Clustering CITE-seq data with a canonical correlation-based deep learning method
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DOI: 10.3389/fgene.2022.977968
Abstract: 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… read more here.
Keywords: seq data; cite seq; clustering cite; correlation ... See more keywords