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Fig. 5 | BMC Bioinformatics

Fig. 5

From: Discrete distributional differential expression (D3E) - a tool for gene expression analysis of single-cell RNA-seq data

Fig. 5

Analysis of experimental data. a Histogram showing the fold-changes for the genes which were considered significantly changed (blue) and not changed (gray) for D3E, DESeq2, limma, edgeR and SCDE. b Histograms showing the distribution of parameter values for all cells from [15]. From top to bottom, the panels represent the frequency, the burst size, the inferred rates for the transcriptional bursting model, and the duty cycle. c Examples of two genes, Cdc42bpb in the top panel and Hist1h2bb in the bottom panel, which were identified as DE by D3E. In both cases, the change in mean expression is less than 70 % whereas the variance increases by >10-fold. d Karnaugh table showing the number of genes identified as differentially expressed by D3E, SCDE, limma, edgeR, and DESeq2 for the two datasets collected by Islam et al. [15]. e Scatterplots showing the mean in mESCs, and the fold-change, as well as the fold-change of the mean compared to the change in degradation rate, burst frequency and burst size. In all panels, black dots represent genes which did not change, red dots represent genes which were deemed significant by D3E

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