scelmo-celllines-gpt-3.5

scELMo Cellline Embeddings

This directory contains cellline embeddings generated using scELMo methodology.

Source

These embeddings are converted from the official scELMo repository: https://github.com/HelloWorldLTY/scELMo

Model Information

• Model: gpt-3.5-turbo
• Embedding Dimension: 1536
• Type: cellline
• Aggregation Mode: wa
• API Model: text-embedding-ada-002

Files

• gene_embeddings.pkl: Gene embeddings dictionary in PerturbLab format
  • Format: {'embeddings': {gene_name: embedding_array}, 'gene_list': [gene_names]}
• config.json: Model configuration

Usage

from perturblab.model.scelmo import scELMoModel

# Load model
model = scELMoModel.from_pretrained('scelmo-celllines-gpt-3.5')

# Use embeddings
embeddings = model.predict_embeddings(adata, aggregation_mode='wa')

Citation

If you use these embeddings, please cite the original scELMo paper:

@article{liu2023scelmo,
  title={scELMo: Embeddings from Language Models are Good Learners for Single-cell Data Analysis},
  author={Liu, Tianyu and Chen, Tianqi and Zheng, Wangjie and Luo, Xiao and Zhao, Hongyu},
  journal={Cell Patterns (in press)},
  pages={2023--12},
  year={2025},
  publisher={Cell Press}
}