10x Xenium
Mouse bone tissue
mouse-bone-data-with-custom-add-on-panel-1-standard__mfemur-edta-3daydecal-section
silver Interactive viewer H&E No linked publication
print(sdata)
SpatialData object
├── Images
│ ├── 'he_image': DataTree[cyx] (3, 44724, 36576), (3, 22362, 18288), (3, 11181, 9144), (3, 5590, 4572), (3, 2795, 2286)
│ ├── 'morphology_focus': DataTree[cyx] (1, 50965, 53975), (1, 25482, 26987), (1, 12741, 13493), (1, 6370, 6746), (1, 3185, 3373)
│ └── 'morphology_mip': DataTree[cyx] (1, 50965, 53975), (1, 25482, 26987), (1, 12741, 13493), (1, 6370, 6746), (1, 3185, 3373)
├── Labels
│ ├── 'cell_labels': DataTree[yx] (50965, 53975), (25482, 26987), (12741, 13493), (6370, 6746), (3185, 3373)
│ └── 'nucleus_labels': DataTree[yx] (50965, 53975), (25482, 26987), (12741, 13493), (6370, 6746), (3185, 3373)
├── Points
│ └── 'transcripts': DataFrame with shape: (49291523, 10) (3D points)
├── Shapes
│ ├── 'cell_boundaries': GeoDataFrame shape: (348141, 1) (2D shapes)
│ ├── 'cell_circles': GeoDataFrame shape: (348141, 2) (2D shapes)
│ └── 'nucleus_boundaries': GeoDataFrame shape: (348141, 1) (2D shapes)
└── Tables
└── 'table': AnnData (348141, 479)
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("6T1aLES2sndpL1bQ") # 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/6T1aLES2sndpL1bQ
# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid 6T1aLES2sndpL1bQ Load with the Python client
# pip install git+https://github.com/theislab/spatialdata-db-client
from sddb import Catalog
ds = Catalog().cohort(uids=["6T1aLES2sndpL1bQ0001"])[0]
ds.elements() # inspect without downloading
sdata = ds.load(lazy=False) # copy to the local cache and openMetadata
- Technology
- 10x Xenium
- Organism
- mouse
- Tissue
- bone tissue
- Modality
- RNA
- Observations
- 348,141
- Transcripts
- 49,291,523
- Tier
- silver
- Chemistry
- Xenium v1
- Resolution
- 36,576 × 44,724 px
- Size
- 9.5 GB
- Sample ID
- mouse-bone-data-with-custom-add-on-panel-1-standard__mfemur-edta-3daydecal-section
- License
- CC BY 4.0
- Published
- Apr 3, 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