Abstract
Single-cell ATAC sequencing (scATAC-seq), a state-of-the-art genomic technique designed to map chromatin accessibility at the single-cell level, presents unique analytical challenges due to limited sampling and data sparsity. In this study, we use case studies to highlight the limitations of conventional peak-based methods for processing scATAC-seq data. These methods can fail to capture precise cell-type-specific regulatory signals, producing results that are difficult to interpret and lack portability, thereby compromising the reproducibility of research findings. To overcome these issues, we introduce CREscendo, a method that utilizes Tn5 cleavage frequencies and regulatory annotations to identify differential usage of candidate regulatory elements (CREs) across cell types. Our research advocates for moving away from traditional peak-based quantification in scATAC-seq toward a more robust framework that relies on a standardized reference of annotated CREs, enhancing both the accuracy and reproducibility of genomic studies.