10x Xenium

Human brain

ffpe-human-brain-cancer-data-with-human-immuno-oncology-profiling-panel-and-custom-add-on-1-standard

silver Interactive viewer H&E glioblastoma multiforme No linked publication

Preview Download via Python Download via CLI Load via sddb

print(sdata)

SpatialData object
├── Images
│     ├── 'he_image': DataTree[cyx] (3, 58584, 38957), (3, 29292, 19478), (3, 14646, 9739), (3, 7323, 4869), (3, 3661, 2434)
│     └── 'morphology_focus': DataTree[cyx] (4, 51043, 53946), (4, 25521, 26973), (4, 12760, 13486), (4, 6380, 6743), (4, 3190, 3371)
├── Labels
│     ├── 'cell_labels': DataTree[yx] (51043, 53946), (25521, 26973), (12760, 13486), (6380, 6743), (3190, 3371)
│     └── 'nucleus_labels': DataTree[yx] (51043, 53946), (25521, 26973), (12760, 13486), (6380, 6743), (3190, 3371)
├── Points
│     └── 'transcripts': DataFrame with shape: (178716169, 11) (3D points)
├── Shapes
│     ├── 'cell_boundaries': GeoDataFrame shape: (816769, 1) (2D shapes)
│     ├── 'cell_circles': GeoDataFrame shape: (816769, 2) (2D shapes)
│     └── 'nucleus_boundaries': GeoDataFrame shape: (818128, 2) (2D shapes)
└── Tables
      └── 'table': AnnData (816769, 480)
with coordinate systems:
    ▸ 'global', with elements:
        he_image (Images), morphology_focus (Images), cell_labels (Labels), nucleus_labels (Labels), transcripts (Points), cell_boundaries (Shapes), cell_circles (Shapes), nucleus_boundaries (Shapes)

Load in Python

import lamindb as ln

db = ln.DB("scverse/spatialdata-db")
artifact = db.Artifact.get("iHSXYBFbeAMN3zxa")   # 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/iHSXYBFbeAMN3zxa

# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid iHSXYBFbeAMN3zxa

Load with the Python client

# pip install git+https://github.com/theislab/spatialdata-db-client
from sddb import Catalog

ds = Catalog().cohort(uids=["iHSXYBFbeAMN3zxa0001"])[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: 10x Xenium
Organism: human
Tissue: brain
Condition: glioblastoma multiforme
Modality: RNA
Observations: 816,769
Transcripts: 178,716,169
Tier: silver
Chemistry: Xenium v1
Resolution: 38,957 × 58,584 px
Size: 28 GB
Sample ID: ffpe-human-brain-cancer-data-with-human-immuno-oncology-profiling-panel-and-custom-add-on-1-standard
License: CC BY 4.0
Published: Apr 15, 2024

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