Spatial#
Warning
This is, for now, just a stub.
Setup#
!lamin init --storage ./test-spatial --schema bionty
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✅ saved: User(uid='DzTjkKse', handle='testuser1', name='Test User1', updated_at=2023-12-05 17:31:34 UTC)
✅ saved: Storage(uid='IwXYNFf4', root='/home/runner/work/lamin-usecases/lamin-usecases/docs/test-spatial', type='local', updated_at=2023-12-05 17:31:34 UTC, created_by_id=1)
💡 loaded instance: testuser1/test-spatial
💡 did not register local instance on hub
import lamindb as ln
import lnschema_bionty as lb
import matplotlib.pyplot as plt
import scanpy as sc
lb.settings.organism = "human"
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💡 lamindb instance: testuser1/test-spatial
ln.track()
💡 notebook imports: lamindb==0.63.2 lnschema_bionty==0.35.3 matplotlib==3.8.2 scanpy==1.9.6
💡 saved: Transform(uid='daeFs3PkquDW-R', name='Spatial', short_name='spatial', version='draft', type=notebook, updated_at=2023-12-05 17:31:38 UTC, created_by_id=1)
💡 saved: Run(uid='v5v6x89ewueA4kp0fISz', run_at=2023-12-05 17:31:38 UTC, transform_id=1, created_by_id=1)
Access 
#
Here, we have a spatial gene expression dataset measured using Visium from Suo22.
This dataset contains two parts:
a high-res image of a slice of fetal liver
a single cell expression dataset in .h5ad
img_path = ln.dev.datasets.file_tiff_suo22()
img = plt.imread(img_path)
plt.imshow(img)
plt.show()
adata = ln.dev.datasets.anndata_suo22_Visium10X()
# subset to the same image
adata = adata[adata.obs["img_id"] == "F121_LP1_4LIV"].copy()
adata
AnnData object with n_obs × n_vars = 3027 × 191
obs: 'in_tissue', 'array_row', 'array_col', 'sample', 'n_genes_by_counts', 'log1p_n_genes_by_counts', 'total_counts', 'log1p_total_counts', 'pct_counts_in_top_50_genes', 'pct_counts_in_top_100_genes', 'pct_counts_in_top_200_genes', 'pct_counts_in_top_500_genes', 'mt_frac', 'img_id', 'EXP_id', 'Organ', 'Fetal_id', 'SN', 'Visium_Area_id', 'Age_PCW', 'Digestion time', 'paths', 'sample_id', '_scvi_batch', '_scvi_labels', '_indices', 'total_cell_abundance'
var: 'feature_types', 'genome', 'SYMBOL', 'mt'
obsm: 'NMF', 'means_cell_abundance_w_sf', 'q05_cell_abundance_w_sf', 'q95_cell_abundance_w_sf', 'spatial', 'stds_cell_abundance_w_sf'
# plot where CD45+ leukocytes are in the slice
sc.pl.scatter(adata, "array_row", "array_col", color="ENSG00000081237")
Register 
#
We’ll register the single-cell data and the image as a Dataset.
file_ad = ln.File.from_anndata(
adata,
description="Suo22 Visium10X image F121_LP1_4LIV",
field=lb.Gene.ensembl_gene_id,
)
file_ad.save()
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❗ 191 terms (100.00%) are not validated for ensembl_gene_id: ENSG00000002586, ENSG00000004468, ENSG00000004897, ENSG00000007312, ENSG00000008086, ENSG00000008128, ENSG00000010278, ENSG00000010610, ENSG00000012124, ENSG00000013725, ENSG00000019582, ENSG00000026508, ENSG00000039068, ENSG00000059758, ENSG00000062038, ENSG00000065883, ENSG00000066294, ENSG00000070831, ENSG00000071991, ENSG00000073754, ...
❗ no validated features, skip creating feature set
❗ 27 terms (100.00%) are not validated for name: in_tissue, array_row, array_col, sample, n_genes_by_counts, log1p_n_genes_by_counts, total_counts, log1p_total_counts, pct_counts_in_top_50_genes, pct_counts_in_top_100_genes, pct_counts_in_top_200_genes, pct_counts_in_top_500_genes, mt_frac, img_id, EXP_id, Organ, Fetal_id, SN, Visium_Area_id, Age_PCW, ...
❗ no validated features, skip creating feature set
file_img = ln.File(img_path, description="Suo22 image F121_LP1_4LIV")
file_img.save()
dataset = ln.Dataset([file_ad, file_img], name="Suo22")
dataset.save()
# clean up test instance
!lamin delete --force test-spatial
!rm -r test-flow
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💡 deleting instance testuser1/test-spatial
✅ deleted instance settings file: /home/runner/.lamin/instance--testuser1--test-spatial.env
✅ instance cache deleted
✅ deleted '.lndb' sqlite file
❗ consider manually deleting your stored data: /home/runner/work/lamin-usecases/lamin-usecases/docs/test-spatial
rm: cannot remove 'test-flow': No such file or directory