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Visium

Human kidney

Mapping single cell transcriptomes in kidney cancer (6800STDY12499506)

bronze Interactive viewer H&E renal cell carcinoma Provisional
Visium
print(sdata) 
SpatialData object
├── Images
│     ├── 'spaceranger130_count_44317_6800STDY12499506_GRCh38-2020-A_hires': DataArray[cyx] (3, 2000, 1909)
│     └── 'spaceranger130_count_44317_6800STDY12499506_GRCh38-2020-A_lowres': DataArray[cyx] (3, 600, 573)
├── Shapes
│     └── 'locations': GeoDataFrame shape: (2029, 2) (2D shapes)
└── Tables
      └── 'table': AnnData (2029, 36601)
with coordinate systems:
    ▸ 'global', with elements:
        spaceranger130_count_44317_6800STDY12499506_GRCh38-2020-A_hires (Images), spaceranger130_count_44317_6800STDY12499506_GRCh38-2020-A_lowres (Images), locations (Shapes)
    ▸ 'spaceranger130_count_44317_6800STDY12499506_GRCh38-2020-A_hires', with elements:
        spaceranger130_count_44317_6800STDY12499506_GRCh38-2020-A_hires (Images), locations (Shapes)
    ▸ 'spaceranger130_count_44317_6800STDY12499506_GRCh38-2020-A_lowres', with elements:
        spaceranger130_count_44317_6800STDY12499506_GRCh38-2020-A_lowres (Images), locations (Shapes)
Install (Python 3.12+) Docs →
Python · sddb client 
from sddb import Catalog

ds = Catalog().dataset("wOJ2llk9o1ohbcF70000")
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("wOJ2llk9o1ohbcF7")   # 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 wOJ2llk9o1ohbcF70000 --dest data/

# or lamin: cache the dataset and print its local path
lamin load https://lamin.ai/scverse/spatialdata-db/artifact/wOJ2llk9o1ohbcF7

# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid wOJ2llk9o1ohbcF7
Install (Python 3.12+) Docs →

License: CC BY 4.0

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16 datasets · publication

Metadata

Technology
Visium
Vendor
10x Genomics
Organism
human
Tissue
kidney
Condition
renal cell carcinoma
Modality
RNA
Observations (spots)
2,029
Tier
bronze
Chemistry
Visium v1
Resolution
1,909 × 2,000 px
mpp
4.928 µm/px
Size
35.6 MB
Sample ID
g67bkbnhhg:6800STDY12499506
License
CC BY 4.0
Published
Oct 10, 2022

Cite this dataset

doi.org/10.17632/g67bkbnhhg.1 ↗
BibTeX 
@article{mendeley:g67bkbnhhg,
  doi = {10.17632/g67bkbnhhg.1},
  title = {Mapping single cell transcriptomes in kidney cancer (6800STDY12499413)},
  year = {2022}
}

Source: data.mendeley.com ↗ · License: CC BY 4.0 ↗ · Reprocessed to SpatialData by SpatialData-DB