def wgsim(args):
"""
%prog wgsim fastafile
Run dwgsim on fastafile.
"""
p = OptionParser(wgsim.__doc__)
p.add_option("--erate", default=.02, type="float",
help="Base error rate of the read [default: %default]")
p.add_option("--distance", default=500, type="int",
help="Outer distance between the two ends [default: %default]")
p.add_option("--genomesize", type="int",
help="Genome size in Mb [default: estimate from data]")
p.add_option("--readlen", default=100, type="int",
help="Length of the read [default: %default]")
p.add_option("--noerrors", default=False, action="store_true",
help="Simulate reads with no errors [default: %default]")
p.set_depth(depth=10)
opts, args = p.parse_args(args)
if len(args) != 1:
sys.exit(not p.print_help())
fastafile, = args
pf = fastafile.split(".")[0]
genomesize = opts.genomesize
size = genomesize * 1000000 if genomesize else Fasta(fastafile).totalsize
depth = opts.depth
readlen = opts.readlen
readnum = size * depth / (2 * readlen)
distance = opts.distance
stdev = distance / 5
outpf = "{0}.{1}bp.{2}x".format(pf, distance, depth)
distance -= 2 * readlen # Outer distance => Inner distance
assert distance >= 0, "Outer distance must be >= 2 * readlen"
logging.debug("Total genome size: {0} bp".format(size))
logging.debug("Target depth: {0}x".format(depth))
logging.debug("Number of read pairs (2x{0}): {1}".format(readlen, readnum))
if opts.noerrors:
opts.erate = 0
cmd = "dwgsim -e {0} -E {0}".format(opts.erate)
if opts.noerrors:
cmd += " -r 0 -R 0 -X 0 -y 0"
cmd += " -d {0} -s {1}".format(distance, stdev)
cmd += " -N {0} -1 {1} -2 {1}".format(readnum, readlen)
cmd += " {0} {1}".format(fastafile, outpf)
sh(cmd)
def wgsim(args):
"""
%prog wgsim fastafile
Run dwgsim on fastafile.
"""
p = OptionParser(wgsim.__doc__)
p.add_option("--erate", default=.02, type="float",
help="Base error rate of the read [default: %default]")
p.add_option("--distance", default=500, type="int",
help="Outer distance between the two ends [default: %default]")
p.add_option("--genomesize", type="int",
help="Genome size in Mb [default: estimate from data]")
p.add_option("--readlen", default=100, type="int",
help="Length of the read [default: %default]")
p.add_option("--noerrors", default=False, action="store_true",
help="Simulate reads with no errors [default: %default]")
p.set_depth(depth=10)
opts, args = p.parse_args(args)
if len(args) != 1:
sys.exit(not p.print_help())
fastafile, = args
pf = fastafile.split(".")[0]
genomesize = opts.genomesize
size = genomesize * 1000000 if genomesize else Fasta(fastafile).totalsize
depth = opts.depth
readlen = opts.readlen
readnum = size * depth / (2 * readlen)
distance = opts.distance
stdev = distance / 5
outpf = "{0}.{1}bp.{2}x".format(pf, distance, depth)
distance -= 2 * readlen # Outer distance => Inner distance
assert distance >= 0, "Outer distance must be >= 2 * readlen"
logging.debug("Total genome size: {0} bp".format(size))
logging.debug("Target depth: {0}x".format(depth))
logging.debug("Number of read pairs (2x{0}): {1}".format(readlen, readnum))
if opts.noerrors:
opts.erate = 0
cmd = "dwgsim -e {0} -E {0}".format(opts.erate)
if opts.noerrors:
cmd += " -r 0 -R 0 -X 0 -y 0"
cmd += " -d {0} -s {1}".format(distance, stdev)
cmd += " -N {0} -1 {1} -2 {1}".format(readnum, readlen)
cmd += " {0} {1}".format(fastafile, outpf)
sh(cmd)
def shred(args):
"""
%prog shred fastafile
Similar to the method of `shredContig` in runCA script. The contigs are
shredded into pseudo-reads with certain length and depth.
"""
p = OptionParser(shred.__doc__)
p.set_depth(depth=2)
p.add_option("--readlen", default=1000, type="int", help="Desired length of the reads [default: %default]")
p.add_option("--minctglen", default=0, type="int", help="Ignore contig sequence less than [default: %default]")
p.add_option("--shift", default=50, type="int", help="Overlap between reads must be at least [default: %default]")
p.add_option(
"--fasta",
default=False,
action="store_true",
help="Output shredded reads as FASTA sequences [default: %default]",
)
opts, args = p.parse_args(args)
if len(args) != 1:
sys.exit(not p.print_help())
fastafile, = args
libID = fastafile.split(".")[0]
depth = opts.depth
readlen = opts.readlen
shift = opts.shift
outfile = libID + ".depth{0}".format(depth)
if opts.fasta:
outfile += ".fasta"
else:
outfile += ".frg"
f = Fasta(fastafile, lazy=True)
fw = must_open(outfile, "w", checkexists=True)
if not opts.fasta:
print >> fw, headerTemplate.format(libID=libID)
"""
Taken from runCA:
|*********|
|###################|
|--------------------------------------------------|
---------------1---------------
---------------2---------------
---------------3---------------
*** - center_increments
### - center_range_width
"""
for ctgID, (name, rec) in enumerate(f.iteritems_ordered()):
seq = rec.seq
seqlen = len(seq)
if seqlen < opts.minctglen:
continue
shredlen = min(seqlen - shift, readlen)
numreads = max(seqlen * depth / shredlen, 1)
center_range_width = seqlen - shredlen
ranges = []
if depth == 1:
if seqlen < readlen:
ranges.append((0, seqlen))
else:
for begin in xrange(0, seqlen, readlen - shift):
end = min(seqlen, begin + readlen)
ranges.append((begin, end))
else:
if numreads == 1:
ranges.append((0, shredlen))
else:
prev_begin = -1
center_increments = center_range_width * 1.0 / (numreads - 1)
for i in xrange(numreads):
begin = center_increments * i
end = begin + shredlen
begin, end = int(begin), int(end)
if begin == prev_begin:
continue
ranges.append((begin, end))
prev_begin = begin
for shredID, (begin, end) in enumerate(ranges):
shredded_seq = seq[begin:end]
fragID = "{0}.{1}.frag{2}.{3}-{4}".format(libID, ctgID, shredID, begin, end)
emitFragment(fw, fragID, libID, shredded_seq, fasta=opts.fasta)
fw.close()
logging.debug("Shredded reads are written to `{0}`.".format(outfile))
return outfile
def novo(args):
"""
%prog novo reads.fastq
Reference-free tGBS pipeline.
"""
from jcvi.assembly.kmer import jellyfish, histogram
from jcvi.assembly.preprocess import diginorm
from jcvi.formats.fasta import filter as fasta_filter, format
from jcvi.apps.cdhit import filter as cdhit_filter
p = OptionParser(novo.__doc__)
p.add_option("--technology", choices=("illumina", "454", "iontorrent"),
default="iontorrent", help="Sequencing platform")
p.add_option("--dedup", choices=("uclust", "cdhit"),
default="cdhit", help="Dedup algorithm")
p.set_depth(depth=50)
p.set_align(pctid=96)
p.set_home("cdhit", default="/usr/local/bin/")
p.set_home("fiona", default="/usr/local/bin/")
p.set_home("jellyfish", default="/usr/local/bin/")
p.set_cpus()
opts, args = p.parse_args(args)
if len(args) != 1:
sys.exit(not p.print_help())
fastqfile, = args
cpus = opts.cpus
depth = opts.depth
pf, sf = fastqfile.rsplit(".", 1)
diginormfile = pf + ".diginorm." + sf
if need_update(fastqfile, diginormfile):
diginorm([fastqfile, "--single", "--depth={0}".format(depth)])
keepabund = fastqfile + ".keep.abundfilt"
sh("cp -s {0} {1}".format(keepabund, diginormfile))
jf = pf + "-K23.histogram"
if need_update(diginormfile, jf):
jellyfish([diginormfile, "--prefix={0}".format(pf),
"--cpus={0}".format(cpus),
"--jellyfish_home={0}".format(opts.jellyfish_home)])
genomesize = histogram([jf, pf, "23"])
fiona = pf + ".fiona.fa"
if need_update(diginormfile, fiona):
cmd = op.join(opts.fiona_home, "fiona")
cmd += " -g {0} -nt {1} --sequencing-technology {2}".\
format(genomesize, cpus, opts.technology)
cmd += " -vv {0} {1}".format(diginormfile, fiona)
logfile = pf + ".fiona.log"
sh(cmd, outfile=logfile, errfile=logfile)
dedup = opts.dedup
pctid = opts.pctid
cons = fiona + ".P{0}.{1}.consensus.fasta".format(pctid, dedup)
if need_update(fiona, cons):
if dedup == "cdhit":
deduplicate([fiona, "--consensus", "--reads",
"--pctid={0}".format(pctid),
"--cdhit_home={0}".format(opts.cdhit_home)])
else:
uclust([fiona, "--pctid={0}".format(pctid)])
filteredfile = pf + ".filtered.fasta"
if need_update(cons, filteredfile):
covfile = pf + ".cov.fasta"
cdhit_filter([cons, "--outfile={0}".format(covfile),
"--minsize={0}".format(depth / 5)])
fasta_filter([covfile, "50", "--outfile={0}".format(filteredfile)])
finalfile = pf + ".final.fasta"
if need_update(filteredfile, finalfile):
format([filteredfile, finalfile, "--sequential=replace",
"--prefix={0}_".format(pf)])
def diginorm(args):
"""
%prog diginorm fastqfile
Run K-mer based normalization. Based on tutorial:
<http://ged.msu.edu/angus/diginorm-2012/tutorial.html>
Assume input is either an interleaved pairs file, or two separate files.
To set up khmer:
$ git clone git://github.com/ged-lab/screed.git
$ git clone git://github.com/ged-lab/khmer.git
$ cd screed
$ python setup.py install
$ cd ../khmer
$ make test
$ export PYTHONPATH=~/export/khmer
"""
from jcvi.formats.fastq import shuffle, pairinplace, split
from jcvi.apps.base import getfilesize
p = OptionParser(diginorm.__doc__)
p.add_option("--single", default=False, action="store_true",
help="Single end reads")
p.add_option("--tablesize", help="Memory size")
p.add_option("--npass", default="1", choices=("1", "2"),
help="How many passes of normalization")
p.set_depth(depth=50)
p.set_home("khmer", default="/usr/local/bin/")
opts, args = p.parse_args(args)
if len(args) not in (1, 2):
sys.exit(not p.print_help())
if len(args) == 2:
fastq = shuffle(args + ["--tag"])
else:
fastq, = args
kh = opts.khmer_home
depth = opts.depth
PE = not opts.single
sys.path.insert(0, op.join(kh, "python"))
pf = fastq.rsplit(".", 1)[0]
keepfile = fastq + ".keep"
hashfile = pf + ".kh"
mints = 10000000
ts = opts.tablesize or ((getfilesize(fastq) / 16 / mints + 1) * mints)
norm_cmd = op.join(kh, "normalize-by-median.py")
filt_cmd = op.join(kh, "filter-abund.py")
if need_update(fastq, (hashfile, keepfile)):
cmd = norm_cmd
cmd += " -C {0} -k 20 -N 4 -x {1}".format(depth, ts)
if PE:
cmd += " -p"
cmd += " -s {0} {1}".format(hashfile, fastq)
sh(cmd)
abundfiltfile = keepfile + ".abundfilt"
if need_update((hashfile, keepfile), abundfiltfile):
cmd = filt_cmd
cmd += " {0} {1}".format(hashfile, keepfile)
sh(cmd)
if opts.npass == "1":
seckeepfile = abundfiltfile
else:
seckeepfile = abundfiltfile + ".keep"
if need_update(abundfiltfile, seckeepfile):
cmd = norm_cmd
cmd += " -C {0} -k 20 -N 4 -x {1}".format(depth - 10, ts / 2)
cmd += " {0}".format(abundfiltfile)
sh(cmd)
if PE:
pairsfile = pairinplace([seckeepfile,
"--base={0}".format(pf + "_norm"), "--rclip=2"])
split([pairsfile])
def expand(args):
"""
%prog expand bes.fasta reads.fastq
Expand sequences using short reads. Useful, for example for getting BAC-end
sequences. The template to use, in `bes.fasta` may just contain the junction
sequences, then align the reads to get the 'flanks' for such sequences.
"""
import math
from jcvi.formats.fasta import Fasta, SeqIO
from jcvi.formats.fastq import readlen, first, fasta
from jcvi.formats.blast import Blast
from jcvi.formats.base import FileShredder
from jcvi.apps.bowtie import align, get_samfile
from jcvi.apps.align import blast
p = OptionParser(expand.__doc__)
p.set_depth(depth=200)
p.set_firstN()
opts, args = p.parse_args(args)
if len(args) != 2:
sys.exit(not p.print_help())
bes, reads = args
size = Fasta(bes).totalsize
rl = readlen([reads])
expected_size = size + 2 * rl
nreads = expected_size * opts.depth / rl
nreads = int(math.ceil(nreads / 1000.)) * 1000
# Attract reads
samfile, logfile = align([bes, reads, "--reorder", "--mapped",
"--firstN={0}".format(opts.firstN)])
samfile, mapped, _ = get_samfile(reads, bes, bowtie=True, mapped=True)
logging.debug("Extract first {0} reads from `{1}`.".format(nreads, mapped))
pf = mapped.split(".")[0]
pf = pf.split("-")[0]
bespf = bes.split(".")[0]
reads = pf + ".expand.fastq"
first([str(nreads), mapped, "-o", reads])
# Perform mini-assembly
fastafile = reads.rsplit(".", 1)[0] + ".fasta"
qualfile = ""
if need_update(reads, fastafile):
fastafile, qualfile = fasta([reads])
contigs = op.join(pf, "454LargeContigs.fna")
if need_update(fastafile, contigs):
cmd = "runAssembly -o {0} -cpu 8 {1}".format(pf, fastafile)
sh(cmd)
assert op.exists(contigs)
# Annotate contigs
blastfile = blast([bes, contigs])
mapping = {}
for query, b in Blast(blastfile).iter_best_hit():
mapping[query] = b
f = Fasta(contigs, lazy=True)
annotatedfasta = ".".join((pf, bespf, "fasta"))
fw = open(annotatedfasta, "w")
keys = list(Fasta(bes).iterkeys_ordered()) # keep an ordered list
recs = []
for key, v in f.iteritems_ordered():
vid = v.id
if vid not in mapping:
continue
b = mapping[vid]
subject = b.subject
rec = v.reverse_complement() if b.orientation == '-' else v
rec.id = rid = "_".join((pf, vid, subject))
rec.description = ""
recs.append((keys.index(subject), rid, rec))
recs = [x[-1] for x in sorted(recs)]
SeqIO.write(recs, fw, "fasta")
fw.close()
FileShredder([samfile, logfile, mapped, reads, fastafile, qualfile, blastfile, pf])
logging.debug("Annotated seqs (n={0}) written to `{1}`.".\
format(len(recs), annotatedfasta))
return annotatedfasta
def diginorm(args):
"""
%prog diginorm fastqfile
Run K-mer based normalization. Based on tutorial:
<http://ged.msu.edu/angus/diginorm-2012/tutorial.html>
Assume input is either an interleaved pairs file, or two separate files.
To set up khmer:
$ git clone git://github.com/ged-lab/screed.git
$ git clone git://github.com/ged-lab/khmer.git
$ cd screed
$ python setup.py install
$ cd ../khmer
$ make test
$ export PYTHONPATH=/root/khmer/python
"""
from jcvi.formats.fastq import shuffle, pairinplace, split
p = OptionParser(diginorm.__doc__)
p.set_depth()
p.set_home("khmer")
opts, args = p.parse_args(args)
if len(args) not in (1, 2):
sys.exit(not p.print_help())
if len(args) == 2:
fastq = shuffle(args + ["--tag"])
else:
fastq, = args
kh = opts.khmer_home
depth = opts.depth
sys.path.insert(0, op.join(kh, "python"))
pf = fastq.rsplit(".", 1)[0]
hashfile = pf + ".kh"
keepfile = fastq + ".keep"
norm_cmd = op.join(kh, "scripts/normalize-by-median.py")
filt_cmd = op.join(kh, "scripts/filter-abund.py")
if need_update(fastq, (hashfile, keepfile)):
cmd = norm_cmd
cmd += " -C {0} -k 20 -N 4 -x 2.5e8 -p".format(depth)
cmd += " --savehash {0} {1}".format(hashfile, fastq)
sh(cmd)
abundfiltfile = keepfile + ".abundfilt"
if need_update((hashfile, keepfile), abundfiltfile):
cmd = filt_cmd
cmd += " {0} {1}".format(hashfile, keepfile)
sh(cmd)
seckeepfile = abundfiltfile + ".keep"
if need_update(abundfiltfile, seckeepfile):
cmd = norm_cmd
cmd += " -C {0} -k 20 -N 4 -x 1e8".format(depth - 5)
cmd += " {0}".format(abundfiltfile)
sh(cmd)
pairsfile = pairinplace([seckeepfile,
"--base={0}".format(pf + "_norm"), "--rclip=2"])
split([pairsfile])
def expand(args):
"""
%prog expand bes.fasta reads.fastq
Expand sequences using short reads. Useful, for example for getting BAC-end
sequences. The template to use, in `bes.fasta` may just contain the junction
sequences, then align the reads to get the 'flanks' for such sequences.
"""
import math
from jcvi.formats.fasta import Fasta, SeqIO
from jcvi.formats.fastq import readlen, first, fasta
from jcvi.formats.blast import Blast
from jcvi.formats.base import FileShredder
from jcvi.apps.bowtie import align, get_samfile
from jcvi.apps.align import blast
p = OptionParser(expand.__doc__)
p.set_depth(depth=200)
p.set_firstN()
opts, args = p.parse_args(args)
if len(args) != 2:
sys.exit(not p.print_help())
bes, reads = args
size = Fasta(bes).totalsize
rl = readlen([reads])
expected_size = size + 2 * rl
nreads = expected_size * opts.depth / rl
nreads = int(math.ceil(nreads / 1000.)) * 1000
# Attract reads
samfile, logfile = align([bes, reads, "--reorder", "--mapped",
"--firstN={0}".format(opts.firstN)])
samfile, mapped, _ = get_samfile(reads, bes, bowtie=True, mapped=True)
logging.debug("Extract first {0} reads from `{1}`.".format(nreads, mapped))
pf = mapped.split(".")[0]
pf = pf.split("-")[0]
bespf = bes.split(".")[0]
reads = pf + ".expand.fastq"
first([str(nreads), mapped, "-o", reads])
# Perform mini-assembly
fastafile = reads.rsplit(".", 1)[0] + ".fasta"
qualfile = ""
if need_update(reads, fastafile):
fastafile, qualfile = fasta([reads])
contigs = op.join(pf, "454LargeContigs.fna")
if need_update(fastafile, contigs):
cmd = "runAssembly -o {0} -cpu 8 {1}".format(pf, fastafile)
sh(cmd)
assert op.exists(contigs)
# Annotate contigs
blastfile = blast([bes, contigs])
mapping = {}
for query, b in Blast(blastfile).iter_best_hit():
mapping[query] = b
f = Fasta(contigs, lazy=True)
annotatedfasta = ".".join((pf, bespf, "fasta"))
fw = open(annotatedfasta, "w")
keys = list(Fasta(bes).iterkeys_ordered()) # keep an ordered list
recs = []
for key, v in f.iteritems_ordered():
vid = v.id
if vid not in mapping:
continue
b = mapping[vid]
subject = b.subject
rec = v.reverse_complement() if b.orientation == '-' else v
rec.id = rid = "_".join((pf, vid, subject))
rec.description = ""
recs.append((keys.index(subject), rid, rec))
recs = [x[-1] for x in sorted(recs)]
SeqIO.write(recs, fw, "fasta")
fw.close()
FileShredder([samfile, logfile, mapped, reads, fastafile, qualfile, blastfile, pf])
logging.debug("Annotated seqs (n={0}) written to `{1}`.".\
format(len(recs), annotatedfasta))
return annotatedfasta
def diginorm(args):
"""
%prog diginorm fastqfile
Run K-mer based normalization. Based on tutorial:
<http://ged.msu.edu/angus/diginorm-2012/tutorial.html>
Assume input is either an interleaved pairs file, or two separate files.
To set up khmer:
$ git clone git://github.com/ged-lab/screed.git
$ git clone git://github.com/ged-lab/khmer.git
$ cd screed
$ python setup.py install
$ cd ../khmer
$ make test
$ export PYTHONPATH=~/export/khmer
"""
from jcvi.formats.fastq import shuffle, pairinplace, split
from jcvi.apps.base import getfilesize
p = OptionParser(diginorm.__doc__)
p.add_option("--single", default=False, action="store_true",
help="Single end reads")
p.add_option("--tablesize", help="Memory size")
p.add_option("--npass", default="1", choices=("1", "2"),
help="How many passes of normalization")
p.set_depth(depth=50)
p.set_home("khmer", default="/usr/local/bin/")
opts, args = p.parse_args(args)
if len(args) not in (1, 2):
sys.exit(not p.print_help())
if len(args) == 2:
fastq = shuffle(args + ["--tag"])
else:
fastq, = args
kh = opts.khmer_home
depth = opts.depth
PE = not opts.single
sys.path.insert(0, op.join(kh, "python"))
pf = fastq.rsplit(".", 1)[0]
keepfile = fastq + ".keep"
hashfile = pf + ".kh"
mints = 10000000
ts = opts.tablesize or ((getfilesize(fastq) / 16 / mints + 1) * mints)
norm_cmd = op.join(kh, "normalize-by-median.py")
filt_cmd = op.join(kh, "filter-abund.py")
if need_update(fastq, (hashfile, keepfile)):
cmd = norm_cmd
cmd += " -C {0} -k 20 -N 4 -x {1}".format(depth, ts)
if PE:
cmd += " -p"
cmd += " -s {0} {1}".format(hashfile, fastq)
sh(cmd)
abundfiltfile = keepfile + ".abundfilt"
if need_update((hashfile, keepfile), abundfiltfile):
cmd = filt_cmd
cmd += " {0} {1}".format(hashfile, keepfile)
sh(cmd)
if opts.npass == "1":
seckeepfile = abundfiltfile
else:
seckeepfile = abundfiltfile + ".keep"
if need_update(abundfiltfile, seckeepfile):
cmd = norm_cmd
cmd += " -C {0} -k 20 -N 4 -x {1}".format(depth - 10, ts / 2)
cmd += " {0}".format(abundfiltfile)
sh(cmd)
if PE:
pairsfile = pairinplace([seckeepfile,
"--base={0}".format(pf + "_norm"), "--rclip=2"])
split([pairsfile])
def novo(args):
"""
%prog novo reads.fastq
Reference-free tGBS pipeline.
"""
from jcvi.assembly.kmer import jellyfish, histogram
from jcvi.assembly.preprocess import diginorm
from jcvi.formats.fasta import filter as fasta_filter, format
from jcvi.apps.cdhit import filter as cdhit_filter
p = OptionParser(novo.__doc__)
p.add_option("--technology",
choices=("illumina", "454", "iontorrent"),
default="iontorrent",
help="Sequencing platform")
p.add_option("--dedup",
choices=("uclust", "cdhit"),
default="cdhit",
help="Dedup algorithm")
p.set_depth(depth=50)
p.set_align(pctid=96)
p.set_home("cdhit")
p.set_home("fiona")
p.set_cpus()
opts, args = p.parse_args(args)
if len(args) != 1:
sys.exit(not p.print_help())
fastqfile, = args
cpus = opts.cpus
depth = opts.depth
pf, sf = fastqfile.rsplit(".", 1)
diginormfile = pf + ".diginorm." + sf
if need_update(fastqfile, diginormfile):
diginorm([fastqfile, "--single", "--depth={0}".format(depth)])
keepabund = fastqfile + ".keep.abundfilt"
sh("cp -s {0} {1}".format(keepabund, diginormfile))
jf = pf + "-K23.histogram"
if need_update(diginormfile, jf):
jellyfish([
diginormfile, "--prefix={0}".format(pf), "--cpus={0}".format(cpus)
])
genomesize = histogram([jf, pf, "23"])
fiona = pf + ".fiona.fa"
if need_update(diginormfile, fiona):
cmd = op.join(opts.fiona_home, "bin/fiona")
cmd += " -g {0} -nt {1} --sequencing-technology {2}".\
format(genomesize, cpus, opts.technology)
cmd += " -vv {0} {1}".format(diginormfile, fiona)
logfile = pf + ".fiona.log"
sh(cmd, outfile=logfile, errfile=logfile)
dedup = opts.dedup
pctid = opts.pctid
cons = fiona + ".P{0}.{1}.consensus.fasta".format(pctid, dedup)
if need_update(fiona, cons):
if dedup == "cdhit":
deduplicate([
fiona, "--consensus", "--reads", "--pctid={0}".format(pctid),
"--cdhit_home={0}".format(opts.cdhit_home)
])
else:
uclust([fiona, "--pctid={0}".format(pctid)])
filteredfile = pf + ".filtered.fasta"
if need_update(cons, filteredfile):
covfile = pf + ".cov.fasta"
cdhit_filter([
cons, "--outfile={0}".format(covfile),
"--minsize={0}".format(depth / 5)
])
fasta_filter([covfile, "50", "--outfile={0}".format(filteredfile)])
finalfile = pf + ".final.fasta"
if need_update(filteredfile, finalfile):
format([
filteredfile, finalfile, "--sequential=replace",
"--prefix={0}_".format(pf)
])
def shred(args):
"""
%prog shred fastafile
Similar to the method of `shredContig` in runCA script. The contigs are
shredded into pseudo-reads with certain length and depth.
"""
p = OptionParser(shred.__doc__)
p.set_depth(depth=2)
p.add_option("--readlen",
default=1000,
type="int",
help="Desired length of the reads [default: %default]")
p.add_option("--minctglen",
default=0,
type="int",
help="Ignore contig sequence less than [default: %default]")
p.add_option(
"--shift",
default=50,
type="int",
help="Overlap between reads must be at least [default: %default]")
p.add_option(
"--fasta",
default=False,
action="store_true",
help="Output shredded reads as FASTA sequences [default: %default]")
opts, args = p.parse_args(args)
if len(args) != 1:
sys.exit(not p.print_help())
fastafile, = args
libID = fastafile.split(".")[0]
depth = opts.depth
readlen = opts.readlen
shift = opts.shift
outfile = libID + ".depth{0}".format(depth)
if opts.fasta:
outfile += ".fasta"
else:
outfile += ".frg"
f = Fasta(fastafile, lazy=True)
fw = must_open(outfile, "w", checkexists=True)
if not opts.fasta:
print >> fw, headerTemplate.format(libID=libID)
"""
Taken from runCA:
|*********|
|###################|
|--------------------------------------------------|
---------------1---------------
---------------2---------------
---------------3---------------
*** - center_increments
### - center_range_width
"""
for ctgID, (name, rec) in enumerate(f.iteritems_ordered()):
seq = rec.seq
seqlen = len(seq)
if seqlen < opts.minctglen:
continue
shredlen = min(seqlen - shift, readlen)
numreads = max(seqlen * depth / shredlen, 1)
center_range_width = seqlen - shredlen
ranges = []
if depth == 1:
if seqlen < readlen:
ranges.append((0, seqlen))
else:
for begin in xrange(0, seqlen, readlen - shift):
end = min(seqlen, begin + readlen)
ranges.append((begin, end))
else:
if numreads == 1:
ranges.append((0, shredlen))
else:
prev_begin = -1
center_increments = center_range_width * 1. / (numreads - 1)
for i in xrange(numreads):
begin = center_increments * i
end = begin + shredlen
begin, end = int(begin), int(end)
if begin == prev_begin:
continue
ranges.append((begin, end))
prev_begin = begin
for shredID, (begin, end) in enumerate(ranges):
shredded_seq = seq[begin:end]
fragID = "{0}.{1}.frag{2}.{3}-{4}".format(libID, ctgID, shredID,
begin, end)
emitFragment(fw, fragID, libID, shredded_seq, fasta=opts.fasta)
fw.close()
logging.debug("Shredded reads are written to `{0}`.".format(outfile))
return outfile
