10x Xenium
Human skin of body
human-skin-preview-data-xenium-human-skin-gene-expression-panel-add-on-1-standard
silver Interactive viewer H&E melanoma No linked publication
print(sdata)
SpatialData object
├── Images
│ ├── 'he_image': DataTree[cyx] (3, 43287, 22209), (3, 21643, 11104), (3, 10821, 5552), (3, 5410, 2776), (3, 2705, 1388)
│ ├── 'morphology_focus': DataTree[cyx] (1, 13725, 28467), (1, 6862, 14233), (1, 3431, 7116), (1, 1715, 3558), (1, 857, 1779)
│ └── 'morphology_mip': DataTree[cyx] (1, 13725, 28467), (1, 6862, 14233), (1, 3431, 7116), (1, 1715, 3558), (1, 857, 1779)
├── Labels
│ ├── 'cell_labels': DataTree[yx] (13725, 28467), (6862, 14233), (3431, 7116), (1715, 3558), (857, 1779)
│ └── 'nucleus_labels': DataTree[yx] (13725, 28467), (6862, 14233), (3431, 7116), (1715, 3558), (857, 1779)
├── Points
│ └── 'transcripts': DataFrame with shape: (15894298, 10) (3D points)
├── Shapes
│ ├── 'cell_boundaries': GeoDataFrame shape: (87499, 1) (2D shapes)
│ ├── 'cell_circles': GeoDataFrame shape: (87499, 2) (2D shapes)
│ └── 'nucleus_boundaries': GeoDataFrame shape: (87499, 1) (2D shapes)
└── Tables
└── 'table': AnnData (87499, 382)
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("y0eYODAHRDVnFbvx") # 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/y0eYODAHRDVnFbvx
# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid y0eYODAHRDVnFbvx Load with the Python client
# pip install git+https://github.com/theislab/spatialdata-db-client
from sddb import Catalog
ds = Catalog().cohort(uids=["y0eYODAHRDVnFbvx0001"])[0]
ds.elements() # inspect without downloading
sdata = ds.load(lazy=False) # copy to the local cache and openMetadata
- Technology
- 10x Xenium
- Organism
- human
- Tissue
- skin of body
- Condition
- melanoma
- Modality
- RNA
- Observations
- 87,499
- Transcripts
- 15,894,298
- Tier
- silver
- Chemistry
- Xenium v1
- Magnification
- 40x
- Resolution
- 22,209 × 43,287 px
- mpp
- 0.002 µm/px
- Size
- 3.5 GB
- Sample ID
- human-skin-preview-data-xenium-human-skin-gene-expression-panel-add-on-1-standard
- License
- CC BY 4.0
- Published
- Dec 7, 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