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Human kidney

human-kidney-11-mm-capture-area-ffpe-2-standard

silver Interactive viewer H&E No linked publication
Human kidney preview
print(sdata)
SpatialData object
├── Images
│     ├── 'CytAssist_11mm_FFPE_Human_Kidney_full_image': DataTree[cyx] (3, 31762, 35976), (3, 15881, 17988), (3, 7940, 8994), (3, 3970, 4497), (3, 1985, 2248)
│     ├── 'CytAssist_11mm_FFPE_Human_Kidney_hires_image': DataArray[cyx] (3, 1766, 2000)
│     └── 'CytAssist_11mm_FFPE_Human_Kidney_lowres_image': DataArray[cyx] (3, 530, 600)
├── Shapes
│     └── 'CytAssist_11mm_FFPE_Human_Kidney': GeoDataFrame shape: (5936, 2) (2D shapes)
└── Tables
      └── 'table': AnnData (5936, 18085)
with coordinate systems:
    ▸ 'CytAssist_11mm_FFPE_Human_Kidney', with elements:
        CytAssist_11mm_FFPE_Human_Kidney_full_image (Images), CytAssist_11mm_FFPE_Human_Kidney_hires_image (Images), CytAssist_11mm_FFPE_Human_Kidney_lowres_image (Images), CytAssist_11mm_FFPE_Human_Kidney (Shapes)
    ▸ 'CytAssist_11mm_FFPE_Human_Kidney_downscaled_hires', with elements:
        CytAssist_11mm_FFPE_Human_Kidney_hires_image (Images), CytAssist_11mm_FFPE_Human_Kidney (Shapes)
    ▸ 'CytAssist_11mm_FFPE_Human_Kidney_downscaled_lowres', with elements:
        CytAssist_11mm_FFPE_Human_Kidney_lowres_image (Images), CytAssist_11mm_FFPE_Human_Kidney (Shapes)
Load in Python
import lamindb as ln

db = ln.DB("scverse/spatialdata-db")
artifact = db.Artifact.get("D4I13ftxuL8b4qjP")   # 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/D4I13ftxuL8b4qjP

# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid D4I13ftxuL8b4qjP
Load with the Python client
# pip install git+https://github.com/theislab/spatialdata-db-client
from sddb import Catalog

ds = Catalog().cohort(uids=["D4I13ftxuL8b4qjP0000"])[0]
ds.elements()                 # inspect without downloading
sdata = ds.load(lazy=False)   # copy to the local cache and open

Docs: finding & loading data →

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Metadata

Technology
Visium
Organism
human
Tissue
kidney
Modality
RNA
Observations
5,936
Tier
silver
Chemistry
Visium CytAssist v2
Magnification
40x
Resolution
35,976 × 31,762 px
mpp
0.251 µm/px
Size
2.5 GB
Sample ID
human-kidney-11-mm-capture-area-ffpe-2-standard
License
CC BY 4.0
Published
Feb 14, 2023

Cite this dataset

No linked publication found — please cite the data source: 10x Genomics ↗.

Source: 10x Genomics ↗ · License: CC BY 4.0 ↗ · Reprocessed to SpatialData by SpatialData-DB