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A pressing challenge in single-cell transcriptomics is to benchmark experimental protocols and computational methods. A solution is to use computational simulators, but existing simulators cannot simultaneously achieve three goals: preserving genes, capturing gene correlations, and generating any number of cells with varying sequencing depths. To fill this gap, we propose scDesign2, a transparent simulator that achieves all three goals and generates high-fidelity synthetic data for multiple single-cell gene expression count-based technologies. In particular, scDesign2 is advantageous in its transparent use of probabilistic models and its ability to capture gene correlations via copulas.   Supplementary Information  The online version contains supplementary material available at (10.1186/s13059-021-02367-2).

scDesign2: a transparent simulator that generates high-fidelity single-cell gene expression count data with gene correlations captured