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Visium

Mouse colon

GSM8429991

bronze Interactive viewer H&E colorectal carcinoma Provisional
Mouse colon preview
print(sdata)
SpatialData object
├── Images
│     ├── 'GSM8429991_SC2200581_hires_image': DataArray[cyx] (3, 2000, 1969)
│     └── 'GSM8429991_SC2200581_lowres_image': DataArray[cyx] (3, 600, 591)
├── Shapes
│     └── 'GSM8429991_SC2200581': GeoDataFrame shape: (2787, 2) (2D shapes)
└── Tables
      └── 'table': AnnData (2787, 32285)
with coordinate systems:
    ▸ 'GSM8429991_SC2200581', with elements:
        GSM8429991_SC2200581_hires_image (Images), GSM8429991_SC2200581_lowres_image (Images), GSM8429991_SC2200581 (Shapes)
    ▸ 'GSM8429991_SC2200581_downscaled_hires', with elements:
        GSM8429991_SC2200581_hires_image (Images), GSM8429991_SC2200581 (Shapes)
    ▸ 'GSM8429991_SC2200581_downscaled_lowres', with elements:
        GSM8429991_SC2200581_lowres_image (Images), GSM8429991_SC2200581 (Shapes)
Load in Python
import lamindb as ln

db = ln.DB("scverse/spatialdata-db")
artifact = db.Artifact.get("MQ0uTWpmzXNyTWje")   # 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/MQ0uTWpmzXNyTWje

# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid MQ0uTWpmzXNyTWje
Load with the Python client
# pip install git+https://github.com/theislab/spatialdata-db-client
from sddb import Catalog

ds = Catalog().cohort(uids=["MQ0uTWpmzXNyTWje0000"])[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
mouse
Tissue
colon
Condition
colorectal carcinoma
Modality
RNA
Observations
2,787
Tier
bronze
Chemistry
Visium v1
Magnification
other
Resolution
1,969 × 2,000 px
mpp
3.461 µm/px
Size
62 MB
Sample ID
GSM8429991
License
unknown
Published
May 4, 2025

Cite this dataset

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

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