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Dataset Card for SpatialRefinery Xenium

What is Xenium von 10x?

A collection of 31 spatial transcriptomic profiles, each linked and aligned to a Whole Slide Image (with pixel size < 0.3 µm/px) and metadata.
Xenium von 10x was assembled from the 10x website encompassing:
- multiple tissues
- 1 species (Homo Sapiens)
- 31 cancer samples

This is a temporary dataset and can have bugs!!!

Instructions for Setting Up HuggingFace Account and Token

1. Create an Account on HuggingFace

Follow the instructions provided on the HuggingFace sign-up page.

2. Accept terms of use of SpatialRefinery

On this page click request access
At this stage, you can already manually inspect the data by navigating in the Files and version

3. Create a Hugging Face Token

Go to Settings: Navigate to your profile settings by clicking on your profile picture in the top right corner and selecting Settings from the dropdown menu.
Access Tokens: In the settings menu, find and click on Access tokens.
Create New Token:
- Click on New token.
- Set the token name (e.g., spatial-refinery).
- Set the access level to Write.
- Click on Create.
Copy Token: After the token is created, copy it to your clipboard. You will need this token for authentication.

4. Logging

Important! Run the following

pip install datasets==2.16.0
pip install huggingface-hub==0.20.0

from huggingface_hub import login
login(token="YOUR HUGGINGFACE TOKEN")

Download the entire Xenium dataset:

import datasets
local_dir='xenium_von_10x' # dataset will be dowloaded to this folder
# Note that the full dataset is around 1TB of data
dataset = datasets.load_dataset(
    'rushin682/xenium_von_10x', 
    cache_dir=local_dir,
    patterns='*'
)

Download a subset of Xenium dataset:

import datasets
local_dir='xenium_von_10x' # dataset will be dowloaded to this folder
ids_to_query = ['HTA12_246_3', 'HTA12_254_8'] # list of ids to query
list_patterns = [f"*{id}[_.]**" for id in ids_to_query]
dataset = datasets.load_dataset(
    'rushin682/xenium_von_10x', 
    cache_dir=local_dir,
    patterns=list_patterns
)

Loading the data with the python library `hest`

Once downloaded, you can then easily iterate through the dataset:

from hest import iter_hest
for st in iter_hest('../xenium_von_10x', id_list=['HTA12_246_3']):
    print(st)

Data organization

For each sample:

wsis/: H&E stained Whole Slide Images in pyramidal Generic TIFF (or pyramidal Generic BigTIFF if >4.1GB)
st/: spatial transcriptomics expressions in a scanpy .h5ad object
metadata/: metadata
biospecimen_figures/: overlay of the WSI with the st spots
thumbnails/: downscaled version of the WSI
tissue_seg/: tissue segmentation masks:
- {id}_vis.jpg: downscaled or full resolution greyscale tissue mask
- {id}_contours.geojson: tissue segmentation contours to load in QuPath
pixel_size_vis/: visualization of the pixel size
cellvit_seg/: cellvit nuclei segmentation

Contact:

Rushin Gindra Helmholtz Munich, Munich ([email protected])

The dataset is distributed under the Attribution-NonCommercial-ShareAlike 4.0 International license (CC BY-NC-SA 4.0 Deed)

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