def convert(args):
"""
%prog convert in.fastq out.fastq
illumina fastq quality encoding uses offset 64, and sanger uses 33. This
script creates a new file with the correct encoding
"""
p = OptionParser(convert.__doc__)
p.set_phred()
opts, args = p.parse_args(args)
if len(args) != 2:
sys.exit(not p.print_help())
infastq, outfastq = args
phred = opts.phred or str(guessoffset([infastq]))
fin = "illumina" if phred == "64" else "sanger"
fout = "sanger" if phred == "64" else "illumina"
seqret = "seqret"
if infastq.endswith(".gz"):
cmd = "zcat {0} | ".format(infastq)
cmd += seqret + " fastq-{0}::stdin fastq-{1}::stdout".format(fin, fout)
else:
cmd = seqret + " fastq-{0}::{1} fastq-{2}::stdout".format(fin, infastq, fout)
sh(cmd, outfile=outfastq)
return outfastq
def fastq(args):
"""
%prog fastq fastqfile
Convert reads formatted as FASTQ file, and convert to CA frg file.
"""
from jcvi.formats.fastq import guessoffset
p = OptionParser(fastq.__doc__)
p.add_option(
"--outtie",
dest="outtie",
default=False,
action="store_true",
help="Are these outie reads?",
)
p.set_phred()
p.set_size()
opts, args = p.parse_args(args)
if len(args) < 1:
sys.exit(p.print_help())
fastqfiles = [get_abs_path(x) for x in args]
size = opts.size
outtie = opts.outtie
if size > 1000 and (not outtie):
logging.debug(
"[warn] long insert size {0} but not outtie".format(size))
mated = size != 0
libname = op.basename(args[0]).split(".")[0]
libname = libname.replace("_1_sequence", "")
frgfile = libname + ".frg"
mean, sv = get_mean_sv(opts.size)
cmd = "fastqToCA"
cmd += " -libraryname {0} ".format(libname)
fastqs = " ".join("-reads {0}".format(x) for x in fastqfiles)
if mated:
assert len(args) in (
1, 2), "you need one or two fastq files for mated library"
fastqs = "-mates {0}".format(",".join(fastqfiles))
cmd += "-insertsize {0} {1} ".format(mean, sv)
cmd += fastqs
offset = int(opts.phred) if opts.phred else guessoffset([fastqfiles[0]])
illumina = offset == 64
if illumina:
cmd += " -type illumina"
if outtie:
cmd += " -outtie"
sh(cmd, outfile=frgfile)
def tophat(args):
"""
%prog tophat folder reference
Run tophat on a folder of reads.
"""
from jcvi.apps.bowtie import check_index
from jcvi.formats.fastq import guessoffset
p = OptionParser(tophat.__doc__)
p.add_option("--gtf", help="Reference annotation [default: %default]")
p.add_option("--single", default=False, action="store_true",
help="Single end mapping")
p.add_option("--intron", default=15000, type="int",
help="Max intron size [default: %default]")
p.add_option("--dist", default=-50, type="int",
help="Mate inner distance [default: %default]")
p.add_option("--stdev", default=50, type="int",
help="Mate standard deviation [default: %default]")
p.set_phred()
p.set_cpus()
opts, args = p.parse_args(args)
if len(args) != 2:
sys.exit(not p.print_help())
num = 1 if opts.single else 2
folder, reference = args
reference = check_index(reference)
for p, prefix in iter_project(folder, n=num):
outdir = "{0}_tophat".format(prefix)
outfile = op.join(outdir, "accepted_hits.bam")
if op.exists(outfile):
logging.debug("File `{0}` found. Skipping.".format(outfile))
continue
cmd = "tophat -p {0}".format(opts.cpus)
if opts.gtf:
cmd += " -G {0}".format(opts.gtf)
cmd += " -o {0}".format(outdir)
if num == 1: # Single-end
a, = p
else: # Paired-end
a, b = p
cmd += " --max-intron-length {0}".format(opts.intron)
cmd += " --mate-inner-dist {0}".format(opts.dist)
cmd += " --mate-std-dev {0}".format(opts.stdev)
phred = opts.phred or str(guessoffset([a]))
if phred == "64":
cmd += " --phred64-quals"
cmd += " {0} {1}".format(reference, " ".join(p))
sh(cmd)
def fastq(args):
"""
%prog fastq fastqfile
Convert reads formatted as FASTQ file, and convert to CA frg file.
"""
from jcvi.formats.fastq import guessoffset
p = OptionParser(fastq.__doc__)
p.add_option(
"--outtie", dest="outtie", default=False, action="store_true", help="Are these outie reads? [default: %default]"
)
p.set_phred()
p.set_size()
opts, args = p.parse_args(args)
if len(args) < 1:
sys.exit(p.print_help())
fastqfiles = [get_abs_path(x) for x in args]
size = opts.size
outtie = opts.outtie
if size > 1000 and (not outtie):
logging.debug("[warn] long insert size {0} but not outtie".format(size))
mated = size != 0
libname = op.basename(args[0]).split(".")[0]
libname = libname.replace("_1_sequence", "")
frgfile = libname + ".frg"
mean, sv = get_mean_sv(opts.size)
cmd = "fastqToCA"
cmd += " -libraryname {0} ".format(libname)
fastqs = " ".join("-reads {0}".format(x) for x in fastqfiles)
if mated:
assert len(args) in (1, 2), "you need one or two fastq files for mated library"
fastqs = "-mates {0}".format(",".join(fastqfiles))
cmd += "-insertsize {0} {1} ".format(mean, sv)
cmd += fastqs
offset = int(opts.phred) if opts.phred else guessoffset([fastqfiles[0]])
illumina = offset == 64
if illumina:
cmd += " -type illumina"
if outtie:
cmd += " -outtie"
sh(cmd, outfile=frgfile)
def convert(args):
"""
%prog convert in.fastq
illumina fastq quality encoding uses offset 64, and sanger uses 33. This
script creates a new file with the correct encoding. Output gzipped file if
input is also gzipped.
"""
p = OptionParser(convert.__doc__)
p.set_phred()
opts, args = p.parse_args(args)
if len(args) != 1:
sys.exit(not p.print_help())
infastq, = args
phred = opts.phred or str(guessoffset([infastq]))
ophred = {"64": "33", "33": "64"}[phred]
gz = infastq.endswith(".gz")
outfastq = infastq.rsplit(".", 1)[0] if gz else infastq
pf, sf = outfastq.rsplit(".", 1)
outfastq = "{0}.q{1}.{2}".format(pf, ophred, sf)
if gz:
outfastq += ".gz"
fin = "illumina" if phred == "64" else "sanger"
fout = "sanger" if phred == "64" else "illumina"
seqret = "seqret"
if infastq.endswith(".gz"):
cmd = "zcat {0} | ".format(infastq)
cmd += seqret + " fastq-{0}::stdin fastq-{1}::stdout".\
format(fin, fout)
else:
cmd = seqret + " fastq-{0}::{1} fastq-{2}::stdout".\
format(fin, infastq, fout)
sh(cmd, outfile=outfastq)
return outfastq
def convert(args):
"""
%prog convert in.fastq
illumina fastq quality encoding uses offset 64, and sanger uses 33. This
script creates a new file with the correct encoding. Output gzipped file if
input is also gzipped.
"""
p = OptionParser(convert.__doc__)
p.set_phred()
opts, args = p.parse_args(args)
if len(args) != 1:
sys.exit(not p.print_help())
infastq, = args
phred = opts.phred or str(guessoffset([infastq]))
ophred = {"64": "33", "33": "64"}[phred]
gz = infastq.endswith(".gz")
outfastq = infastq.rsplit(".", 1)[0] if gz else infastq
pf, sf = outfastq.rsplit(".", 1)
outfastq = "{0}.q{1}.{2}".format(pf, ophred, sf)
if gz:
outfastq += ".gz"
fin = "illumina" if phred == "64" else "sanger"
fout = "sanger" if phred == "64" else "illumina"
seqret = "seqret"
if infastq.endswith(".gz"):
cmd = "zcat {0} | ".format(infastq)
cmd += seqret + " fastq-{0}::stdin fastq-{1}::stdout".\
format(fin, fout)
else:
cmd = seqret + " fastq-{0}::{1} fastq-{2}::stdout".\
format(fin, infastq, fout)
sh(cmd, outfile=outfastq)
return outfastq
def gatk(args):
"""
%prog gatk bamfile reference.fasta
Call SNPs based on GATK best practices.
"""
p = OptionParser(gatk.__doc__)
p.add_option("--indelrealign", default=False, action="store_true",
help="Perform indel realignment")
p.set_home("gatk")
p.set_home("picard")
p.set_phred()
p.set_cpus(cpus=24)
opts, args = p.parse_args(args)
if len(args) != 2:
sys.exit(not p.print_help())
bamfile, ref = args
pf = bamfile.rsplit(".", 1)[0]
mm = MakeManager()
picard = "java -Xmx32g -jar {0}/picard.jar".format(opts.picard_home)
tk = "java -Xmx32g -jar {0}/GenomeAnalysisTK.jar".format(opts.gatk_home)
tk += " -R {0}".format(ref)
# Step 0 - build reference
dictfile = ref.rsplit(".", 1)[0] + ".dict"
cmd1 = picard + " CreateSequenceDictionary"
cmd1 += " R={0} O={1}".format(ref, dictfile)
cmd2 = "samtools faidx {0}".format(ref)
mm.add(ref, dictfile, (cmd1, cmd2))
# Step 1 - sort bam
sortedbamfile = pf + ".sorted.bam"
cmd = picard + " SortSam"
cmd += " INPUT={0} OUTPUT={1}".format(bamfile, sortedbamfile)
cmd += " SORT_ORDER=coordinate CREATE_INDEX=true"
mm.add(bamfile, sortedbamfile, cmd)
# Step 2 - mark duplicates
dedupbamfile = pf + ".dedup.bam"
cmd = picard + " MarkDuplicates"
cmd += " INPUT={0} OUTPUT={1}".format(sortedbamfile, dedupbamfile)
cmd += " METRICS_FILE=dedup.log CREATE_INDEX=true"
mm.add(sortedbamfile, dedupbamfile, cmd)
if opts.indelrealign:
# Step 3 - create indel realignment targets
intervals = pf + ".intervals"
cmd = tk + " -T RealignerTargetCreator"
cmd += " -I {0} -o {1}".format(dedupbamfile, intervals)
mm.add(dedupbamfile, intervals, cmd)
# Step 4 - indel realignment
realignedbamfile = pf + ".realigned.bam"
cmd = tk + " -T IndelRealigner"
cmd += " -targetIntervals {0}".format(intervals)
cmd += " -I {0} -o {1}".format(dedupbamfile, realignedbamfile)
mm.add((dictfile, intervals), realignedbamfile, cmd)
else:
realignedbamfile = dedupbamfile
# Step 5 - SNP calling
vcf = pf + ".vcf"
cmd = tk + " -T HaplotypeCaller"
cmd += " -I {0}".format(realignedbamfile)
cmd += " --genotyping_mode DISCOVERY"
cmd += " -stand_emit_conf 10 -stand_call_conf 30"
cmd += " -nct {0}".format(opts.cpus)
cmd += " -o {0}".format(vcf)
if opts.phred == "64":
cmd += " --fix_misencoded_quality_scores"
mm.add(realignedbamfile, vcf, cmd)
# Step 6 - SNP filtering
filtered_vcf = pf + ".filtered.vcf"
cmd = tk + " -T VariantFiltration"
cmd += " -V {0}".format(vcf)
cmd += ' --filterExpression "DP < 10 || DP > 300 || QD < 2.0 || FS > 60.0 || MQ < 40.0"'
cmd += ' --filterName "LOWQUAL"'
cmd += ' --genotypeFilterExpression "isHomVar == 1"'
cmd += ' --genotypeFilterName "HOMOVAR"'
cmd += ' --genotypeFilterExpression "isHet == 1"'
cmd += ' --genotypeFilterName "HET"'
cmd += " -o {0}".format(filtered_vcf)
mm.add(vcf, filtered_vcf, cmd)
mm.write()
def tophat(args):
"""
%prog tophat folder reference
Run tophat on a folder of reads.
"""
from jcvi.apps.bowtie import check_index
from jcvi.formats.fastq import guessoffset
p = OptionParser(tophat.__doc__)
p.add_option("--gtf", help="Reference annotation [default: %default]")
p.add_option("--single",
default=False,
action="store_true",
help="Single end mapping")
p.add_option("--intron",
default=15000,
type="int",
help="Max intron size [default: %default]")
p.add_option("--dist",
default=-50,
type="int",
help="Mate inner distance [default: %default]")
p.add_option("--stdev",
default=50,
type="int",
help="Mate standard deviation [default: %default]")
p.set_phred()
p.set_cpus()
opts, args = p.parse_args(args)
if len(args) != 2:
sys.exit(not p.print_help())
num = 1 if opts.single else 2
folder, reference = args
reference = check_index(reference)
for p, prefix in iter_project(folder, n=num):
outdir = "{0}_tophat".format(prefix)
outfile = op.join(outdir, "accepted_hits.bam")
if op.exists(outfile):
logging.debug("File `{0}` found. Skipping.".format(outfile))
continue
cmd = "tophat -p {0}".format(opts.cpus)
if opts.gtf:
cmd += " -G {0}".format(opts.gtf)
cmd += " -o {0}".format(outdir)
if num == 1: # Single-end
a, = p
else: # Paired-end
a, b = p
cmd += " --max-intron-length {0}".format(opts.intron)
cmd += " --mate-inner-dist {0}".format(opts.dist)
cmd += " --mate-std-dev {0}".format(opts.stdev)
phred = opts.phred or str(guessoffset([a]))
if phred == "64":
cmd += " --phred64-quals"
cmd += " {0} {1}".format(reference, " ".join(p))
sh(cmd)
def gatk(args):
"""
%prog gatk bamfile reference.fasta
Call SNPs based on GATK best practices.
"""
p = OptionParser(gatk.__doc__)
p.add_option("--indelrealign", default=False, action="store_true",
help="Perform indel realignment")
p.set_home("gatk")
p.set_home("picard")
p.set_phred()
p.set_cpus(cpus=24)
opts, args = p.parse_args(args)
if len(args) != 2:
sys.exit(not p.print_help())
bamfile, ref = args
pf = bamfile.rsplit(".", 1)[0]
mm = MakeManager()
picard = "java -Xmx32g -jar {0}/picard.jar".format(opts.picard_home)
tk = "java -Xmx32g -jar {0}/GenomeAnalysisTK.jar".format(opts.gatk_home)
tk += " -R {0}".format(ref)
# Step 0 - build reference
dictfile = ref.rsplit(".", 1)[0] + ".dict"
cmd1 = picard + " CreateSequenceDictionary"
cmd1 += " R={0} O={1}".format(ref, dictfile)
cmd2 = "samtools faidx {0}".format(ref)
mm.add(ref, dictfile, (cmd1, cmd2))
# Step 1 - sort bam
sortedbamfile = pf + ".sorted.bam"
cmd = picard + " SortSam"
cmd += " INPUT={0} OUTPUT={1}".format(bamfile, sortedbamfile)
cmd += " SORT_ORDER=coordinate CREATE_INDEX=true"
mm.add(bamfile, sortedbamfile, cmd)
# Step 2 - mark duplicates
dedupbamfile = pf + ".dedup.bam"
cmd = picard + " MarkDuplicates"
cmd += " INPUT={0} OUTPUT={1}".format(sortedbamfile, dedupbamfile)
cmd += " METRICS_FILE=dedup.log CREATE_INDEX=true"
mm.add(sortedbamfile, dedupbamfile, cmd)
if opts.indelrealign:
# Step 3 - create indel realignment targets
intervals = pf + ".intervals"
cmd = tk + " -T RealignerTargetCreator"
cmd += " -I {0} -o {1}".format(dedupbamfile, intervals)
mm.add(dedupbamfile, intervals, cmd)
# Step 4 - indel realignment
realignedbamfile = pf + ".realigned.bam"
cmd = tk + " -T IndelRealigner"
cmd += " -targetIntervals {0}".format(intervals)
cmd += " -I {0} -o {1}".format(dedupbamfile, realignedbamfile)
mm.add((dictfile, intervals), realignedbamfile, cmd)
else:
realignedbamfile = dedupbamfile
# Step 5 - SNP calling
vcf = pf + ".vcf"
cmd = tk + " -T HaplotypeCaller"
cmd += " -I {0}".format(realignedbamfile)
cmd += " --genotyping_mode DISCOVERY"
cmd += " -stand_emit_conf 10 -stand_call_conf 30"
cmd += " -nct {0}".format(opts.cpus)
cmd += " -o {0}".format(vcf)
if opts.phred == "64":
cmd += " --fix_misencoded_quality_scores"
mm.add(realignedbamfile, vcf, cmd)
# Step 6 - SNP filtering
filtered_vcf = pf + ".filtered.vcf"
cmd = tk + " -T VariantFiltration"
cmd += " -V {0}".format(vcf)
cmd += ' --filterExpression "DP < 10 || DP > 300 || QD < 2.0 || FS > 60.0 || MQ < 40.0"'
cmd += ' --filterName "LOWQUAL"'
cmd += ' --genotypeFilterExpression "isHomVar == 1"'
cmd += ' --genotypeFilterName "HOMOVAR"'
cmd += ' --genotypeFilterExpression "isHet == 1"'
cmd += ' --genotypeFilterName "HET"'
cmd += " -o {0}".format(filtered_vcf)
mm.add(vcf, filtered_vcf, cmd)
mm.write()
def trim(args):
"""
%prog trim fastqfiles
Trim reads using TRIMMOMATIC. If two fastqfiles are given, then it invokes
the paired reads mode. See manual:
<http://www.usadellab.org/cms/index.php?page=trimmomatic>
"""
tv = "0.32"
TrimJar = "trimmomatic-{0}.jar".format(tv)
p = OptionParser(trim.__doc__)
p.add_option("--path", default=op.join("~/bin", TrimJar),
help="Path to trimmomatic jar file [default: %default]")
p.set_phred()
p.add_option("--nofrags", default=False, action="store_true",
help="Discard frags file in PE mode [default: %default]")
p.add_option("--minqv", default=15, type="int",
help="Average qv after trimming [default: %default]")
p.add_option("--minlen", default=36, type="int",
help="Minimum length after trimming [default: %default]")
p.add_option("--adapteronly", default=False, action="store_true",
help="Only trim adapters with no qv trimming [default: %default]")
p.add_option("--nogz", default=False, action="store_true",
help="Do not write to gzipped files [default: %default]")
p.add_option("--log", default=None, dest="trimlog",
help="Specify a `trimlog` file [default: %default]")
p.set_cpus(cpus=4)
opts, args = p.parse_args(args)
if len(args) not in (1, 2):
sys.exit(not p.print_help())
path = op.expanduser(opts.path)
url = \
"http://www.usadellab.org/cms/uploads/supplementary/Trimmomatic/Trimmomatic-{0}.zip"\
.format(tv)
if not op.exists(path):
path = download(url)
TrimUnzipped = "Trimmomatic-" + tv
if not op.exists(TrimUnzipped):
sh("unzip " + path)
os.remove(path)
path = op.join(TrimUnzipped, TrimJar)
assert op.exists(path), \
"Couldn't find Trimmomatic jar file at `{0}`".\
format(path)
adaptersfile = "adapters.fasta"
Adapters = must_open(op.join(datadir, adaptersfile)).read()
write_file(adaptersfile, Adapters, skipcheck=True)
assert op.exists(adaptersfile), \
"Please place the illumina adapter sequence in `{0}`".\
format(adaptersfile)
if opts.phred is None:
offset = guessoffset([args[0]])
else:
offset = int(opts.phred)
phredflag = " -phred{0}".format(offset)
threadsflag = " -threads {0}".format(opts.cpus)
if opts.trimlog:
trimlog = " -trimlog {0}".format(opts.trimlog)
cmd = "java -Xmx4g -jar {0}".format(path)
frags = ".frags.fastq"
pairs = ".pairs.fastq"
if not opts.nogz:
frags += ".gz"
pairs += ".gz"
get_prefix = lambda x: op.basename(x).replace(".gz", "").rsplit(".", 1)[0]
get_dirname = lambda x: "{0}/".format(op.dirname(x)) if op.dirname(x) else ''
if len(args) == 1:
cmd += " SE"
cmd += phredflag
cmd += threadsflag
if opts.trimlog:
cmd += trimlog
fastqfile, = args
prefix = get_prefix(fastqfile)
dirname = get_dirname(fastqfile)
frags1 = dirname + prefix + frags
cmd += " {0}".format(" ".join((fastqfile, frags1)))
else:
cmd += " PE"
cmd += phredflag
cmd += threadsflag
if opts.trimlog:
cmd += trimlog
fastqfile1, fastqfile2 = args
prefix1 = get_prefix(fastqfile1)
dirname1 = get_dirname(fastqfile1)
prefix2 = get_prefix(fastqfile2)
dirname2 = get_dirname(fastqfile2)
pairs1 = dirname1 + prefix1 + pairs
pairs2 = dirname2 + prefix2 + pairs
frags1 = dirname1 + prefix1 + frags
frags2 = dirname2 + prefix2 + frags
if opts.nofrags:
frags1 = "/dev/null"
frags2 = "/dev/null"
cmd += " {0}".format(" ".join((fastqfile1, fastqfile2, \
pairs1, frags1, pairs2, frags2)))
cmd += " ILLUMINACLIP:{0}:2:30:10".format(adaptersfile)
if not opts.adapteronly:
cmd += " LEADING:3 TRAILING:3"
cmd += " SLIDINGWINDOW:4:{0}".format(opts.minqv)
cmd += " MINLEN:{0}".format(opts.minlen)
if offset != 33:
cmd += " TOPHRED33"
sh(cmd)
