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Visium

Human prostate gland

GSM8557992

bronze Interactive viewer H&E prostate cancer Provisional
Human prostate gland preview
print(sdata)
SpatialData object
├── Images
│     ├── 'GSM8557992_TRNA_13_hires_image': DataArray[cyx] (3, 1909, 2000)
│     └── 'GSM8557992_TRNA_13_lowres_image': DataArray[cyx] (3, 573, 600)
├── Shapes
│     └── 'GSM8557992_TRNA_13': GeoDataFrame shape: (1839, 2) (2D shapes)
└── Tables
      └── 'table': AnnData (1839, 33538)
with coordinate systems:
    ▸ 'GSM8557992_TRNA_13', with elements:
        GSM8557992_TRNA_13_hires_image (Images), GSM8557992_TRNA_13_lowres_image (Images), GSM8557992_TRNA_13 (Shapes)
    ▸ 'GSM8557992_TRNA_13_downscaled_hires', with elements:
        GSM8557992_TRNA_13_hires_image (Images), GSM8557992_TRNA_13 (Shapes)
    ▸ 'GSM8557992_TRNA_13_downscaled_lowres', with elements:
        GSM8557992_TRNA_13_lowres_image (Images), GSM8557992_TRNA_13 (Shapes)
Load in Python
import lamindb as ln

db = ln.DB("scverse/spatialdata-db")
artifact = db.Artifact.get("FNJ5tMHfukzbVfQA")   # 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/FNJ5tMHfukzbVfQA

# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid FNJ5tMHfukzbVfQA
Load with the Python client
# pip install git+https://github.com/theislab/spatialdata-db-client
from sddb import Catalog

ds = Catalog().cohort(uids=["FNJ5tMHfukzbVfQA0000"])[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
1,839
Tier
bronze
Chemistry
Visium v1
Magnification
other
Resolution
2,000 × 1,909 px
mpp
3.685 µm/px
Size
32 MB
Sample ID
GSM8557992
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