scTGCL: A Transformer-Based Graph Contrastive Learning Approach for Efficiently Clustering Single-Cell RNA-seq Data
Md. Shoaib Abdullah Khan, Md. Humayun Kabir, Md. Mahir Faisal
scTGCL improves scRNA-seq clustering by using a Transformer-based graph contrastive learning framework that handles dropout and noise, achieving high accuracy and efficiency.
bioRxiv · Mar 31, 2026 · PreprintBioinformatics