docstring stringlengths 52 499 | function stringlengths 67 35.2k | __index_level_0__ int64 52.6k 1.16M |
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Fetch the ensembl genes
Args:
build(str): ['37', '38'] | def fetch_ensembl_exons(build='37'):
LOG.info("Fetching ensembl exons build %s ...", build)
if build == '37':
url = 'http://grch37.ensembl.org'
else:
url = 'http://www.ensembl.org'
dataset_name = 'hsapiens_gene_ensembl'
dataset = pybiomart.Dataset(name=dataset_name, ho... | 614,982 |
Fetch the necessary mim files using a api key
Args:
api_key(str): A api key necessary to fetch mim data
Returns:
mim_files(dict): A dictionary with the neccesary files | def fetch_hpo_files(hpogenes=False, hpoterms=False, phenotype_to_terms=False, hpodisease=False):
LOG.info("Fetching HPO information from http://compbio.charite.de")
base_url = ('http://compbio.charite.de/jenkins/job/hpo.annotations.monthly/'
'lastStableBuild/artifact/annotation/{}')
hp... | 614,985 |
Parse information about variants.
- Adds information about compounds
- Updates the information about compounds if necessary and 'update=True'
Args:
store(scout.adapter.MongoAdapter)
institute_obj(scout.models.Institute)
case_obj(scout.models.Case)
variant_obj(scout.models.V... | def parse_variant(store, institute_obj, case_obj, variant_obj, update=False, genome_build='37',
get_compounds = True):
has_changed = False
compounds = variant_obj.get('compounds', [])
if compounds and get_compounds:
# Check if we need to add compound information
# If i... | 614,995 |
Get variants info to be exported to file, one list (line) per variant.
Args:
store(scout.adapter.MongoAdapter)
case_obj(scout.models.Case)
variants_query: a list of variant objects, each one is a dictionary
Returns:
export_variants: a list of strings. Ea... | def variant_export_lines(store, case_obj, variants_query):
export_variants = []
for variant in variants_query:
variant_line = []
position = variant['position']
change = variant['reference']+'>'+variant['alternative']
variant_line.append(variant['rank_score'])
varia... | 614,996 |
Returns a header for the CSV file with the filtered variants to be exported.
Args:
case_obj(scout.models.Case)
Returns:
header: includes the fields defined in scout.constants.variants_export EXPORT_HEADER
+ AD_reference, AD_alternate, GT_quality for each sam... | def variants_export_header(case_obj):
header = []
header = header + EXPORT_HEADER
# Add fields specific for case samples
for individual in case_obj['individuals']:
display_name = str(individual['display_name'])
header.append('AD_reference_'+display_name) # Add AD reference field for... | 614,997 |
Pre-process case for the variant view.
Adds information about files from case obj to variant
Args:
store(scout.adapter.MongoAdapter)
case_obj(scout.models.Case)
variant_obj(scout.models.Variant) | def variant_case(store, case_obj, variant_obj):
case_obj['bam_files'] = []
case_obj['mt_bams'] = []
case_obj['bai_files'] = []
case_obj['mt_bais'] = []
case_obj['sample_names'] = []
for individual in case_obj['individuals']:
bam_path = individual.get('bam_file')
mt_bam = ind... | 615,000 |
Compose link to COSMIC Database.
Args:
variant_obj(scout.models.Variant)
Returns:
url_template(str): Link to COSMIIC database if cosmic id is present | def cosmic_link(variant_obj):
cosmic_ids = variant_obj.get('cosmic_ids')
if not cosmic_ids:
return None
else:
cosmic_id = cosmic_ids[0]
url_template = ("https://cancer.sanger.ac.uk/cosmic/mutation/overview?id={}")
return url_template.format(cosmic_id) | 615,011 |
Gather the required data for creating the clinvar submission form
Args:
store(scout.adapter.MongoAdapter)
institute_id(str): Institute ID
case_name(str): case ID
variant_id(str): variant._id
Returns:
a dictionary with all the required data (c... | def clinvar_export(store, institute_id, case_name, variant_id):
institute_obj, case_obj = institute_and_case(store, institute_id, case_name)
pinned = [store.variant(variant_id) or variant_id for variant_id in
case_obj.get('suspects', [])]
variant_obj = store.variant(variant_id)
r... | 615,020 |
Collects all variants from the clinvar submission collection with a specific submission_id
Args:
store(scout.adapter.MongoAdapter)
institute_id(str): Institute ID
case_name(str): case ID
variant_id(str): variant._id
submission_id(str): clinvar submiss... | def get_clinvar_submission(store, institute_id, case_name, variant_id, submission_id):
institute_obj, case_obj = institute_and_case(store, institute_id, case_name)
pinned = [store.variant(variant_id) or variant_id for variant_id in
case_obj.get('suspects', [])]
variant_obj = store.va... | 615,021 |
Collect all verified variants in a list on institutes and save them to file
Args:
store(adapter.MongoAdapter)
institute_list(list): a list of institute ids
temp_excel_dir(os.Path): folder where the temp excel files are written to
Returns:
written_files(int): the number of files... | def verified_excel_file(store, institute_list, temp_excel_dir):
document_lines = []
written_files = 0
today = datetime.datetime.now().strftime('%Y-%m-%d')
LOG.info('Creating verified variant document..')
for cust in institute_list:
verif_vars = store.verified(institute_id=cust)
... | 615,026 |
Build a hpo_term object
Check that the information is correct and add the correct hgnc ids to the
array of genes.
Args:
hpo_info(dict)
Returns:
hpo_obj(scout.models.HpoTerm): A dictionary with hpo information | def build_hpo_term(hpo_info):
try:
hpo_id = hpo_info['hpo_id']
except KeyError:
raise KeyError("Hpo terms has to have a hpo_id")
LOG.debug("Building hpo term %s", hpo_id)
# Add description to HPO term
try:
description = hpo_info['description']
except KeyError:... | 615,027 |
Get the clnsig information
Args:
acc(str): The clnsig accession number, raw from vcf
sig(str): The clnsig significance score, raw from vcf
revstat(str): The clnsig revstat, raw from vcf
transcripts(iterable(dict))
Returns:
clnsig_accsessions(list): A list with clnsig ac... | def parse_clnsig(acc, sig, revstat, transcripts):
clnsig_accsessions = []
if acc:
# New format of clinvar allways have integers as accession numbers
try:
acc = int(acc)
except ValueError:
pass
# There are sometimes different separators so we need to chec... | 615,029 |
Get a list with compounds objects for this variant.
Arguments:
compound_info(str): A Variant dictionary
case_id (str): unique family id
variant_type(str): 'research' or 'clinical'
Returns:
compounds(list(dict)): A list of compounds | def parse_compounds(compound_info, case_id, variant_type):
# We need the case to construct the correct id
compounds = []
if compound_info:
for family_info in compound_info.split(','):
splitted_entry = family_info.split(':')
# This is the family id
if splitted... | 615,032 |
Parse individual information
Args:
sample (dict)
Returns:
{
'individual_id': str,
'father': str,
'mother': str,
'display_name': str,
'sex': str,
'phenotype': str,
'ba... | def parse_individual(sample):
ind_info = {}
if 'sample_id' not in sample:
raise PedigreeError("One sample is missing 'sample_id'")
sample_id = sample['sample_id']
# Check the sex
if 'sex' not in sample:
raise PedigreeError("Sample %s is missing 'sex'" % sample_id)
sex = samp... | 615,054 |
Parse the individual information
Reformat sample information to proper individuals
Args:
samples(list(dict))
Returns:
individuals(list(dict)) | def parse_individuals(samples):
individuals = []
if len(samples) == 0:
raise PedigreeError("No samples could be found")
ind_ids = set()
for sample_info in samples:
parsed_ind = parse_individual(sample_info)
individuals.append(parsed_ind)
ind_ids.add(parsed_ind['indi... | 615,055 |
Parse case information from config or PED files.
Args:
config (dict): case config with detailed information
Returns:
dict: parsed case data | def parse_case(config):
if 'owner' not in config:
raise ConfigError("A case has to have a owner")
if 'family' not in config:
raise ConfigError("A case has to have a 'family'")
individuals = parse_individuals(config['samples'])
case_data = {
'owner': config['owner'],
... | 615,056 |
Parse out minimal family information from a PED file.
Args:
ped_stream(iterable(str))
family_type(str): Format of the pedigree information
Returns:
family_id(str), samples(list[dict]) | def parse_ped(ped_stream, family_type='ped'):
pedigree = FamilyParser(ped_stream, family_type=family_type)
if len(pedigree.families) != 1:
raise PedigreeError("Only one case per ped file is allowed")
family_id = list(pedigree.families.keys())[0]
family = pedigree.families[family_id]
... | 615,057 |
Build a evaluation object ready to be inserted to database
Args:
variant_specific(str): md5 string for the specific variant
variant_id(str): md5 string for the common variant
user_id(str)
user_name(str)
institute_id(str)
case_id(str)
classification(str): The ... | def build_evaluation(variant_specific, variant_id, user_id, user_name,
institute_id, case_id, classification, criteria):
criteria = criteria or []
evaluation_obj = dict(
variant_specific = variant_specific,
variant_id = variant_id,
institute_id = institute_id,
... | 615,058 |
Export all mitochondrial variants for each sample of a case
and write them to an excel file
Args:
adapter(MongoAdapter)
case_id(str)
test(bool): True if the function is called for testing purposes
outpath(str): path to output file
Returns:
... | def mt_report(context, case_id, test, outpath=None):
LOG.info('exporting mitochondrial variants for case "{}"'.format(case_id))
adapter = context.obj['adapter']
query = {'chrom':'MT'}
case_obj = adapter.case(case_id=case_id)
if not case_obj:
LOG.warning('Could not find a scout case w... | 615,059 |
Build a genotype call
Args:
gt_call(dict)
Returns:
gt_obj(dict)
gt_call = dict(
sample_id = str,
display_name = str,
genotype_call = str,
allele_depths = list, # int
read_depth = int,
genotype_quality = int,
) | def build_genotype(gt_call):
gt_obj = dict(
sample_id = gt_call['individual_id'],
display_name = gt_call['display_name'],
genotype_call = gt_call['genotype_call'],
allele_depths = [gt_call['ref_depth'], gt_call['alt_depth']],
read_depth = gt_call['read_depth'],
g... | 615,060 |
Use the algorithm described in ACMG paper to get a ACMG calssification
Args:
acmg_terms(set(str)): A collection of prediction terms
Returns:
prediction(int):
0 - Uncertain Significanse
1 - Benign
2 - Likely Benign
3 - Likely Patho... | def get_acmg(acmg_terms):
prediction = 'uncertain_significance'
# This variable indicates if Pathogenecity Very Strong exists
pvs = False
# Collection of terms with Pathogenecity Strong
ps_terms = []
# Collection of terms with Pathogenecity moderate
pm_terms = []
# Collection of ter... | 615,064 |
Add extra information about genes from gene panels
Args:
variant_obj(dict): A variant from the database
gene_panels(list(dict)): List of panels from database | def add_gene_info(self, variant_obj, gene_panels=None):
gene_panels = gene_panels or []
# Add a variable that checks if there are any refseq transcripts
variant_obj['has_refseq'] = False
# We need to check if there are any additional information in the gene panels
# e... | 615,066 |
Return all variants with sanger information
Args:
institute_id(str)
case_id(str)
Returns:
res(pymongo.Cursor): A Cursor with all variants with sanger activity | def sanger_variants(self, institute_id=None, case_id=None):
query = {'validation': {'$exists': True}}
if institute_id:
query['institute_id'] = institute_id
if case_id:
query['case_id'] = case_id
return self.variant_collection.find(query) | 615,068 |
Returns the specified variant.
Arguments:
document_id : A md5 key that represents the variant or "variant_id"
gene_panels(List[GenePanel])
case_id (str): case id (will search with "variant_id")
Returns:
variant_object(Variant): A odm va... | def variant(self, document_id, gene_panels=None, case_id=None):
query = {}
if case_id:
# search for a variant in a case
query['case_id'] = case_id
query['variant_id'] = document_id
else:
# search with a unique id
query['_id'] =... | 615,069 |
Return all variants seen in a given gene.
If skip not equal to 0 skip the first n variants.
Arguments:
query(dict): A dictionary with querys for the database, including
variant_type: 'clinical', 'research'
category(str): 'sv', 'str', 'snv' or 'cancer'
nr... | def gene_variants(self, query=None,
category='snv', variant_type=['clinical'],
nr_of_variants=50, skip=0):
mongo_variant_query = self.build_variant_query(query=query,
category=category, variant_type=variant_type)
sorting... | 615,070 |
Return all verified variants for a given institute
Args:
institute_id(str): institute id
Returns:
res(list): a list with validated variants | def verified(self, institute_id):
query = {
'verb' : 'validate',
'institute' : institute_id,
}
res = []
validate_events = self.event_collection.find(query)
for validated in list(validate_events):
case_id = validated['case']
... | 615,071 |
Return all causative variants for an institute
Args:
institute_id(str)
case_id(str)
Yields:
str: variant document id | def get_causatives(self, institute_id, case_id=None):
causatives = []
if case_id:
case_obj = self.case_collection.find_one(
{"_id": case_id}
)
causatives = [causative for causative in case_obj['causatives']]
elif institute_... | 615,072 |
Check if there are any variants that are previously marked causative
Loop through all variants that are marked 'causative' for an
institute and check if any of the variants are present in the
current case.
Args:
case_obj (dict): A Case object
... | def check_causatives(self, case_obj=None, institute_obj=None):
institute_id = case_obj['owner'] if case_obj else institute_obj['_id']
institute_causative_variant_ids = self.get_causatives(institute_id)
if len(institute_causative_variant_ids) == 0:
return []
if case_... | 615,073 |
Find the same variant in other cases marked causative.
Args:
case_obj(dict)
variant_obj(dict)
Yields:
other_variant(dict) | def other_causatives(self, case_obj, variant_obj):
# variant id without "*_[variant_type]"
variant_id = variant_obj['display_name'].rsplit('_', 1)[0]
institute_causatives = self.get_causatives(variant_obj['institute'])
for causative_id in institute_causatives:
other... | 615,074 |
Delete variants of one type for a case
This is used when a case is reanalyzed
Args:
case_id(str): The case id
variant_type(str): 'research' or 'clinical'
category(str): 'snv', 'sv' or 'cancer' | def delete_variants(self, case_id, variant_type, category=None):
category = category or ''
LOG.info("Deleting old {0} {1} variants for case {2}".format(
variant_type, category, case_id))
query = {'case_id': case_id, 'variant_type': variant_type}
if category:
... | 615,075 |
Return overlapping variants.
Look at the genes that a variant overlaps to.
Then return all variants that overlap these genes.
If variant_obj is sv it will return the overlapping snvs and oposite
There is a problem when SVs are huge since there are to many overlapping variants.
... | def overlapping(self, variant_obj):
#This is the category of the variants that we want to collect
category = 'snv' if variant_obj['category'] == 'sv' else 'sv'
query = {
'$and': [
{'case_id': variant_obj['case_id']},
{'category': category},
... | 615,076 |
Returns variants that has been evaluated
Return all variants, snvs/indels and svs from case case_id
which have a entry for 'acmg_classification', 'manual_rank', 'dismiss_variant'
or if they are commented.
Args:
case_id(str)
Returns:
variants(iterable(Va... | def evaluated_variants(self, case_id):
# Get all variants that have been evaluated in some way for a case
query = {
'$and': [
{'case_id': case_id},
{
'$or': [
{'acmg_classification': {'$exists': True}},
... | 615,077 |
Given a list of variants get variant objects found in a specific patient
Args:
variants(list): a list of variant ids
sample_name(str): a sample display name
category(str): 'snv', 'sv' ..
Returns:
result(iterable(Variant)) | def sample_variants(self, variants, sample_name, category = 'snv'):
LOG.info('Retrieving variants for subject : {0}'.format(sample_name))
has_allele = re.compile('1|2') # a non wild-type allele is called at least once in this sample
query = {
'$and': [
{'_id... | 615,079 |
Creates a list of submission objects (variant and case-data) from the clinvar submission form in blueprints/variants/clinvar.html.
Args:
form_fields(dict): it's the submission form dictionary. Keys have the same names as CLINVAR_HEADER and CASEDATA_HEADER
Returns:
submission_... | def set_submission_objects(form_fields):
variant_ids = get_submission_variants(form_fields) # A list of variant IDs present in the submitted form
# Extract list of variant objects to be submitted
variant_objs = get_objects_from_form(variant_ids, form_fields, 'variant')
# Extract list of casedata ... | 615,081 |
Extracts a list of variant ids from the clinvar submission form in blueprints/variants/clinvar.html (creation of a new clinvar submission).
Args:
form_fields(dict): it's the submission form dictionary. Keys have the same names as CLINVAR_HEADER and CASEDATA_HEADER
Returns:
cl... | def get_submission_variants(form_fields):
clinvars = []
# if the html checkbox named 'all_vars' is checked in the html form, then all pinned variants from a case should be included in the clinvar submission file,
# otherwise just the selected one.
if 'all_vars' in form_fields:
for field, ... | 615,083 |
Determine which fields to include in csv header by checking a list of submission objects
Args:
submission_objs(list): a list of objects (variants or casedata) to include in a csv file
csv_type(str) : 'variant_data' or 'case_data'
Returns:
custom_header(dict): A dict... | def clinvar_submission_header(submission_objs, csv_type):
complete_header = {} # header containing all available fields
custom_header = {} # header reflecting the real data included in the submission objects
if csv_type == 'variant_data' :
complete_header = CLINVAR_HEADER
else:
c... | 615,084 |
Load all the transcripts
Transcript information is from ensembl.
Args:
adapter(MongoAdapter)
transcripts_lines(iterable): iterable with ensembl transcript lines
build(str)
ensembl_genes(dict): Map from ensembl_id -> HgncGene
Returns:
transcript_objs(list): A list w... | def load_transcripts(adapter, transcripts_lines=None, build='37', ensembl_genes=None):
# Fetch all genes with ensemblid as keys
ensembl_genes = ensembl_genes or adapter.ensembl_genes(build)
if transcripts_lines is None:
transcripts_lines = fetch_ensembl_transcripts(build=build)
# Map with... | 615,086 |
Build a Exon object object
Args:
exon_info(dict): Exon information
Returns:
exon_obj(Exon)
"exon_id": str, # str(chrom-start-end)
"chrom": str,
"start": int,
"end": int,
"transcript": str, # ENST ID
"hgnc_id": int,... | def build_exon(exon_info, build='37'):
try:
chrom = exon_info['chrom']
except KeyError:
raise KeyError("Exons has to have a chromosome")
try:
start = int(exon_info['start'])
except KeyError:
raise KeyError("Exon has to have a start")
except TypeError:
r... | 615,088 |
Extract all OMIM phenotypes available for the case
Args:
case_obj(dict): a scout case object
Returns:
disorders(list): a list of OMIM disorder objects | def omim_terms(case_obj):
LOG.info("Collecting OMIM disorders for case {}".format(case_obj.get('display_name')))
disorders = []
case_disorders = case_obj.get('diagnosis_phenotypes') # array of OMIM terms
if case_disorders:
for disorder in case_disorders:
disorder_obj = {
... | 615,097 |
Updates a case after a submission to MatchMaker Exchange
Args:
case_obj(dict): a scout case object
user_obj(dict): a scout user object
mme_subm_obj(dict): contains MME submission params and server response
Returns:
updated_case(dict... | def case_mme_update(self, case_obj, user_obj, mme_subm_obj):
created = None
patient_ids = []
updated = datetime.now()
if 'mme_submission' in case_obj and case_obj['mme_submission']:
created = case_obj['mme_submission']['created_at']
else:
created ... | 615,106 |
Delete a MatchMaker submission from a case record
and creates the related event.
Args:
case_obj(dict): a scout case object
user_obj(dict): a scout user object
Returns:
updated_case(dict): the updated scout case | def case_mme_delete(self, case_obj, user_obj):
institute_obj = self.institute(case_obj['owner'])
# create events for subjects removal from Matchmaker this cas
for individual in case_obj['individuals']:
if individual['phenotype'] == 2: # affected
# create even... | 615,107 |
Build a institute object
Args:
internal_id(str)
display_name(str)
sanger_recipients(list(str)): List with email addresses
Returns:
institute_obj(scout.models.Institute) | def build_institute(internal_id, display_name, sanger_recipients=None,
coverage_cutoff=None, frequency_cutoff=None):
LOG.info("Building institute %s with display name %s", internal_id,display_name)
institute_obj = Institute(
internal_id=internal_id,
display_name=displ... | 615,108 |
Delete a event
Arguments:
event_id (str): The database key for the event | def delete_event(self, event_id):
LOG.info("Deleting event{0}".format(event_id))
if not isinstance(event_id, ObjectId):
event_id = ObjectId(event_id)
self.event_collection.delete_one({'_id': event_id})
LOG.debug("Event {0} deleted".format(event_id)) | 615,109 |
Fetch events from the database.
Args:
institute (dict): A institute
case (dict): A case
variant_id (str, optional): global variant id
level (str, optional): restrict comments to 'specific' or 'global'
comments (bool, optional): restrict events to in... | def events(self, institute, case=None, variant_id=None, level=None,
comments=False, panel=None):
query = {}
if variant_id:
if comments:
# If it's comment-related event collect global and variant-specific comment events
LOG.debug("Fetc... | 615,111 |
Add a new phenotype term to a case
Create a phenotype term and event with the given information
Args:
institute (Institute): A Institute object
case (Case): Case object
user (User): A User object
link (str): The url to be used in ... | def add_phenotype(self, institute, case, user, link, hpo_term=None,
omim_term=None, is_group=False):
hpo_results = []
try:
if hpo_term:
hpo_results = [hpo_term]
elif omim_term:
LOG.debug("Fetching info for mim term {0... | 615,113 |
Remove an existing phenotype from a case
Args:
institute (dict): A Institute object
case (dict): Case object
user (dict): A User object
link (dict): The url to be used in the event
phenotype_id (str): A phenotype id
Returns:
updat... | def remove_phenotype(self, institute, case, user, link, phenotype_id,
is_group=False):
LOG.info("Removing HPO term from case {0}".format(case['display_name']))
if is_group:
updated_case = self.case_collection.find_one_and_update(
{'_id': cas... | 615,114 |
Parse the genotype calls for a variant
Args:
variant(cyvcf2.Variant)
individuals: List[dict]
individual_positions(dict)
Returns:
genotypes(list(dict)): A list of genotypes | def parse_genotypes(variant, individuals, individual_positions):
genotypes = []
for ind in individuals:
pos = individual_positions[ind['individual_id']]
genotypes.append(parse_genotype(variant, ind, pos))
return genotypes | 615,116 |
Check if a variant is in the Pseudo Autosomal Region or not
Args:
chromosome(str)
position(int)
build(str): The genome build
Returns:
bool | def is_par(chromosome, position, build='37'):
chrom_match = CHR_PATTERN.match(chromosome)
chrom = chrom_match.group(2)
# PAR regions are only on X and Y
if not chrom in ['X','Y']:
return False
# Check if variant is in first PAR region
if PAR_COORDINATES[build][chrom].search(pos... | 615,118 |
Check if the variant is in the interval given by the coordinates
Args:
chromosome(str): Variant chromosome
pos(int): Variant position
coordinates(dict): Dictionary with the region of interest | def check_coordinates(chromosome, pos, coordinates):
chrom_match = CHR_PATTERN.match(chromosome)
chrom = chrom_match.group(2)
if chrom != coordinates['chrom']:
return False
if (pos >= coordinates['start'] and pos <= coordinates['end']):
return True
return False | 615,119 |
Export all genes in gene panels
Exports the union of genes in one or several gene panels to a bed like format with coordinates.
Args:
adapter(scout.adapter.MongoAdapter)
panels(iterable(str)): Iterable with panel ids
bed(bool): If lines should be bed formated | def export_panels(adapter, panels, versions=None, build='37'):
if versions and (len(versions) != len(panels)):
raise SyntaxError("If version specify for each panel")
headers = []
build_string = ("##genome_build={}")
headers.append(build_string.format(build))
header_string = ("##ge... | 615,120 |
Export the genes of a gene panel
Takes a list of gene panel names and return the lines of the gene panels.
Unlike export_panels this function only export the genes and extra information,
not the coordinates.
Args:
adapter(MongoAdapter)
panels(list(str))
version(float):... | def export_gene_panels(adapter, panels, version=None):
if version and len(panels) > 1:
raise SyntaxError("Version only possible with one panel")
bed_string = ("{0}\t{1}\t{2}\t{3}\t{4}\t{5}")
headers = []
# Dictionary with hgnc ids as keys and panel gene information as value.
pane... | 615,121 |
Build a user object
Args:
user_info(dict): A dictionary with user information
Returns:
user_obj(scout.models.User) | def build_user(user_info):
try:
email = user_info['email']
except KeyError as err:
raise KeyError("A user has to have a email")
try:
name = user_info['name']
except KeyError as err:
raise KeyError("A user has to have a name")
user_obj = User(email=email... | 615,133 |
Update an existing gene panel with genes.
Args:
store(scout.adapter.MongoAdapter)
panel_name(str)
csv_lines(iterable(str)): Stream with genes
option(str): 'add' or 'replace'
Returns:
panel_obj(dict) | def update_panel(store, panel_name, csv_lines, option):
new_genes= []
panel_obj = store.gene_panel(panel_name)
if panel_obj is None:
return None
try:
new_genes = parse_genes(csv_lines) # a list of gene dictionaries containing gene info
except SyntaxError as error:
flash(... | 615,136 |
Create a new gene panel.
Args:
store(scout.adapter.MongoAdapter)
institute_id(str)
panel_name(str)
display_name(str)
csv_lines(iterable(str)): Stream with genes
Returns:
panel_id: the ID of the new panel document created or None | def new_panel(store, institute_id, panel_name, display_name, csv_lines):
institute_obj = store.institute(institute_id)
if institute_obj is None:
flash("{}: institute not found".format(institute_id))
return None
panel_obj = store.gene_panel(panel_name)
if panel_obj:
flash("p... | 615,137 |
Export variants which have been verified for an institute
and write them to an excel file.
Args:
collaborator(str): institute id
test(bool): True if the function is called for testing purposes
outpath(str): path to output file
Returns:
written_files(int): number of writ... | def verified(context, collaborator, test, outpath=None):
written_files = 0
collaborator = collaborator or 'cust000'
LOG.info('Exporting verified variants for cust {}'.format(collaborator))
adapter = context.obj['adapter']
verified_vars = adapter.verified(institute_id=collaborator)
LOG.info... | 615,156 |
Get vcf entry from variant object
Args:
variant_obj(dict)
Returns:
variant_string(str): string representing variant in vcf format | def get_vcf_entry(variant_obj, case_id=None):
if variant_obj['category'] == 'snv':
var_type = 'TYPE'
else:
var_type = 'SVTYPE'
info_field = ';'.join(
[
'END='+str(variant_obj['end']),
var_type+'='+variant_obj['sub_category'].upper()
... | 615,158 |
Generate an md5-key from a list of arguments.
Args:
list_of_arguments: A list of strings
Returns:
A md5-key object generated from the list of strings. | def generate_md5_key(list_of_arguments):
for arg in list_of_arguments:
if not isinstance(arg, string_types):
raise SyntaxError("Error in generate_md5_key: "
"Argument: {0} is a {1}".format(arg, type(arg)))
hash = hashlib.md5()
hash.update(' '.join(list... | 615,160 |
Parse the genetic models entry of a vcf
Args:
models_info(str): The raw vcf information
case_id(str)
Returns:
genetic_models(list) | def parse_genetic_models(models_info, case_id):
genetic_models = []
if models_info:
for family_info in models_info.split(','):
splitted_info = family_info.split(':')
if splitted_info[0] == case_id:
genetic_models = splitted_info[1].split('|')
return gene... | 615,169 |
Add a institute to the database
Args:
institute_obj(Institute) | def add_institute(self, institute_obj):
internal_id = institute_obj['internal_id']
display_name = institute_obj['internal_id']
# Check if institute already exists
if self.institute(institute_id=internal_id):
raise IntegrityError("Institute {0} already exists in data... | 615,171 |
Featch a single institute from the backend
Args:
institute_id(str)
Returns:
Institute object | def institute(self, institute_id):
LOG.debug("Fetch institute {}".format(institute_id))
institute_obj = self.institute_collection.find_one({
'_id': institute_id
})
if institute_obj is None:
LOG.debug("Could not find institute {0}".format(institute_id))
... | 615,173 |
Fetch all institutes.
Args:
institute_ids(list(str))
Returns:
res(pymongo.Cursor) | def institutes(self, institute_ids=None):
query = {}
if institute_ids:
query['_id'] = {'$in': institute_ids}
LOG.debug("Fetching all institutes")
return self.institute_collection.find(query) | 615,174 |
Check if a string is a valid date
Args:
date(str)
Returns:
bool | def match_date(date):
date_pattern = re.compile("^(19|20)\d\d[- /.](0[1-9]|1[012])[- /.](0[1-9]|[12][0-9]|3[01])")
if re.match(date_pattern, date):
return True
return False | 615,175 |
Return a datetime object if there is a valid date
Raise exception if date is not valid
Return todays date if no date where added
Args:
date(str)
date_format(str)
Returns:
date_obj(datetime.datetime) | def get_date(date, date_format = None):
date_obj = datetime.datetime.now()
if date:
if date_format:
date_obj = datetime.datetime.strptime(date, date_format)
else:
if match_date(date):
if len(date.split('-')) == 3:
date = date.split... | 615,176 |
Parse transcript information and get the gene information from there.
Use hgnc_id as identifier for genes and ensembl transcript id to identify transcripts
Args:
transcripts(iterable(dict))
Returns:
genes (list(dict)): A list with dictionaries that represents genes | def parse_genes(transcripts):
# Dictionary to group the transcripts by hgnc_id
genes_to_transcripts = {}
# List with all genes and there transcripts
genes = []
hgvs_identifier = None
canonical_transcript = None
exon = None
# Group all transcripts by gene
for transcript in ... | 615,178 |
Parse the rank score
Args:
rank_score_entry(str): The raw rank score entry
case_id(str)
Returns:
rank_score(float) | def parse_rank_score(rank_score_entry, case_id):
rank_score = None
if rank_score_entry:
for family_info in rank_score_entry.split(','):
splitted_info = family_info.split(':')
if case_id == splitted_info[0]:
rank_score = float(splitted_info[1])
return rank... | 615,179 |
Parse transcript information from VCF variants
Args:
raw_transcripts(iterable(dict)): An iterable with raw transcript
information
Yields:
transcript(dict) A dictionary with transcript information | def parse_transcripts(raw_transcripts, allele=None):
for entry in raw_transcripts:
transcript = {}
# There can be several functional annotations for one variant
functional_annotations = entry.get('CONSEQUENCE', '').split('&')
transcript['functional_annotations'] = functional_ann... | 615,181 |
Check if a connection could be made to the mongo process specified
Args:
host(str)
port(int)
username(str)
password(str)
authdb (str): database to to for authentication
max_delay(int): Number of milliseconds to wait for connection
Returns:
bool: If conne... | def check_connection(host='localhost', port=27017, username=None, password=None,
authdb=None, max_delay=1):
#uri looks like:
#mongodb://[username:password@]host1[:port1][,host2[:port2],...[,hostN[:portN]]][/[database][?options]]
if username and password:
uri = ("mongodb://{... | 615,182 |
Build a transcript object
These represents the transcripts that are parsed from the VCF, not
the transcript definitions that are collected from ensembl.
Args:
transcript(dict): Parsed transcript information
Returns:
transcript_obj(dict) | def build_transcript(transcript, build='37'):
# Transcripts has to have an id
transcript_id = transcript['transcript_id']
transcript_obj = dict(
transcript_id = transcript_id
)
# Transcripts has to belong to a gene
transcript_obj['hgnc_id'] = transcript['hgnc_id']
if ... | 615,187 |
Update an existing user.
Args:
user_obj(dict)
Returns:
updated_user(dict) | def update_user(self, user_obj):
LOG.info("Updating user %s", user_obj['_id'])
updated_user = self.user_collection.find_one_and_replace(
{'_id': user_obj['_id']},
user_obj,
return_document=pymongo.ReturnDocument.AFTER
)
return updated_user | 615,188 |
Add a user object to the database
Args:
user_obj(scout.models.User): A dictionary with user information
Returns:
user_info(dict): a copy of what was inserted | def add_user(self, user_obj):
LOG.info("Adding user %s to the database", user_obj['email'])
if not '_id' in user_obj:
user_obj['_id'] = user_obj['email']
try:
self.user_collection.insert_one(user_obj)
LOG.debug("User inserted")
except Dup... | 615,189 |
Return all users from the database
Args:
institute(str): A institute_id
Returns:
res(pymongo.Cursor): A cursor with users | def users(self, institute=None):
query = {}
if institute:
LOG.info("Fetching all users from institute %s", institute)
query = {'institutes': {'$in': [institute]}}
else:
LOG.info("Fetching all users")
res = self.user_collection.fin... | 615,190 |
Fetch a user from the database.
Args:
email(str)
Returns:
user_obj(dict) | def user(self, email):
LOG.info("Fetching user %s", email)
user_obj = self.user_collection.find_one({'_id': email})
return user_obj | 615,191 |
Delete a user from the database
Args:
email(str)
Returns:
user_obj(dict) | def delete_user(self, email):
LOG.info("Deleting user %s", email)
user_obj = self.user_collection.delete_one({'_id': email})
return user_obj | 615,192 |
Load all the exons
Transcript information is from ensembl.
Check that the transcript that the exon belongs to exists in the database
Args:
adapter(MongoAdapter)
exon_lines(iterable): iterable with ensembl exon lines
build(str)
ensembl_transcripts(dict): Existing ensembl... | def load_exons(adapter, exon_lines, build='37', ensembl_genes=None):
# Fetch all genes with ensemblid as keys
ensembl_genes = ensembl_genes or adapter.ensembl_genes(build)
hgnc_id_transcripts = adapter.id_transcripts_by_gene(build=build)
if isinstance(exon_lines, DataFrame):
exons = pa... | 615,198 |
Return a parsed variant
Get all the necessary information to build a variant object
Args:
variant(cyvcf2.Variant)
case(dict)
variant_type(str): 'clinical' or 'research'
rank_results_header(list)
vep_header(list)
individual_positions(dict): Explain what posit... | def parse_variant(variant, case, variant_type='clinical',
rank_results_header=None, vep_header=None,
individual_positions=None, category=None):
# These are to display how the rank score is built
rank_results_header = rank_results_header or []
# Vep information
vep_... | 615,199 |
Update a gene object with links
Args:
gene_obj(dict)
build(int)
Returns:
gene_obj(dict): gene_obj updated with many links | def add_gene_links(gene_obj, build=37):
try:
build = int(build)
except ValueError:
build = 37
# Add links that use the hgnc_id
hgnc_id = gene_obj['hgnc_id']
gene_obj['hgnc_link'] = genenames(hgnc_id)
gene_obj['omim_link'] = omim(hgnc_id)
# Add links that use ensembl_id
... | 615,201 |
Parse an hgnc formated line
Args:
line(list): A list with hgnc gene info
header(list): A list with the header info
Returns:
hgnc_info(dict): A dictionary with the relevant info | def parse_hgnc_line(line, header):
hgnc_gene = {}
line = line.rstrip().split('\t')
raw_info = dict(zip(header, line))
# Skip all genes that have status withdrawn
if 'Withdrawn' in raw_info['status']:
return hgnc_gene
hgnc_symbol = raw_info['symbol']
hgnc_gene['hgnc_symbol']... | 615,206 |
Parse lines with hgnc formated genes
This is designed to take a dump with genes from HGNC.
This is downloaded from:
ftp://ftp.ebi.ac.uk/pub/databases/genenames/new/tsv/hgnc_complete_set.txt
Args:
lines(iterable(str)): An iterable with HGNC formated genes
Yields:
... | def parse_hgnc_genes(lines):
header = []
logger.info("Parsing hgnc genes...")
for index, line in enumerate(lines):
if index == 0:
header = line.split('\t')
elif len(line) > 1:
hgnc_gene = parse_hgnc_line(line=line, header=header)
if hgnc_gene:
... | 615,207 |
Create an open clinvar submission for a user and an institute
Args:
user_id(str): a user ID
institute_id(str): an institute ID
returns:
submission(obj): an open clinvar submission object | def create_submission(self, user_id, institute_id):
submission_obj = {
'status' : 'open',
'created_at' : datetime.now(),
'user_id' : user_id,
'institute_id' : institute_id
}
LOG.info("Creating a new clinvar submission for user '%s' and in... | 615,211 |
Deletes a Clinvar submission object, along with all associated clinvar objects (variants and casedata)
Args:
submission_id(str): the ID of the submission to be deleted
Returns:
deleted_objects(int): the number of associated objects removed (variants and/or cased... | def delete_submission(self, submission_id):
LOG.info("Deleting clinvar submission %s", submission_id)
submission_obj = self.clinvar_submission_collection.find_one({ '_id' : ObjectId(submission_id)})
submission_variants = submission_obj.get('variant_data')
submission_casedata = ... | 615,212 |
Retrieve the database id of an open clinvar submission for a user and institute,
if none is available then create a new submission and return it
Args:
user_id(str): a user ID
institute_id(str): an institute ID
Returns:
submission(obj) : ... | def get_open_clinvar_submission(self, user_id, institute_id):
LOG.info("Retrieving an open clinvar submission for user '%s' and institute %s", user_id, institute_id)
query = dict(user_id=user_id, institute_id=institute_id, status='open')
submission = self.clinvar_submission_collection.... | 615,213 |
saves an official clinvar submission ID in a clinvar submission object
Args:
clinvar_id(str): a string with a format: SUB[0-9]. It is obtained from clinvar portal when starting a new submission
submission_id(str): submission_id(str) : id of the submission to be updated
... | def update_clinvar_id(self, clinvar_id, submission_id ):
updated_submission = self.clinvar_submission_collection.find_one_and_update( {'_id': ObjectId(submission_id)}, { '$set' : {'clinvar_subm_id' : clinvar_id, 'updated_at': datetime.now()} }, upsert=True, return_document=pymongo.ReturnDocument.AFTER ... | 615,214 |
Returns the official Clinvar submission ID for a submission object
Args:
submission_id(str): submission_id(str) : id of the submission
Returns:
clinvar_subm_id(str): a string with a format: SUB[0-9]. It is obtained from clinvar portal when starting a new submiss... | def get_clinvar_id(self, submission_id):
submission_obj = self.clinvar_submission_collection.find_one({'_id': ObjectId(submission_id)})
clinvar_subm_id = submission_obj.get('clinvar_subm_id') # This key does not exist if it was not previously provided by user
return clinvar_subm_id | 615,215 |
Adds submission_objects to clinvar collection and update the coresponding submission object with their id
Args:
submission_id(str) : id of the submission to be updated
submission_objects(tuple): a tuple of 2 elements coresponding to a list of variants and a list of case data... | def add_to_submission(self, submission_id, submission_objects):
LOG.info("Adding new variants and case data to clinvar submission '%s'", submission_id)
# Insert variant submission_objects into clinvar collection
# Loop over the objects
for var_obj in submission_objects[0]:
... | 615,216 |
Set a clinvar submission ID to 'closed'
Args:
submission_id(str): the ID of the clinvar submission to close
Return
updated_submission(obj): the submission object with a 'closed' status | def update_clinvar_submission_status(self, user_id, submission_id, status):
LOG.info('closing clinvar submission "%s"', submission_id)
if status == 'open': # just close the submission its status does not affect the other submissions for this user
# Close all other submissions for t... | 615,217 |
Collect all open and closed clinvar submission created by a user for an institute
Args:
user_id(str): a user ID
institute_id(str): an institute ID
Returns:
submissions(list): a list of clinvar submission objects | def clinvar_submissions(self, user_id, institute_id):
LOG.info("Retrieving all clinvar submissions for user '%s', institute '%s'", user_id, institute_id)
# get first all submission objects
query = dict(user_id=user_id, institute_id=institute_id)
results = list(self.clinvar_submi... | 615,218 |
Get all variants included in clinvar submissions for a case
Args:
case_id(str): a case _id
Returns:
submission_variants(dict): keys are variant ids and values are variant submission objects | def case_to_clinVars(self, case_id):
query = dict(case_id=case_id, csv_type='variant')
clinvar_objs = list(self.clinvar_collection.find(query))
submitted_vars = {}
for clinvar in clinvar_objs:
submitted_vars[clinvar.get('local_id')] = clinvar
return submitte... | 615,221 |
Parse hpo phenotype
Args:
hpo_line(str): A iterable with hpo phenotype lines
Yields:
hpo_info(dict) | def parse_hpo_phenotype(hpo_line):
hpo_line = hpo_line.rstrip().split('\t')
hpo_info = {}
hpo_info['hpo_id'] = hpo_line[0]
hpo_info['description'] = hpo_line[1]
hpo_info['hgnc_symbol'] = hpo_line[3]
return hpo_info | 615,222 |
Parse hpo gene information
Args:
hpo_line(str): A iterable with hpo phenotype lines
Yields:
hpo_info(dict) | def parse_hpo_gene(hpo_line):
if not len(hpo_line) > 3:
return {}
hpo_line = hpo_line.rstrip().split('\t')
hpo_info = {}
hpo_info['hgnc_symbol'] = hpo_line[1]
hpo_info['description'] = hpo_line[2]
hpo_info['hpo_id'] = hpo_line[3]
return hpo_info | 615,223 |
Parse hpo disease line
Args:
hpo_line(str) | def parse_hpo_disease(hpo_line):
hpo_line = hpo_line.rstrip().split('\t')
hpo_info = {}
disease = hpo_line[0].split(':')
hpo_info['source'] = disease[0]
hpo_info['disease_nr'] = int(disease[1])
hpo_info['hgnc_symbol'] = None
hpo_info['hpo_term'] = None
if len(hpo_line) >= ... | 615,224 |
Parse hpo phenotypes
Group the genes that a phenotype is associated to in 'genes'
Args:
hpo_lines(iterable(str)): A file handle to the hpo phenotypes file
Returns:
hpo_terms(dict): A dictionary with hpo_ids as keys and terms as values
{
<hpo_id>: {... | def parse_hpo_phenotypes(hpo_lines):
hpo_terms = {}
LOG.info("Parsing hpo phenotypes...")
for index, line in enumerate(hpo_lines):
if index > 0 and len(line) > 0:
hpo_info = parse_hpo_phenotype(line)
hpo_term = hpo_info['hpo_id']
hgnc_symbol = hpo_info['hgnc_... | 615,225 |
Parse hpo disease phenotypes
Args:
hpo_lines(iterable(str))
Returns:
diseases(dict): A dictionary with mim numbers as keys | def parse_hpo_diseases(hpo_lines):
diseases = {}
LOG.info("Parsing hpo diseases...")
for index, line in enumerate(hpo_lines):
# First line is a header
if index == 0:
continue
# Skip empty lines
if not len(line) > 3:
continue
# Parse the in... | 615,226 |
Parse the map from hpo term to hgnc symbol
Args:
lines(iterable(str)):
Yields:
hpo_to_gene(dict): A dictionary with information on how a term map to a hgnc symbol | def parse_hpo_to_genes(hpo_lines):
for line in hpo_lines:
if line.startswith('#') or len(line) < 1:
continue
line = line.rstrip().split('\t')
hpo_id = line[0]
hgnc_symbol = line[3]
yield {
'hpo_id': hpo_id,
'hgnc_symbol': hgnc... | 615,227 |
Parse HPO gene information
Args:
hpo_lines(iterable(str))
Returns:
diseases(dict): A dictionary with hgnc symbols as keys | def parse_hpo_genes(hpo_lines):
LOG.info("Parsing HPO genes ...")
genes = {}
for index, line in enumerate(hpo_lines):
# First line is header
if index == 0:
continue
if len(line) < 5:
continue
gene_info = parse_hpo_gene(line)
hgnc_symbol = ... | 615,228 |
Get a set with all genes that have incomplete penetrance according to HPO
Args:
hpo_lines(iterable(str))
Returns:
incomplete_penetrance_genes(set): A set with the hgnc symbols of all
genes with incomplete penetrance | def get_incomplete_penetrance_genes(hpo_lines):
genes = parse_hpo_genes(hpo_lines)
incomplete_penetrance_genes = set()
for hgnc_symbol in genes:
if genes[hgnc_symbol].get('incomplete_penetrance'):
incomplete_penetrance_genes.add(hgnc_symbol)
return incomplete_penetrance_genes | 615,229 |
Make sure that the gene panels exist in the database
Also check if the default panels are defined in gene panels
Args:
adapter(MongoAdapter)
panels(list(str)): A list with panel names
Returns:
panels_exists(bool) | def check_panels(adapter, panels, default_panels=None):
default_panels = default_panels or []
panels_exist = True
for panel in default_panels:
if panel not in panels:
log.warning("Default panels have to be defined in panels")
panels_exist = False
for panel in panels:... | 615,234 |
Load all variants in a region defined by a HGNC id
Args:
adapter (MongoAdapter)
case_id (str): Case id
hgnc_id (int): If all variants from a gene should be uploaded
chrom (str): If variants from coordinates should be uploaded
start (int): Start position for region
en... | def load_region(adapter, case_id, hgnc_id=None, chrom=None, start=None, end=None):
if hgnc_id:
gene_obj = adapter.hgnc_gene(hgnc_id)
if not gene_obj:
ValueError("Gene {} does not exist in database".format(hgnc_id))
chrom = gene_obj['chromosome']
start = gene_obj['sta... | 615,235 |
Load a new case from a Scout config.
Args:
adapter(MongoAdapter)
config(dict): loading info
ped(Iterable(str)): Pedigree ingformation
update(bool): If existing case should be updated | def load_scout(adapter, config, ped=None, update=False):
log.info("Check that the panels exists")
if not check_panels(adapter, config.get('gene_panels', []),
config.get('default_gene_panels')):
raise ConfigError("Some panel(s) does not exist in the database")
case_obj = ... | 615,236 |
Get the hgnc id for a gene
The proprity order will be
1. if there is a hgnc id this one will be choosen
2. if the hgnc symbol matches a genes proper hgnc symbol
3. if the symbol ony matches aliases on several genes one will be
choosen at random
Args:
gene... | def get_hgnc_id(gene_info, adapter):
hgnc_id = gene_info.get('hgnc_id')
hgnc_symbol = gene_info.get('hgnc_symbol')
true_id = None
if hgnc_id:
true_id = int(hgnc_id)
else:
gene_result = adapter.hgnc_genes(hgnc_symbol)
if gene_result.count() == 0:
raise Excep... | 615,240 |
Load the hpo terms and hpo diseases into database
Args:
adapter(MongoAdapter)
disease_lines(iterable(str)): These are the omim genemap2 information
hpo_lines(iterable(str))
disease_lines(iterable(str))
hpo_gene_lines(iterable(str)) | def load_hpo(adapter, disease_lines, hpo_disease_lines=None, hpo_lines=None, hpo_gene_lines=None):
# Create a map from gene aliases to gene objects
alias_genes = adapter.genes_by_alias()
# Fetch the hpo terms if no file
if not hpo_lines:
hpo_lines = fetch_hpo_terms()
# Fetch the h... | 615,244 |
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