Human urinary bladder

NCBI601

Preview Download via Python Download via CLI Load via sddb

print(sdata) Copy

SpatialData object
├── Images
│     └── 'NCBI601_full_image': DataTree[cyx] (3, 16208, 17496), (3, 8104, 8748), (3, 4052, 4374), (3, 2026, 2187)
├── Shapes
│     └── 'NCBI601_spots': GeoDataFrame shape: (1469, 2) (2D shapes)
└── Tables
      └── 'table': AnnData (1469, 33538)
with coordinate systems:
    ▸ 'global', with elements:
        NCBI601_full_image (Images), NCBI601_spots (Shapes)

Load in Python Copy

import lamindb as ln

db = ln.DB("scverse/spatialdata-db")
artifact = db.Artifact.get("Cm4epbo9ROhUFjbO")   # 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 Copy

# one-shot: cache the dataset and print its local path
lamin load https://lamin.ai/scverse/spatialdata-db/artifact/Cm4epbo9ROhUFjbO

# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid Cm4epbo9ROhUFjbO

Load with the Python client Copy

# pip install git+https://github.com/theislab/spatialdata-db-client
from sddb import Catalog

ds = Catalog().cohort(uids=["Cm4epbo9ROhUFjbO0000"])[0]
ds.elements()                 # inspect without downloading
sdata = ds.load(lazy=False)   # copy to the local cache and open

Docs: finding & loading data →

Metadata

Technology

Visium

Organism

human

Tissue

urinary bladder

Condition

bladder transitional cell carcinoma

Modality

RNA

Observations

1,469

Tier

silver

Chemistry

Visium v1

Magnification

20x

Resolution

17,496 × 16,208 px

mpp

0.490 µm/px

Size

350 MB

Sample ID

NCBI601

License

CC BY-NC-SA 4.0 NonCommercial

Published

Jun 4, 2021