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AAE-SC: A scRNA-seq Clustering Framework based on Adversarial Autoencoder
2020
IEEE Access
Single-cell RNA sequencing (scRNA-seq) provides the expression profiles of individual cells, and it is expected to provide higher cellular differential resolution than traditional bulk RNA sequencing. In scRNA-seq analysis, clustering is crucial for identifying cell types, and can be potentially exploited to understand high-level biological processes. Recently, autoencoder has been successfully applied in scRNAseq clustering problem and achieved promising results. Most existing works focus on
doi:10.1109/access.2020.3027481
fatcat:agl6cbzjdvborji5dr3spxrfn4