Fig. 4. False discoveries in single-cell DE.

a Schematic illustration of simulation experiments. Single-cell RNA-seq datasets were simulated with varying degrees of heterogeneity between replicates. Replicates were then randomly assigned to either a ‘treatment’ or ‘control’ group, and DE analysis was performed between groups. b Number of DE genes detected in stimulation experiments with varying degrees of heterogeneity between replicates by a representative single-cell DE method, a representative pseudobulk method, and the same pseudobulk method applied to pseudo-replicates. Points and error bars show the mean and standard deviation across ten independent simulations. c Number of DE genes detected by the tests shown in b for genes divided into deciles by the magnitude of the change in variance between biological replicates and pseudo-replicates (∆-variance). d Volcano plots showing DE between T cells from random groups of unstimulated controls drawn from Kang et al.⁵ using a representative pseudobulk method, edgeR-LRT, applied to biological replicates or pseudo-replicates. Discarding information about biological replicates leads to the appearance of false discoveries. e Number of DE genes detected in comparisons of random groups of unstimulated controls from 14 scRNA-seq studies with at least six control samples. f Number of DE genes detected within spinal cord regions from control mice profiled by spatial transcriptomics²⁴ using a representative pseudobulk method, edgeR-LRT (points), or a representative single-cell method, the Wilcoxon rank-sum test (arrowheads). g Mean change in variance between biological replicates and pseudo-replicates for 18 human and 20 mouse scRNA-seq datasets.