Visium HD
Human breast
visium-hd-cytassist-gene-expression-libraries-human-breast-cancer-ffpe-if
silver Interactive viewer H&E breast cancer No linked publication
print(sdata)
SpatialData object
├── Images
│ └── 'Visium_HD_Human_Breast_Cancer_FFPE_full_image': DataTree[cyx] (3, 25550, 26049), (3, 12775, 13024), (3, 6387, 6512), (3, 3193, 3256), (3, 1596, 1628)
├── Shapes
│ ├── 'Visium_HD_Human_Breast_Cancer_FFPE_square_002um': GeoDataFrame shape: (10535119, 1) (2D shapes)
│ ├── 'Visium_HD_Human_Breast_Cancer_FFPE_square_008um': GeoDataFrame shape: (663857, 1) (2D shapes)
│ ├── 'Visium_HD_Human_Breast_Cancer_FFPE_square_016um': GeoDataFrame shape: (167545, 1) (2D shapes)
│ └── 'Visium_HD_Human_Breast_Cancer_FFPE_square_016um_for_vitessce': GeoDataFrame shape: (167545, 2) (2D shapes)
└── Tables
├── 'square_002um': AnnData (10535119, 18085)
├── 'square_008um': AnnData (663857, 18085)
└── 'square_016um': AnnData (167545, 18085)
with coordinate systems:
▸ 'Visium_HD_Human_Breast_Cancer_FFPE', with elements:
Visium_HD_Human_Breast_Cancer_FFPE_full_image (Images), Visium_HD_Human_Breast_Cancer_FFPE_square_002um (Shapes), Visium_HD_Human_Breast_Cancer_FFPE_square_008um (Shapes), Visium_HD_Human_Breast_Cancer_FFPE_square_016um (Shapes), Visium_HD_Human_Breast_Cancer_FFPE_square_016um_for_vitessce (Shapes)
▸ 'Visium_HD_Human_Breast_Cancer_FFPE_downscaled_hires', with elements:
Visium_HD_Human_Breast_Cancer_FFPE_square_002um (Shapes), Visium_HD_Human_Breast_Cancer_FFPE_square_008um (Shapes), Visium_HD_Human_Breast_Cancer_FFPE_square_016um (Shapes), Visium_HD_Human_Breast_Cancer_FFPE_square_016um_for_vitessce (Shapes)
▸ 'Visium_HD_Human_Breast_Cancer_FFPE_downscaled_lowres', with elements:
Visium_HD_Human_Breast_Cancer_FFPE_square_002um (Shapes), Visium_HD_Human_Breast_Cancer_FFPE_square_008um (Shapes), Visium_HD_Human_Breast_Cancer_FFPE_square_016um (Shapes), Visium_HD_Human_Breast_Cancer_FFPE_square_016um_for_vitessce (Shapes) Python · sddb client
from sddb import Catalog
ds = Catalog().dataset("nn422XqX2ljJzIIc0000")
ds.elements() # inspect without downloading
sdata = ds.to_sdata() # cached locally, reused
print(sdata) Python · lamindb
Needs pip install lamindb and network access to the Lamin database, which is limited during the alpha. If it fails, use the Client tab.
import lamindb as ln
db = ln.DB("scverse/spatialdata-db")
artifact = db.Artifact.get("nn422XqX2ljJzIIc") # stem uid: Lamin resolves it to the 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 Shell
# sddb client: download the .zarr into data/
sddb-cli download nn422XqX2ljJzIIc0000 --dest data/
# or lamin: cache the dataset and print its local path
lamin load https://lamin.ai/scverse/spatialdata-db/artifact/nn422XqX2ljJzIIc
# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid nn422XqX2ljJzIIcLicense: CC BY 4.0
Metadata
- Technology
- Visium HD
- Organism
- human
- Tissue
- breast
- Condition
- breast cancer
- Modality
- RNA
- Observations (bins)
- 663,857
- Tier
- silver
- Chemistry
- Visium HD v1
- Magnification
- 20x
- Resolution
- 26,049 × 25,550 px
- mpp
- 0.325 µm/px
- Size
- 5.4 GB
- Sample ID
- visium-hd-cytassist-gene-expression-libraries-human-breast-cancer-ffpe-if
- License
- CC BY 4.0
- Published
- Dec 16, 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