scFed: federated learning for cell type classification with scRNA-seq
组织者
演讲者
时间
2024年04月30日 14:30 至 15:00
地点
理科楼A-304
摘要
The advent of single-cell RNA sequencing (scRNA-seq) has revolutionized our understanding of cellular heterogeneity and complexity in biological tissues. However, the nature of large, sparse scRNA-seq datasets and privacy regulations present challenges for efficient cell identification. Federated learning provides a solution, allowing efficient and private data use. Here, scFed was introduced, and it is a unified federated learning framework that allows for benchmarking of four classification algorithms without violating data privacy, including single-cell-specific and general-purpose classifiers.