← All datasets
Visium HD

Human intestine

GSM9219229

silver Interactive viewer H&E graft versus host disease ✓ Verified publication
Human intestine preview
print(sdata)
SpatialData object
├── Images
│     ├── 'GSM9219229_SLV18_binned_outputs_square_002um_filtered_feature_bc_matrix_hires_image': DataArray[cyx] (3, 5420, 6000)
│     └── 'GSM9219229_SLV18_binned_outputs_square_002um_filtered_feature_bc_matrix_lowres_image': DataArray[cyx] (3, 542, 600)
├── Shapes
│     ├── 'GSM9219229_SLV18_binned_outputs_square_002um_filtered_feature_bc_matrix_square_002um': GeoDataFrame shape: (4246765, 1) (2D shapes)
│     ├── 'GSM9219229_SLV18_binned_outputs_square_002um_filtered_feature_bc_matrix_square_008um': GeoDataFrame shape: (272298, 1) (2D shapes)
│     ├── 'GSM9219229_SLV18_binned_outputs_square_002um_filtered_feature_bc_matrix_square_016um': GeoDataFrame shape: (70199, 1) (2D shapes)
│     └── 'GSM9219229_SLV18_binned_outputs_square_002um_filtered_feature_bc_matrix_square_016um_for_vitessce': GeoDataFrame shape: (70199, 2) (2D shapes)
└── Tables
      ├── 'square_002um': AnnData (4246765, 18085)
      ├── 'square_008um': AnnData (272298, 18085)
      └── 'square_016um': AnnData (70199, 18085)
with coordinate systems:
    ▸ 'GSM9219229_SLV18_binned_outputs_square_002um_filtered_feature_bc_matrix', with elements:
        GSM9219229_SLV18_binned_outputs_square_002um_filtered_feature_bc_matrix_hires_image (Images), GSM9219229_SLV18_binned_outputs_square_002um_filtered_feature_bc_matrix_lowres_image (Images), GSM9219229_SLV18_binned_outputs_square_002um_filtered_feature_bc_matrix_square_002um (Shapes), GSM9219229_SLV18_binned_outputs_square_002um_filtered_feature_bc_matrix_square_008um (Shapes), GSM9219229_SLV18_binned_outputs_square_002um_filtered_feature_bc_matrix_square_016um (Shapes), GSM9219229_SLV18_binned_outputs_square_002um_filtered_feature_bc_matrix_square_016um_for_vitessce (Shapes)
    ▸ 'GSM9219229_SLV18_binned_outputs_square_002um_filtered_feature_bc_matrix_downscaled_hires', with elements:
        GSM9219229_SLV18_binned_outputs_square_002um_filtered_feature_bc_matrix_hires_image (Images), GSM9219229_SLV18_binned_outputs_square_002um_filtered_feature_bc_matrix_square_002um (Shapes), GSM9219229_SLV18_binned_outputs_square_002um_filtered_feature_bc_matrix_square_008um (Shapes), GSM9219229_SLV18_binned_outputs_square_002um_filtered_feature_bc_matrix_square_016um (Shapes), GSM9219229_SLV18_binned_outputs_square_002um_filtered_feature_bc_matrix_square_016um_for_vitessce (Shapes)
    ▸ 'GSM9219229_SLV18_binned_outputs_square_002um_filtered_feature_bc_matrix_downscaled_lowres', with elements:
        GSM9219229_SLV18_binned_outputs_square_002um_filtered_feature_bc_matrix_lowres_image (Images), GSM9219229_SLV18_binned_outputs_square_002um_filtered_feature_bc_matrix_square_002um (Shapes), GSM9219229_SLV18_binned_outputs_square_002um_filtered_feature_bc_matrix_square_008um (Shapes), GSM9219229_SLV18_binned_outputs_square_002um_filtered_feature_bc_matrix_square_016um (Shapes), GSM9219229_SLV18_binned_outputs_square_002um_filtered_feature_bc_matrix_square_016um_for_vitessce (Shapes)
Load in Python
import lamindb as ln

db = ln.DB("scverse/spatialdata-db")
artifact = db.Artifact.get("aLHPhCIyCr1GXyJ8")   # latest version

sdata = artifact.load()   # cache, then load into memory
group = artifact.open()   # stream without downloading
path  = artifact.cache()  # sync into the local cache, returns the path
Load from the CLI
# one-shot: cache the dataset and print its local path
lamin load https://lamin.ai/scverse/spatialdata-db/artifact/aLHPhCIyCr1GXyJ8

# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid aLHPhCIyCr1GXyJ8
Load with the Python client
# pip install git+https://github.com/theislab/spatialdata-db-client
from sddb import Catalog

ds = Catalog().cohort(uids=["aLHPhCIyCr1GXyJ80000"])[0]
ds.elements()                 # inspect without downloading
sdata = ds.load(lazy=False)   # copy to the local cache and open

Docs: finding & loading data →

View on Lamin ↗ Open in Vitessce ↗ Flag a data issue

Metadata

Technology
Visium HD
Organism
human
Tissue
intestine
Condition
graft versus host disease
Modality
RNA
Observations
272,298
Tier
silver
Resolution
6,000 × 5,420 px
mpp
1.591 µm/px
Size
450 MB
Sample ID
GSM9219229
License
unknown
Published
Jun 24, 2026

Cite this dataset

No linked publication found — please cite the data source: NCBI GEO ↗.

Source: NCBI GEO ↗ · Reprocessed to SpatialData by SpatialData-DB