Visium
Mouse skin of body
ZEN65
silver Interactive viewer H&E melanoma Provisional
print(sdata)
SpatialData object
├── Images
│ └── 'ZEN65_full_image': DataTree[cyx] (3, 36416, 35392), (3, 18208, 17696), (3, 9104, 8848), (3, 4552, 4424)
├── Shapes
│ └── 'ZEN65_spots': GeoDataFrame shape: (932, 2) (2D shapes)
└── Tables
└── 'table': AnnData (932, 68886)
with coordinate systems:
▸ 'global', with elements:
ZEN65_full_image (Images), ZEN65_spots (Shapes) Python · sddb client
from sddb import Catalog
ds = Catalog().dataset("QBSrYh5ulOf6jlXy0000")
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("QBSrYh5ulOf6jlXy") # 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 QBSrYh5ulOf6jlXy0000 --dest data/
# or lamin: cache the dataset and print its local path
lamin load https://lamin.ai/scverse/spatialdata-db/artifact/QBSrYh5ulOf6jlXy
# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid QBSrYh5ulOf6jlXyLicense: CC BY-NC-SA 4.0 (noncommercial)
Metadata
- Technology
- Visium
- Organism
- mouse
- Tissue
- skin of body
- Condition
- melanoma
- Modality
- RNA
- Observations (spots)
- 932
- Tier
- silver
- Chemistry
- Visium v1
- Magnification
- 40x
- Resolution
- 35,392 × 36,416 px
- mpp
- 0.221 µm/px
- Size
- 2.4 GB
- Sample ID
- ZEN65
- License
- CC BY-NC-SA 4.0 NonCommercial
- Published
- May 31, 2024
Cite this dataset
doi.org/10.1101/2023.07.27.550727 ↗ BibTeX
@article{Domanskyi_2023,
title = {Nextflow Pipeline for Visium and H&E Data from Patient-Derived Xenograft Samples},
url = {http://dx.doi.org/10.1101/2023.07.27.550727},
DOI = {10.1101/2023.07.27.550727},
publisher = {openRxiv},
author = {Domanskyi, Sergii and Srivastava, Anuj and Kaster, Jessica and Li, Haiyin and Herlyn, Meenhard and Rubinstein, Jill C. and Chuang, Jeffrey H.},
year = {2023},
month = July
}Source: biorxiv.org ↗ · License: CC BY-NC-SA 4.0 ↗ · Reprocessed to SpatialData by SpatialData-DB