Visium

Human gut-associated lymphoid tissue

GSM7986081

bronze Interactive viewer H&E Provisional

Human gut-associated lymphoid tissue preview

Preview Client Lamin CLI

print(sdata)

SpatialData object
├── Images
│     ├── 'GSM7986081_A1_hires_image': DataArray[cyx] (3, 1917, 2000)
│     └── 'GSM7986081_A1_lowres_image': DataArray[cyx] (3, 575, 600)
├── Shapes
│     └── 'GSM7986081_A1': GeoDataFrame shape: (3408, 2) (2D shapes)
└── Tables
      └── 'table': AnnData (3408, 17943)
with coordinate systems:
    ▸ 'GSM7986081_A1', with elements:
        GSM7986081_A1_hires_image (Images), GSM7986081_A1_lowres_image (Images), GSM7986081_A1 (Shapes)
    ▸ 'GSM7986081_A1_downscaled_hires', with elements:
        GSM7986081_A1_hires_image (Images), GSM7986081_A1 (Shapes)
    ▸ 'GSM7986081_A1_downscaled_lowres', with elements:
        GSM7986081_A1_lowres_image (Images), GSM7986081_A1 (Shapes)

Install (Python 3.12+) Docs →

Python · sddb client

from sddb import Catalog

ds = Catalog().dataset("nIcGbbFQe9vAjI5i0000")
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("nIcGbbFQe9vAjI5i")   # 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 nIcGbbFQe9vAjI5i0000 --dest data/

# or lamin: cache the dataset and print its local path
lamin load https://lamin.ai/scverse/spatialdata-db/artifact/nIcGbbFQe9vAjI5i

# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid nIcGbbFQe9vAjI5i

Install (Python 3.12+) Docs →

License: NCBI GEO policy

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Part of collection

Double-negative B cells and DNASE1L3 colocalise with microbiota in gut-associated lymphoid tissue→

2 datasets · other

Metadata

Technology: Visium
Organism: human
Tissue: gut-associated lymphoid tissue
Modality: RNA
Observations (spots): 3,408
Tier: bronze
Chemistry: Visium v1
Magnification: other
Resolution: 2,000 × 1,917 px
mpp: 3.476 µm/px
Size: 19.1 MB
Sample ID: GSM7986081
License: NCBI GEO policy
Published: Mar 28, 2024

Cite this dataset

doi.org/10.1038/s41467-024-48267-4 ↗

BibTeX

@article{Montorsi_2024,
  title = {Double-negative B cells and DNASE1L3 colocalise with microbiota in gut-associated lymphoid tissue},
  volume = {15},
  ISSN = {2041-1723},
  url = {http://dx.doi.org/10.1038/s41467-024-48267-4},
  DOI = {10.1038/s41467-024-48267-4},
  number = {1},
  journal = {Nature Communications},
  publisher = {Springer Science and Business Media LLC},
  author = {Montorsi, Lucia and Pitcher, Michael J. and Zhao, Yuan and Dionisi, Chiara and Demonti, Alicia and Tull, Thomas J. and Dhami, Pawan and Ellis, Richard J. and Bishop, Cynthia and Sanderson, Jeremy D. and Jain, Sahil and D’Cruz, David and Gibbons, Deena L. and Winkler, Thomas H. and Bemark, Mats and Ciccarelli, Francesca D. and Spencer, Jo},
  year = {2024},
  month = May
}

Source: NCBI GEO ↗ · License: NCBI GEO policy ↗ · Reprocessed to SpatialData by SpatialData-DB