from app.funcs.network_graph import NetworkEdgeSchema, NetworkNodeSchema
from app.utils.meta_graph import gwas_label_formatter
node_schemas = [
NetworkNodeSchema(
meta_node="Gwas",
id_col="trait.id",
label_formatter=gwas_label_formatter(node_name=None,
id_col="trait.id",
trait_col="trait.trait"),
),
NetworkNodeSchema(
meta_node="Gwas",
id_col="assoc_trait.id",
label_formatter=gwas_label_formatter(
node_name=None,
id_col="assoc_trait.id",
trait_col="assoc_trait.trait",
),
),
]
edge_schemas = [
NetworkEdgeSchema(
from_col="trait.id",
to_col="assoc_trait.id",
from_meta_node="Gwas",
arrows=False,
meta_rel="GENETIC_COR",
hover_title_formatter=lambda row: None,
)
from app.funcs.network_graph import NetworkEdgeSchema, NetworkNodeSchema
from app.utils.meta_graph import gwas_label_formatter, mr_eve_title_formatter
node_schemas = [
NetworkNodeSchema(
meta_node="GwasExposure",
id_col="trait.id",
label_formatter=gwas_label_formatter(node_name="trait"),
),
NetworkNodeSchema(
meta_node="Gwas",
id_col="assoc_trait.id",
label_formatter=gwas_label_formatter(node_name="assoc_trait"),
),
NetworkNodeSchema(meta_node="Variant", id_col="variant.name"),
NetworkNodeSchema(
meta_node="Gene", id_col="gene.name", match_node_by="name"
),
NetworkNodeSchema(meta_node="Drug", id_col="drug.label"),
]
edge_schemas = [
NetworkEdgeSchema(
from_col="assoc_trait.id",
to_col="trait.id",
from_meta_node="Gwas",
hover_title_formatter=mr_eve_title_formatter(
exposure_id="assoc_trait.id",
outcome_id="trait.id",
estimate="mr.b",
se="mr.se",
gene.name is not null
RETURN
gwas {.id, .trait},
gwas_to_variant {.se, .pval, .samplesize, .beta},
variant {.name},
gene {.name},
protein {.uniprot_id},
pathway {.reactome_id, .name}
ORDER BY gwas_to_variant.pval ;
""",
query_type=GalleryQueryType.cypher,
schema=GallerySchema(
nodes=[
NetworkNodeSchema(
meta_node="Gwas",
id_col="gwas.id",
label_formatter=gwas_label_formatter(),
),
NetworkNodeSchema(
meta_node="Variant",
id_col="variant.name",
label_col="variant.name",
),
NetworkNodeSchema(
meta_node="Gene",
id_col="gene.name",
label_col="gene.name",
match_node_by="name",
),
NetworkNodeSchema(
meta_node="Protein",
from app.funcs.network_graph import NetworkEdgeSchema, NetworkNodeSchema
from app.utils.meta_graph import gwas_label_formatter
node_schemas = [
NetworkNodeSchema(
id_col="gwas.id",
label_formatter=gwas_label_formatter(node_name="gwas"),
meta_node="Gwas",
),
NetworkNodeSchema(id_col="triple.id", meta_node="LiteratureTriple"),
NetworkNodeSchema(id_col="lit.id", meta_node="Literature"),
]
edge_schemas = [
NetworkEdgeSchema(from_col="gwas.id",
to_col="triple.id",
from_meta_node="Gwas"),
NetworkEdgeSchema(
from_col="gwas.id",
to_col="lit.id",
from_meta_node="Gwas",
arrows=False,
dashes=True,
),
NetworkEdgeSchema(
from_col="triple.id",
to_col="lit.id",
from_meta_node="LiteratureTriple",
),
]
RETURN
disease_gwas {.id, .trait},
risk_factor_gwas {.id, .trait},
variant {.name},
gene {.name},
drug {.label},
obs_cor {.cor},
mr {.b, .se, .pval, .selection, .method, .moescore}
ORDER BY mr.pval ;
""",
query_type=GalleryQueryType.cypher,
schema=GallerySchema(
nodes=[
NetworkNodeSchema(
meta_node="GwasPrimary",
id_col="disease_gwas.id",
label_formatter=gwas_label_formatter(node_name="disease_gwas"),
),
NetworkNodeSchema(
meta_node="Gwas",
id_col="risk_factor_gwas.id",
label_formatter=gwas_label_formatter(
node_name="risk_factor_gwas"
),
),
NetworkNodeSchema(meta_node="Variant", id_col="variant.name"),
NetworkNodeSchema(
meta_node="Gene", id_col="gene.name", match_node_by="name"
),
NetworkNodeSchema(meta_node="Drug", id_col="drug.label"),
],
from app.funcs.network_graph import NetworkEdgeSchema, NetworkNodeSchema
from app.utils.meta_graph import gwas_label_formatter
node_schemas = [
NetworkNodeSchema(
id_col="gwas.id",
label_formatter=gwas_label_formatter(node_name="gwas"),
meta_node="Gwas",
),
NetworkNodeSchema(id_col="efo.id", label_col="efo.value", meta_node="Efo"),
NetworkNodeSchema(id_col="disease.id",
label_col="disease.label",
meta_node="Disease"),
]
edge_schemas = [
NetworkEdgeSchema(
from_col="gwas.id",
to_col="efo.id",
from_meta_node="Gwas",
arrows=False,
),
NetworkEdgeSchema(
from_col="efo.id",
to_col="disease.id",
from_meta_node="Disease",
arrows=False,
),
]
RETURN
gwas, assoc_gwas, assoc_gwas2,
mr,
obs_cor1, obs_cor2,
prs1, prs2,
gwas_nlp1, gwas_nlp2
ORDER BY
mr.pval
LIMIT 100
""",
query_type=GalleryQueryType.cypher,
schema=GallerySchema(
nodes=[
NetworkNodeSchema(
meta_node="GwasPrimary",
id_col="gwas.id",
label_col="gwas.trait",
),
NetworkNodeSchema(
meta_node="GwasSecondary",
id_col="assoc_gwas.id",
label_col="assoc_gwas.trait",
),
NetworkNodeSchema(
meta_node="Gwas",
id_col="assoc_gwas2.id",
label_col="assoc_gwas2.trait",
),
],
edges=[
NetworkEdgeSchema(
OPTIONAL MATCH
(g1:Gwas)--(eChild)
OPTIONAL MATCH
(g2:Gwas)--(e)
RETURN
e {.id, .type, .value},
eChild {.id, .type, .value},
g1 {.id, .trait},
g2 {.id, .trait}
LIMIT 5000;
""",
query_type=GalleryQueryType.cypher,
schema=GallerySchema(
nodes=[
NetworkNodeSchema(
meta_node="Gwas", id_col="g1.id", label_col="g1.trait"
),
NetworkNodeSchema(
meta_node="Gwas", id_col="g2.id", label_col="g2.trait"
),
NetworkNodeSchema(
meta_node="EfoPrimary", id_col="e.id", label_col="e.value"
),
NetworkNodeSchema(
meta_node="Efo", id_col="eChild.id", label_col="eChild.value"
),
],
edges=[
NetworkEdgeSchema(
from_col="e.id", to_col="eChild.id", from_meta_node="Efo"
),
from app.funcs.network_graph import NetworkEdgeSchema, NetworkNodeSchema
from app.utils.meta_graph import gwas_label_formatter, mr_eve_title_formatter
node_schemas = [
NetworkNodeSchema(
meta_node="GwasExposure",
id_col="exposure.id",
label_formatter=gwas_label_formatter(node_name="exposure"),
),
NetworkNodeSchema(
meta_node="GwasOutcome",
id_col="outcome.id",
label_formatter=gwas_label_formatter(node_name="outcome"),
),
NetworkNodeSchema(
meta_node="Gwas",
id_col="cf.id",
label_formatter=gwas_label_formatter(node_name="cf"),
),
]
edge_confounder_exposure = {
"confounder":
NetworkEdgeSchema(
from_col="cf.id",
to_col="exposure.id",
from_meta_node="Gwas",
dashes=True,
hover_title_formatter=mr_eve_title_formatter(
exposure_id="cf.id",
outcome_id="exposure.id",
AND exposure.id <> outcome.id AND cf.trait <> exposure.trait
AND cf.trait <> outcome.trait AND exposure.trait <> outcome.trait
RETURN
exposure {.id, .trait},
outcome {.id, .trait},
cf {.id, .trait},
r1 {.b, .se, .pval, .selection, .method, .moescore},
r2 {.b, .se, .pval, .selection, .method, .moescore},
r3 {.b, .se, .pval, .selection, .method, .moescore}
ORDER BY r1.pval;
""",
query_type=GalleryQueryType.cypher,
schema=GallerySchema(
nodes=[
NetworkNodeSchema(meta_node="Gwas",
id_col="cf.id",
label_col="cf.trait"),
NetworkNodeSchema(
meta_node="GwasExposure",
id_col="exposure.id",
label_col="exposure.trait",
),
NetworkNodeSchema(
meta_node="GwasOutcome",
id_col="outcome.id",
label_col="outcome.trait",
),
],
edges=[
NetworkEdgeSchema(from_col="cf.id",
to_col="exposure.id",
from app.funcs.network_graph import NetworkEdgeSchema, NetworkNodeSchema
from app.utils.meta_graph import gwas_label_formatter, mr_eve_title_formatter
# NOTE: it is impossible to specify a study to be exposure or outcome
# in the current api spec, as a study can be both exposure or outcome
# each time.
node_schemas = [
NetworkNodeSchema(
meta_node="Gwas",
id_col="exposure.id",
label_formatter=gwas_label_formatter(
node_name=None, id_col="exposure.id", trait_col="exposure.trait"
),
),
NetworkNodeSchema(
meta_node="Gwas",
id_col="outcome.id",
label_formatter=gwas_label_formatter(
node_name=None, id_col="outcome.id", trait_col="outcome.trait"
),
),
]
edge_schemas = [
NetworkEdgeSchema(
from_col="exposure.id",
to_col="outcome.id",
from_meta_node="Gwas",
hover_title_formatter=mr_eve_title_formatter(
exposure_id="exposure.id", outcome_id="outcome.id"
),
multi_snp_mr_title_formatter = lambda row: """
<b>exposure_ensembl_id</b>: {exposure_ensembl_id},
<b>outcome_id</b>: {outcome_id}</br>
<b>b</b>: {b:.2E}, <b>se</b>: {se:.2E}, <b>p</b>: {p:.2E}
""".format(
exposure_ensembl_id=row["gene.ensembl_id"],
outcome_id=row["gwas.id"],
b=row["r.beta"],
se=row["r.se"],
p=row["r.p"],
)
node_schemas_single_snp = [
NetworkNodeSchema(meta_node="Gene",
id_col="gene.ensembl_id",
label_col="gene.name"),
NetworkNodeSchema(
meta_node="Gwas",
id_col="gwas.id",
label_formatter=lambda row: "{id}: {name}".format(
id=row["gwas.id"], name=row["gwas.trait"]),
),
NetworkNodeSchema(meta_node="Variant", id_col="r.rsid"),
]
node_schemas_multi_snp = [
NetworkNodeSchema(meta_node="Gene",
id_col="gene.ensembl_id",
label_col="gene.name"),
NetworkNodeSchema(