ScEMAIL: Universal and Source-free Annotation Method for scRNA-seq Data with Novel Cell-type Perception.

ABSTRACT: Current cell-type annotation tools for single-cell RNA sequencing (scRNA-seq) data mainly utilize well-annotated source data to help identify cell types in target data. However, on account of privacy preservation, their requirements for raw source data may not always be satisfied. In this case, achieving feature alignment between source and target data explicitly is impossible. Additionally, these methods are barely able to discover the presence of novel cell types. A subjective threshold is often selected by users to detect novel cells. We propose a universal annotation framework for scRNA-seq data called scEMAIL, which automatically detects novel cell types without accessing source data during adaptation. For new cell-type identification, a novel cell-type perception module is designed w

SUBMITTER: Wan H 

PROVIDER: S-EPMC10025768 | biostudies-literature | 2022 Oct

REPOSITORIES: biostudies-literature