Visium
Mouse lung
GSM6108346
bronze Interactive viewer H&E Provisional
print(sdata)
SpatialData object
├── Images
│ ├── 'GSM6108346_Day0_Young_hires_image': DataArray[cyx] (3, 2000, 1999)
│ └── 'GSM6108346_Day0_Young_lowres_image': DataArray[cyx] (3, 600, 600)
├── Shapes
│ └── 'GSM6108346_Day0_Young': GeoDataFrame shape: (1986, 2) (2D shapes)
└── Tables
└── 'table': AnnData (1986, 32285)
with coordinate systems:
▸ 'GSM6108346_Day0_Young', with elements:
GSM6108346_Day0_Young_hires_image (Images), GSM6108346_Day0_Young_lowres_image (Images), GSM6108346_Day0_Young (Shapes)
▸ 'GSM6108346_Day0_Young_downscaled_hires', with elements:
GSM6108346_Day0_Young_hires_image (Images), GSM6108346_Day0_Young (Shapes)
▸ 'GSM6108346_Day0_Young_downscaled_lowres', with elements:
GSM6108346_Day0_Young_lowres_image (Images), GSM6108346_Day0_Young (Shapes) Load in Python
import lamindb as ln
db = ln.DB("scverse/spatialdata-db")
artifact = db.Artifact.get("v5fldM5YTFEHsIdq") # 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/v5fldM5YTFEHsIdq
# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid v5fldM5YTFEHsIdq Load with the Python client
# pip install git+https://github.com/theislab/spatialdata-db-client
from sddb import Catalog
ds = Catalog().cohort(uids=["v5fldM5YTFEHsIdq0000"])[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
- Modality
- RNA
- Observations
- 1,986
- Tier
- bronze
- Chemistry
- Visium v1
- Magnification
- other
- Resolution
- 1,999 × 2,000 px
- mpp
- 4.004 µm/px
- Size
- 23 MB
- Sample ID
- GSM6108346
- 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