10x Xenium
Human tonsil
human-tonsil-data-xenium-human-multi-tissue-and-cancer-panel-1-standard__htonsil-follicular-lymphoid-hyperplasia-section-ffpe
silver Interactive viewer H&E No linked publication
print(sdata)
SpatialData object
├── Images
│ ├── 'he_image': DataTree[cyx] (3, 33969, 47351), (3, 16984, 23675), (3, 8492, 11837), (3, 4246, 5918), (3, 2123, 2959)
│ ├── 'morphology_focus': DataTree[cyx] (1, 61216, 45404), (1, 30608, 22702), (1, 15304, 11351), (1, 7652, 5675), (1, 3826, 2837)
│ └── 'morphology_mip': DataTree[cyx] (1, 61216, 45404), (1, 30608, 22702), (1, 15304, 11351), (1, 7652, 5675), (1, 3826, 2837)
├── Labels
│ ├── 'cell_labels': DataTree[yx] (61216, 45404), (30608, 22702), (15304, 11351), (7652, 5675), (3826, 2837)
│ └── 'nucleus_labels': DataTree[yx] (61216, 45404), (30608, 22702), (15304, 11351), (7652, 5675), (3826, 2837)
├── Points
│ └── 'transcripts': DataFrame with shape: (70975823, 10) (3D points)
├── Shapes
│ ├── 'cell_boundaries': GeoDataFrame shape: (864388, 1) (2D shapes)
│ ├── 'cell_circles': GeoDataFrame shape: (864388, 2) (2D shapes)
│ └── 'nucleus_boundaries': GeoDataFrame shape: (864388, 1) (2D shapes)
└── Tables
└── 'table': AnnData (864388, 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("GAm9924HB8LlNSxO") # 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/GAm9924HB8LlNSxO
# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid GAm9924HB8LlNSxO Load with the Python client
# pip install git+https://github.com/theislab/spatialdata-db-client
from sddb import Catalog
ds = Catalog().cohort(uids=["GAm9924HB8LlNSxO0001"])[0]
ds.elements() # inspect without downloading
sdata = ds.load(lazy=False) # copy to the local cache and openPart of collection
10x-human-tonsil-data-xenium-human-multi-tissue-and-cancer-panel-1-standard→ 2 datasets · other
Metadata
- Technology
- 10x Xenium
- Organism
- human
- Tissue
- tonsil
- Modality
- RNA
- Observations
- 864,388
- Transcripts
- 70,975,823
- Tier
- silver
- Chemistry
- Xenium v1
- Magnification
- 40x
- Resolution
- 47,351 × 33,969 px
- mpp
- 0.002 µm/px
- Size
- 12 GB
- Sample ID
- human-tonsil-data-xenium-human-multi-tissue-and-cancer-panel-1-standard__htonsil-follicular-lymphoid-hyperplasia-section-ffpe
- 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