10x Xenium
Mouse multicellular organism
mouse-pup-preview-data-xenium-mouse-tissue-atlassing-panel-1-standard
silver Interactive viewer H&E No linked publication
print(sdata)
SpatialData object
├── Images
│ ├── 'he_image': DataTree[cyx] (3, 49652, 82033), (3, 24826, 41016), (3, 12413, 20508), (3, 6206, 10254), (3, 3103, 5127)
│ ├── 'morphology_focus': DataTree[cyx] (1, 108670, 53991), (1, 54335, 26995), (1, 27167, 13497), (1, 13583, 6748), (1, 6791, 3374)
│ └── 'morphology_mip': DataTree[cyx] (1, 108670, 53991), (1, 54335, 26995), (1, 27167, 13497), (1, 13583, 6748), (1, 6791, 3374)
├── Labels
│ ├── 'cell_labels': DataTree[yx] (108670, 53991), (54335, 26995), (27167, 13497), (13583, 6748), (6791, 3374)
│ └── 'nucleus_labels': DataTree[yx] (108670, 53991), (54335, 26995), (27167, 13497), (13583, 6748), (6791, 3374)
├── Points
│ └── 'transcripts': DataFrame with shape: (239408816, 10) (3D points)
├── Shapes
│ ├── 'cell_boundaries': GeoDataFrame shape: (1355849, 1) (2D shapes)
│ ├── 'cell_circles': GeoDataFrame shape: (1355849, 2) (2D shapes)
│ └── 'nucleus_boundaries': GeoDataFrame shape: (1355849, 1) (2D shapes)
└── Tables
└── 'table': AnnData (1355849, 379)
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("DIl9SBZ9Ubwcl6N3") # 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/DIl9SBZ9Ubwcl6N3
# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid DIl9SBZ9Ubwcl6N3 Load with the Python client
# pip install git+https://github.com/theislab/spatialdata-db-client
from sddb import Catalog
ds = Catalog().cohort(uids=["DIl9SBZ9Ubwcl6N30001"])[0]
ds.elements() # inspect without downloading
sdata = ds.load(lazy=False) # copy to the local cache and openMetadata
- Technology
- 10x Xenium
- Organism
- mouse
- Tissue
- multicellular organism
- Modality
- RNA
- Observations
- 1,355,849
- Transcripts
- 239,408,816
- Tier
- silver
- Chemistry
- Xenium v1
- Magnification
- 40x
- Resolution
- 82,033 × 49,652 px
- mpp
- 0.000 µm/px
- Size
- 32 GB
- Sample ID
- mouse-pup-preview-data-xenium-mouse-tissue-atlassing-panel-1-standard
- License
- CC BY 4.0
- Published
- Aug 18, 2023
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