compare-biosamples

Compare ENCODE biosample peak sets to identify tissue-specific regulatory elements.

26|5|Updated Mar 8, 2026
One-click install
npx skills add https://github.com/ammawla/encode-toolkit --skill compare-biosamples
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: compare-biosamples
Source: https://github.com/ammawla/encode-toolkit/tree/main/plugin/skills/compare-biosamples
Command: npx skills add https://github.com/ammawla/encode-toolkit --skill compare-biosamples

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

This Skill helps users systematically compare ENCODE experiments across different biosamples to identify tissue-specific regulatory patterns, shared elements, and differences in chromatin accessibility or histone modifications.

Core Features & Use Cases

  • Cross-tissue comparison: Match experiments from different tissues, cell lines, or primary cells based on assay type and metadata.
  • Differential regulatory element detection: Identify tissue-specific enhancers, promoters, and other cis-regulatory elements by comparing peak sets or signal tracks.
  • Batch effect assessment: Evaluate technical confounders such as lab origin, sequencing platform, and pipeline version to ensure valid biological interpretation.
  • Use case: Comparing H3K27ac peaks between liver and pancreas to find liver-specific enhancers involved in metabolic regulation.

Quick Start

Use this Skill to identify tissue-specific enhancers by comparing ENCODE H3K27ac datasets across selected tissues.

Frequently Asked Questions about compare-biosamples

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

FAQPage Schema
How do I compare ENCODE biosample experiments to find tissue-specific regulatory elements?▼

To compare ENCODE biosamples, match experiments by assay type and metadata to identify tissue-specific and shared regulatory elements. This process analyzes peak sets and signal data to reveal regulatory landscape differences across selected biosamples.

What is the best way to identify tissue-specific enhancers from chromatin accessibility data?▼

Identifying tissue-specific enhancers from chromatin data requires comparing peak sets across different biosamples. This Skill detects differential regulatory elements by analyzing peak sets and signal tracks to isolate tissue-specific enhancers and promoters.

Can I assess batch effects and technical confounders when comparing ENCODE ChIP-seq datasets?▼

You can assess batch effects when comparing ENCODE datasets by evaluating technical confounders such as lab origin, sequencing platform, and pipeline version. This ensures valid biological interpretation of tissue-specific regulatory differences.

Does this approach work for comparing histone modifications across different cell lines?▼

Yes, this approach works for comparing histone modifications across different cell lines and primary cells. It facilitates cross-tissue comparison by analyzing signal tracks to understand differences in histone modification patterns.

How do I find shared regulatory elements between liver and pancreas ENCODE datasets?▼

To find shared regulatory elements between liver and pancreas datasets, compare peak sets from both tissues. This Skill identifies both tissue-specific and shared cis-regulatory elements by matching peak data across biosamples.