SwarmMAP: Swarm Learning for Decentralized Cell Type Annotation in Single Cell Sequencing Data.

ABSTRACT: Rapid technological advancements have made it possible to generate single-cell data at a large scale. Several laboratories around the world can now generate single-cell transcriptomic data from different tissues. Unsupervised clustering, followed by annotation of the cell type of the identified clusters, is a crucial step in single-cell analyses. However, there is no consensus on the marker genes to use for annotation, and cell-type annotation is currently mostly done by manual inspection of marker genes, which is irreproducible, and poorly scalable. Additionally, patient-privacy is also a critical issue with human datasets. There is a critical need to standardize and automate cell-type annotation across datasets in a privacy-preserving manner. Here, we developed SwarmMAP that uses Swarm L

SUBMITTER: Saldanha OL 

PROVIDER: S-EPMC11761033 | biostudies-literature | 2025 Jan

REPOSITORIES: biostudies-literature