Visium
Mouse lung
GSM8478586
silver H&E osteosarcoma No linked publication
print(sdata)
SpatialData object
├── Images
│ ├── 'GSM8478586_SP0001_SP0001_filtered_feature_bc_matrix_full_image': DataTree[cyx] (3, 3000, 3000), (3, 1500, 1500), (3, 750, 750), (3, 375, 375), (3, 187, 187)
│ ├── 'GSM8478586_SP0001_SP0001_filtered_feature_bc_matrix_hires_image': DataArray[cyx] (3, 1907, 2000)
│ └── 'GSM8478586_SP0001_SP0001_filtered_feature_bc_matrix_lowres_image': DataArray[cyx] (3, 572, 600)
├── Shapes
│ └── 'GSM8478586_SP0001_SP0001_filtered_feature_bc_matrix': GeoDataFrame shape: (1652, 2) (2D shapes)
└── Tables
└── 'table': AnnData (1652, 19465)
with coordinate systems:
▸ 'GSM8478586_SP0001_SP0001_filtered_feature_bc_matrix', with elements:
GSM8478586_SP0001_SP0001_filtered_feature_bc_matrix_full_image (Images), GSM8478586_SP0001_SP0001_filtered_feature_bc_matrix_hires_image (Images), GSM8478586_SP0001_SP0001_filtered_feature_bc_matrix_lowres_image (Images), GSM8478586_SP0001_SP0001_filtered_feature_bc_matrix (Shapes)
▸ 'GSM8478586_SP0001_SP0001_filtered_feature_bc_matrix_downscaled_hires', with elements:
GSM8478586_SP0001_SP0001_filtered_feature_bc_matrix_hires_image (Images), GSM8478586_SP0001_SP0001_filtered_feature_bc_matrix (Shapes)
▸ 'GSM8478586_SP0001_SP0001_filtered_feature_bc_matrix_downscaled_lowres', with elements:
GSM8478586_SP0001_SP0001_filtered_feature_bc_matrix_lowres_image (Images), GSM8478586_SP0001_SP0001_filtered_feature_bc_matrix (Shapes) Load in Python
import lamindb as ln
db = ln.DB("scverse/spatialdata-db")
artifact = db.Artifact.get("xZlv4fpqMQu3VT7m") # 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/xZlv4fpqMQu3VT7m
# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid xZlv4fpqMQu3VT7m Load with the Python client
# pip install git+https://github.com/theislab/spatialdata-db-client
from sddb import Catalog
ds = Catalog().cohort(uids=["xZlv4fpqMQu3VT7m0000"])[0]
ds.elements() # inspect without downloading
sdata = ds.load(lazy=False) # copy to the local cache and openMetadata
- Technology
- Visium
- Organism
- mouse
- Tissue
- lung
- Condition
- osteosarcoma
- Modality
- RNA
- Observations
- 1,652
- Tier
- silver
- Chemistry
- Visium v1
- Resolution
- 2,000 × 1,907 px
- mpp
- 2.769 µm/px
- Size
- 56 MB
- Sample ID
- GSM8478586
- License
- unknown
- Published
- May 9, 2024
Cite this dataset
No linked publication found — please cite the data source: NCBI GEO ↗.
Source: NCBI GEO ↗ · Reprocessed to SpatialData by SpatialData-DB