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Bayesian Gamma-Negative Binomial Modeling of Single-Cell RNA Sequencing Data
[article]
2019
arXiv
pre-print
Single-cell RNA sequencing (scRNA-seq) is a powerful profiling technique at the single-cell resolution. Appropriate analysis of scRNA-seq data can characterize molecular heterogeneity and shed light into the underlying cellular process to better understand development and disease mechanisms. The unique analytic challenge is to appropriately model highly over-dispersed scRNA-seq count data with prevalent dropouts (zero counts), making zero-inflated dimensionality reduction techniques popular for
arXiv:1908.00650v1
fatcat:mj7cwzekizdo3meguy3quyqzuu