Visium

Mouse brain

NCBI658

silver Interactive viewer H&E ✓ Verified publication

Preview Download via Python Download via CLI Load via sddb

print(sdata)

SpatialData object
├── Images
│     └── 'NCBI658_full_image': DataTree[cyx] (3, 47104, 48640), (3, 23552, 24320), (3, 11776, 12160), (3, 5888, 6080)
├── Shapes
│     └── 'NCBI658_spots': GeoDataFrame shape: (3116, 2) (2D shapes)
└── Tables
      └── 'table': AnnData (3116, 32285)
with coordinate systems:
    ▸ 'global', with elements:
        NCBI658_full_image (Images), NCBI658_spots (Shapes)

Load in Python

import lamindb as ln

db = ln.DB("scverse/spatialdata-db")
artifact = db.Artifact.get("lkTJyxak9yywUBB1")   # 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/lkTJyxak9yywUBB1

# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid lkTJyxak9yywUBB1

Load with the Python client

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

ds = Catalog().cohort(uids=["lkTJyxak9yywUBB10000"])[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

Spatial Multimodal Analysis: MALDI-MSI and Spatial Transcriptomics within the same tissue section→

19 datasets · comparison

Metadata

Technology: Visium
Organism: mouse
Tissue: brain
Modality: RNA
Observations: 3,116
Tier: silver
Chemistry: Visium v1
Magnification: 40x
Resolution: 48,640 × 47,104 px
mpp: 0.172 µm/px
Size: 2.9 GB
Sample ID: NCBI658
License: CC BY-NC-SA 4.0 NonCommercial
Published: May 21, 2023

Cite this dataset

doi.org/10.1038/s41587-023-01937-y ↗

BibTeX

@article{Vicari_2023,
  title = {Spatial multimodal analysis of transcriptomes and metabolomes in tissues},
  volume = {42},
  ISSN = {1546-1696},
  url = {http://dx.doi.org/10.1038/s41587-023-01937-y},
  DOI = {10.1038/s41587-023-01937-y},
  number = {7},
  journal = {Nature Biotechnology},
  publisher = {Springer Science and Business Media LLC},
  author = {Vicari, Marco and Mirzazadeh, Reza and Nilsson, Anna and Shariatgorji, Reza and Bjärterot, Patrik and Larsson, Ludvig and Lee, Hower and Nilsson, Mats and Foyer, Julia and Ekvall, Markus and Czarnewski, Paulo and Zhang, Xiaoqun and Svenningsson, Per and Käll, Lukas and Andrén, Per E. and Lundeberg, Joakim},
  year = {2023},
  month = Sept,
  pages = {1046–1050}
}

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