A marker gene-based method for identifying the cell-type of origin from single-cell RNA sequencing data.

ABSTRACT: Single-cell RNA sequencing (scRNA-seq) experiments provide opportunities to peer into complex tissues at single-cell resolution. However, insightful biological interpretation of scRNA-seq data relies upon precise identification of cell types. The ability to identify the origin of a cell quickly and accurately will greatly improve downstream analyses. We present Sargent, a transformation-free, cluster-free, single-cell annotation algorithm for rapidly identifying the cell types of origin based on cell type-specific markers. We demonstrate Sargent's high accuracy by annotating simulated datasets. Further, we compare Sargent performance against expert-annotated scRNA-seq data from human organs including PBMC, heart, kidney, and lung. We demonstrate that Sargent retains both the flexibility an

SUBMITTER: Nouri N 

PROVIDER: S-EPMC10326446 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature