---
viewer: false

license: cc-by-nc-sa-4.0
language:
- en
tags:
- spatial-transcriptomics
- histology
- pathology
- benchmark
task_categories:
- image-classification
- feature-extraction
- image-segmentation
size_categories:
- 100B<n<1T

extra_gated_prompt: >-
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  - Any commercial use, sale, or other monetization of the dataset and its derivatives, which include models trained on outputs from the datasets, is prohibited and requires prior approval. 
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  - This dataset is provided “as-is” without warranties of any kind, express or implied. This dataset has not been reviewed, certified, or approved by any regulatory body, including but not limited to the FDA (U.S.), EMA (Europe), MHRA (UK), or other medical device authorities. Any application of this dataset in healthcare or biomedical settings must comply with relevant regulatory requirements and undergo independent validation. Users assume full responsibility for how they use this dataset and any resulting consequences. The authors, contributors, and distributors disclaim any liability for damages, direct or indirect, resulting from dataset use. Users are responsible for ensuring compliance with data protection regulations (e.g., GDPR, HIPAA) when using it in research that involves patient data.
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      - Models Benchmarking
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---
# Dataset Card for SpatialRefinery Xenium

<!-- <img src="fig1a.jpg" alt="Description" style="width: 38%;" align="right"/> -->


#### What is Xenium von 10x?

- A collection of <b>31</b> 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](https://huggingface.co/join).

### 2. Accept terms of use of SpatialRefinery

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

### 3. Create a Hugging Face Token

1. **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.

2. **Access Tokens:** In the settings menu, find and click on `Access tokens`.

3. **Create New Token:**
   - Click on `New token`.
   - Set the token name (e.g., `spatial-refinery`).
   - Set the access level to `Write`.
   - Click on `Create`.

4. **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:
```python
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:
```python
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:
```python
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:
- <b>Rushin Gindra</b> Helmholtz Munich, Munich (`rushin.gindra@helmholtz-munich.de`)

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