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# Region2Vec ChIP-atlas hg38
## Model Details
### Model Description
This is a region2vec model trained on the hg38 ChIP-atlas ATAC-seq data
- **Developed by:** Nathan LeRoy
- **Model type:** Region2Vec
- **Language(s) (NLP):** hg38
### Model Sources [optional]
<!-- Provide the basic links for the model. -->
- **Repository:** https://github.com/databio/geniml
- **Paper [optional]:** https://academic.oup.com/bioinformatics/article/37/23/4299/6307720
## Uses
This model can be used to generate embeddings of genomic regions or region sets. Once embeddings are obtained, they can be directly used for clustering, classification, or search and retrieval tasks. It is limited to hg38. It is not recommended to use this model for data outside ATAC-seq.
## How to Get Started with the Model
You can download and start encoding new genomic region data using the following code:
```python
from geniml.region2vec.experimental import Region2VecExModel
model = Region2VecExModel("databio/r2v-ChIP-atlas-v2")
embeddings = model.encode("path/to/file.bed")
print(embeddings.shape)
```
[More Information Needed]
## Training Details
### Training Data
TODO
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