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tooluniverse-regulatory-variant-analysis

This skill systematically evaluates non-coding variants through GWAS associations, tissue-specific eQTL effects, and regulatory context. It integrates ENCODE chromatin marks, RegulomeDB scores, and transcription factor binding data to build evidence-graded functional impact predictions, distinguishing regulatory mechanisms from coding pathogenicity.

tooluniverse-regulatory-variant-analysis interprets non-coding GWAS variants by integrating eQTL, chromatin, and regulatory element evidence.

AI-generated summary based on this skill's SKILL.md

1,595 242 Apache-2.0updated by mims-harvard

Decision gist · record as of 2026-07-27

tooluniverse-regulatory-variant-analysis interprets non-coding GWAS variants by integrating eQTL, chromatin, and regulatory element evidence. This skill systematically evaluates non-coding variants through GWAS associations, tissue-specific eQTL effects, and regulatory context. It integrates ENCODE chromatin marks, RegulomeDB scores, and transcription factor binding data to build evidence-graded functional impact predictions, distinguishing regulatory mechanisms from coding pathogenicity.

manual: git clone https://github.com/mims-harvard/ToolUniverse → cp -r ToolUniverse/skills/tooluniverse-regulatory-variant-analysis ~/.claude/skills/tooluniverse-regulatory-variant-analysis
skills/tooluniverse-regulatory-variant-analysis/SKILL.md · version 3c799baf

Use it when

  • tooluniverse-regulatory-variant-analysis performs tissue-specific eQTL analysis to link variants to gene expression changes.
  • tooluniverse-regulatory-variant-analysis evaluates transcription factor binding disruption by analyzing how variants affect binding sites.

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Read SKILL.md below before installing (1 file). Open directory: indexed for reading, not audited.

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Install

mims-harvard/ToolUniverse/tooluniverse-regulatory-variant-analysis · repository language: Python

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Frequently asked questions

AI-generated answers based on this skill's SKILL.md and metadata

How does tooluniverse-regulatory-variant-analysis interpret non-coding GWAS variants?

tooluniverse-regulatory-variant-analysis systematically evaluates non-coding variants by integrating GWAS associations with tissue-specific eQTL effects and regulatory context. It combines ENCODE chromatin marks, RegulomeDB scores, and transcription factor binding data to build evidence-graded functional impact predictions, distinguishing regulatory mechanisms from coding pathogenicity.

What eQTL analysis capabilities does tooluniverse-regulatory-variant-analysis provide?

tooluniverse-regulatory-variant-analysis performs tissue-specific eQTL analysis to link variants to gene expression changes, enabling variant-to-gene mapping through GTEx data and other eQTL resources. This allows you to understand how non-coding variants affect expression across different tissues and cell types.

How does tooluniverse-regulatory-variant-analysis assess transcription factor binding disruption?

tooluniverse-regulatory-variant-analysis evaluates transcription factor binding disruption by analyzing how variants affect binding sites and chromatin state impact. It synthesizes multi-layer evidence including ENCODE histone marks and regulatory element annotations to classify functional impact of binding site alterations.

Can tooluniverse-regulatory-variant-analysis map trait associations and regulatory element overlap?

Yes. tooluniverse-regulatory-variant-analysis maps trait associations and assesses regulatory element overlap for disease variants. It detects active enhancers, poised enhancers, and other regulatory elements that overlap with GWAS hits, helping identify which regulatory mechanisms drive trait associations.

What evidence layers does tooluniverse-regulatory-variant-analysis synthesize for variant classification?

tooluniverse-regulatory-variant-analysis synthesizes multiple evidence layers including GWAS catalog associations, tissue-specific eQTL effects, ENCODE chromatin accessibility and histone marks, RegulomeDB regulatory scores, transcription factor binding predictions, and chromatin state annotations to produce comprehensive functional impact classifications.

How can I use tooluniverse-regulatory-variant-analysis for fine-mapping non-coding disease variants?

tooluniverse-regulatory-variant-analysis supports fine-mapping by integrating regulatory element overlap detection, rs ID annotation lookup, intronic variant mechanism analysis, and multi-layer regulatory evidence synthesis. This workflow helps prioritize causal variants among GWAS signals through regulatory context and functional predictions.

SKILL.md

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COMPUTE, DON'T DESCRIBE

When analysis requires computation (statistics, data processing, scoring, enrichment), write and run Python code via Bash. Don't describe what you would do — execute it and report actual results. Use ToolUniverse tools to retrieve data, then Python (pandas, scipy, statsmodels, matplotlib) to analyze it.

Regulatory Variant Analysis Skill

Systematic regulatory variant interpretation: discover trait associations from GWAS, map eQTL effects, annotate chromatin context, assess regulatory element overlap, and produce evidence-graded functional impact predictions for non-coding variants.

When to Use

  • "What GWAS associations exist for rs12913832?"
  • "Find eQTLs for the APOE locus in brain tissue"
  • "What regulatory

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More skills Regulomedb Database (NOASSERTION) · tooluniverse-gwas-finemapping (Apache-2.0) · Gwas Database (NOASSERTION) · tooluniverse-variant-functional-annotation (Apache-2.0) · tooluniverse-pharmacogenomics (Apache-2.0) · gnomad-database (MIT) · clinpgx-database (Apache-2.0) · gwas-database (Apache-2.0)

Tags
gwas-interpretationregulatory-genomicseqtl-mappingchromatin-annotationnon-coding-variantstranscription-factor-bindingenhancer-discoveryfunctional-predictiontissue-specificityvariant-prioritization