10x Xenium
Mouse brain
xenium-in-situ-analysis-of-alzheimers-disease-mouse-model-brain-coronal-sections-from-one-hemisphere-over-a-time-course-1-standard__ffpe-tgcrnd8-2-5-months
silver Interactive viewer Alzheimer disease No linked publication
print(sdata)
SpatialData object
├── Images
│ ├── 'morphology_focus': DataTree[cyx] (1, 20739, 28492), (1, 10369, 14246), (1, 5184, 7123), (1, 2592, 3561), (1, 1296, 1780)
│ └── 'morphology_mip': DataTree[cyx] (1, 20739, 28492), (1, 10369, 14246), (1, 5184, 7123), (1, 2592, 3561), (1, 1296, 1780)
├── Labels
│ ├── 'cell_labels': DataTree[yx] (20739, 28492), (10369, 14246), (5184, 7123), (2592, 3561), (1296, 1780)
│ └── 'nucleus_labels': DataTree[yx] (20739, 28492), (10369, 14246), (5184, 7123), (2592, 3561), (1296, 1780)
├── Points
│ └── 'transcripts': DataFrame with shape: (17052241, 10) (3D points)
├── Shapes
│ ├── 'cell_boundaries': GeoDataFrame shape: (53913, 1) (2D shapes)
│ ├── 'cell_circles': GeoDataFrame shape: (53913, 2) (2D shapes)
│ └── 'nucleus_boundaries': GeoDataFrame shape: (53913, 1) (2D shapes)
└── Tables
└── 'table': AnnData (53913, 347)
with coordinate systems:
▸ 'global', with elements:
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("oDMUnabf6lLrDmY1") # 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/oDMUnabf6lLrDmY1
# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid oDMUnabf6lLrDmY1 Load with the Python client
# pip install git+https://github.com/theislab/spatialdata-db-client
from sddb import Catalog
ds = Catalog().cohort(uids=["oDMUnabf6lLrDmY10000"])[0]
ds.elements() # inspect without downloading
sdata = ds.load(lazy=False) # copy to the local cache and openMetadata
- Technology
- 10x Xenium
- Organism
- mouse
- Tissue
- brain
- Condition
- Alzheimer disease
- Modality
- RNA
- Observations
- 53,913
- Transcripts
- 17,052,241
- Tier
- silver
- Chemistry
- Xenium v1
- Size
- 1.9 GB
- Sample ID
- xenium-in-situ-analysis-of-alzheimers-disease-mouse-model-brain-coronal-sections-from-one-hemisphere-over-a-time-course-1-standard__ffpe-tgcrnd8-2-5-months
- License
- CC BY 4.0
- Published
- Jul 13, 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