A Review of Single-Cell RNA-Seq Annotation, Integration, and Cell-Cell Communication.
Cells
; 12(15)2023 07 30.
Article
en En
| MEDLINE
| ID: mdl-37566049
ABSTRACT
Single-cell RNA sequencing (scRNA-seq) has emerged as a powerful tool for investigating cellular biology at an unprecedented resolution, enabling the characterization of cellular heterogeneity, identification of rare but significant cell types, and exploration of cell-cell communications and interactions. Its broad applications span both basic and clinical research domains. In this comprehensive review, we survey the current landscape of scRNA-seq analysis methods and tools, focusing on count modeling, cell-type annotation, data integration, including spatial transcriptomics, and the inference of cell-cell communication. We review the challenges encountered in scRNA-seq analysis, including issues of sparsity or low expression, reliability of cell annotation, and assumptions in data integration, and discuss the potential impact of suboptimal clustering and differential expression analysis tools on downstream analyses, particularly in identifying cell subpopulations. Finally, we discuss recent advancements and future directions for enhancing scRNA-seq analysis. Specifically, we highlight the development of novel tools for annotating single-cell data, integrating and interpreting multimodal datasets covering transcriptomics, epigenomics, and proteomics, and inferring cellular communication networks. By elucidating the latest progress and innovation, we provide a comprehensive overview of the rapidly advancing field of scRNA-seq analysis.
Palabras clave
Texto completo:
1
Bases de datos:
MEDLINE
Asunto principal:
Comunicación Celular
/
Análisis de Expresión Génica de una Sola Célula
Tipo de estudio:
Prognostic_studies
Idioma:
En
Revista:
Cells
Año:
2023
Tipo del documento:
Article
País de afiliación:
Estados Unidos