scBASE: A Bayesian mixture model for the analysis of allelic expression in single cells
Choi, K.; Raghupathy, N.; Churchill, G. A.
Show abstract
Allele-specific expression (ASE) at single-cell resolution is a critical tool for understanding the stochastic and dynamic features of gene expression. However, low read coverage and high biological variability present challenges for analyzing ASE. We propose a new method for ASE analysis from single cell RNA-Seq data that accurately classifies allelic expression states and improves estimation of allelic proportions by pooling information across cells.
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