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Visium

Human breast

NCBI776

silver Interactive viewer H&E invasive ductal breast carcinoma ✓ Verified publication
Human breast preview
print(sdata) 
SpatialData object
├── Images
│     └── 'NCBI776_full_image': DataTree[cyx] (3, 21571, 19505), (3, 10785, 9752), (3, 5392, 4876), (3, 2696, 2438)
├── Shapes
│     └── 'NCBI776_spots': GeoDataFrame shape: (4992, 2) (2D shapes)
└── Tables
      └── 'table': AnnData (4992, 18085)
with coordinate systems:
    ▸ 'global', with elements:
        NCBI776_full_image (Images), NCBI776_spots (Shapes)
Install (Python 3.12+) Docs →
Python · sddb client 
from sddb import Catalog

ds = Catalog().dataset("DPfgYNfUW4QNUwxj0000")
ds.elements()          # inspect without downloading
sdata = ds.to_sdata()  # cached locally, reused
print(sdata)
Install (Python 3.12+) Docs →
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("DPfgYNfUW4QNUwxj")   # 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
Install (Python 3.12+) Docs →
Shell 
# sddb client: download the .zarr into data/
sddb-cli download DPfgYNfUW4QNUwxj0000 --dest data/

# or lamin: cache the dataset and print its local path
lamin load https://lamin.ai/scverse/spatialdata-db/artifact/DPfgYNfUW4QNUwxj

# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid DPfgYNfUW4QNUwxj
Install (Python 3.12+) Docs →

License: CC BY-NC-SA 4.0 (noncommercial)

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Metadata

Technology
Visium
Organism
human
Tissue
breast
Condition
invasive ductal breast carcinoma
Modality
RNA
Observations (spots)
4,992
Tier
silver
Chemistry
Visium v1
Magnification
20x
Resolution
19,505 × 21,571 px
mpp
0.548 µm/px
Size
1.1 GB
Sample ID
NCBI776
License
CC BY-NC-SA 4.0 NonCommercial
Published
Oct 9, 2023

Cite this dataset

doi.org/10.1038/s41467-023-43458-x ↗
BibTeX 
@article{Janesick_2023,
  title = {High resolution mapping of the tumor microenvironment using integrated single-cell, spatial and in situ analysis},
  volume = {14},
  ISSN = {2041-1723},
  url = {http://dx.doi.org/10.1038/s41467-023-43458-x},
  DOI = {10.1038/s41467-023-43458-x},
  number = {1},
  journal = {Nature Communications},
  publisher = {Springer Science and Business Media LLC},
  author = {Janesick, Amanda and Shelansky, Robert and Gottscho, Andrew D. and Wagner, Florian and Williams, Stephen R. and Rouault, Morgane and Beliakoff, Ghezal and Morrison, Carolyn A. and Oliveira, Michelli F. and Sicherman, Jordan T. and Kohlway, Andrew and Abousoud, Jawad and Drennon, Tingsheng Yu and Mohabbat, Seayar H. and Taylor, Sarah E. B.},
  year = {2023},
  month = Dec
}

Source: nature.com ↗ · License: CC BY-NC-SA 4.0 ↗ · Reprocessed to SpatialData by SpatialData-DB