Visium
Human ectocervix
GSM8811065
silver Interactive viewer H&E HIV infectious disease No linked publication
print(sdata)
SpatialData object
├── Images
│ ├── 'GSM8811065_P047_P047_hires_image': DataArray[cyx] (3, 1937, 2000)
│ └── 'GSM8811065_P047_P047_lowres_image': DataArray[cyx] (3, 581, 600)
├── Shapes
│ └── 'GSM8811065_P047_P047': GeoDataFrame shape: (1180, 2) (2D shapes)
└── Tables
└── 'table': AnnData (1180, 36601)
with coordinate systems:
▸ 'GSM8811065_P047_P047', with elements:
GSM8811065_P047_P047_hires_image (Images), GSM8811065_P047_P047_lowres_image (Images), GSM8811065_P047_P047 (Shapes)
▸ 'GSM8811065_P047_P047_downscaled_hires', with elements:
GSM8811065_P047_P047_hires_image (Images), GSM8811065_P047_P047 (Shapes)
▸ 'GSM8811065_P047_P047_downscaled_lowres', with elements:
GSM8811065_P047_P047_lowres_image (Images), GSM8811065_P047_P047 (Shapes) Load in Python
import lamindb as ln
db = ln.DB("scverse/spatialdata-db")
artifact = db.Artifact.get("82PTWDLzBULPv7vN") # 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/82PTWDLzBULPv7vN
# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid 82PTWDLzBULPv7vN Load with the Python client
# pip install git+https://github.com/theislab/spatialdata-db-client
from sddb import Catalog
ds = Catalog().cohort(uids=["82PTWDLzBULPv7vN0000"])[0]
ds.elements() # inspect without downloading
sdata = ds.load(lazy=False) # copy to the local cache and openPart of collection
Spatial transcriptomics and in situ immune cell profiling of the host ectocervical landscape of HIV infected Kenyan sex working women→ 10 datasets · comparison
Metadata
- Technology
- Visium
- Organism
- human
- Tissue
- ectocervix
- Condition
- HIV infectious disease
- Modality
- RNA
- Observations
- 1,180
- Tier
- silver
- Chemistry
- Visium v1
- Resolution
- 2,000 × 1,937 px
- mpp
- 3.545 µm/px
- Size
- 21 MB
- Sample ID
- GSM8811065
- License
- unknown
- Published
- Nov 3, 2022
Cite this dataset
No linked publication found — please cite the data source: NCBI GEO ↗.
Source: NCBI GEO ↗ · Reprocessed to SpatialData by SpatialData-DB