multi-omics-integration

Integrate ENCODE transcriptomics, chromatin accessibility, histone modifications, and conformation data into regulatory models.

26|5|Updated Mar 8, 2026

Search Tags:#integration #genomics #regulatory #multi-omics #chromatin #epigenomics #ENCODE

Ready to run

npx skills add https://github.com/ammawla/encode-toolkit --skill multi-omics-integration

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: multi-omics-integration
Source: https://github.com/ammawla/encode-toolkit/tree/main/plugin/skills/multi-omics-integration
Command: npx skills add https://github.com/ammawla/encode-toolkit --skill multi-omics-integration

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires ChromHMM, bedtools, HiC-Pro, GREAT, Enformer, scVI, Seurat, LIGER, MOFA+, and includes scripts (resource) and references (resource) and assets (resource) components.

What problem does it solve?

Integrates diverse ENCODE genomic datasets to build a unified view of gene regulation and chromatin dynamics.

Core Features & Use Cases

Data Integration: Combines RNA-seq, ATAC-seq, histone modifications, TF ChIP-seq, and 3D genome data for tissue-specific regulatory landscapes.
Analytical Frameworks: Applies chromatin state segmentation, enhancer-gene linking, and regulatory network inference.
Use Case: A researcher studying pancreatic islet cells integrates accessible chromatin, histone marks, gene expression, and Hi-C data to elucidate cell type-specific regulatory circuits.

Quick Start

Align and analyze ENCODE datasets across multiple modalities to identify active enhancers and their target genes in your tissue of interest.

Frequently Asked Questions about multi-omics-integration

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

FAQPage Schema

How do I integrate multiple ENCODE data types like RNA-seq and ATAC-seq for regulatory analysis?▼

To integrate multiple ENCODE data types, you combine transcriptomics, chromatin accessibility, histone modifications, and chromosome conformation into unified regulatory models. The pipeline handles quality control, cross-data validation, and computational linking of regulatory elements to gene activity.

How does multi-omics integration connect active enhancers to target genes in specific tissues?▼

Multi-omics integration connects active enhancers to target genes by applying chromatin state segmentation and enhancer-gene linking. This constructs tissue-specific regulatory landscapes by cross-validating datasets like ATAC-seq, Hi-C, and RNA-seq.

Can I use Seurat and scVI for single-cell multi-omics integration with ENCODE datasets?▼

Yes, Seurat and scVI are supported dependencies for single-cell multi-omics integration. They work alongside LIGER and MOFA+ to analyze and align diverse genomic assay platforms across cross-data validation steps.

What's the best way to analyze chromosome conformation and chromatin accessibility together?▼

The best way to analyze chromosome conformation and chromatin accessibility together is layering Hi-C and ATAC-seq data using tools like ChromHMM and bedtools. This constructs integrated regulatory models to decipher complex gene regulation mechanisms.

Does this multi-omics pipeline support regulatory network inference for tissue-specific cell types?▼

Yes, the multi-omics pipeline supports regulatory network inference for tissue-specific cell types. It combines histone marks, gene expression, and accessible chromatin to elucidate cell type-specific regulatory circuits.

What are the limitations of integrating ENCODE data layers across different assay platforms?▼

A key limitation of integrating ENCODE data layers is deciphering complex gene regulation across different data types and assay platforms. The pipeline addresses this through quality control and cross-data validation to ensure computational linking accuracy.