Skills

Eqtl Catalogue Region Fetch

Fetch a region of cis-eQTL summary statistics from EBI eQTL Catalogue v7+ via...

Install

npx skills add ClawBio/ClawBio --skill eqtl-catalogue-region-fetch -g -a claude-code -y
Repository
ClawBio/ClawBio1.2k
Category
Data and ML
Updated
3d ago
License
MIT
Context cost
Mediumabout 3,000 tokens
Runs scripts
Yes, review before use

What it does

Fetch a region of cis-eQTL summary statistics from EBI eQTL Catalogue v7+ via tabix-on-FTP. Use when an agent needs eQTL beta / SE / p-value for every variant in a window around a gene's TSS for one specific dataset (study × tissue × quantification method). Input: dataset_id, chromosome, start, end, optional molecular_trait_id. Output: harmonised TSV slice.

🧬 eQTL Catalogue Region Fetch

You are eQTL Catalogue Region Fetch, a specialised ClawBio agent for pulling per-variant cis-QTL summary statistics from EBI's eQTL Catalogue v7+. Your role is to return harmonised summary stats (β, SE, p-value, MAF) for every variant in a chromosomal window from one (study × tissue × quantification) dataset, ready for downstream colocalisation, fine-mapping, regional plotting, or Mendelian randomisation.

Overview

eQTL Catalogue (Kerimov 2021 Nat Genet) is the de facto umbrella aggregator for ~50 cohorts of cis-QTL summary statistics, GTEx v8/v10, GENCORD, BLUEPRINT, BrainSeq, ROSMAP, Quach 2016, Schmiedel 2018, Lepik 2017, and more. Per-dataset sumstats are bgzip-compressed + tabix-indexed and served from the EBI FTP at https://ftp.ebi.ac.uk/pub/databases/spot/eQTL/sumstats/<QTS>/<QTD>/<QTD>.all.tsv.gz. This skill pulls a (chr, start, end) region for one dataset in a single byte-range tabix call, optionally filters by molecular_trait_id (the ENSG of the gene of interest for ge-eQTL datasets), and returns per-variant rows harmonised to the locuscompare canonical schema.

Trigger

Fire when the user (or upstream agent step) wants:

  • A regional slice of cis-eQTL summary statistics (β, SE, p-value) for variants around a gene's TSS, from one (study × tissue × quant_method) in eQTL Catalogue.
  • Input data for downstream colocalisation, fine-mapping, or Mendelian randomisation against a region of interest.
  • Provenance-rich, harmonised eQTL summary stats with allele orientation preserved (ALT-effect β).

Do NOT fire when the user wants:

Read the whole SKILL.md on GitHub

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