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Visium

Human prostate gland

GSM8558007

bronze Interactive viewer H&E prostate cancer Provisional
Human prostate gland preview
print(sdata)
SpatialData object
├── Images
│     ├── 'GSM8558007_NEADT_11_hires_image': DataArray[cyx] (3, 2000, 1334)
│     └── 'GSM8558007_NEADT_11_lowres_image': DataArray[cyx] (3, 600, 400)
├── Shapes
│     └── 'GSM8558007_NEADT_11': GeoDataFrame shape: (4401, 2) (2D shapes)
└── Tables
      └── 'table': AnnData (4401, 33538)
with coordinate systems:
    ▸ 'GSM8558007_NEADT_11', with elements:
        GSM8558007_NEADT_11_hires_image (Images), GSM8558007_NEADT_11_lowres_image (Images), GSM8558007_NEADT_11 (Shapes)
    ▸ 'GSM8558007_NEADT_11_downscaled_hires', with elements:
        GSM8558007_NEADT_11_hires_image (Images), GSM8558007_NEADT_11 (Shapes)
    ▸ 'GSM8558007_NEADT_11_downscaled_lowres', with elements:
        GSM8558007_NEADT_11_lowres_image (Images), GSM8558007_NEADT_11 (Shapes)
Load in Python
import lamindb as ln

db = ln.DB("scverse/spatialdata-db")
artifact = db.Artifact.get("DzKUGMARKVO2ha4v")   # 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/DzKUGMARKVO2ha4v

# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid DzKUGMARKVO2ha4v
Load with the Python client
# pip install git+https://github.com/theislab/spatialdata-db-client
from sddb import Catalog

ds = Catalog().cohort(uids=["DzKUGMARKVO2ha4v0000"])[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
prostate gland
Condition
prostate cancer
Modality
RNA
Observations
4,401
Tier
bronze
Chemistry
Visium v1
Magnification
other
Resolution
1,334 × 2,000 px
mpp
5.541 µm/px
Size
54 MB
Sample ID
GSM8558007
License
unknown
Published
Oct 29, 2024

Cite this dataset

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

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