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1380 lines (1220 loc) · 39.5 KB
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#!/usr/bin/env python
# -*- coding: utf-8 -*-
"""
Create samplot vcf commands to execute and generate
companion HTML image browser.
Note: additional arguments are passed through to samplot plot
"""
from __future__ import print_function
import argparse
from collections import Counter
import logging
import operator
import os
import random
import sys
import re
import pysam
from jinja2 import Environment, FileSystemLoader, select_autoescape
try:
from shlex import quote
except ImportError:
from pipes import quote
from .samplot import add_plot
logger = logging.getLogger(__name__)
cmp_lookup = {
">": operator.gt, # e.g. DHFC < 0.5
"<": operator.lt,
"<=": operator.le,
">=": operator.ge,
"==": operator.eq,
"contains": operator.contains, # e.g. CSQ contains HIGH
"exists": lambda a, b: True, # e.g. exists smoove_gene
}
class Sample(object):
__slots__ = [
"family_id",
"id",
"paternal_id",
"maternal_id",
"mom",
"dad",
"kids",
"i",
]
def __init__(self, line):
toks = line.rstrip().split()
self.family_id = toks[0]
self.id = toks[1]
self.paternal_id = toks[2]
self.maternal_id = toks[3]
self.kids = []
self.i = -1 # index in the vcf.
def __repr__(self):
return "Sample(id:{id},paternal_id:{pid},maternal_id:{mid})".format(
id=self.id, pid=self.paternal_id, mid=self.maternal_id
)
def flatten(value, sep=","):
"""
>>> flatten([1,2,3,4])
'1,2,3,4'
>>> flatten((5,6))
'5,6'
>>> flatten(0.987654321)
'0.987654'
>>> flatten(7)
'7'
>>> flatten("flatten")
'flatten'
"""
flat = None
# tuple or list
if isinstance(value, tuple) or isinstance(value, list):
flat = sep.join([str(i) for i in value])
# reformats long float values
elif isinstance(value, float):
flat = "%.6f" % (value,)
# string and int
else:
flat = str(value)
return flat
def get_format_fields(ids, variant):
"""
args:
ids (list) - list of FORMAT field IDs, e.g. ['AS', 'AP', 'DHFFC']
variant (pysam.libcbcf.VariantRecord)
returns:
list
"""
sample_format = []
for i, sample_fields in enumerate(variant.samples.values()):
for field_id in ids:
sample_field_val = flatten(sample_fields.get(field_id, ""))
if sample_field_val:
if len(sample_format) < i + 1:
sample_format.append("")
else:
sample_format[i] += " "
sample_format[i] += "{}={}".format(field_id, sample_field_val)
return sample_format
def get_format_title(samples, ids, variant):
"""
args:
samples (list) - list of sample IDs in order of VCF annotations
ids (list) - list of FORMAT field IDs, e.g. ['AS', 'AP', 'DHFFC']
variant (pysam.libcbcf.VariantRecord)
returns:
dict
"""
fields = get_format_fields(ids, variant)
return dict(zip(samples, fields))
def make_plot_titles(samples, attr_values):
"""
keeping this method separate in the event we add more things to the title
args:
samples (list) - list of sample IDs
attr_values (str) - string of VCF FORMAT values
returns:
dict
>>> make_plot_titles(
['s1', 's2', 's3'],
{
's1': 'AS=0 AP=0',
's2': 'AS=0 AP=1',
's3': 'AS=1 AP=1'
}
)
{
's1': "'s1 AS=0 AP=0'",
's2': "'s2 AS=0 AP=1'",
's3': "'s3 AS=1 AP=1'"
}
"""
plot_titles = dict()
for sample in samples:
if sample in attr_values:
plot_titles[sample] = quote("%s %s" % (sample, attr_values[sample]))
return plot_titles
def get_overlap(
tabix,
chrom,
start,
end,
priority=["exon", "gene", "transcript", "cds"],
no_hit="intergenic",
fix_chr=True,
):
"""
args:
tabix (pysam.libctabix.TabixFile) - open TabixFile
chrom (str)
start (int)
end (int)
priority (Optional[list]) - order of preferred region annotation
no_hit (Optional[str]) - use this annotation if no matches among priority
fix_chr (Optional[bool]) - try to fetch a region using both
non-'chr' and 'chr' prefix on failures
returns:
str
"""
overlaps = None
try:
overlaps = set(
[i.split("\t")[2].lower() for i in tabix.fetch(chrom, start, end)]
)
except IndexError:
# probably not a gff3
logger.warning("Invalid annotation file specified for --gff3")
overlaps = None
except ValueError:
if fix_chr:
# try removing chr
if chrom.startswith("chr"):
overlaps = get_overlap(
tabix, chrom[3:], start, end, priority, no_hit, False
)
# or adding chr
else:
overlaps = get_overlap(
tabix,
"chr{chrom}".format(chrom=chrom),
start,
end,
priority,
no_hit,
False,
)
except:
# bad regions
logger.warning(
"Error fetching {chrom}:{start}-{end}".format(
chrom=chrom, start=start, end=end
)
)
overlaps = None
overlap = ""
if overlaps:
for feature in priority:
if feature in overlaps:
overlap = feature
break
else:
# fetching overlaps failed
overlap = "unknown"
if not overlap and no_hit:
overlap = no_hit
return overlap
def parse_ped(path, vcf_samples=None):
if path is None:
return {}
samples = []
look = {}
for line in open(path):
samples.append(Sample(line))
look[samples[-1].id] = samples[-1]
for s in samples:
s.dad = look.get(s.paternal_id)
if s.dad is not None:
s.dad.kids.append(s)
s.mom = look.get(s.maternal_id)
if s.mom is not None:
s.mom.kids.append(s)
# match these samples to the ones in the VCF.
if vcf_samples is not None:
result = []
for i, variant_sample in enumerate(vcf_samples):
if variant_sample not in look:
continue
result.append(next(s for s in samples if s.id == variant_sample))
result[-1].i = i
samples = result
return {s.id: s for s in samples}
def get_names_to_bams(bams, name_list=None):
"""
get mapping from names (read group samples) to bam paths)
this is useful because the VCF has the names and we'll want the bam paths
for those samples
if name_list is passed in as a parameter those will be used instead
"""
names = {}
if name_list:
if len(name_list) != len(bams):
logger.error("List of sample IDs does not match list of alignment files.")
sys.exit(1)
for i, p in enumerate(bams):
names[name_list[i]] = p
else:
for p in bams:
b = pysam.AlignmentFile(p)
# TODO - catch specific exception
try:
names[b.header["RG"][0]["SM"]] = p
except Exception as e:
logger.error("No RG field in alignment file {}".format(p))
logger.error("Include ordered list of sample IDs to avoid this error")
print(e, file=sys.stderr)
sys.exit(1)
return names
def tryfloat(v):
try:
return float(v)
except:
return v
def to_exprs(astr):
"""
an expr is just a 3-tuple of "name", fn, value"
e.g. "DHFFC", operator.lt, 0.7"
>>> to_exprs("DHFFC < 0.5 & SVTYPE == 'DEL'")
[('DHFFC', <built-in function lt>, 0.5), ('SVTYPE', <built-in function eq>, 'DEL')]
>>> to_exprs("CSQ contains 'HIGH'")
[('CSQ', <built-in function contains>, 'HIGH')]
"""
astr = (x.strip() for x in astr.strip().split("&"))
result = []
for a in astr:
a = [x.strip() for x in a.split()]
if len(a) == 2:
assert a[1] == "exists", ("bad expression", a)
a.append("extra_arg")
assert len(a) == 3, ("bad expression", a)
assert a[1] in cmp_lookup, (
"comparison:"
+ a[1]
+ " not supported. must be one of:"
+ ",".join(cmp_lookup.keys())
)
result.append((a[0], cmp_lookup[a[1]], tryfloat(a[2].strip("'").strip('"'))))
return result
def check_expr(vdict, expr):
"""
>>> check_expr({"CSQ": "asdfHIGHasdf"},
to_exprs("CSQ contains 'HIGH'"))
True
>>> check_expr({"CSQ": "asdfHIGHasdf", "DHFC": 1.1},
to_exprs("CSQ contains 'HIGH' & DHFC < 0.5"))
False
>>> check_expr({"CSQ": "asdfHIGHasdf", "DHFC": 1.1},
to_exprs("CSQ contains 'HIGH' & DHFC < 1.5"))
True
>>> check_expr({"smoove_gene": "asdf"},
to_exprs("smoove_gene exists"))
True
>>> check_expr({"smooe_gene": "asdf"},
to_exprs("smoove_gene exists"))
False
>>> check_expr({"smoove_gene": ""},
to_exprs("smoove_gene exists"))
True
"""
# a single set of exprs must be "anded"
for name, fcmp, val in expr:
# NOTE: asking for a missing annotation will return false.
if name not in vdict:
return False
if not fcmp(vdict[name], val):
return False
return True
def make_single(vdict):
"""
>>> d = {"xx": (1,)}
>>> make_single(d)
{'xx': 1}
"""
for k in vdict.keys():
if isinstance(vdict[k], tuple) and len(vdict[k]) == 1:
vdict[k] = vdict[k][0]
return vdict
def get_dn_row(ped_samples):
for s in ped_samples.values():
if s.mom is not None and s.dad is not None:
return '{title:"de novo", field:"dn"}'
return ""
def read_important_regions(bedfilename):
if not bedfilename:
return None
important_regions = {}
with open(bedfilename, "r") as bedfile:
for line in bedfile:
pos_fields = line.strip().split()
region_string = "_".join(pos_fields[1:3])
if pos_fields[0] not in important_regions:
important_regions[pos_fields[0]] = []
important_regions[pos_fields[0]].append(region_string)
return important_regions
def var_in_important_regions(important_regions, chrom, start, end, svtype):
if not important_regions:
# if no important regions are set all locations are valid
return True
if chrom in important_regions:
for region in important_regions[chrom]:
region_st, region_end = [int(x) for x in region.split("_")]
if (
region_st <= start <= region_end
or region_st <= end <= region_end
or start <= region_st <= end
):
return True
logger.debug(
"Skipping {} at {}:{}-{}, outside important_regions coordinates".format(
svtype, chrom, start, end
)
)
return False
def cram_input(bams):
for bam in bams:
if bam.endswith(".cram"):
return True
return False
def above_call_rate(gts, sample_count, min_call_rate, svtype, chrom, start, end):
"""
skips variants with call rate below min_call_rate if set
"""
if not min_call_rate:
return True
call_rate = (sample_count - sum(None in g for g in gts)) / sample_count
if min_call_rate and (call_rate < min_call_rate):
logger.debug(
(
"Skipping {} at {}:{}-{}, call rate of variant "
+ "({}) below min_call_rate"
).format(svtype, chrom, start, end, call_rate),
)
return False
return True
def below_max_hets(gts, max_hets, svtype, chrom, start, end):
"""
skips variants with more than max_hets heterozygotes
if max_hets is set
"""
if not max_hets:
return False
# requisite hets/hom-alts
het_count = sum(sum(x) >= 1 for x in gts if None not in x)
if het_count > max_hets:
logger.debug(
"Skipping {} at {}:{}-{}, more than max_hets heterozygotes".format(
svtype, chrom, start, end
)
)
return False
return True
def no_variant_found(gts, svtype, chrom, start, end):
"""
skips variants with no non-ref samples
"""
if not any(sum(x) > 0 for x in gts if None not in x):
logger.debug(
"Skipping {} at {}:{}-{}, no samples have non-ref genotypes".format(
svtype, chrom, start, end
)
)
return True
return False
def get_plottable_samples(
gts, variant, plot_all, filters, svtype, chrom, start, end,
):
"""
gets the samples and indices for all those which need to be plotted,
which means passing filters and, if not plot_all, having a nonref genotype
"""
if plot_all:
test_idxs = [i for i, gt in enumerate(gts)]
if len(test_idxs) == 0:
logger.debug(
"No samples found for {} at {}:{}-{}".format(svtype, chrom, start, end)
)
else:
test_idxs = [i for i, gt in enumerate(gts) if None not in gt and sum(gt) > 0]
if len(test_idxs) == 0:
logger.debug(
"No non-reference samples found for {} at {}:{}-{}".format(
svtype, chrom, start, end
)
)
test_samples = [s for i, s in enumerate(variant.samples.values()) if i in test_idxs]
# apply filters if set
if len(filters) == 0:
idxs = test_idxs
else:
idxs = []
odict = make_single(dict(variant.info.items()))
for i, ts in enumerate(test_samples):
vdict = odict.copy()
vdict.update(make_single(dict(ts.items())))
if any(check_expr(vdict, fs) for fs in filters):
idxs.append(test_idxs[i])
if len(idxs) == 0:
logger.debug(
"No samples pass filters for {} at {}:{}-{}".format(
svtype, chrom, start, end
)
)
return idxs, test_samples
def get_variant_samples(
idxs, vcf_samples, names_to_bams, svtype, chrom, start, end,
):
"""
gets the samples that need to be plotted and have alignment files assigned
"""
variant_samples = []
for i in idxs:
if vcf_samples[i] in names_to_bams:
variant_samples.append(vcf_samples[i])
if len(variant_samples) == 0:
logger.debug(
(
"Skipping {} at {}:{}-{}, no plottable samples "
+ "with matched alignment files"
).format(svtype, chrom, start, end),
)
return variant_samples
def get_denovos(
denovo_row,
test_samples,
variant_samples,
ped_samples,
svtype,
chrom,
start,
end,
dn_only,
):
"""
we call it a de novo if the sample passed the filters but the mom and
dad had homref genotypes before filtering.
so stringent filtering on the kid and lenient on parents.
"""
denovo_svs = []
if denovo_row != "":
test_sample_names = {s.name for s in test_samples}
for variant_sample in variant_samples:
sample = ped_samples[variant_sample]
if sample.mom is None or sample.dad is None:
continue
if (
sample.mom.id not in test_sample_names
and sample.dad.id not in test_sample_names
):
denovo_svs.append(sample.id)
if len(denovo_svs) <= 0 and dn_only:
logger.debug(
"Skipping {} at {}:{}-{}, dn_only selected and no de novos found".format(
svtype, chrom, start, end
),
)
return denovo_svs
def get_family_controls(
ped,
denovo_svs,
variant_samples,
ped_samples,
max_hets,
bams,
names_to_bams,
vcf_samples_set,
):
"""
tries to find family members to use as controls for putative de novos
"""
# do DN samples first so we can see parents.
# TODO also need to do the non-denovos as they seem to have been forgotten
for variant_sample in denovo_svs + [
x for x in variant_samples if x not in denovo_svs
]:
sample = ped_samples.get(variant_sample)
if sample is None:
continue
if (
sample.mom is not None
and sample.mom.id not in variant_samples
and sample.mom.id in vcf_samples_set
):
variant_samples.append("mom-of-%s[%s]" % (variant_sample, sample.mom.id))
bams.append(names_to_bams[sample.mom.id])
if (
sample.dad is not None
and sample.dad.id not in variant_samples
and sample.dad.id in vcf_samples_set
):
variant_samples.append("dad-of-%s[%s]" % (variant_sample, sample.dad.id))
bams.append(names_to_bams[sample.dad.id])
for kid in sample.kids:
if kid.id not in variant_samples and kid.id in vcf_samples_set:
variant_samples.append("kid-of-%s[%s]" % (variant_sample, kid.id))
bams.append(names_to_bams[kid.id])
if max_hets:
if len(bams) > 1.5 * max_hets:
break
if max_hets:
if len(bams) > 1.5 * max_hets:
break
return variant_samples, bams
def get_nonfamily_controls(
gts, vcf_samples, variant_samples, names_to_bams, min_entries, bams
):
# extend with some controls:
hom_ref_idxs = [
i for i, gt in enumerate(gts) if len(gt) == 2 and gt[0] == 0 and gt[1] == 0
]
if len(hom_ref_idxs) > 3:
random.shuffle(hom_ref_idxs)
hom_ref_samples = []
for i in hom_ref_idxs:
if vcf_samples[i] in names_to_bams:
hom_ref_samples.append(vcf_samples[i])
to_add_count = min_entries - len(bams)
bams.extend(names_to_bams[s] for s in hom_ref_samples[:to_add_count])
variant_samples += ["control-sample:" + s for s in hom_ref_samples[:to_add_count]]
return variant_samples, bams
def create_metadata(
variant,
translocation_chrom,
svtype,
sample_str,
n_samples,
annotations,
denovo_row,
denovo_svs,
):
"""
creates a dict with the info about the SV
that will be used in the website
"""
data_dict = {
"chrom": variant.chrom,
"chrom2": translocation_chrom,
"start": variant.start,
"end": variant.stop,
"svtype": svtype,
"svlength": variant.stop - variant.start,
"samples": sample_str,
"nsamples": n_samples,
}
if annotations:
data_dict["overlaps"] = get_overlap(
annotations, variant.chrom, variant.start, variant.stop
)
if denovo_row != "":
data_dict["dn"] = ",".join(denovo_svs)
return data_dict
def format_template(
variant,
data_dict,
max_entries,
bams,
variant_samples,
plot_titles,
out_dir,
output_type,
svtype,
downsample,
pass_through_args,
):
"""
formates the template string for generation of the final command
"""
if data_dict["chrom2"] is None:
figname_template = "{svtype}_{chrom}_{start}_{end}.{itype}"
else:
figname_template = "{svtype}_{chrom}_{start}_{chrom2}_{end}.{itype}"
fig_path = os.path.join(
out_dir, figname_template.format(itype=output_type, **data_dict),
)
if "CIPOS" in variant.info:
v = variant.info["CIPOS"]
cipos = "--start_ci '%s,%s'" % (abs(int(v[0])), abs(int(v[1])))
else:
cipos = ""
if "CIEND" in variant.info:
v = variant.info["CIEND"]
ciend = "--end_ci '%s,%s'" % (abs(int(v[0])), abs(int(v[1])))
else:
ciend = ""
# dynamically set Z to speed drawing and remove noise for larger events
z = 3
if variant.stop - variant.start > 2000:
z = 4
if variant.stop - variant.start > 10000:
z = 6
if variant.stop - variant.start > 20000:
z = 9
if data_dict["chrom2"] is None:
z = 3
if max_entries:
bams = bams[:max_entries]
variant_samples = variant_samples[:max_entries]
# update titles based on FORMAT fields requested
title_list = list()
for variant_sample in variant_samples:
if variant_sample in plot_titles:
title_list.append(plot_titles[variant_sample])
else:
title_list.append(variant_sample)
start = variant.start
stop = variant.stop
start2 = None
stop2 = None
if data_dict["chrom2"] is None:
template = (
"samplot plot {extra_args} -z {z} -n {titles} "
+ "{cipos} {ciend} {svtype} -c {chrom} -s {start} "
+ "-e {end} -o {fig_path} -d {downsample} -b {bams}"
)
else:
template = (
"samplot plot {extra_args} -z {z} -n {titles} "
+ "{cipos} {ciend} {svtype} -c {chrom} -s {start} "
+ "-e {end} -o {fig_path} -d {downsample} -b {bams} "
+ "-c {chrom2} -s {start2} -e {end2}"
)
# For interchromosomal variants the 2nd breakpoint position should
# not be encoded in INFO/END tag although some callers still do this.
# Currently it is unclear if there is a good replacement. Delly uses
# INFO/POS2 for this, GATK-SV uses INFO/END2, dysgu uses INFO/CHR2_POS.
# see: https://github.com/dellytools/delly/issues/159
# see: https://gatk.broadinstitute.org/hc/en-us/articles/5334587352219-How-to-interpret-SV-VCFs
# TODO - if the SV breakpoints are specified in the ALT field one
# could use this info to get the 2nd breakpoint position
if "POS2" in variant.info:
start2 = variant.info["POS2"]
elif "END2" in variant.info:
start2 = variant.info["END2"]
elif "CHR2_POS" in variant.info:
start2 = variant.info["CHR2_POS"]
else:
start2 = stop
# Update stop if INFO/END denotes the 2nd breakpoint
stop = start + 1
stop2 = start2 + 1
command = template.format(
extra_args=" ".join(pass_through_args),
bams=" ".join(bams),
titles=" ".join(title_list),
z=z,
cipos=cipos,
ciend=ciend,
svtype="-t " + svtype if svtype != "SV" else "",
fig_path=fig_path,
chrom=variant.chrom,
start=start,
end=stop,
downsample=downsample,
chrom2=data_dict["chrom2"],
start2=start2,
end2=stop2,
) + "\n"
return command
def write_site(table_data, out_dir, output_type, annotations, denovo_row):
# grab the template
env = Environment(
loader=FileSystemLoader(os.path.join(os.path.dirname(__file__), "templates")),
autoescape=select_autoescape(["html"]),
)
html_template = env.get_template("samplot_vcf.html")
# write index.html
with open("{out_dir}/index.html".format(out_dir=out_dir), "w") as fh:
print(
html_template.render(
data=table_data,
plot_type=output_type,
gff3="true" if annotations else "false",
denovo="true" if denovo_row else "false",
),
file=fh,
)
def is_simply_skippable(
variant,
vcf_samples,
gts,
important_regions,
max_mb,
min_bp,
min_call_rate,
max_hets,
plot_all,
translocation_chrom,
):
"""
checks several basic terms that could filter this variant out
specifically, if the variant type is INS,
or fails the important regions,
max_mb, min_bp, min_call_rate, or max_hets filters
"""
svtype = variant.info.get("SVTYPE", "SV")
# skips variants outside important regions if those are set
if not var_in_important_regions(
important_regions, variant.chrom, variant.start, variant.stop, svtype,
):
return True
# skips insertions
if svtype in ("INS"):
logger.debug(
"Skipping {} at {}:{}-{}, INS type not supported".format(
svtype, variant.chrom, variant.start, variant.stop
)
)
return True
# skips variants over max_mb length, if set
if max_mb and (variant.stop - variant.start > max_mb * 1000000):
logger.debug(
"Skipping {} at {}:{}-{}, variant length greater than max_mb".format(
svtype, variant.chrom, variant.start, variant.stop
)
)
return True
# skips variants under min_bp, if set
if (variant.stop - variant.start < min_bp) and translocation_chrom is None:
logger.debug(
"Skipping {} at {}:{}-{}, variant length shorter than min_bp".format(
svtype, variant.chrom, variant.start, variant.stop
)
)
return True
# skips variants if the call rate is below min_call_rate, if set
if not above_call_rate(
gts,
len(vcf_samples),
min_call_rate,
svtype,
variant.chrom,
variant.start,
variant.stop,
):
return True
# skips variants if there are more hets than max_hets, if set
if below_max_hets(
gts, max_hets, svtype, variant.chrom, variant.start, variant.stop
):
return True
# skips variants where no sample is non-ref, if plot_all is not set
if not plot_all:
if no_variant_found(
gts, svtype, variant.chrom, variant.start, variant.stop
):
return True
return False
def generate_commands(
vcf,
plot_all,
max_mb,
min_bp,
min_call_rate,
max_hets,
dn_only,
ped,
important_regions,
format_field_ids,
min_entries,
max_entries,
out_dir,
output_type,
downsample,
filters,
ped_samples,
denovo_row,
names_to_bams,
annotations,
pass_through_args,
):
"""
for every variant in vcf, process and output plot
command - if and only if it passes filters
"""
commands = []
table_data = []
vcf_samples = vcf.header.samples
vcf_samples_set = set(vcf_samples)
vcf_samples_list = list(vcf_samples)
vcf_stats = Counter()
# Check if VCF samples match BAMs
if vcf_samples_set != set(names_to_bams):
missing_vcf_samples = vcf_samples_set - set(names_to_bams)
missing_bam_samples = set(names_to_bams) - vcf_samples_set
logger.warning(
"VCF samples and BAMs do not match. "
"This may be due to different sample names in the VCF and BAMs."
)
if missing_vcf_samples:
logger.warning(
"VCF samples missing from BAMs: {}".format(", ".join(missing_vcf_samples))
)
if missing_bam_samples:
logger.warning(
"BAMs missing from VCF samples: {}".format(", ".join(missing_bam_samples))
)
for var_count, variant in enumerate(vcf):
translocation_chrom = None
svtype = variant.info.get("SVTYPE", "SV")
# get genotypes
gts = [s.get("GT", (None, None)) for s in variant.samples.values()]
# handle translocations
if svtype in ["BND", "TRA"]:
try:
translocation_chrom = variant.info.get("CHR2")
except (KeyError, ValueError) as e:
logger.debug(e)
logger.info(f"Translocation {svtype} on {variant.chrom}:{variant.start}"
"skipped due to missing CHR2 INFO field.")
if is_simply_skippable(
variant,
vcf_samples,
gts,
important_regions,
max_mb,
min_bp,
min_call_rate,
max_hets,
plot_all,
translocation_chrom,
):
vcf_stats["Skipped"] += 1
continue
# gets the list of samples to plot
# skips ref samples if plot_all isn't set
# and applies user-defined filters
idxs, test_samples = get_plottable_samples(
gts,
variant,
plot_all,
filters,
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