scNucMap

scNucMap leverages the unique characteristics of single-cell micrococcal nuclease sequencing (scMNase-seq) data to map the landscapes of candidate nucleosome-free regions (NFRs) and illuminate the relationship between regulatory networks and nucleosome positioning at single-cell resolution.

Key Features:

• Cell Clustering: Demonstrates 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.
• Transcription Factor Identification: Identifies significant transcription factors associated with nucleosome depletion at cis-regulatory elements (CREs) at both single-cell and cell-cluster levels.
• Cell-Type Annotation: Facilitates cell-type annotation through regulatory network inference based on nucleosome depletion patterns.
• Cross-Modality Versatility: Enriches standard analyses of scATAC-seq data with complementary insights into nucleosome architecture.

Scientific Applications:

• Chromatin Dynamics Analysis: Decodes scMNase-seq data to generate precise and context-dependent insights into chromatin dynamics and gene regulation.
• Regulatory Network Inference: Infers gene regulatory networks by mapping nucleosome depletion around cis-regulatory elements (CREs) associated with CRE activity.
• Multimodal Epigenetic Studies: Supports multimodal studies by analyzing both scMNase-seq and scATAC-seq data to reveal nucleosome architecture and regulatory relationships.
• Cellular Heterogeneity Characterization: Captures cellular heterogeneity in epigenetic regulation through simultaneous measurement of nucleosome positioning and chromatin accessibility at single-cell resolution.

Methodology:

scNucMap is specifically designed to decode scMNase-seq data by leveraging its unique characteristics to map candidate nucleosome-free regions.