FedscGen: privacy-preserving federated batch effect correction of single-cell RNA sequencing data

FedscGen: privacy-preserving federated batch effect correction of single-cell RNA sequencing data

Abstract Single-cell RNA-seq data from clinical samples often suffer from batch effects, but data sharing is limited due to genomic privacy concerns. We present FedscGen, a privacy-preserving communication-efficient federated method built upon the scGen model, enhanced with secure multiparty computa...

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Bibliographic Details
Main Authors: Mohammad Bakhtiari, Stefan Bonn, Fabian Theis, Olga Zolotareva, Jan Baumbach
Format: Article
Language:English
Published: BMC 2025-07-01
Series:Genome Biology
Subjects:
Batch effect correction
Federated learning
Privacy-preserving computation
Single-cell RNA-seq
Secure multiparty computation (SMPC)
Generative models
Online Access:https://doi.org/10.1186/s13059-025-03684-6
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