GOTHiC

GOTHiC identifies statistically significant long-range chromatin interactions from Hi-C data to assign distal regulatory elements to target gene promoters and characterize spatial genome organization.

Key Features:

• Cumulative Binomial Test: Uses a cumulative binomial test to detect interactions with more mapped read pairs than expected by chance.
• Input: Processes mapped paired next-generation sequencing (NGS) reads from Hi-C experiments.
• Output Specification: Outputs lists of significant interactions aggregated at specified genomic bin sizes.
• Promoter Capture Enrichment: Supports analysis of Hi-C libraries enriched by sequence capture for annotated promoters.
• Restriction Fragment Resolution: Operates at restriction fragment resolution to link interacting elements to specific promoters.
• Genome-wide Assignment: Assigns long-range interacting elements to target genes across the genome.

Scientific Applications:

• Regulatory Architecture Mapping: Elucidates the regulatory architecture of mammalian genomes by linking distal regulatory elements to promoters at high resolution.
• Cell-type Interaction Profiling: Applied to embryonic stem cells (ESCs) and fetal liver cells to map promoter-centered interaction networks.
• Histone Mark and TF Association: Reveals that active genes associate with distal sites marked by active histone modifications and transcription factor binding, while inactive genes associate with regions bearing repressive histone marks.
• Coregulated Gene Clustering: Detects nonrandom clustering of coregulated genes within spatial interaction networks, as observed for transcription factor genes in ESCs.

Methodology:

Aggregates mapped paired NGS Hi-C reads into genomic bins at specified sizes and computes interaction significance using a cumulative binomial test to generate a list of significant interactions.