def test_build_empty():
## GIVEN a variant with no information
variant = {}
## WHEN building a variant_obj
## THEN a Key Error should be raised since mandatory fields are missing
with pytest.raises(KeyError):
build_variant(variant, INSTITUTE_ID)
def test_build_with_gene_info(parsed_variant):
## GIVEN information about a variant
## WHEN adding gene and transcript information and building variant
transcript_info = {
'functional_annotations': ['transcript_ablation'],
'transcript_id': 'ENST00000249504',
'hgnc_id': 5134,
'sift_prediction': 'deleterious'
}
gene_info = {
'transcripts': [transcript_info],
'most_severe_transcript': transcript_info,
'most_severe_consequence': 'transcript_ablation',
'most_severe_sift': 'deleterious',
'most_severe_polyphen': None,
'hgnc_id': 5134,
'region_annotation': 'exonic',
}
parsed_variant['genes'].append(gene_info)
variant_obj = build_variant(parsed_variant, INSTITUTE_ID)
## THEN assert the information is added
assert variant_obj['institute'] == INSTITUTE_ID
assert len(variant_obj['genes']) == 1
def test_build_cadd_score(parsed_variants, institute_obj):
for index,variant in enumerate(parsed_variants):
if variant.get('cadd_score'):
variant_obj = build_variant(variant, institute_obj)
assert variant_obj['cadd_score'] == variant['cadd_score']
assert index > 0
def test_build_minimal(case_obj):
## GIVEN a variant with minimal information
class Cyvcf2Variant(object):
def __init__(self):
self.CHROM = '1'
self.REF = 'A'
self.ALT = ['C']
self.POS = 10
self.end = 11
self.FILTER = None
self.ID = '.'
self.QUAL = None
self.var_type = 'snp'
self.INFO = {}
variant = Cyvcf2Variant()
parsed_variant = parse_variant(variant, case_obj)
assert 'ids' in parsed_variant
variant_obj = build_variant(parsed_variant, INSTITUTE_ID)
assert variant_obj['_id'] == parsed_variant['ids']['document_id']
def test_build_with_hgnc_info(parsed_variant):
## GIVEN information about a variant
## WHEN adding gene and transcript information and building variant
transcript_info = {
'functional_annotations': ['transcript_ablation'],
'transcript_id': 'ENST00000249504',
'hgnc_id': 5134,
'sift_prediction': 'deleterious'
}
gene_info = {
'transcripts': [transcript_info],
'most_severe_transcript': transcript_info,
'most_severe_consequence': 'transcript_ablation',
'most_severe_sift': 'deleterious',
'most_severe_polyphen': None,
'hgnc_id': 5134,
'region_annotation': 'exonic',
}
parsed_variant['genes'].append(gene_info)
transcript_1 = {
'ensembl_transcript_id': 'ENST00000498438',
'is_primary': False,
'start': 176968944,
'end': 176974482
}
transcript_2 = {
'ensembl_transcript_id': 'ENST00000249504',
'is_primary': True,
'refseq_id': 'NM_021192',
'start': 176972014,
'end': 176974722,
}
hgnc_transcripts = [
transcript_1,
transcript_2
]
hgnc_gene = {
'hgnc_id': 5134,
'hgnc_symbol': 'HOXD11',
'ensembl_id': 'ENSG00000128713',
'chromosome': '2',
'start': 176968944,
'end': 176974722,
'build': 37,
'description': 'homeobox D11',
'aliases': ['HOX4', 'HOXD11', 'HOX4F'],
'entrez_id': 3237,
'omim_ids': 142986,
'pli_score': 0.0131898476206074,
'primary_transcripts': ['NM_021192'],
'ucsc_id': 'uc010fqx.4',
'uniprot_ids': ['P31277'],
'vega_id': 'OTTHUMG00000132510',
'transcripts': hgnc_transcripts,
'incomplete_penetrance': False,
'ad': True,
'ar': False,
'xd': False,
'xr': False,
'x': False,
'y': False,
'transcripts_dict': {
'ENST00000498438': transcript_1,
'ENST00000249504': transcript_2,
}
}
hgncid_to_gene = {5134: hgnc_gene}
variant_obj = build_variant(parsed_variant, INSTITUTE_ID, hgncid_to_gene=hgncid_to_gene)
## THEN assert the information is added
assert variant_obj['institute'] == INSTITUTE_ID
assert variant_obj['genes'][0]['hgnc_id'] == 5134
assert variant_obj['genes'][0]['hgnc_symbol'] == 'HOXD11'
assert variant_obj['genes'][0]['inheritance'] == ['AD']
def test_build_sv_variants(parsed_sv_variants, institute_obj):
for variant in parsed_sv_variants:
variant_obj = build_variant(variant, institute_obj)
assert variant_obj['chromosome'] == variant['chromosome']
assert variant_obj['category'] == 'sv'
def test_build_sv_variant(parsed_sv_variant, institute_obj):
variant_obj = build_variant(parsed_sv_variant, institute_obj)
assert variant_obj['chromosome'] == parsed_sv_variant['chromosome']
assert variant_obj['category'] == 'sv'
def _load_variants(self, variants, variant_type, case_obj, individual_positions, rank_threshold,
institute_id, build=None, rank_results_header=None, vep_header=None,
category='snv', sample_info = None):
"""Perform the loading of variants
This is the function that loops over the variants, parse them and build the variant
objects so they are ready to be inserted into the database.
"""
build = build or '37'
genes = [gene_obj for gene_obj in self.all_genes(build=build)]
gene_to_panels = self.gene_to_panels(case_obj)
hgncid_to_gene = self.hgncid_to_gene(genes=genes)
genomic_intervals = self.get_coding_intervals(genes=genes)
LOG.info("Start inserting variants into database")
start_insertion = datetime.now()
start_five_thousand = datetime.now()
# These are the number of parsed varaints
nr_variants = 0
# These are the number of variants that meet the criteria and gets inserted
nr_inserted = 0
# This is to keep track of blocks of inserted variants
inserted = 1
nr_bulks = 0
# We want to load batches of variants to reduce the number of network round trips
bulk = {}
current_region = None
for nr_variants, variant in enumerate(variants):
# All MT variants are loaded
mt_variant = 'MT' in variant.CHROM
rank_score = parse_rank_score(variant.INFO.get('RankScore'), case_obj['_id'])
# Check if the variant should be loaded at all
# if rank score is None means there are no rank scores annotated, all variants will be loaded
# Otherwise we load all variants above a rank score treshold
# Except for MT variants where we load all variants
if (rank_score is None) or (rank_score > rank_threshold) or mt_variant:
nr_inserted += 1
# Parse the vcf variant
parsed_variant = parse_variant(
variant=variant,
case=case_obj,
variant_type=variant_type,
rank_results_header=rank_results_header,
vep_header=vep_header,
individual_positions=individual_positions,
category=category,
)
# Build the variant object
variant_obj = build_variant(
variant=parsed_variant,
institute_id=institute_id,
gene_to_panels=gene_to_panels,
hgncid_to_gene=hgncid_to_gene,
sample_info=sample_info
)
# Check if the variant is in a genomic region
var_chrom = variant_obj['chromosome']
var_start = variant_obj['position']
# We need to make sure that the interval has a length > 0
var_end = variant_obj['end'] + 1
var_id = variant_obj['_id']
# If the bulk should be loaded or not
load = True
new_region = None
genomic_regions = genomic_intervals.get(var_chrom, IntervalTree()).search(var_start, var_end)
# If the variant is in a coding region
if genomic_regions:
# We know there is data here so get the interval id
new_region = genomic_regions.pop().data
# If the variant is in the same region as previous
# we add it to the same bulk
if new_region == current_region:
load = False
# This is the case where the variant is intergenic
else:
# If the previous variant was also intergenic we add the variant to the bulk
if not current_region:
load = False
# We need to have a max size of the bulk
if len(bulk) > 10000:
load = True
# Load the variant object
if load:
# If the variant bulk contains coding variants we want to update the compounds
if current_region:
self.update_compounds(bulk)
try:
# Load the variants
self.load_variant_bulk(list(bulk.values()))
nr_bulks += 1
except IntegrityError as error:
pass
bulk = {}
current_region = new_region
bulk[var_id] = variant_obj
if (nr_variants != 0 and nr_variants % 5000 == 0):
LOG.info("%s variants parsed", str(nr_variants))
LOG.info("Time to parse variants: %s",
(datetime.now() - start_five_thousand))
start_five_thousand = datetime.now()
if (nr_inserted != 0 and (nr_inserted * inserted) % (1000 * inserted) == 0):
LOG.info("%s variants inserted", nr_inserted)
inserted += 1
# If the variants are in a coding region we update the compounds
if current_region:
self.update_compounds(bulk)
# Load the final variant bulk
self.load_variant_bulk(list(bulk.values()))
nr_bulks += 1
LOG.info("All variants inserted, time to insert variants: {0}".format(
datetime.now() - start_insertion))
if nr_variants:
nr_variants += 1
LOG.info("Nr variants parsed: %s", nr_variants)
LOG.info("Nr variants inserted: %s", nr_inserted)
LOG.debug("Nr bulks inserted: %s", nr_bulks)
return nr_inserted
def test_build_sv_variants(parsed_sv_variants, institute_obj):
for variant in parsed_sv_variants:
variant_obj = build_variant(variant, institute_obj)
assert variant_obj["chromosome"] == variant["chromosome"]
assert variant_obj["category"] == "sv"
def test_build_sv_variant(parsed_sv_variant, institute_obj):
variant_obj = build_variant(parsed_sv_variant, institute_obj)
assert variant_obj["chromosome"] == parsed_sv_variant["chromosome"]
assert variant_obj["category"] == "sv"
def test_build_variant(parsed_variant):
variant_obj = build_variant(parsed_variant, INSTITUTE_ID)
assert variant_obj["chromosome"] == parsed_variant["chromosome"]
assert variant_obj["category"] == "snv"
assert variant_obj["institute"] == INSTITUTE_ID
def _load_variants(
self,
variants,
variant_type,
case_obj,
individual_positions,
rank_threshold,
institute_id,
build=None,
rank_results_header=None,
vep_header=None,
category="snv",
sample_info=None,
):
"""Perform the loading of variants
This is the function that loops over the variants, parse them and build the variant
objects so they are ready to be inserted into the database.
Args:
variants(iterable(cyvcf2.Variant))
variant_type(str): ['clinical', 'research']
case_obj(dict)
individual_positions(dict): How individuals are positioned in vcf
rank_treshold(int): Only load variants with a rank score > than this
institute_id(str)
build(str): Genome build
rank_results_header(list): Rank score categories
vep_header(list)
category(str): ['snv','sv','cancer','str']
sample_info(dict): A dictionary with info about samples.
Strictly for cancer to tell which is tumor
Returns:
nr_inserted(int)
"""
build = build or "37"
genes = [gene_obj for gene_obj in self.all_genes(build=build)]
gene_to_panels = self.gene_to_panels(case_obj)
hgncid_to_gene = self.hgncid_to_gene(genes=genes)
genomic_intervals = self.get_coding_intervals(genes=genes)
LOG.info(
"Start inserting {0} {1} variants into database".format(
variant_type, category
)
)
start_insertion = datetime.now()
start_five_thousand = datetime.now()
# These are the number of parsed varaints
nr_variants = 0
# These are the number of variants that meet the criteria and gets inserted
nr_inserted = 0
# This is to keep track of blocks of inserted variants
inserted = 1
nr_bulks = 0
# We want to load batches of variants to reduce the number of network round trips
bulk = {}
current_region = None
for nr_variants, variant in enumerate(variants):
# All MT variants are loaded
mt_variant = "MT" in variant.CHROM
rank_score = parse_rank_score(
variant.INFO.get("RankScore"), case_obj["_id"]
)
pathogenic = is_pathogenic(variant)
# Check if the variant should be loaded at all
# if rank score is None means there are no rank scores annotated, all variants will be loaded
# Otherwise we load all variants above a rank score treshold
# Except for MT variants where we load all variants
if (
(rank_score is None)
or (rank_score > rank_threshold)
or mt_variant
or pathogenic
):
nr_inserted += 1
# Parse the vcf variant
parsed_variant = parse_variant(
variant=variant,
case=case_obj,
variant_type=variant_type,
rank_results_header=rank_results_header,
vep_header=vep_header,
individual_positions=individual_positions,
category=category,
)
# Build the variant object
variant_obj = build_variant(
variant=parsed_variant,
institute_id=institute_id,
gene_to_panels=gene_to_panels,
hgncid_to_gene=hgncid_to_gene,
sample_info=sample_info,
)
# Check if the variant is in a genomic region
var_chrom = variant_obj["chromosome"]
var_start = variant_obj["position"]
# We need to make sure that the interval has a length > 0
var_end = variant_obj["end"] + 1
var_id = variant_obj["_id"]
# If the bulk should be loaded or not
load = True
new_region = None
intervals = genomic_intervals.get(var_chrom, IntervalTree())
genomic_regions = intervals.overlap(var_start, var_end)
# If the variant is in a coding region
if genomic_regions:
# We know there is data here so get the interval id
new_region = genomic_regions.pop().data
# If the variant is in the same region as previous
# we add it to the same bulk
if new_region == current_region:
load = False
# This is the case where the variant is intergenic
else:
# If the previous variant was also intergenic we add the variant to the bulk
if not current_region:
load = False
# We need to have a max size of the bulk
if len(bulk) > 10000:
load = True
# Load the variant object
if load:
# If the variant bulk contains coding variants we want to update the compounds
if current_region:
self.update_compounds(bulk)
try:
# Load the variants
self.load_variant_bulk(list(bulk.values()))
nr_bulks += 1
except IntegrityError as error:
pass
bulk = {}
current_region = new_region
bulk[var_id] = variant_obj
if nr_variants != 0 and nr_variants % 5000 == 0:
LOG.info("%s variants parsed", str(nr_variants))
LOG.info(
"Time to parse variants: %s",
(datetime.now() - start_five_thousand),
)
start_five_thousand = datetime.now()
if (
nr_inserted != 0
and (nr_inserted * inserted) % (1000 * inserted) == 0
):
LOG.info("%s variants inserted", nr_inserted)
inserted += 1
# If the variants are in a coding region we update the compounds
if current_region:
self.update_compounds(bulk)
# Load the final variant bulk
self.load_variant_bulk(list(bulk.values()))
nr_bulks += 1
LOG.info(
"All variants inserted, time to insert variants: {0}".format(
datetime.now() - start_insertion
)
)
if nr_variants:
nr_variants += 1
LOG.info("Nr variants parsed: %s", nr_variants)
LOG.info("Nr variants inserted: %s", nr_inserted)
LOG.debug("Nr bulks inserted: %s", nr_bulks)
return nr_inserted
def sv_variant_objs(request, parsed_sv_variants, institute_obj):
"""Get a generator with parsed variants"""
print('')
return (build_variant(variant, institute_obj)
for variant in parsed_sv_variants)
def test_compounds_region(real_populated_database, case_obj, variant_clinical_file):
"""When loading the variants not all variants will be loaded, only the ones that
have a rank score above a treshold.
This implies that some compounds will have the status 'not_loaded'=True.
When loading all variants for a region then all variants should
have status 'not_loaded'=False.
"""
adapter = real_populated_database
variant_type = 'clinical'
category = 'snv'
## GIVEN a database without any variants
assert adapter.variant_collection.find().count() == 0
institute_obj = adapter.institute_collection.find_one()
institute_id = institute_obj['_id']
## WHEN loading variants into the database without updating compound information
vcf_obj = VCF(variant_clinical_file)
rank_results_header = parse_rank_results_header(vcf_obj)
vep_header = parse_vep_header(vcf_obj)
individual_positions = {}
for i, ind in enumerate(vcf_obj.samples):
individual_positions[ind] = i
variants = []
for i,variant in enumerate(vcf_obj):
parsed_variant = parse_variant(
variant=variant,
case=case_obj,
variant_type='clinical',
rank_results_header=rank_results_header,
vep_header=vep_header,
individual_positions=individual_positions,
category='snv',
)
variant_obj = build_variant(
variant=parsed_variant,
institute_id=institute_id,
)
variants.append(variant_obj)
# Load all variants
adapter.variant_collection.insert_many(variants)
print("Nr variants: {0}".format(len(variants)))
## THEN assert that the variants does not have updated compound information
nr_compounds = 0
for var in adapter.variant_collection.find():
if not var.get('compounds'):
continue
for comp in var['compounds']:
if 'genes' in comp:
assert False
if 'not_loaded' in comp:
assert False
nr_compounds += 1
assert nr_compounds > 0
## WHEN updating all compounds for a case
adapter.update_case_compounds(case_obj)
hgnc_ids = set([gene['hgnc_id'] for gene in adapter.all_genes()])
nr_compounds = 0
## THEN assert that all compounds (within the gene defenition) are updated
for var in adapter.variant_collection.find():
cont = False
for hgnc_id in var['hgnc_ids']:
if hgnc_id not in hgnc_ids:
cont = True
if cont:
continue
if not var.get('compounds'):
continue
for comp in var['compounds']:
nr_compounds += 1
if not 'genes' in comp:
# pp(var)
assert False
if not 'not_loaded' in comp:
assert False
assert nr_compounds > 0
def test_build_variant(parsed_variant):
variant_obj = build_variant(parsed_variant, INSTITUTE_ID)
assert variant_obj['chromosome'] == parsed_variant['chromosome']
assert variant_obj['category'] == 'snv'
assert variant_obj['institute'] == INSTITUTE_ID
def _load_variants(self, variants, variant_type, case_obj, individual_positions, rank_threshold,
institute_id, build=None, rank_results_header=None, vep_header=None,
category='snv', sample_info = None):
"""Perform the loading of variants
This is the function that loops over the variants, parse them and build the variant
objects so they are ready to be inserted into the database.
"""
build = build or '37'
genes = [gene_obj for gene_obj in self.all_genes(build=build)]
gene_to_panels = self.gene_to_panels(case_obj)
hgncid_to_gene = self.hgncid_to_gene(genes=genes)
genomic_intervals = self.get_coding_intervals(genes=genes)
LOG.info("Start inserting {0} {1} variants into database".format(variant_type, category))
start_insertion = datetime.now()
start_five_thousand = datetime.now()
# These are the number of parsed varaints
nr_variants = 0
# These are the number of variants that meet the criteria and gets inserted
nr_inserted = 0
# This is to keep track of blocks of inserted variants
inserted = 1
nr_bulks = 0
# We want to load batches of variants to reduce the number of network round trips
bulk = {}
current_region = None
for nr_variants, variant in enumerate(variants):
# All MT variants are loaded
mt_variant = 'MT' in variant.CHROM
rank_score = parse_rank_score(variant.INFO.get('RankScore'), case_obj['_id'])
# Check if the variant should be loaded at all
# if rank score is None means there are no rank scores annotated, all variants will be loaded
# Otherwise we load all variants above a rank score treshold
# Except for MT variants where we load all variants
if (rank_score is None) or (rank_score > rank_threshold) or mt_variant:
nr_inserted += 1
# Parse the vcf variant
parsed_variant = parse_variant(
variant=variant,
case=case_obj,
variant_type=variant_type,
rank_results_header=rank_results_header,
vep_header=vep_header,
individual_positions=individual_positions,
category=category,
)
# Build the variant object
variant_obj = build_variant(
variant=parsed_variant,
institute_id=institute_id,
gene_to_panels=gene_to_panels,
hgncid_to_gene=hgncid_to_gene,
sample_info=sample_info
)
# Check if the variant is in a genomic region
var_chrom = variant_obj['chromosome']
var_start = variant_obj['position']
# We need to make sure that the interval has a length > 0
var_end = variant_obj['end'] + 1
var_id = variant_obj['_id']
# If the bulk should be loaded or not
load = True
new_region = None
genomic_regions = genomic_intervals.get(var_chrom, IntervalTree()).search(var_start, var_end)
# If the variant is in a coding region
if genomic_regions:
# We know there is data here so get the interval id
new_region = genomic_regions.pop().data
# If the variant is in the same region as previous
# we add it to the same bulk
if new_region == current_region:
load = False
# This is the case where the variant is intergenic
else:
# If the previous variant was also intergenic we add the variant to the bulk
if not current_region:
load = False
# We need to have a max size of the bulk
if len(bulk) > 10000:
load = True
# Load the variant object
if load:
# If the variant bulk contains coding variants we want to update the compounds
if current_region:
self.update_compounds(bulk)
try:
# Load the variants
self.load_variant_bulk(list(bulk.values()))
nr_bulks += 1
except IntegrityError as error:
pass
bulk = {}
current_region = new_region
bulk[var_id] = variant_obj
if (nr_variants != 0 and nr_variants % 5000 == 0):
LOG.info("%s variants parsed", str(nr_variants))
LOG.info("Time to parse variants: %s",
(datetime.now() - start_five_thousand))
start_five_thousand = datetime.now()
if (nr_inserted != 0 and (nr_inserted * inserted) % (1000 * inserted) == 0):
LOG.info("%s variants inserted", nr_inserted)
inserted += 1
# If the variants are in a coding region we update the compounds
if current_region:
self.update_compounds(bulk)
# Load the final variant bulk
self.load_variant_bulk(list(bulk.values()))
nr_bulks += 1
LOG.info("All variants inserted, time to insert variants: {0}".format(
datetime.now() - start_insertion))
if nr_variants:
nr_variants += 1
LOG.info("Nr variants parsed: %s", nr_variants)
LOG.info("Nr variants inserted: %s", nr_inserted)
LOG.debug("Nr bulks inserted: %s", nr_bulks)
return nr_inserted
def test_compounds_region(real_populated_database, case_obj,
variant_clinical_file):
"""When loading the variants not all variants will be loaded, only the ones that
have a rank score above a treshold.
This implies that some compounds will have the status 'not_loaded'=True.
When loading all variants for a region then all variants should
have status 'not_loaded'=False.
"""
adapter = real_populated_database
variant_type = 'clinical'
category = 'snv'
## GIVEN a database without any variants
assert adapter.variant_collection.find().count() == 0
institute_obj = adapter.institute_collection.find_one()
institute_id = institute_obj['_id']
## WHEN loading variants into the database without updating compound information
vcf_obj = VCF(variant_clinical_file)
rank_results_header = parse_rank_results_header(vcf_obj)
vep_header = parse_vep_header(vcf_obj)
individual_positions = {}
for i, ind in enumerate(vcf_obj.samples):
individual_positions[ind] = i
variants = []
for i, variant in enumerate(vcf_obj):
parsed_variant = parse_variant(
variant=variant,
case=case_obj,
variant_type='clinical',
rank_results_header=rank_results_header,
vep_header=vep_header,
individual_positions=individual_positions,
category='snv',
)
variant_obj = build_variant(
variant=parsed_variant,
institute_id=institute_id,
)
variants.append(variant_obj)
# Load all variants
adapter.variant_collection.insert_many(variants)
print("Nr variants: {0}".format(len(variants)))
## THEN assert that the variants does not have updated compound information
nr_compounds = 0
for var in adapter.variant_collection.find():
if not var.get('compounds'):
continue
for comp in var['compounds']:
if 'genes' in comp:
assert False
if 'not_loaded' in comp:
assert False
nr_compounds += 1
assert nr_compounds > 0
## WHEN updating all compounds for a case
adapter.update_case_compounds(case_obj)
hgnc_ids = set([gene['hgnc_id'] for gene in adapter.all_genes()])
nr_compounds = 0
## THEN assert that all compounds (within the gene defenition) are updated
for var in adapter.variant_collection.find():
cont = False
for hgnc_id in var['hgnc_ids']:
if hgnc_id not in hgnc_ids:
cont = True
if cont:
continue
if not var.get('compounds'):
continue
for comp in var['compounds']:
nr_compounds += 1
if not 'genes' in comp:
# pp(var)
assert False
if not 'not_loaded' in comp:
assert False
assert nr_compounds > 0
