Visium
Human infrapatellar fat pad
GSM8016283
silver Interactive viewer H&E osteoarthritis, knee ✓ Verified publication
print(sdata)
SpatialData object
├── Images
│ ├── 'GSM8016283_KneeOA_ObeseBMI14_full_image': DataTree[cyx] (3, 3000, 3000), (3, 1500, 1500), (3, 750, 750), (3, 375, 375), (3, 187, 187)
│ ├── 'GSM8016283_KneeOA_ObeseBMI14_hires_image': DataArray[cyx] (3, 2000, 1510)
│ └── 'GSM8016283_KneeOA_ObeseBMI14_lowres_image': DataArray[cyx] (3, 600, 453)
├── Shapes
│ └── 'GSM8016283_KneeOA_ObeseBMI14': GeoDataFrame shape: (3034, 2) (2D shapes)
└── Tables
└── 'table': AnnData (3034, 18085)
with coordinate systems:
▸ 'GSM8016283_KneeOA_ObeseBMI14', with elements:
GSM8016283_KneeOA_ObeseBMI14_full_image (Images), GSM8016283_KneeOA_ObeseBMI14_hires_image (Images), GSM8016283_KneeOA_ObeseBMI14_lowres_image (Images), GSM8016283_KneeOA_ObeseBMI14 (Shapes)
▸ 'GSM8016283_KneeOA_ObeseBMI14_downscaled_hires', with elements:
GSM8016283_KneeOA_ObeseBMI14_hires_image (Images), GSM8016283_KneeOA_ObeseBMI14 (Shapes)
▸ 'GSM8016283_KneeOA_ObeseBMI14_downscaled_lowres', with elements:
GSM8016283_KneeOA_ObeseBMI14_lowres_image (Images), GSM8016283_KneeOA_ObeseBMI14 (Shapes) Load in Python
import lamindb as ln
db = ln.DB("scverse/spatialdata-db")
artifact = db.Artifact.get("iFa4spQHpAQW5irr") # 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/iFa4spQHpAQW5irr
# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid iFa4spQHpAQW5irr Load with the Python client
# pip install git+https://github.com/theislab/spatialdata-db-client
from sddb import Catalog
ds = Catalog().cohort(uids=["iFa4spQHpAQW5irr0000"])[0]
ds.elements() # inspect without downloading
sdata = ds.load(lazy=False) # copy to the local cache and openPart of collection
Cell and Transcriptomic Diversity of Infrapatellar Fat Pad during Knee Osteoarthritis [Spatial Transcriptomics]→ 12 datasets · other
Metadata
- Technology
- Visium
- Organism
- human
- Tissue
- infrapatellar fat pad
- Condition
- osteoarthritis, knee
- Modality
- RNA
- Observations
- 3,034
- Tier
- silver
- Chemistry
- Visium CytAssist v2
- Resolution
- 1,510 × 2,000 px
- mpp
- 4.037 µm/px
- Size
- 34 MB
- Sample ID
- GSM8016283
- License
- NCBI GEO policy
- Published
- Oct 7, 2024
Cite this dataset
doi.org/10.1136/ard-2024-225928 ↗ BibTeX
@article{Peters_2025,
title = {Cell and transcriptomic diversity of infrapatellar fat pad during knee osteoarthritis},
volume = {84},
ISSN = {0003-4967},
url = {http://dx.doi.org/10.1136/ard-2024-225928},
DOI = {10.1136/ard-2024-225928},
number = {2},
journal = {Annals of the Rheumatic Diseases},
publisher = {Elsevier BV},
author = {Peters, Hayley and Potla, Pratibha and Rockel, Jason S. and Tockovska, Teodora and Pastrello, Chiara and Jurisica, Igor and Delos Santos, Keemo and Vohra, Shabana and Fine, Noah and Lively, Starlee and Perry, Kim and Looby, Nikita and Li, Sheng Han and Chandran, Vinod and Hueniken, Katrina and Kaur, Paramvir and Perruccio, Anthony V. and Mahomed, Nizar N. and Rampersaud, Raja and Syed, Khalid and Gracey, Eric and Krawetz, Roman and Buechler, Matthew B. and Gandhi, Rajiv and Kapoor, Mohit},
year = {2025},
month = Feb,
pages = {351–367}
}Source: NCBI GEO ↗ · License: NCBI GEO policy ↗ · Reprocessed to SpatialData by SpatialData-DB