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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.
Article in Zh | WPRIM | ID: wpr-921840
Responsible library: WPRO
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.
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Full text: 1 Index: WPRIM Main subject: Base Sequence / Gene Expression Regulation / Sequence Analysis, RNA / Gene Expression Profiling / Single-Cell Analysis Limits: Humans Language: Zh Journal: Journal of Biomedical Engineering Year: 2021 Type: Article
Full text: 1 Index: WPRIM Main subject: Base Sequence / Gene Expression Regulation / Sequence Analysis, RNA / Gene Expression Profiling / Single-Cell Analysis Limits: Humans Language: Zh Journal: Journal of Biomedical Engineering Year: 2021 Type: Article