def main(debug=None):
args = docopt(__doc__, argv=debug, version=__version__)
if args["<vcf>"] == "":
print(__doc__)
v = vcf(args["<vcf>"])
for line in v.output_raw():
if line.startswith("#CHROM"):
line = line.split("\t")
if args["--subst"]:
find_replace = [re.split("[:=,]", x) for x in args["--subst"]]
for orig, replacement in find_replace:
for n, sample in enumerate(line[9:]):
if sample == orig:
line[9 + n] = replacement
if args["--prefix"]:
line[9:] = [args["--prefix"] + x for x in line[9:]]
if args["--suffix"]:
line[9:] = [x + args["--suffix"] for x in line[9:]]
print '\t'.join(line)
else:
print(line.strip())
def main(debug=None):
args = docopt(__doc__,
argv=debug,
version=__version__)
if args["<vcf>"] == "":
print(__doc__)
v = vcf(args["<vcf>"])
for line in v.output_raw():
if line.startswith("#CHROM"):
line = line.split("\t")
if args["--subst"]:
find_replace = [re.split("[:=,]", x) for x in args["--subst"]]
for orig, replacement in find_replace:
for n, sample in enumerate(line[9:]):
if sample == orig:
line[9+n] = replacement
if args["--prefix"]:
line[9:] = [args["--prefix"] + x for x in line[9:]]
if args["--suffix"]:
line[9:] = [x + args["--suffix"] for x in line[9:]]
print '\t'.join(line)
else:
print(line.strip())
def main(debug=None):
args = docopt(__doc__,
argv=debug,
options_first=False,
version=__version__)
def first(s):
return s[0].replace(".", "N")
firstv = np.vectorize(first)
v = vcf(args["<vcf>"])
if len(v.samples) <= 1:
exit(puts_err(
colored.red("\n\tVCF must have at least two samples.\n")))
if args["<region>"]:
variant_set = v(args["<region>"])
else:
variant_set = v
if args["fasta"] or args["tree"]:
"""
Generate an aligned fasta from a VCF file.
"""
gt_set = np.chararray((0, len(v.samples)))
gt_set = []
for line in variant_set:
if line.is_snp:
gt_set.append(firstv(line.gt_bases))
if len(gt_set) == 0:
exit(puts_err("No genotypes"))
gt_set = np.vstack(gt_set)
seqs = zip(v.samples, np.transpose(gt_set))
if args["fasta"]:
for sample, seq in seqs:
print(">" + sample)
print(''.join(seq))
elif args["tree"]:
"""
Generate a phylogenetic tree using an aligned fasta with muscle.
"""
# Check for muscle dependency
check_program_exists("muscle")
fasta = ""
with indent(4):
puts_err(colored.blue("\nGenerating Fasta\n"))
for sample, seq in seqs:
fasta += ">" + sample + "\n" + ''.join(seq) + "\n"
tree_type = "upgma" # default is upgma
if args["nj"]:
tree_type = "neighborjoining"
with indent(4):
puts_err(colored.blue("\nGenerating " + tree_type + " Tree\n"))
comm = ["muscle", "-maketree", "-in", "-", "-cluster", tree_type]
tree, err = Popen(comm, stdin=PIPE,
stdout=PIPE).communicate(input=fasta)
# output tree
print(tree)
if args["--plot"]:
from jinja2 import Template
import webbrowser
import tempfile
prefix = os.path.dirname(
os.path.abspath(
sys.modules['vcfkit'].__file__)) + "/static"
template = open(prefix + "/tree.html", 'r').read()
tree_template = Template(template)
html_out = tempfile.NamedTemporaryFile(suffix=".html",
delete=False)
with html_out as f:
tree = tree.replace("\n", "")
sample_len = len(v.samples)
f.write(tree_template.render(**locals()))
webbrowser.open("file://" + html_out.name)
""" Converts Genotype likelyhoods to phred scaled (PL) genotype likelyhoods. """
return -int(gl * 10)
debug = None
if len(sys.argv) == 1:
debug = ['primer', "--ref=WBcel235", "test.vcf.gz"]
if __name__ == '__main__':
# print debug
args = docopt(__doc__,
version='VCF-Toolbox v0.1',
argv=debug,
options_first=False)
# Locate Reference
v = vcf(args["<vcf>"])
format_added = False
if args["transfer-filter"]:
for line in v.output_raw():
line = line.strip()
if line.startswith("#CHROM"):
# Get Sample information and count
samples = line.strip().split("\t")[9:]
elif line.startswith("#"):
# Add Info line for het polarization flag
if line.startswith("##FORMAT") and format_added is False:
format_added = True
line = line + "\n##FORMAT=<ID=FT,Number=1,Type=String,Description=\"Genotype-level filter\">"
else:
line = line.split("\t")
FILTER = line[6]
def main(debug=None):
args = docopt(__doc__,
version='VCF-Toolbox v0.1',
argv=debug,
options_first=False)
module_path = os.path.split(os.path.realpath(__file__))[0]
handle = open(args["<seq>"], "rb")
reference = resolve_reference_genome(args["--ref"])
if args["<vcf>"]:
concordance = True
v = vcf(args["<vcf>"])
samples = v.samples
if args["--vcf-sites"] and args["<vcf>"] is None:
with indent(4):
exit(puts_err(colored.red("\nMust specify <vcf> with --vcf-sites\n")))
# Setup reference for blast call
b = blast(reference)
# Set file type:
sequence_file_type = seq_type(args["<seq>"])
# Output header
print("\t".join(blast_variant.output_order))
for record in SeqIO.parse(handle, sequence_file_type):
# Resolve sample within fasta line
sample = resolve_sample_from_line(samples, handle.name)
if not sample:
sample = resolve_sample_from_line(samples, record.name)
blast_results = b.blast_call(record)
classification = ""
for n, variant in enumerate(blast_results):
output_line = False
if variant is None:
puts_err(colored.red("No Results for " + sample + " " + record.description))
continue
if args["<vcf>"]:
if n == 0:
vcf_variants = []
for vcf_variant in v(variant.region()):
if sample:
gt = format_gt(vcf_variant.gt_bases[v.samples.index(sample)])
vcf_variants.append([vcf_variant.CHROM,
vcf_variant.POS,
gt,
vcf_variant.REF,
vcf_variant.ALT])
vcf_variant_positions = [x[0:2] for x in vcf_variants]
chrom_pos = variant.chrom_pos_allele()[0:2]
vcf_variant_match = [x for x in vcf_variants if x[0:2] == chrom_pos]
if vcf_variant_match:
vcf_variant_match = vcf_variant_match[0]
variant.vcf_gt = vcf_variant_match[2]
variant.REF = vcf_variant_match[3]
variant.ALT = ','.join(vcf_variant_match[4])
variant.fetch_variant_type()
if variant.REF == variant.seq_gt and variant.seq_gt == variant.vcf_gt:
variant.classification = "TN"
elif variant.REF != variant.seq_gt and variant.seq_gt == variant.vcf_gt:
variant.classification = "TP"
elif variant.REF == variant.seq_gt and variant.seq_gt != variant.vcf_gt:
variant.classification = "FP"
elif variant.REF != variant.seq_gt and variant.seq_gt != variant.vcf_gt:
variant.classification = "FN"
else:
variant.REF = ""
variant.ALT = ""
variant.fetch_variant_type()
variant.classification = ""
if args["--vcf-sites"] and variant.classification != "":
output_line = True
elif args["--all-sites"] is True:
output_line = True
else:
if args["--all-sites"]:
output_line = True
elif variant.is_variant:
output_line = True
if output_line:
variant.sample = sample
if record.description:
variant.description = record.description
else:
variant.description = os.path.split(handle.name)[1]
print '\t'.join([str(variant)])
tgt = '/'.join([gt_dict[int(x)] for x in re.split("[\|/]", val["GT"])])
return tgt
debug = None
if len(sys.argv) == 1:
debug = ['vcf2sql', "test.vcf.gz"]
if __name__ == '__main__':
args = docopt(__doc__,
argv=debug,
options_first=False)
timestamp = datetime.datetime.now()
module_path = os.path.split(os.path.realpath(__file__))[0]
v = vcf(args["<vcf>"])
vcf_safe = v.filename.replace(".", "_")
tsv_out = v.filename.replace("vcf", "tsv").replace(
"bcf", "tsv").replace(".gz", "") + ".gz"
info_cols = [map(autoconvert, list(x)) + ["INFO"]
for x in r_info.findall(v.raw_header)]
format_cols = [map(autoconvert, list(x)) + ["FORMAT"]
for x in r_format.findall(v.raw_header)]
if args["--simple"]:
info_cols = [x for x in info_cols if x[0] in simple_fields]
format_cols = [x for x in format_cols if x[0] in simple_fields]
if args["sqlite"]:
db = SqliteDatabase(args["--db"])
def main(debug = None):
args = docopt(__doc__,
version='VCF-Toolbox v0.1',
argv = debug,
options_first=False)
if args["--soft-filter"] and not args["--mode"]:
exit(message("Must Specify --mode with soft-filter"))
v = vcf(args["<vcf>"])
n_samples = len(v.samples) * 1.0
f = {}
filter_s = [x for x in args.values() if x in ["REF","HET","ALT","MISSING"]][0]
# Filter by rate or by number?
if args["--min"]:
direction = "<"
if int(float(args["--min"])) != float(args["--min"]):
filter_key_min = "r_" + filter_s
filter_val_min = float(args["--min"])
filter_type = "FREQUENCY"
else:
filter_key_min = filter_s
filter_val_min = int(float(args["--min"]))
filter_type = "COUNT"
filter_value = filter_val_min
if args["--max"]:
direction = ">"
if int(float(args["--max"])) != float(args["--max"]):
filter_key_max = "r_" + filter_s
filter_val_max = float(args["--max"])
filter_type = "FREQUENCY"
else:
filter_key_max = filter_s
filter_val_max = int(float(args["--max"]))
filter_type = "COUNT"
filter_value = filter_val_max
# Output header
header = v.raw_header.splitlines()
for n, i in enumerate(header):
if i.startswith("##FILTER") and args["--soft-filter"]:
filter_name = args["--soft-filter"]
filter_line = """##FILTER=<ID={filter_name},Description="Apply filter if {filter_type}({filter_s}) {direction} {filter_value}">""".format(**locals())
header.insert(n+1, filter_line)
break
header = '\n'.join(header) + "\n"
sys.stdout.write(header)
for line in v:
filtered = False
f["ALT"] = line.num_hom_alt
f["HET"] = line.num_het
f["REF"] = line.num_hom_ref
f["MISSING"] = int(n_samples - line.num_called)
f["r_ALT"] = f["ALT"] / n_samples
f["r_HET"] = f["HET"] / n_samples
f["r_REF"] = f["REF"] / n_samples
f["r_MISSING"] = f["MISSING"] / n_samples
if args["--min"]:
if f[filter_key_min] < filter_val_min:
filtered = True
if args["--max"]:
if f[filter_key_max] > filter_val_max:
filtered = True
if args["--soft-filter"]:
line = str(line).split("\t")
if args["--mode"] == "x":
line[6] = "PASS"
if filtered is False:
sys.stdout.write('\t'.join(line))
else:
if args["--mode"] == "+":
if line[6] == "PASS":
line[6] = ""
line[6] = ';'.join([line[6]] + [args["--soft-filter"]]).strip(";")
elif args["--mode"] == "x":
line[6] = args["--soft-filter"]
sys.stdout.write('\t'.join(line))
elif filtered is False:
sys.stdout.write(str(line))
def main(debug=None):
args = docopt(__doc__,
argv=debug,
options_first=False,
version=__version__)
def first(s):
return s[0].replace(".", "N")
firstv = np.vectorize(first)
v = vcf(args["<vcf>"])
if len(v.samples) <= 1:
exit(puts_err(colored.red("\n\tVCF must have at least two samples.\n")))
if args["<region>"]:
variant_set = v(args["<region>"])
else:
variant_set = v
if args["fasta"] or args["tree"]:
"""
Generate an aligned fasta from a VCF file.
"""
gt_set = np.chararray((0,len(v.samples)))
gt_set = []
for line in variant_set:
if line.is_snp:
gt_set.append(firstv(line.gt_bases))
if len(gt_set) == 0:
exit(puts_err("No genotypes"))
gt_set = np.vstack(gt_set)
seqs = zip(v.samples, np.transpose(gt_set))
if args["fasta"]:
for sample, seq in seqs:
print(">" + sample)
print(''.join(seq))
elif args["tree"]:
"""
Generate a phylogenetic tree using an aligned fasta with muscle.
"""
# Check for muscle dependency
check_program_exists("muscle")
fasta = ""
with indent(4):
puts_err(colored.blue("\nGenerating Fasta\n"))
for sample, seq in seqs:
fasta += ">" + sample + "\n" + ''.join(seq) + "\n"
tree_type = "upgma" # default is upgma
if args["nj"]:
tree_type = "neighborjoining"
with indent(4):
puts_err(colored.blue("\nGenerating " + tree_type + " Tree\n"))
comm = ["muscle", "-maketree", "-in", "-", "-cluster", tree_type]
tree, err = Popen(comm, stdin=PIPE, stdout=PIPE).communicate(input=fasta)
# output tree
print(tree)
if args["--plot"]:
from jinja2 import Template
import webbrowser
import tempfile
prefix = os.path.dirname(os.path.abspath(sys.modules['vcfkit'].__file__)) + "/static"
template = open(prefix + "/tree.html",'r').read()
tree_template = Template(template)
html_out = tempfile.NamedTemporaryFile(suffix=".html", delete=False)
with html_out as f:
tree = tree.replace("\n", "")
sample_len = len(v.samples)
f.write(tree_template.render(**locals()))
webbrowser.open("file://" + html_out.name)
def main(debug=None):
args = docopt(__doc__,
argv=debug,
options_first=False,
version=__version__)
module_path = os.path.split(os.path.realpath(__file__))[0]
v = vcf(args["<vcf>"])
samples = v.samples
_ROOT = os.path.split(os.path.dirname(vk.__file__))[0]
if args["fasta"] or args["tree"]:
"""
Generate an aligned fasta from a VCF file.
"""
seqs = {}
for sample in samples:
seqs[sample] = []
for line in v:
if line.is_snp:
non_missing = [x.replace(".", "-") for x in line.gt_bases]
sample_gt = zip(samples, [x[-1] for x in non_missing])
for sample, gt in sample_gt:
seqs[sample].append(gt)
if not args["tree"]:
for sample, seq in seqs.items():
print(">" + sample)
print(''.join(seq))
elif args["tree"]:
"""
Generate a phylogenetic tree using an aligned fasta with muscle.
"""
# Check for muscle dependency
check_program_exists("muscle")
fasta = ""
with indent(4):
puts_err(colored.blue("\nGenerating Fasta\n"))
for sample, seq in seqs.items():
fasta += ">" + sample + "\n" + ''.join(seq) + "\n"
tree_type = "upgma" # default is upgma
if args["nj"]:
tree_type = "neighborjoining"
with indent(4):
puts_err(colored.blue("\nGenerating " + tree_type + " Tree\n"))
comm = ["muscle", "-maketree", "-in", "-", "-cluster", tree_type]
tree, err = Popen(comm, stdin=PIPE,
stdout=PIPE).communicate(input=fasta)
print(tree)
if args["--plot"]:
from jinja2 import Template
import webbrowser
import tempfile
# R code for plotting here!
prefix = _ROOT + "/static"
tree_template = Template(
open(_ROOT + "/static/tree.html", 'r').read())
html_out = tempfile.NamedTemporaryFile(suffix=".html",
delete=False)
with html_out as f:
tree = tree.replace("\n", "")
sample_len = len(samples)
f.write(tree_template.render(**locals()))
# print html_out.name
webbrowser.open("file://" + html_out.name)
def main(debug=None):
args = docopt(__doc__,
version='VCF-Toolbox v0.1',
argv=debug,
options_first=False)
module_path = os.path.split(os.path.realpath(__file__))[0]
handle = open(args["<seq>"], "rb")
reference = resolve_reference_genome(args["--ref"])
if args["<vcf>"]:
concordance = True
v = vcf(args["<vcf>"])
samples = v.samples
if args["--vcf-sites"] and args["<vcf>"] is None:
with indent(4):
exit(
puts_err(
colored.red("\nMust specify <vcf> with --vcf-sites\n")))
# Setup reference for blast call
b = blast(reference)
# Set file type:
sequence_file_type = seq_type(args["<seq>"])
# Output header
print("\t".join(blast_variant.output_order))
for record in SeqIO.parse(handle, sequence_file_type):
# Resolve sample within fasta line
sample = resolve_sample_from_line(samples, handle.name)
if not sample:
sample = resolve_sample_from_line(samples, record.name)
blast_results = b.blast_call(record)
classification = ""
for n, variant in enumerate(blast_results):
output_line = False
if variant is None:
puts_err(
colored.red("No Results for " + sample + " " +
record.description))
continue
if args["<vcf>"]:
if n == 0:
vcf_variants = []
for vcf_variant in v(variant.region()):
if sample:
gt = format_gt(
vcf_variant.gt_bases[v.samples.index(sample)])
vcf_variants.append([
vcf_variant.CHROM, vcf_variant.POS, gt,
vcf_variant.REF, vcf_variant.ALT
])
vcf_variant_positions = [
x[0:2] for x in vcf_variants
]
chrom_pos = variant.chrom_pos_allele()[0:2]
vcf_variant_match = [
x for x in vcf_variants if x[0:2] == chrom_pos
]
if vcf_variant_match:
vcf_variant_match = vcf_variant_match[0]
variant.vcf_gt = vcf_variant_match[2]
variant.REF = vcf_variant_match[3]
variant.ALT = ','.join(vcf_variant_match[4])
variant.fetch_variant_type()
if variant.REF == variant.seq_gt and variant.seq_gt == variant.vcf_gt:
variant.classification = "TN"
elif variant.REF != variant.seq_gt and variant.seq_gt == variant.vcf_gt:
variant.classification = "TP"
elif variant.REF == variant.seq_gt and variant.seq_gt != variant.vcf_gt:
variant.classification = "FP"
elif variant.REF != variant.seq_gt and variant.seq_gt != variant.vcf_gt:
variant.classification = "FN"
else:
variant.REF = ""
variant.ALT = ""
variant.fetch_variant_type()
variant.classification = ""
if args["--vcf-sites"] and variant.classification != "":
output_line = True
elif args["--all-sites"] is True:
output_line = True
else:
if args["--all-sites"]:
output_line = True
elif variant.is_variant:
output_line = True
if output_line:
variant.sample = sample
if record.description:
variant.description = record.description
else:
variant.description = os.path.split(handle.name)[1]
print '\t'.join([str(variant)])
