scVGATAE: A Variational Graph Attentional Autoencoder Model for Clustering Single-Cell RNA-seq Data
scVGATAE: A Variational Graph Attentional Autoencoder Model for Clustering Single-Cell RNA-seq Data
About this item
Full title
Author / Creator
Liu, Lijun , Wu, Xiaoyang , Yu, Jun , Zhang, Yuduo , Niu, Kaixing and Yu, Anli
Publisher
Switzerland: MDPI AG
Journal title
Language
English
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Publication information
Publisher
Switzerland: MDPI AG
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Scope and Contents
Contents
Single-cell RNA sequencing (scRNA-seq) is now a successful technology for identifying cell heterogeneity, revealing new cell subpopulations, and predicting developmental trajectories. A crucial component in scRNA-seq is the precise identification of cell subsets. Although many unsupervised clustering methods have been developed for clustering cell...
Alternative Titles
Full title
scVGATAE: A Variational Graph Attentional Autoencoder Model for Clustering Single-Cell RNA-seq Data
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Author / Creator
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Record Identifier
TN_cdi_doaj_primary_oai_doaj_org_article_6e18ca828f904b919c419f513f2be47b
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_6e18ca828f904b919c419f513f2be47b
Other Identifiers
ISSN
2079-7737
E-ISSN
2079-7737
DOI
10.3390/biology13090713
