Visium

Human prostate gland

MEND144

silver Interactive viewer H&E prostatic acinar adenocarcinoma ✓ Verified publication

Preview Download via Python Download via CLI Load via sddb

print(sdata)

SpatialData object
├── Images
│     └── 'MEND144_full_image': DataTree[cyx] (3, 24258, 24000), (3, 12129, 12000), (3, 6064, 6000), (3, 3032, 3000)
├── Shapes
│     └── 'MEND144_spots': GeoDataFrame shape: (4074, 2) (2D shapes)
└── Tables
      └── 'table': AnnData (4074, 33538)
with coordinate systems:
    ▸ 'global', with elements:
        MEND144_full_image (Images), MEND144_spots (Shapes)

Load in Python

import lamindb as ln

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

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

Load with the Python client

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

ds = Catalog().cohort(uids=["TRXqnywjwWSokaRe0000"])[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

Spatially resolved clonal copy number alterations in benign and malignant tissueJus→

23 datasets · replicates

Metadata

Technology: Visium
Organism: human
Tissue: prostate gland
Condition: prostatic acinar adenocarcinoma
Modality: RNA
Observations: 4,074
Tier: silver
Chemistry: Visium v1
Magnification: 20x
Resolution: 24,000 × 24,258 px
mpp: 0.341 µm/px
Size: 1.3 GB
Sample ID: MEND144
License: CC BY-NC-SA 4.0 NonCommercial
Published: Mar 25, 2024

Cite this dataset

doi.org/10.1038/s41586-022-05023-2 ↗

BibTeX

@article{Erickson_2022,
  title = {Spatially resolved clonal copy number alterations in benign and malignant tissue},
  volume = {608},
  ISSN = {1476-4687},
  url = {http://dx.doi.org/10.1038/s41586-022-05023-2},
  DOI = {10.1038/s41586-022-05023-2},
  number = {7922},
  journal = {Nature},
  publisher = {Springer Science and Business Media LLC},
  author = {Erickson, Andrew and He, Mengxiao and Berglund, Emelie and Marklund, Maja and Mirzazadeh, Reza and Schultz, Niklas and Kvastad, Linda and Andersson, Alma and Bergenstråhle, Ludvig and Bergenstråhle, Joseph and Larsson, Ludvig and Alonso Galicia, Leire and Shamikh, Alia and Basmaci, Elisa and Díaz De Ståhl, Teresita and Rajakumar, Timothy and Doultsinos, Dimitrios and Thrane, Kim and Ji, Andrew L. and Khavari, Paul A. and Tarish, Firaz and Tanoglidi, Anna and Maaskola, Jonas and Colling, Richard and Mirtti, Tuomas and Hamdy, Freddie C. and Woodcock, Dan J. and Helleday, Thomas and Mills, Ian G. and Lamb, Alastair D. and Lundeberg, Joakim},
  year = {2022},
  month = Aug,
  pages = {360–367}
}

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