CellPLM
A pre-trained language model for single-cell RNA sequencing data that encodes cell-cell relations and accelerates inference for downstream tasks.
What is CellPLM?
CellPLM is a pre-trained language model specifically designed for single-cell RNA sequencing data analysis. It encodes cell-cell relations to create more accurate biological representations, solving the limitation of models that treat cells in isolation. The model achieves state-of-the-art performance on downstream tasks like cell-type annotation with significantly faster inference speeds.
Bioinformaticians, computational biologists, and researchers working with single-cell RNA sequencing data who need accurate and efficient tools for cell-type annotation and other downstream analysis tasks.
Developers choose CellPLM because it uniquely models cell-cell relationships rather than treating cells independently, leading to more biologically meaningful representations. It offers both superior accuracy compared to alternatives like scGPT and Geneformer, and 100x faster inference speeds, making it practical for large-scale analyses.
Overview
Official repo for CellPLM: Pre-training of Cell Language Model Beyond Single Cells.
Use Cases
Best For
- Cell-type annotation across diverse tissue datasets
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