Visium
Human colon
GSM9322961
silver Interactive viewer H&E colorectal carcinoma No linked publication
print(sdata)
SpatialData object
├── Images
│ ├── 'GSM9322961_TR16_23542_hires_image': DataArray[cyx] (3, 1299, 2000)
│ └── 'GSM9322961_TR16_23542_lowres_image': DataArray[cyx] (3, 390, 600)
├── Shapes
│ └── 'GSM9322961_TR16_23542': GeoDataFrame shape: (4564, 2) (2D shapes)
└── Tables
└── 'table': AnnData (4564, 18085)
with coordinate systems:
▸ 'GSM9322961_TR16_23542', with elements:
GSM9322961_TR16_23542_hires_image (Images), GSM9322961_TR16_23542_lowres_image (Images), GSM9322961_TR16_23542 (Shapes)
▸ 'GSM9322961_TR16_23542_downscaled_hires', with elements:
GSM9322961_TR16_23542_hires_image (Images), GSM9322961_TR16_23542 (Shapes)
▸ 'GSM9322961_TR16_23542_downscaled_lowres', with elements:
GSM9322961_TR16_23542_lowres_image (Images), GSM9322961_TR16_23542 (Shapes) Load in Python
import lamindb as ln
db = ln.DB("scverse/spatialdata-db")
artifact = db.Artifact.get("l4gygKGF3CVWnkN6") # 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/l4gygKGF3CVWnkN6
# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid l4gygKGF3CVWnkN6 Load with the Python client
# pip install git+https://github.com/theislab/spatialdata-db-client
from sddb import Catalog
ds = Catalog().cohort(uids=["l4gygKGF3CVWnkN60000"])[0]
ds.elements() # inspect without downloading
sdata = ds.load(lazy=False) # copy to the local cache and openPart of collection
Collagen Alignment and Spatial Transcriptomics Analysis (CASTA) reveals gene programs associated with collagen alignmet in colorectal cancer→ 5 datasets · other
Metadata
- Technology
- Visium
- Organism
- human
- Tissue
- colon
- Condition
- colorectal carcinoma
- Modality
- RNA
- Observations
- 4,564
- Tier
- silver
- Chemistry
- Visium v1
- Resolution
- 2,000 × 1,299 px
- mpp
- 9.977 µm/px
- Size
- 20 MB
- Sample ID
- GSM9322961
- License
- unknown
- Published
- Nov 29, 2025
Cite this dataset
No linked publication found — please cite the data source: NCBI GEO ↗.
Source: NCBI GEO ↗ · Reprocessed to SpatialData by SpatialData-DB