Ploidy inference from single-cell data: application to human and mouse cell atlases

Single-cell RNA-seq and other omics assays are revolutionizing our understanding of biology. Ploidy, which is relevant to numerous biological phenomena, including development, metabolism, and tissue regeneration, has remained elusive in single-cell assays. Here, we developed a statistical method to infer ploidy from single-cell ATAC-seq data. When applied to human and mouse cell atlases, our method facilitated the detection of polyploidy across a range of cell types in a systematic manner. This method enables the integration of ploidy analysis into single-cell studies.