A review on integration methods for single-cell data / 生物医学工程学杂志
Journal of Biomedical Engineering
;
(6): 1010-1017, 2021.
Artigo
em Chinês
| WPRIM
| ID: wpr-921840
ABSTRACT
The emergence of single-cell sequencing technology enables people to observe cells with unprecedented precision. However, it is difficult to capture the information on all cells and genes in one single-cell RNA sequencing (scRNA-seq) experiment. Single-cell data of a single modality cannot explain cell state and system changes in detail. The integrative analysis of single-cell data aims to address these two types of problems. Integrating multiple scRNA-seq data can collect complete cell types and provide a powerful boost for the construction of cell atlases. Integrating single-cell multimodal data can be used to study the causal relationship and gene regulation mechanism across modalities. The development and application of data integration methods helps fully explore the richness and relevance of single-cell data and discover meaningful biological changes. Based on this, this article reviews the basic principles, methods and applications of multiple scRNA-seq data integration and single-cell multimodal data integration. Moreover, the advantages and disadvantages of existing methods are discussed. Finally, the future development is prospected.
Texto completo:
DisponíveL
Índice:
WPRIM (Pacífico Ocidental)
Assunto principal:
Sequência de Bases
/
Regulação da Expressão Gênica
/
Análise de Sequência de RNA
/
Perfilação da Expressão Gênica
/
Análise de Célula Única
Limite:
Humanos
Idioma:
Chinês
Revista:
Journal of Biomedical Engineering
Ano de publicação:
2021
Tipo de documento:
Artigo
Similares
MEDLINE
...
LILACS
LIS