Supporting population allele frequencies #29
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| Original file line number | Diff line number | Diff line change |
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| @@ -0,0 +1,34 @@ | ||
| { | ||
| "1000_genomes": [ | ||
| {"name": "1000GENOMES:phase_3:ALL", "frequencies": {"af": "AF"}}, | ||
| {"name": "1000GENOMES:phase_3:AFR", "frequencies": {"af": "AFR_AF"}}, | ||
| {"name": "1000GENOMES:phase_3:AMR", "frequencies": {"af": "AMR_AF"}}, | ||
| {"name": "1000GENOMES:phase_3:EAS", "frequencies": {"af": "EAS_AF"}}, | ||
| {"name": "1000GENOMES:phase_3:EUR", "frequencies": {"af": "EUR_AF"}}, | ||
| {"name": "1000GENOMES:phase_3:SAS", "frequencies": {"af": "SAS_AF" }} | ||
| ], | ||
| "gnomAD_exomes": [ | ||
| {"name": "gnomADe:ALL", "frequencies": {"af": "gnomAD_exomes_AF", "ac": "gnomAD_exomes_AC", "an": "gnomAD_exomes_AN"}}, | ||
| {"name": "gnomADe:afr", "frequencies": {"af": "gnomAD_exomes_AF_afr", "ac": "gnomAD_exomes_AC_afr", "an": "gnomAD_exomes_AN_afr"}}, | ||
| {"name": "gnomADe:amr", "frequencies": {"af": "gnomAD_exomes_AF_amr", "ac": "gnomAD_exomes_AC_amr", "an": "gnomAD_exomes_AN_amr"}}, | ||
| {"name": "gnomADe:asj", "frequencies": {"af": "gnomAD_exomes_AF_asj", "ac": "gnomAD_exomes_AC_asj", "an": "gnomAD_exomes_AN_asj"}}, | ||
| {"name": "gnomADe:eas", "frequencies": {"af": "gnomAD_exomes_AF_eas", "ac": "gnomAD_exomes_AC_eas", "an": "gnomAD_exomes_AN_eas"}}, | ||
| {"name": "gnomADe:fin", "frequencies": {"af": "gnomAD_exomes_AF_fin", "ac": "gnomAD_exomes_AC_fin", "an": "gnomAD_exomes_AN_fin"}}, | ||
| {"name": "gnomADe:nfe", "frequencies": {"af": "gnomAD_exomes_AF_nfe", "ac": "gnomAD_exomes_AC_nfe", "an": "gnomAD_exomes_AN_nfe"}}, | ||
| {"name": "gnomADe:oth", "frequencies": {"af": "gnomAD_exomes_AF_oth", "ac": "gnomAD_exomes_AC_oth", "an": "gnomAD_exomes_AN_oth"}}, | ||
| {"name": "gnomADe:sas", "frequencies": {"af": "gnomAD_exomes_AF_sas", "ac": "gnomAD_exomes_AC_sas", "an": "gnomAD_exomes_AN_sas"}} | ||
| ], | ||
| "gnomAD_genomes": [ | ||
| {"name": "gnomADg:ALL", "frequencies": {"af": "gnomAD_genomes_AF", "ac": "gnomAD_genomes_AC", "an": "gnomAD_genomes_AN"}}, | ||
| {"name": "gnomADg:afr", "frequencies": {"af": "gnomAD_genomes_AF_afr", "ac": "gnomAD_genomes_AC_afr", "an": "gnomAD_genomes_AN_afr"}}, | ||
| {"name": "gnomADg:ami", "frequencies": {"af": "gnomAD_genomes_AF_ami", "ac": "gnomAD_genomes_AC_ami", "an": "gnomAD_genomes_AN_ami"}}, | ||
| {"name": "gnomADg:amr", "frequencies": {"af": "gnomAD_genomes_AF_amr", "ac": "gnomAD_genomes_AC_amr", "an": "gnomAD_genomes_AN_amr"}}, | ||
| {"name": "gnomADg:asj", "frequencies": {"af": "gnomAD_genomes_AF_asj", "ac": "gnomAD_genomes_AC_asj", "an": "gnomAD_genomes_AN_asj"}}, | ||
| {"name": "gnomADg:eas", "frequencies": {"af": "gnomAD_genomes_AF_eas", "ac": "gnomAD_genomes_AC_eas", "an": "gnomAD_genomes_AN_eas"}}, | ||
| {"name": "gnomADg:fin", "frequencies": {"af": "gnomAD_genomes_AF_fin", "ac": "gnomAD_genomes_AC_fin", "an": "gnomAD_genomes_AN_fin"}}, | ||
| {"name": "gnomADg:mid", "frequencies": {"af": "gnomAD_genomes_AF_mid", "ac": "gnomAD_genomes_AC_mid", "an": "gnomAD_genomes_AN_mid"}}, | ||
| {"name": "gnomADg:nfe", "frequencies": {"af": "gnomAD_genomes_AF_nfe", "ac": "gnomAD_genomes_AC_nfe", "an": "gnomAD_genomes_AN_nfe"}}, | ||
| {"name": "gnomADg:oth", "frequencies": {"af": "gnomAD_genomes_AF_oth", "ac": "gnomAD_genomes_AC_oth", "an": "gnomAD_genomes_AN_oth"}}, | ||
| {"name": "gnomADg:sas", "frequencies": {"af": "gnomAD_genomes_AF_sas", "ac": "gnomAD_genomes_AC_sas", "an": "gnomAD_genomes_AN_sas"}} | ||
| ] | ||
| } |
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@@ -27,6 +27,7 @@ def __init__(self, record: Any, header: Any) -> None: | |
| self.info = record.INFO | ||
| self.type = "Variant" | ||
| self.vep_version = re.search("v\d+", self.header.get_lines("VEP")[0].value).group() | ||
| self.population_map = {} | ||
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| def get_alternative_names(self) -> List: | ||
| return [] | ||
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@@ -196,7 +197,7 @@ def get_most_severe_consequence(self) -> Mapping: | |
| csq_record_list = csq_record.split("|") | ||
| for cons in csq_record_list[consequence_index].split("&"): | ||
| rank = consequence_rank[cons] | ||
| consequence_map[int(rank)] = cons | ||
| return{ | ||
| "result": consequence_map[min(consequence_map.keys())] , | ||
| "analysis_method": { | ||
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@@ -240,34 +241,101 @@ def get_info_key_index(self, key: str, info_id: str ="CSQ") -> int: | |
| for index, value in enumerate(csq_list): | ||
| if value == key: | ||
| return index | ||
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| def traverse_population_info(self) -> Mapping: | ||
| directory = os.path.dirname(__file__) | ||
| with open(os.path.join(directory,'populations.json')) as pop_file: | ||
| pop_mapping = json.load(pop_file) | ||
| population_frequency_map = {} | ||
| for csq_record in self.info["CSQ"]: | ||
| csq_record_list = csq_record.split("|") | ||
| allele_index = self.get_info_key_index("Allele") | ||
| if csq_record_list[allele_index] is not None: | ||
| if csq_record_list[allele_index] not in population_frequency_map.keys(): | ||
| population_frequency_map[csq_record_list[allele_index]] = {} | ||
| for pop_key, pop in pop_mapping.items(): | ||
| for sub_pop in pop: | ||
| if sub_pop["name"] in population_frequency_map[csq_record_list[allele_index]]: | ||
| continue | ||
| allele_count = allele_number = allele_frequency = None | ||
| for freq_key, freq_val in sub_pop["frequencies"].items(): | ||
| col_index = self.get_info_key_index(freq_val) | ||
| if col_index and csq_record_list[col_index] is not None: | ||
| if freq_key == "af": | ||
| allele_frequency = csq_record_list[col_index] or None | ||
| elif freq_key == "an": | ||
| allele_number = csq_record_list[col_index] or None | ||
| elif freq_key == "ac": | ||
| allele_count = csq_record_list[col_index] or None | ||
| else: | ||
| raise Exception('Frequency metric is not recognised') | ||
| population_frequency = { | ||
| "population_name": sub_pop["name"], | ||
| "allele_frequency": allele_frequency, | ||
| "allele_count": allele_count, | ||
| "allele_number": allele_number, | ||
| "is_minor_allele": False, | ||
| "is_hpmaf": False | ||
| } | ||
| if allele_frequency: | ||
| population_frequency_map[csq_record_list[allele_index]][sub_pop["name"]] = population_frequency | ||
| return population_frequency_map | ||
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| def set_frequency_flags(self): | ||
| """ | ||
| Calculates MAF (minor allele frequency) and HPMAF by iterating through each allele | ||
| """ | ||
| allele_list = self.get_alleles() | ||
| directory = os.path.dirname(__file__) | ||
| with open(os.path.join(directory,'populations.json')) as pop_file: | ||
| pop_mapping = json.load(pop_file) | ||
| pop_names = [] | ||
| for pop in pop_mapping.values(): | ||
| pop_names.extend([sub_pop["name"] for sub_pop in pop]) | ||
| hpmaf = [] | ||
| pop_frequency_map = self.traverse_population_info() | ||
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| for pop_name in pop_names: | ||
| by_population = [] | ||
| for allele in allele_list: | ||
| if allele.minimise_allele(allele.alt) in pop_frequency_map: | ||
| pop_freqs = pop_frequency_map[allele.minimise_allele(allele.alt)].values() | ||
| # Calculate reference allele from parsed frequency info of all alleles | ||
| if allele.get_allele_type()["accession_id"] == "biological_region" and len(by_population)>0 : | ||
| allele_frequency_ref = 1 - sum(list(zip(*by_population))[0]) | ||
| if allele_frequency_ref <= 1 and allele_frequency_ref >= 0: | ||
| population_frequency_ref = { | ||
| "population_name": pop_name, | ||
| "allele_frequency": allele_frequency_ref , | ||
| "allele_count": None, | ||
| "allele_number": None, | ||
| "is_minor_allele": False, | ||
| "is_hpmaf": False | ||
| } | ||
| minimised_allele = allele.minimise_allele(allele.alt) | ||
| if minimised_allele not in pop_frequency_map: | ||
| pop_frequency_map[minimised_allele] = {} | ||
| pop_frequency_map[minimised_allele][pop_name] = population_frequency_ref | ||
| by_population.append([allele_frequency_ref,minimised_allele,pop_name]) | ||
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| else: | ||
| for pop_freq in pop_freqs: | ||
| if pop_name == pop_freq["population_name"] and pop_freq["allele_frequency"]: | ||
| minimised_allele = allele.minimise_allele(allele.alt) | ||
| by_population.append([float(pop_freq["allele_frequency"]),minimised_allele, pop_name]) | ||
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| by_population_sorted = sorted(by_population, key=lambda item: item[0]) | ||
| if len(by_population_sorted) >= 2: | ||
| maf_frequency, maf_allele, maf_population = by_population_sorted[-2] | ||
| pop_frequency_map[maf_allele][maf_population]["is_minor_allele"] = True | ||
| hpmaf.append([maf_frequency,maf_allele,maf_population]) | ||
| if len(hpmaf) > 0: | ||
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There was a problem hiding this comment. There can be multiple Not much effect in EV currently as not part of the view. There was a problem hiding this comment. Thanks @nakib103 , this seems valid. Similarly, there can be multiple alleles having MAF, we need to mark them. Example to test multiple alleles having same MAF: There was a problem hiding this comment. Thanks Likhitha, also tested for |
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| hpmaf_sorted = sorted(hpmaf, key=lambda item: item[0]) | ||
| _, hpmaf_allele, hpmaf_population = hpmaf_sorted[-1] | ||
| pop_frequency_map[hpmaf_allele][hpmaf_population]["is_hpmaf"] = True | ||
| return pop_frequency_map | ||
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| @@ -0,0 +1,14 @@ | ||
| type Population{ | ||
| """ | ||
| Population | ||
| """ | ||
| name: String ## Requires to be nullable as super-population can be a null field | ||
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There was a problem hiding this comment. Does the comment refer to the correct field? It correctly points out that the super_population field is nullable; but this is the There was a problem hiding this comment. Due to the way GraphQL handles nullability, a nullable Type (Type population in case of Error: There was a problem hiding this comment.
The error looks to me like the resolver is trying to return some empty super-population object rather than a true null. GraphQL type validator seems to be saying here that it received an object, rather than a null; and when it looked into its Consider this api: https://swapi-graphql.eskerda.vercel.app/
if you request a person with a non-existing id, there is an error about the missing person; but the person in the data is just set to null, and there are no errors about the non-nullable field Person.id
There was a problem hiding this comment. Thanks @azangru , you are right. This seems be to an issue with the metadata file which should be fixed in the latest commits |
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| size: Int! | ||
| description: String! | ||
| type: String | ||
| is_global: Boolean | ||
| is_from_genotypes: Boolean | ||
| display_group_name: String | ||
| super_population: Population | ||
| sub_populations: [Population] | ||
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There was a problem hiding this comment. Looks like all fields in the schema should be non-nullable (unless There was a problem hiding this comment. Updated the file according to VDM, all the fields except |
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| } | ||
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| @@ -1,5 +1,5 @@ | ||
| query pop_example { | ||
| populations(genome_id: "a7335667-93e7-11ec-a39d-005056b38ce3") | ||
| { | ||
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| name | ||
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We now have multiple population and corresponding MAF. We should somehow have a way to tell which MAF we want to represent in the GB drawer. Before, we only have one population and it was not a issue.
It does not effect the current EV design.
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This may need further discussion for how we would like the API to communicate this, for example, through a field in
variantor through the sorting order inpopulation_allele_frequencies