---
language: en
tags:
- single-cell
- rna-seq
- leukemia
- scvi
- bioinformatics
license: mit
---

# LeukoMap scVI Model

This is a trained scVI (single-cell Variational Inference) model for pediatric leukemia single-cell RNA-seq analysis.

## Model Details

- **Model Type**: scVI (single-cell Variational Inference)
- **Training Data**: Caron et al. (2020) pediatric leukemia dataset
- **Architecture**: Variational Autoencoder for single-cell data
- **Latent Dimensions**: Unknown
- **Training Epochs**: Unknown

## Usage

```python
from scvi.model import SCVI
import scanpy as sc

# Load your AnnData object
adata = sc.read_h5ad("your_data.h5ad")

# Load the model
model = SCVI.load("your-username/leukomap-scvi", adata)

# Get latent representation
latent = model.get_latent_representation()
```

## Dataset

This model was trained on the Caron et al. (2020) pediatric leukemia dataset:
- **GEO Accession**: GSE132509
- **Paper**: https://doi.org/10.1038/s41598-020-64929-x
- **Original Analysis**: https://github.com/CBC-UCONN/Single-Cell-Transcriptomics

## Citation

If you use this model, please cite:
- Caron et al. (2020) Single-cell analysis of childhood leukemia reveals a link between developmental states and ribosomal protein expression as a source of intra-individual heterogeneity
- Lopez et al. (2018) Deep generative modeling for single-cell transcriptomics