' % base)
print('Loading sequences from %s' % repr(filenames))
if args.output:
print('Outputting sequences to', args.output)
print('making countgraph', file=sys.stderr)
htable = khmer_args.create_countgraph(args)
htable.set_use_bigcount(args.bigcount)
total_coverage = 0.
n = 0
for index, filename in enumerate(filenames):
for record in screed.open(filename):
seq = record.sequence.upper()
if 'N' in seq:
seq = seq.replace('N', 'A')
try:
med, _, _ = htable.get_median_count(seq)
except ValueError:
continue
total_coverage += med
n += 1
if total_coverage / float(n) > args.coverage:
print('reached target average coverage:', \
total_coverage / float(n))
break
htable.consume(seq)
if args.output:
args.output.write(output_single(record))
if n % 100000 == 0:
print('...', index, filename, n, total_coverage / float(n))
if total_coverage / float(n) > args.coverage:
break
print('Collected %d reads' % (n,))
if args.report_total_kmers:
print('Total number of k-mers: {0}'.format(
htable.n_occupied()), file=sys.stderr)
print('saving', base)
htable.save(base)
info_fp = open(base + '.info', 'w')
info_fp.write('through end: %s\n' % filenames[-1])
# Change 0.2 only if you really grok it. HINT: You don't.
fp_rate = khmer.calc_expected_collisions(htable, False,
max_false_pos=.2)
print('fp rate estimated to be %1.3f' % fp_rate)
print('fp rate estimated to be %1.3f' % fp_rate, file=info_fp)
print('DONE.')
