10x Xenium
Mouse skin of back
GSM8586920
bronze Interactive viewer Provisional
print(sdata)
SpatialData object
├── Labels
│ ├── 'cell_labels': DataTree[yx] (72917, 25282), (36458, 12641), (18229, 6320), (9114, 3160), (4557, 1580)
│ └── 'nucleus_labels': DataTree[yx] (72781, 25199), (36390, 12599), (18195, 6299), (9097, 3149), (4548, 1574)
├── Points
│ └── 'transcripts': DataFrame with shape: (7884648, 10) (3D points)
├── Shapes
│ ├── 'cell_boundaries': GeoDataFrame shape: (91345, 1) (2D shapes)
│ ├── 'cell_circles': GeoDataFrame shape: (91345, 2) (2D shapes)
│ └── 'nucleus_boundaries': GeoDataFrame shape: (91345, 1) (2D shapes)
└── Tables
└── 'table': AnnData (91345, 328)
with coordinate systems:
▸ 'global', with elements:
cell_labels (Labels), nucleus_labels (Labels), transcripts (Points), cell_boundaries (Shapes), cell_circles (Shapes), nucleus_boundaries (Shapes) Load in Python
import lamindb as ln
db = ln.DB("scverse/spatialdata-db")
artifact = db.Artifact.get("Mt10CWKfiOhkaASZ") # 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/Mt10CWKfiOhkaASZ
# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid Mt10CWKfiOhkaASZ Load with the Python client
# pip install git+https://github.com/theislab/spatialdata-db-client
from sddb import Catalog
ds = Catalog().cohort(uids=["Mt10CWKfiOhkaASZ0000"])[0]
ds.elements() # inspect without downloading
sdata = ds.load(lazy=False) # copy to the local cache and openPart of collection
Reprogramming of epidermal keratinocytes by PITX1 transforms the cutaneous cellular landscape and promotes wound healing [Xenium]→ 4 datasets · comparison
Metadata
- Technology
- 10x Xenium
- Organism
- mouse
- Tissue
- skin of back
- Modality
- RNA
- Observations
- 91,345
- Transcripts
- 7,884,648
- Tier
- bronze
- Size
- 399 MB
- Sample ID
- GSM8586920
- License
- unknown
- Published
- Nov 22, 2024
Cite this dataset
No linked publication found — please cite the data source: NCBI GEO ↗.
Source: NCBI GEO ↗ · Reprocessed to SpatialData by SpatialData-DB