We are not able to exposing full summary statistics via the API, however, we do allow users to find all known GWAS or QTL signals where the queried variant is part of the credible sets. Essentially reproducing the GWAS and QTL tables you can find on the variant page.
The API query examples show how to pull credible sets. This example also pulls study level information (studyId, disease, traitName) + corresponding disease and disease categories (diseaseName and therapeuticAreas). If these annotations are not enough you can add more study annotation eg. publicationFirstAuthor, pubmedId, cohorts etc
query GWASCredibleSetsQuery($variantId: String!, $size: Int!, $index: Int!) {
variant(variantId: $variantId) {
id
referenceAllele
alternateAllele
gwasCredibleSets: credibleSets(studyTypes: [gwas], page: { size: $size, index: $index }) {
count
rows {
studyLocusId
pValueMantissa
pValueExponent
beta
finemappingMethod
confidence
variant {
id
chromosome
position
referenceAllele
alternateAllele
}
study {
traitFromSource
id
diseases {
name
id
therapeuticAreas {
name
id
}
}
}
locus(variantIds: [$variantId]) {
rows {
posteriorProbability
}
}
locusSize: locus {
count
}
l2GPredictions(page: { size: 1, index: 0 }) {
rows {
target {
id
approvedSymbol
}
score
}
}
}
}
}
}
Given the following query parameters:
{
"variantId": "1_154453788_C_T",
"size": 500,
"index": 0
}
This is one of the returned credible set:
{
"studyLocusId": "00c812e382a81bd696d654936e960be3",
"pValueMantissa": 1.0130000114440918,
"pValueExponent": -10,
"beta": -0.0751,
"finemappingMethod": "PICS",
"confidence": "PICS fine-mapped credible set extracted from summary statistics",
"variant": {
"id": "1_154452980_G_A",
"chromosome": "1",
"position": 154452980,
"referenceAllele": "G",
"alternateAllele": "A"
},
"study": {
"traitFromSource": "Rheumatoid arthritis",
"id": "GCST90013534",
"diseases": [
{
"name": "rheumatoid arthritis",
"id": "EFO_0000685",
"therapeuticAreas": [
{
"name": "immune system disease",
"id": "EFO_0000540"
},
{
"name": "musculoskeletal or connective tissue disease",
"id": "OTAR_0000006"
},
{
"name": "phenotype",
"id": "EFO_0000651"
}
]
}
]
},
"locus": {
"rows": [
{
"posteriorProbability": 0.054693652754671196
}
]
},
"locusSize": {
"count": 31
},
"l2GPredictions": {
"rows": [
{
"target": {
"id": "ENSG00000160712",
"approvedSymbol": "IL6R"
},
"score": 0.8838409781455994
}
]
}
}
Not exactly sure if anything else is missing for you?