Attention-based deep clustering method for scRNA-seq cell type identification

Single-cell sequencing (scRNA-seq) technology provides higher resolution of cellular differences than bulk RNA sequencing and reveals the heterogeneity in biological research. The analysis of scRNA-seq datasets is premised on the subpopulation assignment. When an appropriate reference is not availab...

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Bibliographic Details
Published in:	PLoS computational biology Vol. 19; no. 11; p. e1011641
Main Authors:	Li, Shenghao, Guo, Hui, Zhang, Simai, Li, Yizhou, Li, Menglong
Format:	Journal Article
Language:	English
Published:	United States Public Library of Science 01.11.2023 Public Library of Science (PLoS)
Subjects:	Algorithms Biological research Breast cancer Cell fusion Cells Clustering Computational linguistics Data visualization Datasets Deep learning Embedding Gene expression Gene sequencing Genetic aspects Graph neural networks Heterogeneity Identification and classification Language processing Methods Natural language interfaces Representations RNA sequencing China
ISSN:	1553-7358, 1553-734X, 1553-7358
Online Access:	Get full text
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