Query artifacts¶
Here, we’ll query artifacts and inspect their metadata.
This guide can be skipped if you are only interested in how to leverage the overall collection.
import lamindb as ln
import bionty as bt
ln.track("agayZTonayqA")
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→ connected lamindb: testuser1/test-scrna
→ created Transform('agayZTonayqA0000', key='scrna3.ipynb'), started new Run('X4SzPBQCx7is9Kun') at 2025-11-26 11:07:08 UTC
→ notebook imports: bionty==1.9.1 lamindb==1.16.1
Query artifacts by provenance metadata¶
Query the transform, e.g., by key:
transform = ln.Transform.get(key="scrna.ipynb")
transform
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Transform(uid='uis9JE6QvjtV0000', version=None, is_latest=True, key='scrna.ipynb', description='scRNA-seq', type='notebook', hash='d6nbXlW_Fw7QJiczNGpj-g', reference=None, reference_type=None, branch_id=1, space_id=1, created_by_id=1, created_at=2025-11-26 11:06:21 UTC, is_locked=False)
Query the artifact:
ln.Artifact.filter(transform=transform).to_dataframe()
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| uid | key | description | suffix | kind | otype | size | hash | n_files | n_observations | version | is_latest | is_locked | created_at | branch_id | space_id | storage_id | run_id | schema_id | created_by_id | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| id | ||||||||||||||||||||
| 1 | RN05RcFzLZWRsad20000 | datasets/conde22.h5ad | None | .h5ad | dataset | AnnData | 57612943 | t_YJQpYrAyAGhs7Ir68zKj | None | 1648 | None | True | False | 2025-11-26 11:06:47.005000+00:00 | 1 | 1 | 1 | 1 | 3 | 1 |
Query artifacts by biological metadata¶
tissues = bt.Tissue.lookup()
query = ln.Artifact.filter(
tissues=tissues.blood,
)
query.to_dataframe()
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| uid | key | description | suffix | kind | otype | size | hash | n_files | n_observations | version | is_latest | is_locked | created_at | branch_id | space_id | storage_id | run_id | schema_id | created_by_id | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| id | ||||||||||||||||||||
| 1 | RN05RcFzLZWRsad20000 | datasets/conde22.h5ad | None | .h5ad | dataset | AnnData | 57612943 | t_YJQpYrAyAGhs7Ir68zKj | None | 1648 | None | True | False | 2025-11-26 11:06:47.005000+00:00 | 1 | 1 | 1 | 1 | 3 | 1 |
Inspect artifact metadata¶
Query all artifacts that measured the “cell_type” feature:
query_set = ln.Artifact.filter(feature_sets__features__name="cell_type").all()
artifact1, artifact2 = query_set[0], query_set[1]
artifact1.describe()
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Artifact: datasets/conde22.h5ad (0000) ├── uid: RN05RcFzLZWRsad20000 run: NrVbfmV (scrna.ipynb) │ kind: dataset otype: AnnData │ hash: t_YJQpYrAyAGhs7Ir68zKj size: 54.9 MB │ branch: main space: all │ created_at: 2025-11-26 11:06:47 UTC created_by: testuser1 │ n_observations: 1648 ├── storage/path: │ /home/runner/work/lamin-usecases/lamin-usecases/docs/test-scrna/.lamindb/RN05RcFzLZWRsad20000.h5ad ├── Dataset features │ ├── obs (4) │ │ assay bionty.ExperimentalFactor 10x 3' v3, 10x 5' v1, 10x 5' v2 │ │ cell_type bionty.CellType CD16-negative, CD56-bright natural kill… │ │ tissue bionty.Tissue blood, bone marrow, caecum, duodenum, i… │ │ donor str │ └── var.T (36283 bionty.Gene.ense… └── Labels └── .tissues bionty.Tissue blood, thoracic lymph node, spleen, lun… .cell_types bionty.CellType classical monocyte, T follicular helper… .experimental_factors bionty.ExperimentalFactor 10x 3' v3, 10x 5' v2, 10x 5' v1
artifact1.view_lineage()
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artifact2.describe()
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Artifact: scrna/dataset2.h5ad (0001) | description: 10x reference adata, trusted cell type annotation ├── uid: YPzTiZZiULn5ufBM0001 run: hzx93VM (scrna2.ipynb) │ kind: dataset otype: AnnData │ hash: 57xpUqmnZeBP6et6xOCcPA size: 835.8 KB │ branch: main space: all │ created_at: 2025-11-26 11:07:03 UTC created_by: testuser1 │ n_observations: 70 ├── storage/path: │ /home/runner/work/lamin-usecases/lamin-usecases/docs/test-scrna/.lamindb/YPzTiZZiULn5ufBM0001.h5ad ├── Dataset features │ ├── obs (1) │ │ cell_type bionty.CellType B cell, CD19-positive, CD14-positive mo… │ └── var.T (754 bionty.Gene.ensemb… │ HES4 num │ TNFRSF4 num │ SSU72 num │ PARK7 num │ RBP7 num │ SRM num │ MAD2L2 num │ AGTRAP num │ TNFRSF1B num │ EFHD2 num │ NECAP2 num │ HP1BP3 num │ C1QA num │ C1QB num │ HNRNPR num │ GALE num │ STMN1 num │ CD52 num │ FGR num │ ATP5IF1 num └── Labels └── .cell_types bionty.CellType CD8-positive, alpha-beta memory T cell,…
artifact2.view_lineage()
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