spatial transcriptomics
Human breast
SPA91
silver Interactive viewer H&E invasive ductal breast carcinoma ✓ Verified publication

print(sdata)
SpatialData object
├── Images
│ └── 'SPA91_full_image': DataTree[cyx] (3, 9846, 9323), (3, 4923, 4661), (3, 2461, 2330), (3, 1230, 1165)
├── Shapes
│ └── 'SPA91_spots': GeoDataFrame shape: (297, 2) (2D shapes)
└── Tables
└── 'table': AnnData (297, 17316)
with coordinate systems:
▸ 'global', with elements:
SPA91_full_image (Images), SPA91_spots (Shapes) Python · sddb client
from sddb import Catalog
ds = Catalog().dataset("5kCsryIYSQiVqtyl0000")
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("5kCsryIYSQiVqtyl") # 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 5kCsryIYSQiVqtyl0000 --dest data/
# or lamin: cache the dataset and print its local path
lamin load https://lamin.ai/scverse/spatialdata-db/artifact/5kCsryIYSQiVqtyl
# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid 5kCsryIYSQiVqtyl License: CC BY-NC-SA 4.0 (noncommercial)
Part of collection
Integrating spatial gene expression and breast tumour morphology via deep learning→ 84 datasets · comparison
Metadata
- Technology
- spatial transcriptomics
- Organism
- human
- Tissue
- breast
- Condition
- invasive ductal breast carcinoma
- Modality
- RNA
- Observations (spots)
- 297
- Tier
- silver
- Chemistry
- ST 1k
- Resolution
- 9,323 × 9,846 px
- mpp
- 0.686 µm/px
- Size
- 163 MB
- Sample ID
- SPA91
- License
- CC BY-NC-SA 4.0 NonCommercial
- Published
- Nov 30, 2021
Cite this dataset
doi.org/10.1126/science.aaf2403 ↗ BibTeX
@article{St_hl_2016,
title = {Visualization and analysis of gene expression in tissue sections by spatial transcriptomics},
volume = {353},
ISSN = {1095-9203},
url = {http://dx.doi.org/10.1126/science.aaf2403},
DOI = {10.1126/science.aaf2403},
number = {6294},
journal = {Science},
publisher = {American Association for the Advancement of Science (AAAS)},
author = {Ståhl, Patrik L. and Salmén, Fredrik and Vickovic, Sanja and Lundmark, Anna and Navarro, José Fernández and Magnusson, Jens and Giacomello, Stefania and Asp, Michaela and Westholm, Jakub O. and Huss, Mikael and Mollbrink, Annelie and Linnarsson, Sten and Codeluppi, Simone and Borg, Åke and Pontén, Fredrik and Costea, Paul Igor and Sahlén, Pelin and Mulder, Jan and Bergmann, Olaf and Lundeberg, Joakim and Frisén, Jonas},
year = {2016},
month = July,
pages = {78–82}
} Source: science.org ↗ · License: CC BY-NC-SA 4.0 ↗ · Reprocessed to SpatialData by SpatialData-DB