Human kidney

Xenium Renal Cell Carcinoma Unprocessed (tumor1_region3)

SpatialData object
├── Points
│     └── 'transcripts': DataFrame with shape: (9264047, 8) (3D points)
├── Shapes
│     └── 'cell_circles': GeoDataFrame shape: (40356, 2) (2D shapes)
└── Tables
      └── 'table': AnnData (40356, 380)
with coordinate systems:
    ▸ 'global', with elements:
        transcripts (Points), cell_circles (Shapes)

from sddb import Catalog

ds = Catalog().dataset("aERbYNMkSGnEiMmS0000")
ds.elements()          # inspect without downloading
sdata = ds.to_sdata()  # cached locally, reused
print(sdata)

import lamindb as ln

db = ln.DB("scverse/spatialdata-db")
artifact = db.Artifact.get("aERbYNMkSGnEiMmS")   # stem uid: Lamin resolves it to the 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

# sddb client: download the .zarr into data/
sddb-cli download aERbYNMkSGnEiMmS0000 --dest data/

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

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

Metadata

Technology

Xenium

Vendor

10x Genomics

Panel

280-gene breast base + 100 custom genes (stated)

Organism

human

Tissue

kidney

Condition

clear cell renal carcinoma

Modality

RNA

Observations (cells)

40,356

Transcripts

9,264,047

Target genes

380

Tier

bronze

Size

333 MB

Sample ID

29886158:tumor1_region3

License

CC BY 4.0

Published

Aug 11, 2025

Review

region = one Xenium region of a patient sample; whether a region is tumour or adjacent tissue is not stated

@article{figshare:29886158,
  doi = {10.6084/m9.figshare.29886158.v1},
  title = {Xenium Renal Cell Carcinoma Unprocessed (tumor2_region4)},
  year = {2025}
}