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Visium

Human lung

GSM8699170

bronze Interactive viewer H&E obsolete idiopathic pulmonary fibrosis Provisional
Human lung preview
print(sdata)
SpatialData object
├── Images
│     ├── 'GSM8699170_JKPF3_1_hires_image': DataArray[cyx] (3, 2000, 1818)
│     └── 'GSM8699170_JKPF3_1_lowres_image': DataArray[cyx] (4, 600, 546)
├── Shapes
│     └── 'GSM8699170_JKPF3_1': GeoDataFrame shape: (2413, 2) (2D shapes)
└── Tables
      └── 'table': AnnData (2413, 33538)
with coordinate systems:
    ▸ 'GSM8699170_JKPF3_1', with elements:
        GSM8699170_JKPF3_1_hires_image (Images), GSM8699170_JKPF3_1_lowres_image (Images), GSM8699170_JKPF3_1 (Shapes)
    ▸ 'GSM8699170_JKPF3_1_downscaled_hires', with elements:
        GSM8699170_JKPF3_1_hires_image (Images), GSM8699170_JKPF3_1 (Shapes)
    ▸ 'GSM8699170_JKPF3_1_downscaled_lowres', with elements:
        GSM8699170_JKPF3_1_lowres_image (Images), GSM8699170_JKPF3_1 (Shapes)
Load in Python
import lamindb as ln

db = ln.DB("scverse/spatialdata-db")
artifact = db.Artifact.get("kRQFX70gKcnH6Wpf")   # 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/kRQFX70gKcnH6Wpf

# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid kRQFX70gKcnH6Wpf
Load with the Python client
# pip install git+https://github.com/theislab/spatialdata-db-client
from sddb import Catalog

ds = Catalog().cohort(uids=["kRQFX70gKcnH6Wpf0000"])[0]
ds.elements()                 # inspect without downloading
sdata = ds.load(lazy=False)   # copy to the local cache and open

Docs: finding & loading data →

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Metadata

Technology
Visium
Organism
human
Tissue
lung
Condition
obsolete idiopathic pulmonary fibrosis
Modality
RNA
Observations
2,413
Tier
bronze
Chemistry
Visium v1
Magnification
other
Resolution
1,818 × 2,000 px
mpp
4.050 µm/px
Size
26 MB
Sample ID
GSM8699170
License
unknown
Published
Aug 11, 2025

Cite this dataset

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

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