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bedrock.bio

open_targets.association_by_datatype_indirect

import bedrock_bio as bb

rel = bb.load_table('open_targets.association_by_datatype_indirect')

df = rel.limit(5).pl()  # Polars
df = rel.limit(5).df()  # Pandas
df.head()
diseaseId targetId aggregationType aggregationValue associationScore evidenceCount timeseries currentNovelty version
0 EFO_0000180 ENSG00000159216 datatypeId literature 0.155116 2 [{'year': 2019, 'associationScore': 0.15207417... 0.001521 26.09
1 EFO_0000180 ENSG00000206047 datatypeId literature 0.067715 4 [{'year': 2015, 'associationScore': 0.06771525... 0.000000 26.09
2 EFO_0000195 ENSG00000006831 datatypeId literature 0.127914 27 [{'year': 2005, 'associationScore': 0.0, 'nove... 0.007279 26.09
3 EFO_0000195 ENSG00000077782 datatypeId literature 0.050447 9 [{'year': 2022, 'associationScore': 0.04433469... 0.005357 26.09
4 EFO_0000195 ENSG00000100473 datatypeId rna_expression 0.608297 1 [{'year': 2025, 'associationScore': 0.0, 'nove... 0.000000 26.09

Description

Section titled “Description”

Data type-specific metrics for indirect target-disease associations and its development over time implying association novelty.

Dataset contains association scores calculated for each data type indepedently for the aggregation of all evidence supporting any given target-disease.

This dataset contains indirect associations, therefore evidence is propagated across the disease or phenotype space using the Experimental Factor Ontology [Target-Disease]

Partitions

Section titled “Partitions”

Not partitioned.

Schema

Section titled “Schema”
Column Type Description
diseaseId TEXT Open Targets disease identifier
targetId TEXT Unique identifier for the target [bioregistry:ensembl]
aggregationType TEXT Evidence column used to aggregate data: datatypeId
aggregationValue TEXT Datasource identifier of the group: eg. genetics_literature
associationScore DOUBLE Current disease/target association score of evidence from the given datatype
evidenceCount BIGINT Total number of evidence supporting the disease/target association for a given datatype
timeseries STRUCT(year INT, associationScore DOUBLE, novelty DOUBLE, yearlyEvidenceCount BIGINT)[] Timeseries describing the evolution of association
currentNovelty DOUBLE Novelty of the disease/target association
version TEXT Open Targets Platform release version (major.minor), e.g. 26.09. Added during ingest.