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A Hybrid Deep Clustering Approach for Robust Cell Type Profiling Using Single-cell RNA-seq Data: Supplementary Figures and Tables
[article]
2019
bioRxiv
pre-print
Single-cell RNA sequencing (scRNA-seq) is a recent technology that enables fine-grained discovery of cellular subtypes and specific cell states. It routinely uses machine learning methods, such as feature learning, clustering, and classification, to assist in uncovering novel information from scRNA-seq data. However, current methods are not well suited to deal with the substantial amounts of noise that is created by the experiments or the variation that occurs due to differences in the cells of
doi:10.1101/511626
fatcat:fp2vlwr63jdsdfv3jdfjqitequ