open_targets.l2g_prediction

Python

In [1]:

import bedrock_bio as bb

rel = bb.load_table('open_targets.l2g_prediction')

df = rel.limit(5).pl()  # Polars
df = rel.limit(5).df()  # Pandas
df.head()

Out[1]:

	studyLocusId	geneId	score	features	shapBaseValue	version
0	0355bf3ca72c63994531d4b9f9dc97c5	ENSG00000008130	0.435808	[{'name': 'eQtlColocClppMaximum', 'value': 0.0...	0.037827	26.09
1	14e83c3693c2eb404247135604a084e8	ENSG00000188157	0.781170	[{'name': 'eQtlColocClppMaximum', 'value': 0.1...	0.037827	26.09
2	159b90d5db5640cb5e0cc5d7f2f64329	ENSG00000162576	0.347903	[{'name': 'eQtlColocClppMaximum', 'value': 0.0...	0.037827	26.09
3	1976e56b722b073b81eddd83ed23b0ed	ENSG00000130764	0.469119	[{'name': 'eQtlColocClppMaximum', 'value': 0.0...	0.037827	26.09
4	1baa945b441d5323dd417386bbaf538f	ENSG00000157933	0.732882	[{'name': 'eQtlColocClppMaximum', 'value': 0.0...	0.037827	26.09

R

In [1]:

library(bedrockbio)

lf <- load_table("open_targets.l2g_prediction")
df <- head(lf, 5) |> collect()

head(df)

Out[1]:

Sample output (5 rows, showing 5 of 6 columns)
   studyLocusId             | geneId          | score               | shapBaseValue       | version
   ------------------------ | --------------- | ------------------- | ------------------- | -------
0  0355bf3ca72c63994531d4b… | ENSG00000008130 | 0.4358077943325043  | 0.03782660514116287 | 26.09
1  14e83c3693c2eb404247135… | ENSG00000188157 | 0.7811703085899353  | 0.03782660514116287 | 26.09
2  159b90d5db5640cb5e0cc5d… | ENSG00000162576 | 0.3479028642177582  | 0.03782660514116287 | 26.09
3  1976e56b722b073b81eddd8… | ENSG00000130764 | 0.46911901235580444 | 0.03782660514116287 | 26.09
4  1baa945b441d5323dd41738… | ENSG00000157933 | 0.7328820824623108  | 0.03782660514116287 | 26.09

Description

Predictions from our Locus-to-Gene (L2G) gene assignment model.

The dataset contains all predictions for every combination of credible set and genes in the region as well as statistics to explain the model interpretation of the predictions [Genetics]

Partitions

Not partitioned.

Schema

Column	Type	Description
studyLocusId	TEXT	Study-locus identifier for the credible set
geneId	TEXT	Identifier of the gene/target
score	DOUBLE	Locus-to-Gene (L2G) score prediction for the given studyLocusId-geneId pair
features	STRUCT(name TEXT, value FLOAT, shapValue FLOAT)[]	List of Locus-to-Gene (L2G) feature values
shapBaseValue	FLOAT	SHAP base value
version	TEXT	Open Targets Platform release version (major.minor), e.g. 26.09. Added during ingest.