Visium
Mouse lung
GSM5808056
bronze Interactive viewer H&E lung adenocarcinoma Provisional
print(sdata)
SpatialData object
├── Images
│ ├── 'GSM5808056_KP_3_hires_image': DataArray[cyx] (3, 1985, 2000)
│ └── 'GSM5808056_KP_3_lowres_image': DataArray[cyx] (3, 596, 600)
├── Shapes
│ └── 'GSM5808056_KP_3': GeoDataFrame shape: (1244, 2) (2D shapes)
└── Tables
└── 'table': AnnData (1244, 32289)
with coordinate systems:
▸ 'GSM5808056_KP_3', with elements:
GSM5808056_KP_3_hires_image (Images), GSM5808056_KP_3_lowres_image (Images), GSM5808056_KP_3 (Shapes)
▸ 'GSM5808056_KP_3_downscaled_hires', with elements:
GSM5808056_KP_3_hires_image (Images), GSM5808056_KP_3 (Shapes)
▸ 'GSM5808056_KP_3_downscaled_lowres', with elements:
GSM5808056_KP_3_lowres_image (Images), GSM5808056_KP_3 (Shapes) Load in Python
import lamindb as ln
db = ln.DB("scverse/spatialdata-db")
artifact = db.Artifact.get("MqfJGOHE4O2JofMe") # 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/MqfJGOHE4O2JofMe
# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid MqfJGOHE4O2JofMe Load with the Python client
# pip install git+https://github.com/theislab/spatialdata-db-client
from sddb import Catalog
ds = Catalog().cohort(uids=["MqfJGOHE4O2JofMe0000"])[0]
ds.elements() # inspect without downloading
sdata = ds.load(lazy=False) # copy to the local cache and openPart of collection
Perturb-map coupled with spatial transcriptomics identifies mutation associated gene signatures in a mouse model of lung adenocarcinoma→ 4 datasets · other
Metadata
- Technology
- Visium
- Organism
- mouse
- Tissue
- lung
- Condition
- lung adenocarcinoma
- Modality
- RNA
- Observations
- 1,244
- Tier
- bronze
- Chemistry
- Visium v1
- Magnification
- other
- Resolution
- 2,000 × 1,985 px
- mpp
- 3.680 µm/px
- Size
- 23 MB
- Sample ID
- GSM5808056
- License
- unknown
- Published
- Jan 15, 2022
Cite this dataset
No linked publication found — please cite the data source: NCBI GEO ↗.
Source: NCBI GEO ↗ · Reprocessed to SpatialData by SpatialData-DB