Single-cell omics arena: evaluation of large language models for automatic cell-type annotations on single-cell omics data via RNA-seq bridging.

ABSTRACT: The single-cell sequencing revolution enables simultaneous molecular profiling of various modalities across thousands of individual cells, allowing scientists to investigate the diverse functions of complex tissues. Among all the analysis steps, assigning individual cells to specific types is fundamental for understanding cellular heterogeneity. However, this process is labor-intensive and requires extensive expert knowledge. Recent advances in large language models (LLMs) have demonstrated their ability to automatically extract biological knowledge, such as marker genes, promoting efficient, and automated cell-type annotations. To evaluate the capability of modern LLMs in automating the cell-type identification process, we first introduce an automated cell-type annotation method with comp

SUBMITTER: Liu J 

PROVIDER: S-EPMC12641614 | biostudies-literature | 2025 Nov

REPOSITORIES: biostudies-literature