scNucMap: mapping the nucleosome landscapes at single-cell resolution.

Abstract

Nucleosome depletion around cis-regulatory elements (CREs) is associated with CRE activity and implies the underlying gene regulatory network. Single-cell micrococcal nuclease sequencing (scMNase-seq) enables the simultaneous measurement of nucleosome positioning and chromatin accessibility at single-cell resolution, thereby capturing cellular heterogeneity in epigenetic regulation. However, there is currently no computational tool specifically designed to decode scMNase-seq data, impeding the generation of more precise and context-dependent insights into chromatin dynamics and gene regulation. Here, we present scNucMap, a tool designed to leverage the unique characteristics of scMNase-seq data to map the landscapes of candidate nucleosome-free regions (NFRs). scNucMap demonstrated superior performance and robustness in cell clustering on scMNase-seq data compared to Signac and chromVAR across diverse sample compositions and data complexities, achieving higher overall accuracy and Kappa coefficients. Additionally, scNucMap identified significant TFs associated with nucleosome depletion at CREs at both single-cell and cell-cluster levels, thereby facilitating cell-type annotation and regulatory network inference. When applied to scATAC-seq data, scNucMap enriched standard analyses with complementary insights into nucleosome architecture, underscoring its cross‑modality versatility. Overall, scNucMap exhibits both high reliability and adaptability, making it an effective tool for analyzing scMNase-seq data and supporting multimodal studies, thereby illuminating the intricate relationship between regulatory networks and nucleosome positioning at single-cell resolution. scNucMap is available at https://github.com/qianming-bioinfo/scNucMap.