10x Xenium
Human breast
GSM7780155
bronze Interactive viewer breast cancer Provisional
print(sdata)
SpatialData object
├── Images
│ ├── 'morphology_focus': DataTree[cyx] (1, 24890, 34142), (1, 12445, 17071), (1, 6222, 8535), (1, 3111, 4267), (1, 1555, 2133)
│ └── 'morphology_mip': DataTree[cyx] (1, 24890, 34142), (1, 12445, 17071), (1, 6222, 8535), (1, 3111, 4267), (1, 1555, 2133)
├── Labels
│ ├── 'cell_labels': DataTree[yx] (24890, 34142), (12445, 17071), (6222, 8535), (3111, 4267), (1555, 2133)
│ └── 'nucleus_labels': DataTree[yx] (24890, 34142), (12445, 17071), (6222, 8535), (3111, 4267), (1555, 2133)
├── Points
│ └── 'transcripts': DataFrame with shape: (15643054, 10) (3D points)
├── Shapes
│ ├── 'cell_boundaries': GeoDataFrame shape: (142272, 1) (2D shapes)
│ ├── 'cell_circles': GeoDataFrame shape: (142272, 2) (2D shapes)
│ └── 'nucleus_boundaries': GeoDataFrame shape: (142272, 1) (2D shapes)
└── Tables
└── 'table': AnnData (142272, 288)
with coordinate systems:
▸ 'global', with elements:
morphology_focus (Images), morphology_mip (Images), 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("isk4XamNDjIO3BD9") # 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/isk4XamNDjIO3BD9
# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid isk4XamNDjIO3BD9 Load with the Python client
# pip install git+https://github.com/theislab/spatialdata-db-client
from sddb import Catalog
ds = Catalog().cohort(uids=["isk4XamNDjIO3BD90000"])[0]
ds.elements() # inspect without downloading
sdata = ds.load(lazy=False) # copy to the local cache and openMetadata
- Technology
- 10x Xenium
- Organism
- human
- Tissue
- breast
- Condition
- breast cancer
- Modality
- RNA
- Observations
- 142,272
- Transcripts
- 15,643,054
- Tier
- bronze
- Size
- 2.9 GB
- Sample ID
- GSM7780155
- License
- unknown
- Published
- Oct 9, 2023
Cite this dataset
No linked publication found — please cite the data source: NCBI GEO ↗.
Source: NCBI GEO ↗ · Reprocessed to SpatialData by SpatialData-DB