Skip to content

GWAS Studies and Associations

See the FAQ for dependencies and return conventions.

1) Retrieve GWAS associations for a SNP

  • Purpose: Retrieve GWAS associations for a SNP.
  • Method: Use GWASAssociationsForSNP to query or submit the supplied input and parse the response.
  • API： dnakit.databases.gwas_get_associations_for_snp(*, rs_id, sort=None, direction=None, size=None, page=None, verbose=True)
  • Input: Provide rs_id.
  • Output: Returns a list of records; each record includes association_id, p_value, beta, efo_traits and related fields.
  • Example code:
import dnakit

result = dnakit.databases.gwas_get_associations_for_snp(
    rs_id='rs7903146',
    sort='p_value',
    direction='asc',
    size=5,
    verbose=False,
)
print(result)
  • Example output: The response has the following shape; records depend on the input and source.

Response-shape excerpt; <…> denotes type placeholders, not a captured query result.

[
  {
    "association_id": "<integer>",
    "p_value": "<number>",
    "beta": "<string>",
    "efo_traits": [
      "<object>"
    ],
    "reported_trait": [
      "<string>"
    ],
    "accession_id": "<string>",
    "pubmed_id": "<string>",
    "first_author": "<string>"
  }
]

Full parameters and usage notes

2) Retrieve associations from a GWAS study

  • Purpose: Retrieve associations from a GWAS study.
  • Method: Use GWASAssociationsForStudy to query or submit the supplied input and parse the response.
  • API： dnakit.databases.gwas_get_associations_for_study(*, accession_id, size=None, page=None, verbose=True)
  • Input: Provide accession_id.
  • Output: Returns a list of records; each record includes association_id, p_value, beta, efo_traits and related fields.
  • Example code:
import dnakit

result = dnakit.databases.gwas_get_associations_for_study(
    accession_id='GCST000392',
    size=10,
    verbose=False,
)
print(result)
  • Example output: The response has the following shape; records depend on the input and source.

Response-shape excerpt; <…> denotes type placeholders, not a captured query result.

[
  {
    "association_id": "<integer>",
    "p_value": "<number>",
    "beta": "<string>",
    "efo_traits": [
      "<object>"
    ],
    "reported_trait": [
      "<string>"
    ],
    "accession_id": "<string>",
    "pubmed_id": "<string>",
    "first_author": "<string>"
  }
]

Full parameters and usage notes

3) Retrieve GWAS associations for a trait

  • Purpose: Retrieve GWAS associations for a trait.
  • Method: Use GWASAssociationsForTrait to query or submit the supplied input and parse the response.
  • API： dnakit.databases.gwas_get_associations_for_trait(*, disease_trait=None, efo_uri=None, efo_id=None, efo_trait=None, size=None, page=None, verbose=True)
  • Input: Choose filters as shown in the example; omitted options use the operation defaults. Select exactly one argument group: disease_trait / efo_uri / efo_id / efo_trait.
  • Output: Returns a list of records; each record includes association_id, p_value, beta, efo_traits and related fields.
  • Example code:
import dnakit

result = dnakit.databases.gwas_get_associations_for_trait(
    disease_trait='type 2 diabetes',
    size=10,
    verbose=False,
)
print(result)
  • Example output: The response has the following shape; records depend on the input and source.

Response-shape excerpt; <…> denotes type placeholders, not a captured query result.

[
  {
    "association_id": "<integer>",
    "p_value": "<number>",
    "beta": "<string>",
    "efo_traits": [
      "<object>"
    ],
    "reported_trait": [
      "<string>"
    ],
    "accession_id": "<string>",
    "pubmed_id": "<string>",
    "first_author": "<string>"
  }
]

Full parameters and usage notes

4) Retrieve GWAS SNP details by rsID

  • Purpose: Retrieve GWAS SNP details by rsID.
  • Method: Use GWASSNPByID to query or submit the supplied input and parse the response.
  • API： dnakit.databases.gwas_get_snp_by_id(*, rs_id, verbose=True)
  • Input: Provide rs_id.
  • Output: Returns a mapping with rs_id, merged, functional_class, last_update_date and related fields.
  • Example code:
import dnakit

result = dnakit.databases.gwas_get_snp_by_id(
    rs_id='rs429358',
    verbose=False,
)
print(result)
  • Example output: The response has the following shape; records depend on the input and source.

Response-shape excerpt; <…> denotes type placeholders, not a captured query result.

{
  "rs_id": "<string>",
  "merged": "<integer>",
  "functional_class": "<string>",
  "last_update_date": "<string>",
  "locations": [
    {
      "chromosome_name": "<string>",
      "chromosome_position": "<integer>",
      "region": "<object>"
    }
  ],
  "alleles": "<string>",
  "most_severe_consequence": "<string>",
  "mapped_genes": [
    "<string>"
  ]
}

Full parameters and usage notes

5) Retrieve GWAS SNPs mapped to a gene

  • Purpose: Retrieve GWAS SNPs mapped to a gene.
  • Method: Use GWASSNPsForGene to query or submit the supplied input and parse the response.
  • API： dnakit.databases.gwas_get_snps_for_gene(*, size=None, page=None, gene_symbol=None, gene=None, mapped_gene=None, verbose=True)
  • Input: Choose filters as shown in the example; omitted options use the operation defaults.
  • Output: Returns a list of records; each record includes rs_id, merged, functional_class, last_update_date and related fields.
  • Example code:
import dnakit

result = dnakit.databases.gwas_get_snps_for_gene(
    mapped_gene='BRCA1',
    size=10,
    page=1,
    verbose=False,
)
print(result)
  • Example output: The response has the following shape; records depend on the input and source.

Response-shape excerpt; <…> denotes type placeholders, not a captured query result.

[
  {
    "rs_id": "<string>",
    "merged": "<integer>",
    "functional_class": "<string>",
    "last_update_date": "<string>",
    "locations": [
      "<object>"
    ],
    "alleles": "<string>",
    "most_severe_consequence": "<string>",
    "mapped_genes": [
      "<string>"
    ]
  }
]

Full parameters and usage notes

6) Retrieve GWAS studies for a trait

  • Purpose: Retrieve GWAS studies for a trait.
  • Method: Use GWASStudiesForTrait to query or submit the supplied input and parse the response.
  • API： dnakit.databases.gwas_get_studies_for_trait(*, disease_trait=None, efo_uri=None, efo_id=None, efo_trait=None, cohort=None, gxe=None, full_pvalue_set=None, size=None, page=None, verbose=True)
  • Input: Choose filters as shown in the example; omitted options use the operation defaults. Select exactly one argument group: disease_trait / efo_uri / efo_id / efo_trait.
  • Output: Returns a list of records; each record includes accession_id, disease_trait, efo_traits, initial_sample_size and related fields.
  • Example code:
import dnakit

result = dnakit.databases.gwas_get_studies_for_trait(
    disease_trait='hypertension',
    size=5,
    verbose=False,
)
print(result)
  • Example output: The response has the following shape; records depend on the input and source.

Response-shape excerpt; <…> denotes type placeholders, not a captured query result.

[
  {
    "accession_id": "<string>",
    "disease_trait": "<string>",
    "efo_traits": [
      "<object>"
    ],
    "initial_sample_size": "<string>",
    "replication_sample_size": "<string>",
    "discovery_ancestry": [
      "<string>"
    ],
    "replication_ancestry": [
      "<string>"
    ],
    "cohort": [
      "<string>"
    ]
  }
]

Full parameters and usage notes

7) Retrieve a GWAS study by accession

  • Purpose: Retrieve a GWAS study by accession.
  • Method: Use GWASStudyByID to query or submit the supplied input and parse the response.
  • API： dnakit.databases.gwas_get_study_by_id(*, study_id=None, accession_id=None, verbose=True)
  • Input: Choose filters as shown in the example; omitted options use the operation defaults.
  • Output: Returns a mapping with accession_id, disease_trait, efo_traits, initial_sample_size and related fields.
  • Example code:
import dnakit

result = dnakit.databases.gwas_get_study_by_id(
    study_id='GCST000392',
    verbose=False,
)
print(result)
  • Example output: The response has the following shape; records depend on the input and source.

Response-shape excerpt; <…> denotes type placeholders, not a captured query result.

{
  "accession_id": "<string>",
  "disease_trait": "<string>",
  "efo_traits": [
    {
      "efo_id": "<string>",
      "efo_trait": "<string>"
    }
  ],
  "initial_sample_size": "<string>",
  "replication_sample_size": "<string>",
  "discovery_ancestry": [
    "<string>"
  ],
  "replication_ancestry": [
    "<string>"
  ],
  "cohort": [
    "<string>"
  ]
}

Full parameters and usage notes

8) Find GWAS variants associated with a disease or trait

  • Purpose: Find GWAS variants associated with a disease or trait.
  • Method: Use GWASVariantsForTrait to query or submit the supplied input and parse the response.
  • API： dnakit.databases.gwas_get_variants_for_trait(*, disease_trait=None, trait=None, efo_uri=None, efo_id=None, efo_trait=None, size=None, limit=None, page=None, sort=None, direction=None, p_value_threshold=None, verbose=True)
  • Input: Choose filters as shown in the example; omitted options use the operation defaults. Select exactly one argument group: disease_trait / trait / efo_uri / efo_id / efo_trait.
  • Output: Returns a list of records; each record includes association_id, risk_frequency, pvalue_description, range and related fields.
  • Example code:
import dnakit

result = dnakit.databases.gwas_get_variants_for_trait(
    disease_trait='breast cancer',
    size=20,
    verbose=False,
)
print(result)
  • Example output: The response has the following shape; records depend on the input and source.

Response-shape excerpt; <…> denotes type placeholders, not a captured query result.

[
  {
    "association_id": "<integer>",
    "risk_frequency": "<string>",
    "pvalue_description": "<string>",
    "range": "<string>",
    "locations": [
      "<object>"
    ],
    "rs_id": "<string>",
    "merged": "<integer>",
    "functional_class": "<string>"
  }
]

Full parameters and usage notes

9) Search GWAS associations by keyword

  • Purpose: Search GWAS associations by keyword.
  • Method: Use GWASAssociationSearch to query or submit the supplied input and parse the response.
  • API： dnakit.databases.gwas_search_associations(*, disease_trait=None, query=None, efo_uri=None, efo_id=None, efo_trait=None, rs_id=None, accession_id=None, p_value=None, p_value_threshold=None, sort=None, direction=None, size=None, page=None, verbose=True)
  • Input: Choose filters as shown in the example; omitted options use the operation defaults.
  • Output: Returns a list of records; each record includes association_id, p_value, beta, efo_traits and related fields.
  • Example code:
import dnakit

result = dnakit.databases.gwas_search_associations(
    disease_trait='coronary artery disease',
    size=5,
    verbose=False,
)
print(result)
  • Example output: The response has the following shape; records depend on the input and source.

Response-shape excerpt; <…> denotes type placeholders, not a captured query result.

[
  {
    "association_id": "<integer>",
    "p_value": "<number>",
    "beta": "<string>",
    "efo_traits": [
      "<object>"
    ],
    "reported_trait": [
      "<string>"
    ],
    "accession_id": "<string>",
    "pubmed_id": "<string>",
    "first_author": "<string>"
  }
]

Full parameters and usage notes

10) Search gene GWAS associations and risk alleles

  • Purpose: Search gene GWAS associations and risk alleles.
  • Method: Use GWASGeneSearch to query or submit the supplied input and parse the response.
  • API： dnakit.databases.gwas_search_associations_by_gene(*, gene_name, size=None, verbose=True)
  • Input: Provide gene_name.
  • Output: Returns a mapping with gene_name, association_count, associations, total_found and related fields.
  • Example code:
import dnakit

result = dnakit.databases.gwas_search_associations_by_gene(
    gene_name='TP53',
    size=5,
    verbose=False,
)
print(result)
  • Example output: The response has the following shape; records depend on the input and source.

Response-shape excerpt; <…> denotes type placeholders, not a captured query result.

{
  "gene_name": "<string>",
  "association_count": "<integer>",
  "associations": [
    "<object>"
  ],
  "total_found": "<integer>",
  "queried_gene_name": "<string>",
  "gene_name_note": "<string>"
}

Full parameters and usage notes

11) Search GWAS SNPs by rsID or gene

  • Purpose: Search GWAS SNPs by rsID or gene.
  • Method: Use GWASSNPSearch to query or submit the supplied input and parse the response.
  • API： dnakit.databases.gwas_search_snps(*, rs_id=None, mapped_gene=None, size=None, page=None, verbose=True)
  • Input: Choose filters as shown in the example; omitted options use the operation defaults.
  • Output: Returns a list of records; each record includes rs_id, merged, functional_class, last_update_date and related fields.
  • Example code:
import dnakit

result = dnakit.databases.gwas_search_snps(
    mapped_gene='BRCA1',
    size=5,
    verbose=False,
)
print(result)
  • Example output: The response has the following shape; records depend on the input and source.

Response-shape excerpt; <…> denotes type placeholders, not a captured query result.

[
  {
    "rs_id": "<string>",
    "merged": "<integer>",
    "functional_class": "<string>",
    "last_update_date": "<string>",
    "locations": [
      "<object>"
    ],
    "alleles": "<string>",
    "most_severe_consequence": "<string>",
    "mapped_genes": [
      "<string>"
    ]
  }
]

Full parameters and usage notes

12) Search GWAS studies by trait and cohort

  • Purpose: Search GWAS studies by trait and cohort.
  • Method: Use GWASStudySearch to query or submit the supplied input and parse the response.
  • API： dnakit.databases.gwas_search_studies(*, disease_trait=None, efo_uri=None, efo_id=None, efo_trait=None, cohort=None, gxe=None, full_pvalue_set=None, size=None, page=None, verbose=True)
  • Input: Choose filters as shown in the example; omitted options use the operation defaults.
  • Output: Returns a list of records; each record includes accession_id, disease_trait, efo_traits, initial_sample_size and related fields.
  • Example code:
import dnakit

result = dnakit.databases.gwas_search_studies(
    disease_trait='diabetes',
    size=5,
    verbose=False,
)
print(result)
  • Example output: The response has the following shape; records depend on the input and source.

Response-shape excerpt; <…> denotes type placeholders, not a captured query result.

[
  {
    "accession_id": "<string>",
    "disease_trait": "<string>",
    "efo_traits": [
      "<object>"
    ],
    "initial_sample_size": "<string>",
    "replication_sample_size": "<string>",
    "discovery_ancestry": [
      "<string>"
    ],
    "replication_ancestry": [
      "<string>"
    ],
    "cohort": [
      "<string>"
    ]
  }
]

Full parameters and usage notes