hvantk:resource-gtex-eqtl

Standardize GTEx cis-eQTL summary statistics into unified Hail Tables.

Updated Feb 2, 2024
One-click install
npx skills add https://github.com/bigbio/hvantk --skill hvantk-resource-gtex-eqtl
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: hvantk:resource-gtex-eqtl
Source: https://github.com/bigbio/hvantk/tree/main/hvantk/skills/gtex_eqtl
Command: npx skills add https://github.com/bigbio/hvantk --skill hvantk-resource-gtex-eqtl

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires hail, pyspark, requests, requests-mock, pytest, and includes scripts (resource) components.

What problem does it solve?

This skill addresses the complexity of integrating heterogeneous GTEx cis-eQTL summary statistics into multiomics analysis pipelines by standardizing disparate raw formats into a unified, high-performance Hail Table.

Core Features & Use Cases

  • Multi-Source Ingestion: Seamlessly processes GTEx v11 (parquet), GTEx v8 (TSV), and eQTLGen (TSV) datasets using a single builder interface.
  • Triple-Keyed Schema: Normalizes data into a (locus, alleles, gene_id) structure, enabling precise cross-table joins and downstream QTL cascade analysis.
  • Use Case: Researchers can use this to rapidly build tissue-specific eQTL tables for colocalization or variant annotation tasks without manually handling format drifts or versioning issues.

Quick Start

Use the hvantk reprocess command to build a GTEx eQTL table for Liver tissue from your local parquet directory.

Frequently Asked Questions about hvantk:resource-gtex-eqtl

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

FAQPage Schema
How do I build a Hail Table from GTEx eQTL summary statistics?▼

You can build a Hail Table from GTEx eQTL data by using the hvantk reprocess command to standardize raw parquet or TSV files into a unified (locus, alleles, gene_id) schema for downstream analysis.

Can I ingest both GTEx v8 TSV and v11 parquet eQTL datasets?▼

Yes, multi-source ingestion supports both GTEx v11 parquet and GTEx v8 TSV datasets. It applies consistent variant parsing and gene-ID normalization to standardize disparate formats into a unified Hail Table.

How do I normalize heterogeneous eQTL data for multiomics integration?▼

You normalize heterogeneous eQTL data by applying consistent variant parsing and gene-ID normalization to create a triple-keyed (locus, alleles, gene_id) schema, enabling precise cross-table joins and downstream QTL cascade analysis.

Do I need Hail and PySpark to process GTEx variant-gene associations?▼

Yes, Hail and PySpark are required dependencies to process GTEx variant-gene associations. They provide the high-performance environment required to build and query the standardized eQTL Hail Tables.

What is the best way to standardize eQTLGen TSV files for QTL cascade joins?▼

The best way to standardize eQTLGen TSV files for QTL cascade joins is using the builder interface that normalizes the raw TSV data into a triple-keyed (locus, alleles, gene_id) Hail Table format.