10x Xenium
Human bone marrow
human-bone-and-bone-marrow-data-with-custom-add-on-panel-1-standard__hbonemarrow-acute-lymphoid-leukemia-section
silver Interactive viewer H&E acute lymphoblastic leukemia No linked publication
print(sdata)
SpatialData object
├── Images
│ ├── 'he_image': DataTree[cyx] (3, 37252, 11024), (3, 18626, 5512), (3, 9313, 2756), (3, 4656, 1378), (3, 2328, 689)
│ ├── 'morphology_focus': DataTree[cyx] (1, 17145, 48266), (1, 8572, 24133), (1, 4286, 12066), (1, 2143, 6033), (1, 1071, 3016)
│ └── 'morphology_mip': DataTree[cyx] (1, 17145, 48266), (1, 8572, 24133), (1, 4286, 12066), (1, 2143, 6033), (1, 1071, 3016)
├── Labels
│ ├── 'cell_labels': DataTree[yx] (17145, 48266), (8572, 24133), (4286, 12066), (2143, 6033), (1071, 3016)
│ └── 'nucleus_labels': DataTree[yx] (17145, 48266), (8572, 24133), (4286, 12066), (2143, 6033), (1071, 3016)
├── Points
│ └── 'transcripts': DataFrame with shape: (8311608, 10) (3D points)
├── Shapes
│ ├── 'cell_boundaries': GeoDataFrame shape: (225906, 1) (2D shapes)
│ ├── 'cell_circles': GeoDataFrame shape: (225906, 2) (2D shapes)
│ └── 'nucleus_boundaries': GeoDataFrame shape: (225906, 1) (2D shapes)
└── Tables
└── 'table': AnnData (225906, 477)
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("aISiYhEynUVzlDd1") # 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/aISiYhEynUVzlDd1
# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid aISiYhEynUVzlDd1 Load with the Python client
# pip install git+https://github.com/theislab/spatialdata-db-client
from sddb import Catalog
ds = Catalog().cohort(uids=["aISiYhEynUVzlDd10001"])[0]
ds.elements() # inspect without downloading
sdata = ds.load(lazy=False) # copy to the local cache and openPart of collection
10x-human-bone-and-bone-marrow-data-with-custom-add-on-panel-1-standard→ 3 datasets · other
Metadata
- Technology
- 10x Xenium
- Organism
- human
- Tissue
- bone marrow
- Condition
- acute lymphoblastic leukemia
- Modality
- RNA
- Observations
- 225,906
- Transcripts
- 8,311,608
- Tier
- silver
- Chemistry
- Xenium v1
- Magnification
- 40x
- Resolution
- 11,024 × 37,252 px
- mpp
- 0.002 µm/px
- Size
- 2.9 GB
- Sample ID
- human-bone-and-bone-marrow-data-with-custom-add-on-panel-1-standard__hbonemarrow-acute-lymphoid-leukemia-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