Visium
Human breast
fresh-frozen-visium-on-cytassist-human-breast-cancer-probe-based-whole-transcriptome-profiling-2-standard
silver Interactive viewer H&E breast cancer No linked publication
print(sdata)
SpatialData object
├── Images
│ ├── 'CytAssist_Fresh_Frozen_Human_Breast_Cancer_full_image': DataTree[cyx] (3, 38232, 20690), (3, 19116, 10345), (3, 9558, 5172), (3, 4779, 2586), (3, 2389, 1293)
│ ├── 'CytAssist_Fresh_Frozen_Human_Breast_Cancer_hires_image': DataArray[cyx] (3, 2000, 1083)
│ └── 'CytAssist_Fresh_Frozen_Human_Breast_Cancer_lowres_image': DataArray[cyx] (3, 600, 325)
├── Shapes
│ └── 'CytAssist_Fresh_Frozen_Human_Breast_Cancer': GeoDataFrame shape: (1657, 2) (2D shapes)
└── Tables
└── 'table': AnnData (1657, 18085)
with coordinate systems:
▸ 'CytAssist_Fresh_Frozen_Human_Breast_Cancer', with elements:
CytAssist_Fresh_Frozen_Human_Breast_Cancer_full_image (Images), CytAssist_Fresh_Frozen_Human_Breast_Cancer_hires_image (Images), CytAssist_Fresh_Frozen_Human_Breast_Cancer_lowres_image (Images), CytAssist_Fresh_Frozen_Human_Breast_Cancer (Shapes)
▸ 'CytAssist_Fresh_Frozen_Human_Breast_Cancer_downscaled_hires', with elements:
CytAssist_Fresh_Frozen_Human_Breast_Cancer_hires_image (Images), CytAssist_Fresh_Frozen_Human_Breast_Cancer (Shapes)
▸ 'CytAssist_Fresh_Frozen_Human_Breast_Cancer_downscaled_lowres', with elements:
CytAssist_Fresh_Frozen_Human_Breast_Cancer_lowres_image (Images), CytAssist_Fresh_Frozen_Human_Breast_Cancer (Shapes) Load in Python
import lamindb as ln
db = ln.DB("scverse/spatialdata-db")
artifact = db.Artifact.get("ZVcVo4W9i7TwYcEL") # 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/ZVcVo4W9i7TwYcEL
# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid ZVcVo4W9i7TwYcEL Load with the Python client
# pip install git+https://github.com/theislab/spatialdata-db-client
from sddb import Catalog
ds = Catalog().cohort(uids=["ZVcVo4W9i7TwYcEL0000"])[0]
ds.elements() # inspect without downloading
sdata = ds.load(lazy=False) # copy to the local cache and openMetadata
- Technology
- Visium
- Organism
- human
- Tissue
- breast
- Condition
- breast cancer
- Modality
- RNA
- Observations
- 1,657
- Tier
- silver
- Chemistry
- Visium CytAssist v2
- Magnification
- 40x
- Resolution
- 20,690 × 38,232 px
- mpp
- 0.215 µm/px
- Size
- 1.5 GB
- Sample ID
- fresh-frozen-visium-on-cytassist-human-breast-cancer-probe-based-whole-transcriptome-profiling-2-standard
- License
- CC BY 4.0
- Published
- Jan 6, 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