Abstract <p>Single-cell assay for transposase-accessible chromatin sequencing (scATAC-seq) allows for deciphering the epigenetic landscape at single-cell resolution. The inaccuracies in annotations and the scarcity of available real datasets hinder the unbiased and comprehensive evaluation of computational methods designed for scATAC-seq data analysis, which underscores the importance of scATAC-seq data simulation methods. Existing scATAC-seq data simulation methods impose strict requirements on the prior distribution of the data and fail to generate simulated data with a consistent manifold structure aligned with real data. In this study, we propose DiTSim, a scATAC-seq data simulation method based on diffusion transformers. DiTSim efficiently fits the global distribution of real scATAC-seq datasets and stably synthesizes samples with known cell type annotations for assessing scATAC-seq data analysis pipelines. Through comprehensive experiments on multiple datasets, DiTSim has demonstrated its outstanding performance in achieving consistency with real data and robustness to datasets with diverse characteristics. Moreover, extensive enrichment analysis demonstrates that DiTSim has the capability to imbue simulated data with biological significance, a critical aspect often overlooked in prior studies.</p> Graphical Abstract <p></p>