metadata
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
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