Cell-type annotation with accurate unseen cell-type identification using multiple references.

ABSTRACT: The recent advances in single-cell RNA sequencing (scRNA-seq) techniques have stimulated efforts to identify and characterize the cellular composition of complex tissues. With the advent of various sequencing techniques, automated cell-type annotation using a well-annotated scRNA-seq reference becomes popular. But it relies on the diversity of cell types in the reference, which may not capture all the cell types present in the query data of interest. There are generally unseen cell types in the query data of interest because most data atlases are obtained for different purposes and techniques. Identifying previously unseen cell types is essential for improving annotation accuracy and uncovering novel biological discoveries. To address this challenge, we propose mtANN (multiple-reference-ba

SUBMITTER: Xiong YX 

PROVIDER: S-EPMC10335708 | biostudies-literature | 2023 Jun

REPOSITORIES: biostudies-literature