def iterate_double_fasta ( fn1, fn2 ):
iterator = FastaIterator.iterate_together( fn1, fn2 )
for seq1, seq2 in iterator:
yield AlignedPairs.UnalignedPair(
token1 = seq1.title,
sequence1 = seq1.sequence,
token2 = seq2.title,
sequence2 = seq2.sequence )
def main(argv=None):
if argv is None:
argv = sys.argv
parser = E.OptionParser(version="%prog version",
usage=globals()["__doc__"])
parser.add_option(
"--output-quality-format", dest="q_format", type="int",
help="sequence quality format, e.g 33 = +33/Sanger"
"[default=%default].")
parser.add_option(
"--output-paired-end", dest="paired", action="store_true",
help="generate paired end reads [default = %default].")
parser.add_option(
"--insert-length-mean", dest="insert_mean", type="float",
help="mean insert length [default = %default].")
parser.add_option(
"--insert-length-sd", dest="insert_sd", type="float",
help="insert length standard deviation [default = %default].")
parser.add_option(
"--counts-method", dest="counts_method", type="choice",
choices=("reads", "copies"),
help="simulate a ground truth number of reads per entry or"
"copies per entry [default = %default].")
parser.add_option(
"--counts-min", dest="counts_min", type="float",
help="minimum number of reads/read pairs per fasta entry"
"or copies per entry [default = %default].")
parser.add_option(
"--counts-max", dest="counts_max", type="float",
help="maximum number of reads/read pairs per fasta entry "
"or copies per entry [default = %default].")
parser.add_option(
"--output-read-length", dest="read_length", type="int",
help="read length [default = %default].")
parser.add_option(
"--sequence-error-phred", dest="phred", type="int",
help="phred quality score [default = %default].")
parser.add_option(
"--output-counts", dest="output_counts", type="string",
help="name for counts outfile [default=%default].")
parser.add_option(
"--output-fastq2", dest="fastq2_out", type="string",
help="filename for second fastq outfile [default=%default].")
parser.add_option(
"--premrna-fraction", dest="premrna_fraction", type="float",
help="the fraction of reads to simulate from pre-mRNA"
"[default= % default].")
parser.add_option(
"--infile-premrna-fasta", dest="premrna_fasta", type="string",
help="filename for pre-mRNA fasta[default=%default].")
parser.set_defaults(
q_format=33,
paired=False,
insert_mean=0,
insert_sd=1,
counts_method="reads",
counts_min=1,
counts_max=1,
read_length=50,
fastq2_out=None,
output_counts=None,
phred=30,
premrna_fraction=0,
premrna_fasta=None
)
(options, args) = E.Start(parser)
if options.paired:
assert options.fastq2_out, ("must specify a second fastq outfile for "
"paired end (--output-fastq2)")
outf2 = IOTools.openFile(options.fastq2_out, "w")
if options.premrna_fraction:
assert options.premrna_fasta, ("must specfify the location of the"
"fasta file for the pre-mRNA")
# the sequence quality string will always be the same so define here
sequence_quality = chr(options.q_format + options.phred)
qual = "".join([sequence_quality] * options.read_length)
if options.premrna_fraction:
iterator = FastaIterator.iterate_together(
options.stdin, IOTools.openFile(options.premrna_fasta))
else:
iterator = FastaIterator.FastaIterator(options.stdin)
# set a cut off of twice the read/pair length for short entries
if options.paired:
minimum_entry_length = (
2 * ((options.read_length * 2) + options.insert_mean))
else:
minimum_entry_length = 2 * options.read_length
c = collections.Counter()
counts = collections.Counter()
copies = collections.Counter()
for f_entry in iterator:
if options.premrna_fraction:
assert getTitle(f_entry[0]) == getTitle(f_entry[1]), (
"entry ids do not match: %s != %s" % (
f_entry[0].title, f_entry[1].title))
entry = f_entry[0]
pre_entry = f_entry[1]
else:
entry = f_entry
# reject short fasta entries
if len(entry.sequence) < minimum_entry_length:
E.info("skipping short transcript: %s length=%i"
% (entry.title, len(entry.sequence)))
c['skipped'] += 1
continue
else:
c['not_skipped'] += 1
if options.paired:
fragment_length = (
(2 * options.read_length) + options.insert_mean)
else:
fragment_length = options.read_length
reads_per_entry = float(len(entry.sequence)) / fragment_length
if options.counts_method == "reads":
n_reads = random.randint(options.counts_min,
options.counts_max + 1)
n_copies = float(n_reads) / reads_per_entry
if options.premrna_fraction:
n_reads_pre = int(round(n_reads * options.premrna_fraction))
elif options.counts_method == "copies":
# random float [0-1]
rand = np.random.random_sample()
n_copies = (options.counts_min +
(rand * (options.counts_max - options.counts_min)))
n_reads = int(round(n_copies * reads_per_entry, 0))
# as n_reads must be rounded to int, need to redefine n_copies
n_copies = float(n_reads) / reads_per_entry
if options.premrna_fraction:
reads_per_pre_entry = (float(len(pre_entry.sequence)) /
fragment_length)
n_copies_pre = n_copies * options.premrna_fraction
n_reads_pre = int(round(n_copies_pre * reads_per_pre_entry, 0))
# as n_reads_pre must be rounded to int, need to
# redefine n_copies_pre
n_copies_pre = float(n_reads_pre) / reads_per_pre_entry
entry_id = getTitle(entry)
counts[entry_id] = n_reads
copies[entry_id] = n_copies
if "N" in entry.sequence.upper():
E.warn("fasta entry %s contains unknown bases ('N')" % entry_id)
for i in range(0, n_reads):
read = generateRead(entry=entry.sequence.upper(),
read_length=options.read_length,
error_rate=options.phred,
paired=options.paired,
insert_mean=options.insert_mean,
insert_sd=options.insert_sd)
if options.paired:
r1, r2 = read
h1 = "@%s_%i/1" % (entry_id, i)
h2 = "@%s_%i/2" % (entry_id, i)
options.stdout.write("\n".join((h1, r1, "+", qual)) + "\n")
outf2.write("\n".join((h2, r2, "+", qual)) + "\n")
else:
h = "@%s_%i/1" % (entry_id, i)
options.stdout.write("\n".join((h, read, "+", qual)) + "\n")
if options.premrna_fraction:
c['pre_counts'] += n_reads_pre
c['pre_copies'] += n_copies_pre
for i in range(0, n_reads_pre):
read = generateRead(entry=pre_entry.sequence.upper(),
read_length=options.read_length,
error_rate=options.phred,
paired=options.paired,
insert_mean=options.insert_mean,
insert_sd=options.insert_sd)
if options.paired:
r1, r2 = read
h1 = "@%s_pre-mRNA_%i/1" % (entry_id, i)
h2 = "@%s_pre-mRNA_%i/2" % (entry_id, i)
options.stdout.write("\n".join((h1, r1, "+", qual)) + "\n")
outf2.write("\n".join((h2, r2, "+", qual)) + "\n")
else:
h = "@%s_pre-mRNA_%i/1" % (entry_id, i)
options.stdout.write("\n".join((h, read, "+", qual)) + "\n")
if options.paired:
outf2.close()
with IOTools.openFile(options.output_counts, "w") as counts_out:
counts_out.write("%s\n" % "\t".join(("id", "read_count", "tpm")))
sum_copies = sum(copies.values())
sum_counts = sum(counts.values())
for entry_id, count in counts.items():
tpm = 1000000 * (float(copies[entry_id]) / sum_copies)
counts_out.write(
"%s\n" % "\t".join(map(str, (entry_id, count, tpm))))
E.info("Reads simulated for %i fasta entries, %i entries skipped"
% (c['not_skipped'], c['skipped']))
E.info("Simulated: %i reads (%i mRNA, %i pre-mRNA), "
"%f transcripts (%f mRNA, %f pre-mRNA)" % (
sum_counts + c['pre_counts'], sum_counts, c['pre_counts'],
sum_copies + c['pre_copies'], sum_copies, c['pre_copies']))
E.Stop()
def main(argv=None):
if argv is None:
argv = sys.argv
parser = E.OptionParser(version="%prog version",
usage=globals()["__doc__"])
parser.add_option("--output-quality-format",
dest="q_format",
type="int",
help="sequence quality format, e.g 33 = +33/Sanger"
"[default=%default].")
parser.add_option("--output-paired-end",
dest="paired",
action="store_true",
help="generate paired end reads [default = %default].")
parser.add_option("--insert-length-mean",
dest="insert_mean",
type="float",
help="mean insert length [default = %default].")
parser.add_option(
"--insert-length-sd",
dest="insert_sd",
type="float",
help="insert length standard deviation [default = %default].")
parser.add_option(
"--counts-method",
dest="counts_method",
type="choice",
choices=("reads", "copies"),
help="simulate a ground truth number of reads per entry or"
"copies per entry [default = %default].")
parser.add_option("--counts-min",
dest="counts_min",
type="float",
help="minimum number of reads/read pairs per fasta entry"
"or copies per entry [default = %default].")
parser.add_option(
"--counts-max",
dest="counts_max",
type="float",
help="maximum number of reads/read pairs per fasta entry "
"or copies per entry [default = %default].")
parser.add_option("--output-read-length",
dest="read_length",
type="int",
help="read length [default = %default].")
parser.add_option("--sequence-error-phred",
dest="phred",
type="int",
help="phred quality score [default = %default].")
parser.add_option("--output-counts",
dest="output_counts",
type="string",
help="name for counts outfile [default=%default].")
parser.add_option(
"--output-fastq2",
dest="fastq2_out",
type="string",
help="filename for second fastq outfile [default=%default].")
parser.add_option("--premrna-fraction",
dest="premrna_fraction",
type="float",
help="the fraction of reads to simulate from pre-mRNA"
"[default= % default].")
parser.add_option("--infile-premrna-fasta",
dest="premrna_fasta",
type="string",
help="filename for pre-mRNA fasta[default=%default].")
parser.set_defaults(q_format=33,
paired=False,
insert_mean=0,
insert_sd=1,
counts_method="reads",
counts_min=1,
counts_max=1,
read_length=50,
fastq2_out=None,
output_counts=None,
phred=30,
premrna_fraction=0,
premrna_fasta=None)
(options, args) = E.Start(parser)
if options.paired:
assert options.fastq2_out, ("must specify a second fastq outfile for "
"paired end (--output-fastq2)")
outf2 = IOTools.openFile(options.fastq2_out, "w")
if options.premrna_fraction:
assert options.premrna_fasta, ("must specfify the location of the"
"fasta file for the pre-mRNA")
# the sequence quality string will always be the same so define here
sequence_quality = chr(options.q_format + options.phred)
qual = "".join([sequence_quality] * options.read_length)
if options.premrna_fraction:
iterator = FastaIterator.iterate_together(
options.stdin, IOTools.openFile(options.premrna_fasta))
else:
iterator = FastaIterator.FastaIterator(options.stdin)
# set a cut off of twice the read/pair length for short entries
if options.paired:
minimum_entry_length = (
2 * ((options.read_length * 2) + options.insert_mean))
else:
minimum_entry_length = 2 * options.read_length
c = collections.Counter()
counts = collections.Counter()
copies = collections.Counter()
for f_entry in iterator:
if options.premrna_fraction:
assert getTitle(f_entry[0]) == getTitle(
f_entry[1]), ("entry ids do not match: %s != %s" %
(f_entry[0].title, f_entry[1].title))
entry = f_entry[0]
pre_entry = f_entry[1]
else:
entry = f_entry
# reject short fasta entries
if len(entry.sequence) < minimum_entry_length:
E.info("skipping short transcript: %s length=%i" %
(entry.title, len(entry.sequence)))
c['skipped'] += 1
continue
else:
c['not_skipped'] += 1
if options.paired:
fragment_length = ((2 * options.read_length) + options.insert_mean)
else:
fragment_length = options.read_length
reads_per_entry = float(len(entry.sequence)) / fragment_length
if options.counts_method == "reads":
n_reads = random.randint(options.counts_min,
options.counts_max + 1)
n_copies = float(n_reads) / reads_per_entry
if options.premrna_fraction:
n_reads_pre = int(round(n_reads * options.premrna_fraction))
elif options.counts_method == "copies":
# random float [0-1]
rand = np.random.random_sample()
n_copies = (options.counts_min +
(rand * (options.counts_max - options.counts_min)))
n_reads = int(round(n_copies * reads_per_entry, 0))
# as n_reads must be rounded to int, need to redefine n_copies
n_copies = float(n_reads) / reads_per_entry
if options.premrna_fraction:
reads_per_pre_entry = (float(len(pre_entry.sequence)) /
fragment_length)
n_copies_pre = n_copies * options.premrna_fraction
n_reads_pre = int(round(n_copies_pre * reads_per_pre_entry, 0))
# as n_reads_pre must be rounded to int, need to
# redefine n_copies_pre
n_copies_pre = float(n_reads_pre) / reads_per_pre_entry
entry_id = getTitle(entry)
counts[entry_id] = n_reads
copies[entry_id] = n_copies
if "N" in entry.sequence.upper():
E.warn("fasta entry %s contains unknown bases ('N')" % entry_id)
for i in range(0, n_reads):
read = generateRead(entry=entry.sequence.upper(),
read_length=options.read_length,
error_rate=options.phred,
paired=options.paired,
insert_mean=options.insert_mean,
insert_sd=options.insert_sd)
if options.paired:
r1, r2 = read
h1 = "@%s_%i/1" % (entry_id, i)
h2 = "@%s_%i/2" % (entry_id, i)
options.stdout.write("\n".join((h1, r1, "+", qual)) + "\n")
outf2.write("\n".join((h2, r2, "+", qual)) + "\n")
else:
h = "@%s_%i/1" % (entry_id, i)
options.stdout.write("\n".join((h, read, "+", qual)) + "\n")
if options.premrna_fraction:
c['pre_counts'] += n_reads_pre
c['pre_copies'] += n_copies_pre
for i in range(0, n_reads_pre):
read = generateRead(entry=pre_entry.sequence.upper(),
read_length=options.read_length,
error_rate=options.phred,
paired=options.paired,
insert_mean=options.insert_mean,
insert_sd=options.insert_sd)
if options.paired:
r1, r2 = read
h1 = "@%s_pre-mRNA_%i/1" % (entry_id, i)
h2 = "@%s_pre-mRNA_%i/2" % (entry_id, i)
options.stdout.write("\n".join((h1, r1, "+", qual)) + "\n")
outf2.write("\n".join((h2, r2, "+", qual)) + "\n")
else:
h = "@%s_pre-mRNA_%i/1" % (entry_id, i)
options.stdout.write("\n".join((h, read, "+", qual)) +
"\n")
if options.paired:
outf2.close()
with IOTools.openFile(options.output_counts, "w") as counts_out:
counts_out.write("%s\n" % "\t".join(("id", "read_count", "tpm")))
sum_copies = sum(copies.values())
sum_counts = sum(counts.values())
for entry_id, count in counts.items():
tpm = 1000000 * (float(copies[entry_id]) / sum_copies)
counts_out.write("%s\n" %
"\t".join(map(str, (entry_id, count, tpm))))
E.info("Reads simulated for %i fasta entries, %i entries skipped" %
(c['not_skipped'], c['skipped']))
E.info("Simulated: %i reads (%i mRNA, %i pre-mRNA), "
"%f transcripts (%f mRNA, %f pre-mRNA)" %
(sum_counts + c['pre_counts'], sum_counts, c['pre_counts'],
sum_copies + c['pre_copies'], sum_copies, c['pre_copies']))
E.Stop()