scGPT

scGPT is a foundation model designed for single-cell multi-omics data analysis using generative AI. It leverages transformer architecture pretrained on millions of single-cell profiles to enable a wide range of downstream biological tasks, advancing computational biology by providing a powerful, unified model for cellular data.

Key Features

• Pretrained Model Zoo — Offers multiple organ-specific and whole-human models trained on millions of cells for various applications.
• Zero-Shot Applications — Supports tasks like cell embedding and reference mapping without task-specific training.
• Reference Mapping — Enables fast similarity search across millions of cells using efficient indexing with faiss.
• Multi-Task Fine-Tuning — Can be adapted for scRNA-seq integration, cell type annotation, perturbation prediction, and GRN inference.
• Online Tools — Provides accessible web applications for reference mapping, cell annotation, and GRN inference via cloud GPUs.

Philosophy

scGPT aims to build a foundational AI model for single-cell biology, democratizing access to advanced computational methods and accelerating discoveries in multi-omics research through open-source collaboration.