Human skin of body

NCBI770

Preview Download via Python Download via CLI Load via sddb

print(sdata) Copy

SpatialData object
├── Images
│     └── 'NCBI770_full_image': DataTree[cyx] (3, 15872, 15872), (3, 7936, 7936), (3, 3968, 3968), (3, 1984, 1984)
├── Shapes
│     └── 'NCBI770_spots': GeoDataFrame shape: (666, 2) (2D shapes)
└── Tables
      └── 'table': AnnData (666, 16157)
with coordinate systems:
    ▸ 'global', with elements:
        NCBI770_full_image (Images), NCBI770_spots (Shapes)

Load in Python Copy

import lamindb as ln

db = ln.DB("scverse/spatialdata-db")
artifact = db.Artifact.get("YTRS2J6byBSnZouy")   # 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/YTRS2J6byBSnZouy

# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid YTRS2J6byBSnZouy

Load with the Python client Copy

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

ds = Catalog().cohort(uids=["YTRS2J6byBSnZouy0001"])[0]
ds.elements()                 # inspect without downloading
sdata = ds.load(lazy=False)   # copy to the local cache and open

Docs: finding & loading data →

Metadata

Technology

spatial transcriptomics

Organism

human

Tissue

skin of body

Condition

skin squamous cell carcinoma

Modality

RNA

Observations

666

Tier

silver

Chemistry

ST 2k

Magnification

20x

Resolution

15,872 × 15,872 px

mpp

0.366 µm/px

Size

202 MB

Sample ID

NCBI770

License

CC BY-NC-SA 4.0 NonCommercial

Published

Jun 22, 2020