Visium
Mouse lung
GSM6108349
bronze Interactive viewer H&E influenza Provisional
print(sdata)
SpatialData object
├── Images
│ ├── 'GSM6108349_Day3_Aged_hires_image': DataArray[cyx] (3, 1840, 2000)
│ └── 'GSM6108349_Day3_Aged_lowres_image': DataArray[cyx] (3, 552, 600)
├── Shapes
│ └── 'GSM6108349_Day3_Aged': GeoDataFrame shape: (2520, 2) (2D shapes)
└── Tables
└── 'table': AnnData (2520, 32285)
with coordinate systems:
▸ 'GSM6108349_Day3_Aged', with elements:
GSM6108349_Day3_Aged_hires_image (Images), GSM6108349_Day3_Aged_lowres_image (Images), GSM6108349_Day3_Aged (Shapes)
▸ 'GSM6108349_Day3_Aged_downscaled_hires', with elements:
GSM6108349_Day3_Aged_hires_image (Images), GSM6108349_Day3_Aged (Shapes)
▸ 'GSM6108349_Day3_Aged_downscaled_lowres', with elements:
GSM6108349_Day3_Aged_lowres_image (Images), GSM6108349_Day3_Aged (Shapes) Load in Python
import lamindb as ln
db = ln.DB("scverse/spatialdata-db")
artifact = db.Artifact.get("Nxu2cj3NDlYPzD5K") # 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/Nxu2cj3NDlYPzD5K
# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid Nxu2cj3NDlYPzD5K Load with the Python client
# pip install git+https://github.com/theislab/spatialdata-db-client
from sddb import Catalog
ds = Catalog().cohort(uids=["Nxu2cj3NDlYPzD5K0000"])[0]
ds.elements() # inspect without downloading
sdata = ds.load(lazy=False) # copy to the local cache and openPart of collection
Spatial sequencing of young and aged lungs following influenza A virus infection→ 6 datasets · time course
Metadata
- Technology
- Visium
- Organism
- mouse
- Tissue
- lung
- Condition
- influenza
- Modality
- RNA
- Observations
- 2,520
- Tier
- bronze
- Chemistry
- Visium v1
- Magnification
- other
- Resolution
- 2,000 × 1,840 px
- mpp
- 4.311 µm/px
- Size
- 28 MB
- Sample ID
- GSM6108349
- License
- unknown
- Published
- Oct 16, 2023
Cite this dataset
No linked publication found — please cite the data source: NCBI GEO ↗.
Source: NCBI GEO ↗ · Reprocessed to SpatialData by SpatialData-DB