spatial transcriptomics

Human breast

SPA65

silver Interactive viewer H&E invasive ductal breast carcinoma ✓ Verified publication

Preview Download via Python Download via CLI Load via sddb

print(sdata)

SpatialData object
├── Images
│     └── 'SPA65_full_image': DataTree[cyx] (3, 9923, 9315), (3, 4961, 4657), (3, 2480, 2328), (3, 1240, 1164)
├── Shapes
│     └── 'SPA65_spots': GeoDataFrame shape: (498, 2) (2D shapes)
└── Tables
      └── 'table': AnnData (498, 16999)
with coordinate systems:
    ▸ 'global', with elements:
        SPA65_full_image (Images), SPA65_spots (Shapes)

Load in Python

import lamindb as ln

db = ln.DB("scverse/spatialdata-db")
artifact = db.Artifact.get("UfbvhrWVUQiABCBQ")   # 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/UfbvhrWVUQiABCBQ

# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid UfbvhrWVUQiABCBQ

Load with the Python client

# pip install git+https://github.com/theislab/spatialdata-db-client
from sddb import Catalog

ds = Catalog().cohort(uids=["UfbvhrWVUQiABCBQ0000"])[0]
ds.elements()                 # inspect without downloading
sdata = ds.load(lazy=False)   # copy to the local cache and open

Docs: finding & loading data →

View on Lamin ↗ Open in Vitessce ↗ Flag a data issue

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: 498
Tier: silver
Chemistry: ST 1k
Resolution: 9,315 × 9,923 px
mpp: 0.687 µm/px
Size: 182 MB
Sample ID: SPA65
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