Characterizing noise structure in single-cell RNA-seq distinguishes genuine from technical stochastic allelic expression
Kim, J.K., Kolodziejczyk, A.A., Illicic, T. et al.
Single-cell RNA-sequencing (scRNA-seq) facilitates identification of new cell types and gene regulatory networks as well as dissection of the kinetics of gene expression and patterns of allele-specific expression. However, to facilitate such analyses, separating biological variability from the high level of technical noise that affects scRNA-seq protocols is vital. Here we describe and validate a generative statistical model that accurately quantifies technical noise with the help of external RNA spike-ins. Applying our approach to investigate stochastic allele-specific expression in individual cells we demonstrate that a large fraction of stochastic allele-specific expression can be explained by technical noise, especially for low and moderately expressed genes: we predict that only 17.8% of stochastic allele-specific expression patterns are attributable to biological noise with the remainder due to technical noise.
Kim, J.K., Kolodziejczyk, A.A., Illicic, T. et al. "Characterizing noise structure in single-cell RNA-seq distinguishes genuine from technical stochastic allelic expression" Nature Communications (2015): 8,687