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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
import operator
import random
import pysam
from jinja2 import Environment, FileSystemLoader, select_autoescape
    from shlex import quote
except ImportError:
    from pipes import quote
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))
    >>> flatten(0.987654321)
    '0.987654'
    >>> flatten(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
        flat = str(value)
    return flat
def zip_lists(value):
    >>> zip_lists([[0,1,2], [3,4,5]])
    ['0 3', '1 4', '2 5']
    return [flatten(i, sep=" ") for i in zip(*value)]
def get_format_fields(ids, variant):
        ids (list) - list of FORMAT field IDs, e.g. ['AS', 'AP', 'DHFFC']
        variant (pysam.libcbcf.VariantRecord)
    returns:
        list
    fields = list()
    for i in ids:
        fields.append(
            ["%s=%s" % (i, flatten(j.get(i, ""))) for j in variant.samples.values()]
    return zip_lists(fields)
def get_format_title(samples, ids, variant):
        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
        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(
    priority=["exon", "gene", "transcript", "cds"],
    no_hit="intergenic",
    fix_chr=True,
        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
        overlaps = set(
            [i.split("\t")[2].lower() for i in tabix.fetch(chrom, start, end)]
    except IndexError:
        # probably not a gff or gtf
        print("Invalid annotation file specified for --gff")
        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,
                    priority,
                    no_hit,
                    False,
    except:
        # bad regions
        print(
            "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
        # 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 not variant_sample 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):
            sys.exit("List of sample IDs does not match list of alignment files.")
        for i, p in enumerate(bams):
            names[name_list[i]] = p
        for p in bams:
            b = pysam.AlignmentFile(p)
            try:
                names[b.header["RG"][0]["SM"]] = p
            except:
                sys.exit(
                    "No RG field in alignment file "
                    + ". \nInclude ordered list of sample IDs to avoid this error"
    return names
def tryfloat(v):
        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'"))
    >>> check_expr({"CSQ": "asdfHIGHasdf", "DHFC": 1.1}, to_exprs("CSQ contains 'HIGH' & DHFC < 0.5"))
    >>> check_expr({"CSQ": "asdfHIGHasdf", "DHFC": 1.1}, to_exprs("CSQ contains 'HIGH' & DHFC < 1.5"))
    >>> check_expr({"smoove_gene": "asdf"}, to_exprs("smoove_gene exists"))
    >>> check_expr({"smooe_gene": "asdf"}, to_exprs("smoove_gene exists"))
    >>> check_expr({"smoove_gene": ""}, to_exprs("smoove_gene exists"))
    # a single set of exprs must be "anded"
    for name, fcmp, val in expr:
        # NOTE: asking for a missing annotation will return false.
        if not name 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):
    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):
    if chrom in important_regions:
        for region in important_regions[chrom]:
            region_st, region_end = [int(x) for x in region.split("_")]
                region_st <= start <= region_end
                or region_st <= end <= region_end
                or start <= region_st <= end
                return True
    return False
def cram_input(bams):
    for bam in bams:
        if bam.endswith(".cram"):
            return True
    return False
def vcf(parser):
    Generate commands for plotting variants from VCF, create html for showing them
    args, pass_through_args = parser.parse_known_args()
    if args.dn_only and not args.ped:
        sys.exit("Missing --ped, required when using --dn_only")
    if cram_input(args.bams):
        if "-r" not in pass_through_args and not "--reference" in pass_through_args:
            sys.exit(
                "ERROR: missing reference file required for CRAM. "
                + "Use -r option. (Run `samplot.py -h` for more help)"
    vcf = pysam.VariantFile(args.vcf)
    vcf_samples = vcf.header.samples
    vcf_samples_set = set(vcf_samples)
    vcf_samples_list = list(vcf_samples)
    annotations = None
    if args.gff:
        annotations = pysam.TabixFile(args.gff)
    filters = [to_exprs(f) for f in args.filter]
    ped_samples = parse_ped(args.ped, vcf_samples)
    # this is empty unless we have a sample with both parents defined.
    dn_row = get_dn_row(ped_samples)
    if not os.path.exists(args.out_dir):
        os.makedirs(args.out_dir)
    names_to_bams = get_names_to_bams(args.bams, args.sample_ids)
    important_regions = None
    if args.important_regions:
        important_regions = read_important_regions(args.important_regions)
    tabledata = []
    # user requested FORMAT fields to add to plot title
    format_field_ids = None
    if args.format:
        format_field_ids = args.format.split(",")
    out_file = open(args.command_file, "w")
    for var_count,variant in enumerate(vcf):
        translocation_chrom = None
        svtype = variant.info.get("SVTYPE", "SV")
        if svtype in ["BND","TRA"]:
            try:
                translocation_chrom = variant.info.get("CHR2")
            except:
        if args.important_regions:
            if not var_in_important_regions(
                important_regions, variant.chrom, variant.start, variant.stop
                if args.debug:
                    print("Skipping {} at {}:{}-{}, outside important_regions coordinates".format(
                        svtype, variant.chrom, variant.start, variant.stop),file=sys.stderr)
                continue
        if svtype in ("INS"):
            if args.debug:
                print("Skipping {} at {}:{}-{}, INS type not supported".format(
                    svtype, variant.chrom, variant.start, variant.stop),file=sys.stderr)
            continue
        if args.max_mb and (variant.stop - variant.start > args.max_mb * 1000000):
            if args.debug:
                print("Skipping {} at {}:{}-{}, variant length greater than max_mb".format(
                    svtype, variant.chrom, variant.start, variant.stop),file=sys.stderr)
            continue
        if (variant.stop - variant.start < args.min_bp) and translocation_chrom is None:
            if args.debug:
                print("Skipping {} at {}:{}-{}, variant length shorter than min_bp".format(
                    svtype, variant.chrom, variant.start, variant.stop),file=sys.stderr)
            continue
        gts = [s.get("GT", (None, None)) for s in variant.samples.values()]
        if sum(None in g for g in gts) >= args.min_call_rate * len(vcf_samples):
            if args.debug:
                print("Skipping {} at {}:{}-{}, call rate of variant below min_call_rate".format(
                    svtype, variant.chrom, variant.start, variant.stop),file=sys.stderr)
            continue
        if args.max_hets:
            # requisite hets/hom-alts
            if sum(sum(x) >= 1 for x in gts if not None in x) > args.max_hets:
                if args.debug:
                    print("Skipping {} at {}:{}-{}, more than max_hets heterozygotes".format(
                        svtype, variant.chrom, variant.start, variant.stop),file=sys.stderr)
                continue
        if not any(sum(x) > 0 for x in gts if not None in x):
            if args.debug:
                print("Skipping {} at {}:{}-{}, no samples have non-ref genotypes".format(
                    svtype, variant.chrom, variant.start, variant.stop),file=sys.stderr)
            continue
        test_idxs = [i for i, gt in enumerate(gts) if not None in gt and sum(gt) > 0]
        test_samples = [
            s for i, s in enumerate(variant.samples.values()) if i in test_idxs
        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:
            continue
        is_dn = []
        # 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.
        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:
            if args.debug:
                print("Skipping {} at {}:{}-{}, no samples with matched alignment files have variant".format(
                    svtype, variant.chrom, variant.start, variant.stop),file=sys.stderr)
            continue
        bams = [names_to_bams[s] for s in variant_samples]
        if dn_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
                    not sample.mom.id in test_sample_names
                    and not sample.dad.id in test_sample_names
                    is_dn.append(sample.id)
        if len(is_dn) <= 0 and args.dn_only:
            if args.debug:
                print("Skipping {} at {}:{}-{}, dn_only selected and no de novos found".format(
                    svtype, variant.chrom, variant.start, variant.stop),file=sys.stderr)
            continue
        # save these for the html.
        n_samples = len(variant_samples)
        # semi-colon delimited eases CSV export from HTML
        sample_str = ";".join(variant_samples)
        # dict holding sample to FORMAT title string
        plot_titles = dict()
        if format_field_ids:
            format_attrs = get_format_title(vcf_samples_list, format_field_ids, variant)
            plot_titles = make_plot_titles(variant_samples, format_attrs)
        # try to get family members
        if args.ped is not None:
            # do DN samples first so we can see parents.
            for variant_sample in is_dn + [
                x for x in variant_samples if not x in is_dn
                s = ped_samples.get(variant_sample)
                if s is None:
                    continue
                    s.mom is not None
                    and not s.mom.id in variant_samples
                    and s.mom.id in vcf_samples_set
                    variant_samples.append("mom-of-%s[%s]" % (variant_sample, s.mom.id))
                    bams.append(names_to_bams[s.mom.id])
                    s.dad is not None
                    and not s.dad.id in variant_samples
                    and s.dad.id in vcf_samples_set
                    variant_samples.append("dad-of-%s[%s]" % (variant_sample, s.dad.id))
                    bams.append(names_to_bams[s.dad.id])
                for kid in s.kids:
                    if not kid.id 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 args.max_hets:
                        if len(bams) > 1.5 * args.max_hets:
                if args.max_hets:
                    if len(bams) > 1.5 * args.max_hets:
        elif args.min_entries and len(bams) < args.min_entries:
            # extend with some controls:
            hom_ref_idxs = [
                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 = args.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]
        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, translocation_chrom
        if dn_row != "":
            data_dict["dn"] = ",".join(is_dn)
        if translocation_chrom is None:
            template = "{svtype}_{chrom}_{start}_{end}.{itype}"
        else:
            template = "{svtype}_{chrom}_{start}_{chrom2}_{end}.{itype}"
        fig_path = os.path.join(
            args.out_dir,
            template.format(itype=args.output_type, **data_dict),
        tabledata.append(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
        if variant.stop - variant.start > 2000:
        if variant.stop - variant.start > 10000:
        if variant.stop - variant.start > 20000:
        if args.max_entries:
            bams = bams[: args.max_entries]
            variant_samples = variant_samples[: args.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)
        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}")
        start = variant.start
        stop = variant.stop
        start2 = None
        stop2 = None
        if translocation_chrom is not None:
            template += " -c {chrom2} -s {start2} -e {end2}"
            start2 = stop
            stop2 = start2 + 1
            stop = start + 1
        template += "\n"
        out_file.write(
            template.format(
                extra_args=" ".join(pass_through_args),
                bams=" ".join(bams),
                titles=" ".join(title_list),
                cipos=cipos,
                ciend=ciend,
                svtype="-t " + svtype if svtype != "SV" else "",
                fig_path=fig_path,
                chrom=variant.chrom,
                start=start,
                end=stop,
                downsample=args.downsample,
                chrom2=translocation_chrom,
                start2=start2,
                end2=stop2,
    if args.debug:
        print("VCF entry count:",var_count+1 ,file=sys.stderr)
    if args.command_file:
        out_file.close()
    # 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=args.out_dir), "w") as fh:
        print(
            html_template.render(
                data=tabledata,
                plot_type=args.output_type,
                gff="true" if annotations else "false",
                denovo="true" if dn_row else "false",
            file=fh,
    if not args.manual_run:
        import subprocess
        # make runnable and then run it
        os.chmod(args.command_file, 0o755)
        subprocess.call(os.path.join(".", args.command_file), shell=True)
        os.remove(args.command_file)
def add_vcf(parent_parser):
    """Defines allowed arguments for samplot's vcf plotter
    import doctest
    parser = parent_parser.add_parser(
        "vcf",
        formatter_class=argparse.ArgumentDefaultsHelpFormatter,
        help="Generates commands to plot images with `samplot plot`,"
        + " using VCF file to define regions",
    if len(sys.argv) > 1 and sys.argv[1] == "test":
        r = doctest.testmod()
        print(r)
        sys.exit(r.failed)
    parser.add_argument("--vcf", "-v", help="VCF file containing structural variants")
    parser.add_argument(
        "-d", "--out-dir", help="path to write output PNGs", default="samplot-out"
    parser.add_argument("--ped", help="path ped (or .fam) file")
    parser.add_argument(
        "--dn_only",
        help="plots only putative de novo variants (PED file required)",
        action="store_true",
    parser.add_argument(
        "--min_call_rate",
        type=float,
        help="only plot variants with at least this call-rate",
        default=0.95,
    parser.add_argument(
        "--filter",
        action="append",
        help="simple filter that samples"
        + " must meet. Join multiple filters with '&' and specify --filter multiple times for 'or'"
        + " e.g. DHFFC < 0.7 & SVTYPE = 'DEL'",
        default=[],
    parser.add_argument(
        "-O",
        "--output_type",
        choices=("png", "pdf", "eps", "jpg"),
        help="type of output figure",
        default="png",
    parser.add_argument(
        "--max_hets",
        type=int,
        help="only plot variants with at most this many heterozygotes",
        required=False,
    parser.add_argument(
        "--min_entries",
        type=int,
        help="try to include homref samples as controls to get this many samples in plot",
        default=6,
    parser.add_argument(
        "--max_entries",
        type=int,
        help="only plot at most this many heterozygotes",
        default=10,
    parser.add_argument(
        "--max_mb",
        type=int,
        help="skip variants longer than this many megabases",
    parser.add_argument(
        "--min_bp",
        type=int,
        help="skip variants shorter than this many bases",
        default=20,
    parser.add_argument(
        "--important_regions",
        help="only report variants that overlap regions in this bed file",
        required=False,
    parser.add_argument(
        "-b",
        "--bams",
        type=str,
        nargs="+",
        help="Space-delimited list of BAM/CRAM file names",
        required=True,
    parser.add_argument(
        "--sample_ids",
        type=str,
        nargs="+",
        help="Space-delimited list of sample IDs, must have same order as BAM/CRAM file names. BAM RG tag required if this is omitted.",
        required=False,
    parser.add_argument(
        "--command_file",
        help="store commands in this file.",
        default="samplot_vcf_cmds.tmp",
        required=False,
    parser.add_argument(
        "--format",
        default="AS,AP,DHFFC",
        help="comma separated list of FORMAT fields to include in sample plot title",
    parser.add_argument(
        "--gff",
        help="genomic regions (.gff with .tbi in same directory) used when building HTML table and table filters",
    parser.add_argument(
        "--downsample", help="Number of normal reads/pairs to plot", default=1, type=int
    parser.add_argument(
        "--manual_run",
        help="don't auto-run the samplot plot commands (command_file will be deleted)",
        default=False,
        action="store_true",
    parser.add_argument(
        "--debug",
        help="prints out the reason each skipped variant entry is skipped",
        default=False,
        action="store_true",
    parser.set_defaults(func=vcf)
if __name__ == "__main__":
    print("Run as samplot module with `samplot vcf`")
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