skills.rest
ammawla
ammawlaCOMMUNITY
Explore all skills by this author →
Website𝕏@alex_mawlaGitHub

hic-aggregation

Aggregate Hi-C loop calls from multiple experiments into a union chromatin contact catalog.

26|5|Updated Mar 8, 2026
Search Tags:#bioinformatics#data aggregation#hic#chromatin#genome architecture#3d contacts
One-click install
npx skills add https://github.com/ammawla/encode-toolkit --skill hic-aggregation
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: hic-aggregation
Source: https://github.com/ammawla/encode-toolkit/tree/main/plugin/skills/hic-aggregation
Command: npx skills add https://github.com/ammawla/encode-toolkit --skill hic-aggregation

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill enables users to compile comprehensive catalogs of chromatin loops by aggregating Hi-C loop calls across multiple experiments, donors, and labs, providing insights into 3D genome organization.

Core Features & Use Cases

  • Union Catalog Construction: Merge BEDPE loop calls at resolution-aware anchors to produce a comprehensive set of chromatin contacts.
  • Experiment Screening: Identify and select high-quality Hi-C datasets passing ENCODE standards for inclusion.
  • Use Case: A researcher wants to combine loops from pancreas tissue across different labs to identify conserved structural features near the MYC gene.

Quick Start

Use this Skill to aggregate Hi-C loop calls from multiple experiments and generate a union catalog of chromatin contacts in your region of interest.

Frequently Asked Questions about hic-aggregation

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I merge Hi-C loop calls from multiple experiments into a single chromatin contact map?▼

Merge Hi-C loop calls by aggregating BEDPE files from multiple experiments at resolution-aware anchors to produce a comprehensive union catalog of 3D chromatin contacts. This Skill supports harmonizing differing resolutions automatically.

What is the best way to combine Hi-C data across different labs and donors?▼

Combine Hi-C data across labs by screening for high-quality datasets passing ENCODE standards, then merging loop calls into a single catalog. This identifies conserved structural genomic features across diverse experimental sources.

Can I filter low-quality Hi-C datasets before aggregating chromatin loops?▼

Yes, perform experiment screening to identify and select high-quality Hi-C datasets passing ENCODE standards before inclusion. This quality filtering ensures only robust data contributes to your final chromatin contact map.

How do I harmonize different resolutions when aggregating Hi-C loops?▼

Harmonize different Hi-C resolutions by merging BEDPE loop calls at resolution-aware anchors. This ensures structural genomic features and regulatory interactions remain accurately aligned across all aggregated experiments.

Does this approach support annotating structural genomic features in 3D genome architecture studies?▼

Yes, annotating structural genomic features is supported when aggregating Hi-C loop calls. This is suitable for researchers studying 3D genome architecture and identifying conserved regulatory interactions near specific genes.

Related Skills

Explore More Content & Communication Skills→
BIsnake2001BIsnake2001
12

hic-loop-calling

Detect chromatin loops from Hi-C data using cooltools and output BEDPE files.

Community
Advanced
zhouboyu-xrealzhouboyu-xreal

bioinformatics

Accesses bioinformatics tools and reference material for genomic and biological data analysis.

Community
Advanced
TianGzlabTianGzlab
155

genomics-epigenomics

Perform ATAC-seq and ChIP-seq peak calling with MACS3 and motif enrichment using Homer.

Official
Advanced
supportersimulatorsupportersimulator
2

fleet-race

Runs three-machine competitive analysis with cross-rebuttal and chief synthesis.

Community
Advanced