Mango

Mango analyzes ChIA-PET data to detect genome-wide chromatin looping interactions and quantify their statistical confidence for interpretation of three-dimensional genome organization.

Key Features:

• Complete Data Processing Pipeline: Executes the full set of computational steps required for ChIA-PET data processing and interaction calling.
• Statistical Confidence Estimates: Provides statistical confidence estimates for detected chromatin interactions.
• Bias Correction: Corrects for differential peak enrichment and genomic proximity to reduce bias in interaction detection.
• Validation Against Hi-C Data: Produces interaction calls that show improved agreement with high-resolution Hi-C data and has been compared to ChIA-PET Tool and ChiaSig.
• Discovery of Chromatin Loop Trends: Recovers enrichment of architectural proteins CTCF, RAD21, SMC3, and ZNF143 at interaction anchors and highlights a bias for convergent CTCF motifs.

Scientific Applications:

• Genome architecture mapping: Detection and characterization of chromatin loops to inform three-dimensional genome organization from ChIA-PET datasets.
• Gene regulation studies: Investigation of how chromatin looping influences transcriptional control and regulatory element interactions.
• Cellular processes and disease research: Exploration of loop-mediated regulatory mechanisms relevant to cellular function and disease-associated genomic regulation.

Methodology:

Implements a complete ChIA-PET data processing pipeline that integrates advanced statistical techniques, computes statistical confidence estimates, and applies bias correction algorithms for differential peak enrichment and genomic proximity.