Visium
Mouse skin of body
GSM6319696
silver Interactive viewer H&E melanoma No linked publication
print(sdata)
SpatialData object
├── Images
│ ├── 'GSM6319696_Visium_2_full_image': DataTree[cyx] (3, 9727, 9792), (3, 4863, 4896), (3, 2431, 2448), (3, 1215, 1224), (3, 607, 612)
│ └── 'GSM6319696_Visium_2_hires_image': DataArray[cyx] (3, 1987, 2000)
├── Shapes
│ └── 'GSM6319696_Visium_2': GeoDataFrame shape: (4992, 2) (2D shapes)
└── Tables
└── 'table': AnnData (4992, 31053)
with coordinate systems:
▸ 'GSM6319696_Visium_2', with elements:
GSM6319696_Visium_2_full_image (Images), GSM6319696_Visium_2_hires_image (Images), GSM6319696_Visium_2 (Shapes)
▸ 'GSM6319696_Visium_2_downscaled_hires', with elements:
GSM6319696_Visium_2_hires_image (Images), GSM6319696_Visium_2 (Shapes)
▸ 'GSM6319696_Visium_2_downscaled_lowres', with elements:
GSM6319696_Visium_2 (Shapes) Load in Python
import lamindb as ln
db = ln.DB("scverse/spatialdata-db")
artifact = db.Artifact.get("2C5l0CSuEsrANhCX") # 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/2C5l0CSuEsrANhCX
# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid 2C5l0CSuEsrANhCX Load with the Python client
# pip install git+https://github.com/theislab/spatialdata-db-client
from sddb import Catalog
ds = Catalog().cohort(uids=["2C5l0CSuEsrANhCX0000"])[0]
ds.elements() # inspect without downloading
sdata = ds.load(lazy=False) # copy to the local cache and openPart of collection
A cellular hierarchy in melanoma uncouples growth and metastasis→ 2 datasets · other
Metadata
- Technology
- Visium
- Organism
- mouse
- Tissue
- skin of body
- Condition
- melanoma
- Modality
- RNA
- Observations
- 4,992
- Tier
- silver
- Chemistry
- Visium v1
- Resolution
- 9,792 × 9,727 px
- mpp
- 0.806 µm/px
- Size
- 233 MB
- Sample ID
- GSM6319696
- License
- unknown
- Published
- Jul 9, 2022
Cite this dataset
No linked publication found — please cite the data source: NCBI GEO ↗.
Source: NCBI GEO ↗ · Reprocessed to SpatialData by SpatialData-DB