BIMSA > Seminar on Bioinformatics scFed: federated learning for cell type classification with scRNA-seq
scFed: federated learning for cell type classification with scRNA-seq
Organizer
Shing Toung Yau
Speaker
Nan Sun
Time
Tuesday, April 30, 2024 2:30 PM - 3:00 PM
Venue
理科楼A-304
Abstract
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.