build_pop.py

#!/usr/bin/env python3

import sys
import os
import shutil
import random
import argparse
import traceback
from collections import OrderedDict
import vcf
from Bio import SeqIO
import tempfile
from pysam import tabix_compress, tabix_index, VariantFile
from lib.variants_simulator import VariantsSimulator
from lib.exceptions import InputException, ExecException
import multiprocessing
import subprocess


class Print:
    def __init__(self, stdout=None, stderr=None):
        self.stdout = stdout
        self.stderr = stderr
        if self.stdout is not None and os.path.isfile(self.stdout):
            os.remove(self.stdout)
        if self.stderr is not None and os.path.isfile(self.stderr):
            os.remove(self.stderr)

    def out(self, message):
        if self.stdout is not None:
            with open(self.stdout, "a") as stdout_f:
                print(message, file=stdout_f)
        else:
            print(message, file=sys.stdout)

    def err(self, message):
        if self.stderr is not None:
            with open(self.stderr, "a") as stderr_f:
                print(message, file=stderr_f)
        else:
            print(message, file=sys.stderr)


def check_min_size(value):
    ivalue = int(value)
    if ivalue <= 1:
        raise argparse.ArgumentTypeError("%s is an invalid size value (>= 1)" % value)
    return ivalue


def parse_args():
    """
    Parse script arguments
    :return: argparse arguments object
    """
    parser = argparse.ArgumentParser(description='Generate simulated populations with SV',
                                     formatter_class=argparse.ArgumentDefaultsHelpFormatter)
    parser.add_argument("-n", "--nb-inds", help="Number of individuals to generate", type=int)
    parser.add_argument("-r", "--reference", help="Reference genome", required=True)
    parser.add_argument("-ns", "--nstretches", help="N-stretches positions bed file", required=False)
    parser.add_argument("-s", "--sv-list", help="File containing the SVs", required=False)
    parser.add_argument("-c", "--coverage", help="Coverage of reads", default=15, type=int)
    parser.add_argument("-o", "--output-dir", help="Output directory", default="res")
    parser.add_argument("-e", "--force-outputdir", help="Delete output directory before start, if already exists",
                        action='store_const', const=True, default=False)
    parser.add_argument("-f", "--force-polymorphism", help="Force polymorphism for each SV", action='store_const',
                        const=True, default=False)
    parser.add_argument("-a", "--haploid", help="Make a haploid genome, instead of diploid one", action="store_const",
                        const=True, default=False)
    parser.add_argument("-pd", "--proba-del", help="Probabilty to have a deletion", type=float, default=0.000001)
    parser.add_argument("-pi", "--proba-inv", help="Probablity to have an insertion", type=float, default=0.000001)
    parser.add_argument("-l", "--read-len", help="Generate reads having a length of LEN", type=int, default=100)
    parser.add_argument("-m", "--insert-len-mean", help="Generate inserts (fragments) having an average length of LEN",
                        type=int, default=300)
    parser.add_argument("-v", "--insert-len-sd", help="Set the standard deviation of the insert (fragment) length (%%)",
                        type=int, default=30)
    parser.add_argument("-q", "--quiet", help="Don't ask anything, choose default answer instead", action="store_const",
                        const=True, default=False)
    parser.add_argument("-md", "--min-deletions", help="Minimum of deletions to generate (>=1)", default=0,
                        type=check_min_size)
    parser.add_argument("-mi", "--min-inversions", help="Minimum of inversions to generate (>=1)", default=0,
                        type=check_min_size)
    parser.add_argument("--max-try", help="Maximum of tries", default=10, type=check_min_size)
    parser.add_argument("-t", "--threads", help="Number of threads", default=multiprocessing.cpu_count(), type=int)
    parser.add_argument("-g", "--genotypes", help="Position of SV with genotypes of individuals")

    args = parser.parse_args()

    if args.nb_inds is None and args.genotypes is None:
        parser.error("--nb-inds parameter is required (except if --genotypes parameter is given)")

    if args.proba_del > 1 or args.proba_del < 0:
        parser.error("Probability of deletions must be between 0 and 1")

    if args.proba_inv > 1 or args.proba_inv < 0:
        parser.error("Probability of inversions must be between 0 and 1")

    if args.proba_del + args.proba_inv > 1:
        parser.error("Sum of inversions and deletions probabilities must be lesser than 1")

    return args


def _allele(frequency):
    """
    Get randomly an allele, given a frequency
    :param frequency: frequency of the allele {float}
    :return: allele randomly choosen {0 or 1}
    """
    return 1 if random.uniform(0, 1) < frequency else 0


def _get_genotypes_for_inds(nb_inds, haploid, freq):
    """
    Get genotypes for each individual
    :param nb_inds: number of individuals {int}
    :param haploid: is the genome hamploid {bool}
    :param freq: frequency of the allele {float}
    :return: list of genotypes, vcf data {list}
    """
    all_genotypes = []
    genotypes_row = []
    for i in range(1, nb_inds + 1):
        if not haploid:
            genotype = str(_allele(freq)) + "/" + str(_allele(freq))
        else:
            genotype = str(_allele(freq))
        genotype_data = vcf.model._Call(None, "indiv" + str(i), vcf.model.make_calldata_tuple("GT")(GT=genotype))
        genotypes_row.append(genotype_data)
        all_genotypes.append(genotype)
    return all_genotypes, genotypes_row


def _svsort(sv, chrm, genotypes_for_inds):
    """
    Function to sort regions
    :param sv: the variant
    :param chrm: chromosome {str}
    :param genotypes_for_inds: dictionary of genotypes for each individual
    """
    return int(genotypes_for_inds[chrm][sv]["start"])


def _build_vcf_header(vcf_file, prg_path, tmp_dir, nb_inds):
    """
    Build header of the VCF file
    :param vcf_file: vcf file full path name {str}
    :param prg_path: program path {str}
    :param tmp_dir: temporary directory {str}
    :param nb_inds: number of individuals {int}
    """
    try:
        with open(os.path.join(prg_path, "template.vcf"), "r") as template:
            try:
                with open(vcf_file, "w") as my_template:
                    for line in template:
                        if line[:6] == "#CHROM":
                            line = line.replace("\n", "")
                            for i in range(0, nb_inds):
                                line += "\tindiv" + str(i+1)
                            line += "\n"
                        my_template.write(line)
            except IOError:
                raise ExecException("ERROR: unable to create template file \"{0}\" in temp dir.".
                                format(os.path.join(tmp_dir, "template.vcf")))
    except IOError:
        raise ExecException("ERROR: template file not found in program directory.")


def build_genotypes_vcf_list(deletions: dict, inversions: dict, output_vcf, haploid, force_polymorphism, nb_inds,
                             tmp_dir, prg_path):
    """
    Build VCF file describing genotypes for each individual (and the associated python dictionary)
    :param deletions: deletions description {dict}
    :param inversions: inversions description {dict}
    :param output_vcf: output VCF file full path name {str}
    :param haploid: is haploid {bool}
    :param force_polymorphism: force polymorphism {bool}
    :param nb_inds: number of individuals {int}
    :param tmp_dir: temporary directory {str}
    :param prg_path: program path {str}
    :return: dictionary of genotypes for each variant for each dictionary {OrderedDict}
    """
    genotypes_for_inds_DEL = OrderedDict()
    # { chr: { id_indiv: {start: #start, end: #end, genotypes: [[0,1],[1,1],...], ...}, # ...}

    vcf_file = os.path.join(tmp_dir, "template.vcf")

    # Build VCF header:
    _build_vcf_header(vcf_file, prg_path, tmp_dir, nb_inds)

    records = []

    # Deletions:
    for chrm, deletes in deletions.items():
        for delete in deletes:
            if chrm not in genotypes_for_inds_DEL:
                genotypes_for_inds_DEL[chrm] = {}
            genotypes_for_inds_DEL[chrm][delete["name"]] = {"start": delete["start"], "end": delete["end"], "genotypes": []}

            # Get genotypes:
            all_genotypes, genotypes = [], []
            if force_polymorphism:
                polymorph = False
                while not polymorph:
                    all_genotypes, genotypes = _get_genotypes_for_inds(nb_inds, haploid, delete["freq"])
                    polymorph = len(set(all_genotypes)) > 1
            else:
                all_genotypes, genotypes = _get_genotypes_for_inds(nb_inds, haploid, delete["freq"])
            genotypes_for_inds_DEL[chrm][delete["name"]]["genotypes"] = [x.split("/") for x in all_genotypes]

            info = {"END": delete["end"], "AF": delete["freq"]}
            vcf_record = vcf.model._Record(chrm, delete["start"], delete["name"], "N", [vcf.model._SV("DEL")], ".",
                                           ".", info, "GT", [0], genotypes)
            records.append(vcf_record)

    # Inversions:
    genotypes_for_inds_INV = OrderedDict()
    for chrm, the_inversions in inversions.items():
        for inversion in the_inversions:
            if chrm not in genotypes_for_inds_INV:
                genotypes_for_inds_INV[chrm] = {}
            genotypes_for_inds_INV[chrm][inversion["name"]] = {"start": inversion["start"], "end": inversion["end"],
                                                           "genotypes": []}
            # Get genotypes:
            all_genotypes, genotypes = [], []
            if force_polymorphism:
                polymorph = False
                while not polymorph:
                    all_genotypes, genotypes = _get_genotypes_for_inds(nb_inds, haploid, inversion["freq"])
                    polymorph = len(set(all_genotypes)) > 1
            else:
                all_genotypes, genotypes = _get_genotypes_for_inds(nb_inds, haploid, inversion["freq"])
            genotypes_for_inds_INV[chrm][inversion["name"]]["genotypes"] = [x.split("/") for x in all_genotypes]

            info = {"END": inversion["end"], "AF": inversion["freq"]}
            vcf_record = vcf.model._Record(chrm, inversion["start"], inversion["name"], "N", [vcf.model._SV("INV")],
                                           ".", ".", info, "GT", [0], genotypes)
            records.append(vcf_record)

    records.sort(key=lambda r: (r.CHROM, r.start))

    with open(output_vcf, "w") as o_vcf:
        vcf_reader = vcf.Reader(filename=vcf_file)
        vcf_writer = vcf.Writer(o_vcf, vcf_reader)
        for record in records:
            vcf_writer.write_record(record)
        vcf_writer.close()

    tabix_compress(output_vcf, output_vcf + ".gz", True)
    tabix_index(output_vcf + ".gz", force=True, preset="vcf")

    os.remove(output_vcf)

    return genotypes_for_inds_DEL, genotypes_for_inds_INV


def load_genotypes_from_file(genotypes_file):
    variants = VariantFile(genotypes_file)
    genotypes_for_inds_DEL = {}
    genotypes_for_inds_INV = {}
    nb_inds = 0
    for variant in variants:
        chrm = variant.chrom
        id_v = variant.id
        start = variant.start
        end = variant.stop
        type_v = variant.alts[0][1:-1]
        samples = variant.samples
        gt = [list(map(str, samples[x]["GT"])) for x in samples]
        genotypes_for_inds = None
        if type_v == "DEL":
            genotypes_for_inds = genotypes_for_inds_DEL
        elif type_v == "INV":
            genotypes_for_inds = genotypes_for_inds_INV
        else:
            print("ERROR: Variant type not supported: %s. Ignoring this line..." % type_v)
        if genotypes_for_inds is not None:
            if chrm not in genotypes_for_inds:
                genotypes_for_inds[chrm] = {}
            genotypes_for_inds[chrm][id_v] = {
                "start": start,
                "end": end,
                "genotypes": gt
            }
            nb_inds = len(gt)
    return nb_inds, genotypes_for_inds_DEL, genotypes_for_inds_INV


def _compute_keeped_genomic_regions(svs, svs_infos, haploid):
    """
    Get list of all regions keeped (not deleted)
    :param svs: list of variants (deletions) {list}
    :param svs_infos: infos of variants {dict}
    :param haploid: is haploid {bool}
    :return: regions for each individuals {OrderedDict}, the last position for each region {OrderedDict}
    """
    regions = OrderedDict()
    current_region_pointer = OrderedDict()
    for svs_i in svs:
        i = 0
        for genotypes in svs_infos[svs_i]["genotypes"]:
            if i not in regions:
                regions[i] = {}
                current_region_pointer[i] = {}
            for j in range(0, 2 if not haploid else 1):  # For each chromosome of the diploid genome, or the chromosome
                # of the haploid genome
                if j not in regions[i]:
                    regions[i][j] = []
                    current_region_pointer[i][j] = "0"
                if svs_infos[svs_i]["genotypes"][i][j] == "1":
                    regions[i][j].append([current_region_pointer[i][j], svs_infos[svs_i]["start"]])
                    current_region_pointer[i][j] = svs_infos[svs_i]["end"]
            i += 1
    return regions, current_region_pointer


def _build_fastas_deletions(chrm, regions, current_region_pointer, output_dir, fasta_orig_chr, last_nt):
    """
    Build fasta files
    :param chrm:
    :param regions:
    :param current_region_pointer:
    :param output_dir:
    :param fasta_orig_chr:
    :param last_nt:
    :return:
    """
    n = 0
    fastas = []
    for indiv, chrs_dips in regions.items():
        id_chrs = list(chrs_dips.keys())
        id_chrs = sorted(id_chrs)
        c = 0
        fastas.append([])
        for id_chr in id_chrs:
            chr_dip = chrs_dips[id_chr]  # SVs for each diploid chromosome
            logs_regions = []  # Store logs

            # Build FASTA and store logs:

            fasta = ""
            last_one = 0
            for chr_region in chr_dip:
                fasta += fasta_orig_chr[n][c][int(chr_region[0]):int(chr_region[1])]
                logs_regions.append("\t".join(str(x) for x in chr_region))
                last_one = int(chr_region[1])
            if last_one < last_nt:
                logs_regions.append("\t".join([str(current_region_pointer[indiv][id_chr]), str(last_nt)]))
                fasta += fasta_orig_chr[n][c][int(current_region_pointer[indiv][id_chr]):last_nt]
            fastas[n].append(fasta)

            # Write logs
            try:
                with open(os.path.join(output_dir, "indiv" + str(indiv + 1) + ".regions.log"), "a") as log_handle:
                    log_handle.write(chrm + "_" + str(id_chr) + "\t")
                    log_handle.write("\n\t".join(logs_regions))
                    log_handle.write("\n")
            except IOError:
                raise ExecException("ERROR: unable to write log file: \"{0}\"".
                                    format(os.path.join(output_dir, "indiv" + str(indiv + 1) + ".regions.log")))
            c += 1
        n += 1
    return fastas


def _build_fastas_inversions(fasta_orig_chrm: dict, genotypes_for_inds: dict, nb_inds, haploid):
    fastas = []
    for j in range(0, nb_inds):
        fastas.append([fasta_orig_chrm] if haploid else [fasta_orig_chrm, fasta_orig_chrm])
    for inv_name, props in genotypes_for_inds.items():
        i = 0
        for genotype in props["genotypes"]:
            for k in range(0, len(genotype)):
                if genotype[k] == "1":
                    start = int(props["start"])
                    end = int(props["end"])
                    o_id = fastas[i][k].id
                    o_name = fastas[i][k].name
                    o_description = fastas[i][k].description
                    fastas[i][k] = fastas[i][k][:start] + fastas[i][k][start:end].reverse_complement() + \
                                   fastas[i][k][end:]
                    fastas[i][k].id = o_id
                    fastas[i][k].name = o_name
                    fastas[i][k].description = o_description
            i += 1
    return fastas


def _write_fastas(fastas, output_dir):
    for indiv, chrs_dips in zip(range(0, len(fastas)), fastas):
        for id_chr, fasta in zip(range(0, len(chrs_dips)), chrs_dips):
            try:
                with open(os.path.join(output_dir, "indiv" + str(indiv + 1) + "_chr_" + str(id_chr) + ".fasta"),
                          "a") as output_handle:
                    SeqIO.write(fasta, output_handle, "fasta")
            except IOError:
                raise ExecException("ERROR: unable to write \"{0}\" file.".
                                    format(os.path.join(output_dir, "indiv" + str(indiv + 1) + "_chr_" + str(id_chr) +
                                                        ".fasta")))


def build_fastas_chromosomes(reference, genotypes_for_inds_DEL, genotypes_for_inds_INV, haploid, output_dir, nb_inds,
                             printer):
    printer.out("BUILD FASTA GENOME FOR EACH INDIVIDUAL...\n")
    fasta_orig = SeqIO.index(reference, "fasta")

    # First, inversions (does not change coordinates):
    printer.out("STARTING WITH INVERSIONS...")
    fastas_by_chrm = {}
    for chrm, svs_infos in genotypes_for_inds_INV.items():
        printer.out("PROCESSING CHROMOSOME {0}...\n".format(chrm))
        svs = list(svs_infos.keys())
        fastas_by_chrm[chrm] = _build_fastas_inversions(fasta_orig[chrm], genotypes_for_inds_INV[chrm], nb_inds, haploid)

    printer.out("STARTING WITH DELETIONS...")
    # Then, deletions:
    for chrm, svs_infos in genotypes_for_inds_DEL.items():
        printer.out("PROCESSING CHROMOSOME {0}...\n".format(chrm))

        svs = list(svs_infos.keys())
        svs = sorted(svs, key=lambda x:_svsort(x, chrm, genotypes_for_inds_DEL))

        if chrm in fastas_by_chrm:
            fastas_orig_chr = fastas_by_chrm[chrm]
        else:  # Build data as _build_fastas_inversions does
            fastas_orig_chr = []
            for i in range(0, nb_inds):
                fastas_orig_chr.append([fasta_orig[chrm]] if haploid else [fasta_orig[chrm], fasta_orig[chrm]])
        last_nt = len(fastas_orig_chr[0][0])-1

        # Compute keeped genomic regions for each diploid chromosome:
        regions, current_region_pointer = _compute_keeped_genomic_regions(svs, svs_infos, haploid)

        # Build FASTA of each diploid/haploid chromosome:
        fastas_by_chrm[chrm] = _build_fastas_deletions(chrm, regions, current_region_pointer, output_dir, fastas_orig_chr, last_nt)

    printer.out("WRITING FASTAS...")
    for chrm, fastas in fastas_by_chrm.items():
        _write_fastas(fastas, output_dir)
    printer.out("")


def generate_samples_fastq(haploid, nb_inds, output_dir, coverage, read_len, insert_len_mean, insert_len_sd,
                           prg_path, threads, stdout, stderr):

    # Generate reads for all individuals:
    cmd = [prg_path + "/pirs/pirs", "simulate", "-z", "-x", str(coverage), "-d", "-B",
           prg_path + "/pirs/Profiles/Base-Calling_Profiles/humNew.PE100.matrix.gz", "-I",
           prg_path + "/pirs/Profiles/InDel_Profiles/phixv2.InDel.matrix", "-l", str(read_len), "-m",
           str(insert_len_mean), "-v", str(insert_len_sd),
           "-G", prg_path + "/pirs/Profiles/GC-depth_Profiles/humNew.gcdep_100.dat", "-t", str(threads), "-o"]
    if haploid:
        cmd.remove("-d")
    for i in range(1, nb_inds+1):
        cmd_full = cmd + [output_dir, "-s", "indiv%d" % i]
        prefix_fasta = os.path.join(output_dir, "indiv" + str(i))
        chr0 = prefix_fasta + "_chr_0.fasta"
        if not haploid:
            chr1 = prefix_fasta + "_chr_1.fasta"
            cmd_full += [chr0, chr1]
        else:
            cmd_full.append(chr0)
        subprocess.call(cmd_full, stdout=open(stdout, "a") if stdout is not None else None,
                        stderr=open(stderr, "a") if stderr is not None else None)


def confirm(deletions: dict, inversions: dict, variants: dict, printer: Print, ask=True):
    # Deletions:
    nb_dels = 0
    variants_del = sorted(variants["DEL"], key=lambda x: x["min"])
    variants_del_counts = OrderedDict()
    variants_del_counts_chr = {}
    for variant in variants_del:
        variants_del_counts["{0}-{1}".format(variant["min"], variant["max"])] = 0
    for chrm, deletes in deletions.items():
        nb_dels_chr = len(deletes)
        nb_dels += nb_dels_chr
        variants_del_counts_chr[chrm] = nb_dels_chr
        for delete in deletes:
            v_len = delete["length"]
            for variant in variants_del:
                if variant["min"] < v_len <= variant["max"]:
                    variants_del_counts["{0}-{1}".format(variant["min"], variant["max"])] += 1
                    break
    printer.out("We generate {0} deletion variants.".format(nb_dels))
    if nb_dels > 0:
        printer.out("Ranges:")
        for v_range, v_count in variants_del_counts.items():
            printer.out("\t- Range {0}: {1}".format(v_range, v_count))
        printer.out("Chromosomes:")
        for chrm in sorted(list(variants_del_counts_chr.keys())):
            printer.out("\t- {0}: {1}".format(chrm, variants_del_counts_chr[chrm]))
    printer.out("")

    # inversions:
    nb_invs = 0
    variants_inv = sorted(variants["INV"], key=lambda x: x["min"])
    variants_inv_counts = OrderedDict()
    variants_inv_counts_chr = {}
    for variant in variants_inv:
        variants_inv_counts["{0}-{1}".format(variant["min"], variant["max"])] = 0
    for chrm, the_inversions in inversions.items():
        nb_invs_chr = len(the_inversions)
        nb_invs += nb_invs_chr
        variants_inv_counts_chr[chrm] = nb_invs_chr
        for inversion in the_inversions:
            v_len = inversion["length"]
            for variant in variants_inv:
                if variant["min"] < v_len <= variant["max"]:
                    variants_inv_counts["{0}-{1}".format(variant["min"], variant["max"])] += 1
                    break
    printer.out("We generate {0} inversion variants.".format(nb_invs))
    if nb_invs > 0:
        printer.out("Ranges:")
        for v_range, v_count in variants_inv_counts.items():
            printer.out("\t- Range {0}: {1}".format(v_range, v_count))
        printer.out("Chromosomes:")
        for chrm in sorted(list(variants_inv_counts_chr.keys())):
            printer.out("\t- {0}: {1}".format(chrm, variants_inv_counts_chr[chrm]))
    printer.out("")

    # Confirm:
    if ask:
        return input("Continue [Y/n]? ") in ["y", "Y", ""]
    return True


def init(output_dir, force_outputdir, sv_list, nstretches, nb_inds, reference, proba_del, proba_inv, haploid,
         force_polymorphism, coverage, read_len, insert_len_mean, insert_len_sd, threads, genotypes=None,
         min_deletions=1, min_inversions=1, max_try=10, quiet=True, stdout=None, stderr=None):

    printer = Print(stdout=stdout, stderr=stderr)

    if os.path.isdir(output_dir):
        if force_outputdir:
            shutil.rmtree(output_dir)
        else:
            printer.err("Error: output directory {0} already exists.".format(output_dir))
            return 1
    elif os.path.isfile(output_dir):
        printer.err("Error: unable to create output directory {0}: file exists.".format(output_dir))
        return 1

    if nb_inds is not None and nb_inds < 2:
        printer.err("nb-inds must be at least 2")
        return 1

    if not os.path.isfile(reference + ".fai"):
        os.system("samtools faidx " + reference)

    tmp_dir = tempfile.mkdtemp()

    prg_path = os.path.dirname(os.path.realpath(__file__))

    os.mkdir(output_dir)

    ############################
    # Define fixed files names #
    ############################
    output_vcf = os.path.join(output_dir, "genotypes.vcf")

    ################
    # Launch steps #
    ################

    deletions = None
    inversions = None
    sv_sim = None

    if genotypes is None:
        printer.out("GENERATE RANDOM DELETIONS VARIANTS...\n")
        try:
            nb_deletions = -1  # To allow 0 deletions
            nb_inversions = -1  # To allow 0 inversions
            nb_try = 0
            sv_sim = VariantsSimulator(sv_list, nstretches, threads, stdout, stderr)
            printer.out("Try to generate at least %s deletions and %s inversions..." % (min_deletions, min_inversions))
            max_del = 0
            max_inv = 0
            while (nb_deletions < min_deletions or nb_inversions < min_inversions) and nb_try < max_try:
                printer.out("\nTry {0} / {1}...".format(nb_try + 1, max_try))
                nb_deletions, deletions, nb_inversions, inversions = sv_sim.get_random_variants(proba_del, proba_inv,
                                                                                                reference)
                max_del = max(max_del, nb_deletions)
                max_inv = max(max_inv, nb_inversions)
                sv_sim.print_flush()
                nb_try += 1
            if nb_deletions < min_deletions:
                printer.err("\nUnable to generate %s deletions. Try to reduce size of deletions or increase "
                                     "general probability to have a deletion." % min_deletions)
                printer.out("\nMaximum of each event: %d deletions, %d inversions." % (max_del, max_inv))
                return 1
            if nb_inversions < min_inversions:
                printer.err("\nUnable to generate %s inversions. Try to reduce size of inversions or increase "
                            "general probability to have an inversion." % min_inversions)
                printer.out("\nMaximum of each event: %d deletions, %d inversions." % (max_del, max_inv))
                return 1
            printer.out("")
        except InputException as e:
            printer.err(e)
            return 1
        except IOError as e:
            printer.err(e)
            return 1
        except Exception:
            printer.err(traceback.format_exc())
            return 1
        printer_confirm = printer
        ok = True
        if genotypes is None:
            if quiet:
                printer_confirm = Print(stdout=os.path.join(output_dir, "confirm.txt"), stderr=stderr)
                ok = confirm(deletions, inversions, sv_sim.variants, printer_confirm, False)
            else:
                ok = confirm(deletions, inversions, sv_sim.variants, printer_confirm)
        if ok:
            try:
                if genotypes is None:
                    printer.out("GENERATE SUMMARY VCF FILE...\n")
                    genotypes_for_inds_DEL, genotypes_for_inds_INV = \
                        build_genotypes_vcf_list(deletions, inversions, output_vcf, haploid, force_polymorphism, nb_inds,
                                                 tmp_dir, prg_path)
                else:
                    nb_inds, genotypes_for_inds_DEL, genotypes_for_inds_INV = load_genotypes_from_file(genotypes)
                    if nb_inds < 2:
                        printer.err("nb-inds must be at least 2")
                        return 1
                build_fastas_chromosomes(reference, genotypes_for_inds_DEL, genotypes_for_inds_INV, haploid, output_dir,
                                         nb_inds, printer)
                printer.out("GENERATE RANDOM READS FOR EACH INDIVIDUAL FROM GENOME...\n")
                generate_samples_fastq(haploid, nb_inds, output_dir, coverage, read_len, insert_len_mean,
                                       insert_len_sd, prg_path, threads, stdout, stderr)
                printer.out("DONE!\n")
            except ExecException as e:
                printer.err(e)
                return 1
            except Exception:
                printer.err(traceback.format_exc())
                return 1
        else:
            printer.out("Aborted!\n")
    return 0


def main():
    args = parse_args()
    init(**{k: v for k, v in vars(args).items() if k in init.__code__.co_varnames})


if __name__ == '__main__':
    sys.exit(main())