ScBOL: a universal cell type identification framework for single-cell and spatial transcriptomics data.

ABSTRACT:

Motivation

Over the past decade, single-cell transcriptomic technologies have experienced remarkable advancements, enabling the simultaneous profiling of gene expressions across thousands of individual cells. Cell type identification plays an essential role in exploring tissue heterogeneity and characterizing cell state differences. With more and more well-annotated reference data becoming available, massive automatic identification methods have sprung up to simplify the annotation process on unlabeled target data by transferring the cell type knowledge. However, in practice, the target data often include some novel cell types that are not in the reference data. Most existing works usually classify these private cells as one generic 'unassigned' group and learn the features of know

SUBMITTER: Zhai Y 

PROVIDER: S-EPMC11056022 | biostudies-literature | 2024 Mar

REPOSITORIES: biostudies-literature