Snapshot

Snapshot clusters and visualizes candidate cis-regulatory elements (cCREs) using binarized epigenetic signal patterns to identify regulatory events during cell differentiation.

Key Features:

• Binarized Indexing Strategy: Uses a binarized indexing representation of epigenetic signals to cluster cCREs and reduce data complexity.
• Visualization Capabilities: Produces figures that depict signal and epigenetic state patterns across cCRE clusters and differentiation stages.
• Hierarchical Analysis: Supports analysis across various hierarchies of cell types to focus on lineage- or stage-specific regulatory events.
• Performance on VISION Hematopoiesis Data: Demonstrated on VISION consortium hematopoiesis data with improved interpretation and reproduction of identified cCRE clusters compared with other methods.

Scientific Applications:

• Cell Differentiation Studies: Identification of distinct cCRE clusters associated with gene expression changes during development and differentiation.
• Hematopoiesis Research: Analysis of lineage-specific regulatory events and epigenetic history in hematopoietic differentiation using VISION consortium data.
• Developmental Biology, Stem Cell Research, and Disease Modeling: Elucidation of regulatory networks driven by epigenetic state patterns relevant to development, stem cell biology, and disease contexts.

Methodology:

Clusters cCREs using a binarized indexing strategy applied to epigenetic signals, generates visualizations of signal and epigenetic state patterns across clusters and differentiation stages, and performs hierarchical analysis across cell-type hierarchies.