Clustering CITE-seq data with a canonical correlation-based deep learning method

Single-cell multiomics sequencing techniques have rapidly developed in the past few years. Among these techniques, single-cell cellular indexing of transcriptomes and epitopes (CITE-seq) allows simultaneous quantification of gene expression and surface proteins. Clustering CITE-seq data have the gre...

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Detalles Bibliográficos
Autores principales: Yuan, Musu, Chen, Liang, Deng, Minghua
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Genetics
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9441595/
https://www.ncbi.nlm.nih.gov/pubmed/36072672
http://dx.doi.org/10.3389/fgene.2022.977968

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9441595/
https://www.ncbi.nlm.nih.gov/pubmed/36072672
http://dx.doi.org/10.3389/fgene.2022.977968

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