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Fig. 5 | Genome Biology

Fig. 5

From: Normalization and variance stabilization of single-cell RNA-seq data using regularized negative binomial regression

Fig. 5

The regularized NB model is an attractive middle ground between two extremes. a For four genes, we show the relationship between cell sequencing depth and molecular counts. White points show the observed data. Background color represents the Pearson residual magnitude under three error models. For MALAT1 (does not vary across cell types), the Poisson error model does not account for overdispersion and incorrectly infers significant residual variation (biological heterogeneity). For S100A9 (a CD14+ monocyte marker) and CD74 (expressed in antigen-presenting cells), the non-regularized NB model overfits the data and collapses biological heterogeneity. For PPBP (a Megakaryocyte marker), both non-regularized models wrongly fit a negative slope. b Boxplot of Pearson residuals for models shown in a. X-axis range shown is limited to [ − 8, 25] for visual clarity

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