10x Xenium
Human heart
human-heart-data-xenium-human-multi-tissue-and-cancer-panel-1-standard
silver Interactive viewer H&E No linked publication
print(sdata)
SpatialData object
├── Images
│ ├── 'he_image': DataTree[cyx] (3, 10645, 24544), (3, 5322, 12272), (3, 2661, 6136), (3, 1330, 3068), (3, 665, 1534)
│ ├── 'morphology_focus': DataTree[cyx] (1, 34050, 14326), (1, 17025, 7163), (1, 8512, 3581), (1, 4256, 1790), (1, 2128, 895)
│ └── 'morphology_mip': DataTree[cyx] (1, 34050, 14326), (1, 17025, 7163), (1, 8512, 3581), (1, 4256, 1790), (1, 2128, 895)
├── Labels
│ ├── 'cell_labels': DataTree[yx] (34050, 14326), (17025, 7163), (8512, 3581), (4256, 1790), (2128, 895)
│ └── 'nucleus_labels': DataTree[yx] (34050, 14326), (17025, 7163), (8512, 3581), (4256, 1790), (2128, 895)
├── Points
│ └── 'transcripts': DataFrame with shape: (2452409, 10) (3D points)
├── Shapes
│ ├── 'cell_boundaries': GeoDataFrame shape: (26366, 1) (2D shapes)
│ ├── 'cell_circles': GeoDataFrame shape: (26366, 2) (2D shapes)
│ └── 'nucleus_boundaries': GeoDataFrame shape: (26366, 1) (2D shapes)
└── Tables
└── 'table': AnnData (26366, 377)
with coordinate systems:
▸ 'global', with elements:
he_image (Images), 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("Lgv6nVzHIwrsIwiz") # 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/Lgv6nVzHIwrsIwiz
# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid Lgv6nVzHIwrsIwiz Load with the Python client
# pip install git+https://github.com/theislab/spatialdata-db-client
from sddb import Catalog
ds = Catalog().cohort(uids=["Lgv6nVzHIwrsIwiz0001"])[0]
ds.elements() # inspect without downloading
sdata = ds.load(lazy=False) # copy to the local cache and openMetadata
- Technology
- 10x Xenium
- Organism
- human
- Tissue
- heart
- Modality
- RNA
- Observations
- 26,366
- Transcripts
- 2,452,409
- Tier
- silver
- Chemistry
- Xenium v1
- Magnification
- 40x
- Resolution
- 24,544 × 10,645 px
- mpp
- 0.003 µm/px
- Size
- 1.7 GB
- Sample ID
- human-heart-data-xenium-human-multi-tissue-and-cancer-panel-1-standard
- License
- CC BY 4.0
- Published
- Mar 5, 2024
Cite this dataset
No linked publication found — please cite the data source: 10x Genomics ↗.
Source: 10x Genomics ↗ · License: CC BY 4.0 ↗ · Reprocessed to SpatialData by SpatialData-DB