cLoops2

cLoops2 performs comprehensive analysis of chromatin interaction data to detect and quantify loops, annotate enhancer–promoter and other regulatory interactions, and compare datasets produced by 3D mapping technologies such as TrAC-looping and Hi-C.

Key Features:

• Peak-calling: Identifies regions with significant chromatin interaction signal from 3D mapping data.
• Loop-calling: Detects pairwise chromatin loops between genomic loci such as enhancers and promoters.
• Differentially Enriched Loops Calling: Tests for variations in loop enrichment across conditions or samples.
• Loops Annotation: Annotates loops with genomic features to support biological interpretation.
• Interaction Resolution Estimation: Estimates the resolution of detected interactions to assess mapping precision.
• Data Similarity Estimation: Quantifies similarity between chromatin interaction datasets.
• Features Quantification: Measures quantitative features of loops and interaction anchors.
• Feature Aggregation Analysis: Aggregates per-feature measurements for integrated analyses.
• Visualization: Produces representations of interaction networks and loop features.

Scientific Applications:

• Gene regulation: Maps enhancer–promoter and other regulatory loops to study mechanisms controlling gene expression.
• Epigenetics: Characterizes chromatin interaction patterns relevant to epigenetic regulation.
• Chromatin architecture: Resolves 3D chromatin organization at high resolution.
• Comparative interaction analysis: Identifies differential loop enrichment and dataset similarities across conditions or samples.

Methodology:

Performs peak-calling, loop-calling, differential loop calling, loop annotation, interaction resolution estimation, data similarity estimation, feature quantification, feature aggregation analysis, and visualization on 3D chromatin interaction data from technologies such as TrAC-looping and Hi-C.