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#! /usr/bin/env python3
"""mergeSV : merge SV on the basis of their intervals
The merging is done by identifiying connected components in a graph.
The graph is constructing taking the SV a node and an edge connects two nodes
if the conresponding intervals exhibits a reciprocal overlap of a least R0%.
Additional constraints on the precision of breakpoints (left and right) can be specified.
Each connected component is termed a CNVR (Copy Number Variation Region)
and is associated to the corresponding CNVs.
"""
import argparse, sys
import glob
import vcf
import string
import re
from svreader.vcfwrapper import VCFReader
from svinterval import construct_overlap_graph, connected_components
import xlsxwriter
prg_path = os.path.dirname(os.path.realpath(__file__))
alphabet = list(string.ascii_uppercase)
xlsx_cols = alphabet.copy()
for i in alphabet:
for j in alphabet:
xlsx_cols.append(i + j)
def get_args():
parser = argparse.ArgumentParser(formatter_class=argparse.ArgumentDefaultsHelpFormatter, description="\
mergeIndividualSV \n \
description: Merge SV based on reciprocal overlap")
#parser.add_argument('-v', '--vcf', type=str, required=True, help='vcf file(s), comma-separated')
parser.add_argument('-v', '--vcf', type=str, required=True, help='folder containing all vcf results files')
parser.add_argument('-t', '--true-vcf', type=str, required=True, help='VCF file containing the simulated deletions')
parser.add_argument('-f', '--filtered-vcf', type=str, required=False,
help='VCF file containing the filtered results')
parser.add_argument('-g', '--genotypes', type=str, help="VCF file containing genotypes")
parser.add_argument('--overlap_cutoff', type=float, default=0.5, help='cutoff for reciprocal overlap')
parser.add_argument('--left_precision', type=int, default=-1, help='left breakpoint precision')
parser.add_argument('--right_precision', type=int, default=-1, help='right breakpoint precision')
parser.add_argument('-o', '--output', type=str, default="results.xlsx", help='output Excel file')
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# parse the arguments
args = parser.parse_args()
if args.left_precision == -1:
args.left_precision = sys.maxsize
if args.right_precision == -1:
args.right_precision = sys.maxsize
# send back the user input
return args
# A small wrapper to print to stderr
def eprint(*args, **kwargs):
print(*args, file=sys.stderr, **kwargs)
def to_vcf_record(cnv):
info = { "SVLEN" : cnv.length(),
"SVTYPE" : "DEL",
"END" : cnv.end,
"NUM_CNV" : cnv.NumCNV(),
"CNV":",".join(cnv.CNV()),
"CALLERS":",".join(cnv.Callers()),
"NUM_CALLERS":cnv.NumCallers(),
"CIPOS":cnv.cipos(),
"CIEND":cnv.ciend(),
"PRECISION":",".join(map(str,cnv.precision())),
"CALLERSVSAMPLES":",".join(cnv.CallersVsamples())
}
alt = [vcf.model._SV("DEL")]
if not cnv.IsPrecise():
info['IMPRECISE'] = True
else:
info['REPR_CNV'] = cnv.repr_cnv()
vcf_record = vcf.model._Record(cnv.chrom,
cnv.start,
cnv.name,
"N",
alt,
".",
".",
info,
"",
[0],
[])
return vcf_record
def passed_variant(record):
"""Did this variant pass?"""
return record.filter is None or len(record.filter) == 0 or "PASS" in record.filter
# --------------------------------------
# main function
def read_vcf_file(infile):
SVSet=[]
ids = []
for record in VCFReader(infile):
if not passed_variant(record):
continue
SVSet.append(record)
ids.append(record.id)
return SVSet, ids
def svsort(sv, records):
"""
Function to sort regions
"""
if records[sv]["start"] != "":
return int(records[sv]["start"])
first_tool = list(records[sv]["tools"].keys())[0]
return int(records[sv]["tools"][first_tool]["start"])
def get_gt(geno, true_gt):
if true_gt is not None:
if geno == "1/0" and true_gt == "0/1":
geno = "0/1"
elif geno == "0/1" and true_gt == "1/0":
geno = "1/0"
return geno
def get_max_len(cell, col, max_col_len):
return max(len(str(cell)), max_col_len[col] if col in max_col_len else 0)
def main():
# parse the command line args
args = get_args()
genotypes = {}
nb_inds = 0
if args.genotypes:
genotypes_raw = os.popen("zcat genotype_chr_chr12.vcf.gz " + args.true_vcf + " | " +
os.path.join(prg_path, "vawk") + " '{ print $3,S$*$GT}'").read().split("\n")
for gt in genotypes_raw:
if gt != "":
gt_l = gt.split("\t")
genotypes[gt_l[0]] = gt_l[1:]
nb_inds = len(gt_l[1:])
overlap_cutoff = args.overlap_cutoff
left_precision = args.left_precision
right_precision = args.right_precision
color_not_found = "#FE2E2E"
color_col_filter = "#BEF781"
color_is_kept = "#81F781"
color_false_positive = "#FE642E"
filenames = []
filenames += glob.glob(args.vcf + "/**/*.vcf", recursive=True)
filenames += glob.glob(args.vcf + "/**/*.vcf.gz", recursive=True)
true_ones = args.true_vcf
# Reading all the vcf files
SVSet=[]
for infile in filenames:
eprint(" Reading file %s" % (infile))
SVSet += read_vcf_file(infile)[0]
SVSet_to, true_ones_records = read_vcf_file(true_ones)
SVSet += SVSet_to
filtered_records = None
if args.filtered_vcf:
filtered_records = read_vcf_file(args.filtered_vcf)[1]
eprint("Computing Connected components")
construct_overlap_graph(SVSet,overlap_cutoff,left_precision,right_precision)
number = 1
records = {}
tools = set()
orphans = 0
for components in connected_components(SVSet):
names = []
results = {}
true_one = None
for node in components:
names.append(node.id)
if node.id in true_ones_records:
true_one = node.id
records[true_one] = {
"start": node.start,
"end": node.end,
"length": int(node.end) - int(node.start),
"tools": {},
"orphan": False,
"genotypes": genotypes[true_one] if true_one in genotypes else None
}
else:
tool_name = node.id.split("_")[0]
results[tool_name] = {
"start": node.start,
"end": node.end,
"length": int(node.end) - int(node.start),
"filtered": (node.id in filtered_records) if filtered_records is not None else False,
"genotypes": genotypes[node.id] if node.id in genotypes else None
}
tools.add(tool_name)
if true_one is not None:
records[true_one]["tools"] = results
else:
orphans += 1
records["orphan_" + str(orphans)] = {
"start": "",
"end": "",
"length": "",
"tools": results,
"orphan": True,
"genotypes": None
}
names.sort()
eprint("Group #%i: %s" % (number, ", ".join(names)))
number += 1
nb_records = len(records)
cells = {
"A1": {"text": "RESULTS", "format": {"bg_color": "#ffe856"}},
"A2": {"text": "Deletion", "format": {"bold": True}},
"A" + str(1+nb_records+3): {"text": "DIFFS", "format": {"bg_color": "#ffe856"}},
"A" + str(2+nb_records+3): {"text": "Deletion", "format": {"bold": True}}
}
cells_gt = {
"A1": {"text": "GENOTYPES", "format": {"bg_color": "#ffe856"}},
"A2": {"text": "Deletion", "format": {"bold": True}}
}
tools = sorted(tools)
nb_tools = len(tools)
headers = []
for tool in ["Real data"] + tools + (["Filtered results"] if filtered_records is not None else []):
#cells[xlsx_cols[i] + "1"] = cells[xlsx_cols[i] + str(1+nb_records+3)] = {"text": tool, "format": ""}
headers.append(tool)
l_format = {"bold": True}
if tool == "Filtered results":
l_format["bg_color"] = color_col_filter
cells[xlsx_cols[i] + "2"] = cells[xlsx_cols[i] + str(2+nb_records+3)] = {"text": "Start", "format": l_format}
max_col_len[i] = get_max_len("Start", i, max_col_len)
cells[xlsx_cols[i + 1] + "2"] = cells[xlsx_cols[i+1] + str(2+nb_records+3)] = {"text": "End",
"format": l_format}
max_col_len[i+1] = get_max_len("End", i+1, max_col_len)
cells[xlsx_cols[i + 2] + "2"] = cells[xlsx_cols[i+2] + str(2+nb_records+3)] = {"text": "Length",
"format": l_format}
max_col_len[i+2] = get_max_len("Length", i+2, max_col_len)
# Genotypes:
for k in range(0, nb_inds):
cells_gt[xlsx_cols[j+k] + "2"] = {"text": "INDIV_" + str(k+1), "format": {"bold": True}}
rec_keys = sorted(records.keys(), key=lambda x:svsort(x, records))
i = 3
for id in rec_keys:
record = records[id]
cells[xlsx_cols[0] + str(i)] = cells[xlsx_cols[0] + str(i+nb_records+3)] = {"text": id, "format": {}}
max_col_len[0] = get_max_len(id, 0, max_col_len)
print(max_col_len[0])
cells_gt[xlsx_cols[0] + str(i)] = {"text": id, "format": {}}
cells[xlsx_cols[1] + str(i)] = cells[xlsx_cols[1] + str(i+nb_records+3)] = {"text": record["start"],
"format": {}}
max_col_len[1] = get_max_len(record["start"], 1, max_col_len)
my_start = record["start"]
cells[xlsx_cols[2] + str(i)] = cells[xlsx_cols[2] + str(i+nb_records+3)] = {"text": record["end"],
"format": {}}
max_col_len[2] = get_max_len(record["end"], 2, max_col_len)
my_end = record["end"]
cells[xlsx_cols[3] + str(i)] = cells[xlsx_cols[3] + str(i+nb_records+3)] = {"text": record["length"],
"format": {}}
max_col_len[3] = get_max_len(record["length"], 3, max_col_len)
# Genotypes:
my_genotypes = None
if record["genotypes"] is not None:
for gt in range(0, len(record["genotypes"])):
cells_gt[xlsx_cols[1+gt] + str(i)] = {"text": record["genotypes"][gt], "format": {}}
my_genotypes = record["genotypes"]
is_kept = False
for tool in tools:
if tool in record["tools"]:
if record["tools"][tool]["filtered"]:
is_kept = True
sv_format = {"bg_color": color_is_kept}
# Raw values:
cells[xlsx_cols[1+((nb_tools+1)*3)] + str(i)] = {"text": record["tools"][tool]["start"],
"format": {"bg_color": color_col_filter}}
max_col_len[1+((nb_tools+1)*3)] = \
get_max_len(record["tools"][tool]["start"], 1 + ((nb_tools + 1) * 3),
max_col_len)
cells[xlsx_cols[1+((nb_tools+1)*3)+1] + str(i)] = {"text": record["tools"][tool]["end"],
"format": {"bg_color": color_col_filter}}
max_col_len[1 + ((nb_tools + 1) * 3)+1] = \
get_max_len(record["tools"][tool]["end"], 1 + ((nb_tools + 1) * 3)+1,
max_col_len)
cells[xlsx_cols[1+((nb_tools+1)*3)+2] + str(i)] = {"text": record["tools"][tool]["length"],
"format": {"bg_color": color_col_filter}}
max_col_len[1 + ((nb_tools + 1) * 3) + 2] = \
get_max_len(record["tools"][tool]["length"], 1 + ((nb_tools + 1) * 3) + 2,
max_col_len)
# Diffs:
if my_start != "":
cells[xlsx_cols[1+((nb_tools+1)*3)] + str(i+nb_records+3)] = {
"text": record["tools"][tool]["start"] - my_start, "format": {"bg_color": color_col_filter}}
cells[xlsx_cols[1+((nb_tools+1)*3) + 1] + str(i+nb_records+3)] = {
"text": record["tools"][tool]["end"] - my_end, "format": {"bg_color": color_col_filter}}
cells[xlsx_cols[1+((nb_tools+1)*3) + 2] + str(i+nb_records+3)] = {
"text": record["tools"][tool]["length"] - my_length,
"format": {"bg_color": color_col_filter}}
else:
cells[xlsx_cols[1 + ((nb_tools + 1) * 3)] + str(i + nb_records + 3)] = {
"text": "?????", "format": {"bg_color": color_col_filter}}
cells[xlsx_cols[1 + ((nb_tools + 1) * 3) + 1] + str(i + nb_records + 3)] = {
"text": "?????","format": {"bg_color": color_col_filter}}
cells[xlsx_cols[1 + ((nb_tools + 1) * 3) + 2] + str(i + nb_records + 3)] = {
"text": "?????", "format": {"bg_color": color_col_filter}}
# Genotypes:
if record["tools"][tool]["genotypes"] is not None:
the_genotypes = record["tools"][tool]["genotypes"]
for gt in range(0, len(the_genotypes)):
true_gt = my_genotypes[gt]
geno = get_gt(the_genotypes[gt], true_gt)
gt_format = {"bg_color": color_col_filter}
if geno != my_genotypes[gt]:
gt_format["font_color"] = "#ff0000"
cells_gt[xlsx_cols[1 + ((nb_tools + 1) * nb_inds) + gt] + str(i)] = \
{"text": geno, "format": gt_format}
else:
sv_format = {}
# Raw values:
cells[xlsx_cols[j] + str(i)] = {"text": record["tools"][tool]["start"], "format": sv_format}
max_col_len[j] = get_max_len(record["tools"][tool]["start"], j, max_col_len)
cells[xlsx_cols[j + 1] + str(i)] = {"text": record["tools"][tool]["end"], "format": sv_format}
max_col_len[j + 1] = get_max_len(record["tools"][tool]["end"], j + 1, max_col_len)
cells[xlsx_cols[j + 2] + str(i)] = {"text": record["tools"][tool]["length"], "format": sv_format}
max_col_len[j + 2] = get_max_len(record["tools"][tool]["length"], j + 2, max_col_len)
# Diffs :
if my_start != "":
cells[xlsx_cols[j] + str(i+nb_records+3)] = {"text": record["tools"][tool]["start"] - my_start,
"format": sv_format}
cells[xlsx_cols[j + 1] + str(i+nb_records+3)] = {"text": record["tools"][tool]["end"] - my_end,
"format": sv_format}
cells[xlsx_cols[j + 2] + str(i+nb_records+3)] = {"text": record["tools"][tool]["length"] - my_length,
"format": sv_format}
else:
cells[xlsx_cols[j] + str(i + nb_records + 3)] = {"text": "NA", "format": sv_format}
cells[xlsx_cols[j + 1] + str(i + nb_records + 3)] = {"text": "NA", "format": sv_format}
cells[xlsx_cols[j + 2] + str(i + nb_records + 3)] = {"text": "NA", "format": sv_format}
# Genotypes:
if record["tools"][tool]["genotypes"] is not None:
the_genotypes = record["tools"][tool]["genotypes"]
for gt in range(0, len(the_genotypes)):
true_gt = my_genotypes[gt]
geno = get_gt(the_genotypes[gt], true_gt)
gt_format = sv_format.copy()
if geno != true_gt:
gt_format["font_color"] = "#ff0000"
cells_gt[xlsx_cols[g + gt] + str(i)] = \
{"text": geno, "format": gt_format}
else:
for k in range(0,3):
cells[xlsx_cols[j + k] + str(i)] = {"text": "", "format": {"bg_color": color_not_found}}
cells[xlsx_cols[j + k] + str(i+nb_records+3)] = {"text": "", "format": {"bg_color": color_not_found}}
# Genotype:
for gt in range(0, nb_inds):
cells_gt[xlsx_cols[g + gt] + str(i)] = {"text": "", "format": {"bg_color": "#000000"}}
if is_kept:
cells[xlsx_cols[0] + str(i)]["format"]["bg_color"] = \
cells[xlsx_cols[0] + str(i+nb_records+3)]["format"]["bg_color"] = color_is_kept
elif filtered_records is not None:
cells[xlsx_cols[1 + ((nb_tools + 1) * 3)] + str(i)] = {"text": "", "format": {"bg_color": color_not_found}}
cells[xlsx_cols[1 + ((nb_tools + 1) * 3) + 1] + str(i)] = {"text": "", "format": {"bg_color": color_not_found}}
cells[xlsx_cols[1 + ((nb_tools + 1) * 3) + 2] + str(i)] = {"text": "", "format": {"bg_color": color_not_found}}
cells[xlsx_cols[1 + ((nb_tools + 1) * 3)] + str(i + nb_records + 3)] = {"text": "",
"format": {"bg_color": color_not_found}}
cells[xlsx_cols[1 + ((nb_tools + 1) * 3) + 1] + str(i + nb_records + 3)] = {
"text": "", "format": {"bg_color": color_not_found}}
cells[xlsx_cols[1 + ((nb_tools + 1) * 3) + 2] + str(i + nb_records + 3)] = {
"text": "", "format": {"bg_color": color_not_found}}
# Genotype:
for gt in range(0, nb_inds):
cells_gt[xlsx_cols[1 + ((nb_tools + 1) * nb_inds) + gt] + str(i)] = {"text": "", "format":
{"bg_color": "#000000"}}
# False positives (orphans) in orange:
if re.match(r"^orphan_\d+$", id):
cells[xlsx_cols[0] + str(i)]["format"]["bg_color"] = \
cells[xlsx_cols[0] + str(i+nb_records+3)]["format"]["bg_color"] = color_false_positive
i += 1
# Create document:
with xlsxwriter.Workbook(args.output) as workbook:
worksheet = workbook.add_worksheet("SVs")
max_header_length = max(len(header), max_header_length)
if i < len(headers) - 1 or filtered_records is None:
merge_format = workbook.add_format({'align': 'center'})
else:
merge_format = workbook.add_format({'align': 'center', 'bg_color': color_col_filter})
worksheet.merge_range(xlsx_cols[1 + i * 3] + "1:" + xlsx_cols[3 + i * 3] + "1", header, merge_format)
diff_line = str(1+nb_records+3)
worksheet.merge_range(xlsx_cols[1 + i * 3] + diff_line + ":" + xlsx_cols[3 + i * 3] + diff_line, header,
merge_format)
i += 1
for cell_id, cell_content in cells.items():
cell_format = workbook.add_format(cell_content["format"])
worksheet.write(cell_id, cell_content["text"], cell_format)
# Resize columns:
for col, max_len in max_col_len.items():
print(col,max_len)
worksheet.set_column(col, col, max_len+1)
# Genotypes:
if args.genotypes:
worksheet_gt = workbook.add_worksheet("Genotypes")
i = 0
for header in headers:
if i < len(headers) - 1 or filtered_records is None:
merge_format = workbook.add_format({'align': 'center'})
else:
merge_format = workbook.add_format({'align': 'center', 'bg_color': color_col_filter})
worksheet_gt.merge_range(xlsx_cols[1 + i * nb_inds] + "1:" + xlsx_cols[nb_inds + i * nb_inds] + "1",
header, merge_format)
i += 1
for cell_id, cell_content in cells_gt.items():
cell_format = workbook.add_format(cell_content["format"])
worksheet_gt.write(cell_id, cell_content["text"], cell_format)
worksheet_gt.freeze_panes(0, 9)
worksheet_gt.set_column(0, 0, max_col_len[0]+1)
print("")
print("###########")
print("# RESULTS #")
print("###########")
print("")
print(str(number-1) + " Results found")
print(str(orphans) + " False Positive")
print("")
print("Results saved in " + args.output)
print("")
# initialize the script
if __name__ == '__main__':
try:
sys.exit(main())
except:
raise