alterlab-gtex

Query GTEx v10 eQTL and expression data to identify affected genes and tissues.

58|9|Updated Mar 16, 2026

Search Tags:#genomics #gene-expression #eqtl #gtex #sqtl #tissue-regulation

Ready to run

npx skills add https://github.com/AlterLab-IEU/AlterLab-Academic-Skills --skill alterlab-gtex

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: alterlab-gtex
Source: https://github.com/AlterLab-IEU/AlterLab-Academic-Skills/tree/main/skills/databases/alterlab-gtex
Command: npx skills add https://github.com/AlterLab-IEU/AlterLab-Academic-Skills --skill alterlab-gtex

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

GTEx-based data enables researchers to interpret non-coding genetic variation by linking variants to tissue-specific gene expression and regulatory effects.

Core Features & Use Cases

Access tissue-specific expression (median TPM) and regulatory QTL data across 54 tissues via GTEx REST API.
Retrieve significant eQTLs, sQTLs, and eGenes to prioritize tissues and candidate genes for functional follow-up.
Use cases include interpreting GWAS loci by mapping signals to genes and tissues and exploring tissue-specific regulatory mechanisms.

Quick Start

Query a gene's tissue-specific expression and its significant eQTLs across GTEx tissues to interpret a GWAS signal.

Frequently Asked Questions about alterlab-gtex

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

FAQPage Schema

How do I link GWAS signals to tissue-specific gene expression?▼

To map genetic variants to tissue-specific gene regulation, you query GTEx v10 eQTL and expression data. This process identifies affected genes and tissues, returning gene symbols, tissue IDs, p-values, and effect sizes to prioritize candidate genes for functional follow-up.

What is the difference between eQTL and sQTL data in GTEx tissue regulation analysis?▼

eQTLs link genetic variants to changes in overall gene expression levels, while sQTLs affect mRNA splicing patterns. Analyzing both across GTEx v10 tissues helps determine tissue specificity and uncover distinct regulatory mechanisms for disease.

How do I retrieve significant eQTLs and median TPM expression for a specific gene across GTEx tissues?▼

You retrieve significant eQTLs and median TPM expression by querying GTEx REST API endpoints for association and expression data. The process handles pagination automatically to return tissue-specific regulatory effects and expression metrics.

Can I use GTEx v10 data to prioritize tissues for non-coding genetic variant interpretation?▼

Yes, you can prioritize tissues by applying GTEx v10 eQTL and sQTL data across 54 tissue types. This identifies which tissues show significant regulatory effects for your variant, helping pinpoint the most relevant biological contexts for disease mechanisms.

Does querying GTEx association endpoints for multiple tissues require handling pagination?▼

Yes, querying GTEx association and expression endpoints across multiple tissues requires handling pagination to retrieve complete datasets. This process manages pagination internally to ensure all significant eQTLs, sQTLs, and gene symbols are returned accurately.

What limitations exist when interpreting GWAS loci using GTEx tissue-specific regulatory data?▼

A key limitation is that GTEx data covers 54 specific tissue types, so regulatory effects in unprofiled tissues remain undetected. Additionally, significant eQTLs indicate statistical correlation rather than direct causation, requiring further functional follow-up to confirm disease mechanisms.