scdrakex 1.1.5

scGPT embedding extension for scDrake

scDrake's scGPT Extension

This code is fork from scGPT, which is a single-cell GPT model for gene expression data ¹. This extension adds embedding calculation support for the scDrake framework², which is a framework for building and deploying single-cell data analysis. This extension is designed to work with the scDrake framework and trying to provide a set of tools for building and deploying single-cell models.

Installation

Dependencies

• Python >= 3.8
• PyTorch >= 2.3.0

install

$ python -m pip install torch scdrakex

install for development

$ python -m pip install -e .

Pretrained scGPT Model

available at scGPT

Usage

from scdrakex.task.rembedding import r_embed_data

# count_matrix: a sparse matrix of shape (n_cells, n_genes)
# genes: a list of gene symbols
# model_dir: the path to the Pretrained scGPT Model directory
# output: ndarray of shape (n_cells, n_embedding)

embeding = r_embed_data(
    count_matrix = count_matrix,
    genes = genes,
    model_dir = "scGPT_human",
)

References

1. Cui, H., Wang, C., Maan, H. et al. scGPT: toward building a foundation model for single-cell multi-omics using generative AI. Nat Methods 21, 1470–1480 (2024). ↩

2. Kubovčiak, J., Kolář, M., & Novotný, J. (2023). Scdrake: a reproducible and scalable pipeline for scRNA-seq data analysis. Bioinformatics Advances, 3(1). https://doi.org/10.1093/bioadv/vbad089 ↩