Visium
Human ovary
GSM7090084
bronze Interactive viewer H&E ovarian cancer Provisional
print(sdata)
SpatialData object
├── Images
│ ├── 'GSM7090084_GenolabM_A1-2_hires_image': DataArray[cyx] (3, 2000, 1956)
│ └── 'GSM7090084_GenolabM_A1-2_lowres_image': DataArray[cyx] (3, 600, 587)
├── Shapes
│ └── 'GSM7090084_GenolabM_A1-2': GeoDataFrame shape: (2558, 2) (2D shapes)
└── Tables
└── 'table': AnnData (2558, 17943)
with coordinate systems:
▸ 'GSM7090084_GenolabM_A1-2', with elements:
GSM7090084_GenolabM_A1-2_hires_image (Images), GSM7090084_GenolabM_A1-2_lowres_image (Images), GSM7090084_GenolabM_A1-2 (Shapes)
▸ 'GSM7090084_GenolabM_A1-2_downscaled_hires', with elements:
GSM7090084_GenolabM_A1-2_hires_image (Images), GSM7090084_GenolabM_A1-2 (Shapes)
▸ 'GSM7090084_GenolabM_A1-2_downscaled_lowres', with elements:
GSM7090084_GenolabM_A1-2_lowres_image (Images), GSM7090084_GenolabM_A1-2 (Shapes) Load in Python
import lamindb as ln
db = ln.DB("scverse/spatialdata-db")
artifact = db.Artifact.get("h3m59d8yfATAme0K") # 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/h3m59d8yfATAme0K
# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid h3m59d8yfATAme0K Load with the Python client
# pip install git+https://github.com/theislab/spatialdata-db-client
from sddb import Catalog
ds = Catalog().cohort(uids=["h3m59d8yfATAme0K0000"])[0]
ds.elements() # inspect without downloading
sdata = ds.load(lazy=False) # copy to the local cache and openPart of collection
Comparison of the Illumina NextSeq 2000 and GeneMind Genolab M sequencing platforms for spatial transcriptomics→ 6 datasets · replicates
Metadata
- Technology
- Visium
- Organism
- human
- Tissue
- ovary
- Condition
- ovarian cancer
- Modality
- RNA
- Observations
- 2,558
- Tier
- bronze
- Chemistry
- Visium v1
- Resolution
- 1,956 × 2,000 px
- mpp
- 3.388 µm/px
- Size
- 23 MB
- Sample ID
- GSM7090084
- License
- unknown
- Published
- Mar 13, 2023
Cite this dataset
No linked publication found — please cite the data source: NCBI GEO ↗.
Source: NCBI GEO ↗ · Reprocessed to SpatialData by SpatialData-DB